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.

E-Index for Differentiating Complex Dynamic Traits

PubMed Central

Qi, Jiandong; Sun, Jianfeng; Wang, Jianxin

2016-01-01

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

A systems-genetics approach and data mining tool to assist in the discovery of genes underlying complex traits in Oryza sativa.

PubMed

Ficklin, Stephen P; Feltus, Frank Alex

2013-01-01

Many traits of biological and agronomic significance in plants are controlled in a complex manner where multiple genes and environmental signals affect the expression of the phenotype. In Oryza sativa (rice), thousands of quantitative genetic signals have been mapped to the rice genome. In parallel, thousands of gene expression profiles have been generated across many experimental conditions. Through the discovery of networks with real gene co-expression relationships, it is possible to identify co-localized genetic and gene expression signals that implicate complex genotype-phenotype relationships. In this work, we used a knowledge-independent, systems genetics approach, to discover a high-quality set of co-expression networks, termed Gene Interaction Layers (GILs). Twenty-two GILs were constructed from 1,306 Affymetrix microarray rice expression profiles that were pre-clustered to allow for improved capture of gene co-expression relationships. Functional genomic and genetic data, including over 8,000 QTLs and 766 phenotype-tagged SNPs (p-value < = 0.001) from genome-wide association studies, both covering over 230 different rice traits were integrated with the GILs. An online systems genetics data-mining resource, the GeneNet Engine, was constructed to enable dynamic discovery of gene sets (i.e. network modules) that overlap with genetic traits. GeneNet Engine does not provide the exact set of genes underlying a given complex trait, but through the evidence of gene-marker correspondence, co-expression, and functional enrichment, site visitors can identify genes with potential shared causality for a trait which could then be used for experimental validation. A set of 2 million SNPs was incorporated into the database and serve as a potential set of testable biomarkers for genes in modules that overlap with genetic traits. Herein, we describe two modules found using GeneNet Engine, one with significant overlap with the trait amylose content and another with significant overlap with blast disease resistance.

A Systems-Genetics Approach and Data Mining Tool to Assist in the Discovery of Genes Underlying Complex Traits in Oryza sativa

PubMed Central

Ficklin, Stephen P.; Feltus, Frank Alex

2013-01-01

Many traits of biological and agronomic significance in plants are controlled in a complex manner where multiple genes and environmental signals affect the expression of the phenotype. In Oryza sativa (rice), thousands of quantitative genetic signals have been mapped to the rice genome. In parallel, thousands of gene expression profiles have been generated across many experimental conditions. Through the discovery of networks with real gene co-expression relationships, it is possible to identify co-localized genetic and gene expression signals that implicate complex genotype-phenotype relationships. In this work, we used a knowledge-independent, systems genetics approach, to discover a high-quality set of co-expression networks, termed Gene Interaction Layers (GILs). Twenty-two GILs were constructed from 1,306 Affymetrix microarray rice expression profiles that were pre-clustered to allow for improved capture of gene co-expression relationships. Functional genomic and genetic data, including over 8,000 QTLs and 766 phenotype-tagged SNPs (p-value < = 0.001) from genome-wide association studies, both covering over 230 different rice traits were integrated with the GILs. An online systems genetics data-mining resource, the GeneNet Engine, was constructed to enable dynamic discovery of gene sets (i.e. network modules) that overlap with genetic traits. GeneNet Engine does not provide the exact set of genes underlying a given complex trait, but through the evidence of gene-marker correspondence, co-expression, and functional enrichment, site visitors can identify genes with potential shared causality for a trait which could then be used for experimental validation. A set of 2 million SNPs was incorporated into the database and serve as a potential set of testable biomarkers for genes in modules that overlap with genetic traits. Herein, we describe two modules found using GeneNet Engine, one with significant overlap with the trait amylose content and another with significant overlap with blast disease resistance. PMID:23874666

Differential effects of social stress on laboratory-based decision-making are related to both impulsive personality traits and gender.

PubMed

Wise, Richard J; Phung, Alissa L; Labuschagne, Izelle; Stout, Julie C

2015-01-01

Urgency is the tendency to make impulsive decisions under extreme positive or negative emotional states. Stress, gender and impulsive personality traits are all known to influence decision-making, but no studies have examined the interplay of all of these factors. We exposed 78 men and women to a stress or a non-stress condition, and then administered the Balloon Analogue Risk Task. We found that stress effects varied as a function of gender and urgency traits. Under stress, women low in negative urgency and men high in negative urgency made fewer risky decisions. Positive urgency yielded a similar pattern. Thus, decisions under stress depend on a complex interplay between gender and impulsive personality traits. These findings have implications for clinical disorders, such as substance use disorders, in which there are known deficits in decision-making and high levels of impulsive traits.

Advanced complex trait analysis.

PubMed

Gray, A; Stewart, I; Tenesa, A

2012-12-01

The Genome-wide Complex Trait Analysis (GCTA) software package can quantify the contribution of genetic variation to phenotypic variation for complex traits. However, as those datasets of interest continue to increase in size, GCTA becomes increasingly computationally prohibitive. We present an adapted version, Advanced Complex Trait Analysis (ACTA), demonstrating dramatically improved performance. We restructure the genetic relationship matrix (GRM) estimation phase of the code and introduce the highly optimized parallel Basic Linear Algebra Subprograms (BLAS) library combined with manual parallelization and optimization. We introduce the Linear Algebra PACKage (LAPACK) library into the restricted maximum likelihood (REML) analysis stage. For a test case with 8999 individuals and 279,435 single nucleotide polymorphisms (SNPs), we reduce the total runtime, using a compute node with two multi-core Intel Nehalem CPUs, from ∼17 h to ∼11 min. The source code is fully available under the GNU Public License, along with Linux binaries. For more information see http://www.epcc.ed.ac.uk/software-products/acta. a.gray@ed.ac.uk Supplementary data are available at Bioinformatics online.

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

PubMed Central

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

2012-01-01

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

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

PubMed

Georges, Michel

2007-01-01

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

Deciphering the Interdependence between Ecological and Evolutionary Networks.

PubMed

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

2018-05-24

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

Advances in cereal genomics and applications in crop breeding.

PubMed

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

2006-11-01

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

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.

The search for Pleiades in trait constellations: functional integration and phenotypic selection in the complex flowers of Morrenia brachystephana (Apocynaceae).

PubMed

Baranzelli, M C; Sérsic, A N; Cocucci, A A

2014-04-01

Pollinator-mediated natural selection on single traits, such as corolla tube or spur length, has been well documented. However, flower phenotypes are usually complex, and selection is expected to act on several traits that functionally interact rather than on a single isolated trait. Despite the fact that selection on complex phenotypes is expectedly widespread, multivariate selection modelling on such phenotypes still remains under-explored in plants. Species of the subfamily Asclepiadoideae (Apocynaceae) provide an opportunity to study such complex flower contrivances integrated by fine-scaled organs from disparate developmental origin. We studied the correlation structure among linear floral traits (i) by testing a priori morphological, functional or developmental hypotheses among traits and (ii) by exploring the organization of flower covariation, considering alternative expectations of modular organization or whole flower integration through conditional dependence analysis (CDA) and integration matrices. The phenotypic selection approach was applied to determine whether floral traits involved in the functioning of the pollination mechanism were affected by natural selection. Floral integration was low, suggesting that flowers are organized in more than just one correlation pleiad; our hypothetical functional correlation matrix was significantly correlated with the empirical matrix, and the CDA revealed three putative modules. Analyses of phenotypic selection showed significant linear and correlational gradients, lending support to expectations of functional interactions between floral traits. Significant correlational selection gradients found involved traits of different floral whorls, providing evidence for the existence of functional integration across developmental domains. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Association genetics of growth and adaptive traits in loblolly pine (Pinus taeda L.) using whole-exome-discovered polymorphisms

Treesearch

Mengmeng Lu; Konstantin V. Krutovsky; C. Dana Nelson; Jason B. West; Nathalie A. Reilly; Carol A. Loopstra

2017-01-01

In the USA, forest genetics research began over 100 years ago and loblolly pine breeding programs were established in the 1950s. However, the genetics underlying complex traits of loblolly pine remains to be discovered. To address this, adaptive and growth traits were measured and analyzed in a clonally tested loblolly pine (Pinus taeda L.) population. Over 2.8 million...

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...

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

PubMed

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

2016-04-01

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

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

Synergism and Antagonism of Proximate Mechanisms Enable and Constrain the Response to Simultaneous Selection on Body Size and Development Time: An Empirical Test Using Experimental Evolution.

PubMed

Davidowitz, Goggy; Roff, Derek; Nijhout, H Frederik

2016-11-01

Natural selection acts on multiple traits simultaneously. How mechanisms underlying such traits enable or constrain their response to simultaneous selection is poorly understood. We show how antagonism and synergism among three traits at the developmental level enable or constrain evolutionary change in response to simultaneous selection on two focal traits at the phenotypic level. After 10 generations of 25% simultaneous directional selection on all four combinations of body size and development time in Manduca sexta (Sphingidae), the changes in the three developmental traits predict 93% of the response of development time and 100% of the response of body size. When the two focal traits were under synergistic selection, the response to simultaneous selection was enabled by juvenile hormone and ecdysteroids and constrained by growth rate. When the two focal traits were under antagonistic selection, the response to selection was due primarily to change in growth rate and constrained by the two hormonal traits. The approach used here reduces the complexity of the developmental and endocrine mechanisms to three proxy traits. This generates explicit predictions for the evolutionary response to selection that are based on biologically informed mechanisms. This approach has broad applicability to a diverse range of taxa, including algae, plants, amphibians, mammals, and insects.

Adaptive Value of Phenological Traits in Stressful Environments: Predictions Based on Seed Production and Laboratory Natural Selection

PubMed Central

Glorieux, Cédric; Cuguen, Joel; Roux, Fabrice

2012-01-01

Phenological traits often show variation within and among natural populations of annual plants. Nevertheless, the adaptive value of post-anthesis traits is seldom tested. In this study, we estimated the adaptive values of pre- and post-anthesis traits in two stressful environments (water stress and interspecific competition), using the selfing annual species Arabidopsis thaliana. By estimating seed production and by performing laboratory natural selection (LNS), we assessed the strength and nature (directional, disruptive and stabilizing) of selection acting on phenological traits in A. thaliana under the two tested stress conditions, each with four intensities. Both the type of stress and its intensity affected the strength and nature of selection, as did genetic constraints among phenological traits. Under water stress, both experimental approaches demonstrated directional selection for a shorter life cycle, although bolting time imposes a genetic constraint on the length of the interval between bolting and anthesis. Under interspecific competition, results from the two experimental approaches showed discrepancies. Estimation of seed production predicted directional selection toward early pre-anthesis traits and long post-anthesis periods. In contrast, the LNS approach suggested neutrality for all phenological traits. This study opens questions on adaptation in complex natural environment where many selective pressures act simultaneously. PMID:22403624

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

PubMed

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

2015-10-01

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

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

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

Fitness consequences of larval traits persist across the metamorphic boundary.

PubMed

Crean, Angela J; Monro, Keyne; Marshall, Dustin J

2011-11-01

Metamorphosis is thought to provide an adaptive decoupling between traits specialized for each life-history stage in species with complex life cycles. However, an increasing number of studies are finding that larval traits can carry-over to influence postmetamorphic performance, suggesting that these life-history stages may not be free to evolve independently of each other. We used a phenotypic selection framework to compare the relative and interactive effects of larval size, time to hatching, and time to settlement on postmetamorphic survival and growth in a marine invertebrate, Styela plicata. Time to hatching was the only larval trait found to be under directional selection, individuals that took more time to hatch into larvae survived better after metamorphosis but grew more slowly. Nonlinear selection was found to act on multivariate trait combinations, once again acting in opposite directions for selection acting via survival and growth. Individuals with above average values of larval traits were most likely to survive, but surviving individuals with intermediate larval traits grew to the largest size. These results demonstrate that larval traits can have multiple, complex fitness consequences that persist across the metamorphic boundary; and thus postmetamorphic selection pressures may constrain the evolution of larval traits. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Adaptive landscape and functional diversity of Neotropical cichlids: implications for the ecology and evolution of Cichlinae (Cichlidae; Cichliformes).

PubMed

Arbour, J H; López-Fernández, H

2014-11-01

Morphological, lineage and ecological diversity can vary substantially even among closely related lineages. Factors that influence morphological diversification, especially in functionally relevant traits, can help to explain the modern distribution of disparity across phylogenies and communities. Multivariate axes of feeding functional morphology from 75 species of Neotropical cichlid and a stepwise-AIC algorithm were used to estimate the adaptive landscape of functional morphospace in Cichlinae. Adaptive landscape complexity and convergence, as well as the functional diversity of Cichlinae, were compared with expectations under null evolutionary models. Neotropical cichlid feeding function varied primarily between traits associated with ram feeding vs. suction feeding/biting and secondarily with oral jaw muscle size and pharyngeal crushing capacity. The number of changes in selective regimes and the amount of convergence between lineages was higher than expected under a null model of evolution, but convergence was not higher than expected under a similarly complex adaptive landscape. Functional disparity was compatible with an adaptive landscape model, whereas the distribution of evolutionary change through morphospace corresponded with a process of evolution towards a single adaptive peak. The continentally distributed Neotropical cichlids have evolved relatively rapidly towards a number of adaptive peaks in functional trait space. Selection in Cichlinae functional morphospace is more complex than expected under null evolutionary models. The complexity of selective constraints in feeding morphology has likely been a significant contributor to the diversity of feeding ecology in this clade. © 2014 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

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.

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

Selection of Yeasts as Starter Cultures for Table Olives: A Step-by-Step Procedure

PubMed Central

Bevilacqua, Antonio; Corbo, Maria Rosaria; Sinigaglia, Milena

2012-01-01

The selection of yeasts intended as starters for table olives is a complex process, including a characterization step at laboratory level and a validation at lab level and factory-scale. The characterization at lab level deals with the assessment of some technological traits (growth under different temperatures and at alkaline pHs, effect of salt, and for probiotic strains the resistance to preservatives), enzymatic activities, and some new functional properties (probiotic traits, production of vitamin B-complex, biological debittering). The paper reports on these traits, focusing both on their theoretical implications and lab protocols; moreover, there are some details on predictive microbiology for yeasts of table olives and on the use of multivariate approaches to select suitable starters. PMID:22666220

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

USDA-ARS?s Scientific Manuscript database

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

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

PubMed

Suzuki, Takao K

2017-06-01

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

Dissection of Host Susceptibility to Bacterial Infections and Its Toxins.

PubMed

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

2017-01-01

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

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

PubMed

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

2017-01-01

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

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

PubMed

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

2017-08-24

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

Practical applications of the bioinformatics toolbox for narrowing quantitative trait loci.

PubMed

Burgess-Herbert, Sarah L; Cox, Allison; Tsaih, Shirng-Wern; Paigen, Beverly

2008-12-01

Dissecting the genes involved in complex traits can be confounded by multiple factors, including extensive epistatic interactions among genes, the involvement of epigenetic regulators, and the variable expressivity of traits. Although quantitative trait locus (QTL) analysis has been a powerful tool for localizing the chromosomal regions underlying complex traits, systematically identifying the causal genes remains challenging. Here, through its application to plasma levels of high-density lipoprotein cholesterol (HDL) in mice, we demonstrate a strategy for narrowing QTL that utilizes comparative genomics and bioinformatics techniques. We show how QTL detected in multiple crosses are subjected to both combined cross analysis and haplotype block analysis; how QTL from one species are mapped to the concordant regions in another species; and how genomewide scans associating haplotype groups with their phenotypes can be used to prioritize the narrowed regions. Then we illustrate how these individual methods for narrowing QTL can be systematically integrated for mouse chromosomes 12 and 15, resulting in a significantly reduced number of candidate genes, often from hundreds to <10. Finally, we give an example of how additional bioinformatics resources can be combined with experiments to determine the most likely quantitative trait genes.

A Simple Test Identifies Selection on Complex Traits.

PubMed

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

2018-05-01

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

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

PubMed

Wos, Guillaume; Willi, Yvonne

2018-05-26

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

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.

Limited plasticity in the phenotypic variance-covariance matrix for male advertisement calls in the black field cricket, Teleogryllus commodus

PubMed Central

Pitchers, W. R.; Brooks, R.; Jennions, M. D.; Tregenza, T.; Dworkin, I.; Hunt, J.

2013-01-01

Phenotypic integration and plasticity are central to our understanding of how complex phenotypic traits evolve. Evolutionary change in complex quantitative traits can be predicted using the multivariate breeders’ equation, but such predictions are only accurate if the matrices involved are stable over evolutionary time. Recent work, however, suggests that these matrices are temporally plastic, spatially variable and themselves evolvable. The data available on phenotypic variance-covariance matrix (P) stability is sparse, and largely focused on morphological traits. Here we compared P for the structure of the complex sexual advertisement call of six divergent allopatric populations of the Australian black field cricket, Teleogryllus commodus. We measured a subset of calls from wild-caught crickets from each of the populations and then a second subset after rearing crickets under common-garden conditions for three generations. In a second experiment, crickets from each population were reared in the laboratory on high- and low-nutrient diets and their calls recorded. In both experiments, we estimated P for call traits and used multiple methods to compare them statistically (Flury hierarchy, geometric subspace comparisons and random skewers). Despite considerable variation in means and variances of individual call traits, the structure of P was largely conserved among populations, across generations and between our rearing diets. Our finding that P remains largely stable, among populations and between environmental conditions, suggests that selection has preserved the structure of call traits in order that they can function as an integrated unit. PMID:23530814

From cultural traditions to cumulative culture: parameterizing the differences between human and nonhuman culture.

PubMed

Kempe, Marius; Lycett, Stephen J; Mesoudi, Alex

2014-10-21

Diverse species exhibit cultural traditions, i.e. population-specific profiles of socially learned traits, from songbird dialects to primate tool-use behaviours. However, only humans appear to possess cumulative culture, in which cultural traits increase in complexity over successive generations. Theoretically, it is currently unclear what factors give rise to these phenomena, and consequently why cultural traditions are found in several species but cumulative culture in only one. Here, we address this by constructing and analysing cultural evolutionary models of both phenomena that replicate empirically attestable levels of cultural variation and complexity in chimpanzees and humans. In our model of cultural traditions (Model 1), we find that realistic cultural variation between populations can be maintained even when individuals in different populations invent the same traits and migration between populations is frequent, and under a range of levels of social learning accuracy. This lends support to claims that putative cultural traditions are indeed cultural (rather than genetic) in origin, and suggests that cultural traditions should be widespread in species capable of social learning. Our model of cumulative culture (Model 2) indicates that both the accuracy of social learning and the number of cultural demonstrators interact to determine the complexity of a trait that can be maintained in a population. Combining these models (Model 3) creates two qualitatively distinct regimes in which there are either a few, simple traits, or many, complex traits. We suggest that these regimes correspond to nonhuman and human cultures, respectively. The rarity of cumulative culture in nature may result from this interaction between social learning accuracy and number of demonstrators. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

PubMed

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

2017-08-31

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

Use of genetic data to infer population-specific ecological and phenotypic traits from mixed aggregations

USGS Publications Warehouse

Moran, Paul; Bromaghin, Jeffrey F.; Masuda, Michele

2014-01-01

Many applications in ecological genetics involve sampling individuals from a mixture of multiple biological populations and subsequently associating those individuals with the populations from which they arose. Analytical methods that assign individuals to their putative population of origin have utility in both basic and applied research, providing information about population-specific life history and habitat use, ecotoxins, pathogen and parasite loads, and many other non-genetic ecological, or phenotypic traits. Although the question is initially directed at the origin of individuals, in most cases the ultimate desire is to investigate the distribution of some trait among populations. Current practice is to assign individuals to a population of origin and study properties of the trait among individuals within population strata as if they constituted independent samples. It seemed that approach might bias population-specific trait inference. In this study we made trait inferences directly through modeling, bypassing individual assignment. We extended a Bayesian model for population mixture analysis to incorporate parameters for the phenotypic trait and compared its performance to that of individual assignment with a minimum probability threshold for assignment. The Bayesian mixture model outperformed individual assignment under some trait inference conditions. However, by discarding individuals whose origins are most uncertain, the individual assignment method provided a less complex analytical technique whose performance may be adequate for some common trait inference problems. Our results provide specific guidance for method selection under various genetic relationships among populations with different trait distributions.

Use of Genetic Data to Infer Population-Specific Ecological and Phenotypic Traits from Mixed Aggregations

PubMed Central

Moran, Paul; Bromaghin, Jeffrey F.; Masuda, Michele

2014-01-01

Many applications in ecological genetics involve sampling individuals from a mixture of multiple biological populations and subsequently associating those individuals with the populations from which they arose. Analytical methods that assign individuals to their putative population of origin have utility in both basic and applied research, providing information about population-specific life history and habitat use, ecotoxins, pathogen and parasite loads, and many other non-genetic ecological, or phenotypic traits. Although the question is initially directed at the origin of individuals, in most cases the ultimate desire is to investigate the distribution of some trait among populations. Current practice is to assign individuals to a population of origin and study properties of the trait among individuals within population strata as if they constituted independent samples. It seemed that approach might bias population-specific trait inference. In this study we made trait inferences directly through modeling, bypassing individual assignment. We extended a Bayesian model for population mixture analysis to incorporate parameters for the phenotypic trait and compared its performance to that of individual assignment with a minimum probability threshold for assignment. The Bayesian mixture model outperformed individual assignment under some trait inference conditions. However, by discarding individuals whose origins are most uncertain, the individual assignment method provided a less complex analytical technique whose performance may be adequate for some common trait inference problems. Our results provide specific guidance for method selection under various genetic relationships among populations with different trait distributions. PMID:24905464

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

PubMed

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

2017-07-01

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

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

PubMed

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

2013-08-01

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

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

PubMed Central

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

2013-01-01

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

Divide and conquer: intermediate levels of population fragmentation maximize cultural accumulation.

PubMed

Derex, Maxime; Perreault, Charles; Boyd, Robert

2018-04-05

Identifying the determinants of cumulative cultural evolution is a key issue in the interdisciplinary field of cultural evolution. A widely held view is that large and well-connected social networks facilitate cumulative cultural evolution because they promote the spread of useful cultural traits and prevent the loss of cultural knowledge through factors such as drift. This view stems from models that focus on the transmission of cultural information, without considering how new cultural traits actually arise. In this paper, we review the literature from various fields that suggest that, under some circumstances, increased connectedness can decrease cultural diversity and reduce innovation rates. Incorporating this idea into an agent-based model, we explore the effect of population fragmentation on cumulative culture and show that, for a given population size, there exists an intermediate level of population fragmentation that maximizes the rate of cumulative cultural evolution. This result is explained by the fact that fully connected, non-fragmented populations are able to maintain complex cultural traits but produce insufficient variation and so lack the cultural diversity required to produce highly complex cultural traits. Conversely, highly fragmented populations produce a variety of cultural traits but cannot maintain complex ones. In populations with intermediate levels of fragmentation, cultural loss and cultural diversity are balanced in a way that maximizes cultural complexity. Our results suggest that population structure needs to be taken into account when investigating the relationship between demography and cumulative culture.This article is part of the theme issue 'Bridging cultural gaps: interdisciplinary studies in human cultural evolution'. © 2018 The Author(s).

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

A Neurogenetic Approach to Impulsivity

PubMed Central

Congdon, Eliza; Canli, Turhan

2008-01-01

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

Matching consumer feeding behaviours and resource traits: a fourth-corner problem in food-web theory.

PubMed

Monteiro, Angelo Barbosa; Faria, Lucas Del Bianco

2018-06-06

For decades, food web theory has proposed phenomenological models for the underlying structure of ecological networks. Generally, these models rely on latent niche variables that match the feeding behaviour of consumers with their resource traits. In this paper, we used a comprehensive database to evaluate different hypotheses on the best dependency structure of trait-matching patterns between consumers and resource traits. We found that consumer feeding behaviours had complex interactions with resource traits; however, few dimensions (i.e. latent variables) could reproduce the trait-matching patterns. We discuss our findings in the light of three food web models designed to reproduce the multidimensionality of food web data; additionally, we discuss how using species traits clarify food webs beyond species pairwise interactions and enable studies to infer ecological generality at larger scales, despite potential taxonomic differences, variations in ecological conditions and differences in species abundance between communities. © 2018 John Wiley & Sons Ltd/CNRS.

Leaf traits in parental and hybrid species of Sorbus (Rosaceae).

PubMed

Durkovic, Jaroslav; Kardosová, Monika; Canová, Ingrid; Lagana, Rastislav; Priwitzer, Tibor; Chorvát, Dusan; Cicák, Alojz; Pichler, Viliam

2012-09-01

Knowledge of functional leaf traits can provide important insights into the processes structuring plant communities. In the genus Sorbus, the generation of taxonomic novelty through reticulate evolution that gives rise to new microspecies is believed to be driven primarily by a series of interspecific hybridizations among closely related taxa. We tested hypotheses for dispersion of intermediacy across the leaf traits in Sorbus hybrids and for trait linkages with leaf area and specific leaf area. Here, we measured and compared the whole complex of growth, vascular, and ecophysiological leaf traits among parental (Sorbus aria, Sorbus aucuparia, Sorbus chamaemespilus) and natural hybrid (Sorbus montisalpae, Sorbus zuzanae) species growing under field conditions. A recently developed atomic force microscopy technique, PeakForce quantitative nanomechanical mapping, was used to characterize the topography of cell wall surfaces of tracheary elements and to map the reduced Young's modulus of elasticity. Intermediacy was associated predominantly with leaf growth traits, whereas vascular and ecophysiological traits were mainly parental-like and transgressive phenotypes. Larger-leaf species tended to have lower modulus of elasticity values for midrib tracheary element cell walls. Leaves with a biomass investment related to a higher specific leaf area had a lower density. Leaf area- and length-normalized theoretical hydraulic conductivity was related to leaf thickness. For the whole complex of examined leaf traits, hybrid microspecies were mosaics of parental-like, intermediate, and transgressive phenotypes. The high proportion of transgressive character expressions found in Sorbus hybrids implies that generation of extreme traits through transgressive segregation played a key role in the speciation process.

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

PubMed

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

2015-02-01

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

Floral trait variation and integration as a function of sexual deception in Gorteria diffusa

PubMed Central

Ellis, Allan G.; Brockington, Samuel F.; de Jager, Marinus L.; Mellers, Gregory; Walker, Rachel H.; Glover, Beverley J.

2014-01-01

Phenotypic integration, the coordinated covariance of suites of morphological traits, is critical for proper functioning of organisms. Angiosperm flowers are complex structures comprising suites of traits that function together to achieve effective pollen transfer. Floral integration could reflect shared genetic and developmental control of these traits, or could arise through pollinator-imposed stabilizing correlational selection on traits. We sought to expose mechanisms underlying floral trait integration in the sexually deceptive daisy, Gorteria diffusa, by testing the hypothesis that stabilizing selection imposed by male pollinators on floral traits involved in mimicry has resulted in tighter integration. To do this, we quantified patterns of floral trait variance and covariance in morphologically divergent G. diffusa floral forms representing a continuum in the levels of sexual deception. We show that integration of traits functioning in visual attraction of male pollinators increases with pollinator deception, and is stronger than integration of non-mimicry trait modules. Consistent patterns of within-population trait variance and covariance across floral forms suggest that integration has not been built by stabilizing correlational selection on genetically independent traits. Instead pollinator specialization has selected for tightened integration within modules of linked traits. Despite potentially strong constraint on morphological evolution imposed by developmental genetic linkages between traits, we demonstrate substantial divergence in traits across G. diffusa floral forms and show that divergence has often occurred without altering within-population patterns of trait correlations. PMID:25002705

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

PubMed Central

2011-01-01

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

Statistical power and utility of meta-analysis methods for cross-phenotype genome-wide association studies.

PubMed

Zhu, Zhaozhong; Anttila, Verneri; Smoller, Jordan W; Lee, Phil H

2018-01-01

Advances in recent genome wide association studies (GWAS) suggest that pleiotropic effects on human complex traits are widespread. A number of classic and recent meta-analysis methods have been used to identify genetic loci with pleiotropic effects, but the overall performance of these methods is not well understood. In this work, we use extensive simulations and case studies of GWAS datasets to investigate the power and type-I error rates of ten meta-analysis methods. We specifically focus on three conditions commonly encountered in the studies of multiple traits: (1) extensive heterogeneity of genetic effects; (2) characterization of trait-specific association; and (3) inflated correlation of GWAS due to overlapping samples. Although the statistical power is highly variable under distinct study conditions, we found the superior power of several methods under diverse heterogeneity. In particular, classic fixed-effects model showed surprisingly good performance when a variant is associated with more than a half of study traits. As the number of traits with null effects increases, ASSET performed the best along with competitive specificity and sensitivity. With opposite directional effects, CPASSOC featured the first-rate power. However, caution is advised when using CPASSOC for studying genetically correlated traits with overlapping samples. We conclude with a discussion of unresolved issues and directions for future research.

Exploiting induced variation to dissect quantitative traits in barley.

PubMed

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

2010-04-01

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

Deploying QTL-seq for rapid delineation of a potential candidate gene underlying major trait-associated QTL in chickpea

PubMed Central

Das, Shouvik; Upadhyaya, Hari D.; Bajaj, Deepak; Kujur, Alice; Badoni, Saurabh; Laxmi; Kumar, Vinod; Tripathi, Shailesh; Gowda, C. L. Laxmipathi; Sharma, Shivali; Singh, Sube; Tyagi, Akhilesh K.; Parida, Swarup K.

2015-01-01

A rapid high-resolution genome-wide strategy for molecular mapping of major QTL(s)/gene(s) regulating important agronomic traits is vital for in-depth dissection of complex quantitative traits and genetic enhancement in chickpea. The present study for the first time employed a NGS-based whole-genome QTL-seq strategy to identify one major genomic region harbouring a robust 100-seed weight QTL using an intra-specific 221 chickpea mapping population (desi cv. ICC 7184 × desi cv. ICC 15061). The QTL-seq-derived major SW QTL (CaqSW1.1) was further validated by single-nucleotide polymorphism (SNP) and simple sequence repeat (SSR) marker-based traditional QTL mapping (47.6% R2 at higher LOD >19). This reflects the reliability and efficacy of QTL-seq as a strategy for rapid genome-wide scanning and fine mapping of major trait regulatory QTLs in chickpea. The use of QTL-seq and classical QTL mapping in combination narrowed down the 1.37 Mb (comprising 177 genes) major SW QTL (CaqSW1.1) region into a 35 kb genomic interval on desi chickpea chromosome 1 containing six genes. One coding SNP (G/A)-carrying constitutive photomorphogenic9 (COP9) signalosome complex subunit 8 (CSN8) gene of these exhibited seed-specific expression, including pronounced differential up-/down-regulation in low and high seed weight mapping parents and homozygous individuals during seed development. The coding SNP mined in this potential seed weight-governing candidate CSN8 gene was found to be present exclusively in all cultivated species/genotypes, but not in any wild species/genotypes of primary, secondary and tertiary gene pools. This indicates the effect of strong artificial and/or natural selection pressure on target SW locus during chickpea domestication. The proposed QTL-seq-driven integrated genome-wide strategy has potential to delineate major candidate gene(s) harbouring a robust trait regulatory QTL rapidly with optimal use of resources. This will further assist us to extrapolate the molecular mechanism underlying complex quantitative traits at a genome-wide scale leading to fast-paced marker-assisted genetic improvement in diverse crop plants, including chickpea. PMID:25922536

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

PubMed

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

2018-02-09

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

Identifying gene networks underlying the neurobiology of ethanol and alcoholism.

PubMed

Wolen, Aaron R; Miles, Michael F

2012-01-01

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

Quantitative trait loci (QTLs) for water use and crop production traits co-locate with major QTL for tolerance to water deficit in a fine-mapping population of pearl millet (Pennisetum glaucum L. R.Br.).

PubMed

Tharanya, Murugesan; Kholova, Jana; Sivasakthi, Kaliamoorthy; Seghal, Deepmala; Hash, Charles Tom; Raj, Basker; Srivastava, Rakesh Kumar; Baddam, Rekha; Thirunalasundari, Thiyagarajan; Yadav, Rattan; Vadez, Vincent

2018-04-21

Four genetic regions associated with water use traits, measured at different levels of plant organization, and with agronomic traits were identified within a previously reported region for terminal water deficit adaptation on linkage group 2. Close linkages between these traits showed the value of phenotyping both for agronomic and secondary traits to better understand plant productive processes. Water saving traits are critical for water stress adaptation of pearl millet, whereas maximizing water use is key to the absence of stress. This research aimed at demonstrating the close relationship between traits measured at different levels of plant organization, some putatively involved in water stress adaptation, and those responsible for agronomic performance. A fine-mapping population of pearl millet, segregating for a previously identified quantitative trait locus (QTL) for adaptation to terminal drought stress on LG02, was phenotyped for traits at different levels of plant organization in different experimental environments (pot culture, high-throughput phenotyping platform, lysimeters, and field). The linkages among traits across the experimental systems were analysed using principal component analysis and QTL co-localization approach. Four regions within the LG02-QTL were found and revealed substantial co-mapping of water use and agronomic traits. These regions, identified across experimental systems, provided genetic evidence of the tight linkages between traits phenotyped at a lower level of plant organization and agronomic traits assessed in the field, therefore deepening our understanding of complex traits and then benefiting both geneticists and breeders. In short: (1) under no/mild stress conditions, increasing biomass and tiller production increased water use and eventually yield; (2) under severe stress conditions, water savings at vegetative stage, from lower plant vigour and fewer tillers in that population, led to more water available during grain filling, expression of stay-green phenotypes, and higher yield.

Image-Based High-Throughput Field Phenotyping of Crop Roots1[W][OPEN

PubMed Central

Bucksch, Alexander; Burridge, James; York, Larry M.; Das, Abhiram; Nord, Eric; Weitz, Joshua S.; Lynch, Jonathan P.

2014-01-01

Current plant phenotyping technologies to characterize agriculturally relevant traits have been primarily developed for use in laboratory and/or greenhouse conditions. In the case of root architectural traits, this limits phenotyping efforts, largely, to young plants grown in specialized containers and growth media. Hence, novel approaches are required to characterize mature root systems of older plants grown under actual soil conditions in the field. Imaging methods able to address the challenges associated with characterizing mature root systems are rare due, in part, to the greater complexity of mature root systems, including the larger size, overlap, and diversity of root components. Our imaging solution combines a field-imaging protocol and algorithmic approach to analyze mature root systems grown in the field. Via two case studies, we demonstrate how image analysis can be utilized to estimate localized root traits that reliably capture heritable architectural diversity as well as environmentally induced architectural variation of both monocot and dicot plants. In the first study, we show that our algorithms and traits (including 13 novel traits inaccessible to manual estimation) can differentiate nine maize (Zea mays) genotypes 8 weeks after planting. The second study focuses on a diversity panel of 188 cowpea (Vigna unguiculata) genotypes to identify which traits are sufficient to differentiate genotypes even when comparing plants whose harvesting date differs up to 14 d. Overall, we find that automatically derived traits can increase both the speed and reproducibility of the trait estimation pipeline under field conditions. PMID:25187526

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.

Sexual selection and the evolution of genital shape and complexity in water striders.

PubMed

Rowe, Locke; Arnqvist, Göran

2012-01-01

Animal genitalia show two striking but incompletely understood evolutionary trends: a great evolutionary divergence in the shape of genitalic structures, and characteristic structural complexity. Both features are thought to result from sexual selection, but explicit comparative tests are hampered by the fact that it is difficult to quantify both morphological complexity and divergence in shape. We undertake a comparative study of multiple nongenitalic and male genital traits in a clade of 15 water strider species to quantify complexity and shape divergence. We show that genital structures are more complex and their shape more divergent among species than nongenital traits. Further, intromittent genital traits are more complex and have evolved more divergently than nonintromittent genital traits. More importantly, shape and complexity of nonintromittent genital traits show correlated evolution with indices of premating sexual selection and intromittent genital traits with postmating sexual selection, suggesting that the evolution of different components of genital morphology are shaped independently by distinct forms of sexual selection. Our quantitative results provide direct comparative support for the hypothesis that sexual selection is associated with morphological complexity in genitalic traits and highlight the importance of quantifying morphological shape and complexity, rather than size in studies of genital evolution. © 2011 The Author(s). Evolution © 2011 The Society for the Study of Evolution.

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.

Genomic selection and complex trait prediction using a fast EM algorithm applied to genome-wide markers

PubMed Central

2010-01-01

Background The information provided by dense genome-wide markers using high throughput technology is of considerable potential in human disease studies and livestock breeding programs. Genome-wide association studies relate individual single nucleotide polymorphisms (SNP) from dense SNP panels to individual measurements of complex traits, with the underlying assumption being that any association is caused by linkage disequilibrium (LD) between SNP and quantitative trait loci (QTL) affecting the trait. Often SNP are in genomic regions of no trait variation. Whole genome Bayesian models are an effective way of incorporating this and other important prior information into modelling. However a full Bayesian analysis is often not feasible due to the large computational time involved. Results This article proposes an expectation-maximization (EM) algorithm called emBayesB which allows only a proportion of SNP to be in LD with QTL and incorporates prior information about the distribution of SNP effects. The posterior probability of being in LD with at least one QTL is calculated for each SNP along with estimates of the hyperparameters for the mixture prior. A simulated example of genomic selection from an international workshop is used to demonstrate the features of the EM algorithm. The accuracy of prediction is comparable to a full Bayesian analysis but the EM algorithm is considerably faster. The EM algorithm was accurate in locating QTL which explained more than 1% of the total genetic variation. A computational algorithm for very large SNP panels is described. Conclusions emBayesB is a fast and accurate EM algorithm for implementing genomic selection and predicting complex traits by mapping QTL in genome-wide dense SNP marker data. Its accuracy is similar to Bayesian methods but it takes only a fraction of the time. PMID:20969788

Signatures of negative selection in the genetic architecture of human complex traits.

PubMed

Zeng, Jian; de Vlaming, Ronald; Wu, Yang; Robinson, Matthew R; Lloyd-Jones, Luke R; Yengo, Loic; Yap, Chloe X; Xue, Angli; Sidorenko, Julia; McRae, Allan F; Powell, Joseph E; Montgomery, Grant W; Metspalu, Andres; Esko, Tonu; Gibson, Greg; Wray, Naomi R; Visscher, Peter M; Yang, Jian

2018-05-01

We develop a Bayesian mixed linear model that simultaneously estimates single-nucleotide polymorphism (SNP)-based heritability, polygenicity (proportion of SNPs with nonzero effects), and the relationship between SNP effect size and minor allele frequency for complex traits in conventionally unrelated individuals using genome-wide SNP data. We apply the method to 28 complex traits in the UK Biobank data (N = 126,752) and show that on average, 6% of SNPs have nonzero effects, which in total explain 22% of phenotypic variance. We detect significant (P < 0.05/28) signatures of natural selection in the genetic architecture of 23 traits, including reproductive, cardiovascular, and anthropometric traits, as well as educational attainment. The significant estimates of the relationship between effect size and minor allele frequency in complex traits are consistent with a model of negative (or purifying) selection, as confirmed by forward simulation. We conclude that negative selection acts pervasively on the genetic variants associated with human complex traits.

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

Trait variation and genetic diversity in a banana genomic selection training population

PubMed Central

Nyine, Moses; Uwimana, Brigitte; Swennen, Rony; Batte, Michael; Brown, Allan; Christelová, Pavla; Hřibová, Eva; Lorenzen, Jim

2017-01-01

Banana (Musa spp.) is an important crop in the African Great Lakes region in terms of income and food security, with the highest per capita consumption worldwide. Pests, diseases and climate change hamper sustainable production of bananas. New breeding tools with increased crossbreeding efficiency are being investigated to breed for resistant, high yielding hybrids of East African Highland banana (EAHB). These include genomic selection (GS), which will benefit breeding through increased genetic gain per unit time. Understanding trait variation and the correlation among economically important traits is an essential first step in the development and selection of suitable GS models for banana. In this study, we tested the hypothesis that trait variations in bananas are not affected by cross combination, cycle, field management and their interaction with genotype. A training population created using EAHB breeding material and its progeny was phenotyped in two contrasting conditions. A high level of correlation among vegetative and yield related traits was observed. Therefore, genomic selection models could be developed for traits that are easily measured. It is likely that the predictive ability of traits that are difficult to phenotype will be similar to less difficult traits they are highly correlated with. Genotype response to cycle and field management practices varied greatly with respect to traits. Yield related traits accounted for 31–35% of principal component variation under low and high input field management conditions. Resistance to Black Sigatoka was stable across cycles but varied under different field management depending on the genotype. The best cross combination was 1201K-1xSH3217 based on selection response (R) of hybrids. Genotyping using simple sequence repeat (SSR) markers revealed that the training population was genetically diverse, reflecting a complex pedigree background, which was mostly influenced by the male parents. PMID:28586365

Trait variation and genetic diversity in a banana genomic selection training population.

PubMed

Nyine, Moses; Uwimana, Brigitte; Swennen, Rony; Batte, Michael; Brown, Allan; Christelová, Pavla; Hřibová, Eva; Lorenzen, Jim; Doležel, Jaroslav

2017-01-01

Banana (Musa spp.) is an important crop in the African Great Lakes region in terms of income and food security, with the highest per capita consumption worldwide. Pests, diseases and climate change hamper sustainable production of bananas. New breeding tools with increased crossbreeding efficiency are being investigated to breed for resistant, high yielding hybrids of East African Highland banana (EAHB). These include genomic selection (GS), which will benefit breeding through increased genetic gain per unit time. Understanding trait variation and the correlation among economically important traits is an essential first step in the development and selection of suitable GS models for banana. In this study, we tested the hypothesis that trait variations in bananas are not affected by cross combination, cycle, field management and their interaction with genotype. A training population created using EAHB breeding material and its progeny was phenotyped in two contrasting conditions. A high level of correlation among vegetative and yield related traits was observed. Therefore, genomic selection models could be developed for traits that are easily measured. It is likely that the predictive ability of traits that are difficult to phenotype will be similar to less difficult traits they are highly correlated with. Genotype response to cycle and field management practices varied greatly with respect to traits. Yield related traits accounted for 31-35% of principal component variation under low and high input field management conditions. Resistance to Black Sigatoka was stable across cycles but varied under different field management depending on the genotype. The best cross combination was 1201K-1xSH3217 based on selection response (R) of hybrids. Genotyping using simple sequence repeat (SSR) markers revealed that the training population was genetically diverse, reflecting a complex pedigree background, which was mostly influenced by the male parents.

The genetic and environmental foundations of political, psychological, social, and economic behaviors: a panel study of twins and families.

PubMed

Hatemi, Peter K; Smith, Kevin; Alford, John R; Martin, Nicholas G; Hibbing, John R

2015-06-01

Here we introduce the Genetic and Environmental Foundations of Political and Economic Behaviors: A Panel Study of Twins and Families (PIs Alford, Hatemi, Hibbing, Martin, and Smith). This study was designed to explore the genetic and environmental influences on social, economic, and political behaviors and attitudes. It involves identifying the psychological mechanisms that operate on these traits, the heritability of complex economic and political traits under varying conditions, and specific genetic correlates of attitudes and behaviors. In addition to describing the study, we conduct novel analyses on the data, estimating the heritability of two traits so far unexplored in the extant literature: Machiavellianism and Baron-Cohen's Empathizing Quotient.

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

PubMed Central

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

2016-01-01

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

Sperm competition, sperm numbers and sperm quality in muroid rodents.

PubMed

Gómez Montoto, Laura; Magaña, Concepción; Tourmente, Maximiliano; Martín-Coello, Juan; Crespo, Cristina; Luque-Larena, Juan José; Gomendio, Montserrat; Roldan, Eduardo R S

2011-03-25

Sperm competition favors increases in relative testes mass and production efficiency, and changes in sperm phenotype that result in faster swimming speeds. However, little is known about its effects on traits that contribute to determine the quality of a whole ejaculate (i.e., proportion of motile, viable, morphologically normal and acrosome intact sperm) and that are key determinants of fertilization success. Two competing hypotheses lead to alternative predictions: (a) sperm quantity and quality traits co-evolve under sperm competition because they play complementary roles in determining ejaculate's competitive ability, or (b) energetic constraints force trade-offs between traits depending on their relevance in providing a competitive advantage. We examined relationships between sperm competition levels, sperm quantity, and traits that determine ejaculate quality, in a comparative study of 18 rodent species using phylogenetically controlled analyses. Total sperm numbers were positively correlated to proportions of normal sperm, acrosome integrity and motile sperm; the latter three were also significantly related among themselves, suggesting no trade-offs between traits. In addition, testes mass corrected for body mass (i.e., relative testes mass), showed a strong association with sperm numbers, and positive significant associations with all sperm traits that determine ejaculate quality with the exception of live sperm. An "overall sperm quality" parameter obtained by principal component analysis (which explained 85% of the variance) was more strongly associated with relative testes mass than any individual quality trait. Overall sperm quality was as strongly associated with relative testes mass as sperm numbers. Thus, sperm quality traits improve under sperm competition in an integrated manner suggesting that a combination of all traits is what makes ejaculates more competitive. In evolutionary terms this implies that a complex network of genetic and developmental pathways underlying processes of sperm formation, maturation, transport in the female reproductive tract, and preparation for fertilization must all evolve in concert.

Selection and constraint underlie irreversibility of tooth loss in cypriniform fishes

PubMed Central

Aigler, Sharon R.; Jandzik, David; Hatta, Kohei; Uesugi, Kentaro; Stock, David W.

2014-01-01

The apparent irreversibility of the loss of complex traits in evolution (Dollo’s Law) has been explained either by constraints on generating the lost traits or the complexity of selection required for their return. Distinguishing between these explanations is challenging, however, and little is known about the specific nature of potential constraints. We investigated the mechanisms underlying the irreversibility of trait loss using reduction of dentition in cypriniform fishes, a lineage that includes the zebrafish (Danio rerio) as a model. Teeth were lost from the mouth and upper pharynx in this group at least 50 million y ago and retained only in the lower pharynx. We identified regional loss of expression of the Ectodysplasin (Eda) signaling ligand as a likely cause of dentition reduction. In addition, we found that overexpression of this gene in the zebrafish is sufficient to restore teeth to the upper pharynx but not to the mouth. Because both regions are competent to respond to Eda signaling with transcriptional output, the likely constraint on the reappearance of oral teeth is the alteration of multiple genetic pathways required for tooth development. The upper pharyngeal teeth are fully formed, but do not exhibit the ancestral relationship to other pharyngeal structures, suggesting that they would not be favored by selection. Our results illustrate an underlying commonality between constraint and selection as explanations for the irreversibility of trait loss; multiple genetic changes would be required to restore teeth themselves to the oral region and optimally functioning ones to the upper pharynx. PMID:24821783

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

PubMed Central

Jiang, Yiwei

2013-01-01

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

Improving crop salt tolerance.

PubMed

Flowers, T J

2004-02-01

Salinity is an ever-present threat to crop yields, especially in countries where irrigation is an essential aid to agriculture. Although the tolerance of saline conditions by plants is variable, crop species are generally intolerant of one-third of the concentration of salts found in seawater. Attempts to improve the salt tolerance of crops through conventional breeding programmes have met with very limited success, due to the complexity of the trait: salt tolerance is complex genetically and physiologically. Tolerance often shows the characteristics of a multigenic trait, with quantitative trait loci (QTLs) associated with tolerance identified in barley, citrus, rice, and tomato and with ion transport under saline conditions in barley, citrus and rice. Physiologically salt tolerance is also complex, with halophytes and less tolerant plants showing a wide range of adaptations. Attempts to enhance tolerance have involved conventional breeding programmes, the use of in vitro selection, pooling physiological traits, interspecific hybridization, using halophytes as alternative crops, the use of marker-aided selection, and the use of transgenic plants. It is surprising that, in spite of the complexity of salt tolerance, there are commonly claims in the literature that the transfer of a single or a few genes can increase the tolerance of plants to saline conditions. Evaluation of such claims reveals that, of the 68 papers produced between 1993 and early 2003, only 19 report quantitative estimates of plant growth. Of these, four papers contain quantitative data on the response of transformants and wild-type of six species without and with salinity applied in an appropriate manner. About half of all the papers report data on experiments conducted under conditions where there is little or no transpiration: such experiments may provide insights into components of tolerance, but are not grounds for claims of enhanced tolerance at the whole plant level. Whether enhanced tolerance, where properly established, is due to the chance alteration of a factor that is limiting in a complex chain or an effect on signalling remains to be elucidated. After ten years of research using transgenic plants to alter salt tolerance, the value of this approach has yet to be established in the field.

Floral trait variation and integration as a function of sexual deception in Gorteria diffusa.

PubMed

Ellis, Allan G; Brockington, Samuel F; de Jager, Marinus L; Mellers, Gregory; Walker, Rachel H; Glover, Beverley J

2014-08-19

Phenotypic integration, the coordinated covariance of suites of morphological traits, is critical for proper functioning of organisms. Angiosperm flowers are complex structures comprising suites of traits that function together to achieve effective pollen transfer. Floral integration could reflect shared genetic and developmental control of these traits, or could arise through pollinator-imposed stabilizing correlational selection on traits. We sought to expose mechanisms underlying floral trait integration in the sexually deceptive daisy, Gorteria diffusa, by testing the hypothesis that stabilizing selection imposed by male pollinators on floral traits involved in mimicry has resulted in tighter integration. To do this, we quantified patterns of floral trait variance and covariance in morphologically divergent G. diffusa floral forms representing a continuum in the levels of sexual deception. We show that integration of traits functioning in visual attraction of male pollinators increases with pollinator deception, and is stronger than integration of non-mimicry trait modules. Consistent patterns of within-population trait variance and covariance across floral forms suggest that integration has not been built by stabilizing correlational selection on genetically independent traits. Instead pollinator specialization has selected for tightened integration within modules of linked traits. Despite potentially strong constraint on morphological evolution imposed by developmental genetic linkages between traits, we demonstrate substantial divergence in traits across G. diffusa floral forms and show that divergence has often occurred without altering within-population patterns of trait correlations. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

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

PubMed Central

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

2015-01-01

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

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

PubMed Central

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

2014-01-01

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

Beyond The Blueprint: Development Of Genome-Informed Trait-Based Models For Prediction Of Microbial Dynamics And Biogeochemical Rates

NASA Astrophysics Data System (ADS)

Brodie, E.; King, E.; Molins, S.; Karaoz, U.; Johnson, J. N.; Bouskill, N.; Hug, L. A.; Thomas, B. C.; Castelle, C. J.; Beller, H. R.; Banfield, J. F.; Steefel, C. I.

