EvolQG - An R package for evolutionary quantitative genetics

PubMed Central

Melo, Diogo; Garcia, Guilherme; Hubbe, Alex; Assis, Ana Paula; Marroig, Gabriel

2016-01-01

We present an open source package for performing evolutionary quantitative genetics analyses in the R environment for statistical computing. Evolutionary theory shows that evolution depends critically on the available variation in a given population. When dealing with many quantitative traits this variation is expressed in the form of a covariance matrix, particularly the additive genetic covariance matrix or sometimes the phenotypic matrix, when the genetic matrix is unavailable and there is evidence the phenotypic matrix is sufficiently similar to the genetic matrix. Given this mathematical representation of available variation, the \\textbf{EvolQG} package provides functions for calculation of relevant evolutionary statistics; estimation of sampling error; corrections for this error; matrix comparison via correlations, distances and matrix decomposition; analysis of modularity patterns; and functions for testing evolutionary hypotheses on taxa diversification. PMID:27785352

Genetic data analysis for plant and animal breeding

USDA-ARS?s Scientific Manuscript database

This book is an advanced textbook covering the application of quantitative genetics theory to analysis of actual data (both trait and DNA marker information) for breeding populations of crops, trees, and animals. Chapter 1 is an introduction to basic software used for trait data analysis. Chapter 2 ...

Gene Level Meta-Analysis of Quantitative Traits by Functional Linear Models.

PubMed

Fan, Ruzong; Wang, Yifan; Boehnke, Michael; Chen, Wei; Li, Yun; Ren, Haobo; Lobach, Iryna; Xiong, Momiao

2015-08-01

Meta-analysis of genetic data must account for differences among studies including study designs, markers genotyped, and covariates. The effects of genetic variants may differ from population to population, i.e., heterogeneity. Thus, meta-analysis of combining data of multiple studies is difficult. Novel statistical methods for meta-analysis are needed. In this article, functional linear models are developed for meta-analyses that connect genetic data to quantitative traits, adjusting for covariates. The models can be used to analyze rare variants, common variants, or a combination of the two. Both likelihood-ratio test (LRT) and F-distributed statistics are introduced to test association between quantitative traits and multiple variants in one genetic region. Extensive simulations are performed to evaluate empirical type I error rates and power performance of the proposed tests. The proposed LRT and F-distributed statistics control the type I error very well and have higher power than the existing methods of the meta-analysis sequence kernel association test (MetaSKAT). We analyze four blood lipid levels in data from a meta-analysis of eight European studies. The proposed methods detect more significant associations than MetaSKAT and the P-values of the proposed LRT and F-distributed statistics are usually much smaller than those of MetaSKAT. The functional linear models and related test statistics can be useful in whole-genome and whole-exome association studies. Copyright © 2015 by the Genetics Society of America.

Quantitative analysis of terahertz spectra for illicit drugs using adaptive-range micro-genetic algorithm

NASA Astrophysics Data System (ADS)

Chen, Yi; Ma, Yong; Lu, Zheng; Peng, Bei; Chen, Qin

2011-08-01

In the field of anti-illicit drug applications, many suspicious mixture samples might consist of various drug components—for example, a mixture of methamphetamine, heroin, and amoxicillin—which makes spectral identification very difficult. A terahertz spectroscopic quantitative analysis method using an adaptive range micro-genetic algorithm with a variable internal population (ARVIPɛμGA) has been proposed. Five mixture cases are discussed using ARVIPɛμGA driven quantitative terahertz spectroscopic analysis in this paper. The devised simulation results show agreement with the previous experimental results, which suggested that the proposed technique has potential applications for terahertz spectral identifications of drug mixture components. The results show agreement with the results obtained using other experimental and numerical techniques.

MaGelLAn 1.0: a software to facilitate quantitative and population genetic analysis of maternal inheritance by combination of molecular and pedigree information.

PubMed

Ristov, Strahil; Brajkovic, Vladimir; Cubric-Curik, Vlatka; Michieli, Ivan; Curik, Ino

2016-09-10

Identification of genes or even nucleotides that are responsible for quantitative and adaptive trait variation is a difficult task due to the complex interdependence between a large number of genetic and environmental factors. The polymorphism of the mitogenome is one of the factors that can contribute to quantitative trait variation. However, the effects of the mitogenome have not been comprehensively studied, since large numbers of mitogenome sequences and recorded phenotypes are required to reach the adequate power of analysis. Current research in our group focuses on acquiring the necessary mitochondria sequence information and analysing its influence on the phenotype of a quantitative trait. To facilitate these tasks we have produced software for processing pedigrees that is optimised for maternal lineage analysis. We present MaGelLAn 1.0 (maternal genealogy lineage analyser), a suite of four Python scripts (modules) that is designed to facilitate the analysis of the impact of mitogenome polymorphism on quantitative trait variation by combining molecular and pedigree information. MaGelLAn 1.0 is primarily used to: (1) optimise the sampling strategy for molecular analyses; (2) identify and correct pedigree inconsistencies; and (3) identify maternal lineages and assign the corresponding mitogenome sequences to all individuals in the pedigree, this information being used as input to any of the standard software for quantitative genetic (association) analysis. In addition, MaGelLAn 1.0 allows computing the mitogenome (maternal) effective population sizes and probability of mitogenome (maternal) identity that are useful for conservation management of small populations. MaGelLAn is the first tool for pedigree analysis that focuses on quantitative genetic analyses of mitogenome data. It is conceived with the purpose to significantly reduce the effort in handling and preparing large pedigrees for processing the information linked to maternal lines. The software source code, along with the manual and the example files can be downloaded at http://lissp.irb.hr/software/magellan-1-0/ and https://github.com/sristov/magellan .

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.

Learning abilities and disabilities: generalist genes in early adolescence.

PubMed

Davis, Oliver S P; Haworth, Claire M A; Plomin, Robert

2009-01-01

The new view of cognitive neuropsychology that considers not just case studies of rare severe disorders but also common disorders, as well as normal variation and quantitative traits, is more amenable to recent advances in molecular genetics, such as genome-wide association studies, and advances in quantitative genetics, such as multivariate genetic analysis. A surprising finding emerging from multivariate quantitative genetic studies across diverse learning abilities is that most genetic influences are shared: they are "generalist", rather than "specialist". We exploited widespread access to inexpensive and fast Internet connections in the United Kingdom to assess over 5000 pairs of 12-year-old twins from the Twins Early Development Study (TEDS) on four distinct batteries: reading, mathematics, general cognitive ability (g) and, for the first time, language. Genetic correlations remain high among all of the measured abilities, with language as highly correlated genetically with g as reading and mathematics. Despite developmental upheaval, generalist genes remain important into early adolescence, suggesting optimal strategies for molecular genetic studies seeking to identify the genes of small effect that influence learning abilities and disabilities.

Genetic analysis of PAX3 for diagnosis of Waardenburg syndrome type I.

PubMed

Matsunaga, Tatsuo; Mutai, Hideki; Namba, Kazunori; Morita, Noriko; Masuda, Sawako

2013-04-01

PAX3 genetic analysis increased the diagnostic accuracy for Waardenburg syndrome type I (WS1). Analysis of the three-dimensional (3D) structure of PAX3 helped verify the pathogenicity of a missense mutation, and multiple ligation-dependent probe amplification (MLPA) analysis of PAX3 increased the sensitivity of genetic diagnosis in patients with WS1. Clinical diagnosis of WS1 is often difficult in individual patients with isolated, mild, or non-specific symptoms. The objective of the present study was to facilitate the accurate diagnosis of WS1 through genetic analysis of PAX3 and to expand the spectrum of known PAX3 mutations. In two Japanese families with WS1, we conducted a clinical evaluation of symptoms and genetic analysis, which involved direct sequencing, MLPA analysis, quantitative PCR of PAX3, and analysis of the predicted 3D structure of PAX3. The normal-hearing control group comprised 92 subjects who had normal hearing according to pure tone audiometry. In one family, direct sequencing of PAX3 identified a heterozygous mutation, p.I59F. Analysis of PAX3 3D structures indicated that this mutation distorted the DNA-binding site of PAX3. In the other family, MLPA analysis and subsequent quantitative PCR detected a large, heterozygous deletion spanning 1759-2554 kb that eliminated 12-18 genes including a whole PAX3 gene.

Path analysis of the genetic integration of traits in the sand cricket: a novel use of BLUPs.

PubMed

Roff, D A; Fairbairn, D J

2011-09-01

This study combines path analysis with quantitative genetics to analyse a key life history trade-off in the cricket, Gryllus firmus. We develop a path model connecting five traits associated with the trade-off between flight capability and reproduction and test this model using phenotypic data and estimates of breeding values (best linear unbiased predictors) from a half-sibling experiment. Strong support by both types of data validates our causal model and indicates concordance between the phenotypic and genetic expression of the trade-off. Comparisons of the trade-off between sexes and wing morphs reveal that these discrete phenotypes are not genetically independent and that the evolutionary trajectories of the two wing morphs are more tightly constrained to covary than those of the two sexes. Our results illustrate the benefits of combining a quantitative genetic analysis, which examines statistical correlations between traits, with a path model that focuses upon the causal components of variation. © 2011 The Authors. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.

Genetic Variants Associated With Quantitative Glucose Homeostasis Traits Translate to Type 2 Diabetes in Mexican Americans: The GUARDIAN (Genetics Underlying Diabetes in Hispanics) Consortium.

PubMed

Palmer, Nicholette D; Goodarzi, Mark O; Langefeld, Carl D; Wang, Nan; Guo, Xiuqing; Taylor, Kent D; Fingerlin, Tasha E; Norris, Jill M; Buchanan, Thomas A; Xiang, Anny H; Haritunians, Talin; Ziegler, Julie T; Williams, Adrienne H; Stefanovski, Darko; Cui, Jinrui; Mackay, Adrienne W; Henkin, Leora F; Bergman, Richard N; Gao, Xiaoyi; Gauderman, James; Varma, Rohit; Hanis, Craig L; Cox, Nancy J; Highland, Heather M; Below, Jennifer E; Williams, Amy L; Burtt, Noel P; Aguilar-Salinas, Carlos A; Huerta-Chagoya, Alicia; Gonzalez-Villalpando, Clicerio; Orozco, Lorena; Haiman, Christopher A; Tsai, Michael Y; Johnson, W Craig; Yao, Jie; Rasmussen-Torvik, Laura; Pankow, James; Snively, Beverly; Jackson, Rebecca D; Liu, Simin; Nadler, Jerry L; Kandeel, Fouad; Chen, Yii-Der I; Bowden, Donald W; Rich, Stephen S; Raffel, Leslie J; Rotter, Jerome I; Watanabe, Richard M; Wagenknecht, Lynne E

2015-05-01

Insulin sensitivity, insulin secretion, insulin clearance, and glucose effectiveness exhibit strong genetic components, although few studies have examined their genetic architecture or influence on type 2 diabetes (T2D) risk. We hypothesized that loci affecting variation in these quantitative traits influence T2D. We completed a multicohort genome-wide association study to search for loci influencing T2D-related quantitative traits in 4,176 Mexican Americans. Quantitative traits were measured by the frequently sampled intravenous glucose tolerance test (four cohorts) or euglycemic clamp (three cohorts), and random-effects models were used to test the association between loci and quantitative traits, adjusting for age, sex, and admixture proportions (Discovery). Analysis revealed a significant (P < 5.00 × 10(-8)) association at 11q14.3 (MTNR1B) with acute insulin response. Loci with P < 0.0001 among the quantitative traits were examined for translation to T2D risk in 6,463 T2D case and 9,232 control subjects of Mexican ancestry (Translation). Nonparametric meta-analysis of the Discovery and Translation cohorts identified significant associations at 6p24 (SLC35B3/TFAP2A) with glucose effectiveness/T2D, 11p15 (KCNQ1) with disposition index/T2D, and 6p22 (CDKAL1) and 11q14 (MTNR1B) with acute insulin response/T2D. These results suggest that T2D and insulin secretion and sensitivity have both shared and distinct genetic factors, potentially delineating genomic components of these quantitative traits that drive the risk for T2D. © 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

Computational, Integrative, and Comparative Methods for the Elucidation of Genetic Coexpression Networks

DOE PAGES

Baldwin, Nicole E.; Chesler, Elissa J.; Kirov, Stefan; ...

2005-01-01

Gene expression microarray data can be used for the assembly of genetic coexpression network graphs. Using mRNA samples obtained from recombinant inbred Mus musculus strains, it is possible to integrate allelic variation with molecular and higher-order phenotypes. The depth of quantitative genetic analysis of microarray data can be vastly enhanced utilizing this mouse resource in combination with powerful computational algorithms, platforms, and data repositories. The resulting network graphs transect many levels of biological scale. This approach is illustrated with the extraction of cliques of putatively co-regulated genes and their annotation using gene ontology analysis and cis -regulatory element discovery. Themore » causal basis for co-regulation is detected through the use of quantitative trait locus mapping.« less

Pleiotropy Analysis of Quantitative Traits at Gene Level by Multivariate Functional Linear Models

PubMed Central

Wang, Yifan; Liu, Aiyi; Mills, James L.; Boehnke, Michael; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Xiong, Momiao; Wu, Colin O.; Fan, Ruzong

2015-01-01

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai–Bartlett trace, Hotelling–Lawley trace, and Wilks’s Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. PMID:25809955

Pleiotropy analysis of quantitative traits at gene level by multivariate functional linear models.

PubMed

Wang, Yifan; Liu, Aiyi; Mills, James L; Boehnke, Michael; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao; Wu, Colin O; Fan, Ruzong

2015-05-01

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. © 2015 WILEY PERIODICALS, INC.

Quantitative genetic analysis of injury liability in infants and toddlers

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

Phillips, K.; Matheny, A.P. Jr.

1995-02-27

A threshold model of latent liability was applied to infant and toddler twin data on total count of injuries sustained during the interval from birth to 36 months of age. A quantitative genetic analysis of estimated twin correlations in injury liability indicated strong genetic dominance effects, but no additive genetic variance was detected. Because interpretations involving overdominance have little research support, the results may be due to low order epistasis or other interaction effects. Boys had more injuries than girls, but this effect was found only for groups whose parents were prompted and questioned in detail about their children`s injuries.more » Activity and impulsivity are two behavioral predictors of childhood injury, and the results are discussed in relation to animal research on infant and adult activity levels, and impulsivity in adult humans. Genetic epidemiological approaches to childhood injury should aid in targeting higher risk children for preventive intervention. 30 refs., 4 figs., 3 tabs.« less

Quantitative analysis of fatty-acid-based biofuels produced by wild-type and genetically engineered cyanobacteria by gas chromatography-mass spectrometry.

PubMed

Guan, Wenna; Zhao, Hui; Lu, Xuefeng; Wang, Cong; Yang, Menglong; Bai, Fali

2011-11-11

Simple and rapid quantitative determination of fatty-acid-based biofuels is greatly important for the study of genetic engineering progress for biofuels production by microalgae. Ideal biofuels produced from biological systems should be chemically similar to petroleum, like fatty-acid-based molecules including free fatty acids, fatty acid methyl esters, fatty acid ethyl esters, fatty alcohols and fatty alkanes. This study founded a gas chromatography-mass spectrometry (GC-MS) method for simultaneous quantification of seven free fatty acids, nine fatty acid methyl esters, five fatty acid ethyl esters, five fatty alcohols and three fatty alkanes produced by wild-type Synechocystis PCC 6803 and its genetically engineered strain. Data obtained from GC-MS analyses were quantified using internal standard peak area comparisons. The linearity, limit of detection (LOD) and precision (RSD) of the method were evaluated. The results demonstrated that fatty-acid-based biofuels can be directly determined by GC-MS without derivation. Therefore, rapid and reliable quantitative analysis of fatty-acid-based biofuels produced by wild-type and genetically engineered cyanobacteria can be achieved using the GC-MS method founded in this work. Copyright © 2011 Elsevier B.V. All rights reserved.

Systematic profiling of Caenorhabditis elegans locomotive behaviors reveals additional components in G-protein Gαq signaling.

PubMed

Yu, Hui; Aleman-Meza, Boanerges; Gharib, Shahla; Labocha, Marta K; Cronin, Christopher J; Sternberg, Paul W; Zhong, Weiwei

2013-07-16

Genetic screens have been widely applied to uncover genetic mechanisms of movement disorders. However, most screens rely on human observations of qualitative differences. Here we demonstrate the application of an automatic imaging system to conduct a quantitative screen for genes regulating the locomotive behavior in Caenorhabditis elegans. Two hundred twenty-seven neuronal signaling genes with viable homozygous mutants were selected for this study. We tracked and recorded each animal for 4 min and analyzed over 4,400 animals of 239 genotypes to obtain a quantitative, 10-parameter behavioral profile for each genotype. We discovered 87 genes whose inactivation causes movement defects, including 50 genes that had never been associated with locomotive defects. Computational analysis of the high-content behavioral profiles predicted 370 genetic interactions among these genes. Network partition revealed several functional modules regulating locomotive behaviors, including sensory genes that detect environmental conditions, genes that function in multiple types of excitable cells, and genes in the signaling pathway of the G protein Gαq, a protein that is essential for animal life and behavior. We developed quantitative epistasis analysis methods to analyze the locomotive profiles and validated the prediction of the γ isoform of phospholipase C as a component in the Gαq pathway. These results provided a system-level understanding of how neuronal signaling genes coordinate locomotive behaviors. This study also demonstrated the power of quantitative approaches in genetic studies.

The Quantitative Basis of the Arabidopsis Innate Immune System to Endemic Pathogens Depends on Pathogen Genetics

PubMed Central

Corwin, Jason A.; Copeland, Daniel; Feusier, Julie; Subedy, Anushriya; Eshbaugh, Robert; Palmer, Christine; Maloof, Julin; Kliebenstein, Daniel J.

2016-01-01

The most established model of the eukaryotic innate immune system is derived from examples of large effect monogenic quantitative resistance to pathogens. However, many host-pathogen interactions involve many genes of small to medium effect and exhibit quantitative resistance. We used the Arabidopsis-Botrytis pathosystem to explore the quantitative genetic architecture underlying host innate immune system in a population of Arabidopsis thaliana. By infecting a diverse panel of Arabidopsis accessions with four phenotypically and genotypically distinct isolates of the fungal necrotroph B. cinerea, we identified a total of 2,982 genes associated with quantitative resistance using lesion area and 3,354 genes associated with camalexin production as measures of the interaction. Most genes were associated with resistance to a specific Botrytis isolate, which demonstrates the influence of pathogen genetic variation in analyzing host quantitative resistance. While known resistance genes, such as receptor-like kinases (RLKs) and nucleotide-binding site leucine-rich repeat proteins (NLRs), were found to be enriched among associated genes, they only account for a small fraction of the total genes associated with quantitative resistance. Using publically available co-expression data, we condensed the quantitative resistance associated genes into co-expressed gene networks. GO analysis of these networks implicated several biological processes commonly connected to disease resistance, including defense hormone signaling and ROS production, as well as novel processes, such as leaf development. Validation of single gene T-DNA knockouts in a Col-0 background demonstrate a high success rate (60%) when accounting for differences in environmental and Botrytis genetic variation. This study shows that the genetic architecture underlying host innate immune system is extremely complex and is likely able to sense and respond to differential virulence among pathogen genotypes. PMID:26866607

The Quantitative Basis of the Arabidopsis Innate Immune System to Endemic Pathogens Depends on Pathogen Genetics.

PubMed

Corwin, Jason A; Copeland, Daniel; Feusier, Julie; Subedy, Anushriya; Eshbaugh, Robert; Palmer, Christine; Maloof, Julin; Kliebenstein, Daniel J

2016-02-01

The most established model of the eukaryotic innate immune system is derived from examples of large effect monogenic quantitative resistance to pathogens. However, many host-pathogen interactions involve many genes of small to medium effect and exhibit quantitative resistance. We used the Arabidopsis-Botrytis pathosystem to explore the quantitative genetic architecture underlying host innate immune system in a population of Arabidopsis thaliana. By infecting a diverse panel of Arabidopsis accessions with four phenotypically and genotypically distinct isolates of the fungal necrotroph B. cinerea, we identified a total of 2,982 genes associated with quantitative resistance using lesion area and 3,354 genes associated with camalexin production as measures of the interaction. Most genes were associated with resistance to a specific Botrytis isolate, which demonstrates the influence of pathogen genetic variation in analyzing host quantitative resistance. While known resistance genes, such as receptor-like kinases (RLKs) and nucleotide-binding site leucine-rich repeat proteins (NLRs), were found to be enriched among associated genes, they only account for a small fraction of the total genes associated with quantitative resistance. Using publically available co-expression data, we condensed the quantitative resistance associated genes into co-expressed gene networks. GO analysis of these networks implicated several biological processes commonly connected to disease resistance, including defense hormone signaling and ROS production, as well as novel processes, such as leaf development. Validation of single gene T-DNA knockouts in a Col-0 background demonstrate a high success rate (60%) when accounting for differences in environmental and Botrytis genetic variation. This study shows that the genetic architecture underlying host innate immune system is extremely complex and is likely able to sense and respond to differential virulence among pathogen genotypes.

Correlation of genetic risk and messenger RNA expression in a Th17/IL23 pathway analysis in inflammatory bowel disease.

PubMed

Fransen, Karin; van Sommeren, Suzanne; Westra, Harm-Jan; Veenstra, Monique; Lamberts, Letitia E; Modderman, Rutger; Dijkstra, Gerard; Fu, Jingyuan; Wijmenga, Cisca; Franke, Lude; Weersma, Rinse K; van Diemen, Cleo C

2014-05-01

The Th17/IL23 pathway has both genetically and biologically been implicated in the pathogenesis of the inflammatory bowel diseases (IBD), Crohn's disease, and ulcerative colitis. So far, it is unknown whether and how associated risk variants affect expression of the genes encoding for Th17/IL23 pathway proteins. Ten IBD-associated SNPs residing near Th17/IL23 genes were used to construct a genetic risk model in 753 Dutch IBD cases and 1045 controls. In an independent cohort of 40 Crohn's disease, 40 ulcerative colitis, and 40 controls, the genetic risk load and presence of IBD were correlated to quantitative PCR-generated messenger RNA (mRNA) expression of 9 representative Th17/IL23 genes in both unstimulated and PMA/CaLo stimulated peripheral blood mononuclear cells. In 1240 individuals with various immunological diseases with whole genome genotype and mRNA-expression data, we also assessed correlation between genetic risk load and differential mRNA expression and sought for SNPs affecting expression of all currently known Th17/IL23 pathway genes (cis-expression quantitative trait locus). The presence of IBD, but not the genetic risk load, was correlated to differential mRNA expression for IL6 in unstimulated peripheral blood mononuclear cells and to IL23A and RORC in response to stimulation. The cis-expression quantitative trait locus analysis showed little evidence for correlation between genetic risk load and mRNA expression of Th17/IL23 genes, because we identified for only 2 of 22 Th17/IL23 genes a cis-expression quantitative trait locus single nucleotide polymorphism that is also associated to IBD (STAT3 and CCR6). Our results suggest that only the presence of IBD and not the genetic risk load alters mRNA expression levels of IBD-associated Th17/IL23 genes.

Exploring and Harnessing Haplotype Diversity to Improve Yield Stability in Crops.

PubMed

Qian, Lunwen; Hickey, Lee T; Stahl, Andreas; Werner, Christian R; Hayes, Ben; Snowdon, Rod J; Voss-Fels, Kai P

2017-01-01

In order to meet future food, feed, fiber, and bioenergy demands, global yields of all major crops need to be increased significantly. At the same time, the increasing frequency of extreme weather events such as heat and drought necessitates improvements in the environmental resilience of modern crop cultivars. Achieving sustainably increase yields implies rapid improvement of quantitative traits with a very complex genetic architecture and strong environmental interaction. Latest advances in genome analysis technologies today provide molecular information at an ultrahigh resolution, revolutionizing crop genomic research, and paving the way for advanced quantitative genetic approaches. These include highly detailed assessment of population structure and genotypic diversity, facilitating the identification of selective sweeps and signatures of directional selection, dissection of genetic variants that underlie important agronomic traits, and genomic selection (GS) strategies that not only consider major-effect genes. Single-nucleotide polymorphism (SNP) markers today represent the genotyping system of choice for crop genetic studies because they occur abundantly in plant genomes and are easy to detect. SNPs are typically biallelic, however, hence their information content compared to multiallelic markers is low, limiting the resolution at which SNP-trait relationships can be delineated. An efficient way to overcome this limitation is to construct haplotypes based on linkage disequilibrium, one of the most important features influencing genetic analyses of crop genomes. Here, we give an overview of the latest advances in genomics-based haplotype analyses in crops, highlighting their importance in the context of polyploidy and genome evolution, linkage drag, and co-selection. We provide examples of how haplotype analyses can complement well-established quantitative genetics frameworks, such as quantitative trait analysis and GS, ultimately providing an effective tool to equip modern crops with environment-tailored characteristics.

Single-Cell Quantitative PCR: Advances and Potential in Cancer Diagnostics.

PubMed

Ok, Chi Young; Singh, Rajesh R; Salim, Alaa A

2016-01-01

Tissues are heterogeneous in their components. If cells of interest are a minor population of collected tissue, it would be difficult to obtain genetic or genomic information of the interested cell population with conventional genomic DNA extraction from the collected tissue. Single-cell DNA analysis is important in the analysis of genetics of cell clonality, genetic anticipation, and single-cell DNA polymorphisms. Single-cell PCR using Single Cell Ampligrid/GeXP platform is described in this chapter.

Comparative genetic analysis of lint yield and fiber quality among single, three-way, and double crosses in upland cotton

USDA-ARS?s Scientific Manuscript database

Decisions on the appropriate crossing systems to employ for genetic improvement of quantitative traits are critical in cotton breeding. Determination of genetic variance for lint yield and fiber quality in three different crossing schemes, i.e., single cross (SC), three-way cross (TWC), and double ...

Joint analysis of binary and quantitative traits with data sharing and outcome-dependent sampling.

PubMed

Zheng, Gang; Wu, Colin O; Kwak, Minjung; Jiang, Wenhua; Joo, Jungnam; Lima, Joao A C

2012-04-01

We study the analysis of a joint association between a genetic marker with both binary (case-control) and quantitative (continuous) traits, where the quantitative trait values are only available for the cases due to data sharing and outcome-dependent sampling. Data sharing becomes common in genetic association studies, and the outcome-dependent sampling is the consequence of data sharing, under which a phenotype of interest is not measured for some subgroup. The trend test (or Pearson's test) and F-test are often, respectively, used to analyze the binary and quantitative traits. Because of the outcome-dependent sampling, the usual F-test can be applied using the subgroup with the observed quantitative traits. We propose a modified F-test by also incorporating the genotype frequencies of the subgroup whose traits are not observed. Further, a combination of this modified F-test and Pearson's test is proposed by Fisher's combination of their P-values as a joint analysis. Because of the correlation of the two analyses, we propose to use a Gamma (scaled chi-squared) distribution to fit the asymptotic null distribution for the joint analysis. The proposed modified F-test and the joint analysis can also be applied to test single trait association (either binary or quantitative trait). Through simulations, we identify the situations under which the proposed tests are more powerful than the existing ones. Application to a real dataset of rheumatoid arthritis is presented. © 2012 Wiley Periodicals, Inc.

Using multiple PCR and CE with chemiluminescence detection for simultaneous qualitative and quantitative analysis of genetically modified organism.

PubMed

Guo, Longhua; Qiu, Bin; Chi, Yuwu; Chen, Guonan

2008-09-01

In this paper, an ultrasensitive CE-CL detection system coupled with a novel double-on-column coaxial flow detection interface was developed for the detection of PCR products. A reliable procedure based on this system had been demonstrated for qualitative and quantitative analysis of genetically modified organism-the detection of Roundup Ready Soy (RRS) samples was presented as an example. The promoter, terminator, function and two reference genes of RRS were amplified with multiplex PCR simultaneously. After that, the multiplex PCR products were labeled with acridinium ester at the 5'-terminal through an amino modification and then analyzed by the proposed CE-CL system. Reproducibility of analysis times and peak heights for the CE-CL analysis were determined to be better than 0.91 and 3.07% (RSD, n=15), respectively, for three consecutive days. It was shown that this method could accurately and qualitatively detect RRS standards and the simulative samples. The evaluation in terms of quantitative analysis of RRS provided by this new method was confirmed by comparing our assay results with those of the standard real-time quantitative PCR (RT-QPCR) using SYBR Green I dyes. The results showed a good coherence between the two methods. This approach demonstrated the possibility for accurate qualitative and quantitative detection of GM plants in a single run.

Effect of genetic algorithm as a variable selection method on different chemometric models applied for the analysis of binary mixture of amoxicillin and flucloxacillin: A comparative study

NASA Astrophysics Data System (ADS)

Attia, Khalid A. M.; Nassar, Mohammed W. I.; El-Zeiny, Mohamed B.; Serag, Ahmed

2016-03-01

Different chemometric models were applied for the quantitative analysis of amoxicillin (AMX), and flucloxacillin (FLX) in their binary mixtures, namely, partial least squares (PLS), spectral residual augmented classical least squares (SRACLS), concentration residual augmented classical least squares (CRACLS) and artificial neural networks (ANNs). All methods were applied with and without variable selection procedure (genetic algorithm GA). The methods were used for the quantitative analysis of the drugs in laboratory prepared mixtures and real market sample via handling the UV spectral data. Robust and simpler models were obtained by applying GA. The proposed methods were found to be rapid, simple and required no preliminary separation steps.

A Chromosome-Scale Assembly of the Bactrocera cucurbitae Genome Provides Insight to the Genetic Basis of white pupae

PubMed Central

Sim, Sheina B.; Geib, Scott M.

2017-01-01

Genetic sexing strains (GSS) used in sterile insect technique (SIT) programs are textbook examples of how classical Mendelian genetics can be directly implemented in the management of agricultural insect pests. Although the foundation of traditionally developed GSS are single locus, autosomal recessive traits, their genetic basis are largely unknown. With the advent of modern genomic techniques, the genetic basis of sexing traits in GSS can now be further investigated. This study is the first of its kind to integrate traditional genetic techniques with emerging genomics to characterize a GSS using the tephritid fruit fly pest Bactrocera cucurbitae as a model. These techniques include whole-genome sequencing, the development of a mapping population and linkage map, and quantitative trait analysis. The experiment designed to map the genetic sexing trait in B. cucurbitae, white pupae (wp), also enabled the generation of a chromosome-scale genome assembly by integrating the linkage map with the assembly. Quantitative trait loci analysis revealed SNP loci near position 42 MB on chromosome 3 to be tightly linked to wp. Gene annotation and synteny analysis show a near perfect relationship between chromosomes in B. cucurbitae and Muller elements A–E in Drosophila melanogaster. This chromosome-scale genome assembly is complete, has high contiguity, was generated using a minimal input DNA, and will be used to further characterize the genetic mechanisms underlying wp. Knowledge of the genetic basis of genetic sexing traits can be used to improve SIT in this species and expand it to other economically important Diptera. PMID:28450369

Current and future developments in patents for quantitative trait loci in dairy cattle.

PubMed

Weller, Joel I

2007-01-01

Many studies have proposed that rates of genetic gain in dairy cattle can be increased by direct selection on the individual quantitative loci responsible for the genetic variation in these traits, or selection on linked genetic markers. The development of DNA-level genetic markers has made detection of QTL nearly routine in all major livestock species. The studies that attempted to detect genes affecting quantitative traits can be divided into two categories: analysis of candidate genes, and genome scans based on within-family genetic linkage. To date, 12 patent cooperative treaty (PCT) and US patents have been registered for DNA sequences claimed to be associated with effects on economic traits in dairy cattle. All claim effects on milk production, but other traits are also included in some of the claims. Most of the sequences found by the candidate gene approach are of dubious validity, and have been repeated in only very few independent studies. The two missense mutations on chromosomes 6 and 14 affecting milk concentration derived from genome scans are more solidly based, but the claims are also disputed. A few PCT in dairy cattle are commercialized as genetic tests where commercial dairy farmers are the target market.

A Quantitative Comparison of the Similarity between Genes and Geography in Worldwide Human Populations

PubMed Central

Wang, Chaolong; Zöllner, Sebastian; Rosenberg, Noah A.

2012-01-01

Multivariate statistical techniques such as principal components analysis (PCA) and multidimensional scaling (MDS) have been widely used to summarize the structure of human genetic variation, often in easily visualized two-dimensional maps. Many recent studies have reported similarity between geographic maps of population locations and MDS or PCA maps of genetic variation inferred from single-nucleotide polymorphisms (SNPs). However, this similarity has been evident primarily in a qualitative sense; and, because different multivariate techniques and marker sets have been used in different studies, it has not been possible to formally compare genetic variation datasets in terms of their levels of similarity with geography. In this study, using genome-wide SNP data from 128 populations worldwide, we perform a systematic analysis to quantitatively evaluate the similarity of genes and geography in different geographic regions. For each of a series of regions, we apply a Procrustes analysis approach to find an optimal transformation that maximizes the similarity between PCA maps of genetic variation and geographic maps of population locations. We consider examples in Europe, Sub-Saharan Africa, Asia, East Asia, and Central/South Asia, as well as in a worldwide sample, finding that significant similarity between genes and geography exists in general at different geographic levels. The similarity is highest in our examples for Asia and, once highly distinctive populations have been removed, Sub-Saharan Africa. Our results provide a quantitative assessment of the geographic structure of human genetic variation worldwide, supporting the view that geography plays a strong role in giving rise to human population structure. PMID:22927824

A quantitative comparison of the similarity between genes and geography in worldwide human populations.

PubMed

Wang, Chaolong; Zöllner, Sebastian; Rosenberg, Noah A

2012-08-01

Multivariate statistical techniques such as principal components analysis (PCA) and multidimensional scaling (MDS) have been widely used to summarize the structure of human genetic variation, often in easily visualized two-dimensional maps. Many recent studies have reported similarity between geographic maps of population locations and MDS or PCA maps of genetic variation inferred from single-nucleotide polymorphisms (SNPs). However, this similarity has been evident primarily in a qualitative sense; and, because different multivariate techniques and marker sets have been used in different studies, it has not been possible to formally compare genetic variation datasets in terms of their levels of similarity with geography. In this study, using genome-wide SNP data from 128 populations worldwide, we perform a systematic analysis to quantitatively evaluate the similarity of genes and geography in different geographic regions. For each of a series of regions, we apply a Procrustes analysis approach to find an optimal transformation that maximizes the similarity between PCA maps of genetic variation and geographic maps of population locations. We consider examples in Europe, Sub-Saharan Africa, Asia, East Asia, and Central/South Asia, as well as in a worldwide sample, finding that significant similarity between genes and geography exists in general at different geographic levels. The similarity is highest in our examples for Asia and, once highly distinctive populations have been removed, Sub-Saharan Africa. Our results provide a quantitative assessment of the geographic structure of human genetic variation worldwide, supporting the view that geography plays a strong role in giving rise to human population structure.

Quantitative descriptions of generalized arousal, an elementary function of the vertebrate brain

PubMed Central

Quinkert, Amy Wells; Vimal, Vivek; Weil, Zachary M.; Reeke, George N.; Schiff, Nicholas D.; Banavar, Jayanth R.; Pfaff, Donald W.

2011-01-01

We review a concept of the most primitive, fundamental function of the vertebrate CNS, generalized arousal (GA). Three independent lines of evidence indicate the existence of GA: statistical, genetic, and mechanistic. Here we ask, is this concept amenable to quantitative analysis? Answering in the affirmative, four quantitative approaches have proven useful: (i) factor analysis, (ii) information theory, (iii) deterministic chaos, and (iv) application of a Gaussian equation. It strikes us that, to date, not just one but at least four different quantitative approaches seem necessary for describing different aspects of scientific work on GA. PMID:21555568

IWGT report on quantitative approaches to genotoxicity risk ...

EPA Pesticide Factsheets

This is the second of two reports from the International Workshops on Genotoxicity Testing (IWGT) Working Group on Quantitative Approaches to Genetic Toxicology Risk Assessment (the QWG). The first report summarized the discussions and recommendations of the QWG related to the need for quantitative dose–response analysis of genetic toxicology data, the existence and appropriate evaluation of threshold responses, and methods to analyze exposure-response relationships and derive points of departure (PoDs) from which acceptable exposure levels could be determined. This report summarizes the QWG discussions and recommendations regarding appropriate approaches to evaluate exposure-related risks of genotoxic damage, including extrapolation below identified PoDs and across test systems and species. Recommendations include the selection of appropriate genetic endpoints and target tissues, uncertainty factors and extrapolation methods to be considered, the importance and use of information on mode of action, toxicokinetics, metabolism, and exposure biomarkers when using quantitative exposure-response data to determine acceptable exposure levels in human populations or to assess the risk associated with known or anticipated exposures. The empirical relationship between genetic damage (mutation and chromosomal aberration) and cancer in animal models was also examined. It was concluded that there is a general correlation between cancer induction and mutagenic and/or clast

Functional linear models for association analysis of quantitative traits.

PubMed

Fan, Ruzong; Wang, Yifan; Mills, James L; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao

2013-11-01

Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F-distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT-O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT-O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study. © 2013 WILEY PERIODICALS, INC.

A simple bias correction in linear regression for quantitative trait association under two-tail extreme selection.

PubMed

Kwan, Johnny S H; Kung, Annie W C; Sham, Pak C

2011-09-01

Selective genotyping can increase power in quantitative trait association. One example of selective genotyping is two-tail extreme selection, but simple linear regression analysis gives a biased genetic effect estimate. Here, we present a simple correction for the bias.

Systematic exploration of essential yeast gene function with temperature-sensitive mutants

PubMed Central

Li, Zhijian; Vizeacoumar, Franco J; Bahr, Sondra; Li, Jingjing; Warringer, Jonas; Vizeacoumar, Frederick S; Min, Renqiang; VanderSluis, Benjamin; Bellay, Jeremy; DeVit, Michael; Fleming, James A; Stephens, Andrew; Haase, Julian; Lin, Zhen-Yuan; Baryshnikova, Anastasia; Lu, Hong; Yan, Zhun; Jin, Ke; Barker, Sarah; Datti, Alessandro; Giaever, Guri; Nislow, Corey; Bulawa, Chris; Myers, Chad L; Costanzo, Michael; Gingras, Anne-Claude; Zhang, Zhaolei; Blomberg, Anders; Bloom, Kerry; Andrews, Brenda; Boone, Charles

2012-01-01

Conditional temperature-sensitive (ts) mutations are valuable reagents for studying essential genes in the yeast Saccharomyces cerevisiae. We constructed 787 ts strains, covering 497 (~45%) of the 1,101 essential yeast genes, with ~30% of the genes represented by multiple alleles. All of the alleles are integrated into their native genomic locus in the S288C common reference strain and are linked to a kanMX selectable marker, allowing further genetic manipulation by synthetic genetic array (SGA)–based, high-throughput methods. We show two such manipulations: barcoding of 440 strains, which enables chemical-genetic suppression analysis, and the construction of arrays of strains carrying different fluorescent markers of subcellular structure, which enables quantitative analysis of phenotypes using high-content screening. Quantitative analysis of a GFP-tubulin marker identified roles for cohesin and condensin genes in spindle disassembly. This mutant collection should facilitate a wide range of systematic studies aimed at understanding the functions of essential genes. PMID:21441928

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.

Quantitative and Comparative Profiling of Protease Substrates through a Genetically Encoded Multifunctional Photocrosslinker.

PubMed

He, Dan; Xie, Xiao; Yang, Fan; Zhang, Heng; Su, Haomiao; Ge, Yun; Song, Haiping; Chen, Peng R

2017-11-13

A genetically encoded, multifunctional photocrosslinker was developed for quantitative and comparative proteomics. By bearing a bioorthogonal handle and a releasable linker in addition to its photoaffinity warhead, this probe enables the enrichment of transient and low-abundance prey proteins after intracellular photocrosslinking and prey-bait separation, which can be subject to stable isotope dimethyl labeling and mass spectrometry analysis. This quantitative strategy (termed isoCAPP) allowed a comparative proteomic approach to be adopted to identify the proteolytic substrates of an E. coli protease-chaperone dual machinery DegP. Two newly identified substrates were subsequently confirmed by proteolysis experiments. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Genetic and Quantitative Trait Locus Analysis for Bio-Oil Compounds after Fast Pyrolysis in Maize Cobs.

PubMed

Jeffrey, Brandon; Kuzhiyil, Najeeb; de Leon, Natalia; Lübberstedt, Thomas

2016-01-01

Fast pyrolysis has been identified as one of the biorenewable conversion platforms that could be a part of an alternative energy future, but it has not yet received the same attention as cellulosic ethanol in the analysis of genetic inheritance within potential feedstocks such as maize. Ten bio-oil compounds were measured via pyrolysis/gas chromatography-mass spectrometry (Py/GC-MS) in maize cobs. 184 recombinant inbred lines (RILs) of the intermated B73 x Mo17 (IBM) Syn4 population were analyzed in two environments, using 1339 markers, for quantitative trait locus (QTL) mapping. QTL mapping was performed using composite interval mapping with significance thresholds established by 1000 permutations at α = 0.05. 50 QTL were found in total across those ten traits with R2 values ranging from 1.7 to 5.8%, indicating a complex quantitative inheritance of these traits.

Interdependence of PRECIS Role Operators: A Quantitative Analysis of Their Associations.

ERIC Educational Resources Information Center

Mahapatra, Manoranjan; Biswas, Subal Chandra

1986-01-01

Analyzes associations among different role operators quantitatively by taking input strings from 200 abstracts, each related to subject fields of taxation, genetic psychology, and Shakespearean drama, and subjecting them to the Chi-square test. Significant associations by other differencing operators and connectives are discussed. A schema of role…

Quantitative mutant analysis of viral quasispecies by chip-based matrix-assisted laser desorption/ ionization time-of-flight mass spectrometry

PubMed Central

Amexis, Georgios; Oeth, Paul; Abel, Kenneth; Ivshina, Anna; Pelloquin, Francois; Cantor, Charles R.; Braun, Andreas; Chumakov, Konstantin

2001-01-01

RNA viruses exist as quasispecies, heterogeneous and dynamic mixtures of mutants having one or more consensus sequences. An adequate description of the genomic structure of such viral populations must include the consensus sequence(s) plus a quantitative assessment of sequence heterogeneities. For example, in quality control of live attenuated viral vaccines, the presence of even small quantities of mutants or revertants may indicate incomplete or unstable attenuation that may influence vaccine safety. Previously, we demonstrated the monitoring of oral poliovirus vaccine with the use of mutant analysis by PCR and restriction enzyme cleavage (MAPREC). In this report, we investigate genetic variation in live attenuated mumps virus vaccine by using both MAPREC and a platform (DNA MassArray) based on matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry. Mumps vaccines prepared from the Jeryl Lynn strain typically contain at least two distinct viral substrains, JL1 and JL2, which have been characterized by full length sequencing. We report the development of assays for characterizing sequence variants in these substrains and demonstrate their use in quantitative analysis of substrains and sequence variations in mixed virus cultures and mumps vaccines. The results obtained from both the MAPREC and MALDI-TOF methods showed excellent correlation. This suggests the potential utility of MALDI-TOF for routine quality control of live viral vaccines and for assessment of genetic stability and quantitative monitoring of genetic changes in other RNA viruses of clinical interest. PMID:11593021

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

Assessment of a Competency-Based Undergraduate Course on Genetic and Genomics.

PubMed

Kronk, Rebecca; Colbert, Alison; Lengetti, Evelyn

2017-08-24

In response to new demands in the nursing profession, an innovative undergraduate genetics course was designed based on the Essential Nursing Competencies and Curricula Guidelines for Genetics and Genomics. Reflective journaling and storytelling were used as major pedagogies, alongside more traditional approaches. Thematic content analysis of student reflections revealed transformational learning as the major theme emerging from genomic and genetic knowledge acquisition. Quantitative analyses of precourse/postcourse student self-assessments of competencies revealed significant findings.

Construction of a genetic linkage map and analysis of quantitative trait loci associated with the agronomically important traits of Pleurotus eryngii

Treesearch

Chak Han Im; Young-Hoon Park; Kenneth E. Hammel; Bokyung Park; Soon Wook Kwon; Hojin Ryu; Jae-San Ryu

2016-01-01

Breeding new strains with improved traits is a long-standing goal of mushroom breeders that can be expedited by marker-assisted selection (MAS). We constructed a genetic linkage map of Pleurotus eryngii based on segregation analysis of markers in postmeiotic monokaryons from KNR2312. In total, 256 loci comprising 226 simple sequence-repeat (SSR) markers, 2 mating-type...

Development and application of SINE multilocus and quantitative genetic markers to study oilseed rape (Brassica napus L.) crops.

PubMed

Allnutt, T R; Roper, K; Henry, C

2008-01-23

A genetic marker system based on the S1 Short Interspersed Elements (SINEs) in the important commercial crop, oilseed rape ( Brassica napus L.) has been developed. SINEs provided a successful multilocus, dominant marker system that was capable of clearly delineating winter- and spring-type crop varieties. Sixteen of 20 varieties tested showed unique profiles from the 17 polymorphic SINE markers generated. The 3' or 5' flank region of nine SINE markers were cloned, and DNA was sequenced. In addition, one putative pre-transposition SINE allele was cloned and sequenced. Two SINE flanking sequences were used to design real-time PCR assays. These quantitative SINE assays were applied to study the genetic structure of eight fields of oilseed rape crops. Studied fields were more genetically diverse than expected for the chosen loci (mean H T = 0.23). The spatial distribution of SINE marker frequencies was highly structured in some fields, suggesting locations of volunteer impurities within the crop. In one case, the assay identified a mislabeling of the crop variety. SINE markers were a useful tool for crop genetics, phylogenetics, variety identification, and purity analysis. The use and further application of quantitative, real-time PCR markers are discussed.

Improving power and robustness for detecting genetic association with extreme-value sampling design.

PubMed

Chen, Hua Yun; Li, Mingyao

2011-12-01

Extreme-value sampling design that samples subjects with extremely large or small quantitative trait values is commonly used in genetic association studies. Samples in such designs are often treated as "cases" and "controls" and analyzed using logistic regression. Such a case-control analysis ignores the potential dose-response relationship between the quantitative trait and the underlying trait locus and thus may lead to loss of power in detecting genetic association. An alternative approach to analyzing such data is to model the dose-response relationship by a linear regression model. However, parameter estimation from this model can be biased, which may lead to inflated type I errors. We propose a robust and efficient approach that takes into consideration of both the biased sampling design and the potential dose-response relationship. Extensive simulations demonstrate that the proposed method is more powerful than the traditional logistic regression analysis and is more robust than the linear regression analysis. We applied our method to the analysis of a candidate gene association study on high-density lipoprotein cholesterol (HDL-C) which includes study subjects with extremely high or low HDL-C levels. Using our method, we identified several SNPs showing a stronger evidence of association with HDL-C than the traditional case-control logistic regression analysis. Our results suggest that it is important to appropriately model the quantitative traits and to adjust for the biased sampling when dose-response relationship exists in extreme-value sampling designs. © 2011 Wiley Periodicals, Inc.

Analysis of conditional genetic effects and variance components in developmental genetics.

PubMed

Zhu, J

1995-12-01

A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.

Analysis of Conditional Genetic Effects and Variance Components in Developmental Genetics

PubMed Central

Zhu, J.

1995-01-01

A genetic model with additive-dominance effects and genotype X environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t - 1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects. PMID:8601500

Smoothing of the bivariate LOD score for non-normal quantitative traits.

PubMed

Buil, Alfonso; Dyer, Thomas D; Almasy, Laura; Blangero, John

2005-12-30

Variance component analysis provides an efficient method for performing linkage analysis for quantitative traits. However, type I error of variance components-based likelihood ratio testing may be affected when phenotypic data are non-normally distributed (especially with high values of kurtosis). This results in inflated LOD scores when the normality assumption does not hold. Even though different solutions have been proposed to deal with this problem with univariate phenotypes, little work has been done in the multivariate case. We present an empirical approach to adjust the inflated LOD scores obtained from a bivariate phenotype that violates the assumption of normality. Using the Collaborative Study on the Genetics of Alcoholism data available for the Genetic Analysis Workshop 14, we show how bivariate linkage analysis with leptokurtotic traits gives an inflated type I error. We perform a novel correction that achieves acceptable levels of type I error.

Harnessing quantitative genetics and genomics for understanding and improving complex traits in crops

USDA-ARS?s Scientific Manuscript database

Classical quantitative genetics aids crop improvement by providing the means to estimate heritability, genetic correlations, and predicted responses to various selection schemes. Genomics has the potential to aid quantitative genetics and applied crop improvement programs via large-scale, high-thro...

Endogenous Reference Genes and Their Quantitative Real-Time PCR Assays for Genetically Modified Bread Wheat (Triticum aestivum L.) Detection.

PubMed

Yang, Litao; Quan, Sheng; Zhang, Dabing

2017-01-01

Endogenous reference genes (ERG) and their derivate analytical methods are standard requirements for analysis of genetically modified organisms (GMOs). Development and validation of suitable ERGs is the primary step for establishing assays that monitoring the genetically modified (GM) contents in food/feed samples. Herein, we give a review of the ERGs currently used for GM wheat analysis, such as ACC1, PKABA1, ALMT1, and Waxy-D1, as well as their performances in GM wheat analysis. Also, we discussed one model for developing and validating one ideal RG for one plant species based on our previous research work.

QTL meta-analysis provides a comprehensive view of loci controlling partial resistance to Aphanomyces euteiches in four sources of resistance in pea

USDA-ARS?s Scientific Manuscript database

More knowledge about diversity of Quantitative Trait Loci (QTL) controlling polygenic disease resistance in natural genetic variation of crop species is required for durably improving plant genetic resistances to pathogens. Polygenic partial resistance to Aphanomyces root rot, due to Aphanomcyces eu...

Testing for biases in selection on avian reproductive traits and partitioning direct and indirect selection using quantitative genetic models.

PubMed

Reed, Thomas E; Gienapp, Phillip; Visser, Marcel E

2016-10-01

Key life history traits such as breeding time and clutch size are frequently both heritable and under directional selection, yet many studies fail to document microevolutionary responses. One general explanation is that selection estimates are biased by the omission of correlated traits that have causal effects on fitness, but few valid tests of this exist. Here, we show, using a quantitative genetic framework and six decades of life-history data on two free-living populations of great tits Parus major, that selection estimates for egg-laying date and clutch size are relatively unbiased. Predicted responses to selection based on the Robertson-Price Identity were similar to those based on the multivariate breeder's equation (MVBE), indicating that unmeasured covarying traits were not missing from the analysis. Changing patterns of phenotypic selection on these traits (for laying date, linked to climate change) therefore reflect changing selection on breeding values, and genetic constraints appear not to limit their independent evolution. Quantitative genetic analysis of correlational data from pedigreed populations can be a valuable complement to experimental approaches to help identify whether apparent associations between traits and fitness are biased by missing traits, and to parse the roles of direct versus indirect selection across a range of environments. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

An eQTL Analysis of Partial Resistance to Puccinia hordei in Barley

PubMed Central

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

2010-01-01

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

Genome-wide Linkage Analysis for Identifying Quantitative Trait Loci Involved in the Regulation of Lipoprotein a (Lpa) Levels

PubMed Central

López, Sonia; Buil, Alfonso; Ordoñez, Jordi; Souto, Juan Carlos; Almasy, Laura; Lathrop, Mark; Blangero, John; Blanco-Vaca, Francisco; Fontcuberta, Jordi; Soria, José Manuel

2009-01-01

Lipoprotein Lp(a) levels are highly heritable and are associated with cardiovascular risk. We performed a genome-wide linkage analysis to delineate the genomic regions that influence the concentration of Lp(a) in families from the Genetic Analysis of Idiopathic Thrombophilia (GAIT) Project. Lp(a) levels were measured in 387 individuals belonging to 21 extended Spanish families. A total of 485 DNA microsatellite markers were genotyped to provide a 7.1 cM genetic map. A variance component linkage method was used to evaluate linkage and to detect quantitative trait loci (QTLs). The main QTL that showed strong evidence of linkage with Lp(a) levels was located at the structural gene for apo(a) on Chromosome 6 (LOD score=13.8). Interestingly, another QTL influencing Lp(a) concentration was located on Chromosome 2 with a LOD score of 2.01. This region contains several candidate genes. One of them is the tissue factor pathway inhibitor (TFPI), which has antithrombotic action and also has the ability to bind lipoproteins. However, quantitative trait association analyses performed with 12 SNPs in TFPI gene revealed no association with Lp(a) levels. Our study confirms previous results on the genetic basis of Lp(a) levels. In addition, we report a new QTL on Chromosome 2 involved in the quantitative variation of Lp(a). These data should serve as the basis for further detection of candidate genes and to elucidate the relationship between the concentration of Lp(a) and cardiovascular risk. PMID:18560444

Interlaboratory validation of quantitative duplex real-time PCR method for screening analysis of genetically modified maize.

PubMed

Takabatake, Reona; Koiwa, Tomohiro; Kasahara, Masaki; Takashima, Kaori; Futo, Satoshi; Minegishi, Yasutaka; Akiyama, Hiroshi; Teshima, Reiko; Oguchi, Taichi; Mano, Junichi; Furui, Satoshi; Kitta, Kazumi

2011-01-01

To reduce the cost and time required to routinely perform the genetically modified organism (GMO) test, we developed a duplex quantitative real-time PCR method for a screening analysis simultaneously targeting an event-specific segment for GA21 and Cauliflower Mosaic Virus 35S promoter (P35S) segment [Oguchi et al., J. Food Hyg. Soc. Japan, 50, 117-125 (2009)]. To confirm the validity of the method, an interlaboratory collaborative study was conducted. In the collaborative study, conversion factors (Cfs), which are required to calculate the GMO amount (%), were first determined for two real-time PCR instruments, the ABI PRISM 7900HT and the ABI PRISM 7500. A blind test was then conducted. The limit of quantitation for both GA21 and P35S was estimated to be 0.5% or less. The trueness and precision were evaluated as the bias and reproducibility of the relative standard deviation (RSD(R)). The determined bias and RSD(R) were each less than 25%. We believe the developed method would be useful for the practical screening analysis of GM maize.

Capturing neutral and adaptive genetic diversity for conservation in a highly structured tree species.

PubMed

Rodríguez-Quilón, Isabel; Santos-Del-Blanco, Luis; Serra-Varela, María Jesús; Koskela, Jarkko; González-Martínez, Santiago C; Alía, Ricardo

2016-10-01

Preserving intraspecific genetic diversity is essential for long-term forest sustainability in a climate change scenario. Despite that, genetic information is largely neglected in conservation planning, and how conservation units should be defined is still heatedly debated. Here, we use maritime pine (Pinus pinaster Ait.), an outcrossing long-lived tree with a highly fragmented distribution in the Mediterranean biodiversity hotspot, to prove the importance of accounting for genetic variation, of both neutral molecular markers and quantitative traits, to define useful conservation units. Six gene pools associated to distinct evolutionary histories were identified within the species using 12 microsatellites and 266 single nucleotide polymorphisms (SNPs). In addition, height and survival standing variation, their genetic control, and plasticity were assessed in a multisite clonal common garden experiment (16 544 trees). We found high levels of quantitative genetic differentiation within previously defined neutral gene pools. Subsequent cluster analysis and post hoc trait distribution comparisons allowed us to define 10 genetically homogeneous population groups with high evolutionary potential. They constitute the minimum number of units to be represented in a maritime pine dynamic conservation program. Our results uphold that the identification of conservation units below the species level should account for key neutral and adaptive components of genetic diversity, especially in species with strong population structure and complex evolutionary histories. The environmental zonation approach currently used by the pan-European genetic conservation strategy for forest trees would be largely improved by gradually integrating molecular and quantitative trait information, as data become available. © 2016 by the Ecological Society of America.

Genomic atlas of the human plasma proteome.

PubMed

Sun, Benjamin B; Maranville, Joseph C; Peters, James E; Stacey, David; Staley, James R; Blackshaw, James; Burgess, Stephen; Jiang, Tao; Paige, Ellie; Surendran, Praveen; Oliver-Williams, Clare; Kamat, Mihir A; Prins, Bram P; Wilcox, Sheri K; Zimmerman, Erik S; Chi, An; Bansal, Narinder; Spain, Sarah L; Wood, Angela M; Morrell, Nicholas W; Bradley, John R; Janjic, Nebojsa; Roberts, David J; Ouwehand, Willem H; Todd, John A; Soranzo, Nicole; Suhre, Karsten; Paul, Dirk S; Fox, Caroline S; Plenge, Robert M; Danesh, John; Runz, Heiko; Butterworth, Adam S

2018-06-01

Although plasma proteins have important roles in biological processes and are the direct targets of many drugs, the genetic factors that control inter-individual variation in plasma protein levels are not well understood. Here we characterize the genetic architecture of the human plasma proteome in healthy blood donors from the INTERVAL study. We identify 1,927 genetic associations with 1,478 proteins, a fourfold increase on existing knowledge, including trans associations for 1,104 proteins. To understand the consequences of perturbations in plasma protein levels, we apply an integrated approach that links genetic variation with biological pathway, disease, and drug databases. We show that protein quantitative trait loci overlap with gene expression quantitative trait loci, as well as with disease-associated loci, and find evidence that protein biomarkers have causal roles in disease using Mendelian randomization analysis. By linking genetic factors to diseases via specific proteins, our analyses highlight potential therapeutic targets, opportunities for matching existing drugs with new disease indications, and potential safety concerns for drugs under development.

Applications of population genetics to animal breeding, from wright, fisher and lush to genomic prediction.

PubMed

Hill, William G

2014-01-01

Although animal breeding was practiced long before the science of genetics and the relevant disciplines of population and quantitative genetics were known, breeding programs have mainly relied on simply selecting and mating the best individuals on their own or relatives' performance. This is based on sound quantitative genetic principles, developed and expounded by Lush, who attributed much of his understanding to Wright, and formalized in Fisher's infinitesimal model. Analysis at the level of individual loci and gene frequency distributions has had relatively little impact. Now with access to genomic data, a revolution in which molecular information is being used to enhance response with "genomic selection" is occurring. The predictions of breeding value still utilize multiple loci throughout the genome and, indeed, are largely compatible with additive and specifically infinitesimal model assumptions. I discuss some of the history and genetic issues as applied to the science of livestock improvement, which has had and continues to have major spin-offs into ideas and applications in other areas.

Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models

PubMed Central

Chiu, Chi-yang; Jung, Jeesun; Chen, Wei; Weeks, Daniel E; Ren, Haobo; Boehnke, Michael; Amos, Christopher I; Liu, Aiyi; Mills, James L; Ting Lee, Mei-ling; Xiong, Momiao; Fan, Ruzong

2017-01-01

To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai–Bartlett trace, Hotelling–Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied to analyze lipid traits in eight European cohorts. It is shown that it is more advantageous to perform multivariate analysis than univariate analysis in general, and it is more advantageous to perform meta-analysis of multiple studies instead of analyzing the individual studies separately. The proposed models require individual observations. The value of the current paper can be seen at least for two reasons: (a) the proposed methods can be applied to studies that have individual genotype data; (b) the proposed methods can be used as a criterion for future work that uses summary statistics to build test statistics to meta-analyze the data. PMID:28000696

Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models.

PubMed

Chiu, Chi-Yang; Jung, Jeesun; Chen, Wei; Weeks, Daniel E; Ren, Haobo; Boehnke, Michael; Amos, Christopher I; Liu, Aiyi; Mills, James L; Ting Lee, Mei-Ling; Xiong, Momiao; Fan, Ruzong

2017-02-01

To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied to analyze lipid traits in eight European cohorts. It is shown that it is more advantageous to perform multivariate analysis than univariate analysis in general, and it is more advantageous to perform meta-analysis of multiple studies instead of analyzing the individual studies separately. The proposed models require individual observations. The value of the current paper can be seen at least for two reasons: (a) the proposed methods can be applied to studies that have individual genotype data; (b) the proposed methods can be used as a criterion for future work that uses summary statistics to build test statistics to meta-analyze the data.

Effects of normalization on quantitative traits in association test

PubMed Central

2009-01-01

Background Quantitative trait loci analysis assumes that the trait is normally distributed. In reality, this is often not observed and one strategy is to transform the trait. However, it is not clear how much normality is required and which transformation works best in association studies. Results We performed simulations on four types of common quantitative traits to evaluate the effects of normalization using the logarithm, Box-Cox, and rank-based transformations. The impact of sample size and genetic effects on normalization is also investigated. Our results show that rank-based transformation gives generally the best and consistent performance in identifying the causal polymorphism and ranking it highly in association tests, with a slight increase in false positive rate. Conclusion For small sample size or genetic effects, the improvement in sensitivity for rank transformation outweighs the slight increase in false positive rate. However, for large sample size and genetic effects, normalization may not be necessary since the increase in sensitivity is relatively modest. PMID:20003414

Untargeted Metabolic Quantitative Trait Loci Analyses Reveal a Relationship between Primary Metabolism and Potato Tuber Quality1[W][OA

PubMed Central

Carreno-Quintero, Natalia; Acharjee, Animesh; Maliepaard, Chris; Bachem, Christian W.B.; Mumm, Roland; Bouwmeester, Harro; Visser, Richard G.F.; Keurentjes, Joost J.B.

2012-01-01

Recent advances in -omics technologies such as transcriptomics, metabolomics, and proteomics along with genotypic profiling have permitted dissection of the genetics of complex traits represented by molecular phenotypes in nonmodel species. To identify the genetic factors underlying variation in primary metabolism in potato (Solanum tuberosum), we have profiled primary metabolite content in a diploid potato mapping population, derived from crosses between S. tuberosum and wild relatives, using gas chromatography-time of flight-mass spectrometry. In total, 139 polar metabolites were detected, of which we identified metabolite quantitative trait loci for approximately 72% of the detected compounds. In order to obtain an insight into the relationships between metabolic traits and classical phenotypic traits, we also analyzed statistical associations between them. The combined analysis of genetic information through quantitative trait locus coincidence and the application of statistical learning methods provide information on putative indicators associated with the alterations in metabolic networks that affect complex phenotypic traits. PMID:22223596

MONITORING MYCOTOXIN PRODUCTION AT THE GENETIC LEVEL ON VARIOUS GROWTH SUBSTRATES USING QUANTITATIVE REVERSE TRANSCRIPTION POLYMERASE CHAIN REACTION?EXPERIMENT DESIGN

EPA Science Inventory

The paper describes a method of analyzing the production of mycotoxins at the genetic level by monitoring the intracellular levels of messenger RNA (mRNA). Initial work will focus on threshing out the mycotoxin gene clusters in Stachybotrys chartarum followed by analysis of toxin...

Early rooting of dormant hardwood cuttings of Populus: analysis of quantitative genetics and genotype x environment interactions

Treesearch

Ronald S., Jr. Zalesny; Don E. Riemenschneider; Richard B. Hall

2005-01-01

Rooting of hardwood cuttings is under strong genetic control, although genotype x environment interactions affect selection of promising genotypes. Our objectives were (1) to assess the variation in rooting ability among 21 Populus clones and (2) to examine genotype x environment interactions to refine clonal recommendations. The clones belonged to...

Genetic analysis of grain attributes, milling performance, and end-use quality traits in hard red spring wheat (Triticum aestivum L.)

USDA-ARS?s Scientific Manuscript database

Wheat kernel texture dictates U.S. wheat market class and culinary end-uses. Of interest to wheat breeders is to identify quantitative trait loci (QTL) for wheat kernel texture, milling performance, or end-use quality because it is imperative for wheat breeders to ascertain the genetic architecture ...

Variation in seed dormancy quantitative trait loci in Arabidopsis thaliana originating from one site.

PubMed

Silady, Rebecca A; Effgen, Sigi; Koornneef, Maarten; Reymond, Matthieu

2011-01-01

A Quantitative Trait Locus (QTL) analysis was performed using two novel Recombinant Inbred Line (RIL) populations, derived from the progeny between two Arabidopsis thaliana genotypes collected at the same site in Kyoto (Japan) crossed with the reference laboratory strain Landsberg erecta (Ler). We used these two RIL populations to determine the genetic basis of seed dormancy and flowering time, which are assumed to be the main traits controlling life history variation in Arabidopsis. The analysis revealed quantitative variation for seed dormancy that is associated with allelic variation at the seed dormancy QTL DOG1 (for Delay Of Germination 1) in one population and at DOG6 in both. These DOG QTL have been previously identified using mapping populations derived from accessions collected at different sites around the world. Genetic variation within a population may enhance its ability to respond accurately to variation within and between seasons. In contrast, variation for flowering time, which also segregated within each mapping population, is mainly governed by the same QTL.

Power Analysis of Artificial Selection Experiments Using Efficient Whole Genome Simulation of Quantitative Traits

PubMed Central

Kessner, Darren; Novembre, John

2015-01-01

Evolve and resequence studies combine artificial selection experiments with massively parallel sequencing technology to study the genetic basis for complex traits. In these experiments, individuals are selected for extreme values of a trait, causing alleles at quantitative trait loci (QTL) to increase or decrease in frequency in the experimental population. We present a new analysis of the power of artificial selection experiments to detect and localize quantitative trait loci. This analysis uses a simulation framework that explicitly models whole genomes of individuals, quantitative traits, and selection based on individual trait values. We find that explicitly modeling QTL provides qualitatively different insights than considering independent loci with constant selection coefficients. Specifically, we observe how interference between QTL under selection affects the trajectories and lengthens the fixation times of selected alleles. We also show that a substantial portion of the genetic variance of the trait (50–100%) can be explained by detected QTL in as little as 20 generations of selection, depending on the trait architecture and experimental design. Furthermore, we show that power depends crucially on the opportunity for recombination during the experiment. Finally, we show that an increase in power is obtained by leveraging founder haplotype information to obtain allele frequency estimates. PMID:25672748

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.

Quantitative autistic trait measurements index background genetic risk for ASD in Hispanic families.

PubMed

Page, Joshua; Constantino, John Nicholas; Zambrana, Katherine; Martin, Eden; Tunc, Ilker; Zhang, Yi; Abbacchi, Anna; Messinger, Daniel

2016-01-01

Recent studies have indicated that quantitative autistic traits (QATs) of parents reflect inherited liabilities that may index background genetic risk for clinical autism spectrum disorder (ASD) in their offspring. Moreover, preferential mating for QATs has been observed as a potential factor in concentrating autistic liabilities in some families across generations. Heretofore, intergenerational studies of QATs have focused almost exclusively on Caucasian populations-the present study explored these phenomena in a well-characterized Hispanic population. The present study examined QAT scores in siblings and parents of 83 Hispanic probands meeting research diagnostic criteria for ASD, and 64 non-ASD controls, using the Social Responsiveness Scale-2 (SRS-2). Ancestry of the probands was characterized by genotype, using information from 541,929 single nucleotide polymorphic markers. In families of Hispanic children with an ASD diagnosis, the pattern of quantitative trait correlations observed between ASD-affected children and their first-degree relatives (ICCs on the order of 0.20), between unaffected first-degree relatives in ASD-affected families (sibling/mother ICC = 0.36; sibling/father ICC = 0.53), and between spouses (mother/father ICC = 0.48) were in keeping with the influence of transmitted background genetic risk and strong preferential mating for variation in quantitative autistic trait burden. Results from analysis of ancestry-informative genetic markers among probands in this sample were consistent with that from other Hispanic populations. Quantitative autistic traits represent measurable indices of inherited liability to ASD in Hispanic families. The accumulation of autistic traits occurs within generations, between spouses, and across generations, among Hispanic families affected by ASD. The occurrence of preferential mating for QATs-the magnitude of which may vary across cultures-constitutes a mechanism by which background genetic liability for ASD can accumulate in a given family in successive generations.

