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

PubMed

Xue, Angli; Wang, Hongcheng; Zhu, Jun

2017-09-28

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

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

PubMed Central

2011-01-01

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

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

PubMed

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

2012-01-01

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

An evolutionary algorithm that constructs recurrent neural networks.

PubMed

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.

Selection and explosive growth alter genetic architecture and hamper the detection of causal rare variants

PubMed Central

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

Genetics of dispersal.

PubMed

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

2018-02-01

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

Genetics of dispersal

PubMed Central

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

2017-01-01

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

The evolution of phenotypic integration: How directional selection reshapes covariation in mice

PubMed Central

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

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 ...

Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases

PubMed Central

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

Genetic Basis of Haloperidol Resistance in Saccharomyces cerevisiae Is Complex and Dose Dependent

PubMed Central

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

How important are rare variants in common disease?

PubMed

Saint Pierre, Aude; Génin, Emmanuelle

2014-09-01

Genome-wide association studies have uncovered hundreds of common genetic variants involved in complex diseases. However, for most complex diseases, these common genetic variants only marginally contribute to disease susceptibility. It is now argued that rare variants located in different genes could in fact play a more important role in disease susceptibility than common variants. These rare genetic variants were not captured by genome-wide association studies using single nucleotide polymorphism-chips but with the advent of next-generation sequencing technologies, they have become detectable. It is now possible to study their contribution to common disease by resequencing samples of cases and controls or by using new genotyping exome arrays that cover rare alleles. In this review, we address the question of the contribution of rare variants in common disease by taking the examples of different diseases for which some resequencing studies have already been performed, and by summarizing the results of simulation studies conducted so far to investigate the genetic architecture of complex traits in human. So far, empirical data have not allowed the exclusion of many models except the most extreme ones involving only a small number of rare variants with large effects contributing to complex disease. To unravel the genetic architecture of complex disease, case-control data will not be sufficient, and alternative study designs need to be proposed together with methodological developments. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Systems genetics approaches to understand complex traits

PubMed Central

Civelek, Mete; Lusis, Aldons J.

2014-01-01

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

Exploring the unknown: assumptions about allelic architecture and strategies for susceptibility variant discovery.

PubMed

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.

Missing heritability and strategies for finding the underlying causes of complex disease

PubMed Central

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

The evolution of phenotypic integration: How directional selection reshapes covariation in mice.

PubMed

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.

Selection and explosive growth alter genetic architecture and hamper the detection of causal rare variants.

PubMed

Uricchio, Lawrence H; Zaitlen, Noah A; Ye, Chun Jimmie; Witte, John S; Hernandez, Ryan D

2016-07-01

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. © 2016 Uricchio et al.; Published by Cold Spring Harbor Laboratory Press.

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

PubMed

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

2018-06-13

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

Multigenic Natural Variation Underlies Caenorhabditis elegans Olfactory Preference for the Bacterial Pathogen Serratia marcescens

PubMed Central

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

Non-Linear Pattern Formation in Bone Growth and Architecture

PubMed Central

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.

PubMed

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.

The genetic architecture of pediatric cognitive abilities in the Philadelphia Neurodevelopmental Cohort

PubMed Central

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

The Architecture of the Pollen Hoarding Syndrome in Honey Bees: Implications for Understanding Social Evolution, Behavioral Syndromes, and Selective Breeding

PubMed Central

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

The Architecture of the Pollen Hoarding Syndrome in Honey Bees: Implications for Understanding Social Evolution, Behavioral Syndromes, and Selective Breeding.

PubMed

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.

The Genetic Architecture of Major Depressive Disorder in Han Chinese Women.

PubMed

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

PubMed Central

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

Genetic control of inflorescence architecture in legumes

PubMed Central

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

PAY1 improves plant architecture and enhances grain yield in rice.

PubMed

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.

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

PubMed

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

2013-10-01

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

The Genetic Architecture of Complex Traits in Teosinte (Zea mays ssp. parviglumis): New Evidence from Association Mapping

USDA-ARS?s Scientific Manuscript database

Our previous association analyses showed that variation at major regulatory genes contributes to standing variation for complex traits in Balsas teosinte, the progenitor of maize. This study expands our previous association mapping effort in teosinte by testing 123 markers in 52 candidate genes for ...

Genome-wide association analyses identify new risk variants and the genetic architecture of amyotrophic lateral sclerosis

PubMed Central

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

ViSEN: methodology and software for visualization of statistical epistasis networks

PubMed Central

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

Outer nuclear membrane protein Kuduk modulates the LINC complex and nuclear envelope architecture

PubMed Central

Ding, Zhao-Ying; Huang, Yu-Cheng; Lee, Myong-Chol; Tseng, Min-Jen; Chi, Ya-Hui

2017-01-01

Linker of nucleoskeleton and cytoskeleton (LINC) complexes spanning the nuclear envelope (NE) contribute to nucleocytoskeletal force transduction. A few NE proteins have been found to regulate the LINC complex. In this study, we identify one, Kuduk (Kud), which can reside at the outer nuclear membrane and is required for the development of Drosophila melanogaster ovarian follicles and NE morphology of myonuclei. Kud associates with LINC complex components in an evolutionarily conserved manner. Loss of Kud increases the level but impairs functioning of the LINC complex. Overexpression of Kud suppresses NE targeting of cytoskeleton-free LINC complexes. Thus, Kud acts as a quality control mechanism for LINC-mediated nucleocytoskeletal connections. Genetic data indicate that Kud also functions independently of the LINC complex. Overexpression of the human orthologue TMEM258 in Drosophila proved functional conservation. These findings expand our understanding of the regulation of LINC complexes and NE architecture. PMID:28716842

Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large-scale genetic studies.

PubMed

Atkinson, Jonathan A; Lobet, Guillaume; Noll, Manuel; Meyer, Patrick E; Griffiths, Marcus; Wells, Darren M

2017-10-01

Genetic analyses of plant root systems require large datasets of extracted architectural traits. To quantify such traits from images of root systems, researchers often have to choose between automated tools (that are prone to error and extract only a limited number of architectural traits) or semi-automated ones (that are highly time consuming). We trained a Random Forest algorithm to infer architectural traits from automatically extracted image descriptors. The training was performed on a subset of the dataset, then applied to its entirety. This strategy allowed us to (i) decrease the image analysis time by 73% and (ii) extract meaningful architectural traits based on image descriptors. We also show that these traits are sufficient to identify the quantitative trait loci that had previously been discovered using a semi-automated method. We have shown that combining semi-automated image analysis with machine learning algorithms has the power to increase the throughput of large-scale root studies. We expect that such an approach will enable the quantification of more complex root systems for genetic studies. We also believe that our approach could be extended to other areas of plant phenotyping. © The Authors 2017. Published by Oxford University Press.

Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large-scale genetic studies

PubMed Central

Atkinson, Jonathan A.; Lobet, Guillaume; Noll, Manuel; Meyer, Patrick E.; Griffiths, Marcus

2017-01-01

Abstract Genetic analyses of plant root systems require large datasets of extracted architectural traits. To quantify such traits from images of root systems, researchers often have to choose between automated tools (that are prone to error and extract only a limited number of architectural traits) or semi-automated ones (that are highly time consuming). We trained a Random Forest algorithm to infer architectural traits from automatically extracted image descriptors. The training was performed on a subset of the dataset, then applied to its entirety. This strategy allowed us to (i) decrease the image analysis time by 73% and (ii) extract meaningful architectural traits based on image descriptors. We also show that these traits are sufficient to identify the quantitative trait loci that had previously been discovered using a semi-automated method. We have shown that combining semi-automated image analysis with machine learning algorithms has the power to increase the throughput of large-scale root studies. We expect that such an approach will enable the quantification of more complex root systems for genetic studies. We also believe that our approach could be extended to other areas of plant phenotyping. PMID:29020748

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

PubMed

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

2008-08-27

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

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2017-08-10

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

A systems approach defining constraints of the genome architecture on lineage selection and evolvability during somatic cancer evolution

PubMed Central

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

Understanding Evolutionary Potential in Virtual CPU Instruction Set Architectures

PubMed Central

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

Environmentally induced changes in correlated responses to selection reveal variable pleiotropy across a complex genetic network.

PubMed

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).

ENVIRONMENTALLY INDUCED CHANGES IN CORRELATED RESPONSES TO SELECTION REVEAL VARIABLE PLEIOTROPY ACROSS A COMPLEX GENETIC NETWORK

PubMed Central

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

Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap.

PubMed

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.

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

PubMed Central

Chen, Guo-Bo

2016-01-01

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

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

PubMed

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

2015-01-01

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

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

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

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

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

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

DOE PAGES

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

2016-08-15

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

GAPIT version 2: an enhanced integrated tool for genomic association and prediction

USDA-ARS?s Scientific Manuscript database

Most human diseases and agriculturally important traits are complex. Dissecting their genetic architecture requires continued development of innovative and powerful statistical methods. Corresponding advances in computing tools are critical to efficiently use these statistical innovations and to enh...

Advancing the understanding of autism disease mechanisms through genetics

PubMed Central

de la Torre-Ubieta, Luis; Won, Hyejung; Stein, Jason L; Geschwind, Daniel H

2016-01-01

Progress in understanding the genetic etiology of autism spectrum disorders (ASD) has fueled remarkable advances in our understanding of its potential neurobiological mechanisms. Yet, at the same time, these findings highlight extraordinary causal diversity and complexity at many levels ranging from molecules to circuits and emphasize the gaps in our current knowledge. Here we review current understanding of the genetic architecture of ASD and integrate genetic evidence, neuropathology and studies in model systems with how they inform mechanistic models of ASD pathophysiology. Despite the challenges, these advances provide a solid foundation for the development of rational, targeted molecular therapies. PMID:27050589

Engineering Promoter Architecture in Oleaginous Yeast Yarrowia lipolytica.

PubMed

Shabbir Hussain, Murtaza; Gambill, Lauren; Smith, Spencer; Blenner, Mark A

2016-03-18

Eukaryotic promoters have a complex architecture to control both the strength and timing of gene transcription spanning up to thousands of bases from the initiation site. This complexity makes rational fine-tuning of promoters in fungi difficult to predict; however, this very same complexity enables multiple possible strategies for engineering promoter strength. Here, we studied promoter architecture in the oleaginous yeast, Yarrowia lipolytica. While recent studies have focused on upstream activating sequences, we systematically examined various components common in fungal promoters. Here, we examine several promoter components including upstream activating sequences, proximal promoter sequences, core promoters, and the TATA box in autonomously replicating expression plasmids and integrated into the genome. Our findings show that promoter strength can be fine-tuned through the engineering of the TATA box sequence, core promoter, and upstream activating sequences. Additionally, we identified a previously unreported oleic acid responsive transcription enhancement in the XPR2 upstream activating sequences, which illustrates the complexity of fungal promoters. The promoters engineered here provide new genetic tools for metabolic engineering in Y. lipolytica and provide promoter engineering strategies that may be useful in engineering other non-model fungal systems.

Getting to the roots of it: Genetic and hormonal control of root architecture

PubMed Central

Jung, Janelle K. H.; McCouch, Susan

2013-01-01

Root system architecture (RSA) – the spatial configuration of a root system – is an important developmental and agronomic trait, with implications for overall plant architecture, growth rate and yield, abiotic stress resistance, nutrient uptake, and developmental plasticity in response to environmental changes. Root architecture is modulated by intrinsic, hormone-mediated pathways, intersecting with pathways that perceive and respond to external, environmental signals. The recent development of several non-invasive 2D and 3D root imaging systems has enhanced our ability to accurately observe and quantify architectural traits on complex whole-root systems. Coupled with the powerful marker-based genotyping and sequencing platforms currently available, these root phenotyping technologies lend themselves to large-scale genome-wide association studies, and can speed the identification and characterization of the genes and pathways involved in root system development. This capability provides the foundation for examining the contribution of root architectural traits to the performance of crop varieties in diverse environments. This review focuses on our current understanding of the genes and pathways involved in determining RSA in response to both intrinsic and extrinsic (environmental) response pathways, and provides a brief overview of the latest root system phenotyping technologies and their potential impact on elucidating the genetic control of root development in plants. PMID:23785372

High-Throughput Phenotyping and QTL Mapping Reveals the Genetic Architecture of Maize Plant Growth.

PubMed

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.

High-Throughput Phenotyping and QTL Mapping Reveals the Genetic Architecture of Maize Plant Growth1[OPEN

PubMed Central

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

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

PubMed Central

Weiss, Kenneth M.

2008-01-01

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

Plug-and-Play Multicellular Circuits with Time-Dependent Dynamic Responses.

PubMed

Urrios, Arturo; Gonzalez-Flo, Eva; Canadell, David; de Nadal, Eulàlia; Macia, Javier; Posas, Francesc

2018-04-20

Synthetic biology studies aim to develop cellular devices for biomedical applications. These devices, based on living instead of electronic or electromechanic technology, might provide alternative treatments for a wide range of diseases. However, the feasibility of these devices depends, in many cases, on complex genetic circuits that must fulfill physiological requirements. In this work, we explored the potential of multicellular architectures to act as an alternative to complex circuits for implementation of new devices. As a proof of concept, we developed specific circuits for insulin or glucagon production in response to different glucose levels. Here, we show that fundamental features, such as circuit's affinity or sensitivity, are dependent on the specific configuration of the multicellular consortia, providing a method for tuning these properties without genetic engineering. As an example, we have designed and built circuits with an incoherent feed-forward loop architecture (FFL) that can be easily adjusted to generate single pulse responses. Our results might serve as a blueprint for future development of cellular devices for glycemia regulation in diabetic patients.

A Parallel Trade Study Architecture for Design Optimization of Complex Systems

NASA Technical Reports Server (NTRS)

Kim, Hongman; Mullins, James; Ragon, Scott; Soremekun, Grant; Sobieszczanski-Sobieski, Jaroslaw

2005-01-01

Design of a successful product requires evaluating many design alternatives in a limited design cycle time. This can be achieved through leveraging design space exploration tools and available computing resources on the network. This paper presents a parallel trade study architecture to integrate trade study clients and computing resources on a network using Web services. The parallel trade study solution is demonstrated to accelerate design of experiments, genetic algorithm optimization, and a cost as an independent variable (CAIV) study for a space system application.

Genetic Architecture of Hybrid Male Sterility in Drosophila: Analysis of Intraspecies Variation for Interspecies Isolation

PubMed Central

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

2008-01-01

Background The genetic basis of postzygotic isolation is a central puzzle in evolutionary biology. Evolutionary forces causing hybrid sterility or inviability act on the responsible genes while they still are polymorphic, thus we have to study these traits as they arise, before isolation is complete. Methodology/Principal Findings Isofemale strains of D. mojavensis vary significantly in their production of sterile F1 sons when females are crossed to D. arizonae males. We took advantage of the intraspecific polymorphism, in a novel design, to perform quantitative trait locus (QTL) mapping analyses directly on F1 hybrid male sterility itself. We found that the genetic architecture of the polymorphism for hybrid male sterility (HMS) in the F1 is complex, involving multiple QTL, epistasis, and cytoplasmic effects. Conclusions/Significance The role of extensive intraspecific polymorphism, multiple QTL, and epistatic interactions in HMS in this young species pair shows that HMS is arising as a complex trait in this system. Directional selection alone would be unlikely to maintain polymorphism at multiple loci, thus we hypothesize that directional selection is unlikely to be the only evolutionary force influencing postzygotic isolation. PMID:18728782

Experimental game theory and behavior genetics.

PubMed

Cesarini, David; Dawes, Christopher T; Johannesson, Magnus; Lichtenstein, Paul; Wallace, Björn

2009-06-01

We summarize the findings from a research program studying the heritability of behavior in a number of widely used economic games, including trust, dictator, and ultimatum games. Results from the standard behavior genetic variance decomposition suggest that strategies and fundamental economic preference parameters are moderately heritable, with estimates ranging from 18 to 42%. In addition, we also report new evidence on so-called "hyperfair" preferences in the ultimatum game. We discuss the implications of our findings with special reference to current efforts that seek to understand the molecular genetic architecture of complex social behaviors.

The genetic architecture of novel trophic specialists: larger effect sizes are associated with exceptional oral jaw diversification in a pupfish adaptive radiation.

PubMed

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.

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

PubMed

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

2015-12-01

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

Genetic architecture of wood properties based on association analysis and co-expression networks in white spruce.

PubMed

Lamara, Mebarek; Raherison, Elie; Lenz, Patrick; Beaulieu, Jean; Bousquet, Jean; MacKay, John

2016-04-01

Association studies are widely utilized to analyze complex traits but their ability to disclose genetic architectures is often limited by statistical constraints, and functional insights are usually minimal in nonmodel organisms like forest trees. We developed an approach to integrate association mapping results with co-expression networks. We tested single nucleotide polymorphisms (SNPs) in 2652 candidate genes for statistical associations with wood density, stiffness, microfibril angle and ring width in a population of 1694 white spruce trees (Picea glauca). Associations mapping identified 229-292 genes per wood trait using a statistical significance level of P < 0.05 to maximize discovery. Over-representation of genes associated for nearly all traits was found in a xylem preferential co-expression group developed in independent experiments. A xylem co-expression network was reconstructed with 180 wood associated genes and several known MYB and NAC regulators were identified as network hubs. The network revealed a link between the gene PgNAC8, wood stiffness and microfibril angle, as well as considerable within-season variation for both genetic control of wood traits and gene expression. Trait associations were distributed throughout the network suggesting complex interactions and pleiotropic effects. Our findings indicate that integration of association mapping and co-expression networks enhances our understanding of complex wood traits. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Local Genetic Correlation Gives Insights into the Shared Genetic Architecture of Complex Traits.

PubMed

Shi, Huwenbo; Mancuso, Nicholas; Spendlove, Sarah; Pasaniuc, Bogdan

2017-11-02

Although genetic correlations between complex traits provide valuable insights into epidemiological and etiological studies, a precise quantification of which genomic regions disproportionately contribute to the genome-wide correlation is currently lacking. Here, we introduce ρ-HESS, a technique to quantify the correlation between pairs of traits due to genetic variation at a small region in the genome. Our approach requires GWAS summary data only and makes no distributional assumption on the causal variant effect sizes while accounting for linkage disequilibrium (LD) and overlapping GWAS samples. We analyzed large-scale GWAS summary data across 36 quantitative traits, and identified 25 genomic regions that contribute significantly to the genetic correlation among these traits. Notably, we find 6 genomic regions that contribute to the genetic correlation of 10 pairs of traits that show negligible genome-wide correlation, further showcasing the power of local genetic correlation analyses. Finally, we report the distribution of local genetic correlations across the genome for 55 pairs of traits that show putative causal relationships. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Cortical Folding of the Primate Brain: An Interdisciplinary Examination of the Genetic Architecture, Modularity, and Evolvability of a Significant Neurological Trait in Pedigreed Baboons (Genus Papio)

PubMed Central

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

The Value of Extended Pedigrees for Next-Generation Analysis of Complex Disease in the Rhesus Macaque

PubMed Central

Vinson, Amanda; Prongay, Kamm; Ferguson, Betsy

2013-01-01

Complex diseases (e.g., cardiovascular disease and type 2 diabetes, among many others) pose the biggest threat to human health worldwide and are among the most challenging to investigate. Susceptibility to complex disease may be caused by multiple genetic variants (GVs) and their interaction, by environmental factors, and by interaction between GVs and environment, and large study cohorts with substantial analytical power are typically required to elucidate these individual contributions. Here, we discuss the advantages of both power and feasibility afforded by the use of extended pedigrees of rhesus macaques (Macaca mulatta) for genetic studies of complex human disease based on next-generation sequence data. We present these advantages in the context of previous research conducted in rhesus macaques for several representative complex diseases. We also describe a single, multigeneration pedigree of Indian-origin rhesus macaques and a sample biobank we have developed for genetic analysis of complex disease, including power of this pedigree to detect causal GVs using either genetic linkage or association methods in a variance decomposition approach. Finally, we summarize findings of significant heritability for a number of quantitative traits that demonstrate that genetic contributions to risk factors for complex disease can be detected and measured in this pedigree. We conclude that the development and application of an extended pedigree to analysis of complex disease traits in the rhesus macaque have shown promising early success and that genome-wide genetic and higher order -omics studies in this pedigree are likely to yield useful insights into the architecture of complex human disease. PMID:24174435

Progress of genome wide association study in domestic animals

PubMed Central

2012-01-01

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

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

PubMed Central

2012-01-01

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

Genome complexity, robustness and genetic interactions in digital organisms

NASA Astrophysics Data System (ADS)

Lenski, Richard E.; Ofria, Charles; Collier, Travis C.; Adami, Christoph

1999-08-01

Digital organisms are computer programs that self-replicate, mutate and adapt by natural selection. They offer an opportunity to test generalizations about living systems that may extend beyond the organic life that biologists usually study. Here we have generated two classes of digital organism: simple programs selected solely for rapid replication, and complex programs selected to perform mathematical operations that accelerate replication through a set of defined `metabolic' rewards. To examine the differences in their genetic architecture, we introduced millions of single and multiple mutations into each organism and measured the effects on the organism's fitness. The complex organisms are more robust than the simple ones with respect to the average effects of single mutations. Interactions among mutations are common and usually yield higher fitness than predicted from the component mutations assuming multiplicative effects; such interactions are especially important in the complex organisms. Frequent interactions among mutations have also been seen in bacteria, fungi and fruitflies. Our findings support the view that interactions are a general feature of genetic systems.

Genome complexity, robustness and genetic interactions in digital organisms.

PubMed

Lenski, R E; Ofria, C; Collier, T C; Adami, C

1999-08-12

Digital organisms are computer programs that self-replicate, mutate and adapt by natural selection. They offer an opportunity to test generalizations about living systems that may extend beyond the organic life that biologists usually study. Here we have generated two classes of digital organism: simple programs selected solely for rapid replication, and complex programs selected to perform mathematical operations that accelerate replication through a set of defined 'metabolic' rewards. To examine the differences in their genetic architecture, we introduced millions of single and multiple mutations into each organism and measured the effects on the organism's fitness. The complex organisms are more robust than the simple ones with respect to the average effects of single mutations. Interactions among mutations are common and usually yield higher fitness than predicted from the component mutations assuming multiplicative effects; such interactions are especially important in the complex organisms. Frequent interactions among mutations have also been seen in bacteria, fungi and fruitflies. Our findings support the view that interactions are a general feature of genetic systems.

Network Analysis Reveals Putative Genes Affecting Meat Quality in Angus Cattle.

PubMed

Mateescu, Raluca G; Garrick, Dorian J; Reecy, James M

2017-01-01

Improvements in eating satisfaction will benefit consumers and should increase beef demand which is of interest to the beef industry. Tenderness, juiciness, and flavor are major determinants of the palatability of beef and are often used to reflect eating satisfaction. Carcass qualities are used as indicator traits for meat quality, with higher quality grade carcasses expected to relate to more tender and palatable meat. However, meat quality is a complex concept determined by many component traits making interpretation of genome-wide association studies (GWAS) on any one component challenging to interpret. Recent approaches combining traditional GWAS with gene network interactions theory could be more efficient in dissecting the genetic architecture of complex traits. Phenotypic measures of 23 traits reflecting carcass characteristics, components of meat quality, along with mineral and peptide concentrations were used along with Illumina 54k bovine SNP genotypes to derive an annotated gene network associated with meat quality in 2,110 Angus beef cattle. The efficient mixed model association (EMMAX) approach in combination with a genomic relationship matrix was used to directly estimate the associations between 54k SNP genotypes and each of the 23 component traits. Genomic correlated regions were identified by partial correlations which were further used along with an information theory algorithm to derive gene network clusters. Correlated SNP across 23 component traits were subjected to network scoring and visualization software to identify significant SNP. Significant pathways implicated in the meat quality complex through GO term enrichment analysis included angiogenesis, inflammation, transmembrane transporter activity, and receptor activity. These results suggest that network analysis using partial correlations and annotation of significant SNP can reveal the genetic architecture of complex traits and provide novel information regarding biological mechanisms and genes that lead to complex phenotypes, like meat quality, and the nutritional and healthfulness value of beef. Improvements in genome annotation and knowledge of gene function will contribute to more comprehensive analyses that will advance our ability to dissect the complex architecture of complex traits.

CLONAL EVOLUTION IN CANCER

PubMed Central

Greaves, Mel; Maley, Carlo C.

2012-01-01

Cancers evolve by a reiterative process of clonal expansion, genetic diversification and clonal selection within the adaptive landscapes of tissue ecosystems. The dynamics are complex with highly variable patterns of genetic diversity and resultant clonal architecture. Therapeutic intervention may decimate cancer clones, and erode their habitats, but inadvertently provides potent selective pressure for the expansion of resistant variants. The inherently Darwinian character of cancer lies at the heart of therapeutic failure but perhaps also holds the key to more effective control. PMID:22258609

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...

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

PubMed Central

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

2017-01-01

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

Identification of 64 Novel Genetic Loci Provides an Expanded View on the Genetic Architecture of Coronary Artery Disease.

PubMed

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.

A model for family-based case-control studies of genetic imprinting and epistasis.

PubMed

Li, Xin; Sui, Yihan; Liu, Tian; Wang, Jianxin; Li, Yongci; Lin, Zhenwu; Hegarty, John; Koltun, Walter A; Wang, Zuoheng; Wu, Rongling

2014-11-01

Genetic imprinting, or called the parent-of-origin effect, has been recognized to play an important role in the formation and pathogenesis of human diseases. Although the epigenetic mechanisms that establish genetic imprinting have been a focus of many genetic studies, our knowledge about the number of imprinting genes and their chromosomal locations and interactions with other genes is still scarce, limiting precise inference of the genetic architecture of complex diseases. In this article, we present a statistical model for testing and estimating the effects of genetic imprinting on complex diseases using a commonly used case-control design with family structure. For each subject sampled from a case and control population, we not only genotype its own single nucleotide polymorphisms (SNPs) but also collect its parents' genotypes. By tracing the transmission pattern of SNP alleles from parental to offspring generation, the model allows the characterization of genetic imprinting effects based on Pearson tests of a 2 × 2 contingency table. The model is expanded to test the interactions between imprinting effects and additive, dominant and epistatic effects in a complex web of genetic interactions. Statistical properties of the model are investigated, and its practical usefulness is validated by a real data analysis. The model will provide a useful tool for genome-wide association studies aimed to elucidate the picture of genetic control over complex human diseases. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

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

PubMed Central

Lorenz, Kim; Cohen, Barak A.

2012-01-01

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

ERECTA signaling controls Arabidopsis inflorescence architecture through chromatin-mediated activation of PRE1 expression.

PubMed

Cai, Hanyang; Zhao, Lihua; Wang, Lulu; Zhang, Man; Su, Zhenxia; Cheng, Yan; Zhao, Heming; Qin, Yuan

2017-06-01

Flowering plants display a remarkable diversity in inflorescence architecture, and pedicel length is one of the key contributors to this diversity. In Arabidopsis thaliana, the receptor-like kinase ERECTA (ER) mediated signaling pathway plays important roles in regulating inflorescence architecture by promoting cell proliferation. However, the regulating mechanism remains elusive in the pedicel. Genetic interactions between ERECTA signaling and the chromatin remodeling complex SWR1 in the control of inflorescence architecture were studied. Comparative transcriptome analysis was applied to identify downstream components. Chromatin immunoprecipitation and nucleosome occupancy was further investigated. The results indicated that the chromatin remodeler SWR1 coordinates with ERECTA signaling in regulating inflorescence architecture by activating the expression of PRE1 family genes and promoting pedicel elongation. It was found that SWR1 is required for the incorporation of the H2A.Z histone variant into nucleosomes of the whole PRE1 gene family and the ERECTA controlled expression of PRE1 gene family through regulating nucleosome dynamics. We propose that utilization of a chromatin remodeling complex to regulate gene expression is a common theme in developmental control across kingdoms. These findings shed light on the mechanisms through which chromatin remodelers orchestrate complex transcriptional regulation of gene expression in coordination with a developmental cue. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Genomic architecture of adaptive color pattern divergence and convergence in Heliconius butterflies

PubMed Central

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

To Your Health: NLM update transcript - Genetic architecture of mental disorders

MedlinePlus

... 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 ...

The Genetic Architecture of a Complex Ecological Trait: Host Plant Use in the Specialist Moth, Heliothis subflexa

PubMed Central

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

Genetic architecture of adiposity and organ weight using combined generation QTL analysis.

PubMed

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.

Genetic architectures of seropositive and seronegative rheumatic diseases.

PubMed

Kirino, Yohei; Remmers, Elaine F

2015-07-01

Rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis and some other rheumatic diseases are genetically complex, with evidence of familial clustering, but not of Mendelian inheritance. These diseases are thought to result from contributions and interactions of multiple genetic and nongenetic risk factors, which have small effects individually. Genome-wide association studies (GWAS) of large collections of data from cases and controls have revealed many genetic factors that contribute to non-Mendelian rheumatic diseases, thus providing insights into associated molecular mechanisms. This Review summarizes methods for the identification of gene variants that influence genetically complex diseases and focuses on what we have learned about the rheumatic diseases for which GWAS have been reported. Our review of the disease-associated loci identified to date reveals greater sharing of risk loci among the groups of seropositive (diseases in which specific autoantibodies are often present) or seronegative diseases than between these two groups. The nature of the shared and discordant loci suggests important similarities and differences among these diseases.

Genetic and Environmental Architecture of Changes in Episodic Memory from Middle to Late Middle Age

PubMed Central

Panizzon, Matthew S.; Neale, Michael C.; Docherty, Anna R.; Franz, Carol E.; Jacobson, Kristen C.; Toomey, Rosemary; Xian, Hong; Vasilopoulos, Terrie; Rana, Brinda K.; McKenzie, Ruth M.; Lyons, Michael J.; Kremen, William S.

2015-01-01

Episodic memory is a complex construct at both the phenotypic and genetic level. Ample evidence supports age-related cognitive stability and change being accounted for by general and domain-specific factors. We hypothesized that general and specific factors would underlie change even within this single cognitive domain. We examined six measures from three episodic memory tests in a narrow age cohort at middle and late middle age. The factor structure was invariant across occasions. At both timepoints two of three test-specific factors (story recall, design recall) had significant genetic influences independent of the general memory factor. Phenotypic stability was moderate to high, and primarily accounted for by genetic influences, except for one test-specific factor (list learning). Mean change over time was nonsignificant for one test-level factor; one declined; one improved. The results highlight the phenotypic and genetic complexity of memory and memory change, and shed light on an understudied period of life. PMID:25938244

Genetic and environmental architecture of changes in episodic memory from middle to late middle age.

PubMed

Panizzon, Matthew S; Neale, Michael C; Docherty, Anna R; Franz, Carol E; Jacobson, Kristen C; Toomey, Rosemary; Xian, Hong; Vasilopoulos, Terrie; Rana, Brinda K; McKenzie, Ruth; Lyons, Michael J; Kremen, William S

2015-06-01

Episodic memory is a complex construct at both the phenotypic and genetic level. Ample evidence supports age-related cognitive stability and change being accounted for by general and domain-specific factors. We hypothesized that general and specific factors would underlie change even within this single cognitive domain. We examined 6 measures from 3 episodic memory tests in a narrow age cohort at middle and late middle age. The factor structure was invariant across occasions. At both timepoints 2 of 3 test-specific factors (story recall, design recall) had significant genetic influences independent of the general memory factor. Phenotypic stability was moderate to high, and primarily accounted for by genetic influences, except for 1 test-specific factor (list learning). Mean change over time was nonsignificant for 1 test-level factor; 1 declined; 1 improved. The results highlight the phenotypic and genetic complexity of memory and memory change, and shed light on an understudied period of life. (c) 2015 APA, all rights reserved.

Complex genetic diseases: controversy over the Croesus code.

PubMed

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).

Sex-dependent expression of behavioural genetic architectures and the evolution of sexual dimorphism.

PubMed

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).

Insights into the genetics of gastroesophageal reflux disease (GERD) and GERD-related disorders.

PubMed

Böhmer, A C; Schumacher, J

2017-02-01

Gastroesophageal reflux disease (GERD) is associated with obesity and hiatal hernia, and often precedes the development of Barrett's esophagus (BE) and esophageal adenocarcinoma (EA). Epidemiological studies show that the global prevalence of GERD is increasing. GERD is a multifactorial disease with a complex genetic architecture. Genome-wide association studies (GWAS) have provided initial insights into the genetic background of GERD. The present review summarizes current knowledge of the genetics of GERD and a possible genetic overlap between GERD and BE and EA. The review discusses genes and cellular pathways that have been implicated through GWAS, and provides an outlook on how future molecular research will enhance understanding of GERD pathophysiology. © 2017 John Wiley & Sons Ltd.

The Genetic Basis of Upland/Lowland Ecotype Divergence in Switchgrass (Panicum virgatum)

PubMed Central

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

Dendritic Cytoskeletal Architecture Is Modulated by Combinatorial Transcriptional Regulation in Drosophila melanogaster.

PubMed

Das, Ravi; Bhattacharjee, Shatabdi; Patel, Atit A; Harris, Jenna M; Bhattacharya, Surajit; Letcher, Jamin M; Clark, Sarah G; Nanda, Sumit; Iyer, Eswar Prasad R; Ascoli, Giorgio A; Cox, Daniel N

2017-12-01

Transcription factors (TFs) have emerged as essential cell autonomous mediators of subtype specific dendritogenesis; however, the downstream effectors of these TFs remain largely unknown, as are the cellular events that TFs control to direct morphological change. As dendritic morphology is largely dictated by the organization of the actin and microtubule (MT) cytoskeletons, elucidating TF-mediated cytoskeletal regulatory programs is key to understanding molecular control of diverse dendritic morphologies. Previous studies in Drosophila melanogaster have demonstrated that the conserved TFs Cut and Knot exert combinatorial control over aspects of dendritic cytoskeleton development, promoting actin and MT-based arbor morphology, respectively. To investigate transcriptional targets of Cut and/or Knot regulation, we conducted systematic neurogenomic studies, coupled with in vivo genetic screens utilizing multi-fluor cytoskeletal and membrane marker reporters. These analyses identified a host of putative Cut and/or Knot effector molecules, and a subset of these putative TF targets converge on modulating dendritic cytoskeletal architecture, which are grouped into three major phenotypic categories, based upon neuromorphometric analyses: complexity enhancer, complexity shifter, and complexity suppressor. Complexity enhancer genes normally function to promote higher order dendritic growth and branching with variable effects on MT stabilization and F-actin organization, whereas complexity shifter and complexity suppressor genes normally function in regulating proximal-distal branching distribution or in restricting higher order branching complexity, respectively, with spatially restricted impacts on the dendritic cytoskeleton. Collectively, we implicate novel genes and cellular programs by which TFs distinctly and combinatorially govern dendritogenesis via cytoskeletal modulation. Copyright © 2017 by the Genetics Society of America.

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

PubMed Central

Monir, Md. Mamun; Zhu, Jun

2017-01-01

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

Inference of the genetic architecture underlying BMI and height with the use of 20,240 sibling pairs.

PubMed

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.

Differential Regulation of Cryptic Genetic Variation Shapes the Genetic Interactome Underlying Complex Traits.

PubMed

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.

Differential Regulation of Cryptic Genetic Variation Shapes the Genetic Interactome Underlying Complex Traits

PubMed Central

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

Strategy Revealing Phenotypic Differences among Synthetic Oscillator Designs

PubMed Central

2015-01-01

Considerable progress has been made in identifying and characterizing the component parts of genetic oscillators, which play central roles in all organisms. Nonlinear interaction among components is sufficiently complex that mathematical models are required to elucidate their elusive integrated behavior. Although natural and synthetic oscillators exhibit common architectures, there are numerous differences that are poorly understood. Utilizing synthetic biology to uncover basic principles of simpler circuits is a way to advance understanding of natural circadian clocks and rhythms. Following this strategy, we address the following questions: What are the implications of different architectures and molecular modes of transcriptional control for the phenotypic repertoire of genetic oscillators? Are there designs that are more realizable or robust? We compare synthetic oscillators involving one of three architectures and various combinations of the two modes of transcriptional control using a methodology that provides three innovations: a rigorous definition of phenotype, a procedure for deconstructing complex systems into qualitatively distinct phenotypes, and a graphical representation for illuminating the relationship between genotype, environment, and the qualitatively distinct phenotypes of a system. These methods provide a global perspective on the behavioral repertoire, facilitate comparisons of alternatives, and assist the rational design of synthetic gene circuitry. In particular, the results of their application here reveal distinctive phenotypes for several designs that have been studied experimentally as well as a best design among the alternatives that has yet to be constructed and tested. PMID:25019938

Predicting the difficulty of pure, strict, epistatic models: metrics for simulated model selection.

PubMed

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.

Parametric and Nonparametric Statistical Methods for Genomic Selection of Traits with Additive and Epistatic Genetic Architectures

PubMed Central

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

PubMed

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

2017-01-01

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

The Molecular Genetic Architecture of Self-Employment

PubMed Central

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

GAMETES: a fast, direct algorithm for generating pure, strict, epistatic models with random architectures.

PubMed

Urbanowicz, Ryan J; Kiralis, Jeff; Sinnott-Armstrong, Nicholas A; Heberling, Tamra; Fisher, Jonathan M; Moore, Jason H

2012-10-01

Geneticists who look beyond single locus disease associations require additional strategies for the detection of complex multi-locus effects. Epistasis, a multi-locus masking effect, presents a particular challenge, and has been the target of bioinformatic development. Thorough evaluation of new algorithms calls for simulation studies in which known disease models are sought. To date, the best methods for generating simulated multi-locus epistatic models rely on genetic algorithms. However, such methods are computationally expensive, difficult to adapt to multiple objectives, and unlikely to yield models with a precise form of epistasis which we refer to as pure and strict. Purely and strictly epistatic models constitute the worst-case in terms of detecting disease associations, since such associations may only be observed if all n-loci are included in the disease model. This makes them an attractive gold standard for simulation studies considering complex multi-locus effects. We introduce GAMETES, a user-friendly software package and algorithm which generates complex biallelic single nucleotide polymorphism (SNP) disease models for simulation studies. GAMETES rapidly and precisely generates random, pure, strict n-locus models with specified genetic constraints. These constraints include heritability, minor allele frequencies of the SNPs, and population prevalence. GAMETES also includes a simple dataset simulation strategy which may be utilized to rapidly generate an archive of simulated datasets for given genetic models. We highlight the utility and limitations of GAMETES with an example simulation study using MDR, an algorithm designed to detect epistasis. GAMETES is a fast, flexible, and precise tool for generating complex n-locus models with random architectures. While GAMETES has a limited ability to generate models with higher heritabilities, it is proficient at generating the lower heritability models typically used in simulation studies evaluating new algorithms. In addition, the GAMETES modeling strategy may be flexibly combined with any dataset simulation strategy. Beyond dataset simulation, GAMETES could be employed to pursue theoretical characterization of genetic models and epistasis.

Design and Implementation of the International Genetics and Translational Research in Transplantation Network.

PubMed

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.

Determination of nonlinear genetic architecture using compressed sensing.

PubMed

Ho, Chiu Man; Hsu, Stephen D H

2015-01-01

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

Assessing the complex architecture of polygenic traits in diverged yeast populations.

PubMed

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.

The Genetic Basis of Plant Architecture in 10 Maize Recombinant Inbred Line Populations1[OPEN

PubMed Central

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

Ensemble Learning of QTL Models Improves Prediction of Complex Traits

PubMed Central

Bian, Yang; Holland, James B.

2015-01-01

Quantitative trait locus (QTL) models can provide useful insights into trait genetic architecture because of their straightforward interpretability but are less useful for genetic prediction because of the difficulty in including the effects of numerous small effect loci without overfitting. Tight linkage between markers introduces near collinearity among marker genotypes, complicating the detection of QTL and estimation of QTL effects in linkage mapping, and this problem is exacerbated by very high density linkage maps. Here we developed a thinning and aggregating (TAGGING) method as a new ensemble learning approach to QTL mapping. TAGGING reduces collinearity problems by thinning dense linkage maps, maintains aspects of marker selection that characterize standard QTL mapping, and by ensembling, incorporates information from many more markers-trait associations than traditional QTL mapping. The objective of TAGGING was to improve prediction power compared with QTL mapping while also providing more specific insights into genetic architecture than genome-wide prediction models. TAGGING was compared with standard QTL mapping using cross validation of empirical data from the maize (Zea mays L.) nested association mapping population. TAGGING-assisted QTL mapping substantially improved prediction ability for both biparental and multifamily populations by reducing both the variance and bias in prediction. Furthermore, an ensemble model combining predictions from TAGGING-assisted QTL and infinitesimal models improved prediction abilities over the component models, indicating some complementarity between model assumptions and suggesting that some trait genetic architectures involve a mixture of a few major QTL and polygenic effects. PMID:26276383

Enabling complex genetic circuits to respond to extrinsic environmental signals.

PubMed

Hoynes-O'Connor, Allison; Shopera, Tatenda; Hinman, Kristina; Creamer, John Philip; Moon, Tae Seok

2017-07-01

Genetic circuits have the potential to improve a broad range of metabolic engineering processes and address a variety of medical and environmental challenges. However, in order to engineer genetic circuits that can meet the needs of these real-world applications, genetic sensors that respond to relevant extrinsic and intrinsic signals must be implemented in complex genetic circuits. In this work, we construct the first AND and NAND gates that respond to temperature and pH, two signals that have relevance in a variety of real-world applications. A previously identified pH-responsive promoter and a temperature-responsive promoter were extracted from the E. coli genome, characterized, and modified to suit the needs of the genetic circuits. These promoters were combined with components of the type III secretion system in Salmonella typhimurium and used to construct a set of AND gates with up to 23-fold change. Next, an antisense RNA was integrated into the circuit architecture to invert the logic of the AND gate and generate a set of NAND gates with up to 1168-fold change. These circuits provide the first demonstration of complex pH- and temperature-responsive genetic circuits, and lay the groundwork for the use of similar circuits in real-world applications. Biotechnol. Bioeng. 2017;114: 1626-1631. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Identification of multiple genetic loci in the mouse controlling immobility time in the tail suspension and forced swimming tests.

PubMed

Abou-Elnaga, Ahmed F; Torigoe, Daisuke; Fouda, Mohamed M; Darwish, Ragab A; Abou-Ismail, Usama A; Morimatsu, Masami; Agui, Takashi

2015-05-01

Depression is one of the most famous psychiatric disorders in humans in all over the countries and considered a complex neurobehavioral trait and difficult to identify causal genes. Tail suspension test (TST) and forced swimming test (FST) are widely used for assessing depression-like behavior and antidepressant activity in mice. A variety of antidepressant agents are known to reduce immobility time in both TST and FST. To identify genetic determinants of immobility duration in both tests, we analyzed 101 F2 mice from an intercross between C57BL/6 and DBA/2 strains. Quantitative trait locus (QTL) mapping using 106 microsatellite markers revealed three loci (two significant and one suggestive) and five suggestive loci controlling immobility time in the TST and FST, respectively. Results of QTL analysis suggest a broad description of the genetic architecture underlying depression, providing underpinnings for identifying novel molecular targets for antidepressants to clear the complex genetic mechanisms of depressive disorders.

Explosive genetic evidence for explosive human population growth

PubMed Central

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

Implications of sex-specific selection for the genetic basis of disease.

PubMed

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.

Genetics and the making of Homo sapiens.

PubMed

Carroll, Sean B

2003-04-24

Understanding the genetic basis of the physical and behavioural traits that distinguish humans from other primates presents one of the great new challenges in biology. Of the millions of base-pair differences between humans and chimpanzees, which particular changes contributed to the evolution of human features after the separation of the Pan and Homo lineages 5-7 million years ago? How can we identify the 'smoking guns' of human genetic evolution from neutral ticks of the molecular evolutionary clock? The magnitude and rate of morphological evolution in hominids suggests that many independent and incremental developmental changes have occurred that, on the basis of recent findings in model animals, are expected to be polygenic and regulatory in nature. Comparative genomics, population genetics, gene-expression analyses and medical genetics have begun to make complementary inroads into the complex genetic architecture of human evolution.

