Comprehensive Identification Of Specific Genes Controlling Complex Traits Through A Genome-Wide Screen for Cis-Acting Regulatory Elements - An Example Using Marek's Disease

USDA-ARS?s Scientific Manuscript database

The comprehensive identification of genes underlying phenotypic variation of complex traits remains a major challenge. Most genome-wide screens lack sufficient resolving power as they typically depend on linkage. An alternate method is to screen for allele-specific expression (ASE), a simple yet pow...

Good genes, complementary genes and human mate preferences.

PubMed

Roberts, S Craig; Little, Anthony C

2008-03-01

The past decade has witnessed a rapidly growing interest in the biological basis of human mate choice. Here we review recent studies that demonstrate preferences for traits which might reveal genetic quality to prospective mates, with potential but still largely unknown influence on offspring fitness. These include studies assessing visual, olfactory and auditory preferences for potential good-gene indicator traits, such as dominance or bilateral symmetry. Individual differences in these robust preferences mainly arise through within and between individual variation in condition and reproductive status. Another set of studies have revealed preferences for traits indicating complementary genes, focussing on discrimination of dissimilarity at genes in the major histocompatibility complex (MHC). As in animal studies, we are only just beginning to understand how preferences for specific traits vary and inter-relate, how consideration of good and compatible genes can lead to substantial variability in individual mate choice decisions and how preferences expressed in one sensory modality may reflect those in another. Humans may be an ideal model species in which to explore these interesting complexities.

Good genes, complementary genes and human mate preferences.

PubMed

Roberts, S Craig; Little, Anthony C

2008-09-01

The past decade has witnessed a rapidly growing interest in the biological basis of human mate choice. Here we review recent studies that demonstrate preferences for traits which might reveal genetic quality to prospective mates, with potential but still largely unknown influence on offspring fitness. These include studies assessing visual, olfactory and auditory preferences for potential good-gene indicator traits, such as dominance or bilateral symmetry. Individual differences in these robust preferences mainly arise through within and between individual variation in condition and reproductive status. Another set of studies have revealed preferences for traits indicating complementary genes, focussing on discrimination of dissimilarity at genes in the major histocompatibility complex (MHC). As in animal studies, we are only just beginning to understand how preferences for specific traits vary and inter-relate, how consideration of good and compatible genes can lead to substantial variability in individual mate choice decisions and how preferences expressed in one sensory modality may reflect those in another. Humans may be an ideal model species in which to explore these interesting complexities.

Genetic and Genomic Analysis of a Fat Mass Trait with Complex Inheritance Reveals Marked Sex Specificity

PubMed Central

Wang, Hui; Drake, Thomas A; Lusis, Aldons J

2006-01-01

The integration of expression profiling with linkage analysis has increasingly been used to identify genes underlying complex phenotypes. The effects of gender on the regulation of many physiological traits are well documented; however, “genetical genomic” analyses have not yet addressed the degree to which their conclusions are affected by sex. We constructed and densely genotyped a large F2 intercross derived from the inbred mouse strains C57BL/6J and C3H/HeJ on an apolipoprotein E null (ApoE−/−) background. This BXH.ApoE−/− population recapitulates several “metabolic syndrome” phenotypes. The cross consists of 334 animals of both sexes, allowing us to specifically test for the dependence of linkage on sex. We detected several thousand liver gene expression quantitative trait loci, a significant proportion of which are sex-biased. We used these analyses to dissect the genetics of gonadal fat mass, a complex trait with sex-specific regulation. We present evidence for a remarkably high degree of sex-dependence on both the cis and trans regulation of gene expression. We demonstrate how these analyses can be applied to the study of the genetics underlying gonadal fat mass, a complex trait showing significantly female-biased heritability. These data have implications on the potential effects of sex on the genetic regulation of other complex traits. PMID:16462940

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.

Network-based Analysis of Genome Wide Association Data Provides Novel Candidate Genes for Lipid and Lipoprotein Traits*

PubMed Central

Sharma, Amitabh; Gulbahce, Natali; Pevzner, Samuel J.; Menche, Jörg; Ladenvall, Claes; Folkersen, Lasse; Eriksson, Per; Orho-Melander, Marju; Barabási, Albert-László

2013-01-01

Genome wide association studies (GWAS) identify susceptibility loci for complex traits, but do not identify particular genes of interest. Integration of functional and network information may help in overcoming this limitation and identifying new susceptibility loci. Using GWAS and comorbidity data, we present a network-based approach to predict candidate genes for lipid and lipoprotein traits. We apply a prediction pipeline incorporating interactome, co-expression, and comorbidity data to Global Lipids Genetics Consortium (GLGC) GWAS for four traits of interest, identifying phenotypically coherent modules. These modules provide insights regarding gene involvement in complex phenotypes with multiple susceptibility alleles and low effect sizes. To experimentally test our predictions, we selected four candidate genes and genotyped representative SNPs in the Malmö Diet and Cancer Cardiovascular Cohort. We found significant associations with LDL-C and total-cholesterol levels for a synonymous SNP (rs234706) in the cystathionine beta-synthase (CBS) gene (p = 1 × 10−5 and adjusted-p = 0.013, respectively). Further, liver samples taken from 206 patients revealed that patients with the minor allele of rs234706 had significant dysregulation of CBS (p = 0.04). Despite the known biological role of CBS in lipid metabolism, SNPs within the locus have not yet been identified in GWAS of lipoprotein traits. Thus, the GWAS-based Comorbidity Module (GCM) approach identifies candidate genes missed by GWAS studies, serving as a broadly applicable tool for the investigation of other complex disease phenotypes. PMID:23882023

Four Linked Genes Participate in Controlling Sporulation Efficiency in Budding Yeast

PubMed Central

Ben-Ari, Giora; Zenvirth, Drora; Sherman, Amir; David, Lior; Klutstein, Michael; Lavi, Uri; Hillel, Jossi; Simchen, Giora

2006-01-01

Quantitative traits are conditioned by several genetic determinants. Since such genes influence many important complex traits in various organisms, the identification of quantitative trait loci (QTLs) is of major interest, but still encounters serious difficulties. We detected four linked genes within one QTL, which participate in controlling sporulation efficiency in Saccharomyces cerevisiae. Following the identification of single nucleotide polymorphisms by comparing the sequences of 145 genes between the parental strains SK1 and S288c, we analyzed the segregating progeny of the cross between them. Through reciprocal hemizygosity analysis, four genes, RAS2, PMS1, SWS2, and FKH2, located in a region of 60 kilobases on Chromosome 14, were found to be associated with sporulation efficiency. Three of the four “high” sporulation alleles are derived from the “low” sporulating strain. Two of these sporulation-related genes were verified through allele replacements. For RAS2, the causative variation was suggested to be a single nucleotide difference in the upstream region of the gene. This quantitative trait nucleotide accounts for sporulation variability among a set of ten closely related winery yeast strains. Our results provide a detailed view of genetic complexity in one “QTL region” that controls a quantitative trait and reports a single nucleotide polymorphism-trait association in wild strains. Moreover, these findings have implications on QTL identification in higher eukaryotes. PMID:17112318

A computational interactome for prioritizing genes associated with complex agronomic traits in rice (Oryza sativa).

PubMed

Liu, Shiwei; Liu, Yihui; Zhao, Jiawei; Cai, Shitao; Qian, Hongmei; Zuo, Kaijing; Zhao, Lingxia; Zhang, Lida

2017-04-01

Rice (Oryza sativa) is one of the most important staple foods for more than half of the global population. Many rice traits are quantitative, complex and controlled by multiple interacting genes. Thus, a full understanding of genetic relationships will be critical to systematically identify genes controlling agronomic traits. We developed a genome-wide rice protein-protein interaction network (RicePPINet, http://netbio.sjtu.edu.cn/riceppinet) using machine learning with structural relationship and functional information. RicePPINet contained 708 819 predicted interactions for 16 895 non-transposable element related proteins. The power of the network for discovering novel protein interactions was demonstrated through comparison with other publicly available protein-protein interaction (PPI) prediction methods, and by experimentally determined PPI data sets. Furthermore, global analysis of domain-mediated interactions revealed RicePPINet accurately reflects PPIs at the domain level. Our studies showed the efficiency of the RicePPINet-based method in prioritizing candidate genes involved in complex agronomic traits, such as disease resistance and drought tolerance, was approximately 2-11 times better than random prediction. RicePPINet provides an expanded landscape of computational interactome for the genetic dissection of agronomically important traits in rice. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Dissection of complicate genetic architecture and breeding perspective of cottonseed traits by genome-wide association study.

PubMed

Du, Xiongming; Liu, Shouye; Sun, Junling; Zhang, Gengyun; Jia, Yinhua; Pan, Zhaoe; Xiang, Haitao; He, Shoupu; Xia, Qiuju; Xiao, Songhua; Shi, Weijun; Quan, Zhiwu; Liu, Jianguang; Ma, Jun; Pang, Baoyin; Wang, Liru; Sun, Gaofei; Gong, Wenfang; Jenkins, Johnie N; Lou, Xiangyang; Zhu, Jun; Xu, Haiming

2018-06-13

Cottonseed is one of the most important raw materials for plant protein, oil and alternative biofuel for diesel engines. Understanding the complex genetic basis of cottonseed traits is requisite for achieving efficient genetic improvement of the traits. However, it is not yet clear about their genetic architecture in genomic level. GWAS has been an effective way to explore genetic basis of quantitative traits in human and many crops. This study aims to dissect genetic mechanism seven cottonseed traits by a GWAS for genetic improvement. A genome-wide association study (GWAS) based on a full gene model with gene effects as fixed and gene-environment interaction as random, was conducted for protein, oil and 5 fatty acids using 316 accessions and ~ 390 K SNPs. Totally, 124 significant quantitative trait SNPs (QTSs), consisting of 16, 21, 87 for protein, oil and fatty acids (palmitic, linoleic, oleic, myristic, stearic), respectively, were identified and the broad-sense heritability was estimated from 71.62 to 93.43%; no QTS-environment interaction was detected for the protein, the palmitic and the oleic contents; the protein content was predominantly controlled by epistatic effects accounting for 65.18% of the total variation, but the oil content and the fatty acids except the palmitic were mainly determined by gene main effects and no epistasis was detected for the myristic and the stearic. Prediction of superior pure line and hybrid revealed the potential of the QTSs in the improvement of cottonseed traits, and the hybrid could achieve higher or lower genetic values compared with pure lines. This study revealed complex genetic architecture of seven cottonseed traits at whole genome-wide by mixed linear model approach; the identified genetic variants and estimated genetic component effects of gene, gene-gene and gene-environment interaction provide cotton geneticist or breeders new knowledge on the genetic mechanism of the traits and the potential molecular breeding design strategy.

Intelligence: shared genetic basis between Mendelian disorders and a polygenic trait.

PubMed

Franić, Sanja; Groen-Blokhuis, Maria M; Dolan, Conor V; Kattenberg, Mathijs V; Pool, René; Xiao, Xiangjun; Scheet, Paul A; Ehli, Erik A; Davies, Gareth E; van der Sluis, Sophie; Abdellaoui, Abdel; Hansell, Narelle K; Martin, Nicholas G; Hudziak, James J; van Beijsterveldt, Catherina E M; Swagerman, Suzanne C; Hulshoff Pol, Hilleke E; de Geus, Eco J C; Bartels, Meike; Ropers, H Hilger; Hottenga, Jouke-Jan; Boomsma, Dorret I

2015-10-01

Multiple inquiries into the genetic etiology of human traits indicated an overlap between genes underlying monogenic disorders (eg, skeletal growth defects) and those affecting continuous variability of related quantitative traits (eg, height). Extending the idea of a shared genetic basis between a Mendelian disorder and a classic polygenic trait, we performed an association study to examine the effect of 43 genes implicated in autosomal recessive cognitive disorders on intelligence in an unselected Dutch population (N=1316). Using both single-nucleotide polymorphism (SNP)- and gene-based association testing, we detected an association between intelligence and the genes of interest, with genes ELP2, TMEM135, PRMT10, and RGS7 showing the strongest associations. This is a demonstration of the relevance of genes implicated in monogenic disorders of intelligence to normal-range intelligence, and a corroboration of the utility of employing knowledge on monogenic disorders in identifying the genetic variability underlying complex traits.

A powerful approach reveals numerous expression quantitative trait haplotypes in multiple tissues.

PubMed

Ying, Dingge; Li, Mulin Jun; Sham, Pak Chung; Li, Miaoxin

2018-04-26

Recently many studies showed single nucleotide polymorphisms (SNPs) affect gene expression and contribute to development of complex traits/diseases in a tissue context-dependent manner. However, little is known about haplotype's influence on gene expression and complex traits, which reflects the interaction effect between SNPs. In the present study, we firstly proposed a regulatory region guided eQTL haplotype association analysis approach, and then systematically investigate the expression quantitative trait loci (eQTL) haplotypes in 20 different tissues by the approach. The approach has a powerful design of reducing computational burden by the utilization of regulatory predictions for candidate SNP selection and multiple testing corrections on non-independent haplotypes. The application results in multiple tissues showed that haplotype-based eQTLs not only increased the number of eQTL genes in a tissue specific manner, but were also enriched in loci that associated with complex traits in a tissue-matched manner. In addition, we found that tag SNPs of eQTL haplotypes from whole blood were selectively enriched in certain combination of regulatory elements (e.g. promoters and enhancers) according to predicted chromatin states. In summary, this eQTL haplotype detection approach, together with the application results, shed insights into synergistic effect of sequence variants on gene expression and their susceptibility to complex diseases. The executable application "eHaplo" is implemented in Java and is publicly available at http://grass.cgs.hku.hk/limx/ehaplo/. jonsonfox@gmail.com, limiaoxin@mail.sysu.edu.cn. Supplementary data are available at Bioinformatics online.

Genetic Complexity and Quantitative Trait Loci Mapping of Yeast Morphological Traits

PubMed Central

Nogami, Satoru; Ohya, Yoshikazu; Yvert, Gaël

2007-01-01

Functional genomics relies on two essential parameters: the sensitivity of phenotypic measures and the power to detect genomic perturbations that cause phenotypic variations. In model organisms, two types of perturbations are widely used. Artificial mutations can be introduced in virtually any gene and allow the systematic analysis of gene function via mutants fitness. Alternatively, natural genetic variations can be associated to particular phenotypes via genetic mapping. However, the access to genome manipulation and breeding provided by model organisms is sometimes counterbalanced by phenotyping limitations. Here we investigated the natural genetic diversity of Saccharomyces cerevisiae cellular morphology using a very sensitive high-throughput imaging platform. We quantified 501 morphological parameters in over 50,000 yeast cells from a cross between two wild-type divergent backgrounds. Extensive morphological differences were found between these backgrounds. The genetic architecture of the traits was complex, with evidence of both epistasis and transgressive segregation. We mapped quantitative trait loci (QTL) for 67 traits and discovered 364 correlations between traits segregation and inheritance of gene expression levels. We validated one QTL by the replacement of a single base in the genome. This study illustrates the natural diversity and complexity of cellular traits among natural yeast strains and provides an ideal framework for a genetical genomics dissection of multiple traits. Our results did not overlap with results previously obtained from systematic deletion strains, showing that both approaches are necessary for the functional exploration of genomes. PMID:17319748

ATHENA: A knowledge-based hybrid backpropagation-grammatical evolution neural network algorithm for discovering epistasis among quantitative trait Loci

PubMed Central

2010-01-01

Background Growing interest and burgeoning technology for discovering genetic mechanisms that influence disease processes have ushered in a flood of genetic association studies over the last decade, yet little heritability in highly studied complex traits has been explained by genetic variation. Non-additive gene-gene interactions, which are not often explored, are thought to be one source of this "missing" heritability. Methods Stochastic methods employing evolutionary algorithms have demonstrated promise in being able to detect and model gene-gene and gene-environment interactions that influence human traits. Here we demonstrate modifications to a neural network algorithm in ATHENA (the Analysis Tool for Heritable and Environmental Network Associations) resulting in clear performance improvements for discovering gene-gene interactions that influence human traits. We employed an alternative tree-based crossover, backpropagation for locally fitting neural network weights, and incorporation of domain knowledge obtainable from publicly accessible biological databases for initializing the search for gene-gene interactions. We tested these modifications in silico using simulated datasets. Results We show that the alternative tree-based crossover modification resulted in a modest increase in the sensitivity of the ATHENA algorithm for discovering gene-gene interactions. The performance increase was highly statistically significant when backpropagation was used to locally fit NN weights. We also demonstrate that using domain knowledge to initialize the search for gene-gene interactions results in a large performance increase, especially when the search space is larger than the search coverage. Conclusions We show that a hybrid optimization procedure, alternative crossover strategies, and incorporation of domain knowledge from publicly available biological databases can result in marked increases in sensitivity and performance of the ATHENA algorithm for detecting and modelling gene-gene interactions that influence a complex human trait. PMID:20875103

Deciphering the Interdependence between Ecological and Evolutionary Networks.

PubMed

Melián, Carlos J; Matthews, Blake; de Andreazzi, Cecilia S; Rodríguez, Jorge P; Harmon, Luke J; Fortuna, Miguel A

2018-05-24

Biological systems consist of elements that interact within and across hierarchical levels. For example, interactions among genes determine traits of individuals, competitive and cooperative interactions among individuals influence population dynamics, and interactions among species affect the dynamics of communities and ecosystem processes. Such systems can be represented as hierarchical networks, but can have complex dynamics when interdependencies among levels of the hierarchy occur. We propose integrating ecological and evolutionary processes in hierarchical networks to explore interdependencies in biological systems. We connect gene networks underlying predator-prey trait distributions to food webs. Our approach addresses longstanding questions about how complex traits and intraspecific trait variation affect the interdependencies among biological levels and the stability of meta-ecosystems. Copyright © 2018 Elsevier Ltd. All rights reserved.

Advances in cereal genomics and applications in crop breeding.

PubMed

Varshney, Rajeev K; Hoisington, David A; Tyagi, Akhilesh K

2006-11-01

Recent advances in cereal genomics have made it possible to analyse the architecture of cereal genomes and their expressed components, leading to an increase in our knowledge of the genes that are linked to key agronomically important traits. These studies have used molecular genetic mapping of quantitative trait loci (QTL) of several complex traits that are important in breeding. The identification and molecular cloning of genes underlying QTLs offers the possibility to examine the naturally occurring allelic variation for respective complex traits. Novel alleles, identified by functional genomics or haplotype analysis, can enrich the genetic basis of cultivated crops to improve productivity. Advances made in cereal genomics research in recent years thus offer the opportunities to enhance the prediction of phenotypes from genotypes for cereal breeding.

Tilting at Quixotic Trait Loci (QTL): An Evolutionary Perspective on Genetic Causation

PubMed Central

Weiss, Kenneth M.

2008-01-01

Recent years have seen great advances in generating and analyzing data to identify the genetic architecture of biological traits. Human disease has understandably received intense research focus, and the genes responsible for most Mendelian diseases have successfully been identified. However, the same advances have shown a consistent if less satisfying pattern, in which complex traits are affected by variation in large numbers of genes, most of which have individually minor or statistically elusive effects, leaving the bulk of genetic etiology unaccounted for. This pattern applies to diverse and unrelated traits, not just disease, in basically all species, and is consistent with evolutionary expectations, raising challenging questions about the best way to approach and understand biological complexity. PMID:18711218

Studying Gene and Gene-Environment Effects of Uncommon and Common Variants on Continuous Traits: A Marker-Set Approach Using Gene-Trait Similarity Regression

PubMed Central

Tzeng, Jung-Ying; Zhang, Daowen; Pongpanich, Monnat; Smith, Chris; McCarthy, Mark I.; Sale, Michèle M.; Worrall, Bradford B.; Hsu, Fang-Chi; Thomas, Duncan C.; Sullivan, Patrick F.

2011-01-01

Genomic association analyses of complex traits demand statistical tools that are capable of detecting small effects of common and rare variants and modeling complex interaction effects and yet are computationally feasible. In this work, we introduce a similarity-based regression method for assessing the main genetic and interaction effects of a group of markers on quantitative traits. The method uses genetic similarity to aggregate information from multiple polymorphic sites and integrates adaptive weights that depend on allele frequencies to accomodate common and uncommon variants. Collapsing information at the similarity level instead of the genotype level avoids canceling signals that have the opposite etiological effects and is applicable to any class of genetic variants without the need for dichotomizing the allele types. To assess gene-trait associations, we regress trait similarities for pairs of unrelated individuals on their genetic similarities and assess association by using a score test whose limiting distribution is derived in this work. The proposed regression framework allows for covariates, has the capacity to model both main and interaction effects, can be applied to a mixture of different polymorphism types, and is computationally efficient. These features make it an ideal tool for evaluating associations between phenotype and marker sets defined by linkage disequilibrium (LD) blocks, genes, or pathways in whole-genome analysis. PMID:21835306

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.

Use of biological priors enhances understanding of genetic architecture and genomic prediction of complex traits within and between dairy cattle breeds.

PubMed

Fang, Lingzhao; Sahana, Goutam; Ma, Peipei; Su, Guosheng; Yu, Ying; Zhang, Shengli; Lund, Mogens Sandø; Sørensen, Peter

2017-08-10

A better understanding of the genetic architecture underlying complex traits (e.g., the distribution of causal variants and their effects) may aid in the genomic prediction. Here, we hypothesized that the genomic variants of complex traits might be enriched in a subset of genomic regions defined by genes grouped on the basis of "Gene Ontology" (GO), and that incorporating this independent biological information into genomic prediction models might improve their predictive ability. Four complex traits (i.e., milk, fat and protein yields, and mastitis) together with imputed sequence variants in Holstein (HOL) and Jersey (JER) cattle were analysed. We first carried out a post-GWAS analysis in a HOL training population to assess the degree of enrichment of the association signals in the gene regions defined by each GO term. We then extended the genomic best linear unbiased prediction model (GBLUP) to a genomic feature BLUP (GFBLUP) model, including an additional genomic effect quantifying the joint effect of a group of variants located in a genomic feature. The GBLUP model using a single random effect assumes that all genomic variants contribute to the genomic relationship equally, whereas GFBLUP attributes different weights to the individual genomic relationships in the prediction equation based on the estimated genomic parameters. Our results demonstrate that the immune-relevant GO terms were more associated with mastitis than milk production, and several biologically meaningful GO terms improved the prediction accuracy with GFBLUP for the four traits, as compared with GBLUP. The improvement of the genomic prediction between breeds (the average increase across the four traits was 0.161) was more apparent than that it was within the HOL (the average increase across the four traits was 0.020). Our genomic feature modelling approaches provide a framework to simultaneously explore the genetic architecture and genomic prediction of complex traits by taking advantage of independent biological knowledge.

Assessment of Tools for Marker-Assisted Selection in a Marine Commercial Species: Significant Association between MSTN-1 Gene Polymorphism and Growth Traits

PubMed Central

Sánchez-Ramos, Irma; Cross, Ismael; Mácha, Jaroslav; Martínez-Rodríguez, Gonzalo; Krylov, Vladimir; Rebordinos, Laureana

2012-01-01

Growth is a priority trait from the point of view of genetic improvement. Molecular markers linked to quantitative trait loci (QTL) have been regarded as useful for marker-assisted selection in complex traits as growth. Polymorphisms have been studied in five candidate genes influencing growth in gilthead seabream (Sparus aurata): the growth hormone (GH), insulin-like growth factor-1 (IGF-1), myostatin (MSTN-1), prolactin (PRL), and somatolactin (SL) genes. Specimens evaluated were from a commercial broodstock comprising 131 breeders (from which 36 males and 44 females contributed to the progeny). In all samples eleven gene fragments, covering more than 13,000 bp, generated by PCR-RFLP, were analyzed; tests were made for significant associations between these markers and growth traits. ANOVA results showed a significant association between MSTN-1 gene polymorphism and growth traits. Pairwise tests revealed several RFLPs in the MSTN-1 gene with significant heterogeneity of genotypes among size groups. PRL and MSTN-1 genes presented linkage disequilibrium. The MSTN-1 gene was mapped in the centromeric region of a medium-size acrocentric chromosome pair. PMID:22666112

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

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.

Predictable transcriptome evolution in the convergent and complex bioluminescent organs of squid

PubMed Central

Pankey, M. Sabrina; Minin, Vladimir N.; Imholte, Greg C.; Suchard, Marc A.; Oakley, Todd H.

2014-01-01

Despite contingency in life’s history, the similarity of evolutionarily convergent traits may represent predictable solutions to common conditions. However, the extent to which overall gene expression levels (transcriptomes) underlying convergent traits are themselves convergent remains largely unexplored. Here, we show strong statistical support for convergent evolutionary origins and massively parallel evolution of the entire transcriptomes in symbiotic bioluminescent organs (bacterial photophores) from two divergent squid species. The gene expression similarities are so strong that regression models of one species’ photophore can predict organ identity of a distantly related photophore from gene expression levels alone. Our results point to widespread parallel changes in gene expression evolution associated with convergent origins of complex organs. Therefore, predictable solutions may drive not only the evolution of novel, complex organs but also the evolution of overall gene expression levels that underlie them. PMID:25336755

Lessons learned from the dog genome.

PubMed

Wayne, Robert K; Ostrander, Elaine A

2007-11-01

Extensive genetic resources and a high-quality genome sequence position the dog as an important model species for understanding genome evolution, population genetics and genes underlying complex phenotypic traits. Newly developed genomic resources have expanded our understanding of canine evolutionary history and dog origins. Domestication involved genetic contributions from multiple populations of gray wolves probably through backcrossing. More recently, the advent of controlled breeding practices has segregated genetic variability into distinct dog breeds that possess specific phenotypic traits. Consequently, genome-wide association and selective sweep scans now allow the discovery of genes underlying breed-specific characteristics. The dog is finally emerging as a novel resource for studying the genetic basis of complex traits, including behavior.

Multiple OPR genes influence personality traits in substance dependent and healthy subjects in two American populations

PubMed Central

Luo, Xingguang; Zuo, Lingjun; Kranzler, Henry; Zhang, Huiping; Wang, Shuang; Gelernter, Joel

2011-01-01

Background Personality traits are among the most complex quantitative traits. Certain personality traits are associated with substance dependence (SD); genetic factors may influence both. Associations between opioid receptor (OPR) genes and SD have been reported. This study investigated the relationship between OPR genes and personality traits in a case-control sample. Methods We assessed dimensions of the five-factor model of personality in 556 subjects: 250 with SD [181 European-Americans (EAs) and 69 African-Americans (AAs)] and 306 healthy subjects (266 EAs and 40 AAs). We genotyped 20 OPRM1 markers, 8 OPRD1 markers, and 7 OPRK1 markers, and 38 unlinked ancestry-informative markers in these subjects. The relationships between OPR genes and personality traits were examined using MANCOVA, controlling for gene-gene interaction effects and potential confounders. Associations were decomposed by Roy-Bargmann Stepdown ANCOVA. Results Personality traits were associated as main or interaction effects with the haplotypes, diplotypes, alleles and genotypes at the three OPR genes (0.002

Incorporating gene-environment interaction in testing for association with rare genetic variants.

PubMed

Chen, Han; Meigs, James B; Dupuis, Josée

2014-01-01

The incorporation of gene-environment interactions could improve the ability to detect genetic associations with complex traits. For common genetic variants, single-marker interaction tests and joint tests of genetic main effects and gene-environment interaction have been well-established and used to identify novel association loci for complex diseases and continuous traits. For rare genetic variants, however, single-marker tests are severely underpowered due to the low minor allele frequency, and only a few gene-environment interaction tests have been developed. We aimed at developing powerful and computationally efficient tests for gene-environment interaction with rare variants. In this paper, we propose interaction and joint tests for testing gene-environment interaction of rare genetic variants. Our approach is a generalization of existing gene-environment interaction tests for multiple genetic variants under certain conditions. We show in our simulation studies that our interaction and joint tests have correct type I errors, and that the joint test is a powerful approach for testing genetic association, allowing for gene-environment interaction. We also illustrate our approach in a real data example from the Framingham Heart Study. Our approach can be applied to both binary and continuous traits, it is powerful and computationally efficient.

Identifying gene networks underlying the neurobiology of ethanol and alcoholism.

PubMed

Wolen, Aaron R; Miles, Michael F

2012-01-01

For complex disorders such as alcoholism, identifying the genes linked to these diseases and their specific roles is difficult. Traditional genetic approaches, such as genetic association studies (including genome-wide association studies) and analyses of quantitative trait loci (QTLs) in both humans and laboratory animals already have helped identify some candidate genes. However, because of technical obstacles, such as the small impact of any individual gene, these approaches only have limited effectiveness in identifying specific genes that contribute to complex diseases. The emerging field of systems biology, which allows for analyses of entire gene networks, may help researchers better elucidate the genetic basis of alcoholism, both in humans and in animal models. Such networks can be identified using approaches such as high-throughput molecular profiling (e.g., through microarray-based gene expression analyses) or strategies referred to as genetical genomics, such as the mapping of expression QTLs (eQTLs). Characterization of gene networks can shed light on the biological pathways underlying complex traits and provide the functional context for identifying those genes that contribute to disease development.

Integrated genomics and molecular breeding approaches for dissecting the complex quantitative traits in crop plants.

PubMed

Kujur, Alice; Saxena, Maneesha S; Bajaj, Deepak; Laxmi; Parida, Swarup K

2013-12-01

The enormous population growth, climate change and global warming are now considered major threats to agriculture and world's food security. To improve the productivity and sustainability of agriculture, the development of highyielding and durable abiotic and biotic stress-tolerant cultivars and/climate resilient crops is essential. Henceforth, understanding the molecular mechanism and dissection of complex quantitative yield and stress tolerance traits is the prime objective in current agricultural biotechnology research. In recent years, tremendous progress has been made in plant genomics and molecular breeding research pertaining to conventional and next-generation whole genome, transcriptome and epigenome sequencing efforts, generation of huge genomic, transcriptomic and epigenomic resources and development of modern genomics-assisted breeding approaches in diverse crop genotypes with contrasting yield and abiotic stress tolerance traits. Unfortunately, the detailed molecular mechanism and gene regulatory networks controlling such complex quantitative traits is not yet well understood in crop plants. Therefore, we propose an integrated strategies involving available enormous and diverse traditional and modern -omics (structural, functional, comparative and epigenomics) approaches/resources and genomics-assisted breeding methods which agricultural biotechnologist can adopt/utilize to dissect and decode the molecular and gene regulatory networks involved in the complex quantitative yield and stress tolerance traits in crop plants. This would provide clues and much needed inputs for rapid selection of novel functionally relevant molecular tags regulating such complex traits to expedite traditional and modern marker-assisted genetic enhancement studies in target crop species for developing high-yielding stress-tolerant varieties.

Improving breeding efficiency in potato using molecular and quantitative genetics.

PubMed

Slater, Anthony T; Cogan, Noel O I; Hayes, Benjamin J; Schultz, Lee; Dale, M Finlay B; Bryan, Glenn J; Forster, John W

2014-11-01

Potatoes are highly heterozygous and the conventional breeding of superior germplasm is challenging, but use of a combination of MAS and EBVs can accelerate genetic gain. Cultivated potatoes are highly heterozygous due to their outbreeding nature, and suffer acute inbreeding depression. Modern potato cultivars also exhibit tetrasomic inheritance. Due to this genetic heterogeneity, the large number of target traits and the specific requirements of commercial cultivars, potato breeding is challenging. A conventional breeding strategy applies phenotypic recurrent selection over a number of generations, a process which can take over 10 years. Recently, major advances in genetics and molecular biology have provided breeders with molecular tools to accelerate gains for some traits. Marker-assisted selection (MAS) can be effectively used for the identification of major genes and quantitative trait loci that exhibit large effects. There are also a number of complex traits of interest, such as yield, that are influenced by a large number of genes of individual small effect where MAS will be difficult to deploy. Progeny testing and the use of pedigree in the analysis can provide effective identification of the superior genetic factors that underpin these complex traits. Recently, it has been shown that estimated breeding values (EBVs) can be developed for complex potato traits. Using a combination of MAS and EBVs for simple and complex traits can lead to a significant reduction in the length of the breeding cycle for the identification of superior germplasm.

Genome-wide association analysis of seedling root development in maize (Zea mays L.).

PubMed

Pace, Jordon; Gardner, Candice; Romay, Cinta; Ganapathysubramanian, Baskar; Lübberstedt, Thomas

2015-02-05

Plants rely on the root system for anchorage to the ground and the acquisition and absorption of nutrients critical to sustaining productivity. A genome wide association analysis enables one to analyze allelic diversity of complex traits and identify superior alleles. 384 inbred lines from the Ames panel were genotyped with 681,257 single nucleotide polymorphism markers using Genotyping-by-Sequencing technology and 22 seedling root architecture traits were phenotyped. Utilizing both a general linear model and mixed linear model, a GWAS study was conducted identifying 268 marker trait associations (p ≤ 5.3×10(-7)). Analysis of significant SNP markers for multiple traits showed that several were located within gene models with some SNP markers localized within regions of previously identified root quantitative trait loci. Gene model GRMZM2G153722 located on chromosome 4 contained nine significant markers. This predicted gene is expressed in roots and shoots. This study identifies putatively associated SNP markers associated with root traits at the seedling stage. Some SNPs were located within or near (<1 kb) gene models. These gene models identify possible candidate genes involved in root development at the seedling stage. These and respective linked or functional markers could be targets for breeders for marker assisted selection of seedling root traits.

Plasticity first: molecular signatures of a complex morphological trait in filamentous cyanobacteria.

PubMed

Koch, Robin; Kupczok, Anne; Stucken, Karina; Ilhan, Judith; Hammerschmidt, Katrin; Dagan, Tal

2017-08-31

Filamentous cyanobacteria that differentiate multiple cell types are considered the peak of prokaryotic complexity and their evolution has been studied in the context of multicellularity origins. Species that form true-branching filaments exemplify the most complex cyanobacteria. However, the mechanisms underlying the true-branching morphology remain poorly understood despite of several investigations that focused on the identification of novel genes or pathways. An alternative route for the evolution of novel traits is based on existing phenotypic plasticity. According to that scenario - termed genetic assimilation - the fixation of a novel phenotype precedes the fixation of the genotype. Here we show that the evolution of transcriptional regulatory elements constitutes a major mechanism for the evolution of new traits. We found that supplementation with sucrose reconstitutes the ancestral branchless phenotype of two true-branching Fischerella species and compared the transcription start sites (TSSs) between the two phenotypic states. Our analysis uncovers several orthologous TSSs whose transcription level is correlated with the true-branching phenotype. These TSSs are found in genes that encode components of the septosome and elongasome (e.g., fraC and mreB). The concept of genetic assimilation supplies a tenable explanation for the evolution of novel traits but testing its feasibility is hindered by the inability to recreate and study the evolution of present-day traits. We present a novel approach to examine transcription data for the plasticity first route and provide evidence for its occurrence during the evolution of complex colony morphology in true-branching cyanobacteria. Our results reveal a route for evolution of the true-branching phenotype in cyanobacteria via modification of the transcription level of pre-existing genes. Our study supplies evidence for the 'plasticity-first' hypothesis and highlights the importance of transcriptional regulation in the evolution of novel traits.

Integrating Sequence-based GWAS and RNA-Seq Provides Novel Insights into the Genetic Basis of Mastitis and Milk Production in Dairy Cattle

PubMed Central

Fang, Lingzhao; Sahana, Goutam; Su, Guosheng; Yu, Ying; Zhang, Shengli; Lund, Mogens Sandø; Sørensen, Peter

2017-01-01

Connecting genome-wide association study (GWAS) to biological mechanisms underlying complex traits is a major challenge. Mastitis resistance and milk production are complex traits of economic importance in the dairy sector and are associated with intra-mammary infection (IMI). Here, we integrated IMI-relevant RNA-Seq data from Holstein cattle and sequence-based GWAS data from three dairy cattle breeds (i.e., Holstein, Nordic red cattle, and Jersey) to explore the genetic basis of mastitis resistance and milk production using post-GWAS analyses and a genomic feature linear mixed model. At 24 h post-IMI, genes responsive to IMI in the mammary gland were preferentially enriched for genetic variants associated with mastitis resistance rather than milk production. Response genes in the liver were mainly enriched for variants associated with mastitis resistance at an early time point (3 h) post-IMI, whereas responsive genes at later stages were enriched for associated variants with milk production. The up- and down-regulated genes were enriched for associated variants with mastitis resistance and milk production, respectively. The patterns were consistent across breeds, indicating that different breeds shared similarities in the genetic basis of these traits. Our approaches provide a framework for integrating multiple layers of data to understand the genetic architecture underlying complex traits. PMID:28358110

Recent advancements to study flowering time in almond and other Prunus species

PubMed Central

Sánchez-Pérez, Raquel; Del Cueto, Jorge; Dicenta, Federico; Martínez-Gómez, Pedro

2014-01-01

Flowering time is an important agronomic trait in almond since it is decisive to avoid the late frosts that affect production in early flowering cultivars. Evaluation of this complex trait is a long process because of the prolonged juvenile period of trees and the influence of environmental conditions affecting gene expression year by year. Consequently, flowering time has to be studied for several years to have statistical significant results. This trait is the result of the interaction between chilling and heat requirements. Flowering time is a polygenic trait with high heritability, although a major gene Late blooming (Lb) was described in “Tardy Nonpareil.” Molecular studies at DNA level confirmed this polygenic nature identifying several genome regions (Quantitative Trait Loci, QTL) involved. Studies about regulation of gene expression are scarcer although several transcription factors have been described as responsible for flowering time. From the metabolomic point of view, the integrated analysis of the mechanisms of accumulation of cyanogenic glucosides and flowering regulation through transcription factors open new possibilities in the analysis of this complex trait in almond and in other Prunus species (apricot, cherry, peach, plum). New opportunities are arising from the integration of recent advancements including phenotypic, genetic, genomic, transcriptomic, and metabolomics studies from the beginning of dormancy until flowering. PMID:25071812

Systems genetics approaches to understand complex traits

PubMed Central

Civelek, Mete; Lusis, Aldons J.

2014-01-01

Systems genetics is an approach to understand the flow of biological information that underlies complex traits. It uses a range of experimental and statistical methods to quantitate and integrate intermediate phenotypes, such as transcript, protein or metabolite levels, in populations that vary for traits of interest. Systems genetics studies have provided the first global view of the molecular architecture of complex traits and are useful for the identification of genes, pathways and networks that underlie common human diseases. Given the urgent need to understand how the thousands of loci that have been identified in genome-wide association studies contribute to disease susceptibility, systems genetics is likely to become an increasingly important approach to understanding both biology and disease. PMID:24296534

Joint Analysis of Strain and Parent-of-Origin Effects for Recombinant Inbred Intercrosses Generated from Multiparent Populations with the Collaborative Cross as an Example.

PubMed

Liu, Yanyan; Xiong, Sican; Sun, Wei; Zou, Fei

2018-02-02

Multiparent populations (MPP) have become popular resources for complex trait mapping because of their wider allelic diversity and larger population size compared with traditional two-way recombinant inbred (RI) strains. In mice, the collaborative cross (CC) is one of the most popular MPP and is derived from eight genetically diverse inbred founder strains. The strategy of generating RI intercrosses (RIX) from MPP in general and from the CC in particular can produce a large number of completely reproducible heterozygote genomes that better represent the (outbred) human population. Since both maternal and paternal haplotypes of each RIX are readily available, RIX is a powerful resource for studying both standing genetic and epigenetic variations of complex traits, in particular, the parent-of-origin (PoO) effects, which are important contributors to many complex traits. Furthermore, most complex traits are affected by >1 genes, where multiple quantitative trait locus mapping could be more advantageous. In this paper, for MPP-RIX data but taking CC-RIX as a working example, we propose a general Bayesian variable selection procedure to simultaneously search for multiple genes with founder allelic effects and PoO effects. The proposed model respects the complex relationship among RIX samples, and the performance of the proposed method is examined by extensive simulations. Copyright © 2018 Liu et al.

Early warm-rewarding parenting moderates the genetic contributions to callous-unemotional traits in childhood.

PubMed

Henry, Jeffrey; Dionne, Ginette; Viding, Essi; Vitaro, Frank; Brendgen, Mara; Tremblay, Richard E; Boivin, Michel

2018-04-23

Previous gene-environment interaction studies of CU traits have relied on the candidate gene approach, which does not account for the entire genetic load of complex phenotypes. Moreover, these studies have not examined the role of positive environmental factors such as warm/rewarding parenting. The aim of the present study was to determine whether early warm/rewarding parenting moderates the genetic contributions (i.e., heritability) to callous-unemotional (CU) traits at school age. Data were collected in a population sample of 662 twin pairs (Quebec Newborn Twin Study - QNTS). Mothers reported on their warm/rewarding parenting. Teachers assessed children's CU traits. These reports were subjected to twin modeling. Callous-unemotional traits were highly heritable, with the remaining variance accounted for by nonshared environmental factors. Warm/rewarding parenting significantly moderated the role of genes in CU traits; heritability was lower when children received high warm/rewarding parenting than when they were exposed to low warm/rewarding parenting. High warm/rewarding parenting may partly impede the genetic expression of CU traits. Developmental models of CU traits need to account for such gene-environment processes. © 2018 Association for Child and Adolescent Mental Health.

Exploiting induced variation to dissect quantitative traits in barley.

PubMed

Druka, Arnis; Franckowiak, Jerome; Lundqvist, Udda; Bonar, Nicola; Alexander, Jill; Guzy-Wrobelska, Justyna; Ramsay, Luke; Druka, Ilze; Grant, Iain; Macaulay, Malcolm; Vendramin, Vera; Shahinnia, Fahimeh; Radovic, Slobodanka; Houston, Kelly; Harrap, David; Cardle, Linda; Marshall, David; Morgante, Michele; Stein, Nils; Waugh, Robbie

2010-04-01

The identification of genes underlying complex quantitative traits such as grain yield by means of conventional genetic analysis (positional cloning) requires the development of several large mapping populations. However, it is possible that phenotypically related, but more extreme, allelic variants generated by mutational studies could provide a means for more efficient cloning of QTLs (quantitative trait loci). In barley (Hordeum vulgare), with the development of high-throughput genome analysis tools, efficient genome-wide identification of genetic loci harbouring mutant alleles has recently become possible. Genotypic data from NILs (near-isogenic lines) that carry induced or natural variants of genes that control aspects of plant development can be compared with the location of QTLs to potentially identify candidate genes for development--related traits such as grain yield. As yield itself can be divided into a number of allometric component traits such as tillers per plant, kernels per spike and kernel size, mutant alleles that both affect these traits and are located within the confidence intervals for major yield QTLs may represent extreme variants of the underlying genes. In addition, the development of detailed comparative genomic models based on the alignment of a high-density barley gene map with the rice and sorghum physical maps, has enabled an informed prioritization of 'known function' genes as candidates for both QTLs and induced mutant genes.

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

PubMed

Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao

2016-04-01

To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.

Plasticity Regulators Modulate Specific Root Traits in Discrete Nitrogen Environments

PubMed Central

Gifford, Miriam L.; Banta, Joshua A.; Katari, Manpreet S.; Hulsmans, Jo; Chen, Lisa; Ristova, Daniela; Tranchina, Daniel; Purugganan, Michael D.; Coruzzi, Gloria M.; Birnbaum, Kenneth D.

2013-01-01

Plant development is remarkably plastic but how precisely can the plant customize its form to specific environments? When the plant adjusts its development to different environments, related traits can change in a coordinated fashion, such that two traits co-vary across many genotypes. Alternatively, traits can vary independently, such that a change in one trait has little predictive value for the change in a second trait. To characterize such “tunability” in developmental plasticity, we carried out a detailed phenotypic characterization of complex root traits among 96 accessions of the model Arabidopsis thaliana in two nitrogen environments. The results revealed a surprising level of independence in the control of traits to environment – a highly tunable form of plasticity. We mapped genetic architecture of plasticity using genome-wide association studies and further used gene expression analysis to narrow down gene candidates in mapped regions. Mutants in genes implicated by association and expression analysis showed precise defects in the predicted traits in the predicted environment, corroborating the independent control of plasticity traits. The overall results suggest that there is a pool of genetic variability in plants that controls traits in specific environments, with opportunity to tune crop plants to a given environment. PMID:24039603

Epistasis interaction of QTL effects as a genetic parameter influencing estimation of the genetic additive effect.

PubMed

Bocianowski, Jan

2013-03-01

Epistasis, an additive-by-additive interaction between quantitative trait loci, has been defined as a deviation from the sum of independent effects of individual genes. Epistasis between QTLs assayed in populations segregating for an entire genome has been found at a frequency close to that expected by chance alone. Recently, epistatic effects have been considered by many researchers as important for complex traits. In order to understand the genetic control of complex traits, it is necessary to clarify additive-by-additive interactions among genes. Herein we compare estimates of a parameter connected with the additive gene action calculated on the basis of two models: a model excluding epistasis and a model with additive-by-additive interaction effects. In this paper two data sets were analysed: 1) 150 barley doubled haploid lines derived from the Steptoe × Morex cross, and 2) 145 DH lines of barley obtained from the Harrington × TR306 cross. The results showed that in cases when the effect of epistasis was different from zero, the coefficient of determination was larger for the model with epistasis than for the one excluding epistasis. These results indicate that epistatic interaction plays an important role in controlling the expression of complex traits.

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.

Neofunctionalization of embryonic head patterning genes facilitates the positioning of novel traits on the dorsal head of adult beetles.

PubMed

Zattara, Eduardo E; Busey, Hannah A; Linz, David M; Tomoyasu, Yoshinori; Moczek, Armin P

2016-07-13

The origin and integration of novel traits are fundamental processes during the developmental evolution of complex organisms. Yet how novel traits integrate into pre-existing contexts remains poorly understood. Beetle horns represent a spectacular evolutionary novelty integrated within the context of the adult dorsal head, a highly conserved trait complex present since the origin of insects. We investigated whether otd1/2 and six3, members of a highly conserved gene network that instructs the formation of the anterior end of most bilaterians, also play roles in patterning more recently evolved traits. Using ablation-based fate-mapping, comparative larval RNA interference (RNAi) and transcript sequencing, we found that otd1/2, but not six3, play a fundamental role in the post-embryonic formation of the adult dorsal head and head horns of Onthophagus beetles. By contrast, neither gene appears to pattern the adult head of Tribolium flour beetles even though all are expressed in the dorsal head epidermis of both Onthophagus and Tribolium We propose that, at least in beetles, the roles of otd genes during post-embryonic development are decoupled from their embryonic functions, and that potentially non-functional post-embryonic expression in the dorsal head facilitated their co-option into a novel horn-patterning network during Onthophagus evolution. © 2016 The Author(s).

Neofunctionalization of embryonic head patterning genes facilitates the positioning of novel traits on the dorsal head of adult beetles

PubMed Central

Busey, Hannah A.; Linz, David M.; Tomoyasu, Yoshinori; Moczek, Armin P.

2016-01-01

The origin and integration of novel traits are fundamental processes during the developmental evolution of complex organisms. Yet how novel traits integrate into pre-existing contexts remains poorly understood. Beetle horns represent a spectacular evolutionary novelty integrated within the context of the adult dorsal head, a highly conserved trait complex present since the origin of insects. We investigated whether otd1/2 and six3, members of a highly conserved gene network that instructs the formation of the anterior end of most bilaterians, also play roles in patterning more recently evolved traits. Using ablation-based fate-mapping, comparative larval RNA interference (RNAi) and transcript sequencing, we found that otd1/2, but not six3, play a fundamental role in the post-embryonic formation of the adult dorsal head and head horns of Onthophagus beetles. By contrast, neither gene appears to pattern the adult head of Tribolium flour beetles even though all are expressed in the dorsal head epidermis of both Onthophagus and Tribolium. We propose that, at least in beetles, the roles of otd genes during post-embryonic development are decoupled from their embryonic functions, and that potentially non-functional post-embryonic expression in the dorsal head facilitated their co-option into a novel horn-patterning network during Onthophagus evolution. PMID:27412276

Association of candidate genes with drought tolerance traits in diverse perennial ryegrass accessions

PubMed Central

Jiang, Yiwei

2013-01-01

Drought is a major environmental stress limiting growth of perennial grasses in temperate regions. Plant drought tolerance is a complex trait that is controlled by multiple genes. Candidate gene association mapping provides a powerful tool for dissection of complex traits. Candidate gene association mapping of drought tolerance traits was conducted in 192 diverse perennial ryegrass (Lolium perenne L.) accessions from 43 countries. The panel showed significant variations in leaf wilting, leaf water content, canopy and air temperature difference, and chlorophyll fluorescence under well-watered and drought conditions across six environments. Analysis of 109 simple sequence repeat markers revealed five population structures in the mapping panel. A total of 2520 expression-based sequence readings were obtained for a set of candidate genes involved in antioxidant metabolism, dehydration, water movement across membranes, and signal transduction, from which 346 single nucleotide polymorphisms were identified. Significant associations were identified between a putative LpLEA3 encoding late embryogenesis abundant group 3 protein and a putative LpFeSOD encoding iron superoxide dismutase and leaf water content, as well as between a putative LpCyt Cu-ZnSOD encoding cytosolic copper-zinc superoxide dismutase and chlorophyll fluorescence under drought conditions. Four of these identified significantly associated single nucleotide polymorphisms from these three genes were also translated to amino acid substitutions in different genotypes. These results indicate that allelic variation in these genes may affect whole-plant response to drought stress in perennial ryegrass. PMID:23386684

On the holistic approach in cellular and cancer biology: nonlinearity, complexity, and quasi-determinism of the dynamic cellular network.

PubMed

Waliszewski, P; Molski, M; Konarski, J

1998-06-01

A keystone of the molecular reductionist approach to cellular biology is a specific deductive strategy relating genotype to phenotype-two distinct categories. This relationship is based on the assumption that the intermediary cellular network of actively transcribed genes and their regulatory elements is deterministic (i.e., a link between expression of a gene and a phenotypic trait can always be identified, and evolution of the network in time is predetermined). However, experimental data suggest that the relationship between genotype and phenotype is nonbijective (i.e., a gene can contribute to the emergence of more than just one phenotypic trait or a phenotypic trait can be determined by expression of several genes). This implies nonlinearity (i.e., lack of the proportional relationship between input and the outcome), complexity (i.e. emergence of the hierarchical network of multiple cross-interacting elements that is sensitive to initial conditions, possesses multiple equilibria, organizes spontaneously into different morphological patterns, and is controlled in dispersed rather than centralized manner), and quasi-determinism (i.e., coexistence of deterministic and nondeterministic events) of the network. Nonlinearity within the space of the cellular molecular events underlies the existence of a fractal structure within a number of metabolic processes, and patterns of tissue growth, which is measured experimentally as a fractal dimension. Because of its complexity, the same phenotype can be associated with a number of alternative sequences of cellular events. Moreover, the primary cause initiating phenotypic evolution of cells such as malignant transformation can be favored probabilistically, but not identified unequivocally. Thermodynamic fluctuations of energy rather than gene mutations, the material traits of the fluctuations alter both the molecular and informational structure of the network. Then, the interplay between deterministic chaos, complexity, self-organization, and natural selection drives formation of malignant phenotype. This concept offers a novel perspective for investigation of tumorigenesis without invalidating current molecular findings. The essay integrates the ideas of the sciences of complexity in a biological context.

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.

Use of Multivariate Linkage Analysis for Dissection of a Complex Cognitive Trait

PubMed Central

Marlow, Angela J.; Fisher, Simon E.; Francks, Clyde; MacPhie, I. Laurence; Cherny, Stacey S.; Richardson, Alex J.; Talcott, Joel B.; Stein, John F.; Monaco, Anthony P.; Cardon, Lon R.

2003-01-01

Replication of linkage results for complex traits has been exceedingly difficult, owing in part to the inability to measure the precise underlying phenotype, small sample sizes, genetic heterogeneity, and statistical methods employed in analysis. Often, in any particular study, multiple correlated traits have been collected, yet these have been analyzed independently or, at most, in bivariate analyses. Theoretical arguments suggest that full multivariate analysis of all available traits should offer more power to detect linkage; however, this has not yet been evaluated on a genomewide scale. Here, we conduct multivariate genomewide analyses of quantitative-trait loci that influence reading- and language-related measures in families affected with developmental dyslexia. The results of these analyses are substantially clearer than those of previous univariate analyses of the same data set, helping to resolve a number of key issues. These outcomes highlight the relevance of multivariate analysis for complex disorders for dissection of linkage results in correlated traits. The approach employed here may aid positional cloning of susceptibility genes in a wide spectrum of complex traits. PMID:12587094

Identifying candidate genes affecting developmental time in Drosophila melanogaster: pervasive pleiotropy and gene-by-environment interaction

PubMed Central

Mensch, Julián; Lavagnino, Nicolás; Carreira, Valeria Paula; Massaldi, Ana; Hasson, Esteban; Fanara, Juan José

2008-01-01

Background Understanding the genetic architecture of ecologically relevant adaptive traits requires the contribution of developmental and evolutionary biology. The time to reach the age of reproduction is a complex life history trait commonly known as developmental time. In particular, in holometabolous insects that occupy ephemeral habitats, like fruit flies, the impact of developmental time on fitness is further exaggerated. The present work is one of the first systematic studies of the genetic basis of developmental time, in which we also evaluate the impact of environmental variation on the expression of the trait. Results We analyzed 179 co-isogenic single P[GT1]-element insertion lines of Drosophila melanogaster to identify novel genes affecting developmental time in flies reared at 25°C. Sixty percent of the lines showed a heterochronic phenotype, suggesting that a large number of genes affect this trait. Mutant lines for the genes Merlin and Karl showed the most extreme phenotypes exhibiting a developmental time reduction and increase, respectively, of over 2 days and 4 days relative to the control (a co-isogenic P-element insertion free line). In addition, a subset of 42 lines selected at random from the initial set of 179 lines was screened at 17°C. Interestingly, the gene-by-environment interaction accounted for 52% of total phenotypic variance. Plastic reaction norms were found for a large number of developmental time candidate genes. Conclusion We identified components of several integrated time-dependent pathways affecting egg-to-adult developmental time in Drosophila. At the same time, we also show that many heterochronic phenotypes may arise from changes in genes involved in several developmental mechanisms that do not explicitly control the timing of specific events. We also demonstrate that many developmental time genes have pleiotropic effects on several adult traits and that the action of most of them is sensitive to temperature during development. Taken together, our results stress the need to take into account the effect of environmental variation and the dynamics of gene interactions on the genetic architecture of this complex life-history trait. PMID:18687152

Genomic Prediction and Association Mapping of Curd-Related Traits in Gene Bank Accessions of Cauliflower.

PubMed

Thorwarth, Patrick; Yousef, Eltohamy A A; Schmid, Karl J

2018-02-02

Genetic resources are an important source of genetic variation for plant breeding. Genome-wide association studies (GWAS) and genomic prediction greatly facilitate the analysis and utilization of useful genetic diversity for improving complex phenotypic traits in crop plants. We explored the potential of GWAS and genomic prediction for improving curd-related traits in cauliflower ( Brassica oleracea var. botrytis ) by combining 174 randomly selected cauliflower gene bank accessions from two different gene banks. The collection was genotyped with genotyping-by-sequencing (GBS) and phenotyped for six curd-related traits at two locations and three growing seasons. A GWAS analysis based on 120,693 single-nucleotide polymorphisms identified a total of 24 significant associations for curd-related traits. The potential for genomic prediction was assessed with a genomic best linear unbiased prediction model and BayesB. Prediction abilities ranged from 0.10 to 0.66 for different traits and did not differ between prediction methods. Imputation of missing genotypes only slightly improved prediction ability. Our results demonstrate that GWAS and genomic prediction in combination with GBS and phenotyping of highly heritable traits can be used to identify useful quantitative trait loci and genotypes among genetically diverse gene bank material for subsequent utilization as genetic resources in cauliflower breeding. Copyright © 2018 Thorwarth et al.

Detection of Epistasis for Flowering Time Using Bayesian Multilocus Estimation in a Barley MAGIC Population

PubMed Central

Mathew, Boby; Léon, Jens; Sannemann, Wiebke; Sillanpää, Mikko J.

2018-01-01

Gene-by-gene interactions, also known as epistasis, regulate many complex traits in different species. With the availability of low-cost genotyping it is now possible to study epistasis on a genome-wide scale. However, identifying genome-wide epistasis is a high-dimensional multiple regression problem and needs the application of dimensionality reduction techniques. Flowering Time (FT) in crops is a complex trait that is known to be influenced by many interacting genes and pathways in various crops. In this study, we successfully apply Sure Independence Screening (SIS) for dimensionality reduction to identify two-way and three-way epistasis for the FT trait in a Multiparent Advanced Generation Inter-Cross (MAGIC) barley population using the Bayesian multilocus model. The MAGIC barley population was generated from intercrossing among eight parental lines and thus, offered greater genetic diversity to detect higher-order epistatic interactions. Our results suggest that SIS is an efficient dimensionality reduction approach to detect high-order interactions in a Bayesian multilocus model. We also observe that many of our findings (genomic regions with main or higher-order epistatic effects) overlap with known candidate genes that have been already reported in barley and closely related species for the FT trait. PMID:29254994

Symbiosis within Symbiosis: Evolving Nitrogen-Fixing Legume Symbionts.

PubMed

Remigi, Philippe; Zhu, Jun; Young, J Peter W; Masson-Boivin, Catherine

2016-01-01

Bacterial accessory genes are genomic symbionts with an evolutionary history and future that is different from that of their hosts. Packages of accessory genes move from strain to strain and confer important adaptations, such as interaction with eukaryotes. The ability to fix nitrogen with legumes is a remarkable example of a complex trait spread by horizontal transfer of a few key symbiotic genes, converting soil bacteria into legume symbionts. Rhizobia belong to hundreds of species restricted to a dozen genera of the Alphaproteobacteria and Betaproteobacteria, suggesting infrequent successful transfer between genera but frequent successful transfer within genera. Here we review the genetic and environmental conditions and selective forces that have shaped evolution of this complex symbiotic trait. Copyright © 2015 Elsevier Ltd. All rights reserved.

Genetic studies of plasma analytes identify novel potential biomarkers for several complex traits

PubMed Central

Deming, Yuetiva; Xia, Jian; Cai, Yefei; Lord, Jenny; Del-Aguila, Jorge L.; Fernandez, Maria Victoria; Carrell, David; Black, Kathleen; Budde, John; Ma, ShengMei; Saef, Benjamin; Howells, Bill; Bertelsen, Sarah; Bailey, Matthew; Ridge, Perry G.; Hefti, Franz; Fillit, Howard; Zimmerman, Earl A.; Celmins, Dzintra; Brown, Alice D.; Carrillo, Maria; Fleisher, Adam; Reeder, Stephanie; Trncic, Nadira; Burke, Anna; Tariot, Pierre; Reiman, Eric M.; Chen, Kewei; Sabbagh, Marwan N.; Beiden, Christine M.; Jacobson, Sandra A.; Sirrel, Sherye A.; Doody, Rachelle S.; Villanueva-Meyer, Javier; Chowdhury, Munir; Rountree, Susan; Dang, Mimi; Kowall, Neil; Killiany, Ronald; Budson, Andrew E.; Norbash, Alexander; Johnson, Patricia Lynn; Green, Robert C.; Marshall, Gad; Johnson, Keith A.; Sperling, Reisa A.; Snyder, Peter; Salloway, Stephen; Malloy, Paul; Correia, Stephen; Bernick, Charles; Munic, Donna; Stern, Yaakov; Honig, Lawrence S.; Bell, Karen L.; Relkin, Norman; Chaing, Gloria; Ravdin, Lisa; Paul, Steven; Flashman, Laura A.; Seltzer, Marc; Hynes, Mary L.; Santulli, Robert B.; Bates, Vernice; Capote, Horacio; Rainka, Michelle; Friedl, Karl; Murali Doraiswamy, P.; Petrella, Jeffrey R.; Borges-Neto, Salvador; James, Olga; Wong, Terence; Coleman, Edward; Schwartz, Adam; Cellar, Janet S.; Levey, Allan L.; Lah, James J.; Behan, Kelly; Scott Turner, Raymond; Johnson, Kathleen; Reynolds, Brigid; Pearlson, Godfrey D.; Blank, Karen; Anderson, Karen; Obisesan, Thomas O.; Wolday, Saba; Allard, Joanne; Lerner, Alan; Ogrocki, Paula; Tatsuoka, Curtis; Fatica, Parianne; Farlow, Martin R.; Saykin, Andrew J.; Foroud, Tatiana M.; Shen, Li; Faber, Kelly; Kim, Sungeun; Nho, Kwangsik; Marie Hake, Ann; Matthews, Brandy R.; Brosch, Jared R.; Herring, Scott; Hunt, Cynthia; Albert, Marilyn; Onyike, Chiadi; D’Agostino, Daniel; Kielb, Stephanie; Graff-Radford, Neill R; Parfitt, Francine; Kendall, Tracy; Johnson, Heather; Petersen, Ronald; Jack, Clifford R.; Bernstein, Matthew; Borowski, Bret; Gunter, Jeff; Senjem, Matt; Vemuri, Prashanthi; Jones, David; Kantarci, Kejal; Ward, Chad; Mason, Sara S.; Albers, Colleen S.; Knopman, David; Johnson, Kris; Chertkow, Howard; Hosein, Chris; Mintzer, Jacob; Spicer, Kenneth; Bachman, David; Grossman, Hillel; Mitsis, Effie; Pomara, Nunzio; Hernando, Raymundo; Sarrael, Antero; Potter, William; Buckholtz, Neil; Hsiao, John; Kittur, Smita; Galvin, James E.; Cerbone, Brittany; Michel, Christina A.; Pogorelec, Dana M.; Rusinek, Henry; de Leon, Mony J; Glodzik, Lidia; De Santi, Susan; Johnson, Nancy; Chuang-Kuo; Kerwin, Diana; Bonakdarpour, Borna; Weintraub, Sandra; Grafman, Jordan; Lipowski, Kristine; Mesulam, Marek-Marsel; Scharre, Douglas W.; Kataki, Maria; Adeli, Anahita; Kaye, Jeffrey; Quinn, Joseph; Silbert, Lisa; Lind, Betty; Carter, Raina; Dolen, Sara; Borrie, Michael; Lee, T-Y; Bartha, Rob; Martinez, Walter; Villena, Teresa; Sadowsky, Carl; Khachaturian, Zaven; Ott, Brian R.; Querfurth, Henry; Tremont, Geoffrey; Frank, Richard; Fleischman, Debra; Arfanakis, Konstantinos; Shah, Raj C.; deToledo-Morrell, Leyla; Sorensen, Greg; Finger, Elizabeth; Pasternack, Stephen; Rachinsky, Irina; Drost, Dick; Rogers, John; Kertesz, Andrew; Furst, Ansgar J.; Chad, Stevan; Yesavage, Jerome; Taylor, Joy L.; Lane, Barton; Rosen, Allyson; Tinklenberg, Jared; Black, Sandra; Stefanovic, Bojana; Caldwell, Curtis; Robin Hsiung, Ging-Yuek; Mudge, Benita; Assaly, Michele; Fox, Nick; Schultz, Susan K.; Boles Ponto, Laura L.; Shim, Hyungsub; Ekstam Smith, Karen; Burns, Jeffrey M.; Swerdlow, Russell H.; Brooks, William M.; Marson, Daniel; Griffith, Randall; Clark, David; Geldmacher, David; Brockington, John; Roberson, Erik; Natelson Love, Marissa; DeCarli, Charles; Carmichael, Owen; Olichney, John; Maillard, Pauline; Fletcher, Evan; Nguyen, Dana; Preda, Andrian; Potkin, Steven; Mulnard, Ruth A.; Thai, Gaby; McAdams-Ortiz, Catherine; Landau, Susan; Jagust, William; Apostolova, Liana; Tingus, Kathleen; Woo, Ellen; Silverman, Daniel H.S.; Lu, Po H.; Bartzokis, George; Thompson, Paul; Donohue, Michael; Thomas, Ronald G.; Walter, Sarah; Gessert, Devon; Brewer, James; Vanderswag, Helen; Sather, Tamie; Jiminez, Gus; Balasubramanian, Archana B.; Mason, Jennifer; Sim, Iris; Aisen, Paul; Davis, Melissa; Morrison, Rosemary; Harvey, Danielle; Thal, Lean; Beckett, Laurel; Neylan, Thomas; Finley, Shannon; Weiner, Michael W.; Hayes, Jacqueline; Rosen, Howard J.; Miller, Bruce L.; Perry, David; Massoglia, Dino; Brawman-Mentzer, Olga; Schuff, Norbert; Smith, Charles D.; Hardy, Peter; Sinha, Partha; Oates, Elizabeth; Conrad, Gary; Koeppe, Robert A.; Lord, Joanne L.; Heidebrink, Judith L.; Arnold, Steven E.; Karlawish, Jason H.; Wolk, David; Clark, Christopher M.; Trojanowki, John Q.; Shaw, Leslie M.; Lee, Virginia; Korecka, Magdalena; Figurski, Michal; Toga, Arthur W.; Crawford, Karen; Neu, Scott; Schneider, Lon S.; Pawluczyk, Sonia; Beccera, Mauricio; Teodoro, Liberty; Spann, Bryan M.; Womack, Kyle; Mathews, Dana; Quiceno, Mary; Foster, Norm; Montine, Tom; Fruehling, J. Jay; Harding, Sandra; Johnson, Sterling; Asthana, Sanjay; Carlsson, Cynthia M.; Petrie, Eric C.; Peskind, Elaine; Li, Gail; Porsteinsson, Anton P.; Goldstein, Bonnie S.; Martin, Kim; Makino, Kelly M.; Ismail, M. Saleem; Brand, Connie; Smith, Amanda; Ashok Raj, Balebail; Fargher, Kristin; Kuller, Lew; Mathis, Chet; Ann Oakley, Mary; Lopez, Oscar L.; Simpson, Donna M.; Sink, Kaycee M.; Gordineer, Leslie; Williamson, Jeff D.; Garg, Pradeep; Watkins, Franklin; Cairns, Nigel J.; Raichle, Marc; Morris, John C.; Householder, Erin; Taylor-Reinwald, Lisa; Holtzman, David; Ances, Beau; Carroll, Maria; Creech, Mary L.; Franklin, Erin; Mintun, Mark A.; Schneider, Stacy; Oliver, Angela; Duara, Ranjan; Varon, Daniel; Greig, Maria T.; Roberts, Peggy; Varma, Pradeep; MacAvoy, Martha G.; Carson, Richard E.; van Dyck, Christopher H.; Davies, Peter; Holtzman, David; Morris, John C.; Bales, Kelly; Pickering, Eve H.; Lee, Jin-Moo; Heitsch, Laura; Kauwe, John; Goate, Alison; Piccio, Laura; Cruchaga, Carlos

2016-01-01

Genome-wide association studies of 146 plasma protein levels in 818 individuals revealed 56 genome-wide significant associations (28 novel) with 47 analytes. Loci associated with plasma levels of 39 proteins tested have been previously associated with various complex traits such as heart disease, inflammatory bowel disease, Type 2 diabetes, and multiple sclerosis. These data suggest that these plasma protein levels may constitute informative endophenotypes for these complex traits. We found three potential pleiotropic genes: ABO for plasma SELE and ACE levels, FUT2 for CA19-9 and CEA plasma levels, and APOE for ApoE and CRP levels. We also found multiple independent signals in loci associated with plasma levels of ApoH, CA19-9, FetuinA, IL6r, and LPa. Our study highlights the power of biological traits for genetic studies to identify genetic variants influencing clinically relevant traits, potential pleiotropic effects, and complex disease associations in the same locus.

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

Progress of genome wide association study in domestic animals

PubMed Central

2012-01-01

Domestic animals are invaluable resources for study of the molecular architecture of complex traits. Although the mapping of quantitative trait loci (QTL) responsible for economically important traits in domestic animals has achieved remarkable results in recent decades, not all of the genetic variation in the complex traits has been captured because of the low density of markers used in QTL mapping studies. The genome wide association study (GWAS), which utilizes high-density single-nucleotide polymorphism (SNP), provides a new way to tackle this issue. Encouraging achievements in dissection of the genetic mechanisms of complex diseases in humans have resulted from the use of GWAS. At present, GWAS has been applied to the field of domestic animal breeding and genetics, and some advances have been made. Many genes or markers that affect economic traits of interest in domestic animals have been identified. In this review, advances in the use of GWAS in domestic animals are described. PMID:22958308

Investigation of four porcine candidate genes (H-FABP, MYOD1, UCP3 and MASTR) for meat quality traits in Large White pigs.

PubMed

Han, Xuelei; Jiang, Tengfei; Yang, Huawei; Zhang, Qingde; Wang, Weimin; Fan, Bin; Liu, Bang

2012-06-01

Meat quality traits are economically important traits of swine, and are controlled by multiple genes as complex quantitative traits. In the present study four genes, H-FABP (heart fatty acid-binding protein), MASTR (MEF2 activating motif and SAP domain containing transcriptional regulator), UCP3 (uncoupling protein 3) and MYOD1 (myogenic differentiation 1) were researched in Large White pigs. The polymorphisms H-FABP T/C of 5'UTR, MYOD1 g.257 A>C, UCP3 g.1406 G>A in exon 3 and MASTR c.187 C>T have been reported to be associated with meat quality traits in pigs. The aim of this study was to analyze the effect of single and multiple markers for single traits in Large White pigs. The single marker association analysis showed that the H-FABP and MASTR genes were associated with IMF (intramuscular fat content) (P < 0.05), and that the g.257 A>C of MYOD1 gene was most significantly related to muscle pH value (P < 0.01). The multiple markers for IMF were analyzed by combining the markers and quantitative trait modes into the linear regression. The results revealed that H-FABP and MASTR integrate gene networks for IMF. Thus, our study results suggested that H-FABP and MASTR polymorphisms could be used as genetic markers in the marker-assisted selection towards the improvement of IMF in Large White pigs.

Cross-Study Comparison Reveals Common Genomic, Network, and Functional Signatures of Desiccation Resistance in Drosophila melanogaster

PubMed Central

Telonis-Scott, Marina; Sgrò, Carla M.; Hoffmann, Ary A.; Griffin, Philippa C.

2016-01-01

Repeated attempts to map the genomic basis of complex traits often yield different outcomes because of the influence of genetic background, gene-by-environment interactions, and/or statistical limitations. However, where repeatability is low at the level of individual genes, overlap often occurs in gene ontology categories, genetic pathways, and interaction networks. Here we report on the genomic overlap for natural desiccation resistance from a Pool-genome-wide association study experiment and a selection experiment in flies collected from the same region in southeastern Australia in different years. We identified over 600 single nucleotide polymorphisms associated with desiccation resistance in flies derived from almost 1,000 wild-caught genotypes, a similar number of loci to that observed in our previous genomic study of selected lines, demonstrating the genetic complexity of this ecologically important trait. By harnessing the power of cross-study comparison, we narrowed the candidates from almost 400 genes in each study to a core set of 45 genes, enriched for stimulus, stress, and defense responses. In addition to gene-level overlap, there was higher order congruence at the network and functional levels, suggesting genetic redundancy in key stress sensing, stress response, immunity, signaling, and gene expression pathways. We also identified variants linked to different molecular aspects of desiccation physiology previously verified from functional experiments. Our approach provides insight into the genomic basis of a complex and ecologically important trait and predicts candidate genetic pathways to explore in multiple genetic backgrounds and related species within a functional framework. PMID:26733490

Comparing GWAS Results of Complex Traits Using Full Genetic Model and Additive Models for Revealing Genetic Architecture

PubMed Central

Monir, Md. Mamun; Zhu, Jun

2017-01-01

Most of the genome-wide association studies (GWASs) for human complex diseases have ignored dominance, epistasis and ethnic interactions. We conducted comparative GWASs for total cholesterol using full model and additive models, which illustrate the impacts of the ignoring genetic variants on analysis results and demonstrate how genetic effects of multiple loci could differ across different ethnic groups. There were 15 quantitative trait loci with 13 individual loci and 3 pairs of epistasis loci identified by full model, whereas only 14 loci (9 common loci and 5 different loci) identified by multi-loci additive model. Again, 4 full model detected loci were not detected using multi-loci additive model. PLINK-analysis identified two loci and GCTA-analysis detected only one locus with genome-wide significance. Full model identified three previously reported genes as well as several new genes. Bioinformatics analysis showed some new genes are related with cholesterol related chemicals and/or diseases. Analyses of cholesterol data and simulation studies revealed that the full model performs were better than the additive-model performs in terms of detecting power and unbiased estimations of genetic variants of complex traits. PMID:28079101

Survey of the Heritability and Sparse Architecture of Gene Expression Traits across Human Tissues.

PubMed

Wheeler, Heather E; Shah, Kaanan P; Brenner, Jonathon; Garcia, Tzintzuni; Aquino-Michaels, Keston; Cox, Nancy J; Nicolae, Dan L; Im, Hae Kyung

2016-11-01

Understanding the genetic architecture of gene expression traits is key to elucidating the underlying mechanisms of complex traits. Here, for the first time, we perform a systematic survey of the heritability and the distribution of effect sizes across all representative tissues in the human body. We find that local h2 can be relatively well characterized with 59% of expressed genes showing significant h2 (FDR < 0.1) in the DGN whole blood cohort. However, current sample sizes (n ≤ 922) do not allow us to compute distal h2. Bayesian Sparse Linear Mixed Model (BSLMM) analysis provides strong evidence that the genetic contribution to local expression traits is dominated by a handful of genetic variants rather than by the collective contribution of a large number of variants each of modest size. In other words, the local architecture of gene expression traits is sparse rather than polygenic across all 40 tissues (from DGN and GTEx) examined. This result is confirmed by the sparsity of optimal performing gene expression predictors via elastic net modeling. To further explore the tissue context specificity, we decompose the expression traits into cross-tissue and tissue-specific components using a novel Orthogonal Tissue Decomposition (OTD) approach. Through a series of simulations we show that the cross-tissue and tissue-specific components are identifiable via OTD. Heritability and sparsity estimates of these derived expression phenotypes show similar characteristics to the original traits. Consistent properties relative to prior GTEx multi-tissue analysis results suggest that these traits reflect the expected biology. Finally, we apply this knowledge to develop prediction models of gene expression traits for all tissues. The prediction models, heritability, and prediction performance R2 for original and decomposed expression phenotypes are made publicly available (https://github.com/hakyimlab/PrediXcan).

A Systems Approach Identifies Networks and Genes Linking Sleep and Stress: Implications for Neuropsychiatric Disorders

PubMed Central

Jiang, Peng; Scarpa, Joseph R.; Fitzpatrick, Karrie; Losic, Bojan; Gao, Vance D.; Hao, Ke; Summa, Keith C.; Yang, He S.; Zhang, Bin; Allada, Ravi; Vitaterna, Martha H.; Turek, Fred W.; Kasarskis, Andrew

2016-01-01

SUMMARY Sleep dysfunction and stress susceptibility are co-morbid complex traits, which often precede and predispose patients to a variety of neuropsychiatric diseases. Here, we demonstrate multi-level organizations of genetic landscape, candidate genes, and molecular networks associated with 328 stress and sleep traits in a chronically stressed population of 338 (C57BL/6J×A/J) F2 mice. We constructed striatal gene co-expression networks, revealing functionally and cell-type specific gene co-regulations important for stress and sleep. Using a composite ranking system, we identified network modules most relevant for 15 independent phenotypic categories, highlighting a mitochondria/synaptic module that links sleep and stress. The key network regulators of this module are overrepresented with genes implicated in neuropsychiatric diseases. Our work suggests the interplay between sleep, stress, and neuropathology emerge from genetic influences on gene expression and their collective organization through complex molecular networks, providing a framework to interrogate the mechanisms underlying sleep, stress susceptibility, and related neuropsychiatric disorders. PMID:25921536

Integrated translational genomics for analysis of complex traits in sorghum

USDA-ARS?s Scientific Manuscript database

We will report on the integration of sequencing and genotype data from natural variation (by whole genome resequencing [wgs] or genotype by sequencing [gbs]), transcriptome (RNA-seq) and mutant analysis (also by wgs) with the goal of identifying genes controlling important agronomic traits and tran...

Sunflower Hybrid Breeding: From Markers to Genomic Selection

PubMed Central

Dimitrijevic, Aleksandra; Horn, Renate

2018-01-01

In sunflower, molecular markers for simple traits as, e.g., fertility restoration, high oleic acid content, herbicide tolerance or resistances to Plasmopara halstedii, Puccinia helianthi, or Orobanche cumana have been successfully used in marker-assisted breeding programs for years. However, agronomically important complex quantitative traits like yield, heterosis, drought tolerance, oil content or selection for disease resistance, e.g., against Sclerotinia sclerotiorum have been challenging and will require genome-wide approaches. Plant genetic resources for sunflower are being collected and conserved worldwide that represent valuable resources to study complex traits. Sunflower association panels provide the basis for genome-wide association studies, overcoming disadvantages of biparental populations. Advances in technologies and the availability of the sunflower genome sequence made novel approaches on the whole genome level possible. Genotype-by-sequencing, and whole genome sequencing based on next generation sequencing technologies facilitated the production of large amounts of SNP markers for high density maps as well as SNP arrays and allowed genome-wide association studies and genomic selection in sunflower. Genome wide or candidate gene based association studies have been performed for traits like branching, flowering time, resistance to Sclerotinia head and stalk rot. First steps in genomic selection with regard to hybrid performance and hybrid oil content have shown that genomic selection can successfully address complex quantitative traits in sunflower and will help to speed up sunflower breeding programs in the future. To make sunflower more competitive toward other oil crops higher levels of resistance against pathogens and better yield performance are required. In addition, optimizing plant architecture toward a more complex growth type for higher plant densities has the potential to considerably increase yields per hectare. Integrative approaches combining omic technologies (genomics, transcriptomics, proteomics, metabolomics and phenomics) using bioinformatic tools will facilitate the identification of target genes and markers for complex traits and will give a better insight into the mechanisms behind the traits. PMID:29387071

Quantitative gene-gene and gene-environment mapping for leaf shape variation using tree-based models

USDA-ARS?s Scientific Manuscript database

Leaf shape traits have long been a focus of many disciplines, but searching for complex genetic and environmental interactive mechanisms regulating leaf shape variation has not yet been well developed. The question of the respective roles of gene and environment and how they interplay to modulate l...

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.

Genetics of preeclampsia: what are the challenges?

PubMed

Bernard, Nathalie; Giguère, Yves

2003-07-01

Despite recent efforts to identify susceptibility genes of preeclampsia, the genetic determinants of the condition remain ill-defined, as is the situation for most disorders of complex inheritance patterns. The angiotensinogen, factor V, and methylenetetrahydrofolate reductase genes have been investigated in different populations, as have other genes involved in blood pressure, vascular volume control, thrombophilia, lipid metabolism, oxidative stress, and endothelial dysfunction. The study of the genetics of complex traits is faced with both methodological and genetic issues; these include adequate sample size to allow for the identification of modest genetic effects, of gene-gene and gene-environment interactions, the study of adequate quantitative traits and extreme phenotypes, haplotype analyses, statistical genetics, genome-wide (hypothesis-free) versus candidate-gene (hypothesis-driven) approaches, and the validation of positive associations. The use of genetically well-characterized populations showing a founder effect, such as the French-Canadian population of Quebec, in genetic association studies, may help to unravel the susceptibility genes of disorders showing complex inheritance, such as preeclampsia. It is necessary to better evaluate the role of the fetal genome in the resulting predisposition to preeclampsia and its complications. Eventually, we may be able to integrate genetic information to better identify the women at risk of developing preeclampsia, and to improve the management of those suffering from this condition.

Hormone response to bidirectional selection on social behavior.

PubMed

Amdam, Gro V; Page, Robert E; Fondrk, M Kim; Brent, Colin S

2010-01-01

Behavior is a quantitative trait determined by multiple genes. Some of these genes may have effects from early development and onward by influencing hormonal systems that are active during different life-stages leading to complex associations, or suites, of traits. Honey bees (Apis mellifera) have been used extensively in experiments on the genetic and hormonal control of complex social behavior, but the relationships between their early developmental processes and adult behavioral variation are not well understood. Bidirectional selective breeding on social food-storage behavior produced two honey bee strains, each with several sublines, that differ in an associated suite of anatomical, physiological, and behavioral traits found in unselected wild type bees. Using these genotypes, we document strain-specific changes during larval, pupal, and early adult life-stages for the central insect hormones juvenile hormone (JH) and ecdysteroids. Strain differences correlate with variation in female reproductive anatomy (ovary size), which can be influenced by JH during development, and with secretion rates of ecdysteroid from the ovaries of adults. Ovary size was previously assigned to the suite of traits of honey bee food-storage behavior. Our findings support that bidirectional selection on honey bee social behavior acted on pleiotropic gene networks. These networks may bias a bee's adult phenotype by endocrine effects on early developmental processes that regulate variation in reproductive traits. © 2010 Wiley Periodicals, Inc.