Short Communication: Genetic linkage map of Cucurbita maxima with molecular and morphological markers.

PubMed

Ge, Y; Li, X; Yang, X X; Cui, C S; Qu, S P

2015-05-22

Cucurbita maxima is one of the most widely cultivated vegetables in China and exhibits distinct morphological characteristics. In this study, genetic linkage analysis with 57 simple-sequence repeats, 21 amplified fragment length polymorphisms, 3 random-amplified polymorphic DNA, and one morphological marker revealed 20 genetic linkage groups of C. maxima covering a genetic distance of 991.5 cM with an average of 12.1 cM between adjacent markers. Genetic linkage analysis identified the simple-sequence repeat marker 'PU078072' 5.9 cM away from the locus 'Rc', which controls rind color. The genetic map in the present study will be useful for better mapping, tagging, and cloning of quantitative trait loci/gene(s) affecting economically important traits and for breeding new varieties of C. maxima through marker-assisted selection.

Dissecting genetic architecture of grape proanthocyanidin composition through quantitative trait locus mapping

PubMed Central

2012-01-01

Background Proanthocyanidins (PAs), or condensed tannins, are flavonoid polymers, widespread throughout the plant kingdom, which provide protection against herbivores while conferring organoleptic and nutritive values to plant-derived foods, such as wine. However, the genetic basis of qualitative and quantitative PA composition variation is still poorly understood. To elucidate the genetic architecture of the complex grape PA composition, we first carried out quantitative trait locus (QTL) analysis on a 191-individual pseudo-F1 progeny. Three categories of PA variables were assessed: total content, percentages of constitutive subunits and composite ratio variables. For nine functional candidate genes, among which eight co-located with QTLs, we performed association analyses using a diversity panel of 141 grapevine cultivars in order to identify causal SNPs. Results Multiple QTL analysis revealed a total of 103 and 43 QTLs, respectively for seed and skin PA variables. Loci were mainly of additive effect while some loci were primarily of dominant effect. Results also showed a large involvement of pairwise epistatic interactions in shaping PA composition. QTLs for PA variables in skin and seeds differed in number, position, involvement of epistatic interaction and allelic effect, thus revealing different genetic determinisms for grape PA composition in seeds and skin. Association results were consistent with QTL analyses in most cases: four out of nine tested candidate genes (VvLAR1, VvMYBPA2, VvCHI1, VvMYBPA1) showed at least one significant association with PA variables, especially VvLAR1 revealed as of great interest for further functional investigation. Some SNP-phenotype associations were observed only in the diversity panel. Conclusions This study presents the first QTL analysis on grape berry PA composition with a comparison between skin and seeds, together with an association study. Our results suggest a complex genetic control for PA traits and different genetic architectures for grape PA composition between berry skin and seeds. This work also uncovers novel genomic regions for further investigation in order to increase our knowledge of the genetic basis of PA composition. PMID:22369244

Combining quantitative trait loci analysis with physiological models to predict genotype-specific transpiration rates.

PubMed

Reuning, Gretchen A; Bauerle, William L; Mullen, Jack L; McKay, John K

2015-04-01

Transpiration is controlled by evaporative demand and stomatal conductance (gs ), and there can be substantial genetic variation in gs . A key parameter in empirical models of transpiration is minimum stomatal conductance (g0 ), a trait that can be measured and has a large effect on gs and transpiration. In Arabidopsis thaliana, g0 exhibits both environmental and genetic variation, and quantitative trait loci (QTL) have been mapped. We used this information to create a genetically parameterized empirical model to predict transpiration of genotypes. For the parental lines, this worked well. However, in a recombinant inbred population, the predictions proved less accurate. When based only upon their genotype at a single g0 QTL, genotypes were less distinct than our model predicted. Follow-up experiments indicated that both genotype by environment interaction and a polygenic inheritance complicate the application of genetic effects into physiological models. The use of ecophysiological or 'crop' models for predicting transpiration of novel genetic lines will benefit from incorporating further knowledge of the genetic control and degree of independence of core traits/parameters underlying gs variation. © 2014 John Wiley & Sons Ltd.

Genetical genomics of Populus leaf shape variation

DOE PAGES

Drost, Derek R.; Puranik, Swati; Novaes, Evandro; ...

2015-06-30

Leaf morphology varies extensively among plant species and is under strong genetic control. Mutagenic screens in model systems have identified genes and established molecular mechanisms regulating leaf initiation, development, and shape. However, it is not known whether this diversity across plant species is related to naturally occurring variation at these genes. Quantitative trait locus (QTL) analysis has revealed a polygenic control for leaf shape variation in different species suggesting that loci discovered by mutagenesis may only explain part of the naturally occurring variation in leaf shape. Here we undertook a genetical genomics study in a poplar intersectional pseudo-backcross pedigree tomore » identify genetic factors controlling leaf shape. Here, the approach combined QTL discovery in a genetic linkage map anchored to the Populus trichocarpa reference genome sequence and transcriptome analysis.« less

Construction of a High-Density Genetic Map from RNA-Seq Data for an Arabidopsis Bay-0 × Shahdara RIL Population

PubMed Central

Serin, Elise A. R.; Snoek, L. B.; Nijveen, Harm; Willems, Leo A. J.; Jiménez-Gómez, Jose M.; Hilhorst, Henk W. M.; Ligterink, Wilco

2017-01-01

High-density genetic maps are essential for high resolution mapping of quantitative traits. Here, we present a new genetic map for an Arabidopsis Bayreuth × Shahdara recombinant inbred line (RIL) population, built on RNA-seq data. RNA-seq analysis on 160 RILs of this population identified 30,049 single-nucleotide polymorphisms (SNPs) covering the whole genome. Based on a 100-kbp window SNP binning method, 1059 bin-markers were identified, physically anchored on the genome. The total length of the RNA-seq genetic map spans 471.70 centimorgans (cM) with an average marker distance of 0.45 cM and a maximum marker distance of 4.81 cM. This high resolution genotyping revealed new recombination breakpoints in the population. To highlight the advantages of such high-density map, we compared it to two publicly available genetic maps for the same population, comprising 69 PCR-based markers and 497 gene expression markers derived from microarray data, respectively. In this study, we show that SNP markers can effectively be derived from RNA-seq data. The new RNA-seq map closes many existing gaps in marker coverage, saturating the previously available genetic maps. Quantitative trait locus (QTL) analysis for published phenotypes using the available genetic maps showed increased QTL mapping resolution and reduced QTL confidence interval using the RNA-seq map. The new high-density map is a valuable resource that facilitates the identification of candidate genes and map-based cloning approaches. PMID:29259624

Integrating Genomic Analysis with the Genetic Basis of Gene Expression: Preliminary Evidence of the Identification of Causal Genes for Cardiovascular and Metabolic Traits Related to Nutrition in Mexicans123

PubMed Central

Bastarrachea, Raúl A.; Gallegos-Cabriales, Esther C.; Nava-González, Edna J.; Haack, Karin; Voruganti, V. Saroja; Charlesworth, Jac; Laviada-Molina, Hugo A.; Veloz-Garza, Rosa A.; Cardenas-Villarreal, Velia Margarita; Valdovinos-Chavez, Salvador B.; Gomez-Aguilar, Patricia; Meléndez, Guillermo; López-Alvarenga, Juan Carlos; Göring, Harald H. H.; Cole, Shelley A.; Blangero, John; Comuzzie, Anthony G.; Kent, Jack W.

2012-01-01

Whole-transcriptome expression profiling provides novel phenotypes for analysis of complex traits. Gene expression measurements reflect quantitative variation in transcript-specific messenger RNA levels and represent phenotypes lying close to the action of genes. Understanding the genetic basis of gene expression will provide insight into the processes that connect genotype to clinically significant traits representing a central tenet of system biology. Synchronous in vivo expression profiles of lymphocytes, muscle, and subcutaneous fat were obtained from healthy Mexican men. Most genes were expressed at detectable levels in multiple tissues, and RNA levels were correlated between tissue types. A subset of transcripts with high reliability of expression across tissues (estimated by intraclass correlation coefficients) was enriched for cis-regulated genes, suggesting that proximal sequence variants may influence expression similarly in different cellular environments. This integrative global gene expression profiling approach is proving extremely useful for identifying genes and pathways that contribute to complex clinical traits. Clearly, the coincidence of clinical trait quantitative trait loci and expression quantitative trait loci can help in the prioritization of positional candidate genes. Such data will be crucial for the formal integration of positional and transcriptomic information characterized as genetical genomics. PMID:22797999

Qualitative and Quantitative Pedigree Analysis: Graph Theory, Computer Software, and Case Studies.

ERIC Educational Resources Information Center

Jungck, John R.; Soderberg, Patti

1995-01-01

Presents a series of elementary mathematical tools for re-representing pedigrees, pedigree generators, pedigree-driven database management systems, and case studies for exploring genetic relationships. (MKR)

Tendency for interlaboratory precision in the GMO analysis method based on real-time PCR.

PubMed

Kodama, Takashi; Kurosawa, Yasunori; Kitta, Kazumi; Naito, Shigehiro

2010-01-01

The Horwitz curve estimates interlaboratory precision as a function only of concentration, and is frequently used as a method performance criterion in food analysis with chemical methods. The quantitative biochemical methods based on real-time PCR require an analogous criterion to progressively promote method validation. We analyzed the tendency of precision using a simplex real-time PCR technique in 53 collaborative studies of seven genetically modified (GM) crops. Reproducibility standard deviation (SR) and repeatability standard deviation (Sr) of the genetically modified organism (GMO) amount (%) was more or less independent of GM crops (i.e., maize, soybean, cotton, oilseed rape, potato, sugar beet, and rice) and evaluation procedure steps. Some studies evaluated whole steps consisting of DNA extraction and PCR quantitation, whereas others focused only on the PCR quantitation step by using DNA extraction solutions. Therefore, SR and Sr for GMO amount (%) are functions only of concentration similar to the Horwitz curve. We proposed S(R) = 0.1971C 0.8685 and S(r) = 0.1478C 0.8424, where C is the GMO amount (%). We also proposed a method performance index in GMO quantitative methods that is analogous to the Horwitz Ratio.

Marker-based quantitative genetics in the wild?: the heritability and genetic correlation of chemical defenses in eucalyptus.

PubMed

Andrew, R L; Peakall, R; Wallis, I R; Wood, J T; Knight, E J; Foley, W J

2005-12-01

Marker-based methods for estimating heritability and genetic correlation in the wild have attracted interest because traditional methods may be impractical or introduce bias via G x E effects, mating system variation, and sampling effects. However, they have not been widely used, especially in plants. A regression-based approach, which uses a continuous measure of genetic relatedness, promises to be particularly appropriate for use in plants with mixed-mating systems and overlapping generations. Using this method, we found significant narrow-sense heritability of foliar defense chemicals in a natural population of Eucalyptus melliodora. We also demonstrated a genetic basis for the phenotypic correlation underlying an ecological example of conditioned flavor aversion involving different biosynthetic pathways. Our results revealed that heritability estimates depend on the spatial scale of the analysis in a way that offers insight into the distribution of genetic and environmental variance. This study is the first to successfully use a marker-based method to measure quantitative genetic parameters in a tree. We suggest that this method will prove to be a useful tool in other studies and offer some recommendations for future applications of the method.

Mapping of epistatic quantitative trait loci in four-way crosses.

PubMed

He, Xiao-Hong; Qin, Hongde; Hu, Zhongli; Zhang, Tianzhen; Zhang, Yuan-Ming

2011-01-01

Four-way crosses (4WC) involving four different inbred lines often appear in plant and animal commercial breeding programs. Direct mapping of quantitative trait loci (QTL) in these commercial populations is both economical and practical. However, the existing statistical methods for mapping QTL in a 4WC population are built on the single-QTL genetic model. This simple genetic model fails to take into account QTL interactions, which play an important role in the genetic architecture of complex traits. In this paper, therefore, we attempted to develop a statistical method to detect epistatic QTL in 4WC population. Conditional probabilities of QTL genotypes, computed by the multi-point single locus method, were used to sample the genotypes of all putative QTL in the entire genome. The sampled genotypes were used to construct the design matrix for QTL effects. All QTL effects, including main and epistatic effects, were simultaneously estimated by the penalized maximum likelihood method. The proposed method was confirmed by a series of Monte Carlo simulation studies and real data analysis of cotton. The new method will provide novel tools for the genetic dissection of complex traits, construction of QTL networks, and analysis of heterosis.

Quantitative trait loci that control the oil content variation of rapeseed (Brassica napus L.).

PubMed

Jiang, Congcong; Shi, Jiaqin; Li, Ruiyuan; Long, Yan; Wang, Hao; Li, Dianrong; Zhao, Jianyi; Meng, Jinling

2014-04-01

This report describes an integrative analysis of seed-oil-content quantitative trait loci (QTL) in Brassica napus , using a high-density genetic map to align QTL among different populations. Rapeseed (Brassica napus) is an important source of edible oil and sustainable energy. Given the challenge involved in using only a few genes to substantially increase the oil content of rapeseed without affecting the fatty acid composition, exploitation of a greater number of genetic loci that regulate the oil content variation among rapeseed germplasm is of fundamental importance. In this study, we investigated variation in the seed-oil content among two related genetic populations of Brassica napus, the TN double-haploid population and its derivative reconstructed-F2 population. Each population was grown in multiple experiments under different environmental conditions. Mapping of quantitative trait loci (QTL) identified 41 QTL in the TN populations. Furthermore, of the 20 pairs of epistatic interaction loci detected, approximately one-third were located within the QTL intervals. The use of common markers on different genetic maps and the TN genetic map as a reference enabled us to project QTL from an additional three genetic populations onto the TN genetic map. In summary, we used the TN genetic map of the B. napus genome to identify 46 distinct QTL regions that control seed-oil content on 16 of the 19 linkage groups of B. napus. Of these, 18 were each detected in multiple populations. The present results are of value for ongoing efforts to breed rapeseed with high oil content, and alignment of the QTL makes an important contribution to the development of an integrative system for genetic studies of rapeseed.

Establishment of apoptotic regulatory network for genetic markers of colorectal cancer.

PubMed

Hao, Yibin; Shan, Guoyong; Nan, Kejun

2017-03-01

Our purpose is to screen out genetic markers applicable to early diagnosis for colorectal cancer and to establish apoptotic regulatory network model for colorectal cancer, thereby providing theoretical evidence and targeted therapy for early diagnosis of colorectal cancer. Taking databases including CNKI, VIP, Wanfang data, Pub Med, and MEDLINE as main sources of literature retrieval, literatures associated with genetic markers applied to early diagnosis of colorectal cancer were searched to perform comprehensive and quantitative analysis by Meta analysis, hence screening genetic markers used in early diagnosis of colorectal cancer. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were employed to establish apoptotic regulatory network model based on screened genetic markers, and then verification experiment was conducted. Through Meta analysis, seven genetic markers were screened out, including WWOX, K-ras, COX-2, p53, APC, DCC and PTEN, among which DCC shows highest diagnostic efficiency. GO analysis of genetic markers found that six genetic markers played role in biological process, molecular function and cellular component. It was indicated in apoptotic regulatory network built by KEGG analysis and verification experiment that WWOX could promote tumor cell apoptotic in colorectal cancer and elevate expression level of p53. The apoptotic regulatory model of colorectal cancer established in this study provides clinically theoretical evidence and targeted therapy for early diagnosis of colorectal cancer.

Genetics of Variation in Serum Uric Acid and Cardiovascular Risk Factors in Mexican Americans

PubMed Central

Voruganti, V. Saroja; Nath, Subrata D.; Cole, Shelley A.; Thameem, Farook; Jowett, Jeremy B.; Bauer, Richard; MacCluer, Jean W.; Blangero, John; Comuzzie, Anthony G.; Abboud, Hanna E.; Arar, Nedal H.

2009-01-01

Background: Elevated serum uric acid is associated with several cardiovascular disease (CVD) risk factors such as hypertension, inflammation, endothelial dysfunction, insulin resistance, dyslipidemia, and obesity. However, the role of uric acid as an independent risk factor for CVD is not yet clear. Objective: The aim of the study was to localize quantitative trait loci regulating variation in serum uric acid and also establish the relationship between serum uric acid and other CVD risk factors in Mexican Americans (n = 848; men = 310, women = 538) participating in the San Antonio Family Heart Study. Methods: Quantitative genetic analysis was conducted using variance components decomposition method, implemented in the software program SOLAR. Results: Mean ± sd of serum uric acid was 5.35 ± 1.38 mg/dl. Univariate genetic analysis showed serum uric acid and other CVD risk markers to be significantly heritable (P < 0.005). Bivariate analysis showed significant correlation of serum uric acid with body mass index, waist circumference, waist/hip ratio, total body fat, plasma insulin, serum triglycerides, high-density lipoprotein cholesterol, C-reactive protein, and granulocyte macrophage-colony stimulating factor (P < 0.05). A genome-wide scan for detecting quantitative trait loci regulating serum uric acid variation showed a significant logarithm of odds (LOD) score of 4.72 (empirical LOD score = 4.62; P < 0.00001) on chromosome 3p26. One LOD support interval contains 25 genes, of which an interesting candidate gene is chemokine receptor 2. Summary: There is a significant genetic component in the variation in serum uric acid and evidence of pleiotropy between serum uric acid and other cardiovascular risk factors. PMID:19001525

gQTL: A Web Application for QTL Analysis Using the Collaborative Cross Mouse Genetic Reference Population.

PubMed

Konganti, Kranti; Ehrlich, Andre; Rusyn, Ivan; Threadgill, David W

2018-06-07

Multi-parental recombinant inbred populations, such as the Collaborative Cross (CC) mouse genetic reference population, are increasingly being used for analysis of quantitative trait loci (QTL). However specialized analytic software for these complex populations is typically built in R that works only on command-line, which limits the utility of these powerful resources for many users. To overcome analytic limitations, we developed gQTL, a web accessible, simple graphical user interface application based on the DOQTL platform in R to perform QTL mapping using data from CC mice. Copyright © 2018, G3: Genes, Genomes, Genetics.

Applications of the 1000 Genomes Project resources

PubMed Central

Zheng-Bradley, Xiangqun

2017-01-01

Abstract The 1000 Genomes Project created a valuable, worldwide reference for human genetic variation. Common uses of the 1000 Genomes dataset include genotype imputation supporting Genome-wide Association Studies, mapping expression Quantitative Trait Loci, filtering non-pathogenic variants from exome, whole genome and cancer genome sequencing projects, and genetic analysis of population structure and molecular evolution. In this article, we will highlight some of the multiple ways that the 1000 Genomes data can be and has been utilized for genetic studies. PMID:27436001

Quantitative genetics of circulating Hyaluronic Acid (HA) and its correlation with hand osteoarthritis and obesity-related phenotypes in a community-based sample.

PubMed

Prakash, Jai; Gabdulina, Gulzhan; Trofimov, Svetlana; Livshits, Gregory

2017-09-01

One of the potential molecular biomarkers of osteoarthritis (OA) is hyaluronic acid (HA). HA levels may be related to the severity and progression of OA. However, little is known about the contribution of major risk factors for osteoarthritis, e.g. obesity-related phenotypes and genetics to HA variation. To clarify the quantitative effect of these factors on HA. An ethnically homogeneous sample of 911 apparently healthy European-derived individuals, assessed for radiographic hand osteoarthritis (RHOA), HA, leptin, adiponectin, and several anthropometrical measures of obesity-related phenotypes was studied. Model-based quantitative genetic analysis was used to reveal genetic and shared environmental factors affecting the variation of the study's phenotypes. The HA levels significantly correlated with the age, RHOA, adiponectin, obesity-related phenotypes, and the waist-to-hip ratio. The putative genetic effects contributed significantly to the variation of HA (66.2 ± 9.3%) and they were also significant factors in the variations of all the other studied phenotypes, with the heritability estimate ranging between 0.122 ± 4.4% (WHR) and 45.7 ± 2.2% (joint space narrowing). This is the first study to report heritability estimates of HA variation and its correlation with obesity-related phenotypes, ADP and RHOA. However, the nature of genetic effects on HA and its correlation with other study phenotypes require further clarification.

Genetic approaches in comparative and evolutionary physiology

PubMed Central

Bridgham, Jamie T.; Kelly, Scott A.; Garland, Theodore

2015-01-01

Whole animal physiological performance is highly polygenic and highly plastic, and the same is generally true for the many subordinate traits that underlie performance capacities. Quantitative genetics, therefore, provides an appropriate framework for the analysis of physiological phenotypes and can be used to infer the microevolutionary processes that have shaped patterns of trait variation within and among species. In cases where specific genes are known to contribute to variation in physiological traits, analyses of intraspecific polymorphism and interspecific divergence can reveal molecular mechanisms of functional evolution and can provide insights into the possible adaptive significance of observed sequence changes. In this review, we explain how the tools and theory of quantitative genetics, population genetics, and molecular evolution can inform our understanding of mechanism and process in physiological evolution. For example, lab-based studies of polygenic inheritance can be integrated with field-based studies of trait variation and survivorship to measure selection in the wild, thereby providing direct insights into the adaptive significance of physiological variation. Analyses of quantitative genetic variation in selection experiments can be used to probe interrelationships among traits and the genetic basis of physiological trade-offs and constraints. We review approaches for characterizing the genetic architecture of physiological traits, including linkage mapping and association mapping, and systems approaches for dissecting intermediary steps in the chain of causation between genotype and phenotype. We also discuss the promise and limitations of population genomic approaches for inferring adaptation at specific loci. We end by highlighting the role of organismal physiology in the functional synthesis of evolutionary biology. PMID:26041111

Genetic approaches in comparative and evolutionary physiology.

PubMed

Storz, Jay F; Bridgham, Jamie T; Kelly, Scott A; Garland, Theodore

2015-08-01

Whole animal physiological performance is highly polygenic and highly plastic, and the same is generally true for the many subordinate traits that underlie performance capacities. Quantitative genetics, therefore, provides an appropriate framework for the analysis of physiological phenotypes and can be used to infer the microevolutionary processes that have shaped patterns of trait variation within and among species. In cases where specific genes are known to contribute to variation in physiological traits, analyses of intraspecific polymorphism and interspecific divergence can reveal molecular mechanisms of functional evolution and can provide insights into the possible adaptive significance of observed sequence changes. In this review, we explain how the tools and theory of quantitative genetics, population genetics, and molecular evolution can inform our understanding of mechanism and process in physiological evolution. For example, lab-based studies of polygenic inheritance can be integrated with field-based studies of trait variation and survivorship to measure selection in the wild, thereby providing direct insights into the adaptive significance of physiological variation. Analyses of quantitative genetic variation in selection experiments can be used to probe interrelationships among traits and the genetic basis of physiological trade-offs and constraints. We review approaches for characterizing the genetic architecture of physiological traits, including linkage mapping and association mapping, and systems approaches for dissecting intermediary steps in the chain of causation between genotype and phenotype. We also discuss the promise and limitations of population genomic approaches for inferring adaptation at specific loci. We end by highlighting the role of organismal physiology in the functional synthesis of evolutionary biology. Copyright © 2015 the American Physiological Society.

Quantitative genetic analysis of the body composition and blood pressure association in two ethnically diverse populations.

PubMed

Ghosh, Sudipta; Dosaev, Tasbulat; Prakash, Jai; Livshits, Gregory

2017-04-01

The major aim of this study was to conduct comparative quantitative-genetic analysis of the body composition (BCP) and somatotype (STP) variation, as well as their correlations with blood pressure (BP) in two ethnically, culturally and geographically different populations: Santhal, indigenous ethnic group from India and Chuvash, indigenous population from Russia. Correspondently two pedigree-based samples were collected from 1,262 Santhal and1,558 Chuvash individuals, respectively. At the first stage of the study, descriptive statistics and a series of univariate regression analyses were calculated. Finally, multiple and multivariate regression (MMR) analyses, with BP measurements as dependent variables and age, sex, BCP and STP as independent variables were carried out in each sample separately. The significant and independent covariates of BP were identified and used for re-examination in pedigree-based variance decomposition analysis. Despite clear and significant differences between the populations in BCP/STP, both Santhal and Chuvash were found to be predominantly mesomorphic irrespective of their sex. According to MMR analyses variation of BP significantly depended on age and mesomorphic component in both samples, and in addition on sex, ectomorphy and fat mass index in Santhal and on fat free mass index in Chuvash samples, respectively. Additive genetic component contributes to a substantial proportion of blood pressure and body composition variance. Variance component analysis in addition to above mentioned results suggests that additive genetic factors influence BP and BCP/STP associations significantly. © 2017 Wiley Periodicals, Inc.

On normality, ethnicity, and missing values in quantitative trait locus mapping

PubMed Central

Labbe, Aurélie; Wormald, Hanna

2005-01-01

Background This paper deals with the detection of significant linkage for quantitative traits using a variance components approach. Microsatellite markers were obtained for the Genetic Analysis Workshop 14 Collaborative Study on the Genetics of Alcoholism data. Ethnic heterogeneity, highly skewed quantitative measures, and a high rate of missing values are all present in this dataset and well known to impact upon linkage analysis. This makes it a good candidate for investigation. Results As expected, we observed a number of changes in LOD scores, especially for chromosomes 1, 7, and 18, along with the three factors studied. A dramatic example of such changes can be found in chromosome 7. Highly significant linkage to one of the quantitative traits became insignificant when a proper normalizing transformation of the trait was used and when analysis was carried out on an ethnically homogeneous subset of the original pedigrees. Conclusion In agreement with existing literature, transforming a trait to ensure normality using a Box-Cox transformation is highly recommended in order to avoid false-positive linkages. Furthermore, pedigrees should be sorted by ethnic groups and analyses should be carried out separately. Finally, one should be aware that the inclusion of covariates with a high rate of missing values reduces considerably the number of subjects included in the model. In such a case, the loss in power may be large. Imputation methods are then recommended. PMID:16451664

Putative regulatory sites unraveled by network-embedded thermodynamic analysis of metabolome data

PubMed Central

Kümmel, Anne; Panke, Sven; Heinemann, Matthias

2006-01-01

As one of the most recent members of the omics family, large-scale quantitative metabolomics data are currently complementing our systems biology data pool and offer the chance to integrate the metabolite level into the functional analysis of cellular networks. Network-embedded thermodynamic analysis (NET analysis) is presented as a framework for mechanistic and model-based analysis of these data. By coupling the data to an operating metabolic network via the second law of thermodynamics and the metabolites' Gibbs energies of formation, NET analysis allows inferring functional principles from quantitative metabolite data; for example it identifies reactions that are subject to active allosteric or genetic regulation as exemplified with quantitative metabolite data from Escherichia coli and Saccharomyces cerevisiae. Moreover, the optimization framework of NET analysis was demonstrated to be a valuable tool to systematically investigate data sets for consistency, for the extension of sub-omic metabolome data sets and for resolving intracompartmental concentrations from cell-averaged metabolome data. Without requiring any kind of kinetic modeling, NET analysis represents a perfectly scalable and unbiased approach to uncover insights from quantitative metabolome data. PMID:16788595

Applications of Population Genetics to Animal Breeding, from Wright, Fisher and Lush to Genomic Prediction

PubMed Central

Hill, William G.

2014-01-01

Although animal breeding was practiced long before the science of genetics and the relevant disciplines of population and quantitative genetics were known, breeding programs have mainly relied on simply selecting and mating the best individuals on their own or relatives’ performance. This is based on sound quantitative genetic principles, developed and expounded by Lush, who attributed much of his understanding to Wright, and formalized in Fisher’s infinitesimal model. Analysis at the level of individual loci and gene frequency distributions has had relatively little impact. Now with access to genomic data, a revolution in which molecular information is being used to enhance response with “genomic selection” is occurring. The predictions of breeding value still utilize multiple loci throughout the genome and, indeed, are largely compatible with additive and specifically infinitesimal model assumptions. I discuss some of the history and genetic issues as applied to the science of livestock improvement, which has had and continues to have major spin-offs into ideas and applications in other areas. PMID:24395822

Molecular Diversity and Population Structure of a Worldwide Collection of Cultivated Tetraploid Alfalfa (Medicago sativa subsp. sativa L.) Germplasm as Revealed by Microsatellite Markers.

PubMed

Qiang, Haiping; Chen, Zhihong; Zhang, Zhengli; Wang, Xuemin; Gao, Hongwen; Wang, Zan

2015-01-01

Information on genetic diversity and population structure of a tetraploid alfalfa collection might be valuable in effective use of the genetic resources. A set of 336 worldwide genotypes of tetraploid alfalfa (Medicago sativa subsp. sativa L.) was genotyped using 85 genome-wide distributed SSR markers to reveal the genetic diversity and population structure in the alfalfa. Genetic diversity analysis identified a total of 1056 alleles across 85 marker loci. The average expected heterozygosity and polymorphism information content values were 0.677 and 0.638, respectively, showing high levels of genetic diversity in the cultivated tetraploid alfalfa germplasm. Comparison of genetic characteristics across chromosomes indicated regions of chromosomes 2 and 3 had the highest genetic diversity. A higher genetic diversity was detected in alfalfa landraces than that of wild materials and cultivars. Two populations were identified by the model-based population structure, principal coordinate and neighbor-joining analyses, corresponding to China and other parts of the world. However, lack of strictly correlation between clustering and geographic origins suggested extensive germplasm exchanges of alfalfa germplasm across diverse geographic regions. The quantitative analysis of the genetic diversity and population structure in this study could be useful for genetic and genomic analysis and utilization of the genetic variation in alfalfa breeding.

The genetic architecture of sexually selected traits in two natural populations of Drosophila montana

PubMed Central

Veltsos, P; Gregson, E; Morrissey, B; Slate, J; Hoikkala, A; Butlin, R K; Ritchie, M G

2015-01-01

We investigated the genetic architecture of courtship song and cuticular hydrocarbon traits in two phygenetically distinct populations of Drosophila montana. To study natural variation in these two important traits, we analysed within-population crosses among individuals sampled from the wild. Hence, the genetic variation analysed should represent that available for natural and sexual selection to act upon. In contrast to previous between-population crosses in this species, no major quantitative trait loci (QTLs) were detected, perhaps because the between-population QTLs were due to fixed differences between the populations. Partitioning the trait variation to chromosomes suggested a broadly polygenic genetic architecture of within-population variation, although some chromosomes explained more variation in one population compared with the other. Studies of natural variation provide an important contrast to crosses between species or divergent lines, but our analysis highlights recent concerns that segregating variation within populations for important quantitative ecological traits may largely consist of small effect alleles, difficult to detect with studies of moderate power. PMID:26198076

Collaborative ring trial of the papaya endogenous reference gene and its polymerase chain reaction assays for genetically modified organism analysis.

PubMed

Wei, Jiaojun; Li, Feiwu; Guo, Jinchao; Li, Xiang; Xu, Junfeng; Wu, Gang; Zhang, Dabing; Yang, Litao

2013-11-27

The papaya (Carica papaya L.) Chymopapain (CHY) gene has been reported as a suitable endogenous reference gene for genetically modified (GM) papaya detection in previous studies. Herein, we further validated the use of the CHY gene and its qualitative and quantitative polymerase chain reaction (PCR) assays through an interlaboratory collaborative ring trial. A total of 12 laboratories working on detection of genetically modified organisms participated in the ring trial and returned test results. Statistical analysis of the returned results confirmed the species specificity, low heterogeneity, and single-copy number of the CHY gene among different papaya varieties. The limit of detection of the CHY qualitative PCR assay was 0.1%, while the limit of quantification of the quantitative PCR assay was ∼25 copies of haploid papaya genome with acceptable PCR efficiency and linearity. The differences between the tested and true values of papaya content in 10 blind samples ranged from 0.84 to 6.58%. These results indicated that the CHY gene was suitable as an endogenous reference gene for the identification and quantification of GM papaya.

A linkage and family-based association analysis of a potential neurocognitive endophenotype of bipolar disorder.

PubMed

Savitz, Jonathan; van der Merwe, Lize; Solms, Mark; Ramesar, Rajkumar

2007-01-01

The identification of the genetic variants underpinning bipolar disorder (BPD) has been impeded by a complex pattern of inheritance characterized by genetic and phenotypic heterogeneity, genetic epistasis, and gene-environment interactions. In this paper two strategies were used to ameliorate these confounding factors. A unique South African sample including 190 individuals of the relatively, reproductively isolated Afrikaner population was assessed with a battery of neuropsychological tests in an attempt to identify a BPD-associated quantitative trait or endophenotype. BPD individuals performed significantly worse than their unaffected relatives on visual and verbal memory tasks, a finding congruent with the literature. Afocused linkage and family-based association study was carried out using this memory-related endophenotype. In the largest 77-strong Afrikaner pedigree significant evidence for linkage was detected on chromosome 22q11, a region previously implicated in BPD. The quantitative transmission disequilibrium tests-based association analysis suggested that functional variants of the DRD4 and MAO-A genes modulate memory-related cognition. We speculate that polymorphisms at these loci may predispose to a subtype of BPD characterized by memory-related deficits.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-07-12

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

Genetics Home Reference: prostate cancer

MedlinePlus

... prostate cancer Genetic Testing Registry: Prostate cancer aggressiveness quantitative trait locus on chromosome 19 Genetic Testing Registry: ... OMIM (25 links) PROSTATE CANCER PROSTATE CANCER AGGRESSIVENESS QUANTITATIVE TRAIT LOCUS ON CHROMOSOME 19 PROSTATE CANCER ANTIGEN ...

Genetics and child psychiatry: I Advances in quantitative and molecular genetics.

PubMed

Rutter, M; Silberg, J; O'Connor, T; Simonoff, E

1999-01-01

Advances in quantitative psychiatric genetics as a whole are reviewed with respect to conceptual and methodological issues in relation to statistical model fitting, new genetic designs, twin and adoptee studies, definition of the phenotype, pervasiveness of genetic influences, pervasiveness of environmental influences, shared and nonshared environmental effects, and nature-nurture interplay. Advances in molecular genetics are discussed in relation to the shifts in research strategies to investigate multifactorial disorders (affected relative linkage designs, association strategies, and quantitative trait loci studies); new techniques and identified genetic mechanisms (expansion of trinucleotide repeats, genomic imprinting, mitochondrial DNA, fluorescent in-situ hybridisation, behavioural phenotypes, and animal models); and the successful localisation of genes.

Testing natural selection vs. genetic drift in phenotypic evolution using quantitative trait locus data.

PubMed Central

Orr, H A

1998-01-01

Evolutionary biologists have long sought a way to determine whether a phenotypic difference between two taxa was caused by natural selection or random genetic drift. Here I argue that data from quantitative trait locus (QTL) analyses can be used to test the null hypothesis of neutral phenotypic evolution. I propose a sign test that compares the observed number of plus and minus alleles in the "high line" with that expected under neutrality, conditioning on the known phenotypic difference between the taxa. Rejection of the null hypothesis implies a role for directional natural selection. This test is applicable to any character in any organism in which QTL analysis can be performed. PMID:9691061

Identifying Genotype-by-Environment Interactions in the Metabolism of Germinating Arabidopsis Seeds Using Generalized Genetical Genomics 1[C][W][OA

PubMed Central

Joosen, Ronny Viktor Louis; Arends, Danny; Li, Yang; Willems, Leo A.J.; Keurentjes, Joost J.B.; Ligterink, Wilco; Jansen, Ritsert C.; Hilhorst, Henk W.M.

2013-01-01

A complex phenotype such as seed germination is the result of several genetic and environmental cues and requires the concerted action of many genes. The use of well-structured recombinant inbred lines in combination with “omics” analysis can help to disentangle the genetic basis of such quantitative traits. This so-called genetical genomics approach can effectively capture both genetic and epistatic interactions. However, to understand how the environment interacts with genomic-encoded information, a better understanding of the perception and processing of environmental signals is needed. In a classical genetical genomics setup, this requires replication of the whole experiment in different environmental conditions. A novel generalized setup overcomes this limitation and includes environmental perturbation within a single experimental design. We developed a dedicated quantitative trait loci mapping procedure to implement this approach and used existing phenotypical data to demonstrate its power. In addition, we studied the genetic regulation of primary metabolism in dry and imbibed Arabidopsis (Arabidopsis thaliana) seeds. In the metabolome, many changes were observed that were under both environmental and genetic controls and their interaction. This concept offers unique reduction of experimental load with minimal compromise of statistical power and is of great potential in the field of systems genetics, which requires a broad understanding of both plasticity and dynamic regulation. PMID:23606598

[Phenotypic and genetic analysis of a patient presented with Tietz/Waardenburg type II a syndrome].

PubMed

Wang, Huanhuan; Tang, Lifang; Zhang, Jingmin; Hu, Qin; Chen, Yingwei; Xiao, Bing

2015-08-01

To determine the genetic cause for a patient featuring decreased pigmentation of the skin and iris, hearing loss and multiple congenital anomalies. Routine chromosomal banding was performed to analyze the karyotype of the patient and his parents. Single nucleotide polymorphism array (SNP array) was employed to identify cryptic chromosome aberrations, and quantitative real-time PCR was used to confirm the results. Karyotype analysis has revealed no obvious anomaly for the patient and his parents. SNP array analysis of the patient has demonstrated a 3.9 Mb deletion encompassing 3p13p14.1, which caused loss of entire MITF gene. The deletion was confirmed by quantitative real-time PCR. Clinical features of the patient have included severe bilateral hearing loss, decreased pigmentation of the skin and iris and multiple congenital anomalies. The patient, carrying a 3p13p14.1 deletion, has features of Tietz syndrome/Waardenburg syndrome type IIa. This case may provide additional data for the study of genotype-phenotype correlation of this disease.

A unifying theory for genetic epidemiological analysis of binary disease data

PubMed Central

2014-01-01

Background Genetic selection for host resistance offers a desirable complement to chemical treatment to control infectious disease in livestock. Quantitative genetics disease data frequently originate from field studies and are often binary. However, current methods to analyse binary disease data fail to take infection dynamics into account. Moreover, genetic analyses tend to focus on host susceptibility, ignoring potential variation in infectiousness, i.e. the ability of a host to transmit the infection. This stands in contrast to epidemiological studies, which reveal that variation in infectiousness plays an important role in the progression and severity of epidemics. In this study, we aim at filling this gap by deriving an expression for the probability of becoming infected that incorporates infection dynamics and is an explicit function of both host susceptibility and infectiousness. We then validate this expression according to epidemiological theory and by simulating epidemiological scenarios, and explore implications of integrating this expression into genetic analyses. Results Our simulations show that the derived expression is valid for a range of stochastic genetic-epidemiological scenarios. In the particular case of variation in susceptibility only, the expression can be incorporated into conventional quantitative genetic analyses using a complementary log-log link function (rather than probit or logit). Similarly, if there is moderate variation in both susceptibility and infectiousness, it is possible to use a logarithmic link function, combined with an indirect genetic effects model. However, in the presence of highly infectious individuals, i.e. super-spreaders, the use of any model that is linear in susceptibility and infectiousness causes biased estimates. Thus, in order to identify super-spreaders, novel analytical methods using our derived expression are required. Conclusions We have derived a genetic-epidemiological function for quantitative genetic analyses of binary infectious disease data, which, unlike current approaches, takes infection dynamics into account and allows for variation in host susceptibility and infectiousness. PMID:24552188

A unifying theory for genetic epidemiological analysis of binary disease data.

PubMed

Lipschutz-Powell, Debby; Woolliams, John A; Doeschl-Wilson, Andrea B

2014-02-19

Genetic selection for host resistance offers a desirable complement to chemical treatment to control infectious disease in livestock. Quantitative genetics disease data frequently originate from field studies and are often binary. However, current methods to analyse binary disease data fail to take infection dynamics into account. Moreover, genetic analyses tend to focus on host susceptibility, ignoring potential variation in infectiousness, i.e. the ability of a host to transmit the infection. This stands in contrast to epidemiological studies, which reveal that variation in infectiousness plays an important role in the progression and severity of epidemics. In this study, we aim at filling this gap by deriving an expression for the probability of becoming infected that incorporates infection dynamics and is an explicit function of both host susceptibility and infectiousness. We then validate this expression according to epidemiological theory and by simulating epidemiological scenarios, and explore implications of integrating this expression into genetic analyses. Our simulations show that the derived expression is valid for a range of stochastic genetic-epidemiological scenarios. In the particular case of variation in susceptibility only, the expression can be incorporated into conventional quantitative genetic analyses using a complementary log-log link function (rather than probit or logit). Similarly, if there is moderate variation in both susceptibility and infectiousness, it is possible to use a logarithmic link function, combined with an indirect genetic effects model. However, in the presence of highly infectious individuals, i.e. super-spreaders, the use of any model that is linear in susceptibility and infectiousness causes biased estimates. Thus, in order to identify super-spreaders, novel analytical methods using our derived expression are required. We have derived a genetic-epidemiological function for quantitative genetic analyses of binary infectious disease data, which, unlike current approaches, takes infection dynamics into account and allows for variation in host susceptibility and infectiousness.

Defining the consequences of genetic variation on a proteome–wide scale

PubMed Central

Chick, Joel M.; Munger, Steven C.; Simecek, Petr; Huttlin, Edward L.; Choi, Kwangbom; Gatti, Daniel M.; Raghupathy, Narayanan; Svenson, Karen L.; Churchill, Gary A.; Gygi, Steven P.

2016-01-01

Genetic variation modulates protein expression through both transcriptional and post-transcriptional mechanisms. To characterize the consequences of natural genetic diversity on the proteome, here we combine a multiplexed, mass spectrometry-based method for protein quantification with an emerging outbred mouse model containing extensive genetic variation from eight inbred founder strains. By measuring genome-wide transcript and protein expression in livers from 192 Diversity outbred mice, we identify 2,866 protein quantitative trait loci (pQTL) with twice as many local as distant genetic variants. These data support distinct transcriptional and post-transcriptional models underlying the observed pQTL effects. Using a sensitive approach to mediation analysis, we often identified a second protein or transcript as the causal mediator of distant pQTL. Our analysis reveals an extensive network of direct protein–protein interactions. Finally, we show that local genotype can provide accurate predictions of protein abundance in an independent cohort of collaborative cross mice. PMID:27309819

Development and interlaboratory validation of quantitative polymerase chain reaction method for screening analysis of genetically modified soybeans.

PubMed

Takabatake, Reona; Onishi, Mari; Koiwa, Tomohiro; Futo, Satoshi; Minegishi, Yasutaka; Akiyama, Hiroshi; Teshima, Reiko; Kurashima, Takeyo; Mano, Junichi; Furui, Satoshi; Kitta, Kazumi

2013-01-01

A novel real-time polymerase chain reaction (PCR)-based quantitative screening method was developed for three genetically modified soybeans: RRS, A2704-12, and MON89788. The 35S promoter (P35S) of cauliflower mosaic virus is introduced into RRS and A2704-12 but not MON89788. We then designed a screening method comprised of the combination of the quantification of P35S and the event-specific quantification of MON89788. The conversion factor (Cf) required to convert the amount of a genetically modified organism (GMO) from a copy number ratio to a weight ratio was determined experimentally. The trueness and precision were evaluated as the bias and reproducibility of relative standard deviation (RSDR), respectively. The determined RSDR values for the method were less than 25% for both targets. We consider that the developed method would be suitable for the simple detection and approximate quantification of GMO.

GenomeFingerprinter: the genome fingerprint and the universal genome fingerprint analysis for systematic comparative genomics.

PubMed

Ai, Yuncan; Ai, Hannan; Meng, Fanmei; Zhao, Lei

2013-01-01

No attention has been paid on comparing a set of genome sequences crossing genetic components and biological categories with far divergence over large size range. We define it as the systematic comparative genomics and aim to develop the methodology. First, we create a method, GenomeFingerprinter, to unambiguously produce a set of three-dimensional coordinates from a sequence, followed by one three-dimensional plot and six two-dimensional trajectory projections, to illustrate the genome fingerprint of a given genome sequence. Second, we develop a set of concepts and tools, and thereby establish a method called the universal genome fingerprint analysis (UGFA). Particularly, we define the total genetic component configuration (TGCC) (including chromosome, plasmid, and phage) for describing a strain as a systematic unit, the universal genome fingerprint map (UGFM) of TGCC for differentiating strains as a universal system, and the systematic comparative genomics (SCG) for comparing a set of genomes crossing genetic components and biological categories. Third, we construct a method of quantitative analysis to compare two genomes by using the outcome dataset of genome fingerprint analysis. Specifically, we define the geometric center and its geometric mean for a given genome fingerprint map, followed by the Euclidean distance, the differentiate rate, and the weighted differentiate rate to quantitatively describe the difference between two genomes of comparison. Moreover, we demonstrate the applications through case studies on various genome sequences, giving tremendous insights into the critical issues in microbial genomics and taxonomy. We have created a method, GenomeFingerprinter, for rapidly computing, geometrically visualizing, intuitively comparing a set of genomes at genome fingerprint level, and hence established a method called the universal genome fingerprint analysis, as well as developed a method of quantitative analysis of the outcome dataset. These have set up the methodology of systematic comparative genomics based on the genome fingerprint analysis.

Study on Analysis of Variance on the indigenous wild and cultivated rice species of Manipur Valley

NASA Astrophysics Data System (ADS)

Medhabati, K.; Rohinikumar, M.; Rajiv Das, K.; Henary, Ch.; Dikash, Th.

2012-10-01

The analysis of variance revealed considerable variation among the cultivars and the wild species for yield and other quantitative characters in both the years of investigation. The highly significant differences among the cultivars in year wise and pooled analysis of variance for all the 12 characters reveal that there are enough genetic variabilities for all the characters studied. The existence of genetic variability is of paramount importance for starting a judicious plant breeding programme. Since introduced high yielding rice cultivars usually do not perform well. Improvement of indigenous cultivars is a clear choice for increase of rice production. The genetic variability of 37 rice germplasms in 12 agronomic characters estimated in the present study can be used in breeding programme

COMPARISON OF GENETIC METHODS TO OPTICAL METHODS IN THE IDENTIFICATION AND ASSESSMENT OF MOLD IN THE BUILT ENVIRONMENT -- COMPARISON OF TAQMAN AND MICROSCOPIC ANALYSIS OF CLADOSPORIUM SPORES RETRIEVED FROM ZEFON AIR-O-CELL TRACES

EPA Science Inventory

Recent advances in the sequencing of relevant water intrusion fungi by the EPA, combined with the development of probes and primers have allowed for the unequivocal quantitative and qualitative identification of fungi in selected matrices.

In this pilot study, quantitative...

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

PubMed Central

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

1996-01-01

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

Mapping Quantitative Field Resistance Against Apple Scab in a 'Fiesta' x 'Discovery' Progeny.

PubMed

Liebhard, R; Koller, B; Patocchi, A; Kellerhals, M; Pfammatter, W; Jermini, M; Gessler, C

2003-04-01

ABSTRACT Breeding of resistant apple cultivars (Malus x domestica) as a disease management strategy relies on the knowledge and understanding of the underlying genetics. The availability of molecular markers and genetic linkage maps enables the detection and the analysis of major resistance genes as well as of quantitative trait loci (QTL) contributing to the resistance of a genotype. Such a genetic linkage map was constructed, based on a segregating population of the cross between apple cvs. Fiesta (syn. Red Pippin) and Discovery. The progeny was observed for 3 years at three different sites in Switzerland and field resistance against apple scab (Venturia inaequalis) was assessed. Only a weak correlation was detected between leaf scab and fruit scab. A QTL analysis was performed, based on the genetic linkage map consisting of 804 molecular markers and covering all 17 chromosomes of apple. With the maximum likelihood-based interval mapping method, eight genomic regions were identified, six conferring resistance against leaf scab and two conferring fruit scab resistance. Although cv. Discovery showed a much stronger resistance against scab in the field, most QTL identified were attributed to the more susceptible parent 'Fiesta'. This indicated a high degree of homozygosity at the scab resistance loci in 'Discovery', preventing their detection in the progeny due to the lack of segregation.

Comparison of Genetic Diversity between Chinese and American Soybean (Glycine max (L.)) Accessions Revealed by High-Density SNPs

PubMed Central

Liu, Zhangxiong; Li, Huihui; Wen, Zixiang; Fan, Xuhong; Li, Yinghui; Guan, Rongxia; Guo, Yong; Wang, Shuming; Wang, Dechun; Qiu, Lijuan

2017-01-01

Soybean is one of the most important economic crops for both China and the United States (US). The exchange of germplasm between these two countries has long been active. In order to investigate genetic relationships between Chinese and US soybean germplasm, 277 Chinese soybean accessions and 300 US soybean accessions from geographically diverse regions were analyzed using 5,361 SNP markers. The genetic diversity and the polymorphism information content (PIC) of the Chinese accessions was higher than that of the US accessions. Population structure analysis, principal component analysis, and cluster analysis all showed that the genetic basis of Chinese soybeans is distinct from that of the USA. The groupings observed in clustering analysis reflected the geographical origins of the accessions; this conclusion was validated with both genetic distance analysis and relative kinship analysis. FST-based and EigenGWAS statistical analysis revealed high genetic variation between the two subpopulations. Analysis of the 10 loci with the strongest selection signals showed that many loci were located in chromosome regions that have previously been identified as quantitative trait loci (QTL) associated with environmental-adaptation-related and yield-related traits. The pattern of diversity among the American and Chinese accessions should help breeders to select appropriate parental accessions to enhance the performance of future soybean cultivars. PMID:29250088

Applications of the 1000 Genomes Project resources.

PubMed

Zheng-Bradley, Xiangqun; Flicek, Paul

2017-05-01

The 1000 Genomes Project created a valuable, worldwide reference for human genetic variation. Common uses of the 1000 Genomes dataset include genotype imputation supporting Genome-wide Association Studies, mapping expression Quantitative Trait Loci, filtering non-pathogenic variants from exome, whole genome and cancer genome sequencing projects, and genetic analysis of population structure and molecular evolution. In this article, we will highlight some of the multiple ways that the 1000 Genomes data can be and has been utilized for genetic studies. © The Author 2016. Published by Oxford University Press.

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.

Genomic Quantitative Genetics to Study Evolution in the Wild.

PubMed

Gienapp, Phillip; Fior, Simone; Guillaume, Frédéric; Lasky, Jesse R; Sork, Victoria L; Csilléry, Katalin

2017-12-01

Quantitative genetic theory provides a means of estimating the evolutionary potential of natural populations. However, this approach was previously only feasible in systems where the genetic relatedness between individuals could be inferred from pedigrees or experimental crosses. The genomic revolution opened up the possibility of obtaining the realized proportion of genome shared among individuals in natural populations of virtually any species, which could promise (more) accurate estimates of quantitative genetic parameters in virtually any species. Such a 'genomic' quantitative genetics approach relies on fewer assumptions, offers a greater methodological flexibility, and is thus expected to greatly enhance our understanding of evolution in natural populations, for example, in the context of adaptation to environmental change, eco-evolutionary dynamics, and biodiversity conservation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Genetics Home Reference: congenital afibrinogenemia

MedlinePlus

... Neerman-Arbez M. FGB mutations leading to congenital quantitative fibrinogen deficiencies: an update and report of four ... R, Staeger P, Antonarakis SE, Morris MA. Molecular analysis of the fibrinogen gene cluster in 16 patients with congenital afibrinogenemia: novel truncating ... Support USA. ...

A comparison of cosegregation analysis methods for the clinical setting.

PubMed

Rañola, John Michael O; Liu, Quanhui; Rosenthal, Elisabeth A; Shirts, Brian H

2018-04-01

Quantitative cosegregation analysis can help evaluate the pathogenicity of genetic variants. However, genetics professionals without statistical training often use simple methods, reporting only qualitative findings. We evaluate the potential utility of quantitative cosegregation in the clinical setting by comparing three methods. One thousand pedigrees each were simulated for benign and pathogenic variants in BRCA1 and MLH1 using United States historical demographic data to produce pedigrees similar to those seen in the clinic. These pedigrees were analyzed using two robust methods, full likelihood Bayes factors (FLB) and cosegregation likelihood ratios (CSLR), and a simpler method, counting meioses. Both FLB and CSLR outperform counting meioses when dealing with pathogenic variants, though counting meioses is not far behind. For benign variants, FLB and CSLR greatly outperform as counting meioses is unable to generate evidence for benign variants. Comparing FLB and CSLR, we find that the two methods perform similarly, indicating that quantitative results from either of these methods could be combined in multifactorial calculations. Combining quantitative information will be important as isolated use of cosegregation in single families will yield classification for less than 1% of variants. To encourage wider use of robust cosegregation analysis, we present a website ( http://www.analyze.myvariant.org ) which implements the CSLR, FLB, and Counting Meioses methods for ATM, BRCA1, BRCA2, CHEK2, MEN1, MLH1, MSH2, MSH6, and PMS2. We also present an R package, CoSeg, which performs the CSLR analysis on any gene with user supplied parameters. Future variant classification guidelines should allow nuanced inclusion of cosegregation evidence against pathogenicity.

Establishment of apoptotic regulatory network for genetic markers of colorectal cancer and optimal selection of traditional Chinese medicine target.

PubMed

Tian, Tongde; Chen, Chuanliang; Yang, Feng; Tang, Jingwen; Pei, Junwen; Shi, Bian; Zhang, Ning; Zhang, Jianhua

2017-03-01

The paper aimed to screen out genetic markers applicable to early diagnosis for colorectal cancer and establish apoptotic regulatory network model for colorectal cancer, and to analyze the current situation of traditional Chinese medicine (TCM) target, thereby providing theoretical evidence for early diagnosis and targeted therapy of colorectal cancer. Taking databases including CNKI, VIP, Wanfang data, Pub Med, and MEDLINE as main sources of literature retrieval, literatures associated with genetic markers that are applied to early diagnosis of colorectal cancer were searched and performed comprehensive and quantitative analysis by Meta analysis, hence screening genetic markers used in early diagnosis of colorectal cancer. KEGG analysis was employed to establish apoptotic regulatory network model based on screened genetic markers, and optimization was conducted on TCM targets. Through Meta analysis, seven genetic markers were screened out, including WWOX, K-ras, COX-2, P53, APC, DCC and PTEN, among which DCC has the highest diagnostic efficiency. Apoptotic regulatory network was built by KEGG analysis. Currently, it was reported that TCM has regulatory function on gene locus in apoptotic regulatory network. The apoptotic regulatory model of colorectal cancer established in this study provides theoretical evidence for early diagnosis and TCM targeted therapy of colorectal cancer in clinic.

Long-Range Regulatory Polymorphisms Affecting a GABA Receptor Constitute a Quantitative Trait Locus (QTL) for Social Behavior in Caenorhabditis elegans

PubMed Central

Bendesky, Andres; Pitts, Jason; Rockman, Matthew V.; Chen, William C.; Tan, Man-Wah; Kruglyak, Leonid; Bargmann, Cornelia I.

2012-01-01

Aggregation is a social behavior that varies between and within species, providing a model to study the genetic basis of behavioral diversity. In the nematode Caenorhabditis elegans, aggregation is regulated by environmental context and by two neuromodulatory pathways, one dependent on the neuropeptide receptor NPR-1 and one dependent on the TGF-β family protein DAF-7. To gain further insight into the genetic regulation of aggregation, we characterize natural variation underlying behavioral differences between two wild-type C. elegans strains, N2 and CB4856. Using quantitative genetic techniques, including a survey of chromosome substitution strains and QTL analysis of recombinant inbred lines, we identify three new QTLs affecting aggregation in addition to the two known N2 mutations in npr-1 and glb-5. Fine-mapping with near-isogenic lines localized one QTL, accounting for 5%–8% of the behavioral variance between N2 and CB4856, 3′ to the transcript of the GABA neurotransmitter receptor gene exp-1. Quantitative complementation tests demonstrated that this QTL affects exp-1, identifying exp-1 and GABA signaling as new regulators of aggregation. exp-1 interacts genetically with the daf-7 TGF-β pathway, which integrates food availability and population density, and exp-1 mutations affect the level of daf-7 expression. Our results add to growing evidence that genetic variation affecting neurotransmitter receptor genes is a source of natural behavioral variation. PMID:23284308

Molecular Diversity and Population Structure of a Worldwide Collection of Cultivated Tetraploid Alfalfa (Medicago sativa subsp. sativa L.) Germplasm as Revealed by Microsatellite Markers

PubMed Central

Qiang, Haiping; Chen, Zhihong; Zhang, Zhengli; Wang, Xuemin; Gao, Hongwen; Wang, Zan

2015-01-01

Information on genetic diversity and population structure of a tetraploid alfalfa collection might be valuable in effective use of the genetic resources. A set of 336 worldwide genotypes of tetraploid alfalfa (Medicago sativa subsp. sativa L.) was genotyped using 85 genome-wide distributed SSR markers to reveal the genetic diversity and population structure in the alfalfa. Genetic diversity analysis identified a total of 1056 alleles across 85 marker loci. The average expected heterozygosity and polymorphism information content values were 0.677 and 0.638, respectively, showing high levels of genetic diversity in the cultivated tetraploid alfalfa germplasm. Comparison of genetic characteristics across chromosomes indicated regions of chromosomes 2 and 3 had the highest genetic diversity. A higher genetic diversity was detected in alfalfa landraces than that of wild materials and cultivars. Two populations were identified by the model-based population structure, principal coordinate and neighbor-joining analyses, corresponding to China and other parts of the world. However, lack of strictly correlation between clustering and geographic origins suggested extensive germplasm exchanges of alfalfa germplasm across diverse geographic regions. The quantitative analysis of the genetic diversity and population structure in this study could be useful for genetic and genomic analysis and utilization of the genetic variation in alfalfa breeding. PMID:25901573

Quantitative genetic analysis of brain copper and zinc in BXD recombinant inbred mice.

PubMed

Jones, Leslie C; McCarthy, Kristin A; Beard, John L; Keen, Carl L; Jones, Byron C

2006-01-01

Copper and zinc are trace nutrients essential for normal brain function, yet an excess of these elements can be toxic. It is important therefore that these metals be closely regulated. We recently conducted a quantitative trait loci (QTL) analysis to identify chromosomal regions in the mouse containing possible regulatory genes. The animals came from 15 strains of the BXD/Ty recombinant inbred (RI) strain panel and the brain regions analyzed were frontal cortex, caudate-putamen, nucleus accumbens and ventral midbrain. Several QTL were identified for copper and/or zinc, most notably on chromosomes 1, 8, 16 and 17. Genetic correlational analysis also revealed associations between these metals and dopamine, cocaine responses, saccharine preference, immune response and seizure susceptibility. Notably, the QTL on chromosome 17 is also associated with seizure susceptibility and contains the histocompatibility H2 complex. This work shows that regulation of zinc and copper is under polygenic influence and is intimately related to CNS function. Future work will reveal genes underlying the QTL and how they interact with other genes and the environment. More importantly, revelation of the genetic underpinnings of copper and zinc brain homeostasis will aid our understanding of neurological diseases that are related to copper and zinc imbalance.

Easy calculations of lod scores and genetic risks on small computers.

PubMed Central

Lathrop, G M; Lalouel, J M

1984-01-01

A computer program that calculates lod scores and genetic risks for a wide variety of both qualitative and quantitative genetic traits is discussed. An illustration is given of the joint use of a genetic marker, affection status, and quantitative information in counseling situations regarding Duchenne muscular dystrophy. PMID:6585139

Quantitative Genetics in the Era of Molecular Genetics: Learning Abilities and Disabilities as an Example

ERIC Educational Resources Information Center

Haworth, Claire M. A.; Plomin, Robert

2010-01-01

Objective: To consider recent findings from quantitative genetic research in the context of molecular genetic research, especially genome-wide association studies. We focus on findings that go beyond merely estimating heritability. We use learning abilities and disabilities as examples. Method: Recent twin research in the area of learning…

Quantitative genetics of age at reproduction in wild swans: Support for antagonistic pleiotropy models of senescence

PubMed Central

Charmantier, Anne; Perrins, Christopher; McCleery, Robin H.; Sheldon, Ben C.

2006-01-01

Why do individuals stop reproducing after a certain age, and how is this age determined? The antagonistic pleiotropy theory for the evolution of senescence predicts that increased early-life performance should be accompanied by earlier (or faster) senescence. Hence, an individual that has started to breed early should also lose its reproductive capacities early. We investigate here the relationship between age at first reproduction (AFR) and age at last reproduction (ALR) in a free-ranging mute swan (Cygnus olor) population monitored for 36 years. Using multivariate analyses on the longitudinal data, we show that both traits are strongly selected in opposite directions. Analysis of the phenotypic covariance between these characters shows that individuals vary in their inherent quality, such that some individuals have earlier AFR and later ALR than expected. Quantitative genetic pedigree analyses show that both traits possess additive genetic variance but also that AFR and ALR are positively genetically correlated. Hence, although both traits display heritable variation and are under opposing directional selection, their evolution is constrained by a strong evolutionary tradeoff. These results are consistent with the theory that increased early-life performance comes with faster senescence because of genetic tradeoffs. PMID:16618935

High-Content Screening for Quantitative Cell Biology.

PubMed

Mattiazzi Usaj, Mojca; Styles, Erin B; Verster, Adrian J; Friesen, Helena; Boone, Charles; Andrews, Brenda J

2016-08-01

High-content screening (HCS), which combines automated fluorescence microscopy with quantitative image analysis, allows the acquisition of unbiased multiparametric data at the single cell level. This approach has been used to address diverse biological questions and identify a plethora of quantitative phenotypes of varying complexity in numerous different model systems. Here, we describe some recent applications of HCS, ranging from the identification of genes required for specific biological processes to the characterization of genetic interactions. We review the steps involved in the design of useful biological assays and automated image analysis, and describe major challenges associated with each. Additionally, we highlight emerging technologies and future challenges, and discuss how the field of HCS might be enhanced in the future. Copyright © 2016 Elsevier Ltd. All rights reserved.

Using information content and base frequencies to distinguish mutations from genetic polymorphisms in splice junction recognition sites.

PubMed

Rogan, P K; Schneider, T D

1995-01-01

Predicting the effects of nucleotide substitutions in human splice sites has been based on analysis of consensus sequences. We used a graphic representation of sequence conservation and base frequency, the sequence logo, to demonstrate that a change in a splice acceptor of hMSH2 (a gene associated with familial nonpolyposis colon cancer) probably does not reduce splicing efficiency. This confirms a population genetic study that suggested that this substitution is a genetic polymorphism. The information theory-based sequence logo is quantitative and more sensitive than the corresponding splice acceptor consensus sequence for detection of true mutations. Information analysis may potentially be used to distinguish polymorphisms from mutations in other types of transcriptional, translational, or protein-coding motifs.

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.

Metabolite profiling and quantitative genetics of natural variation for flavonoids in Arabidopsis

PubMed Central

Routaboul, Jean-Marc; Dubos, Christian; Beck, Gilles; Marquis, Catherine; Bidzinski, Przemyslaw; Loudet, Olivier; Lepiniec, Loïc

2012-01-01

Little is known about the range and the genetic bases of naturally occurring variation for flavonoids. Using Arabidopsis thaliana seed as a model, the flavonoid content of 41 accessions and two recombinant inbred line (RIL) sets derived from divergent accessions (Cvi-0×Col-0 and Bay-0×Shahdara) were analysed. These accessions and RILs showed mainly quantitative rather than qualitative changes. To dissect the genetic architecture underlying these differences, a quantitative trait locus (QTL) analysis was performed on the two segregating populations. Twenty-two flavonoid QTLs were detected that accounted for 11–64% of the observed trait variations, only one QTL being common to both RIL sets. Sixteen of these QTLs were confirmed and coarsely mapped using heterogeneous inbred families (HIFs). Three genes, namely TRANSPARENT TESTA (TT)7, TT15, and MYB12, were proposed to underlie their variations since the corresponding mutants and QTLs displayed similar specific flavonoid changes. Interestingly, most loci did not co-localize with any gene known to be involved in flavonoid metabolism. This latter result shows that novel functions have yet to be characterized and paves the way for their isolation. PMID:22442426

Divergent selection along climatic gradients in a rare central European endemic species, Saxifraga sponhemica

PubMed Central

Walisch, Tania J.; Colling, Guy; Bodenseh, Melanie; Matthies, Diethart

2015-01-01

Background and Aims The effects of habitat fragmentation on quantitative genetic variation in plant populations are still poorly known. Saxifraga sponhemica is a rare endemic of Central Europe with a disjunct distribution, and a stable and specialized habitat of treeless screes and cliffs. This study therefore used S. sponhemica as a model species to compare quantitative and molecular variation in order to explore (1) the relative importance of drift and selection in shaping the distribution of quantitative genetic variation along climatic gradients; (2) the relationship between plant fitness, quantitative genetic variation, molecular genetic variation and population size; and (3) the relationship between the differentiation of a trait among populations and its evolvability. Methods Genetic variation within and among 22 populations from the whole distribution area of S. sponhemica was studied using RAPD (random amplified polymorphic DNA) markers, and climatic variables were obtained for each site. Seeds were collected from each population and germinated, and seedlings were transplanted into a common garden for determination of variation in plant traits. Key Results In contrast to previous results from rare plant species, strong evidence was found for divergent selection. Most population trait means of S. sponhemica were significantly related to climate gradients, indicating adaptation. Quantitative genetic differentiation increased with geographical distance, even when neutral molecular divergence was controlled for, and QST exceeded FST for some traits. The evolvability of traits was negatively correlated with the degree of differentiation among populations (QST), i.e. traits under strong selection showed little genetic variation within populations. The evolutionary potential of a population was not related to its size, the performance of the population or its neutral genetic diversity. However, performance in the common garden was lower for plants from populations with reduced molecular genetic variation, suggesting inbreeding depression due to genetic erosion. Conclusions The findings suggest that studies of molecular and quantitative genetic variation may provide complementary insights important for the conservation of rare species. The strong differentiation of quantitative traits among populations shows that selection can be an important force for structuring variation in evolutionarily important traits even for rare endemic species restricted to very specific habitats. PMID:25862244

Quantitative Resistance: More Than Just Perception of a Pathogen

PubMed Central

2017-01-01

Molecular plant pathology has focused on studying large-effect qualitative resistance loci that predominantly function in detecting pathogens and/or transmitting signals resulting from pathogen detection. By contrast, less is known about quantitative resistance loci, particularly the molecular mechanisms controlling variation in quantitative resistance. Recent studies have provided insight into these mechanisms, showing that genetic variation at hundreds of causal genes may underpin quantitative resistance. Loci controlling quantitative resistance contain some of the same causal genes that mediate qualitative resistance, but the predominant mechanisms of quantitative resistance extend beyond pathogen recognition. Indeed, most causal genes for quantitative resistance encode specific defense-related outputs such as strengthening of the cell wall or defense compound biosynthesis. Extending previous work on qualitative resistance to focus on the mechanisms of quantitative resistance, such as the link between perception of microbe-associated molecular patterns and growth, has shown that the mechanisms underlying these defense outputs are also highly polygenic. Studies that include genetic variation in the pathogen have begun to highlight a potential need to rethink how the field considers broad-spectrum resistance and how it is affected by genetic variation within pathogen species and between pathogen species. These studies are broadening our understanding of quantitative resistance and highlighting the potentially vast scale of the genetic basis of quantitative resistance. PMID:28302676

Highly sensitive and quantitative detection of rare pathogens through agarose droplet microfluidic emulsion PCR at the single-cell level.

