On the reconciliation of missing heritability for genome-wide association studies
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
Fox, Charles W; Wagner, James D; Cline, Sara; Thomas, Frances Ann; Messina, Frank J
2009-05-01
Independent populations subjected to similar environments often exhibit convergent evolution. An unresolved question is the frequency with which such convergence reflects parallel genetic mechanisms. We examined the convergent evolution of egg-laying behavior in the seed-feeding beetle Callosobruchus maculatus. Females avoid ovipositing on seeds bearing conspecific eggs, but the degree of host discrimination varies among geographic populations. In a previous experiment, replicate lines switched from a small host to a large one evolved reduced discrimination after 40 generations. We used line crosses to determine the genetic architecture underlying this rapid response. The most parsimonious genetic models included dominance and/or epistasis for all crosses. The genetic architecture underlying reduced discrimination in two lines was not significantly different from the architecture underlying differences between geographic populations, but the architecture underlying the divergence of a third line differed from all others. We conclude that convergence of this complex trait may in some cases involve parallel genetic mechanisms.
Zhang, Zhe; Erbe, Malena; He, Jinlong; Ober, Ulrike; Gao, Ning; Zhang, Hao; Simianer, Henner; Li, Jiaqi
2015-02-09
Obtaining accurate predictions of unobserved genetic or phenotypic values for complex traits in animal, plant, and human populations is possible through whole-genome prediction (WGP), a combined analysis of genotypic and phenotypic data. Because the underlying genetic architecture of the trait of interest is an important factor affecting model selection, we propose a new strategy, termed BLUP|GA (BLUP-given genetic architecture), which can use genetic architecture information within the dataset at hand rather than from public sources. This is achieved by using a trait-specific covariance matrix ( T: ), which is a weighted sum of a genetic architecture part ( S: matrix) and the realized relationship matrix ( G: ). The algorithm of BLUP|GA (BLUP-given genetic architecture) is provided and illustrated with real and simulated datasets. Predictive ability of BLUP|GA was validated with three model traits in a dairy cattle dataset and 11 traits in three public datasets with a variety of genetic architectures and compared with GBLUP and other approaches. Results show that BLUP|GA outperformed GBLUP in 20 of 21 scenarios in the dairy cattle dataset and outperformed GBLUP, BayesA, and BayesB in 12 of 13 traits in the analyzed public datasets. Further analyses showed that the difference of accuracies for BLUP|GA and GBLUP significantly correlate with the distance between the T: and G: matrices. The new strategy applied in BLUP|GA is a favorable and flexible alternative to the standard GBLUP model, allowing to account for the genetic architecture of the quantitative trait under consideration when necessary. This feature is mainly due to the increased similarity between the trait-specific relationship matrix ( T: matrix) and the genetic relationship matrix at unobserved causal loci. Applying BLUP|GA in WGP would ease the burden of model selection. Copyright © 2015 Zhang et al.
Han, Chang S; Dingemanse, Niels J
2017-10-11
Empirical studies imply that sex-specific genetic architectures can resolve evolutionary conflicts between males and females, and thereby facilitate the evolution of sexual dimorphism. Sex-specificity of behavioural genetic architectures has, however, rarely been considered. Moreover, as the expression of genetic (co)variances is often environment-dependent, general inferences on sex-specific genetic architectures require estimates of quantitative genetics parameters under multiple conditions. We measured exploration and aggression in pedigreed populations of southern field crickets ( Gryllus bimaculatus ) raised on either naturally balanced (free-choice) or imbalanced (protein-deprived) diets. For each dietary condition, we measured for each behavioural trait (i) level of sexual dimorphism, (ii) level of sex-specificity of survival selection gradients, (iii) level of sex-specificity of additive genetic variance, and (iv) strength of the cross-sex genetic correlation. We report here evidence for sexual dimorphism in behaviour as well as sex-specificity in the expression of genetic (co)variances as predicted by theory. The additive genetic variances of exploration and aggression were significantly greater in males compared with females. Cross-sex genetic correlations were highly positive for exploration but deviating (significantly) from one for aggression; findings were consistent across dietary treatments. This suggests that genetic architectures characterize the sexually dimorphic focal behaviours across various key environmental conditions in the wild. Our finding also highlights that sexual conflict can be resolved by evolving sexually independent genetic architectures. © 2017 The Author(s).
Howard, Réka; Carriquiry, Alicia L.; Beavis, William D.
2014-01-01
Parametric and nonparametric methods have been developed for purposes of predicting phenotypes. These methods are based on retrospective analyses of empirical data consisting of genotypic and phenotypic scores. Recent reports have indicated that parametric methods are unable to predict phenotypes of traits with known epistatic genetic architectures. Herein, we review parametric methods including least squares regression, ridge regression, Bayesian ridge regression, least absolute shrinkage and selection operator (LASSO), Bayesian LASSO, best linear unbiased prediction (BLUP), Bayes A, Bayes B, Bayes C, and Bayes Cπ. We also review nonparametric methods including Nadaraya-Watson estimator, reproducing kernel Hilbert space, support vector machine regression, and neural networks. We assess the relative merits of these 14 methods in terms of accuracy and mean squared error (MSE) using simulated genetic architectures consisting of completely additive or two-way epistatic interactions in an F2 population derived from crosses of inbred lines. Each simulated genetic architecture explained either 30% or 70% of the phenotypic variability. The greatest impact on estimates of accuracy and MSE was due to genetic architecture. Parametric methods were unable to predict phenotypic values when the underlying genetic architecture was based entirely on epistasis. Parametric methods were slightly better than nonparametric methods for additive genetic architectures. Distinctions among parametric methods for additive genetic architectures were incremental. Heritability, i.e., proportion of phenotypic variability, had the second greatest impact on estimates of accuracy and MSE. PMID:24727289
The Genetic Basis of Plant Architecture in 10 Maize Recombinant Inbred Line Populations1[OPEN
Pan, Qingchun; Xu, Yuancheng; Peng, Yong; Zhan, Wei; Li, Wenqiang; Li, Lin
2017-01-01
Plant architecture is a key factor affecting planting density and grain yield in maize (Zea mays). However, the genetic mechanisms underlying plant architecture in diverse genetic backgrounds have not been fully addressed. Here, we performed a large-scale phenotyping of 10 plant architecture-related traits and dissected the genetic loci controlling these traits in 10 recombinant inbred line populations derived from 14 diverse genetic backgrounds. Nearly 800 quantitative trait loci (QTLs) with major and minor effects were identified as contributing to the phenotypic variation of plant architecture-related traits. Ninety-two percent of these QTLs were detected in only one population, confirming the diverse genetic backgrounds of the mapping populations and the prevalence of rare alleles in maize. The numbers and effects of QTLs are positively associated with the phenotypic variation in the population, which, in turn, correlates positively with parental phenotypic and genetic variations. A large proportion (38.5%) of QTLs was associated with at least two traits, suggestive of the frequent occurrence of pleiotropic loci or closely linked loci. Key developmental genes, which previously were shown to affect plant architecture in mutant studies, were found to colocalize with many QTLs. Five QTLs were further validated using the segregating populations developed from residual heterozygous lines present in the recombinant inbred line populations. Additionally, one new plant height QTL, qPH3, has been fine-mapped to a 600-kb genomic region where three candidate genes are located. These results provide insights into the genetic mechanisms controlling plant architecture and will benefit the selection of ideal plant architecture in maize breeding. PMID:28838954
The Genetic Basis of Plant Architecture in 10 Maize Recombinant Inbred Line Populations.
Pan, Qingchun; Xu, Yuancheng; Li, Kun; Peng, Yong; Zhan, Wei; Li, Wenqiang; Li, Lin; Yan, Jianbing
2017-10-01
Plant architecture is a key factor affecting planting density and grain yield in maize ( Zea mays ). However, the genetic mechanisms underlying plant architecture in diverse genetic backgrounds have not been fully addressed. Here, we performed a large-scale phenotyping of 10 plant architecture-related traits and dissected the genetic loci controlling these traits in 10 recombinant inbred line populations derived from 14 diverse genetic backgrounds. Nearly 800 quantitative trait loci (QTLs) with major and minor effects were identified as contributing to the phenotypic variation of plant architecture-related traits. Ninety-two percent of these QTLs were detected in only one population, confirming the diverse genetic backgrounds of the mapping populations and the prevalence of rare alleles in maize. The numbers and effects of QTLs are positively associated with the phenotypic variation in the population, which, in turn, correlates positively with parental phenotypic and genetic variations. A large proportion (38.5%) of QTLs was associated with at least two traits, suggestive of the frequent occurrence of pleiotropic loci or closely linked loci. Key developmental genes, which previously were shown to affect plant architecture in mutant studies, were found to colocalize with many QTLs. Five QTLs were further validated using the segregating populations developed from residual heterozygous lines present in the recombinant inbred line populations. Additionally, one new plant height QTL, qPH3 , has been fine-mapped to a 600-kb genomic region where three candidate genes are located. These results provide insights into the genetic mechanisms controlling plant architecture and will benefit the selection of ideal plant architecture in maize breeding. © 2017 American Society of Plant Biologists. All Rights Reserved.
The genetic basis of alcoholism: multiple phenotypes, many genes, complex networks.
Morozova, Tatiana V; Goldman, David; Mackay, Trudy F C; Anholt, Robert R H
2012-02-20
Alcoholism is a significant public health problem. A picture of the genetic architecture underlying alcohol-related phenotypes is emerging from genome-wide association studies and work on genetically tractable model organisms.
The genetic basis of alcoholism: multiple phenotypes, many genes, complex networks
2012-01-01
Alcoholism is a significant public health problem. A picture of the genetic architecture underlying alcohol-related phenotypes is emerging from genome-wide association studies and work on genetically tractable model organisms. PMID:22348705
Saastamoinen, Marjo; Bocedi, Greta; Cote, Julien; Legrand, Delphine; Guillaume, Frédéric; Wheat, Christopher W; Fronhofer, Emanuel A; Garcia, Cristina; Henry, Roslyn; Husby, Arild; Baguette, Michel; Bonte, Dries; Coulon, Aurélie; Kokko, Hanna; Matthysen, Erik; Niitepõld, Kristjan; Nonaka, Etsuko; Stevens, Virginie M; Travis, Justin M J; Donohue, Kathleen; Bullock, James M; Del Mar Delgado, Maria
2018-02-01
Dispersal is a process of central importance for the ecological and evolutionary dynamics of populations and communities, because of its diverse consequences for gene flow and demography. It is subject to evolutionary change, which begs the question, what is the genetic basis of this potentially complex trait? To address this question, we (i) review the empirical literature on the genetic basis of dispersal, (ii) explore how theoretical investigations of the evolution of dispersal have represented the genetics of dispersal, and (iii) discuss how the genetic basis of dispersal influences theoretical predictions of the evolution of dispersal and potential consequences. Dispersal has a detectable genetic basis in many organisms, from bacteria to plants and animals. Generally, there is evidence for significant genetic variation for dispersal or dispersal-related phenotypes or evidence for the micro-evolution of dispersal in natural populations. Dispersal is typically the outcome of several interacting traits, and this complexity is reflected in its genetic architecture: while some genes of moderate to large effect can influence certain aspects of dispersal, dispersal traits are typically polygenic. Correlations among dispersal traits as well as between dispersal traits and other traits under selection are common, and the genetic basis of dispersal can be highly environment-dependent. By contrast, models have historically considered a highly simplified genetic architecture of dispersal. It is only recently that models have started to consider multiple loci influencing dispersal, as well as non-additive effects such as dominance and epistasis, showing that the genetic basis of dispersal can influence evolutionary rates and outcomes, especially under non-equilibrium conditions. For example, the number of loci controlling dispersal can influence projected rates of dispersal evolution during range shifts and corresponding demographic impacts. Incorporating more realism in the genetic architecture of dispersal is thus necessary to enable models to move beyond the purely theoretical towards making more useful predictions of evolutionary and ecological dynamics under current and future environmental conditions. To inform these advances, empirical studies need to answer outstanding questions concerning whether specific genes underlie dispersal variation, the genetic architecture of context-dependent dispersal phenotypes and behaviours, and correlations among dispersal and other traits. © 2017 The Authors. Biological Reviews published by John Wiley & Sons Ltd on behalf of Cambridge Philosophical Society.
Bocedi, Greta; Cote, Julien; Legrand, Delphine; Guillaume, Frédéric; Wheat, Christopher W.; Fronhofer, Emanuel A.; Garcia, Cristina; Henry, Roslyn; Husby, Arild; Baguette, Michel; Bonte, Dries; Coulon, Aurélie; Kokko, Hanna; Matthysen, Erik; Niitepõld, Kristjan; Nonaka, Etsuko; Stevens, Virginie M.; Travis, Justin M. J.; Donohue, Kathleen; Bullock, James M.; del Mar Delgado, Maria
2017-01-01
ABSTRACT Dispersal is a process of central importance for the ecological and evolutionary dynamics of populations and communities, because of its diverse consequences for gene flow and demography. It is subject to evolutionary change, which begs the question, what is the genetic basis of this potentially complex trait? To address this question, we (i) review the empirical literature on the genetic basis of dispersal, (ii) explore how theoretical investigations of the evolution of dispersal have represented the genetics of dispersal, and (iii) discuss how the genetic basis of dispersal influences theoretical predictions of the evolution of dispersal and potential consequences. Dispersal has a detectable genetic basis in many organisms, from bacteria to plants and animals. Generally, there is evidence for significant genetic variation for dispersal or dispersal‐related phenotypes or evidence for the micro‐evolution of dispersal in natural populations. Dispersal is typically the outcome of several interacting traits, and this complexity is reflected in its genetic architecture: while some genes of moderate to large effect can influence certain aspects of dispersal, dispersal traits are typically polygenic. Correlations among dispersal traits as well as between dispersal traits and other traits under selection are common, and the genetic basis of dispersal can be highly environment‐dependent. By contrast, models have historically considered a highly simplified genetic architecture of dispersal. It is only recently that models have started to consider multiple loci influencing dispersal, as well as non‐additive effects such as dominance and epistasis, showing that the genetic basis of dispersal can influence evolutionary rates and outcomes, especially under non‐equilibrium conditions. For example, the number of loci controlling dispersal can influence projected rates of dispersal evolution during range shifts and corresponding demographic impacts. Incorporating more realism in the genetic architecture of dispersal is thus necessary to enable models to move beyond the purely theoretical towards making more useful predictions of evolutionary and ecological dynamics under current and future environmental conditions. To inform these advances, empirical studies need to answer outstanding questions concerning whether specific genes underlie dispersal variation, the genetic architecture of context‐dependent dispersal phenotypes and behaviours, and correlations among dispersal and other traits. PMID:28776950
2011-01-01
Background Biologists studying adaptation under sexual selection have spent considerable effort assessing the relative importance of two groups of models, which hinge on the idea that females gain indirect benefits via mate discrimination. These are the good genes and genetic compatibility models. Quantitative genetic studies have advanced our understanding of these models by enabling assessment of whether the genetic architectures underlying focal phenotypes are congruent with either model. In this context, good genes models require underlying additive genetic variance, while compatibility models require non-additive variance. Currently, we know very little about how the expression of genotypes comprised of distinct parental haplotypes, or how levels and types of genetic variance underlying key phenotypes, change across environments. Such knowledge is important, however, because genotype-environment interactions can have major implications on the potential for evolutionary responses to selection. Results We used a full diallel breeding design to screen for complex genotype-environment interactions, and genetic architectures underlying key morphological traits, across two thermal environments (the lab standard 27°C, and the cooler 23°C) in the Australian field cricket, Teleogryllus oceanicus. In males, complex three-way interactions between sire and dam parental haplotypes and the rearing environment accounted for up to 23 per cent of the scaled phenotypic variance in the traits we measured (body mass, pronotum width and testes mass), and each trait harboured significant additive genetic variance in the standard temperature (27°C) only. In females, these three-way interactions were less important, with interactions between the paternal haplotype and rearing environment accounting for about ten per cent of the phenotypic variance (in body mass, pronotum width and ovary mass). Of the female traits measured, only ovary mass for crickets reared at the cooler temperature (23°C), exhibited significant levels of additive genetic variance. Conclusions Our results show that the genetics underlying phenotypic expression can be complex, context-dependent and different in each of the sexes. We discuss the implications of these results, particularly in terms of the evolutionary processes that hinge on good and compatible genes models. PMID:21791118
Genetic architecture of plant stress resistance: multi-trait genome-wide association mapping.
Thoen, Manus P M; Davila Olivas, Nelson H; Kloth, Karen J; Coolen, Silvia; Huang, Ping-Ping; Aarts, Mark G M; Bac-Molenaar, Johanna A; Bakker, Jaap; Bouwmeester, Harro J; Broekgaarden, Colette; Bucher, Johan; Busscher-Lange, Jacqueline; Cheng, Xi; Fradin, Emilie F; Jongsma, Maarten A; Julkowska, Magdalena M; Keurentjes, Joost J B; Ligterink, Wilco; Pieterse, Corné M J; Ruyter-Spira, Carolien; Smant, Geert; Testerink, Christa; Usadel, Björn; van Loon, Joop J A; van Pelt, Johan A; van Schaik, Casper C; van Wees, Saskia C M; Visser, Richard G F; Voorrips, Roeland; Vosman, Ben; Vreugdenhil, Dick; Warmerdam, Sonja; Wiegers, Gerrie L; van Heerwaarden, Joost; Kruijer, Willem; van Eeuwijk, Fred A; Dicke, Marcel
2017-02-01
Plants are exposed to combinations of various biotic and abiotic stresses, but stress responses are usually investigated for single stresses only. Here, we investigated the genetic architecture underlying plant responses to 11 single stresses and several of their combinations by phenotyping 350 Arabidopsis thaliana accessions. A set of 214 000 single nucleotide polymorphisms (SNPs) was screened for marker-trait associations in genome-wide association (GWA) analyses using tailored multi-trait mixed models. Stress responses that share phytohormonal signaling pathways also share genetic architecture underlying these responses. After removing the effects of general robustness, for the 30 most significant SNPs, average quantitative trait locus (QTL) effect sizes were larger for dual stresses than for single stresses. Plants appear to deploy broad-spectrum defensive mechanisms influencing multiple traits in response to combined stresses. Association analyses identified QTLs with contrasting and with similar responses to biotic vs abiotic stresses, and below-ground vs above-ground stresses. Our approach allowed for an unprecedented comprehensive genetic analysis of how plants deal with a wide spectrum of stress conditions. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.
The genetic architecture of susceptibility to parasites.
Wilfert, Lena; Schmid-Hempel, Paul
2008-06-30
The antagonistic co-evolution of hosts and their parasites is considered to be a potential driving force in maintaining host genetic variation including sexual reproduction and recombination. The examination of this hypothesis calls for information about the genetic basis of host-parasite interactions - such as how many genes are involved, how big an effect these genes have and whether there is epistasis between loci. We here examine the genetic architecture of quantitative resistance in animal and plant hosts by concatenating published studies that have identified quantitative trait loci (QTL) for host resistance in animals and plants. Collectively, these studies show that host resistance is affected by few loci. We particularly show that additional epistatic interactions, especially between loci on different chromosomes, explain a majority of the effects. Furthermore, we find that when experiments are repeated using different host or parasite genotypes under otherwise identical conditions, the underlying genetic architecture of host resistance can vary dramatically - that is, involves different QTLs and epistatic interactions. QTLs and epistatic loci vary much less when host and parasite types remain the same but experiments are repeated in different environments. This pattern of variability of the genetic architecture is predicted by strong interactions between genotypes and corroborates the prevalence of varying host-parasite combinations over varying environmental conditions. Moreover, epistasis is a major determinant of phenotypic variance for host resistance. Because epistasis seems to occur predominantly between, rather than within, chromosomes, segregation and chromosome number rather than recombination via cross-over should be the major elements affecting adaptive change in host resistance.
Yadav, Anupama; Dhole, Kaustubh; Sinha, Himanshu
2016-12-01
Cryptic genetic variation (CGV) refers to genetic variants whose effects are buffered in most conditions but manifest phenotypically upon specific genetic and environmental perturbations. Despite having a central role in adaptation, contribution of CGV to regulation of quantitative traits is unclear. Instead, a relatively simplistic architecture of additive genetic loci is known to regulate phenotypic variation in most traits. In this paper, we investigate the regulation of CGV and its implication on the genetic architecture of quantitative traits at a genome-wide level. We use a previously published dataset of biparental recombinant population of Saccharomyces cerevisiae phenotyped in 34 diverse environments to perform single locus, two-locus, and covariance mapping. We identify loci that have independent additive effects as well as those which regulate the phenotypic manifestation of other genetic variants (variance QTL). We find that whereas additive genetic variance is predominant, a higher order genetic interaction network regulates variation in certain environments. Despite containing pleiotropic loci, with effects across environments, these genetic networks are highly environment specific. CGV is buffered under most allelic combinations of these networks and perturbed only in rare combinations resulting in high phenotypic variance. The presence of such environment specific genetic networks is the underlying cause of abundant gene–environment interactions. We demonstrate that overlaying identified molecular networks on such genetic networks can identify potential candidate genes and underlying mechanisms regulating phenotypic variation. Such an integrated approach applied to human disease datasets has the potential to improve the ability to predict disease predisposition and identify specific therapeutic targets.
Yadav, Anupama; Dhole, Kaustubh
2016-01-01
Cryptic genetic variation (CGV) refers to genetic variants whose effects are buffered in most conditions but manifest phenotypically upon specific genetic and environmental perturbations. Despite having a central role in adaptation, contribution of CGV to regulation of quantitative traits is unclear. Instead, a relatively simplistic architecture of additive genetic loci is known to regulate phenotypic variation in most traits. In this paper, we investigate the regulation of CGV and its implication on the genetic architecture of quantitative traits at a genome-wide level. We use a previously published dataset of biparental recombinant population of Saccharomyces cerevisiae phenotyped in 34 diverse environments to perform single locus, two-locus, and covariance mapping. We identify loci that have independent additive effects as well as those which regulate the phenotypic manifestation of other genetic variants (variance QTL). We find that whereas additive genetic variance is predominant, a higher order genetic interaction network regulates variation in certain environments. Despite containing pleiotropic loci, with effects across environments, these genetic networks are highly environment specific. CGV is buffered under most allelic combinations of these networks and perturbed only in rare combinations resulting in high phenotypic variance. The presence of such environment specific genetic networks is the underlying cause of abundant gene–environment interactions. We demonstrate that overlaying identified molecular networks on such genetic networks can identify potential candidate genes and underlying mechanisms regulating phenotypic variation. Such an integrated approach applied to human disease datasets has the potential to improve the ability to predict disease predisposition and identify specific therapeutic targets. PMID:28172852
Understanding Evolutionary Potential in Virtual CPU Instruction Set Architectures
Bryson, David M.; Ofria, Charles
2013-01-01
We investigate fundamental decisions in the design of instruction set architectures for linear genetic programs that are used as both model systems in evolutionary biology and underlying solution representations in evolutionary computation. We subjected digital organisms with each tested architecture to seven different computational environments designed to present a range of evolutionary challenges. Our goal was to engineer a general purpose architecture that would be effective under a broad range of evolutionary conditions. We evaluated six different types of architectural features for the virtual CPUs: (1) genetic flexibility: we allowed digital organisms to more precisely modify the function of genetic instructions, (2) memory: we provided an increased number of registers in the virtual CPUs, (3) decoupled sensors and actuators: we separated input and output operations to enable greater control over data flow. We also tested a variety of methods to regulate expression: (4) explicit labels that allow programs to dynamically refer to specific genome positions, (5) position-relative search instructions, and (6) multiple new flow control instructions, including conditionals and jumps. Each of these features also adds complication to the instruction set and risks slowing evolution due to epistatic interactions. Two features (multiple argument specification and separated I/O) demonstrated substantial improvements in the majority of test environments, along with versions of each of the remaining architecture modifications that show significant improvements in multiple environments. However, some tested modifications were detrimental, though most exhibit no systematic effects on evolutionary potential, highlighting the robustness of digital evolution. Combined, these observations enhance our understanding of how instruction architecture impacts evolutionary potential, enabling the creation of architectures that support more rapid evolution of complex solutions to a broad range of challenges. PMID:24376669
Genetic Architecture of Nest Building in Mice LG/J × SM/J
Sauce, Bruno; de Brito, Reinaldo Alves; Peripato, Andrea Cristina
2012-01-01
Maternal care is critical to offspring growth and survival, which is greatly improved by building an effective nest. Some suggest that genetic variation and underlying genetic effects differ between fitness-related traits and other phenotypes. We investigated the genetic architecture of a fitness-related trait, nest building, in F2 female mice intercrossed from inbred strains SM/J and LG/J using a QTL analysis for six related nest phenotypes (Presence and Structure pre- and postpartum, prepartum Material Used and postpartum Temperature). We found 15 direct-effect QTLs explaining from 4 to 13% of the phenotypic variation in nest building, mostly with non-additive effect. Epistatic analyses revealed 71 significant epistatic interactions which together explain from 28.4 to 75.5% of the variation, indicating an important role for epistasis in the adaptive process of nest building behavior in mice. Our results suggest a genetic architecture with small direct effects and a larger number of epistatic interactions as expected for fitness-related phenotypes. PMID:22654894
Ritchie, Marylyn D; White, Bill C; Parker, Joel S; Hahn, Lance W; Moore, Jason H
2003-01-01
Background Appropriate definition of neural network architecture prior to data analysis is crucial for successful data mining. This can be challenging when the underlying model of the data is unknown. The goal of this study was to determine whether optimizing neural network architecture using genetic programming as a machine learning strategy would improve the ability of neural networks to model and detect nonlinear interactions among genes in studies of common human diseases. Results Using simulated data, we show that a genetic programming optimized neural network approach is able to model gene-gene interactions as well as a traditional back propagation neural network. Furthermore, the genetic programming optimized neural network is better than the traditional back propagation neural network approach in terms of predictive ability and power to detect gene-gene interactions when non-functional polymorphisms are present. Conclusion This study suggests that a machine learning strategy for optimizing neural network architecture may be preferable to traditional trial-and-error approaches for the identification and characterization of gene-gene interactions in common, complex human diseases. PMID:12846935
Distinct Genetic Architectures for Male and Female Inflorescence Traits of Maize
Brown, Patrick J.; Upadyayula, Narasimham; Mahone, Gregory S.; Tian, Feng; Bradbury, Peter J.; Myles, Sean; Holland, James B.; Flint-Garcia, Sherry; McMullen, Michael D.; Buckler, Edward S.; Rocheford, Torbert R.
2011-01-01
We compared the genetic architecture of thirteen maize morphological traits in a large population of recombinant inbred lines. Four traits from the male inflorescence (tassel) and three traits from the female inflorescence (ear) were measured and studied using linkage and genome-wide association analyses and compared to three flowering and three leaf traits previously studied in the same population. Inflorescence loci have larger effects than flowering and leaf loci, and ear effects are larger than tassel effects. Ear trait models also have lower predictive ability than tassel, flowering, or leaf trait models. Pleiotropic loci were identified that control elongation of ear and tassel, consistent with their common developmental origin. For these pleiotropic loci, the ear effects are larger than tassel effects even though the same causal polymorphisms are likely involved. This implies that the observed differences in genetic architecture are not due to distinct features of the underlying polymorphisms. Our results support the hypothesis that genetic architecture is a function of trait stability over evolutionary time, since the traits that changed most during the relatively recent domestication of maize have the largest effects. PMID:22125498
A two-locus model of spatially varying stabilizing or directional selection on a quantitative trait
Geroldinger, Ludwig; Bürger, Reinhard
2014-01-01
The consequences of spatially varying, stabilizing or directional selection on a quantitative trait in a subdivided population are studied. A deterministic two-locus two-deme model is employed to explore the effects of migration, the degree of divergent selection, and the genetic architecture, i.e., the recombination rate and ratio of locus effects, on the maintenance of genetic variation. The possible equilibrium configurations are determined as functions of the migration rate. They depend crucially on the strength of divergent selection and the genetic architecture. The maximum migration rates are investigated below which a stable fully polymorphic equilibrium or a stable single-locus polymorphism can exist. Under stabilizing selection, but with different optima in the demes, strong recombination may facilitate the maintenance of polymorphism. However usually, and in particular with directional selection in opposite direction, the critical migration rates are maximized by a concentrated genetic architecture, i.e., by a major locus and a tightly linked minor one. Thus, complementing previous work on the evolution of genetic architectures in subdivided populations subject to diversifying selection, it is shown that concentrated architectures may aid the maintenance of polymorphism. Conditions are obtained when this is the case. Finally, the dependence of the phenotypic variance, linkage disequilibrium, and various measures of local adaptation and differentiation on the parameters is elaborated. PMID:24726489
A two-locus model of spatially varying stabilizing or directional selection on a quantitative trait.
Geroldinger, Ludwig; Bürger, Reinhard
2014-06-01
The consequences of spatially varying, stabilizing or directional selection on a quantitative trait in a subdivided population are studied. A deterministic two-locus two-deme model is employed to explore the effects of migration, the degree of divergent selection, and the genetic architecture, i.e., the recombination rate and ratio of locus effects, on the maintenance of genetic variation. The possible equilibrium configurations are determined as functions of the migration rate. They depend crucially on the strength of divergent selection and the genetic architecture. The maximum migration rates are investigated below which a stable fully polymorphic equilibrium or a stable single-locus polymorphism can exist. Under stabilizing selection, but with different optima in the demes, strong recombination may facilitate the maintenance of polymorphism. However usually, and in particular with directional selection in opposite direction, the critical migration rates are maximized by a concentrated genetic architecture, i.e., by a major locus and a tightly linked minor one. Thus, complementing previous work on the evolution of genetic architectures in subdivided populations subject to diversifying selection, it is shown that concentrated architectures may aid the maintenance of polymorphism. Conditions are obtained when this is the case. Finally, the dependence of the phenotypic variance, linkage disequilibrium, and various measures of local adaptation and differentiation on the parameters is elaborated. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
Assessing the evidence for shared genetic risks across psychiatric disorders and traits.
Martin, Joanna; Taylor, Mark J; Lichtenstein, Paul
2017-12-04
Genetic influences play a significant role in risk for psychiatric disorders, prompting numerous endeavors to further understand their underlying genetic architecture. In this paper, we summarize and review evidence from traditional twin studies and more recent genome-wide molecular genetic analyses regarding two important issues that have proven particularly informative for psychiatric genetic research. First, emerging results are beginning to suggest that genetic risk factors for some (but not all) clinically diagnosed psychiatric disorders or extreme manifestations of psychiatric traits in the population share genetic risks with quantitative variation in milder traits of the same disorder throughout the general population. Second, there is now evidence for substantial sharing of genetic risks across different psychiatric disorders. This extends to the level of characteristic traits throughout the population, with which some clinical disorders also share genetic risks. In this review, we summarize and evaluate the evidence for these two issues, for a range of psychiatric disorders. We then critically appraise putative interpretations regarding the potential meaning of genetic correlation across psychiatric phenotypes. We highlight several new methods and studies which are already using these insights into the genetic architecture of psychiatric disorders to gain additional understanding regarding the underlying biology of these disorders. We conclude by outlining opportunities for future research in this area.
Jacobs, Arne; Hughes, Martin R; Robinson, Paige C; Adams, Colin E; Elmer, Kathryn R
2018-05-31
Identifying the genetic basis underlying phenotypic divergence and reproductive isolation is a longstanding problem in evolutionary biology. Genetic signals of adaptation and reproductive isolation are often confounded by a wide range of factors, such as variation in demographic history or genomic features. Brown trout ( Salmo trutta ) in the Loch Maree catchment, Scotland, exhibit reproductively isolated divergent life history morphs, including a rare piscivorous (ferox) life history form displaying larger body size, greater longevity and delayed maturation compared to sympatric benthivorous brown trout. Using a dataset of 16,066 SNPs, we analyzed the evolutionary history and genetic architecture underlying this divergence. We found that ferox trout and benthivorous brown trout most likely evolved after recent secondary contact of two distinct glacial lineages, and identified 33 genomic outlier windows across the genome, of which several have most likely formed through selection. We further identified twelve candidate genes and biological pathways related to growth, development and immune response potentially underpinning the observed phenotypic differences. The identification of clear genomic signals divergent between life history phenotypes and potentially linked to reproductive isolation, through size assortative mating, as well as the identification of the underlying demographic history, highlights the power of genomic studies of young species pairs for understanding the factors shaping genetic differentiation.
The Genetic Basis of Upland/Lowland Ecotype Divergence in Switchgrass (Panicum virgatum)
Milano, Elizabeth R.; Lowry, David B.; Juenger, Thomas E.
2016-01-01
The evolution of locally adapted ecotypes is a common phenomenon that generates diversity within plant species. However, we know surprisingly little about the genetic mechanisms underlying the locally adapted traits involved in ecotype formation. The genetic architecture underlying locally adapted traits dictates how an organism will respond to environmental selection pressures, and has major implications for evolutionary ecology, conservation, and crop breeding. To understand the genetic architecture underlying the divergence of switchgrass (Panicum virgatum) ecotypes, we constructed a genetic mapping population through a four-way outbred cross between two northern upland and two southern lowland accessions. Trait segregation in this mapping population was largely consistent with multiple independent loci controlling the suite of traits that characterizes ecotype divergence. We assembled a joint linkage map using ddRADseq, and mapped quantitative trait loci (QTL) for traits that are divergent between ecotypes, including flowering time, plant size, physiological processes, and disease resistance. Overall, we found that most QTL had small to intermediate effects. While we identified colocalizing QTL for multiple traits, we did not find any large-effect QTL that clearly controlled multiple traits through pleiotropy or tight physical linkage. These results indicate that ecologically important traits in switchgrass have a complex genetic basis, and that similar loci may underlie divergence across the geographic range of the ecotypes. PMID:27613751
Phadnis, Nitin
2011-11-01
Understanding the genetic basis of reproductive isolation between recently diverged species is a central problem in evolutionary genetics. Here, I present analyses of the genetic architecture underlying hybrid male sterility and segregation distortion between the Bogota and USA subspecies of Drosophila pseudoobscura. Previously, a single gene, Overdrive (Ovd), was shown to be necessary but not sufficient for both male sterility and segregation distortion in F(1) hybrids between these subspecies, requiring several interacting partner loci for full manifestation of hybrid phenomena. I map these partner loci separately on the Bogota X chromosome and USA autosomes using a combination of different mapping strategies. I find that hybrid sterility involves a single hybrid incompatibility of at least seven interacting partner genes that includes three large-effect loci. Segregation distortion involves three loci on the Bogota X chromosome and one locus on the autosomes. The genetic bases of hybrid sterility and segregation distortion are at least partially--but not completely--overlapping. My results lay the foundation for fine-mapping experiments to identify the complete set of genes that interact with Overdrive. While individual genes that cause hybrid sterility or inviability have been identified in a few cases, my analysis provides a comprehensive look at the genetic architecture of all components of a hybrid incompatibility underlying F(1) hybrid sterility. Such an analysis would likely be unfeasible for most species pairs due to their divergence time and emphasizes the importance of young species pairs such as the D. pseudoobscura subspecies studied here.
Remington, David L
2015-12-01
Perspectives on the role of large-effect quantitative trait loci (QTL) in the evolution of complex traits have shifted back and forth over the past few decades. Different sets of studies have produced contradictory insights on the evolution of genetic architecture. I argue that much of the confusion results from a failure to distinguish mutational and allelic effects, a limitation of using the Fisherian model of adaptive evolution as the lens through which the evolution of adaptive variation is examined. A molecular-based perspective reveals that allelic differences can involve the cumulative effects of many mutations plus intragenic recombination, a model that is supported by extensive empirical evidence. I discuss how different selection regimes could produce very different architectures of allelic effects under a molecular-based model, which may explain conflicting insights on genetic architecture from studies of variation within populations versus between divergently selected populations. I address shortcomings of genome-wide association study (GWAS) practices in light of more suitable models of allelic evolution, and suggest alternate GWAS strategies to generate more valid inferences about genetic architecture. Finally, I discuss how adopting more suitable models of allelic evolution could help redirect research on complex trait evolution toward addressing more meaningful questions in evolutionary biology. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.
Genetic diversity of root system architecture in response to drought stress in grain legumes.
Ye, Heng; Roorkiwal, Manish; Valliyodan, Babu; Zhou, Lijuan; Chen, Pengyin; Varshney, Rajeev K; Nguyen, Henry T
2018-06-06
Climate change has increased the occurrence of extreme weather patterns globally, causing significant reductions in crop production, and hence threatening food security. In order to meet the food demand of the growing world population, a faster rate of genetic gains leading to productivity enhancement for major crops is required. Grain legumes are an essential commodity in optimal human diets and animal feed because of their unique nutritional composition. Currently, limited water is a major constraint in grain legume production. Root system architecture (RSA) is an important developmental and agronomic trait, which plays vital roles in plant adaptation and productivity under water-limited environments. A deep and proliferative root system helps extract sufficient water and nutrients under these stress conditions. The integrated genetics and genomics approach to dissect molecular processes from genome to phenome is key to achieve increased water capture and use efficiency through developing better root systems. Success in crop improvement under drought depends on discovery and utilization of genetic variations existing in the germplasm. In this review, we summarize current progress in the genetic diversity in major legume crops, quantitative trait loci (QTLs) associated with RSA, and the importance and applications of recent discoveries associated with the beneficial root traits towards better RSA for enhanced drought tolerance and yield.
An Exploratory Study on DRD2 and Creative Potential
ERIC Educational Resources Information Center
Zhang, Shun; Zhang, Muzi; Zhang, Jinghuan
2014-01-01
One critical step toward to a better understanding of creativity is to unveil its underlying genetic architectures. Recently, several studies have been conducted to investigate the effects of dopamine (DA) and 5-hydroxytryptamine (5-HT) related genetic polymorphisms on creativity. Among DA related genes, dopamine D2 receptor gene…
The Genetic Basis of Upland/Lowland Ecotype Divergence in Switchgrass (Panicum virgatum)
Milano, E. R.; Lowry, D. B.; Juenger, T. E.
2016-09-09
The evolution of locally adapted ecotypes is a common phenomenon that generates diversity within plant species. However, we know surprisingly little about the genetic mechanisms underlying the locally adapted traits involved in ecotype formation. The genetic architecture underlying locally adapted traits dictates how an organism will respond to environmental selection pressures, and has major implications for evolutionary ecology, conservation, and crop breeding. To understand the genetic architecture underlying the divergence of switchgrass (Panicum virgatum) ecotypes, we constructed a genetic mapping population through a four-way outbred cross between two northern upland and two southern lowland accessions. Trait segregation in this mappingmore » population was largely consistent with multiple independent loci controlling the suite of traits that characterizes ecotype divergence. We assembled a joint linkage map using ddRADseq, and mapped quantitative trait loci (QTL) for traits that are divergent between ecotypes, including flowering time, plant size, physiological processes, and disease resistance. Overall, we found that most QTL had small to intermediate effects. While we identified colocalizing QTL for multiple traits, we did not find any large-effect QTL that clearly controlled multiple traits through pleiotropy or tight physical linkage. These results indicate that ecologically important traits in switchgrass have a complex genetic basis, and that similar loci may underlie divergence across the geographic range of the ecotypes.« less
The Genetic Basis of Upland/Lowland Ecotype Divergence in Switchgrass (Panicum virgatum)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Milano, E. R.; Lowry, D. B.; Juenger, T. E.
The evolution of locally adapted ecotypes is a common phenomenon that generates diversity within plant species. However, we know surprisingly little about the genetic mechanisms underlying the locally adapted traits involved in ecotype formation. The genetic architecture underlying locally adapted traits dictates how an organism will respond to environmental selection pressures, and has major implications for evolutionary ecology, conservation, and crop breeding. To understand the genetic architecture underlying the divergence of switchgrass (Panicum virgatum) ecotypes, we constructed a genetic mapping population through a four-way outbred cross between two northern upland and two southern lowland accessions. Trait segregation in this mappingmore » population was largely consistent with multiple independent loci controlling the suite of traits that characterizes ecotype divergence. We assembled a joint linkage map using ddRADseq, and mapped quantitative trait loci (QTL) for traits that are divergent between ecotypes, including flowering time, plant size, physiological processes, and disease resistance. Overall, we found that most QTL had small to intermediate effects. While we identified colocalizing QTL for multiple traits, we did not find any large-effect QTL that clearly controlled multiple traits through pleiotropy or tight physical linkage. These results indicate that ecologically important traits in switchgrass have a complex genetic basis, and that similar loci may underlie divergence across the geographic range of the ecotypes.« less
Phadnis, Nitin
2011-01-01
Understanding the genetic basis of reproductive isolation between recently diverged species is a central problem in evolutionary genetics. Here, I present analyses of the genetic architecture underlying hybrid male sterility and segregation distortion between the Bogota and USA subspecies of Drosophila pseudoobscura. Previously, a single gene, Overdrive (Ovd), was shown to be necessary but not sufficient for both male sterility and segregation distortion in F1 hybrids between these subspecies, requiring several interacting partner loci for full manifestation of hybrid phenomena. I map these partner loci separately on the Bogota X chromosome and USA autosomes using a combination of different mapping strategies. I find that hybrid sterility involves a single hybrid incompatibility of at least seven interacting partner genes that includes three large-effect loci. Segregation distortion involves three loci on the Bogota X chromosome and one locus on the autosomes. The genetic bases of hybrid sterility and segregation distortion are at least partially—but not completely—overlapping. My results lay the foundation for fine-mapping experiments to identify the complete set of genes that interact with Overdrive. While individual genes that cause hybrid sterility or inviability have been identified in a few cases, my analysis provides a comprehensive look at the genetic architecture of all components of a hybrid incompatibility underlying F1 hybrid sterility. Such an analysis would likely be unfeasible for most species pairs due to their divergence time and emphasizes the importance of young species pairs such as the D. pseudoobscura subspecies studied here. PMID:21900263
Evolutionary genetics of host shifts in herbivorous insects: insights from the age of genomics.
Vertacnik, Kim L; Linnen, Catherine R
2017-02-01
Adaptation to different host taxa is a key driver of insect diversification. Herbivorous insects are classic models for ecological and evolutionary research, but it is recent advances in sequencing, statistics, and molecular technologies that have cleared the way for investigations into the proximate genetic mechanisms underlying host shifts. In this review, we discuss how genome-scale data are revealing-at resolutions previously unimaginable-the genetic architecture of host-use traits, the causal loci underlying host shifts, and the predictability of host-use evolution. Collectively, these studies are providing novel insights into longstanding questions about host-use evolution. On the basis of this synthesis, we suggest that different host-use traits are likely to differ in their genetic architecture (number of causal loci and the nature of their genetic correlations) and genetic predictability (extent of gene or mutation reuse), indicating that any conclusions about the causes and consequences of host-use evolution will depend heavily on which host-use traits are investigated. To draw robust conclusions and identify general patterns in host-use evolution, we argue that investigation of diverse host-use traits and identification of causal genes and mutations should be the top priorities for future studies on the evolutionary genetics of host shifts. © 2017 New York Academy of Sciences.
Griswold, Cortland K
2015-12-21
Epistatic gene action occurs when mutations or alleles interact to produce a phenotype. Theoretically and empirically it is of interest to know whether gene interactions can facilitate the evolution of diversity. In this paper, we explore how epistatic gene action affects the additive genetic component or heritable component of multivariate trait variation, as well as how epistatic gene action affects the evolvability of multivariate traits. The analysis involves a sexually reproducing and recombining population. Our results indicate that under stabilizing selection conditions a population with a mixed additive and epistatic genetic architecture can have greater multivariate additive genetic variation and evolvability than a population with a purely additive genetic architecture. That greater multivariate additive genetic variation can occur with epistasis is in contrast to previous theory that indicated univariate additive genetic variation is decreased with epistasis under stabilizing selection conditions. In a multivariate setting, epistasis leads to less relative covariance among individuals in their genotypic, as well as their breeding values, which facilitates the maintenance of additive genetic variation and increases a population׳s evolvability. Our analysis involves linking the combinatorial nature of epistatic genetic effects to the ancestral graph structure of a population to provide insight into the consequences of epistasis on multivariate trait variation and evolution. Copyright © 2015 Elsevier Ltd. All rights reserved.
The genetic architecture of long QT syndrome: A critical reappraisal.
Giudicessi, John R; Wilde, Arthur A M; Ackerman, Michael J
2018-03-30
Collectively, the completion of the Human Genome Project and subsequent development of high-throughput next-generation sequencing methodologies have revolutionized genomic research. However, the rapid sequencing and analysis of thousands upon thousands of human exomes and genomes has taught us that most genes, including those known to cause heritable cardiovascular disorders such as long QT syndrome, harbor an unexpected background rate of rare, and presumably innocuous, non-synonymous genetic variation. In this Review, we aim to reappraise the genetic architecture underlying both the acquired and congenital forms of long QT syndrome by examining how the clinical phenotype associated with and background genetic variation in long QT syndrome-susceptibility genes impacts the clinical validity of existing gene-disease associations and the variant classification and reporting strategies that serve as the foundation for diagnostic long QT syndrome genetic testing. Copyright © 2018 Elsevier Inc. All rights reserved.
COMPLEXO: identifying the missing heritability of breast cancer via next generation collaboration.
Southey, Melissa C; Park, Daniel J; Nguyen-Dumont, Tu; Campbell, Ian; Thompson, Ella; Trainer, Alison H; Chenevix-Trench, Georgia; Simard, Jacques; Dumont, Martine; Soucy, Penny; Thomassen, Mads; Jønson, Lars; Pedersen, Inge S; Hansen, Thomas Vo; Nevanlinna, Heli; Khan, Sofia; Sinilnikova, Olga; Mazoyer, Sylvie; Lesueur, Fabienne; Damiola, Francesca; Schmutzler, Rita; Meindl, Alfons; Hahnen, Eric; Dufault, Michael R; Chris Chan, Tl; Kwong, Ava; Barkardóttir, Rosa; Radice, Paolo; Peterlongo, Paolo; Devilee, Peter; Hilbers, Florentine; Benitez, Javier; Kvist, Anders; Törngren, Therese; Easton, Douglas; Hunter, David; Lindstrom, Sara; Kraft, Peter; Zheng, Wei; Gao, Yu-Tang; Long, Jirong; Ramus, Susan; Feng, Bing-Jian; Weitzel, Jeffrey N; Nathanson, Katherine; Offit, Kenneth; Joseph, Vijai; Robson, Mark; Schrader, Kasmintan; Wang, San; Kim, Yeong C; Lynch, Henry; Snyder, Carrie; Tavtigian, Sean; Neuhausen, Susan; Couch, Fergus J; Goldgar, David E
2013-06-21
Linkage analysis, positional cloning, candidate gene mutation scanning and genome-wide association study approaches have all contributed significantly to our understanding of the underlying genetic architecture of breast cancer. Taken together, these approaches have identified genetic variation that explains approximately 30% of the overall familial risk of breast cancer, implying that more, and likely rarer, genetic susceptibility alleles remain to be discovered.
Application of Response Surface Methods To Determine Conditions for Optimal Genomic Prediction
Howard, Réka; Carriquiry, Alicia L.; Beavis, William D.
2017-01-01
An epistatic genetic architecture can have a significant impact on prediction accuracies of genomic prediction (GP) methods. Machine learning methods predict traits comprised of epistatic genetic architectures more accurately than statistical methods based on additive mixed linear models. The differences between these types of GP methods suggest a diagnostic for revealing genetic architectures underlying traits of interest. In addition to genetic architecture, the performance of GP methods may be influenced by the sample size of the training population, the number of QTL, and the proportion of phenotypic variability due to genotypic variability (heritability). Possible values for these factors and the number of combinations of the factor levels that influence the performance of GP methods can be large. Thus, efficient methods for identifying combinations of factor levels that produce most accurate GPs is needed. Herein, we employ response surface methods (RSMs) to find the experimental conditions that produce the most accurate GPs. We illustrate RSM with an example of simulated doubled haploid populations and identify the combination of factors that maximize the difference between prediction accuracies of best linear unbiased prediction (BLUP) and support vector machine (SVM) GP methods. The greatest impact on the response is due to the genetic architecture of the population, heritability of the trait, and the sample size. When epistasis is responsible for all of the genotypic variance and heritability is equal to one and the sample size of the training population is large, the advantage of using the SVM method vs. the BLUP method is greatest. However, except for values close to the maximum, most of the response surface shows little difference between the methods. We also determined that the conditions resulting in the greatest prediction accuracy for BLUP occurred when genetic architecture consists solely of additive effects, and heritability is equal to one. PMID:28720710
Evolution of genetic architecture under directional selection.
Hansen, Thomas F; Alvarez-Castro, José M; Carter, Ashley J R; Hermisson, Joachim; Wagner, Günter P
2006-08-01
We investigate the multilinear epistatic model under mutation-limited directional selection. We confirm previous results that only directional epistasis, in which genes on average reinforce or diminish each other's effects, contribute to the initial evolution of mutational effects. Thus, either canalization or decanalization can occur under directional selection, depending on whether positive or negative epistasis is prevalent. We then focus on the evolution of the epistatic coefficients themselves. In the absence of higher-order epistasis, positive pairwise epistasis will tend to weaken relative to additive effects, while negative pairwise epistasis will tend to become strengthened. Positive third-order epistasis will counteract these effects, while negative third-order epistasis will reinforce them. More generally, gene interactions of all orders have an inherent tendency for negative changes under directional selection, which can only be modified by higher-order directional epistasis. We identify three types of nonadditive quasi-equilibrium architectures that, although not strictly stable, can be maintained for an extended time: (1) nondirectional epistatic architectures; (2) canalized architectures with strong epistasis; and (3) near-additive architectures in which additive effects keep increasing relative to epistasis.
PAY1 improves plant architecture and enhances grain yield in rice.
Zhao, Lei; Tan, Lubin; Zhu, Zuofeng; Xiao, Langtao; Xie, Daoxin; Sun, Chuanqing
2015-08-01
Plant architecture, a complex of the important agronomic traits that determine grain yield, is a primary target of artificial selection of rice domestication and improvement. Some important genes affecting plant architecture and grain yield have been isolated and characterized in recent decades; however, their underlying mechanism remains to be elucidated. Here, we report genetic identification and functional analysis of the PLANT ARCHITECTURE AND YIELD 1 (PAY1) gene in rice, which affects plant architecture and grain yield in rice. Transgenic plants over-expressing PAY1 had twice the number of grains per panicle and consequently produced nearly 38% more grain yield per plant than control plants. Mechanistically, PAY1 could improve plant architecture via affecting polar auxin transport activity and altering endogenous indole-3-acetic acid distribution. Furthermore, introgression of PAY1 into elite rice cultivars, using marker-assisted background selection, dramatically increased grain yield compared with the recipient parents. Overall, these results demonstrated that PAY1 could be a new beneficial genetic resource for shaping ideal plant architecture and breeding high-yielding rice varieties. © 2015 The Authors The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.
How the Timing and Quality of Early Experiences Influence the Development of Brain Architecture
ERIC Educational Resources Information Center
Fox, Sharon E.; Levitt, Pat; Nelson, Charles A., III.
2010-01-01
Early life events can exert a powerful influence on both the pattern of brain architecture and behavioral development. In this study a conceptual framework is provided for considering how the structure of early experience gets "under the skin." The study begins with a description of the genetic framework that lays the foundation for brain…
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.
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.
USDA-ARS?s Scientific Manuscript database
Evaluating variability of rice response to concurrent increases in CO2 and temperature forecasted for future climates is a prerequisite step towards characterizing the genetic architecture underlying this response. Expanding on previous single cultivar studies, we evaluated eleven biogeographically ...
Genetic architecture and the evolution of sex.
Lohaus, Rolf; Burch, Christina L; Azevedo, Ricardo B R
2010-01-01
Theoretical investigations of the advantages of sex have tended to treat the genetic architecture of organisms as static and have not considered that genetic architecture might coevolve with reproductive mode. As a result, some potential advantages of sex may have been missed. Using a gene network model, we recently showed that recombination imposes selection for robustness to mutation and that negative epistasis can evolve as a by-product of this selection. These results motivated a detailed exploration of the mutational deterministic hypothesis, a hypothesis in which the advantage of sex depends critically on epistasis. We found that sexual populations do evolve higher mean fitness and lower genetic load than asexual populations at equilibrium, and, under moderate stabilizing selection and large population size, these equilibrium sexual populations resist invasion by asexuals. However, we found no evidence that these long- and short-term advantages to sex were explained by the negative epistasis that evolved in our experiments. The long-term advantage of sex was that sexual populations evolved a lower deleterious mutation rate, but this property was not sufficient to account for the ability of sexual populations to resist invasion by asexuals. The ability to resist asexual invasion was acquired simultaneously with an increase in recombinational robustness that minimized the cost of sex. These observations provide the first direct evidence that sexual reproduction does indeed select for conditions that favor its own maintenance. Furthermore, our results highlight the importance of considering a dynamic view of the genetic architecture to understand the evolution of sex and recombination.
Nishino, Jo; Kochi, Yuta; Shigemizu, Daichi; Kato, Mamoru; Ikari, Katsunori; Ochi, Hidenori; Noma, Hisashi; Matsui, Kota; Morizono, Takashi; Boroevich, Keith A.; Tsunoda, Tatsuhiko; Matsui, Shigeyuki
2018-01-01
Genome-wide association studies (GWAS) suggest that the genetic architecture of complex diseases consists of unexpectedly numerous variants with small effect sizes. However, the polygenic architectures of many diseases have not been well characterized due to lack of simple and fast methods for unbiased estimation of the underlying proportion of disease-associated variants and their effect-size distribution. Applying empirical Bayes estimation of semi-parametric hierarchical mixture models to GWAS summary statistics, we confirmed that schizophrenia was extremely polygenic [~40% of independent genome-wide SNPs are risk variants, most within odds ratio (OR = 1.03)], whereas rheumatoid arthritis was less polygenic (~4 to 8% risk variants, significant portion reaching OR = 1.05 to 1.1). For rheumatoid arthritis, stratified estimations revealed that expression quantitative loci in blood explained large genetic variance, and low- and high-frequency derived alleles were prone to be risk and protective, respectively, suggesting a predominance of deleterious-risk and advantageous-protective mutations. Despite genetic correlation, effect-size distributions for schizophrenia and bipolar disorder differed across allele frequency. These analyses distinguished disease polygenic architectures and provided clues for etiological differences in complex diseases. PMID:29740473
ERIC Educational Resources Information Center
Tosto, Maria G.; Hayiou-Thomas, Marianna E.; Harlaar, Nicole; Prom-Wormley, Elizabeth; Dale, Philip S.; Plomin, Robert
2017-01-01
This study examines the genetic and environmental etiology underlying the development of oral language and reading skills, and the relationship between them, over a long period of developmental time spanning middle childhood and adolescence. It focuses particularly on the differential relationship between language and two different aspects of…
The Genetic Architecture of Climatic Adaptation of Tropical Cattle
Porto-Neto, Laercio R.; Reverter, Antonio; Prayaga, Kishore C.; Chan, Eva K. F.; Johnston, David J.; Hawken, Rachel J.; Fordyce, Geoffry; Garcia, Jose Fernando; Sonstegard, Tad S.; Bolormaa, Sunduimijid; Goddard, Michael E.; Burrow, Heather M.; Henshall, John M.; Lehnert, Sigrid A.; Barendse, William
2014-01-01
Adaptation of global food systems to climate change is essential to feed the world. Tropical cattle production, a mainstay of profitability for farmers in the developing world, is dominated by heat, lack of water, poor quality feedstuffs, parasites, and tropical diseases. In these systems European cattle suffer significant stock loss, and the cross breeding of taurine x indicine cattle is unpredictable due to the dilution of adaptation to heat and tropical diseases. We explored the genetic architecture of ten traits of tropical cattle production using genome wide association studies of 4,662 animals varying from 0% to 100% indicine. We show that nine of the ten have genetic architectures that include genes of major effect, and in one case, a single location that accounted for more than 71% of the genetic variation. One genetic region in particular had effects on parasite resistance, yearling weight, body condition score, coat colour and penile sheath score. This region, extending 20 Mb on BTA5, appeared to be under genetic selection possibly through maintenance of haplotypes by breeders. We found that the amount of genetic variation and the genetic correlations between traits did not depend upon the degree of indicine content in the animals. Climate change is expected to expand some conditions of the tropics to more temperate environments, which may impact negatively on global livestock health and production. Our results point to several important genes that have large effects on adaptation that could be introduced into more temperate cattle without detrimental effects on productivity. PMID:25419663
Conservatism and novelty in the genetic architecture of adaptation in Heliconius butterflies.
Huber, B; Whibley, A; Poul, Y L; Navarro, N; Martin, A; Baxter, S; Shah, A; Gilles, B; Wirth, T; McMillan, W O; Joron, M
2015-05-01
Understanding the genetic architecture of adaptive traits has been at the centre of modern evolutionary biology since Fisher; however, evaluating how the genetic architecture of ecologically important traits influences their diversification has been hampered by the scarcity of empirical data. Now, high-throughput genomics facilitates the detailed exploration of variation in the genome-to-phenotype map among closely related taxa. Here, we investigate the evolution of wing pattern diversity in Heliconius, a clade of neotropical butterflies that have undergone an adaptive radiation for wing-pattern mimicry and are influenced by distinct selection regimes. Using crosses between natural wing-pattern variants, we used genome-wide restriction site-associated DNA (RAD) genotyping, traditional linkage mapping and multivariate image analysis to study the evolution of the architecture of adaptive variation in two closely related species: Heliconius hecale and H. ismenius. We implemented a new morphometric procedure for the analysis of whole-wing pattern variation, which allows visualising spatial heatmaps of genotype-to-phenotype association for each quantitative trait locus separately. We used the H. melpomene reference genome to fine-map variation for each major wing-patterning region uncovered, evaluated the role of candidate genes and compared genetic architectures across the genus. Our results show that, although the loci responding to mimicry selection are highly conserved between species, their effect size and phenotypic action vary throughout the clade. Multilocus architecture is ancestral and maintained across species under directional selection, whereas the single-locus (supergene) inheritance controlling polymorphism in H. numata appears to have evolved only once. Nevertheless, the conservatism in the wing-patterning toolkit found throughout the genus does not appear to constrain phenotypic evolution towards local adaptive optima.
The Molecular Basis of Development.
ERIC Educational Resources Information Center
Gehring, Walter J.
1985-01-01
Basic architecture of embryo development appears to be under homeobox control (a short stretch of DNA). Outlines research on this genetic segment in fruit flies which led to identification of this control on the embryo's spatial organization. Indicates that molecular mechanisms underlying development may be much more universal than previously…
Xue, Angli; Wang, Hongcheng; Zhu, Jun
2017-09-28
Startle behavior is important for survival, and abnormal startle responses are related to several neurological diseases. Drosophila melanogaster provides a powerful system to investigate the genetic underpinnings of variation in startle behavior. Since mechanically induced, startle responses and environmental conditions can be readily quantified and precisely controlled. The 156 wild-derived fully sequenced lines of the Drosophila Genetic Reference Panel (DGRP) were used to identify SNPs and transcripts associated with variation in startle behavior. The results validated highly significant effects of 33 quantitative trait SNPs (QTSs) and 81 quantitative trait transcripts (QTTs) directly associated with phenotypic variation of startle response. We also detected QTT variation controlled by 20 QTSs (tQTSs) and 73 transcripts (tQTTs). Association mapping based on genomic and transcriptomic data enabled us to construct a complex genetic network that underlies variation in startle behavior. Based on principles of evolutionary conservation, human orthologous genes could be superimposed on this network. This study provided both genetic and biological insights into the variation of startle response behavior of Drosophila melanogaster, and highlighted the importance of genetic network to understand the genetic architecture of complex traits.
Genetic Architecture of Skin and Eye Color in an African-European Admixed Population
Beleza, Sandra; Johnson, Nicholas A.; Candille, Sophie I.; Absher, Devin M.; Coram, Marc A.; Lopes, Jailson; Campos, Joana; Araújo, Isabel Inês; Anderson, Tovi M.; Vilhjálmsson, Bjarni J.; Nordborg, Magnus; Correia e Silva, António; Shriver, Mark D.; Rocha, Jorge
2013-01-01
Variation in human skin and eye color is substantial and especially apparent in admixed populations, yet the underlying genetic architecture is poorly understood because most genome-wide studies are based on individuals of European ancestry. We study pigmentary variation in 699 individuals from Cape Verde, where extensive West African/European admixture has given rise to a broad range in trait values and genomic ancestry proportions. We develop and apply a new approach for measuring eye color, and identify two major loci (HERC2[OCA2] P = 2.3×10−62, SLC24A5 P = 9.6×10−9) that account for both blue versus brown eye color and varying intensities of brown eye color. We identify four major loci (SLC24A5 P = 5.4×10−27, TYR P = 1.1×10−9, APBA2[OCA2] P = 1.5×10−8, SLC45A2 P = 6×10−9) for skin color that together account for 35% of the total variance, but the genetic component with the largest effect (∼44%) is average genomic ancestry. Our results suggest that adjacent cis-acting regulatory loci for OCA2 explain the relationship between skin and eye color, and point to an underlying genetic architecture in which several genes of moderate effect act together with many genes of small effect to explain ∼70% of the estimated heritability. PMID:23555287
A population genetic interpretation of GWAS findings for human quantitative traits
Bullaughey, Kevin; Hudson, Richard R.; Sella, Guy
2018-01-01
Human genome-wide association studies (GWASs) are revealing the genetic architecture of anthropomorphic and biomedical traits, i.e., the frequencies and effect sizes of variants that contribute to heritable variation in a trait. To interpret these findings, we need to understand how genetic architecture is shaped by basic population genetics processes—notably, by mutation, natural selection, and genetic drift. Because many quantitative traits are subject to stabilizing selection and because genetic variation that affects one trait often affects many others, we model the genetic architecture of a focal trait that arises under stabilizing selection in a multidimensional trait space. We solve the model for the phenotypic distribution and allelic dynamics at steady state and derive robust, closed-form solutions for summary statistics of the genetic architecture. Our results provide a simple interpretation for missing heritability and why it varies among traits. They predict that the distribution of variances contributed by loci identified in GWASs is well approximated by a simple functional form that depends on a single parameter: the expected contribution to genetic variance of a strongly selected site affecting the trait. We test this prediction against the results of GWASs for height and body mass index (BMI) and find that it fits the data well, allowing us to make inferences about the degree of pleiotropy and mutational target size for these traits. Our findings help to explain why the GWAS for height explains more of the heritable variance than the similarly sized GWAS for BMI and to predict the increase in explained heritability with study sample size. Considering the demographic history of European populations, in which these GWASs were performed, we further find that most of the associations they identified likely involve mutations that arose shortly before or during the Out-of-Africa bottleneck at sites with selection coefficients around s = 10−3. PMID:29547617
2013-01-01
Inherited retinal degenerative diseases (RDDs) display wide variation in their mode of inheritance, underlying genetic defects, age of onset, and phenotypic severity. Molecular mechanisms have not been delineated for many retinal diseases, and treatment options are limited. In most instances, genotype-phenotype correlations have not been elucidated because of extensive clinical and genetic heterogeneity. Next-generation sequencing (NGS) methods, including exome, genome, transcriptome and epigenome sequencing, provide novel avenues towards achieving comprehensive understanding of the genetic architecture of RDDs. Whole-exome sequencing (WES) has already revealed several new RDD genes, whereas RNA-Seq and ChIP-Seq analyses are expected to uncover novel aspects of gene regulation and biological networks that are involved in retinal development, aging and disease. In this review, we focus on the genetic characterization of retinal and macular degeneration using NGS technology and discuss the basic framework for further investigations. We also examine the challenges of NGS application in clinical diagnosis and management. PMID:24112618
Hallsson, Lára R; Björklund, Mats
2012-01-01
Knowledge of heritability and genetic correlations are of central importance in the study of adaptive trait evolution and genetic constraints. We use a paternal half-sib-full-sib breeding design to investigate the genetic architecture of three life-history and morphological traits in the seed beetle, Callosobruchus maculatus. Heritability was significant for all traits under observation and genetic correlations between traits (r(A)) were low. Interestingly, we found substantial sex-specific genetic effects and low genetic correlations between sexes (r(MF)) in traits that are only moderately (weight at emergence) to slightly (longevity) sexually dimorphic. Furthermore, we found an increased sire ([Formula: see text]) compared to dam ([Formula: see text]) variance component within trait and sex. Our results highlight that the genetic architecture even of the same trait should not be assumed to be the same for males and females. Furthermore, it raises the issue of the presence of unnoticed environmental effects that may inflate estimates of heritability. Overall, our study stresses the fact that estimates of quantitative genetic parameters are not only population, time, environment, but also sex specific. Thus, extrapolation between sexes and studies should be treated with caution.
Hallsson, Lára R; Björklund, Mats
2012-01-01
Knowledge of heritability and genetic correlations are of central importance in the study of adaptive trait evolution and genetic constraints. We use a paternal half-sib-full-sib breeding design to investigate the genetic architecture of three life-history and morphological traits in the seed beetle, Callosobruchus maculatus. Heritability was significant for all traits under observation and genetic correlations between traits (rA) were low. Interestingly, we found substantial sex-specific genetic effects and low genetic correlations between sexes (rMF) in traits that are only moderately (weight at emergence) to slightly (longevity) sexually dimorphic. Furthermore, we found an increased sire () compared to dam () variance component within trait and sex. Our results highlight that the genetic architecture even of the same trait should not be assumed to be the same for males and females. Furthermore, it raises the issue of the presence of unnoticed environmental effects that may inflate estimates of heritability. Overall, our study stresses the fact that estimates of quantitative genetic parameters are not only population, time, environment, but also sex specific. Thus, extrapolation between sexes and studies should be treated with caution. PMID:22408731
Bartholomé, Jérôme; Mabiala, André; Savelli, Bruno; Bert, Didier; Brendel, Oliver; Plomion, Christophe; Gion, Jean-Marc
2015-06-01
In the context of climate change, the water-use efficiency (WUE) of highly productive tree varieties, such as eucalypts, has become a major issue for breeding programmes. This study set out to dissect the genetic architecture of carbon isotope composition (δ(13) C), a proxy of WUE, across several environments. A family of Eucalyptus urophylla × E. grandis was planted in three trials and phenotyped for δ(13) C and growth traits. High-resolution genetic maps enabled us to target genomic regions underlying δ(13) C quantitative trait loci (QTLs) on the E. grandis genome. Of the 15 QTLs identified for δ(13) C, nine were stable across the environments and three displayed significant QTL-by-environment interaction, suggesting medium to high genetic determinism for this trait. Only one colocalization was found between growth and δ(13) C. Gene ontology (GO) term enrichment analysis suggested candidate genes related to foliar δ(13) C, including two involved in the regulation of stomatal movements. This study provides the first report of the genetic architecture of δ(13) C and its relation to growth in Eucalyptus. The low correlations found between the two traits at phenotypic and genetic levels suggest the possibility of improving the WUE of Eucalyptus varieties without having an impact on breeding for growth. © 2015 CIRAD. New Phytologist © 2015 New Phytologist Trust.
To Your Health: NLM update transcript - Genetic architecture of mental disorders
... html To Your Health: NLM update Transcript Genetic architecture of mental disorders : 04/30/2018 To use ... disorders may have a distinctive molecular or genetic architecture that may provide a way to better diagnose ...
Sexual selection and genetic colour polymorphisms in animals.
Wellenreuther, Maren; Svensson, Erik I; Hansson, Bengt
2014-11-01
Genetic colour polymorphisms are widespread across animals and often subjected to complex selection regimes. Traditionally, colour morphs were used as simple visual markers to measure allele frequency changes in nature, selection, population divergence and speciation. With advances in sequencing technology and analysis methods, several model systems are emerging where the molecular targets of selection are being described. Here, we discuss recent studies on the genetics of sexually selected colour polymorphisms, aiming at (i) reviewing the evidence of sexual selection on colour polymorphisms, (ii) highlighting the genetic architecture, molecular and developmental basis underlying phenotypic colour diversification and (iii) discuss how the maintenance of such polymorphisms might be facilitated or constrained by these. Studies of the genetic architecture of colour polymorphism point towards the importance of tight clustering of colour loci with other trait loci, such as in the case of inversions and supergene structures. Other interesting findings include linkage between colour loci and mate preferences or sex determination, and the role of introgression and regulatory variation in fuelling polymorphisms. We highlight that more studies are needed that explicitly integrate fitness consequences of sexual selection on colour with the underlying molecular targets of colour to gain insights into the evolutionary consequences of sexual selection on polymorphism maintenance. © 2014 John Wiley & Sons Ltd.
USDA-ARS?s Scientific Manuscript database
Cassava (Manihot esculenta) is a crucial, under-researched crop feeding millions worldwide, especially in Africa. Cassava mosaic disease (CMD) has plagued production in Africa for over a century. Bi-parental mapping studies suggest primarily a single major gene mediates resistance. To be certain and...
Wu, Yongzhen; Fu, Yongcai; Zhao, Shuangshuang; Gu, Ping; Zhu, Zuofeng; Sun, Chuanqing; Tan, Lubin
2016-01-01
Panicle architecture and seed size are important agronomic traits that directly determine grain yield in rice (Oryza sativa L.). Although a number of key genes controlling panicle architecture and seed size have been cloned and characterized in recent years, their genetic and molecular mechanisms remain unclear. In this study, we identified a mutant that produced panicles with fascicled primary branching and reduced seeds in size. We isolated the underlying CLUSTERED PRIMARY BRANCH 1 (CPB1) gene, a new allele of DWARF11 (D11) encoding a cytochrome P450 protein involved in brassinosteroid (BR) biosynthesis pathway. Genetic transformation experiments confirmed that a His360Leu amino acid substitution residing in the highly conserved region of CPB1/D11 was responsible for the panicle architecture and seed size changes in the cpb1 mutants. Overexpression of CPB1/D11 under the background of cpb1 mutant not only rescued normal panicle architecture and plant height, but also had a larger leaf angle and seed size than the controls. Furthermore, the CPB1/D11 transgenic plants driven by panicle-specific promoters can enlarge seed size and enhance grain yield without affecting other favourable agronomic traits. These results demonstrated that the specific mutation in CPB1/D11 influenced development of panicle architecture and seed size, and manipulation of CPB1/D11 expression using the panicle-specific promoter could be used to increase seed size, leading to grain yield improvement in rice. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.
Missing heritability and strategies for finding the underlying causes of complex disease
Eichler, Evan E.; Flint, Jonathan; Gibson, Greg; Kong, Augustine; Leal, Suzanne M.; Moore, Jason H.; Nadeau, Joseph H.
2010-01-01
Although recent genome-wide studies have provided valuable insights into the genetic basis of human disease, they have explained relatively little of the heritability of most complex traits, and the variants identified through these studies have small effect sizes. This has led to the important and hotly debated issue of where the ‘missing heritability’ of complex diseases might be found. Here, seven leading geneticists offer their opinion about where this heritability is likely to lie, what this could tell us about the underlying genetic architecture of common diseases and how this could inform research strategies for uncovering genetic risk factors. PMID:20479774
Wild emmer genome architecture and diversity elucidate wheat evolution and domestication.
Avni, Raz; Nave, Moran; Barad, Omer; Baruch, Kobi; Twardziok, Sven O; Gundlach, Heidrun; Hale, Iago; Mascher, Martin; Spannagl, Manuel; Wiebe, Krystalee; Jordan, Katherine W; Golan, Guy; Deek, Jasline; Ben-Zvi, Batsheva; Ben-Zvi, Gil; Himmelbach, Axel; MacLachlan, Ron P; Sharpe, Andrew G; Fritz, Allan; Ben-David, Roi; Budak, Hikmet; Fahima, Tzion; Korol, Abraham; Faris, Justin D; Hernandez, Alvaro; Mikel, Mark A; Levy, Avraham A; Steffenson, Brian; Maccaferri, Marco; Tuberosa, Roberto; Cattivelli, Luigi; Faccioli, Primetta; Ceriotti, Aldo; Kashkush, Khalil; Pourkheirandish, Mohammad; Komatsuda, Takao; Eilam, Tamar; Sela, Hanan; Sharon, Amir; Ohad, Nir; Chamovitz, Daniel A; Mayer, Klaus F X; Stein, Nils; Ronen, Gil; Peleg, Zvi; Pozniak, Curtis J; Akhunov, Eduard D; Distelfeld, Assaf
2017-07-07
Wheat ( Triticum spp.) is one of the founder crops that likely drove the Neolithic transition to sedentary agrarian societies in the Fertile Crescent more than 10,000 years ago. Identifying genetic modifications underlying wheat's domestication requires knowledge about the genome of its allo-tetraploid progenitor, wild emmer ( T. turgidum ssp. dicoccoides ). We report a 10.1-gigabase assembly of the 14 chromosomes of wild tetraploid wheat, as well as analyses of gene content, genome architecture, and genetic diversity. With this fully assembled polyploid wheat genome, we identified the causal mutations in Brittle Rachis 1 ( TtBtr1 ) genes controlling shattering, a key domestication trait. A study of genomic diversity among wild and domesticated accessions revealed genomic regions bearing the signature of selection under domestication. This reference assembly will serve as a resource for accelerating the genome-assisted improvement of modern wheat varieties. Copyright © 2017, American Association for the Advancement of Science.
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.
Genetic architecture and balancing selection: the life and death of differentiated variants.
Llaurens, Violaine; Whibley, Annabel; Joron, Mathieu
2017-05-01
Balancing selection describes any form of natural selection, which results in the persistence of multiple variants of a trait at intermediate frequencies within populations. By offering up a snapshot of multiple co-occurring functional variants and their interactions, systems under balancing selection can reveal the evolutionary mechanisms favouring the emergence and persistence of adaptive variation in natural populations. We here focus on the mechanisms by which several functional variants for a given trait can arise, a process typically requiring multiple epistatic mutations. We highlight how balancing selection can favour specific features in the genetic architecture and review the evolutionary and molecular mechanisms shaping this architecture. First, balancing selection affects the number of loci underlying differentiated traits and their respective effects. Control by one or few loci favours the persistence of differentiated functional variants by limiting intergenic recombination, or its impact, and may sometimes lead to the evolution of supergenes. Chromosomal rearrangements, particularly inversions, preventing adaptive combinations from being dissociated are increasingly being noted as features of such systems. Similarly, due to the frequency of heterozygotes maintained by balancing selection, dominance may be a key property of adaptive variants. High heterozygosity and limited recombination also influence associated genetic load, as linked recessive deleterious mutations may be sheltered. The capture of deleterious elements in a locus under balancing selection may reinforce polymorphism by further promoting heterozygotes. Finally, according to recent genomewide scans, balanced polymorphism might be more pervasive than generally thought. We stress the need for both functional and ecological studies to characterize the evolutionary mechanisms operating in these systems. © 2017 John Wiley & Sons Ltd.
Development and Genetic Control of Plant Architecture and Biomass in the Panicoid Grass, Setaria
Mauro-Herrera, Margarita; Doust, Andrew N.
2016-01-01
The architecture of a plant affects its ability to compete for light and to respond to environmental stresses, thus affecting overall fitness and productivity. Two components of architecture, branching and height, were studied in 182 F7 recombinant inbred lines (RILs) at the vegetative, flowering and mature developmental stages in the panicoid C4 model grass system, Setaria. The RIL population was derived from a cross between domesticated S. italica (foxtail millet) and its wild relative S. viridis (green foxtail). In both field and greenhouse trials the wild parent was taller initially, started branching earlier, and flowered earlier, while the domesticated parent was shorter initially, but flowered later, producing a robust tall plant architecture with more nodes and leaves on the main culm and few or no branches. Biomass was highly correlated with height of the plant and number of nodes on the main culm, and generally showed a negative relationship with branch number. However, several of the RILs with the highest biomass in both trials were significantly more branched than the domesticated parent of the cross. Quantitative trait loci (QTL) analyses indicate that both height and branching are controlled by multiple genetic regions, often with QTL for both traits colocalizing in the same genomic regions. Genomic positions of several QTL colocalize with QTL in syntenic regions in other species and contain genes known to control branching and height in sorghum, maize, and switchgrass. Included in these is the ortholog of the rice SD-1 semi-dwarfing gene, which underlies one of the major Setaria height QTL. Understanding the relationships between height and branching patterns in Setaria, and their genetic control, is an important step to gaining a comprehensive knowledge of the development and genetic regulation of panicoid grass architecture. PMID:26985990
Development and Genetic Control of Plant Architecture and Biomass in the Panicoid Grass, Setaria.
Mauro-Herrera, Margarita; Doust, Andrew N
2016-01-01
The architecture of a plant affects its ability to compete for light and to respond to environmental stresses, thus affecting overall fitness and productivity. Two components of architecture, branching and height, were studied in 182 F7 recombinant inbred lines (RILs) at the vegetative, flowering and mature developmental stages in the panicoid C4 model grass system, Setaria. The RIL population was derived from a cross between domesticated S. italica (foxtail millet) and its wild relative S. viridis (green foxtail). In both field and greenhouse trials the wild parent was taller initially, started branching earlier, and flowered earlier, while the domesticated parent was shorter initially, but flowered later, producing a robust tall plant architecture with more nodes and leaves on the main culm and few or no branches. Biomass was highly correlated with height of the plant and number of nodes on the main culm, and generally showed a negative relationship with branch number. However, several of the RILs with the highest biomass in both trials were significantly more branched than the domesticated parent of the cross. Quantitative trait loci (QTL) analyses indicate that both height and branching are controlled by multiple genetic regions, often with QTL for both traits colocalizing in the same genomic regions. Genomic positions of several QTL colocalize with QTL in syntenic regions in other species and contain genes known to control branching and height in sorghum, maize, and switchgrass. Included in these is the ortholog of the rice SD-1 semi-dwarfing gene, which underlies one of the major Setaria height QTL. Understanding the relationships between height and branching patterns in Setaria, and their genetic control, is an important step to gaining a comprehensive knowledge of the development and genetic regulation of panicoid grass architecture.
NASA Astrophysics Data System (ADS)
Uchida, Satoshi; Yamamoto, Hitoshi; Okada, Isamu; Sasaki, Tatsuya
2018-02-01
Indirect reciprocity is one of the basic mechanisms to sustain mutual cooperation, by which beneficial acts are returned, not by the recipient, but by third parties. This mechanism relies on the ability of individuals to know the past actions of others, and to assess those actions. There are many different systems of assessing others, which can be interpreted as rudimentary social norms (i.e., views on what is “good” or “bad”). In this paper, impacts of different adaptive architectures, i.e., ways for individuals to adapt to environments, on indirect reciprocity are investigated. We examine two representative architectures: one based on replicator dynamics and the other on genetic algorithm. Different from the replicator dynamics, the genetic algorithm requires describing the mixture of all possible norms in the norm space under consideration. Therefore, we also propose an analytic method to study norm ecosystems in which all possible second order social norms potentially exist and compete. The analysis reveals that the different adaptive architectures show different paths to the evolution of cooperation. Especially we find that so called Stern-Judging, one of the best studied norms in the literature, exhibits distinct behaviors in both architectures. On one hand, in the replicator dynamics, Stern-Judging remains alive and gets a majority steadily when the population reaches a cooperative state. On the other hand, in the genetic algorithm, it gets a majority only temporarily and becomes extinct in the end.
Atkinson, Elizabeth G.; Rogers, Jeffrey; Mahaney, Michael C.; Cox, Laura A.; Cheverud, James M.
2015-01-01
Folding of the primate brain cortex allows for improved neural processing power by increasing cortical surface area for the allocation of neurons. The arrangement of folds (sulci) and ridges (gyri) across the cerebral cortex is thought to reflect the underlying neural network. Gyrification, an adaptive trait with a unique evolutionary history, is affected by genetic factors different from those affecting brain volume. Using a large pedigreed population of ∼1000 Papio baboons, we address critical questions about the genetic architecture of primate brain folding, the interplay between genetics, brain anatomy, development, patterns of cortical–cortical connectivity, and gyrification’s potential for future evolution. Through Mantel testing and cluster analyses, we find that the baboon cortex is quite evolvable, with high integration between the genotype and phenotype. We further find significantly similar partitioning of variation between cortical development, anatomy, and connectivity, supporting the predictions of tension-based models for sulcal development. We identify a significant, moderate degree of genetic control over variation in sulcal length, with gyrus-shape features being more susceptible to environmental effects. Finally, through QTL mapping, we identify novel chromosomal regions affecting variation in brain folding. The most significant QTL contain compelling candidate genes, including gene clusters associated with Williams and Down syndromes. The QTL distribution suggests a complex genetic architecture for gyrification with both polygeny and pleiotropy. Our results provide a solid preliminary characterization of the genetic basis of primate brain folding, a unique and biomedically relevant phenotype with significant implications in primate brain evolution. PMID:25873632
Next Generation Image-Based Phenotyping of Root System Architecture
NASA Astrophysics Data System (ADS)
Davis, T. W.; Shaw, N. M.; Cheng, H.; Larson, B. G.; Craft, E. J.; Shaff, J. E.; Schneider, D. J.; Piñeros, M. A.; Kochian, L. V.