2014-12-01

In soils and sediments microorganisms perform essential ecosystem services through their roles in regulating the stability of carbon and the flux of nutrients, and the purification of water. But these are complex systems with the physical, chemical and biological components all intimately connected. Components of this complexity are gradually being uncovered and our understanding of the extent of microbial functional diversity in particular has been enhanced greatly with the development of cultivation independent approaches. However we have not moved far beyond a descriptive and correlative use of this powerful resource. As the ability to reconstruct thousands of genomes from microbial populations using metagenomic techniques gains momentum, the challenge will be to develop an understanding of how these metabolic blueprints serve to influence the fitness of organisms within these complex systems and how populations emerge and impact the physical and chemical properties of their environment. In the presentation we will discuss the development of a trait-based model of microbial activity that simulates coupled guilds of microorganisms that are parameterized including traits extracted from large-scale metagenomic data. Using a reactive transport framework we simulate the thermodynamics of coupled electron donor and acceptor reactions to predict the energy available for respiration, biomass development and exo-enzyme production. Each group within a functional guild is parameterized with a unique combination of traits governing organism fitness under dynamic environmental conditions. This presentation will address our latest developments in the estimation of trait values related to growth rate and the identification and linkage of key fitness traits associated with respiratory and fermentative pathways, macromolecule depolymerization enzymes and nitrogen fixation from metagenomic data. We are testing model sensitivity to initial microbial composition and intra-guild trait variability amongst other parameters and are using this model to explore abiotic controls on community emergence and impact on rates of reactions that contribute to the cycling of carbon across biogeochemical gradients from the soil to the subsurface.

Association analysis of multiple traits by an approach of combining P values.

PubMed

Chen, Lili; Wang, Yong; Zhou, Yajing

2018-03-01

Increasing evidence shows that one variant can affect multiple traits, which is a widespread phenomenon in complex diseases. Joint analysis of multiple traits can increase statistical power of association analysis and uncover the underlying genetic mechanism. Although there are many statistical methods to analyse multiple traits, most of these methods are usually suitable for detecting common variants associated with multiple traits. However, because of low minor allele frequency of rare variant, these methods are not optimal for rare variant association analysis. In this paper, we extend an adaptive combination of P values method (termed ADA) for single trait to test association between multiple traits and rare variants in the given region. For a given region, we use reverse regression model to test each rare variant associated with multiple traits and obtain the P value of single-variant test. Further, we take the weighted combination of these P values as the test statistic. Extensive simulation studies show that our approach is more powerful than several other comparison methods in most cases and is robust to the inclusion of a high proportion of neutral variants and the different directions of effects of causal variants.

Borderline personality disorder traits and their relationship with dimensions of normative personality: a web-based cohort and twin study

PubMed Central

Kendler, K. S.; Myers, J.; Reichborn-Kjennerud, T.

2011-01-01

Objective To describe the structure of genetic and environmental risk factors for four dimensions of borderline personality disorder (BPD) and to understand the source of resemblance of these dimensions and normal personality. Method A web-based sample (n = 44,112 including 542 twin pairs) completed items from 4 scales of the Dimensional Assessment of Personality Pathology Basic Questionnaire and the Big Five Inventory. Results A one-factor common pathway model best fits the 4 BPD scales producing a highly heritable latent liability (heritability = 60%) and strong loadings on all 4 dimensions. Affective instability had the lowest trait-specific genetic loading, suggesting that it was a core feature of BPD. A complex pattern of genetic and environmental associations was found between the big five personality traits and BPD dimensions. The strongest genetic correlations with the BPD traits were generally seen for neuroticism (positive), followed by conscientiousness and agreeableness, both negative. Conclusion In the general population, these four BPD dimensions reflect one underlying highly heritable factor. The association between normative personality and dimensions of BPD is complex with high degrees of genetic correlation. PMID:21198457

Borderline personality disorder traits and their relationship with dimensions of normative personality: a web-based cohort and twin study.

PubMed

Kendler, K S; Myers, J; Reichborn-Kjennerud, T

2011-05-01

To describe the structure of genetic and environmental risk factors for four dimensions of borderline personality disorder (BPD) and to understand the source of resemblance of these dimensions and normal personality. A web-based sample (n = 44,112 including 542 twin pairs) completed items from 4 scales of the Dimensional Assessment of Personality Pathology Basic Questionnaire and the Big Five Inventory. A one-factor common pathway model best fits the 4 BPD scales producing a highly heritable latent liability (heritability = 60%) and strong loadings on all 4 dimensions. Affective instability had the lowest trait-specific genetic loading, suggesting that it was a core feature of BPD. A complex pattern of genetic and environmental associations was found between the big five personality traits and BPD dimensions. The strongest genetic correlations with the BPD traits were generally seen for neuroticism (positive), followed by conscientiousness and agreeableness, both negative. In the general population, these four BPD dimensions reflect one underlying highly heritable factor. The association between normative personality and dimensions of BPD is complex with high degrees of genetic correlation. © 2010 John Wiley & Sons A/S.

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.

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

Long-term dynamics of adaptive evolution in a globally important phytoplankton species to ocean acidification

PubMed Central

Schlüter, Lothar; Lohbeck, Kai T.; Gröger, Joachim P.; Riebesell, Ulf; Reusch, Thorsten B. H.

2016-01-01

Marine phytoplankton may adapt to ocean change, such as acidification or warming, because of their large population sizes and short generation times. Long-term adaptation to novel environments is a dynamic process, and phenotypic change can take place thousands of generations after exposure to novel conditions. We conducted a long-term evolution experiment (4 years = 2100 generations), starting with a single clone of the abundant and widespread coccolithophore Emiliania huxleyi exposed to three different CO2 levels simulating ocean acidification (OA). Growth rates as a proxy for Darwinian fitness increased only moderately under both levels of OA [+3.4% and +4.8%, respectively, at 1100 and 2200 μatm partial pressure of CO2 (Pco2)] relative to control treatments (ambient CO2, 400 μatm). Long-term adaptation to OA was complex, and initial phenotypic responses of ecologically important traits were later reverted. The biogeochemically important trait of calcification, in particular, that had initially been restored within the first year of evolution was later reduced to levels lower than the performance of nonadapted populations under OA. Calcification was not constitutively lost but returned to control treatment levels when high CO2–adapted isolates were transferred back to present-day control CO2 conditions. Selection under elevated CO2 exacerbated a general decrease of cell sizes under long-term laboratory evolution. Our results show that phytoplankton may evolve complex phenotypic plasticity that can affect biogeochemically important traits, such as calcification. Adaptive evolution may play out over longer time scales (>1 year) in an unforeseen way under future ocean conditions that cannot be predicted from initial adaptation responses. PMID:27419227

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

PubMed

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

2011-03-01

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

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

PubMed Central

Kessner, Darren; Novembre, John

2015-01-01

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

SNPs located at CpG sites modulate genome-epigenome interaction

USDA-ARS?s Scientific Manuscript database

DNA methylation is an important molecular-level phenotype that links genotypes and complex disease traits. Previous studies have found local correlation between genetic variants and DNA methylation levels (cis-meQTLs). However, general mechanisms underlying cis-meQTLs are unclear. We conducted a cis...

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

Analysis of cohort studies with multivariate and partially observed disease classification data.

PubMed

Chatterjee, Nilanjan; Sinha, Samiran; Diver, W Ryan; Feigelson, Heather Spencer

2010-09-01

Complex diseases like cancers can often be classified into subtypes using various pathological and molecular traits of the disease. In this article, we develop methods for analysis of disease incidence in cohort studies incorporating data on multiple disease traits using a two-stage semiparametric Cox proportional hazards regression model that allows one to examine the heterogeneity in the effect of the covariates by the levels of the different disease traits. For inference in the presence of missing disease traits, we propose a generalization of an estimating equation approach for handling missing cause of failure in competing-risk data. We prove asymptotic unbiasedness of the estimating equation method under a general missing-at-random assumption and propose a novel influence-function-based sandwich variance estimator. The methods are illustrated using simulation studies and a real data application involving the Cancer Prevention Study II nutrition cohort.

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

Treesearch

Xiaoqing Yu; Guihua Bai; Shuwei Liu; Na Luo; Ying Wang; Douglas S. Richmond; Paula M. Pijut; Scott A. Jackson; Jianming Yu; Yiwei Jiang

2013-01-01

Drought is a major environmental stress limiting growth of perennial grasses in temperate regions. Plant drought tolerance is a complex trait that is controlled by multiple genes. Candidate gene association mapping provides a powerful tool for dissection of complex traits. Candidate gene association mapping of drought tolerance traits was conducted in 192 diverse...

The place of development in mathematical evolutionary theory.

PubMed

Rice, Sean H

2012-09-01

Development plays a critical role in structuring the joint offspring-parent phenotype distribution. It thus must be part of any truly general evolutionary theory. Historically, the offspring-parent distribution has often been treated in such a way as to bury the contribution of development, by distilling from it a single term, either heritability or additive genetic variance, and then working only with this term. I discuss two reasons why this approach is no longer satisfactory. First, the regression of expected offspring phenotype on parent phenotype can easily be nonlinear, and this nonlinearity can have a pronounced impact on the response to selection. Second, even when the offspring-parent regression is linear, it is nearly always a function of the environment, and the precise way that heritability covaries with the environment can have a substantial effect on adaptive evolution. Understanding these complexities of the offspring-parent distribution will require understanding of the developmental processes underlying the traits of interest. I briefly discuss how we can incorporate such complexity into formal evolutionary theory, and why it is likely to be important even for traits that are not traditionally the focus of evo-devo research. Finally, I briefly discuss a topic that is widely seen as being squarely in the domain of evo-devo: novelty. I argue that the same conceptual and mathematical framework that allows us to incorporate developmental complexity into simple models of trait evolution also yields insight into the evolution of novel traits. Copyright © 2011 Wiley Periodicals, Inc., A Wiley Company.

Genome Wide Association Study for Drought, Aflatoxin Resistance, and Important Agronomic Traits of Maize Hybrids in the Sub-Tropics

PubMed Central

Farfan, Ivan D. Barrero; De La Fuente, Gerald N.; Murray, Seth C.; Isakeit, Thomas; Huang, Pei-Cheng; Warburton, Marilyn; Williams, Paul; Windham, Gary L.; Kolomiets, Mike

2015-01-01

The primary maize (Zea mays L.) production areas are in temperate regions throughout the world and this is where most maize breeding is focused. Important but lower yielding maize growing regions such as the sub-tropics experience unique challenges, the greatest of which are drought stress and aflatoxin contamination. Here we used a diversity panel consisting of 346 maize inbred lines originating in temperate, sub-tropical and tropical areas testcrossed to stiff-stalk line Tx714 to investigate these traits. Testcross hybrids were evaluated under irrigated and non-irrigated trials for yield, plant height, ear height, days to anthesis, days to silking and other agronomic traits. Irrigated trials were also inoculated with Aspergillus flavus and evaluated for aflatoxin content. Diverse maize testcrosses out-yielded commercial checks in most trials, which indicated the potential for genetic diversity to improve sub-tropical breeding programs. To identify genomic regions associated with yield, aflatoxin resistance and other important agronomic traits, a genome wide association analysis was performed. Using 60,000 SNPs, this study found 10 quantitative trait variants for grain yield, plant and ear height, and flowering time after stringent multiple test corrections, and after fitting different models. Three of these variants explained 5–10% of the variation in grain yield under both water conditions. Multiple identified SNPs co-localized with previously reported QTL, which narrows the possible location of causal polymorphisms. Novel significant SNPs were also identified. This study demonstrated the potential to use genome wide association studies to identify major variants of quantitative and complex traits such as yield under drought that are still segregating between elite inbred lines. PMID:25714370

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

PubMed Central

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

2014-01-01

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

Decoupled evolution of floral traits and climatic preferences in a clade of Neotropical Gesneriaceae.

PubMed

Serrano-Serrano, Martha Liliana; Perret, Mathieu; Guignard, Maïté; Chautems, Alain; Silvestro, Daniele; Salamin, Nicolas

2015-11-10

Major factors influencing the phenotypic diversity of a lineage can be recognized by characterizing the extent and mode of trait evolution between related species. Here, we compared the evolutionary dynamics of traits associated with floral morphology and climatic preferences in a clade composed of the genera Codonanthopsis, Codonanthe and Nematanthus (Gesneriaceae). To test the mode and specific components that lead to phenotypic diversity in this group, we performed a Bayesian phylogenetic analysis of combined nuclear and plastid DNA sequences and modeled the evolution of quantitative traits related to flower shape and size and to climatic preferences. We propose an alternative approach to display graphically the complex dynamics of trait evolution along a phylogenetic tree using a wide range of evolutionary scenarios. Our results demonstrated heterogeneous trait evolution. Floral shapes displaced into separate regimes selected by the different pollinator types (hummingbirds versus insects), while floral size underwent a clade-specific evolution. Rates of evolution were higher for the clade that is hummingbird pollinated and experienced flower resupination, compared with species pollinated by bees, suggesting a relevant role of plant-pollinator interactions in lowland rainforest. The evolution of temperature preferences is best explained by a model with distinct selective regimes between the Brazilian Atlantic Forest and the other biomes, whereas differentiation along the precipitation axis was characterized by higher rates, compared with temperature, and no regime or clade-specific patterns. Our study shows different selective regimes and clade-specific patterns in the evolution of morphological and climatic components during the diversification of Neotropical species. Our new graphical visualization tool allows the representation of trait trajectories under parameter-rich models, thus contributing to a better understanding of complex evolutionary dynamics.

Accuracy of whole-genome prediction using a genetic architecture-enhanced variance-covariance matrix.

PubMed

Zhang, Zhe; Erbe, Malena; He, Jinlong; Ober, Ulrike; Gao, Ning; Zhang, Hao; Simianer, Henner; Li, Jiaqi

2015-02-09

Obtaining accurate predictions of unobserved genetic or phenotypic values for complex traits in animal, plant, and human populations is possible through whole-genome prediction (WGP), a combined analysis of genotypic and phenotypic data. Because the underlying genetic architecture of the trait of interest is an important factor affecting model selection, we propose a new strategy, termed BLUP|GA (BLUP-given genetic architecture), which can use genetic architecture information within the dataset at hand rather than from public sources. This is achieved by using a trait-specific covariance matrix ( T: ), which is a weighted sum of a genetic architecture part ( S: matrix) and the realized relationship matrix ( G: ). The algorithm of BLUP|GA (BLUP-given genetic architecture) is provided and illustrated with real and simulated datasets. Predictive ability of BLUP|GA was validated with three model traits in a dairy cattle dataset and 11 traits in three public datasets with a variety of genetic architectures and compared with GBLUP and other approaches. Results show that BLUP|GA outperformed GBLUP in 20 of 21 scenarios in the dairy cattle dataset and outperformed GBLUP, BayesA, and BayesB in 12 of 13 traits in the analyzed public datasets. Further analyses showed that the difference of accuracies for BLUP|GA and GBLUP significantly correlate with the distance between the T: and G: matrices. The new strategy applied in BLUP|GA is a favorable and flexible alternative to the standard GBLUP model, allowing to account for the genetic architecture of the quantitative trait under consideration when necessary. This feature is mainly due to the increased similarity between the trait-specific relationship matrix ( T: matrix) and the genetic relationship matrix at unobserved causal loci. Applying BLUP|GA in WGP would ease the burden of model selection. Copyright © 2015 Zhang et al.

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.

Bridging Inter- and Intraspecific Trait Evolution with a Hierarchical Bayesian Approach.

PubMed

Kostikova, Anna; Silvestro, Daniele; Pearman, Peter B; Salamin, Nicolas

2016-05-01

The evolution of organisms is crucially dependent on the evolution of intraspecific variation. Its interactions with selective agents in the biotic and abiotic environments underlie many processes, such as intraspecific competition, resource partitioning and, eventually, species formation. Nevertheless, comparative models of trait evolution neither allow explicit testing of hypotheses related to the evolution of intraspecific variation nor do they simultaneously estimate rates of trait evolution by accounting for both trait mean and variance. Here, we present a model of phenotypic trait evolution using a hierarchical Bayesian approach that simultaneously incorporates interspecific and intraspecific variation. We assume that species-specific trait means evolve under a simple Brownian motion process, whereas species-specific trait variances are modeled with Brownian or Ornstein-Uhlenbeck processes. After evaluating the power of the method through simulations, we examine whether life-history traits impact evolution of intraspecific variation in the Eriogonoideae (buckwheat family, Polygonaceae). Our model is readily extendible to more complex scenarios of the evolution of inter- and intraspecific variation and presents a step toward more comprehensive comparative models for macroevolutionary studies. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Genetic Analysis of Kernel Traits in Maize-Teosinte Introgression Populations.

PubMed

Liu, Zhengbin; Garcia, Arturo; McMullen, Michael D; Flint-Garcia, Sherry A

2016-08-09

Seed traits have been targeted by human selection during the domestication of crop species as a way to increase the caloric and nutritional content of food during the transition from hunter-gather to early farming societies. The primary seed trait under selection was likely seed size/weight as it is most directly related to overall grain yield. Additional seed traits involved in seed shape may have also contributed to larger grain. Maize (Zea mays ssp. mays) kernel weight has increased more than 10-fold in the 9000 years since domestication from its wild ancestor, teosinte (Z. mays ssp. parviglumis). In order to study how size and shape affect kernel weight, we analyzed kernel morphometric traits in a set of 10 maize-teosinte introgression populations using digital imaging software. We identified quantitative trait loci (QTL) for kernel area and length with moderate allelic effects that colocalize with kernel weight QTL. Several genomic regions with strong effects during maize domestication were detected, and a genetic framework for kernel traits was characterized by complex pleiotropic interactions. Our results both confirm prior reports of kernel domestication loci and identify previously uncharacterized QTL with a range of allelic effects, enabling future research into the genetic basis of these traits. Copyright © 2016 Liu et al.

Genetic Analysis of Kernel Traits in Maize-Teosinte Introgression Populations

PubMed Central

Liu, Zhengbin; Garcia, Arturo; McMullen, Michael D.; Flint-Garcia, Sherry A.

2016-01-01

Seed traits have been targeted by human selection during the domestication of crop species as a way to increase the caloric and nutritional content of food during the transition from hunter-gather to early farming societies. The primary seed trait under selection was likely seed size/weight as it is most directly related to overall grain yield. Additional seed traits involved in seed shape may have also contributed to larger grain. Maize (Zea mays ssp. mays) kernel weight has increased more than 10-fold in the 9000 years since domestication from its wild ancestor, teosinte (Z. mays ssp. parviglumis). In order to study how size and shape affect kernel weight, we analyzed kernel morphometric traits in a set of 10 maize-teosinte introgression populations using digital imaging software. We identified quantitative trait loci (QTL) for kernel area and length with moderate allelic effects that colocalize with kernel weight QTL. Several genomic regions with strong effects during maize domestication were detected, and a genetic framework for kernel traits was characterized by complex pleiotropic interactions. Our results both confirm prior reports of kernel domestication loci and identify previously uncharacterized QTL with a range of allelic effects, enabling future research into the genetic basis of these traits. PMID:27317774

Dissecting the Phenotypic Components of Crop Plant Growth and Drought Responses Based on High-Throughput Image Analysis[W][OPEN

PubMed Central

Chen, Dijun; Neumann, Kerstin; Friedel, Swetlana; Kilian, Benjamin; Chen, Ming; Altmann, Thomas; Klukas, Christian

2014-01-01

Significantly improved crop varieties are urgently needed to feed the rapidly growing human population under changing climates. While genome sequence information and excellent genomic tools are in place for major crop species, the systematic quantification of phenotypic traits or components thereof in a high-throughput fashion remains an enormous challenge. In order to help bridge the genotype to phenotype gap, we developed a comprehensive framework for high-throughput phenotype data analysis in plants, which enables the extraction of an extensive list of phenotypic traits from nondestructive plant imaging over time. As a proof of concept, we investigated the phenotypic components of the drought responses of 18 different barley (Hordeum vulgare) cultivars during vegetative growth. We analyzed dynamic properties of trait expression over growth time based on 54 representative phenotypic features. The data are highly valuable to understand plant development and to further quantify growth and crop performance features. We tested various growth models to predict plant biomass accumulation and identified several relevant parameters that support biological interpretation of plant growth and stress tolerance. These image-based traits and model-derived parameters are promising for subsequent genetic mapping to uncover the genetic basis of complex agronomic traits. Taken together, we anticipate that the analytical framework and analysis results presented here will be useful to advance our views of phenotypic trait components underlying plant development and their responses to environmental cues. PMID:25501589

Estimated breeding values for canine hip dysplasia radiographic traits in a cohort of Australian German Shepherd dogs.

PubMed

Wilson, Bethany J; Nicholas, Frank W; James, John W; Wade, Claire M; Thomson, Peter C

2013-01-01

Canine hip dysplasia (CHD) is a serious and common musculoskeletal disease of pedigree dogs and therefore represents both an important welfare concern and an imperative breeding priority. The typical heritability estimates for radiographic CHD traits suggest that the accuracy of breeding dog selection could be substantially improved by the use of estimated breeding values (EBVs) in place of selection based on phenotypes of individuals. The British Veterinary Association/Kennel Club scoring method is a complex measure composed of nine bilateral ordinal traits, intended to evaluate both early and late dysplastic changes. However, the ordinal nature of the traits may represent a technical challenge for calculation of EBVs using linear methods. The purpose of the current study was to calculate EBVs of British Veterinary Association/Kennel Club traits in the Australian population of German Shepherd Dogs, using linear (both as individual traits and a summed phenotype), binary and ordinal methods to determine the optimal method for EBV calculation. Ordinal EBVs correlated well with linear EBVs (r = 0.90-0.99) and somewhat well with EBVs for the sum of the individual traits (r = 0.58-0.92). Correlation of ordinal and binary EBVs varied widely (r = 0.24-0.99) depending on the trait and cut-point considered. The ordinal EBVs have increased accuracy (0.48-0.69) of selection compared with accuracies from individual phenotype-based selection (0.40-0.52). Despite the high correlations between linear and ordinal EBVs, the underlying relationship between EBVs calculated by the two methods was not always linear, leading us to suggest that ordinal models should be used wherever possible. As the population of German Shepherd Dogs which was studied was purportedly under selection for the traits studied, we examined the EBVs for evidence of a genetic trend in these traits and found substantial genetic improvement over time. This study suggests the use of ordinal EBVs could increase the rate of genetic improvement in this population.

Variation in functional responses to water stress and differentiation between natural allopolyploid populations in the Brachypodium distachyon species complex.

PubMed

Martínez, Luisa M; Fernández-Ocaña, Ana; Rey, Pedro J; Salido, Teresa; Amil-Ruiz, Francisco; Manzaneda, Antonio J

2018-06-08

Some polyploid species show enhanced physiological tolerance to drought compared with their progenitors. However, very few studies have examined the consistency of physiological drought response between genetically differentiated natural polyploid populations, which is key to evaluation of the importance of adaptive evolution after polyploidization in those systems where drought exerts a selective pressure. A comparative functional approach was used to investigate differentiation of drought-tolerance-related traits in the Brachypodium species complex, a model system for grass polyploid adaptive speciation and functional genomics that comprises three closely related annual species: the two diploid parents, B. distachyon and B. stacei, and the allotetraploid derived from them, B. hybridum. Differentiation of drought-tolerance-related traits between ten genetically distinct B. hybridum populations and its ecological correlates was further analysed. The functional drought response is overall well differentiated between Brachypodium species. Brachypodium hybridum allotetraploids showed a transgressive expression pattern in leaf phytohormone content in response to drought. In contrast, other B. hybridum physiological traits correlated to B. stacei ones. Particularly, proline and water content were the traits that best discriminated these species from B. distachyon under drought. After polyploid formation and/or colonization, B. hybridum populations have adaptively diverged physiologically and genetically in response to variations in aridity.

Phenotypic landscape inference reveals multiple evolutionary paths to C4 photosynthesis

PubMed Central

Williams, Ben P; Johnston, Iain G; Covshoff, Sarah; Hibberd, Julian M

2013-01-01

C4 photosynthesis has independently evolved from the ancestral C3 pathway in at least 60 plant lineages, but, as with other complex traits, how it evolved is unclear. Here we show that the polyphyletic appearance of C4 photosynthesis is associated with diverse and flexible evolutionary paths that group into four major trajectories. We conducted a meta-analysis of 18 lineages containing species that use C3, C4, or intermediate C3–C4 forms of photosynthesis to parameterise a 16-dimensional phenotypic landscape. We then developed and experimentally verified a novel Bayesian approach based on a hidden Markov model that predicts how the C4 phenotype evolved. The alternative evolutionary histories underlying the appearance of C4 photosynthesis were determined by ancestral lineage and initial phenotypic alterations unrelated to photosynthesis. We conclude that the order of C4 trait acquisition is flexible and driven by non-photosynthetic drivers. This flexibility will have facilitated the convergent evolution of this complex trait. DOI: http://dx.doi.org/10.7554/eLife.00961.001 PMID:24082995

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

PubMed

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

2015-10-01

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

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

PubMed

Xue, Angli; Wang, Hongcheng; Zhu, Jun

2017-09-28

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

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

Relationships between structural complexity, coral traits, and reef fish assemblages

NASA Astrophysics Data System (ADS)

Darling, Emily S.; Graham, Nicholas A. J.; Januchowski-Hartley, Fraser A.; Nash, Kirsty L.; Pratchett, Morgan S.; Wilson, Shaun K.

2017-06-01

With the ongoing loss of coral cover and the associated flattening of reef architecture, understanding the links between coral habitat and reef fishes is of critical importance. Here, we investigate whether considering coral traits and functional diversity provides new insights into the relationship between structural complexity and reef fish communities, and whether coral traits and community composition can predict structural complexity. Across 157 sites in Seychelles, Maldives, the Chagos Archipelago, and Australia's Great Barrier Reef, we find that structural complexity and reef zone are the strongest and most consistent predictors of reef fish abundance, biomass, species richness, and trophic structure. However, coral traits, diversity, and life histories provided additional predictive power for models of reef fish assemblages, and were key drivers of structural complexity. Our findings highlight that reef complexity relies on living corals—with different traits and life histories—continuing to build carbonate skeletons, and that these nuanced relationships between coral assemblages and habitat complexity can affect the structure of reef fish assemblages. Seascape-level estimates of structural complexity are rapid and cost effective with important implications for the structure and function of fish assemblages, and should be incorporated into monitoring programs.

Phenotypes from ancient DNA: approaches, insights and prospects.

PubMed

Fortes, Gloria G; Speller, Camilla F; Hofreiter, Michael; King, Turi E

2013-08-01

The great majority of phenotypic characteristics are complex traits, complicating the identification of the genes underlying their expression. However, both methodological and theoretical progress in genome-wide association studies have resulted in a much better understanding of the underlying genetics of many phenotypic traits, including externally visible characteristics (EVCs) such as eye and hair color. Consequently, it has become possible to predict EVCs from human samples lacking phenotypic information. Predicting EVCs from genetic evidence is clearly appealing for forensic applications involving the personal identification of human remains. Now, a recent paper has reported the genetic determination of eye and hair color in samples up to 800 years old. The ability to predict EVCs from ancient human remains opens up promising perspectives for ancient DNA research, as this could allow studies to directly address archaeological and evolutionary questions related to the temporal and geographical origins of the genetic variants underlying phenotypes. © 2013 WILEY Periodicals, Inc.

GWAS4D: multidimensional analysis of context-specific regulatory variant for human complex diseases and traits.

PubMed

Huang, Dandan; Yi, Xianfu; Zhang, Shijie; Zheng, Zhanye; Wang, Panwen; Xuan, Chenghao; Sham, Pak Chung; Wang, Junwen; Li, Mulin Jun

2018-05-16

Genome-wide association studies have generated over thousands of susceptibility loci for many human complex traits, and yet for most of these associations the true causal variants remain unknown. Tissue/cell type-specific prediction and prioritization of non-coding regulatory variants will facilitate the identification of causal variants and underlying pathogenic mechanisms for particular complex diseases and traits. By leveraging recent large-scale functional genomics/epigenomics data, we develop an intuitive web server, GWAS4D (http://mulinlab.tmu.edu.cn/gwas4d or http://mulinlab.org/gwas4d), that systematically evaluates GWAS signals and identifies context-specific regulatory variants. The updated web server includes six major features: (i) updates the regulatory variant prioritization method with our new algorithm; (ii) incorporates 127 tissue/cell type-specific epigenomes data; (iii) integrates motifs of 1480 transcriptional regulators from 13 public resources; (iv) uniformly processes Hi-C data and generates significant interactions at 5 kb resolution across 60 tissues/cell types; (v) adds comprehensive non-coding variant functional annotations; (vi) equips a highly interactive visualization function for SNP-target interaction. Using a GWAS fine-mapped set for 161 coronary artery disease risk loci, we demonstrate that GWAS4D is able to efficiently prioritize disease-causal regulatory variants.

Global genetic differentiation of complex traits shaped by natural selection in humans.

PubMed

Guo, Jing; Wu, Yang; Zhu, Zhihong; Zheng, Zhili; Trzaskowski, Maciej; Zeng, Jian; Robinson, Matthew R; Visscher, Peter M; Yang, Jian

2018-05-14

There are mean differences in complex traits among global human populations. We hypothesize that part of the phenotypic differentiation is due to natural selection. To address this hypothesis, we assess the differentiation in allele frequencies of trait-associated SNPs among African, Eastern Asian, and European populations for ten complex traits using data of large sample size (up to ~405,000). We show that SNPs associated with height ([Formula: see text]), waist-to-hip ratio ([Formula: see text]), and schizophrenia ([Formula: see text]) are significantly more differentiated among populations than matched "control" SNPs, suggesting that these trait-associated SNPs have undergone natural selection. We further find that SNPs associated with height ([Formula: see text]) and schizophrenia ([Formula: see text]) show significantly higher variance in linkage disequilibrium (LD) scores across populations than control SNPs. Our results support the hypothesis that natural selection has shaped the genetic differentiation of complex traits, such as height and schizophrenia, among worldwide populations.

Ritual, emotion, and sacred symbols : The evolution of religion as an adaptive complex.

PubMed

Alcorta, Candace S; Sosis, Richard

2005-12-01

This paper considers religion in relation to four recurrent traits: belief systems incorporating supernatural agents and counterintuitive concepts, communal ritual, separation of the sacred and the profane, and adolescence as a preferred developmental period for religious transmission. These co-occurring traits are viewed as an adaptive complex that offers clues to the evolution of religion from its nonhuman ritual roots. We consider the critical element differentiating religious from non-human ritual to be the conditioned association of emotion and abstract symbols. We propose neurophysiological mechanisms underlying such associations and argue that the brain plasticity of human adolescence constitutes an "experience expectant" developmental period for ritual conditioning of sacred symbols. We suggest that such symbols evolved to solve an ecological problem by extending communication and coordination of social relations across time and space.

Symbiotic Dinoflagellate Functional Diversity Mediates Coral Survival under Ecological Crisis.

PubMed

Suggett, David J; Warner, Mark E; Leggat, William

2017-10-01

Coral reefs have entered an era of 'ecological crisis' as climate change drives catastrophic reef loss worldwide. Coral growth and stress susceptibility are regulated by their endosymbiotic dinoflagellates (genus Symbiodinium). The phylogenetic diversity of Symbiodinium frequently corresponds to patterns of coral health and survival, but knowledge of functional diversity is ultimately necessary to reconcile broader ecological success over space and time. We explore here functional traits underpinning the complex biology of Symbiodinium that spans free-living algae to coral endosymbionts. In doing so we propose a mechanistic framework integrating the primary traits of resource acquisition and utilisation as a means to explain Symbiodinium functional diversity and to resolve the role of Symbiodinium in driving the stability of coral reefs under an uncertain future. Copyright © 2017 Elsevier Ltd. All rights reserved.

Directed evolution and synthetic biology applications to microbial systems.

PubMed

Bassalo, Marcelo C; Liu, Rongming; Gill, Ryan T

2016-06-01

Biotechnology applications require engineering complex multi-genic traits. The lack of knowledge on the genetic basis of complex phenotypes restricts our ability to rationally engineer them. However, complex phenotypes can be engineered at the systems level, utilizing directed evolution strategies that drive whole biological systems toward desired phenotypes without requiring prior knowledge of the genetic basis of the targeted trait. Recent developments in the synthetic biology field accelerates the directed evolution cycle, facilitating engineering of increasingly complex traits in biological systems. In this review, we summarize some of the most recent advances in directed evolution and synthetic biology that allows engineering of complex traits in microbial systems. Then, we discuss applications that can be achieved through engineering at the systems level. Copyright © 2016 Elsevier Ltd. All rights reserved.

Giftedness and Genetics: The Emergenic-Epigenetic Model and Its Implications

ERIC Educational Resources Information Center

Simonton, Dean Keith

2005-01-01

The genetic endowment underlying giftedness may operate in a far more complex manner than often expressed in most theoretical accounts of the phenomenon. First, an endowment may be emergenic. That is, a gift may consist of multiple traits (multidimensional) that are inherited in a multiplicative (configurational), rather than an additive (simple)…

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

USDA-ARS?s Scientific Manuscript database

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

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

PubMed

Waliszewski, P; Molski, M; Konarski, J

1998-06-01

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

Dissecting the genetics of complex traits using summary association statistics.

PubMed

Pasaniuc, Bogdan; Price, Alkes L

2017-02-01

During the past decade, genome-wide association studies (GWAS) have been used to successfully identify tens of thousands of genetic variants associated with complex traits and diseases. These studies have produced extensive repositories of genetic variation and trait measurements across large numbers of individuals, providing tremendous opportunities for further analyses. However, privacy concerns and other logistical considerations often limit access to individual-level genetic data, motivating the development of methods that analyse summary association statistics. Here, we review recent progress on statistical methods that leverage summary association data to gain insights into the genetic basis of complex traits and diseases.

Dissecting the genetics of complex traits using summary association statistics

PubMed Central

Pasaniuc, Bogdan; Price, Alkes L.

2017-01-01

During the past decade, genome-wide association studies (GWAS) have successfully identified tens of thousands of genetic variants associated with complex traits and diseases. These studies have produced extensive repositories of genetic variation and trait measurements across large numbers of individuals, providing tremendous opportunities for further analyses. However, privacy concerns and other logistical considerations often limit access to individual-level genetic data, motivating the development of methods that analyze summary association statistics. Here we review recent progress on statistical methods that leverage summary association data to gain insights into the genetic basis of complex traits and diseases. PMID:27840428

Evolution of male coloration during a post-Pleistocene radiation of Bahamas mosquitofish (Gambusia hubbsi).

PubMed

Martin, Ryan A; Riesch, Rüdiger; Heinen-Kay, Justa L; Langerhans, R Brian

2014-02-01

Sexual signal evolution can be complex because multiple factors influence the production, transmission, and reception of sexual signals, as well as receivers' responses to them. To grasp the relative importance of these factors in generating signal diversity, we must simultaneously investigate multiple selective agents and signaling traits within a natural system. We use the model system of the radiation of Bahamas mosquitofish (Gambusia hubbsi) inhabiting blue holes to test the effects of resource availability, male body size and other life-history traits, key aspects of the transmission environment, sex ratio, and predation risk on variation in multiple male color traits. Consistent with previous work examining other traits in this system, several color traits have repeatedly diverged between predation regimes, exhibiting greater elaboration in the absence of predators. However, other factors proved influential as well, with variation in resource levels, body size, relative testes size, and background water color being especially important for several color traits. For one prominent signaling trait, orange dorsal fins, we further confirmed a genetic basis underlying population differences using a laboratory common-garden experiment. We illustrate a promising approach for gaining a detailed understanding of the many contributing factors in the evolution of multivariate sexual signals. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

Asynchrony of senescence among phenotypic traits in a wild mammal population

PubMed Central

Hayward, Adam D.; Moorad, Jacob; Regan, Charlotte E.; Berenos, Camillo; Pilkington, Jill G.; Pemberton, Josephine M.; Nussey, Daniel H.

2015-01-01

The degree to which changes in lifespan are coupled to changes in senescence in different physiological systems and phenotypic traits is a central question in biogerontology. It is underpinned by deeper biological questions about whether or not senescence is a synchronised process, or whether levels of synchrony depend on species or environmental context. Understanding how natural selection shapes patterns of synchrony in senescence across physiological systems and phenotypic traits demands the longitudinal study of many phenotypes under natural conditions. Here, we examine the patterns of age-related variation in late adulthood in a wild population of Soay sheep (Ovis aries) that have been the subject of individual-based monitoring for thirty years. We examined twenty different phenotypic traits in both males and females, encompassing vital rates (survival and fecundity), maternal reproductive performance (offspring birth weight, birth date and survival), male rutting behaviour, home range measures, parasite burdens, and body mass. We initially quantified age-related variation in each trait having controlled for annual variation in the environment, among-individual variation and selective disappearance effects. We then standardised our age-specific trait means and tested whether age trajectories could be meaningfully grouped according to sex or the type of trait. Whilst most traits showed age-related declines in later life, we found striking levels of asynchrony both within and between the sexes. Of particular note, female fecundity and reproductive performance declined with age, but male annual reproductive success did not. We also discovered that whilst home range size and quality decline with age in females, home range size increases with age in males. Our findings highlight the complexity of phenotypic ageing under natural conditions and, along with emerging data from other wild populations and laboratory models, suggest that the long-standing hypothesis within evolutionary biology that fitness-related traits should senesce in a synchronous manner is seriously flawed. PMID:26277618

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

PubMed Central

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

2008-01-01

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

Deploying a Proximal Sensing Cart to Identify Drought-Adaptive Traits in Upland Cotton for High-Throughput Phenotyping

PubMed Central

Thompson, Alison L.; Thorp, Kelly R.; Conley, Matthew; Andrade-Sanchez, Pedro; Heun, John T.; Dyer, John M.; White, Jeffery W.

2018-01-01

Field-based high-throughput phenotyping is an emerging approach to quantify difficult, time-sensitive plant traits in relevant growing conditions. Proximal sensing carts represent an alternative platform to more costly high-clearance tractors for phenotyping dynamic traits in the field. A proximal sensing cart and specifically a deployment protocol, were developed to phenotype traits related to drought tolerance in the field. The cart-sensor package included an infrared thermometer, ultrasonic transducer, multi-spectral reflectance sensor, weather station, and RGB cameras. The cart deployment protocol was evaluated on 35 upland cotton (Gossypium hirsutum L.) entries grown in 2017 at Maricopa, AZ, United States. Experimental plots were grown under well-watered and water-limited conditions using a (0,1) alpha lattice design and evaluated in June and July. Total collection time of the 0.87 hectare field averaged 2 h and 27 min and produced 50.7 MB and 45.7 GB of data from the sensors and RGB cameras, respectively. Canopy temperature, crop water stress index (CWSI), canopy height, normalized difference vegetative index (NDVI), and leaf area index (LAI) differed among entries and showed an interaction with the water regime (p < 0.05). Broad-sense heritability (H2) estimates ranged from 0.097 to 0.574 across all phenotypes and collections. Canopy cover estimated from RGB images increased with counts of established plants (r = 0.747, p = 0.033). Based on the cart-derived phenotypes, three entries were found to have improved drought-adaptive traits compared to a local adapted cultivar. These results indicate that the deployment protocol developed for the cart and sensor package can measure multiple traits rapidly and accurately to characterize complex plant traits under drought conditions. PMID:29868041

Grouping methods for estimating the prevalences of rare traits from complex survey data that preserve confidentiality of respondents.

PubMed

Hyun, Noorie; Gastwirth, Joseph L; Graubard, Barry I

2018-03-26

Originally, 2-stage group testing was developed for efficiently screening individuals for a disease. In response to the HIV/AIDS epidemic, 1-stage group testing was adopted for estimating prevalences of a single or multiple traits from testing groups of size q, so individuals were not tested. This paper extends the methodology of 1-stage group testing to surveys with sample weighted complex multistage-cluster designs. Sample weighted-generalized estimating equations are used to estimate the prevalences of categorical traits while accounting for the error rates inherent in the tests. Two difficulties arise when using group testing in complex samples: (1) How does one weight the results of the test on each group as the sample weights will differ among observations in the same group. Furthermore, if the sample weights are related to positivity of the diagnostic test, then group-level weighting is needed to reduce bias in the prevalence estimation; (2) How does one form groups that will allow accurate estimation of the standard errors of prevalence estimates under multistage-cluster sampling allowing for intracluster correlation of the test results. We study 5 different grouping methods to address the weighting and cluster sampling aspects of complex designed samples. Finite sample properties of the estimators of prevalences, variances, and confidence interval coverage for these grouping methods are studied using simulations. National Health and Nutrition Examination Survey data are used to illustrate the methods. Copyright © 2018 John Wiley & Sons, Ltd.

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

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.

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

PubMed

Kwak, Il-Youp; Pan, Wei

2017-01-01

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

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

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

PubMed Central

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

2017-01-01

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

Autism spectrum traits and visual processing in young adults with very low birth weight: the Helsinki Study of Very Low Birth Weight adults.

PubMed

Wolford, E; Pesonen, A-K; Heinonen, K; Lahti, M; Pyhälä, R; Lahti, J; Hovi, P; Strang-Karlsson, S; Eriksson, J G; Andersson, S; Järvenpää, A-L; Kajantie, E; Räikkönen, K

2017-04-01

Visual processing problems may be one underlying factor for cognitive impairments related to autism spectrum disorders (ASDs). We examined associations between ASD-traits (Autism-Spectrum Quotient) and visual processing performance (Rey-Osterrieth Complex Figure Test; Block Design task of the Wechsler Adult Intelligence Scale-III) in young adults (mean age=25.0, s.d.=2.1 years) born preterm at very low birth weight (VLBW; <1500 g) (n=101) or at term (n=104). A higher level of ASD-traits was associated with slower global visual processing speed among the preterm VLBW, but not among the term-born group (P<0.04 for interaction). Our findings suggest that the associations between ASD-traits and visual processing may be restricted to individuals born preterm, and related specifically to global, not local visual processing. Our findings point to cumulative social and neurocognitive problems in those born preterm at VLBW.

Coordination and plasticity in leaf anatomical traits of invasive and native vine species.

PubMed

Osunkoya, Olusegun O; Boyne, Richard; Scharaschkin, Tanya

2014-09-01

• Plant invasiveness can be promoted by higher values of adaptive traits (e.g., photosynthetic capacity, biomass accumulation), greater plasticity and coordination of these traits, and by higher and positive relative influence of these functionalities on fitness, such as increasing reproductive output. However, the data set for this premise rarely includes linkages between epidermal-stomatal traits, leaf internal anatomy, and physiological performance.• Three ecological pairs of invasive vs. noninvasive (native) woody vine species of South-East Queensland, Australia were investigated for trait differences in leaf morphology and anatomy under varying light intensity. The linkages of these traits with physiological performance (e.g., water-use efficiency, photosynthesis, and leaf construction cost) and plant adaptive traits of specific leaf area, biomass, and relative growth rates were also explored.• Except for stomatal size, mean leaf anatomical traits differed significantly between the two groups. Plasticity of traits and, to a very limited extent, their phenotypic integration were higher in the invasive relative to the native species. ANOVA, ordination, and analysis of similarity suggest that for leaf morphology and anatomy, the three functional strategies contribute to the differences between the two groups in the order phenotypic plasticity > trait means > phenotypic integration.• The linkages demonstrated in the study between stomatal complex/gross anatomy and physiology are scarce in the ecological literature of plant invasiveness, but the findings suggest that leaf anatomical traits need to be considered routinely as part of weed species assessment and in the worldwide leaf economic spectrum. © 2014 Botanical Society of America, Inc.

Genotype × environment interaction is weaker in genitalia than in mating signals and body traits in Enchenopa treehoppers (Hemiptera: Membracidae).

PubMed

Rodríguez, Rafael L; Al-Wathiqui, Nooria

2011-07-01

Theory predicts that selection acting across environments should erode genetic variation in reaction norms; i.e., selection should weaken genotype × environment interaction (G × E). In spite of this expectation, G × E is often detected in fitness-related traits. It thus appears that G × E is at least sometimes sustained under selection, a possibility that highlights the need for theory that can account for variation in the presence and strength of G × E. We tested the hypothesis that trait differences in developmental architecture contribute to variation in the expression of G × E. Specifically, we assessed the influence of canalization (robustness to genetic or environmental perturbations) and condition-dependence (association between trait expression and prior resource acquisition or vital cellular processes). We compared G × E across three trait types expected to differ in canalization and condition-dependence: mating signals, body size-related traits, and genitalia. Because genitalia are expected to show the least condition-dependence and the most canalization, they should express weaker G × E than the other trait types. Our study species was a member of the Enchenopa binotata species complex of treehoppers. We found significant G × E in most traits; G × E was strongest in signals and body traits, and weakest in genitalia. These results support the hypothesis that trait differences in developmental architecture (canalization and condition-dependence) contribute to variation in the expression of G × E. We discuss implications for the dynamics of sexual selection on different trait types.

Anxiety promotes memory for mood-congruent faces but does not alter loss aversion

PubMed Central

Charpentier, Caroline J.; Hindocha, Chandni; Roiser, Jonathan P.; Robinson, Oliver J.

2016-01-01

Pathological anxiety is associated with disrupted cognitive processing, including working memory and decision-making. In healthy individuals, experimentally-induced state anxiety or high trait anxiety often results in the deployment of adaptive harm-avoidant behaviours. However, how these processes affect cognition is largely unknown. To investigate this question, we implemented a translational within-subjects anxiety induction, threat of shock, in healthy participants reporting a wide range of trait anxiety scores. Participants completed a gambling task, embedded within an emotional working memory task, with some blocks under unpredictable threat and others safe from shock. Relative to the safe condition, threat of shock improved recall of threat-congruent (fearful) face location, especially in highly trait anxious participants. This suggests that threat boosts working memory for mood-congruent stimuli in vulnerable individuals, mirroring memory biases in clinical anxiety. By contrast, Bayesian analysis indicated that gambling decisions were better explained by models that did not include threat or treat anxiety, suggesting that: (i) higher-level executive functions are robust to these anxiety manipulations; and (ii) decreased risk-taking may be specific to pathological anxiety. These findings provide insight into the complex interactions between trait anxiety, acute state anxiety and cognition, and may help understand the cognitive mechanisms underlying adaptive anxiety. PMID:27098489

Anxiety promotes memory for mood-congruent faces but does not alter loss aversion.

PubMed

Charpentier, Caroline J; Hindocha, Chandni; Roiser, Jonathan P; Robinson, Oliver J

2016-04-21

Pathological anxiety is associated with disrupted cognitive processing, including working memory and decision-making. In healthy individuals, experimentally-induced state anxiety or high trait anxiety often results in the deployment of adaptive harm-avoidant behaviours. However, how these processes affect cognition is largely unknown. To investigate this question, we implemented a translational within-subjects anxiety induction, threat of shock, in healthy participants reporting a wide range of trait anxiety scores. Participants completed a gambling task, embedded within an emotional working memory task, with some blocks under unpredictable threat and others safe from shock. Relative to the safe condition, threat of shock improved recall of threat-congruent (fearful) face location, especially in highly trait anxious participants. This suggests that threat boosts working memory for mood-congruent stimuli in vulnerable individuals, mirroring memory biases in clinical anxiety. By contrast, Bayesian analysis indicated that gambling decisions were better explained by models that did not include threat or treat anxiety, suggesting that: (i) higher-level executive functions are robust to these anxiety manipulations; and (ii) decreased risk-taking may be specific to pathological anxiety. These findings provide insight into the complex interactions between trait anxiety, acute state anxiety and cognition, and may help understand the cognitive mechanisms underlying adaptive anxiety.

Positive Traits in the Bipolar Spectrum: The Space between Madness and Genius

PubMed Central

Greenwood, Tiffany A.

2017-01-01

Bipolar disorder is a severe, lifelong mood disorder for which little is currently understood of the genetic mechanisms underlying risk. By examining related dimensional phenotypes, we may further our understanding of the disorder. Creativity has a historical connection with the bipolar spectrum and is particularly enhanced among unaffected first-degree relatives and those with bipolar spectrum traits. This suggests that some aspects of the bipolar spectrum may confer advantages, while more severe expressions of symptoms negatively influence creative accomplishment. Creativity is a complex, multidimensional construct with both cognitive and affective components, many of which appear to reflect a shared genetic vulnerability with bipolar disorder. It is suggested that a subset of bipolar risk variants confer advantages as positive traits according to an inverted-U-shaped curve with clinically unaffected allele carriers benefitting from the positive traits and serving to maintain the risk alleles in the population. The association of risk genes with creativity in healthy individuals (e.g., NRG1), as well as an overall sharing of common genetic variation between bipolar patients and creative individuals, provides support for this model. Current findings are summarized from a multidisciplinary perspective to demonstrate the feasibility of research in this area to reveal the mechanisms underlying illness. PMID:28277566

Root aquaporins contribute to whole plant water fluxes under drought stress in rice (Oryza sativa L.).

PubMed

Grondin, Alexandre; Mauleon, Ramil; Vadez, Vincent; Henry, Amelia

2016-02-01

Aquaporin activity and root anatomy may affect root hydraulic properties under drought stress. To better understand the function of aquaporins in rice root water fluxes under drought, we studied the root hydraulic conductivity (Lpr) and root sap exudation rate (Sr) in the presence or absence of an aquaporin inhibitor (azide) under well-watered conditions and following drought stress in six diverse rice varieties. Varieties varied in Lpr and Sr under both conditions. The contribution of aquaporins to Lpr was generally high (up to 79% under well-watered conditions and 85% under drought stress) and differentially regulated under drought. Aquaporin contribution to Sr increased in most varieties after drought, suggesting a crucial role for aquaporins in osmotic water fluxes during drought and recovery. Furthermore, root plasma membrane aquaporin (PIP) expression and root anatomical properties were correlated with hydraulic traits. Three chromosome regions highly correlated with hydraulic traits of the OryzaSNP panel were identified, but did not co-locate with known aquaporins. These results therefore highlight the importance of aquaporins in the rice root radial water pathway, but emphasize the complex range of additional mechanisms related to root water fluxes and drought response. © 2015 John Wiley & Sons Ltd.

QTL analysis of genotype x environment interactions affecting cotton fiber quality.

PubMed

Paterson, A H; Saranga, Y; Menz, M; Jiang, C-X; Wright, R J

2003-02-01

Cotton is unusual among major crops in that large acreages are grown under both irrigated and rainfed conditions, making genotype x environment interactions of even greater importance than usual in designing crop-improvement strategies. We describe the impact of well-watered versus water-limited growth conditions on the genetic control of fiber quality, a complex suite of traits that collectively determine the utility of cotton. Fiber length, length uniformity, elongation, strength, fineness, and color (yellowness) were influenced by 6, 7, 9, 21, 25 and 11 QTLs (respectively) that could be detected in one or more treatments. The genetic control of cotton fiber quality was markedly affected both by general differences between growing seasons ("years") and by specific differences in water management regimes. Seventeen QTLs were detected only in the water-limited treatment while only two were specific to the well-watered treatment, suggesting that improvement of fiber quality under water stress may be even more complicated than improvement of this already complex trait under well-watered conditions. In crops such as cotton with widespread use of both irrigated and rainfed production systems, the need to manipulate larger numbers of genes to confer adequate quality under both sets of conditions will reduce the expected rate of genetic gain. These difficulties may be partly ameliorated by efficiencies gained through identification and use of diagnostic DNA markers, including those identified herein.