PubMed

Zhu, Zhi; Zhang, Wenhua; Leng, Xuefei; Zhang, Mingxia; Guan, Zhichao; Lu, Jiangquan; Yang, Chaoyong James

2012-10-21

Genetic alternations can serve as highly specific biomarkers to distinguish fatal bacteria or cancer cells from their normal counterparts. However, these mutations normally exist in very rare amount in the presence of a large excess of non-mutated analogs. Taking the notorious pathogen E. coli O157:H7 as the target analyte, we have developed an agarose droplet-based microfluidic ePCR method for highly sensitive, specific and quantitative detection of rare pathogens in the high background of normal bacteria. Massively parallel singleplex and multiplex PCR at the single-cell level in agarose droplets have been successfully established. Moreover, we challenged the system with rare pathogen detection and realized the sensitive and quantitative analysis of a single E. coli O157:H7 cell in the high background of 100,000 excess normal K12 cells. For the first time, we demonstrated rare pathogen detection through agarose droplet microfluidic ePCR. Such a multiplex single-cell agarose droplet amplification method enables ultra-high throughput and multi-parameter genetic analysis of large population of cells at the single-cell level to uncover the stochastic variations in biological systems.

EPS-LASSO: Test for High-Dimensional Regression Under Extreme Phenotype Sampling of Continuous Traits.

PubMed

Xu, Chao; Fang, Jian; Shen, Hui; Wang, Yu-Ping; Deng, Hong-Wen

2018-01-25

Extreme phenotype sampling (EPS) is a broadly-used design to identify candidate genetic factors contributing to the variation of quantitative traits. By enriching the signals in extreme phenotypic samples, EPS can boost the association power compared to random sampling. Most existing statistical methods for EPS examine the genetic factors individually, despite many quantitative traits have multiple genetic factors underlying their variation. It is desirable to model the joint effects of genetic factors, which may increase the power and identify novel quantitative trait loci under EPS. The joint analysis of genetic data in high-dimensional situations requires specialized techniques, e.g., the least absolute shrinkage and selection operator (LASSO). Although there are extensive research and application related to LASSO, the statistical inference and testing for the sparse model under EPS remain unknown. We propose a novel sparse model (EPS-LASSO) with hypothesis test for high-dimensional regression under EPS based on a decorrelated score function. The comprehensive simulation shows EPS-LASSO outperforms existing methods with stable type I error and FDR control. EPS-LASSO can provide a consistent power for both low- and high-dimensional situations compared with the other methods dealing with high-dimensional situations. The power of EPS-LASSO is close to other low-dimensional methods when the causal effect sizes are small and is superior when the effects are large. Applying EPS-LASSO to a transcriptome-wide gene expression study for obesity reveals 10 significant body mass index associated genes. Our results indicate that EPS-LASSO is an effective method for EPS data analysis, which can account for correlated predictors. The source code is available at https://github.com/xu1912/EPSLASSO. hdeng2@tulane.edu. Supplementary data are available at Bioinformatics online. © The Author (2018). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Lack of effect of lactose digestion status on baseline fecal microflora

PubMed Central

Szilagyi, Andrew; Shrier, Ian; Chong, George; Je, Jung Sung; Park, Sunghoon; Heilpern, Debra; Lalonde, Catherine; Cote, Louis-Francois; Lee, Byong

2009-01-01

BACKGROUND: The genetics of intestinal lactase divide the world’s population into two phenotypes: the ability (a dominant trait) or inability (a recessive trait) to digest lactose. A prebiotic effect of lactose may impact the colonic flora of these phenotypes differently. OBJECTIVE: To detect and evaluate the effects of lactose on subjects divided according to their ability to digest lactose. METHODS: A total of 57 healthy maldigesters (n=30) and digesters (n=27) completed diet questionnaires, genetic and breath hydrogen testing, and quantitative stool analysis for species of bacteria. Log10 transformation of bacterial counts was compared with lactose intake in both groups using multiple regression analysis. RESULTS: There was a significant relationship between genetic and breath hydrogen tests. Daily lactose intake was marginally lower in lactose maldigesters (median [interquartile range] 12.2 g [31 g] versus 15 g [29.6 g], respectively). There was no relationship between lactose intake and breath hydrogen tests in either group. There were no differences in bacterial counts between the two groups, nor was there a relationship between bacterial counts and lactose intake in either group. CONCLUSION: The differential bacterial effects of lactose were not quantitatively detected in stool samples taken in the present study. PMID:19893771

Validation and application of quantitative PCR assays using host-specific Bacteroidales genetic markers for swine fecal pollution tracking.

PubMed

Fan, Lihua; Shuai, Jiangbing; Zeng, Ruoxue; Mo, Hongfei; Wang, Suhua; Zhang, Xiaofeng; He, Yongqiang

2017-12-01

Genome fragment enrichment (GFE) method was applied to identify host-specific bacterial genetic markers that differ among different fecal metagenomes. To enrich for swine-specific DNA fragments, swine fecal DNA composite (n = 34) was challenged against a DNA composite consisting of cow, human, goat, sheep, chicken, duck and goose fecal DNA extracts (n = 83). Bioinformatic analyses of 384 non-redundant swine enriched metagenomic sequences indicated a preponderance of Bacteroidales-like regions predicted to encode metabolism-associated, cellular processes and information storage and processing. After challenged against fecal DNA extracted from different animal sources, four sequences from the clone libraries targeting two Bacteroidales- (genes 1-38 and 3-53), a Clostridia- (gene 2-109) as well as a Bacilli-like sequence (gene 2-95), respectively, showed high specificity to swine feces based on PCR analysis. Host-specificity and host-sensitivity analysis confirmed that oligonucleotide primers and probes capable of annealing to select Bacteroidales-like sequences (1-38 and 3-53) exhibited high specificity (>90%) in quantitative PCR assays with 71 fecal DNAs from non-target animal sources. The two assays also demonstrated broad distributions of corresponding genetic markers (>94% positive) among 72 swine feces. After evaluation with environmental water samples from different areas, swine-targeted assays based on two Bacteroidales-like GFE sequences appear to be suitable quantitative tracing tools for swine fecal pollution. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantitative genetic analysis of the bTB diagnostic single intradermal comparative cervical test (SICCT).

PubMed

Tsairidou, Smaragda; Brotherstone, Susan; Coffey, Mike; Bishop, Stephen C; Woolliams, John A

2016-11-24

Bovine tuberculosis (bTB) is a disease of significant economic importance and is a persistent animal health problem with implications for public health worldwide. Control of bTB in the UK has relied on diagnosis through the single intradermal comparative cervical test (SICCT). However, limitations in the sensitivity of this test hinder successful eradication and the control of bTB remains a major challenge. Genetic selection for cattle that are more resistant to bTB infection can assist in bTB control. The aim of this study was to conduct a quantitative genetic analysis of SICCT measurements collected during bTB herd testing. Genetic selection for bTB resistance will be partially informed by SICCT-based diagnosis; therefore it is important to know whether, in addition to increasing bTB resistance, this might also alter genetically the epidemiological characteristics of SICCT. Our main findings are that: (1) the SICCT test is robust at the genetic level, since its hierarchy and comparative nature provide substantial protection against random genetic changes that arise from genetic drift and from correlated responses among its components due to either natural or artificial selection; (2) the comparative nature of SICCT provides effective control for initial skin thickness and age-dependent differences; and (3) continuous variation in SICCT is only lowly heritable and has a weak correlation with SICCT positivity among healthy animals which was not significantly different from zero (P > 0.05). These emerging results demonstrate that genetic selection for bTB resistance is unlikely to change the probability of correctly identifying non-infected animals, i.e. the test's specificity, while reducing the overall number of cases. This study cannot exclude all theoretical risks from selection on resistance to bTB infection but the role of SICCT in disease control is unlikely to be rapidly undermined, with any adverse correlated responses expected to be weak and slow, which allow them to be monitored and managed.

Construction of a genetic map using EST-SSR markers and QTL analysis of major agronomic characters in hexaploid sweet potato (Ipomoea batatas (L.) Lam).

PubMed

Kim, Jin-Hee; Chung, Il Kyung; Kim, Kyung-Min

2017-01-01

The Sweet potato, Ipomoea batatas (L.) Lam, is difficult to study in genetics and genomics because it is a hexaploid. The sweet potato study not have been performed domestically or internationally. In this study was performed to construct genetic map and quantitative trait loci (QTL) analysis. A total of 245 EST-SSR markers were developed, and the map was constructed by using 210 of those markers. The total map length was 1508.1 cM, and the mean distance between markers was 7.2 cM. Fifteen characteristics were investigated for QTLs analysis. According to those, the Four QTLs were identified, and The LOD score was 3.0. Further studies need to develop molecular markers in terms of EST-SSR markers for doing to be capable of efficient breeding. The genetic map created here using EST-SSR markers will facilitate planned breeding of sweet potato cultivars with various desirable traits.

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.

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

Physiologically based pharmacokinetic (PBPK) modeling considering methylated trivalent arsenicals

EPA Science Inventory

PBPK modeling provides a quantitative biologically-based framework to integrate diverse types of information for application to risk analysis. For example, genetic polymorphisms in arsenic metabolizing enzymes (AS3MT) can lead to differences in target tissue dosimetry for key tri...

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

PubMed

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

2018-06-25

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

Quality of Life and Psychological State in Chinese Breast Cancer Patients Who Received BRCA1/2 Genetic Testing

PubMed Central

Qiu, Jiajia; Guan, Jiaqin; Yang, Xiaochen; Wu, Jiong; Liu, Guangyu; Di, Genhong; Chen, Canming; Hou, Yifeng; Han, Qixia; Shen, Zhenzhou; Shao, Zhimin; Hu, Zhen

2016-01-01

Background This study aims to understand the quality of life (QOL) and psychological state (PS) of Chinese breast cancer patients who received BRCA1/2 genetic testing; to examine the psychological changes between BRCA1/2 mutation carriers and non-carriers; and to further explore the psychological experience of BRCA1/2 mutation carriers. Methods This study was combined with quantitative and qualitative designs. First, we performed a quantitative investigation using FACT-B (Chinese version) and Irritability, Depression and Anxiety scale (IDA) to assess the QOL and PS in breast cancer patients who received BRCA1/2 genetic testing. Then semi-structured in-depth qualitative interviews among 13 mutation carriers were conducted in hospital. Results Results from the quantitative study showed QOL scores were relatively high and the IDA scores were relatively low among the patients, and there was no significant difference in the QOL or IDA scores between non-carriers and carriers. Based on the qualitative analysis, four main themes emerged: (1) Finding the reason for having breast cancer; (2) Negative emotions; (3) Behavioral changes; (4) Lack of information. Conclusions The present study showed that QOL and PS are good among the breast cancer patients who received genetic testing. Genetic testing itself does not cause long psychosocial effects. BRCA1/2 mutation carriers may have certain negative emotions at the first stage they knew the testing results and may initiate behavioral and lifestyle changes. The patients with a BRCA1/2 mutation desire knowledge with regard to genetic aspects in mainland China. Professional information and advice can be provided to relieve the patients’ negative emotions when they were informed of gene defect. PMID:27428375

Genetic variation maintained in multilocus models of additive quantitative traits under stabilizing selection.

PubMed Central

Bürger, R; Gimelfarb, A

1999-01-01

Stabilizing selection for an intermediate optimum is generally considered to deplete genetic variation in quantitative traits. However, conflicting results from various types of models have been obtained. While classical analyses assuming a large number of independent additive loci with individually small effects indicated that no genetic variation is preserved under stabilizing selection, several analyses of two-locus models showed the contrary. We perform a complete analysis of a generalization of Wright's two-locus quadratic-optimum model and investigate numerically the ability of quadratic stabilizing selection to maintain genetic variation in additive quantitative traits controlled by up to five loci. A statistical approach is employed by choosing randomly 4000 parameter sets (allelic effects, recombination rates, and strength of selection) for a given number of loci. For each parameter set we iterate the recursion equations that describe the dynamics of gamete frequencies starting from 20 randomly chosen initial conditions until an equilibrium is reached, record the quantities of interest, and calculate their corresponding mean values. As the number of loci increases from two to five, the fraction of the genome expected to be polymorphic declines surprisingly rapidly, and the loci that are polymorphic increasingly are those with small effects on the trait. As a result, the genetic variance expected to be maintained under stabilizing selection decreases very rapidly with increased number of loci. The equilibrium structure expected under stabilizing selection on an additive trait differs markedly from that expected under selection with no constraints on genotypic fitness values. The expected genetic variance, the expected polymorphic fraction of the genome, as well as other quantities of interest, are only weakly dependent on the selection intensity and the level of recombination. PMID:10353920

A quantitative genetic analysis of hibernation emergence date in a wild population of Columbian ground squirrels.

PubMed

Lane, J E; Kruuk, L E B; Charmantier, A; Murie, J O; Coltman, D W; Buoro, M; Raveh, S; Dobson, F S

2011-09-01

The life history schedules of wild organisms have long attracted scientific interest, and, in light of ongoing climate change, an understanding of their genetic and environmental underpinnings is increasingly becoming of applied concern. We used a multi-generation pedigree and detailed phenotypic records, spanning 18 years, to estimate the quantitative genetic influences on the timing of hibernation emergence in a wild population of Columbian ground squirrels (Urocitellus columbianus). Emergence date was significantly heritable [h(2) = 0.22 ± 0.05 (in females) and 0.34 ± 0.14 (in males)], and there was a positive genetic correlation (r(G) = 0.76 ± 0.22) between male and female emergence dates. In adult females, the heritabilities of body mass at emergence and oestrous date were h(2) = 0.23 ± 0.09 and h(2) = 0.18 ± 0.12, respectively. The date of hibernation emergence has been hypothesized to have evolved so as to synchronize subsequent reproduction with upcoming peaks in vegetation abundance. In support of this hypothesis, although levels of phenotypic variance in emergence date were higher than oestrous date, there was a highly significant genetic correlation between the two (r(G) = 0.98 ± 0.01). Hibernation is a prominent feature in the annual cycle of many small mammals, but our understanding of its influences lags behind that for phenological traits in many other taxa. Our results provide the first insight into its quantitative genetic influences and thus help contribute to a more general understanding of its evolutionary significance. © 2011 The Authors. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.

Quantitative trait locus analysis of heterosis for plant height and ear height in an elite maize hybrid zhengdan 958 by design III.

PubMed

Li, Hongjian; Yang, Qingsong; Fan, Nannan; Zhang, Ming; Zhai, Huijie; Ni, Zhongfu; Zhang, Yirong

2017-04-17

Plant height (PH) and ear height (EH) are two important agronomic traits in maize selection breeding. F 1 hybrid exhibit significant heterosis for PH and EH as compared to their parental inbred lines. To understand the genetic basis of heterosis controlling PH and EH, we conducted quantitative trait locus (QTL) analysis using a recombinant inbreed line (RIL) based design III population derived from the elite maize hybrid Zhengdan 958 in five environments. A total of 14 environmentally stable QTLs were identified, and the number of QTLs for Z 1 and Z 2 populations was six and eight, respectively. Notably, all the eight environmentally stable QTLs for Z 2 were characterized by overdominance effect (OD), suggesting that overdominant QTLs were the most important contributors to heterosis for PH and EH. Furthermore, 14 environmentally stable QTLs were anchored on six genomic regions, among which four are trait-specific QTLs, suggesting that the genetic basis for PH and EH is partially different. Additionally, qPH.A-1.3, modifying about 10 centimeters of PH, was further validated in backcross populations. The genetic basis for PH and EH is partially different, and overdominant QTLs are important factors for heterosis of PH and EH. A major QTL qPH.A-1.3 may be a desired target for genetic improvement of maize plant height.

Spotsizer: High-throughput quantitative analysis of microbial growth.

PubMed

Bischof, Leanne; Převorovský, Martin; Rallis, Charalampos; Jeffares, Daniel C; Arzhaeva, Yulia; Bähler, Jürg

2016-10-01

Microbial colony growth can serve as a useful readout in assays for studying complex genetic interactions or the effects of chemical compounds. Although computational tools for acquiring quantitative measurements of microbial colonies have been developed, their utility can be compromised by inflexible input image requirements, non-trivial installation procedures, or complicated operation. Here, we present the Spotsizer software tool for automated colony size measurements in images of robotically arrayed microbial colonies. Spotsizer features a convenient graphical user interface (GUI), has both single-image and batch-processing capabilities, and works with multiple input image formats and different colony grid types. We demonstrate how Spotsizer can be used for high-throughput quantitative analysis of fission yeast growth. The user-friendly Spotsizer tool provides rapid, accurate, and robust quantitative analyses of microbial growth in a high-throughput format. Spotsizer is freely available at https://data.csiro.au/dap/landingpage?pid=csiro:15330 under a proprietary CSIRO license.

QUANTITATIVE GENETIC ACTIVITY GRAPHICAL PROFILES FOR USE IN CHEMICAL EVALUATION

EPA Science Inventory

A graphic approach termed a Genetic Activity Profile (GAP) has been developed to display a matrix of data on the genetic and related effects of selected chemical agents. he profiles provide a visual overview of the quantitative (doses) and qualitative (test results) data for each...

Breeding and quantitative genetics advances in sunflower Sclerotinia research

USDA-ARS?s Scientific Manuscript database

Genetic research of the sunflower research unit, USDA-ARS, in Fargo, ND, was discussed in a presentation to a group of producers, industry representatives, and scientists. The need for sunflower quantitative genetics research to find and capture Sclerotinia resistance is increasing with every year t...

Variable selection based near infrared spectroscopy quantitative and qualitative analysis on wheat wet gluten

NASA Astrophysics Data System (ADS)

Lü, Chengxu; Jiang, Xunpeng; Zhou, Xingfan; Zhang, Yinqiao; Zhang, Naiqian; Wei, Chongfeng; Mao, Wenhua

2017-10-01

Wet gluten is a useful quality indicator for wheat, and short wave near infrared spectroscopy (NIRS) is a high performance technique with the advantage of economic rapid and nondestructive test. To study the feasibility of short wave NIRS analyzing wet gluten directly from wheat seed, 54 representative wheat seed samples were collected and scanned by spectrometer. 8 spectral pretreatment method and genetic algorithm (GA) variable selection method were used to optimize analysis. Both quantitative and qualitative model of wet gluten were built by partial least squares regression and discriminate analysis. For quantitative analysis, normalization is the optimized pretreatment method, 17 wet gluten sensitive variables are selected by GA, and GA model performs a better result than that of all variable model, with R2V=0.88, and RMSEV=1.47. For qualitative analysis, automatic weighted least squares baseline is the optimized pretreatment method, all variable models perform better results than those of GA models. The correct classification rates of 3 class of <24%, 24-30%, >30% wet gluten content are 95.45, 84.52, and 90.00%, respectively. The short wave NIRS technique shows potential for both quantitative and qualitative analysis of wet gluten for wheat seed.

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.

The integration of quantitative genetics, paleontology, and neontology reveals genetic underpinnings of primate dental evolution.

PubMed

Hlusko, Leslea J; Schmitt, Christopher A; Monson, Tesla A; Brasil, Marianne F; Mahaney, Michael C

2016-08-16

Developmental genetics research on mice provides a relatively sound understanding of the genes necessary and sufficient to make mammalian teeth. However, mouse dentitions are highly derived compared with human dentitions, complicating the application of these insights to human biology. We used quantitative genetic analyses of data from living nonhuman primates and extensive osteological and paleontological collections to refine our assessment of dental phenotypes so that they better represent how the underlying genetic mechanisms actually influence anatomical variation. We identify ratios that better characterize the output of two dental genetic patterning mechanisms for primate dentitions. These two newly defined phenotypes are heritable with no measurable pleiotropic effects. When we consider how these two phenotypes vary across neontological and paleontological datasets, we find that the major Middle Miocene taxonomic shift in primate diversity is characterized by a shift in these two genetic outputs. Our results build on the mouse model by combining quantitative genetics and paleontology, and thereby elucidate how genetic mechanisms likely underlie major events in primate evolution.

A new method of linkage analysis using LOD scores for quantitative traits supports linkage of monoamine oxidase activity to D17S250 in the Collaborative Study on the Genetics of Alcoholism pedigrees.

PubMed

Curtis, David; Knight, Jo; Sham, Pak C

2005-09-01

Although LOD score methods have been applied to diseases with complex modes of inheritance, linkage analysis of quantitative traits has tended to rely on non-parametric methods based on regression or variance components analysis. Here, we describe a new method for LOD score analysis of quantitative traits which does not require specification of a mode of inheritance. The technique is derived from the MFLINK method for dichotomous traits. A range of plausible transmission models is constructed, constrained to yield the correct population mean and variance for the trait but differing with respect to the contribution to the variance due to the locus under consideration. Maximized LOD scores under homogeneity and admixture are calculated, as is a model-free LOD score which compares the maximized likelihoods under admixture assuming linkage and no linkage. These LOD scores have known asymptotic distributions and hence can be used to provide a statistical test for linkage. The method has been implemented in a program called QMFLINK. It was applied to data sets simulated using a variety of transmission models and to a measure of monoamine oxidase activity in 105 pedigrees from the Collaborative Study on the Genetics of Alcoholism. With the simulated data, the results showed that the new method could detect linkage well if the true allele frequency for the trait was close to that specified. However, it performed poorly on models in which the true allele frequency was much rarer. For the Collaborative Study on the Genetics of Alcoholism data set only a modest overlap was observed between the results obtained from the new method and those obtained when the same data were analysed previously using regression and variance components analysis. Of interest is that D17S250 produced a maximized LOD score under homogeneity and admixture of 2.6 but did not indicate linkage using the previous methods. However, this region did produce evidence for linkage in a separate data set, suggesting that QMFLINK may have been able to detect a true linkage which was not picked up by the other methods. The application of model-free LOD score analysis to quantitative traits is novel and deserves further evaluation of its merits and disadvantages relative to other methods.

A novel structure-aware sparse learning algorithm for brain imaging genetics.

PubMed

Du, Lei; Jingwen, Yan; Kim, Sungeun; Risacher, Shannon L; Huang, Heng; Inlow, Mark; Moore, Jason H; Saykin, Andrew J; Shen, Li

2014-01-01

Brain imaging genetics is an emergent research field where the association between genetic variations such as single nucleotide polymorphisms (SNPs) and neuroimaging quantitative traits (QTs) is evaluated. Sparse canonical correlation analysis (SCCA) is a bi-multivariate analysis method that has the potential to reveal complex multi-SNP-multi-QT associations. Most existing SCCA algorithms are designed using the soft threshold strategy, which assumes that the features in the data are independent from each other. This independence assumption usually does not hold in imaging genetic data, and thus inevitably limits the capability of yielding optimal solutions. We propose a novel structure-aware SCCA (denoted as S2CCA) algorithm to not only eliminate the independence assumption for the input data, but also incorporate group-like structure in the model. Empirical comparison with a widely used SCCA implementation, on both simulated and real imaging genetic data, demonstrated that S2CCA could yield improved prediction performance and biologically meaningful findings.

Construction of a high-density linkage map and mapping quantitative trait loci for somatic embryogenesis using leaf petioles as explants in upland cotton (Gossypium hirsutum L.).

PubMed

Xu, Zhenzhen; Zhang, Chaojun; Ge, Xiaoyang; Wang, Ni; Zhou, Kehai; Yang, Xiaojie; Wu, Zhixia; Zhang, Xueyan; Liu, Chuanliang; Yang, Zuoren; Li, Changfeng; Liu, Kun; Yang, Zhaoen; Qian, Yuyuan; Li, Fuguang

2015-07-01

The first high-density linkage map was constructed to identify quantitative trait loci (QTLs) for somatic embryogenesis (SE) in cotton ( Gossypium hirsutum L.) using leaf petioles as explants. Cotton transformation is highly limited by only a few regenerable genotypes and the lack of understanding of the genetic and molecular basis of somatic embryogenesis (SE) in cotton (Gossypium hirsutum L.). To construct a more saturated linkage map and further identify quantitative trait loci (QTLs) for SE using leaf petioles as explants, a high embryogenesis frequency line (W10) from the commercial Chinese cotton cultivar CRI24 was crossed with TM-1, a genetic standard upland cotton with no embryogenesis frequency. The genetic map spanned 2300.41 cM in genetic distance and contained 411 polymorphic simple sequence repeat (SSR) loci. Of the 411 mapped loci, 25 were developed from unigenes identified for SE in our previous study. Six QTLs for SE were detected by composite interval mapping method, each explaining 6.88-37.07% of the phenotypic variance. Single marker analysis was also performed to verify the reliability of QTLs detection, and the SSR markers NAU3325 and DPL0209 were detected by the two methods. Further studies on the relatively stable and anchoring QTLs/markers for SE in an advanced population of W10 × TM-1 and other cross combinations with different SE abilities may shed light on the genetic and molecular mechanism of SE in cotton.

[Analytic methods for seed models with genotype x environment interactions].

PubMed

Zhu, J

1996-01-01

Genetic models with genotype effect (G) and genotype x environment interaction effect (GE) are proposed for analyzing generation means of seed quantitative traits in crops. The total genetic effect (G) is partitioned into seed direct genetic effect (G0), cytoplasm genetic of effect (C), and maternal plant genetic effect (Gm). Seed direct genetic effect (G0) can be further partitioned into direct additive (A) and direct dominance (D) genetic components. Maternal genetic effect (Gm) can also be partitioned into maternal additive (Am) and maternal dominance (Dm) genetic components. The total genotype x environment interaction effect (GE) can also be partitioned into direct genetic by environment interaction effect (G0E), cytoplasm genetic by environment interaction effect (CE), and maternal genetic by environment interaction effect (GmE). G0E can be partitioned into direct additive by environment interaction (AE) and direct dominance by environment interaction (DE) genetic components. GmE can also be partitioned into maternal additive by environment interaction (AmE) and maternal dominance by environment interaction (DmE) genetic components. Partitions of genetic components are listed for parent, F1, F2 and backcrosses. A set of parents, their reciprocal F1 and F2 seeds is applicable for efficient analysis of seed quantitative traits. MINQUE(0/1) method can be used for estimating variance and covariance components. Unbiased estimation for covariance components between two traits can also be obtained by the MINQUE(0/1) method. Random genetic effects in seed models are predictable by the Adjusted Unbiased Prediction (AUP) approach with MINQUE(0/1) method. The jackknife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects, which can be further used in a t-test for parameter. Unbiasedness and efficiency for estimating variance components and predicting genetic effects are tested by Monte Carlo simulations.

Quantitative genetic models of sexual conflict based on interacting phenotypes.

PubMed

Moore, Allen J; Pizzari, Tommaso

2005-05-01

Evolutionary conflict arises between reproductive partners when alternative reproductive opportunities are available. Sexual conflict can generate sexually antagonistic selection, which mediates sexual selection and intersexual coevolution. However, despite intense interest, the evolutionary implications of sexual conflict remain unresolved. We propose a novel theoretical approach to study the evolution of sexually antagonistic phenotypes based on quantitative genetics and the measure of social selection arising from male-female interactions. We consider the phenotype of one sex as both a genetically influenced evolving trait as well as the (evolving) social environment in which the phenotype of the opposite sex evolves. Several important points emerge from our analysis, including the relationship between direct selection on one sex and indirect effects through selection on the opposite sex. We suggest that the proposed approach may be a valuable tool to complement other theoretical approaches currently used to study sexual conflict. Most importantly, our approach highlights areas where additional empirical data can help clarify the role of sexual conflict in the evolutionary process.

Quantitative Resistance: More Than Just Perception of a Pathogen.

PubMed

Corwin, Jason A; Kliebenstein, Daniel J

2017-04-01

Molecular plant pathology has focused on studying large-effect qualitative resistance loci that predominantly function in detecting pathogens and/or transmitting signals resulting from pathogen detection. By contrast, less is known about quantitative resistance loci, particularly the molecular mechanisms controlling variation in quantitative resistance. Recent studies have provided insight into these mechanisms, showing that genetic variation at hundreds of causal genes may underpin quantitative resistance. Loci controlling quantitative resistance contain some of the same causal genes that mediate qualitative resistance, but the predominant mechanisms of quantitative resistance extend beyond pathogen recognition. Indeed, most causal genes for quantitative resistance encode specific defense-related outputs such as strengthening of the cell wall or defense compound biosynthesis. Extending previous work on qualitative resistance to focus on the mechanisms of quantitative resistance, such as the link between perception of microbe-associated molecular patterns and growth, has shown that the mechanisms underlying these defense outputs are also highly polygenic. Studies that include genetic variation in the pathogen have begun to highlight a potential need to rethink how the field considers broad-spectrum resistance and how it is affected by genetic variation within pathogen species and between pathogen species. These studies are broadening our understanding of quantitative resistance and highlighting the potentially vast scale of the genetic basis of quantitative resistance. © 2017 American Society of Plant Biologists. All rights reserved.

Genotype-phenotype association study via new multi-task learning model

PubMed Central

Huo, Zhouyuan; Shen, Dinggang

2018-01-01

Research on the associations between genetic variations and imaging phenotypes is developing with the advance in high-throughput genotype and brain image techniques. Regression analysis of single nucleotide polymorphisms (SNPs) and imaging measures as quantitative traits (QTs) has been proposed to identify the quantitative trait loci (QTL) via multi-task learning models. Recent studies consider the interlinked structures within SNPs and imaging QTs through group lasso, e.g. ℓ2,1-norm, leading to better predictive results and insights of SNPs. However, group sparsity is not enough for representing the correlation between multiple tasks and ℓ2,1-norm regularization is not robust either. In this paper, we propose a new multi-task learning model to analyze the associations between SNPs and QTs. We suppose that low-rank structure is also beneficial to uncover the correlation between genetic variations and imaging phenotypes. Finally, we conduct regression analysis of SNPs and QTs. Experimental results show that our model is more accurate in prediction than compared methods and presents new insights of SNPs. PMID:29218896

Fine-Mapping and Selective Sweep Analysis of QTL for Cold Tolerance in Drosophila melanogaster

PubMed Central

Wilches, Ricardo; Voigt, Susanne; Duchen, Pablo; Laurent, Stefan; Stephan, Wolfgang

2014-01-01

There is a growing interest in investigating the relationship between genes with signatures of natural selection and genes identified in QTL mapping studies using combined population and quantitative genetics approaches. We dissected an X-linked interval of 6.2 Mb, which contains two QTL underlying variation in chill coma recovery time (CCRT) in Drosophila melanogaster from temperate (European) and tropical (African) regions. This resulted in two relatively small regions of 131 kb and 124 kb. The latter one co-localizes with a very strong selective sweep in the European population. We examined the genes within and near the sweep region individually using gene expression analysis and P-element insertion lines. Of the genes overlapping with the sweep, none appears to be related to CCRT. However, we have identified a new candidate gene of CCRT, brinker, which is located just outside the sweep region and is inducible by cold stress. We discuss these results in light of recent population genetics theories on quantitative traits. PMID:24970882

DRIFTSEL: an R package for detecting signals of natural selection in quantitative traits.

PubMed

Karhunen, M; Merilä, J; Leinonen, T; Cano, J M; Ovaskainen, O

2013-07-01

Approaches and tools to differentiate between natural selection and genetic drift as causes of population differentiation are of frequent demand in evolutionary biology. Based on the approach of Ovaskainen et al. (2011), we have developed an R package (DRIFTSEL) that can be used to differentiate between stabilizing selection, diversifying selection and random genetic drift as causes of population differentiation in quantitative traits when neutral marker and quantitative genetic data are available. Apart from illustrating the use of this method and the interpretation of results using simulated data, we apply the package on data from three-spined sticklebacks (Gasterosteus aculeatus) to highlight its virtues. DRIFTSEL can also be used to perform usual quantitative genetic analyses in common-garden study designs. © 2013 John Wiley & Sons Ltd.

MetaFluxNet: the management of metabolic reaction information and quantitative metabolic flux analysis.

PubMed

Lee, Dong-Yup; Yun, Hongsoek; Park, Sunwon; Lee, Sang Yup

2003-11-01

MetaFluxNet is a program package for managing information on the metabolic reaction network and for quantitatively analyzing metabolic fluxes in an interactive and customized way. It allows users to interpret and examine metabolic behavior in response to genetic and/or environmental modifications. As a result, quantitative in silico simulations of metabolic pathways can be carried out to understand the metabolic status and to design the metabolic engineering strategies. The main features of the program include a well-developed model construction environment, user-friendly interface for metabolic flux analysis (MFA), comparative MFA of strains having different genotypes under various environmental conditions, and automated pathway layout creation. http://mbel.kaist.ac.kr/ A manual for MetaFluxNet is available as PDF file.

[Direct-to-consumer genetic testing through Internet: marketing, ethical and social issues].

PubMed

Ducournau, Pascal; Gourraud, Pierre-Antoine; Rial-Sebbag, Emmanuelle; Bulle, Alexandre; Cambon-Thomsen, Anne

2011-01-01

We probably did not anticipate all the consequences of the direct to consumer genetic tests on Internet, resulting from the combined skills of communication and genomic advances. What are the commercial strategies used by the companies offering direct-to-consumer genetic tests on Internet and what are the different social expectations on which they focus? Through a quantitative and qualitative analysis of the web sites offering such tests, it seems that these companies target a triple market based on: the "healthism" which raises health and hygiene to the top of the social values; the contemporary demands of the users to become actual actors of health decisions; and finally on the need for bio-social relationships. These three commercial strategies underlie various ethical and societal issues justifying a general analysis.

Identifying haplotypes for flowering and QTLs for fruit quality in the RosBREED Michigan and Oregon strawberry (Fragaria ×ananassa) breeding sets using pedigree-based analysis [abstract

USDA-ARS?s Scientific Manuscript database

Strawberry (Fragaria ×ananassa) is consumed for its flavor and health benefits. Over the last two decades, several quantitative trait loci (QTL) analysis studies for consumer traits were conducted using low-density genetic maps. The previous studies utilized low-throughput genotyping methodologies. ...

Development and application of a multi-targeting reference plasmid as calibrator for analysis of five genetically modified soybean events.

PubMed

Pi, Liqun; Li, Xiang; Cao, Yiwei; Wang, Canhua; Pan, Liangwen; Yang, Litao

2015-04-01

Reference materials are important in accurate analysis of genetically modified organism (GMO) contents in food/feeds, and development of novel reference plasmid is a new trend in the research of GMO reference materials. Herein, we constructed a novel multi-targeting plasmid, pSOY, which contained seven event-specific sequences of five GM soybeans (MON89788-5', A2704-12-3', A5547-127-3', DP356043-5', DP305423-3', A2704-12-5', and A5547-127-5') and sequence of soybean endogenous reference gene Lectin. We evaluated the specificity, limit of detection and quantification, and applicability of pSOY in both qualitative and quantitative PCR analyses. The limit of detection (LOD) was as low as 20 copies in qualitative PCR, and the limit of quantification (LOQ) in quantitative PCR was 10 copies. In quantitative real-time PCR analysis, the PCR efficiencies of all event-specific and Lectin assays were higher than 90%, and the squared regression coefficients (R(2)) were more than 0.999. The quantification bias varied from 0.21% to 19.29%, and the relative standard deviations were from 1.08% to 9.84% in simulated samples analysis. All the results demonstrated that the developed multi-targeting plasmid, pSOY, was a credible substitute of matrix reference materials, and could be used as a reliable reference calibrator in the identification and quantification of multiple GM soybean events.

Genetic analysis of dyslexia candidate genes in the European cross-linguistic NeuroDys cohort.

PubMed

Becker, Jessica; Czamara, Darina; Scerri, Tom S; Ramus, Franck; Csépe, Valéria; Talcott, Joel B; Stein, John; Morris, Andrew; Ludwig, Kerstin U; Hoffmann, Per; Honbolygó, Ferenc; Tóth, Dénes; Fauchereau, Fabien; Bogliotti, Caroline; Iannuzzi, Stéphanie; Chaix, Yves; Valdois, Sylviane; Billard, Catherine; George, Florence; Soares-Boucaud, Isabelle; Gérard, Christophe-Loïc; van der Mark, Sanne; Schulz, Enrico; Vaessen, Anniek; Maurer, Urs; Lohvansuu, Kaisa; Lyytinen, Heikki; Zucchelli, Marco; Brandeis, Daniel; Blomert, Leo; Leppänen, Paavo H T; Bruder, Jennifer; Monaco, Anthony P; Müller-Myhsok, Bertram; Kere, Juha; Landerl, Karin; Nöthen, Markus M; Schulte-Körne, Gerd; Paracchini, Silvia; Peyrard-Janvid, Myriam; Schumacher, Johannes

2014-05-01

Dyslexia is one of the most common childhood disorders with a prevalence of around 5-10% in school-age children. Although an important genetic component is known to have a role in the aetiology of dyslexia, we are far from understanding the molecular mechanisms leading to the disorder. Several candidate genes have been implicated in dyslexia, including DYX1C1, DCDC2, KIAA0319, and the MRPL19/C2ORF3 locus, each with reports of both positive and no replications. We generated a European cross-linguistic sample of school-age children - the NeuroDys cohort - that includes more than 900 individuals with dyslexia, sampled with homogenous inclusion criteria across eight European countries, and a comparable number of controls. Here, we describe association analysis of the dyslexia candidate genes/locus in the NeuroDys cohort. We performed both case-control and quantitative association analyses of single markers and haplotypes previously reported to be dyslexia-associated. Although we observed association signals in samples from single countries, we did not find any marker or haplotype that was significantly associated with either case-control status or quantitative measurements of word-reading or spelling in the meta-analysis of all eight countries combined. Like in other neurocognitive disorders, our findings underline the need for larger sample sizes to validate possibly weak genetic effects.

Genetics of the Framingham Heart Study Population

PubMed Central

Govindaraju, Diddahally R.; Cupples, L. Adrienne; Kannel, William B.; O’Donnell, Christopher J.; Atwood, Larry D.; D’Agostino, Ralph B.; Fox, Caroline S.; Larson, Marty; Levy, Daniel; Morabito, Joanne; Vasan, Ramachandran S.; Splansky, Greta Lee; Wolf, Philip A.; Benjamin, Emelia J.

2010-01-01

This article provides an introduction to the Framingham Heart Study (FHS) and the genetic research related to cardiovascular diseases conducted in this unique population1. It briefly describes the origins of the study, the risk factors that contribute to heart disease and the approaches taken to discover the genetic basis of some of these risk factors. The genetic architecture of several biological risk factors has been explained using family studies, segregation analysis, heritability, phenotypic and genetic correlations. Many quantitative trait loci underlying cardiovascular diseases have been discovered using different molecular markers. Additionally, results from genome-wide association studies using 100,000 markers, and the prospects of using 550,000 markers for association studies are presented. Finally, the use of this unique sample in genotype and environment interaction is described. PMID:19010253

Harnessing Connectivity in a Large-Scale Small-Molecule Sensitivity Dataset | Office of Cancer Genomics

Cancer.gov

Identifying genetic alterations that prime a cancer cell to respond to a particular therapeutic agent can facilitate the development of precision cancer medicines. Cancer cell-line (CCL) profiling of small-molecule sensitivity has emerged as an unbiased method to assess the relationships between genetic or cellular features of CCLs and small-molecule response. Here, we developed annotated cluster multidimensional enrichment analysis to explore the associations between groups of small molecules and groups of CCLs in a new, quantitative sensitivity dataset.

Development and in-house validation of the event-specific qualitative and quantitative PCR detection methods for genetically modified cotton MON15985.

PubMed

Jiang, Lingxi; Yang, Litao; Rao, Jun; Guo, Jinchao; Wang, Shu; Liu, Jia; Lee, Seonghun; Zhang, Dabing

2010-02-01

To implement genetically modified organism (GMO) labeling regulations, an event-specific analysis method based on the junction sequence between exogenous integration and host genomic DNA has become the preferential approach for GMO identification and quantification. In this study, specific primers and TaqMan probes based on the revealed 5'-end junction sequence of GM cotton MON15985 were designed, and qualitative and quantitative polymerase chain reaction (PCR) assays were established employing the designed primers and probes. In the qualitative PCR assay, the limit of detection (LOD) was 0.5 g kg(-1) in 100 ng total cotton genomic DNA, corresponding to about 17 copies of haploid cotton genomic DNA, and the LOD and limit of quantification (LOQ) for quantitative PCR assay were 10 and 17 copies of haploid cotton genomic DNA, respectively. Furthermore, the developed quantitative PCR assays were validated in-house by five different researchers. Also, five practical samples with known GM contents were quantified using the developed PCR assay in in-house validation, and the bias between the true and quantification values ranged from 2.06% to 12.59%. This study shows that the developed qualitative and quantitative PCR methods are applicable for the identification and quantification of GM cotton MON15985 and its derivates.

Proteomic analysis of hair shafts from monozygotic twins: Expression profiles and genetically variant peptides.

PubMed

Wu, Pei-Wen; Mason, Katelyn E; Durbin-Johnson, Blythe P; Salemi, Michelle; Phinney, Brett S; Rocke, David M; Parker, Glendon J; Rice, Robert H

2017-07-01

Forensic association of hair shaft evidence with individuals is currently assessed by comparing mitochondrial DNA haplotypes of reference and casework samples, primarily for exclusionary purposes. Present work tests and validates more recent proteomic approaches to extract quantitative transcriptional and genetic information from hair samples of monozygotic twin pairs, which would be predicted to partition away from unrelated individuals if the datasets contain identifying information. Protein expression profiles and polymorphic, genetically variant hair peptides were generated from ten pairs of monozygotic twins. Profiling using the protein tryptic digests revealed that samples from identical twins had typically an order of magnitude fewer protein expression differences than unrelated individuals. The data did not indicate that the degree of difference within twin pairs increased with age. In parallel, data from the digests were used to detect genetically variant peptides that result from common nonsynonymous single nucleotide polymorphisms in genes expressed in the hair follicle. Compilation of the variants permitted sorting of the samples by hierarchical clustering, permitting accurate matching of twin pairs. The results demonstrate that genetic differences are detectable by proteomic methods and provide a framework for developing quantitative statistical estimates of personal identification that increase the value of hair shaft evidence. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Maternal genetic effects on adaptive divergence between anadromous and resident brook charr during early life history.

PubMed

Perry, G M L; Audet, C; Bernatchez, L

2005-09-01

The importance of directional selection relative to neutral evolution may be determined by comparing quantitative genetic variation in phenotype (Q(ST)) to variation at neutral molecular markers (F(ST)). Quantitative divergence between salmonid life history types is often considerable, but ontogenetic changes in the significance of major sources of genetic variance during post-hatch development suggest that selective differentiation varies by developmental stage. In this study, we tested the hypothesis that maternal genetic differentiation between anadromous and resident brook charr (Salvelinus fontinalis Mitchill) populations for early quantitative traits (embryonic size/growth, survival, egg number and developmental time) would be greater than neutral genetic differentiation, but that the maternal genetic basis for differentiation would be higher for pre-resorption traits than post-resorption traits. Quantitative genetic divergence between anadromous (seawater migratory) and resident Laval River (Québec) brook charr based on maternal genetic variance was high (Q(ST) > 0.4) for embryonic length, yolk sac volume, embryonic growth rate and time to first response to feeding relative to neutral genetic differentiation [F(ST) = 0.153 (0.071-0.214)], with anadromous females having positive genetic coefficients for all of the above characters. However, Q(ST) was essentially zero for all traits post-resorption of the yolk sac. Our results indicate that the observed divergence between resident and anadromous brook charr has been driven by directional selection, and may therefore be adaptive. Moreover, they provide among the first evidence that the relative importance of selective differentiation may be highly context-specific, and varies by genetic contributions to phenotype by parental sex at specific points in offspring ontogeny. This in turn suggests that interpretations of Q(ST)-F(ST) comparisons may be improved by considering the structure of quantitative genetic architecture by age category and the sex of the parent used in estimation.

Are quantitative trait-dependent sampling designs cost-effective for analysis of rare and common variants?

PubMed

Yilmaz, Yildiz E; Bull, Shelley B

2011-11-29

Use of trait-dependent sampling designs in whole-genome association studies of sequence data can reduce total sequencing costs with modest losses of statistical efficiency. In a quantitative trait (QT) analysis of data from the Genetic Analysis Workshop 17 mini-exome for unrelated individuals in the Asian subpopulation, we investigate alternative designs that sequence only 50% of the entire cohort. In addition to a simple random sampling design, we consider extreme-phenotype designs that are of increasing interest in genetic association analysis of QTs, especially in studies concerned with the detection of rare genetic variants. We also evaluate a novel sampling design in which all individuals have a nonzero probability of being selected into the sample but in which individuals with extreme phenotypes have a proportionately larger probability. We take differential sampling of individuals with informative trait values into account by inverse probability weighting using standard survey methods which thus generalizes to the source population. In replicate 1 data, we applied the designs in association analysis of Q1 with both rare and common variants in the FLT1 gene, based on knowledge of the generating model. Using all 200 replicate data sets, we similarly analyzed Q1 and Q4 (which is known to be free of association with FLT1) to evaluate relative efficiency, type I error, and power. Simulation study results suggest that the QT-dependent selection designs generally yield greater than 50% relative efficiency compared to using the entire cohort, implying cost-effectiveness of 50% sample selection and worthwhile reduction of sequencing costs.

The SCHEIE Visual Field Grading System

PubMed Central

Sankar, Prithvi S.; O’Keefe, Laura; Choi, Daniel; Salowe, Rebecca; Miller-Ellis, Eydie; Lehman, Amanda; Addis, Victoria; Ramakrishnan, Meera; Natesh, Vikas; Whitehead, Gideon; Khachatryan, Naira; O’Brien, Joan

2017-01-01

Objective No method of grading visual field (VF) defects has been widely accepted throughout the glaucoma community. The SCHEIE (Systematic Classification of Humphrey visual fields-Easy Interpretation and Evaluation) grading system for glaucomatous visual fields was created to convey qualitative and quantitative information regarding visual field defects in an objective, reproducible, and easily applicable manner for research purposes. Methods The SCHEIE grading system is composed of a qualitative and quantitative score. The qualitative score consists of designation in one or more of the following categories: normal, central scotoma, paracentral scotoma, paracentral crescent, temporal quadrant, nasal quadrant, peripheral arcuate defect, expansive arcuate, or altitudinal defect. The quantitative component incorporates the Humphrey visual field index (VFI), location of visual defects for superior and inferior hemifields, and blind spot involvement. Accuracy and speed at grading using the qualitative and quantitative components was calculated for non-physician graders. Results Graders had a median accuracy of 96.67% for their qualitative scores and a median accuracy of 98.75% for their quantitative scores. Graders took a mean of 56 seconds per visual field to assign a qualitative score and 20 seconds per visual field to assign a quantitative score. Conclusion The SCHEIE grading system is a reproducible tool that combines qualitative and quantitative measurements to grade glaucomatous visual field defects. The system aims to standardize clinical staging and to make specific visual field defects more easily identifiable. Specific patterns of visual field loss may also be associated with genetic variants in future genetic analysis. PMID:28932621

Quantitative Genetic Modeling of the Parental Care Hypothesis for the Evolution of Endothermy

PubMed Central

Bacigalupe, Leonardo D.; Moore, Allen J.; Nespolo, Roberto F.; Rezende, Enrico L.; Bozinovic, Francisco

2017-01-01

There are two heuristic explanations proposed for the evolution of endothermy in vertebrates: a correlated response to selection for stable body temperatures, or as a correlated response to increased activity. Parental care has been suggested as a major driving force in this context given its impact on the parents' activity levels and energy budgets, and in the offspring's growth rates due to food provisioning and controlled incubation temperature. This results in a complex scenario involving multiple traits and transgenerational fitness benefits that can be hard to disentangle, quantify and ultimately test. Here we demonstrate how standard quantitative genetic models of maternal effects can be applied to study the evolution of endothermy, focusing on the interplay between daily energy expenditure (DEE) of the mother and growth rates of the offspring. Our model shows that maternal effects can dramatically exacerbate evolutionary responses to selection in comparison to regular univariate models (breeder's equation). This effect would emerge from indirect selection mediated by maternal effects concomitantly with a positive genetic covariance between DEE and growth rates. The multivariate nature of selection, which could favor a higher DEE, higher growth rates or both, might partly explain how high turnover rates were continuously favored in a self-reinforcing process. Overall, our quantitative genetic analysis provides support for the parental care hypothesis for the evolution of endothermy. We contend that much has to be gained from quantifying maternal and developmental effects on metabolic and thermoregulatory variation during adulthood. PMID:29311952

Study books on ADHD genetics: balanced or biased?

PubMed

Te Meerman, Sanne; Batstra, Laura; Hoekstra, Rink; Grietens, Hans

2017-06-01

Academic study books are essential assets for disseminating knowledge about ADHD to future healthcare professionals. This study examined if they are balanced with regard to genetics. We selected and analyzed study books (N=43) used in (pre) master's programmes at 10 universities in the Netherlands. Because the mere behaviourally informed quantitative genetics give a much higher effect size of the genetic involvement in ADHD, it is important that study books contrast these findings with molecular genetics' outcomes. The latter studies use real genetic data, and their low effect sizes expose the potential weaknesses of quantitative genetics, like underestimating the involvement of the environment. Only a quarter of books mention both effect sizes and contrast these findings, while another quarter does not discuss any effect size. Most importantly, however, roughly half of the books in our sample mention only the effect sizes from quantitative genetic studies without addressing the low explained variance of molecular genetic studies. This may confuse readers by suggesting that the weakly associated genes support the quite spectacular, but potentially flawed estimates of twin, family and adoption studies, while they actually contradict them.

Quantitative trait loci and metabolic pathways

PubMed Central

McMullen, M. D.; Byrne, P. F.; Snook, M. E.; Wiseman, B. R.; Lee, E. A.; Widstrom, N. W.; Coe, E. H.

1998-01-01

The interpretation of quantitative trait locus (QTL) studies is limited by the lack of information on metabolic pathways leading to most economic traits. Inferences about the roles of the underlying genes with a pathway or the nature of their interaction with other loci are generally not possible. An exception is resistance to the corn earworm Helicoverpa zea (Boddie) in maize (Zea mays L.) because of maysin, a C-glycosyl flavone synthesized in silks via a branch of the well characterized flavonoid pathway. Our results using flavone synthesis as a model QTL system indicate: (i) the importance of regulatory loci as QTLs, (ii) the importance of interconnecting biochemical pathways on product levels, (iii) evidence for “channeling” of intermediates, allowing independent synthesis of related compounds, (iv) the utility of QTL analysis in clarifying the role of specific genes in a biochemical pathway, and (v) identification of a previously unknown locus on chromosome 9S affecting flavone level. A greater understanding of the genetic basis of maysin synthesis and associated corn earworm resistance should lead to improved breeding strategies. More broadly, the insights gained in relating a defined genetic and biochemical pathway affecting a quantitative trait should enhance interpretation of the biological basis of variation for other quantitative traits. PMID:9482823

Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas-fir

Treesearch

Nicholas C. Wheeler; Kathleen D. Jermstad; Konstantin V. Krutovsky; Sally N. Aitken; Glenn T. Howe; Jodie Krakowski; David B. Neale

2005-01-01

Quantitative trait locus (QTL) analyses are used by geneticists to characterize the genetic architecture of quantitative traits, provide a foundation for marker-aided-selection (MAS), and provide a framework for positional selection of candidate genes. The most useful QTL for breeding applications are those that have been verified in time, space, and/or genetic...

Dominant Epistasis Between Two Quantitative Trait Loci Governing Sporulation Efficiency in Yeast Saccharomyces cerevisiae

PubMed Central

Bergman, Juraj; Mitrikeski, Petar T.

2015-01-01

Summary Sporulation efficiency in the yeast Saccharomyces cerevisiae is a well-established model for studying quantitative traits. A variety of genes and nucleotides causing different sporulation efficiencies in laboratory, as well as in wild strains, has already been extensively characterised (mainly by reciprocal hemizygosity analysis and nucleotide exchange methods). We applied a different strategy in order to analyze the variation in sporulation efficiency of laboratory yeast strains. Coupling classical quantitative genetic analysis with simulations of phenotypic distributions (a method we call phenotype modelling) enabled us to obtain a detailed picture of the quantitative trait loci (QTLs) relationships underlying the phenotypic variation of this trait. Using this approach, we were able to uncover a dominant epistatic inheritance of loci governing the phenotype. Moreover, a molecular analysis of known causative quantitative trait genes and nucleotides allowed for the detection of novel alleles, potentially responsible for the observed phenotypic variation. Based on the molecular data, we hypothesise that the observed dominant epistatic relationship could be caused by the interaction of multiple quantitative trait nucleotides distributed across a 60--kb QTL region located on chromosome XIV and the RME1 locus on chromosome VII. Furthermore, we propose a model of molecular pathways which possibly underlie the phenotypic variation of this trait. PMID:27904371

Garlic (Allium sativum L.) fertility: transcriptome and proteome analyses provide insight into flower and pollen development

PubMed Central

Shemesh-Mayer, Einat; Ben-Michael, Tomer; Rotem, Neta; Rabinowitch, Haim D.; Doron-Faigenboim, Adi; Kosmala, Arkadiusz; Perlikowski, Dawid; Sherman, Amir; Kamenetsky, Rina

2015-01-01

Commercial cultivars of garlic, a popular condiment, are sterile, making genetic studies and breeding of this plant challenging. However, recent fertility restoration has enabled advanced physiological and genetic research and hybridization in this important crop. Morphophysiological studies, combined with transcriptome and proteome analyses and quantitative PCR validation, enabled the identification of genes and specific processes involved in gametogenesis in fertile and male-sterile garlic genotypes. Both genotypes exhibit normal meiosis at early stages of anther development, but in the male-sterile plants, tapetal hypertrophy after microspore release leads to pollen degeneration. Transcriptome analysis and global gene-expression profiling showed that >16,000 genes are differentially expressed in the fertile vs. male-sterile developing flowers. Proteome analysis and quantitative comparison of 2D-gel protein maps revealed 36 significantly different protein spots, 9 of which were present only in the male-sterile genotype. Bioinformatic and quantitative PCR validation of 10 candidate genes exhibited significant expression differences between male-sterile and fertile flowers. A comparison of morphophysiological and molecular traits of fertile and male-sterile garlic flowers suggests that respiratory restrictions and/or non-regulated programmed cell death of the tapetum can lead to energy deficiency and consequent pollen abortion. Potential molecular markers for male fertility and sterility in garlic are proposed. PMID:25972879

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.

Validation of PCR methods for quantitation of genetically modified plants in food.

PubMed

Hübner, P; Waiblinger, H U; Pietsch, K; Brodmann, P

2001-01-01

For enforcement of the recently introduced labeling threshold for genetically modified organisms (GMOs) in food ingredients, quantitative detection methods such as quantitative competitive (QC-PCR) and real-time PCR are applied by official food control laboratories. The experiences of 3 European food control laboratories in validating such methods were compared to describe realistic performance characteristics of quantitative PCR detection methods. The limit of quantitation (LOQ) of GMO-specific, real-time PCR was experimentally determined to reach 30-50 target molecules, which is close to theoretical prediction. Starting PCR with 200 ng genomic plant DNA, the LOQ depends primarily on the genome size of the target plant and ranges from 0.02% for rice to 0.7% for wheat. The precision of quantitative PCR detection methods, expressed as relative standard deviation (RSD), varied from 10 to 30%. Using Bt176 corn containing test samples and applying Bt176 specific QC-PCR, mean values deviated from true values by -7to 18%, with an average of 2+/-10%. Ruggedness of real-time PCR detection methods was assessed in an interlaboratory study analyzing commercial, homogeneous food samples. Roundup Ready soybean DNA contents were determined in the range of 0.3 to 36%, relative to soybean DNA, with RSDs of about 25%. Taking the precision of quantitative PCR detection methods into account, suitable sample plans and sample sizes for GMO analysis are suggested. Because quantitative GMO detection methods measure GMO contents of samples in relation to reference material (calibrants), high priority must be given to international agreements and standardization on certified reference materials.

Quantitative second-harmonic generation imaging to detect osteogenesis imperfecta in human skin samples

NASA Astrophysics Data System (ADS)

Adur, J.; Ferreira, A. E.; D'Souza-Li, L.; Pelegati, V. B.; de Thomaz, A. A.; Almeida, D. B.; Baratti, M. O.; Carvalho, H. F.; Cesar, C. L.

2012-03-01

Osteogenesis Imperfecta (OI) is a genetic disorder that leads to bone fractures due to mutations in the Col1A1 or Col1A2 genes that affect the primary structure of the collagen I chain with the ultimate outcome in collagen I fibrils that are either reduced in quantity or abnormally organized in the whole body. A quick test screening of the patients would largely reduce the sample number to be studied by the time consuming molecular genetics techniques. For this reason an assessment of the human skin collagen structure by Second Harmonic Generation (SHG) can be used as a screening technique to speed up the correlation of genetics/phenotype/OI types understanding. In the present work we have used quantitative second harmonic generation (SHG) imaging microscopy to investigate the collagen matrix organization of the OI human skin samples comparing with normal control patients. By comparing fibril collagen distribution and spatial organization, we calculated the anisotropy and texture patterns of this structural protein. The analysis of the anisotropy was performed by means of the two-dimensional Discrete Fourier Transform and image pattern analysis with Gray-Level Co-occurrence Matrix (GLCM). From these results, we show that statistically different results are obtained for the normal and disease states of OI.

Assessing the cost of implementing the 2011 Society of Obstetricians and Gynecologists of Canada and Canadian College of Medical Genetics practice guidelines on the detection of fetal aneuploidies.

PubMed

Lilley, Margaret; Hume, Stacey; Karpoff, Nina; Maire, Georges; Taylor, Sherry; Tomaszewski, Robert; Yoshimoto, Maisa; Christian, Susan

2017-09-01

The Society of Obstetricians and Gynecologists of Canada and the Canadian College of Medical Genetics published guidelines, in 2011, recommending replacement of karyotype with quantitative fluorescent polymerase chain reaction when prenatal testing is performed because of an increased risk of a common aneuploidy. This study's objective is to perform a cost analysis following the implementation of quantitative fluorescent polymerase chain reaction as a stand-alone test. A total of 658 samples were received between 1 April 2014 and 31 August 2015: 576 amniocentesis samples and 82 chorionic villi sampling. A chromosome abnormality was identified in 14% (93/658) of the prenatal samples tested. The implementation of the 2011 Society of Obstetricians and Gynecologists of Canada and the Canadian College of Medical Genetics guidelines in Edmonton and Northern Alberta resulted in a cost savings of $46 295.80. The replacement of karyotype with chromosomal microarray for some indications would be associated with additional costs. The implementation of new test methods may provide cost savings or added costs. Cost analysis is important to consider during the implementation of new guidelines or technologies. © 2017 John Wiley & Sons, Ltd. © 2017 John Wiley & Sons, Ltd.

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

RFLP Analysis and Allelic Discrimination with Real-Time PCR Using the Human Lactase Persistence Trait: A Pair of Molecular Genetic Investigations

ERIC Educational Resources Information Center

Weinlander, Kenneth M.; Hall, David J.; De Stasio, Elizabeth A.

2010-01-01

We describe here two open-ended laboratory investigations for an undergraduate laboratory course that uses students' DNA as templates for quantitative real-time PCR and for traditional PCR followed by RFLP analysis. Students are captivated by the immediacy of the application and the relevance of the genotypes and traits, lactase persistence or…

Genetic basis for evolved tolerance to dioxin-like pollutants in wild Atlantic killifish: more than the aryl hydrocarbon receptor

USDA-ARS?s Scientific Manuscript database

Atlantic killifish (Fundulus heteroclitus) resident to some US urban and industrialized estuaries demonstrate recently evolved and extreme tolerance to toxic dioxin-like compounds (DLCs). Here we provide an unusually comprehensive accounting (69%) through Quantitative Trait Locus (QTL) analysis of ...

Genetic basis for evolved tolerance to dioxin-like pollutants in wild atlantic killifish: more than the aryl hydrocarbon receptor

USDA-ARS?s Scientific Manuscript database

Atlantic killifish (Fundulus heteroclitus) resident to some US urban and industrialized estuaries demonstrate recently evolved and extreme tolerance to toxic dioxin-like compounds (DLCs). Here we provide an unusually comprehensive accounting (69%) through Quantitative Trait Locus (QTL) analysis of ...

Additive genetic variation in the craniofacial skeleton of baboons (genus Papio) and its relationship to body and cranial size.

PubMed

Joganic, Jessica L; Willmore, Katherine E; Richtsmeier, Joan T; Weiss, Kenneth M; Mahaney, Michael C; Rogers, Jeffrey; Cheverud, James M

2018-02-01

Determining the genetic architecture of quantitative traits and genetic correlations among them is important for understanding morphological evolution patterns. We address two questions regarding papionin evolution: (1) what effect do body and cranial size, age, and sex have on phenotypic (V P ) and additive genetic (V A ) variation in baboon crania, and (2) how might additive genetic correlations between craniofacial traits and body mass affect morphological evolution? We use a large captive pedigreed baboon sample to estimate quantitative genetic parameters for craniofacial dimensions (EIDs). Our models include nested combinations of the covariates listed above. We also simulate the correlated response of a given EID due to selection on body mass alone. Covariates account for 1.2-91% of craniofacial V P . EID V A decreases across models as more covariates are included. The median genetic correlation estimate between each EID and body mass is 0.33. Analysis of the multivariate response to selection reveals that observed patterns of craniofacial variation in extant baboons cannot be attributed solely to correlated response to selection on body mass, particularly in males. Because a relatively large proportion of EID V A is shared with body mass variation, different methods of correcting for allometry by statistically controlling for size can alter residual V P patterns. This may conflate direct selection effects on craniofacial variation with those resulting from a correlated response to body mass selection. This shared genetic variation may partially explain how selection for increased body mass in two different papionin lineages produced remarkably similar craniofacial phenotypes. © 2017 Wiley Periodicals, Inc.

The influence of genetic drift and selection on quantitative traits in a plant pathogenic fungus.

PubMed

Stefansson, Tryggvi S; McDonald, Bruce A; Willi, Yvonne

2014-01-01

Genetic drift and selection are ubiquitous evolutionary forces acting to shape genetic variation in populations. While their relative importance has been well studied in plants and animals, less is known about their relative importance in fungal pathogens. Because agro-ecosystems are more homogeneous environments than natural ecosystems, stabilizing selection may play a stronger role than genetic drift or diversifying selection in shaping genetic variation among populations of fungal pathogens in agro-ecosystems. We tested this hypothesis by conducting a QST/FST analysis using agricultural populations of the barley pathogen Rhynchosporium commune. Population divergence for eight quantitative traits (QST) was compared with divergence at eight neutral microsatellite loci (FST) for 126 pathogen strains originating from nine globally distributed field populations to infer the effects of genetic drift and types of selection acting on each trait. Our analyses indicated that five of the eight traits had QST values significantly lower than FST, consistent with stabilizing selection, whereas one trait, growth under heat stress (22°C), showed evidence of diversifying selection and local adaptation (QST>FST). Estimates of heritability were high for all traits (means ranging between 0.55-0.84), and average heritability across traits was negatively correlated with microsatellite gene diversity. Some trait pairs were genetically correlated and there was significant evidence for a trade-off between spore size and spore number, and between melanization and growth under benign temperature. Our findings indicate that many ecologically and agriculturally important traits are under stabilizing selection in R. commune and that high within-population genetic variation is maintained for these traits.

QTL mapping for sexually dimorphic fitness-related traits in wild bighorn sheep

PubMed Central

Poissant, J; Davis, C S; Malenfant, R M; Hogg, J T; Coltman, D W

2012-01-01

Dissecting the genetic architecture of fitness-related traits in wild populations is key to understanding evolution and the mechanisms maintaining adaptive genetic variation. We took advantage of a recently developed genetic linkage map and phenotypic information from wild pedigreed individuals from Ram Mountain, Alberta, Canada, to study the genetic architecture of ecologically important traits (horn volume, length, base circumference and body mass) in bighorn sheep. In addition to estimating sex-specific and cross-sex quantitative genetic parameters, we tested for the presence of quantitative trait loci (QTLs), colocalization of QTLs between bighorn sheep and domestic sheep, and sex × QTL interactions. All traits showed significant additive genetic variance and genetic correlations tended to be positive. Linkage analysis based on 241 microsatellite loci typed in 310 pedigreed animals resulted in no significant and five suggestive QTLs (four for horn dimension on chromosomes 1, 18 and 23, and one for body mass on chromosome 26) using genome-wide significance thresholds (Logarithm of odds (LOD) >3.31 and >1.88, respectively). We also confirmed the presence of a horn dimension QTL in bighorn sheep at the only position known to contain a similar QTL in domestic sheep (on chromosome 10 near the horns locus; nominal P<0.01) and highlighted a number of regions potentially containing weight-related QTLs in both species. As expected for sexually dimorphic traits involved in male–male combat, loci with sex-specific effects were detected. This study lays the foundation for future work on adaptive genetic variation and the evolutionary dynamics of sexually dimorphic traits in bighorn sheep. PMID:21847139

Quantitative detection method for Roundup Ready soybean in food using duplex real-time PCR MGB chemistry.

PubMed

Samson, Maria Cristina; Gullì, Mariolina; Marmiroli, Nelson

2010-07-01

Methodologies that enable the detection of genetically modified organisms (GMOs) (authorized and non-authorized) in food and feed strongly influence the potential for adequate updating and implementation of legislation together with labeling requirements. Quantitative polymerase chain reaction (qPCR) systems were designed to boost the sensitivity and specificity on the identification of GMOs in highly degraded DNA samples; however, such testing will become economically difficult to cope with due to increasing numbers of approved genetically modified (GM) lines. Multiplexing approaches are therefore in development to provide cost-efficient solution. Construct-specific primers and probe were developed for quantitative analysis of Roundup Ready soybean (RRS) event glyphosate-tolerant soybean (GTS) 40-3-2. The lectin gene (Le1) was used as a reference gene, and its specificity was verified. RRS- and Le1-specific quantitative real-time PCR (qRTPCR) were optimized in a duplex platform that has been validated with respect to limit of detection (LOD) and limit of quantification (LOQ), as well as accuracy. The analysis of model processed food samples showed that the degradation of DNA has no adverse or little effects on the performance of quantification assay. In this study, a duplex qRTPCR using TaqMan minor groove binder-non-fluorescent quencher (MGB-NFQ) chemistry was developed for specific detection and quantification of RRS event GTS 40-3-2 that can be used for practical monitoring in processed food products.

Quantitative analysis of microtubule orientation in interdigitated leaf pavement cells.