Advances in cereal genomics and applications in crop breeding.

PubMed

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

2006-11-01

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

Systems Engineering Design Via Experimental Operation Research: Complex Organizational Metric for Programmatic Risk Environments (COMPRE)

NASA Technical Reports Server (NTRS)

Mog, Robert A.

1999-01-01

Unique and innovative graph theory, neural network, organizational modeling, and genetic algorithms are applied to the design and evolution of programmatic and organizational architectures. Graph theory representations of programs and organizations increase modeling capabilities and flexibility, while illuminating preferable programmatic/organizational design features. Treating programs and organizations as neural networks results in better system synthesis, and more robust data modeling. Organizational modeling using covariance structures enhances the determination of organizational risk factors. Genetic algorithms improve programmatic evolution characteristics, while shedding light on rulebase requirements for achieving specified technological readiness levels, given budget and schedule resources. This program of research improves the robustness and verifiability of systems synthesis tools, including the Complex Organizational Metric for Programmatic Risk Environments (COMPRE).

GENETIC VARIATION IN BABOON CRANIOFACIAL SEXUAL DIMORPHISM

PubMed Central

Willmore, Katherine E.; Roseman, Charles C.; Rogers, Jeffrey; Richtsmeier, Joan T.; Cheverud, James M.

2010-01-01

Sexual dimorphism is a widespread phenomenon and contributes greatly to intraspecies variation. Despite a long history of active research, the genetic basis of dimorphism for complex traits remains unknown. Understanding the sex-specific differences in genetic architecture for cranial traits in a highly dimorphic species could identify possible mechanisms through which selection acts to produce dimorphism. Using distances calculated from three-dimensional landmark data from CT scans of 402 baboon skulls from a known genealogy, we estimated genetic variance parameters in both sexes to determine the presence of gene-by-sex (G × S) interactions and X-linked heritability. We hypothesize that traits exhibiting the greatest degree of sexual dimorphism (facial traits in baboons) will demonstrate either stronger G × S interactions or X-linked effects. We found G × S interactions and X-linked effects for a few measures that span the areas connecting the face to the neurocranium but for no traits restricted to the face. This finding suggests that facial traits will have a limited response to selection for further evolution of dimorphism in this population. We discuss the implications of our results with respect to the origins of cranial sexual dimorphism in this baboon sample, and how the genetic architecture of these traits affects their potential for future evolution. PMID:19210535

Sexual selection and genetic colour polymorphisms in animals.

PubMed

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.

The genetic architecture of economic and political preferences.

PubMed

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.

Admixture in Latin America.

PubMed

Adhikari, Kaustubh; Mendoza-Revilla, Javier; Chacón-Duque, Juan Camilo; Fuentes-Guajardo, Macarena; Ruiz-Linares, Andrés

2016-12-01

Latin Americans arguably represent the largest recently admixed populations in the world. This reflects a history of massive settlement by immigrants (mostly Europeans and Africans) and their variable admixture with Natives, starting in 1492. This process resulted in the population of Latin America showing an extensive genetic and phenotypic diversity. Here we review how genetic analyses are being applied to examine the demographic history of this population, including patterns of mating, population structure and ancestry. The admixture history of Latin America, and the resulting extensive diversity of the region, represents a natural experiment offering an advantageous setting for genetic association studies. We review how recent analyses in Latin Americans are contributing to elucidating the genetic architecture of human complex traits. Copyright © 2016 Elsevier Ltd. All rights reserved.

Partitioning heritability analysis reveals a shared genetic basis of brain anatomy and schizophrenia

PubMed Central

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

Partitioning heritability analysis reveals a shared genetic basis of brain anatomy and schizophrenia.

PubMed

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.

The Genetic Basis of Upland/Lowland Ecotype Divergence in Switchgrass (Panicum virgatum)

DOE PAGES

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

The Genetic Basis of Plant Architecture in 10 Maize Recombinant Inbred Line Populations.

PubMed

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.

Mapping complex traits as a dynamic system

PubMed Central

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

Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility.

PubMed

Mahajan, Anubha; Go, Min Jin; Zhang, Weihua; Below, Jennifer E; Gaulton, Kyle J; Ferreira, Teresa; Horikoshi, Momoko; Johnson, Andrew D; Ng, Maggie C Y; Prokopenko, Inga; Saleheen, Danish; Wang, Xu; Zeggini, Eleftheria; Abecasis, Goncalo R; Adair, Linda S; Almgren, Peter; Atalay, Mustafa; Aung, Tin; Baldassarre, Damiano; Balkau, Beverley; Bao, Yuqian; Barnett, Anthony H; Barroso, Ines; Basit, Abdul; Been, Latonya F; Beilby, John; Bell, Graeme I; Benediktsson, Rafn; Bergman, Richard N; Boehm, Bernhard O; Boerwinkle, Eric; Bonnycastle, Lori L; Burtt, Noël; Cai, Qiuyin; Campbell, Harry; Carey, Jason; Cauchi, Stephane; Caulfield, Mark; Chan, Juliana C N; Chang, Li-Ching; Chang, Tien-Jyun; Chang, Yi-Cheng; Charpentier, Guillaume; Chen, Chien-Hsiun; Chen, Han; Chen, Yuan-Tsong; Chia, Kee-Seng; Chidambaram, Manickam; Chines, Peter S; Cho, Nam H; Cho, Young Min; Chuang, Lee-Ming; Collins, Francis S; Cornelis, Marylin C; Couper, David J; Crenshaw, Andrew T; van Dam, Rob M; Danesh, John; Das, Debashish; de Faire, Ulf; Dedoussis, George; Deloukas, Panos; Dimas, Antigone S; Dina, Christian; Doney, Alex S; Donnelly, Peter J; Dorkhan, Mozhgan; van Duijn, Cornelia; Dupuis, Josée; Edkins, Sarah; Elliott, Paul; Emilsson, Valur; Erbel, Raimund; Eriksson, Johan G; Escobedo, Jorge; Esko, Tonu; Eury, Elodie; Florez, Jose C; Fontanillas, Pierre; Forouhi, Nita G; Forsen, Tom; Fox, Caroline; Fraser, Ross M; Frayling, Timothy M; Froguel, Philippe; Frossard, Philippe; Gao, Yutang; Gertow, Karl; Gieger, Christian; Gigante, Bruna; Grallert, Harald; Grant, George B; Grrop, Leif C; Groves, Chrisropher J; Grundberg, Elin; Guiducci, Candace; Hamsten, Anders; Han, Bok-Ghee; Hara, Kazuo; Hassanali, Neelam; Hattersley, Andrew T; Hayward, Caroline; Hedman, Asa K; Herder, Christian; Hofman, Albert; Holmen, Oddgeir L; Hovingh, Kees; Hreidarsson, Astradur B; Hu, Cheng; Hu, Frank B; Hui, Jennie; Humphries, Steve E; Hunt, Sarah E; Hunter, David J; Hveem, Kristian; Hydrie, Zafar I; Ikegami, Hiroshi; Illig, Thomas; Ingelsson, Erik; Islam, Muhammed; Isomaa, Bo; Jackson, Anne U; Jafar, Tazeen; James, Alan; Jia, Weiping; Jöckel, Karl-Heinz; Jonsson, Anna; Jowett, Jeremy B M; Kadowaki, Takashi; Kang, Hyun Min; Kanoni, Stavroula; Kao, Wen Hong L; Kathiresan, Sekar; Kato, Norihiro; Katulanda, Prasad; Keinanen-Kiukaanniemi, Kirkka M; Kelly, Ann M; Khan, Hassan; Khaw, Kay-Tee; Khor, Chiea-Chuen; Kim, Hyung-Lae; Kim, Sangsoo; Kim, Young Jin; Kinnunen, Leena; Klopp, Norman; Kong, Augustine; Korpi-Hyövälti, Eeva; Kowlessur, Sudhir; Kraft, Peter; Kravic, Jasmina; Kristensen, Malene M; Krithika, S; Kumar, Ashish; Kumate, Jesus; Kuusisto, Johanna; Kwak, Soo Heon; Laakso, Markku; Lagou, Vasiliki; Lakka, Timo A; Langenberg, Claudia; Langford, Cordelia; Lawrence, Robert; Leander, Karin; Lee, Jen-Mai; Lee, Nanette R; Li, Man; Li, Xinzhong; Li, Yun; Liang, Junbin; Liju, Samuel; Lim, Wei-Yen; Lind, Lars; Lindgren, Cecilia M; Lindholm, Eero; Liu, Ching-Ti; Liu, Jian Jun; Lobbens, Stéphane; Long, Jirong; Loos, Ruth J F; Lu, Wei; Luan, Jian'an; Lyssenko, Valeriya; Ma, Ronald C W; Maeda, Shiro; Mägi, Reedik; Männisto, Satu; Matthews, David R; Meigs, James B; Melander, Olle; Metspalu, Andres; Meyer, Julia; Mirza, Ghazala; Mihailov, Evelin; Moebus, Susanne; Mohan, Viswanathan; Mohlke, Karen L; Morris, Andrew D; Mühleisen, Thomas W; Müller-Nurasyid, Martina; Musk, Bill; Nakamura, Jiro; Nakashima, Eitaro; Navarro, Pau; Ng, Peng-Keat; Nica, Alexandra C; Nilsson, Peter M; Njølstad, Inger; Nöthen, Markus M; Ohnaka, Keizo; Ong, Twee Hee; Owen, Katharine R; Palmer, Colin N A; Pankow, James S; Park, Kyong Soo; Parkin, Melissa; Pechlivanis, Sonali; Pedersen, Nancy L; Peltonen, Leena; Perry, John R B; Peters, Annette; Pinidiyapathirage, Janini M; Platou, Carl G; Potter, Simon; Price, Jackie F; Qi, Lu; Radha, Venkatesan; Rallidis, Loukianos; Rasheed, Asif; Rathman, Wolfgang; Rauramaa, Rainer; Raychaudhuri, Soumya; Rayner, N William; Rees, Simon D; Rehnberg, Emil; Ripatti, Samuli; Robertson, Neil; Roden, Michael; Rossin, Elizabeth J; Rudan, Igor; Rybin, Denis; Saaristo, Timo E; Salomaa, Veikko; Saltevo, Juha; Samuel, Maria; Sanghera, Dharambir K; Saramies, Jouko; Scott, James; Scott, Laura J; Scott, Robert A; Segrè, Ayellet V; Sehmi, Joban; Sennblad, Bengt; Shah, Nabi; Shah, Sonia; Shera, A Samad; Shu, Xiao Ou; Shuldiner, Alan R; Sigurđsson, Gunnar; Sijbrands, Eric; Silveira, Angela; Sim, Xueling; Sivapalaratnam, Suthesh; Small, Kerrin S; So, Wing Yee; Stančáková, Alena; Stefansson, Kari; Steinbach, Gerald; Steinthorsdottir, Valgerdur; Stirrups, Kathleen; Strawbridge, Rona J; Stringham, Heather M; Sun, Qi; Suo, Chen; Syvänen, Ann-Christine; Takayanagi, Ryoichi; Takeuchi, Fumihiko; Tay, Wan Ting; Teslovich, Tanya M; Thorand, Barbara; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Tikkanen, Emmi; Trakalo, Joseph; Tremoli, Elena; Trip, Mieke D; Tsai, Fuu Jen; Tuomi, Tiinamaija; Tuomilehto, Jaakko; Uitterlinden, Andre G; Valladares-Salgado, Adan; Vedantam, Sailaja; Veglia, Fabrizio; Voight, Benjamin F; Wang, Congrong; Wareham, Nicholas J; Wennauer, Roman; Wickremasinghe, Ananda R; Wilsgaard, Tom; Wilson, James F; Wiltshire, Steven; Winckler, Wendy; Wong, Tien Yin; Wood, Andrew R; Wu, Jer-Yuarn; Wu, Ying; Yamamoto, Ken; Yamauchi, Toshimasa; Yang, Mingyu; Yengo, Loic; Yokota, Mitsuhiro; Young, Robin; Zabaneh, Delilah; Zhang, Fan; Zhang, Rong; Zheng, Wei; Zimmet, Paul Z; Altshuler, David; Bowden, Donald W; Cho, Yoon Shin; Cox, Nancy J; Cruz, Miguel; Hanis, Craig L; Kooner, Jaspal; Lee, Jong-Young; Seielstad, Mark; Teo, Yik Ying; Boehnke, Michael; Parra, Esteban J; Chambers, Jonh C; Tai, E Shyong; McCarthy, Mark I; Morris, Andrew P

2014-03-01

To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.

Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility

PubMed Central

2014-01-01

To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS) including 26,488 cases and 83,964 controls of European, East Asian, South Asian, and Mexican and Mexican American ancestry. We observed significant excess in directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven novel T2D susceptibility loci. Furthermore, we observed considerable improvements in fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterisation of complex trait loci, and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry. PMID:24509480

Genetics and intelligence differences: five special findings.

PubMed

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

PubMed Central

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

Natural genetic variation of root system architecture from Arabidopsis to Brachypodium: towards adaptive value.

PubMed

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.

Genetic mouse models relevant to schizophrenia: taking stock and looking forward.

PubMed

Harrison, Paul J; Pritchett, David; Stumpenhorst, Katharina; Betts, Jill F; Nissen, Wiebke; Schweimer, Judith; Lane, Tracy; Burnet, Philip W J; Lamsa, Karri P; Sharp, Trevor; Bannerman, David M; Tunbridge, Elizabeth M

2012-03-01

Genetic mouse models relevant to schizophrenia complement, and have to a large extent supplanted, pharmacological and lesion-based rat models. The main attraction is that they potentially have greater construct validity; however, they share the fundamental limitations of all animal models of psychiatric disorder, and must also be viewed in the context of the uncertain and complex genetic architecture of psychosis. Some of the key issues, including the choice of gene to target, the manner of its manipulation, gene-gene and gene-environment interactions, and phenotypic characterization, are briefly considered in this commentary, illustrated by the relevant papers reported in this special issue. Copyright © 2011 Elsevier Ltd. All rights reserved.

Genetic basis to hybrid inviability is more complex than hybrid male sterility in Caenorhabditis nematodes.

PubMed

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.

Use of support vector machines for disease risk prediction in genome-wide association studies: concerns and opportunities.

PubMed

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.

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

PubMed

Veturi, Yogasudha; Ritchie, Marylyn D

2018-01-01

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

Phenome-Wide Association Study (PheWAS) for Detection of Pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network

PubMed Central

Pendergrass, Sarah A.; Brown-Gentry, Kristin; Dudek, Scott; Frase, Alex; Torstenson, Eric S.; Goodloe, Robert; Ambite, Jose Luis; Avery, Christy L.; Buyske, Steve; Bůžková, Petra; Deelman, Ewa; Fesinmeyer, Megan D.; Haiman, Christopher A.; Heiss, Gerardo; Hindorff, Lucia A.; Hsu, Chu-Nan; Jackson, Rebecca D.; Kooperberg, Charles; Le Marchand, Loic; Lin, Yi; Matise, Tara C.; Monroe, Kristine R.; Moreland, Larry; Park, Sungshim L.; Reiner, Alex; Wallace, Robert; Wilkens, Lynn R.; Crawford, Dana C.; Ritchie, Marylyn D.

2013-01-01

Using a phenome-wide association study (PheWAS) approach, we comprehensively tested genetic variants for association with phenotypes available for 70,061 study participants in the Population Architecture using Genomics and Epidemiology (PAGE) network. Our aim was to better characterize the genetic architecture of complex traits and identify novel pleiotropic relationships. This PheWAS drew on five population-based studies representing four major racial/ethnic groups (European Americans (EA), African Americans (AA), Hispanics/Mexican-Americans, and Asian/Pacific Islanders) in PAGE, each site with measurements for multiple traits, associated laboratory measures, and intermediate biomarkers. A total of 83 single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) were genotyped across two or more PAGE study sites. Comprehensive tests of association, stratified by race/ethnicity, were performed, encompassing 4,706 phenotypes mapped to 105 phenotype-classes, and association results were compared across study sites. A total of 111 PheWAS results had significant associations for two or more PAGE study sites with consistent direction of effect with a significance threshold of p<0.01 for the same racial/ethnic group, SNP, and phenotype-class. Among results identified for SNPs previously associated with phenotypes such as lipid traits, type 2 diabetes, and body mass index, 52 replicated previously published genotype–phenotype associations, 26 represented phenotypes closely related to previously known genotype–phenotype associations, and 33 represented potentially novel genotype–phenotype associations with pleiotropic effects. The majority of the potentially novel results were for single PheWAS phenotype-classes, for example, for CDKN2A/B rs1333049 (previously associated with type 2 diabetes in EA) a PheWAS association was identified for hemoglobin levels in AA. Of note, however, GALNT2 rs2144300 (previously associated with high-density lipoprotein cholesterol levels in EA) had multiple potentially novel PheWAS associations, with hypertension related phenotypes in AA and with serum calcium levels and coronary artery disease phenotypes in EA. PheWAS identifies associations for hypothesis generation and exploration of the genetic architecture of complex traits. PMID:23382687

Human MHC architecture and evolution: implications for disease association studies

PubMed Central

Traherne, J A

2008-01-01

Major histocompatibility complex (MHC) variation is a key determinant of susceptibility and resistance to a large number of infectious, autoimmune and other diseases. Identification of the MHC variants conferring susceptibility to disease is problematic, due to high levels of variation and linkage disequilibrium. Recent cataloguing and analysis of variation over the complete MHC has facilitated localization of susceptibility loci for autoimmune diseases, and provided insight into the MHC's evolution. This review considers how the unusual genetic characteristics of the MHC impact on strategies to identify variants causing, or contributing to, disease phenotypes. It also considers the MHC in relation to novel mechanisms influencing gene function and regulation, such as epistasis, epigenetics and microRNAs. These developments, along with recent technological advances, shed light on genetic association in complex disease. PMID:18397301

Common mechanisms of excitatory and inhibitory imbalance in schizophrenia and autism spectrum disorders.

PubMed

Gao, R; Penzes, P

2015-01-01

Autism Spectrum Disorders (ASD) and Schizophrenia (SCZ) are cognitive disorders with complex genetic architectures but overlapping behavioral phenotypes, which suggests common pathway perturbations. Multiple lines of evidence implicate imbalances in excitatory and inhibitory activity (E/I imbalance) as a shared pathophysiological mechanism. Thus, understanding the molecular underpinnings of E/I imbalance may provide essential insight into the etiology of these disorders and may uncover novel targets for future drug discovery. Here, we review key genetic, physiological, neuropathological, functional, and pathway studies that suggest alterations to excitatory/inhibitory circuits are keys to ASD and SCZ pathogenesis.

Mirror representations innate versus determined by experience: a viewpoint from learning theory.

PubMed

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.

Cross-disorder genome-wide analyses suggest a complex genetic relationship between Tourette's syndrome and OCD.

PubMed

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.

Type VI secretion systems of human gut Bacteroidales segregate into three genetic architectures, two of which are contained on mobile genetic elements.

PubMed

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.

Genome survey and high-density genetic map construction provide genomic and genetic resources for the Pacific White Shrimp Litopenaeus vannamei

PubMed Central

Yu, Yang; Zhang, Xiaojun; Yuan, Jianbo; Li, Fuhua; Chen, Xiaohan; Zhao, Yongzhen; Huang, Long; Zheng, Hongkun; Xiang, Jianhai

2015-01-01

The Pacific white shrimp Litopenaeus vannamei is the dominant crustacean species in global seafood mariculture. Understanding the genome and genetic architecture is useful for deciphering complex traits and accelerating the breeding program in shrimp. In this study, a genome survey was conducted and a high-density linkage map was constructed using a next-generation sequencing approach. The genome survey was used to identify preliminary genome characteristics and to generate a rough reference for linkage map construction. De novo SNP discovery resulted in 25,140 polymorphic markers. A total of 6,359 high-quality markers were selected for linkage map construction based on marker coverage among individuals and read depths. For the linkage map, a total of 6,146 markers spanning 4,271.43 cM were mapped to 44 sex-averaged linkage groups, with an average marker distance of 0.7 cM. An integration analysis linked 5,885 genome scaffolds and 1,504 BAC clones to the linkage map. Based on the high-density linkage map, several QTLs for body weight and body length were detected. This high-density genetic linkage map reveals basic genomic architecture and will be useful for comparative genomics research, genome assembly and genetic improvement of L. vannamei and other penaeid shrimp species. PMID:26503227

Enhanced control of cucumber wilt disease by Bacillus amyloliquefaciens SQR9 by altering the regulation of Its DegU phosphorylation.

PubMed

Xu, Zhihui; Zhang, Ruifu; Wang, Dandan; Qiu, Meihua; Feng, Haichao; Zhang, Nan; Shen, Qirong

2014-05-01

Bacillus amyloliquefaciens strain SQR9, isolated from the cucumber rhizosphere, suppresses the growth of Fusarium oxysporum in the cucumber rhizosphere and protects the host plant from pathogen invasion through efficient root colonization. In the Gram-positive bacterium Bacillus, the response regulator DegU regulates genetic competence, swarming motility, biofilm formation, complex colony architecture, and protease production. In this study, we report that stepwise phosphorylation of DegU in B. amyloliquefaciens SQR9 can influence biocontrol activity by coordinating multicellular behavior and regulating the synthesis of antibiotics. Results from in vitro and in situ experiments and quantitative PCR (qPCR) studies demonstrate the following: (i) that the lowest level of phosphorylated DegU (DegU∼P) (the degQ mutation) impairs complex colony architecture, biofilm formation, colonization activities, and biocontrol efficiency of Fusarium wilt disease but increases the production of macrolactin and bacillaene, and (ii) that increasing the level of DegU∼P by degQ and degSU overexpression significantly improves complex colony architecture, biofilm formation, colonization activities, production of the antibiotics bacillomycin D and difficidin, and efficiency of biocontrol of Fusarium wilt disease. The results offer a new strategy to enhance the biocontrol efficacy of Bacillus amyloliquefaciens SQR9.

Genetic architecture of threshold reaction norms for male alternative reproductive tactics in Atlantic salmon (Salmo salar L.)

PubMed Central

Lepais, Olivier; Manicki, Aurélie; Glise, Stéphane; Buoro, Mathieu; Bardonnet, Agnès

2017-01-01

Alternative mating tactics have important ecological and evolutionary implications and are determined by complex interactions between environmental and genetic factors. Here, we study the genetic effect and architecture of the variability in reproductive tactics among Atlantic salmon males which can either mature sexually early in life in freshwater or more commonly only after completing a migration at sea. We applied the latent environmental threshold model (LETM), which provides a conceptual framework linking individual status to a threshold controlling the decision to develop alternative traits, in an innovative experimental design using a semi-natural river which allowed for ecologically relevant phenotypic expression. Early male parr maturation rates varied greatly across families (10 to 93%) which translated into 90% [64–100%] of the phenotypic variation explained by genetic variation. Three significant QTLs were found for the maturation status, however only one collocated with a highly significant QTL explaining 20.6% of the variability of the maturation threshold located on chromosome 25 and encompassing a locus previously shown to be linked to sea age at maturity in anadromous Atlantic salmon. These results provide new empirical illustration of the relevance of the LETM for a better understanding of alternative mating tactics evolution in natural populations. PMID:28281522

The genetic architecture of economic and political preferences

PubMed Central

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.

2012-01-01

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. PMID:22566634

New approaches to optimization in aerospace conceptual design

NASA Technical Reports Server (NTRS)

Gage, Peter J.

1995-01-01

Aerospace design can be viewed as an optimization process, but conceptual studies are rarely performed using formal search algorithms. Three issues that restrict the success of automatic search are identified in this work. New approaches are introduced to address the integration of analyses and optimizers, to avoid the need for accurate gradient information and a smooth search space (required for calculus-based optimization), and to remove the restrictions imposed by fixed complexity problem formulations. (1) Optimization should be performed in a flexible environment. A quasi-procedural architecture is used to conveniently link analysis modules and automatically coordinate their execution. It efficiently controls a large-scale design tasks. (2) Genetic algorithms provide a search method for discontinuous or noisy domains. The utility of genetic optimization is demonstrated here, but parameter encodings and constraint-handling schemes must be carefully chosen to avoid premature convergence to suboptimal designs. The relationship between genetic and calculus-based methods is explored. (3) A variable-complexity genetic algorithm is created to permit flexible parameterization, so that the level of description can change during optimization. This new optimizer automatically discovers novel designs in structural and aerodynamic tasks.

Shared Genetic Architecture in the Relationship between Adult Stature and Subclinical Coronary Artery Atherosclerosis

PubMed Central

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

Shared genetic architecture in the relationship between adult stature and subclinical coronary artery atherosclerosis.

PubMed

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.

Novel Genes Affecting the Interaction between the Cabbage Whitefly and Arabidopsis Uncovered by Genome-Wide Association Mapping

PubMed Central

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

An overview of the genetic dissection of complex traits.

PubMed

Rao, D C

2008-01-01

Thanks to the recent revolutionary genomic advances such as the International HapMap consortium, resolution of the genetic architecture of common complex traits is beginning to look hopeful. While demonstrating the feasibility of genome-wide association (GWA) studies, the pathbreaking Wellcome Trust Case Control Consortium (WTCCC) study also serves to underscore the critical importance of very large sample sizes and draws attention to potential problems, which need to be addressed as part of the study design. Even the large WTCCC study had vastly inadequate power for several of the associations reported (and confirmed) and, therefore, most of the regions harboring relevant associations may not be identified anytime soon. This chapter provides an overview of some of the key developments in the methodological approaches to genetic dissection of common complex traits. Constrained Bayesian networks are suggested as especially useful for analysis of pathway-based SNPs. Likewise, composite likelihood is suggested as a promising method for modeling complex systems. It discusses the key steps in a study design, with an emphasis on GWA studies. Potential limitations highlighted by the WTCCC GWA study are discussed, including problems associated with massive genotype imputation, analysis of pooled national samples, shared controls, and the critical role of interactions. GWA studies clearly need massive sample sizes that are only possible through genuine collaborations. After all, for common complex traits, the question is not whether we can find some pieces of the puzzle, but how large and what kind of a sample we need to (nearly) solve the genetic puzzle.

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

PubMed Central

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

2017-01-01

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

Transancestral mapping and genetic load in systemic lupus erythematosus.

PubMed

Langefeld, Carl D; Ainsworth, Hannah C; Cunninghame Graham, Deborah S; Kelly, Jennifer A; Comeau, Mary E; Marion, Miranda C; Howard, Timothy D; Ramos, Paula S; Croker, Jennifer A; Morris, David L; Sandling, Johanna K; Almlöf, Jonas Carlsson; Acevedo-Vásquez, Eduardo M; Alarcón, Graciela S; Babini, Alejandra M; Baca, Vicente; Bengtsson, Anders A; Berbotto, Guillermo A; Bijl, Marc; Brown, Elizabeth E; Brunner, Hermine I; Cardiel, Mario H; Catoggio, Luis; Cervera, Ricard; Cucho-Venegas, Jorge M; Dahlqvist, Solbritt Rantapää; D'Alfonso, Sandra; Da Silva, Berta Martins; de la Rúa Figueroa, Iñigo; Doria, Andrea; Edberg, Jeffrey C; Endreffy, Emőke; Esquivel-Valerio, Jorge A; Fortin, Paul R; Freedman, Barry I; Frostegård, Johan; García, Mercedes A; de la Torre, Ignacio García; Gilkeson, Gary S; Gladman, Dafna D; Gunnarsson, Iva; Guthridge, Joel M; Huggins, Jennifer L; James, Judith A; Kallenberg, Cees G M; Kamen, Diane L; Karp, David R; Kaufman, Kenneth M; Kottyan, Leah C; Kovács, László; Laustrup, Helle; Lauwerys, Bernard R; Li, Quan-Zhen; Maradiaga-Ceceña, Marco A; Martín, Javier; McCune, Joseph M; McWilliams, David R; Merrill, Joan T; Miranda, Pedro; Moctezuma, José F; Nath, Swapan K; Niewold, Timothy B; Orozco, Lorena; Ortego-Centeno, Norberto; Petri, Michelle; Pineau, Christian A; Pons-Estel, Bernardo A; Pope, Janet; Raj, Prithvi; Ramsey-Goldman, Rosalind; Reveille, John D; Russell, Laurie P; Sabio, José M; Aguilar-Salinas, Carlos A; Scherbarth, Hugo R; Scorza, Raffaella; Seldin, Michael F; Sjöwall, Christopher; Svenungsson, Elisabet; Thompson, Susan D; Toloza, Sergio M A; Truedsson, Lennart; Tusié-Luna, Teresa; Vasconcelos, Carlos; Vilá, Luis M; Wallace, Daniel J; Weisman, Michael H; Wither, Joan E; Bhangale, Tushar; Oksenberg, Jorge R; Rioux, John D; Gregersen, Peter K; Syvänen, Ann-Christine; Rönnblom, Lars; Criswell, Lindsey A; Jacob, Chaim O; Sivils, Kathy L; Tsao, Betty P; Schanberg, Laura E; Behrens, Timothy W; Silverman, Earl D; Alarcón-Riquelme, Marta E; Kimberly, Robert P; Harley, John B; Wakeland, Edward K; Graham, Robert R; Gaffney, Patrick M; Vyse, Timothy J

2017-07-17

Systemic lupus erythematosus (SLE) is an autoimmune disease with marked gender and ethnic disparities. We report a large transancestral association study of SLE using Immunochip genotype data from 27,574 individuals of European (EA), African (AA) and Hispanic Amerindian (HA) ancestry. We identify 58 distinct non-HLA regions in EA, 9 in AA and 16 in HA (∼50% of these regions have multiple independent associations); these include 24 novel SLE regions (P<5 × 10 -8 ), refined association signals in established regions, extended associations to additional ancestries, and a disentangled complex HLA multigenic effect. The risk allele count (genetic load) exhibits an accelerating pattern of SLE risk, leading us to posit a cumulative hit hypothesis for autoimmune disease. Comparing results across the three ancestries identifies both ancestry-dependent and ancestry-independent contributions to SLE risk. Our results are consistent with the unique and complex histories of the populations sampled, and collectively help clarify the genetic architecture and ethnic disparities in SLE.

Transancestral mapping and genetic load in systemic lupus erythematosus

PubMed Central

Langefeld, Carl D.; Ainsworth, Hannah C.; Graham, Deborah S. Cunninghame; Kelly, Jennifer A.; Comeau, Mary E.; Marion, Miranda C.; Howard, Timothy D.; Ramos, Paula S.; Croker, Jennifer A.; Morris, David L.; Sandling, Johanna K.; Almlöf, Jonas Carlsson; Acevedo-Vásquez, Eduardo M.; Alarcón, Graciela S.; Babini, Alejandra M.; Baca, Vicente; Bengtsson, Anders A.; Berbotto, Guillermo A.; Bijl, Marc; Brown, Elizabeth E.; Brunner, Hermine I.; Cardiel, Mario H.; Catoggio, Luis; Cervera, Ricard; Cucho-Venegas, Jorge M.; Dahlqvist, Solbritt Rantapää; D’Alfonso, Sandra; Da Silva, Berta Martins; de la Rúa Figueroa, Iñigo; Doria, Andrea; Edberg, Jeffrey C.; Endreffy, Emőke; Esquivel-Valerio, Jorge A.; Fortin, Paul R.; Freedman, Barry I.; Frostegård, Johan; García, Mercedes A.; de la Torre, Ignacio García; Gilkeson, Gary S.; Gladman, Dafna D.; Gunnarsson, Iva; Guthridge, Joel M.; Huggins, Jennifer L.; James, Judith A.; Kallenberg, Cees G. M.; Kamen, Diane L.; Karp, David R.; Kaufman, Kenneth M.; Kottyan, Leah C.; Kovács, László; Laustrup, Helle; Lauwerys, Bernard R.; Li, Quan-Zhen; Maradiaga-Ceceña, Marco A.; Martín, Javier; McCune, Joseph M.; McWilliams, David R.; Merrill, Joan T.; Miranda, Pedro; Moctezuma, José F.; Nath, Swapan K.; Niewold, Timothy B.; Orozco, Lorena; Ortego-Centeno, Norberto; Petri, Michelle; Pineau, Christian A.; Pons-Estel, Bernardo A.; Pope, Janet; Raj, Prithvi; Ramsey-Goldman, Rosalind; Reveille, John D.; Russell, Laurie P.; Sabio, José M.; Aguilar-Salinas, Carlos A.; Scherbarth, Hugo R.; Scorza, Raffaella; Seldin, Michael F.; Sjöwall, Christopher; Svenungsson, Elisabet; Thompson, Susan D.; Toloza, Sergio M. A.; Truedsson, Lennart; Tusié-Luna, Teresa; Vasconcelos, Carlos; Vilá, Luis M.; Wallace, Daniel J.; Weisman, Michael H.; Wither, Joan E.; Bhangale, Tushar; Oksenberg, Jorge R.; Rioux, John D.; Gregersen, Peter K.; Syvänen, Ann-Christine; Rönnblom, Lars; Criswell, Lindsey A.; Jacob, Chaim O.; Sivils, Kathy L.; Tsao, Betty P.; Schanberg, Laura E.; Behrens, Timothy W.; Silverman, Earl D.; Alarcón-Riquelme, Marta E.; Kimberly, Robert P.; Harley, John B.; Wakeland, Edward K.; Graham, Robert R.; Gaffney, Patrick M.; Vyse, Timothy J.

2017-01-01

Systemic lupus erythematosus (SLE) is an autoimmune disease with marked gender and ethnic disparities. We report a large transancestral association study of SLE using Immunochip genotype data from 27,574 individuals of European (EA), African (AA) and Hispanic Amerindian (HA) ancestry. We identify 58 distinct non-HLA regions in EA, 9 in AA and 16 in HA (∼50% of these regions have multiple independent associations); these include 24 novel SLE regions (P<5 × 10−8), refined association signals in established regions, extended associations to additional ancestries, and a disentangled complex HLA multigenic effect. The risk allele count (genetic load) exhibits an accelerating pattern of SLE risk, leading us to posit a cumulative hit hypothesis for autoimmune disease. Comparing results across the three ancestries identifies both ancestry-dependent and ancestry-independent contributions to SLE risk. Our results are consistent with the unique and complex histories of the populations sampled, and collectively help clarify the genetic architecture and ethnic disparities in SLE. PMID:28714469

Epistatic Effects Contribute to Variation in BMD in Fischer 344 × Lewis F2 Rats

PubMed Central

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.

PubMed

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

PubMed Central

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

2013-01-01

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

Genetic Complexity and Quantitative Trait Loci Mapping of Yeast Morphological Traits

PubMed Central

Nogami, Satoru; Ohya, Yoshikazu; Yvert, Gaël

2007-01-01

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

An Association Mapping Framework To Account for Potential Sex Difference in Genetic Architectures.

PubMed

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.

Genetic architecture and genomic patterns of gene flow between hybridizing species of Picea

PubMed Central

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

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

PubMed

Masojć, Piotr; Milczarski, P; Kruszona, P

2017-08-01

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

Genome-wide dissection of hybrid sterility in Drosophila confirms a polygenic threshold architecture.

PubMed

Morán, Tomás; Fontdevila, Antonio

2014-01-01

To date, different studies about the genetic basis of hybrid male sterility (HMS), a postzygotic reproductive barrier thoroughly investigated using Drosophila species, have demonstrated that no single major gene can produce hybrid sterility without the cooperation of several genetic factors. Early work using hybrids between Drosophila koepferae (Dk) and Drosophila buzzatii (Db) was consistent with the idea that HMS requires the cooperation of several genetic factors, supporting a polygenic threshold (PT) model. Here we present a genome-wide mapping strategy to test the PT model, analyzing serially backcrossed fertile and sterile males in which the Dk genome was introgressed into the Db background. We identified 32 Dk-specific markers significantly associated with hybrid sterility. Our results demonstrate 1) a strong correlation between the number of segregated sterility markers and males' degree of sterility, 2) the exchangeability among markers, 3) their tendency to cluster into low-recombining chromosomal regions, and 4) the requirement for a minimum number (threshold) of markers to elicit sterility. Although our findings do not contradict a role for occasional major hybrid-sterility genes, they conform more to the view that HMS primarily evolves by the cumulative action of many interacting genes of minor effect in a complex PT architecture.

Genetic Complexity of Episodic Memory: A Twin Approach to Studies of Aging

PubMed Central

Kremen, William S.; Spoon, Kelly M.; Jacobson, Kristen C.; Vasilopoulos, Terrie; McCaffery, Jeanne M.; Panizzon, Matthew S.; Franz, Carol E.; Vuoksimaa, Eero; Xian, Hong; Rana, Brinda K.; Toomey, Rosemary; McKenzie, Ruth; Lyons, Michael J.

2016-01-01

Episodic memory change is a central issue in cognitive aging, and understanding that process will require elucidation of its genetic underpinnings. A key limiting factor in genetically informed research on memory has been lack of attention to genetic and phenotypic complexity, as if “memory is memory” and all well-validated assessments are essentially equivalent. Here we applied multivariate twin models to data from late-middle-aged participants in the Vietnam Era Twin Study of Aging to examine the genetic architecture of 6 measures from 3 standard neuropsychological tests: the California Verbal Learning Test-2, and Wechsler Memory Scale-III Logical Memory (LM) and Visual Reproductions (VR). An advantage of the twin method is that it can estimate the extent to which latent genetic influences are shared or independent across different measures before knowing which specific genes are involved. The best-fitting model was a higher order common pathways model with a heritable higher order general episodic memory factor and three test-specific subfactors. More importantly, substantial genetic variance was accounted for by genetic influences that were specific to the latent LM and VR subfactors (28% and 30%, respectively) and independent of the general factor. Such unique genetic influences could partially account for replication failures. Moreover, if different genes influence different memory phenotypes, they could well have different age-related trajectories. This approach represents an important step toward providing critical information for all types of genetically informative studies of aging and memory. PMID:24956007

Genetic effects influencing risk for major depressive disorder in China and Europe.

PubMed

Bigdeli, T B; Ripke, S; Peterson, R E; Trzaskowski, M; Bacanu, S-A; Abdellaoui, A; Andlauer, T F M; Beekman, A T F; Berger, K; Blackwood, D H R; Boomsma, D I; Breen, G; Buttenschøn, H N; Byrne, E M; Cichon, S; Clarke, T-K; Couvy-Duchesne, B; Craddock, N; de Geus, E J C; Degenhardt, F; Dunn, E C; Edwards, A C; Fanous, A H; Forstner, A J; Frank, J; Gill, M; Gordon, S D; Grabe, H J; Hamilton, S P; Hardiman, O; Hayward, C; Heath, A C; Henders, A K; Herms, S; Hickie, I B; Hoffmann, P; Homuth, G; Hottenga, J-J; Ising, M; Jansen, R; Kloiber, S; Knowles, J A; Lang, M; Li, Q S; Lucae, S; MacIntyre, D J; Madden, P A F; Martin, N G; McGrath, P J; McGuffin, P; McIntosh, A M; Medland, S E; Mehta, D; Middeldorp, C M; Milaneschi, Y; Montgomery, G W; Mors, O; Müller-Myhsok, B; Nauck, M; Nyholt, D R; Nöthen, M M; Owen, M J; Penninx, B W J H; Pergadia, M L; Perlis, R H; Peyrot, W J; Porteous, D J; Potash, J B; Rice, J P; Rietschel, M; Riley, B P; Rivera, M; Schoevers, R; Schulze, T G; Shi, J; Shyn, S I; Smit, J H; Smoller, J W; Streit, F; Strohmaier, J; Teumer, A; Treutlein, J; Van der Auwera, S; van Grootheest, G; van Hemert, A M; Völzke, H; Webb, B T; Weissman, M M; Wellmann, J; Willemsen, G; Witt, S H; Levinson, D F; Lewis, C M; Wray, N R; Flint, J; Sullivan, P F; Kendler, K S

2017-03-28

Major depressive disorder (MDD) is a common, complex psychiatric disorder and a leading cause of disability worldwide. Despite twin studies indicating its modest heritability (~30-40%), extensive heterogeneity and a complex genetic architecture have complicated efforts to detect associated genetic risk variants. We combined single-nucleotide polymorphism (SNP) summary statistics from the CONVERGE and PGC studies of MDD, representing 10 502 Chinese (5282 cases and 5220 controls) and 18 663 European (9447 cases and 9215 controls) subjects. We determined the fraction of SNPs displaying consistent directions of effect, assessed the significance of polygenic risk scores and estimated the genetic correlation of MDD across ancestries. Subsequent trans-ancestry meta-analyses combined SNP-level evidence of association. Sign tests and polygenic score profiling weakly support an overlap of SNP effects between East Asian and European populations. We estimated the trans-ancestry genetic correlation of lifetime MDD as 0.33; female-only and recurrent MDD yielded estimates of 0.40 and 0.41, respectively. Common variants downstream of GPHN achieved genome-wide significance by Bayesian trans-ancestry meta-analysis (rs9323497; log 10 Bayes Factor=8.08) but failed to replicate in an independent European sample (P=0.911). Gene-set enrichment analyses indicate enrichment of genes involved in neuronal development and axonal trafficking. We successfully demonstrate a partially shared polygenic basis of MDD in East Asian and European populations. Taken together, these findings support a complex etiology for MDD and possible population differences in predisposing genetic factors, with important implications for future genetic studies.

Genetic effects influencing risk for major depressive disorder in China and Europe

PubMed Central

Bigdeli, T B; Ripke, S; Peterson, R E; Trzaskowski, M; Bacanu, S-A; Abdellaoui, A; Andlauer, T F M; Beekman, A T F; Berger, K; Blackwood, D H R; Boomsma, D I; Breen, G; Buttenschøn, H N; Byrne, E M; Cichon, S; Clarke, T-K; Couvy-Duchesne, B; Craddock, N; de Geus, E J C; Degenhardt, F; Dunn, E C; Edwards, A C; Fanous, A H; Forstner, A J; Frank, J; Gill, M; Gordon, S D; Grabe, H J; Hamilton, S P; Hardiman, O; Hayward, C; Heath, A C; Henders, A K; Herms, S; Hickie, I B; Hoffmann, P; Homuth, G; Hottenga, J-J; Ising, M; Jansen, R; Kloiber, S; Knowles, J A; Lang, M; Li, Q S; Lucae, S; MacIntyre, D J; Madden, P A F; Martin, N G; McGrath, P J; McGuffin, P; McIntosh, A M; Medland, S E; Mehta, D; Middeldorp, C M; Milaneschi, Y; Montgomery, G W; Mors, O; Müller-Myhsok, B; Nauck, M; Nyholt, D R; Nöthen, M M; Owen, M J; Penninx, B W J H; Pergadia, M L; Perlis, R H; Peyrot, W J; Porteous, D J; Potash, J B; Rice, J P; Rietschel, M; Riley, B P; Rivera, M; Schoevers, R; Schulze, T G; Shi, J; Shyn, S I; Smit, J H; Smoller, J W; Streit, F; Strohmaier, J; Teumer, A; Treutlein, J; Van der Auwera, S; van Grootheest, G; van Hemert, A M; Völzke, H; Webb, B T; Weissman, M M; Wellmann, J; Willemsen, G; Witt, S H; Levinson, D F; Lewis, C M; Wray, N R; Flint, J; Sullivan, P F; Kendler, K S

2017-01-01

Major depressive disorder (MDD) is a common, complex psychiatric disorder and a leading cause of disability worldwide. Despite twin studies indicating its modest heritability (~30–40%), extensive heterogeneity and a complex genetic architecture have complicated efforts to detect associated genetic risk variants. We combined single-nucleotide polymorphism (SNP) summary statistics from the CONVERGE and PGC studies of MDD, representing 10 502 Chinese (5282 cases and 5220 controls) and 18 663 European (9447 cases and 9215 controls) subjects. We determined the fraction of SNPs displaying consistent directions of effect, assessed the significance of polygenic risk scores and estimated the genetic correlation of MDD across ancestries. Subsequent trans-ancestry meta-analyses combined SNP-level evidence of association. Sign tests and polygenic score profiling weakly support an overlap of SNP effects between East Asian and European populations. We estimated the trans-ancestry genetic correlation of lifetime MDD as 0.33; female-only and recurrent MDD yielded estimates of 0.40 and 0.41, respectively. Common variants downstream of GPHN achieved genome-wide significance by Bayesian trans-ancestry meta-analysis (rs9323497; log10 Bayes Factor=8.08) but failed to replicate in an independent European sample (P=0.911). Gene-set enrichment analyses indicate enrichment of genes involved in neuronal development and axonal trafficking. We successfully demonstrate a partially shared polygenic basis of MDD in East Asian and European populations. Taken together, these findings support a complex etiology for MDD and possible population differences in predisposing genetic factors, with important implications for future genetic studies. PMID:28350396

Integrating Genetics and Social Science: Genetic Risk Scores

PubMed Central

Belsky, Daniel W.; Israel, Salomon

2014-01-01

The sequencing of the human genome and the advent of low-cost genome-wide assays that generate millions of observations of individual genomes in a matter of hours constitute a disruptive innovation for social science. Many public-use social science datasets have or will soon add genome-wide genetic data. With these new data come technical challenges, but also new possibilities. Among these, the lowest hanging fruit and the most potentially disruptive to existing research programs is the ability to measure previously invisible contours of health and disease risk within populations. In this article, we outline why now is the time for social scientists to bring genetics into their research programs. We discuss how to select genetic variants to study. We explain how the polygenic architecture of complex traits and the low penetrance of individual genetic loci pose challenges to research integrating genetics and social science. We introduce genetic risk scores as a method of addressing these challenges and provide guidance on how genetic risk scores can be constructed. We conclude by outlining research questions that are ripe for social science inquiry. PMID:25343363

The transformative potential of an integrative approach to pregnancy.

