Functional relevance for type 1 diabetes mellitus-associated genetic variants by using integrative analyses.

PubMed

Qiu, Ying-Hua; Deng, Fei-Yan; Tang, Zai-Xiang; Jiang, Zhen-Huan; Lei, Shu-Feng

2015-10-01

Type 1 diabetes mellitus (type 1 DM) is an autoimmune disease. Although genome-wide association studies (GWAS) and meta-analyses have successfully identified numerous type 1 DM-associated susceptibility loci, the underlying mechanisms for these susceptibility loci are currently largely unclear. Based on publicly available datasets, we performed integrative analyses (i.e., integrated gene relationships among implicated loci, differential gene expression analysis, functional prediction and functional annotation clustering analysis) and combined with expression quantitative trait loci (eQTL) results to further explore function mechanisms underlying the associations between genetic variants and type 1 DM. Among a total of 183 type 1 DM-associated SNPs, eQTL analysis showed that 17 SNPs with cis-regulated eQTL effects on 9 genes. All the 9 eQTL genes enrich in immune-related pathways or Gene Ontology (GO) terms. Functional prediction analysis identified 5 SNPs located in transcription factor (TF) binding sites. Of the 9 eQTL genes, 6 (TAP2, HLA-DOB, HLA-DQB1, HLA-DQA1, HLA-DRB5 and CTSH) were differentially expressed in type 1 DM-associated related cells. Especially, rs3825932 in CTSH has integrative functional evidence supporting the association with type 1 DM. These findings indicated that integrative analyses can yield important functional information to link genetic variants and type 1 DM. Copyright © 2015 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.

Genomic networks of hybrid sterility.

PubMed

Turner, Leslie M; White, Michael A; Tautz, Diethard; Payseur, Bret A

2014-02-01

Hybrid dysfunction, a common feature of reproductive barriers between species, is often caused by negative epistasis between loci ("Dobzhansky-Muller incompatibilities"). The nature and complexity of hybrid incompatibilities remain poorly understood because identifying interacting loci that affect complex phenotypes is difficult. With subspecies in the early stages of speciation, an array of genetic tools, and detailed knowledge of reproductive biology, house mice (Mus musculus) provide a model system for dissecting hybrid incompatibilities. Male hybrids between M. musculus subspecies often show reduced fertility. Previous studies identified loci and several X chromosome-autosome interactions that contribute to sterility. To characterize the genetic basis of hybrid sterility in detail, we used a systems genetics approach, integrating mapping of gene expression traits with sterility phenotypes and QTL. We measured genome-wide testis expression in 305 male F2s from a cross between wild-derived inbred strains of M. musculus musculus and M. m. domesticus. We identified several thousand cis- and trans-acting QTL contributing to expression variation (eQTL). Many trans eQTL cluster into eleven 'hotspots,' seven of which co-localize with QTL for sterility phenotypes identified in the cross. The number and clustering of trans eQTL-but not cis eQTL-were substantially lower when mapping was restricted to a 'fertile' subset of mice, providing evidence that trans eQTL hotspots are related to sterility. Functional annotation of transcripts with eQTL provides insights into the biological processes disrupted by sterility loci and guides prioritization of candidate genes. Using a conditional mapping approach, we identified eQTL dependent on interactions between loci, revealing a complex system of epistasis. Our results illuminate established patterns, including the role of the X chromosome in hybrid sterility. The integrated mapping approach we employed is applicable in a broad range of organisms and we advocate for widespread adoption of a network-centered approach in speciation genetics.

A novel eQTL-based analysis reveals the biology of breast cancer risk loci

PubMed Central

Li, Qiyuan; Seo, Ji-Heui; Stranger, Barbara; McKenna, Aaron; Pe'er, Itsik; LaFramboise, Thomas; Brown, Myles; Tyekucheva, Svitlana; Freedman, Matthew L.

2014-01-01

Summary Germline determinants of gene expression in tumors are less studied due to the complexity of transcript regulation caused by somatically acquired alterations. We performed expression quantitative trait locus (eQTL) based analyses using the multi-level information provided in The Cancer Genome Atlas (TCGA). Of the factors we measured, cis-acting eQTL saccounted for 1.2% of the total variation of tumor gene expression, while somatic copy number alteration and CpG methylation accounted for 7.3% and 3.3%, respectively. eQTL analyses of 15 previously reported breast cancer risk loci resulted in discovery of three variants that are significantly associated with transcript levels (FDR<0.1). In a novel trans- based analysis, an additional three risk loci were identified to act through ESR1, MYC, and KLF4. These findings provide a more comprehensive picture of gene expression determinants in breast cancer as well as insights into the underlying biology of breast cancer risk loci. PMID:23374354

Mapping eQTL Networks with Mixed Graphical Markov Models

PubMed Central

Tur, Inma; Roverato, Alberto; Castelo, Robert

2014-01-01

Expression quantitative trait loci (eQTL) mapping constitutes a challenging problem due to, among other reasons, the high-dimensional multivariate nature of gene-expression traits. Next to the expression heterogeneity produced by confounding factors and other sources of unwanted variation, indirect effects spread throughout genes as a result of genetic, molecular, and environmental perturbations. From a multivariate perspective one would like to adjust for the effect of all of these factors to end up with a network of direct associations connecting the path from genotype to phenotype. In this article we approach this challenge with mixed graphical Markov models, higher-order conditional independences, and q-order correlation graphs. These models show that additive genetic effects propagate through the network as function of gene–gene correlations. Our estimation of the eQTL network underlying a well-studied yeast data set leads to a sparse structure with more direct genetic and regulatory associations that enable a straightforward comparison of the genetic control of gene expression across chromosomes. Interestingly, it also reveals that eQTLs explain most of the expression variability of network hub genes. PMID:25271303

An integrative systems genetics approach reveals potential causal genes and pathways related to obesity.

PubMed

Kogelman, Lisette J A; Zhernakova, Daria V; Westra, Harm-Jan; Cirera, Susanna; Fredholm, Merete; Franke, Lude; Kadarmideen, Haja N

2015-10-20

Obesity is a multi-factorial health problem in which genetic factors play an important role. Limited results have been obtained in single-gene studies using either genomic or transcriptomic data. RNA sequencing technology has shown its potential in gaining accurate knowledge about the transcriptome, and may reveal novel genes affecting complex diseases. Integration of genomic and transcriptomic variation (expression quantitative trait loci [eQTL] mapping) has identified causal variants that affect complex diseases. We integrated transcriptomic data from adipose tissue and genomic data from a porcine model to investigate the mechanisms involved in obesity using a systems genetics approach. Using a selective gene expression profiling approach, we selected 36 animals based on a previously created genomic Obesity Index for RNA sequencing of subcutaneous adipose tissue. Differential expression analysis was performed using the Obesity Index as a continuous variable in a linear model. eQTL mapping was then performed to integrate 60 K porcine SNP chip data with the RNA sequencing data. Results were restricted based on genome-wide significant single nucleotide polymorphisms, detected differentially expressed genes, and previously detected co-expressed gene modules. Further data integration was performed by detecting co-expression patterns among eQTLs and integration with protein data. Differential expression analysis of RNA sequencing data revealed 458 differentially expressed genes. The eQTL mapping resulted in 987 cis-eQTLs and 73 trans-eQTLs (false discovery rate < 0.05), of which the cis-eQTLs were associated with metabolic pathways. We reduced the eQTL search space by focusing on differentially expressed and co-expressed genes and disease-associated single nucleotide polymorphisms to detect obesity-related genes and pathways. Building a co-expression network using eQTLs resulted in the detection of a module strongly associated with lipid pathways. Furthermore, we detected several obesity candidate genes, for example, ENPP1, CTSL, and ABHD12B. To our knowledge, this is the first study to perform an integrated genomics and transcriptomics (eQTL) study using, and modeling, genomic and subcutaneous adipose tissue RNA sequencing data on obesity in a porcine model. We detected several pathways and potential causal genes for obesity. Further validation and investigation may reveal their exact function and association with obesity.

Cell Specific eQTL Analysis without Sorting Cells

PubMed Central

Esko, Tõnu; Peters, Marjolein J.; Schurmann, Claudia; Schramm, Katharina; Kettunen, Johannes; Yaghootkar, Hanieh; Fairfax, Benjamin P.; Andiappan, Anand Kumar; Li, Yang; Fu, Jingyuan; Karjalainen, Juha; Platteel, Mathieu; Visschedijk, Marijn; Weersma, Rinse K.; Kasela, Silva; Milani, Lili; Tserel, Liina; Peterson, Pärt; Reinmaa, Eva; Hofman, Albert; Uitterlinden, André G.; Rivadeneira, Fernando; Homuth, Georg; Petersmann, Astrid; Lorbeer, Roberto; Prokisch, Holger; Meitinger, Thomas; Herder, Christian; Roden, Michael; Grallert, Harald; Ripatti, Samuli; Perola, Markus; Wood, Andrew R.; Melzer, David; Ferrucci, Luigi; Singleton, Andrew B.; Hernandez, Dena G.; Knight, Julian C.; Melchiotti, Rossella; Lee, Bernett; Poidinger, Michael; Zolezzi, Francesca; Larbi, Anis; Wang, De Yun; van den Berg, Leonard H.; Veldink, Jan H.; Rotzschke, Olaf; Makino, Seiko; Salomaa, Veikko; Strauch, Konstantin; Völker, Uwe; van Meurs, Joyce B. J.; Metspalu, Andres; Wijmenga, Cisca; Jansen, Ritsert C.; Franke, Lude

2015-01-01

The functional consequences of trait associated SNPs are often investigated using expression quantitative trait locus (eQTL) mapping. While trait-associated variants may operate in a cell-type specific manner, eQTL datasets for such cell-types may not always be available. We performed a genome-environment interaction (GxE) meta-analysis on data from 5,683 samples to infer the cell type specificity of whole blood cis-eQTLs. We demonstrate that this method is able to predict neutrophil and lymphocyte specific cis-eQTLs and replicate these predictions in independent cell-type specific datasets. Finally, we show that SNPs associated with Crohn’s disease preferentially affect gene expression within neutrophils, including the archetypal NOD2 locus. PMID:25955312

Impact of a cis-associated gene expression SNP in 20q11.22 on bipolar disorder susceptibility, hippocampal structure and cognitive performance

PubMed Central

Li, Ming; Luo, Xiong-jian; Landén, Mikael; Bergen, Sarah E.; Hultman, Christina M.; Li, Xiao; Zhang, Wen; Yao, Yong-Gang; Zhang, Chen; Liu, Jiewei; Mattheisen, Manuel; Cichon, Sven; Mühleisen, Thomas W.; Degenhardt, Franziska A.; Nöthen, Markus M.; Schulze, Thomas G.; Grigoroiu-Serbanescu, Maria; Li, Hao; Fuller, Chris K.; Chen, Chunhui; Dong, Qi; Chen, Chuansheng; Jamain, Stéphane; Leboyer, Marion; Bellivier, Frank; Etain, Bruno; Kahn, Jean-Pierre; Henry, Chantal; Preisig, Martin; Kutalik, Zoltán; Castelao, Enrique; Wright, Adam; Mitchell, Philip B.; Fullerton, Janice M.; Schofield, Peter R.; Montgomery, Grant W.; Medland, Sarah E.; Gordon, Scott D.; Martin, Nicholas G.; Rietschel, Marcella; Liu, Chunyu; Kleinman, Joel E.; Hyde, Thomas M.; Weinberger, Daniel R.; Su, Bing

2016-01-01

Summary Bipolar disorder (BPD) is a highly heritable polygenic disorder. Recent enrichment analyses suggest that there may be true risk variants for BPD among the expression quantitative trait loci (eQTL) in the brain. Aims We sought to assess the impact of eQTL variants on BPD risk by combining data from both BPD genome-wide association study (GWAS) and brain eQTL. Method To detect single-nucleotide polymorphisms (SNPs) that influence expression levels of genes associated with BPD, we jointly analyzed data from a BPD GWAS (7,481 cases and 9,250 controls) and a genome-wide brain (cortical) eQTL (193 healthy controls) using a Bayesian statistical method, with independent follow-up replications. The identified risk SNP was then further tested for association with hippocampal volume (N=5,775) and cognitive performance (N=342) among healthy subjects. Results Integrative analysis revealed a significant association between a brain eQTL rs6088662 in 20q11.22 and BPD (Log Bayes Factor=5.48; BPD p-val=5.85×10−5). Follow-up studies across multiple independent samples confirmed the association of the risk SNP (rs6088662) with gene expression and BPD susceptibility (p-val=3.54×10−8). Further exploratory analysis revealed that rs6088662 is also associated with hippocampal volume and cognitive performance in healthy subjects. Conclusions Our findings suggest that 20q11.22 is likely a risk region for BPD, highlighting the informativeness of integrating functional annotation of genetic variants for gene expression in advancing our understanding of the biological basis underlying complex diseases such as BPD. PMID:26338991

Impact of a cis-associated gene expression SNP on chromosome 20q11.22 on bipolar disorder susceptibility, hippocampal structure and cognitive performance.

PubMed

Li, Ming; Luo, Xiong-jian; Landén, Mikael; Bergen, Sarah E; Hultman, Christina M; Li, Xiao; Zhang, Wen; Yao, Yong-Gang; Zhang, Chen; Liu, Jiewei; Mattheisen, Manuel; Cichon, Sven; Mühleisen, Thomas W; Degenhardt, Franziska A; Nöthen, Markus M; Schulze, Thomas G; Grigoroiu-Serbanescu, Maria; Li, Hao; Fuller, Chris K; Chen, Chunhui; Dong, Qi; Chen, Chuansheng; Jamain, Stéphane; Leboyer, Marion; Bellivier, Frank; Etain, Bruno; Kahn, Jean-Pierre; Henry, Chantal; Preisig, Martin; Kutalik, Zoltán; Castelao, Enrique; Wright, Adam; Mitchell, Philip B; Fullerton, Janice M; Schofield, Peter R; Montgomery, Grant W; Medland, Sarah E; Gordon, Scott D; Martin, Nicholas G; Rietschel, Marcella; Liu, Chunyu; Kleinman, Joel E; Hyde, Thomas M; Weinberger, Daniel R; Su, Bing

2016-02-01

Bipolar disorder is a highly heritable polygenic disorder. Recent enrichment analyses suggest that there may be true risk variants for bipolar disorder in the expression quantitative trait loci (eQTL) in the brain. We sought to assess the impact of eQTL variants on bipolar disorder risk by combining data from both bipolar disorder genome-wide association studies (GWAS) and brain eQTL. To detect single nucleotide polymorphisms (SNPs) that influence expression levels of genes associated with bipolar disorder, we jointly analysed data from a bipolar disorder GWAS (7481 cases and 9250 controls) and a genome-wide brain (cortical) eQTL (193 healthy controls) using a Bayesian statistical method, with independent follow-up replications. The identified risk SNP was then further tested for association with hippocampal volume (n = 5775) and cognitive performance (n = 342) among healthy individuals. Integrative analysis revealed a significant association between a brain eQTL rs6088662 on chromosome 20q11.22 and bipolar disorder (log Bayes factor = 5.48; bipolar disorder P = 5.85 × 10(-5)). Follow-up studies across multiple independent samples confirmed the association of the risk SNP (rs6088662) with gene expression and bipolar disorder susceptibility (P = 3.54 × 10(-8)). Further exploratory analysis revealed that rs6088662 is also associated with hippocampal volume and cognitive performance in healthy individuals. Our findings suggest that 20q11.22 is likely a risk region for bipolar disorder; they also highlight the informative value of integrating functional annotation of genetic variants for gene expression in advancing our understanding of the biological basis underlying complex disorders, such as bipolar disorder. © The Royal College of Psychiatrists 2016.

Integrated genomic approaches to identification of candidate genes underlying metabolic and cardiovascular phenotypes in the spontaneously hypertensive rat.

PubMed

Morrissey, Catherine; Grieve, Ian C; Heinig, Matthias; Atanur, Santosh; Petretto, Enrico; Pravenec, Michal; Hubner, Norbert; Aitman, Timothy J

2011-11-07

The spontaneously hypertensive rat (SHR) is a widely used rodent model of hypertension and metabolic syndrome. Previously we identified thousands of cis-regulated expression quantitative trait loci (eQTLs) across multiple tissues using a panel of rat recombinant inbred (RI) strains derived from Brown Norway and SHR progenitors. These cis-eQTLs represent potential susceptibility loci underlying physiological and pathophysiological traits manifested in SHR. We have prioritized 60 cis-eQTLs and confirmed differential expression between the parental strains by quantitative PCR in 43 (72%) of the eQTL transcripts. Quantitative trait transcript (QTT) analysis in the RI strains showed highly significant correlation between cis-eQTL transcript abundance and clinically relevant traits such as systolic blood pressure and blood glucose, with the physical location of a subset of the cis-eQTLs colocalizing with "physiological" QTLs (pQTLs) for these same traits. These colocalizing correlated cis-eQTLs (c3-eQTLs) are highly attractive as primary susceptibility loci for the colocalizing pQTLs. Furthermore, sequence analysis of the c3-eQTL genes identified single nucleotide polymorphisms (SNPs) that are predicted to affect transcription factor binding affinity, splicing and protein function. These SNPs, which potentially alter transcript abundance and stability, represent strong candidate factors underlying not just eQTL expression phenotypes, but also the correlated metabolic and physiological traits. In conclusion, by integration of genomic sequence, eQTL and QTT datasets we have identified several genes that are strong positional candidates for pathophysiological traits observed in the SHR strain. These findings provide a basis for the functional testing and ultimate elucidation of the molecular basis of these metabolic and cardiovascular phenotypes.

Adaptive linear rank tests for eQTL studies

PubMed Central

Szymczak, Silke; Scheinhardt, Markus O.; Zeller, Tanja; Wild, Philipp S.; Blankenberg, Stefan; Ziegler, Andreas

2013-01-01

Expression quantitative trait loci (eQTL) studies are performed to identify single-nucleotide polymorphisms that modify average expression values of genes, proteins, or metabolites, depending on the genotype. As expression values are often not normally distributed, statistical methods for eQTL studies should be valid and powerful in these situations. Adaptive tests are promising alternatives to standard approaches, such as the analysis of variance or the Kruskal–Wallis test. In a two-stage procedure, skewness and tail length of the distributions are estimated and used to select one of several linear rank tests. In this study, we compare two adaptive tests that were proposed in the literature using extensive Monte Carlo simulations of a wide range of different symmetric and skewed distributions. We derive a new adaptive test that combines the advantages of both literature-based approaches. The new test does not require the user to specify a distribution. It is slightly less powerful than the locally most powerful rank test for the correct distribution and at least as powerful as the maximin efficiency robust rank test. We illustrate the application of all tests using two examples from different eQTL studies. PMID:22933317

Adaptive linear rank tests for eQTL studies.

PubMed

Szymczak, Silke; Scheinhardt, Markus O; Zeller, Tanja; Wild, Philipp S; Blankenberg, Stefan; Ziegler, Andreas

2013-02-10

Expression quantitative trait loci (eQTL) studies are performed to identify single-nucleotide polymorphisms that modify average expression values of genes, proteins, or metabolites, depending on the genotype. As expression values are often not normally distributed, statistical methods for eQTL studies should be valid and powerful in these situations. Adaptive tests are promising alternatives to standard approaches, such as the analysis of variance or the Kruskal-Wallis test. In a two-stage procedure, skewness and tail length of the distributions are estimated and used to select one of several linear rank tests. In this study, we compare two adaptive tests that were proposed in the literature using extensive Monte Carlo simulations of a wide range of different symmetric and skewed distributions. We derive a new adaptive test that combines the advantages of both literature-based approaches. The new test does not require the user to specify a distribution. It is slightly less powerful than the locally most powerful rank test for the correct distribution and at least as powerful as the maximin efficiency robust rank test. We illustrate the application of all tests using two examples from different eQTL studies. Copyright © 2012 John Wiley & Sons, Ltd.

Genomic Networks of Hybrid Sterility

PubMed Central

Turner, Leslie M.; White, Michael A.; Tautz, Diethard; Payseur, Bret A.

2014-01-01

Hybrid dysfunction, a common feature of reproductive barriers between species, is often caused by negative epistasis between loci (“Dobzhansky-Muller incompatibilities”). The nature and complexity of hybrid incompatibilities remain poorly understood because identifying interacting loci that affect complex phenotypes is difficult. With subspecies in the early stages of speciation, an array of genetic tools, and detailed knowledge of reproductive biology, house mice (Mus musculus) provide a model system for dissecting hybrid incompatibilities. Male hybrids between M. musculus subspecies often show reduced fertility. Previous studies identified loci and several X chromosome-autosome interactions that contribute to sterility. To characterize the genetic basis of hybrid sterility in detail, we used a systems genetics approach, integrating mapping of gene expression traits with sterility phenotypes and QTL. We measured genome-wide testis expression in 305 male F2s from a cross between wild-derived inbred strains of M. musculus musculus and M. m. domesticus. We identified several thousand cis- and trans-acting QTL contributing to expression variation (eQTL). Many trans eQTL cluster into eleven ‘hotspots,’ seven of which co-localize with QTL for sterility phenotypes identified in the cross. The number and clustering of trans eQTL—but not cis eQTL—were substantially lower when mapping was restricted to a ‘fertile’ subset of mice, providing evidence that trans eQTL hotspots are related to sterility. Functional annotation of transcripts with eQTL provides insights into the biological processes disrupted by sterility loci and guides prioritization of candidate genes. Using a conditional mapping approach, we identified eQTL dependent on interactions between loci, revealing a complex system of epistasis. Our results illuminate established patterns, including the role of the X chromosome in hybrid sterility. The integrated mapping approach we employed is applicable in a broad range of organisms and we advocate for widespread adoption of a network-centered approach in speciation genetics. PMID:24586194

Powerful Identification of Cis-regulatory SNPs in Human Primary Monocytes Using Allele-Specific Gene Expression

PubMed Central

Almlöf, Jonas Carlsson; Lundmark, Per; Lundmark, Anders; Ge, Bing; Maouche, Seraya; Göring, Harald H. H.; Liljedahl, Ulrika; Enström, Camilla; Brocheton, Jessy; Proust, Carole; Godefroy, Tiphaine; Sambrook, Jennifer G.; Jolley, Jennifer; Crisp-Hihn, Abigail; Foad, Nicola; Lloyd-Jones, Heather; Stephens, Jonathan; Gwilliam, Rhian; Rice, Catherine M.; Hengstenberg, Christian; Samani, Nilesh J.; Erdmann, Jeanette; Schunkert, Heribert; Pastinen, Tomi; Deloukas, Panos; Goodall, Alison H.; Ouwehand, Willem H.; Cambien, François; Syvänen, Ann-Christine

2012-01-01

A large number of genome-wide association studies have been performed during the past five years to identify associations between SNPs and human complex diseases and traits. The assignment of a functional role for the identified disease-associated SNP is not straight-forward. Genome-wide expression quantitative trait locus (eQTL) analysis is frequently used as the initial step to define a function while allele-specific gene expression (ASE) analysis has not yet gained a wide-spread use in disease mapping studies. We compared the power to identify cis-acting regulatory SNPs (cis-rSNPs) by genome-wide allele-specific gene expression (ASE) analysis with that of traditional expression quantitative trait locus (eQTL) mapping. Our study included 395 healthy blood donors for whom global gene expression profiles in circulating monocytes were determined by Illumina BeadArrays. ASE was assessed in a subset of these monocytes from 188 donors by quantitative genotyping of mRNA using a genome-wide panel of SNP markers. The performance of the two methods for detecting cis-rSNPs was evaluated by comparing associations between SNP genotypes and gene expression levels in sample sets of varying size. We found that up to 8-fold more samples are required for eQTL mapping to reach the same statistical power as that obtained by ASE analysis for the same rSNPs. The performance of ASE is insensitive to SNPs with low minor allele frequencies and detects a larger number of significantly associated rSNPs using the same sample size as eQTL mapping. An unequivocal conclusion from our comparison is that ASE analysis is more sensitive for detecting cis-rSNPs than standard eQTL mapping. Our study shows the potential of ASE mapping in tissue samples and primary cells which are difficult to obtain in large numbers. PMID:23300628

Genetics of Sputum Gene Expression in Chronic Obstructive Pulmonary Disease

PubMed Central

Qiu, Weiliang; Cho, Michael H.; Riley, John H.; Anderson, Wayne H.; Singh, Dave; Bakke, Per; Gulsvik, Amund; Litonjua, Augusto A.; Lomas, David A.; Crapo, James D.; Beaty, Terri H.; Celli, Bartolome R.; Rennard, Stephen; Tal-Singer, Ruth; Fox, Steven M.; Silverman, Edwin K.; Hersh, Craig P.

2011-01-01

Previous expression quantitative trait loci (eQTL) studies have performed genetic association studies for gene expression, but most of these studies examined lymphoblastoid cell lines from non-diseased individuals. We examined the genetics of gene expression in a relevant disease tissue from chronic obstructive pulmonary disease (COPD) patients to identify functional effects of known susceptibility genes and to find novel disease genes. By combining gene expression profiling on induced sputum samples from 131 COPD cases from the ECLIPSE Study with genomewide single nucleotide polymorphism (SNP) data, we found 4315 significant cis-eQTL SNP-probe set associations (3309 unique SNPs). The 3309 SNPs were tested for association with COPD in a genomewide association study (GWAS) dataset, which included 2940 COPD cases and 1380 controls. Adjusting for 3309 tests (p<1.5e-5), the two SNPs which were significantly associated with COPD were located in two separate genes in a known COPD locus on chromosome 15: CHRNA5 and IREB2. Detailed analysis of chromosome 15 demonstrated additional eQTLs for IREB2 mapping to that gene. eQTL SNPs for CHRNA5 mapped to multiple linkage disequilibrium (LD) bins. The eQTLs for IREB2 and CHRNA5 were not in LD. Seventy-four additional eQTL SNPs were associated with COPD at p<0.01. These were genotyped in two COPD populations, finding replicated associations with a SNP in PSORS1C1, in the HLA-C region on chromosome 6. Integrative analysis of GWAS and gene expression data from relevant tissue from diseased subjects has located potential functional variants in two known COPD genes and has identified a novel COPD susceptibility locus. PMID:21949713

Accurate and fast multiple-testing correction in eQTL studies.

PubMed

Sul, Jae Hoon; Raj, Towfique; de Jong, Simone; de Bakker, Paul I W; Raychaudhuri, Soumya; Ophoff, Roel A; Stranger, Barbara E; Eskin, Eleazar; Han, Buhm

2015-06-04

In studies of expression quantitative trait loci (eQTLs), it is of increasing interest to identify eGenes, the genes whose expression levels are associated with variation at a particular genetic variant. Detecting eGenes is important for follow-up analyses and prioritization because genes are the main entities in biological processes. To detect eGenes, one typically focuses on the genetic variant with the minimum p value among all variants in cis with a gene and corrects for multiple testing to obtain a gene-level p value. For performing multiple-testing correction, a permutation test is widely used. Because of growing sample sizes of eQTL studies, however, the permutation test has become a computational bottleneck in eQTL studies. In this paper, we propose an efficient approach for correcting for multiple testing and assess eGene p values by utilizing a multivariate normal distribution. Our approach properly takes into account the linkage-disequilibrium structure among variants, and its time complexity is independent of sample size. By applying our small-sample correction techniques, our method achieves high accuracy in both small and large studies. We have shown that our method consistently produces extremely accurate p values (accuracy > 98%) for three human eQTL datasets with different sample sizes and SNP densities: the Genotype-Tissue Expression pilot dataset, the multi-region brain dataset, and the HapMap 3 dataset. Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

POEM: Identifying Joint Additive Effects on Regulatory Circuits.

PubMed

Botzman, Maya; Nachshon, Aharon; Brodt, Avital; Gat-Viks, Irit

2016-01-01

Expression Quantitative Trait Locus (eQTL) mapping tackles the problem of identifying variation in DNA sequence that have an effect on the transcriptional regulatory network. Major computational efforts are aimed at characterizing the joint effects of several eQTLs acting in concert to govern the expression of the same genes. Yet, progress toward a comprehensive prediction of such joint effects is limited. For example, existing eQTL methods commonly discover interacting loci affecting the expression levels of a module of co-regulated genes. Such "modularization" approaches, however, are focused on epistatic relations and thus have limited utility for the case of additive (non-epistatic) effects. Here we present POEM (Pairwise effect On Expression Modules), a methodology for identifying pairwise eQTL effects on gene modules. POEM is specifically designed to achieve high performance in the case of additive joint effects. We applied POEM to transcription profiles measured in bone marrow-derived dendritic cells across a population of genotyped mice. Our study reveals widespread additive, trans-acting pairwise effects on gene modules, characterizes their organizational principles, and highlights high-order interconnections between modules within the immune signaling network. These analyses elucidate the central role of additive pairwise effect in regulatory circuits, and provide computational tools for future investigations into the interplay between eQTLs. The software described in this article is available at csgi.tau.ac.il/POEM/.

POEM: Identifying Joint Additive Effects on Regulatory Circuits

PubMed Central

Botzman, Maya; Nachshon, Aharon; Brodt, Avital; Gat-Viks, Irit

2016-01-01

Motivation: Expression Quantitative Trait Locus (eQTL) mapping tackles the problem of identifying variation in DNA sequence that have an effect on the transcriptional regulatory network. Major computational efforts are aimed at characterizing the joint effects of several eQTLs acting in concert to govern the expression of the same genes. Yet, progress toward a comprehensive prediction of such joint effects is limited. For example, existing eQTL methods commonly discover interacting loci affecting the expression levels of a module of co-regulated genes. Such “modularization” approaches, however, are focused on epistatic relations and thus have limited utility for the case of additive (non-epistatic) effects. Results: Here we present POEM (Pairwise effect On Expression Modules), a methodology for identifying pairwise eQTL effects on gene modules. POEM is specifically designed to achieve high performance in the case of additive joint effects. We applied POEM to transcription profiles measured in bone marrow-derived dendritic cells across a population of genotyped mice. Our study reveals widespread additive, trans-acting pairwise effects on gene modules, characterizes their organizational principles, and highlights high-order interconnections between modules within the immune signaling network. These analyses elucidate the central role of additive pairwise effect in regulatory circuits, and provide computational tools for future investigations into the interplay between eQTLs. Availability: The software described in this article is available at csgi.tau.ac.il/POEM/. PMID:27148351

An eQTL Analysis of Partial Resistance to Puccinia hordei in Barley

PubMed Central

Chen, Xinwei; Hackett, Christine A.; Niks, Rients E.; Hedley, Peter E.; Booth, Clare; Druka, Arnis; Marcel, Thierry C.; Vels, Anton; Bayer, Micha; Milne, Iain; Morris, Jenny; Ramsay, Luke; Marshall, David; Cardle, Linda; Waugh, Robbie

2010-01-01

Background Genetic resistance to barley leaf rust caused by Puccinia hordei involves both R genes and quantitative trait loci. The R genes provide higher but less durable resistance than the quantitative trait loci. Consequently, exploring quantitative or partial resistance has become a favorable alternative for controlling disease. Four quantitative trait loci for partial resistance to leaf rust have been identified in the doubled haploid Steptoe (St)/Morex (Mx) mapping population. Further investigations are required to study the molecular mechanisms underpinning partial resistance and ultimately identify the causal genes. Methodology/Principal Findings We explored partial resistance to barley leaf rust using a genetical genomics approach. We recorded RNA transcript abundance corresponding to each probe on a 15K Agilent custom barley microarray in seedlings from St and Mx and 144 doubled haploid lines of the St/Mx population. A total of 1154 and 1037 genes were, respectively, identified as being P. hordei-responsive among the St and Mx and differentially expressed between P. hordei-infected St and Mx. Normalized ratios from 72 distant-pair hybridisations were used to map the genetic determinants of variation in transcript abundance by expression quantitative trait locus (eQTL) mapping generating 15685 eQTL from 9557 genes. Correlation analysis identified 128 genes that were correlated with resistance, of which 89 had eQTL co-locating with the phenotypic quantitative trait loci (pQTL). Transcript abundance in the parents and conservation of synteny with rice allowed us to prioritise six genes as candidates for Rphq11, the pQTL of largest effect, and highlight one, a phospholipid hydroperoxide glutathione peroxidase (HvPHGPx) for detailed analysis. Conclusions/Significance The eQTL approach yielded information that led to the identification of strong candidate genes underlying pQTL for resistance to leaf rust in barley and on the general pathogen response pathway. The dataset will facilitate a systems appraisal of this host-pathogen interaction and, potentially, for other traits measured in this population. PMID:20066049

Effectively identifying regulatory hotspots while capturing expression heterogeneity in gene expression studies

PubMed Central

2014-01-01

Expression quantitative trait loci (eQTL) mapping is a tool that can systematically identify genetic variation affecting gene expression. eQTL mapping studies have shown that certain genomic locations, referred to as regulatory hotspots, may affect the expression levels of many genes. Recently, studies have shown that various confounding factors may induce spurious regulatory hotspots. Here, we introduce a novel statistical method that effectively eliminates spurious hotspots while retaining genuine hotspots. Applied to simulated and real datasets, we validate that our method achieves greater sensitivity while retaining low false discovery rates compared to previous methods. PMID:24708878

A Bayesian Framework to Account for Complex Non-Genetic Factors in Gene Expression Levels Greatly Increases Power in eQTL Studies

PubMed Central

Durbin, Richard; Winn, John

2010-01-01

Gene expression measurements are influenced by a wide range of factors, such as the state of the cell, experimental conditions and variants in the sequence of regulatory regions. To understand the effect of a variable of interest, such as the genotype of a locus, it is important to account for variation that is due to confounding causes. Here, we present VBQTL, a probabilistic approach for mapping expression quantitative trait loci (eQTLs) that jointly models contributions from genotype as well as known and hidden confounding factors. VBQTL is implemented within an efficient and flexible inference framework, making it fast and tractable on large-scale problems. We compare the performance of VBQTL with alternative methods for dealing with confounding variability on eQTL mapping datasets from simulations, yeast, mouse, and human. Employing Bayesian complexity control and joint modelling is shown to result in more precise estimates of the contribution of different confounding factors resulting in additional associations to measured transcript levels compared to alternative approaches. We present a threefold larger collection of cis eQTLs than previously found in a whole-genome eQTL scan of an outbred human population. Altogether, 27% of the tested probes show a significant genetic association in cis, and we validate that the additional eQTLs are likely to be real by replicating them in different sets of individuals. Our method is the next step in the analysis of high-dimensional phenotype data, and its application has revealed insights into genetic regulation of gene expression by demonstrating more abundant cis-acting eQTLs in human than previously shown. Our software is freely available online at http://www.sanger.ac.uk/resources/software/peer/. PMID:20463871

Effectively Identifying eQTLs from Multiple Tissues by Combining Mixed Model and Meta-analytic Approaches

PubMed Central

Choi, Ted; Eskin, Eleazar

2013-01-01

Gene expression data, in conjunction with information on genetic variants, have enabled studies to identify expression quantitative trait loci (eQTLs) or polymorphic locations in the genome that are associated with expression levels. Moreover, recent technological developments and cost decreases have further enabled studies to collect expression data in multiple tissues. One advantage of multiple tissue datasets is that studies can combine results from different tissues to identify eQTLs more accurately than examining each tissue separately. The idea of aggregating results of multiple tissues is closely related to the idea of meta-analysis which aggregates results of multiple genome-wide association studies to improve the power to detect associations. In principle, meta-analysis methods can be used to combine results from multiple tissues. However, eQTLs may have effects in only a single tissue, in all tissues, or in a subset of tissues with possibly different effect sizes. This heterogeneity in terms of effects across multiple tissues presents a key challenge to detect eQTLs. In this paper, we develop a framework that leverages two popular meta-analysis methods that address effect size heterogeneity to detect eQTLs across multiple tissues. We show by using simulations and multiple tissue data from mouse that our approach detects many eQTLs undetected by traditional eQTL methods. Additionally, our method provides an interpretation framework that accurately predicts whether an eQTL has an effect in a particular tissue. PMID:23785294

Dissection of expression-quantitative trait locus and allele specificity using a haploid/diploid plant system - insights into compensatory evolution of transcriptional regulation within populations.

PubMed

Verta, Jukka-Pekka; Landry, Christian R; MacKay, John

2016-07-01

Regulation of gene expression plays a central role in translating genotypic variation into phenotypic variation. Dissection of the genetic basis of expression variation is key to understanding how expression regulation evolves. Such analyses remain challenging in contexts where organisms are outbreeding, highly heterozygous and long-lived such as in the case of conifer trees. We developed an RNA sequencing (RNA-seq)-based approach for both expression-quantitative trait locus (eQTL) mapping and the detection of cis-acting (allele-specific) vs trans-acting (non-allele-specific) eQTLs. This method can be potentially applied to many conifers. We used haploid and diploid meiotic seed tissues of a single self-fertilized white spruce (Picea glauca) individual to dissect eQTLs according to linkage and allele specificity. The genetic architecture of local eQTLs linked to the expressed genes was particularly complex, consisting of cis-acting, trans-acting and, surprisingly, compensatory cis-trans effects. These compensatory effects influence expression in opposite directions and are neutral when combined in homozygotes. Nearly half of local eQTLs were under compensation, indicating that close linkage between compensatory cis-trans factors is common in spruce. Compensated genes were overrepresented in developmental and cell organization functions. Our haploid-diploid eQTL analysis in spruce revealed that compensatory cis-trans eQTLs segregate within populations and evolve in close genetic linkage. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Integrating genome-wide association study and expression quantitative trait loci data identifies multiple genes and gene set associated with neuroticism.

PubMed

Fan, Qianrui; Wang, Wenyu; Hao, Jingcan; He, Awen; Wen, Yan; Guo, Xiong; Wu, Cuiyan; Ning, Yujie; Wang, Xi; Wang, Sen; Zhang, Feng

2017-08-01

Neuroticism is a fundamental personality trait with significant genetic determinant. To identify novel susceptibility genes for neuroticism, we conducted an integrative analysis of genomic and transcriptomic data of genome wide association study (GWAS) and expression quantitative trait locus (eQTL) study. GWAS summary data was driven from published studies of neuroticism, totally involving 170,906 subjects. eQTL dataset containing 927,753 eQTLs were obtained from an eQTL meta-analysis of 5311 samples. Integrative analysis of GWAS and eQTL data was conducted by summary data-based Mendelian randomization (SMR) analysis software. To identify neuroticism associated gene sets, the SMR analysis results were further subjected to gene set enrichment analysis (GSEA). The gene set annotation dataset (containing 13,311 annotated gene sets) of GSEA Molecular Signatures Database was used. SMR single gene analysis identified 6 significant genes for neuroticism, including MSRA (p value=2.27×10 -10 ), MGC57346 (p value=6.92×10 -7 ), BLK (p value=1.01×10 -6 ), XKR6 (p value=1.11×10 -6 ), C17ORF69 (p value=1.12×10 -6 ) and KIAA1267 (p value=4.00×10 -6 ). Gene set enrichment analysis observed significant association for Chr8p23 gene set (false discovery rate=0.033). Our results provide novel clues for the genetic mechanism studies of neuroticism. Copyright © 2017. Published by Elsevier Inc.

Expression Quantitative Trait Locus Mapping across Water Availability Environments Reveals Contrasting Associations with Genomic Features in Arabidopsis[C][W][OPEN

PubMed Central

Lowry, David B.; Logan, Tierney L.; Santuari, Luca; Hardtke, Christian S.; Richards, James H.; DeRose-Wilson, Leah J.; McKay, John K.; Sen, Saunak; Juenger, Thomas E.

2013-01-01

The regulation of gene expression is crucial for an organism’s development and response to stress, and an understanding of the evolution of gene expression is of fundamental importance to basic and applied biology. To improve this understanding, we conducted expression quantitative trait locus (eQTL) mapping in the Tsu-1 (Tsushima, Japan) × Kas-1 (Kashmir, India) recombinant inbred line population of Arabidopsis thaliana across soil drying treatments. We then used genome resequencing data to evaluate whether genomic features (promoter polymorphism, recombination rate, gene length, and gene density) are associated with genes responding to the environment (E) or with genes with genetic variation (G) in gene expression in the form of eQTLs. We identified thousands of genes that responded to soil drying and hundreds of main-effect eQTLs. However, we identified very few statistically significant eQTLs that interacted with the soil drying treatment (GxE eQTL). Analysis of genome resequencing data revealed associations of several genomic features with G and E genes. In general, E genes had lower promoter diversity and local recombination rates. By contrast, genes with eQTLs (G) had significantly greater promoter diversity and were located in genomic regions with higher recombination. These results suggest that genomic architecture may play an important a role in the evolution of gene expression. PMID:24045022

Genome-wide analysis of the genetic regulation of gene expression in human neutrophils

PubMed Central

Andiappan, Anand Kumar; Melchiotti, Rossella; Poh, Tuang Yeow; Nah, Michelle; Puan, Kia Joo; Vigano, Elena; Haase, Doreen; Yusof, Nurhashikin; San Luis, Boris; Lum, Josephine; Kumar, Dilip; Foo, Shihui; Zhuang, Li; Vasudev, Anusha; Irwanto, Astrid; Lee, Bernett; Nardin, Alessandra; Liu, Hong; Zhang, Furen; Connolly, John; Liu, Jianjun; Mortellaro, Alessandra; Wang, De Yun; Poidinger, Michael; Larbi, Anis; Zolezzi, Francesca; Rotzschke, Olaf

2015-01-01

Neutrophils are an abundant immune cell type involved in both antimicrobial defence and autoimmunity. The regulation of their gene expression, however, is still largely unknown. Here we report an eQTL study on isolated neutrophils from 114 healthy individuals of Chinese ethnicity, identifying 21,210 eQTLs on 832 unique genes. Unsupervised clustering analysis of these eQTLs confirms their role in inflammatory responses and immunological diseases but also indicates strong involvement in dermatological pathologies. One of the strongest eQTL identified (rs2058660) is also the tagSNP of a linkage block reported to affect leprosy and Crohn's disease in opposite directions. In a functional study, we can link the C allele with low expression of the β-chain of IL18-receptor (IL18RAP). In neutrophils, this results in a reduced responsiveness to IL-18, detected both on the RNA and protein level. Thus, the polymorphic regulation of human neutrophils can impact beneficial as well as pathological inflammatory responses. PMID:26259071

Genetics and Genomics of Social Behavior in a Chicken Model.

PubMed

Johnsson, Martin; Henriksen, Rie; Fogelholm, Jesper; Höglund, Andrey; Jensen, Per; Wright, Dominic

2018-05-01

The identification of genes affecting sociality can give insights into the maintenance and development of sociality and personality. In this study, we used the combination of an advanced intercross between wild and domestic chickens with a combined QTL and eQTL genetical genomics approach to identify genes for social reinstatement, a social and anxiety-related behavior. A total of 24 social reinstatement QTL were identified and overlaid with over 600 eQTL obtained from the same birds using hypothalamic tissue. Correlations between overlapping QTL and eQTL indicated five strong candidate genes, with the gene TTRAP being strongly significantly correlated with multiple aspects of social reinstatement behavior, as well as possessing a highly significant eQTL. Copyright © 2018 by the Genetics Society of America.

Genevar: a database and Java application for the analysis and visualization of SNP-gene associations in eQTL studies.

PubMed

Yang, Tsun-Po; Beazley, Claude; Montgomery, Stephen B; Dimas, Antigone S; Gutierrez-Arcelus, Maria; Stranger, Barbara E; Deloukas, Panos; Dermitzakis, Emmanouil T

2010-10-01

Genevar (GENe Expression VARiation) is a database and Java tool designed to integrate multiple datasets, and provides analysis and visualization of associations between sequence variation and gene expression. Genevar allows researchers to investigate expression quantitative trait loci (eQTL) associations within a gene locus of interest in real time. The database and application can be installed on a standard computer in database mode and, in addition, on a server to share discoveries among affiliations or the broader community over the Internet via web services protocols. http://www.sanger.ac.uk/resources/software/genevar.

ADP ribosyl-cyclases (CD38/CD157), social skills and friendship.

PubMed

Chong, Anne; Malavasi, Fabio; Israel, Salomon; Khor, Chiea Chuen; Yap, Von Bing; Monakhov, Mikhail; Chew, Soo Hong; Lai, Poh San; Ebstein, Richard P

2017-04-01

Why some individuals seek social engagement while others shy away has profound implications for normal and pathological human behavior. Evidence suggests that oxytocin (OT), the paramount human social hormone, and CD38 that governs OT release, contribute to individual differences in social skills from intense social involvement to extreme avoidance that characterize autism. To explore the neurochemical underpinnings of sociality, CD38 expression of peripheral blood leukocytes (PBL) was measured in Han Chinese undergraduates. First, CD38 mRNA levels were correlated with lower Autism Quotient (AQ), indicating enhanced social skills. AQ assesses the extent of autistic-like traits including the propensity and dexterity needed for successful social engagement in the general population. Second, three CD157 eQTL SNPs in the CD38/CD157 gene region were associated with CD38 expression. CD157 is a paralogue of CD38 and is contiguous with it on chromosome 4p15. Third, association was also observed between the CD157 eQTL SNPs, CD38 expression and AQ. In the full model, CD38 expression and CD157 eQTL SNPs altogether account for a substantial 14% of the variance in sociality. Fourth, functionality of CD157 eQTL SNPs was suggested by a significant association with plasma oxytocin immunoreactivity products. Fifth, the ecological validity of these findings was demonstrated with subjects with higher PBL CD38 expression having more friends, especially for males. Furthermore, CD157 sequence variation predicts scores on the Friendship questionnaire. To summarize, this study by uniquely leveraging various measures reveals salient elements contributing to nonkin sociality and friendship, revealing a likely pathway underpinning the transition from normality to psychopathology. Copyright © 2017 Elsevier Ltd. All rights reserved.

Genome-wide identification of expression quantitative trait loci for human telomerase.

PubMed

Kim, Hanseol; Ryu, Jihye; Lee, Chaeyoung

2016-10-01

A genome-wide association study was conducted to identify expression quantitative trait loci (eQTL) for human telomerase.We tested the genetic associations of nucleotide variants with expression of the genes encoding human telomerase reverse transcriptase (hTERT) and telomerase RNA components (TERC) in lymphoblastoid cell lines derived from 373 Europeans.Our results revealed 6 eQTLs associated with hTERT (P < 5 × 10). One eQTL (rs17755753) was located in the intron 1 of the gene encoding R-spondin-3 (RSPO3), a well-known Wnt signaling regulator. Transcriptome-wide association analysis for these eQTLs revealed their additional associations with the expression of 29 genes (P < 4.75 × 10), including prickle planar cell polarity protein 2 (PRICKLE2) gene important for the Wnt signaling pathway. This concurs with previous studies in which significant expressional relationships between hTERT and some genes (β-catenin and Wnt-3a) in the Wnt signaling pathway have been observed.This study suggested 6 novel eQTLs for hTERT and the association of hTERT with the Wnt signaling pathway. Further studies are needed to understand their underlying mechanisms to improve our understanding of the role of hTERT in cancer.

Aberrant Gene Expression in Humans

PubMed Central

Yang, Ence; Ji, Guoli; Brinkmeyer-Langford, Candice L.; Cai, James J.

2015-01-01

Gene expression as an intermediate molecular phenotype has been a focus of research interest. In particular, studies of expression quantitative trait loci (eQTL) have offered promise for understanding gene regulation through the discovery of genetic variants that explain variation in gene expression levels. Existing eQTL methods are designed for assessing the effects of common variants, but not rare variants. Here, we address the problem by establishing a novel analytical framework for evaluating the effects of rare or private variants on gene expression. Our method starts from the identification of outlier individuals that show markedly different gene expression from the majority of a population, and then reveals the contributions of private SNPs to the aberrant gene expression in these outliers. Using population-scale mRNA sequencing data, we identify outlier individuals using a multivariate approach. We find that outlier individuals are more readily detected with respect to gene sets that include genes involved in cellular regulation and signal transduction, and less likely to be detected with respect to the gene sets with genes involved in metabolic pathways and other fundamental molecular functions. Analysis of polymorphic data suggests that private SNPs of outlier individuals are enriched in the enhancer and promoter regions of corresponding aberrantly-expressed genes, suggesting a specific regulatory role of private SNPs, while the commonly-occurring regulatory genetic variants (i.e., eQTL SNPs) show little evidence of involvement. Additional data suggest that non-genetic factors may also underlie aberrant gene expression. Taken together, our findings advance a novel viewpoint relevant to situations wherein common eQTLs fail to predict gene expression when heritable, rare inter-individual variation exists. The analytical framework we describe, taking into consideration the reality of differential phenotypic robustness, may be valuable for investigating complex traits and conditions. PMID:25617623

Genevar: a database and Java application for the analysis and visualization of SNP-gene associations in eQTL studies

PubMed Central

Yang, Tsun-Po; Beazley, Claude; Montgomery, Stephen B.; Dimas, Antigone S.; Gutierrez-Arcelus, Maria; Stranger, Barbara E.; Deloukas, Panos; Dermitzakis, Emmanouil T.

2010-01-01

Summary: Genevar (GENe Expression VARiation) is a database and Java tool designed to integrate multiple datasets, and provides analysis and visualization of associations between sequence variation and gene expression. Genevar allows researchers to investigate expression quantitative trait loci (eQTL) associations within a gene locus of interest in real time. The database and application can be installed on a standard computer in database mode and, in addition, on a server to share discoveries among affiliations or the broader community over the Internet via web services protocols. Availability: http://www.sanger.ac.uk/resources/software/genevar Contact: emmanouil.dermitzakis@unige.ch PMID:20702402

Systems genetics reveals a transcriptional network associated with susceptibility in the maize-grey leaf spot pathosystem

USDA-ARS?s Scientific Manuscript database

We have applied a systems genetics approach to elucidate molecular mechanisms of maize responses to gray leaf spot (GLS) disease, caused by Cercospora zeina, a major threat to maize production globally. We conducted expression QTL (eQTL) analysis of gene expression variation measured in earleaf samp...

kruX: matrix-based non-parametric eQTL discovery.

PubMed

Qi, Jianlong; Asl, Hassan Foroughi; Björkegren, Johan; Michoel, Tom

2014-01-14

The Kruskal-Wallis test is a popular non-parametric statistical test for identifying expression quantitative trait loci (eQTLs) from genome-wide data due to its robustness against variations in the underlying genetic model and expression trait distribution, but testing billions of marker-trait combinations one-by-one can become computationally prohibitive. We developed kruX, an algorithm implemented in Matlab, Python and R that uses matrix multiplications to simultaneously calculate the Kruskal-Wallis test statistic for several millions of marker-trait combinations at once. KruX is more than ten thousand times faster than computing associations one-by-one on a typical human dataset. We used kruX and a dataset of more than 500k SNPs and 20k expression traits measured in 102 human blood samples to compare eQTLs detected by the Kruskal-Wallis test to eQTLs detected by the parametric ANOVA and linear model methods. We found that the Kruskal-Wallis test is more robust against data outliers and heterogeneous genotype group sizes and detects a higher proportion of non-linear associations, but is more conservative for calling additive linear associations. kruX enables the use of robust non-parametric methods for massive eQTL mapping without the need for a high-performance computing infrastructure and is freely available from http://krux.googlecode.com.

Sherlock: Detecting Gene-Disease Associations by Matching Patterns of Expression QTL and GWAS

PubMed Central

He, Xin; Fuller, Chris K.; Song, Yi; Meng, Qingying; Zhang, Bin; Yang, Xia; Li, Hao

2013-01-01

Genetic mapping of complex diseases to date depends on variations inside or close to the genes that perturb their activities. A strong body of evidence suggests that changes in gene expression play a key role in complex diseases and that numerous loci perturb gene expression in trans. The information in trans variants, however, has largely been ignored in the current analysis paradigm. Here we present a statistical framework for genetic mapping by utilizing collective information in both cis and trans variants. We reason that for a disease-associated gene, any genetic variation that perturbs its expression is also likely to influence the disease risk. Thus, the expression quantitative trait loci (eQTL) of the gene, which constitute a unique “genetic signature,” should overlap significantly with the set of loci associated with the disease. We translate this idea into a computational algorithm (named Sherlock) to search for gene-disease associations from GWASs, taking advantage of independent eQTL data. Application of this strategy to Crohn disease and type 2 diabetes predicts a number of genes with possible disease roles, including several predictions supported by solid experimental evidence. Importantly, predicted genes are often implicated by multiple trans eQTL with moderate associations. These genes are far from any GWAS association signals and thus cannot be identified from the GWAS alone. Our approach allows analysis of association data from a new perspective and is applicable to any complex phenotype. It is readily generalizable to molecular traits other than gene expression, such as metabolites, noncoding RNAs, and epigenetic modifications. PMID:23643380

SPIRE, a modular pipeline for eQTL analysis of RNA-Seq data, reveals a regulatory hotspot controlling miRNA expression in C. elegans.

PubMed

Kel, Ivan; Chang, Zisong; Galluccio, Nadia; Romeo, Margherita; Beretta, Stefano; Diomede, Luisa; Mezzelani, Alessandra; Milanesi, Luciano; Dieterich, Christoph; Merelli, Ivan

2016-10-18

The interpretation of genome-wide association study is difficult, as it is hard to understand how polymorphisms can affect gene regulation, in particular for trans-regulatory elements located far from their controlling gene. Using RNA or protein expression data as phenotypes, it is possible to correlate their variations with specific genotypes. This technique is usually referred to as expression Quantitative Trait Loci (eQTLs) analysis and only few packages exist for the integration of genotype patterns and expression profiles. In particular, tools are needed for the analysis of next-generation sequencing (NGS) data on a genome-wide scale, which is essential to identify eQTLs able to control a large number of genes (hotspots). Here we present SPIRE (Software for Polymorphism Identification Regulating Expression), a generic, modular and functionally highly flexible pipeline for eQTL processing. SPIRE integrates different univariate and multivariate approaches for eQTL analysis, paying particular attention to the scalability of the procedure in order to support cis- as well as trans-mapping, thus allowing the identification of hotspots in NGS data. In particular, we demonstrated how SPIRE can handle big association study datasets, reproducing published results and improving the identification of trans-eQTLs. Furthermore, we employed the pipeline to analyse novel data concerning the genotypes of two different C. elegans strains (N2 and Hawaii) and related miRNA expression data, obtained using RNA-Seq. A miRNA regulatory hotspot was identified in chromosome 1, overlapping the transcription factor grh-1, known to be involved in the early phases of embryonic development of C. elegans. In a follow-up qPCR experiment we were able to verify most of the predicted eQTLs, as well as to show, for a novel miRNA, a significant difference in the sequences of the two analysed strains of C. elegans. SPIRE is publicly available as open source software at , together with some example data, a readme file, supplementary material and a short tutorial.

Dissecting the genetics of the human transcriptome identifies novel trait-related trans-eQTLs and corroborates the regulatory relevance of non-protein coding loci†

PubMed Central

Kirsten, Holger; Al-Hasani, Hoor; Holdt, Lesca; Gross, Arnd; Beutner, Frank; Krohn, Knut; Horn, Katrin; Ahnert, Peter; Burkhardt, Ralph; Reiche, Kristin; Hackermüller, Jörg; Löffler, Markus; Teupser, Daniel; Thiery, Joachim; Scholz, Markus

2015-01-01

Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait-associated SNPs. However, power of most genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters and enrichment of co-localized functional elements. We found eQTLs for about 85% of analysed genes, and 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 Mb to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might frequently be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. Yet, we show for strongly heritable transcripts that still little trans-chromosomal heritability is explained by all identified trans-eSNPs; however, our data suggest that most cis-heritability of these transcripts seems explained. Dissection of co-localized functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene expression, pathways and disease-related processes. PMID:26019233

High-Dimensional Heteroscedastic Regression with an Application to eQTL Data Analysis

PubMed Central

Daye, Z. John; Chen, Jinbo; Li, Hongzhe

2011-01-01

Summary We consider the problem of high-dimensional regression under non-constant error variances. Despite being a common phenomenon in biological applications, heteroscedasticity has, so far, been largely ignored in high-dimensional analysis of genomic data sets. We propose a new methodology that allows non-constant error variances for high-dimensional estimation and model selection. Our method incorporates heteroscedasticity by simultaneously modeling both the mean and variance components via a novel doubly regularized approach. Extensive Monte Carlo simulations indicate that our proposed procedure can result in better estimation and variable selection than existing methods when heteroscedasticity arises from the presence of predictors explaining error variances and outliers. Further, we demonstrate the presence of heteroscedasticity in and apply our method to an expression quantitative trait loci (eQTLs) study of 112 yeast segregants. The new procedure can automatically account for heteroscedasticity in identifying the eQTLs that are associated with gene expression variations and lead to smaller prediction errors. These results demonstrate the importance of considering heteroscedasticity in eQTL data analysis. PMID:22547833

Regulatory Architecture of Gene Expression Variation in the Threespine Stickleback Gasterosteus aculeatus.

PubMed

Pritchard, Victoria L; Viitaniemi, Heidi M; McCairns, R J Scott; Merilä, Juha; Nikinmaa, Mikko; Primmer, Craig R; Leder, Erica H

2017-01-05

Much adaptive evolutionary change is underlain by mutational variation in regions of the genome that regulate gene expression rather than in the coding regions of the genes themselves. An understanding of the role of gene expression variation in facilitating local adaptation will be aided by an understanding of underlying regulatory networks. Here, we characterize the genetic architecture of gene expression variation in the threespine stickleback (Gasterosteus aculeatus), an important model in the study of adaptive evolution. We collected transcriptomic and genomic data from 60 half-sib families using an expression microarray and genotyping-by-sequencing, and located expression quantitative trait loci (eQTL) underlying the variation in gene expression in liver tissue using an interval mapping approach. We identified eQTL for several thousand expression traits. Expression was influenced by polymorphism in both cis- and trans-regulatory regions. Trans-eQTL clustered into hotspots. We did not identify master transcriptional regulators in hotspot locations: rather, the presence of hotspots may be driven by complex interactions between multiple transcription factors. One observed hotspot colocated with a QTL recently found to underlie salinity tolerance in the threespine stickleback. However, most other observed hotspots did not colocate with regions of the genome known to be involved in adaptive divergence between marine and freshwater habitats. Copyright © 2017 Pritchard et al.

Regulatory Architecture of Gene Expression Variation in the Threespine Stickleback Gasterosteus aculeatus

PubMed Central

Pritchard, Victoria L.; Viitaniemi, Heidi M.; McCairns, R. J. Scott; Merilä, Juha; Nikinmaa, Mikko; Primmer, Craig R.; Leder, Erica H.

2016-01-01

Much adaptive evolutionary change is underlain by mutational variation in regions of the genome that regulate gene expression rather than in the coding regions of the genes themselves. An understanding of the role of gene expression variation in facilitating local adaptation will be aided by an understanding of underlying regulatory networks. Here, we characterize the genetic architecture of gene expression variation in the threespine stickleback (Gasterosteus aculeatus), an important model in the study of adaptive evolution. We collected transcriptomic and genomic data from 60 half-sib families using an expression microarray and genotyping-by-sequencing, and located expression quantitative trait loci (eQTL) underlying the variation in gene expression in liver tissue using an interval mapping approach. We identified eQTL for several thousand expression traits. Expression was influenced by polymorphism in both cis- and trans-regulatory regions. Trans-eQTL clustered into hotspots. We did not identify master transcriptional regulators in hotspot locations: rather, the presence of hotspots may be driven by complex interactions between multiple transcription factors. One observed hotspot colocated with a QTL recently found to underlie salinity tolerance in the threespine stickleback. However, most other observed hotspots did not colocate with regions of the genome known to be involved in adaptive divergence between marine and freshwater habitats. PMID:27836907

kruX: matrix-based non-parametric eQTL discovery

PubMed Central

2014-01-01

Background The Kruskal-Wallis test is a popular non-parametric statistical test for identifying expression quantitative trait loci (eQTLs) from genome-wide data due to its robustness against variations in the underlying genetic model and expression trait distribution, but testing billions of marker-trait combinations one-by-one can become computationally prohibitive. Results We developed kruX, an algorithm implemented in Matlab, Python and R that uses matrix multiplications to simultaneously calculate the Kruskal-Wallis test statistic for several millions of marker-trait combinations at once. KruX is more than ten thousand times faster than computing associations one-by-one on a typical human dataset. We used kruX and a dataset of more than 500k SNPs and 20k expression traits measured in 102 human blood samples to compare eQTLs detected by the Kruskal-Wallis test to eQTLs detected by the parametric ANOVA and linear model methods. We found that the Kruskal-Wallis test is more robust against data outliers and heterogeneous genotype group sizes and detects a higher proportion of non-linear associations, but is more conservative for calling additive linear associations. Conclusion kruX enables the use of robust non-parametric methods for massive eQTL mapping without the need for a high-performance computing infrastructure and is freely available from http://krux.googlecode.com. PMID:24423115

Detection of a Cis eQTL Controlling BMCO1 Gene Expression Leads to the Identification of a QTG for Chicken Breast Meat Color

PubMed Central

Le Bihan-Duval, Elisabeth; Nadaf, Javad; Berri, Cécile; Pitel, Frédérique; Graulet, Benoît; Godet, Estelle; Leroux, Sophie Y.; Demeure, Olivier; Lagarrigue, Sandrine; Duby, Cécile; Cogburn, Larry A.; Beaumont, Catherine M.; Duclos, Michel J.

2011-01-01

Classical quantitative trait loci (QTL) analysis and gene expression QTL (eQTL) were combined to identify the causal gene (or QTG) underlying a highly significant QTL controlling the variation of breast meat color in a F2 cross between divergent high-growth (HG) and low-growth (LG) chicken lines. Within this meat quality QTL, BCMO1 (Accession number GenBank: AJ271386), encoding the β-carotene 15, 15′-monooxygenase, a key enzyme in the conversion of β-carotene into colorless retinal, was a good functional candidate. Analysis of the abundance of BCMO1 mRNA in breast muscle of the HG x LG F2 population allowed for the identification of a strong cis eQTL. Moreover, reevaluation of the color QTL taking BCMO1 mRNA levels as a covariate indicated that BCMO1 mRNA levels entirely explained the variations in meat color. Two fully-linked single nucleotide polymorphisms (SNP) located within the proximal promoter of BCMO1 gene were identified. Haplotype substitution resulted in a marked difference in BCMO1 promoter activity in vitro. The association study in the F2 population revealed a three-fold difference in BCMO1 expression leading to a difference of 1 standard deviation in yellow color between the homozygous birds at this haplotype. This difference in meat yellow color was fully consistent with the difference in carotenoid content (i.e. lutein and zeaxanthin) evidenced between the two alternative haplotypes. A significant association between the haplotype, the level of BCMO1 expression and the yellow color of the meat was also recovered in an unrelated commercial broiler population. The mutation could be of economic importance for poultry production by making possible a gene-assisted selection for color, a determining aspect of meat quality. Moreover, this natural genetic diversity constitutes a new model for the study of β-carotene metabolism which may act upon diverse biological processes as precursor of the vitamin A. PMID:21750696

Mapping eQTLs in the Norfolk Island Genetic Isolate Identifies Candidate Genes for CVD Risk Traits

PubMed Central

Benton, Miles C.; Lea, Rod A.; Macartney-Coxson, Donia; Carless, Melanie A.; Göring, Harald H.; Bellis, Claire; Hanna, Michelle; Eccles, David; Chambers, Geoffrey K.; Curran, Joanne E.; Harper, Jacquie L.; Blangero, John; Griffiths, Lyn R.

2013-01-01

Cardiovascular disease (CVD) affects millions of people worldwide and is influenced by numerous factors, including lifestyle and genetics. Expression quantitative trait loci (eQTLs) influence gene expression and are good candidates for CVD risk. Founder-effect pedigrees can provide additional power to map genes associated with disease risk. Therefore, we identified eQTLs in the genetic isolate of Norfolk Island (NI) and tested for associations between these and CVD risk factors. We measured genome-wide transcript levels of blood lymphocytes in 330 individuals and used pedigree-based heritability analysis to identify heritable transcripts. eQTLs were identified by genome-wide association testing of these transcripts. Testing for association between CVD risk factors (i.e., blood lipids, blood pressure, and body fat indices) and eQTLs revealed 1,712 heritable transcripts (p < 0.05) with heritability values ranging from 0.18 to 0.84. From these, we identified 200 cis-acting and 70 trans-acting eQTLs (p < 1.84 × 10−7) An eQTL-centric analysis of CVD risk traits revealed multiple associations, including 12 previously associated with CVD-related traits. Trait versus eQTL regression modeling identified four CVD risk candidates (NAAA, PAPSS1, NME1, and PRDX1), all of which have known biological roles in disease. In addition, we implicated several genes previously associated with CVD risk traits, including MTHFR and FN3KRP. We have successfully identified a panel of eQTLs in the NI pedigree and used this to implicate several genes in CVD risk. Future studies are required for further assessing the functional importance of these eQTLs and whether the findings here also relate to outbred populations. PMID:24314549

Decomposing genomic variance using information from GWA, GWE and eQTL analysis.

PubMed

Ehsani, A; Janss, L; Pomp, D; Sørensen, P

2016-04-01

A commonly used procedure in genome-wide association (GWA), genome-wide expression (GWE) and expression quantitative trait locus (eQTL) analyses is based on a bottom-up experimental approach that attempts to individually associate molecular variants with complex traits. Top-down modeling of the entire set of genomic data and partitioning of the overall variance into subcomponents may provide further insight into the genetic basis of complex traits. To test this approach, we performed a whole-genome variance components analysis and partitioned the genomic variance using information from GWA, GWE and eQTL analyses of growth-related traits in a mouse F2 population. We characterized the mouse trait genetic architecture by ordering single nucleotide polymorphisms (SNPs) based on their P-values and studying the areas under the curve (AUCs). The observed traits were found to have a genomic variance profile that differed significantly from that expected of a trait under an infinitesimal model. This situation was particularly true for both body weight and body fat, for which the AUCs were much higher compared with that of glucose. In addition, SNPs with a high degree of trait-specific regulatory potential (SNPs associated with subset of transcripts that significantly associated with a specific trait) explained a larger proportion of the genomic variance than did SNPs with high overall regulatory potential (SNPs associated with transcripts using traditional eQTL analysis). We introduced AUC measures of genomic variance profiles that can be used to quantify relative importance of SNPs as well as degree of deviation of a trait's inheritance from an infinitesimal model. The shape of the curve aids global understanding of traits: The steeper the left-hand side of the curve, the fewer the number of SNPs controlling most of the phenotypic variance. © 2015 Stichting International Foundation for Animal Genetics.

Transcriptional risk scores link GWAS to eQTLs and predict complications in Crohn's disease.

PubMed

Marigorta, Urko M; Denson, Lee A; Hyams, Jeffrey S; Mondal, Kajari; Prince, Jarod; Walters, Thomas D; Griffiths, Anne; Noe, Joshua D; Crandall, Wallace V; Rosh, Joel R; Mack, David R; Kellermayer, Richard; Heyman, Melvin B; Baker, Susan S; Stephens, Michael C; Baldassano, Robert N; Markowitz, James F; Kim, Mi-Ok; Dubinsky, Marla C; Cho, Judy; Aronow, Bruce J; Kugathasan, Subra; Gibson, Greg

2017-10-01

Gene expression profiling can be used to uncover the mechanisms by which loci identified through genome-wide association studies (GWAS) contribute to pathology. Given that most GWAS hits are in putative regulatory regions and transcript abundance is physiologically closer to the phenotype of interest, we hypothesized that summation of risk-allele-associated gene expression, namely a transcriptional risk score (TRS), should provide accurate estimates of disease risk. We integrate summary-level GWAS and expression quantitative trait locus (eQTL) data with RNA-seq data from the RISK study, an inception cohort of pediatric Crohn's disease. We show that TRSs based on genes regulated by variants linked to inflammatory bowel disease (IBD) not only outperform genetic risk scores (GRSs) in distinguishing Crohn's disease from healthy samples, but also serve to identify patients who in time will progress to complicated disease. Our dissection of eQTL effects may be used to distinguish genes whose association with disease is through promotion versus protection, thereby linking statistical association to biological mechanism. The TRS approach constitutes a potential strategy for personalized medicine that enhances inference from static genotypic risk assessment.

Genetic Dissection of Nutrition-Induced Plasticity in Insulin/Insulin-Like Growth Factor Signaling and Median Life Span in a Drosophila Multiparent Population

PubMed Central

Stanley, Patrick D.; Ng’oma, Enoch; O’Day, Siri; King, Elizabeth G.

2017-01-01

The nutritional environments that organisms experience are inherently variable, requiring tight coordination of how resources are allocated to different functions relative to the total amount of resources available. A growing body of evidence supports the hypothesis that key endocrine pathways play a fundamental role in this coordination. In particular, the insulin/insulin-like growth factor signaling (IIS) and target of rapamycin (TOR) pathways have been implicated in nutrition-dependent changes in metabolism and nutrient allocation. However, little is known about the genetic basis of standing variation in IIS/TOR or how diet-dependent changes in expression in this pathway influence phenotypes related to resource allocation. To characterize natural genetic variation in the IIS/TOR pathway, we used >250 recombinant inbred lines (RILs) derived from a multiparental mapping population, the Drosophila Synthetic Population Resource, to map transcript-level QTL of genes encoding 52 core IIS/TOR components in three different nutritional environments [dietary restriction (DR), control (C), and high sugar (HS)]. Nearly all genes, 87%, were significantly differentially expressed between diets, though not always in ways predicted by loss-of-function mutants. We identified cis (i.e., local) expression QTL (eQTL) for six genes, all of which are significant in multiple nutrient environments. Further, we identified trans (i.e., distant) eQTL for two genes, specific to a single nutrient environment. Our results are consistent with many small changes in the IIS/TOR pathways. A discriminant function analysis for the C and DR treatments identified a pattern of gene expression associated with the diet treatment. Mapping the composite discriminant function scores revealed a significant global eQTL within the DR diet. A correlation between the discriminant function scores and the median life span (r = 0.46) provides evidence that gene expression changes in response to diet are associated with longevity in these RILs. PMID:28592498

Integrated Genome-wide association and hypothalamus eQTL studies indicate a link between the circadian rhythm-related gene PER1 and coping behavior

PubMed Central

Ponsuksili, Siriluck; Zebunke, Manuela; Murani, Eduard; Trakooljul, Nares; Krieter, Joachim; Puppe, Birger; Schwerin, Manfred; Wimmers, Klaus

2015-01-01

Animal personality and coping styles are basic concepts for evaluating animal welfare. Struggling response of piglets in so-called backtests early in life reflects their coping strategy. Behavioral reactions of piglets in backtests have a moderate heritability, but their genetic basis largely remains unknown. Here, latency, duration and frequency of struggling attempts during one-minute backtests were repeatedly recorded of piglets at days 5, 12, 19, and 26. A genome-wide association study for backtest traits revealed 465 significant SNPs (FDR ≤ 0.05) mostly located in QTL (quantitative trait locus) regions on chromosome 3, 5, 12 and 16. In order to capture genes in these regions, 37 transcripts with significant SNPs were selected for expressionQTL analysis in the hypothalamus. Eight genes (ASGR1, CPAMD8, CTC1, FBXO39, IL19, LOC100511790, RAD51B, UBOX5) had cis- and five (RANGRF, PER1, PDZRN3, SH2D4B, LONP2) had trans-expressionQTL. In particular, for PER1, with known physiological implications for maintenance of circadian rhythms, a role in coping behavior was evidenced by confirmed association in an independent population. For CTC1 a cis-expression QTL and the consistent relationship of gene polymorphism, mRNA expression level and backtest traits promoted its link to coping style. GWAS and eQTL analyses uncovered positional and functional gene candidates for coping behavior. PMID:26537429

Integrated Genome-wide association and hypothalamus eQTL studies indicate a link between the circadian rhythm-related gene PER1 and coping behavior.

PubMed

Ponsuksili, Siriluck; Zebunke, Manuela; Murani, Eduard; Trakooljul, Nares; Krieter, Joachim; Puppe, Birger; Schwerin, Manfred; Wimmers, Klaus

2015-11-05

Animal personality and coping styles are basic concepts for evaluating animal welfare. Struggling response of piglets in so-called backtests early in life reflects their coping strategy. Behavioral reactions of piglets in backtests have a moderate heritability, but their genetic basis largely remains unknown. Here, latency, duration and frequency of struggling attempts during one-minute backtests were repeatedly recorded of piglets at days 5, 12, 19, and 26. A genome-wide association study for backtest traits revealed 465 significant SNPs (FDR ≤ 0.05) mostly located in QTL (quantitative trait locus) regions on chromosome 3, 5, 12 and 16. In order to capture genes in these regions, 37 transcripts with significant SNPs were selected for expressionQTL analysis in the hypothalamus. Eight genes (ASGR1, CPAMD8, CTC1, FBXO39, IL19, LOC100511790, RAD51B, UBOX5) had cis- and five (RANGRF, PER1, PDZRN3, SH2D4B, LONP2) had trans-expressionQTL. In particular, for PER1, with known physiological implications for maintenance of circadian rhythms, a role in coping behavior was evidenced by confirmed association in an independent population. For CTC1 a cis-expression QTL and the consistent relationship of gene polymorphism, mRNA expression level and backtest traits promoted its link to coping style. GWAS and eQTL analyses uncovered positional and functional gene candidates for coping behavior.

Analysis of Multiple Association Studies Provides Evidence of an Expression QTL Hub in Gene-Gene Interaction Network Affecting HDL Cholesterol Levels

PubMed Central

Ma, Li; Ballantyne, Christie; Brautbar, Ariel; Keinan, Alon

2014-01-01

Epistasis has been suggested to underlie part of the missing heritability in genome-wide association studies. In this study, we first report an analysis of gene-gene interactions affecting HDL cholesterol (HDL-C) levels in a candidate gene study of 2,091 individuals with mixed dyslipidemia from a clinical trial. Two additional studies, the Atherosclerosis Risk in Communities study (ARIC; n = 9,713) and the Multi-Ethnic Study of Atherosclerosis (MESA; n = 2,685), were considered for replication. We identified a gene-gene interaction between rs1532085 and rs12980554 (P = 7.1×10−7) in their effect on HDL-C levels, which is significant after Bonferroni correction (P c = 0.017) for the number of SNP pairs tested. The interaction successfully replicated in the ARIC study (P = 7.0×10−4; P c = 0.02). Rs1532085, an expression QTL (eQTL) of LIPC, is one of the two SNPs involved in another, well-replicated gene-gene interaction underlying HDL-C levels. To further investigate the role of this eQTL SNP in gene-gene interactions affecting HDL-C, we tested in the ARIC study for interaction between this SNP and any other SNP genome-wide. We found the eQTL to be involved in a few suggestive interactions, one of which significantly replicated in MESA. Importantly, these gene-gene interactions, involving only rs1532085, explain an additional 1.4% variation of HDL-C, on top of the 0.65% explained by rs1532085 alone. LIPC plays a key role in the lipid metabolism pathway and it, and rs1532085 in particular, has been associated with HDL-C and other lipid levels. Collectively, we discovered several novel gene-gene interactions, all involving an eQTL of LIPC, thus suggesting a hub role of LIPC in the gene-gene interaction network that regulates HDL-C levels, which in turn raises the hypothesis that LIPC's contribution is largely via interactions with other lipid metabolism related genes. PMID:24651390

Dissecting the genetics of the human transcriptome identifies novel trait-related trans-eQTLs and corroborates the regulatory relevance of non-protein coding loci†.

PubMed

Kirsten, Holger; Al-Hasani, Hoor; Holdt, Lesca; Gross, Arnd; Beutner, Frank; Krohn, Knut; Horn, Katrin; Ahnert, Peter; Burkhardt, Ralph; Reiche, Kristin; Hackermüller, Jörg; Löffler, Markus; Teupser, Daniel; Thiery, Joachim; Scholz, Markus

2015-08-15

Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait-associated SNPs. However, power of most genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters and enrichment of co-localized functional elements. We found eQTLs for about 85% of analysed genes, and 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 Mb to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might frequently be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. Yet, we show for strongly heritable transcripts that still little trans-chromosomal heritability is explained by all identified trans-eSNPs; however, our data suggest that most cis-heritability of these transcripts seems explained. Dissection of co-localized functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene expression, pathways and disease-related processes. © The Author 2015. Published by Oxford University Press.

An Integrative Genetics Approach to Identify Candidate Genes Regulating BMD: Combining Linkage, Gene Expression, and Association

PubMed Central

Farber, Charles R; van Nas, Atila; Ghazalpour, Anatole; Aten, Jason E; Doss, Sudheer; Sos, Brandon; Schadt, Eric E; Ingram-Drake, Leslie; Davis, Richard C; Horvath, Steve; Smith, Desmond J; Drake, Thomas A; Lusis, Aldons J

2009-01-01

Numerous quantitative trait loci (QTLs) affecting bone traits have been identified in the mouse; however, few of the underlying genes have been discovered. To improve the process of transitioning from QTL to gene, we describe an integrative genetics approach, which combines linkage analysis, expression QTL (eQTL) mapping, causality modeling, and genetic association in outbred mice. In C57BL/6J × C3H/HeJ (BXH) F2 mice, nine QTLs regulating femoral BMD were identified. To select candidate genes from within each QTL region, microarray gene expression profiles from individual F2 mice were used to identify 148 genes whose expression was correlated with BMD and regulated by local eQTLs. Many of the genes that were the most highly correlated with BMD have been previously shown to modulate bone mass or skeletal development. Candidates were further prioritized by determining whether their expression was predicted to underlie variation in BMD. Using network edge orienting (NEO), a causality modeling algorithm, 18 of the 148 candidates were predicted to be causally related to differences in BMD. To fine-map QTLs, markers in outbred MF1 mice were tested for association with BMD. Three chromosome 11 SNPs were identified that were associated with BMD within the Bmd11 QTL. Finally, our approach provides strong support for Wnt9a, Rasd1, or both underlying Bmd11. Integration of multiple genetic and genomic data sets can substantially improve the efficiency of QTL fine-mapping and candidate gene identification. PMID:18767929

eQTL networks unveil enriched mRNA master integrators downstream of complex disease-associated SNPs.

PubMed

Li, Haiquan; Pouladi, Nima; Achour, Ikbel; Gardeux, Vincent; Li, Jianrong; Li, Qike; Zhang, Hao Helen; Martinez, Fernando D; 'Skip' Garcia, Joe G N; Lussier, Yves A

2015-12-01

The causal and interplay mechanisms of Single Nucleotide Polymorphisms (SNPs) associated with complex diseases (complex disease SNPs) investigated in genome-wide association studies (GWAS) at the transcriptional level (mRNA) are poorly understood despite recent advancements such as discoveries reported in the Encyclopedia of DNA Elements (ENCODE) and Genotype-Tissue Expression (GTex). Protein interaction network analyses have successfully improved our understanding of both single gene diseases (Mendelian diseases) and complex diseases. Whether the mRNAs downstream of complex disease genes are central or peripheral in the genetic information flow relating DNA to mRNA remains unclear and may be disease-specific. Using expression Quantitative Trait Loci (eQTL) that provide DNA to mRNA associations and network centrality metrics, we hypothesize that we can unveil the systems properties of information flow between SNPs and the transcriptomes of complex diseases. We compare different conditions such as naïve SNP assignments and stringent linkage disequilibrium (LD) free assignments for transcripts to remove confounders from LD. Additionally, we compare the results from eQTL networks between lymphoblastoid cell lines and liver tissue. Empirical permutation resampling (p<0.001) and theoretic Mann-Whitney U test (p<10(-30)) statistics indicate that mRNAs corresponding to complex disease SNPs via eQTL associations are likely to be regulated by a larger number of SNPs than expected. We name this novel property mRNA hubness in eQTL networks, and further term mRNAs with high hubness as master integrators. mRNA master integrators receive and coordinate the perturbation signals from large numbers of polymorphisms and respond to the personal genetic architecture integratively. This genetic signal integration contrasts with the mechanism underlying some Mendelian diseases, where a genetic polymorphism affecting a single protein hub produces a divergent signal that affects a large number of downstream proteins. Indeed, we verify that this property is independent of the hubness in protein networks for which these mRNAs are transcribed. Our findings provide novel insights into the pleiotropy of mRNAs targeted by complex disease polymorphisms and the architecture of the information flow between the genetic polymorphisms and transcriptomes of complex diseases. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Expression quantitative trait loci and genetic regulatory network analysis reveals that Gabra2 is involved in stress responses in the mouse.

PubMed

Dai, Jiajuan; Wang, Xusheng; Chen, Ying; Wang, Xiaodong; Zhu, Jun; Lu, Lu

2009-11-01

Previous studies have revealed that the subunit alpha 2 (Gabra2) of the gamma-aminobutyric acid receptor plays a critical role in the stress response. However, little is known about the gentetic regulatory network for Gabra2 and the stress response. We combined gene expression microarray analysis and quantitative trait loci (QTL) mapping to characterize the genetic regulatory network for Gabra2 expression in the hippocampus of BXD recombinant inbred (RI) mice. Our analysis found that the expression level of Gabra2 exhibited much variation in the hippocampus across the BXD RI strains and between the parental strains, C57BL/6J, and DBA/2J. Expression QTL (eQTL) mapping showed three microarray probe sets of Gabra2 to have highly significant linkage likelihood ratio statistic (LRS) scores. Gene co-regulatory network analysis showed that 10 genes, including Gria3, Chka, Drd3, Homer1, Grik2, Odz4, Prkag2, Grm5, Gabrb1, and Nlgn1 are directly or indirectly associated with stress responses. Eleven genes were implicated as Gabra2 downstream genes through mapping joint modulation. The genetical genomics approach demonstrates the importance and the potential power of the eQTL studies in identifying genetic regulatory networks that contribute to complex traits, such as stress responses.

Gene signatures of postoperative atrial fibrillation in atrial tissue after coronary artery bypass grafting surgery in patients receiving β-blockers.

PubMed

Kertai, Miklos D; Qi, Wenjing; Li, Yi-Ju; Lombard, Frederick W; Liu, Yutao; Smith, Michael P; Stafford-Smith, Mark; Newman, Mark F; Milano, Carmelo A; Mathew, Joseph P; Podgoreanu, Mihai V

2016-03-01

Atrial tissue gene expression profiling may help to determine how differentially expressed genes in the human atrium before cardiopulmonary bypass (CPB) are related to subsequent biologic pathway activation patterns, and whether specific expression profiles are associated with an increased risk for postoperative atrial fibrillation (AF) or altered response to β-blocker (BB) therapy after coronary artery bypass grafting (CABG) surgery. Right atrial appendage (RAA) samples were collected from 45 patients who were receiving perioperative BB treatment, and underwent CABG surgery. The isolated RNA samples were used for microarray gene expression analysis, to identify probes that were expressed differently in patients with and without postoperative AF. Gene expression analysis was performed to identify probes that were expressed differently in patients with and without postoperative AF. Gene set enrichment analysis (GSEA) was performed to determine how sets of genes might be systematically altered in patients with postoperative AF. Of the 45 patients studied, genomic DNA from 42 patients was used for target sequencing of 66 candidate genes potentially associated with AF, and 2,144 single-nucleotide polymorphisms (SNPs) were identified. We then performed expression quantitative trait loci (eQTL) analysis to determine the correlation between SNPs identified in the genotyped patients, and RAA expression. Probes that met a false discovery rate<0.25 were selected for eQTL analysis. Of the 17,678 gene expression probes analyzed, 2 probes met our prespecified significance threshold of false discovery rate<0.25. The most significant probe corresponded to vesicular overexpressed in cancer - prosurvival protein 1 gene (VOPP1; 1.83 fold change; P=3.47×10(-7)), and was up-regulated in patients with postoperative AF, whereas the second most significant probe, which corresponded to the LOC389286 gene (0.49 fold change; P=1.54×10(-5)), was down-regulated in patients with postoperative AF. GSEA highlighted the role of VOPP1 in pathways with biologic relevance to myocardial homeostasis, and oxidative stress and redox modulation. Candidate gene eQTL showed a trans-acting association between variants of G protein-coupled receptor kinase 5 gene, previously linked to altered BB response, and high expression of VOPP1. In patients undergoing CABG surgery, RAA gene expression profiling, and pathway and eQTL analysis suggested that VOPP1 plays a novel etiological role in postoperative AF despite perioperative BB therapy. Copyright © 2016. Published by Elsevier Ltd.

Genetical Toxicogenomics in Drosophila Identifies Master Modulatory Loci that are Regulated by Developmental Exposure to Lead

PubMed Central

Ruden, Douglas M.; Chen, Lang; Possidente, Debra; Possidente, Bernard; Rasouli, Parsa; Wang, Luan; Lu, Xiangyi; Garfinkel, Mark D.; Hirsch, Helmut V. B.; Page, Grier P.

2009-01-01

The genetics of gene expression in recombinant inbred lines (RILs) can be mapped as expression quantitative trait loci (eQTLs). So-called “genetical genomics” studies have identified locally-acting eQTLs (cis-eQTLs) for genes that show differences in steady state RNA levels. These studies have also identified distantly-acting master-modulatory trans-eQTLs that regulate tens or hundreds of transcripts (hotspots or transbands). We expand on these studies by performing genetical genomics experiments in two environments in order to identify trans-eQTL that might be regulated by developmental exposure to the neurotoxin lead. Flies from each of 75 RIL were raised from eggs to adults on either control food (made with 250 µM sodium acetate), or lead-treated food (made with 250 µM lead acetate, PbAc). RNA expression analyses of whole adult male flies (5–10 days old) were performed with Affymetrix DrosII whole genome arrays (18,952 probesets). Among the 1,389 genes with cis-eQTL, there were 405 genes unique to control flies and 544 genes unique to lead-treated ones (440 genes had the same cis-eQTLs in both samples). There are 2,396 genes with trans-eQTL which mapped to 12 major transbands with greater than 95 genes. Permutation analyses of the strain labels but not the expression data suggests that the total number of eQTL and the number of transbands are more important criteria for validation than the size of the transband. Two transbands, one located on the 2nd chromosome and one on the 3rd chromosome, co-regulate 33 lead-induced genes, many of which are involved in neurodevelopmental processes. For these 33 genes, rather than allelic variation at one locus exerting differential effects in two environments, we found that variation at two different loci are required for optimal effects on lead-induced expression. PMID:19737576

Transcriptional regulation of PNPLA3 and its impact on susceptibility to nonalcoholic fatty liver Disease (NAFLD) in humans

PubMed Central

Wang, Xiaoliang; Gawrieh, Samer; Gamazon, Eric R.; Athinarayanan, Shaminie; Liu, Yang-Lin; Darlay, Rebecca; Cordell, Heather J; Daly, Ann K

2017-01-01

The increased expression of PNPLA3148M leads to hepatosteatosis in mice. This study aims to investigate the genetic control of hepatic PNPLA3 transcription and to explore its impact on NAFLD risk in humans. Through a locus-wide expression quantitative trait loci (eQTL) mapping in two human liver sample sets, a PNPLA3 intronic SNP, rs139051 A>G was identified as a significant eQTL (p = 6.6×10−8) influencing PNPLA3 transcription, with the A allele significantly associated with increased PNPLA3 mRNA. An electrophoresis mobility shift assay further demonstrated that the A allele has enhanced affinity to nuclear proteins than the G allele. The impact of this eQTL on NAFLD risk was further tested in three independent populations. We found that rs139051 did not independently affect the NAFLD risk, whilst rs738409 did not significantly modulate PNPLA3 transcription but was associated with NAFLD risk. The A-G haplotype associated with higher transcription of the disease-risk rs738409 G allele conferred similar risk for NAFLD compared to the G-G haplotype that possesses a lower transcription level. Our study suggests that the pathogenic role of PNPLA3148M in NAFLD is independent of the gene transcription in humans, which may be attributed to the high endogenous transcription level of PNPLA3 gene in human livers. PMID:27744419

Transcriptional regulation of PNPLA3 and its impact on susceptibility to nonalcoholic fatty liver Disease (NAFLD) in humans.

PubMed

Liu, Wanqing; Anstee, Quentin M; Wang, Xiaoliang; Gawrieh, Samer; Gamazon, Eric R; Athinarayanan, Shaminie; Liu, Yang-Lin; Darlay, Rebecca; Cordell, Heather J; Daly, Ann K; Day, Chris P; Chalasani, Naga

2016-10-13

The increased expression of PNPLA3 148M leads to hepatosteatosis in mice. This study aims to investigate the genetic control of hepatic PNPLA3 transcription and to explore its impact on NAFLD risk in humans. Through a locus-wide expression quantitative trait loci (eQTL) mapping in two human liver sample sets, a PNPLA3 intronic SNP, rs139051 A>G was identified as a significant eQTL ( p = 6.6×10 -8 ) influencing PNPLA3 transcription, with the A allele significantly associated with increased PNPLA3 mRNA. An electrophoresis mobility shift assay further demonstrated that the A allele has enhanced affinity to nuclear proteins than the G allele. The impact of this eQTL on NAFLD risk was further tested in three independent populations. We found that rs139051 did not independently affect the NAFLD risk, whilst rs738409 did not significantly modulate PNPLA3 transcription but was associated with NAFLD risk. The A-G haplotype associated with higher transcription of the disease-risk rs738409 G allele conferred similar risk for NAFLD compared to the G-G haplotype that possesses a lower transcription level. Our study suggests that the pathogenic role of PNPLA3 148M in NAFLD is independent of the gene transcription in humans, which may be attributed to the high endogenous transcription level of PNPLA3 gene in human livers.

Physical Interactions and Expression Quantitative Traits Loci Identify Regulatory Connections for Obesity and Type 2 Diabetes Associated SNPs

PubMed Central

Fadason, Tayaza; Ekblad, Cameron; Ingram, John R.; Schierding, William S.; O'Sullivan, Justin M.

2017-01-01

The mechanisms that underlie the association between obesity and type 2 diabetes are not fully understood. Here, we investigated the role of the 3D genome organization in the pathogeneses of obesity and type-2 diabetes. We interpreted the combined and differential impacts of 196 diabetes and 390 obesity associated single nucleotide polymorphisms (SNPs) by integrating data on the genes with which they physically interact (as captured by Hi-C) and the functional [i.e., expression quantitative trait loci (eQTL)] outcomes associated with these interactions. We identified 861 spatially regulated genes (e.g., AP3S2, ELP5, SVIP, IRS1, FADS2, WFS1, RBM6, HORMAD1, PYROXD2), which are enriched in tissues (e.g., adipose, skeletal muscle, pancreas) and biological processes and canonical pathways (e.g., lipid metabolism, leptin, and glucose-insulin signaling pathways) that are important for the pathogenesis of type 2 diabetes and obesity. Our discovery-based approach also identifies enrichment for eQTL SNP-gene interactions in tissues that are not classically associated with diabetes or obesity. We propose that the combinatorial action of active obesity and diabetes spatial eQTL SNPs on their gene pairs within different tissues reduces the ability of these tissues to contribute to the maintenance of a healthy energy metabolism. PMID:29081791

WormQTLHD--a web database for linking human disease to natural variation data in C. elegans.

PubMed

van der Velde, K Joeri; de Haan, Mark; Zych, Konrad; Arends, Danny; Snoek, L Basten; Kammenga, Jan E; Jansen, Ritsert C; Swertz, Morris A; Li, Yang

2014-01-01

Interactions between proteins are highly conserved across species. As a result, the molecular basis of multiple diseases affecting humans can be studied in model organisms that offer many alternative experimental opportunities. One such organism-Caenorhabditis elegans-has been used to produce much molecular quantitative genetics and systems biology data over the past decade. We present WormQTL(HD) (Human Disease), a database that quantitatively and systematically links expression Quantitative Trait Loci (eQTL) findings in C. elegans to gene-disease associations in man. WormQTL(HD), available online at http://www.wormqtl-hd.org, is a user-friendly set of tools to reveal functionally coherent, evolutionary conserved gene networks. These can be used to predict novel gene-to-gene associations and the functions of genes underlying the disease of interest. We created a new database that links C. elegans eQTL data sets to human diseases (34 337 gene-disease associations from OMIM, DGA, GWAS Central and NHGRI GWAS Catalogue) based on overlapping sets of orthologous genes associated to phenotypes in these two species. We utilized QTL results, high-throughput molecular phenotypes, classical phenotypes and genotype data covering different developmental stages and environments from WormQTL database. All software is available as open source, built on MOLGENIS and xQTL workbench.

Mapping of Gene Expression Reveals CYP27A1 as a Susceptibility Gene for Sporadic ALS

PubMed Central

van Rheenen, Wouter; Franke, Lude; Jansen, Ritsert C.; van Es, Michael A.; van Vught, Paul W. J.; Blauw, Hylke M.; Groen, Ewout J. N.; Horvath, Steve; Estrada, Karol; Rivadeneira, Fernando; Hofman, Albert; Uitterlinden, Andre G.; Robberecht, Wim; Andersen, Peter M.; Melki, Judith; Meininger, Vincent; Hardiman, Orla; Landers, John E.; Brown, Robert H.; Shatunov, Aleksey; Shaw, Christopher E.; Leigh, P. Nigel; Al-Chalabi, Ammar; Ophoff, Roel A.

2012-01-01

Amyotrophic lateral sclerosis (ALS) is a progressive, neurodegenerative disease characterized by loss of upper and lower motor neurons. ALS is considered to be a complex trait and genome-wide association studies (GWAS) have implicated a few susceptibility loci. However, many more causal loci remain to be discovered. Since it has been shown that genetic variants associated with complex traits are more likely to be eQTLs than frequency-matched variants from GWAS platforms, we conducted a two-stage genome-wide screening for eQTLs associated with ALS. In addition, we applied an eQTL analysis to finemap association loci. Expression profiles using peripheral blood of 323 sporadic ALS patients and 413 controls were mapped to genome-wide genotyping data. Subsequently, data from a two-stage GWAS (3,568 patients and 10,163 controls) were used to prioritize eQTLs identified in the first stage (162 ALS, 207 controls). These prioritized eQTLs were carried forward to the second sample with both gene-expression and genotyping data (161 ALS, 206 controls). Replicated eQTL SNPs were then tested for association in the second-stage GWAS data to find SNPs associated with disease, that survived correction for multiple testing. We thus identified twelve cis eQTLs with nominally significant associations in the second-stage GWAS data. Eight SNP-transcript pairs of highest significance (lowest p = 1.27×10−51) withstood multiple-testing correction in the second stage and modulated CYP27A1 gene expression. Additionally, we show that C9orf72 appears to be the only gene in the 9p21.2 locus that is regulated in cis, showing the potential of this approach in identifying causative genes in association loci in ALS. This study has identified candidate genes for sporadic ALS, most notably CYP27A1. Mutations in CYP27A1 are causal to cerebrotendinous xanthomatosis which can present as a clinical mimic of ALS with progressive upper motor neuron loss, making it a plausible susceptibility gene for ALS. PMID:22509407

Multiple correlation analyses revealed complex relationship between DNA methylation and mRNA expression in human peripheral blood mononuclear cells.

PubMed

Xie, Fang-Fei; Deng, Fei-Yan; Wu, Long-Fei; Mo, Xing-Bo; Zhu, Hong; Wu, Jian; Guo, Yu-Fan; Zeng, Ke-Qin; Wang, Ming-Jun; Zhu, Xiao-Wei; Xia, Wei; Wang, Lan; He, Pei; Bing, Peng-Fei; Lu, Xin; Zhang, Yong-Hong; Lei, Shu-Feng

2018-01-01

DNA methylation is an important regulator on the mRNA expression. However, a genome-wide correlation pattern between DNA methylation and mRNA expression in human peripheral blood mononuclear cells (PBMCs) is largely unknown. The comprehensive relationship between mRNA and DNA methylation was explored by using four types of correlation analyses and a genome-wide methylation-mRNA expression quantitative trait locus (eQTL) analysis in PBMCs in 46 unrelated female subjects. An enrichment analysis was performed to detect biological function for the detected genes. Single pair correlation coefficient (r T1 ) between methylation level and mRNA is moderate (-0.63-0.62) in intensity, and the negative and positive correlations are nearly equal in quantity. Correlation analysis on each gene (T4) found 60.1% genes showed correlations between mRNA and gene-based methylation at P < 0.05 and more than 5.96% genes presented very strong correlation (R T4  > 0.8). Methylation sites have regulation effects on mRNA expression in eQTL analysis, with more often observations in region of transcription start site (TSS). The genes under significant methylation regulation both in correlation analysis and eQTL analysis tend to cluster to the categories (e.g., transcription, translation, regulation of transcription) that are essential for maintaining the basic life activities of cells. Our findings indicated that DNA methylation has predictive regulation effect on mRNA with a very complex pattern in PBMCs. The results increased our understanding on correlation of methylation and mRNA and also provided useful clues for future epigenetic studies in exploring biological and disease-related regulatory mechanisms in PBMC.

Changes in macrophage transcriptome associate with systemic sclerosis and mediate GSDMA contribution to disease risk

PubMed Central

Koturan, Surya; Ko, Jeong-Hun; Fonseca, Carmen; Harmston, Nathan; Game, Laurence; Martin, Javier; Ong, Voon; Abraham, David J; Denton, Christopher P; Behmoaras, Jacques; Petretto, Enrico

2018-01-01

Objectives Several common and rare risk variants have been reported for systemic sclerosis (SSc), but the effector cell(s) mediating the function of these genetic variants remains to be elucidated. While innate immune cells have been proposed as the critical targets to interfere with the disease process underlying SSc, no studies have comprehensively established their effector role. Here we investigated the contribution of monocyte-derived macrophages (MDMs) in mediating genetic susceptibility to SSc. Methods We carried out RNA sequencing and genome-wide genotyping in MDMs from 57 patients with SSc and 15 controls. Our differential expression and expression quantitative trait locus (eQTL) analysis in SSc was further integrated with epigenetic, expression and eQTL data from skin, monocytes, neutrophils and lymphocytes. Results We identified 602 genes upregulated and downregulated in SSc macrophages that were significantly enriched for genes previously implicated in SSc susceptibility (P=5×10−4), and 270 cis-regulated genes in MDMs. Among these, GSDMA was reported to carry an SSc risk variant (rs3894194) regulating expression of neighbouring genes in blood. We show that GSDMA is upregulated in SSc MDMs (P=8.4×10−4) but not in the skin, and is a significant eQTL in SSc macrophages and lipopolysaccharide/interferon gamma (IFNγ)-stimulated monocytes. Furthermore, we identify an SSc macrophage transcriptome signature characterised by upregulation of glycolysis, hypoxia and mTOR signalling and a downregulation of IFNγ response pathways. Conclusions Our data further establish the link between macrophages and SSc, and suggest that the contribution of the rs3894194 risk variant to SSc susceptibility can be mediated by GSDMA expression in macrophages. PMID:29348297

The Hypoxic Response Contributes to Altered Gene Expression and Pre-Capillary Pulmonary Hypertension in Patients with Sickle Cell Disease

PubMed Central

Zhang, Xu; Zhang, Wei; Ma, Shwu-Fan; Desai, Ankit A.; Saraf, Santosh; Miasniakova, Galina; Sergueeva, Adelina; Ammosova, Tatiana; Xu, Min; Nekhai, Sergei; Abbasi, Taimur; Casanova, Nancy G.; Steinberg, Martin H.; Baldwin, Clinton T.; Sebastiani, Paola; Prchal, Josef T.; Kittles, Rick; Garcia, Joe G. N.; Machado, Roberto F.; Gordeuk, Victor R.

2014-01-01

Background We postulated that the hypoxic response in sickle cell disease (SCD) contributes to altered gene expression and pulmonary hypertension, a complication associated with early mortality. Methods and Results To identify genes regulated by the hypoxic response and not other effects of chronic anemia, we compared expression variation in peripheral blood mononuclear cells from 13 SCD subjects with hemoglobin SS genotype and 15 Chuvash polycythemia subjects (VHLR200W homozygotes with constitutive up-regulation of hypoxia inducible factors in the absence of anemia or hypoxia). At 5% false discovery rate, 1040 genes exhibited >1.15 fold change in both conditions; 297 were up-regulated and 743 down-regulated including MAPK8 encoding a mitogen-activated protein kinase important for apoptosis, T-cell differentiation and inflammatory responses. Association mapping with a focus on local regulatory polymorphisms in 61 SCD patients identified expression quantitative trait loci (eQTL) for 103 of these hypoxia response genes. In a University of Illinois SCD cohort the A allele of a MAPK8 eQTL, rs10857560, was associated with pre-capillary pulmonary hypertension defined as mean pulmonary artery pressure ≥25 and pulmonary capillary wedge pressure ≤15 mm Hg at right heart catheterization (allele frequency=0.66; OR=13.8, P=0.00036, n=238). This association was confirmed in an independent Walk-PHaSST cohort (allele frequency=0.65; OR=11.3, P=0.0025, n=519). The homozygous AA genotype of rs10857560 was associated with decreased MAPK8 expression and present in all 14 identified pre-capillary pulmonary hypertension cases among the combined 757 patients. Conclusions Our study demonstrates a prominent hypoxic transcription component in SCD and a MAPK8 eQTL associated with pre-capillary pulmonary hypertension. PMID:24515990

MeQTL analysis of childhood obesity links epigenetics with a risk SNP rs17782313 near MC4R from meta-analysis.

PubMed

Tang, Yuping; Jin, Bo; Zhou, Lingling; Lu, Weifeng

2017-01-10

Earlier GWAS has identified that rs17782313 near MC4R was associated with obesity. However, subsequent studies showed conflicting results, especially among childhood. Besides, the mechanisms underlying the association between rs17782313 and childhood obesity remain largely unexplored, and genetic and epigenetic may interact and together affect the development of childhood obesity. We conducted a comprehensive meta-analysis to assess the association between rs17782313 and childhood obesity. MeQTL and eQTL analysis was applied to explore the effect of rs17782313 on DNA methylation and MC4R expression. We found that rs17782313 near MC4R was associated with increased childhood obesity risk and BMI z-score in several inheritable models (P < 0.05). Additionally, the similar trend was observed among subgroups of Asians, Caucasian. Furthermore, meQTL and eQTL analysis indicated that individuals carrying rs17782313 TT genotype were significantly associated with increased methylation level of cg10097150 located in MC4R promoter and decreased expression of MC4R than those with CT/CC genotype (P = 1.7 × 10-4 and P = 1.9 × 10-3 respectively). Our results strongly confirmed that rs17782313 was associated with increased risk of childhood obesity. Furthermore, rs17782313 T allele was correlated with promoter hypermethylation and decreased expression of MC4R, thus involved in the development of childhood obesity.

PExFInS: An Integrative Post-GWAS Explorer for Functional Indels and SNPs

PubMed Central

Cheng, Zhongshan; Chu, Hin; Fan, Yanhui; Li, Cun; Song, You-Qiang; Zhou, Jie; Yuen, Kwok-Yung

2015-01-01

Expression quantitative trait loci (eQTLs) mapping and linkage disequilibrium (LD) analysis have been widely employed to interpret findings of genome-wide association studies (GWAS). With the availability of deep sequencing data of 423 lymphoblastoid cell lines (LCLs) from six global populations and the microarray expression data, we performed eQTL analysis, identified more than 228 K SNP cis-eQTLs and 21 K indel cis-eQTLs and generated a LCL cis-eQTL database. We demonstrate that the percentages of population-shared and population-specific cis-eQTLs are comparable; while indel cis-eQTLs in the population-specific subsection make more contribution to gene expression variations than those in the population-shared subsection. We found cis-eQTLs, especially the population-shared cis-eQTLs are significantly enriched toward transcription start site. Moreover, the National Human Genome Research Institute cataloged GWAS SNPs are enriched for LCL cis-eQTLs. Specifically, 32.8% GWAS SNPs are LCL cis-eQTLs, among which 12.5% can be tagged by indel cis-eQTLs, suggesting the fundamental contribution of indel cis-eQTLs to GWAS association signals. To search for functional indels and SNPs tagging GWAS SNPs, a pipeline Post-GWAS Explorer for Functional Indels and SNPs (PExFInS) has been developed, integrating LD analysis, functional annotation from public databases, cis-eQTL mapping with our LCL cis-eQTL database and other published cis-eQTL datasets. PMID:26612672

Human population-specific gene expression and transcriptional network modification with polymorphic transposable elements

PubMed Central

Wang, Lu; Mariño-Ramírez, Leonardo

2017-01-01

Abstract Transposable element (TE) derived sequences are known to contribute to the regulation of the human genome. The majority of known TE-derived regulatory sequences correspond to relatively ancient insertions, which are fixed across human populations. The extent to which human genetic variation caused by recent TE activity leads to regulatory polymorphisms among populations has yet to be thoroughly explored. In this study, we searched for associations between polymorphic TE (polyTE) loci and human gene expression levels using an expression quantitative trait loci (eQTL) approach. We compared locus-specific polyTE insertion genotypes to B cell gene expression levels among 445 individuals from 5 human populations. Numerous human polyTE loci correspond to both cis and trans eQTL, and their regulatory effects are directly related to cell type-specific function in the immune system. PolyTE loci are associated with differences in expression between European and African population groups, and a single polyTE loci is indirectly associated with the expression of numerous genes via the regulation of the B cell-specific transcription factor PAX5. The polyTE-gene expression associations we found indicate that human TE genetic variation can have important phenotypic consequences. Our results reveal that TE-eQTL are involved in population-specific gene regulation as well as transcriptional network modification. PMID:27998931

Common Genetic Polymorphisms Influence Blood Biomarker Measurements in COPD.

PubMed

Sun, Wei; Kechris, Katerina; Jacobson, Sean; Drummond, M Bradley; Hawkins, Gregory A; Yang, Jenny; Chen, Ting-Huei; Quibrera, Pedro Miguel; Anderson, Wayne; Barr, R Graham; Basta, Patricia V; Bleecker, Eugene R; Beaty, Terri; Casaburi, Richard; Castaldi, Peter; Cho, Michael H; Comellas, Alejandro; Crapo, James D; Criner, Gerard; Demeo, Dawn; Christenson, Stephanie A; Couper, David J; Curtis, Jeffrey L; Doerschuk, Claire M; Freeman, Christine M; Gouskova, Natalia A; Han, MeiLan K; Hanania, Nicola A; Hansel, Nadia N; Hersh, Craig P; Hoffman, Eric A; Kaner, Robert J; Kanner, Richard E; Kleerup, Eric C; Lutz, Sharon; Martinez, Fernando J; Meyers, Deborah A; Peters, Stephen P; Regan, Elizabeth A; Rennard, Stephen I; Scholand, Mary Beth; Silverman, Edwin K; Woodruff, Prescott G; O'Neal, Wanda K; Bowler, Russell P

2016-08-01

Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p < 8 X 10-10) pQTLs in 38 (43%) of blood proteins tested. Most pQTL SNPs were novel with low overlap to eQTL SNPs. The pQTL SNPs explained >10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10-392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In conclusion, given the frequency of highly significant local pQTLs, the large amount of variance potentially explained by pQTL, and the differences observed between pQTLs and eQTLs SNPs, we recommend that protein biomarker-disease association studies take into account the potential effect of common local SNPs and that pQTLs be integrated along with eQTLs to uncover disease mechanisms. Large-scale blood biomarker studies would also benefit from close attention to the ABO blood group.

Common Genetic Polymorphisms Influence Blood Biomarker Measurements in COPD

PubMed Central

Drummond, M. Bradley; Hawkins, Gregory A.; Yang, Jenny; Chen, Ting-huei; Quibrera, Pedro Miguel; Anderson, Wayne; Barr, R. Graham; Bleecker, Eugene R.; Beaty, Terri; Casaburi, Richard; Castaldi, Peter; Cho, Michael H.; Comellas, Alejandro; Crapo, James D.; Criner, Gerard; Demeo, Dawn; Christenson, Stephanie A.; Couper, David J.; Doerschuk, Claire M.; Freeman, Christine M.; Gouskova, Natalia A.; Han, MeiLan K.; Hanania, Nicola A.; Hansel, Nadia N.; Hersh, Craig P.; Hoffman, Eric A.; Kaner, Robert J.; Kanner, Richard E.; Kleerup, Eric C.; Lutz, Sharon; Martinez, Fernando J.; Meyers, Deborah A.; Peters, Stephen P.; Regan, Elizabeth A.; Rennard, Stephen I.; Scholand, Mary Beth; Silverman, Edwin K.; Woodruff, Prescott G.; O’Neal, Wanda K.; Bowler, Russell P.

2016-01-01

Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p < 8 X 10−10) pQTLs in 38 (43%) of blood proteins tested. Most pQTL SNPs were novel with low overlap to eQTL SNPs. The pQTL SNPs explained >10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10−392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In conclusion, given the frequency of highly significant local pQTLs, the large amount of variance potentially explained by pQTL, and the differences observed between pQTLs and eQTLs SNPs, we recommend that protein biomarker-disease association studies take into account the potential effect of common local SNPs and that pQTLs be integrated along with eQTLs to uncover disease mechanisms. Large-scale blood biomarker studies would also benefit from close attention to the ABO blood group. PMID:27532455

Identification of eQTLs for Hepatic Xbp1s and Socs3 Gene Expression in Mice Fed a High-Fat, High-Caloric Diet

PubMed Central

Pasricha, Sarina; Kenney-Hunt, Jane; Anderson, Kristy; Jafari, Nadereh; Hall, Rabea A.; Lammert, Frank; Cheverud, James; Green, Richard M.

2015-01-01

Nonalcoholic fatty liver disease (NAFLD) is a highly prevalent form of human hepatic disease and feeding mice a high-fat, high-caloric (HFHC) diet is a standard model of NAFLD. To better understand the genetic basis of NAFLD, we conducted an expression quantitative trait locus (eQTL) analysis of mice fed a HFHC diet. Two-hundred sixty-five (A/J × C57BL/6J) F2 male mice were fed a HFHC diet for 8 wk. eQTL analysis was utilized to identify genomic regions that regulate hepatic gene expression of Xbp1s and Socs3. We identified two overlapping loci for Xbp1s and Socs3 on Chr 1 (164.0–185.4 Mb and 174.4–190.5 Mb, respectively) and Chr 11 (41.1–73.1 Mb and 44.0–68.6 Mb, respectively), and an additional locus for Socs3 on Chr 12 (109.9–117.4 Mb). C57BL/6J-Chr 11A/J/ NaJ mice fed a HFHC diet manifested the A/J phenotype of increased Xbp1s and Socs3 gene expression (P < 0.05), whereas C57BL/6J-Chr 1A/J/ NaJ mice retained the C57BL/6J phenotype. In addition, we replicated the eQTLs on Chr 1 and Chr 12 (LOD scores ≥3.5) using mice from the BXD murine reference panel challenged with CCl4 to induce chronic liver injury and fibrosis. We have identified overlapping eQTLs for Xbp1 and Socs3 on Chr 1 and Chr 11, and consomic mice confirmed that replacing the C57BL/6J Chr 11 with the A/J Chr 11 resulted in an A/J phenotype for Xbp1 and Socs3 gene expression. Identification of the genes for these eQTLs will lead to a better understanding of the genetic factors responsible for NAFLD and potentially other hepatic diseases. PMID:25617409

Integration of QTL and bioinformatic tools to identify candidate genes for triglycerides in mice[S

PubMed Central

Leduc, Magalie S.; Hageman, Rachael S.; Verdugo, Ricardo A.; Tsaih, Shirng-Wern; Walsh, Kenneth; Churchill, Gary A.; Paigen, Beverly

2011-01-01

To identify genetic loci influencing lipid levels, we performed quantitative trait loci (QTL) analysis between inbred mouse strains MRL/MpJ and SM/J, measuring triglyceride levels at 8 weeks of age in F2 mice fed a chow diet. We identified one significant QTL on chromosome (Chr) 15 and three suggestive QTL on Chrs 2, 7, and 17. We also carried out microarray analysis on the livers of parental strains of 282 F2 mice and used these data to find cis-regulated expression QTL. We then narrowed the list of candidate genes under significant QTL using a “toolbox” of bioinformatic resources, including haplotype analysis; parental strain comparison for gene expression differences and nonsynonymous coding single nucleotide polymorphisms (SNP); cis-regulated eQTL in livers of F2 mice; correlation between gene expression and phenotype; and conditioning of expression on the phenotype. We suggest Slc25a7 as a candidate gene for the Chr 7 QTL and, based on expression differences, five genes (Polr3 h, Cyp2d22, Cyp2d26, Tspo, and Ttll12) as candidate genes for Chr 15 QTL. This study shows how bioinformatics can be used effectively to reduce candidate gene lists for QTL related to complex traits. PMID:21622629

An xQTL map integrates the genetic architecture of the human brain's transcriptome and epigenome.