2016-12-01
The development of the Plant Root Imaging and Data Acquisition (PRIDA) hardware/software system enables researchers to collect digital images, along with all the relevant experimental details, of a range of hydroponically grown agricultural crop roots for 2D and 3D trait analysis. Previous efforts of image-based root phenotyping focused on young cereals, such as rice; however, there is a growing need to measure both older and larger root systems, such as those of maize and sorghum, to improve our understanding of the underlying genetics that control favorable rooting traits for plant breeding programs to combat the agricultural risks presented by climate change. Therefore, a larger imaging apparatus has been prototyped for capturing 3D root architecture with an adaptive control system and innovative plant root growth media that retains three-dimensional root architectural features. New publicly available multi-platform software has been released with considerations for both high throughput (e.g., 3D imaging of a single root system in under ten minutes) and high portability (e.g., support for the Raspberry Pi computer). The software features unified data collection, management, exploration and preservation for continued trait and genetics analysis of root system architecture. The new system makes data acquisition efficient and includes features that address the needs of researchers and technicians, such as reduced imaging time, semi-automated camera calibration with uncertainty characterization, and safe storage of the critical experimental data.
Nandamuri, Sri Pratima; Dalton, Brian E; Carleton, Karen L
2017-06-01
African cichlids are an exemplary system to study organismal diversity and rapid speciation. Species differ in external morphology including jaw shape and body coloration, but also differ in sensory systems including vision. All cichlids have 7 cone opsin genes with species differing broadly in which opsins are expressed. The differential opsin expression results in closely related species with substantial differences in spectral sensitivity of their photoreceptors. In this work, we take a first step in determining the genetic basis of opsin expression in cichlids. Using a second generation cross between 2 species with different opsin expression patterns, we make a conservative estimate that short wavelength opsin expression is regulated by a few loci. Genetic mapping in 96 F2 hybrids provides clear evidence of a cis-regulatory region for SWS1 opsin that explains 34% of the variation in expression between the 2 species. Additionally, in situ hybridization has shown that SWS1 and SWS2B opsins are coexpressed in individual single cones in the retinas of F2 progeny. Results from this work will contribute to a better understanding of the genetic architecture underlying opsin expression. This knowledge will help answer long-standing questions about the evolutionary processes fundamental to opsin expression variation and how this contributes to adaptive cichlid divergence. © The American Genetic Association 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Multivariate Analysis of the Cotton Seed Ionome Reveals a Shared Genetic Architecture
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
Santangelo, James S; Johnson, Marc T J; Ness, Rob W
2018-05-16
Urban environments offer the opportunity to study the role of adaptive and non-adaptive evolutionary processes on an unprecedented scale. While the presence of parallel clines in heritable phenotypic traits is often considered strong evidence for the role of natural selection, non-adaptive evolutionary processes can also generate clines, and this may be more likely when traits have a non-additive genetic basis due to epistasis. In this paper, we use spatially explicit simulations modelled according to the cyanogenesis (hydrogen cyanide, HCN) polymorphism in white clover ( Trifolium repens ) to examine the formation of phenotypic clines along urbanization gradients under varying levels of drift, gene flow and selection. HCN results from an epistatic interaction between two Mendelian-inherited loci. Our results demonstrate that the genetic architecture of this trait makes natural populations susceptible to decreases in HCN frequencies via drift. Gradients in the strength of drift across a landscape resulted in phenotypic clines with lower frequencies of HCN in strongly drifting populations, giving the misleading appearance of deterministic adaptive changes in the phenotype. Studies of heritable phenotypic change in urban populations should generate null models of phenotypic evolution based on the genetic architecture underlying focal traits prior to invoking selection's role in generating adaptive differentiation. © 2018 The Author(s).
Martin, Noland H; Sapir, Yuval; Arnold, Michael L
2008-04-01
In animal-pollinated plants, pollinator preferences for divergent floral forms can lead to partial reproductive isolation. We describe regions of plant genomes that affect pollinator preferences for two species of Louisiana Irises, Iris brevicaulis and Iris fulva, and their artificial hybrids. Iris brevicaulis and I. fulva possess bee and bird-pollination syndromes, respectively. Hummingbirds preferred I. fulva and under-visited both I. brevicaulis and backcrosses toward this species. Lepidopterans preferred I. fulva and backcrosses toward I. fulva, but also under-visited I. brevicaulis and I. brevicaulis backcrosses. Bumblebees preferred I. brevicaulis and F1 hybrids and rarely visited I. fulva. Although all three pollen vectors preferred one or the other species, these preferences did not prevent visitation to other hybrid/parental classes. Quantitative trait locus (QTL) mapping, in reciprocal BC1 mapping populations, defined the genetic architecture of loci that affected pollinator behavior. We detected six and nine QTLs that affected pollinator visitation rates in the BCIb and BCIf mapping populations, respectively, with as many as three QTLs detected for each trait. Overall, this study reflects the possible role of quantitative genetic factors in determining (1) reproductive isolation, (2) the pattern of pollinator-mediated genetic exchange, and thus (3) hybrid zone evolution.
Environmental effects on the structure of the G-matrix.
Wood, Corlett W; Brodie, Edmund D
2015-11-01
Genetic correlations between traits determine the multivariate response to selection in the short term, and thereby play a causal role in evolutionary change. Although individual studies have documented environmentally induced changes in genetic correlations, the nature and extent of environmental effects on multivariate genetic architecture across species and environments remain largely uncharacterized. We reviewed the literature for estimates of the genetic variance-covariance (G) matrix in multiple environments, and compared differences in G between environments to the divergence in G between conspecific populations (measured in a common garden). We found that the predicted evolutionary trajectory differed as strongly between environments as it did between populations. Between-environment differences in the underlying structure of G (total genetic variance and the relative magnitude and orientation of genetic correlations) were equal to or greater than between-population differences. Neither environmental novelty, nor the difference in mean phenotype predicted these differences in G. Our results suggest that environmental effects on multivariate genetic architecture may be comparable to the divergence that accumulates over dozens or hundreds of generations between populations. We outline avenues of future research to address the limitations of existing data and characterize the extent to which lability in genetic correlations shapes evolution in changing environments. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.
Morgante, Fabio; Huang, Wen; Maltecca, Christian; Mackay, Trudy F C
2018-06-01
Predicting complex phenotypes from genomic data is a fundamental aim of animal and plant breeding, where we wish to predict genetic merits of selection candidates; and of human genetics, where we wish to predict disease risk. While genomic prediction models work well with populations of related individuals and high linkage disequilibrium (LD) (e.g., livestock), comparable models perform poorly for populations of unrelated individuals and low LD (e.g., humans). We hypothesized that low prediction accuracies in the latter situation may occur when the genetics architecture of the trait departs from the infinitesimal and additive architecture assumed by most prediction models. We used simulated data for 10,000 lines based on sequence data from a population of unrelated, inbred Drosophila melanogaster lines to evaluate this hypothesis. We show that, even in very simplified scenarios meant as a stress test of the commonly used Genomic Best Linear Unbiased Predictor (G-BLUP) method, using all common variants yields low prediction accuracy regardless of the trait genetic architecture. However, prediction accuracy increases when predictions are informed by the genetic architecture inferred from mapping the top variants affecting main effects and interactions in the training data, provided there is sufficient power for mapping. When the true genetic architecture is largely or partially due to epistatic interactions, the additive model may not perform well, while models that account explicitly for interactions generally increase prediction accuracy. Our results indicate that accounting for genetic architecture can improve prediction accuracy for quantitative traits.
Comparative analysis of genetic architectures for nine developmental traits of rye.
Masojć, Piotr; Milczarski, P; Kruszona, P
2017-08-01
Genetic architectures of plant height, stem thickness, spike length, awn length, heading date, thousand-kernel weight, kernel length, leaf area and chlorophyll content were aligned on the DArT-based high-density map of the 541 × Ot1-3 RILs population of rye using the genes interaction assorting by divergent selection (GIABDS) method. Complex sets of QTL for particular traits contained 1-5 loci of the epistatic D class and 10-28 loci of the hypostatic, mostly R and E classes controlling traits variation through D-E or D-R types of two-loci interactions. QTL were distributed on each of the seven rye chromosomes in unique positions or as a coinciding loci for 2-8 traits. Detection of considerable numbers of the reversed (D', E' and R') classes of QTL might be attributed to the transgression effects observed for most of the studied traits. First examples of E* and F QTL classes, defined in the model, are reported for awn length, leaf area, thousand-kernel weight and kernel length. The results of this study extend experimental data to 11 quantitative traits (together with pre-harvest sprouting and alpha-amylase activity) for which genetic architectures fit the model of mechanism underlying alleles distribution within tails of bi-parental populations. They are also a valuable starting point for map-based search of genes underlying detected QTL and for planning advanced marker-assisted multi-trait breeding strategies.
Veturi, Yogasudha; Ritchie, Marylyn D
2018-01-01
Transcriptome-wide association studies (TWAS) have recently been employed as an approach that can draw upon the advantages of genome-wide association studies (GWAS) and gene expression studies to identify genes associated with complex traits. Unlike standard GWAS, summary level data suffices for TWAS and offers improved statistical power. Two popular TWAS methods include either (a) imputing the cis genetic component of gene expression from smaller sized studies (using multi-SNP prediction or MP) into much larger effective sample sizes afforded by GWAS - TWAS-MP or (b) using summary-based Mendelian randomization - TWAS-SMR. Although these methods have been effective at detecting functional variants, it remains unclear how extensive variability in the genetic architecture of complex traits and diseases impacts TWAS results. Our goal was to investigate the different scenarios under which these methods yielded enough power to detect significant expression-trait associations. In this study, we conducted extensive simulations based on 6000 randomly chosen, unrelated Caucasian males from Geisinger's MyCode population to compare the power to detect cis expression-trait associations (within 500 kb of a gene) using the above-described approaches. To test TWAS across varying genetic backgrounds we simulated gene expression and phenotype using different quantitative trait loci per gene and cis-expression /trait heritability under genetic models that differentiate the effect of causality from that of pleiotropy. For each gene, on a training set ranging from 100 to 1000 individuals, we either (a) estimated regression coefficients with gene expression as the response using five different methods: LASSO, elastic net, Bayesian LASSO, Bayesian spike-slab, and Bayesian ridge regression or (b) performed eQTL analysis. We then sampled with replacement 50,000, 150,000, and 300,000 individuals respectively from the testing set of the remaining 5000 individuals and conducted GWAS on each set. Subsequently, we integrated the GWAS summary statistics derived from the testing set with the weights (or eQTLs) derived from the training set to identify expression-trait associations using (a) TWAS-MP (b) TWAS-SMR (c) eQTL-based GWAS, or (d) standalone GWAS. Finally, we examined the power to detect functionally relevant genes using the different approaches under the considered simulation scenarios. In general, we observed great similarities among TWAS-MP methods although the Bayesian methods resulted in improved power in comparison to LASSO and elastic net as the trait architecture grew more complex while training sample sizes and expression heritability remained small. Finally, we observed high power under causality but very low to moderate power under pleiotropy.
Pacheco-Villalobos, David; Hardtke, Christian S
2012-06-05
Root system architecture is a trait that displays considerable plasticity because of its sensitivity to environmental stimuli. Nevertheless, to a significant degree it is genetically constrained as suggested by surveys of its natural genetic variation. A few regulators of root system architecture have been isolated as quantitative trait loci through the natural variation approach in the dicotyledon model, Arabidopsis. This provides proof of principle that allelic variation for root system architecture traits exists, is genetically tractable, and might be exploited for crop breeding. Beyond Arabidopsis, Brachypodium could serve as both a credible and experimentally accessible model for root system architecture variation in monocotyledons, as suggested by first glimpses of the different root morphologies of Brachypodium accessions. Whether a direct knowledge transfer gained from molecular model system studies will work in practice remains unclear however, because of a lack of comprehensive understanding of root system physiology in the native context. For instance, apart from a few notable exceptions, the adaptive value of genetic variation in root system modulators is unknown. Future studies should thus aim at comprehensive characterization of the role of genetic players in root system architecture variation by taking into account the native environmental conditions, in particular soil characteristics.
Gaitán-Espitia, Juan Diego; Marshall, Dustin; Dupont, Sam; Bacigalupe, Leonardo D.; Bodrossy, Levente; Hobday, Alistair J.
2017-01-01
Geographical gradients in selection can shape different genetic architectures in natural populations, reflecting potential genetic constraints for adaptive evolution under climate change. Investigation of natural pH/pCO2 variation in upwelling regions reveals different spatio-temporal patterns of natural selection, generating genetic and phenotypic clines in populations, and potentially leading to local adaptation, relevant to understanding effects of ocean acidification (OA). Strong directional selection, associated with intense and continuous upwellings, may have depleted genetic variation in populations within these upwelling regions, favouring increased tolerances to low pH but with an associated cost in other traits. In contrast, diversifying or weak directional selection in populations with seasonal upwellings or outside major upwelling regions may have resulted in higher genetic variances and the lack of genetic correlations among traits. Testing this hypothesis in geographical regions with similar environmental conditions to those predicted under climate change will build insights into how selection may act in the future and how populations may respond to stressors such as OA. PMID:28148831
HpQTL: a geometric morphometric platform to compute the genetic architecture of heterophylly.
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.
The genetics of human obesity.
Xia, Qianghua; Grant, Struan F A
2013-04-01
It has long been known that there is a genetic component to obesity, and that characterizing this underlying factor would likely offer the possibility of better intervention in the future. Monogenic obesity has proved to be relatively straightforward, with a combination of linkage analysis and mouse models facilitating the identification of multiple genes. In contrast, genome-wide association studies have successfully revealed a variety of genetic loci associated with the more common form of obesity, allowing for very strong consensus on the underlying genetic architecture of the phenotype for the first time. Although a number of significant findings have been made, it appears that very little of the apparent heritability of body mass index has actually been explained to date. New approaches for data analyses and advances in technology will be required to uncover the elusive missing heritability, and to aid in the identification of the key causative genetic underpinnings of obesity. © 2013 New York Academy of Sciences.
Sun, Zhengxi; Su, Chao; Yun, Jinxia; Jiang, Qiong; Wang, Lixiang; Wang, Youning; Cao, Dong; Zhao, Fang; Zhao, Qingsong; Zhang, Mengchen; Zhou, Bin; Zhang, Lei; Kong, Fanjiang; Liu, Baohui; Tong, Yiping; Li, Xia
2018-05-05
The optimization of plant architecture in order to breed high-yielding soya bean cultivars is a goal of researchers. Tall plants bearing many long branches are desired, but only modest success in reaching these goals has been achieved. MicroRNA156 (miR156)-SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SPL) gene modules play pivotal roles in controlling shoot architecture and other traits in crops like rice and wheat. However, the effects of miR156-SPL modules on soya bean architecture and yield, and the molecular mechanisms underlying these effects, remain largely unknown. In this study, we achieved substantial improvements in soya bean architecture and yield by overexpressing GmmiR156b. Transgenic plants produced significantly increased numbers of long branches, nodes and pods, and they exhibited an increased 100-seed weight, resulting in a 46%-63% increase in yield per plant. Intriguingly, GmmiR156b overexpression had no significant impact on plant height in a growth room or under field conditions; however, it increased stem thickness significantly. Our data indicate that GmmiR156b modulates these traits mainly via the direct cleavage of SPL transcripts. Moreover, we found that GmSPL9d is expressed in the shoot apical meristem and axillary meristems (AMs) of soya bean, and that GmSPL9d may regulate axillary bud formation and branching by physically interacting with the homeobox gene WUSCHEL (WUS), a central regulator of AM formation. Together, our results identify GmmiR156b as a promising target for the improvement of soya bean plant architecture and yields, and they reveal a new and conserved regulatory cascade involving miR156-SPL-WUS that will help researchers decipher the genetic basis of plant architecture. © 2018 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.
Paccard, Antoine; Van Buskirk, Josh; Willi, Yvonne
2016-05-01
Species distribution limits are hypothesized to be caused by small population size and limited genetic variation in ecologically relevant traits, but earlier studies have not evaluated genetic variation in multivariate phenotypes. We asked whether populations at the latitudinal edges of the distribution have altered quantitative genetic architecture of ecologically relevant traits compared with midlatitude populations. We calculated measures of evolutionary potential in nine Arabidopsis lyrata populations spanning the latitudinal range of the species in eastern and midwestern North America. Environments at the latitudinal extremes have reduced water availability, and therefore plants were assessed under wet and dry treatments. We estimated genetic variance-covariance (G-) matrices for 10 traits related to size, development, and water balance. Populations at southern and northern distribution edges had reduced levels of genetic variation across traits, but their G-matrices were more spherical; G-matrix orientation was unrelated to latitude. As a consequence, the predicted short-term response to selection was at least as strong in edge populations as in central populations. These results are consistent with genetic drift eroding variation and reducing the effectiveness of correlational selection at distribution margins. We conclude that genetic variation of isolated traits poorly predicts the capacity to evolve in response to multivariate selection and that the response to selection may frequently be greater than expected at species distribution margins because of genetic drift.
Effect of manipulating recombination rates on response to selection in livestock breeding programs.
Battagin, Mara; Gorjanc, Gregor; Faux, Anne-Michelle; Johnston, Susan E; Hickey, John M
2016-06-22
In this work, we performed simulations to explore the potential of manipulating recombination rates to increase response to selection in livestock breeding programs. We carried out ten replicates of several scenarios that followed a common overall structure but differed in the average rate of recombination along the genome (expressed as the length of a chromosome in Morgan), the genetic architecture of the trait under selection, and the selection intensity under truncation selection (expressed as the proportion of males selected). Recombination rates were defined by simulating nine different chromosome lengths: 0.10, 0.25, 0.50, 1, 2, 5, 10, 15 and 20 Morgan, respectively. One Morgan was considered to be the typical chromosome length for current livestock species. The genetic architecture was defined by the number of quantitative trait variants (QTV) that affected the trait under selection. Either a large (10,000) or a small (1000 or 500) number of QTV was simulated. Finally, the proportions of males selected under truncation selection as sires for the next generation were equal to 1.2, 2.4, 5, or 10 %. Increasing recombination rate increased the overall response to selection and decreased the loss of genetic variance. The difference in cumulative response between low and high recombination rates increased over generations. At low recombination rates, cumulative response to selection tended to asymptote sooner and the genetic variance was completely eroded. If the trait under selection was affected by few QTV, differences between low and high recombination rates still existed, but the selection limit was reached at all rates of recombination. Higher recombination rates can enhance the efficiency of breeding programs to turn genetic variation into response to selection. However, to increase response to selection significantly, the recombination rate would need to be increased 10- or 20-fold. The biological feasibility and consequences of such large increases in recombination rates are unknown.
Genetic architecture of adiposity and organ weight using combined generation QTL analysis.
Fawcett, Gloria L; Roseman, Charles C; Jarvis, Joseph P; Wang, Bing; Wolf, Jason B; Cheverud, James M
2008-08-01
We present here a detailed study of the genetic contributions to adult body size and adiposity in the LG,SM advanced intercross line (AIL), an obesity model. This study represents a first step in fine-mapping obesity quantitative trait loci (QTLs) in an AIL. QTLs for adiposity in this model were previously isolated to chromosomes 1, 6, 7, 8, 9, 12, 13, and 18. This study focuses on heritable contributions and the genetic architecture of fatpad and organ weights. We analyzed both the F(2) and F(3) generations of the LG,SM AIL population single-nucleotide polymorphism (SNP) genotyped with a marker density of approximately 4 cM. We replicate 88% of the previously identified obesity QTLs and identify 13 new obesity QTLs. Nearly half of the single-trait QTLs were sex-specific. Several broad QTL regions were resolved into multiple, narrower peaks. The 113 single-trait QTLs for organs and body weight clustered into 27 pleiotropic loci. A large number of epistatic interactions are described which begin to elucidate potential interacting molecular networks. We present a relatively rapid means to obtain fine-mapping details from AILs using dense marker maps and consecutive generations. Analysis of the complex genetic architecture underlying fatpad and organ weights in this model may eventually help to elucidate not only heritable contributions to obesity but also common gene sets for obesity and its comorbidities.
ViSEN: methodology and software for visualization of statistical epistasis networks
Hu, Ting; Chen, Yuanzhu; Kiralis, Jeff W.; Moore, Jason H.
2013-01-01
The non-linear interaction effect among multiple genetic factors, i.e. epistasis, has been recognized as a key component in understanding the underlying genetic basis of complex human diseases and phenotypic traits. Due to the statistical and computational complexity, most epistasis studies are limited to interactions with an order of two. We developed ViSEN to analyze and visualize epistatic interactions of both two-way and three-way. ViSEN not only identifies strong interactions among pairs or trios of genetic attributes, but also provides a global interaction map that shows neighborhood and clustering structures. This visualized information could be very helpful to infer the underlying genetic architecture of complex diseases and to generate plausible hypotheses for further biological validations. ViSEN is implemented in Java and freely available at https://sourceforge.net/projects/visen/. PMID:23468157
Genetics of coronary artery disease: discovery, biology and clinical translation
Khera, Amit V.; Kathiresan, Sekar
2018-01-01
Coronary artery disease is the leading global cause of mortality. Long recognized to be heritable, recent advances have started to unravel the genetic architecture of the disease. Common variant association studies have linked about 60 genetic loci to coronary risk. Large-scale gene sequencing efforts and functional studies have facilitated a better understanding of causal risk factors, elucidated underlying biology and informed the development of new therapeutics. Moving forward, genetic testing could enable precision medicine approaches, by identifying subgroups of patients at increased risk of CAD or those with a specific driving pathophysiology in whom a therapeutic or preventive approach is most useful. PMID:28286336
Jordan, Daniel M; Do, Ron
2018-04-11
While sequence-based genetic tests have long been available for specific loci, especially for Mendelian disease, the rapidly falling costs of genome-wide genotyping arrays, whole-exome sequencing, and whole-genome sequencing are moving us toward a future where full genomic information might inform the prognosis and treatment of a variety of diseases, including complex disease. Similarly, the availability of large populations with full genomic information has enabled new insights about the etiology and genetic architecture of complex disease. Insights from the latest generation of genomic studies suggest that our categorization of diseases as complex may conceal a wide spectrum of genetic architectures and causal mechanisms that ranges from Mendelian forms of complex disease to complex regulatory structures underlying Mendelian disease. Here, we review these insights, along with advances in the prediction of disease risk and outcomes from full genomic information. Expected final online publication date for the Annual Review of Genomics and Human Genetics Volume 19 is August 31, 2018. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
Glater, Elizabeth E.; Rockman, Matthew V.; Bargmann, Cornelia I.
2013-01-01
The nematode Caenorhabditis elegans can use olfaction to discriminate among different kinds of bacteria, its major food source. We asked how natural genetic variation contributes to choice behavior, focusing on differences in olfactory preference behavior between two wild-type C. elegans strains. The laboratory strain N2 strongly prefers the odor of Serratia marcescens, a soil bacterium that is pathogenic to C. elegans, to the odor of Escherichia coli, a commonly used laboratory food source. The divergent Hawaiian strain CB4856 has a weaker attraction to Serratia than the N2 strain, and this behavioral difference has a complex genetic basis. At least three quantitative trait loci (QTLs) from the CB4856 Hawaii strain (HW) with large effect sizes lead to reduced Serratia preference when introgressed into an N2 genetic background. These loci interact and have epistatic interactions with at least two antagonistic QTLs from HW that increase Serratia preference. The complex genetic architecture of this C. elegans trait is reminiscent of the architecture of mammalian metabolic and behavioral traits. PMID:24347628
Wild emmer genome architecture and diversity elucidate wheat evolution and domestication
USDA-ARS?s Scientific Manuscript database
Wheat (Triticum spp.) is one of the founder crops that likely drove the Neolithic transition to sedentary agrarian societies in the Fertile Crescent over 10,000 years ago. Identifying genetic modifications underlying wheat's domestication requires knowledge of the genome of its allo-tetraploid proge...
Uga, Yusaku; Sugimoto, Kazuhiko; Ogawa, Satoshi; Rane, Jagadish; Ishitani, Manabu; Hara, Naho; Kitomi, Yuka; Inukai, Yoshiaki; Ono, Kazuko; Kanno, Noriko; Inoue, Haruhiko; Takehisa, Hinako; Motoyama, Ritsuko; Nagamura, Yoshiaki; Wu, Jianzhong; Matsumoto, Takashi; Takai, Toshiyuki; Okuno, Kazutoshi; Yano, Masahiro
2013-09-01
The genetic improvement of drought resistance is essential for stable and adequate crop production in drought-prone areas. Here we demonstrate that alteration of root system architecture improves drought avoidance through the cloning and characterization of DEEPER ROOTING 1 (DRO1), a rice quantitative trait locus controlling root growth angle. DRO1 is negatively regulated by auxin and is involved in cell elongation in the root tip that causes asymmetric root growth and downward bending of the root in response to gravity. Higher expression of DRO1 increases the root growth angle, whereby roots grow in a more downward direction. Introducing DRO1 into a shallow-rooting rice cultivar by backcrossing enabled the resulting line to avoid drought by increasing deep rooting, which maintained high yield performance under drought conditions relative to the recipient cultivar. Our experiments suggest that control of root system architecture will contribute to drought avoidance in crops.
Coyne, Michael J; Roelofs, Kevin G; Comstock, Laurie E
2016-01-15
Type VI secretion systems (T6SSs) are contact-dependent antagonistic systems employed by Gram negative bacteria to intoxicate other bacteria or eukaryotic cells. T6SSs were recently discovered in a few Bacteroidetes strains, thereby extending the presence of these systems beyond Proteobacteria. The present study was designed to analyze in a global nature the diversity, abundance, and properties of T6SSs in the Bacteroidales, the most predominant Gram negative bacterial order of the human gut. By performing extensive bioinformatics analyses and creating hidden Markov models for Bacteroidales Tss proteins, we identified 130 T6SS loci in 205 human gut Bacteroidales genomes. Of the 13 core T6SS proteins of Proteobacteria, human gut Bacteroidales T6SS loci encode orthologs of nine, and an additional five other core proteins not present in Proteobacterial T6SSs. The Bacteroidales T6SS loci segregate into three distinct genetic architectures with extensive DNA identity between loci of a given genetic architecture. We found that divergent DNA regions of a genetic architecture encode numerous types of effector and immunity proteins and likely include new classes of these proteins. TheT6SS loci of genetic architecture 1 are contained on highly similar integrative conjugative elements (ICEs), as are the T6SS loci of genetic architecture 2, whereas the T6SS loci of genetic architecture 3 are not and are confined to Bacteroides fragilis. Using collections of co-resident Bacteroidales strains from human subjects, we provide evidence for the transfer of genetic architecture 1 T6SS loci among co-resident Bacteroidales species in the human gut. However, we also found that established ecosystems can harbor strains with distinct T6SS of all genetic architectures. This is the first study to comprehensively analyze of the presence and diversity of T6SS loci within an order of bacteria and to analyze T6SSs of bacteria from a natural community. These studies demonstrate that more than half of our gut Bacteroidales, equivalent to about ¼ of the bacteria of this ecosystem, encode T6SSs. The data reveal several novel properties of these systems and suggest that antagonism between or distributed defense among these abundant intestinal bacteria may be common in established human gut communities.
Predicting the difficulty of pure, strict, epistatic models: metrics for simulated model selection.
Urbanowicz, Ryan J; Kiralis, Jeff; Fisher, Jonathan M; Moore, Jason H
2012-09-26
Algorithms designed to detect complex genetic disease associations are initially evaluated using simulated datasets. Typical evaluations vary constraints that influence the correct detection of underlying models (i.e. number of loci, heritability, and minor allele frequency). Such studies neglect to account for model architecture (i.e. the unique specification and arrangement of penetrance values comprising the genetic model), which alone can influence the detectability of a model. In order to design a simulation study which efficiently takes architecture into account, a reliable metric is needed for model selection. We evaluate three metrics as predictors of relative model detection difficulty derived from previous works: (1) Penetrance table variance (PTV), (2) customized odds ratio (COR), and (3) our own Ease of Detection Measure (EDM), calculated from the penetrance values and respective genotype frequencies of each simulated genetic model. We evaluate the reliability of these metrics across three very different data search algorithms, each with the capacity to detect epistatic interactions. We find that a model's EDM and COR are each stronger predictors of model detection success than heritability. This study formally identifies and evaluates metrics which quantify model detection difficulty. We utilize these metrics to intelligently select models from a population of potential architectures. This allows for an improved simulation study design which accounts for differences in detection difficulty attributed to model architecture. We implement the calculation and utilization of EDM and COR into GAMETES, an algorithm which rapidly and precisely generates pure, strict, n-locus epistatic models.
Identification of gene networks underlying dystocia in dairy cattle
USDA-ARS?s Scientific Manuscript database
Dystocia is a trait with a high impact in the dairy industry. Among its risk factors are calf weight, gestation length, breed and conformation. Biological networks have been proposed to capture the genetic architecture of complex traits, where GWAS show limitations. The objective of this study was t...
Genetic Basis of Haloperidol Resistance in Saccharomyces cerevisiae Is Complex and Dose Dependent
Wang, Xin; Kruglyak, Leonid
2014-01-01
The genetic basis of most heritable traits is complex. Inhibitory compounds and their effects in model organisms have been used in many studies to gain insights into the genetic architecture underlying quantitative traits. However, the differential effect of compound concentration has not been studied in detail. In this study, we used a large segregant panel from a cross between two genetically divergent yeast strains, BY4724 (a laboratory strain) and RM11_1a (a vineyard strain), to study the genetic basis of variation in response to different doses of a drug. Linkage analysis revealed that the genetic architecture of resistance to the small-molecule therapeutic drug haloperidol is highly dose-dependent. Some of the loci identified had effects only at low doses of haloperidol, while other loci had effects primarily at higher concentrations of the drug. We show that a major QTL affecting resistance across all concentrations of haloperidol is caused by polymorphisms in SWH1, a homologue of human oxysterol binding protein. We identify a complex set of interactions among the alleles of the genes SWH1, MKT1, and IRA2 that are most pronounced at a haloperidol dose of 200 µM and are only observed when the remainder of the genome is of the RM background. Our results provide further insight into the genetic basis of drug resistance. PMID:25521586
Complex genetic diseases: controversy over the Croesus code.
Wright, A F; Hastie, N D
2001-01-01
The polarization of views on how best to exploit new information from the Human Genome Project for medicine reflects our ignorance of the genetic architecture underlying common diseases: are susceptibility alleles common or rare, neutral or deleterious, few or many? Single-nucleotide polymorphism (SNP) technology is almost in place to dissect such diseases and to create a personalized medicine, but success is critically dependent on the biology and "Nature to be commanded must be obeyed" (Francis Bacon, 1620, Novum Organum).
An Association Mapping Framework To Account for Potential Sex Difference in Genetic Architectures.
Kang, Eun Yong; Lee, Cue Hyunkyu; Furlotte, Nicholas A; Joo, Jong Wha J; Kostem, Emrah; Zaitlen, Noah; Eskin, Eleazar; Han, Buhm
2018-05-11
Over the past few years, genome-wide association studies have identified many trait-associated loci that have different effects on females and males, which increased attention to the genetic architecture differences between the sexes. The between-sex differences in genetic architectures can cause a variety of phenomena such as differences in the effect sizes at trait-associated loci, differences in the magnitudes of polygenic background effects, and differences in the phenotypic variances. However, current association testing approaches for dealing with sex, such as including sex as a covariate, cannot fully account for these phenomena and can be suboptimal in statistical power. We present a novel association mapping framework, MetaSex, that can comprehensively account for the genetic architecture differences between the sexes. Through simulations and applications to real data, we show that our framework has superior performance than previous approaches in association mapping. Copyright © 2018, Genetics.
Gaitán-Espitia, Juan Diego; Marshall, Dustin; Dupont, Sam; Bacigalupe, Leonardo D; Bodrossy, Levente; Hobday, Alistair J
2017-02-01
Geographical gradients in selection can shape different genetic architectures in natural populations, reflecting potential genetic constraints for adaptive evolution under climate change. Investigation of natural pH/pCO 2 variation in upwelling regions reveals different spatio-temporal patterns of natural selection, generating genetic and phenotypic clines in populations, and potentially leading to local adaptation, relevant to understanding effects of ocean acidification (OA). Strong directional selection, associated with intense and continuous upwellings, may have depleted genetic variation in populations within these upwelling regions, favouring increased tolerances to low pH but with an associated cost in other traits. In contrast, diversifying or weak directional selection in populations with seasonal upwellings or outside major upwelling regions may have resulted in higher genetic variances and the lack of genetic correlations among traits. Testing this hypothesis in geographical regions with similar environmental conditions to those predicted under climate change will build insights into how selection may act in the future and how populations may respond to stressors such as OA. © 2017 The Author(s).
Systems genetics approaches to understand complex traits
Civelek, Mete; Lusis, Aldons J.
2014-01-01
Systems genetics is an approach to understand the flow of biological information that underlies complex traits. It uses a range of experimental and statistical methods to quantitate and integrate intermediate phenotypes, such as transcript, protein or metabolite levels, in populations that vary for traits of interest. Systems genetics studies have provided the first global view of the molecular architecture of complex traits and are useful for the identification of genes, pathways and networks that underlie common human diseases. Given the urgent need to understand how the thousands of loci that have been identified in genome-wide association studies contribute to disease susceptibility, systems genetics is likely to become an increasingly important approach to understanding both biology and disease. PMID:24296534
Linnen, Catherine R; O'Quin, Claire T; Shackleford, Taylor; Sears, Connor R; Lindstedt, Carita
2018-05-01
Pigmentation has emerged as a premier model for understanding the genetic basis of phenotypic evolution, and a growing catalog of color loci is starting to reveal biases in the mutations, genes, and genetic architectures underlying color variation in the wild. However, existing studies have sampled a limited subset of taxa, color traits, and developmental stages. To expand the existing sample of color loci, we performed QTL mapping analyses on two types of larval pigmentation traits that vary among populations of the redheaded pine sawfly ( Neodiprion lecontei ): carotenoid-based yellow body color and melanin-based spotting pattern. For both traits, our QTL models explained a substantial proportion of phenotypic variation and suggested a genetic architecture that is neither monogenic nor highly polygenic. Additionally, we used our linkage map to anchor the current N. lecontei genome assembly. With these data, we identified promising candidate genes underlying (1) a loss of yellow pigmentation in populations in the mid-Atlantic/northeastern United States [C locus-associated membrane protein homologous to a mammalian HDL receptor-2 gene ( Cameo2 ) and lipid transfer particle apolipoproteins II and I gene ( apoLTP-II/I )], and (2) a pronounced reduction in black spotting in Great Lakes populations [members of the yellow gene family, tyrosine hydroxylase gene ( pale ), and dopamine N -acetyltransferase gene ( Dat )]. Several of these genes also contribute to color variation in other wild and domesticated taxa. Overall, our findings are consistent with the hypothesis that predictable genes of large effect contribute to color evolution in nature. Copyright © 2018 by the Genetics Society of America.
Genetic studies of Crohn's disease: Past, present and future
Liu, Jimmy Z.; Anderson, Carl A.
2014-01-01
The exact aetiology of Crohn's disease is unknown, though it is clear from early epidemiological studies that a combination of genetic and environmental risk factors contributes to an individual's disease susceptibility. Here, we review the history of gene-mapping studies of Crohn's disease, from the linkage-based studies that first implicated the NOD2 locus, through to modern-day genome-wide association studies that have discovered over 140 loci associated with Crohn's disease and yielded novel insights into the biological pathways underlying pathogenesis. We describe on-going and future gene-mapping studies that utilise next generation sequencing technology to pinpoint causal variants and identify rare genetic variation underlying Crohn's disease risk. We comment on the utility of genetic markers for predicting an individual's disease risk and discuss their potential for identifying novel drug targets and influencing disease management. Finally, we describe how these studies have shaped and continue to shape our understanding of the genetic architecture of Crohn's disease. PMID:24913378
Zhang, Hengyou; Song, Qijian; Griffin, Joshua D; Song, Bao-Hua
2017-12-01
The soybean cyst nematode (SCN) is one of the most destructive pathogens of soybean plants worldwide. Host-plant resistance is an environmentally friendly method to mitigate SCN damage. To date, the resistant soybean cultivars harbor limited genetic variation, and some are losing resistance. Thus, a better understanding of the genetic mechanisms of the SCN resistance, as well as developing diverse resistant soybean cultivars, is urgently needed. In this study, a genome-wide association study (GWAS) was conducted using 1032 wild soybean (Glycine soja) accessions with over 42,000 single-nucleotide polymorphisms (SNPs) to understand the genetic architecture of G. soja resistance to SCN race 1. Ten SNPs were significantly associated with the response to race 1. Three SNPs on chromosome 18 were localized within the previously identified quantitative trait loci (QTLs), and two of which were localized within a strong linkage disequilibrium block encompassing a nucleotide-binding (NB)-ARC disease resistance gene (Glyma.18G102600). Genes encoding methyltransferases, the calcium-dependent signaling protein, the leucine-rich repeat kinase family protein, and the NB-ARC disease resistance protein, were identified as promising candidate genes. The identified SNPs and candidate genes can not only shed light on the molecular mechanisms underlying SCN resistance, but also can facilitate soybean improvement employing wild genetic resources.
Oppenheim, Sara J; Gould, Fred; Hopper, Keith R
2018-03-01
Intraspecific variation in ecologically important traits is a cornerstone of Darwin's theory of evolution by natural selection. The evolution and maintenance of this variation depends on genetic architecture, which in turn determines responses to natural selection. Some models suggest that traits with complex architectures are less likely to respond to selection than those with simple architectures, yet rapid divergence has been observed in such traits. The simultaneous evolutionary lability and genetic complexity of host plant use in the Lepidopteran subfamily Heliothinae suggest that architecture may not constrain ecological adaptation in this group. Here we investigate the response of Chloridea virescens, a generalist that feeds on diverse plant species, to selection for performance on a novel host, Physalis angulata (Solanaceae). P. angulata is the preferred host of Chloridea subflexa, a narrow specialist on the genus Physalis. In previous experiments, we found that the performance of C. subflexa on P. angulata depends on many loci of small effect distributed throughout the genome, but whether the same architecture would be involved in the generalist's adoption of P. angulata was unknown. Here we report a rapid response to selection in C. virescens for performance on P. angulata, and establish that the genetic architecture of intraspecific variation is quite similar to that of the interspecific differences in terms of the number, distribution, and effect sizes of the QTL involved. We discuss the impact of genetic architecture on the ability of Heliothine moths to respond to varying ecological selection pressures.
The variable genomic architecture of isolation between hybridizing species of house mice.
Teeter, Katherine C; Thibodeau, Lisa M; Gompert, Zachariah; Buerkle, C Alex; Nachman, Michael W; Tucker, Priscilla K
2010-02-01
Studies of the genetics of hybrid zones can provide insight into the genomic architecture of species boundaries. By examining patterns of introgression of multiple loci across a hybrid zone, it may be possible to identify regions of the genome that have experienced selection. Here, we present a comparison of introgression in two replicate transects through the house mouse hybrid zone through central Europe, using data from 41 single nucleotide markers. Using both genomic and geographic clines, we found many differences in patterns of introgression between the two transects, as well as some similarities. We found that many loci may have experienced the effects of selection at linked sites, including selection against hybrid genotypes, as well as positive selection in the form of genotypes introgressed into a foreign genetic background. We also found many positive associations of conspecific alleles among unlinked markers, which could be caused by epistatic interactions. Different patterns of introgression in the two transects highlight the challenge of using hybrid zones to identify genes underlying isolation and raise the possibility that the genetic basis of isolation between these species may be dependent on the local population genetic make-up or the local ecological setting.
Bieri, Jonas; Kawecki, Tadeusz J
2003-02-01
We investigated the genetic architecture underlying differentiation in fitness-related traits between two pairs of populations of the seed beetle Callosobruchus maculatus (Coleoptera: Bruchidae). These populations had geographically distant (> 2000 km) origins but evolved in a uniform laboratory environment for 120 generations. For each pair of populations (Nigeria x Yemen and Cameroon x Uganda) we estimated the means of five fitness-related characters and a measure of fitness (net reproductive rate R0) in each of the parental populations and 12 types of hybrids (two F1 and two F2 lines and eight backcrosses). Models containing up to nine composite genetic parameters were fitted to the means of the 14 lines. The patterns of line means for all traits in the Nigeria x Yemen cross and for four traits (larval survival, developmental rate, female body weight, and fecundity) in the Cameroon x Uganda cross were best explained by models including additive, dominance, and maternal effects, but excluding epistasis. We did not find any evidence for outbreeding depression for any trait. An epistatic component of divergence was detected for egg hatching success and R0 in the Cameroon x Uganda cross, but its sign was opposite to that expected under outbreeding depression, that is, additive x additive epistasis had a positive effect on the performance of F2 hybrids. All traits except fecundity showed a pattern of heterosis. A large difference of egg-hatching success between the two reciprocal F1 lines in that cross was best explained as fertilization incompatibility between Cameroon females and sperm carrying Uganda genes. The results suggest that these populations have not converged to the same life-history phenotype and genetic architecture, despite 120 generations of uniform natural selection. However, the absence of outbreeding depression implies that they did not evolve toward different adaptive peaks.
Baseline genetic associations in the Parkinson's Progression Markers Initiative (PPMI).
Nalls, Mike A; Keller, Margaux F; Hernandez, Dena G; Chen, Lan; Stone, David J; Singleton, Andrew B
2016-01-01
The Parkinson's Progression Marker Initiative is an international multicenter study whose main goal is investigating markers for Parkinson's disease (PD) progression as part of a path to a treatment for the disease. This manuscript describes the baseline genetic architecture of this study, providing not only a catalog of disease-linked variants and mutations, but also quantitative measures with which to adjust for population structure. Three hundred eighty-three newly diagnosed typical PD cases, 65 atypical PD and 178 healthy controls, from the Parkinson's Progression Marker Initiative study have been genotyped on the NeuroX or Immunochip arrays. These data are freely available to all researchers interested in pursuing PD research within the Parkinson's Progression Marker Initiative. The Parkinson's Progression Marker Initiative represents a study population with low genetic heterogeneity. We recapitulate known PD associations from large-scale genome-wide association studies and refine genetic risk score models for PD predictability (area under the curve, ∼0.74). We show the presence of six LRRK2 p.G2019S and nine GBA p.N370S mutation carriers. The Parkinson's Progression Marker Initiative study and its genetic data are useful in studies of PD biomarkers. The genetic architecture described here will be useful in the analysis of myriad biological and clinical traits within this study. © 2015 International Parkinson and Movement Disorder Society.
Thorleifsson, Gudmar; Ahluwalia, Tarunveer S.; Steinthorsdottir, Valgerdur; Bjarnason, Helgi; Gudbjartsson, Daniel F.; Magnusson, Olafur T.; Sparsø, Thomas; Albrechtsen, Anders; Kong, Augustine; Masson, Gisli; Tian, Geng; Cao, Hongzhi; Nie, Chao; Kristiansen, Karsten; Husemoen, Lise Lotte; Thuesen, Betina; Li, Yingrui; Nielsen, Rasmus; Linneberg, Allan; Olafsson, Isleifur; Eyjolfsson, Gudmundur I.; Jørgensen, Torben; Wang, Jun; Hansen, Torben; Thorsteinsdottir, Unnur; Stefánsson, Kari; Pedersen, Oluf
2013-01-01
Genome-wide association studies have mainly relied on common HapMap sequence variations. Recently, sequencing approaches have allowed analysis of low frequency and rare variants in conjunction with common variants, thereby improving the search for functional variants and thus the understanding of the underlying biology of human traits and diseases. Here, we used a large Icelandic whole genome sequence dataset combined with Danish exome sequence data to gain insight into the genetic architecture of serum levels of vitamin B12 (B12) and folate. Up to 22.9 million sequence variants were analyzed in combined samples of 45,576 and 37,341 individuals with serum B12 and folate measurements, respectively. We found six novel loci associating with serum B12 (CD320, TCN2, ABCD4, MMAA, MMACHC) or folate levels (FOLR3) and confirmed seven loci for these traits (TCN1, FUT6, FUT2, CUBN, CLYBL, MUT, MTHFR). Conditional analyses established that four loci contain additional independent signals. Interestingly, 13 of the 18 identified variants were coding and 11 of the 13 target genes have known functions related to B12 and folate pathways. Contrary to epidemiological studies we did not find consistent association of the variants with cardiovascular diseases, cancers or Alzheimer's disease although some variants demonstrated pleiotropic effects. Although to some degree impeded by low statistical power for some of these conditions, these data suggest that sequence variants that contribute to the population diversity in serum B12 or folate levels do not modify the risk of developing these conditions. Yet, the study demonstrates the value of combining whole genome and exome sequencing approaches to ascertain the genetic and molecular architectures underlying quantitative trait associations. PMID:23754956
Genetics of the Framingham Heart Study Population
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
Genetic pleiotropy explains associations between musical auditory discrimination and intelligence.
Mosing, Miriam A; Pedersen, Nancy L; Madison, Guy; Ullén, Fredrik
2014-01-01
Musical aptitude is commonly measured using tasks that involve discrimination of different types of musical auditory stimuli. Performance on such different discrimination tasks correlates positively with each other and with intelligence. However, no study to date has explored these associations using a genetically informative sample to estimate underlying genetic and environmental influences. In the present study, a large sample of Swedish twins (N = 10,500) was used to investigate the genetic architecture of the associations between intelligence and performance on three musical auditory discrimination tasks (rhythm, melody and pitch). Phenotypic correlations between the tasks ranged between 0.23 and 0.42 (Pearson r values). Genetic modelling showed that the covariation between the variables could be explained by shared genetic influences. Neither shared, nor non-shared environment had a significant effect on the associations. Good fit was obtained with a two-factor model where one underlying shared genetic factor explained all the covariation between the musical discrimination tasks and IQ, and a second genetic factor explained variance exclusively shared among the discrimination tasks. The results suggest that positive correlations among musical aptitudes result from both genes with broad effects on cognition, and genes with potentially more specific influences on auditory functions.
Genetic Pleiotropy Explains Associations between Musical Auditory Discrimination and Intelligence
Mosing, Miriam A.; Pedersen, Nancy L.; Madison, Guy; Ullén, Fredrik
2014-01-01
Musical aptitude is commonly measured using tasks that involve discrimination of different types of musical auditory stimuli. Performance on such different discrimination tasks correlates positively with each other and with intelligence. However, no study to date has explored these associations using a genetically informative sample to estimate underlying genetic and environmental influences. In the present study, a large sample of Swedish twins (N = 10,500) was used to investigate the genetic architecture of the associations between intelligence and performance on three musical auditory discrimination tasks (rhythm, melody and pitch). Phenotypic correlations between the tasks ranged between 0.23 and 0.42 (Pearson r values). Genetic modelling showed that the covariation between the variables could be explained by shared genetic influences. Neither shared, nor non-shared environment had a significant effect on the associations. Good fit was obtained with a two-factor model where one underlying shared genetic factor explained all the covariation between the musical discrimination tasks and IQ, and a second genetic factor explained variance exclusively shared among the discrimination tasks. The results suggest that positive correlations among musical aptitudes result from both genes with broad effects on cognition, and genes with potentially more specific influences on auditory functions. PMID:25419664
Matsuda, Fumio; Nakabayashi, Ryo; Yang, Zhigang; Okazaki, Yozo; Yonemaru, Jun-ichi; Ebana, Kaworu; Yano, Masahiro; Saito, Kazuki
2015-01-01
Plants produce structurally diverse secondary (specialized) metabolites to increase their fitness for survival under adverse environments. Several bioactive compounds for new drugs have been identified through screening of plant extracts. In this study, genome-wide association studies (GWAS) were conducted to investigate the genetic architecture behind the natural variation of rice secondary metabolites. GWAS using the metabolome data of 175 rice accessions successfully identified 323 associations among 143 single nucleotide polymorphisms (SNPs) and 89 metabolites. The data analysis highlighted that levels of many metabolites are tightly associated with a small number of strong quantitative trait loci (QTLs). The tight association may be a mechanism generating strains with distinct metabolic composition through the crossing of two different strains. The results indicate that one plant species produces more diverse phytochemicals than previously expected, and plants still contain many useful compounds for human applications. PMID:25267402
Genetic Architecture of Micro-Environmental Plasticity in Drosophila melanogaster.
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.
Adaptations to local environments in modern human populations.
Jeong, Choongwon; Di Rienzo, Anna
2014-12-01
After leaving sub-Saharan Africa around 50000-100000 years ago, anatomically modern humans have quickly occupied extremely diverse environments. Human populations were exposed to further environmental changes resulting from cultural innovations, such as the spread of farming, which gave rise to new selective pressures related to pathogen exposures and dietary shifts. In addition to changing the frequency of individual adaptive alleles, natural selection may also shape the overall genetic architecture of adaptive traits. Here, we review recent advances in understanding the genetic architecture of adaptive human phenotypes based on insights from the studies of lactase persistence, skin pigmentation and high-altitude adaptation. These adaptations evolved in parallel in multiple human populations, providing a chance to investigate independent realizations of the evolutionary process. We suggest that the outcome of adaptive evolution is often highly variable even under similar selective pressures. Finally, we highlight a growing need for detecting adaptations that did not follow the classical sweep model and for incorporating new sources of genetic evidence such as information from ancient DNA. Copyright © 2014 Elsevier Ltd. All rights reserved.
Wang, Diane R; Han, Rongkui; Wolfrum, Edward J; McCouch, Susan R
2017-07-01
Harnessing stem carbohydrate dynamics in grasses offers an opportunity to help meet future demands for plant-based food, fiber and fuel production, but requires a greater understanding of the genetic controls that govern the synthesis, interconversion and transport of such energy reserves. We map out a blueprint of the genetic architecture of rice (Oryza sativa) stem nonstructural carbohydrates (NSC) at two critical developmental time-points using a subpopulation-specific genome-wide association approach on two diverse germplasm panels followed by quantitative trait loci (QTL) mapping in a biparental population. Overall, 26 QTL are identified; three are detected in multiple panels and are associated with starch-at-maturity, sucrose-at-maturity and NSC-at-heading. They tag OsHXK6 (rice hexokinase), ISA2 (rice isoamylase) and a tandem array of sugar transporters. This study provides the foundation for more in-depth molecular investigation to validate candidate genes underlying rice stem NSC and informs future comparative studies in other agronomically vital grass species. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Diane R.; Han, Rongkui; Wolfrum, Edward J.
Harnessing stem carbohydrate dynamics in grasses offers an opportunity to help meet future demands for plant-based food, fiber and fuel production, but requires a greater understanding of the genetic controls that govern the synthesis, interconversion and transport of such energy reserves. We map out a blueprint of the genetic architecture of rice ( Oryza sativa) stem nonstructural carbohydrates (NSC) at two critical developmental time-points using a subpopulation-specific genome-wide association approach on two diverse germplasm panels followed by quantitative trait loci (QTL) mapping in a biparental population. Overall, 26 QTL are identified; three are detected in multiple panels and are associatedmore » with starch-at-maturity, sucrose-at-maturity and NSC-at-heading. They tag OsHXK6 (rice hexokinase), ISA2 (rice isoamylase) and a tandem array of sugar transporters. Furthermore, this study provides the foundation for more in-depth molecular investigation to validate candidate genes underlying rice stem NSC and informs future comparative studies in other agronomically vital grass species.« less
The evolution of phenotypic integration: How directional selection reshapes covariation in mice
Penna, Anna; Melo, Diogo; Bernardi, Sandra; Oyarzabal, Maria Inés; Marroig, Gabriel
2017-01-01
Abstract Variation is the basis for evolution, and understanding how variation can evolve is a central question in biology. In complex phenotypes, covariation plays an even more important role, as genetic associations between traits can bias and alter evolutionary change. Covariation can be shaped by complex interactions between loci, and this genetic architecture can also change during evolution. In this article, we analyzed mouse lines experimentally selected for changes in size to address the question of how multivariate covariation changes under directional selection, as well as to identify the consequences of these changes to evolution. Selected lines showed a clear restructuring of covariation in their cranium and, instead of depleting their size variation, these lines increased their magnitude of integration and the proportion of variation associated with the direction of selection. This result is compatible with recent theoretical works on the evolution of covariation that take the complexities of genetic architecture into account. This result also contradicts the traditional view of the effects of selection on available covariation and suggests a much more complex view of how populations respond to selection. PMID:28685813
Wang, Diane R.; Han, Rongkui; Wolfrum, Edward J.; ...
2017-05-30
Harnessing stem carbohydrate dynamics in grasses offers an opportunity to help meet future demands for plant-based food, fiber and fuel production, but requires a greater understanding of the genetic controls that govern the synthesis, interconversion and transport of such energy reserves. We map out a blueprint of the genetic architecture of rice ( Oryza sativa) stem nonstructural carbohydrates (NSC) at two critical developmental time-points using a subpopulation-specific genome-wide association approach on two diverse germplasm panels followed by quantitative trait loci (QTL) mapping in a biparental population. Overall, 26 QTL are identified; three are detected in multiple panels and are associatedmore » with starch-at-maturity, sucrose-at-maturity and NSC-at-heading. They tag OsHXK6 (rice hexokinase), ISA2 (rice isoamylase) and a tandem array of sugar transporters. Furthermore, this study provides the foundation for more in-depth molecular investigation to validate candidate genes underlying rice stem NSC and informs future comparative studies in other agronomically vital grass species.« less
Quantitative genetics of immunity and life history under different photoperiods.
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.
Lindy B. Mullen; H. Arthur Woods; Michael K. Schwartz; Adam J. Sepulveda; Winsor H. Lowe
2010-01-01
The network architecture of streams and rivers constrains evolutionary, demographic and ecological processes of freshwater organisms. This consistent architecture also makes stream networks useful for testing general models of population genetic structure and the scaling of gene flow. We examined genetic structure and gene flow in the facultatively paedomorphic Idaho...
The genetic architecture of maize height.
Peiffer, Jason A; Romay, Maria C; Gore, Michael A; Flint-Garcia, Sherry A; Zhang, Zhiwu; Millard, Mark J; Gardner, Candice A C; McMullen, Michael D; Holland, James B; Bradbury, Peter J; Buckler, Edward S
2014-04-01
Height is one of the most heritable and easily measured traits in maize (Zea mays L.). Given a pedigree or estimates of the genomic identity-by-state among related plants, height is also accurately predictable. But, mapping alleles explaining natural variation in maize height remains a formidable challenge. To address this challenge, we measured the plant height, ear height, flowering time, and node counts of plants grown in >64,500 plots across 13 environments. These plots contained >7300 inbreds representing most publically available maize inbreds in the United States and families of the maize Nested Association Mapping (NAM) panel. Joint-linkage mapping of quantitative trait loci (QTL), fine mapping in near isogenic lines (NILs), genome-wide association studies (GWAS), and genomic best linear unbiased prediction (GBLUP) were performed. The heritability of maize height was estimated to be >90%. Mapping NAM family-nested QTL revealed the largest explained 2.1 ± 0.9% of height variation. The effects of two tropical alleles at this QTL were independently validated by fine mapping in NIL families. Several significant associations found by GWAS colocalized with established height loci, including brassinosteroid-deficient dwarf1, dwarf plant1, and semi-dwarf2. GBLUP explained >80% of height variation in the panels and outperformed bootstrap aggregation of family-nested QTL models in evaluations of prediction accuracy. These results revealed maize height was under strong genetic control and had a highly polygenic genetic architecture. They also showed that multiple models of genetic architecture differing in polygenicity and effect sizes can plausibly explain a population's variation in maize height, but they may vary in predictive efficacy.
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
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.
Molecular basis of angiosperm tree architecture.
Hollender, Courtney A; Dardick, Chris
2015-04-01
The architecture of trees greatly impacts the productivity of orchards and forestry plantations. Amassing greater knowledge on the molecular genetics that underlie tree form can benefit these industries, as well as contribute to basic knowledge of plant developmental biology. This review describes the fundamental components of branch architecture, a prominent aspect of tree structure, as well as genetic and hormonal influences inferred from studies in model plant systems and from trees with non-standard architectures. The bulk of the molecular and genetic data described here is from studies of fruit trees and poplar, as these species have been the primary subjects of investigation in this field of science. No claim to original US Government works. New Phytologist © 2014 New Phytologist Trust.
Implications of sex-specific selection for the genetic basis of disease.
Morrow, Edward H; Connallon, Tim
2013-12-01
Mutation and selection are thought to shape the underlying genetic basis of many common human diseases. However, both processes depend on the context in which they occur, such as environment, genetic background, or sex. Sex has widely known effects on phenotypic expression of genotype, but an analysis of how it influences the evolutionary dynamics of disease-causing variants has not yet been explored. We develop a simple population genetic model of disease susceptibility and evaluate it using a biologically plausible empirically based distribution of fitness effects among contributing mutations. The model predicts that alleles under sex-differential selection, including sexually antagonistic alleles, will disproportionately contribute to genetic variation for disease predisposition, thereby generating substantial sexual dimorphism in the genetic architecture of complex (polygenic) diseases. This is because such alleles evolve into higher population frequencies for a given effect size, relative to alleles experiencing equally strong purifying selection in both sexes. Our results provide a theoretical justification for expecting a sexually dimorphic genetic basis for variation in complex traits such as disease. Moreover, they suggest that such dimorphism is interesting - not merely something to control for - because it reflects the action of natural selection in molding the evolution of common disease phenotypes.
Yuan, Wei; Flowers, Jonathan M.; Sahraie, Dustin J.; Purugganan, Michael D.
2016-01-01
The expansion of species ranges frequently necessitates responses to novel environments. In plants, the ability of seeds to disperse to marginal areas relies in part to its ability to germinate under stressful conditions. Here we examine the genetic architecture of Arabidopsis thaliana germination speed under a novel, saline environment, using an Extreme QTL (X-QTL) mapping platform we previously developed. We find that early germination in normal and salt conditions both rely on a QTL on the distal arm of chromosome 4, but we also find unique QTL on chromosomes 1, 2, 4, and 5 that are specific to salt stress environments. Moreover, different QTLs are responsible for early vs. late germination, suggesting a temporal component to the expression of life history under these stress conditions. Our results indicate that cryptic genetic variation exists for responses to a novel abiotic stress, which may suggest a role of such variation in adaptation to new climactic conditions or growth environments. PMID:27543295
Bundus, Joanna D; Wang, Donglin; Cutter, Asher D
2018-04-07
Hybrid male sterility often evolves before female sterility or inviability of hybrids, implying that the accumulation of divergence between separated lineages should lead hybrid male sterility to have a more polygenic basis. However, experimental evidence is mixed. Here, we use the nematodes Caenorhabditis remanei and C. latens to characterize the underlying genetic basis of asymmetric hybrid male sterility and hybrid inviability. We demonstrate that hybrid male sterility is consistent with a simple genetic basis, involving a single X-autosome incompatibility. We also show that hybrid inviability involves more genomic compartments, involving diverse nuclear-nuclear incompatibilities, a mito-nuclear incompatibility, and maternal effects. These findings demonstrate that male sensitivity to genetic perturbation may be genetically simple compared to hybrid inviability in Caenorhabditis and motivates tests of generality for the genetic architecture of hybrid incompatibility across the breadth of phylogeny.
Architecture of the wood-wide web: Rhizopogon spp. genets link multiple Douglas-fir cohorts.
Beiler, Kevin J; Durall, Daniel M; Simard, Suzanne W; Maxwell, Sheri A; Kretzer, Annette M
2010-01-01
*The role of mycorrhizal networks in forest dynamics is poorly understood because of the elusiveness of their spatial structure. We mapped the belowground distribution of the fungi Rhizopogon vesiculosus and Rhizopogon vinicolor and interior Douglas-fir trees (Pseudotsuga menziesii var. glauca) to determine the architecture of a mycorrhizal network in a multi-aged old-growth forest. *Rhizopogon spp. mycorrhizas were collected within a 30 x 30 m plot. Trees and fungal genets were identified using multi-locus microsatellite DNA analysis. Tree genotypes from mycorrhizas were matched to reference trees aboveground. Two trees were considered linked if they shared the same fungal genet(s). *The two Rhizopogon species each formed 13-14 genets, each colonizing up to 19 trees in the plot. Rhizopogon vesiculosus genets were larger, occurred at greater depths, and linked more trees than genets of R. vinicolor. Multiple tree cohorts were linked, with young saplings established within the mycorrhizal network of Douglas-fir veterans. A strong positive relationship was found between tree size and connectivity, resulting in a scale-free network architecture with small-world properties. *This mycorrhizal network architecture suggests an efficient and robust network, where large trees play a foundational role in facilitating conspecific regeneration and stabilizing the ecosystem.
3D sorghum reconstructions from depth images identify QTL regulating shoot architecture
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mccormick, Ryan F.; Truong, Sandra K.; Mullet, John E.
Dissecting the genetic basis of complex traits is aided by frequent and nondestructive measurements. Advances in range imaging technologies enable the rapid acquisition of three-dimensional (3D) data from an imaged scene. A depth camera was used to acquire images of sorghum (Sorghum bicolor), an important grain, forage, and bioenergy crop, at multiple developmental time points from a greenhouse-grown recombinant inbred line population. A semiautomated software pipeline was developed and used to generate segmented, 3D plant reconstructions from the images. Automated measurements made from 3D plant reconstructions identified quantitative trait loci for standard measures of shoot architecture, such as shoot height,more » leaf angle, and leaf length, and for novel composite traits, such as shoot compactness. The phenotypic variability associated with some of the quantitative trait loci displayed differences in temporal prevalence; for example, alleles closely linked with the sorghum Dwarf3 gene, an auxin transporter and pleiotropic regulator of both leaf inclination angle and shoot height, influence leaf angle prior to an effect on shoot height. Furthermore, variability in composite phenotypes that measure overall shoot architecture, such as shoot compactness, is regulated by loci underlying component phenotypes like leaf angle. As such, depth imaging is an economical and rapid method to acquire shoot architecture phenotypes in agriculturally important plants like sorghum to study the genetic basis of complex traits.« less
3D sorghum reconstructions from depth images identify QTL regulating shoot architecture
Mccormick, Ryan F.; Truong, Sandra K.; Mullet, John E.
2016-08-15
Dissecting the genetic basis of complex traits is aided by frequent and nondestructive measurements. Advances in range imaging technologies enable the rapid acquisition of three-dimensional (3D) data from an imaged scene. A depth camera was used to acquire images of sorghum (Sorghum bicolor), an important grain, forage, and bioenergy crop, at multiple developmental time points from a greenhouse-grown recombinant inbred line population. A semiautomated software pipeline was developed and used to generate segmented, 3D plant reconstructions from the images. Automated measurements made from 3D plant reconstructions identified quantitative trait loci for standard measures of shoot architecture, such as shoot height,more » leaf angle, and leaf length, and for novel composite traits, such as shoot compactness. The phenotypic variability associated with some of the quantitative trait loci displayed differences in temporal prevalence; for example, alleles closely linked with the sorghum Dwarf3 gene, an auxin transporter and pleiotropic regulator of both leaf inclination angle and shoot height, influence leaf angle prior to an effect on shoot height. Furthermore, variability in composite phenotypes that measure overall shoot architecture, such as shoot compactness, is regulated by loci underlying component phenotypes like leaf angle. As such, depth imaging is an economical and rapid method to acquire shoot architecture phenotypes in agriculturally important plants like sorghum to study the genetic basis of complex traits.« less
Sikkink, Kristin L; Reynolds, Rose M; Cresko, William A; Phillips, Patrick C
2015-05-01
Selection in novel environments can lead to a coordinated evolutionary response across a suite of characters. Environmental conditions can also potentially induce changes in the genetic architecture of complex traits, which in turn could alter the pattern of the multivariate response to selection. We describe a factorial selection experiment using the nematode Caenorhabditis remanei in which two different stress-related phenotypes (heat and oxidative stress resistance) were selected under three different environmental conditions. The pattern of covariation in the evolutionary response between phenotypes or across environments differed depending on the environment in which selection occurred, including asymmetrical responses to selection in some cases. These results indicate that variation in pleiotropy across the stress response network is highly sensitive to the external environment. Our findings highlight the complexity of the interaction between genes and environment that influences the ability of organisms to acclimate to novel environments. They also make clear the need to identify the underlying genetic basis of genetic correlations in order understand how patterns of pleiotropy are distributed across complex genetic networks. © 2015 The Author(s).
Sikkink, Kristin L.; Reynolds, Rose M.; Cresko, William A.; Phillips, Patrick C.
2017-01-01
Selection in novel environments can lead to a coordinated evolutionary response across a suite of characters. Environmental conditions can also potentially induce changes in the genetic architecture of complex traits, which in turn could alter the pattern of the multivariate response to selection. We describe a factorial selection experiment using the nematode Caenorhabditis remanei in which two different stress-related phenotypes (heat and oxidative stress resistance) were selected under three different environmental conditions. The pattern of covariation in the evolutionary response between phenotypes or across environments differed depending on the environment in which selection occurred, including asymmetrical responses to selection in some cases. These results indicate that variation in pleiotropy across the stress response network is highly sensitive to the external environment. Our findings highlight the complexity of the interaction between genes and environment that influences the ability of organisms to acclimate to novel environments. They also make clear the need to identify the underlying genetic basis of genetic correlations in order understand how patterns of pleiotropy are distributed across complex genetic networks. PMID:25809411
Feldman, Max J.; Paul, Rachel E.; Banan, Darshi; ...
2017-06-23
Vertical growth of plants is a dynamic process that is influenced by genetic and environmental factors and has a pronounced effect on overall plant architecture and biomass composition. For this research, we have performed six controlled growth trials of an interspecific Setaria italica x Setaria viridis recombinant inbred line population to assess how the genetic architecture of plant height is influenced by developmental queues, water availability and planting density. The non-destructive nature of plant height measurements has enabled us to monitor height throughout the plant life cycle in both field and controlled environments. We find that plant height is reducedmore » under water limitation and high density planting and affected by growth environment (field vs. growth chamber). The results support a model where plant height is a heritable, polygenic trait and that the major genetic loci that influence plant height function independent of growth environment. The identity and contribution of loci that influence height changes dynamically throughout development and the reduction of growth observed in water limited environments is a consequence of delayed progression through the genetic program which establishes plant height in Setaria. In this population, alleles inherited from the weedy S. viridis parent act to increase plant height early, whereas a larger number of small effect alleles inherited from the domesticated S. italica parent collectively act to increase plant height later in development.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Feldman, Max J.; Paul, Rachel E.; Banan, Darshi
Vertical growth of plants is a dynamic process that is influenced by genetic and environmental factors and has a pronounced effect on overall plant architecture and biomass composition. For this research, we have performed six controlled growth trials of an interspecific Setaria italica x Setaria viridis recombinant inbred line population to assess how the genetic architecture of plant height is influenced by developmental queues, water availability and planting density. The non-destructive nature of plant height measurements has enabled us to monitor height throughout the plant life cycle in both field and controlled environments. We find that plant height is reducedmore » under water limitation and high density planting and affected by growth environment (field vs. growth chamber). The results support a model where plant height is a heritable, polygenic trait and that the major genetic loci that influence plant height function independent of growth environment. The identity and contribution of loci that influence height changes dynamically throughout development and the reduction of growth observed in water limited environments is a consequence of delayed progression through the genetic program which establishes plant height in Setaria. In this population, alleles inherited from the weedy S. viridis parent act to increase plant height early, whereas a larger number of small effect alleles inherited from the domesticated S. italica parent collectively act to increase plant height later in development.« less
Paul, Rachel E.; Sebastian, Jose; Yee, Muh-Ching; Jiang, Hui; Lipka, Alexander E.; Brutnell, Thomas P.; Dinneny, José R.; Leakey, Andrew D. B.
2017-01-01
Vertical growth of plants is a dynamic process that is influenced by genetic and environmental factors and has a pronounced effect on overall plant architecture and biomass composition. We have performed six controlled growth trials of an interspecific Setaria italica x Setaria viridis recombinant inbred line population to assess how the genetic architecture of plant height is influenced by developmental queues, water availability and planting density. The non-destructive nature of plant height measurements has enabled us to monitor height throughout the plant life cycle in both field and controlled environments. We find that plant height is reduced under water limitation and high density planting and affected by growth environment (field vs. growth chamber). The results support a model where plant height is a heritable, polygenic trait and that the major genetic loci that influence plant height function independent of growth environment. The identity and contribution of loci that influence height changes dynamically throughout development and the reduction of growth observed in water limited environments is a consequence of delayed progression through the genetic program which establishes plant height in Setaria. In this population, alleles inherited from the weedy S. viridis parent act to increase plant height early, whereas a larger number of small effect alleles inherited from the domesticated S. italica parent collectively act to increase plant height later in development. PMID:28644860
Feldman, Max J; Paul, Rachel E; Banan, Darshi; Barrett, Jennifer F; Sebastian, Jose; Yee, Muh-Ching; Jiang, Hui; Lipka, Alexander E; Brutnell, Thomas P; Dinneny, José R; Leakey, Andrew D B; Baxter, Ivan
2017-06-01
Vertical growth of plants is a dynamic process that is influenced by genetic and environmental factors and has a pronounced effect on overall plant architecture and biomass composition. We have performed six controlled growth trials of an interspecific Setaria italica x Setaria viridis recombinant inbred line population to assess how the genetic architecture of plant height is influenced by developmental queues, water availability and planting density. The non-destructive nature of plant height measurements has enabled us to monitor height throughout the plant life cycle in both field and controlled environments. We find that plant height is reduced under water limitation and high density planting and affected by growth environment (field vs. growth chamber). The results support a model where plant height is a heritable, polygenic trait and that the major genetic loci that influence plant height function independent of growth environment. The identity and contribution of loci that influence height changes dynamically throughout development and the reduction of growth observed in water limited environments is a consequence of delayed progression through the genetic program which establishes plant height in Setaria. In this population, alleles inherited from the weedy S. viridis parent act to increase plant height early, whereas a larger number of small effect alleles inherited from the domesticated S. italica parent collectively act to increase plant height later in development.
The mathematical limits of genetic prediction for complex chronic disease.
Keyes, Katherine M; Smith, George Davey; Koenen, Karestan C; Galea, Sandro
2015-06-01
Attempts at predicting individual risk of disease based on common germline genetic variation have largely been disappointing. The present paper formalises why genetic prediction at the individual level is and will continue to have limited utility given the aetiological architecture of most common complex diseases. Data were simulated on one million populations with 10 000 individuals in each populations with varying prevalences of a genetic risk factor, an interacting environmental factor and the background rate of disease. The determinant risk ratio and risk difference magnitude for the association between a gene variant and disease is a function of the prevalence of the interacting factors that activate the gene, and the background rate of disease. The risk ratio and total excess cases due to the genetic factor increase as the prevalence of interacting factors increase, and decrease as the background rate of disease increases. Germline genetic variations have high predictive capacity for individual disease only under conditions of high heritability of particular genetic sequences, plausible only under rare variant hypotheses. Under a model of common germline genetic variants that interact with other genes and/or environmental factors in order to cause disease, the predictive capacity of common genetic variants is determined by the prevalence of the factors that interact with the variant and the background rate. A focus on estimating genetic associations for the purpose of prediction without explicitly grounding such work in an understanding of modifiable (including environmentally influenced) factors will be limited in its ability to yield important insights about the risk of disease. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Fildes, Alison; van Jaarsveld, Cornelia H M; Cooke, Lucy; Wardle, Jane; Llewellyn, Clare H
2016-04-01
Food fussiness (FF) is common in early childhood and is often associated with the rejection of nutrient-dense foods such as vegetables and fruit. FF and liking for vegetables and fruit are likely all heritable phenotypes; the genetic influence underlying FF may explain the observed genetic influence on liking for vegetables and fruit. Twin analyses make it possible to get a broad-based estimate of the extent of the shared genetic influence that underlies these traits. We quantified the extent of the shared genetic influence that underlies FF and liking for vegetables and fruit in early childhood with the use of a twin design. Data were from the Gemini cohort, which is a population-based sample of twins born in England and Wales in 2007. Parents of 3-y-old twins (n= 1330 pairs) completed questionnaire measures of their children's food preferences (liking for vegetables and fruit) and the FF scale from the Children's Eating Behavior Questionnaire. Multivariate quantitative genetic modeling was used to estimate common genetic influences that underlie FF and liking for vegetables and fruit. Genetic correlations were significant and moderate to large in size between FF and liking for both vegetables (-0.65) and fruit (-0.43), which indicated that a substantial proportion of the genes that influence FF also influence liking. Common genes that underlie FF and liking for vegetables and fruit largely explained the observed phenotypic correlations between them (68-70%). FF and liking for fruit and vegetables in young children share a large proportion of common genetic factors. The genetic influence on FF may determine why fussy children typically reject fruit and vegetables.
Non-Linear Pattern Formation in Bone Growth and Architecture
Salmon, Phil
2014-01-01
The three-dimensional morphology of bone arises through adaptation to its required engineering performance. Genetically and adaptively bone travels along a complex spatiotemporal trajectory to acquire optimal architecture. On a cellular, micro-anatomical scale, what mechanisms coordinate the activity of osteoblasts and osteoclasts to produce complex and efficient bone architectures? One mechanism is examined here – chaotic non-linear pattern formation (NPF) – which underlies in a unifying way natural structures as disparate as trabecular bone, swarms of birds flying, island formation, fluid turbulence, and others. At the heart of NPF is the fact that simple rules operating between interacting elements, and Turing-like interaction between global and local signals, lead to complex and structured patterns. The study of “group intelligence” exhibited by swarming birds or shoaling fish has led to an embodiment of NPF called “particle swarm optimization” (PSO). This theoretical model could be applicable to the behavior of osteoblasts, osteoclasts, and osteocytes, seeing them operating “socially” in response simultaneously to both global and local signals (endocrine, cytokine, mechanical), resulting in their clustered activity at formation and resorption sites. This represents problem-solving by social intelligence, and could potentially add further realism to in silico computer simulation of bone modeling. What insights has NPF provided to bone biology? One example concerns the genetic disorder juvenile Pagets disease or idiopathic hyperphosphatasia, where the anomalous parallel trabecular architecture characteristic of this pathology is consistent with an NPF paradigm by analogy with known experimental NPF systems. Here, coupling or “feedback” between osteoblasts and osteoclasts is the critical element. This NPF paradigm implies a profound link between bone regulation and its architecture: in bone the architecture is the regulation. The former is the emergent consequence of the latter. PMID:25653638
Non-linear pattern formation in bone growth and architecture.
Salmon, Phil
2014-01-01
The three-dimensional morphology of bone arises through adaptation to its required engineering performance. Genetically and adaptively bone travels along a complex spatiotemporal trajectory to acquire optimal architecture. On a cellular, micro-anatomical scale, what mechanisms coordinate the activity of osteoblasts and osteoclasts to produce complex and efficient bone architectures? One mechanism is examined here - chaotic non-linear pattern formation (NPF) - which underlies in a unifying way natural structures as disparate as trabecular bone, swarms of birds flying, island formation, fluid turbulence, and others. At the heart of NPF is the fact that simple rules operating between interacting elements, and Turing-like interaction between global and local signals, lead to complex and structured patterns. The study of "group intelligence" exhibited by swarming birds or shoaling fish has led to an embodiment of NPF called "particle swarm optimization" (PSO). This theoretical model could be applicable to the behavior of osteoblasts, osteoclasts, and osteocytes, seeing them operating "socially" in response simultaneously to both global and local signals (endocrine, cytokine, mechanical), resulting in their clustered activity at formation and resorption sites. This represents problem-solving by social intelligence, and could potentially add further realism to in silico computer simulation of bone modeling. What insights has NPF provided to bone biology? One example concerns the genetic disorder juvenile Pagets disease or idiopathic hyperphosphatasia, where the anomalous parallel trabecular architecture characteristic of this pathology is consistent with an NPF paradigm by analogy with known experimental NPF systems. Here, coupling or "feedback" between osteoblasts and osteoclasts is the critical element. This NPF paradigm implies a profound link between bone regulation and its architecture: in bone the architecture is the regulation. The former is the emergent consequence of the latter.
Kohl, Kathryn P; Singh, Nadia D
2018-04-01
Phenotypic plasticity is pervasive in nature. One mechanism underlying the evolution and maintenance of such plasticity is environmental heterogeneity. Indeed, theory indicates that both spatial and temporal variation in the environment should favor the evolution of phenotypic plasticity under a variety of conditions. Cyclical environmental conditions have also been shown to yield evolved increases in recombination frequency. Here, we use a panel of replicated experimental evolution populations of D. melanogaster to test whether variable environments favor enhanced plasticity in recombination rate and/or increased recombination rate in response to temperature. In contrast to expectation, we find no evidence for either enhanced plasticity in recombination or increased rates of recombination in the variable environment lines. Our data confirm a role of temperature in mediating recombination fraction in D. melanogaster, and indicate that recombination is genetically and plastically depressed under lower temperatures. Our data further suggest that the genetic architectures underlying plastic recombination and population-level variation in recombination rate are likely to be distinct. © 2018 The Author(s). Evolution © 2018 The Society for the Study of Evolution.
Ku, Lixia; Zhang, Liangkun; Tian, Zhiqiang; Guo, Shulei; Su, Huihui; Ren, Zhenzhen; Wang, Zhiyong; Li, Guohui; Wang, Xiaobo; Zhu, Yuguang; Zhou, Jinlong; Chen, Yanhui
2015-08-01
Plant height is one of the most heritable traits in maize (Zea mays L.). Understanding the genetic control of plant height is important for elucidating the molecular mechanisms that regulate maize development. To investigate the genetic basis of the plant height response to density in maize, we evaluated the effects of two different plant densities (60,000 and 120,000 plant/hm(2)) on three plant height-related traits (plant height, ear height, and ear height-to-plant height ratio) using four sets of recombinant inbred line populations. The phenotypes observed under the two-plant density treatments indicated that high plant density increased the phenotypic performance values of the three measured traits. Twenty-three quantitative trait loci (QTLs) were detected under the two-plant density treatments, and five QTL clusters were located. Nine QTLs were detected under the low plant density treatment, and seven QTLs were detected under the high plant density treatment. Our results suggested that plant height may be controlled mainly by a common set of genes that could be influenced by additional genetic mechanisms when the plants were grown under high plant density. Fine mapping for genetic regions of the stable QTLs across different plant density environments may provide additional information about their different responses to density. The results presented here provide useful information for further research and will help to reveal the molecular mechanisms related to plant height in response to density.
The Importance of Juvenile Root Traits for Crop Yields
NASA Astrophysics Data System (ADS)
White, Philip; Adu, Michael; Broadley, Martin; Brown, Lawrie; Dupuy, Lionel; George, Timothy; Graham, Neil; Hammond, John; Hayden, Rory; Neugebauer, Konrad; Nightingale, Mark; Ramsay, Gavin; Thomas, Catherine; Thompson, Jacqueline; Wishart, Jane; Wright, Gladys
2014-05-01
Genetic variation in root system architecture (RSA) is an under-exploited breeding resource. This is partly a consequence of difficulties in the rapid and accurate assessment of subterranean root systems. However, although the characterisation of root systems of large plants in the field are both time-consuming and labour-intensive, high-throughput (HTP) screens of root systems of juvenile plants can be performed in the field, glasshouse or laboratory. It is hypothesised that improving the root systems of juvenile plants can accelerate access to water and essential mineral elements, leading to rapid crop establishment and, consequently, greater yields. This presentation will illustrate how aspects of the juvenile root systems of potato (Solanum tuberosum L.) and oilseed rape (OSR; Brassica napus L.) correlate with crop yields and examine the reasons for such correlations. It will first describe the significant positive relationships between early root system development, phosphorus acquisition, canopy establishment and eventual yield among potato genotypes. It will report the development of a glasshouse assay for root system architecture (RSA) of juvenile potato plants, the correlations between root system architectures measured in the glasshouse and field, and the relationships between aspects of the juvenile root system and crop yields under drought conditions. It will then describe the development of HTP systems for assaying RSA of OSR seedlings, the identification of genetic loci affecting RSA in OSR, the development of mathematical models describing resource acquisition by OSR, and the correlations between root traits recorded in the HTP systems and yields of OSR in the field.
Cassidy-Bushrow, Andrea E.; Bielak, Lawrence F.; Sheedy, Patrick F.; Turner, Stephen T.; Chu, Julia S.; Peyser, Patricia A.