PubMed

Eidem, Haley R; McGary, Kriston L; Capra, John A; Abbot, Patrick; Rokas, Antonis

2017-09-01

Complex traits typically involve diverse biological pathways and are shaped by numerous genetic and environmental factors. Pregnancy-associated traits and pathologies are further complicated by extensive communication across multiple tissues in two individuals, interactions between two genomes-maternal and fetal-that obscure causal variants and lead to genetic conflict, and rapid evolution of pregnancy-associated traits across mammals and in the human lineage. Given the multi-faceted complexity of human pregnancy, integrative approaches that synthesize diverse data types and analyses harbor tremendous promise to identify the genetic architecture and environmental influences underlying pregnancy-associated traits and pathologies. We review current research that addresses the extreme complexities of traits and pathologies associated with human pregnancy. We find that successful efforts to address the many complexities of pregnancy-associated traits and pathologies often harness the power of many and diverse types of data, including genome-wide association studies, evolutionary analyses, multi-tissue transcriptomic profiles, and environmental conditions. We propose that understanding of pregnancy and its pathologies will be accelerated by computational platforms that provide easy access to integrated data and analyses. By simplifying the integration of diverse data, such platforms will provide a comprehensive synthesis that transcends many of the inherent challenges present in studies of pregnancy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dissection and engineering of the Escherichia coli formate hydrogenlyase complex.

PubMed

McDowall, Jennifer S; Hjersing, M Charlotte; Palmer, Tracy; Sargent, Frank

2015-10-07

The Escherichia coli formate hydrogenlyase (FHL) complex is produced under fermentative conditions and couples formate oxidation to hydrogen production. In this work, the architecture of FHL has been probed by analysing affinity-tagged complexes from various genetic backgrounds. In a successful attempt to stabilize the complex, a strain encoding a fusion between FdhF and HycB has been engineered and characterised. Finally, site-directed mutagenesis of the hycG gene was performed, which is predicted to encode a hydrogenase subunit important for regulating sensitivity to oxygen. This work helps to define the core components of FHL and provides solutions to improving the stability of the enzyme. Copyright © 2015 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

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

PubMed

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

2013-11-20

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

Mapping autism risk loci using genetic linkage and chromosomal rearrangements

PubMed Central

Szatmari, Peter; Paterson, Andrew; Zwaigenbaum, Lonnie; Roberts, Wendy; Brian, Jessica; Liu, Xiao-Qing; Vincent, John; Skaug, Jennifer; Thompson, Ann; Senman, Lili; Feuk, Lars; Qian, Cheng; Bryson, Susan; Jones, Marshall; Marshall, Christian; Scherer, Stephen; Vieland, Veronica; Bartlett, Christopher; Mangin, La Vonne; Goedken, Rhinda; Segre, Alberto; Pericak-Vance, Margaret; Cuccaro, Michael; Gilbert, John; Wright, Harry; Abramson, Ruth; Betancur, Catalina; Bourgeron, Thomas; Gillberg, Christopher; Leboyer, Marion; Buxbaum, Joseph; Davis, Kenneth; Hollander, Eric; Silverman, Jeremy; Hallmayer, Joachim; Lotspeich, Linda; Sutcliffe, James; Haines, Jonathan; Folstein, Susan; Piven, Joseph; Wassink, Thomas; Sheffield, Val; Geschwind, Daniel; Bucan, Maja; Brown, Ted; Cantor, Rita; Constantino, John; Gilliam, Conrad; Herbert, Martha; Lajonchere, Clara; Ledbetter, David; Lese-Martin, Christa; Miller, Janet; Nelson, Stan; Samango-Sprouse, Carol; Spence, Sarah; State, Matthew; Tanzi, Rudolph; Coon, Hilary; Dawson, Geraldine; Devlin, Bernie; Estes, Annette; Flodman, Pamela; Klei, Lambertus; Mcmahon, William; Minshew, Nancy; Munson, Jeff; Korvatska, Elena; Rodier, Patricia; Schellenberg, Gerard; Smith, Moyra; Spence, Anne; Stodgell, Chris; Tepper, Ping Guo; Wijsman, Ellen; Yu, Chang-En; Rogé, Bernadette; Mantoulan, Carine; Wittemeyer, Kerstin; Poustka, Annemarie; Felder, Bärbel; Klauck, Sabine; Schuster, Claudia; Poustka, Fritz; Bölte, Sven; Feineis-Matthews, Sabine; Herbrecht, Evelyn; Schmötzer, Gabi; Tsiantis, John; Papanikolaou, Katerina; Maestrini, Elena; Bacchelli, Elena; Blasi, Francesca; Carone, Simona; Toma, Claudio; Van Engeland, Herman; De Jonge, Maretha; Kemner, Chantal; Koop, Frederieke; Langemeijer, Marjolein; Hijmans, Channa; Staal, Wouter; Baird, Gillian; Bolton, Patrick; Rutter, Michael; Weisblatt, Emma; Green, Jonathan; Aldred, Catherine; Wilkinson, Julie-Anne; Pickles, Andrew; Le Couteur, Ann; Berney, Tom; Mcconachie, Helen; Bailey, Anthony; Francis, Kostas; Honeyman, Gemma; Hutchinson, Aislinn; Parr, Jeremy; Wallace, Simon; Monaco, Anthony; Barnby, Gabrielle; Kobayashi, Kazuhiro; Lamb, Janine; Sousa, Ines; Sykes, Nuala; Cook, Edwin; Guter, Stephen; Leventhal, Bennett; Salt, Jeff; Lord, Catherine; Corsello, Christina; Hus, Vanessa; Weeks, Daniel; Volkmar, Fred; Tauber, Maïté; Fombonne, Eric; Shih, Andy; Meyer, Kacie

2007-01-01

Autism spectrum disorders (ASD) are common, heritable neurodevelopmental conditions. The genetic architecture of ASD is complex, requiring large samples to overcome heterogeneity. Here we broaden coverage and sample size relative to other studies of ASD by using Affymetrix 10K single nucleotide polymorphism (SNP) arrays and 1168 families with ≥ 2 affected individuals to perform the largest linkage scan to date, while also analyzing copy number variation (CNV) in these families. Linkage and CNV analyses implicate chromosome 11p12-p13 and neurexins, respectively, amongst other candidate loci. Neurexins team with previously-implicated neuroligins for glutamatergic synaptogenesis, highlighting glutamate-related genes as promising candidates for ASD. PMID:17322880

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

PubMed

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

2016-11-17

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

Genome-wide meta-analysis identifies multiple novel associations and ethnic heterogeneity of psoriasis susceptibility.

PubMed

Yin, Xianyong; Low, Hui Qi; Wang, Ling; Li, Yonghong; Ellinghaus, Eva; Han, Jiali; Estivill, Xavier; Sun, Liangdan; Zuo, Xianbo; Shen, Changbing; Zhu, Caihong; Zhang, Anping; Sanchez, Fabio; Padyukov, Leonid; Catanese, Joseph J; Krueger, Gerald G; Duffin, Kristina Callis; Mucha, Sören; Weichenthal, Michael; Weidinger, Stephan; Lieb, Wolfgang; Foo, Jia Nee; Li, Yi; Sim, Karseng; Liany, Herty; Irwan, Ishak; Teo, Yikying; Theng, Colin T S; Gupta, Rashmi; Bowcock, Anne; De Jager, Philip L; Qureshi, Abrar A; de Bakker, Paul I W; Seielstad, Mark; Liao, Wilson; Ståhle, Mona; Franke, Andre; Zhang, Xuejun; Liu, Jianjun

2015-04-23

Psoriasis is a common inflammatory skin disease with complex genetics and different degrees of prevalence across ethnic populations. Here we present the largest trans-ethnic genome-wide meta-analysis (GWMA) of psoriasis in 15,369 cases and 19,517 controls of Caucasian and Chinese ancestries. We identify four novel associations at LOC144817, COG6, RUNX1 and TP63, as well as three novel secondary associations within IFIH1 and IL12B. Fine-mapping analysis of MHC region demonstrates an important role for all three HLA class I genes and a complex and heterogeneous pattern of HLA associations between Caucasian and Chinese populations. Further, trans-ethnic comparison suggests population-specific effect or allelic heterogeneity for 11 loci. These population-specific effects contribute significantly to the ethnic diversity of psoriasis prevalence. This study not only provides novel biological insights into the involvement of immune and keratinocyte development mechanism, but also demonstrates a complex and heterogeneous genetic architecture of psoriasis susceptibility across ethnic populations.

Genome-wide meta-analysis identifies multiple novel associations and ethnic heterogeneity of psoriasis susceptibility

PubMed Central

Yin, Xianyong; Low, Hui Qi; Wang, Ling; Li, Yonghong; Ellinghaus, Eva; Han, Jiali; Estivill, Xavier; Sun, Liangdan; Zuo, Xianbo; Shen, Changbing; Zhu, Caihong; Zhang, Anping; Sanchez, Fabio; Padyukov, Leonid; Catanese, Joseph J.; Krueger, Gerald G.; Duffin, Kristina Callis; Mucha, Sören; Weichenthal, Michael; Weidinger, Stephan; Lieb, Wolfgang; Foo, Jia Nee; Li, Yi; Sim, Karseng; Liany, Herty; Irwan, Ishak; Teo, Yikying; Theng, Colin T. S.; Gupta, Rashmi; Bowcock, Anne; De Jager, Philip L.; Qureshi, Abrar A.; de Bakker, Paul I. W.; Seielstad, Mark; Liao, Wilson; Ståhle, Mona; Franke, Andre; Zhang, Xuejun; Liu, Jianjun

2015-01-01

Psoriasis is a common inflammatory skin disease with complex genetics and different degrees of prevalence across ethnic populations. Here we present the largest trans-ethnic genome-wide meta-analysis (GWMA) of psoriasis in 15,369 cases and 19,517 controls of Caucasian and Chinese ancestries. We identify four novel associations at LOC144817, COG6, RUNX1 and TP63, as well as three novel secondary associations within IFIH1 and IL12B. Fine-mapping analysis of MHC region demonstrates an important role for all three HLA class I genes and a complex and heterogeneous pattern of HLA associations between Caucasian and Chinese populations. Further, trans-ethnic comparison suggests population-specific effect or allelic heterogeneity for 11 loci. These population-specific effects contribute significantly to the ethnic diversity of psoriasis prevalence. This study not only provides novel biological insights into the involvement of immune and keratinocyte development mechanism, but also demonstrates a complex and heterogeneous genetic architecture of psoriasis susceptibility across ethnic populations. PMID:25903422

Architecture of the Saccharomyces cerevisiae SAGA transcription coactivator complex

PubMed Central

Han, Yan; Luo, Jie; Ranish, Jeffrey; Hahn, Steven

2014-01-01

The conserved transcription coactivator SAGA is comprised of several modules that are involved in activator binding, TBP binding, histone acetylation (HAT) and deubiquitination (DUB). Crosslinking and mass spectrometry, together with genetic and biochemical analyses, were used to determine the molecular architecture of the SAGA-TBP complex. We find that the SAGA Taf and Taf-like subunits form a TFIID-like core complex at the center of SAGA that makes extensive interactions with all other SAGA modules. SAGA-TBP binding involves a network of interactions between subunits Spt3, Spt8, Spt20, and Spt7. The HAT and DUB modules are in close proximity, and the DUB module modestly stimulates HAT function. The large activator-binding subunit Tra1 primarily connects to the TFIID-like core via its FAT domain. These combined results were used to derive a model for the arrangement of the SAGA subunits and its interactions with TBP. Our results provide new insight into SAGA function in gene regulation, its structural similarity with TFIID, and functional interactions between the SAGA modules. PMID:25216679

Cas5d Protein Processes Pre-crRNA and Assembles into a Cascade-like Interference Complex in Subtype I-C/Dvulg CRISPR-Cas System

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

Nam, Ki Hyun; Haitjema, Charles; Liu, Xueqi

Clustered regularly interspaced short palindromic repeats (CRISPRs), together with an operon of CRISPR-associated (Cas) proteins, form an RNA-based prokaryotic immune system against exogenous genetic elements. Cas5 family proteins are found in several type I CRISPR-Cas systems. Here, we report the molecular function of subtype I-C/Dvulg Cas5d from Bacillus halodurans. We show that Cas5d cleaves pre-crRNA into unit length by recognizing both the hairpin structure and the 3 single stranded sequence in the CRISPR repeat region. Cas5d structure reveals a ferredoxin domain-based architecture and a catalytic triad formed by Y46, K116, and H117 residues. We further show that after pre-crRNA processing,more » Cas5d assembles with crRNA, Csd1, and Csd2 proteins to form a multi-sub-unit interference complex similar to Escherichia coli Cascade (CRISPR-associated complex for antiviral defense) in architecture. Our results suggest that formation of a crRNA-presenting Cascade-like complex is likely a common theme among type I CRISPR subtypes.« less

Autonomous control systems: applications to remote sensing and image processing

NASA Astrophysics Data System (ADS)

Jamshidi, Mohammad

2001-11-01

One of the main challenges of any control (or image processing) paradigm is being able to handle complex systems under unforeseen uncertainties. A system may be called complex here if its dimension (order) is too high and its model (if available) is nonlinear, interconnected, and information on the system is uncertain such that classical techniques cannot easily handle the problem. Examples of complex systems are power networks, space robotic colonies, national air traffic control system, and integrated manufacturing plant, the Hubble Telescope, the International Space Station, etc. Soft computing, a consortia of methodologies such as fuzzy logic, neuro-computing, genetic algorithms and genetic programming, has proven to be powerful tools for adding autonomy and semi-autonomy to many complex systems. For such systems the size of soft computing control architecture will be nearly infinite. In this paper new paradigms using soft computing approaches are utilized to design autonomous controllers and image enhancers for a number of application areas. These applications are satellite array formations for synthetic aperture radar interferometry (InSAR) and enhancement of analog and digital images.

Defining the landscape of adaptive genetic diversity.

PubMed

Eckert, Andrew J; Dyer, Rodney J

2012-06-01

Whether they are used to describe fitness, genome architecture or the spatial distribution of environmental variables, the concept of a landscape has figured prominently in our collective reasoning. The tradition of landscapes in evolutionary biology is one of fitness mapped onto axes defined by phenotypes or molecular sequence states. The characteristics of these landscapes depend on natural selection, which is structured across both genomic and environmental landscapes, and thus, the bridge among differing uses of the landscape concept (i.e. metaphorically or literally) is that of an adaptive phenotype and its distribution across geographical landscapes in relation to selective pressures. One of the ultimate goals of evolutionary biology should thus be to construct fitness landscapes in geographical space. Natural plant populations are ideal systems with which to explore the feasibility of attaining this goal, because much is known about the quantitative genetic architecture of complex traits for many different plant species. What is less known are the molecular components of this architecture. In this issue of Molecular Ecology, Parchman et al. (2012) pioneer one of the first truly genome-wide association studies in a tree that moves us closer to this form of mechanistic understanding for an adaptive phenotype in natural populations of lodgepole pine (Pinus contorta Dougl. ex Loud.). © 2012 Blackwell Publishing Ltd.

Failure to Replicate a Genetic Association May Provide Important Clues About Genetic Architecture

PubMed Central

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

Electrophysiological Endophenotypes for Schizophrenia

PubMed Central

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

2016-01-01

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

The Genetics of Ischemic Heart Disease: From Current Knowledge to Clinical Implications.

PubMed

Elosua, Roberto; Sayols-Baixeras, Sergi

2017-09-01

Ischemic heart disease continues to cause high morbidity and mortality. Its prevalence is expected to increase due to population aging, and its prevention is a major goal of health policies. The risk of developing ischemic heart disease is related to a complex interplay between genetic, environmental, and lifestyle factors. In the last decade, considerable progress has been made in knowledge of the genetic architecture of this disease. This narrative review provides an overview of current knowledge of the genetics of ischemic heart disease and of its translation to clinical practice: identification of new therapeutic targets, assessment of the causal relationship between biomarkers and disease, improved risk prediction, and identification of responders and nonresponders to specific drugs (pharmacogenomics). Copyright © 2017 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

Breaking barriers in the genomics and pharmacogenetics of drug addiction

PubMed Central

Ho, MK; Goldman, D; Heinz, A; Kaprio, J; Kreek, MJ; Li, MD; Munafò, MR; Tyndale, RF

2013-01-01

Drug addictions remain a substantial health issue, with limited treatment options currently available. Despite considerable advances in the understanding of our genetic architecture, the genetic underpinning of complex disorders remains elusive. Numerous candidate genes have been implicated in the etiology and response to treatment for different addictions based on our current understanding of the neurobiology. Genome-wide association studies have also provided novel targets. However, replication of these studies is often lacking which complicates interpretation; this will improve as issues such as phenotypic characterization, the apparent “missing heritability”, the identification of functional variants, and possible gene-environment interactions are addressed. In addition, there is growing evidence that genetic information can be useful for refining the choice of addiction treatment. As genetic testing becomes more common in the practice of medicine, a variety of ethical and practical challenges, some of which are unique to drug addiction, will also need to be considered. PMID:20981002

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

PubMed

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

2011-01-01

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

The Genetics of Autism: Key Issues, Recent Findings and Clinical Implications

PubMed Central

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

An Evolutionary Perspective on Epistasis and the Missing Heritability

PubMed Central

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

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

Exploring Relationships between Canopy Architecture, Light Distribution, and Photosynthesis in Contrasting Rice Genotypes Using 3D Canopy Reconstruction

PubMed Central

Burgess, Alexandra J.; Retkute, Renata; Herman, Tiara; Murchie, Erik H.

2017-01-01

The arrangement of leaf material is critical in determining the light environment, and subsequently the photosynthetic productivity of complex crop canopies. However, links between specific canopy architectural traits and photosynthetic productivity across a wide genetic background are poorly understood for field grown crops. The architecture of five genetically diverse rice varieties—four parental founders of a multi-parent advanced generation intercross (MAGIC) population plus a high yielding Philippine variety (IR64)—was captured at two different growth stages using a method for digital plant reconstruction based on stereocameras. Ray tracing was employed to explore the effects of canopy architecture on the resulting light environment in high-resolution, whilst gas exchange measurements were combined with an empirical model of photosynthesis to calculate an estimated carbon gain and total light interception. To further test the impact of different dynamic light patterns on photosynthetic properties, an empirical model of photosynthetic acclimation was employed to predict the optimal light-saturated photosynthesis rate (Pmax) throughout canopy depth, hypothesizing that light is the sole determinant of productivity in these conditions. First, we show that a plant type with steeper leaf angles allows more efficient penetration of light into lower canopy layers and this, in turn, leads to a greater photosynthetic potential. Second the predicted optimal Pmax responds in a manner that is consistent with fractional interception and leaf area index across this germplasm. However, measured Pmax, especially in lower layers, was consistently higher than the optimal Pmax indicating factors other than light determine photosynthesis profiles. Lastly, varieties with more upright architecture exhibit higher maximum quantum yield of photosynthesis indicating a canopy-level impact on photosynthetic efficiency. PMID:28567045

Scale-dependent genetic structure of the Idaho giant salamander (Dicamptodon aterrimus) in stream networks

Treesearch

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...

Prediction of Aerodynamic Coefficient using Genetic Algorithm Optimized Neural Network for Sparse Data

NASA Technical Reports Server (NTRS)

Rajkumar, T.; Bardina, Jorge; Clancy, Daniel (Technical Monitor)

2002-01-01

Wind tunnels use scale models to characterize aerodynamic coefficients, Wind tunnel testing can be slow and costly due to high personnel overhead and intensive power utilization. Although manual curve fitting can be done, it is highly efficient to use a neural network to define the complex relationship between variables. Numerical simulation of complex vehicles on the wide range of conditions required for flight simulation requires static and dynamic data. Static data at low Mach numbers and angles of attack may be obtained with simpler Euler codes. Static data of stalled vehicles where zones of flow separation are usually present at higher angles of attack require Navier-Stokes simulations which are costly due to the large processing time required to attain convergence. Preliminary dynamic data may be obtained with simpler methods based on correlations and vortex methods; however, accurate prediction of the dynamic coefficients requires complex and costly numerical simulations. A reliable and fast method of predicting complex aerodynamic coefficients for flight simulation I'S presented using a neural network. The training data for the neural network are derived from numerical simulations and wind-tunnel experiments. The aerodynamic coefficients are modeled as functions of the flow characteristics and the control surfaces of the vehicle. The basic coefficients of lift, drag and pitching moment are expressed as functions of angles of attack and Mach number. The modeled and training aerodynamic coefficients show good agreement. This method shows excellent potential for rapid development of aerodynamic models for flight simulation. Genetic Algorithms (GA) are used to optimize a previously built Artificial Neural Network (ANN) that reliably predicts aerodynamic coefficients. Results indicate that the GA provided an efficient method of optimizing the ANN model to predict aerodynamic coefficients. The reliability of the ANN using the GA includes prediction of aerodynamic coefficients to an accuracy of 110% . In our problem, we would like to get an optimized neural network architecture and minimum data set. This has been accomplished within 500 training cycles of a neural network. After removing training pairs (outliers), the GA has produced much better results. The neural network constructed is a feed forward neural network with a back propagation learning mechanism. The main goal has been to free the network design process from constraints of human biases, and to discover better forms of neural network architectures. The automation of the network architecture search by genetic algorithms seems to have been the best way to achieve this goal.

Potential and limits to unravel the genetic architecture and predict the variation of Fusarium head blight resistance in European winter wheat (Triticum aestivum L.).

PubMed

Jiang, Y; Zhao, Y; Rodemann, B; Plieske, J; Kollers, S; Korzun, V; Ebmeyer, E; Argillier, O; Hinze, M; Ling, J; Röder, M S; Ganal, M W; Mette, M F; Reif, J C

2015-03-01

Genome-wide mapping approaches in diverse populations are powerful tools to unravel the genetic architecture of complex traits. The main goals of our study were to investigate the potential and limits to unravel the genetic architecture and to identify the factors determining the accuracy of prediction of the genotypic variation of Fusarium head blight (FHB) resistance in wheat (Triticum aestivum L.) based on data collected with a diverse panel of 372 European varieties. The wheat lines were phenotyped in multi-location field trials for FHB resistance and genotyped with 782 simple sequence repeat (SSR) markers, and 9k and 90k single-nucleotide polymorphism (SNP) arrays. We applied genome-wide association mapping in combination with fivefold cross-validations and observed surprisingly high accuracies of prediction for marker-assisted selection based on the detected quantitative trait loci (QTLs). Using a random sample of markers not selected for marker-trait associations revealed only a slight decrease in prediction accuracy compared with marker-based selection exploiting the QTL information. The same picture was confirmed in a simulation study, suggesting that relatedness is a main driver of the accuracy of prediction in marker-assisted selection of FHB resistance. When the accuracy of prediction of three genomic selection models was contrasted for the three marker data sets, no significant differences in accuracies among marker platforms and genomic selection models were observed. Marker density impacted the accuracy of prediction only marginally. Consequently, genomic selection of FHB resistance can be implemented most cost-efficiently based on low- to medium-density SNP arrays.

Architecture of human translation initiation factor 3

PubMed Central

Querol-Audi, Jordi; Sun, Chaomin; Vogan, Jacob M.; Smith, Duane; Gu, Yu; Cate, Jamie; Nogales, Eva

2013-01-01

SUMMARY Eukaryotic translation initiation factor 3 (eIF3) plays a central role in protein synthesis by organizing the formation of the 43S preinitiation complex. Using genetic tag visualization by electron microscopy, we reveal the molecular organization of ten human eIF3 subunits, including an octameric core. The structure of eIF3 bears a close resemblance to that of the proteasome lid, with a conserved spatial organization of eight core subunits containing PCI and MPN domains that coordinate functional interactions in both complexes. We further show that eIF3 subunits a and c interact with initiation factors eIF1 and eIF1A, which control the stringency of start codon selection. Finally, we find that subunit j, which modulates messenger RNA interactions with the small ribosomal subunit, makes multiple independent interactions with the eIF3 octameric core. These results highlight the conserved architecture of eIF3 and how it scaffolds key factors that control translation initiation in higher eukaryotes, including humans. PMID:23623729

Genetic-based prediction of disease traits: prediction is very difficult, especially about the future†

PubMed Central

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

System design in an evolving system-of-systems architecture and concept of operations

NASA Astrophysics Data System (ADS)

Rovekamp, Roger N., Jr.

Proposals for space exploration architectures have increased in complexity and scope. Constituent systems (e.g., rovers, habitats, in-situ resource utilization facilities, transfer vehicles, etc) must meet the needs of these architectures by performing in multiple operational environments and across multiple phases of the architecture's evolution. This thesis proposes an approach for using system-of-systems engineering principles in conjunction with system design methods (e.g., Multi-objective optimization, genetic algorithms, etc) to create system design options that perform effectively at both the system and system-of-systems levels, across multiple concepts of operations, and over multiple architectural phases. The framework is presented by way of an application problem that investigates the design of power systems within a power sharing architecture for use in a human Lunar Surface Exploration Campaign. A computer model has been developed that uses candidate power grid distribution solutions for a notional lunar base. The agent-based model utilizes virtual control agents to manage the interactions of various exploration and infrastructure agents. The philosophy behind the model is based both on lunar power supply strategies proposed in literature, as well as on the author's own approaches for power distribution strategies of future lunar bases. In addition to proposing a framework for system design, further implications of system-of-systems engineering principles are briefly explored, specifically as they relate to producing more robust cross-cultural system-of-systems architecture solutions.

Molecular basis of angiosperm tree architecture.

PubMed

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.

Failure of replicating the association between hippocampal volume and 3 single-nucleotide polymorphisms identified from the European genome-wide association study in Asian populations.

PubMed

Li, Ming; Ohi, Kazutaka; Chen, Chunhui; He, Qinghua; Liu, Jie-Wei; Chen, Chuansheng; Luo, Xiong-Jian; Dong, Qi; Hashimoto, Ryota; Su, Bing

2014-12-01

Hippocampal volume is a key brain structure for learning ability and memory process, and hippocampal atrophy is a recognized biological marker of Alzheimer's disease. However, the genetic bases of hippocampal volume are still unclear although it is a heritable trait. Genome-wide association studies (GWASs) on hippocampal volume have implicated several significantly associated genetic variants in Europeans. Here, to test the contributions of these GWASs identified genetic variants to hippocampal volume in different ethnic populations, we screened the GWAS-identified candidate single-nucleotide polymorphisms in 3 independent healthy Asian brain imaging samples (a total of 990 subjects). The results showed that none of these single-nucleotide polymorphisms were associated with hippocampal volume in either individual or combined Asian samples. The replication results suggested a complexity of genetic architecture for hippocampal volume and potential genetic heterogeneity between different ethnic populations. Copyright © 2014 Elsevier Inc. All rights reserved.

Reveal, A General Reverse Engineering Algorithm for Inference of Genetic Network Architectures

NASA Technical Reports Server (NTRS)

Liang, Shoudan; Fuhrman, Stefanie; Somogyi, Roland

1998-01-01

Given the immanent gene expression mapping covering whole genomes during development, health and disease, we seek computational methods to maximize functional inference from such large data sets. Is it possible, in principle, to completely infer a complex regulatory network architecture from input/output patterns of its variables? We investigated this possibility using binary models of genetic networks. Trajectories, or state transition tables of Boolean nets, resemble time series of gene expression. By systematically analyzing the mutual information between input states and output states, one is able to infer the sets of input elements controlling each element or gene in the network. This process is unequivocal and exact for complete state transition tables. We implemented this REVerse Engineering ALgorithm (REVEAL) in a C program, and found the problem to be tractable within the conditions tested so far. For n = 50 (elements) and k = 3 (inputs per element), the analysis of incomplete state transition tables (100 state transition pairs out of a possible 10(exp 15)) reliably produced the original rule and wiring sets. While this study is limited to synchronous Boolean networks, the algorithm is generalizable to include multi-state models, essentially allowing direct application to realistic biological data sets. The ability to adequately solve the inverse problem may enable in-depth analysis of complex dynamic systems in biology and other fields.

The chromosome 2p21 region harbors a complex genetic architecture for association with risk for renal cell carcinoma

PubMed Central

Han, Summer S.; Yeager, Meredith; Moore, Lee E.; Wei, Ming-Hui; Pfeiffer, Ruth; Toure, Ousmane; Purdue, Mark P.; Johansson, Mattias; Scelo, Ghislaine; Chung, Charles C.; Gaborieau, Valerie; Zaridze, David; Schwartz, Kendra; Szeszenia-Dabrowska, Neonilia; Davis, Faith; Bencko, Vladimir; Colt, Joanne S.; Janout, Vladimir; Matveev, Vsevolod; Foretova, Lenka; Mates, Dana; Navratilova, M.; Boffetta, Paolo; Berg, Christine D.; Grubb, Robert L.; Stevens, Victoria L.; Thun, Michael J.; Diver, W. Ryan; Gapstur, Susan M.; Albanes, Demetrius; Weinstein, Stephanie J.; Virtamo, Jarmo; Burdett, Laurie; Brisuda, Antonin; McKay, James D.; Fraumeni, Joseph F.; Chatterjee, Nilanjan; Rosenberg, Philip S.; Rothman, Nathaniel; Brennan, Paul; Chow, Wong-Ho; Tucker, Margaret A.; Chanock, Stephen J.; Toro, Jorge R.

2012-01-01

In follow-up of a recent genome-wide association study (GWAS) that identified a locus in chromosome 2p21 associated with risk for renal cell carcinoma (RCC), we conducted a fine mapping analysis of a 120 kb region that includes EPAS1. We genotyped 59 tagged common single-nucleotide polymorphisms (SNPs) in 2278 RCC and 3719 controls of European background and observed a novel signal for rs9679290 [P = 5.75 × 10−8, per-allele odds ratio (OR) = 1.27, 95% confidence interval (CI): 1.17–1.39]. Imputation of common SNPs surrounding rs9679290 using HapMap 3 and 1000 Genomes data yielded two additional signals, rs4953346 (P = 4.09 × 10−14) and rs12617313 (P = 7.48 × 10−12), both highly correlated with rs9679290 (r2 > 0.95), but interestingly not correlated with the two SNPs reported in the GWAS: rs11894252 and rs7579899 (r2 < 0.1 with rs9679290). Genotype analysis of rs12617313 confirmed an association with RCC risk (P = 1.72 × 10−9, per-allele OR = 1.28, 95% CI: 1.18–1.39) In conclusion, we report that chromosome 2p21 harbors a complex genetic architecture for common RCC risk variants. PMID:22113997

Association of polygenic risk for major psychiatric illness with subcortical volumes and white matter integrity in UK Biobank

PubMed Central

Reus, L. M.; Shen, X.; Gibson, J.; Wigmore, E.; Ligthart, L.; Adams, M. J.; Davies, G.; Cox, S. R.; Hagenaars, S. P.; Bastin, M. E.; Deary, I. J.; Whalley, H. C.; McIntosh, A. M.

2017-01-01

Major depressive disorder (MDD), schizophrenia (SCZ) and bipolar disorder (BP) are common, disabling and heritable psychiatric diseases with a complex overlapping polygenic architecture. Individuals with these disorders, as well as their unaffected relatives, show widespread structural differences in corticostriatal and limbic networks. Structural variation in many of these brain regions is also heritable and polygenic but whether their genetic architecture overlaps with that of major psychiatric disorders is unknown. We sought to address this issue by examining the impact of polygenic risk of MDD, SCZ, and BP on subcortical brain volumes and white matter (WM) microstructure in a large single sample of neuroimaging data; the UK Biobank Imaging study. The first release of UK Biobank imaging data comprised participants with overlapping genetic data and subcortical volumes (N = 978) and WM measures (N = 816). The calculation of polygenic risk scores was based on genome-wide association study results generated by the Psychiatric Genomics Consortium. Our findings indicated no statistically significant associations between either subcortical volumes or WM microstructure, and polygenic risk for MDD, SCZ or BP. These findings suggest that subcortical brain volumes and WM microstructure may not be closely linked to the genetic mechanisms of major psychiatric disorders. PMID:28186152

Association of polygenic risk for major psychiatric illness with subcortical volumes and white matter integrity in UK Biobank.

PubMed

Reus, L M; Shen, X; Gibson, J; Wigmore, E; Ligthart, L; Adams, M J; Davies, G; Cox, S R; Hagenaars, S P; Bastin, M E; Deary, I J; Whalley, H C; McIntosh, A M

2017-02-10

Major depressive disorder (MDD), schizophrenia (SCZ) and bipolar disorder (BP) are common, disabling and heritable psychiatric diseases with a complex overlapping polygenic architecture. Individuals with these disorders, as well as their unaffected relatives, show widespread structural differences in corticostriatal and limbic networks. Structural variation in many of these brain regions is also heritable and polygenic but whether their genetic architecture overlaps with that of major psychiatric disorders is unknown. We sought to address this issue by examining the impact of polygenic risk of MDD, SCZ, and BP on subcortical brain volumes and white matter (WM) microstructure in a large single sample of neuroimaging data; the UK Biobank Imaging study. The first release of UK Biobank imaging data comprised participants with overlapping genetic data and subcortical volumes (N = 978) and WM measures (N = 816). The calculation of polygenic risk scores was based on genome-wide association study results generated by the Psychiatric Genomics Consortium. Our findings indicated no statistically significant associations between either subcortical volumes or WM microstructure, and polygenic risk for MDD, SCZ or BP. These findings suggest that subcortical brain volumes and WM microstructure may not be closely linked to the genetic mechanisms of major psychiatric disorders.

Gene flow in Prunus species in the context of novel trait risk assessment.

PubMed

Cici, S Zahra H; Van Acker, Rene C

2010-01-01

Prunus species are important commercial fruit (plums, apricot, peach and cherries), nut (almond) and ornamental trees cultivated broadly worldwide. This review compiles information from available literature on Prunus species in regard to gene flow and hybridization within this complex of species. The review serves as a resource for environmental risk assessment related to pollen mediated gene flow and the release of transgenic Prunus. It reveals that Prunus species, especially plums and cherries show high potential for transgene flow. A range of characteristics including; genetic diversity, genetic bridging capacity, inter- and intra-specific genetic compatibility, self sterility (in most species), high frequency of open pollination, insect assisted pollination, perennial nature, complex phenotypic architecture (canopy height, heterogeneous crown, number of flowers produced in an individual plant), tendency to escape from cultivation, and the existence of ornamental and road side Prunus species suggest that there is a tremendous and complicated ability for pollen mediated gene movement among Prunus species. Ploidy differences among Prunus species do not necessarily provide genetic segregation. The characteristics of Prunu s species highlight the complexity of maintaining coexistence between GM and non-GM Prunus if there were commercial production of GM Prunus species. The results of this review suggest that the commercialization of one GM Prunus species can create coexistence issues for commercial non-GM Prunus production. Despite advances in molecular markers and genetic analysis in agroecology, there remains limited information on the ecological diversity, metapopulation nature, population dynamics, and direct measures of gene flow among different subgenera represented in the Prunus genus. Robust environmental impact, biosafety and coexistence assessments for GM Prunus species will require better understanding of the mechanisms of gene flow and hybridization among species within the Prunus species complex. © ISBR, EDP Sciences, 2011.

Architecture of the wood-wide web: Rhizopogon spp. genets link multiple Douglas-fir cohorts.

PubMed

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.

Reliability and Productivity Modeling for the Optimization of Separated Spacecraft Interferometers

NASA Technical Reports Server (NTRS)

Kenny, Sean (Technical Monitor); Wertz, Julie

2002-01-01

As technological systems grow in capability, they also grow in complexity. Due to this complexity, it is no longer possible for a designer to use engineering judgement to identify the components that have the largest impact on system life cycle metrics, such as reliability, productivity, cost, and cost effectiveness. One way of identifying these key components is to build quantitative models and analysis tools that can be used to aid the designer in making high level architecture decisions. Once these key components have been identified, two main approaches to improving a system using these components exist: add redundancy or improve the reliability of the component. In reality, the most effective approach to almost any system will be some combination of these two approaches, in varying orders of magnitude for each component. Therefore, this research tries to answer the question of how to divide funds, between adding redundancy and improving the reliability of components, to most cost effectively improve the life cycle metrics of a system. While this question is relevant to any complex system, this research focuses on one type of system in particular: Separate Spacecraft Interferometers (SSI). Quantitative models are developed to analyze the key life cycle metrics of different SSI system architectures. Next, tools are developed to compare a given set of architectures in terms of total performance, by coupling different life cycle metrics together into one performance metric. Optimization tools, such as simulated annealing and genetic algorithms, are then used to search the entire design space to find the "optimal" architecture design. Sensitivity analysis tools have been developed to determine how sensitive the results of these analyses are to uncertain user defined parameters. Finally, several possibilities for the future work that could be done in this area of research are presented.

Wild worm embryogenesis harbors ubiquitous polygenic modifier variation.

PubMed

Paaby, Annalise B; White, Amelia G; Riccardi, David D; Gunsalus, Kristin C; Piano, Fabio; Rockman, Matthew V

2015-08-22

Embryogenesis is an essential and stereotypic process that nevertheless evolves among species. Its essentiality may favor the accumulation of cryptic genetic variation (CGV) that has no effect in the wild-type but that enhances or suppresses the effects of rare disruptions to gene function. Here, we adapted a classical modifier screen to interrogate the alleles segregating in natural populations of Caenorhabditis elegans: we induced gene knockdowns and used quantitative genetic methodology to examine how segregating variants modify the penetrance of embryonic lethality. Each perturbation revealed CGV, indicating that wild-type genomes harbor myriad genetic modifiers that may have little effect individually but which in aggregate can dramatically influence penetrance. Phenotypes were mediated by many modifiers, indicating high polygenicity, but the alleles tend to act very specifically, indicating low pleiotropy. Our findings demonstrate the extent of conditional functionality in complex trait architecture.

Genetic Constructor: An Online DNA Design Platform.

PubMed

Bates, Maxwell; Lachoff, Joe; Meech, Duncan; Zulkower, Valentin; Moisy, Anaïs; Luo, Yisha; Tekotte, Hille; Franziska Scheitz, Cornelia Johanna; Khilari, Rupal; Mazzoldi, Florencio; Chandran, Deepak; Groban, Eli

2017-12-15

Genetic Constructor is a cloud Computer Aided Design (CAD) application developed to support synthetic biologists from design intent through DNA fabrication and experiment iteration. The platform allows users to design, manage, and navigate complex DNA constructs and libraries, using a new visual language that focuses on functional parts abstracted from sequence. Features like combinatorial libraries and automated primer design allow the user to separate design from construction by focusing on functional intent, and design constraints aid iterative refinement of designs. A plugin architecture enables contributions from scientists and coders to leverage existing powerful software and connect to DNA foundries. The software is easily accessible and platform agnostic, free for academics, and available in an open-source community edition. Genetic Constructor seeks to democratize DNA design, manufacture, and access to tools and services from the synthetic biology community.

Genetic Architecture and Molecular Networks Underlying Leaf Thickness in Desert-Adapted Tomato Solanum pennellii1[OPEN

PubMed Central

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

High-Density Genetic Mapping Identifies New Susceptibility Variants in Sarcoidosis Phenotypes and Shows Genomic-driven Phenotypic Differences

PubMed Central

Ronninger, Marcus; Shchetynsky, Klementy; Franke, Andre; Nöthen, Markus M.; Müller-Quernheim, Joachim; Schreiber, Stefan; Adrianto, Indra; Karakaya, Bekir; van Moorsel, Coline H. M.; Navratilova, Zdenka; Kolek, Vitezslav; Rybicki, Benjamin A.; Iannuzzi, Michael C.; Petrek, Martin; Grutters, Jan C.; Montgomery, Courtney; Fischer, Annegret; Eklund, Anders; Padyukov, Leonid; Grunewald, Johan

2016-01-01

Rationale: Sarcoidosis is a multisystem disease of unknown cause. Löfgren’s syndrome (LS) is a characteristic subgroup of sarcoidosis that is associated with a good prognosis in sarcoidosis. However, little is known about its genetic architecture or its broader phenotype, non-LS sarcoidosis. Objectives: To address the genetic architecture of sarcoidosis phenotypes, LS and non-LS. Methods: An association study in a white Swedish cohort of 384 LS, 664 non-LS, and 2,086 control subjects, totaling 3,134 subjects using a fine-mapping genotyping platform was conducted. Replication was performed in four independent cohorts, three of white European descent (Germany, n = 4,975; the Netherlands, n = 613; and Czech Republic, n = 521), and one of black African descent (United States, n = 1,657), totaling 7,766 subjects. Measurements and Main Results: A total of 727 LS-associated variants expanding throughout the extended major histocompatibility complex (MHC) region and 68 non-LS–associated variants located in the MHC class II region were identified and confirmed. A shared overlap between LS and non-LS defined by 17 variants located in the MHC class II region was found. Outside the MHC region, two LS-associated loci, in ADCY3 and between CSMD1 and MCPH1, were observed and replicated. Conclusions: Comprehensive and integrative analyses of genetics, transcription, and pathway modeling on LS and non-LS indicates that these sarcoidosis phenotypes have different genetic susceptibility, genomic distributions, and cellular activities, suggesting distinct molecular mechanisms in pathways related to immune response with a common region. PMID:26651848

Describing the genetic architecture of epilepsy through heritability analysis.