Neural Basis of Interpersonal Traits in Neurodegenerative Diseases

PubMed Central

Sollberger, Marc; Stanley, Christine M.; Wilson, Stephen M.; Gyurak, Anett; Beckman, Victoria; Growdon, Matthew; Jang, Jung; Weiner, Michael W.; Miller, Bruce L.; Rankin, Katherine P.

2009-01-01

Several functional and structural imaging studies have investigated the neural basis of personality in healthy adults, but human lesions studies are scarce. Personality changes are a common symptom in patients with neurodegenerative diseases like frontotemporal dementia (FTD) and semantic dementia (SD), allowing a unique window into the neural basis of personality. In this study, we used the Interpersonal Adjective Scales to investigate the structural basis of eight interpersonal traits (dominance, arrogance, coldness, introversion, submissiveness, ingenuousness, warmth, and extraversion) in 257 subjects: 214 patients with neurodegenerative diseases such as FTD, SD, progressive non-fluent aphasia, Alzheimer’s disease, amnestic mild cognitive impairment, corticobasal degeneration, and progressive supranuclear palsy and 43 healthy elderly people. Measures of interpersonal traits were correlated with regional atrophy pattern using voxel-based morphometry (VBM) analysis of structural MR images. Interpersonal traits mapped onto distinct brain regions depending on the degree to which they involved agency and affiliation. Interpersonal traits high in agency related to left dorsolateral prefrontal and left lateral frontopolar regions, whereas interpersonal traits high in affiliation related to right ventromedial prefrontal and right anteromedial temporal regions. Consistent with the existing literature on neural networks underlying social cognition, these results indicate that brain regions related to externally-focused, executive control-related processes underlie agentic interpersonal traits such as dominance, whereas brain regions related to internally-focused, emotion- and reward-related processes underlie affiliative interpersonal traits such as warmth. In addition, these findings indicate that interpersonal traits are subserved by complex neural networks rather than discrete anatomic areas. PMID:19540253

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.

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

PubMed

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

2009-12-01

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

A simple model clarifies the complicated relationships of complex networks

PubMed Central

Zheng, Bojin; Wu, Hongrun; Kuang, Li; Qin, Jun; Du, Wenhua; Wang, Jianmin; Li, Deyi

2014-01-01

Real-world networks such as the Internet and WWW have many common traits. Until now, hundreds of models were proposed to characterize these traits for understanding the networks. Because different models used very different mechanisms, it is widely believed that these traits origin from different causes. However, we find that a simple model based on optimisation can produce many traits, including scale-free, small-world, ultra small-world, Delta-distribution, compact, fractal, regular and random networks. Moreover, by revising the proposed model, the community-structure networks are generated. By this model and the revised versions, the complicated relationships of complex networks are illustrated. The model brings a new universal perspective to the understanding of complex networks and provide a universal method to model complex networks from the viewpoint of optimisation. PMID:25160506

Meta-analysis of correlated traits via summary statistics from GWASs with an application in hypertension.

PubMed

Zhu, Xiaofeng; Feng, Tao; Tayo, Bamidele O; Liang, Jingjing; Young, J Hunter; Franceschini, Nora; Smith, Jennifer A; Yanek, Lisa R; Sun, Yan V; Edwards, Todd L; Chen, Wei; Nalls, Mike; Fox, Ervin; Sale, Michele; Bottinger, Erwin; Rotimi, Charles; Liu, Yongmei; McKnight, Barbara; Liu, Kiang; Arnett, Donna K; Chakravati, Aravinda; Cooper, Richard S; Redline, Susan

2015-01-08

Genome-wide association studies (GWASs) have identified many genetic variants underlying complex traits. Many detected genetic loci harbor variants that associate with multiple-even distinct-traits. Most current analysis approaches focus on single traits, even though the final results from multiple traits are evaluated together. Such approaches miss the opportunity to systemically integrate the phenome-wide data available for genetic association analysis. In this study, we propose a general approach that can integrate association evidence from summary statistics of multiple traits, either correlated, independent, continuous, or binary traits, which might come from the same or different studies. We allow for trait heterogeneity effects. Population structure and cryptic relatedness can also be controlled. Our simulations suggest that the proposed method has improved statistical power over single-trait analysis in most of the cases we studied. We applied our method to the Continental Origins and Genetic Epidemiology Network (COGENT) African ancestry samples for three blood pressure traits and identified four loci (CHIC2, HOXA-EVX1, IGFBP1/IGFBP3, and CDH17; p < 5.0 × 10(-8)) associated with hypertension-related traits that were missed by a single-trait analysis in the original report. Six additional loci with suggestive association evidence (p < 5.0 × 10(-7)) were also observed, including CACNA1D and WNT3. Our study strongly suggests that analyzing multiple phenotypes can improve statistical power and that such analysis can be executed with the summary statistics from GWASs. Our method also provides a way to study a cross phenotype (CP) association by using summary statistics from GWASs of multiple phenotypes. Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

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

Emerging applications of genome-editing technology to examine functionality of GWAS-associated variants for complex traits.

PubMed

Smith, Andrew J P; Deloukas, Panos; Munroe, Patricia B

2018-04-13

Over the last decade, genome-wide association studies (GWAS) have propelled the discovery of thousands of loci associated with complex diseases. The focus is now turning towards the function of these association signals, determining the causal variant(s) amongst those in strong linkage disequilibrium, and identifying their underlying mechanisms, such as long-range gene regulation. Genome-editing techniques utilising zinc-finger nucleases (ZFN), transcription activator-like effector nucleases (TALENs) and clustered regularly-interspaced short palindromic repeats with Cas9 nuclease (CRISPR-Cas9), are becoming the tools of choice to establish functionality for these variants, due to the ability to assess effects of single variants in vivo. This review will discuss examples of how these technologies have begun to aid functional analysis of GWAS loci for complex traits such as cardiovascular disease, type 2 diabetes, cancer, obesity and autoimmune disease. We focus on analysis of variants occurring within non-coding genomic regions, as these comprise the majority of GWAS variants, providing the greatest challenges to determining functionality, and compare editing strategies that provide different levels of evidence for variant functionality. The review describes molecular insights into some of these potentially causal variants, and how these may relate to the pathology of the trait, and look towards future directions for these technologies in post-GWAS analysis, such as base-editing.

QTL analysis of falling number and seed longevity in wheat (Triticum aestivum L.).

PubMed

Börner, Andreas; Nagel, Manuela; Agacka-Mołdoch, Monika; Gierke, Peter Ulrich; Oberforster, Michael; Albrecht, Theresa; Mohler, Volker

2018-02-01

Pre-harvest sprouting (PHS) and seed longevity (SL) are complex biological processes of major importance for agricultural production. In the present study, a recombinant inbred line (RIL) population derived from a cross between the German winter wheat (Triticum aestivum L.) cultivars History and Rubens was used to identify genetic factors controlling these two physiological seed traits. A falling number (FN) test was employed to evaluate PHS, while SL was measured using a germination test (and the speed of germination) after controlled deterioration. FN of the population was assessed in four environments; SL traits were measured in one environment. Four major quantitative trait loci (QTL) for FN were detected on chromosomes 4D, 5A, 5D, and 7B, whereas for SL traits, a major QTL was found on chromosome 1A. The FN QTL on chromosome 4D that coincided with the position of the dwarfing gene Rht-D1b only had effects in environments that were free of PHS. The remaining three QTL for FN were mostly pronounced under conditions conducive to PHS. The QTL on the long arm of chromosome 7B corresponded to the major gene locus controlling late maturity α-amylase (LMA) in wheat. The severity of the LMA phenotype became truly apparent under sprouting conditions. The position on the long arm of chromosome 1A of the QTL for SL points to a new QTL for this important regenerative seed trait.

Genetic analysis of safflower domestication

PubMed Central

2014-01-01

Background Safflower (Carthamus tinctorius L.) is an oilseed crop in the Compositae (a.k.a. Asteraceae) that is valued for its oils rich in unsaturated fatty acids. Here, we present an analysis of the genetic architecture of safflower domestication and compare our findings to those from sunflower (Helianthus annuus L.), an independently domesticated oilseed crop within the same family. We mapped quantitative trait loci (QTL) underlying 24 domestication-related traits in progeny from a cross between safflower and its wild progenitor, Carthamus palaestinus Eig. Also, we compared QTL positions in safflower against those that have been previously identified in cultivated x wild sunflower crosses to identify instances of colocalization. Results We mapped 61 QTL, the vast majority of which (59) exhibited minor or moderate phenotypic effects. The two large-effect QTL corresponded to one each for flower color and leaf spininess. A total of 14 safflower QTL colocalized with previously reported sunflower QTL for the same traits. Of these, QTL for three traits (days to flower, achene length, and number of selfed seed) had cultivar alleles that conferred effects in the same direction in both species. Conclusions As has been observed in sunflower, and unlike many other crops, our results suggest that the genetics of safflower domestication is quite complex. Moreover, our comparative mapping results indicate that safflower and sunflower exhibit numerous instances of QTL colocalization, suggesting that parallel trait transitions during domestication may have been driven, at least in part, by parallel genotypic evolution at some of the same underlying genes. PMID:24502326

Integrating genome-wide association study summaries and element-gene interaction datasets identified multiple associations between elements and complex diseases.

PubMed

He, Awen; Wang, Wenyu; Prakash, N Tejo; Tinkov, Alexey A; Skalny, Anatoly V; Wen, Yan; Hao, Jingcan; Guo, Xiong; Zhang, Feng

2018-03-01

Chemical elements are closely related to human health. Extensive genomic profile data of complex diseases offer us a good opportunity to systemically investigate the relationships between elements and complex diseases/traits. In this study, we applied gene set enrichment analysis (GSEA) approach to detect the associations between elements and complex diseases/traits though integrating element-gene interaction datasets and genome-wide association study (GWAS) data of complex diseases/traits. To illustrate the performance of GSEA, the element-gene interaction datasets of 24 elements were extracted from the comparative toxicogenomics database (CTD). GWAS summary datasets of 24 complex diseases or traits were downloaded from the dbGaP or GEFOS websites. We observed significant associations between 7 elements and 13 complex diseases or traits (all false discovery rate (FDR) < 0.05), including reported relationships such as aluminum vs. Alzheimer's disease (FDR = 0.042), calcium vs. bone mineral density (FDR = 0.031), magnesium vs. systemic lupus erythematosus (FDR = 0.012) as well as novel associations, such as nickel vs. hypertriglyceridemia (FDR = 0.002) and bipolar disorder (FDR = 0.027). Our study results are consistent with previous biological studies, supporting the good performance of GSEA. Our analyzing results based on GSEA framework provide novel clues for discovering causal relationships between elements and complex diseases. © 2017 WILEY PERIODICALS, INC.

Integrating Gene Expression with Summary Association Statistics to Identify Genes Associated with 30 Complex Traits.

PubMed

Mancuso, Nicholas; Shi, Huwenbo; Goddard, Pagé; Kichaev, Gleb; Gusev, Alexander; Pasaniuc, Bogdan

2017-03-02

Although genome-wide association studies (GWASs) have identified thousands of risk loci for many complex traits and diseases, the causal variants and genes at these loci remain largely unknown. Here, we introduce a method for estimating the local genetic correlation between gene expression and a complex trait and utilize it to estimate the genetic correlation due to predicted expression between pairs of traits. We integrated gene expression measurements from 45 expression panels with summary GWAS data to perform 30 multi-tissue transcriptome-wide association studies (TWASs). We identified 1,196 genes whose expression is associated with these traits; of these, 168 reside more than 0.5 Mb away from any previously reported GWAS significant variant. We then used our approach to find 43 pairs of traits with significant genetic correlation at the level of predicted expression; of these, eight were not found through genetic correlation at the SNP level. Finally, we used bi-directional regression to find evidence that BMI causally influences triglyceride levels and that triglyceride levels causally influence low-density lipoprotein. Together, our results provide insight into the role of gene expression in the susceptibility of complex traits and diseases. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

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

PubMed Central

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

2016-01-01

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

Quantification of the effects of architectural traits on dry mass production and light interception of tomato canopy under different temperature regimes using a dynamic functional–structural plant model

PubMed Central

Chen, Tsu-Wei; Nguyen, Thi My Nguyet; Kahlen, Katrin; Stützel, Hartmut

2014-01-01

There is increasing interest in evaluating the environmental effects on crop architectural traits and yield improvement. However, crop models describing the dynamic changes in canopy structure with environmental conditions and the complex interactions between canopy structure, light interception, and dry mass production are only gradually emerging. Using tomato (Solanum lycopersicum L.) as a model crop, a dynamic functional–structural plant model (FSPM) was constructed, parameterized, and evaluated to analyse the effects of temperature on architectural traits, which strongly influence canopy light interception and shoot dry mass. The FSPM predicted the organ growth, organ size, and shoot dry mass over time with high accuracy (>85%). Analyses of this FSPM showed that, in comparison with the reference canopy, shoot dry mass may be affected by leaf angle by as much as 20%, leaf curvature by up to 7%, the leaf length:width ratio by up to 5%, internode length by up to 9%, and curvature ratios and leaf arrangement by up to 6%. Tomato canopies at low temperature had higher canopy density and were more clumped due to higher leaf area and shorter internodes. Interestingly, dry mass production and light interception of the clumped canopy were more sensitive to changes in architectural traits. The complex interactions between architectural traits, canopy light interception, dry mass production, and environmental conditions can be studied by the dynamic FSPM, which may serve as a tool for designing a canopy structure which is ‘ideal’ in a given environment. PMID:25183746

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

PubMed

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

2014-01-01

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

Genetic basis of nitrogen use efficiency and yield stability across environments in winter rapeseed.

PubMed

Bouchet, Anne-Sophie; Laperche, Anne; Bissuel-Belaygue, Christine; Baron, Cécile; Morice, Jérôme; Rousseau-Gueutin, Mathieu; Dheu, Jean-Eric; George, Pierre; Pinochet, Xavier; Foubert, Thomas; Maes, Olivier; Dugué, Damien; Guinot, Florent; Nesi, Nathalie

2016-09-15

Nitrogen use efficiency is an important breeding trait that can be modified to improve the sustainability of many crop species used in agriculture. Rapeseed is a major oil crop with low nitrogen use efficiency, making its production highly dependent on nitrogen input. This complex trait is suspected to be sensitive to genotype × environment interactions, especially genotype × nitrogen interactions. Therefore, phenotyping diverse rapeseed populations under a dense network of trials is a powerful approach to study nitrogen use efficiency in this crop. The present study aimed to determine the quantitative trait loci (QTL) associated with yield in winter oilseed rape and to assess the stability of these regions under contrasting nitrogen conditions for the purpose of increasing nitrogen use efficiency. Genome-wide association studies and linkage analyses were performed on two diversity sets and two doubled-haploid populations. These populations were densely genotyped, and yield-related traits were scored in a multi-environment design including seven French locations, six growing seasons (2009 to 2014) and two nitrogen nutrition levels (optimal versus limited). Very few genotype × nitrogen interactions were detected, and a large proportion of the QTL were stable across nitrogen nutrition conditions. In contrast, strong genotype × trial interactions in which most of the QTL were specific to a single trial were found. To obtain further insight into the QTL × environment interactions, genetic analyses of ecovalence were performed to identify the genomic regions contributing to the genotype × nitrogen and genotype × trial interactions. Fifty-one critical genomic regions contributing to the additive genetic control of yield-associated traits were identified, and the structural organization of these regions in the genome was investigated. Our results demonstrated that the effect of the trial was greater than the effect of nitrogen nutrition levels on seed yield-related traits under our experimental conditions. Nevertheless, critical genomic regions associated with yield that were stable across environments were identified in rapeseed.

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

PubMed

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

2012-01-01

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

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

PubMed

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

2016-10-06

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

Molecular Mechanisms Underlying Abscisic Acid/Gibberellin Balance in the Control of Seed Dormancy and Germination in Cereals

PubMed Central

Tuan, Pham A.; Kumar, Rohit; Rehal, Pawanpuneet K.; Toora, Parneet K.; Ayele, Belay T.

2018-01-01

Seed dormancy is an adaptive trait that does not allow the germination of an intact viable seed under favorable environmental conditions. Non-dormant seeds or seeds with low level of dormancy can germinate readily under optimal environmental conditions, and such a trait leads to preharvest sprouting, germination of seeds on the mother plant prior to harvest, which significantly reduces the yield and quality of cereal crops. High level of dormancy, on the other hand, may lead to non-uniform germination and seedling establishment. Therefore, intermediate dormancy is considered to be a desirable trait as it prevents the problems of sprouting and allows uniformity of postharvest germination of seeds. Induction, maintenance, and release of seed dormancy are complex physiological processes that are influenced by a wide range of endogenous and environmental factors. Plant hormones, mainly abscisic acid (ABA) and gibberellin (GA), are the major endogenous factors that act antagonistically in the control of seed dormancy and germination; ABA positively regulates the induction and maintenance of dormancy, while GA enhances germination. Significant progress has been made in recent years in the elucidation of molecular mechanisms regulating ABA/GA balance and thereby dormancy and germination in cereal seeds, and this review summarizes the current state of knowledge on the topic. PMID:29875780

Strategies for mapping heterogeneous recessive traits by allele-sharing methods.

PubMed Central

Feingold, E; Siegmund, D O

1997-01-01

We investigate strategies for detecting linkage of recessive and partially recessive traits, using sibling pairs and inbred individuals. We assume that a genomewide search is being conducted and that locus heterogeneity of the trait is likely. For sibling pairs, we evaluate the efficiency of different statistics under the assumption that one does not know the true degree of recessiveness of the trait. We recommend a sibling-pair statistic that is a linear compromise between two previously suggested statistics. We also compare the power of sibling pairs to that of more distant relatives, such as cousins. For inbred individuals, we evaluate the power of offspring of different types of matings and compare them to sibling pairs. Over a broad range of trait etiologies, sibling pairs are more powerful than inbred individuals, but for traits caused by very rare alleles, particularly in the case of heterogeneity, inbred individuals can be much more powerful. The models we develop can also be used to examine specific situations other than those we look at. We present this analysis in the idealized context of a dense set of highly polymorphic markers. In general, incorporation of real-world complexities makes inbred individuals, particularly offspring of distant relatives, look slightly less useful than our results imply. PMID:9106544

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

PubMed

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

2011-01-01

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

Genetic constraints on wing pattern variation in Lycaeides butterflies: A case study on mapping complex, multifaceted traits in structured populations.

PubMed

Lucas, Lauren K; Nice, Chris C; Gompert, Zachariah

2018-03-13

Patterns of phenotypic variation within and among species can be shaped and constrained by trait genetic architecture. This is particularly true for complex traits, such as butterfly wing patterns, that consist of multiple elements. Understanding the genetics of complex trait variation across species boundaries is difficult, as it necessitates mapping in structured populations and can involve many loci with small or variable phenotypic effects. Here, we investigate the genetic architecture of complex wing pattern variation in Lycaeides butterflies as a case study of mapping multivariate traits in wild populations that include multiple nominal species or groups. We identify conserved modules of integrated wing pattern elements within populations and species. We show that trait covariances within modules have a genetic basis and thus represent genetic constraints that can channel evolution. Consistent with this, we find evidence that evolutionary changes in wing patterns among populations and species occur in the directions of genetic covariances within these groups. Thus, we show that genetic constraints affect patterns of biological diversity (wing pattern) in Lycaeides, and we provide an analytical template for similar work in other systems. © 2018 John Wiley & Sons Ltd.

The evolution of trade-offs under directional and correlational selection.

PubMed

Roff, Derek A; Fairbairn, Daphne J

2012-08-01

Using quantitative genetic theory, we develop predictions for the evolution of trade-offs in response to directional and correlational selection. We predict that directional selection favoring an increase in one trait in a trade-off will result in change in the intercept but not the slope of the trade-off function, with the mean value of the selected trait increasing and that of the correlated trait decreasing. Natural selection will generally favor an increase in some combination of trait values, which can be represented as directional selection on an index value. Such selection induces both directional and correlational selection on the component traits. Theory predicts that selection on an index value will also change the intercept but not the slope of the trade-off function but because of correlational selection, the direction of change in component traits may be in the same or opposite directions. We test these predictions using artificial selection on the well-established trade-off between fecundity and flight capability in the cricket, Gryllus firmus and compare the empirical results with a priori predictions made using genetic parameters from a separate half-sibling experiment. Our results support the predictions and illustrate the complexity of trade-off evolution when component traits are subject to both directional and correlational selection. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems.

PubMed

Whitacre, James M; Bender, Axel

2010-06-15

A generic mechanism--networked buffering--is proposed for the generation of robust traits in complex systems. It requires two basic conditions to be satisfied: 1) agents are versatile enough to perform more than one single functional role within a system and 2) agents are degenerate, i.e. there exists partial overlap in the functional capabilities of agents. Given these prerequisites, degenerate systems can readily produce a distributed systemic response to local perturbations. Reciprocally, excess resources related to a single function can indirectly support multiple unrelated functions within a degenerate system. In models of genome:proteome mappings for which localized decision-making and modularity of genetic functions are assumed, we verify that such distributed compensatory effects cause enhanced robustness of system traits. The conditions needed for networked buffering to occur are neither demanding nor rare, supporting the conjecture that degeneracy may fundamentally underpin distributed robustness within several biotic and abiotic systems. For instance, networked buffering offers new insights into systems engineering and planning activities that occur under high uncertainty. It may also help explain recent developments in understanding the origins of resilience within complex ecosystems.

Quantitative trait loci for energy balance traits in an advanced intercross line derived from mice divergently selected for heat loss

PubMed Central

Nielsen, Merlyn K.; Thorn, Stephanie R.; Valdar, William; Pomp, Daniel

2014-01-01

Obesity in human populations, currently a serious health concern, is considered to be the consequence of an energy imbalance in which more energy in calories is consumed than is expended. We used interval mapping techniques to investigate the genetic basis of a number of energy balance traits in an F11 advanced intercross population of mice created from an original intercross of lines selected for increased and decreased heat loss. We uncovered a total of 137 quantitative trait loci (QTLs) for these traits at 41 unique sites on 18 of the 20 chromosomes in the mouse genome, with X-linked QTLs being most prevalent. Two QTLs were found for the selection target of heat loss, one on distal chromosome 1 and another on proximal chromosome 2. The number of QTLs affecting the various traits generally was consistent with previous estimates of heritabilities in the same population, with the most found for two bone mineral traits and the least for feed intake and several body composition traits. QTLs were generally additive in their effects, and some, especially those affecting the body weight traits, were sex-specific. Pleiotropy was extensive within trait groups (body weights, adiposity and organ weight traits, bone traits) and especially between body composition traits adjusted and not adjusted for body weight at sacrifice. Nine QTLs were found for one or more of the adiposity traits, five of which appeared to be unique. The confidence intervals among all QTLs averaged 13.3 Mb, much smaller than usually observed in an F2 cross, and in some cases this allowed us to make reasonable inferences about candidate genes underlying these QTLs. This study combined QTL mapping with genetic parameter analysis in a large segregating population, and has advanced our understanding of the genetic architecture of complex traits related to obesity. PMID:24918027

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

PubMed

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

2005-09-01

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

Genome-wide association study of resistance to ear rot by Fusarium verticillioides in a tropical field maize and popcorn core collection

USDA-ARS?s Scientific Manuscript database

Fusarium ear rot (caused by Fusarium verticillioides) is one of the most prevalent diseases of maize worldwide, and has one of the greatest negative economic impacts on this cereal crop globally. Fusarium ear rot is a highly complex trait, under polygenic control with minor effects per gene and low ...

Expression and Regulation of Attachment-Related Emotions in Children with Conduct Problems and Callous-Unemotional Traits.

PubMed

Dadds, Mark R; Gale, Nyree; Godbee, Megan; Moul, Caroline; Pasalich, Dave S; Fink, Elian; Hawes, David J

2016-08-01

Callous-unemotional traits (CU) are defined by low responsiveness to, and unfeeling disregard for the emotions of others. There is controversial evidence, however, that children with high CU traits can demonstrate affective responsiveness under certain conditions, namely those associated with attachment threat. We tested this using 'fear + amusing' and 'attachment rich' stimuli from the Lion King film. Of N = 76, 4-14 years old children, 56 were clinic-referred children divided into high and low CU traits groups, and 20 children were drawn from the community. Participants watched film sequences of fearful, attachment-related and neutral stimuli and their affective responses and emotion-regulation strategies were coded by independent observers. Children in the high CU traits group were able to disengage from the fear stimuli by showing more 'happiness' to a brief slapstick interlude. In the attachment scenario, high CU children expressed similar or trends toward higher emotional responses and emotion regulation strategies, compared to low-CU children and control children. The results support the idea that high CU children may have the potential for emotional responsiveness to complex emotional stimuli in attachment contexts. Implications of these results for the development of interventions are discussed.

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

PubMed Central

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

2015-01-01

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

Nonparametric modeling of longitudinal covariance structure in functional mapping of quantitative trait loci.

PubMed

Yap, John Stephen; Fan, Jianqing; Wu, Rongling

2009-12-01

Estimation of the covariance structure of longitudinal processes is a fundamental prerequisite for the practical deployment of functional mapping designed to study the genetic regulation and network of quantitative variation in dynamic complex traits. We present a nonparametric approach for estimating the covariance structure of a quantitative trait measured repeatedly at a series of time points. Specifically, we adopt Huang et al.'s (2006, Biometrika 93, 85-98) approach of invoking the modified Cholesky decomposition and converting the problem into modeling a sequence of regressions of responses. A regularized covariance estimator is obtained using a normal penalized likelihood with an L(2) penalty. This approach, embedded within a mixture likelihood framework, leads to enhanced accuracy, precision, and flexibility of functional mapping while preserving its biological relevance. Simulation studies are performed to reveal the statistical properties and advantages of the proposed method. A real example from a mouse genome project is analyzed to illustrate the utilization of the methodology. The new method will provide a useful tool for genome-wide scanning for the existence and distribution of quantitative trait loci underlying a dynamic trait important to agriculture, biology, and health sciences.

Leaf-IT: An Android application for measuring leaf area.

PubMed

Schrader, Julian; Pillar, Giso; Kreft, Holger

2017-11-01

The use of plant functional traits has become increasingly popular in ecological studies because plant functional traits help to understand key ecological processes in plant species and communities. This also includes changes in diversity, inter- and intraspecific interactions, and relationships of species at different spatiotemporal scales. Leaf traits are among the most important traits as they describe key dimensions of a plant's life history strategy. Further, leaf area is a key parameter with relevance for other traits such as specific leaf area, which in turn correlates with leaf chemical composition, photosynthetic rate, leaf longevity, and carbon investment. Measuring leaf area usually involves the use of scanners and commercial software and can be difficult under field conditions. We present Leaf-IT, a new smartphone application for measuring leaf area and other trait-related areas. Leaf-IT is free, designed for scientific purposes, and runs on Android 4 or higher. We tested the precision and accuracy using objects with standardized area and compared the area measurements of real leaves with the well-established, commercial software WinFOLIA using the Altman-Bland method. Area measurements of standardized objects show that Leaf-IT measures area with high accuracy and precision. Area measurements with Leaf-IT of real leaves are comparable to those of WinFOLIA. Leaf-IT is an easy-to-use application running on a wide range of smartphones. That increases the portability and use of Leaf-IT and makes it possible to measure leaf area under field conditions typical for remote locations. Its high accuracy and precision are similar to WinFOLIA. Currently, its main limitation is margin detection of damaged leaves or complex leaf morphologies.

Identification of female-specific QTLs affecting an emotionality-related behavior in rats.

PubMed

Ramos, A; Moisan, M P; Chaouloff, F; Mormède, C; Mormède, P

1999-09-01

The influence of genetic factors on psychological traits and disorders has been repeatedly demonstrated; however, the molecular mechanisms underlying such an influence remain largely unknown. Anxiety-related disorders constitute the most common class of mental disorder in humans, with women being diagnosed far more frequently than men. A better understanding of the genetic and gender-related mechanisms mediating anxiety traits should enable the development of more rational methods for preventing and treating anxiety disorders. In this study we have aimed to identify, for the first time, quantitative trait loci (QTL) influencing anxiety/emotionality-related traits in rats. To this end, two strains-Lewis (LEW) and Spontaneously Hypertensive Rats (SHR)-that differ for several behavioral measures of anxiety/emotionality were intercrossed. A QTL analysis of the F2 population revealed suggestive loci for various traits, including behaviors in the elevated plus-maze and blood pressure. In addition, one major QTL explaining 50.4% of the total variance (LOD = 7.22) was identified on chromosome 4 for the locomotion in the central and aversive area of the open field. Two other relevant QTLs have been recently mapped near this chromosomic region in the rat, which also harbors Tac1r, the gene encoding for the substance P receptor. Our major QTL affected females but not males and its effect depended on the type of cross (LEW or SHR grandmothers). The present results reveal a complex genetic basis underlying emotional behaviors and they confirm the existence of interactions between genetic factors and sex for this kind of trait. Further investigation of the loci identified herein may give clues to the pathophysiology of psychiatric disorders such as anxiety-related ones.

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

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

Students' proficiency scores within multitrait item response theory

NASA Astrophysics Data System (ADS)

Scott, Terry F.; Schumayer, Daniel

2015-12-01

In this paper we present a series of item response models of data collected using the Force Concept Inventory. The Force Concept Inventory (FCI) was designed to poll the Newtonian conception of force viewed as a multidimensional concept, that is, as a complex of distinguishable conceptual dimensions. Several previous studies have developed single-trait item response models of FCI data; however, we feel that multidimensional models are also appropriate given the explicitly multidimensional design of the inventory. The models employed in the research reported here vary in both the number of fitting parameters and the number of underlying latent traits assumed. We calculate several model information statistics to ensure adequate model fit and to determine which of the models provides the optimal balance of information and parsimony. Our analysis indicates that all item response models tested, from the single-trait Rasch model through to a model with ten latent traits, satisfy the standard requirements of fit. However, analysis of model information criteria indicates that the five-trait model is optimal. We note that an earlier factor analysis of the same FCI data also led to a five-factor model. Furthermore the factors in our previous study and the traits identified in the current work match each other well. The optimal five-trait model assigns proficiency scores to all respondents for each of the five traits. We construct a correlation matrix between the proficiencies in each of these traits. This correlation matrix shows strong correlations between some proficiencies, and strong anticorrelations between others. We present an interpretation of this correlation matrix.

A carotenogenic mini-pathway introduced into white corn does not affect development or agronomic performance

PubMed Central

Zanga, Daniela; Capell, Teresa; Slafer, Gustavo A.; Christou, Paul; Savin, Roxana

2016-01-01

High-carotenoid corn (Carolight®) has been developed as a vehicle to deliver pro-vitamin A in the diet and thus address vitamin A deficiency in at-risk populations in developing countries. Like any other novel crop, the performance of Carolight® must be tested in different environments to ensure that optimal yields and productivity are maintained, particularly in this case to ensure that the engineered metabolic pathway does not attract a yield penalty. Here we compared the performance of Carolight® with its near isogenic white corn inbred parental line under greenhouse and field conditions, and monitored the stability of the introduced trait. We found that Carolight® was indistinguishable from its near isogenic line in terms of agronomic performance, particularly grain yield and its main components. We also established experimentally that the functionality of the introduced trait was indistinguishable when plants were grown in a controlled environment or in the field. Such thorough characterization under different agronomic conditions is rarely performed even for first-generation traits such as herbicide tolerance and pest resistance, and certainly not for complex second-generation traits such as the metabolic remodeling in the Carolight® variety. Our results therefore indicate that Carolight® can now be incorporated into breeding lines to generate hybrids with locally adapted varieties for further product development and assessment. PMID:27922071

A carotenogenic mini-pathway introduced into white corn does not affect development or agronomic performance.

PubMed

Zanga, Daniela; Capell, Teresa; Slafer, Gustavo A; Christou, Paul; Savin, Roxana

2016-12-06

High-carotenoid corn (Carolight®) has been developed as a vehicle to deliver pro-vitamin A in the diet and thus address vitamin A deficiency in at-risk populations in developing countries. Like any other novel crop, the performance of Carolight® must be tested in different environments to ensure that optimal yields and productivity are maintained, particularly in this case to ensure that the engineered metabolic pathway does not attract a yield penalty. Here we compared the performance of Carolight® with its near isogenic white corn inbred parental line under greenhouse and field conditions, and monitored the stability of the introduced trait. We found that Carolight® was indistinguishable from its near isogenic line in terms of agronomic performance, particularly grain yield and its main components. We also established experimentally that the functionality of the introduced trait was indistinguishable when plants were grown in a controlled environment or in the field. Such thorough characterization under different agronomic conditions is rarely performed even for first-generation traits such as herbicide tolerance and pest resistance, and certainly not for complex second-generation traits such as the metabolic remodeling in the Carolight® variety. Our results therefore indicate that Carolight® can now be incorporated into breeding lines to generate hybrids with locally adapted varieties for further product development and assessment.

Domestication impacts on plant–herbivore interactions: a meta-analysis

PubMed Central

Poveda, Katja

2017-01-01

For millennia, humans have imposed strong selection on domesticated crops, resulting in drastically altered crop phenotypes compared with wild ancestors. Crop yields have increased, but a long-held hypothesis is that domestication has also unintentionally decreased plant defences against herbivores. To test this hypothesis, we conducted a phylogenetically controlled meta-analysis comparing insect herbivore resistance and putative plant defence traits between crops and their wild relatives. Our database included 2098 comparisons made across 73 crops in 89 studies. We found that domestication consistently reduced plant resistance to herbivores, although the magnitude of the effects varied across plant organs and depended on how resistance was measured. However, domestication had no consistent effects on the specific plant defence traits underlying resistance, including secondary metabolites and physical feeding barriers. The values of these traits sometimes increased and sometimes decreased during domestication. Consistent negative effects of domestication were observed only when defence traits were measured in reproductive organs or in the plant organ that was harvested. These results highlight the complexity of evolution under domestication and the need for an improved theoretical understanding of the mechanisms through which agronomic selection can influence the species interactions that impact both the yield and sustainability of our food systems. This article is part of the themed issue ‘Human influences on evolution, and the ecological and societal consequences’. PMID:27920379

A Powerful Approach to Estimating Annotation-Stratified Genetic Covariance via GWAS Summary Statistics.

PubMed

Lu, Qiongshi; Li, Boyang; Ou, Derek; Erlendsdottir, Margret; Powles, Ryan L; Jiang, Tony; Hu, Yiming; Chang, David; Jin, Chentian; Dai, Wei; He, Qidu; Liu, Zefeng; Mukherjee, Shubhabrata; Crane, Paul K; Zhao, Hongyu

2017-12-07

Despite the success of large-scale genome-wide association studies (GWASs) on complex traits, our understanding of their genetic architecture is far from complete. Jointly modeling multiple traits' genetic profiles has provided insights into the shared genetic basis of many complex traits. However, large-scale inference sets a high bar for both statistical power and biological interpretability. Here we introduce a principled framework to estimate annotation-stratified genetic covariance between traits using GWAS summary statistics. Through theoretical and numerical analyses, we demonstrate that our method provides accurate covariance estimates, thereby enabling researchers to dissect both the shared and distinct genetic architecture across traits to better understand their etiologies. Among 50 complex traits with publicly accessible GWAS summary statistics (N total ≈ 4.5 million), we identified more than 170 pairs with statistically significant genetic covariance. In particular, we found strong genetic covariance between late-onset Alzheimer disease (LOAD) and amyotrophic lateral sclerosis (ALS), two major neurodegenerative diseases, in single-nucleotide polymorphisms (SNPs) with high minor allele frequencies and in SNPs located in the predicted functional genome. Joint analysis of LOAD, ALS, and other traits highlights LOAD's correlation with cognitive traits and hints at an autoimmune component for ALS. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Quantitative Trait Loci (QTL)-Guided Metabolic Engineering of a Complex Trait.

PubMed

Maurer, Matthew J; Sutardja, Lawrence; Pinel, Dominic; Bauer, Stefan; Muehlbauer, Amanda L; Ames, Tyler D; Skerker, Jeffrey M; Arkin, Adam P

2017-03-17

Engineering complex phenotypes for industrial and synthetic biology applications is difficult and often confounds rational design. Bioethanol production from lignocellulosic feedstocks is a complex trait that requires multiple host systems to utilize, detoxify, and metabolize a mixture of sugars and inhibitors present in plant hydrolysates. Here, we demonstrate an integrated approach to discovering and optimizing host factors that impact fitness of Saccharomyces cerevisiae during fermentation of a Miscanthus x giganteus plant hydrolysate. We first used high-resolution Quantitative Trait Loci (QTL) mapping and systematic bulk Reciprocal Hemizygosity Analysis (bRHA) to discover 17 loci that differentiate hydrolysate tolerance between an industrially related (JAY291) and a laboratory (S288C) strain. We then used this data to identify a subset of favorable allelic loci that were most amenable for strain engineering. Guided by this "genetic blueprint", and using a dual-guide Cas9-based method to efficiently perform multikilobase locus replacements, we engineered an S288C-derived strain with superior hydrolysate tolerance than JAY291. Our methods should be generalizable to engineering any complex trait in S. cerevisiae, as well as other organisms.

Combining field performance with controlled environment plant imaging to identify the genetic control of growth and transpiration underlying yield response to water-deficit stress in wheat

PubMed Central

Parent, Boris; Shahinnia, Fahimeh; Maphosa, Lance; Berger, Bettina; Rabie, Huwaida; Chalmers, Ken; Kovalchuk, Alex; Langridge, Peter; Fleury, Delphine

2015-01-01

Crop yield in low-rainfall environments is a complex trait under multigenic control that shows significant genotype×environment (G×E) interaction. One way to understand and track this trait is to link physiological studies to genetics by using imaging platforms to phenotype large segregating populations. A wheat population developed from parental lines contrasting in their mechanisms of yield maintenance under water deficit was studied in both an imaging platform and in the field. We combined phenotyping methods in a common analysis pipeline to estimate biomass and leaf area from images and then inferred growth and relative growth rate, transpiration, and water-use efficiency, and applied these to genetic analysis. From the 20 quantitative trait loci (QTLs) found for several traits in the platform, some showed strong effects, accounting for between 26 and 43% of the variation on chromosomes 1A and 1B, indicating that the G×E interaction could be reduced in a controlled environment and by using dynamic variables. Co-location of QTLs identified in the platform and in the field showed a possible common genetic basis at some loci. Co-located QTLs were found for average growth rate, leaf expansion rate, transpiration rate, and water-use efficiency from the platform with yield, spike number, grain weight, grain number, and harvest index in the field. These results demonstrated that imaging platforms are a suitable alternative to field-based screening and may be used to phenotype recombinant lines for positional cloning. PMID:26179580

Simulating the Yield Impacts of Organ-Level Quantitative Trait Loci Associated With Drought Response in Maize: A “Gene-to-Phenotype” Modeling Approach

PubMed Central

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

2009-01-01

Under drought, substantial genotype–environment (G × E) interactions impede breeding progress for yield. Identifying genetic controls associated with yield response is confounded by poor genetic correlations across testing environments. Part of this problem is related to our inability to account for the interplay of genetic controls, physiological traits, and environmental conditions throughout the crop cycle. We propose a modeling approach to bridge this “gene-to-phenotype” gap. For maize under drought, we simulated the impact of quantitative trait loci (QTL) controlling two key processes (leaf and silk elongation) that influence crop growth, water use, and grain yield. Substantial G × E interaction for yield was simulated for hypothetical recombinant inbred lines (RILs) across different seasonal patterns of drought. QTL that accelerated leaf elongation caused an increase in crop leaf area and yield in well-watered or preflowering water deficit conditions, but a reduction in yield under terminal stresses (as such “leafy” genotypes prematurely exhausted the water supply). The QTL impact on yield was substantially enhanced by including pleiotropic effects of these QTL on silk elongation and on consequent grain set. The simulations obtained illustrated the difficulty of interpreting the genetic control of yield for genotypes influenced only by the additive effects of QTL associated with leaf and silk growth. The results highlight the potential of integrative simulation modeling for gene-to-phenotype prediction and for exploiting G × E interactions for complex traits such as drought tolerance. PMID:19786622

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

PubMed Central

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

2018-01-01

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

Modeling adaptation of wetland plants under changing environments

NASA Astrophysics Data System (ADS)

Muneepeerakul, R.; Muneepeerakul, C. P.

2010-12-01

An evolutionary-game-theoretic approach is used to study the changes in traits of wetland plants in response to environmental changes, e.g., altered patterns of rainfall and nutrients. Here, a wetland is considered as a complex adaptive system where plants can adapt their strategies and influence one another. The system is subject to stochastic rainfall, which controls the dynamics of water level, soil moisture, and alternation between aerobic and anaerobic conditions in soil. Based on our previous work, a plant unit is characterized by three traits, namely biomass nitrogen content, specific leaf area, and allocation to rhizome. These traits control the basic functions of plants such as assimilation, respiration, and nutrient uptake, while affecting their environment through litter chemistry, root oxygenation, and thus soil microbial dynamics. The outcome of this evolutionary game, i.e., the best-performing plant traits against the backdrop of these interactions and feedbacks, is analyzed and its implications on important roles of wetlands in supporting our sustainability such as carbon sequestration in biosphere, nutrient cycling, and repository of biodiversity are discussed.

Integrated phenotypes: understanding trait covariation in plants and animals

PubMed Central

Armbruster, W. Scott; Pélabon, Christophe; Bolstad, Geir H.; Hansen, Thomas F.

2014-01-01

Integration and modularity refer to the patterns and processes of trait interaction and independence. Both terms have complex histories with respect to both conceptualization and quantification, resulting in a plethora of integration indices in use. We review briefly the divergent definitions, uses and measures of integration and modularity and make conceptual links to allometry. We also discuss how integration and modularity might evolve. Although integration is generally thought to be generated and maintained by correlational selection, theoretical considerations suggest the relationship is not straightforward. We caution here against uncontrolled comparisons of indices across studies. In the absence of controls for trait number, dimensionality, homology, development and function, it is difficult, or even impossible, to compare integration indices across organisms or traits. We suggest that care be invested in relating measurement to underlying theory or hypotheses, and that summative, theory-free descriptors of integration generally be avoided. The papers that follow in this Theme Issue illustrate the diversity of approaches to studying integration and modularity, highlighting strengths and pitfalls that await researchers investigating integration in plants and animals. PMID:25002693

Ecosystems Biology Approaches To Determine Key Fitness Traits of Soil Microorganisms

NASA Astrophysics Data System (ADS)

Brodie, E.; Zhalnina, K.; Karaoz, U.; Cho, H.; Nuccio, E. E.; Shi, S.; Lipton, M. S.; Zhou, J.; Pett-Ridge, J.; Northen, T.; Firestone, M.

2014-12-01

The application of theoretical approaches such as trait-based modeling represent powerful tools to explain and perhaps predict complex patterns in microbial distribution and function across environmental gradients in space and time. These models are mostly deterministic and where available are built upon a detailed understanding of microbial physiology and response to environmental factors. However as most soil microorganisms have not been cultivated, for the majority our understanding is limited to insights from environmental 'omic information. Information gleaned from 'omic studies of complex systems should be regarded as providing hypotheses, and these hypotheses should be tested under controlled laboratory conditions if they are to be propagated into deterministic models. In a semi-arid Mediterranean grassland system we are attempting to dissect microbial communities into functional guilds with defined physiological traits and are using a range of 'omics approaches to characterize their metabolic potential and niche preference. Initially, two physiologically relevant time points (peak plant activity and prior to wet-up) were sampled and metagenomes sequenced deeply (600-900 Gbp). Following assembly, differential coverage and nucleotide frequency binning were carried out to yield draft genomes. In addition, using a range of cultivation media we have isolated a broad range of bacteria representing abundant bacterial genotypes and with genome sequences of almost 40 isolates are testing genomic predictions regarding growth rate, temperature and substrate utilization in vitro. This presentation will discuss the opportunities and challenges in parameterizing microbial functional guilds from environmental 'omic information for use in trait-based models.

Impact of the Carbon and Nitrogen Supply on Relationships and Connectivity between Metabolism and Biomass in a Broad Panel of Arabidopsis Accessions1[W][OA

PubMed Central

Sulpice, Ronan; Nikoloski, Zoran; Tschoep, Hendrik; Antonio, Carla; Kleessen, Sabrina; Larhlimi, Abdelhalim; Selbig, Joachim; Ishihara, Hirofumi; Gibon, Yves; Fernie, Alisdair R.; Stitt, Mark

2013-01-01

Natural genetic diversity provides a powerful tool to study the complex interrelationship between metabolism and growth. Profiling of metabolic traits combined with network-based and statistical analyses allow the comparison of conditions and identification of sets of traits that predict biomass. However, it often remains unclear why a particular set of metabolites is linked with biomass and to what extent the predictive model is applicable beyond a particular growth condition. A panel of 97 genetically diverse Arabidopsis (Arabidopsis thaliana) accessions was grown in near-optimal carbon and nitrogen supply, restricted carbon supply, and restricted nitrogen supply and analyzed for biomass and 54 metabolic traits. Correlation-based metabolic networks were generated from the genotype-dependent variation in each condition to reveal sets of metabolites that show coordinated changes across accessions. The networks were largely specific for a single growth condition. Partial least squares regression from metabolic traits allowed prediction of biomass within and, slightly more weakly, across conditions (cross-validated Pearson correlations in the range of 0.27–0.58 and 0.21–0.51 and P values in the range of <0.001–<0.13 and <0.001–<0.023, respectively). Metabolic traits that correlate with growth or have a high weighting in the partial least squares regression were mainly condition specific and often related to the resource that restricts growth under that condition. Linear mixed-model analysis using the combined metabolic traits from all growth conditions as an input indicated that inclusion of random effects for the conditions improves predictions of biomass. Thus, robust prediction of biomass across a range of conditions requires condition-specific measurement of metabolic traits to take account of environment-dependent changes of the underlying networks. PMID:23515278

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

PubMed

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

2013-12-01

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

Poly-Omic Prediction of Complex Traits: OmicKriging

PubMed Central

Wheeler, Heather E.; Aquino-Michaels, Keston; Gamazon, Eric R.; Trubetskoy, Vassily V.; Dolan, M. Eileen; Huang, R. Stephanie; Cox, Nancy J.; Im, Hae Kyung

2014-01-01

High-confidence prediction of complex traits such as disease risk or drug response is an ultimate goal of personalized medicine. Although genome-wide association studies have discovered thousands of well-replicated polymorphisms associated with a broad spectrum of complex traits, the combined predictive power of these associations for any given trait is generally too low to be of clinical relevance. We propose a novel systems approach to complex trait prediction, which leverages and integrates similarity in genetic, transcriptomic, or other omics-level data. We translate the omic similarity into phenotypic similarity using a method called Kriging, commonly used in geostatistics and machine learning. Our method called OmicKriging emphasizes the use of a wide variety of systems-level data, such as those increasingly made available by comprehensive surveys of the genome, transcriptome, and epigenome, for complex trait prediction. Furthermore, our OmicKriging framework allows easy integration of prior information on the function of subsets of omics-level data from heterogeneous sources without the sometimes heavy computational burden of Bayesian approaches. Using seven disease datasets from the Wellcome Trust Case Control Consortium (WTCCC), we show that OmicKriging allows simple integration of sparse and highly polygenic components yielding comparable performance at a fraction of the computing time of a recently published Bayesian sparse linear mixed model method. Using a cellular growth phenotype, we show that integrating mRNA and microRNA expression data substantially increases performance over either dataset alone. Using clinical statin response, we show improved prediction over existing methods. PMID:24799323

MicroRNA-guided prioritization of genome-wide association signals reveals the importance of microRNA-target gene networks for complex traits in cattle.

PubMed

Fang, Lingzhao; Sørensen, Peter; Sahana, Goutam; Panitz, Frank; Su, Guosheng; Zhang, Shengli; Yu, Ying; Li, Bingjie; Ma, Li; Liu, George; Lund, Mogens Sandø; Thomsen, Bo

2018-06-19

MicroRNAs (miRNA) are key modulators of gene expression and so act as putative fine-tuners of complex phenotypes. Here, we hypothesized that causal variants of complex traits are enriched in miRNAs and miRNA-target networks. First, we conducted a genome-wide association study (GWAS) for seven functional and milk production traits using imputed sequence variants (13~15 million) and >10,000 animals from three dairy cattle breeds, i.e., Holstein (HOL), Nordic red cattle (RDC) and Jersey (JER). Second, we analyzed for enrichments of association signals in miRNAs and their miRNA-target networks. Our results demonstrated that genomic regions harboring miRNA genes were significantly (P < 0.05) enriched with GWAS signals for milk production traits and mastitis, and that enrichments within miRNA-target gene networks were significantly higher than in random gene-sets for the majority of traits. Furthermore, most between-trait and across-breed correlations of enrichments with miRNA-target networks were significantly greater than with random gene-sets, suggesting pleiotropic effects of miRNAs. Intriguingly, genes that were differentially expressed in response to mammary gland infections were significantly enriched in the miRNA-target networks associated with mastitis. All these findings were consistent across three breeds. Collectively, our observations demonstrate the importance of miRNAs and their targets for the expression of complex traits.

Improving breeding efficiency in potato using molecular and quantitative genetics.

PubMed

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

2014-11-01

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

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.

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

PubMed Central

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

2016-01-01

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

Building phenotype networks to improve QTL detection: a comparative analysis of fatty acid and fat traits in pigs.

PubMed

Yang, B; Navarro, N; Noguera, J L; Muñoz, M; Guo, T F; Yang, K X; Ma, J W; Folch, J M; Huang, L S; Pérez-Enciso, M

2011-10-01

Models in QTL mapping can be improved by considering all potential variables, i.e. we can use remaining traits other than the trait under study as potential predictors. QTL mapping is often conducted by correcting for a few fixed effects or covariates (e.g. sex, age), although many traits with potential causal relationships between them are recorded. In this work, we evaluate by simulation several procedures to identify optimum models in QTL scans: forward selection, undirected dependency graph and QTL-directed dependency graph (QDG). The latter, QDG, performed better in terms of power and false discovery rate and was applied to fatty acid (FA) composition and fat deposition traits in two pig F2 crosses from China and Spain. Compared with the typical QTL mapping, QDG approach revealed several new QTL. To the contrary, several FA QTL on chromosome 4 (e.g. Palmitic, C16:0; Stearic, C18:0) detected by typical mapping vanished after adjusting for phenotypic covariates in QDG mapping. This suggests that the QTL detected in typical mapping could be indirect. When a QTL is supported by both approaches, there is an increased confidence that the QTL have a primary effect on the corresponding trait. An example is a QTL for C16:1 on chromosome 8. In conclusion, mapping QTL based on causal phenotypic networks can increase power and help to make more biologically sound hypothesis on the genetic architecture of complex traits. © 2011 Blackwell Verlag GmbH.

Directional dominance on stature and cognition in diverse human populations.