PubMed

Ng, Bernard; White, Charles C; Klein, Hans-Ulrich; Sieberts, Solveig K; McCabe, Cristin; Patrick, Ellis; Xu, Jishu; Yu, Lei; Gaiteri, Chris; Bennett, David A; Mostafavi, Sara; De Jager, Philip L

2017-10-01

We report a multi-omic resource generated by applying quantitative trait locus (xQTL) analyses to RNA sequence, DNA methylation and histone acetylation data from the dorsolateral prefrontal cortex of 411 older adults who have all three data types. We identify SNPs significantly associated with gene expression, DNA methylation and histone modification levels. Many of these SNPs influence multiple molecular features, and we demonstrate that SNP effects on RNA expression are fully mediated by epigenetic features in 9% of these loci. Further, we illustrate the utility of our new resource, xQTL Serve, by using it to prioritize the cell type(s) most affected by an xQTL. We also reanalyze published genome wide association studies using an xQTL-weighted analysis approach and identify 18 new schizophrenia and 2 new bipolar susceptibility variants, which is more than double the number of loci that can be discovered with a larger blood-based expression eQTL resource.

Quantitative Trait Loci for Cold Tolerance of Rice Recombinant Inbred Lines in Low Temperature Environments

PubMed Central

Jiang, Wenzhu; Jin, Yong-Mei; Lee, Joohyun; Lee, Kang-Ie; Piao, Rihua; Han, Longzhi; Shin, Jin-Chul; Jin, Rong-De; Cao, Tiehua; Pan, Hong-Yu; Du, Xinglin; Koh, Hee-Jong

2011-01-01

Low temperature is one of the major environmental stresses in rice cultivation in high-altitude and high-latitude regions. In this study, we cultivated a set of recombinant inbred lines (RIL) derived from Dasanbyeo (indica) / TR22183 (japonica) crosses in Yanji (high-latitude area), Kunming (high-altitude area), Chuncheon (cold water irrigation) and Suwon (normal) to evaluate the main effects of quantitative trait loci (QTL) and epistatic QTL (E-QTL) with regard to their interactions with environments for coldrelated traits. Six QTLs for spikelet fertility (SF) were identified in three cold treatment locations. Among them, four QTLs on chromosomes 2, 7, 8, and 10 were validated by several near isogenic lines (NILs) under cold treatment in Chuncheon. A total of 57 QTLs and 76 E-QTLs for nine cold-related traits were identified as distributing on all 12 chromosomes; among them, 19 QTLs and E-QTLs showed significant interactions of QTLs and environments (QEIs). The total phenotypic variation explained by each trait ranged from 13.2 to 29.1% in QTLs, 10.6 to 29.0% in EQTLs, 2.2 to 8.8% in QEIs and 1.0% to 7.7% in E-QTL × environment interactions (E-QEIs). These results demonstrate that epistatic effects and QEIs are important properties of QTL parameters for cold tolerance at the reproductive stage. In order to develop cold tolerant varieties adaptable to wide-ranges of cold stress, a strategy facilitating marker-assisted selection (MAS) is being adopted to accumulate QTLs identified from different environments. PMID:22080374

xQTL workbench: a scalable web environment for multi-level QTL analysis.

PubMed

Arends, Danny; van der Velde, K Joeri; Prins, Pjotr; Broman, Karl W; Möller, Steffen; Jansen, Ritsert C; Swertz, Morris A

2012-04-01

xQTL workbench is a scalable web platform for the mapping of quantitative trait loci (QTLs) at multiple levels: for example gene expression (eQTL), protein abundance (pQTL), metabolite abundance (mQTL) and phenotype (phQTL) data. Popular QTL mapping methods for model organism and human populations are accessible via the web user interface. Large calculations scale easily on to multi-core computers, clusters and Cloud. All data involved can be uploaded and queried online: markers, genotypes, microarrays, NGS, LC-MS, GC-MS, NMR, etc. When new data types come available, xQTL workbench is quickly customized using the Molgenis software generator. xQTL workbench runs on all common platforms, including Linux, Mac OS X and Windows. An online demo system, installation guide, tutorials, software and source code are available under the LGPL3 license from http://www.xqtl.org. m.a.swertz@rug.nl.

xQTL workbench: a scalable web environment for multi-level QTL analysis

PubMed Central

Arends, Danny; van der Velde, K. Joeri; Prins, Pjotr; Broman, Karl W.; Möller, Steffen; Jansen, Ritsert C.; Swertz, Morris A.

2012-01-01

Summary: xQTL workbench is a scalable web platform for the mapping of quantitative trait loci (QTLs) at multiple levels: for example gene expression (eQTL), protein abundance (pQTL), metabolite abundance (mQTL) and phenotype (phQTL) data. Popular QTL mapping methods for model organism and human populations are accessible via the web user interface. Large calculations scale easily on to multi-core computers, clusters and Cloud. All data involved can be uploaded and queried online: markers, genotypes, microarrays, NGS, LC-MS, GC-MS, NMR, etc. When new data types come available, xQTL workbench is quickly customized using the Molgenis software generator. Availability: xQTL workbench runs on all common platforms, including Linux, Mac OS X and Windows. An online demo system, installation guide, tutorials, software and source code are available under the LGPL3 license from http://www.xqtl.org. Contact: m.a.swertz@rug.nl PMID:22308096

Identification, Replication, and Functional Fine-Mapping of Expression Quantitative Trait Loci in Primary Human Liver Tissue

PubMed Central

Stanaway, Ian B.; Gamazon, Eric R.; Smith, Joshua D.; Mirkov, Snezana; Ramirez, Jacqueline; Liu, Wanqing; Lin, Yvonne S.; Moloney, Cliona; Aldred, Shelly Force; Trinklein, Nathan D.; Schuetz, Erin; Nickerson, Deborah A.; Thummel, Ken E.; Rieder, Mark J.; Rettie, Allan E.; Ratain, Mark J.; Cox, Nancy J.; Brown, Christopher D.

2011-01-01

The discovery of expression quantitative trait loci (“eQTLs”) can help to unravel genetic contributions to complex traits. We identified genetic determinants of human liver gene expression variation using two independent collections of primary tissue profiled with Agilent (n = 206) and Illumina (n = 60) expression arrays and Illumina SNP genotyping (550K), and we also incorporated data from a published study (n = 266). We found that ∼30% of SNP-expression correlations in one study failed to replicate in either of the others, even at thresholds yielding high reproducibility in simulations, and we quantified numerous factors affecting reproducibility. Our data suggest that drug exposure, clinical descriptors, and unknown factors associated with tissue ascertainment and analysis have substantial effects on gene expression and that controlling for hidden confounding variables significantly increases replication rate. Furthermore, we found that reproducible eQTL SNPs were heavily enriched near gene starts and ends, and subsequently resequenced the promoters and 3′UTRs for 14 genes and tested the identified haplotypes using luciferase assays. For three genes, significant haplotype-specific in vitro functional differences correlated directly with expression levels, suggesting that many bona fide eQTLs result from functional variants that can be mechanistically isolated in a high-throughput fashion. Finally, given our study design, we were able to discover and validate hundreds of liver eQTLs. Many of these relate directly to complex traits for which liver-specific analyses are likely to be relevant, and we identified dozens of potential connections with disease-associated loci. These included previously characterized eQTL contributors to diabetes, drug response, and lipid levels, and they suggest novel candidates such as a role for NOD2 expression in leprosy risk and C2orf43 in prostate cancer. In general, the work presented here will be valuable for future efforts to precisely identify and functionally characterize genetic contributions to a variety of complex traits. PMID:21637794

Adrenal cortex expression quantitative trait loci in a German Holstein × Charolais cross.

PubMed

Brand, Bodo; Scheinhardt, Markus O; Friedrich, Juliane; Zimmer, Daisy; Reinsch, Norbert; Ponsuksili, Siriluck; Schwerin, Manfred; Ziegler, Andreas

2016-10-06

The importance of the adrenal gland in regard to lactation and reproduction in cattle has been recognized early. Caused by interest in animal welfare and the impact of stress on economically important traits in farm animals the adrenal gland and its function within the stress response is of increasing interest. However, the molecular mechanisms and pathways involved in stress-related effects on economically important traits in farm animals are not fully understood. Gene expression is an important mechanism underlying complex traits, and genetic variants affecting the transcript abundance are thought to influence the manifestation of an expressed phenotype. We therefore investigated the genetic background of adrenocortical gene expression by applying an adaptive linear rank test to identify genome-wide expression quantitative trait loci (eQTL) for adrenal cortex transcripts in cattle. A total of 10,986 adrenal cortex transcripts and 37,204 single nucleotide polymorphisms (SNPs) were analysed in 145 F2 cows of a Charolais × German Holstein cross. We identified 505 SNPs that were associated with the abundance of 129 transcripts, comprising 482 cis effects and 17 trans effects. These SNPs were located on all chromosomes but X, 16, 24 and 28. Associated genes are mainly involved in molecular and cellular functions comprising free radical scavenging, cellular compromise, cell morphology and lipid metabolism, including genes such as CYP27A1 and LHCGR that have been shown to affect economically important traits in cattle. In this study we showed that adrenocortical eQTL affect the expression of genes known to contribute to the phenotypic manifestation in cattle. Furthermore, some of the identified genes and related molecular pathways were previously shown to contribute to the phenotypic variation of behaviour, temperament and growth at the onset of puberty in the same population investigated here. We conclude that eQTL analysis appears to be a useful approach providing insight into the molecular and genetic background of complex traits in cattle and will help to understand molecular networks involved.

WormQTLHD—a web database for linking human disease to natural variation data in C. elegans

PubMed Central

van der Velde, K. Joeri; de Haan, Mark; Zych, Konrad; Arends, Danny; Snoek, L. Basten; Kammenga, Jan E.; Jansen, Ritsert C.; Swertz, Morris A.; Li, Yang

2014-01-01

Interactions between proteins are highly conserved across species. As a result, the molecular basis of multiple diseases affecting humans can be studied in model organisms that offer many alternative experimental opportunities. One such organism—Caenorhabditis elegans—has been used to produce much molecular quantitative genetics and systems biology data over the past decade. We present WormQTLHD (Human Disease), a database that quantitatively and systematically links expression Quantitative Trait Loci (eQTL) findings in C. elegans to gene–disease associations in man. WormQTLHD, available online at http://www.wormqtl-hd.org, is a user-friendly set of tools to reveal functionally coherent, evolutionary conserved gene networks. These can be used to predict novel gene-to-gene associations and the functions of genes underlying the disease of interest. We created a new database that links C. elegans eQTL data sets to human diseases (34 337 gene–disease associations from OMIM, DGA, GWAS Central and NHGRI GWAS Catalogue) based on overlapping sets of orthologous genes associated to phenotypes in these two species. We utilized QTL results, high-throughput molecular phenotypes, classical phenotypes and genotype data covering different developmental stages and environments from WormQTL database. All software is available as open source, built on MOLGENIS and xQTL workbench. PMID:24217915

Hypothalamic transcriptomes of 99 mouse strains reveal trans eQTL hotspots, splicing QTLs and novel non-coding genes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hasin-Brumshtein, Yehudit; Khan, Arshad H.; Hormozdiari, Farhad

2016-09-13

Previous studies had shown that the integration of genome wide expression profiles, in metabolic tissues, with genetic and phenotypic variance, provided valuable insight into the underlying molecular mechanisms. We used RNA-Seq to characterize hypothalamic transcriptome in 99 inbred strains of mice from the Hybrid Mouse Diversity Panel (HMDP), a reference resource population for cardiovascular and metabolic traits. We report numerous novel transcripts supported by proteomic analyses, as well as novel non coding RNAs. High resolution genetic mapping of transcript levels in HMDP, reveals bothlocalandtransexpression Quantitative Trait Loci (eQTLs) demonstrating 2transeQTL 'hotspots' associated with expression of hundreds of genes. We alsomore » report thousands of alternative splicing events regulated by genetic variants. Finally, comparison with about 150 metabolic and cardiovascular traits revealed many highly significant associations. Our data provide a rich resource for understanding the many physiologic functions mediated by the hypothalamus and their genetic regulation.« less

Mediation Analysis Demonstrates That Trans-eQTLs Are Often Explained by Cis-Mediation: A Genome-Wide Analysis among 1,800 South Asians

PubMed Central

Pierce, Brandon L.; Tong, Lin; Chen, Lin S.; Rahaman, Ronald; Argos, Maria; Jasmine, Farzana; Roy, Shantanu; Paul-Brutus, Rachelle; Westra, Harm-Jan; Franke, Lude; Esko, Tonu; Zaman, Rakibuz; Islam, Tariqul; Rahman, Mahfuzar; Baron, John A.; Kibriya, Muhammad G.; Ahsan, Habibul

2014-01-01

A large fraction of human genes are regulated by genetic variation near the transcribed sequence (cis-eQTL, expression quantitative trait locus), and many cis-eQTLs have implications for human disease. Less is known regarding the effects of genetic variation on expression of distant genes (trans-eQTLs) and their biological mechanisms. In this work, we use genome-wide data on SNPs and array-based expression measures from mononuclear cells obtained from a population-based cohort of 1,799 Bangladeshi individuals to characterize cis- and trans-eQTLs and determine if observed trans-eQTL associations are mediated by expression of transcripts in cis with the SNPs showing trans-association, using Sobel tests of mediation. We observed 434 independent trans-eQTL associations at a false-discovery rate of 0.05, and 189 of these trans-eQTLs were also cis-eQTLs (enrichment P<0.0001). Among these 189 trans-eQTL associations, 39 were significantly attenuated after adjusting for a cis-mediator based on Sobel P<10-5. We attempted to replicate 21 of these mediation signals in two European cohorts, and while only 7 trans-eQTL associations were present in one or both cohorts, 6 showed evidence of cis-mediation. Analyses of simulated data show that complete mediation will be observed as partial mediation in the presence of mediator measurement error or imperfect LD between measured and causal variants. Our data demonstrates that trans-associations can become significantly stronger or switch directions after adjusting for a potential mediator. Using simulated data, we demonstrate that this phenomenon is expected in the presence of strong cis-trans confounding and when the measured cis-transcript is correlated with the true (unmeasured) mediator. In conclusion, by applying mediation analysis to eQTL data, we show that a substantial fraction of observed trans-eQTL associations can be explained by cis-mediation. Future studies should focus on understanding the mechanisms underlying widespread cis-mediation and their relevance to disease biology, as well as using mediation analysis to improve eQTL discovery. PMID:25474530

Identifying cis-mediators for trans-eQTLs across many human tissues using genomic mediation analysis.

PubMed

Yang, Fan; Wang, Jiebiao; Pierce, Brandon L; Chen, Lin S

2017-11-01

The impact of inherited genetic variation on gene expression in humans is well-established. The majority of known expression quantitative trait loci (eQTLs) impact expression of local genes ( cis -eQTLs). More research is needed to identify effects of genetic variation on distant genes ( trans -eQTLs) and understand their biological mechanisms. One common trans -eQTLs mechanism is "mediation" by a local ( cis ) transcript. Thus, mediation analysis can be applied to genome-wide SNP and expression data in order to identify transcripts that are " cis -mediators" of trans -eQTLs, including those " cis -hubs" involved in regulation of many trans -genes. Identifying such mediators helps us understand regulatory networks and suggests biological mechanisms underlying trans -eQTLs, both of which are relevant for understanding susceptibility to complex diseases. The multitissue expression data from the Genotype-Tissue Expression (GTEx) program provides a unique opportunity to study cis -mediation across human tissue types. However, the presence of complex hidden confounding effects in biological systems can make mediation analyses challenging and prone to confounding bias, particularly when conducted among diverse samples. To address this problem, we propose a new method: Genomic Mediation analysis with Adaptive Confounding adjustment (GMAC). It enables the search of a very large pool of variables, and adaptively selects potential confounding variables for each mediation test. Analyses of simulated data and GTEx data demonstrate that the adaptive selection of confounders by GMAC improves the power and precision of mediation analysis. Application of GMAC to GTEx data provides new insights into the observed patterns of cis -hubs and trans -eQTL regulation across tissue types. © 2017 Yang et al.; Published by Cold Spring Harbor Laboratory Press.

The structure of a gene co-expression network reveals biological functions underlying eQTLs.

PubMed

Villa-Vialaneix, Nathalie; Liaubet, Laurence; Laurent, Thibault; Cherel, Pierre; Gamot, Adrien; SanCristobal, Magali

2013-01-01

What are the commonalities between genes, whose expression level is partially controlled by eQTL, especially with regard to biological functions? Moreover, how are these genes related to a phenotype of interest? These issues are particularly difficult to address when the genome annotation is incomplete, as is the case for mammalian species. Moreover, the direct link between gene expression and a phenotype of interest may be weak, and thus difficult to handle. In this framework, the use of a co-expression network has proven useful: it is a robust approach for modeling a complex system of genetic regulations, and to infer knowledge for yet unknown genes. In this article, a case study was conducted with a mammalian species. It showed that the use of a co-expression network based on partial correlation, combined with a relevant clustering of nodes, leads to an enrichment of biological functions of around 83%. Moreover, the use of a spatial statistics approach allowed us to superimpose additional information related to a phenotype; this lead to highlighting specific genes or gene clusters that are related to the network structure and the phenotype. Three main results are worth noting: first, key genes were highlighted as a potential focus for forthcoming biological experiments; second, a set of biological functions, which support a list of genes under partial eQTL control, was set up by an overview of the global structure of the gene expression network; third, pH was found correlated with gene clusters, and then with related biological functions, as a result of a spatial analysis of the network topology.

Use of eQTL Analysis for the Discovery of Target Genes Identified by GWAS

DTIC Science & Technology

2013-04-01

the biologic pathways affected by these inherited factors, and ultimately to identify targets for disease prediction, risk stratification and...quality using an Agilent chip technology. Cases having a RIN number of 7.0 or greater were considered good quality. Once completed, the optimum set of...AD_________________ Award Number: W81XWH-11-1-0261 TITLE: Use of eQTL Analysis for the Discovery of

Use of eQTL Analysis for the Discovery of Target Genes Identified by GWAS

DTIC Science & Technology

2014-04-01

technology. Cases having a RIN number of 7.0 or greater were considered good quality. Once completed, the optimum set of 500 samples were then selected for...AD_________________ Award Number: W81XWH-11-1-0261 TITLE: Use of eQTL Analysis for the Discovery...Distribution Unlimited The views, opinions and/or findings contained in this report are those of the author(s) and

Genetic regulation of bone metabolism in the chicken: similarities and differences to Mammalian systems.

PubMed

Johnsson, Martin; Jonsson, Kenneth B; Andersson, Leif; Jensen, Per; Wright, Dominic

2015-05-01

Birds have a unique bone physiology, due to the demands placed on them through egg production. In particular their medullary bone serves as a source of calcium for eggshell production during lay and undergoes continuous and rapid remodelling. We take advantage of the fact that bone traits have diverged massively during chicken domestication to map the genetic basis of bone metabolism in the chicken. We performed a quantitative trait locus (QTL) and expression QTL (eQTL) mapping study in an advanced intercross based on Red Junglefowl (the wild progenitor of the modern domestic chicken) and White Leghorn chickens. We measured femoral bone traits in 456 chickens by peripheral computerised tomography and femoral gene expression in a subset of 125 females from the cross with microarrays. This resulted in 25 loci for female bone traits, 26 loci for male bone traits and 6318 local eQTL loci. We then overlapped bone and gene expression loci, before checking for an association between gene expression and trait values to identify candidate quantitative trait genes for bone traits. A handful of our candidates have been previously associated with bone traits in mice, but our results also implicate unexpected and largely unknown genes in bone metabolism. In summary, by utilising the unique bone metabolism of an avian species, we have identified a number of candidate genes affecting bone allocation and metabolism. These findings can have ramifications not only for the understanding of bone metabolism genetics in general, but could also be used as a potential model for osteoporosis as well as revealing new aspects of vertebrate bone regulation or features that distinguish avian and mammalian bone.

A genome-wide survey of CD4+ lymphocyte regulatory genetic variants identifies novel asthma genes

PubMed Central

Sharma, Sunita; Zhou, Xiaobo; Thibault, Derek M.; Himes, Blanca E.; Liu, Andy; Szefler, Stanley J.; Strunk, Robert; Castro, Mario; Hansel, Nadia N.; Diette, Gregory B.; Vonakis, Becky M.; Adkinson, N. Franklin; Avila, Lydiana; Soto-Quiros, Manuel; Barraza-Villareal, Albino; Lemanske, Robert F.; Solway, Julian; Krishnan, Jerry; White, Steven R.; Cheadle, Chris; Berger, Alan E.; Fan, Jinshui; Boorgula, Meher Preethi; Nicolae, Dan; Gilliland, Frank; Barnes, Kathleen; London, Stephanie J.; Martinez, Fernando; Ober, Carole; Celedón, Juan C.; Carey, Vincent J.; Weiss, Scott T.; Raby, Benjamin A.

2014-01-01

Background Genome-wide association studies have yet to identify the majority of genetic variants involved in asthma. We hypothesized that expression quantitative trait locus (eQTL) mapping can identify novel asthma genes by enabling prioritization of putative functional variants for association testing. Objective We evaluated 6,706 cis-acting expression-associated variants (eSNP) identified through a genome-wide eQTL survey of CD4+ lymphocytes for association with asthma. Methods eSNP were tested for association with asthma in 359 asthma cases and 846 controls from the Childhood Asthma Management Program, with verification using family-based testing. Significant associations were tested for replication in 579 parent-child trios with asthma from Costa Rica. Further functional validation was performed by Formaldehyde Assisted Isolation of Regulatory Elements (FAIRE)-qPCR and Chromatin-Immunoprecipitation (ChIP)-PCR in lung derived epithelial cell lines (Beas-2B and A549) and Jurkat cells, a leukemia cell line derived from T lymphocytes. Results Cis-acting eSNP demonstrated associations with asthma in both cohorts. We confirmed the previously-reported association of ORMDL3/GSDMB variants with asthma (combined p=2.9 × 108). Reproducible associations were also observed for eSNP in three additional genes: FADS2 (p=0.002), NAGA (p=0.0002), and F13A1 (p=0.0001). We subsequently demonstrated that FADS2 mRNA is increased in CD4+ lymphocytes in asthmatics, and that the associated eSNPs reside within DNA segments with histone modifications that denote open chromatin status and confer enhancer activity. Conclusions Our results demonstrate the utility of eQTL mapping in the identification of novel asthma genes, and provide evidence for the importance of FADS2, NAGA, and F13A1 in the pathogenesis of asthma. PMID:24934276

Leveraging lung tissue transcriptome to uncover candidate causal genes in COPD genetic associations.

PubMed

Lamontagne, Maxime; Bérubé, Jean-Christophe; Obeidat, Ma'en; Cho, Michael H; Hobbs, Brian D; Sakornsakolpat, Phuwanat; de Jong, Kim; Boezen, H Marike; Nickle, David; Hao, Ke; Timens, Wim; van den Berge, Maarten; Joubert, Philippe; Laviolette, Michel; Sin, Don D; Paré, Peter D; Bossé, Yohan

2018-05-15

Causal genes of chronic obstructive pulmonary disease (COPD) remain elusive. The current study aims at integrating genome-wide association studies (GWAS) and lung expression quantitative trait loci (eQTL) data to map COPD candidate causal genes and gain biological insights into the recently discovered COPD susceptibility loci. Two complementary genomic datasets on COPD were studied. First, the lung eQTL dataset which included whole-genome gene expression and genotyping data from 1038 individuals. Second, the largest COPD GWAS to date from the International COPD Genetics Consortium (ICGC) with 13 710 cases and 38 062 controls. Methods that integrated GWAS with eQTL signals including transcriptome-wide association study (TWAS), colocalization and Mendelian randomization-based (SMR) approaches were used to map causality genes, i.e. genes with the strongest evidence of being the functional effector at specific loci. These methods were applied at the genome-wide level and at COPD risk loci derived from the GWAS literature. Replication was performed using lung data from GTEx. We collated 129 non-overlapping risk loci for COPD from the GWAS literature. At the genome-wide scale, 12 new COPD candidate genes/loci were revealed and six replicated in GTEx including CAMK2A, DMPK, MYO15A, TNFRSF10A, BTN3A2 and TRBV30. In addition, we mapped candidate causal genes for 60 out of the 129 GWAS-nominated loci and 23 of them were replicated in GTEx. Mapping candidate causal genes in lung tissue represents an important contribution to the genetics of COPD, enriches our biological interpretation of GWAS findings, and brings us closer to clinical translation of genetic associations.

Detection of expression quantitative trait Loci in complex mouse crosses: impact and alleviation of data quality and complex population substructure.

PubMed

Iancu, Ovidiu D; Darakjian, Priscila; Kawane, Sunita; Bottomly, Daniel; Hitzemann, Robert; McWeeney, Shannon

2012-01-01

Complex Mus musculus crosses, e.g., heterogeneous stock (HS), provide increased resolution for quantitative trait loci detection. However, increased genetic complexity challenges detection methods, with discordant results due to low data quality or complex genetic architecture. We quantified the impact of theses factors across three mouse crosses and two different detection methods, identifying procedures that greatly improve detection quality. Importantly, HS populations have complex genetic architectures not fully captured by the whole genome kinship matrix, calling for incorporating chromosome specific relatedness information. We analyze three increasingly complex crosses, using gene expression levels as quantitative traits. The three crosses were an F(2) intercross, a HS formed by crossing four inbred strains (HS4), and a HS (HS-CC) derived from the eight lines found in the collaborative cross. Brain (striatum) gene expression and genotype data were obtained using the Illumina platform. We found large disparities between methods, with concordance varying as genetic complexity increased; this problem was more acute for probes with distant regulatory elements (trans). A suite of data filtering steps resulted in substantial increases in reproducibility. Genetic relatedness between samples generated overabundance of detected eQTLs; an adjustment procedure that includes the kinship matrix attenuates this problem. However, we find that relatedness between individuals is not evenly distributed across the genome; information from distinct chromosomes results in relatedness structure different from the whole genome kinship matrix. Shared polymorphisms from distinct chromosomes collectively affect expression levels, confounding eQTL detection. We suggest that considering chromosome specific relatedness can result in improved eQTL detection.

Convergent evidence from systematic analysis of GWAS revealed genetic basis of esophageal cancer.

PubMed

Gao, Xue-Xin; Gao, Lei; Wang, Jiu-Qiang; Qu, Su-Su; Qu, Yue; Sun, Hong-Lei; Liu, Si-Dang; Shang, Ying-Li

2016-07-12

Recent genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with risk of esophageal cancer (EC). However, investigation of genetic basis from the perspective of systematic biology and integrative genomics remains scarce.In this study, we explored genetic basis of EC based on GWAS data and implemented a series of bioinformatics methods including functional annotation, expression quantitative trait loci (eQTL) analysis, pathway enrichment analysis and pathway grouped network analysis.Two hundred and thirteen risk SNPs were identified, in which 44 SNPs were found to have significantly differential gene expression in esophageal tissues by eQTL analysis. By pathway enrichment analysis, 170 risk genes mapped by risk SNPs were enriched into 38 significant GO terms and 17 significant KEGG pathways, which were significantly grouped into 9 sub-networks by pathway grouped network analysis. The 9 groups of interconnected pathways were mainly involved with muscle cell proliferation, cellular response to interleukin-6, cell adhesion molecules, and ethanol oxidation, which might participate in the development of EC.Our findings provide genetic evidence and new insight for exploring the molecular mechanisms of EC.

Bayesian test for colocalisation between pairs of genetic association studies using summary statistics.

PubMed

Giambartolomei, Claudia; Vukcevic, Damjan; Schadt, Eric E; Franke, Lude; Hingorani, Aroon D; Wallace, Chris; Plagnol, Vincent

2014-05-01

Genetic association studies, in particular the genome-wide association study (GWAS) design, have provided a wealth of novel insights into the aetiology of a wide range of human diseases and traits, in particular cardiovascular diseases and lipid biomarkers. The next challenge consists of understanding the molecular basis of these associations. The integration of multiple association datasets, including gene expression datasets, can contribute to this goal. We have developed a novel statistical methodology to assess whether two association signals are consistent with a shared causal variant. An application is the integration of disease scans with expression quantitative trait locus (eQTL) studies, but any pair of GWAS datasets can be integrated in this framework. We demonstrate the value of the approach by re-analysing a gene expression dataset in 966 liver samples with a published meta-analysis of lipid traits including >100,000 individuals of European ancestry. Combining all lipid biomarkers, our re-analysis supported 26 out of 38 reported colocalisation results with eQTLs and identified 14 new colocalisation results, hence highlighting the value of a formal statistical test. In three cases of reported eQTL-lipid pairs (SYPL2, IFT172, TBKBP1) for which our analysis suggests that the eQTL pattern is not consistent with the lipid association, we identify alternative colocalisation results with SORT1, GCKR, and KPNB1, indicating that these genes are more likely to be causal in these genomic intervals. A key feature of the method is the ability to derive the output statistics from single SNP summary statistics, hence making it possible to perform systematic meta-analysis type comparisons across multiple GWAS datasets (implemented online at http://coloc.cs.ucl.ac.uk/coloc/). Our methodology provides information about candidate causal genes in associated intervals and has direct implications for the understanding of complex diseases as well as the design of drugs to target disease pathways.

Integrative eQTL analysis of tumor and host omics data in individuals with bladder cancer.

PubMed

Pineda, Silvia; Van Steen, Kristel; Malats, Núria

2017-09-01

Integrative analyses of several omics data are emerging. The data are usually generated from the same source material (i.e., tumor sample) representing one level of regulation. However, integrating different regulatory levels (i.e., blood) with those from tumor may also reveal important knowledge about the human genetic architecture. To model this multilevel structure, an integrative-expression quantitative trait loci (eQTL) analysis applying two-stage regression (2SR) was proposed. This approach first regressed tumor gene expression levels with tumor markers and the adjusted residuals from the previous model were then regressed with the germline genotypes measured in blood. Previously, we demonstrated that penalized regression methods in combination with a permutation-based MaxT method (Global-LASSO) is a promising tool to fix some of the challenges that high-throughput omics data analysis imposes. Here, we assessed whether Global-LASSO can also be applied when tumor and blood omics data are integrated. We further compared our strategy with two 2SR-approaches, one using multiple linear regression (2SR-MLR) and other using LASSO (2SR-LASSO). We applied the three models to integrate genomic, epigenomic, and transcriptomic data from tumor tissue with blood germline genotypes from 181 individuals with bladder cancer included in the TCGA Consortium. Global-LASSO provided a larger list of eQTLs than the 2SR methods, identified a previously reported eQTLs in prostate stem cell antigen (PSCA), and provided further clues on the complexity of APBEC3B loci, with a minimal false-positive rate not achieved by 2SR-MLR. It also represents an important contribution for omics integrative analysis because it is easy to apply and adaptable to any type of data. © 2017 WILEY PERIODICALS, INC.

Discovering Single Nucleotide Polymorphisms Regulating Human Gene Expression Using Allele Specific Expression from RNA-seq Data

PubMed Central

Kang, Eun Yong; Martin, Lisa J.; Mangul, Serghei; Isvilanonda, Warin; Zou, Jennifer; Ben-David, Eyal; Han, Buhm; Lusis, Aldons J.; Shifman, Sagiv; Eskin, Eleazar

2016-01-01

The study of the genetics of gene expression is of considerable importance to understanding the nature of common, complex diseases. The most widely applied approach to identifying relationships between genetic variation and gene expression is the expression quantitative trait loci (eQTL) approach. Here, we increased the computational power of eQTL with an alternative and complementary approach based on analyzing allele specific expression (ASE). We designed a novel analytical method to identify cis-acting regulatory variants based on genome sequencing and measurements of ASE from RNA-sequencing (RNA-seq) data. We evaluated the power and resolution of our method using simulated data. We then applied the method to map regulatory variants affecting gene expression in lymphoblastoid cell lines (LCLs) from 77 unrelated northern and western European individuals (CEU), which were part of the HapMap project. A total of 2309 SNPs were identified as being associated with ASE patterns. The SNPs associated with ASE were enriched within promoter regions and were significantly more likely to signal strong evidence for a regulatory role. Finally, among the candidate regulatory SNPs, we identified 108 SNPs that were previously associated with human immune diseases. With further improvements in quantifying ASE from RNA-seq, the application of our method to other datasets is expected to accelerate our understanding of the biological basis of common diseases. PMID:27765809

Quantitative and qualitative stem rust resistance factors in barley are associated with transcriptional suppression of defense regulons.

PubMed

Moscou, Matthew J; Lauter, Nick; Steffenson, Brian; Wise, Roger P

2011-07-01

Stem rust (Puccinia graminis f. sp. tritici; Pgt) is a devastating fungal disease of wheat and barley. Pgt race TTKSK (isolate Ug99) is a serious threat to these Triticeae grain crops because resistance is rare. In barley, the complex Rpg-TTKSK locus on chromosome 5H is presently the only known source of qualitative resistance to this aggressive Pgt race. Segregation for resistance observed on seedlings of the Q21861 × SM89010 (QSM) doubled-haploid (DH) population was found to be predominantly qualitative, with little of the remaining variance explained by loci other than Rpg-TTKSK. In contrast, analysis of adult QSM DH plants infected by field inoculum of Pgt race TTKSK in Njoro, Kenya, revealed several additional quantitative trait loci that contribute to resistance. To molecularly characterize these loci, Barley1 GeneChips were used to measure the expression of 22,792 genes in the QSM population after inoculation with Pgt race TTKSK or mock-inoculation. Comparison of expression Quantitative Trait Loci (eQTL) between treatments revealed an inoculation-dependent expression polymorphism implicating Actin depolymerizing factor3 (within the Rpg-TTKSK locus) as a candidate susceptibility gene. In parallel, we identified a chromosome 2H trans-eQTL hotspot that co-segregates with an enhancer of Rpg-TTKSK-mediated, adult plant resistance discovered through the Njoro field trials. Our genome-wide eQTL studies demonstrate that transcript accumulation of 25% of barley genes is altered following challenge by Pgt race TTKSK, but that few of these genes are regulated by the qualitative Rpg-TTKSK on chromosome 5H. It is instead the chromosome 2H trans-eQTL hotspot that orchestrates the largest inoculation-specific responses, where enhanced resistance is associated with transcriptional suppression of hundreds of genes scattered throughout the genome. Hence, the present study associates the early suppression of genes expressed in this host-pathogen interaction with enhancement of R-gene mediated resistance.

Quantitative and Qualitative Stem Rust Resistance Factors in Barley Are Associated with Transcriptional Suppression of Defense Regulons

PubMed Central

Moscou, Matthew J.; Lauter, Nick; Steffenson, Brian; Wise, Roger P.

2011-01-01

Stem rust (Puccinia graminis f. sp. tritici; Pgt) is a devastating fungal disease of wheat and barley. Pgt race TTKSK (isolate Ug99) is a serious threat to these Triticeae grain crops because resistance is rare. In barley, the complex Rpg-TTKSK locus on chromosome 5H is presently the only known source of qualitative resistance to this aggressive Pgt race. Segregation for resistance observed on seedlings of the Q21861 × SM89010 (QSM) doubled-haploid (DH) population was found to be predominantly qualitative, with little of the remaining variance explained by loci other than Rpg-TTKSK. In contrast, analysis of adult QSM DH plants infected by field inoculum of Pgt race TTKSK in Njoro, Kenya, revealed several additional quantitative trait loci that contribute to resistance. To molecularly characterize these loci, Barley1 GeneChips were used to measure the expression of 22,792 genes in the QSM population after inoculation with Pgt race TTKSK or mock-inoculation. Comparison of expression Quantitative Trait Loci (eQTL) between treatments revealed an inoculation-dependent expression polymorphism implicating Actin depolymerizing factor3 (within the Rpg-TTKSK locus) as a candidate susceptibility gene. In parallel, we identified a chromosome 2H trans-eQTL hotspot that co-segregates with an enhancer of Rpg-TTKSK-mediated, adult plant resistance discovered through the Njoro field trials. Our genome-wide eQTL studies demonstrate that transcript accumulation of 25% of barley genes is altered following challenge by Pgt race TTKSK, but that few of these genes are regulated by the qualitative Rpg-TTKSK on chromosome 5H. It is instead the chromosome 2H trans-eQTL hotspot that orchestrates the largest inoculation-specific responses, where enhanced resistance is associated with transcriptional suppression of hundreds of genes scattered throughout the genome. Hence, the present study associates the early suppression of genes expressed in this host–pathogen interaction with enhancement of R-gene mediated resistance. PMID:21829384

A pilot integrative genomics study of GABA and glutamate neurotransmitter systems in suicide, suicidal behavior, and major depressive disorder.

PubMed

Yin, Honglei; Pantazatos, Spiro P; Galfalvy, Hanga; Huang, Yung-Yu; Rosoklija, Gorazd B; Dwork, Andrew J; Burke, Ainsley; Arango, Victoria; Oquendo, Maria A; Mann, John J

2016-04-01

Gamma-amino butyric acid (GABA) and glutamate are the major inhibitory and excitatory neurotransmitters in the mammalian central nervous system, respectively, and have been associated with suicidal behavior and major depressive disorder (MDD). We examined the relationship between genotype, brain transcriptome, and MDD/suicide for 24 genes involved in GABAergic and glutamatergic signaling. In part 1 of the study, 119 candidate SNPs in 24 genes (4 transporters, 4 enzymes, and 16 receptors) were tested for associations with MDD and suicidal behavior in 276 live participants (86 nonfatal suicide attempters with MDD and 190 non-attempters of whom 70% had MDD) and 209 postmortem cases (121 suicide deaths of whom 62% had MDD and 88 sudden death from other causes of whom 11% had MDD) using logistic regression adjusting for sex and age. In part 2, RNA-seq was used to assay isoform-level expression in dorsolateral prefrontal cortex of 59 postmortem samples (21 with MDD and suicide, 9 MDD without suicide, and 29 sudden death non-suicides and no psychiatric illness) using robust regression adjusting for sex, age, and RIN score. In part 3, SNPs with subthreshold (uncorrected) significance levels below 0.05 for an association with suicidal behavior and/or MDD in part 1 were tested for eQTL effects in prefrontal cortex using the Brain eQTL Almanac (www.braineac.org). No SNPs or transcripts were significant after adjustment for multiple comparisons. However, a protein coding transcript (ENST00000414552) of the GABA A receptor, gamma 2 (GABRG2) had lower brain expression postmortem in suicide (P = 0.01) and evidence for association with suicide death (P = 0.03) in a SNP that may be an eQTL in prefrontal cortex (rs424740, P = 0.02). These preliminary results implicate GABRG2 in suicide and warrant further investigation and replication in larger samples. © 2016 Wiley Periodicals, Inc.

Integrative genomics analysis identifies ancestral-related eQTLs on POLB, and supports the association of genetic ancestry with survival disparity in HNSCC

PubMed Central

Ramakodi, Meganathan P.; Devarajan, Karthik; Blackman, Elizabeth; Gibbs, Denise; Luce, Danièle; Deloumeaux, Jacqueline; Duflo, Suzy; Liu, Jeffrey C.; Mehra, Ranee; Kulathinal, Rob J.; Ragin, Camille C.

2016-01-01

BACKGROUND African-Americans (Afr-Amr) with head and neck squamous cell carcinoma (HNSCC) have a lower survival rate than Caucasians (Cau). This study investigates the functional importance of ancestry-informative SNPs in HNSCC and also examines the effect of functionally important genetic elements on racial disparities in HNSCC survival. METHODS Ancestry-informative SNPs, RNAseq, methylation, and copy number variation data for 316 oral cavity and laryngeal cancer patients were analyzed across 178 DNA repair genes. The results of eQTL analyses were also replicated using a Gene Expression Omnibus (GEO) dataset. The effects of eQTLs on overall survival (OS) and disease-free survival (DFS) were evaluated. RESULTS Five ancestry-related SNPs were identified as cis-eQTLs in the POLB gene (FDR<0.01). The homozygous/ heterozygous genotypes containing the Afr-allele showed higher POLB expression relative to the homozygous Cau-allele genotype (P<0.001). A replication study using a GEO dataset validated all five eQTLs, also showing a statistically significant difference in POLB expression based on genetic ancestry (P=0.002). An association was observed between these eQTLs and OS (P<0.037; FDR<0.0363) as well as DFS of oral cavity and laryngeal cancer patients treated with platinum-based chemotherapy and/or radiotherapy (P=0.018 to 0.0629; FDR<0.079). Genotypes containing the Afr-allele were associated with poor OS/DFS compared to homozygous genotypes harboring the Cau-allele. CONCLUSIONS Our analyses show that ancestry-related alleles could act as eQTLs in HNSCC and support the association of ancestry-related genetic factors with survival disparity in patients diagnosed with oral cavity and laryngeal cancer. PMID:27906459

Genetic regulation of gene expression in the lung identifies CST3 and CD22 as potential causal genes for airflow obstruction.

PubMed

Lamontagne, Maxime; Timens, Wim; Hao, Ke; Bossé, Yohan; Laviolette, Michel; Steiling, Katrina; Campbell, Joshua D; Couture, Christian; Conti, Massimo; Sherwood, Karen; Hogg, James C; Brandsma, Corry-Anke; van den Berge, Maarten; Sandford, Andrew; Lam, Stephen; Lenburg, Marc E; Spira, Avrum; Paré, Peter D; Nickle, David; Sin, Don D; Postma, Dirkje S

2014-11-01

COPD is a complex chronic disease with poorly understood pathogenesis. Integrative genomic approaches have the potential to elucidate the biological networks underlying COPD and lung function. We recently combined genome-wide genotyping and gene expression in 1111 human lung specimens to map expression quantitative trait loci (eQTL). To determine causal associations between COPD and lung function-associated single nucleotide polymorphisms (SNPs) and lung tissue gene expression changes in our lung eQTL dataset. We evaluated causality between SNPs and gene expression for three COPD phenotypes: FEV(1)% predicted, FEV(1)/FVC and COPD as a categorical variable. Different models were assessed in the three cohorts independently and in a meta-analysis. SNPs associated with a COPD phenotype and gene expression were subjected to causal pathway modelling and manual curation. In silico analyses evaluated functional enrichment of biological pathways among newly identified causal genes. Biologically relevant causal genes were validated in two separate gene expression datasets of lung tissues and bronchial airway brushings. High reliability causal relations were found in SNP-mRNA-phenotype triplets for FEV(1)% predicted (n=169) and FEV(1)/FVC (n=80). Several genes of potential biological relevance for COPD were revealed. eQTL-SNPs upregulating cystatin C (CST3) and CD22 were associated with worse lung function. Signalling pathways enriched with causal genes included xenobiotic metabolism, apoptosis, protease-antiprotease and oxidant-antioxidant balance. By using integrative genomics and analysing the relationships of COPD phenotypes with SNPs and gene expression in lung tissue, we identified CST3 and CD22 as potential causal genes for airflow obstruction. This study also augmented the understanding of previously described COPD pathways. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Signatures of Evolutionary Adaptation in Quantitative Trait Loci Influencing Trace Element Homeostasis in Liver

PubMed Central

Sabidó, Eduard; Bosch, Elena

2016-01-01

Essential trace elements possess vital functions at molecular, cellular, and physiological levels in health and disease, and they are tightly regulated in the human body. In order to assess variability and potential adaptive evolution of trace element homeostasis, we quantified 18 trace elements in 150 liver samples, together with the expression levels of 90 genes and abundances of 40 proteins involved in their homeostasis. Additionally, we genotyped 169 single nucleotide polymorphism (SNPs) in the same sample set. We detected significant associations for 8 protein quantitative trait loci (pQTL), 10 expression quantitative trait loci (eQTLs), and 15 micronutrient quantitative trait loci (nutriQTL). Six of these exceeded the false discovery rate cutoff and were related to essential trace elements: 1) one pQTL for GPX2 (rs10133290); 2) two previously described eQTLs for HFE (rs12346) and SELO (rs4838862) expression; and 3) three nutriQTLs: The pathogenic C282Y mutation at HFE affecting iron (rs1800562), and two SNPs within several clustered metallothionein genes determining selenium concentration (rs1811322 and rs904773). Within the complete set of significant QTLs (which involved 30 SNPs and 20 gene regions), we identified 12 SNPs with extreme patterns of population differentiation (FST values in the top 5% percentile in at least one HapMap population pair) and significant evidence for selective sweeps involving QTLs at GPX1, SELENBP1, GPX3, SLC30A9, and SLC39A8. Overall, this detailed study of various molecular phenotypes illustrates the role of regulatory variants in explaining differences in trace element homeostasis among populations and in the human adaptive response to environmental pressures related to micronutrients. PMID:26582562

Integrating genome-wide genetic variations and monocyte expression data reveals trans-regulated gene modules in humans.

PubMed

Rotival, Maxime; Zeller, Tanja; Wild, Philipp S; Maouche, Seraya; Szymczak, Silke; Schillert, Arne; Castagné, Raphaele; Deiseroth, Arne; Proust, Carole; Brocheton, Jessy; Godefroy, Tiphaine; Perret, Claire; Germain, Marine; Eleftheriadis, Medea; Sinning, Christoph R; Schnabel, Renate B; Lubos, Edith; Lackner, Karl J; Rossmann, Heidi; Münzel, Thomas; Rendon, Augusto; Erdmann, Jeanette; Deloukas, Panos; Hengstenberg, Christian; Diemert, Patrick; Montalescot, Gilles; Ouwehand, Willem H; Samani, Nilesh J; Schunkert, Heribert; Tregouet, David-Alexandre; Ziegler, Andreas; Goodall, Alison H; Cambien, François; Tiret, Laurence; Blankenberg, Stefan

2011-12-01

One major expectation from the transcriptome in humans is to characterize the biological basis of associations identified by genome-wide association studies. So far, few cis expression quantitative trait loci (eQTLs) have been reliably related to disease susceptibility. Trans-regulating mechanisms may play a more prominent role in disease susceptibility. We analyzed 12,808 genes detected in at least 5% of circulating monocyte samples from a population-based sample of 1,490 European unrelated subjects. We applied a method of extraction of expression patterns-independent component analysis-to identify sets of co-regulated genes. These patterns were then related to 675,350 SNPs to identify major trans-acting regulators. We detected three genomic regions significantly associated with co-regulated gene modules. Association of these loci with multiple expression traits was replicated in Cardiogenics, an independent study in which expression profiles of monocytes were available in 758 subjects. The locus 12q13 (lead SNP rs11171739), previously identified as a type 1 diabetes locus, was associated with a pattern including two cis eQTLs, RPS26 and SUOX, and 5 trans eQTLs, one of which (MADCAM1) is a potential candidate for mediating T1D susceptibility. The locus 12q24 (lead SNP rs653178), which has demonstrated extensive disease pleiotropy, including type 1 diabetes, hypertension, and celiac disease, was associated to a pattern strongly correlating to blood pressure level. The strongest trans eQTL in this pattern was CRIP1, a known marker of cellular proliferation in cancer. The locus 12q15 (lead SNP rs11177644) was associated with a pattern driven by two cis eQTLs, LYZ and YEATS4, and including 34 trans eQTLs, several of them tumor-related genes. This study shows that a method exploiting the structure of co-expressions among genes can help identify genomic regions involved in trans regulation of sets of genes and can provide clues for understanding the mechanisms linking genome-wide association loci to disease.

Identification of Splicing Quantitative Trait Loci (sQTL) in Drosophila melanogaster with Developmental Lead (Pb2+) Exposure.

PubMed

Qu, Wen; Gurdziel, Katherine; Pique-Regi, Roger; Ruden, Douglas M

2017-01-01

Lead (Pb) poisoning has been a major public health issue globally and the recent Flint water crisis has drawn nation-wide attention to its effects. To better understand how lead plays a role as a neurotoxin, we utilized the Drosophila melanogaster model to study the genetic effects of lead exposure during development and identified lead-responsive genes. In our previous studies, we have successfully identified hundreds of lead-responsive expression QTLs (eQTLs) by using RNA-seq analysis on heads collected from the Drosophila Synthetic Population Resource. Cis -eQTLs, also known as allele-specific expression (ASE) polymorphisms, are generally single-nucleotide polymorphisms in the promoter regions of genes that affect expression of the gene, such as by inhibiting the binding of transcription factors. Trans -eQTLs are genes that regulate mRNA levels for many genes, and are generally thought to be SNPs in trans -acting transcription or translation factors. In this study, we focused our attention on alternative splicing events that are affected by lead exposure. Splicing QTLs (sQTLs), which can be caused by SNPs that alter splicing or alternative splicing (AS), such as by changing the sequence-specific binding affinity of splicing factors to the pre-mRNA. We applied two methods in search for sQTLs by using RNA-seq data from control and lead-exposed w 1118 Drosophila heads. First, we used the fraction of reads in a gene that falls in each exon as the phenotype. Second, we directly compared the transcript counts among the various splicing isoforms as the phenotype. Among the 1,236 potential Pb-responsive sQTLs ( p < 0.0001, FDR < 0.39), mostly cis -sQTLs, one of the most distinct genes is Dscam1 (Down Syndrome Cell Adhesion Molecule), which has over 30,000 potential alternative splicing isoforms. We have also identified a candidate Pb-responsive trans -sQTL hotspot that appears to regulate 129 genes that are enriched in the "cation channel" gene ontology category, suggesting a model in which alternative splicing of these channels might lead to an increase in the elimination of Pb 2+ from the neurons encoding these channels. To our knowledge, this is the first paper that uses sQTL analyses to understand the neurotoxicology of an environmental toxin in any organism, and the first reported discovery of a candidate trans -sQTL hotspot.

Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression.

PubMed

Fairfax, Benjamin P; Humburg, Peter; Makino, Seiko; Naranbhai, Vivek; Wong, Daniel; Lau, Evelyn; Jostins, Luke; Plant, Katharine; Andrews, Robert; McGee, Chris; Knight, Julian C

2014-03-07

To systematically investigate the impact of immune stimulation upon regulatory variant activity, we exposed primary monocytes from 432 healthy Europeans to interferon-γ (IFN-γ) or differing durations of lipopolysaccharide and mapped expression quantitative trait loci (eQTLs). More than half of cis-eQTLs identified, involving hundreds of genes and associated pathways, are detected specifically in stimulated monocytes. Induced innate immune activity reveals multiple master regulatory trans-eQTLs including the major histocompatibility complex (MHC), coding variants altering enzyme and receptor function, an IFN-β cytokine network showing temporal specificity, and an interferon regulatory factor 2 (IRF2) transcription factor-modulated network. Induced eQTL are significantly enriched for genome-wide association study loci, identifying context-specific associations to putative causal genes including CARD9, ATM, and IRF8. Thus, applying pathophysiologically relevant immune stimuli assists resolution of functional genetic variants.

Genetical Genomics Identifies the Genetic Architecture for Growth and Weevil Resistance in Spruce

PubMed Central

Porth, Ilga; White, Richard; Jaquish, Barry; Alfaro, René; Ritland, Carol; Ritland, Kermit

2012-01-01

In plants, relationships between resistance to herbivorous insect pests and growth are typically controlled by complex interactions between genetically correlated traits. These relationships often result in tradeoffs in phenotypic expression. In this study we used genetical genomics to elucidate genetic relationships between tree growth and resistance to white pine terminal weevil (Pissodes strobi Peck.) in a pedigree population of interior spruce (Picea glauca, P. engelmannii and their hybrids) that was growing at Vernon, B.C. and segregating for weevil resistance. Genetical genomics uses genetic perturbations caused by allelic segregation in pedigrees to co-locate quantitative trait loci (QTLs) for gene expression and quantitative traits. Bark tissue of apical leaders from 188 trees was assayed for gene expression using a 21.8K spruce EST-spotted microarray; the same individuals were genotyped for 384 SNP markers for the genetic map. Many of the expression QTLs (eQTL) co-localized with resistance trait QTLs. For a composite resistance phenotype of six attack and oviposition traits, 149 positional candidate genes were identified. Resistance and growth QTLs also overlapped with eQTL hotspots along the genome suggesting that: 1) genetic pleiotropy of resistance and growth traits in interior spruce was substantial, and 2) master regulatory genes were important for weevil resistance in spruce. These results will enable future work on functional genetic studies of insect resistance in spruce, and provide valuable information about candidate genes for genetic improvement of spruce. PMID:22973444

Refining Susceptibility Loci of Chronic Obstructive Pulmonary Disease with Lung eqtls

PubMed Central

Lamontagne, Maxime; Couture, Christian; Postma, Dirkje S.; Timens, Wim; Sin, Don D.; Paré, Peter D.; Hogg, James C.; Nickle, David; Laviolette, Michel; Bossé, Yohan

2013-01-01

Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of mortality worldwide. Recent genome-wide association studies (GWAS) have identified robust susceptibility loci associated with COPD. However, the mechanisms mediating the risk conferred by these loci remain to be found. The goal of this study was to identify causal genes/variants within susceptibility loci associated with COPD. In the discovery cohort, genome-wide gene expression profiles of 500 non-tumor lung specimens were obtained from patients undergoing lung surgery. Blood-DNA from the same patients were genotyped for 1,2 million SNPs. Following genotyping and gene expression quality control filters, 409 samples were analyzed. Lung expression quantitative trait loci (eQTLs) were identified and overlaid onto three COPD susceptibility loci derived from GWAS; 4q31 (HHIP), 4q22 (FAM13A), and 19q13 (RAB4B, EGLN2, MIA, CYP2A6). Significant eQTLs were replicated in two independent datasets (n = 363 and 339). SNPs previously associated with COPD and lung function on 4q31 (rs1828591, rs13118928) were associated with the mRNA expression of HHIP. An association between mRNA expression level of FAM13A and SNP rs2045517 was detected at 4q22, but did not reach statistical significance. At 19q13, significant eQTLs were detected with EGLN2. In summary, this study supports HHIP, FAM13A, and EGLN2 as the most likely causal COPD genes on 4q31, 4q22, and 19q13, respectively. Strong lung eQTL SNPs identified in this study will need to be tested for association with COPD in case-control studies. Further functional studies will also be needed to understand the role of genes regulated by disease-related variants in COPD. PMID:23936167

Integrative genomic analysis identifies ancestry-related expression quantitative trait loci on DNA polymerase β and supports the association of genetic ancestry with survival disparities in head and neck squamous cell carcinoma.

PubMed

Ramakodi, Meganathan P; Devarajan, Karthik; Blackman, Elizabeth; Gibbs, Denise; Luce, Danièle; Deloumeaux, Jacqueline; Duflo, Suzy; Liu, Jeffrey C; Mehra, Ranee; Kulathinal, Rob J; Ragin, Camille C

2017-03-01

African Americans with head and neck squamous cell carcinoma (HNSCC) have a lower survival rate than whites. This study investigated the functional importance of ancestry-informative single-nucleotide polymorphisms (SNPs) in HNSCC and also examined the effect of functionally important genetic elements on racial disparities in HNSCC survival. Ancestry-informative SNPs, RNA sequencing, methylation, and copy number variation data for 316 oral cavity and laryngeal cancer patients were analyzed across 178 DNA repair genes. The results of expression quantitative trait locus (eQTL) analyses were also replicated with a Gene Expression Omnibus (GEO) data set. The effects of eQTLs on overall survival (OS) and disease-free survival (DFS) were evaluated. Five ancestry-related SNPs were identified as cis-eQTLs in the DNA polymerase β (POLB) gene (false discovery rate [FDR] < 0.01). The homozygous/heterozygous genotypes containing the African allele showed higher POLB expression than the homozygous white allele genotype (P < .001). A replication study using a GEO data set validated all 5 eQTLs and also showed a statistically significant difference in POLB expression based on genetic ancestry (P = .002). An association was observed between these eQTLs and OS (P < .037; FDR < 0.0363) as well as DFS (P = .018 to .0629; FDR < 0.079) for oral cavity and laryngeal cancer patients treated with platinum-based chemotherapy and/or radiotherapy. Genotypes containing the African allele were associated with poor OS/DFS in comparison with homozygous genotypes harboring the white allele. Analyses show that ancestry-related alleles could act as eQTLs in HNSCC and support the association of ancestry-related genetic factors with survival disparities in patients diagnosed with oral cavity and laryngeal cancer. Cancer 2017;123:849-60. © 2016 American Cancer Society. © 2016 American Cancer Society.

SZDB: A Database for Schizophrenia Genetic Research

PubMed Central

Wu, Yong; Yao, Yong-Gang

2017-01-01

Abstract Schizophrenia (SZ) is a debilitating brain disorder with a complex genetic architecture. Genetic studies, especially recent genome-wide association studies (GWAS), have identified multiple variants (loci) conferring risk to SZ. However, how to efficiently extract meaningful biological information from bulk genetic findings of SZ remains a major challenge. There is a pressing need to integrate multiple layers of data from various sources, eg, genetic findings from GWAS, copy number variations (CNVs), association and linkage studies, gene expression, protein–protein interaction (PPI), co-expression, expression quantitative trait loci (eQTL), and Encyclopedia of DNA Elements (ENCODE) data, to provide a comprehensive resource to facilitate the translation of genetic findings into SZ molecular diagnosis and mechanism study. Here we developed the SZDB database (http://www.szdb.org/), a comprehensive resource for SZ research. SZ genetic data, gene expression data, network-based data, brain eQTL data, and SNP function annotation information were systematically extracted, curated and deposited in SZDB. In-depth analyses and systematic integration were performed to identify top prioritized SZ genes and enriched pathways. Multiple types of data from various layers of SZ research were systematically integrated and deposited in SZDB. In-depth data analyses and integration identified top prioritized SZ genes and enriched pathways. We further showed that genes implicated in SZ are highly co-expressed in human brain and proteins encoded by the prioritized SZ risk genes are significantly interacted. The user-friendly SZDB provides high-confidence candidate variants and genes for further functional characterization. More important, SZDB provides convenient online tools for data search and browse, data integration, and customized data analyses. PMID:27451428

Deciphering the genetic control of gene expression following Mycobacterium leprae antigen stimulation.

PubMed

Manry, Jérémy; Nédélec, Yohann; Fava, Vinicius M; Cobat, Aurélie; Orlova, Marianna; Thuc, Nguyen Van; Thai, Vu Hong; Laval, Guillaume; Barreiro, Luis B; Schurr, Erwin

2017-08-01

Leprosy is a human infectious disease caused by Mycobacterium leprae. A strong host genetic contribution to leprosy susceptibility is well established. However, the modulation of the transcriptional response to infection and the mechanism(s) of disease control are poorly understood. To address this gap in knowledge of leprosy pathogenicity, we conducted a genome-wide search for expression quantitative trait loci (eQTL) that are associated with transcript variation before and after stimulation with M. leprae sonicate in whole blood cells. We show that M. leprae antigen stimulation mainly triggered the upregulation of immune related genes and that a substantial proportion of the differential gene expression is genetically controlled. Indeed, using stringent criteria, we identified 318 genes displaying cis-eQTL at an FDR of 0.01, including 66 genes displaying response-eQTL (reQTL), i.e. cis-eQTL that showed significant evidence for interaction with the M. leprae stimulus. Such reQTL correspond to regulatory variations that affect the interaction between human whole blood cells and M. leprae sonicate and, thus, likely between the human host and M. leprae bacilli. We found that reQTL were significantly enriched among binding sites of transcription factors that are activated in response to infection, and that they were enriched among single nucleotide polymorphisms (SNPs) associated with susceptibility to leprosy per se and Type-I Reaction, and seven of them have been targeted by recent positive selection. Our study suggested that natural selection shaped our genomic diversity to face pathogen exposure including M. leprae infection.

Cis-eQTL analysis and functional validation of candidate susceptibility genes for high-grade serous ovarian cancer.

PubMed

Lawrenson, Kate; Li, Qiyuan; Kar, Siddhartha; Seo, Ji-Heui; Tyrer, Jonathan; Spindler, Tassja J; Lee, Janet; Chen, Yibu; Karst, Alison; Drapkin, Ronny; Aben, Katja K H; Anton-Culver, Hoda; Antonenkova, Natalia; Baker, Helen; Bandera, Elisa V; Bean, Yukie; Beckmann, Matthias W; Berchuck, Andrew; Bisogna, Maria; Bjorge, Line; Bogdanova, Natalia; Brinton, Louise A; Brooks-Wilson, Angela; Bruinsma, Fiona; Butzow, Ralf; Campbell, Ian G; Carty, Karen; Chang-Claude, Jenny; Chenevix-Trench, Georgia; Chen, Anne; Chen, Zhihua; Cook, Linda S; Cramer, Daniel W; Cunningham, Julie M; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas T; Edwards, Robert P; Eilber, Ursula; Ekici, Arif B; Fasching, Peter A; Fridley, Brooke L; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G; Glasspool, Rosalind; Goode, Ellen L; Goodman, Marc T; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hasmad, Hanis Nazihah; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A T; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus; Hosono, Satoyo; Iversen, Edwin S; Jakubowska, Anna; James, Paul; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kruger Kjaer, Susanne; Kelemen, Linda E; Kellar, Melissa; Kelley, Joseph L; Kiemeney, Lambertus A; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D; Lee, Alice W; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon F A G; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; Nevanlinna, Heli; McNeish, Ian; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B; Narod, Steven A; Nedergaard, Lotte; Ness, Roberta B; Azmi, Mat Adenan Noor; Odunsi, Kunle; Olson, Sara H; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste L; Pejovic, Tanja; Pelttari, Liisa M; Permuth-Wey, Jennifer; Phelan, Catherine M; Pike, Malcolm C; Poole, Elizabeth M; Ramus, Susan J; Risch, Harvey A; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H; Rudolph, Anja; Runnebaum, Ingo B; Rzepecka, Iwona K; Salvesen, Helga B; Schildkraut, Joellen M; Schwaab, Ira; Sellers, Thomas A; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C; Sucheston, Lara; Tangen, Ingvild L; Teo, Soo-Hwang; Terry, Kathryn L; Thompson, Pamela J; Timorek, Agnieszka; Tsai, Ya-Yu; Tworoger, Shelley S; van Altena, Anne M; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S; Wicklund, Kristine G; Wilkens, Lynne R; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna H; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Monteiro, Alvaro; Pharoah, Paul D; Gayther, Simon A; Freedman, Matthew L

2015-09-22

Genome-wide association studies have reported 11 regions conferring risk of high-grade serous epithelial ovarian cancer (HGSOC). Expression quantitative trait locus (eQTL) analyses can identify candidate susceptibility genes at risk loci. Here we evaluate cis-eQTL associations at 47 regions associated with HGSOC risk (P≤10(-5)). For three cis-eQTL associations (P<1.4 × 10(-3), FDR<0.05) at 1p36 (CDC42), 1p34 (CDCA8) and 2q31 (HOXD9), we evaluate the functional role of each candidate by perturbing expression of each gene in HGSOC precursor cells. Overexpression of HOXD9 increases anchorage-independent growth, shortens population-doubling time and reduces contact inhibition. Chromosome conformation capture identifies an interaction between rs2857532 and the HOXD9 promoter, suggesting this SNP is a leading causal variant. Transcriptomic profiling after HOXD9 overexpression reveals enrichment of HGSOC risk variants within HOXD9 target genes (P=6 × 10(-10) for risk variants (P<10(-4)) within 10 kb of a HOXD9 target gene in ovarian cells), suggesting a broader role for this network in genetic susceptibility to HGSOC.

Cis-eQTL analysis and functional validation of candidate susceptibility genes for high-grade serous ovarian cancer

PubMed Central

Lawrenson, Kate; Li, Qiyuan; Kar, Siddhartha; Seo, Ji-Heui; Tyrer, Jonathan; Spindler, Tassja J.; Lee, Janet; Chen, Yibu; Karst, Alison; Drapkin, Ronny; Aben, Katja K. H.; Anton-Culver, Hoda; Antonenkova, Natalia; Bowtell, David; Webb, Penelope M.; deFazio, Anna; Baker, Helen; Bandera, Elisa V.; Bean, Yukie; Beckmann, Matthias W.; Berchuck, Andrew; Bisogna, Maria; Bjorge, Line; Bogdanova, Natalia; Brinton, Louise A.; Brooks-Wilson, Angela; Bruinsma, Fiona; Butzow, Ralf; Campbell, Ian G.; Carty, Karen; Chang-Claude, Jenny; Chenevix-Trench, Georgia; Chen, Anne; Chen, Zhihua; Cook, Linda S.; Cramer, Daniel W.; Cunningham, Julie M.; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A.; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas T.; Edwards, Robert P.; Eilber, Ursula; Ekici, Arif B.; Fasching, Peter A.; Fridley, Brooke L.; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G.; Glasspool, Rosalind; Goode, Ellen L.; Goodman, Marc T.; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hasmad, Hanis Nazihah; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A. T.; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus; Hosono, Satoyo; Iversen, Edwin S.; Jakubowska, Anna; James, Paul; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y.; Kruger Kjaer, Susanne; Kelemen, Linda E.; Kellar, Melissa; Kelley, Joseph L.; Kiemeney, Lambertus A.; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D.; Lee, Alice W.; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A.; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon F. A. G.; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R.; Nevanlinna, Heli; McNeish, Ian; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B.; Narod, Steven A.; Nedergaard, Lotte; Ness, Roberta B.; Azmi, Mat Adenan Noor; Odunsi, Kunle; Olson, Sara H.; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste L.; Pejovic, Tanja; Pelttari, Liisa M.; Permuth-Wey, Jennifer; Phelan, Catherine M.; Pike, Malcolm C.; Poole, Elizabeth M.; Ramus, Susan J.; Risch, Harvey A.; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H.; Rudolph, Anja; Runnebaum, Ingo B.; Rzepecka, Iwona K.; Salvesen, Helga B.; Schildkraut, Joellen M.; Schwaab, Ira; Sellers, Thomas A.; Shu, Xiao-Ou; Shvetsov, Yurii B.; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C.; Sucheston, Lara; Tangen, Ingvild L.; Teo, Soo-Hwang; Terry, Kathryn L.; Thompson, Pamela J.; Timorek, Agnieszka; Tsai, Ya-Yu; Tworoger, Shelley S.; van Altena, Anne M.; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A.; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S.; Wicklund, Kristine G.; Wilkens, Lynne R.; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna H.; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Monteiro, Alvaro; Pharoah, Paul D.; Gayther, Simon A.; Freedman, Matthew L.

2015-01-01

Genome-wide association studies have reported 11 regions conferring risk of high-grade serous epithelial ovarian cancer (HGSOC). Expression quantitative trait locus (eQTL) analyses can identify candidate susceptibility genes at risk loci. Here we evaluate cis-eQTL associations at 47 regions associated with HGSOC risk (P≤10−5). For three cis-eQTL associations (P<1.4 × 10−3, FDR<0.05) at 1p36 (CDC42), 1p34 (CDCA8) and 2q31 (HOXD9), we evaluate the functional role of each candidate by perturbing expression of each gene in HGSOC precursor cells. Overexpression of HOXD9 increases anchorage-independent growth, shortens population-doubling time and reduces contact inhibition. Chromosome conformation capture identifies an interaction between rs2857532 and the HOXD9 promoter, suggesting this SNP is a leading causal variant. Transcriptomic profiling after HOXD9 overexpression reveals enrichment of HGSOC risk variants within HOXD9 target genes (P=6 × 10−10 for risk variants (P<10−4) within 10 kb of a HOXD9 target gene in ovarian cells), suggesting a broader role for this network in genetic susceptibility to HGSOC. PMID:26391404

Advances in Genetical Genomics of Plants

PubMed Central

Joosen, R.V.L.; Ligterink, W.; Hilhorst, H.W.M.; Keurentjes, J.J.B.

2009-01-01

Natural variation provides a valuable resource to study the genetic regulation of quantitative traits. In quantitative trait locus (QTL) analyses this variation, captured in segregating mapping populations, is used to identify the genomic regions affecting these traits. The identification of the causal genes underlying QTLs is a major challenge for which the detection of gene expression differences is of major importance. By combining genetics with large scale expression profiling (i.e. genetical genomics), resulting in expression QTLs (eQTLs), great progress can be made in connecting phenotypic variation to genotypic diversity. In this review we discuss examples from human, mouse, Drosophila, yeast and plant research to illustrate the advances in genetical genomics, with a focus on understanding the regulatory mechanisms underlying natural variation. With their tolerance to inbreeding, short generation time and ease to generate large families, plants are ideal subjects to test new concepts in genetics. The comprehensive resources which are available for Arabidopsis make it a favorite model plant but genetical genomics also found its way to important crop species like rice, barley and wheat. We discuss eQTL profiling with respect to cis and trans regulation and show how combined studies with other ‘omics’ technologies, such as metabolomics and proteomics may further augment current information on transcriptional, translational and metabolomic signaling pathways and enable reconstruction of detailed regulatory networks. The fast developments in the ‘omics’ area will offer great potential for genetical genomics to elucidate the genotype-phenotype relationships for both fundamental and applied research. PMID:20514216

QuASAR: quantitative allele-specific analysis of reads

PubMed Central

Harvey, Chris T.; Moyerbrailean, Gregory A.; Davis, Gordon O.; Wen, Xiaoquan; Luca, Francesca; Pique-Regi, Roger

2015-01-01

Motivation: Expression quantitative trait loci (eQTL) studies have discovered thousands of genetic variants that regulate gene expression, enabling a better understanding of the functional role of non-coding sequences. However, eQTL studies are costly, requiring large sample sizes and genome-wide genotyping of each sample. In contrast, analysis of allele-specific expression (ASE) is becoming a popular approach to detect the effect of genetic variation on gene expression, even within a single individual. This is typically achieved by counting the number of RNA-seq reads matching each allele at heterozygous sites and testing the null hypothesis of a 1:1 allelic ratio. In principle, when genotype information is not readily available, it could be inferred from the RNA-seq reads directly. However, there are currently no existing methods that jointly infer genotypes and conduct ASE inference, while considering uncertainty in the genotype calls. Results: We present QuASAR, quantitative allele-specific analysis of reads, a novel statistical learning method for jointly detecting heterozygous genotypes and inferring ASE. The proposed ASE inference step takes into consideration the uncertainty in the genotype calls, while including parameters that model base-call errors in sequencing and allelic over-dispersion. We validated our method with experimental data for which high-quality genotypes are available. Results for an additional dataset with multiple replicates at different sequencing depths demonstrate that QuASAR is a powerful tool for ASE analysis when genotypes are not available. Availability and implementation: http://github.com/piquelab/QuASAR. Contact: fluca@wayne.edu or rpique@wayne.edu Supplementary information: Supplementary Material is available at Bioinformatics online. PMID:25480375

Incorporating Functional Annotations for Fine-Mapping Causal Variants in a Bayesian Framework Using Summary Statistics.

PubMed

Chen, Wenan; McDonnell, Shannon K; Thibodeau, Stephen N; Tillmans, Lori S; Schaid, Daniel J

2016-11-01

Functional annotations have been shown to improve both the discovery power and fine-mapping accuracy in genome-wide association studies. However, the optimal strategy to incorporate the large number of existing annotations is still not clear. In this study, we propose a Bayesian framework to incorporate functional annotations in a systematic manner. We compute the maximum a posteriori solution and use cross validation to find the optimal penalty parameters. By extending our previous fine-mapping method CAVIARBF into this framework, we require only summary statistics as input. We also derived an exact calculation of Bayes factors using summary statistics for quantitative traits, which is necessary when a large proportion of trait variance is explained by the variants of interest, such as in fine mapping expression quantitative trait loci (eQTL). We compared the proposed method with PAINTOR using different strategies to combine annotations. Simulation results show that the proposed method achieves the best accuracy in identifying causal variants among the different strategies and methods compared. We also find that for annotations with moderate effects from a large annotation pool, screening annotations individually and then combining the top annotations can produce overly optimistic results. We applied these methods on two real data sets: a meta-analysis result of lipid traits and a cis-eQTL study of normal prostate tissues. For the eQTL data, incorporating annotations significantly increased the number of potential causal variants with high probabilities. Copyright © 2016 by the Genetics Society of America.

PXK locus in systemic lupus erythematosus: fine mapping and functional analysis reveals novel susceptibility gene ABHD6.

PubMed

Oparina, Nina Y; Delgado-Vega, Angelica M; Martinez-Bueno, Manuel; Magro-Checa, César; Fernández, Concepción; Castro, Rafaela Ortega; Pons-Estel, Bernardo A; D'Alfonso, Sandra; Sebastiani, Gian Domenico; Witte, Torsten; Lauwerys, Bernard R; Endreffy, Emoke; Kovács, László; Escudero, Alejandro; López-Pedrera, Chary; Vasconcelos, Carlos; da Silva, Berta Martins; Frostegård, Johan; Truedsson, Lennart; Martin, Javier; Raya, Enrique; Ortego-Centeno, Norberto; de Los Angeles Aguirre, Maria; de Ramón Garrido, Enrique; Palma, María-Jesús Castillo; Alarcon-Riquelme, Marta E; Kozyrev, Sergey V

2015-03-01

To perform fine mapping of the PXK locus associated with systemic lupus erythematosus (SLE) and study functional effects that lead to susceptibility to the disease. Linkage disequilibrium (LD) mapping was conducted by using 1251 SNPs (single nucleotide polymorphism) covering a 862 kb genomic region on 3p14.3 comprising the PXK locus in 1467 SLE patients and 2377 controls of European origin. Tag SNPs and genotypes imputed with IMPUTE2 were tested for association by using SNPTEST and PLINK. The expression QTLs data included three independent datasets for lymphoblastoid cells of European donors: HapMap3, MuTHER and the cross-platform eQTL catalogue. Correlation analysis of eQTLs was performed using Vassarstats. Alternative splicing for the PXK gene was analysed on mRNA from PBMCs. Fine mapping revealed long-range LD (>200 kb) extended over the ABHD6, RPP14, PXK, and PDHB genes on 3p14.3. The highly correlated variants tagged an SLE-associated haplotype that was less frequent in the patients compared with the controls (OR=0.89, p=0.00684). A robust correlation between the association with SLE and enhanced expression of ABHD6 gene was revealed, while neither expression, nor splicing alterations associated with SLE susceptibility were detected for PXK. The SNP allele frequencies as well as eQTL pattern analysed in the CEU and CHB HapMap3 populations indicate that the SLE association and the effect on ABHD6 expression are specific to Europeans. These results confirm the genetic association of the locus 3p14.3 with SLE in Europeans and point to the ABHD6 and not PXK, as the major susceptibility gene in the region. We suggest a pathogenic mechanism mediated by the upregulation of ABHD6 in individuals carrying the SLE-risk variants. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Genome-wide significant risk associations for mucinous ovarian carcinoma

PubMed Central

Kelemen, Linda E.; Lawrenson, Kate; Tyrer, Jonathan; Li, Qiyuan; M. Lee, Janet; Seo, Ji-Heui; Phelan, Catherine M.; Beesley, Jonathan; Chen, Xiaoqin; Spindler, Tassja J.; Aben, Katja K.H.; Anton-Culver, Hoda; Antonenkova, Natalia; Baker, Helen; Bandera, Elisa V.; Bean, Yukie; Beckmann, Matthias W.; Bisogna, Maria; Bjorge, Line; Bogdanova, Natalia; Brinton, Louise A.; Brooks-Wilson, Angela; Bruinsma, Fiona; Butzow, Ralf; Campbell, Ian G.; Carty, Karen; Chang-Claude, Jenny; Chen, Y. Ann; Chen, Zhihua; Cook, Linda S.; Cramer, Daniel W.; Cunningham, Julie M.; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A.; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas T.; Edwards, Robert P.; Eilber, Ursula; Ekici, Arif B.; Engelholm, Svend Aage; Fasching, Peter A.; Fridley, Brooke L.; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G.; Glasspool, Rosalind; Goode, Ellen L.; Goodman, Marc T.; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hasmad, Hanis Nazihah; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A.T.; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus; Hosono, Satoyo; Iversen, Edwin S.; Jakubowska, Anna; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kellar, Melissa; Kelley, Joseph L.; Kiemeney, Lambertus A.; Krakstad, Camilla; Kjaer, Susanne K.; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D.; Lee, Alice W.; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A.; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon F.A.G.; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R.; McNeish, Iain; Menon, Usha; Modugno, Francesmary; Moes-Sosnowska, Joanna; Moysich, Kirsten B.; Narod, Steven A.; Nedergaard, Lotte; Ness, Roberta B.; Nevanlinna, Heli; Azmi, Mat Adenan Noor; Odunsi, Kunle; Olson, Sara H.; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Paul, James; Pearce, Celeste Leigh; Pejovic, Tanja; Pelttari, Liisa M.; Permuth-Wey, Jennifer; Pike, Malcolm C.; Poole, Elizabeth M.; Ramus, Susan J.; Risch, Harvey A.; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H.; Rudolph, Anja; Runnebaum, Ingo B.; Rzepecka, Iwona K.; Salvesen, Helga B.; Schildkraut, Joellen M.; Schwaab, Ira; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C.; Sucheston, Lara; Tangen, Ingvild L.; Teo, Soo-Hwang; Terry, Kathryn L.; Thompson, Pamela J; Tworoger, Shelley S.; van Altena, Anne M.; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A.; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S.; Wicklund, Kristine G.; Wilkens, Lynne R.; Wlodzimierz, Sawicki; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna H.; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Sellers, Thomas A.; Freedman, Matthew L.; Chenevix-Trench, Georgia; Pharoah, Paul D.; Gayther, Simon A.; Berchuck, Andrew

2015-01-01

Genome-wide association studies have identified several risk associations for ovarian carcinomas (OC) but not for mucinous ovarian carcinomas (MOC). Genotypes from OC cases and controls were imputed into the 1000 Genomes Project reference panel. Analysis of 1,644 MOC cases and 21,693 controls identified three novel risk associations: rs752590 at 2q13 (P = 3.3 × 10−8), rs711830 at 2q31.1 (P = 7.5 × 10−12) and rs688187 at 19q13.2 (P = 6.8 × 10−13). Expression Quantitative Trait Locus (eQTL) analysis in ovarian and colorectal tumors (which are histologically similar to MOC) identified significant eQTL associations for HOXD9 at 2q31.1 in ovarian (P = 4.95 × 10−4, FDR = 0.003) and colorectal (P = 0.01, FDR = 0.09) tumors, and for PAX8 at 2q13 in colorectal tumors (P = 0.03, FDR = 0.09). Chromosome conformation capture analysis identified interactions between the HOXD9 promoter and risk SNPs at 2q31.1. Overexpressing HOXD9 in MOC cells augmented the neoplastic phenotype. These findings provide the first evidence for MOC susceptibility variants and insights into the underlying biology of the disease. PMID:26075790

The complex genetics of gait speed: genome-wide meta-analysis approach

PubMed Central

Lunetta, Kathryn L.; Smith, Jennifer A.; Eicher, John D.; Vered, Rotem; Deelen, Joris; Arnold, Alice M.; Buchman, Aron S.; Tanaka, Toshiko; Faul, Jessica D.; Nethander, Maria; Fornage, Myriam; Adams, Hieab H.; Matteini, Amy M.; Callisaya, Michele L.; Smith, Albert V.; Yu, Lei; De Jager, Philip L.; Evans, Denis A.; Gudnason, Vilmundur; Hofman, Albert; Pattie, Alison; Corley, Janie; Launer, Lenore J.; Knopman, Davis S.; Parimi, Neeta; Turner, Stephen T.; Bandinelli, Stefania; Beekman, Marian; Gutman, Danielle; Sharvit, Lital; Mooijaart, Simon P.; Liewald, David C.; Houwing-Duistermaat, Jeanine J.; Ohlsson, Claes; Moed, Matthijs; Verlinden, Vincent J.; Mellström, Dan; van der Geest, Jos N.; Karlsson, Magnus; Hernandez, Dena; McWhirter, Rebekah; Liu, Yongmei; Thomson, Russell; Tranah, Gregory J.; Uitterlinden, Andre G.; Weir, David R.; Zhao, Wei; Starr, John M.; Johnson, Andrew D.; Ikram, M. Arfan; Bennett, David A.; Cummings, Steven R.; Deary, Ian J.; Harris, Tamara B.; Kardia, Sharon L. R.; Mosley, Thomas H.; Srikanth, Velandai K.; Windham, Beverly G.; Newman, Ann B.; Walston, Jeremy D.; Davies, Gail; Evans, Daniel S.; Slagboom, Eline P.; Ferrucci, Luigi; Kiel, Douglas P.; Murabito, Joanne M.; Atzmon, Gil

2017-01-01

Emerging evidence suggests that the basis for variation in late-life mobility is attributable, in part, to genetic factors, which may become increasingly important with age. Our objective was to systematically assess the contribution of genetic variation to gait speed in older individuals. We conducted a meta-analysis of gait speed GWASs in 31,478 older adults from 17 cohorts of the CHARGE consortium, and validated our results in 2,588 older adults from 4 independent studies. We followed our initial discoveries with network and eQTL analysis of candidate signals in tissues. The meta-analysis resulted in a list of 536 suggestive genome wide significant SNPs in or near 69 genes. Further interrogation with Pathway Analysis placed gait speed as a polygenic complex trait in five major networks. Subsequent eQTL analysis revealed several SNPs significantly associated with the expression of PRSS16, WDSUB1 and PTPRT, which in addition to the meta-analysis and pathway suggested that genetic effects on gait speed may occur through synaptic function and neuronal development pathways. No genome-wide significant signals for gait speed were identified from this moderately large sample of older adults, suggesting that more refined physical function phenotypes will be needed to identify the genetic basis of gait speed in aging. PMID:28077804

Multiple Sclerosis Risk Variant HLA-DRB1*1501 Associates with High Expression of DRB1 Gene in Different Human Populations

PubMed Central

Abad-Grau, María del Mar; Fedetz, María; Izquierdo, Guillermo; Lucas, Miguel; Fernández, Óscar; Ndagire, Dorothy; Catalá-Rabasa, Antonio; Ruiz, Agustín; Gayán, Javier; Delgado, Concepción; Arnal, Carmen

2012-01-01

The human leukocyte antigen (HLA) DRB1*1501 has been consistently associated with multiple sclerosis (MS) in nearly all populations tested. This points to a specific antigen presentation as the pathogenic mechanism though this does not fully explain the disease association. The identification of expression quantitative trait loci (eQTL) for genes in the HLA locus poses the question of the role of gene expression in MS susceptibility. We analyzed the eQTLs in the HLA region with respect to MS-associated HLA-variants obtained from genome-wide association studies (GWAS). We found that the Tag of DRB1*1501, rs3135388 A allele, correlated with high expression of DRB1, DRB5 and DQB1 genes in a Caucasian population. In quantitative terms, the MS-risk AA genotype carriers of rs3135388 were associated with 15.7-, 5.2- and 8.3-fold higher expression of DQB1, DRB5 and DRB1, respectively, than the non-risk GG carriers. The haplotype analysis of expression-associated variants in a Spanish MS cohort revealed that high expression of DRB1 and DQB1 alone did not contribute to the disease. However, in Caucasian, Asian and African American populations, the DRB1*1501 allele was always highly expressed. In other immune related diseases such as type 1 diabetes, inflammatory bowel disease, ulcerative colitis, asthma and IgA deficiency, the best GWAS-associated HLA SNPs were also eQTLs for different HLA Class II genes. Our data suggest that the DR/DQ expression levels, together with specific structural properties of alleles, seem to be the causal effect in MS and in other immunopathologies rather than specific antigen presentation alone. PMID:22253788

Inherited variants in regulatory T cell genes and outcome of ovarian cancer.

PubMed

Goode, Ellen L; DeRycke, Melissa; Kalli, Kimberly R; Oberg, Ann L; Cunningham, Julie M; Maurer, Matthew J; Fridley, Brooke L; Armasu, Sebastian M; Serie, Daniel J; Ramar, Priya; Goergen, Krista; Vierkant, Robert A; Rider, David N; Sicotte, Hugues; Wang, Chen; Winterhoff, Boris; Phelan, Catherine M; Schildkraut, Joellen M; Weber, Rachel P; Iversen, Ed; Berchuck, Andrew; Sutphen, Rebecca; Birrer, Michael J; Hampras, Shalaka; Preus, Leah; Gayther, Simon A; Ramus, Susan J; Wentzensen, Nicolas; Yang, Hannah P; Garcia-Closas, Montserrat; Song, Honglin; Tyrer, Jonathan; Pharoah, Paul P D; Konecny, Gottfried; Sellers, Thomas A; Ness, Roberta B; Sucheston, Lara E; Odunsi, Kunle; Hartmann, Lynn C; Moysich, Kirsten B; Knutson, Keith L

2013-01-01

Although ovarian cancer is the most lethal of gynecologic malignancies, wide variation in outcome following conventional therapy continues to exist. The presence of tumor-infiltrating regulatory T cells (Tregs) has a role in outcome of this disease, and a growing body of data supports the existence of inherited prognostic factors. However, the role of inherited variants in genes encoding Treg-related immune molecules has not been fully explored. We analyzed expression quantitative trait loci (eQTL) and sequence-based tagging single nucleotide polymorphisms (tagSNPs) for 54 genes associated with Tregs in 3,662 invasive ovarian cancer cases. With adjustment for known prognostic factors, suggestive results were observed among rarer histological subtypes; poorer survival was associated with minor alleles at SNPs in RGS1 (clear cell, rs10921202, p=2.7×10(-5)), LRRC32 and TNFRSF18/TNFRSF4 (mucinous, rs3781699, p=4.5×10(-4), and rs3753348, p=9.0×10(-4), respectively), and CD80 (endometrioid, rs13071247, p=8.0×10(-4)). Fo0r the latter, correlative data support a CD80 rs13071247 genotype association with CD80 tumor RNA expression (p=0.006). An additional eQTL SNP in CD80 was associated with shorter survival (rs7804190, p=8.1×10(-4)) among all cases combined. As the products of these genes are known to affect induction, trafficking, or immunosuppressive function of Tregs, these results suggest the need for follow-up phenotypic studies.

Interchromosomal Transfer of Immune Regulation During Infection of Barley with the Powdery Mildew Pathogen

PubMed Central

Surana, Priyanka; Xu, Ruo; Fuerst, Gregory; Chapman, Antony V. E.; Nettleton, Dan; Wise, Roger P.

2017-01-01

Powdery mildew pathogens colonize over 9500 plant species, causing critical yield loss. The Ascomycete fungus, Blumeria graminis f. sp. hordei (Bgh), causes powdery mildew disease in barley (Hordeum vulgare L.). Successful infection begins with penetration of host epidermal cells, culminating in haustorial feeding structures, facilitating delivery of fungal effectors to the plant and exchange of nutrients from host to pathogen. We used expression Quantitative Trait Locus (eQTL) analysis to dissect the temporal control of immunity-associated gene expression in a doubled haploid barley population challenged with Bgh. Two highly significant regions possessing trans eQTL were identified near the telomeric ends of chromosomes (Chr) 2HL and 1HS. Within these regions reside diverse resistance loci derived from barley landrace H. laevigatum (MlLa) and H. vulgare cv. Algerian (Mla1), which associate with the altered expression of 961 and 3296 genes during fungal penetration of the host and haustorial development, respectively. Regulatory control of transcript levels for 299 of the 961 genes is reprioritized from MlLa on 2HL to Mla1 on 1HS as infection progresses, with 292 of the 299 alternating the allele responsible for higher expression, including Adaptin Protein-2 subunit μ AP2M and Vesicle Associated Membrane Protein VAMP72 subfamily members VAMP721/722. AP2M mediates effector-triggered immunity (ETI) via endocytosis of plasma membrane receptor components. VAMP721/722 and SNAP33 form a Soluble N-ethylmaleimide-sensitive factor Attachment Protein REceptor (SNARE) complex with SYP121 (PEN1), which is engaged in pathogen associated molecular pattern (PAMP)-triggered immunity via exocytosis. We postulate that genes regulated by alternate chromosomal positions are repurposed as part of a conserved immune complex to respond to different pathogen attack scenarios. PMID:28790145

QuASAR: quantitative allele-specific analysis of reads.

PubMed

Harvey, Chris T; Moyerbrailean, Gregory A; Davis, Gordon O; Wen, Xiaoquan; Luca, Francesca; Pique-Regi, Roger

2015-04-15

Expression quantitative trait loci (eQTL) studies have discovered thousands of genetic variants that regulate gene expression, enabling a better understanding of the functional role of non-coding sequences. However, eQTL studies are costly, requiring large sample sizes and genome-wide genotyping of each sample. In contrast, analysis of allele-specific expression (ASE) is becoming a popular approach to detect the effect of genetic variation on gene expression, even within a single individual. This is typically achieved by counting the number of RNA-seq reads matching each allele at heterozygous sites and testing the null hypothesis of a 1:1 allelic ratio. In principle, when genotype information is not readily available, it could be inferred from the RNA-seq reads directly. However, there are currently no existing methods that jointly infer genotypes and conduct ASE inference, while considering uncertainty in the genotype calls. We present QuASAR, quantitative allele-specific analysis of reads, a novel statistical learning method for jointly detecting heterozygous genotypes and inferring ASE. The proposed ASE inference step takes into consideration the uncertainty in the genotype calls, while including parameters that model base-call errors in sequencing and allelic over-dispersion. We validated our method with experimental data for which high-quality genotypes are available. Results for an additional dataset with multiple replicates at different sequencing depths demonstrate that QuASAR is a powerful tool for ASE analysis when genotypes are not available. http://github.com/piquelab/QuASAR. fluca@wayne.edu or rpique@wayne.edu Supplementary Material is available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Identification of salt-tolerant QTLs with strong genetic background effect using two sets of reciprocal introgression lines in rice.

PubMed

Cheng, Lirui; Wang, Yun; Meng, Lijun; Hu, Xia; Cui, Yanru; Sun, Yong; Zhu, Linghua; Ali, Jauhar; Xu, Jianlong; Li, Zhikang

2012-01-01

Effect of genetic background on detection of quantitative trait locus (QTL) governing salinity tolerance (ST) was studied using two sets of reciprocal introgression lines (ILs) derived from a cross between a moderately salinity tolerant japonica variety, Xiushui09 from China, and a drought tolerant but salinity susceptible indica breeding line, IR2061-520-6-9 from the Philippines. Salt toxicity symptoms (SST) on leaves, days to seedling survival (DSS), and sodium and potassium uptake by shoots were measured under salinity stress of 140 mmol/L of NaCl. A total of 47 QTLs, including 26 main-effect QTLs (M-QTLs) and 21 epistatic QTLs (E-QTLs), were identified from the two sets of reciprocal ILs. Among the 26 M-QTLs, only four (15.4%) were shared in the reciprocal backgrounds while no shared E-QTLs were detected, indicating that ST QTLs, especially E-QTLs, were very specific to the genetic background. Further, 78.6% of the M-QTLs for SST and DSS identified in the reciprocal ILs were also detected in the recombinant inbred lines (RILs) from the same cross, which clearly brings out the background effect on ST QTL detection and its utilization in ST breeding. The detection of ILs with various levels of pyramiding of nonallelic M-QTL alleles for ST from Xiushui09 into IR2061-520-6-9 allowed us to further improve the ST in rice.

Characterization of candidate genes in inflammatory bowel disease–associated risk loci

PubMed Central

Peloquin, Joanna M.; Sartor, R. Balfour; Newberry, Rodney D.; McGovern, Dermot P.; Yajnik, Vijay; Lira, Sergio A.

2016-01-01

GWAS have linked SNPs to risk of inflammatory bowel disease (IBD), but a systematic characterization of disease-associated genes has been lacking. Prior studies utilized microarrays that did not capture many genes encoded within risk loci or defined expression quantitative trait loci (eQTLs) using peripheral blood, which is not the target tissue in IBD. To address these gaps, we sought to characterize the expression of IBD-associated risk genes in disease-relevant tissues and in the setting of active IBD. Terminal ileal (TI) and colonic mucosal tissues were obtained from patients with Crohn’s disease or ulcerative colitis and from healthy controls. We developed a NanoString code set to profile 678 genes within IBD risk loci. A subset of patients and controls were genotyped for IBD-associated risk SNPs. Analyses included differential expression and variance analysis, weighted gene coexpression network analysis, and eQTL analysis. We identified 116 genes that discriminate between healthy TI and colon samples and uncovered patterns in variance of gene expression that highlight heterogeneity of disease. We identified 107 coexpressed gene pairs for which transcriptional regulation is either conserved or reversed in an inflammation-independent or -dependent manner. We demonstrate that on average approximately 60% of disease-associated genes are differentially expressed in inflamed tissue. Last, we identified eQTLs with either genotype-only effects on expression or an interaction effect between genotype and inflammation. Our data reinforce tissue specificity of expression in disease-associated candidate genes, highlight genes and gene pairs that are regulated in disease-relevant tissue and inflammation, and provide a foundation to advance the understanding of IBD pathogenesis. PMID:27668286

Topological analysis of metabolic networks integrating co-segregating transcriptomes and metabolomes in type 2 diabetic rat congenic series.

PubMed

Dumas, Marc-Emmanuel; Domange, Céline; Calderari, Sophie; Martínez, Andrea Rodríguez; Ayala, Rafael; Wilder, Steven P; Suárez-Zamorano, Nicolas; Collins, Stephan C; Wallis, Robert H; Gu, Quan; Wang, Yulan; Hue, Christophe; Otto, Georg W; Argoud, Karène; Navratil, Vincent; Mitchell, Steve C; Lindon, John C; Holmes, Elaine; Cazier, Jean-Baptiste; Nicholson, Jeremy K; Gauguier, Dominique

2016-09-30

The genetic regulation of metabolic phenotypes (i.e., metabotypes) in type 2 diabetes mellitus occurs through complex organ-specific cellular mechanisms and networks contributing to impaired insulin secretion and insulin resistance. Genome-wide gene expression profiling systems can dissect the genetic contributions to metabolome and transcriptome regulations. The integrative analysis of multiple gene expression traits and metabolic phenotypes (i.e., metabotypes) together with their underlying genetic regulation remains a challenge. Here, we introduce a systems genetics approach based on the topological analysis of a combined molecular network made of genes and metabolites identified through expression and metabotype quantitative trait locus mapping (i.e., eQTL and mQTL) to prioritise biological characterisation of candidate genes and traits. We used systematic metabotyping by 1 H NMR spectroscopy and genome-wide gene expression in white adipose tissue to map molecular phenotypes to genomic blocks associated with obesity and insulin secretion in a series of rat congenic strains derived from spontaneously diabetic Goto-Kakizaki (GK) and normoglycemic Brown-Norway (BN) rats. We implemented a network biology strategy approach to visualize the shortest paths between metabolites and genes significantly associated with each genomic block. Despite strong genomic similarities (95-99 %) among congenics, each strain exhibited specific patterns of gene expression and metabotypes, reflecting the metabolic consequences of series of linked genetic polymorphisms in the congenic intervals. We subsequently used the congenic panel to map quantitative trait loci underlying specific mQTLs and genome-wide eQTLs. Variation in key metabolites like glucose, succinate, lactate, or 3-hydroxybutyrate and second messenger precursors like inositol was associated with several independent genomic intervals, indicating functional redundancy in these regions. To navigate through the complexity of these association networks we mapped candidate genes and metabolites onto metabolic pathways and implemented a shortest path strategy to highlight potential mechanistic links between metabolites and transcripts at colocalized mQTLs and eQTLs. Minimizing the shortest path length drove prioritization of biological validations by gene silencing. These results underline the importance of network-based integration of multilevel systems genetics datasets to improve understanding of the genetic architecture of metabotype and transcriptomic regulation and to characterize novel functional roles for genes determining tissue-specific metabolism.

LSCC SNP variant regulates SOX2 modulation of VDAC3.

PubMed

Chyr, Jacqueline; Guo, Dongmin; Zhou, Xiaobo

2018-04-27

Lung squamous cell carcinoma (LSCC) is a genomically complex malignancy with no effective treatments. Recent studies have found a large number of DNA alterations such as SOX2 amplification in LSCC patients. As a stem cell transcription factor, SOX2 is important for the maintenance of pluripotent cells and may play a role in cancer. To study the downstream mechanisms of SOX2, we employed expression quantitative trait loci (eQTLs) technology to investigate how the presence of SOX2 affects the expression of target genes. We discovered unique eQTLs, such as rs798827-VDAC3 (FDR p -value = 0.0034), that are only found in SOX2-active patients but not in SOX2-inactive patients. SNP rs798827 is within strong linkage disequilibrium ( r 2 = 1) to rs58163073, where rs58163073 [T] allele increases the binding affinity of SOX2 and allele [TA] decreases it. In our analysis, SOX2 silencing downregulates VDAC3 in two LSCC cell lines. Chromatin conformation capturing data indicates that this SNP is located within the same Topologically Associating Domain (TAD) of VDAC3, further suggesting SOX2's role in the regulation of VDAC3 through the binding of rs58163073. By first subgrouping patients based on SOX2 activity, we made more relevant eQTL discoveries and our analysis can be applied to other diseases.

Conditional entropy in variation-adjusted windows detects selection signatures associated with expression quantitative trait loci (eQTLs)

PubMed Central

2015-01-01

Background Over the past 50,000 years, shifts in human-environmental or human-human interactions shaped genetic differences within and among human populations, including variants under positive selection. Shaped by environmental factors, such variants influence the genetics of modern health, disease, and treatment outcome. Because evolutionary processes tend to act on gene regulation, we test whether regulatory variants are under positive selection. We introduce a new approach to enhance detection of genetic markers undergoing positive selection, using conditional entropy to capture recent local selection signals. Results We use conditional logistic regression to compare our Adjusted Haplotype Conditional Entropy (H|H) measure of positive selection to existing positive selection measures. H|H and existing measures were applied to published regulatory variants acting in cis (cis-eQTLs), with conditional logistic regression testing whether regulatory variants undergo stronger positive selection than the surrounding gene. These cis-eQTLs were drawn from six independent studies of genotype and RNA expression. The conditional logistic regression shows that, overall, H|H is substantially more powerful than existing positive-selection methods in identifying cis-eQTLs against other Single Nucleotide Polymorphisms (SNPs) in the same genes. When broken down by Gene Ontology, H|H predictions are particularly strong in some biological process categories, where regulatory variants are under strong positive selection compared to the bulk of the gene, distinct from those GO categories under overall positive selection. . However, cis-eQTLs in a second group of genes lack positive selection signatures detectable by H|H, consistent with ancient short haplotypes compared to the surrounding gene (for example, in innate immunity GO:0042742); under such other modes of selection, H|H would not be expected to be a strong predictor.. These conditional logistic regression models are adjusted for Minor allele frequency(MAF); otherwise, ascertainment bias is a huge factor in all eQTL data sets. Relationships between Gene Ontology categories, positive selection and eQTL specificity were replicated with H|H in a single larger data set. Our measure, Adjusted Haplotype Conditional Entropy (H|H), was essential in generating all of the results above because it: 1) is a stronger overall predictor for eQTLs than comparable existing approaches, and 2) shows low sequential auto-correlation, overcoming problems with convergence of these conditional regression statistical models. Conclusions Our new method, H|H, provides a consistently more robust signal associated with cis-eQTLs compared to existing methods. We interpret this to indicate that some cis-eQTLs are under positive selection compared to their surrounding genes. Conditional entropy indicative of a selective sweep is an especially strong predictor of eQTLs for genes in several biological processes of medical interest. Where conditional entropy is a weak or negative predictor of eQTLs, such as innate immune genes, this would be consistent with balancing selection acting on such eQTLs over long time periods. Different measures of selection may be needed for variant prioritization under other modes of evolutionary selection. PMID:26111110

Genetic drivers of von Willebrand Factor levels in an ischemic stroke population and association with risk for recurrent stroke

PubMed Central

Williams, Stephen R; Hsu, Fang-Chi; Keene, Keith L; Chen, Wei-Min; Dzhivhuho, Godfrey; Rowles, Joe L; Southerland, Andrew M; Furie, Karen L; Rich, Stephen S; Worrall, Bradford B; Sale, Michèle M

2017-01-01

Background and Purpose von Willebrand Factor (vWF) plays an important role in thrombus formation during cerebrovascular damage. We sought to investigate the potential role of circulating vWF in recurrent cerebrovascular events and identify genetic contributors to variation in vWF level in an ischemic stroke population. Methods We analyzed the effect of circulating vWF on risk of recurrent stroke using survival models in the Vitamin Intervention for Stroke Prevention (VISP) trial as well as the utility of vWF in reclassification over traditional factors. We conducted a genome-wide association study (GWAS) with imputation, based upon 1000 Genomes Project data, for circulating vWF levels and then interrogated loci previously associated with vWF levels. We performed expression quantitative trait locus (eQTL) analysis for vWF across different tissues. Results Elevated vWF levels were associated with increased risk for recurrent stroke in VISP. Adding vWF to traditional clinical parameters also improved recurrent stroke risk prediction. We identified SNPs significantly associated with circulating vWF at the ABO locus (p < 5×10-8) and replicated findings from previous genetic associations of vWF levels in humans. eQTL analyses demonstrate that most associated ABO SNPs were also associated with vWF gene expression. Conclusions Elevated vWF levels are associated with recurrent stroke in VISP. In the VISP population, genetic determinants of vWF levels that impact vWF gene expression were identified. These data add to our knowledge of the pathophysiologic and genetic basis for recurrent stroke risk, and may have implications for clinical care decision-making. PMID:28495826

Susceptibility loci of CNOT6 in the general mRNA degradation pathway and lung cancer risk - a re-analysis of eight GWASs

PubMed Central

Zhou, Fei; Wang, Yanru; Liu, Hongliang; Ready, Neal; Han, Younghun; Hung, Rayjean J.; Brhane, Yonathan; McLaughlin, John; Brennan, Paul; Bickeböller, Heike; Rosenberger, Albert; Houlston, Richard S.; Caporaso, Neil; Landi, Maria Teresa; Brüske, Irene; Risch, Angela; Ye, Yuanqing; Wu, Xifeng; Christiani, David C.; Goodman, Gary; Chen, Chu; Amos, Christopher I.; Qingyi, Wei

2017-01-01

Purpose mRNA degradation is an important regulatory step for controlling gene expression and cell functions. Genetic abnormalities of the genes involved in mRNA degradation were found to be associated with cancer risks. Therefore, we systematically investigated the roles of genetic variants of genes in the general mRNA degradation pathway in lung cancer risk. Experimental design Meta-analyses were conducted in six lung cancer genome-wide association studies (GWASs) from the Transdisciplinary Research in Cancer of the Lung and additional two GWASs from Harvard University and deCODE in the International Lung Cancer Consortium. Expression quantitative trait loci analysis (eQTL) was used for in silico functional validation of the identified significant susceptibility loci. Results This pathway-based analysis included 4,603 single nucleotide polymorphisms (SNP) in 68 genes in 14,463 lung cancer cases and 44,188 controls, of which 20 SNPs were found to be associated with lung cancer risk with a false discovery rate threshold of <0.05. Among the 11 newly identified SNPs in CNOT6, which were in high linkage disequilibrium, the rs2453176 with a RegulomDB score “1f” was chosen as the tag SNP for further analysis. We found that the rs2453176 T allele was significantly associated with lung cancer risk (odds ratio=1.11, 95% confidence interval=1.04–1.18, P=0.001) in the eight GWASs. In the eQTL analysis, we found that levels of CNOT6 mRNA expression were significantly correlated with the rs2453176 T allele, which provided additional biological basis for the observed positive association. Conclusion The CNOT6 rs2453176 SNP may be a new functional susceptible locus for lung cancer risk. PMID:27805284

Susceptibility loci of CNOT6 in the general mRNA degradation pathway and lung cancer risk-A re-analysis of eight GWASs.

PubMed

Zhou, Fei; Wang, Yanru; Liu, Hongliang; Ready, Neal; Han, Younghun; Hung, Rayjean J; Brhane, Yonathan; McLaughlin, John; Brennan, Paul; Bickeböller, Heike; Rosenberger, Albert; Houlston, Richard S; Caporaso, Neil; Landi, Maria Teresa; Brüske, Irene; Risch, Angela; Ye, Yuanqing; Wu, Xifeng; Christiani, David C; Goodman, Gary; Chen, Chu; Amos, Christopher I; Wei, Qingyi

2017-04-01

mRNA degradation is an important regulatory step for controlling gene expression and cell functions. Genetic abnormalities involved in mRNA degradation genes were found to be associated with cancer risks. Therefore, we systematically investigated the roles of genetic variants in the general mRNA degradation pathway in lung cancer risk. Meta-analyses were conducted using summary data from six lung cancer genome-wide association studies (GWASs) from the Transdisciplinary Research in Cancer of the Lung and additional two GWASs from Harvard University and deCODE in the International Lung Cancer Consortium. Expression quantitative trait loci analysis (eQTL) was used for in silico functional validation of the identified significant susceptibility loci. This pathway-based analysis included 6816 single nucleotide polymorphisms (SNP) in 68 genes in 14 463 lung cancer cases and 44 188 controls. In the single-locus analysis, we found that 20 SNPs were associated with lung cancer risk with a false discovery rate threshold of <0.05. Among the 11 newly identified SNPs in CNOT6, which were in high linkage disequilibrium, the rs2453176 with a RegulomDB score "1f" was chosen as the tagSNP for further analysis. We found that the rs2453176 T allele was significantly associated with lung cancer risk (odds ratio = 1.11, 95% confidence interval = 1.04-1.18) in the eight GWASs. In the eQTL analysis, we found that levels of CNOT6 mRNA expression were significantly correlated with the rs2453176 T allele, which provided additional biological basis for the observed positive association. The CNOT6 rs2453176 SNP may be a new functional susceptible locus for lung cancer risk. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Genome-wide QTL and bulked transcriptomic analysis reveals new candidate genes for the control of tuber carotenoid content in potato (Solanum tuberosum L.).

PubMed

Campbell, Raymond; Pont, Simon D A; Morris, Jenny A; McKenzie, Gaynor; Sharma, Sanjeev Kumar; Hedley, Pete E; Ramsay, Gavin; Bryan, Glenn J; Taylor, Mark A

2014-09-01

Genome-wide QTL analysis of potato tuber carotenoid content was investigated in populations of Solanum tuberosum Group Phureja that segregate for flesh colour, revealing a novel major QTL on chromosome 9. The carotenoid content of edible plant storage organs is a key nutritional and quality trait. Although the structural genes that encode the biosynthetic enzymes are well characterised, much less is known about the factors that determine overall storage organ content. In this study, genome-wide QTL mapping, in concert with an efficient 'genetical genomics' analysis using bulked samples, has been employed to investigate the genetic architecture of potato tuber carotenoid content. Two diploid populations of Solanum tuberosum Group Phureja were genotyped (AFLP, SSR and DArT markers) and analysed for their tuber carotenoid content over two growing seasons. Common to both populations were QTL that explained relatively small proportions of the variation in constituent carotenoids and a major QTL on chromosome 3 explaining up to 71 % of the variation in carotenoid content. In one of the populations (01H15), a second major carotenoid QTL was identified on chromosome 9, explaining up to 20 % of the phenotypic variation. Whereas the major chromosome 3 QTL was likely to be due to an allele of a gene encoding β-carotene hydroxylase, no known carotenoid biosynthetic genes are located in the vicinity of the chromosome 9 QTL. A unique expression profiling strategy using phenotypically distinct bulks comprised individuals with similar carotenoid content provided further support for the QTL mapping to chromosome 9. This study shows the potential of using the potato genome sequence to link genetic maps to data arising from eQTL approaches to enhance the discovery of candidate genes underlying QTLs.

Functional analysis of the TRIB1 associated locus linked to plasma triglycerides and coronary artery disease.

PubMed

Douvris, Adrianna; Soubeyrand, Sébastien; Naing, Thet; Martinuk, Amy; Nikpay, Majid; Williams, Andrew; Buick, Julie; Yauk, Carole; McPherson, Ruth

2014-06-03

The TRIB1 locus has been linked to hepatic triglyceride metabolism in mice and to plasma triglycerides and coronary artery disease in humans. The lipid-associated single nucleotide polymorphisms (SNPs), identified by genome-wide association studies, are located ≈30 kb downstream from TRIB1, suggesting complex regulatory effects on genes or pathways relevant to hepatic triglyceride metabolism. The goal of this study was to investigate the functional relationship between common SNPs at the TRIB1 locus and plasma lipid traits. Characterization of the risk locus reveals that it encompasses a gene, TRIB1-associated locus (TRIBAL), composed of a well-conserved promoter region and an alternatively spliced transcript. Bioinformatic analysis and resequencing identified a single SNP, rs2001844, within the promoter region that associates with increased plasma triglycerides and reduced high-density lipoprotein cholesterol and coronary artery disease risk. Further, correction for triglycerides as a covariate indicated that the genome-wide association studies association is largely dependent on triglycerides. In addition, we show that rs2001844 is an expression trait locus (eQTL) for TRIB1 expression in blood and alters TRIBAL promoter activity in a reporter assay model. The TRIBAL transcript has features typical of long noncoding RNAs, including poor sequence conservation. Modulation of TRIBAL expression had limited impact on either TRIB1 or lipid regulatory genes mRNA levels in human hepatocyte models. In contrast, TRIB1 knockdown markedly increased TRIBAL expression in HepG2 cells and primary human hepatocytes. These studies demonstrate an interplay between a novel locus, TRIBAL, and TRIB1. TRIBAL is located in the genome-wide association studies identified risk locus, responds to altered expression of TRIB1, harbors a risk SNP that is an eQTL for TRIB1 expression, and associates with plasma triglyceride concentrations. © 2014 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Functional Analysis of the TRIB1 Associated Locus Linked to Plasma Triglycerides and Coronary Artery Disease

PubMed Central

Douvris, Adrianna; Soubeyrand, Sébastien; Naing, Thet; Martinuk, Amy; Nikpay, Majid; Williams, Andrew; Buick, Julie; Yauk, Carole; McPherson, Ruth

2014-01-01

Background The TRIB1 locus has been linked to hepatic triglyceride metabolism in mice and to plasma triglycerides and coronary artery disease in humans. The lipid‐associated single nucleotide polymorphisms (SNPs), identified by genome‐wide association studies, are located ≈30 kb downstream from TRIB1, suggesting complex regulatory effects on genes or pathways relevant to hepatic triglyceride metabolism. The goal of this study was to investigate the functional relationship between common SNPs at the TRIB1 locus and plasma lipid traits. Methods and Results Characterization of the risk locus reveals that it encompasses a gene, TRIB1‐associated locus (TRIBAL), composed of a well‐conserved promoter region and an alternatively spliced transcript. Bioinformatic analysis and resequencing identified a single SNP, rs2001844, within the promoter region that associates with increased plasma triglycerides and reduced high‐density lipoprotein cholesterol and coronary artery disease risk. Further, correction for triglycerides as a covariate indicated that the genome‐wide association studies association is largely dependent on triglycerides. In addition, we show that rs2001844 is an expression trait locus (eQTL) for TRIB1 expression in blood and alters TRIBAL promoter activity in a reporter assay model. The TRIBAL transcript has features typical of long noncoding RNAs, including poor sequence conservation. Modulation of TRIBAL expression had limited impact on either TRIB1 or lipid regulatory genes mRNA levels in human hepatocyte models. In contrast, TRIB1 knockdown markedly increased TRIBAL expression in HepG2 cells and primary human hepatocytes. Conclusions These studies demonstrate an interplay between a novel locus, TRIBAL, and TRIB1. TRIBAL is located in the genome‐wide association studies identified risk locus, responds to altered expression of TRIB1, harbors a risk SNP that is an eQTL for TRIB1 expression, and associates with plasma triglyceride concentrations. PMID:24895164

A Gene Module-Based eQTL Analysis Prioritizing Disease Genes and Pathways in Kidney Cancer.