A Neurogenetic Approach to Impulsivity

PubMed Central

Congdon, Eliza; Canli, Turhan

2008-01-01

Impulsivity is a complex and multidimensional trait that is of interest to both personality psychologists and to clinicians. For investigators seeking the biological basis of personality traits, the use of neuroimaging techniques such as positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) revolutionized personality psychology in less than a decade. Now, another revolution is under way, and it originates from molecular biology. Specifically, new findings in molecular genetics, the detailed mapping and the study of the function of genes, have shown that individual differences in personality traits can be related to individual differences within specific genes. In this article, we will review the current state of the field with respect to the neural and genetic basis of trait impulsivity. PMID:19012655

Identification of gene networks underlying dystocia in dairy cattle

USDA-ARS?s Scientific Manuscript database

Dystocia is a trait with a high impact in the dairy industry. Among its risk factors are calf weight, gestation length, breed and conformation. Biological networks have been proposed to capture the genetic architecture of complex traits, where GWAS show limitations. The objective of this study was t...

Natural Genetic Variation and Candidate Genes for Morphological Traits in Drosophila melanogaster

PubMed Central

Carreira, Valeria Paula; Mensch, Julián; Hasson, Esteban; Fanara, Juan José

2016-01-01

Body size is a complex character associated to several fitness related traits that vary within and between species as a consequence of environmental and genetic factors. Latitudinal and altitudinal clines for different morphological traits have been described in several species of Drosophila and previous work identified genomic regions associated with such variation in D. melanogaster. However, the genetic factors that orchestrate morphological variation have been barely studied. Here, our main objective was to investigate genetic variation for different morphological traits associated to the second chromosome in natural populations of D. melanogaster along latitudinal and altitudinal gradients in Argentina. Our results revealed weak clinal signals and a strong population effect on morphological variation. Moreover, most pairwise comparisons between populations were significant. Our study also showed important within-population genetic variation, which must be associated to the second chromosome, as the lines are otherwise genetically identical. Next, we examined the contribution of different candidate genes to natural variation for these traits. We performed quantitative complementation tests using a battery of lines bearing mutated alleles at candidate genes located in the second chromosome and six second chromosome substitution lines derived from natural populations which exhibited divergent phenotypes. Results of complementation tests revealed that natural variation at all candidate genes studied, invected, Fasciclin 3, toucan, Reticulon-like1, jing and CG14478, affects the studied characters, suggesting that they are Quantitative Trait Genes for morphological traits. Finally, the phenotypic patterns observed suggest that different alleles of each gene might contribute to natural variation for morphological traits. However, non-additive effects cannot be ruled out, as wild-derived strains differ at myriads of second chromosome loci that may interact epistatically with mutant alleles. PMID:27459710

A Fast Multiple-Kernel Method With Applications to Detect Gene-Environment Interaction.

PubMed

Marceau, Rachel; Lu, Wenbin; Holloway, Shannon; Sale, Michèle M; Worrall, Bradford B; Williams, Stephen R; Hsu, Fang-Chi; Tzeng, Jung-Ying

2015-09-01

Kernel machine (KM) models are a powerful tool for exploring associations between sets of genetic variants and complex traits. Although most KM methods use a single kernel function to assess the marginal effect of a variable set, KM analyses involving multiple kernels have become increasingly popular. Multikernel analysis allows researchers to study more complex problems, such as assessing gene-gene or gene-environment interactions, incorporating variance-component based methods for population substructure into rare-variant association testing, and assessing the conditional effects of a variable set adjusting for other variable sets. The KM framework is robust, powerful, and provides efficient dimension reduction for multifactor analyses, but requires the estimation of high dimensional nuisance parameters. Traditional estimation techniques, including regularization and the "expectation-maximization (EM)" algorithm, have a large computational cost and are not scalable to large sample sizes needed for rare variant analysis. Therefore, under the context of gene-environment interaction, we propose a computationally efficient and statistically rigorous "fastKM" algorithm for multikernel analysis that is based on a low-rank approximation to the nuisance effect kernel matrices. Our algorithm is applicable to various trait types (e.g., continuous, binary, and survival traits) and can be implemented using any existing single-kernel analysis software. Through extensive simulation studies, we show that our algorithm has similar performance to an EM-based KM approach for quantitative traits while running much faster. We also apply our method to the Vitamin Intervention for Stroke Prevention (VISP) clinical trial, examining gene-by-vitamin effects on recurrent stroke risk and gene-by-age effects on change in homocysteine level. © 2015 WILEY PERIODICALS, INC.

QTLomics in Soybean: A Way Forward for Translational Genomics and Breeding

PubMed Central

Kumawat, Giriraj; Gupta, Sanjay; Ratnaparkhe, Milind B.; Maranna, Shivakumar; Satpute, Gyanesh K.

2016-01-01

Food legumes play an important role in attaining both food and nutritional security along with sustainable agricultural production for the well-being of humans globally. The various traits of economic importance in legume crops are complex and quantitative in nature, which are governed by quantitative trait loci (QTLs). Mapping of quantitative traits is a tedious and costly process, however, a large number of QTLs has been mapped in soybean for various traits albeit their utilization in breeding programmes is poorly reported. For their effective use in breeding programme it is imperative to narrow down the confidence interval of QTLs, to identify the underlying genes, and most importantly allelic characterization of these genes for identifying superior variants. In the field of functional genomics, especially in the identification and characterization of gene responsible for quantitative traits, soybean is far ahead from other legume crops. The availability of genic information about quantitative traits is more significant because it is easy and effective to identify homologs than identifying shared syntenic regions in other crop species. In soybean, genes underlying QTLs have been identified and functionally characterized for phosphorous efficiency, flowering and maturity, pod dehiscence, hard-seededness, α-Tocopherol content, soybean cyst nematode, sudden death syndrome, and salt tolerance. Candidate genes have also been identified for many other quantitative traits for which functional validation is required. Using the sequence information of identified genes from soybean, comparative genomic analysis of homologs in other legume crops could discover novel structural variants and useful alleles for functional marker development. The functional markers may be very useful for molecular breeding in soybean and harnessing benefit of translational research from soybean to other leguminous crops. Thus, soybean crop can act as a model crop for translational genomics and breeding of quantitative traits in legume crops. In this review, we summarize current status of identification and characterization of genes underlying QTLs for various quantitative traits in soybean and their significance in translational genomics and breeding of other legume crops. PMID:28066449

ATG18 and FAB1 are involved in dehydration stress tolerance in Saccharomyces cerevisiae.

PubMed

López-Martínez, Gema; Margalef-Català, Mar; Salinas, Francisco; Liti, Gianni; Cordero-Otero, Ricardo

2015-01-01

Recently, different dehydration-based technologies have been evaluated for the purpose of cell and tissue preservation. Although some early results have been promising, they have not satisfied the requirements for large-scale applications. The long experience of using quantitative trait loci (QTLs) with the yeast Saccharomyces cerevisiae has proven to be a good model organism for studying the link between complex phenotypes and DNA variations. Here, we use QTL analysis as a tool for identifying the specific yeast traits involved in dehydration stress tolerance. Three hybrids obtained from stable haploids and sequenced in the Saccharomyces Genome Resequencing Project showed intermediate dehydration tolerance in most cases. The dehydration resistance trait of 96 segregants from each hybrid was quantified. A smooth, continuous distribution of the anhydrobiosis tolerance trait was found, suggesting that this trait is determined by multiple QTLs. Therefore, we carried out a QTL analysis to identify the determinants of this dehydration tolerance trait at the genomic level. Among the genes identified after reciprocal hemizygosity assays, RSM22, ATG18 and DBR1 had not been referenced in previous studies. We report new phenotypes for these genes using a previously validated test. Finally, our data illustrates the power of this approach in the investigation of the complex cell dehydration phenotype.

ATG18 and FAB1 Are Involved in Dehydration Stress Tolerance in Saccharomyces cerevisiae

PubMed Central

López-Martínez, Gema; Margalef-Català, Mar; Salinas, Francisco; Liti, Gianni; Cordero-Otero, Ricardo

2015-01-01

Recently, different dehydration-based technologies have been evaluated for the purpose of cell and tissue preservation. Although some early results have been promising, they have not satisfied the requirements for large-scale applications. The long experience of using quantitative trait loci (QTLs) with the yeast Saccharomyces cerevisiae has proven to be a good model organism for studying the link between complex phenotypes and DNA variations. Here, we use QTL analysis as a tool for identifying the specific yeast traits involved in dehydration stress tolerance. Three hybrids obtained from stable haploids and sequenced in the Saccharomyces Genome Resequencing Project showed intermediate dehydration tolerance in most cases. The dehydration resistance trait of 96 segregants from each hybrid was quantified. A smooth, continuous distribution of the anhydrobiosis tolerance trait was found, suggesting that this trait is determined by multiple QTLs. Therefore, we carried out a QTL analysis to identify the determinants of this dehydration tolerance trait at the genomic level. Among the genes identified after reciprocal hemizygosity assays, RSM22, ATG18 and DBR1 had not been referenced in previous studies. We report new phenotypes for these genes using a previously validated test. Finally, our data illustrates the power of this approach in the investigation of the complex cell dehydration phenotype. PMID:25803831

E-Index for Differentiating Complex Dynamic Traits

PubMed Central

Qi, Jiandong; Sun, Jianfeng; Wang, Jianxin

2016-01-01

While it is a daunting challenge in current biology to understand how the underlying network of genes regulates complex dynamic traits, functional mapping, a tool for mapping quantitative trait loci (QTLs) and single nucleotide polymorphisms (SNPs), has been applied in a variety of cases to tackle this challenge. Though useful and powerful, functional mapping performs well only when one or more model parameters are clearly responsible for the developmental trajectory, typically being a logistic curve. Moreover, it does not work when the curves are more complex than that, especially when they are not monotonic. To overcome this inadaptability, we therefore propose a mathematical-biological concept and measurement, E-index (earliness-index), which cumulatively measures the earliness degree to which a variable (or a dynamic trait) increases or decreases its value. Theoretical proofs and simulation studies show that E-index is more general than functional mapping and can be applied to any complex dynamic traits, including those with logistic curves and those with nonmonotonic curves. Meanwhile, E-index vector is proposed as well to capture more subtle differences of developmental patterns. PMID:27064292

Association genetics in Solanum tuberosum provides new insights into potato tuber bruising and enzymatic tissue discoloration

PubMed Central

2011-01-01

Background Most agronomic plant traits result from complex molecular networks involving multiple genes and from environmental factors. One such trait is the enzymatic discoloration of fruit and tuber tissues initiated by mechanical impact (bruising). Tuber susceptibility to bruising is a complex trait of the cultivated potato (Solanum tuberosum) that is crucial for crop quality. As phenotypic evaluation of bruising is cumbersome, the application of diagnostic molecular markers would empower the selection of low bruising potato varieties. The genetic factors and molecular networks underlying enzymatic tissue discoloration are sparsely known. Hitherto there is no association study dealing with tuber bruising and diagnostic markers for enzymatic discoloration are rare. Results The natural genetic diversity for bruising susceptibility was evaluated in elite middle European potato germplasm in order to elucidate its molecular basis. Association genetics using a candidate gene approach identified allelic variants in genes that function in tuber bruising and enzymatic browning. Two hundred and five tetraploid potato varieties and breeding clones related by descent were evaluated for two years in six environments for tuber bruising susceptibility, specific gravity, yield, shape and plant maturity. Correlations were found between different traits. In total 362 polymorphic DNA fragments, derived from 33 candidate genes and 29 SSR loci, were scored in the population and tested for association with the traits using a mixed model approach, which takes into account population structure and kinship. Twenty one highly significant (p < 0.001) and robust marker-trait associations were identified. Conclusions The observed trait correlations and associated marker fragments provide new insight in the molecular basis of bruising susceptibility and its natural variation. The markers diagnostic for increased or decreased bruising susceptibility will facilitate the combination of superior alleles in breeding programs. In addition, this study presents novel candidates that might control enzymatic tissue discoloration and tuber bruising. Their validation and characterization will increase the knowledge about the underlying biological processes. PMID:21208436

Candidate Loci for Yield-Related Traits in Maize Revealed by a Combination of MetaQTL Analysis and Regional Association Mapping

PubMed Central

Chen, Lin; An, Yixin; Li, Yong-xiang; Li, Chunhui; Shi, Yunsu; Song, Yanchun; Zhang, Dengfeng; Wang, Tianyu; Li, Yu

2017-01-01

Maize grain yield and related traits are complex and are controlled by a large number of genes of small effect or quantitative trait loci (QTL). Over the years, a large number of yield-related QTLs have been identified in maize and deposited in public databases. However, integrating and re-analyzing these data and mining candidate loci for yield-related traits has become a major issue in maize. In this study, we collected information on QTLs conferring maize yield-related traits from 33 published studies. Then, 999 of these QTLs were iteratively projected and subjected to meta-analysis to obtain metaQTLs (MQTLs). A total of 76 MQTLs were found across the maize genome. Based on a comparative genomics strategy, several maize orthologs of rice yield-related genes were identified in these MQTL regions. Furthermore, three potential candidate genes (Gene ID: GRMZM2G359974, GRMZM2G301884, and GRMZM2G083894) associated with kernel size and weight within three MQTL regions were identified using regional association mapping, based on the results of the meta-analysis. This strategy, combining MQTL analysis and regional association mapping, is helpful for functional marker development and rapid identification of candidate genes or loci. PMID:29312420

Mapping, fine mapping, and molecular dissection of quantitative trait Loci in domestic animals.

PubMed

Georges, Michel

2007-01-01

Artificial selection has created myriad breeds of domestic animals, each characterized by unique phenotypes pertaining to behavior, morphology, physiology, and disease. Most domestic animal populations share features with isolated founder populations, making them well suited for positional cloning. Genome sequences are now available for most domestic species, and with them a panoply of tools including high-density single-nucleotide polymorphism panels. As a result, domestic animal populations are becoming invaluable resources for studying the molecular architecture of complex traits and of adaptation. Here we review recent progress and issues in the positional identification of genes underlying complex traits in domestic animals. As many phenotypes studied in animals are quantitative, we focus on mapping, fine mapping, and cloning of quantitative trait loci.

The genetics of feed conversion efficiency traits in a commercial broiler line

PubMed Central

Reyer, Henry; Hawken, Rachel; Murani, Eduard; Ponsuksili, Siriluck; Wimmers, Klaus

2015-01-01

Individual feed conversion efficiency (FCE) is a major trait that influences the usage of energy resources and the ecological footprint of livestock production. The underlying biological processes of FCE are complex and are influenced by factors as diverse as climate, feed properties, gut microbiota, and individual genetic predisposition. To gain an insight to the genetic relationships with FCE traits and to contribute to the improvement of FCE in commercial chicken lines, a genome-wide association study was conducted using a commercial broiler population (n = 859) tested for FCE and weight traits during the finisher period from 39 to 46 days of age. Both single-marker (generalized linear model) and multi-marker (Bayesian approach) analyses were applied to the dataset to detect genes associated with the variability in FCE. The separate analyses revealed 22 quantitative trait loci (QTL) regions on 13 different chromosomes; the integration of both approaches resulted in 7 overlapping QTL regions. The analyses pointed to acylglycerol kinase (AGK) and general transcription factor 2-I (GTF2I) as positional and functional candidate genes. Non-synonymous polymorphisms of both candidate genes revealed evidence for a functional importance of these genes by influencing different biological aspects of FCE. PMID:26552583

KMgene: a unified R package for gene-based association analysis for complex traits.

PubMed

Yan, Qi; Fang, Zhou; Chen, Wei; Stegle, Oliver

2018-02-09

In this report, we introduce an R package KMgene for performing gene-based association tests for familial, multivariate or longitudinal traits using kernel machine (KM) regression under a generalized linear mixed model (GLMM) framework. Extensive simulations were performed to evaluate the validity of the approaches implemented in KMgene. http://cran.r-project.org/web/packages/KMgene. qi.yan@chp.edu or wei.chen@chp.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2018. Published by Oxford University Press.

Genomic Prediction for Quantitative Traits Is Improved by Mapping Variants to Gene Ontology Categories in Drosophila melanogaster

PubMed Central

Edwards, Stefan M.; Sørensen, Izel F.; Sarup, Pernille; Mackay, Trudy F. C.; Sørensen, Peter

2016-01-01

Predicting individual quantitative trait phenotypes from high-resolution genomic polymorphism data is important for personalized medicine in humans, plant and animal breeding, and adaptive evolution. However, this is difficult for populations of unrelated individuals when the number of causal variants is low relative to the total number of polymorphisms and causal variants individually have small effects on the traits. We hypothesized that mapping molecular polymorphisms to genomic features such as genes and their gene ontology categories could increase the accuracy of genomic prediction models. We developed a genomic feature best linear unbiased prediction (GFBLUP) model that implements this strategy and applied it to three quantitative traits (startle response, starvation resistance, and chill coma recovery) in the unrelated, sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel. Our results indicate that subsetting markers based on genomic features increases the predictive ability relative to the standard genomic best linear unbiased prediction (GBLUP) model. Both models use all markers, but GFBLUP allows differential weighting of the individual genetic marker relationships, whereas GBLUP weighs the genetic marker relationships equally. Simulation studies show that it is possible to further increase the accuracy of genomic prediction for complex traits using this model, provided the genomic features are enriched for causal variants. Our GFBLUP model using prior information on genomic features enriched for causal variants can increase the accuracy of genomic predictions in populations of unrelated individuals and provides a formal statistical framework for leveraging and evaluating information across multiple experimental studies to provide novel insights into the genetic architecture of complex traits. PMID:27235308

Beyond the Central Dogma: Bringing Epigenetics into the Classroom

ERIC Educational Resources Information Center

Drits-Esser, Dina; Malone, Molly; Barber, Nicola C.; Stark, Louisa A.

2014-01-01

Epigenetics is the study of how external factors and internal cellular signals can lead to changes in the packaging and processing of DNA sequences, thereby altering the expression of genes and traits. Exploring the epigenome introduces students to environmental influences on our genes and the complexities of gene expression. A supplemental…

Gene-Environment Interactions in Genome-Wide Association Studies: Current Approaches and New Directions

ERIC Educational Resources Information Center

Winham, Stacey J.; Biernacka, Joanna M.

2013-01-01

Background: Complex psychiatric traits have long been thought to be the result of a combination of genetic and environmental factors, and gene-environment interactions are thought to play a crucial role in behavioral phenotypes and the susceptibility and progression of psychiatric disorders. Candidate gene studies to investigate hypothesized…

A systems approach identifies networks and genes linking sleep and stress: implications for neuropsychiatric disorders.

PubMed

Jiang, Peng; Scarpa, Joseph R; Fitzpatrick, Karrie; Losic, Bojan; Gao, Vance D; Hao, Ke; Summa, Keith C; Yang, He S; Zhang, Bin; Allada, Ravi; Vitaterna, Martha H; Turek, Fred W; Kasarskis, Andrew

2015-05-05

Sleep dysfunction and stress susceptibility are comorbid complex traits that often precede and predispose patients to a variety of neuropsychiatric diseases. Here, we demonstrate multilevel organizations of genetic landscape, candidate genes, and molecular networks associated with 328 stress and sleep traits in a chronically stressed population of 338 (C57BL/6J × A/J) F2 mice. We constructed striatal gene co-expression networks, revealing functionally and cell-type-specific gene co-regulations important for stress and sleep. Using a composite ranking system, we identified network modules most relevant for 15 independent phenotypic categories, highlighting a mitochondria/synaptic module that links sleep and stress. The key network regulators of this module are overrepresented with genes implicated in neuropsychiatric diseases. Our work suggests that the interplay among sleep, stress, and neuropathology emerges from genetic influences on gene expression and their collective organization through complex molecular networks, providing a framework for interrogating the mechanisms underlying sleep, stress susceptibility, and related neuropsychiatric disorders. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Quantitative analysis of bristle number in Drosophila mutants identifies genes involved in neural development

NASA Technical Reports Server (NTRS)

Norga, Koenraad K.; Gurganus, Marjorie C.; Dilda, Christy L.; Yamamoto, Akihiko; Lyman, Richard F.; Patel, Prajal H.; Rubin, Gerald M.; Hoskins, Roger A.; Mackay, Trudy F.; Bellen, Hugo J.

2003-01-01

BACKGROUND: The identification of the function of all genes that contribute to specific biological processes and complex traits is one of the major challenges in the postgenomic era. One approach is to employ forward genetic screens in genetically tractable model organisms. In Drosophila melanogaster, P element-mediated insertional mutagenesis is a versatile tool for the dissection of molecular pathways, and there is an ongoing effort to tag every gene with a P element insertion. However, the vast majority of P element insertion lines are viable and fertile as homozygotes and do not exhibit obvious phenotypic defects, perhaps because of the tendency for P elements to insert 5' of transcription units. Quantitative genetic analysis of subtle effects of P element mutations that have been induced in an isogenic background may be a highly efficient method for functional genome annotation. RESULTS: Here, we have tested the efficacy of this strategy by assessing the extent to which screening for quantitative effects of P elements on sensory bristle number can identify genes affecting neural development. We find that such quantitative screens uncover an unusually large number of genes that are known to function in neural development, as well as genes with yet uncharacterized effects on neural development, and novel loci. CONCLUSIONS: Our findings establish the use of quantitative trait analysis for functional genome annotation through forward genetics. Similar analyses of quantitative effects of P element insertions will facilitate our understanding of the genes affecting many other complex traits in Drosophila.

New insights from monogenic diabetes for “common” type 2 diabetes

PubMed Central

Tallapragada, Divya Sri Priyanka; Bhaskar, Seema; Chandak, Giriraj R.

2015-01-01

Boundaries between monogenic and complex genetic diseases are becoming increasingly blurred, as a result of better understanding of phenotypes and their genetic determinants. This had a large impact on the way complex disease genetics is now being investigated. Starting with conventional approaches like familial linkage, positional cloning and candidate genes strategies, the scope of complex disease genetics has grown exponentially with scientific and technological advances in recent times. Despite identification of multiple loci harboring common and rare variants associated with complex diseases, interpreting and evaluating their functional role has proven to be difficult. Information from monogenic diseases, especially related to the intermediate traits associated with complex diseases comes handy. The significant overlap between traits and phenotypes of monogenic diseases with related complex diseases provides a platform to understand the disease biology better. In this review, we would discuss about one such complex disease, type 2 diabetes, which shares marked similarity of intermediate traits with different forms of monogenic diabetes. PMID:26300908

Differentially expressed genes during the imbibition of dormant and after-ripened seeds - a reverse genetics approach.

PubMed

Yazdanpanah, Farzaneh; Hanson, Johannes; Hilhorst, Henk W M; Bentsink, Leónie

2017-09-11

Seed dormancy, defined as the incapability of a viable seed to germinate under favourable conditions, is an important trait in nature and agriculture. Despite extensive research on dormancy and germination, many questions about the molecular mechanisms controlling these traits remain unanswered, likely due to its genetic complexity and the large environmental effects which are characteristic of these quantitative traits. To boost research towards revealing mechanisms in the control of seed dormancy and germination we depend on the identification of genes controlling those traits. We used transcriptome analysis combined with a reverse genetics approach to identify genes that are prominent for dormancy maintenance and germination in imbibed seeds of Arabidopsis thaliana. Comparative transcriptomics analysis was employed on freshly harvested (dormant) and after-ripened (AR; non-dormant) 24-h imbibed seeds of four different DELAY OF GERMINATION near isogenic lines (DOGNILs) and the Landsberg erecta (Ler) wild type with varying levels of primary dormancy. T-DNA knock-out lines of the identified genes were phenotypically investigated for their effect on dormancy and AR. We identified conserved sets of 46 and 25 genes which displayed higher expression in seeds of all dormant and all after-ripened DOGNILs and Ler, respectively. Knock-out mutants in these genes showed dormancy and germination related phenotypes. Most of the identified genes had not been implicated in seed dormancy or germination. This research will be useful to further decipher the molecular mechanisms by which these important ecological and commercial traits are regulated.

Experimenting with Spirituality: Analyzing "The God Gene" in a Nonmajors Laboratory Course

ERIC Educational Resources Information Center

Silveira, Linda A.

2008-01-01

References linking genes to complex human traits, such as personality type or disease susceptibility, abound in the news media and popular culture. In his book "The God Gene: How Faith is Hardwired into Our Genes", Dean Hamer argues that a variation in the "VMAT2" gene plays a role in one's openness to spiritual experiences. In a nonmajors class,…

Mapping in an apple (Malus x domestica) F1 segregating population based on physical clustering of differentially expressed genes.

PubMed

Jensen, Philip J; Fazio, Gennaro; Altman, Naomi; Praul, Craig; McNellis, Timothy W

2014-04-04

Apple tree breeding is slow and difficult due to long generation times, self-incompatibility, and complex genetics. The identification of molecular markers linked to traits of interest is a way to expedite the breeding process. In the present study, we aimed to identify genes whose steady-state transcript abundance was associated with inheritance of specific traits segregating in an apple (Malus × domestica) rootstock F1 breeding population, including resistance to powdery mildew (Podosphaera leucotricha) disease and woolly apple aphid (Eriosoma lanigerum). Transcription profiling was performed for 48 individual F1 apple trees from a cross of two highly heterozygous parents, using RNA isolated from healthy, actively-growing shoot tips and a custom apple DNA oligonucleotide microarray representing 26,000 unique transcripts. Genome-wide expression profiles were not clear indicators of powdery mildew or woolly apple aphid resistance phenotype. However, standard differential gene expression analysis between phenotypic groups of trees revealed relatively small sets of genes with trait-associated expression levels. For example, thirty genes were identified that were differentially expressed between trees resistant and susceptible to powdery mildew. Interestingly, the genes encoding twenty-four of these transcripts were physically clustered on chromosome 12. Similarly, seven genes were identified that were differentially expressed between trees resistant and susceptible to woolly apple aphid, and the genes encoding five of these transcripts were also clustered, this time on chromosome 17. In each case, the gene clusters were in the vicinity of previously identified major quantitative trait loci for the corresponding trait. Similar results were obtained for a series of molecular traits. Several of the differentially expressed genes were used to develop DNA polymorphism markers linked to powdery mildew disease and woolly apple aphid resistance. Gene expression profiling and trait-associated transcript analysis using an apple F1 population readily identified genes physically linked to powdery mildew disease resistance and woolly apple aphid resistance loci. This result was especially useful in apple, where extreme levels of heterozygosity make the development of reliable DNA markers quite difficult. The results suggest that this approach could prove effective in crops with complicated genetics, or for which few genomic information resources are available.

Genome wide association mapping for grain shape traits in indica rice.

PubMed

Feng, Yue; Lu, Qing; Zhai, Rongrong; Zhang, Mengchen; Xu, Qun; Yang, Yaolong; Wang, Shan; Yuan, Xiaoping; Yu, Hanyong; Wang, Yiping; Wei, Xinghua

2016-10-01

Using genome-wide association mapping, 47 SNPs within 27 significant loci were identified for four grain shape traits, and 424 candidate genes were predicted from public database. Grain shape is a key determinant of grain yield and quality in rice (Oryza sativa L.). However, our knowledge of genes controlling rice grain shape remains limited. Genome-wide association mapping based on linkage disequilibrium (LD) has recently emerged as an effective approach for identifying genes or quantitative trait loci (QTL) underlying complex traits in plants. In this study, association mapping based on 5291 single nucleotide polymorphisms (SNPs) was conducted to identify significant loci associated with grain shape traits in a global collection of 469 diverse rice accessions. A total of 47 SNPs were located in 27 significant loci for four grain traits, and explained ~44.93-65.90 % of the phenotypic variation for each trait. In total, 424 candidate genes within a 200 kb extension region (±100 kb of each locus) of these loci were predicted. Of them, the cloned genes GS3 and qSW5 showed very strong effects on grain length and grain width in our study. Comparing with previously reported QTLs for grain shape traits, we found 11 novel loci, including 3, 3, 2 and 3 loci for grain length, grain width, grain length-width ratio and thousand grain weight, respectively. Validation of these new loci would be performed in the future studies. These results revealed that besides GS3 and qSW5, multiple novel loci and mechanisms were involved in determining rice grain shape. These findings provided valuable information for understanding of the genetic control of grain shape and molecular marker assistant selection (MAS) breeding in rice.

Genetic differentiation in life history traits and thermal stress performance across a heterogeneous dune landscape in Arabidopsis lyrata.

PubMed

Wos, Guillaume; Willi, Yvonne

2018-05-26

Over very short spatial scales, the habitat of a species can differ in multiple abiotic and biotic factors. These factors may impose natural selection on several traits and can cause genetic differentiation within a population. We studied multivariate genetic differentiation in a plant species of a sand dune landscape by linking environmental variation with differences in genotypic trait values and gene expression levels to find traits and candidate genes of microgeographical adaptation. Maternal seed families of Arabidopsis lyrata were collected in Saugatuck Dunes State Park, Michigan, USA, and environmental parameters were recorded at each collection site. Offspring plants were raised in climate chambers and exposed to one of three temperature treatments: regular occurrence of frost, heat, or constant control conditions. Several traits were assessed: plant growth, time to flowering, and frost and heat resistance. The strongest trait-environment association was between a fast switch to sexual reproduction and weaker growth under frost, and growing in the open, away from trees. The second strongest association was between the trait combination of small plant size and early flowering under control conditions combined with large size under frost, and the combination of environmental conditions of growing close to trees, at low vegetation cover, on dune bottoms. Gene expression analysis by RNA-seq revealed candidate genes involved in multivariate trait differentiation. The results support the hypothesis that in natural populations, many environmental factors impose selection, and that they affect multiple traits, with the relative direction of trait change being complex. The results highlight that heterogeneity in the selection environment over small spatial scales is a main driver of the maintenance of adaptive genetic variation within populations.

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

Strategic approaches to unraveling genetic causes of cardiovascular diseases

USDA-ARS?s Scientific Manuscript database

DNA sequence variants are major components of the "causal field" for virtually all medical phenotypes, whether single gene familial disorders or complex traits without a clear familial aggregation. The causal variants in single gene disorders are necessary and sufficient to impart large effects. In ...

Novel Insights into Tree Biology and Genome Evolution as Revealed Through Genomics.

PubMed

Neale, David B; Martínez-García, Pedro J; De La Torre, Amanda R; Montanari, Sara; Wei, Xiao-Xin

2017-04-28

Reference genome sequences are the key to the discovery of genes and gene families that determine traits of interest. Recent progress in sequencing technologies has enabled a rapid increase in genome sequencing of tree species, allowing the dissection of complex characters of economic importance, such as fruit and wood quality and resistance to biotic and abiotic stresses. Although the number of reference genome sequences for trees lags behind those for other plant species, it is not too early to gain insight into the unique features that distinguish trees from nontree plants. Our review of the published data suggests that, although many gene families are conserved among herbaceous and tree species, some gene families, such as those involved in resistance to biotic and abiotic stresses and in the synthesis and transport of sugars, are often expanded in tree genomes. As the genomes of more tree species are sequenced, comparative genomics will further elucidate the complexity of tree genomes and how this relates to traits unique to trees.

An Unbiased Systems Genetics Approach to Mapping Genetic Loci Modulating Susceptibility to Severe Streptococcal Sepsis

PubMed Central

Abdeltawab, Nourtan F.; Aziz, Ramy K.; Kansal, Rita; Rowe, Sarah L.; Su, Yin; Gardner, Lidia; Brannen, Charity; Nooh, Mohammed M.; Attia, Ramy R.; Abdelsamed, Hossam A.; Taylor, William L.; Lu, Lu; Williams, Robert W.; Kotb, Malak

2008-01-01

Striking individual differences in severity of group A streptococcal (GAS) sepsis have been noted, even among patients infected with the same bacterial strain. We had provided evidence that HLA class II allelic variation contributes significantly to differences in systemic disease severity by modulating host responses to streptococcal superantigens. Inasmuch as the bacteria produce additional virulence factors that participate in the pathogenesis of this complex disease, we sought to identify additional gene networks modulating GAS sepsis. Accordingly, we applied a systems genetics approach using a panel of advanced recombinant inbred mice. By analyzing disease phenotypes in the context of mice genotypes we identified a highly significant quantitative trait locus (QTL) on Chromosome 2 between 22 and 34 Mb that strongly predicts disease severity, accounting for 25%–30% of variance. This QTL harbors several polymorphic genes known to regulate immune responses to bacterial infections. We evaluated candidate genes within this QTL using multiple parameters that included linkage, gene ontology, variation in gene expression, cocitation networks, and biological relevance, and identified interleukin1 alpha and prostaglandin E synthases pathways as key networks involved in modulating GAS sepsis severity. The association of GAS sepsis with multiple pathways underscores the complexity of traits modulating GAS sepsis and provides a powerful approach for analyzing interactive traits affecting outcomes of other infectious diseases. PMID:18421376

Gene- and pathway-based association tests for multiple traits with GWAS summary statistics.

PubMed

Kwak, Il-Youp; Pan, Wei

2017-01-01

To identify novel genetic variants associated with complex traits and to shed new insights on underlying biology, in addition to the most popular single SNP-single trait association analysis, it would be useful to explore multiple correlated (intermediate) traits at the gene- or pathway-level by mining existing single GWAS or meta-analyzed GWAS data. For this purpose, we present an adaptive gene-based test and a pathway-based test for association analysis of multiple traits with GWAS summary statistics. The proposed tests are adaptive at both the SNP- and trait-levels; that is, they account for possibly varying association patterns (e.g. signal sparsity levels) across SNPs and traits, thus maintaining high power across a wide range of situations. Furthermore, the proposed methods are general: they can be applied to mixed types of traits, and to Z-statistics or P-values as summary statistics obtained from either a single GWAS or a meta-analysis of multiple GWAS. Our numerical studies with simulated and real data demonstrated the promising performance of the proposed methods. The methods are implemented in R package aSPU, freely and publicly available at: https://cran.r-project.org/web/packages/aSPU/ CONTACT: weip@biostat.umn.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Characterization, expression profiles, intracellular distribution and association analysis of porcine PNAS-4 gene with production traits.

PubMed

Mo, Delin; Zhu, Zhengmao; te Pas, Marinus F W; Li, Xinyun; Yang, Shulin; Wang, Heng; Wang, Huanling; Li, Kui

2008-06-30

In a previous screen to identify differentially expressed genes associated with embryonic development, the porcine PNAS-4 gene had been found. Considering differentially expressed genes in early stages of muscle development are potential candidate genes to improve meat quality and production efficiency, we determined how porcine PNAS-4 gene regulates meat production. Therefore, this gene has been sequenced, expression analyzed and associated with meat production traits. We cloned the full-length cDNA of porcine PNAS-4 gene encoding a protein of 194 amino acids which was expressed in the Golgi complex. This gene was mapped to chromosome 10, q11-16, in a region of conserved synteny with human chromosome 1 where the human homologous gene was localized. Real-time PCR revealed that PNAS-4 mRNA was widely expressed with highest expression levels in skeletal muscle followed by lymph, liver and other tissues, and showed a down-regulated expression pattern during prenatal development while a up-regulated expression pattern after weaning. Association analysis revealed that allele C of SNP A1813C was prevalent in Chinese indigenous breeds whereas A was dominant allele in Landrace and Large White, and the pigs with homozygous CC had a higher fat content than those of the pigs with other genotypes (P < 0.05). Porcine PNAS-4 protein tagged with green fluorescent protein accumulated in the Golgi complex, and its mRNA showed a widespread expression across many tissues and organs in pigs. It may be an important factor affecting the meat production efficiency, because its down-regulated expression pattern during early embryogenesis suggests involvement in increase of muscle fiber number. In addition, the SNP A1813C associated with fat traits might be a genetic marker for molecular-assisted selection in animal breeding.

Impacts of Population Structure and Analytical Models in Genome-Wide Association Studies of Complex Traits in Forest Trees: A Case Study in Eucalyptus globulus

PubMed Central

Garcia, Martín N.; Acuña, Cintia; Borralho, Nuno M. G.; Grattapaglia, Dario; Marcucci Poltri, Susana N.

2013-01-01

The promise of association genetics to identify genes or genomic regions controlling complex traits has generated a flurry of interest. Such phenotype-genotype associations could be useful to accelerate tree breeding cycles, increase precision and selection intensity for late expressing, low heritability traits. However, the prospects of association genetics in highly heterozygous undomesticated forest trees can be severely impacted by the presence of cryptic population and pedigree structure. To investigate how to better account for this, we compared the GLM and five combinations of the Unified Mixed Model (UMM) on data of a low-density genome-wide association study for growth and wood property traits carried out in a Eucalyptus globulus population (n = 303) with 7,680 Diversity Array Technology (DArT) markers. Model comparisons were based on the degree of deviation from the uniform distribution and estimates of the mean square differences between the observed and expected p-values of all significant marker-trait associations detected. Our analysis revealed the presence of population and family structure. There was not a single best model for all traits. Striking differences in detection power and accuracy were observed among the different models especially when population structure was not accounted for. The UMM method was the best and produced superior results when compared to GLM for all traits. Following stringent correction for false discoveries, 18 marker-trait associations were detected, 16 for tree diameter growth and two for lignin monomer composition (S∶G ratio), a key wood property trait. The two DArT markers associated with S∶G ratio on chromosome 10, physically map within 1 Mbp of the ferulate 5-hydroxylase (F5H) gene, providing a putative independent validation of this marker-trait association. This study details the merit of collectively integrate population structure and relatedness in association analyses in undomesticated, highly heterozygous forest trees, and provides additional insights into the nature of complex quantitative traits in Eucalyptus. PMID:24282578

A genome-wide SNP scan accelerates trait-regulatory genomic loci identification in chickpea

PubMed Central

Kujur, Alice; Bajaj, Deepak; Upadhyaya, Hari D.; Das, Shouvik; Ranjan, Rajeev; Shree, Tanima; 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 identified 44844 high-quality SNPs by sequencing 92 diverse chickpea accessions belonging to a seed and pod trait-specific association panel using reference genome- and de novo-based GBS (genotyping-by-sequencing) assays. A GWAS (genome-wide association study) in an association panel of 211, including the 92 sequenced accessions, identified 22 major genomic loci showing significant association (explaining 23–47% phenotypic variation) with pod and seed number/plant and 100-seed weight. Eighteen trait-regulatory major genomic loci underlying 13 robust QTLs were validated and mapped on an intra-specific genetic linkage map by QTL mapping. A combinatorial approach of GWAS, QTL mapping and gene haplotype-specific LD mapping and transcript profiling uncovered one superior haplotype and favourable natural allelic variants in the upstream regulatory region of a CesA-type cellulose synthase (Ca_Kabuli_CesA3) gene regulating high pod and seed number/plant (explaining 47% phenotypic variation) in chickpea. The up-regulation of this superior gene haplotype correlated with increased transcript expression of Ca_Kabuli_CesA3 gene in the pollen and pod of high pod/seed number accession, resulting in higher cellulose accumulation for normal pollen and pollen tube growth. A rapid combinatorial genome-wide SNP genotyping-based approach has potential to dissect complex quantitative agronomic traits and delineate trait-regulatory genomic loci (candidate genes) for genetic enhancement in crop plants, including chickpea. PMID:26058368

Investigation of the association of two candidate genes (H-FABP and PSMC1) with growth and carcass traits in Qinchuan beef cattle from China.

PubMed

Liang, W; Zhang, H L; Liu, Y; Lu, B C; Liu, X; Li, Q; Cao, Y

2014-03-17

Growth and carcass traits are economically important quality characteristics of beef cattle and are complex quantitative traits that are controlled by multiple genes. In this study, 2 candidate genes, H-FABP (encoding the heart fatty acid-binding protein) and PSMC1 (encoding the proteasome 26S subunit of ATPase 1) were investigated in Qinchuan beef cattle of China. PCR-SSCP and DNA sequencing methods were used to detect mutations in the H-FABP and PSMC1 genes in Qinchuan cattle, and a T>C mutation in exon 1 of H-FABP and a T>C mutation in exon 9 of PSMC1 were identified. The association of these 2 single nucleotide polymorphisms with growth and carcass traits of Qinchuan cattle was analyzed. The T>C mutation in H-FABP was significantly associated with body length and dressing percentage (P < 0.05) and the T>C mutation in PSMC1 with body length and hip width (P < 0.05), indicating that both of the 2 mutations in H-FABP and PSMC1 had effects on growth and carcass traits in the Qinchuan beef cattle breed. Thus, the results of our study suggest that the H-FABP and PSMC1 gene polymorphisms could be used as genetic markers in marker-assisted selection for improving Qinchuan beef cattle.

Determination of nonlinear genetic architecture using compressed sensing.

PubMed

Ho, Chiu Man; Hsu, Stephen D H

2015-01-01

One of the fundamental problems of modern genomics is to extract the genetic architecture of a complex trait from a data set of individual genotypes and trait values. Establishing this important connection between genotype and phenotype is complicated by the large number of candidate genes, the potentially large number of causal loci, and the likely presence of some nonlinear interactions between different genes. Compressed Sensing methods obtain solutions to under-constrained systems of linear equations. These methods can be applied to the problem of determining the best model relating genotype to phenotype, and generally deliver better performance than simply regressing the phenotype against each genetic variant, one at a time. We introduce a Compressed Sensing method that can reconstruct nonlinear genetic models (i.e., including epistasis, or gene-gene interactions) from phenotype-genotype (GWAS) data. Our method uses L1-penalized regression applied to nonlinear functions of the sensing matrix. The computational and data resource requirements for our method are similar to those necessary for reconstruction of linear genetic models (or identification of gene-trait associations), assuming a condition of generalized sparsity, which limits the total number of gene-gene interactions. An example of a sparse nonlinear model is one in which a typical locus interacts with several or even many others, but only a small subset of all possible interactions exist. It seems plausible that most genetic architectures fall in this category. We give theoretical arguments suggesting that the method is nearly optimal in performance, and demonstrate its effectiveness on broad classes of nonlinear genetic models using simulated human genomes and the small amount of currently available real data. A phase transition (i.e., dramatic and qualitative change) in the behavior of the algorithm indicates when sufficient data is available for its successful application. Our results indicate that predictive models for many complex traits, including a variety of human disease susceptibilities (e.g., with additive heritability h (2)∼0.5), can be extracted from data sets comprised of n ⋆∼100s individuals, where s is the number of distinct causal variants influencing the trait. For example, given a trait controlled by ∼10 k loci, roughly a million individuals would be sufficient for application of the method.

Inferring Aggregated Functional Traits from Metagenomic Data Using Constrained Non-negative Matrix Factorization: Application to Fiber Degradation in the Human Gut Microbiota.

PubMed

Raguideau, Sébastien; Plancade, Sandra; Pons, Nicolas; Leclerc, Marion; Laroche, Béatrice

2016-12-01

Whole Genome Shotgun (WGS) metagenomics is increasingly used to study the structure and functions of complex microbial ecosystems, both from the taxonomic and functional point of view. Gene inventories of otherwise uncultured microbial communities make the direct functional profiling of microbial communities possible. The concept of community aggregated trait has been adapted from environmental and plant functional ecology to the framework of microbial ecology. Community aggregated traits are quantified from WGS data by computing the abundance of relevant marker genes. They can be used to study key processes at the ecosystem level and correlate environmental factors and ecosystem functions. In this paper we propose a novel model based approach to infer combinations of aggregated traits characterizing specific ecosystemic metabolic processes. We formulate a model of these Combined Aggregated Functional Traits (CAFTs) accounting for a hierarchical structure of genes, which are associated on microbial genomes, further linked at the ecosystem level by complex co-occurrences or interactions. The model is completed with constraints specifically designed to exploit available genomic information, in order to favor biologically relevant CAFTs. The CAFTs structure, as well as their intensity in the ecosystem, is obtained by solving a constrained Non-negative Matrix Factorization (NMF) problem. We developed a multicriteria selection procedure for the number of CAFTs. We illustrated our method on the modelling of ecosystemic functional traits of fiber degradation by the human gut microbiota. We used 1408 samples of gene abundances from several high-throughput sequencing projects and found that four CAFTs only were needed to represent the fiber degradation potential. This data reduction highlighted biologically consistent functional patterns while providing a high quality preservation of the original data. Our method is generic and can be applied to other metabolic processes in the gut or in other ecosystems.

Optimum study designs.

PubMed

Gu, C; Rao, D C

2001-01-01

Because simplistic designs will lead to prohibitively large sample sizes, the optimization of genetic study designs is critical for successfully mapping genes for complex diseases. Creative designs are necessary for detecting and amplifying the usually weak signals for complex traits. Two important outcomes of a study design--power and resolution--are implicitly tied together by the principle of uncertainty. Overemphasis on either one may lead to suboptimal designs. To achieve optimality for a particular study, therefore, practical measures such as cost-effectiveness must be used to strike a balance between power and resolution. In this light, the myriad of factors involved in study design can be checked for their effects on the ultimate outcomes, and the popular existing designs can be sorted into building blocks that may be useful for particular situations. It is hoped that imaginative construction of novel designs using such building blocks will lead to enhanced efficiency in finding genes for complex human traits.

Bioenergetic Constraints on the Evolution of Complex Life

PubMed Central

Lane, Nick

2014-01-01

All morphologically complex life on Earth, beyond the level of cyanobacteria, is eukaryotic. All eukaryotes share a common ancestor that was already a complex cell. Despite their biochemical virtuosity, prokaryotes show little tendency to evolve eukaryotic traits or large genomes. Here I argue that prokaryotes are constrained by their membrane bioenergetics, for fundamental reasons relating to the origin of life. Eukaryotes arose in a rare endosymbiosis between two prokaryotes, which broke the energetic constraints on prokaryotes and gave rise to mitochondria. Loss of almost all mitochondrial genes produced an extreme genomic asymmetry, in which tiny mitochondrial genomes support, energetically, a massive nuclear genome, giving eukaryotes three to five orders of magnitude more energy per gene than prokaryotes. The requirement for endosymbiosis radically altered selection on eukaryotes, potentially explaining the evolution of unique traits, including the nucleus, sex, two sexes, speciation, and aging. PMID:24789818

Association mapping of grain color, phenolic content, flavonoid content and antioxidant capacity in dehulled rice.

PubMed

Shao, Yafang; Jin, Liang; Zhang, Gan; Lu, Yan; Shen, Yun; Bao, Jinsong

2011-03-01

Phytochemicals such as phenolics and flavonoids in rice grain are antioxidants that are associated with reduced risk of developing chronic diseases including cardiovascular disease, type-2 diabetes and some cancers. Understanding the genetic basis of these traits is necessary for the improvement of nutritional quality by breeding. Association mapping based on linkage disequilibrium has emerged as a powerful strategy for identifying genes or quantitative trait loci (QTL) underlying complex traits in plants. In this study, genome-wide association mapping using models controlling both population structure (Q) and relative kinship (K) were performed to identify the marker loci/QTLs underlying the naturally occurring variations of grain color and nutritional quality traits in 416 rice germplasm accessions including red and black rice. A total of 41 marker loci were identified for all the traits, and it was confirmed that Ra (i.e., Prp-b for purple pericarp) and Rc (brown pericarp and seed coat) genes were main-effect loci for rice grain color and nutritional quality traits. RM228, RM339, fgr (fragrance gene) and RM316 were important markers associated with most of the traits. Association mapping for the traits of the 361 white or non-pigmented rice accessions (i.e., excluding the red and black rice) revealed a total of 11 markers for four color parameters, and one marker (RM346) for phenolic content. Among them, Wx gene locus was identified for the color parameters of lightness (L*), redness (a*) and hue angle (H (o)). Our study suggested that the markers identified in this study can feasibly be used to improve nutritional quality or health benefit properties of rice by marker-assisted selection if the co-segregations of the marker-trait associations are validated in segregating populations.

Quantitative genetic analysis of agronomic and morphological traits in sorghum, Sorghum bicolor

PubMed Central

Mohammed, Riyazaddin; Are, Ashok K.; Bhavanasi, Ramaiah; Munghate, Rajendra S.; Kavi Kishor, Polavarapu B.; Sharma, Hari C.

2015-01-01

The productivity in sorghum is low, owing to various biotic and abiotic constraints. Combining insect resistance with desirable agronomic and morphological traits is important to increase sorghum productivity. Therefore, it is important to understand the variability for various agronomic traits, their heritabilities and nature of gene action to develop appropriate strategies for crop improvement. Therefore, a full diallel set of 10 parents and their 90 crosses including reciprocals were evaluated in replicated trials during the 2013–14 rainy and postrainy seasons. The crosses between the parents with early- and late-flowering flowered early, indicating dominance of earliness for anthesis in the test material used. Association between the shoot fly resistance, morphological, and agronomic traits suggested complex interactions between shoot fly resistance and morphological traits. Significance of the mean sum of squares for GCA (general combining ability) and SCA (specific combining ability) of all the studied traits suggested the importance of both additive and non-additive components in inheritance of these traits. The GCA/SCA, and the predictability ratios indicated predominance of additive gene effects for majority of the traits studied. High broad-sense and narrow-sense heritability estimates were observed for most of the morphological and agronomic traits. The significance of reciprocal combining ability effects for days to 50% flowering, plant height and 100 seed weight, suggested maternal effects for inheritance of these traits. Plant height and grain yield across seasons, days to 50% flowering, inflorescence exsertion, and panicle shape in the postrainy season showed greater specific combining ability variance, indicating the predominance of non-additive type of gene action/epistatic interactions in controlling the expression of these traits. Additive gene action in the rainy season, and dominance in the postrainy season for days to 50% flowering and plant height suggested G X E interactions for these traits. PMID:26579183

Estimating genetic effects and quantifying missing heritability explained by identified rare-variant associations.

PubMed

Liu, Dajiang J; Leal, Suzanne M

2012-10-05

Next-generation sequencing has led to many complex-trait rare-variant (RV) association studies. Although single-variant association analysis can be performed, it is grossly underpowered. Therefore, researchers have developed many RV association tests that aggregate multiple variant sites across a genetic region (e.g., gene), and test for the association between the trait and the aggregated genotype. After these aggregate tests detect an association, it is only possible to estimate the average genetic effect for a group of RVs. As a result of the "winner's curse," such an estimate can be biased. Although for common variants one can obtain unbiased estimates of genetic parameters by analyzing a replication sample, for RVs it is desirable to obtain unbiased genetic estimates for the study where the association is identified. This is because there can be substantial heterogeneity of RV sites and frequencies even among closely related populations. In order to obtain an unbiased estimate for aggregated RV analysis, we developed bootstrap-sample-split algorithms to reduce the bias of the winner's curse. The unbiased estimates are greatly important for understanding the population-specific contribution of RVs to the heritability of complex traits. We also demonstrate both theoretically and via simulations that for aggregate RV analysis the genetic variance for a gene or region will always be underestimated, sometimes substantially, because of the presence of noncausal variants or because of the presence of causal variants with effects of different magnitudes or directions. Therefore, even if RVs play a major role in the complex-trait etiologies, a portion of the heritability will remain missing, and the contribution of RVs to the complex-trait etiologies will be underestimated. Copyright © 2012 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Systems Biology for Smart Crops and Agricultural Innovation: Filling the Gaps between Genotype and Phenotype for Complex Traits Linked with Robust Agricultural Productivity and Sustainability

PubMed Central

Pathak, Rajesh Kumar; Gupta, Sanjay Mohan; Gaur, Vikram Singh; Pandey, Dinesh

2015-01-01

Abstract In recent years, rapid developments in several omics platforms and next generation sequencing technology have generated a huge amount of biological data about plants. Systems biology aims to develop and use well-organized and efficient algorithms, data structure, visualization, and communication tools for the integration of these biological data with the goal of computational modeling and simulation. It studies crop plant systems by systematically perturbing them, checking the gene, protein, and informational pathway responses; integrating these data; and finally, formulating mathematical models that describe the structure of system and its response to individual perturbations. Consequently, systems biology approaches, such as integrative and predictive ones, hold immense potential in understanding of molecular mechanism of agriculturally important complex traits linked to agricultural productivity. This has led to identification of some key genes and proteins involved in networks of pathways involved in input use efficiency, biotic and abiotic stress resistance, photosynthesis efficiency, root, stem and leaf architecture, and nutrient mobilization. The developments in the above fields have made it possible to design smart crops with superior agronomic traits through genetic manipulation of key candidate genes. PMID:26484978

Dissection of Host Susceptibility to Bacterial Infections and Its Toxins.

PubMed

Nashef, Aysar; Agbaria, Mahmoud; Shusterman, Ariel; Lorè, Nicola Ivan; Bragonzi, Alessandra; Wiess, Ervin; Houri-Haddad, Yael; Iraqi, Fuad A

2017-01-01

Infection is one of the leading causes of human mortality and morbidity. Exposure to microbial agents is obviously required. However, also non-microbial environmental and host factors play a key role in the onset, development and outcome of infectious disease, resulting in large of clinical variability between individuals in a population infected with the same microbe. Controlled and standardized investigations of the genetics of susceptibility to infectious disease are almost impossible to perform in humans whereas mouse models allow application of powerful genomic techniques to identify and validate causative genes underlying human diseases with complex etiologies. Most of current animal models used in complex traits diseases genetic mapping have limited genetic diversity. This limitation impedes the ability to create incorporated network using genetic interactions, epigenetics, environmental factors, microbiota, and other phenotypes. A novel mouse genetic reference population for high-resolution mapping and subsequently identifying genes underlying the QTL, namely the Collaborative Cross (CC) mouse genetic reference population (GRP) was recently developed. In this chapter, we discuss a variety of approaches using CC mice for mapping genes underlying quantitative trait loci (QTL) to dissect the host response to polygenic traits, including infectious disease caused by bacterial agents and its toxins.

Identification and reproducibility of diagnostic DNA markers for tuber starch and yield optimization in a novel association mapping population of potato (Solanum tuberosum L.).

PubMed

Schönhals, E M; Ortega, F; Barandalla, L; Aragones, A; Ruiz de Galarreta, J I; Liao, J-C; Sanetomo, R; Walkemeier, B; Tacke, E; Ritter, E; Gebhardt, C

2016-04-01

SNPs in candidate genes Pain - 1, InvCD141 (invertases), SSIV (starch synthase), StCDF1 (transcription factor), LapN (leucine aminopeptidase), and cytoplasm type are associated with potato tuber yield, starch content and/or starch yield. Tuber yield (TY), starch content (TSC), and starch yield (TSY) are complex characters of high importance for the potato crop in general and for industrial starch production in particular. DNA markers associated with superior alleles of genes that control the natural variation of TY, TSC, and TSY could increase precision and speed of breeding new cultivars optimized for potato starch production. Diagnostic DNA markers are identified by association mapping in populations of tetraploid potato varieties and advanced breeding clones. A novel association mapping population of 282 genotypes including varieties, breeding clones and Andean landraces was assembled and field evaluated in Northern Spain for TY, TSC, TSY, tuber number (TN) and tuber weight (TW). The landraces had lower mean values of TY, TW, TN, and TSY. The population was genotyped for 183 microsatellite alleles, 221 single nucleotide polymorphisms (SNPs) in fourteen candidate genes and eight known diagnostic markers for TSC and TSY. Association test statistics including kinship and population structure reproduced five known marker-trait associations of candidate genes and discovered new ones, particularly for tuber yield and starch yield. The inclusion of landraces increased the number of detected marker-trait associations. Integration of the present association mapping results with previous QTL linkage mapping studies for TY, TSC, TSY, TW, TN, and tuberization revealed some hot spots of QTL for these traits in the potato genome. The genomic positions of markers linked or associated with QTL for complex tuber traits suggest high multiplicity and genome wide distribution of the underlying genes.

The Allusion of the Gene: Misunderstandings of the Concepts Heredity and Gene

NASA Astrophysics Data System (ADS)

Falk, Raphael

2014-02-01

Life sciences became Biology, a formal scientific discipline, at the turn of the nineteenth century, when it adopted the methods of reductive physics and chemistry. Mendel's hypothesis of inheritance of discrete factors further introduced a quantitative reductionist dimension into biology. In 1910 Johannsen differentiated between the phenotype, which defines traits, and their genotype, the hereditary essence of such traits and their entities—the genes. The efforts to characterize these entities culminated in 1953, in Watson-Crick's physico-chemical double helix model of DNA, the hereditary matter. However, the more molecular biology advanced the less real were its entities: Genes became generic units of heredity. The increasing role of science in society, and the mutual interdependence of the two on each other augmented the urge of the public at large to find in science icons of authority; the generic nature of the gene concept allowed scientists to offer it as the bait, even though advances in research made it clear that a distinction must be maintained between advances in reductive methodologies and the progress of systems' conceptions. Genes out of context are meaningless. There are no "genes for" a trait: even if a specific change in a site on the DNA sequence may end in a conspicuous change in a trait, it must be realized that many sites in the DNA, in the cell, and in the organism as a complex integrated system in its environment, determine or rather, condition traits. The role of science is asking questions by putting up hypotheses and suggesting methods of testing them rather than in providing definite answers.

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

Physical mapping of QTL for tuber yield, starch content and starch yield in tetraploid potato (Solanum tuberosum L.) by means of genome wide genotyping by sequencing and the 8.3 K SolCAP SNP array.

PubMed

Schönhals, Elske Maria; Ding, Jia; Ritter, Enrique; Paulo, Maria João; Cara, Nicolás; Tacke, Ekhard; Hofferbert, Hans-Reinhard; Lübeck, Jens; Strahwald, Josef; Gebhardt, Christiane

2017-08-22

Tuber yield and starch content of the cultivated potato are complex traits of decisive importance for breeding improved varieties. Natural variation of tuber yield and starch content depends on the environment and on multiple, mostly unknown genetic factors. Dissection and molecular identification of the genes and their natural allelic variants controlling these complex traits will lead to the development of diagnostic DNA-based markers, by which precision and efficiency of selection can be increased (precision breeding). Three case-control populations were assembled from tetraploid potato cultivars based on maximizing the differences between high and low tuber yield (TY), starch content (TSC) and starch yield (TSY, arithmetic product of TY and TSC). The case-control populations were genotyped by restriction-site associated DNA sequencing (RADseq) and the 8.3 k SolCAP SNP genotyping array. The allele frequencies of single nucleotide polymorphisms (SNPs) were compared between cases and controls. RADseq identified, depending on data filtering criteria, between 6664 and 450 genes with one or more differential SNPs for one, two or all three traits. Differential SNPs in 275 genes were detected using the SolCAP array. A genome wide association study using the SolCAP array on an independent, unselected population identified SNPs associated with tuber starch content in 117 genes. Physical mapping of the genes containing differential or associated SNPs, and comparisons between the two genome wide genotyping methods and two different populations identified genome segments on all twelve potato chromosomes harboring one or more quantitative trait loci (QTL) for TY, TSC and TSY. Several hundred genes control tuber yield and starch content in potato. They are unequally distributed on all potato chromosomes, forming clusters between 0.5-4 Mbp width. The largest fraction of these genes had unknown function, followed by genes with putative signalling and regulatory functions. The genetic control of tuber yield and starch content is interlinked. Most differential SNPs affecting both traits had antagonistic effects: The allele increasing TY decreased TSC and vice versa. Exceptions were 89 SNP alleles which had synergistic effects on TY, TSC and TSY. These and the corresponding genes are primary targets for developing diagnostic markers.

Digital Quantification of Human Eye Color Highlights Genetic Association of Three New Loci

PubMed Central

Liu, Fan; Wollstein, Andreas; Hysi, Pirro G.; Ankra-Badu, Georgina A.; Spector, Timothy D.; Park, Daniel; Zhu, Gu; Larsson, Mats; Duffy, David L.; Montgomery, Grant W.; Mackey, David A.; Walsh, Susan; Lao, Oscar; Hofman, Albert; Rivadeneira, Fernando; Vingerling, Johannes R.; Uitterlinden, André G.; Martin, Nicholas G.; Hammond, Christopher J.; Kayser, Manfred

2010-01-01

Previous studies have successfully identified genetic variants in several genes associated with human iris (eye) color; however, they all used simplified categorical trait information. Here, we quantified continuous eye color variation into hue and saturation values using high-resolution digital full-eye photographs and conducted a genome-wide association study on 5,951 Dutch Europeans from the Rotterdam Study. Three new regions, 1q42.3, 17q25.3, and 21q22.13, were highlighted meeting the criterion for genome-wide statistically significant association. The latter two loci were replicated in 2,261 individuals from the UK and in 1,282 from Australia. The LYST gene at 1q42.3 and the DSCR9 gene at 21q22.13 serve as promising functional candidates. A model for predicting quantitative eye colors explained over 50% of trait variance in the Rotterdam Study. Over all our data exemplify that fine phenotyping is a useful strategy for finding genes involved in human complex traits. PMID:20463881

Contrasting Transcriptional Programs Control Postharvest Development of Apples (Malus x domestica Borkh.) Submitted to Cold Storage and Ethylene Blockage.

PubMed

Storch, Tatiane Timm; Finatto, Taciane; Bruneau, Maryline; Orsel-Baldwin, Mathilde; Renou, Jean-Pierre; Rombaldi, Cesar Valmor; Quecini, Vera; Laurens, François; Girardi, César Luis

2017-09-06

Apple is commercially important worldwide. Favorable genomic contexts and postharvest technologies allow year-round availability. Although ripening is considered a unidirectional developmental process toward senescence, storage at low temperatures, alone or in combination with ethylene blockage, is effective in preserving apple properties. Quality traits and genome wide expression were integrated to investigate the mechanisms underlying postharvest changes. Development and conservation techniques were responsible for transcriptional reprogramming and distinct programs associated with quality traits. A large portion of the differentially regulated genes constitutes a program involved in ripening and senescence, whereas a smaller module consists of genes associated with reestablishment and maintenance of juvenile traits after harvest. Ethylene inhibition was associated with a reversal of ripening by transcriptional induction of anabolic pathways. Our results demonstrate that the blockage of ethylene perception and signaling leads to upregulation of genes in anabolic pathways. We also associated complex phenotypes to subsets of differentially regulated genes.

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm.

PubMed

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene x gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene x gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms.

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm

PubMed Central

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene × gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene × gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms. PMID:18466570

Quantitative trait locus mapping of drought and salt tolerance in as introgressed recombinant inbred line population of upland cotton under the greenhouse and feild conditions

USDA-ARS?s Scientific Manuscript database

Drought and salt tolerances are complex traits and controlled by multiple genes, environmental factors and their interactions. Drought and salt stresses can result in more than 50% yield loss in Upland cotton (Gossypium hirsutum L.). G. barbadense L. (the source of Pima cotton) carries desirable tra...

Comparative analysis of transcriptome in two wheat genotypes with contrasting levels of drought tolerance

USDA-ARS?s Scientific Manuscript database

Drought tolerance is a complex trait that is governed by multiple genes. To identify the potential candidate genes, comparative analysis of drought stress-responsive transcriptome between drought-tolerant (Triticum aestivum Cv. C306) and drought-sensitive (Triticum aestivum Cv. WL711) genotypes was ...

Quantitative trait loci mapping and gene network analysis implicate protocadherin-15 as a determinant of brain serotonin transporter expression.

PubMed

Ye, R; Carneiro, A M D; Han, Q; Airey, D; Sanders-Bush, E; Zhang, B; Lu, L; Williams, R; Blakely, R D

2014-03-01

Presynaptic serotonin (5-hydroxytryptamine, 5-HT) transporters (SERT) regulate 5-HT signaling via antidepressant-sensitive clearance of released neurotransmitter. Polymorphisms in the human SERT gene (SLC6A4) have been linked to risk for multiple neuropsychiatric disorders, including depression, obsessive-compulsive disorder and autism. Using BXD recombinant inbred mice, a genetic reference population that can support the discovery of novel determinants of complex traits, merging collective trait assessments with bioinformatics approaches, we examine phenotypic and molecular networks associated with SERT gene and protein expression. Correlational analyses revealed a network of genes that significantly associated with SERT mRNA levels. We quantified SERT protein expression levels and identified region- and gender-specific quantitative trait loci (QTLs), one of which associated with male midbrain SERT protein expression, centered on the protocadherin-15 gene (Pcdh15), overlapped with a QTL for midbrain 5-HT levels. Pcdh15 was also the only QTL-associated gene whose midbrain mRNA expression significantly associated with both SERT protein and 5-HT traits, suggesting an unrecognized role of the cell adhesion protein in the development or function of 5-HT neurons. To test this hypothesis, we assessed SERT protein and 5-HT traits in the Pcdh15 functional null line (Pcdh15(av-) (3J) ), studies that revealed a strong, negative influence of Pcdh15 on these phenotypes. Together, our findings illustrate the power of multidimensional profiling of recombinant inbred lines in the analysis of molecular networks that support synaptic signaling, and that, as in the case of Pcdh15, can reveal novel relationships that may underlie risk for mental illness. © 2014 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Variants in TTC25 affect autistic trait in patients with autism spectrum disorder and general population.

PubMed

Vojinovic, Dina; Brison, Nathalie; Ahmad, Shahzad; Noens, Ilse; Pappa, Irene; Karssen, Lennart C; Tiemeier, Henning; van Duijn, Cornelia M; Peeters, Hilde; Amin, Najaf

2017-08-01

Autism spectrum disorder (ASD) is a highly heritable neurodevelopmental disorder with a complex genetic architecture. To identify genetic variants underlying ASD, we performed single-variant and gene-based genome-wide association studies using a dense genotyping array containing over 2.3 million single-nucleotide variants in a discovery sample of 160 families with at least one child affected with non-syndromic ASD using a binary (ASD yes/no) phenotype and a quantitative autistic trait. Replication of the top findings was performed in Psychiatric Genomics Consortium and Erasmus Rucphen Family (ERF) cohort study. Significant association of quantitative autistic trait was observed with the TTC25 gene at 17q21.2 (effect size=10.2, P-value=3.4 × 10 -7 ) in the gene-based analysis. The gene also showed nominally significant association in the cohort-based ERF study (effect=1.75, P-value=0.05). Meta-analysis of discovery and replication improved the association signal (P-value meta =1.5 × 10 -8 ). No genome-wide significant signal was observed in the single-variant analysis of either the binary ASD phenotype or the quantitative autistic trait. Our study has identified a novel gene TTC25 to be associated with quantitative autistic trait in patients with ASD. The replication of association in a cohort-based study and the effect estimate suggest that variants in TTC25 may also be relevant for broader ASD phenotype in the general population. TTC25 is overexpressed in frontal cortex and testis and is known to be involved in cilium movement and thus an interesting candidate gene for autistic trait.

The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease.

PubMed

Astle, William J; Elding, Heather; Jiang, Tao; Allen, Dave; Ruklisa, Dace; Mann, Alice L; Mead, Daniel; Bouman, Heleen; Riveros-Mckay, Fernando; Kostadima, Myrto A; Lambourne, John J; Sivapalaratnam, Suthesh; Downes, Kate; Kundu, Kousik; Bomba, Lorenzo; Berentsen, Kim; Bradley, John R; Daugherty, Louise C; Delaneau, Olivier; Freson, Kathleen; Garner, Stephen F; Grassi, Luigi; Guerrero, Jose; Haimel, Matthias; Janssen-Megens, Eva M; Kaan, Anita; Kamat, Mihir; Kim, Bowon; Mandoli, Amit; Marchini, Jonathan; Martens, Joost H A; Meacham, Stuart; Megy, Karyn; O'Connell, Jared; Petersen, Romina; Sharifi, Nilofar; Sheard, Simon M; Staley, James R; Tuna, Salih; van der Ent, Martijn; Walter, Klaudia; Wang, Shuang-Yin; Wheeler, Eleanor; Wilder, Steven P; Iotchkova, Valentina; Moore, Carmel; Sambrook, Jennifer; Stunnenberg, Hendrik G; Di Angelantonio, Emanuele; Kaptoge, Stephen; Kuijpers, Taco W; Carrillo-de-Santa-Pau, Enrique; Juan, David; Rico, Daniel; Valencia, Alfonso; Chen, Lu; Ge, Bing; Vasquez, Louella; Kwan, Tony; Garrido-Martín, Diego; Watt, Stephen; Yang, Ying; Guigo, Roderic; Beck, Stephan; Paul, Dirk S; Pastinen, Tomi; Bujold, David; Bourque, Guillaume; Frontini, Mattia; Danesh, John; Roberts, David J; Ouwehand, Willem H; Butterworth, Adam S; Soranzo, Nicole

2016-11-17

Many common variants have been associated with hematological traits, but identification of causal genes and pathways has proven challenging. We performed a genome-wide association analysis in the UK Biobank and INTERVAL studies, testing 29.5 million genetic variants for association with 36 red cell, white cell, and platelet properties in 173,480 European-ancestry participants. This effort yielded hundreds of low frequency (<5%) and rare (<1%) variants with a strong impact on blood cell phenotypes. Our data highlight general properties of the allelic architecture of complex traits, including the proportion of the heritable component of each blood trait explained by the polygenic signal across different genome regulatory domains. Finally, through Mendelian randomization, we provide evidence of shared genetic pathways linking blood cell indices with complex pathologies, including autoimmune diseases, schizophrenia, and coronary heart disease and evidence suggesting previously reported population associations between blood cell indices and cardiovascular disease may be non-causal. Copyright © 2016 Elsevier Inc. All rights reserved.

A Simple Test Identifies Selection on Complex Traits.

PubMed

Beissinger, Tim; Kruppa, Jochen; Cavero, David; Ha, Ngoc-Thuy; Erbe, Malena; Simianer, Henner

2018-05-01

Important traits in agricultural, natural, and human populations are increasingly being shown to be under the control of many genes that individually contribute only a small proportion of genetic variation. However, the majority of modern tools in quantitative and population genetics, including genome-wide association studies and selection-mapping protocols, are designed to identify individual genes with large effects. We have developed an approach to identify traits that have been under selection and are controlled by large numbers of loci. In contrast to existing methods, our technique uses additive-effects estimates from all available markers, and relates these estimates to allele-frequency change over time. Using this information, we generate a composite statistic, denoted [Formula: see text] which can be used to test for significant evidence of selection on a trait. Our test requires pre- and postselection genotypic data but only a single time point with phenotypic information. Simulations demonstrate that [Formula: see text] is powerful for identifying selection, particularly in situations where the trait being tested is controlled by many genes, which is precisely the scenario where classical approaches for selection mapping are least powerful. We apply this test to breeding populations of maize and chickens, where we demonstrate the successful identification of selection on traits that are documented to have been under selection. Copyright © 2018 Beissinger et al.

Complex Genetics of Behavior: BXDs in the Automated Home-Cage.

PubMed

Loos, Maarten; Verhage, Matthijs; Spijker, Sabine; Smit, August B

2017-01-01

This chapter describes a use case for the genetic dissection and automated analysis of complex behavioral traits using the genetically diverse panel of BXD mouse recombinant inbred strains. Strains of the BXD resource differ widely in terms of gene and protein expression in the brain, as well as in their behavioral repertoire. A large mouse resource opens the possibility for gene finding studies underlying distinct behavioral phenotypes, however, such a resource poses a challenge in behavioral phenotyping. To address the specifics of large-scale screening we describe how to investigate: (1) how to assess mouse behavior systematically in addressing a large genetic cohort, (2) how to dissect automation-derived longitudinal mouse behavior into quantitative parameters, and (3) how to map these quantitative traits to the genome, deriving loci underlying aspects of behavior.

Gene expression allelic imbalance in ovine brown adipose tissue impacts energy homeostasis

PubMed Central

Ghazanfar, Shila; Vuocolo, Tony; Morrison, Janna L.; Nicholas, Lisa M.; McMillen, Isabella C.; Yang, Jean Y. H.; Buckley, Michael J.

2017-01-01

Heritable trait variation within a population of organisms is largely governed by DNA variations that impact gene transcription and protein function. Identifying genetic variants that affect complex functional traits is a primary aim of population genetics studies, especially in the context of human disease and agricultural production traits. The identification of alleles directly altering mRNA expression and thereby biological function is challenging due to difficulty in isolating direct effects of cis-acting genetic variations from indirect trans-acting genetic effects. Allele specific gene expression or allelic imbalance in gene expression (AI) occurring at heterozygous loci provides an opportunity to identify genes directly impacted by cis-acting genetic variants as indirect trans-acting effects equally impact the expression of both alleles. However, the identification of genes showing AI in the context of the expression of all genes remains a challenge due to a variety of technical and statistical issues. The current study focuses on the discovery of genes showing AI using single nucleotide polymorphisms as allelic reporters. By developing a computational and statistical process that addressed multiple analytical challenges, we ranked 5,809 genes for evidence of AI using RNA-Seq data derived from brown adipose tissue samples from a cohort of late gestation fetal lambs and then identified a conservative subgroup of 1,293 genes. Thus, AI was extensive, representing approximately 25% of the tested genes. Genes associated with AI were enriched for multiple Gene Ontology (GO) terms relating to lipid metabolism, mitochondrial function and the extracellular matrix. These functions suggest that cis-acting genetic variations causing AI in the population are preferentially impacting genes involved in energy homeostasis and tissue remodelling. These functions may contribute to production traits likely to be under genetic selection in the population. PMID:28665992

Commentary: Fundamental problems with candidate gene-by-environment interaction studies - reflections on Moore and Thoemmes (2016).

PubMed

Border, Richard; Keller, Matthew C

2017-03-01

Moore and Thoemmes elaborate on one particular source of difficulty in the study of candidate gene-by-environment interactions (cG × E): how different biologically plausible configurations of gene-environment covariation can bias estimates of cG × E when not explicitly modeled. However, even if cG × E investigators were able to account for the sources of bias Moore and Thoemmes elaborate, it is unlikely that conventional approaches would yield reliable results. Published cG × E findings to date have generally employed inadequate analytic procedures, have relied on samples orders of magnitude too small to detect plausible effects, and have relied on a particular candidate gene approach that has been unfruitful and largely jettisoned in mainstream genetic analyses of complex traits. Analytic procedures for the study of gene-environment interplay must evolve to meet the challenges that the genetic architecture of complex traits presents, and investigators must collaborate on grander scales if we hope to begin to understand how specific genes and environments combine to affect behavior. © 2017 Association for Child and Adolescent Mental Health.

DNA mismatch repair gene MSH6 implicated in determining age at natural menopause

PubMed Central

Perry, John R.B.; Hsu, Yi-Hsiang; Chasman, Daniel I.; Johnson, Andrew D.; Elks, Cathy; Albrecht, Eva; Andrulis, Irene L.; Beesley, Jonathan; Berenson, Gerald S.; Bergmann, Sven; Bojesen, Stig E.; Bolla, Manjeet K.; Brown, Judith; Buring, Julie E.; Campbell, Harry; Chang-Claude, Jenny; Chenevix-Trench, Georgia; Corre, Tanguy; Couch, Fergus J.; Cox, Angela; Czene, Kamila; D'adamo, Adamo Pio; Davies, Gail; Deary, Ian J.; Dennis, Joe; Easton, Douglas F.; Engelhardt, Ellen G.; Eriksson, Johan G.; Esko, Tõnu; Fasching, Peter A.; Figueroa, Jonine D.; Flyger, Henrik; Fraser, Abigail; Garcia-Closas, Montse; Gasparini, Paolo; Gieger, Christian; Giles, Graham; Guenel, Pascal; Hägg, Sara; Hall, Per; Hayward, Caroline; Hopper, John; Ingelsson, Erik; Kardia, Sharon L.R.; Kasiman, Katherine; Knight, Julia A.; Lahti, Jari; Lawlor, Debbie A.; Magnusson, Patrik K.E.; Margolin, Sara; Marsh, Julie A.; Metspalu, Andres; Olson, Janet E.; Pennell, Craig E.; Polasek, Ozren; Rahman, Iffat; Ridker, Paul M.; Robino, Antonietta; Rudan, Igor; Rudolph, Anja; Salumets, Andres; Schmidt, Marjanka K.; Schoemaker, Minouk J.; Smith, Erin N.; Smith, Jennifer A.; Southey, Melissa; Stöckl, Doris; Swerdlow, Anthony J.; Thompson, Deborah J.; Truong, Therese; Ulivi, Sheila; Waldenberger, Melanie; Wang, Qin; Wild, Sarah; Wilson, James F; Wright, Alan F.; Zgaga, Lina; Ong, Ken K.; Murabito, Joanne M.; Karasik, David; Murray, Anna

2014-01-01

The length of female reproductive lifespan is associated with multiple adverse outcomes, including breast cancer, cardiovascular disease and infertility. The biological processes that govern the timing of the beginning and end of reproductive life are not well understood. Genetic variants are known to contribute to ∼50% of the variation in both age at menarche and menopause, but to date the known genes explain <15% of the genetic component. We have used genome-wide association in a bivariate meta-analysis of both traits to identify genes involved in determining reproductive lifespan. We observed significant genetic correlation between the two traits using genome-wide complex trait analysis. However, we found no robust statistical evidence for individual variants with an effect on both traits. A novel association with age at menopause was detected for a variant rs1800932 in the mismatch repair gene MSH6 (P = 1.9 × 10−9), which was also associated with altered expression levels of MSH6 mRNA in multiple tissues. This study contributes to the growing evidence that DNA repair processes play a key role in ovarian ageing and could be an important therapeutic target for infertility. PMID:24357391

Association weight matrix for the genetic dissection of puberty in beef cattle.

PubMed

Fortes, Marina R S; Reverter, Antonio; Zhang, Yuandan; Collis, Eliza; Nagaraj, Shivashankar H; Jonsson, Nick N; Prayaga, Kishore C; Barris, Wes; Hawken, Rachel J

2010-08-03

We describe a systems biology approach for the genetic dissection of complex traits based on applying gene network theory to the results from genome-wide associations. The associations of single-nucleotide polymorphisms (SNP) that were individually associated with a primary phenotype of interest, age at puberty in our study, were explored across 22 related traits. Genomic regions were surveyed for genes harboring the selected SNP. As a result, an association weight matrix (AWM) was constructed with as many rows as genes and as many columns as traits. Each {i, j} cell value in the AWM corresponds to the z-score normalized additive effect of the ith gene (via its neighboring SNP) on the jth trait. Columnwise, the AWM recovered the genetic correlations estimated via pedigree-based restricted maximum-likelihood methods. Rowwise, a combination of hierarchical clustering, gene network, and pathway analyses identified genetic drivers that would have been missed by standard genome-wide association studies. Finally, the promoter regions of the AWM-predicted targets of three key transcription factors (TFs), estrogen-related receptor gamma (ESRRG), Pal3 motif, bound by a PPAR-gamma homodimer, IR3 sites (PPARG), and Prophet of Pit 1, PROP paired-like homeobox 1 (PROP1), were surveyed to identify binding sites corresponding to those TFs. Applied to our case, the AWM results recapitulate the known biology of puberty, captured experimentally validated binding sites, and identified candidate genes and gene-gene interactions for further investigation.

Improved resolution in the position of drought-related QTLs in a single mapping population of rice by meta-analysis

PubMed Central

Khowaja, Farkhanda S; Norton, Gareth J; Courtois, Brigitte; Price, Adam H

2009-01-01

Background Meta-analysis of QTLs combines the results of several QTL detection studies and provides narrow confidence intervals for meta-QTLs, permitting easier positional candidate gene identification. It is usually applied to multiple mapping populations, but can be applied to one. Here, a meta-analysis of drought related QTLs in the Bala × Azucena mapping population compiles data from 13 experiments and 25 independent screens providing 1,650 individual QTLs separated into 5 trait categories; drought avoidance, plant height, plant biomass, leaf morphology and root traits. A heat map of the overlapping 1 LOD confidence intervals provides an overview of the distribution of QTLs. The programme BioMercator is then used to conduct a formal meta-analysis at example QTL clusters to illustrate the value of meta-analysis of QTLs in this population. Results The heat map graphically illustrates the genetic complexity of drought related traits in rice. QTLs can be linked to their physical position on the rice genome using Additional file 1 provided. Formal meta-analysis on chromosome 1, where clusters of QTLs for all trait categories appear close, established that the sd1 semi-dwarfing gene coincided with a plant height meta-QTL, that the drought avoidance meta-QTL was not likely to be associated with this gene, and that this meta-QTL was not pleiotropic with close meta-QTLs for leaf morphology and root traits. On chromosome 5, evidence suggests that a drought avoidance meta-QTL was pleiotropic with leaf morphology and plant biomass meta-QTLs, but not with meta-QTLs for root traits and plant height 10 cM lower down. A region of dense root QTL activity graphically visible on chromosome 9 was dissected into three meta-QTLs within a space of 35 cM. The confidence intervals for meta-QTLs obtained ranged from 5.1 to 14.5 cM with an average of 9.4 cM, which is approximately 180 genes in rice. Conclusion The meta-analysis is valuable in providing improved ability to dissect the complex genetic structure of traits, and distinguish between pleiotropy and close linkage. It also provides relatively small target regions for the identification of positional candidate genes. PMID:19545420

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.