PubMed

Akita, Kae; Higaki, Takumi; Kutsuna, Natsumaro; Hasezawa, Seiichiro

2015-01-01

Leaf pavement cells are shaped like a jigsaw puzzle in most dicotyledon species. Molecular genetic studies have identified several genes required for pavement cells morphogenesis and proposed that microtubules play crucial roles in the interdigitation of pavement cells. In this study, we performed quantitative analysis of cortical microtubule orientation in leaf pavement cells in Arabidopsis thaliana. We captured confocal images of cortical microtubules in cotyledon leaf epidermis expressing GFP-tubulinβ and quantitatively evaluated the microtubule orientations relative to the pavement cell growth axis using original image processing techniques. Our results showed that microtubules kept parallel orientations to the growth axis during pavement cell growth. In addition, we showed that immersion treatment of seed cotyledons in solutions containing tubulin polymerization and depolymerization inhibitors decreased pavement cell complexity. Treatment with oryzalin and colchicine inhibited the symmetric division of guard mother cells.

GACD: Integrated Software for Genetic Analysis in Clonal F1 and Double Cross Populations.

PubMed

Zhang, Luyan; Meng, Lei; Wu, Wencheng; Wang, Jiankang

2015-01-01

Clonal species are common among plants. Clonal F1 progenies are derived from the hybridization between 2 heterozygous clones. In self- and cross-pollinated species, double crosses can be made from 4 inbred lines. A clonal F1 population can be viewed as a double cross population when the linkage phase is determined. The software package GACD (Genetic Analysis of Clonal F1 and Double cross) is freely available public software, capable of building high-density linkage maps and mapping quantitative trait loci (QTL) in clonal F1 and double cross populations. Three functionalities are integrated in GACD version 1.0: binning of redundant markers (BIN); linkage map construction (CDM); and QTL mapping (CDQ). Output of BIN can be directly used as input of CDM. After adding the phenotypic data, the output of CDM can be used as input of CDQ. Thus, GACD acts as a pipeline for genetic analysis. GACD and example datasets are freely available from www.isbreeding.net. © The American Genetic Association. 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Modelling the co-evolution of indirect genetic effects and inherited variability.

PubMed

Marjanovic, Jovana; Mulder, Han A; Rönnegård, Lars; Bijma, Piter

2018-03-28

When individuals interact, their phenotypes may be affected not only by their own genes but also by genes in their social partners. This phenomenon is known as Indirect Genetic Effects (IGEs). In aquaculture species and some plants, however, competition not only affects trait levels of individuals, but also inflates variability of trait values among individuals. In the field of quantitative genetics, the variability of trait values has been studied as a quantitative trait in itself, and is often referred to as inherited variability. Such studies, however, consider only the genetic effect of the focal individual on trait variability and do not make a connection to competition. Although the observed phenotypic relationship between competition and variability suggests an underlying genetic relationship, the current quantitative genetic models of IGE and inherited variability do not allow for such a relationship. The lack of quantitative genetic models that connect IGEs to inherited variability limits our understanding of the potential of variability to respond to selection, both in nature and agriculture. Models of trait levels, for example, show that IGEs may considerably change heritable variation in trait values. Currently, we lack the tools to investigate whether this result extends to variability of trait values. Here we present a model that integrates IGEs and inherited variability. In this model, the target phenotype, say growth rate, is a function of the genetic and environmental effects of the focal individual and of the difference in trait value between the social partner and the focal individual, multiplied by a regression coefficient. The regression coefficient is a genetic trait, which is a measure of cooperation; a negative value indicates competition, a positive value cooperation, and an increasing value due to selection indicates the evolution of cooperation. In contrast to the existing quantitative genetic models, our model allows for co-evolution of IGEs and variability, as the regression coefficient can respond to selection. Our simulations show that the model results in increased variability of body weight with increasing competition. When competition decreases, i.e., cooperation evolves, variability becomes significantly smaller. Hence, our model facilitates quantitative genetic studies on the relationship between IGEs and inherited variability. Moreover, our findings suggest that we may have been overlooking an entire level of genetic variation in variability, the one due to IGEs.

Assessment on induced genetic variability and divergence in the mutagenized lentil populations of microsperma and macrosperma cultivars developed using physical and chemical mutagenesis

PubMed Central

2017-01-01

Induced mutagenesis was employed to create genetic variation in the lentil cultivars for yield improvement. The assessments were made on genetic variability, character association, and genetic divergence among the twelve mutagenized populations and one parent population of each of the two lentil cultivars, developed by single and combination treatments with gamma rays and hydrazine hydrates. Analysis of variance revealed significant inter-population differences for the observed quantitative phenotypic traits. The sample mean of six treatment populations in each of the cultivar exhibited highly superior quantitative phenotypic traits compared to their parent cultivars. The higher values of heritability and genetic advance with a high genotypic coefficient of variation for most of the yield attributing traits confirmed the possibilities of lentil yield improvement through phenotypic selection. The number of pods and seeds per plant appeared to be priority traits in selection for higher yield due to their strong direct association with yield. The cluster analysis divided the total populations into three divergent groups in each lentil cultivar with parent genotypes in an independent group showing the high efficacy of the mutagens. Considering the highest contribution of yield trait to the genetic divergence among the clustered population, it was confirmed that the mutagenic treatments created a wide heritable variation for the trait in the mutant populations. The selection of high yielding mutants from the mutant populations of DPL 62 (100 Gy) and Pant L 406 (100Gy + 0.1% HZ) in the subsequent generation is expected to give elite lentil cultivars. Also, hybridization between members of the divergent group would produce diverse segregants for crop improvement. Apart from this, the induced mutations at loci controlling economically important traits in the selected high yielding mutants have successfully contributed in diversifying the accessible lentil genetic base and will definitely be of immense value to the future lentil breeding programmes in India. PMID:28922405

Small- and Large-Effect Quantitative Trait Locus Interactions Underlie Variation in Yeast Sporulation Efficiency

PubMed Central

Lorenz, Kim; Cohen, Barak A.

2012-01-01

Quantitative trait loci (QTL) with small effects on phenotypic variation can be difficult to detect and analyze. Because of this a large fraction of the genetic architecture of many complex traits is not well understood. Here we use sporulation efficiency in Saccharomyces cerevisiae as a model complex trait to identify and study small-effect QTL. In crosses where the large-effect quantitative trait nucleotides (QTN) have been genetically fixed we identify small-effect QTL that explain approximately half of the remaining variation not explained by the major effects. We find that small-effect QTL are often physically linked to large-effect QTL and that there are extensive genetic interactions between small- and large-effect QTL. A more complete understanding of quantitative traits will require a better understanding of the numbers, effect sizes, and genetic interactions of small-effect QTL. PMID:22942125

Genetic interactions contribute less than additive effects to quantitative trait variation in yeast

PubMed Central

Bloom, Joshua S.; Kotenko, Iulia; Sadhu, Meru J.; Treusch, Sebastian; Albert, Frank W.; Kruglyak, Leonid

2015-01-01

Genetic mapping studies of quantitative traits typically focus on detecting loci that contribute additively to trait variation. Genetic interactions are often proposed as a contributing factor to trait variation, but the relative contribution of interactions to trait variation is a subject of debate. Here we use a very large cross between two yeast strains to accurately estimate the fraction of phenotypic variance due to pairwise QTL–QTL interactions for 20 quantitative traits. We find that this fraction is 9% on average, substantially less than the contribution of additive QTL (43%). Statistically significant QTL–QTL pairs typically have small individual effect sizes, but collectively explain 40% of the pairwise interaction variance. We show that pairwise interaction variance is largely explained by pairs of loci at least one of which has a significant additive effect. These results refine our understanding of the genetic architecture of quantitative traits and help guide future mapping studies. PMID:26537231

Partial least squares correspondence analysis: A framework to simultaneously analyze behavioral and genetic data.

PubMed

Beaton, Derek; Dunlop, Joseph; Abdi, Hervé

2016-12-01

For nearly a century, detecting the genetic contributions to cognitive and behavioral phenomena has been a core interest for psychological research. Recently, this interest has been reinvigorated by the availability of genotyping technologies (e.g., microarrays) that provide new genetic data, such as single nucleotide polymorphisms (SNPs). These SNPs-which represent pairs of nucleotide letters (e.g., AA, AG, or GG) found at specific positions on human chromosomes-are best considered as categorical variables, but this coding scheme can make difficult the multivariate analysis of their relationships with behavioral measurements, because most multivariate techniques developed for the analysis between sets of variables are designed for quantitative variables. To palliate this problem, we present a generalization of partial least squares-a technique used to extract the information common to 2 different data tables measured on the same observations-called partial least squares correspondence analysis-that is specifically tailored for the analysis of categorical and mixed ("heterogeneous") data types. Here, we formally define and illustrate-in a tutorial format-how partial least squares correspondence analysis extends to various types of data and design problems that are particularly relevant for psychological research that include genetic data. We illustrate partial least squares correspondence analysis with genetic, behavioral, and neuroimaging data from the Alzheimer's Disease Neuroimaging Initiative. R code is available on the Comprehensive R Archive Network and via the authors' websites. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Study books on ADHD genetics: balanced or biased?

PubMed Central

te Meerman, Sanne; Batstra, Laura; Hoekstra, Rink; Grietens, Hans

2017-01-01

ABSTRACT Academic study books are essential assets for disseminating knowledge about ADHD to future healthcare professionals. This study examined if they are balanced with regard to genetics. We selected and analyzed study books (N=43) used in (pre) master’s programmes at 10 universities in the Netherlands. Because the mere behaviourally informed quantitative genetics give a much higher effect size of the genetic involvement in ADHD, it is important that study books contrast these findings with molecular genetics’ outcomes. The latter studies use real genetic data, and their low effect sizes expose the potential weaknesses of quantitative genetics, like underestimating the involvement of the environment. Only a quarter of books mention both effect sizes and contrast these findings, while another quarter does not discuss any effect size. Most importantly, however, roughly half of the books in our sample mention only the effect sizes from quantitative genetic studies without addressing the low explained variance of molecular genetic studies. This may confuse readers by suggesting that the weakly associated genes support the quite spectacular, but potentially flawed estimates of twin, family and adoption studies, while they actually contradict them. PMID:28532325

Rapid changes in genetic architecture of behavioural syndromes following colonization of a novel environment.

PubMed

Karlsson Green, K; Eroukhmanoff, F; Harris, S; Pettersson, L B; Svensson, E I

2016-01-01

Behavioural syndromes, that is correlated behaviours, may be a result from adaptive correlational selection, but in a new environmental setting, the trait correlation might act as an evolutionary constraint. However, knowledge about the quantitative genetic basis of behavioural syndromes, and the stability and evolvability of genetic correlations under different ecological conditions, is limited. We investigated the quantitative genetic basis of correlated behaviours in the freshwater isopod Asellus aquaticus. In some Swedish lakes, A. aquaticus has recently colonized a novel habitat and diverged into two ecotypes, presumably due to habitat-specific selection from predation. Using a common garden approach and animal model analyses, we estimated quantitative genetic parameters for behavioural traits and compared the genetic architecture between the ecotypes. We report that the genetic covariance structure of the behavioural traits has been altered in the novel ecotype, demonstrating divergence in behavioural correlations. Thus, our study confirms that genetic correlations behind behaviours can change rapidly in response to novel selective environments. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

The long-term evolution of multilocus traits under frequency-dependent disruptive selection.

PubMed

van Doorn, G Sander; Dieckmann, Ulf

2006-11-01

Frequency-dependent disruptive selection is widely recognized as an important source of genetic variation. Its evolutionary consequences have been extensively studied using phenotypic evolutionary models, based on quantitative genetics, game theory, or adaptive dynamics. However, the genetic assumptions underlying these approaches are highly idealized and, even worse, predict different consequences of frequency-dependent disruptive selection. Population genetic models, by contrast, enable genotypic evolutionary models, but traditionally assume constant fitness values. Only a minority of these models thus addresses frequency-dependent selection, and only a few of these do so in a multilocus context. An inherent limitation of these remaining studies is that they only investigate the short-term maintenance of genetic variation. Consequently, the long-term evolution of multilocus characters under frequency-dependent disruptive selection remains poorly understood. We aim to bridge this gap between phenotypic and genotypic models by studying a multilocus version of Levene's soft-selection model. Individual-based simulations and deterministic approximations based on adaptive dynamics theory provide insights into the underlying evolutionary dynamics. Our analysis uncovers a general pattern of polymorphism formation and collapse, likely to apply to a wide variety of genetic systems: after convergence to a fitness minimum and the subsequent establishment of genetic polymorphism at multiple loci, genetic variation becomes increasingly concentrated on a few loci, until eventually only a single polymorphic locus remains. This evolutionary process combines features observed in quantitative genetics and adaptive dynamics models, and it can be explained as a consequence of changes in the selection regime that are inherent to frequency-dependent disruptive selection. Our findings demonstrate that the potential of frequency-dependent disruptive selection to maintain polygenic variation is considerably smaller than previously expected.

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.

A modifier of Huntington's disease onset at the MLH1 locus.

PubMed

Lee, Jong-Min; Chao, Michael J; Harold, Denise; Abu Elneel, Kawther; Gillis, Tammy; Holmans, Peter; Jones, Lesley; Orth, Michael; Myers, Richard H; Kwak, Seung; Wheeler, Vanessa C; MacDonald, Marcy E; Gusella, James F

2017-10-01

Huntington's disease (HD) is a dominantly inherited neurodegenerative disease caused by an expanded CAG repeat in HTT. Many clinical characteristics of HD such as age at motor onset are determined largely by the size of HTT CAG repeat. However, emerging evidence strongly supports a role for other genetic factors in modifying the disease pathogenesis driven by mutant huntingtin. A recent genome-wide association analysis to discover genetic modifiers of HD onset age provided initial evidence for modifier loci on chromosomes 8 and 15 and suggestive evidence for a locus on chromosome 3. Here, genotyping of candidate single nucleotide polymorphisms in a cohort of 3,314 additional HD subjects yields independent confirmation of the former two loci and moves the third to genome-wide significance at MLH1, a locus whose mouse orthologue modifies CAG length-dependent phenotypes in a Htt-knock-in mouse model of HD. Both quantitative and dichotomous association analyses implicate a functional variant on ∼32% of chromosomes with the beneficial modifier effect that delays HD motor onset by 0.7 years/allele. Genomic DNA capture and sequencing of a modifier haplotype localize the functional variation to a 78 kb region spanning the 3'end of MLH1 and the 5'end of the neighboring LRRFIP2, and marked by an isoleucine-valine missense variant in MLH1. Analysis of expression Quantitative Trait Loci (eQTLs) provides modest support for altered regulation of MLH1 and LRRFIP2, raising the possibility that the modifier affects regulation of both genes. Finally, polygenic modification score and heritability analyses suggest the existence of additional genetic modifiers, supporting expanded, comprehensive genetic analysis of larger HD datasets. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Quantitative Imaging in Cancer Evolution and Ecology

PubMed Central

Grove, Olya; Gillies, Robert J.

2013-01-01

Cancer therapy, even when highly targeted, typically fails because of the remarkable capacity of malignant cells to evolve effective adaptations. These evolutionary dynamics are both a cause and a consequence of cancer system heterogeneity at many scales, ranging from genetic properties of individual cells to large-scale imaging features. Tumors of the same organ and cell type can have remarkably diverse appearances in different patients. Furthermore, even within a single tumor, marked variations in imaging features, such as necrosis or contrast enhancement, are common. Similar spatial variations recently have been reported in genetic profiles. Radiologic heterogeneity within tumors is usually governed by variations in blood flow, whereas genetic heterogeneity is typically ascribed to random mutations. However, evolution within tumors, as in all living systems, is subject to Darwinian principles; thus, it is governed by predictable and reproducible interactions between environmental selection forces and cell phenotype (not genotype). This link between regional variations in environmental properties and cellular adaptive strategies may permit clinical imaging to be used to assess and monitor intratumoral evolution in individual patients. This approach is enabled by new methods that extract, report, and analyze quantitative, reproducible, and mineable clinical imaging data. However, most current quantitative metrics lack spatialness, expressing quantitative radiologic features as a single value for a region of interest encompassing the whole tumor. In contrast, spatially explicit image analysis recognizes that tumors are heterogeneous but not well mixed and defines regionally distinct habitats, some of which appear to harbor tumor populations that are more aggressive and less treatable than others. By identifying regional variations in key environmental selection forces and evidence of cellular adaptation, clinical imaging can enable us to define intratumoral Darwinian dynamics before and during therapy. Advances in image analysis will place clinical imaging in an increasingly central role in the development of evolution-based patient-specific cancer therapy. © RSNA, 2013 PMID:24062559

Bridging the gap between genome analysis and precision breeding in potato.

PubMed

Gebhardt, Christiane

2013-04-01

Efficiency and precision in plant breeding can be enhanced by using diagnostic DNA-based markers for the selection of superior cultivars. This technique has been applied to many crops, including potatoes. The first generation of diagnostic DNA-based markers useful in potato breeding were enabled by several developments: genetic linkage maps based on DNA polymorphisms, linkage mapping of qualitative and quantitative agronomic traits, cloning and functional analysis of genes for pathogen resistance and genes controlling plant metabolism, and association genetics in collections of tetraploid varieties and advanced breeding clones. Although these have led to significant improvements in potato genetics, the prediction of most, if not all, natural variation in agronomic traits by diagnostic markers ultimately requires the identification of the causal genes and their allelic variants. This objective will be facilitated by new genomic tools, such as genomic resequencing and comparative profiling of the proteome, transcriptome, and metabolome in combination with phenotyping genetic materials relevant for variety development. Copyright © 2012 Elsevier Ltd. All rights reserved.

QuASAR: quantitative allele-specific analysis of reads

PubMed Central

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

2015-01-01

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

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis.

PubMed

Sakhanenko, Nikita A; Kunert-Graf, James; Galas, David J

2017-12-01

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. We present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discrete variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis-that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. We illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.

PEPIS: A Pipeline for Estimating Epistatic Effects in Quantitative Trait Locus Mapping and Genome-Wide Association Studies.

PubMed

Zhang, Wenchao; Dai, Xinbin; Wang, Qishan; Xu, Shizhong; Zhao, Patrick X

2016-05-01

The term epistasis refers to interactions between multiple genetic loci. Genetic epistasis is important in regulating biological function and is considered to explain part of the 'missing heritability,' which involves marginal genetic effects that cannot be accounted for in genome-wide association studies. Thus, the study of epistasis is of great interest to geneticists. However, estimating epistatic effects for quantitative traits is challenging due to the large number of interaction effects that must be estimated, thus significantly increasing computing demands. Here, we present a new web server-based tool, the Pipeline for estimating EPIStatic genetic effects (PEPIS), for analyzing polygenic epistatic effects. The PEPIS software package is based on a new linear mixed model that has been used to predict the performance of hybrid rice. The PEPIS includes two main sub-pipelines: the first for kinship matrix calculation, and the second for polygenic component analyses and genome scanning for main and epistatic effects. To accommodate the demand for high-performance computation, the PEPIS utilizes C/C++ for mathematical matrix computing. In addition, the modules for kinship matrix calculations and main and epistatic-effect genome scanning employ parallel computing technology that effectively utilizes multiple computer nodes across our networked cluster, thus significantly improving the computational speed. For example, when analyzing the same immortalized F2 rice population genotypic data examined in a previous study, the PEPIS returned identical results at each analysis step with the original prototype R code, but the computational time was reduced from more than one month to about five minutes. These advances will help overcome the bottleneck frequently encountered in genome wide epistatic genetic effect analysis and enable accommodation of the high computational demand. The PEPIS is publically available at http://bioinfo.noble.org/PolyGenic_QTL/.

Inheritance of bacterial spot resistance in Capsicum annuum var. annuum.

PubMed

Silva, L R A; Rodrigues, R; Pimenta, S; Correa, J W S; Araújo, M S B; Bento, C S; Sudré, C P

2017-04-20

Since 2008, Brazil is the largest consumer of agrochemicals, which increases production costs and risks of agricultural products, environment, and farmers' contamination. Sweet pepper, which is one of the main consumed vegetables in the country, is on top of the list of the most sprayed crops. The bacterial spot, caused by Xanthomonas spp, is one of the most damaging diseases of pepper crops. Genetic resistant consists of a suitable way of disease control, but development of durable resistant cultivars as well as understanding of plant-bacterium interaction is being a challenge for plant breeders and pathologists worldwide. Inheritance of disease resistance is often variable, depending on genetic background of the parents. The knowledge of the genetic base controlling such resistance is the first step in a breeding program aiming to develop new genotypes, bringing together resistance and other superior agronomic traits. This study reports the genetic basis of bacterial spot resistance in Capsicum annuum var. annuum using mean generation analysis from crosses between accessions UENF 2285 (susceptible) and UENF 1381 (resistant). The plants of each generation were grown in a greenhouse and leaflets were inoculated with bacterial strain ENA 4135 at 10 5 CFU/mL in 1.0 cm 2 of the mesophyll. Evaluations were performed using a scoring scale whose grades ranged from 1.0 (resistant) to 5.0 (susceptible), depending on symptom manifestation. Genetic control of bacterial spot has a quantitative aspect, with higher additive effect. The quantitative analysis showed that five genes were the minimum number controlling bacterial spot resistance. Additive effect was higher (6.06) than dominant (3.31) and explained 86.36% of total variation.

[Study on once sampling quantitation based on information entropy of ISSR amplified bands of Houttuynia cordata].

PubMed

Wang, Haiqin; Liu, Wenlong; He, Fuyuan; Chen, Zuohong; Zhang, Xili; Xie, Xianggui; Zeng, Jiaoli; Duan, Xiaopeng

2012-02-01

To explore the once sampling quantitation of Houttuynia cordata through its DNA polymorphic bands that carried information entropy, from other form that the expression of traditional Chinese medicine polymorphism, genetic polymorphism, of traditional Chinese medicine. The technique of inter simple sequence repeat (ISSR) was applied to analyze genetic polymorphism of H. cordata samples from the same GAP producing area, the DNA genetic bands were transformed its into the information entropy, and the minimum once sampling quantitation with the mathematical mode was measured. One hundred and thirty-four DNA bands were obtained by using 9 screened ISSR primers to amplify from 46 strains DNA samples of H. cordata from the same GAP, the information entropy was H=0.365 6-0.978 6, and RSD was 14.75%. The once sampling quantitation was W=11.22 kg (863 strains). The "once minimum sampling quantitation" were calculated from the angle of the genetic polymorphism of H. cordata, and a great differences between this volume and the amount from the angle of fingerprint were found.

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.

GENOMIC DIVERSITY AND THE MICROENVIRONMENT AS DRIVERS OF PROGRESSION IN DCIS

DTIC Science & Technology

2017-10-01

stains, including quantitative analysis, 7) Identification of upstaged DCIS cases for the radiology aim, 8) Development of image analysis methods for...goals of the project? Aim 1. Determine whether genetic diversity of DCIS is greater in DCIS with adjacent invasive disease compared to DCIS without... compared to DCIS without IDC. Since genomics is not the sole driver of tumor behavior, we will phenotypically characterize DCIS and its

[Landscape and ecological genomics].

PubMed

Tetushkin, E Ia

2013-10-01

Landscape genomics is the modern version of landscape genetics, a discipline that arose approximately 10 years ago as a combination of population genetics, landscape ecology, and spatial statistics. It studies the effects of environmental variables on gene flow and other microevolutionary processes that determine genetic connectivity and variations in populations. In contrast to population genetics, it operates at the level of individual specimens rather than at the level of population samples. Another important difference between landscape genetics and genomics and population genetics is that, in the former, the analysis of gene flow and local adaptations takes quantitative account of landforms and features of the matrix, i.e., hostile spaces that separate species habitats. Landscape genomics is a part of population ecogenomics, which, along with community genomics, is a major part of ecological genomics. One of the principal purposes of landscape genomics is the identification and differentiation of various genome-wide and locus-specific effects. The approaches and computation tools developed for combined analysis of genomic and landscape variables make it possible to detect adaptation-related genome fragments, which facilitates the planning of conservation efforts and the prediction of species' fate in response to expected changes in the environment.

Characterization and application of a quantitative DNA marker that discriminates sex in Chinook salmon (Oncorhynchus tshawytscha)

USGS Publications Warehouse

Clifton, D.R.; Rodriguez, R.J.

1997-01-01

A qualitative male-specific DNA marker (OT-24) was amplified by spPCR (single-primer polymerase chain reaction) from chinook salmon (Oncorhynchus tshawytscha) DNA along with several non-sex-linked products. The termini of the male-specific product were sequenced, and a pair of PeR primers were constructed for marker-specific PCR amplification. Dual primer PCR (dpPCR), with the marker-specific primers, amplified a product from both nudes and females. The amount of dpPCR product amplified from males was at least 100-fold greater than that from females. The quantitative difference between males and females was consistent among geographically distinct populations from western U.S. rivers. In addition, DNA sequence analysis indicated that OT-24 was highly conserved among geographically distinct salmon populations. The qualitative spPCR product segregated through several genetic crosses indicating equal sex ratios among progeny. Identification of the male and female juveniles by dpPCR was consistent with the spPCR analysis. There was no tissue specificity observed by spPCR or dpPCR analysis of this marker. A rapid DNA extraction method and dpPCR analysis were used to nonlethally determine sex ratios in wild spring chinook salmon adults, withheld for genetic and behavioral studies, prior to their development of gross sexual differences in their external morphology.

Characterization and application of a quantitative DNA marker that discriminates sex in chinook salmon (Oncorhynchus tshawytscha)

USGS Publications Warehouse

Clifton, D.R.; Rodriguez, R.J.

1997-01-01

A qualitative male-specific DNA marker (OT-24) was amplified by spPCR (single-primer polymerase chain reaction) from chinook salmon (Oncorhynchus tshawytscha) DNA along with several non-sex-linked products. The termini of the male-specific product were sequenced, and a pair of PeR primers were constructed for marker-specific PCR amplification. Dual primer PCR (dpPCR), with the marker-specific primers, amplified a product from both nudes and females. The amount of dpPCR product amplified from males was at least 100-fold greater than that from females. The quantitative difference between males and females was consistent among geographically distinct populations from western U.S. rivers. In addition, DNA sequence analysis indicated that OT-24 was highly conserved among geographically distinct salmon populations. The qualitative spPCR product segregated through several genetic crosses indicating equal sex ratios among progeny. Identification of the male and female juveniles by dpPCR was consistent with the spPCR analysis. There was no tissue specificity observed by spPCR or dpPCR analysis of this marker. A rapid DNA extraction method and dpPCR analysis were used to nonlethally determine sex ratios in wild spring chinook salmon adults, withheld for genetic and behavioral studies, prior to their development of gross sexual differences in their external morphology.

Quantitative trait loci for a neurocranium deformity, lack of operculum, in gilthead seabream (Sparus aurata L.).

PubMed

Negrín-Báez, D; Navarro, A; Afonso, J M; Toro, M A; Zamorano, M J

2016-04-01

Lack of operculum, a neurocranial deformity, is the most common external abnormality to be found among industrially produced gilthead seabream (Sparus aurata L.), and this entails significant financial losses. This study conducts, for the first time in this species, a quantitative trait loci (QTL) analysis of the lack of operculum. A total of 142 individuals from a paternal half-sibling family (six full-sibling families) were selected for QTL mapping. They had previously shown a highly significant association with the prevalence of lack of operculum in a segregation analysis. All the fish were genotyped for 106 microsatellite markers using a set of multiplex PCRs (ReMsa1-ReMsa13). A linear regression methodology was used for the QTL analysis. Four QTL were detected for this deformity, two of which (QTLOP1 and QTLOP2) were significant. They were located at LG (linkage group) nine and LG10 respectively. Both QTL showed a large effect (about 27%), and furthermore, the association between lack of operculum and sire allelic segregation observed was statistically significant in the QTLOP1 analysis. These results represent a significant step towards including marker-assisted selection for this deformity in genetic breeding programmes to reduce the incidence of the deformity in the species. © 2016 Stichting International Foundation for Animal Genetics.

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

If I Could in a Small Way Help”: Motivations for and Beliefs about Sample Donation for Genetic Research

PubMed Central

Michie, Marsha; Henderson, Gail; Garrett, Joanne; Corbie-Smith, Giselle

2012-01-01

Human genome research depends upon participants who donate genetic samples, but few studies have explored in depth the motivations of genetic research donors. This mixed methods study examines telephone interviews with 752 sample donors in a U.S. genetic epidemiology study investigating colorectal cancer. Quantitative and qualitative results indicate that most participants wanted to help society, and that many also wanted information about their own health, even though such information was not promised. Qualitative analysis reveals that donors believed their samples contributed to a scientific “common good”; imagined samples as information rather than tissues; and often blurred distinctions between research and diagnostic testing of samples. Differences between African American and White perspectives were distinct from educational and other possible explanatory factors. PMID:21680977

[The genetic control of mouse coat color and its applications in genetics teaching].

PubMed

Xing, Wanjin; Morigen, Morigen

2014-10-01

Mice are the most commonly used mammalian model. The coat colors of mice are typical Mendelian traits, which have various colors such as white, black, yellow and agouti. The inheritance of mouse coat color is usually stated as an example only in teaching the knowledge of recessive lethal alleles. After searched the related literatures and summarized the molecular mechanisms of mouse coat color inheritance, we further expanded the application of this example into the introduction of the basic concepts of alleles and Mendelian laws, demonstration of the gene structure and function, regulation of gene expression, gene interaction, epigenetic modification, quantitative genetics, as well as evolutionary genetics. By running this example through the whole genetics-teaching lectures, we help the student to form a systemic and developmental view of genetic analysis. At the same time, this teaching approach not only highlights the advancement and integrity of genetics, but also results in a good teaching effect on inspiring the students' interest and attracting students' attention.

The chicken genome: some good news and some bad news.

PubMed

Dodgson, J B

2007-07-01

The sequencing of the chicken genome has generated a wealth of good news for poultry science. It allows the chicken to be a major player in 21st century biology by providing an entrée into an arsenal of new technologies that can be used to explore virtually any chicken phenotype of interest. The initial technological onslaught has been described in this symposium. The wealth of data available now or soon to be available cannot be explained by simplistic models and will force us to treat the inherent complexity of the chicken in ways that are more realistic but at the same time more difficult to comprehend. Initial single nucleotide polymorphism analyses suggest that broilers retain a remarkable amount of the genetic diversity of predomesticated Jungle Fowl, whereas commercial layer genomes display less diversity and broader linkage disequilibrium. Thus, intensive commercial selection has not fixed a genome rich in wide selective sweeps, at least within the broiler population. Rather, a complex assortment of combinations of ancient allelic diversity survives. Low levels of linkage disequilibrium will make association analysis in broilers more difficult. The wider disequilibrium observed in layers should facilitate the mapping of quantitative trait loci, and at the same time make it more difficult to identify the causative nucleotide change(s). In addition, many quantitative traits may be specific to the genetic background in which they arose and not readily transferable to, or detectable in, other line backgrounds. Despite the obstacles it presents, the genetic complexity of the chicken may also be viewed as good news because it insures that long-term genetic progress will continue via breeding using quantitative genetics, and it surely will keep poultry scientists busy for decades to come. It is now time to move from an emphasis on obtaining "THE" chicken genome sequence to obtaining multiple sequences, especially of foundation stocks, and a broader understanding of the full genetic and phenotypic diversity of the domesticated chicken.

A Simple and Computationally Efficient Approach to Multifactor Dimensionality Reduction Analysis of Gene-Gene Interactions for Quantitative Traits

PubMed Central

Gui, Jiang; Moore, Jason H.; Williams, Scott M.; Andrews, Peter; Hillege, Hans L.; van der Harst, Pim; Navis, Gerjan; Van Gilst, Wiek H.; Asselbergs, Folkert W.; Gilbert-Diamond, Diane

2013-01-01

We present an extension of the two-class multifactor dimensionality reduction (MDR) algorithm that enables detection and characterization of epistatic SNP-SNP interactions in the context of a quantitative trait. The proposed Quantitative MDR (QMDR) method handles continuous data by modifying MDR’s constructive induction algorithm to use a T-test. QMDR replaces the balanced accuracy metric with a T-test statistic as the score to determine the best interaction model. We used a simulation to identify the empirical distribution of QMDR’s testing score. We then applied QMDR to genetic data from the ongoing prospective Prevention of Renal and Vascular End-Stage Disease (PREVEND) study. PMID:23805232

Beyond Punnett Squares: Student Word Association and Explanations of Phenotypic Variation through an Integrative Quantitative Genetics Unit Investigating Anthocyanin Inheritance and Expression in "Brassica rapa" Fast Plants

ERIC Educational Resources Information Center

Batzli, Janet M.; Smith, Amber R.; Williams, Paul H.; McGee, Seth A.; Dosa, Katalin; Pfammatter, Jesse

2014-01-01

Genetics instruction in introductory biology is often confined to Mendelian genetics and avoids the complexities of variation in quantitative traits. Given the driving question "What determines variation in phenotype (Pv)? (Pv=Genotypic variation Gv + environmental variation Ev)," we developed a 4-wk unit for an inquiry-based laboratory…

Population-genetics approach to the genetics of human behaviour.

PubMed

Bulaeva, K B; Isaichev, S A; Pavlova, T A

1990-04-01

Invariant values of inheritance factors within and between different populations can show the existence of and measure the degree of genetic determination of behavioural characters. The absence of inbred depression of quantitative behavioural characters in isolated populations of highland inhabitants of Daghestan is demonstrated by means of comparative analysis of the mean population values of psychophysiological characters in outbred, moderately isolated, and extremely isolated (and inbred) populations. The absence of pronounced adverse effects of inbred marriages, known as the 'Daghestan phenomenon', is explained by the antiquity of the native populations and the severe ecological conditions under which these populations live which have led to elimination of carriers of hereditary diseases and other detrimental phenotypes.

Fine phenotyping of pod and seed traits in Arachis germplasm accessions using digital image analysis

USDA-ARS?s Scientific Manuscript database

Reliable and objective phenotyping of peanut pod and seed traits is important for cultivar selection and genetic mapping of yield components. To develop useful and efficient methods to quantitatively define peanut pod and seed traits, a group of peanut germplasm with high levels of phenotypic varia...

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. ...

Identification of nutrient and physical seed trait QTLs in the model legume, Lotus japonicus

USDA-ARS?s Scientific Manuscript database

Legume seeds have the potential to provide a significant portion of essential micronutrients to the human diet. To identify the genetic basis for seed nutrient density, quantitative trait locus (QTL) analysis was conducted with the Gifu B-129 x Miyakojima MG-20 recombinant inbred population from th...

A large scale joint analysis of flowering time reveals independent temperate adaptations in maize

USDA-ARS?s Scientific Manuscript database

Modulating days to flowering is a key mechanism in plants for adapting to new environments, and variation in days to flowering drives population structure by limiting mating. To elucidate the genetic architecture of flowering across maize, a quantitative trait, we mapped flowering in five global pop...

AGE-RELATED DIFFERENCES IN SUSCEPTIBILITY TO CARCINOGENESIS II, APPROACHES FOR APPLICATION AND UNCERTAINTY ANALYSES FOR INDIVIDUAL GENETICALLY ACTING CARCINOGENS

EPA Science Inventory

An earlier paper (Hattis et al., 2003) developed a quantitative likelihood-based statistical analysis of the differences in apparent sensitivity of rodents to mutagenic carcinogens across three life stages (fetal, birth-weaning, and weaning-60 days) relative to exposures in adult...

Genome-Wide Association Study of Intelligence: Additive Effects of Novel Brain Expressed Genes

ERIC Educational Resources Information Center

Loo, Sandra K.; Shtir, Corina; Doyle, Alysa E.; Mick, Eric; McGough, James J.; McCracken, James; Biederman, Joseph; Smalley, Susan L.; Cantor, Rita M.; Faraone, Stephen V.; Nelson, Stanley F.

2012-01-01

Objective: The purpose of the present study was to identify common genetic variants that are associated with human intelligence or general cognitive ability. Method: We performed a genome-wide association analysis with a dense set of 1 million single-nucleotide polymorphisms (SNPs) and quantitative intelligence scores within an ancestrally…

Nutrient uptake, biomass yield and quantitative analysis of aliphatic aldehydes in cilantro plants

USDA-ARS?s Scientific Manuscript database

The objective of this study was to evaluate the nutrient uptake, biomass production and yield of the major compounds in the essential oil of five genotypes of Coriandrum sativum L. The treatments were four accessions donated by the National Genetic Resources Advisory Council (NGRAC), U.S. Department...

Medium-based noninvasive preimplantation genetic diagnosis for human α-thalassemias-SEA.

PubMed

Wu, Haitao; Ding, Chenhui; Shen, Xiaoting; Wang, Jing; Li, Rong; Cai, Bing; Xu, Yanwen; Zhong, Yiping; Zhou, Canquan

2015-03-01

To develop a noninvasive medium-based preimplantation genetic diagnosis (PGD) test for α-thalassemias-SEA. The embryos of α-thalassemia-SEA carriers undergoing in vitro fertilization (IVF) were cultured. Single cells were biopsied from blastomeres and subjected to fluorescent gap polymerase chain reaction (PCR) analysis; the spent culture media that contained embryo genomic DNA and corresponding blastocysts as verification were subjected to quantitative-PCR (Q-PCR) detection of α-thalassemia-SEA. The diagnosis efficiency and allele dropout (ADO) ratio were calculated, and the cell-free DNA concentration was quantitatively assessed in the culture medium. The diagnosis efficiency of medium-based α-thalassemias-SEA detection significantly increased compared with that of biopsy-based fluorescent gap PCR analysis (88.6% vs 82.1%, P < 0.05). There is no significant difference regarding ADO ratio between them. The optimal time for medium-based α-thalassemias-SEA detection is Day 5 (D5) following IVF. Medium-based α-thalassemias-SEA detection could represent a novel, quick, and noninvasive approach for carriers to undergo IVF and PGD.

Composition and Quantitation of Microalgal Lipids by ERETIC 1H NMR Method

PubMed Central

Nuzzo, Genoveffa; Gallo, Carmela; d’Ippolito, Giuliana; Cutignano, Adele; Sardo, Angela; Fontana, Angelo

2013-01-01

Accurate characterization of biomass constituents is a crucial aspect of research in the biotechnological application of natural products. Here we report an efficient, fast and reproducible method for the identification and quantitation of fatty acids and complex lipids (triacylglycerols, glycolipids, phospholipids) in microalgae under investigation for the development of functional health products (probiotics, food ingredients, drugs, etc.) or third generation biofuels. The procedure consists of extraction of the biological matrix by modified Folch method and direct analysis of the resulting material by proton nuclear magnetic resonance (1H NMR). The protocol uses a reference electronic signal as external standard (ERETIC method) and allows assessment of total lipid content, saturation degree and class distribution in both high throughput screening of algal collection and metabolic analysis during genetic or culturing studies. As proof of concept, the methodology was applied to the analysis of three microalgal species (Thalassiosira weissflogii, Cyclotella cryptica and Nannochloropsis salina) which drastically differ for the qualitative and quantitative composition of their fatty acid-based lipids. PMID:24084790

Transitioning from Targeted to Comprehensive Mass Spectrometry Using Genetic Algorithms.

PubMed

Jaffe, Jacob D; Feeney, Caitlin M; Patel, Jinal; Lu, Xiaodong; Mani, D R

2016-11-01

Targeted proteomic assays are becoming increasingly popular because of their robust quantitative applications enabled by internal standardization, and they can be routinely executed on high performance mass spectrometry instrumentation. However, these assays are typically limited to 100s of analytes per experiment. Considerable time and effort are often expended in obtaining and preparing samples prior to targeted analyses. It would be highly desirable to detect and quantify 1000s of analytes in such samples using comprehensive mass spectrometry techniques (e.g., SWATH and DIA) while retaining a high degree of quantitative rigor for analytes with matched internal standards. Experimentally, it is facile to port a targeted assay to a comprehensive data acquisition technique. However, data analysis challenges arise from this strategy concerning agreement of results from the targeted and comprehensive approaches. Here, we present the use of genetic algorithms to overcome these challenges in order to configure hybrid targeted/comprehensive MS assays. The genetic algorithms are used to select precursor-to-fragment transitions that maximize the agreement in quantification between the targeted and the comprehensive methods. We find that the algorithm we used provided across-the-board improvement in the quantitative agreement between the targeted assay data and the hybrid comprehensive/targeted assay that we developed, as measured by parameters of linear models fitted to the results. We also found that the algorithm could perform at least as well as an independently-trained mass spectrometrist in accomplishing this task. We hope that this approach will be a useful tool in the development of quantitative approaches for comprehensive proteomics techniques. Graphical Abstract ᅟ.

Transitioning from Targeted to Comprehensive Mass Spectrometry Using Genetic Algorithms

NASA Astrophysics Data System (ADS)

Jaffe, Jacob D.; Feeney, Caitlin M.; Patel, Jinal; Lu, Xiaodong; Mani, D. R.

2016-11-01

Targeted proteomic assays are becoming increasingly popular because of their robust quantitative applications enabled by internal standardization, and they can be routinely executed on high performance mass spectrometry instrumentation. However, these assays are typically limited to 100s of analytes per experiment. Considerable time and effort are often expended in obtaining and preparing samples prior to targeted analyses. It would be highly desirable to detect and quantify 1000s of analytes in such samples using comprehensive mass spectrometry techniques (e.g., SWATH and DIA) while retaining a high degree of quantitative rigor for analytes with matched internal standards. Experimentally, it is facile to port a targeted assay to a comprehensive data acquisition technique. However, data analysis challenges arise from this strategy concerning agreement of results from the targeted and comprehensive approaches. Here, we present the use of genetic algorithms to overcome these challenges in order to configure hybrid targeted/comprehensive MS assays. The genetic algorithms are used to select precursor-to-fragment transitions that maximize the agreement in quantification between the targeted and the comprehensive methods. We find that the algorithm we used provided across-the-board improvement in the quantitative agreement between the targeted assay data and the hybrid comprehensive/targeted assay that we developed, as measured by parameters of linear models fitted to the results. We also found that the algorithm could perform at least as well as an independently-trained mass spectrometrist in accomplishing this task. We hope that this approach will be a useful tool in the development of quantitative approaches for comprehensive proteomics techniques.

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

PubMed

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

2017-08-01

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

Universality and predictability in molecular quantitative genetics.

PubMed

Nourmohammad, Armita; Held, Torsten; Lässig, Michael

2013-12-01

Molecular traits, such as gene expression levels or protein binding affinities, are increasingly accessible to quantitative measurement by modern high-throughput techniques. Such traits measure molecular functions and, from an evolutionary point of view, are important as targets of natural selection. We review recent developments in evolutionary theory and experiments that are expected to become building blocks of a quantitative genetics of molecular traits. We focus on universal evolutionary characteristics: these are largely independent of a trait's genetic basis, which is often at least partially unknown. We show that universal measurements can be used to infer selection on a quantitative trait, which determines its evolutionary mode of conservation or adaptation. Furthermore, universality is closely linked to predictability of trait evolution across lineages. We argue that universal trait statistics extends over a range of cellular scales and opens new avenues of quantitative evolutionary systems biology. Copyright © 2013. Published by Elsevier Ltd.

Quantitative analysis of microtubule orientation in interdigitated leaf pavement cells

PubMed Central

Akita, Kae; Higaki, Takumi; Kutsuna, Natsumaro; Hasezawa, Seiichiro

2015-01-01

Leaf pavement cells are shaped like a jigsaw puzzle in most dicotyledon species. Molecular genetic studies have identified several genes required for pavement cells morphogenesis and proposed that microtubules play crucial roles in the interdigitation of pavement cells. In this study, we performed quantitative analysis of cortical microtubule orientation in leaf pavement cells in Arabidopsis thaliana. We captured confocal images of cortical microtubules in cotyledon leaf epidermis expressing GFP-tubulinβ and quantitatively evaluated the microtubule orientations relative to the pavement cell growth axis using original image processing techniques. Our results showed that microtubules kept parallel orientations to the growth axis during pavement cell growth. In addition, we showed that immersion treatment of seed cotyledons in solutions containing tubulin polymerization and depolymerization inhibitors decreased pavement cell complexity. Treatment with oryzalin and colchicine inhibited the symmetric division of guard mother cells. PMID:26039484

Little effect of HSP90 inhibition on the quantitative wing traits variation in Drosophila melanogaster.

PubMed

Takahashi, Kazuo H

2017-02-01

Drosophila wings have been a model system to study the effect of HSP90 on quantitative trait variation. The effect of HSP90 inhibition on environmental buffering of wing morphology varies among studies while the genetic buffering effect of it was examined in only one study and was not detected. Variable results so far might show that the genetic background influences the environmental and genetic buffering effect of HSP90. In the previous studies, the number of the genetic backgrounds used is limited. To examine the effect of HSP90 inhibition with a larger number of genetic backgrounds than the previous studies, 20 wild-type strains of Drosophila melanogaster were used in this study. Here I investigated the effect of HSP90 inhibition on the environmental buffering of wing shape and size by assessing within-individual and among-individual variations, and as a result, I found little or very weak effects on environmental and genetic buffering. The current results suggest that the role of HSP90 as a global regulator of environmental and genetic buffering is limited at least in quantitative traits.

International collaborative study of the endogenous reference gene, sucrose phosphate synthase (SPS), used for qualitative and quantitative analysis of genetically modified rice.

PubMed

Jiang, Lingxi; Yang, Litao; Zhang, Haibo; Guo, Jinchao; Mazzara, Marco; Van den Eede, Guy; Zhang, Dabing

2009-05-13

One rice ( Oryza sativa ) gene, sucrose phosphate synthase (SPS), has been proven to be a suitable endogenous reference gene for genetically modified (GM) rice detection in a previous study. Herein are the reported results of an international collaborative ring trial for validation of the SPS gene as an endogenous reference gene and its optimized qualitative and quantitative polymerase chain reaction (PCR) systems. A total of 12 genetically modified organism (GMO) detection laboratories from seven countries participated in the ring trial and returned their results. The validated results confirmed the species specificity of the method through testing 10 plant genomic DNAs, low heterogeneity, and a stable single-copy number of the rice SPS gene among 7 indica varieties and 5 japonica varieties. The SPS qualitative PCR assay was validated with a limit of detection (LOD) of 0.1%, which corresponded to about 230 copies of haploid rice genomic DNA, while the limit of quantification (LOQ) for the quantitative PCR system was about 23 copies of haploid rice genomic DNA, with acceptable PCR efficiency and linearity. Furthermore, the bias between the test and true values of eight blind samples ranged from 5.22 to 26.53%. Thus, we believe that the SPS gene is suitable for use as an endogenous reference gene for the identification and quantification of GM rice and its derivates.

An event-specific method for the detection and quantification of ML01, a genetically modified Saccharomyces cerevisiae wine strain, using quantitative PCR.

PubMed

Vaudano, Enrico; Costantini, Antonella; Garcia-Moruno, Emilia

2016-10-03

The availability of genetically modified (GM) yeasts for winemaking and, in particular, transgenic strains based on the integration of genetic constructs deriving from other organisms into the genome of Saccharomyces cerevisiae, has been a reality for several years. Despite this, their use is only authorized in a few countries and limited to two strains: ML01, able to convert malic acid into lactic acid during alcoholic fermentation, and ECMo01 suitable for reducing the risk of carbamate production. In this work we propose a quali-quantitative culture-independent method for the detection of GM yeast ML01 in commercial preparations of ADY (Active Dry Yeast) consisting of efficient extraction of DNA and qPCR (quantitative PCR) analysis based on event-specific assay targeting MLC (malolactic cassette), and a taxon-specific S. cerevisiae assay detecting the MRP2 gene. The ADY DNA extraction methodology has been shown to provide good purity DNA suitable for subsequent qPCR. The MLC and MRP2 qPCR assay showed characteristics of specificity, dynamic range, limit of quantification (LOQ) limit of detection (LOD), precision and trueness, which were fully compliant with international reference guidelines. The method has been shown to reliably detect 0.005% (mass/mass) of GM ML01 S. cerevisiae in commercial preparations of ADY. Copyright © 2016 Elsevier B.V. All rights reserved.

An assessment of the reliability of quantitative genetics estimates in study systems with high rate of extra-pair reproduction and low recruitment.

PubMed

Bourret, A; Garant, D

2017-03-01

Quantitative genetics approaches, and particularly animal models, are widely used to assess the genetic (co)variance of key fitness related traits and infer adaptive potential of wild populations. Despite the importance of precision and accuracy of genetic variance estimates and their potential sensitivity to various ecological and population specific factors, their reliability is rarely tested explicitly. Here, we used simulations and empirical data collected from an 11-year study on tree swallow (Tachycineta bicolor), a species showing a high rate of extra-pair paternity and a low recruitment rate, to assess the importance of identity errors, structure and size of the pedigree on quantitative genetic estimates in our dataset. Our simulations revealed an important lack of precision in heritability and genetic-correlation estimates for most traits, a low power to detect significant effects and important identifiability problems. We also observed a large bias in heritability estimates when using the social pedigree instead of the genetic one (deflated heritabilities) or when not accounting for an important cause of resemblance among individuals (for example, permanent environment or brood effect) in model parameterizations for some traits (inflated heritabilities). We discuss the causes underlying the low reliability observed here and why they are also likely to occur in other study systems. Altogether, our results re-emphasize the difficulties of generalizing quantitative genetic estimates reliably from one study system to another and the importance of reporting simulation analyses to evaluate these important issues.

The genetic basis of female multiple mating in a polyandrous livebearing fish

PubMed Central

Evans, Jonathan P; Gasparini, Clelia

2013-01-01

The widespread occurrence of female multiple mating (FMM) demands evolutionary explanation, particularly in the light of the costs of mating. One explanation encapsulated by “good sperm” and “sexy-sperm” (GS-SS) theoretical models is that FMM facilitates sperm competition, thus ensuring paternity by males that pass on genes for elevated sperm competitiveness to their male offspring. While support for this component of GS-SS theory is accumulating, a second but poorly tested assumption of these models is that there should be corresponding heritable genetic variation in FMM – the proposed mechanism of postcopulatory preferences underlying GS-SS models. Here, we conduct quantitative genetic analyses on paternal half-siblings to test this component of GS-SS theory in the guppy (Poecilia reticulata), a freshwater fish with some of the highest known rates of FMM in vertebrates. As with most previous quantitative genetic analyses of FMM in other species, our results reveal high levels of phenotypic variation in this trait and a correspondingly low narrow-sense heritability (h2 = 0.11). Furthermore, although our analysis of additive genetic variance in FMM was not statistically significant (probably owing to limited statistical power), the ensuing estimate of mean-standardized additive genetic variance (IA = 0.7) was nevertheless relatively low compared with estimates published for life-history traits across a broad range of taxa. Our results therefore add to a growing body of evidence that FMM is characterized by relatively low additive genetic variation, thus apparently contradicting GS-SS theory. However, we qualify this conclusion by drawing attention to potential deficiencies in most designs (including ours) that have tested for genetic variation in FMM, particularly those that fail to account for intersexual interactions that underlie FMM in many systems. PMID:23403856

Heritability of seed weight in Maritime pine, a relevant trait in the transmission of environmental maternal effects

PubMed Central

Zas, R; Sampedro, L

2015-01-01

Quantitative seed provisioning is an important life-history trait with strong effects on offspring phenotype and fitness. As for any other trait, heritability estimates are vital for understanding its evolutionary dynamics. However, being a trait in between two generations, estimating additive genetic variation of seed provisioning requires complex quantitative genetic approaches for distinguishing between true genetic and environmental maternal effects. Here, using Maritime pine as a long-lived plant model, we quantified additive genetic variation of cone and seed weight (SW) mean and SW within-individual variation. We used a powerful approach combining both half-sib analysis and parent–offspring regression using several common garden tests established in contrasting environments to separate G, E and G × E effects. Both cone weight and SW mean showed significant genetic variation but were also influenced by the maternal environment. Most of the large variation in SW mean was attributable to additive genetic effects (h2=0.55–0.74). SW showed no apparent G × E interaction, particularly when accounting for cone weight covariation, suggesting that the maternal genotypes actively control the SW mean irrespective of the amount of resources allocated to cones. Within-individual variation in SW was low (12%) relative to between-individual variation (88%), and showed no genetic variation but was largely affected by the maternal environment, with greater variation in the less favourable sites for pine growth. In summary, results were very consistent between the parental and the offspring common garden tests, and clearly indicated heritable genetic variation for SW mean but not for within-individual variation in SW. PMID:25160045

Motivations for genetic testing for lung cancer risk among young smokers.

PubMed

O'Neill, Suzanne C; Lipkus, Isaac M; Sanderson, Saskia C; Shepperd, James; Docherty, Sharron; McBride, Colleen M

2013-11-01

To examine why young people might want to undergo genetic susceptibility testing for lung cancer despite knowing that tested gene variants are associated with small increases in disease risk. The authors used a mixed-method approach to evaluate motives for and against genetic testing and the association between these motivations and testing intentions in 128 college students who smoke. Exploratory factor analysis yielded four reliable factors: Test Scepticism, Test Optimism, Knowledge Enhancement and Smoking Optimism. Test Optimism and Knowledge Enhancement correlated positively with intentions to test in bivariate and multivariate analyses (ps<0.001). Test Scepticism correlated negatively with testing intentions in multivariate analyses (p<0.05). Open-ended questions assessing testing motivations generally replicated themes of the quantitative survey. In addition to learning about health risks, young people may be motivated to seek genetic testing for reasons, such as gaining knowledge about new genetic technologies more broadly.

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

Missing heritability in the tails of quantitative traits? A simulation study on the impact of slightly altered true genetic models.

PubMed

Pütter, Carolin; Pechlivanis, Sonali; Nöthen, Markus M; Jöckel, Karl-Heinz; Wichmann, Heinz-Erich; Scherag, André

2011-01-01

Genome-wide association studies have identified robust associations between single nucleotide polymorphisms and complex traits. As the proportion of phenotypic variance explained is still limited for most of the traits, larger and larger meta-analyses are being conducted to detect additional associations. Here we investigate the impact of the study design and the underlying assumption about the true genetic effect in a bimodal mixture situation on the power to detect associations. We performed simulations of quantitative phenotypes analysed by standard linear regression and dichotomized case-control data sets from the extremes of the quantitative trait analysed by standard logistic regression. Using linear regression, markers with an effect in the extremes of the traits were almost undetectable, whereas analysing extremes by case-control design had superior power even for much smaller sample sizes. Two real data examples are provided to support our theoretical findings and to explore our mixture and parameter assumption. Our findings support the idea to re-analyse the available meta-analysis data sets to detect new loci in the extremes. Moreover, our investigation offers an explanation for discrepant findings when analysing quantitative traits in the general population and in the extremes. Copyright © 2011 S. Karger AG, Basel.

A qualitative and quantitative analysis of the New Zealand media portrayal of Down syndrome.

PubMed

Wardell, S; Fitzgerald, R P; Legge, M; Clift, K

2014-04-01

There are only a small number of studies that systematically explore the tensions between the global shift to universal screening and the media representations of the people with Down syndrome. This paper contributes to the literature by analyzing the New Zealand media coverage of this topic. To describe the content and quality of selected New Zealand media references to Down syndrome in light of the claim by New Zealand support group Saving Downs of state supported eugenics via universal screening. Quantitative content analysis was conducted of 140 relevant New Zealand articles (from 2001 to 2011) and qualitative critical discourse analysis of 18 relevant articles (from 2009 to 2011) selected from television, magazine and newspaper. The content analysis showed no strong directional reporting although the quality of life for people with Down syndrome was represented as slightly negative. Most articles focused on issues of society, government and care rather than genetics. The qualitative analysis identified themes around quality of life, information and bias, preparedness, eugenics, the visualness of disability and the need for public debate around genetic screening and testing. The New Zealand print media coverage of these issues has been relatively balanced. Recent mixed media coverage of the topic is critical, complex and socially inclusive of people with Down syndrome. Copyright © 2014 Elsevier Inc. All rights reserved.

Heritability of circulating growth factors involved in the angiogenesis in healthy human population.

PubMed

Pantsulaia, I; Trofimov, S; Kobyliansky, E; Livshits, G

2004-09-21

The present study examined the extent of genetic and environmental influences on the populational variation of circulating growth factors (VEGF, EGF) involved in angiogenesis in healthy and ethnically homogeneous Caucasian families. The plasma levels of each of the studied biochemical indices were determined by enzyme-linked immunoassay in 478 healthy individuals aged 18-75 years. Quantitative genetic analysis showed that the VEGF and EGF variation was appreciably attributable to genetic effects, with heritability estimates of 79.9% and 48.4%, respectively. Yet, common environmental factors, shared by members of the same household, also played a significant role (P < 0.01) and explained between 20.1% and 32.6% of the variation. The present study additionally examined the covariations between these molecules and either transforming growth factor-beta 1 (TGF-beta 1) or tissue inhibitors of matrix metalloproteinases 1 (TIMP-1), likewise relevant for angiogenesis. Bivariate analysis revealed significant phenotypic correlations (P < 0.002) between all pairs of variables, thus indicating the possible existence of common genetic and environmental factors. The analysis suggested that the pleiotropic genetic effects were consistently the primary (or even the sole) source of correlation between all pairs of studied molecules. The results of our study affirm the existence of specific and common genetic pathways that commonly determine the greater part of the circulating variation of these molecules.

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis

DOE PAGES

Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.

2017-10-13

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis

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

Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less

A PQL (protein quantity loci) analysis of mature pea seed proteins identifies loci determining seed protein composition.

PubMed

Bourgeois, Michael; Jacquin, Françoise; Cassecuelle, Florence; Savois, Vincent; Belghazi, Maya; Aubert, Grégoire; Quillien, Laurence; Huart, Myriam; Marget, Pascal; Burstin, Judith

2011-05-01

Legume seeds are a major source of dietary proteins for humans and animals. Deciphering the genetic control of their accumulation is thus of primary significance towards their improvement. At first, we analysed the genetic variability of the pea seed proteome of three genotypes over 3 years of cultivation. This revealed that seed protein composition variability was under predominant genetic control, with as much as 60% of the spots varying quantitatively among the three genotypes. Then, by combining proteomic and quantitative trait loci (QTL) mapping approaches, we uncovered the genetic architecture of seed proteome variability. Protein quantity loci (PQL) were searched for 525 spots detected on 2-D gels obtained for 157 recombinant inbred lines. Most protein quantity loci mapped in clusters, suggesting that the accumulation of the major storage protein families was under the control of a limited number of loci. While convicilin accumulation was mainly under the control of cis-regulatory regions, vicilins and legumins were controlled by both cis- and trans-regulatory regions. Some loci controlled both seed protein composition and protein content and a locus on LGIIa appears to be a major regulator of protein composition and of protein in vitro digestibility. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

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

Factor analysis in the Genetics of Asthma International Network family study identifies five major quantitative asthma phenotypes.

PubMed

Pillai, S G; Tang, Y; van den Oord, E; Klotsman, M; Barnes, K; Carlsen, K; Gerritsen, J; Lenney, W; Silverman, M; Sly, P; Sundy, J; Tsanakas, J; von Berg, A; Whyte, M; Ortega, H G; Anderson, W H; Helms, P J

2008-03-01

Asthma is a clinically heterogeneous disease caused by a complex interaction between genetic susceptibility and diverse environmental factors. In common with other complex diseases the lack of a standardized scheme to evaluate the phenotypic variability poses challenges in identifying the contribution of genes and environments to disease expression. To determine the minimum number of sets of features required to characterize subjects with asthma which will be useful in identifying important genetic and environmental contributors. Methods Probands aged 7-35 years with physician diagnosed asthma and symptomatic siblings were identified in 1022 nuclear families from 11 centres in six countries forming the Genetics of Asthma International Network. Factor analysis was used to identify distinct phenotypes from questionnaire, clinical, and laboratory data, including baseline pulmonary function, allergen skin prick test (SPT). Five distinct factors were identified:(1) baseline pulmonary function measures [forced expiratory volume in 1 s (FEV(1)) and forced vital capacity (FVC)], (2) specific allergen sensitization by SPT, (3) self-reported allergies, (4) symptoms characteristic of rhinitis and (5) symptoms characteristic of asthma. Replication in symptomatic siblings was consistent with shared genetic and/or environmental effects, and was robust across age groups, gender, and centres. Cronbach's alpha ranged from 0.719 to 0.983 suggesting acceptable internal scale consistencies. Derived scales were correlated with serum IgE, methacholine PC(20), age and asthma severity (interrupted sleep). IgE correlated with all three atopy-related factors, the strongest with the SPT factor whereas severity only correlated with baseline lung function, and with symptoms characteristic of rhinitis and of asthma. In children and adolescents with established asthma, five distinct sets of correlated patient characteristics appear to represent important aspects of the disease. Factor scores as quantitative traits may be better phenotypes in epidemiological and genetic analyses than those categories derived from the presence or absence of combinations of +ve SPTs and/or elevated IgE.

Quantitative proteomics and terminomics to elucidate the role of ubiquitination and proteolysis in adaptive immunity.

PubMed

Klein, Theo; Viner, Rosa I; Overall, Christopher M

2016-10-28

Adaptive immunity is the specialized defence mechanism in vertebrates that evolved to eliminate pathogens. Specialized lymphocytes recognize specific protein epitopes through antigen receptors to mount potent immune responses, many of which are initiated by nuclear factor-kappa B activation and gene transcription. Most, if not all, pathways in adaptive immunity are further regulated by post-translational modification (PTM) of signalling proteins, e.g. phosphorylation, citrullination, ubiquitination and proteolytic processing. The importance of PTMs is reflected by genetic or acquired defects in these pathways that lead to a dysfunctional immune response. Here we discuss the state of the art in targeted proteomics and systems biology approaches to dissect the PTM landscape specifically regarding ubiquitination and proteolysis in B- and T-cell activation. Recent advances have occurred in methods for specific enrichment and targeted quantitation. Together with improved instrument sensitivity, these advances enable the accurate analysis of often rare PTM events that are opaque to conventional proteomics approaches, now rendering in-depth analysis and pathway dissection possible. We discuss published approaches, including as a case study the profiling of the N-terminome of lymphocytes of a rare patient with a genetic defect in the paracaspase protease MALT1, a key regulator protease in antigen-driven signalling, which was manifested by elevated linear ubiquitination.This article is part of the themed issue 'Quantitative mass spectrometry'. © 2016 The Authors.

Multivariate approach in popcorn genotypes using the Ward-MLM strategy: morpho-agronomic analysis and incidence of Fusarium spp.

PubMed

Kurosawa, R N F; do Amaral Junior, A T; Silva, F H L; Dos Santos, A; Vivas, M; Kamphorst, S H; Pena, G F

2017-02-08

The multivariate analyses are useful tools to estimate the genetic variability between accessions. In the breeding programs, the Ward-Modified Location Model (MLM) multivariate method has been a powerful strategy to quantify variability using quantitative and qualitative variables simultaneously. The present study was proposed in view of the dearth of information about popcorn breeding programs under a multivariate approach using the Ward-MLM methodology. The objective of this study was thus to estimate the genetic diversity among 37 genotypes of popcorn aiming to identify divergent groups associated with morpho-agronomic traits and traits related to resistance to Fusarium spp. To this end, 7 qualitative and 17 quantitative variables were analyzed. The experiment was conducted in 2014, at Universidade Estadual do Norte Fluminense, located in Campos dos Goytacazes, RJ, Brazil. The Ward-MLM strategy allowed the identification of four groups as follows: Group I with 10 genotypes, Group II with 11 genotypes, Group III with 9 genotypes, and Group IV with 7 genotypes. Group IV was distant in relation to the other groups, while groups I, II, and III were near. The crosses between genotypes from the other groups with those of group IV allow an exploitation of heterosis. The Ward-MLM strategy provided an appropriate grouping of genotypes; ear weight, ear diameter, and grain yield were the traits that most contributed to the analysis of genetic diversity.

Quantitative Analysis of Repertoire Scale Immunoglobulin properties in Vaccine Induced B cell Responses

DTIC Science & Technology

Immunosequencing now readily generates 103105 sequences per sample ; however, statistical analysis of these repertoires is challenging because of the high genetic...diversity of BCRs and the elaborate clonal relationships among them. To date, most immunosequencing analyses have focused on reporting qualitative ...repertoire differences, (2) identifying how two repertoires differ, and (3) determining appropriate confidence intervals for assessing the size of the differences and their potential biological relevance.

Candidate genetic pathways for attention-deficit/hyperactivity disorder (ADHD) show association to hyperactive/impulsive symptoms in children with ADHD.

PubMed

Bralten, Janita; Franke, Barbara; Waldman, Irwin; Rommelse, Nanda; Hartman, Catharina; Asherson, Philip; Banaschewski, Tobias; Ebstein, Richard P; Gill, Michael; Miranda, Ana; Oades, Robert D; Roeyers, Herbert; Rothenberger, Aribert; Sergeant, Joseph A; Oosterlaan, Jaap; Sonuga-Barke, Edmund; Steinhausen, Hans-Christoph; Faraone, Stephen V; Buitelaar, Jan K; Arias-Vásquez, Alejandro

2013-11-01

Because multiple genes with small effect sizes are assumed to play a role in attention-deficit/hyperactivity disorder (ADHD) etiology, considering multiple variants within the same analysis likely increases the total explained phenotypic variance, thereby boosting the power of genetic studies. This study investigated whether pathway-based analysis could bring scientists closer to unraveling the biology of ADHD. The pathway was described as a predefined gene selection based on a well-established database or literature data. Common genetic variants in pathways involved in dopamine/norepinephrine and serotonin neurotransmission and genes involved in neuritic outgrowth were investigated in cases from the International Multicentre ADHD Genetics (IMAGE) study. Multivariable analysis was performed to combine the effects of single genetic variants within the pathway genes. Phenotypes were DSM-IV symptom counts for inattention and hyperactivity/impulsivity (n = 871) and symptom severity measured with the Conners Parent (n = 930) and Teacher (n = 916) Rating Scales. Summing genetic effects of common genetic variants within the pathways showed a significant association with hyperactive/impulsive symptoms ((p)empirical = .007) but not with inattentive symptoms ((p)empirical = .73). Analysis of parent-rated Conners hyperactive/impulsive symptom scores validated this result ((p)empirical = .0018). Teacher-rated Conners scores were not associated. Post hoc analyses showed a significant contribution of all pathways to the hyperactive/impulsive symptom domain (dopamine/norepinephrine, (p)empirical = .0004; serotonin, (p)empirical = .0149; neuritic outgrowth, (p)empirical = .0452). The present analysis shows an association between common variants in 3 genetic pathways and the hyperactive/impulsive component of ADHD. This study demonstrates that pathway-based association analyses, using quantitative measurements of ADHD symptom domains, can increase the power of genetic analyses to identify biological risk factors involved in this disorder. Copyright © 2013 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Fragman: an R package for fragment analysis.