PubMed

Yang, Mary Qu; Li, Dan; Yang, William; Zhang, Yifan; Liu, Jun; Tong, Weida

2017-01-01

Clear cell renal cell carcinoma (ccRCC) is the most common and most aggressive form of renal cell cancer (RCC). The incidence of RCC has increased steadily in recent years. The pathogenesis of renal cell cancer remains poorly understood. Many of the tumor suppressor genes, oncogenes, and dysregulated pathways in ccRCC need to be revealed for improvement of the overall clinical outlook of the disease. Here, we developed a systems biology approach to prioritize the somatic mutated genes that lead to dysregulation of pathways in ccRCC. The method integrated multi-layer information to infer causative mutations and disease genes. First, we identified differential gene modules in ccRCC by coupling transcriptome and protein-protein interactions. Each of these modules consisted of interacting genes that were involved in similar biological processes and their combined expression alterations were significantly associated with disease type. Then, subsequent gene module-based eQTL analysis revealed somatic mutated genes that had driven the expression alterations of differential gene modules. Our study yielded a list of candidate disease genes, including several known ccRCC causative genes such as BAP1 and PBRM1 , as well as novel genes such as NOD2, RRM1, CSRNP1, SLC4A2, TTLL1 and CNTN1. The differential gene modules and their driver genes revealed by our study provided a new perspective for understanding the molecular mechanisms underlying the disease. Moreover, we validated the results in independent ccRCC patient datasets. Our study provided a new method for prioritizing disease genes and pathways.

Inherited Variants in Regulatory T Cell Genes and Outcome of Ovarian Cancer

PubMed Central

Goode, Ellen L.; DeRycke, Melissa; Kalli, Kimberly R.; Oberg, Ann L.; Cunningham, Julie M.; Maurer, Matthew J.; Fridley, Brooke L.; Armasu, Sebastian M.; Serie, Daniel J.; Ramar, Priya; Goergen, Krista; Vierkant, Robert A.; Rider, David N.; Sicotte, Hugues; Wang, Chen; Winterhoff, Boris; Phelan, Catherine M.; Schildkraut, Joellen M.; Weber, Rachel P.; Iversen, Ed; Berchuck, Andrew; Sutphen, Rebecca; Birrer, Michael J.; Hampras, Shalaka; Preus, Leah; Gayther, Simon A.; Ramus, Susan J.; Wentzensen, Nicolas; Yang, Hannah P.; Garcia-Closas, Montserrat; Song, Honglin; Tyrer, Jonathan; Pharoah, Paul P. D.; Konecny, Gottfried; Sellers, Thomas A.; Ness, Roberta B.; Sucheston, Lara E.; Odunsi, Kunle; Hartmann, Lynn C.; Moysich, Kirsten B.; Knutson, Keith L.

2013-01-01

Although ovarian cancer is the most lethal of gynecologic malignancies, wide variation in outcome following conventional therapy continues to exist. The presence of tumor-infiltrating regulatory T cells (Tregs) has a role in outcome of this disease, and a growing body of data supports the existence of inherited prognostic factors. However, the role of inherited variants in genes encoding Treg-related immune molecules has not been fully explored. We analyzed expression quantitative trait loci (eQTL) and sequence-based tagging single nucleotide polymorphisms (tagSNPs) for 54 genes associated with Tregs in 3,662 invasive ovarian cancer cases. With adjustment for known prognostic factors, suggestive results were observed among rarer histological subtypes; poorer survival was associated with minor alleles at SNPs in RGS1 (clear cell, rs10921202, p = 2.7×10−5), LRRC32 and TNFRSF18/TNFRSF4 (mucinous, rs3781699, p = 4.5×10−4, and rs3753348, p = 9.0×10−4, respectively), and CD80 (endometrioid, rs13071247, p = 8.0×10−4). Fo0r the latter, correlative data support a CD80 rs13071247 genotype association with CD80 tumor RNA expression (p = 0.006). An additional eQTL SNP in CD80 was associated with shorter survival (rs7804190, p = 8.1×10−4) among all cases combined. As the products of these genes are known to affect induction, trafficking, or immunosuppressive function of Tregs, these results suggest the need for follow-up phenotypic studies. PMID:23382860

Genome scan study of prostate cancer in Arabs: identification of three genomic regions with multiple prostate cancer susceptibility loci in Tunisians.

PubMed

Shan, Jingxuan; Al-Rumaihi, Khalid; Rabah, Danny; Al-Bozom, Issam; Kizhakayil, Dhanya; Farhat, Karim; Al-Said, Sami; Kfoury, Hala; Dsouza, Shoba P; Rowe, Jillian; Khalak, Hanif G; Jafri, Shahzad; Aigha, Idil I; Chouchane, Lotfi

2013-05-13

Large databases focused on genetic susceptibility to prostate cancer have been accumulated from population studies of different ancestries, including Europeans and African-Americans. Arab populations, however, have been only rarely studied. Using Affymetrix Genome-Wide Human SNP Array 6, we conducted a genome-wide association study (GWAS) in which 534,781 single nucleotide polymorphisms (SNPs) were genotyped in 221 Tunisians (90 prostate cancer patients and 131 age-matched healthy controls). TaqMan SNP Genotyping Assays on 11 prostate cancer associated SNPs were performed in a distinct cohort of 337 individuals from Arab ancestry living in Qatar and Saudi Arabia (155 prostate cancer patients and 182 age-matched controls). In-silico expression quantitative trait locus (eQTL) analysis along with mRNA quantification of nearby genes was performed to identify loci potentially cis-regulated by the identified SNPs. Three chromosomal regions, encompassing 14 SNPs, are significantly associated with prostate cancer risk in the Tunisian population (P = 1 × 10-4 to P = 1 × 10-5). In addition to SNPs located on chromosome 17q21, previously found associated with prostate cancer in Western populations, two novel chromosomal regions are revealed on chromosome 9p24 and 22q13. eQTL analysis and mRNA quantification indicate that the prostate cancer associated SNPs of chromosome 17 could enhance the expression of STAT5B gene. Our findings, identifying novel GWAS prostate cancer susceptibility loci, indicate that prostate cancer genetic risk factors could be ethnic specific.

Combining Genome Wide Association Study and lung eQTL analysis provides evidence for novel genes associated with asthma

PubMed Central

Nieuwenhuis, Maartje A.; Siedlinski, Matteusz; van den Berge, Maarten; Granell, Raquel; Li, Xingnan; Niens, Marijke; van der Vlies, Pieter; Altmüller, Janine; Nürnberg, Peter; Kerkhof, Marjan; van Schayck, Onno C.; Riemersma, Ronald A.; van der Molen, Thys; de Monchy, Jan G.; Bossé, Yohan; Sandford, Andrew; Bruijnzeel-Koomen, Carla A.; van Wijk, Roy G.; ten Hacken, Nick H.; Timens, Wim; Boezen, H. Marike; Henderson, John; Kabesch, Michael; Vonk, Judith M.; Postma, Dirkje S.; Koppelman, Gerard H.

2016-01-01

Background Genome wide association studies (GWAS) of asthma have identified single nucleotide polymorphisms (SNPs) that modestly increase the risk for asthma. This could be due to phenotypic heterogeneity of asthma. Bronchial hyperresponsiveness (BHR) is a phenotypic hallmark of asthma. We aim to identify susceptibility genes for asthma combined with BHR and analyse the presence of cis-eQTLs among replicated SNPs. Secondly, we compare the genetic association of SNPs previously associated with (doctor diagnosed) asthma to our GWAS of asthma with BHR. Methods A GWAS was performed in 920 asthmatics with BHR and 980 controls. Top SNPs of our GWAS were analysed in four replication cohorts and lung cis-eQTL analysis was performed on replicated SNPs. We investigated association of SNPs previously associated with asthma in our data. Results 368 SNPs were followed up for replication. Six SNPs in genes encoding ABI3BP, NAF1, MICA and the 17q21 locus replicated in one or more cohorts, with one locus (17q21) achieving genome wide significance after meta-analysis. Five out of 6 replicated SNPs regulated 35 gene transcripts in whole lung. Eight of 20 asthma associated SNPs from previous GWAS were significantly associated with asthma and BHR. Three SNPs, in IL-33 and GSDMB, showed larger effect sizes in our data compared to published literature. Conclusions Combining GWAS with subsequent lung eQTL analysis revealed disease associated SNPs regulating lung mRNA expression levels of potential new asthma genes. Adding BHR to the asthma definition does not lead to an overall larger genetic effect size than analysing (doctor’s diagnosed) asthma. PMID:27439200

Identification of the Bile Acid Transporter Slco1a6 as a Candidate Gene That Broadly Affects Gene Expression in Mouse Pancreatic Islets

PubMed Central

Tian, Jianan; Keller, Mark P.; Oler, Angie T.; Rabaglia, Mary E.; Schueler, Kathryn L.; Stapleton, Donald S.; Broman, Aimee Teo; Zhao, Wen; Kendziorski, Christina; Yandell, Brian S.; Hagenbuch, Bruno; Broman, Karl W.; Attie, Alan D.

2015-01-01

We surveyed gene expression in six tissues in an F2 intercross between mouse strains C57BL/6J (abbreviated B6) and BTBR T+ tf/J (abbreviated BTBR) made genetically obese with the Leptinob mutation. We identified a number of expression quantitative trait loci (eQTL) affecting the expression of numerous genes distal to the locus, called trans-eQTL hotspots. Some of these trans-eQTL hotspots showed effects in multiple tissues, whereas some were specific to a single tissue. An unusually large number of transcripts (∼8% of genes) mapped in trans to a hotspot on chromosome 6, specifically in pancreatic islets. By considering the first two principal components of the expression of genes mapping to this region, we were able to convert the multivariate phenotype into a simple Mendelian trait. Fine mapping the locus by traditional methods reduced the QTL interval to a 298-kb region containing only three genes, including Slco1a6, one member of a large family of organic anion transporters. Direct genomic sequencing of all Slco1a6 exons identified a nonsynonymous coding SNP that converts a highly conserved proline residue at amino acid position 564 to serine. Molecular modeling suggests that Pro564 faces an aqueous pore within this 12-transmembrane domain-spanning protein. When transiently overexpressed in HEK293 cells, BTBR organic anion transporting polypeptide (OATP)1A6-mediated cellular uptake of the bile acid taurocholic acid (TCA) was enhanced compared to B6 OATP1A6. Our results suggest that genetic variation in Slco1a6 leads to altered transport of TCA (and potentially other bile acids) by pancreatic islets, resulting in broad gene regulation. PMID:26385979

Efficient Integrative Multi-SNP Association Analysis via Deterministic Approximation of Posteriors.

PubMed

Wen, Xiaoquan; Lee, Yeji; Luca, Francesca; Pique-Regi, Roger

2016-06-02

With the increasing availability of functional genomic data, incorporating genomic annotations into genetic association analysis has become a standard procedure. However, the existing methods often lack rigor and/or computational efficiency and consequently do not maximize the utility of functional annotations. In this paper, we propose a rigorous inference procedure to perform integrative association analysis incorporating genomic annotations for both traditional GWASs and emerging molecular QTL mapping studies. In particular, we propose an algorithm, named deterministic approximation of posteriors (DAP), which enables highly efficient and accurate joint enrichment analysis and identification of multiple causal variants. We use a series of simulation studies to highlight the power and computational efficiency of our proposed approach and further demonstrate it by analyzing the cross-population eQTL data from the GEUVADIS project and the multi-tissue eQTL data from the GTEx project. In particular, we find that genetic variants predicted to disrupt transcription factor binding sites are enriched in cis-eQTLs across all tissues. Moreover, the enrichment estimates obtained across the tissues are correlated with the cell types for which the annotations are derived. Copyright © 2016 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Bipartite Community Structure of eQTLs.

PubMed

Platig, John; Castaldi, Peter J; DeMeo, Dawn; Quackenbush, John

2016-09-01

Genome Wide Association Studies (GWAS) and expression quantitative trait locus (eQTL) analyses have identified genetic associations with a wide range of human phenotypes. However, many of these variants have weak effects and understanding their combined effect remains a challenge. One hypothesis is that multiple SNPs interact in complex networks to influence functional processes that ultimately lead to complex phenotypes, including disease states. Here we present CONDOR, a method that represents both cis- and trans-acting SNPs and the genes with which they are associated as a bipartite graph and then uses the modular structure of that graph to place SNPs into a functional context. In applying CONDOR to eQTLs in chronic obstructive pulmonary disease (COPD), we found the global network "hub" SNPs were devoid of disease associations through GWAS. However, the network was organized into 52 communities of SNPs and genes, many of which were enriched for genes in specific functional classes. We identified local hubs within each community ("core SNPs") and these were enriched for GWAS SNPs for COPD and many other diseases. These results speak to our intuition: rather than single SNPs influencing single genes, we see groups of SNPs associated with the expression of families of functionally related genes and that disease SNPs are associated with the perturbation of those functions. These methods are not limited in their application to COPD and can be used in the analysis of a wide variety of disease processes and other phenotypic traits.

Separate and combined effects of genetic variants and pre-treatment whole blood gene expression on response to exposure-based cognitive behavioural therapy for anxiety disorders.

PubMed

Coleman, Jonathan R I; Lester, Kathryn J; Roberts, Susanna; Keers, Robert; Lee, Sang Hyuck; De Jong, Simone; Gaspar, Héléna; Teismann, Tobias; Wannemüller, André; Schneider, Silvia; Jöhren, Peter; Margraf, Jürgen; Breen, Gerome; Eley, Thalia C

2017-04-01

Exposure-based cognitive behavioural therapy (eCBT) is an effective treatment for anxiety disorders. Response varies between individuals. Gene expression integrates genetic and environmental influences. We analysed the effect of gene expression and genetic markers separately and together on treatment response. Adult participants (n ≤ 181) diagnosed with panic disorder or a specific phobia underwent eCBT as part of standard care. Percentage decrease in the Clinical Global Impression severity rating was assessed across treatment, and between baseline and a 6-month follow-up. Associations with treatment response were assessed using expression data from 3,233 probes, and expression profiles clustered in a data- and literature-driven manner. A total of 3,343,497 genetic variants were used to predict treatment response alone and combined in polygenic risk scores. Genotype and expression data were combined in expression quantitative trait loci (eQTL) analyses. Expression levels were not associated with either treatment phenotype in any analysis. A total of 1,492 eQTLs were identified with q < 0.05, but interactions between genetic variants and treatment response did not affect expression levels significantly. Genetic variants did not significantly predict treatment response alone or in polygenic risk scores. We assessed gene expression alone and alongside genetic variants. No associations with treatment outcome were identified. Future studies require larger sample sizes to discover associations.

Identification of a Novel Mucin Gene HCG22 Associated With Steroid-Induced Ocular Hypertension

PubMed Central

Jeong, Shinwu; Patel, Nitin; Edlund, Christopher K.; Hartiala, Jaana; Hazelett, Dennis J.; Itakura, Tatsuo; Wu, Pei-Chang; Avery, Robert L.; Davis, Janet L.; Flynn, Harry W.; Lalwani, Geeta; Puliafito, Carmen A.; Wafapoor, Hussein; Hijikata, Minako; Keicho, Naoto; Gao, Xiaoyi; Argüeso, Pablo; Allayee, Hooman; Coetzee, Gerhard A.; Pletcher, Mathew T.; Conti, David V.; Schwartz, Stephen G.; Eaton, Alexander M.; Fini, M. Elizabeth

2015-01-01

Purpose. The pathophysiology of ocular hypertension (OH) leading to primary open-angle glaucoma shares many features with a secondary form of OH caused by treatment with glucocorticoids, but also exhibits distinct differences. In this study, a pharmacogenomics approach was taken to discover candidate genes for this disorder. Methods. A genome-wide association study was performed, followed by an independent candidate gene study, using a cohort enrolled from patients treated with off-label intravitreal triamcinolone, and handling change in IOP as a quantitative trait. Results. An intergenic quantitative trait locus (QTL) was identified at chromosome 6p21.33 near the 5′ end of HCG22 that attained the accepted statistical threshold for genome-level significance. The HCG22 transcript, encoding a novel mucin protein, was expressed in trabecular meshwork cells, and expression was stimulated by IL-1, and inhibited by triamcinolone acetate and TGF-β. Bioinformatic analysis defined the QTL as an approximately 4 kilobase (kb) linkage disequilibrium block containing 10 common single nucleotide polymorphisms (SNPs). Four of these SNPs were identified in the National Center for Biotechnology Information (NCBI) GTEx eQTL browser as modifiers of HCG22 expression. Most are predicted to disrupt or improve motifs for transcription factor binding, the most relevant being disruption of the glucocorticoid receptor binding motif. A second QTL was identified within the predicted signal peptide of the HCG22 encoded protein that could affect its secretion. Translation, O-glycosylation, and secretion of the predicted HCG22 protein was verified in cultured trabecular meshwork cells. Conclusions. Identification of two independent QTLs that could affect expression of the HCG22 mucin gene product via two different mechanisms (transcription or secretion) is highly suggestive of a role in steroid-induced OH. PMID:25813999

Expression-associated polymorphisms of CAV1-CAV2 affect intraocular pressure and high-tension glaucoma risk

PubMed Central

Kim, Sewon; Kim, Kyunglan; Heo, Dong Won; Kim, Jong-Sung; Park, Chan Kee; Kim, Chang-sik

2015-01-01

Purpose The human CAV1-CAV2 locus has been associated with susceptibility to primary open-angle glaucoma in four studies of Caucasian, Chinese, and Pakistani populations, although not in several other studies of non-Korean populations. In this study with Korean participants, the CAV1-CAV2 locus was investigated for associations with susceptibility to primary open-angle glaucoma accompanied by elevated intraocular pressure (IOP), namely, high-tension glaucoma (HTG), as well as with IOP elevation, which is a strong risk factor for glaucoma. Methods Two single nucleotide polymorphisms (SNPs) were genotyped in 1,161 Korean participants including 229 patients with HTG and 932 healthy controls and statistically examined for association with HTG susceptibility and IOP. One SNP was rs4236601 G>A, which had been reported in the original study, and the other SNP was rs17588172 T>G, which was perfectly correlated (r2=1) with another reported SNP rs1052990. Expression quantitative trait loci (eQTL) analysis was performed using GENe Expression VARiation (Genevar) data. Results Both SNPs were associated with HTG susceptibility, but the rs4236601 association disappeared when adjusted for the rs17588172 genotype and not vice versa. The minor allele G of rs17588172 was associated significantly with 1.5-fold increased susceptibility to HTG (p=0.0069) and marginally with IOP elevation (p=0.043) versus the major allele T. This minor allele was also associated with decreased CAV1 and CAV2 mRNA in skin and adipose according to the Genevar eQTL analysis. Conclusions The minor allele G of rs17588172 in the CAV1-CAV2 locus is associated with decreased expression of CAV1 and CAV2 in some tissues, marginally with IOP elevation, and consequently with increased susceptibility to HTG. PMID:26015768

XGR software for enhanced interpretation of genomic summary data, illustrated by application to immunological traits.

PubMed

Fang, Hai; Knezevic, Bogdan; Burnham, Katie L; Knight, Julian C

2016-12-13

Biological interpretation of genomic summary data such as those resulting from genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) studies is one of the major bottlenecks in medical genomics research, calling for efficient and integrative tools to resolve this problem. We introduce eXploring Genomic Relations (XGR), an open source tool designed for enhanced interpretation of genomic summary data enabling downstream knowledge discovery. Targeting users of varying computational skills, XGR utilises prior biological knowledge and relationships in a highly integrated but easily accessible way to make user-input genomic summary datasets more interpretable. We show how by incorporating ontology, annotation, and systems biology network-driven approaches, XGR generates more informative results than conventional analyses. We apply XGR to GWAS and eQTL summary data to explore the genomic landscape of the activated innate immune response and common immunological diseases. We provide genomic evidence for a disease taxonomy supporting the concept of a disease spectrum from autoimmune to autoinflammatory disorders. We also show how XGR can define SNP-modulated gene networks and pathways that are shared and distinct between diseases, how it achieves functional, phenotypic and epigenomic annotations of genes and variants, and how it enables exploring annotation-based relationships between genetic variants. XGR provides a single integrated solution to enhance interpretation of genomic summary data for downstream biological discovery. XGR is released as both an R package and a web-app, freely available at http://galahad.well.ox.ac.uk/XGR .

Molecular mechanisms underlying variations in lung function: a systems genetics analysis

PubMed Central

Obeidat, Ma’en; Hao, Ke; Bossé, Yohan; Nickle, David C; Nie, Yunlong; Postma, Dirkje S; Laviolette, Michel; Sandford, Andrew J; Daley, Denise D; Hogg, James C; Elliott, W Mark; Fishbane, Nick; Timens, Wim; Hysi, Pirro G; Kaprio, Jaakko; Wilson, James F; Hui, Jennie; Rawal, Rajesh; Schulz, Holger; Stubbe, Beate; Hayward, Caroline; Polasek, Ozren; Järvelin, Marjo-Riitta; Zhao, Jing Hua; Jarvis, Deborah; Kähönen, Mika; Franceschini, Nora; North, Kari E; Loth, Daan W; Brusselle, Guy G; Smith, Albert Vernon; Gudnason, Vilmundur; Bartz, Traci M; Wilk, Jemma B; O’Connor, George T; Cassano, Patricia A; Tang, Wenbo; Wain, Louise V; Artigas, María Soler; Gharib, Sina A; Strachan, David P; Sin, Don D; Tobin, Martin D; London, Stephanie J; Hall, Ian P; Paré, Peter D

2016-01-01

Summary Background Lung function measures reflect the physiological state of the lung, and are essential to the diagnosis of chronic obstructive pulmonary disease (COPD). The SpiroMeta-CHARGE consortium undertook the largest genome-wide association study (GWAS) so far (n=48 201) for forced expiratory volume in 1 s (FEV1) and the ratio of FEV1 to forced vital capacity (FEV1/FVC) in the general population. The lung expression quantitative trait loci (eQTLs) study mapped the genetic architecture of gene expression in lung tissue from 1111 individuals. We used a systems genetics approach to identify single nucleotide polymorphisms (SNPs) associated with lung function that act as eQTLs and change the level of expression of their target genes in lung tissue; termed eSNPs. Methods The SpiroMeta-CHARGE GWAS results were integrated with lung eQTLs to map eSNPs and the genes and pathways underlying the associations in lung tissue. For comparison, a similar analysis was done in peripheral blood. The lung mRNA expression levels of the eSNP-regulated genes were tested for associations with lung function measures in 727 individuals. Additional analyses identified the pleiotropic effects of eSNPs from the published GWAS catalogue, and mapped enrichment in regulatory regions from the ENCODE project. Finally, the Connectivity Map database was used to identify potential therapeutics in silico that could reverse the COPD lung tissue gene signature. Findings SNPs associated with lung function measures were more likely to be eQTLs and vice versa. The integration mapped the specific genes underlying the GWAS signals in lung tissue. The eSNP-regulated genes were enriched for developmental and inflammatory pathways; by comparison, SNPs associated with lung function that were eQTLs in blood, but not in lung, were only involved in inflammatory pathways. Lung function eSNPs were enriched for regulatory elements and were over-represented among genes showing differential expression during fetal lung development. An mRNA gene expression signature for COPD was identified in lung tissue and compared with the Connectivity Map. This in-silico drug repurposing approach suggested several compounds that reverse the COPD gene expression signature, including a nicotine receptor antagonist. These findings represent novel therapeutic pathways for COPD. Interpretation The system genetics approach identified lung tissue genes driving the variation in lung function and susceptibility to COPD. The identification of these genes and the pathways in which they are enriched is essential to understand the pathophysiology of airway obstruction and to identify novel therapeutic targets and biomarkers for COPD, including drugs that reverse the COPD gene signature in silico. Funding The research reported in this article was not specifically funded by any agency. See Acknowledgments for a full list of funders of the lung eQTL study and the Spiro-Meta CHARGE GWAS. PMID:26404118

Pathway deregulation and expression QTLs in response to Actinobacillus pleuropneumoniae infection in swine.

PubMed

Reiner, Gerald; Dreher, Felix; Drungowski, Mario; Hoeltig, Doris; Bertsch, Natalie; Selke, Martin; Willems, Hermann; Gerlach, Gerald Friedrich; Probst, Inga; Tuemmler, Burkhardt; Waldmann, Karl-Heinz; Herwig, Ralf

2014-12-01

Actinobacillus (A.) pleuropneumoniae is among the most important pathogens in pig. The agent causes severe economic losses due to decreased performance, the occurrence of acute or chronic pleuropneumonia, and an increase in death incidence. Since therapeutics cannot be used in a sustainable manner, and vaccination is not always available, new prophylactic measures are urgently needed. Recent research has provided evidence for a genetic predisposition in susceptibility to A. pleuropneumoniae in a Hampshire × German Landrace F2 family with 170 animals. The aim of the present study is to characterize the expression response in this family in order to unravel resistance and susceptibility mechanisms and to prioritize candidate genes for future fine mapping approaches. F2 pigs differed distinctly in clinical, pathological, and microbiological parameters after challenge with A. pleuropneumoniae. We monitored genome-wide gene expression from the 50 most and 50 least susceptible F2 pigs and identified 171 genes differentially expressed between these extreme phenotypes. We combined expression QTL analyses with network analyses and functional characterization using gene set enrichment analysis and identified a functional hotspot on SSC13, including 55 eQTL. The integration of the different results provides a resource for candidate prioritization for fine mapping strategies, such as TF, TFRC, RUNX1, TCN1, HP, CD14, among others.

Systems genetics: a paradigm to improve discovery of candidate genes and mechanisms underlying complex traits.

PubMed

Feltus, F Alex

2014-06-01

Understanding the control of any trait optimally requires the detection of causal genes, gene interaction, and mechanism of action to discover and model the biochemical pathways underlying the expressed phenotype. Functional genomics techniques, including RNA expression profiling via microarray and high-throughput DNA sequencing, allow for the precise genome localization of biological information. Powerful genetic approaches, including quantitative trait locus (QTL) and genome-wide association study mapping, link phenotype with genome positions, yet genetics is less precise in localizing the relevant mechanistic information encoded in DNA. The coupling of salient functional genomic signals with genetically mapped positions is an appealing approach to discover meaningful gene-phenotype relationships. Techniques used to define this genetic-genomic convergence comprise the field of systems genetics. This short review will address an application of systems genetics where RNA profiles are associated with genetically mapped genome positions of individual genes (eQTL mapping) or as gene sets (co-expression network modules). Both approaches can be applied for knowledge independent selection of candidate genes (and possible control mechanisms) underlying complex traits where multiple, likely unlinked, genomic regions might control specific complex traits. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Efficiently Identifying Significant Associations in Genome-wide Association Studies

PubMed Central

Eskin, Eleazar

2013-01-01

Abstract Over the past several years, genome-wide association studies (GWAS) have implicated hundreds of genes in common disease. More recently, the GWAS approach has been utilized to identify regions of the genome that harbor variation affecting gene expression or expression quantitative trait loci (eQTLs). Unlike GWAS applied to clinical traits, where only a handful of phenotypes are analyzed per study, in eQTL studies, tens of thousands of gene expression levels are measured, and the GWAS approach is applied to each gene expression level. This leads to computing billions of statistical tests and requires substantial computational resources, particularly when applying novel statistical methods such as mixed models. We introduce a novel two-stage testing procedure that identifies all of the significant associations more efficiently than testing all the single nucleotide polymorphisms (SNPs). In the first stage, a small number of informative SNPs, or proxies, across the genome are tested. Based on their observed associations, our approach locates the regions that may contain significant SNPs and only tests additional SNPs from those regions. We show through simulations and analysis of real GWAS datasets that the proposed two-stage procedure increases the computational speed by a factor of 10. Additionally, efficient implementation of our software increases the computational speed relative to the state-of-the-art testing approaches by a factor of 75. PMID:24033261

Genotype-based gene signature of glioma risk.

PubMed

Huang, Yen-Tsung; Zhang, Yi; Wu, Zhijin; Michaud, Dominique S

2017-07-01

Glioma accounts for 80% of malignant brain tumors, but its etiologic determinants remain elusive. Despite genetic susceptibility loci identified by genome-wide association study (GWAS), the agnostic approach leaves open the possibility that other susceptibility genes remain to be discovered. Here we conduct a gene-centric integrative GWAS (iGWAS) of glioma risk that combines transcriptomics and genetics. We synthesized a brain transcriptomics dataset (n = 354), a GWAS dataset (n = 4203), and an advanced glioma tumor transcriptomic dataset (n = 483) to conduct an iGWAS. Using the expression quantitative trait loci (eQTL) dataset, we built models to predict gene expression for the GWAS data, based on eQTL genotypes. With the predicted gene expression, iGWAS analyses were performed using a novel statistical method. Gene signature risk score was constructed using a penalized logistic regression model. A total of 30527 transcripts were analyzed using the iGWAS approach. Four novel glioma susceptibility genes were identified with internal and external validation, including DRD5 (P = 3.0 × 10-79), WDR1 (P = 8.4 × 10-77), NOMO1 (P = 1.3 × 10-25), and PDXDC1 (P = 8.3 × 10-24). The genotype-predicted transcription pattern between cases and controls is consistent with that between tumor and its matched normal tissue. The genotype-based 4-gene signature improved the classification between glioma cases and controls based on age, gender, and population stratification, with area under the receiver operating characteristic curve increasing from 0.77 to 0.85 (P = 8.1 × 10-23). A new genotype-based gene signature of glioma was identified using a novel iGWAS approach, which integrates multiplatform genomic data as well as different genetic association studies. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Mapping Adipose and Muscle Tissue Expression Quantitative Trait Loci in African Americans to Identify Genes for Type 2 Diabetes and Obesity

PubMed Central

Sajuthi, Satria P.; Sharma, Neeraj K.; Chou, Jeff W.; Palmer, Nicholette D.; McWilliams, David R.; Beal, John; Comeau, Mary E.; Ma, Lijun; Calles-Escandon, Jorge; Demons, Jamehl; Rogers, Samantha; Cherry, Kristina; Menon, Lata; Kouba, Ethel; Davis, Donna; Burris, Marcie; Byerly, Sara J.; Ng, Maggie C.Y.; Maruthur, Nisa M.; Patel, Sanjay R.; Bielak, Lawrence F.; Lange, Leslie; Guo, Xiuqing; Sale, Michèle M.; Chan, Kei Hang; Monda, Keri L.; Chen, Gary K.; Taylor, Kira; Palmer, Cameron; Edwards, Todd L; North, Kari E.; Haiman, Christopher A.; Bowden, Donald W.; Freedman, Barry I.; Langefeld, Carl D.; Das, Swapan K.

2016-01-01

Relative to European Americans, type 2 diabetes (T2D) is more prevalent in African Americans (AAs). Genetic variation may modulate transcript abundance in insulin-responsive tissues and contribute to risk; yet published studies identifying expression quantitative trait loci (eQTLs) in African ancestry populations are restricted to blood cells. This study aims to develop a map of genetically regulated transcripts expressed in tissues important for glucose homeostasis in AAs, critical for identifying the genetic etiology of T2D and related traits. Quantitative measures of adipose and muscle gene expression, and genotypic data were integrated in 260 non-diabetic AAs to identify expression regulatory variants. Their roles in genetic susceptibility to T2D, and related metabolic phenotypes were evaluated by mining GWAS datasets. eQTL analysis identified 1,971 and 2,078 cis-eGenes in adipose and muscle, respectively. Cis-eQTLs for 885 transcripts including top cis-eGenes CHURC1, USMG5, and ERAP2, were identified in both tissues. 62.1% of top cis-eSNPs were within ±50kb of transcription start sites and cis-eGenes were enriched for mitochondrial transcripts. Mining GWAS databases revealed association of cis-eSNPs for more than 50 genes with T2D (e.g. PIK3C2A, RBMS1, UFSP1), gluco-metabolic phenotypes, (e.g. INPP5E, SNX17, ERAP2, FN3KRP), and obesity (e.g. POMC, CPEB4). Integration of GWAS meta-analysis data from AA cohorts revealed the most significant association for cis-eSNPs of ATP5SL and MCCC1 genes, with T2D and BMI, respectively. This study developed the first comprehensive map of adipose and muscle tissue eQTLs in AAs (publically accessible at https://mdsetaa.phs.wakehealth.edu) and identified genetically-regulated transcripts for delineating genetic causes of T2D, and related metabolic phenotypes. PMID:27193597

Peripheral Blood Transcriptomic Signatures of Fasting Glucose and Insulin Concentrations

PubMed Central

Chen, Brian H.; Hivert, Marie-France; Peters, Marjolein J.; Pilling, Luke C.; Hogan, John D.; Pham, Lisa M.; Harries, Lorna W.; Fox, Caroline S.; Bandinelli, Stefania; Dehghan, Abbas; Hernandez, Dena G.; Hofman, Albert; Hong, Jaeyoung; Joehanes, Roby; Johnson, Andrew D.; Munson, Peter J.; Rybin, Denis V.; Singleton, Andrew B.; Uitterlinden, André G.; Ying, Saixia; Melzer, David; Levy, Daniel; van Meurs, Joyce B.J.; Ferrucci, Luigi; Florez, Jose C.; Dupuis, Josée

2016-01-01

Genome-wide association studies (GWAS) have successfully identified genetic loci associated with glycemic traits. However, characterizing the functional significance of these loci has proven challenging. We sought to gain insights into the regulation of fasting insulin and fasting glucose through the use of gene expression microarray data from peripheral blood samples of participants without diabetes in the Framingham Heart Study (FHS) (n = 5,056), the Rotterdam Study (RS) (n = 723), and the InCHIANTI Study (Invecchiare in Chianti) (n = 595). Using a false discovery rate q <0.05, we identified three transcripts associated with fasting glucose and 433 transcripts associated with fasting insulin levels after adjusting for age, sex, technical covariates, and complete blood cell counts. Among the findings, circulating IGF2BP2 transcript levels were positively associated with fasting insulin in both the FHS and RS. Using 1000 Genomes–imputed genotype data, we identified 47,587 cis-expression quantitative trait loci (eQTL) and 6,695 trans-eQTL associated with the 433 significant insulin-associated transcripts. Of note, we identified a trans-eQTL (rs592423), where the A allele was associated with higher IGF2BP2 levels and with fasting insulin in an independent genetic meta-analysis comprised of 50,823 individuals. We conclude that integration of genomic and transcriptomic data implicate circulating IGF2BP2 mRNA levels associated with glucose and insulin homeostasis. PMID:27625022

An erythroid-specific ATP2B4 enhancer mediates red blood cell hydration and malaria susceptibility

PubMed Central

Lessard, Samuel; Gatof, Emily Stern; Schupp, Patrick G.; Sher, Falak; Ali, Adnan; Prehar, Sukhpal; Kurita, Ryo; Nakamura, Yukio; Baena, Esther; Oceandy, Delvac; Bauer, Daniel E.

2017-01-01

The lack of mechanistic explanations for many genotype-phenotype associations identified by GWAS precludes thorough assessment of their impact on human health. Here, we conducted an expression quantitative trait locus (eQTL) mapping analysis in erythroblasts and found erythroid-specific eQTLs for ATP2B4, the main calcium ATPase of red blood cells (rbc). The same SNPs were previously associated with mean corpuscular hemoglobin concentration (MCHC) and susceptibility to severe malaria infection. We showed that Atp2b4–/– mice demonstrate increased MCHC, confirming ATP2B4 as the causal gene at this GWAS locus. Using CRISPR-Cas9, we fine mapped the genetic signal to an erythroid-specific enhancer of ATP2B4. Erythroid cells with a deletion of the ATP2B4 enhancer had abnormally high intracellular calcium levels. These results illustrate the power of combined transcriptomic, epigenomic, and genome-editing approaches in characterizing noncoding regulatory elements in phenotype-relevant cells. Our study supports ATP2B4 as a potential target for modulating rbc hydration in erythroid disorders and malaria infection. PMID:28714864

An erythroid-specific ATP2B4 enhancer mediates red blood cell hydration and malaria susceptibility.

PubMed

Lessard, Samuel; Gatof, Emily Stern; Beaudoin, Mélissa; Schupp, Patrick G; Sher, Falak; Ali, Adnan; Prehar, Sukhpal; Kurita, Ryo; Nakamura, Yukio; Baena, Esther; Ledoux, Jonathan; Oceandy, Delvac; Bauer, Daniel E; Lettre, Guillaume

2017-08-01

The lack of mechanistic explanations for many genotype-phenotype associations identified by GWAS precludes thorough assessment of their impact on human health. Here, we conducted an expression quantitative trait locus (eQTL) mapping analysis in erythroblasts and found erythroid-specific eQTLs for ATP2B4, the main calcium ATPase of red blood cells (rbc). The same SNPs were previously associated with mean corpuscular hemoglobin concentration (MCHC) and susceptibility to severe malaria infection. We showed that Atp2b4-/- mice demonstrate increased MCHC, confirming ATP2B4 as the causal gene at this GWAS locus. Using CRISPR-Cas9, we fine mapped the genetic signal to an erythroid-specific enhancer of ATP2B4. Erythroid cells with a deletion of the ATP2B4 enhancer had abnormally high intracellular calcium levels. These results illustrate the power of combined transcriptomic, epigenomic, and genome-editing approaches in characterizing noncoding regulatory elements in phenotype-relevant cells. Our study supports ATP2B4 as a potential target for modulating rbc hydration in erythroid disorders and malaria infection.

A splice mutation in the PHKG1 gene causes high glycogen content and low meat quality in pig skeletal muscle.

PubMed

Ma, Junwu; Yang, Jie; Zhou, Lisheng; Ren, Jun; Liu, Xianxian; Zhang, Hui; Yang, Bin; Zhang, Zhiyan; Ma, Huanban; Xie, Xianhua; Xing, Yuyun; Guo, Yuanmei; Huang, Lusheng

2014-10-01

Glycolytic potential (GP) in skeletal muscle is economically important in the pig industry because of its effect on pork processing yield. We have previously mapped a major quantitative trait loci (QTL) for GP on chromosome 3 in a White Duroc × Erhualian F2 intercross. We herein performed a systems genetic analysis to identify the causal variant underlying the phenotype QTL (pQTL). We first conducted genome-wide association analyses in the F2 intercross and an F19 Sutai pig population. The QTL was then refined to an 180-kb interval based on the 2-LOD drop method. We then performed expression QTL (eQTL) mapping using muscle transcriptome data from 497 F2 animals. Within the QTL interval, only one gene (PHKG1) has a cis-eQTL that was colocolizated with pQTL peaked at the same SNP. The PHKG1 gene encodes a catalytic subunit of the phosphorylase kinase (PhK), which functions in the cascade activation of glycogen breakdown. Deep sequencing of PHKG1 revealed a point mutation (C>A) in a splice acceptor site of intron 9, resulting in a 32-bp deletion in the open reading frame and generating a premature stop codon. The aberrant transcript induces nonsense-mediated decay, leading to lower protein level and weaker enzymatic activity in affected animals. The mutation causes an increase of 43% in GP and a decrease of>20% in water-holding capacity of pork. These effects were consistent across the F2 and Sutai populations, as well as Duroc × (Landrace × Yorkshire) hybrid pigs. The unfavorable allele exists predominantly in Duroc-derived pigs. The findings provide new insights into understanding risk factors affecting glucose metabolism, and would greatly contribute to the genetic improvement of meat quality in Duroc related pigs.

Integrative analysis of GWAS, eQTLs and meQTLs data suggests that multiple gene sets are associated with bone mineral density.

PubMed

Wang, W; Huang, S; Hou, W; Liu, Y; Fan, Q; He, A; Wen, Y; Hao, J; Guo, X; Zhang, F

2017-10-01

Several genome-wide association studies (GWAS) of bone mineral density (BMD) have successfully identified multiple susceptibility genes, yet isolated susceptibility genes are often difficult to interpret biologically. The aim of this study was to unravel the genetic background of BMD at pathway level, by integrating BMD GWAS data with genome-wide expression quantitative trait loci (eQTLs) and methylation quantitative trait loci (meQTLs) data METHOD: We employed the GWAS datasets of BMD from the Genetic Factors for Osteoporosis Consortium (GEFOS), analysing patients' BMD. The areas studied included 32 735 femoral necks, 28 498 lumbar spines, and 8143 forearms. Genome-wide eQTLs (containing 923 021 eQTLs) and meQTLs (containing 683 152 unique methylation sites with local meQTLs) data sets were collected from recently published studies. Gene scores were first calculated by summary data-based Mendelian randomisation (SMR) software and meQTL-aligned GWAS results. Gene set enrichment analysis (GSEA) was then applied to identify BMD-associated gene sets with a predefined significance level of 0.05. We identified multiple gene sets associated with BMD in one or more regions, including relevant known biological gene sets such as the Reactome Circadian Clock (GSEA p-value = 1.0 × 10 -4 for LS and 2.7 × 10 -2 for femoral necks BMD in eQTLs-based GSEA) and insulin-like growth factor receptor binding (GSEA p-value = 5.0 × 10 -4 for femoral necks and 2.6 × 10 -2 for lumbar spines BMD in meQTLs-based GSEA). Our results provided novel clues for subsequent functional analysis of bone metabolism, and illustrated the benefit of integrating eQTLs and meQTLs data into pathway association analysis for genetic studies of complex human diseases. Cite this article : W. Wang, S. Huang, W. Hou, Y. Liu, Q. Fan, A. He, Y. Wen, J. Hao, X. Guo, F. Zhang. Integrative analysis of GWAS, eQTLs and meQTLs data suggests that multiple gene sets are associated with bone mineral density. Bone Joint Res 2017;6:572-576. © 2017 Wang et al.

ITGB5 and AGFG1 variants are associated with severity of airway responsiveness.

PubMed

Himes, Blanca E; Qiu, Weiliang; Klanderman, Barbara; Ziniti, John; Senter-Sylvia, Jody; Szefler, Stanley J; Lemanske, Robert F; Zeiger, Robert S; Strunk, Robert C; Martinez, Fernando D; Boushey, Homer; Chinchilli, Vernon M; Israel, Elliot; Mauger, David; Koppelman, Gerard H; Nieuwenhuis, Maartje A E; Postma, Dirkje S; Vonk, Judith M; Rafaels, Nicholas; Hansel, Nadia N; Barnes, Kathleen; Raby, Benjamin; Tantisira, Kelan G; Weiss, Scott T

2013-08-28

Airway hyperresponsiveness (AHR), a primary characteristic of asthma, involves increased airway smooth muscle contractility in response to certain exposures. We sought to determine whether common genetic variants were associated with AHR severity. A genome-wide association study (GWAS) of AHR, quantified as the natural log of the dosage of methacholine causing a 20% drop in FEV1, was performed with 994 non-Hispanic white asthmatic subjects from three drug clinical trials: CAMP, CARE, and ACRN. Genotyping was performed on Affymetrix 6.0 arrays, and imputed data based on HapMap Phase 2, was used to measure the association of SNPs with AHR using a linear regression model. Replication of primary findings was attempted in 650 white subjects from DAG, and 3,354 white subjects from LHS. Evidence that the top SNPs were eQTL of their respective genes was sought using expression data available for 419 white CAMP subjects. The top primary GWAS associations were in rs848788 (P-value 7.2E-07) and rs6731443 (P-value 2.5E-06), located within the ITGB5 and AGFG1 genes, respectively. The AGFG1 result replicated at a nominally significant level in one independent population (LHS P-value 0.012), and the SNP had a nominally significant unadjusted P-value (0.0067) for being an eQTL of AGFG1. Based on current knowledge of ITGB5 and AGFG1, our results suggest that variants within these genes may be involved in modulating AHR. Future functional studies are required to confirm that our associations represent true biologically significant findings.

Statistical properties of interval mapping methods on quantitative trait loci location: impact on QTL/eQTL analyses

PubMed Central

2012-01-01

Background Quantitative trait loci (QTL) detection on a huge amount of phenotypes, like eQTL detection on transcriptomic data, can be dramatically impaired by the statistical properties of interval mapping methods. One of these major outcomes is the high number of QTL detected at marker locations. The present study aims at identifying and specifying the sources of this bias, in particular in the case of analysis of data issued from outbred populations. Analytical developments were carried out in a backcross situation in order to specify the bias and to propose an algorithm to control it. The outbred population context was studied through simulated data sets in a wide range of situations. The likelihood ratio test was firstly analyzed under the "one QTL" hypothesis in a backcross population. Designs of sib families were then simulated and analyzed using the QTL Map software. On the basis of the theoretical results in backcross, parameters such as the population size, the density of the genetic map, the QTL effect and the true location of the QTL, were taken into account under the "no QTL" and the "one QTL" hypotheses. A combination of two non parametric tests - the Kolmogorov-Smirnov test and the Mann-Whitney-Wilcoxon test - was used in order to identify the parameters that affected the bias and to specify how much they influenced the estimation of QTL location. Results A theoretical expression of the bias of the estimated QTL location was obtained for a backcross type population. We demonstrated a common source of bias under the "no QTL" and the "one QTL" hypotheses and qualified the possible influence of several parameters. Simulation studies confirmed that the bias exists in outbred populations under both the hypotheses of "no QTL" and "one QTL" on a linkage group. The QTL location was systematically closer to marker locations than expected, particularly in the case of low QTL effect, small population size or low density of markers, i.e. designs with low power. Practical recommendations for experimental designs for QTL detection in outbred populations are given on the basis of this bias quantification. Furthermore, an original algorithm is proposed to adjust the location of a QTL, obtained with interval mapping, which co located with a marker. Conclusions Therefore, one should be attentive when one QTL is mapped at the location of one marker, especially under low power conditions. PMID:22520935

Genomic approaches for the elucidation of genes and gene networks underlying cardiovascular traits.

PubMed

Adriaens, M E; Bezzina, C R

2018-06-22

Genome-wide association studies have shed light on the association between natural genetic variation and cardiovascular traits. However, linking a cardiovascular trait associated locus to a candidate gene or set of candidate genes for prioritization for follow-up mechanistic studies is all but straightforward. Genomic technologies based on next-generation sequencing technology nowadays offer multiple opportunities to dissect gene regulatory networks underlying genetic cardiovascular trait associations, thereby aiding in the identification of candidate genes at unprecedented scale. RNA sequencing in particular becomes a powerful tool when combined with genotyping to identify loci that modulate transcript abundance, known as expression quantitative trait loci (eQTL), or loci modulating transcript splicing known as splicing quantitative trait loci (sQTL). Additionally, the allele-specific resolution of RNA-sequencing technology enables estimation of allelic imbalance, a state where the two alleles of a gene are expressed at a ratio differing from the expected 1:1 ratio. When multiple high-throughput approaches are combined with deep phenotyping in a single study, a comprehensive elucidation of the relationship between genotype and phenotype comes into view, an approach known as systems genetics. In this review, we cover key applications of systems genetics in the broad cardiovascular field.

Association study of genetic variants in estrogen metabolic pathway genes and colorectal cancer risk and survival.

PubMed

Li, Shuwei; Xie, Lisheng; Du, Mulong; Xu, Kaili; Zhu, Lingjun; Chu, Haiyan; Chen, Jinfei; Wang, Meilin; Zhang, Zhengdong; Gu, Dongying

2018-05-16

Although studies have investigated the association of genetic variants and the abnormal expression of estrogen-related genes with colorectal cancer risk, the evidence remains inconsistent. We clarified the relationship of genetic variants in estrogen metabolic pathway genes with colorectal cancer risk and survival. A case-control study was performed to assess the association of single-nucleotide polymorphisms (SNPs) in ten candidate genes with colorectal cancer risk in a Chinese population. A logistic regression model and Cox regression model were used to calculate SNP effects on colorectal cancer susceptibility and survival, respectively. Expression quantitative trait loci (eQTL) analysis was conducted using the Genotype-Tissue Expression (GTEx) project dataset. The sequence kernel association test (SKAT) was used to perform gene-set analysis. Colorectal cancer risk and rs3760806 in SULT2B1 were significantly associated in both genders [male: OR = 1.38 (1.15-1.66); female: OR = 1.38 (1.13-1.68)]. Two SNPs in SULT1E1 were related to progression-free survival (PFS) [rs1238574: HR = 1.24 (1.02-1.50), P = 2.79 × 10 -2 ; rs3822172: HR = 1.30 (1.07-1.57), P = 8.44 × 10 -3 ] and overall survival (OS) [rs1238574: HR = 1.51 (1.16-1.97), P = 2.30 × 10 -3 ; rs3822172: HR = 1.53 (1.67-2.00), P = 2.03 × 10 -3 ]. Moreover, rs3760806 was an eQTL for SULT2B1 in colon samples (transverse: P = 3.6 × 10 -3 ; sigmoid: P = 1.0 × 10 -3 ). SULT2B1 expression was significantly higher in colorectal tumor tissues than in normal tissues in the Cancer Genome Atlas (TCGA) database (P < 1.0 × 10 -4 ). Our results indicated that SNPs in estrogen metabolic pathway genes confer colorectal cancer susceptibility and survival.

Mapping cis- and trans-regulatory effects across multiple tissues in twins

PubMed Central

Grundberg, Elin; Small, Kerrin S.; Hedman, Åsa K.; Nica, Alexandra C.; Buil, Alfonso; Keildson, Sarah; Bell, Jordana T.; Yang, Tsun-Po; Meduri, Eshwar; Barrett, Amy; Nisbett, James; Sekowska, Magdalena; Wilk, Alicja; Shin, So-Youn; Glass, Daniel; Travers, Mary; Min, Josine L.; Ring, Sue; Ho, Karen; Thorleifsson, Gudmar; Kong, Augustine; Thorsteindottir, Unnur; Ainali, Chrysanthi; Dimas, Antigone S.; Hassanali, Neelam; Ingle, Catherine; Knowles, David; Krestyaninova, Maria; Lowe, Christopher E.; Di Meglio, Paola; Montgomery, Stephen B.; Parts, Leopold; Potter, Simon; Surdulescu, Gabriela; Tsaprouni, Loukia; Tsoka, Sophia; Bataille, Veronique; Durbin, Richard; Nestle, Frank O.; O’Rahilly, Stephen; Soranzo, Nicole; Lindgren, Cecilia M.; Zondervan, Krina T.; Ahmadi, Kourosh R.; Schadt, Eric E.; Stefansson, Kari; Smith, George Davey; McCarthy, Mark I.; Deloukas, Panos; Dermitzakis, Emmanouil T.; Spector, Tim D.

2013-01-01

Sequence-based variation in gene expression is a key driver of disease risk. Common variants regulating expression in cis have been mapped in many eQTL studies typically in single tissues from unrelated individuals. Here, we present a comprehensive analysis of gene expression across multiple tissues conducted in a large set of mono- and dizygotic twins that allows systematic dissection of genetic (cis and trans) and non-genetic effects on gene expression. Using identity-by-descent estimates, we show that at least 40% of the total heritable cis-effect on expression cannot be accounted for by common cis-variants, a finding which exposes the contribution of low frequency and rare regulatory variants with respect to both transcriptional regulation and complex trait susceptibility. We show that a substantial proportion of gene expression heritability is trans to the structural gene and identify several replicating trans-variants which act predominantly in a tissue-restricted manner and may regulate the transcription of many genes. PMID:22941192

Quantile-based permutation thresholds for quantitative trait loci hotspots.

PubMed

Neto, Elias Chaibub; Keller, Mark P; Broman, Andrew F; Attie, Alan D; Jansen, Ritsert C; Broman, Karl W; Yandell, Brian S

2012-08-01

Quantitative trait loci (QTL) hotspots (genomic locations affecting many traits) are a common feature in genetical genomics studies and are biologically interesting since they may harbor critical regulators. Therefore, statistical procedures to assess the significance of hotspots are of key importance. One approach, randomly allocating observed QTL across the genomic locations separately by trait, implicitly assumes all traits are uncorrelated. Recently, an empirical test for QTL hotspots was proposed on the basis of the number of traits that exceed a predetermined LOD value, such as the standard permutation LOD threshold. The permutation null distribution of the maximum number of traits across all genomic locations preserves the correlation structure among the phenotypes, avoiding the detection of spurious hotspots due to nongenetic correlation induced by uncontrolled environmental factors and unmeasured variables. However, by considering only the number of traits above a threshold, without accounting for the magnitude of the LOD scores, relevant information is lost. In particular, biologically interesting hotspots composed of a moderate to small number of traits with strong LOD scores may be neglected as nonsignificant. In this article we propose a quantile-based permutation approach that simultaneously accounts for the number and the LOD scores of traits within the hotspots. By considering a sliding scale of mapping thresholds, our method can assess the statistical significance of both small and large hotspots. Although the proposed approach can be applied to any type of heritable high-volume "omic" data set, we restrict our attention to expression (e)QTL analysis. We assess and compare the performances of these three methods in simulations and we illustrate how our approach can effectively assess the significance of moderate and small hotspots with strong LOD scores in a yeast expression data set.

QTL mapping for nine drought-responsive agronomic traits in bread wheat under irrigated and rain-fed environments

PubMed Central

Gahlaut, Vijay; Jaiswal, Vandana; Tyagi, Bhudeva S.; Singh, Gyanendra; Sareen, Sindhu; Balyan, Harindra S.

2017-01-01

In bread wheat, QTL interval mapping was conducted for nine important drought responsive agronomic traits. For this purpose, a doubled haploid (DH) mapping population derived from Kukri/Excalibur was grown over three years at four separate locations in India, both under irrigated and rain-fed environments. Single locus analysis using composite interval mapping (CIM) allowed detection of 98 QTL, which included 66 QTL for nine individual agronomic traits and 32 QTL, which affected drought sensitivity index (DSI) for the same nine traits. Two-locus analysis allowed detection of 19 main effect QTL (M-QTL) for four traits (days to anthesis, days to maturity, grain filling duration and thousand grain weight) and 19 pairs of epistatic QTL (E-QTL) for two traits (days to anthesis and thousand grain weight). Eight QTL were common in single locus analysis and two locus analysis. These QTL (identified both in single- and two-locus analysis) were distributed on 20 different chromosomes (except 4D). Important genomic regions on chromosomes 5A and 7A were also identified (5A carried QTL for seven traits and 7A carried QTL for six traits). Marker-assisted recurrent selection (MARS) involving pyramiding of important QTL reported in the present study, together with important QTL reported earlier, may be used for improvement of drought tolerance in wheat. In future, more closely linked markers for the QTL reported here may be developed through fine mapping, and the candidate genes may be identified and used for developing a better understanding of the genetic basis of drought tolerance in wheat. PMID:28793327

Sex difference in EGFR pathways in mouse kidney-potential impact on the immune system.

PubMed

Liu, Fengxia; Jiao, Yan; Jiao, Yun; Garcia-Godoy, Franklin; Gu, Weikuan; Liu, Qingyi

2016-11-24

Epidermal growth factor receptor (Egfr) has been the target of several drugs for cancers. The potential gender differences in genes in the Egfr axis have been suggested in humans and in animal models. Female and male mice from the same recombinant inbred (RI) strain have the same genomic components except the sex difference. A population of different RI mouse strains allows to conduct precise analysis of molecular pathways and regulation of Egfr between female and male mice. The whole genome expression profiles of 70 genetically diverse RI strains of mice were used to compare three major molecular aspects of Egfr gene: the relative expression levels, gene network and expression quantitative trait loci (eQTL) that regulate the expression of Egfr between female and male mice. Our data showed that there is a significant sex difference in the expression levels in kidney. A considerable number of genes in the gene network of Egfr are sex differentially expressed. The expression levels of Egfr in mice are statistical significant different between C57BL/6 J (B6) and DBA/2 J (D2) genotypes in male while no difference in female mice. The eQTLs that regulate the expression levels of Egfr between female and male mice are also different. Furthermore, the differential expression levels of Egfr showed significantly different correlations with two known biological traits between male and female mice. Overall there is a substantial sex difference in the Egfr pathways in mice. These data may have significant impact on drug target design, development, formulation, and dosage determinant for women and men in clinical trials.

Peripheral Blood Transcriptomic Signatures of Fasting Glucose and Insulin Concentrations.

PubMed

Chen, Brian H; Hivert, Marie-France; Peters, Marjolein J; Pilling, Luke C; Hogan, John D; Pham, Lisa M; Harries, Lorna W; Fox, Caroline S; Bandinelli, Stefania; Dehghan, Abbas; Hernandez, Dena G; Hofman, Albert; Hong, Jaeyoung; Joehanes, Roby; Johnson, Andrew D; Munson, Peter J; Rybin, Denis V; Singleton, Andrew B; Uitterlinden, André G; Ying, Saixia; Melzer, David; Levy, Daniel; van Meurs, Joyce B J; Ferrucci, Luigi; Florez, Jose C; Dupuis, Josée; Meigs, James B; Kolaczyk, Eric D

2016-12-01

Genome-wide association studies (GWAS) have successfully identified genetic loci associated with glycemic traits. However, characterizing the functional significance of these loci has proven challenging. We sought to gain insights into the regulation of fasting insulin and fasting glucose through the use of gene expression microarray data from peripheral blood samples of participants without diabetes in the Framingham Heart Study (FHS) (n = 5,056), the Rotterdam Study (RS) (n = 723), and the InCHIANTI Study (Invecchiare in Chianti) (n = 595). Using a false discovery rate q <0.05, we identified three transcripts associated with fasting glucose and 433 transcripts associated with fasting insulin levels after adjusting for age, sex, technical covariates, and complete blood cell counts. Among the findings, circulating IGF2BP2 transcript levels were positively associated with fasting insulin in both the FHS and RS. Using 1000 Genomes-imputed genotype data, we identified 47,587 cis-expression quantitative trait loci (eQTL) and 6,695 trans-eQTL associated with the 433 significant insulin-associated transcripts. Of note, we identified a trans-eQTL (rs592423), where the A allele was associated with higher IGF2BP2 levels and with fasting insulin in an independent genetic meta-analysis comprised of 50,823 individuals. We conclude that integration of genomic and transcriptomic data implicate circulating IGF2BP2 mRNA levels associated with glucose and insulin homeostasis. © 2016 by the American Diabetes Association.

Integration of Population-Level Genotype Data with Functional Annotation Reveals Over-Representation of Long Noncoding RNAs at Ovarian Cancer Susceptibility Loci.

PubMed

Reid, Brett M; Permuth, Jennifer B; Chen, Y Ann; Teer, Jamie K; Monteiro, Alvaro N A; Chen, Zhihua; Tyrer, Jonathan; Berchuck, Andrew; Chenevix-Trench, Georgia; Doherty, Jennifer A; Goode, Ellen L; Iverson, Edwin S; Lawrenson, Kate; Pearce, Celeste L; Pharoah, Paul D; Phelan, Catherine M; Ramus, Susan J; Rossing, Mary Anne; Schildkraut, Joellen M; Cheng, Jin Q; Gayther, Simon A; Sellers, Thomas A

2017-01-01

Genome-wide association studies (GWAS) have identified multiple loci associated with epithelial ovarian cancer (EOC) susceptibility, but further progress requires integration of epidemiology and biology to illuminate true risk loci below genome-wide significance levels (P < 5 × 10 -8 ). Most risk SNPs lie within non-protein-encoding regions, and we hypothesize that long noncoding RNA (lncRNA) genes are enriched at EOC risk regions and represent biologically relevant functional targets. Using imputed GWAS data from about 18,000 invasive EOC cases and 34,000 controls of European ancestry, the GENCODE (v19) lncRNA database was used to annotate SNPs from 13,442 lncRNAs for permutation-based enrichment analysis. Tumor expression quantitative trait locus (eQTL) analysis was performed for sub-genome-wide regions (1 × 10 -5 > P > 5 × 10 -8 ) overlapping lncRNAs. Of 5,294 EOC-associated SNPs (P < 1.0 × 10 -5 ), 1,464 (28%) mapped within 53 unique lncRNAs and an additional 3,484 (66%) SNPs were correlated (r 2 > 0.2) with SNPs within 115 lncRNAs. EOC-associated SNPs comprised 130 independent regions, of which 72 (55%) overlapped with lncRNAs, representing a significant enrichment (P = 5.0 × 10 -4 ) that was more pronounced among a subset of 5,401 lncRNAs with active epigenetic regulation in normal ovarian tissue. EOC-associated lncRNAs and their putative promoters and transcription factors were enriched for biologically relevant pathways and eQTL analysis identified five novel putative risk regions with allele-specific effects on lncRNA gene expression. lncRNAs are significantly enriched at EOC risk regions, suggesting a mechanistic role for lncRNAs in driving predisposition to EOC. lncRNAs represent key candidates for integrative epidemiologic and functional studies. Further research on their biologic role in ovarian cancer is indicated. Cancer Epidemiol Biomarkers Prev; 26(1); 116-25. ©2016 AACR. ©2016 American Association for Cancer Research.

Pervasive pleiotropy between psychiatric disorders and immune disorders revealed by integrative analysis of multiple GWAS

PubMed Central

Wang, Qian; Yang, Can; Gelernter, Joel; Zhao, Hongyu

2015-01-01

Although some existing epidemiological observations and molecular experiments suggested that brain disorders in the realm of psychiatry may be influenced by immune dysregulation, the degree of genetic overlap between psychiatric disorders and immune disorders has not been well established. We investigated this issue by integrative analysis of genome-wide association studies of 18 complex human traits/diseases (five psychiatric disorders, seven immune disorders, and others) and multiple genome-wide annotation resources (Central nervous system genes, immune-related expression-quantitative trait loci (eQTL) and DNase I hypertensive sites from 98 cell-lines). We detected pleiotropy in 24 of the 35 psychiatric-immune disorder pairs. The strongest pleiotropy was observed for schizophrenia-rheumatoid arthritis with MHC region included in the analysis (p = 3.9 × 10−285), and schizophrenia-Crohns disease with MHC region excluded (p = 1.1 × 10−36). Significant enrichment (>1.4 fold) of immune-related eQTL was observed in four psychiatric disorders. Genomic regions responsible for pleiotropy between psychiatric disorders and immune disorders were detected. The MHC region on chromosome 6 appears to be the most important with other regions, such as cytoband 1p13.2, also playing significant roles in pleiotropy. We also found that most alleles shared between schizophrenia and Crohns disease have the same effect direction, with similar trend found for other disorder pairs, such as bipolar-Crohn’s disease. Our results offer a novel birds-eye view of the genetic relationship and demonstrate strong evidence for pervasive pleiotropy between psychiatric disorders and immune disorders. Our findings might open new routes for prevention and treatment strategies for these disorders based on a new appreciation of the importance of immunological mechanisms in mediating risk of many psychiatric diseases. PMID:26340901

Genome-wide meta-analysis identifies five new susceptibility loci for cutaneous malignant melanoma.

PubMed

Law, Matthew H; Bishop, D Timothy; Lee, Jeffrey E; Brossard, Myriam; Martin, Nicholas G; Moses, Eric K; Song, Fengju; Barrett, Jennifer H; Kumar, Rajiv; Easton, Douglas F; Pharoah, Paul D P; Swerdlow, Anthony J; Kypreou, Katerina P; Taylor, John C; Harland, Mark; Randerson-Moor, Juliette; Akslen, Lars A; Andresen, Per A; Avril, Marie-Françoise; Azizi, Esther; Scarrà, Giovanna Bianchi; Brown, Kevin M; Dębniak, Tadeusz; Duffy, David L; Elder, David E; Fang, Shenying; Friedman, Eitan; Galan, Pilar; Ghiorzo, Paola; Gillanders, Elizabeth M; Goldstein, Alisa M; Gruis, Nelleke A; Hansson, Johan; Helsing, Per; Hočevar, Marko; Höiom, Veronica; Ingvar, Christian; Kanetsky, Peter A; Chen, Wei V; Landi, Maria Teresa; Lang, Julie; Lathrop, G Mark; Lubiński, Jan; Mackie, Rona M; Mann, Graham J; Molven, Anders; Montgomery, Grant W; Novaković, Srdjan; Olsson, Håkan; Puig, Susana; Puig-Butille, Joan Anton; Qureshi, Abrar A; Radford-Smith, Graham L; van der Stoep, Nienke; van Doorn, Remco; Whiteman, David C; Craig, Jamie E; Schadendorf, Dirk; Simms, Lisa A; Burdon, Kathryn P; Nyholt, Dale R; Pooley, Karen A; Orr, Nick; Stratigos, Alexander J; Cust, Anne E; Ward, Sarah V; Hayward, Nicholas K; Han, Jiali; Schulze, Hans-Joachim; Dunning, Alison M; Bishop, Julia A Newton; Demenais, Florence; Amos, Christopher I; MacGregor, Stuart; Iles, Mark M

2015-09-01

Thirteen common susceptibility loci have been reproducibly associated with cutaneous malignant melanoma (CMM). We report the results of an international 2-stage meta-analysis of CMM genome-wide association studies (GWAS). This meta-analysis combines 11 GWAS (5 previously unpublished) and a further three stage 2 data sets, totaling 15,990 CMM cases and 26,409 controls. Five loci not previously associated with CMM risk reached genome-wide significance (P < 5 × 10(-8)), as did 2 previously reported but unreplicated loci and all 13 established loci. Newly associated SNPs fall within putative melanocyte regulatory elements, and bioinformatic and expression quantitative trait locus (eQTL) data highlight candidate genes in the associated regions, including one involved in telomere biology.

Genome-wide meta-analysis identifies five new susceptibility loci for cutaneous malignant melanoma

PubMed Central

Law, Matthew H.; Bishop, D. Timothy; Martin, Nicholas G.; Moses, Eric K.; Song, Fengju; Barrett, Jennifer H.; Kumar, Rajiv; Easton, Douglas F.; Pharoah, Paul D. P.; Swerdlow, Anthony J.; Kypreou, Katerina P.; Taylor, John C.; Harland, Mark; Randerson-Moor, Juliette; Akslen, Lars A.; Andresen, Per A.; Avril, Marie-Françoise; Azizi, Esther; Scarrà, Giovanna Bianchi; Brown, Kevin M.; Dębniak, Tadeusz; Duffy, David L.; Elder, David E.; Fang, Shenying; Friedman, Eitan; Galan, Pilar; Ghiorzo, Paola; Gillanders, Elizabeth M.; Goldstein, Alisa M.; Gruis, Nelleke A.; Hansson, Johan; Helsing, Per; Hočevar, Marko; Höiom, Veronica; Ingvar, Christian; Kanetsky, Peter A.; Chen, Wei V.; Landi, Maria Teresa; Lang, Julie; Lathrop, G. Mark; Lubiński, Jan; Mackie, Rona M.; Mann, Graham J.; Molven, Anders; Montgomery, Grant W.; Novaković, Srdjan; Olsson, Håkan; Puig, Susana; Puig-Butille, Joan Anton; Qureshi, Abrar A.; Radford-Smith, Graham L.; van der Stoep, Nienke; van Doorn, Remco; Whiteman, David C.; Craig, Jamie E.; Schadendorf, Dirk; Simms, Lisa A.; Burdon, Kathryn P.; Nyholt, Dale R.; Pooley, Karen A.; Orr, Nick; Stratigos, Alexander J.; Cust, Anne E.; Ward, Sarah V.; Hayward, Nicholas K.; Han, Jiali; Schulze, Hans-Joachim; Dunning, Alison M.; Bishop, Julia A. Newton; MacGregor, Stuart; Iles, Mark M.

2015-01-01

Thirteen common susceptibility loci have been reproducibly associated with cutaneous malignant melanoma (CMM). We report the results of an international 2-stage meta-analysis of CMM genome-wide association studies (GWAS). This meta-analysis combines 11 GWAS (5 previously unpublished) and a further three stage 2 data sets, totaling 15,990 CMM cases and 26,409 controls. Five loci not previously associated with CMM risk reached genome-wide significance (P < 5×10–8), as did two previously-reported but un-replicated loci and all thirteen established loci. Novel SNPs fall within putative melanocyte regulatory elements, and bioinformatic and expression quantitative trait locus (eQTL) data highlight candidate genes including one involved in telomere biology. PMID:26237428

Putative bovine topological association domains and CTCF binding motifs can reduce the search space for causative regulatory variants of complex traits.

PubMed

Wang, Min; Hancock, Timothy P; Chamberlain, Amanda J; Vander Jagt, Christy J; Pryce, Jennie E; Cocks, Benjamin G; Goddard, Mike E; Hayes, Benjamin J

2018-05-24

Topological association domains (TADs) are chromosomal domains characterised by frequent internal DNA-DNA interactions. The transcription factor CTCF binds to conserved DNA sequence patterns called CTCF binding motifs to either prohibit or facilitate chromosomal interactions. TADs and CTCF binding motifs control gene expression, but they are not yet well defined in the bovine genome. In this paper, we sought to improve the annotation of bovine TADs and CTCF binding motifs, and assess whether the new annotation can reduce the search space for cis-regulatory variants. We used genomic synteny to map TADs and CTCF binding motifs from humans, mice, dogs and macaques to the bovine genome. We found that our mapped TADs exhibited the same hallmark properties of those sourced from experimental data, such as housekeeping genes, transfer RNA genes, CTCF binding motifs, short interspersed elements, H3K4me3 and H3K27ac. We showed that runs of genes with the same pattern of allele-specific expression (ASE) (either favouring paternal or maternal allele) were often located in the same TAD or between the same conserved CTCF binding motifs. Analyses of variance showed that when averaged across all bovine tissues tested, TADs explained 14% of ASE variation (standard deviation, SD: 0.056), while CTCF explained 27% (SD: 0.078). Furthermore, we showed that the quantitative trait loci (QTLs) associated with gene expression variation (eQTLs) or ASE variation (aseQTLs), which were identified from mRNA transcripts from 141 lactating cows' white blood and milk cells, were highly enriched at putative bovine CTCF binding motifs. The linearly-furthermost, and most-significant aseQTL and eQTL for each genic target were located within the same TAD as the gene more often than expected (Chi-Squared test P-value < 0.001). Our results suggest that genomic synteny can be used to functionally annotate conserved transcriptional components, and provides a tool to reduce the search space for causative regulatory variants in the bovine genome.

How powerful are summary-based methods for identifying expression-trait associations under different genetic architectures?

PubMed

Veturi, Yogasudha; Ritchie, Marylyn D

2018-01-01

Transcriptome-wide association studies (TWAS) have recently been employed as an approach that can draw upon the advantages of genome-wide association studies (GWAS) and gene expression studies to identify genes associated with complex traits. Unlike standard GWAS, summary level data suffices for TWAS and offers improved statistical power. Two popular TWAS methods include either (a) imputing the cis genetic component of gene expression from smaller sized studies (using multi-SNP prediction or MP) into much larger effective sample sizes afforded by GWAS - TWAS-MP or (b) using summary-based Mendelian randomization - TWAS-SMR. Although these methods have been effective at detecting functional variants, it remains unclear how extensive variability in the genetic architecture of complex traits and diseases impacts TWAS results. Our goal was to investigate the different scenarios under which these methods yielded enough power to detect significant expression-trait associations. In this study, we conducted extensive simulations based on 6000 randomly chosen, unrelated Caucasian males from Geisinger's MyCode population to compare the power to detect cis expression-trait associations (within 500 kb of a gene) using the above-described approaches. To test TWAS across varying genetic backgrounds we simulated gene expression and phenotype using different quantitative trait loci per gene and cis-expression /trait heritability under genetic models that differentiate the effect of causality from that of pleiotropy. For each gene, on a training set ranging from 100 to 1000 individuals, we either (a) estimated regression coefficients with gene expression as the response using five different methods: LASSO, elastic net, Bayesian LASSO, Bayesian spike-slab, and Bayesian ridge regression or (b) performed eQTL analysis. We then sampled with replacement 50,000, 150,000, and 300,000 individuals respectively from the testing set of the remaining 5000 individuals and conducted GWAS on each set. Subsequently, we integrated the GWAS summary statistics derived from the testing set with the weights (or eQTLs) derived from the training set to identify expression-trait associations using (a) TWAS-MP (b) TWAS-SMR (c) eQTL-based GWAS, or (d) standalone GWAS. Finally, we examined the power to detect functionally relevant genes using the different approaches under the considered simulation scenarios. In general, we observed great similarities among TWAS-MP methods although the Bayesian methods resulted in improved power in comparison to LASSO and elastic net as the trait architecture grew more complex while training sample sizes and expression heritability remained small. Finally, we observed high power under causality but very low to moderate power under pleiotropy.

Novel Genetic Variants Associated With Increased Vertebral Volumetric BMD, Reduced Vertebral Fracture Risk, and Increased Expression of SLC1A3 and EPHB2

PubMed Central

Nielson, Carrie M; Liu, Ching-Ti; Smith, Albert V; Ackert-Bicknell, Cheryl L; Reppe, Sjur; Jakobsdottir, Johanna; Wassel, Christina; Register, Thomas C; Oei, Ling; Alonso, Nerea; Oei, Edwin H; Parimi, Neeta; Samelson, Elizabeth J; Nalls, Mike A; Zmuda, Joseph; Lang, Thomas; Bouxsein, Mary; Latourelle, Jeanne; Claussnitzer, Melina; Siggeirsdottir, Kristin; Srikanth, Priya; Lorentzen, Erik; Vandenput, Liesbeth; Langefeld, Carl; Raffield, Laura; Terry, Greg; Cox, Amanda J; Allison, Matthew A; Criqui, Michael H; Bowden, Don; Ikram, M Arfan; Mellstrom, Dan; Karlsson, Magnus K; Carr, John; Budoff, Matthew; Phillips, Caroline; Cupples, L Adrienne; Chou, Wen-Chi; Myers, Richard H; Ralston, Stuart H; Gautvik, Kaare M; Cawthon, Peggy M; Cummings, Steven; Karasik, David; Rivadeneira, Fernando; Gudnason, Vilmundur; Orwoll, Eric S; Harris, Tamara B; Ohlsson, Claes; Kiel, Douglas P; Hsu, Yi-Hsiang

2017-01-01

Genome-wide association studies (GWASs) have revealed numerous loci for areal bone mineral density (aBMD). We completed the first GWAS meta-analysis (n = 15,275) of lumbar spine volumetric BMD (vBMD) measured by quantitative computed tomography (QCT), allowing for examination of the trabecular bone compartment. SNPs that were significantly associated with vBMD were also examined in two GWAS meta-analyses to determine associations with morphometric vertebral fracture (n = 21,701) and clinical vertebral fracture (n = 5893). Expression quantitative trait locus (eQTL) analyses of iliac crest biopsies were performed in 84 postmenopausal women, and murine osteoblast expression of genes implicated by eQTL or by proximity to vBMD-associated SNPs was examined. We identified significant vBMD associations with five loci, including: 1p36.12, containing WNT4 and ZBTB40; 8q24, containing TNFRSF11B; and 13q14, containing AKAP11 and TNFSF11. Two loci (5p13 and 1p36.12) also contained associations with radiographic and clinical vertebral fracture, respectively. In 5p13, rs2468531 (minor allele frequency [MAF] = 3%) was associated with higher vBMD (β = 0.22, p = 1.9 × 10−8) and decreased risk of radiographic vertebral fracture (odds ratio [OR] = 0.75; false discovery rate [FDR] p = 0.01). In 1p36.12, rs12742784 (MAF = 21%) was associated with higher vBMD (β = 0.09, p = 1.2 × 10−10) and decreased risk of clinical vertebral fracture (OR = 0.82; FDR p = 7.4 × 10−4). Both SNPs are noncoding and were associated with increased mRNA expression levels in human bone biopsies: rs2468531 with SLC1A3 (β = 0.28, FDR p = 0.01, involved in glutamate signaling and osteogenic response to mechanical loading) and rs12742784 with EPHB2 (β = 0.12, FDR p = 1.7 × 10−3, functions in bone-related ephrin signaling). Both genes are expressed in murine osteoblasts. This is the first study to linkSLC1A3 and EPHB2 to clinically relevant vertebral osteoporosis phenotypes. These results may help elucidate vertebral bone biology and novel approaches to reducing vertebral fracture incidence. © 2016 American Society for Bone and Mineral Research. PMID:27476799

A novel variant associated with HDL-C levels by modifying DAGLB expression levels: An annotation-based genome-wide association study.

PubMed

Zhou, Dan; Zhang, Dandan; Sun, Xiaohui; Li, Zhiqiang; Ni, Yaqin; Shan, Zhongyan; Li, Hong; Liu, Chengguo; Zhang, Shuai; Liu, Yi; Zheng, Ruizhi; Pan, Feixia; Zhu, Yimin; Shi, Yongyong; Lai, Maode

2018-06-01

Although numbers of genome-wide association studies (GWAS) have been performed for serum lipid levels, limited heritability has been explained. Studies showed that combining data from GWAS and expression quantitative trait loci (eQTLs) signals can both enhance the discovery of trait-associated SNPs and gain a better understanding of the mechanism. We performed an annotation-based, multistage genome-wide screening for serum-lipid-level-associated loci in totally 6863 Han Chinese. A serum high-density lipoprotein cholesterol (HDL-C) associated variant rs1880118 (hg19 chr7:g. 6435220G>C) was replicated (P combined  = 1.4E-10). rs1880118 was associated with DAGLB (diacylglycerol lipase, beta) expression levels in subcutaneous adipose tissue (P = 5.9E-42) and explained 47.7% of the expression variance. After the replication, an active segment covering variants tagged by rs1880118 near 5' of DAGLB was annotated using histone modification and transcription factor binding signals. The luciferase report assay revealed that the segment containing the minor alleles showed increased transcriptional activity compared with segment contains the major alleles, which was consistent with the eQTL analyses. The expression-trait association tests indicated the association between the DAGLB and serum HDL-C levels using gene-based approaches called "TWAS" (P = 3.0E-8), "SMR" (P = 1.1E-4), and "Sherlock" (P = 1.6E-6). To summarize, we identified a novel HDL-C-associated variant which explained nearly half of the expression variance of DAGLB. Integrated analyses established a genotype-gene-phenotype three-way association and expanded our knowledge of DAGLB in lipid metabolism.

SZGR 2.0: a one-stop shop of schizophrenia candidate genes

PubMed Central

Jia, Peilin; Han, Guangchun; Zhao, Junfei; Lu, Pinyi; Zhao, Zhongming

2017-01-01

SZGR 2.0 is a comprehensive resource of candidate variants and genes for schizophrenia, covering genetic, epigenetic, transcriptomic, translational and many other types of evidence. By systematic review and curation of multiple lines of evidence, we included almost all variants and genes that have ever been reported to be associated with schizophrenia. In particular, we collected ∼4200 common variants reported in genome-wide association studies, ∼1000 de novo mutations discovered by large-scale sequencing of family samples, 215 genes spanning rare and replication copy number variations, 99 genes overlapping with linkage regions, 240 differentially expressed genes, 4651 differentially methylated genes and 49 genes as antipsychotic drug targets. To facilitate interpretation, we included various functional annotation data, especially brain eQTL, methylation QTL, brain expression featured in deep categorization of brain areas and developmental stages and brain-specific promoter and enhancer annotations. Furthermore, we conducted cross-study, cross-data type and integrative analyses of the multidimensional data deposited in SZGR 2.0, and made the data and results available through a user-friendly interface. In summary, SZGR 2.0 provides a one-stop shop of schizophrenia variants and genes and their function and regulation, providing an important resource in the schizophrenia and other mental disease community. SZGR 2.0 is available at https://bioinfo.uth.edu/SZGR/. PMID:27733502

Systems Genetics Reveals the Functional Context of PCOS Loci and Identifies Genetic and Molecular Mechanisms of Disease Heterogeneity.

PubMed

Jones, Michelle R; Brower, Meredith A; Xu, Ning; Cui, Jinrui; Mengesha, Emebet; Chen, Yii-Der I; Taylor, Kent D; Azziz, Ricardo; Goodarzi, Mark O

2015-08-01

Genome wide association studies (GWAS) have revealed 11 independent risk loci for polycystic ovary syndrome (PCOS), a common disorder in young women characterized by androgen excess and oligomenorrhea. To put these risk loci and the single nucleotide polymorphisms (SNPs) therein into functional context, we measured DNA methylation and gene expression in subcutaneous adipose tissue biopsies to identify PCOS-specific alterations. Two genes from the LHCGR region, STON1-GTF2A1L and LHCGR, were overexpressed in PCOS. In analysis stratified by obesity, LHCGR was overexpressed only in non-obese PCOS women. Although not differentially expressed in the entire PCOS group, INSR was underexpressed in obese PCOS subjects only. Alterations in gene expression in the LHCGR, RAB5B and INSR regions suggest that SNPs in these loci may be functional and could affect gene expression directly or indirectly via epigenetic alterations. We identified reduced methylation in the LHCGR locus and increased methylation in the INSR locus, changes that are concordant with the altered gene expression profiles. Complex patterns of meQTL and eQTL were identified in these loci, suggesting that local genetic variation plays an important role in gene regulation. We propose that non-obese PCOS women possess significant alterations in LH receptor expression, which drives excess androgen secretion from the ovary. Alternatively, obese women with PCOS possess alterations in insulin receptor expression, with underexpression in metabolic tissues and overexpression in the ovary, resulting in peripheral insulin resistance and excess ovarian androgen production. These studies provide a genetic and molecular basis for the reported clinical heterogeneity of PCOS.

Gene Expression Architecture of Mouse Dorsal and Tail Skin Reveals Functional Differences in Inflammation and Cancer.

PubMed

Quigley, David A; Kandyba, Eve; Huang, Phillips; Halliwill, Kyle D; Sjölund, Jonas; Pelorosso, Facundo; Wong, Christine E; Hirst, Gillian L; Wu, Di; Delrosario, Reyno; Kumar, Atul; Balmain, Allan

2016-07-26

Inherited germline polymorphisms can cause gene expression levels in normal tissues to differ substantially between individuals. We present an analysis of the genetic architecture of normal adult skin from 470 genetically unique mice, demonstrating the effect of germline variants, skin tissue location, and perturbation by exogenous inflammation or tumorigenesis on gene signaling pathways. Gene networks related to specific cell types and signaling pathways, including sonic hedgehog (Shh), Wnt, Lgr family stem cell markers, and keratins, differed at these tissue sites, suggesting mechanisms for the differential susceptibility of dorsal and tail skin to development of skin diseases and tumorigenesis. The Pten tumor suppressor gene network is rewired in premalignant tumors compared to normal tissue, but this response to perturbation is lost during malignant progression. We present a software package for expression quantitative trait loci (eQTL) network analysis and demonstrate how network analysis of whole tissues provides insights into interactions between cell compartments and signaling molecules. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

GSCALite: A Web Server for Gene Set Cancer Analysis.

PubMed

Liu, Chun-Jie; Hu, Fei-Fei; Xia, Mengxuan; Han, Leng; Zhang, Qiong; Guo, An-Yuan

2018-05-22

The availability of cancer genomic data makes it possible to analyze genes related to cancer. Cancer is usually the result of a set of genes and the signal of a single gene could be covered by background noise. Here, we present a web server named Gene Set Cancer Analysis (GSCALite) to analyze a set of genes in cancers with the following functional modules. (i) Differential expression in tumor vs normal, and the survival analysis; (ii) Genomic variations and their survival analysis; (iii) Gene expression associated cancer pathway activity; (iv) miRNA regulatory network for genes; (v) Drug sensitivity for genes; (vi) Normal tissue expression and eQTL for genes. GSCALite is a user-friendly web server for dynamic analysis and visualization of gene set in cancer and drug sensitivity correlation, which will be of broad utilities to cancer researchers. GSCALite is available on http://bioinfo.life.hust.edu.cn/web/GSCALite/. guoay@hust.edu.cn or zhangqiong@hust.edu.cn. Supplementary data are available at Bioinformatics online.

Genetic Variants in the Bone Morphogenic Protein Gene Family Modify the Association between Residential Exposure to Traffic and Peripheral Arterial Disease

PubMed Central

Ward-Caviness, Cavin K.; Neas, Lucas M.; Blach, Colette; Haynes, Carol S.; LaRocque-Abramson, Karen; Grass, Elizabeth; Dowdy, Elaine; Devlin, Robert B.; Diaz-Sanchez, David; Cascio, Wayne E.; Lynn Miranda, Marie; Gregory, Simon G.; Shah, Svati H.; Kraus, William E.; Hauser, Elizabeth R.

2016-01-01

There is a growing literature indicating that genetic variants modify many of the associations between environmental exposures and clinical outcomes, potentially by increasing susceptibility to these exposures. However, genome-scale investigations of these interactions have been rarely performed particularly in the case of air pollution exposures. We performed race-stratified genome-wide gene-environment interaction association studies on European-American (EA, N = 1623) and African-American (AA, N = 554) cohorts to investigate the joint influence of common single nucleotide polymorphisms (SNPs) and residential exposure to traffic (“traffic exposure”)—a recognized vascular disease risk factor—on peripheral arterial disease (PAD). Traffic exposure was estimated via the distance from the primary residence to the nearest major roadway, defined as the nearest limited access highways or major arterial. The rs755249-traffic exposure interaction was associated with PAD at a genome-wide significant level (P = 2.29x10-8) in European-Americans. Rs755249 is located in the 3’ untranslated region of BMP8A, a member of the bone morphogenic protein (BMP) gene family. Further investigation revealed several variants in BMP genes associated with PAD via an interaction with traffic exposure in both the EA and AA cohorts; this included interactions with non-synonymous variants in BMP2, which is regulated by air pollution exposure. The BMP family of genes is linked to vascular growth and calcification and is a novel gene family for the study of PAD pathophysiology. Further investigation of BMP8A using the Genotype Tissue Expression Database revealed multiple variants with nominally significant (P < 0.05) interaction P-values in our EA cohort were significant BMP8A eQTLs in tissue types highlight relevant for PAD such as rs755249 (tibial nerve, eQTL P = 3.6x10-6) and rs1180341 (tibial artery, eQTL P = 5.3x10-6). Together these results reveal a novel gene, and possibly gene family, associated with PAD via an interaction with traffic air pollution exposure. These results also highlight the potential for interactions studies, particularly at the genome scale, to reveal novel biology linking environmental exposures to clinical outcomes. PMID:27082954

Integrative comparison of mRNA expression patterns in breast cancers from Caucasian and Asian Americans with implications for precision medicine

PubMed Central

Wang, Jianan; He, Max M; Li, Liren; Zhang, Jinfeng

2016-01-01

Asian Americans (AS) have significantly lower incidence and mortality rates of breast cancer (BRCA) than Caucasian Americans (CA). While this racial disparity has been documented the underlying pathogenetic factors explaining it are obscure. We addressed this issue by an integrative genomics approach to compare mRNA expression between AS and CA cases of BRCA. RNA-seq data from the Cancer Genome Atlas showed that mRNA expression revealed significant differences at gene and pathway levels. Increased susceptibility and severity in CA patients were likely the result of synergistic environmental and genetic risk factors, with arachidonic acid metabolism and PPAR signaling pathways implicated in linking environmental and genetic factors. An analysis that also added eQTL data from the Genotype-Tissue Expression Project and single nucleotide polymorphism (SNP) data from the 1000 Genomes Project identified several SNPs associated with differentially expressed genes. Overall, the associations we identified may enable a more focused study of genotypic differences that may help explain the disparity in BRCA incidence and mortality rates in CA and AS populations and inform precision medicine. PMID:28069798

Exon-Specific QTLs Skew the Inferred Distribution of Expression QTLs Detected Using Gene Expression Array Data

PubMed Central

Veyrieras, Jean-Baptiste; Gaffney, Daniel J.; Pickrell, Joseph K.; Gilad, Yoav; Stephens, Matthew; Pritchard, Jonathan K.

2012-01-01

Mapping of expression quantitative trait loci (eQTLs) is an important technique for studying how genetic variation affects gene regulation in natural populations. In a previous study using Illumina expression data from human lymphoblastoid cell lines, we reported that cis-eQTLs are especially enriched around transcription start sites (TSSs) and immediately upstream of transcription end sites (TESs). In this paper, we revisit the distribution of eQTLs using additional data from Affymetrix exon arrays and from RNA sequencing. We confirm that most eQTLs lie close to the target genes; that transcribed regions are generally enriched for eQTLs; that eQTLs are more abundant in exons than introns; and that the peak density of eQTLs occurs at the TSS. However, we find that the intriguing TES peak is greatly reduced or absent in the Affymetrix and RNA-seq data. Instead our data suggest that the TES peak observed in the Illumina data is mainly due to exon-specific QTLs that affect 3′ untranslated regions, where most of the Illumina probes are positioned. Nonetheless, we do observe an overall enrichment of eQTLs in exons versus introns in all three data sets, consistent with an important role for exonic sequences in gene regulation. PMID:22359548

Systems Genetics Reveals the Functional Context of PCOS Loci and Identifies Genetic and Molecular Mechanisms of Disease Heterogeneity

PubMed Central

Xu, Ning; Cui, Jinrui; Mengesha, Emebet; Chen, Yii-Der I.; Taylor, Kent D.; Azziz, Ricardo; Goodarzi, Mark O.

2015-01-01

Genome wide association studies (GWAS) have revealed 11 independent risk loci for polycystic ovary syndrome (PCOS), a common disorder in young women characterized by androgen excess and oligomenorrhea. To put these risk loci and the single nucleotide polymorphisms (SNPs) therein into functional context, we measured DNA methylation and gene expression in subcutaneous adipose tissue biopsies to identify PCOS-specific alterations. Two genes from the LHCGR region, STON1-GTF2A1L and LHCGR, were overexpressed in PCOS. In analysis stratified by obesity, LHCGR was overexpressed only in non-obese PCOS women. Although not differentially expressed in the entire PCOS group, INSR was underexpressed in obese PCOS subjects only. Alterations in gene expression in the LHCGR, RAB5B and INSR regions suggest that SNPs in these loci may be functional and could affect gene expression directly or indirectly via epigenetic alterations. We identified reduced methylation in the LHCGR locus and increased methylation in the INSR locus, changes that are concordant with the altered gene expression profiles. Complex patterns of meQTL and eQTL were identified in these loci, suggesting that local genetic variation plays an important role in gene regulation. We propose that non-obese PCOS women possess significant alterations in LH receptor expression, which drives excess androgen secretion from the ovary. Alternatively, obese women with PCOS possess alterations in insulin receptor expression, with underexpression in metabolic tissues and overexpression in the ovary, resulting in peripheral insulin resistance and excess ovarian androgen production. These studies provide a genetic and molecular basis for the reported clinical heterogeneity of PCOS. PMID:26305227

Comprehensive evaluation of disease- and trait-specific enrichment for eight functional elements among GWAS-identified variants.

PubMed

Markunas, Christina A; Johnson, Eric O; Hancock, Dana B

2017-07-01

Genome-wide association study (GWAS)-identified variants are enriched for functional elements. However, we have limited knowledge of how functional enrichment may differ by disease/trait and tissue type. We tested a broad set of eight functional elements for enrichment among GWAS-identified SNPs (p < 5×10 -8 ) from the NHGRI-EBI Catalog across seven disease/trait categories: cancer, cardiovascular disease, diabetes, autoimmune disease, psychiatric disease, neurological disease, and anthropometric traits. SNPs were annotated using HaploReg for the eight functional elements across any tissue: DNase sites, expression quantitative trait loci (eQTL), sequence conservation, enhancers, promoters, missense variants, sequence motifs, and protein binding sites. In addition, tissue-specific annotations were considered for brain vs. blood. Disease/trait SNPs were compared to a control set of 4809 SNPs matched to the GWAS SNPs (N = 1639) on allele frequency, gene density, distance to nearest gene, and linkage disequilibrium at ~3:1 ratio. Enrichment analyses were conducted using logistic regression, with Bonferroni correction. Overall, a significant enrichment was observed for all functional elements, except sequence motifs. Missense SNPs showed the strongest magnitude of enrichment. eQTLs were the only functional element significantly enriched across all diseases/traits. Magnitudes of enrichment were generally similar across diseases/traits, where enrichment was statistically significant. Blood vs. brain tissue effects on enrichment were dependent on disease/trait and functional element (e.g., cardiovascular disease: eQTLs P TissueDifference  = 1.28 × 10 -6 vs. enhancers P TissueDifference  = 0.94). Identifying disease/trait-relevant functional elements and tissue types could provide new insight into the underlying biology, by guiding a priori GWAS analyses (e.g., brain enhancer elements for psychiatric disease) or facilitating post hoc interpretation.

Genetic dissection of the Gpnmb network in the eye.

PubMed

Lu, Hong; Wang, Xusheng; Pullen, Matthew; Guan, Huaijin; Chen, Hui; Sahu, Shwetapadma; Zhang, Bing; Chen, Hao; Williams, Robert W; Geisert, Eldon E; Lu, Lu; Jablonski, Monica M

2011-06-13

To use a systematic genetics approach to investigate the regulation of Gpnmb, a gene that contributes to pigmentary dispersion syndrome (PDS) and pigmentary glaucoma (PG) in the DBA/2J (D2) mouse. Global patterns of gene expression were studied in whole eyes of a large family of BXD mouse strains (n = 67) generated by crossing the PDS- and PG-prone parent (DBA/2J) with a resistant strain (C57BL/6J). Quantitative trait locus (eQTL) mapping methods and gene set analysis were used to evaluate Gpnmb coexpression networks in wild-type and mutant cohorts. The level of Gpnmb expression was associated with a highly significant cis-eQTL at the location of the gene itself. This autocontrol of Gpnmb is likely to be a direct consequence of the known premature stop codon in exon 4. Both gene ontology and coexpression network analyses demonstrated that the mutation in Gpnmb radically modified the set of genes with which Gpnmb expression is correlated. The covariates of wild-type Gpnmb are involved in biological processes including melanin synthesis and cell migration, whereas the covariates of mutant Gpnmb are involved in the biological processes of posttranslational modification, stress activation, and sensory processing. These results demonstrated that a systematic genetics approach provides a powerful tool for constructing coexpression networks that define the biological process categories within which similarly regulated genes function. The authors showed that the R150X mutation in Gpnmb dramatically modified its list of genetic covariates, which may explain the associated ocular pathology.

SZGR 2.0: a one-stop shop of schizophrenia candidate genes.

PubMed

Jia, Peilin; Han, Guangchun; Zhao, Junfei; Lu, Pinyi; Zhao, Zhongming

2017-01-04

SZGR 2.0 is a comprehensive resource of candidate variants and genes for schizophrenia, covering genetic, epigenetic, transcriptomic, translational and many other types of evidence. By systematic review and curation of multiple lines of evidence, we included almost all variants and genes that have ever been reported to be associated with schizophrenia. In particular, we collected ∼4200 common variants reported in genome-wide association studies, ∼1000 de novo mutations discovered by large-scale sequencing of family samples, 215 genes spanning rare and replication copy number variations, 99 genes overlapping with linkage regions, 240 differentially expressed genes, 4651 differentially methylated genes and 49 genes as antipsychotic drug targets. To facilitate interpretation, we included various functional annotation data, especially brain eQTL, methylation QTL, brain expression featured in deep categorization of brain areas and developmental stages and brain-specific promoter and enhancer annotations. Furthermore, we conducted cross-study, cross-data type and integrative analyses of the multidimensional data deposited in SZGR 2.0, and made the data and results available through a user-friendly interface. In summary, SZGR 2.0 provides a one-stop shop of schizophrenia variants and genes and their function and regulation, providing an important resource in the schizophrenia and other mental disease community. SZGR 2.0 is available at https://bioinfo.uth.edu/SZGR/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Association of twelve polymorphisms in three onco-lncRNA genes with hepatocellular cancer risk and prognosis: A case-control study

PubMed Central

Wang, Ben-Gang; Xu, Qian; Lv, Zhi; Fang, Xin-Xin; Ding, Han-Xi; Wen, Jing; Yuan, Yuan

2018-01-01

AIM To evaluate the association of 12 tag single nucleotide polymorphisms (tagSNPs) in three onco-long non-coding RNA (lncRNA) genes (HOTTIP, CCAT2, MALAT1) with the risk and prognosis of hepatocellular cancer (HCC). METHODS Twelve tagSNPs covering the three onco-lncRNAs were genotyped by the KASP method in a total of 1338 samples, including 521 HCC patients and frequency-matched 817 controls. The samples were obtained from an unrelated Chinese population at the First Hospital of China Medical University from 2012-2015. The expression quantitative trait loci (eQTL) analyses were conducted to explore further the potential function of the promising SNPs. RESULTS Three SNPs in HOTTIP, one promoter SNP in MALAT1, and one haplotype of HOTTIP were associated with HCC risk. The HOTTIP rs17501292, rs2067087, and rs17427960 SNPs were increased to 1.55-, 1.20-, and 1.18-fold HCC risk under allelic models (P = 0.012, 0.017 and 0.049, respectively). MALAT1 rs4102217 SNP was increased to a 1.32-fold HCC risk under dominant models (P = 0.028). In addition, the two-way interaction of HOTTIP rs17501292-MALAT1 rs619586 polymorphisms showed a decreased effect on HCC risk (Pinteraction = 0.028, OR = 0.30) and epistasis with each other. HOTTIP rs3807598 variant genotype showed significantly longer survival time in HBV negative subgroup (P = 0.049, HR = 0.12), and MALAT1 rs591291 showed significantly better prognosis in female and HBV negative subgroups (P = 0.022, HR = 0.37; P = 0.042, HR = 0.25, respectively). In the study, no significant effect was observed in eQTL analysis. CONCLUSION Specific lncRNA (HOTTIP and MALAT1) SNPs have potential to be biomarkers for HCC risk and prognosis. PMID:29930469

Genetic and Environmental Pathways in Type 1 Diabetes Complications

DTIC Science & Technology

2010-09-01

active duty members of the military, their families and retired military personnel will potentially allow focused preventative treatment of at- risk...association and assess potential heterogeneity of association signals, such as by ancestry. Query eQTL databases for relevant associations. Goals: 1a1...1, so that at most an average of 7 SNPs remain as potential risk SNPs at each of the 30 loci. In Stage 2 we will genotype another 2000 cases and

Mining disease genes using integrated protein-protein interaction and gene-gene co-regulation information.

PubMed

Li, Jin; Wang, Limei; Guo, Maozu; Zhang, Ruijie; Dai, Qiguo; Liu, Xiaoyan; Wang, Chunyu; Teng, Zhixia; Xuan, Ping; Zhang, Mingming

2015-01-01

In humans, despite the rapid increase in disease-associated gene discovery, a large proportion of disease-associated genes are still unknown. Many network-based approaches have been used to prioritize disease genes. Many networks, such as the protein-protein interaction (PPI), KEGG, and gene co-expression networks, have been used. Expression quantitative trait loci (eQTLs) have been successfully applied for the determination of genes associated with several diseases. In this study, we constructed an eQTL-based gene-gene co-regulation network (GGCRN) and used it to mine for disease genes. We adopted the random walk with restart (RWR) algorithm to mine for genes associated with Alzheimer disease. Compared to the Human Protein Reference Database (HPRD) PPI network alone, the integrated HPRD PPI and GGCRN networks provided faster convergence and revealed new disease-related genes. Therefore, using the RWR algorithm for integrated PPI and GGCRN is an effective method for disease-associated gene mining.

Regulation of gene expression in autoimmune disease loci and the genetic basis of proliferation in CD4+ effector memory T cells.

PubMed

Hu, Xinli; Kim, Hyun; Raj, Towfique; Brennan, Patrick J; Trynka, Gosia; Teslovich, Nikola; Slowikowski, Kamil; Chen, Wei-Min; Onengut, Suna; Baecher-Allan, Clare; De Jager, Philip L; Rich, Stephen S; Stranger, Barbara E; Brenner, Michael B; Raychaudhuri, Soumya

2014-06-01

Genome-wide association studies (GWAS) and subsequent dense-genotyping of associated loci identified over a hundred single-nucleotide polymorphism (SNP) variants associated with the risk of rheumatoid arthritis (RA), type 1 diabetes (T1D), and celiac disease (CeD). Immunological and genetic studies suggest a role for CD4-positive effector memory T (CD+ TEM) cells in the pathogenesis of these diseases. To elucidate mechanisms of autoimmune disease alleles, we investigated molecular phenotypes in CD4+ effector memory T cells potentially affected by these variants. In a cohort of genotyped healthy individuals, we isolated high purity CD4+ TEM cells from peripheral blood, then assayed relative abundance, proliferation upon T cell receptor (TCR) stimulation, and the transcription of 215 genes within disease loci before and after stimulation. We identified 46 genes regulated by cis-acting expression quantitative trait loci (eQTL), the majority of which we detected in stimulated cells. Eleven of the 46 genes with eQTLs were previously undetected in peripheral blood mononuclear cells. Of 96 risk alleles of RA, T1D, and/or CeD in densely genotyped loci, eleven overlapped cis-eQTLs, of which five alleles completely explained the respective signals. A non-coding variant, rs389862A, increased proliferative response (p=4.75 × 10-8). In addition, baseline expression of seventeen genes in resting cells reliably predicted proliferative response after TCR stimulation. Strikingly, however, there was no evidence that risk alleles modulated CD4+ TEM abundance or proliferation. Our study underscores the power of examining molecular phenotypes in relevant cells and conditions for understanding pathogenic mechanisms of disease variants.

Natural sequence variants of yeast environmental sensors confer cell-to-cell expression variability

PubMed Central

Fehrmann, Steffen; Bottin-Duplus, Hélène; Leonidou, Andri; Mollereau, Esther; Barthelaix, Audrey; Wei, Wu; Steinmetz, Lars M; Yvert, Gaël

2013-01-01

Living systems may have evolved probabilistic bet hedging strategies that generate cell-to-cell phenotypic diversity in anticipation of environmental catastrophes, as opposed to adaptation via a deterministic response to environmental changes. Evolution of bet hedging assumes that genotypes segregating in natural populations modulate the level of intraclonal diversity, which so far has largely remained hypothetical. Using a fluorescent Pmet17-GFP reporter, we mapped four genetic loci conferring to a wild yeast strain an elevated cell-to-cell variability in the expression of MET17, a gene regulated by the methionine pathway. A frameshift mutation in the Erc1p transmembrane transporter, probably resulting from a release of laboratory strains from negative selection, reduced Pmet17-GFP expression variability. At a second locus, cis-regulatory polymorphisms increased mean expression of the Mup1p methionine permease, causing increased expression variability in trans. These results demonstrate that an expression quantitative trait locus (eQTL) can simultaneously have a deterministic effect in cis and a probabilistic effect in trans. Our observations indicate that the evolution of transmembrane transporter genes can tune intraclonal variation and may therefore be implicated in both reactive and anticipatory strategies of adaptation. PMID:24104478

Expression Variants of the Lipogenic AGPAT6 Gene Affect Diverse Milk Composition Phenotypes in Bos taurus

PubMed Central

Littlejohn, Mathew D.; Tiplady, Kathryn; Lopdell, Thomas; Law, Tania A.; Scott, Andrew; Harland, Chad; Sherlock, Ric; Henty, Kristen; Obolonkin, Vlad; Lehnert, Klaus; MacGibbon, Alistair; Spelman, Richard J.; Davis, Stephen R.; Snell, Russell G.

2014-01-01

Milk is composed of a complex mixture of lipids, proteins, carbohydrates and various vitamins and minerals as a source of nutrition for young mammals. The composition of milk varies between individuals, with lipid composition in particular being highly heritable. Recent reports have highlighted a region of bovine chromosome 27 harbouring variants affecting milk fat percentage and fatty acid content. We aimed to further investigate this locus in two independent cattle populations, consisting of a Holstein-Friesian x Jersey crossbreed pedigree of 711 F2 cows, and a collection of 32,530 mixed ancestry Bos taurus cows. Bayesian genome-wide association mapping using markers imputed from the Illumina BovineHD chip revealed a large quantitative trait locus (QTL) for milk fat percentage on chromosome 27, present in both populations. We also investigated a range of other milk composition phenotypes, and report additional associations at this locus for fat yield, protein percentage and yield, lactose percentage and yield, milk volume, and the proportions of numerous milk fatty acids. We then used mammary RNA sequence data from 212 lactating cows to assess the transcript abundance of genes located in the milk fat percentage QTL interval. This analysis revealed a strong eQTL for AGPAT6, demonstrating that high milk fat percentage genotype is also additively associated with increased expression of the AGPAT6 gene. Finally, we used whole genome sequence data from six F1 sires to target a panel of novel AGPAT6 locus variants for genotyping in the F2 crossbreed population. Association analysis of 58 of these variants revealed highly significant association for polymorphisms mapping to the 5′UTR exons and intron 1 of AGPAT6. Taken together, these data suggest that variants affecting the expression of AGPAT6 are causally involved in differential milk fat synthesis, with pleiotropic consequences for a diverse range of other milk components. PMID:24465687

Gene-based association study of genes linked to hippocampal sclerosis of aging neuropathology: GRN, TMEM106B, ABCC9, and KCNMB2

PubMed Central

Katsumata, Yuriko; Nelson, Peter T.; Ellingson, Sally R.; Fardo, David W.

2017-01-01

Hippocampal sclerosis of aging (HS-Aging) is a common neurodegenerative condition associated with dementia. To learn more about genetic risk of HS-Aging pathology, we tested gene-based associations of the GRN, TMEM106B, ABCC9, and KCNMB2 genes, which were reported to be associated with HS-Aging pathology in previous studies. Genetic data were obtained from the Alzheimer’s Disease Genetics Consortium (ADGC), linked to autopsy-derived neuropathological outcomes from the National Alzheimer’s Coordinating Center (NACC). Of the 3,251 subjects included in the study, 271 (8.3%) were identified as an HS-Aging case. The significant gene-based association between the ABCC9 gene and HS-Aging appeared to be driven by a region in which a significant haplotype-based association was found. We tested this haplotype as an expression Quantitative Trait Locus (eQTL) using two different public-access brain gene expression databases. The HS-Aging pathology protective ABCC9 haplotype was associated with decreased ABCC9 expression, indicating a possible toxic gain of function. PMID:28131462

Natural genetic variation of the cardiac transcriptome in non-diseased donors and patients with dilated cardiomyopathy.

PubMed

Heinig, Matthias; Adriaens, Michiel E; Schafer, Sebastian; van Deutekom, Hanneke W M; Lodder, Elisabeth M; Ware, James S; Schneider, Valentin; Felkin, Leanne E; Creemers, Esther E; Meder, Benjamin; Katus, Hugo A; Rühle, Frank; Stoll, Monika; Cambien, François; Villard, Eric; Charron, Philippe; Varro, Andras; Bishopric, Nanette H; George, Alfred L; Dos Remedios, Cristobal; Moreno-Moral, Aida; Pesce, Francesco; Bauerfeind, Anja; Rüschendorf, Franz; Rintisch, Carola; Petretto, Enrico; Barton, Paul J; Cook, Stuart A; Pinto, Yigal M; Bezzina, Connie R; Hubner, Norbert

2017-09-14

Genetic variation is an important determinant of RNA transcription and splicing, which in turn contributes to variation in human traits, including cardiovascular diseases. Here we report the first in-depth survey of heart transcriptome variation using RNA-sequencing in 97 patients with dilated cardiomyopathy and 108 non-diseased controls. We reveal extensive differences of gene expression and splicing between dilated cardiomyopathy patients and controls, affecting known as well as novel dilated cardiomyopathy genes. Moreover, we show a widespread effect of genetic variation on the regulation of transcription, isoform usage, and allele-specific expression. Systematic annotation of genome-wide association SNPs identifies 60 functional candidate genes for heart phenotypes, representing 20% of all published heart genome-wide association loci. Focusing on the dilated cardiomyopathy phenotype we found that eQTL variants are also enriched for dilated cardiomyopathy genome-wide association signals in two independent cohorts. RNA transcription, splicing, and allele-specific expression are each important determinants of the dilated cardiomyopathy phenotype and are controlled by genetic factors. Our results represent a powerful resource for the field of cardiovascular genetics.

The allostatic impact of chronic ethanol on gene expression: A genetic analysis of chronic intermittent ethanol treatment in the BXD cohort

PubMed Central

van der Vaart, Andrew D.; Wolstenholme, Jennifer T.; Smith, Maren L.; Harris, Guy M.; Lopez, Marcelo F.; Wolen, Aaron R.; Becker, Howard C.; Williams, Robert W.; Miles, Michael F.

2016-01-01

The transition from acute to chronic ethanol exposure leads to lasting behavioral and physiological changes such as increased consumption, dependence, and withdrawal. Changes in brain gene expression are hypothesized to underlie these adaptive responses to ethanol. Previous studies on acute ethanol identified genetic variation in brain gene expression networks and behavioral responses to ethanol across the BXD panel of recombinant inbred mice. In this work, we have performed the first joint genetic and genomic analysis of transcriptome shifts in response to chronic intermittent ethanol (CIE) by vapor chamber exposure in a BXD cohort. CIE treatment is known to produce significant and sustained changes in ethanol consumption with repeated cycles of ethanol vapor. Using Affymetrix microarray analysis of prefrontal cortex (PFC) and nucleus accumbens (NAC) RNA, we compared CIE expression responses to those seen following acute ethanol treatment, and to voluntary ethanol consumption. Gene expression changes in PFC and NAC after CIE overlapped significantly across brain regions and with previously published expression following acute ethanol. Genes highly modulated by CIE were enriched for specific biological processes including synaptic transmission, neuron ensheathment, intracellular signaling, and neuronal projection development. Expression quantitative trait locus (eQTL) analyses identified genomic loci associated with ethanol-induced transcriptional changes with largely distinct loci identified between brain regions. Correlating CIE-regulated genes to ethanol consumption data identified specific genes highly associated with variation in the increase in drinking seen with repeated cycles of CIE. In particular, multiple myelin-related genes were identified. Furthermore, genetic variance in or near dynamin3 (Dnm3) on Chr1 at ~164 Mb may have a major regulatory role in CIE-responsive gene expression. Dnm3 expression correlates significantly with ethanol consumption, is contained in a highly ranked functional group of CIE-regulated genes in the NAC, and has a cis-eQTL within a genomic region linked with multiple CIE-responsive genes. PMID:27838001

XGAP: a uniform and extensible data model and software platform for genotype and phenotype experiments

PubMed Central

2010-01-01

We present an extensible software model for the genotype and phenotype community, XGAP. Readers can download a standard XGAP (http://www.xgap.org) or auto-generate a custom version using MOLGENIS with programming interfaces to R-software and web-services or user interfaces for biologists. XGAP has simple load formats for any type of genotype, epigenotype, transcript, protein, metabolite or other phenotype data. Current functionality includes tools ranging from eQTL analysis in mouse to genome-wide association studies in humans. PMID:20214801

XGAP: a uniform and extensible data model and software platform for genotype and phenotype experiments.

PubMed

Swertz, Morris A; Velde, K Joeri van der; Tesson, Bruno M; Scheltema, Richard A; Arends, Danny; Vera, Gonzalo; Alberts, Rudi; Dijkstra, Martijn; Schofield, Paul; Schughart, Klaus; Hancock, John M; Smedley, Damian; Wolstencroft, Katy; Goble, Carole; de Brock, Engbert O; Jones, Andrew R; Parkinson, Helen E; Jansen, Ritsert C

2010-01-01

We present an extensible software model for the genotype and phenotype community, XGAP. Readers can download a standard XGAP (http://www.xgap.org) or auto-generate a custom version using MOLGENIS with programming interfaces to R-software and web-services or user interfaces for biologists. XGAP has simple load formats for any type of genotype, epigenotype, transcript, protein, metabolite or other phenotype data. Current functionality includes tools ranging from eQTL analysis in mouse to genome-wide association studies in humans.