2011-01-01
Background Short stature is associated with increased risk of coronary heart disease (CHD); although the mechanisms for this relationship are unknown, shared genetic factors have been proposed. Subclinical atherosclerosis, measured by coronary artery calcification (CAC), is associated with CHD events and represents part of the biological continuum to overt CHD. Many molecular mechanisms of CAC development are shared with bone growth. Thus, we examined whether there was evidence of shared genes (pleiotropy) between adult stature and CAC. Methods 877 asymptomatic white adults (46% men) from 625 families in a community-based sample had computed tomography measures of CAC. Pleiotropy between height and CAC was determined using maximum-likelihood estimation implemented in SOLAR. Results Adult height was significantly and inversely associated with CAC score (P=0.01). After adjusting for age, sex, and CHD risk factors, the estimated genetic correlation between height and CAC score was -0.37 and was significantly different than 0 (P=0.001) and -1 (P<0.001). The environmental correlation between height and CAC score was 0.60 and was significantly different than 0 (P=0.024). Conclusions Further studies of shared genetic factors between height and CAC may provide important insight into the complex genetic architecture of CHD, in part through increased understanding of the molecular pathways underlying the process of both normal growth and disease development. Bivariate genetic linkage analysis may provide a powerful mechanism for identifying specific genomic regions associated with both height and CAC. PMID:21937044
Cassidy-Bushrow, Andrea E; Bielak, Lawrence F; Sheedy, Patrick F; Turner, Stephen T; Chu, Julia S; Peyser, Patricia A
2011-12-01
Short stature is associated with increased risk of coronary heart disease (CHD); although the mechanisms for this relationship are unknown, shared genetic factors have been proposed. Subclinical atherosclerosis, measured by coronary artery calcification (CAC), is associated with CHD events and represents part of the biological continuum to overt CHD. Many molecular mechanisms of CAC development are shared with bone growth. Thus, we examined whether there was evidence of shared genes (pleiotropy) between adult stature and CAC. 877 Asymptomatic white adults (46% men) from 625 families in a community-based sample had computed tomography measures of CAC. Pleiotropy between height and CAC was determined using maximum-likelihood estimation implemented in SOLAR. Adult height was significantly and inversely associated with CAC score (P = 0.01). After adjusting for age, sex and CHD risk factors, the estimated genetic correlation between height and CAC score was -0.37 and was significantly different than 0 (P = 0.001) and -1 (P < 0.001). The environmental correlation between height and CAC score was 0.60 and was significantly different than 0 (P = 0.024). Further studies of shared genetic factors between height and CAC may provide important insight into the complex genetic architecture of CHD, in part through increased understanding of the molecular pathways underlying the process of both normal growth and disease development. Bivariate genetic linkage analysis may provide a powerful mechanism for identifying specific genomic regions associated with both height and CAC. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
Genetic basis of sexual dimorphism in the threespine stickleback Gasterosteus aculeatus
Leinonen, T; Cano, J M; Merilä, J
2011-01-01
Sexual dimorphism (SD) in morphological, behavioural and physiological features is common, but the genetics of SD in the wild has seldom been studied in detail. We investigated the genetic basis of SD in morphological traits of threespine stickleback (Gasterosteus aculeatus) by conducting a large breeding experiment with fish from an ancestral marine population that acts as a source of morphological variation. We also examined the patterns of SD in a set of 38 wild populations from different habitats to investigate the relationship between the genetic architecture of SD of the marine ancestral population in relation to variation within and among natural populations. The results show that genetic architecture in terms of heritabilities, additive genetic variances and covariances (as well as correlations) is very similar in the two sexes in spite of the fact that many of the traits express significant SD. Furthermore, population differences in threespine stickleback body shape and armour SD appear to have evolved despite constraints imposed by genetic architecture. This implies that constraints for the evolution of SD imposed by strong genetic correlations are not as severe and absolute as commonly thought. PMID:20700139
Genetic architecture and genomic patterns of gene flow between hybridizing species of Picea
De La Torre, A; Ingvarsson, P K; Aitken, S N
2015-01-01
Hybrid zones provide an opportunity to study the effects of selection and gene flow in natural settings. We employed nuclear microsatellites (single sequence repeat (SSR)) and candidate gene single-nucleotide polymorphism markers (SNPs) to characterize the genetic architecture and patterns of interspecific gene flow in the Picea glauca × P. engelmannii hybrid zone across a broad latitudinal (40–60 degrees) and elevational (350–3500 m) range in western North America. Our results revealed a wide and complex hybrid zone with broad ancestry levels and low interspecific heterozygosity, shaped by asymmetric advanced-generation introgression, and low reproductive barriers between parental species. The clinal variation based on geographic variables, lack of concordance in clines among loci and the width of the hybrid zone points towards the maintenance of species integrity through environmental selection. Congruency between geographic and genomic clines suggests that loci with narrow clines are under strong selection, favoring either one parental species (directional selection) or their hybrids (overdominance) as a result of strong associations with climatic variables such as precipitation as snow and mean annual temperature. Cline movement due to past demographic events (evidenced by allelic richness and heterozygosity shifts from the average cline center) may explain the asymmetry in introgression and predominance of P. engelmannii found in this study. These results provide insights into the genetic architecture and fine-scale patterns of admixture, and identify loci that may be involved in reproductive barriers between the species. PMID:25806545
Buescher, Elizabeth M.; Moon, Jihyun; Runkel, Anne; Hake, Sarah; Dilkes, Brian P.
2014-01-01
Leaf architecture determines plant structural integrity, light harvesting, and economic considerations such as plant density. Ligules, junctions at the leaf sheath and blade in grasses, protect stalks from environmental stresses and, in conjunction with auricles, controls leaf angle. Previous studies in mutants have recessive liguleless mutants (lg1 and lg2) and dominant mutations in knotted1-like homeobox genes (Lg3-O, Lg4, and Kn1) involved in ligule development. Recently, a new semidominant liguleless mutant, Liguleless narrow (Lgn-R), has been characterized in maize that affects ligule and auricle development and results in a narrow leaf phenotype. We show that quantitative genetic variation affects penetrance of Lgn-R. To examine the genetic architecture underlying Lgn-R expressivity, crosses between Lgn-R/+ mutants in a B73 background and intermated B73 x Mo17 recombinant inbred lines were evaluated in multiple years and locations. A single main-effect quantitative trait locus (QTL) on chromosome 1 (sympathy for the ligule; sol) was discovered with a Mo17-contributed allele that suppressed Lgn-R mutant phenotypes. This QTL has a genetic-interaction with a locus on chromosome 7 (lucifer; lcf) for which the B73-contributed allele increases the ability of the solMo17 allele to suppress Lgn-R. Neither of the genetic intervals likely to contain sol or lcf overlap with any current liguleless genes nor with previously identified genome-wide association QTL connected to leaf architecture. Analysis of phenotypes across environments further identified a genotype by enviroment interaction determining the strength of the sol x lcf interaction. PMID:25344411
Johnston, Susan E; Bérénos, Camillo; Slate, Jon; Pemberton, Josephine M
2016-05-01
Meiotic recombination breaks down linkage disequilibrium (LD) and forms new haplotypes, meaning that it is an important driver of diversity in eukaryotic genomes. Understanding the causes of variation in recombination rate is important in interpreting and predicting evolutionary phenomena and in understanding the potential of a population to respond to selection. However, despite attention in model systems, there remains little data on how recombination rate varies at the individual level in natural populations. Here we used extensive pedigree and high-density SNP information in a wild population of Soay sheep (Ovis aries) to investigate the genetic architecture of individual autosomal recombination rates. Individual rates were high relative to other mammal systems and were higher in males than in females (autosomal map lengths of 3748 and 2860 cM, respectively). The heritability of autosomal recombination rate was low but significant in both sexes (h(2) = 0.16 and 0.12 in females and males, respectively). In females, 46.7% of the heritable variation was explained by a subtelomeric region on chromosome 6; a genome-wide association study showed the strongest associations at locus RNF212, with further associations observed at a nearby ∼374-kb region of complete LD containing three additional candidate loci, CPLX1, GAK, and PCGF3 A second region on chromosome 7 containing REC8 and RNF212B explained 26.2% of the heritable variation in recombination rate in both sexes. Comparative analyses with 40 other sheep breeds showed that haplotypes associated with recombination rates are both old and globally distributed. Both regions have been implicated in rate variation in mice, cattle, and humans, suggesting a common genetic architecture of recombination rate variation in mammals. Copyright © 2016 by the Genetics Society of America.
Joseph, Bindu; Corwin, Jason A; Züst, Tobias; Li, Baohua; Iravani, Majid; Schaepman-Strub, Gabriela; Turnbull, Lindsay A; Kliebenstein, Daniel J
2013-06-01
To understand how genetic architecture translates between phenotypic levels, we mapped the genetic architecture of growth and defense within the Arabidopsis thaliana Kas × Tsu recombinant inbred line population. We measured plant growth using traditional size measurements and size-corrected growth rates. This population contains genetic variation in both the nuclear and cytoplasmic genomes, allowing us to separate their contributions. The cytoplasmic genome regulated a significant variance in growth but not defense, which was due to cytonuclear epistasis. Furthermore, growth adhered to an infinitesimal model of genetic architecture, while defense metabolism was more of a moderate-effect model. We found a lack of concordance between quantitative trait loci (QTL) regulating defense and those regulating growth. Given the published evidence proving the link between glucosinolates and growth, this is likely a false negative result caused by the limited population size. This size limitation creates an inability to test the entire potential genetic landscape possible between these two parents. We uncovered a significant effect of glucosinolates on growth once we accounted for allelic differences in growth QTLs. Therefore, other growth QTLs can mask the effects of defense upon growth. Investigating direct links across phenotypic hierarchies is fraught with difficulty; we identify issues complicating this analysis.
Joseph, Bindu; Corwin, Jason A.; Züst, Tobias; Li, Baohua; Iravani, Majid; Schaepman-Strub, Gabriela; Turnbull, Lindsay A.; Kliebenstein, Daniel J.
2013-01-01
To understand how genetic architecture translates between phenotypic levels, we mapped the genetic architecture of growth and defense within the Arabidopsis thaliana Kas × Tsu recombinant inbred line population. We measured plant growth using traditional size measurements and size-corrected growth rates. This population contains genetic variation in both the nuclear and cytoplasmic genomes, allowing us to separate their contributions. The cytoplasmic genome regulated a significant variance in growth but not defense, which was due to cytonuclear epistasis. Furthermore, growth adhered to an infinitesimal model of genetic architecture, while defense metabolism was more of a moderate-effect model. We found a lack of concordance between quantitative trait loci (QTL) regulating defense and those regulating growth. Given the published evidence proving the link between glucosinolates and growth, this is likely a false negative result caused by the limited population size. This size limitation creates an inability to test the entire potential genetic landscape possible between these two parents. We uncovered a significant effect of glucosinolates on growth once we accounted for allelic differences in growth QTLs. Therefore, other growth QTLs can mask the effects of defense upon growth. Investigating direct links across phenotypic hierarchies is fraught with difficulty; we identify issues complicating this analysis. PMID:23749847
Mosing, Miriam A; Pedersen, Nancy L; Cesarini, David; Johannesson, Magnus; Magnusson, Patrik K E; Nakamura, Jeanne; Madison, Guy; Ullén, Fredrik
2012-01-01
Flow is a psychological state of high but subjectively effortless attention that typically occurs during active performance of challenging tasks and is accompanied by a sense of automaticity, high control, low self-awareness, and enjoyment. Flow proneness is associated with traits and behaviors related to low neuroticism such as emotional stability, conscientiousness, active coping, self-esteem and life satisfaction. Little is known about the genetic architecture of flow proneness, behavioral inhibition and locus of control--traits also associated with neuroticism--and their interrelation. Here, we hypothesized that individuals low in behavioral inhibition and with an internal locus of control would be more likely to experience flow and explored the genetic and environmental architecture of the relationship between the three variables. Behavioral inhibition and locus of control was measured in a large population sample of 3,375 full twin pairs and 4,527 single twins, about 26% of whom also scored the flow proneness questionnaire. Findings revealed significant but relatively low correlations between the three traits and moderate heritability estimates of .41, .45, and .30 for flow proneness, behavioral inhibition, and locus of control, respectively, with some indication of non-additive genetic influences. For behavioral inhibition we found significant sex differences in heritability, with females showing a higher estimate including significant non-additive genetic influences, while in males the entire heritability was due to additive genetic variance. We also found a mainly genetically mediated relationship between the three traits, suggesting that individuals who are genetically predisposed to experience flow, show less behavioral inhibition (less anxious) and feel that they are in control of their own destiny (internal locus of control). We discuss that some of the genes underlying this relationship may include those influencing the function of dopaminergic neural systems.
Widespread genetic linkage of mating signals and preferences in the Hawaiian cricket Laupala
Wiley, Chris; Ellison, Christopher K.; Shaw, Kerry L.
2012-01-01
The evolution of novel sexual communication systems is integral to the process of speciation, as it discourages gene flow between incipient species. Physical linkage between genes underlying male–female communication (i.e. sexual signals and preferences for them) facilitates both rapid and coordinated divergence of sexual communication systems between populations and reduces recombination in the face of occasional hybridization between diverging populations. Despite these ramifications of the genetic architecture of sexual communication for sexual selection and speciation, few studies have examined this relationship empirically. Previous studies of the closely related Hawaiian crickets Laupala paranigra and Laupala kohalensis have indirectly suggested that many of the genes underlying the difference in pulse rate of male song are physically linked with genes underlying the difference in female preference for pulse rate. Using marker-assisted introgression, we moved ‘slow pulse rate’ alleles from L. paranigra at five known quantitative trait loci (QTL) underlying male pulse rate into the ‘fast pulse rate’ genetic background of L. kohalensis and assessed the effect of these loci on female preference. An astounding four out of five song QTL predicted the preferences of female fourth-generation backcrosses, providing direct evidence for the extensive genetic linkage of song and preference in one of the fastest diversifying genera currently known. PMID:21957135
Genetic Architecture of Micro-Environmental Plasticity in Drosophila melanogaster
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
The evolution of phenotypic integration: How directional selection reshapes covariation in mice.
Penna, Anna; Melo, Diogo; Bernardi, Sandra; Oyarzabal, Maria Inés; Marroig, Gabriel
2017-10-01
Variation is the basis for evolution, and understanding how variation can evolve is a central question in biology. In complex phenotypes, covariation plays an even more important role, as genetic associations between traits can bias and alter evolutionary change. Covariation can be shaped by complex interactions between loci, and this genetic architecture can also change during evolution. In this article, we analyzed mouse lines experimentally selected for changes in size to address the question of how multivariate covariation changes under directional selection, as well as to identify the consequences of these changes to evolution. Selected lines showed a clear restructuring of covariation in their cranium and, instead of depleting their size variation, these lines increased their magnitude of integration and the proportion of variation associated with the direction of selection. This result is compatible with recent theoretical works on the evolution of covariation that take the complexities of genetic architecture into account. This result also contradicts the traditional view of the effects of selection on available covariation and suggests a much more complex view of how populations respond to selection. © 2017 The Author(s). Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.
Sack, Laura Magill; Davoli, Teresa; Li, Mamie Z; Li, Yuyang; Xu, Qikai; Naxerova, Kamila; Wooten, Eric C; Bernardi, Ronald J; Martin, Timothy D; Chen, Ting; Leng, Yumei; Liang, Anthony C; Scorsone, Kathleen A; Westbrook, Thomas F; Wong, Kwok-Kin; Elledge, Stephen J
2018-04-05
Genomics has provided a detailed structural description of the cancer genome. Identifying oncogenic drivers that work primarily through dosage changes is a current challenge. Unrestrained proliferation is a critical hallmark of cancer. We constructed modular, barcoded libraries of human open reading frames (ORFs) and performed screens for proliferation regulators in multiple cell types. Approximately 10% of genes regulate proliferation, with most performing in an unexpectedly highly tissue-specific manner. Proliferation drivers in a given cell type showed specific enrichment in somatic copy number changes (SCNAs) from cognate tumors and helped predict aneuploidy patterns in those tumors, implying that tissue-type-specific genetic network architectures underlie SCNA and driver selection in different cancers. In vivo screening confirmed these results. We report a substantial contribution to the catalog of SCNA-associated cancer drivers, identifying 147 amplified and 107 deleted genes as potential drivers, and derive insights about the genetic network architecture of aneuploidy in tumors. Copyright © 2018 Elsevier Inc. All rights reserved.
Mirror representations innate versus determined by experience: a viewpoint from learning theory.
Giese, Martin A
2014-04-01
From the viewpoint of pattern recognition and computational learning, mirror neurons form an interesting multimodal representation that links action perception and planning. While it seems unlikely that all details of such representations are specified by the genetic code, robust learning of such complex representations likely requires an appropriate interplay between plasticity, generalization, and anatomical constraints of the underlying neural architecture.
Prediction of gene expression with cis-SNPs using mixed models and regularization methods.
Zeng, Ping; Zhou, Xiang; Huang, Shuiping
2017-05-11
It has been shown that gene expression in human tissues is heritable, thus predicting gene expression using only SNPs becomes possible. The prediction of gene expression can offer important implications on the genetic architecture of individual functional associated SNPs and further interpretations of the molecular basis underlying human diseases. We compared three types of methods for predicting gene expression using only cis-SNPs, including the polygenic model, i.e. linear mixed model (LMM), two sparse models, i.e. Lasso and elastic net (ENET), and the hybrid of LMM and sparse model, i.e. Bayesian sparse linear mixed model (BSLMM). The three kinds of prediction methods have very different assumptions of underlying genetic architectures. These methods were evaluated using simulations under various scenarios, and were applied to the Geuvadis gene expression data. The simulations showed that these four prediction methods (i.e. Lasso, ENET, LMM and BSLMM) behaved best when their respective modeling assumptions were satisfied, but BSLMM had a robust performance across a range of scenarios. According to R 2 of these models in the Geuvadis data, the four methods performed quite similarly. We did not observe any clustering or enrichment of predictive genes (defined as genes with R 2 ≥ 0.05) across the chromosomes, and also did not see there was any clear relationship between the proportion of the predictive genes and the proportion of genes in each chromosome. However, an interesting finding in the Geuvadis data was that highly predictive genes (e.g. R 2 ≥ 0.30) may have sparse genetic architectures since Lasso, ENET and BSLMM outperformed LMM for these genes; and this observation was validated in another gene expression data. We further showed that the predictive genes were enriched in approximately independent LD blocks. Gene expression can be predicted with only cis-SNPs using well-developed prediction models and these predictive genes were enriched in some approximately independent LD blocks. The prediction of gene expression can shed some light on the functional interpretation for identified SNPs in GWASs.
He, Jin; Jin, Yi; Du, Yan-Lei; Wang, Tao; Turner, Neil C; Yang, Ru-Ping; Siddique, Kadambot H M; Li, Feng-Min
2017-01-01
Water shortage and low phosphorus (P) availability limit yields in soybean. Roots play important roles in water-limited and P-deficient environment, but the underlying mechanisms are largely unknown. In this study we determined the responses of four soybean [ Glycine max (L.) Merr.] genotypes [Huandsedadou (HD), Bailudou (BLD), Jindou 21 (J21), and Zhonghuang 30 (ZH)] to three P levels [applied 0 (P0), 60 (P60), and 120 (P120) mg P kg -1 dry soil to the upper 0.4 m of the soil profile] and two water treatment [well-watered (WW) and water-stressed (WS)] with special reference to root morphology and architecture, we compared yield and its components, root morphology and root architecture to find out which variety and/or what kind of root architecture had high grain yield under P and drought stress. The results showed that water stress and low P, respectively, significantly reduced grain yield by 60 and 40%, daily water use by 66 and 31%, P accumulation by 40 and 80%, and N accumulation by 39 and 65%. The cultivar ZH with the lowest daily water use had the highest grain yield at P60 and P120 under drought. Increased root length was positively associated with N and P accumulation in both the WW and WS treatments, but not with grain yield under water and P deficits. However, in the WS treatment, high adventitious and lateral root densities were associated with high N and P uptake per unit root length which in turn was significantly and positively associated with grain yield. Our results suggest that (1) genetic variation of grain yield, daily water use, P and N accumulation, and root morphology and architecture were observed among the soybean cultivars and ZH had the best yield performance under P and water limited conditions; (2) water has a major influence on nutrient uptake and grain yield, while additional P supply can modestly increase yields under drought in some soybean genotypes; (3) while conserved water use plays an important role in grain yield under drought, root traits also contribute to high nutrient uptake efficiency and benefit yield under drought.
Migault, Vincent; Pallas, Benoît; Costes, Evelyne
2016-01-01
In crops, optimizing target traits in breeding programs can be fostered by selecting appropriate combinations of architectural traits which determine light interception and carbon acquisition. In apple tree, architectural traits were observed to be under genetic control. However, architectural traits also result from many organogenetic and morphological processes interacting with the environment. The present study aimed at combining a FSPM built for apple tree, MAppleT, with genetic determinisms of architectural traits, previously described in a bi-parental population. We focused on parameters related to organogenesis (phyllochron and immediate branching) and morphogenesis processes (internode length and leaf area) during the first year of tree growth. Two independent datasets collected in 2004 and 2007 on 116 genotypes, issued from a 'Starkrimson' × 'Granny Smith' cross, were used. The phyllochron was estimated as a function of thermal time and sylleptic branching was modeled subsequently depending on phyllochron. From a genetic map built with SNPs, marker effects were estimated on four MAppleT parameters with rrBLUP, using 2007 data. These effects were then considered in MAppleT to simulate tree development in the two climatic conditions. The genome wide prediction model gave consistent estimations of parameter values with correlation coefficients between observed values and estimated values from SNP markers ranging from 0.79 to 0.96. However, the accuracy of the prediction model following cross validation schemas was lower. Three integrative traits (the number of leaves, trunk length, and number of sylleptic laterals) were considered for validating MAppleT simulations. In 2007 climatic conditions, simulated values were close to observations, highlighting the correct simulation of genetic variability. However, in 2004 conditions which were not used for model calibration, the simulations differed from observations. This study demonstrates the possibility of integrating genome-based information in a FSPM for a perennial fruit tree. It also showed that further improvements are required for improving the prediction ability. Especially temperature effect should be extended and other factors taken into account for modeling GxE interactions. Improvements could also be expected by considering larger populations and by testing other genome wide prediction models. Despite these limitations, this study opens new possibilities for supporting plant breeding by in silico evaluations of the impact of genotypic polymorphisms on plant integrative phenotypes.
Hemani, Gibran; Yang, Jian; Vinkhuyzen, Anna; Powell, Joseph E; Willemsen, Gonneke; Hottenga, Jouke-Jan; Abdellaoui, Abdel; Mangino, Massimo; Valdes, Ana M; Medland, Sarah E; Madden, Pamela A; Heath, Andrew C; Henders, Anjali K; Nyholt, Dale R; de Geus, Eco J C; Magnusson, Patrik K E; Ingelsson, Erik; Montgomery, Grant W; Spector, Timothy D; Boomsma, Dorret I; Pedersen, Nancy L; Martin, Nicholas G; Visscher, Peter M
2013-11-07
Evidence that complex traits are highly polygenic has been presented by population-based genome-wide association studies (GWASs) through the identification of many significant variants, as well as by family-based de novo sequencing studies indicating that several traits have a large mutational target size. Here, using a third study design, we show results consistent with extreme polygenicity for body mass index (BMI) and height. On a sample of 20,240 siblings (from 9,570 nuclear families), we used a within-family method to obtain narrow-sense heritability estimates of 0.42 (SE = 0.17, p = 0.01) and 0.69 (SE = 0.14, p = 6 × 10(-)(7)) for BMI and height, respectively, after adjusting for covariates. The genomic inflation factors from locus-specific linkage analysis were 1.69 (SE = 0.21, p = 0.04) for BMI and 2.18 (SE = 0.21, p = 2 × 10(-10)) for height. This inflation is free of confounding and congruent with polygenicity, consistent with observations of ever-increasing genomic-inflation factors from GWASs with large sample sizes, implying that those signals are due to true genetic signals across the genome rather than population stratification. We also demonstrate that the distribution of the observed test statistics is consistent with both rare and common variants underlying a polygenic architecture and that previous reports of linkage signals in complex traits are probably a consequence of polygenic architecture rather than the segregation of variants with large effects. The convergent empirical evidence from GWASs, de novo studies, and within-family segregation implies that family-based sequencing studies for complex traits require very large sample sizes because the effects of causal variants are small on average. Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
Kingston, S E; Martino, P; Melendy, M; Reed, F A; Carlon, D B
2018-03-01
A key component to understanding the evolutionary response to a changing climate is linking underlying genetic variation to phenotypic variation in stress response. Here, we use a genome-wide association approach (GWAS) to understand the genetic architecture of calcification rates under simulated climate stress. We take advantage of the genomic gradient across the blue mussel hybrid zone (Mytilus edulis and Mytilus trossulus) in the Gulf of Maine (GOM) to link genetic variation with variance in calcification rates in response to simulated climate change. Falling calcium carbonate saturation states are predicted to negatively impact many marine organisms that build calcium carbonate shells - like blue mussels. We sampled wild mussels and measured net calcification phenotypes after exposing mussels to a 'climate change' common garden, where we raised temperature by 3°C, decreased pH by 0.2 units and limited food supply by filtering out planktonic particles >5 μm, compared to ambient GOM conditions in the summer. This climate change exposure greatly increased phenotypic variation in net calcification rates compared to ambient conditions. We then used regression models to link the phenotypic variation with over 170 000 single nucleotide polymorphism loci (SNPs) generated by genotype by sequencing to identify genomic locations associated with calcification phenotype, and estimate heritability and architecture of the trait. We identified at least one of potentially 2-10 genomic regions responsible for 30% of the phenotypic variation in calcification rates that are potential targets of natural selection by climate change. Our simulations suggest a power of 13.7% with our study's average effective sample size of 118 individuals and rare alleles, but a power of >90% when effective sample size is 900. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.
Failure to Replicate a Genetic Association May Provide Important Clues About Genetic Architecture
Greene, Casey S.; Penrod, Nadia M.; Williams, Scott M.; Moore, Jason H.
2009-01-01
Replication has become the gold standard for assessing statistical results from genome-wide association studies. Unfortunately this replication requirement may cause real genetic effects to be missed. A real result can fail to replicate for numerous reasons including inadequate sample size or variability in phenotype definitions across independent samples. In genome-wide association studies the allele frequencies of polymorphisms may differ due to sampling error or population differences. We hypothesize that some statistically significant independent genetic effects may fail to replicate in an independent dataset when allele frequencies differ and the functional polymorphism interacts with one or more other functional polymorphisms. To test this hypothesis, we designed a simulation study in which case-control status was determined by two interacting polymorphisms with heritabilities ranging from 0.025 to 0.4 with replication sample sizes ranging from 400 to 1600 individuals. We show that the power to replicate the statistically significant independent main effect of one polymorphism can drop dramatically with a change of allele frequency of less than 0.1 at a second interacting polymorphism. We also show that differences in allele frequency can result in a reversal of allelic effects where a protective allele becomes a risk factor in replication studies. These results suggest that failure to replicate an independent genetic effect may provide important clues about the complexity of the underlying genetic architecture. We recommend that polymorphisms that fail to replicate be checked for interactions with other polymorphisms, particularly when samples are collected from groups with distinct ethnic backgrounds or different geographic regions. PMID:19503614
The emotion system promotes diversity and evolvability
Giske, Jarl; Eliassen, Sigrunn; Fiksen, Øyvind; Jakobsen, Per J.; Aksnes, Dag L.; Mangel, Marc; Jørgensen, Christian
2014-01-01
Studies on the relationship between the optimal phenotype and its environment have had limited focus on genotype-to-phenotype pathways and their evolutionary consequences. Here, we study how multi-layered trait architecture and its associated constraints prescribe diversity. Using an idealized model of the emotion system in fish, we find that trait architecture yields genetic and phenotypic diversity even in absence of frequency-dependent selection or environmental variation. That is, for a given environment, phenotype frequency distributions are predictable while gene pools are not. The conservation of phenotypic traits among these genetically different populations is due to the multi-layered trait architecture, in which one adaptation at a higher architectural level can be achieved by several different adaptations at a lower level. Our results emphasize the role of convergent evolution and the organismal level of selection. While trait architecture makes individuals more constrained than what has been assumed in optimization theory, the resulting populations are genetically more diverse and adaptable. The emotion system in animals may thus have evolved by natural selection because it simultaneously enhances three important functions, the behavioural robustness of individuals, the evolvability of gene pools and the rate of evolutionary innovation at several architectural levels. PMID:25100697
The emotion system promotes diversity and evolvability.
Giske, Jarl; Eliassen, Sigrunn; Fiksen, Øyvind; Jakobsen, Per J; Aksnes, Dag L; Mangel, Marc; Jørgensen, Christian
2014-09-22
Studies on the relationship between the optimal phenotype and its environment have had limited focus on genotype-to-phenotype pathways and their evolutionary consequences. Here, we study how multi-layered trait architecture and its associated constraints prescribe diversity. Using an idealized model of the emotion system in fish, we find that trait architecture yields genetic and phenotypic diversity even in absence of frequency-dependent selection or environmental variation. That is, for a given environment, phenotype frequency distributions are predictable while gene pools are not. The conservation of phenotypic traits among these genetically different populations is due to the multi-layered trait architecture, in which one adaptation at a higher architectural level can be achieved by several different adaptations at a lower level. Our results emphasize the role of convergent evolution and the organismal level of selection. While trait architecture makes individuals more constrained than what has been assumed in optimization theory, the resulting populations are genetically more diverse and adaptable. The emotion system in animals may thus have evolved by natural selection because it simultaneously enhances three important functions, the behavioural robustness of individuals, the evolvability of gene pools and the rate of evolutionary innovation at several architectural levels.
Albert, Elise; Segura, Vincent; Gricourt, Justine; Bonnefoi, Julien; Derivot, Laurent; Causse, Mathilde
2016-01-01
Water scarcity constitutes a crucial constraint for agriculture productivity. High-throughput approaches in model plant species identified hundreds of genes potentially involved in survival under drought, but few having beneficial effects on quality and yield. Nonetheless, controlled water deficit may improve fruit quality through higher concentration of flavor compounds. The underlying genetic determinants are still poorly known. In this study, we phenotyped 141 highly diverse small fruit tomato accessions for 27 traits under two contrasting watering conditions. A subset of 55 accessions exhibited increased metabolite contents and maintained yield under water deficit. Using 6100 single nucleotide polymorphisms (SNPs), association mapping revealed 31, 41, and 44 quantitative trait loci (QTLs) under drought, control, and both conditions, respectively. Twenty-five additional QTLs were interactive between conditions, emphasizing the interest in accounting for QTLs by watering regime interactions in fruit quality improvement. Combining our results with the loci previously identified in a biparental progeny resulted in 11 common QTLs and contributed to a first detailed characterization of the genetic determinants of response to water deficit in tomato. Major QTLs for fruit quality traits were dissected and candidate genes were proposed using expression and polymorphism data. The outcomes provide a basis for fruit quality improvement under deficit irrigation while limiting yield losses. PMID:27856709
Automated Synthesis of Architecture of Avionic Systems
NASA Technical Reports Server (NTRS)
Chau, Savio; Xu, Joseph; Dang, Van; Lu, James F.
2006-01-01
The Architecture Synthesis Tool (AST) is software that automatically synthesizes software and hardware architectures of avionic systems. The AST is expected to be most helpful during initial formulation of an avionic-system design, when system requirements change frequently and manual modification of architecture is time-consuming and susceptible to error. The AST comprises two parts: (1) an architecture generator, which utilizes a genetic algorithm to create a multitude of architectures; and (2) a functionality evaluator, which analyzes the architectures for viability, rejecting most of the non-viable ones. The functionality evaluator generates and uses a viability tree a hierarchy representing functions and components that perform the functions such that the system as a whole performs system-level functions representing the requirements for the system as specified by a user. Architectures that survive the functionality evaluator are further evaluated by the selection process of the genetic algorithm. Architectures found to be most promising to satisfy the user s requirements and to perform optimally are selected as parents to the next generation of architectures. The foregoing process is iterated as many times as the user desires. The final output is one or a few viable architectures that satisfy the user s requirements.
Genetic architecture of feed efficiency in mid-lactation Holstein dairy cows
USDA-ARS?s Scientific Manuscript database
The objective of this study was to explore the genetic architecture and biological basis of feed efficiency in lactating Holstein cows. In total, 4,918 cows with actual or imputed genotypes for 60,671 SNP had individual feed intake, milk yield, milk composition, and body weight records. Cows were ...
Caseys, Celine; Stritt, Christoph; Glauser, Gaetan; Blanchard, Thierry; Lexer, Christian
2015-01-01
The mechanisms responsible for the origin, maintenance and evolution of plant secondary metabolite diversity remain largely unknown. Decades of phenotypic studies suggest hybridization as a key player in generating chemical diversity in plants. Knowledge of the genetic architecture and selective constraints of phytochemical traits is key to understanding the effects of hybridization on plant chemical diversity and ecological interactions. Using the European Populus species P. alba (White poplar) and P. tremula (European aspen) and their hybrids as a model, we examined levels of inter- and intraspecific variation, heritabilities, phenotypic correlations, and the genetic architecture of 38 compounds of the phenylpropanoid pathway measured by liquid chromatography and mass spectrometry (UHPLC-MS). We detected 41 quantitative trait loci (QTL) for chlorogenic acids, salicinoids and flavonoids by genetic mapping in natural hybrid crosses. We show that these three branches of the phenylpropanoid pathway exhibit different geographic patterns of variation, heritabilities, and genetic architectures, and that they are affected differently by hybridization and evolutionary constraints. Flavonoid abundances present high species specificity, clear geographic structure, and strong genetic determination, contrary to salicinoids and chlorogenic acids. Salicinoids, which represent important defence compounds in Salicaceae, exhibited pronounced genetic correlations on the QTL map. Our results suggest that interspecific phytochemical differentiation is concentrated in downstream sections of the phenylpropanoid pathway. In particular, our data point to glycosyltransferase enzymes as likely targets of rapid evolution and interspecific differentiation in the ‘model forest tree’ Populus. PMID:26010156
Caseys, Celine; Stritt, Christoph; Glauser, Gaetan; Blanchard, Thierry; Lexer, Christian
2015-01-01
The mechanisms responsible for the origin, maintenance and evolution of plant secondary metabolite diversity remain largely unknown. Decades of phenotypic studies suggest hybridization as a key player in generating chemical diversity in plants. Knowledge of the genetic architecture and selective constraints of phytochemical traits is key to understanding the effects of hybridization on plant chemical diversity and ecological interactions. Using the European Populus species P. alba (White poplar) and P. tremula (European aspen) and their hybrids as a model, we examined levels of inter- and intraspecific variation, heritabilities, phenotypic correlations, and the genetic architecture of 38 compounds of the phenylpropanoid pathway measured by liquid chromatography and mass spectrometry (UHPLC-MS). We detected 41 quantitative trait loci (QTL) for chlorogenic acids, salicinoids and flavonoids by genetic mapping in natural hybrid crosses. We show that these three branches of the phenylpropanoid pathway exhibit different geographic patterns of variation, heritabilities, and genetic architectures, and that they are affected differently by hybridization and evolutionary constraints. Flavonoid abundances present high species specificity, clear geographic structure, and strong genetic determination, contrary to salicinoids and chlorogenic acids. Salicinoids, which represent important defence compounds in Salicaceae, exhibited pronounced genetic correlations on the QTL map. Our results suggest that interspecific phytochemical differentiation is concentrated in downstream sections of the phenylpropanoid pathway. In particular, our data point to glycosyltransferase enzymes as likely targets of rapid evolution and interspecific differentiation in the 'model forest tree' Populus.
Harnessing Genetic Variation in Leaf Angle to Increase Productivity of Sorghum bicolor
Truong, Sandra K.; McCormick, Ryan F.; Rooney, William L.; Mullet, John E.
2015-01-01
The efficiency with which a plant intercepts solar radiation is determined primarily by its architecture. Understanding the genetic regulation of plant architecture and how changes in architecture affect performance can be used to improve plant productivity. Leaf inclination angle, the angle at which a leaf emerges with respect to the stem, is a feature of plant architecture that influences how a plant canopy intercepts solar radiation. Here we identify extensive genetic variation for leaf inclination angle in the crop plant Sorghum bicolor, a C4 grass species used for the production of grain, forage, and bioenergy. Multiple genetic loci that regulate leaf inclination angle were identified in recombinant inbred line populations of grain and bioenergy sorghum. Alleles of sorghum dwarf-3, a gene encoding a P-glycoprotein involved in polar auxin transport, are shown to change leaf inclination angle by up to 34° (0.59 rad). The impact of heritable variation in leaf inclination angle on light interception in sorghum canopies was assessed using functional-structural plant models and field experiments. Smaller leaf inclination angles caused solar radiation to penetrate deeper into the canopy, and the resulting redistribution of light is predicted to increase the biomass yield potential of bioenergy sorghum by at least 3%. These results show that sorghum leaf angle is a heritable trait regulated by multiple loci and that genetic variation in leaf angle can be used to modify plant architecture to improve sorghum crop performance. PMID:26323882
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.
Genetic Architecture of Conspicuous Red Ornaments in Female Threespine Stickleback
Yong, Lengxob; Peichel, Catherine L.; McKinnon, Jeffrey S.
2015-01-01
Explaining the presence of conspicuous female ornaments that take the form of male-typical traits has been a longstanding challenge in evolutionary biology. Such female ornaments have been proposed to evolve via both adaptive and nonadaptive evolutionary processes. Determining the genetic underpinnings of female ornaments is important for elucidating the mechanisms by which such female traits arise and persist in natural populations, but detailed information about their genetic basis is still scarce. In this study, we investigated the genetic architecture of two ornaments, the orange-red throat and pelvic spine, in the threespine stickleback (Gasterosteus aculeatus). Throat coloration is male-specific in ancestral marine populations but has evolved in females in some derived stream populations, whereas sexual dimorphism in pelvic spine coloration is variable among populations. We find that ornaments share a common genetic architecture between the sexes. At least three independent genomic regions contribute to red throat coloration, and harbor candidate genes related to pigment production and pigment cell differentiation. One of these regions is also associated with spine coloration, indicating that both ornaments might be mediated partly via pleiotropic genetic mechanisms. PMID:26715094
Genetic control of inflorescence architecture in legumes
Benlloch, Reyes; Berbel, Ana; Ali, Latifeh; Gohari, Gholamreza; Millán, Teresa; Madueño, Francisco
2015-01-01
The architecture of the inflorescence, the shoot system that bears the flowers, is a main component of the huge diversity of forms found in flowering plants. Inflorescence architecture has also a strong impact on the production of fruits and seeds, and on crop management, two highly relevant agronomical traits. Elucidating the genetic networks that control inflorescence development, and how they vary between different species, is essential to understanding the evolution of plant form and to being able to breed key architectural traits in crop species. Inflorescence architecture depends on the identity and activity of the meristems in the inflorescence apex, which determines when flowers are formed, how many are produced and their relative position in the inflorescence axis. Arabidopsis thaliana, where the genetic control of inflorescence development is best known, has a simple inflorescence, where the primary inflorescence meristem directly produces the flowers, which are thus borne in the main inflorescence axis. In contrast, legumes represent a more complex inflorescence type, the compound inflorescence, where flowers are not directly borne in the main inflorescence axis but, instead, they are formed by secondary or higher order inflorescence meristems. Studies in model legumes such as pea (Pisum sativum) or Medicago truncatula have led to a rather good knowledge of the genetic control of the development of the legume compound inflorescence. In addition, the increasing availability of genetic and genomic tools for legumes is allowing to rapidly extending this knowledge to other grain legume crops. This review aims to describe the current knowledge of the genetic network controlling inflorescence development in legumes. It also discusses how the combination of this knowledge with the use of emerging genomic tools and resources may allow rapid advances in the breeding of grain legume crops. PMID:26257753
Grinde, Kelsey E.; Arbet, Jaron; Green, Alden; O'Connell, Michael; Valcarcel, Alessandra; Westra, Jason; Tintle, Nathan
2017-01-01
To date, gene-based rare variant testing approaches have focused on aggregating information across sets of variants to maximize statistical power in identifying genes showing significant association with diseases. Beyond identifying genes that are associated with diseases, the identification of causal variant(s) in those genes and estimation of their effect is crucial for planning replication studies and characterizing the genetic architecture of the locus. However, we illustrate that straightforward single-marker association statistics can suffer from substantial bias introduced by conditioning on gene-based test significance, due to the phenomenon often referred to as “winner's curse.” We illustrate the ramifications of this bias on variant effect size estimation and variant prioritization/ranking approaches, outline parameters of genetic architecture that affect this bias, and propose a bootstrap resampling method to correct for this bias. We find that our correction method significantly reduces the bias due to winner's curse (average two-fold decrease in bias, p < 2.2 × 10−6) and, consequently, substantially improves mean squared error and variant prioritization/ranking. The method is particularly helpful in adjustment for winner's curse effects when the initial gene-based test has low power and for relatively more common, non-causal variants. Adjustment for winner's curse is recommended for all post-hoc estimation and ranking of variants after a gene-based test. Further work is necessary to continue seeking ways to reduce bias and improve inference in post-hoc analysis of gene-based tests under a wide variety of genetic architectures. PMID:28959274
Insights into the genetic architecture of morphological traits in two passerine bird species.
Silva, C N S; McFarlane, S E; Hagen, I J; Rönnegård, L; Billing, A M; Kvalnes, T; Kemppainen, P; Rønning, B; Ringsby, T H; Sæther, B-E; Qvarnström, A; Ellegren, H; Jensen, H; Husby, A
2017-09-01
Knowledge about the underlying genetic architecture of phenotypic traits is needed to understand and predict evolutionary dynamics. The number of causal loci, magnitude of the effects and location in the genome are, however, still largely unknown. Here, we use genome-wide single-nucleotide polymorphism (SNP) data from two large-scale data sets on house sparrows and collared flycatchers to examine the genetic architecture of different morphological traits (tarsus length, wing length, body mass, bill depth, bill length, total and visible badge size and white wing patches). Genomic heritabilities were estimated using relatedness calculated from SNPs. The proportion of variance captured by the SNPs (SNP-based heritability) was lower in house sparrows compared with collared flycatchers, as expected given marker density (6348 SNPs in house sparrows versus 38 689 SNPs in collared flycatchers). Indeed, after downsampling to similar SNP density and sample size, this estimate was no longer markedly different between species. Chromosome-partitioning analyses demonstrated that the proportion of variance explained by each chromosome was significantly positively related to the chromosome size for some traits and, generally, that larger chromosomes tended to explain proportionally more variation than smaller chromosomes. Finally, we found two genome-wide significant associations with very small-effect sizes. One SNP on chromosome 20 was associated with bill length in house sparrows and explained 1.2% of phenotypic variation (V P ), and one SNP on chromosome 4 was associated with tarsus length in collared flycatchers (3% of V P ). Although we cannot exclude the possibility of undetected large-effect loci, our results indicate a polygenic basis for morphological traits.
The emergence of overlapping scale-free genetic architecture in digital organisms.
Gerlee, P; Lundh, T
2008-01-01
We have studied the evolution of genetic architecture in digital organisms and found that the gene overlap follows a scale-free distribution, which is commonly found in metabolic networks of many organisms. Our results show that the slope of the scale-free distribution depends on the mutation rate and that the gene development is driven by expansion of already existing genes, which is in direct correspondence to the preferential growth algorithm that gives rise to scale-free networks. To further validate our results we have constructed a simple model of gene development, which recapitulates the results from the evolutionary process and shows that the mutation rate affects the tendency of genes to cluster. In addition we could relate the slope of the scale-free distribution to the genetic complexity of the organisms and show that a high mutation rate gives rise to a more complex genetic architecture.
Pilger, Tyler J; Gido, Keith B; Propst, David L; Whitney, James E; Turner, Thomas F
2017-05-01
Dendritic ecological network (DEN) architecture can be a strong predictor of spatial genetic patterns in theoretical and simulation studies. Yet, interspecific differences in dispersal capabilities and distribution within the network may equally affect species' genetic structuring. We characterized patterns of genetic variation from up to ten microsatellite loci for nine numerically dominant members of the upper Gila River fish community, New Mexico, USA. Using comparative landscape genetics, we evaluated the role of network architecture for structuring populations within species (pairwise F ST ) while explicitly accounting for intraspecific demographic influences on effective population size (N e ). Five species exhibited patterns of connectivity and/or genetic diversity gradients that were predicted by network structure. These species were generally considered to be small-bodied or habitat specialists. Spatial variation of N e was a strong predictor of pairwise F ST for two species, suggesting patterns of connectivity may also be influenced by genetic drift independent of network properties. Finally, two study species exhibited genetic patterns that were unexplained by network properties and appeared to be related to nonequilibrium processes. Properties of DENs shape community-wide genetic structure but effects are modified by intrinsic traits and nonequilibrium processes. Further theoretical development of the DEN framework should account for such cases. © 2017 John Wiley & Sons Ltd.
Palmer, Rohan H C; McGeary, John E; Heath, Andrew C; Keller, Matthew C; Brick, Leslie A; Knopik, Valerie S
2015-12-01
Genetic studies of alcohol dependence (AD) have identified several candidate loci and genes, but most observed effects are small and difficult to reproduce. A plausible explanation for inconsistent findings may be a violation of the assumption that genetic factors contributing to each of the seven DSM-IV criteria point to a single underlying dimension of risk. Given that recent twin studies suggest that the genetic architecture of AD is complex and probably involves multiple discrete genetic factors, the current study employed common single nucleotide polymorphisms in two multivariate genetic models to examine the assumption that the genetic risk underlying DSM-IV AD is unitary. AD symptoms and genome-wide single nucleotide polymorphism (SNP) data from 2596 individuals of European descent from the Study of Addiction: Genetics and Environment were analyzed using genomic-relatedness-matrix restricted maximum likelihood. DSM-IV AD symptom covariance was described using two multivariate genetic factor models. Common SNPs explained 30% (standard error=0.136, P=0.012) of the variance in AD diagnosis. Additive genetic effects varied across AD symptoms. The common pathway model approach suggested that symptoms could be described by a single latent variable that had a SNP heritability of 31% (0.130, P=0.008). Similarly, the exploratory genetic factor model approach suggested that the genetic variance/covariance across symptoms could be represented by a single genetic factor that accounted for at least 60% of the genetic variance in any one symptom. Additive genetic effects on DSM-IV alcohol dependence criteria overlap. The assumption of common genetic effects across alcohol dependence symptoms appears to be a valid assumption. © 2015 Society for the Study of Addiction.
Electrophysiological Endophenotypes for Schizophrenia
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
Chen, Zongliang; Wang, Baobao; Dong, Xiaomei; Liu, Han; Ren, Longhui; Chen, Jian; Hauck, Andrew; Song, Weibin; Lai, Jinsheng
2014-06-04
Understanding genetic control of tassel and ear architecture in maize (Zea mays L. ssp. mays) is important due to their relationship with grain yield. High resolution QTL mapping is critical for understanding the underlying molecular basis of phenotypic variation. Advanced populations, such as recombinant inbred lines, have been broadly adopted for QTL mapping; however, construction of large advanced generation crop populations is time-consuming and costly. The rapidly declining cost of genotyping due to recent advances in next-generation sequencing technologies has generated new possibilities for QTL mapping using large early generation populations. A set of 708 F2 progeny derived from inbreds Chang7-2 and 787 were generated and genotyped by whole genome low-coverage genotyping-by-sequencing method (average 0.04×). A genetic map containing 6,533 bin-markers was constructed based on the parental SNPs and a sliding-window method, spanning a total genetic distance of 1,396 cM. The high quality and accuracy of this map was validated by the identification of two well-studied genes, r1, a qualitative trait locus for color of silk (chromosome 10) and ba1 for tassel branch number (chromosome 3). Three traits of tassel and ear architecture were evaluated in this population, a total of 10 QTL were detected using a permutation-based-significance threshold, seven of which overlapped with reported QTL. Three genes (GRMZM2G316366, GRMZM2G492156 and GRMZM5G805008) encoding MADS-box domain proteins and a BTB/POZ domain protein were located in the small intervals of qTBN5 and qTBN7 (~800 Kb and 1.6 Mb in length, respectively) and may be involved in patterning of tassel architecture. The small physical intervals of most QTL indicate high-resolution mapping is obtainable with this method. We constructed an ultra-high-dentisy linkage map for the large early generation population in maize. Our study provides an efficient approach for fast detection of quantitative loci responsible for complex trait variation with high accuracy, thus helping to dissect the underlying molecular basis of phenotypic variation and accelerate improvement of crop breeding in a cost-effective fashion.
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.
Knudsen, Erik S; Balaji, Uthra; Mannakee, Brian; Vail, Paris; Eslinger, Cody; Moxom, Christopher; Mansour, John; Witkiewicz, Agnieszka K
2018-03-01
Pancreatic ductal adenocarcinoma (PDAC) is a therapy recalcitrant disease with the worst survival rate of common solid tumours. Preclinical models that accurately reflect the genetic and biological diversity of PDAC will be important for delineating features of tumour biology and therapeutic vulnerabilities. 27 primary PDAC tumours were employed for genetic analysis and development of tumour models. Tumour tissue was used for derivation of xenografts and cell lines. Exome sequencing was performed on the originating tumour and developed models. RNA sequencing, histological and functional analyses were employed to determine the relationship of the patient-derived models to clinical presentation of PDAC. The cohort employed captured the genetic diversity of PDAC. From most cases, both cell lines and xenograft models were developed. Exome sequencing confirmed preservation of the primary tumour mutations in developed cell lines, which remained stable with extended passaging. The level of genetic conservation in the cell lines was comparable to that observed with patient-derived xenograft (PDX) models. Unlike historically established PDAC cancer cell lines, patient-derived models recapitulated the histological architecture of the primary tumour and exhibited metastatic spread similar to that observed clinically. Detailed genetic analyses of tumours and derived models revealed features of ex vivo evolution and the clonal architecture of PDAC. Functional analysis was used to elucidate therapeutic vulnerabilities of relevance to treatment of PDAC. These data illustrate that with the appropriate methods it is possible to develop cell lines that maintain genetic features of PDAC. Such models serve as important substrates for analysing the significance of genetic variants and create a unique biorepository of annotated cell lines and xenografts that were established simultaneously from same primary tumour. These models can be used to infer genetic and empirically determined therapeutic sensitivities that would be germane to the patient. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
Schrodi, Steven J.; Mukherjee, Shubhabrata; Shan, Ying; Tromp, Gerard; Sninsky, John J.; Callear, Amy P.; Carter, Tonia C.; Ye, Zhan; Haines, Jonathan L.; Brilliant, Murray H.; Crane, Paul K.; Smelser, Diane T.; Elston, Robert C.; Weeks, Daniel E.
2014-01-01
Translation of results from genetic findings to inform medical practice is a highly anticipated goal of human genetics. The aim of this paper is to review and discuss the role of genetics in medically-relevant prediction. Germline genetics presages disease onset and therefore can contribute prognostic signals that augment laboratory tests and clinical features. As such, the impact of genetic-based predictive models on clinical decisions and therapy choice could be profound. However, given that (i) medical traits result from a complex interplay between genetic and environmental factors, (ii) the underlying genetic architectures for susceptibility to common diseases are not well-understood, and (iii) replicable susceptibility alleles, in combination, account for only a moderate amount of disease heritability, there are substantial challenges to constructing and implementing genetic risk prediction models with high utility. In spite of these challenges, concerted progress has continued in this area with an ongoing accumulation of studies that identify disease predisposing genotypes. Several statistical approaches with the aim of predicting disease have been published. Here we summarize the current state of disease susceptibility mapping and pharmacogenetics efforts for risk prediction, describe methods used to construct and evaluate genetic-based predictive models, and discuss applications. PMID:24917882
Genetic architecture for human aggression: A study of gene-phenotype relationship in OMIM.
Zhang-James, Yanli; Faraone, Stephen V
2016-07-01
Genetic studies of human aggression have mainly focused on known candidate genes and pathways regulating serotonin and dopamine signaling and hormonal functions. These studies have taught us much about the genetics of human aggression, but no genetic locus has yet achieved genome-significance. We here present a review based on a paradoxical hypothesis that studies of rare, functional genetic variations can lead to a better understanding of the molecular mechanisms underlying complex multifactorial disorders such as aggression. We examined all aggression phenotypes catalogued in Online Mendelian Inheritance in Man (OMIM), an Online Catalog of Human Genes and Genetic Disorders. We identified 95 human disorders that have documented aggressive symptoms in at least one individual with a well-defined genetic variant. Altogether, we retrieved 86 causal genes. Although most of these genes had not been implicated in human aggression by previous studies, the most significantly enriched canonical pathways had been previously implicated in aggression (e.g., serotonin and dopamine signaling). Our findings provide strong evidence to support the causal role of these pathways in the pathogenesis of aggression. In addition, the novel genes and pathways we identified suggest additional mechanisms underlying the origins of human aggression. Genome-wide association studies with very large samples will be needed to determine if common variants in these genes are risk factors for aggression. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
An evolutionary method for synthesizing technological planning and architectural advance
NASA Astrophysics Data System (ADS)
Cole, Bjorn Forstrom
In the development of systems with ever-increasing performance and/or decreasing drawbacks, there inevitably comes a point where more progress is available by shifting to a new set of principles of use. This shift marks a change in architecture, such as between the piston-driven propeller and the jet engine. The shift also often involves an abandonment of previous competencies that have been developed with great effort, and so a foreknowledge of these shifts can be advantageous. A further motivation for this work is the consideration of the Micro Autonomous Systems and Technology (MAST) project, which aims to develop very small (<5 cm) robots for a variety of uses. This is primarily a technology research project, and there is no baseline morphology for a robot to be considered. This then motivates an interest in the ability to automatically compose physical architectures from a series of components and quantitatively analyze them for a basic, conceptual analysis. The ability to do this would enable researchers to turn attention to the most promising forms. This work presents a method for using technology forecasts of components that enable future architectural shifts in order to forecast those shifts. The method consists of the use of multidimensional S-curves, genetic algorithms, and a graph-based formulation of architecture that is more flexible than other morphological techniques. Potential genetic operators are explored in depth to draft a final graph-based genetic algorithm. This algorithm is then implemented in a design code called Sindri, which leverages a commercial design tool named Pacelab. The first chapters of this thesis provide context and a philosophical background to the studies and research that was conducted. In particular, the idea that technology progresses in a fundamentally gradual way is developed and supported with previous historical research. The import of this is that the future can to some degree be predicted by the past, provided that the appropriate technological antecedents are accounted for in developing the projection. The third chapter of the thesis compiles a series of observations and philosophical considerations into a series of research questions. Some research questions are then answered with further thought, observation, and reading, leading to conjectures on the problem. The remainder require some form of experimentation, and so are used to formulate hypotheses. Falsifiability conditions are then generated from those hypotheses, and used to get the development of experiments to be performed, in this case on a computer upon various conditions of use of a genetic algorithm. The fourth chapter of the thesis walks through the formulation of a method to attack the problem of strategically choosing an architecture. This method is designed to find the optimum architecture under multiple conditions, which is required for the ability to play the "what if" games typically undertaken in strategic situations. The chapter walks through a graph-based representation of architecture, provides the rationale for choosing a given technology forecasting technique, and lays out the implementation of the optimization algorithm, named Sindri, within a commercial analysis code, Pacelab. The fifth chapter of the thesis then tests the Sindri code. The first test applied is a series of standardized combinatorial spaces, which are meant to be analogous to test problems traditionally posed to optimizers (e.g., Rosenbrock's valley function). The results from this test assess the value of various operators used to transform the architecture graph in the course of conducting a genetic search. Finally, this method is employed on a test case involving the transition of a miniature helicopter from glow engine to battery propulsion, and finally to a design where the battery functions as both structure and power source. The final two chapters develop conclusions based on the body of work conducted within this thesis and issue some prescriptions for future work. The future work primarily concerns improving the continuous optimization processes undertaken within Sindri and in further refining the graph-based structure for physical architectures.
Investigating the Genetic Architecture of the PR Interval Using Clinical Phenotypes.
Mosley, Jonathan D; Shoemaker, M Benjamin; Wells, Quinn S; Darbar, Dawood; Shaffer, Christian M; Edwards, Todd L; Bastarache, Lisa; McCarty, Catherine A; Thompson, Will; Chute, Christopher G; Jarvik, Gail P; Crosslin, David R; Larson, Eric B; Kullo, Iftikhar J; Pacheco, Jennifer A; Peissig, Peggy L; Brilliant, Murray H; Linneman, James G; Witte, John S; Denny, Josh C; Roden, Dan M
2017-04-01
One potential use for the PR interval is as a biomarker of disease risk. We hypothesized that quantifying the shared genetic architectures of the PR interval and a set of clinical phenotypes would identify genetic mechanisms contributing to PR variability and identify diseases associated with a genetic predictor of PR variability. We used ECG measurements from the ARIC study (Atherosclerosis Risk in Communities; n=6731 subjects) and 63 genetically modulated diseases from the eMERGE network (Electronic Medical Records and Genomics; n=12 978). We measured pairwise genetic correlations (rG) between PR phenotypes (PR interval, PR segment, P-wave duration) and each of the 63 phenotypes. The PR segment was genetically correlated with atrial fibrillation (rG=-0.88; P =0.0009). An analysis of metabolic phenotypes in ARIC also showed that the P wave was genetically correlated with waist circumference (rG=0.47; P =0.02). A genetically predicted PR interval phenotype based on 645 714 single-nucleotide polymorphisms was associated with atrial fibrillation (odds ratio=0.89 per SD change; 95% confidence interval, 0.83-0.95; P =0.0006). The differing pattern of associations among the PR phenotypes is consistent with analyses that show that the genetic correlation between the P wave and PR segment was not significantly different from 0 (rG=-0.03 [0.16]). The genetic architecture of the PR interval comprises modulators of atrial fibrillation risk and obesity. © 2017 American Heart Association, Inc.
GlobAl Distribution of GEnetic Traits (GADGET) web server: polygenic trait scores worldwide.
Chande, Aroon T; Wang, Lu; Rishishwar, Lavanya; Conley, Andrew B; Norris, Emily T; Valderrama-Aguirre, Augusto; Jordan, I King
2018-05-18
Human populations from around the world show striking phenotypic variation across a wide variety of traits. Genome-wide association studies (GWAS) are used to uncover genetic variants that influence the expression of heritable human traits; accordingly, population-specific distributions of GWAS-implicated variants may shed light on the genetic basis of human phenotypic diversity. With this in mind, we developed the GlobAl Distribution of GEnetic Traits web server (GADGET http://gadget.biosci.gatech.edu). The GADGET web server provides users with a dynamic visual platform for exploring the relationship between worldwide genetic diversity and the genetic architecture underlying numerous human phenotypes. GADGET integrates trait-implicated single nucleotide polymorphisms (SNPs) from GWAS, with population genetic data from the 1000 Genomes Project, to calculate genome-wide polygenic trait scores (PTS) for 818 phenotypes in 2504 individual genomes. Population-specific distributions of PTS are shown for 26 human populations across 5 continental population groups, with traits ordered based on the extent of variation observed among populations. Users of GADGET can also upload custom trait SNP sets to visualize global PTS distributions for their own traits of interest.
Assessment of the Genetic Architecture of Alzheimer's Disease Risk in Rate of Memory Decline.
Del-Aguila, Jorge L; Fernández, Maria Victoria; Schindler, Suzanne; Ibanez, Laura; Deming, Yuetiva; Ma, Shengmei; Saef, Ben; Black, Kathleen; Budde, John; Norton, Joanne; Chasse, Rachel; Harari, Oscar; Goate, Alison; Xiong, Chengjie; Morris, John C; Cruchaga, Carlos
2018-01-01
Many genetic studies for Alzheimer's disease (AD) have been focused on the identification of common genetic variants associated with AD risk and not on other aspects of the disease, such as age at onset or rate of dementia progression. There are multiple approaches to untangling the genetic architecture of these phenotypes. We hypothesized that the genetic architecture of rate of progression is different than the risk for developing AD dementia. To test this hypothesis, we used longitudinal clinical data from ADNI and the Knight-ADRC at Washington University, and we calculated PRS (polygenic risk score) based on the IGAP study to compare the genetic architecture of AD risk and dementia progression. Dementia progression was measured by the change of Clinical Dementia Rating Sum of Boxes (CDR)-SB per year. Out of the 21 loci for AD risk, no association with the rate of dementia progression was found. The PRS rate was significantly associated with the rate of dementia progression (β= 0.146, p = 0.03). In the case of rare variants, TREM2 (β= 0.309, p = 0.02) was also associated with the rate of dementia progression. TREM2 variant carriers showed a 23% faster rate of dementia compared with non-variant carriers. In conclusion, our results indicate that the recently identified common and rare variants for AD susceptibility have a limited impact on the rate of dementia progression in AD patients.
Genetics in child and adolescent psychiatry: methodological advances and conceptual issues.
Hohmann, Sarah; Adamo, Nicoletta; Lahey, Benjamin B; Faraone, Stephen V; Banaschewski, Tobias
2015-06-01
Discovering the genetic basis of early-onset psychiatric disorders has been the aim of intensive research during the last decade. We will first selectively summarize results of genetic research in child and adolescent psychiatry by using examples from different disorders and discuss methodological issues, emerging questions and future directions. In the second part of this review, we will focus on how to link genetic causes of disorders with physiological pathways, discuss the impact of genetic findings on diagnostic systems, prevention and therapeutic interventions. Finally we will highlight some ethical aspects connected to genetic research in child and adolescent psychiatry. Advances in molecular genetic methods have led to insights into the genetic architecture of psychiatric disorders, but not yet provided definite pathways to pathophysiology. If replicated, promising findings from genetic studies might in some cases lead to personalized treatments. On the one hand, knowledge of the genetic basis of disorders may influence diagnostic categories. On the other hand, models also suggest studying the genetic architecture of psychiatric disorders across diagnoses and clinical groups.
Wild, Philipp S.; Felix, Janine F.; Schillert, Arne; Chen, Ming-Huei; Leening, Maarten J.G.; Völker, Uwe; Großmann, Vera; Brody, Jennifer A.; Irvin, Marguerite R.; Shah, Sanjiv J.; Pramana, Setia; Lieb, Wolfgang; Schmidt, Reinhold; Stanton, Alice V.; Malzahn, Dörthe; Lyytikäinen, Leo-Pekka; Tiller, Daniel; Smith, J. Gustav; Di Tullio, Marco R.; Musani, Solomon K.; Morrison, Alanna C.; Pers, Tune H.; Morley, Michael; Kleber, Marcus E.; Aragam, Jayashri; Bis, Joshua C.; Bisping, Egbert; Broeckel, Ulrich; Cheng, Susan; Deckers, Jaap W.; Del Greco M, Fabiola; Edelmann, Frank; Fornage, Myriam; Franke, Lude; Friedrich, Nele; Harris, Tamara B.; Hofer, Edith; Hofman, Albert; Huang, Jie; Hughes, Alun D.; Kähönen, Mika; investigators, KNHI; Kruppa, Jochen; Lackner, Karl J.; Lannfelt, Lars; Laskowski, Rafael; Launer, Lenore J.; Lindgren, Cecilia M.; Loley, Christina; Mayet, Jamil; Medenwald, Daniel; Morris, Andrew P.; Müller, Christian; Müller-Nurasyid, Martina; Nappo, Stefania; Nilsson, Peter M.; Nuding, Sebastian; Nutile, Teresa; Peters, Annette; Pfeufer, Arne; Pietzner, Diana; Pramstaller, Peter P.; Raitakari, Olli T.; Rice, Kenneth M.; Rotter, Jerome I.; Ruohonen, Saku T.; Sacco, Ralph L.; Samdarshi, Tandaw E.; Sharp, Andrew S.P.; Shields, Denis C.; Sorice, Rossella; Sotoodehnia, Nona; Stricker, Bruno H.; Surendran, Praveen; Töglhofer, Anna M.; Uitterlinden, André G.; Völzke, Henry; Ziegler, Andreas; Münzel, Thomas; März, Winfried; Cappola, Thomas P.; Hirschhorn, Joel N.; Mitchell, Gary F.; Smith, Nicholas L.; Fox, Ervin R.; Dueker, Nicole D.; Jaddoe, Vincent W.V.; Melander, Olle; Lehtimäki, Terho; Ciullo, Marina; Hicks, Andrew A.; Lind, Lars; Gudnason, Vilmundur; Pieske, Burkert; Barron, Anthony J.; Zweiker, Robert; Schunkert, Heribert; Ingelsson, Erik; Liu, Kiang; Arnett, Donna K.; Psaty, Bruce M.; Blankenberg, Stefan; Larson, Martin G.; Felix, Stephan B.; Franco, Oscar H.; Zeller, Tanja; Vasan, Ramachandran S.; Dörr, Marcus
2017-01-01
BACKGROUND. Understanding the genetic architecture of cardiac structure and function may help to prevent and treat heart disease. This investigation sought to identify common genetic variations associated with inter-individual variability in cardiac structure and function. METHODS. A GWAS meta-analysis of echocardiographic traits was performed, including 46,533 individuals from 30 studies (EchoGen consortium). The analysis included 16 traits of left ventricular (LV) structure, and systolic and diastolic function. RESULTS. The discovery analysis included 21 cohorts for structural and systolic function traits (n = 32,212) and 17 cohorts for diastolic function traits (n = 21,852). Replication was performed in 5 cohorts (n = 14,321) and 6 cohorts (n = 16,308), respectively. Besides 5 previously reported loci, the combined meta-analysis identified 10 additional genome-wide significant SNPs: rs12541595 near MTSS1 and rs10774625 in ATXN2 for LV end-diastolic internal dimension; rs806322 near KCNRG, rs4765663 in CACNA1C, rs6702619 near PALMD, rs7127129 in TMEM16A, rs11207426 near FGGY, rs17608766 in GOSR2, and rs17696696 in CFDP1 for aortic root diameter; and rs12440869 in IQCH for Doppler transmitral A-wave peak velocity. Findings were in part validated in other cohorts and in GWAS of related disease traits. The genetic loci showed associations with putative signaling pathways, and with gene expression in whole blood, monocytes, and myocardial tissue. CONCLUSION. The additional genetic loci identified in this large meta-analysis of cardiac structure and function provide insights into the underlying genetic architecture of cardiac structure and warrant follow-up in future functional studies. FUNDING. For detailed information per study, see Acknowledgments. PMID:28394258
Genomic atlas of the human plasma proteome.
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.
Frank, Margaret H.; Balaguer, Maria A. de Luis; Li, Mao
2017-01-01
Thicker leaves allow plants to grow in water-limited conditions. However, our understanding of the genetic underpinnings of this highly functional leaf shape trait is poor. We used a custom-built confocal profilometer to directly measure leaf thickness in a set of introgression lines (ILs) derived from the desert tomato Solanum pennellii and identified quantitative trait loci. We report evidence of a complex genetic architecture of this trait and roles for both genetic and environmental factors. Several ILs with thick leaves have dramatically elongated palisade mesophyll cells and, in some cases, increased leaf ploidy. We characterized the thick IL2-5 and IL4-3 in detail and found increased mesophyll cell size and leaf ploidy levels, suggesting that endoreduplication underpins leaf thickness in tomato. Next, we queried the transcriptomes and inferred dynamic Bayesian networks of gene expression across early leaf ontogeny in these lines to compare the molecular networks that pattern leaf thickness. We show that thick ILs share S. pennellii-like expression profiles for putative regulators of cell shape and meristem determinacy as well as a general signature of cell cycle-related gene expression. However, our network data suggest that leaf thickness in these two lines is patterned at least partially by distinct mechanisms. Consistent with this hypothesis, double homozygote lines combining introgression segments from these two ILs show additive phenotypes, including thick leaves, higher ploidy levels, and larger palisade mesophyll cells. Collectively, these data establish a framework of genetic, anatomical, and molecular mechanisms that pattern leaf thickness in desert-adapted tomato. PMID:28794258
Beyond the single gene: How epistasis and gene-by-environment effects influence crop domestication.
Doust, Andrew N; Lukens, Lewis; Olsen, Kenneth M; Mauro-Herrera, Margarita; Meyer, Ann; Rogers, Kimberly
2014-04-29
Domestication is a multifaceted evolutionary process, involving changes in individual genes, genetic interactions, and emergent phenotypes. There has been extensive discussion of the phenotypic characteristics of plant domestication, and recent research has started to identify the specific genes and mutational mechanisms that control domestication traits. However, there is an apparent disconnect between the simple genetic architecture described for many crop domestication traits, which should facilitate rapid phenotypic change under selection, and the slow rate of change reported from the archeobotanical record. A possible explanation involves the middle ground between individual genetic changes and their expression during development, where gene-by-gene (epistatic) and gene-by-environment interactions can modify the expression of phenotypes and opportunities for selection. These aspects of genetic architecture have the potential to significantly slow the speed of phenotypic evolution during crop domestication and improvement. Here we examine whether epistatic and gene-by-environment interactions have shaped how domestication traits have evolved. We review available evidence from the literature, and we analyze two domestication-related traits, shattering and flowering time, in a mapping population derived from a cross between domesticated foxtail millet and its wild progenitor. We find that compared with wild progenitor alleles, those favored during domestication often have large phenotypic effects and are relatively insensitive to genetic background and environmental effects. Consistent selection should thus be able to rapidly change traits during domestication. We conclude that if phenotypic evolution was slow during crop domestication, this is more likely due to cultural or historical factors than epistatic or environmental constraints.
Determination of nonlinear genetic architecture using compressed sensing.
Ho, Chiu Man; Hsu, Stephen D H
2015-01-01
One of the fundamental problems of modern genomics is to extract the genetic architecture of a complex trait from a data set of individual genotypes and trait values. Establishing this important connection between genotype and phenotype is complicated by the large number of candidate genes, the potentially large number of causal loci, and the likely presence of some nonlinear interactions between different genes. Compressed Sensing methods obtain solutions to under-constrained systems of linear equations. These methods can be applied to the problem of determining the best model relating genotype to phenotype, and generally deliver better performance than simply regressing the phenotype against each genetic variant, one at a time. We introduce a Compressed Sensing method that can reconstruct nonlinear genetic models (i.e., including epistasis, or gene-gene interactions) from phenotype-genotype (GWAS) data. Our method uses L1-penalized regression applied to nonlinear functions of the sensing matrix. The computational and data resource requirements for our method are similar to those necessary for reconstruction of linear genetic models (or identification of gene-trait associations), assuming a condition of generalized sparsity, which limits the total number of gene-gene interactions. An example of a sparse nonlinear model is one in which a typical locus interacts with several or even many others, but only a small subset of all possible interactions exist. It seems plausible that most genetic architectures fall in this category. We give theoretical arguments suggesting that the method is nearly optimal in performance, and demonstrate its effectiveness on broad classes of nonlinear genetic models using simulated human genomes and the small amount of currently available real data. A phase transition (i.e., dramatic and qualitative change) in the behavior of the algorithm indicates when sufficient data is available for its successful application. Our results indicate that predictive models for many complex traits, including a variety of human disease susceptibilities (e.g., with additive heritability h (2)∼0.5), can be extracted from data sets comprised of n ⋆∼100s individuals, where s is the number of distinct causal variants influencing the trait. For example, given a trait controlled by ∼10 k loci, roughly a million individuals would be sufficient for application of the method.
The Architecture of Risk for Type 2 Diabetes: Understanding Asia in the Context of Global Findings
Attia, John; Oldmeadow, Christopher; Scott, Rodney J.; Holliday, Elizabeth G.
2014-01-01
The prevalence of Type 2 diabetes is rising rapidly in both developed and developing countries. Asia is developing as the epicentre of the escalating pandemic, reflecting rapid transitions in demography, migration, diet, and lifestyle patterns. The effective management of Type 2 diabetes in Asia may be complicated by differences in prevalence, risk factor profiles, genetic risk allele frequencies, and gene-environment interactions between different Asian countries, and between Asian and other continental populations. To reduce the worldwide burden of T2D, it will be important to understand the architecture of T2D susceptibility both within and between populations. This review will provide an overview of known genetic and nongenetic risk factors for T2D, placing the results from Asian studies in the context of broader global research. Given recent evidence from large-scale genetic studies of T2D, we place special emphasis on emerging knowledge about the genetic architecture of T2D and the potential contribution of genetic effects to population differences in risk. PMID:24744783
Rueppell, Olav
2014-01-01
Social evolution has influenced every aspect of contemporary honey bee biology, but the details are difficult to reconstruct. The reproductive ground plan hypothesis of social evolution proposes that central regulators of the gonotropic cycle of solitary insects have been coopted to coordinate social complexity in honey bees, such as the division of labor among workers. The predicted trait associations between reproductive physiology and social behavior have been identified in the context of the pollen hoarding syndrome, a larger suite of interrelated traits. The genetic architecture of this syndrome is characterized by a partially overlapping genetic architecture with several consistent, pleiotropic QTL. Despite these central QTL and an integrated hormonal regulation, separate aspects of the pollen hoarding syndrome may evolve independently due to peripheral QTL and additionally segregating genetic variance. The characterization of the pollen hoarding syndrome has also demonstrated that this syndrome involves many non-behavioral traits, which may be the case for numerous “behavioral” syndromes. Furthermore, the genetic architecture of the pollen hoarding syndrome has implications for breeding programs for improving honey health and other desirable traits: If these traits are comparable to the pollen hoarding syndrome, consistent pleiotropic QTL will enable marker assisted selection, while sufficient additional genetic variation may permit the dissociation of trade-offs for efficient multiple trait selection. PMID:25506100
Rueppell, Olav
2014-05-01
Social evolution has influenced every aspect of contemporary honey bee biology, but the details are difficult to reconstruct. The reproductive ground plan hypothesis of social evolution proposes that central regulators of the gonotropic cycle of solitary insects have been coopted to coordinate social complexity in honey bees, such as the division of labor among workers. The predicted trait associations between reproductive physiology and social behavior have been identified in the context of the pollen hoarding syndrome, a larger suite of interrelated traits. The genetic architecture of this syndrome is characterized by a partially overlapping genetic architecture with several consistent, pleiotropic QTL. Despite these central QTL and an integrated hormonal regulation, separate aspects of the pollen hoarding syndrome may evolve independently due to peripheral QTL and additionally segregating genetic variance. The characterization of the pollen hoarding syndrome has also demonstrated that this syndrome involves many non-behavioral traits, which may be the case for numerous "behavioral" syndromes. Furthermore, the genetic architecture of the pollen hoarding syndrome has implications for breeding programs for improving honey health and other desirable traits: If these traits are comparable to the pollen hoarding syndrome, consistent pleiotropic QTL will enable marker assisted selection, while sufficient additional genetic variation may permit the dissociation of trade-offs for efficient multiple trait selection.
Albert, Elise; Segura, Vincent; Gricourt, Justine; Bonnefoi, Julien; Derivot, Laurent; Causse, Mathilde
2016-12-01
Water scarcity constitutes a crucial constraint for agriculture productivity. High-throughput approaches in model plant species identified hundreds of genes potentially involved in survival under drought, but few having beneficial effects on quality and yield. Nonetheless, controlled water deficit may improve fruit quality through higher concentration of flavor compounds. The underlying genetic determinants are still poorly known. In this study, we phenotyped 141 highly diverse small fruit tomato accessions for 27 traits under two contrasting watering conditions. A subset of 55 accessions exhibited increased metabolite contents and maintained yield under water deficit. Using 6100 single nucleotide polymorphisms (SNPs), association mapping revealed 31, 41, and 44 quantitative trait loci (QTLs) under drought, control, and both conditions, respectively. Twenty-five additional QTLs were interactive between conditions, emphasizing the interest in accounting for QTLs by watering regime interactions in fruit quality improvement. Combining our results with the loci previously identified in a biparental progeny resulted in 11 common QTLs and contributed to a first detailed characterization of the genetic determinants of response to water deficit in tomato. Major QTLs for fruit quality traits were dissected and candidate genes were proposed using expression and polymorphism data. The outcomes provide a basis for fruit quality improvement under deficit irrigation while limiting yield losses. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.
He, Jin; Jin, Yi; Du, Yan-Lei; Wang, Tao; Turner, Neil C.; Yang, Ru-Ping; Siddique, Kadambot H. M.; Li, Feng-Min
2017-01-01
Water shortage and low phosphorus (P) availability limit yields in soybean. Roots play important roles in water-limited and P-deficient environment, but the underlying mechanisms are largely unknown. In this study we determined the responses of four soybean [Glycine max (L.) Merr.] genotypes [Huandsedadou (HD), Bailudou (BLD), Jindou 21 (J21), and Zhonghuang 30 (ZH)] to three P levels [applied 0 (P0), 60 (P60), and 120 (P120) mg P kg-1 dry soil to the upper 0.4 m of the soil profile] and two water treatment [well-watered (WW) and water-stressed (WS)] with special reference to root morphology and architecture, we compared yield and its components, root morphology and root architecture to find out which variety and/or what kind of root architecture had high grain yield under P and drought stress. The results showed that water stress and low P, respectively, significantly reduced grain yield by 60 and 40%, daily water use by 66 and 31%, P accumulation by 40 and 80%, and N accumulation by 39 and 65%. The cultivar ZH with the lowest daily water use had the highest grain yield at P60 and P120 under drought. Increased root length was positively associated with N and P accumulation in both the WW and WS treatments, but not with grain yield under water and P deficits. However, in the WS treatment, high adventitious and lateral root densities were associated with high N and P uptake per unit root length which in turn was significantly and positively associated with grain yield. Our results suggest that (1) genetic variation of grain yield, daily water use, P and N accumulation, and root morphology and architecture were observed among the soybean cultivars and ZH had the best yield performance under P and water limited conditions; (2) water has a major influence on nutrient uptake and grain yield, while additional P supply can modestly increase yields under drought in some soybean genotypes; (3) while conserved water use plays an important role in grain yield under drought, root traits also contribute to high nutrient uptake efficiency and benefit yield under drought. PMID:28912792
This funding opportunity announcement (FOA) encourages applications that propose to conduct secondary data analysis and integration of existing datasets and database resources, with the ultimate aim to elucidate the genetic architecture of cancer risk and related outcomes. The goal of this initiative is to address key scientific questions relevant to cancer epidemiology by supporting the analysis of existing genetic or genomic datasets, possibly in combination with environmental, outcomes, behavioral, lifestyle, and molecular profiles data.
This funding opportunity announcement (FOA) encourages applications that propose to conduct secondary data analysis and integration of existing datasets and database resources, with the ultimate aim to elucidate the genetic architecture of cancer risk and related outcomes. The goal of this initiative is to address key scientific questions relevant to cancer epidemiology by supporting the analysis of existing genetic or genomic datasets, possibly in combination with environmental, outcomes, behavioral, lifestyle, and molecular profiles data.
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.
Prince, Silvas J; Valliyodan, Babu; Ye, Heng; Yang, Ming; Tai, Shuaishuai; Hu, Wushu; Murphy, Mackensie; Durnell, Lorellin A; Song, Li; Joshi, Trupti; Liu, Yang; Van de Velde, Jan; Vandepoele, Klaas; Grover Shannon, J; Nguyen, Henry T
2018-05-10
Developing crops with better root systems is a promising strategy to ensure productivity in both optimum and stress environments. Root system architectural (RSA) traits in 397 soybean accessions were characterized and a high-density single nucleotide polymorphisms (SNP) based genome-wide association study was performed to identify the underlying genes associated with root structure. SNPs associated with root architectural traits specific to landraces and elite germplasm pools were detected. Four loci were detected in landraces for lateral root number (LRN) and distribution of root thickness in diameter class I with a major locus on chromosome 16. This major loci was detected in the coding region of unknown protein, and subsequent analyses demonstrated that root traits are affected with mutated haplotypes of the gene. In elite germplasm pool, three significant SNPs in alanine-glyoxalate aminotransferase, Leucine-Rich Repeat receptor/No apical meristem and unknown functional genes were found to govern multiple traits including root surface area and volume. However, no major loci were detected for LRN in elite germplasm. Nucleotide diversity analysis found evidence of selective sweeps around the landraces LRN gene. Soybean accessions with minor and mutated allelic variants of LRN gene were found to perform better in both water-limited and optimal field conditions. This article is protected by copyright. All rights reserved.
Xu, Ke; Schadt, Eric E.; Pollard, Katherine S.; Roussos, Panos; Dudley, Joel T.