PubMed

Covarrubias-Pazaran, Giovanny; Diaz-Garcia, Luis; Schlautman, Brandon; Salazar, Walter; Zalapa, Juan

2016-04-21

Determination of microsatellite lengths or other DNA fragment types is an important initial component of many genetic studies such as mutation detection, linkage and quantitative trait loci (QTL) mapping, genetic diversity, pedigree analysis, and detection of heterozygosity. A handful of commercial and freely available software programs exist for fragment analysis; however, most of them are platform dependent and lack high-throughput applicability. We present the R package Fragman to serve as a freely available and platform independent resource for automatic scoring of DNA fragment lengths diversity panels and biparental populations. The program analyzes DNA fragment lengths generated in Applied Biosystems® (ABI) either manually or automatically by providing panels or bins. The package contains additional tools for converting the allele calls to GenAlEx, JoinMap® and OneMap software formats mainly used for genetic diversity and generating linkage maps in plant and animal populations. Easy plotting functions and multiplexing friendly capabilities are some of the strengths of this R package. Fragment analysis using a unique set of cranberry (Vaccinium macrocarpon) genotypes based on microsatellite markers is used to highlight the capabilities of Fragman. Fragman is a valuable new tool for genetic analysis. The package produces equivalent results to other popular software for fragment analysis while possessing unique advantages and the possibility of automation for high-throughput experiments by exploiting the power of R.

Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice.

PubMed

Stewart, Taryn P; Kim, Hyoung Yon; Saxton, Arnold M; Kim, Jung Han

2010-12-19

Type 2 diabetes (T2D) is the most common form of diabetes in humans and is closely associated with dyslipidemia and obesity that magnifies the mortality and morbidity related to T2D. The genetic contribution to human T2D and related metabolic disorders is evident, and mostly follows polygenic inheritance. The TALLYHO/JngJ (TH) mice are a polygenic model for T2D characterized by obesity, hyperinsulinemia, impaired glucose uptake and tolerance, hyperlipidemia, and hyperglycemia. In order to determine the genetic factors that contribute to these T2D related characteristics in TH mice, we interbred TH mice with C57BL/6J (B6) mice. The parental, F1, and F2 mice were phenotyped at 8, 12, 16, 20, and 24 weeks of age for 4-hour fasting plasma triglyceride, cholesterol, insulin, and glucose levels and body, fat pad and carcass weights. The F2 mice were genotyped genome-wide and used for quantitative trait locus (QTL) mapping. We also applied a genetical genomic approach using a subset of the F2 mice to seek candidate genes underlying the QTLs. Major QTLs were detected on chromosomes (Chrs) 1, 11, 4, and 8 for hypertriglyceridemia, 1 and 3 for hypercholesterolemia, 4 for hyperglycemia, 11 and 1 for body weight, 1 for fat pad weight, and 11 and 14 for carcass weight. Most alleles, except for Chr 3 and 14 QTLs, increased phenotypic values when contributed by the TH strain. Fourteen pairs of interacting loci were detected, none of which overlapped the major QTLs. The QTL interval linked to hypercholesterolemia and hypertriglyceridemia on distal Chr 1 contains Apoa2 gene. Sequencing analysis revealed polymorphisms of Apoa2 in TH mice, suggesting Apoa2 as the candidate gene for the hyperlipidemia QTL. Gene expression analysis added novel information and aided in selection of candidates underlying the QTLs. We identified several genetic loci that affect the quantitative variations of plasma lipid and glucose levels and obesity traits in a TH × B6 intercross. Polymorphisms in Apoa2 gene are suggested to be responsible for the Chr 1 QTL linked to hypercholesterolemia and hypertriglyceridemia. Further, genetical genomic analysis led to potential candidate genes for the QTLs.

Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice

PubMed Central

2010-01-01

Background Type 2 diabetes (T2D) is the most common form of diabetes in humans and is closely associated with dyslipidemia and obesity that magnifies the mortality and morbidity related to T2D. The genetic contribution to human T2D and related metabolic disorders is evident, and mostly follows polygenic inheritance. The TALLYHO/JngJ (TH) mice are a polygenic model for T2D characterized by obesity, hyperinsulinemia, impaired glucose uptake and tolerance, hyperlipidemia, and hyperglycemia. Results In order to determine the genetic factors that contribute to these T2D related characteristics in TH mice, we interbred TH mice with C57BL/6J (B6) mice. The parental, F1, and F2 mice were phenotyped at 8, 12, 16, 20, and 24 weeks of age for 4-hour fasting plasma triglyceride, cholesterol, insulin, and glucose levels and body, fat pad and carcass weights. The F2 mice were genotyped genome-wide and used for quantitative trait locus (QTL) mapping. We also applied a genetical genomic approach using a subset of the F2 mice to seek candidate genes underlying the QTLs. Major QTLs were detected on chromosomes (Chrs) 1, 11, 4, and 8 for hypertriglyceridemia, 1 and 3 for hypercholesterolemia, 4 for hyperglycemia, 11 and 1 for body weight, 1 for fat pad weight, and 11 and 14 for carcass weight. Most alleles, except for Chr 3 and 14 QTLs, increased phenotypic values when contributed by the TH strain. Fourteen pairs of interacting loci were detected, none of which overlapped the major QTLs. The QTL interval linked to hypercholesterolemia and hypertriglyceridemia on distal Chr 1 contains Apoa2 gene. Sequencing analysis revealed polymorphisms of Apoa2 in TH mice, suggesting Apoa2 as the candidate gene for the hyperlipidemia QTL. Gene expression analysis added novel information and aided in selection of candidates underlying the QTLs. Conclusions We identified several genetic loci that affect the quantitative variations of plasma lipid and glucose levels and obesity traits in a TH × B6 intercross. Polymorphisms in Apoa2 gene are suggested to be responsible for the Chr 1 QTL linked to hypercholesterolemia and hypertriglyceridemia. Further, genetical genomic analysis led to potential candidate genes for the QTLs. PMID:21167066

Quantitative trait loci associated with anthracnose resistance in sorghum

USDA-ARS?s Scientific Manuscript database

With an aim to develop a durable resistance to the fungal disease anthracnose, two unique genetic sources of resistance were selected to create genetic mapping populations to identify regions of the sorghum genome that encode anthracnose resistance. A series of quantitative trait loci were identifi...

Quantitative PCR for Detection and Enumeration of Genetic Markers of Bovine Fecal Pollution

EPA Science Inventory

Accurate assessment of health risks associated with bovine (cattle) fecal pollution requires a reliable host-specific genetic marker and a rapid quantification method. We report the development of quantitative PCR assays for the detection of two recently described cow feces-spec...

Mapping Quantitative Traits in Unselected Families: Algorithms and Examples

PubMed Central

Dupuis, Josée; Shi, Jianxin; Manning, Alisa K.; Benjamin, Emelia J.; Meigs, James B.; Cupples, L. Adrienne; Siegmund, David

2009-01-01

Linkage analysis has been widely used to identify from family data genetic variants influencing quantitative traits. Common approaches have both strengths and limitations. Likelihood ratio tests typically computed in variance component analysis can accommodate large families but are highly sensitive to departure from normality assumptions. Regression-based approaches are more robust but their use has primarily been restricted to nuclear families. In this paper, we develop methods for mapping quantitative traits in moderately large pedigrees. Our methods are based on the score statistic which in contrast to the likelihood ratio statistic, can use nonparametric estimators of variability to achieve robustness of the false positive rate against departures from the hypothesized phenotypic model. Because the score statistic is easier to calculate than the likelihood ratio statistic, our basic mapping methods utilize relatively simple computer code that performs statistical analysis on output from any program that computes estimates of identity-by-descent. This simplicity also permits development and evaluation of methods to deal with multivariate and ordinal phenotypes, and with gene-gene and gene-environment interaction. We demonstrate our methods on simulated data and on fasting insulin, a quantitative trait measured in the Framingham Heart Study. PMID:19278016

High-density genetic map construction and comparative genome analysis in asparagus bean.

PubMed

Huang, Haitao; Tan, Huaqiang; Xu, Dongmei; Tang, Yi; Niu, Yisong; Lai, Yunsong; Tie, Manman; Li, Huanxiu

2018-03-19

Genetic maps are a prerequisite for quantitative trait locus (QTL) analysis, marker-assisted selection (MAS), fine gene mapping, and assembly of genome sequences. So far, several asparagus bean linkage maps have been established using various kinds of molecular markers. However, these maps were all constructed by gel- or array-based markers. No maps based on sequencing method have been reported. In this study, an NGS-based strategy, SLAF-seq, was applied to create a high-density genetic map for asparagus bean. Through SLAF library construction and Illumina sequencing of two parents and 100 F2 individuals, a total of 55,437 polymorphic SLAF markers were developed and mined for SNP markers. The map consisted of 5,225 SNP markers in 11 LGs, spanning a total distance of 1,850.81 cM, with an average distance between markers of 0.35 cM. Comparative genome analysis with four other legume species, soybean, common bean, mung bean and adzuki bean showed that asparagus bean is genetically more related to adzuki bean. The results will provide a foundation for future genomic research, such as QTL fine mapping, comparative mapping in pulses, and offer support for assembling asparagus bean genome sequence.

Genetic mapping of variation in dauer larvae development in growing populations of Caenorhabditis elegans.

PubMed

Green, J W M; Snoek, L B; Kammenga, J E; Harvey, S C

2013-10-01

In the nematode Caenorhabditis elegans, the appropriate induction of dauer larvae development within growing populations is likely to be a primary determinant of genotypic fitness. The underlying genetic architecture of natural genetic variation in dauer formation has, however, not been thoroughly investigated. Here, we report extensive natural genetic variation in dauer larvae development within growing populations across multiple wild isolates. Moreover, bin mapping of introgression lines (ILs) derived from the genetically divergent isolates N2 and CB4856 reveals 10 quantitative trait loci (QTLs) affecting dauer formation. Comparison of individual ILs to N2 identifies an additional eight QTLs, and sequential IL analysis reveals six more QTLs. Our results also show that a behavioural, laboratory-derived, mutation controlled by the neuropeptide Y receptor homolog npr-1 can affect dauer larvae development in growing populations. These findings illustrate the complex genetic architecture of variation in dauer larvae formation in C. elegans and may help to understand how the control of variation in dauer larvae development has evolved.

Lack of recognition of genetic biodiversity: International policy and its implementation in Baltic Sea marine protected areas.

PubMed

Laikre, Linda; Lundmark, Carina; Jansson, Eeva; Wennerström, Lovisa; Edman, Mari; Sandström, Annica

2016-10-01

Genetic diversity is needed for species' adaptation to changing selective pressures and is particularly important in regions with rapid environmental change such as the Baltic Sea. Conservation measures should consider maintaining large gene pools to maximize species' adaptive potential for long-term survival. In this study, we explored concerns regarding genetic variation in international and national policies that governs biodiversity and evaluated if and how such policy is put into practice in management plans governing Baltic Sea Marine Protected Areas (MPAs) in Sweden, Finland, Estonia, and Germany. We performed qualitative and quantitative textual analysis of 240 documents and found that agreed international and national policies on genetic biodiversity are not reflected in management plans for Baltic Sea MPAs. Management plans in all countries are largely void of goals and strategies for genetic biodiversity, which can partly be explained by a general lack of conservation genetics in policies directed toward aquatic environments.

A quantitative test of population genetics using spatiogenetic patterns in bacterial colonies.

PubMed

Korolev, Kirill S; Xavier, João B; Nelson, David R; Foster, Kevin R

2011-10-01

It is widely accepted that population-genetics theory is the cornerstone of evolutionary analyses. Empirical tests of the theory, however, are challenging because of the complex relationships between space, dispersal, and evolution. Critically, we lack quantitative validation of the spatial models of population genetics. Here we combine analytics, on- and off-lattice simulations, and experiments with bacteria to perform quantitative tests of the theory. We study two bacterial species, the gut microbe Escherichia coli and the opportunistic pathogen Pseudomonas aeruginosa, and show that spatiogenetic patterns in colony biofilms of both species are accurately described by an extension of the one-dimensional stepping-stone model. We use one empirical measure, genetic diversity at the colony periphery, to parameterize our models and show that we can then accurately predict another key variable: the degree of short-range cell migration along an edge. Moreover, the model allows us to estimate other key parameters, including effective population size (density) at the expansion frontier. While our experimental system is a simplification of natural microbial community, we argue that it constitutes proof of principle that the spatial models of population genetics can quantitatively capture organismal evolution.

Teaching Expression Proteomics: From the Wet-Lab to the Laptop

ERIC Educational Resources Information Center

Teixeira, Miguel C.; Santos, Pedro M.; Rodrigues, Catarina; Sa-Correia, Isabel

2009-01-01

Expression proteomics has become, in recent years, a key genome-wide expression approach in fundamental and applied life sciences. This postgenomic technology aims the quantitative analysis of all the proteins or protein forms (the so-called proteome) of a given organism in a given environmental and genetic context. It is a challenge to provide…

Mapping of QTL associated with seed amino acids content in MD96-5722 by "Spencer" RIL population of soybean using SNP markers

USDA-ARS?s Scientific Manuscript database

Soybean seeds are major sources of essential amino acids, protein, and fatty acids. Limited information is available on the genetic analysis of amino acid composition in soybean. Therefore, the objective of this study was to identify genomic regions containing quantitative trait loci (QTL) controlli...

Genetic analysis of adult plant, quantitative resistance to stripe rust in wheat cultivar Stephens in multi-environment trials

USDA-ARS?s Scientific Manuscript database

The wheat (Triticum aestivum L.) cultivar ‘Stephens’ has been grown commercially in the USA Pacific Northwest for 30 years. The durable resistance of ‘Stephens’ to stripe rust (Puccinia striiformis f. sp. tritici) was believed to be due to a combination of seedling and adult plant resistance genes. ...

Multiple loci and genetic interactions involving flowering time genes regulate stem branching among natural variants of Arabidopsis.

PubMed

Huang, Xueqing; Ding, Jia; Effgen, Sigi; Turck, Franziska; Koornneef, Maarten

2013-08-01

Shoot branching is a major determinant of plant architecture. Genetic variants for reduced stem branching in the axils of cauline leaves of Arabidopsis were found in some natural accessions and also at low frequency in the progeny of multiparent crosses. Detailed genetic analysis using segregating populations derived from backcrosses with the parental lines and bulked segregant analysis was used to identify the allelic variation controlling reduced stem branching. Eight quantitative trait loci (QTLs) contributing to natural variation for reduced stem branching were identified (REDUCED STEM BRANCHING 1-8 (RSB1-8)). Genetic analysis showed that RSB6 and RSB7, corresponding to flowering time genes FLOWERING LOCUS C (FLC) and FRIGIDA (FRI), epistatically regulate stem branching. Furthermore, FLOWERING LOCUS T (FT), which corresponds to RSB8 as demonstrated by fine-mapping, transgenic complementation and expression analysis, caused pleiotropic effects not only on flowering time, but, in the specific background of active FRI and FLC alleles, also on the RSB trait. The consequence of allelic variation only expressed in late-flowering genotypes revealed novel and thus far unsuspected roles of several genes well characterized for their roles in flowering time control. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

LOD significance thresholds for QTL analysis in experimental populations of diploid species

PubMed

Van Ooijen JW

1999-11-01

Linkage analysis with molecular genetic markers is a very powerful tool in the biological research of quantitative traits. The lack of an easy way to know what areas of the genome can be designated as statistically significant for containing a gene affecting the quantitative trait of interest hampers the important prediction of the rate of false positives. In this paper four tables, obtained by large-scale simulations, are presented that can be used with a simple formula to get the false-positives rate for analyses of the standard types of experimental populations with diploid species with any size of genome. A new definition of the term 'suggestive linkage' is proposed that allows a more objective comparison of results across species.

Spinal sensory circuits in motion.

PubMed

Böhm, Urs Lucas; Wyart, Claire

2016-12-01

The role of sensory feedback in shaping locomotion has been long debated. Recent advances in genetics and behavior analysis revealed the importance of proprioceptive pathways in spinal circuits. The mechanisms underlying peripheral mechanosensation enabled to unravel the networks that feedback to spinal circuits in order to modulate locomotion. Sensory inputs to the vertebrate spinal cord were long thought to originate from the periphery. Recent studies challenge this view: GABAergic sensory neurons located within the spinal cord have been shown to relay mechanical and chemical information from the cerebrospinal fluid to motor circuits. Innovative approaches combining genetics, quantitative analysis of behavior and optogenetics now allow probing the contribution of these sensory feedback pathways to locomotion and recovery following spinal cord injury. Copyright © 2016 Elsevier Ltd. All rights reserved.

QuASAR: quantitative allele-specific analysis of reads.

PubMed

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

2015-04-15

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

Methodological Variables in the Analysis of Cell-Free DNA.

PubMed

Bronkhorst, Abel Jacobus; Aucamp, Janine; Pretorius, Piet J

2016-01-01

In recent years, cell-free DNA (cfDNA) analysis has received increasing amounts of attention as a potential non-invasive screening tool for the early detection of genetic aberrations and a wide variety of diseases, especially cancer. However, except for some prenatal tests and BEAMing, a technique used to detect mutations in various genes of cancer patients, cfDNA analysis is not yet routinely applied in clinical practice. Although some confusing biological factors inherent to the in vivo setting play a key part, it is becoming increasingly clear that this struggle is mainly due to the lack of an analytical consensus, especially as regards quantitative analyses of cfDNA. In order to use quantitative analysis of cfDNA with confidence, process optimization and standardization are crucial. In this work we aim to elucidate the most confounding variables of each preanalytical step that must be considered for process optimization and equivalence of procedures.

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.

Decay Of Bacterial Pathogens, Fecal Indicators, And Real-Time Quantitative PCR Genetic Markers In Manure-Amended Soils

EPA Science Inventory

This study examined persistence and decay of bacterial pathogens, fecal indicator bacteria (FIB), and emerging real-time quantitative PCR (qPCR) genetic markers for rapid detection of fecal pollution in manure-amended agricultural soils. Known concentrations of transformed green...

Filling the knowledge gap: Integrating quantitative genetics and genomics in graduate education and outreach

USDA-ARS?s Scientific Manuscript database

The genomics revolution provides vital tools to address global food security. Yet to be incorporated into livestock breeding, molecular techniques need to be integrated into a quantitative genetics framework. Within the U.S., with shrinking faculty numbers with the requisite skills, the capacity to ...

Decay Of Bacterial Pathogen, Fecal Indicators, And Real-Time Quantitative PCR Genetic Markers In Manure Amended Soils

EPA Science Inventory

This study examined persistence and decay of bacterial pathogens, fecal indicator bacteria, and emerging real-time quantitative PCR (qPCR) genetic markers for rapid detection of fecal pollution in manre-amended agricultural soils. Known concentrations of transformed green fluore...

Real-time quantitative polymerase chain reaction methods for four genetically modified maize varieties and maize DNA content in food.

PubMed

Brodmann, Peter D; Ilg, Evelyn C; Berthoud, Hélène; Herrmann, Andre

2002-01-01

Quantitative detection methods are needed for enforcement of the recently introduced labeling threshold for genetically modified organisms (GMOs) in food ingredients. This labeling threshold, which is set to 1% in the European Union and Switzerland, must be applied to all approved GMOs. Four different varieties of maize are approved in the European Union: the insect-resistant Bt176 maize (Maximizer), Btl 1 maize, Mon810 (YieldGard) maize, and the herbicide-tolerant T25 (Liberty Link) maize. Because the labeling must be considered individually for each ingredient, a quantitation system for the endogenous maize content is needed in addition to the GMO-specific detection systems. Quantitative real-time polymerase chain reaction detection methods were developed for the 4 approved genetically modified maize varieties and for an endogenous maize (invertase) gene system.

Genetic Changes Accompanying the Domestication of Pisum sativum: Is there a Common Genetic Basis to the ‘Domestication Syndrome’ for Legumes?

PubMed Central

Weeden, Norman F.

2007-01-01

Background and Aims The changes that occur during the domestication of crops such as maize and common bean appear to be controlled by relatively few genes. This study investigates the genetic basis of domestication in pea (Pisum sativum) and compares the genes involved with those determined to be important in common bean domestication. Methods Quantitative trait loci and classical genetic analysis are used to investigate and identify the genes modified at three stages of the domestication process. Five recombinant inbred populations involving crosses between different lines representing different stages are examined. Key Results A minimum of 15 known genes, in addition to a relatively few major quantitative trait loci, are identified as being critical to the domestication process. These genes control traits such as pod dehiscence, seed dormancy, seed size and other seed quality characters, stem height, root mass, and harvest index. Several of the genes have pleiotropic effects that in species possessing a more rudimentary genetic characterization might have been interpreted as clusters of genes. Very little evidence for gene clustering was found in pea. When compared with common bean, pea has used a different set of genes to produce the same or similar phenotypic changes. Conclusions Similar to results for common bean, relatively few genes appear to have been modified during the domestication of pea. However, the genes involved are different, and there does not appear to be a common genetic basis to ‘domestication syndrome’ in the Fabaceae. PMID:17660515

The influence of mutation, recombination, population history, and selection on patterns of genetic diversity in Neisseria meningitidis.

PubMed

Jolley, K A; Wilson, D J; Kriz, P; McVean, G; Maiden, M C J

2005-03-01

Patterns of genetic diversity within populations of human pathogens, shaped by the ecology of host-microbe interactions, contain important information about the epidemiological history of infectious disease. Exploiting this information, however, requires a systematic approach that distinguishes the genetic signal generated by epidemiological processes from the effects of other forces, such as recombination, mutation, and population history. Here, a variety of quantitative techniques were employed to investigate multilocus sequence information from isolate collections of Neisseria meningitidis, a major cause of meningitis and septicemia world wide. This allowed quantitative evaluation of alternative explanations for the observed population structure. A coalescent-based approach was employed to estimate the rate of mutation, the rate of recombination, and the size distribution of recombination fragments from samples from disease-associated and carried meningococci obtained in the Czech Republic in 1993 and a global collection of disease-associated isolates collected globally from 1937 to 1996. The parameter estimates were used to reject a model in which genetic structure arose by chance in small populations, and analysis of molecular variation showed that geographically restricted gene flow was unlikely to be the cause of the genetic structure. The genetic differentiation between disease and carriage isolate collections indicated that, whereas certain genotypes were overrepresented among the disease-isolate collections (the "hyperinvasive" lineages), disease-associated and carried meningococci exhibited remarkably little differentiation at the level of individual nucleotide polymorphisms. In combination, these results indicated the repeated action of natural selection on meningococcal populations, possibly arising from the coevolutionary dynamic of host-pathogen interactions.

Morphoagronomic characterization and genetic diversity of a common bean RIL mapping population derived from the cross Rudá x AND 277.

PubMed

Silva, L C; Batista, R O; Anjos, R S R; Souza, M H; Carneiro, P C S; Souza, T L P O; Barros, E G; Carneiro, J E S

2016-07-29

Recombinant inbred lines (RILs) are a valuable resource for building genetic linkage maps. The presence of genetic variability in the RILs is essential for detecting associations between molecular markers and loci controlling agronomic traits of interest. The main goal of this study was to quantify the genetic diversity of a common bean RIL population derived from a cross between Rudá (Mesoamerican gene pool) and AND 277 (Andean gene pool). This population was developed by the single seed descent method from 500 F2 plants until the F10 generation. Seven quantitative traits were evaluated in the field in 393 RILs, the parental lines, and five control cultivars. The plants were grown using a randomized block design with additional controls and three replicates. Significant differences were observed among the RILs for all evaluated traits (P < 0.01). A comparison of the RILs and parental lines showed significant differences (P < 0.01) for the number of days to flowering (DFL) and to harvest (DH), productivity (PROD) and mass of 100 beans (M100); however, there were no significant differences for plant architecture, degree of seed flatness, or seed shape. These results indicate the occurrence of additive x additive epistatic interactions for DFL, DH, PROD, and M100. The 393 RILs were shown to fall into 10 clusters using Tocher's method. This RIL population clearly contained genetic variability for the evaluated traits, and this variability will be crucial for future studies involving genetic mapping and quantitative trait locus identification and analysis.

FLIPPER, a combinatorial probe for correlated live imaging and electron microscopy, allows identification and quantitative analysis of various cells and organelles.

PubMed

Kuipers, Jeroen; van Ham, Tjakko J; Kalicharan, Ruby D; Veenstra-Algra, Anneke; Sjollema, Klaas A; Dijk, Freark; Schnell, Ulrike; Giepmans, Ben N G

2015-04-01

Ultrastructural examination of cells and tissues by electron microscopy (EM) yields detailed information on subcellular structures. However, EM is typically restricted to small fields of view at high magnification; this makes quantifying events in multiple large-area sample sections extremely difficult. Even when combining light microscopy (LM) with EM (correlated LM and EM: CLEM) to find areas of interest, the labeling of molecules is still a challenge. We present a new genetically encoded probe for CLEM, named "FLIPPER", which facilitates quantitative analysis of ultrastructural features in cells. FLIPPER consists of a fluorescent protein (cyan, green, orange, or red) for LM visualization, fused to a peroxidase allowing visualization of targets at the EM level. The use of FLIPPER is straightforward and because the module is completely genetically encoded, cells can be optimally prepared for EM examination. We use FLIPPER to quantify cellular morphology at the EM level in cells expressing a normal and disease-causing point-mutant cell-surface protein called EpCAM (epithelial cell adhesion molecule). The mutant protein is retained in the endoplasmic reticulum (ER) and could therefore alter ER function and morphology. To reveal possible ER alterations, cells were co-transfected with color-coded full-length or mutant EpCAM and a FLIPPER targeted to the ER. CLEM examination of the mixed cell population allowed color-based cell identification, followed by an unbiased quantitative analysis of the ER ultrastructure by EM. Thus, FLIPPER combines bright fluorescent proteins optimized for live imaging with high sensitivity for EM labeling, thereby representing a promising tool for CLEM.

Relative quantification in seed GMO analysis: state of art and bottlenecks.

PubMed

Chaouachi, Maher; Bérard, Aurélie; Saïd, Khaled

2013-06-01

Reliable quantitative methods are needed to comply with current EU regulations on the mandatory labeling of genetically modified organisms (GMOs) and GMO-derived food and feed products with a minimum GMO content of 0.9 %. The implementation of EU Commission Recommendation 2004/787/EC on technical guidance for sampling and detection which meant as a helpful tool for the practical implementation of EC Regulation 1830/2003, which states that "the results of quantitative analysis should be expressed as the number of target DNA sequences per target taxon specific sequences calculated in terms of haploid genomes". This has led to an intense debate on the type of calibrator best suitable for GMO quantification. The main question addressed in this review is whether reference materials and calibrators should be matrix based or whether pure DNA analytes should be used for relative quantification in GMO analysis. The state of the art, including the advantages and drawbacks, of using DNA plasmid (compared to genomic DNA reference materials) as calibrators, is widely described. In addition, the influence of the genetic structure of seeds on real-time PCR quantitative results obtained for seed lots is discussed. The specific composition of a seed kernel, the mode of inheritance, and the ploidy level ensure that there is discordance between a GMO % expressed as a haploid genome equivalent and a GMO % based on numbers of seeds. This means that a threshold fixed as a percentage of seeds cannot be used as such for RT-PCR. All critical points that affect the expression of the GMO content in seeds are discussed in this paper.

Influence of mom and dad: quantitative genetic models for maternal effects and genomic imprinting.

PubMed

Santure, Anna W; Spencer, Hamish G

2006-08-01

The expression of an imprinted gene is dependent on the sex of the parent it was inherited from, and as a result reciprocal heterozygotes may display different phenotypes. In contrast, maternal genetic terms arise when the phenotype of an offspring is influenced by the phenotype of its mother beyond the direct inheritance of alleles. Both maternal effects and imprinting may contribute to resemblance between offspring of the same mother. We demonstrate that two standard quantitative genetic models for deriving breeding values, population variances and covariances between relatives, are not equivalent when maternal genetic effects and imprinting are acting. Maternal and imprinting effects introduce both sex-dependent and generation-dependent effects that result in differences in the way additive and dominance effects are defined for the two approaches. We use a simple example to demonstrate that both imprinting and maternal genetic effects add extra terms to covariances between relatives and that model misspecification may over- or underestimate true covariances or lead to extremely variable parameter estimation. Thus, an understanding of various forms of parental effects is essential in correctly estimating quantitative genetic variance components.

Computational studies of novel chymase inhibitors against cardiovascular and allergic diseases: mechanism and inhibition.

PubMed

Arooj, Mahreen; Thangapandian, Sundarapandian; John, Shalini; Hwang, Swan; Park, Jong K; Lee, Keun W

2012-12-01

To provide a new idea for drug design, a computational investigation is performed on chymase and its novel 1,4-diazepane-2,5-diones inhibitors that explores the crucial molecular features contributing to binding specificity. Molecular docking studies of inhibitors within the active site of chymase were carried out to rationalize the inhibitory properties of these compounds and understand their inhibition mechanism. The density functional theory method was used to optimize molecular structures with the subsequent analysis of highest occupied molecular orbital, lowest unoccupied molecular orbital, and molecular electrostatic potential maps, which revealed that negative potentials near 1,4-diazepane-2,5-diones ring are essential for effective binding of inhibitors at active site of enzyme. The Bayesian model with receiver operating curve statistic of 0.82 also identified arylsulfonyl and aminocarbonyl as the molecular features favoring and not favoring inhibition of chymase, respectively. Moreover, genetic function approximation was applied to construct 3D quantitative structure-activity relationships models. Two models (genetic function approximation model 1 r(2) = 0.812 and genetic function approximation model 2 r(2) = 0.783) performed better in terms of correlation coefficients and cross-validation analysis. In general, this study is used as example to illustrate how combinational use of 2D/3D quantitative structure-activity relationships modeling techniques, molecular docking, frontier molecular orbital density fields (highest occupied molecular orbital and lowest unoccupied molecular orbital), and molecular electrostatic potential analysis may be useful to gain an insight into the binding mechanism between enzyme and its inhibitors. © 2012 John Wiley & Sons A/S.

designGG: an R-package and web tool for the optimal design of genetical genomics experiments.

PubMed

Li, Yang; Swertz, Morris A; Vera, Gonzalo; Fu, Jingyuan; Breitling, Rainer; Jansen, Ritsert C

2009-06-18

High-dimensional biomolecular profiling of genetically different individuals in one or more environmental conditions is an increasingly popular strategy for exploring the functioning of complex biological systems. The optimal design of such genetical genomics experiments in a cost-efficient and effective way is not trivial. This paper presents designGG, an R package for designing optimal genetical genomics experiments. A web implementation for designGG is available at http://gbic.biol.rug.nl/designGG. All software, including source code and documentation, is freely available. DesignGG allows users to intelligently select and allocate individuals to experimental units and conditions such as drug treatment. The user can maximize the power and resolution of detecting genetic, environmental and interaction effects in a genome-wide or local mode by giving more weight to genome regions of special interest, such as previously detected phenotypic quantitative trait loci. This will help to achieve high power and more accurate estimates of the effects of interesting factors, and thus yield a more reliable biological interpretation of data. DesignGG is applicable to linkage analysis of experimental crosses, e.g. recombinant inbred lines, as well as to association analysis of natural populations.

Genetic dissection of fruiting body-related traits using quantitative trait loci mapping in Lentinula edodes.

PubMed

Gong, Wen-Bing; Li, Lei; Zhou, Yan; Bian, Yin-Bing; Kwan, Hoi-Shan; Cheung, Man-Kit; Xiao, Yang

2016-06-01

To provide a better understanding of the genetic architecture of fruiting body formation of Lentinula edodes, quantitative trait loci (QTLs) mapping was employed to uncover the loci underlying seven fruiting body-related traits (FBRTs). An improved L. edodes genetic linkage map, comprising 572 markers on 12 linkage groups with a total map length of 983.7 cM, was constructed by integrating 82 genomic sequence-based insertion-deletion (InDel) markers into a previously published map. We then detected a total of 62 QTLs for seven target traits across two segregating testcross populations, with individual QTLs contributing 5.5 %-30.2 % of the phenotypic variation. Fifty-three out of the 62 QTLs were clustered in six QTL hotspots, suggesting the existence of main genomic regions regulating the morphological characteristics of fruiting bodies in L. edodes. A stable QTL hotspot on MLG2, containing QTLs for all investigated traits, was identified in both testcross populations. QTLs for related traits were frequently co-located on the linkage groups, demonstrating the genetic basis for phenotypic correlation of traits. Meta-QTL (mQTL) analysis was performed and identified 16 mQTLs with refined positions and narrow confidence intervals (CIs). Nine genes, including those encoding MAP kinase, blue-light photoreceptor, riboflavin-aldehyde-forming enzyme and cyclopropane-fatty-acyl-phospholipid synthase, and cytochrome P450s, were likely to be candidate genes controlling the shape of fruiting bodies. The study has improved our understanding of the genetic architecture of fruiting body formation in L. edodes. To our knowledge, this is the first genome-wide QTL detection of FBRTs in L. edodes. The improved genetic map, InDel markers and QTL hotspot regions revealed here will assist considerably in the conduct of future genetic and breeding studies of L. edodes.

[Morphologic and AFLP analysis of relationships between tulip species Tulipa biebersteiniana (Liliaceae)].

PubMed

Kutlunina, N A; Polezhaeva, M A; Permiakova, M V

2013-04-01

In populations of four species of tulips, (Tulipa biebersteiniana, T. patens, T. scytica and T. riparia) from the Volgograd, Kurgansk, Orenburg, and Chelyabinsk regions and the Republic of Bashkortostan, genetic diversity was studied by means of morphological and AFLP analysis. A morphological analysis of seven quantitative and two qualitative criteria was carried out. Three selective EcoRI/MseI primer pairs allowed one to genotype 81 individuals from 13 tulip populations with 87 loci. The low level of variability by AFLP loci were revealed in all species, including T. biebersteiniana (P = 20.41%, UH(e) = 0.075), T. patens (26.97%, 0.082), T. scytica (27.53%, 0.086), and T. riparia (27.72%, 0.096). According to the AMOVA results, the variability proportion that characterizes the differences between the four Tulip species was lower (F(CT) = 0.235) than between populations within species (F(ST) = 0.439). Tulipa patens is well differentiated by means of Nei's distances, coordination, and analysis in the STRUCTURE program. An analysis in the STRUCTURE revealed four genetic groups of tulips that are not completely in accordance with the analyzed species. This acknowledges the presence of complicated genetic process in the tulip population.

Proton Nuclear Magnetic Resonance-Spectroscopic Discrimination of Wines Reflects Genetic Homology of Several Different Grape (V. vinifera L.) Cultivars.

PubMed

Hu, Boran; Yue, Yaqing; Zhu, Yong; Wen, Wen; Zhang, Fengmin; Hardie, Jim W

2015-01-01

Proton nuclear magnetic resonance spectroscopy coupled multivariate analysis (1H NMR-PCA/PLS-DA) is an important tool for the discrimination of wine products. Although 1H NMR has been shown to discriminate wines of different cultivars, a grape genetic component of the discrimination has been inferred only from discrimination of cultivars of undefined genetic homology and in the presence of many confounding environmental factors. We aimed to confirm the influence of grape genotypes in the absence of those factors. We applied 1H NMR-PCA/PLS-DA and hierarchical cluster analysis (HCA) to wines from five, variously genetically-related grapevine (V. vinifera) cultivars; all grown similarly on the same site and vinified similarly. We also compared the semi-quantitative profiles of the discriminant metabolites of each cultivar with previously reported chemical analyses. The cultivars were clearly distinguishable and there was a general correlation between their grouping and their genetic homology as revealed by recent genomic studies. Between cultivars, the relative amounts of several of the cultivar-related discriminant metabolites conformed closely with reported chemical analyses. Differences in grape-derived metabolites associated with genetic differences alone are a major source of 1H NMR-based discrimination of wines and 1H NMR has the capacity to discriminate between very closely related cultivars. The study confirms that genetic variation among grape cultivars alone can account for the discrimination of wine by 1H NMR-PCA/PLS and indicates that 1H NMR spectra of wine of single grape cultivars may in future be used in tandem with hierarchical cluster analysis to elucidate genetic lineages and metabolomic relations of grapevine cultivars. In the absence of genetic information, for example, where predecessor varieties are no longer extant, this may be a particularly useful approach.

Simplex and duplex event-specific analytical methods for functional biotech maize.

PubMed

Lee, Seong-Hun; Kim, Su-Jeong; Yi, Bu-Young

2009-08-26

Analytical methods are very important in the control of genetically modified organism (GMO) labeling systems or living modified organism (LMO) management for biotech crops. Event-specific primers and probes were developed for qualitative and quantitative analysis for biotech maize event 3272 and LY 038 on the basis of the 3' flanking regions, respectively. The qualitative primers confirmed the specificity by a single PCR product and sensitivity to 0.05% as a limit of detection (LOD). Simplex and duplex quantitative methods were also developed using TaqMan real-time PCR. One synthetic plasmid was constructed from two taxon-specific DNA sequences of maize and two event-specific 3' flanking DNA sequences of event 3272 and LY 038 as reference molecules. In-house validation of the quantitative methods was performed using six levels of mixing samples, from 0.1 to 10.0%. As a result, the biases from the true value and the relative deviations were all within the range of +/-30%. Limits of quantitation (LOQs) of the quantitative methods were all 0.1% for simplex real-time PCRs of event 3272 and LY 038 and 0.5% for duplex real-time PCR of LY 038. This study reports that event-specific analytical methods were applicable for qualitative and quantitative analysis for biotech maize event 3272 and LY 038.

Genetic linkage map construction and QTL mapping of salt tolerance traits in Zoysiagrass (Zoysia japonica).

PubMed

Guo, Hailin; Ding, Wanwen; Chen, Jingbo; Chen, Xuan; Zheng, Yiqi; Wang, Zhiyong; Liu, Jianxiu

2014-01-01

Zoysiagrass (Zoysia Willd.) is an important warm season turfgrass that is grown in many parts of the world. Salt tolerance is an important trait in zoysiagrass breeding programs. In this study, a genetic linkage map was constructed using sequence-related amplified polymorphism markers and random amplified polymorphic DNA markers based on an F1 population comprising 120 progeny derived from a cross between Zoysia japonica Z105 (salt-tolerant accession) and Z061 (salt-sensitive accession). The linkage map covered 1211 cM with an average marker distance of 5.0 cM and contained 24 linkage groups with 242 marker loci (217 sequence-related amplified polymorphism markers and 25 random amplified polymorphic DNA markers). Quantitative trait loci affecting the salt tolerance of zoysiagrass were identified using the constructed genetic linkage map. Two significant quantitative trait loci (qLF-1 and qLF-2) for leaf firing percentage were detected; qLF-1 at 36.3 cM on linkage group LG4 with a logarithm of odds value of 3.27, which explained 13.1% of the total variation of leaf firing and qLF-2 at 42.3 cM on LG5 with a logarithm of odds value of 2.88, which explained 29.7% of the total variation of leaf firing. A significant quantitative trait locus (qSCW-1) for reduced percentage of dry shoot clipping weight was detected at 44.1 cM on LG5 with a logarithm of odds value of 4.0, which explained 65.6% of the total variation. This study provides important information for further functional analysis of salt-tolerance genes in zoysiagrass. Molecular markers linked with quantitative trait loci for salt tolerance will be useful in zoysiagrass breeding programs using marker-assisted selection.

Quantitative trait loci from the host genetic background modulate the durability of a resistance gene: a rational basis for sustainable resistance breeding in plants.

PubMed

Quenouille, J; Paulhiac, E; Moury, B; Palloix, A

2014-06-01

The combination of major resistance genes with quantitative resistance factors is hypothesized as a promising breeding strategy to preserve the durability of resistant cultivar, as recently observed in different pathosystems. Using the pepper (Capsicum annuum)/Potato virus Y (PVY, genus Potyvirus) pathosystem, we aimed at identifying plant genetic factors directly affecting the frequency of virus adaptation to the major resistance gene pvr2(3) and at comparing them with genetic factors affecting quantitative resistance. The resistance breakdown frequency was a highly heritable trait (h(2)=0.87). Four loci including additive quantitative trait loci (QTLs) and epistatic interactions explained together 70% of the variance of pvr2(3) breakdown frequency. Three of the four QTLs controlling pvr2(3) breakdown frequency were also involved in quantitative resistance, strongly suggesting that QTLs controlling quantitative resistance have a pleiotropic effect on the durability of the major resistance gene. With the first mapping of QTLs directly affecting resistance durability, this study provides a rationale for sustainable resistance breeding. Surprisingly, a genetic trade-off was observed between the durability of PVY resistance controlled by pvr2(3) and the spectrum of the resistance against different potyviruses. This trade-off seemed to have been resolved by the combination of minor-effect durability QTLs under long-term farmer selection.

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.

Quantitative trait loci mapping of the mouse plasma proteome (pQTL).

PubMed

Holdt, Lesca M; von Delft, Annette; Nicolaou, Alexandros; Baumann, Sven; Kostrzewa, Markus; Thiery, Joachim; Teupser, Daniel

2013-02-01

A current challenge in the era of genome-wide studies is to determine the responsible genes and mechanisms underlying newly identified loci. Screening of the plasma proteome by high-throughput mass spectrometry (MALDI-TOF MS) is considered a promising approach for identification of metabolic and disease processes. Therefore, plasma proteome screening might be particularly useful for identifying responsible genes when combined with analysis of variation in the genome. Here, we describe a proteomic quantitative trait locus (pQTL) study of plasma proteome screens in an F(2) intercross of 455 mice mapped with 177 genetic markers across the genome. A total of 69 of 176 peptides revealed significant LOD scores (≥5.35) demonstrating strong genetic regulation of distinct components of the plasma proteome. Analyses were confirmed by mechanistic studies and MALDI-TOF/TOF, liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses of the two strongest pQTLs: A pQTL for mass-to-charge ratio (m/z) 3494 (LOD 24.9, D11Mit151) was identified as the N-terminal 35 amino acids of hemoglobin subunit A (Hba) and caused by genetic variation in Hba. Another pQTL for m/z 8713 (LOD 36.4; D1Mit111) was caused by variation in apolipoprotein A2 (Apoa2) and cosegregated with HDL cholesterol. Taken together, we show that genome-wide plasma proteome profiling in combination with genome-wide genetic screening aids in the identification of causal genetic variants affecting abundance of plasma proteins.

Quantitative Trait Loci Mapping of the Mouse Plasma Proteome (pQTL)

PubMed Central

Holdt, Lesca M.; von Delft, Annette; Nicolaou, Alexandros; Baumann, Sven; Kostrzewa, Markus; Thiery, Joachim; Teupser, Daniel

2013-01-01

A current challenge in the era of genome-wide studies is to determine the responsible genes and mechanisms underlying newly identified loci. Screening of the plasma proteome by high-throughput mass spectrometry (MALDI-TOF MS) is considered a promising approach for identification of metabolic and disease processes. Therefore, plasma proteome screening might be particularly useful for identifying responsible genes when combined with analysis of variation in the genome. Here, we describe a proteomic quantitative trait locus (pQTL) study of plasma proteome screens in an F2 intercross of 455 mice mapped with 177 genetic markers across the genome. A total of 69 of 176 peptides revealed significant LOD scores (≥5.35) demonstrating strong genetic regulation of distinct components of the plasma proteome. Analyses were confirmed by mechanistic studies and MALDI-TOF/TOF, liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses of the two strongest pQTLs: A pQTL for mass-to-charge ratio (m/z) 3494 (LOD 24.9, D11Mit151) was identified as the N-terminal 35 amino acids of hemoglobin subunit A (Hba) and caused by genetic variation in Hba. Another pQTL for m/z 8713 (LOD 36.4; D1Mit111) was caused by variation in apolipoprotein A2 (Apoa2) and cosegregated with HDL cholesterol. Taken together, we show that genome-wide plasma proteome profiling in combination with genome-wide genetic screening aids in the identification of causal genetic variants affecting abundance of plasma proteins. PMID:23172855

On the reconciliation of missing heritability for genome-wide association studies

PubMed Central

Chen, Guo-Bo

2016-01-01

The definition of heritability has been unique and clear, but its estimation and estimates vary across studies. Linear mixed model (LMM) and Haseman–Elston (HE) regression analyses are commonly used for estimating heritability from genome-wide association data. This study provides an analytical resolution that can be used to reconcile the differences between LMM and HE in the estimation of heritability given the genetic architecture, which is responsible for these differences. The genetic architecture was classified into three forms via thought experiments: (i) coupling genetic architecture that the quantitative trait loci (QTLs) in the linkage disequilibrium (LD) had a positive covariance; (ii) repulsion genetic architecture that the QTLs in the LD had a negative covariance; (iii) and neutral genetic architecture that the QTLs in the LD had a covariance with a summation of zero. The neutral genetic architecture is so far most embraced, whereas the coupling and the repulsion genetic architecture have not been well investigated. For a quantitative trait under the coupling genetic architecture, HE overestimated the heritability and LMM underestimated the heritability; under the repulsion genetic architecture, HE underestimated but LMM overestimated the heritability for a quantitative trait. These two methods gave identical results under the neutral genetic architecture. A general analytical result for the statistic estimated under HE is given regardless of genetic architecture. In contrast, the performance of LMM remained elusive, such as further depended on the ratio between the sample size and the number of markers, but LMM converged to HE with increased sample size. PMID:27436266

Genetic Determinants of Thrombin Generation and Their Relation to Venous Thrombosis: Results from the GAIT-2 Project

PubMed Central

Martin-Fernandez, Laura; Ziyatdinov, Andrey; Carrasco, Marina; Millon, Juan Antonio; Martinez-Perez, Angel; Vilalta, Noelia; Brunel, Helena; Font, Montserrat; Hamsten, Anders; Souto, Juan Carlos; Soria, José Manuel

2016-01-01

Background Venous thromboembolism (VTE) is a common disease where known genetic risk factors explain only a small portion of the genetic variance. Then, the analysis of intermediate phenotypes, such as thrombin generation assay, can be used to identify novel genetic risk factors that contribute to VTE. Objectives To investigate the genetic basis of distinct quantitative phenotypes of thrombin generation and its relationship to the risk of VTE. Patients/Methods Lag time, thrombin peak and endogenous thrombin potential (ETP) were measured in the families of the Genetic Analysis of Idiopathic Thrombophilia 2 (GAIT-2) Project. This sample consisted of 935 individuals in 35 extended families selected through a proband with idiopathic thrombophilia. We performed also genome wide association studies (GWAS) with thrombin generation phenotypes. Results The results showed that 67% of the variation in the risk of VTE is attributable to genetic factors. The heritabilities of lag time, thrombin peak and ETP were 49%, 54% and 52%, respectively. More importantly, we demonstrated also the existence of positive genetic correlations between thrombin peak or ETP and the risk of VTE. Moreover, the major genetic determinant of thrombin generation was the F2 gene. However, other suggestive signals were observed. Conclusions The thrombin generation phenotypes are strongly genetically determined. The thrombin peak and ETP are significantly genetically correlated with the risk of VTE. In addition, F2 was identified as a major determinant of thrombin generation. We reported suggestive signals that might increase our knowledge to explain the variability of this important phenotype. Validation and functional studies are required to confirm GWAS results. PMID:26784699

Nonlinear Analysis of Time Series in Genome-Wide Linkage Disequilibrium Data

NASA Astrophysics Data System (ADS)

Hernández-Lemus, Enrique; Estrada-Gil, Jesús K.; Silva-Zolezzi, Irma; Fernández-López, J. Carlos; Hidalgo-Miranda, Alfredo; Jiménez-Sánchez, Gerardo

2008-02-01

The statistical study of large scale genomic data has turned out to be a very important tool in population genetics. Quantitative methods are essential to understand and implement association studies in the biomedical and health sciences. Nevertheless, the characterization of recently admixed populations has been an elusive problem due to the presence of a number of complex phenomena. For example, linkage disequilibrium structures are thought to be more complex than their non-recently admixed population counterparts, presenting the so-called ancestry blocks, admixed regions that are not yet smoothed by the effect of genetic recombination. In order to distinguish characteristic features for various populations we have implemented several methods, some of them borrowed or adapted from the analysis of nonlinear time series in statistical physics and quantitative physiology. We calculate the main fractal dimensions (Kolmogorov's capacity, information dimension and correlation dimension, usually named, D0, D1 and D2). We also have made detrended fluctuation analysis and information based similarity index calculations for the probability distribution of correlations of linkage disequilibrium coefficient of six recently admixed (mestizo) populations within the Mexican Genome Diversity Project [1] and for the non-recently admixed populations in the International HapMap Project [2]. Nonlinear correlations showed up as a consequence of internal structure within the haplotype distributions. The analysis of these correlations as well as the scope and limitations of these procedures within the biomedical sciences are discussed.

TheCellMap.org: A Web-Accessible Database for Visualizing and Mining the Global Yeast Genetic Interaction Network

PubMed Central

Usaj, Matej; Tan, Yizhao; Wang, Wen; VanderSluis, Benjamin; Zou, Albert; Myers, Chad L.; Costanzo, Michael; Andrews, Brenda; Boone, Charles

2017-01-01

Providing access to quantitative genomic data is key to ensure large-scale data validation and promote new discoveries. TheCellMap.org serves as a central repository for storing and analyzing quantitative genetic interaction data produced by genome-scale Synthetic Genetic Array (SGA) experiments with the budding yeast Saccharomyces cerevisiae. In particular, TheCellMap.org allows users to easily access, visualize, explore, and functionally annotate genetic interactions, or to extract and reorganize subnetworks, using data-driven network layouts in an intuitive and interactive manner. PMID:28325812

TheCellMap.org: A Web-Accessible Database for Visualizing and Mining the Global Yeast Genetic Interaction Network.

PubMed

Usaj, Matej; Tan, Yizhao; Wang, Wen; VanderSluis, Benjamin; Zou, Albert; Myers, Chad L; Costanzo, Michael; Andrews, Brenda; Boone, Charles

2017-05-05

Providing access to quantitative genomic data is key to ensure large-scale data validation and promote new discoveries. TheCellMap.org serves as a central repository for storing and analyzing quantitative genetic interaction data produced by genome-scale Synthetic Genetic Array (SGA) experiments with the budding yeast Saccharomyces cerevisiae In particular, TheCellMap.org allows users to easily access, visualize, explore, and functionally annotate genetic interactions, or to extract and reorganize subnetworks, using data-driven network layouts in an intuitive and interactive manner. Copyright © 2017 Usaj et al.

Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: A pilot project of the ENIGMA–DTI working group

PubMed Central

Jahanshad, Neda; Kochunov, Peter; Sprooten, Emma; Mandl, René C.; Nichols, Thomas E.; Almassy, Laura; Blangero, John; Brouwer, Rachel M.; Curran, Joanne E.; de Zubicaray, Greig I.; Duggirala, Ravi; Fox, Peter T.; Hong, L. Elliot; Landman, Bennett A.; Martin, Nicholas G.; McMahon, Katie L.; Medland, Sarah E.; Mitchell, Braxton D.; Olvera, Rene L.; Peterson, Charles P.; Starr, John M.; Sussmann, Jessika E.; Toga, Arthur W.; Wardlaw, Joanna M.; Wright, Margaret J.; Hulshoff Pol, Hilleke E.; Bastin, Mark E.; McIntosh, Andrew M.; Deary, Ian J.; Thompson, Paul M.; Glahn, David C.

2013-01-01

The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA–DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18–85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/). PMID:23629049

An integrated genetic map based on four mapping populations and quantitative trait loci associated with economically important traits in watermelon (Citrullus lanatus)

PubMed Central

2014-01-01

Background Modern watermelon (Citrullus lanatus L.) cultivars share a narrow genetic base due to many years of selection for desirable horticultural qualities. Wild subspecies within C. lanatus are important potential sources of novel alleles for watermelon breeding, but successful trait introgression into elite cultivars has had limited success. The application of marker assisted selection (MAS) in watermelon is yet to be realized, mainly due to the past lack of high quality genetic maps. Recently, a number of useful maps have become available, however these maps have few common markers, and were constructed using different marker sets, thus, making integration and comparative analysis among maps difficult. The objective of this research was to use single-nucleotide polymorphism (SNP) anchor markers to construct an integrated genetic map for C. lanatus. Results Under the framework of the high density genetic map, an integrated genetic map was constructed by merging data from four independent mapping experiments using a genetically diverse array of parental lines, which included three subspecies of watermelon. The 698 simple sequence repeat (SSR), 219 insertion-deletion (InDel), 36 structure variation (SV) and 386 SNP markers from the four maps were used to construct an integrated map. This integrated map contained 1339 markers, spanning 798 cM with an average marker interval of 0.6 cM. Fifty-eight previously reported quantitative trait loci (QTL) for 12 traits in these populations were also integrated into the map. In addition, new QTL identified for brix, fructose, glucose and sucrose were added. Some QTL associated with economically important traits detected in different genetic backgrounds mapped to similar genomic regions of the integrated map, suggesting that such QTL are responsible for the phenotypic variability observed in a broad array of watermelon germplasm. Conclusions The integrated map described herein enhances the utility of genomic tools over previous watermelon genetic maps. A large proportion of the markers in the integrated map are SSRs, InDels and SNPs, which are easily transferable across laboratories. Moreover, the populations used to construct the integrated map include all three watermelon subspecies, making this integrated map useful for the selection of breeding traits, identification of QTL, MAS, analysis of germplasm and commercial hybrid seed detection. PMID:24443961

Cross-Population Joint Analysis of eQTLs: Fine Mapping and Functional Annotation

PubMed Central

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

2015-01-01

Mapping expression quantitative trait loci (eQTLs) has been shown as a powerful tool to uncover the genetic underpinnings of many complex traits at molecular level. In this paper, we present an integrative analysis approach that leverages eQTL data collected from multiple population groups. In particular, our approach effectively identifies multiple independent cis-eQTL signals that are consistent across populations, accounting for population heterogeneity in allele frequencies and linkage disequilibrium patterns. Furthermore, by integrating genomic annotations, our analysis framework enables high-resolution functional analysis of eQTLs. We applied our statistical approach to analyze the GEUVADIS data consisting of samples from five population groups. From this analysis, we concluded that i) jointly analysis across population groups greatly improves the power of eQTL discovery and the resolution of fine mapping of causal eQTL ii) many genes harbor multiple independent eQTLs in their cis regions iii) genetic variants that disrupt transcription factor binding are significantly enriched in eQTLs (p-value = 4.93 × 10-22). PMID:25906321

Diversity in ATP concentrations in a single bacterial cell population revealed by quantitative single-cell imaging

PubMed Central

Yaginuma, Hideyuki; Kawai, Shinnosuke; Tabata, Kazuhito V.; Tomiyama, Keisuke; Kakizuka, Akira; Komatsuzaki, Tamiki; Noji, Hiroyuki; Imamura, Hiromi

2014-01-01

Recent advances in quantitative single-cell analysis revealed large diversity in gene expression levels between individual cells, which could affect the physiology and/or fate of each cell. In contrast, for most metabolites, the concentrations were only measureable as ensemble averages of many cells. In living cells, adenosine triphosphate (ATP) is a critically important metabolite that powers many intracellular reactions. Quantitative measurement of the absolute ATP concentration in individual cells has not been achieved because of the lack of reliable methods. In this study, we developed a new genetically-encoded ratiometric fluorescent ATP indicator “QUEEN”, which is composed of a single circularly-permuted fluorescent protein and a bacterial ATP binding protein. Unlike previous FRET-based indicators, QUEEN was apparently insensitive to bacteria growth rate changes. Importantly, intracellular ATP concentrations of numbers of bacterial cells calculated from QUEEN fluorescence were almost equal to those from firefly luciferase assay. Thus, QUEEN is suitable for quantifying the absolute ATP concentration inside bacteria cells. Finally, we found that, even for a genetically-identical Escherichia coli cell population, absolute concentrations of intracellular ATP were significantly diverse between individual cells from the same culture, by imaging QUEEN signals from single cells. PMID:25283467

Preferential access to genetic information from endogenous hominin ancient DNA and accurate quantitative SNP-typing via SPEX

PubMed Central

Brotherton, Paul; Sanchez, Juan J.; Cooper, Alan; Endicott, Phillip

2010-01-01

The analysis of targeted genetic loci from ancient, forensic and clinical samples is usually built upon polymerase chain reaction (PCR)-generated sequence data. However, many studies have shown that PCR amplification from poor-quality DNA templates can create sequence artefacts at significant levels. With hominin (human and other hominid) samples, the pervasive presence of highly PCR-amplifiable human DNA contaminants in the vast majority of samples can lead to the creation of recombinant hybrids and other non-authentic artefacts. The resulting PCR-generated sequences can then be difficult, if not impossible, to authenticate. In contrast, single primer extension (SPEX)-based approaches can genotype single nucleotide polymorphisms from ancient fragments of DNA as accurately as modern DNA. A single SPEX-type assay can amplify just one of the duplex DNA strands at target loci and generate a multi-fold depth-of-coverage, with non-authentic recombinant hybrids reduced to undetectable levels. Crucially, SPEX-type approaches can preferentially access genetic information from damaged and degraded endogenous ancient DNA templates over modern human DNA contaminants. The development of SPEX-type assays offers the potential for highly accurate, quantitative genotyping from ancient hominin samples. PMID:19864251

Inbreeding Depression and Male Survivorship in Drosophila: Implications for Senescence Theory

PubMed Central

Swindell, William R.; Bouzat, Juan L.

2006-01-01

The extent to which inbreeding depression affects longevity and patterns of survivorship is an important issue from several research perspectives, including evolutionary biology, conservation biology, and the genetic analysis of quantitative traits. However, few previous inbreeding depression studies have considered longevity as a focal life-history trait. We maintained laboratory populations of Drosophila melanogaster at census population sizes of 2 and 10 male-female pairs for up to 66 generations and performed repeated assays of male survivorship throughout this time period. On average, significant levels of inbreeding depression were observed for median life span and age-specific mortality. For age-specific mortality, the severity of inbreeding depression increased over the life span. We found that a baseline inbreeding load of 0.307 lethal equivalents per gamete affected age-specific mortality, and that this value increased at a rate of 0.046 per day of the life span. With respect to some survivorship parameters, the differentiation of lineages was nonlinear with respect to the inbreeding coefficient, which suggested that nonadditive genetic variation contributed to variation among lineages. These findings provide insights into the genetic basis of longevity as a quantitative trait and have implications regarding the mutation-accumulation evolutionary explanation of senescence. PMID:16204222

HpQTL: a geometric morphometric platform to compute the genetic architecture of heterophylly.

PubMed

Sun, Lidan; Wang, Jing; Zhu, Xuli; Jiang, Libo; Gosik, Kirk; Sang, Mengmeng; Sun, Fengsuo; Cheng, Tangren; Zhang, Qixiang; Wu, Rongling

2017-02-15

Heterophylly, i.e. morphological changes in leaves along the axis of an individual plant, is regarded as a strategy used by plants to cope with environmental change. However, little is known of the extent to which heterophylly is controlled by genes and how each underlying gene exerts its effect on heterophyllous variation. We described a geometric morphometric model that can quantify heterophylly in plants and further constructed an R-based computing platform by integrating this model into a genetic mapping and association setting. The platform, named HpQTL, allows specific quantitative trait loci mediating heterophyllous variation to be mapped throughout the genome. The statistical properties of HpQTL were examined and validated via computer simulation. Its biological relevance was demonstrated by results from a real data analysis of heterophylly in a wood plant, mei (Prunus mume). HpQTL provides a powerful tool to analyze heterophylly and its underlying genetic architecture in a quantitative manner. It also contributes a new approach for genome-wide association studies aimed to dissect the programmed regulation of plant development and evolution. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A note on the efficiencies of sampling strategies in two-stage Bayesian regional fine mapping of a quantitative trait.

PubMed

Chen, Zhijian; Craiu, Radu V; Bull, Shelley B

2014-11-01

In focused studies designed to follow up associations detected in a genome-wide association study (GWAS), investigators can proceed to fine-map a genomic region by targeted sequencing or dense genotyping of all variants in the region, aiming to identify a functional sequence variant. For the analysis of a quantitative trait, we consider a Bayesian approach to fine-mapping study design that incorporates stratification according to a promising GWAS tag SNP in the same region. Improved cost-efficiency can be achieved when the fine-mapping phase incorporates a two-stage design, with identification of a smaller set of more promising variants in a subsample taken in stage 1, followed by their evaluation in an independent stage 2 subsample. To avoid the potential negative impact of genetic model misspecification on inference we incorporate genetic model selection based on posterior probabilities for each competing model. Our simulation study shows that, compared to simple random sampling that ignores genetic information from GWAS, tag-SNP-based stratified sample allocation methods reduce the number of variants continuing to stage 2 and are more likely to promote the functional sequence variant into confirmation studies. © 2014 WILEY PERIODICALS, INC.

Heritable influences on behavioural problems from early childhood to mid-adolescence: evidence for genetic stability and innovation.

PubMed

Lewis, G J; Plomin, R

2015-07-01

Although behavioural problems (e.g., anxiety, conduct, hyperactivity, peer problems) are known to be heritable both in early childhood and in adolescence, limited work has examined prediction across these ages, and none using a genetically informative sample. We examined, first, whether parental ratings of behavioural problems (indexed by the Strengths and Difficulties questionnaire) at ages 4, 7, 9, 12, and 16 years were stable across these ages. Second, we examined the extent to which stability reflected genetic or environmental effects through multivariate quantitative genetic analysis on data from a large (n > 3000) population (UK) sample of monozygotic and dizygotic twins. Behavioural problems in early childhood (age 4 years) showed significant associations with the corresponding behavioural problem at all subsequent ages. Moreover, stable genetic influences were observed across ages, indicating that biological bases underlying behavioural problems in adolescence are underpinned by genetic influences expressed as early as age 4 years. However, genetic and environmental innovations were also observed at each age. These observations indicate that genetic factors are important for understanding stable individual differences in behavioural problems across childhood and adolescence, although novel genetic influences also facilitate change in such behaviours.

The historical role of species from the Solanaceae plant family in genetic research.

PubMed

Gebhardt, Christiane

2016-12-01

This article evaluates the main contributions of tomato, tobacco, petunia, potato, pepper and eggplant to classical and molecular plant genetics and genomics since the beginning of the twentieth century. Species from the Solanaceae family form integral parts of human civilizations as food sources and drugs since thousands of years, and, more recently, as ornamentals. Some Solanaceous species were subjects of classical and molecular genetic research over the last 100 years. The tomato was one of the principal models in twentieth century classical genetics and a pacemaker of genome analysis in plants including molecular linkage maps, positional cloning of disease resistance genes and quantitative trait loci (QTL). Besides that, tomato is the model for the genetics of fruit development and composition. Tobacco was the major model used to establish the principals and methods of plant somatic cell genetics including in vitro propagation of cells and tissues, totipotency of somatic cells, doubled haploid production and genetic transformation. Petunia was a model for elucidating the biochemical and genetic basis of flower color and development. The cultivated potato is the economically most important Solanaceous plant and ranks third after wheat and rice as one of the world's great food crops. Potato is the model for studying the genetic basis of tuber development. Molecular genetics and genomics of potato, in particular association genetics, made valuable contributions to the genetic dissection of complex agronomic traits and the development of diagnostic markers for breeding applications. Pepper and eggplant are horticultural crops of worldwide relevance. Genetic and genomic research in pepper and eggplant mostly followed the tomato model. Comparative genome analysis of tomato, potato, pepper and eggplant contributed to the understanding of plant genome evolution.

Introduction to focus issue: quantitative approaches to genetic networks.

PubMed

Albert, Réka; Collins, James J; Glass, Leon

2013-06-01

All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks using field-programmable gate arrays. Mathematical analyses will be essential for understanding naturally occurring genetic networks in diverse organisms and for providing a foundation for the improved development of synthetic genetic networks.

Introduction to Focus Issue: Quantitative Approaches to Genetic Networks

NASA Astrophysics Data System (ADS)

Albert, Réka; Collins, James J.; Glass, Leon

2013-06-01

All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks using field-programmable gate arrays. Mathematical analyses will be essential for understanding naturally occurring genetic networks in diverse organisms and for providing a foundation for the improved development of synthetic genetic networks.

Clarifying sub-genomic positions of QTLs for flowering habit and fruit quality in U.S. strawberry (Fragaria ×ananassa) breeding populations using pedigree-based QTL analysis

USDA-ARS?s Scientific Manuscript database

Strawberry (Fragaria ×ananassa) is consumed worldwide for its flavor and nutritional health benefits. Several quantitative trait loci (QTL) were detected in the last two decades for fruit quality and flowering traits using low-density genetic maps. Recent discoveries in allo-octoploid strawberry gen...

Comparative Studies of Blacks and Whites in the United States. Quantitative Studies in Social Relations Series.

ERIC Educational Resources Information Center

Miller, Kent S., Ed.; Dreger, Ralph Mason, Ed.

The contents of this book are organized in seventeen chapters, as follows: (1) "Perspective and Overview," K. S. Miller and R. M. Dreger; (2) "Racial Experimenter Effects," J. M. Sattler; (3) "Behavior-genetic Analysis and its Biosocial Consequences," J. Hirsch; (4) Biological Substrata," R. M. Malina; (5) "Language Abilities of Black Americans,"…

Quantitative genetics of disease traits.

PubMed

Wray, N R; Visscher, P M

2015-04-01

John James authored two key papers on the theory of risk to relatives for binary disease traits and the relationship between parameters on the observed binary scale and an unobserved scale of liability (James Annals of Human Genetics, 1971; 35: 47; Reich, James and Morris Annals of Human Genetics, 1972; 36: 163). These two papers are John James' most cited papers (198 and 328 citations, November 2014). They have been influential in human genetics and have recently gained renewed popularity because of their relevance to the estimation of quantitative genetics parameters for disease traits using SNP data. In this review, we summarize the two early papers and put them into context. We show recent extensions of the theory for ascertained case-control data and review recent applications in human genetics. © 2015 Blackwell Verlag GmbH.

Two quantitative trait loci influence whipworm (Trichuris trichiura) infection in a Nepalese population.

PubMed

Williams-Blangero, Sarah; Vandeberg, John L; Subedi, Janardan; Jha, Bharat; Dyer, Tom D; Blangero, John

2008-04-15

Whipworm (Trichuris trichiura) infection is a soil-transmitted helminth infection that affects >1 billion people. It is a serious public health problem in many developing countries and can result in deficits in growth and cognitive development. In a follow-up study of significant heritability for whipworm infection, we conducted the first genome scan for quantitative trait loci (QTL) influencing the heritability of susceptibility to this important parasitic disease. Whipworm egg counts were determined for 1,253 members of the Jirel population of eastern Nepal. All individuals in the study sample belonged to a single pedigree including >26,000 pairs of relatives that are informative for genetic analysis. Linkage analysis of genome scan data generated for the pedigree provided unambiguous evidence for 2 QTL influencing susceptibility to whipworm infection, one located on chromosome 9 (logarithm of the odds ratio [LOD] score, 3.35; genomewide P = .0138) and the other located on chromosome 18 (LOD score, 3.29; genomewide P = .0159). There was also suggestive evidence that 2 loci located on chromosomes 12 and 13 influenced whipworm infection. The results of this first genome scan for T. trichiura egg counts provides new information on the determinants of genetic predisposition to whipworm infection.

Laboratory evolution of the migratory polymorphism in the sand cricket: combining physiology with quantitative genetics.