Transient Hypermutagenesis Accelerates the Evolution of Legume Endosymbionts following Horizontal Gene Transfer

PubMed Central

Remigi, Philippe; Capela, Delphine; Clerissi, Camille; Tasse, Léna; Torchet, Rachel; Bouchez, Olivier; Batut, Jacques; Cruveiller, Stéphane; Rocha, Eduardo P. C.; Masson-Boivin, Catherine

2014-01-01

Horizontal gene transfer (HGT) is an important mode of adaptation and diversification of prokaryotes and eukaryotes and a major event underlying the emergence of bacterial pathogens and mutualists. Yet it remains unclear how complex phenotypic traits such as the ability to fix nitrogen with legumes have successfully spread over large phylogenetic distances. Here we show, using experimental evolution coupled with whole genome sequencing, that co-transfer of imuABC error-prone DNA polymerase genes with key symbiotic genes accelerates the evolution of a soil bacterium into a legume symbiont. Following introduction of the symbiotic plasmid of Cupriavidus taiwanensis, the Mimosa symbiont, into pathogenic Ralstonia solanacearum we challenged transconjugants to become Mimosa symbionts through serial plant-bacteria co-cultures. We demonstrate that a mutagenesis imuABC cassette encoded on the C. taiwanensis symbiotic plasmid triggered a transient hypermutability stage in R. solanacearum transconjugants that occurred before the cells entered the plant. The generated burst in genetic diversity accelerated symbiotic adaptation of the recipient genome under plant selection pressure, presumably by improving the exploration of the fitness landscape. Finally, we show that plasmid imuABC cassettes are over-represented in rhizobial lineages harboring symbiotic plasmids. Our findings shed light on a mechanism that may have facilitated the dissemination of symbiotic competency among α- and β-proteobacteria in natura and provide evidence for the positive role of environment-induced mutagenesis in the acquisition of a complex lifestyle trait. We speculate that co-transfer of complex phenotypic traits with mutagenesis determinants might frequently enhance the ecological success of HGT. PMID:25181317

Mapping in an apple (Malus x domestica) F1 segregating population based on physical clustering of differentially expressed genes

PubMed Central

2014-01-01

Background Apple tree breeding is slow and difficult due to long generation times, self-incompatibility, and complex genetics. The identification of molecular markers linked to traits of interest is a way to expedite the breeding process. In the present study, we aimed to identify genes whose steady-state transcript abundance was associated with inheritance of specific traits segregating in an apple (Malus × domestica) rootstock F1 breeding population, including resistance to powdery mildew (Podosphaera leucotricha) disease and woolly apple aphid (Eriosoma lanigerum). Results Transcription profiling was performed for 48 individual F1 apple trees from a cross of two highly heterozygous parents, using RNA isolated from healthy, actively-growing shoot tips and a custom apple DNA oligonucleotide microarray representing 26,000 unique transcripts. Genome-wide expression profiles were not clear indicators of powdery mildew or woolly apple aphid resistance phenotype. However, standard differential gene expression analysis between phenotypic groups of trees revealed relatively small sets of genes with trait-associated expression levels. For example, thirty genes were identified that were differentially expressed between trees resistant and susceptible to powdery mildew. Interestingly, the genes encoding twenty-four of these transcripts were physically clustered on chromosome 12. Similarly, seven genes were identified that were differentially expressed between trees resistant and susceptible to woolly apple aphid, and the genes encoding five of these transcripts were also clustered, this time on chromosome 17. In each case, the gene clusters were in the vicinity of previously identified major quantitative trait loci for the corresponding trait. Similar results were obtained for a series of molecular traits. Several of the differentially expressed genes were used to develop DNA polymorphism markers linked to powdery mildew disease and woolly apple aphid resistance. Conclusions Gene expression profiling and trait-associated transcript analysis using an apple F1 population readily identified genes physically linked to powdery mildew disease resistance and woolly apple aphid resistance loci. This result was especially useful in apple, where extreme levels of heterozygosity make the development of reliable DNA markers quite difficult. The results suggest that this approach could prove effective in crops with complicated genetics, or for which few genomic information resources are available. PMID:24708064

A power set-based statistical selection procedure to locate susceptible rare variants associated with complex traits with sequencing data.

PubMed

Sun, Hokeun; Wang, Shuang

2014-08-15

Existing association methods for rare variants from sequencing data have focused on aggregating variants in a gene or a genetic region because of the fact that analysing individual rare variants is underpowered. However, these existing rare variant detection methods are not able to identify which rare variants in a gene or a genetic region of all variants are associated with the complex diseases or traits. Once phenotypic associations of a gene or a genetic region are identified, the natural next step in the association study with sequencing data is to locate the susceptible rare variants within the gene or the genetic region. In this article, we propose a power set-based statistical selection procedure that is able to identify the locations of the potentially susceptible rare variants within a disease-related gene or a genetic region. The selection performance of the proposed selection procedure was evaluated through simulation studies, where we demonstrated the feasibility and superior power over several comparable existing methods. In particular, the proposed method is able to handle the mixed effects when both risk and protective variants are present in a gene or a genetic region. The proposed selection procedure was also applied to the sequence data on the ANGPTL gene family from the Dallas Heart Study to identify potentially susceptible rare variants within the trait-related genes. An R package 'rvsel' can be downloaded from http://www.columbia.edu/∼sw2206/ and http://statsun.pusan.ac.kr. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

The Birth of a Black Rice Gene and Its Local Spread by Introgression

PubMed Central

Oikawa, Tetsuo; Maeda, Hiroaki; Oguchi, Taichi; Yamaguchi, Takuya; Tanabe, Noriko; Ebana, Kaworu; Yano, Masahiro; Izawa, Takeshi

2015-01-01

The origin and spread of novel agronomic traits during crop domestication are complex events in plant evolution. Wild rice (Oryza rufipogon) has red grains due to the accumulation of proanthocyanidins, whereas most cultivated rice (Oryza sativa) varieties have white grains induced by a defective allele in the Rc basic helix-loop-helix (bHLH) gene. Although the events surrounding the origin and spread of black rice traits remain unknown, varieties with black grains due to anthocyanin accumulation are distributed in various locations throughout Asia. Here, we show that the black grain trait originated from ectopic expression of the Kala4 bHLH gene due to rearrangement in the promoter region. Both the Rc and Kala4 genes activate upstream flavonol biosynthesis genes, such as chalcone synthase and dihydroflavonol-4-reductase, and downstream genes, such as leucoanthocyanidin reductase and leucoanthocyanidin dioxygenase, to produce the respective specific pigments. Genome analysis of 21 black rice varieties as well as red- and white-grained landraces demonstrated that black rice arose in tropical japonica and its subsequent spread to the indica subspecies can be attributed to the causal alleles of Kala4. The relatively small size of genomic fragments of tropical japonica origin in some indica varieties indicates that refined introgression must have occurred by natural crossbreeding in the course of evolution of the black trait in rice. PMID:26362607

The Birth of a Black Rice Gene and Its Local Spread by Introgression.

PubMed

Oikawa, Tetsuo; Maeda, Hiroaki; Oguchi, Taichi; Yamaguchi, Takuya; Tanabe, Noriko; Ebana, Kaworu; Yano, Masahiro; Ebitani, Takeshi; Izawa, Takeshi

2015-09-01

The origin and spread of novel agronomic traits during crop domestication are complex events in plant evolution. Wild rice (Oryza rufipogon) has red grains due to the accumulation of proanthocyanidins, whereas most cultivated rice (Oryza sativa) varieties have white grains induced by a defective allele in the Rc basic helix-loop-helix (bHLH) gene. Although the events surrounding the origin and spread of black rice traits remain unknown, varieties with black grains due to anthocyanin accumulation are distributed in various locations throughout Asia. Here, we show that the black grain trait originated from ectopic expression of the Kala4 bHLH gene due to rearrangement in the promoter region. Both the Rc and Kala4 genes activate upstream flavonol biosynthesis genes, such as chalcone synthase and dihydroflavonol-4-reductase, and downstream genes, such as leucoanthocyanidin reductase and leucoanthocyanidin dioxygenase, to produce the respective specific pigments. Genome analysis of 21 black rice varieties as well as red- and white-grained landraces demonstrated that black rice arose in tropical japonica and its subsequent spread to the indica subspecies can be attributed to the causal alleles of Kala4. The relatively small size of genomic fragments of tropical japonica origin in some indica varieties indicates that refined introgression must have occurred by natural crossbreeding in the course of evolution of the black trait in rice. © 2015 American Society of Plant Biologists. All rights reserved.

Exploiting Differential Gene Expression and Epistasis to Discover Candidate Genes for Drought-Associated QTLs in Arabidopsis thaliana.

PubMed

Lovell, John T; Mullen, Jack L; Lowry, David B; Awole, Kedija; Richards, James H; Sen, Saunak; Verslues, Paul E; Juenger, Thomas E; McKay, John K

2015-04-01

Soil water availability represents one of the most important selective agents for plants in nature and the single greatest abiotic determinant of agricultural productivity, yet the genetic bases of drought acclimation responses remain poorly understood. Here, we developed a systems-genetic approach to characterize quantitative trait loci (QTLs), physiological traits and genes that affect responses to soil moisture deficit in the TSUxKAS mapping population of Arabidopsis thaliana. To determine the effects of candidate genes underlying QTLs, we analyzed gene expression as a covariate within the QTL model in an effort to mechanistically link markers, RNA expression, and the phenotype. This strategy produced ranked lists of candidate genes for several drought-associated traits, including water use efficiency, growth, abscisic acid concentration (ABA), and proline concentration. As a proof of concept, we recovered known causal loci for several QTLs. For other traits, including ABA, we identified novel loci not previously associated with drought. Furthermore, we documented natural variation at two key steps in proline metabolism and demonstrated that the mitochondrial genome differentially affects genomic QTLs to influence proline accumulation. These findings demonstrate that linking genome, transcriptome, and phenotype data holds great promise to extend the utility of genetic mapping, even when QTL effects are modest or complex. © 2015 American Society of Plant Biologists. All rights reserved.

Genetic Architecture of a Hormonal Response to Gene Knockdown in Honey Bees

PubMed Central

Rueppell, Olav; Huang, Zachary Y.; Wang, Ying; Fondrk, M. Kim; Page, Robert E.; Amdam, Gro V.

2015-01-01

Variation in endocrine signaling is proposed to underlie the evolution and regulation of social life histories, but the genetic architecture of endocrine signaling is still poorly understood. An excellent example of a hormonally influenced set of social traits is found in the honey bee (Apis mellifera): a dynamic and mutually suppressive relationship between juvenile hormone (JH) and the yolk precursor protein vitellogenin (Vg) regulates behavioral maturation and foraging of workers. Several other traits cosegregate with these behavioral phenotypes, comprising the pollen hoarding syndrome (PHS) one of the best-described animal behavioral syndromes. Genotype differences in responsiveness of JH to Vg are a potential mechanistic basis for the PHS. Here, we reduced Vg expression via RNA interference in progeny from a backcross between 2 selected lines of honey bees that differ in JH responsiveness to Vg reduction and measured JH response and ovary size, which represents another key aspect of the PHS. Genetic mapping based on restriction site-associated DNA tag sequencing identified suggestive quantitative trait loci (QTL) for ovary size and JH responsiveness. We confirmed genetic effects on both traits near many QTL that had been identified previously for their effect on various PHS traits. Thus, our results support a role for endocrine control of complex traits at a genetic level. Furthermore, this first example of a genetic map of a hormonal response to gene knockdown in a social insect helps to refine the genetic understanding of complex behaviors and the physiology that may underlie behavioral control in general. PMID:25596612

Statistical epistasis between candidate gene alleles for complex tuber traits in an association mapping population of tetraploid potato

PubMed Central

Li, Li; Paulo, Maria-João; van Eeuwijk, Fred

2010-01-01

Association mapping using DNA-based markers is a novel tool in plant genetics for the analysis of complex traits. Potato tuber yield, starch content, starch yield and chip color are complex traits of agronomic relevance, for which carbohydrate metabolism plays an important role. At the functional level, the genes and biochemical pathways involved in carbohydrate metabolism are among the best studied in plants. Quantitative traits such as tuber starch and sugar content are therefore models for association genetics in potato based on candidate genes. In an association mapping experiment conducted with a population of 243 tetraploid potato varieties and breeding clones, we previously identified associations between individual candidate gene alleles and tuber starch content, starch yield and chip quality. In the present paper, we tested 190 DNA markers at 36 loci scored in the same association mapping population for pairwise statistical epistatic interactions. Fifty marker pairs were associated mainly with tuber starch content and/or starch yield, at a cut-off value of q ≤ 0.20 for the experiment-wide false discovery rate (FDR). Thirteen marker pairs had an FDR of q ≤ 0.10. Alleles at loci encoding ribulose-bisphosphate carboxylase/oxygenase activase (Rca), sucrose phosphate synthase (Sps) and vacuolar invertase (Pain1) were most frequently involved in statistical epistatic interactions. The largest effect on tuber starch content and starch yield was observed for the paired alleles Pain1-8c and Rca-1a, explaining 9 and 10% of the total variance, respectively. The combination of these two alleles increased the means of tuber starch content and starch yield. Biological models to explain the observed statistical epistatic interactions are discussed. Electronic supplementary material The online version of this article (doi:10.1007/s00122-010-1389-3) contains supplementary material, which is available to authorized users. PMID:20603706

Genome biogeography reveals the intraspecific spread of adaptive mutations for a complex trait.

PubMed

Olofsson, Jill K; Bianconi, Matheus; Besnard, Guillaume; Dunning, Luke T; Lundgren, Marjorie R; Holota, Helene; Vorontsova, Maria S; Hidalgo, Oriane; Leitch, Ilia J; Nosil, Patrik; Osborne, Colin P; Christin, Pascal-Antoine

2016-12-01

Physiological novelties are often studied at macro-evolutionary scales such that their micro-evolutionary origins remain poorly understood. Here, we test the hypothesis that key components of a complex trait can evolve in isolation and later be combined by gene flow. We use C 4 photosynthesis as a study system, a derived physiology that increases plant productivity in warm, dry conditions. The grass Alloteropsis semialata includes C 4 and non-C 4 genotypes, with some populations using laterally acquired C 4 -adaptive loci, providing an outstanding system to track the spread of novel adaptive mutations. Using genome data from C 4 and non-C 4 A. semialata individuals spanning the species' range, we infer and date past migrations of different parts of the genome. Our results show that photosynthetic types initially diverged in isolated populations, where key C 4 components were acquired. However, rare but recurrent subsequent gene flow allowed the spread of adaptive loci across genetic pools. Indeed, laterally acquired genes for key C 4 functions were rapidly passed between populations with otherwise distinct genomic backgrounds. Thus, our intraspecific study of C 4 -related genomic variation indicates that components of adaptive traits can evolve separately and later be combined through secondary gene flow, leading to the assembly and optimization of evolutionary innovations. © 2016 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

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.

Sensory trait variation in an echolocating bat suggests roles for both selection and plasticity

PubMed Central

2014-01-01

Background Across heterogeneous environments selection and gene flow interact to influence the rate and extent of adaptive trait evolution. This complex relationship is further influenced by the rarely considered role of phenotypic plasticity in the evolution of adaptive population variation. Plasticity can be adaptive if it promotes colonization and survival in novel environments and in doing so may increase the potential for future population differentiation via selection. Gene flow between selectively divergent environments may favour the evolution of phenotypic plasticity or conversely, plasticity itself may promote gene flow, leading to a pattern of trait differentiation in the presence of gene flow. Variation in sensory traits is particularly informative in testing the role of environment in trait and population differentiation. Here we test the hypothesis of ‘adaptive differentiation with minimal gene flow’ in resting echolocation frequencies (RF) of Cape horseshoe bats (Rhinolophus capensis) across a gradient of increasingly cluttered habitats. Results Our analysis reveals a geographically structured pattern of increasing RF from open to highly cluttered habitats in R. capensis; however genetic drift appears to be a minor player in the processes influencing this pattern. Although Bayesian analysis of population structure uncovered a number of spatially defined mitochondrial groups and coalescent methods revealed regional-scale gene flow, phylogenetic analysis of mitochondrial sequences did not correlate with RF differentiation. Instead, habitat discontinuities between biomes, and not genetic and geographic distances, best explained echolocation variation in this species. We argue that both selection for increased detection distance in relatively less cluttered habitats and adaptive phenotypic plasticity may have influenced the evolution of matched echolocation frequencies and habitats across different populations. Conclusions Our study reveals significant sensory trait differentiation in the presence of historical gene flow and suggests roles for both selection and plasticity in the evolution of echolocation variation in R. capensis. These results highlight the importance of population level analyses to i) illuminate the subtle interplay between selection, plasticity and gene flow in the evolution of adaptive traits and ii) demonstrate that evolutionary processes may act simultaneously and that their relative influence may vary across different environments. PMID:24674227

Sensory trait variation in an echolocating bat suggests roles for both selection and plasticity.

PubMed

Odendaal, Lizelle J; Jacobs, David S; Bishop, Jacqueline M

2014-03-27

Across heterogeneous environments selection and gene flow interact to influence the rate and extent of adaptive trait evolution. This complex relationship is further influenced by the rarely considered role of phenotypic plasticity in the evolution of adaptive population variation. Plasticity can be adaptive if it promotes colonization and survival in novel environments and in doing so may increase the potential for future population differentiation via selection. Gene flow between selectively divergent environments may favour the evolution of phenotypic plasticity or conversely, plasticity itself may promote gene flow, leading to a pattern of trait differentiation in the presence of gene flow. Variation in sensory traits is particularly informative in testing the role of environment in trait and population differentiation. Here we test the hypothesis of 'adaptive differentiation with minimal gene flow' in resting echolocation frequencies (RF) of Cape horseshoe bats (Rhinolophus capensis) across a gradient of increasingly cluttered habitats. Our analysis reveals a geographically structured pattern of increasing RF from open to highly cluttered habitats in R. capensis; however genetic drift appears to be a minor player in the processes influencing this pattern. Although Bayesian analysis of population structure uncovered a number of spatially defined mitochondrial groups and coalescent methods revealed regional-scale gene flow, phylogenetic analysis of mitochondrial sequences did not correlate with RF differentiation. Instead, habitat discontinuities between biomes, and not genetic and geographic distances, best explained echolocation variation in this species. We argue that both selection for increased detection distance in relatively less cluttered habitats and adaptive phenotypic plasticity may have influenced the evolution of matched echolocation frequencies and habitats across different populations. Our study reveals significant sensory trait differentiation in the presence of historical gene flow and suggests roles for both selection and plasticity in the evolution of echolocation variation in R. capensis. These results highlight the importance of population level analyses to i) illuminate the subtle interplay between selection, plasticity and gene flow in the evolution of adaptive traits and ii) demonstrate that evolutionary processes may act simultaneously and that their relative influence may vary across different environments.

Identification of rhizome-specific genes by genome-wide differential expression analysis in Oryza longistaminata.

PubMed

Hu, Fengyi; Wang, Di; Zhao, Xiuqin; Zhang, Ting; Sun, Haixi; Zhu, Linghua; Zhang, Fan; Li, Lijuan; Li, Qiong; Tao, Dayun; Fu, Binying; Li, Zhikang

2011-01-24

Rhizomatousness is a key component of perenniality of many grasses that contribute to competitiveness and invasiveness of many noxious grass weeds, but can potentially be used to develop perennial cereal crops for sustainable farmers in hilly areas of tropical Asia. Oryza longistaminata, a perennial wild rice with strong rhizomes, has been used as the model species for genetic and molecular dissection of rhizome development and in breeding efforts to transfer rhizome-related traits into annual rice species. In this study, an effort was taken to get insights into the genes and molecular mechanisms underlying the rhizomatous trait in O. longistaminata by comparative analysis of the genome-wide tissue-specific gene expression patterns of five different tissues of O. longistaminata using the Affymetrix GeneChip Rice Genome Array. A total of 2,566 tissue-specific genes were identified in five different tissues of O. longistaminata, including 58 and 61 unique genes that were specifically expressed in the rhizome tips (RT) and internodes (RI), respectively. In addition, 162 genes were up-regulated and 261 genes were down-regulated in RT compared to the shoot tips. Six distinct cis-regulatory elements (CGACG, GCCGCC, GAGAC, AACGG, CATGCA, and TAAAG) were found to be significantly more abundant in the promoter regions of genes differentially expressed in RT than in the promoter regions of genes uniformly expressed in all other tissues. Many of the RT and/or RI specifically or differentially expressed genes were located in the QTL regions associated with rhizome expression, rhizome abundance and rhizome growth-related traits in O. longistaminata and thus are good candidate genes for these QTLs. The initiation and development of the rhizomatous trait in O. longistaminata are controlled by very complex gene networks involving several plant hormones and regulatory genes, different members of gene families showing tissue specificity and their regulated pathways. Auxin/IAA appears to act as a negative regulator in rhizome development, while GA acts as the activator in rhizome development. Co-localization of the genes specifically expressed in rhizome tips and rhizome internodes with the QTLs for rhizome traits identified a large set of candidate genes for rhizome initiation and development in rice for further confirmation.

Genome-wide association studies dissect the genetic networks underlying agronomical traits in soybean.

PubMed

Fang, Chao; Ma, Yanming; Wu, Shiwen; Liu, Zhi; Wang, Zheng; Yang, Rui; Hu, Guanghui; Zhou, Zhengkui; Yu, Hong; Zhang, Min; Pan, Yi; Zhou, Guoan; Ren, Haixiang; Du, Weiguang; Yan, Hongrui; Wang, Yanping; Han, Dezhi; Shen, Yanting; Liu, Shulin; Liu, Tengfei; Zhang, Jixiang; Qin, Hao; Yuan, Jia; Yuan, Xiaohui; Kong, Fanjiang; Liu, Baohui; Li, Jiayang; Zhang, Zhiwu; Wang, Guodong; Zhu, Baoge; Tian, Zhixi

2017-08-24

Soybean (Glycine max [L.] Merr.) is one of the most important oil and protein crops. Ever-increasing soybean consumption necessitates the improvement of varieties for more efficient production. However, both correlations among different traits and genetic interactions among genes that affect a single trait pose a challenge to soybean breeding. To understand the genetic networks underlying phenotypic correlations, we collected 809 soybean accessions worldwide and phenotyped them for two years at three locations for 84 agronomic traits. Genome-wide association studies identified 245 significant genetic loci, among which 95 genetically interacted with other loci. We determined that 14 oil synthesis-related genes are responsible for fatty acid accumulation in soybean and function in line with an additive model. Network analyses demonstrated that 51 traits could be linked through the linkage disequilibrium of 115 associated loci and these links reflect phenotypic correlations. We revealed that 23 loci, including the known Dt1, E2, E1, Ln, Dt2, Fan, and Fap loci, as well as 16 undefined associated loci, have pleiotropic effects on different traits. This study provides insights into the genetic correlation among complex traits and will facilitate future soybean functional studies and breeding through molecular design.

Genetic Variation in the MAPK/ERK Pathway Affects Contact Hypersensitivity Responses.

PubMed

Legrand, Julien M D; Roy, Edwige; Baz, Batoul; Mukhopadhyay, Pamela; Wong, Ho Yi; Ram, Ramesh; Morahan, Grant; Walker, Graeme; Khosrotehrani, Kiarash

2018-05-10

Using a genetic resource that enables rapid mapping of genes for complex traits, we demonstrate dramatic diversity between murine strains in response to immune challenge. We identified several candidate genes that point to the MAPK/ERK pathway as a key modulator of this process. Copyright © 2018. Published by Elsevier Inc.

Comprehensive Genome-wide Screen for Genes with Cis-acting Regulatory Elements That Respond to Marek's Disease Virus Infection

USDA-ARS?s Scientific Manuscript database

The comprehensive identification of genes underlying phenotypic variation of complex traits such as disease resistance remains one of the greatest challenges in biology despite having genome sequences and more powerful tools. Most genome-wide screens lack sufficient resolving power as they typically...

Ovar-DRB1 haplotypes *2001 and *0301 are associated with sheep growth and ewe lifetime prolificacy

USDA-ARS?s Scientific Manuscript database

Background: The major histocompatibility complex (MHC) is an organized cluster of tightly linked vertebrate genes with immunological and non-immunological functions. While the important MHC gene DRB1 has been examined in regard to many sheep infectious disease traits, only one study, based on micros...

Association weight matrix for the genetic dissection of puberty in beef cattle

PubMed Central

Fortes, Marina R. S.; Reverter, Antonio; Zhang, Yuandan; Collis, Eliza; Nagaraj, Shivashankar H.; Jonsson, Nick N.; Prayaga, Kishore C.; Barris, Wes; Hawken, Rachel J.

2010-01-01

We describe a systems biology approach for the genetic dissection of complex traits based on applying gene network theory to the results from genome-wide associations. The associations of single-nucleotide polymorphisms (SNP) that were individually associated with a primary phenotype of interest, age at puberty in our study, were explored across 22 related traits. Genomic regions were surveyed for genes harboring the selected SNP. As a result, an association weight matrix (AWM) was constructed with as many rows as genes and as many columns as traits. Each {i, j} cell value in the AWM corresponds to the z-score normalized additive effect of the ith gene (via its neighboring SNP) on the jth trait. Columnwise, the AWM recovered the genetic correlations estimated via pedigree-based restricted maximum-likelihood methods. Rowwise, a combination of hierarchical clustering, gene network, and pathway analyses identified genetic drivers that would have been missed by standard genome-wide association studies. Finally, the promoter regions of the AWM-predicted targets of three key transcription factors (TFs), estrogen-related receptor γ (ESRRG), Pal3 motif, bound by a PPAR-γ homodimer, IR3 sites (PPARG), and Prophet of Pit 1, PROP paired-like homeobox 1 (PROP1), were surveyed to identify binding sites corresponding to those TFs. Applied to our case, the AWM results recapitulate the known biology of puberty, captured experimentally validated binding sites, and identified candidate genes and gene–gene interactions for further investigation. PMID:20643938

An integrated approach of comparative genomics and heritability analysis of pig and human on obesity trait: evidence for candidate genes on human chromosome 2.

PubMed

Kim, Jaemin; Lee, Taeheon; Kim, Tae-Hun; Lee, Kyung-Tai; Kim, Heebal

2012-12-19

Traditional candidate gene approach has been widely used for the study of complex diseases including obesity. However, this approach is largely limited by its dependence on existing knowledge of presumed biology of the phenotype under investigation. Our combined strategy of comparative genomics and chromosomal heritability estimate analysis of obesity traits, subscapular skinfold thickness and back-fat thickness in Korean cohorts and pig (Sus scrofa), may overcome the limitations of candidate gene analysis and allow us to better understand genetic predisposition to human obesity. We found common genes including FTO, the fat mass and obesity associated gene, identified from significant SNPs by association studies of each trait. These common genes were related to blood pressure and arterial stiffness (P = 1.65E-05) and type 2 diabetes (P = 0.00578). Through the estimation of variance of genetic component (heritability) for each chromosome by SNPs, we observed a significant positive correlation (r = 0.479) between genetic contributions of human and pig to obesity traits. Furthermore, we noted that human chromosome 2 (syntenic to pig chromosomes 3 and 15) was most important in explaining the phenotypic variance for obesity. Obesity genetics still awaits further discovery. Navigating syntenic regions suggests obesity candidate genes on chromosome 2 that are previously known to be associated with obesity-related diseases: MRPL33, PARD3B, ERBB4, STK39, and ZNF385B.

Identification and Validation of Loci Governing Seed Coat Color by Combining Association Mapping and Bulk Segregation Analysis in Soybean

PubMed Central

Ma, Yansong; Tian, Long; Li, Xinxiu; Li, Ying-Hui; Guan, Rongxia; Guo, Yong; Qiu, Li-Juan

2016-01-01

Soybean seed coat exists in a range of colors from yellow, green, brown, black, to bicolor. Classical genetic analysis suggested that soybean seed color was a moderately complex trait controlled by multi-loci. However, only a couple of loci could be detected using a single biparental segregating population. In this study, a combination of association mapping and bulk segregation analysis was employed to identify genes/loci governing this trait in soybean. A total of 14 loci, including nine novel and five previously reported ones, were identified using 176,065 coding SNPs selected from entire SNP dataset among 56 soybean accessions. Four of these loci were confirmed and further mapped using a biparental population developed from the cross between ZP95-5383 (yellow seed color) and NY279 (brown seed color), in which different seed coat colors were further dissected into simple trait pairs (green/yellow, green/black, green/brown, yellow/black, yellow/brown, and black/brown) by continuously developing residual heterozygous lines. By genotyping entire F2 population using flanking markers located in fine-mapping regions, the genetic basis of seed coat color was fully dissected and these four loci could explain all variations of seed colors in this population. These findings will be useful for map-based cloning of genes as well as marker-assisted breeding in soybean. This work also provides an alternative strategy for systematically isolating genes controlling relative complex trait by association analysis followed by biparental mapping. PMID:27404272

Functional Gene Discovery and Characterization of Genes and Alleles Affecting Wood Biomass Yield and Quality in Populus

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

Busov, Victor

Adoption of biofuels as economically and environmentally viable alternative to fossil fuels would require development of specialized bioenergy varieties. A major goal in the breeding of such varieties is the improvement of lignocellulosic biomass yield and quality. These are complex traits and understanding the underpinning molecular mechanism can assist and accelerate their improvement. This is particularly important for tree bioenergy crops like poplars (species and hybrids from the genus Populus), for which breeding progress is extremely slow due to long generation cycles. A variety of approaches have been already undertaken to better understand the molecular bases of biomass yield andmore » quality in poplar. An obvious void in these undertakings has been the application of mutagenesis. Mutagenesis has been instrumental in the discovery and characterization of many plant traits including such that affect biomass yield and quality. In this proposal we use activation tagging to discover genes that can significantly affect biomass associated traits directly in poplar, a premier bioenergy crop. We screened a population of 5,000 independent poplar activation tagging lines under greenhouse conditions for a battery of biomass yield traits. These same plants were then analyzed for changes in wood chemistry using pyMBMS. As a result of these screens we have identified nearly 800 mutants, which are significantly (P<0.05) different when compared to wild type. Of these majority (~700) are affected in one of ten different biomass yield traits and 100 in biomass quality traits (e.g., lignin, S/G ration and C6/C5 sugars). We successfully recovered the position of the tag in approximately 130 lines, showed activation in nearly half of them and performed recapitulation experiments with 20 genes prioritized by the significance of the phenotype. Recapitulation experiments are still ongoing for many of the genes but the results are encouraging. For example, we have shown successful recapitulation for a fascilin-like gene that when overexpressed increase many biomass-yield associated traits. Genes discovered through activation tagging showed polymorphisms in P. trichocarpa association mapping population linked to the traits modified by the activation tagging. This suggests that putative alleles that are associated with improvement of the trait o interest can be discovered and used in marker associated selection. This will significantly simplify and accelerate the breeding efforts.« less

CNV discovery for milk composition traits in dairy cattle using whole genome resequencing.

PubMed

Gao, Yahui; Jiang, Jianping; Yang, Shaohua; Hou, Yali; Liu, George E; Zhang, Shengli; Zhang, Qin; Sun, Dongxiao

2017-03-29

Copy number variations (CNVs) are important and widely distributed in the genome. CNV detection opens a new avenue for exploring genes associated with complex traits in humans, animals and plants. Herein, we present a genome-wide assessment of CNVs that are potentially associated with milk composition traits in dairy cattle. In this study, CNVs were detected based on whole genome re-sequencing data of eight Holstein bulls from four half- and/or full-sib families, with extremely high and low estimated breeding values (EBVs) of milk protein percentage and fat percentage. The range of coverage depth per individual was 8.2-11.9×. Using CNVnator, we identified a total of 14,821 CNVs, including 5025 duplications and 9796 deletions. Among them, 487 differential CNV regions (CNVRs) comprising ~8.23 Mb of the cattle genome were observed between the high and low groups. Annotation of these differential CNVRs were performed based on the cattle genome reference assembly (UMD3.1) and totally 235 functional genes were found within the CNVRs. By Gene Ontology and KEGG pathway analyses, we found that genes were significantly enriched for specific biological functions related to protein and lipid metabolism, insulin/IGF pathway-protein kinase B signaling cascade, prolactin signaling pathway and AMPK signaling pathways. These genes included INS, IGF2, FOXO3, TH, SCD5, GALNT18, GALNT16, ART3, SNCA and WNT7A, implying their potential association with milk protein and fat traits. In addition, 95 CNVRs were overlapped with 75 known QTLs that are associated with milk protein and fat traits of dairy cattle (Cattle QTLdb). In conclusion, based on NGS of 8 Holstein bulls with extremely high and low EBVs for milk PP and FP, we identified a total of 14,821 CNVs, 487 differential CNVRs between groups, and 10 genes, which were suggested as promising candidate genes for milk protein and fat traits.

An integration of genome-wide association study and gene expression profiling to prioritize the discovery of novel susceptibility Loci for osteoporosis-related traits.

PubMed

Hsu, Yi-Hsiang; Zillikens, M Carola; Wilson, Scott G; Farber, Charles R; Demissie, Serkalem; Soranzo, Nicole; Bianchi, Estelle N; Grundberg, Elin; Liang, Liming; Richards, J Brent; Estrada, Karol; Zhou, Yanhua; van Nas, Atila; Moffatt, Miriam F; Zhai, Guangju; Hofman, Albert; van Meurs, Joyce B; Pols, Huibert A P; Price, Roger I; Nilsson, Olle; Pastinen, Tomi; Cupples, L Adrienne; Lusis, Aldons J; Schadt, Eric E; Ferrari, Serge; Uitterlinden, André G; Rivadeneira, Fernando; Spector, Timothy D; Karasik, David; Kiel, Douglas P

2010-06-10

Osteoporosis is a complex disorder and commonly leads to fractures in elderly persons. Genome-wide association studies (GWAS) have become an unbiased approach to identify variations in the genome that potentially affect health. However, the genetic variants identified so far only explain a small proportion of the heritability for complex traits. Due to the modest genetic effect size and inadequate power, true association signals may not be revealed based on a stringent genome-wide significance threshold. Here, we take advantage of SNP and transcript arrays and integrate GWAS and expression signature profiling relevant to the skeletal system in cellular and animal models to prioritize the discovery of novel candidate genes for osteoporosis-related traits, including bone mineral density (BMD) at the lumbar spine (LS) and femoral neck (FN), as well as geometric indices of the hip (femoral neck-shaft angle, NSA; femoral neck length, NL; and narrow-neck width, NW). A two-stage meta-analysis of GWAS from 7,633 Caucasian women and 3,657 men, revealed three novel loci associated with osteoporosis-related traits, including chromosome 1p13.2 (RAP1A, p = 3.6x10(-8)), 2q11.2 (TBC1D8), and 18q11.2 (OSBPL1A), and confirmed a previously reported region near TNFRSF11B/OPG gene. We also prioritized 16 suggestive genome-wide significant candidate genes based on their potential involvement in skeletal metabolism. Among them, 3 candidate genes were associated with BMD in women. Notably, 2 out of these 3 genes (GPR177, p = 2.6x10(-13); SOX6, p = 6.4x10(-10)) associated with BMD in women have been successfully replicated in a large-scale meta-analysis of BMD, but none of the non-prioritized candidates (associated with BMD) did. Our results support the concept of our prioritization strategy. In the absence of direct biological support for identified genes, we highlighted the efficiency of subsequent functional characterization using publicly available expression profiling relevant to the skeletal system in cellular or whole animal models to prioritize candidate genes for further functional validation.

Detection of susceptibility genes as modifiers due to subgroup differences in complex disease.

PubMed

Bergen, Sarah E; Maher, Brion S; Fanous, Ayman H; Kendler, Kenneth S

2010-08-01

Complex diseases invariably involve multiple genes and often exhibit variable symptom profiles. The extent to which disease symptoms, course, and severity differ between affected individuals may result from underlying genetic heterogeneity. Genes with modifier effects may or may not also influence disease susceptibility. In this study, we have simulated data in which a subset of cases differ by some effect size (ES) on a quantitative trait and are also enriched for a risk allele. Power to detect this 'pseudo-modifier' gene in case-only and case-control designs was explored blind to case substructure. Simulations involved 1000 iterations and calculations for 80% power at P<0.01 while varying the risk allele frequency (RAF), sample size (SS), ES, odds ratio (OR), and proportions of the case subgroups. With realistic values for the RAF (0.20), SS (3000) and ES (1), an OR of 1.7 is necessary to detect a pseudo-modifier gene. Unequal numbers of subjects in the case groups result in little decrement in power until the group enriched for the risk allele is <30% or >70% of the total case population. In practice, greater numbers of subjects and selection of a quantitative trait with a large range will provide researchers with greater power to detect a pseudo-modifier gene. However, even under ideal conditions, studies involving alleles with low frequencies or low ORs are usually underpowered for detection of a modifier or susceptibility gene. This may explain some of the inconsistent association results for many candidate gene studies of complex diseases.

Identification and verification of differentially expressed genes in the caprine hypothalamic-pituitary-gonadal axis that are associated with litter size.

PubMed

Feng, Tao; Cao, Gui-Ling; Chu, Ming-Xing; Di, Ran; Huang, Dong-Wei; Liu, Qiu-Yue; Pan, Zhang-Yuan; Jin, Mei; Zhang, Ying-Jie; Li, Ning

2015-02-01

Litter size is a favorable economic trait for the goat industry, but remains a complex trait controlled by multiple genes in multiple organs. Several genes have been identified that may affect embryo survival, follicular development, and the health of fetuses during pregnancy. Jining Grey goats demonstrate the largest litter size among goat breeds indigenous to China. In order to better understand the genetic basis of this trait, six suppression subtractive hybridization (SSH) cDNA libraries were constructed using pooled mRNAs from hypothalamuses, pituitaries, and ovaries of sexually mature and adult polytocous Jining Grey goats, as testers, versus the pooled corresponding mRNAs of monotocous Liaoning Cashmere goats, as drivers. A total of 1,458 true-positive clones--including 955 known genes and 481 known and 22 unknown expressed sequence tags--were obtained from the SSH libraries by sequencing and alignment. The known genes were categorized into cellular processes and signaling information storage and processing, and metabolism. Three genes (FTH1, GH, and SAA) were selected to validate the SSH results by quantitative real-time PCR; all three were up-regulated in the corresponding tissues in the tester group indicating that these are candidate genes associated with the large litter size of Jining Grey goats. Several other identified genes may affect embryo survival, follicular development, and health during pregnancy. This study provides insights into the mechanistic basis by which the caprine hypothalamic-pituitary-gonadal axis affects reproductive traits and provides a theoretical basis for goat production and breeding. © 2015 Wiley Periodicals, Inc.

Evidence of major genes affecting stress response in rainbow trout using Bayesian methods of complex segregation analysis

USDA-ARS?s Scientific Manuscript database

As a first step towards the genetic mapping of quantitative trait loci (QTL) affecting stress response variation in rainbow trout, we performed complex segregation analyses (CSA) fitting mixed inheritance models of plasma cortisol using Bayesian methods in large full-sib families of rainbow trout. ...

Digestive Organ in the Female Reproductive Tract Borrows Genes from Multiple Organ Systems to Adopt Critical Functions

PubMed Central

Meslin, Camille; Plakke, Melissa S.; Deutsch, Aaron B.; Small, Brandon S.; Morehouse, Nathan I.; Clark, Nathan L.

2015-01-01

Persistent adaptive challenges are often met with the evolution of novel physiological traits. Although there are specific examples of single genes providing new physiological functions, studies on the origin of complex organ functions are lacking. One such derived set of complex functions is found in the Lepidopteran bursa copulatrix, an organ within the female reproductive tract that digests nutrients from the male ejaculate or spermatophore. Here, we characterized bursa physiology and the evolutionary mechanisms by which it was equipped with digestive and absorptive functionality. By studying the transcriptome of the bursa and eight other tissues, we revealed a suite of highly expressed and secreted gene products providing the bursa with a combination of stomach-like traits for mechanical and enzymatic digestion of the male spermatophore. By subsequently placing these bursa genes in an evolutionary framework, we found that the vast majority of their novel digestive functions were co-opted by borrowing genes that continue to be expressed in nonreproductive tissues. However, a number of bursa-specific genes have also arisen, some of which represent unique gene families restricted to Lepidoptera and may provide novel bursa-specific functions. This pattern of promiscuous gene borrowing and relatively infrequent evolution of tissue-specific duplicates stands in contrast to studies of the evolution of novelty via single gene co-option. Our results suggest that the evolution of complex organ-level phenotypes may often be enabled (and subsequently constrained) by changes in tissue specificity that allow expression of existing genes in novel contexts, such as reproduction. The extent to which the selective pressures encountered in these novel roles require resolution via duplication and sub/neofunctionalization is likely to be determined by the need for specialized reproductive functionality. Thus, complex physiological phenotypes such as that found in the bursa offer important opportunities for understanding the relative role of pleiotropy and specialization in adaptive evolution. PMID:25725432

Integrating Genetic and Functional Genomic Data to Elucidate Common Disease Tra

NASA Astrophysics Data System (ADS)

Schadt, Eric

2005-03-01

The reconstruction of genetic networks in mammalian systems is one of the primary goals in biological research, especially as such reconstructions relate to elucidating not only common, polygenic human diseases, but living systems more generally. Here I present a statistical procedure for inferring causal relationships between gene expression traits and more classic clinical traits, including complex disease traits. This procedure has been generalized to the gene network reconstruction problem, where naturally occurring genetic variations in segregating mouse populations are used as a source of perturbations to elucidate tissue-specific gene networks. Differences in the extent of genetic control between genders and among four different tissues are highlighted. I also demonstrate that the networks derived from expression data in segregating mouse populations using the novel network reconstruction algorithm are able to capture causal associations between genes that result in increased predictive power, compared to more classically reconstructed networks derived from the same data. This approach to causal inference in large segregating mouse populations over multiple tissues not only elucidates fundamental aspects of transcriptional control, it also allows for the objective identification of key drivers of common human diseases.

Engineering Complex Microbial Phenotypes with Continuous Genetic Integration and Plasmid Based Multi-gene Library

DTIC Science & Technology

2013-10-09

have desirable traits. We aim to enlarge the E. coli genome using Lactobacillusplantarum genes to build cells tolerant to EtOH and BT. L. plantarum is...chemicals III. Approach Objective 1 & la: Integrated heterologous (L. plantarum ) DNA into the E. coli chromosome and selected for insertions that...developed in combination with genes identified from screening L. plantarum libraries. Additionally, we have screened heterologous libraries for

Mapping in an apple (Malus x domestica) F1 segregating population based on physical clustering of differentially expressed genes

USDA-ARS?s Scientific Manuscript database

Background: Apple tree breeding is slow and difficult due to long generation times, self incompatibility, and complex genetics. The identification of molecular markers linked to traits of interest is a way to expedite the breeding process. In the present study, we aimed to identify genes whose stead...

Recent progress in the genetics of spontaneously hypertensive rats.

PubMed

Pravenec, M; Křen, V; Landa, V; Mlejnek, P; Musilová, A; Šilhavý, J; Šimáková, M; Zídek, V

2014-01-01

The spontaneously hypertensive rat (SHR) is the most widely used animal model of essential hypertension and accompanying metabolic disturbances. Recent advances in sequencing of genomes of BN-Lx and SHR progenitors of the BXH/HXB recombinant inbred (RI) strains as well as accumulation of multiple data sets of intermediary phenotypes in the RI strains, including mRNA and microRNA abundance, quantitative metabolomics, proteomics, methylomics or histone modifications, will make it possible to systematically search for genetic variants involved in regulation of gene expression and in the etiology of complex pathophysiological traits. New advances in manipulation of the rat genome, including efficient transgenesis and gene targeting, will enable in vivo functional analyses of selected candidate genes to identify QTL at the molecular level or to provide insight into mechanisms whereby targeted genes affect pathophysiological traits in the SHR.

Genome-Wide Association Study for Muscle Fat Content and Abdominal Fat Traits in Common Carp (Cyprinus carpio)

PubMed Central

Zheng, Xianhu; Kuang, Youyi; Lv, Weihua; Cao, Dingchen; Sun, Zhipeng; Sun, Xiaowen

2016-01-01

Muscle fat content is an important phenotypic trait in fish, as it affects the nutritional, technical and sensory qualities of flesh. To identify loci and candidate genes associated with muscle fat content and abdominal fat traits, we performed a genome-wide association study (GWAS) using the common carp 250 K SNP assay in a common carp F2 resource population. A total of 18 loci surpassing the genome-wide suggestive significance level were detected for 4 traits: fat content in dorsal muscle (MFdo), fat content in abdominal muscle (MFab), abdominal fat weight (AbFW), and AbFW as a percentage of eviscerated weight (AbFP). Among them, one SNP (carp089419) affecting both AbFW and AbFP reached the genome-wide significance level. Ten of those loci were harbored in or near known genes. Furthermore, relative expressions of 5 genes related to MFdo were compared using dorsal muscle samples with high and low phenotypic values. The results showed that 4 genes were differentially expressed between the high and low phenotypic groups. These genes are, therefore, prospective candidate genes for muscle fat content: ankyrin repeat domain 10a (ankrd10a), tetratricopeptide repeat, ankyrin repeat and coiled-coil containing 2 (tanc2), and four jointed box 1 (fjx1) and choline kinase alpha (chka). These results offer valuable insights into the complex genetic basis of fat metabolism and deposition. PMID:28030623

Prioritization of Candidate Genes in QTL Regions for Physiological and Biochemical Traits Underlying Drought Response in Barley (Hordeum vulgare L.)

PubMed Central

Gudys, Kornelia; Guzy-Wrobelska, Justyna; Janiak, Agnieszka; Dziurka, Michał A.; Ostrowska, Agnieszka; Hura, Katarzyna; Jurczyk, Barbara; Żmuda, Katarzyna; Grzybkowska, Daria; Śróbka, Joanna; Urban, Wojciech; Biesaga-Koscielniak, Jolanta; Filek, Maria; Koscielniak, Janusz; Mikołajczak, Krzysztof; Ogrodowicz, Piotr; Krystkowiak, Karolina; Kuczyńska, Anetta; Krajewski, Paweł; Szarejko, Iwona

2018-01-01

Drought is one of the most adverse abiotic factors limiting growth and productivity of crops. Among them is barley, ranked fourth cereal worldwide in terms of harvested acreage and production. Plants have evolved various mechanisms to cope with water deficit at different biological levels, but there is an enormous challenge to decipher genes responsible for particular complex phenotypic traits, in order to develop drought tolerant crops. This work presents a comprehensive approach for elucidation of molecular mechanisms of drought tolerance in barley at the seedling stage of development. The study includes mapping of QTLs for physiological and biochemical traits associated with drought tolerance on a high-density function map, projection of QTL confidence intervals on barley physical map, and the retrievement of positional candidate genes (CGs), followed by their prioritization based on Gene Ontology (GO) enrichment analysis. A total of 64 QTLs for 25 physiological and biochemical traits that describe plant water status, photosynthetic efficiency, osmoprotectant and hormone content, as well as antioxidant activity, were positioned on a consensus map, constructed using RIL populations developed from the crosses between European and Syrian genotypes. The map contained a total of 875 SNP, SSR and CGs, spanning 941.86 cM with resolution of 1.1 cM. For the first time, QTLs for ethylene, glucose, sucrose, maltose, raffinose, α-tocopherol, γ-tocotrienol content, and catalase activity, have been mapped in barley. Based on overlapping confidence intervals of QTLs, 11 hotspots were identified that enclosed more than 60% of mapped QTLs. Genetic and physical map integration allowed the identification of 1,101 positional CGs within the confidence intervals of drought response-specific QTLs. Prioritization resulted in the designation of 143 CGs, among them were genes encoding antioxidants, carboxylic acid biosynthesis enzymes, heat shock proteins, small auxin up-regulated RNAs, nitric oxide synthase, ATP sulfurylases, and proteins involved in regulation of flowering time. This global approach may be proposed for identification of new CGs that underlies QTLs responsible for complex traits. PMID:29946328

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.

Genetic architecture of a hormonal response to gene knockdown in honey bees.

PubMed

Ihle, Kate E; Rueppell, Olav; Huang, Zachary Y; Wang, Ying; Fondrk, M Kim; Page, Robert E; Amdam, Gro V

2015-01-01

Variation in endocrine signaling is proposed to underlie the evolution and regulation of social life histories, but the genetic architecture of endocrine signaling is still poorly understood. An excellent example of a hormonally influenced set of social traits is found in the honey bee (Apis mellifera): a dynamic and mutually suppressive relationship between juvenile hormone (JH) and the yolk precursor protein vitellogenin (Vg) regulates behavioral maturation and foraging of workers. Several other traits cosegregate with these behavioral phenotypes, comprising the pollen hoarding syndrome (PHS) one of the best-described animal behavioral syndromes. Genotype differences in responsiveness of JH to Vg are a potential mechanistic basis for the PHS. Here, we reduced Vg expression via RNA interference in progeny from a backcross between 2 selected lines of honey bees that differ in JH responsiveness to Vg reduction and measured JH response and ovary size, which represents another key aspect of the PHS. Genetic mapping based on restriction site-associated DNA tag sequencing identified suggestive quantitative trait loci (QTL) for ovary size and JH responsiveness. We confirmed genetic effects on both traits near many QTL that had been identified previously for their effect on various PHS traits. Thus, our results support a role for endocrine control of complex traits at a genetic level. Furthermore, this first example of a genetic map of a hormonal response to gene knockdown in a social insect helps to refine the genetic understanding of complex behaviors and the physiology that may underlie behavioral control in general. © The American Genetic Association. 2015.

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.

Genome-wide association analysis of metabolic traits in a birth cohort from a founder population.

PubMed

Sabatti, Chiara; Service, Susan K; Hartikainen, Anna-Liisa; Pouta, Anneli; Ripatti, Samuli; Brodsky, Jae; Jones, Chris G; Zaitlen, Noah A; Varilo, Teppo; Kaakinen, Marika; Sovio, Ulla; Ruokonen, Aimo; Laitinen, Jaana; Jakkula, Eveliina; Coin, Lachlan; Hoggart, Clive; Collins, Andrew; Turunen, Hannu; Gabriel, Stacey; Elliot, Paul; McCarthy, Mark I; Daly, Mark J; Järvelin, Marjo-Riitta; Freimer, Nelson B; Peltonen, Leena

2009-01-01

Genome-wide association studies (GWAS) of longitudinal birth cohorts enable joint investigation of environmental and genetic influences on complex traits. We report GWAS results for nine quantitative metabolic traits (triglycerides, high-density lipoprotein, low-density lipoprotein, glucose, insulin, C-reactive protein, body mass index, and systolic and diastolic blood pressure) in the Northern Finland Birth Cohort 1966 (NFBC1966), drawn from the most genetically isolated Finnish regions. We replicate most previously reported associations for these traits and identify nine new associations, several of which highlight genes with metabolic functions: high-density lipoprotein with NR1H3 (LXRA), low-density lipoprotein with AR and FADS1-FADS2, glucose with MTNR1B, and insulin with PANK1. Two of these new associations emerged after adjustment of results for body mass index. Gene-environment interaction analyses suggested additional associations, which will require validation in larger samples. The currently identified loci, together with quantified environmental exposures, explain little of the trait variation in NFBC1966. The association observed between low-density lipoprotein and an infrequent variant in AR suggests the potential of such a cohort for identifying associations with both common, low-impact and rarer, high-impact quantitative trait loci.

Mapping by sequencing in cotton (Gossypium hirsutum) line MD52ne identified candidate genes for fiber strength and its related quality attributes.

PubMed

Islam, Md S; Zeng, Linghe; Thyssen, Gregory N; Delhom, Christopher D; Kim, Hee Jin; Li, Ping; Fang, David D

2016-06-01

Three QTL regions controlling three fiber quality traits were validated and further fine-mapped with 27 new single nucleotide polymorphism (SNP) markers. Transcriptome analysis suggests that receptor-like kinases found within the validated QTLs are potential candidate genes responsible for superior fiber strength in cotton line MD52ne. Fiber strength, length, maturity and fineness determine the market value of cotton fibers and the quality of spun yarn. Cotton fiber strength has been recognized as a critical quality attribute in the modern textile industry. Fine mapping along with quantitative trait loci (QTL) validation and candidate gene prediction can uncover the genetic and molecular basis of fiber quality traits. Four previously-identified QTLs (qFBS-c3, qSFI-c14, qUHML-c14 and qUHML-c24) related to fiber bundle strength, short fiber index and fiber length, respectively, were validated using an F3 population that originated from a cross of MD90ne × MD52ne. A group of 27 new SNP markers generated from mapping-by-sequencing (MBS) were placed in QTL regions to improve and validate earlier maps. Our refined QTL regions spanned 4.4, 1.8 and 3.7 Mb of physical distance in the Gossypium raimondii reference genome. We performed RNA sequencing (RNA-seq) of 15 and 20 days post-anthesis fiber cells from MD52ne and MD90ne and aligned reads to the G. raimondii genome. The QTL regions contained 21 significantly differentially expressed genes (DEGs) between the two near-isogenic parental lines. SNPs that result in non-synonymous substitutions to amino acid sequences of annotated genes were identified within these DEGs, and mapped. Taken together, transcriptome and amino acid mutation analysis indicate that receptor-like kinase pathway genes are likely candidates for superior fiber strength and length in MD52ne. MBS along with RNA-seq demonstrated a powerful strategy to elucidate candidate genes for the QTLs that control complex traits in a complex genome like tetraploid upland cotton.

A strategy to apply quantitative epistasis analysis on developmental traits.

PubMed

Labocha, Marta K; Yuan, Wang; Aleman-Meza, Boanerges; Zhong, Weiwei

2017-05-15

Genetic interactions are keys to understand complex traits and evolution. Epistasis analysis is an effective method to map genetic interactions. Large-scale quantitative epistasis analysis has been well established for single cells. However, there is a substantial lack of such studies in multicellular organisms and their complex phenotypes such as development. Here we present a method to extend quantitative epistasis analysis to developmental traits. In the nematode Caenorhabditis elegans, we applied RNA interference on mutants to inactivate two genes, used an imaging system to quantitatively measure phenotypes, and developed a set of statistical methods to extract genetic interactions from phenotypic measurement. Using two different C. elegans developmental phenotypes, body length and sex ratio, as examples, we showed that this method could accommodate various metazoan phenotypes with performances comparable to those methods in single cell growth studies. Comparing with qualitative observations, this method of quantitative epistasis enabled detection of new interactions involving subtle phenotypes. For example, several sex-ratio genes were found to interact with brc-1 and brd-1, the orthologs of the human breast cancer genes BRCA1 and BARD1, respectively. We confirmed the brc-1 interactions with the following genes in DNA damage response: C34F6.1, him-3 (ortholog of HORMAD1, HORMAD2), sdc-1, and set-2 (ortholog of SETD1A, SETD1B, KMT2C, KMT2D), validating the effectiveness of our method in detecting genetic interactions. We developed a reliable, high-throughput method for quantitative epistasis analysis of developmental phenotypes.

Combined Large-Scale Phenotyping and Transcriptomics in Maize Reveals a Robust Growth Regulatory Network1[OPEN

PubMed Central

Herman, Dorota; Slabbinck, Bram; Pè, Mario Enrico

2016-01-01

Leaves are vital organs for biomass and seed production because of their role in the generation of metabolic energy and organic compounds. A better understanding of the molecular networks underlying leaf development is crucial to sustain global requirements for food and renewable energy. Here, we combined transcriptome profiling of proliferative leaf tissue with in-depth phenotyping of the fourth leaf at later stages of development in 197 recombinant inbred lines of two different maize (Zea mays) populations. Previously, correlation analysis in a classical biparental mapping population identified 1,740 genes correlated with at least one of 14 traits. Here, we extended these results with data from a multiparent advanced generation intercross population. As expected, the phenotypic variability was found to be larger in the latter population than in the biparental population, although general conclusions on the correlations among the traits are comparable. Data integration from the two diverse populations allowed us to identify a set of 226 genes that are robustly associated with diverse leaf traits. This set of genes is enriched for transcriptional regulators and genes involved in protein synthesis and cell wall metabolism. In order to investigate the molecular network context of the candidate gene set, we integrated our data with publicly available functional genomics data and identified a growth regulatory network of 185 genes. Our results illustrate the power of combining in-depth phenotyping with transcriptomics in mapping populations to dissect the genetic control of complex traits and present a set of candidate genes for use in biomass improvement. PMID:26754667

Combined Large-Scale Phenotyping and Transcriptomics in Maize Reveals a Robust Growth Regulatory Network.

PubMed

Baute, Joke; Herman, Dorota; Coppens, Frederik; De Block, Jolien; Slabbinck, Bram; Dell'Acqua, Matteo; Pè, Mario Enrico; Maere, Steven; Nelissen, Hilde; Inzé, Dirk

2016-03-01

Leaves are vital organs for biomass and seed production because of their role in the generation of metabolic energy and organic compounds. A better understanding of the molecular networks underlying leaf development is crucial to sustain global requirements for food and renewable energy. Here, we combined transcriptome profiling of proliferative leaf tissue with in-depth phenotyping of the fourth leaf at later stages of development in 197 recombinant inbred lines of two different maize (Zea mays) populations. Previously, correlation analysis in a classical biparental mapping population identified 1,740 genes correlated with at least one of 14 traits. Here, we extended these results with data from a multiparent advanced generation intercross population. As expected, the phenotypic variability was found to be larger in the latter population than in the biparental population, although general conclusions on the correlations among the traits are comparable. Data integration from the two diverse populations allowed us to identify a set of 226 genes that are robustly associated with diverse leaf traits. This set of genes is enriched for transcriptional regulators and genes involved in protein synthesis and cell wall metabolism. In order to investigate the molecular network context of the candidate gene set, we integrated our data with publicly available functional genomics data and identified a growth regulatory network of 185 genes. Our results illustrate the power of combining in-depth phenotyping with transcriptomics in mapping populations to dissect the genetic control of complex traits and present a set of candidate genes for use in biomass improvement. © 2016 American Society of Plant Biologists. All Rights Reserved.

Genetic Mechanisms Leading to Sex Differences Across Common Diseases and Anthropometric Traits.

PubMed

Traglia, Michela; Bseiso, Dina; Gusev, Alexander; Adviento, Brigid; Park, Daniel S; Mefford, Joel A; Zaitlen, Noah; Weiss, Lauren A

2017-02-01

Common diseases often show sex differences in prevalence, onset, symptomology, treatment, or prognosis. Although studies have been performed to evaluate sex differences at specific SNP associations, this work aims to comprehensively survey a number of complex heritable diseases and anthropometric traits. Potential genetically encoded sex differences we investigated include differential genetic liability thresholds or distributions, gene-sex interaction at autosomal loci, major contribution of the X-chromosome, or gene-environment interactions reflected in genes responsive to androgens or estrogens. Finally, we tested the overlap between sex-differential association with anthropometric traits and disease risk. We utilized complementary approaches of assessing GWAS association enrichment and SNP-based heritability estimation to explore explicit sex differences, as well as enrichment in sex-implicated functional categories. We do not find consistent increased genetic load in the lower-prevalence sex, or a disproportionate role for the X-chromosome in disease risk, despite sex-heterogeneity on the X for several traits. We find that all anthropometric traits show less than complete correlation between the genetic contribution to males and females, and find a convincing example of autosome-wide genome-sex interaction in multiple sclerosis (P = 1 × 10 -9 ). We also find some evidence for hormone-responsive gene enrichment, and striking evidence of the contribution of sex-differential anthropometric associations to common disease risk, implying that general mechanisms of sexual dimorphism determining secondary sex characteristics have shared effects on disease risk. Copyright © 2017 by the Genetics Society of America.

GENIUS: web server to predict local gene networks and key genes for biological functions.

PubMed

Puelma, Tomas; Araus, Viviana; Canales, Javier; Vidal, Elena A; Cabello, Juan M; Soto, Alvaro; Gutiérrez, Rodrigo A

2017-03-01

GENIUS is a user-friendly web server that uses a novel machine learning algorithm to infer functional gene networks focused on specific genes and experimental conditions that are relevant to biological functions of interest. These functions may have different levels of complexity, from specific biological processes to complex traits that involve several interacting processes. GENIUS also enriches the network with new genes related to the biological function of interest, with accuracies comparable to highly discriminative Support Vector Machine methods. GENIUS currently supports eight model organisms and is freely available for public use at http://networks.bio.puc.cl/genius . genius.psbl@gmail.com. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Transient structural variations have strong effects on quantitative traits and reproductive isolation in fission yeast

PubMed Central

Jeffares, Daniel C.; Jolly, Clemency; Hoti, Mimoza; Speed, Doug; Shaw, Liam; Rallis, Charalampos; Balloux, Francois; Dessimoz, Christophe; Bähler, Jürg; Sedlazeck, Fritz J.

2017-01-01

Large structural variations (SVs) within genomes are more challenging to identify than smaller genetic variants but may substantially contribute to phenotypic diversity and evolution. We analyse the effects of SVs on gene expression, quantitative traits and intrinsic reproductive isolation in the yeast Schizosaccharomyces pombe. We establish a high-quality curated catalogue of SVs in the genomes of a worldwide library of S. pombe strains, including duplications, deletions, inversions and translocations. We show that copy number variants (CNVs) show a variety of genetic signals consistent with rapid turnover. These transient CNVs produce stoichiometric effects on gene expression both within and outside the duplicated regions. CNVs make substantial contributions to quantitative traits, most notably intracellular amino acid concentrations, growth under stress and sugar utilization in winemaking, whereas rearrangements are strongly associated with reproductive isolation. Collectively, these findings have broad implications for evolution and for our understanding of quantitative traits including complex human diseases. PMID:28117401

Living in two worlds: the plant and insect lifestyles of Xylella fastidiosa.

PubMed

Chatterjee, Subhadeep; Almeida, Rodrigo P P; Lindow, Steven

2008-01-01

Diseases caused by Xylella fastidiosa have attained great importance worldwide as the pathogen and its insect vectors have been disseminated. Since this is the first plant pathogenic bacterium for which a complete genome sequence was determined, much progress has been made in understanding the process by which it spreads within the xylem vessels of susceptible plants as well as the traits that contribute to its acquisition and transmission by sharpshooter vectors. Although this pathogen shares many similarities with Xanthomonas species, such as its use of a small fatty acid signal molecule to coordinate virulence gene expression, the traits that it utilizes to cause disease and the manner in which they are regulated differ substantially from those of related plant pathogens. Its complex lifestyle as both a plant and insect colonist involves traits that are in conflict with these stages, thus apparently necessitating the use of a gene regulatory scheme that allows cells expressing different traits to co-occur in the plant.

Ab initio genotype–phenotype association reveals intrinsic modularity in genetic networks

PubMed Central

Slonim, Noam; Elemento, Olivier; Tavazoie, Saeed

2006-01-01

Microbial species express an astonishing diversity of phenotypic traits, behaviors, and metabolic capacities. However, our molecular understanding of these phenotypes is based almost entirely on studies in a handful of model organisms that together represent only a small fraction of this phenotypic diversity. Furthermore, many microbial species are not amenable to traditional laboratory analysis because of their exotic lifestyles and/or lack of suitable molecular genetic techniques. As an adjunct to experimental analysis, we have developed a computational information-theoretic framework that produces high-confidence gene–phenotype predictions using cross-species distributions of genes and phenotypes across 202 fully sequenced archaea and eubacteria. In addition to identifying the genetic basis of complex traits, our approach reveals the organization of these genes into generic preferentially co-inherited modules, many of which correspond directly to known enzymatic pathways, molecular complexes, signaling pathways, and molecular machines. PMID:16732191

A high-density SNP genetic linkage map for the silver-lipped pearl oyster, Pinctada maxima: a valuable resource for gene localisation and marker-assisted selection.

PubMed

Jones, David B; Jerry, Dean R; Khatkar, Mehar S; Raadsma, Herman W; Zenger, Kyall R

2013-11-20

The silver-lipped pearl oyster, Pinctada maxima, is an important tropical aquaculture species extensively farmed for the highly sought "South Sea" pearls. Traditional breeding programs have been initiated for this species in order to select for improved pearl quality, but many economic traits under selection are complex, polygenic and confounded with environmental factors, limiting the accuracy of selection. The incorporation of a marker-assisted selection (MAS) breeding approach would greatly benefit pearl breeding programs by allowing the direct selection of genes responsible for pearl quality. However, before MAS can be incorporated, substantial genomic resources such as genetic linkage maps need to be generated. The construction of a high-density genetic linkage map for P. maxima is not only essential for unravelling the genomic architecture of complex pearl quality traits, but also provides indispensable information on the genome structure of pearl oysters. A total of 1,189 informative genome-wide single nucleotide polymorphisms (SNPs) were incorporated into linkage map construction. The final linkage map consisted of 887 SNPs in 14 linkage groups, spans a total genetic distance of 831.7 centimorgans (cM), and covers an estimated 96% of the P. maxima genome. Assessment of sex-specific recombination across all linkage groups revealed limited overall heterochiasmy between the sexes (i.e. 1.15:1 F/M map length ratio). However, there were pronounced localised differences throughout the linkage groups, whereby male recombination was suppressed near the centromeres compared to female recombination, but inflated towards telomeric regions. Mean values of LD for adjacent SNP pairs suggest that a higher density of markers will be required for powerful genome-wide association studies. Finally, numerous nacre biomineralization genes were localised providing novel positional information for these genes. This high-density SNP genetic map is the first comprehensive linkage map for any pearl oyster species. It provides an essential genomic tool facilitating studies investigating the genomic architecture of complex trait variation and identifying quantitative trait loci for economically important traits useful in genetic selection programs within the P. maxima pearling industry. Furthermore, this map provides a foundation for further research aiming to improve our understanding of the dynamic process of biomineralization, and pearl oyster evolution and synteny.

Genetic factors controlling wool shedding in a composite Easycare sheep flock.

PubMed

Matika, O; Bishop, S C; Pong-Wong, R; Riggio, V; Headon, D J

2013-12-01

Historically, sheep have been selectively bred for desirable traits including wool characteristics. However, recent moves towards extensive farming and reduced farm labour have seen a renewed interest in Easycare breeds. The aim of this study was to quantify the underlying genetic architecture of wool shedding in an Easycare flock. Wool shedding scores were collected from 565 pedigreed commercial Easycare sheep from 2002 to 2010. The wool scoring system was based on a 10-point (0-9) scale, with score 0 for animals retaining full fleece and 9 for those completely shedding. DNA was sampled from 200 animals of which 48 with extreme phenotypes were genotyped using a 50-k SNP chip. Three genetic analyses were performed: heritability analysis, complex segregation analysis to test for a major gene hypothesis and a genome-wide association study to map regions in the genome affecting the trait. Phenotypes were treated as a continuous or binary variable and categories. High estimates of heritability (0.80 when treated as a continuous, 0.65-0.75 as binary and 0.75 as categories) for shedding were obtained from linear mixed model analyses. Complex segregation analysis gave similar estimates (0.80 ± 0.06) to those above with additional evidence for a major gene with dominance effects. Mixed model association analyses identified four significant (P < 0.05) SNPs. Further analyses of these four SNPs in all 200 animals revealed that one of the SNPs displayed dominance effects similar to those obtained from the complex segregation analyses. In summary, we found strong genetic control for wool shedding, demonstrated the possibility of a single putative dominant gene controlling this trait and identified four SNPs that may be in partial linkage disequilibrium with gene(s) controlling shedding. © 2013 University of Edinburgh, Animal Genetics © 2013 Stichting International Foundation for Animal Genetics.

Identification of rhizome-specific genes by genome-wide differential expression Analysis in Oryza longistaminata

PubMed Central

2011-01-01

Background Rhizomatousness is a key component of perenniality of many grasses that contribute to competitiveness and invasiveness of many noxious grass weeds, but can potentially be used to develop perennial cereal crops for sustainable farmers in hilly areas of tropical Asia. Oryza longistaminata, a perennial wild rice with strong rhizomes, has been used as the model species for genetic and molecular dissection of rhizome development and in breeding efforts to transfer rhizome-related traits into annual rice species. In this study, an effort was taken to get insights into the genes and molecular mechanisms underlying the rhizomatous trait in O. longistaminata by comparative analysis of the genome-wide tissue-specific gene expression patterns of five different tissues of O. longistaminata using the Affymetrix GeneChip Rice Genome Array. Results A total of 2,566 tissue-specific genes were identified in five different tissues of O. longistaminata, including 58 and 61 unique genes that were specifically expressed in the rhizome tips (RT) and internodes (RI), respectively. In addition, 162 genes were up-regulated and 261 genes were down-regulated in RT compared to the shoot tips. Six distinct cis-regulatory elements (CGACG, GCCGCC, GAGAC, AACGG, CATGCA, and TAAAG) were found to be significantly more abundant in the promoter regions of genes differentially expressed in RT than in the promoter regions of genes uniformly expressed in all other tissues. Many of the RT and/or RI specifically or differentially expressed genes were located in the QTL regions associated with rhizome expression, rhizome abundance and rhizome growth-related traits in O. longistaminata and thus are good candidate genes for these QTLs. Conclusion The initiation and development of the rhizomatous trait in O. longistaminata are controlled by very complex gene networks involving several plant hormones and regulatory genes, different members of gene families showing tissue specificity and their regulated pathways. Auxin/IAA appears to act as a negative regulator in rhizome development, while GA acts as the activator in rhizome development. Co-localization of the genes specifically expressed in rhizome tips and rhizome internodes with the QTLs for rhizome traits identified a large set of candidate genes for rhizome initiation and development in rice for further confirmation. PMID:21261937

Comparison of statistical tests for association between rare variants and binary traits.

PubMed

Bacanu, Silviu-Alin; Nelson, Matthew R; Whittaker, John C

2012-01-01

Genome-wide association studies have found thousands of common genetic variants associated with a wide variety of diseases and other complex traits. However, a large portion of the predicted genetic contribution to many traits remains unknown. One plausible explanation is that some of the missing variation is due to the effects of rare variants. Nonetheless, the statistical analysis of rare variants is challenging. A commonly used method is to contrast, within the same region (gene), the frequency of minor alleles at rare variants between cases and controls. However, this strategy is most useful under the assumption that the tested variants have similar effects. We previously proposed a method that can accommodate heterogeneous effects in the analysis of quantitative traits. Here we extend this method to include binary traits that can accommodate covariates. We use simulations for a variety of causal and covariate impact scenarios to compare the performance of the proposed method to standard logistic regression, C-alpha, SKAT, and EREC. We found that i) logistic regression methods perform well when the heterogeneity of the effects is not extreme and ii) SKAT and EREC have good performance under all tested scenarios but they can be computationally intensive. Consequently, it would be more computationally desirable to use a two-step strategy by (i) selecting promising genes by faster methods and ii) analyzing selected genes using SKAT/EREC. To select promising genes one can use (1) regression methods when effect heterogeneity is assumed to be low and the covariates explain a non-negligible part of trait variability, (2) C-alpha when heterogeneity is assumed to be large and covariates explain a small fraction of trait's variability and (3) the proposed trend and heterogeneity test when the heterogeneity is assumed to be non-trivial and the covariates explain a large fraction of trait variability.

Genetics of dispersal.

PubMed

Saastamoinen, Marjo; Bocedi, Greta; Cote, Julien; Legrand, Delphine; Guillaume, Frédéric; Wheat, Christopher W; Fronhofer, Emanuel A; Garcia, Cristina; Henry, Roslyn; Husby, Arild; Baguette, Michel; Bonte, Dries; Coulon, Aurélie; Kokko, Hanna; Matthysen, Erik; Niitepõld, Kristjan; Nonaka, Etsuko; Stevens, Virginie M; Travis, Justin M J; Donohue, Kathleen; Bullock, James M; Del Mar Delgado, Maria

2018-02-01

Dispersal is a process of central importance for the ecological and evolutionary dynamics of populations and communities, because of its diverse consequences for gene flow and demography. It is subject to evolutionary change, which begs the question, what is the genetic basis of this potentially complex trait? To address this question, we (i) review the empirical literature on the genetic basis of dispersal, (ii) explore how theoretical investigations of the evolution of dispersal have represented the genetics of dispersal, and (iii) discuss how the genetic basis of dispersal influences theoretical predictions of the evolution of dispersal and potential consequences. Dispersal has a detectable genetic basis in many organisms, from bacteria to plants and animals. Generally, there is evidence for significant genetic variation for dispersal or dispersal-related phenotypes or evidence for the micro-evolution of dispersal in natural populations. Dispersal is typically the outcome of several interacting traits, and this complexity is reflected in its genetic architecture: while some genes of moderate to large effect can influence certain aspects of dispersal, dispersal traits are typically polygenic. Correlations among dispersal traits as well as between dispersal traits and other traits under selection are common, and the genetic basis of dispersal can be highly environment-dependent. By contrast, models have historically considered a highly simplified genetic architecture of dispersal. It is only recently that models have started to consider multiple loci influencing dispersal, as well as non-additive effects such as dominance and epistasis, showing that the genetic basis of dispersal can influence evolutionary rates and outcomes, especially under non-equilibrium conditions. For example, the number of loci controlling dispersal can influence projected rates of dispersal evolution during range shifts and corresponding demographic impacts. Incorporating more realism in the genetic architecture of dispersal is thus necessary to enable models to move beyond the purely theoretical towards making more useful predictions of evolutionary and ecological dynamics under current and future environmental conditions. To inform these advances, empirical studies need to answer outstanding questions concerning whether specific genes underlie dispersal variation, the genetic architecture of context-dependent dispersal phenotypes and behaviours, and correlations among dispersal and other traits. © 2017 The Authors. Biological Reviews published by John Wiley & Sons Ltd on behalf of Cambridge Philosophical Society.

Genetics of dispersal

PubMed Central

Bocedi, Greta; Cote, Julien; Legrand, Delphine; Guillaume, Frédéric; Wheat, Christopher W.; Fronhofer, Emanuel A.; Garcia, Cristina; Henry, Roslyn; Husby, Arild; Baguette, Michel; Bonte, Dries; Coulon, Aurélie; Kokko, Hanna; Matthysen, Erik; Niitepõld, Kristjan; Nonaka, Etsuko; Stevens, Virginie M.; Travis, Justin M. J.; Donohue, Kathleen; Bullock, James M.; del Mar Delgado, Maria

2017-01-01

ABSTRACT Dispersal is a process of central importance for the ecological and evolutionary dynamics of populations and communities, because of its diverse consequences for gene flow and demography. It is subject to evolutionary change, which begs the question, what is the genetic basis of this potentially complex trait? To address this question, we (i) review the empirical literature on the genetic basis of dispersal, (ii) explore how theoretical investigations of the evolution of dispersal have represented the genetics of dispersal, and (iii) discuss how the genetic basis of dispersal influences theoretical predictions of the evolution of dispersal and potential consequences. Dispersal has a detectable genetic basis in many organisms, from bacteria to plants and animals. Generally, there is evidence for significant genetic variation for dispersal or dispersal‐related phenotypes or evidence for the micro‐evolution of dispersal in natural populations. Dispersal is typically the outcome of several interacting traits, and this complexity is reflected in its genetic architecture: while some genes of moderate to large effect can influence certain aspects of dispersal, dispersal traits are typically polygenic. Correlations among dispersal traits as well as between dispersal traits and other traits under selection are common, and the genetic basis of dispersal can be highly environment‐dependent. By contrast, models have historically considered a highly simplified genetic architecture of dispersal. It is only recently that models have started to consider multiple loci influencing dispersal, as well as non‐additive effects such as dominance and epistasis, showing that the genetic basis of dispersal can influence evolutionary rates and outcomes, especially under non‐equilibrium conditions. For example, the number of loci controlling dispersal can influence projected rates of dispersal evolution during range shifts and corresponding demographic impacts. Incorporating more realism in the genetic architecture of dispersal is thus necessary to enable models to move beyond the purely theoretical towards making more useful predictions of evolutionary and ecological dynamics under current and future environmental conditions. To inform these advances, empirical studies need to answer outstanding questions concerning whether specific genes underlie dispersal variation, the genetic architecture of context‐dependent dispersal phenotypes and behaviours, and correlations among dispersal and other traits. PMID:28776950

Linkage and Association Mapping for Two Major Traits Used in the Maritime Pine Breeding Program: Height Growth and Stem Straightness

PubMed Central

Bink, Marco CAM; van Heerwaarden, Joost; Chancerel, Emilie; Boury, Christophe; Lesur, Isabelle; Isik, Fikret; Bouffier, Laurent; Plomion, Christophe

2016-01-01

Background Increasing our understanding of the genetic architecture of complex traits, through analyses of genotype-phenotype associations and of the genes/polymorphisms accounting for trait variation, is crucial, to improve the integration of molecular markers into forest tree breeding. In this study, two full-sib families and one breeding population of maritime pine were used to identify quantitative trait loci (QTLs) for height growth and stem straightness, through linkage analysis (LA) and linkage disequilibrium (LD) mapping approaches. Results The populations used for LA consisted of two unrelated three-generation full-sib families (n = 197 and n = 477). These populations were assessed for height growth or stem straightness and genotyped for 248 and 217 markers, respectively. The population used for LD mapping consisted of 661 founders of the first and second generations of the breeding program. This population was phenotyped for the same traits and genotyped for 2,498 single-nucleotide polymorphism (SNP) markers corresponding to 1,652 gene loci. The gene-based reference genetic map of maritime pine was used to localize and compare the QTLs detected by the two approaches, for both traits. LA identified three QTLs for stem straightness and two QTLs for height growth. The LD study yielded seven significant associations (P ≤ 0.001): four for stem straightness and three for height growth. No colocalisation was found between QTLs identified by LA and SNPs detected by LD mapping for the same trait. Conclusions This study provides the first comparison of LA and LD mapping approaches in maritime pine, highlighting the complementary nature of these two approaches for deciphering the genetic architecture of two mandatory traits of the breeding program. PMID:27806077

Linkage and Association Mapping for Two Major Traits Used in the Maritime Pine Breeding Program: Height Growth and Stem Straightness.

PubMed

Bartholomé, Jérôme; Bink, Marco Cam; van Heerwaarden, Joost; Chancerel, Emilie; Boury, Christophe; Lesur, Isabelle; Isik, Fikret; Bouffier, Laurent; Plomion, Christophe

2016-01-01

Increasing our understanding of the genetic architecture of complex traits, through analyses of genotype-phenotype associations and of the genes/polymorphisms accounting for trait variation, is crucial, to improve the integration of molecular markers into forest tree breeding. In this study, two full-sib families and one breeding population of maritime pine were used to identify quantitative trait loci (QTLs) for height growth and stem straightness, through linkage analysis (LA) and linkage disequilibrium (LD) mapping approaches. The populations used for LA consisted of two unrelated three-generation full-sib families (n = 197 and n = 477). These populations were assessed for height growth or stem straightness and genotyped for 248 and 217 markers, respectively. The population used for LD mapping consisted of 661 founders of the first and second generations of the breeding program. This population was phenotyped for the same traits and genotyped for 2,498 single-nucleotide polymorphism (SNP) markers corresponding to 1,652 gene loci. The gene-based reference genetic map of maritime pine was used to localize and compare the QTLs detected by the two approaches, for both traits. LA identified three QTLs for stem straightness and two QTLs for height growth. The LD study yielded seven significant associations (P ≤ 0.001): four for stem straightness and three for height growth. No colocalisation was found between QTLs identified by LA and SNPs detected by LD mapping for the same trait. This study provides the first comparison of LA and LD mapping approaches in maritime pine, highlighting the complementary nature of these two approaches for deciphering the genetic architecture of two mandatory traits of the breeding program.

The genetic basis of traits regulating sperm competition and polyandry: can selection favour the evolution of good- and sexy-sperm?

PubMed

Evans, Jonathan P; Simmons, Leigh W

2008-09-01

The good-sperm and sexy-sperm (GS-SS) hypotheses predict that female multiple mating (polyandry) can fuel sexual selection for heritable male traits that promote success in sperm competition. A major prediction generated by these models, therefore, is that polyandry will benefit females indirectly via their sons' enhanced fertilization success. Furthermore, like classic 'good genes' and 'sexy son' models for the evolution of female preferences, GS-SS processes predict a genetic correlation between genes for female mating frequency (analogous to the female preference) and those for traits influencing fertilization success (the sexually selected traits). We examine the premise for these predictions by exploring the genetic basis of traits thought to influence fertilization success and female mating frequency. We also highlight recent debates that stress the possible genetic constraints to evolution of traits influencing fertilization success via GS-SS processes, including sex-linked inheritance, nonadditive effects, interacting parental genotypes, and trade-offs between integrated ejaculate components. Despite these possible constraints, the available data suggest that male traits involved in sperm competition typically exhibit substantial additive genetic variance and rapid evolutionary responses to selection. Nevertheless, the limited data on the genetic variation in female mating frequency implicate strong genetic maternal effects, including X-linkage, which is inconsistent with GS-SS processes. Although the relative paucity of studies on the genetic basis of polyandry does not allow us to draw firm conclusions about the evolutionary origins of this trait, the emerging pattern of sex linkage in genes for polyandry is more consistent with an evolutionary history of antagonistic selection over mating frequency. We advocate further development of GS-SS theory to take account of the complex evolutionary dynamics imposed by sexual conflict over mating frequency.

Deletion Analysis of the Tumorous-Head (tuh–3) Gene in DROSOPHILA MELANOGASTER

PubMed Central

Kuhn, David T.; Woods, Daniel F.; Andrew, Deborah J.