2015-01-01
The population persistence of schizophrenia despite associated reductions in fitness and fecundity suggests that the genetic basis of schizophrenia has a complex evolutionary history. A recent meta-analysis of schizophrenia genome-wide association studies offers novel opportunities for assessment of the evolutionary trajectories of schizophrenia-associated loci. In this study, we hypothesize that components of the genetic architecture of schizophrenia are attributable to human lineage-specific evolution. Our results suggest that schizophrenia-associated loci enrich in genes near previously identified human accelerated regions (HARs). Specifically, we find that genes near HARs conserved in nonhuman primates (pHARs) are enriched for schizophrenia-associated loci, and that pHAR-associated schizophrenia genes are under stronger selective pressure than other schizophrenia genes and other pHAR-associated genes. We further evaluate pHAR-associated schizophrenia genes in regulatory network contexts to investigate associated molecular functions and mechanisms. We find that pHAR-associated schizophrenia genes significantly enrich in a GABA-related coexpression module that was previously found to be differentially regulated in schizophrenia affected individuals versus healthy controls. In another two independent networks constructed from gene expression profiles from prefrontal cortex samples, we find that pHAR-associated schizophrenia genes are located in more central positions and their average path lengths to the other nodes are significantly shorter than those of other schizophrenia genes. Together, our results suggest that HARs are associated with potentially important functional roles in the genetic architecture of schizophrenia. PMID:25681384
An Evolutionary Perspective on Epistasis and the Missing Heritability
Hemani, Gibran; Knott, Sara; Haley, Chris
2013-01-01
The relative importance between additive and non-additive genetic variance has been widely argued in quantitative genetics. By approaching this question from an evolutionary perspective we show that, while additive variance can be maintained under selection at a low level for some patterns of epistasis, the majority of the genetic variance that will persist is actually non-additive. We propose that one reason that the problem of the “missing heritability” arises is because the additive genetic variation that is estimated to be contributing to the variance of a trait will most likely be an artefact of the non-additive variance that can be maintained over evolutionary time. In addition, it can be shown that even a small reduction in linkage disequilibrium between causal variants and observed SNPs rapidly erodes estimates of epistatic variance, leading to an inflation in the perceived importance of additive effects. We demonstrate that the perception of independent additive effects comprising the majority of the genetic architecture of complex traits is biased upwards and that the search for causal variants in complex traits under selection is potentially underpowered by parameterising for additive effects alone. Given dense SNP panels the detection of causal variants through genome-wide association studies may be improved by searching for epistatic effects explicitly. PMID:23509438
Baillie, J Kenneth; Bretherick, Andrew; Haley, Christopher S; Clohisey, Sara; Gray, Alan; Neyton, Lucile P A; Barrett, Jeffrey; Stahl, Eli A; Tenesa, Albert; Andersson, Robin; Brown, J Ben; Faulkner, Geoffrey J; Lizio, Marina; Schaefer, Ulf; Daub, Carsten; Itoh, Masayoshi; Kondo, Naoto; Lassmann, Timo; Kawai, Jun; Mole, Damian; Bajic, Vladimir B; Heutink, Peter; Rehli, Michael; Kawaji, Hideya; Sandelin, Albin; Suzuki, Harukazu; Satsangi, Jack; Wells, Christine A; Hacohen, Nir; Freeman, Thomas C; Hayashizaki, Yoshihide; Carninci, Piero; Forrest, Alistair R R; Hume, David A
2018-03-01
Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn's disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits.
Gray, Alan; Neyton, Lucile P. A.; Barrett, Jeffrey; Stahl, Eli A.; Tenesa, Albert; Andersson, Robin; Brown, J. Ben; Faulkner, Geoffrey J.; Lizio, Marina; Schaefer, Ulf; Daub, Carsten; Kondo, Naoto; Lassmann, Timo; Kawai, Jun; Kawaji, Hideya; Suzuki, Harukazu; Satsangi, Jack; Wells, Christine A.; Hacohen, Nir; Freeman, Thomas C.; Hayashizaki, Yoshihide; Forrest, Alistair R. R.; Hume, David A.
2018-01-01
Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn’s disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits. PMID:29494619
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
Survey of the Heritability and Sparse Architecture of Gene Expression Traits across Human Tissues.
Wheeler, Heather E; Shah, Kaanan P; Brenner, Jonathon; Garcia, Tzintzuni; Aquino-Michaels, Keston; Cox, Nancy J; Nicolae, Dan L; Im, Hae Kyung
2016-11-01
Understanding the genetic architecture of gene expression traits is key to elucidating the underlying mechanisms of complex traits. Here, for the first time, we perform a systematic survey of the heritability and the distribution of effect sizes across all representative tissues in the human body. We find that local h2 can be relatively well characterized with 59% of expressed genes showing significant h2 (FDR < 0.1) in the DGN whole blood cohort. However, current sample sizes (n ≤ 922) do not allow us to compute distal h2. Bayesian Sparse Linear Mixed Model (BSLMM) analysis provides strong evidence that the genetic contribution to local expression traits is dominated by a handful of genetic variants rather than by the collective contribution of a large number of variants each of modest size. In other words, the local architecture of gene expression traits is sparse rather than polygenic across all 40 tissues (from DGN and GTEx) examined. This result is confirmed by the sparsity of optimal performing gene expression predictors via elastic net modeling. To further explore the tissue context specificity, we decompose the expression traits into cross-tissue and tissue-specific components using a novel Orthogonal Tissue Decomposition (OTD) approach. Through a series of simulations we show that the cross-tissue and tissue-specific components are identifiable via OTD. Heritability and sparsity estimates of these derived expression phenotypes show similar characteristics to the original traits. Consistent properties relative to prior GTEx multi-tissue analysis results suggest that these traits reflect the expected biology. Finally, we apply this knowledge to develop prediction models of gene expression traits for all tissues. The prediction models, heritability, and prediction performance R2 for original and decomposed expression phenotypes are made publicly available (https://github.com/hakyimlab/PrediXcan).
Johnston, Susan E.; Bérénos, Camillo; Slate, Jon; Pemberton, Josephine M.
2016-01-01
Meiotic recombination breaks down linkage disequilibrium (LD) and forms new haplotypes, meaning that it is an important driver of diversity in eukaryotic genomes. Understanding the causes of variation in recombination rate is important in interpreting and predicting evolutionary phenomena and in understanding the potential of a population to respond to selection. However, despite attention in model systems, there remains little data on how recombination rate varies at the individual level in natural populations. Here we used extensive pedigree and high-density SNP information in a wild population of Soay sheep (Ovis aries) to investigate the genetic architecture of individual autosomal recombination rates. Individual rates were high relative to other mammal systems and were higher in males than in females (autosomal map lengths of 3748 and 2860 cM, respectively). The heritability of autosomal recombination rate was low but significant in both sexes (h2 = 0.16 and 0.12 in females and males, respectively). In females, 46.7% of the heritable variation was explained by a subtelomeric region on chromosome 6; a genome-wide association study showed the strongest associations at locus RNF212, with further associations observed at a nearby ∼374-kb region of complete LD containing three additional candidate loci, CPLX1, GAK, and PCGF3. A second region on chromosome 7 containing REC8 and RNF212B explained 26.2% of the heritable variation in recombination rate in both sexes. Comparative analyses with 40 other sheep breeds showed that haplotypes associated with recombination rates are both old and globally distributed. Both regions have been implicated in rate variation in mice, cattle, and humans, suggesting a common genetic architecture of recombination rate variation in mammals. PMID:27029733
Desgroux, Aurore; Baudais, Valentin N; Aubert, Véronique; Le Roy, Gwenola; de Larambergue, Henri; Miteul, Henri; Aubert, Grégoire; Boutet, Gilles; Duc, Gérard; Baranger, Alain; Burstin, Judith; Manzanares-Dauleux, Maria; Pilet-Nayel, Marie-Laure; Bourion, Virginie
2017-01-01
Combining plant genetic resistance with architectural traits that are unfavorable to disease development is a promising strategy for reducing epidemics. However, few studies have identified root system architecture (RSA) traits with the potential to limit root disease development. Pea is a major cultivated legume worldwide and has a wide level of natural genetic variability for plant architecture. The root pathogen Aphanomyces euteiches is a major limiting factor of pea crop yield. This study aimed to increase the knowledge on the diversity of loci and candidate genes controlling RSA traits in pea and identify RSA genetic loci associated with resistance to A. euteiches which could be combined with resistance QTL in breeding. A comparative genome wide association (GWA) study of plant architecture and resistance to A. euteiches was conducted at the young plant stage in a collection of 266 pea lines contrasted for both traits. The collection was genotyped using 14,157 SNP markers from recent pea genomic resources. It was phenotyped for ten root, shoot and overall plant architecture traits, as well as three disease resistance traits in controlled conditions, using image analysis. We identified a total of 75 short-size genomic intervals significantly associated with plant architecture and overlapping with 46 previously detected QTL. The major consistent intervals included plant shoot architecture or flowering genes ( PsLE, PsTFL1 ) with putative pleiotropic effects on root architecture. A total of 11 genomic intervals were significantly associated with resistance to A. euteiches confirming several consistent previously identified major QTL. One significant SNP, mapped to the major QTL Ae-Ps7.6 , was associated with both resistance and RSA traits. At this marker, the resistance-enhancing allele was associated with an increased total root projected area, in accordance with the correlation observed between resistance and larger root systems in the collection. Seven additional intervals associated with plant architecture overlapped with GWA intervals previously identified for resistance to A. euteiches . This study provides innovative results about genetic interdependency of root disease resistance and RSA inheritance. It identifies pea lines, QTL, closely-linked markers and candidate genes for marker-assisted-selection of RSA loci to reduce Aphanomyces root rot severity in future pea varieties.
Desgroux, Aurore; Baudais, Valentin N.; Aubert, Véronique; Le Roy, Gwenola; de Larambergue, Henri; Miteul, Henri; Aubert, Grégoire; Boutet, Gilles; Duc, Gérard; Baranger, Alain; Burstin, Judith; Manzanares-Dauleux, Maria; Pilet-Nayel, Marie-Laure; Bourion, Virginie
2018-01-01
Combining plant genetic resistance with architectural traits that are unfavorable to disease development is a promising strategy for reducing epidemics. However, few studies have identified root system architecture (RSA) traits with the potential to limit root disease development. Pea is a major cultivated legume worldwide and has a wide level of natural genetic variability for plant architecture. The root pathogen Aphanomyces euteiches is a major limiting factor of pea crop yield. This study aimed to increase the knowledge on the diversity of loci and candidate genes controlling RSA traits in pea and identify RSA genetic loci associated with resistance to A. euteiches which could be combined with resistance QTL in breeding. A comparative genome wide association (GWA) study of plant architecture and resistance to A. euteiches was conducted at the young plant stage in a collection of 266 pea lines contrasted for both traits. The collection was genotyped using 14,157 SNP markers from recent pea genomic resources. It was phenotyped for ten root, shoot and overall plant architecture traits, as well as three disease resistance traits in controlled conditions, using image analysis. We identified a total of 75 short-size genomic intervals significantly associated with plant architecture and overlapping with 46 previously detected QTL. The major consistent intervals included plant shoot architecture or flowering genes (PsLE, PsTFL1) with putative pleiotropic effects on root architecture. A total of 11 genomic intervals were significantly associated with resistance to A. euteiches confirming several consistent previously identified major QTL. One significant SNP, mapped to the major QTL Ae-Ps7.6, was associated with both resistance and RSA traits. At this marker, the resistance-enhancing allele was associated with an increased total root projected area, in accordance with the correlation observed between resistance and larger root systems in the collection. Seven additional intervals associated with plant architecture overlapped with GWA intervals previously identified for resistance to A. euteiches. This study provides innovative results about genetic interdependency of root disease resistance and RSA inheritance. It identifies pea lines, QTL, closely-linked markers and candidate genes for marker-assisted-selection of RSA loci to reduce Aphanomyces root rot severity in future pea varieties. PMID:29354146
Maternal environment affects the genetic basis of seed dormancy in Arabidopsis thaliana.
Postma, Froukje M; Ågren, Jon
2015-02-01
The genetic basis of seed dormancy, a key life history trait important for adaptive evolution in plant populations, has yet been studied only using seeds produced under controlled conditions in greenhouse environments. However, dormancy is strongly affected by maternal environmental conditions, and interactions between seed genotype and maternal environment have been reported. Consequently, the genetic basis of dormancy of seeds produced under natural field conditions remains unclear. We examined the effect of maternal environment on the genetic architecture of seed dormancy using a recombinant inbred line (RIL) population derived from a cross between two locally adapted populations of Arabidopsis thaliana from Italy and Sweden. We mapped quantitative trait loci (QTL) for dormancy of seeds produced in the greenhouse and at the native field sites of the parental genotypes. The Italian genotype produced seeds with stronger dormancy at fruit maturation than did the Swedish genotype in all three environments, and the maternal field environments induced higher dormancy levels compared to the greenhouse environment in both genotypes. Across the three maternal environments, a total of nine dormancy QTL were detected, three of which were only detected among seeds matured in the field, and six of which showed significant QTL × maternal environment interactions. One QTL had a large effect on dormancy across all three environments and colocalized with the candidate gene DOG1. Our results demonstrate the importance of studying the genetic basis of putatively adaptive traits under relevant conditions. © 2015 John Wiley & Sons Ltd.
The evolution of phenotypes and genetic parameters under preferential mating
Roff, Derek A; Fairbairn, Daphne J
2014-01-01
This article extends and adds more realism to Lande's analytical model for evolution under mate choice by using individual-based simulations in which females sample a finite number of males and the genetic architecture of the preference and preferred trait evolves. The simulations show that the equilibrium heritabilities of the preference and preferred trait and the genetic correlation between them (rG), depend critically on aspects of the mating system (the preference function, mode of mate choice, choosiness, and number of potential mates sampled), the presence or absence of natural selection on the preferred trait, and the initial genetic parameters. Under some parameter combinations, preferential mating increased the heritability of the preferred trait, providing a possible resolution for the lek paradox. The Kirkpatrick–Barton approximation for rG proved to be biased downward, but the realized genetic correlations were also low, generally <0.2. Such low values of rG indicate that coevolution of the preference and preferred trait is likely to be very slow and subject to significant stochastic variation. Lande's model accurately predicted the incidence of runaway selection in the simulations, except where preferences were relative and the preferred trait was subject to natural selection. In these cases, runaways were over- or underestimated, depending on the number of males sampled. We conclude that rapid coevolution of preferences and preferred traits is unlikely in natural populations, but that the parameter combinations most conducive to it are most likely to occur in lekking species. PMID:25077025
Advanced nanoelectronic architectures for THz-based biological agent detection
NASA Astrophysics Data System (ADS)
Woolard, Dwight L.; Jensen, James O.
2009-02-01
The U.S. Army Research Office (ARO) and the U.S. Army Edgewood Chemical Biological Center (ECBC) jointly lead and support novel research programs that are advancing the state-of-the-art in nanoelectronic engineering in application areas that have relevance to national defense and security. One fundamental research area that is presently being emphasized by ARO and ECBC is the exploratory investigation of new bio-molecular architectural concepts that can be used to achieve rapid, reagent-less detection and discrimination of biological warfare (BW) agents, through the control of multi-photon and multi-wavelength processes at the nanoscale. This paper will overview an ARO/ECBC led multidisciplinary research program presently under the support of the U.S. Defense Threat Reduction Agency (DTRA) that seeks to develop new devices and nanoelectronic architectures that are effective for extracting THz signatures from target bio-molecules. Here, emphasis will be placed on the new nanosensor concepts and THz/Optical measurement methodologies for spectral-based sequencing/identification of genetic molecules.
Sanjak, Jaleal S.; Long, Anthony D.; Thornton, Kevin R.
2017-01-01
The genetic component of complex disease risk in humans remains largely unexplained. A corollary is that the allelic spectrum of genetic variants contributing to complex disease risk is unknown. Theoretical models that relate population genetic processes to the maintenance of genetic variation for quantitative traits may suggest profitable avenues for future experimental design. Here we use forward simulation to model a genomic region evolving under a balance between recurrent deleterious mutation and Gaussian stabilizing selection. We consider multiple genetic and demographic models, and several different methods for identifying genomic regions harboring variants associated with complex disease risk. We demonstrate that the model of gene action, relating genotype to phenotype, has a qualitative effect on several relevant aspects of the population genetic architecture of a complex trait. In particular, the genetic model impacts genetic variance component partitioning across the allele frequency spectrum and the power of statistical tests. Models with partial recessivity closely match the minor allele frequency distribution of significant hits from empirical genome-wide association studies without requiring homozygous effect sizes to be small. We highlight a particular gene-based model of incomplete recessivity that is appealing from first principles. Under that model, deleterious mutations in a genomic region partially fail to complement one another. This model of gene-based recessivity predicts the empirically observed inconsistency between twin and SNP based estimated of dominance heritability. Furthermore, this model predicts considerable levels of unexplained variance associated with intralocus epistasis. Our results suggest a need for improved statistical tools for region based genetic association and heritability estimation. PMID:28103232
Uemoto, Yoshinobu; Sasaki, Shinji; Kojima, Takatoshi; Sugimoto, Yoshikazu; Watanabe, Toshio
2015-11-19
Genetic variance that is not captured by single nucleotide polymorphisms (SNPs) is due to imperfect linkage disequilibrium (LD) between SNPs and quantitative trait loci (QTLs), and the extent of LD between SNPs and QTLs depends on different minor allele frequencies (MAF) between them. To evaluate the impact of MAF of QTLs on genomic evaluation, we performed a simulation study using real cattle genotype data. In total, 1368 Japanese Black cattle and 592,034 SNPs (Illumina BovineHD BeadChip) were used. We simulated phenotypes using real genotypes under different scenarios, varying the MAF categories, QTL heritability, number of QTLs, and distribution of QTL effect. After generating true breeding values and phenotypes, QTL heritability was estimated and the prediction accuracy of genomic estimated breeding value (GEBV) was assessed under different SNP densities, prediction models, and population size by a reference-test validation design. The extent of LD between SNPs and QTLs in this population was higher in the QTLs with high MAF than in those with low MAF. The effect of MAF of QTLs depended on the genetic architecture, evaluation strategy, and population size in genomic evaluation. In genetic architecture, genomic evaluation was affected by the MAF of QTLs combined with the QTL heritability and the distribution of QTL effect. The number of QTL was not affected on genomic evaluation if the number of QTL was more than 50. In the evaluation strategy, we showed that different SNP densities and prediction models affect the heritability estimation and genomic prediction and that this depends on the MAF of QTLs. In addition, accurate QTL heritability and GEBV were obtained using denser SNP information and the prediction model accounted for the SNPs with low and high MAFs. In population size, a large sample size is needed to increase the accuracy of GEBV. The MAF of QTL had an impact on heritability estimation and prediction accuracy. Most genetic variance can be captured using denser SNPs and the prediction model accounted for MAF, but a large sample size is needed to increase the accuracy of GEBV under all QTL MAF categories.
Pakkasmaa, S; Merilä, J; O'Hara, R B
2003-08-01
The influence of environmental stress on the expression of genetic and maternal effects on the viability traits has seldom been assessed in wild vertebrates. We have estimated genetic and maternal effects on the viability (viz probability of survival, probability of being deformed, and body size and shape) of common frog, Rana temporaria, tadpoles under stressful (low pH) and nonstressful (neutral pH) environmental conditions. A Bayesian analysis using generalized linear mixed models was applied to data from a factorial laboratory experiment. The expression of additive genetic variance was independent of pH treatments, and all traits were significantly heritable (survival: h2 approximately 0.08; deformities: h2 approximately 0.26; body size: h2 approximately 0.12; body shape: h2 approximately 0.14). Likewise, nonadditive genetic contributions to variation in all traits were significant, independent of pH treatments and typically of magnitude similar to the additive genetic effects. Maternal effects were large for all traits, especially for viability itself, and their expression was partly dependent on the environment. In the case of body size, the maternal effects were mediated largely through egg size. In general, the results give little evidence for the conjecture that environmental stress created by low pH would impact strongly on the genetic architecture of fitness-related traits in frogs, and hamper adaptation to stress caused by acidification. The low heritabilities and high dominance contributions conform to the pattern typical for traits subject to relatively strong directional selection.
Heritability of female extra-pair paternity rate in song sparrows (Melospiza melodia)
Reid, Jane M.; Arcese, Peter; Sardell, Rebecca J.; Keller, Lukas F.
2011-01-01
The forces driving the evolution of extra-pair reproduction in socially monogamous animals remain widely debated and unresolved. One key hypothesis is that female extra-pair reproduction evolves through indirect genetic benefits, reflecting increased additive genetic value of extra-pair offspring. Such evolution requires that a female's propensity to produce offspring that are sired by an extra-pair male is heritable. However, additive genetic variance and heritability in female extra-pair paternity (EPP) rate have not been quantified, precluding accurate estimation of the force of indirect selection. Sixteen years of comprehensive paternity and pedigree data from socially monogamous but genetically polygynandrous song sparrows (Melospiza melodia) showed significant additive genetic variance and heritability in the proportion of a female's offspring that was sired by an extra-pair male, constituting major components of the genetic architecture required for extra-pair reproduction to evolve through indirect additive genetic benefits. However, estimated heritabilities were moderately small (0.12 and 0.18 on the observed and underlying latent scales, respectively). The force of selection on extra-pair reproduction through indirect additive genetic benefits may consequently be relatively weak. However, the additive genetic variance and non-zero heritability observed in female EPP rate allow for multiple further genetic mechanisms to drive and constrain mating system evolution. PMID:20980302
How the Timing and Quality of Early Experiences Influence the Development of Brain Architecture
Fox, Sharon E.; Levitt, Pat; Nelson, Charles A.
2009-01-01
Early life events can exert a powerful influence on both the pattern of brain architecture and behavioral development. In this paper a conceptual framework is provided for considering how the structure of early experience gets “under the skin.” The paper begins with a description of the genetic framework that lays the foundation for brain development, and then to the ways experience interacts with and modifies the structures and functions of the developing brain. Much of the attention is focused on early experience and sensitive periods, although it is made clear that later experience also plays an important role in maintaining and elaborating this early wiring diagram, which is critical to establishing a solid footing for development beyond the early years. PMID:20331653
Edwards, Christine E; Ewers, Brent E; Weinig, Cynthia
2016-08-24
Plant performance in agricultural and natural settings varies with moisture availability, and understanding the range of potential drought responses and the underlying genetic architecture is important for understanding how plants will respond to both natural and artificial selection in various water regimes. Here, we raised genotypes of Brassica rapa under well-watered and drought treatments in the field. Our primary goal was to understand the genetic architecture and yield effects of different drought-escape and dehydration-avoidance strategies. Drought treatments reduced soil moisture by 62 % of field capacity. Drought decreased biomass accumulation and fruit production by as much as 48 %, whereas instantaneous water-use efficiency and root:shoot ratio increased. Genotypes differed in the mean value of all traits and in the sensitivity of biomass accumulation, root:shoot ratio, and fruit production to drought. Bivariate correlations involving gas-exchange and phenology were largely constant across environments, whereas those involving root:shoot varied across treatments. Although root:shoot was typically unrelated to gas-exchange or yield under well-watered conditions, genotypes with low to moderate increases in root:shoot allocation in response to drought survived the growing season, maintained maximum photosynthesis levels, and produced more fruit than genotypes with the greatest root allocation under drought. QTL for gas-exchange and yield components (total biomass or fruit production) had common effects across environments while those for root:shoot were often environment-specific. Increases in root allocation beyond those needed to survive and maintain favorable water relations came at the cost of fruit production. The environment-specific effects of root:shoot ratio on yield and the differential expression of QTL for this trait across water regimes have important implications for efforts to improve crops for drought resistance.
Moore, Jason H; Amos, Ryan; Kiralis, Jeff; Andrews, Peter C
2015-01-01
Simulation plays an essential role in the development of new computational and statistical methods for the genetic analysis of complex traits. Most simulations start with a statistical model using methods such as linear or logistic regression that specify the relationship between genotype and phenotype. This is appealing due to its simplicity and because these statistical methods are commonly used in genetic analysis. It is our working hypothesis that simulations need to move beyond simple statistical models to more realistically represent the biological complexity of genetic architecture. The goal of the present study was to develop a prototype genotype–phenotype simulation method and software that are capable of simulating complex genetic effects within the context of a hierarchical biology-based framework. Specifically, our goal is to simulate multilocus epistasis or gene–gene interaction where the genetic variants are organized within the framework of one or more genes, their regulatory regions and other regulatory loci. We introduce here the Heuristic Identification of Biological Architectures for simulating Complex Hierarchical Interactions (HIBACHI) method and prototype software for simulating data in this manner. This approach combines a biological hierarchy, a flexible mathematical framework, a liability threshold model for defining disease endpoints, and a heuristic search strategy for identifying high-order epistatic models of disease susceptibility. We provide several simulation examples using genetic models exhibiting independent main effects and three-way epistatic effects. PMID:25395175
Adib-Samii, Poneh; Devan, William; Traylor, Matthew; Lanfranconi, Silvia; Zhang, Cathy R; Cloonan, Lisa; Falcone, Guido J; Radmanesh, Farid; Fitzpatrick, Kaitlin; Kanakis, Allison; Rothwell, Peter M; Sudlow, Cathie; Boncoraglio, Giorgio B; Meschia, James F; Levi, Chris; Dichgans, Martin; Bevan, Steve; Rosand, Jonathan; Rost, Natalia S; Markus, Hugh S
2015-02-01
Epidemiological studies suggest that white matter hyperintensities (WMH) are extremely heritable, but the underlying genetic variants are largely unknown. Pathophysiological heterogeneity is known to reduce the power of genome-wide association studies (GWAS). Hypertensive and nonhypertensive individuals with WMH might have different underlying pathologies. We used GWAS data to calculate the variance in WMH volume (WMHV) explained by common single nucleotide polymorphisms (SNPs) as a measure of heritability (SNP heritability [HSNP]) and tested the hypothesis that WMH heritability differs between hypertensive and nonhypertensive individuals. WMHV was measured on MRI in the stroke-free cerebral hemisphere of 2336 ischemic stroke cases with GWAS data. After adjustment for age and intracranial volume, we determined which cardiovascular risk factors were independent predictors of WMHV. Using the genome-wide complex trait analysis tool to estimate HSNP for WMHV overall and within subgroups stratified by risk factors found to be significant in multivariate analyses. A significant proportion of the variance of WMHV was attributable to common SNPs after adjustment for significant risk factors (HSNP=0.23; P=0.0026). HSNP estimates were higher among hypertensive individuals (HSNP=0.45; P=7.99×10(-5)); this increase was greater than expected by chance (P=0.012). In contrast, estimates were lower, and nonsignificant, in nonhypertensive individuals (HSNP=0.13; P=0.13). A quarter of variance is attributable to common SNPs, but this estimate was greater in hypertensive individuals. These findings suggest that the genetic architecture of WMH in ischemic stroke differs between hypertensives and nonhypertensives. Future WMHV GWAS studies may gain power by accounting for this interaction. © 2014 The Authors. Published on behalf of the American Heart Association, Inc., by Wolters Kluwer.
Mehrban, Hossein; Lee, Deuk Hwan; Moradi, Mohammad Hossein; IlCho, Chung; Naserkheil, Masoumeh; Ibáñez-Escriche, Noelia
2017-01-04
Hanwoo beef is known for its marbled fat, tenderness, juiciness and characteristic flavor, as well as for its low cholesterol and high omega 3 fatty acid contents. As yet, there has been no comprehensive investigation to estimate genomic selection accuracy for carcass traits in Hanwoo cattle using dense markers. This study aimed at evaluating the accuracy of alternative statistical methods that differed in assumptions about the underlying genetic model for various carcass traits: backfat thickness (BT), carcass weight (CW), eye muscle area (EMA), and marbling score (MS). Accuracies of direct genomic breeding values (DGV) for carcass traits were estimated by applying fivefold cross-validation to a dataset including 1183 animals and approximately 34,000 single nucleotide polymorphisms (SNPs). Accuracies of BayesC, Bayesian LASSO (BayesL) and genomic best linear unbiased prediction (GBLUP) methods were similar for BT, EMA and MS. However, for CW, DGV accuracy was 7% higher with BayesC than with BayesL and GBLUP. The increased accuracy of BayesC, compared to GBLUP and BayesL, was maintained for CW, regardless of the training sample size, but not for BT, EMA, and MS. Genome-wide association studies detected consistent large effects for SNPs on chromosomes 6 and 14 for CW. The predictive performance of the models depended on the trait analyzed. For CW, the results showed a clear superiority of BayesC compared to GBLUP and BayesL. These findings indicate the importance of using a proper variable selection method for genomic selection of traits and also suggest that the genetic architecture that underlies CW differs from that of the other carcass traits analyzed. Thus, our study provides significant new insights into the carcass traits of Hanwoo cattle.
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...
Epistasis and Its Implications for Personal Genetics
Moore, Jason H.; Williams, Scott M.
2009-01-01
The widespread availability of high-throughput genotyping technology has opened the door to the era of personal genetics, which brings to consumers the promise of using genetic variations to predict individual susceptibility to common diseases. Despite easy access to commercial personal genetics services, our knowledge of the genetic architecture of common diseases is still very limited and has not yet fulfilled the promise of accurately predicting most people at risk. This is partly because of the complexity of the mapping relationship between genotype and phenotype that is a consequence of epistasis (gene-gene interaction) and other phenomena such as gene-environment interaction and locus heterogeneity. Unfortunately, these aspects of genetic architecture have not been addressed in most of the genetic association studies that provide the knowledge base for interpreting large-scale genetic association results. We provide here an introductory review of how epistasis can affect human health and disease and how it can be detected in population-based studies. We provide some thoughts on the implications of epistasis for personal genetics and some recommendations for improving personal genetics in light of this complexity. PMID:19733727
Epistasis and its implications for personal genetics.
Moore, Jason H; Williams, Scott M
2009-09-01
The widespread availability of high-throughput genotyping technology has opened the door to the era of personal genetics, which brings to consumers the promise of using genetic variations to predict individual susceptibility to common diseases. Despite easy access to commercial personal genetics services, our knowledge of the genetic architecture of common diseases is still very limited and has not yet fulfilled the promise of accurately predicting most people at risk. This is partly because of the complexity of the mapping relationship between genotype and phenotype that is a consequence of epistasis (gene-gene interaction) and other phenomena such as gene-environment interaction and locus heterogeneity. Unfortunately, these aspects of genetic architecture have not been addressed in most of the genetic association studies that provide the knowledge base for interpreting large-scale genetic association results. We provide here an introductory review of how epistasis can affect human health and disease and how it can be detected in population-based studies. We provide some thoughts on the implications of epistasis for personal genetics and some recommendations for improving personal genetics in light of this complexity.
Robinson, Elise B.; Kirby, Andrew; Ruparel, Kosha; Yang, Jian; McGrath, Lauren; Anttila, Verneri; Neale, Benjamin M.; Merikangas, Kathleen; Lehner, Thomas; Sleiman, Patrick M.A.; Daly, Mark J.; Gur, Ruben; Gur, Raquel; Hakonarson, Hakon
2014-01-01
The objective of this analysis was to examine the genetic architecture of diverse cognitive abilities in children and adolescents, including the magnitude of common genetic effects and patterns of shared and unique genetic influences. Subjects included 3,689 members of the Philadelphia Neurodevelopmental Cohort, a general population sample of ages 8-21 years who completed an extensive battery of cognitive tests. We used genome-wide complex trait analysis (GCTA) to estimate the SNP-based heritability of each domain, as well as the genetic correlation between all domains that showed significant genetic influence. Several of the individual domains suggested strong influence of common genetic variants (e.g. reading ability, h2g=0.43, p=4e-06; emotion identification, h2g=0.36, p=1e-05; verbal memory, h2g=0.24, p=0.005). The genetic correlations highlighted trait domains that are candidates for joint interrogation in future genetic studies (e.g. language reasoning and spatial reasoning, r(g)=0.72, p=0.007). These results can be used to structure future genetic and neuropsychiatric investigations of diverse cognitive abilities. PMID:25023143
USDA-ARS?s Scientific Manuscript database
Modification in plant architecture have been demonstrated as one of the major contributing factors that ushered in the Green Revolution resulting in achieving dramatic increases in grain yield for wheat and rice. For sorghum (Sorghum bicolor L. Moench.), possible alteration in plant architecture is ...
The Genetic Architecture of Barley Plant Stature
Alqudah, Ahmad M.; Koppolu, Ravi; Wolde, Gizaw M.; Graner, Andreas; Schnurbusch, Thorsten
2016-01-01
Plant stature in temperate cereals is predominantly controlled by tillering and plant height as complex agronomic traits, representing important determinants of grain yield. This study was designed to reveal the genetic basis of tillering at five developmental stages and plant height at harvest in 218 worldwide spring barley (Hordeum vulgare L.) accessions under greenhouse conditions. The accessions were structured based on row-type classes [two- vs. six-rowed] and photoperiod response [photoperiod-sensitive (Ppd-H1) vs. reduced photoperiod sensitivity (ppd-H1)]. Phenotypic analyses of both factors revealed profound between group effects on tiller development. To further verify the row-type effect on the studied traits, Six-rowed spike 1 (vrs1) mutants and their two-rowed progenitors were examined for tiller number per plant and plant height. Here, wild-type (Vrs1) plants were significantly taller and had more tillers than mutants suggesting a negative pleiotropic effect of this row-type locus on both traits. Our genome-wide association scans further revealed highly significant associations, thereby establishing a link between the genetic control of row-type, heading time, tillering, and plant height. We further show that associations for tillering and plant height are co-localized with chromosomal segments harboring known plant stature-related phytohormone and sugar-related genes. This work demonstrates the feasibility of the GWAS approach for identifying putative candidate genes for improving plant architecture. PMID:27446200
Ryan, Niamh M; Lihm, Jayon; Kramer, Melissa; McCarthy, Shane; Morris, Stewart W; Arnau-Soler, Aleix; Davies, Gail; Duff, Barbara; Ghiban, Elena; Hayward, Caroline; Deary, Ian J; Blackwood, Douglas H R; Lawrie, Stephen M; McIntosh, Andrew M; Evans, Kathryn L; Porteous, David J; McCombie, W Richard; Thomson, Pippa A
2018-06-07
Psychiatric disorders are a group of genetically related diseases with highly polygenic architectures. Genome-wide association analyses have made substantial progress towards understanding the genetic architecture of these disorders. More recently, exome- and whole-genome sequencing of cases and families have identified rare, high penetrant variants that provide direct functional insight. There remains, however, a gap in the heritability explained by these complementary approaches. To understand how multiple genetic variants combine to modify both severity and penetrance of a highly penetrant variant, we sequenced 48 whole genomes from a family with a high loading of psychiatric disorder linked to a balanced chromosomal translocation. The (1;11)(q42;q14.3) translocation directly disrupts three genes: DISC1, DISC2, DISC1FP and has been linked to multiple brain imaging and neurocognitive outcomes in the family. Using DNA sequence-level linkage analysis, functional annotation and population-based association, we identified common and rare variants in GRM5 (minor allele frequency (MAF) > 0.05), PDE4D (MAF > 0.2) and CNTN5 (MAF < 0.01) that may help explain the individual differences in phenotypic expression in the family. We suggest that whole-genome sequencing in large families will improve the understanding of the combined effects of the rare and common sequence variation underlying psychiatric phenotypes.
A simple genetic architecture underlies morphological variation in dogs.
Boyko, Adam R; Quignon, Pascale; Li, Lin; Schoenebeck, Jeffrey J; Degenhardt, Jeremiah D; Lohmueller, Kirk E; Zhao, Keyan; Brisbin, Abra; Parker, Heidi G; vonHoldt, Bridgett M; Cargill, Michele; Auton, Adam; Reynolds, Andy; Elkahloun, Abdel G; Castelhano, Marta; Mosher, Dana S; Sutter, Nathan B; Johnson, Gary S; Novembre, John; Hubisz, Melissa J; Siepel, Adam; Wayne, Robert K; Bustamante, Carlos D; Ostrander, Elaine A
2010-08-10
Domestic dogs exhibit tremendous phenotypic diversity, including a greater variation in body size than any other terrestrial mammal. Here, we generate a high density map of canine genetic variation by genotyping 915 dogs from 80 domestic dog breeds, 83 wild canids, and 10 outbred African shelter dogs across 60,968 single-nucleotide polymorphisms (SNPs). Coupling this genomic resource with external measurements from breed standards and individuals as well as skeletal measurements from museum specimens, we identify 51 regions of the dog genome associated with phenotypic variation among breeds in 57 traits. The complex traits include average breed body size and external body dimensions and cranial, dental, and long bone shape and size with and without allometric scaling. In contrast to the results from association mapping of quantitative traits in humans and domesticated plants, we find that across dog breeds, a small number of quantitative trait loci (< or = 3) explain the majority of phenotypic variation for most of the traits we studied. In addition, many genomic regions show signatures of recent selection, with most of the highly differentiated regions being associated with breed-defining traits such as body size, coat characteristics, and ear floppiness. Our results demonstrate the efficacy of mapping multiple traits in the domestic dog using a database of genotyped individuals and highlight the important role human-directed selection has played in altering the genetic architecture of key traits in this important species.
A Simple Genetic Architecture Underlies Morphological Variation in Dogs
Schoenebeck, Jeffrey J.; Degenhardt, Jeremiah D.; Lohmueller, Kirk E.; Zhao, Keyan; Brisbin, Abra; Parker, Heidi G.; vonHoldt, Bridgett M.; Cargill, Michele; Auton, Adam; Reynolds, Andy; Elkahloun, Abdel G.; Castelhano, Marta; Mosher, Dana S.; Sutter, Nathan B.; Johnson, Gary S.; Novembre, John; Hubisz, Melissa J.; Siepel, Adam; Wayne, Robert K.; Bustamante, Carlos D.; Ostrander, Elaine A.
2010-01-01
Domestic dogs exhibit tremendous phenotypic diversity, including a greater variation in body size than any other terrestrial mammal. Here, we generate a high density map of canine genetic variation by genotyping 915 dogs from 80 domestic dog breeds, 83 wild canids, and 10 outbred African shelter dogs across 60,968 single-nucleotide polymorphisms (SNPs). Coupling this genomic resource with external measurements from breed standards and individuals as well as skeletal measurements from museum specimens, we identify 51 regions of the dog genome associated with phenotypic variation among breeds in 57 traits. The complex traits include average breed body size and external body dimensions and cranial, dental, and long bone shape and size with and without allometric scaling. In contrast to the results from association mapping of quantitative traits in humans and domesticated plants, we find that across dog breeds, a small number of quantitative trait loci (≤3) explain the majority of phenotypic variation for most of the traits we studied. In addition, many genomic regions show signatures of recent selection, with most of the highly differentiated regions being associated with breed-defining traits such as body size, coat characteristics, and ear floppiness. Our results demonstrate the efficacy of mapping multiple traits in the domestic dog using a database of genotyped individuals and highlight the important role human-directed selection has played in altering the genetic architecture of key traits in this important species. PMID:20711490
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.
Wray, Naomi R; Ripke, Stephan; Mattheisen, Manuel; Trzaskowski, Maciej; Byrne, Enda M; Abdellaoui, Abdel; Adams, Mark J; Agerbo, Esben; Air, Tracy M; Andlauer, Till M F; Bacanu, Silviu-Alin; Bækvad-Hansen, Marie; Beekman, Aartjan F T; Bigdeli, Tim B; Binder, Elisabeth B; Blackwood, Douglas R H; Bryois, Julien; Buttenschøn, Henriette N; Bybjerg-Grauholm, Jonas; Cai, Na; Castelao, Enrique; Christensen, Jane Hvarregaard; Clarke, Toni-Kim; Coleman, Jonathan I R; Colodro-Conde, Lucía; Couvy-Duchesne, Baptiste; Craddock, Nick; Crawford, Gregory E; Crowley, Cheynna A; Dashti, Hassan S; Davies, Gail; Deary, Ian J; Degenhardt, Franziska; Derks, Eske M; Direk, Nese; Dolan, Conor V; Dunn, Erin C; Eley, Thalia C; Eriksson, Nicholas; Escott-Price, Valentina; Kiadeh, Farnush Hassan Farhadi; Finucane, Hilary K; Forstner, Andreas J; Frank, Josef; Gaspar, Héléna A; Gill, Michael; Giusti-Rodríguez, Paola; Goes, Fernando S; Gordon, Scott D; Grove, Jakob; Hall, Lynsey S; Hannon, Eilis; Hansen, Christine Søholm; Hansen, Thomas F; Herms, Stefan; Hickie, Ian B; Hoffmann, Per; Homuth, Georg; Horn, Carsten; Hottenga, Jouke-Jan; Hougaard, David M; Hu, Ming; Hyde, Craig L; Ising, Marcus; Jansen, Rick; Jin, Fulai; Jorgenson, Eric; Knowles, James A; Kohane, Isaac S; Kraft, Julia; Kretzschmar, Warren W; Krogh, Jesper; Kutalik, Zoltán; Lane, Jacqueline M; Li, Yihan; Li, Yun; Lind, Penelope A; Liu, Xiaoxiao; Lu, Leina; MacIntyre, Donald J; MacKinnon, Dean F; Maier, Robert M; Maier, Wolfgang; Marchini, Jonathan; Mbarek, Hamdi; McGrath, Patrick; McGuffin, Peter; Medland, Sarah E; Mehta, Divya; Middeldorp, Christel M; Mihailov, Evelin; Milaneschi, Yuri; Milani, Lili; Mill, Jonathan; Mondimore, Francis M; Montgomery, Grant W; Mostafavi, Sara; Mullins, Niamh; Nauck, Matthias; Ng, Bernard; Nivard, Michel G; Nyholt, Dale R; O'Reilly, Paul F; Oskarsson, Hogni; Owen, Michael J; Painter, Jodie N; Pedersen, Carsten Bøcker; Pedersen, Marianne Giørtz; Peterson, Roseann E; Pettersson, Erik; Peyrot, Wouter J; Pistis, Giorgio; Posthuma, Danielle; Purcell, Shaun M; Quiroz, Jorge A; Qvist, Per; Rice, John P; Riley, Brien P; Rivera, Margarita; Saeed Mirza, Saira; Saxena, Richa; Schoevers, Robert; Schulte, Eva C; Shen, Ling; Shi, Jianxin; Shyn, Stanley I; Sigurdsson, Engilbert; Sinnamon, Grant B C; Smit, Johannes H; Smith, Daniel J; Stefansson, Hreinn; Steinberg, Stacy; Stockmeier, Craig A; Streit, Fabian; Strohmaier, Jana; Tansey, Katherine E; Teismann, Henning; Teumer, Alexander; Thompson, Wesley; Thomson, Pippa A; Thorgeirsson, Thorgeir E; Tian, Chao; Traylor, Matthew; Treutlein, Jens; Trubetskoy, Vassily; Uitterlinden, André G; Umbricht, Daniel; Van der Auwera, Sandra; van Hemert, Albert M; Viktorin, Alexander; Visscher, Peter M; Wang, Yunpeng; Webb, Bradley T; Weinsheimer, Shantel Marie; Wellmann, Jürgen; Willemsen, Gonneke; Witt, Stephanie H; Wu, Yang; Xi, Hualin S; Yang, Jian; Zhang, Futao; Arolt, Volker; Baune, Bernhard T; Berger, Klaus; Boomsma, Dorret I; Cichon, Sven; Dannlowski, Udo; de Geus, E C J; DePaulo, J Raymond; Domenici, Enrico; Domschke, Katharina; Esko, Tõnu; Grabe, Hans J; Hamilton, Steven P; Hayward, Caroline; Heath, Andrew C; Hinds, David A; Kendler, Kenneth S; Kloiber, Stefan; Lewis, Glyn; Li, Qingqin S; Lucae, Susanne; Madden, Pamela F A; Magnusson, Patrik K; Martin, Nicholas G; McIntosh, Andrew M; Metspalu, Andres; Mors, Ole; Mortensen, Preben Bo; Müller-Myhsok, Bertram; Nordentoft, Merete; Nöthen, Markus M; O'Donovan, Michael C; Paciga, Sara A; Pedersen, Nancy L; Penninx, Brenda W J H; Perlis, Roy H; Porteous, David J; Potash, James B; Preisig, Martin; Rietschel, Marcella; Schaefer, Catherine; Schulze, Thomas G; Smoller, Jordan W; Stefansson, Kari; Tiemeier, Henning; Uher, Rudolf; Völzke, Henry; Weissman, Myrna M; Werge, Thomas; Winslow, Ashley R; Lewis, Cathryn M; Levinson, Douglas F; Breen, Gerome; Børglum, Anders D; Sullivan, Patrick F
2018-05-01
Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.
Explosive genetic evidence for explosive human population growth
Gao, Feng; Keinan, Alon
2016-01-01
The advent of next-generation sequencing technology has allowed the collection of vast amounts of genetic variation data. A recurring discovery from studying larger and larger samples of individuals had been the extreme, previously unexpected, excess of very rare genetic variants, which has been shown to be mostly due to the recent explosive growth of human populations. Here, we review recent literature that inferred recent changes in population size in different human populations and with different methodologies, with many pointing to recent explosive growth, especially in European populations for which more data has been available. We also review the state-of-the-art methods and software for the inference of historical population size changes that lead to these discoveries. Finally, we discuss the implications of recent population growth on personalized genomics, on purifying selection in the non-equilibrium state it entails and, as a consequence, on the genetic architecture underlying complex disease and the performance of mapping methods in discovering rare variants that contribute to complex disease risk. PMID:27710906
Molecular genetics of dyslexia: an overview.
Carrion-Castillo, Amaia; Franke, Barbara; Fisher, Simon E
2013-11-01
Dyslexia is a highly heritable learning disorder with a complex underlying genetic architecture. Over the past decade, researchers have pinpointed a number of candidate genes that may contribute to dyslexia susceptibility. Here, we provide an overview of the state of the art, describing how studies have moved from mapping potential risk loci, through identification of associated gene variants, to characterization of gene function in cellular and animal model systems. Work thus far has highlighted some intriguing mechanistic pathways, such as neuronal migration, axon guidance, and ciliary biology, but it is clear that we still have much to learn about the molecular networks that are involved. We end the review by highlighting the past, present, and future contributions of the Dutch Dyslexia Programme to studies of genetic factors. In particular, we emphasize the importance of relating genetic information to intermediate neurobiological measures, as well as the value of incorporating longitudinal and developmental data into molecular designs. Copyright © 2013 John Wiley & Sons, Ltd.
Genetic architecture of domestication-related traits in maize
USDA-ARS?s Scientific Manuscript database
Strong directional selection occurred during the domestication of maize from its wild ancestor teosinte, reducing its genetic diversity, particularly at genes controlling domestication-related traits. Nevertheless, variability for some domestication-related traits is maintained in maize. The genet...
AMD and the alternative complement pathway: genetics and functional implications.
Tan, Perciliz L; Bowes Rickman, Catherine; Katsanis, Nicholas
2016-06-21
Age-related macular degeneration (AMD) is an ocular neurodegenerative disorder and is the leading cause of legal blindness in Western societies, with a prevalence of up to 8 % over the age of 60, which continues to increase with age. AMD is characterized by the progressive breakdown of the macula (the central region of the retina), resulting in the loss of central vision including visual acuity. While its molecular etiology remains unclear, advances in genetics and genomics have illuminated the genetic architecture of the disease and have generated attractive pathomechanistic hypotheses. Here, we review the genetic architecture of AMD, considering the contribution of both common and rare alleles to susceptibility, and we explore the possible mechanistic links between photoreceptor degeneration and the alternative complement pathway, a cascade that has emerged as the most potent genetic driver of this disorder.
NASA Technical Reports Server (NTRS)
Rajkumar, T.; Aragon, Cecilia; Bardina, Jorge; Britten, Roy
2002-01-01
A fast, reliable way of predicting aerodynamic coefficients is produced using a neural network optimized by a genetic algorithm. Basic aerodynamic coefficients (e.g. lift, drag, pitching moment) are modelled as functions of angle of attack and Mach number. The neural network is first trained on a relatively rich set of data from wind tunnel tests of numerical simulations to learn an overall model. Most of the aerodynamic parameters can be well-fitted using polynomial functions. A new set of data, which can be relatively sparse, is then supplied to the network to produce a new model consistent with the previous model and the new data. Because the new model interpolates realistically between the sparse test data points, it is suitable for use in piloted simulations. The genetic algorithm is used to choose a neural network architecture to give best results, avoiding over-and under-fitting of the test data.
Partitioning heritability analysis reveals a shared genetic basis of brain anatomy and schizophrenia
Lee, Phil H.; Baker, Justin T.; Holmes, Avram J.; Jahanshad, Neda; Ge, Tian; Jung, Jae-Yoon; Cruz, Yanela; Manoach, Dara S.; Hibar, Derrek P.; Faskowitz, Joshua; McMahon, Katie L.; de Zubicaray, Greig I.; Martin, Nicolas H.; Wright, Margaret J.; Öngür, Dost; Buckner, Randy; Roffman, Joshua; Thompson, Paul M.; Smoller, Jordan W.
2016-01-01
Schizophrenia is a devastating neurodevelopmental disorder with a complex genetic etiology. Widespread cortical gray matter loss has been observed in patients and prodromal samples. However, it remains unresolved whether schizophrenia-associated cortical structure variations arise due to disease etiology or secondary to the illness. Here we address this question using a partitioning-based heritability analysis of genome-wide SNP and neuroimaging data from 1,750 healthy individuals. We find that schizophrenia-associated genetic variants explain a significantly enriched proportion of trait heritability in eight brain phenotypes (FDR=10%). In particular, intracranial volume (ICV) and left superior frontal gyrus thickness exhibit significant and robust associations with schizophrenia genetic risk under varying SNP selection conditions. Cross disorder comparison suggests that the neurogenetic architecture of schizophrenia-associated brain regions is, at least in part, shared with other psychiatric disorders. Our study highlights key neuroanatomical correlates of schizophrenia genetic risk in the general population. These may provide fundamental insights into the complex pathophysiology of the illness, and a potential link to neurocognitive deficits shaping the disorder. PMID:27725656
Lee, P H; Baker, J T; Holmes, A J; Jahanshad, N; Ge, T; Jung, J-Y; Cruz, Y; Manoach, D S; Hibar, D P; Faskowitz, J; McMahon, K L; de Zubicaray, G I; Martin, N H; Wright, M J; Öngür, D; Buckner, R; Roffman, J; Thompson, P M; Smoller, J W
2016-12-01
Schizophrenia is a devastating neurodevelopmental disorder with a complex genetic etiology. Widespread cortical gray matter loss has been observed in patients and prodromal samples. However, it remains unresolved whether schizophrenia-associated cortical structure variations arise due to disease etiology or secondary to the illness. Here we address this question using a partitioning-based heritability analysis of genome-wide single-nucleotide polymorphism (SNP) and neuroimaging data from 1750 healthy individuals. We find that schizophrenia-associated genetic variants explain a significantly enriched proportion of trait heritability in eight brain phenotypes (false discovery rate=10%). In particular, intracranial volume and left superior frontal gyrus thickness exhibit significant and robust associations with schizophrenia genetic risk under varying SNP selection conditions. Cross-disorder comparison suggests that the neurogenetic architecture of schizophrenia-associated brain regions is, at least in part, shared with other psychiatric disorders. Our study highlights key neuroanatomical correlates of schizophrenia genetic risk in the general population. These may provide fundamental insights into the complex pathophysiology of the illness, and a potential link to neurocognitive deficits shaping the disorder.
A new genetic factor for root gravitropism in rice (Oryza sativa L.).
Shi, Jiang-hua; Hao, Xi; Wu, Zhong-chang; Wu, Ping
2009-10-01
Root gravitropism is one of the important factors to determine root architecture. To understand the mechanism underlying root gravitropism, we isolated a rice (Xiushui63) mutant defective in root gravitropism, designated as gls1. Vertical sections of root caps revealed that gls1 mutant displayed normal distribution of amyloplast in the columella cells compared with the wild type. The gls1 mutant was less sensitive to 2,4-dichlorophenoxyacetic acid (2,4-D) and alpha-naphthaleneacetic acid (NAA) than the wild type. Genetic analysis indicated that the phenotype of gls1 mutant was caused by a single recessive mutation, which is mapped in a 255-kb region between RM16253 and CAPS1 on the short arm of chromosome 4.
Advances in cereal genomics and applications in crop breeding.
Varshney, Rajeev K; Hoisington, David A; Tyagi, Akhilesh K
2006-11-01
Recent advances in cereal genomics have made it possible to analyse the architecture of cereal genomes and their expressed components, leading to an increase in our knowledge of the genes that are linked to key agronomically important traits. These studies have used molecular genetic mapping of quantitative trait loci (QTL) of several complex traits that are important in breeding. The identification and molecular cloning of genes underlying QTLs offers the possibility to examine the naturally occurring allelic variation for respective complex traits. Novel alleles, identified by functional genomics or haplotype analysis, can enrich the genetic basis of cultivated crops to improve productivity. Advances made in cereal genomics research in recent years thus offer the opportunities to enhance the prediction of phenotypes from genotypes for cereal breeding.
Interactions within the MHC contribute to the genetic architecture of celiac disease.
Goudey, Benjamin; Abraham, Gad; Kikianty, Eder; Wang, Qiao; Rawlinson, Dave; Shi, Fan; Haviv, Izhak; Stern, Linda; Kowalczyk, Adam; Inouye, Michael
2017-01-01
Interaction analysis of GWAS can detect signal that would be ignored by single variant analysis, yet few robust interactions in humans have been detected. Recent work has highlighted interactions in the MHC region between known HLA risk haplotypes for various autoimmune diseases. To better understand the genetic interactions underlying celiac disease (CD), we have conducted exhaustive genome-wide scans for pairwise interactions in five independent CD case-control studies, using a rapid model-free approach to examine over 500 billion SNP pairs in total. We found 14 independent interaction signals within the MHC region that achieved stringent replication criteria across multiple studies and were independent of known CD risk HLA haplotypes. The strongest independent CD interaction signal corresponded to genes in the HLA class III region, in particular PRRC2A and GPANK1/C6orf47, which are known to contain variants for non-Hodgkin's lymphoma and early menopause, co-morbidities of celiac disease. Replicable evidence for statistical interaction outside the MHC was not observed. Both within and between European populations, we observed striking consistency of two-locus models and model distribution. Within the UK population, models of CD based on both interactions and additive single-SNP effects increased explained CD variance by approximately 1% over those of single SNPs. The interactions signal detected across the five cohorts indicates the presence of novel associations in the MHC region that cannot be detected using additive models. Our findings have implications for the determination of genetic architecture and, by extension, the use of human genetics for validation of therapeutic targets.
Genetic Architecture of Resistance to Stripe Rust in a Global Winter Wheat Germplasm Collection
Bulli, Peter; Zhang, Junli; Chao, Shiaoman; Chen, Xianming; Pumphrey, Michael
2016-01-01
Virulence shifts in populations of Puccinia striiformis f. sp. tritici (Pst), the causal pathogen of wheat stripe rust, are a major challenge to resistance breeding. The majority of known resistance genes are already ineffective against current races of Pst, necessitating the identification and introgression of new sources of resistance. Germplasm core collections that reflect the range of genetic and phenotypic diversity of crop species are ideal platforms for examining the genetic architecture of complex traits such as resistance to stripe rust. We report the results of genetic characterization and genome-wide association analysis (GWAS) for resistance to stripe rust in a core subset of 1175 accessions in the National Small Grains Collection (NSGC) winter wheat germplasm collection, based on genotyping with the wheat 9K single nucleotide polymorphism (SNP) iSelect assay and phenotyping of seedling and adult plants under natural disease epidemics in four environments. High correlations among the field data translated into high heritability values within and across locations. Population structure was evident when accessions were grouped by stripe rust reaction. GWAS identified 127 resistance loci that were effective across at least two environments, including 20 with significant genome-wide adjusted P-values. Based on relative map positions of previously reported genes and QTL, five of the QTL with significant genome-wide adjusted P-values in this study represent potentially new loci. This study provides an overview of the diversity of Pst resistance in the NSGC winter wheat germplasm core collection, which can be exploited for diversification of stripe rust resistance in breeding programs. PMID:27226168
Genetic Architecture of Resistance to Stripe Rust in a Global Winter Wheat Germplasm Collection.
Bulli, Peter; Zhang, Junli; Chao, Shiaoman; Chen, Xianming; Pumphrey, Michael
2016-08-09
Virulence shifts in populations of Puccinia striiformis f. sp. tritici (Pst), the causal pathogen of wheat stripe rust, are a major challenge to resistance breeding. The majority of known resistance genes are already ineffective against current races of Pst, necessitating the identification and introgression of new sources of resistance. Germplasm core collections that reflect the range of genetic and phenotypic diversity of crop species are ideal platforms for examining the genetic architecture of complex traits such as resistance to stripe rust. We report the results of genetic characterization and genome-wide association analysis (GWAS) for resistance to stripe rust in a core subset of 1175 accessions in the National Small Grains Collection (NSGC) winter wheat germplasm collection, based on genotyping with the wheat 9K single nucleotide polymorphism (SNP) iSelect assay and phenotyping of seedling and adult plants under natural disease epidemics in four environments. High correlations among the field data translated into high heritability values within and across locations. Population structure was evident when accessions were grouped by stripe rust reaction. GWAS identified 127 resistance loci that were effective across at least two environments, including 20 with significant genome-wide adjusted P-values. Based on relative map positions of previously reported genes and QTL, five of the QTL with significant genome-wide adjusted P-values in this study represent potentially new loci. This study provides an overview of the diversity of Pst resistance in the NSGC winter wheat germplasm core collection, which can be exploited for diversification of stripe rust resistance in breeding programs. Copyright © 2016 Bulli et al.
Kooke, Rik; Kruijer, Willem; Bours, Ralph; Becker, Frank; Kuhn, André; van de Geest, Henri; Buntjer, Jaap; Doeswijk, Timo; Guerra, José; Bouwmeester, Harro; Vreugdenhil, Dick; Keurentjes, Joost J B
2016-04-01
Quantitative traits in plants are controlled by a large number of genes and their interaction with the environment. To disentangle the genetic architecture of such traits, natural variation within species can be explored by studying genotype-phenotype relationships. Genome-wide association studies that link phenotypes to thousands of single nucleotide polymorphism markers are nowadays common practice for such analyses. In many cases, however, the identified individual loci cannot fully explain the heritability estimates, suggesting missing heritability. We analyzed 349 Arabidopsis accessions and found extensive variation and high heritabilities for different morphological traits. The number of significant genome-wide associations was, however, very low. The application of genomic prediction models that take into account the effects of all individual loci may greatly enhance the elucidation of the genetic architecture of quantitative traits in plants. Here, genomic prediction models revealed different genetic architectures for the morphological traits. Integrating genomic prediction and association mapping enabled the assignment of many plausible candidate genes explaining the observed variation. These genes were analyzed for functional and sequence diversity, and good indications that natural allelic variation in many of these genes contributes to phenotypic variation were obtained. For ACS11, an ethylene biosynthesis gene, haplotype differences explaining variation in the ratio of petiole and leaf length could be identified. © 2016 American Society of Plant Biologists. All Rights Reserved.
Fang, Lingzhao; Sahana, Goutam; Su, Guosheng; Yu, Ying; Zhang, Shengli; Lund, Mogens Sandø; Sørensen, Peter
2017-01-01
Connecting genome-wide association study (GWAS) to biological mechanisms underlying complex traits is a major challenge. Mastitis resistance and milk production are complex traits of economic importance in the dairy sector and are associated with intra-mammary infection (IMI). Here, we integrated IMI-relevant RNA-Seq data from Holstein cattle and sequence-based GWAS data from three dairy cattle breeds (i.e., Holstein, Nordic red cattle, and Jersey) to explore the genetic basis of mastitis resistance and milk production using post-GWAS analyses and a genomic feature linear mixed model. At 24 h post-IMI, genes responsive to IMI in the mammary gland were preferentially enriched for genetic variants associated with mastitis resistance rather than milk production. Response genes in the liver were mainly enriched for variants associated with mastitis resistance at an early time point (3 h) post-IMI, whereas responsive genes at later stages were enriched for associated variants with milk production. The up- and down-regulated genes were enriched for associated variants with mastitis resistance and milk production, respectively. The patterns were consistent across breeds, indicating that different breeds shared similarities in the genetic basis of these traits. Our approaches provide a framework for integrating multiple layers of data to understand the genetic architecture underlying complex traits. PMID:28358110
van der Harst, Pim; Verweij, Niek
2018-02-02
Coronary artery disease (CAD) is a complex phenotype driven by genetic and environmental factors. Ninety-seven genetic risk loci have been identified to date, but the identification of additional susceptibility loci might be important to enhance our understanding of the genetic architecture of CAD. To expand the number of genome-wide significant loci, catalog functional insights, and enhance our understanding of the genetic architecture of CAD. We performed a genome-wide association study in 34 541 CAD cases and 261 984 controls of UK Biobank resource followed by replication in 88 192 cases and 162 544 controls from CARDIoGRAMplusC4D. We identified 75 loci that replicated and were genome-wide significant ( P <5×10 -8 ) in meta-analysis, 13 of which had not been reported previously. Next, to further identify novel loci, we identified all promising ( P <0.0001) loci in the CARDIoGRAMplusC4D data and performed reciprocal replication and meta-analyses with UK Biobank. This led to the identification of 21 additional novel loci reaching genome-wide significance ( P <5×10 -8 ) in meta-analysis. Finally, we performed a genome-wide meta-analysis of all available data revealing 30 additional novel loci ( P <5×10 -8 ) without further replication. The increase in sample size by UK Biobank raised the number of reconstituted gene sets from 4.2% to 13.9% of all gene sets to be involved in CAD. For the 64 novel loci, 155 candidate causal genes were prioritized, many without an obvious connection to CAD. Fine mapping of the 161 CAD loci generated lists of credible sets of single causal variants and genes for functional follow-up. Genetic risk variants of CAD were linked to development of atrial fibrillation, heart failure, and death. We identified 64 novel genetic risk loci for CAD and performed fine mapping of all 161 risk loci to obtain a credible set of causal variants. The large expansion of reconstituted gene sets argues in favor of an expanded omnigenic model view on the genetic architecture of CAD. © 2017 The Authors.
McCarthy, Mark I
2009-07-03
Identification of common-variant associations for many common disorders has been highly effective, but the loci detected so far typically explain only a small proportion of the genetic predisposition to disease. Extending explained genetic variance is one of the major near-term goals of human genetic research. Next-generation sequencing technologies offer great promise, but optimal strategies for their deployment remain uncertain, not least because we lack a clear view of the characteristics of the variants being sought. Here, I discuss what can and cannot be inferred about complex trait disease architecture from the information currently available and review the implications for future research strategies.
Lopez, Gerardo; Pallas, Benoît; Martinez, Sébastien; Lauri, Pierre-Éric; Regnard, Jean-Luc; Durel, Charles-Éric; Costes, Evelyne
2015-01-01
Water use efficiency (WUE) is a quantitative measurement which improvement is a major issue in the context of global warming and restrictions in water availability for agriculture. In this study, we aimed at studying the variation and genetic control of WUE and the respective role of its components (plant biomass and transpiration) in a perennial fruit crop. We explored an INRA apple core collection grown in a phenotyping platform to screen one-year-old scions for their accumulated biomass, transpiration and WUE under optimal growing conditions. Plant biomass was decompose into morphological components related to either growth or organ expansion. For each trait, nine mixed models were evaluated to account for the genetic effect and spatial heterogeneity inside the platform. The Best Linear Unbiased Predictors of genetic values were estimated after model selection. Mean broad-sense heritabilities were calculated from variance estimates. Heritability values indicated that biomass (0.76) and WUE (0.73) were under genetic control. This genetic control was lower in plant transpiration with an heritability of 0.54. Across the collection, biomass accounted for 70% of the WUE variability. A Hierarchical Ascendant Classification of the core collection indicated the existence of six groups of genotypes with contrasting morphology and WUE. Differences between morphotypes were interpreted as resulting from differences in the main processes responsible for plant growth: cell division leading to the generation of new organs and cell elongation leading to organ dimension. Although further studies will be necessary on mature trees with more complex architecture and multiple sinks such as fruits, this study is a first step for improving apple plant material for the use of water.
Lopez, Gerardo; Pallas, Benoît; Martinez, Sébastien; Lauri, Pierre-Éric; Regnard, Jean-Luc; Durel, Charles-Éric; Costes, Evelyne
2015-01-01
Water use efficiency (WUE) is a quantitative measurement which improvement is a major issue in the context of global warming and restrictions in water availability for agriculture. In this study, we aimed at studying the variation and genetic control of WUE and the respective role of its components (plant biomass and transpiration) in a perennial fruit crop. We explored an INRA apple core collection grown in a phenotyping platform to screen one-year-old scions for their accumulated biomass, transpiration and WUE under optimal growing conditions. Plant biomass was decompose into morphological components related to either growth or organ expansion. For each trait, nine mixed models were evaluated to account for the genetic effect and spatial heterogeneity inside the platform. The Best Linear Unbiased Predictors of genetic values were estimated after model selection. Mean broad-sense heritabilities were calculated from variance estimates. Heritability values indicated that biomass (0.76) and WUE (0.73) were under genetic control. This genetic control was lower in plant transpiration with an heritability of 0.54. Across the collection, biomass accounted for 70% of the WUE variability. A Hierarchical Ascendant Classification of the core collection indicated the existence of six groups of genotypes with contrasting morphology and WUE. Differences between morphotypes were interpreted as resulting from differences in the main processes responsible for plant growth: cell division leading to the generation of new organs and cell elongation leading to organ dimension. Although further studies will be necessary on mature trees with more complex architecture and multiple sinks such as fruits, this study is a first step for improving apple plant material for the use of water. PMID:26717192
The Between-Population Genetic Architecture of Growth, Maturation, and Plasticity in Atlantic Salmon
Debes, Paul Vincent; Fraser, Dylan John; Yates, Matthew; Hutchings, Jeffrey A.
2014-01-01
The between-population genetic architecture for growth and maturation has not been examined in detail for many animal species despite its central importance in understanding hybrid fitness. We studied the genetic architecture of population divergence in: (i) maturation probabilities at the same age; (ii) size at age and growth, while accounting for maturity status and sex; and (iii) growth plasticity in response to environmental factors, using divergent wild and domesticated Atlantic salmon (Salmo salar). Our work examined two populations and their multigenerational hybrids in a common experimental arrangement in which salinity and quantity of suspended sediments were manipulated to mimic naturally occurring environmental variation. Average specific growth rates across environments differed among crosses, maturity groups, and cross-by-maturity groups, but a growth-rate reduction in the presence of suspended sediments was equal for all groups. Our results revealed both additive and nonadditive outbreeding effects for size at age and for growth rates that differed with life stage, as well as the presence of different sex- and size-specific maturation probabilities between populations. The major implication of our work is that estimates of the genetic architecture of growth and maturation can be biased if one does not simultaneously account for temporal changes in growth and for different maturation probabilities between populations. Namely, these correlated traits interact differently within each population and between sexes and among generations, due to nonadditive effects and a level of independence in the genetic control for traits. Our results emphasize the challenges to investigating and predicting phenotypic changes resulting from between-population outbreeding. PMID:24473933
Debes, Paul Vincent; Fraser, Dylan John; Yates, Matthew; Hutchings, Jeffrey A
2014-04-01
The between-population genetic architecture for growth and maturation has not been examined in detail for many animal species despite its central importance in understanding hybrid fitness. We studied the genetic architecture of population divergence in: (i) maturation probabilities at the same age; (ii) size at age and growth, while accounting for maturity status and sex; and (iii) growth plasticity in response to environmental factors, using divergent wild and domesticated Atlantic salmon (Salmo salar). Our work examined two populations and their multigenerational hybrids in a common experimental arrangement in which salinity and quantity of suspended sediments were manipulated to mimic naturally occurring environmental variation. Average specific growth rates across environments differed among crosses, maturity groups, and cross-by-maturity groups, but a growth-rate reduction in the presence of suspended sediments was equal for all groups. Our results revealed both additive and nonadditive outbreeding effects for size at age and for growth rates that differed with life stage, as well as the presence of different sex- and size-specific maturation probabilities between populations. The major implication of our work is that estimates of the genetic architecture of growth and maturation can be biased if one does not simultaneously account for temporal changes in growth and for different maturation probabilities between populations. Namely, these correlated traits interact differently within each population and between sexes and among generations, due to nonadditive effects and a level of independence in the genetic control for traits. Our results emphasize the challenges to investigating and predicting phenotypic changes resulting from between-population outbreeding.
Breeding approaches and genomics technologies to increase crop yield under low-temperature stress.
Jha, Uday Chand; Bohra, Abhishek; Jha, Rintu
2017-01-01
Improved knowledge about plant cold stress tolerance offered by modern omics technologies will greatly inform future crop improvement strategies that aim to breed cultivars yielding substantially high under low-temperature conditions. Alarmingly rising temperature extremities present a substantial impediment to the projected target of 70% more food production by 2050. Low-temperature (LT) stress severely constrains crop production worldwide, thereby demanding an urgent yet sustainable solution. Considerable research progress has been achieved on this front. Here, we review the crucial cellular and metabolic alterations in plants that follow LT stress along with the signal transduction and the regulatory network describing the plant cold tolerance. The significance of plant genetic resources to expand the genetic base of breeding programmes with regard to cold tolerance is highlighted. Also, the genetic architecture of cold tolerance trait as elucidated by conventional QTL mapping and genome-wide association mapping is described. Further, global expression profiling techniques including RNA-Seq along with diverse omics platforms are briefly discussed to better understand the underlying mechanism and prioritize the candidate gene (s) for downstream applications. These latest additions to breeders' toolbox hold immense potential to support plant breeding schemes that seek development of LT-tolerant cultivars. High-yielding cultivars endowed with greater cold tolerance are urgently required to sustain the crop yield under conditions severely challenged by low-temperature.
Similar traits, different genes? Examining convergent evolution in related weedy rice populations.
Thurber, Carrie S; Jia, Melissa H; Jia, Yulin; Caicedo, Ana L
2013-02-01
Convergent phenotypic evolution may or may not be associated with convergent genotypic evolution. Agricultural weeds have repeatedly been selected for weed-adaptive traits such as rapid growth, increased seed dispersal and dormancy, thus providing an ideal system for the study of convergent evolution. Here, we identify QTL underlying weedy traits and compare their genetic architecture to assess the potential for convergent genetic evolution in two distinct populations of weedy rice. F(2) offspring from crosses between an indica cultivar and two individuals from genetically differentiated U.S. weedy rice populations were used to map QTL for four quantitative (heading date, seed shattering, plant height and growth rate) and two qualitative traits. We identified QTL on nine of the twelve rice chromosomes, yet most QTL locations do not overlap between the two populations. Shared QTL among weed groups were only seen for heading date, a trait for which weedy groups have diverged from their cultivated ancestors and from each other. Sharing of some QTL with wild rice also suggests a possible role in weed evolution for genes under selection during domestication. The lack of overlapping QTL for the remaining traits suggests that, despite a close evolutionary relationship, weedy rice groups have adapted to the same agricultural environment through different genetic mechanisms. © 2012 Blackwell Publishing Ltd.
The genetic architecture of resistance to virus infection in Drosophila.
Cogni, Rodrigo; Cao, Chuan; Day, Jonathan P; Bridson, Calum; Jiggins, Francis M
2016-10-01
Variation in susceptibility to infection has a substantial genetic component in natural populations, and it has been argued that selection by pathogens may result in it having a simpler genetic architecture than many other quantitative traits. This is important as models of host-pathogen co-evolution typically assume resistance is controlled by a small number of genes. Using the Drosophila melanogaster multiparent advanced intercross, we investigated the genetic architecture of resistance to two naturally occurring viruses, the sigma virus and DCV (Drosophila C virus). We found extensive genetic variation in resistance to both viruses. For DCV resistance, this variation is largely caused by two major-effect loci. Sigma virus resistance involves more genes - we mapped five loci, and together these explained less than half the genetic variance. Nonetheless, several of these had a large effect on resistance. Models of co-evolution typically assume strong epistatic interactions between polymorphisms controlling resistance, but we were only able to detect one locus that altered the effect of the main effect loci we had mapped. Most of the loci we mapped were probably at an intermediate frequency in natural populations. Overall, our results are consistent with major-effect genes commonly affecting susceptibility to infectious diseases, with DCV resistance being a near-Mendelian trait. © 2016 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.
Emelianov, I; Hernandes-Lopez, A; Torrence, M; Watts, N
2011-01-01
Studying host-based divergence naturally maintained by a balance between selection and gene flow can provide valuable insights into genetic underpinnings of host adaptation and ecological speciation in parasites. Selection-gene flow balance is often postulated in sympatric host races, but direct experimental evidence is scarce. In this study, we present such evidence obtained in host races of Aphidius ervi, an important hymenopteran agent of biological control of aphids in agriculture, using a novel fusion–fission method of gene flow perturbation. In our study, between-race genetic divergence was obliterated by means of advanced hybridisation, followed by a multi-generation exposure of the resulting genetically uniform hybrid swarm to a two-host environment. This fusion–fission procedure was implemented under two contrasting regimes of between-host gene flow in two replicated experiments involving different racial pairs. Host-based genetic fission in response to environmental bimodality occurred in both experiments in as little as six generations of divergent adaptation despite continuous gene flow. We demonstrate that fission recovery of host-based divergence evolved faster and hybridisation-induced linkage disequilibrium decayed slower under restricted (6.7%) compared with unrestricted gene flow, directly pointing at a balance between gene flow and divergent selection. We also show, in four separate tests, that random drift had no or little role in the observed genetic split. Rates and patterns of fission divergence differed between racial pairs. Comparative linkage analysis of these differences is currently under way to test for the role of genomic architecture of adaptation in ecology-driven divergent evolution. PMID:20924399
Alvares, R C; Silva, F C; Melo, L C; Melo, P G S; Pereira, H S
2016-11-21
Slow seed coat darkening is desirable in common bean cultivars and genetic parameters are important to define breeding strategies. The aims of this study were to estimate genetic parameters for plant architecture, grain yield, grain size, and seed-coat darkening in common bean; identify any genetic association among these traits; and select lines that associate desirable phenotypes for these traits. Three experiments were set up in the winter 2012 growing season, in Santo Antônio de Goiás and Brasília, Brazil, including 220 lines obtained from four segregating populations and five parents. A triple lattice 15 x 15 experimental design was used. The traits evaluated were plant architecture, grain yield, grain size, and seed-coat darkening. Analyses of variance were carried out and genetic parameters such as heritability, gain expected from selection, and correlations, were estimated. For selection of superior lines, a "weight-free and parameter-free" index was used. The estimates of genetic variance, heritability, and gain expected from selection were high, indicating good possibility for success in selection of the four traits. The genotype x environment interaction was proportionally more important for yield than for the other traits. There was no strong genetic correlation observed among the four traits, which indicates the possibility of selection of superior lines with many traits. Considering simultaneous selection, it was not possible to join high genetic gains for the four traits. Forty-four lines that combined high yield, more upright plant architecture, slow darkening grains, and commercial grade size were selected.
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.
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
Promoter architecture dictates cell-to-cell variability in gene expression.
Jones, Daniel L; Brewster, Robert C; Phillips, Rob
2014-12-19
Variability in gene expression among genetically identical cells has emerged as a central preoccupation in the study of gene regulation; however, a divide exists between the predictions of molecular models of prokaryotic transcriptional regulation and genome-wide experimental studies suggesting that this variability is indifferent to the underlying regulatory architecture. We constructed a set of promoters in Escherichia coli in which promoter strength, transcription factor binding strength, and transcription factor copy numbers are systematically varied, and used messenger RNA (mRNA) fluorescence in situ hybridization to observe how these changes affected variability in gene expression. Our parameter-free models predicted the observed variability; hence, the molecular details of transcription dictate variability in mRNA expression, and transcriptional noise is specifically tunable and thus represents an evolutionarily accessible phenotypic parameter. Copyright © 2014, American Association for the Advancement of Science.
Ape parasite origins of human malaria virulence genes
Larremore, Daniel B.; Sundararaman, Sesh A.; Liu, Weimin; Proto, William R.; Clauset, Aaron; Loy, Dorothy E.; Speede, Sheri; Plenderleith, Lindsey J.; Sharp, Paul M.; Hahn, Beatrice H.; Rayner, Julian C.; Buckee, Caroline O.
2015-01-01
Antigens encoded by the var gene family are major virulence factors of the human malaria parasite Plasmodium falciparum, exhibiting enormous intra- and interstrain diversity. Here we use network analysis to show that var architecture and mosaicism are conserved at multiple levels across the Laverania subgenus, based on var-like sequences from eight single-species and three multi-species Plasmodium infections of wild-living or sanctuary African apes. Using select whole-genome amplification, we also find evidence of multi-domain var structure and synteny in Plasmodium gaboni, one of the ape Laverania species most distantly related to P. falciparum, as well as a new class of Duffy-binding-like domains. These findings indicate that the modular genetic architecture and sequence diversity underlying var-mediated host-parasite interactions evolved before the radiation of the Laverania subgenus, long before the emergence of P. falciparum. PMID:26456841
Zhou, Bo; Lin, Jian Zhong; Peng, Dan; Yang, Yuan Zhu; Guo, Ming; Tang, Dong Ying; Tan, Xiaofeng; Liu, Xuan Ming
2017-01-01
In many plants, architecture and grain yield are affected by both the environment and genetics. In rice, the tiller is a vital factor impacting plant architecture and regulated by many genes. In this study, we cloned a novel DHHC-type zinc finger protein gene Os02g0819100 and its alternative splice variant OsDHHC1 from the cDNA of rice (Oryza sativa L.), which regulate plant architecture by altering the tiller in rice. The tillers increased by about 40% when this type of DHHC-type zinc finger protein gene was over-expressed in Zhong Hua 11 (ZH11) rice plants. Moreover, the grain yield of transgenic rice increased approximately by 10% compared with wild-type ZH11. These findings provide an important genetic engineering approach for increasing rice yields. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Adaptation of human skin color in various populations.
Deng, Lian; Xu, Shuhua
2018-01-01
Skin color is a well-recognized adaptive trait and has been studied extensively in humans. Understanding the genetic basis of adaptation of skin color in various populations has many implications in human evolution and medicine. Impressive progress has been made recently to identify genes associated with skin color variation in a wide range of geographical and temporal populations. In this review, we discuss what is currently known about the genetics of skin color variation. We enumerated several cases of skin color adaptation in global modern humans and archaic hominins, and illustrated why, when, and how skin color adaptation occurred in different populations. Finally, we provided a summary of the candidate loci associated with pigmentation, which could be a valuable reference for further evolutionary and medical studies. Previous studies generally indicated a complex genetic mechanism underlying the skin color variation, expanding our understanding of the role of population demographic history and natural selection in shaping genetic and phenotypic diversity in humans. Future work is needed to dissect the genetic architecture of skin color adaptation in numerous ethnic minority groups around the world, which remains relatively obscure compared with that of major continental groups, and to unravel the exact genetic basis of skin color adaptation.
Advances in Arachis genomics for peanut improvement
USDA-ARS?s Scientific Manuscript database
Peanut genomics is very challenging due to its inherent problem of genetic architecture. Blockage of gene flow from diploid wild relatives to tetraploid cultivated peanut, recent polyploidization combined with self pollination and narrow genetic base of primary gene pool resulted in low genetic dive...
Xu, Bin; Woodroffe, Abigail; Rodriguez-Murillo, Laura; Roos, J Louw; van Rensburg, Elizabeth J; Abecasis, Gonçalo R; Gogos, Joseph A; Karayiorgou, Maria
2009-09-29
To elucidate the genetic architecture of familial schizophrenia we combine linkage analysis with studies of fine-level chromosomal variation in families recruited from the Afrikaner population in South Africa. We demonstrate that individually rare inherited copy number variants (CNVs) are more frequent in cases with familial schizophrenia as compared to unaffected controls and affect almost exclusively genic regions. Interestingly, we find that while the prevalence of rare structural variants is similar in familial and sporadic cases, the type of variants is markedly different. In addition, using a high-density linkage scan with a panel of nearly 2,000 markers, we identify a region on chromosome 13q34 that shows genome-wide significant linkage to schizophrenia and show that in the families not linked to this locus, there is evidence for linkage to chromosome 1p36. No causative CNVs were identified in either locus. Overall, our results from approaches designed to detect risk variants with relatively low frequency and high penetrance in a well-defined and relatively homogeneous population, provide strong empirical evidence supporting the notion that multiple genetic variants, including individually rare ones, that affect many different genes contribute to the genetic risk of familial schizophrenia. They also highlight differences in the genetic architecture of the familial and sporadic forms of the disease.