Multiplexed droplet single-cell RNA-sequencing using natural genetic variation.

PubMed

Kang, Hyun Min; Subramaniam, Meena; Targ, Sasha; Nguyen, Michelle; Maliskova, Lenka; McCarthy, Elizabeth; Wan, Eunice; Wong, Simon; Byrnes, Lauren; Lanata, Cristina M; Gate, Rachel E; Mostafavi, Sara; Marson, Alexander; Zaitlen, Noah; Criswell, Lindsey A; Ye, Chun Jimmie

2018-01-01

Droplet single-cell RNA-sequencing (dscRNA-seq) has enabled rapid, massively parallel profiling of transcriptomes. However, assessing differential expression across multiple individuals has been hampered by inefficient sample processing and technical batch effects. Here we describe a computational tool, demuxlet, that harnesses natural genetic variation to determine the sample identity of each droplet containing a single cell (singlet) and detect droplets containing two cells (doublets). These capabilities enable multiplexed dscRNA-seq experiments in which cells from unrelated individuals are pooled and captured at higher throughput than in standard workflows. Using simulated data, we show that 50 single-nucleotide polymorphisms (SNPs) per cell are sufficient to assign 97% of singlets and identify 92% of doublets in pools of up to 64 individuals. Given genotyping data for each of eight pooled samples, demuxlet correctly recovers the sample identity of >99% of singlets and identifies doublets at rates consistent with previous estimates. We apply demuxlet to assess cell-type-specific changes in gene expression in 8 pooled lupus patient samples treated with interferon (IFN)-β and perform eQTL analysis on 23 pooled samples.

Identifying candidate genes for Type 2 Diabetes Mellitus and obesity through gene expression profiling in multiple tissues or cells.

PubMed

Chen, Junhui; Meng, Yuhuan; Zhou, Jinghui; Zhuo, Min; Ling, Fei; Zhang, Yu; Du, Hongli; Wang, Xiaoning

2013-01-01

Type 2 Diabetes Mellitus (T2DM) and obesity have become increasingly prevalent in recent years. Recent studies have focused on identifying causal variations or candidate genes for obesity and T2DM via analysis of expression quantitative trait loci (eQTL) within a single tissue. T2DM and obesity are affected by comprehensive sets of genes in multiple tissues. In the current study, gene expression levels in multiple human tissues from GEO datasets were analyzed, and 21 candidate genes displaying high percentages of differential expression were filtered out. Specifically, DENND1B, LYN, MRPL30, POC1B, PRKCB, RP4-655J12.3, HIBADH, and TMBIM4 were identified from the T2DM-control study, and BCAT1, BMP2K, CSRNP2, MYNN, NCKAP5L, SAP30BP, SLC35B4, SP1, BAP1, GRB14, HSP90AB1, ITGA5, and TOMM5 were identified from the obesity-control study. The majority of these genes are known to be involved in T2DM and obesity. Therefore, analysis of gene expression in various tissues using GEO datasets may be an effective and feasible method to determine novel or causal genes associated with T2DM and obesity.

The SNP rs6500843 in 16p13.3 is associated with survival specifically among chemotherapy-treated breast cancer patients.

PubMed

Fagerholm, Rainer; Schmidt, Marjanka K; Khan, Sofia; Rafiq, Sajjad; Tapper, William; Aittomäki, Kristiina; Greco, Dario; Heikkinen, Tuomas; Muranen, Taru A; Fasching, Peter A; Janni, Wolfgang; Weinshilboum, Richard; Loehberg, Christian R; Hopper, John L; Southey, Melissa C; Keeman, Renske; Lindblom, Annika; Margolin, Sara; Mannermaa, Arto; Kataja, Vesa; Chenevix-Trench, Georgia; Lambrechts, Diether; Wildiers, Hans; Chang-Claude, Jenny; Seibold, Petra; Couch, Fergus J; Olson, Janet E; Andrulis, Irene L; Knight, Julia A; García-Closas, Montserrat; Figueroa, Jonine; Hooning, Maartje J; Jager, Agnes; Shah, Mitul; Perkins, Barbara J; Luben, Robert; Hamann, Ute; Kabisch, Maria; Czene, Kamila; Hall, Per; Easton, Douglas F; Pharoah, Paul D P; Liu, Jianjun; Eccles, Diana; Blomqvist, Carl; Nevanlinna, Heli

2015-04-10

We have utilized a two-stage study design to search for SNPs associated with the survival of breast cancer patients treated with adjuvant chemotherapy. Our initial GWS data set consisted of 805 Finnish breast cancer cases (360 treated with adjuvant chemotherapy). The top 39 SNPs from this stage were analyzed in three independent data sets: iCOGS (n=6720 chemotherapy-treated cases), SUCCESS-A (n=3596), and POSH (n=518). Two SNPs were successfully validated: rs6500843 (any chemotherapy; per-allele HR 1.16, 95% C.I. 1.08-1.26, p=0.0001, p(adjusted)=0.0091), and rs11155012 (anthracycline therapy; per-allele HR 1.21, 95% C.I. 1.08-1.35, p=0.0010, p(adjusted)=0.0270). The SNP rs6500843 was found to specifically interact with adjuvant chemotherapy, independently of standard prognostic markers (p(interaction)=0.0009), with the rs6500843-GG genotype corresponding to the highest hazard among chemotherapy-treated cases (HR 1.47, 95% C.I. 1.20-1.80). Upon trans-eQTL analysis of public microarray data, the rs6500843 locus was found to associate with the expression of a group of genes involved in cell cycle control, notably AURKA, the expression of which also exhibited differential prognostic value between chemotherapy-treated and untreated cases in our analysis of microarray data. Based on previously published information, we propose that the eQTL genes may be connected to the rs6500843 locus via a RBFOX1-FOXM1 -mediated regulatory pathway.

Identification of a Sjögren's syndrome susceptibility locus at OAS1 that influences isoform switching, protein expression, and responsiveness to type I interferons

PubMed Central

Li, He; Reksten, Tove Ragna; Ice, John A.; Kelly, Jennifer A.; Adrianto, Indra; Wang, Shaofeng; He, Bo; Grundahl, Kiely M.; Glenn, Stuart B.; Miceli-Richard, Corinne; Bowman, Simon; Lester, Sue; Eriksson, Per; Brun, Johan G.; Gøransson, Lasse G.; Harboe, Erna; Guthridge, Joel M.; Patel, Ketan; Adler, Adam J.; Farris, A. Darise; Brennan, Michael T.; Chodosh, James; Gopalakrishnan, Rajaram; Weisman, Michael H.; Venuturupalli, Swamy; Wallace, Daniel J.; Hefner, Kimberly S.; Houston, Glen D.; Hughes, Pamela J.; Lewis, David M.; Radfar, Lida; Vista, Evan S.; Rohrer, Michael D.; Stone, Donald U.; Vyse, Timothy J.; Harley, John B.; James, Judith A.; Turner, Sean; Alevizos, Ilias; Anaya, Juan-Manuel; Rhodus, Nelson L.; Segal, Barbara M.; Montgomery, Courtney G.; Scofield, R. Hal; Kovats, Susan; Mariette, Xavier; Witte, Torsten; Rischmueller, Maureen; Omdal, Roald; Lessard, Christopher J.; Sivils, Kathy L.

2017-01-01

Sjögren’s syndrome (SS) is a common, autoimmune exocrinopathy distinguished by keratoconjunctivitis sicca and xerostomia. Patients frequently develop serious complications including lymphoma, pulmonary dysfunction, neuropathy, vasculitis, and debilitating fatigue. Dysregulation of type I interferon (IFN) pathway is a prominent feature of SS and is correlated with increased autoantibody titers and disease severity. To identify genetic determinants of IFN pathway dysregulation in SS, we performed cis-expression quantitative trait locus (eQTL) analyses focusing on differentially expressed type I IFN-inducible transcripts identified through a transcriptome profiling study. Multiple cis-eQTLs were associated with transcript levels of 2'-5'-oligoadenylate synthetase 1 (OAS1) peaking at rs10774671 (PeQTL = 6.05 × 10−14). Association of rs10774671 with SS susceptibility was identified and confirmed through meta-analysis of two independent cohorts (Pmeta = 2.59 × 10−9; odds ratio = 0.75; 95% confidence interval = 0.66–0.86). The risk allele of rs10774671 shifts splicing of OAS1 from production of the p46 isoform to multiple alternative transcripts, including p42, p48, and p44. We found that the isoforms were differentially expressed within each genotype in controls and patients with and without autoantibodies. Furthermore, our results showed that the three alternatively spliced isoforms lacked translational response to type I IFN stimulation. The p48 and p44 isoforms also had impaired protein expression governed by the 3' end of the transcripts. The SS risk allele of rs10774671 has been shown by others to be associated with reduced OAS1 enzymatic activity and ability to clear viral infections, as well as reduced responsiveness to IFN treatment. Our results establish OAS1 as a risk locus for SS and support a potential role for defective viral clearance due to altered IFN response as a genetic pathophysiological basis of this complex autoimmune disease. PMID:28640813

Genetic association analyses implicate aberrant regulation of innate and adaptive immunity genes in the pathogenesis of systemic lupus erythematosus

PubMed Central

Graham, Deborah S Cunninghame; Pinder, Christopher L; Tombleson, Philip; Behrens, Timothy W; Martín, Javier; Fairfax, Benjamin P; Knight, Julian C; Chen, Lingyan; Replogle, Joseph; Syvänen, Ann-Christine; Rönnblom, Lars; Graham, Robert R; Wither, Joan E; Rioux, John D; Alarcón-Riquelme, Marta E; Vyse, Timothy J

2015-01-01

Systemic lupus erythematosus (SLE; OMIM 152700) is a genetically complex autoimmune disease characterized by loss of immune tolerance to nuclear and cell surface antigens. Previous genome-wide association studies (GWAS) had modest sample sizes, reducing their scope and reliability. Our study comprised 7,219 cases and 15,991 controls of European ancestry: a new GWAS, meta-analysis with a published GWAS and a replication study. We have mapped 43 susceptibility loci, including 10 novel associations. Assisted by dense genome coverage, imputation provided evidence for missense variants underpinning associations in eight genes. Other likely causal genes were established by examining associated alleles for cis-acting eQTL effects in a range of ex vivo immune cells. We found an over-representation (n=16) of transcription factors among SLE susceptibility genes. This supports the view that aberrantly regulated gene expression networks in multiple cell types in both the innate and adaptive immune response contribute to the risk of developing SLE. PMID:26502338

[Fine mapping of complex disease susceptibility loci].

PubMed

Song, Qingfeng; Zhang, Hongxing; Ma, Yilong; Zhou, Gangqiao

2014-01-01

Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers have identified more than 3800 susceptibility loci for more than 660 diseases or traits. However, the most significantly associated variants or causative variants in these loci and their biological functions have remained to be clarified. These causative variants can help to elucidate the pathogenesis and discover new biomarkers of complex diseases. One of the main goals in the post-GWAS era is to identify the causative variants and susceptibility genes, and clarify their functional aspects by fine mapping. For common variants, imputation or re-sequencing based strategies were implemented to increase the number of analyzed variants and help to identify the most significantly associated variants. In addition, functional element, expression quantitative trait locus (eQTL) and haplotype analyses were performed to identify functional common variants and susceptibility genes. For rare variants, fine mapping was carried out by re-sequencing, rare haplotype analysis, family-based analysis, burden test, etc.This review summarizes the strategies and problems for fine mapping.

Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes

PubMed Central

McKay, James D.; Hung, Rayjean J.; Han, Younghun; Zong, Xuchen; Carreras-Torres, Robert; Christiani, David C.; Caporaso, Neil E.; Johansson, Mattias; Xiao, Xiangjun; Li, Yafang; Byun, Jinyoung; Dunning, Alison; Pooley, Karen A.; Qian, David C.; Ji, Xuemei; Liu, Geoffrey; Timofeeva, Maria N.; Bojesen, Stig E.; Wu, Xifeng; Le Marchand, Loic; Albanes, Demetrios; Bickeböller, Heike; Aldrich, Melinda C.; Bush, William S.; Tardon, Adonina; Rennert, Gad; Teare, M. Dawn; Field, John K.; Kiemeney, Lambertus A.; Lazarus, Philip; Haugen, Aage; Lam, Stephen; Schabath, Matthew B.; Andrew, Angeline S.; Shen, Hongbing; Hong, Yun-Chul; Yuan, Jian-Min; Bertazzi, Pier Alberto; Pesatori, Angela C.; Ye, Yuanqing; Diao, Nancy; Su, Li; Zhang, Ruyang; Brhane, Yonathan; Leighl, Natasha; Johansen, Jakob S.; Mellemgaard, Anders; Saliba, Walid; Haiman, Christopher A.; Wilkens, Lynne R.; Fernandez-Somoano, Ana; Fernandez-Tardon, Guillermo; van der Heijden, Henricus F.M.; Kim, Jin Hee; Dai, Juncheng; Hu, Zhibin; Davies, Michael PA; Marcus, Michael W.; Brunnström, Hans; Manjer, Jonas; Melander, Olle; Muller, David C.; Overvad, Kim; Trichopoulou, Antonia; Tumino, Rosario; Doherty, Jennifer A.; Barnett, Matt P.; Chen, Chu; Goodman, Gary E.; Cox, Angela; Taylor, Fiona; Woll, Penella; Brüske, Irene; Wichmann, H.-Erich; Manz, Judith; Muley, Thomas R.; Risch, Angela; Rosenberger, Albert; Grankvist, Kjell; Johansson, Mikael; Shepherd, Frances A.; Tsao, Ming-Sound; Arnold, Susanne M.; Haura, Eric B.; Bolca, Ciprian; Holcatova, Ivana; Janout, Vladimir; Kontic, Milica; Lissowska, Jolanta; Mukeria, Anush; Ognjanovic, Simona; Orlowski, Tadeusz M.; Scelo, Ghislaine; Swiatkowska, Beata; Zaridze, David; Bakke, Per; Skaug, Vidar; Zienolddiny, Shanbeh; Duell, Eric J.; Butler, Lesley M.; Koh, Woon-Puay; Gao, Yu-Tang; Houlston, Richard S.; McLaughlin, John; Stevens, Victoria L.; Joubert, Philippe; Lamontagne, Maxime; Nickle, David C.; Obeidat, Ma’en; Timens, Wim; Zhu, Bin; Song, Lei; Kachuri, Linda; Artigas, María Soler; Tobin, Martin D.; Wain, Louise V.; Rafnar, Thorunn; Thorgeirsson, Thorgeir E.; Reginsson, Gunnar W.; Stefansson, Kari; Hancock, Dana B.; Bierut, Laura J.; Spitz, Margaret R.; Gaddis, Nathan C.; Lutz, Sharon M.; Gu, Fangyi; Johnson, Eric O.; Kamal, Ahsan; Pikielny, Claudio; Zhu, Dakai; Lindströem, Sara; Jiang, Xia; Tyndale, Rachel F.; Chenevix-Trench, Georgia; Beesley, Jonathan; Bossé, Yohan; Chanock, Stephen; Brennan, Paul; Landi, Maria Teresa; Amos, Christopher I.

2017-01-01

Summary While several lung cancer susceptibility loci have been identified, much of lung cancer heritability remains unexplained. Here, 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated GWAS analysis of lung cancer on 29,266 patients and 56,450 controls. We identified 18 susceptibility loci achieving genome wide significance, including 10 novel loci. The novel loci highlighted the striking heterogeneity in genetic susceptibility across lung cancer histological subtypes, with four loci associated with lung cancer overall and six with lung adenocarcinoma. Gene expression quantitative trait analysis (eQTL) in 1,425 normal lung tissues highlighted RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes, OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer. PMID:28604730

Common variants of OPA1 conferring genetic susceptibility to leprosy in Han Chinese from Southwest China.

PubMed

Xiang, Yang-Lin; Zhang, Deng-Feng; Wang, Dong; Li, Yu-Ye; Yao, Yong-Gang

2015-11-01

Leprosy is an ancient chronic infection caused by Mycobacterium leprae. Onset of leprosy was highly affected by host nutritional condition and energy production, (partially) due to genomic loss and parasitic life style of M. leprae. The optic atrophy 1 (OPA1) gene plays an essential role in mitochondria, which function in cellular energy supply and innate immunity. To investigate the potential involvement of OPA1 in leprosy. We analyzed 7 common genetic variants of OPA1 in 1110 Han Chinese subjects with and without leprosy, followed by mRNA expression profiling and protein-protein interaction (PPI) network analysis. We observed positive associations between OPA1 variants rs9838374 (Pgenotypic=0.003) and rs414237 (Pgenotypic=0.002) with lepromatous leprosy. expression quantitative trait loci (eQTL) analysis showed that the leprosy-related risk allele C of rs414237 is correlated with lower OPA1 mRNA expression level. Indeed, we identified a decrease of OPA1 mRNA expression in both with patients and cellular model of leprosy. In addition, the PPI analysis showed that OPA1 protein was actively involved in the interaction network of M. leprae induced differentially expressed genes. Our results indicated that OPA1 variants confer risk of leprosy and may affect OPA1 expression, mitochondrial function and antimicrobial pathways. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Congruence of Additive and Non-Additive Effects on Gene Expression Estimated from Pedigree and SNP Data

PubMed Central

Powell, Joseph E.; Henders, Anjali K.; McRae, Allan F.; Kim, Jinhee; Hemani, Gibran; Martin, Nicholas G.; Dermitzakis, Emmanouil T.; Gibson, Greg

2013-01-01

There is increasing evidence that heritable variation in gene expression underlies genetic variation in susceptibility to disease. Therefore, a comprehensive understanding of the similarity between relatives for transcript variation is warranted—in particular, dissection of phenotypic variation into additive and non-additive genetic factors and shared environmental effects. We conducted a gene expression study in blood samples of 862 individuals from 312 nuclear families containing MZ or DZ twin pairs using both pedigree and genotype information. From a pedigree analysis we show that the vast majority of genetic variation across 17,994 probes is additive, although non-additive genetic variation is identified for 960 transcripts. For 180 of the 960 transcripts with non-additive genetic variation, we identify expression quantitative trait loci (eQTL) with dominance effects in a sample of 339 unrelated individuals and replicate 31% of these associations in an independent sample of 139 unrelated individuals. Over-dominance was detected and replicated for a trans association between rs12313805 and ETV6, located 4MB apart on chromosome 12. Surprisingly, only 17 probes exhibit significant levels of common environmental effects, suggesting that environmental and lifestyle factors common to a family do not affect expression variation for most transcripts, at least those measured in blood. Consistent with the genetic architecture of common diseases, gene expression is predominantly additive, but a minority of transcripts display non-additive effects. PMID:23696747

Congruence of additive and non-additive effects on gene expression estimated from pedigree and SNP data.

PubMed

Powell, Joseph E; Henders, Anjali K; McRae, Allan F; Kim, Jinhee; Hemani, Gibran; Martin, Nicholas G; Dermitzakis, Emmanouil T; Gibson, Greg; Montgomery, Grant W; Visscher, Peter M

2013-05-01

There is increasing evidence that heritable variation in gene expression underlies genetic variation in susceptibility to disease. Therefore, a comprehensive understanding of the similarity between relatives for transcript variation is warranted--in particular, dissection of phenotypic variation into additive and non-additive genetic factors and shared environmental effects. We conducted a gene expression study in blood samples of 862 individuals from 312 nuclear families containing MZ or DZ twin pairs using both pedigree and genotype information. From a pedigree analysis we show that the vast majority of genetic variation across 17,994 probes is additive, although non-additive genetic variation is identified for 960 transcripts. For 180 of the 960 transcripts with non-additive genetic variation, we identify expression quantitative trait loci (eQTL) with dominance effects in a sample of 339 unrelated individuals and replicate 31% of these associations in an independent sample of 139 unrelated individuals. Over-dominance was detected and replicated for a trans association between rs12313805 and ETV6, located 4MB apart on chromosome 12. Surprisingly, only 17 probes exhibit significant levels of common environmental effects, suggesting that environmental and lifestyle factors common to a family do not affect expression variation for most transcripts, at least those measured in blood. Consistent with the genetic architecture of common diseases, gene expression is predominantly additive, but a minority of transcripts display non-additive effects.

Heritability and genetic basis of protein level variation in an outbred population

PubMed Central

Liu, Yi-Chun; Tekkedil, Manu M.; Steinmetz, Lars M.; Caudy, Amy A.; Fraser, Andrew G.

2014-01-01

The genetic basis of heritable traits has been studied for decades. Although recent mapping efforts have elucidated genetic determinants of transcript levels, mapping of protein abundance has lagged. Here, we analyze levels of 4084 GFP-tagged yeast proteins in the progeny of a cross between a laboratory and a wild strain using flow cytometry and high-content microscopy. The genotype of trans variants contributed little to protein level variation between individual cells but explained >50% of the variance in the population’s average protein abundance for half of the GFP fusions tested. To map trans-acting factors responsible, we performed flow sorting and bulk segregant analysis of 25 proteins, finding a median of five protein quantitative trait loci (pQTLs) per GFP fusion. Further, we find that cis-acting variants predominate; the genotype of a gene and its surrounding region had a large effect on protein level six times more frequently than the rest of the genome combined. We present evidence for both shared and independent genetic control of transcript and protein abundance: More than half of the expression QTLs (eQTLs) contribute to changes in protein levels of regulated genes, but several pQTLs do not affect their cognate transcript levels. Allele replacements of genes known to underlie trans eQTL hotspots confirmed the correlation of effects on mRNA and protein levels. This study represents the first genome-scale measurement of genetic contribution to protein levels in single cells and populations, identifies more than a hundred trans pQTLs, and validates the propagation of effects associated with transcript variation to protein abundance. PMID:24823668

Identification of Splicing Quantitative Trait Loci (sQTL) in Drosophila melanogaster with Developmental Lead (Pb2+) Exposure

PubMed Central

Qu, Wen; Gurdziel, Katherine; Pique-Regi, Roger; Ruden, Douglas M.

2017-01-01

Lead (Pb) poisoning has been a major public health issue globally and the recent Flint water crisis has drawn nation-wide attention to its effects. To better understand how lead plays a role as a neurotoxin, we utilized the Drosophila melanogaster model to study the genetic effects of lead exposure during development and identified lead-responsive genes. In our previous studies, we have successfully identified hundreds of lead-responsive expression QTLs (eQTLs) by using RNA-seq analysis on heads collected from the Drosophila Synthetic Population Resource. Cis-eQTLs, also known as allele-specific expression (ASE) polymorphisms, are generally single-nucleotide polymorphisms in the promoter regions of genes that affect expression of the gene, such as by inhibiting the binding of transcription factors. Trans-eQTLs are genes that regulate mRNA levels for many genes, and are generally thought to be SNPs in trans-acting transcription or translation factors. In this study, we focused our attention on alternative splicing events that are affected by lead exposure. Splicing QTLs (sQTLs), which can be caused by SNPs that alter splicing or alternative splicing (AS), such as by changing the sequence-specific binding affinity of splicing factors to the pre-mRNA. We applied two methods in search for sQTLs by using RNA-seq data from control and lead-exposed w1118 Drosophila heads. First, we used the fraction of reads in a gene that falls in each exon as the phenotype. Second, we directly compared the transcript counts among the various splicing isoforms as the phenotype. Among the 1,236 potential Pb-responsive sQTLs (p < 0.0001, FDR < 0.39), mostly cis-sQTLs, one of the most distinct genes is Dscam1 (Down Syndrome Cell Adhesion Molecule), which has over 30,000 potential alternative splicing isoforms. We have also identified a candidate Pb-responsive trans-sQTL hotspot that appears to regulate 129 genes that are enriched in the “cation channel” gene ontology category, suggesting a model in which alternative splicing of these channels might lead to an increase in the elimination of Pb2+ from the neurons encoding these channels. To our knowledge, this is the first paper that uses sQTL analyses to understand the neurotoxicology of an environmental toxin in any organism, and the first reported discovery of a candidate trans-sQTL hotspot. PMID:29114259

Loci influencing blood pressure identified using a cardiovascular gene-centric array.

PubMed

Ganesh, Santhi K; Tragante, Vinicius; Guo, Wei; Guo, Yiran; Lanktree, Matthew B; Smith, Erin N; Johnson, Toby; Castillo, Berta Almoguera; Barnard, John; Baumert, Jens; Chang, Yen-Pei Christy; Elbers, Clara C; Farrall, Martin; Fischer, Mary E; Franceschini, Nora; Gaunt, Tom R; Gho, Johannes M I H; Gieger, Christian; Gong, Yan; Isaacs, Aaron; Kleber, Marcus E; Mateo Leach, Irene; McDonough, Caitrin W; Meijs, Matthijs F L; Mellander, Olle; Molony, Cliona M; Nolte, Ilja M; Padmanabhan, Sandosh; Price, Tom S; Rajagopalan, Ramakrishnan; Shaffer, Jonathan; Shah, Sonia; Shen, Haiqing; Soranzo, Nicole; van der Most, Peter J; Van Iperen, Erik P A; Van Setten, Jessica; Van Setten, Jessic A; Vonk, Judith M; Zhang, Li; Beitelshees, Amber L; Berenson, Gerald S; Bhatt, Deepak L; Boer, Jolanda M A; Boerwinkle, Eric; Burkley, Ben; Burt, Amber; Chakravarti, Aravinda; Chen, Wei; Cooper-Dehoff, Rhonda M; Curtis, Sean P; Dreisbach, Albert; Duggan, David; Ehret, Georg B; Fabsitz, Richard R; Fornage, Myriam; Fox, Ervin; Furlong, Clement E; Gansevoort, Ron T; Hofker, Marten H; Hovingh, G Kees; Kirkland, Susan A; Kottke-Marchant, Kandice; Kutlar, Abdullah; Lacroix, Andrea Z; Langaee, Taimour Y; Li, Yun R; Lin, Honghuang; Liu, Kiang; Maiwald, Steffi; Malik, Rainer; Murugesan, Gurunathan; Newton-Cheh, Christopher; O'Connell, Jeffery R; Onland-Moret, N Charlotte; Ouwehand, Willem H; Palmas, Walter; Penninx, Brenda W; Pepine, Carl J; Pettinger, Mary; Polak, Joseph F; Ramachandran, Vasan S; Ranchalis, Jane; Redline, Susan; Ridker, Paul M; Rose, Lynda M; Scharnag, Hubert; Schork, Nicholas J; Shimbo, Daichi; Shuldiner, Alan R; Srinivasan, Sathanur R; Stolk, Ronald P; Taylor, Herman A; Thorand, Barbara; Trip, Mieke D; van Duijn, Cornelia M; Verschuren, W Monique; Wijmenga, Cisca; Winkelmann, Bernhard R; Wyatt, Sharon; Young, J Hunter; Boehm, Bernhard O; Caulfield, Mark J; Chasman, Daniel I; Davidson, Karina W; Doevendans, Pieter A; Fitzgerald, Garret A; Gums, John G; Hakonarson, Hakon; Hillege, Hans L; Illig, Thomas; Jarvik, Gail P; Johnson, Julie A; Kastelein, John J P; Koenig, Wolfgang; März, Winfried; Mitchell, Braxton D; Murray, Sarah S; Oldehinkel, Albertine J; Rader, Daniel J; Reilly, Muredach P; Reiner, Alex P; Schadt, Eric E; Silverstein, Roy L; Snieder, Harold; Stanton, Alice V; Uitterlinden, André G; van der Harst, Pim; van der Schouw, Yvonne T; Samani, Nilesh J; Johnson, Andrew D; Munroe, Patricia B; de Bakker, Paul I W; Zhu, Xiaofeng; Levy, Daniel; Keating, Brendan J; Asselbergs, Folkert W

2013-04-15

Blood pressure (BP) is a heritable determinant of risk for cardiovascular disease (CVD). To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP) and pulse pressure (PP), we genotyped ∼50 000 single-nucleotide polymorphisms (SNPs) that capture variation in ∼2100 candidate genes for cardiovascular phenotypes in 61 619 individuals of European ancestry from cohort studies in the USA and Europe. We identified novel associations between rs347591 and SBP (chromosome 3p25.3, in an intron of HRH1) and between rs2169137 and DBP (chromosome1q32.1 in an intron of MDM4) and between rs2014408 and SBP (chromosome 11p15 in an intron of SOX6), previously reported to be associated with MAP. We also confirmed 10 previously known loci associated with SBP, DBP, MAP or PP (ADRB1, ATP2B1, SH2B3/ATXN2, CSK, CYP17A1, FURIN, HFE, LSP1, MTHFR, SOX6) at array-wide significance (P < 2.4 × 10(-6)). We then replicated these associations in an independent set of 65 886 individuals of European ancestry. The findings from expression QTL (eQTL) analysis showed associations of SNPs in the MDM4 region with MDM4 expression. We did not find any evidence of association of the two novel SNPs in MDM4 and HRH1 with sequelae of high BP including coronary artery disease (CAD), left ventricular hypertrophy (LVH) or stroke. In summary, we identified two novel loci associated with BP and confirmed multiple previously reported associations. Our findings extend our understanding of genes involved in BP regulation, some of which may eventually provide new targets for therapeutic intervention.

Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence.

PubMed

Savage, Jeanne E; Jansen, Philip R; Stringer, Sven; Watanabe, Kyoko; Bryois, Julien; de Leeuw, Christiaan A; Nagel, Mats; Awasthi, Swapnil; Barr, Peter B; Coleman, Jonathan R I; Grasby, Katrina L; Hammerschlag, Anke R; Kaminski, Jakob A; Karlsson, Robert; Krapohl, Eva; Lam, Max; Nygaard, Marianne; Reynolds, Chandra A; Trampush, Joey W; Young, Hannah; Zabaneh, Delilah; Hägg, Sara; Hansell, Narelle K; Karlsson, Ida K; Linnarsson, Sten; Montgomery, Grant W; Muñoz-Manchado, Ana B; Quinlan, Erin B; Schumann, Gunter; Skene, Nathan G; Webb, Bradley T; White, Tonya; Arking, Dan E; Avramopoulos, Dimitrios; Bilder, Robert M; Bitsios, Panos; Burdick, Katherine E; Cannon, Tyrone D; Chiba-Falek, Ornit; Christoforou, Andrea; Cirulli, Elizabeth T; Congdon, Eliza; Corvin, Aiden; Davies, Gail; Deary, Ian J; DeRosse, Pamela; Dickinson, Dwight; Djurovic, Srdjan; Donohoe, Gary; Conley, Emily Drabant; Eriksson, Johan G; Espeseth, Thomas; Freimer, Nelson A; Giakoumaki, Stella; Giegling, Ina; Gill, Michael; Glahn, David C; Hariri, Ahmad R; Hatzimanolis, Alex; Keller, Matthew C; Knowles, Emma; Koltai, Deborah; Konte, Bettina; Lahti, Jari; Le Hellard, Stephanie; Lencz, Todd; Liewald, David C; London, Edythe; Lundervold, Astri J; Malhotra, Anil K; Melle, Ingrid; Morris, Derek; Need, Anna C; Ollier, William; Palotie, Aarno; Payton, Antony; Pendleton, Neil; Poldrack, Russell A; Räikkönen, Katri; Reinvang, Ivar; Roussos, Panos; Rujescu, Dan; Sabb, Fred W; Scult, Matthew A; Smeland, Olav B; Smyrnis, Nikolaos; Starr, John M; Steen, Vidar M; Stefanis, Nikos C; Straub, Richard E; Sundet, Kjetil; Tiemeier, Henning; Voineskos, Aristotle N; Weinberger, Daniel R; Widen, Elisabeth; Yu, Jin; Abecasis, Goncalo; Andreassen, Ole A; Breen, Gerome; Christiansen, Lene; Debrabant, Birgit; Dick, Danielle M; Heinz, Andreas; Hjerling-Leffler, Jens; Ikram, M Arfan; Kendler, Kenneth S; Martin, Nicholas G; Medland, Sarah E; Pedersen, Nancy L; Plomin, Robert; Polderman, Tinca J C; Ripke, Stephan; van der Sluis, Sophie; Sullivan, Patrick F; Vrieze, Scott I; Wright, Margaret J; Posthuma, Danielle

2018-06-25

Intelligence is highly heritable 1 and a major determinant of human health and well-being 2 . Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence 3-7 , but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.

Exploring hepsin functional genetic variation association with disease specific protein expression in bipolar disorder: Applications of a proteomic informed genomic approach.

PubMed

Nassan, Malik; Jia, Yun-Fang; Jenkins, Greg; Colby, Colin; Feeder, Scott; Choi, Doo-Sup; Veldic, Marin; McElroy, Susan L; Bond, David J; Weinshilboum, Richard; Biernacka, Joanna M; Frye, Mark A

2017-12-01

In a prior discovery study, increased levels of serum Growth Differentiation Factor 15 (GDF15), Hepsin (HPN), and Matrix Metalloproteinase-7 (MMP7) were observed in bipolar depressed patients vs controls. This exploratory post-hoc analysis applied a proteomic-informed genomic research strategy to study the potential functional role of these proteins in bipolar disorder (BP). Utilizing the Genotype-Tissue Expression (GTEx) database to identify cis-acting blood expression quantitative trait loci (cis-eQTLs), five eQTL variants from the HPN gene were analyzed for association with BP cases using genotype data of cases from the discovery study (n = 58) versus healthy controls (n = 777). After adjusting for relevant covariates, we analyzed the relationship between these 5 cis-eQTLs and HPN serum level in the BP cases. All 5 cis-eQTL minor alleles were significantly more frequent in BP cases vs controls [(rs62122114, OR = 1.6, p = 0.02), (rs67003112, OR = 1.6, p = 0.02), (rs4997929, OR = 1.7, p = 0.01), (rs12610663, OR = 1.7, p = 0.01), (rs62122148, OR = 1.7, P = 0.01)]. The minor allele (A) in rs62122114 was significantly associated with increased serum HPN level in BP cases (Beta = 0.12, P = 0.049). However, this same minor allele was associated with reduced gene expression in GTEx controls. These exploratory analyses suggest that genetic variation in/near the gene encoding for hepsin protein may influence risk of bipolar disorder. This genetic variation, at least for the rs62122114-A allele, may have functional impact (i.e. differential expression) as evidenced by serum HPN protein expression. Although limited by small sample size, this study highlights the merits of proteomic informed functional genomic studies as a tool to investigate with greater precision the genetic risk of bipolar disorder and secondary relationships to protein expression recognizing, and encouraging in subsequent studies, high likelihood of epigenetic modification of genetic disease risk. Copyright © 2017. Published by Elsevier Ltd.

Functional evaluation of genetic variants associated with endometriosis near GREB1.

PubMed

Fung, Jenny N; Holdsworth-Carson, Sarah J; Sapkota, Yadav; Zhao, Zhen Zhen; Jones, Lincoln; Girling, Jane E; Paiva, Premila; Healey, Martin; Nyholt, Dale R; Rogers, Peter A W; Montgomery, Grant W

2015-05-01

Do DNA variants in the growth regulation by estrogen in breast cancer 1 (GREB1) region regulate endometrial GREB1 expression and increase the risk of developing endometriosis in women? We identified new single nucleotide polymorphisms (SNPs) with strong association with endometriosis at the GREB1 locus although we did not detect altered GREB1 expression in endometriosis patients with defined genotypes. Genome-wide association studies have identified the GREB1 region on chromosome 2p25.1 for increasing endometriosis risk. The differential expression of GREB1 has also been reported by others in association with endometriosis disease phenotype. Fine mapping studies comprehensively evaluated SNPs within the GREB1 region in a large-scale data set (>2500 cases and >4000 controls). Publicly available bioinformatics tools were employed to functionally annotate SNPs showing the strongest association signal with endometriosis risk. Endometrial GREB1 mRNA and protein expression was studied with respect to phases of the menstrual cycle (n = 2-45 per cycle stage) and expression quantitative trait loci (eQTL) analysis for significant SNPs were undertaken for GREB1 [mRNA (n = 94) and protein (n = 44) in endometrium]. Participants in this study are females who provided blood and/or endometrial tissue samples in a hospital setting. The key SNPs were genotyped using Sequenom MassARRAY. The functional roles and regulatory annotations for identified SNPs are predicted by various publicly available bioinformatics tools. Endometrial GREB1 expression work employed qRT-PCR, western blotting and immunohistochemistry studies. Fine mapping results identified a number of SNPs showing stronger association (0.004 < P < 0.032) with endometriosis risk than the original GWAS SNP (rs13394619) (P = 0.034). Some of these SNPs were predicted to have functional roles, for example, interaction with transcription factor motifs. The haplotype (a combination of alleles) formed by the risk alleles from two common SNPs showed significant association (P = 0.026) with endometriosis and epistasis analysis showed no evidence for interaction between the two SNPs, suggesting an additive effect of SNPs on endometriosis risk. In normal human endometrium, GREB1 protein expression was altered depending on the cycle stage (significantly different in late proliferative versus late secretory, P < 0.05) and cell type (glandular epithelium, not stromal cells). However, GREB1 expression in endometriosis cases versus controls and eQTL analyses did not reveal any significant changes. In silico prediction tools are generally based on cell lines different to our tissue and disease of interest. Functional annotations drawn from these analyses should be considered with this limitation in mind. We identified cell-specific and hormone-specific changes in GREB1 protein expression. The lack of a significant difference observed following our GREB1 expression studies may be the result of moderate power on mixed cell populations in the endometrial tissue samples. This study further implicates the GREB1 region on chromosome 2p25.1 and the GREB1 gene with involvement in endometriosis risk. More detailed functional studies are required to determine the role of the novel GREB1 transcripts in endometriosis pathophysiology. Funding for this work was provided by NHMRC Project Grants APP1012245, APP1026033, APP1049472 and APP1046880. There are no competing interests. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Weak sharing of genetic association signals in three lung cancer subtypes: evidence at the SNP, gene, regulation, and pathway levels.

PubMed

O'Brien, Timothy D; Jia, Peilin; Caporaso, Neil E; Landi, Maria Teresa; Zhao, Zhongming

2018-02-27

There are two main types of lung cancer: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). NSCLC has many subtypes, but the two most common are lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). These subtypes are mainly classified by physiological and pathological characteristics, although there is increasing evidence of genetic and molecular differences as well. Although some work has been done at the somatic level to explore the genetic and biological differences among subtypes, little work has been done that interrogates these differences at the germline level to characterize the unique and shared susceptibility genes for each subtype. We used single-nucleotide polymorphisms (SNPs) from a genome-wide association study (GWAS) of European samples to interrogate the similarity of the subtypes at the SNP, gene, pathway, and regulatory levels. We expanded these genotyped SNPs to include all SNPs in linkage disequilibrium (LD) using data from the 1000 Genomes Project. We mapped these SNPs to several lung tissue expression quantitative trait loci (eQTL) and enhancer datasets to identify regulatory SNPs and their target genes. We used these genes to perform a biological pathway analysis for each subtype. We identified 8295, 8734, and 8361 SNPs with moderate association signals for LUAD, LUSC, and SCLC, respectively. Those SNPs had p < 1 × 10 - 3 in the original GWAS or were within LD (r 2 > 0.8, Europeans) to the genotyped SNPs. We identified 215, 320, and 172 disease-associated genes for LUAD, LUSC, and SCLC, respectively. Only five genes (CHRNA5, IDH3A, PSMA4, RP11-650 L12.2, and TBC1D2B) overlapped all subtypes. Furthermore, we observed only two pathways from the Kyoto Encyclopedia of Genes and Genomes shared by all subtypes. At the regulatory level, only three eQTL target genes and two enhancer target genes overlapped between all subtypes. Our results suggest that the three lung cancer subtypes do not share much genetic signal at the SNP, gene, pathway, or regulatory level, which differs from the common subtype classification based upon histology. However, three (CHRNA5, IDH3A, and PSMA4) of the five genes shared between the subtypes are well-known lung cancer genes that may act as general lung cancer genes regardless of subtype.

Genome-wide significant risk associations for mucinous ovarian carcinoma.

PubMed

Kelemen, Linda E; Lawrenson, Kate; Tyrer, Jonathan; Li, Qiyuan; Lee, Janet M; Seo, Ji-Heui; Phelan, Catherine M; Beesley, Jonathan; Chen, Xiaoqing; Spindler, Tassja J; Aben, Katja K H; Anton-Culver, Hoda; Antonenkova, Natalia

2015-08-01

Genome-wide association studies have identified several risk associations for ovarian carcinomas but not for mucinous ovarian carcinomas (MOCs). Our analysis of 1,644 MOC cases and 21,693 controls with imputation identified 3 new risk associations: rs752590 at 2q13 (P = 3.3 × 10(-8)), rs711830 at 2q31.1 (P = 7.5 × 10(-12)) and rs688187 at 19q13.2 (P = 6.8 × 10(-13)). We identified significant expression quantitative trait locus (eQTL) associations for HOXD9 at 2q31.1 in ovarian (P = 4.95 × 10(-4), false discovery rate (FDR) = 0.003) and colorectal (P = 0.01, FDR = 0.09) tumors and for PAX8 at 2q13 in colorectal tumors (P = 0.03, FDR = 0.09). Chromosome conformation capture analysis identified interactions between the HOXD9 promoter and risk-associated SNPs at 2q31.1. Overexpressing HOXD9 in MOC cells augmented the neoplastic phenotype. These findings provide the first evidence for MOC susceptibility variants and insights into the underlying biology of the disease.

Predicting enhancer activity and variant impact using gkm-SVM.

PubMed

Beer, Michael A

2017-09-01

We participated in the Critical Assessment of Genome Interpretation eQTL challenge to further test computational models of regulatory variant impact and their association with human disease. Our prediction model is based on a discriminative gapped-kmer SVM (gkm-SVM) trained on genome-wide chromatin accessibility data in the cell type of interest. The comparisons with massively parallel reporter assays (MPRA) in lymphoblasts show that gkm-SVM is among the most accurate prediction models even though all other models used the MPRA data for model training, and gkm-SVM did not. In addition, we compare gkm-SVM with other MPRA datasets and show that gkm-SVM is a reliable predictor of expression and that deltaSVM is a reliable predictor of variant impact in K562 cells and mouse retina. We further show that DHS (DNase-I hypersensitive sites) and ATAC-seq (assay for transposase-accessible chromatin using sequencing) data are equally predictive substrates for training gkm-SVM, and that DHS regions flanked by H3K27Ac and H3K4me1 marks are more predictive than DHS regions alone. © 2017 Wiley Periodicals, Inc.

Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes.

PubMed

McKay, James D; Hung, Rayjean J; Han, Younghun; Zong, Xuchen; Carreras-Torres, Robert; Christiani, David C; Caporaso, Neil E; Johansson, Mattias; Xiao, Xiangjun; Li, Yafang; Byun, Jinyoung; Dunning, Alison; Pooley, Karen A; Qian, David C; Ji, Xuemei; Liu, Geoffrey; Timofeeva, Maria N; Bojesen, Stig E; Wu, Xifeng; Le Marchand, Loic; Albanes, Demetrios; Bickeböller, Heike; Aldrich, Melinda C; Bush, William S; Tardon, Adonina; Rennert, Gad; Teare, M Dawn; Field, John K; Kiemeney, Lambertus A; Lazarus, Philip; Haugen, Aage; Lam, Stephen; Schabath, Matthew B; Andrew, Angeline S; Shen, Hongbing; Hong, Yun-Chul; Yuan, Jian-Min; Bertazzi, Pier Alberto; Pesatori, Angela C; Ye, Yuanqing; Diao, Nancy; Su, Li; Zhang, Ruyang; Brhane, Yonathan; Leighl, Natasha; Johansen, Jakob S; Mellemgaard, Anders; Saliba, Walid; Haiman, Christopher A; Wilkens, Lynne R; Fernandez-Somoano, Ana; Fernandez-Tardon, Guillermo; van der Heijden, Henricus F M; Kim, Jin Hee; Dai, Juncheng; Hu, Zhibin; Davies, Michael P A; Marcus, Michael W; Brunnström, Hans; Manjer, Jonas; Melander, Olle; Muller, David C; Overvad, Kim; Trichopoulou, Antonia; Tumino, Rosario; Doherty, Jennifer A; Barnett, Matt P; Chen, Chu; Goodman, Gary E; Cox, Angela; Taylor, Fiona; Woll, Penella; Brüske, Irene; Wichmann, H-Erich; Manz, Judith; Muley, Thomas R; Risch, Angela; Rosenberger, Albert; Grankvist, Kjell; Johansson, Mikael; Shepherd, Frances A; Tsao, Ming-Sound; Arnold, Susanne M; Haura, Eric B; Bolca, Ciprian; Holcatova, Ivana; Janout, Vladimir; Kontic, Milica; Lissowska, Jolanta; Mukeria, Anush; Ognjanovic, Simona; Orlowski, Tadeusz M; Scelo, Ghislaine; Swiatkowska, Beata; Zaridze, David; Bakke, Per; Skaug, Vidar; Zienolddiny, Shanbeh; Duell, Eric J; Butler, Lesley M; Koh, Woon-Puay; Gao, Yu-Tang; Houlston, Richard S; McLaughlin, John; Stevens, Victoria L; Joubert, Philippe; Lamontagne, Maxime; Nickle, David C; Obeidat, Ma'en; Timens, Wim; Zhu, Bin; Song, Lei; Kachuri, Linda; Artigas, María Soler; Tobin, Martin D; Wain, Louise V; Rafnar, Thorunn; Thorgeirsson, Thorgeir E; Reginsson, Gunnar W; Stefansson, Kari; Hancock, Dana B; Bierut, Laura J; Spitz, Margaret R; Gaddis, Nathan C; Lutz, Sharon M; Gu, Fangyi; Johnson, Eric O; Kamal, Ahsan; Pikielny, Claudio; Zhu, Dakai; Lindströem, Sara; Jiang, Xia; Tyndale, Rachel F; Chenevix-Trench, Georgia; Beesley, Jonathan; Bossé, Yohan; Chanock, Stephen; Brennan, Paul; Landi, Maria Teresa; Amos, Christopher I

2017-07-01

Although several lung cancer susceptibility loci have been identified, much of the heritability for lung cancer remains unexplained. Here 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated genome-wide association study (GWAS) analysis of lung cancer in 29,266 cases and 56,450 controls. We identified 18 susceptibility loci achieving genome-wide significance, including 10 new loci. The new loci highlight the striking heterogeneity in genetic susceptibility across the histological subtypes of lung cancer, with four loci associated with lung cancer overall and six loci associated with lung adenocarcinoma. Gene expression quantitative trait locus (eQTL) analysis in 1,425 normal lung tissue samples highlights RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer.

Cross-cancer genome-wide analysis of lung, ovary, breast, prostate and colorectal cancer reveals novel pleiotropic associations

PubMed Central

Fehringer, Gordon; Kraft, Peter; Pharoah, Paul D.; Eeles, Rosalind A.; Chatterjee, Nilanjan; Schumacher, Fred; Schildkraut, Joellen; Lindström, Sara; Brennan, Paul; Bickeböller, Heike; Houlston, Richard S.; Landi, Maria Teresa; Caporaso, Neil; Risch, Angela; Olama, Ali Amin Al; Berndt, Sonja I; Giovannucci, Edward; Grönberg, Henrik; Kote-Jarai, Zsofia; Ma, Jing; Muir, Kenneth; Stampfer, Meir; Stevens, Victoria L.; Wiklund, Fredrik; Willett, Walter; Goode, Ellen L.; Permuth, Jennifer; Risch, Harvey A.; Reid, Brett M.; Bezieau, Stephane; Brenner, Hermann; Chan, Andrew T.; Chang-Claude, Jenny; Hudson, Thomas J.; Kocarnik, Jonathan K.; Newcomb, Polly A.; Schoen, Robert E.; Slattery, Martha L.; White, Emily; Adank, Muriel A.; Ahsan, Habibul; Aittomäki, Kristiina; Baglietto, Laura; Blomquist, Carl; Canzian, Federico; Czene, Kamila; dos-Santos-Silva, Isabel; Eliassen, A. Heather; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Garcia-Closas, Montserrat; Gaudet, Mia M.; Johnson, Nichola; Hall, Per; Hazra, Aditi; Hein, Rebecca; Hofman, Albert; Hopper, John L.; Irwanto, Astrid; Johansson, Mattias; Kaaks, Rudolf; Kibriya, Muhammad G.; Lichtner, Peter; Liu, Jianjun; Lund, Eiliv; Makalic, Enes; Meindl, Alfons; Müller-Myhsok, Bertram; Muranen, Taru A.; Nevanlinna, Heli; Peeters, Petra H.; Peto, Julian; Prentice, Ross L.; Rahman, Nazneen; Sanchez, Maria Jose; Schmidt, Daniel F.; Schmutzler, Rita K.; Southey, Melissa C.; Tamimi, Rulla; Travis, Ruth C.; Turnbull, Clare; Uitterlinden, Andre G.; Wang, Zhaoming; Whittemore, Alice S.; Yang, Xiaohong R.; Zheng, Wei; Rafnar, Thorunn; Gudmundsson, Julius; Stacey, Simon N.; Stefansson, Kari; Sulem, Patrick; Chen, Y. Ann; Tyrer, Jonathan P.; Christiani, David C.; Wei, Yongyue; Shen, Hongbing; Hu, Zhibin; Shu, Xiao-Ou; Shiraishi, Kouya; Takahashi, Atsushi; Bossé, Yohan; Obeidat, Ma’en; Nickle, David; Timens, Wim; Freedman, Matthew L.; Li, Qiyuan; Seminara, Daniela; Chanock, Stephen J.; Gong, Jian; Peters, Ulrike; Gruber, Stephen B.; Amos, Christopher I.; Sellers, Thomas A.; Easton, Douglas F.; Hunter, David J.; Haiman, Christopher A.; Henderson, Brian E.; Hung, Rayjean J.

2016-01-01

Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-staged approach to conduct genome-wide association studies for lung, ovary, breast, prostate and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression. PMID:27197191

ABCC5 Transporter is a Novel Type 2 Diabetes Susceptibility Gene in European and African American Populations

PubMed Central

Direk, Kenan; Lau, Winston; Small, Kerrin S; Maniatis, Nikolas; Andrew, Toby

2014-01-01

Numerous functional studies have implicated PARL in relation to type 2 diabetes (T2D). We hypothesised that conflicting human association studies may be due to neighbouring causal variants being in linkage disequilibrium (LD) with PARL. We conducted a comprehensive candidate gene study of the extended LD genomic region that includes PARL and transporter ABCC5 using three data sets (two European and one African American), in relation to healthy glycaemic variation, visceral fat accumulation and T2D disease. We observed no evidence for previously reported T2D association with Val262Leu or PARL using array and fine-map genomic and expression data. By contrast, we observed strong evidence of T2D association with ABCC5 (intron 26) for European and African American samples (P = 3E−07) and with ABCC5 adipose expression in Europeans [odds ratio (OR) = 3.8, P = 2E−04]. The genomic location estimate for the ABCC5 functional variant, associated with all phenotypes and expression data (P = 1E−11), was identical for all samples (at Chr3q 185,136 kb B36), indicating that the risk variant is an expression quantitative trait locus (eQTL) with increased expression conferring risk of disease. That the association with T2D is observed in populations of disparate ancestry suggests the variant is a ubiquitous risk factor for T2D. PMID:25117150

Open reading frames associated with cancer in the dark matter of the human genome.

PubMed

Delgado, Ana Paula; Brandao, Pamela; Chapado, Maria Julia; Hamid, Sheilin; Narayanan, Ramaswamy

2014-01-01

The uncharacterized proteins (open reading frames, ORFs) in the human genome offer an opportunity to discover novel targets for cancer. A systematic analysis of the dark matter of the human proteome for druggability and biomarker discovery is crucial to mining the genome. Numerous data mining tools are available to mine these ORFs to develop a comprehensive knowledge base for future target discovery and validation. Using the Genetic Association Database, the ORFs of the human dark matter proteome were screened for evidence of association with neoplasms. The Phenome-Genome Integrator tool was used to establish phenotypic association with disease traits including cancer. Batch analysis of the tools for protein expression analysis, gene ontology and motifs and domains was used to characterize the ORFs. Sixty-two ORFs were identified for neoplasm association. The expression Quantitative Trait Loci (eQTL) analysis identified thirteen ORFs related to cancer traits. Protein expression, motifs and domain analysis and genome-wide association studies verified the relevance of these OncoORFs in diverse tumors. The OncoORFs are also associated with a wide variety of human diseases and disorders. Our results link the OncoORFs to diverse diseases and disorders. This suggests a complex landscape of the uncharacterized proteome in human diseases. These results open the dark matter of the proteome to novel cancer target research. Copyright© 2014, International Institute of Anticancer Research (Dr. John G. Delinasios), All rights reserved.

Genetic variation and gene expression across multiple tissues and developmental stages in a nonhuman primate.

PubMed

Jasinska, Anna J; Zelaya, Ivette; Service, Susan K; Peterson, Christine B; Cantor, Rita M; Choi, Oi-Wa; DeYoung, Joseph; Eskin, Eleazar; Fairbanks, Lynn A; Fears, Scott; Furterer, Allison E; Huang, Yu S; Ramensky, Vasily; Schmitt, Christopher A; Svardal, Hannes; Jorgensen, Matthew J; Kaplan, Jay R; Villar, Diego; Aken, Bronwen L; Flicek, Paul; Nag, Rishi; Wong, Emily S; Blangero, John; Dyer, Thomas D; Bogomolov, Marina; Benjamini, Yoav; Weinstock, George M; Dewar, Ken; Sabatti, Chiara; Wilson, Richard K; Jentsch, J David; Warren, Wesley; Coppola, Giovanni; Woods, Roger P; Freimer, Nelson B

2017-12-01

By analyzing multitissue gene expression and genome-wide genetic variation data in samples from a vervet monkey pedigree, we generated a transcriptome resource and produced the first catalog of expression quantitative trait loci (eQTLs) in a nonhuman primate model. This catalog contains more genome-wide significant eQTLs per sample than comparable human resources and identifies sex- and age-related expression patterns. Findings include a master regulatory locus that likely has a role in immune function and a locus regulating hippocampal long noncoding RNAs (lncRNAs), whose expression correlates with hippocampal volume. This resource will facilitate genetic investigation of quantitative traits, including brain and behavioral phenotypes relevant to neuropsychiatric disorders.

ARLTS1 and Prostate Cancer Risk - Analysis of Expression and Regulation

PubMed Central

Siltanen, Sanna; Fischer, Daniel; Rantapero, Tommi; Laitinen, Virpi; Mpindi, John Patrick; Kallioniemi, Olli; Wahlfors, Tiina; Schleutker, Johanna

2013-01-01

Prostate cancer (PCa) is a heterogeneous trait for which several susceptibility loci have been implicated by genome-wide linkage and association studies. The genomic region 13q14 is frequently deleted in tumour tissues of both sporadic and familial PCa patients and is consequently recognised as a possible locus of tumour suppressor gene(s). Deletions of this region have been found in many other cancers. Recently, we showed that homozygous carriers for the T442C variant of the ARLTS1 gene (ADP-ribosylation factor-like tumour suppressor protein 1 or ARL11, located at 13q14) are associated with an increased risk for both unselected and familial PCa. Furthermore, the variant T442C was observed in greater frequency among malignant tissue samples, PCa cell lines and xenografts, supporting its role in PCa tumourigenesis. In this study, 84 PCa cases and 15 controls were analysed for ARLTS1 expression status in blood-derived RNA. A statistically significant (p = 0.0037) decrease of ARLTS1 expression in PCa cases was detected. Regulation of ARLTS1 expression was analysed with eQTL (expression quantitative trait loci) methods. Altogether fourteen significant cis-eQTLs affecting the ARLTS1 expression level were found. In addition, epistatic interactions of ARLTS1 genomic variants with genes involved in immune system processes were predicted with the MDR program. In conclusion, this study further supports the role of ARLTS1 as a tumour suppressor gene and reveals that the expression is regulated through variants localised in regulatory regions. PMID:23940804

An integrated systems genetics screen reveals the transcriptional structure of inherited predisposition to metastatic disease

PubMed Central

Faraji, Farhoud; Hu, Ying; Wu, Gang; Goldberger, Natalie E.; Walker, Renard C.; Zhang, Jinghui; Hunter, Kent W.

2014-01-01

Metastasis is the result of stochastic genomic and epigenetic events leading to gene expression profiles that drive tumor dissemination. Here we exploit the principle that metastatic propensity is modified by the genetic background to generate prognostic gene expression signatures that illuminate regulators of metastasis. We also identify multiple microRNAs whose germline variation is causally linked to tumor progression and metastasis. We employ network analysis of global gene expression profiles in tumors derived from a panel of recombinant inbred mice to identify a network of co-expressed genes centered on Cnot2 that predicts metastasis-free survival. Modulating Cnot2 expression changes tumor cell metastatic potential in vivo, supporting a functional role for Cnot2 in metastasis. Small RNA sequencing of the same tumor set revealed a negative correlation between expression of the Mir216/217 cluster and tumor progression. Expression quantitative trait locus analysis (eQTL) identified cis-eQTLs at the Mir216/217 locus, indicating that differences in expression may be inherited. Ectopic expression of Mir216/217 in tumor cells suppressed metastasis in vivo. Finally, small RNA sequencing and mRNA expression profiling data were integrated to reveal that miR-3470a/b target a high proportion of network transcripts. In vivo analysis of Mir3470a/b demonstrated that both promote metastasis. Moreover, Mir3470b is a likely regulator of the Cnot2 network as its overexpression down-regulated expression of network hub genes and enhanced metastasis in vivo, phenocopying Cnot2 knockdown. The resulting data from this strategy identify Cnot2 as a novel regulator of metastasis and demonstrate the power of our systems-level approach in identifying modifiers of metastasis. PMID:24322557

Main and epistatic QTL analyses for Sclerotinia Head Rot resistance in sunflower.

PubMed

Zubrzycki, Jeremías Enrique; Maringolo, Carla Andrea; Filippi, Carla Valeria; Quiróz, Facundo José; Nishinakamasu, Verónica; Puebla, Andrea Fabiana; Di Rienzo, Julio A; Escande, Alberto; Lia, Verónica Viviana; Heinz, Ruth Amalia; Hopp, Horacio Esteban; Cervigni, Gerardo D L; Paniego, Norma Beatriz

2017-01-01

Sclerotinia Head Rot (SHR), a disease caused by Sclerotinia sclerotiorum, is one of the most limiting factors in sunflower production. In this study, we identified genomic loci associated with resistance to SHR to support the development of assisted breeding strategies. We genotyped 114 Recombinant Inbred Lines (RILs) along with their parental lines (PAC2 -partially resistant-and RHA266 -susceptible-) by using a 384 single nucleotide polymorphism (SNP) Illumina Oligo Pool Assay to saturate a sunflower genetic map. Subsequently, we tested these lines for SHR resistance using assisted inoculations with S. sclerotiorum ascospores. We also conducted a randomized complete-block assays with three replicates to visually score disease incidence (DI), disease severity (DS), disease intensity (DInt) and incubation period (IP) through four field trials (2010-2014). We finally assessed main effect quantitative trait loci (M-QTLs) and epistatic QTLs (E-QTLs) by composite interval mapping (CIM) and mixed-model-based composite interval mapping (MCIM), respectively. As a result of this study, the improved map incorporates 61 new SNPs over candidate genes. We detected a broad range of narrow sense heritability (h2) values (1.86-59.9%) as well as 36 M-QTLs and 13 E-QTLs along 14 linkage groups (LGs). On LG1, LG10, and LG15, we repeatedly detected QTLs across field trials; which emphasizes their putative effectiveness against SHR. In all selected variables, most of the identified QTLs showed high determination coefficients, associated with moderate to high heritability values. Using markers shared with previous Sclerotinia resistance studies, we compared the QTL locations in LG1, LG2, LG8, LG10, LG11, LG15 and LG16. This study constitutes the largest report of QTLs for SHR resistance in sunflower. Further studies focusing on the regions in LG1, LG10, and LG15 harboring the detected QTLs are necessary to identify causal alleles and contribute to unraveling the complex genetic basis governing the resistance.

Elucidation of the transcription network governing mammalian sex determination by exploiting strain-specific susceptibility to sex reversal

PubMed Central

Munger, Steven C.; Aylor, David L.; Syed, Haider Ali; Magwene, Paul M.; Threadgill, David W.; Capel, Blanche

2009-01-01

Despite the identification of some key genes that regulate sex determination, most cases of disorders of sexual development remain unexplained. Evidence suggests that the sexual fate decision in the developing gonad depends on a complex network of interacting factors that converge on a critical threshold. To elucidate the transcriptional network underlying sex determination, we took the first expression quantitative trait loci (eQTL) approach in a developing organ. We identified reproducible differences in the transcriptome of the embryonic day 11.5 (E11.5) XY gonad between C57BL/6J (B6) and 129S1/SvImJ (129S1), indicating that the reported sensitivity of B6 to sex reversal is consistent with a higher expression of a female-like transcriptome in B6. Gene expression is highly variable in F2 XY gonads from B6 and 129S1 intercrosses, yet strong correlations emerged. We estimated the F2 coexpression network and predicted roles for genes of unknown function based on their connectivity and position within the network. A genetic analysis of the F2 population detected autosomal regions that control the expression of many sex-related genes, including Sry (sex-determining region of the Y chromosome) and Sox9 (Sry-box containing gene 9), the key regulators of male sex determination. Our results reveal the complex transcription architecture underlying sex determination, and provide a mechanism by which individuals may be sensitized for sex reversal. PMID:19884258

Genetic variation and gene expression across multiple tissues and developmental stages in a non-human primate

PubMed Central

Jasinska, Anna J.; Zelaya, Ivette; Service, Susan K.; Peterson, Christine B.; Cantor, Rita M.; Choi, Oi-Wa; DeYoung, Joseph; Eskin, Eleazar; Fairbanks, Lynn A.; Fears, Scott; Furterer, Allison E.; Huang, Yu S.; Ramensky, Vasily; Schmitt, Christopher A.; Svardal, Hannes; Jorgensen, Matthew J.; Kaplan, Jay R.; Villar, Diego; Aken, Bronwen L.; Flicek, Paul; Nag, Rishi; Wong, Emily S.; Blangero, John; Dyer, Thomas D.; Bogomolov, Marina; Benjamini, Yoav; Weinstock, George M.; Dewar, Ken; Sabatti, Chiara; Wilson, Richard K.; Jentsch, J. David; Warren, Wesley; Coppola, Giovanni; Woods, Roger P.; Freimer, Nelson B.

2017-01-01

By analyzing multi-tissue gene expression and genome-wide genetic variation data in samples from a vervet monkey pedigree, we generated a transcriptome resource and produced the first catalogue of expression quantitative trait loci (eQTLs) in a non-human primate model. This catalogue contains more genome-wide significant eQTLs, per sample, than comparable human resources, and reveals sex and age-related expression patterns. Findings include a master regulatory locus that likely plays a role in immune function, and a locus regulating hippocampal long non-coding RNAs (lncRNAs), whose expression correlates with hippocampal volume. This resource will facilitate genetic investigation of quantitative traits, including brain and behavioral phenotypes relevant to neuropsychiatric disorders. PMID:29083405

The abundance of cis-acting loci leading to differential allele expression in F1 mice and their relationship to loci harboring genes affecting complex traits.

PubMed

Yeo, Seungeun; Hodgkinson, Colin A; Zhou, Zhifeng; Jung, Jeesun; Leung, Ming; Yuan, Qiaoping; Goldman, David

2016-08-11

Genome-wide surveys have detected cis-acting quantitative trait loci altering levels of RNA transcripts (RNA-eQTLs) by associating SNV alleles to transcript levels. However, the sensitivity and specificity of detection of cis- expression quantitative trait loci (eQTLs) by genetic approaches, reliant as it is on measurements of transcript levels in recombinant inbred strains or offspring from arranged crosses, is unknown, as is their relationship to QTL's for complex phenotypes. We used transcriptome-wide differential allele expression (DAE) to detect cis-eQTLs in forebrain and kidney from reciprocal crosses between three mouse inbred strains, 129S1/SvlmJ, DBA/2J, and CAST/EiJ and C57BL/6 J. Two of these crosses were previously characterized for cis-eQTLs and QTLs for various complex phenotypes by genetic analysis of recombinant inbred (RI) strains. 5.4 %, 1.9 % and 1.5 % of genes assayed in forebrain of B6/129SF1, B6/DBAF1, and B6/CASTF1 mice, respectively, showed differential allelic expression, indicative of cis-acting alleles at these genes. Moreover, the majority of DAE QTLs were observed to be tissue-specific with only a small fraction showing cis-effects in both tissues. Comparing DAE QTLs in F1 mice to cis-eQTLs previously mapped in RI strains we observed that many of the cis-eQTLs were not confirmed by DAE. Additionally several novel DAE-QTLs not identified as cis-eQTLs were identified suggesting that there are differences in sensitivity and specificity for QTL detection between the two methodologies. Strain specific DAE QTLs in B6/DBAF1 mice were located in excess at candidate genes for alcohol use disorders, seizures, and angiogenesis previously implicated by genetic linkage in C57BL/6J × DBA/2JF2 mice or BXD RI strains. Via a survey for differential allele expression in F1 mice, a substantial proportion of genes were found to have alleles altering expression in cis-acting fashion. Comparing forebrain and kidney, many or most of these alleles were tissue-specific in action. The identification of strain specific DAE QTLs, can assist in assessment of candidate genes located within the large intervals associated with trait QTLs.

Glucocorticoid Receptor Related Genes: Genotype And Brain Gene Expression Relationships To Suicide And Major Depressive Disorder

PubMed Central

Pantazatos, Spiro P.; Huang, Yung-yu; Rosoklija, Gorazd B.; Dwork, Andrew J.; Burke, Ainsley; Arango, Victoria; Oquendo, Maria A.; Mann, J. John

2016-01-01

Introduction We tested the relationship between genotype, gene expression and suicidal behavior and MDD in live subjects and postmortem samples for three genes, associated with the hypothalamic-pituitary-adrenal axis, suicidal behavior and major depressive disorder (MDD); FK506 binding protein 5 (FKBP5), Spindle and kinetochore-associated protein 2 (SKA2) and Glucocorticoid Receptor (NR3C1). Materials and Methods Single-nucleotide polymorphisms (SNPs) and haplotypes were tested for association with suicidal behavior and MDD in a live (N=277) and a postmortem sample (N=209). RNA-seq was used to examine gene and isoform-level brain expression postmortem (Brodmann Area 9) (N=59). Expression quantitative trait loci (eQTL) relationships were examined using a public database (UK Brain Expression Consortium). Results We identified a haplotype within the FKBP5 gene, present in 47% of the live subjects, that was associated with increased risk of suicide attempt (OR=1.58, t=6.03, p=0.014). Six SNPs on this gene, three SNPs on SKA2 and one near NR3C1 showed before-adjustment association with attempted suicide, and two SNPs of SKA2 with suicide death, but none stayed significant after adjustment for multiple testing. Only the SKA2 SNPs were related to expression in the prefrontal cortex. One NR3C1 transcript had lower expression in suicide relative to non-suicide sudden death cases (b=-0.48, SE=0.12, t=-4.02, adjusted p=0.004). Conclusion We have identified an association of FKBP5 haplotype with risk of suicide attempt and found an association between suicide and altered NR3C1 gene expression in the prefrontal cortex. Our findings further implicate hypothalamic pituitary axis dysfunction in suicidal behavior. PMID:27030168

GLUCOCORTICOID RECEPTOR-RELATED GENES: GENOTYPE AND BRAIN GENE EXPRESSION RELATIONSHIPS TO SUICIDE AND MAJOR DEPRESSIVE DISORDER.

PubMed

Yin, Honglei; Galfalvy, Hanga; Pantazatos, Spiro P; Huang, Yung-Yu; Rosoklija, Gorazd B; Dwork, Andrew J; Burke, Ainsley; Arango, Victoria; Oquendo, Maria A; Mann, J John

2016-06-01

We tested the relationship between genotype, gene expression and suicidal behavior and major depressive disorder (MDD) in live subjects and postmortem samples for three genes, associated with the hypothalamic-pituitary-adrenal axis, suicidal behavior, and MDD; FK506-binding protein 5 (FKBP5), Spindle and kinetochore-associated protein 2 (SKA2), and Glucocorticoid Receptor (NR3C1). Single-nucleotide polymorphisms (SNPs) and haplotypes were tested for association with suicidal behavior and MDD in a live (N = 277) and a postmortem sample (N = 209). RNA-seq was used to examine gene and isoform-level brain expression postmortem (Brodmann Area 9; N = 59). Expression quantitative trait loci (eQTL) relationships were examined using a public database (UK Brain Expression Consortium). We identified a haplotype within the FKBP5 gene, present in 47% of the live subjects, which was associated with increased risk of suicide attempt (OR = 1.58, t = 6.03, P = .014). Six SNPs on this gene, three SNPs on SKA2, and one near NR3C1 showed before-adjustment association with attempted suicide, and two SNPs of SKA2 with suicide death, but none stayed significant after adjustment for multiple testing. Only the SKA2 SNPs were related to expression in the prefrontal cortex (pFCTX). One NR3C1 transcript had lower expression in suicide relative to nonsuicide sudden death cases (b = -0.48, SE = 0.12, t = -4.02, adjusted P = .004). We have identified an association of FKBP5 haplotype with risk of suicide attempt and found an association between suicide and altered NR3C1 gene expression in the pFCTX. Our findings further implicate hypothalamic pituitary axis dysfunction in suicidal behavior. © 2016 Wiley Periodicals, Inc.

Correlation analyses revealed global microRNA-mRNA expression associations in human peripheral blood mononuclear cells.

PubMed

Wang, Lan; Zhu, Jiang; Deng, Fei-Yan; Wu, Long-Fei; Mo, Xing-Bo; Zhu, Xiao-Wei; Xia, Wei; Xie, Fang-Fei; He, Pei; Bing, Peng-Fei; Qiu, Ying-Hua; Lin, Xiang; Lu, Xin; Zhang, Lei; Yi, Neng-Jun; Zhang, Yong-Hong; Lei, Shu-Feng

2018-02-01

MicroRNAs (miRNAs) can regulate gene expression through binding to complementary sites in the 3'-untranslated regions of target mRNAs, which will lead to existence of correlation in expression between miRNA and mRNA. However, the miRNA-mRNA correlation patterns are complex and remain largely unclear yet. To establish the global correlation patterns in human peripheral blood mononuclear cells (PBMCs), multiple miRNA-mRNA correlation analyses and expression quantitative trait locus (eQTL) analysis were conducted in this study. We predicted and achieved 861 miRNA-mRNA pairs (65 miRNAs, 412 mRNAs) using multiple bioinformatics programs, and found global negative miRNA-mRNA correlations in PBMC from all 46 study subjects. Among the 861 pairs of correlations, 19.5% were significant (P < 0.05) and ~70% were negative. The correlation network was complex and highlighted key miRNAs/genes in PBMC. Some miRNAs, such as hsa-miR-29a, hsa-miR-148a, regulate a cluster of target genes. Some genes, e.g., TNRC6A, are regulated by multiple miRNAs. The identified genes tend to be enriched in molecular functions of DNA and RNA binding, and biological processes such as protein transport, regulation of translation and chromatin modification. The results provided a global view of the miRNA-mRNA expression correlation profile in human PBMCs, which would facilitate in-depth investigation of biological functions of key miRNAs/mRNAs and better understanding of the pathogenesis underlying PBMC-related diseases.

Cross-Tissue and Tissue-Specific eQTLs: Partitioning the Heritability of a Complex Trait

PubMed Central

Torres, Jason M.; Gamazon, Eric R.; Parra, Esteban J.; Below, Jennifer E.; Valladares-Salgado, Adan; Wacher, Niels; Cruz, Miguel; Hanis, Craig L.; Cox, Nancy J.

2014-01-01

Top signals from genome-wide association studies (GWASs) of type 2 diabetes (T2D) are enriched with expression quantitative trait loci (eQTLs) identified in skeletal muscle and adipose tissue. We therefore hypothesized that such eQTLs might account for a disproportionate share of the heritability estimated from all SNPs interrogated through GWASs. To test this hypothesis, we applied linear mixed models to the Wellcome Trust Case Control Consortium (WTCCC) T2D data set and to data sets representing Mexican Americans from Starr County, TX, and Mexicans from Mexico City. We estimated the proportion of phenotypic variance attributable to the additive effect of all variants interrogated in these GWASs, as well as a much smaller set of variants identified as eQTLs in human adipose tissue, skeletal muscle, and lymphoblastoid cell lines. The narrow-sense heritability explained by all interrogated SNPs in each of these data sets was substantially greater than the heritability accounted for by genome-wide-significant SNPs (∼10%); GWAS SNPs explained over 50% of phenotypic variance in the WTCCC, Starr County, and Mexico City data sets. The estimate of heritability attributable to cross-tissue eQTLs was greater in the WTCCC data set and among lean Hispanics, whereas adipose eQTLs significantly explained heritability among Hispanics with a body mass index ≥ 30. These results support an important role for regulatory variants in the genetic component of T2D susceptibility, particularly for eQTLs that elicit effects across insulin-responsive peripheral tissues. PMID:25439722

Using bioinformatics and systems genetics to dissect HDL-cholesterol genetics in an MRL/MpJ x SM/J intercross.

PubMed

Leduc, Magalie S; Blair, Rachael Hageman; Verdugo, Ricardo A; Tsaih, Shirng-Wern; Walsh, Kenneth; Churchill, Gary A; Paigen, Beverly

2012-06-01

A higher incidence of coronary artery disease is associated with a lower level of HDL-cholesterol. We searched for genetic loci influencing HDL-cholesterol in F2 mice from a cross between MRL/MpJ and SM/J mice. Quantitative trait loci (QTL) mapping revealed one significant HDL QTL (Apoa2 locus), four suggestive QTL on chromosomes 10, 11, 13, and 18 and four additional QTL on chromosomes 1 proximal, 3, 4, and 7 after adjusting HDL for the strong Apoa2 locus. A novel nonsynonymous polymorphism supports Lipg as the QTL gene for the chromosome 18 QTL, and a difference in Abca1 expression in liver tissue supports it as the QTL gene for the chromosome 4 QTL. Using weighted gene co-expression network analysis, we identified a module that after adjustment for Apoa2, correlated with HDL, was genetically determined by a QTL on chromosome 11, and overlapped with the HDL QTL. A combination of bioinformatics tools and systems genetics helped identify several candidate genes for both the chromosome 11 HDL and module QTL based on differential expression between the parental strains, cis regulation of expression, and causality modeling. We conclude that integrating systems genetics to a more-traditional genetics approach improves the power of complex trait gene identification.

Metabolomic Quantitative Trait Loci (mQTL) Mapping Implicates the Ubiquitin Proteasome System in Cardiovascular Disease Pathogenesis.

PubMed

Kraus, William E; Muoio, Deborah M; Stevens, Robert; Craig, Damian; Bain, James R; Grass, Elizabeth; Haynes, Carol; Kwee, Lydia; Qin, Xuejun; Slentz, Dorothy H; Krupp, Deidre; Muehlbauer, Michael; Hauser, Elizabeth R; Gregory, Simon G; Newgard, Christopher B; Shah, Svati H

2015-11-01

Levels of certain circulating short-chain dicarboxylacylcarnitine (SCDA), long-chain dicarboxylacylcarnitine (LCDA) and medium chain acylcarnitine (MCA) metabolites are heritable and predict cardiovascular disease (CVD) events. Little is known about the biological pathways that influence levels of most of these metabolites. Here, we analyzed genetics, epigenetics, and transcriptomics with metabolomics in samples from a large CVD cohort to identify novel genetic markers for CVD and to better understand the role of metabolites in CVD pathogenesis. Using genomewide association in the CATHGEN cohort (N = 1490), we observed associations of several metabolites with genetic loci. Our strongest findings were for SCDA metabolite levels with variants in genes that regulate components of endoplasmic reticulum (ER) stress (USP3, HERC1, STIM1, SEL1L, FBXO25, SUGT1) These findings were validated in a second cohort of CATHGEN subjects (N = 2022, combined p = 8.4x10-6-2.3x10-10). Importantly, variants in these genes independently predicted CVD events. Association of genomewide methylation profiles with SCDA metabolites identified two ER stress genes as differentially methylated (BRSK2 and HOOK2). Expression quantitative trait loci (eQTL) pathway analyses driven by gene variants and SCDA metabolites corroborated perturbations in ER stress and highlighted the ubiquitin proteasome system (UPS) arm. Moreover, culture of human kidney cells in the presence of levels of fatty acids found in individuals with cardiometabolic disease, induced accumulation of SCDA metabolites in parallel with increases in the ER stress marker BiP. Thus, our integrative strategy implicates the UPS arm of the ER stress pathway in CVD pathogenesis, and identifies novel genetic loci associated with CVD event risk.

Metabolomic Quantitative Trait Loci (mQTL) Mapping Implicates the Ubiquitin Proteasome System in Cardiovascular Disease Pathogenesis

PubMed Central

Kraus, William E.; Muoio, Deborah M.; Stevens, Robert; Craig, Damian; Bain, James R.; Grass, Elizabeth; Haynes, Carol; Kwee, Lydia; Qin, Xuejun; Slentz, Dorothy H.; Krupp, Deidre; Muehlbauer, Michael; Hauser, Elizabeth R.; Gregory, Simon G.; Newgard, Christopher B.; Shah, Svati H.

2015-01-01

Levels of certain circulating short-chain dicarboxylacylcarnitine (SCDA), long-chain dicarboxylacylcarnitine (LCDA) and medium chain acylcarnitine (MCA) metabolites are heritable and predict cardiovascular disease (CVD) events. Little is known about the biological pathways that influence levels of most of these metabolites. Here, we analyzed genetics, epigenetics, and transcriptomics with metabolomics in samples from a large CVD cohort to identify novel genetic markers for CVD and to better understand the role of metabolites in CVD pathogenesis. Using genomewide association in the CATHGEN cohort (N = 1490), we observed associations of several metabolites with genetic loci. Our strongest findings were for SCDA metabolite levels with variants in genes that regulate components of endoplasmic reticulum (ER) stress (USP3, HERC1, STIM1, SEL1L, FBXO25, SUGT1) These findings were validated in a second cohort of CATHGEN subjects (N = 2022, combined p = 8.4x10-6–2.3x10-10). Importantly, variants in these genes independently predicted CVD events. Association of genomewide methylation profiles with SCDA metabolites identified two ER stress genes as differentially methylated (BRSK2 and HOOK2). Expression quantitative trait loci (eQTL) pathway analyses driven by gene variants and SCDA metabolites corroborated perturbations in ER stress and highlighted the ubiquitin proteasome system (UPS) arm. Moreover, culture of human kidney cells in the presence of levels of fatty acids found in individuals with cardiometabolic disease, induced accumulation of SCDA metabolites in parallel with increases in the ER stress marker BiP. Thus, our integrative strategy implicates the UPS arm of the ER stress pathway in CVD pathogenesis, and identifies novel genetic loci associated with CVD event risk. PMID:26540294

Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations.

PubMed

Fehringer, Gordon; Kraft, Peter; Pharoah, Paul D; Eeles, Rosalind A; Chatterjee, Nilanjan; Schumacher, Fredrick R; Schildkraut, Joellen M; Lindström, Sara; Brennan, Paul; Bickeböller, Heike; Houlston, Richard S; Landi, Maria Teresa; Caporaso, Neil; Risch, Angela; Amin Al Olama, Ali; Berndt, Sonja I; Giovannucci, Edward L; Grönberg, Henrik; Kote-Jarai, Zsofia; Ma, Jing; Muir, Kenneth; Stampfer, Meir J; Stevens, Victoria L; Wiklund, Fredrik; Willett, Walter C; Goode, Ellen L; Permuth, Jennifer B; Risch, Harvey A; Reid, Brett M; Bezieau, Stephane; Brenner, Hermann; Chan, Andrew T; Chang-Claude, Jenny; Hudson, Thomas J; Kocarnik, Jonathan K; Newcomb, Polly A; Schoen, Robert E; Slattery, Martha L; White, Emily; Adank, Muriel A; Ahsan, Habibul; Aittomäki, Kristiina; Baglietto, Laura; Blomquist, Carl; Canzian, Federico; Czene, Kamila; Dos-Santos-Silva, Isabel; Eliassen, A Heather; Figueroa, Jonine D; Flesch-Janys, Dieter; Fletcher, Olivia; Garcia-Closas, Montserrat; Gaudet, Mia M; Johnson, Nichola; Hall, Per; Hazra, Aditi; Hein, Rebecca; Hofman, Albert; Hopper, John L; Irwanto, Astrid; Johansson, Mattias; Kaaks, Rudolf; Kibriya, Muhammad G; Lichtner, Peter; Liu, Jianjun; Lund, Eiliv; Makalic, Enes; Meindl, Alfons; Müller-Myhsok, Bertram; Muranen, Taru A; Nevanlinna, Heli; Peeters, Petra H; Peto, Julian; Prentice, Ross L; Rahman, Nazneen; Sanchez, Maria Jose; Schmidt, Daniel F; Schmutzler, Rita K; Southey, Melissa C; Tamimi, Rulla; Travis, Ruth C; Turnbull, Clare; Uitterlinden, Andre G; Wang, Zhaoming; Whittemore, Alice S; Yang, Xiaohong R; Zheng, Wei; Buchanan, Daniel D; Casey, Graham; Conti, David V; Edlund, Christopher K; Gallinger, Steven; Haile, Robert W; Jenkins, Mark; Le Marchand, Loïc; Li, Li; Lindor, Noralene M; Schmit, Stephanie L; Thibodeau, Stephen N; Woods, Michael O; Rafnar, Thorunn; Gudmundsson, Julius; Stacey, Simon N; Stefansson, Kari; Sulem, Patrick; Chen, Y Ann; Tyrer, Jonathan P; Christiani, David C; Wei, Yongyue; Shen, Hongbing; Hu, Zhibin; Shu, Xiao-Ou; Shiraishi, Kouya; Takahashi, Atsushi; Bossé, Yohan; Obeidat, Ma'en; Nickle, David; Timens, Wim; Freedman, Matthew L; Li, Qiyuan; Seminara, Daniela; Chanock, Stephen J; Gong, Jian; Peters, Ulrike; Gruber, Stephen B; Amos, Christopher I; Sellers, Thomas A; Easton, Douglas F; Hunter, David J; Haiman, Christopher A; Henderson, Brian E; Hung, Rayjean J

2016-09-01

Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer, and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression. Cancer Res; 76(17); 5103-14. ©2016 AACR. ©2016 American Association for Cancer Research.

BRISK--research-oriented storage kit for biology-related data.

PubMed

Tan, Alan; Tripp, Ben; Daley, Denise

2011-09-01

In genetic science, large-scale international research collaborations represent a growing trend. These collaborations have demanding and challenging database, storage, retrieval and communication needs. These studies typically involve demographic and clinical data, in addition to the results from numerous genomic studies (omics studies) such as gene expression, eQTL, genome-wide association and methylation studies, which present numerous challenges, thus the need for data integration platforms that can handle these complex data structures. Inefficient methods of data transfer and access control still plague research collaboration. As science becomes more and more collaborative in nature, the need for a system that adequately manages data sharing becomes paramount. Biology-Related Information Storage Kit (BRISK) is a package of several web-based data management tools that provide a cohesive data integration and management platform. It was specifically designed to provide the architecture necessary to promote collaboration and expedite data sharing between scientists. The software, documentation, Java source code and demo are available at http://genapha.icapture.ubc.ca/brisk/index.jsp. BRISK was developed in Java, and tested on an Apache Tomcat 6 server with a MySQL database. denise.daley@hli.ubc.ca.

Integrated analysis of genetic variation and gene expression reveals novel variant for increased warfarin dose requirement in African Americans.

PubMed

Hernandez, W; Gamazon, E R; Aquino-Michaels, K; Smithberger, E; O'Brien, T J; Harralson, A F; Tuck, M; Barbour, A; Cavallari, L H; Perera, M A

2017-04-01

Essentials Genetic variants controlling gene regulation have not been explored in pharmacogenomics. We tested liver expression quantitative trait loci for association with warfarin dose response. A novel predictor for increased warfarin dose response in African Americans was identified. Precision medicine must take into account population-specific variation in gene regulation. Background Warfarin is commonly used to control and prevent thromboembolic disorders. However, because of warfarin's complex dose-requirement relationship, safe and effective use is challenging. Pharmacogenomics-guided warfarin dosing algorithms that include the well-established VKORC1 and CYP2C9 polymorphisms explain only a small proportion of inter-individual variability in African Americans (AAs). Objectives We aimed to assess whether transcriptomic analyses could be used to identify regulatory variants associated with warfarin dose response in AAs. Patients/Methods We identified a total of 56 expression quantitative trait loci (eQTLs) for CYP2C9, VKORC1 and CALU derived from human livers and evaluated their association with warfarin dose response in two independent AA warfarin patient cohorts. Results We found that rs4889606, a strong cis-eQTL for VKORC1 (log 10 Bayes Factor = 12.02), is significantly associated with increased warfarin daily dose requirement (β = 1.1; 95% confidence interval [CI] 0.46 to 1.8) in the discovery cohort (n = 305) and in the replication cohort (β = 1.04; 95% CI 0.33 -1.7; n = 141) after conditioning on relevant covariates and the VKORC1 -1639G>A (rs9923231) variant. Inclusion of rs4889606 genotypes, along with CYP2C9 alleles, rs9923231 genotypes and clinical variables, explained 31% of the inter-patient variability in warfarin dose requirement. We demonstrate different linkage disequilibrium patterns in the region encompassing rs4889606 and rs9923231 between AAs and European Americans, which may explain the increased dose requirement found in AAs. Conclusion Our approach of interrogating eQTLs identified in liver has revealed a novel predictor of warfarin dose response in AAs. Our work highlights the utility of leveraging information from regulatory variants mapped in the liver to uncover novel variants associated with drug response and the importance of population-specific research. © 2017 International Society on Thrombosis and Haemostasis.

Novel Genetic Loci Control Calcium Absorption and Femur Bone Mass as well as Their Response to Low Calcium Intake in Male BXD Recombinant Inbred Mice†

PubMed Central

Reyes Fernandez, Perla C.; Replogle, Rebecca A.; Wang, Libo; Zhang, Min; Fleet, James C.

2016-01-01

Low dietary calcium (Ca) intake during growth limits peak bone mass but physiological adaptation can prevent this adverse effect. To assess the genetic control on the physiologic response to dietary Ca restriction (RCR) we conducted a study in 51 BXD lines fed either 0.5% (basal) or 0.25% (low) Ca diets from 4–12 wks of age (n=8/line/diet). Ca absorption (CaAbs), femur bone mineral density (BMD), and bone mineral content (BMC) were examined. ANCOVA with body size as covariate was used to detect significant line and diet main effects, and line-by-diet interactions. Body size-corrected residuals were used for linkage mapping and to estimate heritability (h2). Loci controlling the phenotypes were identified using composite interval mapping on each diet and for the RCR. h2 of basal phenotypes (0.37– 0.43) and their RCR (0.32–0.38) was moderate. For each phenotype we identified multiple QTL on each diet and for the RCR. Several loci affected multiple traits: Chr 1 (88.3–90.6 cM, CaAbs, BMC), Chr 4 (45.8–49.2 cM, CaAbs, BMD, BMC), Chr 8 (28.6–31.6 cM, CaAbs, BMD RCR), and Chr 15 (13.6–24 cM, BMD, BMC), and (32.3–36 cM, CaAbs RCR, BMD). This suggests that gene clusters may regulate interdependent bone-related phenotypes. Using in silico expression QTL (eQTL) mapping and bioinformatic tools we identified novel candidates for the regulation of bone under Ca stress (Ext1, Deptor), and for the first time, we report genes modulating Ca absorption (Inadl, Sc4mol, Sh3rf1 and Dennd3), and both Ca and bone metabolism (Tceanc2, Tll1 and Aadat). Our data reveal gene-by-diet interactions and the existence of novel relationships between bone and Ca metabolism during growth. This article is protected by copyright. All rights reserved PMID:26636428

Using bioinformatics and systems genetics to dissect HDL-cholesterol genetics in an MRL/MpJ × SM/J intercross[S

PubMed Central

Leduc, Magalie S.; Blair, Rachael Hageman; Verdugo, Ricardo A.; Tsaih, Shirng-Wern; Walsh, Kenneth; Churchill, Gary A.; Paigen, Beverly

2012-01-01

A higher incidence of coronary artery disease is associated with a lower level of HDL-cholesterol. We searched for genetic loci influencing HDL-cholesterol in F2 mice from a cross between MRL/MpJ and SM/J mice. Quantitative trait loci (QTL) mapping revealed one significant HDL QTL (Apoa2 locus), four suggestive QTL on chromosomes 10, 11, 13, and 18 and four additional QTL on chromosomes 1 proximal, 3, 4, and 7 after adjusting HDL for the strong Apoa2 locus. A novel nonsynonymous polymorphism supports Lipg as the QTL gene for the chromosome 18 QTL, and a difference in Abca1 expression in liver tissue supports it as the QTL gene for the chromosome 4 QTL. Using weighted gene co-expression network analysis, we identified a module that after adjustment for Apoa2, correlated with HDL, was genetically determined by a QTL on chromosome 11, and overlapped with the HDL QTL. A combination of bioinformatics tools and systems genetics helped identify several candidate genes for both the chromosome 11 HDL and module QTL based on differential expression between the parental strains, cis regulation of expression, and causality modeling. We conclude that integrating systems genetics to a more-traditional genetics approach improves the power of complex trait gene identification. PMID:22498810

HaploReg v4: systematic mining of putative causal variants, cell types, regulators and target genes for human complex traits and disease.

PubMed

Ward, Lucas D; Kellis, Manolis

2016-01-04

More than 90% of common variants associated with complex traits do not affect proteins directly, but instead the circuits that control gene expression. This has increased the urgency of understanding the regulatory genome as a key component for translating genetic results into mechanistic insights and ultimately therapeutics. To address this challenge, we developed HaploReg (http://compbio.mit.edu/HaploReg) to aid the functional dissection of genome-wide association study (GWAS) results, the prediction of putative causal variants in haplotype blocks, the prediction of likely cell types of action, and the prediction of candidate target genes by systematic mining of comparative, epigenomic and regulatory annotations. Since first launching the website in 2011, we have greatly expanded HaploReg, increasing the number of chromatin state maps to 127 reference epigenomes from ENCODE 2012 and Roadmap Epigenomics, incorporating regulator binding data, expanding regulatory motif disruption annotations, and integrating expression quantitative trait locus (eQTL) variants and their tissue-specific target genes from GTEx, Geuvadis, and other recent studies. We present these updates as HaploReg v4, and illustrate a use case of HaploReg for attention deficit hyperactivity disorder (ADHD)-associated SNPs with putative brain regulatory mechanisms. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Interactome-transcriptome analysis discovers signatures complementary to GWAS Loci of Type 2 Diabetes

PubMed Central

Li, Jing-Woei; Lee, Heung-Man; Wang, Ying; Tong, Amy Hin-Yan; Yip, Kevin Y.; Tsui, Stephen Kwok-Wing; Lok, Si; Ozaki, Risa; Luk, Andrea O; Kong, Alice P. S.; So, Wing-Yee; Ma, Ronald C. W.; Chan, Juliana C. N.; Chan, Ting-Fung

2016-01-01

Protein interactions play significant roles in complex diseases. We analyzed peripheral blood mononuclear cells (PBMC) transcriptome using a multi-method strategy. We constructed a tissue-specific interactome (T2Di) and identified 420 molecular signatures associated with T2D-related comorbidity and symptoms, mainly implicated in inflammation, adipogenesis, protein phosphorylation and hormonal secretion. Apart from explaining the residual associations within the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) study, the T2Di signatures were enriched in pathogenic cell type-specific regulatory elements related to fetal development, immunity and expression quantitative trait loci (eQTL). The T2Di revealed a novel locus near a well-established GWAS loci AChE, in which SRRT interacts with JAZF1, a T2D-GWAS gene implicated in pancreatic function. The T2Di also included known anti-diabetic drug targets (e.g. PPARD, MAOB) and identified possible druggable targets (e.g. NCOR2, PDGFR). These T2Di signatures were validated by an independent computational method, and by expression data of pancreatic islet, muscle and liver with some of the signatures (CEBPB, SREBF1, MLST8, SRF, SRRT and SLC12A9) confirmed in PBMC from an independent cohort of 66 T2D and 66 control subjects. By combining prior knowledge and transcriptome analysis, we have constructed an interactome to explain the multi-layered regulatory pathways in T2D. PMID:27752041

The schizophrenia risk gene ZNF804A: clinical associations, biological mechanisms and neuronal functions.

PubMed

Chang, H; Xiao, X; Li, M

2017-07-01

ZNF804A (zinc-finger protein 804A) has been recognized as a schizophrenia risk gene across multiple world populations. Its intronic single-nucleotide polymorphism (SNP) rs1344706 is among one of the strongest susceptibility variants that have achieved genome-wide significance in genome-wide association studies (GWAS) for schizophrenia and has been widely and intensively studied. To elucidate the biological mechanisms underlying the genetic risk conferred by rs1344706, we retrospectively analyzed the progresses in brain gene expression quantitative trait loci (eQTL) analyses, ZNF804A-induced pathway alterations in neural cells and changes in synaptic phenotypes associated with ZNF804A expression. Based on these data, we hypothesize a potential biological mechanism for a genetic risk allele of ZNF804A in schizophrenia pathogenesis. We also review the efforts being made to characterize the affected intermediate phenotypes using neuroimaging and neuropsychological approaches. We then discuss additional common and rare ZNF804A variants in schizophrenia susceptibility and the potential genetic heterogeneity of these genomic loci between Europeans and Asians. This review for we believe the first time systematically presents the evidence for ZNF804A, describing its discovery and likely roles in brain development and schizophrenia pathogenesis. We believe that this work has summarized this information with a systemic and broad assessment of recent findings.

Identifying cis-mediators for trans-eQTLs across many human tissues using genomic mediation analysis

PubMed Central

Yang, Fan; Wang, Jiebiao; Pierce, Brandon L.; Chen, Lin S.

2017-01-01

The impact of inherited genetic variation on gene expression in humans is well-established. The majority of known expression quantitative trait loci (eQTLs) impact expression of local genes (cis-eQTLs). More research is needed to identify effects of genetic variation on distant genes (trans-eQTLs) and understand their biological mechanisms. One common trans-eQTLs mechanism is “mediation” by a local (cis) transcript. Thus, mediation analysis can be applied to genome-wide SNP and expression data in order to identify transcripts that are “cis-mediators” of trans-eQTLs, including those “cis-hubs” involved in regulation of many trans-genes. Identifying such mediators helps us understand regulatory networks and suggests biological mechanisms underlying trans-eQTLs, both of which are relevant for understanding susceptibility to complex diseases. The multitissue expression data from the Genotype-Tissue Expression (GTEx) program provides a unique opportunity to study cis-mediation across human tissue types. However, the presence of complex hidden confounding effects in biological systems can make mediation analyses challenging and prone to confounding bias, particularly when conducted among diverse samples. To address this problem, we propose a new method: Genomic Mediation analysis with Adaptive Confounding adjustment (GMAC). It enables the search of a very large pool of variables, and adaptively selects potential confounding variables for each mediation test. Analyses of simulated data and GTEx data demonstrate that the adaptive selection of confounders by GMAC improves the power and precision of mediation analysis. Application of GMAC to GTEx data provides new insights into the observed patterns of cis-hubs and trans-eQTL regulation across tissue types. PMID:29021290

Cis-Regulatory Variants Affect CHRNA5 mRNA Expression in Populations of African and European Ancestry

PubMed Central

Wang, Jen-Chyong; Spiegel, Noah; Bertelsen, Sarah; Le, Nhung; McKenna, Nicholas; Budde, John P.; Harari, Oscar; Kapoor, Manav; Brooks, Andrew; Hancock, Dana; Tischfield, Jay; Foroud, Tatiana; Bierut, Laura J.; Steinbach, Joe Henry; Edenberg, Howard J.; Traynor, Bryan J.; Goate, Alison M.

2013-01-01

Variants within the gene cluster encoding α3, α5, and β4 nicotinic receptor subunits are major risk factors for substance dependence. The strongest impact on risk is associated with variation in the CHRNA5 gene, where at least two mechanisms are at work: amino acid variation and altered mRNA expression levels. The risk allele of the non-synonymous variant (rs16969968; D398N) primarily occurs on the haplotype containing the low mRNA expression allele. In populations of European ancestry, there are approximately 50 highly correlated variants in the CHRNA5-CHRNA3-CHRNB4 gene cluster and the adjacent PSMA4 gene region that are associated with CHRNA5 mRNA levels. It is not clear which of these variants contribute to the changes in CHRNA5 transcript level. Because populations of African ancestry have reduced linkage disequilibrium among variants spanning this gene cluster, eQTL mapping in subjects of African ancestry could potentially aid in defining the functional variants that affect CHRNA5 mRNA levels. We performed quantitative allele specific gene expression using frontal cortices derived from 49 subjects of African ancestry and 111 subjects of European ancestry. This method measures allele-specific transcript levels in the same individual, which eliminates other biological variation that occurs when comparing expression levels between different samples. This analysis confirmed that substance dependence associated variants have a direct cis-regulatory effect on CHRNA5 transcript levels in human frontal cortices of African and European ancestry and identified 10 highly correlated variants, located in a 9 kb region, that are potential functional variants modifying CHRNA5 mRNA expression levels. PMID:24303001

A Celiac Diasease Associated lncRNA Named HCG14 Regulates NOD1 Expression in Intestinal Cells.

PubMed

Santin, Izortze; Jauregi-Miguel, Amaia; Velayos, Teresa; Castellanos-Rubio, Ainara; Garcia-Etxebarria, Koldo; Romero-Garmendia, Irati; Fernandez-Jimenez, Nora; Irastorza, Iñaki; Castaño, Luis; Bilbao, Jose Ramón

2018-03-29

To identify additional celiac disease associated loci in the Major Histocompatibility Complex independent from classical HLA risk alleles (HLA-DR3-DQ2) and to characterize their potential functional impact in celiac disease pathogenesis at the intestinal level. We performed a high resolution SNP genotyping of the MHC region, comparing HLA-DR3 homozygous celiac patients and non-celiac controls carrying a single copy of the B8-DR3-DQ2 conserved extended haplotype. Expression level of potential novel risk genes was determined by RT-PCR in intestinal biopsies and in intestinal and immune cells isolated from control and celiac individuals. Small interfering RNA-driven silencing of selected genes was performed in the intestinal cell line T84. MHC genotyping revealed two associated SNPs, one located in TRIM27 gene and another in the non-coding gene HCG14. After stratification analysis, only HCG14 showed significant association independent from HLA-DR-DQ loci Expression of HCG14 was slightly downregulated in epithelial cells isolated from duodenal biopsies of celiac patients, and eQTL analysis revealed that polymorphisms in HCG14 region were associated with decreased NOD1 expression in duodenal intestinal cells. We have sucessfully employed a conserved extended haplotype-matching strategy and identified a novel additional celiac disease risk variant in the lncRNA HGC14. This lncRNA seems to regulate the expression of NOD1 in an allele-specific manner. Further functional studies are needed to clarify the role of HCG14 in the regulation of gene expression and to determine the molecular mechanisms by which the risk variant in HCG14 contributes to celiac disease pathogenesis.

Systematic Integration of Brain eQTL and GWAS Identifies ZNF323 as a Novel Schizophrenia Risk Gene and Suggests Recent Positive Selection Based on Compensatory Advantage on Pulmonary Function

PubMed Central

Luo, Xiong-Jian; Mattheisen, Manuel; Li, Ming; Huang, Liang; Rietschel, Marcella; Børglum, Anders D.; Als, Thomas D.; van den Oord, Edwin J.; Aberg, Karolina A.; Mors, Ole; Mortensen, Preben Bo; Luo, Zhenwu; Degenhardt, Franziska; Cichon, Sven; Schulze, Thomas G.; Nöthen, Markus M.; Su, Bing; Zhao, Zhongming; Gan, Lin; Yao, Yong-Gang

2015-01-01

Genome-wide association studies have identified multiple risk variants and loci that show robust association with schizophrenia. Nevertheless, it remains unclear how these variants confer risk to schizophrenia. In addition, the driving force that maintains the schizophrenia risk variants in human gene pool is poorly understood. To investigate whether expression-associated genetic variants contribute to schizophrenia susceptibility, we systematically integrated brain expression quantitative trait loci and genome-wide association data of schizophrenia using Sherlock, a Bayesian statistical framework. Our analyses identified ZNF323 as a schizophrenia risk gene (P = 2.22×10–6). Subsequent analyses confirmed the association of the ZNF323 and its expression-associated single nucleotide polymorphism rs1150711 in independent samples (gene-expression: P = 1.40×10–6; single-marker meta-analysis in the combined discovery and replication sample comprising 44123 individuals: P = 6.85×10−10). We found that the ZNF323 was significantly downregulated in hippocampus and frontal cortex of schizophrenia patients (P = .0038 and P = .0233, respectively). Evidence for pleiotropic effects was detected (association of rs1150711 with lung function and gene expression of ZNF323 in lung: P = 6.62×10–5 and P = 9.00×10–5, respectively) with the risk allele (T allele) for schizophrenia acting as protective allele for lung function. Subsequent population genetics analyses suggest that the risk allele (T) of rs1150711 might have undergone recent positive selection in human population. Our findings suggest that the ZNF323 is a schizophrenia susceptibility gene whose expression may influence schizophrenia risk. Our study also illustrates a possible mechanism for maintaining schizophrenia risk variants in the human gene pool. PMID:25759474

Intronic SNP in ESR1 encoding human estrogen receptor alpha is associated with brain ESR1 mRNA isoform expression and behavioral traits.

PubMed

Pinsonneault, Julia K; Frater, John T; Kompa, Benjamin; Mascarenhas, Roshan; Wang, Danxin; Sadee, Wolfgang

2017-01-01

Genetic variants of ESR1 have been implicated in multiple diseases, including behavioral disorders, but causative variants remain uncertain. We have searched for regulatory variants affecting ESR1 expression in human brain, measuring allelic ESR1 mRNA expression in human brain tissues with marker SNPs in exon4 representing ESR1-008 (or ESRα-36), and in the 3'UTR of ESR1-203, two main ESR1 isoforms in brain. In prefrontal cortex from subjects with bipolar disorder, schizophrenia, and controls (n = 35 each; Stanley Foundation brain bank), allelic ESR1 mRNA ratios deviated from unity up to tenfold at the exon4 marker SNP, with large allelic ratios observed primarily in bipolar and schizophrenic subjects. SNP scanning and targeted sequencing identified rs2144025, associated with large allelic mRNA ratios (p = 1.6E10-6). Moreover, rs2144025 was significantly associated with ESR1 mRNA levels in the Brain eQTL Almanac and in brain regions in the Genotype-Tissue Expression project. In four GWAS cohorts, rs2104425 was significantly associated with behavioral traits, including: hypomanic episodes in female bipolar disorder subjects (GAIN bipolar disorder study; p = 0.0004), comorbid psychological symptoms in both males and females with attention deficit hyperactivity disorder (GAIN ADHD, p = 0.00002), psychological diagnoses in female children (eMERGE study of childhood health, subject age ≥9, p = 0.0009), and traits in schizophrenia (e.g., grandiose delusions, GAIN schizophrenia, p = 0.0004). The first common ESR1 variant (MAF 12-33% across races) linked to regulatory functions, rs2144025 appears conditionally to affect ESR1 mRNA expression in the brain and modulate traits in behavioral disorders.

Intronic SNP in ESR1 encoding human estrogen receptor alpha is associated with brain ESR1 mRNA isoform expression and behavioral traits

PubMed Central

Kompa, Benjamin; Mascarenhas, Roshan; Wang, Danxin; Sadee, Wolfgang

2017-01-01

Genetic variants of ESR1 have been implicated in multiple diseases, including behavioral disorders, but causative variants remain uncertain. We have searched for regulatory variants affecting ESR1 expression in human brain, measuring allelic ESR1 mRNA expression in human brain tissues with marker SNPs in exon4 representing ESR1-008 (or ESRα-36), and in the 3’UTR of ESR1-203, two main ESR1 isoforms in brain. In prefrontal cortex from subjects with bipolar disorder, schizophrenia, and controls (n = 35 each; Stanley Foundation brain bank), allelic ESR1 mRNA ratios deviated from unity up to tenfold at the exon4 marker SNP, with large allelic ratios observed primarily in bipolar and schizophrenic subjects. SNP scanning and targeted sequencing identified rs2144025, associated with large allelic mRNA ratios (p = 1.6E10-6). Moreover, rs2144025 was significantly associated with ESR1 mRNA levels in the Brain eQTL Almanac and in brain regions in the Genotype-Tissue Expression project. In four GWAS cohorts, rs2104425 was significantly associated with behavioral traits, including: hypomanic episodes in female bipolar disorder subjects (GAIN bipolar disorder study; p = 0.0004), comorbid psychological symptoms in both males and females with attention deficit hyperactivity disorder (GAIN ADHD, p = 0.00002), psychological diagnoses in female children (eMERGE study of childhood health, subject age ≥9, p = 0.0009), and traits in schizophrenia (e.g., grandiose delusions, GAIN schizophrenia, p = 0.0004). The first common ESR1 variant (MAF 12–33% across races) linked to regulatory functions, rs2144025 appears conditionally to affect ESR1 mRNA expression in the brain and modulate traits in behavioral disorders. PMID:28617822

Uncovering the genetic architecture of Colletotrichum lindemuthianum resistance through QTL mapping and epistatic interaction analysis in common bean

PubMed Central

González, Ana M.; Yuste-Lisbona, Fernando J.; Rodiño, A. Paula; De Ron, Antonio M.; Capel, Carmen; García-Alcázar, Manuel; Lozano, Rafael; Santalla, Marta

2015-01-01

Colletotrichum lindemuthianum is a hemibiotrophic fungal pathogen that causes anthracnose disease in common bean. Despite the genetics of anthracnose resistance has been studied for a long time, few quantitative trait loci (QTLs) studies have been conducted on this species. The present work examines the genetic basis of quantitative resistance to races 23 and 1545 of C. lindemuthianum in different organs (stem, leaf and petiole). A population of 185 recombinant inbred lines (RIL) derived from the cross PMB0225 × PHA1037 was evaluated for anthracnose resistance under natural and artificial photoperiod growth conditions. Using multi-environment QTL mapping approach, 10 and 16 main effect QTLs were identified for resistance to anthracnose races 23 and 1545, respectively. The homologous genomic regions corresponding to 17 of the 26 main effect QTLs detected were positive for the presence of resistance-associated gene cluster encoding nucleotide-binding and leucine-rich repeat (NL) proteins. Among them, it is worth noting that the main effect QTLs detected on linkage group 05 for resistance to race 1545 in stem, petiole and leaf were located within a 1.2 Mb region. The NL gene Phvul.005G117900 is located in this region, which can be considered an important candidate gene for the non-organ-specific QTL identified here. Furthermore, a total of 39 epistatic QTL (E-QTLs) (21 for resistance to race 23 and 18 for resistance to race 1545) involved in 20 epistatic interactions (eleven and nine interactions for resistance to races 23 and 1545, respectively) were identified. None of the main and epistatic QTLs detected displayed significant environment interaction effects. The present research provides essential information not only for the better understanding of the plant-pathogen interaction but also for the application of genomic assisted breeding for anthracnose resistance improvement in common bean through application of marker-assisted selection (MAS). PMID:25852706

Subtle Changes in Motif Positioning Cause Tissue-Specific Effects on Robustness of an Enhancer's Activity

PubMed Central

Erceg, Jelena; Saunders, Timothy E.; Girardot, Charles; Devos, Damien P.; Hufnagel, Lars; Furlong, Eileen E. M.

2014-01-01

Deciphering the specific contribution of individual motifs within cis-regulatory modules (CRMs) is crucial to understanding how gene expression is regulated and how this process is affected by sequence variation. But despite vast improvements in the ability to identify where transcription factors (TFs) bind throughout the genome, we are limited in our ability to relate information on motif occupancy to function from sequence alone. Here, we engineered 63 synthetic CRMs to systematically assess the relationship between variation in the content and spacing of motifs within CRMs to CRM activity during development using Drosophila transgenic embryos. In over half the cases, very simple elements containing only one or two types of TF binding motifs were capable of driving specific spatio-temporal patterns during development. Different motif organizations provide different degrees of robustness to enhancer activity, ranging from binary on-off responses to more subtle effects including embryo-to-embryo and within-embryo variation. By quantifying the effects of subtle changes in motif organization, we were able to model biophysical rules that explain CRM behavior and may contribute to the spatial positioning of CRM activity in vivo. For the same enhancer, the effects of small differences in motif positions varied in developmentally related tissues, suggesting that gene expression may be more susceptible to sequence variation in one tissue compared to another. This result has important implications for human eQTL studies in which many associated mutations are found in cis-regulatory regions, though the mechanism for how they affect tissue-specific gene expression is often not understood. PMID:24391522

A plausibly causal functional lupus-associated risk variant in the STAT1-STAT4 locus.

PubMed

Patel, Zubin; Lu, Xiaoming; Miller, Daniel; Forney, Carmy R; Lee, Joshua; Lynch, Arthur; Schroeder, Connor; Parks, Lois; Magnusen, Albert F; Chen, Xiaoting; Pujato, Mario; Maddox, Avery; Zoller, Erin E; Namjou, Bahram; Brunner, Hermine I; Henrickson, Michael; Huggins, Jennifer L; Williams, Adrienne H; Ziegler, Julie T; Comeau, Mary E; Marion, Miranda C; Glenn, Stuart B; Adler, Adam; Shen, Nan; Nath, Swapan K; Stevens, Anne M; Freedman, Barry I; Pons-Estel, Bernardo A; Tsao, Betty P; Jacob, Chaim O; Kamen, Diane L; Brown, Elizabeth E; Gilkeson, Gary S; Alarcón, Graciela S; Martin, Javier; Reveille, John D; Anaya, Juan-Manuel; James, Judith A; Sivils, Kathy L; Criswell, Lindsey A; Vilá, Luis M; Petri, Michelle; Scofield, R Hal; Kimberly, Robert P; Edberg, Jeffrey C; Ramsey-Goldman, Rosalind; Bang, So-Young; Lee, Hye-Soon; Bae, Sang-Cheol; Boackle, Susan A; Cunninghame Graham, Deborah; Vyse, Timothy J; Merrill, Joan T; Niewold, Timothy B; Ainsworth, Hannah C; Silverman, Earl D; Weisman, Michael H; Wallace, Daniel J; Raj, Prithvi; Guthridge, Joel M; Gaffney, Patrick M; Kelly, Jennifer A; Alarcón-Riquelme, Marta E; Langefeld, Carl D; Wakeland, Edward K; Kaufman, Kenneth M; Weirauch, Matthew T; Harley, John B; Kottyan, Leah C

2018-04-18

Systemic Lupus Erythematosus (SLE or lupus) (OMIM: 152700) is a chronic autoimmune disease with debilitating inflammation that affects multiple organ systems. The STAT1-STAT4 locus is one of the first and most highly-replicated genetic loci associated with lupus risk. We performed a fine-mapping study to identify plausible causal variants within the STAT1-STAT4 locus associated with increased lupus disease risk. Using complementary frequentist and Bayesian approaches in trans-ancestral Discovery and Replication cohorts, we found one variant whose association with lupus risk is supported across ancestries in both the Discovery and Replication cohorts: rs11889341. In B cell lines from patients with lupus and healthy controls, the lupus risk allele of rs11889341 was associated with increased STAT1 expression. We demonstrated that the transcription factor HMGA1, a member of the HMG transcription factor family with an AT-hook DNA-binding domain, has enriched binding to the risk allele compared to the non-risk allele of rs11889341. We identified a genotype-dependent repressive element in the DNA within the intron of STAT4 surrounding rs11889341. Consistent with expression quantitative trait locus (eQTL) analysis, the lupus risk allele of rs11889341 decreased the activity of this putative repressor. Altogether, we present a plausible molecular mechanism for increased lupus risk at the STAT1-STAT4 locus in which the risk allele of rs11889341, the most probable causal variant, leads to elevated STAT1 expression in B cells due to decreased repressor activity mediated by increased binding of HMGA1.