PubMed

Joshi, Peter K; Esko, Tonu; Mattsson, Hannele; Eklund, Niina; Gandin, Ilaria; Nutile, Teresa; Jackson, Anne U; Schurmann, Claudia; Smith, Albert V; Zhang, Weihua; Okada, Yukinori; Stančáková, Alena; Faul, Jessica D; Zhao, Wei; Bartz, Traci M; Concas, Maria Pina; Franceschini, Nora; Enroth, Stefan; Vitart, Veronique; Trompet, Stella; Guo, Xiuqing; Chasman, Daniel I; O'Connel, Jeffery R; Corre, Tanguy; Nongmaithem, Suraj S; Chen, Yuning; Mangino, Massimo; Ruggiero, Daniela; Traglia, Michela; Farmaki, Aliki-Eleni; Kacprowski, Tim; Bjonnes, Andrew; van der Spek, Ashley; Wu, Ying; Giri, Anil K; Yanek, Lisa R; Wang, Lihua; Hofer, Edith; Rietveld, Cornelius A; McLeod, Olga; Cornelis, Marilyn C; Pattaro, Cristian; Verweij, Niek; Baumbach, Clemens; Abdellaoui, Abdel; Warren, Helen R; Vuckovic, Dragana; Mei, Hao; Bouchard, Claude; Perry, John R B; Cappellani, Stefania; Mirza, Saira S; Benton, Miles C; Broeckel, Ulrich; Medland, Sarah E; Lind, Penelope A; Malerba, Giovanni; Drong, Alexander; Yengo, Loic; Bielak, Lawrence F; Zhi, Degui; van der Most, Peter J; Shriner, Daniel; Mägi, Reedik; Hemani, Gibran; Karaderi, Tugce; Wang, Zhaoming; Liu, Tian; Demuth, Ilja; Zhao, Jing Hua; Meng, Weihua; Lataniotis, Lazaros; van der Laan, Sander W; Bradfield, Jonathan P; Wood, Andrew R; Bonnefond, Amelie; Ahluwalia, Tarunveer S; Hall, Leanne M; Salvi, Erika; Yazar, Seyhan; Carstensen, Lisbeth; de Haan, Hugoline G; Abney, Mark; Afzal, Uzma; Allison, Matthew A; Amin, Najaf; Asselbergs, Folkert W; Bakker, Stephan J L; Barr, R Graham; Baumeister, Sebastian E; Benjamin, Daniel J; Bergmann, Sven; Boerwinkle, Eric; Bottinger, Erwin P; Campbell, Archie; Chakravarti, Aravinda; Chan, Yingleong; Chanock, Stephen J; Chen, Constance; Chen, Y-D Ida; Collins, Francis S; Connell, John; Correa, Adolfo; Cupples, L Adrienne; Smith, George Davey; Davies, Gail; Dörr, Marcus; Ehret, Georg; Ellis, Stephen B; Feenstra, Bjarke; Feitosa, Mary F; Ford, Ian; Fox, Caroline S; Frayling, Timothy M; Friedrich, Nele; Geller, Frank; Scotland, Generation; Gillham-Nasenya, Irina; Gottesman, Omri; Graff, Misa; Grodstein, Francine; Gu, Charles; Haley, Chris; Hammond, Christopher J; Harris, Sarah E; Harris, Tamara B; Hastie, Nicholas D; Heard-Costa, Nancy L; Heikkilä, Kauko; Hocking, Lynne J; Homuth, Georg; Hottenga, Jouke-Jan; Huang, Jinyan; Huffman, Jennifer E; Hysi, Pirro G; Ikram, M Arfan; Ingelsson, Erik; Joensuu, Anni; Johansson, Åsa; Jousilahti, Pekka; Jukema, J Wouter; Kähönen, Mika; Kamatani, Yoichiro; Kanoni, Stavroula; Kerr, Shona M; Khan, Nazir M; Koellinger, Philipp; Koistinen, Heikki A; Kooner, Manraj K; Kubo, Michiaki; Kuusisto, Johanna; Lahti, Jari; Launer, Lenore J; Lea, Rodney A; Lehne, Benjamin; Lehtimäki, Terho; Liewald, David C M; Lind, Lars; Loh, Marie; Lokki, Marja-Liisa; London, Stephanie J; Loomis, Stephanie J; Loukola, Anu; Lu, Yingchang; Lumley, Thomas; Lundqvist, Annamari; Männistö, Satu; Marques-Vidal, Pedro; Masciullo, Corrado; Matchan, Angela; Mathias, Rasika A; Matsuda, Koichi; Meigs, James B; Meisinger, Christa; Meitinger, Thomas; Menni, Cristina; Mentch, Frank D; Mihailov, Evelin; Milani, Lili; Montasser, May E; Montgomery, Grant W; Morrison, Alanna; Myers, Richard H; Nadukuru, Rajiv; Navarro, Pau; Nelis, Mari; Nieminen, Markku S; Nolte, Ilja M; O'Connor, George T; Ogunniyi, Adesola; Padmanabhan, Sandosh; Palmas, Walter R; Pankow, James S; Patarcic, Inga; Pavani, Francesca; Peyser, Patricia A; Pietilainen, Kirsi; Poulter, Neil; Prokopenko, Inga; Ralhan, Sarju; Redmond, Paul; Rich, Stephen S; Rissanen, Harri; Robino, Antonietta; Rose, Lynda M; Rose, Richard; Sala, Cinzia; Salako, Babatunde; Salomaa, Veikko; Sarin, Antti-Pekka; Saxena, Richa; Schmidt, Helena; Scott, Laura J; Scott, William R; Sennblad, Bengt; Seshadri, Sudha; Sever, Peter; Shrestha, Smeeta; Smith, Blair H; Smith, Jennifer A; Soranzo, Nicole; Sotoodehnia, Nona; Southam, Lorraine; Stanton, Alice V; Stathopoulou, Maria G; Strauch, Konstantin; Strawbridge, Rona J; Suderman, Matthew J; Tandon, Nikhil; Tang, Sian-Tsun; Taylor, Kent D; Tayo, Bamidele O; Töglhofer, Anna Maria; Tomaszewski, Maciej; Tšernikova, Natalia; Tuomilehto, Jaakko; Uitterlinden, Andre G; Vaidya, Dhananjay; van Hylckama Vlieg, Astrid; van Setten, Jessica; Vasankari, Tuula; Vedantam, Sailaja; Vlachopoulou, Efthymia; Vozzi, Diego; Vuoksimaa, Eero; Waldenberger, Melanie; Ware, Erin B; Wentworth-Shields, William; Whitfield, John B; Wild, Sarah; Willemsen, Gonneke; Yajnik, Chittaranjan S; Yao, Jie; Zaza, Gianluigi; Zhu, Xiaofeng; Project, The BioBank Japan; Salem, Rany M; Melbye, Mads; Bisgaard, Hans; Samani, Nilesh J; Cusi, Daniele; Mackey, David A; Cooper, Richard S; Froguel, Philippe; Pasterkamp, Gerard; Grant, Struan F A; Hakonarson, Hakon; Ferrucci, Luigi; Scott, Robert A; Morris, Andrew D; Palmer, Colin N A; Dedoussis, George; Deloukas, Panos; Bertram, Lars; Lindenberger, Ulman; Berndt, Sonja I; Lindgren, Cecilia M; Timpson, Nicholas J; Tönjes, Anke; Munroe, Patricia B; Sørensen, Thorkild I A; Rotimi, Charles N; Arnett, Donna K; Oldehinkel, Albertine J; Kardia, Sharon L R; Balkau, Beverley; Gambaro, Giovanni; Morris, Andrew P; Eriksson, Johan G; Wright, Margie J; Martin, Nicholas G; Hunt, Steven C; Starr, John M; Deary, Ian J; Griffiths, Lyn R; Tiemeier, Henning; Pirastu, Nicola; Kaprio, Jaakko; Wareham, Nicholas J; Pérusse, Louis; Wilson, James G; Girotto, Giorgia; Caulfield, Mark J; Raitakari, Olli; Boomsma, Dorret I; Gieger, Christian; van der Harst, Pim; Hicks, Andrew A; Kraft, Peter; Sinisalo, Juha; Knekt, Paul; Johannesson, Magnus; Magnusson, Patrik K E; Hamsten, Anders; Schmidt, Reinhold; Borecki, Ingrid B; Vartiainen, Erkki; Becker, Diane M; Bharadwaj, Dwaipayan; Mohlke, Karen L; Boehnke, Michael; van Duijn, Cornelia M; Sanghera, Dharambir K; Teumer, Alexander; Zeggini, Eleftheria; Metspalu, Andres; Gasparini, Paolo; Ulivi, Sheila; Ober, Carole; Toniolo, Daniela; Rudan, Igor; Porteous, David J; Ciullo, Marina; Spector, Tim D; Hayward, Caroline; Dupuis, Josée; Loos, Ruth J F; Wright, Alan F; Chandak, Giriraj R; Vollenweider, Peter; Shuldiner, Alan; Ridker, Paul M; Rotter, Jerome I; Sattar, Naveed; Gyllensten, Ulf; North, Kari E; Pirastu, Mario; Psaty, Bruce M; Weir, David R; Laakso, Markku; Gudnason, Vilmundur; Takahashi, Atsushi; Chambers, John C; Kooner, Jaspal S; Strachan, David P; Campbell, Harry; Hirschhorn, Joel N; Perola, Markus; Polašek, Ozren; Wilson, James F

2015-07-23

Homozygosity has long been associated with rare, often devastating, Mendelian disorders, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10(-300), 2.1 × 10(-6), 2.5 × 10(-10) and 1.8 × 10(-10), respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months' less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.

Directional dominance on stature and cognition in diverse human populations

PubMed Central

Mattsson, Hannele; Eklund, Niina; Gandin, Ilaria; Nutile, Teresa; Jackson, Anne U.; Schurmann, Claudia; Smith, Albert V.; Zhang, Weihua; Okada, Yukinori; Stančáková, Alena; Faul, Jessica D.; Zhao, Wei; Bartz, Traci M.; Concas, Maria Pina; Franceschini, Nora; Enroth, Stefan; Vitart, Veronique; Trompet, Stella; Guo, Xiuqing; Chasman, Daniel I.; O’Connel, Jeffery R.; Corre, Tanguy; Nongmaithem, Suraj S.; Chen, Yuning; Mangino, Massimo; Ruggiero, Daniela; Traglia, Michela; Farmaki, Aliki-Eleni; Kacprowski, Tim; Bjonnes, Andrew; van der Spek, Ashley; Wu, Ying; Giri, Anil K.; Yanek, Lisa R.; Wang, Lihua; Hofer, Edith; Rietveld, Cornelius A.; McLeod, Olga; Cornelis, Marilyn C.; Pattaro, Cristian; Verweij, Niek; Baumbach, Clemens; Abdellaoui, Abdel; Warren, Helen R.; Vuckovic, Dragana; Mei, Hao; Bouchard, Claude; Perry, John R.B.; Cappellani, Stefania; Mirza, Saira S.; Benton, Miles C.; Broeckel, Ulrich; Medland, Sarah E.; Lind, Penelope A.; Malerba, Giovanni; Drong, Alexander; Yengo, Loic; Bielak, Lawrence F.; Zhi, Degui; van der Most, Peter J.; Shriner, Daniel; Mägi, Reedik; Hemani, Gibran; Karaderi, Tugce; Wang, Zhaoming; Liu, Tian; Demuth, Ilja; Zhao, Jing Hua; Meng, Weihua; Lataniotis, Lazaros; van der Laan, Sander W.; Bradfield, Jonathan P.; Wood, Andrew R.; Bonnefond, Amelie; Ahluwalia, Tarunveer S.; Hall, Leanne M.; Salvi, Erika; Yazar, Seyhan; Carstensen, Lisbeth; de Haan, Hugoline G.; Abney, Mark; Afzal, Uzma; Allison, Matthew A.; Amin, Najaf; Asselbergs, Folkert W.; Bakker, Stephan J.L.; Barr, R. Graham; Baumeister, Sebastian E.; Benjamin, Daniel J.; Bergmann, Sven; Boerwinkle, Eric; Bottinger, Erwin P.; Campbell, Archie; Chakravarti, Aravinda; Chan, Yingleong; Chanock, Stephen J.; Chen, Constance; Chen, Y.-D. Ida; Collins, Francis S.; Connell, John; Correa, Adolfo; Cupples, L. Adrienne; Smith, George Davey; Davies, Gail; Dörr, Marcus; Ehret, Georg; Ellis, Stephen B.; Feenstra, Bjarke; Feitosa, Mary F.; Ford, Ian; Fox, Caroline S.; Frayling, Timothy M.; Friedrich, Nele; Geller, Frank; Scotland, Generation; Gillham-Nasenya, Irina; Gottesman, Omri; Graff, Misa; Grodstein, Francine; Gu, Charles; Haley, Chris; Hammond, Christopher J.; Harris, Sarah E.; Harris, Tamara B.; Hastie, Nicholas D.; Heard-Costa, Nancy L.; Heikkilä, Kauko; Hocking, Lynne J.; Homuth, Georg; Hottenga, Jouke-Jan; Huang, Jinyan; Huffman, Jennifer E.; Hysi, Pirro G.; Ikram, M. Arfan; Ingelsson, Erik; Joensuu, Anni; Johansson, Åsa; Jousilahti, Pekka; Jukema, J. Wouter; Kähönen, Mika; Kamatani, Yoichiro; Kanoni, Stavroula; Kerr, Shona M.; Khan, Nazir M.; Koellinger, Philipp; Koistinen, Heikki A.; Kooner, Manraj K.; Kubo, Michiaki; Kuusisto, Johanna; Lahti, Jari; Launer, Lenore J.; Lea, Rodney A.; Lehne, Benjamin; Lehtimäki, Terho; Liewald, David C.M.; Lind, Lars; Loh, Marie; Lokki, Marja-Liisa; London, Stephanie J.; Loomis, Stephanie J.; Loukola, Anu; Lu, Yingchang; Lumley, Thomas; Lundqvist, Annamari; Männistö, Satu; Marques-Vidal, Pedro; Masciullo, Corrado; Matchan, Angela; Mathias, Rasika A.; Matsuda, Koichi; Meigs, James B.; Meisinger, Christa; Meitinger, Thomas; Menni, Cristina; Mentch, Frank D.; Mihailov, Evelin; Milani, Lili; Montasser, May E.; Montgomery, Grant W.; Morrison, Alanna; Myers, Richard H.; Nadukuru, Rajiv; Navarro, Pau; Nelis, Mari; Nieminen, Markku S.; Nolte, Ilja M.; O’Connor, George T.; Ogunniyi, Adesola; Padmanabhan, Sandosh; Palmas, Walter R.; Pankow, James S.; Patarcic, Inga; Pavani, Francesca; Peyser, Patricia A.; Pietilainen, Kirsi; Poulter, Neil; Prokopenko, Inga; Ralhan, Sarju; Redmond, Paul; Rich, Stephen S.; Rissanen, Harri; Robino, Antonietta; Rose, Lynda M.; Rose, Richard; Sala, Cinzia; Salako, Babatunde; Salomaa, Veikko; Sarin, Antti-Pekka; Saxena, Richa; Schmidt, Helena; Scott, Laura J.; Scott, William R.; Sennblad, Bengt; Seshadri, Sudha; Sever, Peter; Shrestha, Smeeta; Smith, Blair H.; Smith, Jennifer A.; Soranzo, Nicole; Sotoodehnia, Nona; Southam, Lorraine; Stanton, Alice V.; Stathopoulou, Maria G.; Strauch, Konstantin; Strawbridge, Rona J.; Suderman, Matthew J.; Tandon, Nikhil; Tang, Sian-Tsun; Taylor, Kent D.; Tayo, Bamidele O.; Töglhofer, Anna Maria; Tomaszewski, Maciej; Tšernikova, Natalia; Tuomilehto, Jaakko; Uitterlinden, Andre G.; Vaidya, Dhananjay; van Hylckama Vlieg, Astrid; van Setten, Jessica; Vasankari, Tuula; Vedantam, Sailaja; Vlachopoulou, Efthymia; Vozzi, Diego; Vuoksimaa, Eero; Waldenberger, Melanie; Ware, Erin B.; Wentworth-Shields, William; Whitfield, John B.; Wild, Sarah; Willemsen, Gonneke; Yajnik, Chittaranjan S.; Yao, Jie; Zaza, Gianluigi; Zhu, Xiaofeng; Project, The BioBank Japan; Salem, Rany M.; Melbye, Mads; Bisgaard, Hans; Samani, Nilesh J.; Cusi, Daniele; Mackey, David A.; Cooper, Richard S.; Froguel, Philippe; Pasterkamp, Gerard; Grant, Struan F.A.; Hakonarson, Hakon; Ferrucci, Luigi; Scott, Robert A.; Morris, Andrew D.; Palmer, Colin N.A.; Dedoussis, George; Deloukas, Panos; Bertram, Lars; Lindenberger, Ulman; Berndt, Sonja I.; Lindgren, Cecilia M.; Timpson, Nicholas J.; Tönjes, Anke; Munroe, Patricia B.; Sørensen, Thorkild I.A.; Rotimi, Charles N.; Arnett, Donna K.; Oldehinkel, Albertine J.; Kardia, Sharon L.R.; Balkau, Beverley; Gambaro, Giovanni; Morris, Andrew P.; Eriksson, Johan G.; Wright, Margie J.; Martin, Nicholas G.; Hunt, Steven C.; Starr, John M.; Deary, Ian J.; Griffiths, Lyn R.; Tiemeier, Henning; Pirastu, Nicola; Kaprio, Jaakko; Wareham, Nicholas J.; Pérusse, Louis; Wilson, James G.; Girotto, Giorgia; Caulfield, Mark J.; Raitakari, Olli; Boomsma, Dorret I.; Gieger, Christian; van der Harst, Pim; Hicks, Andrew A.; Kraft, Peter; Sinisalo, Juha; Knekt, Paul; Johannesson, Magnus; Magnusson, Patrik K.E.; Hamsten, Anders; Schmidt, Reinhold; Borecki, Ingrid B.; Vartiainen, Erkki; Becker, Diane M.; Bharadwaj, Dwaipayan; Mohlke, Karen L.; Boehnke, Michael; van Duijn, Cornelia M.; Sanghera, Dharambir K.; Teumer, Alexander; Zeggini, Eleftheria; Metspalu, Andres; Gasparini, Paolo; Ulivi, Sheila; Ober, Carole; Toniolo, Daniela; Rudan, Igor; Porteous, David J.; Ciullo, Marina; Spector, Tim D.; Hayward, Caroline; Dupuis, Josée; Loos, Ruth J.F.; Wright, Alan F.; Chandak, Giriraj R.; Vollenweider, Peter; Shuldiner, Alan; Ridker, Paul M.; Rotter, Jerome I.; Sattar, Naveed; Gyllensten, Ulf; North, Kari E.; Pirastu, Mario; Psaty, Bruce M.; Weir, David R.; Laakso, Markku; Gudnason, Vilmundur; Takahashi, Atsushi; Chambers, John C.; Kooner, Jaspal S.; Strachan, David P.; Campbell, Harry; Hirschhorn, Joel N.; Perola, Markus

2015-01-01

Homozygosity has long been associated with rare, often devastating, Mendelian disorders1 and Darwin was one of the first to recognise that inbreeding reduces evolutionary fitness2. However, the effect of the more distant parental relatedness common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity, ROH), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power3,4. Here we use ROH to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts and find statistically significant associations between summed runs of homozygosity (SROH) and four complex traits: height, forced expiratory lung volume in 1 second (FEV1), general cognitive ability (g) and educational attainment (nominal p<1 × 10−300, 2.1 × 10−6, 2.5 × 10−10, 1.8 × 10−10). In each case increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing convincing evidence for the first time that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples5,6, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein (LDL) cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection7, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been. PMID:26131930

Diversification dynamics of rhynchostomatian ciliates: the impact of seven intrinsic traits on speciation and extinction in a microbial group.

PubMed

Vďačný, Peter; Rajter, Ľubomír; Shazib, Shahed Uddin Ahmed; Jang, Seok Won; Shin, Mann Kyoon

2017-08-30

Ciliates are a suitable microbial model to investigate trait-dependent diversification because of their comparatively complex morphology and high diversity. We examined the impact of seven intrinsic traits on speciation, extinction, and net-diversification of rhynchostomatians, a group of comparatively large, predatory ciliates with proboscis carrying a dorsal brush (sensoric structure) and toxicysts (organelles used to kill the prey). Bayesian estimates under the binary-state speciation and extinction model indicate that two types of extrusomes and two-rowed dorsal brush raise diversification through decreasing extinction. On the other hand, the higher number of contractile vacuoles and their dorsal location likely increase diversification via elevating speciation rate. Particular nuclear characteristics, however, do not significantly differ in their diversification rates and hence lineages with various macronuclear patterns and number of micronuclei have similar probabilities to generate new species. Likelihood-based quantitative state diversification analyses suggest that rhynchostomatians conform to Cope's rule in that their diversity linearly grows with increasing body length and relative length of the proboscis. Comparison with other litostomatean ciliates indicates that rhynchostomatians are not among the cladogenically most successful lineages and their survival over several hundred million years could be associated with their comparatively large and complex bodies that reduce the risk of extinction.

Integrative approaches for large-scale transcriptome-wide association studies

PubMed Central

Gusev, Alexander; Ko, Arthur; Shi, Huwenbo; Bhatia, Gaurav; Chung, Wonil; Penninx, Brenda W J H; Jansen, Rick; de Geus, Eco JC; Boomsma, Dorret I; Wright, Fred A; Sullivan, Patrick F; Nikkola, Elina; Alvarez, Marcus; Civelek, Mete; Lusis, Aldons J.; Lehtimäki, Terho; Raitoharju, Emma; Kähönen, Mika; Seppälä, Ilkka; Raitakari, Olli T.; Kuusisto, Johanna; Laakso, Markku; Price, Alkes L.; Pajukanta, Päivi; Pasaniuc, Bogdan

2016-01-01

Many genetic variants influence complex traits by modulating gene expression, thus altering the abundance levels of one or multiple proteins. Here, we introduce a powerful strategy that integrates gene expression measurements with summary association statistics from large-scale genome-wide association studies (GWAS) to identify genes whose cis-regulated expression is associated to complex traits. We leverage expression imputation to perform a transcriptome wide association scan (TWAS) to identify significant expression-trait associations. We applied our approaches to expression data from blood and adipose tissue measured in ~3,000 individuals overall. We imputed gene expression into GWAS data from over 900,000 phenotype measurements to identify 69 novel genes significantly associated to obesity-related traits (BMI, lipids, and height). Many of the novel genes are associated with relevant phenotypes in the Hybrid Mouse Diversity Panel. Our results showcase the power of integrating genotype, gene expression and phenotype to gain insights into the genetic basis of complex traits. PMID:26854917

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).

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

PubMed

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

2018-06-01

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

Sensitivity assessment of freshwater macroinvertebrates to pesticides using biological traits.

PubMed

Ippolito, A; Todeschini, R; Vighi, M

2012-03-01

Assessing the sensitivity of different species to chemicals is one of the key points in predicting the effects of toxic compounds in the environment. Trait-based predicting methods have proved to be extremely efficient for assessing the sensitivity of macroinvertebrates toward compounds with non specific toxicity (narcotics). Nevertheless, predicting the sensitivity of organisms toward compounds with specific toxicity is much more complex, since it depends on the mode of action of the chemical. The aim of this work was to predict the sensitivity of several freshwater macroinvertebrates toward three classes of plant protection products: organophosphates, carbamates and pyrethroids. Two databases were built: one with sensitivity data (retrieved, evaluated and selected from the U.S. Environmental Protection Agency ECOTOX database) and the other with biological traits. Aside from the "traditional" traits usually considered in ecological analysis (i.e. body size, respiration technique, feeding habits, etc.), multivariate analysis was used to relate the sensitivity of organisms to some other characteristics which may be involved in the process of intoxication. Results confirmed that, besides traditional biological traits, related to uptake capability (e.g. body size and body shape) some traits more related to particular metabolic characteristics or patterns have a good predictive capacity on the sensitivity to these kinds of toxic substances. For example, behavioral complexity, assumed as an indicator of nervous system complexity, proved to be an important predictor of sensitivity towards these compounds. These results confirm the need for more complex traits to predict effects of highly specific substances. One key point for achieving a complete mechanistic understanding of the process is the choice of traits, whose role in the discrimination of sensitivity should be clearly interpretable, and not only statistically significant.

Phylogeny and species traits predict bird detectability

USGS Publications Warehouse

Solymos, Peter; Matsuoka, Steven M.; Stralberg, Diana; Barker, Nicole K. S.; Bayne, Erin M.

2018-01-01

Avian acoustic communication has resulted from evolutionary pressures and ecological constraints. We therefore expect that auditory detectability in birds might be predictable by species traits and phylogenetic relatedness. We evaluated the relationship between phylogeny, species traits, and field‐based estimates of the two processes that determine species detectability (singing rate and detection distance) for 141 bird species breeding in boreal North America. We used phylogenetic mixed models and cross‐validation to compare the relative merits of using trait data only, phylogeny only, or the combination of both to predict detectability. We found a strong phylogenetic signal in both singing rates and detection distances; however the strength of phylogenetic effects was less than expected under Brownian motion evolution. The evolution of behavioural traits that determine singing rates was found to be more labile, leaving more room for species to evolve independently, whereas detection distance was mostly determined by anatomy (i.e. body size) and thus the laws of physics. Our findings can help in disentangling how complex ecological and evolutionary mechanisms have shaped different aspects of detectability in boreal birds. Such information can greatly inform single‐ and multi‐species models but more work is required to better understand how to best correct possible biases in phylogenetic diversity and other community metrics.

Linkage disequilibrium interval mapping of quantitative trait loci.

PubMed

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

2006-03-16

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

Mating behavior and the evolution of sperm design

PubMed Central

Schärer, Lukas; Littlewood, D. Timothy J.; Waeschenbach, Andrea; Yoshida, Wataru; Vizoso, Dita B.

2011-01-01

Sperm are the most diverse of all animal cell types, and much of the diversity in sperm design is thought to reflect adaptations to the highly variable conditions under which sperm function and compete to achieve fertilization. Recent work has shown that these conditions often evolve rapidly as a consequence of multiple mating, suggesting a role for sexual selection and sexual conflict in the evolution of sperm design. However, very little of the striking diversity in sperm design is understood functionally, particularly in internally fertilizing organisms. We use phylogenetic comparative analyses covering 16 species of the hermaphroditic flatworm genus Macrostomum to show that a complex sperm design is associated with reciprocal mating and that this complexity is lost secondarily when hypodermic insemination—sperm injection through the epidermis—evolves. Specifically, the complex sperm design, which includes stiff lateral bristles, is likely a male persistence trait associated with sexual conflicts over the fate of received ejaculates and linked to female resistance traits, namely an intriguing postcopulatory sucking behavior and a thickened epithelium of the sperm-receiving organ. Our results suggest that the interactions between sperm donor, sperm, and sperm recipient can change drastically when hypodermic insemination evolves, involving convergent evolution of a needle-like copulatory organ, a simpler sperm design, and a simpler female genital morphology. Our study documents that a shift in the mating behavior may alter fundamentally the conditions under which sperm compete and thereby lead to a drastic change in sperm design. PMID:21220334

Meta-analysis of cotton fiber quality QTLs across diverse environments in a Gossypium hirsutum x G. barbadense RIL population.

PubMed

Lacape, Jean-Marc; Llewellyn, Danny; Jacobs, John; Arioli, Tony; Becker, David; Calhoun, Steve; Al-Ghazi, Yves; Liu, Shiming; Palaï, Oumarou; Georges, Sophie; Giband, Marc; de Assunção, Henrique; Barroso, Paulo Augusto Vianna; Claverie, Michel; Gawryziak, Gérard; Jean, Janine; Vialle, Michèle; Viot, Christopher

2010-06-28

Cotton fibers (produced by Gossypium species) are the premier natural fibers for textile production. The two tetraploid species, G. barbadense (Gb) and G. hirsutum (Gh), differ significantly in their fiber properties, the former having much longer, finer and stronger fibers that are highly prized. A better understanding of the genetics and underlying biological causes of these differences will aid further improvement of cotton quality through breeding and biotechnology. We evaluated an inter-specific Gh x Gb recombinant inbred line (RIL) population for fiber characteristics in 11 independent experiments under field and glasshouse conditions. Sites were located on 4 continents and 5 countries and some locations were analyzed over multiple years. The RIL population displayed a large variability for all major fiber traits. QTL analyses were performed on a per-site basis by composite interval mapping. Among the 651 putative QTLs (LOD > 2), 167 had a LOD exceeding permutation based thresholds. Coincidence in QTL location across data sets was assessed for the fiber trait categories strength, elongation, length, length uniformity, fineness/maturity, and color. A meta-analysis of more than a thousand putative QTLs was conducted with MetaQTL software to integrate QTL data from the RIL and 3 backcross populations (from the same parents) and to compare them with the literature. Although the global level of congruence across experiments and populations was generally moderate, the QTL clustering was possible for 30 trait x chromosome combinations (5 traits in 19 different chromosomes) where an effective co-localization of unidirectional (similar sign of additivity) QTLs from at least 5 different data sets was observed. Most consistent meta-clusters were identified for fiber color on chromosomes c6, c8 and c25, fineness on c15, and fiber length on c3. Meta-analysis provided a reliable means of integrating phenotypic and genetic mapping data across multiple populations and environments for complex fiber traits. The consistent chromosomal regions contributing to fiber quality traits constitute good candidates for the further dissection of the genetic and genomic factors underlying important fiber characteristics, and for marker-assisted selection.

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

PubMed

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

2016-07-16

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

Constitutional mechanisms of vulnerability and resilience to nicotine dependence

PubMed Central

Hiroi, N; Scott, D

2017-01-01

The core nature of nicotine dependence is evident in wide variations in how individuals become and remain smokers. Individuals with pre-existing behavioral traits are more likely to develop nicotine dependence and experience difficulty when attempting to quit. Many molecular factors likely contribute to individual variations in the development of nicotine dependence and behavioral traits in complex manners. However, the identification of such molecules has been hampered by the phenotypic complexity of nicotine dependence and the complex ways molecules affect elements of nicotine dependence. We hypothesize that nicotine dependence is, in part, a result of interactions between nicotine and pre-existing behavioral traits. This perspective suggests that the identification of the molecular bases of such pre-existing behavioral traits will contribute to the development of effective methods for reducing smoking dependence and for helping smokers to quit. PMID:19238150

A Meta-analysis of Plant Photosynthetic Traits and Water-use efficiency Responses to Drought

NASA Astrophysics Data System (ADS)

Zhang, J.

2017-12-01

Drought is predicted to become more intense and frequent in many regions of the world in the context of climate change, especially in the semi-arid regions of the Northern Hemisphere. Understanding the plant photosynthetic traits (Pn, Gs and Tr) and water use efficiency (WUE) response to drought is very important with regard to plant growth and productivity, which could reflect the terrestrial primary productivity worldwide. We used a meta-analysis based on studies of a worldwide range and full plant species Pn, Gs, Tr and WUE under drought condition and aimed to determine the responses of Pn, Gs, Tr and WUE of different drought intensities (mild, moderate and severe), different photosynthetic pathways (C3 and C4) and growth forms (herbs, shrubs, trees and lianas). Furthermore, reveal the differences from different plant groups (e.g. C3 and C4 plants; annual (A-herbs) and perennial (P-herbs) herbs; conifer, deciduous and evergreen trees) under the same drought intensities. Additionally, we analyzed the relationship between stomatal conductance (Gs) with Pn, Tr and WUE. Our results were as follows: 1) drought decreased the photosynthetic traits with the drought stress increasing, but increased the water use efficiency, and increased to the greatest extent in lianas, compared with herbs, shrubs and trees. 2) Furthermore, C4 plants had an advantage in photosynthesis compared to C3 plants under the same drought conditions. However, the WUE in C4 plants was not promoted as in C3 plants. The photosynthesis traits showed a more substantial decrease in P-herbs than in A-herbs. The drought promoted the WUE in P-herbs, but inhibited it in A-herbs. Compared with conifer and deciduous trees, the photosynthesis traits declined the most in evergreen tree. The WUE in deciduous trees showed a more obvious increase among the three leaf habits. 3) Finally, the Gs showed a close relationship with photosynthesis rate (Pn) and transpiration rate (Tr), which could explain 50% of the decrease in the Pn and 72% of the decline in Tr. Nevertheless, the Gs did not show a significant linear correlation with WUE, it's a more complex relationship between them .Our study provides comprehensive information about the changes in plant photosynthetic traits and water use efficiency under drought.

Inconsistencies in spontaneous and intentional trait inferences.

PubMed

Ma, Ning; Vandekerckhove, Marie; Baetens, Kris; Van Overwalle, Frank; Seurinck, Ruth; Fias, Wim

2012-11-01

This study explores the fMRI correlates of observers making trait inferences about other people under conflicting social cues. Participants were presented with several behavioral descriptions involving an agent that implied a particular trait. The last behavior was either consistent or inconsistent with the previously implied trait. This was done under instructions that elicited either spontaneous trait inferences ('read carefully') or intentional trait inferences ('infer a trait'). The results revealed that when the behavioral descriptions violated earlier trait implications, regardless of instruction, the medial prefrontal cortex (mPFC) was more strongly recruited as well as the domain-general conflict network including the posterior medial frontal cortex (pmFC) and the right prefrontal cortex (rPFC). These latter two areas were more strongly activated under intentional than spontaneous instructions. These findings suggest that when trait-relevant behavioral information is inconsistent, not only is activity increased in the mentalizing network responsible for trait processing, but control is also passed to a higher level conflict monitoring network in order to detect and resolve the contradiction.

The effect of induced mutations on quantitative traits in Arabidopsis thaliana: Natural versus artificial conditions.

PubMed

Stearns, Frank W; Fenster, Charles B

2016-12-01

Mutations are the ultimate source of all genetic variations. New mutations are expected to affect quantitative traits differently depending on the extent to which traits contribute to fitness and the environment in which they are tested. The dogma is that the preponderance of mutations affecting fitness will be skewed toward deleterious while their effects on nonfitness traits will be bidirectionally distributed. There are mixed views on the role of stress in modulating these effects. We quantify mutation effects by inducing mutations in Arabidopsis thaliana (Columbia accession) using the chemical ethylmethane sulfonate. We measured the effects of new mutations relative to a premutation founder for fitness components under both natural (field) and artificial (growth room) conditions. Additionally, we measured three other quantitative traits, not expected to contribute directly to fitness, under artificial conditions. We found that induced mutations were equally as likely to increase as decrease a trait when that trait was not closely related to fitness (traits that were neither survivorship nor reproduction). We also found that new mutations were more likely to decrease fitness or fitness-related traits under more stressful field conditions than under relatively benign artificial conditions. In the benign condition, the effect of new mutations on fitness components was similar to traits not as closely related to fitness. These results highlight the importance of measuring the effects of new mutations on fitness and other traits under a range of conditions.

Highly polygenic variation in environmental perception determines dauer larvae formation in growing populations of Caenorhabditis elegans.

PubMed

Green, James W M; Stastna, Jana J; Orbidans, Helen E; Harvey, Simon C

2014-01-01

Determining how complex traits are genetically controlled is a requirement if we are to predict how they evolve and how they might respond to selection. This requires understanding how distinct, and often more simple, life history traits interact and change in response to environmental conditions. In order to begin addressing such issues, we have been analyzing the formation of the developmentally arrested dauer larvae of Caenorhabditis elegans under different conditions. We find that 18 of 22 previously identified quantitative trait loci (QTLs) affecting dauer larvae formation in growing populations, assayed by determining the number of dauer larvae present at food patch exhaustion, can be recovered under various environmental conditions. We also show that food patch size affects both the ability to detect QTLs and estimates of effect size, and demonstrate that an allele of nath-10 affects dauer larvae formation in growing populations. To investigate the component traits that affect dauer larvae formation in growing populations we map, using the same introgression lines, QTLs that affect dauer larvae formation in response to defined amounts of pheromone. This identifies 36 QTLs, again demonstrating the highly polygenic nature of the genetic variation underlying dauer larvae formation. These data indicate that QTLs affecting the number of dauer larvae at food exhaustion in growing populations of C. elegans are highly reproducible, and that nearly all can be explained by variation affecting dauer larvae formation in response to defined amounts of pheromone. This suggests that most variation in dauer larvae formation in growing populations is a consequence of variation in the perception of the food and pheromone environment (i.e. chemosensory variation) and in the integration of these cues.

Combining field performance with controlled environment plant imaging to identify the genetic control of growth and transpiration underlying yield response to water-deficit stress in wheat.

PubMed

Parent, Boris; Shahinnia, Fahimeh; Maphosa, Lance; Berger, Bettina; Rabie, Huwaida; Chalmers, Ken; Kovalchuk, Alex; Langridge, Peter; Fleury, Delphine

2015-09-01

Crop yield in low-rainfall environments is a complex trait under multigenic control that shows significant genotype×environment (G×E) interaction. One way to understand and track this trait is to link physiological studies to genetics by using imaging platforms to phenotype large segregating populations. A wheat population developed from parental lines contrasting in their mechanisms of yield maintenance under water deficit was studied in both an imaging platform and in the field. We combined phenotyping methods in a common analysis pipeline to estimate biomass and leaf area from images and then inferred growth and relative growth rate, transpiration, and water-use efficiency, and applied these to genetic analysis. From the 20 quantitative trait loci (QTLs) found for several traits in the platform, some showed strong effects, accounting for between 26 and 43% of the variation on chromosomes 1A and 1B, indicating that the G×E interaction could be reduced in a controlled environment and by using dynamic variables. Co-location of QTLs identified in the platform and in the field showed a possible common genetic basis at some loci. Co-located QTLs were found for average growth rate, leaf expansion rate, transpiration rate, and water-use efficiency from the platform with yield, spike number, grain weight, grain number, and harvest index in the field. These results demonstrated that imaging platforms are a suitable alternative to field-based screening and may be used to phenotype recombinant lines for positional cloning. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology.

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

Natural selection and inheritance of breeding time and clutch size in the collared flycatcher.

PubMed

Sheldon, B C; Kruuk, L E B; Merilä, J

2003-02-01

Many characteristics of organisms in free-living populations appear to be under directional selection, possess additive genetic variance, and yet show no evolutionary response to selection. Avian breeding time and clutch size are often-cited examples of such characters. We report analyses of inheritance of, and selection on, these traits in a long-term study of a wild population of the collared flycatcher Ficedula albicollis. We used mixed model analysis with REML estimation ("animal models") to make full use of the information in complex multigenerational pedigrees. Heritability of laying date, but not clutch size, was lower than that estimated previously using parent-offspring regressions, although for both traits there was evidence of substantial additive genetic variance (h2 = 0.19 and 0.29, respectively). Laying date and clutch size were negatively genetically correlated (rA = -0.41 +/- 0.09), implying that selection on one of the traits would cause a correlated response in the other, but there was little evidence to suggest that evolution of either trait would be constrained by correlations with other phenotypic characters. Analysis of selection on these traits in females revealed consistent strong directional fecundity selection for earlier breeding at the level of the phenotype (beta = -0.28 +/- 0.03), but little evidence for stabilising selection on breeding time. We found no evidence that clutch size was independently under selection. Analysis of fecundity selection on breeding values for laying date, estimated from an animal model, indicated that selection acts directly on additive genetic variance underlying breeding time (beta = -0.20 +/- 0.04), but not on clutch size (beta = 0.03 +/- 0.05). In contrast, selection on laying date via adult female survival fluctuated in sign between years, and was opposite in sign for selection on phenotypes (negative) and breeding values (positive). Our data thus suggest that any evolutionary response to selection on laying date is partially constrained by underlying life-history trade-offs, and illustrate the difficulties in using purely phenotypic measures and incomplete fitness estimates to assess evolution of life-history trade-offs. We discuss some of the difficulties associated with understanding the evolution of laying date and clutch size in natural populations.

Enhancing genomic prediction with genome-wide association studies in multiparental maize populations

USDA-ARS?s Scientific Manuscript database

Genome-wide association mapping using dense marker sets has identified some nucleotide variants affecting complex traits which have been validated with fine-mapping and functional analysis. Many sequence variants associated with complex traits in maize have small effects and low repeatability, howev...

Different Phylogenetic and Environmental Controls of First-order Root Morphological and Chemical Traits

NASA Astrophysics Data System (ADS)

Wang, R.; Wang, Q.; Zhao, N.; Yu, G.; He, N.

2017-12-01

Fine roots are the most distal roots that act as the primary belowground organs in acquiring limiting nutrients and water from the soil. However, limited by the inconsistency in definitions of fine roots and the different protocols among studies, knowledge of root system traits has, to date, still lagged far behind our understanding of above-ground traits. In particular, whether variation in fine root traits among the plant species along a single root economics spectrum and this underlying mechanism are still hotly debated. In this study, we sampled the first-order root using the standardized protocols, and measured six important root traits related to resource use strategies, from 181 plant species from subtropical to boreal forests. Base on this large dataset, we concluded that different phylogenetic and environmental factors affected on root thickness and nutrient, resulting in the decoupled pattern between them. Specifically, variation in species-level traits related to root thickness (including root diameter, RD and specific root length, SRL) was restricted by common ancestry and little plastic to the changing environments, whereas the large-scale variation in woody root nutrient was mainly controlled by environmental differences, especially soil variables. For community-level traits, mean annual temperature (MAT) mainly influenced the community-level root thickness through the direct effect of changes in plant species composition, while soil P had a positive influence effect on community-level root nitrogen concentration (CWM_RN), reflecting the strong influence of soil fertility on belowground root nutrient. The different environmental constraints and selective pressures acting between root thickness and nutrient traits allows for multiple ecological strategies to adapt to complex environmental conditions. In addition, strong relationships between community-level root traits and environmental variables, due to environmental filters, indicate that in contrast with individual species-level trait, community-aggregated root traits could be used to improve our ability to predict how the distribution of vegetation will change in response to a changing climate.

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

PubMed Central

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

2015-01-01

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

A trait based dynamic energy budget approach to explore emergent microalgal community structure

NASA Astrophysics Data System (ADS)

Cheng, Y.; Bouskill, N.; Karaoz, U.; Geng, H.; Lane, T.; Pett-Ridge, J.; Mayali, X.; Brodie, E.

2015-12-01

Microalgae play important roles in the global carbon budget. Phytoplankton, including microalgae, are responsible for around 50% of global primary production, and also hold promise as a viable renewable biofuel source. Research has been underway for decades to realize the full potential of algal biofuels at the commercial scale, however, uni-algal ponds are typically threatened by collapse due to microalgal grazing and parasite invasions. Recently, it has been proposed that functionally diverse microalgal-bacterial communities can achieve high biomass and/or lipid yields, and are more stable (less susceptible to invasion) than a monoculture. Similar positive diversity-productivity relationships have been observed in a wide range of ecosystem studies, but the purposeful maintenance of a diverse microbiome is less common in managed systems. In our work, a trait based dynamic energy budget model was developed to explore emergent microalgal community structure under various environmental (e.g. light, temperature, nutrient availability) conditions. The complex algal community can be reduced into functional groups (guilds). Each guild (algae or bacteria) is characterized by distinct physiological traits (e.g. nutrient requirement, growth rate, substrate affinity, lipid production) constrained by biochemical trade-offs. These trait values are derived from literature and information encoded in genomic data. Metabolism of the algae and the bacterial species (symbiotic or non-symbiotic) are described within a dynamic energy budget framework. The model offers a mechanistic framework to predict the optimal microalgal community assemblage towards high productivity and resistance to invasion under prevailing environmental conditions.

Different Statistical Approaches to Investigate Porcine Muscle Metabolome Profiles to Highlight New Biomarkers for Pork Quality Assessment

PubMed Central

Welzenbach, Julia; Neuhoff, Christiane; Looft, Christian; Schellander, Karl; Tholen, Ernst; Große-Brinkhaus, Christine

2016-01-01

The aim of this study was to elucidate the underlying biochemical processes to identify potential key molecules of meat quality traits drip loss, pH of meat 1 h post-mortem (pH1), pH in meat 24 h post-mortem (pH24) and meat color. An untargeted metabolomics approach detected the profiles of 393 annotated and 1,600 unknown metabolites in 97 Duroc × Pietrain pigs. Despite obvious differences regarding the statistical approaches, the four applied methods, namely correlation analysis, principal component analysis, weighted network analysis (WNA) and random forest regression (RFR), revealed mainly concordant results. Our findings lead to the conclusion that meat quality traits pH1, pH24 and color are strongly influenced by processes of post-mortem energy metabolism like glycolysis and pentose phosphate pathway, whereas drip loss is significantly associated with metabolites of lipid metabolism. In case of drip loss, RFR was the most suitable method to identify reliable biomarkers and to predict the phenotype based on metabolites. On the other hand, WNA provides the best parameters to investigate the metabolite interactions and to clarify the complex molecular background of meat quality traits. In summary, it was possible to attain findings on the interaction of meat quality traits and their underlying biochemical processes. The detected key metabolites might be better indicators of meat quality especially of drip loss than the measured phenotype itself and potentially might be used as bio indicators. PMID:26919205

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

PubMed

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

2018-02-02

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

Social parasitism and the molecular basis of phenotypic evolution.

PubMed

Cini, Alessandro; Patalano, Solenn; Segonds-Pichon, Anne; Busby, George B J; Cervo, Rita; Sumner, Seirian

2015-01-01

Contrasting phenotypes arise from similar genomes through a combination of losses, gains, co-option and modifications of inherited genomic material. Understanding the molecular basis of this phenotypic diversity is a fundamental challenge in modern evolutionary biology. Comparisons of the genes and their expression patterns underlying traits in closely related species offer an unrivaled opportunity to evaluate the extent to which genomic material is reorganized to produce novel traits. Advances in molecular methods now allow us to dissect the molecular machinery underlying phenotypic diversity in almost any organism, from single-celled entities to the most complex vertebrates. Here we discuss how comparisons of social parasites and their free-living hosts may provide unique insights into the molecular basis of phenotypic evolution. Social parasites evolve from a eusocial ancestor and are specialized to exploit the socially acquired resources of their closely-related eusocial host. Molecular comparisons of such species pairs can reveal how genomic material is re-organized in the loss of ancestral traits (i.e., of free-living traits in the parasites) and the gain of new ones (i.e., specialist traits required for a parasitic lifestyle). We define hypotheses on the molecular basis of phenotypes in the evolution of social parasitism and discuss their wider application in our understanding of the molecular basis of phenotypic diversity within the theoretical framework of phenotypic plasticity and shifting reaction norms. Currently there are no data available to test these hypotheses, and so we also provide some proof of concept data using the paper wasp social parasite/host system (Polistes sulcifer-Polistes dominula). This conceptual framework and first empirical data provide a spring-board for directing future genomic analyses on exploiting social parasites as a route to understanding the evolution of phenotypic specialization.

Identification of Genomic Regions Associated with Phenotypic Variation between Dog Breeds using Selection Mapping

PubMed Central

Derrien, Thomas; Axelsson, Erik; Rosengren Pielberg, Gerli; Sigurdsson, Snaevar; Fall, Tove; Seppälä, Eija H.; Hansen, Mark S. T.; Lawley, Cindy T.; Karlsson, Elinor K.; Bannasch, Danika; Vilà, Carles; Lohi, Hannes; Galibert, Francis; Fredholm, Merete; Häggström, Jens; Hedhammar, Åke; André, Catherine; Lindblad-Toh, Kerstin; Hitte, Christophe; Webster, Matthew T.

2011-01-01

The extraordinary phenotypic diversity of dog breeds has been sculpted by a unique population history accompanied by selection for novel and desirable traits. Here we perform a comprehensive analysis using multiple test statistics to identify regions under selection in 509 dogs from 46 diverse breeds using a newly developed high-density genotyping array consisting of >170,000 evenly spaced SNPs. We first identify 44 genomic regions exhibiting extreme differentiation across multiple breeds. Genetic variation in these regions correlates with variation in several phenotypic traits that vary between breeds, and we identify novel associations with both morphological and behavioral traits. We next scan the genome for signatures of selective sweeps in single breeds, characterized by long regions of reduced heterozygosity and fixation of extended haplotypes. These scans identify hundreds of regions, including 22 blocks of homozygosity longer than one megabase in certain breeds. Candidate selection loci are strongly enriched for developmental genes. We chose one highly differentiated region, associated with body size and ear morphology, and characterized it using high-throughput sequencing to provide a list of variants that may directly affect these traits. This study provides a catalogue of genomic regions showing extreme reduction in genetic variation or population differentiation in dogs, including many linked to phenotypic variation. The many blocks of reduced haplotype diversity observed across the genome in dog breeds are the result of both selection and genetic drift, but extended blocks of homozygosity on a megabase scale appear to be best explained by selection. Further elucidation of the variants under selection will help to uncover the genetic basis of complex traits and disease. PMID:22022279

Identification of genomic regions associated with phenotypic variation between dog breeds using selection mapping.

PubMed

Vaysse, Amaury; Ratnakumar, Abhirami; Derrien, Thomas; Axelsson, Erik; Rosengren Pielberg, Gerli; Sigurdsson, Snaevar; Fall, Tove; Seppälä, Eija H; Hansen, Mark S T; Lawley, Cindy T; Karlsson, Elinor K; Bannasch, Danika; Vilà, Carles; Lohi, Hannes; Galibert, Francis; Fredholm, Merete; Häggström, Jens; Hedhammar, Ake; André, Catherine; Lindblad-Toh, Kerstin; Hitte, Christophe; Webster, Matthew T

2011-10-01

The extraordinary phenotypic diversity of dog breeds has been sculpted by a unique population history accompanied by selection for novel and desirable traits. Here we perform a comprehensive analysis using multiple test statistics to identify regions under selection in 509 dogs from 46 diverse breeds using a newly developed high-density genotyping array consisting of >170,000 evenly spaced SNPs. We first identify 44 genomic regions exhibiting extreme differentiation across multiple breeds. Genetic variation in these regions correlates with variation in several phenotypic traits that vary between breeds, and we identify novel associations with both morphological and behavioral traits. We next scan the genome for signatures of selective sweeps in single breeds, characterized by long regions of reduced heterozygosity and fixation of extended haplotypes. These scans identify hundreds of regions, including 22 blocks of homozygosity longer than one megabase in certain breeds. Candidate selection loci are strongly enriched for developmental genes. We chose one highly differentiated region, associated with body size and ear morphology, and characterized it using high-throughput sequencing to provide a list of variants that may directly affect these traits. This study provides a catalogue of genomic regions showing extreme reduction in genetic variation or population differentiation in dogs, including many linked to phenotypic variation. The many blocks of reduced haplotype diversity observed across the genome in dog breeds are the result of both selection and genetic drift, but extended blocks of homozygosity on a megabase scale appear to be best explained by selection. Further elucidation of the variants under selection will help to uncover the genetic basis of complex traits and disease.