Genetic Architecture Promotes the Evolution and Maintenance of Cooperation
Frénoy, Antoine; Taddei, François; Misevic, Dusan
2013-01-01
When cooperation has a direct cost and an indirect benefit, a selfish behavior is more likely to be selected for than an altruistic one. Kin and group selection do provide evolutionary explanations for the stability of cooperation in nature, but we still lack the full understanding of the genomic mechanisms that can prevent cheater invasion. In our study we used Aevol, an agent-based, in silico genomic platform to evolve populations of digital organisms that compete, reproduce, and cooperate by secreting a public good for tens of thousands of generations. We found that cooperating individuals may share a phenotype, defined as the amount of public good produced, but have very different abilities to resist cheater invasion. To understand the underlying genetic differences between cooperator types, we performed bio-inspired genomics analyses of our digital organisms by recording and comparing the locations of metabolic and secretion genes, as well as the relevant promoters and terminators. Association between metabolic and secretion genes (promoter sharing, overlap via frame shift or sense-antisense encoding) was characteristic for populations with robust cooperation and was more likely to evolve when secretion was costly. In mutational analysis experiments, we demonstrated the potential evolutionary consequences of the genetic association by performing a large number of mutations and measuring their phenotypic and fitness effects. The non-cooperating mutants arising from the individuals with genetic association were more likely to have metabolic deleterious mutations that eventually lead to selection eliminating such mutants from the population due to the accompanying fitness decrease. Effectively, cooperation evolved to be protected and robust to mutations through entangled genetic architecture. Our results confirm the importance of second-order selection on evolutionary outcomes, uncover an important genetic mechanism for the evolution and maintenance of cooperation, and suggest promising methods for preventing gene loss in synthetically engineered organisms. PMID:24278000
Yu, Dongmei; Mathews, Carol A; Scharf, Jeremiah M; Neale, Benjamin M; Davis, Lea K; Gamazon, Eric R; Derks, Eske M; Evans, Patrick; Edlund, Christopher K; Crane, Jacquelyn; Fagerness, Jesen A; Osiecki, Lisa; Gallagher, Patience; Gerber, Gloria; Haddad, Stephen; Illmann, Cornelia; McGrath, Lauren M; Mayerfeld, Catherine; Arepalli, Sampath; Barlassina, Cristina; Barr, Cathy L; Bellodi, Laura; Benarroch, Fortu; Berrió, Gabriel Bedoya; Bienvenu, O Joseph; Black, Donald W; Bloch, Michael H; Brentani, Helena; Bruun, Ruth D; Budman, Cathy L; Camarena, Beatriz; Campbell, Desmond D; Cappi, Carolina; Silgado, Julio C Cardona; Cavallini, Maria C; Chavira, Denise A; Chouinard, Sylvain; Cook, Edwin H; Cookson, M R; Coric, Vladimir; Cullen, Bernadette; Cusi, Daniele; Delorme, Richard; Denys, Damiaan; Dion, Yves; Eapen, Valsama; Egberts, Karin; Falkai, Peter; Fernandez, Thomas; Fournier, Eduardo; Garrido, Helena; Geller, Daniel; Gilbert, Donald L; Girard, Simon L; Grabe, Hans J; Grados, Marco A; Greenberg, Benjamin D; Gross-Tsur, Varda; Grünblatt, Edna; Hardy, John; Heiman, Gary A; Hemmings, Sian M J; Herrera, Luis D; Hezel, Dianne M; Hoekstra, Pieter J; Jankovic, Joseph; Kennedy, James L; King, Robert A; Konkashbaev, Anuar I; Kremeyer, Barbara; Kurlan, Roger; Lanzagorta, Nuria; Leboyer, Marion; Leckman, James F; Lennertz, Leonhard; Liu, Chunyu; Lochner, Christine; Lowe, Thomas L; Lupoli, Sara; Macciardi, Fabio; Maier, Wolfgang; Manunta, Paolo; Marconi, Maurizio; McCracken, James T; Mesa Restrepo, Sandra C; Moessner, Rainald; Moorjani, Priya; Morgan, Jubel; Muller, Heike; Murphy, Dennis L; Naarden, Allan L; Nurmi, Erika; Ochoa, William Cornejo; Ophoff, Roel A; Pakstis, Andrew J; Pato, Michele T; Pato, Carlos N; Piacentini, John; Pittenger, Christopher; Pollak, Yehuda; Rauch, Scott L; Renner, Tobias; Reus, Victor I; Richter, Margaret A; Riddle, Mark A; Robertson, Mary M; Romero, Roxana; Rosário, Maria C; Rosenberg, David; Ruhrmann, Stephan; Sabatti, Chiara; Salvi, Erika; Sampaio, Aline S; Samuels, Jack; Sandor, Paul; Service, Susan K; Sheppard, Brooke; Singer, Harvey S; Smit, Jan H; Stein, Dan J; Strengman, Eric; Tischfield, Jay A; Turiel, Maurizio; Valencia Duarte, Ana V; Vallada, Homero; Veenstra-VanderWeele, Jeremy; Walitza, Susanne; Wang, Ying; Weale, Mike; Weiss, Robert; Wendland, Jens R; Westenberg, Herman G M; Shugart, Yin Yao; Hounie, Ana G; Miguel, Euripedes C; Nicolini, Humberto; Wagner, Michael; Ruiz-Linares, Andres; Cath, Danielle C; McMahon, William; Posthuma, Danielle; Oostra, Ben A; Nestadt, Gerald; Rouleau, Guy A; Purcell, Shaun; Jenike, Michael A; Heutink, Peter; Hanna, Gregory L; Conti, David V; Arnold, Paul D; Freimer, Nelson B; Stewart, S Evelyn; Knowles, James A; Cox, Nancy J; Pauls, David L
2015-01-01
Obsessive-compulsive disorder (OCD) and Tourette's syndrome are highly heritable neurodevelopmental disorders that are thought to share genetic risk factors. However, the identification of definitive susceptibility genes for these etiologically complex disorders remains elusive. The authors report a combined genome-wide association study (GWAS) of Tourette's syndrome and OCD. The authors conducted a GWAS in 2,723 cases (1,310 with OCD, 834 with Tourette's syndrome, 579 with OCD plus Tourette's syndrome/chronic tics), 5,667 ancestry-matched controls, and 290 OCD parent-child trios. GWAS summary statistics were examined for enrichment of functional variants associated with gene expression levels in brain regions. Polygenic score analyses were conducted to investigate the genetic architecture within and across the two disorders. Although no individual single-nucleotide polymorphisms (SNPs) achieved genome-wide significance, the GWAS signals were enriched for SNPs strongly associated with variations in brain gene expression levels (expression quantitative loci, or eQTLs), suggesting the presence of true functional variants that contribute to risk of these disorders. Polygenic score analyses identified a significant polygenic component for OCD (p=2×10(-4)), predicting 3.2% of the phenotypic variance in an independent data set. In contrast, Tourette's syndrome had a smaller, nonsignificant polygenic component, predicting only 0.6% of the phenotypic variance (p=0.06). No significant polygenic signal was detected across the two disorders, although the sample is likely underpowered to detect a modest shared signal. Furthermore, the OCD polygenic signal was significantly attenuated when cases with both OCD and co-occurring Tourette's syndrome/chronic tics were included in the analysis (p=0.01). Previous work has shown that Tourette's syndrome and OCD have some degree of shared genetic variation. However, the data from this study suggest that there are also distinct components to the genetic architectures of these two disorders. Furthermore, OCD with co-occurring Tourette's syndrome/chronic tics may have different underlying genetic susceptibility compared with OCD alone.
Martin, Christopher H; Erickson, Priscilla A; Miller, Craig T
2017-01-01
The genetic architecture of adaptation is fundamental to understanding the mechanisms and constraints governing diversification. However, most case studies focus on loss of complex traits or parallel speciation in similar environments. It is still unclear how the genetic architecture of these local adaptive processes compares to the architecture of evolutionary transitions contributing to morphological and ecological novelty. Here, we identify quantitative trait loci (QTL) between two trophic specialists in an excellent case study for examining the origins of ecological novelty: a sympatric radiation of pupfishes endemic to San Salvador Island, Bahamas, containing a large-jawed scale-eater and a short-jawed molluscivore with a skeletal nasal protrusion. These specialized niches and trophic traits are unique among over 2000 related species. Measurements of the fitness landscape on San Salvador demonstrate multiple fitness peaks and a larger fitness valley isolating the scale-eater from the putative ancestral intermediate phenotype of the generalist, suggesting that more large-effect QTL should contribute to its unique phenotype. We evaluated this prediction using an F2 intercross between these specialists. We present the first linkage map for pupfishes and detect significant QTL for sex and eight skeletal traits. Large-effect QTL contributed more to enlarged scale-eater jaws than the molluscivore nasal protrusion, consistent with predictions from the adaptive landscape. The microevolutionary genetic architecture of large-effect QTL for oral jaws parallels the exceptional diversification rates of oral jaws within the San Salvador radiation observed over macroevolutionary timescales and may have facilitated exceptional trophic novelty in this system. © 2016 John Wiley & Sons Ltd.
Bai, Xufeng; Zhao, Hu; Huang, Yong; Xie, Weibo; Han, Zhongmin; Zhang, Bo; Guo, Zilong; Yang, Lin; Dong, Haijiao; Xue, Weiya; Li, Guangwei; Hu, Gang; Hu, Yong; Xing, Yongzhong
2016-07-01
Panicle architecture determines the number of spikelets per panicle (SPP) and is highly associated with grain yield in rice ( L.). Understanding the genetic basis of panicle architecture is important for improving the yield of rice grain. In this study, we dissected panicle architecture traits into eight components, which were phenotyped from a germplasm collection of 529 cultivars. Multiple regression analysis revealed that the number of secondary branch (NSB) was the major factor that contributed to SPP. Genome-wide association analysis was performed independently for the eight particle architecture traits observed in the and rice subpopulations compared with the whole rice population. In total, 30 loci were associated with these traits. Of these, 13 loci were closely linked to known panicle architecture genes, and 17 novel loci were repeatedly identified in different environments. An association signal cluster was identified for NSB and number of spikelets per secondary branch (NSSB) in the region of 31.6 to 31.7 Mb on chromosome 4. In addition to the common associations detected in both and subpopulations, many associated loci were unique to one subpopulation. For example, and were specifically associated with panicle length (PL) in and rice, respectively. Moreover, the -mediated flowering genes and were associated with the formation of panicle architecture in rice. These results suggest that different gene networks regulate panicle architecture in and rice. Copyright © 2016 Crop Science Society of America.
Du, Xiongming; Liu, Shouye; Sun, Junling; Zhang, Gengyun; Jia, Yinhua; Pan, Zhaoe; Xiang, Haitao; He, Shoupu; Xia, Qiuju; Xiao, Songhua; Shi, Weijun; Quan, Zhiwu; Liu, Jianguang; Ma, Jun; Pang, Baoyin; Wang, Liru; Sun, Gaofei; Gong, Wenfang; Jenkins, Johnie N; Lou, Xiangyang; Zhu, Jun; Xu, Haiming
2018-06-13
Cottonseed is one of the most important raw materials for plant protein, oil and alternative biofuel for diesel engines. Understanding the complex genetic basis of cottonseed traits is requisite for achieving efficient genetic improvement of the traits. However, it is not yet clear about their genetic architecture in genomic level. GWAS has been an effective way to explore genetic basis of quantitative traits in human and many crops. This study aims to dissect genetic mechanism seven cottonseed traits by a GWAS for genetic improvement. A genome-wide association study (GWAS) based on a full gene model with gene effects as fixed and gene-environment interaction as random, was conducted for protein, oil and 5 fatty acids using 316 accessions and ~ 390 K SNPs. Totally, 124 significant quantitative trait SNPs (QTSs), consisting of 16, 21, 87 for protein, oil and fatty acids (palmitic, linoleic, oleic, myristic, stearic), respectively, were identified and the broad-sense heritability was estimated from 71.62 to 93.43%; no QTS-environment interaction was detected for the protein, the palmitic and the oleic contents; the protein content was predominantly controlled by epistatic effects accounting for 65.18% of the total variation, but the oil content and the fatty acids except the palmitic were mainly determined by gene main effects and no epistasis was detected for the myristic and the stearic. Prediction of superior pure line and hybrid revealed the potential of the QTSs in the improvement of cottonseed traits, and the hybrid could achieve higher or lower genetic values compared with pure lines. This study revealed complex genetic architecture of seven cottonseed traits at whole genome-wide by mixed linear model approach; the identified genetic variants and estimated genetic component effects of gene, gene-gene and gene-environment interaction provide cotton geneticist or breeders new knowledge on the genetic mechanism of the traits and the potential molecular breeding design strategy.
An alternative covariance estimator to investigate genetic heterogeneity in populations.
Heslot, Nicolas; Jannink, Jean-Luc
2015-11-26
For genomic prediction and genome-wide association studies (GWAS) using mixed models, covariance between individuals is estimated using molecular markers. Based on the properties of mixed models, using available molecular data for prediction is optimal if this covariance is known. Under this assumption, adding individuals to the analysis should never be detrimental. However, some empirical studies showed that increasing training population size decreased prediction accuracy. Recently, results from theoretical models indicated that even if marker density is high and the genetic architecture of traits is controlled by many loci with small additive effects, the covariance between individuals, which depends on relationships at causal loci, is not always well estimated by the whole-genome kinship. We propose an alternative covariance estimator named K-kernel, to account for potential genetic heterogeneity between populations that is characterized by a lack of genetic correlation, and to limit the information flow between a priori unknown populations in a trait-specific manner. This is similar to a multi-trait model and parameters are estimated by REML and, in extreme cases, it can allow for an independent genetic architecture between populations. As such, K-kernel is useful to study the problem of the design of training populations. K-kernel was compared to other covariance estimators or kernels to examine its fit to the data, cross-validated accuracy and suitability for GWAS on several datasets. It provides a significantly better fit to the data than the genomic best linear unbiased prediction model and, in some cases it performs better than other kernels such as the Gaussian kernel, as shown by an empirical null distribution. In GWAS simulations, alternative kernels control type I errors as well as or better than the classical whole-genome kinship and increase statistical power. No or small gains were observed in cross-validated prediction accuracy. This alternative covariance estimator can be used to gain insight into trait-specific genetic heterogeneity by identifying relevant sub-populations that lack genetic correlation between them. Genetic correlation can be 0 between identified sub-populations by performing automatic selection of relevant sets of individuals to be included in the training population. It may also increase statistical power in GWAS.
The Genetic Architecture of Major Depressive Disorder in Han Chinese Women.
Peterson, Roseann E; Cai, Na; Bigdeli, Tim B; Li, Yihan; Reimers, Mark; Nikulova, Anna; Webb, Bradley T; Bacanu, Silviu-Alin; Riley, Brien P; Flint, Jonathan; Kendler, Kenneth S
2017-02-01
Despite the moderate, well-demonstrated heritability of major depressive disorder (MDD), there has been limited success in identifying replicable genetic risk loci, suggesting a complex genetic architecture. Research is needed to quantify the relative contribution of classes of genetic variation across the genome to inform future genetic studies of MDD. To apply aggregate genetic risk methods to clarify the genetic architecture of MDD by estimating and partitioning heritability by chromosome, minor allele frequency, and functional annotations and to test for enrichment of rare deleterious variants. The CONVERGE (China, Oxford, and Virginia Commonwealth University Experimental Research on Genetic Epidemiology) study collected data on 5278 patients with recurrent MDD from 58 provincial mental health centers and psychiatric departments of general medical hospitals in 45 cities and 23 provinces of China. Screened controls (n = 5196) were recruited from a range of locations, including general hospitals and local community centers. Data were collected from August 1, 2008, to October 31, 2012. Genetic risk for liability to recurrent MDD was partitioned using sparse whole-genome sequencing. In aggregate, common single-nucleotide polymorphisms (SNPs) explained between 20% and 29% of the variance in MDD risk, and the heritability in MDD explained by each chromosome was proportional to its length (r = 0.680; P = .0003), supporting a common polygenic etiology. Partitioning heritability by minor allele frequency indicated that the variance explained was distributed across the allelic frequency spectrum, although relatively common SNPs accounted for a disproportionate fraction of risk. Partitioning by genic annotation indicated a greater contribution of SNPs in protein-coding regions and within 3'-UTR regions of genes. Enrichment of SNPs associated with DNase I-hypersensitive sites was also found in many tissue types, including brain tissue. Examining burden scores from singleton exonic SNPs predicted to be deleterious indicated that cases had significantly more mutations than controls (odds ratio, 1.009; 95% CI, 1.003-1.014; P = .003), including those occurring in genes expressed in the brain (odds ratio, 1.011; 95% CI, 1.003-1.018; P = .004) and within nuclear-encoded genes with mitochondrial gene products (odds ratio, 1.075; 95% CI, 1.018-1.135; P = .009). Results support a complex etiology for MDD and highlight the value of analyzing components of heritability to clarify genetic architecture.
The Genetic Architecture of Major Depressive Disorder in Han Chinese Women
Peterson, Roseann E.; Cai, Na; Bigdeli, Tim B.; Li, Yihan; Reimers, Mark; Nikulova, Anna; Webb, Bradley T.; Bacanu, Silviu-Alin; Riley, Brien P.; Flint, Jonathan; Kendler, Kenneth S.
2017-01-01
IMPORTANCE Despite the moderate, well-demonstrated heritability of major depressive disorder (MDD), there has been limited success in identifying replicable genetic risk loci, suggesting a complex genetic architecture. Research is needed to quantify the relative contribution of classes of genetic variation across the genome to inform future genetic studies of MDD. OBJECTIVES To apply aggregate genetic risk methods to clarify the genetic architecture of MDD by estimating and partitioning heritability by chromosome, minor allele frequency, and functional annotations and to test for enrichment of rare deleterious variants. DESIGN, SETTING, AND PARTICIPANTS The CONVERGE (China, Oxford, and Virginia Commonwealth University Experimental Research on Genetic Epidemiology) study collected data on 5278 patients with recurrent MDD from 58 provincial mental health centers and psychiatric departments of general medical hospitals in 45 cities and 23 provinces of China. Screened controls (n = 5196) were recruited from a range of locations, including general hospitals and local community centers. Data were collected from August 1, 2008, to October 31, 2012. MAIN OUTCOMES AND MEASURES Genetic risk for liability to recurrent MDD was partitioned using sparse whole-genome sequencing. RESULTS In aggregate, common single-nucleotide polymorphisms (SNPs) explained between 20% and 29% of the variance in MDD risk, and the heritability in MDD explained by each chromosome was proportional to its length (r = 0.680; P = .0003), supporting a common polygenic etiology. Partitioning heritability by minor allele frequency indicated that the variance explained was distributed across the allelic frequency spectrum, although relatively common SNPs accounted for a disproportionate fraction of risk. Partitioning by genic annotation indicated a greater contribution of SNPs in protein-coding regions and within 3′-UTR regions of genes. Enrichment of SNPs associated with DNase I-hypersensitive sites was also found in many tissue types, including brain tissue. Examining burden scores from singleton exonic SNPs predicted to be deleterious indicated that cases had significantly more mutations than controls (odds ratio, 1.009; 95% CI, 1.003–1.014; P = .003), including those occurring in genes expressed in the brain (odds ratio, 1.011; 95% CI, 1.003–1.018; P = .004) and within nuclear-encoded genes with mitochondrial gene products (odds ratio, 1.075; 95% CI, 1.018–1.135; P = .009). CONCLUSIONS AND RELEVANCE Results support a complex etiology for MDD and highlight the value of analyzing components of heritability to clarify genetic architecture. PMID:28002544
van Rheenen, Wouter; Shatunov, Aleksey; Dekker, Annelot M; McLaughlin, Russell L; Diekstra, Frank P; Pulit, Sara L; van der Spek, Rick A A; Võsa, Urmo; de Jong, Simone; Robinson, Matthew R; Yang, Jian; Fogh, Isabella; van Doormaal, Perry TC; Tazelaar, Gijs H P; Koppers, Max; Blokhuis, Anna M; Sproviero, William; Jones, Ashley R; Kenna, Kevin P; van Eijk, Kristel R; Harschnitz, Oliver; Schellevis, Raymond D; Brands, William J; Medic, Jelena; Menelaou, Androniki; Vajda, Alice; Ticozzi, Nicola; Lin, Kuang; Rogelj, Boris; Vrabec, Katarina; Ravnik-Glavač, Metka; Koritnik, Blaž; Zidar, Janez; Leonardis, Lea; Grošelj, Leja Dolenc; Millecamps, Stéphanie; Salachas, François; Meininger, Vincent; de Carvalho, Mamede; Pinto, Susana; Mora, Jesus S; Rojas-García, Ricardo; Polak, Meraida; Chandran, Siddharthan; Colville, Shuna; Swingler, Robert; Morrison, Karen E; Shaw, Pamela J; Hardy, John; Orrell, Richard W; Pittman, Alan; Sidle, Katie; Fratta, Pietro; Malaspina, Andrea; Topp, Simon; Petri, Susanne; Abdulla, Susanne; Drepper, Carsten; Sendtner, Michael; Meyer, Thomas; Ophoff, Roel A; Staats, Kim A; Wiedau-Pazos, Martina; Lomen-Hoerth, Catherine; Van Deerlin, Vivianna M; Trojanowski, John Q; Elman, Lauren; McCluskey, Leo; Basak, A Nazli; Tunca, Ceren; Hamzeiy, Hamid; Parman, Yesim; Meitinger, Thomas; Lichtner, Peter; Radivojkov-Blagojevic, Milena; Andres, Christian R; Maurel, Cindy; Bensimon, Gilbert; Landwehrmeyer, Bernhard; Brice, Alexis; Payan, Christine A M; Saker-Delye, Safaa; Dürr, Alexandra; Wood, Nicholas W; Tittmann, Lukas; Lieb, Wolfgang; Franke, Andre; Rietschel, Marcella; Cichon, Sven; Nöthen, Markus M; Amouyel, Philippe; Tzourio, Christophe; Dartigues, Jean-François; Uitterlinden, Andre G; Rivadeneira, Fernando; Estrada, Karol; Hofman, Albert; Curtis, Charles; Blauw, Hylke M; van der Kooi, Anneke J; de Visser, Marianne; Goris, An; Weber, Markus; Shaw, Christopher E; Smith, Bradley N; Pansarasa, Orietta; Cereda, Cristina; Bo, Roberto Del; Comi, Giacomo P; D’Alfonso, Sandra; Bertolin, Cinzia; Sorarù, Gianni; Mazzini, Letizia; Pensato, Viviana; Gellera, Cinzia; Tiloca, Cinzia; Ratti, Antonia; Calvo, Andrea; Moglia, Cristina; Brunetti, Maura; Arcuti, Simona; Capozzo, Rosa; Zecca, Chiara; Lunetta, Christian; Penco, Silvana; Riva, Nilo; Padovani, Alessandro; Filosto, Massimiliano; Muller, Bernard; Stuit, Robbert Jan; Blair, Ian; Zhang, Katharine; McCann, Emily P; Fifita, Jennifer A; Nicholson, Garth A; Rowe, Dominic B; Pamphlett, Roger; Kiernan, Matthew C; Grosskreutz, Julian; Witte, Otto W; Ringer, Thomas; Prell, Tino; Stubendorff, Beatrice; Kurth, Ingo; Hübner, Christian A; Leigh, P Nigel; Casale, Federico; Chio, Adriano; Beghi, Ettore; Pupillo, Elisabetta; Tortelli, Rosanna; Logroscino, Giancarlo; Powell, John; Ludolph, Albert C; Weishaupt, Jochen H; Robberecht, Wim; Van Damme, Philip; Franke, Lude; Pers, Tune H; Brown, Robert H; Glass, Jonathan D; Landers, John E; Hardiman, Orla; Andersen, Peter M; Corcia, Philippe; Vourc’h, Patrick; Silani, Vincenzo; Wray, Naomi R; Visscher, Peter M; de Bakker, Paul I W; van Es, Michael A; Pasterkamp, R Jeroen; Lewis, Cathryn M; Breen, Gerome; Al-Chalabi, Ammar; van den Berg, Leonard H; Veldink, Jan H
2017-01-01
To elucidate the genetic architecture of amyotrophic lateral sclerosis (ALS) and find associated loci, we assembled a custom imputation reference panel from whole-genome-sequenced patients with ALS and matched controls (n = 1,861). Through imputation and mixed-model association analysis in 12,577 cases and 23,475 controls, combined with 2,579 cases and 2,767 controls in an independent replication cohort, we fine-mapped a new risk locus on chromosome 21 and identified C21orf2 as a gene associated with ALS risk. In addition, we identified MOBP and SCFD1 as new associated risk loci. We established evidence of ALS being a complex genetic trait with a polygenic architecture. Furthermore, we estimated the SNP-based heritability at 8.5%, with a distinct and important role for low-frequency variants (frequency 1–10%). This study motivates the interrogation of larger samples with full genome coverage to identify rare causal variants that underpin ALS risk. PMID:27455348
Morris, Andrew P; Voight, Benjamin F; Teslovich, Tanya M; Ferreira, Teresa; Segrè, Ayellet V; Steinthorsdottir, Valgerdur; Strawbridge, Rona J; Khan, Hassan; Grallert, Harald; Mahajan, Anubha; Prokopenko, Inga; Kang, Hyun Min; Dina, Christian; Esko, Tonu; Fraser, Ross M; Kanoni, Stavroula; Kumar, Ashish; Lagou, Vasiliki; Langenberg, Claudia; Luan, Jian'an; Lindgren, Cecilia M; Müller-Nurasyid, Martina; Pechlivanis, Sonali; Rayner, N William; Scott, Laura J; Wiltshire, Steven; Yengo, Loic; Kinnunen, Leena; Rossin, Elizabeth J; Raychaudhuri, Soumya; Johnson, Andrew D; Dimas, Antigone S; Loos, Ruth J F; Vedantam, Sailaja; Chen, Han; Florez, Jose C; Fox, Caroline; Liu, Ching-Ti; Rybin, Denis; Couper, David J; Kao, Wen Hong L; Li, Man; Cornelis, Marilyn C; Kraft, Peter; Sun, Qi; van Dam, Rob M; Stringham, Heather M; Chines, Peter S; Fischer, Krista; Fontanillas, Pierre; Holmen, Oddgeir L; Hunt, Sarah E; Jackson, Anne U; Kong, Augustine; Lawrence, Robert; Meyer, Julia; Perry, John RB; Platou, Carl GP; Potter, Simon; Rehnberg, Emil; Robertson, Neil; Sivapalaratnam, Suthesh; Stančáková, Alena; Stirrups, Kathleen; Thorleifsson, Gudmar; Tikkanen, Emmi; Wood, Andrew R; Almgren, Peter; Atalay, Mustafa; Benediktsson, Rafn; Bonnycastle, Lori L; Burtt, Noël; Carey, Jason; Charpentier, Guillaume; Crenshaw, Andrew T; Doney, Alex S F; Dorkhan, Mozhgan; Edkins, Sarah; Emilsson, Valur; Eury, Elodie; Forsen, Tom; Gertow, Karl; Gigante, Bruna; Grant, George B; Groves, Christopher J; Guiducci, Candace; Herder, Christian; Hreidarsson, Astradur B; Hui, Jennie; James, Alan; Jonsson, Anna; Rathmann, Wolfgang; Klopp, Norman; Kravic, Jasmina; Krjutškov, Kaarel; Langford, Cordelia; Leander, Karin; Lindholm, Eero; Lobbens, Stéphane; Männistö, Satu; Mirza, Ghazala; Mühleisen, Thomas W; Musk, Bill; Parkin, Melissa; Rallidis, Loukianos; Saramies, Jouko; Sennblad, Bengt; Shah, Sonia; Sigurðsson, Gunnar; Silveira, Angela; Steinbach, Gerald; Thorand, Barbara; Trakalo, Joseph; Veglia, Fabrizio; Wennauer, Roman; Winckler, Wendy; Zabaneh, Delilah; Campbell, Harry; van Duijn, Cornelia; Uitterlinden89-, Andre G; Hofman, Albert; Sijbrands, Eric; Abecasis, Goncalo R; Owen, Katharine R; Zeggini, Eleftheria; Trip, Mieke D; Forouhi, Nita G; Syvänen, Ann-Christine; Eriksson, Johan G; Peltonen, Leena; Nöthen, Markus M; Balkau, Beverley; Palmer, Colin N A; Lyssenko, Valeriya; Tuomi, Tiinamaija; Isomaa, Bo; Hunter, David J; Qi, Lu; Shuldiner, Alan R; Roden, Michael; Barroso, Ines; Wilsgaard, Tom; Beilby, John; Hovingh, Kees; Price, Jackie F; Wilson, James F; Rauramaa, Rainer; Lakka, Timo A; Lind, Lars; Dedoussis, George; Njølstad, Inger; Pedersen, Nancy L; Khaw, Kay-Tee; Wareham, Nicholas J; Keinanen-Kiukaanniemi, Sirkka M; Saaristo, Timo E; Korpi-Hyövälti, Eeva; Saltevo, Juha; Laakso, Markku; Kuusisto, Johanna; Metspalu, Andres; Collins, Francis S; Mohlke, Karen L; Bergman, Richard N; Tuomilehto, Jaakko; Boehm, Bernhard O; Gieger, Christian; Hveem, Kristian; Cauchi, Stephane; Froguel, Philippe; Baldassarre, Damiano; Tremoli, Elena; Humphries, Steve E; Saleheen, Danish; Danesh, John; Ingelsson, Erik; Ripatti, Samuli; Salomaa, Veikko; Erbel, Raimund; Jöckel, Karl-Heinz; Moebus, Susanne; Peters, Annette; Illig, Thomas; de Faire, Ulf; Hamsten, Anders; Morris, Andrew D; Donnelly, Peter J; Frayling, Timothy M; Hattersley, Andrew T; Boerwinkle, Eric; Melander, Olle; Kathiresan, Sekar; Nilsson, Peter M; Deloukas, Panos; Thorsteinsdottir, Unnur; Groop, Leif C; Stefansson, Kari; Hu, Frank; Pankow, James S; Dupuis, Josée; Meigs, James B; Altshuler, David; Boehnke, Michael; McCarthy, Mark I
2012-01-01
To extend understanding of the genetic architecture and molecular basis of type 2 diabetes (T2D), we conducted a meta-analysis of genetic variants on the Metabochip involving 34,840 cases and 114,981 controls, overwhelmingly of European descent. We identified ten previously unreported T2D susceptibility loci, including two demonstrating sex-differentiated association. Genome-wide analyses of these data are consistent with a long tail of further common variant loci explaining much of the variation in susceptibility to T2D. Exploration of the enlarged set of susceptibility loci implicates several processes, including CREBBP-related transcription, adipocytokine signalling and cell cycle regulation, in diabetes pathogenesis. PMID:22885922
Sun, Lidan; Wang, Yaqun; Yan, Xiaolan; Cheng, Tangren; Ma, Kaifeng; Yang, Weiru; Pan, Huitang; Zheng, Chengfei; Zhu, Xuli; Wang, Jia; Wu, Rongling; Zhang, Qixiang
2014-01-01
Mei, Prunus mume Sieb. et Zucc., is an ornamental plant popular in East Asia and, as an important member of genus Prunus, has played a pivotal role in systematic studies of the Rosaceae. However, the genetic architecture of botanical traits in this species remains elusive. This paper represents the first genome-wide mapping study of quantitative trait loci (QTLs) that affect stem growth and form, leaf morphology and leaf anatomy in an intraspecific cross derived from two different mei cultivars. Genetic mapping based on a high-density linkage map constricted from 120 SSRs and 1,484 SNPs led to the detection of multiple QTLs for each trait, some of which exert pleiotropic effects on correlative traits. Each QTL explains 3-12% of the phenotypic variance. Several leaf size traits were found to share common QTLs, whereas growth-related traits and plant form traits might be controlled by a different set of QTLs. Our findings provide unique insights into the genetic control of tree growth and architecture in mei and help to develop an efficient breeding program for selecting superior mei cultivars.
Runaway sexual selection leads to good genes.
Chandler, Christopher H; Ofria, Charles; Dworkin, Ian
2013-01-01
Mate choice and sexual displays are widespread in nature, but their evolutionary benefits remain controversial. Theory predicts these traits can be favored by runaway sexual selection, in which preference and display reinforce one another due to genetic correlation; or by good genes benefits, in which mate choice is advantageous because extreme displays indicate a well-adapted genotype. However, these hypotheses are not mutually exclusive, and the adaptive benefits underlying mate choice can themselves evolve. In particular, examining how and why sexual displays become indicators of good genes is challenging in natural systems. Here, we use experimental evolution in "digital organisms" to demonstrate the origins of condition-dependent indicator displays following their spread due to a runaway process. Surprisingly, handicap-like costs are not necessary for displays to become indicators of male viability. Instead, a pleiotropic genetic architecture underlies both displays and viability. Runaway sexual selection and good genes benefits should thus be viewed as interacting mechanisms that reinforce one another. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.
Molecular basis of angiosperm tree architecture
USDA-ARS?s Scientific Manuscript database
The shoot architecture of trees greatly impacts orchard and forest management methods. Amassing greater knowledge of the molecular genetics behind tree form can benefit these industries as well as contribute to basic knowledge of plant developmental biology. This review covers basic components of ...
Kawajiri, Maiko; Fujimoto, Shingo; Yoshida, Kohta; Yamahira, Kazunori; Kitano, Jun
2015-10-28
Traits involved in reproduction evolve rapidly and show great diversity among closely related species. However, the genetic mechanisms that underlie the diversification of courtship traits are mostly unknown. Japanese medaka fishes (Oryzias latipes) use anal fins to attract females and to grasp females during courtship; the males have longer anal fins with male-specific ossified papillary processes on the fin rays. However, anal fin morphology varies between populations: the southern populations tend to have longer anal fins and more processes than the northern populations. In the present study, we conducted quantitative trait locus (QTL) mapping to investigate the genetic architecture underlying the variation in the number of papillary processes of Japanese medaka fish and compared the QTL with previously identified QTL controlling anal fin length. First, we found that only a few QTL were shared between anal fin length and papillary process number. Second, we found that the numbers of papillary processes on different fin rays often were controlled by different QTL. Finally, we produced another independent cross and found that some QTL were repeatable between the two crosses, whereas others were specific to only one cross. These results suggest that variation in the number of papillary processes is polygenic and controlled by QTL that are distinct from those controlling anal fin length. Thus, different courtship traits in Japanese medaka share a small number of QTL and have the potential for independent evolution. Copyright © 2015 Kawajiri et al.
Elucidating the genetic architecture of Adams-Oliver syndrome in a large European cohort.
Meester, Josephina A N; Sukalo, Maja; Schröder, Kim C; Schanze, Denny; Baynam, Gareth; Borck, Guntram; Bramswig, Nuria C; Duman, Duygu; Gilbert-Dussardier, Brigitte; Holder-Espinasse, Muriel; Itin, Peter; Johnson, Diana S; Joss, Shelagh; Koillinen, Hannele; McKenzie, Fiona; Morton, Jenny; Nelle, Heike; Reardon, Willie; Roll, Claudia; Salih, Mustafa A; Savarirayan, Ravi; Scurr, Ingrid; Splitt, Miranda; Thompson, Elizabeth; Titheradge, Hannah; Travers, Colm P; Van Maldergem, Lionel; Whiteford, Margo; Wieczorek, Dagmar; Vandeweyer, Geert; Trembath, Richard; Van Laer, Lut; Loeys, Bart L; Zenker, Martin; Southgate, Laura; Wuyts, Wim
2018-06-20
Adams-Oliver syndrome (AOS) is a rare developmental disorder, characterized by scalp aplasia cutis congenita (ACC) and transverse terminal limb defects (TTLD). Autosomal dominant forms of AOS are linked to mutations in ARHGAP31, DLL4, NOTCH1 or RBPJ, while DOCK6 and EOGT underlie autosomal recessive inheritance. Data on the frequency and distribution of mutations in large cohorts is currently limited. The purpose of this study was therefore to comprehensively examine the genetic architecture of AOS in an extensive cohort. Molecular diagnostic screening of 194 AOS/ACC/TTLD probands/families was conducted using next-generation and/or capillary sequencing analyses. In total, we identified 63 (likely) pathogenic mutations, comprising 56 distinct and 22 novel mutations, providing a molecular diagnosis in 30% of patients. Taken together with previous reports, these findings bring the total number of reported disease variants to 63, with a diagnostic yield of 36% in familial cases. NOTCH1 is the major contributor, underlying 10% of AOS/ACC/TTLD cases, with DLL4 (6%), DOCK6 (6%), ARHGAP31 (3%), EOGT (3%), and RBPJ (2%) representing additional causality in this cohort. We confirm the relevance of genetic screening across the AOS/ACC/TTLD spectrum, highlighting preliminary but important genotype-phenotype correlations. This cohort offers potential for further gene identification to address missing heritability. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
Understanding epigenetic architecture of suicide neurobiology: A critical perspective
Roy, Bhaskar; Dwivedi, Yogesh
2016-01-01
Current understanding of environmental cross-talk with genetic makeup is found to be mediated through an epigenetic interface which is associated with prominent reversible and heritable changes at gene expression level. Recent emergence of epigenetic modulation in shaping the genetic information has become a key regulatory factor in answering the underlying complexities associated with several mental disorders. A comprehensive understanding of the pertinent changes in the epigenetic makeup of suicide phenotype exhibits a characteristic signature with the possibility of using it as a biomarker to help predict the risk factors associated with suicide. Within the scope of this current review, the most sought after epigenetic changes of DNA methylation and histone modification are thoroughly scrutinized to understand their close functional association with the broad spectrum of suicide phenotype. PMID:27836463
Fan, Yu; Xi, Liu; Hughes, Daniel S T; Zhang, Jianjun; Zhang, Jianhua; Futreal, P Andrew; Wheeler, David A; Wang, Wenyi
2016-08-24
Subclonal mutations reveal important features of the genetic architecture of tumors. However, accurate detection of mutations in genetically heterogeneous tumor cell populations using next-generation sequencing remains challenging. We develop MuSE ( http://bioinformatics.mdanderson.org/main/MuSE ), Mutation calling using a Markov Substitution model for Evolution, a novel approach for modeling the evolution of the allelic composition of the tumor and normal tissue at each reference base. MuSE adopts a sample-specific error model that reflects the underlying tumor heterogeneity to greatly improve the overall accuracy. We demonstrate the accuracy of MuSE in calling subclonal mutations in the context of large-scale tumor sequencing projects using whole exome and whole genome sequencing.
Speech and Language: Translating the Genome.
Deriziotis, Pelagia; Fisher, Simon E
2017-09-01
Investigation of the biological basis of human speech and language is being transformed by developments in molecular technologies, including high-throughput genotyping and next-generation sequencing of whole genomes. These advances are shedding new light on the genetic architecture underlying language-related disorders (speech apraxia, specific language impairment, developmental dyslexia) as well as that contributing to variation in relevant skills in the general population. We discuss how state-of-the-art methods are uncovering a range of genetic mechanisms, from rare mutations of large effect to common polymorphisms that increase risk in a subtle way, while converging on neurogenetic pathways that are shared between distinct disorders. We consider the future of the field, highlighting the unusual challenges and opportunities associated with studying genomics of language-related traits. Copyright © 2017 Elsevier Ltd. All rights reserved.
Edla, Damodar Reddy; Kuppili, Venkatanareshbabu; Dharavath, Ramesh; Beechu, Nareshkumar Reddy
2017-01-01
Low-power wearable devices for disease diagnosis are used at anytime and anywhere. These are non-invasive and pain-free for the better quality of life. However, these devices are resource constrained in terms of memory and processing capability. Memory constraint allows these devices to store a limited number of patterns and processing constraint provides delayed response. It is a challenging task to design a robust classification system under above constraints with high accuracy. In this Letter, to resolve this problem, a novel architecture for weightless neural networks (WNNs) has been proposed. It uses variable sized random access memories to optimise the memory usage and a modified binary TRIE data structure for reducing the test time. In addition, a bio-inspired-based genetic algorithm has been employed to improve the accuracy. The proposed architecture is experimented on various disease datasets using its software and hardware realisations. The experimental results prove that the proposed architecture achieves better performance in terms of accuracy, memory saving and test time as compared to standard WNNs. It also outperforms in terms of accuracy as compared to conventional neural network-based classifiers. The proposed architecture is a powerful part of most of the low-power wearable devices for the solution of memory, accuracy and time issues. PMID:28868148
Su, Junji; Li, Libei; Zhang, Chi; Wang, Caixiang; Gu, Lijiao; Wang, Hantao; Wei, Hengling; Liu, Qibao; Huang, Long; Yu, Shuxun
2018-06-01
Thirty significant associations between 22 SNPs and five plant architecture component traits in Chinese upland cotton were identified via GWAS. Four peak SNP loci located on chromosome D03 were simultaneously associated with more plant architecture component traits. A candidate gene, Gh_D03G0922, might be responsible for plant height in upland cotton. A compact plant architecture is increasingly required for mechanized harvesting processes in China. Therefore, cotton plant architecture is an important trait, and its components, such as plant height, fruit branch length and fruit branch angle, affect the suitability of a cultivar for mechanized harvesting. To determine the genetic basis of cotton plant architecture, a genome-wide association study (GWAS) was performed using a panel composed of 355 accessions and 93,250 single nucleotide polymorphisms (SNPs) identified using the specific-locus amplified fragment sequencing method. Thirty significant associations between 22 SNPs and five plant architecture component traits were identified via GWAS. Most importantly, four peak SNP loci located on chromosome D03 were simultaneously associated with more plant architecture component traits, and these SNPs were harbored in one linkage disequilibrium block. Furthermore, 21 candidate genes for plant architecture were predicted in a 0.95-Mb region including the four peak SNPs. One of these genes (Gh_D03G0922) was near the significant SNP D03_31584163 (8.40 kb), and its Arabidopsis homologs contain MADS-box domains that might be involved in plant growth and development. qRT-PCR showed that the expression of Gh_D03G0922 was upregulated in the apical buds and young leaves of the short and compact cotton varieties, and virus-induced gene silencing (VIGS) proved that the silenced plants exhibited increased PH. These results indicate that Gh_D03G0922 is likely the candidate gene for PH in cotton. The genetic variations and candidate genes identified in this study lay a foundation for cultivating moderately short and compact varieties in future Chinese cotton-breeding programs.
Reptiles: a new model for brain evo-devo research.
Nomura, Tadashi; Kawaguchi, Masahumi; Ono, Katsuhiko; Murakami, Yasunori
2013-03-01
Vertebrate brains exhibit vast amounts of anatomical diversity. In particular, the elaborate and complex nervous system of amniotes is correlated with the size of their behavioral repertoire. However, the evolutionary mechanisms underlying species-specific brain morphogenesis remain elusive. In this review we introduce reptiles as a new model organism for understanding brain evolution. These animal groups inherited ancestral traits of brain architectures. We will describe several unique aspects of the reptilian nervous system with a special focus on the telencephalon, and discuss the genetic mechanisms underlying reptile-specific brain morphology. The establishment of experimental evo-devo approaches to studying reptiles will help to shed light on the origin of the amniote brains. Copyright © 2013 Wiley Periodicals, Inc.
Fang, Lingzhao; Sahana, Goutam; Ma, Peipei; Su, Guosheng; Yu, Ying; Zhang, Shengli; Lund, Mogens Sandø; Sørensen, Peter
2017-08-10
A better understanding of the genetic architecture underlying complex traits (e.g., the distribution of causal variants and their effects) may aid in the genomic prediction. Here, we hypothesized that the genomic variants of complex traits might be enriched in a subset of genomic regions defined by genes grouped on the basis of "Gene Ontology" (GO), and that incorporating this independent biological information into genomic prediction models might improve their predictive ability. Four complex traits (i.e., milk, fat and protein yields, and mastitis) together with imputed sequence variants in Holstein (HOL) and Jersey (JER) cattle were analysed. We first carried out a post-GWAS analysis in a HOL training population to assess the degree of enrichment of the association signals in the gene regions defined by each GO term. We then extended the genomic best linear unbiased prediction model (GBLUP) to a genomic feature BLUP (GFBLUP) model, including an additional genomic effect quantifying the joint effect of a group of variants located in a genomic feature. The GBLUP model using a single random effect assumes that all genomic variants contribute to the genomic relationship equally, whereas GFBLUP attributes different weights to the individual genomic relationships in the prediction equation based on the estimated genomic parameters. Our results demonstrate that the immune-relevant GO terms were more associated with mastitis than milk production, and several biologically meaningful GO terms improved the prediction accuracy with GFBLUP for the four traits, as compared with GBLUP. The improvement of the genomic prediction between breeds (the average increase across the four traits was 0.161) was more apparent than that it was within the HOL (the average increase across the four traits was 0.020). Our genomic feature modelling approaches provide a framework to simultaneously explore the genetic architecture and genomic prediction of complex traits by taking advantage of independent biological knowledge.
Choline Metabolites: Gene by Diet Interactions
Smallwood, Tangi; Allayee, Hooman; Bennett, Brian J.
2015-01-01
Purpose of review This review highlights recent advances in our understanding of the interactions between genetic polymorphisms in genes that metabolize choline and the dietary requirements of choline and how these interactions relate to human health and disease. Recent findings The importance of choline as an essential nutrient has been well established but our appreciation of the interaction between our underlying genetic architecture and dietary choline requirements is only beginning. It has been shown in both human and animal studies that choline deficiencies contribute to diseases such as non-alcoholic fatty liver disease and various neurodegenerative diseases. An adequate supply of dietary choline is important for optimum development, highlighted by the increased maternal requirements during fetal development and in breast-fed infants. We discuss recent studies investigating variants in PEMT and MTHFR1 that are associated with a variety of birth defects. In addition to genetic interactions, we discuss several recent studies that uncover changes in fetal global methylation patterns in response to maternal dietary choline intake that result in changes in gene expression in the offspring. In contrast to the developmental role of adequate choline, there is now an appreciation of the role choline has in cardiovascular disease through the gut microbiota-mediated metabolite trimethylamine N-oxide. This pathway highlights some of our understanding of how the microbiome affects nutrient processing and bioavailability. Finally, in order to better characterize the genetic architecture regulating choline requirements, we discuss recent results focused on identifying polymorphisms that regulate choline and its derivative products. Summary Here we discuss recent studies that have advanced our understanding of how specific alleles in key choline metabolism genes are related to dietary choline requirements and human disease. PMID:26655287
Epistatic Effects Contribute to Variation in BMD in Fischer 344 × Lewis F2 Rats
Koller, Daniel L; Liu, Lixiang; Alam, Imranul; Sun, Qiwei; Econs, Michael J; Foroud, Tatiana; Turner, Charles H
2008-01-01
To further delineate the factors underlying the complex genetic architecture of BMD in the rat model, a genome screen for epistatic interactions was conducted. Several significant interactions were identified, involving both previously identified and novel QTLs. Introduction The variation in several of the risk factors for osteoporotic fracture, including BMD, has been shown to be caused largely by genetic differences. However, the genetic architecture of BMD is complex in both humans and in model organisms. We have previously reported quantitative trait locus (QTL) results for BMD from a genome screen of 595 female F2 progeny of Fischer 344 and Lewis rats. These progeny also provide an excellent opportunity to search for epistatic effects, or interaction between genetic loci, that contribute to fracture risk. Materials and Methods Microsatellite marker data from a 20-cM genome screen was analyzed along with weight-adjusted BMD (DXA and pQCT) phenotypic data using the R/qtl software package. Genotype and phenotype data were permuted to determine a genome-wide significance threshold for the epistasis or interaction LOD score corresponding to an α level of 0.01. Results and Conclusions Novel loci on chromosomes 12 and 15 showed a strong epistatic effect on total BMD at the femoral midshaft by pQCT (LOD = 5.4). A previously reported QTL on chromosome 7 was found to interact with a novel locus on chromosome 20 to affect whole lumbar BMD by pQCT (LOD = 6.2). These results provide new information regarding the mode of action of previously identified rat QTLs, as well as identifying novel loci that act in combination with known QTLs or with other novel loci to contribute to the risk factors for osteoporotic fracture. PMID:17907919
Epistatic effects contribute to variation in BMD in Fischer 344 x Lewis F2 rats.
Koller, Daniel L; Liu, Lixiang; Alam, Imranul; Sun, Qiwei; Econs, Michael J; Foroud, Tatiana; Turner, Charles H
2008-01-01
To further delineate the factors underlying the complex genetic architecture of BMD in the rat model, a genome screen for epistatic interactions was conducted. Several significant interactions were identified, involving both previously identified and novel QTLs. The variation in several of the risk factors for osteoporotic fracture, including BMD, has been shown to be caused largely by genetic differences. However, the genetic architecture of BMD is complex in both humans and in model organisms. We have previously reported quantitative trait locus (QTL) results for BMD from a genome screen of 595 female F(2) progeny of Fischer 344 and Lewis rats. These progeny also provide an excellent opportunity to search for epistatic effects, or interaction between genetic loci, that contribute to fracture risk. Microsatellite marker data from a 20-cM genome screen was analyzed along with weight-adjusted BMD (DXA and pQCT) phenotypic data using the R/qtl software package. Genotype and phenotype data were permuted to determine a genome-wide significance threshold for the epistasis or interaction LOD score corresponding to an alpha level of 0.01. Novel loci on chromosomes 12 and 15 showed a strong epistatic effect on total BMD at the femoral midshaft by pQCT (LOD = 5.4). A previously reported QTL on chromosome 7 was found to interact with a novel locus on chromosome 20 to affect whole lumbar BMD by pQCT (LOD = 6.2). These results provide new information regarding the mode of action of previously identified rat QTLs, as well as identifying novel loci that act in combination with known QTLs or with other novel loci to contribute to the risk factors for osteoporotic fracture.
Pharmacological Validation of Candidate Causal Sleep Genes Identified in an N2 Cross
Brunner, Joseph I.; Gotter, Anthony L.; Millstein, Joshua; Garson, Susan; Binns, Jacquelyn; Fox, Steven V.; Savitz, Alan T.; Yang, He S.; Fitzpatrick, Karrie; Zhou, Lili; Owens, Joseph R.; Webber, Andrea L.; Vitaterna, Martha H.; Kasarskis, Andrew; Uebele, Victor N.; Turek, Fred; Renger, John J.; Winrow, Christopher J.
2013-01-01
Despite the substantial impact of sleep disturbances on human health and the many years of study dedicated to understanding sleep pathologies, the underlying genetic mechanisms that govern sleep and wake largely remain unknown. Recently, we completed large scale genetic and gene expression analyses in a segregating inbred mouse cross and identified candidate causal genes that regulate the mammalian sleep-wake cycle, across multiple traits including total sleep time, amounts of REM, non-REM, sleep bout duration and sleep fragmentation. Here we describe a novel approach toward validating candidate causal genes, while also identifying potential targets for sleep-related indications. Select small molecule antagonists and agonists were used to interrogate candidate causal gene function in rodent sleep polysomnography assays to determine impact on overall sleep architecture and to evaluate alignment with associated sleep-wake traits. Significant effects on sleep architecture were observed in validation studies using compounds targeting the muscarinic acetylcholine receptor M3 subunit (Chrm3)(wake promotion), nicotinic acetylcholine receptor alpha4 subunit (Chrna4)(wake promotion), dopamine receptor D5 subunit (Drd5)(sleep induction), serotonin 1D receptor (Htr1d)(altered REM fragmentation), glucagon-like peptide-1 receptor (Glp1r)(light sleep promotion and reduction of deep sleep), and Calcium channel, voltage-dependent, T type, alpha 1I subunit (Cacna1i)(increased bout duration slow wave sleep). Taken together, these results show the complexity of genetic components that regulate sleep-wake traits and highlight the importance of evaluating this complex behavior at a systems level. Pharmacological validation of genetically identified putative targets provides a rapid alternative to generating knock out or transgenic animal models, and may ultimately lead towards new therapeutic opportunities. PMID:22091728
The genetic architecture of coronary artery disease: current knowledge and future opportunities
USDA-ARS?s Scientific Manuscript database
Recent Findings Large-scale studies in human populations, coupled with rapid advances in genetic technologies over the last decade, have clearly established the association of common genetic variation with risk of CAD. However, the effect sizes of the susceptibility alleles are for the most part mod...
USDA-ARS?s Scientific Manuscript database
Genome-wide association studies (GWAS) are a powerful method to dissect the genetic basis of traits, though in practice the effects of complex genetic architecture and population structure remain poorly understood. To compare mapping strategies we dissect the genetic control of flavonoid pigmentatio...
An analysis of genetic architecture in populations of Ponderosa Pine
Yan B. Linhart; Jeffry B. Mitton; Kareen B. Sturgeon; Martha L. Davis
1981-01-01
Patterns of genetic variation were studied in three populations of ponderosa pine in Colorado by using electrophoretically variable protein loci. Significant genetic differences were found between separate clusters of trees and between age classes within populations. In addition, data indicate that differential cone production and differential animal damage have...
Bustamante, M Leonor; Herrera, Luisa; Gaspar, Pablo A; Nieto, Rodrigo; Maturana, Alejandro; Villar, María José; Salinas, Valeria; Silva, Hernán
2017-10-01
Schizophrenia (SZ) is a disorder with a high heritability and a complex architecture. Several dozen genetic variants have been identified as risk factors through genome-wide association studies including large population-based samples. However, the bulk of the risk cannot be accounted for by the genes associated to date. Rare mutations have been historically seen as relevant only for some infrequent, Mendelian forms of psychosis. Recent findings, however, show that the subset of patients that present a mutation with major effect is larger than expected. We discuss some of the molecular findings of these studies. SZ is clinically and genetically heterogeneous. To identify the genetic variation underlying the disorder, research should be focused on features that are more likely a product of genetic heterogeneity. Based on the phenotypical correlations with rare variants, cognition emerges as a relevant domain to study. Cognitive disturbances could be useful in selecting cases that have a higher probability of carrying deleterious mutations, as well as on the correct ascertainment of sporadic cases for the identification of de novo variants. © 2017 Wiley Periodicals, Inc.
Stift, M; Hunter, B D; Shaw, B; Adam, A; Hoebe, P N; Mable, B K
2013-01-01
Newly formed selfing lineages may express recessive genetic load and suffer inbreeding depression. This can have a genome-wide genetic basis, or be due to loci linked to genes under balancing selection. Understanding the genetic architecture of inbreeding depression is important in the context of the maintenance of self-incompatibility and understanding the evolutionary dynamics of S-alleles. We addressed this using North-American subspecies of Arabidopsis lyrata. This species is normally self-incompatible and outcrossing, but some populations have undergone a transition to selfing. The goals of this study were to: (1) quantify the strength of inbreeding depression in North-American populations of A. lyrata; and (2) disentangle the relative contribution of S-linked genetic load compared with overall inbreeding depression. We enforced selfing in self-incompatible plants with known S-locus genotype by treatment with CO2, and compared the performance of selfed vs outcrossed progeny. We found significant inbreeding depression for germination rate (δ=0.33), survival rate to 4 weeks (δ=0.45) and early growth (δ=0.07), but not for flowering rate. For two out of four S-alleles in our design, we detected significant S-linked load reflected by an under-representation of S-locus homozygotes in selfed progeny. The presence or absence of S-linked load could not be explained by the dominance level of S-alleles. Instead, the random nature of the mutation process may explain differences in the recessive deleterious load among lineages. PMID:22892638
A cellular, molecular, and pharmacological basis for appendage regeneration in mice
Leung, Thomas H.; Snyder, Emily R.; Liu, Yinghua; Wang, Jing; Kim, Seung K.
2015-01-01
Regenerative medicine aims to restore normal tissue architecture and function. However, the basis of tissue regeneration in mammalian solid organs remains undefined. Remarkably, mice lacking p21 fully regenerate injured ears without discernable scarring. Here we show that, in wild-type mice following tissue injury, stromal-derived factor-1 (Sdf1) is up-regulated in the wound epidermis and recruits Cxcr4-expressing leukocytes to the injury site. In p21-deficient mice, Sdf1 up-regulation and the subsequent recruitment of Cxcr4-expressing leukocytes are significantly diminished, thereby permitting scarless appendage regeneration. Lineage tracing demonstrates that this regeneration derives from fate-restricted progenitor cells. Pharmacological or genetic disruption of Sdf1–Cxcr4 signaling enhances tissue repair, including full reconstitution of tissue architecture and all cell types. Our findings identify signaling and cellular mechanisms underlying appendage regeneration in mice and suggest new therapeutic approaches for regenerative medicine. PMID:26494786
Xu, Bin; Woodroffe, Abigail; Rodriguez-Murillo, Laura; Roos, J. Louw; van Rensburg, Elizabeth J.; Abecasis, Gonçalo R.; Gogos, Joseph A.; Karayiorgou, Maria
2009-01-01
To elucidate the genetic architecture of familial schizophrenia we combine linkage analysis with studies of fine-level chromosomal variation in families recruited from the Afrikaner population in South Africa. We demonstrate that individually rare inherited copy number variants (CNVs) are more frequent in cases with familial schizophrenia as compared to unaffected controls and affect almost exclusively genic regions. Interestingly, we find that while the prevalence of rare structural variants is similar in familial and sporadic cases, the type of variants is markedly different. In addition, using a high-density linkage scan with a panel of nearly 2,000 markers, we identify a region on chromosome 13q34 that shows genome-wide significant linkage to schizophrenia and show that in the families not linked to this locus, there is evidence for linkage to chromosome 1p36. No causative CNVs were identified in either locus. Overall, our results from approaches designed to detect risk variants with relatively low frequency and high penetrance in a well-defined and relatively homogeneous population, provide strong empirical evidence supporting the notion that multiple genetic variants, including individually rare ones, that affect many different genes contribute to the genetic risk of familial schizophrenia. They also highlight differences in the genetic architecture of the familial and sporadic forms of the disease. PMID:19805367
Lucas, Lauren K; Nice, Chris C; Gompert, Zachariah
2018-03-13
Patterns of phenotypic variation within and among species can be shaped and constrained by trait genetic architecture. This is particularly true for complex traits, such as butterfly wing patterns, that consist of multiple elements. Understanding the genetics of complex trait variation across species boundaries is difficult, as it necessitates mapping in structured populations and can involve many loci with small or variable phenotypic effects. Here, we investigate the genetic architecture of complex wing pattern variation in Lycaeides butterflies as a case study of mapping multivariate traits in wild populations that include multiple nominal species or groups. We identify conserved modules of integrated wing pattern elements within populations and species. We show that trait covariances within modules have a genetic basis and thus represent genetic constraints that can channel evolution. Consistent with this, we find evidence that evolutionary changes in wing patterns among populations and species occur in the directions of genetic covariances within these groups. Thus, we show that genetic constraints affect patterns of biological diversity (wing pattern) in Lycaeides, and we provide an analytical template for similar work in other systems. © 2018 John Wiley & Sons Ltd.
Forest, Adriana R; Semeniuk, Christina A D; Heath, Daniel D; Pitcher, Trevor E
2016-08-01
Chinook salmon, Oncorhynchus tshawytscha, exhibit alternative reproductive tactics (ARTs) where males exist in two phenotypes: large "hooknose" males and smaller "jacks" that reach sexual maturity after only 1 year in seawater. The mechanisms that determine "jacking rate"-the rate at which males precociously sexually mature-are known to involve both genetics and differential growth rates, where individuals that become jacks exhibit higher growth earlier in life. The additive genetic components have been studied and it is known that jack sires produce significantly more jack offspring than hooknose sires, and vice versa. The current study was the first to investigate both additive and non-additive genetic components underlying jacking through the use of a full-factorial breeding design using all hooknose sires. The effect of dams and sires descendant from a marker-assisted broodstock program that identified "high performance" and "low performance" lines using growth- and survival-related gene markers was also studied. Finally, the relative growth of jack, hooknose, and female offspring was examined. No significant dam, sire, or interaction effects were observed in this study, and the maternal, additive, and non-additive components underlying jacking were small. Differences in jacking rates in this study were determined by dam performance line, where dams that originated from the low performance line produced significantly more jacks. Jack offspring in this study had a significantly larger body size than both hooknose males and females starting 1 year post-fertilization. This study provides novel information regarding the genetic architecture underlying ARTs in Chinook salmon that could have implications for the aquaculture industry, where jacks are not favoured due to their small body size and poor flesh quality.
Sandhu, Nitika; Raman, K. Anitha; Torres, Rolando O.; Audebert, Alain; Dardou, Audrey; Kumar, Arvind; Henry, Amelia
2016-01-01
Future rice (Oryza sativa) crops will likely experience a range of growth conditions, and root architectural plasticity will be an important characteristic to confer adaptability across variable environments. In this study, the relationship between root architectural plasticity and adaptability (i.e. yield stability) was evaluated in two traditional × improved rice populations (Aus 276 × MTU1010 and Kali Aus × MTU1010). Forty contrasting genotypes were grown in direct-seeded upland and transplanted lowland conditions with drought and drought + rewatered stress treatments in lysimeter and field studies and a low-phosphorus stress treatment in a Rhizoscope study. Relationships among root architectural plasticity for root dry weight, root length density, and percentage lateral roots with yield stability were identified. Selected genotypes that showed high yield stability also showed a high degree of root plasticity in response to both drought and low phosphorus. The two populations varied in the soil depth effect on root architectural plasticity traits, none of which resulted in reduced grain yield. Root architectural plasticity traits were related to 13 (Aus 276 population) and 21 (Kali Aus population) genetic loci, which were contributed by both the traditional donor parents and MTU1010. Three genomic loci were identified as hot spots with multiple root architectural plasticity traits in both populations, and one locus for both root architectural plasticity and grain yield was detected. These results suggest an important role of root architectural plasticity across future rice crop conditions and provide a starting point for marker-assisted selection for plasticity. PMID:27342311
Human Facial Shape and Size Heritability and Genetic Correlations.
Cole, Joanne B; Manyama, Mange; Larson, Jacinda R; Liberton, Denise K; Ferrara, Tracey M; Riccardi, Sheri L; Li, Mao; Mio, Washington; Klein, Ophir D; Santorico, Stephanie A; Hallgrímsson, Benedikt; Spritz, Richard A
2017-02-01
The human face is an array of variable physical features that together make each of us unique and distinguishable. Striking familial facial similarities underscore a genetic component, but little is known of the genes that underlie facial shape differences. Numerous studies have estimated facial shape heritability using various methods. Here, we used advanced three-dimensional imaging technology and quantitative human genetics analysis to estimate narrow-sense heritability, heritability explained by common genetic variation, and pairwise genetic correlations of 38 measures of facial shape and size in normal African Bantu children from Tanzania. Specifically, we fit a linear mixed model of genetic relatedness between close and distant relatives to jointly estimate variance components that correspond to heritability explained by genome-wide common genetic variation and variance explained by uncaptured genetic variation, the sum representing total narrow-sense heritability. Our significant estimates for narrow-sense heritability of specific facial traits range from 28 to 67%, with horizontal measures being slightly more heritable than vertical or depth measures. Furthermore, for over half of facial traits, >90% of narrow-sense heritability can be explained by common genetic variation. We also find high absolute genetic correlation between most traits, indicating large overlap in underlying genetic loci. Not surprisingly, traits measured in the same physical orientation (i.e., both horizontal or both vertical) have high positive genetic correlations, whereas traits in opposite orientations have high negative correlations. The complex genetic architecture of facial shape informs our understanding of the intricate relationships among different facial features as well as overall facial development. Copyright © 2017 by the Genetics Society of America.
Dudley, Joel T.; Chen, Rong; Sanderford, Maxwell; Butte, Atul J.; Kumar, Sudhir
2012-01-01
Genome-wide disease association studies contrast genetic variation between disease cohorts and healthy populations to discover single nucleotide polymorphisms (SNPs) and other genetic markers revealing underlying genetic architectures of human diseases. Despite scores of efforts over the past decade, many reproducible genetic variants that explain substantial proportions of the heritable risk of common human diseases remain undiscovered. We have conducted a multispecies genomic analysis of 5,831 putative human risk variants for more than 230 disease phenotypes reported in 2,021 studies. We find that the current approaches show a propensity for discovering disease-associated SNPs (dSNPs) at conserved genomic positions because the effect size (odds ratio) and allelic P value of genetic association of an SNP relates strongly to the evolutionary conservation of their genomic position. We propose a new measure for ranking SNPs that integrates evolutionary conservation scores and the P value (E-rank). Using published data from a large case-control study, we demonstrate that E-rank method prioritizes SNPs with a greater likelihood of bona fide and reproducible genetic disease associations, many of which may explain greater proportions of genetic variance. Therefore, long-term evolutionary histories of genomic positions offer key practical utility in reassessing data from existing disease association studies, and in the design and analysis of future studies aimed at revealing the genetic basis of common human diseases. PMID:22389448
Berger, David; You, Tao; Minano, Maravillas R; Grieshop, Karl; Lind, Martin I; Arnqvist, Göran; Maklakov, Alexei A
2016-05-13
Intralocus sexual conflict, arising from selection for different alleles at the same locus in males and females, imposes a constraint on sex-specific adaptation. Intralocus sexual conflict can be alleviated by the evolution of sex-limited genetic architectures and phenotypic expression, but pleiotropic constraints may hinder this process. Here, we explored putative intralocus sexual conflict and genetic (co)variance in a poorly understood behavior with near male-limited expression. Same-sex sexual behaviors (SSBs) generally do not conform to classic evolutionary models of adaptation but are common in male animals and have been hypothesized to result from perception errors and selection for high male mating rates. However, perspectives incorporating sex-specific selection on genes shared by males and females to explain the expression and evolution of SSBs have largely been neglected. We performed two parallel sex-limited artificial selection experiments on SSB in male and female seed beetles, followed by sex-specific assays of locomotor activity and male sex recognition (two traits hypothesized to be functionally related to SSB) and adult reproductive success (allowing us to assess fitness consequences of genetic variance in SSB and its correlated components). Our experiments reveal both shared and sex-limited genetic variance for SSB. Strikingly, genetically correlated responses in locomotor activity and male sex-recognition were associated with sexually antagonistic fitness effects, but these effects differed qualitatively between male and female selection lines, implicating intralocus sexual conflict at both male- and female-specific genetic components underlying SSB. Our study provides experimental support for the hypothesis that widespread pleiotropy generates pervasive intralocus sexual conflict governing the expression of SSBs, suggesting that SSB in one sex can occur due to the expression of genes that carry benefits in the other sex.
Panmictic and Clonal Evolution on a Single Patchy Resource Produces Polymorphic Foraging Guilds
Getz, Wayne M.; Salter, Richard; Lyons, Andrew J.; Sippl-Swezey, Nicolas
2015-01-01
We develop a stochastic, agent-based model to study how genetic traits and experiential changes in the state of agents and available resources influence individuals’ foraging and movement behaviors. These behaviors are manifest as decisions on when to stay and exploit a current resource patch or move to a particular neighboring patch, based on information of the resource qualities of the patches and the anticipated level of intraspecific competition within patches. We use a genetic algorithm approach and an individual’s biomass as a fitness surrogate to explore the foraging strategy diversity of evolving guilds under clonal versus hermaphroditic sexual reproduction. We first present the resource exploitation processes, movement on cellular arrays, and genetic algorithm components of the model. We then discuss their implementation on the Nova software platform. This platform seamlessly combines the dynamical systems modeling of consumer-resource interactions with agent-based modeling of individuals moving over a landscapes, using an architecture that lays transparent the following four hierarchical simulation levels: 1.) within-patch consumer-resource dynamics, 2.) within-generation movement and competition mitigation processes, 3.) across-generation evolutionary processes, and 4.) multiple runs to generate the statistics needed for comparative analyses. The focus of our analysis is on the question of how the biomass production efficiency and the diversity of guilds of foraging strategy types, exploiting resources over a patchy landscape, evolve under clonal versus random hermaphroditic sexual reproduction. Our results indicate greater biomass production efficiency under clonal reproduction only at higher population densities, and demonstrate that polymorphisms evolve and are maintained under random mating systems. The latter result questions the notion that some type of associative mating structure is needed to maintain genetic polymorphisms among individuals exploiting a common patchy resource on an otherwise spatially homogeneous landscape. PMID:26274613
Getting to the roots of it: Genetic and hormonal control of root architecture
Jung, Janelle K. H.; McCouch, Susan
2013-01-01
Root system architecture (RSA) – the spatial configuration of a root system – is an important developmental and agronomic trait, with implications for overall plant architecture, growth rate and yield, abiotic stress resistance, nutrient uptake, and developmental plasticity in response to environmental changes. Root architecture is modulated by intrinsic, hormone-mediated pathways, intersecting with pathways that perceive and respond to external, environmental signals. The recent development of several non-invasive 2D and 3D root imaging systems has enhanced our ability to accurately observe and quantify architectural traits on complex whole-root systems. Coupled with the powerful marker-based genotyping and sequencing platforms currently available, these root phenotyping technologies lend themselves to large-scale genome-wide association studies, and can speed the identification and characterization of the genes and pathways involved in root system development. This capability provides the foundation for examining the contribution of root architectural traits to the performance of crop varieties in diverse environments. This review focuses on our current understanding of the genes and pathways involved in determining RSA in response to both intrinsic and extrinsic (environmental) response pathways, and provides a brief overview of the latest root system phenotyping technologies and their potential impact on elucidating the genetic control of root development in plants. PMID:23785372
Mapping complex traits as a dynamic system
Sun, Lidan; Wu, Rongling
2017-01-01
Despite increasing emphasis on the genetic study of quantitative traits, we are still far from being able to chart a clear picture of their genetic architecture, given an inherent complexity involved in trait formation. A competing theory for studying such complex traits has emerged by viewing their phenotypic formation as a “system” in which a high-dimensional group of interconnected components act and interact across different levels of biological organization from molecules through cells to whole organisms. This system is initiated by a machinery of DNA sequences that regulate a cascade of biochemical pathways to synthesize endophenotypes and further assemble these endophenotypes toward the end-point phenotype in virtue of various developmental changes. This review focuses on a conceptual framework for genetic mapping of complex traits by which to delineate the underlying components, interactions and mechanisms that govern the system according to biological principles and understand how these components function synergistically under the control of quantitative trait loci (QTLs) to comprise a unified whole. This framework is built by a system of differential equations that quantifies how alterations of different components lead to the global change of trait development and function, and provides a quantitative and testable platform for assessing the multiscale interplay between QTLs and development. The method will enable geneticists to shed light on the genetic complexity of any biological system and predict, alter or engineer its physiological and pathological states. PMID:25772476
Lee, Yuh Chwen G; Yang, Qian; Chi, Wanhao; Turkson, Susie A; Du, Wei A; Kemkemer, Claus; Zeng, Zhao-Bang; Long, Manyuan; Zhuang, Xiaoxi
2017-05-01
Foraging behavior is critical for the fitness of individuals. However, the genetic basis of variation in foraging behavior and the evolutionary forces underlying such natural variation have rarely been investigated. We developed a systematic approach to assay the variation in survival rate in a foraging environment for adult flies derived from a wild Drosophila melanogaster population. Despite being such an essential trait, there is substantial variation of foraging behavior among D. melanogaster strains. Importantly, we provided the first evaluation of the potential caveats of using inbred Drosophila strains to perform genome-wide association studies on life-history traits, and concluded that inbreeding depression is unlikely a major contributor for the observed large variation in adult foraging behavior. We found that adult foraging behavior has a strong genetic component and, unlike larval foraging behavior, depends on multiple loci. Identified candidate genes are enriched in those with high expression in adult heads and, demonstrated by expression knock down assay, are involved in maintaining normal functions of the nervous system. Our study not only identified candidate genes for foraging behavior that is relevant to individual fitness, but also shed light on the initial stage underlying the evolution of the behavior. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
The gene-environmental architecture of the development of adolescent substance use.
Vitaro, Frank; Dickson, Daniel J; Brendgen, Mara; Laursen, Brett; Dionne, Ginette; Boivin, Michel
2018-02-19
Using a longitudinal twin design and a latent growth curve/autoregressive approach, this study examined the genetic-environmental architecture of substance use across adolescence. Self-reports of substance use (i.e. alcohol, marijuana) were collected at ages 13, 14, 15, and 17 years from 476 twin pairs (475 boys, 477 girls) living in the Province of Quebec, Canada. Substance use increased linearly across the adolescent years. ACE modeling revealed that genetic, as well as shared and non-shared environmental factors explained the overall level of substance use and that these same factors also partly accounted for growth in substance use from age 13 to 17. Additional genetic factors predicted the growth in substance use. Finally, autoregressive effects revealed age-specific non-shared environmental influences and, to a lesser degree, age-specific genetic influences, which together accounted for the stability of substance use across adolescence. The results support and expand the notion that genetic and environmental influences on substance use during adolescence are both developmentally stable and developmentally dynamic.
Silventoinen, Karri; Kaprio, Jaakko; Yokoyama, Yoshie
2011-03-01
We analyzed the genetic architecture of prepubertal development of relative weight to height in 216 monozygotic and 159 dizygotic complete Japanese twin pairs (52% girls). Ponderal index at birth (kg/m(3)) and body mass index (BMI, kg/m(2)) from 1 to 11 years of age were used. Additive genetic factors explained the major proportion (52-74%) of the variation of BMI from 1 to 11 years of age. Environmental factors common to both co-twins also showed some effect (7-28%), but at most ages this was not statistically significant. Strong genetic tracking was found for BMI from 1 to 11 years of age, but there was also evidence for a persistent effect of common environmental factors. Our results suggest that the genetic architecture of BMI development in the Japanese population is generally similar to that found in previous twin studies in Caucasian populations.
Twin studies advance the understanding of gene-environment interplay in human nutrigenomics.
Pallister, Tess; Spector, Tim D; Menni, Cristina
2014-12-01
Investigations into the genetic architecture of diet-disease relationships are particularly relevant today with the global epidemic of obesity and chronic disease. Twin studies have demonstrated that genetic makeup plays a significant role in a multitude of dietary phenotypes such as energy and macronutrient intakes, dietary patterns, and specific food group intakes. Besides estimating heritability of dietary assessment, twins provide a naturally unique, case-control experiment. Due to their shared upbringing, matched genes and sex (in the case of monozygotic (MZ) twin pairs), and age, twins provide many advantages over classic epidemiological approaches. Future genetic epidemiological studies could benefit from the twin approach particularly where defining what is 'normal' is problematic due to the high inter-individual variability underlying metabolism. Here, we discuss the use of twins to generate heritability estimates of food intake phenotypes. We then highlight the value of discordant MZ pairs to further nutrition research through discovery and validation of biomarkers of intake and health status in collaboration with cutting-edge omics technologies.
Genetic architecture of artemisinin-resistant Plasmodium falciparum
Miotto, Olivo; Amato, Roberto; Ashley, Elizabeth A; MacInnis, Bronwyn; Almagro-Garcia, Jacob; Amaratunga, Chanaki; Lim, Pharath; Mead, Daniel; Oyola, Samuel O; Dhorda, Mehul; Imwong, Mallika; Woodrow, Charles; Manske, Magnus; Stalker, Jim; Drury, Eleanor; Campino, Susana; Amenga-Etego, Lucas; Thanh, Thuy-Nhien Nguyen; Tran, Hien Tinh; Ringwald, Pascal; Bethell, Delia; Nosten, Francois; Phyo, Aung Pyae; Pukrittayakamee, Sasithon; Chotivanich, Kesinee; Chuor, Char Meng; Nguon, Chea; Suon, Seila; Sreng, Sokunthea; Newton, Paul N; Mayxay, Mayfong; Khanthavong, Maniphone; Hongvanthong, Bouasy; Htut, Ye; Han, Kay Thwe; Kyaw, Myat Phone; Faiz, Md Abul; Fanello, Caterina I; Onyamboko, Marie; Mokuolu, Olugbenga A; Jacob, Christopher G; Takala-Harrison, Shannon; Plowe, Christopher V; Day, Nicholas P; Dondorp, Arjen M; Spencer, Chris C A; McVean, Gilean; Fairhurst, Rick M; White, Nicholas J; Kwiatkowski, Dominic P
2015-01-01
We report a large multicenter genome-wide association study of Plasmodium falciparum resistance to artemisinin, the frontline antimalarial drug. Across 15 locations in Southeast Asia, we identified at least 20 mutations in kelch13 (PF3D7_1343700) affecting the encoded propeller and BTB/POZ domains, which were associated with a slow parasite clearance rate after treatment with artemisinin derivatives. Nonsynonymous polymorphisms in fd (ferredoxin), arps10 (apicoplast ribosomal protein S10), mdr2 (multidrug resistance protein 2) and crt (chloroquine resistance transporter) also showed strong associations with artemisinin resistance. Analysis of the fine structure of the parasite population showed that the fd, arps10, mdr2 and crt polymorphisms are markers of a genetic background on which kelch13 mutations are particularly likely to arise and that they correlate with the contemporary geographical boundaries and population frequencies of artemisinin resistance. These findings indicate that the risk of new resistance-causing mutations emerging is determined by specific predisposing genetic factors in the underlying parasite population. PMID:25599401
Joost, Stéphane; Kalbermatten, Michael; Bezault, Etienne; Seehausen, Ole
2012-01-01
When searching for loci possibly under selection in the genome, an alternative to population genetics theoretical models is to establish allele distribution models (ADM) for each locus to directly correlate allelic frequencies and environmental variables such as precipitation, temperature, or sun radiation. Such an approach implementing multiple logistic regression models in parallel was implemented within a computing program named MATSAM: . Recently, this application was improved in order to support qualitative environmental predictors as well as to permit the identification of associations between genomic variation and individual phenotypes, allowing the detection of loci involved in the genetic architecture of polymorphic characters. Here, we present the corresponding methodological developments and compare the results produced by software implementing population genetics theoretical models (DFDIST: and BAYESCAN: ) and ADM (MATSAM: ) in an empirical context to detect signatures of genomic divergence associated with speciation in Lake Victoria cichlid fishes.
Vinkhuyzen, Anna A E; van der Sluis, Sophie; Posthuma, Danielle; Boomsma, Dorret I
2009-07-01
The origin of individual differences in aptitude, defined as a domain-specific skill within the normal ability range, and talent, defined as a domain specific skill of exceptional quality, is under debate. The nature of the variation in aptitudes and exceptional talents across different domains was investigated in a population based twin sample. Self-report data from 1,685 twin pairs (12-24 years) were analyzed for Music, Arts, Writing, Language, Chess, Mathematics, Sports, Memory, and Knowledge. The influence of shared environment was small for both aptitude and talent. Additive and non-additive genetic effects explained the major part of the substantial familial clustering in the aptitude measures with heritability estimates ranging between .32 and .71. Heritability estimates for talents were higher and ranged between .50 and .92. In general, the genetic architecture for aptitude and talent was similar in men and women. Genetic factors contribute to a large extent to variation in aptitude and talent across different domains of intellectual, creative, and sports abilities.
Vasilopoulos, Terrie; Franz, Carol E; Panizzon, Matthew S; Xian, Hong; Grant, Michael D; Lyons, Michael J; Toomey, Rosemary; Jacobson, Kristen C; Kremen, William S
2012-03-01
To examine how genes and environments contribute to relationships among Trail Making Test (TMT) conditions and the extent to which these conditions have unique genetic and environmental influences. Participants included 1,237 middle-aged male twins from the Vietnam Era Twin Study of Aging. The Delis-Kaplan Executive Function System TMT included visual searching, number and letter sequencing, and set-shifting components. Phenotypic correlations among TMT conditions ranged from 0.29 to 0.60, and genes accounted for the majority (58-84%) of each correlation. Overall heritability ranged from 0.34 to 0.62 across conditions. Phenotypic factor analysis suggested a single factor. In contrast, genetic models revealed a single common genetic factor but also unique genetic influences separate from the common factor. Genetic variance (i.e., heritability) of number and letter sequencing was completely explained by the common genetic factor while unique genetic influences separate from the common factor accounted for 57% and 21% of the heritabilities of visual search and set shifting, respectively. After accounting for general cognitive ability, unique genetic influences accounted for 64% and 31% of those heritabilities. A common genetic factor, most likely representing a combination of speed and sequencing, accounted for most of the correlation among TMT 1-4. Distinct genetic factors, however, accounted for a portion of variance in visual scanning and set shifting. Thus, although traditional phenotypic shared variance analysis techniques suggest only one general factor underlying different neuropsychological functions in nonpatient populations, examining the genetic underpinnings of cognitive processes with twin analysis can uncover more complex etiological processes.
What Can Causal Networks Tell Us about Metabolic Pathways?
Blair, Rachael Hageman; Kliebenstein, Daniel J.; Churchill, Gary A.
2012-01-01
Graphical models describe the linear correlation structure of data and have been used to establish causal relationships among phenotypes in genetic mapping populations. Data are typically collected at a single point in time. Biological processes on the other hand are often non-linear and display time varying dynamics. The extent to which graphical models can recapitulate the architecture of an underlying biological processes is not well understood. We consider metabolic networks with known stoichiometry to address the fundamental question: “What can causal networks tell us about metabolic pathways?”. Using data from an Arabidopsis BaySha population and simulated data from dynamic models of pathway motifs, we assess our ability to reconstruct metabolic pathways using graphical models. Our results highlight the necessity of non-genetic residual biological variation for reliable inference. Recovery of the ordering within a pathway is possible, but should not be expected. Causal inference is sensitive to subtle patterns in the correlation structure that may be driven by a variety of factors, which may not emphasize the substrate-product relationship. We illustrate the effects of metabolic pathway architecture, epistasis and stochastic variation on correlation structure and graphical model-derived networks. We conclude that graphical models should be interpreted cautiously, especially if the implied causal relationships are to be used in the design of intervention strategies. PMID:22496633
Dissecting the genetic architecture of F1 hybrid sterility in house mice.