1981-01-01

In the presence of the naturally occurring maternal-effect alleles tuh-1h or tuh-1g, the tuh-3 mutant gene can cause the tumorous-head trait or the sac-testis trait. The tuh-3 gene functions as a semidominant in the presence of the tuh-1h maternal effect. Eye-antennal structures are replaced by posterior abdominal tergites and genital structures. If tuh-1h is replaced by its naturally occurring allele tuh-1g, tuh-3 functions as a recessive hypomorph and the defect switches from anterior to posterior structures, with a male genital-disc defect appearing with variable penetrance. Function and regulation of tuh-3+ may better be understood in light of the cytological localization of tuh-3 either adjacent to or as part of the bithorax complex. The tuh-3+ gene product appears to be essential for normal development, at least in the posterior end of the embryo. PMID:6804305

Six quantitative trait loci influence task thresholds for hygienic behaviour in honeybees (Apis mellifera).

PubMed

Oxley, Peter R; Spivak, Marla; Oldroyd, Benjamin P

2010-04-01

Honeybee hygienic behaviour provides colonies with protection from many pathogens and is an important model system of the genetics of a complex behaviour. It is a textbook example of complex behaviour under simple genetic control: hygienic behaviour consists of two components--uncapping a diseased brood cell, followed by removal of the contents--each of which are thought to be modulated independently by a few loci of medium to large effect. A worker's genetic propensity to engage in hygienic tasks affects the intensity of the stimulus required before she initiates the behaviour. Genetic diversity within colonies leads to task specialization among workers, with a minority of workers performing the majority of nest-cleaning tasks. We identify three quantitative trait loci that influence the likelihood that workers will engage in hygienic behaviour and account for up to 30% of the phenotypic variability in hygienic behaviour in our population. Furthermore, we identify two loci that influence the likelihood that a worker will perform uncapping behaviour only, and one locus that influences removal behaviour. We report the first candidate genes associated with engaging in hygienic behaviour, including four genes involved in olfaction, learning and social behaviour, and one gene involved in circadian locomotion. These candidates will allow molecular characterization of this distinctive behavioural mode of disease resistance, as well as providing the opportunity for marker-assisted selection for this commercially significant trait.

Major Contribution of Flowering Time and Vegetative Growth to Plant Production in Common Bean As Deduced from a Comparative Genetic Mapping.

PubMed

González, Ana M; Yuste-Lisbona, Fernando J; Saburido, Soledad; Bretones, Sandra; De Ron, Antonio M; Lozano, Rafael; Santalla, Marta

2016-01-01

Determinacy growth habit and accelerated flowering traits were selected during or after domestication in common bean. Both processes affect several presumed adaptive traits such as the rate of plant production. There is a close association between flowering initiation and vegetative growth; however, interactions among these two crucial developmental processes and their genetic bases remain unexplored. In this study, with the aim to establish the genetic relationships between these complex processes, a multi-environment quantitative trait locus (QTL) mapping approach was performed in two recombinant inbred line populations derived from inter-gene pool crosses between determinate and indeterminate genotypes. Additive and epistatic QTLs were found to regulate flowering time, vegetative growth, and rate of plant production. Moreover, the pleiotropic patterns of the identified QTLs evidenced that regions controlling time to flowering traits, directly or indirectly, are also involved in the regulation of plant production traits. Further QTL analysis highlighted one QTL, on the lower arm of the linkage group Pv01, harboring the Phvul.001G189200 gene, homologous to the Arabidopsis thaliana TERMINAL FLOWER1 ( TFL1 ) gene, which explained up to 32% of phenotypic variation for time to flowering, 66% for vegetative growth, and 19% for rate of plant production. This finding was consistent with previous results, which have also suggested Phvul.001G189200 (PvTFL1y ) as a candidate gene for determinacy locus. The information here reported can also be applied in breeding programs seeking to optimize key agronomic traits, such as time to flowering, plant height and an improved reproductive biomass, pods, and seed size, as well as yield.

Major Contribution of Flowering Time and Vegetative Growth to Plant Production in Common Bean As Deduced from a Comparative Genetic Mapping

PubMed Central

González, Ana M.; Yuste-Lisbona, Fernando J.; Saburido, Soledad; Bretones, Sandra; De Ron, Antonio M.; Lozano, Rafael; Santalla, Marta

2016-01-01

Determinacy growth habit and accelerated flowering traits were selected during or after domestication in common bean. Both processes affect several presumed adaptive traits such as the rate of plant production. There is a close association between flowering initiation and vegetative growth; however, interactions among these two crucial developmental processes and their genetic bases remain unexplored. In this study, with the aim to establish the genetic relationships between these complex processes, a multi-environment quantitative trait locus (QTL) mapping approach was performed in two recombinant inbred line populations derived from inter-gene pool crosses between determinate and indeterminate genotypes. Additive and epistatic QTLs were found to regulate flowering time, vegetative growth, and rate of plant production. Moreover, the pleiotropic patterns of the identified QTLs evidenced that regions controlling time to flowering traits, directly or indirectly, are also involved in the regulation of plant production traits. Further QTL analysis highlighted one QTL, on the lower arm of the linkage group Pv01, harboring the Phvul.001G189200 gene, homologous to the Arabidopsis thaliana TERMINAL FLOWER1 (TFL1) gene, which explained up to 32% of phenotypic variation for time to flowering, 66% for vegetative growth, and 19% for rate of plant production. This finding was consistent with previous results, which have also suggested Phvul.001G189200 (PvTFL1y) as a candidate gene for determinacy locus. The information here reported can also be applied in breeding programs seeking to optimize key agronomic traits, such as time to flowering, plant height and an improved reproductive biomass, pods, and seed size, as well as yield. PMID:28082996

Whole-Genome Resequencing of Experimental Populations Reveals Polygenic Basis of Egg-Size Variation in Drosophila melanogaster

PubMed Central

Jha, Aashish R.; Miles, Cecelia M.; Lippert, Nodia R.; Brown, Christopher D.; White, Kevin P.; Kreitman, Martin

2015-01-01

Complete genome resequencing of populations holds great promise in deconstructing complex polygenic traits to elucidate molecular and developmental mechanisms of adaptation. Egg size is a classic adaptive trait in insects, birds, and other taxa, but its highly polygenic architecture has prevented high-resolution genetic analysis. We used replicated experimental evolution in Drosophila melanogaster and whole-genome sequencing to identify consistent signatures of polygenic egg-size adaptation. A generalized linear-mixed model revealed reproducible allele frequency differences between replicated experimental populations selected for large and small egg volumes at approximately 4,000 single nucleotide polymorphisms (SNPs). Several hundred distinct genomic regions contain clusters of these SNPs and have lower heterozygosity than the genomic background, consistent with selection acting on polymorphisms in these regions. These SNPs are also enriched among genes expressed in Drosophila ovaries and many of these genes have well-defined functions in Drosophila oogenesis. Additional genes regulating egg development, growth, and cell size show evidence of directional selection as genes regulating these biological processes are enriched for highly differentiated SNPs. Genetic crosses performed with a subset of candidate genes demonstrated that these genes influence egg size, at least in the large genetic background. These findings confirm the highly polygenic architecture of this adaptive trait, and suggest the involvement of many novel candidate genes in regulating egg size. PMID:26044351

Fast and robust group-wise eQTL mapping using sparse graphical models.

PubMed

Cheng, Wei; Shi, Yu; Zhang, Xiang; Wang, Wei

2015-01-16

Genome-wide expression quantitative trait loci (eQTL) studies have emerged as a powerful tool to understand the genetic basis of gene expression and complex traits. The traditional eQTL methods focus on testing the associations between individual single-nucleotide polymorphisms (SNPs) and gene expression traits. A major drawback of this approach is that it cannot model the joint effect of a set of SNPs on a set of genes, which may correspond to hidden biological pathways. We introduce a new approach to identify novel group-wise associations between sets of SNPs and sets of genes. Such associations are captured by hidden variables connecting SNPs and genes. Our model is a linear-Gaussian model and uses two types of hidden variables. One captures the set associations between SNPs and genes, and the other captures confounders. We develop an efficient optimization procedure which makes this approach suitable for large scale studies. Extensive experimental evaluations on both simulated and real datasets demonstrate that the proposed methods can effectively capture both individual and group-wise signals that cannot be identified by the state-of-the-art eQTL mapping methods. Considering group-wise associations significantly improves the accuracy of eQTL mapping, and the successful multi-layer regression model opens a new approach to understand how multiple SNPs interact with each other to jointly affect the expression level of a group of genes.

"Touching Triton": Building Student Understanding of Complex Disease Risk.

PubMed

Loftin, Madelene; East, Kelly; Hott, Adam; Lamb, Neil

2016-01-01

Life science classrooms often emphasize the exception to the rule when it comes to teaching genetics, focusing heavily on rare single-gene and Mendelian traits. By contrast, the vast majority of human traits and diseases are caused by more complicated interactions between genetic and environmental factors. Research indicates that students have a deterministic view of genetics, generalize Mendelian inheritance patterns to all traits, and have unrealistic expectations of genetic technologies. The challenge lies in how to help students analyze complex disease risk with a lack of curriculum materials. Providing open access to both content resources and an engaging storyline can be achieved using a "serious game" model. "Touching Triton" was developed as a serious game in which students are asked to analyze data from a medical record, family history, and genomic report in order to develop an overall lifetime risk estimate of six common, complex diseases. Evaluation of student performance shows significant learning gains in key content areas along with a high level of engagement.

The genetic architecture of local adaptation and reproductive isolation in sympatry within the Mimulus guttatus species complex.

PubMed

Ferris, Kathleen G; Barnett, Laryssa L; Blackman, Benjamin K; Willis, John H

2017-01-01

The genetic architecture of local adaptation has been of central interest to evolutionary biologists since the modern synthesis. In addition to classic theory on the effect size of adaptive mutations by Fisher, Kimura and Orr, recent theory addresses the genetic architecture of local adaptation in the face of ongoing gene flow. This theory predicts that with substantial gene flow between populations local adaptation should proceed primarily through mutations of large effect or tightly linked clusters of smaller effect loci. In this study, we investigate the genetic architecture of divergence in flowering time, mating system-related traits, and leaf shape between Mimulus laciniatus and a sympatric population of its close relative M. guttatus. These three traits are probably involved in M. laciniatus' adaptation to a dry, exposed granite outcrop environment. Flowering time and mating system differences are also reproductive isolating barriers making them 'magic traits'. Phenotypic hybrids in this population provide evidence of recent gene flow. Using next-generation sequencing, we generate dense SNP markers across the genome and map quantitative trait loci (QTLs) involved in flowering time, flower size and leaf shape. We find that interspecific divergence in all three traits is due to few QTL of large effect including a highly pleiotropic QTL on chromosome 8. This QTL region contains the pleiotropic candidate gene TCP4 and is involved in ecologically important phenotypes in other Mimulus species. Our results are consistent with theory, indicating that local adaptation and reproductive isolation with gene flow should be due to few loci with large and pleiotropic effects. © 2016 John Wiley & Sons Ltd.

Association of SNPs in dopamine and serotonin pathway genes and their interacting genes with temperament traits in Charolais cows.

PubMed

Garza-Brenner, E; Sifuentes-Rincón, A M; Randel, R D; Paredes-Sánchez, F A; Parra-Bracamonte, G M; Arellano Vera, W; Rodríguez Almeida, F A; Segura Cabrera, A

2017-08-01

Cattle temperament is a complex trait, and molecular studies aimed at defining this trait are scarce. We used an interaction networks approach to identify new genes (interacting genes) and to estimate their effects and those of 19 dopamine- and serotonin-related genes on the temperament traits of Charolais cattle. The genes proopiomelanocortin (POMC), neuropeptide Y (NPY), solute carrier family 18, member 2 (SLC18A2) and FBJ murine osteosarcoma viral oncogene homologue (FOSFBJ) were identified as new candidates. Their potential to be associated with temperament was estimated according to their reported biological activities, which included interactions with neural activity, receptor function, targeting or synthesis of neurotransmitters and association with behaviour. Pen score (PS) and exit velocity (EV) measures were determined from 412 Charolais cows to calculate their temperament score (TS). Based on the TS, calm (n = 55; TS, 1.09 ± 0.33) and temperamental (n = 58; TS, 2.27 ± 0.639) cows were selected and genotyped using a 248 single-nucleotide variation (SNV) panel. Of the 248 variations in the panel, only 151 were confirmed to be polymorphic (single-nucleotide polymorphisms; SNPs) in the tested population. Single-marker association analyses between genotypes and temperament measures (EV, PS and/or TS) indicated significant associations of six SNPs from four candidate genes. The markers rs109576799 and rs43696138, located in the DRD3 and HTR2A genes, respectively, were significantly associated with both EV and TS traits. Four markers, rs110365063 and rs137756569 from the POMC gene and rs110365063 and rs135155082 located in SLC18A2 and DRD2, respectively, were associated with PS. The variant rs110365063 located in bovine SLC18A2 causes a change in the amino acid sequence from Ala to Thr. Further studies are needed to confirm the association of genetic profile with cattle temperament; however, our study represents important progress in understanding the regulation of cattle temperament by different genes with divergent functions.

Complex Genotype by Environment interactions and changing genetic architectures across thermal environments in the Australian field cricket, Teleogryllus oceanicus

PubMed Central

2011-01-01

Background Biologists studying adaptation under sexual selection have spent considerable effort assessing the relative importance of two groups of models, which hinge on the idea that females gain indirect benefits via mate discrimination. These are the good genes and genetic compatibility models. Quantitative genetic studies have advanced our understanding of these models by enabling assessment of whether the genetic architectures underlying focal phenotypes are congruent with either model. In this context, good genes models require underlying additive genetic variance, while compatibility models require non-additive variance. Currently, we know very little about how the expression of genotypes comprised of distinct parental haplotypes, or how levels and types of genetic variance underlying key phenotypes, change across environments. Such knowledge is important, however, because genotype-environment interactions can have major implications on the potential for evolutionary responses to selection. Results We used a full diallel breeding design to screen for complex genotype-environment interactions, and genetic architectures underlying key morphological traits, across two thermal environments (the lab standard 27°C, and the cooler 23°C) in the Australian field cricket, Teleogryllus oceanicus. In males, complex three-way interactions between sire and dam parental haplotypes and the rearing environment accounted for up to 23 per cent of the scaled phenotypic variance in the traits we measured (body mass, pronotum width and testes mass), and each trait harboured significant additive genetic variance in the standard temperature (27°C) only. In females, these three-way interactions were less important, with interactions between the paternal haplotype and rearing environment accounting for about ten per cent of the phenotypic variance (in body mass, pronotum width and ovary mass). Of the female traits measured, only ovary mass for crickets reared at the cooler temperature (23°C), exhibited significant levels of additive genetic variance. Conclusions Our results show that the genetics underlying phenotypic expression can be complex, context-dependent and different in each of the sexes. We discuss the implications of these results, particularly in terms of the evolutionary processes that hinge on good and compatible genes models. PMID:21791118

Genetic control of complex traits, with a focus on reproduction in pigs.

PubMed

Zak, Louisa J; Gaustad, Ann Helen; Bolarin, Alfonso; Broekhuijse, Marleen L W J; Walling, Grant A; Knol, Egbert F

2017-09-01

Reproductive traits are complex, and desirable reproductive phenotypes, such as litter size or semen quality, are true polygenetic traits determined by multiple gene regulatory pathways. Each individual gene contributes to the overall variation in these traits, so genetic improvements can be achieved using conventional selection methodology. In the past, a pedigree-based-relationship matrix was used; this is now replaced by a combination of pedigree-based- and genomic-relationship matrices. The heritability of reproductive traits is low to moderate, so large-scale data recording is required to identify specific, selectable attributes. Male reproductive traits-including ejaculate volume and sperm progressive motility-are moderately heritable, and could be used in selection programs. A few high-merit artificial-insemination boars can impact many sow populations, so additional knowledge about male reproduction-specifically pre-pubertal detection of infertility and the technologies of semen cryopreservation and sex sorting-should further improve global breeding efforts. Conversely, female pig reproduction is currently a limiting factor of genetic improvement. Litter size and farrowing interval are the main obstacles to increasing selection intensity and to reducing generation interval in a breeding program. Age at puberty and weaning-to-estrus interval can be selected for, thereby reducing the number of non-productive days. The number of piglets born alive and litter weights are also reliably influenced by genetic selection. Characterization of genotype-environment interactions will provide opportunities to match genetics to specific farm systems. Continued investment to understand physiological models for improved phenotyping and the development of technologies to facilitate pig embryo production for genetic selection are warranted to ensure optimal breeding in future generations. © 2017 Wiley Periodicals, Inc.

Transcriptomic Identification of ADH1B as a Novel Candidate Gene for Obesity and Insulin Resistance in Human Adipose Tissue in Mexican Americans from the Veterans Administration Genetic Epidemiology Study (VAGES)

PubMed Central

Winnier, Deidre A.; Fourcaudot, Marcel; Norton, Luke; Abdul-Ghani, Muhammad A.; Hu, Shirley L.; Farook, Vidya S.; Coletta, Dawn K.; Kumar, Satish; Puppala, Sobha; Chittoor, Geetha; Dyer, Thomas D.; Arya, Rector; Carless, Melanie; Lehman, Donna M.; Curran, Joanne E.; Cromack, Douglas T.; Tripathy, Devjit; Blangero, John; Duggirala, Ravindranath; Göring, Harald H. H.; DeFronzo, Ralph A.; Jenkinson, Christopher P.

2015-01-01

Type 2 diabetes (T2D) is a complex metabolic disease that is more prevalent in ethnic groups such as Mexican Americans, and is strongly associated with the risk factors obesity and insulin resistance. The goal of this study was to perform whole genome gene expression profiling in adipose tissue to detect common patterns of gene regulation associated with obesity and insulin resistance. We used phenotypic and genotypic data from 308 Mexican American participants from the Veterans Administration Genetic Epidemiology Study (VAGES). Basal fasting RNA was extracted from adipose tissue biopsies from a subset of 75 unrelated individuals, and gene expression data generated on the Illumina BeadArray platform. The number of gene probes with significant expression above baseline was approximately 31,000. We performed multiple regression analysis of all probes with 15 metabolic traits. Adipose tissue had 3,012 genes significantly associated with the traits of interest (false discovery rate, FDR ≤ 0.05). The significance of gene expression changes was used to select 52 genes with significant (FDR ≤ 10-4) gene expression changes across multiple traits. Gene sets/Pathways analysis identified one gene, alcohol dehydrogenase 1B (ADH1B) that was significantly enriched (P < 10-60) as a prime candidate for involvement in multiple relevant metabolic pathways. Illumina BeadChip derived ADH1B expression data was consistent with quantitative real time PCR data. We observed significant inverse correlations with waist circumference (2.8 x 10-9), BMI (5.4 x 10-6), and fasting plasma insulin (P < 0.001). These findings are consistent with a central role for ADH1B in obesity and insulin resistance and provide evidence for a novel genetic regulatory mechanism for human metabolic diseases related to these traits. PMID:25830378

The complex history of the domestication of rice.

PubMed

Sweeney, Megan; McCouch, Susan

2007-11-01

Rice has been found in archaeological sites dating to 8000 bc, although the date of rice domestication is a matter of continuing debate. Two species of domesticated rice, Oryza sativa (Asian) and Oryza glaberrima (African) are grown globally. Numerous traits separate wild and domesticated rices including changes in: pericarp colour, dormancy, shattering, panicle architecture, tiller number, mating type and number and size of seeds. Genetic studies using diverse methodologies have uncovered a deep population structure within domesticated rice. Two main groups, the indica and japonica subspecies, have been identified with several subpopulations existing within each group. The antiquity of the divide has been estimated at more than 100 000 years ago. This date far precedes domestication, supporting independent domestications of indica and japonica from pre-differentiated pools of the wild ancestor. Crosses between subspecies display sterility and segregate for domestication traits, indicating that different populations are fixed for different networks of alleles conditioning these traits. Numerous domestication QTLs have been identified in crosses between the subspecies and in crosses between wild and domesticated accessions of rice. Many of the QTLs cluster in the same genomic regions, suggesting that a single gene with pleiotropic effects or that closely linked clusters of genes underlie these QTL. Recently, several domestication loci have been cloned from rice, including the gene controlling pericarp colour and two loci for shattering. The distribution and evolutionary history of these genes gives insight into the domestication process and the relationship between the subspecies. The evolutionary history of rice is complex, but recent work has shed light on the genetics of the transition from wild (O. rufipogon and O. nivara) to domesticated (O. sativa) rice. The types of genes involved and the geographic and genetic distribution of alleles will allow scientists to better understand our ancestors and breed better rice for our descendents.

Pharmacological Validation of Candidate Causal Sleep Genes Identified in an N2 Cross

PubMed Central

Brunner, Joseph I.; Gotter, Anthony L.; Millstein, Joshua; Garson, Susan; Binns, Jacquelyn; Fox, Steven V.; Savitz, Alan T.; Yang, He S.; Fitzpatrick, Karrie; Zhou, Lili; Owens, Joseph R.; Webber, Andrea L.; Vitaterna, Martha H.; Kasarskis, Andrew; Uebele, Victor N.; Turek, Fred; Renger, John J.; Winrow, Christopher J.

2013-01-01

Despite the substantial impact of sleep disturbances on human health and the many years of study dedicated to understanding sleep pathologies, the underlying genetic mechanisms that govern sleep and wake largely remain unknown. Recently, we completed large scale genetic and gene expression analyses in a segregating inbred mouse cross and identified candidate causal genes that regulate the mammalian sleep-wake cycle, across multiple traits including total sleep time, amounts of REM, non-REM, sleep bout duration and sleep fragmentation. Here we describe a novel approach toward validating candidate causal genes, while also identifying potential targets for sleep-related indications. Select small molecule antagonists and agonists were used to interrogate candidate causal gene function in rodent sleep polysomnography assays to determine impact on overall sleep architecture and to evaluate alignment with associated sleep-wake traits. Significant effects on sleep architecture were observed in validation studies using compounds targeting the muscarinic acetylcholine receptor M3 subunit (Chrm3)(wake promotion), nicotinic acetylcholine receptor alpha4 subunit (Chrna4)(wake promotion), dopamine receptor D5 subunit (Drd5)(sleep induction), serotonin 1D receptor (Htr1d)(altered REM fragmentation), glucagon-like peptide-1 receptor (Glp1r)(light sleep promotion and reduction of deep sleep), and Calcium channel, voltage-dependent, T type, alpha 1I subunit (Cacna1i)(increased bout duration slow wave sleep). Taken together, these results show the complexity of genetic components that regulate sleep-wake traits and highlight the importance of evaluating this complex behavior at a systems level. Pharmacological validation of genetically identified putative targets provides a rapid alternative to generating knock out or transgenic animal models, and may ultimately lead towards new therapeutic opportunities. PMID:22091728

Engineering Complex Microbial Phenotypes with Continuous Genetic Integration and Plasmid Based Multi-Gene Library

DTIC Science & Technology

2010-01-01

genes from strains that have desirable traits. Here, we aim to enlarge the E. coli genome using Lactobacillus plantarum genes to build cells tolerant to...EtOH and BT. L. plantarum is an organism with established high tolerance to alcohols and solvents more broadly. Objective 2: Build a stress...heterologous (here: L. plantarum ; abbreviated as L. pl) DNA into the E. coli chromosome while selecting for insertions that enhance ethanol tolerance (which

Sensory response system of social behavior tied to female reproductive traits.

PubMed

Tsuruda, Jennifer M; Amdam, Gro V; Page, Robert E

2008-01-01

Honey bees display a complex set of anatomical, physiological, and behavioral traits that correlate with the colony storage of surplus pollen (pollen hoarding). We hypothesize that the association of these traits is a result of pleiotropy in a gene signaling network that was co-opted by natural selection to function in worker division of labor and foraging specialization. By acting on the gene network, selection can change a suite of traits, including stimulus/response relationships that affect individual foraging behavior and alter the colony level trait of pollen hoarding. The 'pollen-hoarding syndrome' of honey bees is the best documented syndrome of insect social organization. It can be exemplified as a link between reproductive anatomy (ovary size), physiology (yolk protein level), and foraging behavior in honey bee strains selected for pollen hoarding, a colony level trait. The syndrome gave rise to the forager-Reproductive Ground Plan Hypothesis (RGPH), which proposes that the regulatory control of foraging onset and foraging preference toward nectar or pollen was derived from a reproductive signaling network. This view was recently challenged. To resolve the controversy, we tested the associations between reproductive anatomy, physiology, and stimulus/response relationships of behavior in wild-type honey bees. Central to the stimulus/response relationships of honey bee foraging behavior and pollen hoarding is the behavioral trait of sensory sensitivity to sucrose (an important sugar in nectar). To test the linkage of reproductive traits and sensory response systems of social behavior, we measured sucrose responsiveness with the proboscis extension response (PER) assay and quantified ovary size and vitellogenin (yolk precursor) gene expression in 6-7-day-old bees by counting ovarioles (ovary filaments) and by using semiquantitative real time RT-PCR. We show that bees with larger ovaries (more ovarioles) are characterized by higher levels of vitellogenin mRNA expression and are more responsive to sucrose solutions, a trait that is central to division of labor and foraging specialization. Our results establish that in wild-type honey bees, ovary size and vitellogenin mRNA level covary with the sucrose sensory response system, an important component of foraging behavior. This finding validates links between reproductive physiology and behavioral-trait associations of the pollen-hoarding syndrome of honey bees, and supports the forager-RGPH. Our data address a current evolutionary debate, and represent the first direct demonstration of the links between reproductive anatomy, physiology, and behavioral response systems that are central to the control of complex social behavior in insects.

An Integration of Genome-Wide Association Study and Gene Expression Profiling to Prioritize the Discovery of Novel Susceptibility Loci for Osteoporosis-Related Traits

PubMed Central

Demissie, Serkalem; Soranzo, Nicole; Bianchi, Estelle N.; Grundberg, Elin; Liang, Liming; Richards, J. Brent; Estrada, Karol; Zhou, Yanhua; van Nas, Atila; Moffatt, Miriam F.; Zhai, Guangju; Hofman, Albert; van Meurs, Joyce B.; Pols, Huibert A. P.; Price, Roger I.; Nilsson, Olle; Pastinen, Tomi; Cupples, L. Adrienne; Lusis, Aldons J.; Schadt, Eric E.; Ferrari, Serge; Uitterlinden, André G.

2010-01-01

Osteoporosis is a complex disorder and commonly leads to fractures in elderly persons. Genome-wide association studies (GWAS) have become an unbiased approach to identify variations in the genome that potentially affect health. However, the genetic variants identified so far only explain a small proportion of the heritability for complex traits. Due to the modest genetic effect size and inadequate power, true association signals may not be revealed based on a stringent genome-wide significance threshold. Here, we take advantage of SNP and transcript arrays and integrate GWAS and expression signature profiling relevant to the skeletal system in cellular and animal models to prioritize the discovery of novel candidate genes for osteoporosis-related traits, including bone mineral density (BMD) at the lumbar spine (LS) and femoral neck (FN), as well as geometric indices of the hip (femoral neck-shaft angle, NSA; femoral neck length, NL; and narrow-neck width, NW). A two-stage meta-analysis of GWAS from 7,633 Caucasian women and 3,657 men, revealed three novel loci associated with osteoporosis-related traits, including chromosome 1p13.2 (RAP1A, p = 3.6×10−8), 2q11.2 (TBC1D8), and 18q11.2 (OSBPL1A), and confirmed a previously reported region near TNFRSF11B/OPG gene. We also prioritized 16 suggestive genome-wide significant candidate genes based on their potential involvement in skeletal metabolism. Among them, 3 candidate genes were associated with BMD in women. Notably, 2 out of these 3 genes (GPR177, p = 2.6×10−13; SOX6, p = 6.4×10−10) associated with BMD in women have been successfully replicated in a large-scale meta-analysis of BMD, but none of the non-prioritized candidates (associated with BMD) did. Our results support the concept of our prioritization strategy. In the absence of direct biological support for identified genes, we highlighted the efficiency of subsequent functional characterization using publicly available expression profiling relevant to the skeletal system in cellular or whole animal models to prioritize candidate genes for further functional validation. PMID:20548944

Association genetics of coastal Douglas fir (Pseudotsuga menziesii var. menziesii, Pinaceae). I. Cold-hardiness related traits.

PubMed

Eckert, Andrew J; Bower, Andrew D; Wegrzyn, Jill L; Pande, Barnaly; Jermstad, Kathleen D; Krutovsky, Konstantin V; St Clair, J Bradley; Neale, David B

2009-08-01

Adaptation to cold is one of the greatest challenges to forest trees. This process is highly synchronized with environmental cues relating to photoperiod and temperature. Here, we use a candidate gene-based approach to search for genetic associations between 384 single-nucleotide polymorphism (SNP) markers from 117 candidate genes and 21 cold-hardiness related traits. A general linear model approach, including population structure estimates as covariates, was implemented for each marker-trait pair. We discovered 30 highly significant genetic associations [false discovery rate (FDR) Q < 0.10] across 12 candidate genes and 10 of the 21 traits. We also detected a set of 7 markers that had elevated levels of differentiation between sampling sites situated across the Cascade crest in northeastern Washington. Marker effects were small (r(2) < 0.05) and within the range of those published previously for forest trees. The derived SNP allele, as measured by a comparison to a recently diverged sister species, typically affected the phenotype in a way consistent with cold hardiness. The majority of markers were characterized as having largely nonadditive modes of gene action, especially underdominance in the case of cold-tolerance related phenotypes. We place these results in the context of trade-offs between the abilities to grow longer and to avoid fall cold damage, as well as putative epigenetic effects. These associations provide insight into the genetic components of complex traits in coastal Douglas fir, as well as highlight the need for landscape genetic approaches to the detection of adaptive genetic diversity.

Association analysis of the monoamine oxidase A gene in bipolar affective disorder by using family-based internal controls

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

Noethen, M.M.; Eggermann, K.; Propping, P.

1995-10-01

It is well accepted that association studies are a major tool in investigating the contribution of single genes to the development of diseases that do not follow simple Mendelian inheritance pattern (so-called complex traits). Such major psychiatric diseases as bipolar affective disorder and schizophrenia clearly fall into this category of diseases. 7 refs., 1 tab.

Testing cross-phenotype effects of rare variants in longitudinal studies of complex traits.

PubMed

Rudra, Pratyaydipta; Broadaway, K Alaine; Ware, Erin B; Jhun, Min A; Bielak, Lawrence F; Zhao, Wei; Smith, Jennifer A; Peyser, Patricia A; Kardia, Sharon L R; Epstein, Michael P; Ghosh, Debashis

2018-06-01

Many gene mapping studies of complex traits have identified genes or variants that influence multiple phenotypes. With the advent of next-generation sequencing technology, there has been substantial interest in identifying rare variants in genes that possess cross-phenotype effects. In the presence of such effects, modeling both the phenotypes and rare variants collectively using multivariate models can achieve higher statistical power compared to univariate methods that either model each phenotype separately or perform separate tests for each variant. Several studies collect phenotypic data over time and using such longitudinal data can further increase the power to detect genetic associations. Although rare-variant approaches exist for testing cross-phenotype effects at a single time point, there is no analogous method for performing such analyses using longitudinal outcomes. In order to fill this important gap, we propose an extension of Gene Association with Multiple Traits (GAMuT) test, a method for cross-phenotype analysis of rare variants using a framework based on the distance covariance. The approach allows for both binary and continuous phenotypes and can also adjust for covariates. Our simple adjustment to the GAMuT test allows it to handle longitudinal data and to gain power by exploiting temporal correlation. The approach is computationally efficient and applicable on a genome-wide scale due to the use of a closed-form test whose significance can be evaluated analytically. We use simulated data to demonstrate that our method has favorable power over competing approaches and also apply our approach to exome chip data from the Genetic Epidemiology Network of Arteriopathy. © 2018 WILEY PERIODICALS, INC.

Pathway-Based Genome-Wide Association Studies for Two Meat Production Traits in Simmental Cattle.

PubMed

Fan, Huizhong; Wu, Yang; Zhou, Xiaojing; Xia, Jiangwei; Zhang, Wengang; Song, Yuxin; Liu, Fei; Chen, Yan; Zhang, Lupei; Gao, Xue; Gao, Huijiang; Li, Junya

2015-12-17

Most single nucleotide polymorphisms (SNPs) detected by genome-wide association studies (GWAS), explain only a small fraction of phenotypic variation. Pathway-based GWAS were proposed to improve the proportion of genes for some human complex traits that could be explained by enriching a mass of SNPs within genetic groups. However, few attempts have been made to describe the quantitative traits in domestic animals. In this study, we used a dataset with approximately 7,700,000 SNPs from 807 Simmental cattle and analyzed live weight and longissimus muscle area using a modified pathway-based GWAS method to orthogonalise the highly linked SNPs within each gene using principal component analysis (PCA). As a result, of the 262 biological pathways of cattle collected from the KEGG database, the gamma aminobutyric acid (GABA)ergic synapse pathway and the non-alcoholic fatty liver disease (NAFLD) pathway were significantly associated with the two traits analyzed. The GABAergic synapse pathway was biologically applicable to the traits analyzed because of its roles in feed intake and weight gain. The proposed method had high statistical power and a low false discovery rate, compared to those of the smallest P-value and SNP set enrichment analysis methods.

Quantitative genetic methods depending on the nature of the phenotypic trait.

PubMed

de Villemereuil, Pierre

2018-01-24

A consequence of the assumptions of the infinitesimal model, one of the most important theoretical foundations of quantitative genetics, is that phenotypic traits are predicted to be most often normally distributed (so-called Gaussian traits). But phenotypic traits, especially those interesting for evolutionary biology, might be shaped according to very diverse distributions. Here, I show how quantitative genetics tools have been extended to account for a wider diversity of phenotypic traits using first the threshold model and then more recently using generalized linear mixed models. I explore the assumptions behind these models and how they can be used to study the genetics of non-Gaussian complex traits. I also comment on three recent methodological advances in quantitative genetics that widen our ability to study new kinds of traits: the use of "modular" hierarchical modeling (e.g., to study survival in the context of capture-recapture approaches for wild populations); the use of aster models to study a set of traits with conditional relationships (e.g., life-history traits); and, finally, the study of high-dimensional traits, such as gene expression. © 2018 New York Academy of Sciences.

The butterfly plant arms-race escalated by gene and genome duplications

PubMed Central

Edger, Patrick P.; Heidel-Fischer, Hanna M.; Bekaert, Michaël; Rota, Jadranka; Glöckner, Gernot; Platts, Adrian E.; Heckel, David G.; Der, Joshua P.; Wafula, Eric K.; Tang, Michelle; Hofberger, Johannes A.; Smithson, Ann; Hall, Jocelyn C.; Blanchette, Matthieu; Bureau, Thomas E.; Wright, Stephen I.; dePamphilis, Claude W.; Eric Schranz, M.; Barker, Michael S.; Conant, Gavin C.; Wahlberg, Niklas; Vogel, Heiko; Pires, J. Chris; Wheat, Christopher W.

2015-01-01

Coevolutionary interactions are thought to have spurred the evolution of key innovations and driven the diversification of much of life on Earth. However, the genetic and evolutionary basis of the innovations that facilitate such interactions remains poorly understood. We examined the coevolutionary interactions between plants (Brassicales) and butterflies (Pieridae), and uncovered evidence for an escalating evolutionary arms-race. Although gradual changes in trait complexity appear to have been facilitated by allelic turnover, key innovations are associated with gene and genome duplications. Furthermore, we show that the origins of both chemical defenses and of molecular counter adaptations were associated with shifts in diversification rates during the arms-race. These findings provide an important connection between the origins of biodiversity, coevolution, and the role of gene and genome duplications as a substrate for novel traits. PMID:26100883

The butterfly plant arms-race escalated by gene and genome duplications.

PubMed

Edger, Patrick P; Heidel-Fischer, Hanna M; Bekaert, Michaël; Rota, Jadranka; Glöckner, Gernot; Platts, Adrian E; Heckel, David G; Der, Joshua P; Wafula, Eric K; Tang, Michelle; Hofberger, Johannes A; Smithson, Ann; Hall, Jocelyn C; Blanchette, Matthieu; Bureau, Thomas E; Wright, Stephen I; dePamphilis, Claude W; Eric Schranz, M; Barker, Michael S; Conant, Gavin C; Wahlberg, Niklas; Vogel, Heiko; Pires, J Chris; Wheat, Christopher W

2015-07-07

Coevolutionary interactions are thought to have spurred the evolution of key innovations and driven the diversification of much of life on Earth. However, the genetic and evolutionary basis of the innovations that facilitate such interactions remains poorly understood. We examined the coevolutionary interactions between plants (Brassicales) and butterflies (Pieridae), and uncovered evidence for an escalating evolutionary arms-race. Although gradual changes in trait complexity appear to have been facilitated by allelic turnover, key innovations are associated with gene and genome duplications. Furthermore, we show that the origins of both chemical defenses and of molecular counter adaptations were associated with shifts in diversification rates during the arms-race. These findings provide an important connection between the origins of biodiversity, coevolution, and the role of gene and genome duplications as a substrate for novel traits.

Genetics and Genomics of Single-Gene Cardiovascular Diseases: Common Hereditary Cardiomyopathies as Prototypes of Single-Gene Disorders

PubMed Central

Marian, Ali J.; van Rooij, Eva; Roberts, Robert

2016-01-01

This is the first of 2 review papers on genetics and genomics appearing as part of the series on “omics.” Genomics pertains to all components of an organism’s genes, whereas genetics involves analysis of a specific gene(s) in the context of heredity. The paper provides introductory comments, describes the basis of human genetic diversity, and addresses the phenotypic consequences of genetic variants. Rare variants with large effect sizes are responsible for single-gene disorders, whereas complex polygenic diseases are typically due to multiple genetic variants, each exerting a modest effect size. To illustrate the clinical implications of genetic variants with large effect sizes, 3 common forms of hereditary cardiomyopathies are discussed as prototypic examples of single-gene disorders, including their genetics, clinical manifestations, pathogenesis, and treatment. The genetic basis of complex traits is discussed in a separate paper. PMID:28007145

FOLATE AND HUMAN DEVELOPMENT: PREFACE

EPA Science Inventory

Neural tube defects (NTDs) are a complex developmental trait in which several genes, interacting with environmental factors, create the phenotype. In the United States, the rate of NTDs has been reported to range from 4 to 10 per 10,000 live births, and NTDs affect approximately...

Endurance Exercise Ability in the Horse: A Trait with Complex Polygenic Determinism

PubMed Central

Ricard, Anne; Robert, Céline; Blouin, Christine; Baste, Fanny; Torquet, Gwendoline; Morgenthaler, Caroline; Rivière, Julie; Mach, Nuria; Mata, Xavier; Schibler, Laurent; Barrey, Eric

2017-01-01

Endurance horses are able to run at more than 20 km/h for 160 km (in bouts of 30–40 km). This level of performance is based on intense aerobic metabolism, effective body heat dissipation and the ability to endure painful exercise. The known heritabilities of endurance performance and exercise-related physiological traits in Arabian horses suggest that adaptation to extreme endurance exercise is influenced by genetic factors. The objective of the present genome-wide association study (GWAS) was to identify single nucleotide polymorphisms (SNPs) related to endurance racing performance in 597 Arabian horses. The performance traits studied were the total race distance, average race speed and finishing status (qualified, eliminated or retired). We used three mixed models that included a fixed allele or genotype effect and a random, polygenic effect. Quantile-quantile plots were acceptable, and the regression coefficients for actual vs. expected log10 p-values ranged from 0.865 to 1.055. The GWAS revealed five significant quantitative trait loci (QTL) corresponding to 6 SNPs on chromosomes 6, 1, 7, 16, and 29 (two SNPs) with corrected p-values from 1.7 × 10−6 to 1.8 × 10−5. Annotation of these 5 QTL revealed two genes: sortilin-related VPS10-domain-containing receptor 3 (SORCS3) on chromosome 1 is involved in protein trafficking, and solute carrier family 39 member 12 (SLC39A12) on chromosome 29 is active in zinc transport and cell homeostasis. These two coding genes could be involved in neuronal tissues (CNS). The other QTL on chromosomes 6, 7, and 16 may be involved in the regulation of the gene expression through non-coding RNAs, CpG islands and transcription factor binding sites. On chromosome 6, a new candidate equine long non-coding RNA (KCNQ1OT1 ortholog: opposite antisense transcript 1 of potassium voltage-gated channel subfamily Q member 1 gene) was predicted in silico and validated by RT-qPCR in primary cultures of equine myoblasts and fibroblasts. This lncRNA could be one element of the cardiac rhythm regulation. Our GWAS revealed that equine performance during endurance races is a complex polygenic trait, and is partially governed by at least 5 QTL: two coding genes involved in neuronal tissues and three other loci with many regulatory functions such as slowing down heart rate. PMID:28702049

Endurance Exercise Ability in the Horse: A Trait with Complex Polygenic Determinism.

PubMed

Ricard, Anne; Robert, Céline; Blouin, Christine; Baste, Fanny; Torquet, Gwendoline; Morgenthaler, Caroline; Rivière, Julie; Mach, Nuria; Mata, Xavier; Schibler, Laurent; Barrey, Eric

2017-01-01

Endurance horses are able to run at more than 20 km/h for 160 km (in bouts of 30-40 km). This level of performance is based on intense aerobic metabolism, effective body heat dissipation and the ability to endure painful exercise. The known heritabilities of endurance performance and exercise-related physiological traits in Arabian horses suggest that adaptation to extreme endurance exercise is influenced by genetic factors. The objective of the present genome-wide association study (GWAS) was to identify single nucleotide polymorphisms (SNPs) related to endurance racing performance in 597 Arabian horses. The performance traits studied were the total race distance, average race speed and finishing status (qualified, eliminated or retired). We used three mixed models that included a fixed allele or genotype effect and a random, polygenic effect. Quantile-quantile plots were acceptable, and the regression coefficients for actual vs. expected log 10 p -values ranged from 0.865 to 1.055. The GWAS revealed five significant quantitative trait loci (QTL) corresponding to 6 SNPs on chromosomes 6, 1, 7, 16, and 29 (two SNPs) with corrected p -values from 1.7 × 10 -6 to 1.8 × 10 -5 . Annotation of these 5 QTL revealed two genes: sortilin-related VPS10-domain-containing receptor 3 ( SORCS3 ) on chromosome 1 is involved in protein trafficking, and solute carrier family 39 member 12 ( SLC39A12 ) on chromosome 29 is active in zinc transport and cell homeostasis. These two coding genes could be involved in neuronal tissues (CNS). The other QTL on chromosomes 6, 7, and 16 may be involved in the regulation of the gene expression through non-coding RNAs, CpG islands and transcription factor binding sites. On chromosome 6, a new candidate equine long non-coding RNA ( KCNQ1OT1 ortholog: opposite antisense transcript 1 of potassium voltage-gated channel subfamily Q member 1 gene) was predicted in silico and validated by RT-qPCR in primary cultures of equine myoblasts and fibroblasts. This lncRNA could be one element of the cardiac rhythm regulation. Our GWAS revealed that equine performance during endurance races is a complex polygenic trait, and is partially governed by at least 5 QTL: two coding genes involved in neuronal tissues and three other loci with many regulatory functions such as slowing down heart rate.

From integrative genomics to systems genetics in the rat to link genotypes to phenotypes

PubMed Central

Moreno-Moral, Aida

2016-01-01

ABSTRACT Complementary to traditional gene mapping approaches used to identify the hereditary components of complex diseases, integrative genomics and systems genetics have emerged as powerful strategies to decipher the key genetic drivers of molecular pathways that underlie disease. Broadly speaking, integrative genomics aims to link cellular-level traits (such as mRNA expression) to the genome to identify their genetic determinants. With the characterization of several cellular-level traits within the same system, the integrative genomics approach evolved into a more comprehensive study design, called systems genetics, which aims to unravel the complex biological networks and pathways involved in disease, and in turn map their genetic control points. The first fully integrated systems genetics study was carried out in rats, and the results, which revealed conserved trans-acting genetic regulation of a pro-inflammatory network relevant to type 1 diabetes, were translated to humans. Many studies using different organisms subsequently stemmed from this example. The aim of this Review is to describe the most recent advances in the fields of integrative genomics and systems genetics applied in the rat, with a focus on studies of complex diseases ranging from inflammatory to cardiometabolic disorders. We aim to provide the genetics community with a comprehensive insight into how the systems genetics approach came to life, starting from the first integrative genomics strategies [such as expression quantitative trait loci (eQTLs) mapping] and concluding with the most sophisticated gene network-based analyses in multiple systems and disease states. Although not limited to studies that have been directly translated to humans, we will focus particularly on the successful investigations in the rat that have led to primary discoveries of genes and pathways relevant to human disease. PMID:27736746

From integrative genomics to systems genetics in the rat to link genotypes to phenotypes.

PubMed

Moreno-Moral, Aida; Petretto, Enrico

2016-10-01

Complementary to traditional gene mapping approaches used to identify the hereditary components of complex diseases, integrative genomics and systems genetics have emerged as powerful strategies to decipher the key genetic drivers of molecular pathways that underlie disease. Broadly speaking, integrative genomics aims to link cellular-level traits (such as mRNA expression) to the genome to identify their genetic determinants. With the characterization of several cellular-level traits within the same system, the integrative genomics approach evolved into a more comprehensive study design, called systems genetics, which aims to unravel the complex biological networks and pathways involved in disease, and in turn map their genetic control points. The first fully integrated systems genetics study was carried out in rats, and the results, which revealed conserved trans-acting genetic regulation of a pro-inflammatory network relevant to type 1 diabetes, were translated to humans. Many studies using different organisms subsequently stemmed from this example. The aim of this Review is to describe the most recent advances in the fields of integrative genomics and systems genetics applied in the rat, with a focus on studies of complex diseases ranging from inflammatory to cardiometabolic disorders. We aim to provide the genetics community with a comprehensive insight into how the systems genetics approach came to life, starting from the first integrative genomics strategies [such as expression quantitative trait loci (eQTLs) mapping] and concluding with the most sophisticated gene network-based analyses in multiple systems and disease states. Although not limited to studies that have been directly translated to humans, we will focus particularly on the successful investigations in the rat that have led to primary discoveries of genes and pathways relevant to human disease. © 2016. Published by The Company of Biologists Ltd.

Brain derived neurotrophic factor gene (BDNF) and personality traits: the modifying effect of season of birth and sex.

PubMed

Kazantseva, A; Gaysina, D; Kutlumbetova, Yu; Kanzafarova, R; Malykh, S; Lobaskova, M; Khusnutdinova, E

2015-01-02

Personality traits are complex phenotypes influenced by interactions of multiple genetic variants of small effect and environmental factors. It has been suggested that the brain derived neurotrophic factor gene (BDNF) is involved in personality traits. Season of birth (SOB) has also been shown to affect personality traits due to its influences on brain development during prenatal and early postnatal periods. The present study aimed to investigate the effects of BDNF on personality traits; and the modifying effects of SOB and sex on associations between BDNF and personality traits. A sample of 1018 young adults (68% women; age range 17-25years) of Caucasian origin from the Russian Federation was assessed on personality traits (Novelty Seeking, Harm Avoidance, Reward Dependence, Persistence, Self-directedness, Cooperativeness, Self-transcendence) with the Temperament and Character Inventory-125 (TCI-125). Associations between personality traits and 12 BDNF SNPs were tested using linear regression models. The present study demonstrated the effect of rs11030102 on Persistence in females only (PFDR=0.043; r(2)=1.3%). There were significant interaction effects between Val66Met (rs6265) and SOB (PFDR=0.048, r(2)=1.4%), and between rs2030323 and SOB (PFDR=0.042, r(2)=1.3%), on Harm Avoidance. Our findings provide evidence for the modifying effect of SOB on the association between BDNF and Harm Avoidance, and for the modifying effect of sex on the association between BDNF and Persistence. Copyright © 2014 Elsevier Inc. All rights reserved.

Sequential recruitment of study participants may inflate genetic heritability estimates.

PubMed

Noce, Damia; Gögele, Martin; Schwienbacher, Christine; Caprioli, Giulia; De Grandi, Alessandro; Foco, Luisa; Platzgummer, Stefan; Pramstaller, Peter P; Pattaro, Cristian

2017-06-01

After the success of genome-wide association studies to uncover complex trait loci, attempts to explain the remaining genetic heritability (h 2 ) are mainly focused on unraveling rare variant associations and gene-gene or gene-environment interactions. Little attention is paid to the possibility that h 2 estimates are inflated as a consequence of the epidemiological study design. We studied the time series of 54 biochemical traits in 4373 individuals from the Cooperative Health Research In South Tyrol (CHRIS) study, a pedigree-based study enrolling ten participants/day over several years, with close relatives preferentially invited within the same day. We observed distributional changes of measured traits over time. We hypothesized that the combination of such changes with the pedigree structure might generate a shared-environment component with consequent h 2 inflation. We performed variance components (VC) h 2 estimation for all traits after accounting for the enrollment period in a linear mixed model (two-stage approach). Accounting for the enrollment period caused a median h 2 reduction of 4%. For 9 traits, the reduction was of >20%. Results were confirmed by a Bayesian Markov chain Monte Carlo analysis with all VCs included at the same time (one-stage approach). The electrolytes were the traits most affected by the enrollment period. The h 2 inflation was independent of the h 2 magnitude, laboratory protocol changes, and length of the enrollment period. The enrollment process may induce shared-environment effects even under very stringent and standardized operating procedures, causing h 2 inflation. Including the day of participation as a random effect is a sensitive way to avoid overestimation.

Berry and phenology-related traits in grapevine (Vitis vinifera L.): From Quantitative Trait Loci to underlying genes

PubMed Central

Costantini, Laura; Battilana, Juri; Lamaj, Flutura; Fanizza, Girolamo; Grando, Maria Stella

2008-01-01

Background The timing of grape ripening initiation, length of maturation period, berry size and seed content are target traits in viticulture. The availability of early and late ripening varieties is desirable for staggering harvest along growing season, expanding production towards periods when the fruit gets a higher value in the market and ensuring an optimal plant adaptation to climatic and geographic conditions. Berry size determines grape productivity; seedlessness is especially demanded in the table grape market and is negatively correlated to fruit size. These traits result from complex developmental processes modified by genetic, physiological and environmental factors. In order to elucidate their genetic determinism we carried out a quantitative analysis in a 163 individuals-F1 segregating progeny obtained by crossing two table grape cultivars. Results Molecular linkage maps covering most of the genome (2n = 38 for Vitis vinifera) were generated for each parent. Eighteen pairs of homologous groups were integrated into a consensus map spanning over 1426 cM with 341 markers (mainly microsatellite, AFLP and EST-derived markers) and an average map distance between loci of 4.2 cM. Segregating traits were evaluated in three growing seasons by recording flowering, veraison and ripening dates and by measuring berry size, seed number and weight. QTL (Quantitative Trait Loci) analysis was carried out based on single marker and interval mapping methods. QTLs were identified for all but one of the studied traits, a number of them steadily over more than one year. Clusters of QTLs for different characters were detected, suggesting linkage or pleiotropic effects of loci, as well as regions affecting specific traits. The most interesting QTLs were investigated at the gene level through a bioinformatic analysis of the underlying Pinot noir genomic sequence. Conclusion Our results revealed novel insights into the genetic control of relevant grapevine features. They provide a basis for performing marker-assisted selection and testing the role of specific genes in trait variation. PMID:18419811

Fitness and Individuality in Complex Life Cycles.

PubMed

Herron, Matthew D

2016-12-01

Complex life cycles are common in the eukaryotic world, and they complicate the question of how to define individuality. Using a bottom-up, gene-centric approach, I consider the concept of fitness in the context of complex life cycles. I analyze the fitness effects of an allele (or a trait) on different biological units within a complex life history and how these effects drive evolutionary change within populations. Based on these effects, I attempt to construct a concept of fitness that accurately predicts evolutionary change in the context of complex life cycles.

Animal models and conserved processes

PubMed Central

2012-01-01

Background The concept of conserved processes presents unique opportunities for using nonhuman animal models in biomedical research. However, the concept must be examined in the context that humans and nonhuman animals are evolved, complex, adaptive systems. Given that nonhuman animals are examples of living systems that are differently complex from humans, what does the existence of a conserved gene or process imply for inter-species extrapolation? Methods We surveyed the literature including philosophy of science, biological complexity, conserved processes, evolutionary biology, comparative medicine, anti-neoplastic agents, inhalational anesthetics, and drug development journals in order to determine the value of nonhuman animal models when studying conserved processes. Results Evolution through natural selection has employed components and processes both to produce the same outcomes among species but also to generate different functions and traits. Many genes and processes are conserved, but new combinations of these processes or different regulation of the genes involved in these processes have resulted in unique organisms. Further, there is a hierarchy of organization in complex living systems. At some levels, the components are simple systems that can be analyzed by mathematics or the physical sciences, while at other levels the system cannot be fully analyzed by reducing it to a physical system. The study of complex living systems must alternate between focusing on the parts and examining the intact whole organism while taking into account the connections between the two. Systems biology aims for this holism. We examined the actions of inhalational anesthetic agents and anti-neoplastic agents in order to address what the characteristics of complex living systems imply for inter-species extrapolation of traits and responses related to conserved processes. Conclusion We conclude that even the presence of conserved processes is insufficient for inter-species extrapolation when the trait or response being studied is located at higher levels of organization, is in a different module, or is influenced by other modules. However, when the examination of the conserved process occurs at the same level of organization or in the same module, and hence is subject to study solely by reductionism, then extrapolation is possible. PMID:22963674

Association genetics and transcriptome analysis reveal a gibberellin-responsive pathway involved in regulating photosynthesis.

PubMed

Xie, Jianbo; Tian, Jiaxing; Du, Qingzhang; Chen, Jinhui; Li, Ying; Yang, Xiaohui; Li, Bailian; Zhang, Deqiang

2016-05-01

Gibberellins (GAs) regulate a wide range of important processes in plant growth and development, including photosynthesis. However, the mechanism by which GAs regulate photosynthesis remains to be understood. Here, we used multi-gene association to investigate the effect of genes in the GA-responsive pathway, as constructed by RNA sequencing, on photosynthesis, growth, and wood property traits, in a population of 435 Populus tomentosa By analyzing changes in the transcriptome following GA treatment, we identified many key photosynthetic genes, in agreement with the observed increase in measurements of photosynthesis. Regulatory motif enrichment analysis revealed that 37 differentially expressed genes related to photosynthesis shared two essential GA-related cis-regulatory elements, the GA response element and the pyrimidine box. Thus, we constructed a GA-responsive pathway consisting of 47 genes involved in regulating photosynthesis, including GID1, RGA, GID2, MYBGa, and 37 photosynthetic differentially expressed genes. Single nucleotide polymorphism (SNP)-based association analysis showed that 142 SNPs, representing 40 candidate genes in this pathway, were significantly associated with photosynthesis, growth, and wood property traits. Epistasis analysis uncovered interactions between 310 SNP-SNP pairs from 37 genes in this pathway, revealing possible genetic interactions. Moreover, a structural gene-gene matrix based on a time-course of transcript abundances provided a better understanding of the multi-gene pathway affecting photosynthesis. The results imply a functional role for these genes in mediating photosynthesis, growth, and wood properties, demonstrating the potential of combining transcriptome-based regulatory pathway construction and genetic association approaches to detect the complex genetic networks underlying quantitative traits. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Identification of Genes Upregulated by the Transcription Factor Bcr1 That Are Involved in Impermeability, Impenetrability, and Drug Resistance of Candida albicans a/α Biofilms

PubMed Central

Srikantha, Thyagarajan; Daniels, Karla J.; Pujol, Claude; Kim, Elena

2013-01-01

Candida albicans forms two types of biofilm, depending upon the configuration of the mating type locus. Although architecturally similar, a/α biofilms are impermeable, impenetrable, and drug resistant, whereas a/a and α/α biofilms lack these traits. The difference appears to be the result of an alternative matrix. Overexpression in a/a cells of BCR1, a master regulator of the a/α matrix, conferred impermeability, impenetrability, and drug resistance to a/a biofilms. Deletion of BCR1 in a/α cells resulted in the loss of these a/α-specific biofilm traits. Using BCR1 overexpression in a/a cells, we screened 107 genes of interest and identified 8 that were upregulated by Bcr1. When each was overexpressed in a/a biofilms, the three a/α traits were partially conferred, and when each was deleted in a/α cells, the traits were partially lost. Five of the eight genes have been implicated in iron homeostasis, and six encode proteins that are either in the wall or plasma membrane or secreted. All six possess sites for O-linked and N-linked glycosylation that, like glycosylphosphatidylinositol (GPI) anchors, can cross-link to the wall and matrix, suggesting that they may exert a structural role in conferring impermeability, impenetrability, and drug resistance, in addition to their physiological functions. The fact that in a screen of 107 genes, all 8 of the Bcr1-upregulated genes identified play a role in impermeability, impenetrability, and drug resistance suggests that the formation of the a/α matrix is highly complex and involves a larger number of genes than the initial ones identified here. PMID:23563485

Whole-Genome Resequencing of Experimental Populations Reveals Polygenic Basis of Egg-Size Variation in Drosophila melanogaster.

PubMed

Jha, Aashish R; Miles, Cecelia M; Lippert, Nodia R; Brown, Christopher D; White, Kevin P; Kreitman, Martin

2015-10-01

Complete genome resequencing of populations holds great promise in deconstructing complex polygenic traits to elucidate molecular and developmental mechanisms of adaptation. Egg size is a classic adaptive trait in insects, birds, and other taxa, but its highly polygenic architecture has prevented high-resolution genetic analysis. We used replicated experimental evolution in Drosophila melanogaster and whole-genome sequencing to identify consistent signatures of polygenic egg-size adaptation. A generalized linear-mixed model revealed reproducible allele frequency differences between replicated experimental populations selected for large and small egg volumes at approximately 4,000 single nucleotide polymorphisms (SNPs). Several hundred distinct genomic regions contain clusters of these SNPs and have lower heterozygosity than the genomic background, consistent with selection acting on polymorphisms in these regions. These SNPs are also enriched among genes expressed in Drosophila ovaries and many of these genes have well-defined functions in Drosophila oogenesis. Additional genes regulating egg development, growth, and cell size show evidence of directional selection as genes regulating these biological processes are enriched for highly differentiated SNPs. Genetic crosses performed with a subset of candidate genes demonstrated that these genes influence egg size, at least in the large genetic background. These findings confirm the highly polygenic architecture of this adaptive trait, and suggest the involvement of many novel candidate genes in regulating egg size. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Diagnostic difficulty of beta-thalassemia syndrome in a multi-transfused patient: contribution of myelogram and studying parents.

PubMed

Trawinski, Élisabeth; Fenneteau, Odile; Le Mouel, Lou; Ithier, Ghislaine; Couque, Nathalie

2017-10-01

We report the case of a 5 year old, initially followed for congenital sideroblastic anemia, whose explorations reveal a complex family hemoglobinopathy. Myelogram performed in children, reveals dystrophic mature erythroblasts with hemoglobinization defect and basophil punctuations. These abnormalities point towards an abnormal synthesis of heme or globin chains. Iterative transfusions in child do not allow interpreting a search for abnormal hemoglobin. However, the analysis carried out in his parents, with increased HBA2 rate and microcytosis concluded in beta-thalassemia trait for father and mother. Knowing that beta-thalassemia syndrome is a genetic condition, usually recessive, the presence of beta-thalassemia trait in parents is in favor of a beta-thalassemia syndrome in child. This diagnostic hypothesis is confirmed by molecular study of globin genes that will reveal a complex hemoglobinopathie for all family's members. The parents are carriers for heterozygous mutation of β + thalassemia that the sick child presents in homozygous state supporting the diagnosis of beta-thalassemia syndrome. Moreover, a triple α globin gene is present respectively at heterozygous state for mother and at homozygous state for father and child. The triple α globin gene is a known factor of aggravation of beta-thalassemia and this clinical case with continuum observed, perfectly illustrates the intricacies between α and β globin genes.

Associating quantitative behavioral traits with gene expression in the brain: searching for diamonds in the hay.

PubMed

Reiner-Benaim, Anat; Yekutieli, Daniel; Letwin, Noah E; Elmer, Gregory I; Lee, Norman H; Kafkafi, Neri; Benjamini, Yoav

2007-09-01

Gene expression and phenotypic functionality can best be associated when they are measured quantitatively within the same experiment. The analysis of such a complex experiment is presented, searching for associations between measures of exploratory behavior in mice and gene expression in brain regions. The analysis of such experiments raises several methodological problems. First and foremost, the size of the pool of potential discoveries being screened is enormous yet only few biologically relevant findings are expected, making the problem of multiple testing especially severe. We present solutions based on screening by testing related hypotheses, then testing the hypotheses of interest. In one variant the subset is selected directly, in the other one a tree of hypotheses is tested hierarchical; both variants control the False Discovery Rate (FDR). Other problems in such experiments are in the fact that the level of data aggregation may be different for the quantitative traits (one per animal) and gene expression measurements (pooled across animals); in that the association may not be linear; and in the resolution of interest only few replications exist. We offer solutions to these problems as well. The hierarchical FDR testing strategies presented here can serve beyond the structure of our motivating example study to any complex microarray study. Supplementary data are available at Bioinformatics online.

Evidence of linkage of HDL level variation to APOC3 in two samples with different ascertainment.

PubMed

Gagnon, France; Jarvik, Gail P; Motulsky, Arno G; Deeb, Samir S; Brunzell, John D; Wijsman, Ellen M

2003-11-01

The APOA1-C3-A4-A5 gene complex encodes genes whose products are implicated in the metabolism of HDL and/or triglycerides. Although the relationship between polymorphisms in this gene cluster and dyslipidemias was first reported more than 15 years ago, association and linkage results have remained inconclusive. This is due, in part, to the oligogenic and multivariate nature of dyslipidemic phenotypes. Therefore, we investigate evidence of linkage of APOC3 and HDL using two samples of dyslipidemic pedigrees: familial combined hyperlipidemia (FCHL) and isolated low-HDL (ILHDL). We used a strategy that deals with several difficulties inherent in the study of complex traits: by using a Bayesian Markov Chain Monte Carlo (MCMC) approach we allow for oligogenic trait models, as well as simultaneous incorporation of covariates, in the context of multipoint analysis. By using this approach on extended pedigrees we provide evidence of linkage of APOC3 and HDL level variation in two samples with different ascertainment. In addition to APOC3, we estimate that two to three genes, each with a substantial effect on total variance, are responsible for HDL variation in both data sets. We also provide evidence, using the FCHL data set, for a pleiotropic effect between HDL, HDL3 and triglycerides at the APOC3 locus.

[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.

Genome sequencing reveals loci under artificial selection that underlie disease phenotypes in the laboratory rat.

PubMed

Atanur, Santosh S; Diaz, Ana Garcia; Maratou, Klio; Sarkis, Allison; Rotival, Maxime; Game, Laurence; Tschannen, Michael R; Kaisaki, Pamela J; Otto, Georg W; Ma, Man Chun John; Keane, Thomas M; Hummel, Oliver; Saar, Kathrin; Chen, Wei; Guryev, Victor; Gopalakrishnan, Kathirvel; Garrett, Michael R; Joe, Bina; Citterio, Lorena; Bianchi, Giuseppe; McBride, Martin; Dominiczak, Anna; Adams, David J; Serikawa, Tadao; Flicek, Paul; Cuppen, Edwin; Hubner, Norbert; Petretto, Enrico; Gauguier, Dominique; Kwitek, Anne; Jacob, Howard; Aitman, Timothy J

2013-08-01

Large numbers of inbred laboratory rat strains have been developed for a range of complex disease phenotypes. To gain insights into the evolutionary pressures underlying selection for these phenotypes, we sequenced the genomes of 27 rat strains, including 11 models of hypertension, diabetes, and insulin resistance, along with their respective control strains. Altogether, we identified more than 13 million single-nucleotide variants, indels, and structural variants across these rat strains. Analysis of strain-specific selective sweeps and gene clusters implicated genes and pathways involved in cation transport, angiotensin production, and regulators of oxidative stress in the development of cardiovascular disease phenotypes in rats. Many of the rat loci that we identified overlap with previously mapped loci for related traits in humans, indicating the presence of shared pathways underlying these phenotypes in rats and humans. These data represent a step change in resources available for evolutionary analysis of complex traits in disease models. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Genome Sequencing Reveals Loci under Artificial Selection that Underlie Disease Phenotypes in the Laboratory Rat

PubMed Central

Atanur, Santosh S.; Diaz, Ana Garcia; Maratou, Klio; Sarkis, Allison; Rotival, Maxime; Game, Laurence; Tschannen, Michael R.; Kaisaki, Pamela J.; Otto, Georg W.; Ma, Man Chun John; Keane, Thomas M.; Hummel, Oliver; Saar, Kathrin; Chen, Wei; Guryev, Victor; Gopalakrishnan, Kathirvel; Garrett, Michael R.; Joe, Bina; Citterio, Lorena; Bianchi, Giuseppe; McBride, Martin; Dominiczak, Anna; Adams, David J.; Serikawa, Tadao; Flicek, Paul; Cuppen, Edwin; Hubner, Norbert; Petretto, Enrico; Gauguier, Dominique; Kwitek, Anne; Jacob, Howard; Aitman, Timothy J.

2013-01-01

Summary Large numbers of inbred laboratory rat strains have been developed for a range of complex disease phenotypes. To gain insights into the evolutionary pressures underlying selection for these phenotypes, we sequenced the genomes of 27 rat strains, including 11 models of hypertension, diabetes, and insulin resistance, along with their respective control strains. Altogether, we identified more than 13 million single-nucleotide variants, indels, and structural variants across these rat strains. Analysis of strain-specific selective sweeps and gene clusters implicated genes and pathways involved in cation transport, angiotensin production, and regulators of oxidative stress in the development of cardiovascular disease phenotypes in rats. Many of the rat loci that we identified overlap with previously mapped loci for related traits in humans, indicating the presence of shared pathways underlying these phenotypes in rats and humans. These data represent a step change in resources available for evolutionary analysis of complex traits in disease models. PaperClip PMID:23890820

A Model of Compound Heterozygous, Loss-of-Function Alleles Is Broadly Consistent with Observations from Complex-Disease GWAS Datasets

PubMed Central

Sanjak, Jaleal S.; Long, Anthony D.; Thornton, Kevin R.

2017-01-01

The genetic component of complex disease risk in humans remains largely unexplained. A corollary is that the allelic spectrum of genetic variants contributing to complex disease risk is unknown. Theoretical models that relate population genetic processes to the maintenance of genetic variation for quantitative traits may suggest profitable avenues for future experimental design. Here we use forward simulation to model a genomic region evolving under a balance between recurrent deleterious mutation and Gaussian stabilizing selection. We consider multiple genetic and demographic models, and several different methods for identifying genomic regions harboring variants associated with complex disease risk. We demonstrate that the model of gene action, relating genotype to phenotype, has a qualitative effect on several relevant aspects of the population genetic architecture of a complex trait. In particular, the genetic model impacts genetic variance component partitioning across the allele frequency spectrum and the power of statistical tests. Models with partial recessivity closely match the minor allele frequency distribution of significant hits from empirical genome-wide association studies without requiring homozygous effect sizes to be small. We highlight a particular gene-based model of incomplete recessivity that is appealing from first principles. Under that model, deleterious mutations in a genomic region partially fail to complement one another. This model of gene-based recessivity predicts the empirically observed inconsistency between twin and SNP based estimated of dominance heritability. Furthermore, this model predicts considerable levels of unexplained variance associated with intralocus epistasis. Our results suggest a need for improved statistical tools for region based genetic association and heritability estimation. PMID:28103232

Setaria viridis as a Model System to Advance Millet Genetics and Genomics

PubMed Central

Huang, Pu; Shyu, Christine; Coelho, Carla P.; Cao, Yingying; Brutnell, Thomas P.

2016-01-01

Millet is a common name for a group of polyphyletic, small-seeded cereal crops that include pearl, finger and foxtail millet. Millet species are an important source of calories for many societies, often in developing countries. Compared to major cereal crops such as rice and maize, millets are generally better adapted to dry and hot environments. Despite their food security value, the genetic architecture of agronomically important traits in millets, including both morphological traits and climate resilience remains poorly studied. These complex traits have been challenging to dissect in large part because of the lack of sufficient genetic tools and resources. In this article, we review the phylogenetic relationship among various millet species and discuss the value of a genetic model system for millet research. We propose that a broader adoption of green foxtail (Setaria viridis) as a model system for millets could greatly accelerate the pace of gene discovery in the millets, and summarize available and emerging resources in S. viridis and its domesticated relative S. italica. These resources have value in forward genetics, reverse genetics and high throughput phenotyping. We describe methods and strategies to best utilize these resources to facilitate the genetic dissection of complex traits. We envision that coupling cutting-edge technologies and the use of S. viridis for gene discovery will accelerate genetic research in millets in general. This will enable strategies and provide opportunities to increase productivity, especially in the semi-arid tropics of Asia and Africa where millets are staple food crops. PMID:27965689

Setaria viridis as a Model System to Advance Millet Genetics and Genomics.

PubMed

Huang, Pu; Shyu, Christine; Coelho, Carla P; Cao, Yingying; Brutnell, Thomas P

2016-01-01

Millet is a common name for a group of polyphyletic, small-seeded cereal crops that include pearl, finger and foxtail millet. Millet species are an important source of calories for many societies, often in developing countries. Compared to major cereal crops such as rice and maize, millets are generally better adapted to dry and hot environments. Despite their food security value, the genetic architecture of agronomically important traits in millets, including both morphological traits and climate resilience remains poorly studied. These complex traits have been challenging to dissect in large part because of the lack of sufficient genetic tools and resources. In this article, we review the phylogenetic relationship among various millet species and discuss the value of a genetic model system for millet research. We propose that a broader adoption of green foxtail ( Setaria viridis ) as a model system for millets could greatly accelerate the pace of gene discovery in the millets, and summarize available and emerging resources in S. viridis and its domesticated relative S. italica . These resources have value in forward genetics, reverse genetics and high throughput phenotyping. We describe methods and strategies to best utilize these resources to facilitate the genetic dissection of complex traits. We envision that coupling cutting-edge technologies and the use of S. viridis for gene discovery will accelerate genetic research in millets in general. This will enable strategies and provide opportunities to increase productivity, especially in the semi-arid tropics of Asia and Africa where millets are staple food crops.

Host Genome Influence on Gut Microbial Composition and Microbial Prediction of Complex Traits in Pigs.

PubMed

Camarinha-Silva, Amelia; Maushammer, Maria; Wellmann, Robin; Vital, Marius; Preuss, Siegfried; Bennewitz, Jörn

2017-07-01

The aim of the present study was to analyze the interplay between gastrointestinal tract (GIT) microbiota, host genetics, and complex traits in pigs using extended quantitative-genetic methods. The study design consisted of 207 pigs that were housed and slaughtered under standardized conditions, and phenotyped for daily gain, feed intake, and feed conversion rate. The pigs were genotyped with a standard 60 K SNP chip. The GIT microbiota composition was analyzed by 16S rRNA gene amplicon sequencing technology. Eight from 49 investigated bacteria genera showed a significant narrow sense host heritability, ranging from 0.32 to 0.57. Microbial mixed linear models were applied to estimate the microbiota variance for each complex trait. The fraction of phenotypic variance explained by the microbial variance was 0.28, 0.21, and 0.16 for daily gain, feed conversion, and feed intake, respectively. The SNP data and the microbiota composition were used to predict the complex traits using genomic best linear unbiased prediction (G-BLUP) and microbial best linear unbiased prediction (M-BLUP) methods, respectively. The prediction accuracies of G-BLUP were 0.35, 0.23, and 0.20 for daily gain, feed conversion, and feed intake, respectively. The corresponding prediction accuracies of M-BLUP were 0.41, 0.33, and 0.33. Thus, in addition to SNP data, microbiota abundances are an informative source of complex trait predictions. Since the pig is a well-suited animal for modeling the human digestive tract, M-BLUP, in addition to G-BLUP, might be beneficial for predicting human predispositions to some diseases, and, consequently, for preventative and personalized medicine. Copyright © 2017 by the Genetics Society of America.

Models of Cultural Niche Construction with Selection and Assortative Mating

PubMed Central

Feldman, Marcus W.

2012-01-01

Niche construction is a process through which organisms modify their environment and, as a result, alter the selection pressures on themselves and other species. In cultural niche construction, one or more cultural traits can influence the evolution of other cultural or biological traits by affecting the social environment in which the latter traits may evolve. Cultural niche construction may include either gene-culture or culture-culture interactions. Here we develop a model of this process and suggest some applications of this model. We examine the interactions between cultural transmission, selection, and assorting, paying particular attention to the complexities that arise when selection and assorting are both present, in which case stable polymorphisms of all cultural phenotypes are possible. We compare our model to a recent model for the joint evolution of religion and fertility and discuss other potential applications of cultural niche construction theory, including the evolution and maintenance of large-scale human conflict and the relationship between sex ratio bias and marriage customs. The evolutionary framework we introduce begins to address complexities that arise in the quantitative analysis of multiple interacting cultural traits. PMID:22905167

Representation matters: quantitative behavioral variation in wild worm strains

NASA Astrophysics Data System (ADS)

Brown, Andre

Natural genetic variation in populations is the basis of genome-wide association studies, an approach that has been applied in large studies of humans to study the genetic architecture of complex traits including disease risk. Of course, the traits you choose to measure determine which associated genes you discover (or miss). In large-scale human studies, the measured traits are usually taken as a given during the association step because they are expensive to collect and standardize. Working with the nematode worm C. elegans, we do not have the same constraints. In this talk I will describe how large-scale imaging of worm behavior allows us to develop alternative representations of behavior that vary differently across wild populations. The alternative representations yield novel traits that can be used for genome-wide association studies and may reveal basic properties of the genotype-phenotype map that are obscured if only a small set of fixed traits are used.

Epistasis × environment interactions among Arabidopsis thaliana glucosinolate genes impact complex traits and fitness in the field.

PubMed

Kerwin, Rachel E; Feusier, Julie; Muok, Alise; Lin, Catherine; Larson, Brandon; Copeland, Daniel; Corwin, Jason A; Rubin, Matthew J; Francisco, Marta; Li, Baohua; Joseph, Bindu; Weinig, Cynthia; Kliebenstein, Daniel J

2017-08-01

Despite the growing number of studies showing that genotype × environment and epistatic interactions control fitness, the influences of epistasis × environment interactions on adaptive trait evolution remain largely uncharacterized. Across three field trials, we quantified aliphatic glucosinolate (GSL) defense chemistry, leaf damage, and relative fitness using mutant lines of Arabidopsis thaliana varying at pairs of causal aliphatic GSL defense genes to test the impact of epistatic and epistasis × environment interactions on adaptive trait variation. We found that aliphatic GSL accumulation was primarily influenced by additive and epistatic genetic variation, leaf damage was primarily influenced by environmental variation and relative fitness was primarily influenced by epistasis and epistasis × environment interactions. Epistasis × environment interactions accounted for up to 48% of the relative fitness variation in the field. At a single field site, the impact of epistasis on relative fitness varied significantly over 2 yr, showing that epistasis × environment interactions within a location can be temporally dynamic. These results suggest that the environmental dependency of epistasis can profoundly influence the response to selection, shaping the adaptive trajectories of natural populations in complex ways, and deserves further consideration in future evolutionary studies. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Camelina sativa, an oilseed at the nexus between model system and commercial crop.

PubMed

Malik, Meghna R; Tang, Jihong; Sharma, Nirmala; Burkitt, Claire; Ji, Yuanyuan; Mykytyshyn, Marie; Bohmert-Tatarev, Karen; Peoples, Oliver; Snell, Kristi D

2018-06-07

The rapid assessment of metabolic engineering strategies in plants is aided by crops that provide simple, high throughput transformation systems, a sequenced genome, and the ability to evaluate the resulting plants in field trials. Camelina sativa provides all of these attributes in a robust oilseed platform. The ability to perform field evaluation of Camelina is a useful, and in some studies essential benefit that allows researchers to evaluate how traits perform outside the strictly controlled conditions of a greenhouse. In the field the plants are subjected to higher light intensities, seasonal diurnal variations in temperature and light, competition for nutrients, and watering regimes dictated by natural weather patterns, all which may affect trait performance. There are difficulties associated with the use of Camelina. The current genetic resources available for Camelina pale in comparison to those developed for the model plant Arabidopsis thaliana; however, the sequence similarity of the Arabidopsis and Camelina genomes often allows the use of Arabidopsis as a reference when additional information is needed. Camelina's genome, an allohexaploid, is more complex than other model crops, but the diploid inheritance of its three subgenomes is straightforward. The need to navigate three copies of each gene in genome editing or mutagenesis experiments adds some complexity but also provides advantages for gene dosage experiments. The ability to quickly engineer Camelina with novel traits, advance generations, and bulk up homozygous lines for small-scale field tests in less than a year, in our opinion, far outweighs the complexities associated with the crop.

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.

Application of Genomic Technologies to the Breeding of Trees

PubMed Central

Badenes, Maria L.; Fernández i Martí, Angel; Ríos, Gabino; Rubio-Cabetas, María J.

2016-01-01

The recent introduction of next generation sequencing (NGS) technologies represents a major revolution in providing new tools for identifying the genes and/or genomic intervals controlling important traits for selection in breeding programs. In perennial fruit trees with long generation times and large sizes of adult plants, the impact of these techniques is even more important. High-throughput DNA sequencing technologies have provided complete annotated sequences in many important tree species. Most of the high-throughput genotyping platforms described are being used for studies of genetic diversity and population structure. Dissection of complex traits became possible through the availability of genome sequences along with phenotypic variation data, which allow to elucidate the causative genetic differences that give rise to observed phenotypic variation. Association mapping facilitates the association between genetic markers and phenotype in unstructured and complex populations, identifying molecular markers for assisted selection and breeding. Also, genomic data provide in silico identification and characterization of genes and gene families related to important traits, enabling new tools for molecular marker assisted selection in tree breeding. Deep sequencing of transcriptomes is also a powerful tool for the analysis of precise expression levels of each gene in a sample. It consists in quantifying short cDNA reads, obtained by NGS technologies, in order to compare the entire transcriptomes between genotypes and environmental conditions. The miRNAs are non-coding short RNAs involved in the regulation of different physiological processes, which can be identified by high-throughput sequencing of RNA libraries obtained by reverse transcription of purified short RNAs, and by in silico comparison with known miRNAs from other species. All together, NGS techniques and their applications have increased the resources for plant breeding in tree species, closing the former gap of genetic tools between trees and annual species. PMID:27895664

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.

Application of Genomic Technologies to the Breeding of Trees.

PubMed

Badenes, Maria L; Fernández I Martí, Angel; Ríos, Gabino; Rubio-Cabetas, María J

2016-01-01

The recent introduction of next generation sequencing (NGS) technologies represents a major revolution in providing new tools for identifying the genes and/or genomic intervals controlling important traits for selection in breeding programs. In perennial fruit trees with long generation times and large sizes of adult plants, the impact of these techniques is even more important. High-throughput DNA sequencing technologies have provided complete annotated sequences in many important tree species. Most of the high-throughput genotyping platforms described are being used for studies of genetic diversity and population structure. Dissection of complex traits became possible through the availability of genome sequences along with phenotypic variation data, which allow to elucidate the causative genetic differences that give rise to observed phenotypic variation. Association mapping facilitates the association between genetic markers and phenotype in unstructured and complex populations, identifying molecular markers for assisted selection and breeding. Also, genomic data provide in silico identification and characterization of genes and gene families related to important traits, enabling new tools for molecular marker assisted selection in tree breeding. Deep sequencing of transcriptomes is also a powerful tool for the analysis of precise expression levels of each gene in a sample. It consists in quantifying short cDNA reads, obtained by NGS technologies, in order to compare the entire transcriptomes between genotypes and environmental conditions. The miRNAs are non-coding short RNAs involved in the regulation of different physiological processes, which can be identified by high-throughput sequencing of RNA libraries obtained by reverse transcription of purified short RNAs, and by in silico comparison with known miRNAs from other species. All together, NGS techniques and their applications have increased the resources for plant breeding in tree species, closing the former gap of genetic tools between trees and annual species.

Deep Evolutionary Comparison of Gene Expression Identifies Parallel Recruitment of Trans-Factors in Two Independent Origins of C4 Photosynthesis

PubMed Central

Kümpers, Britta M. C.; Smith-Unna, Richard D.; Hibberd, Julian M.