PubMed

Speed, Doug; O'Brien, Terence J; Palotie, Aarno; Shkura, Kirill; Marson, Anthony G; Balding, David J; Johnson, Michael R

2014-10-01

Epilepsy is a disease with substantial missing heritability; despite its high genetic component, genetic association studies have had limited success detecting common variants which influence susceptibility. In this paper, we reassess the role of common variants on epilepsy using extensions of heritability analysis. Our data set consists of 1258 UK patients with epilepsy, of which 958 have focal epilepsy, and 5129 population control subjects, with genotypes recorded for over 4 million common single nucleotide polymorphisms. Firstly, we show that on the liability scale, common variants collectively explain at least 26% (standard deviation 5%) of phenotypic variation for all epilepsy and 27% (standard deviation 5%) for focal epilepsy. Secondly we provide a new method for estimating the number of causal variants for complex traits; when applied to epilepsy, our most optimistic estimate suggests that at least 400 variants influence disease susceptibility, with potentially many thousands. Thirdly, we use bivariate analysis to assess how similar the genetic architecture of focal epilepsy is to that of non-focal epilepsy; we demonstrate both significant differences (P = 0.004) and significant similarities (P = 0.01) between the two subtypes, indicating that although the clinical definition of focal epilepsy does identify a genetically distinct epilepsy subtype, there is also scope to improve the classification of epilepsy by incorporating genotypic information. Lastly, we investigate the potential value in using genetic data to diagnose epilepsy following a single epileptic seizure; we find that a prediction model explaining 10% of phenotypic variation could have clinical utility for deciding which single-seizure individuals are likely to benefit from immediate anti-epileptic drug therapy. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain.

Mitochondrial-Nuclear Epistasis: Implications for Human Aging and Longevity

PubMed Central

Tranah, Gregory

2010-01-01

There is substantial evidence that mitochondria are involved in the aging process. Mitochondrial function requires the coordinated expression of hundreds of nuclear genes and a few dozen mitochondrial genes, many of which have been associated with either extended or shortened life span. Impaired mitochondrial function resulting from mtDNA and nuclear DNA variation is likely to contribute to an imbalance in cellular energy homeostasis, increased vulnerability to oxidative stress, and an increased rate of cellular senescence and aging. The complex genetic architecture of mitochondria suggests that there may be an equally complex set of gene interactions (epistases) involving genetic variation in the nuclear and mitochondrial genomes. Results from Drosophila suggest that the effects of mtDNA haplotypes on longevity vary among different nuclear allelic backgrounds, which could account for the inconsistent associations that have been observed between mitochondrial DNA (mtDNA) haplogroups and survival in humans. A diversity of pathways may influence the way mitochondria and nuclear – mitochondrial interactions modulate longevity, including: oxidative phosphorylation; mitochondrial uncoupling; antioxidant defenses; mitochondrial fission and fusion; and sirtuin regulation of mitochondrial genes. We hypothesize that aging and longevity, as complex traits having a significant genetic component, are likely to be controlled by nuclear gene variants interacting with both inherited and somatic mtDNA variability. PMID:20601194

Genetic basis of sexual dimorphism in the threespine stickleback Gasterosteus aculeatus

PubMed Central

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

Architecture of energy balance traits in emerging lines of the Collaborative Cross

PubMed Central

Aylor, David L.; Miller, Darla R.; Churchill, Gary A.; Chesler, Elissa J.; de Villena, Fernando Pardo-Manuel; Threadgill, David W.; Pomp, Daniel

2011-01-01

The potential utility of the Collaborative Cross (CC) mouse resource was evaluated to better understand complex traits related to energy balance. A primary focus was to examine if genetic diversity in emerging CC lines (pre-CC) would translate into equivalent phenotypic diversity. Second, we mapped quantitative trait loci (QTL) for 15 metabolism- and exercise-related phenotypes in this population. We evaluated metabolic and voluntary exercise traits in 176 pre-CC lines, revealing phenotypic variation often exceeding that seen across the eight founder strains from which the pre-CC was derived. Many phenotypic correlations existing within the founder strains were no longer significant in the pre-CC population, potentially representing reduced linkage disequilibrium (LD) of regions harboring multiple genes with effects on energy balance or disruption of genetic structure of extant inbred strains with substantial shared ancestry. QTL mapping revealed five significant and eight suggestive QTL for body weight (Chr 4, 7.54 Mb; CI 3.32–10.34 Mb; Bwq14), body composition, wheel running (Chr 16, 33.2 Mb; CI 32.5–38.3 Mb), body weight change in response to exercise (1: Chr 6, 77.7Mb; CI 72.2–83.4 Mb and 2: Chr 6, 42.8 Mb; CI 39.4–48.1 Mb), and food intake during exercise (Chr 12, 85.1 Mb; CI 82.9–89.0 Mb). Some QTL overlapped with previously mapped QTL for similar traits, whereas other QTL appear to represent novel loci. These results suggest that the CC will be a powerful, high-precision tool for examining the genetic architecture of complex traits such as those involved in regulation of energy balance. PMID:21427413

The Genetic Architecture of Noise-Induced Hearing Loss: Evidence for a Gene-by-Environment Interaction.

PubMed

Lavinsky, Joel; Ge, Marshall; Crow, Amanda L; Pan, Calvin; Wang, Juemei; Salehi, Pezhman; Myint, Anthony; Eskin, Eleazar; Allayee, Hooman; Lusis, Aldons J; Friedman, Rick A

2016-10-13

The discovery of environmentally specific genetic effects is crucial to the understanding of complex traits, such as susceptibility to noise-induced hearing loss (NIHL). We describe the first genome-wide association study (GWAS) for NIHL in a large and well-characterized population of inbred mouse strains, known as the Hybrid Mouse Diversity Panel (HMDP). We recorded auditory brainstem response (ABR) thresholds both pre and post 2-hr exposure to 10-kHz octave band noise at 108 dB sound pressure level in 5-6-wk-old female mice from the HMDP (4-5 mice/strain). From the observation that NIHL susceptibility varied among the strains, we performed a GWAS with correction for population structure and mapped a locus on chromosome 6 that was statistically significantly associated with two adjacent frequencies. We then used a "genetical genomics" approach that included the analysis of cochlear eQTLs to identify candidate genes within the GWAS QTL. In order to validate the gene-by-environment interaction, we compared the effects of the postnoise exposure locus with that from the same unexposed strains. The most significant SNP at chromosome 6 (rs37517079) was associated with noise susceptibility, but was not significant at the same frequencies in our unexposed study. These findings demonstrate that the genetic architecture of NIHL is distinct from that of unexposed hearing levels and provide strong evidence for gene-by-environment interactions in NIHL. Copyright © 2016 Lavinsky et al.

Trans-ethnic Meta-analysis and Functional Annotation Illuminates the Genetic Architecture of Fasting Glucose and Insulin.

PubMed

Liu, Ching-Ti; Raghavan, Sridharan; Maruthur, Nisa; Kabagambe, Edmond Kato; Hong, Jaeyoung; Ng, Maggie C Y; Hivert, Marie-France; Lu, Yingchang; An, Ping; Bentley, Amy R; Drolet, Anne M; Gaulton, Kyle J; Guo, Xiuqing; Armstrong, Loren L; Irvin, Marguerite R; Li, Man; Lipovich, Leonard; Rybin, Denis V; Taylor, Kent D; Agyemang, Charles; Palmer, Nicholette D; Cade, Brian E; Chen, Wei-Min; Dauriz, Marco; Delaney, Joseph A C; Edwards, Todd L; Evans, Daniel S; Evans, Michele K; Lange, Leslie A; Leong, Aaron; Liu, Jingmin; Liu, Yongmei; Nayak, Uma; Patel, Sanjay R; Porneala, Bianca C; Rasmussen-Torvik, Laura J; Snijder, Marieke B; Stallings, Sarah C; Tanaka, Toshiko; Yanek, Lisa R; Zhao, Wei; Becker, Diane M; Bielak, Lawrence F; Biggs, Mary L; Bottinger, Erwin P; Bowden, Donald W; Chen, Guanjie; Correa, Adolfo; Couper, David J; Crawford, Dana C; Cushman, Mary; Eicher, John D; Fornage, Myriam; Franceschini, Nora; Fu, Yi-Ping; Goodarzi, Mark O; Gottesman, Omri; Hara, Kazuo; Harris, Tamara B; Jensen, Richard A; Johnson, Andrew D; Jhun, Min A; Karter, Andrew J; Keller, Margaux F; Kho, Abel N; Kizer, Jorge R; Krauss, Ronald M; Langefeld, Carl D; Li, Xiaohui; Liang, Jingling; Liu, Simin; Lowe, William L; Mosley, Thomas H; North, Kari E; Pacheco, Jennifer A; Peyser, Patricia A; Patrick, Alan L; Rice, Kenneth M; Selvin, Elizabeth; Sims, Mario; Smith, Jennifer A; Tajuddin, Salman M; Vaidya, Dhananjay; Wren, Mary P; Yao, Jie; Zhu, Xiaofeng; Ziegler, Julie T; Zmuda, Joseph M; Zonderman, Alan B; Zwinderman, Aeilko H; Adeyemo, Adebowale; Boerwinkle, Eric; Ferrucci, Luigi; Hayes, M Geoffrey; Kardia, Sharon L R; Miljkovic, Iva; Pankow, James S; Rotimi, Charles N; Sale, Michele M; Wagenknecht, Lynne E; Arnett, Donna K; Chen, Yii-Der Ida; Nalls, Michael A; Province, Michael A; Kao, W H Linda; Siscovick, David S; Psaty, Bruce M; Wilson, James G; Loos, Ruth J F; Dupuis, Josée; Rich, Stephen S; Florez, Jose C; Rotter, Jerome I; Morris, Andrew P; Meigs, James B

2016-07-07

Knowledge of the genetic basis of the type 2 diabetes (T2D)-related quantitative traits fasting glucose (FG) and insulin (FI) in African ancestry (AA) individuals has been limited. In non-diabetic subjects of AA (n = 20,209) and European ancestry (EA; n = 57,292), we performed trans-ethnic (AA+EA) fine-mapping of 54 established EA FG or FI loci with detailed functional annotation, assessed their relevance in AA individuals, and sought previously undescribed loci through trans-ethnic (AA+EA) meta-analysis. We narrowed credible sets of variants driving association signals for 22/54 EA-associated loci; 18/22 credible sets overlapped with active islet-specific enhancers or transcription factor (TF) binding sites, and 21/22 contained at least one TF motif. Of the 54 EA-associated loci, 23 were shared between EA and AA. Replication with an additional 10,096 AA individuals identified two previously undescribed FI loci, chrX FAM133A (rs213676) and chr5 PELO (rs6450057). Trans-ethnic analyses with regulatory annotation illuminate the genetic architecture of glycemic traits and suggest gene regulation as a target to advance precision medicine for T2D. Our approach to utilize state-of-the-art functional annotation and implement trans-ethnic association analysis for discovery and fine-mapping offers a framework for further follow-up and characterization of GWAS signals of complex trait loci. Copyright © 2016 American Society of Human Genetics. All rights reserved.

Genomic and Network Patterns of Schizophrenia Genetic Variation in Human Evolutionary Accelerated Regions

PubMed Central

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

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

DOE PAGES

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

2016-11-28

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

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

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

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

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

The mathematical limits of genetic prediction for complex chronic disease.

PubMed

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.

Implementation of Complex Biological Logic Circuits Using Spatially Distributed Multicellular Consortia

PubMed Central

Urrios, Arturo; de Nadal, Eulàlia; Solé, Ricard; Posas, Francesc

2016-01-01

Engineered synthetic biological devices have been designed to perform a variety of functions from sensing molecules and bioremediation to energy production and biomedicine. Notwithstanding, a major limitation of in vivo circuit implementation is the constraint associated to the use of standard methodologies for circuit design. Thus, future success of these devices depends on obtaining circuits with scalable complexity and reusable parts. Here we show how to build complex computational devices using multicellular consortia and space as key computational elements. This spatial modular design grants scalability since its general architecture is independent of the circuit’s complexity, minimizes wiring requirements and allows component reusability with minimal genetic engineering. The potential use of this approach is demonstrated by implementation of complex logical functions with up to six inputs, thus demonstrating the scalability and flexibility of this method. The potential implications of our results are outlined. PMID:26829588

Vestigialization of an Allosteric Switch: Genetic and Structural Mechanisms for the Evolution of Constitutive Activity in a Steroid Hormone Receptor

PubMed Central

Bridgham, Jamie T.; Keay, June; Ortlund, Eric A.; Thornton, Joseph W.

2014-01-01

An important goal in molecular evolution is to understand the genetic and physical mechanisms by which protein functions evolve and, in turn, to characterize how a protein's physical architecture influences its evolution. Here we dissect the mechanisms for an evolutionary shift in function in the mollusk ortholog of the steroid hormone receptors (SRs), a family of biologically essential transcription factors. In vertebrates, the activity of SRs allosterically depends on binding a hormonal ligand; in mollusks, however, the SR ortholog (called ER, because of high sequence similarity to vertebrate estrogen receptors) activates transcription in the absence of ligand and does not respond to steroid hormones. To understand how this shift in regulation evolved, we combined evolutionary, structural, and functional analyses. We first determined the X-ray crystal structure of the ER of the Pacific oyster Crassostrea gigas (CgER), and found that its ligand pocket is filled with bulky residues that prevent ligand occupancy. To understand the genetic basis for the evolution of mollusk ERs' unique functions, we resurrected an ancient SR progenitor and characterized the effect of historical amino acid replacements on its functions. We found that reintroducing just two ancient replacements from the lineage leading to mollusk ERs recapitulates the evolution of full constitutive activity and the loss of ligand activation. These substitutions stabilize interactions among key helices, causing the allosteric switch to become “stuck” in the active conformation and making activation independent of ligand binding. Subsequent changes filled the ligand pocket without further affecting activity; by degrading the allosteric switch, these substitutions vestigialized elements of the protein's architecture required for ligand regulation and made reversal to the ancestral function more complex. These findings show how the physical architecture of allostery enabled a few large-effect mutations to trigger a profound evolutionary change in the protein's function and shaped the genetics of evolutionary reversibility. PMID:24415950

Defeating the Warrior: genetic architecture of triticale resistance against a novel aggressive yellow rust race.

PubMed

Losert, Dominik; Maurer, Hans Peter; Leiser, Willmar L; Würschum, Tobias

2017-04-01

Genome-wide association mapping of resistance against the novel, aggressive 'Warrior' race of yellow rust in triticale revealed a genetic architecture with some medium-effect QTL and a quantitative component, which in combination confer high levels of resistance on both leaves and ears. Yellow rust is an important destructive fungal disease in small grain cereals and the exotic 'Warrior' race has recently conquered Europe. The aim of this study was to investigate the genetic architecture of yellow rust resistance in hexaploid winter triticale as the basis for a successful resistance breeding. To this end, a diverse panel of 919 genotypes was evaluated for yellow rust infection on leaves and ears in multi-location field trials and genotyped by genotyping-by-sequencing as well as for known Yr resistance loci. Genome-wide association mapping identified ten quantitative trait loci (QTL) for yellow rust resistance on the leaves and seven of these also for ear resistance. The total genotypic variance explained by the QTL amounted to 44.0% for leaf and 26.0% for ear resistance. The same three medium-effect QTL were identified for both traits on chromosomes 1B, 2B, and 7B. Interestingly, plants pyramiding the resistance allele of all three medium-effect QTL were generally most resistant, but constitute less than 5% of the investigated triticale breeding material. Nevertheless, a genome-wide prediction yielded a higher predictive ability than prediction based on these three QTL. Taken together, our results show that yellow rust resistance in winter triticale is genetically complex, including both medium-effect QTL as well as a quantitative resistance component. Resistance to the novel 'Warrior' race of this fungal pathogen is consequently best achieved by recurrent selection in the field based on identified resistant lines and can potentially be assisted by genomic approaches.

Simultaneous improvement of grain yield and protein content in durum wheat by different phenotypic indices and genomic selection.

PubMed

Rapp, M; Lein, V; Lacoudre, F; Lafferty, J; Müller, E; Vida, G; Bozhanova, V; Ibraliu, A; Thorwarth, P; Piepho, H P; Leiser, W L; Würschum, T; Longin, C F H

2018-06-01

Simultaneous improvement of protein content and grain yield by index selection is possible but its efficiency largely depends on the weighting of the single traits. The genetic architecture of these indices is similar to that of the primary traits. Grain yield and protein content are of major importance in durum wheat breeding, but their negative correlation has hampered their simultaneous improvement. To account for this in wheat breeding, the grain protein deviation (GPD) and the protein yield were proposed as targets for selection. The aim of this work was to investigate the potential of different indices to simultaneously improve grain yield and protein content in durum wheat and to evaluate their genetic architecture towards genomics-assisted breeding. To this end, we investigated two different durum wheat panels comprising 159 and 189 genotypes, which were tested in multiple field locations across Europe and genotyped by a genotyping-by-sequencing approach. The phenotypic analyses revealed significant genetic variances for all traits and heritabilities of the phenotypic indices that were in a similar range as those of grain yield and protein content. The GPD showed a high and positive correlation with protein content, whereas protein yield was highly and positively correlated with grain yield. Thus, selecting for a high GPD would mainly increase the protein content whereas a selection based on protein yield would mainly improve grain yield, but a combination of both indices allows to balance this selection. The genome-wide association mapping revealed a complex genetic architecture for all traits with most QTL having small effects and being detected only in one germplasm set, thus limiting the potential of marker-assisted selection for trait improvement. By contrast, genome-wide prediction appeared promising but its performance strongly depends on the relatedness between training and prediction sets.

The Genetic Diversity and Structure of Linkage Disequilibrium of the MTHFR Gene in Populations of Northern Eurasia.

PubMed

Trifonova, E A; Eremina, E R; Urnov, F D; Stepanov, V A

2012-01-01

The structure of the haplotypes and linkage disequilibrium (LD) of the methylenetetrahydrofolate reductase gene (MTHFR) in 9 population groups from Northern Eurasia and populations of the international HapMap project was investigated in the present study. The data suggest that the architecture of LD in the human genome is largely determined by the evolutionary history of populations; however, the results of phylogenetic and haplotype analyses seems to suggest that in fact there may be a common "old" mechanism for the formation of certain patterns of LD. Variability in the structure of LD and the level of diversity of MTHFRhaplotypes cause a certain set of tagSNPs with an established prognostic significance for each population. In our opinion, the results obtained in the present study are of considerable interest for understanding multiple genetic phenomena: namely, the association of interpopulation differences in the patterns of LD with structures possessing a genetic susceptibility to complex diseases, and the functional significance of the pleiotropicMTHFR gene effect. Summarizing the results of this study, a conclusion can be made that the genetic variability analysis with emphasis on the structure of LD in human populations is a powerful tool that can make a significant contribution to such areas of biomedical science as human evolutionary biology, functional genomics, genetics of complex diseases, and pharmacogenomics.

GWAS of human bitter taste perception identifies new loci and reveals additional complexity of bitter taste genetics.

PubMed

Ledda, Mirko; Kutalik, Zoltán; Souza Destito, Maria C; Souza, Milena M; Cirillo, Cintia A; Zamboni, Amabilene; Martin, Nathalie; Morya, Edgard; Sameshima, Koichi; Beckmann, Jacques S; le Coutre, Johannes; Bergmann, Sven; Genick, Ulrich K

2014-01-01

Human perception of bitterness displays pronounced interindividual variation. This phenotypic variation is mirrored by equally pronounced genetic variation in the family of bitter taste receptor genes. To better understand the effects of common genetic variations on human bitter taste perception, we conducted a genome-wide association study on a discovery panel of 504 subjects and a validation panel of 104 subjects from the general population of São Paulo in Brazil. Correction for general taste-sensitivity allowed us to identify a SNP in the cluster of bitter taste receptors on chr12 (10.88- 11.24 Mb, build 36.1) significantly associated (best SNP: rs2708377, P = 5.31 × 10(-13), r(2) = 8.9%, β = -0.12, s.e. = 0.016) with the perceived bitterness of caffeine. This association overlaps with-but is statistically distinct from-the previously identified SNP rs10772420 influencing the perception of quinine bitterness that falls in the same bitter taste cluster. We replicated this association to quinine perception (P = 4.97 × 10(-37), r(2) = 23.2%, β = 0.25, s.e. = 0.020) and additionally found the effect of this genetic locus to be concentration specific with a strong impact on the perception of low, but no impact on the perception of high concentrations of quinine. Our study, thus, furthers our understanding of the complex genetic architecture of bitter taste perception.

A two-locus model of spatially varying stabilizing or directional selection on a quantitative trait

PubMed Central

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.

PubMed

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.

Hierarchical nuclear and cytoplasmic genetic architectures for plant growth and defense within Arabidopsis.

PubMed

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.

Hierarchical Nuclear and Cytoplasmic Genetic Architectures for Plant Growth and Defense within Arabidopsis[C][W

PubMed Central

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

The Impact of Population Demography and Selection on the Genetic Architecture of Complex Traits

PubMed Central

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

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

PubMed

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

2016-11-01

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

Endophenotype Best Practices

PubMed Central

Iacono, William G.; Malone, Stephen M.; Vrieze, Scott I.

2016-01-01

This review examines the current state of electrophysiological endophenotype research and recommends best practices that are based on knowledge gleaned from the last decade of molecular genetic research with complex traits. Endophenotype research is being oversold for its potential to help discover psychopathology relevant genes using the types of small samples feasible for electrophysiological research. This is largely because the genetic architecture of endophenotypes appears to be very much like that of behavioral traits and disorders: they are complex, influenced by many variants (e.g., tens of thousands) within many genes, each contributing a very small effect. Out of over 40 electrophysiological endophenotypes covered by our review, only resting heart, a measure that has received scant advocacy as an endophenotype, emerges as an electrophysiological variable with verified associations with molecular genetic variants. To move the field forward, investigations designed to discover novel variants associated with endophenotypes will need extremely large samples best obtained by forming consortia and sharing data obtained from genome wide arrays. In addition, endophenotype research can benefit from successful molecular genetic studies of psychopathology by examining the degree to which these verified psychopathology-relevant variants are also associated with an endophenotype, and by using knowledge about the functional significance of these variants to generate new endophenotypes. Even without molecular genetic associations, endophenotypes still have value in studying the development of disorders in unaffected individuals at high genetic risk, constructing animal models, and gaining insight into neural mechanisms that are relevant to clinical disorder. PMID:27473600

A speed limit for evolution.

PubMed

Worden, R P

1995-09-07

An upper bound on the speed of evolution is derived. The bound concerns the amount of genetic information which is expressed in observable ways in various aspects of the phenotype. The genetic information expressed in some part of the phenotype of a species cannot increase faster than a given rate, determined by the selection pressure on that part. This rate is typically a small fraction of a bit per generation. Total expressed genetic information cannot increase faster than a species-specific rate--typically a few bits per generation. These bounds apply to all aspects of the phenotype, but are particularly relevant to cognition. As brains are highly complex, we expect large amounts of expressed genetic information in the brain--of the order of 100 kilobytes--yet evolutionary changes in brain genetic information are only a fraction of a bit per generation. This has important consequences for cognitive evolution. The limit implies that the human brain differs from the chimpanzee brain by at most 5 kilobytes of genetic design information. This is not enough to define a Language Acquisition Device, unless it depends heavily on pre-existing primate symbolic cognition. Subject to the evolutionary speed limit, in changing environments a simple, modular brain architecture is fitter than more complex ones. This encourages us to look for simplicity in brain design, rather than expecting the brain to be a patchwork of ad hoc adaptations. The limit implies that pure species selection is not an important mechanism of evolutionary change.

Trafficking of bluetongue virus visualized by recovery of tetracysteine-tagged virion particles.

PubMed

Du, Junzheng; Bhattacharya, Bishnupriya; Ward, Theresa H; Roy, Polly

2014-11-01

Bluetongue virus (BTV), a member of the Orbivirus genus in the Reoviridae family, is a double-capsid insect-borne virus enclosing a genome of 10 double-stranded RNA segments. Like those of other members of the family, BTV virions are nonenveloped particles containing two architecturally complex capsids. The two proteins of the outer capsid, VP2 and VP5, are involved in BTV entry and in the delivery of the transcriptionally active core to the cell cytoplasm. Although the importance of the endocytic pathway in BTV entry has been reported, detailed analyses of entry and the role of each protein in virus trafficking have not been possible due to the lack of availability of a tagged virus. Here, for the first time, we report on the successful manipulation of a segmented genome of a nonenveloped capsid virus by the introduction of tags that were subsequently fluorescently visualized in infected cells. The genetically engineered fluorescent BTV particles were observed to enter live cells immediately after virus adsorption. Further, we showed the separation of VP2 from VP5 during virus entry and confirmed that while VP2 is shed from virions in early endosomes, virus particles still consisting of VP5 were trafficked sequentially from early to late endosomes. Since BTV infects both mammalian and insect cells, the generation of tagged viruses will allow visualization of the trafficking of BTV farther downstream in different host cells. In addition, the tagging technology has potential for transferable application to other nonenveloped complex viruses. Live-virus trafficking in host cells has been highly informative on the interactions between virus and host cells. Although the insertion of fluorescent markers into viral genomes has made it possible to study the trafficking of enveloped viruses, the physical constraints of architecturally complex capsid viruses have imposed practical limitations. In this study, we have successfully genetically engineered the segmented RNA genome of bluetongue virus (BTV), a complex nonenveloped virus belonging to the Reoviridae family. The resulting fluorescent virus particles could be visualized in virus entry studies of both live and fixed cells. This is the first time a structurally complex capsid virus has been successfully genetically manipulated to generate virus particles that could be visualized in infected cells. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Molecular genetics of dyslexia: an overview.

PubMed

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.

Wild worm embryogenesis harbors ubiquitous polygenic modifier variation

PubMed Central

Paaby, Annalise B; White, Amelia G; Riccardi, David D; Gunsalus, Kristin C; Piano, Fabio; Rockman, Matthew V

2015-01-01

Embryogenesis is an essential and stereotypic process that nevertheless evolves among species. Its essentiality may favor the accumulation of cryptic genetic variation (CGV) that has no effect in the wild-type but that enhances or suppresses the effects of rare disruptions to gene function. Here, we adapted a classical modifier screen to interrogate the alleles segregating in natural populations of Caenorhabditis elegans: we induced gene knockdowns and used quantitative genetic methodology to examine how segregating variants modify the penetrance of embryonic lethality. Each perturbation revealed CGV, indicating that wild-type genomes harbor myriad genetic modifiers that may have little effect individually but which in aggregate can dramatically influence penetrance. Phenotypes were mediated by many modifiers, indicating high polygenicity, but the alleles tend to act very specifically, indicating low pleiotropy. Our findings demonstrate the extent of conditional functionality in complex trait architecture. DOI: http://dx.doi.org/10.7554/eLife.09178.001 PMID:26297805

Animal models of gene-environment interaction in schizophrenia: a dimensional perspective

PubMed Central

Ayhan, Yavuz; McFarland, Ross; Pletnikov, Mikhail V.

2015-01-01

Schizophrenia has long been considered as a disorder with multifactorial origins. Recent discoveries have advanced our understanding of the genetic architecture of the disease. However, even with the increase of identified risk variants, heritability estimates suggest an important contribution of non-genetic factors. Various environmental risk factors have been proposed to play a role in the etiopathogenesis of schizophrenia. These include season of birth, maternal infections, obstetric complications, adverse events at early childhood, and drug abuse. Despite the progress in identification of genetic and environmental risk factors, we still have a limited understanding of the mechanisms whereby gene-environment interactions (GxE) operate in schizophrenia and psychoses at large. In this review we provide a critical analysis of current animal models of GxE relevant to psychotic disorders and propose that dimensional perspective will advance our understanding of the complex mechanisms of these disorders. PMID:26510407

New developments in genetics of myositis.

PubMed

Rothwell, Simon; Lamb, Janine A; Chinoy, Hector

2016-11-01

This article reviews the advances that have been made in our understanding of the genetics of the idiopathic inflammatory myopathies (IIM) in the past 2 years, with a particular focus on polymyositis, dermatomyositis and inclusion body myositis. Two large human leukocyte antigen (HLA) imputation studies have confirmed a strong association with the 8.1 ancestral haplotype in clinical subgroups of myositis and suggest multiple independent associations on this haplotype. Risk in these genes may be due to specific amino acid positions within the peptide-binding grooves of HLA molecules. A large genetic study in 2566 IIM patients revealed associations such as PTPN22, STAT4, UBE2L3 and BLK, which overlap with risk variants reported in other seropositive autoimmune diseases. There is also evidence of different genetic architectures in clinical subgroups of IIM. Candidate gene studies in the Japanese and Chinese populations have replicated previous IIM associations which suggest common aetiology between ethnicities. International collaborations have facilitated large genetic studies in IIM that have revealed much about the genetics of this rare complex disease both within the HLA region and genome-wide. Future approaches, such as sequencing and trans-ethnic meta-analyses, will advance our knowledge of IIM genetics.

Estimating Additive and Non-Additive Genetic Variances and Predicting Genetic Merits Using Genome-Wide Dense Single Nucleotide Polymorphism Markers

PubMed Central

Su, Guosheng; Christensen, Ole F.; Ostersen, Tage; Henryon, Mark; Lund, Mogens S.

2012-01-01

Non-additive genetic variation is usually ignored when genome-wide markers are used to study the genetic architecture and genomic prediction of complex traits in human, wild life, model organisms or farm animals. However, non-additive genetic effects may have an important contribution to total genetic variation of complex traits. This study presented a genomic BLUP model including additive and non-additive genetic effects, in which additive and non-additive genetic relation matrices were constructed from information of genome-wide dense single nucleotide polymorphism (SNP) markers. In addition, this study for the first time proposed a method to construct dominance relationship matrix using SNP markers and demonstrated it in detail. The proposed model was implemented to investigate the amounts of additive genetic, dominance and epistatic variations, and assessed the accuracy and unbiasedness of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1) a simple additive genetic model (MA), 2) a model including both additive and additive by additive epistatic genetic effects (MAE), 3) a model including both additive and dominance genetic effects (MAD), and 4) a full model including all three genetic components (MAED). Estimates of narrow-sense heritability were 0.397, 0.373, 0.379 and 0.357 for models MA, MAE, MAD and MAED, respectively. Estimated dominance variance and additive by additive epistatic variance accounted for 5.6% and 9.5% of the total phenotypic variance, respectively. Based on model MAED, the estimate of broad-sense heritability was 0.506. Reliabilities of genomic predicted breeding values for the animals without performance records were 28.5%, 28.8%, 29.2% and 29.5% for models MA, MAE, MAD and MAED, respectively. In addition, models including non-additive genetic effects improved unbiasedness of genomic predictions. PMID:23028912

A Simple and Computationally Efficient Sampling Approach to Covariate Adjustment for Multifactor Dimensionality Reduction Analysis of Epistasis

PubMed Central

Gui, Jiang; Andrew, Angeline S.; Andrews, Peter; Nelson, Heather M.; Kelsey, Karl T.; Karagas, Margaret R.; Moore, Jason H.

2010-01-01

Epistasis or gene-gene interaction is a fundamental component of the genetic architecture of complex traits such as disease susceptibility. Multifactor dimensionality reduction (MDR) was developed as a nonparametric and model-free method to detect epistasis when there are no significant marginal genetic effects. However, in many studies of complex disease, other covariates like age of onset and smoking status could have a strong main effect and may potentially interfere with MDR's ability to achieve its goal. In this paper, we present a simple and computationally efficient sampling method to adjust for covariate effects in MDR. We use simulation to show that after adjustment, MDR has sufficient power to detect true gene-gene interactions. We also compare our method with the state-of-art technique in covariate adjustment. The results suggest that our proposed method performs similarly, but is more computationally efficient. We then apply this new method to an analysis of a population-based bladder cancer study in New Hampshire. PMID:20924193

Man’s Best Friend Becomes Biology’s Best in Show: Genome Analyses in the Domestic Dog*

PubMed Central

Parker, Heidi G.; Shearin, Abigail L.; Ostrander, Elaine A.

2012-01-01

In the last five years, canine genetics has gone from map construction to complex disease deconstruction. The availability of a draft canine genome sequence, dense marker chips, and an understanding of the genome architecture has changed the types of studies canine geneticists can undertake. There is now a clear recognition that the dog system offers the opportunity to understand the genetics of both simple and complex traits, including those associated with morphology, disease susceptibility, and behavior. In this review, we summarize recent findings regarding canine domestication and review new information on the organization of the canine genome. We discuss studies aimed at finding genes controlling morphological phenotypes and provide examples of the way such paradigms may be applied to studies of behavior. We also discuss the many ways in which the dog has illuminated our understanding of human disease and conclude with a discussion on where the field is likely headed in the next five years. PMID:21047261

A Conserved Developmental Mechanism Builds Complex Visual Systems in Insects and Vertebrates

PubMed Central

Joly, Jean-Stéphane; Recher, Gaelle; Brombin, Alessandro; Ngo, Kathy; Hartenstein, Volker

2016-01-01

The visual systems of vertebrates and many other bilaterian clades consist of complex neural structures guiding a wide spectrum of behaviors. Homologies at the level of cell types and even discrete neural circuits have been proposed, but many questions of how the architecture of visual neuropils evolved among different phyla remain open. In this review we argue that the profound conservation of genetic and developmental steps generating the eye and its target neuropils in fish and fruit flies supports a homology between some core elements of bilaterian visual circuitries. Fish retina and tectum, and fly optic lobe, develop from a partitioned, unidirectionally proliferating neurectodermal domain that combines slowly dividing neuroepithelial stem cells and rapidly amplifying progenitors with shared genetic signatures to generate large numbers and different types of neurons in a temporally ordered way. This peculiar ‘conveyor belt neurogenesis’ could play an essential role in generating the topographically ordered circuitry of the visual system. PMID:27780043

Intersection of diverse neuronal genomes and neuropsychiatric disease: The Brain Somatic Mosaicism Network.

PubMed

McConnell, Michael J; Moran, John V; Abyzov, Alexej; Akbarian, Schahram; Bae, Taejeong; Cortes-Ciriano, Isidro; Erwin, Jennifer A; Fasching, Liana; Flasch, Diane A; Freed, Donald; Ganz, Javier; Jaffe, Andrew E; Kwan, Kenneth Y; Kwon, Minseok; Lodato, Michael A; Mills, Ryan E; Paquola, Apua C M; Rodin, Rachel E; Rosenbluh, Chaggai; Sestan, Nenad; Sherman, Maxwell A; Shin, Joo Heon; Song, Saera; Straub, Richard E; Thorpe, Jeremy; Weinberger, Daniel R; Urban, Alexander E; Zhou, Bo; Gage, Fred H; Lehner, Thomas; Senthil, Geetha; Walsh, Christopher A; Chess, Andrew; Courchesne, Eric; Gleeson, Joseph G; Kidd, Jeffrey M; Park, Peter J; Pevsner, Jonathan; Vaccarino, Flora M

2017-04-28

Neuropsychiatric disorders have a complex genetic architecture. Human genetic population-based studies have identified numerous heritable sequence and structural genomic variants associated with susceptibility to neuropsychiatric disease. However, these germline variants do not fully account for disease risk. During brain development, progenitor cells undergo billions of cell divisions to generate the ~80 billion neurons in the brain. The failure to accurately repair DNA damage arising during replication, transcription, and cellular metabolism amid this dramatic cellular expansion can lead to somatic mutations. Somatic mutations that alter subsets of neuronal transcriptomes and proteomes can, in turn, affect cell proliferation and survival and lead to neurodevelopmental disorders. The long life span of individual neurons and the direct relationship between neural circuits and behavior suggest that somatic mutations in small populations of neurons can significantly affect individual neurodevelopment. The Brain Somatic Mosaicism Network has been founded to study somatic mosaicism both in neurotypical human brains and in the context of complex neuropsychiatric disorders. Copyright © 2017, American Association for the Advancement of Science.

The architecture of a modern military health information system.

PubMed

Mukherji, Raj J; Egyhazy, Csaba J

2004-06-01

This article describes a melding of a government-sponsored architecture for complex systems with open systems engineering architecture developed by the Institute for Electrical and Electronics Engineers (IEEE). Our experience in using these two architectures in building a complex healthcare system is described in this paper. The work described shows that it is possible to combine these two architectural frameworks in describing the systems, operational, and technical views of a complex automation system. The advantage in combining the two architectural frameworks lies in the simplicity of implementation and ease of understanding of automation system architectural elements by medical professionals.

The Genetic Architecture of Barley Plant Stature

PubMed Central

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

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

PubMed Central

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

2015-01-01

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

A simple genetic architecture underlies morphological variation in dogs.

PubMed

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.

Retrospective Binary-Trait Association Test Elucidates Genetic Architecture of Crohn Disease

PubMed Central

Jiang, Duo; Zhong, Sheng; McPeek, Mary Sara

2016-01-01

In genetic association testing, failure to properly control for population structure can lead to severely inflated type 1 error and power loss. Meanwhile, adjustment for relevant covariates is often desirable and sometimes necessary to protect against spurious association and to improve power. Many recent methods to account for population structure and covariates are based on linear mixed models (LMMs), which are primarily designed for quantitative traits. For binary traits, however, LMM is a misspecified model and can lead to deteriorated performance. We propose CARAT, a binary-trait association testing approach based on a mixed-effects quasi-likelihood framework, which exploits the dichotomous nature of the trait and achieves computational efficiency through estimating equations. We show in simulation studies that CARAT consistently outperforms existing methods and maintains high power in a wide range of population structure settings and trait models. Furthermore, CARAT is based on a retrospective approach, which is robust to misspecification of the phenotype model. We apply our approach to a genome-wide analysis of Crohn disease, in which we replicate association with 17 previously identified regions. Moreover, our analysis on 5p13.1, an extensively reported region of association, shows evidence for the presence of multiple independent association signals in the region. This example shows how CARAT can leverage known disease risk factors to shed light on the genetic architecture of complex traits. PMID:26833331

Quantitative trait loci × environment interactions for plant morphology vary over ontogeny in Brassica rapa.

PubMed

Dechaine, Jennifer M; Brock, Marcus T; Iniguez-Luy, Federico L; Weinig, Cynthia

2014-01-01

Growth in plants occurs via the addition of repeating modules, suggesting that the genetic architecture of similar subunits may vary between earlier- and later-developing modules. These complex environment × ontogeny interactions are not well elucidated, as studies examining quantitative trait loci (QTLs) expression over ontogeny have not included multiple environments. Here, we characterized the genetic architecture of vegetative traits and onset of reproduction over ontogeny in recombinant inbred lines of Brassica rapa in the field and glasshouse. The magnitude of genetic variation in plasticity of seedling internodes was greater than in those produced later in ontogeny. We correspondingly detected that QTLs for seedling internode length were environment-specific, whereas later in ontogeny the majority of QTLs affected internode lengths in all treatments. The relationship between internode traits and onset of reproduction varied with environment and ontogenetic stage. This relationship was observed only in the glasshouse environment and was largely attributable to one environment-specific QTL. Our results provide the first evidence of a QTL × environment × ontogeny interaction, and provide QTL resolution for differences between early- and later-stage plasticity for stem elongation. These results also suggest potential constraints on morphological evolution in early vs later modules as a result of associations with reproductive timing. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

A Simple Genetic Architecture Underlies Morphological Variation in Dogs

PubMed Central

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

[Progress in studies on the genetic risk factors for nonsyndromic cleft lip or palate in China].

PubMed

Huang, Y Q

2017-04-09

Cleft lip and palate is the most common congenital defects of oral and maxillofacial region in human beings. The etiology of this malformation is complex, with both genetic and environmental causal factors are involved. To provide a better understanding in the genetic etiology of cleft lip or palate, the author summarized recent years studies based on Chinese population. Those researches included validation of some candidate genes for cleft lip or palate, using genome wide association analysis which included six independent cohorts from China to elucidate the genetic architecture of non-syndromic cleft lip with or without cleft palate in Chinese population and finally found a new susceptibility locus. This locus was on the 16p13.3 (rs8049367) between CREBBP and ADCY9. It has been mentioned common methods of genetic analysis involved in the researches on cleft lip or palate in this paper. Furthermore, we try to discuss new methods to illustrate the etiology of cleft lip and palate that could provide more inspiration on future researches.

Estimating directional epistasis

PubMed Central

Le Rouzic, Arnaud

2014-01-01

Epistasis, i.e., the fact that gene effects depend on the genetic background, is a direct consequence of the complexity of genetic architectures. Despite this, most of the models used in evolutionary and quantitative genetics pay scant attention to genetic interactions. For instance, the traditional decomposition of genetic effects models epistasis as noise around the evolutionarily-relevant additive effects. Such an approach is only valid if it is assumed that there is no general pattern among interactions—a highly speculative scenario. Systematic interactions generate directional epistasis, which has major evolutionary consequences. In spite of its importance, directional epistasis is rarely measured or reported by quantitative geneticists, not only because its relevance is generally ignored, but also due to the lack of simple, operational, and accessible methods for its estimation. This paper describes conceptual and statistical tools that can be used to estimate directional epistasis from various kinds of data, including QTL mapping results, phenotype measurements in mutants, and artificial selection responses. As an illustration, I measured directional epistasis from a real-life example. I then discuss the interpretation of the estimates, showing how they can be used to draw meaningful biological inferences. PMID:25071828

The emotion system promotes diversity and evolvability

PubMed Central

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.

PubMed

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.

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 ...

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-02-01

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

Distinct Genetic Architectures for Male and Female Inflorescence Traits of Maize

PubMed Central

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

Effects of Hybridization and Evolutionary Constraints on Secondary Metabolites: The Genetic Architecture of Phenylpropanoids in European Populus Species

PubMed Central

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

Effects of hybridization and evolutionary constraints on secondary metabolites: the genetic architecture of phenylpropanoids in European populus species.

PubMed

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

PubMed Central

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

Application of Response Surface Methods To Determine Conditions for Optimal Genomic Prediction

PubMed Central

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

Genetic Architecture of Nest Building in Mice LG/J × SM/J

PubMed Central

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

Genetic Architecture of Conspicuous Red Ornaments in Female Threespine Stickleback

PubMed Central

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

TATES: Efficient Multivariate Genotype-Phenotype Analysis for Genome-Wide Association Studies

PubMed Central

van der Sluis, Sophie; Posthuma, Danielle; Dolan, Conor V.

2013-01-01

To date, the genome-wide association study (GWAS) is the primary tool to identify genetic variants that cause phenotypic variation. As GWAS analyses are generally univariate in nature, multivariate phenotypic information is usually reduced to a single composite score. This practice often results in loss of statistical power to detect causal variants. Multivariate genotype–phenotype methods do exist but attain maximal power only in special circumstances. Here, we present a new multivariate method that we refer to as TATES (Trait-based Association Test that uses Extended Simes procedure), inspired by the GATES procedure proposed by Li et al (2011). For each component of a multivariate trait, TATES combines p-values obtained in standard univariate GWAS to acquire one trait-based p-value, while correcting for correlations between components. Extensive simulations, probing a wide variety of genotype–phenotype models, show that TATES's false positive rate is correct, and that TATES's statistical power to detect causal variants explaining 0.5% of the variance can be 2.5–9 times higher than the power of univariate tests based on composite scores and 1.5–2 times higher than the power of the standard MANOVA. Unlike other multivariate methods, TATES detects both genetic variants that are common to multiple phenotypes and genetic variants that are specific to a single phenotype, i.e. TATES provides a more complete view of the genetic architecture of complex traits. As the actual causal genotype–phenotype model is usually unknown and probably phenotypically and genetically complex, TATES, available as an open source program, constitutes a powerful new multivariate strategy that allows researchers to identify novel causal variants, while the complexity of traits is no longer a limiting factor. PMID:23359524

Performance and robustness of penalized and unpenalized methods for genetic prediction of complex human disease.