Dzur-Gejdosova, Maria; Simecek, Petr; Gregorova, Sona; Bhattacharyya, Tanmoy; Forejt, Jiri
2012-11-01
Hybrid sterility as a postzygotic reproductive isolation mechanism has been studied for over 80 years, yet the first identifications of hybrid sterility genes in Drosophila and mouse are quite recent. To study the genetic architecture of F(1) hybrid sterility between young subspecies of house mouse Mus m. domesticus and M. m. musculus, we conducted QTL analysis of a backcross between inbred strains representing these two subspecies and probed the role of individual chromosomes in hybrid sterility using the intersubspecific chromosome substitution strains. We provide direct evidence that the asymmetry in male infertility between reciprocal crosses is conferred by the middle region of M. m. musculus Chr X, thus excluding other potential candidates such as Y, imprinted genes, and mitochondrial DNA. QTL analysis identified strong hybrid sterility loci on Chr 17 and Chr X and predicted a set of interchangeable autosomal loci, a subset of which is sufficient to activate the Dobzhansky-Muller incompatibility of the strong loci. Overall, our results indicate the oligogenic nature of F(1) hybrid sterility, which should be amenable to reconstruction by proper combination of chromosome substitution strains. Such a prefabricated model system should help to uncover the gene networks and molecular mechanisms underlying hybrid sterility. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.
Phenotypic and genotypic data integration and exploration through a web-service architecture.
Nuzzo, Angelo; Riva, Alberto; Bellazzi, Riccardo
2009-10-15
Linking genotypic and phenotypic information is one of the greatest challenges of current genetics research. The definition of an Information Technology infrastructure to support this kind of studies, and in particular studies aimed at the analysis of complex traits, which require the definition of multifaceted phenotypes and the integration genotypic information to discover the most prevalent diseases, is a paradigmatic goal of Biomedical Informatics. This paper describes the use of Information Technology methods and tools to develop a system for the management, inspection and integration of phenotypic and genotypic data. We present the design and architecture of the Phenotype Miner, a software system able to flexibly manage phenotypic information, and its extended functionalities to retrieve genotype information from external repositories and to relate it to phenotypic data. For this purpose we developed a module to allow customized data upload by the user and a SOAP-based communications layer to retrieve data from existing biomedical knowledge management tools. In this paper we also demonstrate the system functionality by an example application of the system in which we analyze two related genomic datasets. In this paper we show how a comprehensive, integrated and automated workbench for genotype and phenotype integration can facilitate and improve the hypothesis generation process underlying modern genetic studies.
Camara, Mark D
1997-06-01
This paper reports on an investigation of two populations of Junonia coenia, the buckeye butterfly, one that feeds on the species' typical host plant (Plantago lanceolata) and one that utilizes a novel host plant (Kickxia elatine). I examined these populations for local adaptive responses in terms of oviposition behavior, growth, and chemical defense, on both P. lanceolata and K. elatine. In addition, I examined the genetic architecture underlying these traits using a full-sib quantitative genetic analysis. I found that a significant majority of females prefer the host plant species found at their collection sites in oviposition tests, but that there is no evidence that they are locally adapted in growth performance, as measured by fifth-instar and pupal weights and development times. Neither are there correlations between oviposition preferences of females and the growth performance or levels of chemical defense of their offspring. The two populations studied do, however, show specialization in terms of the levels of chemical defense they sequester from their host plants. I argue that these results indicate that natural enemies are the normal barriers to host range expansion in this oligophagous herbivore because a breakdown in those barriers results in genetic changes that enhance resistance to predation. This is despite the fact that adaptive responses in physiology are unlikely to be limited by a lack of genetic variability; the genetic architecture among traits would be conducive to specialization in growth performance; and there are costs to chemical defense in this species. All these conditions would tend to argue that J. coenia harbors considerable potential for coevolutionary interactions with its chemically defended hosts, but this potential is not realized, probably because natural selection on diet breadth by natural enemies is much stronger than selection from host plants in this system. © 1997 The Society for the Study of Evolution.
Genetic architechture and biological basis for feed efficiency in dairy cattle
USDA-ARS?s Scientific Manuscript database
The genetic architecture of residual feed intake (RFI) and related traits was evaluated using a dataset of 2,894 cows. A Bayesian analysis estimated that markers accounted for 14% of the variance in RFI, and that RFI had considerable genetic variation. Effects of marker windows were small, but QTL p...
Lloyd-Jones, Luke R; Robinson, Matthew R; Moser, Gerhard; Zeng, Jian; Beleza, Sandra; Barsh, Gregory S; Tang, Hua; Visscher, Peter M
2017-06-01
Genetic association studies in admixed populations are underrepresented in the genomics literature, with a key concern for researchers being the adequate control of spurious associations due to population structure. Linear mixed models (LMMs) are well suited for genome-wide association studies (GWAS) because they account for both population stratification and cryptic relatedness and achieve increased statistical power by jointly modeling all genotyped markers. Additionally, Bayesian LMMs allow for more flexible assumptions about the underlying distribution of genetic effects, and can concurrently estimate the proportion of phenotypic variance explained by genetic markers. Using three recently published Bayesian LMMs, Bayes R, BSLMM, and BOLT-LMM, we investigate an existing data set on eye ( n = 625) and skin ( n = 684) color from Cape Verde, an island nation off West Africa that is home to individuals with a broad range of phenotypic values for eye and skin color due to the mix of West African and European ancestry. We use simulations to demonstrate the utility of Bayesian LMMs for mapping loci and studying the genetic architecture of quantitative traits in admixed populations. The Bayesian LMMs provide evidence for two new pigmentation loci: one for eye color ( AHRR ) and one for skin color ( DDB1 ). Copyright © 2017 by the Genetics Society of America.
Lu, Qiongshi; Li, Boyang; Ou, Derek; Erlendsdottir, Margret; Powles, Ryan L; Jiang, Tony; Hu, Yiming; Chang, David; Jin, Chentian; Dai, Wei; He, Qidu; Liu, Zefeng; Mukherjee, Shubhabrata; Crane, Paul K; Zhao, Hongyu
2017-12-07
Despite the success of large-scale genome-wide association studies (GWASs) on complex traits, our understanding of their genetic architecture is far from complete. Jointly modeling multiple traits' genetic profiles has provided insights into the shared genetic basis of many complex traits. However, large-scale inference sets a high bar for both statistical power and biological interpretability. Here we introduce a principled framework to estimate annotation-stratified genetic covariance between traits using GWAS summary statistics. Through theoretical and numerical analyses, we demonstrate that our method provides accurate covariance estimates, thereby enabling researchers to dissect both the shared and distinct genetic architecture across traits to better understand their etiologies. Among 50 complex traits with publicly accessible GWAS summary statistics (N total ≈ 4.5 million), we identified more than 170 pairs with statistically significant genetic covariance. In particular, we found strong genetic covariance between late-onset Alzheimer disease (LOAD) and amyotrophic lateral sclerosis (ALS), two major neurodegenerative diseases, in single-nucleotide polymorphisms (SNPs) with high minor allele frequencies and in SNPs located in the predicted functional genome. Joint analysis of LOAD, ALS, and other traits highlights LOAD's correlation with cognitive traits and hints at an autoimmune component for ALS. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
Parsons, Kevin J; Concannon, Moira; Navon, Dina; Wang, Jason; Ea, Ilene; Groveas, Kiran; Campbell, Calum; Albertson, R Craig
2016-12-01
Phenotypic plasticity allows organisms to change their phenotype in response to shifts in the environment. While a central topic in current discussions of evolutionary potential, a comprehensive understanding of the genetic underpinnings of plasticity is lacking in systems undergoing adaptive diversification. Here, we investigate the genetic basis of phenotypic plasticity in a textbook adaptive radiation, Lake Malawi cichlid fishes. Specifically, we crossed two divergent species to generate an F 3 hybrid mapping population. At early juvenile stages, hybrid families were split and reared in alternate foraging environments that mimicked benthic/scraping or limnetic/sucking modes of feeding. These alternate treatments produced a variation in morphology that was broadly similar to the major axis of divergence among Malawi cichlids, providing support for the flexible stem theory of adaptive radiation. Next, we found that the genetic architecture of several morphological traits was highly sensitive to the environment. In particular, of 22 significant quantitative trait loci (QTL), only one was shared between the environments. In addition, we identified QTL acting across environments with alternate alleles being differentially sensitive to the environment. Thus, our data suggest that while plasticity is largely determined by loci specific to a given environment, it may also be influenced by loci operating across environments. Finally, our mapping data provide evidence for the evolution of plasticity via genetic assimilation at an important regulatory locus, ptch1. In all, our data address long-standing discussions about the genetic basis and evolution of plasticity. They also underscore the importance of the environment in affecting developmental outcomes, genetic architectures, morphological diversity and evolutionary potential. © 2016 John Wiley & Sons Ltd.
Camargo, Anyela V; Mott, Richard; Gardner, Keith A; Mackay, Ian J; Corke, Fiona; Doonan, John H; Kim, Jan T; Bentley, Alison R
2016-01-01
The appropriate timing of developmental transitions is critical for adapting many crops to their local climatic conditions. Therefore, understanding the genetic basis of different aspects of phenology could be useful in highlighting mechanisms underpinning adaptation, with implications in breeding for climate change. For bread wheat ( Triticum aestivum ), the transition from vegetative to reproductive growth, the start and rate of leaf senescence and the relative timing of different stages of flowering and grain filling all contribute to plant performance. In this study we screened under Smart house conditions a large, multi-founder "NIAB elite MAGIC" wheat population, to evaluate the genetic elements that influence the timing of developmental stages in European elite varieties. This panel of recombinant inbred lines was derived from eight parents that are or recently have been grown commercially in the UK and Northern Europe. We undertook a detailed temporal phenotypic analysis under Smart house conditions of the population and its parents, to try to identify known or novel Quantitative Trait Loci associated with variation in the timing of key phenological stages in senescence. This analysis resulted in the detection of QTL interactions with novel traits such the time between "half of ear emergence above flag leaf ligule" and the onset of senescence at the flag leaf as well as traits associated with plant morphology such as stem height. In addition, strong correlations between several traits and the onset of senescence of the flag leaf were identified. This work establishes the value of systematically phenotyping genetically unstructured populations to reveal the genetic architecture underlying morphological variation in commercial wheat.
Evolutionary evidence of the effect of rare variants on disease etiology.
Gorlov, I P; Gorlova, O Y; Frazier, M L; Spitz, M R; Amos, C I
2011-03-01
The common disease/common variant hypothesis has been popular for describing the genetic architecture of common human diseases for several years. According to the originally stated hypothesis, one or a few common genetic variants with a large effect size control the risk of common diseases. A growing body of evidence, however, suggests that rare single-nucleotide polymorphisms (SNPs), i.e. those with a minor allele frequency of less than 5%, are also an important component of the genetic architecture of common human diseases. In this study, we analyzed the relevance of rare SNPs to the risk of common diseases from an evolutionary perspective and found that rare SNPs are more likely than common SNPs to be functional and tend to have a stronger effect size than do common SNPs. This observation, and the fact that most of the SNPs in the human genome are rare, suggests that rare SNPs are a crucial element of the genetic architecture of common human diseases. We propose that the next generation of genomic studies should focus on analyzing rare SNPs. Further, targeting patients with a family history of the disease, an extreme phenotype, or early disease onset may facilitate the detection of risk-associated rare SNPs. © 2010 John Wiley & Sons A/S.
Genomic architecture of adaptive color pattern divergence and convergence in Heliconius butterflies
Supple, Megan A.; Hines, Heather M.; Dasmahapatra, Kanchon K.; Lewis, James J.; Nielsen, Dahlia M.; Lavoie, Christine; Ray, David A.; Salazar, Camilo; McMillan, W. Owen; Counterman, Brian A.
2013-01-01
Identifying the genetic changes driving adaptive variation in natural populations is key to understanding the origins of biodiversity. The mosaic of mimetic wing patterns in Heliconius butterflies makes an excellent system for exploring adaptive variation using next-generation sequencing. In this study, we use a combination of techniques to annotate the genomic interval modulating red color pattern variation, identify a narrow region responsible for adaptive divergence and convergence in Heliconius wing color patterns, and explore the evolutionary history of these adaptive alleles. We use whole genome resequencing from four hybrid zones between divergent color pattern races of Heliconius erato and two hybrid zones of the co-mimic Heliconius melpomene to examine genetic variation across 2.2 Mb of a partial reference sequence. In the intergenic region near optix, the gene previously shown to be responsible for the complex red pattern variation in Heliconius, population genetic analyses identify a shared 65-kb region of divergence that includes several sites perfectly associated with phenotype within each species. This region likely contains multiple cis-regulatory elements that control discrete expression domains of optix. The parallel signatures of genetic differentiation in H. erato and H. melpomene support a shared genetic architecture between the two distantly related co-mimics; however, phylogenetic analysis suggests mimetic patterns in each species evolved independently. Using a combination of next-generation sequencing analyses, we have refined our understanding of the genetic architecture of wing pattern variation in Heliconius and gained important insights into the evolution of novel adaptive phenotypes in natural populations. PMID:23674305
Greenwood, Julian R.; Bencivenga, Stefano; Cockram, James; Cavanagh, Colin; Swain, Steve M.
2018-01-01
The flowers of major cereals are arranged on reproductive branches known as spikelets, which group together to form an inflorescence. Diversity for inflorescence architecture has been exploited during domestication to increase crop yields, and genetic variation for this trait has potential to further boost grain production. Multiple genes that regulate inflorescence architecture have been identified by studying alleles that modify gene activity or dosage; however, little is known in wheat. Here, we show TEOSINTE BRANCHED1 (TB1) regulates inflorescence architecture in bread wheat (Triticum aestivum) by investigating lines that display a form of inflorescence branching known as “paired spikelets.” We show that TB1 interacts with FLOWERING LOCUS T1 and that increased dosage of TB1 alters inflorescence architecture and growth rate in a process that includes reduced expression of meristem identity genes, with allelic diversity for TB1 found to associate genetically with paired spikelet development in modern cultivars. We propose TB1 coordinates formation of axillary spikelets during the vegetative to floral transition and that alleles known to modify dosage or function of TB1 could help increase wheat yields. PMID:29444813
Dixon, Laura E; Greenwood, Julian R; Bencivenga, Stefano; Zhang, Peng; Cockram, James; Mellers, Gregory; Ramm, Kerrie; Cavanagh, Colin; Swain, Steve M; Boden, Scott A
2018-03-01
The flowers of major cereals are arranged on reproductive branches known as spikelets, which group together to form an inflorescence. Diversity for inflorescence architecture has been exploited during domestication to increase crop yields, and genetic variation for this trait has potential to further boost grain production. Multiple genes that regulate inflorescence architecture have been identified by studying alleles that modify gene activity or dosage; however, little is known in wheat. Here, we show TEOSINTE BRANCHED1 ( TB1 ) regulates inflorescence architecture in bread wheat ( Triticum aestivum ) by investigating lines that display a form of inflorescence branching known as "paired spikelets." We show that TB1 interacts with FLOWERING LOCUS T1 and that increased dosage of TB1 alters inflorescence architecture and growth rate in a process that includes reduced expression of meristem identity genes, with allelic diversity for TB1 found to associate genetically with paired spikelet development in modern cultivars. We propose TB1 coordinates formation of axillary spikelets during the vegetative to floral transition and that alleles known to modify dosage or function of TB1 could help increase wheat yields. © 2018 American Society of Plant Biologists. All rights reserved.
Yang, Delong; Liu, Yuan; Cheng, Hongbo; Chang, Lei; Chen, Jingjing; Chai, Shouxi; Li, Mengfei
2016-06-28
Morphological traits related to flag leaves are determinant traits influencing plant architecture and yield potential in wheat (Triticum aestivum L.). However, little is known regarding their genetic controls under drought stress. One hundred and twenty F8-derived recombinant inbred lines from a cross between two common wheat cultivars Longjian 19 and Q9086 were developed to identify quantitative trait loci (QTLs) and to dissect the genetic bases underlying flag leaf width, length, area, length to width ratio and basal angle under drought stress and well-watered conditions consistent over four environments. A total of 55 additive and 51 pairs of epistatic QTLs were identified on all 21 chromosomes except 6D, among which additive loci were highly concentrated in a few of same or adjacent marker intervals in individual chromosomes. Two specific marker intervals of Xwmc694-Xwmc156 on chromosome 1B and Xbarc1072-Xwmc272 on chromosome 2B were co-located by additive QTLs for four tested traits. Twenty additive loci were repeatedly detected in more than two environments, suggestive of stable A-QTLs. A majority of QTLs involved significant additive and epistatic effects, as well as QTL × environment interactions (QEIs). Of these, 72.7 % of additive QEIs and 80 % of epistatic QEIs were related to drought stress with significant genetic effects decreasing phenotypic values. By contrast, additive and QEIs effects contributed more phenotypic variation than epistatic effects. Flag leaf morphology in wheat was predominantly controlled by additive and QEIs effects, where more QEIs effects occurred in drought stress and depressed phenotypic performances. Several QTL clusters indicated tight linkage or pleiotropy in the inheritance of these traits. Twenty stable QTLs for flag leaf morphology are potentially useful for the genetic improvement of drought tolerance in wheat through QTL pyramiding.
Genome-wide analysis identifies 12 loci influencing human reproductive behavior.
Barban, Nicola; Jansen, Rick; de Vlaming, Ronald; Vaez, Ahmad; Mandemakers, Jornt J; Tropf, Felix C; Shen, Xia; Wilson, James F; Chasman, Daniel I; Nolte, Ilja M; Tragante, Vinicius; van der Laan, Sander W; Perry, John R B; Kong, Augustine; Ahluwalia, Tarunveer S; Albrecht, Eva; Yerges-Armstrong, Laura; Atzmon, Gil; Auro, Kirsi; Ayers, Kristin; Bakshi, Andrew; Ben-Avraham, Danny; Berger, Klaus; Bergman, Aviv; Bertram, Lars; Bielak, Lawrence F; Bjornsdottir, Gyda; Bonder, Marc Jan; Broer, Linda; Bui, Minh; Barbieri, Caterina; Cavadino, Alana; Chavarro, Jorge E; Turman, Constance; Concas, Maria Pina; Cordell, Heather J; Davies, Gail; Eibich, Peter; Eriksson, Nicholas; Esko, Tõnu; Eriksson, Joel; Falahi, Fahimeh; Felix, Janine F; Fontana, Mark Alan; Franke, Lude; Gandin, Ilaria; Gaskins, Audrey J; Gieger, Christian; Gunderson, Erica P; Guo, Xiuqing; Hayward, Caroline; He, Chunyan; Hofer, Edith; Huang, Hongyan; Joshi, Peter K; Kanoni, Stavroula; Karlsson, Robert; Kiechl, Stefan; Kifley, Annette; Kluttig, Alexander; Kraft, Peter; Lagou, Vasiliki; Lecoeur, Cecile; Lahti, Jari; Li-Gao, Ruifang; Lind, Penelope A; Liu, Tian; Makalic, Enes; Mamasoula, Crysovalanto; Matteson, Lindsay; Mbarek, Hamdi; McArdle, Patrick F; McMahon, George; Meddens, S Fleur W; Mihailov, Evelin; Miller, Mike; Missmer, Stacey A; Monnereau, Claire; van der Most, Peter J; Myhre, Ronny; Nalls, Mike A; Nutile, Teresa; Kalafati, Ioanna Panagiota; Porcu, Eleonora; Prokopenko, Inga; Rajan, Kumar B; Rich-Edwards, Janet; Rietveld, Cornelius A; Robino, Antonietta; Rose, Lynda M; Rueedi, Rico; Ryan, Kathleen A; Saba, Yasaman; Schmidt, Daniel; Smith, Jennifer A; Stolk, Lisette; Streeten, Elizabeth; Tönjes, Anke; Thorleifsson, Gudmar; Ulivi, Sheila; Wedenoja, Juho; Wellmann, Juergen; Willeit, Peter; Yao, Jie; Yengo, Loic; Zhao, Jing Hua; Zhao, Wei; Zhernakova, Daria V; Amin, Najaf; Andrews, Howard; Balkau, Beverley; Barzilai, Nir; Bergmann, Sven; Biino, Ginevra; Bisgaard, Hans; Bønnelykke, Klaus; Boomsma, Dorret I; Buring, Julie E; Campbell, Harry; Cappellani, Stefania; Ciullo, Marina; Cox, Simon R; Cucca, Francesco; Toniolo, Daniela; Davey-Smith, George; Deary, Ian J; Dedoussis, George; Deloukas, Panos; van Duijn, Cornelia M; de Geus, Eco J C; Eriksson, Johan G; Evans, Denis A; Faul, Jessica D; Sala, Cinzia Felicita; Froguel, Philippe; Gasparini, Paolo; Girotto, Giorgia; Grabe, Hans-Jörgen; Greiser, Karin Halina; Groenen, Patrick J F; de Haan, Hugoline G; Haerting, Johannes; Harris, Tamara B; Heath, Andrew C; Heikkilä, Kauko; Hofman, Albert; Homuth, Georg; Holliday, Elizabeth G; Hopper, John; Hyppönen, Elina; Jacobsson, Bo; Jaddoe, Vincent W V; Johannesson, Magnus; Jugessur, Astanand; Kähönen, Mika; Kajantie, Eero; Kardia, Sharon L R; Keavney, Bernard; Kolcic, Ivana; Koponen, Päivikki; Kovacs, Peter; Kronenberg, Florian; Kutalik, Zoltan; La Bianca, Martina; Lachance, Genevieve; Iacono, William G; Lai, Sandra; Lehtimäki, Terho; Liewald, David C; Lindgren, Cecilia M; Liu, Yongmei; Luben, Robert; Lucht, Michael; Luoto, Riitta; Magnus, Per; Magnusson, Patrik K E; Martin, Nicholas G; McGue, Matt; McQuillan, Ruth; Medland, Sarah E; Meisinger, Christa; Mellström, Dan; Metspalu, Andres; Traglia, Michela; Milani, Lili; Mitchell, Paul; Montgomery, Grant W; Mook-Kanamori, Dennis; de Mutsert, Renée; Nohr, Ellen A; Ohlsson, Claes; Olsen, Jørn; Ong, Ken K; Paternoster, Lavinia; Pattie, Alison; Penninx, Brenda W J H; Perola, Markus; Peyser, Patricia A; Pirastu, Mario; Polasek, Ozren; Power, Chris; Kaprio, Jaakko; Raffel, Leslie J; Räikkönen, Katri; Raitakari, Olli; Ridker, Paul M; Ring, Susan M; Roll, Kathryn; Rudan, Igor; Ruggiero, Daniela; Rujescu, Dan; Salomaa, Veikko; Schlessinger, David; Schmidt, Helena; Schmidt, Reinhold; Schupf, Nicole; Smit, Johannes; Sorice, Rossella; Spector, Tim D; Starr, John M; Stöckl, Doris; Strauch, Konstantin; Stumvoll, Michael; Swertz, Morris A; Thorsteinsdottir, Unnur; Thurik, A Roy; Timpson, Nicholas J; Tung, Joyce Y; Uitterlinden, André G; Vaccargiu, Simona; Viikari, Jorma; Vitart, Veronique; Völzke, Henry; Vollenweider, Peter; Vuckovic, Dragana; Waage, Johannes; Wagner, Gert G; Wang, Jie Jin; Wareham, Nicholas J; Weir, David R; Willemsen, Gonneke; Willeit, Johann; Wright, Alan F; Zondervan, Krina T; Stefansson, Kari; Krueger, Robert F; Lee, James J; Benjamin, Daniel J; Cesarini, David; Koellinger, Philipp D; den Hoed, Marcel; Snieder, Harold; Mills, Melinda C
2016-12-01
The genetic architecture of human reproductive behavior-age at first birth (AFB) and number of children ever born (NEB)-has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the underlying mechanisms of AFB and NEB are poorly understood. We report a large genome-wide association study of both sexes including 251,151 individuals for AFB and 343,072 individuals for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study and 4 additional loci associated in a gene-based effort. These loci harbor genes that are likely to have a role, either directly or by affecting non-local gene expression, in human reproduction and infertility, thereby increasing understanding of these complex traits.
Protein Kinases in Shaping Plant Architecture.
Wu, Juan; Wang, Bo; Xin, Xiaoyun; Ren, Dongtao
2018-02-13
Plant architecture, the three-dimensional organization of the plant body, includes the branching pattern and the size, shape, and position of organs. Plant architecture is genetically controlled and is influenced by environmental conditions. The regulations occur at most of the stages from the first division of the fertilized eggs to the final establishment of plant architecture. Among the various endogenous regulators, protein kinases and their associated signaling pathways have been shown to play important roles in regulating the process of plant architecture establishment. In this review, we summarize recent progress in the understanding of the mechanisms by which plant architecture formation is regulated by protein kinases, especially mitogen-activated protein kinase (MAPK). Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Identifying the genes underlying quantitative traits: a rationale for the QTN programme.
Lee, Young Wha; Gould, Billie A; Stinchcombe, John R
2014-01-01
The goal of identifying the genes or even nucleotides underlying quantitative and adaptive traits has been characterized as the 'QTN programme' and has recently come under severe criticism. Part of the reason for this criticism is that much of the QTN programme has asserted that finding the genes and nucleotides for adaptive and quantitative traits is a fundamental goal, without explaining why it is such a hallowed goal. Here we outline motivations for the QTN programme that offer general insight, regardless of whether QTNs are of large or small effect, and that aid our understanding of the mechanistic dynamics of adaptive evolution. We focus on five areas: (i) vertical integration of insight across different levels of biological organization, (ii) genetic parallelism and the role of pleiotropy in shaping evolutionary dynamics, (iii) understanding the forces maintaining genetic variation in populations, (iv) distinguishing between adaptation from standing variation and new mutation, and (v) the role of genomic architecture in facilitating adaptation. We argue that rather than abandoning the QTN programme, we should refocus our efforts on topics where molecular data will be the most effective for testing hypotheses about phenotypic evolution.
Identifying the genes underlying quantitative traits: a rationale for the QTN programme
Lee, Young Wha; Gould, Billie A.; Stinchcombe, John R.
2014-01-01
The goal of identifying the genes or even nucleotides underlying quantitative and adaptive traits has been characterized as the ‘QTN programme’ and has recently come under severe criticism. Part of the reason for this criticism is that much of the QTN programme has asserted that finding the genes and nucleotides for adaptive and quantitative traits is a fundamental goal, without explaining why it is such a hallowed goal. Here we outline motivations for the QTN programme that offer general insight, regardless of whether QTNs are of large or small effect, and that aid our understanding of the mechanistic dynamics of adaptive evolution. We focus on five areas: (i) vertical integration of insight across different levels of biological organization, (ii) genetic parallelism and the role of pleiotropy in shaping evolutionary dynamics, (iii) understanding the forces maintaining genetic variation in populations, (iv) distinguishing between adaptation from standing variation and new mutation, and (v) the role of genomic architecture in facilitating adaptation. We argue that rather than abandoning the QTN programme, we should refocus our efforts on topics where molecular data will be the most effective for testing hypotheses about phenotypic evolution. PMID:24790125
Genetic association studies of obesity in Africa: a systematic review.
Yako, Y Y; Echouffo-Tcheugui, J B; Balti, E V; Matsha, T E; Sobngwi, E; Erasmus, R T; Kengne, A P
2015-03-01
Obesity is increasing in Africa, but the underlying genetic background largely remains unknown. We assessed existing evidence on genetic determinants of obesity among populations within Africa. MEDLINE and EMBASE were searched and the bibliographies of retrieved articles were examined. Included studies had to report on the association of a genetic marker with obesity indices and the presence/occurrence of obesity/obesity trait. Data were extracted on study design and characteristics, genetic determinants and effect estimates of associations with obesity indices. According to this data, over 300 polymorphisms in 42 genes have been studied in various population groups within Africa mostly through the candidate gene approach. Polymorphisms in genes such as ACE, ADIPOQ, ADRB2, AGRP, AR, CAPN10, CD36, C7orf31, DRD4, FTO, MC3R, MC4R, SGIP1 and LEP were found to be associated with various measures of obesity. Of the 36 polymorphisms previously validated by genome-wide association studies (GWAS) elsewhere, only FTO and MC4R polymorphisms showed significant associations with obesity in black South Africans, Nigerians and Ghanaians. However, these data are insufficient to establish the true nature of genetic susceptibility to obesity in populations within Africa. There has been recent progress in describing the genetic architecture of obesity among populations within Africa. This effort needs to be sustained via GWAS studies. © 2015 World Obesity.
Upweighting rare favourable alleles increases long-term genetic gain in genomic selection programs.
Liu, Huiming; Meuwissen, Theo H E; Sørensen, Anders C; Berg, Peer
2015-03-21
The short-term impact of using different genomic prediction (GP) models in genomic selection has been intensively studied, but their long-term impact is poorly understood. Furthermore, long-term genetic gain of genomic selection is expected to improve by using Jannink's weighting (JW) method, in which rare favourable marker alleles are upweighted in the selection criterion. In this paper, we extend the JW method by including an additional parameter to decrease the emphasis on rare favourable alleles over the time horizon, with the purpose of further improving the long-term genetic gain. We call this new method dynamic weighting (DW). The paper explores the long-term impact of different GP models with or without weighting methods. Different selection criteria were tested by simulating a population of 500 animals with truncation selection of five males and 50 females. Selection criteria included unweighted and weighted genomic estimated breeding values using the JW or DW methods, for which ridge regression (RR) and Bayesian lasso (BL) were used to estimate marker effects. The impacts of these selection criteria were compared under three genetic architectures, i.e. varying numbers of QTL for the trait and for two time horizons of 15 (TH15) or 40 (TH40) generations. For unweighted GP, BL resulted in up to 21.4% higher long-term genetic gain and 23.5% lower rate of inbreeding under TH40 than RR. For weighted GP, DW resulted in 1.3 to 5.5% higher long-term gain compared to unweighted GP. JW, however, showed a 6.8% lower long-term genetic gain relative to unweighted GP when BL was used to estimate the marker effects. Under TH40, both DW and JW obtained significantly higher genetic gain than unweighted GP. With DW, the long-term genetic gain was increased by up to 30.8% relative to unweighted GP, and also increased by 8% relative to JW, although at the expense of a lower short-term gain. Irrespective of the number of QTL simulated, BL is superior to RR in maintaining genetic variance and therefore results in higher long-term genetic gain. Moreover, DW is a promising method with which high long-term genetic gain can be expected within a fixed time frame.
Soltis, Douglas E; Soltis, Pamela S; Albert, Victor A; Oppenheimer, David G; dePamphilis, Claude W; Ma, Hong; Frohlich, Michael W; Theissen, Günter
2002-01-01
To understand the genetic architecture of floral development, including the origin and subsequent diversification of the flower, data are needed not only for a few model organisms but also for gymnosperms, basal angiosperm lineages and early-diverging eudicots. We must link what is known about derived model plants such as Arabidopsis, snapdragon and maize with other angiosperms. To this end, we suggest a massive evolutionary genomics effort focused on the identification and expression patterns of floral genes and elucidation of their expression patterns in 'missing-link' taxa differing in the arrangement, number and organization of floral parts.
Genetic architecture of resistance in Daphnia hosts against two species of host-specific parasites.
Routtu, J; Ebert, D
2015-02-01
Understanding the genetic architecture of host resistance is key for understanding the evolution of host-parasite interactions. Evolutionary models often assume simple genetics based on few loci and strong epistasis. It is unknown, however, whether these assumptions apply to natural populations. Using a quantitative trait loci (QTL) approach, we explore the genetic architecture of resistance in the crustacean Daphnia magna to two of its natural parasites: the horizontally transmitted bacterium Pasteuria ramosa and the horizontally and vertically transmitted microsporidium Hamiltosporidium tvaerminnensis. These two systems have become models for studies on the evolution of host-parasite interactions. In the QTL panel used here, Daphnia's resistance to P. ramosa is controlled by a single major QTL (which explains 50% of the observed variation). Resistance to H. tvaerminnensis horizontal infections shows a signature of a quantitative trait based in multiple loci with weak epistatic interactions (together explaining 38% variation). Resistance to H. tvaerminnensis vertical infections, however, shows only one QTL (explaining 13.5% variance) that colocalizes with one of the QTLs for horizontal infections. QTLs for resistance to Pasteuria and Hamiltosporidium do not colocalize. We conclude that the genetics of resistance in D. magna are drastically different for these two parasites. Furthermore, we infer that based on these and earlier results, the mechanisms of coevolution differ strongly for the two host-parasite systems. Only the Pasteuria-Daphnia system is expected to follow the negative frequency-dependent selection (Red Queen) model. How coevolution works in the Hamiltosporidium-Daphnia system remains unclear.
Genetic architecture of resistance in Daphnia hosts against two species of host-specific parasites
Routtu, J; Ebert, D
2015-01-01
Understanding the genetic architecture of host resistance is key for understanding the evolution of host–parasite interactions. Evolutionary models often assume simple genetics based on few loci and strong epistasis. It is unknown, however, whether these assumptions apply to natural populations. Using a quantitative trait loci (QTL) approach, we explore the genetic architecture of resistance in the crustacean Daphnia magna to two of its natural parasites: the horizontally transmitted bacterium Pasteuria ramosa and the horizontally and vertically transmitted microsporidium Hamiltosporidium tvaerminnensis. These two systems have become models for studies on the evolution of host–parasite interactions. In the QTL panel used here, Daphnia's resistance to P. ramosa is controlled by a single major QTL (which explains 50% of the observed variation). Resistance to H. tvaerminnensis horizontal infections shows a signature of a quantitative trait based in multiple loci with weak epistatic interactions (together explaining 38% variation). Resistance to H. tvaerminnensis vertical infections, however, shows only one QTL (explaining 13.5% variance) that colocalizes with one of the QTLs for horizontal infections. QTLs for resistance to Pasteuria and Hamiltosporidium do not colocalize. We conclude that the genetics of resistance in D. magna are drastically different for these two parasites. Furthermore, we infer that based on these and earlier results, the mechanisms of coevolution differ strongly for the two host–parasite systems. Only the Pasteuria–Daphnia system is expected to follow the negative frequency-dependent selection (Red Queen) model. How coevolution works in the Hamiltosporidium–Daphnia system remains unclear. PMID:25335558
The molecular mechanism of plant gravitropism.
Wu, Di; Huang, Lin-zhou; Gao, Jin; Wang, Yong-hong
2016-07-20
Gravity is an important environmental factor that regulates plant growth and morphogenesis. In response to gravity stimulus, plants can set the optimum angle between the organs and the gravity vector. Plant gravitropism is divided into four sequential steps, including gravity perception, signal transduction, asymmetrical distribution of auxin, and organ curvature. In recent years, large numbers of mutants with defective gravitropism have been identified and genes involved in the regulation of gravitropism have been functionally characterized. In particular, progress has been achieved on elucidating the molecular mechanisms of gravity perception and asymmetrical distribution of auxin. As one of the most important strategies for plant to adapt environmental changes, gravitropism is also involved in the regulation of rice plant architecture and grain yield through modulating rice tiller angle. Therefore, the investigation of plant gravitropism not only contributes to decipher the regulatory mechanisms of plant growth and development, but also helps to guide the genetic improvement of crop architecture. However, the molecular mechanisms and regulatory network of gravitropism remain to be elusive. In this review, we focus on recent progress on elucidating molecular mechanisms underlying gravitropism and its involvement in regulating rice tiller angle, which is an important agronomic trait that determines rice plant architecture and thus grain yields.
Hufnagel, Barbara; de Sousa, Sylvia M.; Assis, Lidianne; Guimaraes, Claudia T.; Leiser, Willmar; Azevedo, Gabriel C.; Negri, Barbara; Larson, Brandon G.; Shaff, Jon E.; Pastina, Maria Marta; Barros, Beatriz A.; Weltzien, Eva; Rattunde, Henry Frederick W.; Viana, Joao H.; Clark, Randy T.; Falcão, Alexandre; Gazaffi, Rodrigo; Garcia, Antonio Augusto F.; Schaffert, Robert E.; Kochian, Leon V.; Magalhaes, Jurandir V.
2014-01-01
Low soil phosphorus (P) availability is a major constraint for crop production in tropical regions. The rice (Oryza sativa) protein kinase, PHOSPHORUS-STARVATION TOLERANCE1 (OsPSTOL1), was previously shown to enhance P acquisition and grain yield in rice under P deficiency. We investigated the role of homologs of OsPSTOL1 in sorghum (Sorghum bicolor) performance under low P. Association mapping was undertaken in two sorghum association panels phenotyped for P uptake, root system morphology and architecture in hydroponics and grain yield and biomass accumulation under low-P conditions, in Brazil and/or in Mali. Root length and root surface area were positively correlated with grain yield under low P in the soil, emphasizing the importance of P acquisition efficiency in sorghum adaptation to low-P availability. SbPSTOL1 alleles reducing root diameter were associated with enhanced P uptake under low P in hydroponics, whereas Sb03g006765 and Sb03g0031680 alleles increasing root surface area also increased grain yield in a low-P soil. SbPSTOL1 genes colocalized with quantitative trait loci for traits underlying root morphology and dry weight accumulation under low P via linkage mapping. Consistent allelic effects for enhanced sorghum performance under low P between association panels, including enhanced grain yield under low P in the soil in Brazil, point toward a relatively stable role for Sb03g006765 across genetic backgrounds and environmental conditions. This study indicates that multiple SbPSTOL1 genes have a more general role in the root system, not only enhancing root morphology traits but also changing root system architecture, which leads to grain yield gain under low-P availability in the soil. PMID:25189534
Implications of behavioral architecture for the evolution of self-organized division of labor.
Duarte, A; Scholtens, E; Weissing, F J
2012-01-01
Division of labor has been studied separately from a proximate self-organization and an ultimate evolutionary perspective. We aim to bring together these two perspectives. So far this has been done by choosing a behavioral mechanism a priori and considering the evolution of the properties of this mechanism. Here we use artificial neural networks to allow for a more open architecture. We study whether emergent division of labor can evolve in two different network architectures; a simple feedforward network, and a more complex network that includes the possibility of self-feedback from previous experiences. We focus on two aspects of division of labor; worker specialization and the ratio of work performed for each task. Colony fitness is maximized by both reducing idleness and achieving a predefined optimal work ratio. Our results indicate that architectural constraints play an important role for the outcome of evolution. With the simplest network, only genetically determined specialization is possible. This imposes several limitations on worker specialization. Moreover, in order to minimize idleness, networks evolve a biased work ratio, even when an unbiased work ratio would be optimal. By adding self-feedback to the network we increase the network's flexibility and worker specialization evolves under a wider parameter range. Optimal work ratios are more easily achieved with the self-feedback network, but still provide a challenge when combined with worker specialization.
Implications of Behavioral Architecture for the Evolution of Self-Organized Division of Labor
Duarte, A.; Scholtens, E.; Weissing, F. J.
2012-01-01
Division of labor has been studied separately from a proximate self-organization and an ultimate evolutionary perspective. We aim to bring together these two perspectives. So far this has been done by choosing a behavioral mechanism a priori and considering the evolution of the properties of this mechanism. Here we use artificial neural networks to allow for a more open architecture. We study whether emergent division of labor can evolve in two different network architectures; a simple feedforward network, and a more complex network that includes the possibility of self-feedback from previous experiences. We focus on two aspects of division of labor; worker specialization and the ratio of work performed for each task. Colony fitness is maximized by both reducing idleness and achieving a predefined optimal work ratio. Our results indicate that architectural constraints play an important role for the outcome of evolution. With the simplest network, only genetically determined specialization is possible. This imposes several limitations on worker specialization. Moreover, in order to minimize idleness, networks evolve a biased work ratio, even when an unbiased work ratio would be optimal. By adding self-feedback to the network we increase the network's flexibility and worker specialization evolves under a wider parameter range. Optimal work ratios are more easily achieved with the self-feedback network, but still provide a challenge when combined with worker specialization. PMID:22457609
Davis Rabosky, Alison R; Cox, Christian L; Rabosky, Daniel L
2016-04-01
Identifying the genetic basis of mimetic signals is critical to understanding both the origin and dynamics of mimicry over time. For species not amenable to large laboratory breeding studies, widespread color polymorphism across natural populations offers a powerful way to assess the relative likelihood of different genetic systems given observed phenotypic frequencies. We classified color phenotype for 2175 ground snakes (Sonora semiannulata) across the continental United States to analyze morph ratios and test among competing hypotheses about the genetic architecture underlying red and black coloration in coral snake mimics. We found strong support for a two-locus model under simple Mendelian inheritance, with red and black pigmentation being controlled by separate loci. We found no evidence of either linkage disequilibrium between loci or sex linkage. In contrast to Batesian mimicry systems such as butterflies in which all color signal components are linked into a single "supergene," our results suggest that the mimetic signal in colubrid snakes can be disrupted through simple recombination and that color evolution is likely to involve discrete gains and losses of each signal component. Both outcomes are likely to contribute to the exponential increase in rates of color evolution seen in snake mimicry systems over insect systems. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.
Genomic architecture of biomass heterosis in Arabidopsis.
Yang, Mei; Wang, Xuncheng; Ren, Diqiu; Huang, Hao; Xu, Miqi; He, Guangming; Deng, Xing Wang
2017-07-25
Heterosis is most frequently manifested by the substantially increased vigorous growth of hybrids compared with their parents. Investigating genomic variations in natural populations is essential to understand the initial molecular mechanisms underlying heterosis in plants. Here, we characterized the genomic architecture associated with biomass heterosis in 200 Arabidopsis hybrids. The genome-wide heterozygosity of hybrids makes a limited contribution to biomass heterosis, and no locus shows an obvious overdominance effect in hybrids. However, the accumulation of significant genetic loci identified in genome-wide association studies (GWAS) in hybrids strongly correlates with better-parent heterosis (BPH). Candidate genes for biomass BPH fall into diverse biological functions, including cellular, metabolic, and developmental processes and stimulus-responsive pathways. Important heterosis candidates include WUSCHEL , ARGOS , and some genes that encode key factors involved in cell cycle regulation. Interestingly, transcriptomic analyses in representative Arabidopsis hybrid combinations reveal that heterosis candidate genes are functionally enriched in stimulus-responsive pathways, including responses to biotic and abiotic stimuli and immune responses. In addition, stimulus-responsive genes are repressed to low-parent levels in hybrids with high BPH, whereas middle-parent expression patterns are exhibited in hybrids with no BPH. Our study reveals a genomic architecture for understanding the molecular mechanisms of biomass heterosis in Arabidopsis , in which the accumulation of the superior alleles of genes involved in metabolic and cellular processes improve the development and growth of hybrids, whereas the overall repressed expression of stimulus-responsive genes prioritizes growth over responding to environmental stimuli in hybrids under normal conditions.
Xu, Shuqing; Schlüter, Philipp M
2015-01-01
Divergent selection by pollinators can bring about strong reproductive isolation via changes at few genes of large effect. This has recently been demonstrated in sexually deceptive orchids, where studies (1) quantified the strength of reproductive isolation in the field; (2) identified genes that appear to be causal for reproductive isolation; and (3) demonstrated selection by analysis of natural variation in gene sequence and expression. In a group of closely related Ophrys orchids, specific floral scent components, namely n-alkenes, are the key floral traits that control specific pollinator attraction by chemical mimicry of insect sex pheromones. The genetic basis of species-specific differences in alkene production mainly lies in two biosynthetic genes encoding stearoyl-acyl carrier protein desaturases (SAD) that are associated with floral scent variation and reproductive isolation between closely related species, and evolve under pollinator-mediated selection. However, the implications of this genetic architecture of key floral traits on the evolutionary processes of pollinator adaptation and speciation in this plant group remain unclear. Here, we expand on these recent findings to model scenarios of adaptive evolutionary change at SAD2 and SAD5, their effects on plant fitness (i.e., offspring number), and the dynamics of speciation. Our model suggests that the two-locus architecture of reproductive isolation allows for rapid sympatric speciation by pollinator shift; however, the likelihood of such pollinator-mediated speciation is asymmetric between the two orchid species O. sphegodes and O. exaltata due to different fitness effects of their predominant SAD2 and SAD5 alleles. Our study not only provides insight into pollinator adaptation and speciation mechanisms of sexually deceptive orchids but also demonstrates the power of applying a modeling approach to the study of pollinator-driven ecological speciation.
Ferris, Kathleen G; Barnett, Laryssa L; Blackman, Benjamin K; Willis, John H
2017-01-01
The genetic architecture of local adaptation has been of central interest to evolutionary biologists since the modern synthesis. In addition to classic theory on the effect size of adaptive mutations by Fisher, Kimura and Orr, recent theory addresses the genetic architecture of local adaptation in the face of ongoing gene flow. This theory predicts that with substantial gene flow between populations local adaptation should proceed primarily through mutations of large effect or tightly linked clusters of smaller effect loci. In this study, we investigate the genetic architecture of divergence in flowering time, mating system-related traits, and leaf shape between Mimulus laciniatus and a sympatric population of its close relative M. guttatus. These three traits are probably involved in M. laciniatus' adaptation to a dry, exposed granite outcrop environment. Flowering time and mating system differences are also reproductive isolating barriers making them 'magic traits'. Phenotypic hybrids in this population provide evidence of recent gene flow. Using next-generation sequencing, we generate dense SNP markers across the genome and map quantitative trait loci (QTLs) involved in flowering time, flower size and leaf shape. We find that interspecific divergence in all three traits is due to few QTL of large effect including a highly pleiotropic QTL on chromosome 8. This QTL region contains the pleiotropic candidate gene TCP4 and is involved in ecologically important phenotypes in other Mimulus species. Our results are consistent with theory, indicating that local adaptation and reproductive isolation with gene flow should be due to few loci with large and pleiotropic effects. © 2016 John Wiley & Sons Ltd.
Whitlock, Alexander O. B.; Peck, Kayla M.; Azevedo, Ricardo B. R.; Burch, Christina L.
2016-01-01
Sex is ubiquitous in the natural world, but the nature of its benefits remains controversial. Previous studies have suggested that a major advantage of sex is its ability to eliminate interference between selection on linked mutations, a phenomenon known as Hill–Robertson interference. However, those studies may have missed both important advantages and important disadvantages of sexual reproduction because they did not allow the distributions of mutational effects and interactions (i.e., the genetic architecture) to evolve. Here we investigate how Hill–Robertson interference interacts with an evolving genetic architecture to affect the evolutionary origin and maintenance of sex by simulating evolution in populations of artificial gene networks. We observed a long-term advantage of sex—equilibrium mean fitness of sexual populations exceeded that of asexual populations—that did not depend on population size. We also observed a short-term advantage of sex—sexual modifier mutations readily invaded asexual populations—that increased with population size, as was observed in previous studies. We show that the long- and short-term advantages of sex were both determined by differences between sexual and asexual populations in the evolutionary dynamics of two properties of the genetic architecture: the deleterious mutation rate (Ud) and recombination load (LR). These differences resulted from a combination of selection to minimize LR, which is experienced only by sexuals, and Hill–Robertson interference experienced primarily by asexuals. In contrast to the previous studies, in which Hill–Robertson interference had only a direct impact on the fitness advantages of sex, the impact of Hill–Robertson interference in our simulations was mediated additionally by an indirect impact on the efficiency with which selection acted to reduce Ud. PMID:27098911
Ensemble learning of QTL models improves prediction of complex traits
USDA-ARS?s Scientific Manuscript database
Quantitative trait locus (QTL) models can provide useful insights into trait genetic architecture because of their straightforward interpretability, but are less useful for genetic prediction due to difficulty in including the effects of numerous small effect loci without overfitting. Tight linkage ...
DRO1 influences root system architecture in Arabidopsis and Prunus species
USDA-ARS?s Scientific Manuscript database
Roots provide essential uptake of water and nutrients from the soil, as well as anchorage and stability for the whole plant. Root orientation or angle is an important component of the overall architecture and depth of the root system; however, little is known about the genetic control of this trai...
Vasilopoulos, Terrie; Franz, Carol E.; Panizzon, Matthew S.; Xian, Hong; Grant, Michael D.; Lyons, Michael J; Toomey, Rosemary; Jacobson, Kristen C.; Kremen, William S.
2012-01-01
Objective To examine how genes and environments contribute to relationships among Trail Making test conditions and the extent to which these conditions have unique genetic and environmental influences. Method Participants included 1237 middle-aged male twins from the Vietnam-Era Twin Study of Aging (VESTA). The Delis-Kaplan Executive Function System Trail Making test included visual searching, number and letter sequencing, and set-shifting components. Results Phenotypic correlations among Trails conditions ranged from 0.29 – 0.60, and genes accounted for the majority (58–84%) of each correlation. Overall heritability ranged from 0.34 to 0.62 across conditions. Phenotypic factor analysis suggested a single factor. In contrast, genetic models revealed a single common genetic factor but also unique genetic influences separate from the common factor. Genetic variance (i.e., heritability) of number and letter sequencing was completely explained by the common genetic factor while unique genetic influences separate from the common factor accounted for 57% and 21% of the heritabilities of visual search and set-shifting, respectively. After accounting for general cognitive ability, unique genetic influences accounted for 64% and 31% of those heritabilities. Conclusions A common genetic factor, most likely representing a combination of speed and sequencing accounted for most of the correlation among Trails 1–4. Distinct genetic factors, however, accounted for a portion of variance in visual scanning and set-shifting. Thus, although traditional phenotypic shared variance analysis techniques suggest only one general factor underlying different neuropsychological functions in non-patient populations, examining the genetic underpinnings of cognitive processes with twin analysis can uncover more complex etiological processes. PMID:22201299
Genetics of coronary artery disease and myocardial infarction
Dai, Xuming; Wiernek, Szymon; Evans, James P; Runge, Marschall S
2016-01-01
Atherosclerotic coronary artery disease (CAD) comprises a broad spectrum of clinical entities that include asymptomatic subclinical atherosclerosis and its clinical complications, such as angina pectoris, myocardial infarction (MI) and sudden cardiac death. CAD continues to be the leading cause of death in industrialized society. The long-recognized familial clustering of CAD suggests that genetics plays a central role in its development, with the heritability of CAD and MI estimated at approximately 50% to 60%. Understanding the genetic architecture of CAD and MI has proven to be difficult and costly due to the heterogeneity of clinical CAD and the underlying multi-decade complex pathophysiological processes that involve both genetic and environmental interactions. This review describes the clinical heterogeneity of CAD and MI to clarify the disease spectrum in genetic studies, provides a brief overview of the historical understanding and estimation of the heritability of CAD and MI, recounts major gene discoveries of potential causal mutations in familial CAD and MI, summarizes CAD and MI-associated genetic variants identified using candidate gene approaches and genome-wide association studies (GWAS), and summarizes the current status of the construction and validations of genetic risk scores for lifetime risk prediction and guidance for preventive strategies. Potential protective genetic factors against the development of CAD and MI are also discussed. Finally, GWAS have identified multiple genetic factors associated with an increased risk of in-stent restenosis following stent placement for obstructive CAD. This review will also address genetic factors associated with in-stent restenosis, which may ultimately guide clinical decision-making regarding revascularization strategies for patients with CAD and MI. PMID:26839654
Pierce, Brandon L; Ahsan, Habibul; Vanderweele, Tyler J
2011-06-01
Mendelian Randomization (MR) studies assess the causality of an exposure-disease association using genetic determinants [i.e. instrumental variables (IVs)] of the exposure. Power and IV strength requirements for MR studies using multiple genetic variants have not been explored. We simulated cohort data sets consisting of a normally distributed disease trait, a normally distributed exposure, which affects this trait and a biallelic genetic variant that affects the exposure. We estimated power to detect an effect of exposure on disease for varying allele frequencies, effect sizes and samples sizes (using two-stage least squares regression on 10,000 data sets-Stage 1 is a regression of exposure on the variant. Stage 2 is a regression of disease on the fitted exposure). Similar analyses were conducted using multiple genetic variants (5, 10, 20) as independent or combined IVs. We assessed IV strength using the first-stage F statistic. Simulations of realistic scenarios indicate that MR studies will require large (n > 1000), often very large (n > 10,000), sample sizes. In many cases, so-called 'weak IV' problems arise when using multiple variants as independent IVs (even with as few as five), resulting in biased effect estimates. Combining genetic factors into fewer IVs results in modest power decreases, but alleviates weak IV problems. Ideal methods for combining genetic factors depend upon knowledge of the genetic architecture underlying the exposure. The feasibility of well-powered, unbiased MR studies will depend upon the amount of variance in the exposure that can be explained by known genetic factors and the 'strength' of the IV set derived from these genetic factors.
Hidden genetic variation in the germline genome of Tetrahymena thermophila.
Dimond, K L; Zufall, R A
2016-06-01
Genome architecture varies greatly among eukaryotes. This diversity may profoundly affect the origin and maintenance of genetic variation within a population. Ciliates are microbial eukaryotes with unusual genome features, such as the separation of germline and somatic genomes within a single cell and amitotic division. These features have previously been proposed to increase the rate of molecular evolution in these species. Here, we assessed the fitness effects of genetic variation in the two genomes of natural isolates of the ciliate Tetrahymena thermophila. We find more extensive genetic variation in fitness in the transcriptionally silent germline genome than in the expressed somatic genome. Surprisingly, this variation is not primarily deleterious, but has both beneficial and deleterious effects. We conclude that Tetrahymena genome architecture allows for the maintenance of genetic variation that would otherwise be eliminated by selection. We consider the effect of selection on the two genomes and the impacts of reproductive strategies and the mechanism of sex determination on the structure of this variation. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.
The Molecular Genetic Architecture of Self-Employment
van der Loos, Matthijs J. H. M.; Rietveld, Cornelius A.; Eklund, Niina; Koellinger, Philipp D.; Rivadeneira, Fernando; Abecasis, Gonçalo R.; Ankra-Badu, Georgina A.; Baumeister, Sebastian E.; Benjamin, Daniel J.; Biffar, Reiner; Blankenberg, Stefan; Boomsma, Dorret I.; Cesarini, David; Cucca, Francesco; de Geus, Eco J. C.; Dedoussis, George; Deloukas, Panos; Dimitriou, Maria; Eiriksdottir, Guðny; Eriksson, Johan; Gieger, Christian; Gudnason, Vilmundur; Höhne, Birgit; Holle, Rolf; Hottenga, Jouke-Jan; Isaacs, Aaron; Järvelin, Marjo-Riitta; Johannesson, Magnus; Kaakinen, Marika; Kähönen, Mika; Kanoni, Stavroula; Laaksonen, Maarit A.; Lahti, Jari; Launer, Lenore J.; Lehtimäki, Terho; Loitfelder, Marisa; Magnusson, Patrik K. E.; Naitza, Silvia; Oostra, Ben A.; Perola, Markus; Petrovic, Katja; Quaye, Lydia; Raitakari, Olli; Ripatti, Samuli; Scheet, Paul; Schlessinger, David; Schmidt, Carsten O.; Schmidt, Helena; Schmidt, Reinhold; Senft, Andrea; Smith, Albert V.; Spector, Timothy D.; Surakka, Ida; Svento, Rauli; Terracciano, Antonio; Tikkanen, Emmi; van Duijn, Cornelia M.; Viikari, Jorma; Völzke, Henry; Wichmann, H. -Erich; Wild, Philipp S.; Willems, Sara M.; Willemsen, Gonneke; van Rooij, Frank J. A.; Groenen, Patrick J. F.; Uitterlinden, André G.; Hofman, Albert; Thurik, A. Roy
2013-01-01
Economic variables such as income, education, and occupation are known to affect mortality and morbidity, such as cardiovascular disease, and have also been shown to be partly heritable. However, very little is known about which genes influence economic variables, although these genes may have both a direct and an indirect effect on health. We report results from the first large-scale collaboration that studies the molecular genetic architecture of an economic variable–entrepreneurship–that was operationalized using self-employment, a widely-available proxy. Our results suggest that common SNPs when considered jointly explain about half of the narrow-sense heritability of self-employment estimated in twin data (σg 2/σP 2 = 25%, h 2 = 55%). However, a meta-analysis of genome-wide association studies across sixteen studies comprising 50,627 participants did not identify genome-wide significant SNPs. 58 SNPs with p<10−5 were tested in a replication sample (n = 3,271), but none replicated. Furthermore, a gene-based test shows that none of the genes that were previously suggested in the literature to influence entrepreneurship reveal significant associations. Finally, SNP-based genetic scores that use results from the meta-analysis capture less than 0.2% of the variance in self-employment in an independent sample (p≥0.039). Our results are consistent with a highly polygenic molecular genetic architecture of self-employment, with many genetic variants of small effect. Although self-employment is a multi-faceted, heavily environmentally influenced, and biologically distal trait, our results are similar to those for other genetically complex and biologically more proximate outcomes, such as height, intelligence, personality, and several diseases. PMID:23593239
The genetic architecture of liver enzyme levels: GGT, ALT and AST.
van Beek, Jenny H D A; de Moor, Marleen H M; de Geus, Eco J C; Lubke, Gitta H; Vink, Jacqueline M; Willemsen, Gonneke; Boomsma, Dorret I
2013-07-01
High levels of liver enzymes GGT, ALT and AST are predictive of disease and all-cause mortality and can reflect liver injury, fatty liver and/or oxidative stress. Variation in GGT, ALT and AST levels is heritable. Moderation of the heritability of these liver enzymes by age and sex has not often been explored, and it is not clear to what extent non-additive genetic and shared environmental factors may play a role. To examine the genetic architecture of GGT, ALT and AST, plasma levels were assessed in a large sample of twins, their siblings, parents and spouses (N = 8,371; age range 18-90). For GGT and ALT, but not for AST, genetic structural equation modeling showed evidence for quantitative sex differences in the genetic architecture. There was no evidence for qualitative sex differences, i.e. the same genes were expressed in males and females. Both additive and non-additive genetic factors were important for GGT in females (total heritability h(2) 60 %) and AST in both sexes (total h(2) 43 %). The heritability of GGT in males and ALT for both sexes was due to additive effects only (GGT males 30 %; ALT males 40 %, females 22 %). Evidence emerged for shared environmental factors influencing GGT in the male offspring generation (variance explained 28 %). Thus, the same genes influence liver enzyme levels across sex and age, but their relative contribution to the variation in GGT and ALT differs in males and females and for GGT across age. Given adequate sample sizes these results suggest that genome-wide association studies may result in the detection of new susceptibility loci for liver enzyme levels when pooling results over sex and age.
Test- and behavior-specific genetic factors affect WKY hypoactivity in tests of emotionality.
Baum, Amber E; Solberg, Leah C; Churchill, Gary A; Ahmadiyeh, Nasim; Takahashi, Joseph S; Redei, Eva E
2006-05-15
Inbred Wistar-Kyoto rats consistently display hypoactivity in tests of emotional behavior. We used them to test the hypothesis that the genetic factors underlying the behavioral decision-making process will vary in different environmental contexts. The contexts used were the open-field test (OFT), a novel environment with no explicit threats present, and the defensive-burying test (DB), a habituated environment into which a threat has been introduced. Rearing, a voluntary behavior was measured in both tests, and our study was the first to look for genetic loci affecting grooming, a relatively automatic, stress-responsive stereotyped behavior. Quantitative trait locus analysis was performed on a population of 486 F2 animals bred from reciprocal inter-crosses. The genetic architectures of DB and OFT rearing, and of DB and OFT grooming, were compared. There were no common loci affecting grooming behavior in both tests. These different contexts produced the stereotyped behavior via different pathways, and genetic factors seem to influence the decision-making pathways and not the expression of the behavior. Three loci were found that affected rearing behavior in both tests. However, in both contexts, other loci had greater effects on the behavior. Our results imply that environmental context's effects on decision-making vary depending on the category of behavior.
Evolution, revolution and heresy in the genetics of infectious disease susceptibility
Hill, Adrian V. S.
2012-01-01
Infectious pathogens have long been recognized as potentially powerful agents impacting on the evolution of human genetic diversity. Analysis of large-scale case–control studies provides one of the most direct means of identifying human genetic variants that currently impact on susceptibility to particular infectious diseases. For over 50 years candidate gene studies have been used to identify loci for many major causes of human infectious mortality, including malaria, tuberculosis, human immunodeficiency virus/acquired immunodeficiency syndrome, bacterial pneumonia and hepatitis. But with the advent of genome-wide approaches, many new loci have been identified in diverse populations. Genome-wide linkage studies identified a few loci, but genome-wide association studies are proving more successful, and both exome and whole-genome sequencing now offer a revolutionary increase in power. Opinions differ on the extent to which the genetic component to common disease susceptibility is encoded by multiple high frequency or rare variants, and the heretical view that most infectious diseases might even be monogenic has been advocated recently. Review of findings to date suggests that the genetic architecture of infectious disease susceptibility may be importantly different from that of non-infectious diseases, and it is suggested that natural selection may be the driving force underlying this difference. PMID:22312051
Genetic dissection of adaptive form and function in rapidly speciating cichlid fishes.
Henning, Frederico; Machado-Schiaffino, Gonzalo; Baumgarten, Lukas; Meyer, Axel
2017-05-01
Genes of major phenotypic effects and strong genetic correlations can facilitate adaptation, direct selective responses, and potentially lead to phenotypic convergence. However, the preponderance of this type of genetic architecture in repeatedly evolved adaptations remains unknown. Using hybrids between Haplochromis chilotes (thick-lipped) and Pundamilia nyererei (thin-lipped) we investigated the genetics underlying hypertrophied lips and elongated heads, traits that evolved repeatedly in cichlids. At least 25 loci of small-to-moderate and mainly additive effects were detected. Phenotypic variation in lip and head morphology was largely independent. Although several QTL overlapped for lip and head morphology traits, they were often of opposite effects. The distribution of effect signs suggests strong selection on lips. The fitness implications of several detected loci were demonstrated using a laboratory assay testing for the association between genotype and variation in foraging performance. The persistence of low fitness alleles in head morphology appears to be maintained through antagonistic pleiotropy/close linkage with positive-effect lip morphology alleles. Rather than being based on few major loci with strong positive genetic correlations, our results indicate that the evolution of the Lake Victoria thick-lipped ecomorph is the result of selection on numerous loci distributed throughout the genome. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.
The Genetics of Autism: Key Issues, Recent Findings and Clinical Implications
El-Fishawy, Paul; State, Matthew W.
2010-01-01
Autism spectrum disorders (ASD’S) are highly heritable. Consequently, gene discovery promises to help illuminate the pathophysiology of these syndromes, yielding important opportunities for the development of novel treatments and a more nuanced understanding of the natural history of these disorders. Although the underlying genetic architecture of ASD’s is not yet known, the literature demonstrates that it is not, writ large, a monogenic disorder with Mendelian inheritance, but rather a group of complex genetic syndromes with risk deriving from genetic variations in multiple genes. The widely accepted “Common Disease-Common Variant” hypothesis predicts that the risk alleles in ASD’s and other complex disorders will be common in the general population. However, recent evidence from gene discovery efforts in a wide range of diseases raises important questions regarding the overall applicability of the theory and the extent of its usefulness in explaining individual genetic liability. In contrast, considerable evidence points to the importance of rare alleles both with regard to their value in providing a foothold into the molecular mechanisms of ASD and their overall contribution to the population-wide risk. This chapter reviews the origins of the common versus rare variant debate, highlights recent findings in the field, and addresses the clinical implications of both common and rare variant discoveries. PMID:20159341
High temperatures reveal cryptic genetic variation in a polymorphic female sperm storage organ.
Berger, David; Bauerfeind, Stephanie Sandra; Blanckenhorn, Wolf Ulrich; Schäfer, Martin Andreas
2011-10-01
Variation in female reproductive morphology may play a decisive role in reproductive isolation by affecting the relative fertilization success of alternative male phenotypes. Yet, knowledge of how environmental variation may influence the development of the female reproductive tract and thus alter the arena of postcopulatory sexual selection is limited. Yellow dung fly females possess either three or four sperm storage compartments, a polymorphism with documented influence on sperm precedence. We performed a quantitative genetics study including 12 populations reared at three developmental temperatures complemented by extensive field data to show that warm developmental temperatures increase the frequency of females with four compartments, revealing striking hidden genetic variation for the polymorphism. Systematic genetic differentiation in growth rate and spermathecal number along latitude, and phenotypic covariance between the traits across temperature treatments suggest that the genetic architecture underlying the polymorphism is shaped by selection on metabolic rate. Our findings illustrate how temperature can modulate the preconditions for sexual selection by differentially exposing novel variation in reproductive morphology. This implies that environmental change may substantially alter the dynamics of sexual selection. We further discuss how temperature-dependent developmental plasticity may have contributed to observed rapid evolutionary transitions in spermathecal morphology. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.
Gene networks associated with conditional fear in mice identified using a systems genetics approach
2011-01-01
Background Our understanding of the genetic basis of learning and memory remains shrouded in mystery. To explore the genetic networks governing the biology of conditional fear, we used a systems genetics approach to analyze a hybrid mouse diversity panel (HMDP) with high mapping resolution. Results A total of 27 behavioral quantitative trait loci were mapped with a false discovery rate of 5%. By integrating fear phenotypes, transcript profiling data from hippocampus and striatum and also genotype information, two gene co-expression networks correlated with context-dependent immobility were identified. We prioritized the key markers and genes in these pathways using intramodular connectivity measures and structural equation modeling. Highly connected genes in the context fear modules included Psmd6, Ube2a and Usp33, suggesting an important role for ubiquitination in learning and memory. In addition, we surveyed the architecture of brain transcript regulation and demonstrated preservation of gene co-expression modules in hippocampus and striatum, while also highlighting important differences. Rps15a, Kif3a, Stard7, 6330503K22RIK, and Plvap were among the individual genes whose transcript abundance were strongly associated with fear phenotypes. Conclusion Application of our multi-faceted mapping strategy permits an increasingly detailed characterization of the genetic networks underlying behavior. PMID:21410935
Avia, Komlan; Coelho, Susana M.; Montecinos, Gabriel J.; Cormier, Alexandre; Lerck, Fiona; Mauger, Stéphane; Faugeron, Sylvain; Valero, Myriam; Cock, J. Mark; Boudry, Pierre
2017-01-01
Deciphering the genetic architecture of adaptation of brown algae to environmental stresses such as temperature and salinity is of evolutionary as well as of practical interest. The filamentous brown alga Ectocarpus sp. is a model for the brown algae and its genome has been sequenced. As sessile organisms, brown algae need to be capable of resisting the various abiotic stressors that act in the intertidal zone (e.g. osmotic pressure, temperature, salinity, UV radiation) and previous studies have shown that an important proportion of the expressed genes is regulated in response to hyposaline, hypersaline or oxidative stress conditions. Using the double digest RAD sequencing method, we constructed a dense genetic map with 3,588 SNP markers and identified 39 QTLs for growth-related traits and their plasticity under different temperature and salinity conditions (tolerance to high temperature and low salinity). GO enrichment tests within QTL intervals highlighted membrane transport processes such as ion transporters. Our study represents a significant step towards deciphering the genetic basis of adaptation of Ectocarpus sp. to stress conditions and provides a substantial resource to the increasing list of tools generated for the species. PMID:28256542
An integrated analysis of genes and functional pathways for aggression in human and rodent models.
Zhang-James, Yanli; Fernàndez-Castillo, Noèlia; Hess, Jonathan L; Malki, Karim; Glatt, Stephen J; Cormand, Bru; Faraone, Stephen V
2018-06-01
Human genome-wide association studies (GWAS), transcriptome analyses of animal models, and candidate gene studies have advanced our understanding of the genetic architecture of aggressive behaviors. However, each of these methods presents unique limitations. To generate a more confident and comprehensive view of the complex genetics underlying aggression, we undertook an integrated, cross-species approach. We focused on human and rodent models to derive eight gene lists from three main categories of genetic evidence: two sets of genes identified in GWAS studies, four sets implicated by transcriptome-wide studies of rodent models, and two sets of genes with causal evidence from online Mendelian inheritance in man (OMIM) and knockout (KO) mice reports. These gene sets were evaluated for overlap and pathway enrichment to extract their similarities and differences. We identified enriched common pathways such as the G-protein coupled receptor (GPCR) signaling pathway, axon guidance, reelin signaling in neurons, and ERK/MAPK signaling. Also, individual genes were ranked based on their cumulative weights to quantify their importance as risk factors for aggressive behavior, which resulted in 40 top-ranked and highly interconnected genes. The results of our cross-species and integrated approach provide insights into the genetic etiology of aggression.
National human genome projects: an update and an agenda.
An, Joon Yong
2017-01-01
Population genetic and human genetic studies are being accelerated with genome technology and data sharing. Accordingly, in the past 10 years, several countries have initiated genetic research using genome technology and identified the genetic architecture of the ethnic groups living in the corresponding country or suggested the genetic foundation of a social phenomenon. Genetic research has been conducted from epidemiological studies that previously described the health or disease conditions in defined population. This perspective summarizes national genome projects conducted in the past 10 years and introduces case studies to utilize genomic data in genetic research.
Field-based phenomics for plant genetics research
USDA-ARS?s Scientific Manuscript database
Perhaps the greatest challenge for crop research in the 21st century is how to predict crop performance as a function of genetic architecture and climate change. Advances in “next generation” DNA sequencing have greatly reduced genotyping costs. Methods for characterization of plant traits (phenotyp...
Kimmel, Charles B.; Cresko, William A.; Phillips, Patrick C.; Ullmann, Bonnie; Currey, Mark; von Hippel, Frank; Kristjánsson, Bjarni K.; Gelmond, Ofer; McGuigan, Katrina
2014-01-01
Evolution of similar phenotypes in independent populations is often taken as evidence of adaptation to the same fitness optimum. However, the genetic architecture of traits might cause evolution to proceed more often toward particular phenotypes, and less often toward others, independently of the adaptive value of the traits. Freshwater populations of Alaskan threespine stickleback have repeatedly evolved the same distinctive opercle shape after divergence from an oceanic ancestor. Here we demonstrate that this pattern of parallel evolution is widespread, distinguishing oceanic and freshwater populations across the Pacific Coast of North America and Iceland. We test whether this parallel evolution reflects genetic bias by estimating the additive genetic variance– covariance matrix (G) of opercle shape in an Alaskan oceanic (putative ancestral) population. We find significant additive genetic variance for opercle shape and that G has the potential to be biasing, because of the existence of regions of phenotypic space with low additive genetic variation. However, evolution did not occur along major eigenvectors of G, rather it occurred repeatedly in the same directions of high evolvability. We conclude that the parallel opercle evolution is most likely due to selection during adaptation to freshwater habitats, rather than due to biasing effects of opercle genetic architecture. PMID:22276538
The genetic architecture of gene expression levels in wild baboons.
Tung, Jenny; Zhou, Xiang; Alberts, Susan C; Stephens, Matthew; Gilad, Yoav
2015-02-25
Primate evolution has been argued to result, in part, from changes in how genes are regulated. However, we still know little about gene regulation in natural primate populations. We conducted an RNA sequencing (RNA-seq)-based study of baboons from an intensively studied wild population. We performed complementary expression quantitative trait locus (eQTL) mapping and allele-specific expression analyses, discovering substantial evidence for, and surprising power to detect, genetic effects on gene expression levels in the baboons. eQTL were most likely to be identified for lineage-specific, rapidly evolving genes; interestingly, genes with eQTL significantly overlapped between baboons and a comparable human eQTL data set. Our results suggest that genes vary in their tolerance of genetic perturbation, and that this property may be conserved across species. Further, they establish the feasibility of eQTL mapping using RNA-seq data alone, and represent an important step towards understanding the genetic architecture of gene expression in primates.
The genetic architecture of gene expression levels in wild baboons
Tung, Jenny; Zhou, Xiang; Alberts, Susan C; Stephens, Matthew; Gilad, Yoav
2015-01-01
Primate evolution has been argued to result, in part, from changes in how genes are regulated. However, we still know little about gene regulation in natural primate populations. We conducted an RNA sequencing (RNA-seq)-based study of baboons from an intensively studied wild population. We performed complementary expression quantitative trait locus (eQTL) mapping and allele-specific expression analyses, discovering substantial evidence for, and surprising power to detect, genetic effects on gene expression levels in the baboons. eQTL were most likely to be identified for lineage-specific, rapidly evolving genes; interestingly, genes with eQTL significantly overlapped between baboons and a comparable human eQTL data set. Our results suggest that genes vary in their tolerance of genetic perturbation, and that this property may be conserved across species. Further, they establish the feasibility of eQTL mapping using RNA-seq data alone, and represent an important step towards understanding the genetic architecture of gene expression in primates. DOI: http://dx.doi.org/10.7554/eLife.04729.001 PMID:25714927
Elucidating the genetic architecture of reproductive ageing in the Japanese population.
Horikoshi, Momoko; Day, Felix R; Akiyama, Masato; Hirata, Makoto; Kamatani, Yoichiro; Matsuda, Koichi; Ishigaki, Kazuyoshi; Kanai, Masahiro; Wright, Hollis; Toro, Carlos A; Ojeda, Sergio R; Lomniczi, Alejandro; Kubo, Michiaki; Ong, Ken K; Perry, John R B
2018-05-17
Population studies elucidating the genetic architecture of reproductive ageing have been largely limited to European ancestries, restricting the generalizability of the findings and overlooking possible key genes poorly captured by common European genetic variation. Here, we report 26 loci (all P < 5 × 10 -8 ) for reproductive ageing, i.e. puberty timing or age at menopause, in a non-European population (up to 67,029 women of Japanese ancestry). Highlighted genes for menopause include GNRH1, which supports a primary, rather than passive, role for hypothalamic-pituitary GnRH signalling in the timing of menopause. For puberty timing, we demonstrate an aetiological role for receptor-like protein tyrosine phosphatases by combining evidence across population genetics and pre- and peri-pubertal changes in hypothalamic gene expression in rodent and primate models. Furthermore, our findings demonstrate widespread differences in allele frequencies and effect estimates between Japanese and European associated variants, highlighting the benefits and challenges of large-scale trans-ethnic approaches.
A Conceptual Framework for Pharmacodynamic Genome-wide Association Studies in Pharmacogenomics
Wu, Rongling; Tong, Chunfa; Wang, Zhong; Mauger, David; Tantisira, Kelan; Szefler, Stanley J.; Chinchilli, Vernon M.; Israel, Elliot
2013-01-01
Summary Genome-wide association studies (GWAS) have emerged as a powerful tool to identify loci that affect drug response or susceptibility to adverse drug reactions. However, current GWAS based on a simple analysis of associations between genotype and phenotype ignores the biochemical reactions of drug response, thus limiting the scope of inference about its genetic architecture. To facilitate the inference of GWAS in pharmacogenomics, we sought to undertake the mathematical integration of the pharmacodynamic process of drug reactions through computational models. By estimating and testing the genetic control of pharmacodynamic and pharmacokinetic parameters, this mechanistic approach does not only enhance the biological and clinical relevance of significant genetic associations, but also improve the statistical power and robustness of gene detection. This report discusses the general principle and development of pharmacodynamics-based GWAS, highlights the practical use of this approach in addressing various pharmacogenomic problems, and suggests that this approach will be an important method to study the genetic architecture of drug responses or reactions. PMID:21920452
High-Throughput Phenotyping and QTL Mapping Reveals the Genetic Architecture of Maize Plant Growth.
Zhang, Xuehai; Huang, Chenglong; Wu, Di; Qiao, Feng; Li, Wenqiang; Duan, Lingfeng; Wang, Ke; Xiao, Yingjie; Chen, Guoxing; Liu, Qian; Xiong, Lizhong; Yang, Wanneng; Yan, Jianbing
2017-03-01
With increasing demand for novel traits in crop breeding, the plant research community faces the challenge of quantitatively analyzing the structure and function of large numbers of plants. A clear goal of high-throughput phenotyping is to bridge the gap between genomics and phenomics. In this study, we quantified 106 traits from a maize ( Zea mays ) recombinant inbred line population ( n = 167) across 16 developmental stages using the automatic phenotyping platform. Quantitative trait locus (QTL) mapping with a high-density genetic linkage map, including 2,496 recombinant bins, was used to uncover the genetic basis of these complex agronomic traits, and 988 QTLs have been identified for all investigated traits, including three QTL hotspots. Biomass accumulation and final yield were predicted using a combination of dissected traits in the early growth stage. These results reveal the dynamic genetic architecture of maize plant growth and enhance ideotype-based maize breeding and prediction. © 2017 American Society of Plant Biologists. All Rights Reserved.
Huang, Chenglong; Wu, Di; Qiao, Feng; Li, Wenqiang; Duan, Lingfeng; Wang, Ke; Xiao, Yingjie; Chen, Guoxing; Liu, Qian; Yang, Wanneng
2017-01-01
With increasing demand for novel traits in crop breeding, the plant research community faces the challenge of quantitatively analyzing the structure and function of large numbers of plants. A clear goal of high-throughput phenotyping is to bridge the gap between genomics and phenomics. In this study, we quantified 106 traits from a maize (Zea mays) recombinant inbred line population (n = 167) across 16 developmental stages using the automatic phenotyping platform. Quantitative trait locus (QTL) mapping with a high-density genetic linkage map, including 2,496 recombinant bins, was used to uncover the genetic basis of these complex agronomic traits, and 988 QTLs have been identified for all investigated traits, including three QTL hotspots. Biomass accumulation and final yield were predicted using a combination of dissected traits in the early growth stage. These results reveal the dynamic genetic architecture of maize plant growth and enhance ideotype-based maize breeding and prediction. PMID:28153923
Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap.
Gandal, Michael J; Haney, Jillian R; Parikshak, Neelroop N; Leppa, Virpi; Ramaswami, Gokul; Hartl, Chris; Schork, Andrew J; Appadurai, Vivek; Buil, Alfonso; Werge, Thomas M; Liu, Chunyu; White, Kevin P; Horvath, Steve; Geschwind, Daniel H
2018-02-09
The predisposition to neuropsychiatric disease involves a complex, polygenic, and pleiotropic genetic architecture. However, little is known about how genetic variants impart brain dysfunction or pathology. We used transcriptomic profiling as a quantitative readout of molecular brain-based phenotypes across five major psychiatric disorders-autism, schizophrenia, bipolar disorder, depression, and alcoholism-compared with matched controls. We identified patterns of shared and distinct gene-expression perturbations across these conditions. The degree of sharing of transcriptional dysregulation is related to polygenic (single-nucleotide polymorphism-based) overlap across disorders, suggesting a substantial causal genetic component. This comprehensive systems-level view of the neurobiological architecture of major neuropsychiatric illness demonstrates pathways of molecular convergence and specificity. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.
Rübben, Albert; Nordhoff, Ole
2013-01-01
Summary Most clinically distinguishable malignant tumors are characterized by specific mutations, specific patterns of chromosomal rearrangements and a predominant mechanism of genetic instability but it remains unsolved whether modifications of cancer genomes can be explained solely by mutations and selection through the cancer microenvironment. It has been suggested that internal dynamics of genomic modifications as opposed to the external evolutionary forces have a significant and complex impact on Darwinian species evolution. A similar situation can be expected for somatic cancer evolution as molecular key mechanisms encountered in species evolution also constitute prevalent mutation mechanisms in human cancers. This assumption is developed into a systems approach of carcinogenesis which focuses on possible inner constraints of the genome architecture on lineage selection during somatic cancer evolution. The proposed systems approach can be considered an analogy to the concept of evolvability in species evolution. The principal hypothesis is that permissive or restrictive effects of the genome architecture on lineage selection during somatic cancer evolution exist and have a measurable impact. The systems approach postulates three classes of lineage selection effects of the genome architecture on somatic cancer evolution: i) effects mediated by changes of fitness of cells of cancer lineage, ii) effects mediated by changes of mutation probabilities and iii) effects mediated by changes of gene designation and physical and functional genome redundancy. Physical genome redundancy is the copy number of identical genetic sequences. Functional genome redundancy of a gene or a regulatory element is defined as the number of different genetic elements, regardless of copy number, coding for the same specific biological function within a cancer cell. Complex interactions of the genome architecture on lineage selection may be expected when modifications of the genome architecture have multiple and possibly opposed effects which manifest themselves at disparate times and progression stages. Dissection of putative mechanisms mediating constraints exerted by the genome architecture on somatic cancer evolution may provide an algorithm for understanding and predicting as well as modifying somatic cancer evolution in individual patients. PMID:23336076
Powell, Joseph E.; Henders, Anjali K.; McRae, Allan F.; Kim, Jinhee; Hemani, Gibran; Martin, Nicholas G.; Dermitzakis, Emmanouil T.; Gibson, Greg
2013-01-01
There is increasing evidence that heritable variation in gene expression underlies genetic variation in susceptibility to disease. Therefore, a comprehensive understanding of the similarity between relatives for transcript variation is warranted—in particular, dissection of phenotypic variation into additive and non-additive genetic factors and shared environmental effects. We conducted a gene expression study in blood samples of 862 individuals from 312 nuclear families containing MZ or DZ twin pairs using both pedigree and genotype information. From a pedigree analysis we show that the vast majority of genetic variation across 17,994 probes is additive, although non-additive genetic variation is identified for 960 transcripts. For 180 of the 960 transcripts with non-additive genetic variation, we identify expression quantitative trait loci (eQTL) with dominance effects in a sample of 339 unrelated individuals and replicate 31% of these associations in an independent sample of 139 unrelated individuals. Over-dominance was detected and replicated for a trans association between rs12313805 and ETV6, located 4MB apart on chromosome 12. Surprisingly, only 17 probes exhibit significant levels of common environmental effects, suggesting that environmental and lifestyle factors common to a family do not affect expression variation for most transcripts, at least those measured in blood. Consistent with the genetic architecture of common diseases, gene expression is predominantly additive, but a minority of transcripts display non-additive effects. PMID:23696747
Powell, Joseph E; Henders, Anjali K; McRae, Allan F; Kim, Jinhee; Hemani, Gibran; Martin, Nicholas G; Dermitzakis, Emmanouil T; Gibson, Greg; Montgomery, Grant W; Visscher, Peter M
2013-05-01
There is increasing evidence that heritable variation in gene expression underlies genetic variation in susceptibility to disease. Therefore, a comprehensive understanding of the similarity between relatives for transcript variation is warranted--in particular, dissection of phenotypic variation into additive and non-additive genetic factors and shared environmental effects. We conducted a gene expression study in blood samples of 862 individuals from 312 nuclear families containing MZ or DZ twin pairs using both pedigree and genotype information. From a pedigree analysis we show that the vast majority of genetic variation across 17,994 probes is additive, although non-additive genetic variation is identified for 960 transcripts. For 180 of the 960 transcripts with non-additive genetic variation, we identify expression quantitative trait loci (eQTL) with dominance effects in a sample of 339 unrelated individuals and replicate 31% of these associations in an independent sample of 139 unrelated individuals. Over-dominance was detected and replicated for a trans association between rs12313805 and ETV6, located 4MB apart on chromosome 12. Surprisingly, only 17 probes exhibit significant levels of common environmental effects, suggesting that environmental and lifestyle factors common to a family do not affect expression variation for most transcripts, at least those measured in blood. Consistent with the genetic architecture of common diseases, gene expression is predominantly additive, but a minority of transcripts display non-additive effects.