PubMed

Roff, Derek A; Fairbairn, Daphne J

2007-01-01

Predicting evolutionary change is the central goal of evolutionary biology because it is the primary means by which we can test evolutionary hypotheses. In this article, we analyze the pattern of evolutionary change in a laboratory population of the wing-dimorphic sand cricket Gryllus firmus resulting from relaxation of selection favoring the migratory (long-winged) morph. Based on a well-characterized trade-off between fecundity and flight capability, we predict that evolution in the laboratory environment should result in a reduction in the proportion of long-winged morphs. We also predict increased fecundity and reduced functionality and weight of the major flight muscles in long-winged females but little change in short-winged (flightless) females. Based on quantitative genetic theory, we predict that the regression equation describing the trade-off between ovary weight and weight of the major flight muscles will show a change in its intercept but not in its slope. Comparisons across generations verify all of these predictions. Further, using values of genetic parameters estimated from previous studies, we show that a quantitative genetic simulation model can account for not only the qualitative changes but also the evolutionary trajectory. These results demonstrate the power of combining quantitative genetic and physiological approaches for understanding the evolution of complex traits.

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.

Behavioral and molecular studies of quantitative differences in hygienic behavior in honeybees.

PubMed

Gempe, Tanja; Stach, Silke; Bienefeld, Kaspar; Otte, Marianne; Beye, Martin

2016-10-21

Hygienic behavior (HB) enables honeybees to tolerate parasites, including infection with the parasitic mite Varroa destructor, and it is a well-known example of a quantitative genetic trait. The understanding of the molecular processes underpinning the quantitative differences in this behavior remains limited. We performed gene expression studies in worker bees that displayed quantitative genetic differences in HB. We established a high and low genetic source of HB performance and studied the engagements into HB of single worker bees under the same environmental conditions. We found that the percentage of worker bees that engaged in a hygienic behavioral task tripled in the high versus low HB sources, thus suggesting that genetic differences may mediate differences in stimulated states to perform HB. We found 501 differently expressed genes (DEGs) in the brains of hygienic and non-hygienic performing workers in the high HB source bees, and 342 DEGs in the brains of hygienic performing worker bees, relative to the gene expression in non-hygienic worker bees from the low HB source group. "Cell surface receptor ligand signal transduction" in the high and "negative regulation of cell communication" in the low HB source were overrepresented molecular processes, suggesting that these molecular processes in the brain may play a role in the regulation of quantitative differences in HB. Moreover, only 21 HB-associated DEGs were common between the high and low HB sources. The better HB colony performance is primarily achieved by a high number of bees engaging in the hygienic tasks that associate with distinct molecular processes in the brain. We propose that different gene products and pathways may mediate the quantitative genetic differences of HB.

Mapping X-Disease Phytoplasma Resistance in Prunus virginiana.

PubMed

Lenz, Ryan R; Dai, Wenhao

2017-01-01

Phytoplasmas such as " Candidatus Phytoplasma pruni," the causal agent of X-disease of stone fruits, lack detailed biological analysis. This has limited the understanding of plant resistance mechanisms. Chokecherry ( Prunus virginiana L.) is a promising model to be used for the plant-phytoplasma interaction due to its documented ability to resist X-disease infection. A consensus chokecherry genetic map "Cho" was developed with JoinMap 4.0 by joining two parental maps. The new map contains a complete set of 16 linkage groups, spanning a genetic distance of 2,172 cM with an average marker density of 3.97 cM. Three significant quantitative trait loci (QTL) associated with X-disease resistance were identified contributing to a total of 45.9% of the phenotypic variation. This updated genetic linkage map and the identified QTL will provide the framework needed to facilitate molecular genetics, genomics, breeding, and biotechnology research concerning X-disease in chokecherry and other Prunus species.

First application of a microsphere-based immunoassay to the detection of genetically modified organisms (GMOs): quantification of Cry1Ab protein in genetically modified maize.

PubMed

Fantozzi, Anna; Ermolli, Monica; Marini, Massimiliano; Scotti, Domenico; Balla, Branko; Querci, Maddalena; Langrell, Stephen R H; Van den Eede, Guy

2007-02-21

An innovative covalent microsphere immunoassay, based on the usage of fluorescent beads coupled to a specific antibody, was developed for the quantification of the endotoxin Cry1Ab present in MON810 and Bt11 genetically modified (GM) maize lines. In particular, a specific protocol was developed to assess the presence of Cry1Ab in a very broad range of GM maize concentrations, from 0.1 to 100% [weight of genetically modified organism (GMO)/weight]. Test linearity was achieved in the range of values from 0.1 to 3%, whereas fluorescence signal increased following a nonlinear model, reaching a plateau at 25%. The limits of detection and quantification were equal to 0.018 and 0.054%, respectively. The present study describes the first application of quantitative high-throughput immunoassays in GMO analysis.

A cis-phase interaction study of genetic variants within the MAOA gene in major depressive disorder.

PubMed

Zhang, JieXu; Chen, YanBo; Zhang, KeRang; Yang, Hong; Sun, Yan; Fang, Yue; Shen, Yan; Xu, Qi

2010-11-01

The genetic basis of major depressive disorder (MDD) has been explored extensively, but the mode of transmission of the disease has yet to be established. To better understand the mechanism by which the monoamine oxidase A (MAOA) gene may play a role in developing MDD, the present work examined the cis-phase interaction between genetic variants within the MAOA gene for the pathogenesis of MDD. A variable number tandem repeat (VNTR) and 19 single nucleotide polymorphisms (SNPs) within the gene were genotyped in 512 unrelated patients with MDD and 567 unrelated control subjects among a Chinese population. Quantitative real-time polymerase chain reaction analysis was applied to test the effect of genetic variants on expression of the MAOA gene in MDD. Neither the VNTR polymorphism nor seven informative SNPs showed allelic association with MDD, but the cis-acting interactions between the VNTR polymorphism and four individual SNPs were strongly associated with MDD risk, of which the VNTR-rs1465107 combination showed the strongest association (p = .000011). Quantitative real-time polymerase chain reaction analysis showed that overall relative quantity of MAOA messenger RNA was significantly higher in patients with MDD than in control subjects (fold change = 5.28, p = 1.7 × 10⁻⁷) and that in the male subjects carrying the VNTR-L, rs1465107-A, rs6323-G, rs2072743-A, or rs1137070-T alleles, expression of MAOA messenger RNA was significantly higher in the patient group than in the control group. The cis-phase interaction between the VNTR polymorphism and functional SNPs may contribute to the etiology of MDD. Copyright © 2010 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Analysis of the quantitative dermatoglyphics of the digito-palmar complex in patients with multiple sclerosis.

PubMed

Supe, S; Milicić, J; Pavićević, R

1997-06-01

Recent studies on the etiopathogenesis of multiple sclerosis (MS) all point out that there is a polygenetical predisposition for this illness. The so called "MS Trait" determines the reactivity of the immunological system upon ecological factors. The development of the glyphological science and the study of the characteristics of the digito-palmar dermatoglyphic complex (for which it was established that they are polygenetically determined characteristics) all enable a better insight into the genetic development during early embriogenesis. The aim of this study was to estimate certain differences in the dermatoglyphics of digito-palmar complexes between the group with multiple sclerosis and the comparable, phenotypically healthy groups of both sexes. This study is based on the analysis of 18 quantitative characteristics of the digito-palmar complex in 125 patients with multiple sclerosis (41 males and 84 females) in comparison to a group of 400 phenotypically healthy patients (200 males and 200 females). The conducted analysis pointed towards a statistically significant decrease of the number of digital and palmar ridges, as well as with lower values of atd angles in a group of MS patients of both sexes. The main discriminators were the characteristic palmar dermatoglyphics with the possibility that the discriminate analysis classifies over 80% of the examinees which exceeds the statistical significance. The results of this study suggest a possible discrimination of patients with MS and the phenotypically health population through the analysis of the dermatoglyphic status, and therefore the possibility that multiple sclerosis is genetically predisposed disease.

Single molecule quantitation and sequencing of rare translocations using microfluidic nested digital PCR.

PubMed

Shuga, Joe; Zeng, Yong; Novak, Richard; Lan, Qing; Tang, Xiaojiang; Rothman, Nathaniel; Vermeulen, Roel; Li, Laiyu; Hubbard, Alan; Zhang, Luoping; Mathies, Richard A; Smith, Martyn T

2013-09-01

Cancers are heterogeneous and genetically unstable. New methods are needed that provide the sensitivity and specificity to query single cells at the genetic loci that drive cancer progression, thereby enabling researchers to study the progression of individual tumors. Here, we report the development and application of a bead-based hemi-nested microfluidic droplet digital PCR (dPCR) technology to achieve 'quantitative' measurement and single-molecule sequencing of somatically acquired carcinogenic translocations at extremely low levels (<10(-6)) in healthy subjects. We use this technique in our healthy study population to determine the overall concentration of the t(14;18) translocation, which is strongly associated with follicular lymphoma. The nested dPCR approach improves the detection limit to 1×10(-7) or lower while maintaining the analysis efficiency and specificity. Further, the bead-based dPCR enabled us to isolate and quantify the relative amounts of the various clonal forms of t(14;18) translocation in these subjects, and the single-molecule sensitivity and resolution of dPCR led to the discovery of new clonal forms of t(14;18) that were otherwise masked by the conventional quantitative PCR measurements. In this manner, we created a quantitative map for this carcinogenic mutation in this healthy population and identified the positions on chromosomes 14 and 18 where the vast majority of these t(14;18) events occur.

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

Investigating genetic loci that encode plant-derived paleoclimate proxies

NASA Astrophysics Data System (ADS)

Bender, A. L. D.; Suess, M.; Chitwood, D. H.; Bradley, A. S.

2016-12-01

Long chain (>C25) n-alkanes in sediments predominantly derive from terrestrial plant waxes. Hydrogen isotope ratios (δD) of leaf wax hydrocarbons correlate with δDH2O of precipitation and are commonly used as paleoclimate proxies. However, biological variability in the isotopic fractionations between water and plant materials also affects the n-alkane δD values. Correct interpretation of this paleoclimate proxy requires that we resolve genetic and environmental effects. Genetic variability underlying differences in leaf wax structure and isotopic composition can be quantitatively determined through the use of model organisms. Interfertile Solanum sect. Lycopersicon (tomato) species provide an ideal model species complex for this approach. We used a set of 76 precisely defined near-isogenic lines (introgression lines [ILs]) in which small genomic regions from the wild tomato relative Solanum pennellii have been introduced into the genome of the domestic tomato, S. lycopersicum. By characterizing quantitative traits of these ILs (leaf wax structure and isotopic composition), we can resolve the degree to which each trait is regulated by genetic versus environmental factors. We present data from two growth experiments conducted with all 76 ILs. In this study, we quantify leaf wax traits, including δD values, δ13C values, and structural metrics including the methylation index (a variable that describes the ratio of iso­- and anteiso- to n-alkanes). Among ILs, δD values vary by up to 35‰ and 60‰ for C31 and C33 n-alkanes, respectively. Many ILs have methylation indices that are discernably different from the parent domesticated tomato (p < 0.001), which suggests that methylation is a highly polygenic trait. This pattern is similar to the genetics that control leaf shape, another trait commonly used as a paleoclimate proxy. Based on our preliminary analysis, we propose candidate genes that control aspects of plant physiology that affect these quantitative traits. Our results have important implications for uncovering the degree to which we can expect environmental versus genetic factors to modulate variability in n-alkane δD values. These findings can inform the interpretation of the proxy signal recovered from the geological record.

Genetic Control of Contagious Asexuality in the Pea Aphid

PubMed Central

Jaquiéry, Julie; Stoeckel, Solenn; Larose, Chloé; Nouhaud, Pierre; Rispe, Claude; Mieuzet, Lucie; Bonhomme, Joël; Mahéo, Frédérique; Legeai, Fabrice; Gauthier, Jean-Pierre; Prunier-Leterme, Nathalie; Tagu, Denis; Simon, Jean-Christophe

2014-01-01

Although evolutionary transitions from sexual to asexual reproduction are frequent in eukaryotes, the genetic bases of such shifts toward asexuality remain largely unknown. We addressed this issue in an aphid species where both sexual and obligate asexual lineages coexist in natural populations. These sexual and asexual lineages may occasionally interbreed because some asexual lineages maintain a residual production of males potentially able to mate with the females produced by sexual lineages. Hence, this species is an ideal model to study the genetic basis of the loss of sexual reproduction with quantitative genetic and population genomic approaches. Our analysis of the co-segregation of ∼300 molecular markers and reproductive phenotype in experimental crosses pinpointed an X-linked region controlling obligate asexuality, this state of character being recessive. A population genetic analysis (>400-marker genome scan) on wild sexual and asexual genotypes from geographically distant populations under divergent selection for reproductive strategies detected a strong signature of divergent selection in the genomic region identified by the experimental crosses. These population genetic data confirm the implication of the candidate region in the control of reproductive mode in wild populations originating from 700 km apart. Patterns of genetic differentiation along chromosomes suggest bidirectional gene flow between populations with distinct reproductive modes, supporting contagious asexuality as a prevailing route to permanent parthenogenesis in pea aphids. This genetic system provides new insights into the mechanisms of coexistence of sexual and asexual aphid lineages. PMID:25473828

A selfish genetic element confers non-Mendelian inheritance in rice.

PubMed

Yu, Xiaowen; Zhao, Zhigang; Zheng, Xiaoming; Zhou, Jiawu; Kong, Weiyi; Wang, Peiran; Bai, Wenting; Zheng, Hai; Zhang, Huan; Li, Jing; Liu, Jiafan; Wang, Qiming; Zhang, Long; Liu, Kai; Yu, Yang; Guo, Xiuping; Wang, Jiulin; Lin, Qibing; Wu, Fuqing; Ren, Yulong; Zhu, Shanshan; Zhang, Xin; Cheng, Zhijun; Lei, Cailin; Liu, Shijia; Liu, Xi; Tian, Yunlu; Jiang, Ling; Ge, Song; Wu, Chuanyin; Tao, Dayun; Wang, Haiyang; Wan, Jianmin

2018-06-08

Selfish genetic elements are pervasive in eukaryote genomes, but their role remains controversial. We show that qHMS7 , a major quantitative genetic locus for hybrid male sterility between wild rice ( Oryza meridionalis ) and Asian cultivated rice ( O. sativa ), contains two tightly linked genes [ Open Reading Frame 2 ( ORF2 ) and ORF3 ]. ORF2 encodes a toxic genetic element that aborts pollen in a sporophytic manner, whereas ORF3 encodes an antidote that protects pollen in a gametophytic manner. Pollens lacking ORF3 are selectively eliminated, leading to segregation distortion in the progeny. Analysis of the genetic sequence suggests that ORF3 arose first, followed by gradual functionalization of ORF2 Furthermore, this toxin-antidote system may have promoted the differentiation and/or maintained the genome stability of wild and cultivated rice. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

SNPassoc: an R package to perform whole genome association studies.

PubMed

González, Juan R; Armengol, Lluís; Solé, Xavier; Guinó, Elisabet; Mercader, Josep M; Estivill, Xavier; Moreno, Víctor

2007-03-01

The popularization of large-scale genotyping projects has led to the widespread adoption of genetic association studies as the tool of choice in the search for single nucleotide polymorphisms (SNPs) underlying susceptibility to complex diseases. Although the analysis of individual SNPs is a relatively trivial task, when the number is large and multiple genetic models need to be explored it becomes necessary a tool to automate the analyses. In order to address this issue, we developed SNPassoc, an R package to carry out most common analyses in whole genome association studies. These analyses include descriptive statistics and exploratory analysis of missing values, calculation of Hardy-Weinberg equilibrium, analysis of association based on generalized linear models (either for quantitative or binary traits), and analysis of multiple SNPs (haplotype and epistasis analysis). Package SNPassoc is available at CRAN from http://cran.r-project.org. A tutorial is available on Bioinformatics online and in http://davinci.crg.es/estivill_lab/snpassoc.

Multi-system Component Phenotypes of Bipolar Disorder for Genetic Investigations of Extended Pedigrees

PubMed Central

Fears, Scott C.; Service, Susan K.; Kremeyer, Barbara; Araya, Carmen; Araya, Xinia; Bejarano, Julio; Ramirez, Margarita; Castrillón, Gabriel; Gomez-Franco, Juliana; Lopez, Maria C.; Montoya, Gabriel; Montoya, Patricia; Aldana, Ileana; Teshiba, Terri M.; Abaryan, Zvart; Al-Sharif, Noor B.; Ericson, Marissa; Jalbrzikowski, Maria; Luykx, Jurjen J.; Navarro, Linda; Tishler, Todd A.; Altshuler, Lori; Bartzokis, George; Escobar, Javier; Glahn, David C.; Ospina-Duque, Jorge; Risch, Neil; Ruiz-Linares, Andrés; Thompson, Paul M.; Cantor, Rita M.; Lopez-Jaramillo, Carlos; Macaya, Gabriel; Molina, Julio; Reus, Victor I.; Sabatti, Chiara; Freimer, Nelson B.; Bearden, Carrie E.

2014-01-01

IMPORTANCE Genetic factors contribute to risk for bipolar disorder (BP), yet its pathogenesis remains poorly understood. A focus on measuring multi-system quantitative traits that may be components of BP psychopathology may enable genetic dissection of this complex disorder, and investigation of extended pedigrees from genetically isolated populations may facilitate the detection of specific genetic variants that impact on BP as well as its component phenotypes. OBJECTIVE To identify quantitative neurocognitive, temperament-related, and neuroanatomic phenotypes that appear heritable and associated with severe bipolar disorder (BP-I), and therefore suitable for genetic linkage and association studies aimed at identifying variants contributing to BP-I risk. DESIGN Multi-generational pedigree study in two closely related, genetically isolated populations: the Central Valley of Costa Rica (CVCR) and Antioquia, Colombia (ANT). PARTICIPANTS 738 individuals, all from CVCR and ANT pedigrees, of whom 181 are affected with BP-I. MAIN OUTCOME MEASURE Familial aggregation (heritability) and association with BP-I of 169 quantitative neurocognitive, temperament, magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) phenotypes. RESULTS Seventy-five percent (126) of the phenotypes investigated were significantly heritable, and 31% (53) were associated with BP-I. About 1/4 of the phenotypes, including measures from each phenotype domain, were both heritable and associated with BP-I. Neuroimaging phenotypes, particularly cortical thickness in prefrontal and temporal regions, and volume and microstructural integrity of the corpus callosum, represented the most promising candidate traits for genetic mapping related to BP based on strong heritability and association with disease. Analyses of phenotypic and genetic covariation identified substantial correlations among the traits, at least some of which share a common underlying genetic architecture. CONCLUSIONS AND RELEVANCE This is the most extensive investigation of BP-relevant component phenotypes to date. Our results identify brain and behavioral quantitative traits that appear to be genetically influenced and show a pattern of BP-I-association within families that is consistent with expectations from case-control studies. Together these phenotypes provide a basis for identifying loci contributing to BP-I risk and for genetic dissection of the disorder. PMID:24522887

The IQ Quantitative Trait Loci Project: A Critique.

ERIC Educational Resources Information Center

King, David

1998-01-01

Describes the IQ Quantitative Trait Loci (QTL) project, an attempt to identify genes underlying IQ score variations using maps from the Human Genome Project. The essay argues against funding the IQ QTL project because it will end the debates about the genetic basis of intelligence and may lead directly to eugenic programs of genetic testing. (SLD)

Prenatal diagnosis and genetic analysis of double trisomy 48,XXX,+18.

PubMed

Chen, C P; Chern, S R; Yeh, L F; Chen, W L; Chen, L F; Wang, W

2000-09-01

Prenatal diagnosis of simultaneous occurrence of double trisomy involving chromosomes 18 and X is extremely rare. We report on the prenatal diagnosis, genetic analysis and clinical manifestations of a fetus with both trisomy 18 and trisomy X. A 26-year-old, para 1 woman was referred for genetic counselling at 36 weeks' gestation with the sonographic findings of intrauterine growth retardation (IUGR), polyhydramnios, ventricular septal defect, and an enlarged cisterna magna. Both cordocentesis and amniocentesis revealed a consistent karyotype of 48,XXX,+18. Quantitative fluorescent polymerase chain reaction using polymorphic small tandem repeat markers specific for chromosomes 18 and X rapidly determined that both aneuploidies arose as a result of non-disjunction in maternal meiosis II. Our case shows that two non-disjunction events can occur not only in the same parent, but also in the same cell division. Our case also shows that double trisomy, 48,XXX,+18, can demonstrate an enlarged cisterna magna, IUGR and polyhydramnios in prenatal ultrasound. Copyright 2000 John Wiley & Sons, Ltd.

Genetic deletion of the EGFR ligand epigen does not affect mouse embryonic development and tissue homeostasis.

PubMed

Dahlhoff, Maik; Schäfer, Matthias; Wolf, Eckhard; Schneider, Marlon R

2013-02-15

The epidermal growth factor receptor (EGFR) is a tyrosine kinase receptor with manifold functions during development, tissue homeostasis and disease. EGFR activation, the formation of homodimers or heterodimers (with the related ERBB2-4 receptors) and downstream signaling is initiated by the binding of a family of structurally related growth factors, the EGFR ligands. Genetic deletion experiments clarified the biological function of all family members except for the last characterized ligand, epigen. We employed gene targeting in mouse embryonic stem cells to generate mice lacking epigen expression. Loss of epigen did not affect mouse development, fertility, or organ physiology. Quantitative RT-PCR analysis revealed increased expression of betacellulin and EGF in a few organs of epigen-deficient mice, suggesting a functional compensation by these ligands. In conclusion, we completed the genetic analysis of EGFR ligands and show that epigen has non-essential functions or functions that can be compensated by other EGFR ligands during growth and tissue homeostasis. Copyright © 2012 Elsevier Inc. All rights reserved.

Refining Intervention Targets in Family-Based Research: Lessons From Quantitative Behavioral Genetics

PubMed Central

Leve, Leslie D.; Harold, Gordon T.; Ge, Xiaojia; Neiderhiser, Jenae M.; Patterson, Gerald

2010-01-01

The results from a large body of family-based research studies indicate that modifying the environment (specifically dimensions of the social environment) through intervention is an effective mechanism for achieving positive outcomes. Parallel to this work is a growing body of evidence from genetically informed studies indicating that social environmental factors are central to enhancing or offsetting genetic influences. Increased precision in the understanding of the role of the social environment in offsetting genetic risk might provide new information about environmental mechanisms that could be applied to prevention science. However, at present, the multifaceted conceptualization of the environment in prevention science is mismatched with the more limited measurement of the environment in many genetically informed studies. A framework for translating quantitative behavioral genetic research to inform the development of preventive interventions is presented in this article. The measurement of environmental indices amenable to modification is discussed within the context of quantitative behavioral genetic studies. In particular, emphasis is placed on the necessary elements that lead to benefits in prevention science, specifically the development of evidence-based interventions. An example from an ongoing prospective adoption study is provided to illustrate the potential of this translational process to inform the selection of preventive intervention targets. PMID:21188273

Genetic Architecture of Micro-Environmental Plasticity in Drosophila melanogaster.

PubMed

Morgante, Fabio; Sørensen, Peter; Sorensen, Daniel A; Maltecca, Christian; Mackay, Trudy F C

2015-05-06

Individuals of the same genotype do not have the same phenotype for quantitative traits when reared under common macro-environmental conditions, a phenomenon called micro-environmental plasticity. Genetic variation in micro-environmental plasticity is assumed in models of the evolution of phenotypic variance, and is important in applied breeding and personalized medicine. Here, we quantified genetic variation for micro-environmental plasticity for three quantitative traits in the inbred, sequenced lines of the Drosophila melanogaster Genetic Reference Panel. We found substantial genetic variation for micro-environmental plasticity for all traits, with broad sense heritabilities of the same magnitude or greater than those of trait means. Micro-environmental plasticity is not correlated with residual segregating variation, is trait-specific, and has genetic correlations with trait means ranging from zero to near unity. We identified several candidate genes associated with micro-environmental plasticity of startle response, including Drosophila Hsp90, setting the stage for future genetic dissection of this phenomenon.

Can genetics help psychometrics? Improving dimensionality assessment through genetic factor modeling.

PubMed

Franić, Sanja; Dolan, Conor V; Borsboom, Denny; Hudziak, James J; van Beijsterveldt, Catherina E M; Boomsma, Dorret I

2013-09-01

In the present article, we discuss the role that quantitative genetic methodology may play in assessing and understanding the dimensionality of psychological (psychometric) instruments. Specifically, we study the relationship between the observed covariance structures, on the one hand, and the underlying genetic and environmental influences giving rise to such structures, on the other. We note that this relationship may be such that it hampers obtaining a clear estimate of dimensionality using standard tools for dimensionality assessment alone. One situation in which dimensionality assessment may be impeded is that in which genetic and environmental influences, of which the observed covariance structure is a function, differ from each other in structure and dimensionality. We demonstrate that in such situations settling dimensionality issues may be problematic, and propose using quantitative genetic modeling to uncover the (possibly different) dimensionalities of the underlying genetic and environmental structures. We illustrate using simulations and an empirical example on childhood internalizing problems.

Genetic variation affecting host-parasite interactions: major-effect quantitative trait loci affect the transmission of sigma virus in Drosophila melanogaster.

PubMed

Bangham, Jenny; Knott, Sara A; Kim, Kang-Wook; Young, Robert S; Jiggins, Francis M

2008-09-01

In natural populations, genetic variation affects resistance to disease. Whether that genetic variation comprises lots of small-effect polymorphisms or a small number of large-effect polymorphisms has implications for adaptation, selection and how genetic variation is maintained in populations. Furthermore, how much genetic variation there is, and the genes that underlie this variation, affects models of co-evolution between parasites and their hosts. We are studying the genetic variation that affects the resistance of Drosophila melanogaster to its natural pathogen--the vertically transmitted sigma virus. We have carried out three separate quantitative trait locus mapping analyses to map gene variants on the second chromosome that cause variation in the rate at which males transmit the infection to their offspring. All three crosses identified a locus in a similar chromosomal location that causes a large drop in the rate at which the virus is transmitted. We also found evidence for an additional smaller-effect quantitative trait locus elsewhere on the chromosome. Our data, together with previous experiments on the sigma virus and parasitoid wasps, indicate that the resistance of D. melanogaster to co-evolved pathogens is controlled by a limited number of major-effect polymorphisms.

Electrophysiological Endophenotypes for Schizophrenia

PubMed Central

Owens, Emily; Bachman, Peter; Glahn, David C; Bearden, Carrie E

2016-01-01

Endophenotypes are quantitative, heritable traits that may help to elucidate the pathophysiologic mechanisms underlying complex disease syndromes, such as schizophrenia. They can be assessed at numerous levels of analysis; here, we review electrophysiological endophenotypes that have shown promise in helping us understand schizophrenia from a more mechanistic point of view. For each endophenotype, we describe typical experimental procedures, reliability, heritability, and reported gene and neurobiological associations. We discuss recent findings regarding the genetic architecture of specific electrophysiological endophenotypes, as well as converging evidence from EEG studies implicating disrupted balance of glutamatergic signaling and GABA-ergic inhibition in the pathophysiology of schizophrenia. We conclude that refining the measurement of electrophysiological endophenotypes, expanding genetic association studies, and integrating datasets are important next steps for understanding the mechanisms that connect identified genetic risk loci for schizophrenia to the disease phenotype. PMID:26954597

Differentiation of five body fluids from forensic samples by expression analysis of four microRNAs using quantitative PCR.

PubMed

Sauer, Eva; Reinke, Ann-Kathrin; Courts, Cornelius

2016-05-01

Applying molecular genetic approaches for the identification of forensically relevant body fluids, which often yield crucial information for the reconstruction of a potential crime, is a current topic of forensic research. Due to their body fluid specific expression patterns and stability against degradation, microRNAs (miRNA) emerged as a promising molecular species, with a range of candidate markers published. The analysis of miRNA via quantitative Real-Time PCR, however, should be based on a relevant strategy of normalization of non-biological variances to deliver reliable and biologically meaningful results. The herein presented work is the as yet most comprehensive study of forensic body fluid identification via miRNA expression analysis based on a thoroughly validated qPCR procedure and unbiased statistical decision making to identify single source samples. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Quantitative genetics of immunity and life history under different photoperiods.

PubMed

Hammerschmidt, K; Deines, P; Wilson, A J; Rolff, J

2012-05-01

Insects with complex life-cycles should optimize age and size at maturity during larval development. When inhabiting seasonal environments, organisms have limited reproductive periods and face fundamental decisions: individuals that reach maturity late in season have to either reproduce at a small size or increase their growth rates. Increasing growth rates is costly in insects because of higher juvenile mortality, decreased adult survival or increased susceptibility to parasitism by bacteria and viruses via compromised immune function. Environmental changes such as seasonality can also alter the quantitative genetic architecture. Here, we explore the quantitative genetics of life history and immunity traits under two experimentally induced seasonal environments in the cricket Gryllus bimaculatus. Seasonality affected the life history but not the immune phenotypes. Individuals under decreasing day length developed slower and grew to a bigger size. We found ample additive genetic variance and heritability for components of immunity (haemocyte densities, proPhenoloxidase activity, resistance against Serratia marcescens), and for the life history traits, age and size at maturity. Despite genetic covariance among traits, the structure of G was inconsistent with genetically based trade-off between life history and immune traits (for example, a strong positive genetic correlation between growth rate and haemocyte density was estimated). However, conditional evolvabilities support the idea that genetic covariance structure limits the capacity of individual traits to evolve independently. We found no evidence for G × E interactions arising from the experimentally induced seasonality.

Quantitative assessment of skin, hair, and iris variation in a diverse sample of individuals and associated genetic variation.

PubMed

Norton, Heather L; Edwards, Melissa; Krithika, S; Johnson, Monique; Werren, Elizabeth A; Parra, Esteban J

2016-08-01

The main goals of this study are to 1) quantitatively measure skin, hair, and iris pigmentation in a diverse sample of individuals, 2) describe variation within and between these samples, and 3) demonstrate how quantitative measures can facilitate genotype-phenotype association tests. We quantitatively characterize skin, hair, and iris pigmentation using the Melanin (M) Index (skin) and CIELab values (hair) in 1,450 individuals who self-identify as African American, East Asian, European, Hispanic, or South Asian. We also quantify iris pigmentation in a subset of these individuals using CIELab values from high-resolution iris photographs. We compare mean skin M index and hair and iris CIELab values among populations using ANOVA and MANOVA respectively and test for genotype-phenotype associations in the European sample. All five populations are significantly different for skin (P <2 × 10(-16) ) and hair color (P <2 × 10(-16) ). Our quantitative analysis of iris and hair pigmentation reinforces the continuous, rather than discrete, nature of these traits. We confirm the association of three loci (rs16891982, rs12203592, and rs12913832) with skin pigmentation and four loci (rs12913832, rs12203592, rs12896399, and rs16891982) with hair pigmentation. Interestingly, the derived rs12203592 T allele located within the IRF4 gene is associated with lighter skin but darker hair color. The quantitative methods used here provide a fine-scale assessment of pigmentation phenotype and facilitate genotype-phenotype associations, even with relatively small sample sizes. This represents an important expansion of current investigations into pigmentation phenotype and associated genetic variation by including non-European and admixed populations. Am J Phys Anthropol 160:570-581, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Systematic analysis of Ca2+ homeostasis in Saccharomyces cerevisiae based on chemical-genetic interaction profiles

PubMed Central

Ghanegolmohammadi, Farzan; Yoshida, Mitsunori; Ohnuki, Shinsuke; Sukegawa, Yuko; Okada, Hiroki; Obara, Keisuke; Kihara, Akio; Suzuki, Kuninori; Kojima, Tetsuya; Yachie, Nozomu; Hirata, Dai; Ohya, Yoshikazu

2017-01-01

We investigated the global landscape of Ca2+ homeostasis in budding yeast based on high-dimensional chemical-genetic interaction profiles. The morphological responses of 62 Ca2+-sensitive (cls) mutants were quantitatively analyzed with the image processing program CalMorph after exposure to a high concentration of Ca2+. After a generalized linear model was applied, an analysis of covariance model was used to detect significant Ca2+–cls interactions. We found that high-dimensional, morphological Ca2+–cls interactions were mixed with positive (86%) and negative (14%) chemical-genetic interactions, whereas one-dimensional fitness Ca2+–cls interactions were all negative in principle. Clustering analysis with the interaction profiles revealed nine distinct gene groups, six of which were functionally associated. In addition, characterization of Ca2+–cls interactions revealed that morphology-based negative interactions are unique signatures of sensitized cellular processes and pathways. Principal component analysis was used to discriminate between suppression and enhancement of the Ca2+-sensitive phenotypes triggered by inactivation of calcineurin, a Ca2+-dependent phosphatase. Finally, similarity of the interaction profiles was used to reveal a connected network among the Ca2+ homeostasis units acting in different cellular compartments. Our analyses of high-dimensional chemical-genetic interaction profiles provide novel insights into the intracellular network of yeast Ca2+ homeostasis. PMID:28566553

Evolutionary speed of species invasions.

PubMed

García-Ramos, Gisela; Rodríguez, Diego

2002-04-01

Successful invasion may depend of the capacity of a species to adjust genetically to a spatially varying environment. This research modeled a species invasion by examining the interaction between a quantitative genetic trait and population density. It assumed: (I) a quantitative genetic trait describes the adaptation of an individual to its local ecological conditions; (2) populations far from the local optimum grow more slowly than those near the optimum; and (3) the evolution of a trait depends on local population density, because differences in local population densities cause asymmetrical gene flow. This genetics-density interaction determined the propagation speed of populations. Numerical simulations showed that populations spread by advancing as two synchronic traveling waves, one for population density and one for trait adaptation. The form of the density wave was a step front that advances homogenizing populations at their carrying capacity; the adaptation wave was a curve with finite slope that homogenizes populations at full adaptation. The largest speed of population expansion, for a dimensionless analysis, corresponded to an almost homogeneous spatial environment when this model approached an ecological description such as the Fisher-Skellam's model. A large genetic response also favored faster speeds. Evolutionary speeds, in a natural scale, showed a wide range of rates that were also slower compared to models that only consider demographics. This evolutionary speed increased with high heritability, strong stabilizing selection, and high intrinsic growth rate. It decreased for steeper environmental gradients. Also indicated was an optimal dispersal rate over which evolutionary speed declined. This is expected because dispersal moves individuals further, but homogenizes populations genetically, making them maladapted. The evolutionary speed was compared to observed data. Furthermore, a moderate increase in the speed of expansion was predicted for ecological changes related to global warming.

One Novel Multiple-Target Plasmid Reference Molecule Targeting Eight Genetically Modified Canola Events for Genetically Modified Canola Detection.

PubMed

Li, Zhuqing; Li, Xiang; Wang, Canhua; Song, Guiwen; Pi, Liqun; Zheng, Lan; Zhang, Dabing; Yang, Litao

2017-09-27

Multiple-target plasmid DNA reference materials have been generated and utilized as good substitutes of matrix-based reference materials in the analysis of genetically modified organisms (GMOs). Herein, we report the construction of one multiple-target plasmid reference molecule, pCAN, which harbors eight GM canola event-specific sequences (RF1, RF2, MS1, MS8, Topas 19/2, Oxy235, RT73, and T45) and a partial sequence of the canola endogenous reference gene PEP. The applicability of this plasmid reference material in qualitative and quantitative PCR assays of the eight GM canola events was evaluated, including the analysis of specificity, limit of detection (LOD), limit of quantification (LOQ), and performance of pCAN in the analysis of various canola samples, etc. The LODs are 15 copies for RF2, MS1, and RT73 assays using pCAN as the calibrator and 10 genome copies for the other events. The LOQ in each event-specific real-time PCR assay is 20 copies. In quantitative real-time PCR analysis, the PCR efficiencies of all event-specific and PEP assays are between 91% and 97%, and the squared regression coefficients (R 2 ) are all higher than 0.99. The quantification bias values varied from 0.47% to 20.68% with relative standard deviation (RSD) from 1.06% to 24.61% in the quantification of simulated samples. Furthermore, 10 practical canola samples sampled from imported shipments in the port of Shanghai, China, were analyzed employing pCAN as the calibrator, and the results were comparable with those assays using commercial certified materials as the calibrator. Concluding from these results, we believe that this newly developed pCAN plasmid is one good candidate for being a plasmid DNA reference material in the detection and quantification of the eight GM canola events in routine analysis.

Genome-wide analysis of ivermectin response by Onchocerca volvulus reveals that genetic drift and soft selective sweeps contribute to loss of drug sensitivity

PubMed Central

Nana-Djeunga, Hugues C.; Kengne-Ouafo, Jonas A.; Pion, Sébastien D. S.; Bopda, Jean; Kamgno, Joseph; Wanji, Samuel; Che, Hua; Kuesel, Annette C.; Walker, Martin; Basáñez, Maria-Gloria; Boakye, Daniel A.; Osei-Atweneboana, Mike Y.; Boussinesq, Michel; Prichard, Roger K.; Grant, Warwick N.

2017-01-01

Background Treatment of onchocerciasis using mass ivermectin administration has reduced morbidity and transmission throughout Africa and Central/South America. Mass drug administration is likely to exert selection pressure on parasites, and phenotypic and genetic changes in several Onchocerca volvulus populations from Cameroon and Ghana—exposed to more than a decade of regular ivermectin treatment—have raised concern that sub-optimal responses to ivermectin's anti-fecundity effect are becoming more frequent and may spread. Methodology/Principal findings Pooled next generation sequencing (Pool-seq) was used to characterise genetic diversity within and between 108 adult female worms differing in ivermectin treatment history and response. Genome-wide analyses revealed genetic variation that significantly differentiated good responder (GR) and sub-optimal responder (SOR) parasites. These variants were not randomly distributed but clustered in ~31 quantitative trait loci (QTLs), with little overlap in putative QTL position and gene content between the two countries. Published candidate ivermectin SOR genes were largely absent in these regions; QTLs differentiating GR and SOR worms were enriched for genes in molecular pathways associated with neurotransmission, development, and stress responses. Finally, single worm genotyping demonstrated that geographic isolation and genetic change over time (in the presence of drug exposure) had a significantly greater role in shaping genetic diversity than the evolution of SOR. Conclusions/Significance This study is one of the first genome-wide association analyses in a parasitic nematode, and provides insight into the genomics of ivermectin response and population structure of O. volvulus. We argue that ivermectin response is a polygenically-determined quantitative trait (QT) whereby identical or related molecular pathways but not necessarily individual genes are likely to determine the extent of ivermectin response in different parasite populations. Furthermore, we propose that genetic drift rather than genetic selection of SOR is the underlying driver of population differentiation, which has significant implications for the emergence and potential spread of SOR within and between these parasite populations. PMID:28746337

Association between dietary fat intake and insulin resistance in Chinese child twins.

PubMed

Huang, Tao; Beaty, Terri; Li, Ji; Liu, Huijuan; Zhao, Wei; Wang, Youfa

2017-01-01

Dietary fat intake is correlated with increased insulin resistance (IR). However, it is unknown whether gene-diet interaction modulates the association. This study estimated heritability of IR measures and the related genetic correlations with fat intake, and tested whether dietary fat intake modifies the genetic influence on type 2 diabetes (T2D)-related traits in Chinese child twins. We included 622 twins aged 7-15 years (n 311 pairs, 162 monozygotic (MZ), 149 dizygotic (DZ)) from south-eastern China. Dietary factors were measured using FFQ. Structural equation models were fit using Mx statistical package. The intra-class correlation coefficients for all traits related to T2D were higher for MZ twins than for DZ twins. Dietary fat and fasting serum insulin (additive genetic correlation (r A) 0·20; 95 % CI 0·08, 0·43), glucose (r A 0·12; 95 % CI 0·01, 0·40), homoeostasis model of assessment-insulin resistance (Homa-IR) (r A 0·22; 95 % CI 0·10, 0·50) and the quantitative insulin sensitivity check index (Quicki) (r A -0·22; 95 % CI -0·40, 0·04) showed strong genetic correlations. Heritabilities of dietary fat intake, fasting glucose and insulin were estimated to be 52, 70 and 70 %, respectively. More than 70 % of the phenotypic correlations between dietary fat and insulin, glucose, Homa-IR and the Quicki index appeared to be mediated by shared genetic influence. Dietary fat significantly modified additive genetic effects on these quantitative traits associated with T2D. Analysis of Chinese twins yielded high estimates of heritability of dietary fat intake and IR. Genetic factors appear to contribute to a high proportion of the variance for both insulin sensitivity and IR. Dietary fat intake modifies the genetic influence on blood levels of insulin and glucose, Homa-IR and the Quicki index.

Consistent etiology of severe, frequent psychotic experiences and milder, less frequent manifestations: A twin study of specific psychotic experiences in adolescence

PubMed Central

Zavos, Helena M.S.; Freeman, Daniel; Haworth, Claire M. A.; McGuire, Philip; Plomin, Robert; Cardno, Alastair G.; Ronald, Angelica

2014-01-01

Context The onset of psychosis is usually preceded by psychotic experiences, but little is known about their causes. The present study investigated the degree of genetic and environmental influences on specific psychotic experiences, assessed dimensionally, in adolescence in the community and in individuals with many, frequent experiences (defined using quantitative cut-offs). The degree of overlap in etiological influences between specific psychotic experiences was also investigated Objective Investigate degree of genetic and environmental influences on specific psychotic experiences, assessed dimensionally, in adolescence in the community and in individuals having many, frequent experiences (defined using quantitative cut-offs). Test degree of overlap in etiological influences between specific psychotic experiences. Design Classic twin design. Structural equation model-fitting. Univariate and bivariate twin models, liability threshold models, DeFries-Fulker extremes analysis and the Cherny Method. Setting Representative community sample of twins from England and Wales. Participants 5059 adolescent twin pairs (Mean age: 16.31 yrs, SD: 0.68 yrs). Main outcome measure Psychotic experiences assessed as quantitative traits (self-rated paranoia, hallucinations, cognitive disorganization, grandiosity, anhedonia; parent-rated negative symptoms). Results Genetic influences were apparent for all psychotic experiences (15-59%) with modest shared environment for hallucinations and negative symptoms (17-24%) and significant nonshared environment (49-64% for the self-rated scales, 17% for Parent-rated Negative Symptoms). Three different empirical approaches converged to suggest that the etiology in extreme groups (most extreme-scoring 5%, 10% and 15%) did not differ significantly from that of the whole distribution. There was no linear change in the heritability across the distribution of psychotic experiences, with the exception of a modest increase in heritability for increasing severity of parent-rated negative symptoms. Of the psychotic experiences that showed covariation, this appeared to be due to shared genetic influences (bivariate heritabilities = .54-.71). Conclusions and Relevance These findings are consistent with the concept of a psychosis continuum, suggesting that the same genetic and environmental factors influence both extreme, frequent psychotic experiences and milder, less frequent manifestations in adolescents. Individual psychotic experiences in adolescence, assessed quantitatively, have lower heritability estimates and higher estimates of nonshared environment than those for the liability to schizophrenia. Heritability varies by type of psychotic experience, being highest for paranoia and parent-rated negative symptoms, and lowest for hallucinations. PMID:25075799

The A-Like Faker Assay for Measuring Yeast Chromosome III Stability.

PubMed

Novoa, Carolina A; Ang, J Sidney; Stirling, Peter C

2018-01-01

The ability to rapidly assess chromosome instability (CIN) has enabled profiling of most yeast genes for potential effects on genome stability. The A-like faker (ALF) assay is one of several qualitative and quantitative marker loss assays that indirectly measure loss or conversion of genetic material using a counterselection step. The ALF assay relies on the ability to count spurious mating events that occur upon loss of the MATα locus of haploid Saccharomyces cerevisiae strains. Here, we describe the deployment of the ALF assay for both rapid and simple qualitative, and more in-depth quantitative analysis allowing determination of absolute ALF frequencies.

Genetic Ancestry, Serum Interferon-α Activity, and Autoantibodies in Systemic Lupus Erythematosus

PubMed Central

Ko, Kichul; Franek, Beverly S.; Marion, Miranda; Kaufman, Kenneth M.; Langefeld, Carl D.; Harley, John B.; Niewold, Timothy B.

2012-01-01

Objective To investigate and refine the relationships among systemic lupus erythematosus (SLE) and related autoantibodies, interferon-α (IFN-α), and various ancestral backgrounds. Methods We investigated quantitatively defined genetic ancestry through principal component analysis in place of self-reported ancestry. Results African ancestry was found to be associated with presence of anti-RNP antibody (p = 0.0026), and anti-RNP was correlated with high levels of IFN-α (p = 2.8 × 10−5). Conclusion Our data support a model in which African ancestry increases the likelihood of SLE-associated autoantibody formation, which subsequently results in higher levels of serum IFN-α. PMID:22505704

The Genotype and Phenotype (GaP) registry: a living biobank for the analysis of quantitative traits.

PubMed

Gregersen, Peter K; Klein, Gila; Keogh, Mary; Kern, Marlena; DeFranco, Margaret; Simpfendorfer, Kim R; Kim, Sun Jung; Diamond, Betty

2015-12-01

We describe the development of the Genotype and Phenotype (GaP) Registry, a living biobank of normal volunteers who are genotyped for genetic markers related to human disease. Participants in the GaP can be recalled for hypothesis driven study of disease associated genetic variants. The GaP has facilitated functional studies of several autoimmune disease associated loci including Csk, Blk, PDRM1 (Blimp-1) and PTPN22. It is likely that expansion of such living biobank registries will play an important role in studying and understanding the function of disease associated alleles in complex disease.

Using Movies to Analyse Gene Circuit Dynamics in Single Cells

PubMed Central

Locke, James CW; Elowitz, Michael B

2010-01-01

Preface Many bacterial systems rely on dynamic genetic circuits to control critical processes. A major goal of systems biology is to understand these behaviours in terms of individual genes and their interactions. However, traditional techniques based on population averages wash out critical dynamics that are either unsynchronized between cells or driven by fluctuations, or ‘noise,’ in cellular components. Recently, the combination of time-lapse microscopy, quantitative image analysis, and fluorescent protein reporters has enabled direct observation of multiple cellular components over time in individual cells. In conjunction with mathematical modelling, these techniques are now providing powerful insights into genetic circuit behaviour in diverse microbial systems. PMID:19369953

Correction of the lack of commutability between plasmid DNA and genomic DNA for quantification of genetically modified organisms using pBSTopas as a model.

PubMed

Zhang, Li; Wu, Yuhua; Wu, Gang; Cao, Yinglong; Lu, Changming

2014-10-01

Plasmid calibrators are increasingly applied for polymerase chain reaction (PCR) analysis of genetically modified organisms (GMOs). To evaluate the commutability between plasmid DNA (pDNA) and genomic DNA (gDNA) as calibrators, a plasmid molecule, pBSTopas, was constructed, harboring a Topas 19/2 event-specific sequence and a partial sequence of the rapeseed reference gene CruA. Assays of the pDNA showed similar limits of detection (five copies for Topas 19/2 and CruA) and quantification (40 copies for Topas 19/2 and 20 for CruA) as those for the gDNA. Comparisons of plasmid and genomic standard curves indicated that the slopes, intercepts, and PCR efficiency for pBSTopas were significantly different from CRM Topas 19/2 gDNA for quantitative analysis of GMOs. Three correction methods were used to calibrate the quantitative analysis of control samples using pDNA as calibrators: model a, or coefficient value a (Cva); model b, or coefficient value b (Cvb); and the novel model c or coefficient formula (Cf). Cva and Cvb gave similar estimated values for the control samples, and the quantitative bias of the low concentration sample exceeded the acceptable range within ±25% in two of the four repeats. Using Cfs to normalize the Ct values of test samples, the estimated values were very close to the reference values (bias -13.27 to 13.05%). In the validation of control samples, model c was more appropriate than Cva or Cvb. The application of Cf allowed pBSTopas to substitute for Topas 19/2 gDNA as a calibrator to accurately quantify the GMO.

mGluR7 genetics and alcohol: intersection yields clues for addiction.

PubMed

Gyetvai, Beatrix; Simonyi, Agnes; Oros, Melinda; Saito, Mariko; Smiley, John; Vadász, Csaba

2011-06-01

Development of addiction to alcohol or other substances can be attributed in part to exposure-dependent modifications at synaptic efficacy leading to an organism which functions at an altered homeostatic setpoint. Genetic factors may also influence setpoints and the stability of the homeostatic system of an organism. Quantitative genetic analysis of voluntary alcohol drinking, and mapping of the involved genes in the quasi-congenic Recombinant QTL Introgression strain system, identified Eac2 as a Quantitative Trait Locus (QTL) on mouse chromosome 6 which explained 18% of the variance with an effect size of 2.09 g/kg/day alcohol consumption, and Grm7 as a quantitative trait gene underlying Eac2 [Vadasz et al. in Neurochem Res 32:1099-1112, 100, Genomics 90:690-702, 102]. In earlier studies, the product of Grm7 mGluR7, a G protein-coupled receptor, has been implicated in stress systems [Mitsukawa et al. in Proc Natl Acad Sci USA 102:18712-18717, 63], anxiety-like behaviors [Cryan et al. in Eur J Neurosci 17:2409-2417, 14], memory [Holscher et al. in Learn Mem 12:450-455, 26], and psychiatric disorders (e.g., [Mick et al. in Am J Med Genet B Neuropsychiatr Genet 147B:1412-1418, 61; Ohtsuki et al. in Schizophr Res 101:9-16, 72; Pergadia et al. in Paper presented at the 38th Annual Meeting of the Behavior Genetics Association, Louisville, Kentucky, USA, 76]. Here, in experiments with mice, we show that (1) Grm7 knockout mice express increased alcohol consumption, (2) sub-congenic, and congenic mice carrying a Grm7 variant characterized by higher Grm7 mRNA drink less alcohol, and show a tendency for higher circadian dark phase motor activity in a wheel running paradigm, respectively, and (3) there are significant genetic differences in Grm7 mRNA abundance in the mouse brain between congenic and background mice identifying brain areas whose function is implicated in addiction related processes. We hypothesize that metabotropic glutamate receptors may function as regulators of homeostasis, and Grm7 (mGluR7) is involved in multiple processes (including stress, circadian activity, reward control, memory, etc.) which interact with substance use and the development of addiction. In conclusion, we suggest that mGluR7 is a significant new therapeutic target in addiction and related neurobehavioral disorders.

Entering the second century of maize quantitative genetics

USDA-ARS?s Scientific Manuscript database

Maize is the most widely grown cereal in the world. In addition to its role in global agriculture, it has also long served as a model organism for genetic research. Maize stands at a genetic crossroads, as it has access to all the tools available for plant genetics but exhibits a genetic architectur...

Genome-wide SNP identification for the construction of a high-resolution genetic map of Japanese flounder (Paralichthys olivaceus): applications to QTL mapping of Vibrio anguillarum disease resistance and comparative genomic analysis

PubMed Central

Shao, Changwei; Niu, Yongchao; Rastas, Pasi; Liu, Yang; Xie, Zhiyuan; Li, Hengde; Wang, Lei; Jiang, Yong; Tai, Shuaishuai; Tian, Yongsheng; Sakamoto, Takashi; Chen, Songlin

2015-01-01

High-resolution genetic maps are essential for fine mapping of complex traits, genome assembly, and comparative genomic analysis. Single-nucleotide polymorphisms (SNPs) are the primary molecular markers used for genetic map construction. In this study, we identified 13,362 SNPs evenly distributed across the Japanese flounder (Paralichthys olivaceus) genome. Of these SNPs, 12,712 high-confidence SNPs were subjected to high-throughput genotyping and assigned to 24 consensus linkage groups (LGs). The total length of the genetic linkage map was 3,497.29 cM with an average distance of 0.47 cM between loci, thereby representing the densest genetic map currently reported for Japanese flounder. Nine positive quantitative trait loci (QTLs) forming two main clusters for Vibrio anguillarum disease resistance were detected. All QTLs could explain 5.1–8.38% of the total phenotypic variation. Synteny analysis of the QTL regions on the genome assembly revealed 12 immune-related genes, among them 4 genes strongly associated with V. anguillarum disease resistance. In addition, 246 genome assembly scaffolds with an average size of 21.79 Mb were anchored onto the LGs; these scaffolds, comprising 522.99 Mb, represented 95.78% of assembled genomic sequences. The mapped assembly scaffolds in Japanese flounder were used for genome synteny analyses against zebrafish (Danio rerio) and medaka (Oryzias latipes). Flounder and medaka were found to possess almost one-to-one synteny, whereas flounder and zebrafish exhibited a multi-syntenic correspondence. The newly developed high-resolution genetic map, which will facilitate QTL mapping, scaffold assembly, and genome synteny analysis of Japanese flounder, marks a milestone in the ongoing genome project for this species. PMID:25762582

The major-effect quantitative trait locus CsARN6.1 encodes an AAA ATPase domain-containing protein that is associated with waterlogging stress tolerance by promoting adventitious root formation

USDA-ARS?s Scientific Manuscript database

In plants, the formation of hypocotyl-derived adventitious roots (AR) is an important morphological acclimation to waterlogging stress, but its genetic basis is largely unknown. In the present study, with combined use of bulked segregant analysis-based high throughput next-gen whole genome sequencin...

A Genome Wide Survey of SNP Variation Reveals the Genetic Structure of Sheep Breeds

USDA-ARS?s Scientific Manuscript database

The genetic structure of sheep reflects their domestication and subsequent formation into discrete breeds. Understanding genetic structure is essential for achieving genetic improvement through genome-wide association studies, genomic selection and the dissection of quantitative traits. After identi...

SoyBase, The USDA-ARS Soybean Genetics and Genomics Database

USDA-ARS?s Scientific Manuscript database

SoyBase, the USDA-ARS soybean genetic database, is a comprehensive repository for professionally curated genetics, genomics and related data resources for soybean. SoyBase contains the most current genetic, physical and genomic sequence maps integrated with qualitative and quantitative traits. The...

Effects of functionally asexual reproduction on quantitative genetic variation in the evening primroses (Oenothera, Onagraceae).

PubMed

Godfrey, Ryan M; Johnson, Marc T J

2014-11-01

It has long been predicted that a loss of sexual reproduction leads to decreased heritable variation within populations and increased differentiation between populations. Despite an abundance of theory, there are few empirical tests of how sex affects genetic variation in phenotypic traits, especially for plants. Here we test whether repeated losses of two critical components of sex (recombination and segregation) in the evening primroses (Oenothera L., Onagraceae) affect quantitative genetic variation within and between populations. We sampled multiple genetic families from 3-5 populations from each of eight Oenothera species, which represented four independent transitions between sexual reproduction and a functionally asexual genetic system called "permanent translocation heterozygosity." We used quantitative genetics methods to partition genetic variation within and between populations for eight plant traits related to growth, leaf physiology, flowering, and resistance to herbivores. Heritability was, on average, 74% higher in sexual Oenothera populations than in functionally asexual populations, with plant growth rate, specific leaf area, and the percentage of leaf water content showing the strongest differences. By contrast, genetic differentiation among populations was 2.8× higher in functionally asexual vs. sexual Oenothera species. This difference was particularly strong for specific leaf area. Sexual populations tended to exhibit higher genetic correlations among traits, but this difference was weakly supported. These results support the prediction that sexual reproduction maintains higher genetic variation within populations, which may facilitate adaptive evolution. We also found partial support for the prediction that a loss of sex leads to greater population differentiation, which may elevate speciation rates. © 2014 Botanical Society of America, Inc.

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.

Is the child 'father of the man'? evaluating the stability of genetic influences across development.

PubMed

Ronald, Angelica

2011-11-01

This selective review considers findings in genetic research that have shed light on how genes operate across development. We will address the question of whether the child is 'father of the Man' from a genetic perspective. In other words, do the same genetic influences affect the same traits across development? Using a 'taster menu' approach and prioritizing newer findings on cognitive and behavioral traits, examples from the following genetic disciplines will be discussed: (a) developmental quantitative genetics (such as longitudinal twin studies), (b) neurodevelopmental genetic syndromes with known genetic causes (such as Williams syndrome), (c) developmental candidate gene studies (such as those that link infant and adult populations), (d) developmental genome-wide association studies (GWAS), and (e) DNA resequencing. Evidence presented here suggests that there is considerable genetic stability of cognitive and behavioral traits across development, but there is also evidence for genetic change. Quantitative genetic studies have a long history of assessing genetic continuity and change across development. It is now time for the newer, more technology-enabled fields such as GWAS and DNA resequencing also to take on board the dynamic nature of human behavior. 2011 Blackwell Publishing Ltd.

A consensus linkage map for molecular markers and Quantitative Trait Loci associated with economically important traits in melon (Cucumis melo L.)

PubMed Central

2011-01-01

Background A number of molecular marker linkage maps have been developed for melon (Cucumis melo L.) over the last two decades. However, these maps were constructed using different marker sets, thus, making comparative analysis among maps difficult. In order to solve this problem, a consensus genetic map in melon was constructed using primarily highly transferable anchor markers that have broad potential use for mapping, synteny, and comparative quantitative trait loci (QTL) analysis, increasing breeding effectiveness and efficiency via marker-assisted selection (MAS). Results Under the framework of the International Cucurbit Genomics Initiative (ICuGI, http://www.icugi.org), an integrated genetic map has been constructed by merging data from eight independent mapping experiments using a genetically diverse array of parental lines. The consensus map spans 1150 cM across the 12 melon linkage groups and is composed of 1592 markers (640 SSRs, 330 SNPs, 252 AFLPs, 239 RFLPs, 89 RAPDs, 15 IMAs, 16 indels and 11 morphological traits) with a mean marker density of 0.72 cM/marker. One hundred and ninety-six of these markers (157 SSRs, 32 SNPs, 6 indels and 1 RAPD) were newly developed, mapped or provided by industry representatives as released markers, including 27 SNPs and 5 indels from genes involved in the organic acid metabolism and transport, and 58 EST-SSRs. Additionally, 85 of 822 SSR markers contributed by Syngenta Seeds were included in the integrated map. In addition, 370 QTL controlling 62 traits from 18 previously reported mapping experiments using genetically diverse parental genotypes were also integrated into the consensus map. Some QTL associated with economically important traits detected in separate studies mapped to similar genomic positions. For example, independently identified QTL controlling fruit shape were mapped on similar genomic positions, suggesting that such QTL are possibly responsible for the phenotypic variability observed for this trait in a broad array of melon germplasm. Conclusions Even though relatively unsaturated genetic maps in a diverse set of melon market types have been published, the integrated saturated map presented herein should be considered the initial reference map for melon. Most of the mapped markers contained in the reference map are polymorphic in diverse collection of germplasm, and thus are potentially transferrable to a broad array of genetic experimentation (e.g., integration of physical and genetic maps, colinearity analysis, map-based gene cloning, epistasis dissection, and marker-assisted selection). PMID:21797998

A consensus linkage map for molecular markers and quantitative trait loci associated with economically important traits in melon (Cucumis melo L.).

PubMed

Diaz, Aurora; Fergany, Mohamed; Formisano, Gelsomina; Ziarsolo, Peio; Blanca, José; Fei, Zhanjun; Staub, Jack E; Zalapa, Juan E; Cuevas, Hugo E; Dace, Gayle; Oliver, Marc; Boissot, Nathalie; Dogimont, Catherine; Pitrat, Michel; Hofstede, René; van Koert, Paul; Harel-Beja, Rotem; Tzuri, Galil; Portnoy, Vitaly; Cohen, Shahar; Schaffer, Arthur; Katzir, Nurit; Xu, Yong; Zhang, Haiying; Fukino, Nobuko; Matsumoto, Satoru; Garcia-Mas, Jordi; Monforte, Antonio J

2011-07-28

A number of molecular marker linkage maps have been developed for melon (Cucumis melo L.) over the last two decades. However, these maps were constructed using different marker sets, thus, making comparative analysis among maps difficult. In order to solve this problem, a consensus genetic map in melon was constructed using primarily highly transferable anchor markers that have broad potential use for mapping, synteny, and comparative quantitative trait loci (QTL) analysis, increasing breeding effectiveness and efficiency via marker-assisted selection (MAS). Under the framework of the International Cucurbit Genomics Initiative (ICuGI, http://www.icugi.org), an integrated genetic map has been constructed by merging data from eight independent mapping experiments using a genetically diverse array of parental lines. The consensus map spans 1150 cM across the 12 melon linkage groups and is composed of 1592 markers (640 SSRs, 330 SNPs, 252 AFLPs, 239 RFLPs, 89 RAPDs, 15 IMAs, 16 indels and 11 morphological traits) with a mean marker density of 0.72 cM/marker. One hundred and ninety-six of these markers (157 SSRs, 32 SNPs, 6 indels and 1 RAPD) were newly developed, mapped or provided by industry representatives as released markers, including 27 SNPs and 5 indels from genes involved in the organic acid metabolism and transport, and 58 EST-SSRs. Additionally, 85 of 822 SSR markers contributed by Syngenta Seeds were included in the integrated map. In addition, 370 QTL controlling 62 traits from 18 previously reported mapping experiments using genetically diverse parental genotypes were also integrated into the consensus map. Some QTL associated with economically important traits detected in separate studies mapped to similar genomic positions. For example, independently identified QTL controlling fruit shape were mapped on similar genomic positions, suggesting that such QTL are possibly responsible for the phenotypic variability observed for this trait in a broad array of melon germplasm. Even though relatively unsaturated genetic maps in a diverse set of melon market types have been published, the integrated saturated map presented herein should be considered the initial reference map for melon. Most of the mapped markers contained in the reference map are polymorphic in diverse collection of germplasm, and thus are potentially transferrable to a broad array of genetic experimentation (e.g., integration of physical and genetic maps, colinearity analysis, map-based gene cloning, epistasis dissection, and marker-assisted selection).

Quantitative and Qualitative Differences in Morphological Traits Revealed between Diploid Fragaria Species

PubMed Central

SARGENT, DANIEL J.; GEIBEL, M.; HAWKINS, J. A.; WILKINSON, M. J.; BATTEY, N. H.; SIMPSON, D. W.

2004-01-01

• Background and Aims The aims of this investigation were to highlight the qualitative and quantitative diversity apparent between nine diploid Fragaria species and produce interspecific populations segregating for a large number of morphological characters suitable for quantitative trait loci analysis. • Methods A qualitative comparison of eight described diploid Fragaria species was performed and measurements were taken of 23 morphological traits from 19 accessions including eight described species and one previously undescribed species. A principal components analysis was performed on 14 mathematically unrelated traits from these accessions, which partitioned the species accessions into distinct morphological groups. Interspecific crosses were performed with accessions of species that displayed significant quantitative divergence and, from these, populations that should segregate for a range of quantitative traits were raised. • Key Results Significant differences between species were observed for all 23 morphological traits quantified and three distinct groups of species accessions were observed after the principal components analysis. Interspecific crosses were performed between these groups, and F2 and backcross populations were raised that should segregate for a range of morphological characters. In addition, the study highlighted a number of distinctive morphological characters in many of the species studied. • Conclusions Diploid Fragaria species are morphologically diverse, yet remain highly interfertile, making the group an ideal model for the study of the genetic basis of phenotypic differences between species through map-based investigation using quantitative trait loci. The segregating interspecific populations raised will be ideal for such investigations and could also provide insights into the nature and extent of genome evolution within this group. PMID:15469944

Genetic and Environmental Influences on Behavior: Capturing All the Interplay

ERIC Educational Resources Information Center

Johnson, Wendy

2007-01-01

Basic quantitative genetic models of human behavioral variation have made clear that individual differences in behavior cannot be understood without acknowledging the importance of genetic influences. Yet these basic models estimate average, population-level genetic and environmental influences, obscuring differences that might exist within the…

Different approaches in Partial Least Squares and Artificial Neural Network models applied for the analysis of a ternary mixture of Amlodipine, Valsartan and Hydrochlorothiazide

NASA Astrophysics Data System (ADS)

Darwish, Hany W.; Hassan, Said A.; Salem, Maissa Y.; El-Zeany, Badr A.

2014-03-01

Different chemometric models were applied for the quantitative analysis of Amlodipine (AML), Valsartan (VAL) and Hydrochlorothiazide (HCT) in ternary mixture, namely, Partial Least Squares (PLS) as traditional chemometric model and Artificial Neural Networks (ANN) as advanced model. PLS and ANN were applied with and without variable selection procedure (Genetic Algorithm GA) and data compression procedure (Principal Component Analysis PCA). The chemometric methods applied are PLS-1, GA-PLS, ANN, GA-ANN and PCA-ANN. The methods were used for the quantitative analysis of the drugs in raw materials and pharmaceutical dosage form via handling the UV spectral data. A 3-factor 5-level experimental design was established resulting in 25 mixtures containing different ratios of the drugs. Fifteen mixtures were used as a calibration set and the other ten mixtures were used as validation set to validate the prediction ability of the suggested methods. The validity of the proposed methods was assessed using the standard addition technique.

Live-cell confocal microscopy and quantitative 4D image analysis of anchor cell invasion through the basement membrane in C. elegans

PubMed Central

Kelley, Laura C.; Wang, Zheng; Hagedorn, Elliott J.; Wang, Lin; Shen, Wanqing; Lei, Shijun; Johnson, Sam A.; Sherwood, David R.

2018-01-01

Cell invasion through basement membrane (BM) barriers is crucial during development, leukocyte trafficking, and for the spread of cancer. Despite its importance in normal and diseased states, the mechanisms that direct invasion are poorly understood, in large part because of the inability to visualize dynamic cell-basement membrane interactions in vivo. This protocol describes multi-channel time-lapse confocal imaging of anchor cell invasion in live C. elegans. Methods presented include outline slide preparation and worm growth synchronization (15 min), mounting (20 min), image acquisition (20-180 min), image processing (20 min), and quantitative analysis (variable timing). Images acquired enable direct measurement of invasive dynamics including invadopodia formation, cell membrane protrusions, and BM removal. This protocol can be combined with genetic analysis, molecular activity probes, and optogenetic approaches to uncover molecular mechanisms underlying cell invasion. These methods can also be readily adapted for real-time analysis of cell migration, basement membrane turnover, and cell membrane dynamics by any worm laboratory. PMID:28880279

A Genome Wide Survey of SNP Variation Reveals the Genetic Structure of Sheep Breeds

PubMed Central

Kijas, James W.; Townley, David; Dalrymple, Brian P.; Heaton, Michael P.; Maddox, Jillian F.; McGrath, Annette; Wilson, Peter; Ingersoll, Roxann G.; McCulloch, Russell; McWilliam, Sean; Tang, Dave; McEwan, John; Cockett, Noelle; Oddy, V. Hutton; Nicholas, Frank W.; Raadsma, Herman

2009-01-01

The genetic structure of sheep reflects their domestication and subsequent formation into discrete breeds. Understanding genetic structure is essential for achieving genetic improvement through genome-wide association studies, genomic selection and the dissection of quantitative traits. After identifying the first genome-wide set of SNP for sheep, we report on levels of genetic variability both within and between a diverse sample of ovine populations. Then, using cluster analysis and the partitioning of genetic variation, we demonstrate sheep are characterised by weak phylogeographic structure, overlapping genetic similarity and generally low differentiation which is consistent with their short evolutionary history. The degree of population substructure was, however, sufficient to cluster individuals based on geographic origin and known breed history. Specifically, African and Asian populations clustered separately from breeds of European origin sampled from Australia, New Zealand, Europe and North America. Furthermore, we demonstrate the presence of stratification within some, but not all, ovine breeds. The results emphasize that careful documentation of genetic structure will be an essential prerequisite when mapping the genetic basis of complex traits. Furthermore, the identification of a subset of SNP able to assign individuals into broad groupings demonstrates even a small panel of markers may be suitable for applications such as traceability. PMID:19270757

Convergent functional genomics in addiction research - a translational approach to study candidate genes and gene networks.