PubMed

Abraham, Gad; Kowalczyk, Adam; Zobel, Justin; Inouye, Michael

2013-02-01

A central goal of medical genetics is to accurately predict complex disease from genotypes. Here, we present a comprehensive analysis of simulated and real data using lasso and elastic-net penalized support-vector machine models, a mixed-effects linear model, a polygenic score, and unpenalized logistic regression. In simulation, the sparse penalized models achieved lower false-positive rates and higher precision than the other methods for detecting causal SNPs. The common practice of prefiltering SNP lists for subsequent penalized modeling was examined and shown to substantially reduce the ability to recover the causal SNPs. Using genome-wide SNP profiles across eight complex diseases within cross-validation, lasso and elastic-net models achieved substantially better predictive ability in celiac disease, type 1 diabetes, and Crohn's disease, and had equivalent predictive ability in the rest, with the results in celiac disease strongly replicating between independent datasets. We investigated the effect of linkage disequilibrium on the predictive models, showing that the penalized methods leverage this information to their advantage, compared with methods that assume SNP independence. Our findings show that sparse penalized approaches are robust across different disease architectures, producing as good as or better phenotype predictions and variance explained. This has fundamental ramifications for the selection and future development of methods to genetically predict human disease. © 2012 WILEY PERIODICALS, INC.

The role of the proline-rich domain of Ssdp1 in the modular architecture of the vertebrate head organizer

PubMed Central

Enkhmandakh, Badam; Makeyev, Alexandr V.; Bayarsaihan, Dashzeveg

2006-01-01

Lim1, Ssdp1, and Ldb1 proteins are components of the Ldb1-associated transcriptional complex, which is important in the head-organizing activity during early mouse development. Depletion of each individual protein alone causes a headless phenotype. To explore in more detail the modular architecture of the complex, we have generated two different gene-trapped mouse lines that express truncated forms of Ssdp1. Embryos derived from the gene-trapped line that encodes a truncated Ssdp1 lacking the proline-rich sequence exhibit a lethal abnormal head-development phenotype, resembling mouse embryos deficient for Lim1, Ssdp1, or Otx2 genes. Embryos derived from the second gene-trapped line, in which most of the proline-rich domain of Ssdp1 is retained, did not show abnormalities in head development. Our data demonstrate that components of the Ldb1-dependent module can be subdivided further into discrete functional domains and that the proline-rich stretch of Ssdp1 is critical for embryonic head development. Furthermore, phylogenetic comparisons revealed that in Caenorhabditis elegans, a similar proline-rich sequence is absent in Ssdp but present in Ldb1. We conclude that although the overall architecture of the Ldb1-dependent module has been preserved, the genetic specification of its individual components has diversified during evolution, without compromising the function of the module. PMID:16864769

The role of the proline-rich domain of Ssdp1 in the modular architecture of the vertebrate head organizer.

PubMed

Enkhmandakh, Badam; Makeyev, Alexandr V; Bayarsaihan, Dashzeveg

2006-08-01

Lim1, Ssdp1, and Ldb1 proteins are components of the Ldb1-associated transcriptional complex, which is important in the head-organizing activity during early mouse development. Depletion of each individual protein alone causes a headless phenotype. To explore in more detail the modular architecture of the complex, we have generated two different gene-trapped mouse lines that express truncated forms of Ssdp1. Embryos derived from the gene-trapped line that encodes a truncated Ssdp1 lacking the proline-rich sequence exhibit a lethal abnormal head-development phenotype, resembling mouse embryos deficient for Lim1, Ssdp1, or Otx2 genes. Embryos derived from the second gene-trapped line, in which most of the proline-rich domain of Ssdp1 is retained, did not show abnormalities in head development. Our data demonstrate that components of the Ldb1-dependent module can be subdivided further into discrete functional domains and that the proline-rich stretch of Ssdp1 is critical for embryonic head development. Furthermore, phylogenetic comparisons revealed that in Caenorhabditis elegans, a similar proline-rich sequence is absent in Ssdp but present in Ldb1. We conclude that although the overall architecture of the Ldb1-dependent module has been preserved, the genetic specification of its individual components has diversified during evolution, without compromising the function of the module.

Genetic variation in CD36, HBA, NOS3 and VCAM1 is associated with chronic haemolysis level in sickle cell anaemia: a longitudinal study.

PubMed

Coelho, Andreia; Dias, Alexandra; Morais, Anabela; Nunes, Baltazar; Ferreira, Emanuel; Picanço, Isabel; Faustino, Paula; Lavinha, João

2014-03-01

Chronic haemolysis stands out as one of the hallmarks of sickle cell anaemia, a clinically heterogeneous autosomal recessive monogenic anaemia. However, the genetic architecture of this sub-phenotype is still poorly understood. Here, we report the results of an association study between haemolysis biomarkers (serum LDH, total bilirubin and reticulocyte count) and the inheritance of 41 genetic variants of ten candidate genes in a series of 99 paediatric SS patients (median current age of 9.9 yr) followed up in two general hospitals in Greater Lisboa area (median follow-up per patient of 5.0 yr). Although in a large number of tests a seemingly significant (i.e. P < 0.05) association was observed, the following ones were confirmed upon correction for multiple comparisons: (i) an increased serum LDH level was associated with haplotype 7 within VCAM1 gene; (ii) a lower total bilirubin was associated with the 3.7-kb deletion at HBA gene, rs2070744_T allele at NOS3 gene, and haplotype 9 within VCAM1 promoter; and (iii) a diminished reticulocyte count was associated with the 3.7-kb deletion at HBA, whereas an increased count was associated with rs1984112_G allele at CD36 gene. On the whole, our findings suggest a complex genetic architecture for the sickle cell anaemia haemolysis process involving multiple pathways, namely control of vascular cell adhesion, NO synthesis and erythrocyte volume and haemoglobinisation. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Genetic Architecture of Resistance to Stripe Rust in a Global Winter Wheat Germplasm Collection

PubMed Central

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.

PubMed

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.

Flattening of Caribbean coral reefs: region-wide declines in architectural complexity

PubMed Central

Alvarez-Filip, Lorenzo; Dulvy, Nicholas K.; Gill, Jennifer A.; Côté, Isabelle M.; Watkinson, Andrew R.

2009-01-01

Coral reefs are rich in biodiversity, in large part because their highly complex architecture provides shelter and resources for a wide range of organisms. Recent rapid declines in hard coral cover have occurred across the Caribbean region, but the concomitant consequences for reef architecture have not been quantified on a large scale to date. We provide, to our knowledge, the first region-wide analysis of changes in reef architectural complexity, using nearly 500 surveys across 200 reefs, between 1969 and 2008. The architectural complexity of Caribbean reefs has declined nonlinearly with the near disappearance of the most complex reefs over the last 40 years. The flattening of Caribbean reefs was apparent by the early 1980s, followed by a period of stasis between 1985 and 1998 and then a resumption of the decline in complexity to the present. Rates of loss are similar on shallow (<6 m), mid-water (6–20 m) and deep (>20 m) reefs and are consistent across all five subregions. The temporal pattern of declining architecture coincides with key events in recent Caribbean ecological history: the loss of structurally complex Acropora corals, the mass mortality of the grazing urchin Diadema antillarum and the 1998 El Nino Southern Oscillation-induced worldwide coral bleaching event. The consistently low estimates of current architectural complexity suggest regional-scale degradation and homogenization of reef structure. The widespread loss of architectural complexity is likely to have serious consequences for reef biodiversity, ecosystem functioning and associated environmental services. PMID:19515663

Elimination of a genetic correlation between the sexes via artificial correlational selection.

PubMed

Delph, Lynda F; Steven, Janet C; Anderson, Ingrid A; Herlihy, Christopher R; Brodie, Edmund D

2011-10-01

Genetic correlations between the sexes can constrain the evolution of sexual dimorphism and be difficult to alter, because traits common to both sexes share the same genetic underpinnings. We tested whether artificial correlational selection favoring specific combinations of male and female traits within families could change the strength of a very high between-sex genetic correlation for flower size in the dioecious plant Silene latifolia. This novel selection dramatically reduced the correlation in two of three selection lines in fewer than five generations. Subsequent selection only on females in a line characterized by a lower between-sex genetic correlation led to a significantly lower correlated response in males, confirming the potential evolutionary impact of the reduced correlation. Although between-sex genetic correlations can potentially constrain the evolution of sexual dimorphism, our findings reveal that these constraints come not from a simple conflict between an inflexible genetic architecture and a pattern of selection working in opposition to it, but rather a complex relationship between a changeable correlation and a form of selection that promotes it. In other words, the form of selection on males and females that leads to sexual dimorphism may also promote the genetic phenomenon that limits sexual dimorphism. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Adaptation of human skin color in various populations.

PubMed

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.

New Genes and New Insights from Old Genes: Update on Alzheimer Disease

PubMed Central

Ringman, John M.; Coppola, Giovanni

2013-01-01

Purpose of Review: This article discusses the current status of knowledge regarding the genetic basis of Alzheimer disease (AD) with a focus on clinically relevant aspects. Recent Findings: The genetic architecture of AD is complex, as it includes multiple susceptibility genes and likely nongenetic factors. Rare but highly penetrant autosomal dominant mutations explain a small minority of the cases but have allowed tremendous advances in understanding disease pathogenesis. The identification of a strong genetic risk factor, APOE, reshaped the field and introduced the notion of genetic risk for AD. More recently, large-scale genome-wide association studies are adding to the picture a number of common variants with very small effect sizes. Large-scale resequencing studies are expected to identify additional risk factors, including rare susceptibility variants and structural variation. Summary: Genetic assessment is currently of limited utility in clinical practice because of the low frequency (Mendelian mutations) or small effect size (common risk factors) of the currently known susceptibility genes. However, genetic studies are identifying with confidence a number of novel risk genes, and this will further our understanding of disease biology and possibly the identification of therapeutic targets. PMID:23558482

River network architecture, genetic effective size and distributional patterns predict differences in genetic structure across species in a dryland stream fish community.

PubMed

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.

GWAS of human bitter taste perception identifies new loci and reveals additional complexity of bitter taste genetics

PubMed Central

Ledda, Mirko; Kutalik, Zoltán; Souza Destito, Maria C.; Souza, Milena M.; Cirillo, Cintia A.; Zamboni, Amabilene; Martin, Nathalie; Morya, Edgard; Sameshima, Koichi; Beckmann, Jacques S.; le Coutre, Johannes; Bergmann, Sven; Genick, Ulrich K.

2014-01-01

Human perception of bitterness displays pronounced interindividual variation. This phenotypic variation is mirrored by equally pronounced genetic variation in the family of bitter taste receptor genes. To better understand the effects of common genetic variations on human bitter taste perception, we conducted a genome-wide association study on a discovery panel of 504 subjects and a validation panel of 104 subjects from the general population of São Paulo in Brazil. Correction for general taste-sensitivity allowed us to identify a SNP in the cluster of bitter taste receptors on chr12 (10.88– 11.24 Mb, build 36.1) significantly associated (best SNP: rs2708377, P = 5.31 × 10−13, r2 = 8.9%, β = −0.12, s.e. = 0.016) with the perceived bitterness of caffeine. This association overlaps with—but is statistically distinct from—the previously identified SNP rs10772420 influencing the perception of quinine bitterness that falls in the same bitter taste cluster. We replicated this association to quinine perception (P = 4.97 × 10−37, r2 = 23.2%, β = 0.25, s.e. = 0.020) and additionally found the effect of this genetic locus to be concentration specific with a strong impact on the perception of low, but no impact on the perception of high concentrations of quinine. Our study, thus, furthers our understanding of the complex genetic architecture of bitter taste perception. PMID:23966204

Corallite skeletal morphological variation in Hawaiian Porites lobata

NASA Astrophysics Data System (ADS)

Tisthammer, Kaho H.; Richmond, Robert H.

2018-06-01

Due to their high morphological plasticity and complex evolutionary history, the species boundaries of many reef-building corals are poorly understood. The skeletal structures of corals have traditionally been used for species identification, but these structures can be highly variable, and currently we lack knowledge regarding the extent of morphological variation within species. Porites species are notorious for their taxonomic difficulties, both morphologically and genetically, and currently there are several unresolved species complexes in the Pacific. Despite its ubiquitous presence and broad use in coral research, Porites lobata belongs to one such unresolved species complex. To understand the degree of intraspecific variation in skeletal morphology, 120 corallites from the Hawaiian P. lobata were examined. A subset of samples from two genetically differentiated populations from contrasting high- and low-stress environments in Maunalua Bay, Hawaii, were then quantitatively analyzed using multivariate morphometrics. Our observations revealed high intraspecific variation in corallite morphology, as well as significant morphological differences between the two populations of P. lobata. Additionally, significant correlation was found between the morphological and genetic distances calculated from approximately 18,000 loci generated from restriction site-associated DNA sequencing. The unique morphological characters observed from the genetically differentiated population under environmental stress suggest that these characters may have adaptive values, but how such traits relate to fitness and how much plasticity they can exhibit remain to be determined by future studies. Relatively simple morphometric analyses used in our study can be useful in clarifying the existing ambiguity in skeletal architecture, thus contributing to resolving species issues in corals.

Understanding epigenetic architecture of suicide neurobiology: A critical perspective

PubMed Central

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

Quantitative analysis of population-scale family trees with millions of relatives.

PubMed

Kaplanis, Joanna; Gordon, Assaf; Shor, Tal; Weissbrod, Omer; Geiger, Dan; Wahl, Mary; Gershovits, Michael; Markus, Barak; Sheikh, Mona; Gymrek, Melissa; Bhatia, Gaurav; MacArthur, Daniel G; Price, Alkes L; Erlich, Yaniv

2018-04-13

Family trees have vast applications in fields as diverse as genetics, anthropology, and economics. However, the collection of extended family trees is tedious and usually relies on resources with limited geographical scope and complex data usage restrictions. We collected 86 million profiles from publicly available online data shared by genealogy enthusiasts. After extensive cleaning and validation, we obtained population-scale family trees, including a single pedigree of 13 million individuals. We leveraged the data to partition the genetic architecture of human longevity and to provide insights into the geographical dispersion of families. We also report a simple digital procedure to overlay other data sets with our resource. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Integrating Evolutionary Game Theory into Mechanistic Genotype-Phenotype Mapping.

PubMed

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

2016-05-01

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

Programmable assembly of nanoarchitectures using genetically engineered viruses.

PubMed

Huang, Yu; Chiang, Chung-Yi; Lee, Soo Kwan; Gao, Yan; Hu, Evelyn L; De Yoreo, James; Belcher, Angela M

2005-07-01

Biological systems possess inherent molecular recognition and self-assembly capabilities and are attractive templates for constructing complex material structures with molecular precision. Here we report the assembly of various nanoachitectures including nanoparticle arrays, hetero-nanoparticle architectures, and nanowires utilizing highly engineered M13 bacteriophage as templates. The genome of M13 phage can be rationally engineered to produce viral particles with distinct substrate-specific peptides expressed on the filamentous capsid and the ends, providing a generic template for programmable assembly of complex nanostructures. Phage clones with gold-binding motifs on the capsid and streptavidin-binding motifs at one end are created and used to assemble Au and CdSe nanocrytals into ordered one-dimensional arrays and more complex geometries. Initial studies show such nanoparticle arrays can further function as templates to nucleate highly conductive nanowires that are important for addressing/interconnecting individual nanostructures.

Local connectome phenotypes predict social, health, and cognitive factors

PubMed Central

Powell, Michael A.; Garcia, Javier O.; Yeh, Fang-Cheng; Vettel, Jean M.

2018-01-01

The unique architecture of the human connectome is defined initially by genetics and subsequently sculpted over time with experience. Thus, similarities in predisposition and experience that lead to similarities in social, biological, and cognitive attributes should also be reflected in the local architecture of white matter fascicles. Here we employ a method known as local connectome fingerprinting that uses diffusion MRI to measure the fiber-wise characteristics of macroscopic white matter pathways throughout the brain. This fingerprinting approach was applied to a large sample (N = 841) of subjects from the Human Connectome Project, revealing a reliable degree of between-subject correlation in the local connectome fingerprints, with a relatively complex, low-dimensional substructure. Using a cross-validated, high-dimensional regression analysis approach, we derived local connectome phenotype (LCP) maps that could reliably predict a subset of subject attributes measured, including demographic, health, and cognitive measures. These LCP maps were highly specific to the attribute being predicted but also sensitive to correlations between attributes. Collectively, these results indicate that the local architecture of white matter fascicles reflects a meaningful portion of the variability shared between subjects along several dimensions. PMID:29911679

Local connectome phenotypes predict social, health, and cognitive factors.

PubMed

Powell, Michael A; Garcia, Javier O; Yeh, Fang-Cheng; Vettel, Jean M; Verstynen, Timothy

2018-01-01

The unique architecture of the human connectome is defined initially by genetics and subsequently sculpted over time with experience. Thus, similarities in predisposition and experience that lead to similarities in social, biological, and cognitive attributes should also be reflected in the local architecture of white matter fascicles. Here we employ a method known as local connectome fingerprinting that uses diffusion MRI to measure the fiber-wise characteristics of macroscopic white matter pathways throughout the brain. This fingerprinting approach was applied to a large sample ( N = 841) of subjects from the Human Connectome Project, revealing a reliable degree of between-subject correlation in the local connectome fingerprints, with a relatively complex, low-dimensional substructure. Using a cross-validated, high-dimensional regression analysis approach, we derived local connectome phenotype (LCP) maps that could reliably predict a subset of subject attributes measured, including demographic, health, and cognitive measures. These LCP maps were highly specific to the attribute being predicted but also sensitive to correlations between attributes. Collectively, these results indicate that the local architecture of white matter fascicles reflects a meaningful portion of the variability shared between subjects along several dimensions.

Forensic-paternity effectiveness and genetics population analysis of six non-CODIS mini-STR loci (D1S1656, D2S441, D6S1043, D10S1248, D12S391, D22S1045) and SE33 in Mestizo and Amerindian populations from Mexico.

PubMed

Burguete-Argueta, Nelsi; Martínez De la Cruz, Braulio; Camacho-Mejorado, Rafael; Santana, Carla; Noris, Gino; López-Bayghen, Esther; Arellano-Galindo, José; Majluf-Cruz, Abraham; Antonio Meraz-Ríos, Marco; Gómez, Rocío

2016-11-01

STRs are powerful tools intensively used in forensic and kinship studies. In order to assess the effectiveness of non-CODIS genetic markers in forensic and paternity tests, the genetic composition of six mini short tandem repeats-mini-STRs-(D1S1656, D2S441, D6S1043, D10S1248, D12S391, D22S1045) and the microsatellite SE33 in Mestizo and Amerindian populations from Mexico were studied. Using multiplex polymerase chain reactions and capillary electrophoresis, this study genotyped all loci from 870 chromosomes and evaluated the statistical genetic parameters. All mini-STRs studied were in agreement with HW and linkage equilibrium; however, an important HW departure for SE33 was found in the Mestizo population (p ≤ 0.0001). Regarding paternity and forensic statistical parameters, high values of combined power discrimination and mean power of exclusion were found using these seven markers. The principal co-ordinate analysis based on allele frequencies of three mini-STRs showed the complex genetic architecture of the Mestizo population. The results indicate that this set of loci is suitable to genetically identify individuals in the Mexican population, supporting its effectiveness in human identification casework. In addition, these findings add new statistical values and emphasise the importance of the use of non-CODIS markers in complex populations in order to avoid erroneous assumptions.

Investigating the Genetic Architecture of the PR Interval Using Clinical Phenotypes.

PubMed

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.

Genetic architecture of atherosclerosis dissected by QTL analyses in three F2 intercrosses of apolipoprotein E-null mice on C57BL6/J, DBA/2J and 129S6/SvEvTac backgrounds

PubMed Central

Makhanova, Natalia; Morgan, Andrew P.; Kayashima, Yukako; Makhanov, Andrei; Hiller, Sylvia; Zhilicheva, Svetlana; Xu, Longquan; Pardo-Manuel de Villena, Fernando; Maeda, Nobuyo

2017-01-01

Quantitative trait locus (QTL) analyses of intercross populations between widely used mouse inbred strains provide a powerful approach for uncovering genetic factors that influence susceptibility to atherosclerosis. Epistatic interactions are common in complex phenotypes and depend on genetic backgrounds. To dissect genetic architecture of atherosclerosis, we analyzed F2 progeny from a cross between apolipoprotein E-null mice on DBA/2J (DBA-apoE) and C57BL/6J (B6-apoE) genetic backgrounds and compared the results with those from two previous F2 crosses of apolipoprotein E-null mice on 129S6/SvEvTac (129-apoE) and DBA-apoE backgrounds, and B6-apoE and 129-apoE backgrounds. In these round-robin crosses, in which each parental strain was crossed with two others, large-effect QTLs are expected to be detectable at least in two crosses. On the other hand, observation of QTLs in one cross only may indicate epistasis and/or absence of statistical power. For atherosclerosis at the aortic arch, Aath4 on chromosome (Chr)2:66 cM follows the first pattern, with significant QTL peaks in (DBAx129)F2 and (B6xDBA)F2 mice but not in (B6x129)F2 mice. We conclude that genetic variants unique to DBA/2J at Aath4 confer susceptibility to atherosclerosis at the aortic arch. A similar pattern was observed for Aath5 on chr10:35 cM, verifying that the variants unique to DBA/2J at this locus protect against arch plaque development. However, multiple loci, including Aath1 (Chr1:49 cM), and Aath2 (Chr1:70 cM) follow the second type of pattern, showing significant peaks in only one of the three crosses (B6-apoE x 129-apoE). As for atherosclerosis at aortic root, the majority of QTLs, including Ath29 (Chr9:33 cM), Ath44 (Chr1:68 cM) and Ath45 (Chr2:83 cM), was also inconsistent, being significant in only one of the three crosses. Only the QTL on Chr7:37 cM was consistently suggestive in two of the three crosses. Thus QTL analysis of round-robin crosses revealed the genetic architecture of atherosclerosis. PMID:28837567

Assessment of the Genetic Architecture of Alzheimer's Disease Risk in Rate of Memory Decline.

PubMed

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.

PubMed

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.

Genetic architecture of sex determination in fish: applications to sex ratio control in aquaculture

PubMed Central

Martínez, Paulino; Viñas, Ana M.; Sánchez, Laura; Díaz, Noelia; Ribas, Laia; Piferrer, Francesc

2014-01-01

Controlling the sex ratio is essential in finfish farming. A balanced sex ratio is usually good for broodstock management, since it enables to develop appropriate breeding schemes. However, in some species the production of monosex populations is desirable because the existence of sexual dimorphism, primarily in growth or first time of sexual maturation, but also in color or shape, can render one sex more valuable. The knowledge of the genetic architecture of sex determination (SD) is convenient for controlling sex ratio and for the implementation of breeding programs. Unlike mammals and birds, which show highly conserved master genes that control a conserved genetic network responsible for gonad differentiation (GD), a huge diversity of SD mechanisms has been reported in fish. Despite theory predictions, more than one gene is in many cases involved in fish SD and genetic differences have been observed in the GD network. Environmental factors also play a relevant role and epigenetic mechanisms are becoming increasingly recognized for the establishment and maintenance of the GD pathways. Although major genetic factors are frequently involved in fish SD, these observations strongly suggest that SD in this group resembles a complex trait. Accordingly, the application of quantitative genetics combined with genomic tools is desirable to address its study and in fact, when applied, it has frequently demonstrated a multigene trait interacting with environmental factors in model and cultured fish species. This scenario has notable implications for aquaculture and, depending upon the species, from chromosome manipulation or environmental control techniques up to classical selection or marker assisted selection programs, are being applied. In this review, we selected four relevant species or fish groups to illustrate this diversity and hence the technologies that can be used by the industry for the control of sex ratio: turbot and European sea bass, two reference species of the European aquaculture, and salmonids and tilapia, representing the fish for which there are well established breeding programs. PMID:25324858

Coral identity underpins architectural complexity on Caribbean reefs.

PubMed

Alvarez-Filip, Lorenzo; Dulvy, Nicholas K; Côte, Isabelle M; Watkinson, Andrew R; Gill, Jennifer A

2011-09-01

The architectural complexity of ecosystems can greatly influence their capacity to support biodiversity and deliver ecosystem services. Understanding the components underlying this complexity can aid the development of effective strategies for ecosystem conservation. Caribbean coral reefs support and protect millions of livelihoods, but recent anthropogenic change is shifting communities toward reefs dominated by stress-resistant coral species, which are often less architecturally complex. With the regionwide decline in reef fish abundance, it is becoming increasingly important to understand changes in coral reef community structure and function. We quantify the influence of coral composition, diversity, and morpho-functional traits on the architectural complexity of reefs across 91 sites at Cozumel, Mexico. Although reef architectural complexity increases with coral cover and species richness, it is highest on sites that are low in taxonomic evenness and dominated by morpho-functionally important, reef-building coral genera, particularly Montastraea. Sites with similar coral community composition also tend to occur on reefs with very similar architectural complexity, suggesting that reef structure tends to be determined by the same key species across sites. Our findings provide support for prioritizing and protecting particular reef types, especially those dominated by key reef-building corals, in order to enhance reef complexity.

Genetic background of osteoporosis.

PubMed

Obermayer-Pietsch, B; Chararas, C; Kotschan, S; Walter, D; Leb, G

2000-01-01

Osteoporosis is a systemic disorder of decreased skeletal mass as measured by bone mineral density (BMD), and disturbed skeletal architecture and function which results in an increased risk for bone fractures with consecutively increased morbidity and mortality. Twin and family studies have shown an important genetic component of BMD of about 40-60%. This exceeds other well known factors influencing BMD such as environmental factors like dietary calcium, physical activity or several drugs and diseases. Therefore, interest increased in the genetic background of bone mineral density. Polymorphisms of the Vitamin D receptor gene were the first to be published in this area. Studies on other loci or candidate genes such as the estrogen receptor gene or the collagen type I alpha1 gene also showed associations with bone mineral density that could explain at least a part of the genetic background of osteoporosis. Recently published data suggest that these genetic markers of bone metabolism are important in interaction with each other or in certain bone-affecting diseases. In the future, genetic studies on osteoporosis will have to screen further relevant genes and markers for bone metabolism as well as to evaluate the complex interactions of genetic influences, so that it would be possible to calculate a patient's individual risk for osteoporosis in the context of environmental influences.

The Architecture of Risk for Type 2 Diabetes: Understanding Asia in the Context of Global Findings

PubMed Central

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

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

PubMed

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

2013-12-01

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

Inherited Paediatric Motor Neuron Disorders: Beyond Spinal Muscular Atrophy

PubMed Central

Sampaio, Hugo; Mowat, David; Roscioli, Tony

2017-01-01

Paediatric motor neuron diseases encompass a group of neurodegenerative diseases characterised by the onset of muscle weakness and atrophy before the age of 18 years, attributable to motor neuron loss across various neuronal networks in the brain and spinal cord. While the genetic underpinnings are diverse, advances in next generation sequencing have transformed diagnostic paradigms. This has reinforced the clinical phenotyping and molecular genetic expertise required to navigate the complexities of such diagnoses. In turn, improved genetic technology and subsequent gene identification have enabled further insights into the mechanisms of motor neuron degeneration and how these diseases form part of a neurodegenerative disorder spectrum. Common pathophysiologies include abnormalities in axonal architecture and function, RNA processing, and protein quality control. This review incorporates an overview of the clinical manifestations, genetics, and pathophysiology of inherited paediatric motor neuron disorders beyond classic SMN1-related spinal muscular atrophy and describes recent advances in next generation sequencing and its clinical application. Specific disease-modifying treatment is becoming a clinical reality in some disorders of the motor neuron highlighting the importance of a timely and specific diagnosis. PMID:28634552

Shifting the focus toward rare variants in schizophrenia to close the gap from genotype to phenotype.

PubMed

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.

Schizophrenia: What's Arc Got to Do with It?

PubMed

Managò, Francesca; Papaleo, Francesco

2017-01-01

Human studies of schizophrenia are now reporting a previously unidentified genetic convergence on postsynaptic signaling complexes such as the activity-regulated cytoskeletal-associated (Arc) gene. However, because this evidence is still very recent, the neurobiological implication of Arc in schizophrenia is still scattered and unrecognized. Here, we first review current and developing findings connecting Arc in schizophrenia. We then highlight recent and previous findings from preclinical mouse models that elucidate how Arc genetic modifications might recapitulate schizophrenia-relevant behavioral phenotypes following the novel Research Domain Criteria (RDoC) framework. Building on this, we finally compare and evaluate several lines of evidence demonstrating that Arc genetics can alter both glutamatergic and dopaminergic systems in a very selective way, again consistent with molecular alterations characteristic of schizophrenia. Despite being only initial, accumulating and compelling data are showing that Arc might be one of the primary biological players in schizophrenia. Synaptic plasticity alterations in the genetic architecture of psychiatric disorders might be a rule, not an exception. Thus, we anticipate that additional evidence will soon emerge to clarify the Arc-dependent mechanisms involved in the psychiatric-related dysfunctional behavior.

Secondary Analysis and Integration of Existing Data to Elucidate the Genetic Architecture of Cancer Risk and Related Outcomes, R21 | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

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.

Secondary Analysis and Integration of Existing Data to Elucidate the Genetic Architecture of Cancer Risk and Related Outcomes, R01 | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

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.

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

PubMed

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

2015-10-01

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

Gene Expression Architecture of Mouse Dorsal and Tail Skin Reveals Functional Differences in Inflammation and Cancer | Office of Cancer Genomics

Cancer.gov

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.

Cryo-EM Structures Reveal Mechanism and Inhibition of DNA Targeting by a CRISPR-Cas Surveillance Complex.

PubMed

Guo, Tai Wei; Bartesaghi, Alberto; Yang, Hui; Falconieri, Veronica; Rao, Prashant; Merk, Alan; Eng, Edward T; Raczkowski, Ashleigh M; Fox, Tara; Earl, Lesley A; Patel, Dinshaw J; Subramaniam, Sriram

2017-10-05

Prokaryotic cells possess CRISPR-mediated adaptive immune systems that protect them from foreign genetic elements, such as invading viruses. A central element of this immune system is an RNA-guided surveillance complex capable of targeting non-self DNA or RNA for degradation in a sequence- and site-specific manner analogous to RNA interference. Although the complexes display considerable diversity in their composition and architecture, many basic mechanisms underlying target recognition and cleavage are highly conserved. Using cryoelectron microscopy (cryo-EM), we show that the binding of target double-stranded DNA (dsDNA) to a type I-F CRISPR system yersinia (Csy) surveillance complex leads to large quaternary and tertiary structural changes in the complex that are likely necessary in the pathway leading to target dsDNA degradation by a trans-acting helicase-nuclease. Comparison of the structure of the surveillance complex before and after dsDNA binding, or in complex with three virally encoded anti-CRISPR suppressors that inhibit dsDNA binding, reveals mechanistic details underlying target recognition and inhibition. Published by Elsevier Inc.

Scanning the landscape of genome architecture of non-O1 and non-O139 Vibrio cholerae by whole genome mapping reveals extensive population genetic diversity

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

Chapman, Carol; Henry, Matthew; Bishop-Lilly, Kimberly A.

Historically, cholera outbreaks have been linked to V. cholerae O1 serogroup strains or its derivatives of the O37 and O139 serogroups. A genomic study on the 2010 Haiti cholera outbreak strains highlighted the putative role of non O1/non-O139 V. cholerae in causing cholera and the lack of genomic sequences of such strains from around the world. Here we address these gaps by scanning a global collection of V. cholerae strains as a first step towards understanding the population genetic diversity and epidemic potential of non O1/non-O139 strains. Whole Genome Mapping (Optical Mapping) based bar coding produces a high resolution, orderedmore » restriction map, depicting a complete view of the unique chromosomal architecture of an organism. To assess the genomic diversity of non-O1/non-O139 V. cholerae, we applied a Whole Genome Mapping strategy on a well-defined and geographically and temporally diverse strain collection, the Sakazaki serogroup type strains. Whole Genome Map data on 91 of the 206 serogroup type strains support the hypothesis that V. cholerae has an unprecedented genetic and genomic structural diversity. Interestingly, we discovered chromosomal fusions in two unusual strains that possess a single chromosome instead of the two chromosomes usually found in V. cholerae. We also found pervasive chromosomal rearrangements such as duplications and indels in many strains. The majority of Vibrio genome sequences currently in public databases are unfinished draft sequences. The Whole Genome Mapping approach presented here enables rapid screening of large strain collections to capture genomic complexities that would not have been otherwise revealed by unfinished draft genome sequencing and thus aids in assembling and finishing draft sequences of complex genomes. Furthermore, Whole Genome Mapping allows for prediction of novel V. cholerae non-O1/non-O139 strains that may have the potential to cause future cholera outbreaks.« less

Scanning the landscape of genome architecture of non-O1 and non-O139 Vibrio cholerae by whole genome mapping reveals extensive population genetic diversity.

PubMed

Chapman, Carol; Henry, Matthew; Bishop-Lilly, Kimberly A; Awosika, Joy; Briska, Adam; Ptashkin, Ryan N; Wagner, Trevor; Rajanna, Chythanya; Tsang, Hsinyi; Johnson, Shannon L; Mokashi, Vishwesh P; Chain, Patrick S G; Sozhamannan, Shanmuga

2015-01-01

Historically, cholera outbreaks have been linked to V. cholerae O1 serogroup strains or its derivatives of the O37 and O139 serogroups. A genomic study on the 2010 Haiti cholera outbreak strains highlighted the putative role of non O1/non-O139 V. cholerae in causing cholera and the lack of genomic sequences of such strains from around the world. Here we address these gaps by scanning a global collection of V. cholerae strains as a first step towards understanding the population genetic diversity and epidemic potential of non O1/non-O139 strains. Whole Genome Mapping (Optical Mapping) based bar coding produces a high resolution, ordered restriction map, depicting a complete view of the unique chromosomal architecture of an organism. To assess the genomic diversity of non-O1/non-O139 V. cholerae, we applied a Whole Genome Mapping strategy on a well-defined and geographically and temporally diverse strain collection, the Sakazaki serogroup type strains. Whole Genome Map data on 91 of the 206 serogroup type strains support the hypothesis that V. cholerae has an unprecedented genetic and genomic structural diversity. Interestingly, we discovered chromosomal fusions in two unusual strains that possess a single chromosome instead of the two chromosomes usually found in V. cholerae. We also found pervasive chromosomal rearrangements such as duplications and indels in many strains. The majority of Vibrio genome sequences currently in public databases are unfinished draft sequences. The Whole Genome Mapping approach presented here enables rapid screening of large strain collections to capture genomic complexities that would not have been otherwise revealed by unfinished draft genome sequencing and thus aids in assembling and finishing draft sequences of complex genomes. Furthermore, Whole Genome Mapping allows for prediction of novel V. cholerae non-O1/non-O139 strains that may have the potential to cause future cholera outbreaks.

Scanning the landscape of genome architecture of non-O1 and non-O139 Vibrio cholerae by whole genome mapping reveals extensive population genetic diversity

DOE PAGES

Chapman, Carol; Henry, Matthew; Bishop-Lilly, Kimberly A.; ...

2015-03-20

Historically, cholera outbreaks have been linked to V. cholerae O1 serogroup strains or its derivatives of the O37 and O139 serogroups. A genomic study on the 2010 Haiti cholera outbreak strains highlighted the putative role of non O1/non-O139 V. cholerae in causing cholera and the lack of genomic sequences of such strains from around the world. Here we address these gaps by scanning a global collection of V. cholerae strains as a first step towards understanding the population genetic diversity and epidemic potential of non O1/non-O139 strains. Whole Genome Mapping (Optical Mapping) based bar coding produces a high resolution, orderedmore » restriction map, depicting a complete view of the unique chromosomal architecture of an organism. To assess the genomic diversity of non-O1/non-O139 V. cholerae, we applied a Whole Genome Mapping strategy on a well-defined and geographically and temporally diverse strain collection, the Sakazaki serogroup type strains. Whole Genome Map data on 91 of the 206 serogroup type strains support the hypothesis that V. cholerae has an unprecedented genetic and genomic structural diversity. Interestingly, we discovered chromosomal fusions in two unusual strains that possess a single chromosome instead of the two chromosomes usually found in V. cholerae. We also found pervasive chromosomal rearrangements such as duplications and indels in many strains. The majority of Vibrio genome sequences currently in public databases are unfinished draft sequences. The Whole Genome Mapping approach presented here enables rapid screening of large strain collections to capture genomic complexities that would not have been otherwise revealed by unfinished draft genome sequencing and thus aids in assembling and finishing draft sequences of complex genomes. Furthermore, Whole Genome Mapping allows for prediction of novel V. cholerae non-O1/non-O139 strains that may have the potential to cause future cholera outbreaks.« less

Detection of gene-environment interaction in pedigree data using genome-wide genotypes.

PubMed

Nivard, Michel G; Middeldorp, Christel M; Lubke, Gitta; Hottenga, Jouke-Jan; Abdellaoui, Abdel; Boomsma, Dorret I; Dolan, Conor V

2016-12-01

Heritability may be estimated using phenotypic data collected in relatives or in distantly related individuals using genome-wide single nucleotide polymorphism (SNP) data. We combined these approaches by re-parameterizing the model proposed by Zaitlen et al and extended this model to include moderation of (total and SNP-based) genetic and environmental variance components by a measured moderator. By means of data simulation, we demonstrated that the type 1 error rates of the proposed test are correct and parameter estimates are accurate. As an application, we considered the moderation by age or year of birth of variance components associated with body mass index (BMI), height, attention problems (AP), and symptoms of anxiety and depression. The genetic variance of BMI was found to increase with age, but the environmental variance displayed a greater increase with age, resulting in a proportional decrease of the heritability of BMI. Environmental variance of height increased with year of birth. The environmental variance of AP increased with age. These results illustrate the assessment of moderation of environmental and genetic effects, when estimating heritability from combined SNP and family data. The assessment of moderation of genetic and environmental variance will enhance our understanding of the genetic architecture of complex traits.

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

PubMed Central

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

2015-01-01

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

A population genetic interpretation of GWAS findings for human quantitative traits

PubMed Central

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

Dosage changes of a segment at 17p13.1 lead to intellectual disability and microcephaly as a result of complex genetic interaction of multiple genes.

PubMed

Carvalho, Claudia M B; Vasanth, Shivakumar; Shinawi, Marwan; Russell, Chad; Ramocki, Melissa B; Brown, Chester W; Graakjaer, Jesper; Skytte, Anne-Bine; Vianna-Morgante, Angela M; Krepischi, Ana C V; Patel, Gayle S; Immken, LaDonna; Aleck, Kyrieckos; Lim, Cynthia; Cheung, Sau Wai; Rosenberg, Carla; Katsanis, Nicholas; Lupski, James R

2014-11-06

The 17p13.1 microdeletion syndrome is a recently described genomic disorder with a core clinical phenotype of intellectual disability, poor to absent speech, dysmorphic features, and a constellation of more variable clinical features, most prominently microcephaly. We identified five subjects with copy-number variants (CNVs) on 17p13.1 for whom we performed detailed clinical and molecular studies. Breakpoint mapping and retrospective analysis of published cases refined the smallest region of overlap (SRO) for microcephaly to a genomic interval containing nine genes. Dissection of this phenotype in zebrafish embryos revealed a complex genetic architecture: dosage perturbation of four genes (ASGR1, ACADVL, DVL2, and GABARAP) impeded neurodevelopment and decreased dosage of the same loci caused a reduced mitotic index in vitro. Moreover, epistatic analyses in vivo showed that dosage perturbations of discrete gene pairings induce microcephaly. Taken together, these studies support a model in which concomitant dosage perturbation of multiple genes within the CNV drive the microcephaly and possibly other neurodevelopmental phenotypes associated with rearrangements in the 17p13.1 SRO. Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations.

PubMed

Liu, Jimmy Z; van Sommeren, Suzanne; Huang, Hailiang; Ng, Siew C; Alberts, Rudi; Takahashi, Atsushi; Ripke, Stephan; Lee, James C; Jostins, Luke; Shah, Tejas; Abedian, Shifteh; Cheon, Jae Hee; Cho, Judy; Dayani, Naser E; Franke, Lude; Fuyuno, Yuta; Hart, Ailsa; Juyal, Ramesh C; Juyal, Garima; Kim, Won Ho; Morris, Andrew P; Poustchi, Hossein; Newman, William G; Midha, Vandana; Orchard, Timothy R; Vahedi, Homayon; Sood, Ajit; Sung, Joseph Y; Malekzadeh, Reza; Westra, Harm-Jan; Yamazaki, Keiko; Yang, Suk-Kyun; Barrett, Jeffrey C; Alizadeh, Behrooz Z; Parkes, Miles; Bk, Thelma; Daly, Mark J; Kubo, Michiaki; Anderson, Carl A; Weersma, Rinse K

2015-09-01

Ulcerative colitis and Crohn's disease are the two main forms of inflammatory bowel disease (IBD). Here we report the first trans-ancestry association study of IBD, with genome-wide or Immunochip genotype data from an extended cohort of 86,640 European individuals and Immunochip data from 9,846 individuals of East Asian, Indian or Iranian descent. We implicate 38 loci in IBD risk for the first time. For the majority of the IBD risk loci, the direction and magnitude of effect are consistent in European and non-European cohorts. Nevertheless, we observe genetic heterogeneity between divergent populations at several established risk loci driven by differences in allele frequency (NOD2) or effect size (TNFSF15 and ATG16L1) or a combination of these factors (IL23R and IRGM). Our results provide biological insights into the pathogenesis of IBD and demonstrate the usefulness of trans-ancestry association studies for mapping loci associated with complex diseases and understanding genetic architecture across diverse populations.

Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations

PubMed Central

Huang, Hailiang; Ng, Siew C; Alberts, Rudi; Takahashi, Atsushi; Ripke, Stephan; Lee, James C; Jostins, Luke; Shah, Tejas; Abedian, Shifteh; Cheon, Jae Hee; Cho, Judy; Dayani, Naser E; Franke, Lude; Fuyuno, Yuta; Hart, Ailsa; Juyal, Ramesh C; Juyal, Garima; Kim, Won Ho; Morris, Andrew P; Poustchi, Hossein; Newman, William G; Midha, Vandana; Orchard, Timothy R; Vahedi, Homayon; Sood, Ajit; Sung, Joseph Y; Malekzadeh, Reza; Westra, Harm-Jan; Yamazaki, Keiko; Yang, Suk-Kyun; Barrett, Jeffrey C; Alizadeh, Behrooz Z; Parkes, Miles; BK, Thelma; Daly, Mark J; Kubo, Michiaki; Anderson, Carl A; Weersma, Rinse K

2016-01-01

Ulcerative colitis and Crohn’s disease are the two main forms of inflammatory bowel disease (IBD). Here, we report the first trans-ethnic association study of IBD, with genome-wide or Immunochip genotype data from an extended cohort of 86,640 European individuals and Immunochip data from 9,846 individuals of East-Asian, Indian or Iranian descent. We implicate 38 loci in IBD risk for the first time. For the majority of IBD risk loci, the direction and magnitude of effect is consistent in European and non-European cohorts. Nevertheless, we observe genetic heterogeneity between divergent populations at several established risk loci driven by a combination of differences in allele frequencies (NOD2), effect sizes (TNFSF15, ATG16L1) or a combination of both (IL23R, IRGM). Our results provide biological insights into the pathogenesis of IBD, and demonstrate the utility of trans-ethnic association studies for mapping complex disease loci and understanding genetic architecture across diverse populations. PMID:26192919

Allele frequency data for 15 autosomal STR loci in eight Indonesian subpopulations.