San-Jose, Luis M; Ducret, Valérie; Ducrest, Anne-Lyse; Simon, Céline; Roulin, Alexandre
2017-10-01
The mean phenotypic effects of a discovered variant help to predict major aspects of the evolution and inheritance of a phenotype. However, differences in the phenotypic variance associated to distinct genotypes are often overlooked despite being suggestive of processes that largely influence phenotypic evolution, such as interactions between the genotypes with the environment or the genetic background. We present empirical evidence for a mutation at the melanocortin-1-receptor gene, a major vertebrate coloration gene, affecting phenotypic variance in the barn owl, Tyto alba. The white MC1R allele, which associates with whiter plumage coloration, also associates with a pronounced phenotypic and additive genetic variance for distinct color traits. Contrarily, the rufous allele, associated with a rufous coloration, relates to a lower phenotypic and additive genetic variance, suggesting that this allele may be epistatic over other color loci. Variance differences between genotypes entailed differences in the strength of phenotypic and genetic associations between color traits, suggesting that differences in variance also alter the level of integration between traits. This study highlights that addressing variance differences of genotypes in wild populations provides interesting new insights into the evolutionary mechanisms and the genetic architecture underlying the phenotype. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.
Yeung, Ellen W; Craggs, Jason G; Gizer, Ian R
2017-11-01
Alcohol use disorder (AUD) is highly comorbid with chronic pain (CP). Evidence has suggested that neuroadaptive processes characterized by reward deficit and stress surfeit are involved in the development of AUD and pain chronification. Neurological data suggest that shared genetic architecture associated with the reward and stress systems may contribute to the comorbidity of AUD and CP. This monograph first delineates the prevailing theories of the development of AUD and pain chronification focusing on the reward and stress systems. It then provides a brief summary of relevant neurological findings followed by an evaluation of evidence documented by molecular genetic studies. Candidate gene association studies have provided some initial support for the genetic overlap between AUD and CP; however, these results must be interpreted with caution until studies with sufficient statistical power are conducted and replications obtained. Genomewide association studies have suggested a number of genes (e.g., TBX19, HTR7, and ADRA1A) that are either directly or indirectly related to the reward and stress systems in the AUD and CP literature. Evidence reviewed in this monograph suggests that shared genetic liability underlying the comorbidity between AUD and CP, if present, is likely to be complex. As the advancement in molecular genetic methods continues, future studies may show broader central nervous system involvement in AUD-CP comorbidity. Copyright © 2017 by the Research Society on Alcoholism.
Merrill, R M; Naisbit, R E; Mallet, J; Jiggins, C D
2013-09-01
Shifts in host-plant use by phytophagous insects have played a central role in their diversification. Evolving host-use strategies will reflect a trade-off between selection pressures. The ecological niche of herbivorous insects is partitioned along several dimensions, and if populations remain in contact, recombination will break down associations between relevant loci. As such, genetic architecture can profoundly affect the coordinated divergence of traits and subsequently the ability to exploit novel habitats. The closely related species Heliconius cydno and H. melpomene differ in mimetic colour pattern, habitat and host-plant use. We investigate the selection pressures and genetic basis underlying host-use differences in these two species. Host-plant surveys reveal that H. melpomene specializes on a single species of Passiflora. This is also true for the majority of other Heliconius species in secondary growth forest at our study site, as expected under a model of interspecific competition. In contrast, H. cydno, which uses closed-forest habitats where both Heliconius and Passiflora are less common, appears not to be restricted by competition and uses a broad selection of the available Passiflora. However, other selection pressures are likely involved, and field experiments reveal that early larval survival of both butterfly species is highest on Passiflora menispermifolia, but most markedly so for H. melpomene, the specialist on that host. Finally, we demonstrate an association between host-plant acceptance and colour pattern amongst interspecific hybrids, suggesting that major loci underlying these important ecological traits are physically linked in the genome. Together, our results reveal ecological and genetic associations between shifts in habitat, host use and mimetic colour pattern that have likely facilitated both speciation and coexistence. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.
The Brassica oleracea genome reveals the asymmetrical evolution of polyploid genomes
Liu, Shengyi; Liu, Yumei; Yang, Xinhua; Tong, Chaobo; Edwards, David; Parkin, Isobel A. P.; Zhao, Meixia; Ma, Jianxin; Yu, Jingyin; Huang, Shunmou; Wang, Xiyin; Wang, Junyi; Lu, Kun; Fang, Zhiyuan; Bancroft, Ian; Yang, Tae-Jin; Hu, Qiong; Wang, Xinfa; Yue, Zhen; Li, Haojie; Yang, Linfeng; Wu, Jian; Zhou, Qing; Wang, Wanxin; King, Graham J; Pires, J. Chris; Lu, Changxin; Wu, Zhangyan; Sampath, Perumal; Wang, Zhuo; Guo, Hui; Pan, Shengkai; Yang, Limei; Min, Jiumeng; Zhang, Dong; Jin, Dianchuan; Li, Wanshun; Belcram, Harry; Tu, Jinxing; Guan, Mei; Qi, Cunkou; Du, Dezhi; Li, Jiana; Jiang, Liangcai; Batley, Jacqueline; Sharpe, Andrew G; Park, Beom-Seok; Ruperao, Pradeep; Cheng, Feng; Waminal, Nomar Espinosa; Huang, Yin; Dong, Caihua; Wang, Li; Li, Jingping; Hu, Zhiyong; Zhuang, Mu; Huang, Yi; Huang, Junyan; Shi, Jiaqin; Mei, Desheng; Liu, Jing; Lee, Tae-Ho; Wang, Jinpeng; Jin, Huizhe; Li, Zaiyun; Li, Xun; Zhang, Jiefu; Xiao, Lu; Zhou, Yongming; Liu, Zhongsong; Liu, Xuequn; Qin, Rui; Tang, Xu; Liu, Wenbin; Wang, Yupeng; Zhang, Yangyong; Lee, Jonghoon; Kim, Hyun Hee; Denoeud, France; Xu, Xun; Liang, Xinming; Hua, Wei; Wang, Xiaowu; Wang, Jun; Chalhoub, Boulos; Paterson, Andrew H
2014-01-01
Polyploidization has provided much genetic variation for plant adaptive evolution, but the mechanisms by which the molecular evolution of polyploid genomes establishes genetic architecture underlying species differentiation are unclear. Brassica is an ideal model to increase knowledge of polyploid evolution. Here we describe a draft genome sequence of Brassica oleracea, comparing it with that of its sister species B. rapa to reveal numerous chromosome rearrangements and asymmetrical gene loss in duplicated genomic blocks, asymmetrical amplification of transposable elements, differential gene co-retention for specific pathways and variation in gene expression, including alternative splicing, among a large number of paralogous and orthologous genes. Genes related to the production of anticancer phytochemicals and morphological variations illustrate consequences of genome duplication and gene divergence, imparting biochemical and morphological variation to B. oleracea. This study provides insights into Brassica genome evolution and will underpin research into the many important crops in this genus. PMID:24852848
Protists and the Wild, Wild West of Gene Expression: New Frontiers, Lawlessness, and Misfits.
Smith, David Roy; Keeling, Patrick J
2016-09-08
The DNA double helix has been called one of life's most elegant structures, largely because of its universality, simplicity, and symmetry. The expression of information encoded within DNA, however, can be far from simple or symmetric and is sometimes surprisingly variable, convoluted, and wantonly inefficient. Although exceptions to the rules exist in certain model systems, the true extent to which life has stretched the limits of gene expression is made clear by nonmodel systems, particularly protists (microbial eukaryotes). The nuclear and organelle genomes of protists are subject to the most tangled forms of gene expression yet identified. The complicated and extravagant picture of the underlying genetics of eukaryotic microbial life changes how we think about the flow of genetic information and the evolutionary processes shaping it. Here, we discuss the origins, diversity, and growing interest in noncanonical protist gene expression and its relationship to genomic architecture.
Genome-wide analysis identifies 12 loci influencing human reproductive behavior
Barban, Nicola; Jansen, Rick; de Vlaming, Ronald; Vaez, Ahmad; Mandemakers, Jornt J.; Tropf, Felix C.; Shen, Xia; Wilson, James F.; Chasman, Daniel I.; Nolte, Ilja M.; Tragante, Vinicius; van der Laan, Sander W.; Perry, John R. B.; Kong, Augustine; Ahluwalia, Tarunveer; Albrecht, Eva; Yerges-Armstrong, Laura; Atzmon, Gil; Auro, Kirsi; Ayers, Kristin; Bakshi, Andrew; Ben-Avraham, Danny; Berger, Klaus; Bergman, Aviv; Bertram, Lars; Bielak, Lawrence F.; Bjornsdottir, Gyda; Bonder, Marc Jan; Broer, Linda; Bui, Minh; Barbieri, Caterina; Cavadino, Alana; Chavarro, Jorge E; Turman, Constance; Concas, Maria Pina; Cordell, Heather J.; Davies, Gail; Eibich, Peter; Eriksson, Nicholas; Esko, Tõnu; Eriksson, Joel; Falahi, Fahimeh; Felix, Janine F.; Fontana, Mark Alan; Franke, Lude; Gandin, Ilaria; Gaskins, Audrey J.; Gieger, Christian; Gunderson, Erica P.; Guo, Xiuqing; Hayward, Caroline; He, Chunyan; Hofer, Edith; Huang, Hongyan; Joshi, Peter K.; Kanoni, Stavroula; Karlsson, Robert; Kiechl, Stefan; Kifley, Annette; Kluttig, Alexander; Kraft, Peter; Lagou, Vasiliki; Lecoeur, Cecile; Lahti, Jari; Li-Gao, Ruifang; Lind, Penelope A.; Liu, Tian; Makalic, Enes; Mamasoula, Crysovalanto; Matteson, Lindsay; Mbarek, Hamdi; McArdle, Patrick F.; McMahon, George; Meddens, S. Fleur W.; Mihailov, Evelin; Miller, Mike; Missmer, Stacey A.; Monnereau, Claire; van der Most, Peter J.; Myhre, Ronny; Nalls, Mike A.; Nutile, Teresa; Panagiota, Kalafati Ioanna; Porcu, Eleonora; Prokopenko, Inga; Rajan, Kumar B.; Rich-Edwards, Janet; Rietveld, Cornelius A.; Robino, Antonietta; Rose, Lynda M.; Rueedi, Rico; Ryan, Kathy; Saba, Yasaman; Schmidt, Daniel; Smith, Jennifer A.; Stolk, Lisette; Streeten, Elizabeth; Tonjes, Anke; Thorleifsson, Gudmar; Ulivi, Sheila; Wedenoja, Juho; Wellmann, Juergen; Willeit, Peter; Yao, Jie; Yengo, Loic; Zhao, Jing Hua; Zhao, Wei; Zhernakova, Daria V.; Amin, Najaf; Andrews, Howard; Balkau, Beverley; Barzilai, Nir; Bergmann, Sven; Biino, Ginevra; Bisgaard, Hans; Bønnelykke, Klaus; Boomsma, Dorret I.; Buring, Julie E.; Campbell, Harry; Cappellani, Stefania; Ciullo, Marina; Cox, Simon R.; Cucca, Francesco; Daniela, Toniolo; Davey-Smith, George; Deary, Ian J.; Dedoussis, George; Deloukas, Panos; van Duijn, Cornelia M.; de Geus, Eco JC.; Eriksson, Johan G.; Evans, Denis A.; Faul, Jessica D.; Felicita, Sala Cinzia; Froguel, Philippe; Gasparini, Paolo; Girotto, Giorgia; Grabe, Hans-Jörgen; Greiser, Karin Halina; Groenen, Patrick J.F.; de Haan, Hugoline G.; Haerting, Johannes; Harris, Tamara B.; Heath, Andrew C.; Heikkilä, Kauko; Hofman, Albert; Homuth, Georg; Holliday, Elizabeth G; Hopper, John; Hypponen, Elina; Jacobsson, Bo; Jaddoe, Vincent W. V.; Johannesson, Magnus; Jugessur, Astanand; Kähönen, Mika; Kajantie, Eero; Kardia, Sharon L.R.; Keavney, Bernard; Kolcic, Ivana; Koponen, Päivikki; Kovacs, Peter; Kronenberg, Florian; Kutalik, Zoltan; La Bianca, Martina; Lachance, Genevieve; Iacono, William; Lai, Sandra; Lehtimäki, Terho; Liewald, David C; Lindgren, Cecilia; Liu, Yongmei; Luben, Robert; Lucht, Michael; Luoto, Riitta; Magnus, Per; Magnusson, Patrik K.E.; Martin, Nicholas G.; McGue, Matt; McQuillan, Ruth; Medland, Sarah E.; Meisinger, Christa; Mellström, Dan; Metspalu, Andres; Michela, Traglia; Milani, Lili; Mitchell, Paul; Montgomery, Grant W.; Mook-Kanamori, Dennis; de Mutsert, Renée; Nohr, Ellen A; Ohlsson, Claes; Olsen, Jørn; Ong, Ken K.; Paternoster, Lavinia; Pattie, Alison; Penninx, Brenda WJH; Perola, Markus; Peyser, Patricia A.; Pirastu, Mario; Polasek, Ozren; Power, Chris; Kaprio, Jaakko; Raffel, Leslie J.; Räikkönen, Katri; Raitakari, Olli; Ridker, Paul M.; Ring, Susan M.; Roll, Kathryn; Rudan, Igor; Ruggiero, Daniela; Rujescu, Dan; Salomaa, Veikko; Schlessinger, David; Schmidt, Helena; Schmidt, Reinhold; Schupf, Nicole; Smit, Johannes; Sorice, Rossella; Spector, Tim D.; Starr, John M.; Stöckl, Doris; Strauch, Konstantin; Stumvoll, Michael; Swertz, Morris A.; Thorsteinsdottir, Unnur; Thurik, A. Roy; Timpson, Nicholas J.; Tönjes, Anke; Tung, Joyce Y.; Uitterlinden, André G.; Vaccargiu, Simona; Viikari, Jorma; Vitart, Veronique; Völzke, Henry; Vollenweider, Peter; Vuckovic, Dragana; Waage, Johannes; Wagner, Gert G.; Wang, Jie Jin; Wareham, Nicholas J.; Weir, David R.; Willemsen, Gonneke; Willeit, Johann; Wright, Alan F.; Zondervan, Krina T.; Stefansson, Kari; Krueger, Robert F.; Lee, James J.; Benjamin, Daniel J.; Cesarini, David; Koellinger, Philipp D.; den Hoed, Marcel; Snieder, Harold; Mills, Melinda C.
2017-01-01
The genetic architecture of human reproductive behavior – age at first birth (AFB) and number of children ever born (NEB) – has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified and the underlying mechanisms of AFB and NEB are poorly understood. We report the largest genome-wide association study to date of both sexes including 251,151 individuals for AFB and 343,072 for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study, and four additional loci in a gene-based effort. These loci harbor genes that are likely to play a role – either directly or by affecting non-local gene expression – in human reproduction and infertility, thereby increasing our understanding of these complex traits. PMID:27798627
Definition of architectural ideotypes for good yield capacity in Coffea canephora.
Cilas, Christian; Bar-Hen, Avner; Montagnon, Christophe; Godin, Christophe
2006-03-01
Yield capacity is a target trait for selection of agronomically desirable lines; it is preferred to simple yields recorded over different harvests. Yield capacity is derived using certain architectural parameters used to measure the components of yield capacity. Observation protocols for describing architecture and yield capacity were applied to six clones of coffee trees (Coffea canephora) in a comparative trial. The observations were used to establish architectural databases, which were explored using AMAPmod, a software dedicated to the analyses of plant architecture data. The traits extracted from the database were used to identify architectural parameters for predicting the yield of the plant material studied. Architectural traits are highly heritable and some display strong genetic correlations with cumulated yield. In particular, the proportion of fruiting nodes at plagiotropic level 15 counting from the top of the tree proved to be a good predictor of yield over two fruiting cycles.
Mullen, Lindy B; Arthur Woods, H; Schwartz, Michael K; Sepulveda, Adam J; Lowe, Winsor H
2010-03-01
The network architecture of streams and rivers constrains evolutionary, demographic and ecological processes of freshwater organisms. This consistent architecture also makes stream networks useful for testing general models of population genetic structure and the scaling of gene flow. We examined genetic structure and gene flow in the facultatively paedomorphic Idaho giant salamander, Dicamptodon aterrimus, in stream networks of Idaho and Montana, USA. We used microsatellite data to test population structure models by (i) examining hierarchical partitioning of genetic variation in stream networks; and (ii) testing for genetic isolation by distance along stream corridors vs. overland pathways. Replicated sampling of streams within catchments within three river basins revealed that hierarchical scale had strong effects on genetic structure and gene flow. amova identified significant structure at all hierarchical scales (among streams, among catchments, among basins), but divergence among catchments had the greatest structural influence. Isolation by distance was detected within catchments, and in-stream distance was a strong predictor of genetic divergence. Patterns of genetic divergence suggest that differentiation among streams within catchments was driven by limited migration, consistent with a stream hierarchy model of population structure. However, there was no evidence of migration among catchments within basins, or among basins, indicating that gene flow only counters the effects of genetic drift at smaller scales (within rather than among catchments). These results show the strong influence of stream networks on population structure and genetic divergence of a salamander, with contrasting effects at different hierarchical scales.
Uga, Yusaku; Assaranurak, Ithipong; Kitomi, Yuka; Larson, Brandon G; Craft, Eric J; Shaff, Jon E; McCouch, Susan R; Kochian, Leon V
2018-04-20
Genetic improvement of root system architecture is a promising approach for improved uptake of water and mineral nutrients distributed unevenly in the soil. To identify genomic regions associated with the length of different root types in rice, we quantified root system architecture in a set of 26 chromosome segment substitution lines derived from a cross between lowland indica rice, IR64, and upland tropical japonica rice, Kinandang Patong, (IK-CSSLs), using 2D & 3D root phenotyping platforms. Lengths of seminal and crown roots in the IK-CSSLs grown under hydroponic conditions were measured by 2D image analysis (RootReader2D). Twelve CSSLs showed significantly longer seminal root length than the recurrent parent IR64. Of these, 8 CSSLs also exhibited longer total length of the three longest crown roots compared to IR64. Three-dimensional image analysis (RootReader3D) for these CSSLs grown in gellan gum revealed that only one CSSL, SL1003, showed significantly longer total root length than IR64. To characterize the root morphology of SL1003 under soil conditions, SL1003 was grown in Turface, a soil-like growth media, and roots were quantified using RootReader3D. SL1003 had larger total root length and increased total crown root length than did IR64, although its seminal root length was similar to that of IR64. The larger TRL in SL1003 may be due to increased crown root length. SL1003 carries an introgression from Kinandang Patong on the long arm of chromosome 1 in the genetic background of IR64. We conclude that this region harbors a QTL controlling crown root elongation.
Sang, Dajun; Chen, Dongqin; Liu, Guifu; Liang, Yan; Huang, Linzhou; Meng, Xiangbing; Chu, Jinfang; Sun, Xiaohong; Dong, Guojun; Yuan, Yundong; Qian, Qian; Li, Jiayang; Wang, Yonghong
2014-01-01
Tiller angle, a key agronomic trait for achieving ideal plant architecture and increasing grain yield, is regulated mainly by shoot gravitropism. Strigolactones (SLs) are a group of newly identified plant hormones that are essential for shoot branching/rice tillering and have further biological functions as yet undetermined. Through screening for suppressors of lazy1 (sols), a classic rice mutant exhibiting large tiller angle and defective shoot gravitropism, we identified multiple SOLS that are involved in the SL biosynthetic or signaling pathway. We show that SL biosynthetic or signaling mutants can rescue the spreading phenotype of lazy1 (la1) and that SLs can inhibit auxin biosynthesis and attenuate rice shoot gravitropism, mainly by decreasing the local indoleacetic acid content. Although both SLs and LA1 are negative regulators of polar auxin transport, SLs do not alter the lateral auxin transport of shoot base, unlike LA1, which is a positive regulator of lateral auxin transport in rice. Genetic evidence demonstrates that SLs and LA1 participate in regulating shoot gravitropism and tiller angle in distinct genetic pathways. In addition, the SL-mediated shoot gravitropism is conserved in Arabidopsis. Our results disclose a new role of SLs and shed light on a previously unidentified mechanism underlying shoot gravitropism. Our study indicates that SLs could be considered as an important tool to achieve ideal plant architecture in the future. PMID:25028496
Sang, Dajun; Chen, Dongqin; Liu, Guifu; Liang, Yan; Huang, Linzhou; Meng, Xiangbing; Chu, Jinfang; Sun, Xiaohong; Dong, Guojun; Yuan, Yundong; Qian, Qian; Li, Jiayang; Wang, Yonghong
2014-07-29
Tiller angle, a key agronomic trait for achieving ideal plant architecture and increasing grain yield, is regulated mainly by shoot gravitropism. Strigolactones (SLs) are a group of newly identified plant hormones that are essential for shoot branching/rice tillering and have further biological functions as yet undetermined. Through screening for suppressors of lazy1 (sols), a classic rice mutant exhibiting large tiller angle and defective shoot gravitropism, we identified multiple SOLS that are involved in the SL biosynthetic or signaling pathway. We show that SL biosynthetic or signaling mutants can rescue the spreading phenotype of lazy1 (la1) and that SLs can inhibit auxin biosynthesis and attenuate rice shoot gravitropism, mainly by decreasing the local indoleacetic acid content. Although both SLs and LA1 are negative regulators of polar auxin transport, SLs do not alter the lateral auxin transport of shoot base, unlike LA1, which is a positive regulator of lateral auxin transport in rice. Genetic evidence demonstrates that SLs and LA1 participate in regulating shoot gravitropism and tiller angle in distinct genetic pathways. In addition, the SL-mediated shoot gravitropism is conserved in Arabidopsis. Our results disclose a new role of SLs and shed light on a previously unidentified mechanism underlying shoot gravitropism. Our study indicates that SLs could be considered as an important tool to achieve ideal plant architecture in the future.
Zhang, Miaomiao; Bo, Wenhao; Xu, Fang; Li, Huan; Ye, Meixia; Jiang, Libo; Shi, Chaozhong; Fu, Yaru; Zhao, Guomiao; Huang, Yuejiao; Gosik, Kirk; Liang, Dan; Wu, Rongling
2017-06-01
The coordination of shoots and roots is critical for plants to adapt to changing environments by fine-tuning energy production in leaves and the availability of water and nutrients from roots. To understand the genetic architecture of how these two organs covary during developmental ontogeny, we conducted a mapping experiment using Euphrates poplar (Populus euphratica), a so-called hero tree able to grow in the desert. We geminated intraspecific F 1 seeds of Euphrates Poplar individually in a tube to obtain a total of 370 seedlings, whose shoot and taproot lengths were measured repeatedly during the early stage of growth. By fitting a growth equation, we estimated asymptotic growth, relative growth rate, the timing of inflection point and duration of linear growth for both shoot and taproot growth. Treating these heterochronic parameters as phenotypes, a univariate mapping model detected 19 heterochronic quantitative trait loci (hQTLs), of which 15 mediate the forms of shoot growth and four mediate taproot growth. A bivariate mapping model identified 11 pleiotropic hQTLs that determine the covariation of shoot and taproot growth. Most QTLs detected reside within the region of candidate genes with various functions, thus confirming their roles in the biochemical processes underlying plant growth. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.
Mittag, Florian; Büchel, Finja; Saad, Mohamad; Jahn, Andreas; Schulte, Claudia; Bochdanovits, Zoltan; Simón-Sánchez, Javier; Nalls, Mike A; Keller, Margaux; Hernandez, Dena G; Gibbs, J Raphael; Lesage, Suzanne; Brice, Alexis; Heutink, Peter; Martinez, Maria; Wood, Nicholas W; Hardy, John; Singleton, Andrew B; Zell, Andreas; Gasser, Thomas; Sharma, Manu
2012-12-01
The success of genome-wide association studies (GWAS) in deciphering the genetic architecture of complex diseases has fueled the expectations whether the individual risk can also be quantified based on the genetic architecture. So far, disease risk prediction based on top-validated single-nucleotide polymorphisms (SNPs) showed little predictive value. Here, we applied a support vector machine (SVM) to Parkinson disease (PD) and type 1 diabetes (T1D), to show that apart from magnitude of effect size of risk variants, heritability of the disease also plays an important role in disease risk prediction. Furthermore, we performed a simulation study to show the role of uncommon (frequency 1-5%) as well as rare variants (frequency <1%) in disease etiology of complex diseases. Using a cross-validation model, we were able to achieve predictions with an area under the receiver operating characteristic curve (AUC) of ~0.88 for T1D, highlighting the strong heritable component (∼90%). This is in contrast to PD, where we were unable to achieve a satisfactory prediction (AUC ~0.56; heritability ~38%). Our simulations showed that simultaneous inclusion of uncommon and rare variants in GWAS would eventually lead to feasible disease risk prediction for complex diseases such as PD. The used software is available at http://www.ra.cs.uni-tuebingen.de/software/MACLEAPS/. © 2012 Wiley Periodicals, Inc.
Nazarian, Alireza; Gezan, Salvador A
2016-03-01
The study of genetic architecture of complex traits has been dramatically influenced by implementing genome-wide analytical approaches during recent years. Of particular interest are genomic prediction strategies which make use of genomic information for predicting phenotypic responses instead of detecting trait-associated loci. In this work, we present the results of a simulation study to improve our understanding of the statistical properties of estimation of genetic variance components of complex traits, and of additive, dominance, and genetic effects through best linear unbiased prediction methodology. Simulated dense marker information was used to construct genomic additive and dominance matrices, and multiple alternative pedigree- and marker-based models were compared to determine if including a dominance term into the analysis may improve the genetic analysis of complex traits. Our results showed that a model containing a pedigree- or marker-based additive relationship matrix along with a pedigree-based dominance matrix provided the best partitioning of genetic variance into its components, especially when some degree of true dominance effects was expected to exist. Also, we noted that the use of a marker-based additive relationship matrix along with a pedigree-based dominance matrix had the best performance in terms of accuracy of correlations between true and estimated additive, dominance, and genetic effects. © The American Genetic Association 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
GENETICS OF WHITE MATTER DEVELOPMENT: A DTI STUDY OF 705 TWINS AND THEIR SIBLINGS AGED 12 TO 29
Chiang, Ming-Chang; McMahon, Katie L.; de Zubicaray, Greig I.; Martin, Nicholas G.; Hickie, Ian; Toga, Arthur W.; Wright, Margaret J.; Thompson, Paul M.
2011-01-01
White matter microstructure is under strong genetic control, yet it is largely unknown how genetic influences change from childhood into adulthood. In one of the largest brain mapping studies ever performed, we determined whether the genetic control over white matter architecture depends on age, sex, socioeconomic status (SES), and intelligence quotient (IQ). We assessed white matter integrity voxelwise using diffusion tensor imaging at high magnetic field (4-Tesla), in 705 twins and their siblings (age range 12–29; 290 M/415 F). White matter integrity was quantified using a widely accepted measure, fractional anisotropy (FA). We fitted gene-environment interaction models pointwise, to visualize brain regions where age, sex, SES and IQ modulate heritability of fiber integrity. We hypothesized that environmental factors would start to outweigh genetic factors during late childhood and adolescence. Genetic influences were greater in adolescence versus adulthood, and greater in males than in females. Socioeconomic status significantly interacted with genes that affect fiber integrity: heritability was higher in those with higher SES. In people with above-average IQ, genetic factors explained over 800% of the observed FA variability in the thalamus, genu, posterior internal capsule, and superior corona radiata. In those with below-average IQ, however, only around 40% FA variability in the same regions was attributable to genetic factors. Genes affect fiber integrity, but their effects vary with age, sex, SES and IQ. Gene-environment interactions are vital to consider in the search for specific genetic polymorphisms that affect brain integrity and connectivity. PMID:20950689
Why Do Membranes of Some Unhealthy Cells Adopt a Cubic Architecture?
Xiao, Qi; Wang, Zhichun; Williams, Dewight; ...
2016-12-05
Nonlamellar lipid arrangements, including cubosomes, appear in unhealthy cells, e.g., when they are subject to stress, starvation, or viral infection. The bioactivity of cubosomes—nanoscale particles exhibiting bicontinuous cubic structures—versus more common vesicles is an unexplored area due to lack of suitable model systems. Here, glycodendrimercubosomes (GDCs)—sugar-presenting cubosomes assembled from Janus glycodendrimers by simple injection into buffer—are proposed as mimics of biological cubic membranes. The bicontinuous cubic GDC architecture has been demonstrated by electron tomography. The stability of these GDCs in buffer enabled studies on lectin-dependent agglutination, revealing significant differences compared with the vesicular glycodendrimersome (GDS) counterpart. In particular, GDCs showedmore » an increased activity toward concanavalin A, as well as an increased sensitivity and selectivity toward two variants of banana lectins, a wild-type and a genetically modified variant, which is not exhibited by GDSs. These results suggest that cells may adapt under unhealthy conditions by undergoing a transformation from lamellar to cubic membranes as a method of defense.« less
Javierre, Biola M; Burren, Oliver S; Wilder, Steven P; Kreuzhuber, Roman; Hill, Steven M; Sewitz, Sven; Cairns, Jonathan; Wingett, Steven W; Várnai, Csilla; Thiecke, Michiel J; Burden, Frances; Farrow, Samantha; Cutler, Antony J; Rehnström, Karola; Downes, Kate; Grassi, Luigi; Kostadima, Myrto; Freire-Pritchett, Paula; Wang, Fan; Stunnenberg, Hendrik G; Todd, John A; Zerbino, Daniel R; Stegle, Oliver; Ouwehand, Willem H; Frontini, Mattia; Wallace, Chris; Spivakov, Mikhail; Fraser, Peter
2016-11-17
Long-range interactions between regulatory elements and gene promoters play key roles in transcriptional regulation. The vast majority of interactions are uncharted, constituting a major missing link in understanding genome control. Here, we use promoter capture Hi-C to identify interacting regions of 31,253 promoters in 17 human primary hematopoietic cell types. We show that promoter interactions are highly cell type specific and enriched for links between active promoters and epigenetically marked enhancers. Promoter interactomes reflect lineage relationships of the hematopoietic tree, consistent with dynamic remodeling of nuclear architecture during differentiation. Interacting regions are enriched in genetic variants linked with altered expression of genes they contact, highlighting their functional role. We exploit this rich resource to connect non-coding disease variants to putative target promoters, prioritizing thousands of disease-candidate genes and implicating disease pathways. Our results demonstrate the power of primary cell promoter interactomes to reveal insights into genomic regulatory mechanisms underlying common diseases. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
Why Do Membranes of Some Unhealthy Cells Adopt a Cubic Architecture?
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xiao, Qi; Wang, Zhichun; Williams, Dewight
Nonlamellar lipid arrangements, including cubosomes, appear in unhealthy cells, e.g., when they are subject to stress, starvation, or viral infection. The bioactivity of cubosomes—nanoscale particles exhibiting bicontinuous cubic structures—versus more common vesicles is an unexplored area due to lack of suitable model systems. Here, glycodendrimercubosomes (GDCs)—sugar-presenting cubosomes assembled from Janus glycodendrimers by simple injection into buffer—are proposed as mimics of biological cubic membranes. The bicontinuous cubic GDC architecture has been demonstrated by electron tomography. The stability of these GDCs in buffer enabled studies on lectin-dependent agglutination, revealing significant differences compared with the vesicular glycodendrimersome (GDS) counterpart. In particular, GDCs showedmore » an increased activity toward concanavalin A, as well as an increased sensitivity and selectivity toward two variants of banana lectins, a wild-type and a genetically modified variant, which is not exhibited by GDSs. These results suggest that cells may adapt under unhealthy conditions by undergoing a transformation from lamellar to cubic membranes as a method of defense.« less
Warren, Andrew; Cheetham, R. Keira; Northen, Helen; O’Donovan, Maria; Malhotra, Shalini; di Pietro, Massimiliano; Ivakhno, Sergii; He, Miao; Weaver, Jamie M.J.; Lynch, Andy G.; Kingsbury, Zoya; Ross, Mark; Humphray, Sean; Bentley, David; Fitzgerald, Rebecca C.
2015-01-01
The molecular genetic relationship between esophageal adenocarcinoma (EAC) and its precursor lesion, Barrett’s esophagus, is poorly understood. Using whole-genome sequencing on 23 paired Barrett’s esophagus and EAC samples, together with one in-depth Barrett’s esophagus case-study sampled over time and space, we have provided new insights on the following aspects: i) Barrett’s esophagus is polyclonal and highly mutated even in the absence of dysplasia; ii) when cancer develops, copy number increases and heterogeneity persists such that the spectrum of mutations often shows surprisingly little overlap between EAC and adjacent Barrett’s esophagus; and iii) despite differences in specific coding mutations the mutational context suggests a common causative insult underlying these two conditions. From a clinical perspective, the histopathological assessment of dysplasia appears to be a poor reflection of the molecular disarray within the Barrett’s epithelium and a molecular Cytosponge™ technique overcomes sampling bias and has capacity to reflect the entire clonal architecture. PMID:26192915
A cellular, molecular, and pharmacological basis for appendage regeneration in mice.
Leung, Thomas H; Snyder, Emily R; Liu, Yinghua; Wang, Jing; Kim, Seung K
2015-10-15
Regenerative medicine aims to restore normal tissue architecture and function. However, the basis of tissue regeneration in mammalian solid organs remains undefined. Remarkably, mice lacking p21 fully regenerate injured ears without discernable scarring. Here we show that, in wild-type mice following tissue injury, stromal-derived factor-1 (Sdf1) is up-regulated in the wound epidermis and recruits Cxcr4-expressing leukocytes to the injury site. In p21-deficient mice, Sdf1 up-regulation and the subsequent recruitment of Cxcr4-expressing leukocytes are significantly diminished, thereby permitting scarless appendage regeneration. Lineage tracing demonstrates that this regeneration derives from fate-restricted progenitor cells. Pharmacological or genetic disruption of Sdf1-Cxcr4 signaling enhances tissue repair, including full reconstitution of tissue architecture and all cell types. Our findings identify signaling and cellular mechanisms underlying appendage regeneration in mice and suggest new therapeutic approaches for regenerative medicine. © 2015 Leung et al.; Published by Cold Spring Harbor Laboratory Press.
Clonal architecture of secondary acute myeloid leukemia defined by single-cell sequencing.
Hughes, Andrew E O; Magrini, Vincent; Demeter, Ryan; Miller, Christopher A; Fulton, Robert; Fulton, Lucinda L; Eades, William C; Elliott, Kevin; Heath, Sharon; Westervelt, Peter; Ding, Li; Conrad, Donald F; White, Brian S; Shao, Jin; Link, Daniel C; DiPersio, John F; Mardis, Elaine R; Wilson, Richard K; Ley, Timothy J; Walter, Matthew J; Graubert, Timothy A
2014-07-01
Next-generation sequencing has been used to infer the clonality of heterogeneous tumor samples. These analyses yield specific predictions-the population frequency of individual clones, their genetic composition, and their evolutionary relationships-which we set out to test by sequencing individual cells from three subjects diagnosed with secondary acute myeloid leukemia, each of whom had been previously characterized by whole genome sequencing of unfractionated tumor samples. Single-cell mutation profiling strongly supported the clonal architecture implied by the analysis of bulk material. In addition, it resolved the clonal assignment of single nucleotide variants that had been initially ambiguous and identified areas of previously unappreciated complexity. Accordingly, we find that many of the key assumptions underlying the analysis of tumor clonality by deep sequencing of unfractionated material are valid. Furthermore, we illustrate a single-cell sequencing strategy for interrogating the clonal relationships among known variants that is cost-effective, scalable, and adaptable to the analysis of both hematopoietic and solid tumors, or any heterogeneous population of cells.
Hall, Molly A; Verma, Anurag; Brown-Gentry, Kristin D; Goodloe, Robert; Boston, Jonathan; Wilson, Sarah; McClellan, Bob; Sutcliffe, Cara; Dilks, Holly H; Gillani, Nila B; Jin, Hailing; Mayo, Ping; Allen, Melissa; Schnetz-Boutaud, Nathalie; Crawford, Dana C; Ritchie, Marylyn D; Pendergrass, Sarah A
2014-12-01
We performed a Phenome-wide association study (PheWAS) utilizing diverse genotypic and phenotypic data existing across multiple populations in the National Health and Nutrition Examination Surveys (NHANES), conducted by the Centers for Disease Control and Prevention (CDC), and accessed by the Epidemiological Architecture for Genes Linked to Environment (EAGLE) study. We calculated comprehensive tests of association in Genetic NHANES using 80 SNPs and 1,008 phenotypes (grouped into 184 phenotype classes), stratified by race-ethnicity. Genetic NHANES includes three surveys (NHANES III, 1999-2000, and 2001-2002) and three race-ethnicities: non-Hispanic whites (n = 6,634), non-Hispanic blacks (n = 3,458), and Mexican Americans (n = 3,950). We identified 69 PheWAS associations replicating across surveys for the same SNP, phenotype-class, direction of effect, and race-ethnicity at p<0.01, allele frequency >0.01, and sample size >200. Of these 69 PheWAS associations, 39 replicated previously reported SNP-phenotype associations, 9 were related to previously reported associations, and 21 were novel associations. Fourteen results had the same direction of effect across more than one race-ethnicity: one result was novel, 11 replicated previously reported associations, and two were related to previously reported results. Thirteen SNPs showed evidence of pleiotropy. We further explored results with gene-based biological networks, contrasting the direction of effect for pleiotropic associations across phenotypes. One PheWAS result was ABCG2 missense SNP rs2231142, associated with uric acid levels in both non-Hispanic whites and Mexican Americans, protoporphyrin levels in non-Hispanic whites and Mexican Americans, and blood pressure levels in Mexican Americans. Another example was SNP rs1800588 near LIPC, significantly associated with the novel phenotypes of folate levels (Mexican Americans), vitamin E levels (non-Hispanic whites) and triglyceride levels (non-Hispanic whites), and replication for cholesterol levels. The results of this PheWAS show the utility of this approach for exposing more of the complex genetic architecture underlying multiple traits, through generating novel hypotheses for future research.
Modeling and Optimization of Multiple Unmanned Aerial Vehicles System Architecture Alternatives
Wang, Weiping; He, Lei
2014-01-01
Unmanned aerial vehicle (UAV) systems have already been used in civilian activities, although very limitedly. Confronted different types of tasks, multi UAVs usually need to be coordinated. This can be extracted as a multi UAVs system architecture problem. Based on the general system architecture problem, a specific description of the multi UAVs system architecture problem is presented. Then the corresponding optimization problem and an efficient genetic algorithm with a refined crossover operator (GA-RX) is proposed to accomplish the architecting process iteratively in the rest of this paper. The availability and effectiveness of overall method is validated using 2 simulations based on 2 different scenarios. PMID:25140328
Why and How We Age, and Is That Process Modifiable?
NASA Astrophysics Data System (ADS)
Arking, R.
Aging is an almost-universal biological process that is better understood in terms of an evolutionary explanation than in terms of a medical or adaptationist explanation. The major advances in human longevity which took place in developed countries during the past century arose from decreases in external (e.g., environmental) sources of mortality, and not from any effect on the aging process. Laboratory studies show that the aging process is under genetic control, can be manipulated, and can be expressed in three different phenotypes. The adult lifespan consists of the health span (ages 20-55 yrs) and the senescent span (ages 55+), with a relatively short but variable transition phase between the two. The most socially desirable phenotype would be that where the transition phase is delayed and the health span extended with little effect on the senescent span. The genetic, nutritional, cell-signaling and pharmecutical interventions inducing this phenotype are discussed. The genetic architecture of senescence is discussed and its stochastic nature made clear. The social and ethical consequences of pharmecutical intervention into the aging process are briefly discussed.
Loss of delta catenin function in severe autism
Turner, Tychele N.; Sharma, Kamal; Oh, Edwin C.; Liu, Yangfan P.; Collins, Ryan L.; Sosa, Maria X.; Auer, Dallas R.; Brand, Harrison; Sanders, Stephan J.; Moreno-De-Luca, Daniel; Pihur, Vasyl; Plona, Teri; Pike, Kristen; Soppet, Daniel R.; Smith, Michael W.; Cheung, Sau Wai; Martin, Christa Lese; State, Matthew W.; Talkowski, Michael E.; Cook, Edwin; Huganir, Richard; Katsanis, Nicholas; Chakravarti, Aravinda
2015-01-01
SUMMARY Autism is a multifactorial neurodevelopmental disorder affecting more males than females; consequently, under a multifactorial genetic hypothesis, females are affected only when they cross a higher biological threshold. We hypothesize that deleterious variants at conserved residues are enriched in severely affected patients arising from FEMFs (female-enriched multiplex families) with severe disease, enhancing the detection of key autism genes in modest numbers of cases. We show the utility of this strategy by identifying missense and dosage sequence variants in the gene encoding the adhesive junction-associated delta catenin protein (CTNND2) in FEMFs and demonstrating their loss-of-function effect by functional analyses in zebrafish embryos and cultured hippocampal neurons from wildtype and Ctnnd2 null mouse embryos. Finally, through gene expression and network analyses, we highlight a critical role for CTNND2 in neuronal development and an intimate connection to chromatin biology. Our data contribute to the understanding of the genetic architecture of autism and suggest that genetic analyses of phenotypic extremes, such as FEMFs, are of innate value in multifactorial disorders. PMID:25807484
Gusev, Alexander; Shi, Huwenbo; Kichaev, Gleb; Pomerantz, Mark; Li, Fugen; Long, Henry W; Ingles, Sue A; Kittles, Rick A; Strom, Sara S; Rybicki, Benjamin A; Nemesure, Barbara; Isaacs, William B; Zheng, Wei; Pettaway, Curtis A; Yeboah, Edward D; Tettey, Yao; Biritwum, Richard B; Adjei, Andrew A; Tay, Evelyn; Truelove, Ann; Niwa, Shelley; Chokkalingam, Anand P; John, Esther M; Murphy, Adam B; Signorello, Lisa B; Carpten, John; Leske, M Cristina; Wu, Suh-Yuh; Hennis, Anslem J M; Neslund-Dudas, Christine; Hsing, Ann W; Chu, Lisa; Goodman, Phyllis J; Klein, Eric A; Witte, John S; Casey, Graham; Kaggwa, Sam; Cook, Michael B; Stram, Daniel O; Blot, William J; Eeles, Rosalind A; Easton, Douglas; Kote-Jarai, Zsofia; Al Olama, Ali Amin; Benlloch, Sara; Muir, Kenneth; Giles, Graham G; Southey, Melissa C; Fitzgerald, Liesel M; Gronberg, Henrik; Wiklund, Fredrik; Aly, Markus; Henderson, Brian E; Schleutker, Johanna; Wahlfors, Tiina; Tammela, Teuvo L J; Nordestgaard, Børge G; Key, Tim J; Travis, Ruth C; Neal, David E; Donovan, Jenny L; Hamdy, Freddie C; Pharoah, Paul; Pashayan, Nora; Khaw, Kay-Tee; Stanford, Janet L; Thibodeau, Stephen N; McDonnell, Shannon K; Schaid, Daniel J; Maier, Christiane; Vogel, Walther; Luedeke, Manuel; Herkommer, Kathleen; Kibel, Adam S; Cybulski, Cezary; Wokolorczyk, Dominika; Kluzniak, Wojciech; Cannon-Albright, Lisa; Teerlink, Craig; Brenner, Hermann; Dieffenbach, Aida K; Arndt, Volker; Park, Jong Y; Sellers, Thomas A; Lin, Hui-Yi; Slavov, Chavdar; Kaneva, Radka; Mitev, Vanio; Batra, Jyotsna; Spurdle, Amanda; Clements, Judith A; Teixeira, Manuel R; Pandha, Hardev; Michael, Agnieszka; Paulo, Paula; Maia, Sofia; Kierzek, Andrzej; Conti, David V; Albanes, Demetrius; Berg, Christine; Berndt, Sonja I; Campa, Daniele; Crawford, E David; Diver, W Ryan; Gapstur, Susan M; Gaziano, J Michael; Giovannucci, Edward; Hoover, Robert; Hunter, David J; Johansson, Mattias; Kraft, Peter; Le Marchand, Loic; Lindström, Sara; Navarro, Carmen; Overvad, Kim; Riboli, Elio; Siddiq, Afshan; Stevens, Victoria L; Trichopoulos, Dimitrios; Vineis, Paolo; Yeager, Meredith; Trynka, Gosia; Raychaudhuri, Soumya; Schumacher, Frederick R; Price, Alkes L; Freedman, Matthew L; Haiman, Christopher A; Pasaniuc, Bogdan
2016-04-07
Although genome-wide association studies have identified over 100 risk loci that explain ∼33% of familial risk for prostate cancer (PrCa), their functional effects on risk remain largely unknown. Here we use genotype data from 59,089 men of European and African American ancestries combined with cell-type-specific epigenetic data to build a genomic atlas of single-nucleotide polymorphism (SNP) heritability in PrCa. We find significant differences in heritability between variants in prostate-relevant epigenetic marks defined in normal versus tumour tissue as well as between tissue and cell lines. The majority of SNP heritability lies in regions marked by H3k27 acetylation in prostate adenoc7arcinoma cell line (LNCaP) or by DNaseI hypersensitive sites in cancer cell lines. We find a high degree of similarity between European and African American ancestries suggesting a similar genetic architecture from common variation underlying PrCa risk. Our findings showcase the power of integrating functional annotation with genetic data to understand the genetic basis of PrCa.
The genetic architecture of NAFLD among inbred strains of mice
Hui, Simon T; Parks, Brian W; Org, Elin; Norheim, Frode; Che, Nam; Pan, Calvin; Castellani, Lawrence W; Charugundla, Sarada; Dirks, Darwin L; Psychogios, Nikolaos; Neuhaus, Isaac; Gerszten, Robert E; Kirchgessner, Todd; Gargalovic, Peter S; Lusis, Aldons J
2015-01-01
To identify genetic and environmental factors contributing to the pathogenesis of non-alcoholic fatty liver disease, we examined liver steatosis and related clinical and molecular traits in more than 100 unique inbred mouse strains, which were fed a diet rich in fat and carbohydrates. A >30-fold variation in hepatic TG accumulation was observed among the strains. Genome-wide association studies revealed three loci associated with hepatic TG accumulation. Utilizing transcriptomic data from the liver and adipose tissue, we identified several high-confidence candidate genes for hepatic steatosis, including Gde1, a glycerophosphodiester phosphodiesterase not previously implicated in triglyceride metabolism. We confirmed the role of Gde1 by in vivo hepatic over-expression and shRNA knockdown studies. We hypothesize that Gde1 expression increases TG production by contributing to the production of glycerol-3-phosphate. Our multi-level data, including transcript levels, metabolite levels, and gut microbiota composition, provide a framework for understanding genetic and environmental interactions underlying hepatic steatosis. DOI: http://dx.doi.org/10.7554/eLife.05607.001 PMID:26067236
Shaheen, Ranad; Faqeih, Eissa; Alshammari, Muneera J; Swaid, Abdulrahman; Al-Gazali, Lihadh; Mardawi, Elham; Ansari, Shinu; Sogaty, Sameera; Seidahmed, Mohammed Z; AlMotairi, Muhammed I; Farra, Chantal; Kurdi, Wesam; Al-Rasheed, Shatha; Alkuraya, Fowzan S
2013-01-01
Meckel–Gruber syndrome (MKS, OMIM #249000) is a multiple congenital malformation syndrome that represents the severe end of the ciliopathy phenotypic spectrum. Despite the relatively common occurrence of this syndrome among Arabs, little is known about its genetic architecture in this population. This is a series of 18 Arab families with MKS, who were evaluated clinically and studied using autozygome-guided mutation analysis and exome sequencing. We show that autozygome-guided candidate gene analysis identified the underlying mutation in the majority (n=12, 71%). Exome sequencing revealed a likely pathogenic mutation in three novel candidate MKS disease genes. These include C5orf42, Ellis–van-Creveld disease gene EVC2 and SEC8 (also known as EXOC4), which encodes an exocyst protein with an established role in ciliogenesis. This is the largest and most comprehensive genomic study on MKS in Arabs and the results, in addition to revealing genetic and allelic heterogeneity, suggest that previously reported disease genes and the novel candidates uncovered by this study account for the overwhelming majority of MKS patients in our population. PMID:23169490
Marangi, Giuseppe; Traynor, Bryan J.
2018-01-01
The genetic architecture of amyotrophic lateral sclerosis (ALS) is being increasingly understood. In this far-reaching review, we examine what is currently known about ALS genetics and how these genes were initially identified. We also discuss the various types of mutations that might underlie this fatal neurodegenerative condition and outline some of the strategies that might be useful in untangling them. These include expansions of short repeat sequences, common and low-frequency genetic variations, de novo mutations, epigenetic changes, somatic mutations, epistasis, oligogenic and polygenic hypotheses. PMID:25316630
Genetic architecture of kernel composition in global sorghum germplasm
USDA-ARS?s Scientific Manuscript database
Sorghum [Sorghum bicolor (L.) Moench] is an important cereal crop for dryland areas in the United States and for small-holder farmers in Africa. Natural variation of sorghum grain composition (protein, fat, and starch) between accessions can be used for crop improvement, but the genetic controls are...
Phytoplasmal infection derails genetically preprogrammed meristem fate and alters plant architecture
USDA-ARS?s Scientific Manuscript database
In the life cycle of higher plants, it is the fate of meristem cells that determines the pattern of growth and development, and therefore plant morphotype and fertility. Floral transition, the turning point from vegetative growth to reproductive development, is achieved via genetically-programmed s...
Cui, Min; Jia, Bo; Liu, Huanhuan; Kan, Xin; Zhang, Yu; Zhou, Ronghua; Li, Zhipeng; Yang, Liang; Deng, Dexiang; Yin, Zhitong
2017-01-01
The leaf number above the primary ear (LA) is a major contributing factor to plant architecture in maize. The yield of leafy maize, which has extra LA compared to normal maize, is higher than normal maize in some regions. One major concern is that increasing LA may be accompanied by increased plant height and/or flowering time. Using an F 2:3 population comprising 192 families derived from a leafy maize line and a normal maize line, an association population comprising 437 inbred maize lines, and a pair of near-isogenic maize lines, we mapped the quantitative trait loci (QTL) associated with LA and assessed its genetic relationship with flowering time and plant height. Ten QTL with an additive and dominant effect, 18 pairs of interacting QTL in the F 2:3 population and seventeen significant SNPs in the association population were detected for LA. Two major QTL, qLA3-4 and qLA7-1 , were repeatedly detected and explained a large proportion of the phenotypic variation. The qLA3-4 was centered on lfy1 , which is a dominant gene underlying extra leaves above the ear in leafy maize. Four LA QTL were found to overlap with flowering time and/or plant height, which suggested that these QTL might have a pleiotropic effect. The pleiotropy of the lfy1 locus on LA, flowering time and plant height were validated by near-isogenic line analysis. These results enhance our understanding of the genetic architecture affecting maize LA and the development of maize hybrids with increased LA.
Kos, M Z; Yan, J; Dick, D M; Agrawal, A; Bucholz, K K; Rice, J P; Johnson, E O; Schuckit, M; Kuperman, S; Kramer, J; Goate, A M; Tischfield, J A; Foroud, T; Nurnberger, J; Hesselbrock, V; Porjesz, B; Bierut, L J; Edenberg, H J; Almasy, L
2013-07-01
Alcohol dependence (AD) is a heritable substance addiction with adverse physical and psychological consequences, representing a major health and economic burden on societies worldwide. Genes thus far implicated via linkage, candidate gene and genome-wide association studies (GWAS) account for only a small fraction of its overall risk, with effects varying across ethnic groups. Here we investigate the genetic architecture of alcoholism and report on the extent to which common, genome-wide SNPs collectively account for risk of AD in two US populations, African-Americans (AAs) and European-Americans (EAs). Analyzing GWAS data for two independent case-control sample sets, we compute polymarker scores that are significantly associated with alcoholism (P = 1.64 × 10(-3) and 2.08 × 10(-4) for EAs and AAs, respectively), reflecting the small individual effects of thousands of variants derived from patterns of allelic architecture that are population specific. Simulations show that disease models based on rare and uncommon causal variants (MAF < 0.05) best fit the observed distribution of polymarker signals. When scoring bins were annotated for gene location and examined for constituent biological networks, gene enrichment is observed for several cellular processes and functions in both EA and AA populations, transcending their underlying allelic differences. Our results reveal key insights into the complex etiology of AD, raising the possibility of an important role for rare and uncommon variants, and identify polygenic mechanisms that encompass a spectrum of disease liability, with some, such as chloride transporters and glycine metabolism genes, displaying subtle, modifying effects that are likely to escape detection in most GWAS designs. © 2013 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.
The Genetic Basis of Composite Spike Form in Barley and ‘Miracle-Wheat’
Poursarebani, Naser; Seidensticker, Tina; Koppolu, Ravi; Trautewig, Corinna; Gawroński, Piotr; Bini, Federica; Govind, Geetha; Rutten, Twan; Sakuma, Shun; Tagiri, Akemi; Wolde, Gizaw M.; Youssef, Helmy M.; Battal, Abdulhamit; Ciannamea, Stefano; Fusca, Tiziana; Nussbaumer, Thomas; Pozzi, Carlo; Börner, Andreas; Lundqvist, Udda; Komatsuda, Takao; Salvi, Silvio; Tuberosa, Roberto; Uauy, Cristobal; Sreenivasulu, Nese; Rossini, Laura; Schnurbusch, Thorsten
2015-01-01
Inflorescences of the tribe Triticeae, which includes wheat (Triticum sp. L.) and barley (Hordeum vulgare L.) are characterized by sessile spikelets directly borne on the main axis, thus forming a branchless spike. ‘Compositum-Barley’ and tetraploid ‘Miracle-Wheat’ (T. turgidum convar. compositum (L.f.) Filat.) display noncanonical spike-branching in which spikelets are replaced by lateral branch-like structures resembling small-sized secondary spikes. As a result of this branch formation ‘Miracle-Wheat’ produces significantly more grains per spike, leading to higher spike yield. In this study, we first isolated the gene underlying spike-branching in ‘Compositum-Barley,’ i.e., compositum 2 (com2). Moreover, we found that COM2 is orthologous to the branched headt (bht) locus regulating spike branching in tetraploid ‘Miracle-Wheat.’ Both genes possess orthologs with similar functions in maize BRANCHED SILKLESS 1 (BD1) and rice FRIZZY PANICLE/BRANCHED FLORETLESS 1 (FZP/BFL1) encoding AP2/ERF transcription factors. Sequence analysis of the bht locus in a collection of mutant and wild-type tetraploid wheat accessions revealed that a single amino acid substitution in the DNA-binding domain gave rise to the domestication of ‘Miracle-Wheat.’ mRNA in situ hybridization, microarray experiments, and independent qRT-PCR validation analyses revealed that the branch repression pathway in barley is governed through the spike architecture gene Six-rowed spike 4 regulating COM2 expression, while HvIDS1 (barley ortholog of maize INDETERMINATE SPIKELET 1) is a putative downstream target of COM2. These findings presented here provide new insights into the genetic basis of spike architecture in Triticeae, and have disclosed new targets for genetic manipulations aiming at boosting wheat’s yield potential. PMID:26156223
Vaughn, Justin N.; Nelson, Randall L.; Song, Qijian; Cregan, Perry B.; Li, Zenglu
2014-01-01
Soybean oil and meal are major contributors to world-wide food production. Consequently, the genetic basis for soybean seed composition has been intensely studied using family-based mapping. Population-based mapping approaches, in the form of genome-wide association (GWA) scans, have been able to resolve loci controlling moderately complex quantitative traits (QTL) in numerous crop species. Yet, it is still unclear how soybean’s unique population history will affect GWA scans. Using one of the populations in this study, we simulated phenotypes resulting from a range of genetic architectures. We found that with a heritability of 0.5, ∼100% and ∼33% of the 4 and 20 simulated QTL can be recovered, respectively, with a false-positive rate of less than ∼6×10−5 per marker tested. Additionally, we demonstrated that combining information from multi-locus mixed models and compressed linear-mixed models improves QTL identification and interpretation. We applied these insights to exploring seed composition in soybean, refining the linkage group I (chromosome 20) protein QTL and identifying additional oil QTL that may allow some decoupling of highly correlated oil and protein phenotypes. Because the value of protein meal is closely related to its essential amino acid profile, we attempted to identify QTL underlying methionine, threonine, cysteine, and lysine content. Multiple QTL were found that have not been observed in family-based mapping studies, and each trait exhibited associations across multiple populations. Chromosomes 1 and 8 contain strong candidate alleles for essential amino acid increases. Overall, we present these and additional data that will be useful in determining breeding strategies for the continued improvement of soybean’s nutrient portfolio. PMID:25246241
Assessing the complex architecture of polygenic traits in diverged yeast populations.
Cubillos, Francisco A; Billi, Eleonora; Zörgö, Enikö; Parts, Leopold; Fargier, Patrick; Omholt, Stig; Blomberg, Anders; Warringer, Jonas; Louis, Edward J; Liti, Gianni
2011-04-01
Phenotypic variation arising from populations adapting to different niches has a complex underlying genetic architecture. A major challenge in modern biology is to identify the causative variants driving phenotypic variation. Recently, the baker's yeast, Saccharomyces cerevisiae has emerged as a powerful model for dissecting complex traits. However, past studies using a laboratory strain were unable to reveal the complete architecture of polygenic traits. Here, we present a linkage study using 576 recombinant strains obtained from crosses of isolates representative of the major lineages. The meiotic recombinational landscape appears largely conserved between populations; however, strain-specific hotspots were also detected. Quantitative measurements of growth in 23 distinct ecologically relevant environments show that our recombinant population recapitulates most of the standing phenotypic variation described in the species. Linkage analysis detected an average of 6.3 distinct QTLs for each condition tested in all crosses, explaining on average 39% of the phenotypic variation. The QTLs detected are not constrained to a small number of loci, and the majority are specific to a single cross-combination and to a specific environment. Moreover, crosses between strains of similar phenotypes generate greater variation in the offspring, suggesting the presence of many antagonistic alleles and epistatic interactions. We found that subtelomeric regions play a key role in defining individual quantitative variation, emphasizing the importance of the adaptive nature of these regions in natural populations. This set of recombinant strains is a powerful tool for investigating the complex architecture of polygenic traits. © 2011 Blackwell Publishing Ltd.
Kumar, Ajay; Mantovani, E E; Seetan, R; Soltani, A; Echeverry-Solarte, M; Jain, S; Simsek, S; Doehlert, D; Alamri, M S; Elias, E M; Kianian, S F; Mergoum, M
2016-03-01
Wheat kernel shape and size has been under selection since early domestication. Kernel morphology is a major consideration in wheat breeding, as it impacts grain yield and quality. A population of 160 recombinant inbred lines (RIL), developed using an elite (ND 705) and a nonadapted genotype (PI 414566), was extensively phenotyped in replicated field trials and genotyped using Infinium iSelect 90K assay to gain insight into the genetic architecture of kernel shape and size. A high density genetic map consisting of 10,172 single nucleotide polymorphism (SNP) markers, with an average marker density of 0.39 cM/marker, identified a total of 29 genomic regions associated with six grain shape and size traits; ∼80% of these regions were associated with multiple traits. The analyses showed that kernel length (KL) and width (KW) are genetically independent, while a large number (∼59%) of the quantitative trait loci (QTL) for kernel shape traits were in common with genomic regions associated with kernel size traits. The most significant QTL was identified on chromosome 4B, and could be an ortholog of major rice grain size and shape gene or . Major and stable loci also were identified on the homeologous regions of Group 5 chromosomes, and in the regions of (6A) and (7A) genes. Both parental genotypes contributed equivalent positive QTL alleles, suggesting that the nonadapted germplasm has a great potential for enhancing the gene pool for grain shape and size. This study provides new knowledge on the genetic dissection of kernel morphology, with a much higher resolution, which may aid further improvement in wheat yield and quality using genomic tools. Copyright © 2016 Crop Science Society of America.
Kernel Machine SNP-set Testing under Multiple Candidate Kernels
Wu, Michael C.; Maity, Arnab; Lee, Seunggeun; Simmons, Elizabeth M.; Harmon, Quaker E.; Lin, Xinyi; Engel, Stephanie M.; Molldrem, Jeffrey J.; Armistead, Paul M.
2013-01-01
Joint testing for the cumulative effect of multiple single nucleotide polymorphisms grouped on the basis of prior biological knowledge has become a popular and powerful strategy for the analysis of large scale genetic association studies. The kernel machine (KM) testing framework is a useful approach that has been proposed for testing associations between multiple genetic variants and many different types of complex traits by comparing pairwise similarity in phenotype between subjects to pairwise similarity in genotype, with similarity in genotype defined via a kernel function. An advantage of the KM framework is its flexibility: choosing different kernel functions allows for different assumptions concerning the underlying model and can allow for improved power. In practice, it is difficult to know which kernel to use a priori since this depends on the unknown underlying trait architecture and selecting the kernel which gives the lowest p-value can lead to inflated type I error. Therefore, we propose practical strategies for KM testing when multiple candidate kernels are present based on constructing composite kernels and based on efficient perturbation procedures. We demonstrate through simulations and real data applications that the procedures protect the type I error rate and can lead to substantially improved power over poor choices of kernels and only modest differences in power versus using the best candidate kernel. PMID:23471868
Evolutionary Local Search of Fuzzy Rules through a novel Neuro-Fuzzy encoding method.
Carrascal, A; Manrique, D; Ríos, J; Rossi, C
2003-01-01
This paper proposes a new approach for constructing fuzzy knowledge bases using evolutionary methods. We have designed a genetic algorithm that automatically builds neuro-fuzzy architectures based on a new indirect encoding method. The neuro-fuzzy architecture represents the fuzzy knowledge base that solves a given problem; the search for this architecture takes advantage of a local search procedure that improves the chromosomes at each generation. Experiments conducted both on artificially generated and real world problems confirm the effectiveness of the proposed approach.
Processor design optimization methodology for synthetic vision systems
NASA Astrophysics Data System (ADS)
Wren, Bill; Tarleton, Norman G.; Symosek, Peter F.
1997-06-01
Architecture optimization requires numerous inputs from hardware to software specifications. The task of varying these input parameters to obtain an optimal system architecture with regard to cost, specified performance and method of upgrade considerably increases the development cost due to the infinitude of events, most of which cannot even be defined by any simple enumeration or set of inequalities. We shall address the use of a PC-based tool using genetic algorithms to optimize the architecture for an avionics synthetic vision system, specifically passive millimeter wave system implementation.
Baumann, Kim; Venail, Julien; Berbel, Ana; Domenech, Maria Jose; Money, Tracy; Conti, Lucio; Hanzawa, Yoshie; Madueno, Francisco; Bradley, Desmond
2015-01-01
Models for the control of above-ground plant architectures show how meristems can be programmed to be either shoots or flowers. Molecular, genetic, transgenic, and mathematical studies have greatly refined these models, suggesting that the phase of the shoot reflects different genes contributing to its repression of flowering, its vegetativeness (‘veg’), before activators promote flower development. Key elements of how the repressor of flowering and shoot meristem gene TFL1 acts have now been tested, by changing its spatiotemporal pattern. It is shown that TFL1 can act outside of its normal expression domain in leaf primordia or floral meristems to repress flower identity. These data show how the timing and spatial pattern of TFL1 expression affect overall plant architecture. This reveals that the underlying pattern of TFL1 interactors is complex and that they may be spatially more widespread than TFL1 itself, which is confined to shoots. However, the data show that while TFL1 and floral genes can both act and compete in the same meristem, it appears that the main shoot meristem is more sensitive to TFL1 rather than floral genes. This spatial analysis therefore reveals how a difference in response helps maintain the ‘veg’ state of the shoot meristem. PMID:26019254
Genetic burden associated with varying degrees of disease severity in endometriosis
Sapkota, Yadav; Attia, John; Gordon, Scott D.; Henders, Anjali K.; Holliday, Elizabeth G.; Rahmioglu, Nilufer; MacGregor, Stuart; Martin, Nicholas G.; McEvoy, Mark; Morris, Andrew P.; Scott, Rodney J.; Zondervan, Krina T.; Montgomery, Grant W.; Nyholt, Dale R.
2015-01-01
Endometriosis is primarily characterized by the presence of tissue resembling endometrium outside the uterine cavity and is usually diagnosed by laparoscopy. The most commonly used classification of disease, the revised American Fertility Society (rAFS) system to grade endometriosis into different stages based on disease severity (I to IV), has been questioned as it does not correlate well with underlying symptoms, posing issues in diagnosis and choice of treatment. Using two independent European genome-wide association (GWA) datasets and top-level classification of the endometriosis cases based on rAFS [minimal or mild (Stage A) and moderate-to-severe (Stage B) disease], we previously showed that Stage B endometriosis has greater contribution of common genetic variation to its aetiology than Stage A disease. Herein, we extend our previous analysis to four endometriosis stages [minimal (Stage I), mild (Stage II), moderate (Stage III) and severe (Stage IV) disease] based on the rAFS classification system and compared the genetic burden across stages. Our results indicate that genetic burden increases from minimal to severe endometriosis. For the minimal disease, genetic factors may contribute to a lesser extent than other disease categories. Mild and moderate endometriosis appeared genetically similar, making it difficult to tease them apart. Consistent with our previous reports, moderate and severe endometriosis showed greater genetic burden than minimal or mild disease. Overall, our results provide new insights into the genetic architecture of endometriosis and further investigation in larger samples may help to understand better the aetiology of varying degrees of endometriosis, enabling improved diagnostic and treatment modalities. PMID:25882541
Genetic Architectures of Quantitative Variation in RNA Editing Pathways
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
Mitochondrial Recombination Reveals Mito-Mito Epistasis in Yeast.
Wolters, John F; Charron, Guillaume; Gaspary, Alec; Landry, Christian R; Fiumera, Anthony C; Fiumera, Heather L
2018-05-01
Genetic variation in mitochondrial DNA (mtDNA) provides adaptive potential although the underlying genetic architecture of fitness components within mtDNAs is not known. To dissect functional variation within mtDNAs, we first identified naturally occurring mtDNAs that conferred high or low fitness in Saccharomyces cerevisiae by comparing growth in strains containing identical nuclear genotypes but different mtDNAs. During respiratory growth under temperature and oxidative stress conditions, mitotype effects were largely independent of nuclear genotypes even in the presence of mito-nuclear interactions. Recombinant mtDNAs were generated to determine fitness components within high- and low-fitness mtDNAs. Based on phenotypic distributions of isogenic strains containing recombinant mtDNAs, we found that multiple loci contributed to mitotype fitness differences. These mitochondrial loci interacted in epistatic, nonadditive ways in certain environmental conditions. Mito-mito epistasis ( i.e. , nonadditive interactions between mitochondrial loci) influenced fitness in progeny from four different crosses, suggesting that mito-mito epistasis is a widespread phenomenon in yeast and other systems with recombining mtDNAs. Furthermore, we found that interruption of coadapted mito-mito interactions produced recombinant mtDNAs with lower fitness. Our results demonstrate that mito-mito epistasis results in functional variation through mitochondrial recombination in fungi, providing modes for adaptive evolution and the generation of mito-mito incompatibilities. Copyright © 2018 by the Genetics Society of America.
Boosting for detection of gene-environment interactions.
Pashova, H; LeBlanc, M; Kooperberg, C
2013-01-30
In genetic association studies, it is typically thought that genetic variants and environmental variables jointly will explain more of the inheritance of a phenotype than either of these two components separately. Traditional methods to identify gene-environment interactions typically consider only one measured environmental variable at a time. However, in practice, multiple environmental factors may each be imprecise surrogates for the underlying physiological process that actually interacts with the genetic factors. In this paper, we develop a variant of L(2) boosting that is specifically designed to identify combinations of environmental variables that jointly modify the effect of a gene on a phenotype. Because the effect modifiers might have a small signal compared with the main effects, working in a space that is orthogonal to the main predictors allows us to focus on the interaction space. In a simulation study that investigates some plausible underlying model assumptions, our method outperforms the least absolute shrinkage and selection and Akaike Information Criterion and Bayesian Information Criterion model selection procedures as having the lowest test error. In an example for the Women's Health Initiative-Population Architecture using Genomics and Epidemiology study, the dedicated boosting method was able to pick out two single-nucleotide polymorphisms for which effect modification appears present. The performance was evaluated on an independent test set, and the results are promising. Copyright © 2012 John Wiley & Sons, Ltd.
An evolutionary algorithm that constructs recurrent neural networks.
Angeline, P J; Saunders, G M; Pollack, J B
1994-01-01
Standard methods for simultaneously inducing the structure and weights of recurrent neural networks limit every task to an assumed class of architectures. Such a simplification is necessary since the interactions between network structure and function are not well understood. Evolutionary computations, which include genetic algorithms and evolutionary programming, are population-based search methods that have shown promise in many similarly complex tasks. This paper argues that genetic algorithms are inappropriate for network acquisition and describes an evolutionary program, called GNARL, that simultaneously acquires both the structure and weights for recurrent networks. GNARL's empirical acquisition method allows for the emergence of complex behaviors and topologies that are potentially excluded by the artificial architectural constraints imposed in standard network induction methods.
Ensemble Learning of QTL Models Improves Prediction of Complex Traits
Bian, Yang; Holland, James B.
2015-01-01
Quantitative trait locus (QTL) models can provide useful insights into trait genetic architecture because of their straightforward interpretability but are less useful for genetic prediction because of the difficulty in including the effects of numerous small effect loci without overfitting. Tight linkage between markers introduces near collinearity among marker genotypes, complicating the detection of QTL and estimation of QTL effects in linkage mapping, and this problem is exacerbated by very high density linkage maps. Here we developed a thinning and aggregating (TAGGING) method as a new ensemble learning approach to QTL mapping. TAGGING reduces collinearity problems by thinning dense linkage maps, maintains aspects of marker selection that characterize standard QTL mapping, and by ensembling, incorporates information from many more markers-trait associations than traditional QTL mapping. The objective of TAGGING was to improve prediction power compared with QTL mapping while also providing more specific insights into genetic architecture than genome-wide prediction models. TAGGING was compared with standard QTL mapping using cross validation of empirical data from the maize (Zea mays L.) nested association mapping population. TAGGING-assisted QTL mapping substantially improved prediction ability for both biparental and multifamily populations by reducing both the variance and bias in prediction. Furthermore, an ensemble model combining predictions from TAGGING-assisted QTL and infinitesimal models improved prediction abilities over the component models, indicating some complementarity between model assumptions and suggesting that some trait genetic architectures involve a mixture of a few major QTL and polygenic effects. PMID:26276383
Chabris, Christopher F; Lee, James J; Benjamin, Daniel J; Beauchamp, Jonathan P; Glaeser, Edward L; Borst, Gregoire; Pinker, Steven; Laibson, David I
2013-10-01
We explain why traits of interest to behavioral scientists may have a genetic architecture featuring hundreds or thousands of loci with tiny individual effects rather than a few with large effects and why such an architecture makes it difficult to find robust associations between traits and genes. We conducted a genome-wide association study at 2 sites, Harvard University and Union College, measuring more than 100 physical and behavioral traits with a sample size typical of candidate gene studies. We evaluated predictions that alleles with large effect sizes would be rare and most traits of interest to social science are likely characterized by a lack of strong directional selection. We also carried out a theoretical analysis of the genetic architecture of traits based on R.A. Fisher's geometric model of natural selection and empirical analyses of the effects of selection bias and phenotype measurement stability on the results of genetic association studies. Although we replicated several known genetic associations with physical traits, we found only 2 associations with behavioral traits that met the nominal genome-wide significance threshold, indicating that physical and behavioral traits are mainly affected by numerous genes with small effects. The challenge for social science genomics is the likelihood that genes are connected to behavioral variation by lengthy, nonlinear, interactive causal chains, and unraveling these chains requires allying with personal genomics to take advantage of the potential for large sample sizes as well as continuing with traditional epidemiological studies.
Mantilla Perez, Maria B; Zhao, Jing; Yin, Yanhai; Hu, Jieyun; Salas Fernandez, Maria G
2014-12-01
This first association analysis between plant architecture and BR candidate genes in sorghum suggests that natural allelic variation has significant and pleiotropic effects on plant architecture phenotypes. Sorghum bicolor (L) Moench is a self-pollinated species traditionally used as a staple crop for human consumption and as a forage crop for livestock feed. Recently, sorghum has received attention as a bioenergy crop due to its water use efficiency and biomass yield potential. Breeding for superior bioenergy-type lines requires knowledge of the genetic mechanisms controlling plant architecture. Brassinosteroids (BRs) are a group of hormones that determine plant growth, development, and architecture. Biochemical and genetic information on BRs are available from model species but the application of that knowledge to crop species has been very limited. A candidate gene association mapping approach and a diverse sorghum collection of 315 accessions were used to assess marker-trait associations between BR biosynthesis and signaling genes and six plant architecture traits. A total of 263 single nucleotide polymorphisms (SNPs) from 26 BR genes were tested, 73 SNPs were significantly associated with the phenotypes of interest and 18 of those were associated with more than one trait. An analysis of the phenotypic variation explained by each BR pathway revealed that the signaling pathway had a larger effect for most phenotypes (R (2) = 0.05-0.23). This study constitutes the first association analysis between plant architecture and BR genes in sorghum and the first LD mapping for leaf angle, stem circumference, panicle exsertion and panicle length. Markers on or close to BKI1 associated with all phenotypes and thus, they are the most important outcomes of this study and will be further validated for their future application in breeding programs.
Genetics and intelligence differences: five special findings.
Plomin, R; Deary, I J
2015-02-01
Intelligence is a core construct in differential psychology and behavioural genetics, and should be so in cognitive neuroscience. It is one of the best predictors of important life outcomes such as education, occupation, mental and physical health and illness, and mortality. Intelligence is one of the most heritable behavioural traits. Here, we highlight five genetic findings that are special to intelligence differences and that have important implications for its genetic architecture and for gene-hunting expeditions. (i) The heritability of intelligence increases from about 20% in infancy to perhaps 80% in later adulthood. (ii) Intelligence captures genetic effects on diverse cognitive and learning abilities, which correlate phenotypically about 0.30 on average but correlate genetically about 0.60 or higher. (iii) Assortative mating is greater for intelligence (spouse correlations ~0.40) than for other behavioural traits such as personality and psychopathology (~0.10) or physical traits such as height and weight (~0.20). Assortative mating pumps additive genetic variance into the population every generation, contributing to the high narrow heritability (additive genetic variance) of intelligence. (iv) Unlike psychiatric disorders, intelligence is normally distributed with a positive end of exceptional performance that is a model for 'positive genetics'. (v) Intelligence is associated with education and social class and broadens the causal perspectives on how these three inter-correlated variables contribute to social mobility, and health, illness and mortality differences. These five findings arose primarily from twin studies. They are being confirmed by the first new quantitative genetic technique in a century-Genome-wide Complex Trait Analysis (GCTA)-which estimates genetic influence using genome-wide genotypes in large samples of unrelated individuals. Comparing GCTA results to the results of twin studies reveals important insights into the genetic architecture of intelligence that are relevant to attempts to narrow the 'missing heritability' gap.
Genetics and intelligence differences: five special findings
Plomin, R; Deary, I J
2015-01-01
Intelligence is a core construct in differential psychology and behavioural genetics, and should be so in cognitive neuroscience. It is one of the best predictors of important life outcomes such as education, occupation, mental and physical health and illness, and mortality. Intelligence is one of the most heritable behavioural traits. Here, we highlight five genetic findings that are special to intelligence differences and that have important implications for its genetic architecture and for gene-hunting expeditions. (i) The heritability of intelligence increases from about 20% in infancy to perhaps 80% in later adulthood. (ii) Intelligence captures genetic effects on diverse cognitive and learning abilities, which correlate phenotypically about 0.30 on average but correlate genetically about 0.60 or higher. (iii) Assortative mating is greater for intelligence (spouse correlations ~0.40) than for other behavioural traits such as personality and psychopathology (~0.10) or physical traits such as height and weight (~0.20). Assortative mating pumps additive genetic variance into the population every generation, contributing to the high narrow heritability (additive genetic variance) of intelligence. (iv) Unlike psychiatric disorders, intelligence is normally distributed with a positive end of exceptional performance that is a model for ‘positive genetics'. (v) Intelligence is associated with education and social class and broadens the causal perspectives on how these three inter-correlated variables contribute to social mobility, and health, illness and mortality differences. These five findings arose primarily from twin studies. They are being confirmed by the first new quantitative genetic technique in a century—Genome-wide Complex Trait Analysis (GCTA)—which estimates genetic influence using genome-wide genotypes in large samples of unrelated individuals. Comparing GCTA results to the results of twin studies reveals important insights into the genetic architecture of intelligence that are relevant to attempts to narrow the ‘missing heritability' gap. PMID:25224258
Multivariate modelling of endophenotypes associated with the metabolic syndrome in Chinese twins.
Pang, Z; Zhang, D; Li, S; Duan, H; Hjelmborg, J; Kruse, T A; Kyvik, K O; Christensen, K; Tan, Q
2010-12-01
The common genetic and environmental effects on endophenotypes related to the metabolic syndrome have been investigated using bivariate and multivariate twin models. This paper extends the pairwise analysis approach by introducing independent and common pathway models to Chinese twin data. The aim was to explore the common genetic architecture in the development of these phenotypes in the Chinese population. Three multivariate models including the full saturated Cholesky decomposition model, the common factor independent pathway model and the common factor common pathway model were fitted to 695 pairs of Chinese twins representing six phenotypes including BMI, total cholesterol, total triacylglycerol, fasting glucose, HDL and LDL. Performances of the nested models were compared with that of the full Cholesky model. Cross-phenotype correlation coefficients gave clear indication of common genetic or environmental backgrounds in the phenotypes. Decomposition of phenotypic correlation by the Cholesky model revealed that the observed phenotypic correlation among lipid phenotypes had genetic and unique environmental backgrounds. Both pathway models suggest a common genetic architecture for lipid phenotypes, which is distinct from that of the non-lipid phenotypes. The declining performance with model restriction indicates biological heterogeneity in development among some of these phenotypes. Our multivariate analyses revealed common genetic and environmental backgrounds for the studied lipid phenotypes in Chinese twins. Model performance showed that physiologically distinct endophenotypes may follow different genetic regulations.
2015-11-01
Genetic association studies of transplantation outcomes have been hampered by small samples and highly complex multifactorial phenotypes, hindering investigations of the genetic architecture of a range of comorbidities which significantly impact graft and recipient life expectancy. We describe here the rationale and design of the International Genetics & Translational Research in Transplantation Network. The network comprises 22 studies to date, including 16494 transplant recipients and 11669 donors, of whom more than 5000 are of non-European ancestry, all of whom have existing genomewide genotype data sets. We describe the rich genetic and phenotypic information available in this consortium comprising heart, kidney, liver, and lung transplant cohorts. We demonstrate significant power in International Genetics & Translational Research in Transplantation Network to detect main effect association signals across regions such as the MHC region as well as genomewide for transplant outcomes that span all solid organs, such as graft survival, acute rejection, new onset of diabetes after transplantation, and for delayed graft function in kidney only. This consortium is designed and statistically powered to deliver pioneering insights into the genetic architecture of transplant-related outcomes across a range of different solid-organ transplant studies. The study design allows a spectrum of analyses to be performed including recipient-only analyses, donor-recipient HLA mismatches with focus on loss-of-function variants and nonsynonymous single nucleotide polymorphisms.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nadeem, A.; Keith, B.D.; Thompson, T.A.