2014-01-01

With at least 60 independent origins spanning monocotyledons and dicotyledons, the C4 photosynthetic pathway represents one of the most remarkable examples of convergent evolution. The recurrent evolution of this highly complex trait involving alterations to leaf anatomy, cell biology and biochemistry allows an increase in productivity by ∼50% in tropical and subtropical areas. The extent to which separate lineages of C4 plants use the same genetic networks to maintain C4 photosynthesis is unknown. We developed a new informatics framework to enable deep evolutionary comparison of gene expression in species lacking reference genomes. We exploited this to compare gene expression in species representing two independent C4 lineages (Cleome gynandra and Zea mays) whose last common ancestor diverged ∼140 million years ago. We define a cohort of 3,335 genes that represent conserved components of leaf and photosynthetic development in these species. Furthermore, we show that genes encoding proteins of the C4 cycle are recruited into networks defined by photosynthesis-related genes. Despite the wide evolutionary separation and independent origins of the C4 phenotype, we report that these species use homologous transcription factors to both induce C4 photosynthesis and to maintain the cell specific gene expression required for the pathway to operate. We define a core molecular signature associated with leaf and photosynthetic maturation that is likely shared by angiosperm species derived from the last common ancestor of the monocotyledons and dicotyledons. We show that deep evolutionary comparisons of gene expression can reveal novel insight into the molecular convergence of highly complex phenotypes and that parallel evolution of trans-factors underpins the repeated appearance of C4 photosynthesis. Thus, exploitation of extant natural variation associated with complex traits can be used to identify regulators. Moreover, the transcription factors that are shared by independent C4 lineages are key targets for engineering the C4 pathway into C3 crops such as rice. PMID:24901697

Imputation of Exome Sequence Variants into Population- Based Samples and Blood-Cell-Trait-Associated Loci in African Americans: NHLBI GO Exome Sequencing Project

PubMed Central

Auer, Paul L.; Johnsen, Jill M.; Johnson, Andrew D.; Logsdon, Benjamin A.; Lange, Leslie A.; Nalls, Michael A.; Zhang, Guosheng; Franceschini, Nora; Fox, Keolu; Lange, Ethan M.; Rich, Stephen S.; O’Donnell, Christopher J.; Jackson, Rebecca D.; Wallace, Robert B.; Chen, Zhao; Graubert, Timothy A.; Wilson, James G.; Tang, Hua; Lettre, Guillaume; Reiner, Alex P.; Ganesh, Santhi K.; Li, Yun

2012-01-01

Researchers have successfully applied exome sequencing to discover causal variants in selected individuals with familial, highly penetrant disorders. We demonstrate the utility of exome sequencing followed by imputation for discovering low-frequency variants associated with complex quantitative traits. We performed exome sequencing in a reference panel of 761 African Americans and then imputed newly discovered variants into a larger sample of more than 13,000 African Americans for association testing with the blood cell traits hemoglobin, hematocrit, white blood count, and platelet count. First, we illustrate the feasibility of our approach by demonstrating genome-wide-significant associations for variants that are not covered by conventional genotyping arrays; for example, one such association is that between higher platelet count and an MPL c.117G>T (p.Lys39Asn) variant encoding a p.Lys39Asn amino acid substitution of the thrombpoietin receptor gene (p = 1.5 × 10−11). Second, we identified an association between missense variants of LCT and higher white blood count (p = 4 × 10−13). Third, we identified low-frequency coding variants that might account for allelic heterogeneity at several known blood cell-associated loci: MPL c.754T>C (p.Tyr252His) was associated with higher platelet count; CD36 c.975T>G (p.Tyr325∗) was associated with lower platelet count; and several missense variants at the α-globin gene locus were associated with lower hemoglobin. By identifying low-frequency missense variants associated with blood cell traits not previously reported by genome-wide association studies, we establish that exome sequencing followed by imputation is a powerful approach to dissecting complex, genetically heterogeneous traits in large population-based studies. PMID:23103231

The Multiple Origins of Complex Multicellularity

NASA Astrophysics Data System (ADS)

Knoll, Andrew H.

2011-05-01

Simple multicellularity has evolved numerous times within the Eukarya, but complex multicellular organisms belong to only six clades: animals, embryophytic land plants, florideophyte red algae, laminarialean brown algae, and two groups of fungi. Phylogeny and genomics suggest a generalized trajectory for the evolution of complex multicellularity, beginning with the co-optation of existing genes for adhesion. Molecular channels to facilitate cell-cell transfer of nutrients and signaling molecules appear to be critical, as this trait occurs in all complex multicellular organisms but few others. Proliferation of gene families for transcription factors and cell signals accompany the key functional innovation of complex multicellular clades: differentiated cells and tissues for the bulk transport of oxygen, nutrients, and molecular signals that enable organisms to circumvent the physical limitations of diffusion. The fossil records of animals and plants document key stages of this trajectory.

Comparative analysis of genetic architectures for nine developmental traits of rye.

PubMed

Masojć, Piotr; Milczarski, P; Kruszona, P

2017-08-01

Genetic architectures of plant height, stem thickness, spike length, awn length, heading date, thousand-kernel weight, kernel length, leaf area and chlorophyll content were aligned on the DArT-based high-density map of the 541 × Ot1-3 RILs population of rye using the genes interaction assorting by divergent selection (GIABDS) method. Complex sets of QTL for particular traits contained 1-5 loci of the epistatic D class and 10-28 loci of the hypostatic, mostly R and E classes controlling traits variation through D-E or D-R types of two-loci interactions. QTL were distributed on each of the seven rye chromosomes in unique positions or as a coinciding loci for 2-8 traits. Detection of considerable numbers of the reversed (D', E' and R') classes of QTL might be attributed to the transgression effects observed for most of the studied traits. First examples of E* and F QTL classes, defined in the model, are reported for awn length, leaf area, thousand-kernel weight and kernel length. The results of this study extend experimental data to 11 quantitative traits (together with pre-harvest sprouting and alpha-amylase activity) for which genetic architectures fit the model of mechanism underlying alleles distribution within tails of bi-parental populations. They are also a valuable starting point for map-based search of genes underlying detected QTL and for planning advanced marker-assisted multi-trait breeding strategies.

Hidden state prediction: a modification of classic ancestral state reconstruction algorithms helps unravel complex symbioses.

PubMed

Zaneveld, Jesse R R; Thurber, Rebecca L V

2014-01-01

Complex symbioses between animal or plant hosts and their associated microbiotas can involve thousands of species and millions of genes. Because of the number of interacting partners, it is often impractical to study all organisms or genes in these host-microbe symbioses individually. Yet new phylogenetic predictive methods can use the wealth of accumulated data on diverse model organisms to make inferences into the properties of less well-studied species and gene families. Predictive functional profiling methods use evolutionary models based on the properties of studied relatives to put bounds on the likely characteristics of an organism or gene that has not yet been studied in detail. These techniques have been applied to predict diverse features of host-associated microbial communities ranging from the enzymatic function of uncharacterized genes to the gene content of uncultured microorganisms. We consider these phylogenetically informed predictive techniques from disparate fields as examples of a general class of algorithms for Hidden State Prediction (HSP), and argue that HSP methods have broad value in predicting organismal traits in a variety of contexts, including the study of complex host-microbe symbioses.

Identification of loci governing eight agronomic traits using a GBS-GWAS approach and validation by QTL mapping in soya bean.

PubMed

Sonah, Humira; O'Donoughue, Louise; Cober, Elroy; Rajcan, Istvan; Belzile, François

2015-02-01

Soya bean is a major source of edible oil and protein for human consumption as well as animal feed. Understanding the genetic basis of different traits in soya bean will provide important insights for improving breeding strategies for this crop. A genome-wide association study (GWAS) was conducted to accelerate molecular breeding for the improvement of agronomic traits in soya bean. A genotyping-by-sequencing (GBS) approach was used to provide dense genome-wide marker coverage (>47,000 SNPs) for a panel of 304 short-season soya bean lines. A subset of 139 lines, representative of the diversity among these, was characterized phenotypically for eight traits under six environments (3 sites × 2 years). Marker coverage proved sufficient to ensure highly significant associations between the genes known to control simple traits (flower, hilum and pubescence colour) and flanking SNPs. Between one and eight genomic loci associated with more complex traits (maturity, plant height, seed weight, seed oil and protein) were also identified. Importantly, most of these GWAS loci were located within genomic regions identified by previously reported quantitative trait locus (QTL) for these traits. In some cases, the reported QTLs were also successfully validated by additional QTL mapping in a biparental population. This study demonstrates that integrating GBS and GWAS can be used as a powerful complementary approach to classical biparental mapping for dissecting complex traits in soya bean. © 2014 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

Quantitative Genomics of 30 Complex Phenotypes in Wagyu x Angus F1 Progeny

PubMed Central

Zhang, Lifan; Michal, Jennifer J.; O'Fallon, James V.; Pan, Zengxiang; Gaskins, Charles T.; Reeves, Jerry J.; Busboom, Jan R.; Zhou, Xiang; Ding, Bo; Dodson, Michael V.; Jiang, Zhihua

2012-01-01

In the present study, a total of 91 genes involved in various pathways were investigated for their associations with six carcass traits and twenty-four fatty acid composition phenotypes in a Wagyu×Angus reference population, including 43 Wagyu bulls and their potential 791 F1 progeny. Of the 182 SNPs evaluated, 102 SNPs that were in Hardy-Weinberg equilibrium with minor allele frequencies (MAF>0.15) were selected for parentage assignment and association studies with these quantitative traits. The parentage assignment revealed that 40 of 43 Wagyu sires produced over 96.71% of the calves in the population. Linkage disequilibrium analysis identified 75 of 102 SNPs derived from 54 genes as tagged SNPs. After Bonferroni correction, single-marker analysis revealed a total of 113 significant associations between 44 genes and 29 phenotypes (adjusted P<0.05). Multiple-marker analysis confirmed single-gene associations for 10 traits, but revealed two-gene networks for 9 traits and three-gene networks for 8 traits. Particularly, we observed that TNF (tumor necrosis factor) gene is significantly associated with both beef marbling score (P=0.0016) and palmitic acid (C16:0) (P=0.0043), RCAN1 (regulator of calcineurin 1) with rib-eye area (P=0.0103), ASB3 (ankyrin repeat and SOCS box-containing 3) with backfat (P=0.0392), ABCA1 (ATP-binding cassette A1) with both palmitic acid (C16:0) (P=0.0025) and oleic acid (C18:1n9) (P=0.0114), SLC27A1(solute carrier family 27 A1) with oleic acid (C18:1n9) (P=0.0155), CRH (corticotropin releasing hormone) with both linolenic acid (OMEGA-3) (P=0.0200) and OMEGA 6:3 RATIO (P=0.0054), SLC27A2 (solute carrier family 27 A2) with both linoleic acid (OMEGA-6) (P=0.0121) and FAT (P=0.0333), GNG3 (guanine nucleotide binding protein gamma 3 with desaturase 9 (P=0.0115), and EFEMP1 (EGF containing fibulin-like extracellular matrix protein 1), PLTP (phospholipid transfer protein) and DSEL (dermatan sulfate epimerase-like) with conjugated linoleic acid (P=0.0042-0.0044), respectively, in the Wagyu x Angus F1 population. In addition, we observed an interesting phenomenon that crossbreeding of different breeds might change gene actions to dominant and overdominant modes, thus explaining the origin of heterosis. The present study confirmed that these important families or pathway-based genes are useful targets for improving meat quality traits and healthful beef products in cattle. PMID:22745575

Linkage disequilibrium interval mapping of quantitative trait loci.

PubMed

Boitard, Simon; Abdallah, Jihad; de Rochambeau, Hubert; Cierco-Ayrolles, Christine; Mangin, Brigitte

2006-03-16

For many years gene mapping studies have been performed through linkage analyses based on pedigree data. Recently, linkage disequilibrium methods based on unrelated individuals have been advocated as powerful tools to refine estimates of gene location. Many strategies have been proposed to deal with simply inherited disease traits. However, locating quantitative trait loci is statistically more challenging and considerable research is needed to provide robust and computationally efficient methods. Under a three-locus Wright-Fisher model, we derived approximate expressions for the expected haplotype frequencies in a population. We considered haplotypes comprising one trait locus and two flanking markers. Using these theoretical expressions, we built a likelihood-maximization method, called HAPim, for estimating the location of a quantitative trait locus. For each postulated position, the method only requires information from the two flanking markers. Over a wide range of simulation scenarios it was found to be more accurate than a two-marker composite likelihood method. It also performed as well as identity by descent methods, whilst being valuable in a wider range of populations. Our method makes efficient use of marker information, and can be valuable for fine mapping purposes. Its performance is increased if multiallelic markers are available. Several improvements can be developed to account for more complex evolution scenarios or provide robust confidence intervals for the location estimates.

Network-Assisted Investigation of Combined Causal Signals from Genome-Wide Association Studies in Schizophrenia

PubMed Central

Jia, Peilin; Wang, Lily; Fanous, Ayman H.; Pato, Carlos N.; Edwards, Todd L.; Zhao, Zhongming

2012-01-01

With the recent success of genome-wide association studies (GWAS), a wealth of association data has been accomplished for more than 200 complex diseases/traits, proposing a strong demand for data integration and interpretation. A combinatory analysis of multiple GWAS datasets, or an integrative analysis of GWAS data and other high-throughput data, has been particularly promising. In this study, we proposed an integrative analysis framework of multiple GWAS datasets by overlaying association signals onto the protein-protein interaction network, and demonstrated it using schizophrenia datasets. Building on a dense module search algorithm, we first searched for significantly enriched subnetworks for schizophrenia in each single GWAS dataset and then implemented a discovery-evaluation strategy to identify module genes with consistent association signals. We validated the module genes in an independent dataset, and also examined them through meta-analysis of the related SNPs using multiple GWAS datasets. As a result, we identified 205 module genes with a joint effect significantly associated with schizophrenia; these module genes included a number of well-studied candidate genes such as DISC1, GNA12, GNA13, GNAI1, GPR17, and GRIN2B. Further functional analysis suggested these genes are involved in neuronal related processes. Additionally, meta-analysis found that 18 SNPs in 9 module genes had P meta<1×10−4, including the gene HLA-DQA1 located in the MHC region on chromosome 6, which was reported in previous studies using the largest cohort of schizophrenia patients to date. These results demonstrated our bi-directional network-based strategy is efficient for identifying disease-associated genes with modest signals in GWAS datasets. This approach can be applied to any other complex diseases/traits where multiple GWAS datasets are available. PMID:22792057

Fungal Traits That Drive Ecosystem Dynamics on Land

PubMed Central

Lennon, Jay T.

2015-01-01

SUMMARY Fungi contribute extensively to a wide range of ecosystem processes, including decomposition of organic carbon, deposition of recalcitrant carbon, and transformations of nitrogen and phosphorus. In this review, we discuss the current knowledge about physiological and morphological traits of fungi that directly influence these processes, and we describe the functional genes that encode these traits. In addition, we synthesize information from 157 whole fungal genomes in order to determine relationships among selected functional genes within fungal taxa. Ecosystem-related traits varied most at relatively coarse taxonomic levels. For example, we found that the maximum amount of variance for traits associated with carbon mineralization, nitrogen and phosphorus cycling, and stress tolerance could be explained at the levels of order to phylum. Moreover, suites of traits tended to co-occur within taxa. Specifically, the genetic capacities for traits that improve stress tolerance—β-glucan synthesis, trehalose production, and cold-induced RNA helicases—were positively related to one another, and they were more evident in yeasts. Traits that regulate the decomposition of complex organic matter—lignin peroxidases, cellobiohydrolases, and crystalline cellulases—were also positively related, but they were more strongly associated with free-living filamentous fungi. Altogether, these relationships provide evidence for two functional groups: stress tolerators, which may contribute to soil carbon accumulation via the production of recalcitrant compounds; and decomposers, which may reduce soil carbon stocks. It is possible that ecosystem functions, such as soil carbon storage, may be mediated by shifts in the fungal community between stress tolerators and decomposers in response to environmental changes, such as drought and warming. PMID:25971588

Genetic Dissection of Maize Embryonic Callus Regenerative Capacity Using Multi-Locus Genome-Wide Association Studies

PubMed Central

Ma, Langlang; Liu, Min; Yan, Yuanyuan; Qing, Chunyan; Zhang, Xiaoling; Zhang, Yanling; Long, Yun; Wang, Lei; Pan, Lang; Zou, Chaoying; Li, Zhaoling; Wang, Yanli; Peng, Huanwei; Pan, Guangtang; Jiang, Zhou; Shen, Yaou

2018-01-01

The regenerative capacity of the embryonic callus, a complex quantitative trait, is one of the main limiting factors for maize transformation. This trait was decomposed into five traits, namely, green callus rate (GCR), callus differentiating rate (CDR), callus plantlet number (CPN), callus rooting rate (CRR), and callus browning rate (CBR). To dissect the genetic foundation of maize transformation, in this study multi-locus genome-wide association studies (GWAS) for the five traits were performed in a population of 144 inbred lines genotyped with 43,427 SNPs. Using the phenotypic values in three environments and best linear unbiased prediction (BLUP) values, as a result, a total of 127, 56, 160, and 130 significant quantitative trait nucleotides (QTNs) were identified by mrMLM, FASTmrEMMA, ISIS EM-BLASSO, and pLARmEB, respectively. Of these QTNs, 63 QTNs were commonly detected, including 15 across multiple environments and 58 across multiple methods. Allele distribution analysis showed that the proportion of superior alleles for 36 QTNs was <50% in 31 elite inbred lines. Meanwhile, these superior alleles had obviously additive effect on the regenerative capacity. This indicates that the regenerative capacity-related traits can be improved by proper integration of the superior alleles using marker-assisted selection. Moreover, a total of 40 candidate genes were found based on these common QTNs. Some annotated genes were previously reported to relate with auxin transport, cell fate, seed germination, or embryo development, especially, GRMZM2G108933 (WOX2) was found to promote maize transgenic embryonic callus regeneration. These identified candidate genes will contribute to a further understanding of the genetic foundation of maize embryonic callus regeneration. PMID:29755499

Development of a D genome specific marker resource for diploid and hexaploid wheat

USDA-ARS?s Scientific Manuscript database

Mapping and map-based cloning of genes that control agriculturally and economically important traits remain great challenges for plants with complex highly repetitive genomes such as those of the grass tribe, Triticeae. Mapping limitations in the Triticeae are primarily due to low frequencies of po...

Neuroscience of resilience and vulnerability for addiction medicine: From genes to behavior.

PubMed

Morrow, Jonathan D; Flagel, Shelly B

2016-01-01

Addiction is a complex behavioral disorder arising from roughly equal contributions of genetic and environmental factors. Behavioral traits such as novelty-seeking, impulsivity, and cue-reactivity have been associated with vulnerability to addiction. These traits, at least in part, arise from individual variation in functional neural systems, such as increased striatal dopaminergic activity and decreased prefrontal cortical control over subcortical emotional and motivational responses. With a few exceptions, genetic studies have largely failed to consistently identify specific alleles that affect addiction liability. This may be due to the multifactorial nature of addiction, with different genes becoming more significant in certain environments or in certain subsets of the population. Epigenetic mechanisms may also be an important source of risk. Adolescence is a particularly critical time period in the development of addiction, and environmental factors at this stage of life can have a large influence on whether inherited risk factors are actually translated into addictive behaviors. Knowledge of how individual differences affect addiction liability at the level of genes, neural systems, behavioral traits, and sociodevelopmental trajectories can help to inform and improve clinical practice. © 2016 Elsevier B.V. All rights reserved.

Alcohol dehydrogenase activities and ethanol tolerance in Anastrepha (Diptera, Tephritidae) fruit-fly species and their hybrids

PubMed Central

2009-01-01

The ADH (alcohol dehydrogenase) system is one of the earliest known models of molecular evolution, and is still the most studied in Drosophila. Herein, we studied this model in the genus Anastrepha (Diptera, Tephritidae). Due to the remarkable advantages it presents, it is possible to cross species with different Adh genotypes and with different phenotype traits related to ethanol tolerance. The two species studied here each have a different number of Adh gene copies, whereby crosses generate polymorphisms in gene number and in composition of the genetic background. We measured certain traits related to ethanol metabolism and tolerance. ADH specific enzyme activity presented gene by environment interactions, and the larval protein content showed an additive pattern of inheritance, whilst ADH enzyme activity per larva presented a complex behavior that may be explained by epistatic effects. Regression models suggest that there are heritable factors acting on ethanol tolerance, which may be related to enzymatic activity of the ADHs and to larval mass, although a pronounced environmental effect on ethanol tolerance was also observed. By using these data, we speculated on the mechanisms of ethanol tolerance and its inheritance as well as of associated traits. PMID:21637665

Enriched pathways for major depressive disorder identified from a genome-wide association study.

PubMed

Kao, Chung-Feng; Jia, Peilin; Zhao, Zhongming; Kuo, Po-Hsiu

2012-11-01

Major depressive disorder (MDD) has caused a substantial burden of disease worldwide with moderate heritability. Despite efforts through conducting numerous association studies and now, genome-wide association (GWA) studies, the success of identifying susceptibility loci for MDD has been limited, which is partially attributed to the complex nature of depression pathogenesis. A pathway-based analytic strategy to investigate the joint effects of various genes within specific biological pathways has emerged as a powerful tool for complex traits. The present study aimed to identify enriched pathways for depression using a GWA dataset for MDD. For each gene, we estimated its gene-wise p value using combined and minimum p value, separately. Canonical pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and BioCarta were used. We employed four pathway-based analytic approaches (gene set enrichment analysis, hypergeometric test, sum-square statistic, sum-statistic). We adjusted for multiple testing using Benjamini & Hochberg's method to report significant pathways. We found 17 significantly enriched pathways for depression, which presented low-to-intermediate crosstalk. The top four pathways were long-term depression (p⩽1×10-5), calcium signalling (p⩽6×10-5), arrhythmogenic right ventricular cardiomyopathy (p⩽1.6×10-4) and cell adhesion molecules (p⩽2.2×10-4). In conclusion, our comprehensive pathway analyses identified promising pathways for depression that are related to neurotransmitter and neuronal systems, immune system and inflammatory response, which may be involved in the pathophysiological mechanisms underlying depression. We demonstrated that pathway enrichment analysis is promising to facilitate our understanding of complex traits through a deeper interpretation of GWA data. Application of this comprehensive analytic strategy in upcoming GWA data for depression could validate the findings reported in this study.

Elucidation of the genetic basis of variation for stem strength characteristics in bread wheat by Associative Transcriptomics.

PubMed

Miller, Charlotte N; Harper, Andrea L; Trick, Martin; Werner, Peter; Waldron, Keith; Bancroft, Ian

2016-07-16

The current approach to reducing the tendency for wheat grown under high fertilizer conditions to collapse (lodge) under the weight of its grain is based on reducing stem height via the introduction of Rht genes. However, these reduce the yield of straw (itself an important commodity) and introduce other undesirable characteristics. Identification of alternative height-control loci is therefore of key interest. In addition, the improvement of stem mechanical strength provides a further way through which lodging can be reduced. To investigate the prospects for genetic alternatives to Rht, we assessed variation for plant height and stem strength properties in a training genetic diversity panel of 100 wheat accessions fixed for Rht. Using mRNAseq data derived from RNA purified from leaves, functional genotypes were developed for the panel comprising 42,066 Single Nucleotide Polymorphism (SNP) markers and 94,060 Gene Expression Markers (GEMs). In the first application in wheat of the recently-developed method of Associative Transcriptomics, we identified associations between trait variation and both SNPs and GEMs. Analysis of marker-trait associations revealed candidates for the causative genes underlying the trait variation, implicating xylan acetylation and the COP9 signalosome as contributing to stem strength and auxin in the control of the observed variation for plant height. Predictive capabilities of key markers for stem strength were validated using a test genetic diversity panel of 30 further wheat accessions. This work illustrates the power of Associative Transcriptomics for the exploration of complex traits of high agronomic importance in wheat. The careful selection of genotypes included in the analysis, allowed for high resolution mapping of novel trait-controlling loci in this staple crop. The use of Gene Expression markers coupled with the more traditional sequence-based markers, provides the power required to understand the biological context of the marker-trait associations observed. This not only adds to the wealth of knowledge that we strive to accumulate regarding gene function and plant adaptation, but also provides breeders with the information required to make more informed decisions regarding the potential consequences of incorporating the use of particular markers into future breeding programmes.

A Genome-Wide mQTL Analysis in Human Adipose Tissue Identifies Genetic Variants Associated with DNA Methylation, Gene Expression and Metabolic Traits

PubMed Central

Volkov, Petr; Olsson, Anders H.; Gillberg, Linn; Jørgensen, Sine W.; Brøns, Charlotte; Eriksson, Karl-Fredrik; Groop, Leif; Jansson, Per-Anders; Nilsson, Emma; Rönn, Tina; Vaag, Allan; Ling, Charlotte

2016-01-01

Little is known about the extent to which interactions between genetics and epigenetics may affect the risk of complex metabolic diseases and/or their intermediary phenotypes. We performed a genome-wide DNA methylation quantitative trait locus (mQTL) analysis in human adipose tissue of 119 men, where 592,794 single nucleotide polymorphisms (SNPs) were related to DNA methylation of 477,891 CpG sites, covering 99% of RefSeq genes. SNPs in significant mQTLs were further related to gene expression in adipose tissue and obesity related traits. We found 101,911 SNP-CpG pairs (mQTLs) in cis and 5,342 SNP-CpG pairs in trans showing significant associations between genotype and DNA methylation in adipose tissue after correction for multiple testing, where cis is defined as distance less than 500 kb between a SNP and CpG site. These mQTLs include reported obesity, lipid and type 2 diabetes loci, e.g. ADCY3/POMC, APOA5, CETP, FADS2, GCKR, SORT1 and LEPR. Significant mQTLs were overrepresented in intergenic regions meanwhile underrepresented in promoter regions and CpG islands. We further identified 635 SNPs in significant cis-mQTLs associated with expression of 86 genes in adipose tissue including CHRNA5, G6PC2, GPX7, RPL27A, THNSL2 and ZFP57. SNPs in significant mQTLs were also associated with body mass index (BMI), lipid traits and glucose and insulin levels in our study cohort and public available consortia data. Importantly, the Causal Inference Test (CIT) demonstrates how genetic variants mediate their effects on metabolic traits (e.g. BMI, cholesterol, high-density lipoprotein (HDL), hemoglobin A1c (HbA1c) and homeostatic model assessment of insulin resistance (HOMA-IR)) via altered DNA methylation in human adipose tissue. This study identifies genome-wide interactions between genetic and epigenetic variation in both cis and trans positions influencing gene expression in adipose tissue and in vivo (dys)metabolic traits associated with the development of obesity and diabetes. PMID:27322064

Quantitative trait locus mapping and analysis of heritable variation in affiliative social behavior and co-occurring traits.

PubMed

Knoll, A T; Jiang, K; Levitt, P

2018-06-01

Humans exhibit broad heterogeneity in affiliative social behavior. Twin and family studies show that individual differences in core dimensions of social behavior are heritable, yet there are knowledge gaps in understanding the underlying genetic and neurobiological mechanisms. Animal genetic reference panels (GRPs) provide a tractable strategy for examining the behavioral and genetic architecture of complex traits. Here, using males from 50 mouse strains from the BXD GRP, 4 domains of affiliative social behavior-social approach, social recognition, direct social interaction (DSI) (partner sniffing) and vocal communication-were examined in 2 widely used behavioral tasks-the 3-chamber and DSI tasks. There was continuous and broad variation in social and nonsocial traits, with moderate to high heritability of social approach sniff preference (0.31), ultrasonic vocalization (USV) count (0.39), partner sniffing (0.51), locomotor activity (0.54-0.66) and anxiety-like behavior (0.36). Principal component analysis shows that variation in social and nonsocial traits are attributable to 5 independent factors. Genome-wide mapping identified significant quantitative trait loci for USV count on chromosome (Chr) 18 and locomotor activity on Chr X, with suggestive loci and candidate quantitative trait genes identified for all traits with one notable exception-partner sniffing in the DSI task. The results show heritable variation in sociability, which is independent of variation in activity and anxiety-like traits. In addition, a highly heritable and ethological domain of affiliative sociability-partner sniffing-appears highly polygenic. These findings establish a basis for identifying functional natural variants, leading to a new understanding typical and atypical sociability. © 2017 The Authors. Genes, Brain and Behavior published by International Behavioural and Neural Genetics Society and John Wiley & Sons Ltd.

Metabolomic analysis of the selection response of Drosophila melanogaster to environmental stress: are there links to gene expression and phenotypic traits?

NASA Astrophysics Data System (ADS)

Malmendal, Anders; Sørensen, Jesper Givskov; Overgaard, Johannes; Holmstrup, Martin; Nielsen, Niels Chr.; Loeschcke, Volker

2013-05-01

We investigated the global metabolite response to artificial selection for tolerance to stressful conditions such as cold, heat, starvation, and desiccation, and for longevity in Drosophila melanogaster. Our findings were compared to data from other levels of biological organization, including gene expression, physiological traits, and organismal stress tolerance phenotype. Overall, we found that selection for environmental stress tolerance changes the metabolomic 1H NMR fingerprint largely in a similar manner independent of the trait selected for, indicating that experimental evolution led to a general stress selection response at the metabolomic level. Integrative analyses across data sets showed little similarity when general correlations between selection effects at the level of the metabolome and gene expression were compared. This is likely due to the fact that the changes caused by these selection regimes were rather mild and/or that the dominating determinants for gene expression and metabolite levels were different. However, expression of a number of genes was correlated with the metabolite data. Many of the identified genes were general stress response genes that are down-regulated in response to selection for some of the stresses in this study. Overall, the results illustrate that selection markedly alters the metabolite profile and that the coupling between different levels of biological organization indeed is present though not very strong for stress selection at this level. The results highlight the extreme complexity of environmental stress adaptation and the difficulty of extrapolating and interpreting responses across levels of biological organization.

Regulation of DNA methylation on EEF1D and RPL8 expression in cattle.

PubMed

Liu, Xuan; Yang, Jie; Zhang, Qin; Jiang, Li

2017-10-01

Dynamic changes to the epigenome play a critical role in a variety of biology processes and complex traits. Many important candidate genes have been identified through our previous genome wide association study (GWAS) on milk production traits in dairy cattle. However, the underlying mechanism of candidate genes have not yet been clearly understood. In this study, we analyzed the methylation variation of the candidate genes, EEF1D and RPL8, which were identified to be strongly associated with milk production traits in dairy cattle in our previous studies, and its effect on protein and mRNA expression. We compared DNA methylation profiles and gene expression levels of EEF1D and RPL8 in five different tissues (heart, liver, mammary gland, ovary and muscle) of three cows. Both genes showed the highest expression level in mammary gland. For RPL8, there was no difference in the DNA methylation pattern in the five tissues, suggesting no effect of DNA methylation on gene expression. For EEF1D, the DNA methylation levels of its first CpG island differed in the five tissues and were negatively correlated with the gene expression levels. To further investigate the function of DNA methylation on the expression of EEF1D, we collected blood samples of three cows at early stage of lactation and in dry period and analyzed its expression and the methylation status of the first CpG island in blood. As a result, the mRNA expression of EEF1D in the dry period was higher than that at the early stage of lactation, while the DNA methylation level in the dry period was lower than that at the early stage of lactation. Our result suggests that the DNA methylation of EEF1D plays an important role in the spatial and temporal regulation of its expression and possibly have an effect on the milk production traits.

Individual differences in personality predict how people look at faces.

PubMed

Perlman, Susan B; Morris, James P; Vander Wyk, Brent C; Green, Steven R; Doyle, Jaime L; Pelphrey, Kevin A

2009-06-22

Determining the ways in which personality traits interact with contextual determinants to shape social behavior remains an important area of empirical investigation. The specific personality trait of neuroticism has been related to characteristic negative emotionality and associated with heightened attention to negative, emotionally arousing environmental signals. However, the mechanisms by which this personality trait may shape social behavior remain largely unspecified. We employed eye tracking to investigate the relationship between characteristics of visual scanpaths in response to emotional facial expressions and individual differences in personality. We discovered that the amount of time spent looking at the eyes of fearful faces was positively related to neuroticism. This finding is discussed in relation to previous behavioral research relating personality to selective attention for trait-congruent emotional information, neuroimaging studies relating differences in personality to amygdala reactivity to socially relevant stimuli, and genetic studies suggesting linkages between the serotonin transporter gene and neuroticism. We conclude that personality may be related to interpersonal interaction by shaping aspects of social cognition as basic as eye contact. In this way, eye gaze represents a possible behavioral link in a complex relationship between genes, brain function, and personality.

The challenges of commercializing second-generation transgenic crop traits necessitate the development of international public sector research infrastructure.

PubMed

Rothstein, Steven J; Bi, Yong-Mei; Coneva, Viktoriya; Han, Mei; Good, Allen

2014-10-01

It has been 30 years since the first transformation of a gene into a plant species, and since that time a number of biotechnology products have been developed, with the most important being insect- and herbicide-resistant crops. The development of second-generation products, including nutrient use efficiency and tolerance to important environmental stressors such as drought, has, up to this time, been less successful. This is in part due to the inherent complexities of these traits and in part due to limitations in research infrastructure necessary for public sector researchers to test their best ideas. Here we discuss lessons from previous work in the generation of the first-generation traits, as well as work from our labs and others on identifying genes for nitrogen use efficiency. We then describe some of the issues that have impeded rapid progress in this area. Finally, we propose the type of public sector organization that we feel is necessary to make advances in important second-generation traits such as nitrogen use efficiency. © 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.

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

Farahani, Poupak; Chiu, Sally; Bowlus, Christopher L.

Obesity is a complex disease. To date, over 100 chromosomal loci for body weight, body fat, regional white adipose tissue weight, and other obesity-related traits have been identified in humans and in animal models. For most loci, the underlying genes are not yet identified; some of these chromosomal loci will be alleles of known obesity genes, whereas many will represent alleles of unknown genes. Microarray analysis allows simultaneous multiple gene and pathway discovery. cDNA and oligonucleotide arrays are commonly used to identify differentially expressed genes by surveys of large numbers of known and unnamed genes. Two papers previously identified genesmore » differentially expressed in adipose tissue of mouse models of obesity and diabetes by analysis of hybridization to Affymetrix oligonucleotide chips.« less

Application of Genome Wide Association and Genomic Prediction for Improvement of Cacao Productivity and Resistance to Black and Frosty Pod Diseases

PubMed Central

Romero Navarro, J. Alberto; Phillips-Mora, Wilbert; Arciniegas-Leal, Adriana; Mata-Quirós, Allan; Haiminen, Niina; Mustiga, Guiliana; Livingstone III, Donald; van Bakel, Harm; Kuhn, David N.; Parida, Laxmi; Kasarskis, Andrew; Motamayor, Juan C.

2017-01-01

Chocolate is a highly valued and palatable confectionery product. Chocolate is primarily made from the processed seeds of the tree species Theobroma cacao. Cacao cultivation is highly relevant for small-holder farmers throughout the tropics, yet its productivity remains limited by low yields and widespread pathogens. A panel of 148 improved cacao clones was assembled based on productivity and disease resistance, and phenotypic single-tree replicated clonal evaluation was performed for 8 years. Using high-density markers, the diversity of clones was expressed relative to 10 known ancestral cacao populations, and significant effects of ancestry were observed in productivity and disease resistance. Genome-wide association (GWA) was performed, and six markers were significantly associated with frosty pod disease resistance. In addition, genomic selection was performed, and consistent with the observed extensive linkage disequilibrium, high predictive ability was observed at low marker densities for all traits. Finally, quantitative trait locus mapping and differential expression analysis of two cultivars with contrasting disease phenotypes were performed to identify genes underlying frosty pod disease resistance, identifying a significant quantitative trait locus and 35 differentially expressed genes using two independent differential expression analyses. These results indicate that in breeding populations of heterozygous and recently admixed individuals, mapping approaches can be used for low complexity traits like pod color cacao, or in other species single gene disease resistance, however genomic selection for quantitative traits remains highly effective relative to mapping. Our results can help guide the breeding process for sustainable improved cacao productivity. PMID:29184558

Genetic Marker Discovery in Complex Traits: A Field Example on Fat Content and Composition in Pigs.

PubMed

Pena, Ramona Natacha; Ros-Freixedes, Roger; Tor, Marc; Estany, Joan

2016-12-14

Among the large number of attributes that define pork quality, fat content and composition have attracted the attention of breeders in the recent years due to their interaction with human health and technological and sensorial properties of meat. In livestock species, fat accumulates in different depots following a temporal pattern that is also recognized in humans. Intramuscular fat deposition rate and fatty acid composition change with life. Despite indication that it might be possible to select for intramuscular fat without affecting other fat depots, to date only one depot-specific genetic marker ( PCK1 c.2456C>A) has been reported. In contrast, identification of polymorphisms related to fat composition has been more successful. For instance, our group has described a variant in the stearoyl-coA desaturase ( SCD ) gene that improves the desaturation index of fat without affecting overall fatness or growth. Identification of mutations in candidate genes can be a tedious and costly process. Genome-wide association studies can help in narrowing down the number of candidate genes by highlighting those which contribute most to the genetic variation of the trait. Results from our group and others indicate that fat content and composition are highly polygenic and that very few genes explain more than 5% of the variance of the trait. Moreover, as the complexity of the genome emerges, the role of non-coding genes and regulatory elements cannot be disregarded. Prediction of breeding values from genomic data is discussed in comparison with conventional best linear predictors of breeding values. An example based on real data is given, and the implications in phenotype prediction are discussed in detail. The benefits and limitations of using large SNP sets versus a few very informative markers as predictors of genetic merit of breeding candidates are evaluated using field data as an example.

A high-density genetic map and QTL analysis of agronomic traits in foxtail millet [Setaria italica (L.) P. Beauv.] using RAD-seq.

PubMed

Wang, Jun; Wang, Zhilan; Du, Xiaofen; Yang, Huiqing; Han, Fang; Han, Yuanhuai; Yuan, Feng; Zhang, Linyi; Peng, Shuzhong; Guo, Erhu

2017-01-01

Foxtail millet (Setaria italica), a very important grain crop in China, has become a new model plant for cereal crops and biofuel grasses. Although its reference genome sequence was released recently, quantitative trait loci (QTLs) controlling complex agronomic traits remains limited. The development of massively parallel genotyping methods and next-generation sequencing technologies provides an excellent opportunity for developing single-nucleotide polymorphisms (SNPs) for linkage map construction and QTL analysis of complex quantitative traits. In this study, a high-throughput and cost-effective RAD-seq approach was employed to generate a high-density genetic map for foxtail millet. A total of 2,668,587 SNP loci were detected according to the reference genome sequence; meanwhile, 9,968 SNP markers were used to genotype 124 F2 progenies derived from the cross between Hongmiaozhangu and Changnong35; a high-density genetic map spanning 1648.8 cM, with an average distance of 0.17 cM between adjacent markers was constructed; 11 major QTLs for eight agronomic traits were identified; five co-dominant DNA markers were developed. These findings will be of value for the identification of candidate genes and marker-assisted selection in foxtail millet.

A high-density genetic map and QTL analysis of agronomic traits in foxtail millet [Setaria italica (L.) P. Beauv.] using RAD-seq

PubMed Central

Wang, Zhilan; Du, Xiaofen; Yang, Huiqing; Han, Fang; Han, Yuanhuai; Yuan, Feng; Zhang, Linyi; Peng, Shuzhong; Guo, Erhu

2017-01-01

Foxtail millet (Setaria italica), a very important grain crop in China, has become a new model plant for cereal crops and biofuel grasses. Although its reference genome sequence was released recently, quantitative trait loci (QTLs) controlling complex agronomic traits remains limited. The development of massively parallel genotyping methods and next-generation sequencing technologies provides an excellent opportunity for developing single-nucleotide polymorphisms (SNPs) for linkage map construction and QTL analysis of complex quantitative traits. In this study, a high-throughput and cost-effective RAD-seq approach was employed to generate a high-density genetic map for foxtail millet. A total of 2,668,587 SNP loci were detected according to the reference genome sequence; meanwhile, 9,968 SNP markers were used to genotype 124 F2 progenies derived from the cross between Hongmiaozhangu and Changnong35; a high-density genetic map spanning 1648.8 cM, with an average distance of 0.17 cM between adjacent markers was constructed; 11 major QTLs for eight agronomic traits were identified; five co-dominant DNA markers were developed. These findings will be of value for the identification of candidate genes and marker-assisted selection in foxtail millet. PMID:28644843

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.

Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index

PubMed Central

Yang, Jian; Bakshi, Andrew; Zhu, Zhihong; Hemani, Gibran; Vinkhuyzen, Anna A.E.; Lee, Sang Hong; Robinson, Matthew R.; Perry, John R.B.; Nolte, Ilja M.; van Vliet-Ostaptchouk, Jana V.; Snieder, Harold; Esko, Tonu; Milani, Lili; Mägi, Reedik; Metspalu, Andres; Hamsten, Anders; Magnusson, Patrik K.E.; Pedersen, Nancy L.; Ingelsson, Erik; Soranzo, Nicole; Keller, Matthew C.; Wray, Naomi R.; Goddard, Michael E.; Visscher, Peter M.

2015-01-01

We propose a method (GREML-LDMS) to estimate heritability for human complex traits in unrelated individuals using whole-genome sequencing (WGS) data. We demonstrate using simulations based on WGS data that ~97% and ~68% of variation at common and rare variants, respectively, can be captured by imputation. Using the GREML-LDMS method, we estimate from 44,126 unrelated individuals that all ~17M imputed variants explain 56% (s.e. = 2.3%) of variance for height and 27% (s.e. = 2.5%) for body mass index (BMI), and find evidence that height- and BMI-associated variants have been under natural selection. Considering imperfect tagging of imputation and potential overestimation of heritability from previous family-based studies, heritability is likely to be 60–70% for height and 30–40% for BMI. Therefore, missing heritability is small for both traits. For further gene discovery of complex traits, a design with SNP arrays followed by imputation is more cost-effective than WGS at current prices. PMID:26323059

Setaria viridis as a Model System to Advance Millet Genetics and Genomics

DOE PAGES

Huang, Pu; Shyu, Christine; Coelho, Carla P.; ...

2016-11-28

Millet is a common name for a group of polyphyletic, small-seeded cereal crops that include pearl, finger and foxtail millet. Millet species are an important source of calories for many societies, often in developing countries. Compared to major cereal crops such as rice and maize, millets are generally better adapted to dry and hot environments. Yet despite their food security value, the genetic architecture of agronomically important traits in millets, including both morphological traits and climate resilience remains poorly studied. These complex traits have been challenging to dissect in large part because of the lack of sufficient genetic tools andmore » resources. In this article, we review the phylogenetic relationship among various millet species and discuss the value of a genetic model system for millet research. We propose that a broader adoption of green foxtail (Setaria viridis) as a model system for millets could greatly accelerate the pace of gene discovery in the millets, and summarize available and emerging resources in S. viridis and its domesticated relative S. italica. These resources have value in forward genetics, reverse genetics and high throughput phenotyping. We describe methods and strategies to best utilize these resources to facilitate the genetic dissection of complex traits. We envision that coupling cutting-edge technologies and the use of S. viridis for gene discovery will accelerate genetic research in millets in general. This will enable strategies and provide opportunities to increase productivity, especially in the semi-arid tropics of Asia and Africa where millets are staple food crops.« less

Setaria viridis as a Model System to Advance Millet Genetics and Genomics

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

Huang, Pu; Shyu, Christine; Coelho, Carla P.

Millet is a common name for a group of polyphyletic, small-seeded cereal crops that include pearl, finger and foxtail millet. Millet species are an important source of calories for many societies, often in developing countries. Compared to major cereal crops such as rice and maize, millets are generally better adapted to dry and hot environments. Yet despite their food security value, the genetic architecture of agronomically important traits in millets, including both morphological traits and climate resilience remains poorly studied. These complex traits have been challenging to dissect in large part because of the lack of sufficient genetic tools andmore » resources. In this article, we review the phylogenetic relationship among various millet species and discuss the value of a genetic model system for millet research. We propose that a broader adoption of green foxtail (Setaria viridis) as a model system for millets could greatly accelerate the pace of gene discovery in the millets, and summarize available and emerging resources in S. viridis and its domesticated relative S. italica. These resources have value in forward genetics, reverse genetics and high throughput phenotyping. We describe methods and strategies to best utilize these resources to facilitate the genetic dissection of complex traits. We envision that coupling cutting-edge technologies and the use of S. viridis for gene discovery will accelerate genetic research in millets in general. This will enable strategies and provide opportunities to increase productivity, especially in the semi-arid tropics of Asia and Africa where millets are staple food crops.« less

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

Detecting gene subnetworks under selection in biological pathways.

PubMed

Gouy, Alexandre; Daub, Joséphine T; Excoffier, Laurent

2017-09-19

Advances in high throughput sequencing technologies have created a gap between data production and functional data analysis. Indeed, phenotypes result from interactions between numerous genes, but traditional methods treat loci independently, missing important knowledge brought by network-level emerging properties. Therefore, detecting selection acting on multiple genes affecting the evolution of complex traits remains challenging. In this context, gene network analysis provides a powerful framework to study the evolution of adaptive traits and facilitates the interpretation of genome-wide data. We developed a method to analyse gene networks that is suitable to evidence polygenic selection. The general idea is to search biological pathways for subnetworks of genes that directly interact with each other and that present unusual evolutionary features. Subnetwork search is a typical combinatorial optimization problem that we solve using a simulated annealing approach. We have applied our methodology to find signals of adaptation to high-altitude in human populations. We show that this adaptation has a clear polygenic basis and is influenced by many genetic components. Our approach, implemented in the R package signet, improves on gene-level classical tests for selection by identifying both new candidate genes and new biological processes involved in adaptation to altitude. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Unveiling network-based functional features through integration of gene expression into protein networks.

PubMed

Jalili, Mahdi; Gebhardt, Tom; Wolkenhauer, Olaf; Salehzadeh-Yazdi, Ali

2018-06-01

Decoding health and disease phenotypes is one of the fundamental objectives in biomedicine. Whereas high-throughput omics approaches are available, it is evident that any single omics approach might not be adequate to capture the complexity of phenotypes. Therefore, integrated multi-omics approaches have been used to unravel genotype-phenotype relationships such as global regulatory mechanisms and complex metabolic networks in different eukaryotic organisms. Some of the progress and challenges associated with integrated omics studies have been reviewed previously in comprehensive studies. In this work, we highlight and review the progress, challenges and advantages associated with emerging approaches, integrating gene expression and protein-protein interaction networks to unravel network-based functional features. This includes identifying disease related genes, gene prioritization, clustering protein interactions, developing the modules, extract active subnetworks and static protein complexes or dynamic/temporal protein complexes. We also discuss how these approaches contribute to our understanding of the biology of complex traits and diseases. This article is part of a Special Issue entitled: Cardiac adaptations to obesity, diabetes and insulin resistance, edited by Professors Jan F.C. Glatz, Jason R.B. Dyck and Christine Des Rosiers. Copyright © 2018 Elsevier B.V. All rights reserved.

A fruit quality gene map of Prunus

PubMed Central

2009-01-01

Background Prunus fruit development, growth, ripening, and senescence includes major biochemical and sensory changes in texture, color, and flavor. The genetic dissection of these complex processes has important applications in crop improvement, to facilitate maximizing and maintaining stone fruit quality from production and processing through to marketing and consumption. Here we present an integrated fruit quality gene map of Prunus containing 133 genes putatively involved in the determination of fruit texture, pigmentation, flavor, and chilling injury resistance. Results A genetic linkage map of 211 markers was constructed for an intraspecific peach (Prunus persica) progeny population, Pop-DG, derived from a canning peach cultivar 'Dr. Davis' and a fresh market cultivar 'Georgia Belle'. The Pop-DG map covered 818 cM of the peach genome and included three morphological markers, 11 ripening candidate genes, 13 cold-responsive genes, 21 novel EST-SSRs from the ChillPeach database, 58 previously reported SSRs, 40 RAFs, 23 SRAPs, 14 IMAs, and 28 accessory markers from candidate gene amplification. The Pop-DG map was co-linear with the Prunus reference T × E map, with 39 SSR markers in common to align the maps. A further 158 markers were bin-mapped to the reference map: 59 ripening candidate genes, 50 cold-responsive genes, and 50 novel EST-SSRs from ChillPeach, with deduced locations in Pop-DG via comparative mapping. Several candidate genes and EST-SSRs co-located with previously reported major trait loci and quantitative trait loci for chilling injury symptoms in Pop-DG. Conclusion The candidate gene approach combined with bin-mapping and availability of a community-recognized reference genetic map provides an efficient means of locating genes of interest in a target genome. We highlight the co-localization of fruit quality candidate genes with previously reported fruit quality QTLs. The fruit quality gene map developed here is a valuable tool for dissecting the genetic architecture of fruit quality traits in Prunus crops. PMID:19995417

Quantitative genetic bases of anthocyanin variation in grape (Vitis vinifera L. ssp. sativa) berry: a quantitative trait locus to quantitative trait nucleotide integrated study.

PubMed

Fournier-Level, Alexandre; Le Cunff, Loïc; Gomez, Camila; Doligez, Agnès; Ageorges, Agnès; Roux, Catherine; Bertrand, Yves; Souquet, Jean-Marc; Cheynier, Véronique; This, Patrice

2009-11-01

The combination of QTL mapping studies of synthetic lines and association mapping studies of natural diversity represents an opportunity to throw light on the genetically based variation of quantitative traits. With the positional information provided through quantitative trait locus (QTL) mapping, which often leads to wide intervals encompassing numerous genes, it is now feasible to directly target candidate genes that are likely to be responsible for the observed variation in completely sequenced genomes and to test their effects through association genetics. This approach was performed in grape, a newly sequenced genome, to decipher the genetic architecture of anthocyanin content. Grapes may be either white or colored, ranging from the lightest pink to the darkest purple tones according to the amount of anthocyanin accumulated in the berry skin, which is a crucial trait for both wine quality and human nutrition. Although the determinism of the white phenotype has been fully identified, the genetic bases of the quantitative variation of anthocyanin content in berry skin remain unclear. A single QTL responsible for up to 62% of the variation in the anthocyanin content was mapped on a Syrah x Grenache F(1) pseudo-testcross. Among the 68 unigenes identified in the grape genome within the QTL interval, a cluster of four Myb-type genes was selected on the basis of physiological evidence (VvMybA1, VvMybA2, VvMybA3, and VvMybA4). From a core collection of natural resources (141 individuals), 32 polymorphisms revealed significant association, and extended linkage disequilibrium was observed. Using a multivariate regression method, we demonstrated that five polymorphisms in VvMybA genes except VvMybA4 (one retrotransposon, three single nucleotide polymorphisms and one 2-bp insertion/deletion) accounted for 84% of the observed variation. All these polymorphisms led to either structural changes in the MYB proteins or differences in the VvMybAs promoters. We concluded that the continuous variation in anthocyanin content in grape was explained mainly by a single gene cluster of three VvMybA genes. The use of natural diversity helped to reduce one QTL to a set of five quantitative trait nucleotides and gave a clear picture of how isogenes combined their effects to shape grape color. Such analysis also illustrates how isogenes combine their effect to shape a complex quantitative trait and enables the definition of markers directly targeted for upcoming breeding programs.

SNP by SNP by environment interaction network of alcoholism.

PubMed

Zollanvari, Amin; Alterovitz, Gil

2017-03-14

Alcoholism has a strong genetic component. Twin studies have demonstrated the heritability of a large proportion of phenotypic variance of alcoholism ranging from 50-80%. The search for genetic variants associated with this complex behavior has epitomized sequence-based studies for nearly a decade. The limited success of genome-wide association studies (GWAS), possibly precipitated by the polygenic nature of complex traits and behaviors, however, has demonstrated the need for novel, multivariate models capable of quantitatively capturing interactions between a host of genetic variants and their association with non-genetic factors. In this regard, capturing the network of SNP by SNP or SNP by environment interactions has recently gained much interest. Here, we assessed 3,776 individuals to construct a network capable of detecting and quantifying the interactions within and between plausible genetic and environmental factors of alcoholism. In this regard, we propose the use of first-order dependence tree of maximum weight as a potential statistical learning technique to delineate the pattern of dependencies underpinning such a complex trait. Using a predictive based analysis, we further rank the genes, demographic factors, biological pathways, and the interactions represented by our SNP [Formula: see text]SNP[Formula: see text]E network. The proposed framework is quite general and can be potentially applied to the study of other complex traits.

The maize methylome influences mRNA splice sites and reveals widespread paramutation-like switches guided by small RNA

USDA-ARS?s Scientific Manuscript database

Background Maize exhibits a wealth of epigenetic phenomena, from transposon silencing, cycling and presetting, to gene imprinting and paramutation. Furthermore, despite the complexity and sophistication of maize breeding, there is a large degree of “hidden” variation for many traits that is difficul...

MaizeGDB: Global support for maize research through open access information [abstract

USDA-ARS?s Scientific Manuscript database

MaizeGDB is the open-access global repository for maize genetic and genomic information – from single genes that determine nutritional quality to whole genome-scale data for complex traits including yield and drought tolerance. The data and tools at MaizeGDB enable researchers from Ethiopia to Ghan...

Between “design” and “bricolage”: Genetic networks, levels of selection, and adaptive evolution

PubMed Central

Wilkins, Adam S.

2007-01-01

The extent to which “developmental constraints” in complex organisms restrict evolutionary directions remains contentious. Yet, other forms of internal constraint, which have received less attention, may also exist. It will be argued here that a set of partial constraints below the level of phenotypes, those involving genes and molecules, influences and channels the set of possible evolutionary trajectories. At the top-most organizational level there are the genetic network modules, whose operations directly underlie complex morphological traits. The properties of these network modules, however, have themselves been set by the evolutionary history of the component genes and their interactions. Characterization of the components, structures, and operational dynamics of specific genetic networks should lead to a better understanding not only of the morphological traits they underlie but of the biases that influence the directions of evolutionary change. Furthermore, such knowledge may permit assessment of the relative degrees of probability of short evolutionary trajectories, those on the microevolutionary scale. In effect, a “network perspective” may help transform evolutionary biology into a scientific enterprise with greater predictive capability than it has hitherto possessed. PMID:17494754

Between "design" and "bricolage": genetic networks, levels of selection, and adaptive evolution.

PubMed

Wilkins, Adam S

2007-05-15

The extent to which "developmental constraints" in complex organisms restrict evolutionary directions remains contentious. Yet, other forms of internal constraint, which have received less attention, may also exist. It will be argued here that a set of partial constraints below the level of phenotypes, those involving genes and molecules, influences and channels the set of possible evolutionary trajectories. At the top-most organizational level there are the genetic network modules, whose operations directly underlie complex morphological traits. The properties of these network modules, however, have themselves been set by the evolutionary history of the component genes and their interactions. Characterization of the components, structures, and operational dynamics of specific genetic networks should lead to a better understanding not only of the morphological traits they underlie but of the biases that influence the directions of evolutionary change. Furthermore, such knowledge may permit assessment of the relative degrees of probability of short evolutionary trajectories, those on the microevolutionary scale. In effect, a "network perspective" may help transform evolutionary biology into a scientific enterprise with greater predictive capability than it has hitherto possessed.

LAILAPS: the plant science search engine.

PubMed

Esch, Maria; Chen, Jinbo; Colmsee, Christian; Klapperstück, Matthias; Grafahrend-Belau, Eva; Scholz, Uwe; Lange, Matthias

2015-01-01

With the number of sequenced plant genomes growing, the number of predicted genes and functional annotations is also increasing. The association between genes and phenotypic traits is currently of great interest. Unfortunately, the information available today is widely scattered over a number of different databases. Information retrieval (IR) has become an all-encompassing bioinformatics methodology for extracting knowledge from complex, heterogeneous and distributed databases, and therefore can be a useful tool for obtaining a comprehensive view of plant genomics, from genes to traits. Here we describe LAILAPS (http://lailaps.ipk-gatersleben.de), an IR system designed to link plant genomic data in the context of phenotypic attributes for a detailed forward genetic research. LAILAPS comprises around 65 million indexed documents, encompassing >13 major life science databases with around 80 million links to plant genomic resources. The LAILAPS search engine allows fuzzy querying for candidate genes linked to specific traits over a loosely integrated system of indexed and interlinked genome databases. Query assistance and an evidence-based annotation system enable time-efficient and comprehensive information retrieval. An artificial neural network incorporating user feedback and behavior tracking allows relevance sorting of results. We fully describe LAILAPS's functionality and capabilities by comparing this system's performance with other widely used systems and by reporting both a validation in maize and a knowledge discovery use-case focusing on candidate genes in barley. © The Author 2014. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists.

Identification and characterization of salt responsive miRNA-SSR markers in rice (Oryza sativa).

PubMed

Mondal, Tapan Kumar; Ganie, Showkat Ahmad

2014-02-10

Salinity is an important abiotic stress that affects agricultural production and productivity. It is a complex trait that is regulated by different molecular mechanisms. miRNAs are non-coding RNAs which are highly conserved and regulate gene expression. Simple sequence repeats (SSRs) are robust molecular markers for studying genetic diversity. Although several SSR markers are available now, challenge remains to identify the trait-specific SSRs which can be used for marker assisted breeding. In order to understand the genetic diversity of salt responsive-miRNA genes in rice, SSR markers were mined from 130 members of salt-responsive miRNA genes of rice and validated among the contrasting panels of tolerant as well as susceptible rice genotypes, each with 12 genotypes. Although 12 miR-SSRs were found to be polymorphic, only miR172b-SSR was able to differentiate the tolerant and susceptible genotypes in 2 different groups. It had also been found that miRNA genes were more diverse in susceptible genotypes than the tolerant one (as indicated by polymorphic index content) which might interfere to form the stem-loop structure of premature miRNA and their subsequent synthesis in susceptible genotypes. Thus, we concluded that length variations of the repeats in salt responsive miRNA genes may be responsible for a possible sensitivity to salinity adaptation. This is the first report of characterization of trait specific miRNA derived SSRs in plants. Copyright © 2013 Elsevier B.V. All rights reserved.

Natural Genetic Variation Influences Protein Abundances in C. elegans Developmental Signalling Pathways

PubMed Central

Singh, Kapil Dev; Roschitzki, Bernd; Snoek, L. Basten; Grossmann, Jonas; Zheng, Xue; Elvin, Mark; Kamkina, Polina; Schrimpf, Sabine P.; Poulin, Gino B.; Kammenga, Jan E.; Hengartner, Michael O.

2016-01-01

Complex traits, including common disease-related traits, are affected by many different genes that function in multiple pathways and networks. The apoptosis, MAPK, Notch, and Wnt signalling pathways play important roles in development and disease progression. At the moment we have a poor understanding of how allelic variation affects gene expression in these pathways at the level of translation. Here we report the effect of natural genetic variation on transcript and protein abundance involved in developmental signalling pathways in Caenorhabditis elegans. We used selected reaction monitoring to analyse proteins from the abovementioned four pathways in a set of recombinant inbred lines (RILs) generated from the wild-type strains N2 (Bristol) and CB4856 (Hawaii) to enable quantitative trait locus (QTL) mapping. About half of the cases from the 44 genes tested showed a statistically significant change in protein abundance between various strains, most of these were however very weak (below 1.3-fold change). We detected a distant QTL on the left arm of chromosome II that affected protein abundance of the phosphatidylserine receptor protein PSR-1, and two separate QTLs that influenced embryonic and ionizing radiation-induced apoptosis on chromosome IV. Our results demonstrate that natural variation in C. elegans is sufficient to cause significant changes in signalling pathways both at the gene expression (transcript and protein abundance) and phenotypic levels. PMID:26985669

Analysis of the porcine APOA2 gene expression in liver, polymorphism identification and association with fatty acid composition traits.

PubMed

Ballester, M; Revilla, M; Puig-Oliveras, A; Marchesi, J A P; Castelló, A; Corominas, J; Fernández, A I; Folch, J M

2016-10-01

APOA2 is a protein implicated in triglyceride, fatty acid and glucose metabolism. In pigs, the APOA2 gene is located on pig chromosome 4 (SSC4) in a QTL region affecting fatty acid composition, fatness and growth traits. In this study, we evaluated APOA2 as a candidate gene for meat quality traits in an Iberian × Landrace backcross population. The APOA2:c.131T>A polymorphism, located in exon 3 of APOA2 and determining a missense mutation, was associated with the percentage of hexadecenoic acid [C16:1(n-9)], linoleic acid [C18:2(n-6)], α-linolenic acid [C18:3(n-3)], dihomo-gamma-linolenic acid [C20:3(n-6)] and polyunsaturated fatty acids (PUFAs) in backfat. Furthermore, this SNP was associated with the global mRNA expression levels of APOA2 in liver and was used as a marker to determine allelic expression imbalance by pyrosequencing. We determined an overexpression of the T allele in heterozygous samples with a mean ratio of 2.8 (T/A), observing a high variability in the allelic expression among individuals. This result suggests that complex regulatory mechanisms, beyond a single polymorphism (e.g. epigenetic effects or multiple cis-acting polymorphisms), may be regulating APOA2 gene expression. © 2016 Stichting International Foundation for Animal Genetics.

A power study of bivariate LOD score analysis of a complex trait and fear/discomfort with strangers

PubMed Central

Ji, Fei; Lee, Dayoung; Mendell, Nancy Role

2005-01-01

Complex diseases are often reported along with disease-related traits (DRT). Sometimes investigators consider both disease and DRT phenotypes separately and sometimes they consider individuals as affected if they have either the disease or the DRT, or both. We propose instead to consider the joint distribution of the disease and the DRT and do a linkage analysis assuming a pleiotropic model. We evaluated our results through analysis of the simulated datasets provided by Genetic Analysis Workshop 14. We first conducted univariate linkage analysis of the simulated disease, Kofendrerd Personality Disorder and one of its simulated associated traits, phenotype b (fear/discomfort with strangers). Subsequently, we considered the bivariate phenotype, which combined the information on Kofendrerd Personality Disorder and fear/discomfort with strangers. We developed a program to perform bivariate linkage analysis using an extension to the Elston-Stewart peeling method of likelihood calculation. Using this program we considered the microsatellites within 30 cM of the gene pleiotropic for this simulated disease and DRT. Based on 100 simulations of 300 families we observed excellent power to detect linkage within 10 cM of the disease locus using the DRT and the bivariate trait. PMID:16451570

A power study of bivariate LOD score analysis of a complex trait and fear/discomfort with strangers.

PubMed

Ji, Fei; Lee, Dayoung; Mendell, Nancy Role

2005-12-30

Complex diseases are often reported along with disease-related traits (DRT). Sometimes investigators consider both disease and DRT phenotypes separately and sometimes they consider individuals as affected if they have either the disease or the DRT, or both. We propose instead to consider the joint distribution of the disease and the DRT and do a linkage analysis assuming a pleiotropic model. We evaluated our results through analysis of the simulated datasets provided by Genetic Analysis Workshop 14. We first conducted univariate linkage analysis of the simulated disease, Kofendrerd Personality Disorder and one of its simulated associated traits, phenotype b (fear/discomfort with strangers). Subsequently, we considered the bivariate phenotype, which combined the information on Kofendrerd Personality Disorder and fear/discomfort with strangers. We developed a program to perform bivariate linkage analysis using an extension to the Elston-Stewart peeling method of likelihood calculation. Using this program we considered the microsatellites within 30 cM of the gene pleiotropic for this simulated disease and DRT. Based on 100 simulations of 300 families we observed excellent power to detect linkage within 10 cM of the disease locus using the DRT and the bivariate trait.

Genetic Dissection of Learning and Memory in Mice

PubMed Central

Mineur, Yann S.; Crusio, Wim E.; Sluyter, Frans

2004-01-01

In this minireview, we discuss different strategies to dissect genetically the keystones of learning and memory. First, we broadly sketch the neurogenetic analysis of complex traits in mice. We then discuss two general strategies to find genes affecting learning and memory: candidate gene studies and whole genome searches. Next, we briefly review more recently developed techniques, such as microarrays and RNA interference. In addition, we focus on gene-environment interactions and endophenotypes. All sections are illustrated with examples from the learning and memory field, including a table summarizing the latest information about genes that have been shown to have effects on learning and memory. PMID:15656270

Association mapping analysis of fiber yield and quality traits in Upland cotton (Gossypium hirsutum L.).

PubMed

Ademe, Mulugeta Seyoum; He, Shoupu; Pan, Zhaoe; Sun, Junling; Wang, Qinglian; Qin, Hongde; Liu, Jinhai; Liu, Hui; Yang, Jun; Xu, Dongyong; Yang, Jinlong; Ma, Zhiying; Zhang, Jinbiao; Li, Zhikun; Cai, Zhongmin; Zhang, Xuelin; Zhang, Xin; Huang, Aifen; Yi, Xianda; Zhou, Guanyin; Li, Lin; Zhu, Haiyong; Pang, Baoyin; Wang, Liru; Jia, Yinhua; Du, Xiongming

2017-12-01

Fiber yield and quality are the most important traits for Upland cotton (Gossypium hirsutum L.). Identifying high yield and good fiber quality genes are the prime concern of researchers in cotton breeding. Association mapping offers an alternative and powerful method for detecting those complex agronomic traits. In this study, 198 simple sequence repeats (SSRs) were used to screen markers associated with fiber yield and quality traits with 302 elite Upland cotton accessions that were evaluated in 12 locations representing the Yellow River and Yangtze River cotton growing regions of China. Three subpopulations were found after the estimation of population structure. The pair-wise kinship values varied from 0 to 0.867. Only 1.59% of the total marker locus pairs showed significant linkage disequilibrium (LD, p < 0.001). The genome-wide LD decayed within the genetic distance of ~30 to 32 cM at r 2  = 0.1, and decreased to ~1 to 2 cM at r 2  = 0.2, indicating the potential for association mapping. Analysis based on a mixed linear model detected 57 significant (p < 0.01) marker-trait associations, including seven associations for fiber length, ten for fiber micronaire, nine for fiber strength, eight for fiber elongation, five for fiber uniformity index, five for fiber uniformity ratio, six for boll weight and seven for lint percent, for a total of 35 SSR markers, of which 11 markers were associated with more than one trait. Among marker-trait associations, 24 associations coincided with the previously reported quantitative trait loci (QTLs), the remainder were newly identified QTLs/genes. The QTLs identified in this study will potentially facilitate improvement of fiber yield and quality in the future cotton molecular breeding programs.

Meta-analysis of sex-specific genome-wide association studies.

PubMed

Magi, Reedik; Lindgren, Cecilia M; Morris, Andrew P

2010-12-01

Despite the success of genome-wide association studies, much of the genetic contribution to complex human traits is still unexplained. One potential source of genetic variation that may contribute to this "missing heritability" is that which differs in magnitude and/or direction between males and females, which could result from sexual dimorphism in gene expression. Such sex-differentiated effects are common in model organisms, and are becoming increasingly evident in human complex traits through large-scale male- and female-specific meta-analyses. In this article, we review the methodology for meta-analysis of sex-specific genome-wide association studies, and propose a sex-differentiated test of association with quantitative or dichotomous traits, which allows for heterogeneity of allelic effects between males and females. We perform detailed simulations to compare the power of the proposed sex-differentiated meta-analysis with the more traditional "sex-combined" approach, which is ambivalent to gender. The results of this study highlight only a small loss in power for the sex-differentiated meta-analysis when the allelic effects of the causal variant are the same in males and females. However, over a range of models of heterogeneity in allelic effects between genders, our sex-differentiated meta-analysis strategy offers substantial gains in power, and thus has the potential to discover novel loci contributing effects to complex human traits with existing genome-wide association data. © 2010 Wiley-Liss, Inc.

Accounting for Population Structure in Gene-by-Environment Interactions in Genome-Wide Association Studies Using Mixed Models.

PubMed

Sul, Jae Hoon; Bilow, Michael; Yang, Wen-Yun; Kostem, Emrah; Furlotte, Nick; He, Dan; Eskin, Eleazar

2016-03-01

Although genome-wide association studies (GWASs) have discovered numerous novel genetic variants associated with many complex traits and diseases, those genetic variants typically explain only a small fraction of phenotypic variance. Factors that account for phenotypic variance include environmental factors and gene-by-environment interactions (GEIs). Recently, several studies have conducted genome-wide gene-by-environment association analyses and demonstrated important roles of GEIs in complex traits. One of the main challenges in these association studies is to control effects of population structure that may cause spurious associations. Many studies have analyzed how population structure influences statistics of genetic variants and developed several statistical approaches to correct for population structure. However, the impact of population structure on GEI statistics in GWASs has not been extensively studied and nor have there been methods designed to correct for population structure on GEI statistics. In this paper, we show both analytically and empirically that population structure may cause spurious GEIs and use both simulation and two GWAS datasets to support our finding. We propose a statistical approach based on mixed models to account for population structure on GEI statistics. We find that our approach effectively controls population structure on statistics for GEIs as well as for genetic variants.

Identification of causal genes for complex traits

PubMed Central

Hormozdiari, Farhad; Kichaev, Gleb; Yang, Wen-Yun; Pasaniuc, Bogdan; Eskin, Eleazar

2015-01-01

Motivation: Although genome-wide association studies (GWAS) have identified thousands of variants associated with common diseases and complex traits, only a handful of these variants are validated to be causal. We consider ‘causal variants’ as variants which are responsible for the association signal at a locus. As opposed to association studies that benefit from linkage disequilibrium (LD), the main challenge in identifying causal variants at associated loci lies in distinguishing among the many closely correlated variants due to LD. This is particularly important for model organisms such as inbred mice, where LD extends much further than in human populations, resulting in large stretches of the genome with significantly associated variants. Furthermore, these model organisms are highly structured and require correction for population structure to remove potential spurious associations. Results: In this work, we propose CAVIAR-Gene (CAusal Variants Identification in Associated Regions), a novel method that is able to operate across large LD regions of the genome while also correcting for population structure. A key feature of our approach is that it provides as output a minimally sized set of genes that captures the genes which harbor causal variants with probability ρ. Through extensive simulations, we demonstrate that our method not only speeds up computation, but also have an average of 10% higher recall rate compared with the existing approaches. We validate our method using a real mouse high-density lipoprotein data (HDL) and show that CAVIAR-Gene is able to identify Apoa2 (a gene known to harbor causal variants for HDL), while reducing the number of genes that need to be tested for functionality by a factor of 2. Availability and implementation: Software is freely available for download at genetics.cs.ucla.edu/caviar. Contact: eeskin@cs.ucla.edu PMID:26072484

Identification of causal genes for complex traits.

PubMed

Hormozdiari, Farhad; Kichaev, Gleb; Yang, Wen-Yun; Pasaniuc, Bogdan; Eskin, Eleazar

2015-06-15

Although genome-wide association studies (GWAS) have identified thousands of variants associated with common diseases and complex traits, only a handful of these variants are validated to be causal. We consider 'causal variants' as variants which are responsible for the association signal at a locus. As opposed to association studies that benefit from linkage disequilibrium (LD), the main challenge in identifying causal variants at associated loci lies in distinguishing among the many closely correlated variants due to LD. This is particularly important for model organisms such as inbred mice, where LD extends much further than in human populations, resulting in large stretches of the genome with significantly associated variants. Furthermore, these model organisms are highly structured and require correction for population structure to remove potential spurious associations. In this work, we propose CAVIAR-Gene (CAusal Variants Identification in Associated Regions), a novel method that is able to operate across large LD regions of the genome while also correcting for population structure. A key feature of our approach is that it provides as output a minimally sized set of genes that captures the genes which harbor causal variants with probability ρ. Through extensive simulations, we demonstrate that our method not only speeds up computation, but also have an average of 10% higher recall rate compared with the existing approaches. We validate our method using a real mouse high-density lipoprotein data (HDL) and show that CAVIAR-Gene is able to identify Apoa2 (a gene known to harbor causal variants for HDL), while reducing the number of genes that need to be tested for functionality by a factor of 2. Software is freely available for download at genetics.cs.ucla.edu/caviar. © The Author 2015. Published by Oxford University Press.

Interspecies Systems Biology Uncovers Metabolites Affecting C. elegans Gene Expression and Life History Traits

PubMed Central

Watson, Emma; MacNeil, Lesley T.; Ritter, Ashlyn D.; Yilmaz, L. Safak; Rosebrock, Adam P.; Caudy, Amy A.; Walhout, Albertha J. M.

2014-01-01

SUMMARY Diet greatly influences gene expression and physiology. In mammals, elucidating the effects and mechanisms of individual nutrients is challenging due to the complexity of both the animal and its diet. Here we used an interspecies systems biology approach with Caenorhabditis elegans and two if its bacterial diets, Escherichia coli and Comamonas aquatica, to identify metabolites that affect the animal’s gene expression and physiology. We identify vitamin B12 as the major dilutable metabolite provided by Comamonas aq. that regulates gene expression, accelerates development and reduces fertility, but does not affect lifespan. We find that vitamin B12 has a dual role in the animal: it affects development and fertility via the methionine/S-Adenosylmethionine (SAM) cycle and breaks down the short-chain fatty acid propionic acid preventing its toxic buildup. Our interspecies systems biology approach provides a paradigm for understanding complex interactions between diet and physiology. PMID:24529378

Cross-Lagged Analysis of Interplay Between Differential Traits in Sibling Pairs: Validation and Application to Parenting Behavior and ADHD Symptomatology.

PubMed

Moscati, Arden; Verhulst, Brad; McKee, Kevin; Silberg, Judy; Eaves, Lindon

2018-01-01

Understanding the factors that contribute to behavioral traits is a complex task, and partitioning variance into latent genetic and environmental components is a useful beginning, but it should not also be the end. Many constructs are influenced by their contextual milieu, and accounting for background effects (such as gene-environment correlation) is necessary to avoid bias. This study introduces a method for examining the interplay between traits, in a longitudinal design using differential items in sibling pairs. The model is validated via simulation and power analysis, and we conclude with an application to paternal praise and ADHD symptoms in a twin sample. The model can help identify what type of genetic and environmental interplay may contribute to the dynamic relationship between traits using a cross-lagged panel framework. Overall, it presents a way to estimate and explicate the developmental interplay between a set of traits, free from many common sources of bias.

Comparison of Leaf Sheath Transcriptome Profiles with Physiological Traits of Bread Wheat Cultivars under Salinity Stress

PubMed Central

Trittermann, Christine; Berger, Bettina; Roy, Stuart J.; Seki, Motoaki; Shinozaki, Kazuo; Tester, Mark

2015-01-01

Salinity stress has significant negative effects on plant biomass production and crop yield. Salinity tolerance is controlled by complex systems of gene expression and ion transport. The relationship between specific features of mild salinity stress adaptation and gene expression was analyzed using four commercial varieties of bread wheat (Triticum aestivum) that have different levels of salinity tolerance. The high-throughput phenotyping system in The Plant Accelerator at the Australian Plant Phenomics Facility revealed variation in shoot relative growth rate and salinity tolerance among the four cultivars. Comparative analysis of gene expression in the leaf sheaths identified genes whose functions are potentially linked to shoot biomass development and salinity tolerance. Early responses to mild salinity stress through changes in gene expression have an influence on the acquisition of stress tolerance and improvement in biomass accumulation during the early “osmotic” phase of salinity stress. In addition, results revealed transcript profiles for the wheat cultivars that were different from those of usual stress-inducible genes, but were related to those of plant growth. These findings suggest that, in the process of breeding, selection of specific traits with various salinity stress-inducible genes in commercial bread wheat has led to adaptation to mild salinity conditions. PMID:26244554

Hidden state prediction: a modification of classic ancestral state reconstruction algorithms helps unravel complex symbioses

PubMed Central

Zaneveld, Jesse R. R.; Thurber, Rebecca L. V.

2014-01-01

Complex symbioses between animal or plant hosts and their associated microbiotas can involve thousands of species and millions of genes. Because of the number of interacting partners, it is often impractical to study all organisms or genes in these host-microbe symbioses individually. Yet new phylogenetic predictive methods can use the wealth of accumulated data on diverse model organisms to make inferences into the properties of less well-studied species and gene families. Predictive functional profiling methods use evolutionary models based on the properties of studied relatives to put bounds on the likely characteristics of an organism or gene that has not yet been studied in detail. These techniques have been applied to predict diverse features of host-associated microbial communities ranging from the enzymatic function of uncharacterized genes to the gene content of uncultured microorganisms. We consider these phylogenetically informed predictive techniques from disparate fields as examples of a general class of algorithms for Hidden State Prediction (HSP), and argue that HSP methods have broad value in predicting organismal traits in a variety of contexts, including the study of complex host-microbe symbioses. PMID:25202302

Simulating the yield impacts of organ-level quantitative trait loci associated with drought response in maize: a "gene-to-phenotype" modeling approach.

PubMed

Chenu, Karine; Chapman, Scott C; Tardieu, François; McLean, Greg; Welcker, Claude; Hammer, Graeme L

2009-12-01

Under drought, substantial genotype-environment (G x E) interactions impede breeding progress for yield. Identifying genetic controls associated with yield response is confounded by poor genetic correlations across testing environments. Part of this problem is related to our inability to account for the interplay of genetic controls, physiological traits, and environmental conditions throughout the crop cycle. We propose a modeling approach to bridge this "gene-to-phenotype" gap. For maize under drought, we simulated the impact of quantitative trait loci (QTL) controlling two key processes (leaf and silk elongation) that influence crop growth, water use, and grain yield. Substantial G x E interaction for yield was simulated for hypothetical recombinant inbred lines (RILs) across different seasonal patterns of drought. QTL that accelerated leaf elongation caused an increase in crop leaf area and yield in well-watered or preflowering water deficit conditions, but a reduction in yield under terminal stresses (as such "leafy" genotypes prematurely exhausted the water supply). The QTL impact on yield was substantially enhanced by including pleiotropic effects of these QTL on silk elongation and on consequent grain set. The simulations obtained illustrated the difficulty of interpreting the genetic control of yield for genotypes influenced only by the additive effects of QTL associated with leaf and silk growth. The results highlight the potential of integrative simulation modeling for gene-to-phenotype prediction and for exploiting G x E interactions for complex traits such as drought tolerance.

Parsing parallel evolution: ecological divergence and differential gene expression in the adaptive radiations of thick-lipped Midas cichlid fishes from Nicaragua.

PubMed

Manousaki, Tereza; Hull, Pincelli M; Kusche, Henrik; Machado-Schiaffino, Gonzalo; Franchini, Paolo; Harrod, Chris; Elmer, Kathryn R; Meyer, Axel

2013-02-01

The study of parallel evolution facilitates the discovery of common rules of diversification. Here, we examine the repeated evolution of thick lips in Midas cichlid fishes (the Amphilophus citrinellus species complex)-from two Great Lakes and two crater lakes in Nicaragua-to assess whether similar changes in ecology, phenotypic trophic traits and gene expression accompany parallel trait evolution. Using next-generation sequencing technology, we characterize transcriptome-wide differential gene expression in the lips of wild-caught sympatric thick- and thin-lipped cichlids from all four instances of repeated thick-lip evolution. Six genes (apolipoprotein D, myelin-associated glycoprotein precursor, four-and-a-half LIM domain protein 2, calpain-9, GTPase IMAP family member 8-like and one hypothetical protein) are significantly underexpressed in the thick-lipped morph across all four lakes. However, other aspects of lips' gene expression in sympatric morphs differ in a lake-specific pattern, including the magnitude of differentially expressed genes (97-510). Generally, fewer genes are differentially expressed among morphs in the younger crater lakes than in those from the older Great Lakes. Body shape, lower pharyngeal jaw size and shape, and stable isotopes (δ(13)C and δ(15)N) differ between all sympatric morphs, with the greatest differentiation in the Great Lake Nicaragua. Some ecological traits evolve in parallel (those related to foraging ecology; e.g. lip size, body and head shape) but others, somewhat surprisingly, do not (those related to diet and food processing; e.g. jaw size and shape, stable isotopes). Taken together, this case of parallelism among thick- and thin-lipped cichlids shows a mosaic pattern of parallel and nonparallel evolution. © 2012 Blackwell Publishing Ltd.

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

On the Origin of Complex Adaptive Traits: Progress Since the Darwin Versus Mivart Debate.

PubMed

Suzuki, Takao K

2017-06-01

The evolutionary origin of complex adaptive traits has been a controversial topic in the history of evolutionary biology. Although Darwin argued for the gradual origins of complex adaptive traits within the theory of natural selection, Mivart insisted that natural selection could not account for the incipient stages of complex traits. The debate starting from Darwin and Mivart eventually engendered two opposite views: gradualism and saltationism. Although this has been a long-standing debate, the issue remains unresolved. However, recent studies have interrogated classic examples of complex traits, such as the asymmetrical eyes of flatfishes and leaf mimicry of butterfly wings, whose origins were debated by Darwin and Mivart. Here, I review recent findings as a starting point to provide a modern picture of the evolution of complex adaptive traits. First, I summarize the empirical evidence that unveils the evolutionary steps toward complex traits. I then argue that the evolution of complex traits could be understood within the concept of "reducible complexity." Through these discussions, I propose a conceptual framework for the formation of complex traits, named as reducible-composable multicomponent systems, that satisfy two major characteristics: reducibility into a sum of subcomponents and composability to construct traits from various additional and combinatorial arrangements of the subcomponents. This conceptual framework provides an analytical foundation for exploring evolutionary pathways to build up complex traits. This review provides certain essential avenues for deciphering the origin of complex adaptive traits. © 2017 Wiley Periodicals, Inc.