Social parasitism and the molecular basis of phenotypic evolution

PubMed Central

Cini, Alessandro; Patalano, Solenn; Segonds-Pichon, Anne; Busby, George B. J.; Cervo, Rita; Sumner, Seirian

2015-01-01

Contrasting phenotypes arise from similar genomes through a combination of losses, gains, co-option and modifications of inherited genomic material. Understanding the molecular basis of this phenotypic diversity is a fundamental challenge in modern evolutionary biology. Comparisons of the genes and their expression patterns underlying traits in closely related species offer an unrivaled opportunity to evaluate the extent to which genomic material is reorganized to produce novel traits. Advances in molecular methods now allow us to dissect the molecular machinery underlying phenotypic diversity in almost any organism, from single-celled entities to the most complex vertebrates. Here we discuss how comparisons of social parasites and their free-living hosts may provide unique insights into the molecular basis of phenotypic evolution. Social parasites evolve from a eusocial ancestor and are specialized to exploit the socially acquired resources of their closely-related eusocial host. Molecular comparisons of such species pairs can reveal how genomic material is re-organized in the loss of ancestral traits (i.e., of free-living traits in the parasites) and the gain of new ones (i.e., specialist traits required for a parasitic lifestyle). We define hypotheses on the molecular basis of phenotypes in the evolution of social parasitism and discuss their wider application in our understanding of the molecular basis of phenotypic diversity within the theoretical framework of phenotypic plasticity and shifting reaction norms. Currently there are no data available to test these hypotheses, and so we also provide some proof of concept data using the paper wasp social parasite/host system (Polistes sulcifer—Polistes dominula). This conceptual framework and first empirical data provide a spring-board for directing future genomic analyses on exploiting social parasites as a route to understanding the evolution of phenotypic specialization. PMID:25741361

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

PubMed

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

2017-09-06

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

Maternal age generates phenotypic variation in C. elegans

PubMed Central

Hidalgo-Carcedo, Cristina; Lehner, Ben

2017-01-01

Genetically identical individuals growing in the same environment often show substantial phenotypic variation within populations of organisms as diverse as bacteria1, nematodes2, rodents3 and humans4. With some exceptions5, the causes are poorly understood. We show here that isogenic Caenorhabditis elegans nematodes vary in their size at hatching, speed of development, growth rate, starvation resistance, fecundity, and also in the rate of development of their germline relative to that of somatic tissues. Surprisingly, we show that the primary cause of this variation is the age of an individual’s mother, with young mothers producing progeny impaired for many traits. We identify age-dependent changes in maternal provisioning of a lipoprotein complex (vitellogenin) to embryos as the molecular mechanism underlying variation in multiple traits throughout the life of an animal. The production of sub-optimal progeny by young mothers likely reflects a trade-off between the competing fitness traits of a short generation time and progeny survival and fecundity. PMID:29186117

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

The genetic architecture of growth and fillet traits in farmed Atlantic salmon (Salmo salar).

PubMed

Tsai, Hsin Yuan; Hamilton, Alastair; Guy, Derrick R; Tinch, Alan E; Bishop, Stephen C; Houston, Ross D

2015-05-19

Performance and quality traits such as harvest weight, fillet weight and flesh color are of economic importance to the Atlantic salmon aquaculture industry. The genetic factors underlying these traits are of scientific and commercial interest. However, such traits are typically polygenic in nature, with the number and size of QTL likely to vary between studies and populations. The aim of this study was to investigate the genetic basis of several growth and fillet traits measured at harvest in a large farmed salmon population by using SNP markers. Due to the marked heterochiasmy in salmonids, an efficient two-stage mapping approach was applied whereby QTL were detected using a sire-based linkage analysis, a sparse SNP marker map and exploiting low rates of recombination, while a subsequent dam-based analysis focused on the significant chromosomes with a denser map to confirm QTL and estimate their position. The harvest traits all showed significant heritability, ranging from 0.05 for fillet yield up to 0.53 for the weight traits. In the sire-based analysis, 1695 offspring with trait records and their 20 sires were successfully genotyped for the SNPs on the sparse map. Chromosomes 13, 18, 19 and 20 were shown to harbor genome-wide significant QTL affecting several growth-related traits. The QTL on chr. 13, 18 and 20 were detected in the dam-based analysis using 512 offspring from 10 dams and explained approximately 6-7 % of the within-family variation in these traits. We have detected several QTL affecting economically important complex traits in a commercial salmon population. Overall, the results suggest that the traits are relatively polygenic and that QTL tend to be pleiotropic (affecting the weight of several components of the harvested fish). Comparison of QTL regions across studies suggests that harvest trait QTL tend to be relatively population-specific. Therefore, the application of marker or genomic selection for improvement in these traits is likely to be most effective when the discovery population is closely related to the selection candidates (e.g. within-family genomic selection).

A multilevel trait-based approach to the ecological performance of Microcystis aeruginosa complex from headwaters to the ocean.

PubMed

Kruk, Carla; Segura, Angel M; Nogueira, Lucía; Alcántara, Ignacio; Calliari, Danilo; Martínez de la Escalera, Gabriela; Carballo, Carmela; Cabrera, Carolina; Sarthou, Florencia; Scavone, Paola; Piccini, Claudia

2017-12-01

The Microcystis aeruginosa complex (MAC) clusters cosmopolitan and conspicuous harmful bloom-forming cyanobacteria able to produce cyanotoxins. It is hypothesized that low temperatures and brackish salinities are the main barriers to MAC proliferation. Here, patterns at multiple levels of organization irrespective of taxonomic identity (i.e. a trait-based approach) were analyzed. MAC responses from the intracellular (e.g. respiratory activity) to the ecosystem level (e.g. blooms) were evaluated in wide environmental gradients. Experimental results on buoyancy and respiratory activity in response to increased salinity (0-35) and a literature review of maximum growth rates under different temperatures and salinities were combined with field sampling from headwaters (800km upstream) to the marine end of the Rio de la Plata estuary (Uruguay-South America). Salinity and temperature were the major variables affecting MAC responses. Experimentally, freshwater MAC cells remained active for 24h in brackish waters (salinity=15) while colonies increased their flotation velocity. At the population level, maximum growth rate decreased with salinity and presented a unimodal exponential response with temperature, showing an optimum at 27.5°C and a rapid decrease thereafter. At the community and ecosystem levels, MAC occurred from fresh to marine waters (salinity 30) with a sustained relative increase of large mucilaginous colonies biovolume with respect to individual cells. Similarly, total biomass and, specific and morphological richness decreased with salinity while blooms were only detected in freshwater both at high (33°C) and low (11°C) temperatures. In brackish waters, large mucilaginous colonies presented advantages under osmotic restrictive conditions. These traits values have also been associated with higher toxicity potential. This suggest salinity or low temperatures would not represent effective barriers for the survival and transport of potentially toxic MAC under likely near future scenarios of increasing human impacts (i.e. eutrophication, dam construction and climate change). Copyright © 2017 Elsevier B.V. All rights reserved.

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

From genotype to phenotype: unraveling the complexities of cold adaptation in forest trees

Treesearch

Glenn T. Howe; Sally N. Aitken; David B. Neale; Kathleen D. Jermstad; Nicholas C. Wheeler; Tony H.H Chen

2003-01-01

Adaptation to winter cold in temperate and boreal trees involves complex genetic, physiological, and developmental processes. Genecological studies demonstrate the existence of steep genetic clines for cold adaptation traits in relation to environmental (mostly temperature related) gradients. Population differentiation is generally stronger for cold adaptation traits...

Evolution of ultraviolet vision in the largest avian radiation - the passerines.

PubMed

Ödeen, Anders; Håstad, Olle; Alström, Per

2011-10-24

Interspecific variation in avian colour vision falls into two discrete classes: violet sensitive (VS) and ultraviolet sensitive (UVS). They are characterised by the spectral sensitivity of the most shortwave sensitive of the four single cones, the SWS1, which is seemingly under direct control of as little as one amino acid substitution in the cone opsin protein. Changes in spectral sensitivity of the SWS1 are ecologically important, as they affect the abilities of birds to accurately assess potential mates, find food and minimise visibility of social signals to predators. Still, available data have indicated that shifts between classes are rare, with only four to five independent acquisitions of UV sensitivity in avian evolution. We have classified a large sample of passeriform species as VS or UVS from genomic DNA and mapped the evolution of this character on a passerine phylogeny inferred from published molecular sequence data. Sequencing a small gene fragment has allowed us to trace the trait changing from one stable state to another through the radiation of the passeriform birds. Their ancestor is hypothesised to be UVS. In the subsequent radiation, colour vision changed between UVS and VS at least eight times. The phylogenetic distribution of SWS1 cone opsin types in Passeriformes reveals a much higher degree of complexity in avian colour vision evolution than what was previously indicated from the limited data available. Clades with variation in the colour vision system are nested among clades with a seemingly stable VS or UVS state, providing a rare opportunity to understand how an ecologically important trait under simple genetic control may co-evolve with, and be stabilised by, associated traits in a character complex.

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

PubMed

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

2012-08-01

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

Accounting for Genotype-by-Environment Interactions and Residual Genetic Variation in Genomic Selection for Water-Soluble Carbohydrate Concentration in Wheat.

PubMed

Ovenden, Ben; Milgate, Andrew; Wade, Len J; Rebetzke, Greg J; Holland, James B

2018-05-31

Abiotic stress tolerance traits are often complex and recalcitrant targets for conventional breeding improvement in many crop species. This study evaluated the potential of genomic selection to predict water-soluble carbohydrate concentration (WSCC), an important drought tolerance trait, in wheat under field conditions. A panel of 358 varieties and breeding lines constrained for maturity was evaluated under rainfed and irrigated treatments across two locations and two years. Whole-genome marker profiles and factor analytic mixed models were used to generate genomic estimated breeding values (GEBVs) for specific environments and environment groups. Additive genetic variance was smaller than residual genetic variance for WSCC, such that genotypic values were dominated by residual genetic effects rather than additive breeding values. As a result, GEBVs were not accurate predictors of genotypic values of the extant lines, but GEBVs should be reliable selection criteria to choose parents for intermating to produce new populations. The accuracy of GEBVs for untested lines was sufficient to increase predicted genetic gain from genomic selection per unit time compared to phenotypic selection if the breeding cycle is reduced by half by the use of GEBVs in off-season generations. Further, genomic prediction accuracy depended on having phenotypic data from environments with strong correlations with target production environments to build prediction models. By combining high-density marker genotypes, stress-managed field evaluations, and mixed models that model simultaneously covariances among genotypes and covariances of complex trait performance between pairs of environments, we were able to train models with good accuracy to facilitate genetic gain from genomic selection. Copyright © 2018 Ovenden et al.

Comparative genome analysis of a thermotolerant Escherichia coli obtained by Genome Replication Engineering Assisted Continuous Evolution (GREACE) and its parent strain provides new understanding of microbial heat tolerance.

PubMed

Luan, Guodong; Bao, Guanhui; Lin, Zhao; Li, Yang; Chen, Zugen; Li, Yin; Cai, Zhen

2015-12-25

Heat tolerance of microbes is of great importance for efficient biorefinery and bioconversion. However, engineering and understanding of microbial heat tolerance are difficult and insufficient because it is a complex physiological trait which probably correlates with all gene functions, genetic regulations, and cellular metabolisms and activities. In this work, a novel strain engineering approach named Genome Replication Engineering Assisted Continuous Evolution (GREACE) was employed to improve the heat tolerance of Escherichia coli. When the E. coli strain carrying a mutator was cultivated under gradually increasing temperature, genome-wide mutations were continuously generated during genome replication and the mutated strains with improved thermotolerance were autonomously selected. A thermotolerant strain HR50 capable of growing at 50°C on LB agar plate was obtained within two months, demonstrating the efficiency of GREACE in improving such a complex physiological trait. To understand the improved heat tolerance, genomes of HR50 and its wildtype strain DH5α were sequenced. Evenly distributed 361 mutations covering all mutation types were found in HR50. Closed material transportations, loose genome conformation, and possibly altered cell wall structure and transcription pattern were the main differences of HR50 compared with DH5α, which were speculated to be responsible for the improved heat tolerance. This work not only expanding our understanding of microbial heat tolerance, but also emphasizing that the in vivo continuous genome mutagenesis method, GREACE, is efficient in improving microbial complex physiological trait. Copyright © 2015 Elsevier B.V. All rights reserved.

Modelling the multidimensional niche by linking functional traits to competitive performance

PubMed Central

Maynard, Daniel S.; Leonard, Kenneth E.; Drake, John M.; Hall, David W.; Crowther, Thomas W.; Bradford, Mark A.

2015-01-01

Linking competitive outcomes to environmental conditions is necessary for understanding species' distributions and responses to environmental change. Despite this importance, generalizable approaches for predicting competitive outcomes across abiotic gradients are lacking, driven largely by the highly complex and context-dependent nature of biotic interactions. Here, we present and empirically test a novel niche model that uses functional traits to model the niche space of organisms and predict competitive outcomes of co-occurring populations across multiple resource gradients. The model makes no assumptions about the underlying mode of competition and instead applies to those settings where relative competitive ability across environments correlates with a quantifiable performance metric. To test the model, a series of controlled microcosm experiments were conducted using genetically related strains of a widespread microbe. The model identified trait microevolution and performance differences among strains, with the predicted competitive ability of each organism mapped across a two-dimensional carbon and nitrogen resource space. Areas of coexistence and competitive dominance between strains were identified, and the predicted competitive outcomes were validated in approximately 95% of the pairings. By linking trait variation to competitive ability, our work demonstrates a generalizable approach for predicting and modelling competitive outcomes across changing environmental contexts. PMID:26136444

Trait anxiety affects decision-making differently in healthy men and women: towards gender-specific endophenotypes of anxiety.

PubMed

de Visser, L; van der Knaap, L J; van de Loo, A J A E; van der Weerd, C M M; Ohl, F; van den Bos, R

2010-05-01

Excessive levels of trait anxiety are a risk factor for psychiatric conditions, including anxiety disorders and substance abuse. High trait anxiety has been associated with altered cognitive functioning, in particular with an attentional bias towards aversive stimuli. Decision-making is a crucial aspect of cognitive functioning that relies on the correct processing and control of emotional stimuli. Interestingly, anxiety and decision-making share underlying neural substrates, involving cortico-limbic pathways, including the amygdala, striatum and medial and dorsolateral prefrontal cortices. In the present study, we investigated the relationship between trait anxiety, measured by the State-Trait Anxiety Inventory, and complex decision-making, measured by the Iowa Gambling Task, in healthy male and female volunteers. The main focus of this study was the inclusion of gender as a discriminative factor. Indeed, we found distinct gender-specific effects of trait anxiety: in men, both low and high anxiety groups showed impaired decision-making compared to medium anxiety individuals, whereas in women only high anxiety individuals performed poorly. Furthermore, anxiety affected decision-making in men early in the task, i.e. the exploration phase, as opposed to an effect on performance in women during the second part of the test, i.e. the exploitation phase. These findings were related to different profiles of trait anxiety in men and women, and were independent of performance in the Wisconsin Card Sorting Test and cortisol levels. Our data show gender-specific effects of trait anxiety on emotional decision-making. We suggest gender-specific endophenotypes of anxiety to exist, that differentially affect cognitive functioning. 2010 Elsevier Ltd. All rights reserved.

Genomic architecture of habitat-related divergence and signature of directional selection in the body shapes of Gnathopogon fishes.

PubMed

Kakioka, Ryo; Kokita, Tomoyuki; Kumada, Hiroki; Watanabe, Katsutoshi; Okuda, Noboru

2015-08-01

Evolution of ecomorphologically relevant traits such as body shapes is important to colonize and persist in a novel environment. Habitat-related adaptive divergence of these traits is therefore common among animals. We studied the genomic architecture of habitat-related divergence in the body shape of Gnathopogon fishes, a novel example of lake-stream ecomorphological divergence, and tested for the action of directional selection on body shape differentiation. Compared to stream-dwelling Gnathopogon elongatus, the sister species Gnathopogon caerulescens, exclusively inhabiting a large ancient lake, had an elongated body, increased proportion of the caudal region and small head, which would be advantageous in the limnetic environment. Using an F2 interspecific cross between the two Gnathopogon species (195 individuals), quantitative trait locus (QTL) analysis with geometric morphometric quantification of body shape and restriction-site associated DNA sequencing-derived markers (1622 loci) identified 26 significant QTLs associated with the interspecific differences of body shape-related traits. These QTLs had small to moderate effects, supporting polygenic inheritance of the body shape-related traits. Each QTL was mostly located on different genomic regions, while colocalized QTLs were detected for some ecomorphologically relevant traits that are proxy of body and caudal peduncle depths, suggesting different degree of modularity among traits. The directions of the body shape QTLs were mostly consistent with the interspecific difference, and QTL sign test suggested a genetic signature of directional selection in the body shape divergence. Thus, we successfully elucidated the genomic architecture underlying the adaptive changes of the quantitative and complex morphological trait in a novel system. © 2015 John Wiley & Sons Ltd.

Modifying agricultural crops for improved nutrition.

PubMed

McGloughlin, Martina Newell

2010-11-30

The first generation of biotechnology products commercialized were crops focusing largely on input agronomic traits whose value was often opaque to consumers. The coming generations of crop plants can be grouped into four broad areas each presenting what, on the surface, may appear as unique challenges and opportunities. The present and future focus is on continuing improvement of agronomic traits such as yield and abiotic stress resistance in addition to the biotic stress tolerance of the present generation; crop plants as biomass feedstocks for biofuels and "bio-synthetics"; value-added output traits such as improved nutrition and food functionality; and plants as production factories for therapeutics and industrial products. From a consumer perspective, the focus on value-added traits, especially improved nutrition, is undoubtedly one of the areas of greatest interest. From a basic nutrition perspective, there is a clear dichotomy in demonstrated need between different regions and socioeconomic groups, the starkest being inappropriate consumption in the developed world and under-nourishment in Less Developed Countries (LDCs). Dramatic increases in the occurrence of obesity and related ailments in affluent regions are in sharp contrast to chronic malnutrition in many LDCs. Both problems require a modified food supply, and the tools of biotechnology have a part to play. Developing plants with improved traits involves overcoming a variety of technical, regulatory and indeed perception hurdles inherent in perceived and real challenges of complex traits modifications. Continuing improvements in molecular and genomic technologies are contributing to the acceleration of product development to produce plants with the appropriate quality traits for the different regions and needs. Crops with improved traits in the pipeline, the evolving technologies and the opportunities and challenges that lie ahead are covered. Copyright © 2010. Published by Elsevier B.V.

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

PubMed

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

2016-10-01

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

Exercise and diet affect quantitative trait loci for body weight and composition traits in an advanced intercross population of mice

PubMed Central

Kelly, Scott A.; Hua, Kunjie; Pomp, Daniel

2012-01-01

Driven by the recent obesity epidemic, interest in understanding the complex genetic and environmental basis of body weight and composition is great. We investigated this by searching for quantitative trait loci (QTLs) affecting a number of weight and adiposity traits in a G10 advanced intercross population produced from crosses of mice in inbred strain C57BL/6J with those in a strain selected for high voluntary wheel running. The mice in this population were fed either a high-fat or a control diet throughout the study and also measured for four exercise traits prior to death, allowing us to test for pre- and postexercise QTLs as well as QTL-by-diet and QTL-by-exercise interactions. Our genome scan uncovered a number of QTLs, of which 40% replicated QTLs previously found for similar traits in an earlier (G4) generation. For those replicated QTLs, the confidence intervals were reduced from an average of 19 Mb in the G4 to 8 Mb in the G10. Four QTLs on chromosomes 3, 8, 13, and 18 were especially prominent in affecting the percentage of fat in the mice. About of all QTLs showed interactions with diet, exercise, or both, their genotypic effects on the traits showing a variety of patterns depending on the diet or level of exercise. It was concluded that the indirect effects of these QTLs provide an underlying genetic basis for the considerable variability in weight or fat loss typically found among individuals on the same diet and/or exercise regimen. PMID:23048196

Infant social attention: an endophenotype of ASD-related traits?

PubMed

Jones, Emily J H; Venema, Kaitlin; Earl, Rachel K; Lowy, Rachel; Webb, Sara J

2017-03-01

As a neurodevelopmental disorder, symptoms of ASD likely emerge from a complex interaction between preexisting genetic vulnerabilities and the child's environment. One way to understand causal paths to ASD is to identify dimensional ASD-related traits that vary in the general population and that predispose individuals with other risk factors toward ASD. Moving beyond behavioral traits to explore underlying neurocognitive processes may further constrain the underlying genetics. Endophenotypes are quantitative, heritable, trait-related differences that are generally assessed with laboratory-based methods, can be identified in the general population, and may be more closely tied to particular causal chains that have a more restricted set of genetic roots. The most fruitful endophenotypes may be those observed in infancy, prior to the emergence of behavioral symptoms that they are hypothesized to cause. Social motivation is an ASD-related trait that is highly heritable. In this study, we investigate whether infant endophenotypes of social attention relate to familial risk for lower social motivation in the general population. We examined whether infant social attention (measured using habituation, EEG power, and event-related potential tasks previously used in infants/toddlers with ASD) varies quantitatively with parental social motivation in 117 six-month-old and 106 twelve-month-old typically developing infants assessed cross-sectionally. To assess heritable aspects of social motivation, primary caregiver biological parents completed two self-report measures of social avoidance and discomfort that have shown high heritability in previous work. Parents with higher social discomfort and avoidance had infants who showed shorter looks to faces but not objects; reduced theta power during naturalistic social attention; and smaller P400 responses to faces versus objects. Early reductions in social attention are continuously related to lower parental social motivation. Alterations in social attention may be infant endophenotypes of social motivation traits related to ASD. © 2016 Association for Child and Adolescent Mental Health.

Infant social attention: an endophenotype of ASD-related traits?

PubMed Central

Jones, Emily J.H.; Venema, Kaitlin; Earl, Rachel K.; Lowy, Rachel; Webb, Sara J.

2018-01-01

Background As a neurodevelopmental disorder, symptoms of ASD likely emerge from a complex interaction between preexisting genetic vulnerabilities and the child’s environment. One way to understand causal paths to ASD is to identify dimensional ASD-related traits that vary in the general population and that predispose individuals with other risk factors toward ASD. Moving beyond behavioral traits to explore underlying neurocognitive processes may further constrain the underlying genetics. Endophenotypes are quantitative, heritable, trait-related differences that are generally assessed with laboratory-based methods, can be identified in the general population, and may be more closely tied to particular causal chains that have a more restricted set of genetic roots. The most fruitful endophenotypes may be those observed in infancy, prior to the emergence of behavioral symptoms that they are hypothesized to cause. Social motivation is an ASD-related trait that is highly heritable. In this study, we investigate whether infant endophenotypes of social attention relate to familial risk for lower social motivation in the general population. Methods We examined whether infant social attention (measured using habituation, EEG power, and event-related potential tasks previously used in infants/toddlers with ASD) varies quantitatively with parental social motivation in 117 six-month-old and 106 twelve-month-old typically developing infants assessed cross-sectionally. To assess heritable aspects of social motivation, primary caregiver biological parents completed two self-report measures of social avoidance and discomfort that have shown high heritability in previous work. Results Parents with higher social discomfort and avoidance had infants who showed shorter looks to faces but not objects; reduced theta power during naturalistic social attention; and smaller P400 responses to faces versus objects. Conclusions Early reductions in social attention are continuously related to lower parental social motivation. Alterations in social attention may be infant endophenotypes of social motivation traits related to ASD. PMID:27861851

Machine Learning Biogeographic Processes from Biotic Patterns: A New Trait-Dependent Dispersal and Diversification Model with Model Choice By Simulation-Trained Discriminant Analysis.

PubMed

Sukumaran, Jeet; Economo, Evan P; Lacey Knowles, L

2016-05-01

Current statistical biogeographical analysis methods are limited in the ways ecology can be related to the processes of diversification and geographical range evolution, requiring conflation of geography and ecology, and/or assuming ecologies that are uniform across all lineages and invariant in time. This precludes the possibility of studying a broad class of macroevolutionary biogeographical theories that relate geographical and species histories through lineage-specific ecological and evolutionary dynamics, such as taxon cycle theory. Here we present a new model that generates phylogenies under a complex of superpositioned geographical range evolution, trait evolution, and diversification processes that can communicate with each other. We present a likelihood-free method of inference under our model using discriminant analysis of principal components of summary statistics calculated on phylogenies, with the discriminant functions trained on data generated by simulations under our model. This approach of model selection by classification of empirical data with respect to data generated under training models is shown to be efficient, robust, and performs well over a broad range of parameter space defined by the relative rates of dispersal, trait evolution, and diversification processes. We apply our method to a case study of the taxon cycle, that is testing for habitat and trophic level constraints in the dispersal regimes of the Wallacean avifaunal radiation. ©The Author(s) 2015. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Does structural complexity determine the morphology of assemblages? An experimental test on three continents.

PubMed

Gibb, Heloise; Parr, Catherine L

2013-01-01

Understanding how species will respond to global change depends on our ability to distinguish generalities from idiosyncrasies. For diverse, but poorly known taxa, such as insects, species traits may provide a short-cut to predicting species turnover. We tested whether ant traits respond consistently to habitat complexity across geographically independent ant assemblages, using an experimental approach and baits. We repeated our study in six paired simple and complex habitats on three continents with distinct ant faunas. We also compared traits amongst ants with different foraging strategies. We hypothesised that ants would be larger, broader, have longer legs and more dorsally positioned eyes in simpler habitats. In agreement with predictions, ants had longer femurs and dorsally positioned eyes in simple habitats. This pattern was most pronounced for ants that discovered resources. Body size and pronotum width responded as predicted for experimental treatments, but were inconsistent across continents. Monopolising ants were smaller, with shorter femurs than those that occupied or discovered resources. Consistent responses for several traits suggest that many, but not all, aspects of morphology respond predictably to habitat complexity, and that foraging strategy is linked with morphology. Some traits thus have the potential to be used to predict the direction of species turnover, changes in foraging strategy and, potentially, evolution in response to changes in habitat structure.

Biodiversity in a complex world: consolidation and progress in functional biodiversity research.

PubMed

Hillebrand, Helmut; Matthiessen, Birte

2009-12-01

The global decline of biodiversity caused by human domination of ecosystems worldwide is supposed to alter important process rates and state variables in these ecosystems. However, there is considerable debate on the prevalence and importance of biodiversity effects on ecosystem function (BDEF). Here, we argue that much of the debate stems from two major shortcomings. First, most studies do not directly link the traits leading to increased or decreased function to the traits needed for species coexistence and dominance. We argue that implementing a trait-based approach and broadening the perception of diversity to include trait dissimilarity or trait divergence will result in more realistic predictions on the consequences of altered biodiversity. Second, the empirical and theoretical studies do not reflect the complexity of natural ecosystems, which makes it difficult to transfer the results to natural situations of species loss. We review how different aspects of complexity (trophic structure, multifunctionality, spatial or temporal heterogeneity, and spatial population dynamics) alter our perception of BDEF. We propose future research avenues concisely testing whether acknowledging this complexity will strengthen the observed biodiversity effects. Finally, we propose that a major future task is to disentangle biodiversity effects on ecosystem function from direct changes in function due to human alterations of abiotic constraints.

Effects of larvicidal and larval nutritional stresses on Anopheles gambiae development, survival and competence for Plasmodium falciparum.

PubMed

Vantaux, Amélie; Ouattarra, Issiaka; Lefèvre, Thierry; Dabiré, Kounbobr Roch

2016-04-23

Many studies have shown that the environment in which larvae develop can influence adult characteristics with consequences for the transmission of pathogens. We investigated how two environmental stresses (larviciding and nutritional stress) interact to affect Anopheles gambiae (previously An. gambiae S molecular form) life history traits and its susceptibility for field isolates of its natural malaria agent Plasmodium falciparum. Larvae were reared in the presence or not of a sub-lethal concentration of larvicide and under a high and low food regimen. Development time, individual size, adult survival and competence for P. falciparum were assessed. Individuals under low food regimen took more time to develop, had a lower development success and were smaller while there was no main effect of larvicide exposure on these traits. However, larvicide exposure impacted individual size in interaction with nutritional stress. Female survival was affected by the interaction between gametocytemia, parasite exposure and larval diet, as well as the interaction between gametocytemia, parasite exposure and larvicidal stress, and the interaction between gametocytemia, larvicidal exposure and larval diet. Among the 951 females dissected 7 days post-infection, 559 (58.78%) harboured parasites. Parasite prevalence was significantly affected by the interaction between larvicidal stress and larval diet. Indeed, females under low food regimen had a higher prevalence than females under high food regimen and this difference was greater under larvicidal stress. The two stresses did not impact parasite intensity. We found that larval nutritional and larvicidal stresses affect mosquito life history traits in complex ways, which could greatly affect P. falciparum transmission. Further studies combining field-based trials on larvicide use and mosquito experimental infections would give a more accurate understanding of the effects of this vector control tool on malaria transmission.

Sunflower Hybrid Breeding: From Markers to Genomic Selection

PubMed Central

Dimitrijevic, Aleksandra; Horn, Renate

2018-01-01

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

Using a system of differential equations that models cattle growth to uncover the genetic basis of complex traits.

PubMed

Freua, Mateus Castelani; Santana, Miguel Henrique de Almeida; Ventura, Ricardo Vieira; Tedeschi, Luis Orlindo; Ferraz, José Bento Sterman

2017-08-01

The interplay between dynamic models of biological systems and genomics is based on the assumption that genetic variation of the complex trait (i.e., outcome of model behavior) arises from component traits (i.e., model parameters) in lower hierarchical levels. In order to provide a proof of concept of this statement for a cattle growth model, we ask whether model parameters map genomic regions that harbor quantitative trait loci (QTLs) already described for the complex trait. We conducted a genome-wide association study (GWAS) with a Bayesian hierarchical LASSO method in two parameters of the Davis Growth Model, a system of three ordinary differential equations describing DNA accretion, protein synthesis and degradation, and fat synthesis. Phenotypic and genotypic data were available for 893 Nellore (Bos indicus) cattle. Computed values for parameter k 1 (DNA accretion rate) ranged from 0.005 ± 0.003 and for α (constant for energy for maintenance requirement) 0.134 ± 0.024. The expected biological interpretation of the parameters is confirmed by QTLs mapped for k 1 and α. QTLs within genomic regions mapped for k 1 are expected to be correlated with the DNA pool: body size and weight. Single nucleotide polymorphisms (SNPs) which were significant for α mapped QTLs that had already been associated with residual feed intake, feed conversion ratio, average daily gain (ADG), body weight, and also dry matter intake. SNPs identified for k 1 were able to additionally explain 2.2% of the phenotypic variability of the complex ADG, even when SNPs for k 1 did not match the genomic regions associated with ADG. Although improvements are needed, our findings suggest that genomic analysis on component traits may help to uncover the genetic basis of more complex traits, particularly when lower biological hierarchies are mechanistically described by mathematical simulation models.

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 ...

Nested association mapping for dissecting complex traits using Peanut 58K SNP array

USDA-ARS?s Scientific Manuscript database

Genome-wide association studies (GWAS) and linkage mapping have been the two most predominant strategies to dissect complex traits, but are limited by the occurrence of false positives reported for GWAS, and low resolution in the case of linkage analysis. This has led to the development of a joint a...

The genetic architecture of a complex ecological trait: host plant use in the specialist moth, HELIOTHIS SUBFLEXA

USDA-ARS?s Scientific Manuscript database

The study of the genetic basis of ecological adaptation remains in its infancy, and most studies have focused on phenotypically simple traits. Host plant use by herbivorous insects is phenotypically complex. While research has illuminated the evolutionary determinants of host use, knowledge of its...

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 ...

Association analysis of three diverse rice (Oryza sativa L.) germplasm collections for loci regulating grain quality traits

USDA-ARS?s Scientific Manuscript database

In rice (Oryza sativa L.), end-use/cooking quality is vital for producers and millions of consumers worldwide. Grain quality is a complex trait with interacting genetic and environmental factors. Deciphering the complex genetic architecture associated with grain quality, will provide vital informati...

Handling Complexity in Animal and Plant Science Research-From Single to Functional Traits: Are We There Yet?

PubMed

Roberts, Jessica; Power, Aoife; Chandra, Shaneel; Chapman, James; Cozzolino, Daniel

2018-05-28

The current knowledge of the main factors governing livestock, crop and plant quality as well as yield in different species is incomplete. For example, this can be evidenced by the persistence of benchmark crop varieties for many decades in spite of the gains achieved over the same period. In recent years, it has been demonstrated that molecular breeding based on DNA markers has led to advances in breeding (animal and crops). However, these advances are not in the way that it was anticipated initially by the researcher in the field. According to several scientists, one of the main reasons for this was related to the evidence that complex target traits such as grain yield, composition or nutritional quality depend on multiple factors in addition to genetics. Therefore, some questions need to be asked: are the current approaches in molecular genetics the most appropriate to deal with complex traits such as yield or quality? Are the current tools for phenotyping complex traits enough to differentiate among genotypes? Do we need to change the way that data is collected and analysed?

Alleles versus mutations: Understanding the evolution of genetic architecture requires a molecular perspective on allelic origins.

PubMed

Remington, David L

2015-12-01

Perspectives on the role of large-effect quantitative trait loci (QTL) in the evolution of complex traits have shifted back and forth over the past few decades. Different sets of studies have produced contradictory insights on the evolution of genetic architecture. I argue that much of the confusion results from a failure to distinguish mutational and allelic effects, a limitation of using the Fisherian model of adaptive evolution as the lens through which the evolution of adaptive variation is examined. A molecular-based perspective reveals that allelic differences can involve the cumulative effects of many mutations plus intragenic recombination, a model that is supported by extensive empirical evidence. I discuss how different selection regimes could produce very different architectures of allelic effects under a molecular-based model, which may explain conflicting insights on genetic architecture from studies of variation within populations versus between divergently selected populations. I address shortcomings of genome-wide association study (GWAS) practices in light of more suitable models of allelic evolution, and suggest alternate GWAS strategies to generate more valid inferences about genetic architecture. Finally, I discuss how adopting more suitable models of allelic evolution could help redirect research on complex trait evolution toward addressing more meaningful questions in evolutionary biology. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

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

PubMed

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

2010-04-01

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

Natural variations in OsγTMT contribute to diversity of the α-tocopherol content in rice.

PubMed

Wang, Xiao-Qiang; Yoon, Min-Young; He, Qiang; Kim, Tae-Sung; Tong, Wei; Choi, Bu-Woong; Lee, Young-Sang; Park, Yong-Jin

2015-12-01

Tocopherols and tocotrienols, collectively known as tocochromanols, are lipid-soluble molecules that belong to the group of vitamin E compounds. Among them, α-tocopherol (αΤ) is one of the antioxidants with diverse functions and benefits for humans and animals. Thus, understanding the genetic basis of these traits would be valuable to improve nutritional quality by breeding in rice. Genome-wide association study (GWAS) has emerged as a powerful strategy for identifying genes or quantitative trait loci (QTL) underlying complex traits in plants. To discover the genes or QTLs underlying the naturally occurring variations of αΤ content in rice, we performed GWAS using 1.44 million high-quality single-nucleotide polymorphisms acquired from re-sequencing of 137 accessions from a diverse rice core collection. Thirteen candidate genes were found across 2-year phenotypic data, among which gamma-tocopherol methyltransferase (OsγTMT) was identified as the major factor responsible for the αΤ content among rice accessions. Nucleotide variations in the coding region of OsγTMT were significantly associated with the αΤ content variations, while nucleotide polymorphisms in the promoter region of OsγTMT also could partly demonstrate the correlation with αΤ content variations, according to our RNA expression analyses. This study provides useful information for genetic factors underlying αΤ content variations in rice, which will significantly contribute the research on αΤ biosynthesis mechanisms and αΤ improvement of rice.

Physiological mechanisms contributing to the QTL-combination effects on improved performance of IR64 rice NILs under drought

PubMed Central

Henry, Amelia; Swamy, B. P. Mallikarjuna; Dixit, Shalabh; Torres, Rolando D.; Batoto, Tristram C.; Manalili, Mervin; Anantha, M. S.; Mandal, N. P.; Kumar, Arvind

2015-01-01

Characterizing the physiological mechanisms behind major-effect drought-yield quantitative trait loci (QTLs) can provide an understanding of the function of the QTLs—as well as plant responses to drought in general. In this study, we characterized rice (Oryza sativa L.) genotypes with QTLs derived from drought-tolerant traditional variety AdaySel that were introgressed into drought-susceptible high-yielding variety IR64, one of the most popular megavarieties in South Asian rainfed lowland systems. Of the different combinations of the four QTLs evaluated, genotypes with two QTLs (qDTY 2.2 + qDTY 4.1) showed the greatest degree of improvement under drought compared with IR64 in terms of yield, canopy temperature, and normalized difference vegetation index (NDVI). Furthermore, qDTY 2.2 and qDTY 4.1 showed a potential for complementarity in that they were each most effective under different severities of drought stress. Multiple drought-response mechanisms were observed to be conferred in the genotypes with the two-QTL combination: higher root hydraulic conductivity and in some cases greater root growth at depth. As evidenced by multiple leaf water status and plant growth indicators, these traits affected transpiration but not transpiration efficiency or harvest index. The results from this study highlight the complex interactions among major-effect drought-yield QTLs and the drought-response traits they confer, and the need to evaluate the optimal combinations of QTLs that complement each other when present in a common genetic background. PMID:25680791

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.

Male pregnancy and the evolution of body segmentation in seahorses and pipefishes.

PubMed

Hoffman, Eric A; Mobley, Kenyon B; Jones, Adam G

2006-02-01

The evolution of complex traits, which are specified by the interplay of multiple genetic loci and environmental effects, is a topic of central importance in evolutionary biology. Here, we show that body and tail vertebral numbers in fishes of the pipefish and seahorse family (Syngnathidae) can serve as a model for studies of quantitative trait evolution. A quantitative genetic analysis of body and tail vertebrae from field-collected families of the Gulf pipefish, Syngnathus scovelli, shows that both traits exhibit significantly positive additive genetic variance, with heritabilities of 0.75 +/- 0.13 (mean +/- standard error) and 0.46 +/- 0.18, respectively. We do not find any evidence for either phenotypic or genetic correlations between the two traits. Pipefish are characterized by male pregnancy, and phylogenetic consideration of body proportions suggests that the position of eggs on the pregnant male's body may have contributed to the evolution of vertebral counts. In terms of numbers of vertebrae, tail-brooding males have longer tails for a given trunk size than do trunk-brooding males. Overall, these results suggest that vertebral counts in pipefish are heritable traits, capable of a response to selection, and they may have experienced an interesting history of selection due to the phenomenon of male pregnancy. Given that these traits vary among populations within species as well as among species, they appear to provide an excellent model for further research on complex trait evolution. Body segmentation may thus afford excellent opportunities for comparative study of homologous complex traits among disparate vertebrate taxa.

Autistic traits and social anxiety predict differential performance on social cognitive tasks in typically developing young adults

PubMed Central

Burk, Joshua A.; Fleckenstein, Katarina; Kozikowski, C. Teal

2018-01-01

The current work examined the unique contribution that autistic traits and social anxiety have on tasks examining attention and emotion processing. In Study 1, 119 typically-developing college students completed a flanker task assessing the control of attention to target faces and away from distracting faces during emotion identification. In Study 2, 208 typically-developing college students performed a visual search task which required identification of whether a series of 8 or 16 emotional faces depicted the same or different emotions. Participants with more self-reported autistic traits performed more slowly on the flanker task in Study 1 than those with fewer autistic traits when stimuli depicted complex emotions. In Study 2, participants higher in social anxiety performed less accurately on trials showing all complex faces; participants with autistic traits showed no differences. These studies suggest that traits related to autism and to social anxiety differentially impact social cognitive processing. PMID:29596523

Complex Genetics and the Etiology of Human Congenital Heart Disease

PubMed Central

Gelb, Bruce D.; Chung, Wendy K.

2014-01-01

Congenital heart disease (CHD) is the most common birth defect. Despite considerable advances in care, CHD remains a major contributor to newborn mortality and is associated with substantial morbidities and premature death. Genetic abnormalities appear to be the primary cause of CHD, but identifying precise defects has proven challenging, principally because CHD is a complex genetic trait. Mainly because of recent advances in genomic technology such as next-generation DNA sequencing, scientists have begun to identify the genetic variants underlying CHD. In this article, the roles of modifier genes, de novo mutations, copy number variants, common variants, and noncoding mutations in the pathogenesis of CHD are reviewed. PMID:24985128

Biological robustness.

PubMed

Kitano, Hiroaki

2004-11-01

Robustness is a ubiquitously observed property of biological systems. It is considered to be a fundamental feature of complex evolvable systems. It is attained by several underlying principles that are universal to both biological organisms and sophisticated engineering systems. Robustness facilitates evolvability and robust traits are often selected by evolution. Such a mutually beneficial process is made possible by specific architectural features observed in robust systems. But there are trade-offs between robustness, fragility, performance and resource demands, which explain system behaviour, including the patterns of failure. Insights into inherent properties of robust systems will provide us with a better understanding of complex diseases and a guiding principle for therapy design.

Chronic subjective dizziness: Analysis of underlying personality factors.

PubMed

Chiarella, G; Petrolo, C; Riccelli, R; Giofrè, L; Olivadese, G; Gioacchini, F M; Scarpa, A; Cassandro, E; Passamonti, L

2016-11-03

Chronic subjective dizziness (CSD) is characterized by persistent dizziness, unsteadiness, and hypersensitivity to one's own motion or exposure to complex visual stimuli. CSD may be triggered, in predisposed individuals with specific personality traits, by acute vestibular diseases. CSD is also thought to arise from failure to re-establish normal balance strategies after resolution of acute vestibular events which may be modulated by diathesis to develop anxiety and depression. To confirm the role of personality traits linked to anxiety and depression (i.e., neuroticism, introversion, low openness) as predisposing factors for CSD and to evaluate how individual differences in these personality traits are associated with CSD severity. We compared 19 CSD patients with 24 individuals who had suffered from periferal vestibular disorders (PVD) (i.e., Benign Paroxysmal Postural Vertigo or Vestibular Neuritis) but had not developed CSD as well as with 25 healthy controls (HC) in terms of personality traits, assessed via the NEO-PI-R questionnaire. CSD patients, relative to PVD patients and HCs, scored higher on the anxiety facet of neuroticism. Total neuroticism scores were also significantly associated with dizziness severity in CSD patients but not PVD patients. Pre-existing anxiety-related personality traits may promote and sustain the initial etiophatogenetic mechanisms linked with the development of CSD. Targeting anxiety-related mechanisms in CSD may be therefore a promising way to reduce the disability associated with CSD.

Allocation, morphology, physiology, architecture: the multiple facets of plant above- and below-ground responses to resource stress.

PubMed

Freschet, Grégoire T; Violle, Cyrille; Bourget, Malo Y; Scherer-Lorenzen, Michael; Fort, Florian

2018-06-01

Plants respond to resource stress by changing multiple aspects of their biomass allocation, morphology, physiology and architecture. To date, we lack an integrated view of the relative importance of these plastic responses in alleviating resource stress and of the consistency/variability of these responses among species. We subjected nine species (legumes, forbs and graminoids) to nitrogen and/or light shortages and measured 11 above-ground and below-ground trait adjustments critical in the alleviation of these stresses (plus several underlying traits). Nine traits out of 11 showed adjustments that improved plants' potential capacity to acquire the limiting resource at a given time. Above ground, aspects of plasticity in allocation, morphology, physiology and architecture all appeared important in improving light capture, whereas below ground, plasticity in allocation and physiology were most critical to improving nitrogen acquisition. Six traits out of 11 showed substantial heterogeneity in species plasticity, with little structuration of these differences within trait covariation syndromes. Such comprehensive assessment of the complex nature of phenotypic responses of plants to multiple stress factors, and the comparison of plant responses across multiple species, makes a clear case for the high (but largely overlooked) diversity of potential plastic responses of plants, and for the need to explore the potential rules structuring them. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

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

PubMed Central

Kujur, Alice; Bajaj, Deepak; Upadhyaya, Hari D.; Das, Shouvik; Ranjan, Rajeev; Shree, Tanima; Saxena, Maneesha S.; Badoni, Saurabh; Kumar, Vinod; Tripathi, Shailesh; Gowda, C.L.L.; Sharma, Shivali; Singh, Sube; Tyagi, Akhilesh K.; Parida, Swarup K.

2015-01-01

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

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

PubMed

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

2015-05-05

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

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

PubMed

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

2010-08-01

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

Individual Cell Based Traits Obtained by Scanning Flow-Cytometry Show Selection by Biotic and Abiotic Environmental Factors during a Phytoplankton Spring Bloom

PubMed Central

Pomati, Francesco; Kraft, Nathan J. B.; Posch, Thomas; Eugster, Bettina; Jokela, Jukka; Ibelings, Bas W.

2013-01-01

In ecology and evolution, the primary challenge in understanding the processes that shape biodiversity is to assess the relationship between the phenotypic traits of organisms and the environment. Here we tested for selection on physio-morphological traits measured by scanning flow-cytometry at the individual level in phytoplankton communities under a temporally changing biotic and abiotic environment. Our aim was to study how high-frequency temporal changes in the environment influence biodiversity dynamics in a natural community. We focused on a spring bloom in Lake Zurich (Switzerland), characterized by rapid changes in phytoplankton, water conditions, nutrients and grazing (mainly mediated by herbivore ciliates). We described bloom dynamics in terms of taxonomic and trait-based diversity and found that diversity dynamics of trait-based groups were more pronounced than those of identified phytoplankton taxa. We characterized the linkage between measured phytoplankton traits, abiotic environmental factors and abundance of the main grazers and observed weak but significant correlations between changing abiotic and biotic conditions and measured size-related and fluorescence-related traits. We tested for deviations in observed community-wide distributions of focal traits from random patterns and found evidence for both clustering and even spacing of traits, occurring sporadically over the time series. Patterns were consistent with environmental filtering and phenotypic divergence under herbivore pressure, respectively. Size-related traits showed significant even spacing during the peak of herbivore abundance, suggesting that morphology-related traits were under selection from grazing. Pigment distribution within cells and colonies appeared instead to be associated with acclimation to temperature and water chemistry. We found support for trade-offs among grazing resistance and environmental tolerance traits, as well as for substantial periods of dynamics in which our measured traits were not under selection. PMID:23951218

Individual cell based traits obtained by scanning flow-cytometry show selection by biotic and abiotic environmental factors during a phytoplankton spring bloom.

PubMed

Pomati, Francesco; Kraft, Nathan J B; Posch, Thomas; Eugster, Bettina; Jokela, Jukka; Ibelings, Bas W

2013-01-01

In ecology and evolution, the primary challenge in understanding the processes that shape biodiversity is to assess the relationship between the phenotypic traits of organisms and the environment. Here we tested for selection on physio-morphological traits measured by scanning flow-cytometry at the individual level in phytoplankton communities under a temporally changing biotic and abiotic environment. Our aim was to study how high-frequency temporal changes in the environment influence biodiversity dynamics in a natural community. We focused on a spring bloom in Lake Zurich (Switzerland), characterized by rapid changes in phytoplankton, water conditions, nutrients and grazing (mainly mediated by herbivore ciliates). We described bloom dynamics in terms of taxonomic and trait-based diversity and found that diversity dynamics of trait-based groups were more pronounced than those of identified phytoplankton taxa. We characterized the linkage between measured phytoplankton traits, abiotic environmental factors and abundance of the main grazers and observed weak but significant correlations between changing abiotic and biotic conditions and measured size-related and fluorescence-related traits. We tested for deviations in observed community-wide distributions of focal traits from random patterns and found evidence for both clustering and even spacing of traits, occurring sporadically over the time series. Patterns were consistent with environmental filtering and phenotypic divergence under herbivore pressure, respectively. Size-related traits showed significant even spacing during the peak of herbivore abundance, suggesting that morphology-related traits were under selection from grazing. Pigment distribution within cells and colonies appeared instead to be associated with acclimation to temperature and water chemistry. We found support for trade-offs among grazing resistance and environmental tolerance traits, as well as for substantial periods of dynamics in which our measured traits were not under selection.

Belowground plant development measured with magnetic resonance imaging (MRI): exploiting the potential for non-invasive trait quantification using sugar beet as a proxy

PubMed Central

Metzner, Ralf; van Dusschoten, Dagmar; Bühler, Jonas; Schurr, Ulrich; Jahnke, Siegfried

2014-01-01

Both structural and functional properties of belowground plant organs are critical for the development and yield of plants but, compared to the shoot, much more difficult to observe due to soil opacity. Many processes concerning the belowground plant performance are not fully understood, in particular spatial and temporal dynamics and their interrelation with environmental factors. We used Magnetic Resonance Imaging (MRI) as a noninvasive method to evaluate which traits can be measured when a complex plant organ is monitored in-vivo while growing in the soil. We chose sugar beet (Beta vulgaris ssp. vulgaris) as a model system. The beet consists mainly of root tissues, is rather complex regarding tissue structure and responses to environmental factors, and thereby a good object to test the applicability of MRI for 3D phenotyping approaches. Over a time period of up to 3 months, traits such as beet morphology or anatomy were followed in the soil and the effect of differently sized pots on beet fresh weight calculated from MRI data was studied. There was a clear positive correlation between the pot size and the increase in fresh weight of a sugar beet over time. Since knowledge of the development of internal beet structures with several concentric cambia, vascular and parenchyma rings is still limited, we consecutively acquired 3D volumetric images on individual plants using the MRI contrast parameter T2 to map the development of rings at the tissue level. This demonstrates that MRI provides versatile protocols to non-invasively measure plant traits in the soil. It opens new avenues to investigate belowground plant performance under adverse environmental conditions such as drought, nutrient shortage, or soil compaction to seek for traits of belowground organs making plants more resilient to stress. PMID:25278947

Combining genetic and physiological data to identify predictors of lifetime reproductive success and the effect of selection on these predictors on underlying fertility traits.

PubMed

Dennis, N A; Stachowicz, K; Visser, B; Hely, F S; Berg, D K; Friggens, N C; Amer, P R; Meier, S; Burke, C R

2018-04-01

Fertility of the dairy cow relies on complex interactions between genetics, physiology, and management. Mathematical modeling can combine a range of information sources to facilitate informed predictions of cow fertility in scenarios that are difficult to evaluate empirically. We have developed a stochastic model that incorporates genetic and physiological data from more than 70 published reports on a wide range of fertility-related traits in dairy cattle. The model simulates pedigree, random mating, genetically correlated traits (in the form of breeding values for traits such as hours in estrus, estrous cycle length, age at puberty, milk yield, and so on), and interacting environmental variables. This model was used to generate a large simulated data set (200,000 cows replicated 100 times) of herd records within a seasonal dairy production system (based on an average New Zealand system). Using these simulated data, we investigated the genetic component of lifetime reproductive success (LRS), which, in reality, would be impractical to assess empirically. We defined LRS as the total number of times, during her lifetime, a cow calved within the first 42 d of the calving season. Sire estimated breeding values for LRS and other traits were calculated using simulated daughter records. Daughter pregnancy rate in the first lactation (PD_1) was the strongest single predictor of a sire's genetic merit for LRS (R 2 = 0.81). A simple predictive model containing PD_1, calving date for the second season and calving rate in the first season provided a good estimate of sire LRS (R 2 = 0.97). Daughters from sires with extremely high (n = 99,995 daughters, sire LRS = +0.70) or low (n = 99,635 daughters, sire LRS = -0.73) LRS estimated breeding values were compared over a single generation. Of the 14 underlying component traits of fertility, 12 were divergent between the 2 lines. This suggests that genetic variation in female fertility has a complex and multifactorial genetic basis. When simulated phenotypes were compared, daughters of the high LRS sires (HiFERT) reached puberty 44.5 d younger and calved ∼14 d younger at each parity than daughters from low LRS sires (LoFERT). Despite having a much lower genetic potential for milk production (-400 L/lactation) than LoFERT cows, HiFERT cows produced 33% more milk over their lifetime due to additional lactations before culling. In summary, this simulation model suggests that LRS contributes substantially to cow productivity, and novel selection criteria would facilitate a more accurate prediction at a younger age. The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Characterization of mature maize (Zea mays L.) root system architecture and complexity in a diverse set of Ex-PVP inbreds and hybrids.