PubMed

Venables, Samantha J; Daniel, Runa; Sarre, Stephen D; Soedarsono, Nurtami; Sudoyo, Herawati; Suryadi, Helena; van Oorschot, Roland A H; Walsh, Simon J; Widodo, Putut T; McNevin, Dennis

2016-01-01

Evolutionary and cultural history can affect the genetic characteristics of a population and influences the frequency of different variants at a particular genetic marker (allele frequency). These characteristics directly influence the strength of forensic DNA evidence and make the availability of suitable allele frequency information for every discrete country or jurisdiction highly relevant. Population sub-structure within Indonesia has not been well characterised but should be expected given the complex geographical, linguistic and cultural architecture of the Indonesian population. Here we use forensic short tandem repeat (STR) markers to identify a number of distinct genetic subpopulations within Indonesia and calculate appropriate population sub-structure correction factors. This data represents the most comprehensive investigation of population sub-structure within Indonesia to date using these markers. The results demonstrate that significant sub-structure is present within the Indonesian population and must be accounted for using island specific allele frequencies and corresponding sub-structure correction factors in the calculation of forensic DNA match statistics. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

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

PubMed Central

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

2012-01-01

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

Single-Locus versus Multilocus Patterns of Local Adaptation to Climate in Eastern White Pine (Pinus strobus, Pinaceae)

PubMed Central

Zinck, John W. R.

2016-01-01

Natural plant populations are often adapted to their local climate and environmental conditions, and populations of forest trees offer some of the best examples of this pattern. However, little empirical work has focused on the relative contribution of single-locus versus multilocus effects to the genetic architecture of local adaptation in plants/forest trees. Here, we employ eastern white pine (Pinus strobus) to test the hypothesis that it is the inter-genic effects that primarily drive climate-induced local adaptation. The genetic structure of 29 range-wide natural populations of eastern white pine was determined in relation to local climatic factors using both a reference set of SSR markers, and SNPs located in candidate genes putatively involved in adaptive response to climate. Comparisons were made between marker sets using standard single-locus outlier analysis, single-locus and multilocus environment association analyses and a novel implementation of Population Graphs. Magnitudes of population structure were similar between the two marker sets. Outlier loci consistent with diversifying selection were rare for both SNPs and SSRs. However, genetic distances based on the multilocus among population covariances (cGD) were significantly more correlated to climate, even after correcting for spatial effects, for SNPs as compared to SSRs. Coalescent simulations confirmed that the differences in mutation rates between SSRs and SNPs did not affect the topologies of the Population Graphs, and hence values of cGD and their correlations with associated climate variables. We conclude that the multilocus covariances among populations primarily reflect adaptation to local climate and environment in eastern white pine. This result highlights the complexity of the genetic architecture of adaptive traits, as well as the need to consider multilocus effects in studies of local adaptation. PMID:27387485

The Influence of Genetics on Response to Treatment with Ranibizumab (Lucentis) for Age-Related Macular Degeneration: The Lucentis Genotype Study (An American Ophthalmological Society Thesis)

PubMed Central

Francis, Peter James

2011-01-01

Purpose Age-related macular degeneration (AMD) has a complex etiology arising from genetic and environmental influences. This past decade have seen several genes associated with the disease. Variants in five genes have been confirmed to play a major role. The objective of this study was to evaluate whether genes influence treatment response to ranibizumab for neovascular AMD. The hypothesis was that an individual’s genetic variation will determine treatment response. Methods The study was a two-site prospective open-label observational study of patients newly diagnosed with exudative (neovascular) AMD receiving intravitreal ranibizumab therapy. Treatment-naïve patients were enrolled at presentation and received monthly “as needed” therapy. Clinical data was collected monthly and DNA extracted. Genotyping was performed using the Illumina (San Diego, California) 660-Quad single-nucleotide polymorphism (SNP) chip. Regression analyses were performed to identify SNPs associated with treatment-response end points. Results Sixty-five patients were enrolled. No serious adverse events were recorded. The primary outcome measure was change in ETDRS visual acuity at 12 months. A SNP in the CFH gene was found to be associated with less improvement in visual acuity while receiving ranibizumab therapy. The C3 gene, among others, was associated with reduced thickening and improved retinal architecture. VEGFA, FLT1, and CFH were associated with requiring fewer ranibizumab injections over the 12-month study. Conclusions This study is one of the first prospective pharmacogenetic study of intravitreal ranibizumab. Although preliminary, the results identify a number of putative genetic variants, which will be further examined by replication and functional studies to elucidate the complete pharmacogenetic architecture of therapy for AMD. PMID:22253485

Into the Fourth Dimension: Dysregulation of Genome Architecture in Aging and Alzheimer's Disease.

PubMed

Winick-Ng, Warren; Rylett, R Jane

2018-01-01

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by synapse dysfunction and cognitive impairment. Understanding the development and progression of AD is challenging, as the disease is highly complex and multifactorial. Both environmental and genetic factors play a role in AD pathogenesis, highlighted by observations of complex DNA modifications at the single gene level, and by new evidence that also implicates changes in genome architecture in AD patients. The four-dimensional structure of chromatin in space and time is essential for context-dependent regulation of gene expression in post-mitotic neurons. Dysregulation of epigenetic processes have been observed in the aging brain and in patients with AD, though there is not yet agreement on the impact of these changes on transcription. New evidence shows that proteins involved in genome organization have altered expression and localization in the AD brain, suggesting that the genomic landscape may play a critical role in the development of AD. This review discusses the role of the chromatin organizers and epigenetic modifiers in post-mitotic cells, the aging brain, and in the development and progression of AD. How these new insights can be used to help determine disease risk and inform treatment strategies will also be discussed.

A mitochondrial-focused genetic interaction map reveals a scaffold-like complex required for inner membrane organization in mitochondria

PubMed Central

Hoppins, Suzanne; Collins, Sean R.; Cassidy-Stone, Ann; Hummel, Eric; DeVay, Rachel M.; Lackner, Laura L.; Westermann, Benedikt; Schuldiner, Maya

2011-01-01

To broadly explore mitochondrial structure and function as well as the communication of mitochondria with other cellular pathways, we constructed a quantitative, high-density genetic interaction map (the MITO-MAP) in Saccharomyces cerevisiae. The MITO-MAP provides a comprehensive view of mitochondrial function including insights into the activity of uncharacterized mitochondrial proteins and the functional connection between mitochondria and the ER. The MITO-MAP also reveals a large inner membrane–associated complex, which we term MitOS for mitochondrial organizing structure, comprised of Fcj1/Mitofilin, a conserved inner membrane protein, and five additional components. MitOS physically and functionally interacts with both outer and inner membrane components and localizes to extended structures that wrap around the inner membrane. We show that MitOS acts in concert with ATP synthase dimers to organize the inner membrane and promote normal mitochondrial morphology. We propose that MitOS acts as a conserved mitochondrial skeletal structure that differentiates regions of the inner membrane to establish the normal internal architecture of mitochondria. PMID:21987634

graph-GPA: A graphical model for prioritizing GWAS results and investigating pleiotropic architecture.

PubMed

Chung, Dongjun; Kim, Hang J; Zhao, Hongyu

2017-02-01

Genome-wide association studies (GWAS) have identified tens of thousands of genetic variants associated with hundreds of phenotypes and diseases, which have provided clinical and medical benefits to patients with novel biomarkers and therapeutic targets. However, identification of risk variants associated with complex diseases remains challenging as they are often affected by many genetic variants with small or moderate effects. There has been accumulating evidence suggesting that different complex traits share common risk basis, namely pleiotropy. Recently, several statistical methods have been developed to improve statistical power to identify risk variants for complex traits through a joint analysis of multiple GWAS datasets by leveraging pleiotropy. While these methods were shown to improve statistical power for association mapping compared to separate analyses, they are still limited in the number of phenotypes that can be integrated. In order to address this challenge, in this paper, we propose a novel statistical framework, graph-GPA, to integrate a large number of GWAS datasets for multiple phenotypes using a hidden Markov random field approach. Application of graph-GPA to a joint analysis of GWAS datasets for 12 phenotypes shows that graph-GPA improves statistical power to identify risk variants compared to statistical methods based on smaller number of GWAS datasets. In addition, graph-GPA also promotes better understanding of genetic mechanisms shared among phenotypes, which can potentially be useful for the development of improved diagnosis and therapeutics. The R implementation of graph-GPA is currently available at https://dongjunchung.github.io/GGPA/.

Conservatism and novelty in the genetic architecture of adaptation in Heliconius butterflies.

PubMed

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.

Alternative cytoskeletal landscapes: cytoskeletal novelty and evolution in basal excavate protists

PubMed Central

Dawson, Scott C.; Paredez, Alexander R.

2016-01-01

Microbial eukaryotes encompass the majority of eukaryotic evolutionary and cytoskeletal diversity. The cytoskeletal complexity observed in multicellular organisms appears to be an expansion of components present in genomes of diverse microbial eukaryotes such as the basal lineage of flagellates, the Excavata. Excavate protists have complex and diverse cytoskeletal architectures and life cycles – essentially alternative cytoskeletal “landscapes” – yet still possess conserved microtubule- and actin-associated proteins. Comparative genomic analyses have revealed that a subset of excavates, however, lack many canonical actin-binding proteins central to actin cytoskeleton function in other eukaryotes. Overall, excavates possess numerous uncharacterized and “hypothetical” genes, and may represent an undiscovered reservoir of novel cytoskeletal genes and cytoskeletal mechanisms. The continued development of molecular genetic tools in these complex microbial eukaryotes will undoubtedly contribute to our overall understanding of cytoskeletal diversity and evolution. PMID:23312067

Coding principles of the canonical cortical microcircuit in the avian brain

PubMed Central

Calabrese, Ana; Woolley, Sarah M. N.

2015-01-01

Mammalian neocortex is characterized by a layered architecture and a common or “canonical” microcircuit governing information flow among layers. This microcircuit is thought to underlie the computations required for complex behavior. Despite the absence of a six-layered cortex, birds are capable of complex cognition and behavior. In addition, the avian auditory pallium is composed of adjacent information-processing regions with genetically identified neuron types and projections among regions comparable with those found in the neocortex. Here, we show that the avian auditory pallium exhibits the same information-processing principles that define the canonical cortical microcircuit, long thought to have evolved only in mammals. These results suggest that the canonical cortical microcircuit evolved in a common ancestor of mammals and birds and provide a physiological explanation for the evolution of neural processes that give rise to complex behavior in the absence of cortical lamination. PMID:25691736

The genetic architecture of susceptibility to parasites.

PubMed

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.

High Resolution Genomic Scans Reveal Genetic Architecture Controlling Alcohol Preference in Bidirectionally Selected Rat Model.

PubMed

Lo, Chiao-Ling; Lossie, Amy C; Liang, Tiebing; Liu, Yunlong; Xuei, Xiaoling; Lumeng, Lawrence; Zhou, Feng C; Muir, William M

2016-08-01

Investigations on the influence of nature vs. nurture on Alcoholism (Alcohol Use Disorder) in human have yet to provide a clear view on potential genomic etiologies. To address this issue, we sequenced a replicated animal model system bidirectionally-selected for alcohol preference (AP). This model is uniquely suited to map genetic effects with high reproducibility, and resolution. The origin of the rat lines (an 8-way cross) resulted in small haplotype blocks (HB) with a corresponding high level of resolution. We sequenced DNAs from 40 samples (10 per line of each replicate) to determine allele frequencies and HB. We achieved ~46X coverage per line and replicate. Excessive differentiation in the genomic architecture between lines, across replicates, termed signatures of selection (SS), were classified according to gene and region. We identified SS in 930 genes associated with AP. The majority (50%) of the SS were confined to single gene regions, the greatest numbers of which were in promoters (284) and intronic regions (169) with the least in exon's (4), suggesting that differences in AP were primarily due to alterations in regulatory regions. We confirmed previously identified genes and found many new genes associated with AP. Of those newly identified genes, several demonstrated neuronal function involved in synaptic memory and reward behavior, e.g. ion channels (Kcnf1, Kcnn3, Scn5a), excitatory receptors (Grin2a, Gria3, Grip1), neurotransmitters (Pomc), and synapses (Snap29). This study not only reveals the polygenic architecture of AP, but also emphasizes the importance of regulatory elements, consistent with other complex traits.

Incorporating Bacteria as a Living Component in Supramolecular Self-Assembled Monolayers through Dynamic Nanoscale Interactions.

PubMed

Sankaran, Shrikrishnan; Kiren, Mustafa Can; Jonkheijm, Pascal

2015-01-01

Supramolecular assemblies, formed through noncovalent interactions, has become particularly attractive to develop dynamic and responsive architectures to address living systems at the nanoscale. Cucurbit[8]uril (CB[8]), a pumpkin shaped macrocylic host molecule, has been successfully used to construct various self-assembled architectures for biomedical applications since it can simultaneously bind two aromatic guest molecules within its cavity. Such architectures can also be designed to respond to external stimuli. Integrating living organisms as an active component into such supramolecular architectures would add a new dimension to the capabilities of such systems. To achieve this, we have incorporated supramolecular functionality at the bacterial surface by genetically modifying a transmembrane protein to display a CB[8]-binding motif as part of a cystine-stabilized miniprotein. We were able to confirm that this supramolecular motif on the bacterial surface specifically binds CB[8] and forms multiple intercellular ternary complexes leading to aggregation of the bacterial solution. We performed various aggregation experiments to understand how CB[8] interacts with this bacterial strain and also demonstrate that it can be chemically reversed using a competitor. To confirm that this strain can be incorporated with a CB[8] based architecture, we show that the bacterial cells were able to adhere to CB[8] self-assembled monolayers (SAMs) on gold and still retain considerable motility for several hours, indicating that the system can potentially be used to develop supramolecular bacterial biomotors. The bacterial strain also has the potential to be combined with other CB[8] based architectures like nanoparticles, vesicles and hydrogels.

Systems genetics of obesity in an F2 pig model by genome-wide association, genetic network, and pathway analyses

PubMed Central

Kogelman, Lisette J. A.; Pant, Sameer D.; Fredholm, Merete; Kadarmideen, Haja N.

2014-01-01

Obesity is a complex condition with world-wide exponentially rising prevalence rates, linked with severe diseases like Type 2 Diabetes. Economic and welfare consequences have led to a raised interest in a better understanding of the biological and genetic background. To date, whole genome investigations focusing on single genetic variants have achieved limited success, and the importance of including genetic interactions is becoming evident. Here, the aim was to perform an integrative genomic analysis in an F2 pig resource population that was constructed with an aim to maximize genetic variation of obesity-related phenotypes and genotyped using the 60K SNP chip. Firstly, Genome Wide Association (GWA) analysis was performed on the Obesity Index to locate candidate genomic regions that were further validated using combined Linkage Disequilibrium Linkage Analysis and investigated by evaluation of haplotype blocks. We built Weighted Interaction SNP Hub (WISH) and differentially wired (DW) networks using genotypic correlations amongst obesity-associated SNPs resulting from GWA analysis. GWA results and SNP modules detected by WISH and DW analyses were further investigated by functional enrichment analyses. The functional annotation of SNPs revealed several genes associated with obesity, e.g., NPC2 and OR4D10. Moreover, gene enrichment analyses identified several significantly associated pathways, over and above the GWA study results, that may influence obesity and obesity related diseases, e.g., metabolic processes. WISH networks based on genotypic correlations allowed further identification of various gene ontology terms and pathways related to obesity and related traits, which were not identified by the GWA study. In conclusion, this is the first study to develop a (genetic) obesity index and employ systems genetics in a porcine model to provide important insights into the complex genetic architecture associated with obesity and many biological pathways that underlie it. PMID:25071839

Comparative Genome-Wide-Association Mapping Identifies Common Loci Controlling Root System Architecture and Resistance to Aphanomyces euteiches in Pea.

PubMed

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.

Comparative Genome-Wide-Association Mapping Identifies Common Loci Controlling Root System Architecture and Resistance to Aphanomyces euteiches in Pea

PubMed Central

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

Quantitative genetics of immunity and life history under different photoperiods.

PubMed

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

2012-05-01

Insects with complex life-cycles should optimize age and size at maturity during larval development. When inhabiting seasonal environments, organisms have limited reproductive periods and face fundamental decisions: individuals that reach maturity late in season have to either reproduce at a small size or increase their growth rates. Increasing growth rates is costly in insects because of higher juvenile mortality, decreased adult survival or increased susceptibility to parasitism by bacteria and viruses via compromised immune function. Environmental changes such as seasonality can also alter the quantitative genetic architecture. Here, we explore the quantitative genetics of life history and immunity traits under two experimentally induced seasonal environments in the cricket Gryllus bimaculatus. Seasonality affected the life history but not the immune phenotypes. Individuals under decreasing day length developed slower and grew to a bigger size. We found ample additive genetic variance and heritability for components of immunity (haemocyte densities, proPhenoloxidase activity, resistance against Serratia marcescens), and for the life history traits, age and size at maturity. Despite genetic covariance among traits, the structure of G was inconsistent with genetically based trade-off between life history and immune traits (for example, a strong positive genetic correlation between growth rate and haemocyte density was estimated). However, conditional evolvabilities support the idea that genetic covariance structure limits the capacity of individual traits to evolve independently. We found no evidence for G × E interactions arising from the experimentally induced seasonality.

Genome-wide analysis identifies 12 loci influencing human reproductive behavior.

PubMed

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.

Deciphering the combinatorial architecture of a Drosophila homeotic gene enhancer

PubMed Central

Drewell, Robert A.; Nevarez, Michael J.; Kurata, Jessica S.; Winkler, Lauren N.; Li, Lily; Dresch, Jacqueline M.

2013-01-01

Summary In Drosophila, the 330 kb bithorax complex regulates cellular differentiation along the anterio-posterior axis during development in the thorax and abdomen and is comprised of three homeotic genes: Ultrabithorax, abdominal-A, and Abdominal-B. The expression of each of these genes is in turn controlled through interactions between transcription factors and a number of cis-regulatory modules in the neighboring intergenic regions. In this study, we examine how the sequence architecture of transcription factor binding sites mediates the functional activity of one of these cis-regulatory modules. Using computational, mathematical modeling and experimental molecular genetic approaches we investigate the IAB7b enhancer, which regulates Abdominal-B expression specifically in the presumptive seventh and ninth abdominal segments of the early embryo. A cross-species comparison of the IAB7b enhancer reveals an evolutionarily conserved signature motif containing two FUSHI-TARAZU activator transcription factor binding sites. We find that the transcriptional repressors KNIRPS, KRUPPEL and GIANT are able to restrict reporter gene expression to the posterior abdominal segments, using different molecular mechanisms including short-range repression and competitive binding. Additionally, we show the functional importance of the spacing between the two FUSHI-TARAZU binding sites and discuss the potential importance of cooperativity for transcriptional activation. Our results demonstrate that the transcriptional output of the IAB7b cis-regulatory module relies on a complex set of combinatorial inputs mediated by specific transcription factor binding and that the sequence architecture at this enhancer is critical to maintain robust regulatory function. PMID:24514265

Human Facial Shape and Size Heritability and Genetic Correlations.

PubMed

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.

Phenotypic and genotypic data integration and exploration through a web-service architecture.

PubMed

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.

Genetic ablation of root cap cells in Arabidopsis

NASA Technical Reports Server (NTRS)

Tsugeki, R.; Fedoroff, N. V.

1999-01-01

The root cap is increasingly appreciated as a complex and dynamic plant organ. Root caps sense and transmit environmental signals, synthesize and secrete small molecules and macromolecules, and in some species shed metabolically active cells. However, it is not known whether root caps are essential for normal shoot and root development. We report the identification of a root cap-specific promoter and describe its use to genetically ablate root caps by directing root cap-specific expression of a diphtheria toxin A-chain gene. Transgenic toxin-expressing plants are viable and have normal aerial parts but agravitropic roots, implying loss of root cap function. Several cell layers are missing from the transgenic root caps, and the remaining cells are abnormal. Although the radial organization of the roots is normal in toxin-expressing plants, the root tips have fewer cytoplasmically dense cells than do wild-type root tips, suggesting that root meristematic activity is lower in transgenic than in wild-type plants. The roots of transgenic plants have more lateral roots and these are, in turn, more highly branched than those of wild-type plants. Thus, root cap ablation alters root architecture both by inhibiting root meristematic activity and by stimulating lateral root initiation. These observations imply that the root caps contain essential components of the signaling system that determines root architecture.

Contribution of Large Region Joint Associations to Complex Traits Genetics

PubMed Central

Paré, Guillaume; Asma, Senay; Deng, Wei Q.

2015-01-01

A polygenic model of inheritance, whereby hundreds or thousands of weakly associated variants contribute to a trait’s heritability, has been proposed to underlie the genetic architecture of complex traits. However, relatively few genetic variants have been positively identified so far and they collectively explain only a small fraction of the predicted heritability. We hypothesized that joint association of multiple weakly associated variants over large chromosomal regions contributes to complex traits variance. Confirmation of such regional associations can help identify new loci and lead to a better understanding of known ones. To test this hypothesis, we first characterized the ability of commonly used genetic association models to identify large region joint associations. Through theoretical derivation and simulation, we showed that multivariate linear models where multiple SNPs are included as independent predictors have the most favorable association profile. Based on these results, we tested for large region association with height in 3,740 European participants from the Health and Retirement Study (HRS) study. Adjusting for SNPs with known association with height, we demonstrated clustering of weak associations (p = 2x10-4) in regions extending up to 433.0 Kb from known height loci. The contribution of regional associations to phenotypic variance was estimated at 0.172 (95% CI 0.063-0.279; p < 0.001), which compared favorably to 0.129 explained by known height variants. Conversely, we showed that suggestively associated regions are enriched for known height loci. To extend our findings to other traits, we also tested BMI, HDLc and CRP for large region associations, with consistent results for CRP. Our results demonstrate the presence of large region joint associations and suggest these can be used to pinpoint weakly associated SNPs. PMID:25856144

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

PubMed

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

2018-03-01

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

How organisms do the right thing: The attractor hypothesis

USGS Publications Warehouse

Emlen, J.M.; Freeman, D.C.; Mills, A.; Graham, J.H.

1998-01-01

Neo-Darwinian theory is highly successful at explaining the emergence of adaptive traits over successive generations. However, there are reasons to doubt its efficacy in explaining the observed, impressively detailed adaptive responses of organisms to day-to-day changes in their surroundings. Also, the theory lacks a clear mechanism to account for both plasticity and canalization. In effect, there is a growing sentiment that the neo-Darwinian paradigm is incomplete, that something more than genetic structure, mutation, genetic drift, and the action of natural selection is required to explain organismal behavior. In this paper we extend the view of organisms as complex self-organizing entities by arguing that basic physical laws, coupled with the acquisitive nature of organisms, makes adaptation all but tautological. That is, much adaptation is an unavoidable emergent property of organisms' complexity and, to some a significant degree, occurs quite independently of genomic changes wrought by natural selection. For reasons that will become obvious, we refer to this assertion as the attractor hypothesis. The arguments also clarify the concept of "adaptation." Adaptation across generations, by natural selection, equates to the (game theoretic) maximization of fitness (the success with which one individual produces more individuals), while self-organizing based adaptation, within generations, equates to energetic efficiency and the matching of intake and biosynthesis to need. Finally, we discuss implications of the attractor hypothesis for a wide variety of genetical and physiological phenomena, including genetic architecture, directed mutation, genetic imprinting, paramutation, hormesis, plasticity, optimality theory, genotype-phenotype linkage and puncuated equilibrium, and present suggestions for tests of the hypothesis. ?? 1998 American Institute of Physics.

How organisms do the right thing: The attractor hypothesis

NASA Astrophysics Data System (ADS)

Emlen, John M.; Freeman, D. Carl; Mills, April; Graham, John H.

1998-09-01

Neo-Darwinian theory is highly successful at explaining the emergence of adaptive traits over successive generations. However, there are reasons to doubt its efficacy in explaining the observed, impressively detailed adaptive responses of organisms to day-to-day changes in their surroundings. Also, the theory lacks a clear mechanism to account for both plasticity and canalization. In effect, there is a growing sentiment that the neo-Darwinian paradigm is incomplete, that something more than genetic structure, mutation, genetic drift, and the action of natural selection is required to explain organismal behavior. In this paper we extend the view of organisms as complex self-organizing entities by arguing that basic physical laws, coupled with the acquisitive nature of organisms, makes adaptation all but tautological. That is, much adaptation is an unavoidable emergent property of organisms' complexity and, to some a significant degree, occurs quite independently of genomic changes wrought by natural selection. For reasons that will become obvious, we refer to this assertion as the attractor hypothesis. The arguments also clarify the concept of "adaptation." Adaptation across generations, by natural selection, equates to the (game theoretic) maximization of fitness (the success with which one individual produces more individuals), while self-organizing based adaptation, within generations, equates to energetic efficiency and the matching of intake and biosynthesis to need. Finally, we discuss implications of the attractor hypothesis for a wide variety of genetical and physiological phenomena, including genetic architecture, directed mutation, genetic imprinting, paramutation, hormesis, plasticity, optimality theory, genotype-phenotype linkage and puncuated equilibrium, and present suggestions for tests of the hypothesis.

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

PubMed Central

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

2018-01-01

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

Does plant architectural complexity increase with increasing habitat complexity? A test with a pioneer shrub in the Brazilian Cerrado.

PubMed

Silveira, F A O; Oliveira, E G

2013-05-01

Understanding variation in plant traits in heterogeneous habitats is important to predict responses to changing environments, but trait-environment associations are poorly known along ecological gradients. We tested the hypothesis that plant architectural complexity increases with habitat complexity along a soil fertility gradient in a Cerrado (Neotropical savanna) area in southeastern Brazil. Plant architecture and productivity (estimated as the total number of healthy infructescences) of Miconia albicans (SW.) Triana were examined in three types of vegetation which together form a natural gradient of increasing soil fertility, tree density and canopy cover: grasslands (campo sujo, CS), shrublands (cerrado sensu strico, CE) and woodlands (cerradão, CD). As expected, plants growing at the CS were shorter and had a lower branching pattern, whereas plants at the CD were the tallest. Unexpectedly, however, CD plants did not show higher architectural complexity compared to CE plants. Higher architectural similarity between CE and CD plants compared to similarity between CS and CE plants suggests reduced expression of functional architectural traits under shade. Plants growing at the CE produced more quaternary shoots, leading to a larger number of infructescences. This higher plant productivity in CE indicates that trait variation in ecological gradients is more complex than previously thought. Nematode-induced galls accounted for fruit destruction in 76.5% infructescences across physiognomies, but percentage of attack was poorly related to architectural variables. Our data suggest shade-induced limitation in M. albicans architecture, and point to complex phenotypic variation in heterogeneous habitats in Neotropical savannas.

Can Evolution Supply What Ecology Demands?

PubMed

Kokko, Hanna; Chaturvedi, Anurag; Croll, Daniel; Fischer, Martin C; Guillaume, Frédéric; Karrenberg, Sophie; Kerr, Ben; Rolshausen, Gregor; Stapley, Jessica

2017-03-01

A simplistic view of the adaptive process pictures a hillside along which a population can climb: when ecological 'demands' change, evolution 'supplies' the variation needed for the population to climb to a new peak. Evolutionary ecologists point out that this simplistic view can be incomplete because the fitness landscape changes dynamically as the population evolves. Geneticists meanwhile have identified complexities relating to the nature of genetic variation and its architecture, and the importance of epigenetic variation is under debate. In this review, we highlight how complexity in both ecological 'demands' and the evolutionary 'supply' influences organisms' ability to climb fitness landscapes that themselves change dynamically as evolution proceeds, and encourage new synthetic effort across research disciplines towards ecologically realistic studies of adaptation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Genetic architecture and the evolution of sex.

PubMed

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.

Genetic architecture of the Delis-Kaplan Executive Function System Trail Making Test: evidence for distinct genetic influences on executive function.

PubMed

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.

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...

The Genetic Architecture of Climatic Adaptation of Tropical Cattle

PubMed Central

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

Developmental and genetic analysis of a short leaf mutant, a key resource for plant architecture modification in sorghum

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 ...

Reorganization of chromosome architecture in replicative cellular senescence.

PubMed

Criscione, Steven W; De Cecco, Marco; Siranosian, Benjamin; Zhang, Yue; Kreiling, Jill A; Sedivy, John M; Neretti, Nicola

2016-02-01

Replicative cellular senescence is a fundamental biological process characterized by an irreversible arrest of proliferation. Senescent cells accumulate a variety of epigenetic changes, but the three-dimensional (3D) organization of their chromatin is not known. We applied a combination of whole-genome chromosome conformation capture (Hi-C), fluorescence in situ hybridization, and in silico modeling methods to characterize the 3D architecture of interphase chromosomes in proliferating, quiescent, and senescent cells. Although the overall organization of the chromatin into active (A) and repressive (B) compartments and topologically associated domains (TADs) is conserved between the three conditions, a subset of TADs switches between compartments. On a global level, the Hi-C interaction matrices of senescent cells are characterized by a relative loss of long-range and gain of short-range interactions within chromosomes. Direct measurements of distances between genetic loci, chromosome volumes, and chromatin accessibility suggest that the Hi-C interaction changes are caused by a significant reduction of the volumes occupied by individual chromosome arms. In contrast, centromeres oppose this overall compaction trend and increase in volume. The structural model arising from our study provides a unique high-resolution view of the complex chromosomal architecture in senescent cells.

Genetic architecture for human aggression: A study of gene-phenotype relationship in OMIM.

PubMed

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.

Shared additive genetic influences on DSM-IV criteria for alcohol dependence in subjects of European ancestry.

PubMed

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.

Lithium Pharmacogenetics: Where Do We Stand?

PubMed

Pisanu, Claudia; Melis, Carla; Squassina, Alessio

2016-11-01

Preclinical Research Bipolar disorder (BPD) is a chronic and disabling psychiatric disorder with a prevalence of 0.8-1.2% in the general population. Although lithium is considered the first-line treatment, a large percentage of patients do not respond sufficiently. Moreover, lithium can induce severe side effects and has poor tolerance and a narrow therapeutic index. The genetics of lithium response has been largely investigated, but findings have so far failed to identify reliable biomarkers to predict clinical response. This has been largely determined by the highly complex phenotipic and genetic architecture of lithium response. To this regard, collaborative initiatives hold the promise to provide robust and standardized methods to disantenagle this complexity, as well as the capacity to collect large samples of patietnts, a crucial requirement to study the genetics of complex phenotypes. The International Consortium on Lithium Genetics (ConLiGen) has recently published the largest study so far on lithium response reporting significant associations for two long noncoding RNAs (lncRNAs). This result provides relevant insights into the pharmacogenetics of lithium supporting the involvement of the noncoding portion of the genome in modulating clinical response. Although a vast body of research is engaged in dissecting the genetic bases of response to lithium, the several drawbacks of lithium therapy have also stimulated multiple efforts to identify new safer treatments. A drug repurposing approach identified ebselen as a potential lithium mimetic, as it shares with lithium the ability to inhibit inositol monophosphatase. Ebselen, an antioxidant glutathione peroxidase mimetic, represents a valid and promising example of new potential therapeutic interventions for BD, but the paucity of data warrant further investigation to elucidate its potential efficacy and safety in the management of BPD. Nevertheless, findings provided by the growing field of pharmacogenomic research will ultimately lead to the identification of new molecular targets and safer treatments for BPD. Drug Dev Res 77 : 368-373, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

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.

PubMed

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.

Genetic architecture of plant stress resistance: multi-trait genome-wide association mapping.

PubMed

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.

A hybrid neural networks-fuzzy logic-genetic algorithm for grade estimation

NASA Astrophysics Data System (ADS)

Tahmasebi, Pejman; Hezarkhani, Ardeshir

2012-05-01

The grade estimation is a quite important and money/time-consuming stage in a mine project, which is considered as a challenge for the geologists and mining engineers due to the structural complexities in mineral ore deposits. To overcome this problem, several artificial intelligence techniques such as Artificial Neural Networks (ANN) and Fuzzy Logic (FL) have recently been employed with various architectures and properties. However, due to the constraints of both methods, they yield the desired results only under the specific circumstances. As an example, one major problem in FL is the difficulty of constructing the membership functions (MFs).Other problems such as architecture and local minima could also be located in ANN designing. Therefore, a new methodology is presented in this paper for grade estimation. This method which is based on ANN and FL is called "Coactive Neuro-Fuzzy Inference System" (CANFIS) which combines two approaches, ANN and FL. The combination of these two artificial intelligence approaches is achieved via the verbal and numerical power of intelligent systems. To improve the performance of this system, a Genetic Algorithm (GA) - as a well-known technique to solve the complex optimization problems - is also employed to optimize the network parameters including learning rate, momentum of the network and the number of MFs for each input. A comparison of these techniques (ANN, Adaptive Neuro-Fuzzy Inference System or ANFIS) with this new method (CANFIS-GA) is also carried out through a case study in Sungun copper deposit, located in East-Azerbaijan, Iran. The results show that CANFIS-GA could be a faster and more accurate alternative to the existing time-consuming methodologies for ore grade estimation and that is, therefore, suggested to be applied for grade estimation in similar problems.

A hybrid neural networks-fuzzy logic-genetic algorithm for grade estimation

PubMed Central

Tahmasebi, Pejman; Hezarkhani, Ardeshir

2012-01-01

The grade estimation is a quite important and money/time-consuming stage in a mine project, which is considered as a challenge for the geologists and mining engineers due to the structural complexities in mineral ore deposits. To overcome this problem, several artificial intelligence techniques such as Artificial Neural Networks (ANN) and Fuzzy Logic (FL) have recently been employed with various architectures and properties. However, due to the constraints of both methods, they yield the desired results only under the specific circumstances. As an example, one major problem in FL is the difficulty of constructing the membership functions (MFs).Other problems such as architecture and local minima could also be located in ANN designing. Therefore, a new methodology is presented in this paper for grade estimation. This method which is based on ANN and FL is called “Coactive Neuro-Fuzzy Inference System” (CANFIS) which combines two approaches, ANN and FL. The combination of these two artificial intelligence approaches is achieved via the verbal and numerical power of intelligent systems. To improve the performance of this system, a Genetic Algorithm (GA) – as a well-known technique to solve the complex optimization problems – is also employed to optimize the network parameters including learning rate, momentum of the network and the number of MFs for each input. A comparison of these techniques (ANN, Adaptive Neuro-Fuzzy Inference System or ANFIS) with this new method (CANFIS–GA) is also carried out through a case study in Sungun copper deposit, located in East-Azerbaijan, Iran. The results show that CANFIS–GA could be a faster and more accurate alternative to the existing time-consuming methodologies for ore grade estimation and that is, therefore, suggested to be applied for grade estimation in similar problems. PMID:25540468

Implications of behavioral architecture for the evolution of self-organized division of labor.

PubMed

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.

Scale-space measures for graph topology link protein network architecture to function.

PubMed

Hulsman, Marc; Dimitrakopoulos, Christos; de Ridder, Jeroen

2014-06-15

The network architecture of physical protein interactions is an important determinant for the molecular functions that are carried out within each cell. To study this relation, the network architecture can be characterized by graph topological characteristics such as shortest paths and network hubs. These characteristics have an important shortcoming: they do not take into account that interactions occur across different scales. This is important because some cellular functions may involve a single direct protein interaction (small scale), whereas others require more and/or indirect interactions, such as protein complexes (medium scale) and interactions between large modules of proteins (large scale). In this work, we derive generalized scale-aware versions of known graph topological measures based on diffusion kernels. We apply these to characterize the topology of networks across all scales simultaneously, generating a so-called graph topological scale-space. The comprehensive physical interaction network in yeast is used to show that scale-space based measures consistently give superior performance when distinguishing protein functional categories and three major types of functional interactions-genetic interaction, co-expression and perturbation interactions. Moreover, we demonstrate that graph topological scale spaces capture biologically meaningful features that provide new insights into the link between function and protein network architecture. Matlab(TM) code to calculate the scale-aware topological measures (STMs) is available at http://bioinformatics.tudelft.nl/TSSA © The Author 2014. Published by Oxford University Press.

Implications of Behavioral Architecture for the Evolution of Self-Organized Division of Labor

PubMed Central

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

Neurogenomics and the role of a large mutational target on rapid behavioral change.

PubMed

Stanley, Craig E; Kulathinal, Rob J

2016-11-08

Behavior, while complex and dynamic, is among the most diverse, derived, and rapidly evolving traits in animals. The highly labile nature of heritable behavioral change is observed in such evolutionary phenomena as the emergence of converged behaviors in domesticated animals, the rapid evolution of preferences, and the routine development of ethological isolation between diverging populations and species. In fact, it is believed that nervous system development and its potential to evolve a seemingly infinite array of behavioral innovations played a major role in the successful diversification of metazoans, including our own human lineage. However, unlike other rapidly evolving functional systems such as sperm-egg interactions and immune defense, the genetic basis of rapid behavioral change remains elusive. Here we propose that the rapid divergence and widespread novelty of innate and adaptive behavior is primarily a function of its genomic architecture. Specifically, we hypothesize that the broad diversity of behavioral phenotypes present at micro- and macroevolutionary scales is promoted by a disproportionately large mutational target of neurogenic genes. We present evidence that these large neuro-behavioral targets are significant and ubiquitous in animal genomes and suggest that behavior's novelty and rapid emergence are driven by a number of factors including more selection on a larger pool of variants, a greater role of phenotypic plasticity, and/or unique molecular features present in large genes. We briefly discuss the origins of these large neurogenic genes, as they relate to the remarkable diversity of metazoan behaviors, and highlight key consequences on both behavioral traits and neurogenic disease across, respectively, evolutionary and ontogenetic time scales. Current approaches to studying the genetic mechanisms underlying rapid phenotypic change primarily focus on identifying signatures of Darwinian selection in protein-coding regions. In contrast, the large mutational target hypothesis places genomic architecture and a larger allelic pool at the forefront of rapid evolutionary change, particularly in genetic systems that are polygenic and regulatory in nature. Genomic data from brain and neural tissues in mammals as well as a preliminary survey of neurogenic genes from comparative genomic data support this hypothesis while rejecting both positive and relaxed selection on proteins or higher mutation rates. In mammals and invertebrates, neurogenic genes harbor larger protein-coding regions and possess a richer regulatory repertoire of miRNA targets and transcription factor binding sites. Overall, neurogenic genes cover a disproportionately large genomic fraction, providing a sizeable substrate for evolutionary, genetic, and molecular mechanisms to act upon. Readily available comparative and functional genomic data provide unexplored opportunities to test whether a distinct neurogenomic architecture can promote rapid behavioral change via several mechanisms unique to large genes, and which components of this large footprint are uniquely metazoan. The large mutational target hypothesis highlights the eminent roles of mutation and functional genomic architecture in generating rapid developmental and evolutionary change. It has broad implications on our understanding of the genetics of complex adaptive traits such as behavior by focusing on the importance of mutational input, from SNPs to alternative transcripts to transposable elements, on driving evolutionary rates of functional systems. Such functional divergence has important implications in promoting behavioral isolation across short- and long-term timescales. Due to genome-scaled polygenic adaptation, the large target effect also contributes to our inability to identify adapted behavioral candidate genes. The presence of large neurogenic genes, particularly in the mammalian brain and other neural tissues, further offers emerging insight into the etiology of neurodevelopmental and neurodegenerative diseases. The well-known correlation between neurological spectrum disorders in children and paternal age may simply be a direct result of aging fathers accumulating mutations across these large neurodevelopmental genes. The large mutational target hypothesis can also explain the rapid evolution of other functional systems covering a large genomic fraction such as male fertility and its preferential association with hybrid male sterility among closely related taxa. Overall, a focus on mutational potential may increase our power in understanding the genetic basis of complex phenotypes such as behavior while filling a general gap in understanding their evolution.

Genetic Characterization of Dog Personality Traits.

PubMed

Ilska, Joanna; Haskell, Marie J; Blott, Sarah C; Sánchez-Molano, Enrique; Polgar, Zita; Lofgren, Sarah E; Clements, Dylan N; Wiener, Pamela

2017-06-01

The genetic architecture of behavioral traits in dogs is of great interest to owners, breeders, and professionals involved in animal welfare, as well as to scientists studying the genetics of animal (including human) behavior. The genetic component of dog behavior is supported by between-breed differences and some evidence of within-breed variation. However, it is a challenge to gather sufficiently large datasets to dissect the genetic basis of complex traits such as behavior, which are both time-consuming and logistically difficult to measure, and known to be influenced by nongenetic factors. In this study, we exploited the knowledge that owners have of their dogs to generate a large dataset of personality traits in Labrador Retrievers. While accounting for key environmental factors, we demonstrate that genetic variance can be detected for dog personality traits assessed using questionnaire data. We identified substantial genetic variance for several traits, including fetching tendency and fear of loud noises, while other traits revealed negligibly small heritabilities. Genetic correlations were also estimated between traits; however, due to fairly large SEs, only a handful of trait pairs yielded statistically significant estimates. Genomic analyses indicated that these traits are mainly polygenic, such that individual genomic regions have small effects, and suggested chromosomal associations for six of the traits. The polygenic nature of these traits is consistent with previous behavioral genetics studies in other species, for example in mouse, and confirms that large datasets are required to quantify the genetic variance and to identify the individual genes that influence behavioral traits. Copyright © 2017 by the Genetics Society of America.

An ultra-high density bin-map for rapid QTL mapping for tassel and ear architecture in a large F₂ maize population.

PubMed

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.

Genome-Wide Association Mapping and Genomic Prediction Elucidate the Genetic Architecture of Morphological Traits in Arabidopsis.

PubMed

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.

Representation matters: quantitative behavioral variation in wild worm strains

NASA Astrophysics Data System (ADS)

Brown, Andre

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

Genome-wide analysis identifies 12 loci influencing human reproductive behavior

PubMed Central

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

Cell-Free and In Vivo Characterization of Lux, Las, and Rpa Quorum Activation Systems in E. coli.

PubMed

Halleran, Andrew D; Murray, Richard M

2018-02-16

Synthetic biologists have turned toward quorum systems as a path for building sophisticated microbial consortia that exhibit group decision making. Currently, however, even the most complex consortium circuits rely on only one or two quorum sensing systems, greatly restricting the available design space. High-throughput characterization of available quorum sensing systems is useful for finding compatible sets of systems that are suitable for a defined circuit architecture. Recently, cell-free systems have gained popularity as a test-bed for rapid prototyping of genetic circuitry. We take advantage of the transcription-translation cell-free system to characterize three commonly used Lux-type quorum activators, Lux, Las, and Rpa. We then compare the cell-free characterization to results obtained in vivo. We find significant genetic crosstalk in both the Las and Rpa systems and substantial signal crosstalk in Lux activation. We show that cell-free characterization predicts crosstalk observed in vivo.

Neurogenetics: Advancing the “Next-Generation” of Brain Research

PubMed Central

Zoghbi, Huda Y.; Warren, Stephen T.

2010-01-01

There can be little doubt that genetics has transformed our understanding of mechanisms mediating brain disorders. The last two decades have brought tremendous progress in terms of accurate molecular diagnoses and knowledge of the genes and pathways that are involved in a large number of neurological and psychiatric disorders. Likewise, new methods and analytical approaches, including genome array studies and “next-generation” sequencing technologies, are bringing us deeper insights into the subtle complexities of the genetic architecture that determines our risks for these disorders. As we now seek to translate these discoveries back to clinical applications, a major challenge for the field will be in bridging the gap between genes and biology. In this Overview of Neuron’s special review issue on neurogenetics, we reflect on progress made over the last two decades and highlight the challenges as well as the exciting opportunities for the future. PMID:20955921

MiR529a modulates panicle architecture through regulating SQUAMOSA PROMOTER BINDING-LIKE genes in rice (Oryza sativa).