Two-trait-locus linkage analysis: A powerful strategy for mapping complex genetic traits

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

Schork, N.J.; Boehnke, M.; Terwilliger, J.D.

1993-11-01

Nearly all diseases mapped to date follow clear Mendelian, single-locus segregation patterns. In contrast, many common familial diseases such as diabetes, psoriasis, several forms of cancer, and schizophrenia are familial and appear to have a genetic component but do not exhibit simple Mendelian transmission. More complex models are required to explain the genetics of these important diseases. In this paper, the authors explore two-trait-locus, two-marker-locus linkage analysis in which two trait loci are mapped simultaneously to separate genetic markers. The authors compare the utility of this approach to standard one-trait-locus, one-marker-locus linkage analysis with and without allowance for heterogeneity. Themore » authors also compare the utility of the two-trait-locus, two-marker-locus analysis to two-trait-locus, one-marker-locus linkage analysis. For common diseases, pedigrees are often bilineal, with disease genes entering via two or more unrelated pedigree members. Since such pedigrees often are avoided in linkage studies, the authors also investigate the relative information content of unilineal and bilineal pedigrees. For the dominant-or-recessive and threshold models that the authors consider, the authors find that two-trait-locus, two-marker-locus linkage analysis can provide substantially more linkage information, as measured by expected maximum lod score, than standard one-trait-locus, one-marker-locus methods, even allowing for heterogeneity, while, for a dominant-or-dominant generating model, one-locus models that allow for heterogeneity extract essentially as much information as the two-trait-locus methods. For these three models, the authors also find that bilineal pedigrees provide sufficient linkage information to warrant their inclusion in such studies. The authors discuss strategies for assessing the significance of the two linkages assumed in two-trait-locus, two-marker-locus models. 37 refs., 1 fig., 4 tabs.« less

Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease.

PubMed

Baillie, J Kenneth; Bretherick, Andrew; Haley, Christopher S; Clohisey, Sara; Gray, Alan; Neyton, Lucile P A; Barrett, Jeffrey; Stahl, Eli A; Tenesa, Albert; Andersson, Robin; Brown, J Ben; Faulkner, Geoffrey J; Lizio, Marina; Schaefer, Ulf; Daub, Carsten; Itoh, Masayoshi; Kondo, Naoto; Lassmann, Timo; Kawai, Jun; Mole, Damian; Bajic, Vladimir B; Heutink, Peter; Rehli, Michael; Kawaji, Hideya; Sandelin, Albin; Suzuki, Harukazu; Satsangi, Jack; Wells, Christine A; Hacohen, Nir; Freeman, Thomas C; Hayashizaki, Yoshihide; Carninci, Piero; Forrest, Alistair R R; Hume, David A

2018-03-01

Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn's disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits.

Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease

PubMed Central

Gray, Alan; Neyton, Lucile P. A.; Barrett, Jeffrey; Stahl, Eli A.; Tenesa, Albert; Andersson, Robin; Brown, J. Ben; Faulkner, Geoffrey J.; Lizio, Marina; Schaefer, Ulf; Daub, Carsten; Kondo, Naoto; Lassmann, Timo; Kawai, Jun; Kawaji, Hideya; Suzuki, Harukazu; Satsangi, Jack; Wells, Christine A.; Hacohen, Nir; Freeman, Thomas C.; Hayashizaki, Yoshihide; Forrest, Alistair R. R.; Hume, David A.

2018-01-01

Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn’s disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits. PMID:29494619

DNA sequence polymorphisms within the bovine guanine nucleotide-binding protein Gs subunit alpha (Gsα)-encoding (GNAS) genomic imprinting domain are associated with performance traits.

PubMed

Sikora, Klaudia M; Magee, David A; Berkowicz, Erik W; Berry, Donagh P; Howard, Dawn J; Mullen, Michael P; Evans, Ross D; Machugh, David E; Spillane, Charles

2011-01-07

Genes which are epigenetically regulated via genomic imprinting can be potential targets for artificial selection during animal breeding. Indeed, imprinted loci have been shown to underlie some important quantitative traits in domestic mammals, most notably muscle mass and fat deposition. In this candidate gene study, we have identified novel associations between six validated single nucleotide polymorphisms (SNPs) spanning a 97.6 kb region within the bovine guanine nucleotide-binding protein Gs subunit alpha gene (GNAS) domain on bovine chromosome 13 and genetic merit for a range of performance traits in 848 progeny-tested Holstein-Friesian sires. The mammalian GNAS domain consists of a number of reciprocally-imprinted, alternatively-spliced genes which can play a major role in growth, development and disease in mice and humans. Based on the current annotation of the bovine GNAS domain, four of the SNPs analysed (rs43101491, rs43101493, rs43101485 and rs43101486) were located upstream of the GNAS gene, while one SNP (rs41694646) was located in the second intron of the GNAS gene. The final SNP (rs41694656) was located in the first exon of transcripts encoding the putative bovine neuroendocrine-specific protein NESP55, resulting in an aspartic acid-to-asparagine amino acid substitution at amino acid position 192. SNP genotype-phenotype association analyses indicate that the single intronic GNAS SNP (rs41694646) is associated (P ≤ 0.05) with a range of performance traits including milk yield, milk protein yield, the content of fat and protein in milk, culled cow carcass weight and progeny carcass conformation, measures of animal body size, direct calving difficulty (i.e. difficulty in calving due to the size of the calf) and gestation length. Association (P ≤ 0.01) with direct calving difficulty (i.e. due to calf size) and maternal calving difficulty (i.e. due to the maternal pelvic width size) was also observed at the rs43101491 SNP. Following adjustment for multiple-testing, significant association (q ≤ 0.05) remained between the rs41694646 SNP and four traits (animal stature, body depth, direct calving difficulty and milk yield) only. Notably, the single SNP in the bovine NESP55 gene (rs41694656) was associated (P ≤ 0.01) with somatic cell count--an often-cited indicator of resistance to mastitis and overall health status of the mammary system--and previous studies have demonstrated that the chromosomal region to where the GNAS domain maps underlies an important quantitative trait locus for this trait. This association, however, was not significant after adjustment for multiple testing. The three remaining SNPs assayed were not associated with any of the performance traits analysed in this study. Analysis of all pairwise linkage disequilibrium (r2) values suggests that most allele substitution effects for the assayed SNPs observed are independent. Finally, the polymorphic coding SNP in the putative bovine NESP55 gene was used to test the imprinting status of this gene across a range of foetal bovine tissues. Previous studies in other mammalian species have shown that DNA sequence variation within the imprinted GNAS gene cluster contributes to several physiological and metabolic disorders, including obesity in humans and mice. Similarly, the results presented here indicate an important role for the imprinted GNAS cluster in underlying complex performance traits in cattle such as animal growth, calving, fertility and health. These findings suggest that GNAS domain-associated polymorphisms may serve as important genetic markers for future livestock breeding programs and support previous studies that candidate imprinted loci may act as molecular targets for the genetic improvement of agricultural populations. In addition, we present new evidence that the bovine NESP55 gene is epigenetically regulated as a maternally expressed imprinted gene in placental and intestinal tissues from 8-10 week old bovine foetuses.

DNA sequence polymorphisms within the bovine guanine nucleotide-binding protein Gs subunit alpha (Gsα)-encoding (GNAS) genomic imprinting domain are associated with performance traits

PubMed Central

2011-01-01

Background Genes which are epigenetically regulated via genomic imprinting can be potential targets for artificial selection during animal breeding. Indeed, imprinted loci have been shown to underlie some important quantitative traits in domestic mammals, most notably muscle mass and fat deposition. In this candidate gene study, we have identified novel associations between six validated single nucleotide polymorphisms (SNPs) spanning a 97.6 kb region within the bovine guanine nucleotide-binding protein Gs subunit alpha gene (GNAS) domain on bovine chromosome 13 and genetic merit for a range of performance traits in 848 progeny-tested Holstein-Friesian sires. The mammalian GNAS domain consists of a number of reciprocally-imprinted, alternatively-spliced genes which can play a major role in growth, development and disease in mice and humans. Based on the current annotation of the bovine GNAS domain, four of the SNPs analysed (rs43101491, rs43101493, rs43101485 and rs43101486) were located upstream of the GNAS gene, while one SNP (rs41694646) was located in the second intron of the GNAS gene. The final SNP (rs41694656) was located in the first exon of transcripts encoding the putative bovine neuroendocrine-specific protein NESP55, resulting in an aspartic acid-to-asparagine amino acid substitution at amino acid position 192. Results SNP genotype-phenotype association analyses indicate that the single intronic GNAS SNP (rs41694646) is associated (P ≤ 0.05) with a range of performance traits including milk yield, milk protein yield, the content of fat and protein in milk, culled cow carcass weight and progeny carcass conformation, measures of animal body size, direct calving difficulty (i.e. difficulty in calving due to the size of the calf) and gestation length. Association (P ≤ 0.01) with direct calving difficulty (i.e. due to calf size) and maternal calving difficulty (i.e. due to the maternal pelvic width size) was also observed at the rs43101491 SNP. Following adjustment for multiple-testing, significant association (q ≤ 0.05) remained between the rs41694646 SNP and four traits (animal stature, body depth, direct calving difficulty and milk yield) only. Notably, the single SNP in the bovine NESP55 gene (rs41694656) was associated (P ≤ 0.01) with somatic cell count--an often-cited indicator of resistance to mastitis and overall health status of the mammary system--and previous studies have demonstrated that the chromosomal region to where the GNAS domain maps underlies an important quantitative trait locus for this trait. This association, however, was not significant after adjustment for multiple testing. The three remaining SNPs assayed were not associated with any of the performance traits analysed in this study. Analysis of all pairwise linkage disequilibrium (r2) values suggests that most allele substitution effects for the assayed SNPs observed are independent. Finally, the polymorphic coding SNP in the putative bovine NESP55 gene was used to test the imprinting status of this gene across a range of foetal bovine tissues. Conclusions Previous studies in other mammalian species have shown that DNA sequence variation within the imprinted GNAS gene cluster contributes to several physiological and metabolic disorders, including obesity in humans and mice. Similarly, the results presented here indicate an important role for the imprinted GNAS cluster in underlying complex performance traits in cattle such as animal growth, calving, fertility and health. These findings suggest that GNAS domain-associated polymorphisms may serve as important genetic markers for future livestock breeding programs and support previous studies that candidate imprinted loci may act as molecular targets for the genetic improvement of agricultural populations. In addition, we present new evidence that the bovine NESP55 gene is epigenetically regulated as a maternally expressed imprinted gene in placental and intestinal tissues from 8-10 week old bovine foetuses. PMID:21214909

Association analysis for udder index and milking speed with imputed whole-genome sequence variants in Nordic Holstein cattle.

PubMed

Jardim, Júlia Gazzoni; Guldbrandtsen, Bernt; Lund, Mogens Sandø; Sahana, Goutam

2018-03-01

Genome-wide association testing facilitates the identification of genetic variants associated with complex traits. Mapping genes that promote genetic resistance to mastitis could reduce the cost of antibiotic use and enhance animal welfare and milk production by improving outcomes of breeding for udder health. Using imputed whole-genome sequence variants, we carried out association studies for 2 traits related to udder health, udder index, and milking speed in Nordic Holstein cattle. A total of 4,921 bulls genotyped with the BovineSNP50 BeadChip array were imputed to high-density genotypes (Illumina BovineHD BeadChip, Illumina, San Diego, CA) and, subsequently, to whole-genome sequence variants. An association analysis was carried out using a linear mixed model. Phenotypes used in the association analyses were deregressed breeding values. Multitrait meta-analysis was carried out for these 2 traits. We identified 10 and 8 chromosomes harboring markers that were significantly associated with udder index and milking speed, respectively. Strongest association signals were observed on chromosome 20 for udder index and chromosome 19 for milking speed. Multitrait meta-analysis identified 13 chromosomes harboring associated markers for the combination of udder index and milking speed. The associated region on chromosome 20 overlapped with earlier reported quantitative trait loci for similar traits in other cattle populations. Moreover, this region was located close to the FYB gene, which is involved in platelet activation and controls IL-2 expression; FYB is a strong candidate gene for udder health and worthy of further investigation. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Genetic determinants of cardiometabolic risk: a proposed model for phenotype association and interaction.

PubMed

Blackett, Piers R; Sanghera, Dharambir K

2013-01-01

This review provides a translational and unifying summary of metabolic syndrome genetics and highlights evidence that genetic studies are starting to unravel and untangle origins of the complex and challenging cluster of disease phenotypes. The associated genes effectively express in the brain, liver, kidney, arterial endothelium, adipocytes, myocytes, and β cells. Progression of syndrome traits has been associated with ectopic lipid accumulation in the arterial wall, visceral adipocytes, myocytes, and liver. Thus, it follows that the genetics of dyslipidemia, obesity, and nonalcoholic fatty liver disease are central in triggering progression of the syndrome to overt expression of disease traits and have become a key focus of interest for early detection and for designing prevention and treatments. To support the "birds' eye view" approach, we provide a road-map depicting commonality and interrelationships between the traits and their genetic and environmental determinants based on known risk factors, metabolic pathways, pharmacologic targets, treatment responses, gene networks, pleiotropy, and association with circadian rhythm. Although only a small portion of the known heritability is accounted for and there is insufficient support for clinical application of gene-based prediction models, there is direction and encouraging progress in a rapidly moving field that is beginning to show clinical relevance. Copyright © 2013 National Lipid Association. Published by Elsevier Inc. All rights reserved.

Genetic Determinants of Cardio-Metabolic Risk: A Proposed Model for Phenotype Association and Interaction

PubMed Central

Blackett, Piers R; Sanghera, Dharambir K

2012-01-01

This review provides a translational and unifying summary of metabolic syndrome genetics and highlights evidence that genetic studies are starting to unravel and untangle origins of the complex and challenging cluster of disease phenotypes. The associated genes effectively express in the brain, liver, kidney, arterial endothelium, adipocytes, myocytes and β cells. Progression of syndrome traits has been associated with ectopic lipid accumulation in the arterial wall, visceral adipocytes, myocytes, and liver. Thus it follows that the genetics of dyslipidemia, obesity, and non-alcoholic fatty liver (NAFLD) disease are central in triggering progression of the syndrome to overt expression of disease traits, and have become a key focus of interest for early detection and for designing prevention and treatments. To support the “birds’ eye view” approach we provide a road-map depicting commonality and interrelationships between the traits and their genetic and environmental determinants based on known risk factors, metabolic pathways, pharmacological targets, treatment responses, gene networks, pleiotropy, and association with circadian rhythm. Although only a small portion of the known heritability is accounted for and there is insufficient support for clinical application of gene-based prediction models, there is direction and encouraging progress in a rapidly moving field that is beginning to show clinical relevance. PMID:23351585

Genetic control of root growth: from genes to networks

PubMed Central

Slovak, Radka; Ogura, Takehiko; Satbhai, Santosh B.; Ristova, Daniela; Busch, Wolfgang

2016-01-01

Background Roots are essential organs for higher plants. They provide the plant with nutrients and water, anchor the plant in the soil, and can serve as energy storage organs. One remarkable feature of roots is that they are able to adjust their growth to changing environments. This adjustment is possible through mechanisms that modulate a diverse set of root traits such as growth rate, diameter, growth direction and lateral root formation. The basis of these traits and their modulation are at the cellular level, where a multitude of genes and gene networks precisely regulate development in time and space and tune it to environmental conditions. Scope This review first describes the root system and then presents fundamental work that has shed light on the basic regulatory principles of root growth and development. It then considers emerging complexities and how they have been addressed using systems-biology approaches, and then describes and argues for a systems-genetics approach. For reasons of simplicity and conciseness, this review is mostly limited to work from the model plant Arabidopsis thaliana, in which much of the research in root growth regulation at the molecular level has been conducted. Conclusions While forward genetic approaches have identified key regulators and genetic pathways, systems-biology approaches have been successful in shedding light on complex biological processes, for instance molecular mechanisms involving the quantitative interaction of several molecular components, or the interaction of large numbers of genes. However, there are significant limitations in many of these methods for capturing dynamic processes, as well as relating these processes to genotypic and phenotypic variation. The emerging field of systems genetics promises to overcome some of these limitations by linking genotypes to complex phenotypic and molecular data using approaches from different fields, such as genetics, genomics, systems biology and phenomics. PMID:26558398

Variation in the Williams syndrome GTF2I gene and anxiety proneness interactively affect prefrontal cortical response to aversive stimuli.

PubMed

Jabbi, M; Chen, Q; Turner, N; Kohn, P; White, M; Kippenhan, J S; Dickinson, D; Kolachana, B; Mattay, V; Weinberger, D R; Berman, K F

2015-08-18

Characterizing the molecular mechanisms underlying the heritability of complex behavioral traits such as human anxiety remains a challenging endeavor for behavioral neuroscience. Copy-number variation (CNV) in the general transcription factor gene, GTF2I, located in the 7q11.23 chromosomal region that is hemideleted in Williams syndrome and duplicated in the 7q11.23 duplication syndrome (Dup7), is associated with gene-dose-dependent anxiety in mouse models and in both Williams syndrome and Dup7. Because of this recent preclinical and clinical identification of a genetic influence on anxiety, we examined whether sequence variation in GTF2I, specifically the single-nucleotide polymorphism rs2527367, interacts with trait and state anxiety to collectively impact neural response to anxiety-laden social stimuli. Two hundred and sixty healthy adults completed the Tridimensional Personality Questionnaire Harm Avoidance (HA) subscale, a trait measure of anxiety proneness, and underwent functional magnetic resonance imaging (fMRI) while matching aversive (fearful or angry) facial identity. We found an interaction between GTF2I allelic variations and HA that affects brain response: in individuals homozygous for the major allele, there was no correlation between HA and whole-brain response to aversive cues, whereas in heterozygotes and individuals homozygous for the minor allele, there was a positive correlation between HA sub-scores and a selective dorsolateral prefrontal cortex (DLPFC) responsivity during the processing of aversive stimuli. These results demonstrate that sequence variation in the GTF2I gene influences the relationship between trait anxiety and brain response to aversive social cues in healthy individuals, supporting a role for this neurogenetic mechanism in anxiety.

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

A survey of single nucleotide polymorphisms identified from whole-genome sequencing and their functional effect in the porcine genome

USDA-ARS?s Scientific Manuscript database

Genetic variants detected from sequence have been used to successfully identify causal variants and map complex traits in several organisms. High and moderate impact variants, those expected to alter or disrupt the protein coded by a gene and those that regulate protein production, likely have a mor...

Selection for genetic markers in beef cattle reveals complex associations of thyroglobulin and casein1-S1 with carcass and meat traits

USDA-ARS?s Scientific Manuscript database

Genetic markers in casein (CSN1S1) and thyroglobulin (TG) genes have previously been associated with fat distribution in cattle. Determining the nature of these genetic associations (additive, recessive, or dominant) has been difficult because both markers have small minor allele frequencies in mos...

The mitonuclear compatibility hypothesis of sexual selection

PubMed Central

Hill, Geoffrey E.; Johnson, James D.

2013-01-01

Why females assess ornaments when choosing mates remains a central question in evolutionary biology. We hypothesize that the imperative for a choosing female to find a mate with nuclear oxidative phosphorylation (OXPHOS) genes that are compatible with her mitochondrial OXPHOS genes drives the evolution of ornaments. Indicator traits are proposed to signal the efficiency of OXPHOS function thus enabling females to select mates with nuclear genes that are compatible with maternal mitochondrial genes in the formation of OXPHOS complexes. Species-typical pattern of ornamentation is proposed to serve as a marker of mitochondrial type ensuring that females assess prospective mates with a shared mitochondrial background. The mitonuclear compatibility hypothesis predicts that the production of ornaments will be closely linked to OXPHOS pathways, and that sexual selection for compatible mates will be strongest when genes for nuclear components of OXPHOS complexes are Z-linked. The implications of this hypothesis are that sexual selection may serve as a driver for the evolution of more efficient cellular respiration. PMID:23945683

Genetic Analysis of Strawberry Fruit Aroma and Identification of O-Methyltransferase FaOMT as the Locus Controlling Natural Variation in Mesifurane Content1[C][W][OA

PubMed Central

Zorrilla-Fontanesi, Yasmín; Rambla, José-Luis; Cabeza, Amalia; Medina, Juan J.; Sánchez-Sevilla, José F.; Valpuesta, Victoriano; Botella, Miguel A.; Granell, Antonio; Amaya, Iraida

2012-01-01

Improvement of strawberry (Fragaria × ananassa) fruit flavor is an important goal in breeding programs. To investigate genetic factors controlling this complex trait, a strawberry mapping population derived from genotype ‘1392’, selected for its superior flavor, and ‘232’ was profiled for volatile compounds over 4 years by headspace solid phase microextraction coupled to gas chromatography and mass spectrometry. More than 300 volatile compounds were detected, of which 87 were identified by comparison of mass spectrum and retention time to those of pure standards. Parental line ‘1392’ displayed higher volatile levels than ‘232’, and these and many other compounds with similar levels in both parents segregated in the progeny. Cluster analysis grouped the volatiles into distinct chemically related families and revealed a complex metabolic network underlying volatile production in strawberry fruit. Quantitative trait loci (QTL) detection was carried out over 3 years based on a double pseudo-testcross strategy. Seventy QTLs covering 48 different volatiles were detected, with several of them being stable over time and mapped as major QTLs. Loci controlling γ-decalactone and mesifurane content were mapped as qualitative traits. Using a candidate gene approach we have assigned genes that are likely responsible for several of the QTLs. As a proof of concept we show that one homoeolog of the O-methyltransferase gene (FaOMT) is the locus responsible for the natural variation of mesifurane content. Sequence analysis identified 30 bp in the promoter of this FaOMT homoeolog containing putative binding sites for basic/helix-loop-helix, MYB, and BZIP transcription factors. This polymorphism fully cosegregates with both the presence of mesifurane and the high expression of FaOMT during ripening. PMID:22474217

Birth Cohort, Age, and Sex Strongly Modulate Effects of Lipid Risk Alleles Identified in Genome-Wide Association Studies

PubMed Central

Kulminski, Alexander M.; Culminskaya, Irina; Arbeev, Konstantin G.; Arbeeva, Liubov; Ukraintseva, Svetlana V.; Stallard, Eric; Wu, Deqing; Yashin, Anatoliy I.

2015-01-01

Insights into genetic origin of diseases and related traits could substantially impact strategies for improving human health. The results of genome-wide association studies (GWAS) are often positioned as discoveries of unconditional risk alleles of complex health traits. We re-analyzed the associations of single nucleotide polymorphisms (SNPs) associated with total cholesterol (TC) in a large-scale GWAS meta-analysis. We focused on three generations of genotyped participants of the Framingham Heart Study (FHS). We show that the effects of all ten directly-genotyped SNPs were clustered in different FHS generations and/or birth cohorts in a sex-specific or sex-unspecific manner. The sample size and procedure-therapeutic issues play, at most, a minor role in this clustering. An important result was clustering of significant associations with the strongest effects in the youngest, or 3rd Generation, cohort. These results imply that an assumption of unconditional connections of these SNPs with TC is generally implausible and that a demographic perspective can substantially improve GWAS efficiency. The analyses of genetic effects in age-matched samples suggest a role of environmental and age-related mechanisms in the associations of different SNPs with TC. Analysis of the literature supports systemic roles for genes for these SNPs beyond those related to lipid metabolism. Our analyses reveal strong antagonistic effects of rs2479409 (the PCSK9 gene) that cautions strategies aimed at targeting this gene in the next generation of lipid drugs. Our results suggest that standard GWAS strategies need to be advanced in order to appropriately address the problem of genetic susceptibility to complex traits that is imperative for translation to health care. PMID:26295473

Increased Transcript Complexity in Genes Associated with Chronic Obstructive Pulmonary Disease

PubMed Central

Lackey, Lela; McArthur, Evonne; Laederach, Alain

2015-01-01

Genome-wide association studies aim to correlate genotype with phenotype. Many common diseases including Type II diabetes, Alzheimer’s, Parkinson’s and Chronic Obstructive Pulmonary Disease (COPD) are complex genetic traits with hundreds of different loci that are associated with varied disease risk. Identifying common features in the genes associated with each disease remains a challenge. Furthermore, the role of post-transcriptional regulation, and in particular alternative splicing, is still poorly understood in most multigenic diseases. We therefore compiled comprehensive lists of genes associated with Type II diabetes, Alzheimer’s, Parkinson’s and COPD in an attempt to identify common features of their corresponding mRNA transcripts within each gene set. The SERPINA1 gene is a well-recognized genetic risk factor of COPD and it produces 11 transcript variants, which is exceptional for a human gene. This led us to hypothesize that other genes associated with COPD, and complex disorders in general, are highly transcriptionally diverse. We found that COPD-associated genes have a statistically significant enrichment in transcript complexity stemming from a disproportionately high level of alternative splicing, however, Type II Diabetes, Alzheimer’s and Parkinson’s disease genes were not significantly enriched. We also identified a subset of transcriptionally complex COPD-associated genes (~40%) that are differentially expressed between mild, moderate and severe COPD. Although the genes associated with other lung diseases are not extensively documented, we found preliminary data that idiopathic pulmonary disease genes, but not cystic fibrosis modulators, are also more transcriptionally complex. Interestingly, complex COPD transcripts are more often the product of alternative acceptor site usage. To verify the biological importance of these alternative transcripts, we used RNA-sequencing analyses to determine that COPD-associated genes are frequently expressed in lung and liver tissues and are regulated in a tissue-specific manner. Additionally, many complex COPD-associated genes are spliced differently between COPD and non-COPD patients. Our analysis therefore suggests that post-transcriptional regulation, particularly alternative splicing, is an important feature specific to COPD disease etiology that warrants further investigation. PMID:26480348

Integrating Evolutionary Game Theory into Mechanistic Genotype-Phenotype Mapping.

PubMed

Zhu, Xuli; Jiang, Libo; Ye, Meixia; Sun, Lidan; Gragnoli, Claudia; Wu, Rongling

2016-05-01

Natural selection has shaped the evolution of organisms toward optimizing their structural and functional design. However, how this universal principle can enhance genotype-phenotype mapping of quantitative traits has remained unexplored. Here we show that the integration of this principle and functional mapping through evolutionary game theory gains new insight into the genetic architecture of complex traits. By viewing phenotype formation as an evolutionary system, we formulate mathematical equations to model the ecological mechanisms that drive the interaction and coordination of its constituent components toward population dynamics and stability. Functional mapping provides a procedure for estimating the genetic parameters that specify the dynamic relationship of competition and cooperation and predicting how genes mediate the evolution of this relationship during trait formation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Genetic diversity of disease-associated loci in Turkish population.

PubMed

Karaca, Sefayet; Cesuroglu, Tomris; Karaca, Mehmet; Erge, Sema; Polimanti, Renato

2015-04-01

Many consortia and international projects have investigated the human genetic variation of a large number of ethno-geographic groups. However, populations with peculiar genetic features, such as the Turkish population, are still absent in publically available datasets. To explore the genetic predisposition to health-related traits of the Turkish population, we analyzed 34 genes associated with different health-related traits (for example, lipid metabolism, cardio-vascular diseases, hormone metabolism, cellular detoxification, aging and energy metabolism). We observed relevant differences between the Turkish population and populations with non-European ancestries (that is, Africa and East Asia) in some of the investigated genes (that is, AGT, APOE, CYP1B1, GNB3, IL10, IL6, LIPC and PON1). As most complex traits are highly polygenic, we developed polygenic scores associated with different health-related traits to explore the genetic diversity of the Turkish population with respect to other human groups. This approach showed significant differences between the Turkish population and populations with non-European ancestries, as well as between Turkish and Northern European individuals. This last finding is in agreement with the genetic structure of European and Middle East populations, and may also agree with epidemiological evidences about the health disparities of Turkish communities in Northern European countries.

Systems Genetics as a Tool to Identify Master Genetic Regulators in Complex Disease.

PubMed

Moreno-Moral, Aida; Pesce, Francesco; Behmoaras, Jacques; Petretto, Enrico

2017-01-01

Systems genetics stems from systems biology and similarly employs integrative modeling approaches to describe the perturbations and phenotypic effects observed in a complex system. However, in the case of systems genetics the main source of perturbation is naturally occurring genetic variation, which can be analyzed at the systems-level to explain the observed variation in phenotypic traits. In contrast with conventional single-variant association approaches, the success of systems genetics has been in the identification of gene networks and molecular pathways that underlie complex disease. In addition, systems genetics has proven useful in the discovery of master trans-acting genetic regulators of functional networks and pathways, which in many cases revealed unexpected gene targets for disease. Here we detail the central components of a fully integrated systems genetics approach to complex disease, starting from assessment of genetic and gene expression variation, linking DNA sequence variation to mRNA (expression QTL mapping), gene regulatory network analysis and mapping the genetic control of regulatory networks. By summarizing a few illustrative (and successful) examples, we highlight how different data-modeling strategies can be effectively integrated in a systems genetics study.

3D sorghum reconstructions from depth images identify QTL regulating shoot architecture

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

Mccormick, Ryan F.; Truong, Sandra K.; Mullet, John E.

Dissecting the genetic basis of complex traits is aided by frequent and nondestructive measurements. Advances in range imaging technologies enable the rapid acquisition of three-dimensional (3D) data from an imaged scene. A depth camera was used to acquire images of sorghum (Sorghum bicolor), an important grain, forage, and bioenergy crop, at multiple developmental time points from a greenhouse-grown recombinant inbred line population. A semiautomated software pipeline was developed and used to generate segmented, 3D plant reconstructions from the images. Automated measurements made from 3D plant reconstructions identified quantitative trait loci for standard measures of shoot architecture, such as shoot height,more » leaf angle, and leaf length, and for novel composite traits, such as shoot compactness. The phenotypic variability associated with some of the quantitative trait loci displayed differences in temporal prevalence; for example, alleles closely linked with the sorghum Dwarf3 gene, an auxin transporter and pleiotropic regulator of both leaf inclination angle and shoot height, influence leaf angle prior to an effect on shoot height. Furthermore, variability in composite phenotypes that measure overall shoot architecture, such as shoot compactness, is regulated by loci underlying component phenotypes like leaf angle. As such, depth imaging is an economical and rapid method to acquire shoot architecture phenotypes in agriculturally important plants like sorghum to study the genetic basis of complex traits.« less

3D sorghum reconstructions from depth images identify QTL regulating shoot architecture

DOE PAGES

Mccormick, Ryan F.; Truong, Sandra K.; Mullet, John E.

2016-08-15

Dissecting the genetic basis of complex traits is aided by frequent and nondestructive measurements. Advances in range imaging technologies enable the rapid acquisition of three-dimensional (3D) data from an imaged scene. A depth camera was used to acquire images of sorghum (Sorghum bicolor), an important grain, forage, and bioenergy crop, at multiple developmental time points from a greenhouse-grown recombinant inbred line population. A semiautomated software pipeline was developed and used to generate segmented, 3D plant reconstructions from the images. Automated measurements made from 3D plant reconstructions identified quantitative trait loci for standard measures of shoot architecture, such as shoot height,more » leaf angle, and leaf length, and for novel composite traits, such as shoot compactness. The phenotypic variability associated with some of the quantitative trait loci displayed differences in temporal prevalence; for example, alleles closely linked with the sorghum Dwarf3 gene, an auxin transporter and pleiotropic regulator of both leaf inclination angle and shoot height, influence leaf angle prior to an effect on shoot height. Furthermore, variability in composite phenotypes that measure overall shoot architecture, such as shoot compactness, is regulated by loci underlying component phenotypes like leaf angle. As such, depth imaging is an economical and rapid method to acquire shoot architecture phenotypes in agriculturally important plants like sorghum to study the genetic basis of complex traits.« less

Genome-Wide Association Study Identifying Candidate Genes Influencing Important Agronomic Traits of Flax (Linum usitatissimum L.) Using SLAF-seq

PubMed Central

Xie, Dongwei; Dai, Zhigang; Yang, Zemao; Sun, Jian; Zhao, Debao; Yang, Xue; Zhang, Liguo; Tang, Qing; Su, Jianguang

2018-01-01

Flax (Linum usitatissimum L.) is an important cash crop, and its agronomic traits directly affect yield and quality. Molecular studies on flax remain inadequate because relatively few flax genes have been associated with agronomic traits or have been identified as having potential applications. To identify markers and candidate genes that can potentially be used for genetic improvement of crucial agronomic traits, we examined 224 specimens of core flax germplasm; specifically, phenotypic data for key traits, including plant height, technical length, number of branches, number of fruits, and 1000-grain weight were investigated under three environmental conditions before specific-locus amplified fragment sequencing (SLAF-seq) was employed to perform a genome-wide association study (GWAS) for these five agronomic traits. Subsequently, the results were used to screen single nucleotide polymorphism (SNP) loci and candidate genes that exhibited a significant correlation with the important agronomic traits. Our analyses identified a total of 42 SNP loci that showed significant correlations with the five important agronomic flax traits. Next, candidate genes were screened in the 10 kb zone of each of the 42 SNP loci. These SNP loci were then analyzed by a more stringent screening via co-identification using both a general linear model (GLM) and a mixed linear model (MLM) as well as co-occurrences in at least two of the three environments, whereby 15 final candidate genes were obtained. Based on these results, we determined that UGT and PL are candidate genes for plant height, GRAS and XTH are candidate genes for the number of branches, Contig1437 and LU0019C12 are candidate genes for the number of fruits, and PHO1 is a candidate gene for the 1000-seed weight. We propose that the identified SNP loci and corresponding candidate genes might serve as a biological basis for improving crucial agronomic flax traits. PMID:29375606

Genome-Wide Association Study Identifying Candidate Genes Influencing Important Agronomic Traits of Flax (Linum usitatissimum L.) Using SLAF-seq.

PubMed

Xie, Dongwei; Dai, Zhigang; Yang, Zemao; Sun, Jian; Zhao, Debao; Yang, Xue; Zhang, Liguo; Tang, Qing; Su, Jianguang

2017-01-01

Flax ( Linum usitatissimum L.) is an important cash crop, and its agronomic traits directly affect yield and quality. Molecular studies on flax remain inadequate because relatively few flax genes have been associated with agronomic traits or have been identified as having potential applications. To identify markers and candidate genes that can potentially be used for genetic improvement of crucial agronomic traits, we examined 224 specimens of core flax germplasm; specifically, phenotypic data for key traits, including plant height, technical length, number of branches, number of fruits, and 1000-grain weight were investigated under three environmental conditions before specific-locus amplified fragment sequencing (SLAF-seq) was employed to perform a genome-wide association study (GWAS) for these five agronomic traits. Subsequently, the results were used to screen single nucleotide polymorphism (SNP) loci and candidate genes that exhibited a significant correlation with the important agronomic traits. Our analyses identified a total of 42 SNP loci that showed significant correlations with the five important agronomic flax traits. Next, candidate genes were screened in the 10 kb zone of each of the 42 SNP loci. These SNP loci were then analyzed by a more stringent screening via co-identification using both a general linear model (GLM) and a mixed linear model (MLM) as well as co-occurrences in at least two of the three environments, whereby 15 final candidate genes were obtained. Based on these results, we determined that UGT and PL are candidate genes for plant height, GRAS and XTH are candidate genes for the number of branches, Contig1437 and LU0019C12 are candidate genes for the number of fruits, and PHO1 is a candidate gene for the 1000-seed weight. We propose that the identified SNP loci and corresponding candidate genes might serve as a biological basis for improving crucial agronomic flax traits.

Dissecting repulsion linkage in the dwarfing gene Dw3 region for sorghum plant height provides insights into heterosis.

PubMed

Li, Xin; Li, Xianran; Fridman, Eyal; Tesso, Tesfaye T; Yu, Jianming

2015-09-22

Heterosis is a main contributor to yield increase in many crop species. Different mechanisms have been proposed for heterosis: dominance, overdominance, epistasis, epigenetics, and protein metabolite changes. However, only limited examples of molecular dissection and validation of these mechanisms are available. Here, we present an example of discovery and validation of heterosis generated by a combination of repulsion linkage and dominance. Using a recombinant inbred line population, a separate quantitative trait locus (QTL) for plant height (qHT7.1) was identified near the genomic region harboring the known auxin transporter Dw3 gene. With two loci having repulsion linkage between two inbreds, heterosis in the hybrid can appear as a single locus with an overdominance mode of inheritance (i.e., pseudo-overdominance). Individually, alleles conferring taller plant height exhibited complete dominance over alleles conferring shorter height. Detailed analyses of different height components demonstrated that qHT7.1 affects both the upper and lower parts of the plant, whereas Dw3 affects only the part below the flag leaf. Computer simulations show that repulsion linkage could influence QTL detection and estimation of effect in segregating populations. Guided by findings in linkage mapping, a genome-wide association study of plant height with a sorghum diversity panel pinpointed genomic regions underlying the trait variation, including Dw1, Dw2, Dw3, Dw4, and qHT7.1. Multilocus mixed model analysis confirmed the advantage of complex trait dissection using an integrated approach. Besides identifying a specific genetic example of heterosis, our research indicated that integrated molecular dissection of complex traits in different population types can enable plant breeders to fine tune the breeding process for crop production.

Selection for Improved Energy Use Efficiency and Drought Tolerance in Canola Results in Distinct Transcriptome and Epigenome Changes.

PubMed

Verkest, Aurine; Byzova, Marina; Martens, Cindy; Willems, Patrick; Verwulgen, Tom; Slabbinck, Bram; Rombaut, Debbie; Van de Velde, Jan; Vandepoele, Klaas; Standaert, Evi; Peeters, Marrit; Van Lijsebettens, Mieke; Van Breusegem, Frank; De Block, Marc

2015-08-01

To increase both the yield potential and stability of crops, integrated breeding strategies are used that have mostly a direct genetic basis, but the utility of epigenetics to improve complex traits is unclear. A better understanding of the status of the epigenome and its contribution to agronomic performance would help in developing approaches to incorporate the epigenetic component of complex traits into breeding programs. Starting from isogenic canola (Brassica napus) lines, epilines were generated by selecting, repeatedly for three generations, for increased energy use efficiency and drought tolerance. These epilines had an enhanced energy use efficiency, drought tolerance, and nitrogen use efficiency. Transcriptome analysis of the epilines and a line selected for its energy use efficiency solely revealed common differentially expressed genes related to the onset of stress tolerance-regulating signaling events. Genes related to responses to salt, osmotic, abscisic acid, and drought treatments were specifically differentially expressed in the drought-tolerant epilines. The status of the epigenome, scored as differential trimethylation of lysine-4 of histone 3, further supported the phenotype by targeting drought-responsive genes and facilitating the transcription of the differentially expressed genes. From these results, we conclude that the canola epigenome can be shaped by selection to increase energy use efficiency and stress tolerance. Hence, these findings warrant the further development of strategies to incorporate epigenetics into breeding. © 2015 American Society of Plant Biologists. All Rights Reserved.

Regional Heritability Mapping Provides Insights into Dry Matter Content in African White and Yellow Cassava Populations.

PubMed

Okeke, Uche Godfrey; Akdemir, Deniz; Rabbi, Ismail; Kulakow, Peter; Jannink, Jean-Luc

2018-03-01

The HarvestPlus program for cassava ( Crantz) fortifies cassava with β-carotene by breeding for carotene-rich tubers (yellow cassava). However, a negative correlation between yellowness and dry matter (DM) content has been identified. We investigated the genetic control of DM in white and yellow cassava. We used regional heritability mapping (RHM) to associate DM with genomic segments in both subpopulations. Significant segments were subjected to candidate gene analysis and candidates were validated with prediction accuracies. The RHM procedure was validated via a simulation approach and revealed significant hits for white cassava on chromosomes 1, 4, 5, 10, 17, and 18, whereas hits for the yellow were on chromosome 1. Candidate gene analysis revealed genes in the carbohydrate biosynthesis pathway including plant serine-threonine protein kinases (SnRKs), UDP (uridine diphosphate)-glycosyltransferases, UDP-sugar transporters, invertases, pectinases, and regulons. Validation using 1252 unique identifiers from the SnRK gene family genome-wide recovered 50% of the predictive accuracy of whole-genome single nucleotide polymorphisms for DM, whereas validation using 53 likely genes (extracted from the literature) from significant segments recovered 32%. Genes including an acid invertase, a neutral or alkaline invertase, and a glucose-6-phosphate isomerase were validated on the basis of an a priori list for the cassava starch pathway, and also a fructose-biphosphate aldolase from the Calvin cycle pathway. The power of the RHM procedure was estimated as 47% when the causal quantitative trait loci generated 10% of the phenotypic variance (sample size = 451). Cassava DM genetics are complex and RHM may be useful for complex traits. Copyright © 2018 Crop Science Society of America.

Cross-ancestry genome-wide association analysis of corneal thickness strengthens link between complex and Mendelian eye diseases.

PubMed

Iglesias, Adriana I; Mishra, Aniket; Vitart, Veronique; Bykhovskaya, Yelena; Höhn, René; Springelkamp, Henriët; Cuellar-Partida, Gabriel; Gharahkhani, Puya; Bailey, Jessica N Cooke; Willoughby, Colin E; Li, Xiaohui; Yazar, Seyhan; Nag, Abhishek; Khawaja, Anthony P; Polašek, Ozren; Siscovick, David; Mitchell, Paul; Tham, Yih Chung; Haines, Jonathan L; Kearns, Lisa S; Hayward, Caroline; Shi, Yuan; van Leeuwen, Elisabeth M; Taylor, Kent D; Bonnemaijer, Pieter; Rotter, Jerome I; Martin, Nicholas G; Zeller, Tanja; Mills, Richard A; Staffieri, Sandra E; Jonas, Jost B; Schmidtmann, Irene; Boutin, Thibaud; Kang, Jae H; Lucas, Sionne E M; Wong, Tien Yin; Beutel, Manfred E; Wilson, James F; Uitterlinden, André G; Vithana, Eranga N; Foster, Paul J; Hysi, Pirro G; Hewitt, Alex W; Khor, Chiea Chuen; Pasquale, Louis R; Montgomery, Grant W; Klaver, Caroline C W; Aung, Tin; Pfeiffer, Norbert; Mackey, David A; Hammond, Christopher J; Cheng, Ching-Yu; Craig, Jamie E; Rabinowitz, Yaron S; Wiggs, Janey L; Burdon, Kathryn P; van Duijn, Cornelia M; MacGregor, Stuart

2018-05-14

Central corneal thickness (CCT) is a highly heritable trait associated with complex eye diseases such as keratoconus and glaucoma. We perform a genome-wide association meta-analysis of CCT and identify 19 novel regions. In addition to adding support for known connective tissue-related pathways, pathway analyses uncover previously unreported gene sets. Remarkably, >20% of the CCT-loci are near or within Mendelian disorder genes. These included FBN1, ADAMTS2 and TGFB2 which associate with connective tissue disorders (Marfan, Ehlers-Danlos and Loeys-Dietz syndromes), and the LUM-DCN-KERA gene complex involved in myopia, corneal dystrophies and cornea plana. Using index CCT-increasing variants, we find a significant inverse correlation in effect sizes between CCT and keratoconus (r = -0.62, P = 5.30 × 10 -5 ) but not between CCT and primary open-angle glaucoma (r = -0.17, P = 0.2). Our findings provide evidence for shared genetic influences between CCT and keratoconus, and implicate candidate genes acting in collagen and extracellular matrix regulation.

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

Effect prediction of identified SNPs linked to fruit quality and chilling injury in peach [Prunus persica (L.) Batsch].

PubMed

Martínez-García, Pedro J; Fresnedo-Ramírez, Jonathan; Parfitt, Dan E; Gradziel, Thomas M; Crisosto, Carlos H

2013-01-01

Single nucleotide polymorphisms (SNPs) are a fundamental source of genomic variation. Large SNP panels have been developed for Prunus species. Fruit quality traits are essential peach breeding program objectives since they determine consumer acceptance, fruit consumption, industry trends and cultivar adoption. For many cultivars, these traits are negatively impacted by cold storage, used to extend fruit market life. The major symptoms of chilling injury are lack of flavor, off flavor, mealiness, flesh browning, and flesh bleeding. A set of 1,109 SNPs was mapped previously and 67 were linked with these complex traits. The prediction of the effects associated with these SNPs on downstream products from the 'peach v1.0' genome sequence was carried out. A total of 2,163 effects were detected, 282 effects (non-synonymous, synonymous or stop codon gained) were located in exonic regions (13.04 %) and 294 placed in intronic regions (13.59 %). An extended list of genes and proteins that could be related to these traits was developed. Two SNP markers that explain a high percentage of the observed phenotypic variance, UCD_SNP_1084 and UCD_SNP_46, are associated with zinc finger (C3HC4-type RING finger) family protein and AOX1A (alternative oxidase 1a) protein groups, respectively. In addition, phenotypic variation suggests that the observed polymorphism for SNP UCD_SNP_1084 [A/G] mutation could be a candidate quantitative trait nucleotide affecting quantitative trait loci for mealiness. The interaction and expression of affected proteins could explain the variation observed in each individual and facilitate understanding of gene regulatory networks for fruit quality traits in peach.

Genome-wide identification and analysis of the B3 superfamily of transcription factors in Brassicaceae and major crop plants.

PubMed

Peng, Fred Y; Weselake, Randall J

2013-05-01

The plant-specific B3 superfamily of transcription factors has diverse functions in plant growth and development. Using a genome-wide domain analysis, we identified 92, 187, 58, 90, 81, 55, and 77 B3 transcription factor genes in the sequenced genome of Arabidopsis, Brassica rapa, castor bean (Ricinus communis), cocoa (Theobroma cacao), soybean (Glycine max), maize (Zea mays), and rice (Oryza sativa), respectively. The B3 superfamily has substantially expanded during the evolution in eudicots particularly in Brassicaceae, as compared to monocots in the analysis. We observed domain duplication in some of these B3 proteins, forming more complex domain architectures than currently understood. We found that the length of B3 domains exhibits a large variation, which may affect their exact number of α-helices and β-sheets in the core structure of B3 domains, and possibly have functional implications. Analysis of the public microarray data indicated that most of the B3 gene pairs encoding Arabidopsis-rice orthologs are preferentially expressed in different tissues, suggesting their different roles in these two species. Using ESTs in crops, we identified many B3 genes preferentially expressed in reproductive tissues. In a sequence-based quantitative trait loci analysis in rice and maize, we have found many B3 genes associated with traits such as grain yield, seed weight and number, and protein content. Our results provide a framework for future studies into the function of B3 genes in different phases of plant development, especially the ones related to traits in major crops.

Genetic architecture of hybrid male sterility in Drosophila: analysis of intraspecies variation for interspecies isolation.

PubMed

Reed, Laura K; LaFlamme, Brooke A; Markow, Therese A

2008-08-27

The genetic basis of postzygotic isolation is a central puzzle in evolutionary biology. Evolutionary forces causing hybrid sterility or inviability act on the responsible genes while they still are polymorphic, thus we have to study these traits as they arise, before isolation is complete. Isofemale strains of D. mojavensis vary significantly in their production of sterile F(1) sons when females are crossed to D. arizonae males. We took advantage of the intraspecific polymorphism, in a novel design, to perform quantitative trait locus (QTL) mapping analyses directly on F(1) hybrid male sterility itself. We found that the genetic architecture of the polymorphism for hybrid male sterility (HMS) in the F(1) is complex, involving multiple QTL, epistasis, and cytoplasmic effects. The role of extensive intraspecific polymorphism, multiple QTL, and epistatic interactions in HMS in this young species pair shows that HMS is arising as a complex trait in this system. Directional selection alone would be unlikely to maintain polymorphism at multiple loci, thus we hypothesize that directional selection is unlikely to be the only evolutionary force influencing postzygotic isolation.

Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index.

PubMed

Yang, Jian; Bakshi, Andrew; Zhu, Zhihong; Hemani, Gibran; Vinkhuyzen, Anna A E; Lee, Sang Hong; Robinson, Matthew R; Perry, John R B; Nolte, Ilja M; van Vliet-Ostaptchouk, Jana V; Snieder, Harold; Esko, Tonu; Milani, Lili; Mägi, Reedik; Metspalu, Andres; Hamsten, Anders; Magnusson, Patrik K E; Pedersen, Nancy L; Ingelsson, Erik; Soranzo, Nicole; Keller, Matthew C; Wray, Naomi R; Goddard, Michael E; Visscher, Peter M

2015-10-01

We propose a method (GREML-LDMS) to estimate heritability for human complex traits in unrelated individuals using whole-genome sequencing data. We demonstrate using simulations based on whole-genome sequencing data that ∼97% and ∼68% of variation at common and rare variants, respectively, can be captured by imputation. Using the GREML-LDMS method, we estimate from 44,126 unrelated individuals that all ∼17 million imputed variants explain 56% (standard error (s.e.) = 2.3%) of variance for height and 27% (s.e. = 2.5%) of variance for body mass index (BMI), and we find evidence that height- and BMI-associated variants have been under natural selection. Considering the imperfect tagging of imputation and potential overestimation of heritability from previous family-based studies, heritability is likely to be 60-70% for height and 30-40% for BMI. Therefore, the missing heritability is small for both traits. For further discovery of genes associated with complex traits, a study design with SNP arrays followed by imputation is more cost-effective than whole-genome sequencing at current prices.

Dissecting genetic architecture of startle response in Drosophila melanogaster using multi-omics information.

PubMed

Xue, Angli; Wang, Hongcheng; Zhu, Jun

2017-09-28

Startle behavior is important for survival, and abnormal startle responses are related to several neurological diseases. Drosophila melanogaster provides a powerful system to investigate the genetic underpinnings of variation in startle behavior. Since mechanically induced, startle responses and environmental conditions can be readily quantified and precisely controlled. The 156 wild-derived fully sequenced lines of the Drosophila Genetic Reference Panel (DGRP) were used to identify SNPs and transcripts associated with variation in startle behavior. The results validated highly significant effects of 33 quantitative trait SNPs (QTSs) and 81 quantitative trait transcripts (QTTs) directly associated with phenotypic variation of startle response. We also detected QTT variation controlled by 20 QTSs (tQTSs) and 73 transcripts (tQTTs). Association mapping based on genomic and transcriptomic data enabled us to construct a complex genetic network that underlies variation in startle behavior. Based on principles of evolutionary conservation, human orthologous genes could be superimposed on this network. This study provided both genetic and biological insights into the variation of startle response behavior of Drosophila melanogaster, and highlighted the importance of genetic network to understand the genetic architecture of complex traits.

From Mendel's discovery on pea to today's plant genetics and breeding : Commemorating the 150th anniversary of the reading of Mendel's discovery.

PubMed

Smýkal, Petr; K Varshney, Rajeev; K Singh, Vikas; Coyne, Clarice J; Domoney, Claire; Kejnovský, Eduard; Warkentin, Thomas

2016-12-01

This work discusses several selected topics of plant genetics and breeding in relation to the 150th anniversary of the seminal work of Gregor Johann Mendel. In 2015, we celebrated the 150th anniversary of the presentation of the seminal work of Gregor Johann Mendel. While Darwin's theory of evolution was based on differential survival and differential reproductive success, Mendel's theory of heredity relies on equality and stability throughout all stages of the life cycle. Darwin's concepts were continuous variation and "soft" heredity; Mendel espoused discontinuous variation and "hard" heredity. Thus, the combination of Mendelian genetics with Darwin's theory of natural selection was the process that resulted in the modern synthesis of evolutionary biology. Although biology, genetics, and genomics have been revolutionized in recent years, modern genetics will forever rely on simple principles founded on pea breeding using seven single gene characters. Purposeful use of mutants to study gene function is one of the essential tools of modern genetics. Today, over 100 plant species genomes have been sequenced. Mapping populations and their use in segregation of molecular markers and marker-trait association to map and isolate genes, were developed on the basis of Mendel's work. Genome-wide or genomic selection is a recent approach for the development of improved breeding lines. The analysis of complex traits has been enhanced by high-throughput phenotyping and developments in statistical and modeling methods for the analysis of phenotypic data. Introgression of novel alleles from landraces and wild relatives widens genetic diversity and improves traits; transgenic methodologies allow for the introduction of novel genes from diverse sources, and gene editing approaches offer possibilities to manipulate gene in a precise manner.

Using the candidate gene approach for detecting genes underlying seed oil concentration and yield in soybean.

PubMed

Eskandari, Mehrzad; Cober, Elroy R; Rajcan, Istvan

2013-07-01

Increasing the oil concentration in soybean seeds has been given more attention in recent years because of demand for both edible oil and biodiesel production. Oil concentration in soybean is a complex quantitative trait regulated by many genes as well as environmental conditions. To identify genes governing seed oil concentration in soybean, 16 putative candidate genes of three important gene families (GPAT: acyl-CoA:sn-glycerol-3-phosphate acyltransferase, DGAT: acyl-CoA:diacylglycerol acyltransferase, and PDAT: phospholipid:diacylglycerol acyltransferase) involved in triacylglycerol (TAG) biosynthesis pathways were selected and their sequences retrieved from the soybean database ( http://www.phytozome.net/soybean ). Three sequence mutations were discovered in either coding or noncoding regions of three DGAT soybean isoforms when comparing the parents of a 203 recombinant inbreed line (RIL) population; OAC Wallace and OAC Glencoe. The RIL population was used to study the effects of these mutations on seed oil concentration and other important agronomic and seed composition traits, including seed yield and protein concentration across three field locations in Ontario, Canada, in 2009 and 2010. An insertion/deletion (indel) mutation in the GmDGAT2B gene in OAC Wallace was significantly associated with reduced seed oil concentration across three environments and reduced seed yield at Woodstock in 2010. A mutation in the 3' untranslated (3'UTR) region of GmDGAT2C was associated with seed yield at Woodstock in 2009. A mutation in the intronic region of GmDGAR1B was associated with seed yield and protein concentration at Ottawa in 2010. The genes identified in this study had minor effects on either seed yield or oil concentration, which was in agreement with the quantitative nature of the traits. However, the novel gene-specific markers designed in the present study can be used in soybean breeding for marker-assisted selection aimed at increasing seed yield and oil concentration with no significant impact on seed protein concentration.

Differences in global gene expression in muscle tissue of Nellore cattle with divergent meat tenderness.

PubMed

Fonseca, Larissa Fernanda Simielli; Gimenez, Daniele Fernanda Jovino; Dos Santos Silva, Danielly Beraldo; Barthelson, Roger; Baldi, Fernando; Ferro, Jesus Aparecido; Albuquerque, Lucia Galvão

2017-12-04

Meat tenderness is the consumer's most preferred sensory attribute. This trait is affected by a number of factors, including genotype, age, animal sex, and pre- and post-slaughter management. In view of the high percentage of Zebu genes in the Brazilian cattle population, mainly Nellore cattle, the improvement of meat tenderness is important since the increasing proportion of Zebu genes in the population reduces meat tenderness. However, the measurement of this trait is difficult once it can only be made after animal slaughtering. New technologies such as RNA-Seq have been used to increase our understanding of the genetic processes regulating quantitative traits phenotypes. The objective of this study was to identify differentially expressed genes related to meat tenderness, in Nellore cattle in order to elucidate the genetic factors associated with meat quality. Samples were collected 24 h postmortem and the meat was not aged. We found 40 differentially expressed genes related to meat tenderness, 17 with known functions. Fourteen genes were up-regulated and 3 were down-regulated in the tender meat group. Genes related to ubiquitin metabolism, transport of molecules such as calcium and oxygen, acid-base balance, collagen production, actin, myosin, and fat were identified. The PCP4L1 (Purkinje cell protein 4 like 1) and BoLA-DQB (major histocompatibility complex, class II, DQ beta) genes were validated by qRT-PCR. The results showed relative expression values similar to those obtained by RNA-Seq, with the same direction of expression (i.e., the two techniques revealed higher expression of PCP4L1 in tender meat samples and of BoLA-DQB in tough meat samples). This study revealed the differential expression of genes and functions in Nellore cattle muscle tissue, which may contain potential biomarkers involved in meat tenderness.

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.

An SNP in the MyoD1 gene intron 2 associated with growth and carcass traits in three duck populations.

PubMed

Wu, Y; Pi, J S; Pan, A L; Pu, Y J; Du, J P; Shen, J; Liang, Z H; Zhang, J R

2012-12-01

Myogenic differentiation 1 (MyoD1) genes belong to the MyoD gene family and play key roles in growth and muscle development. This study was designed to investigate the effects of variants in the MyoD1 gene on duck growth and carcass traits. Three duck populations (Cherry Valley, Jingjiang, and Muscovy) were sampled, their growth and carcass traits were measured, and they were genotyped using the PCR-RFLP method. The results showed one novel polymorphism, an alteration in intron 2 of the MyoD1 gene (A to T). It was associated with the traits of weight at 8 weeks, carcass weight, breast muscle weight, leg muscle weight, eviscerated percentage, percentage of leg muscle weight, dressing percentage, and lean meat percentage. This alteration in intron 2 of MyoD1 may be linked with potential major loci or genes affecting some growth and carcass traits.

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

Snijders, Antoine M.; Langley, Sasha A.; Kim, Young-Mo

Although the gut microbiome plays important roles in host physiology, health and disease1, we lack understanding of the complex interplay between host genetics and early life environment on the microbial and metabolic composition of the gut.We used the genetically diverse Collaborative Cross mouse system2 to discover that early life history impacts themicrobiome composition, whereas dietary changes have only a moderate effect. By contrast, the gut metabolome was shaped mostly by diet, with specific non-dietary metabolites explained by microbial metabolism. Quantitative trait analysis identified mouse genetic trait loci (QTL) that impact the abundances of specific microbes. Human orthologues of genes inmore » the mouse QTL are implicated in gastrointestinal cancer. Additionally, genes located in mouse QTL for Lactobacillales abundance are implicated in arthritis, rheumatic disease and diabetes. Furthermore, Lactobacillales abundance was predictive of higher host T-helper cell counts, suggesting an important link between Lactobacillales and host adaptive immunity.« less

A fast boosting-based screening method for large-scale association study in complex traits with genetic heterogeneity.

PubMed

Wang, Lu-Yong; Fasulo, D

2006-01-01

Genome-wide association study for complex diseases will generate massive amount of single nucleotide polymorphisms (SNPs) data. Univariate statistical test (i.e. Fisher exact test) was used to single out non-associated SNPs. However, the disease-susceptible SNPs may have little marginal effects in population and are unlikely to retain after the univariate tests. Also, model-based methods are impractical for large-scale dataset. Moreover, genetic heterogeneity makes the traditional methods harder to identify the genetic causes of diseases. A more recent random forest method provides a more robust method for screening the SNPs in thousands scale. However, for more large-scale data, i.e., Affymetrix Human Mapping 100K GeneChip data, a faster screening method is required to screening SNPs in whole-genome large scale association analysis with genetic heterogeneity. We propose a boosting-based method for rapid screening in large-scale analysis of complex traits in the presence of genetic heterogeneity. It provides a relatively fast and fairly good tool for screening and limiting the candidate SNPs for further more complex computational modeling task.

Proteins Encoded in Genomic Regions Associated with Immune-Mediated Disease Physically Interact and Suggest Underlying Biology

PubMed Central

Rossin, Elizabeth J.; Lage, Kasper; Raychaudhuri, Soumya; Xavier, Ramnik J.; Tatar, Diana; Benita, Yair

2011-01-01

Genome-wide association studies (GWAS) have defined over 150 genomic regions unequivocally containing variation predisposing to immune-mediated disease. Inferring disease biology from these observations, however, hinges on our ability to discover the molecular processes being perturbed by these risk variants. It has previously been observed that different genes harboring causal mutations for the same Mendelian disease often physically interact. We sought to evaluate the degree to which this is true of genes within strongly associated loci in complex disease. Using sets of loci defined in rheumatoid arthritis (RA) and Crohn's disease (CD) GWAS, we build protein–protein interaction (PPI) networks for genes within associated loci and find abundant physical interactions between protein products of associated genes. We apply multiple permutation approaches to show that these networks are more densely connected than chance expectation. To confirm biological relevance, we show that the components of the networks tend to be expressed in similar tissues relevant to the phenotypes in question, suggesting the network indicates common underlying processes perturbed by risk loci. Furthermore, we show that the RA and CD networks have predictive power by demonstrating that proteins in these networks, not encoded in the confirmed list of disease associated loci, are significantly enriched for association to the phenotypes in question in extended GWAS analysis. Finally, we test our method in 3 non-immune traits to assess its applicability to complex traits in general. We find that genes in loci associated to height and lipid levels assemble into significantly connected networks but did not detect excess connectivity among Type 2 Diabetes (T2D) loci beyond chance. Taken together, our results constitute evidence that, for many of the complex diseases studied here, common genetic associations implicate regions encoding proteins that physically interact in a preferential manner, in line with observations in Mendelian disease. PMID:21249183

Network-Based Identification of Adaptive Pathways in Evolved Ethanol-Tolerant Bacterial Populations

PubMed Central

Swings, Toon; Weytjens, Bram; Schalck, Thomas; Bonte, Camille; Verstraeten, Natalie; Michiels, Jan

2017-01-01

Abstract Efficient production of ethanol for use as a renewable fuel requires organisms with a high level of ethanol tolerance. However, this trait is complex and increased tolerance therefore requires mutations in multiple genes and pathways. Here, we use experimental evolution for a system-level analysis of adaptation of Escherichia coli to high ethanol stress. As adaptation to extreme stress often results in complex mutational data sets consisting of both causal and noncausal passenger mutations, identifying the true adaptive mutations in these settings is not trivial. Therefore, we developed a novel method named IAMBEE (Identification of Adaptive Mutations in Bacterial Evolution Experiments). IAMBEE exploits the temporal profile of the acquisition of mutations during evolution in combination with the functional implications of each mutation at the protein level. These data are mapped to a genome-wide interaction network to search for adaptive mutations at the level of pathways. The 16 evolved populations in our data set together harbored 2,286 mutated genes with 4,470 unique mutations. Analysis by IAMBEE significantly reduced this number and resulted in identification of 90 mutated genes and 345 unique mutations that are most likely to be adaptive. Moreover, IAMBEE not only enabled the identification of previously known pathways involved in ethanol tolerance, but also identified novel systems such as the AcrAB-TolC efflux pump and fatty acids biosynthesis and even allowed to gain insight into the temporal profile of adaptation to ethanol stress. Furthermore, this method offers a solid framework for identifying the molecular underpinnings of other complex traits as well. PMID:28961727

Genetic Mechanisms Leading to Sex Differences Across Common Diseases and Anthropometric Traits

PubMed Central

Traglia, Michela; Bseiso, Dina; Gusev, Alexander; Adviento, Brigid; Park, Daniel S.; Mefford, Joel A.; Zaitlen, Noah; Weiss, Lauren A.

2017-01-01

Common diseases often show sex differences in prevalence, onset, symptomology, treatment, or prognosis. Although studies have been performed to evaluate sex differences at specific SNP associations, this work aims to comprehensively survey a number of complex heritable diseases and anthropometric traits. Potential genetically encoded sex differences we investigated include differential genetic liability thresholds or distributions, gene–sex interaction at autosomal loci, major contribution of the X-chromosome, or gene–environment interactions reflected in genes responsive to androgens or estrogens. Finally, we tested the overlap between sex-differential association with anthropometric traits and disease risk. We utilized complementary approaches of assessing GWAS association enrichment and SNP-based heritability estimation to explore explicit sex differences, as well as enrichment in sex-implicated functional categories. We do not find consistent increased genetic load in the lower-prevalence sex, or a disproportionate role for the X-chromosome in disease risk, despite sex-heterogeneity on the X for several traits. We find that all anthropometric traits show less than complete correlation between the genetic contribution to males and females, and find a convincing example of autosome-wide genome-sex interaction in multiple sclerosis (P = 1 × 10−9). We also find some evidence for hormone-responsive gene enrichment, and striking evidence of the contribution of sex-differential anthropometric associations to common disease risk, implying that general mechanisms of sexual dimorphism determining secondary sex characteristics have shared effects on disease risk. PMID:27974502

QTL analysis of falling number and seed longevity in wheat (Triticum aestivum L.).

PubMed

Börner, Andreas; Nagel, Manuela; Agacka-Mołdoch, Monika; Gierke, Peter Ulrich; Oberforster, Michael; Albrecht, Theresa; Mohler, Volker

2018-02-01

Pre-harvest sprouting (PHS) and seed longevity (SL) are complex biological processes of major importance for agricultural production. In the present study, a recombinant inbred line (RIL) population derived from a cross between the German winter wheat (Triticum aestivum L.) cultivars History and Rubens was used to identify genetic factors controlling these two physiological seed traits. A falling number (FN) test was employed to evaluate PHS, while SL was measured using a germination test (and the speed of germination) after controlled deterioration. FN of the population was assessed in four environments; SL traits were measured in one environment. Four major quantitative trait loci (QTL) for FN were detected on chromosomes 4D, 5A, 5D, and 7B, whereas for SL traits, a major QTL was found on chromosome 1A. The FN QTL on chromosome 4D that coincided with the position of the dwarfing gene Rht-D1b only had effects in environments that were free of PHS. The remaining three QTL for FN were mostly pronounced under conditions conducive to PHS. The QTL on the long arm of chromosome 7B corresponded to the major gene locus controlling late maturity α-amylase (LMA) in wheat. The severity of the LMA phenotype became truly apparent under sprouting conditions. The position on the long arm of chromosome 1A of the QTL for SL points to a new QTL for this important regenerative seed trait.

Novel pedigree analysis implicates DNA repair and chromatin remodeling in multiple myeloma risk

PubMed Central

Curtin, Karen; Rajamanickam, Venkatesh; Jayabalan, David; Atanackovic, Djordje; Rajkumar, S. Vincent; Kumar, Shaji; Slager, Susan; Galia, Perrine; Demangel, Delphine; Salama, Mohamed; Joseph, Vijai; Lipkin, Steven M.; Dumontet, Charles; Vachon, Celine M.

2018-01-01

The high-risk pedigree (HRP) design is an established strategy to discover rare, highly-penetrant, Mendelian-like causal variants. Its success, however, in complex traits has been modest, largely due to challenges of genetic heterogeneity and complex inheritance models. We describe a HRP strategy that addresses intra-familial heterogeneity, and identifies inherited segments important for mapping regulatory risk. We apply this new Shared Genomic Segment (SGS) method in 11 extended, Utah, multiple myeloma (MM) HRPs, and subsequent exome sequencing in SGS regions of interest in 1063 MM / MGUS (monoclonal gammopathy of undetermined significance–a precursor to MM) cases and 964 controls from a jointly-called collaborative resource, including cases from the initial 11 HRPs. One genome-wide significant 1.8 Mb shared segment was found at 6q16. Exome sequencing in this region revealed predicted deleterious variants in USP45 (p.Gln691* and p.Gln621Glu), a gene known to influence DNA repair through endonuclease regulation. Additionally, a 1.2 Mb segment at 1p36.11 is inherited in two Utah HRPs, with coding variants identified in ARID1A (p.Ser90Gly and p.Met890Val), a key gene in the SWI/SNF chromatin remodeling complex. Our results provide compelling statistical and genetic evidence for segregating risk variants for MM. In addition, we demonstrate a novel strategy to use large HRPs for risk-variant discovery more generally in complex traits. PMID:29389935

Novel pedigree analysis implicates DNA repair and chromatin remodeling in multiple myeloma risk.

PubMed

Waller, Rosalie G; Darlington, Todd M; Wei, Xiaomu; Madsen, Michael J; Thomas, Alun; Curtin, Karen; Coon, Hilary; Rajamanickam, Venkatesh; Musinsky, Justin; Jayabalan, David; Atanackovic, Djordje; Rajkumar, S Vincent; Kumar, Shaji; Slager, Susan; Middha, Mridu; Galia, Perrine; Demangel, Delphine; Salama, Mohamed; Joseph, Vijai; McKay, James; Offit, Kenneth; Klein, Robert J; Lipkin, Steven M; Dumontet, Charles; Vachon, Celine M; Camp, Nicola J

2018-02-01

The high-risk pedigree (HRP) design is an established strategy to discover rare, highly-penetrant, Mendelian-like causal variants. Its success, however, in complex traits has been modest, largely due to challenges of genetic heterogeneity and complex inheritance models. We describe a HRP strategy that addresses intra-familial heterogeneity, and identifies inherited segments important for mapping regulatory risk. We apply this new Shared Genomic Segment (SGS) method in 11 extended, Utah, multiple myeloma (MM) HRPs, and subsequent exome sequencing in SGS regions of interest in 1063 MM / MGUS (monoclonal gammopathy of undetermined significance-a precursor to MM) cases and 964 controls from a jointly-called collaborative resource, including cases from the initial 11 HRPs. One genome-wide significant 1.8 Mb shared segment was found at 6q16. Exome sequencing in this region revealed predicted deleterious variants in USP45 (p.Gln691* and p.Gln621Glu), a gene known to influence DNA repair through endonuclease regulation. Additionally, a 1.2 Mb segment at 1p36.11 is inherited in two Utah HRPs, with coding variants identified in ARID1A (p.Ser90Gly and p.Met890Val), a key gene in the SWI/SNF chromatin remodeling complex. Our results provide compelling statistical and genetic evidence for segregating risk variants for MM. In addition, we demonstrate a novel strategy to use large HRPs for risk-variant discovery more generally in complex traits.

Genome-wide association study of resistance to ear rot by Fusarium verticillioides in a tropical field maize and popcorn core collection

USDA-ARS?s Scientific Manuscript database

Fusarium ear rot (caused by Fusarium verticillioides) is one of the most prevalent diseases of maize worldwide, and has one of the greatest negative economic impacts on this cereal crop globally. Fusarium ear rot is a highly complex trait, under polygenic control with minor effects per gene and low ...

9. international mouse genome conference

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

NONE

This conference was held November 12--16, 1995 in Ann Arbor, Michigan. The purpose of this conference was to provide a multidisciplinary forum for exchange of state-of-the-art information on genetic mapping in mice. This report contains abstracts of presentations, focusing on the following areas: mutation identification; comparative mapping; informatics and complex traits; mutagenesis; gene identification and new technology; and genetic and physical mapping.

Genetic Basis Underlying Correlations Among Growth Duration and Yield Traits Revealed by GWAS in Rice (Oryza sativa L.).

PubMed

Li, Fengmei; Xie, Jianyin; Zhu, Xiaoyang; Wang, Xueqiang; Zhao, Yan; Ma, Xiaoqian; Zhang, Zhanying; Rashid, Muhammad A R; Zhang, Zhifang; Zhi, Linran; Zhang, Shuyang; Li, Jinjie; Li, Zichao; Zhang, Hongliang

2018-01-01

Avoidance of disadvantageous genetic correlations among growth duration and yield traits is critical in developing crop varieties that efficiently use light and energy resources and produce high yields. To understand the genetic basis underlying the correlations among heading date and three major yield traits in rice, we investigated the four traits in a diverse and representative core collection of 266 cultivated rice accessions in both long-day and short-day environments, and conducted the genome-wide association study using 4.6 million single nucleotide polymorphisms (SNPs). There were clear positive correlation between heading date and grain number per panicle, and negative correlation between grain number per panicle and panicle number, as well as different degrees of correlations among other traits in different subspecies and environments. We detected 47 pleiotropic genes in 15 pleiotropic quantitative trait loci (pQTLs), 18 pleiotropic genes containing 37 pleiotropic SNPs in 8 pQTLs, 27 pQTLs with r 2 of linkage disequilibrium higher than 0.2, and 39 pairs of interactive genes from 8 metabolic pathways that may contribute to the above phenotypic correlations, but these genetic bases were different for correlations among different traits. Distributions of haplotypes revealed that selection for pleiotropic genes or interactive genes controlling different traits focused on genotypes with weak effect or on those balancing two traits that maximized production but sometimes their utilization strategies depend on the traits and environment. Detection of pQTLs and interactive genes and associated molecular markers will provide an ability to overcome disadvantageous correlations and to utilize the advantageous correlations among traits through marker-assisted selection in breeding.

Simulating the Yield Impacts of Organ-Level Quantitative Trait Loci Associated With Drought Response in Maize: A “Gene-to-Phenotype” Modeling Approach

PubMed Central

Chenu, Karine; Chapman, Scott C.; Tardieu, François; McLean, Greg; Welcker, Claude; Hammer, Graeme L.

2009-01-01

Under drought, substantial genotype–environment (G × E) interactions impede breeding progress for yield. Identifying genetic controls associated with yield response is confounded by poor genetic correlations across testing environments. Part of this problem is related to our inability to account for the interplay of genetic controls, physiological traits, and environmental conditions throughout the crop cycle. We propose a modeling approach to bridge this “gene-to-phenotype” gap. For maize under drought, we simulated the impact of quantitative trait loci (QTL) controlling two key processes (leaf and silk elongation) that influence crop growth, water use, and grain yield. Substantial G × E interaction for yield was simulated for hypothetical recombinant inbred lines (RILs) across different seasonal patterns of drought. QTL that accelerated leaf elongation caused an increase in crop leaf area and yield in well-watered or preflowering water deficit conditions, but a reduction in yield under terminal stresses (as such “leafy” genotypes prematurely exhausted the water supply). The QTL impact on yield was substantially enhanced by including pleiotropic effects of these QTL on silk elongation and on consequent grain set. The simulations obtained illustrated the difficulty of interpreting the genetic control of yield for genotypes influenced only by the additive effects of QTL associated with leaf and silk growth. The results highlight the potential of integrative simulation modeling for gene-to-phenotype prediction and for exploiting G × E interactions for complex traits such as drought tolerance. PMID:19786622

Twin methodology in epigenetic studies.

PubMed

Tan, Qihua; Christiansen, Lene; von Bornemann Hjelmborg, Jacob; Christensen, Kaare

2015-01-01

Since the final decades of the last century, twin studies have made a remarkable contribution to the genetics of human complex traits and diseases. With the recent rapid development in modern biotechnology of high-throughput genetic and genomic analyses, twin modelling is expanding from analysis of diseases to molecular phenotypes in functional genomics especially in epigenetics, a thriving field of research that concerns the environmental regulation of gene expression through DNA methylation, histone modification, microRNA and long non-coding RNA expression, etc. The application of the twin method to molecular phenotypes offers new opportunities to study the genetic (nature) and environmental (nurture) contributions to epigenetic regulation of gene activity during developmental, ageing and disease processes. Besides the classical twin model, the case co-twin design using identical twins discordant for a trait or disease is becoming a popular and powerful design for epigenome-wide association study in linking environmental exposure to differential epigenetic regulation and to disease status while controlling for individual genetic make-up. It can be expected that novel uses of twin methods in epigenetic studies are going to help with efficiently unravelling the genetic and environmental basis of epigenomics in human complex diseases. © 2015. Published by The Company of Biologists Ltd.

Design of microarray experiments for genetical genomics studies.

PubMed

Bueno Filho, Júlio S S; Gilmour, Steven G; Rosa, Guilherme J M

2006-10-01

Microarray experiments have been used recently in genetical genomics studies, as an additional tool to understand the genetic mechanisms governing variation in complex traits, such as for estimating heritabilities of mRNA transcript abundances, for mapping expression quantitative trait loci, and for inferring regulatory networks controlling gene expression. Several articles on the design of microarray experiments discuss situations in which treatment effects are assumed fixed and without any structure. In the case of two-color microarray platforms, several authors have studied reference and circular designs. Here, we discuss the optimal design of microarray experiments whose goals refer to specific genetic questions. Some examples are used to illustrate the choice of a design for comparing fixed, structured treatments, such as genotypic groups. Experiments targeting single genes or chromosomic regions (such as with transgene research) or multiple epistatic loci (such as within a selective phenotyping context) are discussed. In addition, microarray experiments in which treatments refer to families or to subjects (within family structures or complex pedigrees) are presented. In these cases treatments are more appropriately considered to be random effects, with specific covariance structures, in which the genetic goals relate to the estimation of genetic variances and the heritability of transcriptional abundances.

Enhancing GTEx by bridging the gaps between genotype, gene expression, and disease.

PubMed

2017-12-01

Genetic variants have been associated with myriad molecular phenotypes that provide new insight into the range of mechanisms underlying genetic traits and diseases. Identifying any particular genetic variant's cascade of effects, from molecule to individual, requires assaying multiple layers of molecular complexity. We introduce the Enhancing GTEx (eGTEx) project that extends the GTEx project to combine gene expression with additional intermediate molecular measurements on the same tissues to provide a resource for studying how genetic differences cascade through molecular phenotypes to impact human health.

Towards systems genetic analyses in barley: Integration of phenotypic, expression and genotype data into GeneNetwork.

PubMed

Druka, Arnis; Druka, Ilze; Centeno, Arthur G; Li, Hongqiang; Sun, Zhaohui; Thomas, William T B; Bonar, Nicola; Steffenson, Brian J; Ullrich, Steven E; Kleinhofs, Andris; Wise, Roger P; Close, Timothy J; Potokina, Elena; Luo, Zewei; Wagner, Carola; Schweizer, Günther F; Marshall, David F; Kearsey, Michael J; Williams, Robert W; Waugh, Robbie

2008-11-18

A typical genetical genomics experiment results in four separate data sets; genotype, gene expression, higher-order phenotypic data and metadata that describe the protocols, processing and the array platform. Used in concert, these data sets provide the opportunity to perform genetic analysis at a systems level. Their predictive power is largely determined by the gene expression dataset where tens of millions of data points can be generated using currently available mRNA profiling technologies. Such large, multidimensional data sets often have value beyond that extracted during their initial analysis and interpretation, particularly if conducted on widely distributed reference genetic materials. Besides quality and scale, access to the data is of primary importance as accessibility potentially allows the extraction of considerable added value from the same primary dataset by the wider research community. Although the number of genetical genomics experiments in different plant species is rapidly increasing, none to date has been presented in a form that allows quick and efficient on-line testing for possible associations between genes, loci and traits of interest by an entire research community. Using a reference population of 150 recombinant doubled haploid barley lines we generated novel phenotypic, mRNA abundance and SNP-based genotyping data sets, added them to a considerable volume of legacy trait data and entered them into the GeneNetwork http://www.genenetwork.org. GeneNetwork is a unified on-line analytical environment that enables the user to test genetic hypotheses about how component traits, such as mRNA abundance, may interact to condition more complex biological phenotypes (higher-order traits). Here we describe these barley data sets and demonstrate some of the functionalities GeneNetwork provides as an easily accessible and integrated analytical environment for exploring them. By integrating barley genotypic, phenotypic and mRNA abundance data sets directly within GeneNetwork's analytical environment we provide simple web access to the data for the research community. In this environment, a combination of correlation analysis and linkage mapping provides the potential to identify and substantiate gene targets for saturation mapping and positional cloning. By integrating datasets from an unsequenced crop plant (barley) in a database that has been designed for an animal model species (mouse) with a well established genome sequence, we prove the importance of the concept and practice of modular development and interoperability of software engineering for biological data sets.

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.

Using Gene Ontology to describe the role of the neurexin-neuroligin-SHANK complex in human, mouse and rat and its relevance to autism.

PubMed

Patel, Sejal; Roncaglia, Paola; Lovering, Ruth C

2015-06-06

People with an autistic spectrum disorder (ASD) display a variety of characteristic behavioral traits, including impaired social interaction, communication difficulties and repetitive behavior. This complex neurodevelopment disorder is known to be associated with a combination of genetic and environmental factors. Neurexins and neuroligins play a key role in synaptogenesis and neurexin-neuroligin adhesion is one of several processes that have been implicated in autism spectrum disorders. In this report we describe the manual annotation of a selection of gene products known to be associated with autism and/or the neurexin-neuroligin-SHANK complex and demonstrate how a focused annotation approach leads to the creation of more descriptive Gene Ontology (GO) terms, as well as an increase in both the number of gene product annotations and their granularity, thus improving the data available in the GO database. The manual annotations we describe will impact on the functional analysis of a variety of future autism-relevant datasets. Comprehensive gene annotation is an essential aspect of genomic and proteomic studies, as the quality of gene annotations incorporated into statistical analysis tools affects the effective interpretation of data obtained through genome wide association studies, next generation sequencing, proteomic and transcriptomic datasets.

A kernel regression approach to gene-gene interaction detection for case-control studies.

PubMed

Larson, Nicholas B; Schaid, Daniel J

2013-11-01

Gene-gene interactions are increasingly being addressed as a potentially important contributor to the variability of complex traits. Consequently, attentions have moved beyond single locus analysis of association to more complex genetic models. Although several single-marker approaches toward interaction analysis have been developed, such methods suffer from very high testing dimensionality and do not take advantage of existing information, notably the definition of genes as functional units. Here, we propose a comprehensive family of gene-level score tests for identifying genetic elements of disease risk, in particular pairwise gene-gene interactions. Using kernel machine methods, we devise score-based variance component tests under a generalized linear mixed model framework. We conducted simulations based upon coalescent genetic models to evaluate the performance of our approach under a variety of disease models. These simulations indicate that our methods are generally higher powered than alternative gene-level approaches and at worst competitive with exhaustive SNP-level (where SNP is single-nucleotide polymorphism) analyses. Furthermore, we observe that simulated epistatic effects resulted in significant marginal testing results for the involved genes regardless of whether or not true main effects were present. We detail the benefits of our methods and discuss potential genome-wide analysis strategies for gene-gene interaction analysis in a case-control study design. © 2013 WILEY PERIODICALS, INC.