GWAS in a Box: Statistical and Visual Analytics of Structured Associations via GenAMap

PubMed Central

Xing, Eric P.; Curtis, Ross E.; Schoenherr, Georg; Lee, Seunghak; Yin, Junming; Puniyani, Kriti; Wu, Wei; Kinnaird, Peter

2014-01-01

With the continuous improvement in genotyping and molecular phenotyping technology and the decreasing typing cost, it is expected that in a few years, more and more clinical studies of complex diseases will recruit thousands of individuals for pan-omic genetic association analyses. Hence, there is a great need for algorithms and software tools that could scale up to the whole omic level, integrate different omic data, leverage rich structure information, and be easily accessible to non-technical users. We present GenAMap, an interactive analytics software platform that 1) automates the execution of principled machine learning methods that detect genome- and phenome-wide associations among genotypes, gene expression data, and clinical or other macroscopic traits, and 2) provides new visualization tools specifically designed to aid in the exploration of association mapping results. Algorithmically, GenAMap is based on a new paradigm for GWAS and PheWAS analysis, termed structured association mapping, which leverages various structures in the omic data. We demonstrate the function of GenAMap via a case study of the Brem and Kruglyak yeast dataset, and then apply it on a comprehensive eQTL analysis of the NIH heterogeneous stock mice dataset and report some interesting findings. GenAMap is available from http://sailing.cs.cmu.edu/genamap. PMID:24905018

Down-regulation of PRKCB1 expression in Han Chinese patients with subsyndromal symptomatic depression.

PubMed

Guo, Xiaoyun; Li, Zezhi; Zhang, Chen; Yi, Zhenghui; Li, Haozhe; Cao, Lan; Yuan, Chengmei; Hong, Wu; Wu, Zhiguo; Peng, Daihui; Chen, Jun; Xia, Weiping; Zhao, Guoqing; Wang, Fan; Yu, Shunying; Cui, Donghong; Xu, Yifeng; Golam, Chowdhury M I; Smith, Alicia K; Wang, Tong; Fang, Yiru

2015-10-01

Subsyndromal symptomatic depression (SSD) is a common disease with significant social dysfunction. However, SSD is still not well understood and the pathophysiology of it remains unclear. We classified 48 candidate genes for SSD according to our previous study into clusters and pathways using DAVID Bioinformatics Functional Annotation Tool. We further replicated the result by using real-time Quantitative PCR (qPCR) studies to examine the expression of identified genes (i.e., STAT5b, PKCB1, ABL1 and NRAS) in another group of Han Chinese patients with SSD (n = 50). We further validated the result by examining PRKCB1 expression collected from MDD patients (n = 20). To test whether a deficit in PRKCB1 expression leads to dysregulation in PRKCB1 dependent transcript networks, we tested mRNA expression levels for the remaining 44 genes out of 48 genes in SSD patients. Finally, the power of discovery was improved by incorporating information from Quantitative Trait (eQTL) analysis. The results showed that the PRCKB1 gene expression in peripheral blood mononuclear cells (PBMC) was 33.3% down-regulated in SSD patients (n = 48, t = 3.202, p = 0.002), and a more dramatic (n = 17, 49%) down-regulation in MDD patients than control (n = 49, t = 2.114, p = 0.001). We also identified 37 genes that displayed a strong correlation with PRKCB1 mRNA expression levels in SSD patients. The expression of PRKCB1 was regulated by multiple single nucleotide polymorphisms (SNPs) both at the transcript level and exon level. In conclusion, we first found a significant decrease of PRCKB1 mRNA expression in SSD, suggesting PRKCB1 might be the candidate gene and biomarker for SSD. Copyright © 2015 Elsevier Ltd. All rights reserved.

Prospects for advancing defense to cereal rusts through genetical genomics

PubMed Central

Ballini, Elsa; Lauter, Nick; Wise, Roger

2013-01-01

Rusts are one of the most severe threats to cereal crops because new pathogen races emerge regularly, resulting in infestations that lead to large yield losses. In 1999, a new race of stem rust, Puccinia graminis f. sp. tritici (Pgt TTKSK or Ug99), was discovered in Uganda. Most of the wheat and barley cultivars grown currently worldwide are susceptible to this new race. Pgt TTKSK has already spread northward into Iran and will likely spread eastward throughout the Indian subcontinent in the near future. This scenario is not unique to stem rust; new races of leaf rust (Puccinia triticina) and stripe rust (Puccinia striiformis) have also emerged recently. One strategy for countering the persistent adaptability of these pathogens is to stack complete- and partial-resistance genes, which requires significant breeding efforts in order to reduce deleterious effects of linkage drag. These varied resistance combinations are typically more difficult for the pathogen to defeat, since they would be predicted to apply lower selection pressure. Genetical genomics or expression Quantitative Trait Locus (eQTL) analysis enables the identification of regulatory loci that control the expression of many to hundreds of genes. Integrated deployment of these technologies coupled with efficient phenotyping offers significant potential to elucidate the regulatory nodes in genetic networks that orchestrate host defense responses. The focus of this review will be to present advances in genetical genomic experimental designs and analysis, particularly as they apply to the prospects for discovering partial disease resistance alleles in cereals. PMID:23641250

Functional study of risk loci of stem cell-associated gene lin-28B and associations with disease survival outcomes in epithelial ovarian cancer.

PubMed

Lu, Lingeng; Katsaros, Dionyssios; Mayne, Susan T; Risch, Harvey A; Benedetto, Chiara; Canuto, Emilie Marion; Yu, Herbert

2012-11-01

Several single-nucleotide polymorphisms (SNPs) of the stem cell-associated gene lin-28B have been identified in association with ovarian cancer and ovarian cancer-related risk factors. However, whether these SNPs are functional or might be potential biomarkers for ovarian cancer prognosis remains unknown. The purposes of this study were to investigate the functional relevance of the identified lin-28B SNPs, as well as the associations of genotype and phenotype with epithelial ovarian cancer (EOC) survival. We analyzed five SNPs and mRNA levels of lin-28B in 211 primary EOC tissues using Taqman(®) SNP genotyping assays and SYBR green-based real-time PCR, respectively. The RNA secondary structures at the region of a genome-wide association-identified intronic rs314276 were analyzed theoretically with mfold and experimentally with circular dichroism spectroscopy. We found that rs314276 was a cis-acting expression quantitative trait locus (eQTL) in both additive and dominant models, while rs7759938 and rs314277 were significant or of borderline significance in dominant models only. The rs314276 variant significantly affects RNA secondary structure. No SNPs alone were associated with patient survival. However, we found that among patients initially responding to chemotherapy, those with higher lin-28B expression had higher mortality risk (hazard ratio =3.27, 95% confidence interval: 1.63-6.56) and relapse risk (hazard ratio = 2.53, 95% confidence interval: 1.41-4.54) than those with lower expression, and these associations remained in multivariate analyses. These results suggest that rs314276 alters RNA secondary structure and thereby influences gene expression, and that lin-28B is a cancer stem cell-associated marker, which may be a pharmaceutical target in the management of EOC.

Combining mouse mammary gland gene expression and comparative mapping for the identification of candidate genes for QTL of milk production traits in cattle

PubMed Central

Ron, Micha; Israeli, Galit; Seroussi, Eyal; Weller, Joel I; Gregg, Jeffrey P; Shani, Moshe; Medrano, Juan F

2007-01-01

Background Many studies have found segregating quantitative trait loci (QTL) for milk production traits in different dairy cattle populations. However, even for relatively large effects with a saturated marker map the confidence interval for QTL location by linkage analysis spans tens of map units, or hundreds of genes. Combining mapping and arraying has been suggested as an approach to identify candidate genes. Thus, gene expression analysis in the mammary gland of genes positioned in the confidence interval of the QTL can bridge the gap between fine mapping and quantitative trait nucleotide (QTN) determination. Results We hybridized Affymetrix microarray (MG-U74v2), containing 12,488 murine probes, with RNA derived from mammary gland of virgin, pregnant, lactating and involuting C57BL/6J mice in a total of nine biological replicates. We combined microarray data from two additional studies that used the same design in mice with a total of 75 biological replicates. The same filtering and normalization was applied to each microarray data using GeneSpring software. Analysis of variance identified 249 differentially expressed probe sets common to the three experiments along the four developmental stages of puberty, pregnancy, lactation and involution. 212 genes were assigned to their bovine map positions through comparative mapping, and thus form a list of candidate genes for previously identified QTLs for milk production traits. A total of 82 of the genes showed mammary gland-specific expression with at least 3-fold expression over the median representing all tissues tested in GeneAtlas. Conclusion This work presents a web tool for candidate genes for QTL (cgQTL) that allows navigation between the map of bovine milk production QTL, potential candidate genes and their level of expression in mammary gland arrays and in GeneAtlas. Three out of four confirmed genes that affect QTL in livestock (ABCG2, DGAT1, GDF8, IGF2) were over expressed in the target organ. Thus, cgQTL can be used to determine priority of candidate genes for QTN analysis based on differential expression in the target organ. PMID:17584498

Using microarrays to identify positional candidate genes for QTL: the case study of ACTH response in pigs.

PubMed

Jouffe, Vincent; Rowe, Suzanne; Liaubet, Laurence; Buitenhuis, Bart; Hornshøj, Henrik; SanCristobal, Magali; Mormède, Pierre; de Koning, D J

2009-07-16

Microarray studies can supplement QTL studies by suggesting potential candidate genes in the QTL regions, which by themselves are too large to provide a limited selection of candidate genes. Here we provide a case study where we explore ways to integrate QTL data and microarray data for the pig, which has only a partial genome sequence. We outline various procedures to localize differentially expressed genes on the pig genome and link this with information on published QTL. The starting point is a set of 237 differentially expressed cDNA clones in adrenal tissue from two pig breeds, before and after treatment with adrenocorticotropic hormone (ACTH). Different approaches to localize the differentially expressed (DE) genes to the pig genome showed different levels of success and a clear lack of concordance for some genes between the various approaches. For a focused analysis on 12 genes, overlapping QTL from the public domain were presented. Also, differentially expressed genes underlying QTL for ACTH response were described. Using the latest version of the draft sequence, the differentially expressed genes were mapped to the pig genome. This enabled co-location of DE genes and previously studied QTL regions, but the draft genome sequence is still incomplete and will contain many errors. A further step to explore links between DE genes and QTL at the pathway level was largely unsuccessful due to the lack of annotation of the pig genome. This could be improved by further comparative mapping analyses but this would be time consuming. This paper provides a case study for the integration of QTL data and microarray data for a species with limited genome sequence information and annotation. The results illustrate the challenges that must be addressed but also provide a roadmap for future work that is applicable to other non-model species.

Genetic and environmental risk factors for atherosclerosis regulate transcription of phosphatase and actin regulating gene PHACTR1.

PubMed

Reschen, Michael E; Lin, Da; Chalisey, Anil; Soilleux, Elizabeth J; O'Callaghan, Christopher A

2016-07-01

Coronary artery disease (CAD) risk is associated with non-coding genetic variants at the phosphatase and actin regulating protein 1(PHACTR1) gene locus. The PHACTR1 gene encodes an actin-binding protein with phosphatase regulating activity. The mechanism whereby PHACTR1 influences CAD risk is unknown. We hypothesized that PHACTR1 would be expressed in human cell types relevant to CAD and regulated by atherogenic or genetic factors. Using immunohistochemistry, we demonstrate that PHACTR1 protein is expressed strongly in human atherosclerotic plaque macrophages, lipid-laden foam cells, adventitial lymphocytes and endothelial cells. Using a combination of genomic analysis and molecular techniques, we demonstrate that PHACTR1 is expressed as multiple previously uncharacterized transcripts in macrophages, foam cells, lymphocytes and endothelial cells. Immunoblotting confirmed a total absence of PHACTR1 in vascular smooth muscle cells. Real-time quantitative PCR showed that PHACTR1 is regulated by atherogenic and inflammatory stimuli. In aortic endothelial cells, oxLDL and TNF-alpha both upregulated an intermediate length transcript. A short transcript expressed only in immune cells was upregulated in macrophages by oxidized low-density lipoprotein, and oxidized phospholipids but suppressed by lipopolysaccharide or TNF-alpha. In primary human macrophages, we identified a novel expression quantitative trait locus (eQTL) specific for this short transcript, whereby the risk allele at CAD risk SNP rs9349379 is associated with reduced PHACTR1 expression, similar to the effect of an inflammatory stimulus. Our data demonstrate that PHACTR1 is a key atherosclerosis candidate gene since it is regulated by atherogenic stimuli in macrophages and endothelial cells and we identify an effect of the genetic risk variant on PHACTR1 expression in macrophages that is similar to that of an inflammatory stimulus. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Systematic Integration of Brain eQTL and GWAS Identifies ZNF323 as a Novel Schizophrenia Risk Gene and Suggests Recent Positive Selection Based on Compensatory Advantage on Pulmonary Function.

PubMed

Luo, Xiong-Jian; Mattheisen, Manuel; Li, Ming; Huang, Liang; Rietschel, Marcella; Børglum, Anders D; Als, Thomas D; van den Oord, Edwin J; Aberg, Karolina A; Mors, Ole; Mortensen, Preben Bo; Luo, Zhenwu; Degenhardt, Franziska; Cichon, Sven; Schulze, Thomas G; Nöthen, Markus M; Su, Bing; Zhao, Zhongming; Gan, Lin; Yao, Yong-Gang

2015-11-01

Genome-wide association studies have identified multiple risk variants and loci that show robust association with schizophrenia. Nevertheless, it remains unclear how these variants confer risk to schizophrenia. In addition, the driving force that maintains the schizophrenia risk variants in human gene pool is poorly understood. To investigate whether expression-associated genetic variants contribute to schizophrenia susceptibility, we systematically integrated brain expression quantitative trait loci and genome-wide association data of schizophrenia using Sherlock, a Bayesian statistical framework. Our analyses identified ZNF323 as a schizophrenia risk gene (P = 2.22×10(-6)). Subsequent analyses confirmed the association of the ZNF323 and its expression-associated single nucleotide polymorphism rs1150711 in independent samples (gene-expression: P = 1.40×10(-6); single-marker meta-analysis in the combined discovery and replication sample comprising 44123 individuals: P = 6.85×10(-10)). We found that the ZNF323 was significantly downregulated in hippocampus and frontal cortex of schizophrenia patients (P = .0038 and P = .0233, respectively). Evidence for pleiotropic effects was detected (association of rs1150711 with lung function and gene expression of ZNF323 in lung: P = 6.62×10(-5) and P = 9.00×10(-5), respectively) with the risk allele (T allele) for schizophrenia acting as protective allele for lung function. Subsequent population genetics analyses suggest that the risk allele (T) of rs1150711 might have undergone recent positive selection in human population. Our findings suggest that the ZNF323 is a schizophrenia susceptibility gene whose expression may influence schizophrenia risk. Our study also illustrates a possible mechanism for maintaining schizophrenia risk variants in the human gene pool. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Cognitive analysis of schizophrenia risk genes that function as epigenetic regulators of gene expression.

PubMed

Whitton, Laura; Cosgrove, Donna; Clarkson, Christopher; Harold, Denise; Kendall, Kimberley; Richards, Alex; Mantripragada, Kiran; Owen, Michael J; O'Donovan, Michael C; Walters, James; Hartmann, Annette; Konte, Betina; Rujescu, Dan; Gill, Michael; Corvin, Aiden; Rea, Stephen; Donohoe, Gary; Morris, Derek W

2016-12-01

Epigenetic mechanisms are an important heritable and dynamic means of regulating various genomic functions, including gene expression, to orchestrate brain development, adult neurogenesis, and synaptic plasticity. These processes when perturbed are thought to contribute to schizophrenia pathophysiology. A core feature of schizophrenia is cognitive dysfunction. For genetic disorders where cognitive impairment is more severe such as intellectual disability, there are a disproportionally high number of genes involved in the epigenetic regulation of gene transcription. Evidence now supports some shared genetic aetiology between schizophrenia and intellectual disability. GWAS have identified 108 chromosomal regions associated with schizophrenia risk that span 350 genes. This study identified genes mapping to those loci that have epigenetic functions, and tested the risk alleles defining those loci for association with cognitive deficits. We developed a list of 350 genes with epigenetic functions and cross-referenced this with the GWAS loci. This identified eight candidate genes: BCL11B, CHD7, EP300, EPC2, GATAD2A, KDM3B, RERE, SATB2. Using a dataset of Irish psychosis cases and controls (n = 1235), the schizophrenia risk SNPs at these loci were tested for effects on IQ, working memory, episodic memory, and attention. Strongest associations were for rs6984242 with both measures of IQ (P = 0.001) and episodic memory (P = 0.007). We link rs6984242 to CHD7 via a long range eQTL. These associations were not replicated in independent samples. Our study highlights that a number of genes mapping to risk loci for schizophrenia may function as epigenetic regulators of gene expression but further studies are required to establish a role for these genes in cognition. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Whole genome sequencing of an African American family highlights toll like receptor 6 variants in Kawasaki disease susceptibility.

PubMed

Kim, Jihoon; Shimizu, Chisato; Kingsmore, Stephen F; Veeraraghavan, Narayanan; Levy, Eric; Ribeiro Dos Santos, Andre M; Yang, Hai; Flatley, Jay; Hoang, Long Truong; Hibberd, Martin L; Tremoulet, Adriana H; Harismendy, Olivier; Ohno-Machado, Lucila; Burns, Jane C

2017-01-01

Kawasaki disease (KD) is the most common acquired pediatric heart disease. We analyzed Whole Genome Sequences (WGS) from a 6-member African American family in which KD affected two of four children. We sought rare, potentially causative genotypes by sequentially applying the following WGS filters: sequence quality scores, inheritance model (recessive homozygous and compound heterozygous), predicted deleteriousness, allele frequency, genes in KD-associated pathways or with significant associations in published KD genome-wide association studies (GWAS), and with differential expression in KD blood transcriptomes. Biologically plausible genotypes were identified in twelve variants in six genes in the two affected children. The affected siblings were compound heterozygous for the rare variants p.Leu194Pro and p.Arg247Lys in Toll-like receptor 6 (TLR6), which affect TLR6 signaling. The affected children were also homozygous for three common, linked (r2 = 1) intronic single nucleotide variants (SNVs) in TLR6 (rs56245262, rs56083757 and rs7669329), that have previously shown association with KD in cohorts of European descent. Using transcriptome data from pre-treatment whole blood of KD subjects (n = 146), expression quantitative trait loci (eQTL) analyses were performed. Subjects homozygous for the intronic risk allele (A allele of TLR6 rs56245262) had differential expression of Interleukin-6 (IL-6) as a function of genotype (p = 0.0007) and a higher erythrocyte sedimentation rate at diagnosis. TLR6 plays an important role in pathogen-associated molecular pattern recognition, and sequence variations may affect binding affinities that in turn influence KD susceptibility. This integrative genomic approach illustrates how the analysis of WGS in multiplex families with a complex genetic disease allows examination of both the common disease-common variant and common disease-rare variant hypotheses.

Identification and functional analysis of glycemic trait loci in the China Health and Nutrition Survey

PubMed Central

Wu, Ying; Zou, Meng; Raulerson, Chelsea K.; Jackson, Kayla; Yuan, Wentao; Wang, Haifeng; Shou, Weihua; Wang, Ying; Luo, Jingchun; Lange, Leslie A.; Lange, Ethan M.; Gordon-Larsen, Penny; Du, Shufa; Huang, Wei; Mohlke, Karen L.

2018-01-01

To identify genetic contributions to type 2 diabetes (T2D) and related glycemic traits (fasting glucose, fasting insulin, and HbA1c), we conducted genome-wide association analyses (GWAS) in up to 7,178 Chinese subjects from nine provinces in the China Health and Nutrition Survey (CHNS). We examined patterns of population structure within CHNS and found that allele frequencies differed across provinces, consistent with genetic drift and population substructure. We further validated 32 previously described T2D- and glycemic trait-loci, including G6PC2 and SIX3-SIX2 associated with fasting glucose. At G6PC2, we replicated a known fasting glucose-associated variant (rs34177044) and identified a second signal (rs2232326), a low-frequency (4%), probably damaging missense variant (S324P). A variant within the lead fasting glucose-associated signal at SIX3-SIX2 co-localized with pancreatic islet expression quantitative trait loci (eQTL) for SIX3, SIX2, and three noncoding transcripts. To identify variants functionally responsible for the fasting glucose association at SIX3-SIX2, we tested five candidate variants for allelic differences in regulatory function. The rs12712928-C allele, associated with higher fasting glucose and lower transcript expression level, showed lower transcriptional activity in reporter assays and increased binding to GABP compared to the rs12712928-G, suggesting that rs12712928-C contributes to elevated fasting glucose levels by disrupting an islet enhancer, resulting in reduced gene expression. Taken together, these analyses identified multiple loci associated with glycemic traits across China, and suggest a regulatory mechanism at the SIX3-SIX2 fasting glucose GWAS locus. PMID:29621232

Identification of a novel locus on chromosome 2q13, which predisposes to clinical vertebral fractures independently of bone density.

PubMed

Alonso, Nerea; Estrada, Karol; Albagha, Omar M E; Herrera, Lizbeth; Reppe, Sjur; Olstad, Ole K; Gautvik, Kaare M; Ryan, Niamh M; Evans, Kathryn L; Nielson, Carrie M; Hsu, Yi-Hsiang; Kiel, Douglas P; Markozannes, George; Ntzani, Evangelia E; Evangelou, Evangelos; Feenstra, Bjarke; Liu, Xueping; Melbye, Mads; Masi, Laura; Brandi, Maria Luisa; Riches, Philip; Daroszewska, Anna; Olmos, José Manuel; Valero, Carmen; Castillo, Jesús; Riancho, José A; Husted, Lise B; Langdahl, Bente L; Brown, Matthew A; Duncan, Emma L; Kaptoge, Stephen; Khaw, Kay-Tee; Usategui-Martín, Ricardo; Del Pino-Montes, Javier; González-Sarmiento, Rogelio; Lewis, Joshua R; Prince, Richard L; D'Amelio, Patrizia; García-Giralt, Natalia; Nogués, Xavier; Mencej-Bedrac, Simona; Marc, Janja; Wolstein, Orit; Eisman, John A; Oei, Ling; Medina-Gómez, Carolina; Schraut, Katharina E; Navarro, Pau; Wilson, James F; Davies, Gail; Starr, John; Deary, Ian; Tanaka, Toshiko; Ferrucci, Luigi; Gianfrancesco, Fernando; Gennari, Luigi; Lucas, Gavin; Elosua, Roberto; Uitterlinden, André G; Rivadeneira, Fernando; Ralston, Stuart H

2018-03-01

To identify genetic determinants of susceptibility to clinical vertebral fractures, which is an important complication of osteoporosis. Here we conduct a genome-wide association study in 1553 postmenopausal women with clinical vertebral fractures and 4340 controls, with a two-stage replication involving 1028 cases and 3762 controls. Potentially causal variants were identified using expression quantitative trait loci (eQTL) data from transiliac bone biopsies and bioinformatic studies. A locus tagged by rs10190845 was identified on chromosome 2q13, which was significantly associated with clinical vertebral fracture (P=1.04×10 -9 ) with a large effect size (OR 1.74, 95% CI 1.06 to 2.6). Bioinformatic analysis of this locus identified several potentially functional SNPs that are associated with expression of the positional candidate genes TTL (tubulin tyrosine ligase) and SLC20A1 (solute carrier family 20 member 1). Three other suggestive loci were identified on chromosomes 1p31, 11q12 and 15q11. All these loci were novel and had not previously been associated with bone mineral density or clinical fractures. We have identified a novel genetic variant that is associated with clinical vertebral fractures by mechanisms that are independent of BMD. Further studies are now in progress to validate this association and evaluate the underlying mechanism. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Comprehensive genetic assessment of the ESR1 locus identifies a risk region for endometrial cancer.

PubMed

O'Mara, Tracy A; Glubb, Dylan M; Painter, Jodie N; Cheng, Timothy; Dennis, Joe; Attia, John; Holliday, Elizabeth G; McEvoy, Mark; Scott, Rodney J; Ashton, Katie; Proietto, Tony; Otton, Geoffrey; Shah, Mitul; Ahmed, Shahana; Healey, Catherine S; Gorman, Maggie; Martin, Lynn; Hodgson, Shirley; Fasching, Peter A; Hein, Alexander; Beckmann, Matthias W; Ekici, Arif B; Hall, Per; Czene, Kamila; Darabi, Hatef; Li, Jingmei; Dürst, Matthias; Runnebaum, Ingo; Hillemanns, Peter; Dörk, Thilo; Lambrechts, Diether; Depreeuw, Jeroen; Annibali, Daniela; Amant, Frederic; Zhao, Hui; Goode, Ellen L; Dowdy, Sean C; Fridley, Brooke L; Winham, Stacey J; Salvesen, Helga B; Njølstad, Tormund S; Trovik, Jone; Werner, Henrica M J; Tham, Emma; Liu, Tao; Mints, Miriam; Bolla, Manjeet K; Michailidou, Kyriaki; Tyrer, Jonathan P; Wang, Qin; Hopper, John L; Peto, Julian; Swerdlow, Anthony J; Burwinkel, Barbara; Brenner, Hermann; Meindl, Alfons; Brauch, Hiltrud; Lindblom, Annika; Chang-Claude, Jenny; Couch, Fergus J; Giles, Graham G; Kristensen, Vessela N; Cox, Angela; Pharoah, Paul D P; Dunning, Alison M; Tomlinson, Ian; Easton, Douglas F; Thompson, Deborah J; Spurdle, Amanda B

2015-10-01

Excessive exposure to estrogen is a well-established risk factor for endometrial cancer (EC), particularly for cancers of endometrioid histology. The physiological function of estrogen is primarily mediated by estrogen receptor alpha, encoded by ESR1. Consequently, several studies have investigated whether variation at the ESR1 locus is associated with risk of EC, with conflicting results. We performed comprehensive fine-mapping analyses of 3633 genotyped and imputed single nucleotide polymorphisms (SNPs) in 6607 EC cases and 37 925 controls. There was evidence of an EC risk signal located at a potential alternative promoter of the ESR1 gene (lead SNP rs79575945, P=1.86×10(-5)), which was stronger for cancers of endometrioid subtype (P=3.76×10(-6)). Bioinformatic analysis suggests that this risk signal is in a functionally important region targeting ESR1, and eQTL analysis found that rs79575945 was associated with expression of SYNE1, a neighbouring gene. In summary, we have identified a single EC risk signal located at ESR1, at study-wide significance. Given SNPs located at this locus have been associated with risk for breast cancer, also a hormonally driven cancer, this study adds weight to the rationale for performing informed candidate fine-scale genetic studies across cancer types. © 2015 Society for Endocrinology.

Systems Genetic Analysis of Osteoblast-Lineage Cells

PubMed Central

Calabrese, Gina; Bennett, Brian J.; Orozco, Luz; Kang, Hyun M.; Eskin, Eleazar; Dombret, Carlos; De Backer, Olivier; Lusis, Aldons J.; Farber, Charles R.

2012-01-01

The osteoblast-lineage consists of cells at various stages of maturation that are essential for skeletal development, growth, and maintenance. Over the past decade, many of the signaling cascades that regulate this lineage have been elucidated; however, little is known of the networks that coordinate, modulate, and transmit these signals. Here, we identify a gene network specific to the osteoblast-lineage through the reconstruction of a bone co-expression network using microarray profiles collected on 96 Hybrid Mouse Diversity Panel (HMDP) inbred strains. Of the 21 modules that comprised the bone network, module 9 (M9) contained genes that were highly correlated with prototypical osteoblast maker genes and were more highly expressed in osteoblasts relative to other bone cells. In addition, the M9 contained many of the key genes that define the osteoblast-lineage, which together suggested that it was specific to this lineage. To use the M9 to identify novel osteoblast genes and highlight its biological relevance, we knocked-down the expression of its two most connected “hub” genes, Maged1 and Pard6g. Their perturbation altered both osteoblast proliferation and differentiation. Furthermore, we demonstrated the mice deficient in Maged1 had decreased bone mineral density (BMD). It was also discovered that a local expression quantitative trait locus (eQTL) regulating the Wnt signaling antagonist Sfrp1 was a key driver of the M9. We also show that the M9 is associated with BMD in the HMDP and is enriched for genes implicated in the regulation of human BMD through genome-wide association studies. In conclusion, we have identified a physiologically relevant gene network and used it to discover novel genes and regulatory mechanisms involved in the function of osteoblast-lineage cells. Our results highlight the power of harnessing natural genetic variation to generate co-expression networks that can be used to gain insight into the function of specific cell-types. PMID:23300464

New investigations around CYP11A1 and its possible involvement in an androstenone QTL characterised in Large White pigs

PubMed Central

2011-01-01

Background Previously, in boars with extreme androstenone levels, differential expression of the CYP11A1 gene in the testes has been characterised. CYP11A1 is located in a region where a QTL influencing boar fat androstenone levels has been detected in a Large White pig population. Clarifying the role of CYP11A1 in boar taint is important because it catalyses the initial step of androstenone synthesis and also of steroid synthesis. Results A genome-wide association study located CYP11A1 at approximately 1300 kb upstream from SNP H3GA0021967, defining the centre of the region containing the QTL for androstenone variation. In this study, we partially sequenced the CYP11A1 gene and identified several new single nucleotide polymorphisms (SNP) within it. Characterisation of one animal, heterozygous for CYP11A1 testicular expression but homozygous for a haplotype of a large region containing CYP11A1, revealed that variation of CYP11A1 expression is probably regulated by a mutation located downstream from the SNP H3GA0021967. We analysed CYP11A1 expression in LW families according to haplotypes of the QTL region's centre. Effects of haplotypes on CYP11A1 expression and on androstenone accumulation were not concordant. Conclusion This study shows that testicular expression of CYP11A1 is not solely responsible for the QTL influencing boar fat androstenone levels. As a conclusion, we propose to refute the hypothesis that a single mutation located near the centre of the QTL region could control androstenone accumulation in fat by regulating the CYP11A1 expression. PMID:21504607

Reconstructing directed gene regulatory network by only gene expression data.

PubMed

Zhang, Lu; Feng, Xi Kang; Ng, Yen Kaow; Li, Shuai Cheng

2016-08-18

Accurately identifying gene regulatory network is an important task in understanding in vivo biological activities. The inference of such networks is often accomplished through the use of gene expression data. Many methods have been developed to evaluate gene expression dependencies between transcription factor and its target genes, and some methods also eliminate transitive interactions. The regulatory (or edge) direction is undetermined if the target gene is also a transcription factor. Some methods predict the regulatory directions in the gene regulatory networks by locating the eQTL single nucleotide polymorphism, or by observing the gene expression changes when knocking out/down the candidate transcript factors; regrettably, these additional data are usually unavailable, especially for the samples deriving from human tissues. In this study, we propose the Context Based Dependency Network (CBDN), a method that is able to infer gene regulatory networks with the regulatory directions from gene expression data only. To determine the regulatory direction, CBDN computes the influence of source to target by evaluating the magnitude changes of expression dependencies between the target gene and the others with conditioning on the source gene. CBDN extends the data processing inequality by involving the dependency direction to distinguish between direct and transitive relationship between genes. We also define two types of important regulators which can influence a majority of the genes in the network directly or indirectly. CBDN can detect both of these two types of important regulators by averaging the influence functions of candidate regulator to the other genes. In our experiments with simulated and real data, even with the regulatory direction taken into account, CBDN outperforms the state-of-the-art approaches for inferring gene regulatory network. CBDN identifies the important regulators in the predicted network: 1. TYROBP influences a batch of genes that are related to Alzheimer's disease; 2. ZNF329 and RB1 significantly regulate those 'mesenchymal' gene expression signature genes for brain tumors. By merely leveraging gene expression data, CBDN can efficiently infer the existence of gene-gene interactions as well as their regulatory directions. The constructed networks are helpful in the identification of important regulators for complex diseases.

Experimental and Human Evidence for Lipocalin-2 (Neutrophil Gelatinase-Associated Lipocalin [NGAL]) in the Development of Cardiac Hypertrophy and heart failure.

PubMed

Marques, Francine Z; Prestes, Priscilla R; Byars, Sean G; Ritchie, Scott C; Würtz, Peter; Patel, Sheila K; Booth, Scott A; Rana, Indrajeetsinh; Minoda, Yosuke; Berzins, Stuart P; Curl, Claire L; Bell, James R; Wai, Bryan; Srivastava, Piyush M; Kangas, Antti J; Soininen, Pasi; Ruohonen, Saku; Kähönen, Mika; Lehtimäki, Terho; Raitoharju, Emma; Havulinna, Aki; Perola, Markus; Raitakari, Olli; Salomaa, Veikko; Ala-Korpela, Mika; Kettunen, Johannes; McGlynn, Maree; Kelly, Jason; Wlodek, Mary E; Lewandowski, Paul A; Delbridge, Lea M; Burrell, Louise M; Inouye, Michael; Harrap, Stephen B; Charchar, Fadi J

2017-06-14

Cardiac hypertrophy increases the risk of developing heart failure and cardiovascular death. The neutrophil inflammatory protein, lipocalin-2 (LCN2/NGAL), is elevated in certain forms of cardiac hypertrophy and acute heart failure. However, a specific role for LCN2 in predisposition and etiology of hypertrophy and the relevant genetic determinants are unclear. Here, we defined the role of LCN2 in concentric cardiac hypertrophy in terms of pathophysiology, inflammatory expression networks, and genomic determinants. We used 3 experimental models: a polygenic model of cardiac hypertrophy and heart failure, a model of intrauterine growth restriction and Lcn2 -knockout mouse; cultured cardiomyocytes; and 2 human cohorts: 114 type 2 diabetes mellitus patients and 2064 healthy subjects of the YFS (Young Finns Study). In hypertrophic heart rats, cardiac and circulating Lcn2 was significantly overexpressed before, during, and after development of cardiac hypertrophy and heart failure. Lcn2 expression was increased in hypertrophic hearts in a model of intrauterine growth restriction, whereas Lcn2 -knockout mice had smaller hearts. In cultured cardiomyocytes, Lcn2 activated molecular hypertrophic pathways and increased cell size, but reduced proliferation and cell numbers. Increased LCN2 was associated with cardiac hypertrophy and diastolic dysfunction in diabetes mellitus. In the YFS, LCN2 expression was associated with body mass index and cardiac mass and with levels of inflammatory markers. The single-nucleotide polymorphism, rs13297295, located near LCN2 defined a significant cis -eQTL for LCN2 expression. Direct effects of LCN2 on cardiomyocyte size and number and the consistent associations in experimental and human analyses reveal a central role for LCN2 in the ontogeny of cardiac hypertrophy and heart failure. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

FUN-LDA: A Latent Dirichlet Allocation Model for Predicting Tissue-Specific Functional Effects of Noncoding Variation: Methods and Applications.

PubMed

Backenroth, Daniel; He, Zihuai; Kiryluk, Krzysztof; Boeva, Valentina; Pethukova, Lynn; Khurana, Ekta; Christiano, Angela; Buxbaum, Joseph D; Ionita-Laza, Iuliana

2018-05-03

We describe a method based on a latent Dirichlet allocation model for predicting functional effects of noncoding genetic variants in a cell-type- and/or tissue-specific way (FUN-LDA). Using this unsupervised approach, we predict tissue-specific functional effects for every position in the human genome in 127 different tissues and cell types. We demonstrate the usefulness of our predictions by using several validation experiments. Using eQTL data from several sources, including the GTEx project, Geuvadis project, and TwinsUK cohort, we show that eQTLs in specific tissues tend to be most enriched among the predicted functional variants in relevant tissues in Roadmap. We further show how these integrated functional scores can be used for (1) deriving the most likely cell or tissue type causally implicated for a complex trait by using summary statistics from genome-wide association studies and (2) estimating a tissue-based correlation matrix of various complex traits. We found large enrichment of heritability in functional components of relevant tissues for various complex traits, and FUN-LDA yielded higher enrichment estimates than existing methods. Finally, using experimentally validated functional variants from the literature and variants possibly implicated in disease by previous studies, we rigorously compare FUN-LDA with state-of-the-art functional annotation methods and show that FUN-LDA has better prediction accuracy and higher resolution than these methods. In particular, our results suggest that tissue- and cell-type-specific functional prediction methods tend to have substantially better prediction accuracy than organism-level prediction methods. Scores for each position in the human genome and for each ENCODE and Roadmap tissue are available online (see Web Resources). Copyright © 2018 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Identification of genetic variants predictive of early onset pancreatic cancer through a population science analysis of functional genomic datasets

PubMed Central

Chen, Jinyun; Wu, Xifeng; Huang, Yujing; Chen, Wei; Brand, Randall E.; Killary, Ann M.; Sen, Subrata; Frazier, Marsha L.

2016-01-01

Biomarkers are critically needed for the early detection of pancreatic cancer (PC) are urgently needed. Our purpose was to identify a panel of genetic variants that, combined, can predict increased risk for early-onset PC and thereby identify individuals who should begin screening at an early age. Previously, we identified genes using a functional genomic approach that were aberrantly expressed in early pathways to PC tumorigenesis. We now report the discovery of single nucleotide polymorphisms (SNPs) in these genes associated with early age at diagnosis of PC using a two-phase study design. In silico and bioinformatics tools were used to examine functional relevance of the identified SNPs. Eight SNPs were consistently associated with age at diagnosis in the discovery phase, validation phase and pooled analysis. Further analysis of the joint effects of these 8 SNPs showed that, compared to participants carrying none of these unfavorable genotypes (median age at PC diagnosis 70 years), those carrying 1–2, 3–4, or 5 or more unfavorable genotypes had median ages at diagnosis of 64, 63, and 62 years, respectively (P = 3.0E–04). A gene-dosage effect was observed, with age at diagnosis inversely related to number of unfavorable genotypes (Ptrend = 1.0E–04). Using bioinformatics tools, we found that all of the 8 SNPs were predicted to play functional roles in the disruption of transcription factor and/or enhancer binding sites and most of them were expression quantitative trait loci (eQTL) of the target genes. The panel of genetic markers identified may serve as susceptibility markers for earlier PC diagnosis. PMID:27486767

mQTL-seq delineates functionally relevant candidate gene harbouring a major QTL regulating pod number in chickpea

PubMed Central

Das, Shouvik; Singh, Mohar; Srivastava, Rishi; Bajaj, Deepak; Saxena, Maneesha S.; Rana, Jai C.; Bansal, Kailash C.; Tyagi, Akhilesh K.; Parida, Swarup K.

2016-01-01

The present study used a whole-genome, NGS resequencing-based mQTL-seq (multiple QTL-seq) strategy in two inter-specific mapping populations (Pusa 1103 × ILWC 46 and Pusa 256 × ILWC 46) to scan the major genomic region(s) underlying QTL(s) governing pod number trait in chickpea. Essentially, the whole-genome resequencing of low and high pod number-containing parental accessions and homozygous individuals (constituting bulks) from each of these two mapping populations discovered >8 million high-quality homozygous SNPs with respect to the reference kabuli chickpea. The functional significance of the physically mapped SNPs was apparent from the identified 2,264 non-synonymous and 23,550 regulatory SNPs, with 8–10% of these SNPs-carrying genes corresponding to transcription factors and disease resistance-related proteins. The utilization of these mined SNPs in Δ (SNP index)-led QTL-seq analysis and their correlation between two mapping populations based on mQTL-seq, narrowed down two (CaqaPN4.1: 867.8 kb and CaqaPN4.2: 1.8 Mb) major genomic regions harbouring robust pod number QTLs into the high-resolution short QTL intervals (CaqbPN4.1: 637.5 kb and CaqbPN4.2: 1.28 Mb) on chickpea chromosome 4. The integration of mQTL-seq-derived one novel robust QTL with QTL region-specific association analysis delineated the regulatory (C/T) and coding (C/A) SNPs-containing one pentatricopeptide repeat (PPR) gene at a major QTL region regulating pod number in chickpea. This target gene exhibited anther, mature pollen and pod-specific expression, including pronounced higher up-regulated (∼3.5-folds) transcript expression in high pod number-containing parental accessions and homozygous individuals of two mapping populations especially during pollen and pod development. The proposed mQTL-seq-driven combinatorial strategy has profound efficacy in rapid genome-wide scanning of potential candidate gene(s) underlying trait-associated high-resolution robust QTL(s), thereby expediting genomics-assisted breeding and genetic enhancement of crop plants, including chickpea. PMID:26685680

Identification of QTLs associated with oil content and mapping FAD2 genes and their relative contribution to oil quality in peanut (Arachis hypogaea L.).

PubMed

Pandey, Manish K; Wang, Ming Li; Qiao, Lixian; Feng, Suping; Khera, Pawan; Wang, Hui; Tonnis, Brandon; Barkley, Noelle A; Wang, Jianping; Holbrook, C Corley; Culbreath, Albert K; Varshney, Rajeev K; Guo, Baozhu

2014-12-10

Peanut is one of the major source for human consumption worldwide and its seed contain approximately 50% oil. Improvement of oil content and quality traits (high oleic and low linoleic acid) in peanut could be accelerated by exploiting linked markers through molecular breeding. The objective of this study was to identify QTLs associated with oil content, and estimate relative contribution of FAD2 genes (ahFAD2A and ahFAD2B) to oil quality traits in two recombinant inbred line (RIL) populations. Improved genetic linkage maps were developed for S-population (SunOleic 97R × NC94022) with 206 (1780.6 cM) and T-population (Tifrunner × GT-C20) with 378 (2487.4 cM) marker loci. A total of 6 and 9 QTLs controlling oil content were identified in the S- and T-population, respectively. The contribution of each QTL towards oil content variation ranged from 3.07 to 10.23% in the S-population and from 3.93 to 14.07% in the T-population. The mapping positions for ahFAD2A (A sub-genome) and ahFAD2B (B sub-genome) genes were assigned on a09 and b09 linkage groups. The ahFAD2B gene (26.54%, 25.59% and 41.02% PVE) had higher phenotypic effect on oleic acid (C18:1), linoleic acid (C18:2), and oleic/linoleic acid ratio (O/L ratio) than ahFAD2A gene (8.08%, 6.86% and 3.78% PVE). The FAD2 genes had no effect on oil content. This study identified a total of 78 main-effect QTLs (M-QTLs) with up to 42.33% phenotypic variation (PVE) and 10 epistatic QTLs (E-QTLs) up to 3.31% PVE for oil content and quality traits. A total of 78 main-effect QTLs (M-QTLs) and 10 E-QTLs have been detected for oil content and oil quality traits. One major QTL (more than 10% PVE) was identified in both the populations for oil content with source alleles from NC94022 and GT-C20 parental genotypes. FAD2 genes showed high effect for oleic acid (C18:1), linoleic acid (C18:2), and O/L ratio while no effect on total oil content. The information on phenotypic effect of FAD2 genes for oleic acid, linoleic acid and O/L ratio, and oil content will be applied in breeding selection.

Functional regression method for whole genome eQTL epistasis analysis with sequencing data.

PubMed

Xu, Kelin; Jin, Li; Xiong, Momiao

2017-05-18

Epistasis plays an essential rule in understanding the regulation mechanisms and is an essential component of the genetic architecture of the gene expressions. However, interaction analysis of gene expressions remains fundamentally unexplored due to great computational challenges and data availability. Due to variation in splicing, transcription start sites, polyadenylation sites, post-transcriptional RNA editing across the entire gene, and transcription rates of the cells, RNA-seq measurements generate large expression variability and collectively create the observed position level read count curves. A single number for measuring gene expression which is widely used for microarray measured gene expression analysis is highly unlikely to sufficiently account for large expression variation across the gene. Simultaneously analyzing epistatic architecture using the RNA-seq and whole genome sequencing (WGS) data poses enormous challenges. We develop a nonlinear functional regression model (FRGM) with functional responses where the position-level read counts within a gene are taken as a function of genomic position, and functional predictors where genotype profiles are viewed as a function of genomic position, for epistasis analysis with RNA-seq data. Instead of testing the interaction of all possible pair-wises SNPs, the FRGM takes a gene as a basic unit for epistasis analysis, which tests for the interaction of all possible pairs of genes and use all the information that can be accessed to collectively test interaction between all possible pairs of SNPs within two genome regions. By large-scale simulations, we demonstrate that the proposed FRGM for epistasis analysis can achieve the correct type 1 error and has higher power to detect the interactions between genes than the existing methods. The proposed methods are applied to the RNA-seq and WGS data from the 1000 Genome Project. The numbers of pairs of significantly interacting genes after Bonferroni correction identified using FRGM, RPKM and DESeq were 16,2361, 260 and 51, respectively, from the 350 European samples. The proposed FRGM for epistasis analysis of RNA-seq can capture isoform and position-level information and will have a broad application. Both simulations and real data analysis highlight the potential for the FRGM to be a good choice of the epistatic analysis with sequencing data.

Integrating mRNA and miRNA Weighted Gene Co-Expression Networks with eQTLs in the Nucleus Accumbens of Subjects with Alcohol Dependence

PubMed Central

Blevins, Tana; Aliev, Fazil; Adkins, Amy; Hack, Laura; Bigdeli, Tim; D. van der Vaart, Andrew; Web, Bradley Todd; Bacanu, Silviu-Alin; Kalsi, Gursharan; Kendler, Kenneth S.; Miles, Michael F.; Dick, Danielle; Riley, Brien P.; Dumur, Catherine; Vladimirov, Vladimir I.

2015-01-01

Alcohol consumption is known to lead to gene expression changes in the brain. After performing weighted gene co-expression network analyses (WGCNA) on genome-wide mRNA and microRNA (miRNA) expression in Nucleus Accumbens (NAc) of subjects with alcohol dependence (AD; N = 18) and of matched controls (N = 18), six mRNA and three miRNA modules significantly correlated with AD were identified (Bonferoni-adj. p≤ 0.05). Cell-type-specific transcriptome analyses revealed two of the mRNA modules to be enriched for neuronal specific marker genes and downregulated in AD, whereas the remaining four mRNA modules were enriched for astrocyte and microglial specific marker genes and upregulated in AD. Gene set enrichment analysis demonstrated that neuronal specific modules were enriched for genes involved in oxidative phosphorylation, mitochondrial dysfunction and MAPK signaling. Glial-specific modules were predominantly enriched for genes involved in processes related to immune functions, i.e. cytokine signaling (all adj. p≤ 0.05). In mRNA and miRNA modules, 461 and 25 candidate hub genes were identified, respectively. In contrast to the expected biological functions of miRNAs, correlation analyses between mRNA and miRNA hub genes revealed a higher number of positive than negative correlations (χ2 test p≤ 0.0001). Integration of hub gene expression with genome-wide genotypic data resulted in 591 mRNA cis-eQTLs and 62 miRNA cis-eQTLs. mRNA cis-eQTLs were significantly enriched for AD diagnosis and AD symptom counts (adj. p = 0.014 and p = 0.024, respectively) in AD GWAS signals in a large, independent genetic sample from the Collaborative Study on Genetics of Alcohol (COGA). In conclusion, our study identified putative gene network hubs coordinating mRNA and miRNA co-expression changes in the NAc of AD subjects, and our genetic (cis-eQTL) analysis provides novel insights into the etiological mechanisms of AD. PMID:26381263

High-resolution mapping of a fruit firmness-related quantitative trait locus in tomato reveals epistatic interactions associated with a complex combinatorial locus.

PubMed

Chapman, Natalie H; Bonnet, Julien; Grivet, Laurent; Lynn, James; Graham, Neil; Smith, Rebecca; Sun, Guiping; Walley, Peter G; Poole, Mervin; Causse, Mathilde; King, Graham J; Baxter, Charles; Seymour, Graham B

2012-08-01

Fruit firmness in tomato (Solanum lycopersicum) is determined by a number of factors including cell wall structure, turgor, and cuticle properties. Firmness is a complex polygenic trait involving the coregulation of many genes and has proved especially challenging to unravel. In this study, a quantitative trait locus (QTL) for fruit firmness was mapped to tomato chromosome 2 using the Zamir Solanum pennellii interspecific introgression lines (ILs) and fine-mapped in a population consisting of 7,500 F2 and F3 lines from IL 2-3 and IL 2-4. This firmness QTL contained five distinct subpeaks, Fir(s.p.)QTL2.1 to Fir(s.p.)QTL2.5, and an effect on a distal region of IL 2-4 that was nonoverlapping with IL 2-3. All these effects were located within an 8.6-Mb region. Using genetic markers, each subpeak within this combinatorial locus was mapped to a physical location within the genome, and an ethylene response factor (ERF) underlying Fir(s.p.)QTL2.2 and a region containing three pectin methylesterase (PME) genes underlying Fir(s.p.)QTL2.5 were nominated as QTL candidate genes. Statistical models used to explain the observed variability between lines indicated that these candidates and the nonoverlapping portion of IL 2-4 were sufficient to account for the majority of the fruit firmness effects. Quantitative reverse transcription-polymerase chain reaction was used to quantify the expression of each candidate gene. ERF showed increased expression associated with soft fruit texture in the mapping population. In contrast, PME expression was tightly linked with firm fruit texture. Analysis of a range of recombinant lines revealed evidence for an epistatic interaction that was associated with this combinatorial locus.

Studying the genetic basis of drought tolerance in sorghum by managed stress trials and adjustments for phenological and plant height differences.

PubMed

Sabadin, P K; Malosetti, M; Boer, M P; Tardin, F D; Santos, F G; Guimarães, C T; Gomide, R L; Andrade, C L T; Albuquerque, P E P; Caniato, F F; Mollinari, M; Margarido, G R A; Oliveira, B F; Schaffert, R E; Garcia, A A F; van Eeuwijk, F A; Magalhaes, J V

2012-05-01

Managed environments in the form of well watered and water stressed trials were performed to study the genetic basis of grain yield and stay green in sorghum with the objective of validating previously detected QTL. As variations in phenology and plant height may influence QTL detection for the target traits, QTL for flowering time and plant height were introduced as cofactors in QTL analyses for yield and stay green. All but one of the flowering time QTL were detected near yield and stay green QTL. Similar co-localization was observed for two plant height QTL. QTL analysis for yield, using flowering time/plant height cofactors, led to yield QTL on chromosomes 2, 3, 6, 8 and 10. For stay green, QTL on chromosomes 3, 4, 8 and 10 were not related to differences in flowering time/plant height. The physical positions for markers in QTL regions projected on the sorghum genome suggest that the previously detected plant height QTL, Sb-HT9-1, and Dw2, in addition to the maturity gene, Ma5, had a major confounding impact on the expression of yield and stay green QTL. Co-localization between an apparently novel stay green QTL and a yield QTL on chromosome 3 suggests there is potential for indirect selection based on stay green to improve drought tolerance in sorghum. Our QTL study was carried out with a moderately sized population and spanned a limited geographic range, but still the results strongly emphasize the necessity of corrections for phenology in QTL mapping for drought tolerance traits in sorghum.

Genetics of Inflammatory Bowel Diseases

PubMed Central

McGovern, Dermot; Kugathasan, Subra; Cho, Judy H.

2015-01-01

In this Review, we provide an update on genome-wide association studies (GWAS) in inflammatory bowel disease (IBD). In addition, we summarize progress in defining the functional consequences of associated alleles for coding and non-coding genetic variation. In the small minority of loci where major association signals correspond to non-synonymous variation, we summarize studies defining their functional effects and implications for therapeutic targeting. Importantly, the large majority of GWAS-associated loci involve non-coding variation, many of which modulate levels of gene expression. Recent expression quantitative trait loci (eQTL) studies have established that expression of the large majority of human genes is regulated by non-coding genetic variation. Significant advances in defining the epigenetic landscape have demonstrated that IBD GWAS signals are highly enriched within cell-specific active enhancer marks. Studies in European ancestry populations have dominated the landscape of IBD genetics studies, but increasingly, studies in Asian and African-American populations are being reported. Common variation accounts for only a modest fraction of the predicted heritability and the role of rare genetic variation of higher effects (i.e. odds ratios markedly deviating from one) is increasingly being identified through sequencing efforts. These sequencing studies have been particularly productive in very-early onset, more severe cases. A major challenge in IBD genetics will be harnessing the vast array of genetic discovery for clinical utility, through emerging precision medicine initiatives. We discuss the rapidly evolving area of direct to consumer genetic testing, as well as the current utility of clinical exome sequencing, especially in very early onset, severe IBD cases. We summarize recent progress in the pharmacogenetics of IBD with respect of partitioning patient responses to anti-TNF and thiopurine therapies. Highly collaborative studies across research centers and across subspecialties and disciplines will be required to fully realize the promise of genetic discovery in IBD. PMID:26255561

Accumulating evidence for a role of TCF7L2 variants in bipolar disorder with elevated body mass index.

PubMed

Cuellar-Barboza, Alfredo B; Winham, Stacey J; McElroy, Susan L; Geske, Jennifer R; Jenkins, Gregory D; Colby, Colin L; Prieto, Miguel L; Ryu, Euijung; Cunningham, Julie M; Frye, Mark A; Biernacka, Joanna M

2016-03-01

Bipolar disorder (BD) is a complex disease associated with various hereditary traits, including a higher body mass index (BMI). In a prior genome-wide association study, we found that BMI modified the association of rs12772424 - a common variant in the gene encoding transcription factor 7-like 2 (TCF7L2) - with risk for BD. TCF7L2 is a transcription factor in the canonical Wnt pathway, involved in multiple disorders, including diabetes, cancer and psychiatric conditions. Here, using an independent sample, we evaluated 26 TCF7L2 single nucleotide polymorphisms (SNPs) to explore further the association of BD with the TCF7L2-BMI interaction. Using a sample of 662 BD cases and 616 controls, we conducted SNP-level and gene-level tests to assess the evidence for an association between BD and the interaction of BMI and genetic variation in TCF7L2. We also explored the potential mechanism behind the detected associations using human brain expression quantitative trait loci (eQTL) analysis. The analysis provided independent evidence of an rs12772424-BMI interaction (p = 0.011). Furthermore, while overall there was no evidence for SNP marginal effects on BD, the TCF7L2-BMI interaction was significant at the gene level (p = 0.042), with seven of the 26 SNPs showing SNP-BMI interaction effects with p < 0.05. The strongest evidence of interaction was observed for rs7895307 (p = 0.006). TCF7L2 expression showed a significant enrichment of association with the expression of other genes in the Wnt canonical pathway. The current study provides further evidence suggesting that TCF7L2 involvement in BD risk may be regulated by BMI. Detailed, prospective assessment of BMI, comorbidity, and other possible contributing factors is necessary to explain fully the mechanisms underlying this association. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis.

PubMed

Ishikawa, Akira

2017-11-27

Large numbers of quantitative trait loci (QTL) affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs) for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants.

PubMed

Dadaev, Tokhir; Saunders, Edward J; Newcombe, Paul J; Anokian, Ezequiel; Leongamornlert, Daniel A; Brook, Mark N; Cieza-Borrella, Clara; Mijuskovic, Martina; Wakerell, Sarah; Olama, Ali Amin Al; Schumacher, Fredrick R; Berndt, Sonja I; Benlloch, Sara; Ahmed, Mahbubl; Goh, Chee; Sheng, Xin; Zhang, Zhuo; Muir, Kenneth; Govindasami, Koveela; Lophatananon, Artitaya; Stevens, Victoria L; Gapstur, Susan M; Carter, Brian D; Tangen, Catherine M; Goodman, Phyllis; Thompson, Ian M; Batra, Jyotsna; Chambers, Suzanne; Moya, Leire; Clements, Judith; Horvath, Lisa; Tilley, Wayne; Risbridger, Gail; Gronberg, Henrik; Aly, Markus; Nordström, Tobias; Pharoah, Paul; Pashayan, Nora; Schleutker, Johanna; Tammela, Teuvo L J; Sipeky, Csilla; Auvinen, Anssi; Albanes, Demetrius; Weinstein, Stephanie; Wolk, Alicja; Hakansson, Niclas; West, Catharine; Dunning, Alison M; Burnet, Neil; Mucci, Lorelei; Giovannucci, Edward; Andriole, Gerald; Cussenot, Olivier; Cancel-Tassin, Géraldine; Koutros, Stella; Freeman, Laura E Beane; Sorensen, Karina Dalsgaard; Orntoft, Torben Falck; Borre, Michael; Maehle, Lovise; Grindedal, Eli Marie; Neal, David E; Donovan, Jenny L; Hamdy, Freddie C; Martin, Richard M; Travis, Ruth C; Key, Tim J; Hamilton, Robert J; Fleshner, Neil E; Finelli, Antonio; Ingles, Sue Ann; Stern, Mariana C; Rosenstein, Barry; Kerns, Sarah; Ostrer, Harry; Lu, Yong-Jie; Zhang, Hong-Wei; Feng, Ninghan; Mao, Xueying; Guo, Xin; Wang, Guomin; Sun, Zan; Giles, Graham G; Southey, Melissa C; MacInnis, Robert J; FitzGerald, Liesel M; Kibel, Adam S; Drake, Bettina F; Vega, Ana; Gómez-Caamaño, Antonio; Fachal, Laura; Szulkin, Robert; Eklund, Martin; Kogevinas, Manolis; Llorca, Javier; Castaño-Vinyals, Gemma; Penney, Kathryn L; Stampfer, Meir; Park, Jong Y; Sellers, Thomas A; Lin, Hui-Yi; Stanford, Janet L; Cybulski, Cezary; Wokolorczyk, Dominika; Lubinski, Jan; Ostrander, Elaine A; Geybels, Milan S; Nordestgaard, Børge G; Nielsen, Sune F; Weisher, Maren; Bisbjerg, Rasmus; Røder, Martin Andreas; Iversen, Peter; Brenner, Hermann; Cuk, Katarina; Holleczek, Bernd; Maier, Christiane; Luedeke, Manuel; Schnoeller, Thomas; Kim, Jeri; Logothetis, Christopher J; John, Esther M; Teixeira, Manuel R; Paulo, Paula; Cardoso, Marta; Neuhausen, Susan L; Steele, Linda; Ding, Yuan Chun; De Ruyck, Kim; De Meerleer, Gert; Ost, Piet; Razack, Azad; Lim, Jasmine; Teo, Soo-Hwang; Lin, Daniel W; Newcomb, Lisa F; Lessel, Davor; Gamulin, Marija; Kulis, Tomislav; Kaneva, Radka; Usmani, Nawaid; Slavov, Chavdar; Mitev, Vanio; Parliament, Matthew; Singhal, Sandeep; Claessens, Frank; Joniau, Steven; Van den Broeck, Thomas; Larkin, Samantha; Townsend, Paul A; Aukim-Hastie, Claire; Gago-Dominguez, Manuela; Castelao, Jose Esteban; Martinez, Maria Elena; Roobol, Monique J; Jenster, Guido; van Schaik, Ron H N; Menegaux, Florence; Truong, Thérèse; Koudou, Yves Akoli; Xu, Jianfeng; Khaw, Kay-Tee; Cannon-Albright, Lisa; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej; Thibodeau, Stephen N; McDonnell, Shannon K; Schaid, Daniel J; Lindstrom, Sara; Turman, Constance; Ma, Jing; Hunter, David J; Riboli, Elio; Siddiq, Afshan; Canzian, Federico; Kolonel, Laurence N; Le Marchand, Loic; Hoover, Robert N; Machiela, Mitchell J; Kraft, Peter; Freedman, Matthew; Wiklund, Fredrik; Chanock, Stephen; Henderson, Brian E; Easton, Douglas F; Haiman, Christopher A; Eeles, Rosalind A; Conti, David V; Kote-Jarai, Zsofia

2018-06-11

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.

Genome-wide association studies of autoimmune vitiligo identify 23 new risk loci and highlight key pathways and regulatory variants

PubMed Central

Jin, Ying; Andersen, Genevieve; Yorgov, Daniel; Ferrara, Tracey M; Ben, Songtao; Brownson, Kelly M; Holland, Paulene J; Birlea, Stanca A; Siebert, Janet; Hartmann, Anke; Lienert, Anne; van Geel, Nanja; Lambert, Jo; Luiten, Rosalie M; Wolkerstorfer, Albert; van der Veen, JP Wietze; Bennett, Dorothy C; Taïeb, Alain; Ezzedine, Khaled; Kemp, E Helen; Gawkrodger, David J; Weetman, Anthony P; Kõks, Sulev; Prans, Ele; Kingo, Külli; Karelson, Maire; Wallace, Margaret R; McCormack, Wayne T; Overbeck, Andreas; Moretti, Silvia; Colucci, Roberta; Picardo, Mauro; Silverberg, Nanette B; Olsson, Mats; Valle, Yan; Korobko, Igor; Böhm, Markus; Lim, Henry W.; Hamzavi, Iltefat; Zhou, Li; Mi, Qing-Sheng; Fain, Pamela R.; Santorico, Stephanie A; Spritz, Richard A

2016-01-01

Vitiligo is an autoimmune disease in which depigmented skin results from destruction of melanocytes1, with epidemiologic association with other autoimmune diseases2. In previous linkage and genome-wide association studies (GWAS1, GWAS2), we identified 27 vitiligo susceptibility loci in patients of European (EUR) ancestry. We carried out a third GWAS (GWAS3) in EUR subjects, with augmented GWAS1 and GWAS2 controls, genome-wide imputation, and meta-analysis of all three GWAS, followed by an independent replication. The combined analyses, with 4,680 cases and 39,586 controls, identified 23 new loci and 7 suggestive loci, most encoding immune and apoptotic regulators, some also associated with other autoimmune diseases, as well as several melanocyte regulators. Bioinformatic analyses indicate a predominance of causal regulatory variation, some corresponding to eQTL at these loci. Together, the identified genes provide a framework for vitiligo genetic architecture and pathobiology, highlight relationships to other autoimmune diseases and melanoma, and offer potential targets for treatment. PMID:27723757

Association between fibroblast growth factor 21 and bone mineral density in adults.

PubMed

Hao, Ruo-Han; Gao, Jun-Ling; Li, Meng; Huang, Wei; Zhu, Dong-Li; Thynn, Hlaing Nwe; Dong, Shan-Shan; Guo, Yan

2018-02-01

Animal-based studies have reported a decrease in bone mass resulting from high level of fibroblast growth factor 21 (FGF21). However, the correlation between plasma FGF21 levels and bone mineral density (BMD) is paradoxical in previous human-based studies, and the associations between FGF21 gene polymorphisms and BMD haven't been reported yet. Therefore, here, we evaluated plasma FGF21 levels with sufficient study samples, and performed genetic association test to reveal the physiological and genetic role of FGF21 on BMD in adults. Plasma and genetic samples containing 168 and 569 Han Chinese subjects, respectively, were employed in this study. Fasting plasma FGF21 levels were determined using enzyme-linked immunosorbent assay (ELISA). Regional BMD values were measured by dual energy X-ray absorptiometry (DXA). Five variants of FGF21 gene were successfully genotyped. Physiological association suggested that plasma FGF21 levels were inversely correlated with BMD in femoral neck (Neck-BMD: P = 0.039) and Ward's triangle (Ward's-BMD: P = 0.002) of hip region. A FGF21 gene variant, rs490942, was significantly associated with the increase of Ward's-BMD in total (P = 0.027) and female (P = 0.016) cohorts, as well as Neck-BMD in female cohort (P = 7.45 × 10 -3 ). Meanwhile, eQTL results indicated that this SNP was related to the decreased level of FGF21 gene expression. Taking together from both physiological and genetic levels, we suggest that FGF21 is inversely associated with regional BMD. And we haven't observed sex-specific effect in this study.

LRBA Gene Polymorphisms and Risk of Coal Workers’ Pneumoconiosis: A Case–Control Study from China

PubMed Central

Liu, Yi; Yang, Jingjin; Wu, Qiuyun; Han, Ruhui; Yan, Weiwen; Yuan, Jiali; Ji, Xiaoming; Li, Yan; Yao, Wenxi; Ni, Chunhui

2017-01-01

The lipopolysaccharide (LPS)-responsive beige-like anchor protein (LRBA) is a member of the WDL-BEACH-WD (WBW) gene family. Defects in this gene are associated with the disordered autoimmunity in various diseases, including pulmonary fibrosis. In this study, we investigated the association between the functional polymorphisms in LRBA and risk of coal workers’ pneumoconiosis (CWP) in a Chinese population. Three potentially functional polymorphisms (rs2290846, rs3749574, and rs1782360) in LRBA were genotyped and analyzed in a case–control study, including 703 CWP cases and 705 controls. Genotyping was performed by the ABI 7900HT Real Time PCR system. Our results suggested that genotype rs2290846 AA was significantly associated with decreased risk of CWP (Adjusted OR = 0.61, 95% CI = 0.41–0.92), and the recessive model also supported the protective role of the genotype (Adjusted OR = 0.60, 95% CI = 0.40–0.89). Further, the polymorphism of rs2290846 decreased the CWP risk among cases over 27 years of dust exposure (adjusted OR = 0.51, 95% CI = 0.28–0.94) and non-smokers (adjusted OR = 0.58, 95% CI = 0.34–1.00). A potential role of rs2290846 AA has been proposed by expression quantitative trait loci (eQTL) and The Cancer Genome Atlas (TCGA). The present results suggest that LRBA SNPs are associated with CWP susceptibility in a Chinese population. Further studies focused on detailed mechanism or larger cohorts are warranted to validate our findings. PMID:28953250

Lessons from ten years of genome-wide association studies of asthma

PubMed Central

Vicente, Cristina T; Revez, Joana A; Ferreira, Manuel A R

2017-01-01

Twenty-five genome-wide association studies (GWAS) of asthma were published between 2007 and 2016, the largest with a sample size of 157242 individuals. Across these studies, 39 genetic variants in low linkage disequilibrium (LD) with each other were reported to associate with disease risk at a significance threshold of P<5 × 10−8, including 31 in populations of European ancestry. Results from analyses of the UK Biobank data (n=380 503) indicate that at least 28 of the 31 associations reported in Europeans represent true-positive findings, collectively explaining 2.5% of the variation in disease liability (median of 0.06% per variant). We identified 49 transcripts as likely target genes of the published asthma risk variants, mostly based on LD with expression quantitative trait loci (eQTL). Of these genes, 16 were previously implicated in disease pathophysiology by functional studies, including TSLP, TNFSF4, ADORA1, CHIT1 and USF1. In contrast, at present, there is limited or no functional evidence directly implicating the remaining 33 likely target genes in asthma pathophysiology. Some of these genes have a known function that is relevant to allergic disease, including F11R, CD247, PGAP3, AAGAB, CAMK4 and PEX14, and so could be prioritized for functional follow-up. We conclude by highlighting three areas of research that are essential to help translate GWAS findings into clinical research or practice, namely validation of target gene predictions, understanding target gene function and their role in disease pathophysiology and genomics-guided prioritization of targets for drug development. PMID:29333270

QTL and gene expression analyses identify genes affecting carcass weight and marbling on BTA14 in Hanwoo (Korean Cattle).

PubMed

Lee, Seung Hwan; van der Werf, J H J; Kim, Nam Kuk; Lee, Sang Hong; Gondro, C; Park, Eung Woo; Oh, Sung Jong; Gibson, J P; Thompson, J M

2011-10-01

Causal mutations affecting quantitative trait variation can be good targets for marker-assisted selection for carcass traits in beef cattle. In this study, linkage and linkage disequilibrium analysis (LDLA) for four carcass traits was undertaken using 19 markers on bovine chromosome 14. The LDLA analysis detected quantitative trait loci (QTL) for carcass weight (CWT) and eye muscle area (EMA) at the same position at around 50 cM and surrounded by the markers FABP4SNP2774C>G and FABP4_μsat3237. The QTL for marbling (MAR) was identified at the midpoint of markers BMS4513 and RM137 in a 3.5-cM marker interval. The most likely position for a second QTL for CWT was found at the midpoint of tenth marker bracket (FABP4SNP2774C>G and FABP4_μsat3237). For this marker bracket, the total number of haplotypes was 34 with a most common frequency of 0.118. Effects of haplotypes on CWT varied from a -5-kg deviation for haplotype 6 to +8 kg for haplotype 23. To determine which genes contribute to the QTL effect, gene expression analysis was performed in muscle for a wide range of phenotypes. The results demonstrate that two genes, LOC781182 (p = 0.002) and TRPS1 (p = 0.006) were upregulated with increasing CWT and EMA, whereas only LOC614744 (p = 0.04) has a significant effect on intramuscular fat (IMF) content. Two genetic markers detected in FABP4 were the most likely QTL position in this QTL study, but FABP4 did not show a significant effect on both traits (CWT and EMA) in gene expression analysis. We conclude that three genes could be potential causal genes affecting carcass traits CWT, EMA, and IMF in Hanwoo.

Meta-analysis of Polyploid Cotton QTL Shows Unequal Contributions of Subgenomes to a Complex Network of Genes and Gene Clusters Implicated in Lint Fiber Development

PubMed Central

Rong, Junkang; Feltus, F. Alex; Waghmare, Vijay N.; Pierce, Gary J.; Chee, Peng W.; Draye, Xavier; Saranga, Yehoshua; Wright, Robert J.; Wilkins, Thea A.; May, O. Lloyd; Smith, C. Wayne; Gannaway, John R.; Wendel, Jonathan F.; Paterson, Andrew H.

2007-01-01

QTL mapping experiments yield heterogeneous results due to the use of different genotypes, environments, and sampling variation. Compilation of QTL mapping results yields a more complete picture of the genetic control of a trait and reveals patterns in organization of trait variation. A total of 432 QTL mapped in one diploid and 10 tetraploid interspecific cotton populations were aligned using a reference map and depicted in a CMap resource. Early demonstrations that genes from the non-fiber-producing diploid ancestor contribute to tetraploid lint fiber genetics gain further support from multiple populations and environments and advanced-generation studies detecting QTL of small phenotypic effect. Both tetraploid subgenomes contribute QTL at largely non-homeologous locations, suggesting divergent selection acting on many corresponding genes before and/or after polyploid formation. QTL correspondence across studies was only modest, suggesting that additional QTL for the target traits remain to be discovered. Crosses between closely-related genotypes differing by single-gene mutants yield profoundly different QTL landscapes, suggesting that fiber variation involves a complex network of interacting genes. Members of the lint fiber development network appear clustered, with cluster members showing heterogeneous phenotypic effects. Meta-analysis linked to synteny-based and expression-based information provides clues about specific genes and families involved in QTL networks. PMID:17565937

Meta-analysis of polyploid cotton QTL shows unequal contributions of subgenomes to a complex network of genes and gene clusters implicated in lint fiber development.

PubMed

Rong, Junkang; Feltus, F Alex; Waghmare, Vijay N; Pierce, Gary J; Chee, Peng W; Draye, Xavier; Saranga, Yehoshua; Wright, Robert J; Wilkins, Thea A; May, O Lloyd; Smith, C Wayne; Gannaway, John R; Wendel, Jonathan F; Paterson, Andrew H

2007-08-01

QTL mapping experiments yield heterogeneous results due to the use of different genotypes, environments, and sampling variation. Compilation of QTL mapping results yields a more complete picture of the genetic control of a trait and reveals patterns in organization of trait variation. A total of 432 QTL mapped in one diploid and 10 tetraploid interspecific cotton populations were aligned using a reference map and depicted in a CMap resource. Early demonstrations that genes from the non-fiber-producing diploid ancestor contribute to tetraploid lint fiber genetics gain further support from multiple populations and environments and advanced-generation studies detecting QTL of small phenotypic effect. Both tetraploid subgenomes contribute QTL at largely non-homeologous locations, suggesting divergent selection acting on many corresponding genes before and/or after polyploid formation. QTL correspondence across studies was only modest, suggesting that additional QTL for the target traits remain to be discovered. Crosses between closely-related genotypes differing by single-gene mutants yield profoundly different QTL landscapes, suggesting that fiber variation involves a complex network of interacting genes. Members of the lint fiber development network appear clustered, with cluster members showing heterogeneous phenotypic effects. Meta-analysis linked to synteny-based and expression-based information provides clues about specific genes and families involved in QTL networks.

QTL Mapping for Resistance to Iridovirus in Asian Seabass Using Genotyping-by-Sequencing.

PubMed

Wang, Le; Bai, Bin; Huang, Shuqing; Liu, Peng; Wan, Zi Yi; Ye, Baoqing; Wu, Jinlu; Yue, Gen Hua

2017-10-01

Identifying quantitative trait loci (QTL) for viral disease resistance is of particular importance in selective breeding programs of fish species. Genetic markers linked to QTL can be useful in marker-assisted selection (MAS) for elites resistant to specific pathogens. Here, we conducted a genome scan for QTL associated with Singapore grouper iridovirus (SGIV) resistance in an Asian seabass (Lates calcarifer) family, using a high-density linkage map generated with genotyping-by-sequencing. One genome-wide significant and three suggestive QTL were detected at LG21, LG6, LG13, and LG15, respectively. The phenotypic variation explained (PVE) by the four QTL ranged from 7.5 to 15.6%. The position of the most significant QTL at LG21 was located between 31.88 and 36.81 cM. The SNP marker (SNP130416) nearest to the peak of this QTL was significantly associated with SGIV resistance in an unrelated multifamily population. One candidate gene, MECOM, close to the peak of this QTL region, was predicted. Evidence of alternative splicing was observed for MECOM and one specific category of splicing variants was differentially expressed at 5 days post-SGIV infection. The QTL detected in this study are valuable resources and can be used in the selective breeding programs of Asian seabass with regard to resistance to SGIV.

Meta-QTL for resistance to white mold in common bean

PubMed Central

Vasconcellos, Renato C. C.; Oraguzie, O. Blessing; Soler, Alvaro; Arkwazee, Haidar; Myers, James R.; Ferreira, Juan J.; Song, Qijian; McClean, Phil; Miklas, Phillip N.

2017-01-01

White mold, caused by the fungus Sclerotinia sclerotiorum (Lib.) de Bary, is a major disease that limits common bean production and quality worldwide. The host-pathogen interaction is complex, with partial resistance in the host inherited as a quantitative trait with low to moderate heritability. Our objective was to identify meta-QTL conditioning partial resistance to white mold from individual QTL identified across multiple populations and environments. The physical positions for 37 individual QTL were identified across 14 recombinant inbred bi-parental populations (six new, three re-genotyped, and five from the literature). A meta-QTL analysis of the 37 QTL was conducted using the genetic linkage map of Stampede x Red Hawk population as the reference. The 37 QTL condensed into 17 named loci (12 previously named and five new) of which nine were defined as meta-QTL WM1.1, WM2.2, WM3.1, WM5.4, WM6.2, WM7.1, WM7.4, WM7.5, and WM8.3. The nine meta-QTL had confidence intervals ranging from 0.65 to 9.41 Mb. Candidate genes shown to express under S. sclerotiorum infection in other studies, including cell wall receptor kinase, COI1, ethylene responsive transcription factor, peroxidase, and MYB transcription factor, were found within the confidence interval for five of the meta-QTL. The nine meta-QTL are recommended as potential targets for MAS for partial resistance to white mold in common bean. PMID:28199342

Phenotype and Tissue Expression as a Function of Genetic Risk in Polycystic Ovary Syndrome

PubMed Central

Pau, Cindy T.; Mosbruger, Tim; Saxena, Richa; Welt, Corrine K.

2017-01-01

Genome-wide association studies and replication analyses have identified (n = 5) or replicated (n = 10) DNA variants associated with risk for polycystic ovary syndrome (PCOS) in European women. However, the causal gene and underlying mechanism for PCOS risk at these loci have not been determined. We hypothesized that analysis of phenotype, gene expression and metformin response as a function of genotype would identify candidate genes and pathways that could provide insight into the underlying mechanism for risk at these loci. To test the hypothesis, subjects with PCOS (n = 427) diagnosed according to the NIH criteria (< 9 menses per year and clinical or biochemical hyperandrogenism) and controls (n = 407) with extensive phenotyping were studied. A subset of subjects (n = 38) underwent a subcutaneous adipose tissue biopsy for RNA sequencing and were subsequently treated with metformin for 12 weeks with standardized outcomes measured. Data were analyzed according to genotype at PCOS risk loci and adjusted for the false discovery rate. A gene variant in the THADA locus was associated with response to metformin and metformin was a predicted upstream regulator at the same locus. Genotype at the FSHB locus was associated with LH levels. Genes near the PCOS risk loci demonstrated differences in expression as a function of genotype in adipose including BLK and NEIL2 (GATA4 locus), GLIPR1 and PHLDA1 (KRR1 locus). Based on the phenotypes, expression quantitative trait loci (eQTL), and upstream regulatory and pathway analyses we hypothesize that there are PCOS subtypes. FSHB, FHSR and LHR loci may influence PCOS risk based on their relationship to gonadotropin levels. The THADA, GATA4, ERBB4, SUMO1P1, KRR1 and RAB5B loci appear to confer risk through metabolic mechanisms. The IRF1, SUMO1P1 and KRR1 loci may confer PCOS risk in development. The TOX3 and GATA4 loci appear to be involved in inflammation and its consequences. The data suggest potential PCOS subtypes and point to the need for additional studies to replicate these findings and identify personalized diagnosis and treatment options for PCOS. PMID:28068351

Genetic Mapping of Quantitative Trait Loci Controlling Growth and Wood Quality Traits in Eucalyptus Grandis Using a Maternal Half-Sib Family and Rapd Markers

PubMed Central

Grattapaglia, D.; Bertolucci, FLG.; Penchel, R.; Sederoff, R. R.

1996-01-01

Quantitative trait loci (QTL) mapping of forest productivity traits was performed using an open pollinated half-sib family of Eucalyptus grandis. For volume growth, a sequential QTL mapping approach was applied using bulk segregant analysis (BSA), selective genotyping (SG) and cosegregation analysis (CSA). Despite the low heritability of this trait and the heterogeneous genetic background employed for mapping. BSA detected one putative QTL and SG two out of the three later found by CSA. The three putative QTL for volume growth were found to control 13.7% of the phenotypic variation, corresponding to an estimated 43.7% of the genetic variation. For wood specific gravity five QTL were identified controlling 24.7% of the phenotypic variation corresponding to 49% of the genetic variation. Overlapping QTL for CBH, WSG and percentage dry weight of bark were observed. A significant case of digenic epistasis was found, involving unlinked QTL for volume. Our results demonstrate the applicability of the within half-sib design for QTL mapping in forest trees and indicate the existence of major genes involved in the expression of economically important traits related to forest productivity in Eucalyptus grandis. These findings have important implications for marker-assisted tree breeding. PMID:8913761

Human brain arousal in the resting state: a genome-wide association study.

PubMed

Jawinski, Philippe; Kirsten, Holger; Sander, Christian; Spada, Janek; Ulke, Christine; Huang, Jue; Burkhardt, Ralph; Scholz, Markus; Hensch, Tilman; Hegerl, Ulrich

2018-04-27

Arousal affects cognition, emotion, and behavior and has been implicated in the etiology of psychiatric disorders. Although environmental conditions substantially contribute to the level of arousal, stable interindividual characteristics are well-established and a genetic basis has been suggested. Here we investigated the molecular genetics of brain arousal in the resting state by conducting a genome-wide association study (GWAS). We selected N = 1877 participants from the population-based LIFE-Adult cohort. Participants underwent a 20-min eyes-closed resting state EEG, which was analyzed using the computerized VIGALL 2.1 (Vigilance Algorithm Leipzig). At the SNP-level, GWAS analyses revealed no genome-wide significant locus (p < 5E-8), although seven loci were suggestive (p < 1E-6). The strongest hit was an expression quantitative trait locus (eQTL) of TMEM159 (lead-SNP: rs79472635, p = 5.49E-8). Importantly, at the gene-level, GWAS analyses revealed significant evidence for TMEM159 (p = 0.013, Bonferroni-corrected). By mapping our SNPs to the GWAS results from the Psychiatric Genomics Consortium, we found that all corresponding markers of TMEM159 showed nominally significant associations with Major Depressive Disorder (MDD; 0.006 ≤ p ≤ 0.011). More specifically, variants associated with high arousal levels have previously been linked to an increased risk for MDD. In line with this, the MetaXcan database suggests increased expression levels of TMEM159 in MDD, as well as Autism Spectrum Disorder, and Alzheimer's Disease. Furthermore, our pathway analyses provided evidence for a role of sodium/calcium exchangers in resting state arousal. In conclusion, the present GWAS identifies TMEM159 as a novel candidate gene which may modulate the risk for psychiatric disorders through arousal mechanisms. Our results also encourage the elaboration of the previously reported interrelations between ion-channel modulators, sleep-wake behavior, and psychiatric disorders.

A genome-wide association study for somatic cell score using the Illumina high-density bovine beadchip identifies several novel QTL potentially related to mastitis susceptibility

PubMed Central

Meredith, Brian K.; Berry, Donagh P.; Kearney, Francis; Finlay, Emma K.; Fahey, Alan G.; Bradley, Daniel G.; Lynn, David J.

2013-01-01

Mastitis is an inflammation-driven disease of the bovine mammary gland that occurs in response to physical damage or infection and is one of the most costly production-related diseases in the dairy industry worldwide. We performed a genome-wide association study (GWAS) to identify genetic loci associated with somatic cell score (SCS), an indicator trait of mammary gland inflammation. A total of 702 Holstein-Friesian bulls were genotyped for 777,962 single nucleotide polymorphisms (SNPs) and associated with SCS phenotypes. The SCS phenotypes were expressed as daughter yield deviations (DYD) based on a large number of progeny performance records. A total of 138 SNPs on 15 different chromosomes reached genome-wide significance (corrected p-value ≤ 0.05) for association with SCS (after correction for multiple testing). We defined 28 distinct QTL regions and a number of candidate genes located in these QTL regions were identified. The most significant association (p-value = 1.70 × 10−7) was observed on chromosome 6. This QTL had no known genes annotated within it, however, the Ensembl Genome Browser predicted the presence of a small non-coding RNA (a Y RNA gene) in this genomic region. This Y RNA gene was 99% identical to human RNY4. Y RNAs are a rare type of non-coding RNA that were originally discovered due to their association with the autoimmune disease, systemic lupus erythematosus. Examining small-RNA sequencing (RNAseq) data being generated by us in multiple different mastitis-pathogen challenged cell-types has revealed that this Y RNA is expressed (but not differentially expressed) in these cells. Other QTL regions identified in this study also encoded strong candidate genes for mastitis susceptibility. A QTL region on chromosome 13, for example, was found to contain a cluster of β-defensin genes, a gene family with known roles in innate immunity. Due to the increased SNP density, this study also refined the boundaries for several known QTL for SCS and mastitis. PMID:24223582

Host genetic variation influences gene expression response to rhinovirus infection.

PubMed

Çalışkan, Minal; Baker, Samuel W; Gilad, Yoav; Ober, Carole

2015-04-01

Rhinovirus (RV) is the most prevalent human respiratory virus and is responsible for at least half of all common colds. RV infections may result in a broad spectrum of effects that range from asymptomatic infections to severe lower respiratory illnesses. The basis for inter-individual variation in the response to RV infection is not well understood. In this study, we explored whether host genetic variation is associated with variation in gene expression response to RV infections between individuals. To do so, we obtained genome-wide genotype and gene expression data in uninfected and RV-infected peripheral blood mononuclear cells (PBMCs) from 98 individuals. We mapped local and distant genetic variation that is associated with inter-individual differences in gene expression levels (eQTLs) in both uninfected and RV-infected cells. We focused specifically on response eQTLs (reQTLs), namely, genetic associations with inter-individual variation in gene expression response to RV infection. We identified local reQTLs for 38 genes, including genes with known functions in viral response (UBA7, OAS1, IRF5) and genes that have been associated with immune and RV-related diseases (e.g., ITGA2, MSR1, GSTM3). The putative regulatory regions of genes with reQTLs were enriched for binding sites of virus-activated STAT2, highlighting the role of condition-specific transcription factors in genotype-by-environment interactions. Overall, we suggest that the 38 loci associated with inter-individual variation in gene expression response to RV-infection represent promising candidates for affecting immune and RV-related respiratory diseases.

Tissue-specific impact of FADS cluster variants on FADS1 and FADS2 gene expression.

PubMed

Reynolds, Lindsay M; Howard, Timothy D; Ruczinski, Ingo; Kanchan, Kanika; Seeds, Michael C; Mathias, Rasika A; Chilton, Floyd H

2018-01-01

Omega-6 (n-6) and omega-3 (n-3) long (≥ 20 carbon) chain polyunsaturated fatty acids (LC-PUFAs) play a critical role in human health and disease. Biosynthesis of LC-PUFAs from dietary 18 carbon PUFAs in tissues such as the liver is highly associated with genetic variation within the fatty acid desaturase (FADS) gene cluster, containing FADS1 and FADS2 that encode the rate-limiting desaturation enzymes in the LC-PUFA biosynthesis pathway. However, the molecular mechanisms by which FADS genetic variants affect LC-PUFA biosynthesis, and in which tissues, are unclear. The current study examined associations between common single nucleotide polymorphisms (SNPs) within the FADS gene cluster and FADS1 and FADS2 gene expression in 44 different human tissues (sample sizes ranging 70-361) from the Genotype-Tissue Expression (GTEx) Project. FADS1 and FADS2 expression were detected in all 44 tissues. Significant cis-eQTLs (within 1 megabase of each gene, False Discovery Rate, FDR<0.05, as defined by GTEx) were identified in 12 tissues for FADS1 gene expression and 23 tissues for FADS2 gene expression. Six tissues had significant (FDR< 0.05) eQTLs associated with both FADS1 and FADS2 (including artery, esophagus, heart, muscle, nerve, and thyroid). Interestingly, the identified eQTLs were consistently found to be associated in opposite directions for FADS1 and FADS2 expression. Taken together, findings from this study suggest common SNPs within the FADS gene cluster impact the transcription of FADS1 and FADS2 in numerous tissues and raise important questions about how the inverse expression of these two genes impact intermediate molecular (such a LC-PUFA and LC-PUFA-containing glycerolipid levels) and ultimately clinical phenotypes associated with inflammatory diseases and brain health.

Validation of mega-environment universal and specific QTL associated with seed yield and agronomic traits in soybeans.

PubMed

Palomeque, Laura; Liu, Li-Jun; Li, Wenbin; Hedges, Bradley R; Cober, Elroy R; Smid, Mathew P; Lukens, Lewis; Rajcan, Istvan

2010-03-01

The value of quantitative trait loci (QTL) is dependent on the strength of association with the traits of interest, allelic diversity at the QTL and the effect of the genetic background on the expression of the QTL. A number of recent studies have identified QTL associated with traits of interest that appear to be independent of the environment but dependent on the genetic background in which they are found. Therefore, the objective of this study was to validate universal and/or mega-environment-specific seed yield QTL that have been previously reported in an independent recombinant inbred line (RIL) population derived from the cross between an elite Chinese and Canadian parent. The population was evaluated at two field environments in China and in five environments in Canada in 2005 and 2006. Of the seven markers linked to seed yield QTL reported by our group in a previous study, four were polymorphic between the two parents. No association between seed yield and QTL was observed. The result could imply that seed yield QTL were either not stable in this particular genetic background or harboured different alleles than the ones in the original mapping population. QTL(U) Satt162 was associated with several agronomic traits of which lodging was validated. Both the non-adapted and adapted parent contributed favourable alleles to the progeny. Therefore, plant introductions have been validated as a source of favourable alleles that could increase the genetic variability of the soybean germplasm pool and lead to further improvements in seed yield and other agronomic traits.

Transcriptome profiling of two maize inbreds with distinct responses to Gibberella ear rot disease to identify candidate resistance genes.

PubMed

Kebede, Aida Z; Johnston, Anne; Schneiderman, Danielle; Bosnich, Whynn; Harris, Linda J

2018-02-09

Gibberella ear rot (GER) is one of the most economically important fungal diseases of maize in the temperate zone due to moldy grain contaminated with health threatening mycotoxins. To develop resistant genotypes and control the disease, understanding the host-pathogen interaction is essential. RNA-Seq-derived transcriptome profiles of fungal- and mock-inoculated developing kernel tissues of two maize inbred lines were used to identify differentially expressed transcripts and propose candidate genes mapping within GER resistance quantitative trait loci (QTL). A total of 1255 transcripts were significantly (P ≤ 0.05) up regulated due to fungal infection in both susceptible and resistant inbreds. A greater number of transcripts were up regulated in the former (1174) than the latter (497) and increased as the infection progressed from 1 to 2 days after inoculation. Focusing on differentially expressed genes located within QTL regions for GER resistance, we identified 81 genes involved in membrane transport, hormone regulation, cell wall modification, cell detoxification, and biosynthesis of pathogenesis related proteins and phytoalexins as candidate genes contributing to resistance. Applying droplet digital PCR, we validated the expression profiles of a subset of these candidate genes from QTL regions contributed by the resistant inbred on chromosomes 1, 2 and 9. By screening global gene expression profiles for differentially expressed genes mapping within resistance QTL regions, we have identified candidate genes for gibberella ear rot resistance on several maize chromosomes which could potentially lead to a better understanding of Fusarium resistance mechanisms.

Gene Expression Network Reconstruction by Convex Feature Selection when Incorporating Genetic Perturbations

PubMed Central

Logsdon, Benjamin A.; Mezey, Jason

2010-01-01

Cellular gene expression measurements contain regulatory information that can be used to discover novel network relationships. Here, we present a new algorithm for network reconstruction powered by the adaptive lasso, a theoretically and empirically well-behaved method for selecting the regulatory features of a network. Any algorithms designed for network discovery that make use of directed probabilistic graphs require perturbations, produced by either experiments or naturally occurring genetic variation, to successfully infer unique regulatory relationships from gene expression data. Our approach makes use of appropriately selected cis-expression Quantitative Trait Loci (cis-eQTL), which provide a sufficient set of independent perturbations for maximum network resolution. We compare the performance of our network reconstruction algorithm to four other approaches: the PC-algorithm, QTLnet, the QDG algorithm, and the NEO algorithm, all of which have been used to reconstruct directed networks among phenotypes leveraging QTL. We show that the adaptive lasso can outperform these algorithms for networks of ten genes and ten cis-eQTL, and is competitive with the QDG algorithm for networks with thirty genes and thirty cis-eQTL, with rich topologies and hundreds of samples. Using this novel approach, we identify unique sets of directed relationships in Saccharomyces cerevisiae when analyzing genome-wide gene expression data for an intercross between a wild strain and a lab strain. We recover novel putative network relationships between a tyrosine biosynthesis gene (TYR1), and genes involved in endocytosis (RCY1), the spindle checkpoint (BUB2), sulfonate catabolism (JLP1), and cell-cell communication (PRM7). Our algorithm provides a synthesis of feature selection methods and graphical model theory that has the potential to reveal new directed regulatory relationships from the analysis of population level genetic and gene expression data. PMID:21152011

A computational biology approach of a genome-wide screen connected miRNAs to obesity and type 2 diabetes.

PubMed

Gottmann, Pascal; Ouni, Meriem; Saussenthaler, Sophie; Roos, Julian; Stirm, Laura; Jähnert, Markus; Kamitz, Anne; Hallahan, Nicole; Jonas, Wenke; Fritsche, Andreas; Häring, Hans-Ulrich; Staiger, Harald; Blüher, Matthias; Fischer-Posovszky, Pamela; Vogel, Heike; Schürmann, Annette

2018-05-01

Obesity and type 2 diabetes (T2D) arise from the interplay between genetic, epigenetic, and environmental factors. The aim of this study was to combine bioinformatics and functional studies to identify miRNAs that contribute to obesity and T2D. A computational framework (miR-QTL-Scan) was applied by combining QTL, miRNA prediction, and transcriptomics in order to enhance the power for the discovery of miRNAs as regulative elements. Expression of several miRNAs was analyzed in human adipose tissue and blood cells and miR-31 was manipulated in a human fat cell line. In 17 partially overlapping QTL for obesity and T2D 170 miRNAs were identified. Four miRNAs (miR-15b, miR-30b, miR-31, miR-744) were recognized in gWAT (gonadal white adipose tissue) and six (miR-491, miR-455, miR-423-5p, miR-132-3p, miR-365-3p, miR-30b) in BAT (brown adipose tissue). To provide direct functional evidence for the achievement of the miR-QTL-Scan, miR-31 located in the obesity QTL Nob6 was experimentally analyzed. Its expression was higher in gWAT of obese and diabetic mice and humans than of lean controls. Accordingly, 10 potential target genes involved in insulin signaling and adipogenesis were suppressed. Manipulation of miR-31 in human SGBS adipocytes affected the expression of GLUT4, PPARγ, IRS1, and ACACA. In human peripheral blood mononuclear cells (PBMC) miR-15b levels were correlated to baseline blood glucose concentrations and might be an indicator for diabetes. Thus, miR-QTL-Scan allowed the identification of novel miRNAs relevant for obesity and T2D. Copyright © 2018 The Authors. Published by Elsevier GmbH.. All rights reserved.

Genetic susceptibility to bone and soft tissue sarcomas: a field synopsis and meta-analysis.

PubMed

Benna, Clara; Simioni, Andrea; Pasquali, Sandro; De Boni, Davide; Rajendran, Senthilkumar; Spiro, Giovanna; Colombo, Chiara; Virgone, Calogero; DuBois, Steven G; Gronchi, Alessandro; Rossi, Carlo Riccardo; Mocellin, Simone

2018-04-06

The genetic architecture of bone and soft tissue sarcomas susceptibility is yet to be elucidated. We aimed to comprehensively collect and meta-analyze the current knowledge on genetic susceptibility in these rare tumors. We conducted a systematic review and meta-analysis of the evidence on the association between DNA variation and risk of developing sarcomas through searching PubMed, The Cochrane Library, Scopus and Web of Science databases. To evaluate result credibility, summary evidence was graded according to the Venice criteria and false positive report probability (FPRP) was calculated to further validate result noteworthiness. Integrative analysis of genetic and eQTL (expression quantitative trait locus) data was coupled with network and pathway analysis to explore the hypothesis that specific cell functions are involved in sarcoma predisposition. We retrieved 90 eligible studies comprising 47,796 subjects (cases: 14,358, 30%) and investigating 1,126 polymorphisms involving 320 distinct genes. Meta-analysis identified 55 single nucleotide polymorphisms (SNPs) significantly associated with disease risk with a high (N=9), moderate (N=38) and low (N=8) level of evidence, findings being classified as noteworthy basically only when the level of evidence was high. The estimated joint population attributable risk for three independent SNPs (rs11599754 of ZNF365/EGR2 , rs231775 of CTLA4 , and rs454006 of PRKCG ) was 37.2%. We also identified 53 SNPs significantly associated with sarcoma risk based on single studies.Pathway analysis enabled us to propose that sarcoma predisposition might be linked especially to germline variation of genes whose products are involved in the function of the DNA repair machinery. We built the first knowledgebase on the evidence linking DNA variation to sarcomas susceptibility, which can be used to generate mechanistic hypotheses and inform future studies in this field of oncology.

The landscape of inherited and de novo copy number variants in a plasmodium falciparum genetic cross

PubMed Central

2011-01-01

Background Copy number is a major source of genome variation with important evolutionary implications. Consequently, it is essential to determine copy number variant (CNV) behavior, distributions and frequencies across genomes to understand their origins in both evolutionary and generational time frames. We use comparative genomic hybridization (CGH) microarray and the resolution provided by a segregating population of cloned progeny lines of the malaria parasite, Plasmodium falciparum, to identify and analyze the inheritance of 170 genome-wide CNVs. Results We describe CNVs in progeny clones derived from both Mendelian (i.e. inherited) and non-Mendelian mechanisms. Forty-five CNVs were present in the parent lines and segregated in the progeny population. Furthermore, extensive variation that did not conform to strict Mendelian inheritance patterns was observed. 124 CNVs were called in one or more progeny but in neither parent: we observed CNVs in more than one progeny clone that were not identified in either parent, located more frequently in the telomeric-subtelomeric regions of chromosomes and singleton de novo CNVs distributed evenly throughout the genome. Linkage analysis of CNVs revealed dynamic copy number fluctuations and suggested mechanisms that could have generated them. Five of 12 previously identified expression quantitative trait loci (eQTL) hotspots coincide with CNVs, demonstrating the potential for broad influence of CNV on the transcriptional program and phenotypic variation. Conclusions CNVs are a significant source of segregating and de novo genome variation involving hundreds of genes. Examination of progeny genome segments provides a framework to assess the extent and possible origins of CNVs. This segregating genetic system reveals the breadth, distribution and dynamics of CNVs in a surprisingly plastic parasite genome, providing a new perspective on the sources of diversity in parasite populations. PMID:21936954

Informed genome-wide association analysis with family history as a secondary phenotype identifies novel loci of lung cancer.

PubMed

Poirier, Julia G; Brennan, Paul; McKay, James D; Spitz, Margaret R; Bickeböller, Heike; Risch, Angela; Liu, Geoffrey; Le Marchand, Loic; Tworoger, Shelley; McLaughlin, John; Rosenberger, Albert; Heinrich, Joachim; Brüske, Irene; Muley, Thomas; Henderson, Brian E; Wilkens, Lynne R; Zong, Xuchen; Li, Yafang; Hao, Ke; Timens, Wim; Bossé, Yohan; Sin, Don D; Obeidat, Ma'en; Amos, Christopher I; Hung, Rayjean J

2015-03-01

Lung cancer is the leading cause of cancer death worldwide. Although several genetic variants associated with lung cancer have been identified in the past, stringent selection criteria of genome-wide association studies (GWAS) can lead to missed variants. The objective of this study was to uncover missed variants by using the known association between lung cancer and first-degree family history of lung cancer to enrich the variant prioritization for lung cancer susceptibility regions. In this two-stage GWAS study, we first selected a list of variants associated with both lung cancer and family history of lung cancer in four GWAS (3,953 cases, 4,730 controls), then replicated our findings for 30 variants in a meta-analysis of four additional studies (7,510 cases, 7,476 controls). The top ranked genetic variant rs12415204 in chr10q23.33 encoding FFAR4 in the Discovery set was validated in the Replication set with an overall OR of 1.09 (95% CI=1.04, 1.14, P=1.63×10(-4)). When combining the two stages of the study, the strongest association was found in rs1158970 at Ch4p15.2 encoding KCNIP4 with an OR of 0.89 (95% CI=0.85, 0.94, P=9.64×10(-6)). We performed a stratified analysis of rs12415204 and rs1158970 across all eight studies by age, gender, smoking status, and histology, and found consistent results across strata. Four of the 30 replicated variants act as expression quantitative trait loci (eQTL) sites in 1,111 nontumor lung tissues and meet the genome-wide 10% FDR threshold. © 2015 Wiley Periodicals, Inc.

A genome-wide association study of asthma symptoms in Latin American children.

PubMed

Costa, Gustavo N O; Dudbridge, Frank; Fiaccone, Rosemeire L; da Silva, Thiago M; Conceição, Jackson S; Strina, Agostino; Figueiredo, Camila A; Magalhães, Wagner C S; Rodrigues, Maira R; Gouveia, Mateus H; Kehdy, Fernanda S G; Horimoto, Andrea R V R; Horta, Bernardo; Burchard, Esteban G; Pino-Yanes, Maria; Del Rio Navarro, Blanca; Romieu, Isabelle; Hancock, Dana B; London, Stephanie; Lima-Costa, Maria Fernanda; Pereira, Alexandre C; Tarazona, Eduardo; Rodrigues, Laura C; Barreto, Mauricio L

2015-12-03

Asthma is a chronic disease of the airways and, despite the advances in the knowledge of associated genetic regions in recent years, their mechanisms have yet to be explored. Several genome-wide association studies have been carried out in recent years, but none of these have involved Latin American populations with a high level of miscegenation, as is seen in the Brazilian population. 1246 children were recruited from a longitudinal cohort study in Salvador, Brazil. Asthma symptoms were identified in accordance with an International Study of Asthma and Allergies in Childhood (ISAAC) questionnaire. Following quality control, 1,877,526 autosomal SNPs were tested for association with childhood asthma symptoms by logistic regression using an additive genetic model. We complemented the analysis with an estimate of the phenotypic variance explained by common genetic variants. Replications were investigated in independent Mexican and US Latino samples. Two chromosomal regions reached genome-wide significance level for childhood asthma symptoms: the 14q11 region flanking the DAD1 and OXA1L genes (rs1999071, MAF 0.32, OR 1.78, 95% CI 1.45-2.18, p-value 2.83 × 10(-8)) and 15q22 region flanking the FOXB1 gene (rs10519031, MAF 0.04, OR 3.0, 95% CI 2.02-4.49, p-value 6.68 × 10(-8) and rs8029377, MAF 0.03, OR 2.49, 95% CI 1.76-3.53, p-value 2.45 × 10(-7)). eQTL analysis suggests that rs1999071 regulates the expression of OXA1L gene. However, the original findings were not replicated in the Mexican or US Latino samples. We conclude that the 14q11 and 15q22 regions may be associated with asthma symptoms in childhood.

SiNoPsis: Single Nucleotide Polymorphisms selection and promoter profiling.

PubMed

Boloc, Daniel; Rodríguez, Natalia; Gassó, Patricia; Abril, Josep F; Bernardo, Miquel; Lafuente, Amalia; Mas, Sergi

2017-09-14

The selection of a Single Nucleotide Polymorphism (SNP) using bibliographic methods can be a very time-consuming task. Moreover, a SNP selected in this way may not be easily visualized in its genomic context by a standard user hoping to correlate it with other valuable information. Here we propose a web form built on top of Circos that can assist SNP-centred screening, based on their location in the genome and the regulatory modules they can disrupt. Its use may allow researchers to prioritize SNPs in genotyping and disease studies. SiNoPsis is bundled as a web portal. It focuses on the different structures involved in the genomic expression of a gene, especially those found in the core promoter upstream region. These structures include transcription factor binding sites (for promoter and enhancer signals), histones, and promoter flanking regions. Additionally, the tool provides eQTL and linkage disequilibrium (LD) properties for a given SNP query, yielding further clues about other indirectly associated SNPs. Possible disruptions of the aforementioned structures affecting gene transcription are reported using multiple resource databases. SiNoPsis has a simple user-friendly interface, which allows single queries by gene symbol, genomic coordinates, Ensembl gene identifiers, RefSeq transcript identifiers and SNPs. It is the only portal providing useful SNP selection based on regulatory modules and LD with functional variants in both textual and graphic modes (by properly defining the arguments and parameters needed to run Circos). SiNoPsis is freely available at https://compgen.bio.ub.edu/SiNoPsis /. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Deploying QTL-seq for rapid delineation of a potential candidate gene underlying major trait-associated QTL in chickpea

PubMed Central

Das, Shouvik; Upadhyaya, Hari D.; Bajaj, Deepak; Kujur, Alice; Badoni, Saurabh; Laxmi; Kumar, Vinod; Tripathi, Shailesh; Gowda, C. L. Laxmipathi; Sharma, Shivali; Singh, Sube; Tyagi, Akhilesh K.; Parida, Swarup K.

2015-01-01

A rapid high-resolution genome-wide strategy for molecular mapping of major QTL(s)/gene(s) regulating important agronomic traits is vital for in-depth dissection of complex quantitative traits and genetic enhancement in chickpea. The present study for the first time employed a NGS-based whole-genome QTL-seq strategy to identify one major genomic region harbouring a robust 100-seed weight QTL using an intra-specific 221 chickpea mapping population (desi cv. ICC 7184 × desi cv. ICC 15061). The QTL-seq-derived major SW QTL (CaqSW1.1) was further validated by single-nucleotide polymorphism (SNP) and simple sequence repeat (SSR) marker-based traditional QTL mapping (47.6% R2 at higher LOD >19). This reflects the reliability and efficacy of QTL-seq as a strategy for rapid genome-wide scanning and fine mapping of major trait regulatory QTLs in chickpea. The use of QTL-seq and classical QTL mapping in combination narrowed down the 1.37 Mb (comprising 177 genes) major SW QTL (CaqSW1.1) region into a 35 kb genomic interval on desi chickpea chromosome 1 containing six genes. One coding SNP (G/A)-carrying constitutive photomorphogenic9 (COP9) signalosome complex subunit 8 (CSN8) gene of these exhibited seed-specific expression, including pronounced differential up-/down-regulation in low and high seed weight mapping parents and homozygous individuals during seed development. The coding SNP mined in this potential seed weight-governing candidate CSN8 gene was found to be present exclusively in all cultivated species/genotypes, but not in any wild species/genotypes of primary, secondary and tertiary gene pools. This indicates the effect of strong artificial and/or natural selection pressure on target SW locus during chickpea domestication. The proposed QTL-seq-driven integrated genome-wide strategy has potential to delineate major candidate gene(s) harbouring a robust trait regulatory QTL rapidly with optimal use of resources. This will further assist us to extrapolate the molecular mechanism underlying complex quantitative traits at a genome-wide scale leading to fast-paced marker-assisted genetic improvement in diverse crop plants, including chickpea. PMID:25922536

Multienvironment Quantitative Trait Loci Analysis for Photosynthate Acquisition, Accumulation, and Remobilization Traits in Common Bean Under Drought Stress

PubMed Central

Asfaw, Asrat; Blair, Matthew W.; Struik, Paul C.

2012-01-01

Many of the world’s common bean (Phaseolus vulgaris L.) growing regions are prone to either intermittent or terminal drought stress, making drought the primary cause of yield loss under farmers’ field conditions. Improved photosynthate acquisition, accumulation, and then remobilization have been observed as important mechanisms for adaptation to drought stress. The objective of this study was to tag quantitative trait loci (QTL) for photosynthate acquisition, accumulation, and remobilization to grain by using a recombinant inbred line population developed from the Mesoamerican intragenepool cross of drought-susceptible DOR364 and drought-tolerant BAT477 grown under eight environments differing in drought stress across two continents: Africa and South America. The recombinant inbred line population expressed quantitative variation and transgressive segregation for 11 traits associated with drought tolerance. QTL were detected by both a mixed multienvironment model and by composite interval mapping for each environment using a linkage map constructed with 165 genetic markers that covered 11 linkage groups of the common bean genome. In the multienvironment, mixed model, nine QTL were detected for 10 drought stress tolerance mechanism traits found on six of the 11 linkage groups. Significant QTL × environment interaction was observed for six of the nine QTL. QTL × environment interaction was of the cross-over type for three of the six significant QTL with contrasting effect of the parental alleles across different environments. In the composite interval mapping, we found 69 QTL in total. The majority of these were found for Palmira (47) or Awassa (18), with fewer in Malawi (4). Phenotypic variation explained by QTL in single environments ranged up to 37%, and the most consistent QTL were for Soil Plant Analysis Development (SPAD) leaf chlorophyll reading and pod partitioning traits. QTL alignment between the two detection methods showed that yield QTL on b08 and stem carbohydrate QTL on b05 were most consistent between the multilocation model and the single environment detection. Our results indicate the relevance of QTL detection in the sites in which bean breeding will be undertaken and the importance of photosynthate accumulation as a trait for common bean drought tolerance. PMID:22670228

Multienvironment quantitative trait Loci analysis for photosynthate acquisition, accumulation, and remobilization traits in common bean under drought stress.

PubMed

Asfaw, Asrat; Blair, Matthew W; Struik, Paul C

2012-05-01

Many of the world's common bean (Phaseolus vulgaris L.) growing regions are prone to either intermittent or terminal drought stress, making drought the primary cause of yield loss under farmers' field conditions. Improved photosynthate acquisition, accumulation, and then remobilization have been observed as important mechanisms for adaptation to drought stress. The objective of this study was to tag quantitative trait loci (QTL) for photosynthate acquisition, accumulation, and remobilization to grain by using a recombinant inbred line population developed from the Mesoamerican intragenepool cross of drought-susceptible DOR364 and drought-tolerant BAT477 grown under eight environments differing in drought stress across two continents: Africa and South America. The recombinant inbred line population expressed quantitative variation and transgressive segregation for 11 traits associated with drought tolerance. QTL were detected by both a mixed multienvironment model and by composite interval mapping for each environment using a linkage map constructed with 165 genetic markers that covered 11 linkage groups of the common bean genome. In the multienvironment, mixed model, nine QTL were detected for 10 drought stress tolerance mechanism traits found on six of the 11 linkage groups. Significant QTL × environment interaction was observed for six of the nine QTL. QTL × environment interaction was of the cross-over type for three of the six significant QTL with contrasting effect of the parental alleles across different environments. In the composite interval mapping, we found 69 QTL in total. The majority of these were found for Palmira (47) or Awassa (18), with fewer in Malawi (4). Phenotypic variation explained by QTL in single environments ranged up to 37%, and the most consistent QTL were for Soil Plant Analysis Development (SPAD) leaf chlorophyll reading and pod partitioning traits. QTL alignment between the two detection methods showed that yield QTL on b08 and stem carbohydrate QTL on b05 were most consistent between the multilocation model and the single environment detection. Our results indicate the relevance of QTL detection in the sites in which bean breeding will be undertaken and the importance of photosynthate accumulation as a trait for common bean drought tolerance.

A 3’UTR polymorphism marks differential KLRG1 mRNA levels through disruption of a miR-584-5p binding site and associates with pemphigus foliaceus susceptibility

PubMed Central

Cipolla, Gabriel A.; Park, Jong K.; de Oliveira, Liana A.; Lobo-Alves, Sara Cristina; de Almeida, Rodrigo C.; Farias, Ticiana D. J.; Lemos, Débora de S.; Malheiros, Danielle; Lavker, Robert M.; Petzl-Erler, Maria Luiza

2016-01-01

Genetic variations mapping to 3’ untranslated regions (3’UTRs) may overlap with microRNA (miRNA) binding sites, therefore potentially interfering with translation inhibition or messenger RNA (mRNA) degradation. The aim of this study was to investigate whether single nucleotide polymorphisms (SNPs) located within the 3’UTRs of six candidate genes and predicted to interfere with miRNA ligation could account for disease-relevant differential mRNA levels. Focusing on pemphigus foliaceus (PF) – an autoimmune blistering skin condition with unique endemic patterns – we investigated if nine 3’UTR SNPs from the CD1D, CTLA4, KLRD1, KLRG1, NKG7, and TNFSF13B genes differentially expressed in PF were disease-associated. The heterozygous genotype of the KLRG1 rs1805672 polymorphism was associated with increased predisposition to PF (A/G vs. A/A: P=0.038; OR=1.60), and a trend for augmented susceptibility was observed for carriers of the G allele (P=0.094; OR=1.44). In silico analyses suggested that rs1805672 G allele could disrupt binding of miR-584-5p, and indicated rs1805672 as an expression Quantitative Trait Locus (eQTL), with an effect on KLRG1 gene expression. Dual-luciferase assay showed that miR-584-5p mediated approximately 50% downregulation of the reporter gene’s activity through the 3’UTR of KLRG1 harboring rs1805672 A allele (vs. miRNA-negative condition, P=0.006). This silencing relationship was lost after site-directed mutation to G allele (vs. miRNA-negative condition, P=0.391; vs. rs1805672 A allele, P=0.005). Collectively, these results suggest that a disease-associated SNP located within the 3’UTR of KLRG1 directly interferes with miR-584-5p binding, allowing for KLRG1 mRNA differential accumulation, which in turn may contribute to pathogenesis of autoimmune diseases, such as pemphigus. PMID:27424220

A 3'UTR polymorphism marks differential KLRG1 mRNA levels through disruption of a miR-584-5p binding site and associates with pemphigus foliaceus susceptibility.