PubMed

Yue, Erkui; Li, Chao; Li, Yu; Liu, Zhen; Xu, Jian-Hong

2017-07-01

MiR529a affects rice panicle architecture by targeting OsSPL2,OsSPL14 and OsSPL17 genes that could regulate their downstream panicle related genes. The panicle architecture determines the grain yield and quality of rice, which could be regulated by many transcriptional factors. The SQUAMOSA PROMOTER BINDING-LIKE (SPL) transcription factors are involved in the regulation of panicle development, which are targeted by miR156 and miR529. The expression profile demonstrated that miR529a is preferentially expressed in the early panicle of rice and it might regulate panicle development in rice. However, the regulation mechanism of miR529-SPL is still not clear. In this study, we predicted five miR529a putative target genes, OsSPL2, OsSPL14, OsSPL16, OsSPL17 and OsSPL18, while only the expression of OsSPL2, OsSPL14, and OsSPL17 was regulated by miR529a in the rice panicle. Overexpression of miR529a dramatically affected panicle architecture, which was regulated by OsSPL2, OsSPL14, and OsSPL17. Furthermore, the 117, 35, and 25 pathway genes associated with OsSPL2, OsSPL14 and OsSPL17, respectively, were predicted, and they shared 20 putative pathway genes. Our results revealed that miR529a could play a vital role in the regulation of panicle architecture through regulating OsSPL2, OsSPL14, OsSPL17 and the complex networks formed by their pathway and downstream genes. These findings will provide new genetic resources for reshaping ideal plant architecture and breeding high yield rice varieties.

The Between-Population Genetic Architecture of Growth, Maturation, and Plasticity in Atlantic Salmon

PubMed Central

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

The between-population genetic architecture of growth, maturation, and plasticity in Atlantic salmon.

PubMed

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.

Human genetics and genomics a decade after the release of the draft sequence of the human genome.

PubMed

Naidoo, Nasheen; Pawitan, Yudi; Soong, Richie; Cooper, David N; Ku, Chee-Seng

2011-10-01

Substantial progress has been made in human genetics and genomics research over the past ten years since the publication of the draft sequence of the human genome in 2001. Findings emanating directly from the Human Genome Project, together with those from follow-on studies, have had an enormous impact on our understanding of the architecture and function of the human genome. Major developments have been made in cataloguing genetic variation, the International HapMap Project, and with respect to advances in genotyping technologies. These developments are vital for the emergence of genome-wide association studies in the investigation of complex diseases and traits. In parallel, the advent of high-throughput sequencing technologies has ushered in the 'personal genome sequencing' era for both normal and cancer genomes, and made possible large-scale genome sequencing studies such as the 1000 Genomes Project and the International Cancer Genome Consortium. The high-throughput sequencing and sequence-capture technologies are also providing new opportunities to study Mendelian disorders through exome sequencing and whole-genome sequencing. This paper reviews these major developments in human genetics and genomics over the past decade.

Human genetics and genomics a decade after the release of the draft sequence of the human genome

PubMed Central

2011-01-01

Substantial progress has been made in human genetics and genomics research over the past ten years since the publication of the draft sequence of the human genome in 2001. Findings emanating directly from the Human Genome Project, together with those from follow-on studies, have had an enormous impact on our understanding of the architecture and function of the human genome. Major developments have been made in cataloguing genetic variation, the International HapMap Project, and with respect to advances in genotyping technologies. These developments are vital for the emergence of genome-wide association studies in the investigation of complex diseases and traits. In parallel, the advent of high-throughput sequencing technologies has ushered in the 'personal genome sequencing' era for both normal and cancer genomes, and made possible large-scale genome sequencing studies such as the 1000 Genomes Project and the International Cancer Genome Consortium. The high-throughput sequencing and sequence-capture technologies are also providing new opportunities to study Mendelian disorders through exome sequencing and whole-genome sequencing. This paper reviews these major developments in human genetics and genomics over the past decade. PMID:22155605

An integrated analysis of genes and functional pathways for aggression in human and rodent models.

PubMed

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.

The genetic architecture of resistance to virus infection in Drosophila.

PubMed

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.

Genetic architecture of carbon isotope composition and growth in Eucalyptus across multiple environments.

PubMed

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.

Detection of gene–environment interaction in pedigree data using genome-wide genotypes

PubMed Central

Nivard, Michel G; Middeldorp, Christel M; Lubke, Gitta; Hottenga, Jouke-Jan; Abdellaoui, Abdel; Boomsma, Dorret I; Dolan, Conor V

2016-01-01

Heritability may be estimated using phenotypic data collected in relatives or in distantly related individuals using genome-wide single nucleotide polymorphism (SNP) data. We combined these approaches by re-parameterizing the model proposed by Zaitlen et al and extended this model to include moderation of (total and SNP-based) genetic and environmental variance components by a measured moderator. By means of data simulation, we demonstrated that the type 1 error rates of the proposed test are correct and parameter estimates are accurate. As an application, we considered the moderation by age or year of birth of variance components associated with body mass index (BMI), height, attention problems (AP), and symptoms of anxiety and depression. The genetic variance of BMI was found to increase with age, but the environmental variance displayed a greater increase with age, resulting in a proportional decrease of the heritability of BMI. Environmental variance of height increased with year of birth. The environmental variance of AP increased with age. These results illustrate the assessment of moderation of environmental and genetic effects, when estimating heritability from combined SNP and family data. The assessment of moderation of genetic and environmental variance will enhance our understanding of the genetic architecture of complex traits. PMID:27436263

Additive genetic contribution to symptom dimensions in major depressive disorder.

PubMed

Pearson, Rahel; Palmer, Rohan H C; Brick, Leslie A; McGeary, John E; Knopik, Valerie S; Beevers, Christopher G

2016-05-01

Major depressive disorder (MDD) is a phenotypically heterogeneous disorder with a complex genetic architecture. In this study, genomic-relatedness-matrix restricted maximum-likelihood analysis (GREML) was used to investigate the extent to which variance in depression symptoms/symptom dimensions can be explained by variation in common single nucleotide polymorphisms (SNPs) in a sample of individuals with MDD (N = 1,558) who participated in the National Institute of Mental Health Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study. A principal components analysis of items from the Hamilton Rating Scale for Depression (HRSD) obtained prior to treatment revealed 4 depression symptom components: (a) appetite, (b) core depression symptoms (e.g., depressed mood, anhedonia), (c) insomnia, and (d) anxiety. These symptom dimensions were associated with SNP-based heritability (hSNP2) estimates of 30%, 14%, 30%, and 5%, respectively. Results indicated that the genetic contribution of common SNPs to depression symptom dimensions were not uniform. Appetite and insomnia symptoms in MDD had a relatively strong genetic contribution whereas the genetic contribution was relatively small for core depression and anxiety symptoms. While in need of replication, these results suggest that future gene discovery efforts may strongly benefit from parsing depression into its constituent parts. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Genetic architecture of natural variation in Drosophila melanogaster aggressive behavior

PubMed Central

Shorter, John; Couch, Charlene; Huang, Wen; Carbone, Mary Anna; Peiffer, Jason; Anholt, Robert R. H.; Mackay, Trudy F. C.

2015-01-01

Aggression is an evolutionarily conserved complex behavior essential for survival and the organization of social hierarchies. With the exception of genetic variants associated with bioamine signaling, which have been implicated in aggression in many species, the genetic basis of natural variation in aggression is largely unknown. Drosophila melanogaster is a favorable model system for exploring the genetic basis of natural variation in aggression. Here, we performed genome-wide association analyses using the inbred, sequenced lines of the Drosophila melanogaster Genetic Reference Panel (DGRP) and replicate advanced intercross populations derived from the most and least aggressive DGRP lines. We identified genes that have been previously implicated in aggressive behavior as well as many novel loci, including gustatory receptor 63a (Gr63a), which encodes a subunit of the receptor for CO2, and genes associated with development and function of the nervous system. Although genes from the two association analyses were largely nonoverlapping, they mapped onto a genetic interaction network inferred from an analysis of pairwise epistasis in the DGRP. We used mutations and RNAi knock-down alleles to functionally validate 79% of the candidate genes and 75% of the candidate epistatic interactions tested. Epistasis for aggressive behavior causes cryptic genetic variation in the DGRP that is revealed by changing allele frequencies in the outbred populations derived from extreme DGRP lines. This phenomenon may pertain to other fitness traits and species, with implications for evolution, applied breeding, and human genetics. PMID:26100892

Genetic determinants of prepubertal and pubertal growth and development.

PubMed

Thomis, Martine A; Towne, Bradford

2006-12-01

This article surveys the current general understanding of genetic influences on within- and between-population variation in growth and development in the context of establishing an International Growth Standard for Preadolescent and Adolescent Children. Traditional genetic epidemiologic analysis methods are reviewed, and evidence from family studies for genetic effects on different measures of growth and development is then presented. Findings from linkage and association studies seeking to identify specific genomic locations and allelic variants of genes influencing variation in growth and maturation are then summarized. Special mention is made of the need to study the interactions between genes and environments. At present, specific genes and polymorphisms contributing to variation in growth and maturation are only beginning to be identified. Larger genetic epidemiologic studies are needed in different parts of the world to better explore population differences in gene frequencies and gene-environment interactions. As advances continue to be made in molecular and statistical genetic methods, the genetic architecture of complex processes, including those of growth and development, will become better elucidated. For now, it can only be concluded that although the fundamental genetic underpinnings of the growth and development of children worldwide are likely to be essentially the same, there are also likely to be differences between populations in the frequencies of allelic gene variants that influence growth and maturation and in the nature of gene-environment interactions. This does not necessarily preclude an international growth reference, but it does have important implications for the form that such a reference might ultimately take.

Estimation of genetic parameters and selection of high-yielding, upright common bean lines with slow seed-coat darkening.

PubMed

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.

Plant architecture and grain yield are regulated by the novel DHHC-type zinc finger protein genes in rice (Oryza sativa L.).

PubMed

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.

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...

Functional architecture of olfactory ionotropic glutamate receptors.

PubMed

Abuin, Liliane; Bargeton, Benoîte; Ulbrich, Maximilian H; Isacoff, Ehud Y; Kellenberger, Stephan; Benton, Richard

2011-01-13

Ionotropic glutamate receptors (iGluRs) are ligand-gated ion channels that mediate chemical communication between neurons at synapses. A variant iGluR subfamily, the Ionotropic Receptors (IRs), was recently proposed to detect environmental volatile chemicals in olfactory cilia. Here, we elucidate how these peripheral chemosensors have evolved mechanistically from their iGluR ancestors. Using a Drosophila model, we demonstrate that IRs act in combinations of up to three subunits, comprising individual odor-specific receptors and one or two broadly expressed coreceptors. Heteromeric IR complex formation is necessary and sufficient for trafficking to cilia and mediating odor-evoked electrophysiological responses in vivo and in vitro. IRs display heterogeneous ion conduction specificities related to their variable pore sequences, and divergent ligand-binding domains function in odor recognition and cilia localization. Our results provide insights into the conserved and distinct architecture of these olfactory and synaptic ion channels and offer perspectives into the use of IRs as genetically encoded chemical sensors. Copyright © 2011 Elsevier Inc. All rights reserved.

Clonal architecture of secondary acute myeloid leukemia defined by single-cell sequencing.

PubMed

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.

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

PubMed

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

2016-01-01

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

Cryptic relatedness in epidemiologic collections accessed for genetic association studies: experiences from the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study and the National Health and Nutrition Examination Surveys (NHANES).

PubMed

Malinowski, Jennifer; Goodloe, Robert; Brown-Gentry, Kristin; Crawford, Dana C

2015-01-01

Epidemiologic collections have been a major resource for genotype-phenotype studies of complex disease given their large sample size, racial/ethnic diversity, and breadth and depth of phenotypes, traits, and exposures. A major disadvantage of these collections is they often survey households and communities without collecting extensive pedigree data. Failure to account for substantial relatedness can lead to inflated estimates and spurious associations. To examine the extent of cryptic relatedness in an epidemiologic collection, we as the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study accessed the National Health and Nutrition Examination Surveys (NHANES) linked to DNA samples ("Genetic NHANES") from NHANES III and NHANES 1999-2002. NHANES are population-based cross-sectional surveys conducted by the National Center for Health Statistics at the Centers for Disease Control and Prevention. Genome-wide genetic data is not yet available in NHANES, and current data use agreements prohibit the generation of GWAS-level data in NHANES samples due issues in maintaining confidentiality among other ethical concerns. To date, only hundreds of single nucleotide polymorphisms (SNPs) genotyped in a variety of candidate genes are available for analysis in NHANES. We performed identity-by-descent (IBD) estimates in three self-identified subpopulations of Genetic NHANES (non-Hispanic white, non- Hispanic black, and Mexican American) using PLINK software to identify potential familial relationships from presumed unrelated subjects. We then compared the PLINKidentified relationships to those identified by an alternative method implemented in Kinship-based INference for Genome-wide association studies (KING). Overall, both methods identified familial relationships in NHANES III and NHANES 1999-2002 for all three subpopulations, but little concordance was observed between the two methods due in major part to the limited SNP data available in Genetic NHANES. Despite the lack of genome-wide data, our results suggest the presence of cryptic relatedness in this epidemiologic collection and highlight the limitations of restricted datasets such as NHANES in the context of modern day genetic epidemiology studies.

Genetics of coronary artery disease and myocardial infarction

PubMed Central

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

Cross-Disorder Genome-Wide Analyses Suggest a Complex Genetic Relationship Between Tourette Syndrome and Obsessive-Compulsive Disorder

PubMed Central

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; Bloch, Michael H.; Brentani, Helena; Bruun, Ruth D.; Budman, Cathy L.; Camarena, Beatriz; Campbell, Desmond D.; Cappi, Carolina; Cardona Silgado, Julio C.; 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; 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.; 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; Walkup, John; Wang, Ying; Weale, Mike; Weiss, Robert; Wendland, Jens R.; Westenberg, Herman G.M.; Yao, Yin; 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; Stewart, S. Evelyn; Knowles, James A.; Cox, Nancy J.; Pauls, David L.

2014-01-01

Obsessive-compulsive disorder (OCD) and Tourette Syndrome (TS) 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. Here, we report a combined genome-wide association study (GWAS) of TS and OCD in 2723 cases (1310 with OCD, 834 with TS, 579 with OCD plus TS/chronic tics (CT)), 5667 ancestry-matched controls, and 290 OCD parent-child trios. 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, i.e. expression quantitative loci (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, TS had a smaller, non-significant 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 TS/CT were included in the analysis (p=0.01). Previous work has shown that TS 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 TS and OCD. Furthermore, OCD with co-occurring TS/CT may have different underlying genetic susceptibility compared to OCD alone. PMID:25158072

Predicting complex traits using a diffusion kernel on genetic markers with an application to dairy cattle and wheat data

PubMed Central

2013-01-01

Background Arguably, genotypes and phenotypes may be linked in functional forms that are not well addressed by the linear additive models that are standard in quantitative genetics. Therefore, developing statistical learning models for predicting phenotypic values from all available molecular information that are capable of capturing complex genetic network architectures is of great importance. Bayesian kernel ridge regression is a non-parametric prediction model proposed for this purpose. Its essence is to create a spatial distance-based relationship matrix called a kernel. Although the set of all single nucleotide polymorphism genotype configurations on which a model is built is finite, past research has mainly used a Gaussian kernel. Results We sought to investigate the performance of a diffusion kernel, which was specifically developed to model discrete marker inputs, using Holstein cattle and wheat data. This kernel can be viewed as a discretization of the Gaussian kernel. The predictive ability of the diffusion kernel was similar to that of non-spatial distance-based additive genomic relationship kernels in the Holstein data, but outperformed the latter in the wheat data. However, the difference in performance between the diffusion and Gaussian kernels was negligible. Conclusions It is concluded that the ability of a diffusion kernel to capture the total genetic variance is not better than that of a Gaussian kernel, at least for these data. Although the diffusion kernel as a choice of basis function may have potential for use in whole-genome prediction, our results imply that embedding genetic markers into a non-Euclidean metric space has very small impact on prediction. Our results suggest that use of the black box Gaussian kernel is justified, given its connection to the diffusion kernel and its similar predictive performance. PMID:23763755

Genetic Architecture of the Delis-Kaplan Executive Function System Trail Making Test: Evidence for Distinct Genetic Influences on Executive Function

PubMed Central

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

Elucidating the genetic architecture of familial schizophrenia using rare copy number variant and linkage scans.

PubMed

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.

The genetic architecture of long QT syndrome: A critical reappraisal.

PubMed

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.

Technical Reference Suite Addressing Challenges of Providing Assurance for Fault Management Architectural Design

NASA Technical Reports Server (NTRS)

Fitz, Rhonda; Whitman, Gerek

2016-01-01

Research into complexities of software systems Fault Management (FM) and how architectural design decisions affect safety, preservation of assets, and maintenance of desired system functionality has coalesced into a technical reference (TR) suite that advances the provision of safety and mission assurance. The NASA Independent Verification and Validation (IVV) Program, with Software Assurance Research Program support, extracted FM architectures across the IVV portfolio to evaluate robustness, assess visibility for validation and test, and define software assurance methods applied to the architectures and designs. This investigation spanned IVV projects with seven different primary developers, a wide range of sizes and complexities, and encompassed Deep Space Robotic, Human Spaceflight, and Earth Orbiter mission FM architectures. The initiative continues with an expansion of the TR suite to include Launch Vehicles, adding the benefit of investigating differences intrinsic to model-based FM architectures and insight into complexities of FM within an Agile software development environment, in order to improve awareness of how nontraditional processes affect FM architectural design and system health management.

Development and Genetic Control of Plant Architecture and Biomass in the Panicoid Grass, Setaria

PubMed Central

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.

PubMed

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.

The Evolving Complexity of the Podocyte Cytoskeleton.

PubMed

Schell, Christoph; Huber, Tobias B

2017-11-01

Podocytes exhibit a unique cytoskeletal architecture that is fundamentally linked to their function in maintaining the kidney filtration barrier. The cytoskeleton regulates podocyte shape, structure, stability, slit diaphragm insertion, adhesion, plasticity, and dynamic response to environmental stimuli. Genetic mutations demonstrate that even slight impairment of the podocyte cytoskeletal apparatus results in proteinuria and glomerular disease. Moreover, mechanisms underpinning all acquired glomerular pathologies converge on disruption of the cytoskeleton, suggesting that this subcellular structure could be targeted for therapeutic purposes. This review summarizes our current understanding of the function of the cytoskeleton in podocytes and the associated implications for pathophysiology. Copyright © 2017 by the American Society of Nephrology.

ARC-VM: An architecture real options complexity-based valuation methodology for military systems-of-systems acquisitions

NASA Astrophysics Data System (ADS)

Domercant, Jean Charles

The combination of today's national security environment and mandated acquisition policies makes it necessary for military systems to interoperate with each other to greater degrees. This growing interdependency results in complex Systems-of-Systems (SoS) that only continue to grow in complexity to meet evolving capability needs. Thus, timely and affordable acquisition becomes more difficult, especially in the face of mounting budgetary pressures. To counter this, architecting principles must be applied to SoS design. The research objective is to develop an Architecture Real Options Complexity-Based Valuation Methodology (ARC-VM) suitable for acquisition-level decision making, where there is a stated desire for more informed tradeoffs between cost, schedule, and performance during the early phases of design. First, a framework is introduced to measure architecture complexity as it directly relates to military SoS. Development of the framework draws upon a diverse set of disciplines, including Complexity Science, software architecting, measurement theory, and utility theory. Next, a Real Options based valuation strategy is developed using techniques established for financial stock options that have recently been adapted for use in business and engineering decisions. The derived complexity measure provides architects with an objective measure of complexity that focuses on relevant complex system attributes. These attributes are related to the organization and distribution of SoS functionality and the sharing and processing of resources. The use of Real Options provides the necessary conceptual and visual framework to quantifiably and traceably combine measured architecture complexity, time-valued performance levels, as well as programmatic risks and uncertainties. An example suppression of enemy air defenses (SEAD) capability demonstrates the development and usefulness of the resulting architecture complexity & Real Options based valuation methodology. Different portfolios of candidate system types are used to generate an array of architecture alternatives that are then evaluated using an engagement model. This performance data is combined with both measured architecture complexity and programmatic data to assign an acquisition value to each alternative. This proves useful when selecting alternatives most likely to meet current and future capability needs.

Genome-Wide Association Analysis Reveals Different Genetic Control in Panicle Architecture Between and Rice.

PubMed

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.

Comorbidity of Alcohol Use Disorder and Chronic Pain: Genetic Influences on Brain Reward and Stress Systems.

PubMed

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.

Including non-additive genetic effects in Bayesian methods for the prediction of genetic values based on genome-wide markers

PubMed Central

2011-01-01

Background Molecular marker information is a common source to draw inferences about the relationship between genetic and phenotypic variation. Genetic effects are often modelled as additively acting marker allele effects. The true mode of biological action can, of course, be different from this plain assumption. One possibility to better understand the genetic architecture of complex traits is to include intra-locus (dominance) and inter-locus (epistasis) interaction of alleles as well as the additive genetic effects when fitting a model to a trait. Several Bayesian MCMC approaches exist for the genome-wide estimation of genetic effects with high accuracy of genetic value prediction. Including pairwise interaction for thousands of loci would probably go beyond the scope of such a sampling algorithm because then millions of effects are to be estimated simultaneously leading to months of computation time. Alternative solving strategies are required when epistasis is studied. Methods We extended a fast Bayesian method (fBayesB), which was previously proposed for a purely additive model, to include non-additive effects. The fBayesB approach was used to estimate genetic effects on the basis of simulated datasets. Different scenarios were simulated to study the loss of accuracy of prediction, if epistatic effects were not simulated but modelled and vice versa. Results If 23 QTL were simulated to cause additive and dominance effects, both fBayesB and a conventional MCMC sampler BayesB yielded similar results in terms of accuracy of genetic value prediction and bias of variance component estimation based on a model including additive and dominance effects. Applying fBayesB to data with epistasis, accuracy could be improved by 5% when all pairwise interactions were modelled as well. The accuracy decreased more than 20% if genetic variation was spread over 230 QTL. In this scenario, accuracy based on modelling only additive and dominance effects was generally superior to that of the complex model including epistatic effects. Conclusions This simulation study showed that the fBayesB approach is convenient for genetic value prediction. Jointly estimating additive and non-additive effects (especially dominance) has reasonable impact on the accuracy of prediction and the proportion of genetic variation assigned to the additive genetic source. PMID:21867519

Into the Fourth Dimension: Dysregulation of Genome Architecture in Aging and Alzheimer’s Disease

PubMed Central

Winick-Ng, Warren; Rylett, R. Jane

2018-01-01

Alzheimer’s disease (AD) is a progressive neurodegenerative disease characterized by synapse dysfunction and cognitive impairment. Understanding the development and progression of AD is challenging, as the disease is highly complex and multifactorial. Both environmental and genetic factors play a role in AD pathogenesis, highlighted by observations of complex DNA modifications at the single gene level, and by new evidence that also implicates changes in genome architecture in AD patients. The four-dimensional structure of chromatin in space and time is essential for context-dependent regulation of gene expression in post-mitotic neurons. Dysregulation of epigenetic processes have been observed in the aging brain and in patients with AD, though there is not yet agreement on the impact of these changes on transcription. New evidence shows that proteins involved in genome organization have altered expression and localization in the AD brain, suggesting that the genomic landscape may play a critical role in the development of AD. This review discusses the role of the chromatin organizers and epigenetic modifiers in post-mitotic cells, the aging brain, and in the development and progression of AD. How these new insights can be used to help determine disease risk and inform treatment strategies will also be discussed. PMID:29541020

Genetics of reproduction and regulation of honey bee (Apis mellifera L.) social behavior

PubMed Central

Page, Robert E.; Rueppell, Olav; Amdam, Gro V.

2014-01-01

Honey bees form complex societies with a division of labor for reproduction, nutrition, nest construction and maintenance, and defense. How does it evolve? Tasks performed by worker honey bees are distributed in time and space. There is no central control over behavior and there is no central genome on which selection can act and effect adaptive change. For 22 years we have been asking these questions by selecting on a single social trait associated with nutrition: the amount of surplus pollen (a source of protein) that is stored in combs of the nest. Forty-two generations of selection have revealed changes at biological levels extending from the society down to the level of the gene. We show how we constructed this vertical understanding of social evolution using behavioral and anatomical analyses, physiology, genetic mapping, and gene knockdowns. We map out the phenotypic and genetic architectures of food storage and foraging behavior and show how they are linked through broad epistasis and pleiotropy affecting a reproductive regulatory network that influences foraging behavior. PMID:22934646

A comprehensive analysis of rare genetic variation in amyotrophic lateral sclerosis in the UK.

PubMed

Morgan, Sarah; Shatunov, Aleksey; Sproviero, William; Jones, Ashley R; Shoai, Maryam; Hughes, Deborah; Al Khleifat, Ahmad; Malaspina, Andrea; Morrison, Karen E; Shaw, Pamela J; Shaw, Christopher E; Sidle, Katie; Orrell, Richard W; Fratta, Pietro; Hardy, John; Pittman, Alan; Al-Chalabi, Ammar

2017-06-01

Amyotrophic lateral sclerosis is a progressive neurodegenerative disease of motor neurons. About 25 genes have been verified as relevant to the disease process, with rare and common variation implicated. We used next generation sequencing and repeat sizing to comprehensively assay genetic variation in a panel of known amyotrophic lateral sclerosis genes in 1126 patient samples and 613 controls. About 10% of patients were predicted to carry a pathological expansion of the C9orf72 gene. We found an increased burden of rare variants in patients within the untranslated regions of known disease-causing genes, driven by SOD1, TARDBP, FUS, VCP, OPTN and UBQLN2. We found 11 patients (1%) carried more than one pathogenic variant (P = 0.001) consistent with an oligogenic basis of amyotrophic lateral sclerosis. These findings show that the genetic architecture of amyotrophic lateral sclerosis is complex and that variation in the regulatory regions of associated genes may be important in disease pathogenesis. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.

Superstatistical model of bacterial DNA architecture

NASA Astrophysics Data System (ADS)

Bogachev, Mikhail I.; Markelov, Oleg A.; Kayumov, Airat R.; Bunde, Armin

2017-02-01

Understanding the physical principles that govern the complex DNA structural organization as well as its mechanical and thermodynamical properties is essential for the advancement in both life sciences and genetic engineering. Recently we have discovered that the complex DNA organization is explicitly reflected in the arrangement of nucleotides depicted by the universal power law tailed internucleotide interval distribution that is valid for complete genomes of various prokaryotic and eukaryotic organisms. Here we suggest a superstatistical model that represents a long DNA molecule by a series of consecutive ~150 bp DNA segments with the alternation of the local nucleotide composition between segments exhibiting long-range correlations. We show that the superstatistical model and the corresponding DNA generation algorithm explicitly reproduce the laws governing the empirical nucleotide arrangement properties of the DNA sequences for various global GC contents and optimal living temperatures. Finally, we discuss the relevance of our model in terms of the DNA mechanical properties. As an outlook, we focus on finding the DNA sequences that encode a given protein while simultaneously reproducing the nucleotide arrangement laws observed from empirical genomes, that may be of interest in the optimization of genetic engineering of long DNA molecules.

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

PubMed

Border, Richard; Keller, Matthew C

2017-03-01

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

The genetic architecture of normal variation in human pigmentation: an evolutionary perspective and model.

PubMed

McEvoy, Brian; Beleza, Sandra; Shriver, Mark D

2006-10-15

Skin pigmentation varies substantially across human populations in a manner largely coincident with ultraviolet radiation intensity. This observation suggests that natural selection in response to sunlight is a major force in accounting for pigmentation variability. We review recent progress in identifying the genes controlling this variation with a particular focus on the trait's evolutionary past and the potential role of testing for signatures of selection in aiding the discovery of functionally important genes. We have analyzed SNP data from the International HapMap project in 77 pigmentation candidate genes for such signatures. On the basis of these results and other similar work, we provide a tentative three-population model (West Africa, East Asia and North Europe) of the evolutionary-genetic architecture of human pigmentation. These results suggest a complex evolutionary history, with selection acting on different gene targets at different times and places in the human past. Some candidate genes may have been selected in the ancestral human population, others in the 'out of Africa' proto European-Asian population, whereas most appear to have selectively evolved solely in either Europeans or East Asians separately despite the pigmentation similarities between these two populations. Selection signatures can provide important clues to aid gene discovery. However, these should be viewed as complements, rather than replacements of, functional studies including linkage and association analyses, which can directly refine our understanding of the trait.

Designing protein-based biomaterials for medical applications.

PubMed

Gagner, Jennifer E; Kim, Wookhyun; Chaikof, Elliot L

2014-04-01

Biomaterials produced by nature have been honed through billions of years, evolving exquisitely precise structure-function relationships that scientists strive to emulate. Advances in genetic engineering have facilitated extensive investigations to determine how changes in even a single peptide within a protein sequence can produce biomaterials with unique thermal, mechanical and biological properties. Elastin, a naturally occurring protein polymer, serves as a model protein to determine the relationship between specific structural elements and desirable material characteristics. The modular, repetitive nature of the protein facilitates the formation of well-defined secondary structures with the ability to self-assemble into complex three-dimensional architectures on a variety of length scales. Furthermore, many opportunities exist to incorporate other protein-based motifs and inorganic materials into recombinant protein-based materials, extending the range and usefulness of these materials in potential biomedical applications. Elastin-like polypeptides (ELPs) can be assembled into 3-D architectures with precise control over payload encapsulation, mechanical and thermal properties, as well as unique functionalization opportunities through both genetic and enzymatic means. An overview of current protein-based materials, their properties and uses in biomedicine will be provided, with a focus on the advantages of ELPs. Applications of these biomaterials as imaging and therapeutic delivery agents will be discussed. Finally, broader implications and future directions of these materials as diagnostic and therapeutic systems will be explored. Copyright © 2013 Elsevier Ltd. All rights reserved.

Designing Protein-Based Biomaterials for Medical Applications

PubMed Central

Gagner, Jennifer E.; Kim, Wookhyun; Chaikof, Elliot L.

2013-01-01

Biomaterials produced by nature have been honed through billions of years, evolving exquisitely precise structure-function relationships that scientists strive to emulate. Advances in genetic engineering have facilitated extensive investigations to determine how changes in even a single peptide within a protein sequence can produce biomaterials with unique thermal, mechanical and biological properties. Elastin, a naturally occurring protein polymer, serves as a model protein to determine the relationship between specific structural elements and desirable material characteristics. The modular, repetitive nature of the protein facilitates the formation of well-defined secondary structures with the ability to self-assemble into complex three-dimensional architectures on a variety of length scales. Furthermore, many opportunities exist to incorporate other protein-based motifs and inorganic materials into recombinant protein-based materials, extending the range and usefulness of these materials in potential biomedical applications. Elastin-like polypeptides can be assembled into 3D architectures with precise control over payload encapsulation, mechanical and thermal properties, as well as unique functionalization opportunities through both genetic and enzymatic means. An overview of current protein-based materials, their properties and uses in biomedicine will be provided, with a focus on the advantages of elastin-like polypeptides. Applications of these biomaterials as imaging and therapeutic delivery agents will be discussed. Finally, broader implications and future directions of these materials as diagnostic and therapeutic systems will be explored. PMID:24121196

The characteristic patterns of neuronal avalanches in mice under anesthesia and at rest: An investigation using constrained artificial neural networks

PubMed Central

Knöpfel, Thomas; Leech, Robert

2018-01-01

Local perturbations within complex dynamical systems can trigger cascade-like events that spread across significant portions of the system. Cascades of this type have been observed across a broad range of scales in the brain. Studies of these cascades, known as neuronal avalanches, usually report the statistics of large numbers of avalanches, without probing the characteristic patterns produced by the avalanches themselves. This is partly due to limitations in the extent or spatiotemporal resolution of commonly used neuroimaging techniques. In this study, we overcome these limitations by using optical voltage (genetically encoded voltage indicators) imaging. This allows us to record cortical activity in vivo across an entire cortical hemisphere, at both high spatial (~30um) and temporal (~20ms) resolution in mice that are either in an anesthetized or awake state. We then use artificial neural networks to identify the characteristic patterns created by neuronal avalanches in our data. The avalanches in the anesthetized cortex are most accurately classified by an artificial neural network architecture that simultaneously connects spatial and temporal information. This is in contrast with the awake cortex, in which avalanches are most accurately classified by an architecture that treats spatial and temporal information separately, due to the increased levels of spatiotemporal complexity. This is in keeping with reports of higher levels of spatiotemporal complexity in the awake brain coinciding with features of a dynamical system operating close to criticality. PMID:29795654

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

PubMed Central

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

2016-01-01

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

Phenotypic and transcriptional response to selection for alcohol sensitivity in Drosophila melanogaster

PubMed Central

Morozova, Tatiana V; Anholt, Robert RH; Mackay, Trudy FC

2007-01-01

Background Alcoholism is a complex disorder determined by interactions between genetic and environmental risk factors. Drosophila represents a powerful model system to dissect the genetic architecture of alcohol sensitivity, as large numbers of flies can readily be reared in defined genetic backgrounds and under controlled environmental conditions. Furthermore, flies exposed to ethanol undergo physiological and behavioral changes that resemble human alcohol intoxication, including loss of postural control, sedation, and development of tolerance. Results We performed artificial selection for alcohol sensitivity for 35 generations and created duplicate selection lines that are either highly sensitive or resistant to ethanol exposure along with unselected control lines. We used whole genome expression analysis to identify 1,678 probe sets with different expression levels between the divergent lines, pooled across replicates, at a false discovery rate of q < 0.001. We assessed to what extent genes with altered transcriptional regulation might be causally associated with ethanol sensitivity by measuring alcohol sensitivity of 37 co-isogenic P-element insertional mutations in 35 candidate genes, and found that 32 of these mutants differed in sensitivity to ethanol exposure from their co-isogenic controls. Furthermore, 23 of these novel genes have human orthologues. Conclusion Combining whole genome expression profiling with selection for genetically divergent lines is an effective approach for identifying candidate genes that affect complex traits, such as alcohol sensitivity. Because of evolutionary conservation of function, it is likely that human orthologues of genes affecting alcohol sensitivity in Drosophila may contribute to alcohol-associated phenotypes in humans. PMID:17973985

Genome-Wide Gene Set Analysis for Identification of Pathways Associated with Alcohol Dependence

PubMed Central

Biernacka, Joanna M.; Geske, Jennifer; Jenkins, Gregory D.; Colby, Colin; Rider, David N.; Karpyak, Victor M.; Choi, Doo-Sup; Fridley, Brooke L.

2013-01-01

It is believed that multiple genetic variants with small individual effects contribute to the risk of alcohol dependence. Such polygenic effects are difficult to detect in genome-wide association studies that test for association of the phenotype with each single nucleotide polymorphism (SNP) individually. To overcome this challenge, gene set analysis (GSA) methods that jointly test for the effects of pre-defined groups of genes have been proposed. Rather than testing for association between the phenotype and individual SNPs, these analyses evaluate the global evidence of association with a set of related genes enabling the identification of cellular or molecular pathways or biological processes that play a role in development of the disease. It is hoped that by aggregating the evidence of association for all available SNPs in a group of related genes, these approaches will have enhanced power to detect genetic associations with complex traits. We performed GSA using data from a genome-wide study of 1165 alcohol dependent cases and 1379 controls from the Study of Addiction: Genetics and Environment (SAGE), for all 200 pathways listed in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Results demonstrated a potential role of the “Synthesis and Degradation of Ketone Bodies” pathway. Our results also support the potential involvement of the “Neuroactive Ligand Receptor Interaction” pathway, which has previously been implicated in addictive disorders. These findings demonstrate the utility of GSA in the study of complex disease, and suggest specific directions for further research into the genetic architecture of alcohol dependence. PMID:22717047

Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes

PubMed Central

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

Sex-specific genetic variances in life-history and morphological traits of the seed beetle Callosobruchus maculatus.

PubMed

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.

Sex-specific genetic variances in life-history and morphological traits of the seed beetle Callosobruchus maculatus

PubMed Central

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

Genetic control of juvenile growth and botanical architecture in an ornamental woody plant, Prunus mume Sieb. et Zucc. as revealed by a high-density linkage map.

PubMed

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.

NPAS1-ARNT and NPAS3-ARNT crystal structures implicate the bHLH-PAS family as multi-ligand binding transcription factors

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

Wu, Dalei; Su, Xiaoyu; Potluri, Nalini

Here, the neuronal PAS domain proteins NPAS1 and NPAS3 are members of the basic helix-loop-helix-PER-ARNT-SIM (bHLH-PAS) family, and their genetic deficiencies are linked to a variety of human psychiatric disorders including schizophrenia, autism spectrum disorders and bipolar disease. NPAS1 and NPAS3 must each heterodimerize with the aryl hydrocarbon receptor nuclear translocator (ARNT), to form functional transcription complexes capable of DNA binding and gene regulation. Here we examined the crystal structures of multi-domain NPAS1-ARNT and NPAS3-ARNT-DNA complexes, discovering each to contain four putative ligand-binding pockets. Through expanded architectural comparisons between these complexes and HIF-1α-ARNT, HIF-2α-ARNT and CLOCK-BMAL1, we show the widermore » mammalian bHLH-PAS family is capable of multi-ligand-binding and presents as an ideal class of transcription factors for direct targeting by small-molecule drugs.« less

NPAS1-ARNT and NPAS3-ARNT crystal structures implicate the bHLH-PAS family as multi-ligand binding transcription factors

DOE PAGES

Wu, Dalei; Su, Xiaoyu; Potluri, Nalini; ...

2016-10-26

Here, the neuronal PAS domain proteins NPAS1 and NPAS3 are members of the basic helix-loop-helix-PER-ARNT-SIM (bHLH-PAS) family, and their genetic deficiencies are linked to a variety of human psychiatric disorders including schizophrenia, autism spectrum disorders and bipolar disease. NPAS1 and NPAS3 must each heterodimerize with the aryl hydrocarbon receptor nuclear translocator (ARNT), to form functional transcription complexes capable of DNA binding and gene regulation. Here we examined the crystal structures of multi-domain NPAS1-ARNT and NPAS3-ARNT-DNA complexes, discovering each to contain four putative ligand-binding pockets. Through expanded architectural comparisons between these complexes and HIF-1α-ARNT, HIF-2α-ARNT and CLOCK-BMAL1, we show the widermore » mammalian bHLH-PAS family is capable of multi-ligand-binding and presents as an ideal class of transcription factors for direct targeting by small-molecule drugs.« less

Function and regulation of the Mediator complex.

PubMed

Conaway, Ronald C; Conaway, Joan Weliky

2011-04-01

Over the past few years, advances in biochemical and genetic studies of the structure and function of the Mediator complex have shed new light on its subunit architecture and its mechanism of action in transcription by RNA polymerase II (pol II). The development of improved methods for reconstitution of recombinant Mediator subassemblies is enabling more in-depth analyses of basic features of the mechanisms by which Mediator interacts with and controls the activity of pol II and the general initiation factors. The discovery and characterization of multiple, functionally distinct forms of Mediator characterized by the presence or absence of the Cdk8 kinase module have led to new insights into how Mediator functions in both Pol II transcription activation and repression. Finally, progress in studies of the mechanisms by which the transcriptional activation domains (ADs) of DNA binding transcription factors target Mediator have brought to light unexpected complexities in the way Mediator participates in signal transduction. Copyright © 2011 Elsevier Ltd. All rights reserved.

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 ...

Estimation of Additive, Dominance, and Imprinting Genetic Variance Using Genomic Data

PubMed Central

Lopes, Marcos S.; Bastiaansen, John W. M.; Janss, Luc; Knol, Egbert F.; Bovenhuis, Henk

2015-01-01

Traditionally, exploration of genetic variance in humans, plants, and livestock species has been limited mostly to the use of additive effects estimated using pedigree data. However, with the development of dense panels of single-nucleotide polymorphisms (SNPs), the exploration of genetic variation of complex traits is moving from quantifying the resemblance between family members to the dissection of genetic variation at individual loci. With SNPs, we were able to quantify the contribution of additive, dominance, and imprinting variance to the total genetic variance by using a SNP regression method. The method was validated in simulated data and applied to three traits (number of teats, backfat, and lifetime daily gain) in three purebred pig populations. In simulated data, the estimates of additive, dominance, and imprinting variance were very close to the simulated values. In real data, dominance effects account for a substantial proportion of the total genetic variance (up to 44%) for these traits in these populations. The contribution of imprinting to the total phenotypic variance of the evaluated traits was relatively small (1–3%). Our results indicate a strong relationship between additive variance explained per chromosome and chromosome length, which has been described previously for other traits in other species. We also show that a similar linear relationship exists for dominance and imprinting variance. These novel results improve our understanding of the genetic architecture of the evaluated traits and shows promise to apply the SNP regression method to other traits and species, including human diseases. PMID:26438289

Assessing the evidence for shared genetic risks across psychiatric disorders and traits.

PubMed

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.

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

PubMed Central

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

2008-01-01

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

Genome-wide association study identified genetic variations and candidate genes for plant architecture component traits in Chinese upland cotton.

PubMed

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.

Genetic architecture of male sterility and segregation distortion in Drosophila pseudoobscura Bogota-USA hybrids.

PubMed

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.

Integrated Genomic and Network-Based Analyses of Complex Diseases and Human Disease Network.

PubMed

Al-Harazi, Olfat; Al Insaif, Sadiq; Al-Ajlan, Monirah A; Kaya, Namik; Dzimiri, Nduna; Colak, Dilek

2016-06-20

A disease phenotype generally reflects various pathobiological processes that interact in a complex network. The highly interconnected nature of the human protein interaction network (interactome) indicates that, at the molecular level, it is difficult to consider diseases as being independent of one another. Recently, genome-wide molecular measurements, data mining and bioinformatics approaches have provided the means to explore human diseases from a molecular basis. The exploration of diseases and a system of disease relationships based on the integration of genome-wide molecular data with the human interactome could offer a powerful perspective for understanding the molecular architecture of diseases. Recently, subnetwork markers have proven to be more robust and reliable than individual biomarker genes selected based on gene expression profiles alone, and achieve higher accuracy in disease classification. We have applied one of these methodologies to idiopathic dilated cardiomyopathy (IDCM) data that we have generated using a microarray and identified significant subnetworks associated with the disease. In this paper, we review the recent endeavours in this direction, and summarize the existing methodologies and computational tools for network-based analysis of complex diseases and molecular relationships among apparently different disorders and human disease network. We also discuss the future research trends and topics of this promising field. Copyright © 2015 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Ltd. All rights reserved.

Priors in Whole-Genome Regression: The Bayesian Alphabet Returns

PubMed Central

Gianola, Daniel

2013-01-01

Whole-genome enabled prediction of complex traits has received enormous attention in animal and plant breeding and is making inroads into human and even Drosophila genetics. The term “Bayesian alphabet” denotes a growing number of letters of the alphabet used to denote various Bayesian linear regressions that differ in the priors adopted, while sharing the same sampling model. We explore the role of the prior distribution in whole-genome regression models for dissecting complex traits in what is now a standard situation with genomic data where the number of unknown parameters (p) typically exceeds sample size (n). Members of the alphabet aim to confront this overparameterization in various manners, but it is shown here that the prior is always influential, unless n ≫ p. This happens because parameters are not likelihood identified, so Bayesian learning is imperfect. Since inferences are not devoid of the influence of the prior, claims about genetic architecture from these methods should be taken with caution. However, all such procedures may deliver reasonable predictions of complex traits, provided that some parameters (“tuning knobs”) are assessed via a properly conducted cross-validation. It is concluded that members of the alphabet have a room in whole-genome prediction of phenotypes, but have somewhat doubtful inferential value, at least when sample size is such that n ≪ p. PMID:23636739

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...

An analysis of genetic architecture in populations of Ponderosa Pine

Treesearch

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...

Detection of pleiotropy through a Phenome-wide association study (PheWAS) of epidemiologic data as part of the Environmental Architecture for Genes Linked to Environment (EAGLE) study.

PubMed

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.

A Theoretical Approach to Norm Ecosystems: Two Adaptive Architectures of Indirect Reciprocity Show Different Paths to the Evolution of Cooperation

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.

Changing the spatial pattern of TFL1 expression reveals its key role in the shoot meristem in controlling Arabidopsis flowering architecture

PubMed Central

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

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

Genetic architecture of white matter hyperintensities differs in hypertensive and nonhypertensive ischemic stroke.