Integrative genetic analysis of transcription modules: towards filling the gap between genetic lociand inherited traits

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

Li, Hongqiang; Chen, Hao; Bao, Lei

2005-01-01

Genetic loci that regulate inherited traits are routinely identified using quantitative trait locus (QTL) mapping methods. However, the genotype-phenotype associations do not provide information on the gene expression program through which the genetic loci regulate the traits. Transcription modules are 'selfconsistent regulatory units' and are closely related to the modular components of gene regulatory network [Ihmels, J., Friedlander, G., Bergmann, S., Sarig, O., Ziv, Y. and Barkai, N. (2002) Revealing modular organization in the yeast transcriptional network. Nat. Genet., 31, 370-377; Segal, E., Shapira, M., Regev, A., Pe'er, D., Botstein, D., Koller, D. and Friedman, N. (2003) Module networks: identifyingmore » regulatory modules and their condition-specific regulators from gene expression data. Nat. Genet., 34, 166-176]. We used genome-wide genotype and gene expression data of a genetic reference population that consists of mice of 32 recombinant inbred strains to identify the transcription modules and the genetic loci regulating them. Twenty-nine transcription modules defined by genetic variations were identified. Statistically significant associations between the transcription modules and 18 classical physiological and behavioral traits were found. Genome-wide interval mapping showed that major QTLs regulating the transcription modules are often co-localized with the QTLs regulating the associated classical traits. The association and the possible co-regulation of the classical trait and transcription module indicate that the transcription module may be involved in the gene pathways connecting the QTL and the classical trait. Our results show that a transcription module may associate with multiple seemingly unrelated classical traits and a classical trait may associate with different modules. Literature mining results provided strong independent evidences for the relations among genes of the transcription modules, genes in the regions of the QTLs regulating the transcription modules and the keywords representing the classical traits.« less

Association analysis of single nucleotide polymorphisms in candidate genes with root traits in maize (Zea mays L.) seedlings.

PubMed

Kumar, Bharath; Abdel-Ghani, Adel H; Pace, Jordon; Reyes-Matamoros, Jenaro; Hochholdinger, Frank; Lübberstedt, Thomas

2014-07-01

Several genes involved in maize root development have been isolated. Identification of SNPs associated with root traits would enable the selection of maize lines with better root architecture that might help to improve N uptake, and consequently plant growth particularly under N deficient conditions. In the present study, an association study (AS) panel consisting of 74 maize inbred lines was screened for seedling root traits in 6, 10, and 14-day-old seedlings. Allele re-sequencing of candidate root genes Rtcl, Rth3, Rum1, and Rul1 was also carried out in the same AS panel lines. All four candidate genes displayed different levels of nucleotide diversity, haplotype diversity and linkage disequilibrium. Gene based association analyses were carried out between individual polymorphisms in candidate genes, and root traits measured in 6, 10, and 14-day-old maize seedlings. Association analyses revealed several polymorphisms within the Rtcl, Rth3, Rum1, and Rul1 genes associated with seedling root traits. Several nucleotide polymorphisms in Rtcl, Rth3, Rum1, and Rul1 were significantly (P<0.05) associated with seedling root traits in maize suggesting that all four tested genes are involved in the maize root development. Thus considerable allelic variation present in these root genes can be exploited for improving maize root characteristics. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A Simple and Computationally Efficient Sampling Approach to Covariate Adjustment for Multifactor Dimensionality Reduction Analysis of Epistasis

PubMed Central

Gui, Jiang; Andrew, Angeline S.; Andrews, Peter; Nelson, Heather M.; Kelsey, Karl T.; Karagas, Margaret R.; Moore, Jason H.

2010-01-01

Epistasis or gene-gene interaction is a fundamental component of the genetic architecture of complex traits such as disease susceptibility. Multifactor dimensionality reduction (MDR) was developed as a nonparametric and model-free method to detect epistasis when there are no significant marginal genetic effects. However, in many studies of complex disease, other covariates like age of onset and smoking status could have a strong main effect and may potentially interfere with MDR's ability to achieve its goal. In this paper, we present a simple and computationally efficient sampling method to adjust for covariate effects in MDR. We use simulation to show that after adjustment, MDR has sufficient power to detect true gene-gene interactions. We also compare our method with the state-of-art technique in covariate adjustment. The results suggest that our proposed method performs similarly, but is more computationally efficient. We then apply this new method to an analysis of a population-based bladder cancer study in New Hampshire. PMID:20924193

Partitioning of genetic variation between regulatory and coding gene segments: the predominance of software variation in genes encoding introvert proteins.

PubMed

Mitchison, A

1997-01-01

In considering genetic variation in eukaryotes, a fundamental distinction can be made between variation in regulatory (software) and coding (hardware) gene segments. For quantitative traits the bulk of variation, particularly that near the population mean, appears to reside in regulatory segments. The main exceptions to this rule concern proteins which handle extrinsic substances, here termed extrovert proteins. The immune system includes an unusually large proportion of this exceptional category, but even so its chief source of variation may well be polymorphism in regulatory gene segments. The main evidence for this view emerges from genome scanning for quantitative trait loci (QTL), which in the case of the immune system points to a major contribution of pro-inflammatory cytokine genes. Further support comes from sequencing of major histocompatibility complex (Mhc) class II promoters, where a high level of polymorphism has been detected. These Mhc promoters appear to act, in part at least, by gating the back-signal from T cells into antigen-presenting cells. Both these forms of polymorphism are likely to be sustained by the need for flexibility in the immune response. Future work on promoter polymorphism is likely to benefit from the input from genome informatics.

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.

Evo-devo, deep homology and FoxP2: implications for the evolution of speech and language

PubMed Central

Scharff, Constance; Petri, Jana

2011-01-01

The evolution of novel morphological features, such as feathers, involves the modification of developmental processes regulated by gene networks. The fact that genetic novelty operates within developmental constraints is the central tenet of the ‘evo-devo’ conceptual framework. It is supported by findings that certain molecular regulatory pathways act in a similar manner in the development of morphological adaptations, which are not directly related by common ancestry but evolved convergently. The Pax6 gene, important for vision in molluscs, insects and vertebrates, and Hox genes, important for tetrapod limbs and fish fins, exemplify this ‘deep homology’. Recently, ‘evo-devo’ has expanded to the molecular analysis of behavioural traits, including social behaviour, learning and memory. Here, we apply this approach to the evolution of human language. Human speech is a form of auditory-guided, learned vocal motor behaviour that also evolved in certain species of birds, bats and ocean mammals. Genes relevant for language, including the transcription factor FOXP2, have been identified. We review evidence that FoxP2 and its regulatory gene network shapes neural plasticity in cortico-basal ganglia circuits underlying the sensory-guided motor learning in animal models. The emerging picture can help us understand how complex cognitive traits can ‘descend with modification’. PMID:21690130

Evo-devo, deep homology and FoxP2: implications for the evolution of speech and language.

PubMed

Scharff, Constance; Petri, Jana

2011-07-27

The evolution of novel morphological features, such as feathers, involves the modification of developmental processes regulated by gene networks. The fact that genetic novelty operates within developmental constraints is the central tenet of the 'evo-devo' conceptual framework. It is supported by findings that certain molecular regulatory pathways act in a similar manner in the development of morphological adaptations, which are not directly related by common ancestry but evolved convergently. The Pax6 gene, important for vision in molluscs, insects and vertebrates, and Hox genes, important for tetrapod limbs and fish fins, exemplify this 'deep homology'. Recently, 'evo-devo' has expanded to the molecular analysis of behavioural traits, including social behaviour, learning and memory. Here, we apply this approach to the evolution of human language. Human speech is a form of auditory-guided, learned vocal motor behaviour that also evolved in certain species of birds, bats and ocean mammals. Genes relevant for language, including the transcription factor FOXP2, have been identified. We review evidence that FoxP2 and its regulatory gene network shapes neural plasticity in cortico-basal ganglia circuits underlying the sensory-guided motor learning in animal models. The emerging picture can help us understand how complex cognitive traits can 'descend with modification'.

Translating Mendelian and complex inheritance of Alzheimer's disease genes for predicting unique personal genome variants

PubMed Central

Regan, Kelly; Wang, Kanix; Doughty, Emily; Li, Haiquan; Li, Jianrong; Lee, Younghee; Kann, Maricel G

2012-01-01

Objective Although trait-associated genes identified as complex versus single-gene inheritance differ substantially in odds ratio, the authors nonetheless posit that their mechanistic concordance can reveal fundamental properties of the genetic architecture, allowing the automated interpretation of unique polymorphisms within a personal genome. Materials and methods An analytical method, SPADE-gen, spanning three biological scales was developed to demonstrate the mechanistic concordance between Mendelian and complex inheritance of Alzheimer's disease (AD) genes: biological functions (BP), protein interaction modeling, and protein domain implicated in the disease-associated polymorphism. Results Among Gene Ontology (GO) biological processes (BP) enriched at a false detection rate <5% in 15 AD genes of Mendelian inheritance (Online Mendelian Inheritance in Man) and independently in those of complex inheritance (25 host genes of intragenic AD single-nucleotide polymorphisms confirmed in genome-wide association studies), 16 overlapped (empirical p=0.007) and 45 were similar (empirical p<0.009; information theory). SPAN network modeling extended the canonical pathway of AD (KEGG) with 26 new protein interactions (empirical p<0.0001). Discussion The study prioritized new AD-associated biological mechanisms and focused the analysis on previously unreported interactions associated with the biological processes of polymorphisms that affect specific protein domains within characterized AD genes and their direct interactors using (1) concordant GO-BP and (2) domain interactions within STRING protein–protein interactions corresponding to the genomic location of the AD polymorphism (eg, EPHA1, APOE, and CD2AP). Conclusion These results are in line with unique-event polymorphism theory, indicating how disease-associated polymorphisms of Mendelian or complex inheritance relate genetically to those observed as ‘unique personal variants’. They also provide insight for identifying novel targets, for repositioning drugs, and for personal therapeutics. PMID:22319180

Genetic Characterization of Dog Personality Traits.

PubMed

Ilska, Joanna; Haskell, Marie J; Blott, Sarah C; Sánchez-Molano, Enrique; Polgar, Zita; Lofgren, Sarah E; Clements, Dylan N; Wiener, Pamela

2017-06-01

The genetic architecture of behavioral traits in dogs is of great interest to owners, breeders, and professionals involved in animal welfare, as well as to scientists studying the genetics of animal (including human) behavior. The genetic component of dog behavior is supported by between-breed differences and some evidence of within-breed variation. However, it is a challenge to gather sufficiently large datasets to dissect the genetic basis of complex traits such as behavior, which are both time-consuming and logistically difficult to measure, and known to be influenced by nongenetic factors. In this study, we exploited the knowledge that owners have of their dogs to generate a large dataset of personality traits in Labrador Retrievers. While accounting for key environmental factors, we demonstrate that genetic variance can be detected for dog personality traits assessed using questionnaire data. We identified substantial genetic variance for several traits, including fetching tendency and fear of loud noises, while other traits revealed negligibly small heritabilities. Genetic correlations were also estimated between traits; however, due to fairly large SEs, only a handful of trait pairs yielded statistically significant estimates. Genomic analyses indicated that these traits are mainly polygenic, such that individual genomic regions have small effects, and suggested chromosomal associations for six of the traits. The polygenic nature of these traits is consistent with previous behavioral genetics studies in other species, for example in mouse, and confirms that large datasets are required to quantify the genetic variance and to identify the individual genes that influence behavioral traits. Copyright © 2017 by the Genetics Society of America.

Rare-Variant Association Analysis: Study Designs and Statistical Tests

PubMed Central

Lee, Seunggeung; Abecasis, Gonçalo R.; Boehnke, Michael; Lin, Xihong

2014-01-01

Despite the extensive discovery of trait- and disease-associated common variants, much of the genetic contribution to complex traits remains unexplained. Rare variants can explain additional disease risk or trait variability. An increasing number of studies are underway to identify trait- and disease-associated rare variants. In this review, we provide an overview of statistical issues in rare-variant association studies with a focus on study designs and statistical tests. We present the design and analysis pipeline of rare-variant studies and review cost-effective sequencing designs and genotyping platforms. We compare various gene- or region-based association tests, including burden tests, variance-component tests, and combined omnibus tests, in terms of their assumptions and performance. Also discussed are the related topics of meta-analysis, population-stratification adjustment, genotype imputation, follow-up studies, and heritability due to rare variants. We provide guidelines for analysis and discuss some of the challenges inherent in these studies and future research directions. PMID:24995866

Replication of linkage to quantitative trait loci: variation in location and magnitude of the lod score.

PubMed

Hsueh, W C; Göring, H H; Blangero, J; Mitchell, B D

2001-01-01

Replication of linkage signals from independent samples is considered an important step toward verifying the significance of linkage signals in studies of complex traits. The purpose of this empirical investigation was to examine the variability in the precision of localizing a quantitative trait locus (QTL) by analyzing multiple replicates of a simulated data set with the use of variance components-based methods. Specifically, we evaluated across replicates the variation in both the magnitude and the location of the peak lod scores. We analyzed QTLs whose effects accounted for 10-37% of the phenotypic variance in the quantitative traits. Our analyses revealed that the precision of QTL localization was directly related to the magnitude of the QTL effect. For a QTL with effect accounting for > 20% of total phenotypic variation, > 90% of the linkage peaks fall within 10 cM from the true gene location. We found no evidence that, for a given magnitude of the lod score, the presence of interaction influenced the precision of QTL localization.

Allelic frequencies and association with carcass traits of six genes in local subpopulations of Japanese Black cattle.

PubMed

Nishimaki, Takahiro; Ibi, Takayuki; Siqintuya; Kobayashi, Naohiko; Matsuhashi, Tamako; Akiyama, Takayuki; Yoshida, Emi; Imai, Kazumi; Matsui, Mayu; Uemura, Keiichi; Eto, Hisayoshi; Watanabe, Naoto; Fujita, Tatsuo; Saito, Yosuke; Komatsu, Tomohiko; Hoshiba, Hiroshi; Mannen, Hideyuki; Sasazaki, Shinji; Kunieda, Tetsuo

2016-04-01

Marker-assisted selection (MAS) is expected to accelerate the genetic improvement of Japanese Black cattle. However, verification of the effects of the genes for MAS in different subpopulations is required prior to the application of MAS. In this study, we investigated the allelic frequencies and genotypic effects for carcass traits of six genes, which can be used in MAS, in eight local subpopulations. These genes are SCD, FASN and SREBP1, which are associated with the fatty acid composition of meat, and NCAPG, MC1R and F11, which are associated with carcass weight, coat color and blood coagulation abnormality, respectively. The frequencies of desirable alleles of SCD and FASN were relatively high and that of NCAPG was relatively low, and NCAPG was significantly associated with several carcass traits, including carcass weight. The proportions of genotypic variance explained by NCAPG to phenotypic variance were 4.83 for carcass weight. We thus confirmed that NCAPG is a useful marker for selection of carcass traits in these subpopulations. In addition, we found that the desirable alleles of six genes showed no negative effects on carcass traits. Therefore, selection using these genes to improve target traits should not have negative impacts on carcass traits. © 2015 Japanese Society of Animal Science.

Identification of a novel locus associated with skin colour in African-admixed populations

PubMed Central

Hernandez-Pacheco, Natalia; Flores, Carlos; Alonso, Santos; Eng, Celeste; Mak, Angel C. Y.; Hunstman, Scott; Hu, Donglei; White, Marquitta J.; Oh, Sam S.; Meade, Kelley; Farber, Harold J.; Avila, Pedro C.; Serebrisky, Denise; Thyne, Shannon M.; Brigino-Buenaventura, Emerita; Rodriguez-Cintron, William; Sen, Saunak; Kumar, Rajesh; Lenoir, Michael; Rodriguez-Santana, Jose R.; Burchard, Esteban G.; Pino-Yanes, Maria

2017-01-01

Skin pigmentation is a complex trait that varies largely among populations. Most genome-wide association studies of this trait have been performed in Europeans and Asians. We aimed to uncover genes influencing skin colour in African-admixed individuals. We performed a genome-wide association study of melanin levels in 285 Hispanic/Latino individuals from Puerto Rico, analyzing 14 million genetic variants. A total of 82 variants with p-value ≤1 × 10−5 were followed up in 373 African Americans. Fourteen single nucleotide polymorphisms were replicated, of which nine were associated with skin colour at genome-wide significance in a meta-analysis across the two studies. These results validated the association of two previously known skin pigmentation genes, SLC24A5 (minimum p = 2.62 × 10−14, rs1426654) and SLC45A2 (minimum p = 9.71 × 10−10, rs16891982), and revealed the intergenic region of BEND7 and PRPF18 as a novel locus associated with this trait (minimum p = 4.58 × 10−9, rs6602666). The most significant variant within this region is common among African-descent populations but not among Europeans or Native Americans. Our findings support the advantages of analyzing African-admixed populations to discover new genes influencing skin pigmentation. PMID:28300201

Syndromes associated with Homo sapiens pol II regulatory genes.

PubMed

Bina, M; Demmon, S; Pares-Matos, E I

2000-01-01

The molecular basis of human characteristics is an intriguing but an unresolved problem. Human characteristics cover a broad spectrum, from the obvious to the abstract. Obvious characteristics may include morphological features such as height, shape, and facial form. Abstract characteristics may be hidden in processes that are controlled by hormones and the human brain. In this review we examine exaggerated characteristics presented as syndromes. Specifically, we focus on human genes that encode transcription factors to examine morphological, immunological, and hormonal anomalies that result from deletion, insertion, or mutation of genes that regulate transcription by RNA polymerase II (the Pol II genes). A close analysis of abnormal phenotypes can give clues into how sequence variations in regulatory genes and changes in transcriptional control may give rise to characteristics defined as complex traits.

A Critical Look at Entropy-Based Gene-Gene Interaction Measures.

PubMed

Lee, Woojoo; Sjölander, Arvid; Pawitan, Yudi

2016-07-01

Several entropy-based measures for detecting gene-gene interaction have been proposed recently. It has been argued that the entropy-based measures are preferred because entropy can better capture the nonlinear relationships between genotypes and traits, so they can be useful to detect gene-gene interactions for complex diseases. These suggested measures look reasonable at intuitive level, but so far there has been no detailed characterization of the interactions captured by them. Here we study analytically the properties of some entropy-based measures for detecting gene-gene interactions in detail. The relationship between interactions captured by the entropy-based measures and those of logistic regression models is clarified. In general we find that the entropy-based measures can suffer from a lack of specificity in terms of target parameters, i.e., they can detect uninteresting signals as interactions. Numerical studies are carried out to confirm theoretical findings. © 2016 WILEY PERIODICALS, INC.

GENETIC VARIATION IN BABOON CRANIOFACIAL SEXUAL DIMORPHISM

PubMed Central

Willmore, Katherine E.; Roseman, Charles C.; Rogers, Jeffrey; Richtsmeier, Joan T.; Cheverud, James M.

2010-01-01

Sexual dimorphism is a widespread phenomenon and contributes greatly to intraspecies variation. Despite a long history of active research, the genetic basis of dimorphism for complex traits remains unknown. Understanding the sex-specific differences in genetic architecture for cranial traits in a highly dimorphic species could identify possible mechanisms through which selection acts to produce dimorphism. Using distances calculated from three-dimensional landmark data from CT scans of 402 baboon skulls from a known genealogy, we estimated genetic variance parameters in both sexes to determine the presence of gene-by-sex (G × S) interactions and X-linked heritability. We hypothesize that traits exhibiting the greatest degree of sexual dimorphism (facial traits in baboons) will demonstrate either stronger G × S interactions or X-linked effects. We found G × S interactions and X-linked effects for a few measures that span the areas connecting the face to the neurocranium but for no traits restricted to the face. This finding suggests that facial traits will have a limited response to selection for further evolution of dimorphism in this population. We discuss the implications of our results with respect to the origins of cranial sexual dimorphism in this baboon sample, and how the genetic architecture of these traits affects their potential for future evolution. PMID:19210535

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

Gene-trait matching across the Bifidobacterium longum pan-genome reveals considerable diversity in carbohydrate catabolism among human infant strains.

PubMed

Arboleya, Silvia; Bottacini, Francesca; O'Connell-Motherway, Mary; Ryan, C Anthony; Ross, R Paul; van Sinderen, Douwe; Stanton, Catherine

2018-01-08

Bifidobacterium longum is a common member of the human gut microbiota and is frequently present at high numbers in the gut microbiota of humans throughout life, thus indicative of a close symbiotic host-microbe relationship. Different mechanisms may be responsible for the high competitiveness of this taxon in its human host to allow stable establishment in the complex and dynamic intestinal microbiota environment. The objective of this study was to assess the genetic and metabolic diversity in a set of 20 B. longum strains, most of which had previously been isolated from infants, by performing whole genome sequencing and comparative analysis, and to analyse their carbohydrate utilization abilities using a gene-trait matching approach. We analysed their pan-genome and their phylogenetic relatedness. All strains clustered in the B. longum ssp. longum phylogenetic subgroup, except for one individual strain which was found to cluster in the B. longum ssp. suis phylogenetic group. The examined strains exhibit genomic diversity, while they also varied in their sugar utilization profiles. This allowed us to perform a gene-trait matching exercise enabling the identification of five gene clusters involved in the utilization of xylo-oligosaccharides, arabinan, arabinoxylan, galactan and fucosyllactose, the latter of which is an abundant human milk oligosaccharide (HMO). The results showed high diversity in terms of genes and predicted glycosyl-hydrolases, as well as the ability to metabolize a large range of sugars. Moreover, we corroborate the capability of B. longum ssp. longum to metabolise HMOs. Ultimately, their intraspecific genomic diversity and the ability to consume a wide assortment of carbohydrates, ranging from plant-derived carbohydrates to HMOs, may provide an explanation for the competitive advantage and persistence of B. longum in the human gut microbiome.

The genetic architecture of normal variation in human pigmentation: an evolutionary perspective and model.

PubMed

McEvoy, Brian; Beleza, Sandra; Shriver, Mark D

2006-10-15

Skin pigmentation varies substantially across human populations in a manner largely coincident with ultraviolet radiation intensity. This observation suggests that natural selection in response to sunlight is a major force in accounting for pigmentation variability. We review recent progress in identifying the genes controlling this variation with a particular focus on the trait's evolutionary past and the potential role of testing for signatures of selection in aiding the discovery of functionally important genes. We have analyzed SNP data from the International HapMap project in 77 pigmentation candidate genes for such signatures. On the basis of these results and other similar work, we provide a tentative three-population model (West Africa, East Asia and North Europe) of the evolutionary-genetic architecture of human pigmentation. These results suggest a complex evolutionary history, with selection acting on different gene targets at different times and places in the human past. Some candidate genes may have been selected in the ancestral human population, others in the 'out of Africa' proto European-Asian population, whereas most appear to have selectively evolved solely in either Europeans or East Asians separately despite the pigmentation similarities between these two populations. Selection signatures can provide important clues to aid gene discovery. However, these should be viewed as complements, rather than replacements of, functional studies including linkage and association analyses, which can directly refine our understanding of the trait.

Risks and consequences of gene flow from herbicide-resistant crops: canola (Brassica napus L) as a case study.

PubMed

Légère, Anne

2005-03-01

Data from the literature and recent experiments with herbicide-resistant (HR) canola (Brassica napus L) repeatedly confirm that genes and transgenes will flow and hybrids will form if certain conditions are met. These include sympatry with a compatible relative (weedy, wild or crop), synchrony of flowering, successful fertilization and viable offspring. The chance of these events occurring is real; however, it is generally low and varies with species and circumstances. Plants of the same species (non-transgenic or with a different HR transgene) in neighbouring fields may inherit the new HR gene, potentially generating plants with single and multiple HR. For canola, seed losses at harvest and secondary dormancy ensures the persistence over time of the HR trait(s) in the seed bank, and the potential presence of crop volunteers in subsequent crops. Although canola has many wild/weedy relatives, the risk of gene flow is quite low for most of these species, except with Brassica rapa L. Introgression of genes and transgenes in B rapa populations occurs with apparently little or no fitness costs. Consequences of HR canola gene flow for the agro-ecosystem include contamination of seed lots, potentially more complex and costly control strategy, and limitations in cropping system design. Consequences for non-agricultural habitats may be minor but appear largely undocumented. Minister of Public Works and Government Services Canada 2005

Chimpanzee sociability is associated with vasopressin (Avpr1a) but not oxytocin receptor gene (OXTR) variation.

PubMed

Staes, Nicky; Koski, Sonja E; Helsen, Philippe; Fransen, Erik; Eens, Marcel; Stevens, Jeroen M G

2015-09-01

The importance of genes in regulating phenotypic variation of personality traits in humans and animals is becoming increasingly apparent in recent studies. Here we focus on variation in the vasopressin receptor gene 1a (Avpr1a) and oxytocin receptor gene (OXTR) and their effects on social personality traits in chimpanzees. We combine newly available genetic data on Avpr1a and OXTR allelic variation of 62 captive chimpanzees with individual variation in personality, based on behavioral assessments. Our study provides support for the positive association of the Avpr1a promoter region, in particular the presence of DupB, and sociability in chimpanzees. This complements findings of previous studies on adolescent chimpanzees and studies that assessed personality using questionnaire data. In contrast, no significant associations were found for the single nucleotide polymorphism (SNP) ss1388116472 of the OXTR and any of the personality components. Most importantly, our study provides additional evidence for the regulatory function of the 5' promoter region of Avpr1a on social behavior and its evolutionary stable effect across species, including rodents, chimpanzees and humans. Although it is generally accepted that complex social behavior is regulated by a combination of genes, the environment and their interaction, our findings highlight the importance of candidate genes with large effects on behavioral variation. Copyright © 2015 Elsevier Inc. All rights reserved.

Toward Bridging the Mechanistic Gap between Genes and Traits by Emphasizing the Role of Proteins in a Computational Environment

ERIC Educational Resources Information Center

Haskel-Ittah, Michal; Yarden, Anat

2017-01-01

Previous studies have shown that students often ignore molecular mechanisms when describing genetic phenomena. Specifically, students tend to directly link genes to their encoded traits, ignoring the role of proteins as mediators in this process. We tested the ability of 10th grade students to connect genes to traits through proteins, using…

Gene-gene and gene-environment interactions defining lipid-related traits.

PubMed

Ordovás, José M; Robertson, Ruairi; Cléirigh, Ellen Ní

2011-04-01

Steps towards reducing chronic disease progression are continuously being taken through the form of genomic research. Studies over the last year have highlighted more and more polymorphisms, pathways and interactions responsible for metabolic disorders such as cardiovascular disease, obesity and dyslipidemia. Many of these chronic illnesses can be partially blamed by altered lipid metabolism, combined with individual genetic components. Critical evaluation and comparison of these recent studies is essential in order to comprehend the results, conclusions and future prospects in the field of genomics as a whole. Recent literature elucidates significant gene--diet and gene--environment interactions resulting in altered lipid metabolism, inflammation and other metabolic imbalances leading to cardiovascular disease and obesity. Epigenetic and epistatic interactions are now becoming more significantly associated with such disorders, as genomic research digs deeper into the complex nature of genetic individuality and heritability. The vast array of data collected from genome-wide association studies must now be empowered and explored through more complex interaction studies, using standardized methods and larger sample sizes. In doing so the etiology of chronic disease progression will be further understood.

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

Gene regulatory networks reused to build novel traits: co-option of an eye-related gene regulatory network in eye-like organs and red wing patches on insect wings is suggested by optix expression.

PubMed

Monteiro, Antónia

2012-03-01

Co-option of the eye developmental gene regulatory network may have led to the appearance of novel functional traits on the wings of flies and butterflies. The first trait is a recently described wing organ in a species of extinct midge resembling the outer layers of the midge's own compound eye. The second trait is red pigment patches on Heliconius butterfly wings connected to the expression of an eye selector gene, optix. These examples, as well as others, are discussed regarding the type of empirical evidence and burden of proof that have been used to infer gene network co-option underlying the origin of novel traits. A conceptual framework describing increasing confidence in inference of network co-option is proposed. Novel research directions to facilitate inference of network co-option are also highlighted, especially in cases where the pre-existent and novel traits do not resemble each other. Copyright © 2012 WILEY Periodicals, Inc.

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.

Genetic Architecture of Atherosclerosis in Mice: A Systems Genetics Analysis of Common Inbred Strains

PubMed Central

Bennett, Brian J.; Davis, Richard C.; Civelek, Mete; Orozco, Luz; Wu, Judy; Qi, Hannah; Pan, Calvin; Packard, René R. Sevag; Eskin, Eleazar; Yan, Mujing; Kirchgessner, Todd; Wang, Zeneng; Li, Xinmin; Gregory, Jill C.; Hazen, Stanley L.; Gargalovic, Peter S.; Lusis, Aldons J.

2015-01-01

Common forms of atherosclerosis involve multiple genetic and environmental factors. While human genome-wide association studies have identified numerous loci contributing to coronary artery disease and its risk factors, these studies are unable to control environmental factors or examine detailed molecular traits in relevant tissues. We now report a study of natural variations contributing to atherosclerosis and related traits in over 100 inbred strains of mice from the Hybrid Mouse Diversity Panel (HMDP). The mice were made hyperlipidemic by transgenic expression of human apolipoprotein E-Leiden (APOE-Leiden) and human cholesteryl ester transfer protein (CETP). The mice were examined for lesion size and morphology as well as plasma lipid, insulin and glucose levels, and blood cell profiles. A subset of mice was studied for plasma levels of metabolites and cytokines. We also measured global transcript levels in aorta and liver. Finally, the uptake of acetylated LDL by macrophages from HMDP mice was quantitatively examined. Loci contributing to the traits were mapped using association analysis, and relationships among traits were examined using correlation and statistical modeling. A number of conclusions emerged. First, relationships among atherosclerosis and the risk factors in mice resemble those found in humans. Second, a number of trait-loci were identified, including some overlapping with previous human and mouse studies. Third, gene expression data enabled enrichment analysis of pathways contributing to atherosclerosis and prioritization of candidate genes at associated loci in both mice and humans. Fourth, the data provided a number of mechanistic inferences; for example, we detected no association between macrophage uptake of acetylated LDL and atherosclerosis. Fifth, broad sense heritability for atherosclerosis was much larger than narrow sense heritability, indicating an important role for gene-by-gene interactions. Sixth, stepwise linear regression showed that the combined variations in plasma metabolites, including LDL/VLDL-cholesterol, trimethylamine N-oxide (TMAO), arginine, glucose and insulin, account for approximately 30 to 40% of the variation in atherosclerotic lesion area. Overall, our data provide a rich resource for studies of complex interactions underlying atherosclerosis. PMID:26694027

Genetic analysis of the wild strawberry (Fragaria vesca) volatile composition.

PubMed

Urrutia, María; Rambla, José L; Alexiou, Konstantinos G; Granell, Antonio; Monfort, Amparo

2017-12-01

The volatile composition of wild strawberry (Fragaria vesca) fruit differs from that of the cultivated strawberry, having more intense and fruity aromas. Over the last few years, the diploid F. vesca has been recognized as a model species for genetic studies of cultivated strawberry (F. x ananassa), and here a previously developed F. vesca/F. bucharica Near Isogenic Line collection (NIL) was used to explore genetic variability of fruit quality traits. Analysis of fruit volatiles by GC-MS in our NIL collection revealed a complex and highly variable profile. One hundred compounds were unequivocally identified, including esters, aldehydes, ketones, alcohols, terpenoids, furans and lactones. Those in a subset, named key volatile compounds (KVCs), are likely contributors to the special aroma/flavour of wild strawberry. Genetic analysis revealed 50 major quantitative trait loci (QTL) including 14 QTL for KVCs, and one segregating as a dominant monogenetic trait for nerolidol. The most determinant regions affecting QTLs for KVCs, were mapped on LG5 and LG7. New candidate genes for the volatile QTL are proposed, based on differences in gene expression between NILs containing specific fragments of F. bucharica and the F. vesca recurrent genome. A high percentage of these candidate genes/alleles were colocalized within the boundaries of introgressed regions that contain QTLs, appearing to affect volatile metabolite accumulation acting in cis. A NIL collection is a good tool for the genetic dissection of volatile accumulation in wild strawberry fruit and a source of information for genes and alleles which may enhance aroma in cultivated strawberry. Copyright © 2017 The Authors. Published by Elsevier Masson SAS.. All rights reserved.

Global expression studies in baker's yeast reveal target genes for the improvement of industrially-relevant traits: the cases of CAF16 and ORC2.

PubMed

Pérez-Torrado, Roberto; Panadero, Joaquín; Hernández-López, María José; Prieto, José Antonio; Randez-Gil, Francisca

2010-07-13

Recent years have seen a huge growth in the market of industrial yeasts with the need for strains affording better performance or to be used in new applications. Stress tolerance of commercial Saccharomyces cerevisiae yeasts is, without doubt, a trait that needs improving. Such trait is, however, complex, and therefore only in-depth knowledge of their biochemical, physiological and genetic principles can help us to define improvement strategies and to identify the key factors for strain selection. We have determined the transcriptional response of commercial baker's yeast cells to both high-sucrose and lean dough by using DNA macroarrays and liquid dough (LD) model system. Cells from compressed yeast blocks display a reciprocal transcription program to that commonly reported for laboratory strains exposed to osmotic stress. This discrepancy likely reflects differences in strain background and/or experimental design. Quite remarkably, we also found that the transcriptional response of starved baker's yeast cells was qualitatively similar in the presence or absence of sucrose in the LD. Nevertheless, there was a set of differentially regulated genes, which might be relevant for cells to adapt to high osmolarity. Consistent with this, overexpression of CAF16 or ORC2, two transcriptional factor-encoding genes included in this group, had positive effects on leavening activity of baker's yeast. Moreover, these effects were more pronounced during freezing and frozen storage of high-sucrose LD. Engineering of differentially regulated genes opens the possibility to improve the physiological behavior of baker's yeast cells under stress conditions like those encountered in downstream applications.

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

Penn, Kevin; Jenkins, Caroline; Nett, Markus

Linking functional traits to bacterial phylogeny remains a fundamental but elusive goal of microbial ecology 1. Without this information, it becomes impossible to resolve meaningful units of diversity and the mechanisms by which bacteria interact with each other and adapt to environmental change. Ecological adaptations among bacterial populations have been linked to genomic islands, strain-specific regions of DNA that house functionally adaptive traits 2. In the case of environmental bacteria, these traits are largely inferred from bioinformatic or gene expression analyses 2, thus leaving few examples in which the functions of island genes have been experimentally characterized. Here we reportmore » the complete genome sequences of Salinispora tropica and S. arenicola, the first cultured, obligate marine Actinobacteria 3. These two species inhabit benthic marine environments and dedicate 8-10percent of their genomes to the biosynthesis of secondary metabolites. Despite a close phylogenetic relationship, 25 of 37 secondary metabolic pathways are species-specific and located within 21 genomic islands, thus providing new evidence linking secondary metabolism to ecological adaptation. Species-specific differences are also observed in CRISPR sequences, suggesting that variations in phage immunity provide fitness advantages that contribute to the cosmopolitan distribution of S. arenicola 4. The two Salinispora genomes have evolved by complex processes that include the duplication and acquisition of secondary metabolite genes, the products of which provide immediate opportunities for molecular diversification and ecological adaptation. Evidence that secondary metabolic pathways are exchanged by Horizontal Gene Transfer (HGT) yet are fixed among globally distributed populations 5 supports a functional role for their products and suggests that pathway acquisition represents a previously unrecognized force driving bacterial diversification« less

Multi-Tissue Omics Analyses Reveal Molecular Regulatory Networks for Puberty in Composite Beef Cattle

PubMed Central

Cánovas, Angela; Reverter, Antonio; DeAtley, Kasey L.; Ashley, Ryan L.; Colgrave, Michelle L.; Fortes, Marina R. S.; Islas-Trejo, Alma; Lehnert, Sigrid; Porto-Neto, Laercio; Rincón, Gonzalo; Silver, Gail A.; Snelling, Warren M.; Medrano, Juan F.; Thomas, Milton G.

2014-01-01

Puberty is a complex physiological event by which animals mature into an adult capable of sexual reproduction. In order to enhance our understanding of the genes and regulatory pathways and networks involved in puberty, we characterized the transcriptome of five reproductive tissues (i.e. hypothalamus, pituitary gland, ovary, uterus, and endometrium) as well as tissues known to be relevant to growth and metabolism needed to achieve puberty (i.e., longissimus dorsi muscle, adipose, and liver). These tissues were collected from pre- and post-pubertal Brangus heifers (3/8 Brahman; Bos indicus x 5/8 Angus; Bos taurus) derived from a population of cattle used to identify quantitative trait loci associated with fertility traits (i.e., age of first observed corpus luteum (ACL), first service conception (FSC), and heifer pregnancy (HPG)). In order to exploit the power of complementary omics analyses, pre- and post-puberty co-expression gene networks were constructed by combining the results from genome-wide association studies (GWAS), RNA-Seq, and bovine transcription factors. Eight tissues among pre-pubertal and post-pubertal Brangus heifers revealed 1,515 differentially expressed and 943 tissue-specific genes within the 17,832 genes confirmed by RNA-Seq analysis. The hypothalamus experienced the most notable up-regulation of genes via puberty (i.e., 204 out of 275 genes). Combining the results of GWAS and RNA-Seq, we identified 25 loci containing a single nucleotide polymorphism (SNP) associated with ACL, FSC, and (or) HPG. Seventeen of these SNP were within a gene and 13 of the genes were expressed in uterus or endometrium. Multi-tissue omics analyses revealed 2,450 co-expressed genes relative to puberty. The pre-pubertal network had 372,861 connections whereas the post-pubertal network had 328,357 connections. A sub-network from this process revealed key transcriptional regulators (i.e., PITX2, FOXA1, DACH2, PROP1, SIX6, etc.). Results from these multi-tissue omics analyses improve understanding of the number of genes and their complex interactions for puberty in cattle. PMID:25048735

Mitochondrial-Nuclear Epistasis: Implications for Human Aging and Longevity

PubMed Central

Tranah, Gregory

2010-01-01

There is substantial evidence that mitochondria are involved in the aging process. Mitochondrial function requires the coordinated expression of hundreds of nuclear genes and a few dozen mitochondrial genes, many of which have been associated with either extended or shortened life span. Impaired mitochondrial function resulting from mtDNA and nuclear DNA variation is likely to contribute to an imbalance in cellular energy homeostasis, increased vulnerability to oxidative stress, and an increased rate of cellular senescence and aging. The complex genetic architecture of mitochondria suggests that there may be an equally complex set of gene interactions (epistases) involving genetic variation in the nuclear and mitochondrial genomes. Results from Drosophila suggest that the effects of mtDNA haplotypes on longevity vary among different nuclear allelic backgrounds, which could account for the inconsistent associations that have been observed between mitochondrial DNA (mtDNA) haplogroups and survival in humans. A diversity of pathways may influence the way mitochondria and nuclear – mitochondrial interactions modulate longevity, including: oxidative phosphorylation; mitochondrial uncoupling; antioxidant defenses; mitochondrial fission and fusion; and sirtuin regulation of mitochondrial genes. We hypothesize that aging and longevity, as complex traits having a significant genetic component, are likely to be controlled by nuclear gene variants interacting with both inherited and somatic mtDNA variability. PMID:20601194

Why it is hard to find genes associated with social science traits: theoretical and empirical considerations.

PubMed

Chabris, Christopher F; Lee, James J; Benjamin, Daniel J; Beauchamp, Jonathan P; Glaeser, Edward L; Borst, Gregoire; Pinker, Steven; Laibson, David I

2013-10-01

We explain why traits of interest to behavioral scientists may have a genetic architecture featuring hundreds or thousands of loci with tiny individual effects rather than a few with large effects and why such an architecture makes it difficult to find robust associations between traits and genes. We conducted a genome-wide association study at 2 sites, Harvard University and Union College, measuring more than 100 physical and behavioral traits with a sample size typical of candidate gene studies. We evaluated predictions that alleles with large effect sizes would be rare and most traits of interest to social science are likely characterized by a lack of strong directional selection. We also carried out a theoretical analysis of the genetic architecture of traits based on R.A. Fisher's geometric model of natural selection and empirical analyses of the effects of selection bias and phenotype measurement stability on the results of genetic association studies. Although we replicated several known genetic associations with physical traits, we found only 2 associations with behavioral traits that met the nominal genome-wide significance threshold, indicating that physical and behavioral traits are mainly affected by numerous genes with small effects. The challenge for social science genomics is the likelihood that genes are connected to behavioral variation by lengthy, nonlinear, interactive causal chains, and unraveling these chains requires allying with personal genomics to take advantage of the potential for large sample sizes as well as continuing with traditional epidemiological studies.

Identification of Causal Genes, Networks, and Transcriptional Regulators of REM Sleep and Wake

PubMed Central

Millstein, Joshua; Winrow, Christopher J.; Kasarskis, Andrew; Owens, Joseph R.; Zhou, Lili; Summa, Keith C.; Fitzpatrick, Karrie; Zhang, Bin; Vitaterna, Martha H.; Schadt, Eric E.; Renger, John J.; Turek, Fred W.

2011-01-01

Study Objective: Sleep-wake traits are well-known to be under substantial genetic control, but the specific genes and gene networks underlying primary sleep-wake traits have largely eluded identification using conventional approaches, especially in mammals. Thus, the aim of this study was to use systems genetics and statistical approaches to uncover the genetic networks underlying 2 primary sleep traits in the mouse: 24-h duration of REM sleep and wake. Design: Genome-wide RNA expression data from 3 tissues (anterior cortex, hypothalamus, thalamus/midbrain) were used in conjunction with high-density genotyping to identify candidate causal genes and networks mediating the effects of 2 QTL regulating the 24-h duration of REM sleep and one regulating the 24-h duration of wake. Setting: Basic sleep research laboratory. Patients or Participants: Male [C57BL/6J × (BALB/cByJ × C57BL/6J*) F1] N2 mice (n = 283). Interventions: None. Measurements and Results: The genetic variation of a mouse N2 mapping cross was leveraged against sleep-state phenotypic variation as well as quantitative gene expression measurement in key brain regions using integrative genomics approaches to uncover multiple causal sleep-state regulatory genes, including several surprising novel candidates, which interact as components of networks that modulate REM sleep and wake. In particular, it was discovered that a core network module, consisting of 20 genes, involved in the regulation of REM sleep duration is conserved across the cortex, hypothalamus, and thalamus. A novel application of a formal causal inference test was also used to identify those genes directly regulating sleep via control of expression. Conclusion: Systems genetics approaches reveal novel candidate genes, complex networks and specific transcriptional regulators of REM sleep and wake duration in mammals. Citation: Millstein J; Winrow CJ; Kasarskis A; Owens JR; Zhou L; Summa KC; Fitzpatrick K; Zhang B; Vitaterna MH; Schadt EE; Renger JJ; Turek FW. Identification of causal genes, networks, and transcriptional regulators of REM sleep and wake. SLEEP 2011;34(11):1469-1477. PMID:22043117

Genetic architecture and temporal patterns of biomass accumulation in spring barley revealed by image analysis.

PubMed

Neumann, Kerstin; Zhao, Yusheng; Chu, Jianting; Keilwagen, Jens; Reif, Jochen C; Kilian, Benjamin; Graner, Andreas

2017-08-10

Genetic mapping of phenotypic traits generally focuses on a single time point, but biomass accumulates continuously during plant development. Resolution of the temporal dynamics that affect biomass recently became feasible using non-destructive imaging. With the aim to identify key genetic factors for vegetative biomass formation from the seedling stage to flowering, we explored growth over time in a diverse collection of two-rowed spring barley accessions. High heritabilities facilitated the temporal analysis of trait relationships and identification of quantitative trait loci (QTL). Biomass QTL tended to persist only a short period during early growth. More persistent QTL were detected around the booting stage. We identified seven major biomass QTL, which together explain 55% of the genetic variance at the seedling stage, and 43% at the booting stage. Three biomass QTL co-located with genes or QTL involved in phenology. The most important locus for biomass was independent from phenology and is located on chromosome 7HL at 141 cM. This locus explained ~20% of the genetic variance, was significant over a long period of time and co-located with HvDIM, a gene involved in brassinosteroid synthesis. Biomass is a dynamic trait and is therefore orchestrated by different QTL during early and late growth stages. Marker-assisted selection for high biomass at booting stage is most effective by also including favorable alleles from seedling biomass QTL. Selection for dynamic QTL may enhance genetic gain for complex traits such as biomass or, in the future, even grain yield.

Interactions between genetic variation and cellular environment in skeletal muscle gene expression.

PubMed

Taylor, D Leland; Knowles, David A; Scott, Laura J; Ramirez, Andrea H; Casale, Francesco Paolo; Wolford, Brooke N; Guan, Li; Varshney, Arushi; Albanus, Ricardo D'Oliveira; Parker, Stephen C J; Narisu, Narisu; Chines, Peter S; Erdos, Michael R; Welch, Ryan P; Kinnunen, Leena; Saramies, Jouko; Sundvall, Jouko; Lakka, Timo A; Laakso, Markku; Tuomilehto, Jaakko; Koistinen, Heikki A; Stegle, Oliver; Boehnke, Michael; Birney, Ewan; Collins, Francis S

2018-01-01

From whole organisms to individual cells, responses to environmental conditions are influenced by genetic makeup, where the effect of genetic variation on a trait depends on the environmental context. RNA-sequencing quantifies gene expression as a molecular trait, and is capable of capturing both genetic and environmental effects. In this study, we explore opportunities of using allele-specific expression (ASE) to discover cis-acting genotype-environment interactions (GxE)-genetic effects on gene expression that depend on an environmental condition. Treating 17 common, clinical traits as approximations of the cellular environment of 267 skeletal muscle biopsies, we identify 10 candidate environmental response expression quantitative trait loci (reQTLs) across 6 traits (12 unique gene-environment trait pairs; 10% FDR per trait) including sex, systolic blood pressure, and low-density lipoprotein cholesterol. Although using ASE is in principle a promising approach to detect GxE effects, replication of such signals can be challenging as validation requires harmonization of environmental traits across cohorts and a sufficient sampling of heterozygotes for a transcribed SNP. Comprehensive discovery and replication will require large human transcriptome datasets, or the integration of multiple transcribed SNPs, coupled with standardized clinical phenotyping.

Network-Based Identification of Adaptive Pathways in Evolved Ethanol-Tolerant Bacterial Populations.

PubMed

Swings, Toon; Weytjens, Bram; Schalck, Thomas; Bonte, Camille; Verstraeten, Natalie; Michiels, Jan; Marchal, Kathleen

2017-11-01

Efficient production of ethanol for use as a renewable fuel requires organisms with a high level of ethanol tolerance. However, this trait is complex and increased tolerance therefore requires mutations in multiple genes and pathways. Here, we use experimental evolution for a system-level analysis of adaptation of Escherichia coli to high ethanol stress. As adaptation to extreme stress often results in complex mutational data sets consisting of both causal and noncausal passenger mutations, identifying the true adaptive mutations in these settings is not trivial. Therefore, we developed a novel method named IAMBEE (Identification of Adaptive Mutations in Bacterial Evolution Experiments). IAMBEE exploits the temporal profile of the acquisition of mutations during evolution in combination with the functional implications of each mutation at the protein level. These data are mapped to a genome-wide interaction network to search for adaptive mutations at the level of pathways. The 16 evolved populations in our data set together harbored 2,286 mutated genes with 4,470 unique mutations. Analysis by IAMBEE significantly reduced this number and resulted in identification of 90 mutated genes and 345 unique mutations that are most likely to be adaptive. Moreover, IAMBEE not only enabled the identification of previously known pathways involved in ethanol tolerance, but also identified novel systems such as the AcrAB-TolC efflux pump and fatty acids biosynthesis and even allowed to gain insight into the temporal profile of adaptation to ethanol stress. Furthermore, this method offers a solid framework for identifying the molecular underpinnings of other complex traits as well. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Differential gene expression of wheat progeny with contrasting levels of transpiration efficiency.

PubMed

Xue, Gang-Ping; McIntyre, C Lynne; Chapman, Scott; Bower, Neil I; Way, Heather; Reverter, Antonio; Clarke, Bryan; Shorter, Ray

2006-08-01

High water use efficiency or transpiration efficiency (TE) in wheat is a desirable physiological trait for increasing grain yield under water-limited environments. The identification of genes associated with this trait would facilitate the selection for genotypes with higher TE using molecular markers. We performed an expression profiling (microarray) analysis of approximately 16,000 unique wheat ESTs to identify genes that were differentially expressed between wheat progeny lines with contrasting TE levels from a cross between Quarrion (high TE) and Genaro 81 (low TE). We also conducted a second microarray analysis to identify genes responsive to drought stress in wheat leaves. Ninety-three genes that were differentially expressed between high and low TE progeny lines were identified. One fifth of these genes were markedly responsive to drought stress. Several potential growth-related regulatory genes, which were down-regulated by drought, were expressed at a higher level in the high TE lines than the low TE lines and are potentially associated with a biomass production component of the Quarrion-derived high TE trait. Eighteen of the TE differentially expressed genes were further analysed using quantitative RT-PCR on a separate set of plant samples from those used for microarray analysis. The expression levels of 11 of the 18 genes were positively correlated with the high TE trait, measured as carbon isotope discrimination (Delta(13)C). These data indicate that some of these TE differentially expressed genes are candidates for investigating processes that underlie the high TE trait or for use as expression quantitative trait loci (eQTLs) for TE.

Schizophrenia and Human Self-Domestication: An Evolutionary Linguistics Approach.

PubMed

Benítez-Burraco, Antonio; Di Pietro, Lorena; Barba, Marta; Lattanzi, Wanda

2017-01-01

Schizophrenia (SZ) is a pervasive neurodevelopmental disorder that entails social and cognitive deficits, including marked language problems. Its complex multifactorial etiopathogenesis, including genetic and environmental factors, is still widely uncertain. SZ incidence has always been high and quite stable in human populations, across time and regardless of cultural implications, for unclear reasons. It has been hypothesized that SZ pathophysiology may involve the biological components that changed during the recent human evolutionary history, and led to our distinctive mode of cognition, which includes language skills. In this paper we explore this hypothesis, focusing on the self-domestication of the human species. This has been claimed to account for many human-specific distinctive traits, including aspects of our behavior and cognition, and to favor the emergence of complex languages through cultural evolution. The "domestication syndrome" in mammals comprises the constellation of traits exhibited by domesticated strains, seemingly resulting from the hypofunction of the neural crest. It is our intention to show that people with SZ exhibit more marked domesticated traits at the morphological, physiological, and behavioral levels. We also show that genes involved in domestication and neural crest development and function comprise nearly 20% of SZ candidates, most of which exhibit altered expression profiles in the brain of SZ patients, specifically in areas involved in language processing. Based on these observations, we conclude that SZ may represent an abnormal ontogenetic itinerary for the human faculty of language, resulting, at least in part, from changes in genes important for the domestication syndrome and primarily involving the neural crest. © 2017 S. Karger AG, Basel.

A random set scoring model for prioritization of disease candidate genes using protein complexes and data-mining of GeneRIF, OMIM and PubMed records.

PubMed

Jiang, Li; Edwards, Stefan M; Thomsen, Bo; Workman, Christopher T; Guldbrandtsen, Bernt; Sørensen, Peter

2014-09-24

Prioritizing genetic variants is a challenge because disease susceptibility loci are often located in genes of unknown function or the relationship with the corresponding phenotype is unclear. A global data-mining exercise on the biomedical literature can establish the phenotypic profile of genes with respect to their connection to disease phenotypes. The importance of protein-protein interaction networks in the genetic heterogeneity of common diseases or complex traits is becoming increasingly recognized. Thus, the development of a network-based approach combined with phenotypic profiling would be useful for disease gene prioritization. We developed a random-set scoring model and implemented it to quantify phenotype relevance in a network-based disease gene-prioritization approach. We validated our approach based on different gene phenotypic profiles, which were generated from PubMed abstracts, OMIM, and GeneRIF records. We also investigated the validity of several vocabulary filters and different likelihood thresholds for predicted protein-protein interactions in terms of their effect on the network-based gene-prioritization approach, which relies on text-mining of the phenotype data. Our method demonstrated good precision and sensitivity compared with those of two alternative complex-based prioritization approaches. We then conducted a global ranking of all human genes according to their relevance to a range of human diseases. The resulting accurate ranking of known causal genes supported the reliability of our approach. Moreover, these data suggest many promising novel candidate genes for human disorders that have a complex mode of inheritance. We have implemented and validated a network-based approach to prioritize genes for human diseases based on their phenotypic profile. We have devised a powerful and transparent tool to identify and rank candidate genes. Our global gene prioritization provides a unique resource for the biological interpretation of data from genome-wide association studies, and will help in the understanding of how the associated genetic variants influence disease or quantitative phenotypes.

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.

Genetic Architecture of Hybrid Male Sterility in Drosophila: Analysis of Intraspecies Variation for Interspecies Isolation

PubMed Central

Reed, Laura K.; LaFlamme, Brooke A.; Markow, Therese A.

2008-01-01

Background The genetic basis of postzygotic isolation is a central puzzle in evolutionary biology. Evolutionary forces causing hybrid sterility or inviability act on the responsible genes while they still are polymorphic, thus we have to study these traits as they arise, before isolation is complete. Methodology/Principal Findings Isofemale strains of D. mojavensis vary significantly in their production of sterile F1 sons when females are crossed to D. arizonae males. We took advantage of the intraspecific polymorphism, in a novel design, to perform quantitative trait locus (QTL) mapping analyses directly on F1 hybrid male sterility itself. We found that the genetic architecture of the polymorphism for hybrid male sterility (HMS) in the F1 is complex, involving multiple QTL, epistasis, and cytoplasmic effects. Conclusions/Significance The role of extensive intraspecific polymorphism, multiple QTL, and epistatic interactions in HMS in this young species pair shows that HMS is arising as a complex trait in this system. Directional selection alone would be unlikely to maintain polymorphism at multiple loci, thus we hypothesize that directional selection is unlikely to be the only evolutionary force influencing postzygotic isolation. PMID:18728782

Nature, nurture and evolution of intra-species variation in mosquito arbovirus transmission competence.

PubMed

Tabachnick, Walter J

2013-01-11

Mosquitoes vary in their competence or ability to transmit arthropod-borne viruses (arboviruses). Many arboviruses cause disease in humans and animals. Identifying the environmental and genetic causes of variation in mosquito competence for arboviruses is one of the great challenges in public health. Progress identifying genetic (nature) and environmental (nurture) factors influencing mosquito competence for arboviruses is reviewed. There is great complexity in the various traits that comprise mosquito competence. The complex interactions between environmental and genetic factors controlling these traits and the factors shaping variation in Nature are largely unknown. The norms of reaction of specific genes influencing competence, their distributions in natural populations and the effects of genetic polymorphism on phenotypic variation need to be determined. Mechanisms influencing competence are not likely due to natural selection because of the direct effects of the arbovirus on mosquito fitness. More likely the traits for mosquito competence for arboviruses are the effects of adaptations for other functions of these competence mechanisms. Determining these other functions is essential to understand the evolution and distributions of competence for arboviruses. This information is needed to assess risk from mosquito-borne disease, predict new mosquito-arbovirus systems, and provide novel strategies to mitigate mosquito-borne arbovirus transmission.

A Simple Test of Class-Level Genetic Association Can Reveal Novel Cardiometabolic Trait Loci.

PubMed

Qian, Jing; Nunez, Sara; Reed, Eric; Reilly, Muredach P; Foulkes, Andrea S

2016-01-01

Characterizing the genetic determinants of complex diseases can be further augmented by incorporating knowledge of underlying structure or classifications of the genome, such as newly developed mappings of protein-coding genes, epigenetic marks, enhancer elements and non-coding RNAs. We apply a simple class-level testing framework, termed Genetic Class Association Testing (GenCAT), to identify protein-coding gene association with 14 cardiometabolic (CMD) related traits across 6 publicly available genome wide association (GWA) meta-analysis data resources. GenCAT uses SNP-level meta-analysis test statistics across all SNPs within a class of elements, as well as the size of the class and its unique correlation structure, to determine if the class is statistically meaningful. The novelty of findings is evaluated through investigation of regional signals. A subset of findings are validated using recently updated, larger meta-analysis resources. A simulation study is presented to characterize overall performance with respect to power, control of family-wise error and computational efficiency. All analysis is performed using the GenCAT package, R version 3.2.1. We demonstrate that class-level testing complements the common first stage minP approach that involves individual SNP-level testing followed by post-hoc ascribing of statistically significant SNPs to genes and loci. GenCAT suggests 54 protein-coding genes at 41 distinct loci for the 13 CMD traits investigated in the discovery analysis, that are beyond the discoveries of minP alone. An additional application to biological pathways demonstrates flexibility in defining genetic classes. We conclude that it would be prudent to include class-level testing as standard practice in GWA analysis. GenCAT, for example, can be used as a simple, complementary and efficient strategy for class-level testing that leverages existing data resources, requires only summary level data in the form of test statistics, and adds significant value with respect to its potential for identifying multiple novel and clinically relevant trait associations.

Panx3 links body mass index and tumorigenesis in a genetically heterogeneous mouse model of carcinogen-induced cancer. | Office of Cancer Genomics

Cancer.gov

Body mass index (BMI) has been implicated as a primary factor influencing cancer development. However, understanding the relationship between these two complex traits has been confounded by both environmental and genetic heterogeneity. Analysis of QTL linked to tumorigenesis and BMI identified several loci associated with both phenotypes. Exploring these loci in greater detail revealed a novel relationship between the Pannexin 3 gene (Panx3) and both BMI and tumorigenesis. Panx3 is positively associated with BMI and is strongly tied to a lipid metabolism gene expression network.

Architecture of energy balance traits in emerging lines of the Collaborative Cross

PubMed Central

Aylor, David L.; Miller, Darla R.; Churchill, Gary A.; Chesler, Elissa J.; de Villena, Fernando Pardo-Manuel; Threadgill, David W.; Pomp, Daniel

2011-01-01

The potential utility of the Collaborative Cross (CC) mouse resource was evaluated to better understand complex traits related to energy balance. A primary focus was to examine if genetic diversity in emerging CC lines (pre-CC) would translate into equivalent phenotypic diversity. Second, we mapped quantitative trait loci (QTL) for 15 metabolism- and exercise-related phenotypes in this population. We evaluated metabolic and voluntary exercise traits in 176 pre-CC lines, revealing phenotypic variation often exceeding that seen across the eight founder strains from which the pre-CC was derived. Many phenotypic correlations existing within the founder strains were no longer significant in the pre-CC population, potentially representing reduced linkage disequilibrium (LD) of regions harboring multiple genes with effects on energy balance or disruption of genetic structure of extant inbred strains with substantial shared ancestry. QTL mapping revealed five significant and eight suggestive QTL for body weight (Chr 4, 7.54 Mb; CI 3.32–10.34 Mb; Bwq14), body composition, wheel running (Chr 16, 33.2 Mb; CI 32.5–38.3 Mb), body weight change in response to exercise (1: Chr 6, 77.7Mb; CI 72.2–83.4 Mb and 2: Chr 6, 42.8 Mb; CI 39.4–48.1 Mb), and food intake during exercise (Chr 12, 85.1 Mb; CI 82.9–89.0 Mb). Some QTL overlapped with previously mapped QTL for similar traits, whereas other QTL appear to represent novel loci. These results suggest that the CC will be a powerful, high-precision tool for examining the genetic architecture of complex traits such as those involved in regulation of energy balance. PMID:21427413

Detecting Genetic Interactions for Quantitative Traits Using m-Spacing Entropy Measure

PubMed Central

Yee, Jaeyong; Kwon, Min-Seok; Park, Taesung; Park, Mira

2015-01-01

A number of statistical methods for detecting gene-gene interactions have been developed in genetic association studies with binary traits. However, many phenotype measures are intrinsically quantitative and categorizing continuous traits may not always be straightforward and meaningful. Association of gene-gene interactions with an observed distribution of such phenotypes needs to be investigated directly without categorization. Information gain based on entropy measure has previously been successful in identifying genetic associations with binary traits. We extend the usefulness of this information gain by proposing a nonparametric evaluation method of conditional entropy of a quantitative phenotype associated with a given genotype. Hence, the information gain can be obtained for any phenotype distribution. Because any functional form, such as Gaussian, is not assumed for the entire distribution of a trait or a given genotype, this method is expected to be robust enough to be applied to any phenotypic association data. Here, we show its use to successfully identify the main effect, as well as the genetic interactions, associated with a quantitative trait. PMID:26339620

Integrated metagenomic analysis of the rumen microbiome of cattle reveals key biological mechanisms associated with methane traits.

PubMed

Wang, Haiying; Zheng, Huiru; Browne, Fiona; Roehe, Rainer; Dewhurst, Richard J; Engel, Felix; Hemmje, Matthias; Lu, Xiangwu; Walsh, Paul

2017-07-15

Methane is one of the major contributors to global warming. The rumen microbiota is directly involved in methane production in cattle. The link between variation in rumen microbial communities and host genetics has important applications and implications in bioscience. Having the potential to reveal the full extent of microbial gene diversity and complex microbial interactions, integrated metagenomics and network analysis holds great promise in this endeavour. This study investigates the rumen microbial community in cattle through the integration of metagenomic and network-based approaches. Based on the relative abundance of 1570 microbial genes identified in a metagenomics analysis, the co-abundance network was constructed and functional modules of microbial genes were identified. One of the main contributions is to develop a random matrix theory-based approach to automatically determining the correlation threshold used to construct the co-abundance network. The resulting network, consisting of 549 microbial genes and 3349 connections, exhibits a clear modular structure with certain trait-specific genes highly over-represented in modules. More specifically, all the 20 genes previously identified to be associated with methane emissions are found in a module (hypergeometric test, p<10 -11 ). One third of genes are involved in methane metabolism pathways. The further examination of abundance profiles across 8 samples of genes highlights that the revealed pattern of metagenomics abundance has a strong association with methane emissions. Furthermore, the module is significantly enriched with microbial genes encoding enzymes that are directly involved in methanogenesis (hypergeometric test, p<10 -9 ). Copyright © 2017 Elsevier Inc. All rights reserved.

Imaging-Genetics in Dyslexia: Connecting risk genetic variants to brain neuroimaging and ultimately to reading impairments

PubMed Central

Eicher, John D.; Gruen, Jeffrey R.

2013-01-01

Dyslexia is a common pediatric disorder that affects 5-17% of schoolchildren in the United States. It is marked by unexpected difficulties in fluent reading despite adequate intelligence, opportunity, and instruction. Classically, neuropsychologists have studied dyslexia using a variety of neurocognitive batteries to gain insight into the specific deficits and impairments in affected children. Since dyslexia is a complex genetic trait with high heritability, analyses conditioned on performance on these neurocognitive batteries have been used to try to identify associated genes. This has led to some successes in identifying contributing genes, although much of the heritability remains unexplained. Additionally, the lack of relevant human brain tissue for analysis and the challenges of modeling a uniquely human trait in animals are barriers to advancing our knowledge of the underlying pathophysiology. In vivo imaging technologies, however, present new opportunities to examine dyslexia and reading skills in a clearly relevant context in human subjects. Recent investigations have started to integrate these imaging data with genetic data in attempts to gain a more complete and complex understanding of reading processes. In addition to bridging the gap from genetic risk variant to a discernible neuroimaging phenotype and ultimately to the clinical impairments in reading performance, the use of neuroimaging phenotypes will reveal novel risk genes and variants. In this article, we briefly discuss the genetic and imaging investigations and take an in-depth look at the recent imaging-genetics investigations of dyslexia. PMID:23916419

Genetic control of root growth: from genes to networks.

PubMed

Slovak, Radka; Ogura, Takehiko; Satbhai, Santosh B; Ristova, Daniela; Busch, Wolfgang

2016-01-01

Roots are essential organs for higher plants. They provide the plant with nutrients and water, anchor the plant in the soil, and can serve as energy storage organs. One remarkable feature of roots is that they are able to adjust their growth to changing environments. This adjustment is possible through mechanisms that modulate a diverse set of root traits such as growth rate, diameter, growth direction and lateral root formation. The basis of these traits and their modulation are at the cellular level, where a multitude of genes and gene networks precisely regulate development in time and space and tune it to environmental conditions. This review first describes the root system and then presents fundamental work that has shed light on the basic regulatory principles of root growth and development. It then considers emerging complexities and how they have been addressed using systems-biology approaches, and then describes and argues for a systems-genetics approach. For reasons of simplicity and conciseness, this review is mostly limited to work from the model plant Arabidopsis thaliana, in which much of the research in root growth regulation at the molecular level has been conducted. While forward genetic approaches have identified key regulators and genetic pathways, systems-biology approaches have been successful in shedding light on complex biological processes, for instance molecular mechanisms involving the quantitative interaction of several molecular components, or the interaction of large numbers of genes. However, there are significant limitations in many of these methods for capturing dynamic processes, as well as relating these processes to genotypic and phenotypic variation. The emerging field of systems genetics promises to overcome some of these limitations by linking genotypes to complex phenotypic and molecular data using approaches from different fields, such as genetics, genomics, systems biology and phenomics. © The Author 2015. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Identification of multiple interacting alleles conferring low glycerol and high ethanol yield in Saccharomyces cerevisiae ethanolic fermentation

PubMed Central

2013-01-01

Background Genetic engineering of industrial microorganisms often suffers from undesirable side effects on essential functions. Reverse engineering is an alternative strategy to improve multifactorial traits like low glycerol/high ethanol yield in yeast fermentation. Previous rational engineering of this trait always affected essential functions like growth and stress tolerance. We have screened Saccharomyces cerevisiae biodiversity for specific alleles causing lower glycerol/higher ethanol yield, assuming higher compatibility with normal cellular functionality. Previous work identified ssk1E330N…K356N as causative allele in strain CBS6412, which displayed the lowest glycerol/ethanol ratio. Results We have now identified a unique segregant, 26B, that shows similar low glycerol/high ethanol production as the superior parent, but lacks the ssk1E330N…K356N allele. Using segregants from the backcross of 26B with the inferior parent strain, we applied pooled-segregant whole-genome sequence analysis and identified three minor quantitative trait loci (QTLs) linked to low glycerol/high ethanol production. Within these QTLs, we identified three novel alleles of known regulatory and structural genes of glycerol metabolism, smp1R110Q,P269Q, hot1P107S,H274Y and gpd1L164P as causative genes. All three genes separately caused a significant drop in the glycerol/ethanol production ratio, while gpd1L164P appeared to be epistatically suppressed by other alleles in the superior parent. The order of potency in reducing the glycerol/ethanol ratio of the three alleles was: gpd1L164P > hot1P107S,H274Y ≥ smp1R110Q,P269Q. Conclusions Our results show that natural yeast strains harbor multiple specific alleles of genes controlling essential functions, that are apparently compatible with survival in the natural environment. These newly identified alleles can be used as gene tools for engineering industrial yeast strains with multiple subtle changes, minimizing the risk of negatively affecting other essential functions. The gene tools act at the transcriptional, regulatory or structural gene level, distributing the impact over multiple targets and thus further minimizing possible side-effects. In addition, the results suggest polygenic analysis of complex traits as a promising new avenue to identify novel components involved in cellular functions, including those important in industrial applications. PMID:23759206

Genome-wide copy number variation analysis identified deletions in SFMBT1 associated with fasting plasma glucose in a Han Chinese population.

PubMed

Chung, Ren-Hua; Chiu, Yen-Feng; Hung, Yi-Jen; Lee, Wen-Jane; Wu, Kwan-Dun; Chen, Hui-Ling; Lin, Ming-Wei; Chen, Yii-Der I; Quertermous, Thomas; Hsiung, Chao A

2017-08-08

Fasting glucose and fasting insulin are glycemic traits closely related to diabetes, and understanding the role of genetic factors in these traits can help reveal the etiology of type 2 diabetes. Although single nucleotide polymorphisms (SNPs) in several candidate genes have been found to be associated with fasting glucose and fasting insulin, copy number variations (CNVs), which have been reported to be associated with several complex traits, have not been reported for association with these two traits. We aimed to identify CNVs associated with fasting glucose and fasting insulin. We conducted a genome-wide CNV association analysis for fasting plasma glucose (FPG) and fasting plasma insulin (FPI) using a family-based genome-wide association study sample from a Han Chinese population in Taiwan. A family-based CNV association test was developed in this study to identify common CNVs (i.e., CNVs with frequencies ≥ 5%), and a generalized estimating equation approach was used to test the associations between the traits and counts of global rare CNVs (i.e., CNVs with frequencies <5%). We found a significant genome-wide association for common deletions with a frequency of 5.2% in the Scm-like with four mbt domains 1 (SFMBT1) gene with FPG (association p-value = 2×10 -4 and an adjusted p-value = 0.0478 for multiple testing). No significant association was observed between global rare CNVs and FPG or FPI. The deletions in 20 individuals with DNA samples available were successfully validated using PCR-based amplification. The association of the deletions in SFMBT1 with FPG was further evaluated using an independent population-based replication sample obtained from the Taiwan Biobank. An association p-value of 0.065, which was close to the significance level of 0.05, for FPG was obtained by testing 9 individuals with CNVs in the SFMBT1 gene region and 11,692 individuals with normal copies in the replication cohort. Previous studies have found that SNPs in SFMBT1 are associated with blood pressure and serum urate concentration, suggesting that SFMBT1 may have functional implications in some metabolic-related traits.

Emerging applications of genome-editing technology to examine functionality of GWAS-associated variants for complex traits.

PubMed

Smith, Andrew J P; Deloukas, Panos; Munroe, Patricia B

2018-04-13

Over the last decade, genome-wide association studies (GWAS) have propelled the discovery of thousands of loci associated with complex diseases. The focus is now turning towards the function of these association signals, determining the causal variant(s) amongst those in strong linkage disequilibrium, and identifying their underlying mechanisms, such as long-range gene regulation. Genome-editing techniques utilising zinc-finger nucleases (ZFN), transcription activator-like effector nucleases (TALENs) and clustered regularly-interspaced short palindromic repeats with Cas9 nuclease (CRISPR-Cas9), are becoming the tools of choice to establish functionality for these variants, due to the ability to assess effects of single variants in vivo. This review will discuss examples of how these technologies have begun to aid functional analysis of GWAS loci for complex traits such as cardiovascular disease, type 2 diabetes, cancer, obesity and autoimmune disease. We focus on analysis of variants occurring within non-coding genomic regions, as these comprise the majority of GWAS variants, providing the greatest challenges to determining functionality, and compare editing strategies that provide different levels of evidence for variant functionality. The review describes molecular insights into some of these potentially causal variants, and how these may relate to the pathology of the trait, and look towards future directions for these technologies in post-GWAS analysis, such as base-editing.

Association of MAP4K4 gene single nucleotide polymorphism with mastitis and milk traits in Chinese Holstein cattle.

PubMed

Bhattarai, Dinesh; Chen, Xing; Ur Rehman, Zia; Hao, Xingjie; Ullah, Farman; Dad, Rahim; Talpur, Hira Sajjad; Kadariya, Ishwari; Cui, Lu; Fan, Mingxia; Zhang, Shujun

2017-02-01

The objective of the studies presented in this Research Communication was to investigate the association of single nucleotide polymorphisms present in the MAP4K4 gene with different milk traits in dairy cows. Based on previous QTL fine mapping results on bovine chromosome 11, the MAP4K4 gene was selected as a candidate gene to evaluate its effect on somatic cell count and milk traits in ChineseHolstein cows. Milk production traits including milk yield, fat percentage, and protein percentage of each cow were collected using 305 d lactation records. Association between MAP4K4 genotype and different traits and Somatic Cell Score (SCS) was performed using General Linear Regression Model of R. Two SNPs at exon 18 (c.2061T > G and c.2196T > C) with genotype TT in both SNPs were found significantly higher for somatic SCS. We found the significant effect of exon 18 (c.2061T > G) on protein percentage, milk yield and SCS. We identified SNPs at different location of MAP4K4 gene of the cattle and several of them were significantly associated with the somatic cell score and other different milk traits. Thus, MAP4K4 gene could be a useful candidate gene for selection of dairy cattle against mastitis and the identified polymorphisms might potentially be strong genetic markers.

Association between DRD2, 5-HTTLPR, and ALDH2 genes and specific personality traits in alcohol- and opiate-dependent patients.

PubMed

Wang, Tzu-Yun; Lee, Sheng-Yu; Chen, Shiou-Lan; Huang, San-Yuan; Chang, Yun-Hsuan; Tzeng, Nian-Sheng; Wang, Chen-Lin; Hui Lee, I; Yeh, Tzung Lieh; Yang, Yen Kuang; Lu, Ru-Band

2013-08-01

The vulnerability of developing addictions is associated with genetic factors and personality traits. The predisposing genetic variants and personality traits may be common to all addictions or specific to a particular class of addiction. To investigate the relationship between genetic variances, personality traits, and their interactions in addiction are important. We recruited 175 opiate-dependent patients, 102 alcohol-dependent patients, and 111 healthy controls. All participants were diagnosed using DSM-IV criteria and assessed with Tridimensional Personality Questionnaire (TPQ). The dopamine D2 receptor (DRD2), 5-HTT-linked promoter region (5-HTTLPR), and aldehyde dehydrogenase 2 (ALDH2) genes were genotyped using PCR. The genotype frequency of the 5-HTTLPR and ALDH2 was significantly different between the patients and controls (P=0.013, P<0.001, respectively), and borderline significant (P=0.05) for DRD2 polymorphism. Both Novelty Seeking (NS) and Harm Avoidance (HA) scores were higher for patients (P<0.001). After stratification by candidate genes, addicts with ALDH2 *1/*1 interacting with the low-functional group of DRD2 and 5-HTTLPR genes have higher HA traits, whereas addicts with ALDH2 *1/*2 or *2/*2 and low-functional group of DRD2 and 5-HTTLPR genes have higher NS traits. We concluded that addicts, both alcohol- and opiate-dependent patients, have common genetic variants in DRD2 and 5-HTTLPR but specific for ALDH2. Higher NS and HA traits were found in both patient groups with the interaction with DRD2, 5-HTTLPR, and ALDH2 genes. The ALDH2 gene variants had different effect in the NS and HA dimension while the DRD2 and 5-HTTLPR genes did not. Copyright © 2013 Elsevier B.V. All rights reserved.

Serotonin 1B Receptor Gene (HTR1B) Methylation as a Risk Factor for Callous-Unemotional Traits in Antisocial Boys.

PubMed

Moul, Caroline; Dobson-Stone, Carol; Brennan, John; Hawes, David J; Dadds, Mark R

2015-01-01

The serotonin system is thought to play a role in the aetiology of callous-unemotional (CU) traits in children. Previous research identified a functional single nucleotide polymorphism (SNP) from the promoter region of the serotonin 1B receptor gene as being associated with CU traits in boys with antisocial behaviour problems. This research tested the hypothesis that CU traits are associated with reduced methylation of the promoter region of the serotonin 1B receptor gene due to the influence of methylation on gene expression. Participants (N = 117) were boys with antisocial behaviour problems aged 3-16 years referred to University of New South Wales Child Behaviour Research Clinics. Participants volunteered a saliva sample from which the genotype of a SNP from the promoter region of the serotonin 1B receptor gene and the methylation levels of 30 CpG sites from 3 CpG regions surrounding the location of this polymorphism were assayed. Lower levels of serotonin 1B receptor gene methylation were associated with higher levels of CU traits. This relationship, however, was found to be moderated by genotype and carried exclusively by two CpG sites for which levels of methylation were negatively associated with overall methylation levels in this region of the gene. Results provide support to the emerging literature that argues for a genetically-driven system-wide alteration in serotonin function in the aetiology of CU traits. Furthermore, the results suggest that there may be two pathways to CU traits that involve methylation of the serotonin 1B receptor gene; one that is driven by a genotypic risk and another that is associated with risk for generally increased levels of methylation. Future research that aims to replicate and further investigate these results is required.

An intersection network based on combining SNP co-association and RNA co-expression networks for feed utilization traits in Japanese Black cattle.

PubMed

Okada, D; Endo, S; Matsuda, H; Ogawa, S; Taniguchi, Y; Katsuta, T; Watanabe, T; Iwaisaki, H

2018-05-12

Genome-wide association studies (GWAS) of quantitative traits have detected numerous genetic associations, but they encounter difficulties in pinpointing prominent candidate genes and inferring gene networks. The present study used a systems genetics approach integrating GWAS results with external RNA-expression data to detect candidate gene networks in feed utilization and growth traits of Japanese Black cattle, which are matters of concern. A SNP co-association network was derived from significant correlations between SNPs with effects estimated by GWAS across seven phenotypic traits. The resulting network genes contained significant numbers of annotations related to the traits. Using bovine transcriptome data from a public database, an RNA co-expression network was inferred based on the similarity of expression patterns across different tissues. An intersection network was then generated by superimposing the SNP and RNA networks and extracting shared interactions. This intersection network contained four tissue-specific modules: nervous system, reproductive system, muscular system, and glands. To characterize the structure (topographical properties) of the three networks, their scale-free properties were evaluated, which revealed that the intersection network was the most scale-free. In the sub-network containing the most connected transcription factors (URI1, ROCK2 and ETV6), most genes were widely expressed across tissues, and genes previously shown to be involved in the traits were found. Results indicated that the current approach might be used to construct a gene network that better reflects biological information, providing encouragement for the genetic dissection of economically important quantitative traits.

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

Genome-wide identification of allele-specific expression (ASE) in response to Marek's disease virus infection using next generation sequencing.

PubMed

Maceachern, Sean; Muir, William M; Crosby, Seth; Cheng, Hans H

2011-06-03

Marek's disease (MD), a T cell lymphoma induced by the highly oncogenic α-herpesvirus Marek's disease virus (MDV), is the main chronic infectious disease concern threatening the poultry industry. Enhancing genetic resistance to MD in commercial poultry is an attractive method to augment MD vaccines, which is currently the control method of choice. In order to optimally implement this control strategy through marker-assisted selection (MAS) and to gain biological information, it is necessary to identify specific genes that influence MD incidence. A genome-wide screen for allele-specific expression (ASE) in response to MDV infection was conducted. The highly inbred ADOL chicken lines 6 (MD resistant) and 7 (MD susceptible) were inter-mated in reciprocal crosses and half of the progeny challenged with MDV. Splenic RNA pools at a single time after infection for each treatment group point were generated, sequenced using a next generation sequencer, then analyzed for allele-specific expression (ASE). To validate and extend the results, Illumina GoldenGate assays for selected cSNPs were developed and used on all RNA samples from all 6 time points following MDV challenge. RNA sequencing resulted in 11-13+ million mappable reads per treatment group, 1.7+ Gb total sequence, and 22,655 high-confidence cSNPs. Analysis of these cSNPs revealed that 5360 cSNPs in 3773 genes exhibited statistically significant allelic imbalance. Of the 1536 GoldenGate assays, 1465 were successfully scored with all but 19 exhibiting evidence for allelic imbalance. ASE is an efficient method to identify potentially all or most of the genes influencing this complex trait. The identified cSNPs can be further evaluated in resource populations to determine their allelic direction and size of effect on genetic resistance to MD as well as being directly implemented in genomic selection programs. The described method, although demonstrated in inbred chicken lines, is applicable to all traits in any diploid species, and should prove to be a simple method to identify the majority of genes controlling any complex trait.

Breeding and Genetics Symposium: networks and pathways to guide genomic selection.

PubMed

Snelling, W M; Cushman, R A; Keele, J W; Maltecca, C; Thomas, M G; Fortes, M R S; Reverter, A

2013-02-01

Many traits affecting profitability and sustainability of meat, milk, and fiber production are polygenic, with no single gene having an overwhelming influence on observed variation. No knowledge of the specific genes controlling these traits has been needed to make substantial improvement through selection. Significant gains have been made through phenotypic selection enhanced by pedigree relationships and continually improving statistical methodology. Genomic selection, recently enabled by assays for dense SNP located throughout the genome, promises to increase selection accuracy and accelerate genetic improvement by emphasizing the SNP most strongly correlated to phenotype although the genes and sequence variants affecting phenotype remain largely unknown. These genomic predictions theoretically rely on linkage disequilibrium (LD) between genotyped SNP and unknown functional variants, but familial linkage may increase effectiveness when predicting individuals related to those in the training data. Genomic selection with functional SNP genotypes should be less reliant on LD patterns shared by training and target populations, possibly allowing robust prediction across unrelated populations. Although the specific variants causing polygenic variation may never be known with certainty, a number of tools and resources can be used to identify those most likely to affect phenotype. Associations of dense SNP genotypes with phenotype provide a 1-dimensional approach for identifying genes affecting specific traits; in contrast, associations with multiple traits allow defining networks of genes interacting to affect correlated traits. Such networks are especially compelling when corroborated by existing functional annotation and established molecular pathways. The SNP occurring within network genes, obtained from public databases or derived from genome and transcriptome sequences, may be classified according to expected effects on gene products. As illustrated by functionally informed genomic predictions being more accurate than naive whole-genome predictions of beef tenderness, coupling evidence from livestock genotypes, phenotypes, gene expression, and genomic variants with existing knowledge of gene functions and interactions may provide greater insight into the genes and genomic mechanisms affecting polygenic traits and facilitate functional genomic selection for economically important traits.