PubMed

Cipolla, Gabriel A; Park, Jong Kook; de Oliveira, Liana A; Lobo-Alves, Sara Cristina; de Almeida, Rodrigo C; Farias, Ticiana D J; Lemos, Débora de S; Malheiros, Danielle; Lavker, Robert M; Petzl-Erler, Maria Luiza

2016-10-01

Genetic variations mapping to 3' untranslated regions (3'UTRs) may overlap with microRNA (miRNA) binding sites, therefore potentially interfering with translation inhibition or messenger RNA (mRNA) degradation. The aim of this study was to investigate whether single nucleotide polymorphisms (SNPs) located within the 3'UTRs of six candidate genes and predicted to interfere with miRNA ligation could account for disease-relevant differential mRNA levels. Focusing on pemphigus foliaceus (PF) - an autoimmune blistering skin condition with unique endemic patterns - we investigated whether nine 3'UTR SNPs from the CD1D, CTLA4, KLRD1, KLRG1, NKG7, and TNFSF13B genes differentially expressed in PF were disease-associated. The heterozygous genotype of the KLRG1 rs1805672 polymorphism was associated with increased predisposition to PF (A/G vs. A/A: P=0.038; OR=1.60), and a trend for augmented susceptibility was observed for carriers of the G allele (P=0.094; OR=1.44). In silico analyses suggested that rs1805672 G allele could disrupt binding of miR-584-5p, and indicated rs1805672 as an expression Quantitative Trait Locus (eQTL), with an effect on KLRG1 gene expression. Dual-luciferase assay showed that miR-584-5p mediated approximately 50% downregulation of the reporter gene's activity through the 3'UTR of KLRG1 harboring rs1805672 A allele (vs. miRNA-negative condition, P=0.006). This silencing relationship was lost after site-directed mutation to G allele (vs. miRNA-negative condition, P=0.391; vs. rs1805672 A allele, P=0.005). Collectively, these results suggest that a disease-associated SNP located within the 3'UTR of KLRG1 directly interferes with miR-584-5p binding, allowing for KLRG1 mRNA differential accumulation, which in turn may contribute to pathogenesis of autoimmune diseases, such as pemphigus. Copyright © 2016 Elsevier B.V. All rights reserved.

A genetic variant near GATA3 implicated in inherited susceptibility and etiology of benign prostatic hyperplasia (BPH) and lower urinary tract symptoms (LUTS).

PubMed

Na, Rong; Helfand, Brian T; Chen, Haitao; Conran, Carly A; Crawford, Susan E; Hayward, Simon W; Tammela, Teuvo L J; Hoffman-Bolton, Judy; Zheng, Siqun L; Walsh, Patrick C; Schleutker, Johanna; Platz, Elizabeth A; Isaacs, William B; Xu, Jianfeng

2017-08-01

Benign prostatic hyperplasia (BPH) and associated lower urinary tract symptoms (LUTS) are common conditions. Little is known about their etiologies except that studies have suggested a substantial heritable component. Our objective is to provide a comprehensive, genome-wide evaluation of inherited risks and possible mechanisms of etiology in BPH. We performed a three-stage, genome-wide association study (GWAS) of men from three independent populations, the REduction by DUtasteride of prostate Cancer Events (REDUCE) trial, the CLUE II cohort, and a Finnish hospital-based population. DNA samples were genotyped using the Illumina HumanOmniExpress BeadChip in REDUCE and CLUE II, and using the Sequenom iPLEX system for the confirmation stage in the Finnish population. A logistic regression model was used to evaluate the association between each SNP and BPH/LUTS. Fourteen SNPs reached P < 5.0 × 10 -4 in the meta-analysis of the two GWASs (CLUE II and REDUCE). A total of 773 SNPs were chosen for the confirmation step in the Finish cohort. Only one SNP (rs17144046) located ∼489 kb downstream of GATA3 remained significant after correction for multiple testing (P < 6.5 × 10 -5 ). This SNP marginally reached the GWAS significance level after performing a meta-analysis of the three stages (P -meta  = 8.89 × 10 -7 ). Expression quantitative trait loci (eQTL) analyses showed that the risk allele (G) of rs17144046 was significantly associated with increased expression of GATA3 (P = 0.017). Reported studies indicated a close correlation between GATA3 and BPH pathogenesis and progression. Rs17144046 located near GATA3 was significantly associated with BPH/LUTS in three independent populations, but did not reach a stringent GWAS significance level. Genetic variants of GATA3 may play a role in the inherited susceptibility and etiology of BPH/LUTS. Further research in this area is needed. © 2017 Wiley Periodicals, Inc.

Simultaneous grouping pursuit and feature selection over an undirected graph*

PubMed Central

Zhu, Yunzhang; Shen, Xiaotong; Pan, Wei

2013-01-01

Summary In high-dimensional regression, grouping pursuit and feature selection have their own merits while complementing each other in battling the curse of dimensionality. To seek a parsimonious model, we perform simultaneous grouping pursuit and feature selection over an arbitrary undirected graph with each node corresponding to one predictor. When the corresponding nodes are reachable from each other over the graph, regression coefficients can be grouped, whose absolute values are the same or close. This is motivated from gene network analysis, where genes tend to work in groups according to their biological functionalities. Through a nonconvex penalty, we develop a computational strategy and analyze the proposed method. Theoretical analysis indicates that the proposed method reconstructs the oracle estimator, that is, the unbiased least squares estimator given the true grouping, leading to consistent reconstruction of grouping structures and informative features, as well as to optimal parameter estimation. Simulation studies suggest that the method combines the benefit of grouping pursuit with that of feature selection, and compares favorably against its competitors in selection accuracy and predictive performance. An application to eQTL data is used to illustrate the methodology, where a network is incorporated into analysis through an undirected graph. PMID:24098061

Genetic dissection of quantitative trait locus for ethanol sensitivity in long- and short-sleep mice.

PubMed

Bennett, B; Carosone-Link, P; Beeson, M; Gordon, L; Phares-Zook, N; Johnson, T E

2008-08-01

Interval-specific congenic strains (ISCS) allow fine mapping of a quantitative trait locus (QTL), narrowing its confidence interval by an order of magnitude or more. In earlier work, we mapped four QTL specifying differential ethanol sensitivity, assessed by loss of righting reflex because of ethanol (LORE), in the inbred long-sleep (ILS) and inbred short-sleep (ISS) strains, accounting for approximately 50% of the genetic variance for this trait. Subsequently, we generated reciprocal congenic strains in which each full QTL interval from ILS was bred onto the ISS background and vice versa. An earlier paper reported construction and results of the ISCS on the ISS background; here, we describe this process and report results on the ILS background. We developed multiple ISCS for each Lore QTL in which the QTL interval was broken into a number of smaller intervals. For each of the four QTL regions (chromosomes 1, 2, 11 and 15), we were successful in reducing the intervals significantly. Multiple, positive strains were overlapped to generate a single, reduced interval. Subsequently, this reduced region was overlaid on previous reductions from the ISS background congenics, resulting in substantial reductions in all QTL regions by approximately 75% from the initial mapping study. Genes with sequence or expression polymorphisms in the reduced intervals are potential candidates; evidence for these is presented. Genetic background effects can be important in detection of single QTL; combining this information with the generation of congenics on both backgrounds, as described here, is a powerful approach for fine mapping QTL.

Defining the consequences of genetic variation on a proteome–wide scale

PubMed Central

Chick, Joel M.; Munger, Steven C.; Simecek, Petr; Huttlin, Edward L.; Choi, Kwangbom; Gatti, Daniel M.; Raghupathy, Narayanan; Svenson, Karen L.; Churchill, Gary A.; Gygi, Steven P.

2016-01-01

Genetic variation modulates protein expression through both transcriptional and post-transcriptional mechanisms. To characterize the consequences of natural genetic diversity on the proteome, here we combine a multiplexed, mass spectrometry-based method for protein quantification with an emerging outbred mouse model containing extensive genetic variation from eight inbred founder strains. By measuring genome-wide transcript and protein expression in livers from 192 Diversity outbred mice, we identify 2,866 protein quantitative trait loci (pQTL) with twice as many local as distant genetic variants. These data support distinct transcriptional and post-transcriptional models underlying the observed pQTL effects. Using a sensitive approach to mediation analysis, we often identified a second protein or transcript as the causal mediator of distant pQTL. Our analysis reveals an extensive network of direct protein–protein interactions. Finally, we show that local genotype can provide accurate predictions of protein abundance in an independent cohort of collaborative cross mice. PMID:27309819

A large QTL for fear and anxiety mapped using an F2 cross can be dissected into multiple smaller QTLs.

PubMed

Parker, C C; Sokoloff, G; Leung, E; Kirkpatrick, S L; Palmer, A A

2013-10-01

Using chromosome substitution strains (CSS), we previously identified a large quantitative trait locus (QTL) for conditioned fear (CF) on mouse chromosome 10. Here, we used an F2 cross between CSS-10 and C57BL/6J (B6) to localize that QTL to distal chromosome 10. That QTL accounted for all the difference between CSS-10 and B6. We then produced congenic strains to fine-map that interval. We identified two congenic strains that captured some or all the QTL. The larger congenic strain (Line 1: 122.387121-129.068 Mb; build 37) appeared to account for all the difference between CSS-10 and B6. The smaller congenic strain (Line 2: 127.277-129.068 Mb) was intermediate between CSS-10 and B6. We used haplotype mapping followed by quantitative polymerase chain reaction to identify one gene that was differentially expressed in both lines relative to B6 (Rnf41) and one that was differentially expressed between only Line 1 and B6 (Shmt2). These cis-eQTLs may cause the behavioral QTLs; however, further studies are required to validate these candidate genes. More generally, our observation that a large QTL mapped using CSS and F2 crosses can be dissected into multiple smaller QTLs shows a weaknesses of two-stage approaches that seek to use coarse mapping to identify large regions followed by fine-mapping. Indeed, additional dissection of these congenic strains might result in further subdivision of these QTL regions. Despite these limitations, we have successfully fine-mapped two QTLs to small regions and identified putative candidate genes, showing that the congenic approach can be effective for fine-mapping QTLs. © 2013 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

QTL-seq for rapid identification of candidate genes for flowering time in broccoli × cabbage.

PubMed

Shu, Jinshuai; Liu, Yumei; Zhang, Lili; Li, Zhansheng; Fang, Zhiyuan; Yang, Limei; Zhuang, Mu; Zhang, Yangyong; Lv, Honghao

2018-04-01

A major QTL controlling early flowering in broccoli × cabbage was identified by marker analysis and next-generation sequencing, corresponding to GRF6 gene conditioning flowering time in Arabidopsis. Flowering is an important agronomic trait for hybrid production in broccoli and cabbage, but the genetic mechanism underlying this process is unknown. In this study, segregation analysis with BC 1 P1, BC 1 P2, F 2 , and F 2:3 populations derived from a cross between two inbred lines "195" (late-flowering) and "93219" (early flowering) suggested that flowering time is a quantitative trait. Next, employing a next-generation sequencing-based whole-genome QTL-seq strategy, we identified a major genomic region harboring a robust flowering time QTL using an F 2 mapping population, designated Ef2.1 on cabbage chromosome 2 for early flowering. Ef2.1 was further validated by indel (insertion or deletion) marker-based classical QTL mapping, explaining 51.5% (LOD = 37.67) and 54.0% (LOD = 40.5) of the phenotypic variation in F 2 and F 2:3 populations, respectively. Combined QTL-seq and classical QTL analysis narrowed down Ef1.1 to a 228-kb genomic region containing 29 genes. A cabbage gene, Bol024659, was identified in this region, which is a homolog of GRF6, a major gene regulating flowering in Arabidopsis, and was designated BolGRF6. qRT-PCR study of the expression level of BolGRF6 revealed significantly higher expression in the early flowering genotypes. Taken together, our results provide support for BolGRF6 as a possible candidate gene for early flowering in the broccoli line 93219. The identified candidate genomic regions and genes may be useful for molecular breeding to improve broccoli and cabbage flowering times.

Genetic neuropathology of obsessive psychiatric syndromes

PubMed Central

Jaffe, A E; Deep-Soboslay, A; Tao, R; Hauptman, D T; Kaye, W H; Arango, V; Weinberger, D R; Hyde, T M; Kleinman, J E

2014-01-01

Anorexia nervosa (AN), bulimia nervosa (BN) and obsessive-compulsive disorder (OCD) are complex psychiatric disorders with shared obsessive features, thought to arise from the interaction of multiple genes of small effect with environmental factors. Potential candidate genes for AN, BN and OCD have been identified through clinical association and neuroimaging studies; however, recent genome-wide association studies of eating disorders (ED) so far have failed to report significant findings. In addition, few, if any, studies have interrogated postmortem brain tissue for evidence of expression quantitative trait loci (eQTLs) associated with candidate genes, which has particular promise as an approach to elucidating molecular mechanisms of association. We therefore selected single-nucleotide polymorphisms (SNPs) based on candidate gene studies for AN, BN and OCD from the literature, and examined the association of these SNPs with gene expression across the lifespan in prefrontal cortex of a nonpsychiatric control cohort (N=268). Several risk-predisposing SNPs were significantly associated with gene expression among control subjects. We then measured gene expression in the prefrontal cortex of cases previously diagnosed with obsessive psychiatric disorders, for example, ED (N=15) and OCD/obsessive-compulsive personality disorder or tics (OCD/OCPD/Tic; N=16), and nonpsychiatric controls (N=102) and identified 6 and 286 genes that were differentially expressed between ED compared with controls and OCD cases compared with controls, respectively (false discovery rate (FDR) <5%). However, none of the clinical risk SNPs were among the eQTLs and none were significantly associated with gene expression within the broad obsessive cohort, suggesting larger sample sizes or other brain regions may be required to identify candidate molecular mechanisms of clinical association in postmortem brain data sets. PMID:25180571

Genetic neuropathology of obsessive psychiatric syndromes.

PubMed

Jaffe, A E; Deep-Soboslay, A; Tao, R; Hauptman, D T; Kaye, W H; Arango, V; Weinberger, D R; Hyde, T M; Kleinman, J E

2014-09-02

Anorexia nervosa (AN), bulimia nervosa (BN) and obsessive-compulsive disorder (OCD) are complex psychiatric disorders with shared obsessive features, thought to arise from the interaction of multiple genes of small effect with environmental factors. Potential candidate genes for AN, BN and OCD have been identified through clinical association and neuroimaging studies; however, recent genome-wide association studies of eating disorders (ED) so far have failed to report significant findings. In addition, few, if any, studies have interrogated postmortem brain tissue for evidence of expression quantitative trait loci (eQTLs) associated with candidate genes, which has particular promise as an approach to elucidating molecular mechanisms of association. We therefore selected single-nucleotide polymorphisms (SNPs) based on candidate gene studies for AN, BN and OCD from the literature, and examined the association of these SNPs with gene expression across the lifespan in prefrontal cortex of a nonpsychiatric control cohort (N=268). Several risk-predisposing SNPs were significantly associated with gene expression among control subjects. We then measured gene expression in the prefrontal cortex of cases previously diagnosed with obsessive psychiatric disorders, for example, ED (N=15) and OCD/obsessive-compulsive personality disorder or tics (OCD/OCPD/Tic; N=16), and nonpsychiatric controls (N=102) and identified 6 and 286 genes that were differentially expressed between ED compared with controls and OCD cases compared with controls, respectively (false discovery rate (FDR) <5%). However, none of the clinical risk SNPs were among the eQTLs and none were significantly associated with gene expression within the broad obsessive cohort, suggesting larger sample sizes or other brain regions may be required to identify candidate molecular mechanisms of clinical association in postmortem brain data sets.

Molecular mapping and improvement of leaf rust resistance in wheat breeding lines.

PubMed

Tsilo, Toi J; Kolmer, James A; Anderson, James A

2014-08-01

Leaf rust, caused by Puccinia triticina, is the most common and widespread disease of wheat (Triticum aestivum) worldwide. Deployment of host-plant resistance is one of the strategies to reduce losses due to leaf rust disease. The objective of this study was to map genes for adult-plant resistance to leaf rust in a recombinant inbred line (RIL) population originating from MN98550-5/MN99394-1. The mapping population of 139 RILs and five checks were evaluated in 2005, 2009, and 2010 in five environments. Natural infection occurred in the 2005 trials and trials in 2009 and 2010 were inoculated with leaf rust. Four quantitative trait loci (QTL) on chromosomes 2BS, 2DS, 7AL, and 7DS were detected. The QTL on 2BS explained up to 33.6% of the phenotypic variation in leaf rust response, whereas the QTL on 2DS, 7AL, and 7DS explained up to 15.7, 8.1, and 34.2%, respectively. Seedling infection type tests conducted with P. triticina races BBBD and SBDG confirmed that the QTL on 2BS and 2DS were Lr16 and Lr2a, respectively, and these genes were expressed in the seedling and field plot tests. The Lr2a gene mapped at the same location as Sr6. The QTL on 7DS was Lr34. The QTL on 7AL is a new QTL for leaf rust resistance. The joint effects of all four QTL explained 74% of the total phenotypic variation in leaf rust severity. Analysis of different combinations of QTL showed that the RILs containing all four or three of the QTL had the lowest average leaf rust severity in all five environments. Deployment of these QTL in combination or with other effective genes will lead to successful control of leaf rust.

Major quality trait analysis and QTL detection in hexaploid wheat in humid rain-fed agriculture.

PubMed

Li, H M; Tang, Z X; Zhang, H Q; Yan, B J; Ren, Z L

2013-05-21

Humid rain-fed agriculture is a special environment for wheat (Triticum aestivum) culture that tends to negatively affect wheat yield and quality. To identify quality characters of wheat in a humid environment, we conducted quality analysis and quantitative trait loci (QTL) detection in a recombinant inbred line whose parent had a high level of quality for several years. We found that high-quality wheat had less gluten content and lower protein content. Apparently, wheat quality and associated quantity traits were in a dynamic state of equilibrium. We detected 83 QTL for 10 wheat quality traits in this recombinant inbred line population. Nine QTL were detected in both evaluation years; Q.DT.scau-2A, linked to Xwmc522-2A, was detected at the same genetic location in both years. Other QTL for different traits were detected simultaneously in more than one location. Consequently, there appeared to be pleiotropic genes that control wheat quality. Based on previous studies and our research on QTL analysis of grain protein content, we conclude that there must be one or more genes for grain protein content on chromosome 6B, whose expression was little affected by environment. We constructed a consensus map and projected the QTL on it. It was useful for choosing optimal markers for marker-assisted breeding and map-based cloning.

Omic personality: implications of stable transcript and methylation profiles for personalized medicine.

PubMed

Tabassum, Rubina; Sivadas, Ambily; Agrawal, Vartika; Tian, Haozheng; Arafat, Dalia; Gibson, Greg

2015-08-13

Personalized medicine is predicated on the notion that individual biochemical and genomic profiles are relatively constant in times of good health and to some extent predictive of disease or therapeutic response. We report a pilot study quantifying gene expression and methylation profile consistency over time, addressing the reasons for individual uniqueness, and its relation to N = 1 phenotypes. Whole blood samples from four African American women, four Caucasian women, and four Caucasian men drawn from the Atlanta Center for Health Discovery and Well Being study at three successive 6-month intervals were profiled by RNA-Seq, miRNA-Seq, and Illumina Methylation 450 K arrays. Standard regression approaches were used to evaluate the proportion of variance for each type of omic measure among individuals, and to quantify correlations among measures and with clinical attributes related to wellness. Longitudinal omic profiles were in general highly consistent over time, with an average of 67 % variance in transcript abundance, 42 % in CpG methylation level (but 88 % for the most differentiated CpG per gene), and 50 % in miRNA abundance among individuals, which are all comparable to 74 % variance among individuals for 74 clinical traits. One third of the variance could be attributed to differential blood cell type abundance, which was also fairly stable over time, and a lesser amount to expression quantitative trait loci (eQTL) effects. Seven conserved axes of covariance that capture diverse aspects of immune function explained over half of the variance. These axes also explained a considerable proportion of individually extreme transcript abundance, namely approximately 100 genes that were significantly up-regulated or down-regulated in each person and were in some cases enriched for relevant gene activities that plausibly associate with clinical attributes. A similar fraction of genes had individually divergent methylation levels, but these did not overlap with the transcripts, and fewer than 20 % of genes had significantly correlated methylation and gene expression. People express an "omic personality" consisting of peripheral blood transcriptional and epigenetic profiles that are constant over the course of a year and reflect various types of immune activity. Baseline genomic profiles can provide a window into the molecular basis of traits that might be useful for explaining medical conditions or guiding personalized health decisions.

Using genome wide association studies to identify common QTL regions in three different genetic backgrounds based on Iberian pig breed.

PubMed

Martínez-Montes, Ángel M; Fernández, Almudena; Muñoz, María; Noguera, Jose Luis; Folch, Josep M; Fernández, Ana I

2018-01-01

One of the major limitation for the application of QTL results in pig breeding and QTN identification has been the limited number of QTL effects validated in different animal material. The aim of the current work was to validate QTL regions through joint and specific genome wide association and haplotype analyses for growth, fatness and premier cut weights in three different genetic backgrounds, backcrosses based on Iberian pigs, which has a major role in the analysis due to its high productive relevance. The results revealed nine common QTL regions, three segregating in all three backcrosses on SSC1, 0-3 Mb, for body weight, on SSC2, 3-9 Mb, for loin bone-in weight, and on SSC7, 3 Mb, for shoulder weight, and six segregating in two of the three backcrosses, on SSC2, SSC4, SSC6 and SSC10 for backfat thickness, shoulder and ham weights. Besides, 18 QTL regions were specifically identified in one of the three backcrosses, five identified only in BC_LD, seven in BC_DU and six in BC_PI. Beyond identifying and validating QTL, candidate genes and gene variants within the most interesting regions have been explored using functional annotation, gene expression data and SNP identification from RNA-Seq data. The results allowed us to propose a promising list of candidate mutations, those identified in PDE10A, DHCR7, MFN2 and CCNY genes located within the common QTL regions and those identified near ssc-mir-103-1 considered PANK3 regulators to be further analysed.

Identification of Genes Whose Expression Profile Is Associated with Non-Progression towards AIDS Using eQTLs

PubMed Central

Le Clerc, Sigrid; van Manen, Daniëlle; Coulonges, Cédric; Ulveling, Damien; Laville, Vincent; Labib, Taoufik; Taing, Lieng; Delaneau, Olivier; Montes, Matthieu; Schuitemaker, Hanneke; Zagury, Jean-François

2015-01-01

Background Many genome-wide association studies have been performed on progression towards the acquired immune deficiency syndrome (AIDS) and they mainly identified associations within the HLA loci. In this study, we demonstrate that the integration of biological information, namely gene expression data, can enhance the sensitivity of genetic studies to unravel new genetic associations relevant to AIDS. Methods We collated the biological information compiled from three databases of expression quantitative trait loci (eQTLs) involved in cells of the immune system. We derived a list of single nucleotide polymorphisms (SNPs) that are functional in that they correlate with differential expression of genes in at least two of the databases. We tested the association of those SNPs with AIDS progression in two cohorts, GRIV and ACS. Tests on permuted phenotypes of the GRIV and ACS cohorts or on randomised sets of equivalent SNPs allowed us to assess the statistical robustness of this method and to estimate the true positive rate. Results Eight genes were identified with high confidence (p = 0.001, rate of true positives 75%). Some of those genes had previously been linked with HIV infection. Notably, ENTPD4 belongs to the same family as CD39, whose expression has already been associated with AIDS progression; while DNAJB12 is part of the HSP90 pathway, which is involved in the control of HIV latency. Our study also drew our attention to lesser-known functions such as mitochondrial ribosomal proteins and a zinc finger protein, ZFP57, which could be central to the effectiveness of HIV infection. Interestingly, for six out of those eight genes, down-regulation is associated with non-progression, which makes them appealing targets to develop drugs against HIV. PMID:26367535

A genome scan revealed significant associations of growth traits with a major QTL and GHR2 in tilapia

PubMed Central

Liu, Feng; Sun, Fei; Xia, Jun Hong; Li, Jian; Fu, Gui Hong; Lin, Grace; Tu, Rong Jian; Wan, Zi Yi; Quek, Delia; Yue, Gen Hua

2014-01-01

Growth is an important trait in animal breeding. However, the genetic effects underpinning fish growth variability are still poorly understood. QTL mapping and analysis of candidate genes are effective methods to address this issue. We conducted a genome-wide QTL analysis for growth in tilapia. A total of 10, 7 and 8 significant QTLs were identified for body weight, total length and standard length at 140 dph, respectively. The majority of these QTLs were sex-specific. One major QTL for growth traits was identified in the sex-determining locus in LG1, explaining 71.7%, 67.2% and 64.9% of the phenotypic variation (PV) of body weight, total length and standard length, respectively. In addition, a candidate gene GHR2 in a QTL was significantly associated with body weight, explaining 13.1% of PV. Real-time qPCR revealed that different genotypes at the GHR2 locus influenced the IGF-1 expression level. The markers located in the major QTL for growth traits could be used in marker-assisted selection of tilapia. The associations between GHR2 variants and growth traits suggest that the GHR2 gene should be an important gene that explains the difference in growth among tilapia species. PMID:25435025

Pheno2Geno - High-throughput generation of genetic markers and maps from molecular phenotypes for crosses between inbred strains.

PubMed

Zych, Konrad; Li, Yang; van der Velde, Joeri K; Joosen, Ronny V L; Ligterink, Wilco; Jansen, Ritsert C; Arends, Danny

2015-02-19

Genetic markers and maps are instrumental in quantitative trait locus (QTL) mapping in segregating populations. The resolution of QTL localization depends on the number of informative recombinations in the population and how well they are tagged by markers. Larger populations and denser marker maps are better for detecting and locating QTLs. Marker maps that are initially too sparse can be saturated or derived de novo from high-throughput omics data, (e.g. gene expression, protein or metabolite abundance). If these molecular phenotypes are affected by genetic variation due to a major QTL they will show a clear multimodal distribution. Using this information, phenotypes can be converted into genetic markers. The Pheno2Geno tool uses mixture modeling to select phenotypes and transform them into genetic markers suitable for construction and/or saturation of a genetic map. Pheno2Geno excludes candidate genetic markers that show evidence for multiple possibly epistatically interacting QTL and/or interaction with the environment, in order to provide a set of robust markers for follow-up QTL mapping. We demonstrate the use of Pheno2Geno on gene expression data of 370,000 probes in 148 A. thaliana recombinant inbred lines. Pheno2Geno is able to saturate the existing genetic map, decreasing the average distance between markers from 7.1 cM to 0.89 cM, close to the theoretical limit of 0.68 cM (with 148 individuals we expect a recombination every 100/148=0.68 cM); this pinpointed almost all of the informative recombinations in the population. The Pheno2Geno package makes use of genome-wide molecular profiling and provides a tool for high-throughput de novo map construction and saturation of existing genetic maps. Processing of the showcase dataset takes less than 30 minutes on an average desktop PC. Pheno2Geno improves QTL mapping results at no additional laboratory cost and with minimum computational effort. Its results are formatted for direct use in R/qtl, the leading R package for QTL studies. Pheno2Geno is freely available on CRAN under "GNU GPL v3". The Pheno2Geno package as well as the tutorial can also be found at: http://pheno2geno.nl .

Detection of QTL controlling metabolism, meat quality, and liver quality traits of the overfed interspecific hybrid mule duck.

PubMed

Kileh-Wais, M; Elsen, J M; Vignal, A; Feves, K; Vignoles, F; Fernandez, X; Manse, H; Davail, S; André, J M; Bastianelli, D; Bonnal, L; Filangi, O; Baéza, E; Guéméné, D; Genêt, C; Bernadet, M D; Dubos, F; Marie-Etancelin, C

2013-02-01

The mule duck, an interspecific hybrid obtained by crossing common duck (Anas platyrhynchos) females with Muscovy (Cairina moschata) drakes, is widely used for fatty liver production. The purpose of the present study was to detect and map single and pleiotropic QTL that segregate in the common duck species, and influence the expression of traits in their overfed mule duck offspring. To this end, we generated a common duck backcross (BC) population by crossing Kaiya and heavy Pekin experimental lines, which differ notably in regard to the BW and overfeeding ability of their mule progeny. The BC females were mated to Muscovy drakes and, on average, 4 male mule ducks hatched per BC female (1600 in total) and were measured for growth, metabolism during growth and the overfeeding period, overfeeding ability, and the quality of their breast meat and fatty liver. The phenotypic value of BC females was estimated for each trait by assigning to each female the mean value of the phenotypes of her offspring. Estimations allowed for variance, which depended on the number of male offspring per BC and the heritability of the trait considered. The genetic map used for QTL detection consisted of 91 microsatellite markers aggregated into 16 linkage groups (LG) covering a total of 778 cM. Twenty-two QTL were found to be significant at the 1% chromosome-wide threshold level using the single-trait detection option of the QTLMap software. Most of the QTL detected were related to the quality of breast meat and fatty liver: QTL for meat pH 20 min post mortem were mapped to LG4 (at the 1% genome-wide significance level), and QTL for meat lipid content and cooking losses were mapped to LG2a. The QTL related to fatty liver weight and liver protein and lipid content were for the most part detected on LG2c and LG9. Multitrait analysis highlighted the pleiotropic effects of QTL in these chromosome regions. Apart from the strong QTL for plasma triglyceride content at the end of the overfeeding period mapped to chromosome Z using single-trait analysis, all metabolic trait QTL were detected with the multitrait approach: the QTL mapped to LG14 and LG21 affected the plasma cholesterol and triglyceride contents, whereas the QTL mapped to LG2a seemed to impact glycemia and the basal plasma corticosterone content. A greater density genetic map will be needed to further fine map the QTL.

Using genome wide association studies to identify common QTL regions in three different genetic backgrounds based on Iberian pig breed

PubMed Central

Martínez-Montes, Ángel M.; Fernández, Almudena; Muñoz, María; Noguera, Jose Luis; Folch, Josep M.

2018-01-01

One of the major limitation for the application of QTL results in pig breeding and QTN identification has been the limited number of QTL effects validated in different animal material. The aim of the current work was to validate QTL regions through joint and specific genome wide association and haplotype analyses for growth, fatness and premier cut weights in three different genetic backgrounds, backcrosses based on Iberian pigs, which has a major role in the analysis due to its high productive relevance. The results revealed nine common QTL regions, three segregating in all three backcrosses on SSC1, 0–3 Mb, for body weight, on SSC2, 3–9 Mb, for loin bone-in weight, and on SSC7, 3 Mb, for shoulder weight, and six segregating in two of the three backcrosses, on SSC2, SSC4, SSC6 and SSC10 for backfat thickness, shoulder and ham weights. Besides, 18 QTL regions were specifically identified in one of the three backcrosses, five identified only in BC_LD, seven in BC_DU and six in BC_PI. Beyond identifying and validating QTL, candidate genes and gene variants within the most interesting regions have been explored using functional annotation, gene expression data and SNP identification from RNA-Seq data. The results allowed us to propose a promising list of candidate mutations, those identified in PDE10A, DHCR7, MFN2 and CCNY genes located within the common QTL regions and those identified near ssc-mir-103-1 considered PANK3 regulators to be further analysed. PMID:29522525

Integration of Murine and Human Studies for Mapping Periodontitis Susceptibility.

PubMed

Nashef, A; Qabaja, R; Salaymeh, Y; Botzman, M; Munz, M; Dommisch, H; Krone, B; Hoffmann, P; Wellmann, J; Laudes, M; Berger, K; Kocher, T; Loos, B; van der Velde, N; Uitterlinden, A G; de Groot, L C P G M; Franke, A; Offenbacher, S; Lieb, W; Divaris, K; Mott, R; Gat-Viks, I; Wiess, E; Schaefer, A; Iraqi, F A; Haddad, Y H

2018-05-01

Periodontitis is one of the most common inflammatory human diseases with a strong genetic component. Due to the limited sample size of available periodontitis cohorts and the underlying trait heterogeneity, genome-wide association studies (GWASs) of chronic periodontitis (CP) have largely been unsuccessful in identifying common susceptibility factors. A combination of quantitative trait loci (QTL) mapping in mice with association studies in humans has the potential to discover novel risk loci. To this end, we assessed alveolar bone loss in response to experimental periodontal infection in 25 lines (286 mice) from the Collaborative Cross (CC) mouse population using micro-computed tomography (µCT) analysis. The orthologous human chromosomal regions of the significant QTL were analyzed for association using imputed genotype data (OmniExpress BeadChip arrays) derived from case-control samples of aggressive periodontitis (AgP; 896 cases, 7,104 controls) and chronic periodontitis (CP; 2,746 cases, 1,864 controls) of northwest European and European American descent, respectively. In the mouse genome, QTL mapping revealed 2 significant loci (-log P = 5.3; false discovery rate = 0.06) on chromosomes 1 ( Perio3) and 14 ( Perio4). The mapping resolution ranged from ~1.5 to 3 Mb. Perio3 overlaps with a previously reported QTL associated with residual bone volume in F2 cross and includes the murine gene Ccdc121. Its human orthologue showed previously a nominal significant association with CP in humans. Use of variation data from the genomes of the CC founder strains further refined the QTL and suggested 7 candidate genes ( CAPN8, DUSP23, PCDH17, SNORA17, PCDH9, LECT1, and LECT2). We found no evidence of association of these candidates with the human orthologues. In conclusion, the CC populations enabled mapping of confined QTL that confer susceptibility to alveolar bone loss in mice and larger human phenotype-genotype samples and additional expression data from gingival tissues are likely required to identify true positive signals.

Practical applications of the bioinformatics toolbox for narrowing quantitative trait loci.

PubMed

Burgess-Herbert, Sarah L; Cox, Allison; Tsaih, Shirng-Wern; Paigen, Beverly

2008-12-01

Dissecting the genes involved in complex traits can be confounded by multiple factors, including extensive epistatic interactions among genes, the involvement of epigenetic regulators, and the variable expressivity of traits. Although quantitative trait locus (QTL) analysis has been a powerful tool for localizing the chromosomal regions underlying complex traits, systematically identifying the causal genes remains challenging. Here, through its application to plasma levels of high-density lipoprotein cholesterol (HDL) in mice, we demonstrate a strategy for narrowing QTL that utilizes comparative genomics and bioinformatics techniques. We show how QTL detected in multiple crosses are subjected to both combined cross analysis and haplotype block analysis; how QTL from one species are mapped to the concordant regions in another species; and how genomewide scans associating haplotype groups with their phenotypes can be used to prioritize the narrowed regions. Then we illustrate how these individual methods for narrowing QTL can be systematically integrated for mouse chromosomes 12 and 15, resulting in a significantly reduced number of candidate genes, often from hundreds to <10. Finally, we give an example of how additional bioinformatics resources can be combined with experiments to determine the most likely quantitative trait genes.

Quantitative Trait Loci Mapping in Brassica rapa Revealed the Structural and Functional Conservation of Genetic Loci Governing Morphological and Yield Component Traits in the A, B, and C Subgenomes of Brassica Species

PubMed Central

Li, Xiaonan; Ramchiary, Nirala; Dhandapani, Vignesh; Choi, Su Ryun; Hur, Yoonkang; Nou, Ill-Sup; Yoon, Moo Kyoung; Lim, Yong Pyo

2013-01-01

Brassica rapa is an important crop species that produces vegetables, oilseed, and fodder. Although many studies reported quantitative trait loci (QTL) mapping, the genes governing most of its economically important traits are still unknown. In this study, we report QTL mapping for morphological and yield component traits in B. rapa and comparative map alignment between B. rapa, B. napus, B. juncea, and Arabidopsis thaliana to identify candidate genes and conserved QTL blocks between them. A total of 95 QTL were identified in different crucifer blocks of the B. rapa genome. Through synteny analysis with A. thaliana, B. rapa candidate genes and intronic and exonic single nucleotide polymorphisms in the parental lines were detected from whole genome resequenced data, a few of which were validated by mapping them to the QTL regions. Semi-quantitative reverse transcriptase PCR analysis showed differences in the expression levels of a few genes in parental lines. Comparative mapping identified five key major evolutionarily conserved crucifer blocks (R, J, F, E, and W) harbouring QTL for morphological and yield components traits between the A, B, and C subgenomes of B. rapa, B. juncea, and B. napus. The information of the identified candidate genes could be used for breeding B. rapa and other related Brassica species. PMID:23223793

Genetic mapping of clubroot resistance genes in oilseed rape.

PubMed

Werner, S; Diederichsen, E; Frauen, M; Schondelmaier, J; Jung, C

2008-02-01

Clubroot caused by the obligate biotrophic protist Plasmodiophora brassicae is a major disease of Brassica species. Clubroot resistances introduced from B. oleracea var. 'Böhmerwaldkohl' and resistance from B. rapa ECD-04 were genetically mapped in oilseed rape (B. napus L.). A doubled haploid (DH) population of rape seed was developed by crossing a resistant DH-line derived from a resynthesized B. napus with the susceptible cultivar 'Express'. The DH population was tested in the greenhouse against seven P. brassicae isolates showing low and high virulence toward B. oleracea or/and B. rapa. DH-lines with highest or lowest disease scores were used in a bulked segregant analysis (BSA), and 43 polymorphic AFLPs were identified. A genetic map of the whole genome was constructed using 338 AFLP and 156 anchored SSR markers. Nineteen QTL were detected on chromosomes N02, N03, N08, N13, N15, N16 and N19 giving resistance to seven different isolates. Race-specific effects were observed for all QTL, none of the QTL conferred resistance to all isolates. The phenotypic variance explained by the respective QTL ranged between 10.3 and 67.5%. All QTL could be assigned to both ancestral genomes of B. napus. In contrast to previous reports, a clear differentiation into major QTL from B. rapa and minor QTL from B. oleracea could not be found. Composite interval mapping confirmed the linkage relationships determined by BSA, thus demonstrating that markers for oligogenic traits can be selected by merely testing the distributional extremes of a segregating population.

Cryptic Genetic Variation for Arabidopsis thaliana Seed Germination Speed in a Novel Salt Stress Environment

PubMed Central

Yuan, Wei; Flowers, Jonathan M.; Sahraie, Dustin J.; Purugganan, Michael D.

2016-01-01

The expansion of species ranges frequently necessitates responses to novel environments. In plants, the ability of seeds to disperse to marginal areas relies in part to its ability to germinate under stressful conditions. Here we examine the genetic architecture of Arabidopsis thaliana germination speed under a novel, saline environment, using an Extreme QTL (X-QTL) mapping platform we previously developed. We find that early germination in normal and salt conditions both rely on a QTL on the distal arm of chromosome 4, but we also find unique QTL on chromosomes 1, 2, 4, and 5 that are specific to salt stress environments. Moreover, different QTLs are responsible for early vs. late germination, suggesting a temporal component to the expression of life history under these stress conditions. Our results indicate that cryptic genetic variation exists for responses to a novel abiotic stress, which may suggest a role of such variation in adaptation to new climactic conditions or growth environments. PMID:27543295

Integration of copy number and transcriptomics provides risk stratification in prostate cancer: A discovery and validation cohort study

PubMed Central

Ross-Adams, H.; Lamb, A.D.; Dunning, M.J.; Halim, S.; Lindberg, J.; Massie, C.M.; Egevad, L.A.; Russell, R.; Ramos-Montoya, A.; Vowler, S.L.; Sharma, N.L.; Kay, J.; Whitaker, H.; Clark, J.; Hurst, R.; Gnanapragasam, V.J.; Shah, N.C.; Warren, A.Y.; Cooper, C.S.; Lynch, A.G.; Stark, R.; Mills, I.G.; Grönberg, H.; Neal, D.E.

2015-01-01

Background Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome. Methods In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone. Findings We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions. Interpretation For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts. PMID:26501111

Redox-dependent interaction between thaumatin-like protein and β-glucan influences malting quality of barley.

PubMed

Singh, Surinder; Tripathi, Rajiv K; Lemaux, Peggy G; Buchanan, Bob B; Singh, Jaswinder

2017-07-18

Barley is the cornerstone of the malting and brewing industry. It is known that 250 quantitative trait loci (QTLs) of the grain are associated with 19 malting-quality phenotypes. However, only a few of the contributing genetic components have been identified. One of these, on chromosome 4H, contains a major malting QTL, QTL2, located near the telomeric region that accounts, respectively, for 28.9% and 37.6% of the variation in the β-glucan and extract fractions of malt. In the current study, we dissected the QTL2 region using an expression- and microsynteny-based approach. From a set of 22 expressed sequence tags expressed in seeds at the malting stage, we identified a candidate gene, TLP8 ( thaumatin-like protein 8 ), which was differentially expressed and influenced malting quality. Transcript abundance and protein profiles of TLP8 were studied in different malt and feed varieties using quantitative PCR, immunoblotting, and enzyme-linked immunosorbent assay (ELISA). The experiments demonstrated that TLP8 binds to insoluble (1, 3, 1, 4)-β-D glucan in grain extracts, thereby facilitating the removal of this undesirable polysaccharide during malting. Further, the binding of TLP8 to β-glucan was dependent on redox. These findings represent a stride forward in our understanding of the malting process and provide a foundation for future improvements in the final beer-making process.

Fabp7 Maps to a Quantitative Trait Locus for a Schizophrenia Endophenotype

PubMed Central

Watanabe, Akiko; Toyota, Tomoko; Owada, Yuji; Hayashi, Takeshi; Iwayama, Yoshimi; Matsumata, Miho; Ishitsuka, Yuichi; Nakaya, Akihiro; Maekawa, Motoko; Ohnishi, Tetsuo; Arai, Ryoichi; Sakurai, Katsuyasu; Yamada, Kazuo; Kondo, Hisatake; Hashimoto, Kenji; Osumi, Noriko; Yoshikawa, Takeo

2007-01-01

Deficits in prepulse inhibition (PPI) are a biological marker for schizophrenia. To unravel the mechanisms that control PPI, we performed quantitative trait loci (QTL) analysis on 1,010 F2 mice derived by crossing C57BL/6 (B6) animals that show high PPI with C3H/He (C3) animals that show low PPI. We detected six major loci for PPI, six for the acoustic startle response, and four for latency to response peak, some of which were sex-dependent. A promising candidate on the Chromosome 10-QTL was Fabp7 (fatty acid binding protein 7, brain), a gene with functional links to the N-methyl-D-aspartic acid (NMDA) receptor and expression in astrocytes. Fabp7-deficient mice showed decreased PPI and a shortened startle response latency, typical of the QTL's proposed effects. A quantitative complementation test supported Fabp7 as a potential PPI-QTL gene, particularly in male mice. Disruption of Fabp7 attenuated neurogenesis in vivo. Human FABP7 showed altered expression in schizophrenic brains and genetic association with schizophrenia, which were both evident in males when samples were divided by sex. These results suggest that FABP7 plays a novel and crucial role, linking the NMDA, neurodevelopmental, and glial theories of schizophrenia pathology and the PPI endophenotype, with larger or overt effects in males. We also discuss the results from the perspective of fetal programming. PMID:18001149

Analysis of the QTL for sleep homeostasis in mice: Homer1a is a likely candidate.

PubMed

Mackiewicz, M; Paigen, B; Naidoo, N; Pack, A I

2008-03-14

Electroencephalographic oscillations in the frequency range of 0.5-4 Hz, characteristic of slow-wave sleep (SWS), are often referred to as the delta oscillation or delta power. Delta power reflects sleep intensity and correlates with the homeostatic response to sleep loss. A published survey of inbred strains of mice demonstrated that the time course of accumulation of delta power varied among inbred strains, and the segregation of the rebound of delta power in BxD recombinant inbred strains identified a genomic region on chromosome 13 referred to as the delta power in SWS (or Dps1). The quantitative trait locus (QTL) contains genes that modify the accumulation of delta power after sleep deprivation. Here, we narrow the QTL using interval-specific haplotype analysis and present a comprehensive annotation of the remaining genes in the Dps1 region with sequence comparisons to identify polymorphisms within the coding and regulatory regions. We established the expression pattern of selected genes located in the Dps1 interval in sleep and wakefulness in B6 and D2 parental strains. Taken together, these steps reduced the number of potential candidate genes that may underlie the accumulation of delta power after sleep deprivation and explain the Dps1 QTL. The strongest candidate gene is Homer1a, which is supported by expression differences between sleep and wakefulness and the SNP polymorphism in the upstream regulatory regions.

Loci on chromosomes 1A and 2A affect resistance to tan (yellow) spot in wheat populations not segregating for tsn1.

PubMed

Shankar, Manisha; Jorgensen, Dorthe; Taylor, Julian; Chalmers, Ken J; Fox, Rebecca; Hollaway, Grant J; Neate, Stephen M; McLean, Mark S; Vassos, Elysia; Golzar, Hossein; Loughman, Robert; Mather, Diane E

2017-12-01

QTL for tan spot resistance were mapped on wheat chromosomes 1A and 2A. Lines were developed with resistance alleles at these loci and at the tsn1 locus on chromosome 5B. These lines expressed significantly higher resistance than the parent with tsn1 only. Tan spot (syn. yellow spot and yellow leaf spot) caused by Pyrenophora tritici-repentis is an important foliar disease of wheat in Australia. Few resistance genes have been mapped in Australian germplasm and only one, known as tsn1 located on chromosome 5B, is known in Australian breeding programs. This gene confers insensitivity to the fungal effector ToxA. The main aim of this study was to map novel resistance loci in two populations: Calingiri/Wyalkatchem, which is fixed for the ToxA-insensitivity allele tsn1, and IGW2574/Annuello, which is fixed for the ToxA-sensitivity allele Tsn1. A second aim was to combine new loci with tsn1 to develop lines with improved resistance. Tan spot severity was evaluated at various growth stages and in multiple environments. Symptom severity traits exhibited quantitative variation. The most significant quantitative trait loci (QTL) were detected on chromosomes 2A and 1A. The QTL on 2A explained up to 29.2% of the genotypic variation in the Calingiri/Wyalkatchem population with the resistance allele contributed by Wyalkatchem. The QTL on 1A explained up to 28.1% of the genotypic variation in the IGW2574/Annuello population with the resistance allele contributed by Annuello. The resistance alleles at both QTL were successfully combined with tsn1 to develop lines that express significantly better resistance at both seedling and adult plant stages than Calingiri which has tsn1 only.

Relationship of the Interaction Between Two Quantitative Trait Loci with γ-Globin Expression in β-Thalassemia Intermedia Patients.

PubMed

NickAria, Shiva; Haghpanah, Sezaneh; Ramzi, Mani; Karimi, Mehran

2018-05-10

Globin switching is a significant factor on blood hemoglobin (Hb) level but its molecular mechanisms have not yet been identified, however, several quantitative trait loci (QTL) and polymorphisms involved regions on chromosomes 2p, 6q, 8q and X account for variation in the γ-globin expression level. We studied the effect of interaction between a region on intron six of the TOX gene, chromosome 8q (chr8q) and XmnI locus on the γ-globin promoter, chr11p on γ-globin expression in 150 β-thalassemia intermedia (β-TI) patients, evaluated by statistical interaction analysis. Our results showed a significant interaction between one QTL on intron six of the TOX gene (rs9693712) and XmnI locus that effect γ-globin expression. Interchromosomal interaction mediates through transcriptional machanisms to preserve true genome architectural features, chromosomes localization and DNA bending. This interaction can be a part of the unknown molecular mechanism of globin switching and regulation of gene expression.

Analysis of porcine MUC4 gene as a candidate gene for prolificacy QTL on SSC13 in an Iberian × Meishan F2 population.

PubMed

Balcells, Ingrid; Castelló, Anna; Mercadé, Anna; Noguera, José L; Fernández-Rodríguez, Amanda; Sànchez, Armand; Tomàs, Anna

2011-10-31

Reproductive traits, such as prolificacy, are of great interest to the pig industry. Better understanding of their genetic architecture should help to increase the efficiency of pig productivity through the implementation of marker assisted selection (MAS) programmes. The Mucin 4 (MUC4) gene has been evaluated as a candidate gene for a prolificacy QTL described in an Iberian × Meishan (Ib × Me) F2 intercross. For association analyses, two previously described SNPs (DQ124298:g.243A>G and DQ124298:g.344A>G) were genotyped in 347 pigs from the Ib × Me population. QTL for the number of piglets born alive (NBA) and for the total number of piglets born (TNB) were confirmed on SSC13 at positions 44 cM and 51 cM, respectively. The MUC4 gene was successfully located within the confidence intervals of both QTL. Only DQ124298:g.344A>G MUC4 polymorphism was significantly associated with both NBA and TNB (P-value < 0.05) with favourable effects coming from the Meishan origin. MUC4 expression level was determined in F2 sows displaying extreme phenotypes for the number of embryos (NE) at 30-32 days of gestation. Differences in the uterine expression of MUC4 were found between high (NE ≥ 13) and low (NE ≤ 11) prolificacy sows. Overall, MUC4 expression in high prolificacy sows was almost two-fold increased compared with low prolificacy sows. Our data suggest that MUC4 could play an important role in the establishment of an optimal uterine environment that would increase embryonic survival during pig gestation.

Using probe genotypes to dissect QTL × environment interactions for grain yield components in winter wheat.

PubMed

Zheng, Bing Song; Le Gouis, Jacques; Leflon, Martine; Rong, Wen Ying; Laperche, Anne; Brancourt-Hulmel, Maryse

2010-11-01

Yield is known to be a complex trait, the expression of which interacts strongly with environmental conditions. Understanding the genetic basis of these genotype × environment interactions, particularly under limited input levels, is a key objective when selecting wheat genotypes adapted to specific environments. Our principal objectives were thus: (1) to identify genomic regions [quantitative trait loci (QTL)] involving QTL × environment interactions (QEI) and (2) to develop a strategy to understand the specificity of these regions to certain environments. The two main components of yield were studied: kernel number (KN) and thousand-kernel weight (TKW). The Arche × Récital doubled-haploid population of 222 lines was grown in replicated field trials during 2000 and 2001 at three locations in France, under two nitrogen levels. The 12 environments were characterized in terms of water deficit, radiation, temperature and nitrogen stress based on measurements conducted on the four-probe genotypes: Arche, Récital, Ritmo and Soissons. A four-step strategy was developed to explain QTL specificity to some environments: (1) the detection of QTL for KN and TKW in each environment; (2) the estimation of genotypic sensitivities as the factorial regression slope of KN and TKW to environmental covariates and the detection of QTL for these genotypic sensitivities; (3) study of the co-locations of QTL for KN and TKW and of the QTL for sensitivities; in the event of a co-location partitioning the QEI, appropriate covariates were employed; (4) a description of the environments where QTL were detected for KN and TKW using the environmental covariates. A total of 131 QTL were found to be associated with KN, TKW and their sensitivity to environmental covariates across the 12 environments. Four of these QTL, for both KN and TKW, were located on linkage groups 1B, 2D1, 4B and 5A1, and displayed pleiotropic effects. Factorial regression explained from 15.1 to 83.2% of the QEI for KN and involved three major environmental covariates: cumulative radiation-days ±3 days at meiosis, cumulative degree-days >25°C ±3 days at meiosis and nitrogen stress at flowering. For TKW, 13.5-81.8% of the effect of the QEI was partitioned and involved three major environmental covariates: water deficit from flowering to the milk stage, cumulative degree-days >0°C from the milk stage to maturity and soil water deficit at maturity. A comparative analysis was then performed on the QTL detected during this and previous studies published on QEI and some interacting QTL may be common to different genetic backgrounds. Focusing on these QTL common to different genetic backgrounds would give some guidance to understand genotype × environment interaction.

A first linkage map and downy mildew resistance QTL discovery for sweet basil (Ocimum basilicum) facilitated by double digestion restriction site associated DNA sequencing (ddRADseq).

PubMed

Pyne, Robert; Honig, Josh; Vaiciunas, Jennifer; Koroch, Adolfina; Wyenandt, Christian; Bonos, Stacy; Simon, James

2017-01-01

Limited understanding of sweet basil (Ocimum basilicum L.) genetics and genome structure has reduced efficiency of breeding strategies. This is evidenced by the rapid, worldwide dissemination of basil downy mildew (Peronospora belbahrii) in the absence of resistant cultivars. In an effort to improve available genetic resources, expressed sequence tag simple sequence repeat (EST-SSR) and single nucleotide polymorphism (SNP) markers were developed and used to genotype the MRI x SB22 F2 mapping population, which segregates for response to downy mildew. SNP markers were generated from genomic sequences derived from double digestion restriction site associated DNA sequencing (ddRADseq). Disomic segregation was observed in both SNP and EST-SSR markers providing evidence of an O. basilicum allotetraploid genome structure and allowing for subsequent analysis of the mapping population as a diploid intercross. A dense linkage map was constructed using 42 EST-SSR and 1,847 SNP markers spanning 3,030.9 cM. Multiple quantitative trait loci (QTL) model (MQM) analysis identified three QTL that explained 37-55% of phenotypic variance associated with downy mildew response across three environments. A single major QTL, dm11.1 explained 21-28% of phenotypic variance and demonstrated dominant gene action. Two minor QTL dm9.1 and dm14.1 explained 5-16% and 4-18% of phenotypic variance, respectively. Evidence is provided for an additive effect between the two minor QTL and the major QTL dm11.1 increasing downy mildew susceptibility. Results indicate that ddRADseq-facilitated SNP and SSR marker genotyping is an effective approach for mapping the sweet basil genome.

A first linkage map and downy mildew resistance QTL discovery for sweet basil (Ocimum basilicum) facilitated by double digestion restriction site associated DNA sequencing (ddRADseq)

PubMed Central

Honig, Josh; Vaiciunas, Jennifer; Koroch, Adolfina; Wyenandt, Christian; Bonos, Stacy; Simon, James

2017-01-01

Limited understanding of sweet basil (Ocimum basilicum L.) genetics and genome structure has reduced efficiency of breeding strategies. This is evidenced by the rapid, worldwide dissemination of basil downy mildew (Peronospora belbahrii) in the absence of resistant cultivars. In an effort to improve available genetic resources, expressed sequence tag simple sequence repeat (EST-SSR) and single nucleotide polymorphism (SNP) markers were developed and used to genotype the MRI x SB22 F2 mapping population, which segregates for response to downy mildew. SNP markers were generated from genomic sequences derived from double digestion restriction site associated DNA sequencing (ddRADseq). Disomic segregation was observed in both SNP and EST-SSR markers providing evidence of an O. basilicum allotetraploid genome structure and allowing for subsequent analysis of the mapping population as a diploid intercross. A dense linkage map was constructed using 42 EST-SSR and 1,847 SNP markers spanning 3,030.9 cM. Multiple quantitative trait loci (QTL) model (MQM) analysis identified three QTL that explained 37–55% of phenotypic variance associated with downy mildew response across three environments. A single major QTL, dm11.1 explained 21–28% of phenotypic variance and demonstrated dominant gene action. Two minor QTL dm9.1 and dm14.1 explained 5–16% and 4–18% of phenotypic variance, respectively. Evidence is provided for an additive effect between the two minor QTL and the major QTL dm11.1 increasing downy mildew susceptibility. Results indicate that ddRADseq-facilitated SNP and SSR marker genotyping is an effective approach for mapping the sweet basil genome. PMID:28922359

A major X-linked locus affects kidney function in mice

PubMed Central

Leduc, Magalie S.; Savage, Holly S.; Stearns, Timothy M.; Cario, Clinton L.; Walsh, Kenneth A.; Paigen, Beverly; Berndt, Annerose

2012-01-01

Chronic kidney disease is a common disease with increasing prevalence in the western population. One common reason for chronic kidney failure is diabetic nephropathy. Diabetic nephropathy and hyperglycemia are characteristics of the mouse inbred strain KK/HlJ, which is predominantly used as a model for metabolic syndrome due to its inherited glucose intolerance and insulin resistance. We used KK/HlJ, an albuminuria-sensitive strain, and C57BL/6J, an albuminuria-resistant strain, to perform a quantitative trait locus (QTL) cross to identify the genetic basis for chronic kidney failure. Albumin-creatinine-ratio (ACR) was measured in 130 F2 male offspring. One significant QTL was identified on chromosome (Chr) X and four suggestive QTLs were found on Chrs 6, 7, 12, and 13. Narrowing of the QTL region was focused on the X-linked QTL and performed by incorporating genotype and expression analyses for genes located in the region. From the 485 genes identified in the X-linked QTL region, a few candidate genes were identified using a combination of bioinformatic evidence based on genomic comparison of the parental strains and known function in urine homeostasis. Finally, this study demonstrates the significance of the X chromosome in the genetic determination of albuminuria. PMID:23011808

Assessment of gene-by-sex interaction effect on bone mineral density.

PubMed

Liu, Ching-Ti; Estrada, Karol; Yerges-Armstrong, Laura M; Amin, Najaf; Evangelou, Evangelos; Li, Guo; Minster, Ryan L; Carless, Melanie A; Kammerer, Candace M; Oei, Ling; Zhou, Yanhua; Alonso, Nerea; Dailiana, Zoe; Eriksson, Joel; García-Giralt, Natalia; Giroux, Sylvie; Husted, Lise Bjerre; Khusainova, Rita I; Koromila, Theodora; Kung, Annie Waichee; Lewis, Joshua R; Masi, Laura; Mencej-Bedrac, Simona; Nogues, Xavier; Patel, Millan S; Prezelj, Janez; Richards, J Brent; Sham, Pak Chung; Spector, Timothy; Vandenput, Liesbeth; Xiao, Su-Mei; Zheng, Hou-Feng; Zhu, Kun; Balcells, Susana; Brandi, Maria Luisa; Frost, Morten; Goltzman, David; González-Macías, Jesús; Karlsson, Magnus; Khusnutdinova, Elza K; Kollia, Panagoula; Langdahl, Bente Lomholt; Ljunggren, Osten; Lorentzon, Mattias; Marc, Janja; Mellström, Dan; Ohlsson, Claes; Olmos, José M; Ralston, Stuart H; Riancho, José A; Rousseau, François; Urreizti, Roser; Van Hul, Wim; Zarrabeitia, María T; Castano-Betancourt, Martha; Demissie, Serkalem; Grundberg, Elin; Herrera, Lizbeth; Kwan, Tony; Medina-Gómez, Carolina; Pastinen, Tomi; Sigurdsson, Gunnar; Thorleifsson, Gudmar; Vanmeurs, Joyce Bj; Blangero, John; Hofman, Albert; Liu, Yongmei; Mitchell, Braxton D; O'Connell, Jeffrey R; Oostra, Ben A; Rotter, Jerome I; Stefansson, Kari; Streeten, Elizabeth A; Styrkarsdottir, Unnur; Thorsteinsdottir, Unnur; Tylavsky, Frances A; Uitterlinden, Andre; Cauley, Jane A; Harris, Tamara B; Ioannidis, John Pa; Psaty, Bruce M; Robbins, John A; Zillikens, M Carola; Vanduijn, Cornelia M; Prince, Richard L; Karasik, David; Rivadeneira, Fernando; Kiel, Douglas P; Cupples, L Adrienne; Hsu, Yi-Hsiang

2012-10-01

Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however, the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome-wide, and performed expression quantitative trait loci (eQTL) analysis and bioinformatics network analysis. We conducted an autosomal genome-wide meta-analysis of gene-by-sex interaction on lumbar spine (LS) and femoral neck (FN) BMD in 25,353 individuals from 8 cohorts. In a second stage, we followed up the 12 top single-nucleotide polymorphisms (SNPs; p < 1 × 10(-5) ) in an additional set of 24,763 individuals. Gene-by-sex interaction and sex-specific effects were examined in these 12 SNPs. We detected one novel genome-wide significant interaction associated with LS-BMD at the Chr3p26.1-p25.1 locus, near the GRM7 gene (male effect = 0.02 and p = 3.0 × 10(-5) ; female effect = -0.007 and p = 3.3 × 10(-2) ), and 11 suggestive loci associated with either FN- or LS-BMD in discovery cohorts. However, there was no evidence for genome-wide significant (p < 5 × 10(-8) ) gene-by-sex interaction in the joint analysis of discovery and replication cohorts. Despite the large collaborative effort, no genome-wide significant evidence for gene-by-sex interaction was found to influence BMD variation in this screen of autosomal markers. If they exist, gene-by-sex interactions for BMD probably have weak effects, accounting for less than 0.08% of the variation in these traits per implicated SNP. © 2012 American Society for Bone and Mineral Research. Copyright © 2012 American Society for Bone and Mineral Research.

Genome-Wide Association and Trans-ethnic Meta-Analysis for Advanced Diabetic Kidney Disease: Family Investigation of Nephropathy and Diabetes (FIND).

PubMed

Iyengar, Sudha K; Sedor, John R; Freedman, Barry I; Kao, W H Linda; Kretzler, Matthias; Keller, Benjamin J; Abboud, Hanna E; Adler, Sharon G; Best, Lyle G; Bowden, Donald W; Burlock, Allison; Chen, Yii-Der Ida; Cole, Shelley A; Comeau, Mary E; Curtis, Jeffrey M; Divers, Jasmin; Drechsler, Christiane; Duggirala, Ravi; Elston, Robert C; Guo, Xiuqing; Huang, Huateng; Hoffmann, Michael Marcus; Howard, Barbara V; Ipp, Eli; Kimmel, Paul L; Klag, Michael J; Knowler, William C; Kohn, Orly F; Leak, Tennille S; Leehey, David J; Li, Man; Malhotra, Alka; März, Winfried; Nair, Viji; Nelson, Robert G; Nicholas, Susanne B; O'Brien, Stephen J; Pahl, Madeleine V; Parekh, Rulan S; Pezzolesi, Marcus G; Rasooly, Rebekah S; Rotimi, Charles N; Rotter, Jerome I; Schelling, Jeffrey R; Seldin, Michael F; Shah, Vallabh O; Smiles, Adam M; Smith, Michael W; Taylor, Kent D; Thameem, Farook; Thornley-Brown, Denyse P; Truitt, Barbara J; Wanner, Christoph; Weil, E Jennifer; Winkler, Cheryl A; Zager, Philip G; Igo, Robert P; Hanson, Robert L; Langefeld, Carl D

2015-08-01

Diabetic kidney disease (DKD) is the most common etiology of chronic kidney disease (CKD) in the industrialized world and accounts for much of the excess mortality in patients with diabetes mellitus. Approximately 45% of U.S. patients with incident end-stage kidney disease (ESKD) have DKD. Independent of glycemic control, DKD aggregates in families and has higher incidence rates in African, Mexican, and American Indian ancestral groups relative to European populations. The Family Investigation of Nephropathy and Diabetes (FIND) performed a genome-wide association study (GWAS) contrasting 6,197 unrelated individuals with advanced DKD with healthy and diabetic individuals lacking nephropathy of European American, African American, Mexican American, or American Indian ancestry. A large-scale replication and trans-ethnic meta-analysis included 7,539 additional European American, African American and American Indian DKD cases and non-nephropathy controls. Within ethnic group meta-analysis of discovery GWAS and replication set results identified genome-wide significant evidence for association between DKD and rs12523822 on chromosome 6q25.2 in American Indians (P = 5.74x10-9). The strongest signal of association in the trans-ethnic meta-analysis was with a SNP in strong linkage disequilibrium with rs12523822 (rs955333; P = 1.31x10-8), with directionally consistent results across ethnic groups. These 6q25.2 SNPs are located between the SCAF8 and CNKSR3 genes, a region with DKD relevant changes in gene expression and an eQTL with IPCEF1, a gene co-translated with CNKSR3. Several other SNPs demonstrated suggestive evidence of association with DKD, within and across populations. These data identify a novel DKD susceptibility locus with consistent directions of effect across diverse ancestral groups and provide insight into the genetic architecture of DKD.

Genomewide meta-analysis identifies loci associated with IGF-I and IGFBP-3 levels with impact on age-related traits.

PubMed

Teumer, Alexander; Qi, Qibin; Nethander, Maria; Aschard, Hugues; Bandinelli, Stefania; Beekman, Marian; Berndt, Sonja I; Bidlingmaier, Martin; Broer, Linda; Cappola, Anne; Ceda, Gian Paolo; Chanock, Stephen; Chen, Ming-Huei; Chen, Tai C; Chen, Yii-Der Ida; Chung, Jonathan; Del Greco Miglianico, Fabiola; Eriksson, Joel; Ferrucci, Luigi; Friedrich, Nele; Gnewuch, Carsten; Goodarzi, Mark O; Grarup, Niels; Guo, Tingwei; Hammer, Elke; Hayes, Richard B; Hicks, Andrew A; Hofman, Albert; Houwing-Duistermaat, Jeanine J; Hu, Frank; Hunter, David J; Husemoen, Lise L; Isaacs, Aaron; Jacobs, Kevin B; Janssen, Joop A M J L; Jansson, John-Olov; Jehmlich, Nico; Johnson, Simon; Juul, Anders; Karlsson, Magnus; Kilpelainen, Tuomas O; Kovacs, Peter; Kraft, Peter; Li, Chao; Linneberg, Allan; Liu, Yongmei; Loos, Ruth J F; Lorentzon, Mattias; Lu, Yingchang; Maggio, Marcello; Magi, Reedik; Meigs, James; Mellström, Dan; Nauck, Matthias; Newman, Anne B; Pollak, Michael N; Pramstaller, Peter P; Prokopenko, Inga; Psaty, Bruce M; Reincke, Martin; Rimm, Eric B; Rotter, Jerome I; Saint Pierre, Aude; Schurmann, Claudia; Seshadri, Sudha; Sjögren, Klara; Slagboom, P Eline; Strickler, Howard D; Stumvoll, Michael; Suh, Yousin; Sun, Qi; Zhang, Cuilin; Svensson, Johan; Tanaka, Toshiko; Tare, Archana; Tönjes, Anke; Uh, Hae-Won; van Duijn, Cornelia M; van Heemst, Diana; Vandenput, Liesbeth; Vasan, Ramachandran S; Völker, Uwe; Willems, Sara M; Ohlsson, Claes; Wallaschofski, Henri; Kaplan, Robert C

2016-10-01

The growth hormone/insulin-like growth factor (IGF) axis can be manipulated in animal models to promote longevity, and IGF-related proteins including IGF-I and IGF-binding protein-3 (IGFBP-3) have also been implicated in risk of human diseases including cardiovascular diseases, diabetes, and cancer. Through genomewide association study of up to 30 884 adults of European ancestry from 21 studies, we confirmed and extended the list of previously identified loci associated with circulating IGF-I and IGFBP-3 concentrations (IGF1, IGFBP3, GCKR, TNS3, GHSR, FOXO3, ASXL2, NUBP2/IGFALS, SORCS2, and CELSR2). Significant sex interactions, which were characterized by different genotype-phenotype associations between men and women, were found only for associations of IGFBP-3 concentrations with SNPs at the loci IGFBP3 and SORCS2. Analyses of SNPs, gene expression, and protein levels suggested that interplay between IGFBP3 and genes within the NUBP2 locus (IGFALS and HAGH) may affect circulating IGF-I and IGFBP-3 concentrations. The IGF-I-decreasing allele of SNP rs934073, which is an eQTL of ASXL2, was associated with lower adiposity and higher likelihood of survival beyond 90 years. The known longevity-associated variant rs2153960 (FOXO3) was observed to be a genomewide significant SNP for IGF-I concentrations. Bioinformatics analysis suggested enrichment of putative regulatory elements among these IGF-I- and IGFBP-3-associated loci, particularly of rs646776 at CELSR2. In conclusion, this study identified several loci associated with circulating IGF-I and IGFBP-3 concentrations and provides clues to the potential role of the IGF axis in mediating effects of known (FOXO3) and novel (ASXL2) longevity-associated loci. © 2016 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

Genetic susceptibility to bone and soft tissue sarcomas: a field synopsis and meta-analysis

PubMed Central

Benna, Clara; Simioni, Andrea; Pasquali, Sandro; De Boni, Davide; Rajendran, Senthilkumar; Spiro, Giovanna; Colombo, Chiara; Virgone, Calogero; DuBois, Steven G.; Gronchi, Alessandro; Rossi, Carlo Riccardo; Mocellin, Simone

2018-01-01

Background The genetic architecture of bone and soft tissue sarcomas susceptibility is yet to be elucidated. We aimed to comprehensively collect and meta-analyze the current knowledge on genetic susceptibility in these rare tumors. Methods We conducted a systematic review and meta-analysis of the evidence on the association between DNA variation and risk of developing sarcomas through searching PubMed, The Cochrane Library, Scopus and Web of Science databases. To evaluate result credibility, summary evidence was graded according to the Venice criteria and false positive report probability (FPRP) was calculated to further validate result noteworthiness. Integrative analysis of genetic and eQTL (expression quantitative trait locus) data was coupled with network and pathway analysis to explore the hypothesis that specific cell functions are involved in sarcoma predisposition. Results We retrieved 90 eligible studies comprising 47,796 subjects (cases: 14,358, 30%) and investigating 1,126 polymorphisms involving 320 distinct genes. Meta-analysis identified 55 single nucleotide polymorphisms (SNPs) significantly associated with disease risk with a high (N=9), moderate (N=38) and low (N=8) level of evidence, findings being classified as noteworthy basically only when the level of evidence was high. The estimated joint population attributable risk for three independent SNPs (rs11599754 of ZNF365/EGR2, rs231775 of CTLA4, and rs454006 of PRKCG) was 37.2%. We also identified 53 SNPs significantly associated with sarcoma risk based on single studies. Pathway analysis enabled us to propose that sarcoma predisposition might be linked especially to germline variation of genes whose products are involved in the function of the DNA repair machinery. Conclusions We built the first knowledgebase on the evidence linking DNA variation to sarcomas susceptibility, which can be used to generate mechanistic hypotheses and inform future studies in this field of oncology. PMID:29719630

Integration of multiethnic fine-mapping and genomic annotation to prioritize candidate functional SNPs at prostate cancer susceptibility regions

PubMed Central

Han, Ying; Hazelett, Dennis J.; Wiklund, Fredrik; Schumacher, Fredrick R.; Stram, Daniel O.; Berndt, Sonja I.; Wang, Zhaoming; Rand, Kristin A.; Hoover, Robert N.; Machiela, Mitchell J.; Yeager, Merideth; Burdette, Laurie; Chung, Charles C.; Hutchinson, Amy; Yu, Kai; Xu, Jianfeng; Travis, Ruth C.; Key, Timothy J.; Siddiq, Afshan; Canzian, Federico; Takahashi, Atsushi; Kubo, Michiaki; Stanford, Janet L.; Kolb, Suzanne; Gapstur, Susan M.; Diver, W. Ryan; Stevens, Victoria L.; Strom, Sara S.; Pettaway, Curtis A.; Al Olama, Ali Amin; Kote-Jarai, Zsofia; Eeles, Rosalind A.; Yeboah, Edward D.; Tettey, Yao; Biritwum, Richard B.; Adjei, Andrew A.; Tay, Evelyn; Truelove, Ann; Niwa, Shelley; Chokkalingam, Anand P.; Isaacs, William B.; Chen, Constance; Lindstrom, Sara; Le Marchand, Loic; Giovannucci, Edward L.; Pomerantz, Mark; Long, Henry; Li, Fugen; Ma, Jing; Stampfer, Meir; John, Esther M.; Ingles, Sue A.; Kittles, Rick A.; Murphy, Adam B.; Blot, William J.; Signorello, Lisa B.; Zheng, Wei; Albanes, Demetrius; Virtamo, Jarmo; Weinstein, Stephanie; Nemesure, Barbara; Carpten, John; Leske, M. Cristina; Wu, Suh-Yuh; Hennis, Anselm J. M.; Rybicki, Benjamin A.; Neslund-Dudas, Christine; Hsing, Ann W.; Chu, Lisa; Goodman, Phyllis J.; Klein, Eric A.; Zheng, S. Lilly; Witte, John S.; Casey, Graham; Riboli, Elio; Li, Qiyuan; Freedman, Matthew L.; Hunter, David J.; Gronberg, Henrik; Cook, Michael B.; Nakagawa, Hidewaki; Kraft, Peter; Chanock, Stephen J.; Easton, Douglas F.; Henderson, Brian E.; Coetzee, Gerhard A.; Conti, David V.; Haiman, Christopher A.

2015-01-01

Interpretation of biological mechanisms underlying genetic risk associations for prostate cancer is complicated by the relatively large number of risk variants (n = 100) and the thousands of surrogate SNPs in linkage disequilibrium. Here, we combined three distinct approaches: multiethnic fine-mapping, putative functional annotation (based upon epigenetic data and genome-encoded features), and expression quantitative trait loci (eQTL) analyses, in an attempt to reduce this complexity. We examined 67 risk regions using genotyping and imputation-based fine-mapping in populations of European (cases/controls: 8600/6946), African (cases/controls: 5327/5136), Japanese (cases/controls: 2563/4391) and Latino (cases/controls: 1034/1046) ancestry. Markers at 55 regions passed a region-specific significance threshold (P-value cutoff range: 3.9 × 10−4–5.6 × 10−3) and in 30 regions we identified markers that were more significantly associated with risk than the previously reported variants in the multiethnic sample. Novel secondary signals (P < 5.0 × 10−6) were also detected in two regions (rs13062436/3q21 and rs17181170/3p12). Among 666 variants in the 55 regions with P-values within one order of magnitude of the most-associated marker, 193 variants (29%) in 48 regions overlapped with epigenetic or other putative functional marks. In 11 of the 55 regions, cis-eQTLs were detected with nearby genes. For 12 of the 55 regions (22%), the most significant region-specific, prostate-cancer associated variant represented the strongest candidate functional variant based on our annotations; the number of regions increased to 20 (36%) and 27 (49%) when examining the 2 and 3 most significantly associated variants in each region, respectively. These results have prioritized subsets of candidate variants for downstream functional evaluation. PMID:26162851

Integration of multiethnic fine-mapping and genomic annotation to prioritize candidate functional SNPs at prostate cancer susceptibility regions.

PubMed

Han, Ying; Hazelett, Dennis J; Wiklund, Fredrik; Schumacher, Fredrick R; Stram, Daniel O; Berndt, Sonja I; Wang, Zhaoming; Rand, Kristin A; Hoover, Robert N; Machiela, Mitchell J; Yeager, Merideth; Burdette, Laurie; Chung, Charles C; Hutchinson, Amy; Yu, Kai; Xu, Jianfeng; Travis, Ruth C; Key, Timothy J; Siddiq, Afshan; Canzian, Federico; Takahashi, Atsushi; Kubo, Michiaki; Stanford, Janet L; Kolb, Suzanne; Gapstur, Susan M; Diver, W Ryan; Stevens, Victoria L; Strom, Sara S; Pettaway, Curtis A; Al Olama, Ali Amin; Kote-Jarai, Zsofia; Eeles, Rosalind A; Yeboah, Edward D; Tettey, Yao; Biritwum, Richard B; Adjei, Andrew A; Tay, Evelyn; Truelove, Ann; Niwa, Shelley; Chokkalingam, Anand P; Isaacs, William B; Chen, Constance; Lindstrom, Sara; Le Marchand, Loic; Giovannucci, Edward L; Pomerantz, Mark; Long, Henry; Li, Fugen; Ma, Jing; Stampfer, Meir; John, Esther M; Ingles, Sue A; Kittles, Rick A; Murphy, Adam B; Blot, William J; Signorello, Lisa B; Zheng, Wei; Albanes, Demetrius; Virtamo, Jarmo; Weinstein, Stephanie; Nemesure, Barbara; Carpten, John; Leske, M Cristina; Wu, Suh-Yuh; Hennis, Anselm J M; Rybicki, Benjamin A; Neslund-Dudas, Christine; Hsing, Ann W; Chu, Lisa; Goodman, Phyllis J; Klein, Eric A; Zheng, S Lilly; Witte, John S; Casey, Graham; Riboli, Elio; Li, Qiyuan; Freedman, Matthew L; Hunter, David J; Gronberg, Henrik; Cook, Michael B; Nakagawa, Hidewaki; Kraft, Peter; Chanock, Stephen J; Easton, Douglas F; Henderson, Brian E; Coetzee, Gerhard A; Conti, David V; Haiman, Christopher A

2015-10-01

Interpretation of biological mechanisms underlying genetic risk associations for prostate cancer is complicated by the relatively large number of risk variants (n = 100) and the thousands of surrogate SNPs in linkage disequilibrium. Here, we combined three distinct approaches: multiethnic fine-mapping, putative functional annotation (based upon epigenetic data and genome-encoded features), and expression quantitative trait loci (eQTL) analyses, in an attempt to reduce this complexity. We examined 67 risk regions using genotyping and imputation-based fine-mapping in populations of European (cases/controls: 8600/6946), African (cases/controls: 5327/5136), Japanese (cases/controls: 2563/4391) and Latino (cases/controls: 1034/1046) ancestry. Markers at 55 regions passed a region-specific significance threshold (P-value cutoff range: 3.9 × 10(-4)-5.6 × 10(-3)) and in 30 regions we identified markers that were more significantly associated with risk than the previously reported variants in the multiethnic sample. Novel secondary signals (P < 5.0 × 10(-6)) were also detected in two regions (rs13062436/3q21 and rs17181170/3p12). Among 666 variants in the 55 regions with P-values within one order of magnitude of the most-associated marker, 193 variants (29%) in 48 regions overlapped with epigenetic or other putative functional marks. In 11 of the 55 regions, cis-eQTLs were detected with nearby genes. For 12 of the 55 regions (22%), the most significant region-specific, prostate-cancer associated variant represented the strongest candidate functional variant based on our annotations; the number of regions increased to 20 (36%) and 27 (49%) when examining the 2 and 3 most significantly associated variants in each region, respectively. These results have prioritized subsets of candidate variants for downstream functional evaluation. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Genome-wide association study of antisocial personality disorder

PubMed Central

Rautiainen, M-R; Paunio, T; Repo-Tiihonen, E; Virkkunen, M; Ollila, H M; Sulkava, S; Jolanki, O; Palotie, A; Tiihonen, J

2016-01-01

The pathophysiology of antisocial personality disorder (ASPD) remains unclear. Although the most consistent biological finding is reduced grey matter volume in the frontal cortex, about 50% of the total liability to developing ASPD has been attributed to genetic factors. The contributing genes remain largely unknown. Therefore, we sought to study the genetic background of ASPD. We conducted a genome-wide association study (GWAS) and a replication analysis of Finnish criminal offenders fulfilling DSM-IV criteria for ASPD (N=370, N=5850 for controls, GWAS; N=173, N=3766 for controls and replication sample). The GWAS resulted in suggestive associations of two clusters of single-nucleotide polymorphisms at 6p21.2 and at 6p21.32 at the human leukocyte antigen (HLA) region. Imputation of HLA alleles revealed an independent association with DRB1*01:01 (odds ratio (OR)=2.19 (1.53–3.14), P=1.9 × 10-5). Two polymorphisms at 6p21.2 LINC00951–LRFN2 gene region were replicated in a separate data set, and rs4714329 reached genome-wide significance (OR=1.59 (1.37–1.85), P=1.6 × 10−9) in the meta-analysis. The risk allele also associated with antisocial features in the general population conditioned for severe problems in childhood family (β=0.68, P=0.012). Functional analysis in brain tissue in open access GTEx and Braineac databases revealed eQTL associations of rs4714329 with LINC00951 and LRFN2 in cerebellum. In humans, LINC00951 and LRFN2 are both expressed in the brain, especially in the frontal cortex, which is intriguing considering the role of the frontal cortex in behavior and the neuroanatomical findings of reduced gray matter volume in ASPD. To our knowledge, this is the first study showing genome-wide significant and replicable findings on genetic variants associated with any personality disorder. PMID:27598967

Genome-wide association study of antisocial personality disorder.

PubMed

Rautiainen, M-R; Paunio, T; Repo-Tiihonen, E; Virkkunen, M; Ollila, H M; Sulkava, S; Jolanki, O; Palotie, A; Tiihonen, J

2016-09-06

The pathophysiology of antisocial personality disorder (ASPD) remains unclear. Although the most consistent biological finding is reduced grey matter volume in the frontal cortex, about 50% of the total liability to developing ASPD has been attributed to genetic factors. The contributing genes remain largely unknown. Therefore, we sought to study the genetic background of ASPD. We conducted a genome-wide association study (GWAS) and a replication analysis of Finnish criminal offenders fulfilling DSM-IV criteria for ASPD (N=370, N=5850 for controls, GWAS; N=173, N=3766 for controls and replication sample). The GWAS resulted in suggestive associations of two clusters of single-nucleotide polymorphisms at 6p21.2 and at 6p21.32 at the human leukocyte antigen (HLA) region. Imputation of HLA alleles revealed an independent association with DRB1*01:01 (odds ratio (OR)=2.19 (1.53-3.14), P=1.9 × 10(-5)). Two polymorphisms at 6p21.2 LINC00951-LRFN2 gene region were replicated in a separate data set, and rs4714329 reached genome-wide significance (OR=1.59 (1.37-1.85), P=1.6 × 10(-9)) in the meta-analysis. The risk allele also associated with antisocial features in the general population conditioned for severe problems in childhood family (β=0.68, P=0.012). Functional analysis in brain tissue in open access GTEx and Braineac databases revealed eQTL associations of rs4714329 with LINC00951 and LRFN2 in cerebellum. In humans, LINC00951 and LRFN2 are both expressed in the brain, especially in the frontal cortex, which is intriguing considering the role of the frontal cortex in behavior and the neuroanatomical findings of reduced gray matter volume in ASPD. To our knowledge, this is the first study showing genome-wide significant and replicable findings on genetic variants associated with any personality disorder.

Genome-Wide Association and Trans-ethnic Meta-Analysis for Advanced Diabetic Kidney Disease: Family Investigation of Nephropathy and Diabetes (FIND)

PubMed Central

Kretzler, Matthias; Keller, Benjamin J.; Adler, Sharon G.; Best, Lyle G.; Bowden, Donald W.; Burlock, Allison; Chen, Yii-Der Ida; Cole, Shelley A.; Comeau, Mary E.; Curtis, Jeffrey M.; Divers, Jasmin; Drechsler, Christiane; Duggirala, Ravi; Elston, Robert C.; Guo, Xiuqing; Huang, Huateng; Hoffmann, Michael Marcus; Howard, Barbara V.; Ipp, Eli; Kimmel, Paul L.; Klag, Michael J.; Knowler, William C.; Kohn, Orly F.; Leak, Tennille S.; Leehey, David J.; Li, Man; Malhotra, Alka; März, Winfried; Nair, Viji; Nelson, Robert G.; Nicholas, Susanne B.; O’Brien, Stephen J.; Pahl, Madeleine V.; Parekh, Rulan S.; Pezzolesi, Marcus G.; Rasooly, Rebekah S.; Rotimi, Charles N.; Rotter, Jerome I.; Schelling, Jeffrey R.; Seldin, Michael F.; Shah, Vallabh O.; Smiles, Adam M.; Smith, Michael W.; Taylor, Kent D.; Thameem, Farook; Thornley-Brown, Denyse P.; Truitt, Barbara J.; Wanner, Christoph; Weil, E. Jennifer; Winkler, Cheryl A.; Zager, Philip G.; Igo, Robert P.; Hanson, Robert L.; Langefeld, Carl D.

2015-01-01

Diabetic kidney disease (DKD) is the most common etiology of chronic kidney disease (CKD) in the industrialized world and accounts for much of the excess mortality in patients with diabetes mellitus. Approximately 45% of U.S. patients with incident end-stage kidney disease (ESKD) have DKD. Independent of glycemic control, DKD aggregates in families and has higher incidence rates in African, Mexican, and American Indian ancestral groups relative to European populations. The Family Investigation of Nephropathy and Diabetes (FIND) performed a genome-wide association study (GWAS) contrasting 6,197 unrelated individuals with advanced DKD with healthy and diabetic individuals lacking nephropathy of European American, African American, Mexican American, or American Indian ancestry. A large-scale replication and trans-ethnic meta-analysis included 7,539 additional European American, African American and American Indian DKD cases and non-nephropathy controls. Within ethnic group meta-analysis of discovery GWAS and replication set results identified genome-wide significant evidence for association between DKD and rs12523822 on chromosome 6q25.2 in American Indians (P = 5.74x10-9). The strongest signal of association in the trans-ethnic meta-analysis was with a SNP in strong linkage disequilibrium with rs12523822 (rs955333; P = 1.31x10-8), with directionally consistent results across ethnic groups. These 6q25.2 SNPs are located between the SCAF8 and CNKSR3 genes, a region with DKD relevant changes in gene expression and an eQTL with IPCEF1, a gene co-translated with CNKSR3. Several other SNPs demonstrated suggestive evidence of association with DKD, within and across populations. These data identify a novel DKD susceptibility locus with consistent directions of effect across diverse ancestral groups and provide insight into the genetic architecture of DKD. PMID:26305897

Genetic mapping of new seed-expressed polyphenol oxidase genes in wheat (Triticum aestivum L.).

PubMed

Beecher, Brian S; Carter, Arron H; See, Deven R

2012-05-01

Polyphenol oxidase (PPO) enzymatic activity is a major cause in time-dependent discoloration in wheat dough products. The PPO-A1 and PPO-D1 genes have been shown to contribute to wheat kernel PPO activity. Recently a novel PPO gene family consisting of the PPO-A2, PPO-B2, and PPO-D2 genes has been identified and shown to be expressed in wheat kernels. In this study, the sequences of these five kernel PPO genes were determined for the spring wheat cultivars Louise and Penawawa. The two cultivars were found to be polymorphic at each of the PPO loci. Three novel alleles were isolated from Louise. The Louise X Penawawa mapping population was used to genetically map all five PPO genes. All map to the long arm of homeologous group 2 chromosomes. PPO-A2 was found to be located 8.9 cM proximal to PPO-A1 on the long arm of chromosome 2A. Similarly, PPO-D1 and PPO-D2 were separated by 10.7 cM on the long arm of chromosome 2D. PPO-B2 mapped to the long arm of chromosome 2B and was the site of a novel QTL for polyphenol oxidase activity. Five other PPO QTL were identified in this study. One QTL corresponds to the previously described PPO-D1 locus, one QTL corresponds to the PPO-D2 locus, whereas the remaining three are located on chromosome 2B.

Multiple Quantitative Trait Loci Influence the Shape of a Male-Specific Genital Structure in Drosophila melanogaster

PubMed Central

McNeil, Casey L.; Bain, Clint L.; Macdonald, Stuart J.

2011-01-01

The observation that male genitalia diverge more rapidly than other morphological traits during evolution is taxonomically widespread and likely due to some form of sexual selection. One way to elucidate the evolutionary forces acting on these traits is to detail the genetic architecture of variation both within and between species, a program of research that is considerably more tractable in a model system. Drosophila melanogaster and its sibling species, D. simulans, D. mauritiana, and D. sechellia, are morphologically distinguishable only by the shape of the posterior lobe, a male-specific elaboration of the genital arch. We extend earlier studies identifying quantitative trait loci (QTL) responsible for lobe divergence across species and report the first genetic dissection of lobe shape variation within a species. Using an advanced intercross mapping design, we identify three autosomal QTL contributing to the difference in lobe shape between a pair of D. melanogaster inbred lines. The QTL each contribute 4.6–10.7% to shape variation, and two show a significant epistatic interaction. Interestingly, these intraspecific QTL map to the same locations as interspecific lobe QTL, implying some shared genetic control of the trait within and between species. As a first step toward a mechanistic understanding of natural lobe shape variation, we find an association between our QTL data and a set of genes that show sex-biased expression in the developing genital imaginal disc (the precursor of the adult genitalia). These genes are good candidates to harbor naturally segregating polymorphisms contributing to posterior lobe shape. PMID:22384345

Identification of QTLs conferring resistance to downy mildews of maize in Asia.

PubMed

George, M L C; Prasanna, B M; Rathore, R S; Setty, T A S; Kasim, F; Azrai, M; Vasal, S; Balla, O; Hautea, D; Canama, A; Regalado, E; Vargas, M; Khairallah, M; Jeffers, D; Hoisington, D

2003-08-01

Downy mildew is one of the most destructive diseases of maize in subtropical and tropical regions in Asia. As a prerequisite for improving downy mildew resistance in maize, we analyzed quantitative trait loci (QTLs) involved in resistance to the important downy mildew pathogens--Peronosclerospora sorghi (sorghum downy mildew) and P. heteropogoni (Rajasthan downy mildew) in India, P. maydis (Java downy mildew) in Indonesia, P. zeae in Thailand and P. philippinensis in the Philippines--using a recombinant inbred line population derived from a cross between Ki3 (downy mildew resistant) and CML139 (susceptible). Resistance was evaluated as percentage disease incidence in replicated field trials at five downy mildew 'hotspots' in the four countries. Heritability estimates of individual environments ranged from 0.58 to 0.75 with an across environment heritability of 0.50. Composite interval mapping was applied for QTL detection using a previously constructed restriction fragment length polymorphism linkage map. The investigation resulted in the identification of six genomic regions on chromosomes 1, 2, 6, 7 and 10 involved in the resistance to the downy mildews under study, explaining, in total, 26-57% of the phenotypic variance for disease response. Most QTL alleles conferring resistance to the downy mildews were from Ki3. All QTLs showed significant QTL x environment interactions, suggesting that the expression of the QTL may be environment-dependent. A strong QTL on chromosome 6 was stable across environments, significantly affecting disease resistance at the five locations in four Asian countries. Simple-sequence repeat markers tightly linked to this QTL were identified for potential use in marker-assisted selection.

The maternally expressed WRKY transcription factor TTG2 controls lethality in interploidy crosses of Arabidopsis.

PubMed

Dilkes, Brian P; Spielman, Melissa; Weizbauer, Renate; Watson, Brian; Burkart-Waco, Diana; Scott, Rod J; Comai, Luca

2008-12-09

The molecular mechanisms underlying lethality of F1 hybrids between diverged parents are one target of speciation research. Crosses between diploid and tetraploid individuals of the same genotype can result in F1 lethality, and this dosage-sensitive incompatibility plays a role in polyploid speciation. We have identified variation in F1 lethality in interploidy crosses of Arabidopsis thaliana and determined the genetic architecture of the maternally expressed variation via QTL mapping. A single large-effect QTL, DR. STRANGELOVE 1 (DSL1), was identified as well as two QTL with epistatic relationships to DSL1. DSL1 affects the rate of postzygotic lethality via expression in the maternal sporophyte. Fine mapping placed DSL1 in an interval encoding the maternal effect transcription factor TTG2. Maternal parents carrying loss-of-function mutations in TTG2 suppressed the F1 lethality caused by paternal excess interploidy crosses. The frequency of cellularization in the endosperm was similarly affected by both natural variation and ttg2 loss-of-function mutants. The simple genetic basis of the natural variation and effects of single-gene mutations suggests that F1 lethality in polyploids could evolve rapidly. Furthermore, the role of the sporophytically active TTG2 gene in interploidy crosses indicates that the developmental programming of the mother regulates the viability of interploidy hybrid offspring.

Mapping Loci That Control Tuber and Foliar Symptoms Caused by PVY in Autotetraploid Potato (Solanum tuberosum L.).

PubMed

da Silva, Washington L; Ingram, Jason; Hackett, Christine A; Coombs, Joseph J; Douches, David; Bryan, Glenn J; De Jong, Walter; Gray, Stewart

2017-11-06

Potato tuber necrotic ringspot disease (PTNRD) is a tuber deformity associated with infection by the tuber necrotic strain of Potato virus Y (PVY NTN ). PTNRD negatively impacts tuber quality and marketability, and poses a serious threat to seed and commercial potato production worldwide. PVY NTN symptoms differ in the cultivars Waneta and Pike: Waneta expresses severe PTNRD and foliar mosaic with vein and leaf necrosis, whereas Pike does not express PTNRD and mosaic is the only foliar symptom. To map loci that influence tuber and foliar symptoms, 236 F 1 progeny of a cross between Waneta and Pike were inoculated with PVY NTN isolate NY090029 and genotyped using 12,808 potato SNPs. Foliar symptom type and severity were monitored for 10 wk, while tubers were evaluated for PTNRD expression at harvest and again after 60 d in storage. Pairwise correlation analyses indicate a strong association between PTNRD and vein necrosis (τ = 0.4195). QTL analyses revealed major-effect QTL on chromosomes 4 and 5 for mosaic, 4 for PTNRD, and 5 for foliar necrosis symptoms. Locating QTL associated with PVY-related symptoms provides a foundation for breeders to develop markers that can be used to eliminate potato clones with undesirable phenotypes, e.g. , those likely to develop PTNRD or to be symptomless carriers of PVY. Copyright © 2017 Silva et al.

Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer.

PubMed

Couch, Fergus J; Kuchenbaecker, Karoline B; Michailidou, Kyriaki; Mendoza-Fandino, Gustavo A; Nord, Silje; Lilyquist, Janna; Olswold, Curtis; Hallberg, Emily; Agata, Simona; Ahsan, Habibul; Aittomäki, Kristiina; Ambrosone, Christine; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Arun, Banu K; Arver, Brita; Barile, Monica; Barkardottir, Rosa B; Barrowdale, Daniel; Beckmann, Lars; Beckmann, Matthias W; Benitez, Javier; Blank, Stephanie V; Blomqvist, Carl; Bogdanova, Natalia V; Bojesen, Stig E; Bolla, Manjeet K; Bonanni, Bernardo; Brauch, Hiltrud; Brenner, Hermann; Burwinkel, Barbara; Buys, Saundra S; Caldes, Trinidad; Caligo, Maria A; Canzian, Federico; Carpenter, Jane; Chang-Claude, Jenny; Chanock, Stephen J; Chung, Wendy K; Claes, Kathleen B M; Cox, Angela; Cross, Simon S; Cunningham, Julie M; Czene, Kamila; Daly, Mary B; Damiola, Francesca; Darabi, Hatef; de la Hoya, Miguel; Devilee, Peter; Diez, Orland; Ding, Yuan C; Dolcetti, Riccardo; Domchek, Susan M; Dorfling, Cecilia M; Dos-Santos-Silva, Isabel; Dumont, Martine; Dunning, Alison M; Eccles, Diana M; Ehrencrona, Hans; Ekici, Arif B; Eliassen, Heather; Ellis, Steve; Fasching, Peter A; Figueroa, Jonine; Flesch-Janys, Dieter; Försti, Asta; Fostira, Florentia; Foulkes, William D; Friebel, Tara; Friedman, Eitan; Frost, Debra; Gabrielson, Marike; Gammon, Marilie D; Ganz, Patricia A; Gapstur, Susan M; Garber, Judy; Gaudet, Mia M; Gayther, Simon A; Gerdes, Anne-Marie; Ghoussaini, Maya; Giles, Graham G; Glendon, Gord; Godwin, Andrew K; Goldberg, Mark S; Goldgar, David E; González-Neira, Anna; Greene, Mark H; Gronwald, Jacek; Guénel, Pascal; Gunter, Marc; Haeberle, Lothar; Haiman, Christopher A; Hamann, Ute; Hansen, Thomas V O; Hart, Steven; Healey, Sue; Heikkinen, Tuomas; Henderson, Brian E; Herzog, Josef; Hogervorst, Frans B L; Hollestelle, Antoinette; Hooning, Maartje J; Hoover, Robert N; Hopper, John L; Humphreys, Keith; Hunter, David J; Huzarski, Tomasz; Imyanitov, Evgeny N; Isaacs, Claudine; Jakubowska, Anna; James, Paul; Janavicius, Ramunas; Jensen, Uffe Birk; John, Esther M; Jones, Michael; Kabisch, Maria; Kar, Siddhartha; Karlan, Beth Y; Khan, Sofia; Khaw, Kay-Tee; Kibriya, Muhammad G; Knight, Julia A; Ko, Yon-Dschun; Konstantopoulou, Irene; Kosma, Veli-Matti; Kristensen, Vessela; Kwong, Ava; Laitman, Yael; Lambrechts, Diether; Lazaro, Conxi; Lee, Eunjung; Le Marchand, Loic; Lester, Jenny; Lindblom, Annika; Lindor, Noralane; Lindstrom, Sara; Liu, Jianjun; Long, Jirong; Lubinski, Jan; Mai, Phuong L; Makalic, Enes; Malone, Kathleen E; Mannermaa, Arto; Manoukian, Siranoush; Margolin, Sara; Marme, Frederik; Martens, John W M; McGuffog, Lesley; Meindl, Alfons; Miller, Austin; Milne, Roger L; Miron, Penelope; Montagna, Marco; Mazoyer, Sylvie; Mulligan, Anna M; Muranen, Taru A; Nathanson, Katherine L; Neuhausen, Susan L; Nevanlinna, Heli; Nordestgaard, Børge G; Nussbaum, Robert L; Offit, Kenneth; Olah, Edith; Olopade, Olufunmilayo I; Olson, Janet E; Osorio, Ana; Park, Sue K; Peeters, Petra H; Peissel, Bernard; Peterlongo, Paolo; Peto, Julian; Phelan, Catherine M; Pilarski, Robert; Poppe, Bruce; Pylkäs, Katri; Radice, Paolo; Rahman, Nazneen; Rantala, Johanna; Rappaport, Christine; Rennert, Gad; Richardson, Andrea; Robson, Mark; Romieu, Isabelle; Rudolph, Anja; Rutgers, Emiel J; Sanchez, Maria-Jose; Santella, Regina M; Sawyer, Elinor J; Schmidt, Daniel F; Schmidt, Marjanka K; Schmutzler, Rita K; Schumacher, Fredrick; Scott, Rodney; Senter, Leigha; Sharma, Priyanka; Simard, Jacques; Singer, Christian F; Sinilnikova, Olga M; Soucy, Penny; Southey, Melissa; Steinemann, Doris; Stenmark-Askmalm, Marie; Stoppa-Lyonnet, Dominique; Swerdlow, Anthony; Szabo, Csilla I; Tamimi, Rulla; Tapper, William; Teixeira, Manuel R; Teo, Soo-Hwang; Terry, Mary B; Thomassen, Mads; Thompson, Deborah; Tihomirova, Laima; Toland, Amanda E; Tollenaar, Robert A E M; Tomlinson, Ian; Truong, Thérèse; Tsimiklis, Helen; Teulé, Alex; Tumino, Rosario; Tung, Nadine; Turnbull, Clare; Ursin, Giski; van Deurzen, Carolien H M; van Rensburg, Elizabeth J; Varon-Mateeva, Raymonda; Wang, Zhaoming; Wang-Gohrke, Shan; Weiderpass, Elisabete; Weitzel, Jeffrey N; Whittemore, Alice; Wildiers, Hans; Winqvist, Robert; Yang, Xiaohong R; Yannoukakos, Drakoulis; Yao, Song; Zamora, M Pilar; Zheng, Wei; Hall, Per; Kraft, Peter; Vachon, Celine; Slager, Susan; Chenevix-Trench, Georgia; Pharoah, Paul D P; Monteiro, Alvaro A N; García-Closas, Montserrat; Easton, Douglas F; Antoniou, Antonis C

2016-04-27

Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P<5 × 10(-8)) with oestrogen receptor (ER)-negative breast cancer and BRCA1-associated breast cancer risk. In this study, to identify new ER-negative susceptibility loci, we performed a meta-analysis of 11 genome-wide association studies (GWAS) consisting of 4,939 ER-negative cases and 14,352 controls, combined with 7,333 ER-negative cases and 42,468 controls and 15,252 BRCA1 mutation carriers genotyped on the iCOGS array. We identify four previously unidentified loci including two loci at 13q22 near KLF5, a 2p23.2 locus near WDR43 and a 2q33 locus near PPIL3 that display genome-wide significant associations with ER-negative breast cancer. In addition, 19 known breast cancer risk loci have genome-wide significant associations and 40 had moderate associations (P<0.05) with ER-negative disease. Using functional and eQTL studies we implicate TRMT61B and WDR43 at 2p23.2 and PPIL3 at 2q33 in ER-negative breast cancer aetiology. All ER-negative loci combined account for ∼11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction.

Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer

PubMed Central

Couch, Fergus J.; Kuchenbaecker, Karoline B.; Michailidou, Kyriaki; Mendoza-Fandino, Gustavo A.; Nord, Silje; Lilyquist, Janna; Olswold, Curtis; Hallberg, Emily; Agata, Simona; Ahsan, Habibul; Aittomäki, Kristiina; Ambrosone, Christine; Andrulis, Irene L.; Anton-Culver, Hoda; Arndt, Volker; Arun, Banu K.; Arver, Brita; Barile, Monica; Barkardottir, Rosa B.; Barrowdale, Daniel; Beckmann, Lars; Beckmann, Matthias W.; Benitez, Javier; Blank, Stephanie V.; Blomqvist, Carl; Bogdanova, Natalia V.; Bojesen, Stig E.; Bolla, Manjeet K.; Bonanni, Bernardo; Brauch, Hiltrud; Brenner, Hermann; Burwinkel, Barbara; Buys, Saundra S.; Caldes, Trinidad; Caligo, Maria A.; Canzian, Federico; Carpenter, Jane; Chang-Claude, Jenny; Chanock, Stephen J.; Chung, Wendy K.; Claes, Kathleen B. M.; Cox, Angela; Cross, Simon S.; Cunningham, Julie M.; Czene, Kamila; Daly, Mary B.; Damiola, Francesca; Darabi, Hatef; de la Hoya, Miguel; Devilee, Peter; Diez, Orland; Ding, Yuan C.; Dolcetti, Riccardo; Domchek, Susan M.; Dorfling, Cecilia M.; dos-Santos-Silva, Isabel; Dumont, Martine; Dunning, Alison M.; Eccles, Diana M.; Ehrencrona, Hans; Ekici, Arif B.; Eliassen, Heather; Ellis, Steve; Fasching, Peter A.; Figueroa, Jonine; Flesch-Janys, Dieter; Försti, Asta; Fostira, Florentia; Foulkes, William D.; Friebel, Tara; Friedman, Eitan; Frost, Debra; Gabrielson, Marike; Gammon, Marilie D.; Ganz, Patricia A.; Gapstur, Susan M.; Garber, Judy; Gaudet, Mia M.; Gayther, Simon A.; Gerdes, Anne-Marie; Ghoussaini, Maya; Giles, Graham G.; Glendon, Gord; Godwin, Andrew K.; Goldberg, Mark S.; Goldgar, David E.; González-Neira, Anna; Greene, Mark H.; Gronwald, Jacek; Guénel, Pascal; Gunter, Marc; Haeberle, Lothar; Haiman, Christopher A.; Hamann, Ute; Hansen, Thomas V. O.; Hart, Steven; Healey, Sue; Heikkinen, Tuomas; Henderson, Brian E.; Herzog, Josef; Hogervorst, Frans B. L.; Hollestelle, Antoinette; Hooning, Maartje J.; Hoover, Robert N.; Hopper, John L.; Humphreys, Keith; Hunter, David J.; Huzarski, Tomasz; Imyanitov, Evgeny N.; Isaacs, Claudine; Jakubowska, Anna; James, Paul; Janavicius, Ramunas; Jensen, Uffe Birk; John, Esther M.; Jones, Michael; Kabisch, Maria; Kar, Siddhartha; Karlan, Beth Y.; Khan, Sofia; Khaw, Kay-Tee; Kibriya, Muhammad G.; Knight, Julia A.; Ko, Yon-Dschun; Konstantopoulou, Irene; Kosma, Veli-Matti; Kristensen, Vessela; Kwong, Ava; Laitman, Yael; Lambrechts, Diether; Lazaro, Conxi; Lee, Eunjung; Le Marchand, Loic; Lester, Jenny; Lindblom, Annika; Lindor, Noralane; Lindstrom, Sara; Liu, Jianjun; Long, Jirong; Lubinski, Jan; Mai, Phuong L.; Makalic, Enes; Malone, Kathleen E.; Mannermaa, Arto; Manoukian, Siranoush; Margolin, Sara; Marme, Frederik; Martens, John W. M.; McGuffog, Lesley; Meindl, Alfons; Miller, Austin; Milne, Roger L.; Miron, Penelope; Montagna, Marco; Mazoyer, Sylvie; Mulligan, Anna M.; Muranen, Taru A.; Nathanson, Katherine L.; Neuhausen, Susan L.; Nevanlinna, Heli; Nordestgaard, Børge G.; Nussbaum, Robert L.; Offit, Kenneth; Olah, Edith; Olopade, Olufunmilayo I.; Olson, Janet E.; Osorio, Ana; Park, Sue K.; Peeters, Petra H.; Peissel, Bernard; Peterlongo, Paolo; Peto, Julian; Phelan, Catherine M.; Pilarski, Robert; Poppe, Bruce; Pylkäs, Katri; Radice, Paolo; Rahman, Nazneen; Rantala, Johanna; Rappaport, Christine; Rennert, Gad; Richardson, Andrea; Robson, Mark; Romieu, Isabelle; Rudolph, Anja; Rutgers, Emiel J.; Sanchez, Maria-Jose; Santella, Regina M.; Sawyer, Elinor J.; Schmidt, Daniel F.; Schmidt, Marjanka K.; Schmutzler, Rita K.; Schumacher, Fredrick; Scott, Rodney; Senter, Leigha; Sharma, Priyanka; Simard, Jacques; Singer, Christian F.; Sinilnikova, Olga M.; Soucy, Penny; Southey, Melissa; Steinemann, Doris; Stenmark-Askmalm, Marie; Stoppa-Lyonnet, Dominique; Swerdlow, Anthony; Szabo, Csilla I.; Tamimi, Rulla; Tapper, William; Teixeira, Manuel R.; Teo, Soo-Hwang; Terry, Mary B.; Thomassen, Mads; Thompson, Deborah; Tihomirova, Laima; Toland, Amanda E.; Tollenaar, Robert A. E. M.; Tomlinson, Ian; Truong, Thérèse; Tsimiklis, Helen; Teulé, Alex; Tumino, Rosario; Tung, Nadine; Turnbull, Clare; Ursin, Giski; van Deurzen, Carolien H. M.; van Rensburg, Elizabeth J.; Varon-Mateeva, Raymonda; Wang, Zhaoming; Wang-Gohrke, Shan; Weiderpass, Elisabete; Weitzel, Jeffrey N.; Whittemore, Alice; Wildiers, Hans; Winqvist, Robert; Yang, Xiaohong R.; Yannoukakos, Drakoulis; Yao, Song; Zamora, M Pilar; Zheng, Wei; Hall, Per; Kraft, Peter; Vachon, Celine; Slager, Susan; Chenevix-Trench, Georgia; Pharoah, Paul D. P.; Monteiro, Alvaro A. N.; García-Closas, Montserrat; Easton, Douglas F.; Antoniou, Antonis C.

2016-01-01

Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P<5 × 10−8) with oestrogen receptor (ER)-negative breast cancer and BRCA1-associated breast cancer risk. In this study, to identify new ER-negative susceptibility loci, we performed a meta-analysis of 11 genome-wide association studies (GWAS) consisting of 4,939 ER-negative cases and 14,352 controls, combined with 7,333 ER-negative cases and 42,468 controls and 15,252 BRCA1 mutation carriers genotyped on the iCOGS array. We identify four previously unidentified loci including two loci at 13q22 near KLF5, a 2p23.2 locus near WDR43 and a 2q33 locus near PPIL3 that display genome-wide significant associations with ER-negative breast cancer. In addition, 19 known breast cancer risk loci have genome-wide significant associations and 40 had moderate associations (P<0.05) with ER-negative disease. Using functional and eQTL studies we implicate TRMT61B and WDR43 at 2p23.2 and PPIL3 at 2q33 in ER-negative breast cancer aetiology. All ER-negative loci combined account for ∼11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction. PMID:27117709

An Integrated Genomic Approach for Rapid Delineation of Candidate Genes Regulating Agro-Morphological Traits in Chickpea

PubMed Central

Saxena, Maneesha S.; Bajaj, Deepak; Das, Shouvik; Kujur, Alice; Kumar, Vinod; Singh, Mohar; Bansal, Kailash C.; Tyagi, Akhilesh K.; Parida, Swarup K.

2014-01-01

The identification and fine mapping of robust quantitative trait loci (QTLs)/genes governing important agro-morphological traits in chickpea still lacks systematic efforts at a genome-wide scale involving wild Cicer accessions. In this context, an 834 simple sequence repeat and single-nucleotide polymorphism marker-based high-density genetic linkage map between cultivated and wild parental accessions (Cicer arietinum desi cv. ICC 4958 and Cicer reticulatum wild cv. ICC 17160) was constructed. This inter-specific genetic map comprising eight linkage groups spanned a map length of 949.4 cM with an average inter-marker distance of 1.14 cM. Eleven novel major genomic regions harbouring 15 robust QTLs (15.6–39.8% R2 at 4.2–15.7 logarithm of odds) associated with four agro-morphological traits (100-seed weight, pod and branch number/plant and plant hairiness) were identified and mapped on chickpea chromosomes. Most of these QTLs showed positive additive gene effects with effective allelic contribution from ICC 4958, particularly for increasing seed weight (SW) and pod and branch number. One robust SW-influencing major QTL region (qSW4.2) has been narrowed down by combining QTL mapping with high-resolution QTL region-specific association analysis, differential expression profiling and gene haplotype-based association/LD mapping. This enabled to delineate a strong SW-regulating ABI3VP1 transcription factor (TF) gene at trait-specific QTL interval and consequently identified favourable natural allelic variants and superior high seed weight-specific haplotypes in the upstream regulatory region of this gene showing increased transcript expression during seed development. The genes (TFs) harbouring diverse trait-regulating QTLs, once validated and fine-mapped by our developed rapid integrated genomic approach and through gene/QTL map-based cloning, can be utilized as potential candidates for marker-assisted genetic enhancement of chickpea. PMID:25335477

Altered sleep and affect in the neurotensin receptor 1 knockout mouse.

PubMed

Fitzpatrick, Karrie; Winrow, Christopher J; Gotter, Anthony L; Millstein, Joshua; Arbuzova, Janna; Brunner, Joseph; Kasarskis, Andrew; Vitaterna, Martha H; Renger, John J; Turek, Fred W

2012-07-01

Sleep and mood disorders have long been understood to have strong genetic components, and there is considerable comorbidity of sleep abnormalities and mood disorders, suggesting the involvement of common genetic pathways. Here, we examine a candidate gene implicated in the regulation of both sleep and affective behavior using a knockout mouse model. Previously, we identified a quantitative trait locus (QTL) for REM sleep amount, REM sleep bout number, and wake amount in a genetically segregating population of mice. Here, we show that traits mapping to this QTL correlated with an expression QTL for neurotensin receptor 1 (Ntsr1), a receptor for neurotensin, a ligand known to be involved in several psychiatric disorders. We examined sleep as well as behaviors indicative of anxiety and depression in the NTSR1 knockout mouse. NTSR1 knockouts had a lower percentage of sleep time spent in REM sleep in the dark phase and a larger diurnal variation in REM sleep duration than wild types under baseline conditions. Following sleep deprivation, NTSR1 knockouts exhibited more wake and less NREM rebound sleep. NTSR1 knockouts also showed increased anxious and despair behaviors. Here we illustrate a link between expression of the Ntsr1 gene and sleep traits previously associated with a particular QTL. We also demonstrate a relationship between Ntsr1 and anxiety and despair behaviors. Given the considerable evidence that anxiety and depression are closely linked with abnormalities in sleep, the data presented here provide further evidence that neurotensin and Ntsr1 may be a component of a pathway involved in both sleep and mood disorders.

A Multi-Trait, Meta-analysis for Detecting Pleiotropic Polymorphisms for Stature, Fatness and Reproduction in Beef Cattle

PubMed Central

Bolormaa, Sunduimijid; Pryce, Jennie E.; Reverter, Antonio; Zhang, Yuandan; Barendse, William; Kemper, Kathryn; Tier, Bruce; Savin, Keith; Hayes, Ben J.; Goddard, Michael E.