PubMed

Hauck, Andrew L; Novais, Joana; Grift, Tony E; Bohn, Martin O

2015-01-01

The mature root system is a vital plant organ, which is critical to plant performance. Commercial maize (Zea mays L.) breeding has resulted in a steady increase in plant performance over time, along with noticeable changes in above ground vegetative traits, but the corresponding changes in the root system are not presently known. In this study, roughly 2500 core root systems from field trials of a set of 10 diverse elite inbreds formerly protected by Plant Variety Protection plus B73 and Mo17 and the 66 diallel intercrosses among them were evaluated for root traits using high throughput image-based phenotyping. Overall root architecture was modeled by root angle (RA) and stem diameter (SD), while root complexity, the amount of root branching, was quantified using fractal analysis to obtain values for fractal dimension (FD) and fractal abundance (FA). For each trait, per se line effects were highly significant and the most important contributor to trait performance. Mid-parent heterosis and specific combining ability was also highly significant for FD, FA, and RA, while none of the traits showed significant general combining ability. The interaction between the environment and the additive line effect was also significant for all traits. Within the inbred and hybrid generations, FD and FA were highly correlated (rp ≥ 0.74), SD was moderately correlated to FD and FA (0.69 ≥ rp ≥ 0.48), while the correlation between RA and other traits was low (0.13 ≥ rp ≥ -0.40). Inbreds with contrasting effects on complexity and architecture traits were observed, suggesting that root complexity and architecture traits are inherited independently. A more comprehensive understanding of the maize root system and the way it interacts with the environment will be useful for defining adaptation to nutrient acquisition and tolerance to stress from drought and high plant densities, critical factors in the yield gains of modern hybrids.

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

Integrating modelling and phenotyping approaches to identify and screen complex traits - Illustration for transpiration efficiency in cereals.

PubMed

Chenu, K; van Oosterom, E J; McLean, G; Deifel, K S; Fletcher, A; Geetika, G; Tirfessa, A; Mace, E S; Jordan, D R; Sulman, R; Hammer, G L

2018-02-21

Following advances in genetics, genomics, and phenotyping, trait selection in breeding is limited by our ability to understand interactions within the plants and with their environments, and to target traits of most relevance for the target population of environments. We propose an integrated approach that combines insights from crop modelling, physiology, genetics, and breeding to identify traits valuable for yield gain in the target population of environments, develop relevant high-throughput phenotyping platforms, and identify genetic controls and their values in production environments. This paper uses transpiration efficiency (biomass produced per unit of water used) as an example of a complex trait of interest to illustrate how the approach can guide modelling, phenotyping, and selection in a breeding program. We believe that this approach, by integrating insights from diverse disciplines, can increase the resource use efficiency of breeding programs for improving yield gains in target populations of environments.

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

The Evolution of Biological Complexity in Digital Organisms

NASA Astrophysics Data System (ADS)

Ofria, Charles

2013-03-01

When Darwin first proposed his theory of evolution by natural selection, he realized that it had a problem explaining the origins of traits of ``extreme perfection and complication'' such as the vertebrate eye. Critics of Darwin's theory have latched onto this perceived flaw as a proof that Darwinian evolution is impossible. In anticipation of this issue, Darwin described the perfect data needed to understand this process, but lamented that such data are ``scarcely ever possible'' to obtain. In this talk, I will discuss research where we use populations of digital organisms (self-replicating and evolving computer programs) to elucidate the genetic and evolutionary processes by which new, highly-complex traits arise, drawing inspiration directly from Darwin's wistful thinking and hypotheses. During the process of evolution in these fully-transparent computational environments we can measure the incorporation of new information into the genome, a process akin to a natural Maxwell's Demon, and identify the original source of any such information. We show that, as Darwin predicted, much of the information used to encode a complex trait was already in the genome as part of simpler evolved traits, and that many routes must be possible for a new complex trait to have a high probability of successfully evolving. In even more extreme examples of the evolution of complexity, we are now using these same principles to examine the evolutionary dynamics the drive major transitions in evolution; that is transitions to higher-levels of organization, which are some of the most complex evolutionary events to occur in nature. Finally, I will explore some of the implications of this research to other aspects of evolutionary biology and as well as ways that these evolutionary principles can be applied toward solving computational and engineering problems.

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

PubMed

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

2015-09-22

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

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

PubMed

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

2016-04-01

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

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

PubMed

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

2015-09-01

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

Integrating Nonadditive Genomic Relationship Matrices into the Study of Genetic Architecture of Complex Traits.

PubMed

Nazarian, Alireza; Gezan, Salvador A

2016-03-01

The study of genetic architecture of complex traits has been dramatically influenced by implementing genome-wide analytical approaches during recent years. Of particular interest are genomic prediction strategies which make use of genomic information for predicting phenotypic responses instead of detecting trait-associated loci. In this work, we present the results of a simulation study to improve our understanding of the statistical properties of estimation of genetic variance components of complex traits, and of additive, dominance, and genetic effects through best linear unbiased prediction methodology. Simulated dense marker information was used to construct genomic additive and dominance matrices, and multiple alternative pedigree- and marker-based models were compared to determine if including a dominance term into the analysis may improve the genetic analysis of complex traits. Our results showed that a model containing a pedigree- or marker-based additive relationship matrix along with a pedigree-based dominance matrix provided the best partitioning of genetic variance into its components, especially when some degree of true dominance effects was expected to exist. Also, we noted that the use of a marker-based additive relationship matrix along with a pedigree-based dominance matrix had the best performance in terms of accuracy of correlations between true and estimated additive, dominance, and genetic effects. © The American Genetic Association 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Does Structural Complexity Determine the Morphology of Assemblages? An Experimental Test on Three Continents

PubMed Central

Gibb, Heloise; Parr, Catherine L.

2013-01-01

Understanding how species will respond to global change depends on our ability to distinguish generalities from idiosyncrasies. For diverse, but poorly known taxa, such as insects, species traits may provide a short-cut to predicting species turnover. We tested whether ant traits respond consistently to habitat complexity across geographically independent ant assemblages, using an experimental approach and baits. We repeated our study in six paired simple and complex habitats on three continents with distinct ant faunas. We also compared traits amongst ants with different foraging strategies. We hypothesised that ants would be larger, broader, have longer legs and more dorsally positioned eyes in simpler habitats. In agreement with predictions, ants had longer femurs and dorsally positioned eyes in simple habitats. This pattern was most pronounced for ants that discovered resources. Body size and pronotum width responded as predicted for experimental treatments, but were inconsistent across continents. Monopolising ants were smaller, with shorter femurs than those that occupied or discovered resources. Consistent responses for several traits suggest that many, but not all, aspects of morphology respond predictably to habitat complexity, and that foraging strategy is linked with morphology. Some traits thus have the potential to be used to predict the direction of species turnover, changes in foraging strategy and, potentially, evolution in response to changes in habitat structure. PMID:23691137

Environmental variability and acoustic signals: a multi-level approach in songbirds.

PubMed

Medina, Iliana; Francis, Clinton D

2012-12-23

Among songbirds, growing evidence suggests that acoustic adaptation of song traits occurs in response to habitat features. Despite extensive study, most research supporting acoustic adaptation has only considered acoustic traits averaged for species or populations, overlooking intraindividual variation of song traits, which may facilitate effective communication in heterogeneous and variable environments. Fewer studies have explicitly incorporated sexual selection, which, if strong, may favour variation across environments. Here, we evaluate the prevalence of acoustic adaptation among 44 species of songbirds by determining how environmental variability and sexual selection intensity are associated with song variability (intraindividual and intraspecific) and short-term song complexity. We show that variability in precipitation can explain short-term song complexity among taxonomically diverse songbirds, and that precipitation seasonality and the intensity of sexual selection are related to intraindividual song variation. Our results link song complexity to environmental variability, something previously found for mockingbirds (Family Mimidae). Perhaps more importantly, our results illustrate that individual variation in song traits may be shaped by both environmental variability and strength of sexual selection.

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.

Enhancing knowledge and technology adoption in a misunderstood discipline: The weight trait project

USDA-ARS?s Scientific Manuscript database

Currently several commercial DNA marker panels are available for complex traits. In the fall of 2009, the American Angus Association integrated the results of an Angus-specific marker panel into their national cattle evaluation for carcass traits. Despite this advancement, there still exists treme...

Callous-unemotional traits are associated with deficits in recognizing complex emotions in preadolescent children.

PubMed

Sharp, Carla; Vanwoerden, Salome; Van Baardewijk, Y; Tackett, J L; Stegge, H

2015-06-01

The aims of the current study were to show that the affective component of psychopathy (callous-unemotional traits) is related to deficits in recognizing emotions over and above other psychopathy dimensions and to show that this relationship is driven by a specific deficit in recognizing complex emotions more so than basic emotions. The authors administered the Child Eyes Test to assess emotion recognition in a community sample of preadolescent children between the ages of 10 and 12 (N = 417; 53.6% boys). The task required children to identify a broad array of emotions from photographic stimuli depicting the eye region of the face. Stimuli were then divided into complex or basic emotions. Results demonstrated a unique association between callous-unemotional traits and complex emotions, with weaker associations with basic emotion recognition, over and above other dimensions of psychopathy.

Stochastic dynamics of adaptive trait and neutral marker driven by eco-evolutionary feedbacks.

PubMed

Billiard, Sylvain; Ferrière, Régis; Méléard, Sylvie; Tran, Viet Chi

2015-11-01

How the neutral diversity is affected by selection and adaptation is investigated in an eco-evolutionary framework. In our model, we study a finite population in continuous time, where each individual is characterized by a trait under selection and a completely linked neutral marker. Population dynamics are driven by births and deaths, mutations at birth, and competition between individuals. Trait values influence ecological processes (demographic events, competition), and competition generates selection on trait variation, thus closing the eco-evolutionary feedback loop. The demographic effects of the trait are also expected to influence the generation and maintenance of neutral variation. We consider a large population limit with rare mutation, under the assumption that the neutral marker mutates faster than the trait under selection. We prove the convergence of the stochastic individual-based process to a new measure-valued diffusive process with jumps that we call Substitution Fleming-Viot Process (SFVP). When restricted to the trait space this process is the Trait Substitution Sequence first introduced by Metz et al. (1996). During the invasion of a favorable mutation, a genetical bottleneck occurs and the marker associated with this favorable mutant is hitchhiked. By rigorously analysing the hitchhiking effect and how the neutral diversity is restored afterwards, we obtain the condition for a time-scale separation; under this condition, we show that the marker distribution is approximated by a Fleming-Viot distribution between two trait substitutions. We discuss the implications of the SFVP for our understanding of the dynamics of neutral variation under eco-evolutionary feedbacks and illustrate the main phenomena with simulations. Our results highlight the joint importance of mutations, ecological parameters, and trait values in the restoration of neutral diversity after a selective sweep.

Frequency-dependent and correlational selection pressures have conflicting consequences for assortative mating in a color-polymorphic lizard, Uta stansburiana.

PubMed

Lancaster, Lesley T; McAdam, Andrew G; Hipsley, Christy A; Sinervo, Barry R

2014-08-01

Genetically determined polymorphisms incorporating multiple traits can persist in nature under chronic, fluctuating, and sometimes conflicting selection pressures. Balancing selection among morphs preserves equilibrium frequencies, while correlational selection maintains favorable trait combinations within each morph. Under negative frequency-dependent selection, females should mate (often disassortatively) with rare male morphotypes to produce conditionally fit offspring. Conversely, under correlational selection, females should mate assortatively to preserve coadapted gene complexes and avoid ontogenetic conflict. Using controlled breeding designs, we evaluated consequences of assortative mating patterns in color-polymorphic side-blotched lizards (Uta stansburiana), to identify conflict between these sources of selection. Females who mated disassortatively, and to conditionally high-quality males in the context of frequency-dependent selection, experienced highest fertility rates. In contrast, assortatively mated females experienced higher fetal viability rates. The trade-off between fertility and egg viability resulted in no overall fitness benefit to either assortative or disassortative mating patterns. These results suggest that ongoing conflict between correlational and frequency dependent selection in polymorphic populations may generate a trade-off between rare-morph advantage and phenotypic integration and between assortative and disassortative mating decisions. More generally, interactions among multiple sources of diversity-promoting selection can alter adaptations and dynamics predicted to arise under any of these regimes alone.

Feedback between environment and traits under selection in a seasonal environment: consequences for experimental evolution.

PubMed

Collot, Dorian; Nidelet, Thibault; Ramsayer, Johan; Martin, Olivier C; Méléard, Sylvie; Dillmann, Christine; Sicard, Delphine; Legrand, Judith

2018-04-11

Batch cultures are frequently used in experimental evolution to study the dynamics of adaptation. Although they are generally considered to simply drive a growth rate increase, other fitness components can also be selected for. Indeed, recurrent batches form a seasonal environment where different phases repeat periodically and different traits can be under selection in the different seasons. Moreover, the system being closed, organisms may have a strong impact on the environment. Thus, the study of adaptation should take into account the environment and eco-evolutionary feedbacks. Using data from an experimental evolution on yeast Saccharomyces cerevisiae , we developed a mathematical model to understand which traits are under selection, and what is the impact of the environment for selection in a batch culture. We showed that two kinds of traits are under selection in seasonal environments: life-history traits, related to growth and mortality, but also transition traits, related to the ability to react to environmental changes. The impact of environmental conditions can be summarized by the length of the different seasons which weight selection on each trait: the longer a season is, the higher the selection on associated traits. Since phenotypes drive season length, eco-evolutionary feedbacks emerge. Our results show how evolution in successive batches can affect season lengths and strength of selection on different traits. © 2018 The Author(s).

Hydrodynamic Trait Coordination and Cost-Benefit Tradeoffs throughout the Isohydric-Anisohydric Continuum in Trees

NASA Astrophysics Data System (ADS)

Mirfenderesgi, G.; Matheny, A. M.; Bohrer, G.

2017-12-01

Whole-plant hydraulic performance depends on the integrated function of complexes of traits, such as embolism resistance and xylem anatomy, stomatal closure mechanisms, hydraulic architecture, and root properties. The diversity of such traits produces a wide range of response strategies to both short-term variation of soil moisture and VPD, and to long-term changes to climate and hydrological cycles which affect water availability. This study aims to assess the role of different hydraulic trait combinations in trees' vulnerability to limitations in soil water availability. We use a quantitative hydrodynamic modeling framework which allows studying the influence of each suits of plant hydraulic traits independently, and assess how the different trait groups interact with each other to form viable hydraulic strategies in response to reduced soil moisture availability. We utilize the advanced plant hydrodynamic model, FETCH2, which resolves plant functional hydrodynamics, using parameters that represent emergent physiological traits at the root, stem and leaf levels. FETCH2 simulates the integrated plant-level transpiration and water capacitance, provided hydraulic traits and environmental forcing. We define a multi-dimensional hydraulic "trait space" by considering a broad continuum of hydraulic traits at each of the leaf, stem, and root levels. We test the consequences of different strategies under a range of environmental conditions, representing typical wet, intermediate, and dry conditions, based on as observations in a research forest in Northern Michigan, USA. We evaluate the degree to which simulated trees suffer hydraulic failure due to cavitation, resulting in loss of xylem conductivity, or carbon starvation, through leaf water-potential-driven reduction of stomatal conductance. Our result demonstrated that risk-prone leaf strategy when combined with risk-adverse xylem traits may expose plant to the risk of hydraulic failure due to declining water potential during period of low soil moisture and high VPD. However, if this strategy is coupled with deep roots, the plant is less likely to experience water stress even during periods of low soil water availability and high evaporative demand.

On the role of mid-infrared predicted phenotypes in fertility and health dairy breeding programs.

PubMed

Bastin, C; Théron, L; Lainé, A; Gengler, N

2016-05-01

Fertility and health traits are of prime importance in dairy breeding programs. However, these traits are generally complex, difficult to record, and lowly heritable (<0.10), thereby hampering genetic improvement in disease resistance and fertility. Hence, indicators are useful in the prediction of genetic merit for fertility and health traits as long as they are easier to measure than direct fitness traits, heritable, and genetically correlated. Considering that changes in (fine) milk composition over a lactation reflect the physiological status of the cow, mid-infrared (MIR) analysis of milk opens the door to a wide range of potential indicator traits of fertility and health. Previous studies investigated the phenotypic and genetic relationships between fertility and MIR-predicted phenotypes, most being related to negative postpartum energy balance and body fat mobilization (e.g., fat:protein ratio, urea, fatty acids profile). Results showed that a combination of various fatty acid traits (e.g., C18:1 cis-9 and C10:0) could be used to improve fertility. Furthermore, occurrence of (sub)clinical ketosis has been related to milk-based phenotypes such as fat:protein ratio, fatty acids, and ketone bodies. Hence, MIR-predicted acetone and β-hydroxybutyrate contents in milk could be useful for breeding cows less susceptible to ketosis. Although studies investigating the genetic association among mastitis and MIR-predicted phenotypes are scarce, a wide range of traits, potentially predicted by MIR spectrometry, are worthy of consideration. These include traits related to the disease response of the cow (e.g., lactoferrin), reduced secretory activity (e.g., casein), and the alteration of the blood-milk barrier (e.g., minerals). Moreover, direct MIR prediction of fertility and health traits should be further considered. To conclude, MIR-predicted phenotypes have a role to play in the improvement of dairy cow fertility and health. However, further studies are warranted to (1) grasp underlying associations among MIR-predicted indicator and fitness traits, (2) estimate the genetic parameters, and (3) include these traits in broader breeding strategies. Copyright © 2016 American Dairy Science Association. 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.

Sequential recruitment of study participants may inflate genetic heritability estimates.

PubMed

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

2017-06-01

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

Understanding the individual to implement the ecosystem approach to fisheries management.

PubMed

Ward, Taylor D; Algera, Dirk A; Gallagher, Austin J; Hawkins, Emily; Horodysky, Andrij; Jørgensen, Christian; Killen, Shaun S; McKenzie, David J; Metcalfe, Julian D; Peck, Myron A; Vu, Maria; Cooke, Steven J

2016-01-01

Ecosystem-based approaches to fisheries management (EAFMs) have emerged as requisite for sustainable use of fisheries resources. At the same time, however, there is a growing recognition of the degree of variation among individuals within a population, as well as the ecological consequences of this variation. Managing resources at an ecosystem level calls on practitioners to consider evolutionary processes, and ample evidence from the realm of fisheries science indicates that anthropogenic disturbance can drive changes in predominant character traits (e.g. size at maturity). Eco-evolutionary theory suggests that human-induced trait change and the modification of selective regimens might contribute to ecosystem dynamics at a similar magnitude to species extirpation, extinction and ecological dysfunction. Given the dynamic interaction between fisheries and target species via harvest and subsequent ecosystem consequences, we argue that individual diversity in genetic, physiological and behavioural traits are important considerations under EAFMs. Here, we examine the role of individual variation in a number of contexts relevant to fisheries management, including the potential ecological effects of rapid trait change. Using select examples, we highlight the extent of phenotypic diversity of individuals, as well as the ecological constraints on such diversity. We conclude that individual phenotypic diversity is a complex phenomenon that needs to be considered in EAFMs, with the ultimate realization that maintaining or increasing individual trait diversity may afford not only species, but also entire ecosystems, with enhanced resilience to environmental perturbations. Put simply, individuals are the foundation from which population- and ecosystem-level traits emerge and are therefore of central importance for the ecosystem-based approaches to fisheries management.

Understanding the individual to implement the ecosystem approach to fisheries management

PubMed Central

Ward, Taylor D.; Algera, Dirk A.; Gallagher, Austin J.; Hawkins, Emily; Horodysky, Andrij; Jørgensen, Christian; Killen, Shaun S.; McKenzie, David J.; Metcalfe, Julian D.; Peck, Myron A.; Vu, Maria; Cooke, Steven J.

2016-01-01

Ecosystem-based approaches to fisheries management (EAFMs) have emerged as requisite for sustainable use of fisheries resources. At the same time, however, there is a growing recognition of the degree of variation among individuals within a population, as well as the ecological consequences of this variation. Managing resources at an ecosystem level calls on practitioners to consider evolutionary processes, and ample evidence from the realm of fisheries science indicates that anthropogenic disturbance can drive changes in predominant character traits (e.g. size at maturity). Eco-evolutionary theory suggests that human-induced trait change and the modification of selective regimens might contribute to ecosystem dynamics at a similar magnitude to species extirpation, extinction and ecological dysfunction. Given the dynamic interaction between fisheries and target species via harvest and subsequent ecosystem consequences, we argue that individual diversity in genetic, physiological and behavioural traits are important considerations under EAFMs. Here, we examine the role of individual variation in a number of contexts relevant to fisheries management, including the potential ecological effects of rapid trait change. Using select examples, we highlight the extent of phenotypic diversity of individuals, as well as the ecological constraints on such diversity. We conclude that individual phenotypic diversity is a complex phenomenon that needs to be considered in EAFMs, with the ultimate realization that maintaining or increasing individual trait diversity may afford not only species, but also entire ecosystems, with enhanced resilience to environmental perturbations. Put simply, individuals are the foundation from which population- and ecosystem-level traits emerge and are therefore of central importance for the ecosystem-based approaches to fisheries management. PMID:27293757

High-precision genetic mapping of behavioral traits in the diversity outbred mouse population

PubMed Central

Logan, R W; Robledo, R F; Recla, J M; Philip, V M; Bubier, J A; Jay, J J; Harwood, C; Wilcox, T; Gatti, D M; Bult, C J; Churchill, G A; Chesler, E J

2013-01-01

Historically our ability to identify genetic variants underlying complex behavioral traits in mice has been limited by low mapping resolution of conventional mouse crosses. The newly developed Diversity Outbred (DO) population promises to deliver improved resolution that will circumvent costly fine-mapping studies. The DO is derived from the same founder strains as the Collaborative Cross (CC), including three wild-derived strains. Thus the DO provides more allelic diversity and greater potential for discovery compared to crosses involving standard mouse strains. We have characterized 283 male and female DO mice using open-field, light–dark box, tail-suspension and visual-cliff avoidance tests to generate 38 behavioral measures. We identified several quantitative trait loci (QTL) for these traits with support intervals ranging from 1 to 3 Mb in size. These intervals contain relatively few genes (ranging from 5 to 96). For a majority of QTL, using the founder allelic effects together with whole genome sequence data, we could further narrow the positional candidates. Several QTL replicate previously published loci. Novel loci were also identified for anxiety- and activity-related traits. Half of the QTLs are associated with wild-derived alleles, confirming the value to behavioral genetics of added genetic diversity in the DO. In the presence of wild-alleles we sometimes observe behaviors that are qualitatively different from the expected response. Our results demonstrate that high-precision mapping of behavioral traits can be achieved with moderate numbers of DO animals, representing a significant advance in our ability to leverage the mouse as a tool for behavioral genetics PMID:23433259

Chromosomes 3B and 4D are associated with several milling and baking quality traits in a soft white spring wheat (Triticum aestivum L.) population.

PubMed

Carter, A H; Garland-Campbell, K; Morris, C F; Kidwell, K K

2012-04-01

Wheat is marketed based on end-use quality characteristics and better knowledge of the underlying genetics of specific quality parameters is essential to enhance the breeding process. A set of 188 recombinant inbred lines from a 'Louise' by 'Penawawa' mapping population was grown in two crop years at two locations in the Pacific Northwest region of the United States and data were collected on 17 end-use quality traits using established quality analysis protocols. Using an established genetic linkage map, composite interval mapping was used to identify QTL associated with 16 of the 17 quality traits. QTL were found on 13 of the 21 wheat chromosomes. A large number of QTL were located on chromosomes 3B and 4D and coincided with traits for milling quality and starch functionality. Chromosome 3B contained 10 QTL, which were localized to a 26.2 cM region. Chromosome 4D contained 7 QTL, all of which were located on an 18.8 cM region of this chromosome. The majority of the alleles for superior end-use quality were associated with the cultivar Louise. The identified QTL detected remained highly significant independent of grain yield and protein quantity. The identification of these QTL for end-use quality gives key insight into the relationship and complexity of end-use quality traits. It also improves our understanding of these relationships, thereby allowing plant breeders to make valuable gains from selection for these important traits.

In Vivo fitness associated with high virulence in a vertebrate virus is a complex trait regulated by host entry, replication, and shedding

USGS Publications Warehouse

Wargo, Andrew R.; Kurath, Gael

2011-01-01

The relationship between pathogen fitness and virulence is typically examined by quantifying only one or two pathogen fitness traits. More specifically, it is regularly assumed that within-host replication, as a precursor to transmission, is the driving force behind virulence. In reality, many traits contribute to pathogen fitness, and each trait could drive the evolution of virulence in different ways. Here, we independently quantified four viral infection cycle traits, namely, host entry, within-host replication, within-host coinfection fitness, and shedding, in vivo, in the vertebrate virus Infectious hematopoietic necrosis virus (IHNV). We examined how each of these stages of the viral infection cycle contributes to the fitness of IHNV genotypes that differ in virulence in rainbow trout. This enabled us to determine how infection cycle fitness traits are independently associated with virulence. We found that viral fitness was independently regulated by each of the traits examined, with the largest impact on fitness being provided by within-host replication. Furthermore, the more virulent of the two genotypes of IHNV we used had advantages in all of the traits quantified. Our results are thus congruent with the assumption that virulence and within-host replication are correlated but suggest that infection cycle fitness is complex and that replication is not the only trait associated with virulence.

A G protein alpha null mutation confers prolificacy potential in maize

DOE PAGES

Urano, Daisuke; Jackson, David; Jones, Alan M.

2015-05-06

Plasticity in plant development is controlled by environmental signals through largely unknown signalling networks. Signalling coupled by the heterotrimeric G protein complex underlies various developmental pathways in plants. The morphology of two plastic developmental pathways, root system architecture and female inflorescence formation, was quantitatively assessed in a mutant compact plant 2 (ct2) lacking the alpha subunit of the heterotrimeric G protein complex in maize. The ct2 mutant partially compensated for a reduced shoot height by increased total leaf number, and had far more ears, even in the presence of pollination signals. Lastly, the maize heterotrimeric G protein complex is importantmore » in some plastic developmental traits in maize. In particular, the maize Gα subunit is required to dampen the overproduction of female inflorescences.« less

A Computational Algorithm for Functional Clustering of Proteome Dynamics During Development

PubMed Central

Wang, Yaqun; Wang, Ningtao; Hao, Han; Guo, Yunqian; Zhen, Yan; Shi, Jisen; Wu, Rongling

2014-01-01

Phenotypic traits, such as seed development, are a consequence of complex biochemical interactions among genes, proteins and metabolites, but the underlying mechanisms that operate in a coordinated and sequential manner remain elusive. Here, we address this issue by developing a computational algorithm to monitor proteome changes during the course of trait development. The algorithm is built within the mixture-model framework in which each mixture component is modeled by a specific group of proteins that display a similar temporal pattern of expression in trait development. A nonparametric approach based on Legendre orthogonal polynomials was used to fit dynamic changes of protein expression, increasing the power and flexibility of protein clustering. By analyzing a dataset of proteomic dynamics during early embryogenesis of the Chinese fir, the algorithm has successfully identified several distinct types of proteins that coordinate with each other to determine seed development in this forest tree commercially and environmentally important to China. The algorithm will find its immediate applications for the characterization of mechanistic underpinnings for any other biological processes in which protein abundance plays a key role. PMID:24955031

Linkage Analysis of a Model Quantitative Trait in Humans: Finger Ridge Count Shows Significant Multivariate Linkage to 5q14.1

PubMed Central

Medland, Sarah E; Loesch, Danuta Z; Mdzewski, Bogdan; Zhu, Gu; Montgomery, Grant W; Martin, Nicholas G

2007-01-01

The finger ridge count (a measure of pattern size) is one of the most heritable complex traits studied in humans and has been considered a model human polygenic trait in quantitative genetic analysis. Here, we report the results of the first genome-wide linkage scan for finger ridge count in a sample of 2,114 offspring from 922 nuclear families. Both univariate linkage to the absolute ridge count (a sum of all the ridge counts on all ten fingers), and multivariate linkage analyses of the counts on individual fingers, were conducted. The multivariate analyses yielded significant linkage to 5q14.1 (Logarithm of odds [LOD] = 3.34, pointwise-empirical p-value = 0.00025) that was predominantly driven by linkage to the ring, index, and middle fingers. The strongest univariate linkage was to 1q42.2 (LOD = 2.04, point-wise p-value = 0.002, genome-wide p-value = 0.29). In summary, the combination of univariate and multivariate results was more informative than simple univariate analyses alone. Patterns of quantitative trait loci factor loadings consistent with developmental fields were observed, and the simple pleiotropic model underlying the absolute ridge count was not sufficient to characterize the interrelationships between the ridge counts of individual fingers. PMID:17907812

Evaluating physiological responses of plants to salinity stress

PubMed Central

Negrão, S.; Schmöckel, S. M.; Tester, M.

2017-01-01

Background Because soil salinity is a major abiotic constraint affecting crop yield, much research has been conducted to develop plants with improved salinity tolerance. Salinity stress impacts many aspects of a plant’s physiology, making it difficult to study in toto. Instead, it is more tractable to dissect the plant’s response into traits that are hypothesized to be involved in the overall tolerance of the plant to salinity. Scope and conclusions We discuss how to quantify the impact of salinity on different traits, such as relative growth rate, water relations, transpiration, transpiration use efficiency, ionic relations, photosynthesis, senescence, yield and yield components. We also suggest some guidelines to assist with the selection of appropriate experimental systems, imposition of salinity stress, and obtaining and analysing relevant physiological data using appropriate indices. We illustrate how these indices can be used to identify relationships amongst the proposed traits to identify which traits are the most important contributors to salinity tolerance. Salinity tolerance is complex and involves many genes, but progress has been made in studying the mechanisms underlying a plant’s response to salinity. Nevertheless, several previous studies on salinity tolerance could have benefited from improved experimental design. We hope that this paper will provide pertinent information to researchers on performing proficient assays and interpreting results from salinity tolerance experiments. PMID:27707746

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.

Leaf-trait plasticity and species vulnerability to climate change in a Mongolian steppe.

PubMed

Liancourt, Pierre; Boldgiv, Bazartseren; Song, Daniel S; Spence, Laura A; Helliker, Brent R; Petraitis, Peter S; Casper, Brenda B

2015-09-01

Climate change is expected to modify plant assemblages in ways that will have major consequences for ecosystem functions. How climate change will affect community composition will depend on how individual species respond, which is likely related to interspecific differences in functional traits. The extraordinary plasticity of some plant traits is typically neglected in assessing how climate change will affect different species. In the Mongolian steppe, we examined whether leaf functional traits under ambient conditions and whether plasticity in these traits under altered climate could explain climate-induced biomass responses in 12 co-occurring plant species. We experimentally created three probable climate change scenarios and used a model selection procedure to determine the set of baseline traits or plasticity values that best explained biomass response. Under all climate change scenarios, plasticity for at least one leaf trait correlated with change in species performance, while functional leaf-trait values in ambient conditions did not. We demonstrate that trait plasticity could play a critical role in vulnerability of species to a rapidly changing environment. Plasticity should be considered when examining how climate change will affect plant performance, species' niche spaces, and ecological processes that depend on plant community composition. © 2015 John Wiley & Sons Ltd.

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

PubMed Central

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

2013-01-01

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

Modelling water use efficiency in a dynamic environment: An example using Arabidopsis thaliana.

PubMed

Vialet-Chabrand, S; Matthews, J S A; Brendel, O; Blatt, M R; Wang, Y; Hills, A; Griffiths, H; Rogers, S; Lawson, T

2016-10-01

Intrinsic water use efficiency (Wi), the ratio of net CO2 assimilation (A) over stomatal conductance to water vapour (gs), is a complex trait used to assess plant performance. Improving Wi could lead in theory to higher productivity or reduced water usage by the plant, but the physiological traits for improvement and their combined effects on Wi have not been clearly identified. Under fluctuating light intensity, the temporal response of gs is an order of magnitude slower than A, which results in rapid variations in Wi. Compared to traditional approaches, our new model scales stoma behaviour at the leaf level to predict gs and A during a diurnal period, reproducing natural fluctuations of light intensity, in order to dissect Wi into traits of interest. The results confirmed the importance of stomatal density and photosynthetic capacity on Wi but also revealed the importance of incomplete stomatal closure under dark conditions as well as stomatal sensitivity to light intensity. The observed continuous decrease of A and gs over the diurnal period was successfully described by negative feedback of the accumulation of photosynthetic products. Investigation into the impact of leaf anatomy on temporal responses of A, gs and Wi revealed that a high density of stomata produces the most rapid response of gs but may result in lower Wi. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Identification of Single-Nucleotide Polymorphic Loci Associated with Biomass Yield under Water Deficit in Alfalfa (Medicago sativa L.) Using Genome-Wide Sequencing and Association Mapping

PubMed Central

Yu, Long-Xi

2017-01-01

Alfalfa is a worldwide grown forage crop and is important due to its high biomass production and nutritional value. However, the production of alfalfa is challenged by adverse environmental factors such as drought and other stresses. Developing drought resistance alfalfa is an important breeding target for enhancing alfalfa productivity in arid and semi-arid regions. In the present study, we used genotyping-by-sequencing and genome-wide association to identify marker loci associated with biomass yield under drought in the field in a panel of diverse germplasm of alfalfa. A total of 28 markers at 22 genetic loci were associated with yield under water deficit, whereas only four markers associated with the same trait under well-watered condition. Comparisons of marker-trait associations between water deficit and well-watered conditions showed non-similarity except one. Most of the markers were identical across harvest periods within the treatment, although different levels of significance were found among the three harvests. The loci associated with biomass yield under water deficit located throughout all chromosomes in the alfalfa genome agreed with previous reports. Our results suggest that biomass yield under drought is a complex quantitative trait with polygenic inheritance and may involve a different mechanism compared to that of non-stress. BLAST searches of the flanking sequences of the associated loci against DNA databases revealed several stress-responsive genes linked to the drought resistance loci, including leucine-rich repeat receptor-like kinase, B3 DNA-binding domain protein, translation initiation factor IF2, and phospholipase-like protein. With further investigation, those markers closely linked to drought resistance can be used for MAS to accelerate the development of new alfalfa cultivars with improved resistance to drought and other abiotic stresses. PMID:28706532

Genome wide association analysis for seedling response traits to thermal stress in sorghum germplasm

USDA-ARS?s Scientific Manuscript database

The sorghum association panel exhibited extensive variation for seedling traits under cold and heat stress. Genome-wide analyses identified thirty single nucleotide polymorphisms (SNPs) that were strongly associated with traits measured at seedling stage under cold stress and tagged genes that act a...

The impact of personality traits and professional experience on police officers' shooting performance under pressure.

PubMed

Landman, Annemarie; Nieuwenhuys, Arne; Oudejans, Raôul R D

2016-07-01

We explored the impact of professional experience and personality on police officers' shooting performance under pressure. We recruited: (1) regular officers, (2) officers wanting to join a specialised arrest unit (AU) (expected to possess more stress-resistant traits; pre-AU) and (3) officers from this unit (expected to also possess more professional experience; AU) (all male). In Phase 1, we determined personality traits and experience. In Phase 2, state anxiety, shot accuracy, decision-making (shoot/don't shoot), movement speed and gaze behaviour were measured while officers performed a shooting test under low and high pressure. Results indicate minimal differences in personality among groups and superior performance of AU officers. Regression analyses showed that state anxiety and shooting performance under high pressure were first predicted by AU experience and second by certain personality traits. Results suggest that although personality traits attenuate the impact of high pressure, it is relevant experience that secures effective performance under pressure. Practitioner Summary: To obtain information for police selection and training purposes, we let officers who differed in personality and experience execute a shooting test under low and high pressure. Outcomes indicate that experience affected anxiety and performance most strongly, while personality traits of thrill- and adventure-seeking and self-control also had an effect.

Genetic Control of Plasticity in Root Morphology and Anatomy of Rice in Response to Water Deficit1[OPEN

PubMed Central

Tamilselvan, Anandhan; Lawas, Lovely M.F.; Quinones, Cherryl; Bahuguna, Rajeev N.; Dingkuhn, Michael

2017-01-01

Elucidating the genetic control of rooting behavior under water-deficit stress is essential to breed climate-robust rice (Oryza sativa) cultivars. Using a diverse panel of 274 indica genotypes grown under control and water-deficit conditions during vegetative growth, we phenotyped 35 traits, mostly related to root morphology and anatomy, involving 45,000 root-scanning images and nearly 25,000 cross sections from the root-shoot junction. The phenotypic plasticity of these traits was quantified as the relative change in trait value under water-deficit compared with control conditions. We then carried out a genome-wide association analysis on these traits and their plasticity, using 45,608 high-quality single-nucleotide polymorphisms. One hundred four significant loci were detected for these traits under control conditions, 106 were detected under water-deficit stress, and 76 were detected for trait plasticity. We predicted 296 (control), 284 (water-deficit stress), and 233 (plasticity) a priori candidate genes within linkage disequilibrium blocks for these loci. We identified key a priori candidate genes regulating root growth and development and relevant alleles that, upon validation, can help improve rice adaptation to water-deficit stress. PMID:28600346

Mapping quantitative trait loci for binary trait in the F2:3 design.

PubMed

Zhu, Chengsong; Zhang, Yuan-Ming; Guo, Zhigang

2008-12-01

In the analysis of inheritance of quantitative traits with low heritability, an F(2:3) design that genotypes plants in F(2) and phenotypes plants in F(2:3) progeny is often used in plant genetics. Although statistical approaches for mapping quantitative trait loci (QTL) in the F(2:3) design have been well developed, those for binary traits of biological interest and economic importance are seldom addressed. In this study, an attempt was made to map binary trait loci (BTL) in the F(2:3) design. The fundamental idea was: the F(2) plants were genotyped, all phenotypic values of each F(2:3) progeny were measured for binary trait, and these binary trait values and the marker genotype informations were used to detect BTL under the penetrance and liability models. The proposed method was verified by a series of Monte-Carlo simulation experiments. These results showed that maximum likelihood approaches under the penetrance and liability models provide accurate estimates for the effects and the locations of BTL with high statistical power, even under of low heritability. Moreover, the penetrance model is as efficient as the liability model, and the F(2:3) design is more efficient than classical F(2) design, even though only a single progeny is collected from each F(2:3) family. With the maximum likelihood approaches under the penetrance and the liability models developed in this study, we can map binary traits as we can do for quantitative trait in the F(2:3) design.

Red Blood Cell Immune Complex Binding Capacity in Children with Sickle Cell Trait (HbAS) Living in P. falciparum Malaria Holoendemic Region of Western Kenya

DTIC Science & Technology

2012-12-08

the erythrocytes in normal individuals and also in certain disease states such as systemic lupus erythematosus, HIV and some hemolytic anemia. In these...chronic conditions including malaria, HIV infection and others are known to interfere with the parameters under investigation such as complement...Craig M, Deichmann U, Marsh K. Estimating mortality, morbidity and disability due to malaria among Africa’s non- pregnant population. Bull World Health

Urban habitat complexity affects species richness but not environmental filtering of morphologically-diverse ants

PubMed Central

Nash, Michael A.; Christie, Fiona J.; Hahs, Amy K.; Livesley, Stephen J.

2015-01-01

Habitat complexity is a major determinant of structure and diversity of ant assemblages. Following the size-grain hypothesis, smaller ant species are likely to be advantaged in more complex habitats compared to larger species. Habitat complexity can act as an environmental filter based on species size and morphological traits, therefore affecting the overall structure and diversity of ant assemblages. In natural and semi-natural ecosystems, habitat complexity is principally regulated by ecological successions or disturbance such as fire and grazing. Urban ecosystems provide an opportunity to test relationships between habitat, ant assemblage structure and ant traits using novel combinations of habitat complexity generated and sustained by human management. We sampled ant assemblages in low-complexity and high-complexity parks, and high-complexity woodland remnants, hypothesizing that (i) ant abundance and species richness would be higher in high-complexity urban habitats, (ii) ant assemblages would differ between low- and high-complexity habitats and (iii) ants living in high-complexity habitats would be smaller than those living in low-complexity habitats. Contrary to our hypothesis, ant species richness was higher in low-complexity habitats compared to high-complexity habitats. Overall, ant assemblages were significantly different among the habitat complexity types investigated, although ant size and morphology remained the same. Habitat complexity appears to affect the structure of ant assemblages in urban ecosystems as previously observed in natural and semi-natural ecosystems. However, the habitat complexity filter does not seem to be linked to ant morphological traits related to body size. PMID:26528416

Beyond the climate envelope: using trait filtering models to predict biome boundaries from plant physiology.

NASA Astrophysics Data System (ADS)

Fisher, R.; Hoffmann, W. A.; Muszala, S.

2014-12-01

The introduction of second-generation dynamic vegetation models - which simulate the distribution of light resources between plant types along the vertical canopy profile, and therefore facilitate the representation of plant competition explicitly - is a large increase in the complexity and fidelity with which the terrestrial biosphere is abstracted into Earth System Models. In this new class of model, biome boundaries are predicted as the emergent properties of plant physiology, and are therefore sensitive to the high-dimensional parameterizations of plant functional traits. These new approaches offer the facility to quantitatively test ecophysiological hypotheses of plant distribution at large scales, a field which remains surprisingly under-developed. Here we describe experiments conducted with the Community Land Model Ecosystem Demography component, CLM(ED), in which we reduce the complexity of the problem by testing how individual plant functional trait changes to control the location of biome boundaries between functional types. Specifically, we investigate which physiological trade-offs determine the boundary between frequently burned savanna and forest biomes, and attempt to distinguish how each strategic life-history trade-off (carbon storage, bark investment, re-sprouting strategy) contributes towards the maintenance of sharp geographical gradients between fire adapted and typically inflammable closed canopy ecosystems. This study forms part of the planning for a model-inspired fire manipulation experiment at the cerrado-forest boundary in South-Eastern Brazil, and the results will be used to guide future data-collection and analysis strategies.

Does incubation temperature fluctuation influence hatchling phenotypes in reptiles? A test using parthenogenetic geckos.

PubMed

Andrewartha, Sarah J; Mitchell, Nicola J; Frappell, Peter B

2010-01-01

Many lineages of parthenogenetic organisms have persisted through significant environmental change despite the constraints imposed by their fixed genotype and limited evolutionary potential. The ability of parthenogens to occur sympatrically with sexual relatives may in part be due to phenotypic plasticity in their responses to their environment, especially with respect to incubation temperature--a maternally selected trait. Here we measured the incubation temperatures selected by two lineages of triploid parthenogenic geckos in the Heteronotia binoei complex by allowing them to deposit clutches along a thermal gradient. The average nest temperature selected was 28.4 degrees C, with no significant differences between parthenogenic races or individual clones. To investigate the effect of nest-temperature variability on physiological and morphological traits, we incubated eggs from different races at one of four incubation regimes (32 degrees +/- 0 degrees, +/- 3 degrees , +/- 5 degrees , or +/- 9 degrees C). Embryos incubated at constant 32 degrees C developed faster than embryos reared under increasing extremes of diel temperature fluctuation (+/- 3 degrees , +/- 5 degrees C), and incubation at 32 degrees +/- 9 degrees C was unsuccessful. Incubation regime had no effect on the body size, preferred substrate temperature, or mass-specific .V(O2) of hatchlings. However, parthenogenic race had a significant effect on egg mass, tail length, snout-to-vent length, total length, and .V(O2) . We conclude that developmental traits are strongly influenced by clonal genotypes in this parthenogenic complex but are well buffered against fluctuations in incubation temperature.

Deciphering the evolution of herbicide resistance in weeds.

PubMed

Délye, Christophe; Jasieniuk, Marie; Le Corre, Valérie

2013-11-01

Resistance to herbicides in arable weeds is increasing rapidly worldwide and threatening global food security. Resistance has now been reported to all major herbicide modes of action despite the development of resistance management strategies in the 1990s. We review here recent advances in understanding the genetic bases and evolutionary drivers of herbicide resistance that highlight the complex nature of selection for this adaptive trait. Whereas early studied cases of resistance were highly herbicide-specific and largely under monogenic control, cases of greatest concern today generally involve resistance to multiple modes of action, are under polygenic control, and are derived from pre-existing stress response pathways. Although 'omics' approaches should enable unraveling the genetic bases of complex resistances, the appearance, selection, and spread of herbicide resistance in weed populations can only be fully elucidated by focusing on evolutionary dynamics and implementing integrative modeling efforts. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

PubMed

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

2018-04-26

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

How rare bone diseases have informed our knowledge of complex diseases.

PubMed

Johnson, Mark L

2016-01-01

Rare bone diseases, generally defined as monogenic traits with either autosomal recessive or dominant patterns of inheritance, have provided a rich database of genes and associated pathways over the past 2-3 decades. The molecular genetic dissection of these bone diseases has yielded some major surprises in terms of the causal genes and/or involved pathways. The discovery of genes/pathways involved in diseases such as osteopetrosis, osteosclerosis, osteogenesis imperfecta and many other rare bone diseases have all accelerated our understanding of complex traits. Importantly these discoveries have provided either direct validation for a specific gene embedded in a group of genes within an interval identified through a complex trait genome-wide association study (GWAS) or based upon the pathway associated with a monogenic trait gene, provided a means to prioritize a large number of genes for functional validation studies. In some instances GWAS studies have yielded candidate genes that fall within linkage intervals associated with monogenic traits and resulted in the identification of causal mutations in those rare diseases. Driving all of this discovery is a complement of technologies such as genome sequencing, bioinformatics and advanced statistical analysis methods that have accelerated genetic dissection and greatly reduced the cost. Thus, rare bone disorders in partnership with GWAS have brought us to the brink of a new era of personalized genomic medicine in which the prevention and management of complex diseases will be driven by the molecular understanding of each individuals contributing genetic risks for disease.

Effects of light on direct and indirect defences against herbivores of young plants of Mallotus japonicus demonstrate a trade-off between two indirect defence traits

PubMed Central

Yamawo, Akira; Hada, Yoshio

2010-01-01

Background and Aims Although most studies on plant defence strategies have focused on a particular defence trait, some plant species develop multiple defence traits. To clarify the effects of light on the development of multiple defence traits, the production of direct and indirect defence traits of young plants of Mallotus japonicus were examined experimentally under different light conditions. Methods The young plants were cultivated under three light conditions in the experimental field for 3 months from May to July. Numbers of ants and pearl bodies on leaves in July were examined. After cultivation, the plants were collected and the developments of trichomes and pellucid dots, and extrafloral nectaries (EFNs) on the leaves were examined. On plants without nectar-collecting insects, the size of EFNs and the volume of extrafloral nectar secreted from the EFNs were examined. Key results Densities of trichomes and pellucid dots did not differ significantly among the plants under the different light conditions, suggesting that the chemical and physical defences function under both high and low light availability. The number of EFNs on the leaves did not differ significantly among the plants under the different light conditions, but there appeared to be a trade-off between the size of EFNs and the number of pearl bodies; the largest EFNs and the smallest number of pearl bodies were found under high light availability. EFN size was significantly correlated with the volume of extrafloral nectar secreted for 24 h. The number of ants on the plants was smaller under low light availability than under high and moderate light availability. Conclusions These results suggest that direct defence traits function regardless of light conditions, but light conditions affected the development of indirect defence traits. PMID:20472698

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

PubMed

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

2017-09-11

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

Trait Variation Along a Forest Successional Gradient in Dry Tropical Forest, Florida Keys

NASA Astrophysics Data System (ADS)

Subedi, S.; Ross, M. S.

2016-12-01

In most part of South Florida tropical dry forests, the early colonized trees on disturbed uplands are mostly deciduous species cable of surviving for several years after establishment. However, trees in mature forests are generally characterized by a suite of evergreen species, most of which are completely absent in younger stands even in seedling stage. This complete transition from one functional group to another in the course of stand development suggests a distinct change in the underlying environment during the course of succession. Such change in hammock functional groups as a function of the changing environmental drivers during succession in tropical dry forests is unknown and addressing this question may help to understand which drivers of change act as filters that select for and against particular groups of species and traits. In this study, we evaluate number of important functional traits (specific leaf area, wood density, leaf d13C, leaf N:P ratio, and architectural traits such as height, crown dimensions, diameter at breast height) for woody plant species occurring along a successional gradient across three ecological scales, community, species, and individual. A significant change in the overall trait distribution across the successional gradient is found. Intraspecific trait variation within the community is increased with increase in forest age. Most of these traits have shown correlation with stand age and showed preference to a certain environment. Stand age is the most important variable explaining the distribution of community characteristics. It is found that early successional forest are mostly shaped by environmental driven processes, and as forest get older and structurally more complex, they are increasingly shaped by competitively driven processes leading to limiting similarity. This study has shown that the patterns of trait shift can be predictable and can be used to characterize habitats and stage of forest succession in dry tropical forest.

Prediction of reduction in aggressive behaviour of growing pigs using skin lesion traits as selection criteria.

PubMed

Desire, S; Turner, S P; D'Eath, R B; Doeschl-Wilson, A B; Lewis, C R G; Roehe, R

2016-08-01

Aggression at regrouping is a common issue in pig farming. Skin lesions are genetically and phenotypically correlated with aggression and have been shown to have a significant heritable component. This study predicts the magnitude of reduction in complex aggressive behavioural traits when using lesion numbers on different body regions at two different time points as selection criteria, to identify the optimum skin lesion trait for selection purposes. In total, 1146 pigs were mixed into new social groups, and skin lesions were counted 24 h (SL24h) and 3 weeks (SL3wk) post-mixing, on the anterior, centre and posterior regions of the body. An animal model was used to estimate genetic parameters for skin lesion traits and 14 aggressive behavioural traits. Estimated breeding values (EBVs) and phenotypic values were scaled and standardised to allow direct comparison across multiple traits. Individuals with SL24h and SL3wk EBVs in the least aggressive 10% of the population were compared with the population mean to predict the expected genetic and phenotypic response in aggressive behaviour to selection. At mixing, selection for low anterior lesions was predicted to affect substantially more behavioural traits of aggressiveness than lesions obtained on other body parts, with EBVs between -0.21 and -1.17 SD below the population mean. Individuals with low central SL24h EBVs also had low EBVs for aggressive traits (-0.33 to -0.55). Individuals with high SL3wk EBVs had low EBVs for aggression at mixing (between -0.24 and -0.53 SD below the population mean), although this was predicted to affect fewer traits than selection against SL24h. These results suggest that selection against anterior SL24h would result in the greatest genetic and phenotypic reduction in aggressive behaviour recorded at mixing. Selection for increased SL3wk was predicted to reduce aggression at mixing; however, current understanding about aggressive behaviour under stable social conditions is insufficient to recommend using this trait for selection purposes.