PubMed

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.

Common biological networks underlie genetic risk for alcoholism in African- and European-American populations.

PubMed

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 Architecture of Seed Composition in Soybean Is Refined by Genome-Wide Association Scans Across Multiple Populations

PubMed Central

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

High-throughput neuroimaging-genetics computational infrastructure

PubMed Central

Dinov, Ivo D.; Petrosyan, Petros; Liu, Zhizhong; Eggert, Paul; Hobel, Sam; Vespa, Paul; Woo Moon, Seok; Van Horn, John D.; Franco, Joseph; Toga, Arthur W.

2014-01-01

Many contemporary neuroscientific investigations face significant challenges in terms of data management, computational processing, data mining, and results interpretation. These four pillars define the core infrastructure necessary to plan, organize, orchestrate, validate, and disseminate novel scientific methods, computational resources, and translational healthcare findings. Data management includes protocols for data acquisition, archival, query, transfer, retrieval, and aggregation. Computational processing involves the necessary software, hardware, and networking infrastructure required to handle large amounts of heterogeneous neuroimaging, genetics, clinical, and phenotypic data and meta-data. Data mining refers to the process of automatically extracting data features, characteristics and associations, which are not readily visible by human exploration of the raw dataset. Result interpretation includes scientific visualization, community validation of findings and reproducible findings. In this manuscript we describe the novel high-throughput neuroimaging-genetics computational infrastructure available at the Institute for Neuroimaging and Informatics (INI) and the Laboratory of Neuro Imaging (LONI) at University of Southern California (USC). INI and LONI include ultra-high-field and standard-field MRI brain scanners along with an imaging-genetics database for storing the complete provenance of the raw and derived data and meta-data. In addition, the institute provides a large number of software tools for image and shape analysis, mathematical modeling, genomic sequence processing, and scientific visualization. A unique feature of this architecture is the Pipeline environment, which integrates the data management, processing, transfer, and visualization. Through its client-server architecture, the Pipeline environment provides a graphical user interface for designing, executing, monitoring validating, and disseminating of complex protocols that utilize diverse suites of software tools and web-services. These pipeline workflows are represented as portable XML objects which transfer the execution instructions and user specifications from the client user machine to remote pipeline servers for distributed computing. Using Alzheimer's and Parkinson's data, we provide several examples of translational applications using this infrastructure1. PMID:24795619

Elucidating the genetic architecture of familial schizophrenia using rare copy number variant and linkage scans

PubMed Central

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

Rice Root Architectural Plasticity Traits and Genetic Regions for Adaptability to Variable Cultivation and Stress Conditions1[OPEN

PubMed Central

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

Research in Optical Symbolic Tasks

DTIC Science & Technology

1989-11-29

November 1989. Specifically, we have concentrated on the following topics: complexity studies for optical neural and digital systems, architecture and...1989. Specifically, we hav, concentrated on the following topics: complexity studies for optical neural and digital systems, architecture and models for...Digital Systems 1.1 Digital Optical Parallel System Complexity Our study of digital optical system complexity has included a comparison of optical and

Allele-specific gene expression in a wild nonhuman primate population

PubMed Central

Tung, J.; Akinyi, M. Y.; Mutura, S.; Altmann, J.; Wray, G. A.; Alberts, S. C.

2015-01-01

Natural populations hold enormous potential for evolutionary genetic studies, especially when phenotypic, genetic and environmental data are all available on the same individuals. However, untangling the genotype-phenotype relationship in natural populations remains a major challenge. Here, we describe results of an investigation of one class of phenotype, allele-specific gene expression (ASGE), in the well-studied natural population of baboons of the Amboseli basin, Kenya. ASGE measurements identify cases in which one allele of a gene is overexpressed relative to the alternative allele of the same gene, within individuals, thus providing a control for background genetic and environmental effects. Here, we characterize the incidence of ASGE in the Amboseli baboon population, focusing on the genetic and environmental contributions to ASGE in a set of eleven genes involved in immunity and defence. Within this set, we identify evidence for common ASGE in four genes. We also present examples of two relationships between cis-regulatory genetic variants and the ASGE phenotype. Finally, we identify one case in which this relationship is influenced by a novel gene-environment interaction. Specifically, the dominance rank of an individual’s mother during its early life (an aspect of that individual’s social environment) influences the expression of the gene CCL5 via an interaction with cis-regulatory genetic variation. These results illustrate how environmental and ecological data can be integrated into evolutionary genetic studies of functional variation in natural populations. They also highlight the potential importance of early life environmental variation in shaping the genetic architecture of complex traits in wild mammals. PMID:21226779

Aerodynamic Design of Complex Configurations Using Cartesian Methods and CAD Geometry

NASA Technical Reports Server (NTRS)

Nemec, Marian; Aftosmis, Michael J.; Pulliam, Thomas H.

2003-01-01

The objective for this paper is to present the development of an optimization capability for the Cartesian inviscid-flow analysis package of Aftosmis et al. We evaluate and characterize the following modules within the new optimization framework: (1) A component-based geometry parameterization approach using a CAD solid representation and the CAPRI interface. (2) The use of Cartesian methods in the development Optimization techniques using a genetic algorithm. The discussion and investigations focus on several real world problems of the optimization process. We examine the architectural issues associated with the deployment of a CAD-based design approach in a heterogeneous parallel computing environment that contains both CAD workstations and dedicated compute nodes. In addition, we study the influence of noise on the performance of optimization techniques, and the overall efficiency of the optimization process for aerodynamic design of complex three-dimensional configurations. of automated optimization tools. rithm and a gradient-based algorithm.

Defining Determinants and Dynamics and Cellulose Microfibril Biosynthesis, Assembly and Degredation OSP Number: 63079/A001

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

None, None

The central paradigm for converting plant biomass into soluble sugars for subsequent conversion to transportation fuels involves the enzymatic depolymerization of lignocellulosic plant cell walls by microbial enzymes. Despite decades of intensive research, this is still a relatively inefficient process, due largely to the recalcitrance and enormous complexity of the substrate. A major obstacle is still insufficient understanding of the detailed structure and biosynthesis of major wall components, including cellulose. For example, although cellulose is generally depicted as rigid, insoluble, uniformly crystalline microfibrils that are resistant to enzymatic degradation, the in vivo structures of plant cellulose microfibrils are surprisingly complex.more » Crystallinity is frequently disrupted, for example by dislocations and areas containing chain ends, resulting in “amorphous” disordered regions. Importantly, microfibril structure and the relative proportions of crystalline and non-crystalline disordered surface regions vary substantially and yet the molecular mechanisms by which plants regulate microfibril crystallinity, and other aspects of microfibril architecture, are still entirely unknown. This obviously has a profound effect on susceptibility to enzymatic hydrolysis and so this is a critical area of research in order to characterize and optimize cellulosic biomass degradation. The entire field of cell wall assembly, as distinct from polysaccharide biosynthesis, and the degree to which they are coupled, are relatively unexplored, despite the great potential for major advances in addressing the hurdle of biomass recalcitrance. Our overarching hypothesis was that identification of the molecular machinery that determine microfibril polymerization, deposition and structure will allow the design of more effective degradative systems, and the generation of cellulosic materials with enhanced and predictable bioconversion characteristics. Our experimental framework had been based on the idea that the most effective way to address this long standing and highly complex question is to adopt a broad ‘systems approach’. Accordingly, we assembled a multi-disciplinary collaborative team with collective expertise in plant biology and molecular genetics, polymer structure and chemistry, enzyme biochemistry and biochemical engineering. We used a spectrum of cutting edge technologies, including plant functional genomics, chemical genetics, live cell imaging, advanced microscopy, high energy X-ray spectroscopy and nanotechnology, to study the molecular determinants of cellulose microfibril structure. Importantly, this research effort was closely coupled with an analytical pipeline to characterize the effects of altering microfibril architecture on bioconversion potential, with the goal of generating predictive models to help guide the identification, development and implementation of new feedstocks. This project therefore spanned core basic science and applied research, in line with the goals of the program. Over the course of the project, accomplishments included: - Establishing platforms through reverse and forward genetics to identify and manipulate candidate genes that influence cellulose microfibril synthesis and structure in a model C3 grass, Brachypodium distachyon and a model C4 grass Setaria viridis; Identifying and characterizing the effects of a number of cellulose biosynthesis inhibitors (CBIs), and particularly those that target monocots with the aim of generating resistance loci; Developing protocols for the use of high energy X-ray diffraction (XRD) to study the structure and organization of cellulose microfibrils in plant walls, notably those in Arabidopsis and Brachypodium; Using the chemical and genetic based inhibition strategies to develop new mechanistic models of cellulose microfibril crystallization, and of how altering microfibril architecture influences digestibility.« less

RUNX1 mutations in acute myeloid leukemia are associated with distinct clinico-pathologic and genetic features.

PubMed

Gaidzik, V I; Teleanu, V; Papaemmanuil, E; Weber, D; Paschka, P; Hahn, J; Wallrabenstein, T; Kolbinger, B; Köhne, C H; Horst, H A; Brossart, P; Held, G; Kündgen, A; Ringhoffer, M; Götze, K; Rummel, M; Gerstung, M; Campbell, P; Kraus, J M; Kestler, H A; Thol, F; Heuser, M; Schlegelberger, B; Ganser, A; Bullinger, L; Schlenk, R F; Döhner, K; Döhner, H

2016-11-01

We evaluated the frequency, genetic architecture, clinico-pathologic features and prognostic impact of RUNX1 mutations in 2439 adult patients with newly-diagnosed acute myeloid leukemia (AML). RUNX1 mutations were found in 245 of 2439 (10%) patients; were almost mutually exclusive of AML with recurrent genetic abnormalities; and they co-occurred with a complex pattern of gene mutations, frequently involving mutations in epigenetic modifiers (ASXL1, IDH2, KMT2A, EZH2), components of the spliceosome complex (SRSF2, SF3B1) and STAG2, PHF6, BCOR. RUNX1 mutations were associated with older age (16-59 years: 8.5%; ⩾60 years: 15.1%), male gender, more immature morphology and secondary AML evolving from myelodysplastic syndrome. In univariable analyses, RUNX1 mutations were associated with inferior event-free (EFS, P<0.0001), relapse-free (RFS, P=0.0007) and overall survival (OS, P<0.0001) in all patients, remaining significant when age was considered. In multivariable analysis, RUNX1 mutations predicted for inferior EFS (P=0.01). The effect of co-mutation varied by partner gene, where patients with the secondary genotypes RUNX1 mut /ASXL1 mut (OS, P=0.004), RUNX1 mut /SRSF2 mut (OS, P=0.007) and RUNX1 mut /PHF6 mut (OS, P=0.03) did significantly worse, whereas patients with the genotype RUNX1 mut /IDH2 mut (OS, P=0.04) had a better outcome. In conclusion, RUNX1-mutated AML is associated with a complex mutation cluster and is correlated with distinct clinico-pathologic features and inferior prognosis.

Genetic variants associated with the root system architecture of oilseed rape (Brassica napus L.) under contrasting phosphate supply.

PubMed

Wang, Xiaohua; Chen, Yanling; Thomas, Catherine L; Ding, Guangda; Xu, Ping; Shi, Dexu; Grandke, Fabian; Jin, Kemo; Cai, Hongmei; Xu, Fangsen; Yi, Bin; Broadley, Martin R; Shi, Lei

2017-08-01

Breeding crops with ideal root system architecture for efficient absorption of phosphorus is an important strategy to reduce the use of phosphate fertilizers. To investigate genetic variants leading to changes in root system architecture, 405 oilseed rape cultivars were genotyped with a 60K Brassica Infinium SNP array in low and high P environments. A total of 285 single-nucleotide polymorphisms were associated with root system architecture traits at varying phosphorus levels. Nine single-nucleotide polymorphisms corroborate a previous linkage analysis of root system architecture quantitative trait loci in the BnaTNDH population. One peak single-nucleotide polymorphism region on A3 was associated with all root system architecture traits and co-localized with a quantitative trait locus for primary root length at low phosphorus. Two more single-nucleotide polymorphism peaks on A5 for root dry weight at low phosphorus were detected in both growth systems and co-localized with a quantitative trait locus for the same trait. The candidate genes identified on A3 form a haplotype 'BnA3Hap', that will be important for understanding the phosphorus/root system interaction and for the incorporation into Brassica napus breeding programs. © The Author 2017. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

The gene-environmental architecture of the development of adolescent substance use.

PubMed

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.

Genetic regulation of pre-pubertal development of body mass index: a longitudinal study of Japanese twin boys and girls.

PubMed

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.

Genetic architecture of retinal and macular degenerative diseases: the promise and challenges of next-generation sequencing

PubMed Central

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

Limits to behavioral evolution: the quantitative genetics of a complex trait under directional selection.

PubMed

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.

Three-dimensional facies architecture of the Salem Limestone (middle Mississippian), Eastern Margin of Illinois basin

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

Structural insights into the functions of the FANCM-FAAP24 complex in DNA repair

PubMed Central

Yang, Hui; Zhang, Tianlong; Tao, Ye; Wang, Fang; Tong, Liang; Ding, Jianping

2013-01-01

Fanconi anemia (FA) is a genetically heterogeneous disorder associated with deficiencies in the FA complementation group network. FA complementation group M (FANCM) and FA-associated protein 24 kDa (FAAP24) form a stable complex to anchor the FA core complex to chromatin in repairing DNA interstrand crosslinks. Here, we report the first crystal structure of the C-terminal segment of FANCM in complex with FAAP24. The C-terminal segment of FANCM and FAAP24 both consist of a nuclease domain at the N-terminus and a tandem helix-hairpin-helix (HhH)2 domain at the C-terminus. The FANCM-FAAP24 complex exhibits a similar architecture as that of ApXPF. However, the variations of several key residues and the electrostatic property at the active-site region render a catalytically inactive nuclease domain of FANCM, accounting for the lack of nuclease activity. We also show that the first HhH motif of FAAP24 is a potential binding site for DNA, which plays a critical role in targeting FANCM-FAAP24 to chromatin. These results reveal the mechanistic insights into the functions of FANCM-FAAP24 in DNA repair. PMID:24003026

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...

Polygenic risk score and heritability estimates reveals a genetic relationship between ASD and OCD.

PubMed

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.

Uncovering Local Trends in Genetic Effects of Multiple Phenotypes via Functional Linear Models.

PubMed

Vsevolozhskaya, Olga A; Zaykin, Dmitri V; Barondess, David A; Tong, Xiaoren; Jadhav, Sneha; Lu, Qing

2016-04-01

Recent technological advances equipped researchers with capabilities that go beyond traditional genotyping of loci known to be polymorphic in a general population. Genetic sequences of study participants can now be assessed directly. This capability removed technology-driven bias toward scoring predominantly common polymorphisms and let researchers reveal a wealth of rare and sample-specific variants. Although the relative contributions of rare and common polymorphisms to trait variation are being debated, researchers are faced with the need for new statistical tools for simultaneous evaluation of all variants within a region. Several research groups demonstrated flexibility and good statistical power of the functional linear model approach. In this work we extend previous developments to allow inclusion of multiple traits and adjustment for additional covariates. Our functional approach is unique in that it provides a nuanced depiction of effects and interactions for the variables in the model by representing them as curves varying over a genetic region. We demonstrate flexibility and competitive power of our approach by contrasting its performance with commonly used statistical tools and illustrate its potential for discovery and characterization of genetic architecture of complex traits using sequencing data from the Dallas Heart Study. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Multi-omics analysis of inflammatory bowel disease.

PubMed

Huang, Hu; Vangay, Pajau; McKinlay, Christopher E; Knights, Dan

2014-12-01

Crohn's disease and ulcerative colitis, known together as inflammatory bowel disease (IBD), are severe autoimmune disorders now causing gut inflammation and ulceration, among other symptoms, in up to 1 in 250 people worldwide. Incidence and prevalence of IBD have been increasing dramatically over the past several decades, although the causes for this increase are still unknown. IBD has both a complex genotype and a complex phenotype, and although it has received substantial attention from the medical research community over recent years, much of the etiology remains unexplained. Genome-wide association studies have identified a rich genetic signature of disease risk in patients with IBD, consisting of at least 163 genetic loci. Many of these loci contain genes directly involved in microbial handling, indicating that the genetic architecture of the disease has been driven by host-microbe interactions. In addition, systematic shifts in gut microbiome structure (enterotype) and function have been observed in patients with IBD. Furthermore, both the host genotype and enterotype are associated with aspects of the disease phenotype, including location of the disease. This provides strong evidence of interactions between host genotype and enterotype; however, there is a lack of published multi-omics data from IBD patients, and a lack of bioinformatics tools for modeling such systems. In this article we discuss, from a computational biologist's point of view, the potential benefits of and the challenges involved in designing and analyzing such multi-omics studies of IBD. Copyright © 2014 Elsevier B.V. All rights reserved.

Reptiles: a new model for brain evo-devo research.

PubMed

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.

Foraging environment determines the genetic architecture and evolutionary potential of trophic morphology in cichlid fishes.

PubMed

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.

Genetic structure of the Newfoundland and Labrador population: founder effects modulate variability.

PubMed

Zhai, Guangju; Zhou, Jiayi; Woods, Michael O; Green, Jane S; Parfrey, Patrick; Rahman, Proton; Green, Roger C

2016-07-01

The population of the province of Newfoundland and Labrador (NL) has been a resource for genetic studies because of its historical isolation and increased prevalence of several monogenic disorders. Controversy remains regarding the genetic substructure and the extent of genetic homogeneity, which have implications for disease gene mapping. Population substructure has been reported from other isolated populations such as Iceland, Finland and Sardinia. We undertook this study to further our understanding of the genetic architecture of the NL population. We enrolled 494 individuals randomly selected from NL. Genome-wide SNP data were analyzed together with that from 14 other populations including HapMap3, Ireland, Britain and Native American samples from the Human Genome Diversity Project. Using multidimensional scaling and admixture analysis, we observed that the genetic structure of the NL population resembles that of the British population but can be divided into three clusters that correspond to religious/ethnic origins: Protestant English, Roman Catholic Irish and North American aboriginals. We observed reduced heterozygosity and an increased inbreeding coefficient (mean=0.005), which corresponds to that expected in the offspring of third-cousin marriages. We also found that the NL population has a significantly higher number of runs of homozygosity (ROH) and longer lengths of ROH segments. These results are consistent with our understanding of the population history and indicate that the NL population may be ideal for identifying recessive variants for complex diseases that affect populations of European origin.

Evolutionary evidence of the effect of rare variants on disease etiology.

PubMed

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.

Genetic Architecture of Male Sterility and Segregation Distortion in Drosophila pseudoobscura Bogota–USA Hybrids

PubMed Central

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

TEOSINTE BRANCHED1 Regulates Inflorescence Architecture and Development in Bread Wheat (Triticum aestivum)[OPEN

PubMed Central

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

TEOSINTE BRANCHED1 Regulates Inflorescence Architecture and Development in Bread Wheat (Triticum aestivum).

PubMed

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.

Rare Inherited and De Novo CNVs Reveal Complex Contributions to ASD Risk in Multiplex Families.

PubMed

Leppa, Virpi M; Kravitz, Stephanie N; Martin, Christa Lese; Andrieux, Joris; Le Caignec, Cedric; Martin-Coignard, Dominique; DyBuncio, Christina; Sanders, Stephan J; Lowe, Jennifer K; Cantor, Rita M; Geschwind, Daniel H

2016-09-01

Rare mutations, including copy-number variants (CNVs), contribute significantly to autism spectrum disorder (ASD) risk. Although their importance has been established in families with only one affected child (simplex families), the contribution of both de novo and inherited CNVs to ASD in families with multiple affected individuals (multiplex families) is less well understood. We analyzed 1,532 families from the Autism Genetic Resource Exchange (AGRE) to assess the impact of de novo and rare CNVs on ASD risk in multiplex families. We observed a higher burden of large, rare CNVs, including inherited events, in individuals with ASD than in their unaffected siblings (odds ratio [OR] = 1.7), but the rate of de novo events was significantly lower than in simplex families. In previously characterized ASD risk loci, we identified 49 CNVs, comprising 24 inherited events, 19 de novo events, and 6 events of unknown inheritance, a significant enrichment in affected versus control individuals (OR = 3.3). In 21 of the 30 families (71%) in whom at least one affected sibling harbored an established ASD major risk CNV, including five families harboring inherited CNVs, the CNV was not shared by all affected siblings, indicating that other risk factors are contributing. We also identified a rare risk locus for ASD and language delay at chromosomal region 2q24 (implicating NR4A2) and another lower-penetrance locus involving inherited deletions and duplications of WWOX. The genetic architecture in multiplex families differs from that in simplex families and is complex, warranting more complete genetic characterization of larger multiplex ASD cohorts. Copyright © 2016 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

NLR mutations suppressing immune hybrid incompatibility and their effects on disease resistance.

PubMed

Atanasov, Kostadin Evgeniev; Liu, Changxin; Erban, Alexander; Kopka, Joachim; Parker, Jane E; Alcázar, Rubén

2018-05-23

Genetic divergence between populations can lead to reproductive isolation. Hybrid incompatibilities (HI) represent intermediate points along a continuum towards speciation. In plants, genetic variation in disease resistance (R) genes underlies several cases of HI. The progeny of a cross between Arabidopsis (Arabidopsis thaliana) accessions Landsberg (Ler, Poland) and Kashmir-2 (Kas-2, central Asia) exhibits immune-related HI. This incompatibility is due to a genetic interaction between a cluster of eight TNL (TOLL/INTERLEUKIN1 RECEPTOR- NUCLEOTIDE BINDING - LEUCINE RICH REPEAT) RPP1 (RECOGNITION OF PERONOSPORA PARASITICA 1)- like genes (R1- R8) from Ler and central Asian alleles of a Strubbelig-family receptor-like kinase (SRF3) from Kas-2. In characterizing mutants altered in Ler/Kas-2 HI, we mapped multiple mutations to the RPP1-like Ler locus. Analysis of these suppressor of Ler/Kas-2 incompatibility (sulki) mutants reveals complex, additive and epistatic interactions underlying RPP1-like Ler locus activity. The effects of these mutations were measured on basal defense, global gene expression, primary metabolism, and disease resistance to a local Hyaloperonospora arabidopsidis isolate (Hpa Gw) collected from Gorzów (Gw), where the Landsberg accession originated. Gene expression sectors and metabolic hallmarks identified for HI are both dependent and independent of RPP1-like Ler members. We establish that mutations suppressing immune-related Ler/Kas-2 HI do not compromise resistance to Hpa Gw. QTL mapping analysis of Hpa Gw resistance point to RPP7 as the causal locus. This work provides insight into the complex genetic architecture of the RPP1-like Ler locus and immune-related HI in Arabidopsis and into the contributions of RPP1-like genes to HI and defense. {copyright, serif} 2018 American Society of Plant Biologists. All rights reserved.

Translating Mendelian and complex inheritance of Alzheimer's disease genes for predicting unique personal genome variants

PubMed Central

Regan, Kelly; Wang, Kanix; Doughty, Emily; Li, Haiquan; Li, Jianrong; Lee, Younghee; Kann, Maricel G

2012-01-01

Objective Although trait-associated genes identified as complex versus single-gene inheritance differ substantially in odds ratio, the authors nonetheless posit that their mechanistic concordance can reveal fundamental properties of the genetic architecture, allowing the automated interpretation of unique polymorphisms within a personal genome. Materials and methods An analytical method, SPADE-gen, spanning three biological scales was developed to demonstrate the mechanistic concordance between Mendelian and complex inheritance of Alzheimer's disease (AD) genes: biological functions (BP), protein interaction modeling, and protein domain implicated in the disease-associated polymorphism. Results Among Gene Ontology (GO) biological processes (BP) enriched at a false detection rate <5% in 15 AD genes of Mendelian inheritance (Online Mendelian Inheritance in Man) and independently in those of complex inheritance (25 host genes of intragenic AD single-nucleotide polymorphisms confirmed in genome-wide association studies), 16 overlapped (empirical p=0.007) and 45 were similar (empirical p<0.009; information theory). SPAN network modeling extended the canonical pathway of AD (KEGG) with 26 new protein interactions (empirical p<0.0001). Discussion The study prioritized new AD-associated biological mechanisms and focused the analysis on previously unreported interactions associated with the biological processes of polymorphisms that affect specific protein domains within characterized AD genes and their direct interactors using (1) concordant GO-BP and (2) domain interactions within STRING protein–protein interactions corresponding to the genomic location of the AD polymorphism (eg, EPHA1, APOE, and CD2AP). Conclusion These results are in line with unique-event polymorphism theory, indicating how disease-associated polymorphisms of Mendelian or complex inheritance relate genetically to those observed as ‘unique personal variants’. They also provide insight for identifying novel targets, for repositioning drugs, and for personal therapeutics. PMID:22319180

Acoustic simulation in architecture with parallel algorithm

NASA Astrophysics Data System (ADS)

Li, Xiaohong; Zhang, Xinrong; Li, Dan

2004-03-01

In allusion to complexity of architecture environment and Real-time simulation of architecture acoustics, a parallel radiosity algorithm was developed. The distribution of sound energy in scene is solved with this method. And then the impulse response between sources and receivers at frequency segment, which are calculated with multi-process, are combined into whole frequency response. The numerical experiment shows that parallel arithmetic can improve the acoustic simulating efficiency of complex scene.

Petri net model for analysis of concurrently processed complex algorithms

NASA Technical Reports Server (NTRS)

Stoughton, John W.; Mielke, Roland R.

1986-01-01

This paper presents a Petri-net model suitable for analyzing the concurrent processing of computationally complex algorithms. The decomposed operations are to be processed in a multiple processor, data driven architecture. Of particular interest is the application of the model to both the description of the data/control flow of a particular algorithm, and to the general specification of the data driven architecture. A candidate architecture is also presented.

Identifying disease polymorphisms from case-control genetic association data.

PubMed

Park, L

2010-12-01

In case-control association studies, it is typical to observe several associated polymorphisms in a gene region. Often the most significantly associated polymorphism is considered to be the disease polymorphism; however, it is not clear whether it is the disease polymorphism or there is more than one disease polymorphism in the gene region. Currently, there is no method that can handle these problems based on the linkage disequilibrium (LD) relationship between polymorphisms. To distinguish real disease polymorphisms from markers in LD, a method that can detect disease polymorphisms in a gene region has been developed. Relying on the LD between polymorphisms in controls, the proposed method utilizes model-based likelihood ratio tests to find disease polymorphisms. This method shows reliable Type I and Type II error rates when sample sizes are large enough, and works better with re-sequenced data. Applying this method to fine mapping using re-sequencing or dense genotyping data would provide important information regarding the genetic architecture of complex traits.

Supergenes and their role in evolution.

PubMed

Thompson, M J; Jiggins, C D

2014-07-01

Adaptation is commonly a multidimensional problem, with changes in multiple traits required to match a complex environment. This is epitomized by balanced polymorphisms in which multiple phenotypes co-exist and are maintained in a population by a balance of selective forces. Consideration of such polymorphisms led to the concept of the supergene, where alternative phenotypes in a balanced polymorphism segregate as if controlled by a single genetic locus, resulting from tight genetic linkage between multiple functional loci. Recently, the molecular basis for several supergenes has been resolved. Thus, major chromosomal inversions have been shown to be associated with polymorphisms in butterflies, ants and birds, offering a mechanism for localised reduction in recombination. In several examples of plant self-incompatibility, the functional role of multiple elements within the supergene architecture has been demonstrated, conclusively showing that balanced polymorphism can be maintained at multiple coadapted and tightly linked elements. Despite recent criticism, we argue that the supergene concept remains relevant and is more testable than ever with modern molecular methods.

Protein Kinases in Shaping Plant Architecture.

PubMed

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.

Fourier transform spectrometer controller for partitioned architectures

NASA Astrophysics Data System (ADS)

Tamas-Selicean, D.; Keymeulen, D.; Berisford, D.; Carlson, R.; Hand, K.; Pop, P.; Wadsworth, W.; Levy, R.

The current trend in spacecraft computing is to integrate applications of different criticality levels on the same platform using no separation. This approach increases the complexity of the development, verification and integration processes, with an impact on the whole system life cycle. Researchers at ESA and NASA advocated for the use of partitioned architecture to reduce this complexity. Partitioned architectures rely on platform mechanisms to provide robust temporal and spatial separation between applications. Such architectures have been successfully implemented in several industries, such as avionics and automotive. In this paper we investigate the challenges of developing and the benefits of integrating a scientific instrument, namely a Fourier Transform Spectrometer, in such a partitioned architecture.

Scalable boson sampling with time-bin encoding using a loop-based architecture.

PubMed

Motes, Keith R; Gilchrist, Alexei; Dowling, Jonathan P; Rohde, Peter P

2014-09-19

We present an architecture for arbitrarily scalable boson sampling using two nested fiber loops. The architecture has fixed experimental complexity, irrespective of the size of the desired interferometer, whose scale is limited only by fiber and switch loss rates. The architecture employs time-bin encoding, whereby the incident photons form a pulse train, which enters the loops. Dynamically controlled loop coupling ratios allow the construction of the arbitrary linear optics interferometers required for boson sampling. The architecture employs only a single point of interference and may thus be easier to stabilize than other approaches. The scheme has polynomial complexity and could be realized using demonstrated present-day technologies.

Noise-Coupled Image Rejection Architecture of Complex Bandpass ΔΣAD Modulator

NASA Astrophysics Data System (ADS)

San, Hao; Kobayashi, Haruo

This paper proposes a new realization technique of image rejection function by noise-coupling architecture, which is used for a complex bandpass ΔΣAD modulator. The complex bandpass ΔΣAD modulator processes just input I and Q signals, not image signals, and the AD conversion can be realized with low power dissipation. It realizes an asymmetric noise-shaped spectra, which is desirable for such low-IF receiver applications. However, the performance of the complex bandpass ΔΣAD modulator suffers from the mismatch between internal analog I and Q paths. I/Q path mismatch causes an image signal, and the quantization noise of the mirror image band aliases into the desired signal band, which degrades the SQNDR (Signal to Quantization Noise and Distortion Ratio) of the modulator. In our proposed modulator architecture, an extra notch for image rejection is realized by noise-coupled topology. We just add some passive capacitors and switches to the modulator; the additional integrator circuit composed of an operational amplifier in the conventional image rejection realization is not necessary. Therefore, the performance of the complex modulator can be effectively raised without additional power dissipation. We have performed simulation with MATLAB to confirm the validity of the proposed architecture. The simulation results show that the proposed architecture can achieve the realization of image-rejection effectively, and improve the SQNDR of the complex bandpass ΔΣAD modulator.

Phenotyping: Using Machine Learning for Improved Pairwise Genotype Classification Based on Root Traits

PubMed Central

Zhao, Jiangsan; Bodner, Gernot; Rewald, Boris

2016-01-01

Phenotyping local crop cultivars is becoming more and more important, as they are an important genetic source for breeding – especially in regard to inherent root system architectures. Machine learning algorithms are promising tools to assist in the analysis of complex data sets; novel approaches are need to apply them on root phenotyping data of mature plants. A greenhouse experiment was conducted in large, sand-filled columns to differentiate 16 European Pisum sativum cultivars based on 36 manually derived root traits. Through combining random forest and support vector machine models, machine learning algorithms were successfully used for unbiased identification of most distinguishing root traits and subsequent pairwise cultivar differentiation. Up to 86% of pea cultivar pairs could be distinguished based on top five important root traits (Timp5) – Timp5 differed widely between cultivar pairs. Selecting top important root traits (Timp) provided a significant improved classification compared to using all available traits or randomly selected trait sets. The most frequent Timp of mature pea cultivars was total surface area of lateral roots originating from tap root segments at 0–5 cm depth. The high classification rate implies that culturing did not lead to a major loss of variability in root system architecture in the studied pea cultivars. Our results illustrate the potential of machine learning approaches for unbiased (root) trait selection and cultivar classification based on rather small, complex phenotypic data sets derived from pot experiments. Powerful statistical approaches are essential to make use of the increasing amount of (root) phenotyping information, integrating the complex trait sets describing crop cultivars. PMID:27999587

SZDB: A Database for Schizophrenia Genetic Research

PubMed Central

Wu, Yong; Yao, Yong-Gang

2017-01-01

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

Missing links: the genetic architecture of flowers [correction of flower] and floral diversification.

PubMed

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.

PubMed

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

PubMed Central

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

Telomere healing following DNA polymerase arrest-induced breakages is likely the main mechanism generating chromosome 4p terminal deletions.

PubMed

Hannes, Femke; Van Houdt, Jeroen; Quarrell, Oliver W; Poot, Martin; Hochstenbach, Ron; Fryns, Jean-Pierre; Vermeesch, Joris R

2010-12-01

Constitutional developmental disorders are frequently caused by terminal chromosomal deletions. The mechanisms and/or architectural features that might underlie those chromosome breakages remain largely unexplored. Because telomeres are the vital DNA protein complexes stabilizing linear chromosomes against chromosome degradation, fusion, and incomplete replication, those terminal-deleted chromosomes acquired new telomeres either by telomere healing or by telomere capture. To unravel the mechanisms leading to chromosomal breakage and healing, we sequenced nine chromosome 4p terminal deletion boundaries. A computational analysis of the breakpoint flanking region, including 12 previously published pure terminal breakage sites, was performed in order to identify architectural features that might be involved in this process. All terminal 4p truncations were likely stabilized by telomerase-mediated telomere healing. In the majority of breakpoints multiple genetic elements have a potential to induce secondary structures and an enrichment in replication stalling site motifs were identified. These findings suggest DNA replication stalling-induced chromosome breakage during early development is the first mechanistic step leading toward terminal deletion syndromes. © 2010 Wiley-Liss, Inc.

Remodeling the zonula adherens in response to tension and the role of afadin in this response

PubMed Central

Acharya, Bipul R.; Peyret, Grégoire; Fardin, Marc-Antoine; Mège, René-Marc; Ladoux, Benoit; Yap, Alpha S.; Fanning, Alan S.

2016-01-01

Morphogenesis requires dynamic coordination between cell–cell adhesion and the cytoskeleton to allow cells to change shape and move without losing tissue integrity. We used genetic tools and superresolution microscopy in a simple model epithelial cell line to define how the molecular architecture of cell–cell zonula adherens (ZA) is modified in response to elevated contractility, and how these cells maintain tissue integrity. We previously found that depleting zonula occludens 1 (ZO-1) family proteins in MDCK cells induces a highly organized contractile actomyosin array at the ZA. We find that ZO knockdown elevates contractility via a Shroom3/Rho-associated, coiled-coil containing protein kinase (ROCK) pathway. Our data suggest that each bicellular border is an independent contractile unit, with actin cables anchored end-on to cadherin complexes at tricellular junctions. Cells respond to elevated contractility by increasing junctional afadin. Although ZO/afadin knockdown did not prevent contractile array assembly, it dramatically altered cell shape and barrier function in response to elevated contractility. We propose that afadin acts as a robust protein scaffold that maintains ZA architecture at tricellular junctions. PMID:27114502

Modular architecture of the T4 phage superfamily: A conserved core genome and a plastic periphery

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

Comeau, Andre M.; Bertrand, Claire; Letarov, Andrei

2007-06-05

Among the most numerous objects in the biosphere, phages show enormous diversity in morphology and genetic content. We have sequenced 7 T4-like phages and compared their genome architecture. All seven phages share a core genome with T4 that is interrupted by several hyperplastic regions (HPRs) where most of their divergence occurs. The core primarily includes homologues of essential T4 genes, such as the virion structure and DNA replication genes. In contrast, the HPRs contain mostly novel genes of unknown function and origin. A few of the HPR genes that can be assigned putative functions, such as a series of novelmore » Internal Proteins, are implicated in phage adaptation to the host. Thus, the T4-like genome appears to be partitioned into discrete segments that fulfil different functions and behave differently in evolution. Such partitioning may be critical for these large and complex phages to maintain their flexibility, while simultaneously allowing them to conserve their highly successful virion design and mode of replication.« less

A Principled Approach to the Specification of System Architectures for Space Missions

NASA Technical Reports Server (NTRS)

McKelvin, Mark L. Jr.; Castillo, Robert; Bonanne, Kevin; Bonnici, Michael; Cox, Brian; Gibson, Corrina; Leon, Juan P.; Gomez-Mustafa, Jose; Jimenez, Alejandro; Madni, Azad

2015-01-01

Modern space systems are increasing in complexity and scale at an unprecedented pace. Consequently, innovative methods, processes, and tools are needed to cope with the increasing complexity of architecting these systems. A key systems challenge in practice is the ability to scale processes, methods, and tools used to architect complex space systems. Traditionally, the process for specifying space system architectures has largely relied on capturing the system architecture in informal descriptions that are often embedded within loosely coupled design documents and domain expertise. Such informal descriptions often lead to misunderstandings between design teams, ambiguous specifications, difficulty in maintaining consistency as the architecture evolves throughout the system development life cycle, and costly design iterations. Therefore, traditional methods are becoming increasingly inefficient to cope with ever-increasing system complexity. We apply the principles of component-based design and platform-based design to the development of the system architecture for a practical space system to demonstrate feasibility of our approach using SysML. Our results show that we are able to apply a systematic design method to manage system complexity, thus enabling effective data management, semantic coherence and traceability across different levels of abstraction in the design chain. Just as important, our approach enables interoperability among heterogeneous tools in a concurrent engineering model based design environment.

Environmental effects on the structure of the G-matrix.

PubMed

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.

Stem cells and bone diseases: new tools, new perspective

PubMed Central

Riminucci, Mara; Remoli, Cristina; Robey, Pamela G.; Bianco, Paolo

2017-01-01

Postnatal skeletal stem cells are a unique class of progenitors with biological properties that extend well beyond the limits of stemness as commonly defined. Skeletal stem cells sustain skeletal tissue homeostasis, organize and maintain the complex architectural structure of the bone marrow microenvironment and provide a niche for hematopoietic progenitor cells. The identification of stem cells in the human post-natal skeleton has profoundly changed our approach to the physiology and pathology of this system. Skeletal diseases have been long interpreted essentially in terms of defective function of differentiated cells and/or abnormal turnover of the matrix they produce. The notion of a skeletal stem cell has brought forth multiple, novel concepts in skeletal biology that provide potential alternative concepts. At the same time, the recognition of the complex functions played by skeletal progenitors, such as the structural and functional organization of the bone marrow, has provided an innovative, unifying perspective for understanding bone and bone marrow changes simultaneously occurring in many disorders. Finally, the possibility to isolate and highly enrich for skeletal progenitors, enables us to reproduce perfectly normal or pathological organ miniatures. These, in turn, provide suitable models to investigate and manipulate the pathogenetic mechanisms of many genetic and non-genetic skeletal diseases. PMID:25240458

Genetics of reproduction and regulation of honeybee (Apis mellifera L.) social behavior.

PubMed

Page, Robert E; Rueppell, Olav; Amdam, Gro V

2012-01-01

Honeybees form complex societies with a division of labor for reproduction, nutrition, nest construction and maintenance, and defense. How does it evolve? Tasks performed by worker honeybees are distributed in time and space. There is no central control over behavior and there is no central genome on which selection can act and effect adaptive change. For 22 years, we have been addressing these questions by selecting on a single social trait associated with nutrition: the amount of surplus pollen (a source of protein) that is stored in the combs of the nest. Forty-two generations of selection have revealed changes at biological levels extending from the society down to the level of the gene. We show how we constructed this vertical understanding of social evolution using behavioral and anatomical analyses, physiology, genetic mapping, and gene knockdowns. We map out the phenotypic and genetic architectures of food storage and foraging behavior and show how they are linked through broad epistasis and pleiotropy affecting a reproductive regulatory network that influences foraging behavior. This is remarkable because worker honeybees have reduced reproductive organs and are normally sterile; however, the reproductive regulatory network has been co-opted for behavioral division of labor.

Emerging Trends in Epigenetic Regulation of Nutrient Deficiency Response in Plants.

PubMed

Sirohi, Gunjan; Pandey, Bipin K; Deveshwar, Priyanka; Giri, Jitender

2016-03-01

Diverse environmental stimuli largely affect the ionic balance of soil, which have a direct effect on growth and crop yield. Details are fast emerging on the genetic/molecular regulators, at whole-genome levels, of plant responses to mineral deficiencies in model and crop plants. These genetic regulators determine the root architecture and physiological adaptations for better uptake and utilization of minerals from soil. Recent evidence also shows the potential roles of epigenetic mechanisms in gene regulation, driven by minerals imbalance. Mineral deficiency or sufficiency leads to developmental plasticity in plants for adaptation, which is preceded by a change in the pattern of gene expression. Notably, such changes at molecular levels are also influenced by altered chromatin structure and methylation patterns, or involvement of other epigenetic components. Interestingly, many of the changes induced by mineral deficiency are also inheritable in the form of epigenetic memory. Unravelling these mechanisms in response to mineral deficiency would further advance our understanding of this complex plant response. Further studies on such approaches may serve as an exciting interaction model of epigenetic and genetic regulations of mineral homeostasis in plants and designing strategies for crop improvement.

A high throughput architecture for a low complexity soft-output demapping algorithm

NASA Astrophysics Data System (ADS)

Ali, I.; Wasenmüller, U.; Wehn, N.

2015-11-01

Iterative channel decoders such as Turbo-Code and LDPC decoders show exceptional performance and therefore they are a part of many wireless communication receivers nowadays. These decoders require a soft input, i.e., the logarithmic likelihood ratio (LLR) of the received bits with a typical quantization of 4 to 6 bits. For computing the LLR values from a received complex symbol, a soft demapper is employed in the receiver. The implementation cost of traditional soft-output demapping methods is relatively large in high order modulation systems, and therefore low complexity demapping algorithms are indispensable in low power receivers. In the presence of multiple wireless communication standards where each standard defines multiple modulation schemes, there is a need to have an efficient demapper architecture covering all the flexibility requirements of these standards. Another challenge associated with hardware implementation of the demapper is to achieve a very high throughput in double iterative systems, for instance, MIMO and Code-Aided Synchronization. In this paper, we present a comprehensive communication and hardware performance evaluation of low complexity soft-output demapping algorithms to select the best algorithm for implementation. The main goal of this work is to design a high throughput, flexible, and area efficient architecture. We describe architectures to execute the investigated algorithms. We implement these architectures on a FPGA device to evaluate their hardware performance. The work has resulted in a hardware architecture based on the figured out best low complexity algorithm delivering a high throughput of 166 Msymbols/second for Gray mapped 16-QAM modulation on Virtex-5. This efficient architecture occupies only 127 slice registers, 248 slice LUTs and 2 DSP48Es.

Complex Event Recognition Architecture

NASA Technical Reports Server (NTRS)

Fitzgerald, William A.; Firby, R. James

2009-01-01

Complex Event Recognition Architecture (CERA) is the name of a computational architecture, and software that implements the architecture, for recognizing complex event patterns that may be spread across multiple streams of input data. One of the main components of CERA is an intuitive event pattern language that simplifies what would otherwise be the complex, difficult tasks of creating logical descriptions of combinations of temporal events and defining rules for combining information from different sources over time. In this language, recognition patterns are defined in simple, declarative statements that combine point events from given input streams with those from other streams, using conjunction, disjunction, and negation. Patterns can be built on one another recursively to describe very rich, temporally extended combinations of events. Thereafter, a run-time matching algorithm in CERA efficiently matches these patterns against input data and signals when patterns are recognized. CERA can be used to monitor complex systems and to signal operators or initiate corrective actions when anomalous conditions are recognized. CERA can be run as a stand-alone monitoring system, or it can be integrated into a larger system to automatically trigger responses to changing environments or problematic situations.

An Evolving Genetic Architecture Interacts with Hill–Robertson Interference to Determine the Benefit of Sex

PubMed Central

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

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...