PubMed

Spanagel, Rainer

2013-01-01

Convergent functional genomics (CFG) is a translational methodology that integrates in a Bayesian fashion multiple lines of evidence from studies in human and animal models to get a better understanding of the genetics of a disease or pathological behavior. Here the integration of data sets that derive from forward genetics in animals and genetic association studies including genome wide association studies (GWAS) in humans is described for addictive behavior. The aim of forward genetics in animals and association studies in humans is to identify mutations (e.g. SNPs) that produce a certain phenotype; i.e. "from phenotype to genotype". Most powerful in terms of forward genetics is combined quantitative trait loci (QTL) analysis and gene expression profiling in recombinant inbreed rodent lines or genetically selected animals for a specific phenotype, e.g. high vs. low drug consumption. By Bayesian scoring genomic information from forward genetics in animals is then combined with human GWAS data on a similar addiction-relevant phenotype. This integrative approach generates a robust candidate gene list that has to be functionally validated by means of reverse genetics in animals; i.e. "from genotype to phenotype". It is proposed that studying addiction relevant phenotypes and endophenotypes by this CFG approach will allow a better determination of the genetics of addictive behavior.

Genetic research: who is at risk for alcoholism.

PubMed

Foroud, Tatiana; Edenberg, Howard J; Crabbe, John C

2010-01-01

The National Institute on Alcohol Abuse and Alcoholism (NIAAA) was founded 40 years ago to help elucidate the biological underpinnings of alcohol dependence, including the potential contribution of genetic factors. Twin, adoption, and family studies conclusively demonstrated that genetic factors account for 50 to 60 percent of the variance in risk for developing alcoholism. Case-control studies and linkage analyses have helped identify DNA variants that contribute to increased risk, and the NIAAA-sponsored Collaborative Studies on Genetics of Alcoholism (COGA) has the expressed goal of identifying contributing genes using state-of-the-art genetic technologies. These efforts have ascertained several genes that may contribute to an increased risk of alcoholism, including certain variants encoding alcohol-metabolizing enzymes and neurotransmitter receptors. Genome-wide association studies allowing the analysis of millions of genetic markers located throughout the genome will enable discovery of further candidate genes. In addition to these human studies, genetic animal models of alcohol's effects and alcohol use have greatly advanced our understanding of the genetic basis of alcoholism, resulting in the identification of quantitative trait loci and allowing for targeted manipulation of candidate genes. Novel research approaches-for example, into epigenetic mechanisms of gene regulation-also are under way and undoubtedly will further clarify the genetic basis of alcoholism.

Multivariate genetic architecture of the Anolis dewlap reveals both shared and sex-specific features of a sexually dimorphic ornament.

PubMed

Cox, R M; Costello, R A; Camber, B E; McGlothlin, J W

2017-07-01

Darwin viewed the ornamentation of females as an indirect consequence of sexual selection on males and the transmission of male phenotypes to females via the 'laws of inheritance'. Although a number of studies have supported this view by demonstrating substantial between-sex genetic covariance for ornament expression, the majority of this work has focused on avian plumage. Moreover, few studies have considered the genetic basis of ornaments from a multivariate perspective, which may be crucial for understanding the evolution of sex differences in general, and of complex ornaments in particular. Here, we provide a multivariate, quantitative-genetic analysis of a sexually dimorphic ornament that has figured prominently in studies of sexual selection: the brightly coloured dewlap of Anolis lizards. Using data from a paternal half-sibling breeding experiment in brown anoles (Anolis sagrei), we show that multiple aspects of dewlap size and colour exhibit significant heritability and a genetic variance-covariance structure (G) that is broadly similar in males (G m ) and females (G f ). Whereas sexually monomorphic aspects of the dewlap, such as hue, exhibit significant between-sex genetic correlations (r mf ), sexually dimorphic features, such as area and brightness, exhibit reduced r mf values that do not differ from zero. Using a modified random skewers analysis, we show that the between-sex genetic variance-covariance matrix (B) should not strongly constrain the independent responses of males and females to sexually antagonistic selection. Our microevolutionary analysis is in broad agreement with macroevolutionary perspectives indicating considerable scope for the independent evolution of coloration and ornamentation in males and females. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Segregation of a QTL cluster for home-cage activity using a new mapping method based on regression analysis of congenic mouse strains

PubMed Central

Kato, S; Ishii, A; Nishi, A; Kuriki, S; Koide, T

2014-01-01

Recent genetic studies have shown that genetic loci with significant effects in whole-genome quantitative trait loci (QTL) analyses were lost or weakened in congenic strains. Characterisation of the genetic basis of this attenuated QTL effect is important to our understanding of the genetic mechanisms of complex traits. We previously found that a consomic strain, B6-Chr6CMSM, which carries chromosome 6 of a wild-derived strain MSM/Ms on the genetic background of C57BL/6J, exhibited lower home-cage activity than C57BL/6J. In the present study, we conducted a composite interval QTL analysis using the F2 mice derived from a cross between C57BL/6J and B6-Chr6CMSM. We found one QTL peak that spans 17.6 Mbp of chromosome 6. A subconsomic strain that covers the entire QTL region also showed lower home-cage activity at the same level as the consomic strain. We developed 15 congenic strains, each of which carries a shorter MSM/Ms-derived chromosomal segment from the subconsomic strain. Given that the results of home-cage activity tests on the congenic strains cannot be explained by a simple single-gene model, we applied regression analysis to segregate the multiple genetic loci. The results revealed three loci (loci 1–3) that have the effect of reducing home-cage activity and one locus (locus 4) that increases activity. We also found that the combination of loci 3 and 4 cancels out the effects of the congenic strains, which indicates the existence of a genetic mechanism related to the loss of QTLs. PMID:24781804

The Value of Extended Pedigrees for Next-Generation Analysis of Complex Disease in the Rhesus Macaque

PubMed Central

Vinson, Amanda; Prongay, Kamm; Ferguson, Betsy

2013-01-01

Complex diseases (e.g., cardiovascular disease and type 2 diabetes, among many others) pose the biggest threat to human health worldwide and are among the most challenging to investigate. Susceptibility to complex disease may be caused by multiple genetic variants (GVs) and their interaction, by environmental factors, and by interaction between GVs and environment, and large study cohorts with substantial analytical power are typically required to elucidate these individual contributions. Here, we discuss the advantages of both power and feasibility afforded by the use of extended pedigrees of rhesus macaques (Macaca mulatta) for genetic studies of complex human disease based on next-generation sequence data. We present these advantages in the context of previous research conducted in rhesus macaques for several representative complex diseases. We also describe a single, multigeneration pedigree of Indian-origin rhesus macaques and a sample biobank we have developed for genetic analysis of complex disease, including power of this pedigree to detect causal GVs using either genetic linkage or association methods in a variance decomposition approach. Finally, we summarize findings of significant heritability for a number of quantitative traits that demonstrate that genetic contributions to risk factors for complex disease can be detected and measured in this pedigree. We conclude that the development and application of an extended pedigree to analysis of complex disease traits in the rhesus macaque have shown promising early success and that genome-wide genetic and higher order -omics studies in this pedigree are likely to yield useful insights into the architecture of complex human disease. PMID:24174435

Image analysis of the blood cells for cytomorphodiagnostics and control of the effectiveness treatment

NASA Astrophysics Data System (ADS)

Zhukotsky, Alexander V.; Kogan, Emmanuil M.; Kopylov, Victor F.; Marchenko, Oleg V.; Lomakin, O. A.

1994-07-01

A new method for morphodensitometric analysis of blood cells was applied for medically screening some ecological influence and infection pathologies. A complex algorithm of computational image processing was created for supra molecular restructurings of interphase chromatin of lymphocytes research. It includes specific methods of staining and unifies different quantitative analysis methods. Our experience with the use of a television image analyzer in cytological and immunological studies made it possible to carry out some research in morphometric analysis of chromatin structure in interphase lymphocyte nuclei in genetic and virus pathologies. In our study to characterize lymphocytes as an image-forming system by a rigorous mathematical description we used an approach involving contaminant evaluation of the topography of chromatin network intact and victims' lymphocytes. It is also possible to digitize data, which revealed significant distinctions between control and experiment. The method allows us to observe the minute structural changes in chromatin, especially eu- and hetero-chromatin that were previously studied by genetics only in chromosomes.

A differential mobility spectrometry/mass spectrometry platform for the rapid detection and quantitation of DNA adduct dG-ABP.

PubMed

Kafle, Amol; Klaene, Joshua; Hall, Adam B; Glick, James; Coy, Stephen L; Vouros, Paul

2013-07-15

There is continued interest in exploring new analytical technologies for the detection and quantitation of DNA adducts, biomarkers which provide direct evidence of exposure and genetic damage in cells. With the goal of reducing clean-up steps and improving sample throughput, a Differential Mobility Spectrometry/Mass Spectrometry (DMS/MS) platform has been introduced for adduct analysis. A DMS/MS platform has been utilized for the analysis of dG-ABP, the deoxyguanosine adduct of the bladder carcinogen 4-aminobiphenyl (4-ABP). After optimization of the DMS parameters, each sample was analyzed in just 30 s following a simple protein precipitation step of the digested DNA. A detection limit of one modification in 10^6 nucleosides has been achieved using only 2 µg of DNA. A brief comparison (quantitative and qualitative) with liquid chromatography/mass spectrometry is also presented highlighting the advantages of using the DMS/MS method as a high-throughput platform. The data presented demonstrate the successful application of a DMS/MS/MS platform for the rapid quantitation of DNA adducts using, as a model analyte, the deoxyguanosine adduct of the bladder carcinogen 4-aminobiphenyl. Copyright © 2013 John Wiley & Sons, Ltd.

Eco-genetic modeling of contemporary life-history evolution.

PubMed

Dunlop, Erin S; Heino, Mikko; Dieckmann, Ulf

2009-10-01

We present eco-genetic modeling as a flexible tool for exploring the course and rates of multi-trait life-history evolution in natural populations. We build on existing modeling approaches by combining features that facilitate studying the ecological and evolutionary dynamics of realistically structured populations. In particular, the joint consideration of age and size structure enables the analysis of phenotypically plastic populations with more than a single growth trajectory, and ecological feedback is readily included in the form of density dependence and frequency dependence. Stochasticity and life-history trade-offs can also be implemented. Critically, eco-genetic models permit the incorporation of salient genetic detail such as a population's genetic variances and covariances and the corresponding heritabilities, as well as the probabilistic inheritance and phenotypic expression of quantitative traits. These inclusions are crucial for predicting rates of evolutionary change on both contemporary and longer timescales. An eco-genetic model can be tightly coupled with empirical data and therefore may have considerable practical relevance, in terms of generating testable predictions and evaluating alternative management measures. To illustrate the utility of these models, we present as an example an eco-genetic model used to study harvest-induced evolution of multiple traits in Atlantic cod. The predictions of our model (most notably that harvesting induces a genetic reduction in age and size at maturation, an increase or decrease in growth capacity depending on the minimum-length limit, and an increase in reproductive investment) are corroborated by patterns observed in wild populations. The predicted genetic changes occur together with plastic changes that could phenotypically mask the former. Importantly, our analysis predicts that evolutionary changes show little signs of reversal following a harvest moratorium. This illustrates how predictions offered by eco-genetic models can enable and guide evolutionarily sustainable resource management.

Association between KCNJ11 gene polymorphisms and risk of type 2 diabetes mellitus in East Asian populations: a meta-analysis in 42,573 individuals.

PubMed

Yang, Lijuan; Zhou, Xianghai; Luo, Yingying; Sun, Xiuqin; Tang, Yong; Guo, Wulan; Han, Xueyao; Ji, Linong

2012-01-01

A number of studies have been performed to identify the association between potassium inwardly-rectifying channel, subfamily J, member 11 (KCNJ11) gene and type 2 diabetes mellitus (T2DM) in East Asian populations, with inconsistent results. The main aim of this work was to evaluate more precisely the genetic influence of KCNJ11 on T2DM in East Asian populations by means of a meta-analysis. We identified 20 articles for qualitative analysis and 16 were eligible for quantitative analysis (meta-analysis) by database searching up to May 2010. The association was assessed under different genetic models, and the pooled odds ratios (ORs) with 95% confidence intervals (95% CIs) were calculated. The allelic and genotypic contrast demonstrated that the association between KCNJ11 and T2DM was significant for rs5210. However, not all results for rs5215 and rs5218 showed significant associations. For rs5219, the combined ORs (95% CIs) for allelic contrast, dominant and recessive models contrast (with allelic frequency and genotypic distribution data) were 1.139 (1.093-1.188), 1.177 (1.099-1.259) and 1.207 (1.094-1.332), respectively (random effect model). The analysis on the most completely adjusted ORs (95% CIs) by the covariates of rs5219 all presented significant associations under different genetic models. Population-stratified analysis (Korean, Japanese and Chinese) and sensitivity analysis verified the significant results. Cumulative meta-analysis including publication time and sample size illustrated the exaggerated genetic effect in the earliest studies. Heterogeneity and publication bias were assessed. Our study verified that single nucleotide polymorphisms (SNPs) of KCNJ11 gene were significantly associated with the risk of T2DM in East Asian populations.

Genetic basis in motor skill and hand preference for tool use in chimpanzees (Pan troglodytes).

PubMed

Hopkins, William D; Reamer, Lisa; Mareno, Mary Catherine; Schapiro, Steven J

2015-02-07

Chimpanzees are well known for their tool using abilities. Numerous studies have documented variability in tool use among chimpanzees and the role that social learning and other factors play in their development. There are also findings on hand use in both captive and wild chimpanzees; however, less understood are the potential roles of genetic and non-genetic mechanisms in determining individual differences in tool use skill and laterality. Here, we examined heritability in tool use skill and handedness for a probing task in a sample of 243 captive chimpanzees. Quantitative genetic analysis, based on the extant pedigrees, showed that overall both tool use skill and handedness were significantly heritable. Significant heritability in motor skill was evident in two genetically distinct populations of apes, and between two cohorts that received different early social rearing experiences. We further found that motor skill decreased with age and that males were more commonly left-handed than females. Collectively, these data suggest that though non-genetic factors do influence tool use performance and handedness in chimpanzees, genetic factors also play a significant role, as has been reported in humans. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Multiple capacitors for natural genetic variation in Drosophila melanogaster.

PubMed

Takahashi, Kazuo H

2013-03-01

Cryptic genetic variation (CGV) or a standing genetic variation that is not ordinarily expressed as a phenotype is released when the robustness of organisms is impaired under environmental or genetic perturbations. Evolutionary capacitors modulate the amount of genetic variation exposed to natural selection and hidden cryptically; they have a fundamental effect on the evolvability of traits on evolutionary timescales. In this study, I have demonstrated the effects of multiple genomic regions of Drosophila melanogaster on CGV in wing shape. I examined the effects of 61 genomic deficiencies on quantitative and qualitative natural genetic variation in the wing shape of D. melanogaster. I have identified 10 genomic deficiencies that do not encompass a known candidate evolutionary capacitor, Hsp90, exposing natural CGV differently depending on the location of the deficiencies in the genome. Furthermore, five genomic deficiencies uncovered qualitative CGV in wing morphology. These findings suggest that CGV in wing shape of wild-type D. melanogaster is regulated by multiple capacitors with divergent functions. Future analysis of genes encompassed by these genomic regions would help elucidate novel capacitor genes and better understand the general features of capacitors regarding natural genetic variation. © 2012 Blackwell Publishing Ltd.

Quantitative characterization of genetic parts and circuits for plant synthetic biology.

PubMed

Schaumberg, Katherine A; Antunes, Mauricio S; Kassaw, Tessema K; Xu, Wenlong; Zalewski, Christopher S; Medford, June I; Prasad, Ashok

2016-01-01

Plant synthetic biology promises immense technological benefits, including the potential development of a sustainable bio-based economy through the predictive design of synthetic gene circuits. Such circuits are built from quantitatively characterized genetic parts; however, this characterization is a significant obstacle in work with plants because of the time required for stable transformation. We describe a method for rapid quantitative characterization of genetic plant parts using transient expression in protoplasts and dual luciferase outputs. We observed experimental variability in transient-expression assays and developed a mathematical model to describe, as well as statistical normalization methods to account for, this variability, which allowed us to extract quantitative parameters. We characterized >120 synthetic parts in Arabidopsis and validated our method by comparing transient expression with expression in stably transformed plants. We also tested >100 synthetic parts in sorghum (Sorghum bicolor) protoplasts, and the results showed that our method works in diverse plant groups. Our approach enables the construction of tunable gene circuits in complex eukaryotic organisms.

The genetic architecture of low-temperature adaptation in the wine yeast Saccharomyces cerevisiae.

PubMed

García-Ríos, Estéfani; Morard, Miguel; Parts, Leopold; Liti, Gianni; Guillamón, José M

2017-02-14

Low-temperature growth and fermentation of wine yeast can enhance wine aroma and make them highly desirable traits for the industry. Elucidating response to cold in Saccharomyces cerevisiae is, therefore, of paramount importance to select or genetically improve new wine strains. As most enological traits of industrial importance in yeasts, adaptation to low temperature is a polygenic trait regulated by many interacting loci. In order to unravel the genetic determinants of low-temperature fermentation, we mapped quantitative trait loci (QTLs) by bulk segregant analyses in the F13 offspring of two Saccharomyces cerevisiae industrial strains with divergent performance at low temperature. We detected four genomic regions involved in the adaptation at low temperature, three of them located in the subtelomeric regions (chromosomes XIII, XV and XVI) and one in the chromosome XIV. The QTL analysis revealed that subtelomeric regions play a key role in defining individual variation, which emphasizes the importance of these regions' adaptive nature. The reciprocal hemizygosity analysis (RHA), run to validate the genes involved in low-temperature fermentation, showed that genetic variation in mitochondrial proteins, maintenance of correct asymmetry and distribution of phospholipid in the plasma membrane are key determinants of low-temperature adaptation.

Exploring the interaction among EPHX1, GSTP1, SERPINE2, and TGFB1 contributing to the quantitative traits of chronic obstructive pulmonary disease in Chinese Han population.

PubMed

An, Li; Lin, Yingxiang; Yang, Ting; Hua, Lin

2016-05-18

Currently, the majority of genetic association studies on chronic obstructive pulmonary disease (COPD) risk focused on identifying the individual effects of single nucleotide polymorphisms (SNPs) as well as their interaction effects on the disease. However, conventional genetic studies often use binary disease status as the primary phenotype, but for COPD, many quantitative traits have the potential correlation with the disease status and closely reflect pathological changes. Here, we genotyped 44 SNPs from four genes (EPHX1, GSTP1, SERPINE2, and TGFB1) in 310 patients and 203 controls which belonged to the Chinese Han population to test the two-way and three-way genetic interactions with COPD-related quantitative traits using recently developed generalized multifactor dimensionality reduction (GMDR) and quantitative multifactor dimensionality reduction (QMDR) algorithms. Based on the 310 patients and the whole samples of 513 subjects, the best gene-gene interactions models were detected for four lung-function-related quantitative traits. For the forced expiratory volume in 1 s (FEV1), the best interaction was seen from EPHX1, SERPINE2, and GSTP1. For FEV1%pre, the forced vital capacity (FVC), and FEV1/FVC, the best interactions were seen from SERPINE2 and TGFB1. The results of this study provide further evidence for the genotype combinations at risk of developing COPD in Chinese Han population and improve the understanding on the genetic etiology of COPD and COPD-related quantitative traits.

Population size is weakly related to quantitative genetic variation and trait differentiation in a stream fish.

PubMed

Wood, Jacquelyn L A; Tezel, Defne; Joyal, Destin; Fraser, Dylan J

2015-09-01

How population size influences quantitative genetic variation and differentiation among natural, fragmented populations remains unresolved. Small, isolated populations might occupy poor quality habitats and lose genetic variation more rapidly due to genetic drift than large populations. Genetic drift might furthermore overcome selection as population size decreases. Collectively, this might result in directional changes in additive genetic variation (VA ) and trait differentiation (QST ) from small to large population size. Alternatively, small populations might exhibit larger variation in VA and QST if habitat fragmentation increases variability in habitat types. We explored these alternatives by investigating VA and QST using nine fragmented populations of brook trout varying 50-fold in census size N (179-8416) and 10-fold in effective number of breeders, Nb (18-135). Across 15 traits, no evidence was found for consistent differences in VA and QST with population size and almost no evidence for increased variability of VA or QST estimates at small population size. This suggests that (i) small populations of some species may retain adaptive potential according to commonly adopted quantitative genetic measures and (ii) populations of varying sizes experience a variety of environmental conditions in nature, however extremely large studies are likely required before any firm conclusions can be made. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Genetic variability of VEGF pathway genes in six randomized phase III trials assessing the addition of bevacizumab to standard therapy.

PubMed

de Haas, Sanne; Delmar, Paul; Bansal, Aruna T; Moisse, Matthieu; Miles, David W; Leighl, Natasha; Escudier, Bernard; Van Cutsem, Eric; Carmeliet, Peter; Scherer, Stefan J; Pallaud, Celine; Lambrechts, Diether

2014-10-01

Despite extensive translational research, no validated biomarkers predictive of bevacizumab treatment outcome have been identified. We performed a meta-analysis of individual patient data from six randomized phase III trials in colorectal, pancreatic, lung, renal, breast, and gastric cancer to explore the potential relationships between 195 common genetic variants in the vascular endothelial growth factor (VEGF) pathway and bevacizumab treatment outcome. The analysis included 1,402 patients (716 bevacizumab-treated and 686 placebo-treated). Twenty variants were associated (P < 0.05) with progression-free survival (PFS) in bevacizumab-treated patients. Of these, 4 variants in EPAS1 survived correction for multiple testing (q < 0.05). Genotype-by-treatment interaction tests revealed that, across these 20 variants, 3 variants in VEGF-C (rs12510099), EPAS1 (rs4953344), and IL8RA (rs2234671) were potentially predictive (P < 0.05), but not resistant to multiple testing (q > 0.05). A weak genotype-by-treatment interaction effect was also observed for rs699946 in VEGF-A, whereas Bayesian genewise analysis revealed that genetic variability in VHL was associated with PFS in the bevacizumab arm (q < 0.05). Variants in VEGF-A, EPAS1, and VHL were located in expression quantitative loci derived from lymphoblastoid cell lines, indicating that they affect the expression levels of their respective gene. This large genetic analysis suggests that variants in VEGF-A, EPAS1, IL8RA, VHL, and VEGF-C have potential value in predicting bevacizumab treatment outcome across tumor types. Although these associations did not survive correction for multiple testing in a genotype-by-interaction analysis, they are among the strongest predictive effects reported to date for genetic variants and bevacizumab efficacy.

Making Quantitative Genetics Relevant: Effectiveness of a Laboratory Investigation that Links Scientific Research, Commercial Applications, and Legal Issues

ERIC Educational Resources Information Center

Rutledge, Michael L.; Mathis, Philip M.; Seipelt, Rebecca L.

2005-01-01

As students apply their knowledge of scientific concepts and of science as a method of inquiry, learning becomes relevant. This laboratory exercise is designed to foster students' understanding of the genetics of quantitative traits and of the nature of science as a method of inquiry by engaging them in a real-world business scenario. During the…

Genetic variation for agronomic and fiber quality traits in a population derived from high-quality cotton germplasm

USDA-ARS?s Scientific Manuscript database

Genetic improvement of fiber quality is necessary to meet the requirements of processors and users of cotton fiber. To foster genetic improvement of cotton fiber quality, adequate genetic variation for the quantitatively inherited physical properties of cotton is required. Additionally, knowledge of...

Use of FTA® classic cards for epigenetic analysis of sperm DNA.

PubMed

Serra, Olga; Frazzi, Raffaele; Perotti, Alessio; Barusi, Lorenzo; Buschini, Annamaria

2018-02-01

FTA® technologies provide the most reliable method for DNA extraction. Although FTA technologies have been widely used for genetic analysis, there is no literature on their use for epigenetic analysis yet. We present for the first time, a simple method for quantitative methylation assessment based on sperm cells stored on Whatman FTA classic cards. Specifically, elution of seminal DNA from FTA classic cards was successfully tested with an elution buffer and an incubation step in a thermocycler. The eluted DNA was bisulfite converted, amplified by PCR, and a region of interest was pyrosequenced.

PERCH: A Unified Framework for Disease Gene Prioritization.

PubMed

Feng, Bing-Jian

2017-03-01

To interpret genetic variants discovered from next-generation sequencing, integration of heterogeneous information is vital for success. This article describes a framework named PERCH (Polymorphism Evaluation, Ranking, and Classification for a Heritable trait), available at http://BJFengLab.org/. It can prioritize disease genes by quantitatively unifying a new deleteriousness measure called BayesDel, an improved assessment of the biological relevance of genes to the disease, a modified linkage analysis, a novel rare-variant association test, and a converted variant call quality score. It supports data that contain various combinations of extended pedigrees, trios, and case-controls, and allows for a reduced penetrance, an elevated phenocopy rate, liability classes, and covariates. BayesDel is more accurate than PolyPhen2, SIFT, FATHMM, LRT, Mutation Taster, Mutation Assessor, PhyloP, GERP++, SiPhy, CADD, MetaLR, and MetaSVM. The overall approach is faster and more powerful than the existing quantitative method pVAAST, as shown by the simulations of challenging situations in finding the missing heritability of a complex disease. This framework can also classify variants of unknown significance (variants of uncertain significance) by quantitatively integrating allele frequencies, deleteriousness, association, and co-segregation. PERCH is a versatile tool for gene prioritization in gene discovery research and variant classification in clinical genetic testing. © 2016 The Authors. **Human Mutation published by Wiley Periodicals, Inc.

Genetic variants associated with the root system architecture of oilseed rape (Brassica napus L.) under contrasting phosphate supply.

PubMed

Wang, Xiaohua; Chen, Yanling; Thomas, Catherine L; Ding, Guangda; Xu, Ping; Shi, Dexu; Grandke, Fabian; Jin, Kemo; Cai, Hongmei; Xu, Fangsen; Yi, Bin; Broadley, Martin R; Shi, Lei

2017-08-01

Breeding crops with ideal root system architecture for efficient absorption of phosphorus is an important strategy to reduce the use of phosphate fertilizers. To investigate genetic variants leading to changes in root system architecture, 405 oilseed rape cultivars were genotyped with a 60K Brassica Infinium SNP array in low and high P environments. A total of 285 single-nucleotide polymorphisms were associated with root system architecture traits at varying phosphorus levels. Nine single-nucleotide polymorphisms corroborate a previous linkage analysis of root system architecture quantitative trait loci in the BnaTNDH population. One peak single-nucleotide polymorphism region on A3 was associated with all root system architecture traits and co-localized with a quantitative trait locus for primary root length at low phosphorus. Two more single-nucleotide polymorphism peaks on A5 for root dry weight at low phosphorus were detected in both growth systems and co-localized with a quantitative trait locus for the same trait. The candidate genes identified on A3 form a haplotype 'BnA3Hap', that will be important for understanding the phosphorus/root system interaction and for the incorporation into Brassica napus breeding programs. © The Author 2017. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

In vitro propagation of Rauwolfia serpentina using liquid medium, assessment of genetic fidelity of micropropagated plants, and simultaneous quantitation of reserpine, ajmaline, and ajmalicine.

PubMed

Goel, M K; Mehrotra, S; Kukreja, A K; Shanker, K; Khanuja, S P S

2009-01-01

Rauwolfia serpentina holds an important position in the pharmaceutical world because of its immense anti-hypertensive properties resulting from the presence of reserpine in the oleoresin fraction of the roots. Poor seed viability, low seed germination rate, and enormous genetic variability are the major constraints for the commercial cultivation of R. serpentina through conventional mode. The present optimized protocol offers an impeccable end to end method from the establishment of aseptic cultures to in-vitro plantlet production employing semisolid as well liquid nutrient culture medium and assessment of their genetic fidelity using polymerase chain reaction based rapid amplification of polymorphic DNA analysis. In vitro shoots multiplied on Murashige and Skoog basal liquid nutrients supplemented with benzo[a]pyrene (1.0 mg/L) and NAA (0.1 mg/L) and in-vitro rhizogenesis was observed in modified MS basal nutrient containing NAA (1.0 mg/L) and 2% sucrose. In-vitro raised plants exhibited 90-95% survival under glass house/field condition and 85% similarity in the plants regenerated through this protocol. Field established plants were harvested and extraction of indole alkaloid particularly reserpine, ajmaline and ajmalicine and their simultaneous quantitation was performed using monolithic reverse phase high-performance liquid chromatography (HPLC).

Arms race between selfishness and policing: two-trait quantitative genetic model for caste fate conflict in eusocial Hymenoptera.

PubMed

Dobata, Shigeto

2012-12-01

Policing against selfishness is now regarded as the main force maintaining cooperation, by reducing costly conflict in complex social systems. Although policing has been studied extensively in social insect colonies, its coevolution against selfishness has not been fully captured by previous theories. In this study, I developed a two-trait quantitative genetic model of the conflict between selfish immature females (usually larvae) and policing workers in eusocial Hymenoptera over the immatures' propensity to develop into new queens. This model allows for the analysis of coevolution between genomes expressed in immatures and workers that collectively determine the immatures' queen caste fate. The main prediction of the model is that a higher level of polyandry leads to a smaller fraction of queens produced among new females through caste fate policing. The other main prediction of the present model is that, as a result of arms race, caste fate policing by workers coevolves with exaggerated selfishness of the immatures achieving maximum potential to develop into queens. Moreover, the model can incorporate genetic correlation between traits, which has been largely unexplored in social evolution theory. This study highlights the importance of understanding social traits as influenced by the coevolution of conflicting genomes. © 2012 The Author. Evolution© 2012 The Society for the Study of Evolution.

Quantitative trait loci segregating in crosses between New Hampshire and White Leghorn chicken lines: II. Muscle weight and carcass composition.

PubMed

Nassar, M K; Goraga, Z S; Brockmann, G A

2012-12-01

In order to identify genetic factors influencing muscle weight and carcass composition in chicken, a linkage analysis was performed with 278 F(2) males of reciprocal crosses between the extremely different inbred lines New Hampshire (NHI) and White Leghorn (WL77). The NHI line had been selected for high meat yield and the WL77 for low egg weight before inbreeding. Highly significant quantitative trait loci (QTL) controlling body weight and the weights of carcass, breast muscle, drumsticks-thighs and wings were identified on GGA4 between 151.5 and 160.5 cM and on GGA27 between 4 and 52 cM. These genomic regions explained 13.7-40.2% and 5.3-13.8% of the phenotypic F(2) variances of the corresponding traits respectively. Additional genome-wide highly significant QTL for the weight of drumsticks-thighs were mapped on GGA1, 5 and 7. Moreover, significant QTL controlling body weight were found on GGA2 and 11. The data obtained in this study can be used for increasing the mapping resolution and subsequent gene targeting on GGA4 and 27 by combining data with other crosses where the same QTL were found. © 2012 The Authors, Animal Genetics © 2012 Stichting International Foundation for Animal Genetics.

A novel quadruplex real-time PCR method for simultaneous detection of Cry2Ae and two genetically modified cotton events (GHB119 and T304-40).

PubMed

Li, Xiang; Wang, Xiuxiu; Yang, Jielin; Liu, Yueming; He, Yuping; Pan, Liangwen

2014-05-16

To date, over 150 genetically modified (GM) crops are widely cultivated. To comply with regulations developed for genetically modified organisms (GMOs), including labeling policies, many detection methods for GMO identification and quantification have been developed. To detect the entrance and exit of unauthorized GM crop events in China, we developed a novel quadruplex real-time PCR method for simultaneous detection and quantification of GM cotton events GHB119 and T304-40 in cotton-derived products (based on the 5'-flanking sequence) and the insect-resistance gene Cry2Ae. The limit of detection was 10 copies for GHB119 and Cry2Ae and 25 copies for T304-40. The limit of quantification was 25 copies for GHB119 and Cry2Ae and 50 copies for T304-40. Moreover, low bias and acceptable standard deviation and relative standard deviation values were obtained in quantification analysis of six blind samples containing different GHB119 and T304-40 ingredients. The developed quadruplex quantitative method could be used for quantitative detection of two GM cotton events (GHB119 and T304-40) and Cry2Ae gene ingredient in cotton derived products.

A novel quadruplex real-time PCR method for simultaneous detection of Cry2Ae and two genetically modified cotton events (GHB119 and T304-40)

PubMed Central

2014-01-01

Background To date, over 150 genetically modified (GM) crops are widely cultivated. To comply with regulations developed for genetically modified organisms (GMOs), including labeling policies, many detection methods for GMO identification and quantification have been developed. Results To detect the entrance and exit of unauthorized GM crop events in China, we developed a novel quadruplex real-time PCR method for simultaneous detection and quantification of GM cotton events GHB119 and T304-40 in cotton-derived products (based on the 5′-flanking sequence) and the insect-resistance gene Cry2Ae. The limit of detection was 10 copies for GHB119 and Cry2Ae and 25 copies for T304-40. The limit of quantification was 25 copies for GHB119 and Cry2Ae and 50 copies for T304-40. Moreover, low bias and acceptable standard deviation and relative standard deviation values were obtained in quantification analysis of six blind samples containing different GHB119 and T304-40 ingredients. Conclusions The developed quadruplex quantitative method could be used for quantitative detection of two GM cotton events (GHB119 and T304-40) and Cry2Ae gene ingredient in cotton derived products. PMID:24884946

An independent component analysis confounding factor correction framework for identifying broad impact expression quantitative trait loci

PubMed Central

Ju, Jin Hyun; Crystal, Ronald G.

2017-01-01

Genome-wide expression Quantitative Trait Loci (eQTL) studies in humans have provided numerous insights into the genetics of both gene expression and complex diseases. While the majority of eQTL identified in genome-wide analyses impact a single gene, eQTL that impact many genes are particularly valuable for network modeling and disease analysis. To enable the identification of such broad impact eQTL, we introduce CONFETI: Confounding Factor Estimation Through Independent component analysis. CONFETI is designed to address two conflicting issues when searching for broad impact eQTL: the need to account for non-genetic confounding factors that can lower the power of the analysis or produce broad impact eQTL false positives, and the tendency of methods that account for confounding factors to model broad impact eQTL as non-genetic variation. The key advance of the CONFETI framework is the use of Independent Component Analysis (ICA) to identify variation likely caused by broad impact eQTL when constructing the sample covariance matrix used for the random effect in a mixed model. We show that CONFETI has better performance than other mixed model confounding factor methods when considering broad impact eQTL recovery from synthetic data. We also used the CONFETI framework and these same confounding factor methods to identify eQTL that replicate between matched twin pair datasets in the Multiple Tissue Human Expression Resource (MuTHER), the Depression Genes Networks study (DGN), the Netherlands Study of Depression and Anxiety (NESDA), and multiple tissue types in the Genotype-Tissue Expression (GTEx) consortium. These analyses identified both cis-eQTL and trans-eQTL impacting individual genes, and CONFETI had better or comparable performance to other mixed model confounding factor analysis methods when identifying such eQTL. In these analyses, we were able to identify and replicate a few broad impact eQTL although the overall number was small even when applying CONFETI. In light of these results, we discuss the broad impact eQTL that have been previously reported from the analysis of human data and suggest that considerable caution should be exercised when making biological inferences based on these reported eQTL. PMID:28505156

An independent component analysis confounding factor correction framework for identifying broad impact expression quantitative trait loci.

PubMed

Ju, Jin Hyun; Shenoy, Sushila A; Crystal, Ronald G; Mezey, Jason G

2017-05-01

Genome-wide expression Quantitative Trait Loci (eQTL) studies in humans have provided numerous insights into the genetics of both gene expression and complex diseases. While the majority of eQTL identified in genome-wide analyses impact a single gene, eQTL that impact many genes are particularly valuable for network modeling and disease analysis. To enable the identification of such broad impact eQTL, we introduce CONFETI: Confounding Factor Estimation Through Independent component analysis. CONFETI is designed to address two conflicting issues when searching for broad impact eQTL: the need to account for non-genetic confounding factors that can lower the power of the analysis or produce broad impact eQTL false positives, and the tendency of methods that account for confounding factors to model broad impact eQTL as non-genetic variation. The key advance of the CONFETI framework is the use of Independent Component Analysis (ICA) to identify variation likely caused by broad impact eQTL when constructing the sample covariance matrix used for the random effect in a mixed model. We show that CONFETI has better performance than other mixed model confounding factor methods when considering broad impact eQTL recovery from synthetic data. We also used the CONFETI framework and these same confounding factor methods to identify eQTL that replicate between matched twin pair datasets in the Multiple Tissue Human Expression Resource (MuTHER), the Depression Genes Networks study (DGN), the Netherlands Study of Depression and Anxiety (NESDA), and multiple tissue types in the Genotype-Tissue Expression (GTEx) consortium. These analyses identified both cis-eQTL and trans-eQTL impacting individual genes, and CONFETI had better or comparable performance to other mixed model confounding factor analysis methods when identifying such eQTL. In these analyses, we were able to identify and replicate a few broad impact eQTL although the overall number was small even when applying CONFETI. In light of these results, we discuss the broad impact eQTL that have been previously reported from the analysis of human data and suggest that considerable caution should be exercised when making biological inferences based on these reported eQTL.

Molecular Diagnostics in Colorectal Carcinoma: Advances and Applications for 2018.

PubMed

Bhalla, Amarpreet; Zulfiqar, Muhammad; Bluth, Martin H

2018-06-01

The molecular pathogenesis and classification of colorectal carcinoma are based on the traditional adenomaecarcinoma sequence, serrated polyp pathway, and microsatellite instability (MSI). The genetic basis for hereditary nonpolyposis colorectal cancer is the detection of mutations in the MLH1, MSH2, MSH6, PMS2, and EPCAM genes. Genetic testing for Lynch syndrome includes MSI testing, methylator phenotype testing, BRAF mutation testing, and molecular testing for germline mutations in MMR genes. Molecular makers with predictive and prognostic implications include quantitative multigene reverse transcriptase polymerase chain reaction assay and KRAS and BRAF mutation analysis. Mismatch repair-deficient tumors have higher rates of programmed death-ligand 1 expression. Cell-free DNA analysis in fluids are proving beneficial for diagnosis and prognosis in these disease states towards effective patient management. Copyright © 2018 Elsevier Inc. All rights reserved.

Proton Nuclear Magnetic Resonance-Spectroscopic Discrimination of Wines Reflects Genetic Homology of Several Different Grape (V. vinifera L.) Cultivars

PubMed Central

Zhu, Yong; Wen, Wen; Zhang, Fengmin; Hardie, Jim W.

2015-01-01

Background and Aims Proton nuclear magnetic resonance spectroscopy coupled multivariate analysis (1H NMR-PCA/PLS-DA) is an important tool for the discrimination of wine products. Although 1H NMR has been shown to discriminate wines of different cultivars, a grape genetic component of the discrimination has been inferred only from discrimination of cultivars of undefined genetic homology and in the presence of many confounding environmental factors. We aimed to confirm the influence of grape genotypes in the absence of those factors. Methods and Results We applied 1H NMR-PCA/PLS-DA and hierarchical cluster analysis (HCA) to wines from five, variously genetically-related grapevine (V. vinifera) cultivars; all grown similarly on the same site and vinified similarly. We also compared the semi-quantitative profiles of the discriminant metabolites of each cultivar with previously reported chemical analyses. The cultivars were clearly distinguishable and there was a general correlation between their grouping and their genetic homology as revealed by recent genomic studies. Between cultivars, the relative amounts of several of the cultivar-related discriminant metabolites conformed closely with reported chemical analyses. Conclusions Differences in grape-derived metabolites associated with genetic differences alone are a major source of 1H NMR-based discrimination of wines and 1H NMR has the capacity to discriminate between very closely related cultivars. Significance of the Study The study confirms that genetic variation among grape cultivars alone can account for the discrimination of wine by 1H NMR-PCA/PLS and indicates that 1H NMR spectra of wine of single grape cultivars may in future be used in tandem with hierarchical cluster analysis to elucidate genetic lineages and metabolomic relations of grapevine cultivars. In the absence of genetic information, for example, where predecessor varieties are no longer extant, this may be a particularly useful approach. PMID:26658757

Environmental quality and evolutionary potential: lessons from wild populations

PubMed Central

Charmantier, Anne; Garant, Dany

2005-01-01

An essential requirement to determine a population's potential for evolutionary change is to quantify the amount of genetic variability expressed for traits under selection. Early investigations in laboratory conditions showed that the magnitude of the genetic and environmental components of phenotypic variation can change with environmental conditions. However, there is no consensus as to how the expression of genetic variation is sensitive to different environmental conditions. Recently, the study of quantitative genetics in the wild has been revitalized by new pedigree analyses based on restricted maximum likelihood, resulting in a number of studies investigating these questions in wild populations. Experimental manipulation of environmental quality in the wild, as well as the use of naturally occurring favourable or stressful environments, has broadened the treatment of different taxa and traits. Here, we conduct a meta-analysis on recent studies comparing heritability in favourable versus unfavourable conditions in non-domestic and non-laboratory animals. The results provide evidence for increased heritability in more favourable conditions, significantly so for morphometric traits but not for traits more closely related to fitness. We discuss how these results are explained by underlying changes in variance components, and how they represent a major step in our understanding of evolutionary processes in wild populations. We also show how these trends contrast with the prevailing view resulting mainly from laboratory experiments on Drosophila. Finally, we underline the importance of taking into account the environmental variation in models predicting quantitative trait evolution. PMID:16011915

Genetic Map Construction and Quantitative Trait Locus (QTL) Detection of Growth-Related Traits in Litopenaeus vannamei for Selective Breeding Applications

PubMed Central

Andriantahina, Farafidy; Liu, Xiaolin; Huang, Hao

2013-01-01

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 (MAS) in complex traits as growth. Using an intermediate F2 cross of slow and fast growth parents, a genetic linkage map of Pacific whiteleg shrimp, Litopenaeusvannamei , based on amplified fragment length polymorphisms (AFLP) and simple sequence repeats (SSR) markers was constructed. Meanwhile, QTL analysis was performed for growth-related traits. The linkage map consisted of 451 marker loci (429 AFLPs and 22 SSRs) which formed 49 linkage groups with an average marker space of 7.6 cM; they spanned a total length of 3627.6 cM, covering 79.50% of estimated genome size. 14 QTLs were identified for growth-related traits, including three QTLs for body weight (BW), total length (TL) and partial carapace length (PCL), two QTLs for body length (BL), one QTL for first abdominal segment depth (FASD), third abdominal segment depth (TASD) and first abdominal segment width (FASW), which explained 2.62 to 61.42% of phenotypic variation. Moreover, comparison of linkage maps between L . vannamei and Penaeus japonicus was applied, providing a new insight into the genetic base of QTL affecting the growth-related traits. The new results will be useful for conducting MAS breeding schemes in L . vannamei . PMID:24086466

Genetic Architecture of Micro-Environmental Plasticity in Drosophila melanogaster

PubMed Central

Morgante, Fabio; Sørensen, Peter; Sorensen, Daniel A.; Maltecca, Christian; Mackay, Trudy F. C.

2015-01-01

Individuals of the same genotype do not have the same phenotype for quantitative traits when reared under common macro-environmental conditions, a phenomenon called micro-environmental plasticity. Genetic variation in micro-environmental plasticity is assumed in models of the evolution of phenotypic variance, and is important in applied breeding and personalized medicine. Here, we quantified genetic variation for micro-environmental plasticity for three quantitative traits in the inbred, sequenced lines of the Drosophila melanogaster Genetic Reference Panel. We found substantial genetic variation for micro-environmental plasticity for all traits, with broad sense heritabilities of the same magnitude or greater than those of trait means. Micro-environmental plasticity is not correlated with residual segregating variation, is trait-specific, and has genetic correlations with trait means ranging from zero to near unity. We identified several candidate genes associated with micro-environmental plasticity of startle response, including Drosophila Hsp90, setting the stage for future genetic dissection of this phenomenon. PMID:25943032

Genetic and Dyanmic Analysis of Murine Peak Bone Density

DTIC Science & Technology

1997-10-01

atherosclerosis, obesity, type U diabetes , and osteoporosis. Until recently, mapping genes that underlie quantitative traits was not possible, but in the last...by L- phenylalanine . By the addition of 15mM L- phenylalanine , up to 90% of intestinal alkaline phosphatase can be inhibited without significantly...affecting the skeletal isoenzyme activity. The phenylalanine inhibition assay exhibited intra-assay (n=10) and inter-assay (n=8) variation (CV) between

Genome-wide QTL analysis for anxiety trait in bipolar disorder type I.

PubMed

Contreras, J; Hare, E; Chavarría-Soley, G; Raventós, H

2018-07-01

Genetic studies have been consistent that bipolar disorder type I (BPI) runs in families and that this familial aggregation is strongly influenced by genes. In a preliminary study, we proved that anxiety trait meets endophenotype criteria for BPI. We assessed 619 individuals from the Central Valley of Costa Rica (CVCR) who have received evaluation for anxiety following the same methodological procedure used for the initial pilot study. Our goal was to conduct a multipoint quantitative trait linkage analysis to identify quantitative trait loci (QTLs) related to anxiety trait in subjects with BPI. We conducted the statistical analyses using Quantitative Trait Loci method (Variance-components models), implemented in Sequential Oligogenic Linkage Analysis Routines (SOLAR), using 5606 single nucleotide polymorphism (SNPs). We identified a suggestive linkage signal with a LOD score of 2.01 at chromosome 2 (2q13-q14). Since confounding factors such as substance abuse, medical illness and medication history were not assessed in our study, these conclusions should be taken as preliminary. We conclude that region 2q13-q14 may harbor a candidate gene(s) with an important role in the pathophysiology of BPI and anxiety. Published by Elsevier B.V.

Germplasm-regression-combined (GRC) marker-trait association identification in plant breeding: a challenge for plant biotechnological breeding under soil water deficit conditions.

PubMed

Ruan, Cheng-Jiang; Xu, Xue-Xuan; Shao, Hong-Bo; Jaleel, Cheruth Abdul

2010-09-01

In the past 20 years, the major effort in plant breeding has changed from quantitative to molecular genetics with emphasis on quantitative trait loci (QTL) identification and marker assisted selection (MAS). However, results have been modest. This has been due to several factors including absence of tight linkage QTL, non-availability of mapping populations, and substantial time needed to develop such populations. To overcome these limitations, and as an alternative to planned populations, molecular marker-trait associations have been identified by the combination between germplasm and the regression technique. In the present preview, the authors (1) survey the successful applications of germplasm-regression-combined (GRC) molecular marker-trait association identification in plants; (2) describe how to do the GRC analysis and its differences from mapping QTL based on a linkage map reconstructed from the planned populations; (3) consider the factors that affect the GRC association identification, including selections of optimal germplasm and molecular markers and testing of identification efficiency of markers associated with traits; and (4) finally discuss the future prospects of GRC marker-trait association analysis used in plant MAS/QTL breeding programs, especially in long-juvenile woody plants when no other genetic information such as linkage maps and QTL are available.

Dynamics of plasma proteome during leptin-replacement therapy in genetically based leptin deficiency.

PubMed

Andreev, V P; Dwivedi, R C; Paz-Filho, G; Krokhin, O V; Wong, M-L; Wilkins, J A; Licinio, J

2011-06-01

The effects of leptin-replacement therapy on the plasma proteome of three unique adults with genetically based leptin deficiency were studied longitudinally during the course of recombinant human leptin-replacement treatment. Quantitative proteomics analysis was performed in plasma samples collected during four stages: before leptin treatment was initiated, after 1.5 and 6 years of leptin-replacement treatment, and after 7 weeks of temporary interruption of leptin-replacement therapy. Of 500 proteins reliably identified and quantitated in those four stages, about 100 were differentially abundant twofold or more in one or more stages. Synchronous dynamics of abundances of about 90 proteins was observed reflecting both short- and long-term effects of leptin-replacement therapy. Pathways and processes enriched with overabundant synchronous proteins were cell adhesion, cytoskeleton remodeling, cell cycle, blood coagulation, glycolysis, and gluconeogenesis. Plausible common regulators of the above synchronous proteins were identified using transcription regulation network analysis. The generated network included two transcription factors (c-Myc and androgen receptor) that are known to activate each other through a double-positive feedback loop, which may represent a potential molecular mechanism for the long-term effects of leptin-replacement therapy. Our findings may help to elucidate the effects of leptin on insulin resistance.

Haplotypes in the APOA1-C3-A4-A5 gene cluster affect plasma lipids in both humans and baboons

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

Wang, Qian-fei; Liu, Xin; O'Connell, Jeff

2003-09-15

Genetic studies in non-human primates serve as a potential strategy for identifying genomic intervals where polymorphisms impact upon human disease-related phenotypes. It remains unclear, however, whether independently arising polymorphisms in orthologous regions of non-human primates leads to similar variation in a quantitative trait found in both species. To explore this paradigm, we studied a baboon apolipoprotein gene cluster (APOA1/C3/A4/A5) for which the human gene orthologs have well established roles in influencing plasma HDL-cholesterol and triglyceride concentrations. Our extensive polymorphism analysis of this 68 kb gene cluster in 96 pedigreed baboons identified several haplotype blocks each with limited diversity, consistent withmore » haplotype findings in humans. To determine whether baboons, like humans, also have particular haplotypes associated with lipid phenotypes, we genotyped 634 well characterized baboons using 16 haplotype tagging SNPs. Genetic analysis of single SNPs, as well as haplotypes, revealed an association of APOA5 and APOC3 variants with HDL cholesterol and triglyceride concentrations, respectively. Thus, independent variation in orthologous genomic intervals does associate with similar quantitative lipid traits in both species, supporting the possibility of uncovering human QTL genes in a highly controlled non-human primate model.« less

Transcriptional analysis of the Arabidopsis ovule by massively parallel signature sequencing

PubMed Central

Sánchez-León, Nidia; Arteaga-Vázquez, Mario; Alvarez-Mejía, César; Mendiola-Soto, Javier; Durán-Figueroa, Noé; Rodríguez-Leal, Daniel; Rodríguez-Arévalo, Isaac; García-Campayo, Vicenta; García-Aguilar, Marcelina; Olmedo-Monfil, Vianey; Arteaga-Sánchez, Mario; Martínez de la Vega, Octavio; Nobuta, Kan; Vemaraju, Kalyan; Meyers, Blake C.; Vielle-Calzada, Jean-Philippe

2012-01-01

The life cycle of flowering plants alternates between a predominant sporophytic (diploid) and an ephemeral gametophytic (haploid) generation that only occurs in reproductive organs. In Arabidopsis thaliana, the female gametophyte is deeply embedded within the ovule, complicating the study of the genetic and molecular interactions involved in the sporophytic to gametophytic transition. Massively parallel signature sequencing (MPSS) was used to conduct a quantitative large-scale transcriptional analysis of the fully differentiated Arabidopsis ovule prior to fertilization. The expression of 9775 genes was quantified in wild-type ovules, additionally detecting >2200 new transcripts mapping to antisense or intergenic regions. A quantitative comparison of global expression in wild-type and sporocyteless (spl) individuals resulted in 1301 genes showing 25-fold reduced or null activity in ovules lacking a female gametophyte, including those encoding 92 signalling proteins, 75 transcription factors, and 72 RNA-binding proteins not reported in previous studies based on microarray profiling. A combination of independent genetic and molecular strategies confirmed the differential expression of 28 of them, showing that they are either preferentially active in the female gametophyte, or dependent on the presence of a female gametophyte to be expressed in sporophytic cells of the ovule. Among 18 genes encoding pentatricopeptide-repeat proteins (PPRs) that show transcriptional activity in wild-type but not spl ovules, CIHUATEOTL (At4g38150) is specifically expressed in the female gametophyte and necessary for female gametogenesis. These results expand the nature of the transcriptional universe present in the ovule of Arabidopsis, and offer a large-scale quantitative reference of global expression for future genomic and developmental studies. PMID:22442422

Transcriptional analysis of the Arabidopsis ovule by massively parallel signature sequencing.

PubMed

Sánchez-León, Nidia; Arteaga-Vázquez, Mario; Alvarez-Mejía, César; Mendiola-Soto, Javier; Durán-Figueroa, Noé; Rodríguez-Leal, Daniel; Rodríguez-Arévalo, Isaac; García-Campayo, Vicenta; García-Aguilar, Marcelina; Olmedo-Monfil, Vianey; Arteaga-Sánchez, Mario; de la Vega, Octavio Martínez; Nobuta, Kan; Vemaraju, Kalyan; Meyers, Blake C; Vielle-Calzada, Jean-Philippe

2012-06-01

The life cycle of flowering plants alternates between a predominant sporophytic (diploid) and an ephemeral gametophytic (haploid) generation that only occurs in reproductive organs. In Arabidopsis thaliana, the female gametophyte is deeply embedded within the ovule, complicating the study of the genetic and molecular interactions involved in the sporophytic to gametophytic transition. Massively parallel signature sequencing (MPSS) was used to conduct a quantitative large-scale transcriptional analysis of the fully differentiated Arabidopsis ovule prior to fertilization. The expression of 9775 genes was quantified in wild-type ovules, additionally detecting >2200 new transcripts mapping to antisense or intergenic regions. A quantitative comparison of global expression in wild-type and sporocyteless (spl) individuals resulted in 1301 genes showing 25-fold reduced or null activity in ovules lacking a female gametophyte, including those encoding 92 signalling proteins, 75 transcription factors, and 72 RNA-binding proteins not reported in previous studies based on microarray profiling. A combination of independent genetic and molecular strategies confirmed the differential expression of 28 of them, showing that they are either preferentially active in the female gametophyte, or dependent on the presence of a female gametophyte to be expressed in sporophytic cells of the ovule. Among 18 genes encoding pentatricopeptide-repeat proteins (PPRs) that show transcriptional activity in wild-type but not spl ovules, CIHUATEOTL (At4g38150) is specifically expressed in the female gametophyte and necessary for female gametogenesis. These results expand the nature of the transcriptional universe present in the ovule of Arabidopsis, and offer a large-scale quantitative reference of global expression for future genomic and developmental studies.

A Second-Generation Device for Automated Training and Quantitative Behavior Analyses of Molecularly-Tractable Model Organisms

PubMed Central

Blackiston, Douglas; Shomrat, Tal; Nicolas, Cindy L.; Granata, Christopher; Levin, Michael

2010-01-01

A deep understanding of cognitive processes requires functional, quantitative analyses of the steps leading from genetics and the development of nervous system structure to behavior. Molecularly-tractable model systems such as Xenopus laevis and planaria offer an unprecedented opportunity to dissect the mechanisms determining the complex structure of the brain and CNS. A standardized platform that facilitated quantitative analysis of behavior would make a significant impact on evolutionary ethology, neuropharmacology, and cognitive science. While some animal tracking systems exist, the available systems do not allow automated training (feedback to individual subjects in real time, which is necessary for operant conditioning assays). The lack of standardization in the field, and the numerous technical challenges that face the development of a versatile system with the necessary capabilities, comprise a significant barrier keeping molecular developmental biology labs from integrating behavior analysis endpoints into their pharmacological and genetic perturbations. Here we report the development of a second-generation system that is a highly flexible, powerful machine vision and environmental control platform. In order to enable multidisciplinary studies aimed at understanding the roles of genes in brain function and behavior, and aid other laboratories that do not have the facilities to undergo complex engineering development, we describe the device and the problems that it overcomes. We also present sample data using frog tadpoles and flatworms to illustrate its use. Having solved significant engineering challenges in its construction, the resulting design is a relatively inexpensive instrument of wide relevance for several fields, and will accelerate interdisciplinary discovery in pharmacology, neurobiology, regenerative medicine, and cognitive science. PMID:21179424

Genetic analysis of metabolites in apple fruits indicates an mQTL hotspot for phenolic compounds on linkage group 16

PubMed Central

Khan, Sabaz Ali; Chibon, Pierre-Yves; de Vos, Ric C.H.; Schipper, Bert A.; Walraven, Evert; Beekwilder, Jules; van Dijk, Thijs; Finkers, Richard; Visser, Richard G.F.; van de Weg, Eric W.; Bovy, Arnaud; Cestaro, Alessandro; Velasco, Riccardo; Jacobsen, Evert; Schouten, Henk J.

2012-01-01

Apple (Malus×domestica Borkh) is among the main sources of phenolic compounds in the human diet. The genetic basis of the quantitative variations of these potentially beneficial phenolic compounds was investigated. A segregating F1 population was used to map metabolite quantitative trait loci (mQTLs). Untargeted metabolic profiling of peel and flesh tissues of ripe fruits was performed using liquid chromatography–mass spectrometry (LC-MS), resulting in the detection of 418 metabolites in peel and 254 in flesh. In mQTL mapping using MetaNetwork, 669 significant mQTLs were detected: 488 in the peel and 181 in the flesh. Four linkage groups (LGs), LG1, LG8, LG13, and LG16, were found to contain mQTL hotspots, mainly regulating metabolites that belong to the phenylpropanoid pathway. The genetics of annotated metabolites was studied in more detail using MapQTL®. A number of quercetin conjugates had mQTLs on LG1 or LG13. The most important mQTL hotspot with the largest number of metabolites was detected on LG16: mQTLs for 33 peel-related and 17 flesh-related phenolic compounds. Structural genes involved in the phenylpropanoid biosynthetic pathway were located, using the apple genome sequence. The structural gene leucoanthocyanidin reductase (LAR1) was in the mQTL hotspot on LG16, as were seven transcription factor genes. The authors believe that this is the first time that a QTL analysis was performed on such a high number of metabolites in an outbreeding plant species. PMID:22330898

Genetic and Transcriptomic Bases of Intestinal Epithelial Barrier Dysfunction in Inflammatory Bowel Disease.

PubMed

Vancamelbeke, Maaike; Vanuytsel, Tim; Farré, Ricard; Verstockt, Sare; Ferrante, Marc; Van Assche, Gert; Rutgeerts, Paul; Schuit, Frans; Vermeire, Séverine; Arijs, Ingrid; Cleynen, Isabelle

2017-10-01

Intestinal barrier defects are common in patients with inflammatory bowel disease (IBD). To identify which components could underlie these changes, we performed an in-depth analysis of epithelial barrier genes in IBD. A set of 128 intestinal barrier genes was selected. Polygenic risk scores were generated based on selected barrier gene variants that were associated with Crohn's disease (CD) or ulcerative colitis (UC) in our study. Gene expression was analyzed using microarray and quantitative reverse transcription polymerase chain reaction. Influence of barrier gene variants on expression was studied by cis-expression quantitative trait loci mapping and comparing patients with low- and high-risk scores. Barrier risk scores were significantly higher in patients with IBD than controls. At single-gene level, the associated barrier single-nucleotide polymorphisms were most significantly enriched in PTGER4 for CD and HNF4A for UC. As a group, the regulating proteins were most enriched for CD and UC. Expression analysis showed that many epithelial barrier genes were significantly dysregulated in active CD and UC, with overrepresentation of mucus layer genes. In uninflamed CD ileum and IBD colon, most barrier gene levels restored to normal, except for MUC1 and MUC4 that remained persistently increased compared with controls. Expression levels did not depend on cis-regulatory variants nor combined genetic risk. We found genetic and transcriptomic dysregulations of key epithelial barrier genes and components in IBD. Of these, we believe that mucus genes, in particular MUC1 and MUC4, play an essential role in the pathogenesis of IBD and could represent interesting targets for treatment.

Trabecular bone microarchitecture analysis, a way for an early detection of genetic dwarfism? Case study of a dwarf mother's offspring.

PubMed

Colombo, Antony; Hoogland, Menno; Coqueugniot, Hélène; Dutour, Olivier; Waters-Rist, Andrea

2018-03-01

A 66 year-old woman with a disproportionate dwarfism and who bore seven children was discovered at the Middenbeemster archaeological site (The Netherlands). Three are perinates and show no macroscopic or radiological evidence for a FGFR3 mutation causing hypo-or achondroplasia. This mutation induces dysfunction of the growth cartilage, leading to abnormalities in the development of trabecular bone. Because the mutation is autosomal dominant, these perinates have a 50% risk of having been affected. This study determines whether trabecular bone microarchitecture (TBMA) analysis is useful for detecting genetic dwarfism. Proximal metaphyses of humeri were μCT-scanned with a resolution of 7-12 μm. Three volumes of interest were segmented from each bone with TIVMI© software. The TBMA was quantified in BoneJ© using six parameters on which a multivariate analysis was then performed. Two of the Middenbeemster perinates show a quantitatively different TBMA organization. These results and the family's medical history suggest a diagnosis of genetic dwarfism for this two perinates. This study provides evidence to support the efficacy of μCT for diagnosing early-stage bone disease. Copyright © 2017 Elsevier Inc. All rights reserved.

Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large-scale genetic studies.

PubMed

Atkinson, Jonathan A; Lobet, Guillaume; Noll, Manuel; Meyer, Patrick E; Griffiths, Marcus; Wells, Darren M

2017-10-01

Genetic analyses of plant root systems require large datasets of extracted architectural traits. To quantify such traits from images of root systems, researchers often have to choose between automated tools (that are prone to error and extract only a limited number of architectural traits) or semi-automated ones (that are highly time consuming). We trained a Random Forest algorithm to infer architectural traits from automatically extracted image descriptors. The training was performed on a subset of the dataset, then applied to its entirety. This strategy allowed us to (i) decrease the image analysis time by 73% and (ii) extract meaningful architectural traits based on image descriptors. We also show that these traits are sufficient to identify the quantitative trait loci that had previously been discovered using a semi-automated method. We have shown that combining semi-automated image analysis with machine learning algorithms has the power to increase the throughput of large-scale root studies. We expect that such an approach will enable the quantification of more complex root systems for genetic studies. We also believe that our approach could be extended to other areas of plant phenotyping. © The Authors 2017. Published by Oxford University Press.

A comparative analysis of the effectiveness of cytogenetic and molecular genetic methods in the detection of Down syndrome.

PubMed

Mačkić-Đurović, Mirela; Projić, Petar; Ibrulj, Slavka; Cakar, Jasmina; Marjanović, Damir

2014-05-01

The goal of this study was to examine the effectiveness of 6 STR markers application (D21S1435, D21S11, D21S1270, D21S1411, D21S226 and IFNAR) in molecular genetic diagnostics of Down syndrome (DS) and to compare it with cytogenetic method. Testing was performed on 73 children, with the previously cytogenetically confirmed Down syndrome. DNA isolated from the buccal swab was used. Previously mentioned loci located on chromosome 21 were simultaneously amplified using quantitative fluorescence PCR (QF PCR). Using this method, 60 previously cytogenetically diagnosed DS with standard type of trisomy 21 were confirmed. Furthermore, six of eight children with mosaic type of DS were detected. Two false negative results for mosaic type of DS were obtained. Finally, five children with the translocation type of Down syndrome were also confirmed with this molecular test. In conclusion, molecular genetic analysis of STR loci is fast, cheap and simple method that could be used in detection of DS. Regarding possible false results detected for certain number of mosaic types, cytogenetic analysis should be used as a confirmatory test.

Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large-scale genetic studies

PubMed Central

Atkinson, Jonathan A.; Lobet, Guillaume; Noll, Manuel; Meyer, Patrick E.; Griffiths, Marcus

2017-01-01

Abstract Genetic analyses of plant root systems require large datasets of extracted architectural traits. To quantify such traits from images of root systems, researchers often have to choose between automated tools (that are prone to error and extract only a limited number of architectural traits) or semi-automated ones (that are highly time consuming). We trained a Random Forest algorithm to infer architectural traits from automatically extracted image descriptors. The training was performed on a subset of the dataset, then applied to its entirety. This strategy allowed us to (i) decrease the image analysis time by 73% and (ii) extract meaningful architectural traits based on image descriptors. We also show that these traits are sufficient to identify the quantitative trait loci that had previously been discovered using a semi-automated method. We have shown that combining semi-automated image analysis with machine learning algorithms has the power to increase the throughput of large-scale root studies. We expect that such an approach will enable the quantification of more complex root systems for genetic studies. We also believe that our approach could be extended to other areas of plant phenotyping. PMID:29020748

Genetic Architectures of Quantitative Variation in RNA Editing Pathways

PubMed Central

Gu, Tongjun; Gatti, Daniel M.; Srivastava, Anuj; Snyder, Elizabeth M.; Raghupathy, Narayanan; Simecek, Petr; Svenson, Karen L.; Dotu, Ivan; Chuang, Jeffrey H.; Keller, Mark P.; Attie, Alan D.; Braun, Robert E.; Churchill, Gary A.