The Quantitative-MFG Test: A Linear Mixed Effect Model to Detect Maternal-Offspring Gene Interactions.

PubMed

Clark, Michelle M; Blangero, John; Dyer, Thomas D; Sobel, Eric M; Sinsheimer, Janet S

2016-01-01

Maternal-offspring gene interactions, aka maternal-fetal genotype (MFG) incompatibilities, are neglected in complex diseases and quantitative trait studies. They are implicated in birth to adult onset diseases but there are limited ways to investigate their influence on quantitative traits. We present the quantitative-MFG (QMFG) test, a linear mixed model where maternal and offspring genotypes are fixed effects and residual correlations between family members are random effects. The QMFG handles families of any size, common or general scenarios of MFG incompatibility, and additional covariates. We develop likelihood ratio tests (LRTs) and rapid score tests and show they provide correct inference. In addition, the LRT's alternative model provides unbiased parameter estimates. We show that testing the association of SNPs by fitting a standard model, which only considers the offspring genotypes, has very low power or can lead to incorrect conclusions. We also show that offspring genetic effects are missed if the MFG modeling assumptions are too restrictive. With genome-wide association study data from the San Antonio Family Heart Study, we demonstrate that the QMFG score test is an effective and rapid screening tool. The QMFG test therefore has important potential to identify pathways of complex diseases for which the genetic etiology remains to be discovered. © 2015 John Wiley & Sons Ltd/University College London.

XPAT: a toolkit to conduct cross-platform association studies with heterogeneous sequencing datasets.

PubMed

Yu, Yao; Hu, Hao; Bohlender, Ryan J; Hu, Fulan; Chen, Jiun-Sheng; Holt, Carson; Fowler, Jerry; Guthery, Stephen L; Scheet, Paul; Hildebrandt, Michelle A T; Yandell, Mark; Huff, Chad D

2018-04-06

High-throughput sequencing data are increasingly being made available to the research community for secondary analyses, providing new opportunities for large-scale association studies. However, heterogeneity in target capture and sequencing technologies often introduce strong technological stratification biases that overwhelm subtle signals of association in studies of complex traits. Here, we introduce the Cross-Platform Association Toolkit, XPAT, which provides a suite of tools designed to support and conduct large-scale association studies with heterogeneous sequencing datasets. XPAT includes tools to support cross-platform aware variant calling, quality control filtering, gene-based association testing and rare variant effect size estimation. To evaluate the performance of XPAT, we conducted case-control association studies for three diseases, including 783 breast cancer cases, 272 ovarian cancer cases, 205 Crohn disease cases and 3507 shared controls (including 1722 females) using sequencing data from multiple sources. XPAT greatly reduced Type I error inflation in the case-control analyses, while replicating many previously identified disease-gene associations. We also show that association tests conducted with XPAT using cross-platform data have comparable performance to tests using matched platform data. XPAT enables new association studies that combine existing sequencing datasets to identify genetic loci associated with common diseases and other complex traits.

Association of RUNX2 and TNFSF11 genes with production traits in a paternal broiler line.

PubMed

Grupioni, N V; Stafuzza, N B; Carvajal, A B; Ibelli, A M G; Peixoto, J O; Ledur, M C; Munari, D P

2017-03-22

Intense selection for production traits has improved the genetic gain of important economic traits. However, selection for performance and carcass traits has led to the onset of locomotors problems and decreasing bone strength in broilers. Thus, genes associated with bone integrity traits have become candidates for genetic studies in order to reduce the impact of bone disorders in broilers. This study investigated the association of the RUNX2 and TNFSF11 genes with 79 traits related to performance, carcass composition, organs, and bone integrity in a paternal broiler line. Analyses of genetic association between single-nucleotide polymorphisms (SNPs) and traits were carried out using the maximum likelihood procedures for mixed models. Genetic associations (P < 0.05) were found between SNP g.124,883A>G in the RUNX2 gene and chilled femur weight (additive plus dominance deviation effects within sex) and with performance traits (additive within sex and additive effects). The SNP g.14,862T>C in the TNFSF11 gene presented genetic associations (P < 0.05) with additive plus dominance deviation effects within sex for performance traits. Suggestive genetic associations (P < 0.10) were found with abdominal fat and its yield. Selection based on SNPs g.14,862T>C in TNFSF11 and g.124,883A>G in RUNX2 could be used to improve performance and carcass quality traits in the population studied, although SNP g.14,862T>C was not in Hardy-Weinberg equilibrium because it was not undergoing a selection process. Furthermore, it is important to validate these markers in an unrelated population for use in the selection process.

Towards systems genetic analyses in barley: Integration of phenotypic, expression and genotype data into GeneNetwork

PubMed Central

Druka, Arnis; Druka, Ilze; Centeno, Arthur G; Li, Hongqiang; Sun, Zhaohui; Thomas, William TB; Bonar, Nicola; Steffenson, Brian J; Ullrich, Steven E; Kleinhofs, Andris; Wise, Roger P; Close, Timothy J; Potokina, Elena; Luo, Zewei; Wagner, Carola; Schweizer, Günther F; Marshall, David F; Kearsey, Michael J; Williams, Robert W; Waugh, Robbie

2008-01-01

Background A typical genetical genomics experiment results in four separate data sets; genotype, gene expression, higher-order phenotypic data and metadata that describe the protocols, processing and the array platform. Used in concert, these data sets provide the opportunity to perform genetic analysis at a systems level. Their predictive power is largely determined by the gene expression dataset where tens of millions of data points can be generated using currently available mRNA profiling technologies. Such large, multidimensional data sets often have value beyond that extracted during their initial analysis and interpretation, particularly if conducted on widely distributed reference genetic materials. Besides quality and scale, access to the data is of primary importance as accessibility potentially allows the extraction of considerable added value from the same primary dataset by the wider research community. Although the number of genetical genomics experiments in different plant species is rapidly increasing, none to date has been presented in a form that allows quick and efficient on-line testing for possible associations between genes, loci and traits of interest by an entire research community. Description Using a reference population of 150 recombinant doubled haploid barley lines we generated novel phenotypic, mRNA abundance and SNP-based genotyping data sets, added them to a considerable volume of legacy trait data and entered them into the GeneNetwork . GeneNetwork is a unified on-line analytical environment that enables the user to test genetic hypotheses about how component traits, such as mRNA abundance, may interact to condition more complex biological phenotypes (higher-order traits). Here we describe these barley data sets and demonstrate some of the functionalities GeneNetwork provides as an easily accessible and integrated analytical environment for exploring them. Conclusion By integrating barley genotypic, phenotypic and mRNA abundance data sets directly within GeneNetwork's analytical environment we provide simple web access to the data for the research community. In this environment, a combination of correlation analysis and linkage mapping provides the potential to identify and substantiate gene targets for saturation mapping and positional cloning. By integrating datasets from an unsequenced crop plant (barley) in a database that has been designed for an animal model species (mouse) with a well established genome sequence, we prove the importance of the concept and practice of modular development and interoperability of software engineering for biological data sets. PMID:19017390

Can a few non‐coding mutations make a human brain?

PubMed Central

Franchini, Lucía F.

2015-01-01

The recent finding that the human version of a neurodevelopmental enhancer of the Wnt receptor Frizzled 8 (FZD8) gene alters neural progenitor cell cycle timing and brain size is a step forward to understanding human brain evolution. The human brain is distinctive in terms of its cognitive abilities as well as its susceptibility to neurological disease. Identifying which of the millions of genomic changes that occurred during human evolution led to these and other uniquely human traits is extremely challenging. Recent studies have demonstrated that many of the fastest evolving regions of the human genome function as gene regulatory enhancers during embryonic development and that the human‐specific mutations in them might alter expression patterns. However, elucidating molecular and cellular effects of sequence or expression pattern changes is a major obstacle to discovering the genetic bases of the evolution of our species. There is much work to do before human‐specific genetic and genomic changes are linked to complex human traits. Also watch the Video Abstract. PMID:26350501

Influence of early life exposure, host genetics and diet on the mouse gut microbiome and metabolome

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

Snijders, Antoine M.; Langley, Sasha A.; Kim, Young-Mo

Although the gut microbiome plays important roles in host physiology, health and disease1, we lack understanding of the complex interplay between host genetics and early life environment on the microbial and metabolic composition of the gut.We used the genetically diverse Collaborative Cross mouse system2 to discover that early life history impacts themicrobiome composition, whereas dietary changes have only a moderate effect. By contrast, the gut metabolome was shaped mostly by diet, with specific non-dietary metabolites explained by microbial metabolism. Quantitative trait analysis identified mouse genetic trait loci (QTL) that impact the abundances of specific microbes. Human orthologues of genes inmore » the mouse QTL are implicated in gastrointestinal cancer. Additionally, genes located in mouse QTL for Lactobacillales abundance are implicated in arthritis, rheumatic disease and diabetes. Furthermore, Lactobacillales abundance was predictive of higher host T-helper cell counts, suggesting an important link between Lactobacillales and host adaptive immunity.« less

Exome sequencing of extreme phenotypes identifies DCTN4 as a modifier of chronic Pseudomonas aeruginosa infection in cystic fibrosis.

PubMed

Emond, Mary J; Louie, Tin; Emerson, Julia; Zhao, Wei; Mathias, Rasika A; Knowles, Michael R; Wright, Fred A; Rieder, Mark J; Tabor, Holly K; Nickerson, Deborah A; Barnes, Kathleen C; Gibson, Ronald L; Bamshad, Michael J

2012-07-08

Exome sequencing has become a powerful and effective strategy for the discovery of genes underlying Mendelian disorders. However, use of exome sequencing to identify variants associated with complex traits has been more challenging, partly because the sample sizes needed for adequate power may be very large. One strategy to increase efficiency is to sequence individuals who are at both ends of a phenotype distribution (those with extreme phenotypes). Because the frequency of alleles that contribute to the trait are enriched in one or both phenotype extremes, a modest sample size can potentially be used to identify novel candidate genes and/or alleles. As part of the National Heart, Lung, and Blood Institute (NHLBI) Exome Sequencing Project (ESP), we used an extreme phenotype study design to discover that variants in DCTN4, encoding a dynactin protein, are associated with time to first P. aeruginosa airway infection, chronic P. aeruginosa infection and mucoid P. aeruginosa in individuals with cystic fibrosis.

Learned Vocal Variation Is Associated with Abrupt Cryptic Genetic Change in a Parrot Species Complex

PubMed Central

Ribot, Raoul F. H.; Buchanan, Katherine L.; Endler, John A.; Joseph, Leo; Bennett, Andrew T. D.; Berg, Mathew L.

2012-01-01

Contact zones between subspecies or closely related species offer valuable insights into speciation processes. A typical feature of such zones is the presence of clinal variation in multiple traits. The nature of these traits and the concordance among clines are expected to influence whether and how quickly speciation will proceed. Learned signals, such as vocalizations in species having vocal learning (e.g. humans, many birds, bats and cetaceans), can exhibit rapid change and may accelerate reproductive isolation between populations. Therefore, particularly strong concordance among clines in learned signals and population genetic structure may be expected, even among continuous populations in the early stages of speciation. However, empirical evidence for this pattern is often limited because differences in vocalisations between populations are driven by habitat differences or have evolved in allopatry. We tested for this pattern in a unique system where we may be able to separate effects of habitat and evolutionary history. We studied geographic variation in the vocalizations of the crimson rosella (Platycercus elegans) parrot species complex. Parrots are well known for their life-long vocal learning and cognitive abilities. We analysed contact calls across a ca 1300 km transect encompassing populations that differed in neutral genetic markers and plumage colour. We found steep clinal changes in two acoustic variables (fundamental frequency and peak frequency position). The positions of the two clines in vocal traits were concordant with a steep cline in microsatellite-based genetic variation, but were discordant with the steep clines in mtDNA, plumage and habitat. Our study provides new evidence that vocal variation, in a species with vocal learning, can coincide with areas of restricted gene flow across geographically continuous populations. Our results suggest that traits that evolve culturally can be strongly associated with reduced gene flow between populations, and therefore may promote speciation, even in the absence of other barriers. PMID:23227179

Associations between variants of the HAL gene and milk production traits in Chinese Holstein cows.

PubMed

Wang, Haifei; Jiang, Li; Wang, Wenwen; Zhang, Shengli; Yin, Zongjun; Zhang, Qin; Liu, Jian-Feng

2014-11-25

The histidine ammonia-lyse gene (HAL) encodes the histidine ammonia-lyase, which catalyzes the first reaction of histidine catabolism. In our previous genome-wide association study in Chinese Holstein cows to identify genetic variants affecting milk production traits, a SNP (rs41647754) located 357 bp upstream of HAL, was found to be significantly associated with milk yield and milk protein yield. In addition, the HAL gene resides within the reported QTLs for milk production traits. The aims of this study were to identify genetic variants in HAL and to test the association between these variants and milk production traits. Fifteen SNPs were identified within the regions under study of the HAL gene, including three coding mutations, seven intronic mutations, one promoter region mutation, and four 3'UTR mutations. Nine of these identified SNPs were chosen for subsequent genotyping and association analyses. Our results showed that five SNP markers (ss974768522, ss974768525, ss974768531, ss974768533 and ss974768534) were significantly associated with one or more milk production traits. Haplotype analysis showed that two haplotype blocks were significantly associated with milk yield and milk protein yield, providing additional support for the association between HAL variants and milk production traits in dairy cows (P < 0.05). Our study shows evidence of significant associations between SNPs within the HAL gene and milk production traits in Chinese Holstein cows, indicating the potential role of HAL variants in these traits. These identified SNPs may serve as genetic markers used in genomic selection schemes to accelerate the genetic gains of milk production traits in dairy cattle.

The genetic regulatory network centered on Pto-Wuschela and its targets involved in wood formation revealed by association studies.

PubMed

Yang, Xiaohui; Wei, Zunzheng; Du, Qingzhang; Chen, Jinhui; Wang, Qingshi; Quan, Mingyang; Song, Yuepeng; Xie, Jianbo; Zhang, Deqiang

2015-11-09

Transcription factors (TFs) regulate gene expression and can strongly affect phenotypes. However, few studies have examined TF variants and TF interactions with their targets in plants. Here, we used genetic association in 435 unrelated individuals of Populus tomentosa to explore the variants in Pto-Wuschela and its targets to decipher the genetic regulatory network of Pto-Wuschela. Our bioinformatics and co-expression analysis identified 53 genes with the motif TCACGTGA as putative targets of Pto-Wuschela. Single-marker association analysis showed that Pto-Wuschela was associated with wood properties, which is in agreement with the observation that it has higher expression in stem vascular tissues in Populus. Also, SNPs in the 53 targets were associated with growth or wood properties under additive or dominance effects, suggesting these genes and Pto-Wuschela may act in the same genetic pathways that affect variation in these quantitative traits. Epistasis analysis indicated that 75.5% of these genes directly or indirectly interacted Pto-Wuschela, revealing the coordinated genetic regulatory network formed by Pto-Wuschela and its targets. Thus, our study provides an alternative method for dissection of the interactions between a TF and its targets, which will strength our understanding of the regulatory roles of TFs in complex traits in plants.

CYTOKINE GENE VARIATIONS ASSOCIATED WITH TRAIT AND STATE ANXIETY IN ONCOLOGY PATIENTS AND THEIR FAMILY CAREGIVERS

PubMed Central

Miaskowski, Christine; Cataldo, Janine K.; Baggott, Christina R.; West, Claudia; Dunn, Laura B.; Dhruva, Anand; Merriman, John D.; Langford, Dale J.; Kober, Kord M.; Paul, Steven M.; Cooper, Bruce A.; Aouizerat, Bradley E.

2017-01-01

Purpose Anxiety is common among cancer patients and their family caregivers (FCs) and is associated with poorer outcomes. Recently, associations between inflammation and anxiety were identified. However, the relationship between variations in cytokine genes and anxiety warrants investigation. Therefore, phenotypic and genotypic characteristics associated with trait and state anxiety were evaluated in a sample of 167 oncology patients with breast, prostate, lung, or brain cancer and 85 of their FCs. Methods Using multiple regression analyses, the associations between participants’ demographic and clinical characteristics, as well as variations in cytokine genes and trait and state anxiety were evaluated. Results In the bivariate analyses, a number of phenotypic characteristics were associated with both trait and state anxiety (e.g., age, functional status). However, some associations were specific only to trait anxiety (e.g., number of comorbid conditions) or state anxiety (e.g., participation with a FC). Variations in three cytokine genes (i.e., interleukin (IL) 1 beta, IL1 receptor 2 (IL1R2), nuclear factor kappa beta 2 (NFKB2)) were associated with trait anxiety and variations in two genes (i.e., IL1R2, tumor necrosis factor alpha (TNFA)) were associated with state anxiety. Conclusions These findings suggest that both trait and state anxiety need to be assessed in oncology patients and their FCs. Furthermore, variations in cytokine genes may contribute to higher levels of anxiety in oncology patients and their FCs. PMID:25249351

Using genetic markers to orient the edges in quantitative trait networks: the NEO software.

PubMed

Aten, Jason E; Fuller, Tova F; Lusis, Aldons J; Horvath, Steve

2008-04-15

Systems genetic studies have been used to identify genetic loci that affect transcript abundances and clinical traits such as body weight. The pairwise correlations between gene expression traits and/or clinical traits can be used to define undirected trait networks. Several authors have argued that genetic markers (e.g expression quantitative trait loci, eQTLs) can serve as causal anchors for orienting the edges of a trait network. The availability of hundreds of thousands of genetic markers poses new challenges: how to relate (anchor) traits to multiple genetic markers, how to score the genetic evidence in favor of an edge orientation, and how to weigh the information from multiple markers. We develop and implement Network Edge Orienting (NEO) methods and software that address the challenges of inferring unconfounded and directed gene networks from microarray-derived gene expression data by integrating mRNA levels with genetic marker data and Structural Equation Model (SEM) comparisons. The NEO software implements several manual and automatic methods for incorporating genetic information to anchor traits. The networks are oriented by considering each edge separately, thus reducing error propagation. To summarize the genetic evidence in favor of a given edge orientation, we propose Local SEM-based Edge Orienting (LEO) scores that compare the fit of several competing causal graphs. SEM fitting indices allow the user to assess local and overall model fit. The NEO software allows the user to carry out a robustness analysis with regard to genetic marker selection. We demonstrate the utility of NEO by recovering known causal relationships in the sterol homeostasis pathway using liver gene expression data from an F2 mouse cross. Further, we use NEO to study the relationship between a disease gene and a biologically important gene co-expression module in liver tissue. The NEO software can be used to orient the edges of gene co-expression networks or quantitative trait networks if the edges can be anchored to genetic marker data. R software tutorials, data, and supplementary material can be downloaded from: http://www.genetics.ucla.edu/labs/horvath/aten/NEO.

Discovery of single nucleotide polymorphisms in candidate genes associated with fertility and production traits in Holstein cattle

PubMed Central

2013-01-01

Background Identification of single nucleotide polymorphisms (SNPs) for specific genes involved in reproduction might improve reliability of genomic estimates for these low-heritability traits. Semen from 550 Holstein bulls of high (≥ 1.7; n = 288) or low (≤ −2; n = 262) daughter pregnancy rate (DPR) was genotyped for 434 candidate SNPs using the Sequenom MassARRAY® system. Three types of SNPs were evaluated: SNPs previously reported to be associated with reproductive traits or physically close to genetic markers for reproduction, SNPs in genes that are well known to be involved in reproductive processes, and SNPs in genes that are differentially expressed between physiological conditions in a variety of tissues associated in reproductive function. Eleven reproduction and production traits were analyzed. Results A total of 40 SNPs were associated (P < 0.05) with DPR. Among these were genes involved in the endocrine system, cell signaling, immune function and inhibition of apoptosis. A total of 10 genes were regulated by estradiol. In addition, 22 SNPs were associated with heifer conception rate, 33 with cow conception rate, 36 with productive life, 34 with net merit, 23 with milk yield, 19 with fat yield, 13 with fat percent, 19 with protein yield, 22 with protein percent, and 13 with somatic cell score. The allele substitution effect for SNPs associated with heifer conception rate, cow conception rate, productive life and net merit were in the same direction as for DPR. Allele substitution effects for several SNPs associated with production traits were in the opposite direction as DPR. Nonetheless, there were 29 SNPs associated with DPR that were not negatively associated with production traits. Conclusion SNPs in a total of 40 genes associated with DPR were identified as well as SNPs for other traits. It might be feasible to include these SNPs into genomic tests of reproduction and other traits. The genes associated with DPR are likely to be important for understanding the physiology of reproduction. Given the large number of SNPs associated with DPR that were not negatively associated with production traits, it should be possible to select for DPR without compromising production. PMID:23759029

Identification and fine mapping of a stay-green gene (Brnye1) in pakchoi (Brassica campestris L. ssp. chinensis).

PubMed

Wang, Nan; Liu, Zhiyong; Zhang, Yun; Li, Chengyu; Feng, Hui

2018-03-01

Using bulked segregant analysis combined with next-generation sequencing, we delimited the Brnye1 gene responsible for the stay-green trait of nye in pakchoi. Sequence analysis identified Bra019346 as the candidate gene. "Stay-green" refers to a plant trait whereby leaves remain green during senescence. This trait is useful in the cultivation of pakchoi (Brassica campestris L. ssp. chinensis), which is marketed as a green leaf product. This study aimed to identify the gene responsible for the stay-green trait in pakchoi. We identified a stay-green mutant in pakchoi, which we termed "nye". Genetic analysis revealed that the stay-green trait is controlled by a single recessive gene, Brnye1. Using the BSA-seq method, a 3.0-Mb candidate region was mapped on chromosome A03, which helped us localize Brnye1 to an 81.01-kb interval between SSR markers SSRWN27 and SSRWN30 via linkage analysis in an F 2 population. We identified 12 genes in this region, 11 of which were annotated based on the Brassica rapa annotation database, and one was a functionally unknown gene. An orthologous gene of the Arabidopsis gene AtNYE1, Bra019346, was identified as the potential candidate for Brnye1. Sequence analysis revealed a 40-bp insertion in the second exon of Bra019346 in nye, which generated the TAA stop codon. A candidate gene-specific Indel marker in 1561 F 2 individuals showed perfect cosegregation with Brnye1 in the nye mutant. These results provide a foundation for uncovering the molecular mechanism of the stay-green trait in pakchoi.

Expression profiles and associations of muscle regulatory factor (MRF) genes with growth traits in Tibetan chickens.

PubMed

Zhang, R; Li, R; Zhi, L; Xu, Y; Lin, Y; Chen, L

2018-02-01

1. Muscle regulatory factors (MRFs), including Myf5, Myf6 (MRF4/herculin), MyoD and MyoG (myogenin), play pivotal roles in muscle growth and development. Therefore, they are considered as candidate genes for meat production traits in livestock and poultry. 2. The objective of this study was to investigate the expression profiles of these genes in skeletal muscles (breast muscle and thigh muscle) at 5 developmental stages (0, 81, 119, 154 and 210 d old) of Tibetan chickens. Relationships between expressions of these genes and growth and carcass traits in these chickens were also estimated. 3. The expression profiles showed that in the breast muscle of both genders the mRNA levels of MRF genes were highest on the day of hatching, then declined significantly from d 0 to d 81, and fluctuated in a certain range from d 81 to d 210. However, the expression of Myf5, Myf6 and MyoG reached peaks in the thigh muscle in 118-d-old females and for MyoD in 154-d-old females, whereas the mRNA amounts of MRF genes in the male thigh muscle were in a narrow range from d 0 to d 210. 4. Correlation analysis suggested that gender had an influence on the relationships of MRF gene expression with growth traits. The RNA levels of MyoD, Myf5 genes in male breast muscle were positively related with several growth traits of Tibetan chickens (P < 0.05). No correlation was found between expressions of MRF genes and carcass traits of the chickens. 5. These results will provide a base for functional studies of MRF genes on growth and development of Tibetan chickens, as well as selective breeding and resource exploration.

How well do plant hydraulic traits predict species’ distributions across the world

USDA-ARS?s Scientific Manuscript database

Climate–trait associations are becoming ever-more important as plant breeding and gene modification efforts enable the targeting of specific traits and specific genes. It is well-understood that climate represents a constraint to the evolution of plant species. Although this statement is intuitive...

Computational identification of a new SelD-like family that may participate in sulfur metabolism in hyperthermophilic sulfur-reducing archaea.

PubMed

Li, Gao-Peng; Jiang, Liang; Ni, Jia-Zuan; Liu, Qiong; Zhang, Yan

2014-10-17

Selenium (Se) and sulfur (S) are closely related elements that exhibit similar chemical properties. Some genes related to S metabolism are also involved in Se utilization in many organisms. However, the evolutionary relationship between the two utilization traits is unclear. In this study, we conducted a comparative analysis of the selenophosphate synthetase (SelD) family, a key protein for all known Se utilization traits, in all sequenced archaea. Our search showed a very limited distribution of SelD and Se utilization in this kingdom. Interestingly, a SelD-like protein was detected in two orders of Crenarchaeota: Sulfolobales and Thermoproteales. Sequence and phylogenetic analyses revealed that SelD-like protein contains the same domain and conserved functional residues as those of SelD, and might be involved in S metabolism in these S-reducing organisms. Further genome-wide analysis of patterns of gene occurrence in different thermoproteales suggested that several genes, including SirA-like, Prx-like and adenylylsulfate reductase, were strongly related to SelD-like gene. Based on these findings, we proposed a simple model wherein SelD-like may play an important role in the biosynthesis of certain thiophosphate compound. Our data suggest novel genes involved in S metabolism in hyperthermophilic S-reducing archaea, and may provide a new window for understanding the complex relationship between Se and S metabolism in archaea.

Multilocus patterns of nucleotide diversity and divergence reveal positive selection at candidate genes related to cold hardiness in coastal Douglas Fir (Pseudotsuga menziesii var. menziesii).

PubMed

Eckert, Andrew J; Wegrzyn, Jill L; Pande, Barnaly; Jermstad, Kathleen D; Lee, Jennifer M; Liechty, John D; Tearse, Brandon R; Krutovsky, Konstantin V; Neale, David B

2009-09-01

Forest trees exhibit remarkable adaptations to their environments. The genetic basis for phenotypic adaptation to climatic gradients has been established through a long history of common garden, provenance, and genecological studies. The identities of genes underlying these traits, however, have remained elusive and thus so have the patterns of adaptive molecular diversity in forest tree genomes. Here, we report an analysis of diversity and divergence for a set of 121 cold-hardiness candidate genes in coastal Douglas fir (Pseudotsuga menziesii var. menziesii). Application of several different tests for neutrality, including those that incorporated demographic models, revealed signatures of selection consistent with selective sweeps at three to eight loci, depending upon the severity of a bottleneck event and the method used to detect selection. Given the high levels of recombination, these candidate genes are likely to be closely linked to the target of selection if not the genes themselves. Putative homologs in Arabidopsis act primarily to stabilize the plasma membrane and protect against denaturation of proteins at freezing temperatures. These results indicate that surveys of nucleotide diversity and divergence, when framed within the context of further association mapping experiments, will come full circle with respect to their utility in the dissection of complex phenotypic traits into their genetic components.

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

Dissection of additive, dominance, and imprinting effects for production and reproduction traits in Holstein cattle.

PubMed

Jiang, Jicai; Shen, Botong; O'Connell, Jeffrey R; VanRaden, Paul M; Cole, John B; Ma, Li

2017-05-30

Although genome-wide association and genomic selection studies have primarily focused on additive effects, dominance and imprinting effects play an important role in mammalian biology and development. The degree to which these non-additive genetic effects contribute to phenotypic variation and whether QTL acting in a non-additive manner can be detected in genetic association studies remain controversial. To empirically answer these questions, we analyzed a large cattle dataset that consisted of 42,701 genotyped Holstein cows with genotyped parents and phenotypic records for eight production and reproduction traits. SNP genotypes were phased in pedigree to determine the parent-of-origin of alleles, and a three-component GREML was applied to obtain variance decomposition for additive, dominance, and imprinting effects. The results showed a significant non-zero contribution from dominance to production traits but not to reproduction traits. Imprinting effects significantly contributed to both production and reproduction traits. Interestingly, imprinting effects contributed more to reproduction traits than to production traits. Using GWAS and imputation-based fine-mapping analyses, we identified and validated a dominance association signal with milk yield near RUNX2, a candidate gene that has been associated with milk production in mice. When adding non-additive effects into the prediction models, however, we observed little or no increase in prediction accuracy for the eight traits analyzed. Collectively, our results suggested that non-additive effects contributed a non-negligible amount (more for reproduction traits) to the total genetic variance of complex traits in cattle, and detection of QTLs with non-additive effect is possible in GWAS using a large dataset.

The multiscale backbone of the human phenotype network based on biological pathways.

PubMed

Darabos, Christian; White, Marquitta J; Graham, Britney E; Leung, Derek N; Williams, Scott M; Moore, Jason H

2014-01-25

Networks are commonly used to represent and analyze large and complex systems of interacting elements. In systems biology, human disease networks show interactions between disorders sharing common genetic background. We built pathway-based human phenotype network (PHPN) of over 800 physical attributes, diseases, and behavioral traits; based on about 2,300 genes and 1,200 biological pathways. Using GWAS phenotype-to-genes associations, and pathway data from Reactome, we connect human traits based on the common patterns of human biological pathways, detecting more pleiotropic effects, and expanding previous studies from a gene-centric approach to that of shared cell-processes. The resulting network has a heavily right-skewed degree distribution, placing it in the scale-free region of the network topologies spectrum. We extract the multi-scale information backbone of the PHPN based on the local densities of the network and discarding weak connection. Using a standard community detection algorithm, we construct phenotype modules of similar traits without applying expert biological knowledge. These modules can be assimilated to the disease classes. However, we are able to classify phenotypes according to shared biology, and not arbitrary disease classes. We present examples of expected clinical connections identified by PHPN as proof of principle. We unveil a previously uncharacterized connection between phenotype modules and discuss potential mechanistic connections that are obvious only in retrospect. The PHPN shows tremendous potential to become a useful tool both in the unveiling of the diseases' common biology, and in the elaboration of diagnosis and treatments.

Natural variations in OsγTMT contribute to diversity of the α-tocopherol content in rice.

PubMed

Wang, Xiao-Qiang; Yoon, Min-Young; He, Qiang; Kim, Tae-Sung; Tong, Wei; Choi, Bu-Woong; Lee, Young-Sang; Park, Yong-Jin

2015-12-01

Tocopherols and tocotrienols, collectively known as tocochromanols, are lipid-soluble molecules that belong to the group of vitamin E compounds. Among them, α-tocopherol (αΤ) is one of the antioxidants with diverse functions and benefits for humans and animals. Thus, understanding the genetic basis of these traits would be valuable to improve nutritional quality by breeding in rice. Genome-wide association study (GWAS) has emerged as a powerful strategy for identifying genes or quantitative trait loci (QTL) underlying complex traits in plants. To discover the genes or QTLs underlying the naturally occurring variations of αΤ content in rice, we performed GWAS using 1.44 million high-quality single-nucleotide polymorphisms acquired from re-sequencing of 137 accessions from a diverse rice core collection. Thirteen candidate genes were found across 2-year phenotypic data, among which gamma-tocopherol methyltransferase (OsγTMT) was identified as the major factor responsible for the αΤ content among rice accessions. Nucleotide variations in the coding region of OsγTMT were significantly associated with the αΤ content variations, while nucleotide polymorphisms in the promoter region of OsγTMT also could partly demonstrate the correlation with αΤ content variations, according to our RNA expression analyses. This study provides useful information for genetic factors underlying αΤ content variations in rice, which will significantly contribute the research on αΤ biosynthesis mechanisms and αΤ improvement of rice.

Genome-wide association study to identify candidate loci and genes for Mn toxicity tolerance in rice

PubMed Central

Shrestha, Asis; Dziwornu, Ambrose Kwaku; Ueda, Yoshiaki; Wu, Lin-Bo; Mathew, Boby

2018-01-01

Manganese (Mn) is an essential micro-nutrient for plants, but flooded rice fields can accumulate high levels of Mn2+ leading to Mn toxicity. Here, we present a genome-wide association study (GWAS) to identify candidate loci conferring Mn toxicity tolerance in rice (Oryza sativa L.). A diversity panel of 288 genotypes was grown in hydroponic solutions in a greenhouse under optimal and toxic Mn concentrations. We applied a Mn toxicity treatment (5 ppm Mn2+, 3 weeks) at twelve days after transplanting. Mn toxicity caused moderate damage in rice in terms of biomass loss and symptom formation despite extremely high shoot Mn concentrations ranging from 2.4 to 17.4 mg g-1. The tropical japonica subpopulation was more sensitive to Mn toxicity than other subpopulations. Leaf damage symptoms were significantly correlated with Mn uptake into shoots. Association mapping was conducted for seven traits using 416741 single nucleotide polymorphism (SNP) markers using a mixed linear model, and detected six significant associations for the traits shoot manganese concentration and relative shoot length. Candidate regions contained genes coding for a heavy metal transporter, peroxidase precursor and Mn2+ ion binding proteins. The significant marker SNP-2.22465867 caused an amino acid change in a gene (LOC_Os02g37170) with unknown function. This study demonstrated significant natural variation in rice for Mn toxicity tolerance and the possibility of using GWAS to unravel genetic factors responsible for such complex traits. PMID:29425206

Genome-wide association study to identify candidate loci and genes for Mn toxicity tolerance in rice.

PubMed

Shrestha, Asis; Dziwornu, Ambrose Kwaku; Ueda, Yoshiaki; Wu, Lin-Bo; Mathew, Boby; Frei, Michael

2018-01-01

Manganese (Mn) is an essential micro-nutrient for plants, but flooded rice fields can accumulate high levels of Mn2+ leading to Mn toxicity. Here, we present a genome-wide association study (GWAS) to identify candidate loci conferring Mn toxicity tolerance in rice (Oryza sativa L.). A diversity panel of 288 genotypes was grown in hydroponic solutions in a greenhouse under optimal and toxic Mn concentrations. We applied a Mn toxicity treatment (5 ppm Mn2+, 3 weeks) at twelve days after transplanting. Mn toxicity caused moderate damage in rice in terms of biomass loss and symptom formation despite extremely high shoot Mn concentrations ranging from 2.4 to 17.4 mg g-1. The tropical japonica subpopulation was more sensitive to Mn toxicity than other subpopulations. Leaf damage symptoms were significantly correlated with Mn uptake into shoots. Association mapping was conducted for seven traits using 416741 single nucleotide polymorphism (SNP) markers using a mixed linear model, and detected six significant associations for the traits shoot manganese concentration and relative shoot length. Candidate regions contained genes coding for a heavy metal transporter, peroxidase precursor and Mn2+ ion binding proteins. The significant marker SNP-2.22465867 caused an amino acid change in a gene (LOC_Os02g37170) with unknown function. This study demonstrated significant natural variation in rice for Mn toxicity tolerance and the possibility of using GWAS to unravel genetic factors responsible for such complex traits.

Characterization of phenylpropanoid pathway genes within European maize (Zea mays L.) inbreds

PubMed Central

Andersen, Jeppe Reitan; Zein, Imad; Wenzel, Gerhard; Darnhofer, Birte; Eder, Joachim; Ouzunova, Milena; Lübberstedt, Thomas

2008-01-01

Background Forage quality of maize is influenced by both the content and structure of lignins in the cell wall. Biosynthesis of monolignols, constituting the complex structure of lignins, is catalyzed by enzymes in the phenylpropanoid pathway. Results In the present study we have amplified partial genomic fragments of six putative phenylpropanoid pathway genes in a panel of elite European inbred lines of maize (Zea mays L.) contrasting in forage quality traits. Six loci, encoding C4H, 4CL1, 4CL2, C3H, F5H, and CAD, displayed different levels of nucleotide diversity and linkage disequilibrium (LD) possibly reflecting different levels of selection. Associations with forage quality traits were identified for several individual polymorphisms within the 4CL1, C3H, and F5H genomic fragments when controlling for both overall population structure and relative kinship. A 1-bp indel in 4CL1 was associated with in vitro digestibility of organic matter (IVDOM), a non-synonymous SNP in C3H was associated with IVDOM, and an intron SNP in F5H was associated with neutral detergent fiber. However, the C3H and F5H associations did not remain significant when controlling for multiple testing. Conclusion While the number of lines included in this study limit the power of the association analysis, our results imply that genetic variation for forage quality traits can be mined in phenylpropanoid pathway genes of elite breeding lines of maize. PMID:18173847

Genome-Wide Sequence Variation Identification and Floral-Associated Trait Comparisons Based on the Re-sequencing of the ‘Nagafu No. 2’ and ‘Qinguan’ Varieties of Apple (Malus domestica Borkh.)

PubMed Central

Xing, Libo; Zhang, Dong; Song, Xiaomin; Weng, Kai; Shen, Yawen; Li, Youmei; Zhao, Caiping; Ma, Juanjuan; An, Na; Han, Mingyu

2016-01-01

Apple (Malus domestica Borkh.) is a commercially important fruit worldwide. Detailed information on genomic DNA polymorphisms, which are important for understanding phenotypic traits, is lacking for the apple. We re-sequenced two elite apple varieties, ‘Nagafu No. 2’ and ‘Qinguan,’ which have different characteristics. We identified many genomic variations, including 2,771,129 single nucleotide polymorphisms (SNPs), 82,663 structural variations (SVs), and 1,572,803 insertion/deletions (INDELs) in ‘Nagafu No. 2’ and 2,262,888 SNPs, 63,764 SVs, and 1,294,060 INDELs in ‘Qinguan.’ The ‘SNP,’ ‘INDEL,’ and ‘SV’ distributions were non-random, with variation-rich or -poor regions throughout the genomes. In ‘Nagafu No. 2’ and ‘Qinguan’ there were 171,520 and 147,090 non-synonymous SNPs spanning 23,111 and 21,400 genes, respectively; 3,963 and 3,196 SVs in 3,431 and 2,815 genes, respectively; and 1,834 and 1,451 INDELs in 1,681 and 1,345 genes, respectively. Genetic linkage maps of 190 flowering genes associated with multiple flowering pathways in ‘Nagafu No. 2,’ ‘Qinguan,’ and ‘Golden Delicious,’ identified complex regulatory mechanisms involved in floral induction, flower bud formation, and flowering characteristics, which might reflect the genetic variation of the flowering genes. Expression profiling of key flowering genes in buds and leaves suggested that the photoperiod and autonomous flowering pathways are major contributors to the different floral-associated traits between ‘Nagafu No. 2’ and ‘Qinguan.’ The genome variation data provided a foundation for the further exploration of apple diversity and gene–phenotype relationships, and for future research on molecular breeding to improve apple and related species. PMID:27446138

Alcohol-related Genes Show an Enrichment of Associations with a Persistent Externalizing Factor

PubMed Central

Ashenhurst, James R.; Harden, K. Paige; Corbin, William R.; Fromme, Kim

2016-01-01

Research using twins has found that much of the variability in externalizing phenotypes – including alcohol and drug use, impulsive personality traits, risky sex and property crime – is explained by genetic factors. Nevertheless, identification of specific genes and variants associated with these traits has proven to be difficult, likely because individual differences in externalizing are explained by many genes of small individual effect. Moreover, twin research indicates that heritable variance in externalizing behaviors is mostly shared across the externalizing spectrum rather than specific to any behavior. We use a longitudinal, “deep phenotyping” approach to model a general externalizing factor reflecting persistent engagement in a variety of socially problematic behaviors measured at eleven assessment occasions spanning early adulthood (ages 18 to 28). In an ancestrally homogenous sample of non-Hispanic Whites (N = 337), we then tested for enrichment of associations between the persistent externalizing factor and a set of 3,281 polymorphisms within 104 genes that were previously identified as associated with alcohol-use behaviors. Next we tested for enrichment among domain-specific factors (e.g., property crime) composed of residual variance not accounted for by the common factor. Significance was determined relative to bootstrapped empirical thresholds derived from permutations of phenotypic data. Results indicated significant enrichment of genetic associations for persistent externalizing, but not for domain-specific factors. Consistent with twin research findings, these results suggest that genetic variants are broadly associated with externalizing behaviors rather than unique to specific behaviors. General Scientific Summary This study shows that variation in 104 genes is associated with socially problematic “externalizing” behavior, including substance misuse, property crime, risky sex, and aspects of impulsive personality. Importantly, this association was with the common variation across these behaviors rather than with the variation unique to any given behavior. The manuscript demonstrates a potentially advantageous technique for relating sets of hypothesized genes to complex traits or behaviors. PMID:27505405

Candidate Gene Identification of Feed Efficiency and Coat Color Traits in a C57BL/6J × Kunming F2 Mice Population Using Genome-Wide Association Study.

PubMed

Miao, Yuanxin; Soudy, Fathia; Xu, Zhong; Liao, Mingxing; Zhao, Shuhong; Li, Xinyun

2017-01-01

Feed efficiency (FE) is a very important trait in livestock industry. Identification of the candidate genes could be of benefit for the improvement of FE trait. Mouse is used as the model for many studies in mammals. In this study, the candidate genes related to FE and coat color were identified using C57BL/6J (C57) × Kunming (KM) F2 mouse population. GWAS results showed that 61 and 2 SNPs were genome-wise suggestive significantly associated with feed conversion ratio (FCR) and feed intake (FI) traits, respectively. Moreover, the Erbin, Msrb2, Ptf1a, and Fgf10 were considered as the candidate genes of FE. The Lpl was considered as the candidate gene of FI. Further, the coat color trait was studied. KM mice are white and C57 ones are black. The GWAS results showed that the most significant SNP was located at chromosome 7, and the closely linked gene was Tyr. Therefore, our study offered useful target genes related to FE in mice; these genes may play similar roles in FE of livestock. Also, we identified the major gene of coat color in mice, which would be useful for better understanding of natural mutation of the coat color in mice.

Pathogenic variants for Mendelian and complex traits in exomes of 6,517 European and African Americans: implications for the return of incidental results.

PubMed

Tabor, Holly K; Auer, Paul L; Jamal, Seema M; Chong, Jessica X; Yu, Joon-Ho; Gordon, Adam S; Graubert, Timothy A; O'Donnell, Christopher J; Rich, Stephen S; Nickerson, Deborah A; Bamshad, Michael J

2014-08-07

Exome sequencing (ES) is rapidly being deployed for use in clinical settings despite limited empirical data about the number and types of incidental results (with potential clinical utility) that could be offered for return to an individual. We analyzed deidentified ES data from 6,517 participants (2,204 African Americans and 4,313 European Americans) from the National Heart, Lung, and Blood Institute Exome Sequencing Project. We characterized the frequencies of pathogenic alleles in genes underlying Mendelian conditions commonly assessed by newborn-screening (NBS, n = 39) programs, genes associated with age-related macular degeneration (ARMD, n = 17), and genes known to influence drug response (PGx, n = 14). From these 70 genes, we identified 10,789 variants and curated them by manual review of OMIM, HGMD, locus-specific databases, or primary literature to a total of 399 validated pathogenic variants. The mean number of risk alleles per individual was 15.3. Every individual had at least five known PGx alleles, 99% of individuals had at least one ARMD risk allele, and 45% of individuals were carriers for at least one pathogenic NBS allele. The carrier burden for severe recessive childhood disorders was 0.57. Our results demonstrate that risk alleles of potential clinical utility for both Mendelian and complex traits are detectable in every individual. These findings highlight the necessity of developing guidelines and policies that consider the return of results to all individuals and underscore the need to develop innovative approaches and tools that enable individuals to exercise their choice about the return of incidental results. Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Sexual selection and the evolution of genital shape and complexity in water striders.

PubMed

Rowe, Locke; Arnqvist, Göran

2012-01-01

Animal genitalia show two striking but incompletely understood evolutionary trends: a great evolutionary divergence in the shape of genitalic structures, and characteristic structural complexity. Both features are thought to result from sexual selection, but explicit comparative tests are hampered by the fact that it is difficult to quantify both morphological complexity and divergence in shape. We undertake a comparative study of multiple nongenitalic and male genital traits in a clade of 15 water strider species to quantify complexity and shape divergence. We show that genital structures are more complex and their shape more divergent among species than nongenital traits. Further, intromittent genital traits are more complex and have evolved more divergently than nonintromittent genital traits. More importantly, shape and complexity of nonintromittent genital traits show correlated evolution with indices of premating sexual selection and intromittent genital traits with postmating sexual selection, suggesting that the evolution of different components of genital morphology are shaped independently by distinct forms of sexual selection. Our quantitative results provide direct comparative support for the hypothesis that sexual selection is associated with morphological complexity in genitalic traits and highlight the importance of quantifying morphological shape and complexity, rather than size in studies of genital evolution. © 2011 The Author(s). Evolution © 2011 The Society for the Study of Evolution.

Allelic variants of ADH, ALDH and the five factor model of personality in alcohol dependence syndrome

PubMed Central

Salujha, S. K.; Chaudhury, S.; Menon, P. K.; Srivastava, K.; Gupta, A.

2014-01-01

Background: The etiology of alcohol dependence is a complex interplay of biopsychosocial factors. The genes for alcohol-metabolizing enzymes: Alcohol dehydrogenase (ADH2 and ADH3) and aldehyde dehydrogenase (ALDH2) exhibit functional polymorphisms. Vulnerability of alcohol dependence may also be in part due to heritable personality traits. Aim: To determine whether any association exists between polymorphisms of ADH2, ADH3 and ALDH2 and alcohol dependence syndrome in a group of Asian Indians. In addition, the personality of these patients was assessed to identify traits predisposing to alcoholism. Materials and Methods: In this study, 100 consecutive males with alcohol dependence syndrome attending the psychiatric outpatient department of a tertiary care service hospital and an equal number of matched healthy controls were included with their consent. Blood samples of all the study cases and controls were collected and genotyped for the ADH2, ADH3 and ALDH2 loci. Personality was evaluated using the neuroticism, extraversion, openness (NEO) personality inventory and sensation seeking scale. Results: Allele frequencies of ADH2*2 (0.50), ADH3*1 (0.67) and ALSH2*2 (0.09) were significantly low in the alcohol dependent subjects. Personality traits of NEO personality inventory and sensation seeking were significantly higher when compared to controls. Conclusions: The functional polymorphisms of genes coding for alcohol metabolizing enzymes and personality traits of NEO and sensation seeking may affect the propensity to develop dependence. PMID:25535445

[Polymorphism of POU1F1 gene and PRL gene and their combined effects on milk performance traits in Chinese Holstein cattle].

PubMed

Jia, Xiang-Jie; Wang, Chang-Fa; Yang, Gui-Wen; Huang, Jin-Ming; Li, Qiu-Ling; Zhong, Ji-Feng

2011-12-01

Three novel SNPs were found by DNA sequencing, PCR-RFLP and CRS-PCR methods were used for genotyping in 979 Chinese Holstein cattle. One SNP, G1178C, was identified in exon 2 of POU1F1 gene. Two novel SNPs, A906G and A1134G, were identified in 5'-flanking regulatory region (5'-UTR) of PRL gene. The association between polymorphisms of the two genes and milk performance traits were analyzed with PROC GLM of SAS. The results showed that GC genotype at 1178 locus of POU1F1 gene was advantageous for milk yield, milk protein yield, and milk fat yield. AG genotype at 906 locus was advantageous for milk yield. There was no significant difference between 1134 locus and milk performance traits of 5'-UTR of PRL gene. Analysis of genotype combination effect on milk production traits showed that the effect of combined genotype was not simple sum of single genotypes and the effects of gene pyramiding seemed to be more important in molecular breeding.

Molecular Breeding Algae For Improved Traits For The Conversion Of Waste To Fuels And Commodities.

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

Bagwell, C.

This Exploratory LDRD aimed to develop molecular breeding methodology for biofuel algal strain improvement for applications in waste to energy / commodity conversion technologies. Genome shuffling technologies, specifically protoplast fusion, are readily available for the rapid production of genetic hybrids for trait improvement and have been used successfully in bacteria, yeast, plants and animals. However, genome fusion has not been developed for exploiting the remarkable untapped potential of eukaryotic microalgae for large scale integrated bio-conversion and upgrading of waste components to valued commodities, fuel and energy. The proposed molecular breeding technology is effectively sexual reproduction in algae; though compared tomore » traditional breeding, the molecular route is rapid, high-throughput and permits selection / improvement of complex traits which cannot be accomplished by traditional genetics. Genome fusion technologies are the cutting edge of applied biotechnology. The goals of this Exploratory LDRD were to 1) establish reliable methodology for protoplast production among diverse microalgal strains, and 2) demonstrate genome fusion for hybrid strain production using a single gene encoded trait as a proof of the concept.« less

Major genes and QTL influencing wool production and quality: a review.

PubMed

Purvis, Ian William; Franklin, Ian Robert

2005-01-01

The opportunity exists to utilise our knowledge of major genes that influence the economically important traits in wool sheep. Genes with Mendelian inheritance have been identified for many important traits in wool sheep. Of particular importance are genes influencing pigmentation, wool quality and the keratin proteins, the latter of which are important for the morphology of the wool fibre. Gene mapping studies have identified some chromosomal regions associated with variation in wool quality and production traits. The challenge now is to build on this knowledge base in a cost-effective way to deliver molecular tools that facilitate enhanced genetic improvement programs for wool sheep.

Emerging trends in the functional genomics of the abiotic stress response in crop plants.

PubMed

Vij, Shubha; Tyagi, Akhilesh K

2007-05-01

Plants are exposed to different abiotic stresses, such as water deficit, high temperature, salinity, cold, heavy metals and mechanical wounding, under field conditions. It is estimated that such stress conditions can potentially reduce the yield of crop plants by more than 50%. Investigations of the physiological, biochemical and molecular aspects of stress tolerance have been conducted to unravel the intrinsic mechanisms developed during evolution to mitigate against stress by plants. Before the advent of the genomics era, researchers primarily used a gene-by-gene approach to decipher the function of the genes involved in the abiotic stress response. However, abiotic stress tolerance is a complex trait and, although large numbers of genes have been identified to be involved in the abiotic stress response, there remain large gaps in our understanding of the trait. The availability of the genome sequences of certain important plant species has enabled the use of strategies, such as genome-wide expression profiling, to identify the genes associated with the stress response, followed by the verification of gene function by the analysis of mutants and transgenics. Certain components of both abscisic acid-dependent and -independent cascades involved in the stress response have already been identified. Information originating from the genome-wide analysis of abiotic stress tolerance will help to provide an insight into the stress-responsive network(s), and may allow the modification of this network to reduce the loss caused by stress and to increase agricultural productivity.

The genetic basis for survivorship in coronary artery disease

PubMed Central

Dungan, Jennifer R.; Hauser, Elizabeth R.; Qin, Xuejun; Kraus, William E.

2013-01-01

Survivorship is a trait characterized by endurance and virility in the face of hardship. It is largely considered a psychosocial attribute developed during fatal conditions, rather than a biological trait for robustness in the context of complex, age-dependent diseases like coronary artery disease (CAD). The purpose of this paper is to present the novel phenotype, survivorship in CAD as an observed survival advantage concurrent with clinically significant CAD. We present a model for characterizing survivorship in CAD and its relationships with overlapping time- and clinically-related phenotypes. We offer an optimal measurement interval for investigating survivorship in CAD. We hypothesize genetic contributions to this construct and review the literature for evidence of genetic contribution to overlapping phenotypes in support of our hypothesis. We also present preliminary evidence of genetic effects on survival in people with clinically significant CAD from a primary case-control study of symptomatic coronary disease. Identifying gene variants that confer improved survival in the context of clinically appreciable CAD may improve our understanding of cardioprotective mechanisms acting at the gene level and potentially impact patients clinically in the future. Further, characterizing other survival-variant genetic effects may improve signal-to-noise ratio in detecting gene associations for CAD. PMID:24143143

Ethylene regulates Apple (Malus x domestica) fruit softening through a dose x time-dependent mechanism and through differential sensitivities and dependencies of cell wall-modifying genes.

PubMed

Ireland, Hilary S; Gunaseelan, Kularajathevan; Muddumage, Ratnasiri; Tacken, Emma J; Putterill, Jo; Johnston, Jason W; Schaffer, Robert J

2014-05-01

In fleshy fruit species that have a strong requirement for ethylene to ripen, ethylene is synthesized autocatalytically, producing increasing concentrations as the fruits ripen. Apple fruit with the ACC OXIDASE 1 (ACO1) gene suppressed cannot produce ethylene autocatalytically at ripening. Using these apple lines, an ethylene sensitivity dependency model was previously proposed, with traits such as softening showing a high dependency for ethylene as well as low sensitivity. In this study, it is shown that the molecular control of fruit softening is a complex process, with different cell wall-related genes being independently regulated and exhibiting differential sensitivities to and dependencies on ethylene at the transcriptional level. This regulation is controlled through a dose × time mechanism, which results in a temporal transcriptional response that would allow for progressive cell wall disassembly and thus softening. This research builds on the sensitivity dependency model and shows that ethylene-dependent traits can progress over time to the same degree with lower levels of ethylene. This suggests that a developmental clock measuring cumulative ethylene controls the fruit ripening process.

Genetic Variants Associated with Hyperandrogenemia in PCOS Pathophysiology

PubMed Central

2018-01-01

Polycystic ovary syndrome is a multifactorial endocrine disorder whose pathophysiology baffles many researchers till today. This syndrome is typically characterized by anovulatory cycles and infertility, altered gonadotropin levels, obesity, and bulky multifollicular ovaries on ultrasound. Hyperandrogenism and insulin resistance are hallmark features of its complex pathophysiology. Hyperandrogenemia is a salient feature of PCOS and a major contributor to cosmetic anomalies including hirsutism, acne, and male pattern alopecia in affected women. Increased androgen levels may be intrinsic or aggravated by preexisting insulin resistance in women with PCOS. Studies have reported augmented ovarian steroidogenesis patterns attributed mainly to theca cell hypertrophy and altered expression of key enzymes in the steroidogenic pathway. Candidate gene studies have been performed in order to delineate the association of polymorphisms in genes, which encode enzymes in the intricate cascade of steroidogenesis or modulate the levels and action of circulating androgens, with risk of PCOS development and its related traits. However, inconsistent findings have impacted the emergence of a unanimously accepted genetic marker for PCOS susceptibility. In the current review, we have summarized the influence of polymorphisms in important androgen related genes in governing genetic predisposition to PCOS and its related metabolic and reproductive traits. PMID:29670770

Getting to the roots of it: Genetic and hormonal control of root architecture

PubMed Central

Jung, Janelle K. H.; McCouch, Susan

2013-01-01

Root system architecture (RSA) – the spatial configuration of a root system – is an important developmental and agronomic trait, with implications for overall plant architecture, growth rate and yield, abiotic stress resistance, nutrient uptake, and developmental plasticity in response to environmental changes. Root architecture is modulated by intrinsic, hormone-mediated pathways, intersecting with pathways that perceive and respond to external, environmental signals. The recent development of several non-invasive 2D and 3D root imaging systems has enhanced our ability to accurately observe and quantify architectural traits on complex whole-root systems. Coupled with the powerful marker-based genotyping and sequencing platforms currently available, these root phenotyping technologies lend themselves to large-scale genome-wide association studies, and can speed the identification and characterization of the genes and pathways involved in root system development. This capability provides the foundation for examining the contribution of root architectural traits to the performance of crop varieties in diverse environments. This review focuses on our current understanding of the genes and pathways involved in determining RSA in response to both intrinsic and extrinsic (environmental) response pathways, and provides a brief overview of the latest root system phenotyping technologies and their potential impact on elucidating the genetic control of root development in plants. PMID:23785372

The Transcription Factor Rbf1 Is the Master Regulator for b-Mating Type Controlled Pathogenic Development in Ustilago maydis

PubMed Central

Vranes, Miroslav; Wahl, Ramon; Pothiratana, Chetsada; Schuler, David; Vincon, Volker; Finkernagel, Florian; Flor-Parra, Ignacio; Kämper, Jörg

2010-01-01

In the phytopathogenic basidiomycete Ustilago maydis, sexual and pathogenic development are tightly connected and controlled by the heterodimeric bE/bW transcription factor complex encoded by the b-mating type locus. The formation of the active bE/bW heterodimer leads to the formation of filaments, induces a G2 cell cycle arrest, and triggers pathogenicity. Here, we identify a set of 345 bE/bW responsive genes which show altered expression during these developmental changes; several of these genes are associated with cell cycle coordination, morphogenesis and pathogenicity. 90% of the genes that show altered expression upon bE/bW-activation require the zinc finger transcription factor Rbf1, one of the few factors directly regulated by the bE/bW heterodimer. Rbf1 is a novel master regulator in a multilayered network of transcription factors that facilitates the complex regulatory traits of sexual and pathogenic development. PMID:20700446

An integrated map of structural variation in 2,504 human genomes.

PubMed

Sudmant, Peter H; Rausch, Tobias; Gardner, Eugene J; Handsaker, Robert E; Abyzov, Alexej; Huddleston, John; Zhang, Yan; Ye, Kai; Jun, Goo; Fritz, Markus Hsi-Yang; Konkel, Miriam K; Malhotra, Ankit; Stütz, Adrian M; Shi, Xinghua; Casale, Francesco Paolo; Chen, Jieming; Hormozdiari, Fereydoun; Dayama, Gargi; Chen, Ken; Malig, Maika; Chaisson, Mark J P; Walter, Klaudia; Meiers, Sascha; Kashin, Seva; Garrison, Erik; Auton, Adam; Lam, Hugo Y K; Mu, Xinmeng Jasmine; Alkan, Can; Antaki, Danny; Bae, Taejeong; Cerveira, Eliza; Chines, Peter; Chong, Zechen; Clarke, Laura; Dal, Elif; Ding, Li; Emery, Sarah; Fan, Xian; Gujral, Madhusudan; Kahveci, Fatma; Kidd, Jeffrey M; Kong, Yu; Lameijer, Eric-Wubbo; McCarthy, Shane; Flicek, Paul; Gibbs, Richard A; Marth, Gabor; Mason, Christopher E; Menelaou, Androniki; Muzny, Donna M; Nelson, Bradley J; Noor, Amina; Parrish, Nicholas F; Pendleton, Matthew; Quitadamo, Andrew; Raeder, Benjamin; Schadt, Eric E; Romanovitch, Mallory; Schlattl, Andreas; Sebra, Robert; Shabalin, Andrey A; Untergasser, Andreas; Walker, Jerilyn A; Wang, Min; Yu, Fuli; Zhang, Chengsheng; Zhang, Jing; Zheng-Bradley, Xiangqun; Zhou, Wanding; Zichner, Thomas; Sebat, Jonathan; Batzer, Mark A; McCarroll, Steven A; Mills, Ryan E; Gerstein, Mark B; Bashir, Ali; Stegle, Oliver; Devine, Scott E; Lee, Charles; Eichler, Evan E; Korbel, Jan O

2015-10-01

Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.

Comprehensive coverage of cardiovascular disease data in the disease portals at the Rat Genome Database.

PubMed

Wang, Shur-Jen; Laulederkind, Stanley J F; Hayman, G Thomas; Petri, Victoria; Smith, Jennifer R; Tutaj, Marek; Nigam, Rajni; Dwinell, Melinda R; Shimoyama, Mary

2016-08-01

Cardiovascular diseases are complex diseases caused by a combination of genetic and environmental factors. To facilitate progress in complex disease research, the Rat Genome Database (RGD) provides the community with a disease portal where genome objects and biological data related to cardiovascular diseases are systematically organized. The purpose of this study is to present biocuration at RGD, including disease, genetic, and pathway data. The RGD curation team uses controlled vocabularies/ontologies to organize data curated from the published literature or imported from disease and pathway databases. These organized annotations are associated with genes, strains, and quantitative trait loci (QTLs), thus linking functional annotations to genome objects. Screen shots from the web pages are used to demonstrate the organization of annotations at RGD. The human cardiovascular disease genes identified by annotations were grouped according to data sources and their annotation profiles were compared by in-house tools and other enrichment tools available to the public. The analysis results show that the imported cardiovascular disease genes from ClinVar and OMIM are functionally different from the RGD manually curated genes in terms of pathway and Gene Ontology annotations. The inclusion of disease genes from other databases enriches the collection of disease genes not only in quantity but also in quality. Copyright © 2016 the American Physiological Society.

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

Advances in QTL Mapping in Pigs

PubMed Central

Rothschild, Max F.; Hu, Zhi-liang; Jiang, Zhihua

2007-01-01

Over the past 15 years advances in the porcine genetic linkage map and discovery of useful candidate genes have led to valuable gene and trait information being discovered. Early use of exotic breed crosses and now commercial breed crosses for quantitative trait loci (QTL) scans and candidate gene analyses have led to 110 publications which have identified 1,675 QTL. Additionally, these studies continue to identify genes associated with economically important traits such as growth rate, leanness, feed intake, meat quality, litter size, and disease resistance. A well developed QTL database called PigQTLdb is now as a valuable tool for summarizing and pinpointing in silico regions of interest to researchers. The commercial pig industry is actively incorporating these markers in marker-assisted selection along with traditional performance information to improve traits of economic performance. The long awaited sequencing efforts are also now beginning to provide sequence available for both comparative genomics and large scale single nucleotide polymorphism (SNP) association studies. While these advances are all positive, development of useful new trait families and measurement of new or underlying traits still limits future discoveries. A review of these developments is presented. PMID:17384738

Genetic and genomic analyses for economically important traits and their applications in molecular breeding of cultured fish.

PubMed

Tong, JinGou; Sun, XiaoWen

2015-02-01

The traits of cultured fish must continually be genetically improved to supply high-quality animal protein for human consumption. Economically important fish traits are controlled by multiple gene quantitative trait loci (QTL), most of which have minor effects, but a few genes may have major effects useful for molecular breeding. In this review, we chose relevant studies on some of the most intensively cultured fish and concisely summarize progress on identifying and verifying QTLs for such traits as growth, disease and stress resistance and sex in recent decades. The potential applications of these major-effect genes and their associated markers in marker-assisted selection and molecular breeding, as well as future research directions are also discussed. These genetic and genomic analyses will be valuable for elucidating the mechanisms modulating economically important traits and to establish more effective molecular breeding techniques in fish.

The dopamine transporter gene may not contribute to susceptibility and the specific personality traits of amphetamine dependence.

PubMed

Tzeng, Nian-Sheng; Lu, Ru-Band; Yeh, Hui-Wen; Yeh, Yi-Wei; Huang, Chang-Chih; Yen, Che-Hung; Kuo, Shin-Chang; Chen, Chun-Yen; Chang, Hsin-An; Ho, Pei-Shen; Cheng, Serena; Shih, Mei-Chen; Huang, San-Yuan

2015-04-01

A substantial amount of evidence suggests that dysfunction of the dopamine transporter may be involved in the pathophysiology of amphetamine dependence (AD). The aim of this study was to examine whether the dopamine transporter gene (DAT1, SLC6A3) is associated with development of AD and whether this gene influences personality traits in patients with AD. Eighteen polymorphisms of the DAT1 gene were analyzed in a case-control study that included 909 Han Chinese men (568 patients with AD and 341 control subjects). The patients fulfilled the DSM-IV-TR criteria for AD. The Tridimensional Personality Questionnaire (TPQ) was used to assess personality traits and to examine the association between these traits and DAT1 gene variants. A weak association was found between the rs27072 polymorphism and development of AD, but these borderline associations were unconfirmed by logistic regression and haplotype analysis. Although harm avoidance and novelty seeking scores were significantly higher in patients than in controls, DAT1 polymorphisms did not influence these scores. This study suggests that high harm avoidance and novelty seeking personality traits may be a risk factor for the development of AD. However, the DAT1 gene may not contribute to AD susceptibility and specific personality traits observed in AD among Han Chinese men. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

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.

Global expression studies in baker's yeast reveal target genes for the improvement of industrially-relevant traits: the cases of CAF16 and ORC2

PubMed Central

2010-01-01

Background Recent years have seen a huge growth in the market of industrial yeasts with the need for strains affording better performance or to be used in new applications. Stress tolerance of commercial Saccharomyces cerevisiae yeasts is, without doubt, a trait that needs improving. Such trait is, however, complex, and therefore only in-depth knowledge of their biochemical, physiological and genetic principles can help us to define improvement strategies and to identify the key factors for strain selection. Results We have determined the transcriptional response of commercial baker's yeast cells to both high-sucrose and lean dough by using DNA macroarrays and liquid dough (LD) model system. Cells from compressed yeast blocks display a reciprocal transcription program to that commonly reported for laboratory strains exposed to osmotic stress. This discrepancy likely reflects differences in strain background and/or experimental design. Quite remarkably, we also found that the transcriptional response of starved baker's yeast cells was qualitatively similar in the presence or absence of sucrose in the LD. Nevertheless, there was a set of differentially regulated genes, which might be relevant for cells to adapt to high osmolarity. Consistent with this, overexpression of CAF16 or ORC2, two transcriptional factor-encoding genes included in this group, had positive effects on leavening activity of baker's yeast. Moreover, these effects were more pronounced during freezing and frozen storage of high-sucrose LD. Conclusions Engineering of differentially regulated genes opens the possibility to improve the physiological behavior of baker's yeast cells under stress conditions like those encountered in downstream applications. PMID:20626860

Expression studies of six human obesity-related genes in seven tissues from divergent pig breeds.

PubMed

Cirera, S; Jensen, M S; Elbrønd, V S; Moesgaard, S G; Christoffersen, B Ø; Kadarmideen, H N; Skovgaard, K; Bruun, C V; Karlskov-Mortensen, P; Jørgensen, C B; Fredholm, M

2014-02-01

Obesity has reached epidemic proportions globally and has become the cause of several major health risks worldwide. Presently, more than 100 loci have been related to obesity and metabolic traits in humans by genome-wide association studies. The complex genetic architecture behind obesity has triggered a need for the development of better animal models than rodents. The pig has emerged as a very promising biomedical model to study human obesity traits. In this study, we have characterized the expression patterns of six obesity-related genes, leptin (LEP), leptin receptor (LEPR), melanocortin 4 receptor (MC4R), fat mass and obesity associated (FTO), neuronal growth regulator 1 (NEGR)1 and adiponectin (ADIPOQ), in seven obesity-relevant tissues (liver; muscle; pancreas; hypothalamus; and retroperitoneal, subcutaneous and mesenteric adipose tissues) in two pig breeds (production pigs and Göttingen minipigs) that deviate phenotypically and genetically from each other with respect to obesity traits. We observe significant differential expression for LEP, LEPR and ADIPOQ in muscle and in all three adipose tissues. Interestingly, in pancreas, LEP expression is only detected in the fat minipigs. FTO shows significant differential expression in all tissues analyzed, and NEGR1 shows significant differential expression in muscle, pancreas, hypothalamus and subcutaneous adipose tissue. The MC4R transcript can be detected only in hypothalamus. In general, the expression profiles of the investigated genes are in accordance with those observed in human studies. Our study shows that both the differences between the investigated breeds and the phenotypic state with respect to obesity/leanness play a large role for differential expression of the obesity-related genes. © 2013 The Authors, Animal Genetics © 2013 Stichting International Foundation for Animal Genetics.

Association Analysis in Rice: From Application to Utilization

PubMed Central

Zhang, Peng; Zhong, Kaizhen; Shahid, Muhammad Qasim; Tong, Hanhua

2016-01-01

Association analysis based on linkage disequilibrium (LD) is an efficient way to dissect complex traits and to identify gene functions in rice. Although association analysis is an effective way to construct fine maps for quantitative traits, there are a few issues which need to be addressed. In this review, we will first summarize type, structure, and LD level of populations used for association analysis of rice, and then discuss the genotyping methods and statistical approaches used for association analysis in rice. Moreover, we will review current shortcomings and benefits of association analysis as well as specific types of future research to overcome these shortcomings. Furthermore, we will analyze the reasons for the underutilization of the results within association analysis in rice breeding. PMID:27582745

Cloning of DOG1, a quantitative trait locus controlling seed dormancy in Arabidopsis.

PubMed

Bentsink, Leónie; Jowett, Jemma; Hanhart, Corrie J; Koornneef, Maarten

2006-11-07

Genetic variation for seed dormancy in nature is a typical quantitative trait controlled by multiple loci on which environmental factors have a strong effect. Finding the genes underlying dormancy quantitative trait loci is a major scientific challenge, which also has relevance for agriculture and ecology. In this study we describe the identification of the DELAY OF GERMINATION 1 (DOG1) gene previously identified as a quantitative trait locus involved in the control of seed dormancy. This gene was isolated by a combination of positional cloning and mutant analysis and is absolutely required for the induction of seed dormancy. DOG1 is a member of a small gene family of unknown molecular function, with five members in Arabidopsis. The functional natural allelic variation present in Arabidopsis is caused by polymorphisms in the cis-regulatory region of the DOG1 gene and results in considerable expression differences between the DOG1 alleles of the accessions analyzed.

One novel SNP of growth hormone gene and its associations with growth and carcass traits in ducks.

PubMed

Wu, Y; Pan, A L; Pi, J S; Pu, Y J; Du, J P; Liang, Z H; Shen, J

2012-08-01

In this study, the growth hormone (GH) gene was studied as a candidate gene for growth and carcass traits of three duck populations (Cherry Valley duck, Muscovy duck and Jingjiang duck). Three pairs of primers were designed to detect single nucleotide polymorphisms of introns 2, 3 and 4 of the GH gene by polymerase chain reaction-restriction fragment length polymorphism and sequencing methods. Only the products amplified from intron 2 displayed polymorphism. The results showed one novel polymorphism: a variation in intron 2 of GH gene (C172T, JN408701 and JN408702). It was associated with some growth and carcass traits in three duck populations including birth weight, 8-week weight, carcass weight, breast muscle weight, leg muscle weight, eviscerated weight, lean meat rate, dressing percentage, etc. And the TT and CT genotypes were associated with superior growth and carcass traits in carcass weight, dressing percentage and percentage of eviscerated weight. Therefore, the variation in intron 2 of GH may be a molecular marker for superior growth and carcass traits in above duck populations.

Localization of canine brachycephaly using an across breed mapping approach.

PubMed

Bannasch, Danika; Young, Amy; Myers, Jeffrey; Truvé, Katarina; Dickinson, Peter; Gregg, Jeffrey; Davis, Ryan; Bongcam-Rudloff, Eric; Webster, Matthew T; Lindblad-Toh, Kerstin; Pedersen, Niels

2010-03-10

The domestic dog, Canis familiaris, exhibits profound phenotypic diversity and is an ideal model organism for the genetic dissection of simple and complex traits. However, some of the most interesting phenotypes are fixed in particular breeds and are therefore less tractable to genetic analysis using classical segregation-based mapping approaches. We implemented an across breed mapping approach using a moderately dense SNP array, a low number of animals and breeds carefully selected for the phenotypes of interest to identify genetic variants responsible for breed-defining characteristics. Using a modest number of affected (10-30) and control (20-60) samples from multiple breeds, the correct chromosomal assignment was identified in a proof of concept experiment using three previously defined loci; hyperuricosuria, white spotting and chondrodysplasia. Genome-wide association was performed in a similar manner for one of the most striking morphological traits in dogs: brachycephalic head type. Although candidate gene approaches based on comparable phenotypes in mice and humans have been utilized for this trait, the causative gene has remained elusive using this method. Samples from nine affected breeds and thirteen control breeds identified strong genome-wide associations for brachycephalic head type on Cfa 1. Two independent datasets identified the same genomic region. Levels of relative heterozygosity in the associated region indicate that it has been subjected to a selective sweep, consistent with it being a breed defining morphological characteristic. Genotyping additional dogs in the region confirmed the association. To date, the genetic structure of dog breeds has primarily been exploited for genome wide association for segregating traits. These results demonstrate that non-segregating traits under strong selection are equally tractable to genetic analysis using small sample numbers.

Identification of multiple genetic loci in the mouse controlling immobility time in the tail suspension and forced swimming tests.

PubMed

Abou-Elnaga, Ahmed F; Torigoe, Daisuke; Fouda, Mohamed M; Darwish, Ragab A; Abou-Ismail, Usama A; Morimatsu, Masami; Agui, Takashi

2015-05-01

Depression is one of the most famous psychiatric disorders in humans in all over the countries and considered a complex neurobehavioral trait and difficult to identify causal genes. Tail suspension test (TST) and forced swimming test (FST) are widely used for assessing depression-like behavior and antidepressant activity in mice. A variety of antidepressant agents are known to reduce immobility time in both TST and FST. To identify genetic determinants of immobility duration in both tests, we analyzed 101 F2 mice from an intercross between C57BL/6 and DBA/2 strains. Quantitative trait locus (QTL) mapping using 106 microsatellite markers revealed three loci (two significant and one suggestive) and five suggestive loci controlling immobility time in the TST and FST, respectively. Results of QTL analysis suggest a broad description of the genetic architecture underlying depression, providing underpinnings for identifying novel molecular targets for antidepressants to clear the complex genetic mechanisms of depressive disorders.

In Search of the Perfect Phenotype: An Analysis of Linkage and Association Studies of Reading and Reading-Related Processes

PubMed Central

Skiba, Thomas; Landi, Nicole; Wagner, Richard

2011-01-01

Reading ability and specific reading disability (SRD) are complex traits involving several cognitive processes and are shaped by a complex interplay of genetic and environmental forces. Linkage studies of these traits have identified several susceptibility loci. Association studies have gone further in detecting candidate genes that might underlie these signals. These results have been obtained in samples of mainly European ancestry, which vary in their languages, inclusion criteria, and phenotype assessments. Such phenotypic heterogeneity across samples makes understanding the relationship between reading (dis)ability and reading-related processes and the genetic factors difficult; in addition, it may negatively influence attempts at replication. In moving forward, the identification of preferable phenotypes for future sample collection may improve the replicability of findings. This review of all published linkage and association results from the past 15 years was conducted to determine if certain phenotypes produce more replicable and consistent results than others. PMID:21243420

Genetic Architecture of Ear Fasciation in Maize (Zea mays) under QTL Scrutiny

PubMed Central

Mendes-Moreira, Pedro; Alves, Mara L.; Satovic, Zlatko; dos Santos, João Pacheco; Santos, João Nina; Souza, João Cândido; Pêgo, Silas E.; Hallauer, Arnel R.; Vaz Patto, Maria Carlota

2015-01-01

Maize ear fasciation Knowledge of the genes affecting maize ear inflorescence may lead to better grain yield modeling. Maize ear fasciation, defined as abnormal flattened ears with high kernel row number, is a quantitative trait widely present in Portuguese maize landraces. Material and Methods Using a segregating population derived from an ear fasciation contrasting cross (consisting of 149 F2:3 families) we established a two location field trial using a complete randomized block design. Correlations and heritabilities for several ear fasciation-related traits and yield were determined. Quantitative Trait Loci (QTL) involved in the inheritance of those traits were identified and candidate genes for these QTL proposed. Results and Discussion Ear fasciation broad-sense heritability was 0.73. Highly significant correlations were found between ear fasciation and some ear and cob diameters and row number traits. For the 23 yield and ear fasciation-related traits, 65 QTL were identified, out of which 11 were detected in both environments, while for the three principal components, five to six QTL were detected per environment. Detected QTL were distributed across 17 genomic regions and explained individually, 8.7% to 22.4% of the individual traits or principal components phenotypic variance. Several candidate genes for these QTL regions were proposed, such as bearded-ear1, branched silkless1, compact plant1, ramosa2, ramosa3, tasselseed4 and terminal ear1. However, many QTL mapped to regions without known candidate genes, indicating potential chromosomal regions not yet targeted for maize ear traits selection. Conclusions Portuguese maize germplasm represents a valuable source of genes or allelic variants for yield improvement and elucidation of the genetic basis of ear fasciation traits. Future studies should focus on fine mapping of the identified genomic regions with the aim of map-based cloning. PMID:25923975

Genetic Architecture of Ear Fasciation in Maize (Zea mays) under QTL Scrutiny.

PubMed

Mendes-Moreira, Pedro; Alves, Mara L; Satovic, Zlatko; Dos Santos, João Pacheco; Santos, João Nina; Souza, João Cândido; Pêgo, Silas E; Hallauer, Arnel R; Vaz Patto, Maria Carlota

2015-01-01

Knowledge of the genes affecting maize ear inflorescence may lead to better grain yield modeling. Maize ear fasciation, defined as abnormal flattened ears with high kernel row number, is a quantitative trait widely present in Portuguese maize landraces. Using a segregating population derived from an ear fasciation contrasting cross (consisting of 149 F2:3 families) we established a two location field trial using a complete randomized block design. Correlations and heritabilities for several ear fasciation-related traits and yield were determined. Quantitative Trait Loci (QTL) involved in the inheritance of those traits were identified and candidate genes for these QTL proposed. Ear fasciation broad-sense heritability was 0.73. Highly significant correlations were found between ear fasciation and some ear and cob diameters and row number traits. For the 23 yield and ear fasciation-related traits, 65 QTL were identified, out of which 11 were detected in both environments, while for the three principal components, five to six QTL were detected per environment. Detected QTL were distributed across 17 genomic regions and explained individually, 8.7% to 22.4% of the individual traits or principal components phenotypic variance. Several candidate genes for these QTL regions were proposed, such as bearded-ear1, branched silkless1, compact plant1, ramosa2, ramosa3, tasselseed4 and terminal ear1. However, many QTL mapped to regions without known candidate genes, indicating potential chromosomal regions not yet targeted for maize ear traits selection. Portuguese maize germplasm represents a valuable source of genes or allelic variants for yield improvement and elucidation of the genetic basis of ear fasciation traits. Future studies should focus on fine mapping of the identified genomic regions with the aim of map-based cloning.

Signatures of negative selection in the genetic architecture of human complex traits.

PubMed

Zeng, Jian; de Vlaming, Ronald; Wu, Yang; Robinson, Matthew R; Lloyd-Jones, Luke R; Yengo, Loic; Yap, Chloe X; Xue, Angli; Sidorenko, Julia; McRae, Allan F; Powell, Joseph E; Montgomery, Grant W; Metspalu, Andres; Esko, Tonu; Gibson, Greg; Wray, Naomi R; Visscher, Peter M; Yang, Jian

2018-05-01

We develop a Bayesian mixed linear model that simultaneously estimates single-nucleotide polymorphism (SNP)-based heritability, polygenicity (proportion of SNPs with nonzero effects), and the relationship between SNP effect size and minor allele frequency for complex traits in conventionally unrelated individuals using genome-wide SNP data. We apply the method to 28 complex traits in the UK Biobank data (N = 126,752) and show that on average, 6% of SNPs have nonzero effects, which in total explain 22% of phenotypic variance. We detect significant (P < 0.05/28) signatures of natural selection in the genetic architecture of 23 traits, including reproductive, cardiovascular, and anthropometric traits, as well as educational attainment. The significant estimates of the relationship between effect size and minor allele frequency in complex traits are consistent with a model of negative (or purifying) selection, as confirmed by forward simulation. We conclude that negative selection acts pervasively on the genetic variants associated with human complex traits.

Insulin-like growth factor I gene polymorphism associated with growth and carcass traits in Thai synthetic chickens.

PubMed

Promwatee, N; Laopaiboon, B; Vongpralub, T; Phasuk, Y; Kunhareang, S; Boonkum, W; Duangjinda, M

2013-03-15

Four Thai synthetic chicken lines (Kaen Thong, Khai Mook Esarn, Soi Nin, and Soi Pet) originated from Thai native and exotic commercial chickens were evaluated for their growth and carcass traits with the purpose of developing a Thai broiler breeding program. Insulin-like growth factor I (IGF-I) gene is known to play an important role in growth, proliferation and differentiation. Consequently, we investigated the possibility of using the IGF-I gene for marker-assisted selection in Thai synthetic chickens. We looked for variations in the IGF-I gene and studied their association with growth and carcass traits; 1046 chickens were genotyped using PCR-RFLP methods. A general linear model was used to analyze associations of the IGF-I polymorphism with growth and carcass traits. Kaen Thong, Khai Mook Esarn, and Soi Nin chickens were found to carry similar frequencies of alleles A and C (0.40-0.60), while Soi Pet chickens had high frequencies of allele C (0.75). The IGF-I gene was significantly associated with some growth traits (body weight at hatching, and at 4, 8, 12, and 14 weeks of age; average daily gain during 0-12 and 0-14 weeks of age) in all synthetic chickens. Carcass traits (the percentage of dressing and pectoralis major) were significantly different only in Khai Mook Esarn chickens. We conclude that IGF-I can be used as a marker gene for the selection of growth and carcass traits of synthetic chickens in a marker-assisted selection program.