2014-01-01

Polymorphisms that affect complex traits or quantitative trait loci (QTL) often affect multiple traits. We describe two novel methods (1) for finding single nucleotide polymorphisms (SNPs) significantly associated with one or more traits using a multi-trait, meta-analysis, and (2) for distinguishing between a single pleiotropic QTL and multiple linked QTL. The meta-analysis uses the effect of each SNP on each of n traits, estimated in single trait genome wide association studies (GWAS). These effects are expressed as a vector of signed t-values (t) and the error covariance matrix of these t values is approximated by the correlation matrix of t-values among the traits calculated across the SNP (V). Consequently, t'V−1t is approximately distributed as a chi-squared with n degrees of freedom. An attractive feature of the meta-analysis is that it uses estimated effects of SNPs from single trait GWAS, so it can be applied to published data where individual records are not available. We demonstrate that the multi-trait method can be used to increase the power (numbers of SNPs validated in an independent population) of GWAS in a beef cattle data set including 10,191 animals genotyped for 729,068 SNPs with 32 traits recorded, including growth and reproduction traits. We can distinguish between a single pleiotropic QTL and multiple linked QTL because multiple SNPs tagging the same QTL show the same pattern of effects across traits. We confirm this finding by demonstrating that when one SNP is included in the statistical model the other SNPs have a non-significant effect. In the beef cattle data set, cluster analysis yielded four groups of QTL with similar patterns of effects across traits within a group. A linear index was used to validate SNPs having effects on multiple traits and to identify additional SNPs belonging to these four groups. PMID:24675618

QTL mapping and transcriptome analysis of cowpea reveals candidate genes for root-knot nematode resistance

PubMed Central

Ndeve, Arsenio Daniel; Huynh, Bao-Lam; Matthews, William Charles; Roberts, Philip Alan

2018-01-01

Cowpea is one of the most important food and forage legumes in drier regions of the tropics and subtropics. However, cowpea yield worldwide is markedly below the known potential due to abiotic and biotic stresses, including parasitism by root-knot nematodes (Meloidogyne spp., RKN). Two resistance genes with dominant effect, Rk and Rk2, have been reported to provide resistance against RKN in cowpea. Despite their description and use in breeding for resistance to RKN and particularly genetic mapping of the Rk locus, the exact genes conferring resistance to RKN remain unknown. In the present work, QTL mapping using recombinant inbred line (RIL) population 524B x IT84S-2049 segregating for a newly mapped locus and analysis of the transcriptome changes in two cowpea near-isogenic lines (NIL) were used to identify candidate genes for Rk and the newly mapped locus. A major QTL, designated QRk-vu9.1, associated with resistance to Meloidogyne javanica reproduction, was detected and mapped on linkage group LG9 at position 13.37 cM using egg production data. Transcriptome analysis on resistant and susceptible NILs 3 and 9 days after inoculation revealed up-regulation of 109 and 98 genes and down-regulation of 110 and 89 genes, respectively, out of 19,922 unique genes mapped to the common bean reference genome. Among the differentially expressed genes, four and nine genes were found within the QRk-vu9.1 and QRk-vu11.1 QTL intervals, respectively. Six of these genes belong to the TIR-NBS-LRR family of resistance genes and three were upregulated at one or more time-points. Quantitative RT-PCR validated gene expression to be positively correlated with RNA-seq expression pattern for eight genes. Future functional analysis of these cowpea genes will enhance our understanding of Rk-mediated resistance and identify the specific gene responsible for the resistance. PMID:29300744

QTL mapping and transcriptome analysis of cowpea reveals candidate genes for root-knot nematode resistance.

PubMed

Santos, Jansen Rodrigo Pereira; Ndeve, Arsenio Daniel; Huynh, Bao-Lam; Matthews, William Charles; Roberts, Philip Alan

2018-01-01

Cowpea is one of the most important food and forage legumes in drier regions of the tropics and subtropics. However, cowpea yield worldwide is markedly below the known potential due to abiotic and biotic stresses, including parasitism by root-knot nematodes (Meloidogyne spp., RKN). Two resistance genes with dominant effect, Rk and Rk2, have been reported to provide resistance against RKN in cowpea. Despite their description and use in breeding for resistance to RKN and particularly genetic mapping of the Rk locus, the exact genes conferring resistance to RKN remain unknown. In the present work, QTL mapping using recombinant inbred line (RIL) population 524B x IT84S-2049 segregating for a newly mapped locus and analysis of the transcriptome changes in two cowpea near-isogenic lines (NIL) were used to identify candidate genes for Rk and the newly mapped locus. A major QTL, designated QRk-vu9.1, associated with resistance to Meloidogyne javanica reproduction, was detected and mapped on linkage group LG9 at position 13.37 cM using egg production data. Transcriptome analysis on resistant and susceptible NILs 3 and 9 days after inoculation revealed up-regulation of 109 and 98 genes and down-regulation of 110 and 89 genes, respectively, out of 19,922 unique genes mapped to the common bean reference genome. Among the differentially expressed genes, four and nine genes were found within the QRk-vu9.1 and QRk-vu11.1 QTL intervals, respectively. Six of these genes belong to the TIR-NBS-LRR family of resistance genes and three were upregulated at one or more time-points. Quantitative RT-PCR validated gene expression to be positively correlated with RNA-seq expression pattern for eight genes. Future functional analysis of these cowpea genes will enhance our understanding of Rk-mediated resistance and identify the specific gene responsible for the resistance.

Restriction site polymorphism-based candidate gene mapping for seedling drought tolerance in cowpea [Vigna unguiculata (L.) Walp.].

PubMed

Muchero, Wellington; Ehlers, Jeffrey D; Roberts, Philip A

2010-02-01

Quantitative trait loci (QTL) studies provide insight into the complexity of drought tolerance mechanisms. Molecular markers used in these studies also allow for marker-assisted selection (MAS) in breeding programs, enabling transfer of genetic factors between breeding lines without complete knowledge of their exact nature. However, potential for recombination between markers and target genes limit the utility of MAS-based strategies. Candidate gene mapping offers an alternative solution to identify trait determinants underlying QTL of interest. Here, we used restriction site polymorphisms to investigate co-location of candidate genes with QTL for seedling drought stress-induced premature senescence identified previously in cowpea. Genomic DNA isolated from 113 F(2:8) RILs of drought-tolerant IT93K503-1 and drought susceptible CB46 genotypes was digested with combinations of EcoR1 and HpaII, Mse1, or Msp1 restriction enzymes and amplified with primers designed from 13 drought-responsive cDNAs. JoinMap 3.0 and MapQTL 4.0 software were used to incorporate polymorphic markers onto the AFLP map and to analyze their association with the drought response QTL. Seven markers co-located with peaks of previously identified QTL. Isolation, sequencing, and blast analysis of these markers confirmed their significant homology with drought or other abiotic stress-induced expressed sequence tags (EST) from cowpea and other plant systems. Further, homology with coding sequences for a multidrug resistance protein 3 and a photosystem I assembly protein ycf3 was revealed in two of these candidates. These results provide a platform for the identification and characterization of genetic trait determinants underlying seedling drought tolerance in cowpea.

Allelic Variation in Paralogs of GDP-l-Galactose Phosphorylase Is a Major Determinant of Vitamin C Concentrations in Apple Fruit1[C][W][OA

PubMed Central

Mellidou, Ifigeneia; Chagné, David; Laing, William A.; Keulemans, Johan; Davey, Mark W.

2012-01-01

To identify the genetic factors underlying the regulation of fruit vitamin C (l-ascorbic acid [AsA]) concentrations, quantitative trait loci (QTL) studies were carried out in an F1 progeny derived from a cross between the apple (Malus × domestica) cultivars Telamon and Braeburn over three years. QTL were identified for AsA, glutathione, total antioxidant activity in both flesh and skin tissues, and various quality traits, including flesh browning. Four regions on chromosomes 10, 11, 16, and 17 contained stable fruit AsA-QTL clusters. Mapping of AsA metabolic genes identified colocations between orthologs of GDP-l-galactose phosphorylase (GGP), dehydroascorbate reductase (DHAR), and nucleobase-ascorbate transporter within these QTL clusters. Of particular interest are the three paralogs of MdGGP, which all colocated within AsA-QTL clusters. Allelic variants of MdGGP1 and MdGGP3 derived from the cultivar Braeburn parent were also consistently associated with higher fruit total AsA concentrations both within the mapping population (up to 10-fold) and across a range of commercial apple germplasm (up to 6-fold). Striking differences in the expression of the cv Braeburn MdGGP1 allele between fruit from high- and low-AsA genotypes clearly indicate a key role for MdGGP1 in the regulation of fruit AsA concentrations, and this MdGGP allele-specific single-nucleotide polymorphism marker represents an excellent candidate for directed breeding for enhanced fruit AsA concentrations. Interestingly, colocations were also found between MdDHAR3-3 and a stable QTL for browning in the cv Telamon parent, highlighting links between the redox status of the AsA pool and susceptibility to flesh browning. PMID:23001142

Bayesian QTL mapping using genome-wide SSR markers and segregating population derived from a cross of two commercial F1 hybrids of tomato.

PubMed

Ohyama, Akio; Shirasawa, Kenta; Matsunaga, Hiroshi; Negoro, Satomi; Miyatake, Koji; Yamaguchi, Hirotaka; Nunome, Tsukasa; Iwata, Hiroyoshi; Fukuoka, Hiroyuki; Hayashi, Takeshi

2017-08-01

Using newly developed euchromatin-derived genomic SSR markers and a flexible Bayesian mapping method, 13 significant agricultural QTLs were identified in a segregating population derived from a four-way cross of tomato. So far, many QTL mapping studies in tomato have been performed for progeny obtained from crosses between two genetically distant parents, e.g., domesticated tomatoes and wild relatives. However, QTL information of quantitative traits related to yield (e.g., flower or fruit number, and total or average weight of fruits) in such intercross populations would be of limited use for breeding commercial tomato cultivars because individuals in the populations have specific genetic backgrounds underlying extremely different phenotypes between the parents such as large fruit in domesticated tomatoes and small fruit in wild relatives, which may not be reflective of the genetic variation in tomato breeding populations. In this study, we constructed F 2 population derived from a cross between two commercial F 1 cultivars in tomato to extract QTL information practical for tomato breeding. This cross corresponded to a four-way cross, because the four parental lines of the two F 1 cultivars were considered to be the founders. We developed 2510 new expressed sequence tag (EST)-based (euchromatin-derived) genomic SSR markers and selected 262 markers from these new SSR markers and publicly available SSR markers to construct a linkage map. QTL analysis for ten agricultural traits of tomato was performed based on the phenotypes and marker genotypes of F 2 plants using a flexible Bayesian method. As results, 13 QTL regions were detected for six traits by the Bayesian method developed in this study.

How to perform RT-qPCR accurately in plant species? A case study on flower colour gene expression in an azalea (Rhododendron simsii hybrids) mapping population.

PubMed

De Keyser, Ellen; Desmet, Laurence; Van Bockstaele, Erik; De Riek, Jan

2013-06-24

Flower colour variation is one of the most crucial selection criteria in the breeding of a flowering pot plant, as is also the case for azalea (Rhododendron simsii hybrids). Flavonoid biosynthesis was studied intensively in several species. In azalea, flower colour can be described by means of a 3-gene model. However, this model does not clarify pink-coloration. The last decade gene expression studies have been implemented widely for studying flower colour. However, the methods used were often only semi-quantitative or quantification was not done according to the MIQE-guidelines. We aimed to develop an accurate protocol for RT-qPCR and to validate the protocol to study flower colour in an azalea mapping population. An accurate RT-qPCR protocol had to be established. RNA quality was evaluated in a combined approach by means of different techniques e.g. SPUD-assay and Experion-analysis. We demonstrated the importance of testing noRT-samples for all genes under study to detect contaminating DNA. In spite of the limited sequence information available, we prepared a set of 11 reference genes which was validated in flower petals; a combination of three reference genes was most optimal. Finally we also used plasmids for the construction of standard curves. This allowed us to calculate gene-specific PCR efficiencies for every gene to assure an accurate quantification. The validity of the protocol was demonstrated by means of the study of six genes of the flavonoid biosynthesis pathway. No correlations were found between flower colour and the individual expression profiles. However, the combination of early pathway genes (CHS, F3H, F3'H and FLS) is clearly related to co-pigmentation with flavonols. The late pathway genes DFR and ANS are to a minor extent involved in differentiating between coloured and white flowers. Concerning pink coloration, we could demonstrate that the lower intensity in this type of flowers is correlated to the expression of F3'H. Currently in plant research, validated and qualitative RT-qPCR protocols are still rare. The protocol in this study can be implemented on all plant species to assure accurate quantification of gene expression. We have been able to correlate flower colour to the combined regulation of structural genes, both in the early and late branch of the pathway. This allowed us to differentiate between flower colours in a broader genetic background as was done so far in flower colour studies. These data will now be used for eQTL mapping to comprehend even more the regulation of this pathway.

How to perform RT-qPCR accurately in plant species? A case study on flower colour gene expression in an azalea (Rhododendron simsii hybrids) mapping population

PubMed Central

2013-01-01

Background Flower colour variation is one of the most crucial selection criteria in the breeding of a flowering pot plant, as is also the case for azalea (Rhododendron simsii hybrids). Flavonoid biosynthesis was studied intensively in several species. In azalea, flower colour can be described by means of a 3-gene model. However, this model does not clarify pink-coloration. The last decade gene expression studies have been implemented widely for studying flower colour. However, the methods used were often only semi-quantitative or quantification was not done according to the MIQE-guidelines. We aimed to develop an accurate protocol for RT-qPCR and to validate the protocol to study flower colour in an azalea mapping population. Results An accurate RT-qPCR protocol had to be established. RNA quality was evaluated in a combined approach by means of different techniques e.g. SPUD-assay and Experion-analysis. We demonstrated the importance of testing noRT-samples for all genes under study to detect contaminating DNA. In spite of the limited sequence information available, we prepared a set of 11 reference genes which was validated in flower petals; a combination of three reference genes was most optimal. Finally we also used plasmids for the construction of standard curves. This allowed us to calculate gene-specific PCR efficiencies for every gene to assure an accurate quantification. The validity of the protocol was demonstrated by means of the study of six genes of the flavonoid biosynthesis pathway. No correlations were found between flower colour and the individual expression profiles. However, the combination of early pathway genes (CHS, F3H, F3'H and FLS) is clearly related to co-pigmentation with flavonols. The late pathway genes DFR and ANS are to a minor extent involved in differentiating between coloured and white flowers. Concerning pink coloration, we could demonstrate that the lower intensity in this type of flowers is correlated to the expression of F3'H. Conclusions Currently in plant research, validated and qualitative RT-qPCR protocols are still rare. The protocol in this study can be implemented on all plant species to assure accurate quantification of gene expression. We have been able to correlate flower colour to the combined regulation of structural genes, both in the early and late branch of the pathway. This allowed us to differentiate between flower colours in a broader genetic background as was done so far in flower colour studies. These data will now be used for eQTL mapping to comprehend even more the regulation of this pathway. PMID:23800303

Allelic variations and differential expressions detected at quantitative trait loci for salt stress tolerance in wheat.

PubMed

Oyiga, Benedict C; Sharma, Ram C; Baum, Michael; Ogbonnaya, Francis C; Léon, Jens; Ballvora, Agim

2018-05-01

The increasing salinization of agricultural lands is a threat to global wheat production. Understanding of the mechanistic basis of salt tolerance (ST) is essential for developing breeding and selection strategies that would allow for increased wheat production under saline conditions to meet the increasing global demand. We used a set that consists of 150 internationally derived winter and facultative wheat cultivars genotyped with a 90K SNP chip and phenotyped for ST across three growth stages and for ionic (leaf K + and Na +  contents) traits to dissect the genetic architecture regulating ST in wheat. Genome-wide association mapping revealed 187 Single Nucleotide Polymorphism (SNPs) (R 2  = 3.00-30.67%), representing 37 quantitative trait loci (QTL), significantly associated with the ST traits. Of these, four QTL on 1BS, 2AL, 2BS and 3AL were associated with ST across the three growth stages and with the ionic traits. Novel QTL were also detected on 1BS and 1DL. Candidate genes linked to these polymorphisms were uncovered, and expression analyses were performed and validated on them under saline and non-saline conditions using transcriptomics and qRT-PCR data. Expressed sequence comparisons in contrasting ST wheat genotypes identified several non-synonymous/missense mutation sites that are contributory to the ST trait variations, indicating the biological relevance of these polymorphisms that can be exploited in breeding for ST in wheat. © 2017 The Authors. Plant, Cell & Environment published by JohnWiley & Sons Ltd.

Estimation and interpretation of genetic effects with epistasis using the NOIA model.

PubMed

Alvarez-Castro, José M; Carlborg, Orjan; Rönnegård, Lars

2012-01-01

We introduce this communication with a brief outline of the historical landmarks in genetic modeling, especially concerning epistasis. Then, we present methods for the use of genetic modeling in QTL analyses. In particular, we summarize the essential expressions of the natural and orthogonal interactions (NOIA) model of genetic effects. Our motivation for reviewing that theory here is twofold. First, this review presents a digest of the expressions for the application of the NOIA model, which are often mixed with intermediate and additional formulae in the original articles. Second, we make the required theory handy for the reader to relate the genetic concepts to the particular mathematical expressions underlying them. We illustrate those relations by providing graphical interpretations and a diagram summarizing the key features for applying genetic modeling with epistasis in comprehensive QTL analyses. Finally, we briefly review some examples of the application of NOIA to real data and the way it improves the interpretability of the results.

Ultra-high density intra-specific genetic linkage maps accelerate identification of functionally relevant molecular tags governing important agronomic traits in chickpea

PubMed Central

Kujur, Alice; Upadhyaya, Hari D.; Shree, Tanima; Bajaj, Deepak; Das, Shouvik; Saxena, Maneesha S.; Badoni, Saurabh; Kumar, Vinod; Tripathi, Shailesh; Gowda, C. L. L.; Sharma, Shivali; Singh, Sube; Tyagi, Akhilesh K.; Parida, Swarup K.

2015-01-01

We discovered 26785 and 16573 high-quality SNPs differentiating two parental genotypes of a RIL mapping population using reference desi and kabuli genome-based GBS assay. Of these, 3625 and 2177 SNPs have been integrated into eight desi and kabuli chromosomes, respectively in order to construct ultra-high density (0.20–0.37 cM) intra-specific chickpea genetic linkage maps. One of these constructed high-resolution genetic map has potential to identify 33 major genomic regions harbouring 35 robust QTLs (PVE: 17.9–39.7%) associated with three agronomic traits, which were mapped within <1 cM mean marker intervals on desi chromosomes. The extended LD (linkage disequilibrium) decay (~15 cM) in chromosomes of genetic maps have encouraged us to use a rapid integrated approach (comparative QTL mapping, QTL-region specific haplotype/LD-based trait association analysis, expression profiling and gene haplotype-based association mapping) rather than a traditional QTL map-based cloning method to narrow-down one major seed weight (SW) robust QTL region. It delineated favourable natural allelic variants and superior haplotype-containing one seed-specific candidate embryo defective gene regulating SW in chickpea. The ultra-high-resolution genetic maps, QTLs/genes and alleles/haplotypes-related genomic information generated and integrated strategy for rapid QTL/gene identification developed have potential to expedite genomics-assisted breeding applications in crop plants, including chickpea for their genetic enhancement. PMID:25942004

Systems genetics of intravenous cocaine self-administration in the BXD recombinant inbred mouse panel

PubMed Central

Dickson, Price E.; Miller, Mellessa M.; Calton, Michele A.; Bubier, Jason A.; Cook, Melloni N.; Goldowitz, Daniel; Chesler, Elissa J.; Mittleman, Guy

2015-01-01

Rationale Cocaine addiction is a major public health problem with a substantial genetic basis for which the biological mechanisms remain largely unknown. Systems genetics is a powerful method for discovering novel mechanisms underlying complex traits, and intravenous drug self-administration (IVSA) is the gold standard for assessing volitional drug use in preclinical studies. We have integrated these approaches to identify novel genes and networks underling cocaine use in mice. Methods Mice from 39 BXD strains acquired cocaine IVSA (0.56 mg/kg/infusion). Mice from 29 BXD strains completed a full dose-response curve (0.032 – 1.8 mg/kg/infusion). Results We identified independent genetic correlations between cocaine IVSA and measures of environmental exploration and cocaine sensitization. We identified genome-wide significant QTL on chromosomes 7 and 11 associated with shifts in the dose-response curve and on chromosome 16 associated with sessions to acquire cocaine IVSA. Using publicly available gene expression data from the nucleus accumbens, midbrain, and prefrontal cortex of drug-naïve mice, we identified Aplp1 and Cyfip2 as positional candidates underlying the behavioral QTL on chromosomes 7 and 11, respectively. A genome-wide significant trans-eQTL linking Fam53b (a GWAS candidate for human cocaine dependence) on chromosome 7 to the cocaine IVSA behavioral QTL on chromosome 11 was identified in the midbrain; Fam53b and Cyfip2 were co-expressed genome-wide significantly in the midbrain. This finding indicates that cocaine IVSA studies using mice can identify genes involved in human cocaine use. Conclusions These data provide novel candidate genes underlying cocaine IVSA in mice, and suggest mechanisms driving human cocaine use. PMID:26581503

Identification of a QTL in Mus musculus for Alcohol Preference, Withdrawal, and Ap3m2 Expression Using Integrative Functional Genomics and Precision Genetics

PubMed Central

Bubier, Jason A.; Jay, Jeremy J.; Baker, Christopher L.; Bergeson, Susan E.; Ohno, Hiroshi; Metten, Pamela; Crabbe, John C.; Chesler, Elissa J.

2014-01-01

Extensive genetic and genomic studies of the relationship between alcohol drinking preference and withdrawal severity have been performed using animal models. Data from multiple such publications and public data resources have been incorporated in the GeneWeaver database with >60,000 gene sets including 285 alcohol withdrawal and preference-related gene sets. Among these are evidence for positional candidates regulating these behaviors in overlapping quantitative trait loci (QTL) mapped in distinct mouse populations. Combinatorial integration of functional genomics experimental results revealed a single QTL positional candidate gene in one of the loci common to both preference and withdrawal. Functional validation studies in Ap3m2 knockout mice confirmed these relationships. Genetic validation involves confirming the existence of segregating polymorphisms that could account for the phenotypic effect. By exploiting recent advances in mouse genotyping, sequence, epigenetics, and phylogeny resources, we confirmed that Ap3m2 resides in an appropriately segregating genomic region. We have demonstrated genetic and alcohol-induced regulation of Ap3m2 expression. Although sequence analysis revealed no polymorphisms in the Ap3m2-coding region that could account for all phenotypic differences, there are several upstream SNPs that could. We have identified one of these to be an H3K4me3 site that exhibits strain differences in methylation. Thus, by making cross-species functional genomics readily computable we identified a common QTL candidate for two related bio-behavioral processes via functional evidence and demonstrate sufficiency of the genetic locus as a source of variation underlying two traits. PMID:24923803

Identification of a QTL in Mus musculus for alcohol preference, withdrawal, and Ap3m2 expression using integrative functional genomics and precision genetics.

PubMed

Bubier, Jason A; Jay, Jeremy J; Baker, Christopher L; Bergeson, Susan E; Ohno, Hiroshi; Metten, Pamela; Crabbe, John C; Chesler, Elissa J

2014-08-01

Extensive genetic and genomic studies of the relationship between alcohol drinking preference and withdrawal severity have been performed using animal models. Data from multiple such publications and public data resources have been incorporated in the GeneWeaver database with >60,000 gene sets including 285 alcohol withdrawal and preference-related gene sets. Among these are evidence for positional candidates regulating these behaviors in overlapping quantitative trait loci (QTL) mapped in distinct mouse populations. Combinatorial integration of functional genomics experimental results revealed a single QTL positional candidate gene in one of the loci common to both preference and withdrawal. Functional validation studies in Ap3m2 knockout mice confirmed these relationships. Genetic validation involves confirming the existence of segregating polymorphisms that could account for the phenotypic effect. By exploiting recent advances in mouse genotyping, sequence, epigenetics, and phylogeny resources, we confirmed that Ap3m2 resides in an appropriately segregating genomic region. We have demonstrated genetic and alcohol-induced regulation of Ap3m2 expression. Although sequence analysis revealed no polymorphisms in the Ap3m2-coding region that could account for all phenotypic differences, there are several upstream SNPs that could. We have identified one of these to be an H3K4me3 site that exhibits strain differences in methylation. Thus, by making cross-species functional genomics readily computable we identified a common QTL candidate for two related bio-behavioral processes via functional evidence and demonstrate sufficiency of the genetic locus as a source of variation underlying two traits. Copyright © 2014 by the Genetics Society of America.

Transcriptome analysis of Brassica napus pod using RNA-Seq and identification of lipid-related candidate genes.

PubMed

Xu, Hai-Ming; Kong, Xiang-Dong; Chen, Fei; Huang, Ji-Xiang; Lou, Xiang-Yang; Zhao, Jian-Yi

2015-10-24

Brassica napus is an important oilseed crop. Dissection of the genetic architecture underlying oil-related biological processes will greatly facilitates the genetic improvement of rapeseed. The differential gene expression during pod development offers a snapshot on the genes responsible for oil accumulation in. To identify candidate genes in the linkage peaks reported previously, we used RNA sequencing (RNA-Seq) technology to analyze the pod transcriptomes of German cultivar Sollux and Chinese inbred line Gaoyou. The RNA samples were collected for RNA-Seq at 5-7, 15-17 and 25-27 days after flowering (DAF). Bioinformatics analysis was performed to investigate differentially expressed genes (DEGs). Gene annotation analysis was integrated with QTL mapping and Brassica napus pod transcriptome profiling to detect potential candidate genes in oilseed. Four hundred sixty five and two thousand, one hundred fourteen candidate DEGs were identified, respectively, between two varieties at the same stages and across different periods of each variety. Then, 33 DEGs between Sollux and Gaoyou were identified as the candidate genes affecting seed oil content by combining those DEGs with the quantitative trait locus (QTL) mapping results, of which, one was found to be homologous to Arabidopsis thaliana lipid-related genes. Intervarietal DEGs of lipid pathways in QTL regions represent important candidate genes for oil-related traits. Integrated analysis of transcriptome profiling, QTL mapping and comparative genomics with other relative species leads to efficient identification of most plausible functional genes underlying oil-content related characters, offering valuable resources for bettering breeding program of Brassica napus. This study provided a comprehensive overview on the pod transcriptomes of two varieties with different oil-contents at the three developmental stages.

Genome-wide dynamics of alternative polyadenylation in rice

PubMed Central

Fu, Haihui; Yang, Dewei; Su, Wenyue; Ma, Liuyin; Shen, Yingjia; Ji, Guoli; Ye, Xinfu; Wu, Xiaohui

2016-01-01

Alternative polyadenylation (APA), in which a transcript uses one of the poly(A) sites to define its 3′-end, is a common regulatory mechanism in eukaryotic gene expression. However, the potential of APA in determining crop agronomic traits remains elusive. This study systematically tallied poly(A) sites of 14 different rice tissues and developmental stages using the poly(A) tag sequencing (PAT-seq) approach. The results indicate significant involvement of APA in developmental and quantitative trait loci (QTL) gene expression. About 48% of all expressed genes use APA to generate transcriptomic and proteomic diversity. Some genes switch APA sites, allowing differentially expressed genes to use alternate 3′ UTRs. Interestingly, APA in mature pollen is distinct where differential expression levels of a set of poly(A) factors and different distributions of APA sites are found, indicating a unique mRNA 3′-end formation regulation during gametophyte development. Equally interesting, statistical analyses showed that QTL tends to use APA for regulation of gene expression of many agronomic traits, suggesting a potential important role of APA in rice production. These results provide thus far the most comprehensive and high-resolution resource for advanced analysis of APA in crops and shed light on how APA is associated with trait formation in eukaryotes. PMID:27733415

Identifying Rare FHB-Resistant Segregants in Intransigent Backcross and F2 Winter Wheat Populations.

PubMed

Clark, Anthony J; Sarti-Dvorjak, Daniela; Brown-Guedira, Gina; Dong, Yanhong; Baik, Byung-Kee; Van Sanford, David A

2016-01-01

Fusarium head blight (FHB), caused mainly by Fusarium graminearum Schwabe [telomorph: Gibberella zeae Schwein.(Petch)] in the US, is one of the most destructive diseases of wheat (Triticum aestivum L. and T. durum L.). Infected grain is usually contaminated with deoxynivalenol (DON), a serious mycotoxin. The challenge in FHB resistance breeding is combining resistance with superior agronomic and quality characteristics. Exotic QTL are widely used to improve FHB resistance. Success depends on the genetic background into which the QTL are introgressed, whether through backcrossing or forward crossing; QTL expression is impossible to predict. In this study four high-yielding soft red winter wheat breeding lines with little or no scab resistance were each crossed to a donor parent (VA01W-476) with resistance alleles at two QTL: Fhb1 (chromosome 3BS) and QFhs.nau-2DL (chromosome 2DL) to generate backcross and F2 progeny. F2 individuals were genotyped and assigned to 4 groups according to presence/ absence of resistance alleles at one or both QTL. The effectiveness of these QTL in reducing FHB rating, incidence, index, severity, Fusarium-damaged kernels (FDK) and DON, in F2-derived lines was assessed over 2 years. Fhb1 showed an average reduction in DON of 17.5%, and conferred significant resistance in 3 of 4 populations. QFhs.nau-2DL reduced DON 6.7% on average and conferred significant resistance in 2 of 4 populations. The combination of Fhb1 and QFhs.nau-2DL resistance reduced DON 25.5% across all populations. Double resistant lines had significantly reduced DON compared to double susceptible lines in 3 populations. Backcross derived progeny were planted in replicated yield trials (2011 and 2012) and in a scab nursery in 2012. Several top yielding lines performed well in the scab nursery, with acceptable DON concentrations, even though the average effect of either QTL in this population was not significant. Population selection is often viewed as an "all or nothing" process: if the average resistance level is insufficient, the population is discarded. These results indicate that it may be possible to find rare segregants which combine scab resistance, superior agronomic performance and acceptable quality even in populations in which the average effect of the QTL is muted or negligible.

QTL and QTL x environment effects on agronomic and nitrogen acquisition traits in rice.

PubMed

Senthilvel, Senapathy; Vinod, Kunnummal Kurungara; Malarvizhi, Palaniappan; Maheswaran, Marappa

2008-09-01

Agricultural environments deteriorate due to excess nitrogen application. Breeding for low nitrogen responsive genotypes can reduce soil nitrogen input. Rice genotypes respond variably to soil available nitrogen. The present study attempted quantification of genotype x nitrogen level interaction and mapping of quantitative trait loci (QTLs) associated with nitrogen use efficiency (NUE) and other associated agronomic traits. Twelve parameters were observed across a set of 82 double haploid (DH) lines derived from IR64/Azucena. Three nitrogen regimes namely, native (0 kg/ha; no nitrogen applied), optimum (100 kg/ha) and high (200 kg/ha) replicated thrice were the environments. The parents and DH lines were significantly varying for all traits under different nitrogen regimes. All traits except plant height recorded significant genotype x environment interaction. Individual plant yield was positively correlated with nitrogen use efficiency and nitrogen uptake. Sixteen QTLs were detected by composite interval mapping. Eleven QTLs showed significant QTL x environment interactions. On chromosome 3, seven QTLs were detected associated with nitrogen use, plant yield and associated traits. A QTL region between markers RZ678, RZ574 and RZ284 was associated with nitrogen use and yield. This chromosomal region was enriched with expressed gene sequences of known key nitrogen assimilation genes.

Bioinformatics-Based Identification of Candidate Genes from QTLs Associated with Cell Wall Traits in Populus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ranjan, Priya; Yin, Tongming; Zhang, Xinye

2009-11-01

Quantitative trait locus (QTL) studies are an integral part of plant research and are used to characterize the genetic basis of phenotypic variation observed in structured populations and inform marker-assisted breeding efforts. These QTL intervals can span large physical regions on a chromosome comprising hundreds of genes, thereby hampering candidate gene identification. Genome history, evolution, and expression evidence can be used to narrow the genes in the interval to a smaller list that is manageable for detailed downstream functional genomics characterization. Our primary motivation for the present study was to address the need for a research methodology that identifies candidatemore » genes within a broad QTL interval. Here we present a bioinformatics-based approach for subdividing candidate genes within QTL intervals into alternate groups of high probability candidates. Application of this approach in the context of studying cell wall traits, specifically lignin content and S/G ratios of stem and root in Populus plants, resulted in manageable sets of genes of both known and putative cell wall biosynthetic function. These results provide a roadmap for future experimental work leading to identification of new genes controlling cell wall recalcitrance and, ultimately, in the utility of plant biomass as an energy feedstock.« less

Fine-Mapping and Selective Sweep Analysis of QTL for Cold Tolerance in Drosophila melanogaster

PubMed Central

Wilches, Ricardo; Voigt, Susanne; Duchen, Pablo; Laurent, Stefan; Stephan, Wolfgang

2014-01-01

There is a growing interest in investigating the relationship between genes with signatures of natural selection and genes identified in QTL mapping studies using combined population and quantitative genetics approaches. We dissected an X-linked interval of 6.2 Mb, which contains two QTL underlying variation in chill coma recovery time (CCRT) in Drosophila melanogaster from temperate (European) and tropical (African) regions. This resulted in two relatively small regions of 131 kb and 124 kb. The latter one co-localizes with a very strong selective sweep in the European population. We examined the genes within and near the sweep region individually using gene expression analysis and P-element insertion lines. Of the genes overlapping with the sweep, none appears to be related to CCRT. However, we have identified a new candidate gene of CCRT, brinker, which is located just outside the sweep region and is inducible by cold stress. We discuss these results in light of recent population genetics theories on quantitative traits. PMID:24970882

The Genetic Architecture of Noise-Induced Hearing Loss: Evidence for a Gene-by-Environment Interaction.

PubMed

Lavinsky, Joel; Ge, Marshall; Crow, Amanda L; Pan, Calvin; Wang, Juemei; Salehi, Pezhman; Myint, Anthony; Eskin, Eleazar; Allayee, Hooman; Lusis, Aldons J; Friedman, Rick A

2016-10-13

The discovery of environmentally specific genetic effects is crucial to the understanding of complex traits, such as susceptibility to noise-induced hearing loss (NIHL). We describe the first genome-wide association study (GWAS) for NIHL in a large and well-characterized population of inbred mouse strains, known as the Hybrid Mouse Diversity Panel (HMDP). We recorded auditory brainstem response (ABR) thresholds both pre and post 2-hr exposure to 10-kHz octave band noise at 108 dB sound pressure level in 5-6-wk-old female mice from the HMDP (4-5 mice/strain). From the observation that NIHL susceptibility varied among the strains, we performed a GWAS with correction for population structure and mapped a locus on chromosome 6 that was statistically significantly associated with two adjacent frequencies. We then used a "genetical genomics" approach that included the analysis of cochlear eQTLs to identify candidate genes within the GWAS QTL. In order to validate the gene-by-environment interaction, we compared the effects of the postnoise exposure locus with that from the same unexposed strains. The most significant SNP at chromosome 6 (rs37517079) was associated with noise susceptibility, but was not significant at the same frequencies in our unexposed study. These findings demonstrate that the genetic architecture of NIHL is distinct from that of unexposed hearing levels and provide strong evidence for gene-by-environment interactions in NIHL. Copyright © 2016 Lavinsky et al.

Genomic Regions Influencing Seminal Root Traits in Barley.

PubMed

Robinson, Hannah; Hickey, Lee; Richard, Cecile; Mace, Emma; Kelly, Alison; Borrell, Andrew; Franckowiak, Jerome; Fox, Glen

2016-03-01

Water availability is a major limiting factor for crop production, making drought adaptation and its many component traits a desirable attribute of plant cultivars. Previous studies in cereal crops indicate that root traits expressed at early plant developmental stages, such as seminal root angle and root number, are associated with water extraction at different depths. Here, we conducted the first study to map seminal root traits in barley ( L.). Using a recently developed high-throughput phenotyping method, a panel of 30 barley genotypes and a doubled-haploid (DH) population (ND24260 × 'Flagship') comprising 330 lines genotyped with diversity array technology (DArT) markers were evaluated for seminal root angle (deviation from vertical) and root number under controlled environmental conditions. A high degree of phenotypic variation was observed in the panel of 30 genotypes: 13.5 to 82.2 and 3.6 to 6.9° for root angle and root number, respectively. A similar range was observed in the DH population: 16.4 to 70.5 and 3.6 to 6.5° for root angle and number, respectively. Seven quantitative trait loci (QTL) for seminal root traits (root angle, two QTL; root number, five QTL) were detected in the DH population. A major QTL influencing both root angle and root number (/) was positioned on chromosome 5HL. Across-species analysis identified 10 common genes underlying root trait QTL in barley, wheat ( L.), and sorghum [ (L.) Moench]. Here, we provide insight into seminal root phenotypes and provide a first look at the genetics controlling these traits in barley. Copyright © 2016 Crop Science Society of America.

Multi-location wheat stripe rust QTL analysis: genetic background and epistatic interactions.

PubMed

Vazquez, M Dolores; Zemetra, Robert; Peterson, C James; Chen, Xianming M; Heesacker, Adam; Mundt, Christopher C

2015-07-01

Epistasis and genetic background were important influences on expression of stripe rust resistance in two wheat RIL populations, one with resistance conditioned by two major genes and the other conditioned by several minor QTL. Stripe rust is a foliar disease of wheat (Triticum aestivum L.) caused by the air-borne fungus Puccinia striiformis f. sp. tritici and is present in most regions around the world where commercial wheat is grown. Breeding for durable resistance to stripe rust continues to be a priority, but also is a challenge due to the complexity of interactions among resistance genes and to the wide diversity and continuous evolution of the pathogen races. The goal of this study was to detect chromosomal regions for resistance to stripe rust in two winter wheat populations, 'Tubbs'/'NSA-98-0995' (T/N) and 'Einstein'/'Tubbs' (E/T), evaluated across seven environments and mapped with diversity array technology and simple sequence repeat markers covering polymorphic regions of ≈1480 and 1117 cM, respectively. Analysis of variance for phenotypic data revealed significant (P < 0.01) genotypic differentiation for stripe rust among the recombinant inbred lines. Results for quantitative trait loci/locus (QTL) analysis in the E/T population indicated that two major QTL located in chromosomes 2AS and 6AL, with epistatic interaction between them, were responsible for the main phenotypic response. For the T/N population, eight QTL were identified, with those in chromosomes 2AL and 2BL accounting for the largest percentage of the phenotypic variance.

Population- and individual-specific regulatory variation in Sardinia.

PubMed

Pala, Mauro; Zappala, Zachary; Marongiu, Mara; Li, Xin; Davis, Joe R; Cusano, Roberto; Crobu, Francesca; Kukurba, Kimberly R; Gloudemans, Michael J; Reinier, Frederic; Berutti, Riccardo; Piras, Maria G; Mulas, Antonella; Zoledziewska, Magdalena; Marongiu, Michele; Sorokin, Elena P; Hess, Gaelen T; Smith, Kevin S; Busonero, Fabio; Maschio, Andrea; Steri, Maristella; Sidore, Carlo; Sanna, Serena; Fiorillo, Edoardo; Bassik, Michael C; Sawcer, Stephen J; Battle, Alexis; Novembre, John; Jones, Chris; Angius, Andrea; Abecasis, Gonçalo R; Schlessinger, David; Cucca, Francesco; Montgomery, Stephen B

2017-05-01

Genetic studies of complex traits have mainly identified associations with noncoding variants. To further determine the contribution of regulatory variation, we combined whole-genome and transcriptome data for 624 individuals from Sardinia to identify common and rare variants that influence gene expression and splicing. We identified 21,183 expression quantitative trait loci (eQTLs) and 6,768 splicing quantitative trait loci (sQTLs), including 619 new QTLs. We identified high-frequency QTLs and found evidence of selection near genes involved in malarial resistance and increased multiple sclerosis risk, reflecting the epidemiological history of Sardinia. Using family relationships, we identified 809 segregating expression outliers (median z score of 2.97), averaging 13.3 genes per individual. Outlier genes were enriched for proximal rare variants, providing a new approach to study large-effect regulatory variants and their relevance to traits. Our results provide insight into the effects of regulatory variants and their relationship to population history and individual genetic risk.

QTL fine mapping with Bayes C(π): a simulation study.

PubMed

van den Berg, Irene; Fritz, Sébastien; Boichard, Didier

2013-06-19

Accurate QTL mapping is a prerequisite in the search for causative mutations. Bayesian genomic selection models that analyse many markers simultaneously should provide more accurate QTL detection results than single-marker models. Our objectives were to (a) evaluate by simulation the influence of heritability, number of QTL and number of records on the accuracy of QTL mapping with Bayes Cπ and Bayes C; (b) estimate the QTL status (homozygous vs. heterozygous) of the individuals analysed. This study focussed on the ten largest detected QTL, assuming they are candidates for further characterization. Our simulations were based on a true dairy cattle population genotyped for 38,277 phased markers. Some of these markers were considered biallelic QTL and used to generate corresponding phenotypes. Different numbers of records (4387 and 1500), heritability values (0.1, 0.4 and 0.7) and numbers of QTL (10, 100 and 1000) were studied. QTL detection was based on the posterior inclusion probability for individual markers, or on the sum of the posterior inclusion probabilities for consecutive markers, estimated using Bayes C or Bayes Cπ. The QTL status of the individuals was derived from the contrast between the sums of the SNP allelic effects of their chromosomal segments. The proportion of markers with null effect (π) frequently did not reach convergence, leading to poor results for Bayes Cπ in QTL detection. Fixing π led to better results. Detection of the largest QTL was most accurate for medium to high heritability, for low to moderate numbers of QTL, and with a large number of records. The QTL status was accurately inferred when the distribution of the contrast between chromosomal segment effects was bimodal. QTL detection is feasible with Bayes C. For QTL detection, it is recommended to use a large dataset and to focus on highly heritable traits and on the largest QTL. QTL statuses were inferred based on the distribution of the contrast between chromosomal segment effects.

ACC oxidase and miRNA 159a, and their involvement in fresh fruit bunch yield (FFB) via sex ratio determination in oil palm.

PubMed

Somyong, Suthasinee; Poopear, Supannee; Sunner, Supreet Kaur; Wanlayaporn, Kitti; Jomchai, Nukoon; Yoocha, Thippawan; Ukoskit, Kittipat; Tangphatsornruang, Sithichoke; Tragoonrung, Somvong

2016-06-01

Oil palm (Elaeis guineesis Jacq.) is the most productive oil-bearing crop, yielding more oil per area than any other oil-bearing crops. However, there are still efforts to improve oil palm yield, in order to serve consumer and manufacturer demand. Oil palm produces female and male inflorescences in an alternating cycle. So, high sex ratio (SR), the ratio of female inflorescences to the total inflorescences, is a favorable trait in term of increasing yields in oil palm. This study aims to understand the genetic control for SR related traits, such as fresh fruit bunch yield (FFB), by characterizing genes at FFB quantitative trait loci (QTLs) on linkage 10 (chromosome 6) and linkage 15 (chromosome 10). Published oil palm sequences at the FFB QTLs were used to develop gene-based and simple sequence repeat (SSR) markers. We used the multiple QTL analysis model (MQM) to characterize the relationship of new markers with the SR traits in the oil palm population. The RNA expression of the most linked QTL genes was also evaluated in various tissues of oil palm. We identified EgACCO1 (encoding aminocyclopropane carboxylate (ACC) oxidase) at chromosome 10 and EgmiR159a (microRNA 159a) at chromosome 6 to be the most linked QTL genes or determinants for FFB yield and/or female inflorescence number with a phenotype variance explained (PVE) from 10.4 to 15 % and suggest that these play the important roles in sex determination and differentiation in oil palm. The strongest expression of EgACCO1 and the predicted precursor of EgmiR159a was found in ovaries and, to a lesser extent, fruit development. In addition, highly normalized expression of EgmiR159a was found in female flowers. In summary, the QTL analysis and the RNA expression reveal that EgACCO1 and EgmiR159a are the potential genetic factors involved in female flower determination and hence would affect yield in oil palm. However, to clarify how these genetic factors regulate female flower determination, more investigation of their down regulation or target may be essential. Additionally, if more sex determination genes controlled by plant hormones are identified, it may possible to reveal a crosstalk of sex determination genes with hormones and environment factors.

Rapid identification of QTLs underlying resistance to Cucumber mosaic virus in pepper (Capsicum frutescens).

PubMed

Guo, Guangjun; Wang, Shubin; Liu, Jinbing; Pan, Baogui; Diao, Weiping; Ge, Wei; Gao, Changzhou; Snyder, John C

2017-01-01

Next-generation sequencing enabled a fast discovery of QTLs controlling CMV resistant in pepper. The gene CA02g19570 as a possible candidate gene of qCmr2.1 was identified for resistance to CMV in pepper. Cucumber mosaic virus (CMV) is one of the most important viruses infecting pepper, but the genetic basis of CMV resistance in pepper is elusive. In this study, we identified a candidate gene for CMV resistance QTL, qCmr2.1 through SLAF-seq. Segregation analysis in F 2 , BC 1 and F 2:3 populations derived from a cross between two inbred lines 'PBC688' (CMV-resistant) and 'G29' (CMV-susceptible) suggested quantitative inheritance of resistance to CMV in pepper. Genome-wide comparison of SNP profiles between the CMV-resistant and CMV-susceptible bulks constructed from an F 2 population identified two QTLs, designated as qCmr2.1 on chromosome 2 and qCmr11.1 on chromosome 11 for resistance to CMV in PBC688, which were confirmed by InDel marker-based classical QTL mapping in the F 2 population. As a major QTL, joint SLAF-seq and traditional QTL analysis delimited qCmr2.1 to a 330 kb genomic region. Two pepper genes, CA02g19570 and CA02g19600, were identified in this region, which are homologous with the genes LOC104113703, LOC104248995, LOC102603934 and LOC101248357, which were predicted to encode N-like protein associated with TMV-resistant in Solanum crops. Quantitative RT-PCR revealed higher expression levels of CA02g19570 in CMV resistance genotypes. The CA02g19600 did not exhibit obvious regularity in expression patterns. Higher relative expression levels of CA02g19570 in PBC688 and F 1 were compared with those in G29 during days after inoculation. These results provide support for CA02g19570 as a possible candidate gene of qCmr2.1 for resistance to CMV in pepper.

Characterization of the Maize Chitinase Genes and Their Effect on Aspergillus flavus and Aflatoxin Accumulation Resistance

PubMed Central

Hawkins, Leigh K.; Mylroie, J. Erik; Oliveira, Dafne A.; Smith, J. Spencer; Ozkan, Seval; Windham, Gary L.; Williams, W. Paul; Warburton, Marilyn L.

2015-01-01

Maize (Zea mays L.) is a crop of global importance, but prone to contamination by aflatoxins produced by fungi in the genus Aspergillus. The development of resistant germplasm and the identification of genes contributing to resistance would aid in the reduction of the problem with a minimal need for intervention by farmers. Chitinolytic enzymes respond to attack by potential pathogens and have been demonstrated to increase insect and fungal resistance in plants. Here, all chitinase genes in the maize genome were characterized via sequence diversity and expression patterns. Recent evolution within this gene family was noted. Markers from within each gene were developed and used to map the phenotypic effect on resistance of each gene in up to four QTL mapping populations and one association panel. Seven chitinase genes were identified that had alleles associated with increased resistance to aflatoxin accumulation and A. flavus infection in field grown maize. The chitinase in bin 1.05 identified a new and highly significant QTL, while chitinase genes in bins 2.04 and 5.03 fell directly beneath the peaks of previously published QTL. The expression patterns of these genes corroborate possible grain resistance mechanisms. Markers from within the gene sequences or very closely linked to them are presented to aid in the use of marker assisted selection to improve this trait. PMID:26090679

Characterization of the Maize Chitinase Genes and Their Effect on Aspergillus flavus and Aflatoxin Accumulation Resistance.

PubMed

Hawkins, Leigh K; Mylroie, J Erik; Oliveira, Dafne A; Smith, J Spencer; Ozkan, Seval; Windham, Gary L; Williams, W Paul; Warburton, Marilyn L

2015-01-01

Maize (Zea mays L.) is a crop of global importance, but prone to contamination by aflatoxins produced by fungi in the genus Aspergillus. The development of resistant germplasm and the identification of genes contributing to resistance would aid in the reduction of the problem with a minimal need for intervention by farmers. Chitinolytic enzymes respond to attack by potential pathogens and have been demonstrated to increase insect and fungal resistance in plants. Here, all chitinase genes in the maize genome were characterized via sequence diversity and expression patterns. Recent evolution within this gene family was noted. Markers from within each gene were developed and used to map the phenotypic effect on resistance of each gene in up to four QTL mapping populations and one association panel. Seven chitinase genes were identified that had alleles associated with increased resistance to aflatoxin accumulation and A. flavus infection in field grown maize. The chitinase in bin 1.05 identified a new and highly significant QTL, while chitinase genes in bins 2.04 and 5.03 fell directly beneath the peaks of previously published QTL. The expression patterns of these genes corroborate possible grain resistance mechanisms. Markers from within the gene sequences or very closely linked to them are presented to aid in the use of marker assisted selection to improve this trait.

Distinctive roles of age, sex, and genetics in shaping transcriptional variation of human immune responses to microbial challenges.

PubMed

Piasecka, Barbara; Duffy, Darragh; Urrutia, Alejandra; Quach, Hélène; Patin, Etienne; Posseme, Céline; Bergstedt, Jacob; Charbit, Bruno; Rouilly, Vincent; MacPherson, Cameron R; Hasan, Milena; Albaud, Benoit; Gentien, David; Fellay, Jacques; Albert, Matthew L; Quintana-Murci, Lluis

2018-01-16

The contribution of host genetic and nongenetic factors to immunological differences in humans remains largely undefined. Here, we generated bacterial-, fungal-, and viral-induced immune transcriptional profiles in an age- and sex-balanced cohort of 1,000 healthy individuals and searched for the determinants of immune response variation. We found that age and sex affected the transcriptional response of most immune-related genes, with age effects being more stimulus-specific relative to sex effects, which were largely shared across conditions. Although specific cell populations mediated the effects of age and sex on gene expression, including CD8 + T cells for age and CD4 + T cells and monocytes for sex, we detected a direct effect of these intrinsic factors for the majority of immune genes. The mapping of expression quantitative trait loci (eQTLs) revealed that genetic factors had a stronger effect on immune gene regulation than age and sex, yet they affected a smaller number of genes. Importantly, we identified numerous genetic variants that manifested their regulatory effects exclusively on immune stimulation, including a Candida albicans -specific master regulator at the CR1 locus. These response eQTLs were enriched in disease-associated variants, particularly for autoimmune and inflammatory disorders, indicating that differences in disease risk may result from regulatory variants exerting their effects only in the presence of immune stress. Together, this study quantifies the respective effects of age, sex, genetics, and cellular heterogeneity on the interindividual variability of immune responses and constitutes a valuable resource for further exploration in the context of different infection risks or disease outcomes. Copyright © 2018 the Author(s). Published by PNAS.

Comprehensive analysis of Arabidopsis expression level polymorphisms with simple inheritance

PubMed Central

Plantegenet, Stephanie; Weber, Johann; Goldstein, Darlene R; Zeller, Georg; Nussbaumer, Cindy; Thomas, Jérôme; Weigel, Detlef; Harshman, Keith; Hardtke, Christian S

2009-01-01

In Arabidopsis thaliana, gene expression level polymorphisms (ELPs) between natural accessions that exhibit simple, single locus inheritance are promising quantitative trait locus (QTL) candidates to explain phenotypic variability. It is assumed that such ELPs overwhelmingly represent regulatory element polymorphisms. However, comprehensive genome-wide analyses linking expression level, regulatory sequence and gene structure variation are missing, preventing definite verification of this assumption. Here, we analyzed ELPs observed between the Eil-0 and Lc-0 accessions. Compared with non-variable controls, 5′ regulatory sequence variation in the corresponding genes is indeed increased. However, ∼42% of all the ELP genes also carry major transcription unit deletions in one parent as revealed by genome tiling arrays, representing a >4-fold enrichment over controls. Within the subset of ELPs with simple inheritance, this proportion is even higher and deletions are generally more severe. Similar results were obtained from analyses of the Bay-0 and Sha accessions, using alternative technical approaches. Collectively, our results suggest that drastic structural changes are a major cause for ELPs with simple inheritance, corroborating experimentally observed indel preponderance in cloned Arabidopsis QTL. PMID:19225455

Cotton QTLdb: a cotton QTL database for QTL analysis, visualization, and comparison between Gossypium hirsutum and G. hirsutum × G. barbadense populations.

PubMed

Said, Joseph I; Knapka, Joseph A; Song, Mingzhou; Zhang, Jinfa

2015-08-01

A specialized database currently containing more than 2200 QTL is established, which allows graphic presentation, visualization and submission of QTL. In cotton quantitative trait loci (QTL), studies are focused on intraspecific Gossypium hirsutum and interspecific G. hirsutum × G. barbadense populations. These two populations are commercially important for the textile industry and are evaluated for fiber quality, yield, seed quality, resistance, physiological, and morphological trait QTL. With meta-analysis data based on the vast amount of QTL studies in cotton it will be beneficial to organize the data into a functional database for the cotton community. Here we provide a tool for cotton researchers to visualize previously identified QTL and submit their own QTL to the Cotton QTLdb database. The database provides the user with the option of selecting various QTL trait types from either the G. hirsutum or G. hirsutum × G. barbadense populations. Based on the user's QTL trait selection, graphical representations of chromosomes of the population selected are displayed in publication ready images. The database also provides users with trait information on QTL, LOD scores, and explained phenotypic variances for all QTL selected. The CottonQTLdb database provides cotton geneticist and breeders with statistical data on cotton QTL previously identified and provides a visualization tool to view QTL positions on chromosomes. Currently the database (Release 1) contains 2274 QTLs, and succeeding QTL studies will be updated regularly by the curators and members of the cotton community that contribute their data to keep the database current. The database is accessible from http://www.cottonqtldb.org.

Changes in DNA methylation over the growing season differ between North Carolina farmworkers and non-farmworkers.

PubMed

Howard, Timothy D; Hsu, Fang-Chi; Chen, Haiying; Quandt, Sara A; Talton, Jennifer W; Summers, Phillip; Arcury, Thomas A

2016-10-01

The occupational risk to farmworkers, particularly chronic exposure to pesticides, is an acknowledged environmental and work-related health problem. Epigenetics has recently been shown to contribute to a number of complex diseases and traits, including measures of cognitive function and preclinical neurodegenerative disease. We sought to determine whether changes in DNA methylation existed between farmworker and non-farmworker populations and to identify the genes most likely involved in those changes. Eighty-three farmworkers and 60 non-farmworkers were selected from PACE4, a community-based, participatory research project comparing occupational exposures between immigrant Latino farmworker and non-farmworker manual workers. Measurements of DNA methylation were performed with the Infinium HumanMethylation450 BeadChip, at the beginning and end of the 2012 growing season. Bonferroni adjustment was used to identify significant findings (p = 1.03 × 10(-7), based on 485,000 tested methylation sites), although less stringent criteria (i.e., p ≤ 1 × 10(-6)) were used to identify sites of interest. Expression quantitative trait locus (eQTL) databases were used to help identify the most likely functional genes for each associated methylation site. Methylation at 36 CpG sites, located in or near 72 genes, differed between the two groups (p ≤ 1 × 10(-6)). The difference between the two groups was generally due to an increase in methylation in the farmworkers and a slight decrease in methylation in the non-farmworkers. Enrichment was observed in several biological pathways, including those involved in the immune response, as well as growth hormone signaling, role of BRCA1 in DNA damage response, p70S6K signaling, and PI3K signaling in B lymphocytes. We identified considerable changes in DNA methylation at 36 CpG sites over the growing season that differed between farmworkers and non-farmworkers. Dominant pathways included immune-related (HLA) processes, as well as a number of diverse biological systems. Further studies are necessary to determine which exposures or behaviors are responsible for the observed changes, and whether these changes eventually lead to disease-related phenotypes in this population.

Gene-centric meta-analyses for central adiposity traits in up to 57 412 individuals of European descent confirm known loci and reveal several novel associations

PubMed Central

Yoneyama, Sachiko; Guo, Yiran; Lanktree, Matthew B.; Barnes, Michael R.; Elbers, Clara C.; Karczewski, Konrad J; Padmanabhan, Sandosh; Bauer, Florianne; Baumert, Jens; Beitelshees, Amber; Berenson, Gerald S.; Boer, Jolanda M.A.; Burke, Gregory; Cade, Brian; Chen, Wei; Cooper-Dehoff, Rhonda M.; Gaunt, Tom R.; Gieger, Christian; Gong, Yan; Gorski, Mathias; Heard-Costa, Nancy; Johnson, Toby; Lamonte, Michael J.; Mcdonough, Caitrin; Monda, Keri L.; Onland-Moret, N. Charlotte; Nelson, Christopher P.; O'Connell, Jeffrey R.; Ordovas, Jose; Peter, Inga; Peters, Annette; Shaffer, Jonathan; Shen, Haiqinq; Smith, Erin; Speilotes, Liz; Thomas, Fridtjof; Thorand, Barbara; Monique Verschuren, W. M.; Anand, Sonia S.; Dominiczak, Anna; Davidson, Karina W.; Hegele, Robert A.; Heid, Iris; Hofker, Marten H.; Huggins, Gordon S.; Illig, Thomas; Johnson, Julie A.; Kirkland, Susan; König, Wolfgang; Langaee, Taimour Y.; Mccaffery, Jeanne; Melander, Olle; Mitchell, Braxton D.; Munroe, Patricia; Murray, Sarah S.; Papanicolaou, George; Redline, Susan; Reilly, Muredach; Samani, Nilesh J.; Schork, Nicholas J.; Van Der Schouw, Yvonne T.; Shimbo, Daichi; Shuldiner, Alan R.; Tobin, Martin D.; Wijmenga, Cisca; Yusuf, Salim; Hakonarson, Hakon; Lange, Leslie A.; Demerath, Ellen W; Fox, Caroline S.; North, Kari E; Reiner, Alex P.; Keating, Brendan; Taylor, Kira C.

2014-01-01

Waist circumference (WC) and waist-to-hip ratio (WHR) are surrogate measures of central adiposity that are associated with adverse cardiovascular events, type 2 diabetes and cancer independent of body mass index (BMI). WC and WHR are highly heritable with multiple susceptibility loci identified to date. We assessed the association between SNPs and BMI-adjusted WC and WHR and unadjusted WC in up to 57 412 individuals of European descent from 22 cohorts collaborating with the NHLBI's Candidate Gene Association Resource (CARe) project. The study population consisted of women and men aged 20–80 years. Study participants were genotyped using the ITMAT/Broad/CARE array, which includes ∼50 000 cosmopolitan tagged SNPs across ∼2100 cardiovascular-related genes. Each trait was modeled as a function of age, study site and principal components to control for population stratification, and we conducted a fixed-effects meta-analysis. No new loci for WC were observed. For WHR analyses, three novel loci were significantly associated (P < 2.4 × 10−6). Previously unreported rs2811337-G near TMCC1 was associated with increased WHR (β ± SE, 0.048 ± 0.008, P = 7.7 × 10−9) as was rs7302703-G in HOXC10 (β = 0.044 ± 0.008, P = 2.9 × 10−7) and rs936108-C in PEMT (β = 0.035 ± 0.007, P = 1.9 × 10−6). Sex-stratified analyses revealed two additional novel signals among females only, rs12076073-A in SHC1 (β = 0.10 ± 0.02, P = 1.9 × 10−6) and rs1037575-A in ATBDB4 (β = 0.046 ± 0.01, P = 2.2 × 10−6), supporting an already established sexual dimorphism of central adiposity-related genetic variants. Functional analysis using ENCODE and eQTL databases revealed that several of these loci are in regulatory regions or regions with differential expression in adipose tissue. PMID:24345515

Genetics of Species Differences in the Wild Annual Sunflowers, Helianthus annuus and H. petiolaris

PubMed Central

Lexer, Christian; Rosenthal, David M.; Raymond, Olivier; Donovan, Lisa A.; Rieseberg, Loren H.

2005-01-01

Much of our knowledge of speciation genetics stems from quantitative trait locus (QTL) studies. However, interpretations of the size and distribution of QTL underlying species differences are complicated by differences in the way QTL magnitudes are estimated. Also, many studies fail to exploit information about QTL directions or to compare inter- and intraspecific QTL variation. Here, we comprehensively analyze an extensive QTL data set for an interspecific backcross between two wild annual sunflowers, Helianthus annuus and H. petiolaris, interpret different estimates of QTL magnitudes, identify trait groups that have diverged through selection, and compare inter- and intraspecific QTL magnitudes. Our results indicate that even minor QTL (in terms of backcross variance) may be surprisingly large compared to levels of standing variation in the parental species or phenotypic differences between them. Morphological traits, particularly flower morphology, were more strongly or consistently selected than life history or physiological traits. Also, intraspecific QTL were generally smaller than interspecific ones, consistent with the prediction that larger QTL are more likely to spread to fixation across a subdivided population. Our results inform the genetics of species differences in Helianthus and suggest an approach for the simultaneous mapping of inter- and intraspecific QTL. PMID:15545657

Adult Plant Leaf Rust Resistance Derived from Toropi Wheat is Conditioned by Lr78 and Three Minor QTL.

PubMed

Kolmer, J A; Bernardo, A; Bai, G; Hayden, M J; Chao, S

2018-02-01

Leaf rust caused by Puccinia triticina is an important disease of wheat in many regions worldwide. Durable or long-lasting leaf rust resistance has been difficult to achieve because populations of P. triticina are highly variable for virulence to race-specific resistance genes, and respond to selection by resistance genes in released wheat cultivars. The wheat cultivar Toropi, developed and grown in Brazil, was noted to have long-lasting leaf rust resistance that was effective only in adult plants. The objectives of this study were to determine the chromosome location of the leaf rust resistance genes derived from Toropi in two populations of recombinant inbred lines in a partial Thatcher wheat background. In the first population, a single gene with major effects on chromosome 5DS that mapped 2.2 centimorgans distal to IWA6289, strongly reduced leaf rust severity in all 3 years of field plot tests. This gene for adult plant leaf rust resistance was designated as Lr78. In the second population, quantitative trait loci (QTL) with small effects on chromosomes 1BL, 3BS, and 4BS were found. These QTL expressed inconsistently over 4 years of field plot tests. The adult plant leaf rust resistance derived from Toropi involved a complex combination of QTL with large and small effects.

A single major QTL controls expression of larval Cry1F resistance trait in Ostrinia nubilalis (Lepidoptera: Crambidae) and is independent of midgut receptor genes

USDA-ARS?s Scientific Manuscript database

European corn borer, Ostrinia nubilalis (Lepidoptera: Crambidae), is an introduced crop pest in North America that causes major damage to corn, and reduces yield of food, feed, and biofuel materials. Transgenic hybrid corn expressing the Bacillus thuringiensis (Bt) toxin Cry1F is highly lethal to O...

Comprehensive QTL mapping survey dissects the complex fruit texture physiology in apple (Malus x domestica Borkh.).

PubMed

Longhi, Sara; Moretto, Marco; Viola, Roberto; Velasco, Riccardo; Costa, Fabrizio

2012-02-01

Fruit ripening is a complex physiological process in plants whereby cell wall programmed changes occur mainly to promote seed dispersal. Cell wall modification also directly regulates the textural properties, a fundamental aspect of fruit quality. In this study, two full-sib populations of apple, with 'Fuji' as the common maternal parent, crossed with 'Delearly' and 'Pink Lady', were used to understand the control of fruit texture by QTL mapping and in silico gene mining. Texture was dissected with a novel high resolution phenomics strategy, simultaneously profiling both mechanical and acoustic fruit texture components. In 'Fuji × Delearly' nine linkage groups were associated with QTLs accounting from 15.6% to 49% of the total variance, and a highly significant QTL cluster for both textural components was mapped on chromosome 10 and co-located with Md-PG1, a polygalacturonase gene that, in apple, is known to be involved in cell wall metabolism processes. In addition, other candidate genes related to Md-NOR and Md-RIN transcription factors, Md-Pel (pectate lyase), and Md-ACS1 were mapped within statistical intervals. In 'Fuji × Pink Lady', a smaller set of linkage groups associated with the QTLs identified for fruit texture (15.9-34.6% variance) was observed. The analysis of the phenotypic variance over a two-dimensional PCA plot highlighted a transgressive segregation for this progeny, revealing two QTL sets distinctively related to both mechanical and acoustic texture components. The mining of the apple genome allowed the discovery of the gene inventory underlying each QTL, and functional profile assessment unravelled specific gene expression patterns of these candidate genes.

QTL analysis of dietary obesity in C57BL/6byj X 129P3/J F2 mice: diet- and sex-dependent effects.

PubMed

Lin, Cailu; Theodorides, Maria L; McDaniel, Amanda H; Tordoff, Michael G; Zhang, Qinmin; Li, Xia; Bosak, Natalia; Bachmanov, Alexander A; Reed, Danielle R

2013-01-01

Obesity is a heritable trait caused by complex interactions between genes and environment, including diet. Gene-by-diet interactions are difficult to study in humans because the human diet is hard to control. Here, we used mice to study dietary obesity genes, by four methods. First, we bred 213 F2 mice from strains that are susceptible [C57BL/6ByJ (B6)] or resistant [129P3/J (129)] to dietary obesity. Percent body fat was assessed after mice ate low-energy diet and again after the same mice ate high-energy diet for 8 weeks. Linkage analyses identified QTLs associated with dietary obesity. Three methods were used to filter candidate genes within the QTL regions: (a) association mapping was conducted using >40 strains; (b) differential gene expression and (c) comparison of genomic DNA sequence, using two strains closely related to the progenitor strains from Experiment 1. The QTL effects depended on whether the mice were male or female or which diet they were recently fed. After feeding a low-energy diet, percent body fat was linked to chr 7 (LOD=3.42). After feeding a high-energy diet, percent body fat was linked to chr 9 (Obq5; LOD=3.88), chr 12 (Obq34; LOD=3.88), and chr 17 (LOD=4.56). The Chr 7 and 12 QTLs were sex dependent and all QTL were diet-dependent. The combination of filtering methods highlighted seven candidate genes within the QTL locus boundaries: Crx, Dmpk, Ahr, Mrpl28, Glo1, Tubb5, and Mut. However, these filtering methods have limitations so gene identification will require alternative strategies, such as the construction of congenics with very small donor regions.

Verification of QTL for Grain Starch Content and Its Genetic Correlation with Oil Content Using Two Connected RIL Populations in High-Oil Maize

PubMed Central

Yang, Guohu; Dong, Yongbin; Li, Yuling; Wang, Qilei; Shi, Qingling; Zhou, Qiang

2013-01-01

Grain oil content is negatively correlated with starch content in maize in general. In this study, 282 and 263 recombinant inbred lines (RIL) developed from two crosses between one high-oil maize inbred and two normal dent maize inbreds were evaluated for grain starch content and its correlation with oil content under four environments. Single-trait QTL for starch content in single-population and joint-population analysis, and multiple-trait QTL for both starch and oil content were detected, and compared with the result obtained in the two related F2∶3 populations. Totally, 20 single-population QTL for grain starch content were detected. No QTL was simultaneously detected across all ten cases. QTL at bins 5.03 and 9.03 were all detected in both populations and in 4 and 5 cases, respectively. Only 2 of the 16 joint-population QTL had significant effects in both populations. Three single-population QTL and 8 joint-population QTL at bins 1.03, 1.04–1.05, 3.05, 8.04–8.05, 9.03, and 9.05 could be considered as fine-mapped. Common QTL across F2∶3 and RIL generations were observed at bins 5.04, 8.04 and 8.05 in population 1 (Pop.1), and at bin 5.03 in population 2 (Pop.2). QTL at bins 3.02–3.03, 3.05, 8.04–8.05 and 9.03 should be focused in high-starch maize breeding. In multiple-trait QTL analysis, 17 starch-oil QTL were detected, 10 in Pop.1 and 7 in Pop.2. And 22 single-trait QTL failed to show significance in multiple-trait analysis, 13 QTL for starch content and 9 QTL for oil content. However, QTL at bins 1.03, 6.03–6.04 and 8.03–8.04 might increase grain starch content and/or grain oil content without reduction in another trait. Further research should be conducted to validate the effect of these QTL in the simultaneous improvement of grain starch and oil content in maize. PMID:23320103

Deciphering mechanisms underlying the genetic variation of general production and liver quality traits in the overfed mule duck by pQTL analyses.

PubMed

François, Yoannah; Vignal, Alain; Molette, Caroline; Marty-Gasset, Nathalie; Davail, Stéphane; Liaubet, Laurence; Marie-Etancelin, Christel

2017-04-19

The aim of this study was to analyse the mechanisms that underlie phenotypic quantitative trait loci (QTL) in overfed mule ducks by identifying co-localized proteomic QTL (pQTL). The QTL design consisted of three families of common ducks that were progeny-tested by using 294 male mule ducks. This population of common ducks was genotyped using a genetic map that included 334 genetic markers located across 28 APL chromosomes (APL for Anas platyrhynchos). Mule ducks were phenotyped for 49 traits related to growth, metabolism, overfeeding ability and meat and fatty liver quality, and 326 soluble fatty liver proteins were quantified. One hundred and seventy-six pQTL and 80 phenotypic QTL were detected at the 5% chromosome-wide significance threshold. The great majority of the identified pQTL were trans-acting and localized on a chromosome other than that carrying the coding gene. The most significant pQTL (1% genome-wide significance) were found for alpha-enolase on APL18 and fatty acid synthase on APL24. Some proteins were associated with numerous pQTL (for example, 17 and 14 pQTL were detected for alpha-enolase and apolipoprotein A1, respectively) and pQTL hotspots were observed on some chromosomes (APL18, 24, 25 and 29). We detected 66 co-localized phenotypic QTL and pQTL for which the significance of the two-trait QTL (2t-QTL) analysis was higher than that of the strongest QTL using a single-trait approach. Among these, 16 2t-QTL were pleiotropic. For example, on APL15, melting rate and abundance of two alpha-enolase spots appeared to be impacted by a single locus that is involved in the glycolytic process. On APLZ, we identified a pleiotropic QTL that modified both the blood level of glucose at the beginning of the force-feeding period and the concentration of glutamate dehydrogenase, which, in humans, is involved in increased glucose absorption by the liver when the glutamate dehydrogenase 1 gene is mutated. We identified pleiotropic loci that affect metabolic pathways linked to glycolysis or lipogenesis, and in the end to fatty liver quality. Further investigation, via transcriptomics and metabolomics approaches, is required to confirm the biomarkers that were found to impact the genetic variability of these phenotypic traits.

Quantitative trait loci and metabolic pathways: genetic control of the concentration of maysin, a corn earworm resistance factor, in maize silks.

PubMed Central

Byrne, P F; McMullen, M D; Snook, M E; Musket, T A; Theuri, J M; Widstrom, N W; Wiseman, B R; Coe, E H

1996-01-01

Interpretation of quantitative trait locus (QTL) studies of agronomic traits is limited by lack of knowledge of biochemical pathways leading to trait expression. To more fully elucidate the biological significance of detected QTL, we chose a trait that is the product of a well-characterized pathway, namely the concentration of maysin, a C-glycosyl flavone, in silks of maize, Zea mays L. Maysin is a host-plant resistance factor against the corn earworm, Helicoverpa zea (Boddie). We determined silk maysin concentrations and restriction fragment length polymorphism genotypes at flavonoid pathway loci or linked markers for 285 F2 plants derived from the cross of lines GT114 and GT119. Single-factor analysis of variance indicated that the p1 region on chromosome 1 accounted for 58.0% of the phenotypic variance and showed additive gene action. The p1 locus is a transcription activator for portions of the flavonoid pathway. A second QTL, represented by marker umc 105a near the brown pericarp1 locus on chromosome 9, accounted for 10.8% of the variance. Gene action of this region was dominant for low maysin, but was only expressed in the presence of a functional p1 allele. The model explaining the greatest proportion of phenotypic variance (75.9%) included p1, umc105a, umc166b (chromosome 1), r1 (chromosome 10), and two epistatic interaction terms, p1 x umc105a and p1 x r1. Our results provide evidence that regulatory loci have a central role and that there is a complex interplay among different branches of the flavonoid pathway in the expression of this trait. PMID:11607699

Sex-dependent genetic effects on immune responses to a parasitic nematode.

PubMed

Hayes, Kelly S; Hager, Reinmar; Grencis, Richard K

2014-03-14

Many disease aetiologies have sex specific effects, which have important implications for disease management. It is now becoming increasingly evident that such effects are the result of the differential expression of autosomal genes rather than sex-specific genes. Such sex-specific variation in the response to Trichuris muris, a murine parasitic nematode infection and model for the human parasitic nematode T. trichiura, has been well documented, however, the underlying genetic causes of these differences have been largely neglected. We used the BXD mouse set of recombinant inbred strains to identify sex-specific loci that contribute to immune phenotypes in T. muris infection. Response phenotypes to T. muris infection were found to be highly variable between different lines of BXD mice. A significant QTL on chromosome 5 (TM5) associated with IFN-γ production was found in male mice but not in female mice. This QTL was in the same location as a suggestive QTL for TNF-α and IL-6 production in male mice suggesting a common control of these pro-inflammatory cytokines. A second QTL was identified on chromosome 4 (TM4) affecting worm burden in both male and female cohorts. We have identified several genes as potential candidates for modifying responses to T. muris infection. We have used the largest mammalian genetic model system, the BXD mouse population, to identify candidate genes with sex-specific effects in immune responses to T. muris infection. Some of these genes may be differentially expressed in male and female mice leading to the difference in immune response between the sexes reported in previous studies. Our study further highlights the importance of considering sex as an important factor in investigations of immune response at the genome-wide level, in particular the bias that can be introduced when generalizing results obtained from only one sex or a mixed sex population. Rather, analyses of interaction effects between sex and genotype should be part of future studies.

Comparative Transcriptome Profiles of Near-Isogenic Hexaploid Wheat Lines Differing for Effective Alleles at the 2DL FHB Resistance QTL

PubMed Central

Biselli, Chiara; Bagnaresi, Paolo; Faccioli, Primetta; Hu, Xinkun; Balcerzak, Margaret; Mattera, Maria G.; Yan, Zehong; Ouellet, Therese; Cattivelli, Luigi; Valè, Giampiero

2018-01-01

Fusarium head blight (FHB), caused by the fungus Fusarium graminearum, represents one of the major wheat diseases worldwide, determining severe yield losses and reduction of grain quality due to the accumulation of mycotoxins. The molecular response associated with the wheat 2DL FHB resistance QTL was mined through a comprehensive transcriptomic analysis of the early response to F. graminearum infection, at 3 days post-inoculation, in spikelets and rachis. The analyses were conducted on two near isogenic lines (NILs) differing for the presence of the 2DL QTL (2-2618, resistant 2DL+ and 2-2890, susceptible null). The general response to fungal infection in terms of mRNAs accumulation trend was similar in both NILs, even though involving an higher number of DEGs in the susceptible NIL, and included down-regulation of the primary and energy metabolism, up-regulation of enzymes implicated in lignin and phenylpropanoid biosynthesis, activation of hormons biosynthesis and signal transduction pathways and genes involved in redox homeostasis and transcriptional regulation. The search for candidate genes with expression profiles associated with the 2DL QTL for FHB resistance led to the discovery of processes differentially modulated in the R and S NILs related to cell wall metabolism, sugar and JA signaling, signal reception and transduction, regulation of the redox status and transcription factors. Wheat FHB response-related miRNAs differentially regulated were also identified as putatively implicated in the superoxide dismutase activities and affecting genes regulating responses to biotic/abiotic stresses and auxin signaling. Altered gene expression was also observed for fungal non-codingRNAs. The putative targets of two of these were represented by the wheat gene WIR1A, involved in resistance response, and a gene encoding a jacalin-related lectin protein, which participate in biotic and abiotic stress response, supporting the presence of a cross-talk between the plant and the fungus. PMID:29434615

Altered Sleep and Affect in the Neurotensin Receptor 1 Knockout Mouse

PubMed Central

Fitzpatrick, Karrie; Winrow, Christopher J.; Gotter, Anthony L.; Millstein, Joshua; Arbuzova, Janna; Brunner, Joseph; Kasarskis, Andrew; Vitaterna, Martha H.; Renger, John J.; Turek, Fred W.

2012-01-01

Study Objective: Sleep and mood disorders have long been understood to have strong genetic components, and there is considerable comorbidity of sleep abnormalities and mood disorders, suggesting the involvement of common genetic pathways. Here, we examine a candidate gene implicated in the regulation of both sleep and affective behavior using a knockout mouse model. Design: Previously, we identified a quantitative trait locus (QTL) for REM sleep amount, REM sleep bout number, and wake amount in a genetically segregating population of mice. Here, we show that traits mapping to this QTL correlated with an expression QTL for neurotensin receptor 1 (Ntsr1), a receptor for neurotensin, a ligand known to be involved in several psychiatric disorders. We examined sleep as well as behaviors indicative of anxiety and depression in the NTSR1 knockout mouse. Measurements and Results: NTSR1 knockouts had a lower percentage of sleep time spent in REM sleep in the dark phase and a larger diurnal variation in REM sleep duration than wild types under baseline conditions. Following sleep deprivation, NTSR1 knockouts exhibited more wake and less NREM rebound sleep. NTSR1 knockouts also showed increased anxious and despair behaviors. Conclusions: Here we illustrate a link between expression of the Ntsr1 gene and sleep traits previously associated with a particular QTL. We also demonstrate a relationship between Ntsr1 and anxiety and despair behaviors. Given the considerable evidence that anxiety and depression are closely linked with abnormalities in sleep, the data presented here provide further evidence that neurotensin and Ntsr1 may be a component of a pathway involved in both sleep and mood disorders. Citation: Fitzpatrick K; Winrow CJ; Gotter AL; Millstein J; Arbuzova J; Brunner J; Kasarskis A; Vitaterna MH; Renger JJ; Turek FW. Altered sleep and affect in the neurotensin receptor 1 knockout mouse. SLEEP 2012;35(7):949-956. PMID:22754041

Building phenotype networks to improve QTL detection: a comparative analysis of fatty acid and fat traits in pigs.

PubMed

Yang, B; Navarro, N; Noguera, J L; Muñoz, M; Guo, T F; Yang, K X; Ma, J W; Folch, J M; Huang, L S; Pérez-Enciso, M

2011-10-01

Models in QTL mapping can be improved by considering all potential variables, i.e. we can use remaining traits other than the trait under study as potential predictors. QTL mapping is often conducted by correcting for a few fixed effects or covariates (e.g. sex, age), although many traits with potential causal relationships between them are recorded. In this work, we evaluate by simulation several procedures to identify optimum models in QTL scans: forward selection, undirected dependency graph and QTL-directed dependency graph (QDG). The latter, QDG, performed better in terms of power and false discovery rate and was applied to fatty acid (FA) composition and fat deposition traits in two pig F2 crosses from China and Spain. Compared with the typical QTL mapping, QDG approach revealed several new QTL. To the contrary, several FA QTL on chromosome 4 (e.g. Palmitic, C16:0; Stearic, C18:0) detected by typical mapping vanished after adjusting for phenotypic covariates in QDG mapping. This suggests that the QTL detected in typical mapping could be indirect. When a QTL is supported by both approaches, there is an increased confidence that the QTL have a primary effect on the corresponding trait. An example is a QTL for C16:1 on chromosome 8. In conclusion, mapping QTL based on causal phenotypic networks can increase power and help to make more biologically sound hypothesis on the genetic architecture of complex traits. © 2011 Blackwell Verlag GmbH.

QTL Analyses in Multiple Populations Employed for the Fine Mapping and Identification of Candidate Genes at a Locus Affecting Sugar Accumulation in Melon (Cucumis melo L.)

PubMed Central

Argyris, Jason M.; Díaz, Aurora; Ruggieri, Valentino; Fernández, Marta; Jahrmann, Torben; Gibon, Yves; Picó, Belén; Martín-Hernández, Ana M.; Monforte, Antonio J.; Garcia-Mas, Jordi

2017-01-01

Sugar content is the major determinant of both fruit quality and consumer acceptance in melon (Cucumis melo L), and is a primary target for crop improvement. Near-isogenic lines (NILs) derived from the intraspecific cross between a “Piel de Sapo” (PS) type and the exotic cultivar “Songwhan Charmi” (SC), and several populations generated from the cross of PS × Ames 24294 (“Trigonus”), a wild melon, were used to identify QTL related to sugar and organic acid composition. Seventy-eight QTL were detected across several locations and different years, with three important clusters related to sugar content located on chromosomes 4, 5, and 7. Two PS × SC NILs (SC5-1 and SC5-2) sharing a common genomic interval of 1.7 Mb at the top of chromosome 5 contained QTL reducing soluble solids content (SSC) and sucrose content by an average of 29 and 68%, respectively. This cluster collocated with QTL affecting sugar content identified in other studies in lines developed from the PS × SC cross and supported the presence of a stable consensus locus involved in sugar accumulation that we named SUCQSC5.1. QTL reducing soluble solids and sucrose content identified in the “Trigonus” mapping populations, as well as QTL identified in previous studies from other ssp. agrestis sources, collocated with SUCQSC5.1, suggesting that they may be allelic and implying a role in domestication. In subNILs derived from the PS × SC5-1 cross, SUCQSC5.1 reduced SSC and sucrose content by an average of 18 and 34%, respectively, and was fine-mapped to a 56.1 kb interval containing four genes. Expression analysis of the candidate genes in mature fruit showed differences between the subNILs with PS alleles that were “high” sugar and SC alleles of “low” sugar phenotypes for MELO3C014519, encoding a putative BEL1-like homeodomain protein. Sequence differences in the gene predicted to affect protein function were restricted to SC and other ssp. agrestis cultivar groups. These results provide the basis for further investigation of genes affecting sugar accumulation in melon. PMID:29018473

Quantitative trait locus mapping and functional genomics of an organophosphate resistance trait in the western corn rootworm, Diabrotica virgifera virgifera.

PubMed

Coates, B S; Alves, A P; Wang, H; Zhou, X; Nowatzki, T; Chen, H; Rangasamy, M; Robertson, H M; Whitfield, C W; Walden, K K; Kachman, S D; French, B W; Meinke, L J; Hawthorne, D; Abel, C A; Sappington, T W; Siegfried, B D; Miller, N J

2016-02-01

The western corn rootworm, Diabrotica virgifera virgifera, is an insect pest of corn and population suppression with chemical insecticides is an important management tool. Traits conferring organophosphate insecticide resistance have increased in frequency amongst D. v. virgifera populations, resulting in the reduced efficacy in many corn-growing regions of the USA. We used comparative functional genomic and quantitative trait locus (QTL) mapping approaches to investigate the genetic basis of D. v. virgifera resistance to the organophosphate methyl-parathion. RNA from adult methyl-parathion resistant and susceptible adults was hybridized to 8331 microarray probes. The results predicted that 11 transcripts were significantly up-regulated in resistant phenotypes, with the most significant (fold increases ≥ 2.43) being an α-esterase-like transcript. Differential expression was validated only for the α-esterase (ST020027A20C03), with 11- to 13-fold greater expression in methyl-parathion resistant adults (P < 0.05). Progeny with a segregating methyl-parathion resistance trait were obtained from a reciprocal backcross design. QTL analyses of high-throughput single nucleotide polymorphism genotype data predicted involvement of a single genome interval. These data suggest that a specific carboyxesterase may function in field-evolved corn rootworm resistance to organophosphates, even though direct linkage between the QTL and this locus could not be established. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Whole-genome scan to detect quantitative trait loci associated with milk protein composition in 3 French dairy cattle breeds.

PubMed

Sanchez, M P; Govignon-Gion, A; Ferrand, M; Gelé, M; Pourchet, D; Amigues, Y; Fritz, S; Boussaha, M; Capitan, A; Rocha, D; Miranda, G; Martin, P; Brochard, M; Boichard, D

2016-10-01

In the context of the PhénoFinLait project, a genome-wide analysis was performed to detect quantitative trait loci (QTL) that affect milk protein composition estimated using mid-infrared spectrometry in the Montbéliarde (MO), Normande (NO), and Holstein (HO) French dairy cattle breeds. The 6 main milk proteins (α-lactalbumin, β-lactoglobulin, and αS1-, αS2-, β-, and κ-caseins) expressed as grams per 100g of milk (% of milk) or as grams per 100g of protein (% of protein) were estimated in 848,068 test-day milk samples from 156,660 cows. Genotyping was performed for 2,773 MO, 2,673 NO, and 2,208 HO cows using the Illumina BovineSNP50 BeadChip (Illumina Inc., San Diego, CA). Individual test-day records were adjusted for environmental effects and then averaged per cow to define the phenotypes analyzed. Quantitative trait loci detection was performed within each breed using a linkage disequilibrium and linkage analysis approach. A total of 39 genomic regions distributed on 20 of the 29 Bos taurus autosomes (BTA) were significantly associated with milk protein composition at a genome-wide level of significance in at least 1 of the 3 breeds. The 9 most significant QTL were located on BTA2 (133 Mbp), BTA6 (38, 47, and 87 Mbp), BTA11 (103 Mbp), BTA14 (1.8 Mbp), BTA20 (32 and 58 Mbp), and BTA29 (8 Mbp). The BTA6 (87 Mbp), BTA11, and BTA20 (58 Mbp) QTL were found in all 3 breeds, and they had highly significant effects on κ-casein, β-lactoglobulin, and α-lactalbumin, expressed as a percentage of protein, respectively. Each of these QTL explained between 13% (BTA14) and 51% (BTA11) of the genetic variance of the trait. Many other QTL regions were also identified in at least one breed. They were located on 14 additional chromosomes (1, 3, 4, 5, 7, 15, 17, 19, 21, 22, 24, 25, 26, and 27), and they explained 2 to 8% of the genetic variance of 1 or more protein composition traits. Concordance analyses, performed between QTL status and sequence-derived polymorphisms from 13 bulls, revealed previously known causal polymorphisms in LGB (BTA11) and GHR (BTA20 at 32 Mbp) and excluded some other previously described mutations. These results constitute a first step in identifying causal mutations and using routinely collected mid-infrared predictions in future genomic selection programs to improve bovine milk protein composition. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Ensemble Learning of QTL Models Improves Prediction of Complex Traits

PubMed Central

Bian, Yang; Holland, James B.

2015-01-01

Quantitative trait locus (QTL) models can provide useful insights into trait genetic architecture because of their straightforward interpretability but are less useful for genetic prediction because of the difficulty in including the effects of numerous small effect loci without overfitting. Tight linkage between markers introduces near collinearity among marker genotypes, complicating the detection of QTL and estimation of QTL effects in linkage mapping, and this problem is exacerbated by very high density linkage maps. Here we developed a thinning and aggregating (TAGGING) method as a new ensemble learning approach to QTL mapping. TAGGING reduces collinearity problems by thinning dense linkage maps, maintains aspects of marker selection that characterize standard QTL mapping, and by ensembling, incorporates information from many more markers-trait associations than traditional QTL mapping. The objective of TAGGING was to improve prediction power compared with QTL mapping while also providing more specific insights into genetic architecture than genome-wide prediction models. TAGGING was compared with standard QTL mapping using cross validation of empirical data from the maize (Zea mays L.) nested association mapping population. TAGGING-assisted QTL mapping substantially improved prediction ability for both biparental and multifamily populations by reducing both the variance and bias in prediction. Furthermore, an ensemble model combining predictions from TAGGING-assisted QTL and infinitesimal models improved prediction abilities over the component models, indicating some complementarity between model assumptions and suggesting that some trait genetic architectures involve a mixture of a few major QTL and polygenic effects. PMID:26276383

Mapping carcass and meat quality QTL on Sus Scrofa chromosome 2 in commercial finishing pigs

PubMed Central

Heuven, Henri CM; van Wijk, Rik HJ; Dibbits, Bert; van Kampen, Tony A; Knol, Egbert F; Bovenhuis, Henk

2009-01-01

Quantitative trait loci (QTL) affecting carcass and meat quality located on SSC2 were identified using variance component methods. A large number of traits involved in meat and carcass quality was detected in a commercial crossbred population: 1855 pigs sired by 17 boars from a synthetic line, which where homozygous (A/A) for IGF2. Using combined linkage and linkage disequilibrium mapping (LDLA), several QTL significantly affecting loin muscle mass, ham weight and ham muscles (outer ham and knuckle ham) and meat quality traits, such as Minolta-L* and -b*, ultimate pH and Japanese colour score were detected. These results agreed well with previous QTL-studies involving SSC2. Since our study is carried out on crossbreds, different QTL may be segregating in the parental lines. To address this question, we compared models with a single QTL-variance component with models allowing for separate sire and dam QTL-variance components. The same QTL were identified using a single QTL variance component model compared to a model allowing for separate variances with minor differences with respect to QTL location. However, the variance component method made it possible to detect QTL segregating in the paternal line (e.g. HAMB), the maternal lines (e.g. Ham) or in both (e.g. pHu). Combining association and linkage information among haplotypes improved slightly the significance of the QTL compared to an analysis using linkage information only. PMID:19284675

Identification of major and minor QTL for ecologically important morphological traits in three-spined sticklebacks (Gasterosteus aculeatus).

PubMed

Liu, Jun; Shikano, Takahito; Leinonen, Tuomas; Cano, José Manuel; Li, Meng-Hua; Merilä, Juha

2014-04-16

Quantitative trait locus (QTL) mapping studies of Pacific three-spined sticklebacks (Gasterosteus aculeatus) have uncovered several genomic regions controlling variability in different morphological traits, but QTL studies of Atlantic sticklebacks are lacking. We mapped QTL for 40 morphological traits, including body size, body shape, and body armor, in a F2 full-sib cross between northern European marine and freshwater three-spined sticklebacks. A total of 52 significant QTL were identified at the 5% genome-wide level. One major QTL explaining 74.4% of the total variance in lateral plate number was detected on LG4, whereas several major QTL for centroid size (a proxy for body size), and the lengths of two dorsal spines, pelvic spine, and pelvic girdle were mapped on LG21 with the explained variance ranging from 27.9% to 57.6%. Major QTL for landmark coordinates defining body shape variation also were identified on LG21, with each explaining ≥15% of variance in body shape. Multiple QTL for different traits mapped on LG21 overlapped each other, implying pleiotropy and/or tight linkage. Thus, apart from providing confirmatory data to support conclusions born out of earlier QTL studies of Pacific sticklebacks, this study also describes several novel QTL of both major and smaller effect for ecologically important traits. The finding that many major QTL mapped on LG21 suggests that this linkage group might be a hotspot for genetic determinants of ecologically important morphological traits in three-spined sticklebacks.

An Efficient Strategy Combining SSR Markers- and Advanced QTL-seq-driven QTL Mapping Unravels Candidate Genes Regulating Grain Weight in Rice

PubMed Central

Daware, Anurag; Das, Sweta; Srivastava, Rishi; Badoni, Saurabh; Singh, Ashok K.; Agarwal, Pinky; Parida, Swarup K.; Tyagi, Akhilesh K.

2016-01-01

Development and use of genome-wide informative simple sequence repeat (SSR) markers and novel integrated genomic strategies are vital to drive genomics-assisted breeding applications and for efficient dissection of quantitative trait loci (QTLs) underlying complex traits in rice. The present study developed 6244 genome-wide informative SSR markers exhibiting in silico fragment length polymorphism based on repeat-unit variations among genomic sequences of 11 indica, japonica, aus, and wild rice accessions. These markers were mapped on diverse coding and non-coding sequence components of known cloned/candidate genes annotated from 12 chromosomes and revealed a much higher amplification (97%) and polymorphic potential (88%) along with wider genetic/functional diversity level (16–74% with a mean 53%) especially among accessions belonging to indica cultivar group, suggesting their utility in large-scale genomics-assisted breeding applications in rice. A high-density 3791 SSR markers-anchored genetic linkage map (IR 64 × Sonasal) spanning 2060 cM total map-length with an average inter-marker distance of 0.54 cM was generated. This reference genetic map identified six major genomic regions harboring robust QTLs (31% combined phenotypic variation explained with a 5.7–8.7 LOD) governing grain weight on six rice chromosomes. One strong grain weight major QTL region (OsqGW5.1) was narrowed-down by integrating traditional QTL mapping with high-resolution QTL region-specific integrated SSR and single nucleotide polymorphism markers-based QTL-seq analysis and differential expression profiling. This led us to delineate two natural allelic variants in two known cis-regulatory elements (RAV1AAT and CARGCW8GAT) of glycosyl hydrolase and serine carboxypeptidase genes exhibiting pronounced seed-specific differential regulation in low (Sonasal) and high (IR 64) grain weight mapping parental accessions. Our genome-wide SSR marker resource (polymorphic within/between diverse cultivar groups) and integrated genomic strategy can efficiently scan functionally relevant potential molecular tags (markers, candidate genes and alleles) regulating complex agronomic traits (grain weight) and expedite marker-assisted genetic enhancement in rice. PMID:27833617

Bias correction for estimated QTL effects using the penalized maximum likelihood method.

PubMed

Zhang, J; Yue, C; Zhang, Y-M

2012-04-01

A penalized maximum likelihood method has been proposed as an important approach to the detection of epistatic quantitative trait loci (QTL). However, this approach is not optimal in two special situations: (1) closely linked QTL with effects in opposite directions and (2) small-effect QTL, because the method produces downwardly biased estimates of QTL effects. The present study aims to correct the bias by using correction coefficients and shifting from the use of a uniform prior on the variance parameter of a QTL effect to that of a scaled inverse chi-square prior. The results of Monte Carlo simulation experiments show that the improved method increases the power from 25 to 88% in the detection of two closely linked QTL of equal size in opposite directions and from 60 to 80% in the identification of QTL with small effects (0.5% of the total phenotypic variance). We used the improved method to detect QTL responsible for the barley kernel weight trait using 145 doubled haploid lines developed in the North American Barley Genome Mapping Project. Application of the proposed method to other shrinkage estimation of QTL effects is discussed.

Mapping of epistatic quantitative trait loci in four-way crosses.

PubMed

He, Xiao-Hong; Qin, Hongde; Hu, Zhongli; Zhang, Tianzhen; Zhang, Yuan-Ming

2011-01-01

Four-way crosses (4WC) involving four different inbred lines often appear in plant and animal commercial breeding programs. Direct mapping of quantitative trait loci (QTL) in these commercial populations is both economical and practical. However, the existing statistical methods for mapping QTL in a 4WC population are built on the single-QTL genetic model. This simple genetic model fails to take into account QTL interactions, which play an important role in the genetic architecture of complex traits. In this paper, therefore, we attempted to develop a statistical method to detect epistatic QTL in 4WC population. Conditional probabilities of QTL genotypes, computed by the multi-point single locus method, were used to sample the genotypes of all putative QTL in the entire genome. The sampled genotypes were used to construct the design matrix for QTL effects. All QTL effects, including main and epistatic effects, were simultaneously estimated by the penalized maximum likelihood method. The proposed method was confirmed by a series of Monte Carlo simulation studies and real data analysis of cotton. The new method will provide novel tools for the genetic dissection of complex traits, construction of QTL networks, and analysis of heterosis.

Genomic Correlates of Relationship QTL Involved in Fore- versus Hind Limb Divergence in Mice

PubMed Central

Pavlicev, Mihaela; Wagner, Günter P.; Noonan, James P.; Hallgrímsson, Benedikt; Cheverud, James M.

2013-01-01

Divergence of serially homologous elements of organisms is a common evolutionary pattern contributing to increased phenotypic complexity. Here, we study the genomic intervals affecting the variational independence of fore- and hind limb traits within an experimental mouse population. We use an advanced intercross of inbred mouse strains to map the loci associated with the degree of autonomy between fore- and hind limb long bone lengths (loci affecting the relationship between traits, relationship quantitative trait loci [rQTL]). These loci have been proposed to interact locally with the products of pleiotropic genes, thereby freeing the local trait from the variational constraint due to pleiotropic mutations. Using the known polymorphisms (single nucleotide polymorphisms [SNPs]) between the parental strains, we characterized and compared the genomic regions in which the rQTL, as well as their interaction partners (intQTL), reside. We find that these two classes of QTL intervals harbor different kinds of molecular variation. SNPs in rQTL intervals more frequently reside in limb-specific cis-regulatory regions than SNPs in intQTL intervals. The intQTL loci modified by the rQTL, in contrast, show the signature of protein-coding variation. This result is consistent with the widely accepted view that protein-coding mutations have broader pleiotropic effects than cis-regulatory polymorphisms. For both types of QTL intervals, the underlying candidate genes are enriched for genes involved in protein binding. This finding suggests that rQTL effects are caused by local interactions among the products of the causal genes harbored in rQTL and intQTL intervals. This is the first study to systematically document the population-level molecular variation underlying the evolution of character individuation. PMID:24065733

Novel Autism Subtype-Dependent Genetic Variants Are Revealed by Quantitative Trait and Subphenotype Association Analyses of Published GWAS Data

PubMed Central

Hu, Valerie W.; Addington, Anjene; Hyman, Alexander

2011-01-01

The heterogeneity of symptoms associated with autism spectrum disorders (ASDs) has presented a significant challenge to genetic analyses. Even when associations with genetic variants have been identified, it has been difficult to associate them with a specific trait or characteristic of autism. Here, we report that quantitative trait analyses of ASD symptoms combined with case-control association analyses using distinct ASD subphenotypes identified on the basis of symptomatic profiles result in the identification of highly significant associations with 18 novel single nucleotide polymorphisms (SNPs). The symptom categories included deficits in language usage, non-verbal communication, social development, and play skills, as well as insistence on sameness or ritualistic behaviors. Ten of the trait-associated SNPs, or quantitative trait loci (QTL), were associated with more than one subtype, providing partial replication of the identified QTL. Notably, none of the novel SNPs is located within an exonic region, suggesting that these hereditary components of ASDs are more likely related to gene regulatory processes (or gene expression) than to structural or functional changes in gene products. Seven of the QTL reside within intergenic chromosomal regions associated with rare copy number variants that have been previously reported in autistic samples. Pathway analyses of the genes associated with the QTL identified in this study implicate neurological functions and disorders associated with autism pathophysiology. This study underscores the advantage of incorporating both quantitative traits as well as subphenotypes into large-scale genome-wide analyses of complex disorders. PMID:21556359

Long-Range Regulatory Polymorphisms Affecting a GABA Receptor Constitute a Quantitative Trait Locus (QTL) for Social Behavior in Caenorhabditis elegans

PubMed Central

Bendesky, Andres; Pitts, Jason; Rockman, Matthew V.; Chen, William C.; Tan, Man-Wah; Kruglyak, Leonid; Bargmann, Cornelia I.

2012-01-01

Aggregation is a social behavior that varies between and within species, providing a model to study the genetic basis of behavioral diversity. In the nematode Caenorhabditis elegans, aggregation is regulated by environmental context and by two neuromodulatory pathways, one dependent on the neuropeptide receptor NPR-1 and one dependent on the TGF-β family protein DAF-7. To gain further insight into the genetic regulation of aggregation, we characterize natural variation underlying behavioral differences between two wild-type C. elegans strains, N2 and CB4856. Using quantitative genetic techniques, including a survey of chromosome substitution strains and QTL analysis of recombinant inbred lines, we identify three new QTLs affecting aggregation in addition to the two known N2 mutations in npr-1 and glb-5. Fine-mapping with near-isogenic lines localized one QTL, accounting for 5%–8% of the behavioral variance between N2 and CB4856, 3′ to the transcript of the GABA neurotransmitter receptor gene exp-1. Quantitative complementation tests demonstrated that this QTL affects exp-1, identifying exp-1 and GABA signaling as new regulators of aggregation. exp-1 interacts genetically with the daf-7 TGF-β pathway, which integrates food availability and population density, and exp-1 mutations affect the level of daf-7 expression. Our results add to growing evidence that genetic variation affecting neurotransmitter receptor genes is a source of natural behavioral variation. PMID:23284308

Microarray-assisted fine-mapping of quantitative trait loci for cold tolerance in rice.

PubMed

Liu, Fengxia; Xu, Wenying; Song, Qian; Tan, Lubin; Liu, Jiayong; Zhu, Zuofeng; Fu, Yongcai; Su, Zhen; Sun, Chuanqing

2013-05-01

Many important agronomic traits, including cold stress resistance, are complex and controlled by quantitative trait loci (QTLs). Isolation of these QTLs will greatly benefit the agricultural industry but it is a challenging task. This study explored an integrated strategy by combining microarray with QTL-mapping in order to identify cold-tolerant QTLs from a cold-tolerant variety IL112 at early-seedling stage. All the early seedlings of IL112 survived normally for 9 d at 4-5°C, while Guichao2 (GC2), an indica cultivar, died after 4 d under the same conditions. Using the F2:3 population derived from the progeny of GC2 and IL112, we identified seven QTLs for cold tolerance. Furthermore, we performed Affymetrix rice whole-genome array hybridization and obtained the expression profiles of IL112 and GC2 under both low-temperature and normal conditions. Four genes were selected as cold QTL-related candidates, based on microarray data mining and QTL-mapping. One candidate gene, LOC_Os07g22494, was shown to be highly associated with cold tolerance in a number of rice varieties and in the F2:3 population, and its overexpression transgenic rice plants displayed strong tolerance to low temperature at early-seedling stage. The results indicated that overexpression of this gene (LOC_Os07g22494) could increase cold tolerance in rice seedlings. Therefore, this study provides a promising strategy for identifying candidate genes in defined QTL regions.

QTL affecting fitness of hybrids between wild and cultivated soybeans in experimental fields

PubMed Central

Kuroda, Yosuke; Kaga, Akito; Tomooka, Norihiko; Yano, Hiroshi; Takada, Yoshitake; Kato, Shin; Vaughan, Duncan

2013-01-01

The objective of this study was to identify quantitative trait loci (QTL) affecting fitness of hybrids between wild soybean (Glycine soja) and cultivated soybean (Glycine max). Seed dormancy and seed number, both of which are important for fitness, were evaluated by testing artificial hybrids of G. soja × G. max in a multiple-site field trial. Generally, the fitness of the F1 hybrids and hybrid derivatives from self-pollination was lower than that of G. soja due to loss of seed dormancy, whereas the fitness of hybrid derivatives with higher proportions of G. soja genetic background was comparable with that of G. soja. These differences were genetically dissected into QTL for each population. Three QTLs for seed dormancy and one QTL for total seed number were detected in the F2 progenies of two diverse cross combinations. At those four QTLs, the G. max alleles reduced seed number and severely reduced seed survival during the winter, suggesting that major genes acquired during soybean adaptation to cultivation have a selective disadvantage in natural habitats. In progenies with a higher proportion of G. soja genetic background, the genetic effects of the G. max alleles were not expressed as phenotypes because the G. soja alleles were dominant over the G. max alleles. Considering the highly inbreeding nature of these species, most hybrid derivatives would disappear quickly in early self-pollinating generations in natural habitats because of the low fitness of plants carrying G. max alleles. PMID:23919159

Deciphering the genetic control of fruit texture in apple by multiple family-based analysis and genome-wide association

PubMed Central

Di Guardo, Mario; Bink, Marco C.A.M.; Guerra, Walter; Letschka, Thomas; Lozano, Lidia; Busatto, Nicola; Poles, Lara; Tadiello, Alice; Bianco, Luca; Visser, Richard G.F.; van de Weg, Eric

2017-01-01

Abstract Fruit texture is a complex feature composed of mechanical and acoustic properties relying on the modifications occurring in the cell wall throughout fruit development and ripening. Apple is characterized by a large variation in fruit texture behavior that directly impacts both the consumer’s appreciation and post-harvest performance. To decipher the genetic control of fruit texture comprehensively, two complementing quantitative trait locus (QTL) mapping approaches were employed. The first was represented by a pedigree-based analysis (PBA) carried out on six full-sib pedigreed families, while the second was a genome-wide association study (GWAS) performed on a collection of 233 apple accessions. Both plant materials were genotyped with a 20K single nucleotide polymorphism (SNP) array and phenotyped with a sophisticated high-resolution texture analyzer. The overall QTL results indicated the fundamental role of chromosome 10 in controlling the mechanical properties, while chromosomes 2 and 14 were more associated with the acoustic response. The latter QTL, moreover, showed a consistent relationship between the QTL-estimated genotypes and the acoustic performance assessed among seedlings. The in silico annotation of these intervals revealed interesting candidate genes potentially involved in fruit texture regulation, as suggested by the gene expression profile. The joint integration of these approaches sheds light on the specific control of fruit texture, enabling important genetic information to assist in the selection of valuable fruit quality apple varieties. PMID:28338805

Deciphering the genetic control of fruit texture in apple by multiple family-based analysis and genome-wide association.

PubMed

Di Guardo, Mario; Bink, Marco C A M; Guerra, Walter; Letschka, Thomas; Lozano, Lidia; Busatto, Nicola; Poles, Lara; Tadiello, Alice; Bianco, Luca; Visser, Richard G F; van de Weg, Eric; Costa, Fabrizio

2017-03-01

Fruit texture is a complex feature composed of mechanical and acoustic properties relying on the modifications occurring in the cell wall throughout fruit development and ripening. Apple is characterized by a large variation in fruit texture behavior that directly impacts both the consumer's appreciation and post-harvest performance. To decipher the genetic control of fruit texture comprehensively, two complementing quantitative trait locus (QTL) mapping approaches were employed. The first was represented by a pedigree-based analysis (PBA) carried out on six full-sib pedigreed families, while the second was a genome-wide association study (GWAS) performed on a collection of 233 apple accessions. Both plant materials were genotyped with a 20K single nucleotide polymorphism (SNP) array and phenotyped with a sophisticated high-resolution texture analyzer. The overall QTL results indicated the fundamental role of chromosome 10 in controlling the mechanical properties, while chromosomes 2 and 14 were more associated with the acoustic response. The latter QTL, moreover, showed a consistent relationship between the QTL-estimated genotypes and the acoustic performance assessed among seedlings. The in silico annotation of these intervals revealed interesting candidate genes potentially involved in fruit texture regulation, as suggested by the gene expression profile. The joint integration of these approaches sheds light on the specific control of fruit texture, enabling important genetic information to assist in the selection of valuable fruit quality apple varieties. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Identification of Candidate Genes Underlying an Iron Efficiency Quantitative Trait Locus in Soybean1

PubMed Central

Peiffer, Gregory A.; King, Keith E.; Severin, Andrew J.; May, Gregory D.; Cianzio, Silvia R.; Lin, Shun Fu; Lauter, Nicholas C.; Shoemaker, Randy C.

2012-01-01

Prevalent on calcareous soils in the United States and abroad, iron deficiency is among the most common and severe nutritional stresses in plants. In soybean (Glycine max) commercial plantings, the identification and use of iron-efficient genotypes has proven to be the best form of managing this soil-related plant stress. Previous studies conducted in soybean identified a significant iron efficiency quantitative trait locus (QTL) explaining more than 70% of the phenotypic variation for the trait. In this research, we identified candidate genes underlying this QTL through molecular breeding, mapping, and transcriptome sequencing. Introgression mapping was performed using two related near-isogenic lines in which a region located on soybean chromosome 3 required for iron efficiency was identified. The region corresponds to the previously reported iron efficiency QTL. The location was further confirmed through QTL mapping conducted in this study. Transcriptome sequencing and quantitative real-time-polymerase chain reaction identified two genes encoding transcription factors within the region that were significantly induced in soybean roots under iron stress. The two induced transcription factors were identified as homologs of the subgroup lb basic helix-loop-helix (bHLH) genes that are known to regulate the strategy I response in Arabidopsis (Arabidopsis thaliana). Resequencing of these differentially expressed genes unveiled a significant deletion within a predicted dimerization domain. We hypothesize that this deletion disrupts the Fe-DEFICIENCY-INDUCED TRANSCRIPTION FACTOR (FIT)/bHLH heterodimer that has been shown to induce known iron acquisition genes. PMID:22319075

Integration of genetic, genomic and transcriptomic information identifies putative regulators of adventitious root formation in Populus

DOE PAGES

Ribeiro, Cintia L.; Silva, Cynthia M.; Drost, Derek R.; ...

2016-03-16

In this study, adventitious roots (AR) develop from tissues other than the primary root, in a process physiologically regulated by phytohormones. Adventitious roots provide structural support and contribute to water and nutrient absorption, and are critical for commercial vegetative propagation of several crops. Here we quantified the number of AR, root architectural traits and root biomass in cuttings from a pseudo-backcross population of Populus deltoides and Populus trichocarpa. Quantitative trait loci (QTL) mapping and whole-transcriptome analysis of individuals with alternative QTL alleles for AR number were used to identify putative regulators of AR development. As a result, parental individuals andmore » progeny showed extensive segregation for AR developmental traits. Quantitative trait loci for number of AR mapped consistently in the same interval of linkage group (LG) II and LG XIV, explaining 7–10 % of the phenotypic variation. A time series transcriptome analysis identified 26,121 genes differentially expressed during AR development, particularly during the first 24 h after cuttings were harvested. Of those, 1929 genes were differentially regulated between individuals carrying alternative alleles for the two QTL for number of AR, in one or more time point. Eighty-one of these genes were physically located within the QTL intervals for number of AR, including putative homologs of the Arabidopsis genes SUPERROOT2 (SUR2) and TRYPTOPHAN SYNTHASE ALPHA CHAIN (TSA1), both of which are involved in the auxin indole-3-acetic acid (IAA) biosynthesis pathway. In conclusion, this study suggests the involvement of two genes of the tryptophan-dependent auxin biosynthesis pathway, SUR2 and TSA1, in the regulation of a critical trait for the clonal propagation of woody species. A possible model for this regulation is that poplar individuals that have poor AR formation synthesize auxin indole-3-acetic acid (IAA) primarily through the tryptophan (Trp) pathway. Much of the Trp pathway flux appears to be directed to the synthesis of indole glucosinolates (IG), as suggested by the over-expression of SUR2. Individuals that are efficient in AR formation may utilize alternative (non-Trp) pathways to synthesize IAA, based on the observation that they down-regulate the expression of TSA1, one of the critical steps in the synthesis of tryptophan.« less

Identification of Quantitative Trait Loci That Determine Plasma Total-Cholesterol and Triglyceride Concentrations in DDD/Sgn and C57BL/6J Inbred Mice.

PubMed

Suto, Jun-Ichi; Kojima, Misaki

2017-01-01

DDD/Sgn mice have significantly higher plasma lipid concentrations than C57BL/6J mice. In the present study, we performed quantitative trait loci (QTL) mapping for plasma total-cholesterol (CHO) and triglyceride (TG) concentrations in reciprocal F 2 male intercross populations between the two strains. By single-QTL scans, we identified four significant QTL on chromosomes (Chrs) 1, 5, 17, and 19 for CHO and two significant QTL on Chrs 1 and 12 for TG. By including cross direction as an interactive covariate, we identified separate significant QTL on Chr 17 for CHO but none for TG. When the large phenotypic effect of QTL on Chr 1 was controlled by composite interval mapping, we identified three additional significant QTL on Chrs 3, 4, and 9 for CHO but none for TG. QTL on Chr 19 was a novel QTL for CHO and the allelic effect of this QTL significantly differed between males and females. Whole-exome sequence analysis in DDD/Sgn mice suggested that Apoa2 and Acads were the plausible candidate genes underlying CHO QTL on Chrs 1 and 5, respectively. Thus, we identified a multifactorial basis for plasma lipid concentrations in male mice. These findings will provide insight into the genetic mechanisms of plasma lipid metabolism.