2016-01-01

RNA editing refers to post-transcriptional processes that alter the base sequence of RNA. Recently, hundreds of new RNA editing targets have been reported. However, the mechanisms that determine the specificity and degree of editing are not well understood. We examined quantitative variation of site-specific editing in a genetically diverse multiparent population, Diversity Outbred mice, and mapped polymorphic loci that alter editing ratios globally for C-to-U editing and at specific sites for A-to-I editing. An allelic series in the C-to-U editing enzyme Apobec1 influences the editing efficiency of Apob and 58 additional C-to-U editing targets. We identified 49 A-to-I editing sites with polymorphisms in the edited transcript that alter editing efficiency. In contrast to the shared genetic control of C-to-U editing, most of the variable A-to-I editing sites were determined by local nucleotide polymorphisms in proximity to the editing site in the RNA secondary structure. Our results indicate that RNA editing is a quantitative trait subject to genetic variation and that evolutionary constraints have given rise to distinct genetic architectures in the two canonical types of RNA editing. PMID:26614740

Domestication to Crop Improvement: Genetic Resources for Sorghum and Saccharum (Andropogoneae)

PubMed Central

Dillon, Sally L.; Shapter, Frances M.; Henry, Robert J.; Cordeiro, Giovanni; Izquierdo, Liz; Lee, L. Slade

2007-01-01

Background Both sorghum (Sorghum bicolor) and sugarcane (Saccharum officinarum) are members of the Andropogoneae tribe in the Poaceae and are each other's closest relatives amongst cultivated plants. Both are relatively recent domesticates and comparatively little of the genetic potential of these taxa and their wild relatives has been captured by breeding programmes to date. This review assesses the genetic gains made by plant breeders since domestication and the progress in the characterization of genetic resources and their utilization in crop improvement for these two related species. Genetic Resources The genome of sorghum has recently been sequenced providing a great boost to our knowledge of the evolution of grass genomes and the wealth of diversity within S. bicolor taxa. Molecular analysis of the Sorghum genus has identified close relatives of S. bicolor with novel traits, endosperm structure and composition that may be used to expand the cultivated gene pool. Mutant populations (including TILLING populations) provide a useful addition to genetic resources for this species. Sugarcane is a complex polyploid with a large and variable number of copies of each gene. The wild relatives of sugarcane represent a reservoir of genetic diversity for use in sugarcane improvement. Techniques for quantitative molecular analysis of gene or allele copy number in this genetically complex crop have been developed. SNP discovery and mapping in sugarcane has been advanced by the development of high-throughput techniques for ecoTILLING in sugarcane. Genetic linkage maps of the sugarcane genome are being improved for use in breeding selection. The improvement of both sorghum and sugarcane will be accelerated by the incorporation of more diverse germplasm into the domesticated gene pools using molecular tools and the improved knowledge of these genomes. PMID:17766842

Toward Genetics-Based Virus Taxonomy: Comparative Analysis of a Genetics-Based Classification and the Taxonomy of Picornaviruses

PubMed Central

Lauber, Chris

2012-01-01

Virus taxonomy has received little attention from the research community despite its broad relevance. In an accompanying paper (C. Lauber and A. E. Gorbalenya, J. Virol. 86:3890–3904, 2012), we have introduced a quantitative approach to hierarchically classify viruses of a family using pairwise evolutionary distances (PEDs) as a measure of genetic divergence. When applied to the six most conserved proteins of the Picornaviridae, it clustered 1,234 genome sequences in groups at three hierarchical levels (to which we refer as the “GENETIC classification”). In this study, we compare the GENETIC classification with the expert-based picornavirus taxonomy and outline differences in the underlying frameworks regarding the relation of virus groups and genetic diversity that represent, respectively, the structure and content of a classification. To facilitate the analysis, we introduce two novel diagrams. The first connects the genetic diversity of taxa to both the PED distribution and the phylogeny of picornaviruses. The second depicts a classification and the accommodated genetic diversity in a standardized manner. Generally, we found striking agreement between the two classifications on species and genus taxa. A few disagreements concern the species Human rhinovirus A and Human rhinovirus C and the genus Aphthovirus, which were split in the GENETIC classification. Furthermore, we propose a new supergenus level and universal, level-specific PED thresholds, not reached yet by many taxa. Since the species threshold is approached mostly by taxa with large sampling sizes and those infecting multiple hosts, it may represent an upper limit on divergence, beyond which homologous recombination in the six most conserved genes between two picornaviruses might not give viable progeny. PMID:22278238

Toward genetics-based virus taxonomy: comparative analysis of a genetics-based classification and the taxonomy of picornaviruses.

PubMed

Lauber, Chris; Gorbalenya, Alexander E

2012-04-01

Virus taxonomy has received little attention from the research community despite its broad relevance. In an accompanying paper (C. Lauber and A. E. Gorbalenya, J. Virol. 86:3890-3904, 2012), we have introduced a quantitative approach to hierarchically classify viruses of a family using pairwise evolutionary distances (PEDs) as a measure of genetic divergence. When applied to the six most conserved proteins of the Picornaviridae, it clustered 1,234 genome sequences in groups at three hierarchical levels (to which we refer as the "GENETIC classification"). In this study, we compare the GENETIC classification with the expert-based picornavirus taxonomy and outline differences in the underlying frameworks regarding the relation of virus groups and genetic diversity that represent, respectively, the structure and content of a classification. To facilitate the analysis, we introduce two novel diagrams. The first connects the genetic diversity of taxa to both the PED distribution and the phylogeny of picornaviruses. The second depicts a classification and the accommodated genetic diversity in a standardized manner. Generally, we found striking agreement between the two classifications on species and genus taxa. A few disagreements concern the species Human rhinovirus A and Human rhinovirus C and the genus Aphthovirus, which were split in the GENETIC classification. Furthermore, we propose a new supergenus level and universal, level-specific PED thresholds, not reached yet by many taxa. Since the species threshold is approached mostly by taxa with large sampling sizes and those infecting multiple hosts, it may represent an upper limit on divergence, beyond which homologous recombination in the six most conserved genes between two picornaviruses might not give viable progeny.

Biology Undergraduates' Misconceptions about Genetic Drift

ERIC Educational Resources Information Center

Andrews, T. M.; Price, R. M.; Mead, L. S.; McElhinny, T. L.; Thanukos, A.; Perez, K. E.; Herreid, C. F.; Terry, D. R.; Lemons, P. P.

2012-01-01

This study explores biology undergraduates' misconceptions about genetic drift. We use qualitative and quantitative methods to describe students' definitions, identify common misconceptions, and examine differences before and after instruction on genetic drift. We identify and describe five overarching categories that include 16 distinct…

Recent Achievements in Characterizing the Histone Code and Approaches to Integrating Epigenomics and Systems Biology.

PubMed

Janssen, K A; Sidoli, S; Garcia, B A

2017-01-01

Functional epigenetic regulation occurs by dynamic modification of chromatin, including genetic material (i.e., DNA methylation), histone proteins, and other nuclear proteins. Due to the highly complex nature of the histone code, mass spectrometry (MS) has become the leading technique in identification of single and combinatorial histone modifications. MS has now overcome antibody-based strategies due to its automation, high resolution, and accurate quantitation. Moreover, multiple approaches to analysis have been developed for global quantitation of posttranslational modifications (PTMs), including large-scale characterization of modification coexistence (middle-down and top-down proteomics), which is not currently possible with any other biochemical strategy. Recently, our group and others have simplified and increased the effectiveness of analyzing histone PTMs by improving multiple MS methods and data analysis tools. This review provides an overview of the major achievements in the analysis of histone PTMs using MS with a focus on the most recent improvements. We speculate that the workflow for histone analysis at its state of the art is highly reliable in terms of identification and quantitation accuracy, and it has the potential to become a routine method for systems biology thanks to the possibility of integrating histone MS results with genomics and proteomics datasets. © 2017 Elsevier Inc. All rights reserved.

Quantitative Analysis of Food and Feed Samples with Droplet Digital PCR

PubMed Central

Morisset, Dany; Štebih, Dejan; Milavec, Mojca; Gruden, Kristina; Žel, Jana

2013-01-01

In this study, the applicability of droplet digital PCR (ddPCR) for routine analysis in food and feed samples was demonstrated with the quantification of genetically modified organisms (GMOs). Real-time quantitative polymerase chain reaction (qPCR) is currently used for quantitative molecular analysis of the presence of GMOs in products. However, its use is limited for detecting and quantifying very small numbers of DNA targets, as in some complex food and feed matrices. Using ddPCR duplex assay, we have measured the absolute numbers of MON810 transgene and hmg maize reference gene copies in DNA samples. Key performance parameters of the assay were determined. The ddPCR system is shown to offer precise absolute and relative quantification of targets, without the need for calibration curves. The sensitivity (five target DNA copies) of the ddPCR assay compares well with those of individual qPCR assays and of the chamber digital PCR (cdPCR) approach. It offers a dynamic range over four orders of magnitude, greater than that of cdPCR. Moreover, when compared to qPCR, the ddPCR assay showed better repeatability at low target concentrations and a greater tolerance to inhibitors. Finally, ddPCR throughput and cost are advantageous relative to those of qPCR for routine GMO quantification. It is thus concluded that ddPCR technology can be applied for routine quantification of GMOs, or any other domain where quantitative analysis of food and feed samples is needed. PMID:23658750

Regression and Data Mining Methods for Analyses of Multiple Rare Variants in the Genetic Analysis Workshop 17 Mini-Exome Data

PubMed Central

Bailey-Wilson, Joan E.; Brennan, Jennifer S.; Bull, Shelley B; Culverhouse, Robert; Kim, Yoonhee; Jiang, Yuan; Jung, Jeesun; Li, Qing; Lamina, Claudia; Liu, Ying; Mägi, Reedik; Niu, Yue S.; Simpson, Claire L.; Wang, Libo; Yilmaz, Yildiz E.; Zhang, Heping; Zhang, Zhaogong

2012-01-01

Group 14 of Genetic Analysis Workshop 17 examined several issues related to analysis of complex traits using DNA sequence data. These issues included novel methods for analyzing rare genetic variants in an aggregated manner (often termed collapsing rare variants), evaluation of various study designs to increase power to detect effects of rare variants, and the use of machine learning approaches to model highly complex heterogeneous traits. Various published and novel methods for analyzing traits with extreme locus and allelic heterogeneity were applied to the simulated quantitative and disease phenotypes. Overall, we conclude that power is (as expected) dependent on locus-specific heritability or contribution to disease risk, large samples will be required to detect rare causal variants with small effect sizes, extreme phenotype sampling designs may increase power for smaller laboratory costs, methods that allow joint analysis of multiple variants per gene or pathway are more powerful in general than analyses of individual rare variants, population-specific analyses can be optimal when different subpopulations harbor private causal mutations, and machine learning methods may be useful for selecting subsets of predictors for follow-up in the presence of extreme locus heterogeneity and large numbers of potential predictors. PMID:22128066

Analysis of spatial heterogeneity in normal epithelium and preneoplastic alterations in mouse prostate tumor models

PubMed Central

Valkonen, Mira; Ruusuvuori, Pekka; Kartasalo, Kimmo; Nykter, Matti; Visakorpi, Tapio; Latonen, Leena

2017-01-01

Cancer involves histological changes in tissue, which is of primary importance in pathological diagnosis and research. Automated histological analysis requires ability to computationally separate pathological alterations from normal tissue with all its variables. On the other hand, understanding connections between genetic alterations and histological attributes requires development of enhanced analysis methods suitable also for small sample sizes. Here, we set out to develop computational methods for early detection and distinction of prostate cancer-related pathological alterations. We use analysis of features from HE stained histological images of normal mouse prostate epithelium, distinguishing the descriptors for variability between ventral, lateral, and dorsal lobes. In addition, we use two common prostate cancer models, Hi-Myc and Pten+/− mice, to build a feature-based machine learning model separating the early pathological lesions provoked by these genetic alterations. This work offers a set of computational methods for separation of early neoplastic lesions in the prostates of model mice, and provides proof-of-principle for linking specific tumor genotypes to quantitative histological characteristics. The results obtained show that separation between different spatial locations within the organ, as well as classification between histologies linked to different genetic backgrounds, can be performed with very high specificity and sensitivity. PMID:28317907

A rat genetic map constructed by representational difference analysis markers with suitability for large-scale typing.

PubMed Central

Toyota, M; Canzian, F; Ushijima, T; Hosoya, Y; Kuramoto, T; Serikawa, T; Imai, K; Sugimura, T; Nagao, M

1996-01-01

Representational difference analysis (RDA) was applied to isolate chromosomal markers in the rat. Four series of RDA [restriction enzymes, BamHI and HindIII; subtraction of ACI/N (ACI) amplicon from BUF/Nac (BUF) amplicon and vice versa] yielded 131 polymorphic markers; 125 of these markers were mapped to all chromosomes except for chromosome X. This was done by using a mapping panel of 105 ACI x BUF F2 rats. To complement the relative paucity of chromosomal markers in the rat, genetically directed RDA, which allows isolation of polymorphic markers in the specific chromosomal region, was performed. By changing the F2 driver-DNA allele frequency around the region, four markers were isolated from the D1Ncc1 locus. Twenty-five of 27 RDA markers were informative regarding the dot blot analysis of amplicons, hybridizing only with tester amplicons. Dot blot analysis at a high density per unit of area made it possible to process a large number of samples. Quantitative trait loci can now be mapped in the rat genome by processing a large number of samples with RDA markers and then by isolating markers close to the loci of interest by genetically directed RDA. Images Fig. 1 Fig. 3 Fig. 4 PMID:8632989

MutAIT: an online genetic toxicology data portal and analysis tools.

PubMed

Avancini, Daniele; Menzies, Georgina E; Morgan, Claire; Wills, John; Johnson, George E; White, Paul A; Lewis, Paul D

2016-05-01

Assessment of genetic toxicity and/or carcinogenic activity is an essential element of chemical screening programs employed to protect human health. Dose-response and gene mutation data are frequently analysed by industry, academia and governmental agencies for regulatory evaluations and decision making. Over the years, a number of efforts at different institutions have led to the creation and curation of databases to house genetic toxicology data, largely, with the aim of providing public access to facilitate research and regulatory assessments. This article provides a brief introduction to a new genetic toxicology portal called Mutation Analysis Informatics Tools (MutAIT) (www.mutait.org) that provides easy access to two of the largest genetic toxicology databases, the Mammalian Gene Mutation Database (MGMD) and TransgenicDB. TransgenicDB is a comprehensive collection of transgenic rodent mutation data initially compiled and collated by Health Canada. The updated MGMD contains approximately 50 000 individual mutation spectral records from the published literature. The portal not only gives access to an enormous quantity of genetic toxicology data, but also provides statistical tools for dose-response analysis and calculation of benchmark dose. Two important R packages for dose-response analysis are provided as web-distributed applications with user-friendly graphical interfaces. The 'drsmooth' package performs dose-response shape analysis and determines various points of departure (PoD) metrics and the 'PROAST' package provides algorithms for dose-response modelling. The MutAIT statistical tools, which are currently being enhanced, provide users with an efficient and comprehensive platform to conduct quantitative dose-response analyses and determine PoD values that can then be used to calculate human exposure limits or margins of exposure. © The Author 2015. Published by Oxford University Press on behalf of the UK Environmental Mutagen Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Generalist Genes: Genetic Links between Brain, Mind, and Education

ERIC Educational Resources Information Center

Plomin, Robert; Kovas, Yulia; Haworth, Claire M. A.

2007-01-01

Genetics contributes importantly to learning abilities and disabilities--not just to reading, the target of most genetic research, but also to mathematics and other academic areas as well. One of the most important recent findings from quantitative genetic research such as twin studies is that the same set of genes is largely responsible for…

Genetic and environmental factors affecting early rooting of six Populus genomic groups: implications for tree improvement

Treesearch

Ronald S., Jr. Zalesny

2006-01-01

Genetic and environmental factors affect the early rooting of Populus planted as unrooted hardwood cuttings. Populus genotypes of six genomic groups were tested in numerous studies for the quantitative genetics of rooting, along with effects of preplanting treatments and soil temperature. Genetics data (e.g. heritabilities,...

Genetic and Environmental Influences on Negative Life Events from Late Childhood to Adolescence

ERIC Educational Resources Information Center

Johnson, Daniel P.; Rhee, Soo Hyun; Whisman, Mark A.; Corley, Robin P.; Hewitt, John K.

2013-01-01

This multiwave longitudinal study tested two quantitative genetic developmental models to examine genetic and environmental influences on exposure to negative dependent and independent life events. Participants (N = 457 twin pairs) completed measures of life events annually from ages 9 to 16. The same genetic factors influenced exposure to…

High-performance single cell genetic analysis using microfluidic emulsion generator arrays.

PubMed

Zeng, Yong; Novak, Richard; Shuga, Joe; Smith, Martyn T; Mathies, Richard A

2010-04-15

High-throughput genetic and phenotypic analysis at the single cell level is critical to advance our understanding of the molecular mechanisms underlying cellular function and dysfunction. Here we describe a high-performance single cell genetic analysis (SCGA) technique that combines high-throughput microfluidic emulsion generation with single cell multiplex polymerase chain reaction (PCR). Microfabricated emulsion generator array (MEGA) devices containing 4, 32, and 96 channels are developed to confer a flexible capability of generating up to 3.4 x 10(6) nanoliter-volume droplets per hour. Hybrid glass-polydimethylsiloxane diaphragm micropumps integrated into the MEGA chips afford uniform droplet formation, controlled generation frequency, and effective transportation and encapsulation of primer functionalized microbeads and cells. A multiplex single cell PCR method is developed to detect and quantify both wild type and mutant/pathogenic cells. In this method, microbeads functionalized with multiple forward primers targeting specific genes from different cell types are used for solid-phase PCR in droplets. Following PCR, the droplets are lysed and the beads are pooled and rapidly analyzed by multicolor flow cytometry. Using Escherichia coli bacterial cells as a model, we show that this technique enables digital detection of pathogenic E. coli O157 cells in a high background of normal K12 cells, with a detection limit on the order of 1/10(5). This result demonstrates that multiplex SCGA is a promising tool for high-throughput quantitative digital analysis of genetic variation in complex populations.

High-Performance Single Cell Genetic Analysis Using Microfluidic Emulsion Generator Arrays

PubMed Central

Zeng, Yong; Novak, Richard; Shuga, Joe; Smith, Martyn T.; Mathies, Richard A.

2010-01-01

High-throughput genetic and phenotypic analysis at the single cell level is critical to advance our understanding of the molecular mechanisms underlying cellular function and dysfunction. Here we describe a high-performance single cell genetic analysis (SCGA) technique that combines high-throughput microfluidic emulsion generation with single cell multiplex PCR. Microfabricated emulsion generator array (MEGA) devices containing 4, 32 and 96 channels are developed to confer a flexible capability of generating up to 3.4 × 106 nanoliter-volume droplets per hour. Hybrid glass-polydimethylsiloxane diaphragm micropumps integrated into the MEGA chips afford uniform droplet formation, controlled generation frequency, and effective transportation and encapsulation of primer functionalized microbeads and cells. A multiplex single cell PCR method is developed to detect and quantify both wild type and mutant/pathogenic cells. In this method, microbeads functionalized with multiple forward primers targeting specific genes from different cell types are used for solid-phase PCR in droplets. Following PCR, the droplets are lysed, the beads are pooled and rapidly analyzed by multi-color flow cytometry. Using E. coli bacterial cells as a model, we show that this technique enables digital detection of pathogenic E. coli O157 cells in a high background of normal K12 cells, with a detection limit on the order of 1:105. This result demonstrates that multiplex SCGA is a promising tool for high-throughput quantitative digital analysis of genetic variation in complex populations. PMID:20192178

Mapping X-Disease Phytoplasma Resistance in Prunus virginiana

PubMed Central

Lenz, Ryan R.; Dai, Wenhao

2017-01-01

Phytoplasmas such as “Candidatus Phytoplasma pruni,” the causal agent of X-disease of stone fruits, lack detailed biological analysis. This has limited the understanding of plant resistance mechanisms. Chokecherry (Prunus virginiana L.) is a promising model to be used for the plant-phytoplasma interaction due to its documented ability to resist X-disease infection. A consensus chokecherry genetic map “Cho” was developed with JoinMap 4.0 by joining two parental maps. The new map contains a complete set of 16 linkage groups, spanning a genetic distance of 2,172 cM with an average marker density of 3.97 cM. Three significant quantitative trait loci (QTL) associated with X-disease resistance were identified contributing to a total of 45.9% of the phenotypic variation. This updated genetic linkage map and the identified QTL will provide the framework needed to facilitate molecular genetics, genomics, breeding, and biotechnology research concerning X-disease in chokecherry and other Prunus species. PMID:29238359

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.

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

Efficient and accurate causal inference with hidden confounders from genome-transcriptome variation data

PubMed Central

2017-01-01

Mapping gene expression as a quantitative trait using whole genome-sequencing and transcriptome analysis allows to discover the functional consequences of genetic variation. We developed a novel method and ultra-fast software Findr for higly accurate causal inference between gene expression traits using cis-regulatory DNA variations as causal anchors, which improves current methods by taking into consideration hidden confounders and weak regulations. Findr outperformed existing methods on the DREAM5 Systems Genetics challenge and on the prediction of microRNA and transcription factor targets in human lymphoblastoid cells, while being nearly a million times faster. Findr is publicly available at https://github.com/lingfeiwang/findr. PMID:28821014

SCOPA and META-SCOPA: software for the analysis and aggregation of genome-wide association studies of multiple correlated phenotypes.

PubMed

Mägi, Reedik; Suleimanov, Yury V; Clarke, Geraldine M; Kaakinen, Marika; Fischer, Krista; Prokopenko, Inga; Morris, Andrew P

2017-01-11

Genome-wide association studies (GWAS) of single nucleotide polymorphisms (SNPs) have been successful in identifying loci contributing genetic effects to a wide range of complex human diseases and quantitative traits. The traditional approach to GWAS analysis is to consider each phenotype separately, despite the fact that many diseases and quantitative traits are correlated with each other, and often measured in the same sample of individuals. Multivariate analyses of correlated phenotypes have been demonstrated, by simulation, to increase power to detect association with SNPs, and thus may enable improved detection of novel loci contributing to diseases and quantitative traits. We have developed the SCOPA software to enable GWAS analysis of multiple correlated phenotypes. The software implements "reverse regression" methodology, which treats the genotype of an individual at a SNP as the outcome and the phenotypes as predictors in a general linear model. SCOPA can be applied to quantitative traits and categorical phenotypes, and can accommodate imputed genotypes under a dosage model. The accompanying META-SCOPA software enables meta-analysis of association summary statistics from SCOPA across GWAS. Application of SCOPA to two GWAS of high-and low-density lipoprotein cholesterol, triglycerides and body mass index, and subsequent meta-analysis with META-SCOPA, highlighted stronger association signals than univariate phenotype analysis at established lipid and obesity loci. The META-SCOPA meta-analysis also revealed a novel signal of association at genome-wide significance for triglycerides mapping to GPC5 (lead SNP rs71427535, p = 1.1x10 -8 ), which has not been reported in previous large-scale GWAS of lipid traits. The SCOPA and META-SCOPA software enable discovery and dissection of multiple phenotype association signals through implementation of a powerful reverse regression approach.

Genetic Mapping in Mice Reveals the Involvement of Pcdh9 in Long-Term Social and Object Recognition and Sensorimotor Development.

PubMed

Bruining, Hilgo; Matsui, Asuka; Oguro-Ando, Asami; Kahn, René S; Van't Spijker, Heleen M; Akkermans, Guus; Stiedl, Oliver; van Engeland, Herman; Koopmans, Bastijn; van Lith, Hein A; Oppelaar, Hugo; Tieland, Liselotte; Nonkes, Lourens J; Yagi, Takeshi; Kaneko, Ryosuke; Burbach, J Peter H; Yamamoto, Nobuhiko; Kas, Martien J

2015-10-01

Quantitative genetic analysis of basic mouse behaviors is a powerful tool to identify novel genetic phenotypes contributing to neurobehavioral disorders. Here, we analyzed genetic contributions to single-trial, long-term social and nonsocial recognition and subsequently studied the functional impact of an identified candidate gene on behavioral development. Genetic mapping of single-trial social recognition was performed in chromosome substitution strains, a sophisticated tool for detecting quantitative trait loci (QTL) of complex traits. Follow-up occurred by generating and testing knockout (KO) mice of a selected QTL candidate gene. Functional characterization of these mice was performed through behavioral and neurological assessments across developmental stages and analyses of gene expression and brain morphology. Chromosome substitution strain 14 mapping studies revealed an overlapping QTL related to long-term social and object recognition harboring Pcdh9, a cell-adhesion gene previously associated with autism spectrum disorder. Specific long-term social and object recognition deficits were confirmed in homozygous (KO) Pcdh9-deficient mice, while heterozygous mice only showed long-term social recognition impairment. The recognition deficits in KO mice were not associated with alterations in perception, multi-trial discrimination learning, sociability, behavioral flexibility, or fear memory. Rather, KO mice showed additional impairments in sensorimotor development reflected by early touch-evoked biting, rotarod performance, and sensory gating deficits. This profile emerged with structural changes in deep layers of sensory cortices, where Pcdh9 is selectively expressed. This behavior-to-gene study implicates Pcdh9 in cognitive functions required for long-term social and nonsocial recognition. This role is supported by the involvement of Pcdh9 in sensory cortex development and sensorimotor phenotypes. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Hd6, a rice quantitative trait locus involved in photoperiod sensitivity, encodes the α subunit of protein kinase CK2

PubMed Central

Takahashi, Yuji; Shomura, Ayahiko; Sasaki, Takuji; Yano, Masahiro

2001-01-01

Hd6 is a quantitative trait locus involved in rice photoperiod sensitivity. It was detected in backcross progeny derived from a cross between the japonica variety Nipponbare and the indica variety Kasalath. To isolate a gene at Hd6, we used a large segregating population for the high-resolution and fine-scale mapping of Hd6 and constructed genomic clone contigs around the Hd6 region. Linkage analysis with P1-derived artificial chromosome clone-derived DNA markers delimited Hd6 to a 26.4-kb genomic region. We identified a gene encoding the α subunit of protein kinase CK2 (CK2α) in this region. The Nipponbare allele of CK2α contains a premature stop codon, and the resulting truncated product is undoubtedly nonfunctional. Genetic complementation analysis revealed that the Kasalath allele of CK2α increases days-to-heading. Map-based cloning with advanced backcross progeny enabled us to identify a gene underlying a quantitative trait locus even though it exhibited a relatively small effect on the phenotype. PMID:11416158

USE OF GENOTOXIC ACTIVITY PROFILES IN ASSESSMENT OF CARCINOGENESIS AND TRANSMISSIBLE GENETIC EFFECTS

EPA Science Inventory

A methodology has been developed to display and evaluate multiple test quantitative information on genetic toxicants for purposes of assessing carcinogenesis and transmissible genetic effects. ose Information is collected from the open literature: either the lowest effective dose...

Eye regression in blind Astyanax cavefish may facilitate the evolution of an adaptive behavior and its sensory receptors.

PubMed

Borowsky, Richard

2013-07-11

The forces driving the evolutionary loss or simplification of traits such as vision and pigmentation in cave animals are still debated. Three alternative hypotheses are direct selection against the trait, genetic drift, and indirect selection due to antagonistic pleiotropy. Recent work establishes that Astyanax cavefish exhibit vibration attraction behavior (VAB), a presumed behavioral adaptation to finding food in the dark not exhibited by surface fish. Genetic analysis revealed two regions in the genome with quantitative trait loci (QTL) for both VAB and eye size. These observations were interpreted as genetic evidence that selection for VAB indirectly drove eye regression through antagonistic pleiotropy and, further, that this is a general mechanism to account for regressive evolution. These conclusions are unsupported by the data; the analysis fails to establish pleiotropy and ignores the numerous other QTL that map to, and potentially interact, in the same regions. It is likely that all three forces drive evolutionary change. We will be able to distinguish among them in individual cases only when we have identified the causative alleles and characterized their effects.

Genetic analysis of arsenic accumulation in maize using QTL mapping

NASA Astrophysics Data System (ADS)

Fu, Zhongjun; Li, Weihua; Xing, Xiaolong; Xu, Mengmeng; Liu, Xiaoyang; Li, Haochuan; Xue, Yadong; Liu, Zonghua; Tang, Jihua

2016-02-01

Arsenic (As) is a toxic heavy metal that can accumulate in crops and poses a threat to human health. The genetic mechanism of As accumulation is unclear. Herein, we used quantitative trait locus (QTL) mapping to unravel the genetic basis of As accumulation in a maize recombinant inbred line population derived from the Chinese crossbred variety Yuyu22. The kernels had the lowest As content among the different maize tissues, followed by the axes, stems, bracts and leaves. Fourteen QTLs were identified at each location. Some of these QTLs were identified in different environments and were also detected by joint analysis. Compared with the B73 RefGen v2 reference genome, the distributions and effects of some QTLs were closely linked to those of QTLs detected in a previous study; the QTLs were likely in strong linkage disequilibrium. Our findings could be used to help maintain maize production to satisfy the demand for edible corn and to decrease the As content in As-contaminated soil through the selection and breeding of As pollution-safe cultivars.

Genetic analysis of arsenic accumulation in maize using QTL mapping.

PubMed

Fu, Zhongjun; Li, Weihua; Xing, Xiaolong; Xu, Mengmeng; Liu, Xiaoyang; Li, Haochuan; Xue, Yadong; Liu, Zonghua; Tang, Jihua

2016-02-16

Arsenic (As) is a toxic heavy metal that can accumulate in crops and poses a threat to human health. The genetic mechanism of As accumulation is unclear. Herein, we used quantitative trait locus (QTL) mapping to unravel the genetic basis of As accumulation in a maize recombinant inbred line population derived from the Chinese crossbred variety Yuyu22. The kernels had the lowest As content among the different maize tissues, followed by the axes, stems, bracts and leaves. Fourteen QTLs were identified at each location. Some of these QTLs were identified in different environments and were also detected by joint analysis. Compared with the B73 RefGen v2 reference genome, the distributions and effects of some QTLs were closely linked to those of QTLs detected in a previous study; the QTLs were likely in strong linkage disequilibrium. Our findings could be used to help maintain maize production to satisfy the demand for edible corn and to decrease the As content in As-contaminated soil through the selection and breeding of As pollution-safe cultivars.

Quantitative analysis of production traits in saltwater crocodiles (Crocodylus porosus): II. age at slaughter.

PubMed

Isberg, S R; Thomson, P C; Nicholas, F W; Barker, S G; Moran, C

2005-12-01

Crocodile morphometric (head, snout-vent and total length) measurements were recorded at three stages during the production chain: hatching, inventory [average age (+/-SE) is 265.1 +/- 0.4 days] and slaughter (average age is 1037.8 +/- 0.4 days). Crocodile skins are used for the manufacture of exclusive leather products, with the most common-sized skin sold having 35-45 cm in belly width. One of the breeding objectives for inclusion into a multitrait genetic improvement programme for saltwater crocodiles is the time taken for a juvenile to reach this size or age at slaughter. A multivariate restricted maximum likelihood analysis provided (co)variance components for estimating the first published genetic parameter estimates for these traits. Heritability (+/-SE) estimates for the traits hatchling snout-vent length, inventory head length and age at slaughter were 0.60 (0.15), 0.59 (0.12) and 0.40 (0.10) respectively. There were strong negative genetic (-0.81 +/- 0.08) and phenotypic (-0.82 +/- 0.02) correlations between age at slaughter and inventory head length.

The efficiency of close inbreeding to reduce genetic adaptation to captivity

PubMed Central

Theodorou, K; Couvet, D

2015-01-01

Although ex situ conservation is indispensable for thousands of species, captive breeding is associated with negative genetic changes: loss of genetic variance and genetic adaptation to captivity that is deleterious in the wild. We used quantitative genetic individual-based simulations to model the effect of genetic management on the evolution of a quantitative trait and the associated fitness of wild-born individuals that are brought to captivity. We also examined the feasibility of the breeding strategies under a scenario of a large number of loci subject to deleterious mutations. We compared two breeding strategies: repeated half-sib mating and a method of minimizing mean coancestry (referred to as gc/mc). Our major finding was that half-sib mating is more effective in reducing genetic adaptation to captivity than the gc/mc method. Moreover, half-sib mating retains larger allelic and adaptive genetic variance. Relative to initial standing variation, the additive variance of the quantitative trait increased under half-sib mating during the sojourn in captivity. Although fragmentation into smaller populations improves the efficiency of the gc/mc method, half-sib mating still performs better in the scenarios tested. Half-sib mating shows two caveats that could mitigate its beneficial effects: low heterozygosity and high risk of extinction when populations are of low fecundity and size and one of the following conditions are met: (i) the strength of selection in captivity is comparable with that in the wild, (ii) deleterious mutations are numerous and only slightly deleterious. Experimental validation of half-sib mating is therefore needed for the advancement of captive breeding programs. PMID:25052417

Genetic variance of tolerance and the toxicant threshold model.

PubMed

Tanaka, Yoshinari; Mano, Hiroyuki; Tatsuta, Haruki

2012-04-01

A statistical genetics method is presented for estimating the genetic variance (heritability) of tolerance to pollutants on the basis of a standard acute toxicity test conducted on several isofemale lines of cladoceran species. To analyze the genetic variance of tolerance in the case when the response is measured as a few discrete states (quantal endpoints), the authors attempted to apply the threshold character model in quantitative genetics to the threshold model separately developed in ecotoxicology. The integrated threshold model (toxicant threshold model) assumes that the response of a particular individual occurs at a threshold toxicant concentration and that the individual tolerance characterized by the individual's threshold value is determined by genetic and environmental factors. As a case study, the heritability of tolerance to p-nonylphenol in the cladoceran species Daphnia galeata was estimated by using the maximum likelihood method and nested analysis of variance (ANOVA). Broad-sense heritability was estimated to be 0.199 ± 0.112 by the maximum likelihood method and 0.184 ± 0.089 by ANOVA; both results implied that the species examined had the potential to acquire tolerance to this substance by evolutionary change. Copyright © 2012 SETAC.

Exploration of the Genetic Organization of Morphological Modularity on the Mouse Mandible Using a Set of Interspecific Recombinant Congenic Strains Between C57BL/6 and Mice of the Mus spretus Species

PubMed Central

Burgio, Gaëtan; Baylac, Michel; Heyer, Evelyne; Montagutelli, Xavier

2012-01-01

Morphological integration and modularity within semi-autonomous modules are essential mechanisms for the evolution of morphological traits. However, the genetic makeup responsible for the control of variational modularity is still relatively unknown. In our study, we tested the hypothesis that the genetic variation for mandible shape clustered into two morphogenetic components: the alveolar group and the ascending ramus. We used the mouse as a model system to investigate genetics determinants of mandible shape. To do this, we used a combination of geometric morphometric tools and a set of 18 interspecific recombinant congenic strains (IRCS) derived from the distantly related species, Mus spretus SEG/Pas and Mus musculus C57BL/6. Quantitative trait loci (QTL) analysis comparing mandible morphometry between the C57BL/6 and the IRCSs identified 42 putative SEG/Pas segments responsible for the genetic variation. The magnitude of the QTL effects was dependent on the proportion of SEG/Pas genome inherited. Using a multivariate correlation coefficient adapted for modularity assessment and a two-block partial least squares analysis to explore the morphological integration, we found that these QTL clustered into two well-integrated morphogenetic groups, corresponding to the ascending ramus and the alveolar region. Together, these results provide evidence that the mouse mandible is subjected to genetic coordination in a modular manner. PMID:23050236

[Detection of genetically modified soy (Roundup-Ready) in processed food products].

PubMed

Hagen, M; Beneke, B

2000-01-01

In this study, the application of a qualitative and a quantitative method of analysis to detect genetically modified RR-Soy (Roundup-Ready Soy) in processed foods is described. A total of 179 various products containing soy such as baby food and diet products, soy drinks and desserts, tofu and tofu products, soy based meat substitutes, soy protein, breads, flour, granules, cereals, noodles, soy bean sprouts, fats and oils as well as condiments were investigated following the pattern of the section 35 LMBG-method L 23.01.22-1. The DNA was extracted from the samples and analysed using a soybean specific lectin gene PCR as well as a PCR, specific for the genetic modification. Additional, by means of PCR in combination with fluorescence-detection (TaqMan 5'-Nuclease Assay), suspicious samples were subjected to a real-time quantification of the percentage of genetically modified RR-Soy. The methods of analysis proved to be extremely sensitive and specific in regard to the food groups checked. The fats and oils, as well as the condiments were the exceptions in which amplifiable soy DNA could not be detected. The genetic modification of RR-Soy was detected in 34 samples. Eight of these samples contained more than 1% of RR-Soy. It is necessary to determine the percentage of transgenic soy in order to assess whether genetically modified ingredients were deliberately added, or whether they were caused by technically unavoidable contamination (for example during transportation and processing).

The genetics of muscle atrophy and growth: the impact and implications of polymorphisms in animals and humans.

PubMed

Gordon, Erynn S; Gordish Dressman, Heather A; Hoffman, Eric P

2005-10-01

Much of the vast diversity we see in animals and people is governed by genetic loci that have quantitative effects of phenotype (quantitative trait loci; QTLs). Here we review the current knowledge of the genetics of atrophy and hypertrophy in both animal husbandry (meat quantity and quality), and humans (muscle size and performance). The selective breeding of animals for meat has apparently led to a few genetic loci with strong effects, with different loci in different animals. In humans, muscle quantitative trait loci (QTLs) appear to be more complex, with few "major" loci identified to date, although this is likely to change in the near future. We describe how the same phenotypic traits we see as positive, greater lean muscle mass in cattle or a better exercise results in humans, can also have negative "side effects" given specific environmental challenges. We also discuss the strength and limitations of single nucleotide polymorphisms (SNP) association studies; what the reader should look for and expect in a published study. Lastly we discuss the ethical and societal implications of this genetic information. As more and more research into the genetic loci that dictate phenotypic traits become available, the ethical implications of testing for these loci become increasingly important. As a society, most accept testing for genetic diseases or susceptibility, but do we as easily accept testing to determine one's athletic potential to be an Olympic endurance runner, or quarterback on the high school football team.

Metabolomics and In-Silico Analysis Reveal Critical Energy Deregulations in Animal Models of Parkinson’s Disease

PubMed Central

Poliquin, Pierre O.; Chen, Jingkui; Cloutier, Mathieu; Trudeau, Louis-Éric; Jolicoeur, Mario

2013-01-01

Parkinson’s disease (PD) is a multifactorial disease known to result from a variety of factors. Although age is the principal risk factor, other etiological mechanisms have been identified, including gene mutations and exposure to toxins. Deregulation of energy metabolism, mostly through the loss of complex I efficiency, is involved in disease progression in both the genetic and sporadic forms of the disease. In this study, we investigated energy deregulation in the cerebral tissue of animal models (genetic and toxin induced) of PD using an approach that combines metabolomics and mathematical modelling. In a first step, quantitative measurements of energy-related metabolites in mouse brain slices revealed most affected pathways. A genetic model of PD, the Park2 knockout, was compared to the effect of CCCP, a complex I blocker. Model simulated and experimental results revealed a significant and sustained decrease in ATP after CCCP exposure, but not in the genetic mice model. In support to data analysis, a mathematical model of the relevant metabolic pathways was developed and calibrated onto experimental data. In this work, we show that a short-term stress response in nucleotide scavenging is most probably induced by the toxin exposure. In turn, the robustness of energy-related pathways in the model explains how genetic perturbations, at least in young animals, are not sufficient to induce significant changes at the metabolite level. PMID:23935941

Identification of successive flowering phases highlights a new genetic control of the flowering pattern in strawberry

PubMed Central

Perrotte, Justine; Guédon, Yann; Gaston, Amèlia; Denoyes, Béatrice

2016-01-01

The genetic control of the switch between seasonal and perpetual flowering has been deciphered in various perennial species. However, little is known about the genetic control of the dynamics of perpetual flowering, which changes abruptly at well-defined time instants during the growing season. Here, we characterize the perpetual flowering pattern and identify new genetic controls of this pattern in the cultivated strawberry. Twenty-one perpetual flowering strawberry genotypes were phenotyped at the macroscopic scale for their course of emergence of inflorescences and stolons during the growing season. A longitudinal analysis based on the segmentation of flowering rate profiles using multiple change-point models was conducted. The flowering pattern of perpetual flowering genotypes takes the form of three or four successive phases: an autumn-initiated flowering phase, a flowering pause, and a single stationary perpetual flowering phase or two perpetual flowering phases, the second one being more intense. The genetic control of flowering was analysed by quantitative trait locus mapping of flowering traits based on these flowering phases. We showed that the occurrence of a fourth phase of intense flowering is controlled by a newly identified locus, different from the locus FaPFRU, controlling the switch between seasonal and perpetual flowering behaviour. The role of this locus was validated by the analysis of data obtained previously during six consecutive years. PMID:27664957

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

A rapid generalized least squares model for a genome-wide quantitative trait association analysis in families.

PubMed

Li, Xiang; Basu, Saonli; Miller, Michael B; Iacono, William G; McGue, Matt

2011-01-01

Genome-wide association studies (GWAS) using family data involve association analyses between hundreds of thousands of markers and a trait for a large number of related individuals. The correlations among relatives bring statistical and computational challenges when performing these large-scale association analyses. Recently, several rapid methods accounting for both within- and between-family variation have been proposed. However, these techniques mostly model the phenotypic similarities in terms of genetic relatedness. The familial resemblances in many family-based studies such as twin studies are not only due to the genetic relatedness, but also derive from shared environmental effects and assortative mating. In this paper, we propose 2 generalized least squares (GLS) models for rapid association analysis of family-based GWAS, which accommodate both genetic and environmental contributions to familial resemblance. In our first model, we estimated the joint genetic and environmental variations. In our second model, we estimated the genetic and environmental components separately. Through simulation studies, we demonstrated that our proposed approaches are more powerful and computationally efficient than a number of existing methods are. We show that estimating the residual variance-covariance matrix in the GLS models without SNP effects does not lead to an appreciable bias in the p values as long as the SNP effect is small (i.e. accounting for no more than 1% of trait variance). Copyright © 2011 S. Karger AG, Basel.

Multivariate Analysis of the Cotton Seed Ionome Reveals a Shared Genetic Architecture

PubMed Central

Pauli, Duke; Ziegler, Greg; Ren, Min; Jenks, Matthew A.; Hunsaker, Douglas J.; Zhang, Min; Baxter, Ivan; Gore, Michael A.

2018-01-01

To mitigate the effects of heat and drought stress, a better understanding of the genetic control of physiological responses to these environmental conditions is needed. To this end, we evaluated an upland cotton (Gossypium hirsutum L.) mapping population under water-limited and well-watered conditions in a hot, arid environment. The elemental concentrations (ionome) of seed samples from the population were profiled in addition to those of soil samples taken from throughout the field site to better model environmental variation. The elements profiled in seeds exhibited moderate to high heritabilities, as well as strong phenotypic and genotypic correlations between elements that were not altered by the imposed irrigation regimes. Quantitative trait loci (QTL) mapping results from a Bayesian classification method identified multiple genomic regions where QTL for individual elements colocalized, suggesting that genetic control of the ionome is highly interrelated. To more fully explore this genetic architecture, multivariate QTL mapping was implemented among groups of biochemically related elements. This analysis revealed both additional and pleiotropic QTL responsible for coordinated control of phenotypic variation for elemental accumulation. Machine learning algorithms that utilized only ionomic data predicted the irrigation regime under which genotypes were evaluated with very high accuracy. Taken together, these results demonstrate the extent to which the seed ionome is genetically interrelated and predictive of plant physiological responses to adverse environmental conditions. PMID:29437829

Lost in Translation? A Comparison of Cancer-Genetics Reporting in the Press Release and its Subsequent Coverage in Lay Press1

PubMed Central

Brechman, Jean M.; Lee, Chul-joo; Cappella, Joseph N.

2014-01-01

Understanding how genetic science is communicated to the lay public is of great import, given that media coverage of genetics is increasing exponentially and that the ways in which discoveries are presented in the news can have significant effects on a variety of health outcomes. To address this issue, this study examines the presentation of genetic research relating to cancer outcomes and behaviors (i.e., prostate cancer, breast cancer, colon cancer, smoking and obesity) in both the press release (N = 23) and its subsequent news coverage (N = 71) by using both quantitative content analysis and qualitative textual analysis. In contrast to earlier studies reporting that news stories often misrepresent genetics by presenting biologically deterministic and simplified portrayals (e.g., Mountcastle-Shah et al., 2003; Ten Eych & Williment, 2003), our data shows no clear trends in the direction of distortion toward deterministic claims in news articles. Also, other errors commonly attributed to science journalism, such as lack of qualifying details and use of oversimplified language (e.g., “fat gene”) are observed in press releases. These findings suggest that the intermediary press release rather than news coverage may serve as a source of distortion in the dissemination of science to the lay public. The implications of this study for future research in this area are discussed. PMID:25568611

Genetic basis of climatic adaptation in scots pine by bayesian quantitative trait locus analysis.

PubMed Central

Hurme, P; Sillanpää, M J; Arjas, E; Repo, T; Savolainen, O

2000-01-01

We examined the genetic basis of large adaptive differences in timing of bud set and frost hardiness between natural populations of Scots pine. As a mapping population, we considered an "open-pollinated backcross" progeny by collecting seeds of a single F(1) tree (cross between trees from southern and northern Finland) growing in southern Finland. Due to the special features of the design (no marker information available on grandparents or the father), we applied a Bayesian quantitative trait locus (QTL) mapping method developed previously for outcrossed offspring. We found four potential QTL for timing of bud set and seven for frost hardiness. Bayesian analyses detected more QTL than ANOVA for frost hardiness, but the opposite was true for bud set. These QTL included alleles with rather large effects, and additionally smaller QTL were supported. The largest QTL for bud set date accounted for about a fourth of the mean difference between populations. Thus, natural selection during adaptation has resulted in selection of at least some alleles of rather large effect. PMID:11063704

Genetic Regulation of Hypothalamic Cocaine and Amphetamine-Regulated Transcript (CART) in BxD Inbred Mice

PubMed Central

Hawks, Brian W.; Li, Wei; Garlow, Steven J.

2009-01-01

Cocaine-Amphetamine Regulated Transcript (CART) peptides are implicated in a wide range of behaviors including in the reinforcing properties of psychostimulants, feeding and energy balance and stress and anxiety responses. We conducted a complex trait analysis to examine natural variation in the regulation of CART transcript abundance (CARTta) in the hypothalamus. CART transcript abundance was measured in total hypothalamic RNA from 26 BxD recombinant inbred (RI) mouse strains and in the C57BL/6 (B6) and DBA/2J (D2) progenitor strains. The strain distribution pattern for CARTta was continuous across the RI panel, which is consistent with this being a quantitative trait. Marker regression and interval mapping revealed significant quantitative trait loci (QTL) on mouse chromosome 4 (around 58.2cM) and chromosome 11 (between 20–36cM) that influence CARTta and account for 31% of the between strain variance in this phenotype. There are numerous candidate genes and QTL in these chromosomal regions that may indicate shared genetic regulation between CART expression and other neurobiological processes referable to known actions of this neuropeptide. PMID:18199428

Quantitative proteomic analysis of human breast epithelial cells with differential telomere length

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

Yu, Li-Rong; Chan, King C.; Tahara, Hidetoshi

Telomeres play important functional roles in cell proliferation, cell cycle regulation, and genetic stability, in which telomere length is critical. In this study, quantitative proteome comparisons for the human breast epithelial cells with short and long telomeres (184-hTERT{sub L} vs. 184-hTERT{sub S} and 90P-hTERT{sub L} vs. 90P-hTERT{sub S}), resulting from transfection of the human telomerase reverse transcriptase (hTERT) gene, were performed using cleavable isotope-coded affinity tags. More than 2000 proteins were quantified in each comparative experiment, with approximately 77% of the proteins identified in both analyses. In the cells with long telomeres, significant and consistent alterations were observed in metabolismmore » (amino acid, nucleotide, and lipid metabolism), genetic information transmission (transcription and translation regulation, spliceosome and ribosome complexes), and cell signaling. Interestingly, the DNA excision repair pathway is enhanced, while integrin and its ligands are downregulated in the cells with long telomeres. These results may provide valuable information related to telomere functions.« less

Genetic Architecture of Local Adaptation in Lunar and Diurnal Emergence Times of the Marine Midge Clunio marinus (Chironomidae, Diptera)

PubMed Central

Kaiser, Tobias S.; Heckel, David G.

2012-01-01

Circadian rhythms pre-adapt the physiology of most organisms to predictable daily changes in the environment. Some marine organisms also show endogenous circalunar rhythms. The genetic basis of the circalunar clock and its interaction with the circadian clock is unknown. Both clocks can be studied in the marine midge Clunio marinus (Chironomidae, Diptera), as different populations have different local adaptations in their lunar and diurnal rhythms of adult emergence, which can be analyzed by crossing experiments. We investigated the genetic basis of population variation in clock properties by constructing the first genetic linkage map for this species, and performing quantitative trait locus (QTL) analysis on variation in both lunar and diurnal timing. The genome has a genetic length of 167–193 centimorgans based on a linkage map using 344 markers, and a physical size of 95–140 megabases estimated by flow cytometry. Mapping the sex determining locus shows that females are the heterogametic sex, unlike most other Chironomidae. We identified two QTL each for lunar emergence time and diurnal emergence time. The distribution of QTL confirms a previously hypothesized genetic basis to a correlation of lunar and diurnal emergence times in natural populations. Mapping of clock genes and light receptors identified ciliary opsin 2 (cOps2) as a candidate to be involved in both lunar and diurnal timing; cryptochrome 1 (cry1) as a candidate gene for lunar timing; and two timeless (tim2, tim3) genes as candidate genes for diurnal timing. This QTL analysis of lunar rhythmicity, the first in any species, provides a unique entree into the molecular analysis of the lunar clock. PMID:22384150

Genetic architecture of local adaptation in lunar and diurnal emergence times of the marine midge Clunio marinus (Chironomidae, Diptera).

PubMed

Kaiser, Tobias S; Heckel, David G

2012-01-01

Circadian rhythms pre-adapt the physiology of most organisms to predictable daily changes in the environment. Some marine organisms also show endogenous circalunar rhythms. The genetic basis of the circalunar clock and its interaction with the circadian clock is unknown. Both clocks can be studied in the marine midge Clunio marinus (Chironomidae, Diptera), as different populations have different local adaptations in their lunar and diurnal rhythms of adult emergence, which can be analyzed by crossing experiments. We investigated the genetic basis of population variation in clock properties by constructing the first genetic linkage map for this species, and performing quantitative trait locus (QTL) analysis on variation in both lunar and diurnal timing. The genome has a genetic length of 167-193 centimorgans based on a linkage map using 344 markers, and a physical size of 95-140 megabases estimated by flow cytometry. Mapping the sex determining locus shows that females are the heterogametic sex, unlike most other Chironomidae. We identified two QTL each for lunar emergence time and diurnal emergence time. The distribution of QTL confirms a previously hypothesized genetic basis to a correlation of lunar and diurnal emergence times in natural populations. Mapping of clock genes and light receptors identified ciliary opsin 2 (cOps2) as a candidate to be involved in both lunar and diurnal timing; cryptochrome 1 (cry1) as a candidate gene for lunar timing; and two timeless (tim2, tim3) genes as candidate genes for diurnal timing. This QTL analysis of lunar rhythmicity, the first in any species, provides a unique entree into the molecular analysis of the lunar clock.

Mapping Genes that Contribute to Daunorubicin-Induced Cytotoxicity

PubMed Central

Duan, Shiwei; Bleibel, Wasim K.; Huang, Rong Stephanie; Shukla, Sunita J.; Wu, Xiaolin; Badner, Judith A.; Dolan, M. Eileen

2009-01-01

Daunorubicin is an anthracycline antibiotic agent used in the treatment of hematopoietic malignancies. Toxicities associated with this agent include myelosuppression and cardiotoxicity; however, the genes or genetic determinants that contribute to these toxicities are unknown. We present an unbiased genome-wide approach that incorporates heritability, whole-genome linkage analysis, and linkage-directed association to uncover genetic variants contributing to the sensitivity to daunorubicin-induced cytotoxicity. Cell growth inhibition in 324 Centre d’ Etude du Polymorphisme Humain lymphoblastoid cell lines (24 pedigrees) was evaluated following treatment with daunorubicin for 72 h. Heritability analysis showed a significant genetic component contributing to the cytotoxic phenotypes (h2 = 0.18–0.63at 0.0125, 0.025, 0.05, 0.1, 0.2, and 1.0 µmol/L daunorubicin and at the IC50, the dose required to inhibit 50% cell growth). Whole-genome linkage scans at all drug concentrations and IC50 uncovered 11 regions with moderate peak LOD scores (>1.5), including 4q28.2 to 4q32.3 with a maximum LOD score of 3.18. The quantitative transmission disequilibrium tests were done using 31,312 high-frequency single-nucleotide polymorphisms (SNP) located in the 1 LOD confidence interval of these 11 regions. Thirty genes were identified as significantly associated with daunorubicin-induced cytotoxicity (P ≤ 2.0 × 10−4, false discovery rate ≤ 0.1). Pathway and functional gene ontology analysis showed that these genes were overrepresented in the phosphatidylinositol signaling system, axon guidance pathway, and GPI-anchored proteins family. Our findings suggest that a proportion of susceptibility to daunorubicin-induced cytotoxicity may be controlled by genetic determinants and that analysis using linkage-directed association studies with dense SNP markers can be used to identify the genetic variants contributing to cytotoxicity. PMID:17545624

TANGO: a generic tool for high-throughput 3D image analysis for studying nuclear organization.

PubMed

Ollion, Jean; Cochennec, Julien; Loll, François; Escudé, Christophe; Boudier, Thomas

2013-07-15

The cell nucleus is a highly organized cellular organelle that contains the genetic material. The study of nuclear architecture has become an important field of cellular biology. Extracting quantitative data from 3D fluorescence imaging helps understand the functions of different nuclear compartments. However, such approaches are limited by the requirement for processing and analyzing large sets of images. Here, we describe Tools for Analysis of Nuclear Genome Organization (TANGO), an image analysis tool dedicated to the study of nuclear architecture. TANGO is a coherent framework allowing biologists to perform the complete analysis process of 3D fluorescence images by combining two environments: ImageJ (http://imagej.nih.gov/ij/) for image processing and quantitative analysis and R (http://cran.r-project.org) for statistical processing of measurement results. It includes an intuitive user interface providing the means to precisely build a segmentation procedure and set-up analyses, without possessing programming skills. TANGO is a versatile tool able to process large sets of images, allowing quantitative study of nuclear organization. TANGO is composed of two programs: (i) an ImageJ plug-in and (ii) a package (rtango) for R. They are both free and open source, available (http://biophysique.mnhn.fr/tango) for Linux, Microsoft Windows and Macintosh OSX. Distribution is under the GPL v.2 licence. thomas.boudier@snv.jussieu.fr Supplementary data are available at Bioinformatics online.

Adaptive potential of northernmost tree populations to climate change, with emphasis on Scots pine (Pinus sylvestris L.).

PubMed

Savolainen, Outi; Kujala, Sonja T; Sokol, Catherina; Pyhäjärvi, Tanja; Avia, Komlan; Knürr, Timo; Kärkkäinen, Katri; Hicks, Sheila

2011-01-01

The adaptive potential of the northernmost Pinus sylvestris L. (and other northern tree) populations is considered by examining first the current patterns of quantitative genetic adaptive traits, which show high population differentiation and clines. We then consider the postglacial history of the populations using both paleobiological and genetic data. The current patterns of diversity at nuclear genes suggest that the traces of admixture are mostly visible in mitochondrial DNA variation patterns. There is little evidence of increased diversity due to admixture between an eastern and western colonization lineage, but no signal of reduced diversity (due to sequential bottlenecks) either. Quantitative trait variation in the north is not associated with the colonizing lineages. The current clines arose rapidly and may be based on standing genetic variation. The initial phenotypic response of Scots pine in the north is predicted to be increased survival and growth. The genetic responses are examined based on quantitative genetic predictions of sustained selection response and compared with earlier simulation results that have aimed at more ecological realism. The phenotypic responses of increased growth and survival reduce the opportunity for selection and delay the evolutionary responses. The lengthening of the thermal growing period also causes selection on the critical photoperiod in the different populations. Future studies should aim at including multiple ecological and genetic factors in evaluating potential responses.

A Quantitative Chemotherapy Genetic Interaction Map Reveals Factors Associated with PARP Inhibitor Resistance. | Office of Cancer Genomics

Cancer.gov

Chemotherapy is used to treat most cancer patients, yet our understanding of factors that dictate response and resistance to such drugs remains limited. We report the generation of a quantitative chemical-genetic interaction map in human mammary epithelial cells charting the impact of the knockdown of 625 genes related to cancer and DNA repair on sensitivity to 29 drugs, covering all classes of chemotherapy.

A quantitative chemotherapy genetic interaction map reveals new factors associated with PARP inhibitor resistance | Office of Cancer Genomics

Cancer.gov

Nearly every cancer patient is treated with chemotherapy yet our understanding of factors that dictate response and resistance to such agents remains limited. We report the generation of a quantitative chemical-genetic interaction map in human mammary epithelial cells that charts the impact of knockdown of 625 cancer and DNA repair related genes on sensitivity to 29 drugs, covering all classes of cancer chemotherapeutics.

The phylogeny of swimming kinematics: The environment controls flagellar waveforms in sperm motility

NASA Astrophysics Data System (ADS)

Guasto, Jeffrey; Burton, Lisa; Zimmer, Richard; Hosoi, Anette; Stocker, Roman

2013-11-01

In recent years, phylogenetic and molecular analyses have dominated the study of ecology and evolution. However, physical interactions between organisms and their environment, a fundamental determinant of organism ecology and evolution, are mediated by organism form and function, highlighting the need to understand the mechanics of basic survival strategies, including locomotion. Focusing on spermatozoa, we combined high-speed video microscopy and singular value decomposition analysis to quantitatively compare the flagellar waveforms of eight species, ranging from marine invertebrates to humans. We found striking similarities in sperm swimming kinematics between genetically dissimilar organisms, which could not be uncovered by phylogenetic analysis. The emergence of dominant waveform patterns across species are suggestive of biological optimization for flagellar locomotion and point toward environmental cues as drivers of this convergence. These results reinforce the power of quantitative kinematic analysis to understand the physical drivers of evolution and as an approach to uncover new solutions for engineering applications, such as micro-robotics.

Approaches in Characterizing Genetic Structure and Mapping in a Rice Multiparental Population.

PubMed

Raghavan, Chitra; Mauleon, Ramil; Lacorte, Vanica; Jubay, Monalisa; Zaw, Hein; Bonifacio, Justine; Singh, Rakesh Kumar; Huang, B Emma; Leung, Hei

2017-06-07

Multi-parent Advanced Generation Intercross (MAGIC) populations are fast becoming mainstream tools for research and breeding, along with the technology and tools for analysis. This paper demonstrates the analysis of a rice MAGIC population from data filtering to imputation and processing of genetic data to characterizing genomic structure, and finally quantitative trait loci (QTL) mapping. In this study, 1316 S6:8 indica MAGIC (MI) lines and the eight founders were sequenced using Genotyping by Sequencing (GBS). As the GBS approach often includes missing data, the first step was to impute the missing SNPs. The observable number of recombinations in the population was then explored. Based on this case study, a general outline of procedures for a MAGIC analysis workflow is provided, as well as for QTL mapping of agronomic traits and biotic and abiotic stress, using the results from both association and interval mapping approaches. QTL for agronomic traits (yield, flowering time, and plant height), physical (grain length and grain width) and cooking properties (amylose content) of the rice grain, abiotic stress (submergence tolerance), and biotic stress (brown spot disease) were mapped. Through presenting this extensive analysis in the MI population in rice, we highlight important considerations when choosing analytical approaches. The methods and results reported in this paper will provide a guide to future genetic analysis methods applied to multi-parent populations. Copyright © 2017 Raghavan et al.

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

PubMed

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

2016-07-26

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

Resolving the Effects of Maternal and Offspring Genotype on Dyadic Outcomes in Genome Wide Complex Trait Analysis (“M-GCTA”)

PubMed Central

Pourcain, Beate St.; Smith, George Davey; York, Timothy P.; Evans, David M.

2014-01-01

Genome wide complex trait analysis (GCTA) is extended to include environmental effects of the maternal genotype on offspring phenotype (“maternal effects”, M-GCTA). The model includes parameters for the direct effects of the offspring genotype, maternal effects and the covariance between direct and maternal effects. Analysis of simulated data, conducted in OpenMx, confirmed that model parameters could be recovered by full information maximum likelihood (FIML) and evaluated the biases that arise in conventional GCTA when indirect genetic effects are ignored. Estimates derived from FIML in OpenMx showed very close agreement to those obtained by restricted maximum likelihood using the published algorithm for GCTA. The method was also applied to illustrative perinatal phenotypes from ∼4,000 mother-offspring pairs from the Avon Longitudinal Study of Parents and Children. The relative merits of extended GCTA in contrast to quantitative genetic approaches based on analyzing the phenotypic covariance structure of kinships are considered. PMID:25060210

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

PubMed Central

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

2017-01-01

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

Extension of the Haseman-Elston regression model to longitudinal data.

PubMed

Won, Sungho; Elston, Robert C; Park, Taesung

2006-01-01

We propose an extension to longitudinal data of the Haseman and Elston regression method for linkage analysis. The proposed model is a mixed model having several random effects. As response variable, we investigate the sibship sample mean corrected cross-product (smHE) and the BLUP-mean corrected cross product (pmHE), comparing them with the original squared difference (oHE), the overall mean corrected cross-product (rHE), and the weighted average of the squared difference and the squared mean-corrected sum (wHE). The proposed model allows for the correlation structure of longitudinal data. Also, the model can test for gene x time interaction to discover genetic variation over time. The model was applied in an analysis of the Genetic Analysis Workshop 13 (GAW13) simulated dataset for a quantitative trait simulating systolic blood pressure. Independence models did not preserve the test sizes, while the mixed models with both family and sibpair random effects tended to preserve size well. Copyright 2006 S. Karger AG, Basel.

A multivariate analysis of genetic variation in the advertisement call of the gray treefrog, Hyla versicolor.

PubMed

Welch, Allison M; Smith, Michael J; Gerhardt, H Carl

2014-06-01

Genetic variation in sexual displays is crucial for an evolutionary response to sexual selection, but can be eroded by strong selection. Identifying the magnitude and sources of additive genetic variance underlying sexually selected traits is thus an important issue in evolutionary biology. We conducted a quantitative genetics experiment with gray treefrogs (Hyla versicolor) to investigate genetic variances and covariances among features of the male advertisement call. Two energetically expensive traits showed significant genetic variation: call duration, expressed as number of pulses per call, and call rate, represented by its inverse, call period. These two properties also showed significant genetic covariance, consistent with an energetic constraint to call production. Combining the genetic variance-covariance matrix with previous estimates of directional sexual selection imposed by female preferences predicts a limited increase in call duration but no change in call rate despite significant selection on both traits. In addition to constraints imposed by the genetic covariance structure, an evolutionary response to sexual selection may also be limited by high energetic costs of long-duration calls and by preferences that act most strongly against very short-duration calls. Meanwhile, the persistence of these preferences could be explained by costs of mating with males with especially unattractive calls. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Reply.

ERIC Educational Resources Information Center

Gottlieb, Gilbert

1995-01-01

Argues that a truly developmental behavior genetics will have to go beyond the traditional quantitative approach of population genetics in order to produce developmental explanatory content about differences and similarities in developmental outcomes. (MDM)

Attention Deficit Hyperactivity Disorder with Reading Disabilities: Preliminary Genetic Findings on the Involvement of the ADRA2A Gene

ERIC Educational Resources Information Center

Stevenson, J.; Langley, K.; Pay, H.; Payton, A.; Worthington, J.; Ollier, W.; Thapar, A.

2005-01-01

Background: Attention deficit/hyperactivity disorder (ADHD) and reading disability (RD) tend to co-occur and quantitative genetic studies have shown this to arise primarily through shared genetic influences. However, molecular genetic studies have shown different genes to be associated with each of these conditions. Neurobiological studies have…

Quantitative Trait Loci Controlling Vegetative Growth Rate in the Edible Basidiomycete Pleurotus ostreatus

PubMed Central

Larraya, Luis M.; Idareta, Eneko; Arana, Dani; Ritter, Enrique; Pisabarro, Antonio G.; Ramírez, Lucia

2002-01-01

Mycelium growth rate is a quantitative characteristic that exhibits continuous variation. This trait has applied interest, as growth rate is correlated with production yield and increased advantage against competitors. In this work, we studied growth rate variation in the edible basidiomycete Pleurotus ostreatus growing as monokaryotic or dikaryotic mycelium on Eger medium or on wheat straw. Our analysis resulted in identification of several genomic regions (quantitative trait loci [QTLs]) involved in the control of growth rate that can be mapped on the genetic linkage map of this fungus. In some cases monokaryotic and dikaryotic QTLs clustered at the same map position, indicating that there are principal genomic areas responsible for growth rate control. The availability of this linkage map of growth rate QTLs can help in the design of rational strain breeding programs based on genomic information. PMID:11872457

Genetic Analysis and QTL Mapping of Fruit Peduncle Length in Cucumber (Cucumis sativus L.)

PubMed Central

Zhang, Song; Wang, Ye; Zhang, Sheng-Ping; Gu, Xing-Fang

2016-01-01

Mechanized harvesting of cucumbers offers significant advantages compared to manual labor as both shortages and costs of labor increase. However the efficient use of machines depends on breeding plants with longer peduncles, but the genetic and molecular basis of fruit peduncle development in cucumber is not well understood. In this study, F2 populations were developed from a cross between two inbred lines, 1101 with a long peduncle and 1694 with a short peduncle. These were grown at two field sites, Hainan, with a tropical marine climate, in December 2014, and Beijing, with a warm temperate climate, in May 2015. Electron microscope examination of the pith cells in the peduncles of the two parental lines showed that line 1101 had significantly greater numbers of smaller cells compared to line 1694. The inheritance of cucumber fruit peduncle length (FPL) was investigated by the mixed major gene and polygene inheritance model. Genetic analysis indicated that FPL in cucumber is quantitatively inherited and controlled by one additive major gene and additive-dominant polygenes (D-2 model). A total of 1460 pairs of SSR (simple sequence repeat) primers were analyzed to identify quantitative trait loci (QTLs). Two similar genetic maps with 78 SSR markers which covered 720.6 cM in seven linkage groups were constructed based on two F2 populations. QTL analysis from the data collected at the two field sites showed that there are two minor QTLs on chromosome 1, named qfpl1.1 and qfpl1.2, and one major QTL on chromosome 6, named qfpl6.1. The marker UW021226, which was the closest one to qfpl6.1, had an accuracy rate of 79.0% when tested against plants selected from populations of the two parents. The results from this study provide insights into the inheritance and molecular mechanism of the variation of FPL in cucumber, and further research will be carried out to fine map qfpl6.1 to develop more accurate markers for MAS breeding. PMID:27936210

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

Complex polarimetric and spectral techniques in diagnostics of blood plasma of patients with ovarian cancer as a preliminary stage molecular genetic screening

NASA Astrophysics Data System (ADS)

Grzegorzewski, B.; Peresunko, O. P.; Yermolenko, S. B.

2018-01-01

This work is devoted to the substantiation and selection of patients with ovarian cancer (OC) for the purpose of conducting expensive molecular genetic studies on genotyping. As diagnostic methods have been used ultraviolet spectrometry samples of blood plasma in the liquid state, infrared spectroscopy middle range (2,5 - 25 microns) dry residue of plasma polarization and laser diagnostic technique of thin histological sections of biological tissues. Obtained results showed that the use of spectrophotometry in the range of 1000-3000 cm-1 allowed to establish quantitative parameters of the plasma absorption rate of blood of patients in the third group in different ranges, which would allow in the future to conduct an express analysis of the patient's condition (procedure screening) for further molecular-genetic typing on BRCA I and II.

Modular analysis of the probabilistic genetic interaction network.

PubMed

Hou, Lin; Wang, Lin; Qian, Minping; Li, Dong; Tang, Chao; Zhu, Yunping; Deng, Minghua; Li, Fangting

2011-03-15

Epistatic Miniarray Profiles (EMAP) has enabled the mapping of large-scale genetic interaction networks; however, the quantitative information gained from EMAP cannot be fully exploited since the data are usually interpreted as a discrete network based on an arbitrary hard threshold. To address such limitations, we adopted a mixture modeling procedure to construct a probabilistic genetic interaction network and then implemented a Bayesian approach to identify densely interacting modules in the probabilistic network. Mixture modeling has been demonstrated as an effective soft-threshold technique of EMAP measures. The Bayesian approach was applied to an EMAP dataset studying the early secretory pathway in Saccharomyces cerevisiae. Twenty-seven modules were identified, and 14 of those were enriched by gold standard functional gene sets. We also conducted a detailed comparison with state-of-the-art algorithms, hierarchical cluster and Markov clustering. The experimental results show that the Bayesian approach outperforms others in efficiently recovering biologically significant modules.