High Density Linkage Map Construction and QTL Detection for Three Silique-Related Traits in Orychophragmus violaceus Derived Brassica napus Population.

PubMed

Yang, Yi; Shen, Yusen; Li, Shunda; Ge, Xianhong; Li, Zaiyun

2017-01-01

Seeds per silique (SS), seed weight (SW), and silique length (SL) are important determinant traits of seed yield potential in rapeseed ( Brassica napus L.), and are controlled by naturally occurring quantitative trait loci (QTLs). Mapping QTLs to narrow chromosomal regions provides an effective means of characterizing the genetic basis of these complex traits. Orychophragmus violaceus is a crucifer with long siliques, many SS, and heavy seeds. A novel B. napus introgression line with many SS was previously selected from multiple crosses ( B. rapa ssp. chinesis × O. violaceus ) × B. napus . In present study, a doubled haploid (DH) population with 167 lines was established from a cross between the introgression line and a line with far fewer SS, in order to detect QTLs for silique-related traits. By screening with a Brassica 60K single nucleotide polymorphism (SNP) array, a high-density linkage map consisting of 1,153 bins and spanning a cumulative length of 2,209.1 cM was constructed, using 12,602 high-quality polymorphic SNPs in the DH population. The average recombination bin densities of the A and C subgenomes were 1.7 and 2.4 cM, respectively. 45 QTLs were identified for the three traits in all, which explained 4.0-34.4% of the total phenotypic variation; 20 of them were integrated into three unique QTLs by meta-analysis. These unique QTLs revealed a significant positive correlation between SS and SL and a significant negative correlation between SW and SS, and were mapped onto the linkage groups A05, C08, and C09. A trait-by-trait meta-analysis revealed eight, four, and seven consensus QTLs for SS, SW, and SL, respectively, and five major QTLs ( cqSS.A09b, cqSS.C09, cqSW.A05, cqSW.C09 , and cqSL.C09 ) were identified. Five, three, and four QTLs for SS, SW, and SL, respectively, might be novel QTLs because of the existence of alien genetic loci for these traits in the alien introgression. Thirty-eight candidate genes underlying nine QTLs for silique-related traits were identified.

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

PubMed

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

2017-04-01

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

Searching new signals for production traits through gene-based association analysis in three Italian cattle breeds.

PubMed

Capomaccio, Stefano; Milanesi, Marco; Bomba, Lorenzo; Cappelli, Katia; Nicolazzi, Ezequiel L; Williams, John L; Ajmone-Marsan, Paolo; Stefanon, Bruno

2015-08-01

Genome-wide association studies (GWAS) have been widely applied to disentangle the genetic basis of complex traits. In cattle breeds, classical GWAS approaches with medium-density marker panels are far from conclusive, especially for complex traits. This is due to the intrinsic limitations of GWAS and the assumptions that are made to step from the association signals to the functional variations. Here, we applied a gene-based strategy to prioritize genotype-phenotype associations found for milk production and quality traits with classical approaches in three Italian dairy cattle breeds with different sample sizes (Italian Brown n = 745; Italian Holstein n = 2058; Italian Simmental n = 477). Although classical regression on single markers revealed only a single genome-wide significant genotype-phenotype association, for Italian Holstein, the gene-based approach identified specific genes in each breed that are associated with milk physiology and mammary gland development. As no standard method has yet been established to step from variation to functional units (i.e., genes), the strategy proposed here may contribute to revealing new genes that play significant roles in complex traits, such as those investigated here, amplifying low association signals using a gene-centric approach. © 2015 Stichting International Foundation for Animal Genetics.

Temperament types are associated with weak self-construct, elevated distress and emotion-oriented coping in schizophrenia: evidence for a complex vulnerability marker?

PubMed

Ritsner, Michael; Susser, Ehud

2004-10-30

Knowledge concerning temperament factors involved in vulnerability to schizophrenia is limited. We hypothesized that temperament and self-variables (emotional distress, coping styles, self-efficacy and self-esteem) might present a complex trait marker for underlying vulnerability to schizophrenia. We sought to (1) assess temperament dimensions and types in schizophrenia patients and healthy controls using the Tridimensional Personality Questionnaire (TPQ), and (2) explore their association with symptom dimensions, emotional distress, coping styles, self-constructs, demographic and background variables. We evaluated 90 consecutively recruited DSM-IV schizophrenia patients and 136 healthy controls matched for gender and age. We found that the harm avoidance (HA) factor was higher, while reward dependence (RD) was lower in schizophrenia patients than in healthy controls. Relationships of negative symptoms to novelty seeking (NS) and general psychopathology with both NS and HA show a confounding relation to self-variables. TPQ temperament types were defined by dichotomization into high and low according to medians of the three TPQ temperament dimensions. The odds ratios for the HA and HA/NS temperament types were significantly higher, while the NS/RD type was lower in schizophrenia patients than in healthy controls. HA/NS, HA/RD and high-HA/NS/RD types revealed higher scores for emotional distress, emotion-oriented coping and lower scores on self-constructs. No links were found between temperament types and schizophrenia symptom dimensions, task and avoidance oriented coping, or demographic and background variables. Thus, our findings strengthen the hypothesis that temperament types, when associated with elevated emotional distress, emotion-oriented coping and weak self-constructs, might represent a complex trait marker for underlying vulnerability to schizophrenia.

Effects of Cerium Oxide Nanoparticles on Sorghum Plant Traits

NASA Astrophysics Data System (ADS)

Mu, L.; Chen, Y.; Darnault, C. J. G.; Rauh, B.; Kresovich, S.; Korte, C.

2015-12-01

Nanotechnology and nanomaterials are considered as the development of the modern science. However, besides with that wide application, nanoparticles arouse to the side effects on the environment and human health. As the catalyst of ceramics and fuel industry, Cerium (IV) oxide nanoparticles (CeO2 NPs) can be found in the environment following their use and life-cycle. Therefore, it is critical to assess the potential effects that CeO2 NPs found in soils may have on plants. In this study, CeO2 NPs were analyzed for the potential influence on the sorghum [Sorghum bicolor (L.) Moench] (Reg. no. 126) (PI 154844) growth and traits. The objectives of this research were to determine whether CeO2 NPs impact the sorghum germination and growth characteristics. The sorghum was grown in the greenhouse located at Biosystems Research Complex, Clemson University under different CeO2 NPs treatments (0mg; 100mg; 500mg; 1000mg CeO2 NPs/Kg soil) and harvested around each month. At the end of the each growing period, above ground vegetative tissue was air-dried, ground to 2mm particle size and compositional traits estimated using near-infrared spectroscopy. Also, the NPK value of the sorghum tissue was tested by Clemson Agriculture Center. After the first harvest, the result showed that the height of above ground biomass under the nanoparticles stress was higher than that of control group. This difference between the control and the nanoparticles treatments was significant (F>F0.05; LSD). Our results also indicated that some of the compositional traits were impacted by the different treatments, including the presence and/or concentrations of the nanoparticles.

Genomic Correlates of Relationship QTL Involved in Fore- versus Hind Limb Divergence in Mice

PubMed Central

Pavlicev, Mihaela; Wagner, Günter P.; Noonan, James P.; Hallgrímsson, Benedikt; Cheverud, James M.

2013-01-01

Divergence of serially homologous elements of organisms is a common evolutionary pattern contributing to increased phenotypic complexity. Here, we study the genomic intervals affecting the variational independence of fore- and hind limb traits within an experimental mouse population. We use an advanced intercross of inbred mouse strains to map the loci associated with the degree of autonomy between fore- and hind limb long bone lengths (loci affecting the relationship between traits, relationship quantitative trait loci [rQTL]). These loci have been proposed to interact locally with the products of pleiotropic genes, thereby freeing the local trait from the variational constraint due to pleiotropic mutations. Using the known polymorphisms (single nucleotide polymorphisms [SNPs]) between the parental strains, we characterized and compared the genomic regions in which the rQTL, as well as their interaction partners (intQTL), reside. We find that these two classes of QTL intervals harbor different kinds of molecular variation. SNPs in rQTL intervals more frequently reside in limb-specific cis-regulatory regions than SNPs in intQTL intervals. The intQTL loci modified by the rQTL, in contrast, show the signature of protein-coding variation. This result is consistent with the widely accepted view that protein-coding mutations have broader pleiotropic effects than cis-regulatory polymorphisms. For both types of QTL intervals, the underlying candidate genes are enriched for genes involved in protein binding. This finding suggests that rQTL effects are caused by local interactions among the products of the causal genes harbored in rQTL and intQTL intervals. This is the first study to systematically document the population-level molecular variation underlying the evolution of character individuation. PMID:24065733

Genotypic variation in the ability of landraces and commercial cereal varieties to avoid manganese deficiency in soils with limited manganese availability: is there a role for root-exuded phytases?

PubMed

George, Timothy S; French, Andrew S; Brown, Lawrie K; Karley, Alison J; White, Philip J; Ramsay, Luke; Daniell, Tim J

2014-07-01

The marginal agricultural-systems of the Machair in the Western Isles of Scotland often have limited micronutrient availability because of alkaline soils. Traditional landraces of oats, barley and rye are thought to be better adapted to cope with the limited manganese (Mn) availability of these soils. When commercial cultivars are grown on the Machair, limited Mn-availability reduces crop yield and quality. We hypothesised that traditional cereal landraces selected on the Machair acquire Mn more effectively and that this could be linked to exudation of phytase from roots which would release Mn complexed with inositol phosphates. Growth and Mn-acquisition of five landraces and three commercial cultivars of barley and oats were determined in Machair soil. In addition, root phytase activities were assayed under Mn-starvation and sufficiency in hydroponics. In Machair soil, landraces had greater capacity for acquiring Mn and a greater ability to achieve maximum yield compared to the commercial cultivars. Under Mn-starvation, root phytase exudation was upregulated in all plants, suggesting that this trait might allow cereals to acquire more Mn when Mn-availability is limited. In the landraces, exuded phytase activity related positively to relative Mn-accumulation, whereas in the commercial cultivars this relationship was negative, suggesting that this trait may be secondary to an efficiency trait that has been lost from commercial germplasm by breeding. This research shows that cereal landraces possess traits that could be useful for improving the Mn-acquisition of commercial varieties. Exploiting the genetic diversity of landraces could improve the sustainability of agriculture on marginal calcareous lands globally. © 2014 Scandinavian Plant Physiology Society.

Quantitative Genetic Analysis Reveals Potential to Genetically Improve Fruit Yield and Drought Resistance Simultaneously in Coriander

PubMed Central

Khodadadi, Mostafa; Dehghani, Hamid; Jalali Javaran, Mokhtar

2017-01-01

Enhancing water use efficiency of coriander (Coriandrum sativum L.) is a major focus for coriander breeding to cope with drought stress. The purpose of this study was; (a) to identify the predominant mechanism(s) of drought resistance in coriander and (b) to evaluate the genetic control mechanism(s) of traits associated with drought resistance and higher fruit yield. To reach this purpose, 15 half-diallel hybrids of coriander and their six parents were evaluated under well-watered and water deficit stressed (WDS) in both glasshouse lysimetric and field conditions. The parents were selected for their different response to water deficit stress following preliminary experiments. Results revealed that the genetic control mechanism of fruit yield is complex, variable and highly affected by environment. The mode of inheritance and nature of gene action for percent assimilate partitioned to fruits were similar to those for flowering time in both well-watered and WDS conditions. A significant negative genetic linkage was found between fruit yield and percent assimilate partitioned to root, percent assimilate partitioned to shoot, root number, root diameter, root dry mass, root volume, and early flowering. Thus, to improve fruit yield under water deficit stress, selection of low values of these traits could be used. In contrast, a significant positive genetic linkage between fruit yield and percent assimilate partitioned to fruits, leaf relative water content and chlorophyll content indicate selection for high values of these traits. These secondary or surrogate traits could be selected during early segregating generations. The early ripening parent (P1; TN-59-230) contained effective genes involved in preferred percent assimilate partitioning to fruit and drought stress resistance. In conclusion, genetic improvement of fruit yield and drought resistance could be simultaneously gained in coriander when breeding for drought resistance. PMID:28473836

Characterising variation in wheat traits under hostile soil conditions in India

PubMed Central

Khokhar, Jaswant S.; Sareen, Sindhu; Tyagi, Bhudeva S.; Singh, Gyanendra; Chowdhury, Apurba K.; Dhar, Tapamay; Singh, Vinod; King, Ian P.; Young, Scott D.

2017-01-01

Intensive crop breeding has increased wheat yields and production in India. Wheat improvement in India typically involves selecting yield and component traits under non-hostile soil conditions at regional scales. The aim of this study is to quantify G*E interactions on yield and component traits to further explore site-specific trait selection for hostile soils. Field experiments were conducted at six sites (pH range 4.5–9.5) in 2013–14 and 2014–15, in three agro-climatic regions of India. At each site, yield and component traits were measured on 36 genotypes, representing elite varieties from a wide genetic background developed for different regions. Mean grain yields ranged from 1.0 to 5.5 t ha-1 at hostile and non-hostile sites, respectively. Site (E) had the largest effect on yield and component traits, however, interactions between genotype and site (G*E) affected most traits to a greater extent than genotype alone. Within each agro-climatic region, yield and component traits correlated positively between hostile and non-hostile sites. However, some genotypes performed better under hostile soils, with site-specific relationships between yield and component traits, which supports the value of ongoing site-specific selection activities. PMID:28604800

Dissection of complex adult traits in a mouse synthetic population.

PubMed

Burke, David T; Kozloff, Kenneth M; Chen, Shu; West, Joshua L; Wilkowski, Jodi M; Goldstein, Steven A; Miller, Richard A; Galecki, Andrzej T

2012-08-01

Finding the causative genetic variations that underlie complex adult traits is a significant experimental challenge. The unbiased search strategy of genome-wide association (GWAS) has been used extensively in recent human population studies. These efforts, however, typically find only a minor fraction of the genetic loci that are predicted to affect variation. As an experimental model for the analysis of adult polygenic traits, we measured a mouse population for multiple phenotypes and conducted a genome-wide search for effector loci. Complex adult phenotypes, related to body size and bone structure, were measured as component phenotypes, and each subphenotype was associated with a genomic spectrum of candidate effector loci. The strategy successfully detected several loci for the phenotypes, at genome-wide significance, using a single, modest-sized population (N = 505). The effector loci each explain 2%-10% of the measured trait variation and, taken together, the loci can account for over 25% of a trait's total population variation. A replicate population (N = 378) was used to confirm initially observed loci for one trait (femur length), and, when the two groups were merged, the combined population demonstrated increased power to detect loci. In contrast to human population studies, our mouse genome-wide searches find loci that individually explain a larger fraction of the observed variation. Also, the additive effects of our detected mouse loci more closely match the predicted genetic component of variation. The genetic loci discovered are logical candidates for components of the genetic networks having evolutionary conservation with human biology.

Inferential Costs of Trait Centrality in Impression Formation: Organization in Memory and Misremembering

PubMed Central

Nunes, Ludmila D.; Garcia-Marques, Leonel; Ferreira, Mário B.; Ramos, Tânia

2017-01-01

An extension of the DRM paradigm was used to study the impact of central traits (Asch, 1946) in impression formation. Traits corresponding to the four clusters of the implicit theory of personality—intellectual, positive and negative; and social, positive and negative (Rosenberg et al., 1968)—were used to develop lists containing several traits of one cluster and one central trait prototypical of the opposite cluster. Participants engaging in impression formation relative to participants engaging in memorization not only produced higher levels of false memories corresponding to the same cluster of the list traits but, under response time pressure at retrieval, also produced more false memories of the cluster corresponding to the central trait. We argue that the importance of central traits stems from their ability to activate their corresponding semantic space within a specialized associative memory structure underlying the implicit theory of personality. PMID:28878708

Novel throughput phenotyping platforms in plant genetic studies.

PubMed

Montes, Juan M; Melchinger, Albrecht E; Reif, Jochen C

2007-10-01

Unraveling the genetic basis of complex traits in plants is limited by the lack of appropriate phenotyping platforms that enable high-throughput screening of many genotypes in multilocation field trials. Near-infrared spectroscopy on agricultural harvesters and spectral reflectance of plant canopies have recently been reported as promising components of novel phenotyping platforms. Understanding the genetic basis of complex traits is now within reach with the use of these new techniques.

Capitalizing on fine milk composition for breeding and management of dairy cows.

PubMed

Gengler, N; Soyeurt, H; Dehareng, F; Bastin, C; Colinet, F; Hammami, H; Vanrobays, M-L; Lainé, A; Vanderick, S; Grelet, C; Vanlierde, A; Froidmont, E; Dardenne, P

2016-05-01

The challenge of managing and breeding dairy cows is permanently adapting to changing production circumstances under socio-economic constraints. If managing and breeding address different timeframes of action, both need relevant phenotypes that allow for precise monitoring of the status of the cows, and their health, behavior, and well-being as well as their environmental impact and the quality of their products (i.e., milk and subsequently dairy products). Milk composition has been identified as an important source of information because it could reflect, at least partially, all these elements. Major conventional milk components such as fat, protein, urea, and lactose contents are routinely predicted by mid-infrared (MIR) spectrometry and have been widely used for these purposes. But, milk composition is much more complex and other nonconventional milk components, potentially predicted by MIR, might be informative. Such new milk-based phenotypes should be considered given that they are cheap, rapidly obtained, usable on a large scale, robust, and reliable. In a first approach, new phenotypes can be predicted from MIR spectra using techniques based on classical prediction equations. This method was used successfully for many novel traits (e.g., fatty acids, lactoferrin, minerals, milk technological properties, citrate) that can be then useful for management and breeding purposes. An innovation was to consider the longitudinal nature of the relationship between the trait of interest and the MIR spectra (e.g., to predict methane from MIR). By avoiding intermediate steps, prediction errors can be minimized when traits of interest (e.g., methane, energy balance, ketosis) are predicted directly from MIR spectra. In a second approach, research is ongoing to detect and exploit patterns in an innovative manner, by comparing observed with expected MIR spectra directly (e.g., pregnancy). All of these traits can then be used to define best practices, adjust feeding and health management, improve animal welfare, improve milk quality, and mitigate environmental impact. Under the condition that MIR data are available on a large scale, phenotypes for these traits will allow genetic and genomic evaluations. Introduction of novel traits into the breeding objectives will need additional research to clarify socio-economic weights and genetic correlations with other traits of interest. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Receiver discriminability drives the evolution of complex sexual signals by sexual selection.

PubMed

Cui, Jianguo; Song, Xiaowei; Zhu, Bicheng; Fang, Guangzhan; Tang, Yezhong; Ryan, Michael J

2016-04-01

A hallmark of sexual selection by mate choice is the evolution of exaggerated traits, such as longer tails in birds and more acoustic components in the calls of birds and frogs. Trait elaboration can be opposed by costs such as increased metabolism and greater predation risk, but cognitive processes of the receiver can also put a brake on trait elaboration. For example, according to Weber's Law traits of a fixed absolute difference will be more difficult to discriminate as the absolute magnitude increases. Here, we show that in the Emei music frog (Babina daunchina) increases in the fundamental frequency between successive notes in the male advertisement call, which increases the spectral complexity of the call, facilitates the female's ability to compare the number of notes between calls. These results suggest that female's discriminability provides the impetus to switch from enhancement of signaling magnitude (i.e., adding more notes into calls) to employing a new signal feature (i.e., increasing frequency among notes) to increase complexity. We suggest that increasing the spectral complexity of notes ameliorates some of the effects of Weber's Law, and highlights how perceptual and cognitive biases of choosers can have important influences on the evolution of courtship signals. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

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

PubMed Central

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

2012-01-01

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

Epistatic effects between pairs of the growth hormone secretagogue receptor 1a, growth hormone, growth hormone receptor, non-SMC condensin I complex, subunit G and stearoyl-CoA desaturase genes on carcass, price-related and fatty acid composition traits in Japanese Black cattle.

PubMed

Komatsu, Masanori; Nishino, Kagetomo; Fujimori, Yuki; Haga, Yasutoshi; Iwama, Nagako; Arakawa, Aisaku; Aihara, Yoshito; Takeda, Hisato; Takahashi, Hideaki

2018-02-01

Growth hormone secretagogue receptor 1a (GHSR1a), growth hormone (GH), growth hormone receptor (GHR), non-SMC condensin I complex, subunit G (NCAPG) and stearoyl-CoA desaturase (SCD), are known to play important roles in growth and lipid metabolisms. Single and epistatic effects of the five genes on carcass, price-related and fatty acid (FA) composition traits were analyzed in a commercial Japanese Black cattle population of Ibaraki Prefecture. A total of 650 steers and 116 heifers for carcass and price-related traits, and 158 steers for FA composition traits were used in this study. Epistatic effects between pairs of the five genes were found in several traits. Alleles showing strain-specific differences in the five genes had significant single and epistatic effects in some traits. The data suggest that a TG-repeat polymorphism of the GHSR1a.5'UTR-(TG) n locus plays a central role in gene-gene epistatic interaction of FA composition traits in the adipose tissue of Japanese Black cattle. © 2017 Japanese Society of Animal Science.

Life-history strategies constrain invertebrate community tolerance to multiple stressors: A case study in the Ebro basin.

PubMed

Mondy, Cédric P; Muñoz, Isabel; Dolédec, Sylvain

2016-12-01

Multiple stressors constitute a serious threat to aquatic ecosystems, particularly in the Mediterranean region where water scarcity is likely to interact with other anthropogenic stressors. Biological traits potentially allow the unravelling of the effects of multiple stressors. However, thus far, trait-based approaches have failed to fully deliver on their promise and still lack strong predictive power when multiple stressors are present. We aimed to quantify specific community tolerances against six anthropogenic stressors and investigate the responses of the underlying macroinvertebrate biological traits and their combinations. We built and calibrated boosted regression tree models to predict community tolerances using multiple biological traits with a priori hypotheses regarding their individual responses to specific stressors. We analysed the combinations of traits underlying community tolerance and the effect of trait association on this tolerance. Our results validated the following three hypotheses: (i) the community tolerance models efficiently and robustly related trait combinations to stressor intensities and, to a lesser extent, to stressors related to the presence of dams and insecticides; (ii) the effects of traits on community tolerance not only depended on trait identity but also on the trait associations emerging at the community level from the co-occurrence of different traits in species; and (iii) the community tolerances and the underlying trait combinations were specific to the different stressors. This study takes a further step towards predictive tools in community ecology that consider combinations and associations of traits as the basis of stressor tolerance. Additionally, the community tolerance concept has potential application to help stream managers in the decision process regarding management options. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

A model of ecological and evolutionary consequences of color polymorphism.

PubMed

Forsman, Anders; Ahnesjö, Jonas; Caesar, Sofia; Karlsson, Magnus

2008-01-01

We summarize direct and indirect effects on fitness components of animal color pattern and present a synthesis of theories concerning the ecological and evolutionary dynamics of chromatic multiple niche polymorphisms. Previous endeavors have aimed primarily at identifying conditions that promote the evolution and maintenance of polymorphisms. We consider in a conceptual model also the reciprocal influence of color polymorphism on population processes and propose that polymorphism entails selective advantages that may promote the ecological success of polymorphic species. The model begins with an evolutionary branching event from mono- to polymorphic condition that, under the influence of correlational selection, is predicted to promote the evolution of physical integration of coloration and other traits (cf. multi-trait coevolution and complex phenotypes). We propose that the coexistence within a population of alternative ecomorphs with coadapted gene complexes promotes utilization of diverse environmental resources, population stability and persistence, colonization success, and range expansions, and enhances the evolutionary potential and speciation. Conversely, we predict polymorphic populations to be less vulnerable to environmental change and at lower risk of range contractions and extinctions compared with monomorphic populations. We offer brief suggestions as to how these falsifiable predictions may be tested.

Developmental temperature affects the expression of ejaculatory traits and the outcome of sperm competition in Callosobruchus maculatus.

PubMed

Vasudeva, R; Deeming, D C; Eady, P E

2014-09-01

The outcome of post-copulatory sexual selection is determined by a complex set of interactions between the primary reproductive traits of two or more males and their interactions with the reproductive traits of the female. Recently, a number of studies have shown the primary reproductive traits of both males and females express phenotypic plasticity in response to the thermal environment experienced during ontogeny. However, how plasticity in these traits affects the dynamics of sperm competition remains largely unknown. Here, we demonstrate plasticity in testes size, sperm size and sperm number in response to developmental temperature in the bruchid beetle Callosobruchus maculatus. Males reared at the highest temperature eclosed at the smallest body size and had the smallest absolute and relative testes size. Males reared at both the high- and low-temperature extremes produced both fewer and smaller sperm than males reared at intermediate temperatures. In the absence of sperm competition, developmental temperature had no effect on male fertility. However, under conditions of sperm competition, males reared at either temperature extreme were less competitive in terms of sperm offence (P(2)), whereas those reared at the lowest temperature were less competitive in terms of sperm defence (P(1)). This suggests the developmental pathways that regulate the phenotypic expression of these ejaculatory traits are subject to both natural and sexual selection: natural selection in the pre-ejaculatory environment and sexual selection in the post-ejaculatory environment. In nature, thermal heterogeneity during development is commonplace. Therefore, we suggest the interplay between ecology and development represents an important, yet hitherto underestimated component of male fitness via post-copulatory sexual selection. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

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

PubMed

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

2017-08-01

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

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

CONAN: copy number variation analysis software for genome-wide association studies

PubMed Central

2010-01-01

Background Genome-wide association studies (GWAS) based on single nucleotide polymorphisms (SNPs) revolutionized our perception of the genetic regulation of complex traits and diseases. Copy number variations (CNVs) promise to shed additional light on the genetic basis of monogenic as well as complex diseases and phenotypes. Indeed, the number of detected associations between CNVs and certain phenotypes are constantly increasing. However, while several software packages support the determination of CNVs from SNP chip data, the downstream statistical inference of CNV-phenotype associations is still subject to complicated and inefficient in-house solutions, thus strongly limiting the performance of GWAS based on CNVs. Results CONAN is a freely available client-server software solution which provides an intuitive graphical user interface for categorizing, analyzing and associating CNVs with phenotypes. Moreover, CONAN assists the evaluation process by visualizing detected associations via Manhattan plots in order to enable a rapid identification of genome-wide significant CNV regions. Various file formats including the information on CNVs in population samples are supported as input data. Conclusions CONAN facilitates the performance of GWAS based on CNVs and the visual analysis of calculated results. CONAN provides a rapid, valid and straightforward software solution to identify genetic variation underlying the 'missing' heritability for complex traits that remains unexplained by recent GWAS. The freely available software can be downloaded at http://genepi-conan.i-med.ac.at. PMID:20546565

Heritability maps of human face morphology through large-scale automated three-dimensional phenotyping

NASA Astrophysics Data System (ADS)

Tsagkrasoulis, Dimosthenis; Hysi, Pirro; Spector, Tim; Montana, Giovanni

2017-04-01

The human face is a complex trait under strong genetic control, as evidenced by the striking visual similarity between twins. Nevertheless, heritability estimates of facial traits have often been surprisingly low or difficult to replicate. Furthermore, the construction of facial phenotypes that correspond to naturally perceived facial features remains largely a mystery. We present here a large-scale heritability study of face geometry that aims to address these issues. High-resolution, three-dimensional facial models have been acquired on a cohort of 952 twins recruited from the TwinsUK registry, and processed through a novel landmarking workflow, GESSA (Geodesic Ensemble Surface Sampling Algorithm). The algorithm places thousands of landmarks throughout the facial surface and automatically establishes point-wise correspondence across faces. These landmarks enabled us to intuitively characterize facial geometry at a fine level of detail through curvature measurements, yielding accurate heritability maps of the human face (www.heritabilitymaps.info).

Mind over motor mapping: Driver response to changing vehicle dynamics.

PubMed

Bruno, Jennifer L; Baker, Joseph M; Gundran, Andrew; Harbott, Lene K; Stuart, Zachary; Piccirilli, Aaron M; Hosseini, S M Hadi; Gerdes, J Christian; Reiss, Allan L

2018-06-08

Improvements in vehicle safety require understanding of the neural systems that support the complex, dynamic task of real-world driving. We used functional near infrared spectroscopy (fNIRS) and pupilometry to quantify cortical and physiological responses during a realistic, simulated driving task in which vehicle dynamics were manipulated. Our results elucidate compensatory changes in driver behavior in response to changes in vehicle handling. We also describe associated neural and physiological responses under different levels of mental workload. The increased cortical activation we observed during the late phase of the experiment may indicate motor learning in prefrontal-parietal networks. Finally, relationships among cortical activation, steering control, and individual personality traits suggest that individual brain states and traits may be useful in predicting a driver's response to changes in vehicle dynamics. Results such as these will be useful for informing the design of automated safety systems that facilitate safe and supportive driver-car communication. © 2018 Wiley Periodicals, Inc.

Guess LOD approach: sufficient conditions for robustness.

PubMed

Williamson, J A; Amos, C I

1995-01-01

Analysis of genetic linkage between a disease and a marker locus requires specifying a genetic model describing both the inheritance pattern and the gene frequencies of the marker and trait loci. Misspecification of the genetic model is likely for etiologically complex diseases. In previous work we have shown through analytic studies that misspecifying the genetic model for disease inheritance does not lead to excess false-positive evidence for genetic linkage provided the genetic marker alleles of all pedigree members are known, or can be inferred without bias from the data. Here, under various selection or ascertainment schemes we extend these previous results to situations in which the genetic model for the marker locus may be incorrect. We provide sufficient conditions for the asymptotic unbiased estimation of the recombination fraction under the null hypothesis of no linkage, and also conditions for the limiting distribution of the likelihood ratio test for no linkage to be chi-squared. Through simulation studies we document some situations under which asymptotic bias can result when the genetic model is misspecified. Among those situations under which an excess of false-positive evidence for genetic linkage can be generated, the most common is failure to provide accurate estimates of the marker allele frequencies. We show that in most cases false-positive evidence for genetic linkage is unlikely to result solely from the misspecification of the genetic model for disease or trait inheritance.

Rapid adaptation to mammalian sociality via sexually selected traits

PubMed Central

2013-01-01

Background Laboratory studies show that the components of sexual selection (e.g., mate choice and intrasexual competition) can profoundly affect the development and fitness of offspring. Less is known, however, about the total effects of sexual selection on offspring in normal social conditions. Complex social networks, such as dominance hierarchies, regulate the opportunity for mating success, and are often missing from laboratory studies. Social selection is an extended view of sexual selection that incorporates competition during sexual and nonsexual interactions, and predicts complex evolutionary dynamics. Whether social selection improves or constrains offspring fitness is controversial. Results To identify fitness consequences of social selection, wild-derived mice that had bred under laboratory conditions for eight generations were re-introduced to naturalistic competition in enclosures for three consecutive generations (promiscuous line). In parallel, a control lineage bred in cages under random mate assignment (monogamous line). A direct competition experiment using second-generation animals revealed that promiscuous line males had greater reproductive success than monogamous line males (particularly during extra-territorial matings), in spite of higher mortality and equivalent success in social dominance and sperm competition. There were no major female fitness effects (though promiscuous line females had fewer litters than monogamous line females). This result suggested that selection primarily acted upon a sexually attractive male phenotype in the promiscuous line, a hypothesis we confirmed in female odor and mating preference trials. Conclusions We present novel evidence for the strength of sexual selection under normal social conditions, and show rapid male adaptation driven largely by sexual trait expression, with tradeoffs in survivorship and female fecundity. Re-introducing wild-derived mice to competition quickly uncovers sexually selected phenotypes otherwise lost in normal colony breeding. PMID:23577674

Kernel Machine SNP-set Testing under Multiple Candidate Kernels

PubMed Central

Wu, Michael C.; Maity, Arnab; Lee, Seunggeun; Simmons, Elizabeth M.; Harmon, Quaker E.; Lin, Xinyi; Engel, Stephanie M.; Molldrem, Jeffrey J.; Armistead, Paul M.

2013-01-01

Joint testing for the cumulative effect of multiple single nucleotide polymorphisms grouped on the basis of prior biological knowledge has become a popular and powerful strategy for the analysis of large scale genetic association studies. The kernel machine (KM) testing framework is a useful approach that has been proposed for testing associations between multiple genetic variants and many different types of complex traits by comparing pairwise similarity in phenotype between subjects to pairwise similarity in genotype, with similarity in genotype defined via a kernel function. An advantage of the KM framework is its flexibility: choosing different kernel functions allows for different assumptions concerning the underlying model and can allow for improved power. In practice, it is difficult to know which kernel to use a priori since this depends on the unknown underlying trait architecture and selecting the kernel which gives the lowest p-value can lead to inflated type I error. Therefore, we propose practical strategies for KM testing when multiple candidate kernels are present based on constructing composite kernels and based on efficient perturbation procedures. We demonstrate through simulations and real data applications that the procedures protect the type I error rate and can lead to substantially improved power over poor choices of kernels and only modest differences in power versus using the best candidate kernel. PMID:23471868

A randomised-controlled trial investigating potential underlying mechanisms of a functionality-based approach to improving women's body image.

PubMed

Alleva, Jessica M; Diedrichs, Phillippa C; Halliwell, Emma; Martijn, Carolien; Stuijfzand, Bobby G; Treneman-Evans, Georgia; Rumsey, Nichola

2018-06-01

Focusing on body functionality is a promising technique for improving women's body image. This study replicates prior research in a large novel sample, tests longer-term follow-up effects, and investigates underlying mechanisms of these effects (body complexity and body-self integration). British women (N = 261) aged 18-30 who wanted to improve their body image were randomised to Expand Your Horizon (three online body functionality writing exercises) or an active control. Trait body image was assessed at Pretest, Posttest, 1-week, and 1-month Follow-Up. To explore whether changes in body complexity and body-self integration 'buffer' the impact of negative body-related experiences, participants also completed beauty-ideal media exposure. Relative to the control, intervention participants experienced improved appearance satisfaction, functionality satisfaction, body appreciation, and body complexity at Posttest, and at both Follow-Ups. Neither body complexity nor body-self integration mediated intervention effects. Media exposure decreased state body satisfaction among intervention and control participants, but neither body complexity nor body-self integration moderated these effects. The findings underscore the value of focusing on body functionality for improving body image and show that effects persist one month post-intervention. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

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.

Trait coordination, mechanical behaviour and growth form plasticity of Amborella trichopoda under variation in canopy openness

PubMed Central

Trueba, Santiago; Isnard, Sandrine; Barthélémy, Daniel; Olson, Mark E.

2016-01-01

Understanding the distribution of traits across the angiosperm phylogeny helps map the nested hierarchy of features that characterize key nodes. Finding that Amborella is sister to the rest of the angiosperms has raised the question of whether it shares certain key functional trait characteristics, and plastic responses apparently widespread within the angiosperms at large. With this in mind, we test the hypothesis that local canopy openness induces plastic responses. We used this variation in morphological and functional traits to estimate the pervasiveness of trait scaling and leaf and stem economics. We studied the architecture of Amborella and how it varies under different degrees of canopy openness. We analyzed the coordination of 12 leaf and stem structural and functional traits, and the association of this covariation with differing morphologies. The Amborella habit is made up of a series of sympodial modules that vary in size and branching pattern under different canopy openness. Amborella stems vary from self-supporting to semi-scandent. Changes in stem elongation and leaf size in Amborella produce distinct morphologies under different light environments. Correlations were found between most leaf and stem functional traits. Stem tissue rigidity decreased with increasing canopy openness. Despite substantial modulation of leaf size and leaf mass per area by light availability, branches in different light environments had similar leaf area-stem size scaling. The sympodial growth observed in Amborella could point to an angiosperm synapomorphy. Our study provides evidence of intraspecific coordination between leaf and stem economic spectra. Trait variation along these spectra is likely adaptive under different light environments and is consistent with these plastic responses having been present in the angiosperm common ancestor. PMID:27672131

Experimental evidence that the Ornstein-Uhlenbeck model best describes the evolution of leaf litter decomposability.

PubMed

Pan, Xu; Cornelissen, Johannes H C; Zhao, Wei-Wei; Liu, Guo-Fang; Hu, Yu-Kun; Prinzing, Andreas; Dong, Ming; Cornwell, William K

2014-09-01

Leaf litter decomposability is an important effect trait for ecosystem functioning. However, it is unknown how this effect trait evolved through plant history as a leaf 'afterlife' integrator of the evolution of multiple underlying traits upon which adaptive selection must have acted. Did decomposability evolve in a Brownian fashion without any constraints? Was evolution rapid at first and then slowed? Or was there an underlying mean-reverting process that makes the evolution of extreme trait values unlikely? Here, we test the hypothesis that the evolution of decomposability has undergone certain mean-reverting forces due to strong constraints and trade-offs in the leaf traits that have afterlife effects on litter quality to decomposers. In order to test this, we examined the leaf litter decomposability and seven key leaf traits of 48 tree species in the temperate area of China and fitted them to three evolutionary models: Brownian motion model (BM), Early burst model (EB), and Ornstein-Uhlenbeck model (OU). The OU model, which does not allow unlimited trait divergence through time, was the best fit model for leaf litter decomposability and all seven leaf traits. These results support the hypothesis that neither decomposability nor the underlying traits has been able to diverge toward progressively extreme values through evolutionary time. These results have reinforced our understanding of the relationships between leaf litter decomposability and leaf traits in an evolutionary perspective and may be a helpful step toward reconstructing deep-time carbon cycling based on taxonomic composition with more confidence.

Trypanotolerance in N’Dama x Boran crosses under natural trypanosome challenge: effect of test-year environment, gender, and breed composition

PubMed Central

2012-01-01

Background Trypanosomosis, a protozoal disease affecting livestock, transmitted by Glossina (tsetse) flies is a major constraint to agricultural production in Sub-Saharan Africa. It is accepted that utilization of the native trypanotolerance exhibited in some of the African cattle breeds to improve trypanotolerance of more productive but susceptible breeds, will offer a cost effective and sustainable solution to the problem. The success of this approach is based on the premise that quantitative trait loci previously identified under relatively controlled situations confer useful trypanotolerance under natural field situations. As part of a study to authenticate this hypothesis, a population of 192 cattle, consisting of six batches of N’Dama and Kenya-Boran backcross animals [(N’Dama x Kenya-Boran) x Kenya-Boran] born over the period 2002 to 2006 was constructed. Some of the batches also included pure Kenya-Boran cattle, or N’Dama x Kenya- Boran F1 animals. Each batch was exposed as yearlings to natural field trypanosomosis challenge over a period of about one year; the entire challenge period extending from December 2003 to June 2007. Performance of the animals was evaluated by weekly or biweekly measurements of body weight, packed blood cell volume (PCV), parasitemia score, and number of trypanocide treatments. From these basic data, 49 phenotypes were constructed reflecting dynamics of body weight, packed cell volume (PCV) and parasitemia under challenge. Results Females were distinctly more trypanotolerant than males. F1, backcross and pure Kenya- Boran animals ranked in that order with respect to trypanotolerance. Overall batch effects were highly significant (p<0.001) for most traits, and were generally more significant than the gender or genetic type effects. The superior trypanotolerance of the F1 animals was expressed in all three components of animal defense strategies against pathogens: Avoidance resistance, and tolerance. Conclusions The results show that trypanotolerance derived from the N’Dama is expressed under field conditions; and that the trait is primarily additive in nature, being expressed in heterozygous condition and in a three-quarters Boran genetic background. The results further, underscore the complexity of the trait in the field manifesting all three host disease-control strategies, and show the importance of gender and local environmental conditions in determining response to challenge. PMID:23075408

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

PubMed

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

2015-04-01

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

Phenotypic integration among trabecular and cortical bone traits establishes mechanical functionality of inbred mouse vertebrae.

PubMed

Tommasini, Steven M; Hu, Bin; Nadeau, Joseph H; Jepsen, Karl J

2009-04-01

Conventional approaches to identifying quantitative trait loci (QTLs) regulating bone mass and fragility are limited because they examine cortical and trabecular traits independently. Prior work examining long bones from young adult mice and humans indicated that skeletal traits are functionally related and that compensatory interactions among morphological and compositional traits are critical for establishing mechanical function. However, it is not known whether trait covariation (i.e., phenotypic integration) also is important for establishing mechanical function in more complex, corticocancellous structures. Covariation among trabecular, cortical, and compositional bone traits was examined in the context of mechanical functionality for L(4) vertebral bodies across a panel of 16-wk-old female AXB/BXA recombinant inbred (RI) mouse strains. The unique pattern of randomization of the A/J and C57BL/6J (B6) genome among the RI panel provides a powerful tool that can be used to measure the tendency for different traits to covary and to study the biology of complex traits. We tested the hypothesis that genetic variants affecting vertebral size and mass are buffered by changes in the relative amounts of cortical and trabecular bone and overall mineralization. Despite inheriting random sets of A/J and B6 genomes, the RI strains inherited nonrandom sets of cortical and trabecular bone traits. Path analysis, which is a multivariate analysis that shows how multiple traits covary simultaneously when confounding variables like body size are taken into consideration, showed that RI strains that tended to have smaller vertebrae relative to body size achieved mechanical functionality by increasing mineralization and the relative amounts of cortical and trabecular bone. The interdependence among corticocancellous traits in the vertebral body indicated that variation in trabecular bone traits among inbred mouse strains, which is often thought to arise from genetic factors, is also determined in part by the adaptive response to variation in traits describing the cortical shell. The covariation among corticocancellous traits has important implications for genetic analyses and for interpreting the response of bone to genetic and environmental perturbations.

Fine Tuning Gene Expression: The Epigenome

PubMed Central

Mohtat, Davoud; Susztak, Katalin

2011-01-01

An epigenetic trait is a stably inherited phenotype resulting from changes in a chromosome without alterations in the DNA sequence. Epigenetic modifications, such as; DNA methylation, together with covalent modification of histones, are thought to alter chromatin density and accessibility of the DNA to cellular machinery, thereby modulating the transcriptional potential of the underlying DNA sequence. As epigenetic marks under environmental influence, epigenetics provides an added layer of variation that might mediate the relationship between genotype and internal and external environmental factors. Integration of our knowledge in genetics, epigenomics and genomics with the use of systems biology tools may present investigators with new powerful tools to study many complex human diseases such as kidney disease. PMID:21044758

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.

Using IRT Trait Estimates versus Summated Scores in Predicting Outcomes

ERIC Educational Resources Information Center

Xu, Ting; Stone, Clement A.

2012-01-01

It has been argued that item response theory trait estimates should be used in analyses rather than number right (NR) or summated scale (SS) scores. Thissen and Orlando postulated that IRT scaling tends to produce trait estimates that are linearly related to the underlying trait being measured. Therefore, IRT trait estimates can be more useful…

Trait plasticity, not values, best corresponds with woodland plant success in novel and manipulated habitats

Treesearch

Robert J. Warren; Jeffrey K. Lake

2012-01-01

Aims: The clustering of plants with similar leaf traits along environmental gradients may arise from adaptation as well as acclimation to heterogeneous habitat conditions. Determining the forces that shape plant leaf traits requires both linking variation in trait morphology with abiotic gradients and linking that trait variation with plant performance under varying...

How does epistasis influence the response to selection?

PubMed Central

Barton, N H

2017-01-01

Much of quantitative genetics is based on the ‘infinitesimal model', under which selection has a negligible effect on the genetic variance. This is typically justified by assuming a very large number of loci with additive effects. However, it applies even when genes interact, provided that the number of loci is large enough that selection on each of them is weak relative to random drift. In the long term, directional selection will change allele frequencies, but even then, the effects of epistasis on the ultimate change in trait mean due to selection may be modest. Stabilising selection can maintain many traits close to their optima, even when the underlying alleles are weakly selected. However, the number of traits that can be optimised is apparently limited to ~4Ne by the ‘drift load', and this is hard to reconcile with the apparent complexity of many organisms. Just as for the mutation load, this limit can be evaded by a particular form of negative epistasis. A more robust limit is set by the variance in reproductive success. This suggests that selection accumulates information most efficiently in the infinitesimal regime, when selection on individual alleles is weak, and comparable with random drift. A review of evidence on selection strength suggests that although most variance in fitness may be because of alleles with large Nes, substantial amounts of adaptation may be because of alleles in the infinitesimal regime, in which epistasis has modest effects. PMID:27901509

How does epistasis influence the response to selection?

PubMed

Barton, N H

2017-01-01

Much of quantitative genetics is based on the 'infinitesimal model', under which selection has a negligible effect on the genetic variance. This is typically justified by assuming a very large number of loci with additive effects. However, it applies even when genes interact, provided that the number of loci is large enough that selection on each of them is weak relative to random drift. In the long term, directional selection will change allele frequencies, but even then, the effects of epistasis on the ultimate change in trait mean due to selection may be modest. Stabilising selection can maintain many traits close to their optima, even when the underlying alleles are weakly selected. However, the number of traits that can be optimised is apparently limited to ~4N e by the 'drift load', and this is hard to reconcile with the apparent complexity of many organisms. Just as for the mutation load, this limit can be evaded by a particular form of negative epistasis. A more robust limit is set by the variance in reproductive success. This suggests that selection accumulates information most efficiently in the infinitesimal regime, when selection on individual alleles is weak, and comparable with random drift. A review of evidence on selection strength suggests that although most variance in fitness may be because of alleles with large N e s, substantial amounts of adaptation may be because of alleles in the infinitesimal regime, in which epistasis has modest effects.

Microarray-assisted fine-mapping of quantitative trait loci for cold tolerance in rice.

PubMed

Liu, Fengxia; Xu, Wenying; Song, Qian; Tan, Lubin; Liu, Jiayong; Zhu, Zuofeng; Fu, Yongcai; Su, Zhen; Sun, Chuanqing

2013-05-01

Many important agronomic traits, including cold stress resistance, are complex and controlled by quantitative trait loci (QTLs). Isolation of these QTLs will greatly benefit the agricultural industry but it is a challenging task. This study explored an integrated strategy by combining microarray with QTL-mapping in order to identify cold-tolerant QTLs from a cold-tolerant variety IL112 at early-seedling stage. All the early seedlings of IL112 survived normally for 9 d at 4-5°C, while Guichao2 (GC2), an indica cultivar, died after 4 d under the same conditions. Using the F2:3 population derived from the progeny of GC2 and IL112, we identified seven QTLs for cold tolerance. Furthermore, we performed Affymetrix rice whole-genome array hybridization and obtained the expression profiles of IL112 and GC2 under both low-temperature and normal conditions. Four genes were selected as cold QTL-related candidates, based on microarray data mining and QTL-mapping. One candidate gene, LOC_Os07g22494, was shown to be highly associated with cold tolerance in a number of rice varieties and in the F2:3 population, and its overexpression transgenic rice plants displayed strong tolerance to low temperature at early-seedling stage. The results indicated that overexpression of this gene (LOC_Os07g22494) could increase cold tolerance in rice seedlings. Therefore, this study provides a promising strategy for identifying candidate genes in defined QTL regions.

Selection in action: dissecting the molecular underpinnings of the increasing muscle mass of Belgian Blue Cattle.

PubMed

Druet, Tom; Ahariz, Naima; Cambisano, Nadine; Tamma, Nico; Michaux, Charles; Coppieters, Wouter; Charlier, Carole; Georges, Michel

2014-09-17

Belgian Blue cattle are famous for their exceptional muscular development or "double-muscling". This defining feature emerged following the fixation of a loss-of-function variant in the myostatin gene in the eighties. Since then, sustained selection has further increased muscle mass of Belgian Blue animals to a comparable extent. In the present paper, we study the genetic determinants of this second wave of muscle growth. A scan for selective sweeps did not reveal the recent fixation of another allele with major effect on muscularity. However, a genome-wide association study identified two genome-wide significant and three suggestive quantitative trait loci (QTL) affecting specific muscle groups and jointly explaining 8-21% of the heritability. The top two QTL are caused by presumably recent mutations on unique haplotypes that have rapidly risen in frequency in the population. While one appears on its way to fixation, the ascent of the other is compromised as the likely underlying MRC2 mutation causes crooked tail syndrome in homozygotes. Genomic prediction models indicate that the residual additive variance is largely polygenic. Contrary to complex traits in humans which have a near-exclusive polygenic architecture, muscle mass in beef cattle (as other production traits under directional selection), appears to be controlled by (i) a handful of recent mutations with large effect that rapidly sweep through the population, and (ii) a large number of presumably older variants with very small effects that rise slowly in the population (polygenic adaptation).

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

PubMed

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

2016-04-01

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

Genetic, Genomic, and Breeding Approaches to Further Explore Kernel Composition Traits and Grain Yield in Maize

ERIC Educational Resources Information Center

Da Silva, Helena Sofia Pereira

2009-01-01

Maize ("Zea mays L.") is a model species well suited for the dissection of complex traits which are often of commercial value. The purpose of this research was to gain a deeper understanding of the genetic control of maize kernel composition traits starch, protein, and oil concentration, and also kernel weight and grain yield. Germplasm with…

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

PubMed

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

2016-09-30

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

Levels and domains in personality: an introduction.

PubMed

Emmons, R A

1995-09-01

This special issue is centered around the problem of levels and domains in personality functioning. What kind of constructs--and at what levels and in what domains--are needed to understand what a person is like? To account for the complexity and scope of human lives, personality psychologists have traditionally put forth lists and taxonomies of factors, features, and variables that must be taken into consideration in formulating an adequate psychological portrait of the whole person. The five-factor model of personality traits has recently been offered as a comprehensive framework; however, critical analyses of the trait concept have revealed the limitations of a trait-based model of personality. Recognizing that the concept of trait is indispensable to a vital psychology of personality, this special issue aims to (a) communicate recent developments and organizational frameworks for understanding the person at multiple levels and in varied domains, and (b) articulate and elaborate units of analysis that, when combined with trait assessments, yield a psychology of personality that is commensurate with the complexity of individual functioning and that offers greater potential for the attainment of the original goals of the discipline.

Prediction of human adaptation and performance in underwater environments.

PubMed

Colodro Plaza, Joaquín; Garcés de los Fayos Ruiz, Enrique J; López García, Juan J; Colodro Conde, Lucía

2014-01-01

Environmental stressors require the professional diver to undergo a complex process of psychophysiological adaptation in order to overcome the demands of an extreme environment and carry out effective and efficient work under water. The influence of cognitive and personality traits in predicting underwater performance and adaptation has been a common concern for diving psychology, and definitive conclusions have not been reached. In this ex post facto study, psychological and academic data were analyzed from a large sample of personnel participating in scuba diving courses carried out in the Spanish Navy Diving Center. In order to verify the relevance of individual differences in adaptation to a hostile environment, we evaluated the predictive validity of general mental ability and personality traits with regression techniques. The data indicated the existence of psychological variables that can predict the performance ( R² = .30, p <.001) and adaptation ( R²(N) = .51, p <.001) of divers in underwater environment. These findings support the hypothesis that individual differences are related to the probability of successful adaptation and effective performance in professional diving. These results also verify that dispositional traits play a decisive role in diving training and are significant factors in divers' psychological fitness.