Mapping of sedimentary surfaces in the Middle Mississippian Salem Limestone exposed on sawed quarry walls in south-central Indiana has revealed a hierarchy of depositional units representative of the extremely dynamic hydrographic regime of the upper shoreface zone. The depositional units on the scale of microform and mesoform are represented by the microfacies and the facies respectively. Based on their hierarchy, genetically related depositional units and associated bounding surfaces were grouped together to construct four architectural packages (APs) of the scale of mesoforms. AP-I is dominantly an echinoderm- and bryozoan-rich grainstone and consists of bedforms ranging from small ripples bounded bymore » first-order surfaces to two- and three- dimensional megaripples bounded by the second-order surfaces. It formed as part of a giant ramp (asymmetric wavefield) within the intrashoal channel setting. AP-II, also a skeletal grainstone, is a complex of giant sandwaves that moved into the area under the infulence of a storm and partly filled the basal channel form of AP-I. Large avalanche foresets with tangential toesets prevail. AP-III is a dark-gray spatially discontinuous skeletal grainstone to packstone that laterally grades into a skeletal packstone to wackestone. It locally developed overhangs, rips-ups, and hardground on its upper surface. AP-IV is a skeletal and oolitic grainstone formed of tabular two-dimensional megaripples (planar cross-beds) and three-dimensional oscillatory megaripples (trough cross-beds). These architectural packages based on the bedform architecture and micro-and mesoscale compositional changes can be used to characterize micro-, meso, and macroscale heterogeneities. Models of facies architecture from this and similar outcrop studies can be applied to the subsurface Salem reservoirs in the Illinois Basin using cores.« less
Genetic Architecture of Flooding Tolerance in the Dry Bean Middle-American Diversity Panel
Soltani, Ali; MafiMoghaddam, Samira; Walter, Katelynn; Restrepo-Montoya, Daniel; Mamidi, Sujan; Schroder, Stephan; Lee, Rian; McClean, Phillip E.; Osorno, Juan M.
2017-01-01
Flooding is a devastating abiotic stress that endangers crop production in the twenty-first century. Because of the severe susceptibility of common bean (Phaseolus vulgaris L.) to flooding, an understanding of the genetic architecture and physiological responses of this crop will set the stage for further improvement. However, challenging phenotyping methods hinder a large-scale genetic study of flooding tolerance in common bean and other economically important crops. A greenhouse phenotyping protocol was developed to evaluate the flooding conditions at early stages. The Middle-American diversity panel (n = 272) of common bean was developed to capture most of the diversity exits in North American germplasm. This panel was evaluated for seven traits under both flooded and non-flooded conditions at two early developmental stages. A subset of contrasting genotypes was further evaluated in the field to assess the relationship between greenhouse and field data under flooding condition. A genome-wide association study using ~150 K SNPs was performed to discover genomic regions associated with multiple physiological responses. The results indicate a significant strong correlation (r > 0.77) between greenhouse and field data, highlighting the reliability of greenhouse phenotyping method. Black and small red beans were the least affected by excess water at germination stage. At the seedling stage, pinto and great northern genotypes were the most tolerant. Root weight reduction due to flooding was greatest in pink and small red cultivars. Flooding reduced the chlorophyll content to the greatest extent in the navy bean cultivars compared with other market classes. Races of Durango/Jalisco and Mesoamerica were separated by both genotypic and phenotypic data indicating the potential effect of eco-geographical variations. Furthermore, several loci were identified that potentially represent the antagonistic pleiotropy. The GWAS analysis revealed peaks at Pv08/1.6 Mb and Pv02/41 Mb that are associated with root weight and germination rate, respectively. These regions are syntenic with two QTL reported in soybean (Glycine max L.) that contribute to flooding tolerance, suggesting a conserved evolutionary pathway involved in flooding tolerance for these related legumes. PMID:28729876
Genetic Architecture of Flooding Tolerance in the Dry Bean Middle-American Diversity Panel.
Soltani, Ali; MafiMoghaddam, Samira; Walter, Katelynn; Restrepo-Montoya, Daniel; Mamidi, Sujan; Schroder, Stephan; Lee, Rian; McClean, Phillip E; Osorno, Juan M
2017-01-01
Flooding is a devastating abiotic stress that endangers crop production in the twenty-first century. Because of the severe susceptibility of common bean ( Phaseolus vulgaris L.) to flooding, an understanding of the genetic architecture and physiological responses of this crop will set the stage for further improvement. However, challenging phenotyping methods hinder a large-scale genetic study of flooding tolerance in common bean and other economically important crops. A greenhouse phenotyping protocol was developed to evaluate the flooding conditions at early stages. The Middle-American diversity panel ( n = 272) of common bean was developed to capture most of the diversity exits in North American germplasm. This panel was evaluated for seven traits under both flooded and non-flooded conditions at two early developmental stages. A subset of contrasting genotypes was further evaluated in the field to assess the relationship between greenhouse and field data under flooding condition. A genome-wide association study using ~150 K SNPs was performed to discover genomic regions associated with multiple physiological responses. The results indicate a significant strong correlation ( r > 0.77) between greenhouse and field data, highlighting the reliability of greenhouse phenotyping method. Black and small red beans were the least affected by excess water at germination stage. At the seedling stage, pinto and great northern genotypes were the most tolerant. Root weight reduction due to flooding was greatest in pink and small red cultivars. Flooding reduced the chlorophyll content to the greatest extent in the navy bean cultivars compared with other market classes. Races of Durango/Jalisco and Mesoamerica were separated by both genotypic and phenotypic data indicating the potential effect of eco-geographical variations. Furthermore, several loci were identified that potentially represent the antagonistic pleiotropy. The GWAS analysis revealed peaks at Pv08/1.6 Mb and Pv02/41 Mb that are associated with root weight and germination rate, respectively. These regions are syntenic with two QTL reported in soybean ( Glycine max L.) that contribute to flooding tolerance, suggesting a conserved evolutionary pathway involved in flooding tolerance for these related legumes.
USDA-ARS?s Scientific Manuscript database
The study of the genetic basis of ecological adaptation remains in its infancy, and most studies have focused on phenotypically simple traits. Host plant use by herbivorous insects is phenotypically complex. While research has illuminated the evolutionary determinants of host use, knowledge of its...
USDA-ARS?s Scientific Manuscript database
Both insufficient and excessive male inflorescence size leads to a reduction in maize yield. Knowledge of the genetic architecture of male inflorescence is essential to achieve the optimum inflorescence size for maize breeding. In this study, we used approximately eight thousand inbreds, including b...
The genetic and biological basis of feed efficiency in mid-lactation Holstein dairy cows
USDA-ARS?s Scientific Manuscript database
The objective of this study was to characterize the genetic architecture and biological basis of feed efficiency in lactating Holstein cows. In total, 4,916 cows with actual or imputed genotypes for 60,671 SNP had individual feed intake, milk yield, milk composition, and body weight records. Cows we...
USDA-ARS?s Scientific Manuscript database
In rice (Oryza sativa L.), end-use/cooking quality is vital for producers and millions of consumers worldwide. Grain quality is a complex trait with interacting genetic and environmental factors. Deciphering the complex genetic architecture associated with grain quality, will provide vital informati...
USDA-ARS?s Scientific Manuscript database
Vertical growth of plants is a dynamic process that is influenced by genetic and environmental factors and has a pronounced effect on overall plant architecture and biomass composition. We have performed twelve controlled growth trials of an interspecific Setaria italica x Setaria viridis recombinan...
Oppenheim, Sara J.; Gould, Fred; Hopper, Keith R.
2012-01-01
We used genetic mapping to examine the genetic architecture of differences in host plant use between two species of noctuid moths, Heliothis subflexa, a specialist on Physalis spp., and its close relative, the broad generalist H. virescens. We introgressed H. subflexa chromosomes into the H. virescens background and analyzed 1,462 backcross insects. The effects of H. subflexa-origin chromosomes were small when measured as the percent variation explained in backcross populations (0.2 to 5%), but were larger when considered in relation to the interspecific difference explained (1.5 to 165%). Most significant chromosomes had effects on more than one trait, and their effects varied between years, sexes, and genetic backgrounds. Different chromosomes could produce similar phenotypes, suggesting that the same trait might be controlled by different chromosomes in different backcross populations. It appears that many loci of small effect contribute to the use of Physalis by H. subflexa. We hypothesize that behavioral changes may have paved the way for physiological adaptation to Physalis by the generalist ancestor of H. subflexa and H. virescens. PMID:23106701
Pritchard, Victoria L; Viitaniemi, Heidi M; McCairns, R J Scott; Merilä, Juha; Nikinmaa, Mikko; Primmer, Craig R; Leder, Erica H
2017-01-05
Much adaptive evolutionary change is underlain by mutational variation in regions of the genome that regulate gene expression rather than in the coding regions of the genes themselves. An understanding of the role of gene expression variation in facilitating local adaptation will be aided by an understanding of underlying regulatory networks. Here, we characterize the genetic architecture of gene expression variation in the threespine stickleback (Gasterosteus aculeatus), an important model in the study of adaptive evolution. We collected transcriptomic and genomic data from 60 half-sib families using an expression microarray and genotyping-by-sequencing, and located expression quantitative trait loci (eQTL) underlying the variation in gene expression in liver tissue using an interval mapping approach. We identified eQTL for several thousand expression traits. Expression was influenced by polymorphism in both cis- and trans-regulatory regions. Trans-eQTL clustered into hotspots. We did not identify master transcriptional regulators in hotspot locations: rather, the presence of hotspots may be driven by complex interactions between multiple transcription factors. One observed hotspot colocated with a QTL recently found to underlie salinity tolerance in the threespine stickleback. However, most other observed hotspots did not colocate with regions of the genome known to be involved in adaptive divergence between marine and freshwater habitats. Copyright © 2017 Pritchard et al.
Pritchard, Victoria L.; Viitaniemi, Heidi M.; McCairns, R. J. Scott; Merilä, Juha; Nikinmaa, Mikko; Primmer, Craig R.; Leder, Erica H.
2016-01-01
Much adaptive evolutionary change is underlain by mutational variation in regions of the genome that regulate gene expression rather than in the coding regions of the genes themselves. An understanding of the role of gene expression variation in facilitating local adaptation will be aided by an understanding of underlying regulatory networks. Here, we characterize the genetic architecture of gene expression variation in the threespine stickleback (Gasterosteus aculeatus), an important model in the study of adaptive evolution. We collected transcriptomic and genomic data from 60 half-sib families using an expression microarray and genotyping-by-sequencing, and located expression quantitative trait loci (eQTL) underlying the variation in gene expression in liver tissue using an interval mapping approach. We identified eQTL for several thousand expression traits. Expression was influenced by polymorphism in both cis- and trans-regulatory regions. Trans-eQTL clustered into hotspots. We did not identify master transcriptional regulators in hotspot locations: rather, the presence of hotspots may be driven by complex interactions between multiple transcription factors. One observed hotspot colocated with a QTL recently found to underlie salinity tolerance in the threespine stickleback. However, most other observed hotspots did not colocate with regions of the genome known to be involved in adaptive divergence between marine and freshwater habitats. PMID:27836907
Cousminer, Diana L; Berry, Diane J; Timpson, Nicholas J; Ang, Wei; Thiering, Elisabeth; Byrne, Enda M; Taal, H Rob; Huikari, Ville; Bradfield, Jonathan P; Kerkhof, Marjan; Groen-Blokhuis, Maria M; Kreiner-Møller, Eskil; Marinelli, Marcella; Holst, Claus; Leinonen, Jaakko T; Perry, John R B; Surakka, Ida; Pietiläinen, Olli; Kettunen, Johannes; Anttila, Verneri; Kaakinen, Marika; Sovio, Ulla; Pouta, Anneli; Das, Shikta; Lagou, Vasiliki; Power, Chris; Prokopenko, Inga; Evans, David M; Kemp, John P; St Pourcain, Beate; Ring, Susan; Palotie, Aarno; Kajantie, Eero; Osmond, Clive; Lehtimäki, Terho; Viikari, Jorma S; Kähönen, Mika; Warrington, Nicole M; Lye, Stephen J; Palmer, Lyle J; Tiesler, Carla M T; Flexeder, Claudia; Montgomery, Grant W; Medland, Sarah E; Hofman, Albert; Hakonarson, Hakon; Guxens, Mònica; Bartels, Meike; Salomaa, Veikko; Murabito, Joanne M; Kaprio, Jaakko; Sørensen, Thorkild I A; Ballester, Ferran; Bisgaard, Hans; Boomsma, Dorret I; Koppelman, Gerard H; Grant, Struan F A; Jaddoe, Vincent W V; Martin, Nicholas G; Heinrich, Joachim; Pennell, Craig E; Raitakari, Olli T; Eriksson, Johan G; Smith, George Davey; Hyppönen, Elina; Järvelin, Marjo-Riitta; McCarthy, Mark I; Ripatti, Samuli; Widén, Elisabeth
2013-07-01
The pubertal height growth spurt is a distinctive feature of childhood growth reflecting both the central onset of puberty and local growth factors. Although little is known about the underlying genetics, growth variability during puberty correlates with adult risks for hormone-dependent cancer and adverse cardiometabolic health. The only gene so far associated with pubertal height growth, LIN28B, pleiotropically influences childhood growth, puberty and cancer progression, pointing to shared underlying mechanisms. To discover genetic loci influencing pubertal height and growth and to place them in context of overall growth and maturation, we performed genome-wide association meta-analyses in 18 737 European samples utilizing longitudinally collected height measurements. We found significant associations (P < 1.67 × 10(-8)) at 10 loci, including LIN28B. Five loci associated with pubertal timing, all impacting multiple aspects of growth. In particular, a novel variant correlated with expression of MAPK3, and associated both with increased prepubertal growth and earlier menarche. Another variant near ADCY3-POMC associated with increased body mass index, reduced pubertal growth and earlier puberty. Whereas epidemiological correlations suggest that early puberty marks a pathway from rapid prepubertal growth to reduced final height and adult obesity, our study shows that individual loci associating with pubertal growth have variable longitudinal growth patterns that may differ from epidemiological observations. Overall, this study uncovers part of the complex genetic architecture linking pubertal height growth, the timing of puberty and childhood obesity and provides new information to pinpoint processes linking these traits.
Genetic and developmental basis for parallel evolution and its significance for hominoid evolution.
Reno, Philip L
2014-01-01
Greater understanding of ape comparative anatomy and evolutionary history has brought a general appreciation that the hominoid radiation is characterized by substantial homoplasy.(1-4) However, little consensus has been reached regarding which features result from repeated evolution. This has important implications for reconstructing ancestral states throughout hominoid evolution, including the nature of the Pan-Homo last common ancestor (LCA). Advances from evolutionary developmental biology (evo-devo) have expanded the diversity of model organisms available for uncovering the morphogenetic mechanisms underlying instances of repeated phenotypic change. Of particular relevance to hominoids are data from adaptive radiations of birds, fish, and even flies demonstrating that parallel phenotypic changes often use similar genetic and developmental mechanisms. The frequent reuse of a limited set of genes and pathways underlying phenotypic homoplasy suggests that the conserved nature of the genetic and developmental architecture of animals can influence evolutionary outcomes. Such biases are particularly likely to be shared by closely related taxa that reside in similar ecological niches and face common selective pressures. Consideration of these developmental and ecological factors provides a strong theoretical justification for the substantial homoplasy observed in the evolution of complex characters and the remarkable parallel similarities that can occur in closely related taxa. Thus, as in other branches of the hominoid radiation, repeated phenotypic evolution within African apes is also a distinct possibility. If so, the availability of complete genomes for each of the hominoid genera makes them another model to explore the genetic basis of repeated evolution. © 2014 Wiley Periodicals, Inc.
Cousminer, Diana L.; Berry, Diane J.; Timpson, Nicholas J.; Ang, Wei; Thiering, Elisabeth; Byrne, Enda M.; Taal, H. Rob; Huikari, Ville; Bradfield, Jonathan P.; Kerkhof, Marjan; Groen-Blokhuis, Maria M.; Kreiner-Møller, Eskil; Marinelli, Marcella; Holst, Claus; Leinonen, Jaakko T.; Perry, John R.B.; Surakka, Ida; Pietiläinen, Olli; Kettunen, Johannes; Anttila, Verneri; Kaakinen, Marika; Sovio, Ulla; Pouta, Anneli; Das, Shikta; Lagou, Vasiliki; Power, Chris; Prokopenko, Inga; Evans, David M.; Kemp, John P.; St Pourcain, Beate; Ring, Susan; Palotie, Aarno; Kajantie, Eero; Osmond, Clive; Lehtimäki, Terho; Viikari, Jorma S.; Kähönen, Mika; Warrington, Nicole M.; Lye, Stephen J.; Palmer, Lyle J.; Tiesler, Carla M.T.; Flexeder, Claudia; Montgomery, Grant W.; Medland, Sarah E.; Hofman, Albert; Hakonarson, Hakon; Guxens, Mònica; Bartels, Meike; Salomaa, Veikko; Murabito, Joanne M.; Kaprio, Jaakko; Sørensen, Thorkild I.A.; Ballester, Ferran; Bisgaard, Hans; Boomsma, Dorret I.; Koppelman, Gerard H.; Grant, Struan F.A.; Jaddoe, Vincent W.V.; Martin, Nicholas G.; Heinrich, Joachim; Pennell, Craig E.; Raitakari, Olli T.; Eriksson, Johan G.; Smith, George Davey; Hyppönen, Elina; Järvelin, Marjo-Riitta; McCarthy, Mark I.; Ripatti, Samuli; Widén, Elisabeth
2013-01-01
The pubertal height growth spurt is a distinctive feature of childhood growth reflecting both the central onset of puberty and local growth factors. Although little is known about the underlying genetics, growth variability during puberty correlates with adult risks for hormone-dependent cancer and adverse cardiometabolic health. The only gene so far associated with pubertal height growth, LIN28B, pleiotropically influences childhood growth, puberty and cancer progression, pointing to shared underlying mechanisms. To discover genetic loci influencing pubertal height and growth and to place them in context of overall growth and maturation, we performed genome-wide association meta-analyses in 18 737 European samples utilizing longitudinally collected height measurements. We found significant associations (P < 1.67 × 10−8) at 10 loci, including LIN28B. Five loci associated with pubertal timing, all impacting multiple aspects of growth. In particular, a novel variant correlated with expression of MAPK3, and associated both with increased prepubertal growth and earlier menarche. Another variant near ADCY3-POMC associated with increased body mass index, reduced pubertal growth and earlier puberty. Whereas epidemiological correlations suggest that early puberty marks a pathway from rapid prepubertal growth to reduced final height and adult obesity, our study shows that individual loci associating with pubertal growth have variable longitudinal growth patterns that may differ from epidemiological observations. Overall, this study uncovers part of the complex genetic architecture linking pubertal height growth, the timing of puberty and childhood obesity and provides new information to pinpoint processes linking these traits. PMID:23449627
Careau, Vincent; Wolak, Matthew E; Carter, Patrick A; Garland, Theodore
2013-11-01
Replicated selection experiments provide a powerful way to study how "multiple adaptive solutions" may lead to differences in the quantitative-genetic architecture of selected traits and whether this may translate into differences in the timing at which evolutionary limits are reached. We analyze data from 31 generations (n=17,988) of selection on voluntary wheel running in house mice. The rate of initial response, timing of selection limit, and height of the plateau varied significantly between sexes and among the four selected lines. Analyses of litter size and realized selection differentials seem to rule out counterposing natural selection as a cause of the selection limits. Animal-model analyses showed that although the additive genetic variance was significantly lower in selected than control lines, both before and after the limits, the decrease was not sufficient to explain the limits. Moreover, directional selection promoted a negative covariance between additive and maternal genetic variance over the first 10 generations. These results stress the importance of replication in selection studies of higher-level traits and highlight the fact that long-term predictions of response to selection are not necessarily expected to be linear because of the variable effects of selection on additive genetic variance and maternal effects. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.
Butler, Merlin G; Rafi, Syed K; McGuire, Austen; Manzardo, Ann M
2016-01-01
To provide an update of currently recognized clinically relevant candidate and known genes for human reproduction and related infertility plotted on high resolution chromosome ideograms (850 band level) and represented alphabetically in tabular form. Descriptive authoritative computer-based website and peer-reviewed medical literature searches used pertinent keywords representing human reproduction and related infertility along with genetics and gene mutations. A master list of genes associated with human reproduction and related infertility was generated with a visual representation of gene locations on high resolution chromosome ideograms. GeneAnalytics pathway analysis was carried out on the resulting list of genes to assess underlying genetic architecture for infertility. Advances in genetic technology have led to the discovery of genes responsible for reproduction and related infertility. Genes identified (N=371) in our search primarily impact ovarian steroidogenesis through sex hormone biology, germ cell production, genito-urinary or gonadal development and function, and related peptide production, receptors and regulatory factors. The location of gene symbols plotted on high resolution chromosome ideograms forms a conceptualized image of the distribution of human reproduction genes. The updated master list can be used to promote better awareness of genetics of reproduction and related infertility and advance discoveries on genetic causes and disease mechanisms. Copyright © 2015 Elsevier B.V. All rights reserved.
Fan, Jean; Lee, Hae-Ock; Lee, Soohyun; Ryu, Da-Eun; Lee, Semin; Xue, Catherine; Kim, Seok Jin; Kim, Kihyun; Barkas, Nikolas; Park, Peter J; Park, Woong-Yang; Kharchenko, Peter V
2018-06-13
Characterization of intratumoral heterogeneity is critical to cancer therapy, as presence of phenotypically diverse cell populations commonly fuels relapse and resistance to treatment. Although genetic variation is a well-studied source of intratumoral heterogeneity, the functional impact of most genetic alterations remains unclear. Even less understood is the relative importance of other factors influencing heterogeneity, such as epigenetic state or tumor microenvironment. To investigate the relationship between genetic and transcriptional heterogeneity in a context of cancer progression, we devised a computational approach called HoneyBADGER to identify copy number variation and loss-of-heterozygosity in individual cells from single-cell RNA-sequencing data. By integrating allele and normalized expression information, HoneyBADGER is able to identify and infer the presence of subclone-specific alterations in individual cells and reconstruct underlying subclonal architecture. Examining several tumor types, we show that HoneyBADGER is effective at identifying deletion, amplifications, and copy-neutral loss-of-heterozygosity events, and is capable of robustly identifying subclonal focal alterations as small as 10 megabases. We further apply HoneyBADGER to analyze single cells from a progressive multiple myeloma patient to identify major genetic subclones that exhibit distinct transcriptional signatures relevant to cancer progression. Surprisingly, other prominent transcriptional subpopulations within these tumors did not line up with the genetic subclonal structure, and were likely driven by alternative, non-clonal mechanisms. These results highlight the need for integrative analysis to understand the molecular and phenotypic heterogeneity in cancer. Published by Cold Spring Harbor Laboratory Press.
Jones, David B; Jerry, Dean R; Khatkar, Mehar S; Raadsma, Herman W; Zenger, Kyall R
2013-11-20
The silver-lipped pearl oyster, Pinctada maxima, is an important tropical aquaculture species extensively farmed for the highly sought "South Sea" pearls. Traditional breeding programs have been initiated for this species in order to select for improved pearl quality, but many economic traits under selection are complex, polygenic and confounded with environmental factors, limiting the accuracy of selection. The incorporation of a marker-assisted selection (MAS) breeding approach would greatly benefit pearl breeding programs by allowing the direct selection of genes responsible for pearl quality. However, before MAS can be incorporated, substantial genomic resources such as genetic linkage maps need to be generated. The construction of a high-density genetic linkage map for P. maxima is not only essential for unravelling the genomic architecture of complex pearl quality traits, but also provides indispensable information on the genome structure of pearl oysters. A total of 1,189 informative genome-wide single nucleotide polymorphisms (SNPs) were incorporated into linkage map construction. The final linkage map consisted of 887 SNPs in 14 linkage groups, spans a total genetic distance of 831.7 centimorgans (cM), and covers an estimated 96% of the P. maxima genome. Assessment of sex-specific recombination across all linkage groups revealed limited overall heterochiasmy between the sexes (i.e. 1.15:1 F/M map length ratio). However, there were pronounced localised differences throughout the linkage groups, whereby male recombination was suppressed near the centromeres compared to female recombination, but inflated towards telomeric regions. Mean values of LD for adjacent SNP pairs suggest that a higher density of markers will be required for powerful genome-wide association studies. Finally, numerous nacre biomineralization genes were localised providing novel positional information for these genes. This high-density SNP genetic map is the first comprehensive linkage map for any pearl oyster species. It provides an essential genomic tool facilitating studies investigating the genomic architecture of complex trait variation and identifying quantitative trait loci for economically important traits useful in genetic selection programs within the P. maxima pearling industry. Furthermore, this map provides a foundation for further research aiming to improve our understanding of the dynamic process of biomineralization, and pearl oyster evolution and synteny.
Polygenic risk score and heritability estimates reveals a genetic relationship between ASD and OCD.
Guo, W; Samuels, J F; Wang, Y; Cao, H; Ritter, M; Nestadt, P S; Krasnow, J; Greenberg, B D; Fyer, A J; McCracken, J T; Geller, D A; Murphy, D L; Knowles, J A; Grados, M A; Riddle, M A; Rasmussen, S A; McLaughlin, N C; Nurmi, E L; Askland, K D; Cullen, B A; Piacentini, J; Pauls, D L; Bienvenu, O J; Stewart, S E; Goes, F S; Maher, B; Pulver, A E; Valle, D; Mattheisen, M; Qian, J; Nestadt, G; Shugart, Y Y
2017-07-01
Obsessive-compulsive disorder (OCD) and Autism spectrum disorder (ASD) are both highly heritable neurodevelopmental disorders that conceivably share genetic risk factors. However, the underlying genetic determinants remain largely unknown. In this work, the authors describe a combined genome-wide association study (GWAS) of ASD and OCD. The OCD dataset includes 2998 individuals in nuclear families. The ASD dataset includes 6898 individuals in case-parents trios. GWAS summary statistics were examined for potential enrichment of functional variants associated with gene expression levels in brain regions. The top ranked SNP is rs4785741 (chromosome 16) with P value=6.9×10 -7 in our re-analysis. Polygenic risk score analyses were conducted to investigate the genetic relationship within and across the two disorders. These analyses identified a significant polygenic component of ASD, predicting 0.11% of the phenotypic variance in an independent OCD data set. In addition, we examined the genomic architecture of ASD and OCD by estimating heritability on different chromosomes and different allele frequencies, analyzing genome-wide common variant data by using the Genome-wide Complex Trait Analysis (GCTA) program. The estimated global heritability of OCD is 0.427 (se=0.093) and 0.174 (se=0.053) for ASD in these imputed data. Published by Elsevier B.V.
Saumitou-Laprade, Pierre; Vernet, Philippe; Vekemans, Xavier; Billiard, Sylvain; Gallina, Sophie; Essalouh, Laila; Mhaïs, Ali; Moukhli, Abdelmajid; El Bakkali, Ahmed; Barcaccia, Gianni; Alagna, Fiammetta; Mariotti, Roberto; Cultrera, Nicolò G M; Pandolfi, Saverio; Rossi, Martina; Khadari, Bouchaïb; Baldoni, Luciana
2017-10-01
The olive ( Olea europaea L.) is a typical important perennial crop species for which the genetic determination and even functionality of self-incompatibility (SI) are still largely unresolved. It is still not known whether SI is under gametophytic or sporophytic genetic control, yet fruit production in orchards depends critically on successful ovule fertilization. We studied the genetic determination of SI in olive in light of recent discoveries in other genera of the Oleaceae family. Using intra- and interspecific stigma tests on 89 genotypes representative of species-wide olive diversity and the compatibility/incompatibility reactions of progeny plants from controlled crosses, we confirmed that O. europaea shares the same homomorphic diallelic self-incompatibility (DSI) system as the one recently identified in Phillyrea angustifolia and Fraxinus ornus . SI is sporophytic in olive. The incompatibility response differs between the two SI groups in terms of how far pollen tubes grow before growth is arrested within stigma tissues. As a consequence of this DSI system, the chance of cross-incompatibility between pairs of varieties in an orchard is high (50%) and fruit production may be limited by the availability of compatible pollen. The discovery of the DSI system in O. europaea will undoubtedly offer opportunities to optimize fruit production.
Ahuja, Abha; Singh, Rama S
2008-05-01
We investigated the genetic architecture of variation in male sex comb bristle number, a rapidly evolving secondary sexual character of Drosophila. Twenty-four generations of divergent artificial selection for sex comb bristle number in a heterogeneous population of Drosophila melanogaster resulted in a significant response that was more pronounced in the direction of low bristle numbers. We observed a strong positive correlated response to selection in the corresponding female transverse bristle row. The correlated response in male abdominal and sternopleural bristle numbers, on the other hand, did not follow the same pattern as sex comb bristle number differences between selection lines. Relaxation-of-selection experiments along with mate choice and fecundity assays using the selection lines developed demonstrated the action of stabilizing selection on sex comb bristle number. Our results show (1) substantial genetic variation underlying sex comb bristle number variation; (2) a weak relationship between the sex comb and developmentally related, non-sex bristle systems; and (3) that sexual selection may be a driving force in sex comb evolution, indicating the potential of sex combs to diversify rapidly during population differentiation and speciation. We discuss the implications of these results for theories of genetic variation in display and nondisplay male sex traits.
Ahuja, Abha; De Vito, Scott; Singh, Rama S
2011-04-01
Genetic architecture of variation underlying male sex comb bristle number, a rapidly evolving secondary sexual character of Drosophila, was examined. First, in order to test for condition dependence, diet was manipulated in a set of ten Drosophila melanogaster full-sib families. We confirmed heightened condition dependent expression of sex comb bristle number and its female homologue (distal transverse row bristles) as compared to non-sex sternopleural bristles. Significant genotype by environment effects were detected for the sex traits indicating a genetic basis for condition dependence. Next we measured sex comb bristle number and sternopleural bristle number, as well as residual mass, a commonly used condition index, in a set of thirty half-sib families. Sire effect was not significant for sex comb and sternopleural bristle number, and we detected a strong dominance and/or maternal effect or X chromosome effect for both traits. A strong sire effect was detected for condition and its heritability was the highest as compared to sex comb and sternopleural bristles. We discuss our results in light of the rapid response to divergent artificial selection for sex comb bristle number reported previously. The nature of genetic variation for male sex traits continues to be an important unresolved issue in evolutionary biology.
Li, Riqing; Xia, Jixing; Xu, Yiwei; Zhao, Xiucai; Liu, Yao-Guang; Chen, Yuanling
2014-01-01
Plant height is an important agronomic trait for crop architecture and yield. Most known factors determining plant height function in gibberellin or brassinosteroid biosynthesis or signal transduction. Here, we report a japonica rice (Oryza sativa ssp. japonica) dominant dwarf mutant, Photoperiod-sensitive dwarf 1 (Psd1). The Psd1 mutant showed impaired cell division and elongation, and a severe dwarf phenotype under long-day conditions, but nearly normal growth in short-day. The plant height of Psd1 mutant could not be rescued by gibberellin or brassinosteroid treatment. Genetic analysis with R1 and F2 populations determined that Psd1 phenotype was controlled by a single dominant locus. Linkage analysis with 101 tall F2 plants grown in a long-day season, which were derived from a cross between Psd1 and an indica cultivar, located Psd1 locus on chromosome 1. Further fine-mapping with 1017 tall F2 plants determined this locus on an 11.5-kb region. Sequencing analysis of this region detected a mutation site in a gene encoding a putative lipid transfer protein; the mutation produces a truncated C-terminus of the protein. This study establishes the genetic foundation for understanding the molecular mechanisms regulating plant cell division and elongation mediated by interaction between genetic and environmental factors.
Weiss, Kenneth M; Buchanan, Anne V
2011-08-01
Genes are generally assumed to be primary biological causes of biological phenotypes and their evolution. In just over a century, a research agenda that has built on Mendel's experiments and on Darwin's theory of natural selection as a law of nature has had unprecedented scientific success in isolating and characterizing many aspects of genetic causation. We revel in these successes, and yet the story is not quite so simple. The complex cooperative nature of genetic architecture and its evolution include teasingly tractable components, but much remains elusive. The proliferation of data generated in our "omics" age raises the question of whether we even have (or need) a unified theory or "law" of life, or even clear standards of inference by which to answer the question. If not, this not only has implications for the widely promulgated belief that we will soon be able to predict phenotypes like disease risk from genes, but also speaks to the limitations in the underlying science itself. Much of life seems to be characterized by ad hoc, ephemeral, contextual probabilism without proper underlying distributions. To the extent that this is true, causal effects are not asymptotically predictable, and new ways of understanding life may be required.
Weiss, Kenneth M.; Buchanan, Anne V.
2011-01-01
Genes are generally assumed to be primary biological causes of biological phenotypes and their evolution. In just over a century, a research agenda that has built on Mendel’s experiments and on Darwin’s theory of natural selection as a law of nature has had unprecedented scientific success in isolating and characterizing many aspects of genetic causation. We revel in these successes, and yet the story is not quite so simple. The complex cooperative nature of genetic architecture and its evolution include teasingly tractable components, but much remains elusive. The proliferation of data generated in our “omics” age raises the question of whether we even have (or need) a unified theory or “law” of life, or even clear standards of inference by which to answer the question. If not, this not only has implications for the widely promulgated belief that we will soon be able to predict phenotypes like disease risk from genes, but also speaks to the limitations in the underlying science itself. Much of life seems to be characterized by ad hoc, ephemeral, contextual probabilism without proper underlying distributions. To the extent that this is true, causal effects are not asymptotically predictable, and new ways of understanding life may be required. PMID:21828277
OsRAMOSA2 Shapes Panicle Architecture through Regulating Pedicel Length.
Lu, Huan; Dai, Zhengyan; Li, Ling; Wang, Jiang; Miao, Xuexia; Shi, Zhenying
2017-01-01
The panicle architecture of rice is an important characteristic that influences reproductive success and yield. It is largely determined by the number and length of the primary and secondary branches. The number of panicle branches is defined by the inflorescence meristem state between determinacy and indeterminacy; for example, the maize ramosa2 ( ra2 ) mutant has more branches in its tassel through loss of spikelet determinacy. Some genes and factors influencing the number of primary and secondary branches have been studied, but little is known about the molecular mechanism underlying pedicel development, which also influences panicle architecture. We report here that rice OsRAMOSA2 ( OsRA2 ) gene modifies panicle architecture through regulating pedicel length. Ectopic expression of OsRA2 resulted in a shortened pedicel while inhibition of OsRA2 through RNA interference produced elongated pedicel. In addition, OsRA2 influenced seed morphology. The OsRA2 protein localized to the nucleus and showed transcriptional activation in yeast; in accordance with its function in pedicel development, OsRA2 mRNA was enriched in the anlagen of axillary meristems, such as primary and secondary branch meristems and the spikelet meristems of young panicles. This indicates a conserved role of OsRA2 for shaping the initial steps of inflorescence architecture. Genetic analysis revealed that OsRA2 may control panicle architecture using the same pathway as that of the axillary meristem gene LAX1 ( LAX PANICLE1 ). Moreover, OsRA2 acted downstream of RCN2 in regulating pedicel and branch lengths, but upstream of RCN2 for control of the number of secondary branches, indicating that branch number and length development in the panicle were respectively regulated using parallel pathway. Functional conservation between OsRA2 and AtLOB , and the conservation and diversification of RA2 in maize and rice are also discussed.
Autism spectrum disorders: an updated guide for genetic counseling.
Griesi-Oliveira, Karina; Sertié, Andréa Laurato
2017-01-01
Autism spectrum disorder is a complex and genetically heterogeneous disorder, which has hampered the identification of the etiological factors in each patient and, consequently, the genetic counseling for families at risk. However, in the last decades, the remarkable advances in the knowledge of genetic aspects of autism based on genetic and molecular research, as well as the development of new molecular diagnostic tools, have substantially changed this scenario. Nowadays, it is estimated that using the currently available molecular tests, a potential underlying genetic cause can be identified in nearly 25% of cases. Combined with clinical assessment, prenatal history evaluation and investigation of other physiological aspects, an etiological explanation for the disease can be found for approximately 30 to 40% of patients. Therefore, in view of the current knowledge about the genetic architecture of autism spectrum disorder, which has contributed for a more precise genetic counseling, and of the potential benefits that an etiological investigation can bring to patients and families, molecular genetic investigation has become increasingly important. Here, we discuss the current view of the genetic architecture of autism spectrum disorder, and list the main associated genetic alterations, the available molecular tests and the key aspects for the genetic counseling of these families. RESUMO O transtorno do espectro autista é um distúrbio complexo e geneticamente heterogêneo, o que sempre dificultou a identificação de sua etiologia em cada paciente em particular e, por consequência, o aconselhamento genético das famílias. Porém, nas últimas décadas, o acúmulo crescente de conhecimento oriundo das pesquisas sobre os aspectos genéticos e moleculares desta doença, assim como o desenvolvimento de novas ferramentas de diagnóstico molecular, tem mudado este cenário de forma substancial. Atualmente, estima-se que, por meio de testes moleculares, é possível detectar uma alteração genética potencialmente causal em cerca de 25% dos casos. Considerando-se também a avaliação clínica, a história pré-natal e a investigação de outros aspectos fisiológicos, pode-se atribuir uma etiologia para aproximadamente 30 a 40% dos pacientes. Assim, em vista do conhecimento atual sobre a arquitetura genética do transtorno do espectro autista, que tem tornado o aconselhamento genético cada vez mais preciso, e dos potenciais benefícios que a investigação etiológica pode trazer aos pacientes e familiares, tornam-se cada vez mais importantes os testes genéticos moleculares. Apresentamos aqui uma breve discussão sobre a visão atual da arquitetura genética dos transtornos do espectro autista, listando as principais alterações genéticas associadas, os testes moleculares disponíveis e os principais aspectos a se considerar para o aconselhamento genético destas famílias.
Zenooz, Alireza Moosavi; Ashtiani, Farzin Zokaee; Ranjbar, Reza; Nikbakht, Fatemeh; Bolouri, Oberon
2017-07-03
Biodiesel production from microalgae feedstock should be performed after growth and harvesting of the cells, and the most feasible method for harvesting and dewatering of microalgae is flocculation. Flocculation modeling can be used for evaluation and prediction of its performance under different affective parameters. However, the modeling of flocculation in microalgae is not simple and has not performed yet, under all experimental conditions, mostly due to different behaviors of microalgae cells during the process under different flocculation conditions. In the current study, the modeling of microalgae flocculation is studied with different neural network architectures. Microalgae species, Chlorella sp., was flocculated with ferric chloride under different conditions and then the experimental data modeled using artificial neural network. Neural network architectures of multilayer perceptron (MLP) and radial basis function architectures, failed to predict the targets successfully, though, modeling was effective with ensemble architecture of MLP networks. Comparison between the performances of the ensemble and each individual network explains the ability of the ensemble architecture in microalgae flocculation modeling.
Weather prediction using a genetic memory
NASA Technical Reports Server (NTRS)
Rogers, David
1990-01-01
Kanaerva's sparse distributed memory (SDM) is an associative memory model based on the mathematical properties of high dimensional binary address spaces. Holland's genetic algorithms are a search technique for high dimensional spaces inspired by evolutional processes of DNA. Genetic Memory is a hybrid of the above two systems, in which the memory uses a genetic algorithm to dynamically reconfigure its physical storage locations to reflect correlations between the stored addresses and data. This architecture is designed to maximize the ability of the system to scale-up to handle real world problems.
Speakman, John R.; Westerterp, Klaas R.
2013-01-01
SUMMARY The thrifty-gene hypothesis (TGH) posits that the modern genetic predisposition to obesity stems from a historical past where famine selected for genes that promote efficient fat deposition. It has been previously argued that such a scenario is unfeasible because under such strong selection any gene favouring fat deposition would rapidly move to fixation. Hence, we should all be predisposed to obesity: which we are not. The genetic architecture of obesity that has been revealed by genome-wide association studies (GWAS), however, calls into question such an argument. Obesity is caused by mutations in many hundreds (maybe thousands) of genes, each with a very minor, independent and additive impact. Selection on such genes would probably be very weak because the individual advantages they would confer would be very small. Hence, the genetic architecture of the epidemic may indeed be compatible with, and hence support, the TGH. To evaluate whether this is correct, it is necessary to know the likely effects of the identified GWAS alleles on survival during starvation. This would allow definition of their advantage in famine conditions, and hence the likely selection pressure for such alleles to have spread over the time course of human evolution. We constructed a mathematical model of weight loss under total starvation using the established principles of energy balance. Using the model, we found that fatter individuals would indeed survive longer and, at a given body weight, females would survive longer than males, when totally starved. An allele causing deposition of an extra 80 g of fat would result in an extension of life under total starvation by about 1.1–1.6% in an individual with 10 kg of fat and by 0.25–0.27% in an individual carrying 32 kg of fat. A mutation causing a per allele effect of 0.25% would become completely fixed in a population with an effective size of 5 million individuals in 6000 selection events. Because there have probably been about 24,000 famine events since the evolution of hominins 4 million years ago, there has been ample time even for genes with only very minor impacts on adiposity to move to fixation. The observed polymorphic variation in the genes causing the predisposition to obesity is incompatible with the TGH, unless all these single nucleotide polymorphisms (SNPs) arose in the last 900,000 years, a requirement we know is incorrect. The TGH is further weakened by the observation of no link between the effect size of these SNPs and their prevalence, which would be anticipated under the TGH model of selection if all the SNPs had arisen in the last 900,000 years. PMID:22864023
The Impact of Population Demography and Selection on the Genetic Architecture of Complex Traits
Lohmueller, Kirk E.
2014-01-01
Population genetic studies have found evidence for dramatic population growth in recent human history. It is unclear how this recent population growth, combined with the effects of negative natural selection, has affected patterns of deleterious variation, as well as the number, frequency, and effect sizes of mutations that contribute risk to complex traits. Because researchers are performing exome sequencing studies aimed at uncovering the role of low-frequency variants in the risk of complex traits, this topic is of critical importance. Here I use simulations under population genetic models where a proportion of the heritability of the trait is accounted for by mutations in a subset of the exome. I show that recent population growth increases the proportion of nonsynonymous variants segregating in the population, but does not affect the genetic load relative to a population that did not expand. Under a model where a mutation's effect on a trait is correlated with its effect on fitness, rare variants explain a greater portion of the additive genetic variance of the trait in a population that has recently expanded than in a population that did not recently expand. Further, when using a single-marker test, for a given false-positive rate and sample size, recent population growth decreases the expected number of significant associations with the trait relative to the number detected in a population that did not expand. However, in a model where there is no correlation between a mutation's effect on fitness and the effect on the trait, common variants account for much of the additive genetic variance, regardless of demography. Moreover, here demography does not affect the number of significant associations detected. These findings suggest recent population history may be an important factor influencing the power of association tests and in accounting for the missing heritability of certain complex traits. PMID:24875776
Amplifying genetic logic gates.
Bonnet, Jerome; Yin, Peter; Ortiz, Monica E; Subsoontorn, Pakpoom; Endy, Drew
2013-05-03
Organisms must process information encoded via developmental and environmental signals to survive and reproduce. Researchers have also engineered synthetic genetic logic to realize simpler, independent control of biological processes. We developed a three-terminal device architecture, termed the transcriptor, that uses bacteriophage serine integrases to control the flow of RNA polymerase along DNA. Integrase-mediated inversion or deletion of DNA encoding transcription terminators or a promoter modulates transcription rates. We realized permanent amplifying AND, NAND, OR, XOR, NOR, and XNOR gates actuated across common control signal ranges and sequential logic supporting autonomous cell-cell communication of DNA encoding distinct logic-gate states. The single-layer digital logic architecture developed here enables engineering of amplifying logic gates to control transcription rates within and across diverse organisms.
Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas-fir
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...
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 ...
Barbara J. Bentz; Ryan B. Bracewell; Karen E. Mock; Michael E. Pfrender
2011-01-01
Phenotypic plasticity in thermally-regulated traits enables close tracking of changing environmental conditions, and can thereby enhance the potential for rapid population increase, a hallmark of outbreak insect species. In a changing climate, exposure to conditions that exceed the capacity of existing phenotypic plasticity may occur. Combining information on genetic...
Cross-sex genetic correlation does not extend to sexual size dimorphism in spiders
NASA Astrophysics Data System (ADS)
Turk, Eva; Kuntner, Matjaž; Kralj-Fišer, Simona
2018-02-01
Males and females are often subjected to different selection pressures for homologous traits, resulting in sex-specific optima. Because organismal attributes usually share their genetic architectures, sex-specific selection may lead to intralocus sexual conflict. Evolution of sexual dimorphism may resolve this conflict, depending on the degree of cross-sex genetic correlation ( r MF) and the strength of sex-specific selection. In theory, high r MF implies that sexes largely share the genetic base for a given trait and are consequently sexually monomorphic, while low r MF indicates a sex-specific genetic base and sexual dimorphism. Here, we broadly test this hypothesis on three spider species with varying degrees of female-biased sexual size dimorphism, Larinioides sclopetarius (sexual dimorphism index, SDI = 0.85), Nuctenea umbratica (SDI = 0.60), and Zygiella x-notata (SDI = 0.46). We assess r MF via same-sex and opposite-sex heritability estimates. We find moderate body mass heritability but no obvious patterns in sex-specific heritability. Against the prediction, the degree of sexual size dimorphism is unrelated to the relative strength of same-sex versus opposite-sex heritability. Our results do not support the hypothesis that sexual size dimorphism is negatively associated with r MF. We conclude that sex-specific genetic architecture may not be necessary for the evolution of a sexually dimorphic trait.
Blankers, T; Lübke, A K; Hennig, R M
2015-09-01
Studying the genetic architecture of sexual traits provides insight into the rate and direction at which traits can respond to selection. Traits associated with few loci and limited genetic and phenotypic constraints tend to evolve at high rates typically observed for secondary sexual characters. Here, we examined the genetic architecture of song traits and female song preferences in the field crickets Gryllus rubens and Gryllus texensis. Song and preference data were collected from both species and interspecific F1 and F2 hybrids. We first analysed phenotypic variation to examine interspecific differentiation and trait distributions in parental and hybrid generations. Then, the relative contribution of additive and additive-dominance variation was estimated. Finally, phenotypic variance-covariance (P) matrices were estimated to evaluate the multivariate phenotype available for selection. Song traits and preferences had unimodal trait distributions, and hybrid offspring were intermediate with respect to the parents. We uncovered additive and dominance variation in song traits and preferences. For two song traits, we found evidence for X-linked inheritance. On the one hand, the observed genetic architecture does not suggest rapid divergence, although sex linkage may have allowed for somewhat higher evolutionary rates. On the other hand, P matrices revealed that multivariate variation in song traits aligned with major dimensions in song preferences, suggesting a strong selection response. We also found strong covariance between the main traits that are sexually selected and traits that are not directly selected by females, providing an explanation for the striking multivariate divergence in male calling songs despite limited divergence in female preferences. © 2015 European Society For Evolutionary Biology.
Genetic Dissection of Leaf Development in Brassica rapa Using a Genetical Genomics Approach1[W
Xiao, Dong; Wang, Huange; Basnet, Ram Kumar; Zhao, Jianjun; Lin, Ke; Hou, Xilin; Bonnema, Guusje
2014-01-01
The paleohexaploid crop Brassica rapa harbors an enormous reservoir of morphological variation, encompassing leafy vegetables, vegetable and fodder turnips (Brassica rapa, ssp. campestris), and oil crops, with different crops having very different leaf morphologies. In the triplicated B. rapa genome, many genes have multiple paralogs that may be regulated differentially and contribute to phenotypic variation. Using a genetical genomics approach, phenotypic data from a segregating doubled haploid population derived from a cross between cultivar Yellow sarson (oil type) and cultivar Pak choi (vegetable type) were used to identify loci controlling leaf development. Twenty-five colocalized phenotypic quantitative trait loci (QTLs) contributing to natural variation for leaf morphological traits, leaf number, plant architecture, and flowering time were identified. Genetic analysis showed that four colocalized phenotypic QTLs colocalized with flowering time and leaf trait candidate genes, with their cis-expression QTLs and cis- or trans-expression QTLs for homologs of genes playing a role in leaf development in Arabidopsis (Arabidopsis thaliana). The leaf gene BRASSICA RAPA KIP-RELATED PROTEIN2_A03 colocalized with QTLs for leaf shape and plant height; BRASSICA RAPA ERECTA_A09 colocalized with QTLs for leaf color and leaf shape; BRASSICA RAPA LONGIFOLIA1_A10 colocalized with QTLs for leaf size, leaf color, plant branching, and flowering time; while the major flowering time gene, BRASSICA RAPA FLOWERING LOCUS C_A02, colocalized with QTLs explaining variation in flowering time, plant architectural traits, and leaf size. Colocalization of these QTLs points to pleiotropic regulation of leaf development and plant architectural traits in B. rapa. PMID:24394778
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
Genetic Architecture of a Hormonal Response to Gene Knockdown in Honey Bees
Rueppell, Olav; Huang, Zachary Y.; Wang, Ying; Fondrk, M. Kim; Page, Robert E.; Amdam, Gro V.
2015-01-01
Variation in endocrine signaling is proposed to underlie the evolution and regulation of social life histories, but the genetic architecture of endocrine signaling is still poorly understood. An excellent example of a hormonally influenced set of social traits is found in the honey bee (Apis mellifera): a dynamic and mutually suppressive relationship between juvenile hormone (JH) and the yolk precursor protein vitellogenin (Vg) regulates behavioral maturation and foraging of workers. Several other traits cosegregate with these behavioral phenotypes, comprising the pollen hoarding syndrome (PHS) one of the best-described animal behavioral syndromes. Genotype differences in responsiveness of JH to Vg are a potential mechanistic basis for the PHS. Here, we reduced Vg expression via RNA interference in progeny from a backcross between 2 selected lines of honey bees that differ in JH responsiveness to Vg reduction and measured JH response and ovary size, which represents another key aspect of the PHS. Genetic mapping based on restriction site-associated DNA tag sequencing identified suggestive quantitative trait loci (QTL) for ovary size and JH responsiveness. We confirmed genetic effects on both traits near many QTL that had been identified previously for their effect on various PHS traits. Thus, our results support a role for endocrine control of complex traits at a genetic level. Furthermore, this first example of a genetic map of a hormonal response to gene knockdown in a social insect helps to refine the genetic understanding of complex behaviors and the physiology that may underlie behavioral control in general. PMID:25596612
40 CFR 35.937-12 - Subcontracts under subagreements for architectural or engineering services.
Code of Federal Regulations, 2011 CFR
2011-07-01
... architectural or engineering services. 35.937-12 Section 35.937-12 Protection of Environment ENVIRONMENTAL... engineering services. (a) Neither award and execution of subcontracts under a prime contract for architectural or engineering services, nor the procurement and negotiation procedures used by the engineer in...
40 CFR 35.937-12 - Subcontracts under subagreements for architectural or engineering services.
Code of Federal Regulations, 2012 CFR
2012-07-01
... architectural or engineering services. 35.937-12 Section 35.937-12 Protection of Environment ENVIRONMENTAL... engineering services. (a) Neither award and execution of subcontracts under a prime contract for architectural or engineering services, nor the procurement and negotiation procedures used by the engineer in...
40 CFR 35.937-12 - Subcontracts under subagreements for architectural or engineering services.
Code of Federal Regulations, 2013 CFR
2013-07-01
... architectural or engineering services. 35.937-12 Section 35.937-12 Protection of Environment ENVIRONMENTAL... engineering services. (a) Neither award and execution of subcontracts under a prime contract for architectural or engineering services, nor the procurement and negotiation procedures used by the engineer in...
40 CFR 35.937-12 - Subcontracts under subagreements for architectural or engineering services.
Code of Federal Regulations, 2010 CFR
2010-07-01
... architectural or engineering services. 35.937-12 Section 35.937-12 Protection of Environment ENVIRONMENTAL... engineering services. (a) Neither award and execution of subcontracts under a prime contract for architectural or engineering services, nor the procurement and negotiation procedures used by the engineer in...
40 CFR 35.937-12 - Subcontracts under subagreements for architectural or engineering services.
Code of Federal Regulations, 2014 CFR
2014-07-01
... architectural or engineering services. 35.937-12 Section 35.937-12 Protection of Environment ENVIRONMENTAL... engineering services. (a) Neither award and execution of subcontracts under a prime contract for architectural or engineering services, nor the procurement and negotiation procedures used by the engineer in...
GENETIC VARIATION IN BABOON CRANIOFACIAL SEXUAL DIMORPHISM
Willmore, Katherine E.; Roseman, Charles C.; Rogers, Jeffrey; Richtsmeier, Joan T.; Cheverud, James M.
2010-01-01
Sexual dimorphism is a widespread phenomenon and contributes greatly to intraspecies variation. Despite a long history of active research, the genetic basis of dimorphism for complex traits remains unknown. Understanding the sex-specific differences in genetic architecture for cranial traits in a highly dimorphic species could identify possible mechanisms through which selection acts to produce dimorphism. Using distances calculated from three-dimensional landmark data from CT scans of 402 baboon skulls from a known genealogy, we estimated genetic variance parameters in both sexes to determine the presence of gene-by-sex (G × S) interactions and X-linked heritability. We hypothesize that traits exhibiting the greatest degree of sexual dimorphism (facial traits in baboons) will demonstrate either stronger G × S interactions or X-linked effects. We found G × S interactions and X-linked effects for a few measures that span the areas connecting the face to the neurocranium but for no traits restricted to the face. This finding suggests that facial traits will have a limited response to selection for further evolution of dimorphism in this population. We discuss the implications of our results with respect to the origins of cranial sexual dimorphism in this baboon sample, and how the genetic architecture of these traits affects their potential for future evolution. PMID:19210535
Genetic Architecture of Flowering-Time Variation in Brachypodium distachyon
DOE Office of Scientific and Technical Information (OSTI.GOV)
Woods, Daniel P.; Bednarek, Ryland; Bouché, Frédéric
The transition to reproductive development is a crucial step in the plant life cycle, and the timing of this transition is an important factor in crop yields. Here, we report new insights into the genetic control of natural variation in flowering time in Brachypodium distachyon, a nondomesticated pooid grass closely related to cereals such as wheat (Triticum spp.) and barley (Hordeum vulgare L.). A recombinant inbred line population derived from a cross between the rapid-flowering accession Bd21 and the delayed-flowering accession Bd1-1 were grown in a variety of environmental conditions to enable exploration of the genetic architecture of flowering time.more » A genotyping-by-sequencing approach was used to develop SNP markers for genetic map construction, and quantitative trait loci (QTLs) that control differences in flowering time were identified. Many of the flowering-time QTLs are detected across a range of photoperiod and vernalization conditions, suggesting that the genetic control of flowering within this population is robust. The two major QTLs identified in undomesticated B. distachyon colocalize with VERNALIZATION1/PHYTOCHROME C and VERNALIZATION2, loci identified as flowering regulators in the domesticated crops wheat and barley. This suggests that variation in flowering time is controlled in part by a set of genes broadly conserved within pooid grasses.« less
Genetic Architecture of Flowering-Time Variation in Brachypodium distachyon
Woods, Daniel P.; Bednarek, Ryland; Bouché, Frédéric; ...
2016-10-14
The transition to reproductive development is a crucial step in the plant life cycle, and the timing of this transition is an important factor in crop yields. Here, we report new insights into the genetic control of natural variation in flowering time in Brachypodium distachyon, a nondomesticated pooid grass closely related to cereals such as wheat (Triticum spp.) and barley (Hordeum vulgare L.). A recombinant inbred line population derived from a cross between the rapid-flowering accession Bd21 and the delayed-flowering accession Bd1-1 were grown in a variety of environmental conditions to enable exploration of the genetic architecture of flowering time.more » A genotyping-by-sequencing approach was used to develop SNP markers for genetic map construction, and quantitative trait loci (QTLs) that control differences in flowering time were identified. Many of the flowering-time QTLs are detected across a range of photoperiod and vernalization conditions, suggesting that the genetic control of flowering within this population is robust. The two major QTLs identified in undomesticated B. distachyon colocalize with VERNALIZATION1/PHYTOCHROME C and VERNALIZATION2, loci identified as flowering regulators in the domesticated crops wheat and barley. This suggests that variation in flowering time is controlled in part by a set of genes broadly conserved within pooid grasses.« less
The genetic architecture of economic and political preferences.
Benjamin, Daniel J; Cesarini, David; van der Loos, Matthijs J H M; Dawes, Christopher T; Koellinger, Philipp D; Magnusson, Patrik K E; Chabris, Christopher F; Conley, Dalton; Laibson, David; Johannesson, Magnus; Visscher, Peter M
2012-05-22
Preferences are fundamental building blocks in all models of economic and political behavior. We study a new sample of comprehensively genotyped subjects with data on economic and political preferences and educational attainment. We use dense single nucleotide polymorphism (SNP) data to estimate the proportion of variation in these traits explained by common SNPs and to conduct genome-wide association study (GWAS) and prediction analyses. The pattern of results is consistent with findings for other complex traits. First, the estimated fraction of phenotypic variation that could, in principle, be explained by dense SNP arrays is around one-half of the narrow heritability estimated using twin and family samples. The molecular-genetic-based heritability estimates, therefore, partially corroborate evidence of significant heritability from behavior genetic studies. Second, our analyses suggest that these traits have a polygenic architecture, with the heritable variation explained by many genes with small effects. Our results suggest that most published genetic association studies with economic and political traits are dramatically underpowered, which implies a high false discovery rate. These results convey a cautionary message for whether, how, and how soon molecular genetic data can contribute to, and potentially transform, research in social science. We propose some constructive responses to the inferential challenges posed by the small explanatory power of individual SNPs.
Harder, Lawrence D.; Prusinkiewicz, Przemyslaw
2013-01-01
Background Most angiosperms present flowers in inflorescences, which play roles in reproduction, primarily related to pollination, beyond those served by individual flowers alone. An inflorescence's overall reproductive contribution depends primarily on the three-dimensional arrangement of the floral canopy and its dynamics during its flowering period. These features depend in turn on characteristics of the underlying branching structure (scaffold) that supports and supplies water and nutrients to the floral canopy. This scaffold is produced by developmental algorithms that are genetically specified and hormonally mediated. Thus, the extensive inflorescence diversity evident among angiosperms evolves through changes in the developmental programmes that specify scaffold characteristics, which in turn modify canopy features that promote reproductive performance in a particular pollination and mating environment. Nevertheless, developmental and ecological aspects of inflorescences have typically been studied independently, limiting comprehensive understanding of the relations between inflorescence form, reproductive function, and evolution. Scope This review fosters an integrated perspective on inflorescences by summarizing aspects of their development and pollination function that enable and guide inflorescence evolution and diversification. Conclusions The architecture of flowering inflorescences comprises three related components: topology (branching patterns, flower number), geometry (phyllotaxis, internode and pedicel lengths, three-dimensional flower arrangement) and phenology (flower opening rate and longevity, dichogamy). Genetic and developmental evidence reveals that these components are largely subject to quantitative control. Consequently, inflorescence evolution proceeds along a multidimensional continuum. Nevertheless, some combinations of topology, geometry and phenology are represented more commonly than others, because they serve reproductive function particularly effectively. For wind-pollinated species, these combinations often represent compromise solutions to the conflicting physical influences on pollen removal, transport and deposition. For animal-pollinated species, dominant selective influences include the conflicting benefits of large displays for attracting pollinators and of small displays for limiting among-flower self-pollination. The variety of architectural components that comprise inflorescences enable diverse resolutions of these conflicts. PMID:23243190
Vinod; Naik, Bhojaraja K.; Chand, Suresh; Deshmukh, Rupesh; Mallick, Niharika; Singh, Sanjay; Singh, Nagendra Kumar; Tomar, S. M. S.
2016-01-01
Water availability is a major limiting factor for wheat (Triticum aestivum L.) production in rain-fed agricultural systems worldwide. Root architecture is important for water and nutrition acquisition for all crops, including wheat. A set of 158 diverse wheat genotypes of Australian (72) and Indian (86) origin were studied for morpho-agronomical traits in field under irrigated and drought stress conditions during 2010–11 and 2011-12.Out of these 31 Indian wheat genotypes comprising 28 hexaploid (Triticum aestivum L.) and 3 tetraploid (T. durum) were characterized for root traits at reproductive stage in polyvinyl chloride (PVC) pipes. Roots of drought tolerant genotypes grew upto137cm (C306) as compared to sensitive one of 63cm with a mean value of 94.8cm. Root architecture traits of four drought tolerant (C306, HW2004, HD2888 and NI5439) and drought sensitive (HD2877, HD2012, HD2851 and MACS2496) genotypes were also observed at 6 and 9 days old seedling stage. The genotypes did not show any significant variation for root traits except for longer coleoptiles and shoot and higher absorptive surface area in drought tolerant genotypes. The visible evaluation of root images using WinRhizo Tron root scanner of drought tolerant genotype HW2004 indicated compact root system with longer depth while drought sensitive genotype HD2877 exhibited higher horizontal root spread and less depth at reproductive stage. Thirty SSR markers were used to study genetic variation which ranged from 0.12 to 0.77 with an average value of 0.57. The genotypes were categorized into three subgroups as highly tolerant, sensitive, moderately sensitive and tolerant as intermediate group based on UPGMA cluster, STRUCTURE and principal coordinate analyses. The genotypic clustering was positively correlated to grouping based on root and morpho-agronomical traits. The genetic variability identified in current study demonstrated these traits can be used to improve drought tolerance and association mapping. PMID:27280445
Genetic architecture of a hormonal response to gene knockdown in honey bees.
Ihle, Kate E; Rueppell, Olav; Huang, Zachary Y; Wang, Ying; Fondrk, M Kim; Page, Robert E; Amdam, Gro V
2015-01-01
Variation in endocrine signaling is proposed to underlie the evolution and regulation of social life histories, but the genetic architecture of endocrine signaling is still poorly understood. An excellent example of a hormonally influenced set of social traits is found in the honey bee (Apis mellifera): a dynamic and mutually suppressive relationship between juvenile hormone (JH) and the yolk precursor protein vitellogenin (Vg) regulates behavioral maturation and foraging of workers. Several other traits cosegregate with these behavioral phenotypes, comprising the pollen hoarding syndrome (PHS) one of the best-described animal behavioral syndromes. Genotype differences in responsiveness of JH to Vg are a potential mechanistic basis for the PHS. Here, we reduced Vg expression via RNA interference in progeny from a backcross between 2 selected lines of honey bees that differ in JH responsiveness to Vg reduction and measured JH response and ovary size, which represents another key aspect of the PHS. Genetic mapping based on restriction site-associated DNA tag sequencing identified suggestive quantitative trait loci (QTL) for ovary size and JH responsiveness. We confirmed genetic effects on both traits near many QTL that had been identified previously for their effect on various PHS traits. Thus, our results support a role for endocrine control of complex traits at a genetic level. Furthermore, this first example of a genetic map of a hormonal response to gene knockdown in a social insect helps to refine the genetic understanding of complex behaviors and the physiology that may underlie behavioral control in general. © The American Genetic Association. 2015.
QTL mapping for sexually dimorphic fitness-related traits in wild bighorn sheep
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
Muller, Martha; Obert, Caroline; Burnham, Corinna; Mann, Beth; Li, Yimei; Hayden, Randall T; Pestina, Tamara; Persons, Derek; Camilli, Andrew
2014-01-01
Summary Sickle cell disease (SCD) patients are at high risk of contracting pneumococcal infection. To address this risk, they receive pneumococcal vaccines, and antibiotic prophylaxis and treatment. To assess the impact of SCD and these interventions on pneumococcal genetic architecture, we examined the genomes of over 300 pneumococcal isolates from SCD patients over 20 years. Modern SCD strains retained invasive capacity but shifted away from the serotypes used in vaccines. These strains had specific genetic changes related to antibiotic resistance, capsule biosynthesis, metabolism and metal transport. A murine SCD model coupled with Tn-seq mutagenesis identified 60 non-capsular pneumococcal genes under differential selective pressure in SCD, which correlated with aspects of SCD pathophysiology. Further, virulence determinants in the SCD context were distinct from the general population and protective capacity of potential antigens was lost over time in SCD. This highlights the importance of understanding bacterial pathogenesis in the context of high-risk individuals. PMID:24832453
Efficient Bayesian mixed model analysis increases association power in large cohorts
Loh, Po-Ru; Tucker, George; Bulik-Sullivan, Brendan K; Vilhjálmsson, Bjarni J; Finucane, Hilary K; Salem, Rany M; Chasman, Daniel I; Ridker, Paul M; Neale, Benjamin M; Berger, Bonnie; Patterson, Nick; Price, Alkes L
2014-01-01
Linear mixed models are a powerful statistical tool for identifying genetic associations and avoiding confounding. However, existing methods are computationally intractable in large cohorts, and may not optimize power. All existing methods require time cost O(MN2) (where N = #samples and M = #SNPs) and implicitly assume an infinitesimal genetic architecture in which effect sizes are normally distributed, which can limit power. Here, we present a far more efficient mixed model association method, BOLT-LMM, which requires only a small number of O(MN)-time iterations and increases power by modeling more realistic, non-infinitesimal genetic architectures via a Bayesian mixture prior on marker effect sizes. We applied BOLT-LMM to nine quantitative traits in 23,294 samples from the Women’s Genome Health Study (WGHS) and observed significant increases in power, consistent with simulations. Theory and simulations show that the boost in power increases with cohort size, making BOLT-LMM appealing for GWAS in large cohorts. PMID:25642633
Lin, J. Z.; Ritland, K.
1997-01-01
Theoretical predictions about the evolution of selfing depend on the genetic architecture of loci controlling selfing (monogenic vs. polygenic determination, large vs. small effect of alleles, dominance vs. recessiveness), and studies of such architecture are lacking. We inferred the genetic basis of mating system differences between the outbreeding Mimulus guttatus and the inbreeding M. platycalyx by quantitative trait locus (QTL) mapping using random amplified polymorphic DNA and isozyme markers. One to three QTL were detected for each of five mating system characters, and each QTL explained 7.6-28.6% of the phenotypic variance. Taken together, QTL accounted for up to 38% of the variation in mating system characters, and a large proportion of variation was unaccounted for. Inferred QTL often affected more than one trait, contributing to the genetic correlation between those traits. These results are consistent with the hypothesis that quantitative variation in plant mating system characters is primarily controlled by loci with small effect. PMID:9215912
Zaitlen, Noah A.; Ye, Chun Jimmie; Witte, John S.
2016-01-01
The role of rare alleles in complex phenotypes has been hotly debated, but most rare variant association tests (RVATs) do not account for the evolutionary forces that affect genetic architecture. Here, we use simulation and numerical algorithms to show that explosive population growth, as experienced by human populations, can dramatically increase the impact of very rare alleles on trait variance. We then assess the ability of RVATs to detect causal loci using simulations and human RNA-seq data. Surprisingly, we find that statistical performance is worst for phenotypes in which genetic variance is due mainly to rare alleles, and explosive population growth decreases power. Although many studies have attempted to identify causal rare variants, few have reported novel associations. This has sometimes been interpreted to mean that rare variants make negligible contributions to complex trait heritability. Our work shows that RVATs are not robust to realistic human evolutionary forces, so general conclusions about the impact of rare variants on complex traits may be premature. PMID:27197206
Most genetic risk for autism resides with common variation
Gaugler, Trent; Klei, Lambertus; Sanders, Stephan J.; Bodea, Corneliu A.; Goldberg, Arthur P.; Lee, Ann B.; Mahajan, Milind; Manaa, Dina; Pawitan, Yudi; Reichert, Jennifer; Ripke, Stephan; Sandin, Sven; Sklar, Pamela; Svantesson, Oscar; Reichenberg, Abraham; Hultman, Christina M.; Devlin, Bernie
2014-01-01
A key component of genetic architecture is the allelic spectrum influencing trait variability. For autism spectrum disorder (henceforth autism) the nature of its allelic spectrum is uncertain. Individual risk genes have been identified from rare variation, especially de novo mutations1–8. From this evidence one might conclude that rare variation dominates its allelic spectrum, yet recent studies show that common variation, individually of small effect, has substantial impact en masse9,10. At issue is how much of an impact relative to rare variation. Using a unique epidemiological sample from Sweden, novel methods that distinguish total narrow-sense heritability from that due to common variation, and by synthesizing results from other studies, we reach several conclusions about autism’s genetic architecture: its narrow-sense heritability is ≈54% and most traces to common variation; rare de novo mutations contribute substantially to individuals’ liability; still their contribution to variance in liability, 2.6%, is modest compared to heritable variation. PMID:25038753
Signatures of negative selection in the genetic architecture of human complex traits.
Zeng, Jian; de Vlaming, Ronald; Wu, Yang; Robinson, Matthew R; Lloyd-Jones, Luke R; Yengo, Loic; Yap, Chloe X; Xue, Angli; Sidorenko, Julia; McRae, Allan F; Powell, Joseph E; Montgomery, Grant W; Metspalu, Andres; Esko, Tonu; Gibson, Greg; Wray, Naomi R; Visscher, Peter M; Yang, Jian
2018-05-01
We develop a Bayesian mixed linear model that simultaneously estimates single-nucleotide polymorphism (SNP)-based heritability, polygenicity (proportion of SNPs with nonzero effects), and the relationship between SNP effect size and minor allele frequency for complex traits in conventionally unrelated individuals using genome-wide SNP data. We apply the method to 28 complex traits in the UK Biobank data (N = 126,752) and show that on average, 6% of SNPs have nonzero effects, which in total explain 22% of phenotypic variance. We detect significant (P < 0.05/28) signatures of natural selection in the genetic architecture of 23 traits, including reproductive, cardiovascular, and anthropometric traits, as well as educational attainment. The significant estimates of the relationship between effect size and minor allele frequency in complex traits are consistent with a model of negative (or purifying) selection, as confirmed by forward simulation. We conclude that negative selection acts pervasively on the genetic variants associated with human complex traits.
Most genetic risk for autism resides with common variation.
Gaugler, Trent; Klei, Lambertus; Sanders, Stephan J; Bodea, Corneliu A; Goldberg, Arthur P; Lee, Ann B; Mahajan, Milind; Manaa, Dina; Pawitan, Yudi; Reichert, Jennifer; Ripke, Stephan; Sandin, Sven; Sklar, Pamela; Svantesson, Oscar; Reichenberg, Abraham; Hultman, Christina M; Devlin, Bernie; Roeder, Kathryn; Buxbaum, Joseph D
2014-08-01
A key component of genetic architecture is the allelic spectrum influencing trait variability. For autism spectrum disorder (herein termed autism), the nature of the allelic spectrum is uncertain. Individual risk-associated genes have been identified from rare variation, especially de novo mutations. From this evidence, one might conclude that rare variation dominates the allelic spectrum in autism, yet recent studies show that common variation, individually of small effect, has substantial impact en masse. At issue is how much of an impact relative to rare variation this common variation has. Using a unique epidemiological sample from Sweden, new methods that distinguish total narrow-sense heritability from that due to common variation and synthesis of results from other studies, we reach several conclusions about autism's genetic architecture: its narrow-sense heritability is ∼52.4%, with most due to common variation, and rare de novo mutations contribute substantially to individual liability, yet their contribution to variance in liability, 2.6%, is modest compared to that for heritable variation.
Structural Genomics: Correlation Blocks, Population Structure, and Genome Architecture
Hu, Xin-Sheng; Yeh, Francis C.; Wang, Zhiquan
2011-01-01
An integration of the pattern of genome-wide inter-site associations with evolutionary forces is important for gaining insights into the genomic evolution in natural or artificial populations. Here, we assess the inter-site correlation blocks and their distributions along chromosomes. A correlation block is broadly termed as the DNA segment within which strong correlations exist between genetic diversities at any two sites. We bring together the population genetic structure and the genomic diversity structure that have been independently built on different scales and synthesize the existing theories and methods for characterizing genomic structure at the population level. We discuss how population structure could shape correlation blocks and their patterns within and between populations. Effects of evolutionary forces (selection, migration, genetic drift, and mutation) on the pattern of genome-wide correlation blocks are discussed. In eukaryote organisms, we briefly discuss the associations between the pattern of correlation blocks and genome assembly features in eukaryote organisms, including the impacts of multigene family, the perturbation of transposable elements, and the repetitive nongenic sequences and GC-rich isochores. Our reviews suggest that the observable pattern of correlation blocks can refine our understanding of the ecological and evolutionary processes underlying the genomic evolution at the population level. PMID:21886455
Vontimitta, Vijay; Olukolu, Bode A; Penning, Bryan W; Johal, Gurmukh; Balint-Kurti, P J
2015-11-01
In this paper, we determine the genetic architecture controlling leaf flecking in maize and investigate its relationship to disease resistance and the defense response. Flecking is defined as a mild, often environmentally dependent lesion phenotype observed on the leaves of several commonly used maize inbred lines. Anecdotal evidence suggests a link between flecking and enhanced broad-spectrum disease resistance. Neither the genetic basis underlying flecking nor its possible relationship to disease resistance has been systematically evaluated. The commonly used maize inbred Mo17 has a mild flecking phenotype. The IBM-advanced intercross mapping population, derived from a cross between Mo17 and another commonly used inbred B73, has been used for mapping a number of traits in maize including several related to disease resistance. In this study, flecking was assessed in the IBM population over 6 environments. Several quantitative trait loci for flecking were identified, with the strongest one located on chromosome 6. Low but moderately significant correlations were observed between stronger flecking and higher disease resistance with respect to two diseases, southern leaf blight and northern leaf blight and between stronger flecking and a stronger defense response.
Metabolite profiling and quantitative genetics of natural variation for flavonoids in Arabidopsis
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
Co-evolution of Mycobacterium tuberculosis and Homo sapiens
Brites, Daniela; Gagneux, Sebastien
2015-01-01
The causative agent of human tuberculosis (TB), Mycobacterium tuberculosis, is an obligate pathogen that evolved to exclusively persist in human populations. For M. tuberculosis to transmit from person to person, it has to cause pulmonary disease. Therefore, M. tuberculosis virulence has likely been a significant determinant of the association between M. tuberculosis and humans. Indeed, the evolutionary success of some M. tuberculosis genotypes seems at least partially attributable to their increased virulence. The latter possibly evolved as a consequence of human demographic expansions. If co-evolution occurred, humans would have counteracted to minimize the deleterious effects of M. tuberculosis virulence. The fact that human resistance to infection has a strong genetic basis is a likely consequence of such a counter-response. The genetic architecture underlying human resistance to M. tuberculosis remains largely elusive. However, interactions between human genetic polymorphisms and M. tuberculosis genotypes have been reported. Such interactions are consistent with local adaptation and allow for a better understanding of protective immunity in TB. Future ‘genome-to-genome’ studies, in which locally associated human and M. tuberculosis genotypes are interrogated in conjunction, will help identify new protective antigens for the development of better TB vaccines. PMID:25703549
DRO1 influences root system architecture in Arabidopsis and Prunus species.
Guseman, Jessica M; Webb, Kevin; Srinivasan, Chinnathambi; Dardick, Chris
2017-03-01
Roots provide essential uptake of water and nutrients from the soil, as well as anchorage and stability for the whole plant. Root orientation, or angle, is an important component of the overall architecture and depth of the root system; however, little is known about the genetic control of this trait. Recent reports in Oryza sativa (rice) identified a role for DEEPER ROOTING 1 (DRO1) in influencing the orientation of the root system, leading to positive changes in grain yields under water-limited conditions. Here we found that DRO1 and DRO1-related genes are present across diverse plant phyla, and fall within the IGT gene family. The IGT family also includes TAC1 and LAZY1, which are known to affect the orientation of lateral shoots. Consistent with a potential role in root development, DRO1 homologs in Arabidopsis and peach showed root-specific expression. Promoter-reporter constructs revealed that AtDRO1 is predominantly expressed in both the root vasculature and root tips, in a distinct developmental pattern. Mutation of AtDRO1 led to more horizontal lateral root angles. Overexpression of AtDRO1 under a constitutive promoter resulted in steeper lateral root angles, as well as shoot phenotypes including upward leaf curling, shortened siliques and narrow lateral branch angles. A conserved C-terminal EAR-like motif found in IGT genes was required for these ectopic phenotypes. Overexpression of PpeDRO1 in Prunus domestica (plum) led to deeper-rooting phenotypes. Collectively, these data indicate a potential application for DRO1-related genes to alter root architecture for drought avoidance and improved resource use. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.
Broekgaarden, Colette; Bucher, Johan; Bac-Molenaar, Johanna; Keurentjes, Joost J. B.; Kruijer, Willem; Voorrips, Roeland E.; Vosman, Ben
2015-01-01
Plants have evolved a variety of ways to defend themselves against biotic attackers. This has resulted in the presence of substantial variation in defense mechanisms among plants, even within a species. Genome-wide association (GWA) mapping is a useful tool to study the genetic architecture of traits, but has so far only had limited exploitation in studies of plant defense. Here, we study the genetic architecture of defense against the phloem-feeding insect cabbage whitefly (Aleyrodes proletella) in Arabidopsis thaliana. We determined whitefly performance, i.e. the survival and reproduction of whitefly females, on 360 worldwide selected natural accessions and subsequently performed GWA mapping using 214,051 SNPs. Substantial variation for whitefly adult survival and oviposition rate (number of eggs laid per female per day) was observed between the accessions. We identified 39 candidate SNPs for either whitefly adult survival or oviposition rate, all with relatively small effects, underpinning the complex architecture of defense traits. Among the corresponding candidate genes, i.e. genes in linkage disequilibrium (LD) with candidate SNPs, none have previously been identified as a gene playing a role in the interaction between plants and phloem-feeding insects. Whitefly performance on knock-out mutants of a number of candidate genes was significantly affected, validating the potential of GWA mapping for novel gene discovery in plant-insect interactions. Our results show that GWA analysis is a very useful tool to gain insight into the genetic architecture of plant defense against herbivorous insects, i.e. we identified and validated several genes affecting whitefly performance that have not previously been related to plant defense against herbivorous insects. PMID:26699853
2009-01-01
Background The study of biological networks has led to the development of increasingly large and detailed models. Computer tools are essential for the simulation of the dynamical behavior of the networks from the model. However, as the size of the models grows, it becomes infeasible to manually verify the predictions against experimental data or identify interesting features in a large number of simulation traces. Formal verification based on temporal logic and model checking provides promising methods to automate and scale the analysis of the models. However, a framework that tightly integrates modeling and simulation tools with model checkers is currently missing, on both the conceptual and the implementational level. Results We have developed a generic and modular web service, based on a service-oriented architecture, for integrating the modeling and formal verification of genetic regulatory networks. The architecture has been implemented in the context of the qualitative modeling and simulation tool GNA and the model checkers NUSMV and CADP. GNA has been extended with a verification module for the specification and checking of biological properties. The verification module also allows the display and visual inspection of the verification results. Conclusions The practical use of the proposed web service is illustrated by means of a scenario involving the analysis of a qualitative model of the carbon starvation response in E. coli. The service-oriented architecture allows modelers to define the model and proceed with the specification and formal verification of the biological properties by means of a unified graphical user interface. This guarantees a transparent access to formal verification technology for modelers of genetic regulatory networks. PMID:20042075
A test for selection employing quantitative trait locus and mutation accumulation data.
Rice, Daniel P; Townsend, Jeffrey P
2012-04-01
Evolutionary biologists attribute much of the phenotypic diversity observed in nature to the action of natural selection. However, for many phenotypic traits, especially quantitative phenotypic traits, it has been challenging to test for the historical action of selection. An important challenge for biologists studying quantitative traits, therefore, is to distinguish between traits that have evolved under the influence of strong selection and those that have evolved neutrally. Most existing tests for selection employ molecular data, but selection also leaves a mark on the genetic architecture underlying a trait. In particular, the distribution of quantitative trait locus (QTL) effect sizes and the distribution of mutational effects together provide information regarding the history of selection. Despite the increasing availability of QTL and mutation accumulation data, such data have not yet been effectively exploited for this purpose. We present a model of the evolution of QTL and employ it to formulate a test for historical selection. To provide a baseline for neutral evolution of the trait, we estimate the distribution of mutational effects from mutation accumulation experiments. We then apply a maximum-likelihood-based method of inference to estimate the range of selection strengths under which such a distribution of mutations could generate the observed QTL. Our test thus represents the first integration of population genetic theory and QTL data to measure the historical influence of selection.