Identification of Quantitative Trait Loci That Determine Plasma Total-Cholesterol and Triglyceride Concentrations in DDD/Sgn and C57BL/6J Inbred Mice

PubMed Central

Kojima, Misaki

2017-01-01

DDD/Sgn mice have significantly higher plasma lipid concentrations than C57BL/6J mice. In the present study, we performed quantitative trait loci (QTL) mapping for plasma total-cholesterol (CHO) and triglyceride (TG) concentrations in reciprocal F2 male intercross populations between the two strains. By single-QTL scans, we identified four significant QTL on chromosomes (Chrs) 1, 5, 17, and 19 for CHO and two significant QTL on Chrs 1 and 12 for TG. By including cross direction as an interactive covariate, we identified separate significant QTL on Chr 17 for CHO but none for TG. When the large phenotypic effect of QTL on Chr 1 was controlled by composite interval mapping, we identified three additional significant QTL on Chrs 3, 4, and 9 for CHO but none for TG. QTL on Chr 19 was a novel QTL for CHO and the allelic effect of this QTL significantly differed between males and females. Whole-exome sequence analysis in DDD/Sgn mice suggested that Apoa2 and Acads were the plausible candidate genes underlying CHO QTL on Chrs 1 and 5, respectively. Thus, we identified a multifactorial basis for plasma lipid concentrations in male mice. These findings will provide insight into the genetic mechanisms of plasma lipid metabolism. PMID:28642824

Identification of Major and Minor QTL for Ecologically Important Morphological Traits in Three-Spined Sticklebacks (Gasterosteus aculeatus)

PubMed Central

Liu, Jun; Shikano, Takahito; Leinonen, Tuomas; Cano, José Manuel; Li, Meng-Hua; Merilä, Juha

2014-01-01

Quantitative trait locus (QTL) mapping studies of Pacific three-spined sticklebacks (Gasterosteus aculeatus) have uncovered several genomic regions controlling variability in different morphological traits, but QTL studies of Atlantic sticklebacks are lacking. We mapped QTL for 40 morphological traits, including body size, body shape, and body armor, in a F2 full-sib cross between northern European marine and freshwater three-spined sticklebacks. A total of 52 significant QTL were identified at the 5% genome-wide level. One major QTL explaining 74.4% of the total variance in lateral plate number was detected on LG4, whereas several major QTL for centroid size (a proxy for body size), and the lengths of two dorsal spines, pelvic spine, and pelvic girdle were mapped on LG21 with the explained variance ranging from 27.9% to 57.6%. Major QTL for landmark coordinates defining body shape variation also were identified on LG21, with each explaining ≥15% of variance in body shape. Multiple QTL for different traits mapped on LG21 overlapped each other, implying pleiotropy and/or tight linkage. Thus, apart from providing confirmatory data to support conclusions born out of earlier QTL studies of Pacific sticklebacks, this study also describes several novel QTL of both major and smaller effect for ecologically important traits. The finding that many major QTL mapped on LG21 suggests that this linkage group might be a hotspot for genetic determinants of ecologically important morphological traits in three-spined sticklebacks. PMID:24531726

Meta-QTL analysis of seed iron and zinc concentration and content in common bean (Phaseolus vulgaris L.).

PubMed

Izquierdo, Paulo; Astudillo, Carolina; Blair, Matthew W; Iqbal, Asif M; Raatz, Bodo; Cichy, Karen A

2018-05-11

Twelve meta-QTL for seed Fe and Zn concentration and/or content were identified from 87 QTL originating from seven population grown in sixteen field trials. These meta-QTL include 2 specific to iron, 2 specific to zinc and 8 that co-localize for iron and zinc concentrations and/or content. Common bean (Phaseolus vulgaris L.) is the most important legume for human consumption worldwide and it is an important source of microelements, especially iron and zinc. Bean biofortification breeding programs develop new varieties with high levels of Fe and Zn targeted for countries with human micronutrient deficiencies. Biofortification efforts thus far have relied on phenotypic selection of raw seed mineral concentrations in advanced generations. While numerous quantitative trait loci (QTL) studies have been conducted to identify genomic regions associated with increased Fe and Zn concentration in seeds, these results have yet to be employed for marker-assisted breeding. The objective of this study was to conduct a meta-analysis from seven QTL studies in Andean and Middle American intra- and inter-gene pool populations to identify the regions in the genome that control the Fe and Zn levels in seeds. Two meta-QTL specific to Fe and two meta-QTL specific to Zn were identified. Additionally, eight Meta QTL that co-localized for Fe and Zn concentration and/or content were identified across seven chromosomes. The Fe and Zn shared meta-QTL could be useful candidates for marker-assisted breeding to simultaneously increase seed Fe and Zn. The physical positions for 12 individual meta-QTL were identified and within five of the meta-QTL, candidate genes were identified from six gene families that have been associated with transport of iron and zinc in plants.

Mapping Quantitative Trait Loci (QTL) in sheep. III. QTL for carcass composition traits derived from CT scans and aligned with a meta-assembly for sheep and cattle carcass QTL.

PubMed

Cavanagh, Colin R; Jonas, Elisabeth; Hobbs, Matthew; Thomson, Peter C; Tammen, Imke; Raadsma, Herman W

2010-09-16

An (Awassi × Merino) × Merino single-sire backcross family with 165 male offspring was used to map quantitative trait loci (QTL) for body composition traits on a framework map of 189 microsatellite loci across all autosomes. Two cohorts were created from the experimental progeny to represent alternative maturity classes for body composition assessment. Animals were raised under paddock conditions prior to entering the feedlot for a 90-day fattening phase. Body composition traits were derived in vivo at the end of the experiment prior to slaughter at 2 (cohort 1) and 3.5 (cohort 2) years of age, using computed tomography. Image analysis was used to gain accurate predictions for 13 traits describing major fat depots, lean muscle, bone, body proportions and body weight which were used for single- and two-QTL mapping analysis. Using a maximum-likelihood approach, three highly significant (LOD ≥ 3), 15 significant (LOD ≥ 2), and 11 suggestive QTL (1.7 ≤ LOD < 2) were detected on eleven chromosomes. Regression analysis confirmed 28 of these QTL and an additional 17 suggestive (P < 0.1) and two significant (P < 0.05) QTL were identified using this method. QTL with pleiotropic effects for two or more tissues were identified on chromosomes 1, 6, 10, 14, 16 and 23. No tissue-specific QTL were identified.A meta-assembly of ovine QTL for carcass traits from this study and public domain sources was performed and compared with a corresponding bovine meta-assembly. The assembly demonstrated QTL with effects on carcass composition in homologous regions on OAR1, 2, 6 and 21.

Comparative mapping reveals quantitative trait loci that affect spawning time in coho salmon (Oncorhynchus kisutch)

PubMed Central

Araneda, Cristian; Díaz, Nelson F.; Gomez, Gilda; López, María Eugenia; Iturra, Patricia

2012-01-01

Spawning time in salmonids is a sex-limited quantitative trait that can be modified by selection. In rainbow trout (Oncorhynchus mykiss), various quantitative trait loci (QTL) that affect the expression of this trait have been discovered. In this study, we describe four microsatellite loci associated with two possible spawning time QTL regions in coho salmon (Oncorhynchus kisutch). The four loci were identified in females from two populations (early and late spawners) produced by divergent selection from the same base population. Three of the loci (OmyFGT34TUF, One2ASC and One19ASC) that were strongly associated with spawning time in coho salmon (p < 0.0002) were previously associated with QTL for the same trait in rainbow trout; a fourth loci (Oki10) with a suggestive association (p = 0.00035) mapped 10 cM from locus OmyFGT34TUF in rainbow trout. The changes in allelic frequency observed after three generations of selection were greater than expected because of genetic drift. This work shows that comparing information from closely-related species is a valid strategy for identifying QTLs for marker-assisted selection in species whose genomes are poorly characterized or lack a saturated genetic map. PMID:22888302

QTL Dissection of Lag Phase in Wine Fermentation Reveals a New Translocation Responsible for Saccharomyces cerevisiae Adaptation to Sulfite

PubMed Central

Zimmer, Adrien; Durand, Cécile; Loira, Nicolás; Durrens, Pascal; Sherman, David James; Marullo, Philippe

2014-01-01

Quantitative genetics and QTL mapping are efficient strategies for deciphering the genetic polymorphisms that explain the phenotypic differences of individuals within the same species. Since a decade, this approach has been applied to eukaryotic microbes such as Saccharomyces cerevisiae in order to find natural genetic variations conferring adaptation of individuals to their environment. In this work, a QTL responsible for lag phase duration in the alcoholic fermentation of grape juice was dissected by reciprocal hemizygosity analysis. After invalidating the effect of some candidate genes, a chromosomal translocation affecting the lag phase was brought to light using de novo assembly of parental genomes. This newly described translocation (XV-t-XVI) involves the promoter region of ADH1 and the gene SSU1 and confers an increased expression of the sulfite pump during the first hours of alcoholic fermentation. This translocation constitutes another adaptation route of wine yeast to sulfites in addition to the translocation VIII-t-XVI previously described. A population survey of both translocation forms in a panel of domesticated yeast strains suggests that the translocation XV-t-XVI has been empirically selected by human activity. PMID:24489712

Genetic Determinism of Fearfulness, General Activity and Feeding Behavior in Chickens and Its Relationship with Digestive Efficiency.

PubMed

Mignon-Grasteau, Sandrine; Chantry-Darmon, Céline; Boscher, Marie-Yvonne; Sellier, Nadine; Le Bihan-Duval, Elisabeth; Bertin, Aline

2017-01-01

The genetic relationships between behavior and digestive efficiency were studied in 860 chickens from a cross between two lines divergently selected on digestive efficiency. At 2 weeks of age each chick was video-recorded in the home pen to characterize general activity and feeding behavior. Tonic immobility and open-field tests were also carried out individually to evaluate emotional reactivity (i.e. the propensity to express fear responses). Digestive efficiency was measured at 3 weeks. Genetic parameters of behavior traits were estimated. Birds were genotyped on 3379 SNP markers to detect QTLs. Heritabilities of behavioral traits were low, apart from tonic immobility (0.17-0.18) and maximum meal length (0.14). The genetic correlations indicated that the most efficient birds fed more frequently and were less fearful. We detected 14 QTL (9 for feeding behavior, 3 for tonic immobility, 2 for frequency of lying). Nine of them co-localized with QTL for efficiency, anatomy of the digestive tract, feed intake or microbiota composition. Four genes involved in fear reactions were identified in the QTL for tonic immobility on GGA1.

Identification of trait-improving quantitative trait loci for grain yield components from a dent corn inbred line in an advanced backcross BC2F2 population and comparison with its F2:3 population in popcorn.

PubMed

Li, Y L; Niu, S Z; Dong, Y B; Cui, D Q; Wang, Y Z; Liu, Y Y; Wei, M G

2007-06-01

Normal maize germplasm could be used to improve the grain yield of popcorn inbreds. Our first objective was to locate genetic factors associated with trait variation and make first assessment on the efficiency of advanced backcross quantitative trait locus (AB-QTL) analysis for the identification and transfer of favorable QTL alleles for grain yield components from the dent corn inbred. A second objective was to compare the detection of QTL in the BC2F2 population with results using F(2:3) lines of the same parents. Two hundred and twenty selected BC2F2 families developed from a cross between Dan232 and an elite popcorn inbred N04 were evaluated for six grain yield components under two environments, and genotyped by means of 170 SSR markers. Using composite interval mapping (CIM), a total of 19 significant QTL were detected. Eighteen QTL had favorable alleles contributed by the dent corn parent Dan232. Sixteen of these favorable QTL alleles were not in the same or near marker intervals with QTL for popping characteristics. Six QTL were also detected in the F(2:3) population. Improved N04 could be developed from 210 and 208 families with higher grain weight per plant and/or 100-grain weight, respectively, and 35 families with the same or higher popping expansion volume than N04. In addition, near isogenic lines containing detected QTL (QTL-NILs) for grain weight per plant and/or 100-grain weight could be obtained from 12 families. Our study demonstrated that the AB-QTL method can be applied to identify and manipulate favorable QTL alleles from normal corn inbreds and combine QTL detection and popcorn breeding efficiently.

Genome-wide linkage mapping of yield-related traits in three Chinese bread wheat populations using high-density SNP markers.

PubMed

Li, Faji; Wen, Weie; He, Zhonghu; Liu, Jindong; Jin, Hui; Cao, Shuanghe; Geng, Hongwei; Yan, Jun; Zhang, Pingzhi; Wan, Yingxiu; Xia, Xianchun

2018-06-01

We identified 21 new and stable QTL, and 11 QTL clusters for yield-related traits in three bread wheat populations using the wheat 90 K SNP assay. Identification of quantitative trait loci (QTL) for yield-related traits and closely linked molecular markers is important in order to identify gene/QTL for marker-assisted selection (MAS) in wheat breeding. The objectives of the present study were to identify QTL for yield-related traits and dissect the relationships among different traits in three wheat recombinant inbred line (RIL) populations derived from crosses Doumai × Shi 4185 (D × S), Gaocheng 8901 × Zhoumai 16 (G × Z) and Linmai 2 × Zhong 892 (L × Z). Using the available high-density linkage maps previously constructed with the wheat 90 K iSelect single nucleotide polymorphism (SNP) array, 65, 46 and 53 QTL for 12 traits were identified in the three RIL populations, respectively. Among them, 34, 23 and 27 were likely to be new QTL. Eighteen common QTL were detected across two or three populations. Eleven QTL clusters harboring multiple QTL were detected in different populations, and the interval 15.5-32.3 cM around the Rht-B1 locus on chromosome 4BS harboring 20 QTL is an important region determining grain yield (GY). Thousand-kernel weight (TKW) is significantly affected by kernel width and plant height (PH), whereas flag leaf width can be used to select lines with large kernel number per spike. Eleven candidate genes were identified, including eight cloned genes for kernel, heading date (HD) and PH-related traits as well as predicted genes for TKW, spike length and HD. The closest SNP markers of stable QTL or QTL clusters can be used for MAS in wheat breeding using kompetitive allele-specific PCR or semi-thermal asymmetric reverse PCR assays for improvement of GY.

Two distinct classes of QTL determine rust resistance in sorghum.

PubMed

Wang, Xuemin; Mace, Emma; Hunt, Colleen; Cruickshank, Alan; Henzell, Robert; Parkes, Heidi; Jordan, David

2014-12-31

Agriculture is facing enormous challenges to feed a growing population in the face of rapidly evolving pests and pathogens. The rusts, in particular, are a major pathogen of cereal crops with the potential to cause large reductions in yield. Improving stable disease resistance is an on-going major and challenging focus for many plant breeding programs, due to the rapidly evolving nature of the pathogen. Sorghum is a major summer cereal crop that is also a host for a rust pathogen Puccinia purpurea, which occurs in almost all sorghum growing areas of the world, causing direct and indirect yield losses in sorghum worldwide, however knowledge about its genetic control is still limited. In order to further investigate this issue, QTL and association mapping methods were implemented to study rust resistance in three bi-parental populations and an association mapping set of elite breeding lines in different environments. In total, 64 significant or highly significant QTL and 21 suggestive rust resistance QTL were identified representing 55 unique genomic regions. Comparisons across populations within the current study and with rust QTL identified previously in both sorghum and maize revealed a high degree of correspondence in QTL location. Negative phenotypic correlations were observed between rust, maturity and height, indicating a trend for both early maturing and shorter genotypes to be more susceptible to rust. The significant amount of QTL co-location across traits, in addition to the consistency in the direction of QTL allele effects, has provided evidence to support pleiotropic QTL action across rust, height, maturity and stay-green, supporting the role of carbon stress in susceptibility to rust. Classical rust resistance QTL regions that did not co-locate with height, maturity or stay-green QTL were found to be significantly enriched for the defence-related NBS-encoding gene family, in contrast to the lack of defence-related gene enrichment in multi-trait effect rust resistance QTL. The distinction of disease resistance QTL hot-spots, enriched with defence-related gene families from QTL which impact on development and partitioning, provides plant breeders with knowledge which will allow for fast-tracking varieties with both durable pathogen resistance and appropriate adaptive traits.

The pig genome project has plenty to squeal about.

PubMed

Fan, B; Gorbach, D M; Rothschild, M F

2011-01-01

Significant progress on pig genetics and genomics research has been witnessed in recent years due to the integration of advanced molecular biology techniques, bioinformatics and computational biology, and the collaborative efforts of researchers in the swine genomics community. Progress on expanding the linkage map has slowed down, but the efforts have created a higher-resolution physical map integrating the clone map and BAC end sequence. The number of QTL mapped is still growing and most of the updated QTL mapping results are available through PigQTLdb. Additionally, expression studies using high-throughput microarrays and other gene expression techniques have made significant advancements. The number of identified non-coding RNAs is rapidly increasing and their exact regulatory functions are being explored. A publishable draft (build 10) of the swine genome sequence was available for the pig genomics community by the end of December 2010. Build 9 of the porcine genome is currently available with Ensembl annotation; manual annotation is ongoing. These drafts provide useful tools for such endeavors as comparative genomics and SNP scans for fine QTL mapping. A recent community-wide effort to create a 60K porcine SNP chip has greatly facilitated whole-genome association analyses, haplotype block construction and linkage disequilibrium mapping, which can contribute to whole-genome selection. The future 'systems biology' that integrates and optimizes the information from all research levels can enhance the pig community's understanding of the full complexity of the porcine genome. These recent technological advances and where they may lead are reviewed. Copyright © 2011 S. Karger AG, Basel.

CaAP2 transcription factor is a candidate gene for a flowering repressor and a candidate for controlling natural variation of flowering time in Capsicum annuum.

PubMed

Borovsky, Yelena; Sharma, Vinod K; Verbakel, Henk; Paran, Ilan

2015-06-01

The APETALA2 transcription factor homolog CaAP2 is a candidate gene for a flowering repressor in pepper, as revealed by induced-mutation phenotype, and a candidate underlying a major QTL controlling natural variation in flowering time. To decipher the genetic control of transition to flowering in pepper (Capsicum spp.) and determine the extent of gene function conservation compared to model species, we isolated and characterized several ethyl methanesulfonate (EMS)-induced mutants that vary in their flowering time compared to the wild type. In the present study, we report on the isolation of an early-flowering mutant that flowers after four leaves on the primary stem compared to nine leaves in the wild-type 'Maor'. By genetic mapping and sequencing of putative candidate genes linked to the mutant phenotype, we identified a member of the APETALA2 (AP2) transcription factor family, CaAP2, which was disrupted in the early-flowering mutant. CaAP2 is a likely ortholog of AP2 that functions as a repressor of flowering in Arabidopsis. To test whether CaAP2 has an effect on controlling natural variation in the transition to flowering in pepper, we performed QTL mapping for flowering time in a cross between early and late-flowering C. annuum accessions. We identified a major QTL in a region of chromosome 2 in which CaAP2 was the most significant marker, explaining 52 % of the phenotypic variation of the trait. Sequence comparison of the CaAP2 open reading frames in the two parents used for QTL mapping did not reveal significant variation. In contrast, significant differences in expression level of CaAP2 were detected between near-isogenic lines that differ for the flowering time QTL, supporting the putative function of CaAP2 as a major repressor of flowering in pepper.

Identification of candidate genes involved in Witches' broom disease resistance in a segregating mapping population of Theobroma cacao L. in Brazil.

PubMed

Royaert, Stefan; Jansen, Johannes; da Silva, Daniela Viana; de Jesus Branco, Samuel Martins; Livingstone, Donald S; Mustiga, Guiliana; Marelli, Jean-Philippe; Araújo, Ioná Santos; Corrêa, Ronan Xavier; Motamayor, Juan Carlos

2016-02-11

Witches' broom disease (WBD) caused by the fungus Moniliophthora perniciosa is responsible for considerable economic losses for cacao producers. One of the ways to combat WBD is to plant resistant cultivars. Resistance may be governed by a few genetic factors, mainly found in wild germplasm. We developed a dense genetic linkage map with a length of 852.8 cM that contains 3,526 SNPs and is based on the MP01 mapping population, which counts 459 trees from a cross between the resistant 'TSH 1188' and the tolerant 'CCN 51' at the Mars Center for Cocoa Science in Barro Preto, Bahia, Brazil. Seven quantitative trait loci (QTL) that are associated with WBD were identified on five different chromosomes using a multi-trait QTL analysis for outbreeders. Phasing of the haplotypes at the major QTL region on chromosome IX on a diversity panel of genotypes clearly indicates that the major resistance locus comes from a well-known source of WBD resistance, the clone 'SCAVINA 6'. Various potential candidate genes identified within all QTL may be involved in different steps leading to disease resistance. Preliminary expression data indicate that at least three of these candidate genes may play a role during the first 12 h after infection, with clear differences between 'CCN 51' and 'TSH 1188'. We combined the information from a large mapping population with very distinct parents that segregate for WBD, a dense set of mapped markers, rigorous phenotyping capabilities and the availability of a sequenced genome to identify several genomic regions that are involved in WBD resistance. We also identified a novel source of resistance that most likely comes from the 'CCN 51' parent. Thanks to the large population size of the MP01 population, we were able to pick up QTL and markers with relatively small effects that can contribute to the creation and selection of more tolerant/resistant plant material.

QTL Analysis of Dietary Obesity in C57BL/6byj X 129P3/J F2 Mice: Diet- and Sex-Dependent Effects

PubMed Central

Lin, Cailu; Theodorides, Maria L.; McDaniel, Amanda H.; Tordoff, Michael G.; Zhang, Qinmin; Li, Xia; Bosak, Natalia; Bachmanov, Alexander A.; Reed, Danielle R.

2013-01-01

Obesity is a heritable trait caused by complex interactions between genes and environment, including diet. Gene-by-diet interactions are difficult to study in humans because the human diet is hard to control. Here, we used mice to study dietary obesity genes, by four methods. First, we bred 213 F2 mice from strains that are susceptible [C57BL/6ByJ (B6)] or resistant [129P3/J (129)] to dietary obesity. Percent body fat was assessed after mice ate low-energy diet and again after the same mice ate high-energy diet for 8 weeks. Linkage analyses identified QTLs associated with dietary obesity. Three methods were used to filter candidate genes within the QTL regions: (a) association mapping was conducted using >40 strains; (b) differential gene expression and (c) comparison of genomic DNA sequence, using two strains closely related to the progenitor strains from Experiment 1. The QTL effects depended on whether the mice were male or female or which diet they were recently fed. After feeding a low-energy diet, percent body fat was linked to chr 7 (LOD = 3.42). After feeding a high-energy diet, percent body fat was linked to chr 9 (Obq5; LOD = 3.88), chr 12 (Obq34; LOD = 3.88), and chr 17 (LOD = 4.56). The Chr 7 and 12 QTLs were sex dependent and all QTL were diet-dependent. The combination of filtering methods highlighted seven candidate genes within the QTL locus boundaries: Crx, Dmpk, Ahr, Mrpl28, Glo1, Tubb5, and Mut. However, these filtering methods have limitations so gene identification will require alternative strategies, such as the construction of congenics with very small donor regions. PMID:23922663

Mapping of quantitative trait loci for grain yield and its components in a US popular winter wheat TAM 111 using 90K SNPs.

PubMed

Assanga, Silvano O; Fuentealba, Maria; Zhang, Guorong; Tan, ChorTee; Dhakal, Smit; Rudd, Jackie C; Ibrahim, Amir M H; Xue, Qingwu; Haley, Scott; Chen, Jianli; Chao, Shiaoman; Baker, Jason; Jessup, Kirk; Liu, Shuyu

2017-01-01

Stable quantitative trait loci (QTL) are important for deployment in marker assisted selection in wheat (Triticum aestivum L.) and other crops. We reported QTL discovery in wheat using a population of 217 recombinant inbred lines and multiple statistical approach including multi-environment, multi-trait and epistatic interactions analysis. We detected nine consistent QTL linked to different traits on chromosomes 1A, 2A, 2B, 5A, 5B, 6A, 6B and 7A. Grain yield QTL were detected on chromosomes 2B.1 and 5B across three or four models of GenStat, MapQTL, and QTLNetwork while the QTL on chromosomes 5A.1, 6A.2, and 7A.1 were only significant with yield from one or two models. The phenotypic variation explained (PVE) by the QTL on 2B.1 ranged from 3.3-25.1% based on single and multi-environment models in GenStat and was pleiotropic or co-located with maturity (days to heading) and yield related traits (test weight, thousand kernel weight, harvest index). The QTL on 5B at 211 cM had PVE range of 1.8-9.3% and had no significant pleiotropic effects. Other consistent QTL detected in this study were linked to yield related traits and agronomic traits. The QTL on 1A was consistent for the number of spikes m-2 across environments and all the four analysis models with a PVE range of 5.8-8.6%. QTL for kernels spike-1 were found in chromosomes 1A, 2A.1, 2B.1, 6A.2, and 7A.1 with PVE ranged from 5.6-12.8% while QTL for thousand kernel weight were located on chromosomes 1A, 2B.1, 5A.1, 6A.2, 6B.1 and 7A.1 with PVEranged from 2.7-19.5%. Among the consistent QTL, five QTL had significant epistatic interactions (additive × additive) at least for one trait and none revealed significant additive × additive × environment interactions. Comparative analysis revealed that the region within the confidence interval of the QTL on 5B from 211.4-244.2 cM is also linked to genes for aspartate-semialdehyde dehydrogenase, splicing regulatory glutamine/lysine-rich protein 1 isoform X1, and UDP-glucose 6-dehydrogenase 1-like isoform X1. The stable QTL could be important for further validation, high throughput SNP development, and marker-assisted selection (MAS) in wheat.

Comparative quantitative trait loci for silique length and seed weight in Brassica napus.

PubMed

Fu, Ying; Wei, Dayong; Dong, Hongli; He, Yajun; Cui, Yixin; Mei, Jiaqin; Wan, Huafang; Li, Jiana; Snowdon, Rod; Friedt, Wolfgang; Li, Xiaorong; Qian, Wei

2015-09-23

Silique length (SL) and seed weight (SW) are important yield-associated traits in rapeseed (Brassica napus). Although many quantitative trait loci (QTL) for SL and SW have been identified in B. napus, comparative analysis for those QTL is seldom performed. In the present study, 20 and 21 QTL for SL and SW were identified in doubled haploid (DH) and DH-derived reconstructed F2 populations in rapeseed, explaining 55.1-74.3% and 24.4-62.9% of the phenotypic variation across three years, respectively. Of which, 17 QTL with partially or completely overlapped confidence interval on chromosome A09, were homologous with two overlapped QTL on chromosome C08 by aligning QTL confidence intervals with the reference genomes of Brassica crops. By high density selective genotyping of DH lines with extreme phenotypes, using a Brassica single-nucleotide polymorphism (SNP) array, the QTL on chromosome A09 was narrowed, and aligned into 1.14-Mb region from 30.84 to 31.98 Mb on chromosome R09 of B. rapa and 1.05-Mb region from 27.21 to 28.26 Mb on chromosome A09 of B. napus. The alignment of QTL with Brassica reference genomes revealed homologous QTL on A09 and C08 for SL. The narrowed QTL region provides clues for gene cloning and breeding cultivars by marker-assisted selection.

Effect and mode of action of the Texel muscling QTL (TM-QTL) on carcass traits in purebred Texel lambs.

PubMed

Macfarlane, J M; Lambe, N R; Matika, O; Johnson, P L; Wolf, B T; Haresign, W; Bishop, S C; Bünger, L

2014-07-01

TM-QTL is a quantitative trait locus (QTL) on ovine chromosome 18 (OAR18) known to affect loin muscling in Texel sheep. Previous work suggested that its mode of inheritance is consistent with paternal polar overdominance, but this has yet to be formally demonstrated. This study used purebred Texel sheep segregating for TM-QTL to confirm its presence in the chromosomal region in which it was first reported and to determine its pattern of inheritance. To do so, this study used the first available data from a Texel flock, which included homozygote TM-QTL carriers (TM/TM; n=34) in addition to homozygote non-carriers (+/+; n=40 and, heterozygote TM-QTL-carriers inheriting TM-QTL from their sire (TM/+; n=53) or their dam (+/TM; n=17). Phenotypes included a wide range of loin muscling, carcass composition and tissue distribution traits. The presence of a QTL affecting ultrasound muscle depth on OAR18 was confirmed with a paternal QTL effect ranging from +0.54 to +2.82 mm UMD (s.e. 0.37 to 0.57 mm) across the sires segregating for TM-QTL. Loin muscle width, depth and area, loin muscle volume and dissected M. longissimus lumborum weight were significantly greater for TM/+ than +/+ lambs (+2.9% to +7.9%; P<0.05). There was significant evidence that the effect of TM-QTL on the various loin muscling traits measured was paternally polar overdominant (P<0.05). In contrast, there was an additive effect of TM-QTL on both live weight at 20 weeks and carcass weight; TM/TM animals were significantly (P<0.05) heavier than +/+ (+11.1% and +7.3%, respectively) and +/TM animals (+11.9% and +11.7%, respectively), with TM/+ intermediate. Weights of the leg, saddle and shoulder region (corrected for carcass weight) were similar in the genotypic groups. There was a tendency for lambs inheriting TM-QTL from their sire to be less fat with slightly more muscle than non-carriers. For example, carcass muscle weight measured by live animal CT-scanning was 2.8% higher in TM/TM than +/+ lambs (P<0.05), carcass muscle weight measured by carcass CT-scanning was 1.36% higher in TM/+ than +/+ lambs (P<0.05), and weight of fat trimmed from the carcass cuts was significantly lower for TM/+ than +/+ lambs (-11.2%; P<0.05). No negative effects of TM-QTL on carcass traits were found. Optimal commercial use of TM-QTL within the sheep industry would require some consideration, due to the apparently different mode of action of the two main effects of TM-QTL (on growth and muscling).

Functional Multi-Locus QTL Mapping of Temporal Trends in Scots Pine Wood Traits

PubMed Central

Li, Zitong; Hallingbäck, Henrik R.; Abrahamsson, Sara; Fries, Anders; Gull, Bengt Andersson; Sillanpää, Mikko J.; García-Gil, M. Rosario

2014-01-01

Quantitative trait loci (QTL) mapping of wood properties in conifer species has focused on single time point measurements or on trait means based on heterogeneous wood samples (e.g., increment cores), thus ignoring systematic within-tree trends. In this study, functional QTL mapping was performed for a set of important wood properties in increment cores from a 17-yr-old Scots pine (Pinus sylvestris L.) full-sib family with the aim of detecting wood trait QTL for general intercepts (means) and for linear slopes by increasing cambial age. Two multi-locus functional QTL analysis approaches were proposed and their performances were compared on trait datasets comprising 2 to 9 time points, 91 to 455 individual tree measurements and genotype datasets of amplified length polymorphisms (AFLP), and single nucleotide polymorphism (SNP) markers. The first method was a multilevel LASSO analysis whereby trend parameter estimation and QTL mapping were conducted consecutively; the second method was our Bayesian linear mixed model whereby trends and underlying genetic effects were estimated simultaneously. We also compared several different hypothesis testing methods under either the LASSO or the Bayesian framework to perform QTL inference. In total, five and four significant QTL were observed for the intercepts and slopes, respectively, across wood traits such as earlywood percentage, wood density, radial fiberwidth, and spiral grain angle. Four of these QTL were represented by candidate gene SNPs, thus providing promising targets for future research in QTL mapping and molecular function. Bayesian and LASSO methods both detected similar sets of QTL given datasets that comprised large numbers of individuals. PMID:25305041

Functional multi-locus QTL mapping of temporal trends in Scots pine wood traits.

PubMed

Li, Zitong; Hallingbäck, Henrik R; Abrahamsson, Sara; Fries, Anders; Gull, Bengt Andersson; Sillanpää, Mikko J; García-Gil, M Rosario

2014-10-09

Quantitative trait loci (QTL) mapping of wood properties in conifer species has focused on single time point measurements or on trait means based on heterogeneous wood samples (e.g., increment cores), thus ignoring systematic within-tree trends. In this study, functional QTL mapping was performed for a set of important wood properties in increment cores from a 17-yr-old Scots pine (Pinus sylvestris L.) full-sib family with the aim of detecting wood trait QTL for general intercepts (means) and for linear slopes by increasing cambial age. Two multi-locus functional QTL analysis approaches were proposed and their performances were compared on trait datasets comprising 2 to 9 time points, 91 to 455 individual tree measurements and genotype datasets of amplified length polymorphisms (AFLP), and single nucleotide polymorphism (SNP) markers. The first method was a multilevel LASSO analysis whereby trend parameter estimation and QTL mapping were conducted consecutively; the second method was our Bayesian linear mixed model whereby trends and underlying genetic effects were estimated simultaneously. We also compared several different hypothesis testing methods under either the LASSO or the Bayesian framework to perform QTL inference. In total, five and four significant QTL were observed for the intercepts and slopes, respectively, across wood traits such as earlywood percentage, wood density, radial fiberwidth, and spiral grain angle. Four of these QTL were represented by candidate gene SNPs, thus providing promising targets for future research in QTL mapping and molecular function. Bayesian and LASSO methods both detected similar sets of QTL given datasets that comprised large numbers of individuals. Copyright © 2014 Li et al.

Mapping and expression of candidate genes for development rate in rainbow trout (Oncorhynchus mykiss)

USDA-ARS?s Scientific Manuscript database

Development rate has important implications for many aspects of an individual's biology. In rainbow trout (Oncorhynchus mykiss), a major QTL for embryonic development rate has been detected on chromosome 5, but at present, few candidate genes have been mapped to this region. This paucity of known ge...

Genetic dissection of growth, wood basic density and gene expression in interspecific backcrosses of Eucalyptus grandis and E. urophylla

PubMed Central

2012-01-01

Background F1 hybrid clones of Eucalyptus grandis and E. urophylla are widely grown for pulp and paper production in tropical and subtropical regions. Volume growth and wood quality are priority objectives in Eucalyptus tree improvement. The molecular basis of quantitative variation and trait expression in eucalypt hybrids, however, remains largely unknown. The recent availability of a draft genome sequence (http://www.phytozome.net) and genome-wide genotyping platforms, combined with high levels of genetic variation and high linkage disequilibrium in hybrid crosses, greatly facilitate the detection of quantitative trait loci (QTLs) as well as underlying candidate genes for growth and wood property traits. In this study, we used Diversity Arrays Technology markers to assess the genetic architecture of volume growth (diameter at breast height, DBH) and wood basic density in four-year-old progeny of an interspecific backcross pedigree of E. grandis and E. urophylla. In addition, we used Illumina RNA-Seq expression profiling in the E. urophylla backcross family to identify cis- and trans-acting polymorphisms (eQTLs) affecting transcript abundance of genes underlying QTLs for wood basic density. Results A total of five QTLs for DBH and 12 for wood basic density were identified in the two backcross families. Individual QTLs for DBH and wood basic density explained 3.1 to 12.2% of phenotypic variation. Candidate genes underlying QTLs for wood basic density on linkage groups 8 and 9 were found to share trans-acting eQTLs located on linkage groups 4 and 10, which in turn coincided with QTLs for wood basic density suggesting that these QTLs represent segregating components of an underlying transcriptional network. Conclusion This is the first demonstration of the use of next-generation expression profiling to quantify transcript abundance in a segregating tree population and identify candidate genes potentially affecting wood property variation. The QTLs identified in this study provide a resource for identifying candidate genes and developing molecular markers for marker-assisted breeding of volume growth and wood basic density. Our results suggest that integrated analysis of transcript and trait variation in eucalypt hybrids can be used to dissect the molecular basis of quantitative variation in wood property traits. PMID:22817272

The Diversity Outbred Mouse Population

PubMed Central

Churchill, Gary A.; Gatti, Daniel M.; Munger, Steven C.; Svenson, Karen L.

2012-01-01

The Diversity Outbred (DO) population is a heterogeneous stock derived from the same eight founder strains as the Collaborative Cross (CC) inbred strains. Genetically heterogeneous DO mice display a broad range of phenotypes. Natural levels of heterozygosity provide genetic buffering and, as a result, DO mice are robust and breed well. Genetic mapping analysis in the DO presents new challenges and opportunities. Specialized algorithms are required to reconstruct haplotypes from high-density SNP array data. The eight founder haplotypes can be combined into 36 possible diplotypes, which must be accommodated in QTL mapping analysis. Population structure of the DO must be taken into account here. Estimated allele effects of 8 founder haplotypes provide information that is not available in two-parent crosses and can dramatically reduce the number of candidate loci. Allele effects can also distinguish chance co-location of QTL from pleiotropy – which provides a basis for establishing causality in expression QTL studies. We recommended sample sizes of 200 to 800 mice for QTL mapping studies, larger than for traditional crosses. The CC inbred strains provide a resource for independent validation of DO mapping results. Genetic heterogeneity of the DO can provide a powerful advantage in our ability to generalize conclusions to other genetically diverse populations. Genetic diversity can also help to avoid the pitfall of identifying an idiosyncratic reaction that occurs only in a limited genetic context. Informatics tools and data resources associated with the CC, the DO, and their founder strains are developing rapidly. We anticipate a flood of new results to follow as our community begins to adopt and utilize these new genetic resource populations. PMID:22892839

Behavioral genomics of honeybee foraging and nest defense

NASA Astrophysics Data System (ADS)

Hunt, Greg J.; Amdam, Gro V.; Schlipalius, David; Emore, Christine; Sardesai, Nagesh; Williams, Christie E.; Rueppell, Olav; Guzmán-Novoa, Ernesto; Arechavaleta-Velasco, Miguel; Chandra, Sathees; Fondrk, M. Kim; Beye, Martin; Page, Robert E.

2007-04-01

The honeybee has been the most important insect species for study of social behavior. The recently released draft genomic sequence for the bee will accelerate honeybee behavioral genetics. Although we lack sufficient tools to manipulate this genome easily, quantitative trait loci (QTLs) that influence natural variation in behavior have been identified and tested for their effects on correlated behavioral traits. We review what is known about the genetics and physiology of two behavioral traits in honeybees, foraging specialization (pollen versus nectar), and defensive behavior, and present evidence that map-based cloning of genes is more feasible in the bee than in other metazoans. We also present bioinformatic analyses of candidate genes within QTL confidence intervals (CIs). The high recombination rate of the bee made it possible to narrow the search to regions containing only 17-61 predicted peptides for each QTL, although CIs covered large genetic distances. Knowledge of correlated behavioral traits, comparative bioinformatics, and expression assays facilitated evaluation of candidate genes. An overrepresentation of genes involved in ovarian development and insulin-like signaling components within pollen foraging QTL regions suggests that an ancestral reproductive gene network was co-opted during the evolution of foraging specialization. The major QTL influencing defensive/aggressive behavior contains orthologs of genes involved in central nervous system activity and neurogenesis. Candidates at the other two defensive-behavior QTLs include modulators of sensory signaling ( Am5HT 7 serotonin receptor, AmArr4 arrestin, and GABA-B-R1 receptor). These studies are the first step in linking natural variation in honeybee social behavior to the identification of underlying genes.

The statistical analysis of multi-environment data: modeling genotype-by-environment interaction and its genetic basis

PubMed Central

Malosetti, Marcos; Ribaut, Jean-Marcel; van Eeuwijk, Fred A.

2013-01-01

Genotype-by-environment interaction (GEI) is an important phenomenon in plant breeding. This paper presents a series of models for describing, exploring, understanding, and predicting GEI. All models depart from a two-way table of genotype by environment means. First, a series of descriptive and explorative models/approaches are presented: Finlay–Wilkinson model, AMMI model, GGE biplot. All of these approaches have in common that they merely try to group genotypes and environments and do not use other information than the two-way table of means. Next, factorial regression is introduced as an approach to explicitly introduce genotypic and environmental covariates for describing and explaining GEI. Finally, QTL modeling is presented as a natural extension of factorial regression, where marker information is translated into genetic predictors. Tests for regression coefficients corresponding to these genetic predictors are tests for main effect QTL expression and QTL by environment interaction (QEI). QTL models for which QEI depends on environmental covariables form an interesting model class for predicting GEI for new genotypes and new environments. For realistic modeling of genotypic differences across multiple environments, sophisticated mixed models are necessary to allow for heterogeneity of genetic variances and correlations across environments. The use and interpretation of all models is illustrated by an example data set from the CIMMYT maize breeding program, containing environments differing in drought and nitrogen stress. To help readers to carry out the statistical analyses, GenStat® programs, 15th Edition and Discovery® version, are presented as “Appendix.” PMID:23487515

Six Novel Loci Associated with Circulating VEGF Levels Identified by a Meta-analysis of Genome-Wide Association Studies

PubMed Central

Song, Ci; Nutile, Teresa; Vernon Smith, Albert; Concas, Maria Pina; Traglia, Michela; Barbieri, Caterina; Ndiaye, Ndeye Coumba; Stathopoulou, Maria G.; Lagou, Vasiliki; Maestrale, Giovanni Battista; Sala, Cinzia; Debette, Stephanie; Kovacs, Peter; Lind, Lars; Lamont, John; Fitzgerald, Peter; Tönjes, Anke; Gudnason, Vilmundur; Toniolo, Daniela; Pirastu, Mario; Bellenguez, Celine; Vasan, Ramachandran S.; Ingelsson, Erik; Leutenegger, Anne-Louise; Johnson, Andrew D.; DeStefano, Anita L.; Visvikis-Siest, Sophie; Seshadri, Sudha; Ciullo, Marina

2016-01-01

Vascular endothelial growth factor (VEGF) is an angiogenic and neurotrophic factor, secreted by endothelial cells, known to impact various physiological and disease processes from cancer to cardiovascular disease and to be pharmacologically modifiable. We sought to identify novel loci associated with circulating VEGF levels through a genome-wide association meta-analysis combining data from European-ancestry individuals and using a dense variant map from 1000 genomes imputation panel. Six discovery cohorts including 13,312 samples were analyzed, followed by in-silico and de-novo replication studies including an additional 2,800 individuals. A total of 10 genome-wide significant variants were identified at 7 loci. Four were novel loci (5q14.3, 10q21.3, 16q24.2 and 18q22.3) and the leading variants at these loci were rs114694170 (MEF2C, P = 6.79x10-13), rs74506613 (JMJD1C, P = 1.17x10-19), rs4782371 (ZFPM1, P = 1.59x10-9) and rs2639990 (ZADH2, P = 1.72x10-8), respectively. We also identified two new independent variants (rs34528081, VEGFA, P = 1.52x10-18; rs7043199, VLDLR-AS1, P = 5.12x10-14) at the 3 previously identified loci and strengthened the evidence for the four previously identified SNPs (rs6921438, LOC100132354, P = 7.39x10-1467; rs1740073, C6orf223, P = 2.34x10-17; rs6993770, ZFPM2, P = 2.44x10-60; rs2375981, KCNV2, P = 1.48x10-100). These variants collectively explained up to 52% of the VEGF phenotypic variance. We explored biological links between genes in the associated loci using Ingenuity Pathway Analysis that emphasized their roles in embryonic development and function. Gene set enrichment analysis identified the ERK5 pathway as enriched in genes containing VEGF associated variants. eQTL analysis showed, in three of the identified regions, variants acting as both cis and trans eQTLs for multiple genes. Most of these genes, as well as some of those in the associated loci, were involved in platelet biogenesis and functionality, suggesting the importance of this process in regulation of VEGF levels. This work also provided new insights into the involvement of genes implicated in various angiogenesis related pathologies in determining circulating VEGF levels. The understanding of the molecular mechanisms by which the identified genes affect circulating VEGF levels could be important in the development of novel VEGF-related therapies for such diseases. PMID:26910538

QTL analysis of citrus tristeza virus-citradia interaction.

PubMed

Asins, M J; Bernet, G P; Ruiz, C; Cambra, M; Guerri, J; Carbonell, E A

2004-02-01

Citrus tristeza virus (CTV) has caused the death of millions of trees grafted on sour orange ( Citrus aurantium). However, this rootstock is very well adapted to the Mediterranean, semi-arid conditions. The aim of the present research is to genetically analyze the accumulation of CTV in a progeny derived from the cross between C. aurantium and Poncirus trifoliata, both resistant to CTV isolate T-346. Graft propagation of 104 hybrids was done on healthy sweet orange as a rootstock. Three months later, each rootstock was graft inoculated with two patches of infected tissue (isolate T-346). One, 2, and sometimes, 3 and 4 years after inoculation, hybrids and infected patches were tested for CTV by tissue-blot immuno-assay. Additionally, CTV multiplication was evaluated every year as the optical density of double-antibody sandwich enzyme-linked immuno-sorbent assay reactions. Linkage maps for P. trifoliata based on 63 markers, and for C. aurantium based on 157 markers, were used. Most molecular markers were microsatellites and IRAP (inter-retrotransposon amplified polymorphisms). Some analogues of resistance and expressed sequences were also included for candidate gene analysis. Resistance against CTV was analyzed as a quantitative trait (CTV accumulation) by QTL (quantitative trait loci) analysis to avoid the assumption of monogenic control. Three major resistance QTLs were detected where the P. trifoliata resistance gene, Ctv-R, had been previously located in other progenies. Up to five minor QTLs were detected ( Ctv-A(1) to Ctv-A(5)). A significant epistatic interaction involving Ctv-R(1) and Ctv-A(1) was also found. An analogue of a resistance gene is a candidate for Ctv-A(3), and two expressed sequences are candidates for Ctv-A(1) and Ctv-A(5). Single-strand conformational polymorphism analysis of CTV genes QTL P20 and P25 (coat protein) in susceptible hybrids, was carried out to test whether or not any QTL accumulation was a defeated resistance gene. Since the same haplotype of the virus was visualized independently on the CTV titer, differences in the amount of virions are not explained through the selection of CTV genotypes by the host, but through differences among citradias in CTV replication and/or movement.

Small- and Large-Effect Quantitative Trait Locus Interactions Underlie Variation in Yeast Sporulation Efficiency

PubMed Central

Lorenz, Kim; Cohen, Barak A.

2012-01-01

Quantitative trait loci (QTL) with small effects on phenotypic variation can be difficult to detect and analyze. Because of this a large fraction of the genetic architecture of many complex traits is not well understood. Here we use sporulation efficiency in Saccharomyces cerevisiae as a model complex trait to identify and study small-effect QTL. In crosses where the large-effect quantitative trait nucleotides (QTN) have been genetically fixed we identify small-effect QTL that explain approximately half of the remaining variation not explained by the major effects. We find that small-effect QTL are often physically linked to large-effect QTL and that there are extensive genetic interactions between small- and large-effect QTL. A more complete understanding of quantitative traits will require a better understanding of the numbers, effect sizes, and genetic interactions of small-effect QTL. PMID:22942125

A Comprehensive Analysis of Alternative Splicing in Paleopolyploid Maize.

PubMed

Mei, Wenbin; Liu, Sanzhen; Schnable, James C; Yeh, Cheng-Ting; Springer, Nathan M; Schnable, Patrick S; Barbazuk, William B

2017-01-01

Identifying and characterizing alternative splicing (AS) enables our understanding of the biological role of transcript isoform diversity. This study describes the use of publicly available RNA-Seq data to identify and characterize the global diversity of AS isoforms in maize using the inbred lines B73 and Mo17, and a related species, sorghum. Identification and characterization of AS within maize tissues revealed that genes expressed in seed exhibit the largest differential AS relative to other tissues examined. Additionally, differences in AS between the two genotypes B73 and Mo17 are greatest within genes expressed in seed. We demonstrate that changes in the level of alternatively spliced transcripts (intron retention and exon skipping) do not solely reflect differences in total transcript abundance, and we present evidence that intron retention may act to fine-tune gene expression across seed development stages. Furthermore, we have identified temperature sensitive AS in maize and demonstrate that drought-induced changes in AS involve distinct sets of genes in reproductive and vegetative tissues. Examining our identified AS isoforms within B73 × Mo17 recombinant inbred lines (RILs) identified splicing QTL (sQTL). The 43.3% of cis- sQTL regulated junctions are actually identified as alternatively spliced junctions in our analysis, while 10 Mb windows on each side of 48.2% of trans -sQTLs overlap with splicing related genes. Using sorghum as an out-group enabled direct examination of loss or conservation of AS between homeologous genes representing the two subgenomes of maize. We identify several instances where AS isoforms that are conserved between one maize homeolog and its sorghum ortholog are absent from the second maize homeolog, suggesting that these AS isoforms may have been lost after the maize whole genome duplication event. This comprehensive analysis provides new insights into the complexity of AS in maize.

Identification of Candidate Genes Responsible for Stem Pith Production Using Expression Analysis in Solid-Stemmed Wheat.

PubMed

Oiestad, A J; Martin, J M; Cook, J; Varella, A C; Giroux, M J

2017-07-01

The wheat stem sawfly (WSS) is an economically important pest of wheat in the Northern Great Plains. The primary means of WSS control is resistance associated with the single quantitative trait locus (QTL) , which controls most stem solidness variation. The goal of this study was to identify stem solidness candidate genes via RNA-seq. This study made use of 28 single nucleotide polymorphism (SNP) makers derived from expressed sequence tags (ESTs) linked to contained within a 5.13 cM region. Allele specific expression of EST markers was examined in stem tissue for solid and hollow-stemmed pairs of two spring wheat near isogenic lines (NILs) differing for the QTL. Of the 28 ESTs, 13 were located within annotated genes and 10 had detectable stem expression. Annotated genes corresponding to four of the ESTs were differentially expressed between solid and hollow-stemmed NILs and represent possible stem solidness gene candidates. Further examination of the 5.13 cM region containing the 28 EST markers identified 260 annotated genes. Twenty of the 260 linked genes were up-regulated in hollow NIL stems, while only seven genes were up-regulated in solid NIL stems. An -methyltransferase within the region of interest was identified as a candidate based on differential expression between solid and hollow-stemmed NILs and putative function. Further study of these candidate genes may lead to the identification of the gene(s) controlling stem solidness and an increased ability to select for wheat stem solidness and manage WSS. Copyright © 2017 Crop Science Society of America.

A comparative meta-analysis of QTL between intraspecific Gossypium hirsutum interspecific populations and Gossypium hirsutum x Gossypium barbadense populations

USDA-ARS?s Scientific Manuscript database

Recent Meta-analysis of quantitative trait loci (QTL) in tetraploid cotton (Gossypium spp.) has identified regions of the genome with high concentrations of various trait QTL called clusters, and specific trait QTL called hotspots. The Meta-analysis included all population types of Gossypium mixing ...

Quantitative trait loci that control body weight in DDD/Sgn and C57BL/6J inbred mice.

PubMed

Suto, Jun-Ichi; Kojima, Misaki

2017-02-01

Inbred DDD/Sgn mice are heavier than inbred C57BL/6J mice. In the present study, we performed quantitative trait loci (QTL) mapping for body weight using R/qtl in reciprocal F 2 male populations between the two strains. We identified four significant QTL on Chrs 1, 2, 5, and 17 (proximal region). The DDD/Sgn allele was associated with increased body weight at QTL on Chrs 1 and 5, and the DDD/Sgn allele was associated with decreased body weight at QTL on Chrs 2 and 17. A multiple regression analysis indicated that the detected QTL explain 30.94 % of the body weight variation. Because DDD/Sgn male mice have extremely high levels of circulating testosterone relative to other inbred mouse strains, we performed QTL mapping for plasma testosterone level to examine the effect of testosterone levels on body weight. We identified one suggestive QTL on Chr 5, which overlapped with body weight QTL. The DDD/Sgn allele was associated with increased testosterone level. Thus, we confirmed that there was a genetic basis for the changes in body weight and testosterone levels in male mice. These findings provide insights into the genetic mechanism by which body weight is controlled in male mice.

Genetic control and comparative genomic analysis of flowering time in Setaria (Poaceae).

PubMed

Mauro-Herrera, Margarita; Wang, Xuewen; Barbier, Hugues; Brutnell, Thomas P; Devos, Katrien M; Doust, Andrew N

2013-02-01

We report the first study on the genetic control of flowering in Setaria, a panicoid grass closely related to switchgrass, and in the same subfamily as maize and sorghum. A recombinant inbred line mapping population derived from a cross between domesticated Setaria italica (foxtail millet) and its wild relative Setaria viridis (green millet), was grown in eight trials with varying environmental conditions to identify a small number of quantitative trait loci (QTL) that control differences in flowering time. Many of the QTL across trials colocalize, suggesting that the genetic control of flowering in Setaria is robust across a range of photoperiod and other environmental factors. A detailed comparison of QTL for flowering in Setaria, sorghum, and maize indicates that several of the major QTL regions identified in maize and sorghum are syntenic orthologs with Setaria QTL, although the maize large effect QTL on chromosome 10 is not. Several Setaria QTL intervals had multiple LOD peaks and were composed of multiple syntenic blocks, suggesting that observed QTL represent multiple tightly linked loci. Candidate genes from flowering time pathways identified in rice and Arabidopsis were identified in Setaria QTL intervals, including those involved in the CONSTANS photoperiod pathway. However, only three of the approximately seven genes cloned for flowering time in maize colocalized with Setaria QTL. This suggests that variation in flowering time in separate grass lineages is controlled by a combination of conserved and lineage specific genes.

Genetic Control and Comparative Genomic Analysis of Flowering Time in Setaria (Poaceae)

PubMed Central

Mauro-Herrera, Margarita; Wang, Xuewen; Barbier, Hugues; Brutnell, Thomas P.; Devos, Katrien M.; Doust, Andrew N.

2013-01-01

We report the first study on the genetic control of flowering in Setaria, a panicoid grass closely related to switchgrass, and in the same subfamily as maize and sorghum. A recombinant inbred line mapping population derived from a cross between domesticated Setaria italica (foxtail millet) and its wild relative Setaria viridis (green millet), was grown in eight trials with varying environmental conditions to identify a small number of quantitative trait loci (QTL) that control differences in flowering time. Many of the QTL across trials colocalize, suggesting that the genetic control of flowering in Setaria is robust across a range of photoperiod and other environmental factors. A detailed comparison of QTL for flowering in Setaria, sorghum, and maize indicates that several of the major QTL regions identified in maize and sorghum are syntenic orthologs with Setaria QTL, although the maize large effect QTL on chromosome 10 is not. Several Setaria QTL intervals had multiple LOD peaks and were composed of multiple syntenic blocks, suggesting that observed QTL represent multiple tightly linked loci. Candidate genes from flowering time pathways identified in rice and Arabidopsis were identified in Setaria QTL intervals, including those involved in the CONSTANS photoperiod pathway. However, only three of the approximately seven genes cloned for flowering time in maize colocalized with Setaria QTL. This suggests that variation in flowering time in separate grass lineages is controlled by a combination of conserved and lineage specific genes. PMID:23390604

Genome-Wide Identification and Expression Analysis of WRKY Transcription Factors under Multiple Stresses in Brassica napus

PubMed Central

He, Yajun; Mao, Shaoshuai; Gao, Yulong; Zhu, Liying; Wu, Daoming; Cui, Yixin; Li, Jiana; Qian, Wei

2016-01-01

WRKY transcription factors play important roles in responses to environmental stress stimuli. Using a genome-wide domain analysis, we identified 287 WRKY genes with 343 WRKY domains in the sequenced genome of Brassica napus, 139 in the A sub-genome and 148 in the C sub-genome. These genes were classified into eight groups based on phylogenetic analysis. In the 343 WRKY domains, a total of 26 members showed divergence in the WRKY domain, and 21 belonged to group I. This finding suggested that WRKY genes in group I are more active and variable compared with genes in other groups. Using genome-wide identification and analysis of the WRKY gene family in Brassica napus, we observed genome duplication, chromosomal/segmental duplications and tandem duplication. All of these duplications contributed to the expansion of the WRKY gene family. The duplicate segments that were detected indicated that genome duplication events occurred in the two diploid progenitors B. rapa and B. olearecea before they combined to form B. napus. Analysis of the public microarray database and EST database for B. napus indicated that 74 WRKY genes were induced or preferentially expressed under stress conditions. According to the public QTL data, we identified 77 WRKY genes in 31 QTL regions related to various stress tolerance. We further evaluated the expression of 26 BnaWRKY genes under multiple stresses by qRT-PCR. Most of the genes were induced by low temperature, salinity and drought stress, indicating that the WRKYs play important roles in B. napus stress responses. Further, three BnaWRKY genes were strongly responsive to the three multiple stresses simultaneously, which suggests that these 3 WRKY may have multi-functional roles in stress tolerance and can potentially be used in breeding new rapeseed cultivars. We also found six tandem repeat pairs exhibiting similar expression profiles under the various stress conditions, and three pairs were mapped in the stress related QTL regions, indicating tandem duplicate WRKYs in the adaptive responses to environmental stimuli during the evolution process. Our results provide a framework for future studies regarding the function of WRKY genes in response to stress in B. napus. PMID:27322342

Genome-Wide Identification and Expression Analysis of WRKY Transcription Factors under Multiple Stresses in Brassica napus.

PubMed

He, Yajun; Mao, Shaoshuai; Gao, Yulong; Zhu, Liying; Wu, Daoming; Cui, Yixin; Li, Jiana; Qian, Wei

2016-01-01

WRKY transcription factors play important roles in responses to environmental stress stimuli. Using a genome-wide domain analysis, we identified 287 WRKY genes with 343 WRKY domains in the sequenced genome of Brassica napus, 139 in the A sub-genome and 148 in the C sub-genome. These genes were classified into eight groups based on phylogenetic analysis. In the 343 WRKY domains, a total of 26 members showed divergence in the WRKY domain, and 21 belonged to group I. This finding suggested that WRKY genes in group I are more active and variable compared with genes in other groups. Using genome-wide identification and analysis of the WRKY gene family in Brassica napus, we observed genome duplication, chromosomal/segmental duplications and tandem duplication. All of these duplications contributed to the expansion of the WRKY gene family. The duplicate segments that were detected indicated that genome duplication events occurred in the two diploid progenitors B. rapa and B. olearecea before they combined to form B. napus. Analysis of the public microarray database and EST database for B. napus indicated that 74 WRKY genes were induced or preferentially expressed under stress conditions. According to the public QTL data, we identified 77 WRKY genes in 31 QTL regions related to various stress tolerance. We further evaluated the expression of 26 BnaWRKY genes under multiple stresses by qRT-PCR. Most of the genes were induced by low temperature, salinity and drought stress, indicating that the WRKYs play important roles in B. napus stress responses. Further, three BnaWRKY genes were strongly responsive to the three multiple stresses simultaneously, which suggests that these 3 WRKY may have multi-functional roles in stress tolerance and can potentially be used in breeding new rapeseed cultivars. We also found six tandem repeat pairs exhibiting similar expression profiles under the various stress conditions, and three pairs were mapped in the stress related QTL regions, indicating tandem duplicate WRKYs in the adaptive responses to environmental stimuli during the evolution process. Our results provide a framework for future studies regarding the function of WRKY genes in response to stress in B. napus.

Deficiency mapping of quantitative trait loci affecting longevity in Drosophila melanogaster.

PubMed Central

Pasyukova, E G; Vieira, C; Mackay, T F

2000-01-01

In a previous study, sex-specific quantitative trait loci (QTL) affecting adult longevity were mapped by linkage to polymorphic roo transposable element markers, in a population of recombinant inbred lines derived from the Oregon and 2b strains of Drosophila melanogaster. Two life span QTL were each located on chromosomes 2 and 3, within sections 33E-46C and 65D-85F on the cytological map, respectively. We used quantitative deficiency complementation mapping to further resolve the locations of life span QTL within these regions. The Oregon and 2b strains were each crossed to 47 deficiencies spanning cytological regions 32F-44E and 64C-76B, and quantitative failure of the QTL alleles to complement the deficiencies was assessed. We initially detected a minimum of five and four QTL in the chromosome 2 and 3 regions, respectively, illustrating that multiple linked factors contribute to each QTL detected by recombination mapping. The QTL locations inferred from deficiency mapping did not generally correspond to those of candidate genes affecting oxidative and thermal stress or glucose metabolism. The chromosome 2 QTL in the 35B-E region was further resolved to a minimum of three tightly linked QTL, containing six genetically defined loci, 24 genes, and predicted genes that are positional candidates corresponding to life span QTL. This region was also associated with quantitative variation in life span in a sample of 10 genotypes collected from nature. Quantitative deficiency complementation is an efficient method for fine-scale QTL mapping in Drosophila and can be further improved by controlling the background genotype of the strains to be tested. PMID:11063689

lme4qtl: linear mixed models with flexible covariance structure for genetic studies of related individuals.

PubMed

Ziyatdinov, Andrey; Vázquez-Santiago, Miquel; Brunel, Helena; Martinez-Perez, Angel; Aschard, Hugues; Soria, Jose Manuel

2018-02-27

Quantitative trait locus (QTL) mapping in genetic data often involves analysis of correlated observations, which need to be accounted for to avoid false association signals. This is commonly performed by modeling such correlations as random effects in linear mixed models (LMMs). The R package lme4 is a well-established tool that implements major LMM features using sparse matrix methods; however, it is not fully adapted for QTL mapping association and linkage studies. In particular, two LMM features are lacking in the base version of lme4: the definition of random effects by custom covariance matrices; and parameter constraints, which are essential in advanced QTL models. Apart from applications in linkage studies of related individuals, such functionalities are of high interest for association studies in situations where multiple covariance matrices need to be modeled, a scenario not covered by many genome-wide association study (GWAS) software. To address the aforementioned limitations, we developed a new R package lme4qtl as an extension of lme4. First, lme4qtl contributes new models for genetic studies within a single tool integrated with lme4 and its companion packages. Second, lme4qtl offers a flexible framework for scenarios with multiple levels of relatedness and becomes efficient when covariance matrices are sparse. We showed the value of our package using real family-based data in the Genetic Analysis of Idiopathic Thrombophilia 2 (GAIT2) project. Our software lme4qtl enables QTL mapping models with a versatile structure of random effects and efficient computation for sparse covariances. lme4qtl is available at https://github.com/variani/lme4qtl .

Quantitative trait loci for yield and grain plumpness relative to maturity in three populations of barley (Hordeum vulgare L.) grown in a low rain-fall environment

PubMed Central

Obsa, Bulti Tesso; Eglinton, Jason; Coventry, Stewart; March, Timothy; Guillaume, Maxime; Le, Thanh Phuoc; Hayden, Matthew; Langridge, Peter

2017-01-01

Identifying yield and grain plumpness QTL that are independent of developmental variation or phenology is of paramount importance for developing widely adapted and stable varieties through the application of marker assisted selection. The current study was designed to dissect the genetic basis of yield performance and grain plumpness in southern Australia using three doubled haploid (DH) populations developed from crosses between adapted parents that are similar in maturity and overall plant development. Three interconnected genetic populations, Commander x Fleet (CF), Commander x WI4304 (CW), and Fleet x WI4304 (FW) developed from crossing of Australian elite barley genotypes, were used to map QTL controlling yield and grain plumpness. QTL for grain plumpness and yield were analysed using genetic linkage maps made of genotyping-by-sequencing markers and major phenology genes, and field trials at three drought prone environments for two growing seasons. Seventeen QTL were detected for grain plumpness. Eighteen yield QTL explaining from 1.2% to 25.0% of the phenotypic variation were found across populations and environments. Significant QTL x environment interaction was observed for all grain plumpness and yield QTL, except QPlum.FW-4H.1 and QYld.FW-2H.1. Unlike previous yield QTL studies in barley, none of the major developmental genes, including Ppd-H1, Vrn-H1, Vrn-H2 and Vrn-H3, that drive barley adaption significantly affected grain plumpness and yield here. Twenty-two QTL controlled yield or grain plumpness independently of known maturity QTL or genes. Adjustment for maturity effects through co-variance analysis had no major effect on these yield QTL indicating that they control yield per se. PMID:28542571

Quantitative trait loci for yield and grain plumpness relative to maturity in three populations of barley (Hordeum vulgare L.) grown in a low rain-fall environment.

PubMed

Obsa, Bulti Tesso; Eglinton, Jason; Coventry, Stewart; March, Timothy; Guillaume, Maxime; Le, Thanh Phuoc; Hayden, Matthew; Langridge, Peter; Fleury, Delphine

2017-01-01

Identifying yield and grain plumpness QTL that are independent of developmental variation or phenology is of paramount importance for developing widely adapted and stable varieties through the application of marker assisted selection. The current study was designed to dissect the genetic basis of yield performance and grain plumpness in southern Australia using three doubled haploid (DH) populations developed from crosses between adapted parents that are similar in maturity and overall plant development. Three interconnected genetic populations, Commander x Fleet (CF), Commander x WI4304 (CW), and Fleet x WI4304 (FW) developed from crossing of Australian elite barley genotypes, were used to map QTL controlling yield and grain plumpness. QTL for grain plumpness and yield were analysed using genetic linkage maps made of genotyping-by-sequencing markers and major phenology genes, and field trials at three drought prone environments for two growing seasons. Seventeen QTL were detected for grain plumpness. Eighteen yield QTL explaining from 1.2% to 25.0% of the phenotypic variation were found across populations and environments. Significant QTL x environment interaction was observed for all grain plumpness and yield QTL, except QPlum.FW-4H.1 and QYld.FW-2H.1. Unlike previous yield QTL studies in barley, none of the major developmental genes, including Ppd-H1, Vrn-H1, Vrn-H2 and Vrn-H3, that drive barley adaption significantly affected grain plumpness and yield here. Twenty-two QTL controlled yield or grain plumpness independently of known maturity QTL or genes. Adjustment for maturity effects through co-variance analysis had no major effect on these yield QTL indicating that they control yield per se.

Quantitative trait loci affecting the 3D skull shape and size in mouse and prioritization of candidate genes in-silico

PubMed Central

Maga, A. Murat; Navarro, Nicolas; Cunningham, Michael L.; Cox, Timothy C.

2015-01-01

We describe the first application of high-resolution 3D micro-computed tomography, together with 3D landmarks and geometric morphometrics, to map QTL responsible for variation in skull shape and size using a backcross between C57BL/6J and A/J inbred strains. Using 433 animals, 53 3D landmarks, and 882 SNPs from autosomes, we identified seven QTL responsible for the skull size (SCS.qtl) and 30 QTL responsible for the skull shape (SSH.qtl). Size, sex, and direction-of-cross were all significant factors and included in the analysis as covariates. All autosomes harbored at least one SSH.qtl, sometimes up to three. Effect sizes of SSH.qtl appeared to be small, rarely exceeding 1% of the overall shape variation. However, they account for significant amount of variation in some specific directions of the shape space. Many QTL have stronger effect on the neurocranium than expected from a random vector that will parcellate uniformly across the four cranial regions. On the contrary, most of QTL have an effect on the palate weaker than expected. Combined interval length of 30 SSH.qtl was about 315 MB and contained 2476 known protein coding genes. We used a bioinformatics approach to filter these candidate genes and identified 16 high-priority candidates that are likely to play a role in the craniofacial development and disorders. Thus, coupling the QTL mapping approach in model organisms with candidate gene enrichment approaches appears to be a feasible way to identify high-priority candidates genes related to the structure or tissue of interest. PMID:25859222

Comparative genome-wide mapping versus extreme pool-genotyping and development of diagnostic SNP markers linked to QTL for adult plant resistance to stripe rust in common wheat.

PubMed

Wu, Jianhui; Huang, Shuo; Zeng, Qingdong; Liu, Shengjie; Wang, Qilin; Mu, Jingmei; Yu, Shizhou; Han, Dejun; Kang, Zhensheng

2018-06-16

A major stripe rust resistance QTL on chromosome 4BL was localized to a 4.5-Mb interval using comparative QTL mapping methods and validated in 276 wheat genotypes by haplotype analysis. CYMMIT-derived wheat line P10103 was previously identified to have adult plant resistance (APR) to stripe rust in the greenhouse and field. The conventional approach for QTL mapping in common wheat is laborious. Here, we performed QTL detection of APR using a combination of genome-wide scanning and extreme pool-genotyping. SNP-based genetic maps were constructed using the Wheat55 K SNP array to genotype a recombinant inbred line (RIL) population derived from the cross Mingxian 169 × P10103. Five stable QTL were detected across multiple environments. A fter comparing SNP profiles from contrasting, extreme DNA pools of RILs six putative QTL were located to approximate chromosome positions. A major QTL on chromosome 4B was identified in F 2:4 contrasting pools from cross Zhengmai 9023 × P10103. A consensus QTL (LOD = 26-40, PVE = 42-55%), named QYr.nwafu-4BL, was defined and localized to a 4.5-Mb interval flanked by SNP markers AX-110963704 and AX-110519862 in chromosome arm 4BL. Based on stripe rust response, marker genotypes, pedigree analysis and mapping data, QYr.nwafu-4BL is likely to be a new APR QTL. The applicability of the SNP-based markers flanking QYr.nwafu-4BL was validated on a diversity panel of 276 wheat lines. The additional minor QTL on chromosomes 4A, 5A, 5B and 6A enhanced the level of resistance conferred by QYr.nwafu-4BL. Marker-assisted pyramiding of QYr.nwafu-4BL and other favorable minor QTL in new wheat cultivars should improve the level of APR to stripe rust.

QTL mapping of downy and powdery mildew resistances in PI 197088 cucumber with genotyping-by-sequencing in RIL population.

PubMed

Wang, Yuhui; VandenLangenberg, Kyle; Wen, Changlong; Wehner, Todd C; Weng, Yiqun

2018-03-01

Host resistances in PI 197088 cucumber to downy and powdery mildew pathogens are conferred by 11 (3 with major effect) and 4 (1 major effect) QTL, respectively, and three of which are co-localized. The downy mildew (DM) and powdery mildew (PM) are the two most important foliar diseases of cucurbit crops worldwide. The cucumber accession PI 197088 exhibits high-level resistances to both pathogens. Here, we reported QTL mapping results for DM and PM resistances with 148 recombinant inbred lines from a cross between PI 197088 and the susceptible line 'Coolgreen'. Phenotypic data on responses to natural DM and PM infection were collected in multi-year and multi-location replicated field trials. A high-density genetic map with 2780 single nucleotide polymorphisms (SNPs) from genotyping-by-sequencing and 55 microsatellite markers was developed, which revealed genomic regions with segregation distortion and mis-assemblies in the '9930' cucumber draft genome. QTL analysis identified 11 and 4 QTL for DM and PM resistances accounting for more than 73.5 and 63.0% total phenotypic variance, respectively. Among the 11 DM resistance QTL, dm5.1, dm5.2, and dm5.3 were major-effect contributing QTL, whereas dm1.1, dm2.1, and dm6.2 conferred susceptibility. Of the 4 QTL for PM resistance, pm5.1 was the major-effect QTL explaining 32.4% phenotypic variance and the minor-effect QTL pm6.1 contributed to disease susceptibility. Three PM QTL, pm2.1, pm5.1, and pm6.1, were co-localized with DM QTL dm2.1, dm5.2, and dm6.1, respectively, which was consistent with the observed linkage of PM and DM resistances in PI 197088. The genetic architecture of DM resistance in PI 197088 and another resistant line WI7120 (PI 330628) was compared, and the potential of using PI 197088 in cucumber breeding for downy and powdery mildew resistances is discussed.

Genetic Analysis of Fusarium Head Blight Resistance in CIMMYT Bread Wheat Line C615 Using Traditional and Conditional QTL Mapping

PubMed Central

Yi, Xin; Cheng, Jingye; Jiang, Zhengning; Hu, Wenjing; Bie, Tongde; Gao, Derong; Li, Dongsheng; Wu, Ronglin; Li, Yuling; Chen, Shulin; Cheng, Xiaoming; Liu, Jian; Zhang, Yong; Cheng, Shunhe

2018-01-01

Fusarium head blight (FHB) is a destructive wheat disease present throughout the world, and host resistance is an effective and economical strategy used to control FHB. Lack of adequate resistance resource is still a main bottleneck for FHB genetics and wheat breeding research. The synthetic-derived bread wheat line C615, which does not carry the Fhb1 gene, is a promising source of FHB resistance for breeding. A population of 198 recombinant inbred lines (RILs) produced by crossing C615 with the susceptible cultivar Yangmai 13 was evaluated for FHB response using point and spray inoculations. As the disease phenotype is frequently complicated by other agronomic traits, we used both traditional and multivariate conditional QTL mapping approaches to investigate the genetic relationships (at the individual QTL level) between FHB resistance and plant height (PH), spike compactness (SC), and days to flowering (FD). A linkage map was constructed from 3,901 polymorphic SNP markers, which covered 2,549.2 cM. Traditional and conditional QTL mapping analyses found 13 and 22 QTL for FHB, respectively; 10 were identified by both methods. Among these 10, three QTL from C615 were detected in multiple years; these QTL were located on chromosomes 2AL, 2DS, and 2DL. Conditional QTL mapping analysis indicated that, at the QTL level, SC strongly influenced FHB in point inoculation; whereas PH and SC contributed more to FHB than did FD in spray inoculation. The three stable QTL (QFhbs-jaas.2AL, QFhbp-jaas.2DS, and QFhbp-jaas.2DL) for FHB were partly affected by or were independent of the three agronomic traits. The QTL detected in this study improve our understanding of the genetic relationships between FHB response and related traits at the QTL level and provide useful information for marker-assisted selection for the improvement of FHB resistance in breeding. PMID:29780395

Molecular mapping of QTL alleles of Brassica oleracea affecting days to flowering and photosensitivity in spring Brassica napus

PubMed Central

Bennett, Rick A.; Kebede, Berisso

2018-01-01

Earliness of flowering and maturity are important traits in spring Brassica napus canola–whether grown under long- or short-day condition. By use of a spring B. napus mapping population carrying the genome content of B. oleracea and testing this population under 10 to 18 h photoperiod and 18 to 20 0C (day) temperature conditions, we identified a major QTL on the chromosome C1 affecting flowering time without being influenced by photoperiod and temperature, and a major QTL on C9 affecting flowering time under a short photoperiod (10 h); in both cases, the QTL alleles reducing the number of days to flowering in B. napus were introgressed from the late flowering species B. oleracea. Additive effect of the C1 QTL allele at 14 to18 h photoperiod was 1.1 to 2.9 days; however, the same QTL allele exerted an additive effect of 6.2 days at 10 h photoperiod. Additive effect of the C9 QTL at 10 h photoperiod was 2.8 days. These two QTL also showed significant interaction in the control of flowering only under a short-day (10 h photoperiod) condition with an effect of 2.3 days. A few additional QTL were also detected on the chromosomes C2 and C8; however, none of these QTL could be detected under all photoperiod and temperature conditions. BLASTn search identified several putative flowering time genes on the chromosomes C1 and C9 and located the physical position of the QTL markers in the Brassica genome; however, only a few of these genes were found within the QTL region. Thus, the molecular markers and the genomic regions identified in this research could potentially be used in breeding for the development of early flowering photoinsensitive B. napus canola cultivars, as well as for identification of candidate genes involved in flowering time variation and photosensitivity. PMID:29320498

Molecular mapping of QTL alleles of Brassica oleracea affecting days to flowering and photosensitivity in spring Brassica napus.

PubMed

Rahman, Habibur; Bennett, Rick A; Kebede, Berisso

2018-01-01

Earliness of flowering and maturity are important traits in spring Brassica napus canola-whether grown under long- or short-day condition. By use of a spring B. napus mapping population carrying the genome content of B. oleracea and testing this population under 10 to 18 h photoperiod and 18 to 20 0C (day) temperature conditions, we identified a major QTL on the chromosome C1 affecting flowering time without being influenced by photoperiod and temperature, and a major QTL on C9 affecting flowering time under a short photoperiod (10 h); in both cases, the QTL alleles reducing the number of days to flowering in B. napus were introgressed from the late flowering species B. oleracea. Additive effect of the C1 QTL allele at 14 to18 h photoperiod was 1.1 to 2.9 days; however, the same QTL allele exerted an additive effect of 6.2 days at 10 h photoperiod. Additive effect of the C9 QTL at 10 h photoperiod was 2.8 days. These two QTL also showed significant interaction in the control of flowering only under a short-day (10 h photoperiod) condition with an effect of 2.3 days. A few additional QTL were also detected on the chromosomes C2 and C8; however, none of these QTL could be detected under all photoperiod and temperature conditions. BLASTn search identified several putative flowering time genes on the chromosomes C1 and C9 and located the physical position of the QTL markers in the Brassica genome; however, only a few of these genes were found within the QTL region. Thus, the molecular markers and the genomic regions identified in this research could potentially be used in breeding for the development of early flowering photoinsensitive B. napus canola cultivars, as well as for identification of candidate genes involved in flowering time variation and photosensitivity.

Genetic Analysis of Fusarium Head Blight Resistance in CIMMYT Bread Wheat Line C615 Using Traditional and Conditional QTL Mapping.

PubMed

Yi, Xin; Cheng, Jingye; Jiang, Zhengning; Hu, Wenjing; Bie, Tongde; Gao, Derong; Li, Dongsheng; Wu, Ronglin; Li, Yuling; Chen, Shulin; Cheng, Xiaoming; Liu, Jian; Zhang, Yong; Cheng, Shunhe

2018-01-01

Fusarium head blight (FHB) is a destructive wheat disease present throughout the world, and host resistance is an effective and economical strategy used to control FHB. Lack of adequate resistance resource is still a main bottleneck for FHB genetics and wheat breeding research. The synthetic-derived bread wheat line C615, which does not carry the Fhb1 gene, is a promising source of FHB resistance for breeding. A population of 198 recombinant inbred lines (RILs) produced by crossing C615 with the susceptible cultivar Yangmai 13 was evaluated for FHB response using point and spray inoculations. As the disease phenotype is frequently complicated by other agronomic traits, we used both traditional and multivariate conditional QTL mapping approaches to investigate the genetic relationships (at the individual QTL level) between FHB resistance and plant height (PH), spike compactness (SC), and days to flowering (FD). A linkage map was constructed from 3,901 polymorphic SNP markers, which covered 2,549.2 cM. Traditional and conditional QTL mapping analyses found 13 and 22 QTL for FHB, respectively; 10 were identified by both methods. Among these 10, three QTL from C615 were detected in multiple years; these QTL were located on chromosomes 2AL, 2DS, and 2DL. Conditional QTL mapping analysis indicated that, at the QTL level, SC strongly influenced FHB in point inoculation; whereas PH and SC contributed more to FHB than did FD in spray inoculation. The three stable QTL ( QFhbs-jaas.2AL, QFhbp-jaas.2DS , and QFhbp-jaas.2DL ) for FHB were partly affected by or were independent of the three agronomic traits. The QTL detected in this study improve our understanding of the genetic relationships between FHB response and related traits at the QTL level and provide useful information for marker-assisted selection for the improvement of FHB resistance in breeding.

Comparative mapping of quantitative trait loci for Fusarium head blight resistance and anther retention in the winter wheat population Capo × Arina.

PubMed

Buerstmayr, Maria; Buerstmayr, Hermann

2015-08-01

Fusarium resistance in Arina is highly quantitative and governed by multiple small effect QTL. Anther retention has a high correlation with FHB susceptibility and appears a practicable indirect selection target for enhancing FHB resistance. The Swiss winter wheat cultivar Arina possesses a high resistance level constituted by a number of small to medium effect QTL reported from three independent mapping populations. Yet these overlap only for one resistance QTL on the long arm of chromosome 1B. The present study characterized Fusarium head blight (FHB) resistance in a population of 171 recombinant inbred lines from a cross between Arina (resistant) and Capo (moderately resistant). The population was evaluated for FHB resistance under field conditions for 3 years. Additionally, we phenotyped anther retention, plant height and flowering date to analyze their association with resistance. Lines with a low proportion of retained anthers after flowering and tall plants were significantly less diseased, while flowering date had no association with FHB severity. QTL analysis identified eight small to medium effect QTL for FHB severity, of which QTL on 1BS, 3B, 4AL and 6BL likely correspond to resistance alleles already detected in previously studied Arina populations. QTL for anther retention mapped to 4AL, 6BL and 5AS. Notably, QTL on 4AL and 6BL overlapped with QTL for FHB severity. A single small effect QTL for plant height was detected on 5AS and no QTL was identified for flowering date. Genotypes having three or four resistance alleles in combination showed a good resistance level, indicating pyramiding resistance QTL as a powerful approach for breeding resistant cultivars. Selection for rapid and complete anther extrusion appears promising as an indirect selection criterion for enhancing FHB resistance.

Confirmation and fine-mapping of a major QTL for resistance to infectious pancreatic necrosis in Atlantic salmon (Salmo salar): population-level associations between markers and trait

PubMed Central

Moen, Thomas; Baranski, Matthew; Sonesson, Anna K; Kjøglum, Sissel

2009-01-01

Background Infectious pancreatic necrosis (IPN) is one of the most prevalent and economically devastating diseases in Atlantic salmon (Salmo salar) farming worldwide. The disease causes large mortalities at both the fry- and post-smolt stages. Family selection for increased IPN resistance is performed through the use of controlled challenge tests, where survival rates of sib-groups are recorded. However, since challenge-tested animals cannot be used as breeding candidates, within-family selection is not performed and only half of the genetic variation for IPN resistance is being exploited. DNA markers linked to quantitative trait loci (QTL) affecting IPN resistance would therefore be a powerful selection tool. The aim of this study was to identify and fine-map QTL for IPN-resistance in Atlantic salmon, for use in marker-assisted selection to increase the rate of genetic improvement for this trait. Results A genome scan was carried out using 10 large full-sib families of challenge-tested Atlantic salmon post-smolts and microsatellite markers distributed across the genome. One major QTL for IPN-resistance was detected, explaining 29% and 83% of the phenotypic and genetic variances, respectively. This QTL mapped to the same location as a QTL recently detected in a Scottish Atlantic salmon population. The QTL was found to be segregating in 10 out of 20 mapping parents, and subsequent fine-mapping with additional markers narrowed the QTL peak to a 4 cM region on linkage group 21. Challenge-tested fry were used to show that the QTL had the same effect on fry as on post-smolt, with the confidence interval for QTL position in fry overlapping the confidence interval found in post-smolts. A total of 178 parents were tested for segregation of the QTL, identifying 72 QTL-heterozygous parents. Genotypes at QTL-heterozygous parents were used to determine linkage phases between alleles at the underlying DNA polymorphism and alleles at single markers or multi-marker haplotypes. One four-marker haplotype was found to be the best predictor of QTL alleles, and was successfully used to deduce genotypes of the underlying polymorphism in 72% of the parents of the next generation within a breeding nucleus. A highly significant population-level correlation was found between deduced alleles at the underlying polymorphism and survival of offspring groups in the fry challenge test, parents with the three deduced genotypes (QQ, Qq, qq) having mean offspring mortality rates of 0.13, 0.32, and 0.49, respectively. The frequency of the high-resistance allele (Q) in the population was estimated to be 0.30. Apart from this major QTL, one other experiment-wise significant QTL for IPN-resistance was detected, located on linkage group 4. Conclusion The QTL confirmed in this study represents a case of a major gene explaining the bulk of genetic variation for a presumed complex trait. QTL genotypes were deduced within most parents of the 2005 generation of a major breeding company, providing a solid framework for linkage-based MAS within the whole population in subsequent generations. Since haplotype-trait associations valid at the population level were found, there is also a potential for MAS based on linkage disequilibrium (LD). However, in order to use MAS across many generations without reassessment of linkage phases between markers and the underlying polymorphism, the QTL needs to be positioned with even greater accuracy. This will require higher marker densities than are currently available. PMID:19664221

The ZmCLA4 gene in the qLA4-1 QTL controls leaf angle in maize (Zea mays L.).

PubMed

Zhang, J; Ku, L X; Han, Z P; Guo, S L; Liu, H J; Zhang, Z Z; Cao, L R; Cui, X J; Chen, Y H

2014-09-01

Maize architecture is a major contributing factor to their high level of productivity. Maize varieties with an erect-leaf-angle (LA) phenotype, which increases light harvesting for photosynthesis and grain-filling, have elevated grain yields. Although a large body of information is available on the map positions of quantitative trait loci (QTL) for LA, little is known about the molecular mechanism of these QTL. In this study, the ZmCLA4 gene, which is responsible for the qLA4-1 QTL associated with LA, was identified and isolated by fine mapping and positional cloning. The ZmCLA4 gene is an orthologue of LAZY1 in rice and Arabidopsis. Sequence analysis revealed two SNPs and two indel sites in ZmCLA4 between the D132 and D132-NIL inbred maize lines. Association analysis showed that C/T/mutation667 and CA/indel965 were strongly associated with LA. Subcellular localization verified the functions of a predicted transmembrane domain and a nuclear localization signal in ZmCLA4. Transgenic maize plants with a down-regulated ZmCLA4 RNAi construct and transgenic rice plants over-expressing ZmCLA4 confirmed that the ZmCLA4 gene located in the qLA4 QTL regulated LA. The allelic variants of ZmCLA4 in the D132 and D132-NIL lines exhibited significant differences in leaf angle. ZmCLA4 transcript accumulation was higher in D132-NIL than in D132 during all the developmental stages and was negatively correlated with LA. The gravitropic response was increased and cell shape and number at the leaf and stem junctions were altered in D132-NIL relative to D132. These findings suggest that ZmCLA4 plays a negative role in the control of maize LA through the alteration of mRNA accumulation, leading to altered shoot gravitropism and cell development. The cloning of the gene responsible for the qLA4-1 QTL provides information on the molecular mechanisms of LA in maize and an opportunity for the improvement of plant architecture with regard to LA through maize breeding. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

The expression of a naturally occuriing truncated allele of an alpha-SNAP gene suppresses plant parasitic nematode infection

USDA-ARS?s Scientific Manuscript database

rhg1, defined within a 67 kb region of DNA on chromosome 18, is a major quantitative trait locus (QTL) in Glycine max (soybean) providing defense to the soybean cyst nematode (Heterodera glycines). Transcriptional mapping experiments identified an alpha soluble NSF attachment protein (alpha-SNAP) wi...

QTL mapping of flowering time, fruit size and number in populations involving andromonoecious true lemon cucumber

USDA-ARS?s Scientific Manuscript database

Andromonoecious sex expression in cucumber is controlled by the m locus, which encodes the 1-aminocyclopropane-1 –carboxylic acid synthase (ACS) in the ethylene biosynthesis pathway. This gene seems to have pleotropic effects on fruit size and number, but the genetic basis is unknown. The True Lemon...

Linkage of an ABCC transporter to a single QTL that controls Ostrinia nubilalis larval resistance to the Bacillus thuringiensis Cry1Fa toxin

USDA-ARS?s Scientific Manuscript database

Field evolved resistance of insect populations to Bacillus thuringiensis (Bt) crystalline (Cry) toxins expressed by crop plants has resulted in reduced control of insect feeding damage to field crops, and threatens the sustainability of Bt transgenic technologies. A single quantitative trait locus ...

Genome-scan analysis for genetic mapping of quantitative trait loci underlying birth weight and onset of puberty in doe kids (Capra hircus).

PubMed

Esmailizadeh, A K

2014-12-01

The objective of this study was to locate quantitative trait loci (QTL) causing variation in birth weight and age of puberty of doe kids in a population of Rayini cashmere goats. Four hundred and thirty kids from five half-sib families were genotyped for 116 microsatellite markers located on the caprine autosomes. The traits recorded were birth weight of the male and female kids, body weight at puberty, average daily gain from birth to age of puberty and age at puberty of the doe kids. QTL analysis was conducted using the least squares interval mapping approach. Linkage analysis indicated significant QTL for birth weight on Capra hircus chromosomes (CHI) 4, 5, 6, 18 and 21. Five QTL located on CHI 5, 14 and 29 were associated with age at puberty. Across-family analysis revealed evidence for overlapping QTL affecting birth weight (78 cM), body weight at puberty (72 cM), average daily gain from birth to age of puberty (72 cM) and age at puberty (76 cM) on CHI 5 and overlapping QTL controlling body weight at puberty and age at puberty on CHI 14 at 18-19 cM. The proportion of the phenotypic variance explained by the detected QTL ranged between 7.9% and 14.4%. Confirming some of the previously reported results for birth weight and growth QTL in goats, this study identified more QTL for these traits and is the first report of QTL for onset of puberty in doe kids. © 2014 Stichting International Foundation for Animal Genetics.

Replication of long-bone length QTL in the F9-F10 LG,SM advanced intercross.

PubMed

Norgard, Elizabeth A; Jarvis, Joseph P; Roseman, Charles C; Maxwell, Taylor J; Kenney-Hunt, Jane P; Samocha, Kaitlin E; Pletscher, L Susan; Wang, Bing; Fawcett, Gloria L; Leatherwood, Christopher J; Wolf, Jason B; Cheverud, James M

2009-04-01

Quantitative trait locus (QTL) mapping techniques are frequently used to identify genomic regions associated with variation in phenotypes of interest. However, the F(2) intercross and congenic strain populations usually employed have limited genetic resolution resulting in relatively large confidence intervals that greatly inhibit functional confirmation of statistical results. Here we use the increased resolution of the combined F(9) and F(10) generations (n = 1455) of the LG,SM advanced intercross to fine-map previously identified QTL associated with the lengths of the humerus, ulna, femur, and tibia. We detected 81 QTL affecting long-bone lengths. Of these, 49 were previously identified in the combined F(2)-F(3) population of this intercross, while 32 represent novel contributors to trait variance. Pleiotropy analysis suggests that most QTL affect three to four long bones or serially homologous limb segments. We also identified 72 epistatic interactions involving 38 QTL and 88 novel regions. This analysis shows that using later generations of an advanced intercross greatly facilitates fine-mapping of confidence intervals, resolving three F(2)-F(3) QTL into multiple linked loci and narrowing confidence intervals of other loci, as well as allowing identification of additional QTL. Further characterization of the biological bases of these QTL will help provide a better understanding of the genetics of small variations in long-bone length.

Application of a new IBD-based QTL mapping method to common wheat breeding population: analysis of kernel hardness and dough strength.

PubMed

Crepieux, Sebastien; Lebreton, Claude; Flament, Pascal; Charmet, Gilles

2005-11-01

Mapping quantitative trait loci (QTL) in plants is usually conducted using a population derived from a cross between two inbred lines. The power of such QTL detection and the estimation of the effects highly depend on the choice of the two parental lines. Thus, the QTL found represent only a small part of the genetic architecture and can be of limited economical interest in marker-assisted selection. On the other hand, applied breeding programmes evaluate large numbers of progeny derived from multiple-related crosses for a wide range of agronomic traits. It is assumed that the development of statistical techniques to deal with pedigrees in existing plant populations would increase the relevance and cost effectiveness of QTL mapping in a breeding context. In this study, we applied a two-step IBD-based-variance component method to a real wheat breeding population, composed of 374 F6 lines derived from 80 different parents. Two bread wheat quality related traits were analysed by the method. Results obtained show very close agreement with major genes and QTL already known for those two traits. With this new QTL mapping strategy, inferences about QTL can be drawn across the breeding programme rather than being limited to the sample of progeny from a single cross and thus the use of the detected QTL in assisting breeding would be facilitated.

Identification of quantitative trait loci influencing wood specific gravity in an outbred pedigree of loblolly pine

Treesearch

A. Groover; M. Devey; T. Fiddler; J. Lee; R. Megraw; T. Mitchel-Olds; B. Sherman; S. Vujcic; C. Williams; D. Neale

1994-01-01

We report the identification of quantitative trait loci (QTL) influencing wood specific gravity (WSG) in an outbred pedigree of loblolly pine (Pinus taeda L.) . QTL mapping in an outcrossing species is complicated by the presence of multiple alleles (>2) at QTL and marker loci. Multiple alleles at QTL allow the examination of interaction among...

A high-density genetic map and growth related QTL mapping in bighead carp (Hypophthalmichthys nobilis)

PubMed Central

Fu, Beide; Liu, Haiyang; Yu, Xiaomu; Tong, Jingou

2016-01-01

Growth related traits in fish are controlled by quantitative trait loci (QTL), but no QTL for growth have been detected in bighead carp (Hypophthalmichthys nobilis) due to the lack of high-density genetic map. In this study, an ultra-high density genetic map was constructed with 3,121 SNP markers by sequencing 117 individuals in a F1 family using 2b-RAD technology. The total length of the map was 2341.27 cM, with an average marker interval of 0.75 cM. A high level of genomic synteny between our map and zebrafish was detected. Based on this genetic map, one genome-wide significant and 37 suggestive QTL for five growth-related traits were identified in 6 linkage groups (i.e. LG3, LG11, LG15, LG18, LG19, LG22). The phenotypic variance explained (PVE) by these QTL varied from 15.4% to 38.2%. Marker within the significant QTL region was surrounded by CRP1 and CRP2, which played an important role in muscle cell division. These high-density map and QTL information provided a solid base for QTL fine mapping and comparative genomics in bighead carp. PMID:27345016

Quantitative trait loci affecting lactose and total solids on chromosome 6 in Brazilian Gir dairy cattle.

PubMed

Silva, A A; Azevedo, A L S; Gasparini, K; Verneque, R S; Peixoto, M G C D; Panetto, B R; Guimarães, S E F; Machado, M A

2011-10-31

Fourteen Brazilian Gir sire families with 657 daughters were analyzed for quantitative trait loci (QTL) on chromosome 6 affecting lactose and total solids. Cows and sires were genotyped with 27 microsatellites with a mean spacing between markers of 4.9 cM. We used a 1% chromosome-wide threshold for QTL qualification. A QTL for lactose yield was found close to marker MNB66 in three families. A QTL for total solid yield was identified close to marker BMS2508 in three families. A QTL for lactose percentage, close to marker DIK1182, was identified in two families. A QTL for total solid percentage, close to marker MNB208, was identified in four families. These QTLs could be used for selection of animals in dairy production systems.

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans.

PubMed

Amin Al Olama, Ali; Dadaev, Tokhir; Hazelett, Dennis J; Li, Qiuyan; Leongamornlert, Daniel; Saunders, Edward J; Stephens, Sarah; Cieza-Borrella, Clara; Whitmore, Ian; Benlloch Garcia, Sara; Giles, Graham G; Southey, Melissa C; Fitzgerald, Liesel; Gronberg, Henrik; Wiklund, Fredrik; Aly, Markus; Henderson, Brian E; Schumacher, Fredrick; Haiman, Christopher A; Schleutker, Johanna; Wahlfors, Tiina; Tammela, Teuvo L; Nordestgaard, Børge G; Key, Tim J; Travis, Ruth C; Neal, David E; Donovan, Jenny L; Hamdy, Freddie C; Pharoah, Paul; Pashayan, Nora; Khaw, Kay-Tee; Stanford, Janet L; Thibodeau, Stephen N; Mcdonnell, Shannon K; Schaid, Daniel J; Maier, Christiane; Vogel, Walther; Luedeke, Manuel; Herkommer, Kathleen; Kibel, Adam S; Cybulski, Cezary; Wokołorczyk, Dominika; Kluzniak, Wojciech; Cannon-Albright, Lisa; Brenner, Hermann; Butterbach, Katja; Arndt, Volker; Park, Jong Y; Sellers, Thomas; Lin, Hui-Yi; Slavov, Chavdar; Kaneva, Radka; Mitev, Vanio; Batra, Jyotsna; Clements, Judith A; Spurdle, Amanda; Teixeira, Manuel R; Paulo, Paula; Maia, Sofia; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej; Govindasami, Koveela; Guy, Michelle; Lophatonanon, Artitaya; Muir, Kenneth; Viñuela, Ana; Brown, Andrew A; Freedman, Mathew; Conti, David V; Easton, Douglas; Coetzee, Gerhard A; Eeles, Rosalind A; Kote-Jarai, Zsofia

2015-10-01

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same region. © The Author 2015. Published by Oxford University Press.

Assessment of Gene-by-Sex Interaction Effect on Bone Mineral Density

PubMed Central

Liu, Ching-Ti; Estrada, Karol; Yerges-Armstrong, Laura M.; Amin, Najaf; Evangelou, Evangelos; Li, Guo; Minster, Ryan L.; Carless, Melanie A.; Kammerer, Candace M.; Oei, Ling; Zhou, Yanhua; Alonso, Nerea; Dailiana, Zoe; Eriksson, Joel; García-Giralt, Natalia; Giroux, Sylvie; Husted, Lise Bjerre; Khusainova, Rita I.; Koromila, Theodora; Kung, Annie WaiChee; Lewis, Joshua R.; Masi, Laura; Mencej-Bedrac, Simona; Nogues, Xavier; Patel, Millan S.; Prezelj, Janez; Richards, J Brent; Sham, Pak Chung; Spector, Timothy; Vandenput, Liesbeth; Xiao, Su-Mei; Zheng, Hou-Feng; Zhu, Kun; Balcells, Susana; Brandi, Maria Luisa; Frost, Morten; Goltzman, David; González-Macías, Jesús; Karlsson, Magnus; Khusnutdinova, Elza K.; Kollia, Panagoula; Langdahl, Bente Lomholt; Ljunggren, Östen; Lorentzon, Mattias; Marc, Janja; Mellström, Dan; Ohlsson, Claes; Olmos, José M.; Ralston, Stuart H.; Riancho, José A.; Rousseau, François; Urreizti, Roser; Van Hul, Wim; Zarrabeitia, María T.; Castano-Betancourt, Martha; Demissie, Serkalem; Grundberg, Elin; Herrera, Lizbeth; Kwan, Tony; Medina-Gómez, Carolina; Pastinen, Tomi; Sigurdsson, Gunnar; Thorleifsson, Gudmar; vanMeurs, Joyce B.J.; Blangero, John; Hofman, Albert; Liu, Yongmei; Mitchell, Braxton D.; O’Connell, Jeffrey R.; Oostra, Ben A.; Rotter, Jerome I; Stefansson, Kari; Streeten, Elizabeth A.; Styrkarsdottir, Unnur; Thorsteinsdottir, Unnur; Tylavsky, Frances A.; Uitterlinden, Andre; Cauley, Jane A.; Harris, Tamara B.; Ioannidis, John P.A.; Psaty, Bruce M.; Robbins, John A; Zillikens, M. Carola; vanDuijn, Cornelia M.; Prince, Richard L.; Karasik, David; Rivadeneira, Fernando; Kiel, Douglas P.; Cupples, L. Adrienne; Hsu, Yi-Hsiang

2012-01-01

Background Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome-wide, and performed eQTL analysis and bioinformatics network analysis. Methods We conducted an autosomal genome-wide meta-analysis of gene-by-sex interaction on lumbar spine (LS-) and femoral neck (FN-) BMD, in 25,353 individuals from eight cohorts. In a second stage, we followed up the 12 top SNPs (P<1×10−5) in an additional set of 24,763 individuals. Gene-by-sex interaction and sex-specific effects were examined in these 12 SNPs. Results We detected one novel genome-wide significant interaction associated with LS-BMD at the Chr3p26.1-p25.1 locus, near the GRM7 gene (male effect = 0.02 & p-value = 3.0×10−5; female effect = −0.007 & p-value=3.3×10−2) and eleven suggestive loci associated with either FN- or LS-BMD in discovery cohorts. However, there was no evidence for genome-wide significant (P<5×10−8) gene-by-sex interaction in the joint analysis of discovery and replication cohorts. Conclusion Despite the large collaborative effort, no genome-wide significant evidence for gene-by-sex interaction was found influencing BMD variation in this screen of autosomal markers. If they exist, gene-by-sex interactions for BMD probably have weak effects, accounting for less than 0.08% of the variation in these traits per implicated SNP. PMID:22692763

Fine-Mapping of the 1p11.2 Breast Cancer Susceptibility Locus

PubMed Central

Horne, Hisani N.; Chung, Charles C.; Zhang, Han; Yu, Kai; Prokunina-Olsson, Ludmila; Michailidou, Kyriaki; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Hopper, John L.; Southey, Melissa C.; Schmidt, Marjanka K.; Broeks, Annegien; Muir, Kenneth; Lophatananon, Artitaya; Fasching, Peter A.; Beckmann, Matthias W.; Fletcher, Olivia; Johnson, Nichola; Sawyer, Elinor J.; Tomlinson, Ian; Burwinkel, Barbara; Marme, Frederik; Guénel, Pascal; Truong, Thérèse; Bojesen, Stig E.; Flyger, Henrik; Benitez, Javier; González-Neira, Anna; Anton-Culver, Hoda; Neuhausen, Susan L.; Brenner, Hermann; Arndt, Volker; Meindl, Alfons; Schmutzler, Rita K.; Brauch, Hiltrud; Hamann, Ute; Nevanlinna, Heli; Khan, Sofia; Matsuo, Keitaro; Iwata, Hiroji; Dörk, Thilo; Bogdanova, Natalia V.; Lindblom, Annika; Margolin, Sara; Mannermaa, Arto; Kosma, Veli-Matti; Chenevix-Trench, Georgia; Wu, Anna H.; ven den Berg, David; Smeets, Ann; Zhao, Hui; Chang-Claude, Jenny; Rudolph, Anja; Radice, Paolo; Barile, Monica; Couch, Fergus J.; Vachon, Celine; Giles, Graham G.; Milne, Roger L.; Haiman, Christopher A.; Marchand, Loic Le; Goldberg, Mark S.; Teo, Soo H.; Taib, Nur A. M.; Kristensen, Vessela; Borresen-Dale, Anne-Lise; Zheng, Wei; Shrubsole, Martha; Winqvist, Robert; Jukkola-Vuorinen, Arja; Andrulis, Irene L.; Knight, Julia A.; Devilee, Peter; Seynaeve, Caroline; García-Closas, Montserrat; Czene, Kamila; Darabi, Hatef; Hollestelle, Antoinette; Martens, John W. M.; Li, Jingmei; Lu, Wei; Shu, Xiao-Ou; Cox, Angela; Cross, Simon S.; Blot, William; Cai, Qiuyin; Shah, Mitul; Luccarini, Craig; Baynes, Caroline; Harrington, Patricia; Kang, Daehee; Choi, Ji-Yeob; Hartman, Mikael; Chia, Kee Seng; Kabisch, Maria; Torres, Diana; Jakubowska, Anna; Lubinski, Jan; Sangrajrang, Suleeporn; Brennan, Paul; Slager, Susan; Yannoukakos, Drakoulis; Shen, Chen-Yang; Hou, Ming-Feng; Swerdlow, Anthony; Orr, Nick; Simard, Jacques; Hall, Per; Pharoah, Paul D. P.

2016-01-01

The Cancer Genetic Markers of Susceptibility genome-wide association study (GWAS) originally identified a single nucleotide polymorphism (SNP) rs11249433 at 1p11.2 associated with breast cancer risk. To fine-map this locus, we genotyped 92 SNPs in a 900kb region (120,505,799–121,481,132) flanking rs11249433 in 45,276 breast cancer cases and 48,998 controls of European, Asian and African ancestry from 50 studies in the Breast Cancer Association Consortium. Genotyping was done using iCOGS, a custom-built array. Due to the complicated nature of the region on chr1p11.2: 120,300,000–120,505,798, that lies near the centromere and contains seven duplicated genomic segments, we restricted analyses to 429 SNPs excluding the duplicated regions (42 genotyped and 387 imputed). Per-allelic associations with breast cancer risk were estimated using logistic regression models adjusting for study and ancestry-specific principal components. The strongest association observed was with the original identified index SNP rs11249433 (minor allele frequency (MAF) 0.402; per-allele odds ratio (OR) = 1.10, 95% confidence interval (CI) 1.08–1.13, P = 1.49 x 10-21). The association for rs11249433 was limited to ER-positive breast cancers (test for heterogeneity P≤8.41 x 10-5). Additional analyses by other tumor characteristics showed stronger associations with moderately/well differentiated tumors and tumors of lobular histology. Although no significant eQTL associations were observed, in silico analyses showed that rs11249433 was located in a region that is likely a weak enhancer/promoter. Fine-mapping analysis of the 1p11.2 breast cancer susceptibility locus confirms this region to be limited to risk to cancers that are ER-positive. PMID:27556229

Fine-Mapping of the 1p11.2 Breast Cancer Susceptibility Locus.

PubMed

Horne, Hisani N; Chung, Charles C; Zhang, Han; Yu, Kai; Prokunina-Olsson, Ludmila; Michailidou, Kyriaki; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; Hopper, John L; Southey, Melissa C; Schmidt, Marjanka K; Broeks, Annegien; Muir, Kenneth; Lophatananon, Artitaya; Fasching, Peter A; Beckmann, Matthias W; Fletcher, Olivia; Johnson, Nichola; Sawyer, Elinor J; Tomlinson, Ian; Burwinkel, Barbara; Marme, Frederik; Guénel, Pascal; Truong, Thérèse; Bojesen, Stig E; Flyger, Henrik; Benitez, Javier; González-Neira, Anna; Anton-Culver, Hoda; Neuhausen, Susan L; Brenner, Hermann; Arndt, Volker; Meindl, Alfons; Schmutzler, Rita K; Brauch, Hiltrud; Hamann, Ute; Nevanlinna, Heli; Khan, Sofia; Matsuo, Keitaro; Iwata, Hiroji; Dörk, Thilo; Bogdanova, Natalia V; Lindblom, Annika; Margolin, Sara; Mannermaa, Arto; Kosma, Veli-Matti; Chenevix-Trench, Georgia; Wu, Anna H; Ven den Berg, David; Smeets, Ann; Zhao, Hui; Chang-Claude, Jenny; Rudolph, Anja; Radice, Paolo; Barile, Monica; Couch, Fergus J; Vachon, Celine; Giles, Graham G; Milne, Roger L; Haiman, Christopher A; Marchand, Loic Le; Goldberg, Mark S; Teo, Soo H; Taib, Nur A M; Kristensen, Vessela; Borresen-Dale, Anne-Lise; Zheng, Wei; Shrubsole, Martha; Winqvist, Robert; Jukkola-Vuorinen, Arja; Andrulis, Irene L; Knight, Julia A; Devilee, Peter; Seynaeve, Caroline; García-Closas, Montserrat; Czene, Kamila; Darabi, Hatef; Hollestelle, Antoinette; Martens, John W M; Li, Jingmei; Lu, Wei; Shu, Xiao-Ou; Cox, Angela; Cross, Simon S; Blot, William; Cai, Qiuyin; Shah, Mitul; Luccarini, Craig; Baynes, Caroline; Harrington, Patricia; Kang, Daehee; Choi, Ji-Yeob; Hartman, Mikael; Chia, Kee Seng; Kabisch, Maria; Torres, Diana; Jakubowska, Anna; Lubinski, Jan; Sangrajrang, Suleeporn; Brennan, Paul; Slager, Susan; Yannoukakos, Drakoulis; Shen, Chen-Yang; Hou, Ming-Feng; Swerdlow, Anthony; Orr, Nick; Simard, Jacques; Hall, Per; Pharoah, Paul D P; Easton, Douglas F; Chanock, Stephen J; Dunning, Alison M; Figueroa, Jonine D

2016-01-01

The Cancer Genetic Markers of Susceptibility genome-wide association study (GWAS) originally identified a single nucleotide polymorphism (SNP) rs11249433 at 1p11.2 associated with breast cancer risk. To fine-map this locus, we genotyped 92 SNPs in a 900kb region (120,505,799-121,481,132) flanking rs11249433 in 45,276 breast cancer cases and 48,998 controls of European, Asian and African ancestry from 50 studies in the Breast Cancer Association Consortium. Genotyping was done using iCOGS, a custom-built array. Due to the complicated nature of the region on chr1p11.2: 120,300,000-120,505,798, that lies near the centromere and contains seven duplicated genomic segments, we restricted analyses to 429 SNPs excluding the duplicated regions (42 genotyped and 387 imputed). Per-allelic associations with breast cancer risk were estimated using logistic regression models adjusting for study and ancestry-specific principal components. The strongest association observed was with the original identified index SNP rs11249433 (minor allele frequency (MAF) 0.402; per-allele odds ratio (OR) = 1.10, 95% confidence interval (CI) 1.08-1.13, P = 1.49 x 10-21). The association for rs11249433 was limited to ER-positive breast cancers (test for heterogeneity P≤8.41 x 10-5). Additional analyses by other tumor characteristics showed stronger associations with moderately/well differentiated tumors and tumors of lobular histology. Although no significant eQTL associations were observed, in silico analyses showed that rs11249433 was located in a region that is likely a weak enhancer/promoter. Fine-mapping analysis of the 1p11.2 breast cancer susceptibility locus confirms this region to be limited to risk to cancers that are ER-positive.

Fine mapping and candidate gene analysis of qFL-chr1, a fiber length QTL in cotton.

PubMed

Xu, Peng; Gao, Jin; Cao, Zhibin; Chee, Peng W; Guo, Qi; Xu, Zhenzhen; Paterson, Andrew H; Zhang, Xianggui; Shen, Xinlian

2017-06-01

A fiber length QTL, qFL-chr1, was fine mapped to a 0.9 cM interval of cotton chromosome 1. Two positional candidate genes showed positive correlation between gene expression level and fiber length. Prior analysis of a backcross-self mapping population derived from a cross between Gossypium hirsutum L. and G. barbadense L. revealed a QTL on chromosome 1 associated with increased fiber length (qFL-chr1), which was confirmed in three independent populations of near-isogenic introgression lines (NIILs). Here, a single NIIL, R01-40-08, was used to develop a large population segregating for the target region. Twenty-two PCR-based polymorphic markers used to genotype 1672 BC 4 F 2 plants identified 432 recombinants containing breakpoints in the target region. Substitution mapping using 141 informative recombinants narrowed the position of qFL-chr1 to a 1.0-cM interval between SSR markers MUSS084 and CIR018. To exclude possible effects of non-target introgressions on fiber length, different heterozygous BC 4 F 3 plants introgressed between SSR markers NAU3384 and CGR5144 were selected to develop sub-NILs. The qFL-chr1 was further mapped at 0.9-cM interval between MUSS422 and CIR018 by comparisons of sub-NIL phenotype, and increased fiber length by ~1 mm. The 2.38-Mb region between MUSS422 and CIR018 in G. barbadense contained 19 annotated genes. Expression levels of two of these genes, GOBAR07705 (encoding 1-aminocyclopropane-1-carboxylate synthase) and GOBAR25992 (encoding amino acid permease), were positively correlated with fiber length in a small F 2 population, supporting these genes as candidates for qFL-chr1.

Genetic Mapping in Mice Reveals the Involvement of Pcdh9 in Long-Term Social and Object Recognition and Sensorimotor Development.

PubMed

Bruining, Hilgo; Matsui, Asuka; Oguro-Ando, Asami; Kahn, René S; Van't Spijker, Heleen M; Akkermans, Guus; Stiedl, Oliver; van Engeland, Herman; Koopmans, Bastijn; van Lith, Hein A; Oppelaar, Hugo; Tieland, Liselotte; Nonkes, Lourens J; Yagi, Takeshi; Kaneko, Ryosuke; Burbach, J Peter H; Yamamoto, Nobuhiko; Kas, Martien J

2015-10-01

Quantitative genetic analysis of basic mouse behaviors is a powerful tool to identify novel genetic phenotypes contributing to neurobehavioral disorders. Here, we analyzed genetic contributions to single-trial, long-term social and nonsocial recognition and subsequently studied the functional impact of an identified candidate gene on behavioral development. Genetic mapping of single-trial social recognition was performed in chromosome substitution strains, a sophisticated tool for detecting quantitative trait loci (QTL) of complex traits. Follow-up occurred by generating and testing knockout (KO) mice of a selected QTL candidate gene. Functional characterization of these mice was performed through behavioral and neurological assessments across developmental stages and analyses of gene expression and brain morphology. Chromosome substitution strain 14 mapping studies revealed an overlapping QTL related to long-term social and object recognition harboring Pcdh9, a cell-adhesion gene previously associated with autism spectrum disorder. Specific long-term social and object recognition deficits were confirmed in homozygous (KO) Pcdh9-deficient mice, while heterozygous mice only showed long-term social recognition impairment. The recognition deficits in KO mice were not associated with alterations in perception, multi-trial discrimination learning, sociability, behavioral flexibility, or fear memory. Rather, KO mice showed additional impairments in sensorimotor development reflected by early touch-evoked biting, rotarod performance, and sensory gating deficits. This profile emerged with structural changes in deep layers of sensory cortices, where Pcdh9 is selectively expressed. This behavior-to-gene study implicates Pcdh9 in cognitive functions required for long-term social and nonsocial recognition. This role is supported by the involvement of Pcdh9 in sensory cortex development and sensorimotor phenotypes. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.