Effect of trait anxiety on prefrontal control mechanisms during emotional conflict.

PubMed

Comte, Magali; Cancel, Aïda; Coull, Jennifer T; Schön, Daniele; Reynaud, Emmanuelle; Boukezzi, Sarah; Rousseau, Pierre-François; Robert, Gabriel; Khalfa, Stéphanie; Guedj, Eric; Blin, Olivier; Weinberger, Daniel R; Fakra, Eric

2015-06-01

Converging evidence points to a link between anxiety proneness and altered emotional functioning, including threat-related biases in selective attention and higher susceptibility to emotionally ambiguous stimuli. However, during these complex emotional situations, it remains unclear how trait anxiety affects the engagement of the prefrontal emotional control system and particularly the anterior cingulate cortex (ACC), a core region at the intersection of the limbic and prefrontal systems. Using an emotional conflict task and functional magnetic resonance imaging (fMRI), we investigated in healthy subjects the relations between trait anxiety and both regional activity and functional connectivity (psychophysiological interaction) of the ACC. Higher levels of anxiety were associated with stronger task-related activation in ACC but with reduced functional connectivity between ACC and lateral prefrontal cortex (LPFC). These results support the hypothesis that when one is faced with emotionally incompatible information, anxiety leads to inefficient high-order control, characterized by insufficient ACC-LPFC functional coupling and increases, possibly compensatory, in activation of ACC. Our findings provide a deeper understanding of the pathophysiology of the neural circuitry underlying anxiety and may offer potential treatment markers for anxiety disorders. © 2015 Wiley Periodicals, Inc.

The curvilinear relationship between work pressure and momentary task performance: the role of state and trait core self-evaluations.

PubMed

Hofmans, Joeri; Debusscher, Jonas; Dóci, Edina; Spanouli, Andromachi; De Fruyt, Filip

2015-01-01

Whereas several studies have demonstrated that core self-evaluations (CSE)-or one's appraisals about one's own self-worth, capabilities, and competences-relate to job outcomes, less is known about the mechanisms underlying these relationships. In the present study, we address this issue by examining the role of within- and between-person variation in CSE in the relationship between work pressure and task performance. We hypothesized that (a) work pressure relates to task performance in a curvilinear way, (b) state CSE mediates the curvilinear relationship between work pressure and task performance, and (c) the relationship between work pressure and state CSE is moderated by trait CSE. Our hypotheses were tested via a 10-day daily diary study with 55 employees in which trait CSE was measured at baseline, while work pressure, task performance, and state CSE were assessed on a daily basis. Bayesian multilevel path analysis showed that work pressure affects task performance via state CSE, with state CSE increasing as long as the employee feels that (s)he is able to handle the work pressure, while it decreases when the level of work pressure exceeds the employees' coping abilities. Moreover, we found that for people low on trait CSE, the depleting effect of work pressure via state CSE happens for low levels of work pressure, while for people high in trait CSE the depleting effect is located at high levels of work pressure. Together, our findings suggest that the impact of work pressure on task performance is driven by a complex interplay of between- and within-person differences in CSE.

Can diversity in root architecture explain plant water use efficiency? A modeling study

PubMed Central

Tron, Stefania; Bodner, Gernot; Laio, Francesco; Ridolfi, Luca; Leitner, Daniel

2015-01-01

Drought stress is a dominant constraint to crop production. Breeding crops with adapted root systems for effective uptake of water represents a novel strategy to increase crop drought resistance. Due to complex interaction between root traits and high diversity of hydrological conditions, modeling provides important information for trait based selection. In this work we use a root architecture model combined with a soil-hydrological model to analyze whether there is a root system ideotype of general adaptation to drought or water uptake efficiency of root systems is a function of specific hydrological conditions. This was done by modeling transpiration of 48 root architectures in 16 drought scenarios with distinct soil textures, rainfall distributions, and initial soil moisture availability. We find that the efficiency in water uptake of root architecture is strictly dependent on the hydrological scenario. Even dense and deep root systems are not superior in water uptake under all hydrological scenarios. Our results demonstrate that mere architectural description is insufficient to find root systems of optimum functionality. We find that in environments with sufficient rainfall before the growing season, root depth represents the key trait for the exploration of stored water, especially in fine soils. Root density, instead, especially near the soil surface, becomes the most relevant trait for exploiting soil moisture when plant water supply is mainly provided by rainfall events during the root system development. We therefore concluded that trait based root breeding has to consider root systems with specific adaptation to the hydrology of the target environment. PMID:26412932

Can diversity in root architecture explain plant water use efficiency? A modeling study.

PubMed

Tron, Stefania; Bodner, Gernot; Laio, Francesco; Ridolfi, Luca; Leitner, Daniel

2015-09-24

Drought stress is a dominant constraint to crop production. Breeding crops with adapted root systems for effective uptake of water represents a novel strategy to increase crop drought resistance. Due to complex interaction between root traits and high diversity of hydrological conditions, modeling provides important information for trait based selection. In this work we use a root architecture model combined with a soil-hydrological model to analyze whether there is a root system ideotype of general adaptation to drought or water uptake efficiency of root systems is a function of specific hydrological conditions. This was done by modeling transpiration of 48 root architectures in 16 drought scenarios with distinct soil textures, rainfall distributions, and initial soil moisture availability. We find that the efficiency in water uptake of root architecture is strictly dependent on the hydrological scenario. Even dense and deep root systems are not superior in water uptake under all hydrological scenarios. Our results demonstrate that mere architectural description is insufficient to find root systems of optimum functionality. We find that in environments with sufficient rainfall before the growing season, root depth represents the key trait for the exploration of stored water, especially in fine soils. Root density, instead, especially near the soil surface, becomes the most relevant trait for exploiting soil moisture when plant water supply is mainly provided by rainfall events during the root system development. We therefore concluded that trait based root breeding has to consider root systems with specific adaptation to the hydrology of the target environment.

Taking off the training wheels: the properties of a dynamic vegetation model without climate envelopes

DOE PAGES

Fisher, R. A.; Muszala, S.; Verteinstein, M.; ...

2015-04-29

We describe an implementation of the Ecosystem Demography (ED) concept in the Community Land Model. The structure of CLM(ED) and the physiological and structural modifications applied to the CLM are presented. A major motivation of this development is to allow the prediction of biome boundaries directly from plant physiological traits via their competitive interactions. Here we investigate the performance of the model for an example biome boundary in Eastern North America. We explore the sensitivity of the predicted biome boundaries and ecosystem properties to the variation of leaf properties determined by the parameter space defined by the GLOPNET global leafmore » trait database. Further, we investigate the impact of four sequential alterations to the structural assumptions in the model governing the relative carbon economy of deciduous and evergreen plants. The default assumption is that the costs and benefits of deciduous vs. evergreen leaf strategies, in terms of carbon assimilation and expenditure, can reproduce the geographical structure of biome boundaries and ecosystem functioning. We find some support for this assumption, but only under particular combinations of model traits and structural assumptions. Many questions remain regarding the preferred methods for deployment of plant trait information in land surface models. In some cases, plant traits might best be closely linked with each other, but we also find support for direct linkages to environmental conditions. We advocate for intensified study of the costs and benefits of plant life history strategies in different environments, and for the increased use of parametric and structural ensembles in the development and analysis of complex vegetation models.« less

Taking off the training wheels: the properties of a dynamic vegetation model without climate envelopes

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

Fisher, R. A.; Muszala, S.; Verteinstein, M.

We describe an implementation of the Ecosystem Demography (ED) concept in the Community Land Model. The structure of CLM(ED) and the physiological and structural modifications applied to the CLM are presented. A major motivation of this development is to allow the prediction of biome boundaries directly from plant physiological traits via their competitive interactions. Here we investigate the performance of the model for an example biome boundary in Eastern North America. We explore the sensitivity of the predicted biome boundaries and ecosystem properties to the variation of leaf properties determined by the parameter space defined by the GLOPNET global leafmore » trait database. Further, we investigate the impact of four sequential alterations to the structural assumptions in the model governing the relative carbon economy of deciduous and evergreen plants. The default assumption is that the costs and benefits of deciduous vs. evergreen leaf strategies, in terms of carbon assimilation and expenditure, can reproduce the geographical structure of biome boundaries and ecosystem functioning. We find some support for this assumption, but only under particular combinations of model traits and structural assumptions. Many questions remain regarding the preferred methods for deployment of plant trait information in land surface models. In some cases, plant traits might best be closely linked with each other, but we also find support for direct linkages to environmental conditions. We advocate for intensified study of the costs and benefits of plant life history strategies in different environments, and for the increased use of parametric and structural ensembles in the development and analysis of complex vegetation models.« less

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.

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

PubMed Central

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

2017-01-01

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

Partially incorrect fossil data augment analyses of discrete trait evolution in living species.

PubMed

Puttick, Mark N

2016-08-01

Ancestral state reconstruction of discrete character traits is often vital when attempting to understand the origins and homology of traits in living species. The addition of fossils has been shown to alter our understanding of trait evolution in extant taxa, but researchers may avoid using fossils alongside extant species if only few are known, or if the designation of the trait of interest is uncertain. Here, I investigate the impacts of fossils and incorrectly coded fossils in the ancestral state reconstruction of discrete morphological characters under a likelihood model. Under simulated phylogenies and data, likelihood-based models are generally accurate when estimating ancestral node values. Analyses with combined fossil and extant data always outperform analyses with extant species alone, even when around one quarter of the fossil information is incorrect. These results are especially pronounced when model assumptions are violated, such as when there is a trend away from the root value. Fossil data are of particular importance when attempting to estimate the root node character state. Attempts should be made to include fossils in analysis of discrete traits under likelihood, even if there is uncertainty in the fossil trait data. © 2016 The Authors.

The Impact of the Emerging Genomics Data on the Management of Agerelated Phenotypes in the Context of Cellular Senescence.

PubMed

Montesanto, Alberto; Geracitano, Silvana; Garasto, Sabrina; Fusco, Sergio; Lattanzio, Fabrizia; Passarino, Giuseppe; Corsonello, Andrea

2016-01-01

Before the last decade, attempts to identify the genetic factors involved in the susceptibility to age-related complex diseases such as cardiovascular disease, diabetes and cancer had very limited success. Recently, two important advancements have provided new opportunities to improve our knowledge in this field. Firstly, it has emerged the concept of studying the molecular mechanisms underlying the age related decline of the organism (such as cellular senescence), rather than the genetics of single disorders. In addition, advances in DNA technology have uncovered an incredible number of common susceptibility variants for several complex traits. Despite these progresses, the translation of these discoveries into clinical practice has been very difficult. To date, several attempts in translating genomics to medicine are being carried out to look for the best way by which genomic discoveries may improve our understanding of fundamental issues in the prediction and prevention of some complex diseases. The successful strategy seems to be testing simultaneously multiple susceptibility variants in combination with traditional risk factors. In fact, such approach showed that genetic factors substantially improve the prediction of complex diseases especially for coronary heart disease and prostate cancer, making possible appropriate behavioural and medical interventions. In the future, the identification of new genetic variants and their inclusion into current risk profile models will probably improve the discrimination power of these models for other complex diseases such as type 2 diabetes mellitus and breast cancer. On the other hand, for traits with low heritability, this improvement will probably be negligible, and this will urge further researches on the role played by traditional and newly discovered non-genetic risk factors.

Applications of machine learning and data mining methods to detect associations of rare and common variants with complex traits.

PubMed

Lu, Ake Tzu-Hui; Austin, Erin; Bonner, Ashley; Huang, Hsin-Hsiung; Cantor, Rita M

2014-09-01

Machine learning methods (MLMs), designed to develop models using high-dimensional predictors, have been used to analyze genome-wide genetic and genomic data to predict risks for complex traits. We summarize the results from six contributions to our Genetic Analysis Workshop 18 working group; these investigators applied MLMs and data mining to analyses of rare and common genetic variants measured in pedigrees. To develop risk profiles, group members analyzed blood pressure traits along with single-nucleotide polymorphisms and rare variant genotypes derived from sequence and imputation analyses in large Mexican American pedigrees. Supervised MLMs included penalized regression with varying penalties, support vector machines, and permanental classification. Unsupervised MLMs included sparse principal components analysis and sparse graphical models. Entropy-based components analyses were also used to mine these data. None of the investigators fully capitalized on the genetic information provided by the complete pedigrees. Their approaches either corrected for the nonindependence of the individuals within the pedigrees or analyzed only those who were independent. Some methods allowed for covariate adjustment, whereas others did not. We evaluated these methods using a variety of metrics. Four contributors conducted primary analyses on the real data, and the other two research groups used the simulated data with and without knowledge of the underlying simulation model. One group used the answers to the simulated data to assess power and type I errors. Although the MLMs applied were substantially different, each research group concluded that MLMs have advantages over standard statistical approaches with these high-dimensional data. © 2014 WILEY PERIODICALS, INC.

GiNA, an Efficient and High-Throughput Software for Horticultural Phenotyping

PubMed Central

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

2016-01-01

Traditional methods for trait phenotyping have been a bottleneck for research in many crop species due to their intensive labor, high cost, complex implementation, lack of reproducibility and propensity to subjective bias. Recently, multiple high-throughput phenotyping platforms have been developed, but most of them are expensive, species-dependent, complex to use, and available only for major crops. To overcome such limitations, we present the open-source software GiNA, which is a simple and free tool for measuring horticultural traits such as shape- and color-related parameters of fruits, vegetables, and seeds. GiNA is multiplatform software available in both R and MATLAB® programming languages and uses conventional images from digital cameras with minimal requirements. It can process up to 11 different horticultural morphological traits such as length, width, two-dimensional area, volume, projected skin, surface area, RGB color, among other parameters. Different validation tests produced highly consistent results under different lighting conditions and camera setups making GiNA a very reliable platform for high-throughput phenotyping. In addition, five-fold cross validation between manually generated and GiNA measurements for length and width in cranberry fruits were 0.97 and 0.92. In addition, the same strategy yielded prediction accuracies above 0.83 for color estimates produced from images of cranberries analyzed with GiNA compared to total anthocyanin content (TAcy) of the same fruits measured with the standard methodology of the industry. Our platform provides a scalable, easy-to-use and affordable tool for massive acquisition of phenotypic data of fruits, seeds, and vegetables. PMID:27529547

GiNA, an Efficient and High-Throughput Software for Horticultural Phenotyping.

PubMed

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

2016-01-01

Traditional methods for trait phenotyping have been a bottleneck for research in many crop species due to their intensive labor, high cost, complex implementation, lack of reproducibility and propensity to subjective bias. Recently, multiple high-throughput phenotyping platforms have been developed, but most of them are expensive, species-dependent, complex to use, and available only for major crops. To overcome such limitations, we present the open-source software GiNA, which is a simple and free tool for measuring horticultural traits such as shape- and color-related parameters of fruits, vegetables, and seeds. GiNA is multiplatform software available in both R and MATLAB® programming languages and uses conventional images from digital cameras with minimal requirements. It can process up to 11 different horticultural morphological traits such as length, width, two-dimensional area, volume, projected skin, surface area, RGB color, among other parameters. Different validation tests produced highly consistent results under different lighting conditions and camera setups making GiNA a very reliable platform for high-throughput phenotyping. In addition, five-fold cross validation between manually generated and GiNA measurements for length and width in cranberry fruits were 0.97 and 0.92. In addition, the same strategy yielded prediction accuracies above 0.83 for color estimates produced from images of cranberries analyzed with GiNA compared to total anthocyanin content (TAcy) of the same fruits measured with the standard methodology of the industry. Our platform provides a scalable, easy-to-use and affordable tool for massive acquisition of phenotypic data of fruits, seeds, and vegetables.

Enhancing GTEx by bridging the gaps between genotype, gene expression, and disease.

PubMed

2017-12-01

Genetic variants have been associated with myriad molecular phenotypes that provide new insight into the range of mechanisms underlying genetic traits and diseases. Identifying any particular genetic variant's cascade of effects, from molecule to individual, requires assaying multiple layers of molecular complexity. We introduce the Enhancing GTEx (eGTEx) project that extends the GTEx project to combine gene expression with additional intermediate molecular measurements on the same tissues to provide a resource for studying how genetic differences cascade through molecular phenotypes to impact human health.

Exploring the Estimation of Examinee Locations Using Multidimensional Latent Trait Models under Different Distributional Assumptions

ERIC Educational Resources Information Center

Jang, Hyesuk

2014-01-01

This study aims to evaluate a multidimensional latent trait model to determine how well the model works in various empirical contexts. Contrary to the assumption of these latent trait models that the traits are normally distributed, situations in which the latent trait is not shaped with a normal distribution may occur (Sass et al, 2008; Woods…

Effect of shading intensity on morphological and color traits, and chemical components of new tea (Camellia sinensis L.) shoots under direct covering cultivation.

PubMed

Sano, Tomohito; Horie, Hideki; Matsunaga, Akiko; Hirono, Yuhei

2018-05-02

Use of covering cultivation to shade tea (Camellia sinensis L.) trees to produce high-quality, high-priced green tea has recently increased in Japan. Knowledge of shading effects on morphological and color traits, and chemical components of new tea shoots is important for product quality and productivity. We assessed these traits of tea shoots and their relationships under covering cultivation of various radiation intensities. Leaf thickness, LMA (leaf mass per area), and leaf density of new tea leaves were smaller under covering culture than under open-field culture. SPAD values and chlorophyll contents were larger under covering culture than under open culture. The derived exponential equation for estimating chlorophyll contents from SPAD values was improved by considering leaf thickness. Covering culture decreased EC (epicatechin) and EGC (epigallocatechin) contents, and increased theanine and caffeine contents. Principal component analysis on shoot and leaf traits indicated that LMA, and chlorophyll, EC, and EGC contents were strongly associated with shading effects. Morphological and color traits, and chemical components of new tea shoots and leaves varied depending on radiation intensity, shoot growth, and cropping season. These findings are useful for covering cultivation with high quality and high productivity in tea gardens. This article is protected by copyright. All rights reserved.

Trait Anxiety Has Effect on Decision Making under Ambiguity but Not Decision Making under Risk

PubMed Central

Zhang, Long; Wang, Kai; Zhu, Chunyan; Yu, Fengqiong; Chen, Xingui

2015-01-01

Previous studies have reported that trait anxiety (TA) affects decision making. However, results remain largely inconsistent across studies. The aim of the current study was to further address the interaction between TA and decision making. 304 subjects without depression from a sample consisting of 642 participants were grouped into high TA (HTA), medium TA (MTA) and low TA (LTA) groups based on their TA scores from State Trait Anxiety Inventory. All subjects were assessed with the Iowa Gambling Task (IGT) that measures decision making under ambiguity and the Game of Dice Task (GDT) that measures decision making under risk. While the HTA and LTA groups performed worse on the IGT compared to the MTA group, performances on the GDT between the three groups did not differ. Furthermore, the LTA and HTA groups showed different individual deck level preferences in the IGT: the former showed a preference for deck B indicating that these subjects focused more on the magnitude of rewards, and the latter showed a preference for deck A indicating significant decision making impairment. Our findings suggest that trait anxiety has effect on decision making under ambiguity but not decision making under risk and different levels of trait anxiety related differently to individual deck level preferences in the IGT. PMID:26000629

Detecting Hidden Diversification Shifts in Models of Trait-Dependent Speciation and Extinction.

PubMed

Beaulieu, Jeremy M; O'Meara, Brian C

2016-07-01

The distribution of diversity can vary considerably from clade to clade. Attempts to understand these patterns often employ state-dependent speciation and extinction models to determine whether the evolution of a particular novel trait has increased speciation rates and/or decreased extinction rates. It is still unclear, however, whether these models are uncovering important drivers of diversification, or whether they are simply pointing to more complex patterns involving many unmeasured and co-distributed factors. Here we describe an extension to the popular state-dependent speciation and extinction models that specifically accounts for the presence of unmeasured factors that could impact diversification rates estimated for the states of any observed trait, addressing at least one major criticism of BiSSE (Binary State Speciation and Extinction) methods. Specifically, our model, which we refer to as HiSSE (Hidden State Speciation and Extinction), assumes that related to each observed state in the model are "hidden" states that exhibit potentially distinct diversification dynamics and transition rates than the observed states in isolation. We also demonstrate how our model can be used as character-independent diversification models that allow for a complex diversification process that is independent of the evolution of a character. Under rigorous simulation tests and when applied to empirical data, we find that HiSSE performs reasonably well, and can at least detect net diversification rate differences between observed and hidden states and detect when diversification rate differences do not correlate with the observed states. We discuss the remaining issues with state-dependent speciation and extinction models in general, and the important ways in which HiSSE provides a more nuanced understanding of trait-dependent diversification. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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

PubMed

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

2014-01-01

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

Experimental evidence that the Ornstein-Uhlenbeck model best describes the evolution of leaf litter decomposability

PubMed Central

Pan, Xu; Cornelissen, Johannes H C; Zhao, Wei-Wei; Liu, Guo-Fang; Hu, Yu-Kun; Prinzing, Andreas; Dong, Ming; Cornwell, William K

2014-01-01

Leaf litter decomposability is an important effect trait for ecosystem functioning. However, it is unknown how this effect trait evolved through plant history as a leaf ‘afterlife’ integrator of the evolution of multiple underlying traits upon which adaptive selection must have acted. Did decomposability evolve in a Brownian fashion without any constraints? Was evolution rapid at first and then slowed? Or was there an underlying mean-reverting process that makes the evolution of extreme trait values unlikely? Here, we test the hypothesis that the evolution of decomposability has undergone certain mean-reverting forces due to strong constraints and trade-offs in the leaf traits that have afterlife effects on litter quality to decomposers. In order to test this, we examined the leaf litter decomposability and seven key leaf traits of 48 tree species in the temperate area of China and fitted them to three evolutionary models: Brownian motion model (BM), Early burst model (EB), and Ornstein-Uhlenbeck model (OU). The OU model, which does not allow unlimited trait divergence through time, was the best fit model for leaf litter decomposability and all seven leaf traits. These results support the hypothesis that neither decomposability nor the underlying traits has been able to diverge toward progressively extreme values through evolutionary time. These results have reinforced our understanding of the relationships between leaf litter decomposability and leaf traits in an evolutionary perspective and may be a helpful step toward reconstructing deep-time carbon cycling based on taxonomic composition with more confidence. PMID:25535551

Quantitative trait loci analyses and RNA-seq identify genes affecting stress response in rainbow trout

USDA-ARS?s Scientific Manuscript database

Genomic analyses have the potential to impact aquaculture production traits by identifying markers as proxies for traits which are expensive or difficult to measure and characterizing genetic variation and biochemical mechanisms underlying phenotypic variation. One such trait is the response of rai...

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

PubMed

Liu, Dajiang J; Leal, Suzanne M

2012-10-05

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

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

PubMed

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

2015-01-01

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

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

PubMed Central

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

2014-01-01

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

Genome-wide association study reveals putative regulators of bioenergy traits in Populus deltoides

DOE PAGES

Fahrenkrog, Annette M.; Neves, Leandro G.; Resende, Jr., Marcio F. R.; ...

2016-09-06

Genome-wide association studies (GWAS) have been used extensively to dissect the genetic regulation of complex traits in plants. These studies have focused largely on the analysis of common genetic variants despite the abundance of rare polymorphisms in several species, and their potential role in trait variation. Here, we conducted the first GWAS in Populus deltoides, a genetically diverse keystone forest species in North America and an important short rotation woody crop for the bioenergy industry. We searched for associations between eight growth and wood composition traits, and common and low-frequency single-nucleotide polymorphisms detected by targeted resequencing of 18 153 genesmore » in a population of 391 unrelated individuals. To increase power to detect associations with low-frequency variants, multiple-marker association tests were used in combination with single-marker association tests. Significant associations were discovered for all phenotypes and are indicative that low-frequency polymorphisms contribute to phenotypic variance of several bioenergy traits. Our results suggest that both common and low-frequency variants need to be considered for a comprehensive understanding of the genetic regulation of complex traits, particularly in species that carry large numbers of rare polymorphisms. Lastly, these polymorphisms may be critical for the development of specialized plant feedstocks for bioenergy.« less

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

PubMed Central

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

2015-01-01

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

Diversity, competition, extinction: the ecophysics of language change.

PubMed

Solé, Ricard V; Corominas-Murtra, Bernat; Fortuny, Jordi

2010-12-06

As indicated early by Charles Darwin, languages behave and change very much like living species. They display high diversity, differentiate in space and time, emerge and disappear. A large body of literature has explored the role of information exchanges and communicative constraints in groups of agents under selective scenarios. These models have been very helpful in providing a rationale on how complex forms of communication emerge under evolutionary pressures. However, other patterns of large-scale organization can be described using mathematical methods ignoring communicative traits. These approaches consider shorter time scales and have been developed by exploiting both theoretical ecology and statistical physics methods. The models are reviewed here and include extinction, invasion, origination, spatial organization, coexistence and diversity as key concepts and are very simple in their defining rules. Such simplicity is used in order to catch the most fundamental laws of organization and those universal ingredients responsible for qualitative traits. The similarities between observed and predicted patterns indicate that an ecological theory of language is emerging, supporting (on a quantitative basis) its ecological nature, although key differences are also present. Here, we critically review some recent advances and outline their implications and limitations as well as highlight problems for future research.

Diversity, competition, extinction: the ecophysics of language change

PubMed Central

Solé, Ricard V.; Corominas-Murtra, Bernat; Fortuny, Jordi

2010-01-01

As indicated early by Charles Darwin, languages behave and change very much like living species. They display high diversity, differentiate in space and time, emerge and disappear. A large body of literature has explored the role of information exchanges and communicative constraints in groups of agents under selective scenarios. These models have been very helpful in providing a rationale on how complex forms of communication emerge under evolutionary pressures. However, other patterns of large-scale organization can be described using mathematical methods ignoring communicative traits. These approaches consider shorter time scales and have been developed by exploiting both theoretical ecology and statistical physics methods. The models are reviewed here and include extinction, invasion, origination, spatial organization, coexistence and diversity as key concepts and are very simple in their defining rules. Such simplicity is used in order to catch the most fundamental laws of organization and those universal ingredients responsible for qualitative traits. The similarities between observed and predicted patterns indicate that an ecological theory of language is emerging, supporting (on a quantitative basis) its ecological nature, although key differences are also present. Here, we critically review some recent advances and outline their implications and limitations as well as highlight problems for future research. PMID:20591847

A test for selection employing quantitative trait locus and mutation accumulation data.

PubMed

Rice, Daniel P; Townsend, Jeffrey P

2012-04-01

Evolutionary biologists attribute much of the phenotypic diversity observed in nature to the action of natural selection. However, for many phenotypic traits, especially quantitative phenotypic traits, it has been challenging to test for the historical action of selection. An important challenge for biologists studying quantitative traits, therefore, is to distinguish between traits that have evolved under the influence of strong selection and those that have evolved neutrally. Most existing tests for selection employ molecular data, but selection also leaves a mark on the genetic architecture underlying a trait. In particular, the distribution of quantitative trait locus (QTL) effect sizes and the distribution of mutational effects together provide information regarding the history of selection. Despite the increasing availability of QTL and mutation accumulation data, such data have not yet been effectively exploited for this purpose. We present a model of the evolution of QTL and employ it to formulate a test for historical selection. To provide a baseline for neutral evolution of the trait, we estimate the distribution of mutational effects from mutation accumulation experiments. We then apply a maximum-likelihood-based method of inference to estimate the range of selection strengths under which such a distribution of mutations could generate the observed QTL. Our test thus represents the first integration of population genetic theory and QTL data to measure the historical influence of selection.

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

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

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

1993-11-01

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

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.

Quantifying multi-dimensional functional trait spaces of trees: empirical versus theoretical approaches

NASA Astrophysics Data System (ADS)

Ogle, K.; Fell, M.; Barber, J. J.

2016-12-01

Empirical, field studies of plant functional traits have revealed important trade-offs among pairs or triplets of traits, such as the leaf (LES) and wood (WES) economics spectra. Trade-offs include correlations between leaf longevity (LL) vs specific leaf area (SLA), LL vs mass-specific leaf respiration rate (RmL), SLA vs RmL, and resistance to breakage vs wood density. Ordination analyses (e.g., PCA) show groupings of traits that tend to align with different life-history strategies or taxonomic groups. It is unclear, however, what underlies such trade-offs and emergent spectra. Do they arise from inherent physiological constraints on growth, or are they more reflective of environmental filtering? The relative importance of these mechanisms has implications for predicting biogeochemical cycling, which is influenced by trait distributions of the plant community. We address this question using an individual-based model of tree growth (ACGCA) to quantify the theoretical trait space of trees that emerges from physiological constraints. ACGCA's inputs include 32 physiological, anatomical, and allometric traits, many of which are related to the LES and WES. We fit ACGCA to 1.6 million USFS FIA observations of tree diameters and heights to obtain vectors of trait values that produce realistic growth, and we explored the structure of this trait space. No notable correlations emerged among the 496 trait pairs, but stepwise regressions revealed complicated multi-variate structure: e.g., relationships between pairs of traits (e.g., RmL and SLA) are governed by other traits (e.g., LL, radiation-use efficiency [RUE]). We also simulated growth under various canopy gap scenarios that impose varying degrees of environmental filtering to explore the multi-dimensional trait space (hypervolume) of trees that died vs survived. The centroid and volume of the hypervolumes differed among dead and live trees, especially under gap conditions leading to low mortality. Traits most predictive of tree-level mortality were maximum tree height, RUE, xylem conducting area, and branch turn-over rate. We are using these hypervolumes as priors to an emulator that approximates the ACGCA, which we are fitting to the FIA data to quantify species-specific trait spectra and to explore factors giving rise to species differences.

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.

Sky island bird populations isolated by ancient genetic barriers are characterized by different song traits than those isolated by recent deforestation.

PubMed

Purushotham, Chetana B; Robin, V V

2016-10-01

Various mechanisms of isolation can structure populations and result in cultural and genetic differentiation. Similar to genetic markers, for songbirds, culturally transmitted sexual signals such as breeding song can be used as a measure of differentiation as songs can also be impacted by geographic isolation resulting in population-level differences in song structure. Several studies have found differences in song structure either across ancient geographic barriers or across contemporary habitat barriers owing to deforestation. However, very few studies have examined the effect of both ancient barriers and recent deforestation in the same system. In this study, we examined the geographic variation in song structure across six populations of the White-bellied Shortwing, a threatened and endemic songbird species complex found on isolated mountaintops or "sky islands" of the Western Ghats. While some sky islands in the system are isolated by ancient valleys, others are separated by deforestation. We examined 14 frequency and temporal spectral traits and two syntax traits from 835 songs of 38 individuals across the six populations. We identified three major song clusters based on a discriminant model of spectral traits, degree of similarity of syntax features, as well as responses of birds to opportunistic playback. However, some traits like complex vocal mechanisms (CVM), relating to the use of syrinxes, clearly differentiated both ancient and recently fragmented populations. We suggest that CVMs may have a cultural basis and can be used to identify culturally isolated populations that cannot be differentiated using genetic markers or commonly used frequency-based song traits. Our results demonstrate the use of bird songs to reconstruct phylogenetic groups and impacts of habitat fragmentation even in complex scenarios of historic and contemporary isolation.

Selection of Drought Tolerant Maize Hybrids Using Path Coefficient Analysis and Selection Index.

PubMed

Dao, Abdalla; Sanou, Jacob; V S Traore, Edgar; Gracen, Vernon; Danquah, Eric Y

2017-01-01

In drought-prone environments, direct selection for yield is not adequate because of the variable environment and genotype x environment interaction. Therefore, the use of secondary traits in addition to yield has been suggested. The relative usefulness of secondary traits as indirect selection criteria for maize grain yield is determined by the magnitudes of their genetic variance, heritability and genetic correlation with the grain yield. Forty eight testcross hybrids derived from lines with different genetic background and geographical origins plus 7 checks were evaluated in both well-watered and water-stressed conditions over two years for grain yield and secondary traits to determine the most appropriate secondary traits and select drought tolerant hybrids. Study found that broad-sense heritability of grain yield and Ear Per Plant (EPP) increased under drought stress. Ear aspect (EASP) and ear height (EHT) had larger correlation coefficients and direct effect on grain yield but in opposite direction, negative and positive respectively. Traits like, EPP, Tassel Size (TS) and Plant Recovery (PR) contributed to increase yield via EASP by a large negative indirect effect. Under drought stress, EHT had positive and high direct effect and negative indirect effect via plant height on grain yield indicating that the ratio between ear and plant heights (R-EPH) was associated to grain yield. Path coefficient analysis showed that traits EPP, TS, PR, EASP, R-EPH were important secondary traits in the present experiment. These traits were used in a selection index to classify hybrids according to their performance under drought. The selection procedure included also a Relative Decrease in Yield (RDY) index. Some secondary traits reported as significant selection criteria for selection under drought stress were not finally established in the present study. This is because the relationship between grain and secondary traits can be affected by various factors including germplasm, environment and applied statistical analysis. Therefore, different traits and selection procedure should be applied in the selection process of drought tolerant genotypes for diverse genetic materials and growing conditions.

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

PubMed Central

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

2013-01-01

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

Estimating rice yield related traits and quantitative trait loci analysis under different nitrogen treatments using a simple tower-based field phenotyping system with modified single-lens reflex cameras

NASA Astrophysics Data System (ADS)

Naito, Hiroki; Ogawa, Satoshi; Valencia, Milton Orlando; Mohri, Hiroki; Urano, Yutaka; Hosoi, Fumiki; Shimizu, Yo; Chavez, Alba Lucia; Ishitani, Manabu; Selvaraj, Michael Gomez; Omasa, Kenji

2017-03-01

Application of field based high-throughput phenotyping (FB-HTP) methods for monitoring plant performance in real field conditions has a high potential to accelerate the breeding process. In this paper, we discuss the use of a simple tower based remote sensing platform using modified single-lens reflex cameras for phenotyping yield traits in rice under different nitrogen (N) treatments over three years. This tower based phenotyping platform has the advantages of simplicity, ease and stability in terms of introduction, maintenance and continual operation under field conditions. Out of six phenological stages of rice analyzed, the flowering stage was the most useful in the estimation of yield performance under field conditions. We found a high correlation between several vegetation indices (simple ratio (SR), normalized difference vegetation index (NDVI), transformed vegetation index (TVI), corrected transformed vegetation index (CTVI), soil-adjusted vegetation index (SAVI) and modified soil-adjusted vegetation index (MSAVI)) and multiple yield traits (panicle number, grain weight and shoot biomass) across a three trials. Among all of the indices studied, SR exhibited the best performance in regards to the estimation of grain weight (R2 = 0.80). Under our tower-based field phenotyping system (TBFPS), we identified quantitative trait loci (QTL) for yield related traits using a mapping population of chromosome segment substitution lines (CSSLs) and a single nucleotide polymorphism data set. Our findings suggest the TBFPS can be useful for the estimation of yield performance during early crop development. This can be a major opportunity for rice breeders whom desire high throughput phenotypic selection for yield performance traits.

Detecting sexually antagonistic coevolution with population crosses.

PubMed

Rowe, Locke; Cameron, Erin; Day, Troy

2003-10-07

The result of population crosses on traits such as mating rate, oviposition rate and survivorship are increasingly used to distinguish between modes of coevolution between the sexes. Two key hypotheses, erected from a verbal theory of sexually antagonistic coevolution, have been the subject of several recent tests. First, statistical interactions arising in population crosses are suggested to be indicative of a complex signal/receiver system. In the case of oviposition rates, an interaction between populations (x, y and z) would be indicated by the rank order of female oviposition rates achieved by x, y and z males changing depending upon the female (x, y or z) with which they mated. Second, under sexually antagonistic coevolution females will do 'best' when mated with their own males, where best is defined by the weakest response to the signal and the highest fitness. We test these hypotheses by crossing strains generated from a formal model of sexually antagonistic coevolution. Strains differ in the strength of natural selection acting on male and female traits. In our model, we assume sexually antagonistic coevolution of a single male signal and female receptor. The female receptor is treated as a preference function where both the slope and intercept of the function can evolve. Our results suggest that neither prediction is consistently supported. Interactions are not diagnostic of complex signal-receiver systems, and even under sexually antagonistic coevolution, females may do better mating with males of strains other than their own. These results suggest a reinterpretation of several recent experiments and have important implications for developing theories of speciation when sexually antagonistic coevolution is involved.

Good genes, complementary genes and human mate preferences.

PubMed

Roberts, S Craig; Little, Anthony C

2008-03-01

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

Good genes, complementary genes and human mate preferences.

PubMed

Roberts, S Craig; Little, Anthony C

2008-09-01

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

A Tricky Trait: Applying the Fruits of the "Function Debate" in the Philosophy of Biology to the "Venom Debate" in the Science of Toxinology.

PubMed

Jackson, Timothy N W; Fry, Bryan G

2016-09-07

The "function debate" in the philosophy of biology and the "venom debate" in the science of toxinology are conceptually related. Venom systems are complex multifunctional traits that have evolved independently numerous times throughout the animal kingdom. No single concept of function, amongst those popularly defended, appears adequate to describe these systems in all their evolutionary contexts and extant variations. As such, a pluralistic view of function, previously defended by some philosophers of biology, is most appropriate. Venom systems, like many other functional traits, exist in nature as points on a continuum and the boundaries between "venomous" and "non-venomous" species may not always be clearly defined. This paper includes a brief overview of the concept of function, followed by in-depth discussion of its application to venom systems. A sound understanding of function may aid in moving the venom debate forward. Similarly, consideration of a complex functional trait such as venom may be of interest to philosophers of biology.

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

PubMed

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

2016-01-01

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

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

Evaluating the dimensionality of first grade written composition

PubMed Central

Kim, Young-Suk; Al Otaiba, Stephanie; Folsom, Jessica S.; Greulich, Luana; Puranik, Cynthia

2013-01-01

Purpose We examined dimensions of written composition using multiple evaluative approaches such as an adapted 6+1 trait scoring, syntactic complexity measures, and productivity measures. We further examined unique relations of oral language and literacy skills to the identified dimensions of written composition. Method A large sample of first grade students (N = 527) was assessed on their language, reading, spelling, letter writing automaticity, and writing in the spring. Data were analyzed using a latent variable approach including confirmatory factor analysis and structural equation modeling. Results The seven traits in the 6+1 trait system were best described as two constructs: substantive quality, and spelling and writing conventions. When the other evaluation procedures such as productivity and syntactic complexity indicators were included, four dimensions emerged: substantive quality, productivity, syntactic complexity, and spelling and writing conventions. Language and literacy predictors were differentially related to each dimension in written composition. Conclusions These four dimensions may be a useful guideline for evaluating developing beginning writer’s compositions. PMID:24687472

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

PubMed

de Villemereuil, Pierre

2018-01-24

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

Interrelationships between trait anxiety, situational stress and mental effort predict phonological processing efficiency, but not effectiveness.

PubMed

Edwards, Elizabeth J; Edwards, Mark S; Lyvers, Michael

2016-08-01

Attentional control theory (ACT) describes the mechanisms associated with the relationship between anxiety and cognitive performance. We investigated the relationship between cognitive trait anxiety, situational stress and mental effort on phonological performance using a simple (forward-) and complex (backward-) word span task. Ninety undergraduate students participated in the study. Predictor variables were cognitive trait anxiety, indexed using questionnaire scores; situational stress, manipulated using ego threat instructions; and perceived level of mental effort, measured using a visual analogue scale. Criterion variables (a) performance effectiveness (accuracy) and (b) processing efficiency (accuracy divided by response time) were analyzed in separate multiple moderated-regression analyses. The results revealed (a) no relationship between the predictors and performance effectiveness, and (b) a significant 3-way interaction on processing efficiency for both the simple and complex tasks, such that at higher effort, trait anxiety and situational stress did not predict processing efficiency, whereas at lower effort, higher trait anxiety was associated with lower efficiency at high situational stress, but not at low situational stress. Our results were in full support of the assumptions of ACT and implications for future research are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

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

Fahrenkrog, Annette M.; Neves, Leandro G.; Resende, Jr., Marcio F. R.

Genome-wide association studies (GWAS) have been used extensively to dissect the genetic regulation of complex traits in plants. These studies have focused largely on the analysis of common genetic variants despite the abundance of rare polymorphisms in several species, and their potential role in trait variation. Here, we conducted the first GWAS in Populus deltoides, a genetically diverse keystone forest species in North America and an important short rotation woody crop for the bioenergy industry. We searched for associations between eight growth and wood composition traits, and common and low-frequency single-nucleotide polymorphisms detected by targeted resequencing of 18 153 genesmore » in a population of 391 unrelated individuals. To increase power to detect associations with low-frequency variants, multiple-marker association tests were used in combination with single-marker association tests. Significant associations were discovered for all phenotypes and are indicative that low-frequency polymorphisms contribute to phenotypic variance of several bioenergy traits. Our results suggest that both common and low-frequency variants need to be considered for a comprehensive understanding of the genetic regulation of complex traits, particularly in species that carry large numbers of rare polymorphisms. Lastly, these polymorphisms may be critical for the development of specialized plant feedstocks for bioenergy.« less

Evolution of branched regulatory genetic pathways: directional selection on pleiotropic loci accelerates developmental system drift.

PubMed

Johnson, Norman A; Porter, Adam H

2007-01-01

Developmental systems are regulated by a web of interacting loci. One common and useful approach in studying the evolution of development is to focus on classes of interacting elements within these systems. Here, we use individual-based simulations to study the evolution of traits controlled by branched developmental pathways involving three loci, where one locus regulates two different traits. We examined the system under a variety of selective regimes. In the case where one branch was under stabilizing selection and the other under directional selection, we observed "developmental system drift": the trait under stabilizing selection showed little phenotypic change even though the loci underlying that trait showed considerable evolutionary divergence. This occurs because the pleiotropic locus responds to directional selection and compensatory mutants are then favored in the pathway under stabilizing selection. Though developmental system drift may be caused by other mechanisms, it seems likely that it is accelerated by the same underlying genetic mechanism as that producing the Dobzhansky-Muller incompatibilities that lead to speciation in both linear and branched pathways. We also discuss predictions of our model for developmental system drift and how different selective regimes affect probabilities of speciation in the branched pathway system.

Genomic Regions Associated with Root Traits under Drought Stress in Tropical Maize (Zea mays L.)

PubMed Central

Zaidi, P. H.; Krishna, Girish; Krishnamurthy, L.; Gajanan, S.; Babu, Raman; Zerka, M.; Vinayan, M. T.; Vivek, B. S.

2016-01-01

An association mapping panel, named as CIMMYT Asia association mapping (CAAM) panel, involving 396 diverse tropical maize lines were phenotyped for various structural and functional traits of roots under drought and well-watered conditions. The experiment was conducted during Kharif (summer-rainy) season of 2012 and 2013 in root phenotyping facility at CIMMYT-Hyderabad, India. The CAAM panel was genotyped to generate 955, 690 SNPs through GBS v2.7 using Illumina Hi-seq 2000/2500 at Institute for Genomic Diversity, Cornell University, Ithaca, NY, USA. GWAS analysis was carried out using 331,390 SNPs filtered from the entire set of SNPs revealed a total of 50 and 67 SNPs significantly associated for root functional (transpiration efficiency, flowering period water use) and structural traits (rooting depth, root dry weight, root length, root volume, root surface area and root length density), respectively. In addition to this, 37 SNPs were identified for grain yield and shoot biomass under well-watered and drought stress. Though many SNPs were found to have significant association with the traits under study, SNPs that were common for more than one trait were discussed in detail. A total 18 SNPs were found to have common association with more than one trait, out of which 12 SNPs were found within or near the various gene functional regions. In this study we attempted to identify the trait specific maize lines based on the presence of favorable alleles for the SNPs associated with multiple traits. Two SNPs S3_128533512 and S7_151238865 were associated with transpiration efficiency, shoot biomass and grain yield under well-watered condition. Based on favorable allele for these SNPs seven inbred lines were identified. Similarly, four lines were identified for transpiration efficiency and shoot biomass under drought stress based on the presence of favorable allele for the common SNPs S1_211520521, S2_20017716, S3_57210184 and S7_130878458 and three lines were identified for flowering period water-use, transpiration efficiency, root dry weight and root volume based on the presence of favorable allele for the common SNPs S3_162065732 and S3_225760139. PMID:27768702

Autistic traits in children with ADHD index clinical and cognitive problems.

PubMed

Cooper, Miriam; Martin, Joanna; Langley, Kate; Hamshere, Marian; Thapar, Anita

2014-01-01

Traits of autistic spectrum disorders (ASD) occur frequently in attention deficit hyperactivity disorder (ADHD), but the significance of their presence in terms of phenotype and underlying neurobiology is not properly understood. This analysis aimed to determine whether higher levels of autistic traits, as measured by the Social Communication Questionnaire (SCQ), index a more severe presentation in a large, rigorously phenotyped sample of children with ADHD (N=711). Regression analyses were used to examine association of SCQ scores with core ADHD features, clinical comorbidities and cognitive and developmental features, with adjustment for putative confounders. For outcomes showing association with total SCQ score, secondary analyses determined levels of differential association of the three ASD sub-domains. Results suggest that increasing ASD symptomatology within ADHD is associated with a more severe phenotype in terms of oppositional, conduct and anxiety symptoms, lower full-scale IQ, working memory deficits and general motor problems. These associations persisted after accounting for ADHD severity, suggesting that autistic symptomatology independently indexes the severity of comorbid impairments in the context of ADHD. Sub-domain scores did not show unique contributions to most outcomes, except that social deficits were independently associated with oppositional symptoms and repetitive behaviours independently predicted hyperactive-impulsive symptoms and motor problems. It would be worthwhile for clinicians to consider levels of socio-communicative and repetitive traits in those with ADHD who do not meet diagnostic criteria for ASD, as they index higher levels of phenotypic complexity, which may have implications for efficacy of interventions.

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

PubMed

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

2012-12-19

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

Evolutionary fields can explain patterns of high-dimensional complexity in ecology

NASA Astrophysics Data System (ADS)

Wilsenach, James; Landi, Pietro; Hui, Cang

2017-04-01

One of the properties that make ecological systems so unique is the range of complex behavioral patterns that can be exhibited by even the simplest communities with only a few species. Much of this complexity is commonly attributed to stochastic factors that have very high-degrees of freedom. Orthodox study of the evolution of these simple networks has generally been limited in its ability to explain complexity, since it restricts evolutionary adaptation to an inertia-free process with few degrees of freedom in which only gradual, moderately complex behaviors are possible. We propose a model inspired by particle-mediated field phenomena in classical physics in combination with fundamental concepts in adaptation, which suggests that small but high-dimensional chaotic dynamics near to the adaptive trait optimum could help explain complex properties shared by most ecological datasets, such as aperiodicity and pink, fractal noise spectra. By examining a simple predator-prey model and appealing to real ecological data, we show that this type of complexity could be easily confused for or confounded by stochasticity, especially when spurred on or amplified by stochastic factors that share variational and spectral properties with the underlying dynamics.

What Explains Patterns of Diversification and Richness among Animal Phyla?

PubMed Central

Jezkova, Tereza; Wiens, John J.

2016-01-01

Animal phyla vary dramatically in species richness (from 1 species to >1.2 million), but the causes of this variation remain largely unknown. Animals have also evolved striking variation in morphology and ecology, including sessile marine taxa lacking heads, eyes, limbs, and complex organs (e.g. sponges), parasitic worms (e.g. nematodes, platyhelminths), and taxa with eyes, skeletons, limbs, and complex organs that dominate terrestrial ecosystems (arthropods, chordates). Relating this remarkable variation in traits to the diversification and richness of animal phyla is a fundamental yet unresolved problem in biology. Here, we test the impacts of 18 traits (including morphology, ecology, reproduction, and development) on diversification and richness of extant animal phyla. Using phylogenetic multiple regression, the best-fitting model includes five traits that explain ~74% of the variation in diversification rates (dioecy, parasitism, eyes/photoreceptors, a skeleton, non-marine habitat). However, a model including just three (skeleton, parasitism, habitat) explains nearly as much variation (~67%). Diversification rates then largely explain richness patterns. Our results also identify many striking traits that have surprisingly little impact on diversification (e.g. head, limbs, and complex circulatory and digestive systems). Overall, our results reveal the key factors that shape large-scale patterns of diversification and richness across >80% of all extant, described species. PMID:28221832

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

PubMed

Bocianowski, Jan

2013-03-01

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

What Explains Patterns of Diversification and Richness among Animal Phyla?

PubMed

Jezkova, Tereza; Wiens, John J

2017-03-01

Animal phyla vary dramatically in species richness (from one species to >1.2 million), but the causes of this variation remain largely unknown. Animals have also evolved striking variation in morphology and ecology, including sessile marine taxa lacking heads, eyes, limbs, and complex organs (e.g., sponges), parasitic worms (e.g., nematodes, platyhelminths), and taxa with eyes, skeletons, limbs, and complex organs that dominate terrestrial ecosystems (arthropods, chordates). Relating this remarkable variation in traits to the diversification and richness of animal phyla is a fundamental yet unresolved problem in biology. Here, we test the impacts of 18 traits (including morphology, ecology, reproduction, and development) on diversification and richness of extant animal phyla. Using phylogenetic multiple regression, the best-fitting model includes five traits that explain ∼74% of the variation in diversification rates (dioecy, parasitism, eyes/photoreceptors, a skeleton, nonmarine habitat). However, a model including just three (skeleton, parasitism, habitat) explains nearly as much variation (∼67%). Diversification rates then largely explain richness patterns. Our results also identify many striking traits that have surprisingly little impact on diversification (e.g., head, limbs, and complex circulatory and digestive systems). Overall, our results reveal the key factors that shape large-scale patterns of diversification and richness across >80% of all extant, described species.

Integrated translational genomics for analysis of complex traits in sorghum

USDA-ARS?s Scientific Manuscript database

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

The promise of genomics in the study of plant-pollinator interactions

PubMed Central

2013-01-01

Flowers exist in exceedingly complex fitness landscapes, in which subtle variation in each trait can affect the pollinators, herbivores and pleiotropically linked traits in other plant tissues. A whole-genome approach to flower evolution will help our understanding of plant-pollinator interactions. PMID:23796166

Analysis of Sequence Data Under Multivariate Trait-Dependent Sampling.

PubMed

Tao, Ran; Zeng, Donglin; Franceschini, Nora; North, Kari E; Boerwinkle, Eric; Lin, Dan-Yu

2015-06-01

High-throughput DNA sequencing allows for the genotyping of common and rare variants for genetic association studies. At the present time and for the foreseeable future, it is not economically feasible to sequence all individuals in a large cohort. A cost-effective strategy is to sequence those individuals with extreme values of a quantitative trait. We consider the design under which the sampling depends on multiple quantitative traits. Under such trait-dependent sampling, standard linear regression analysis can result in bias of parameter estimation, inflation of type I error, and loss of power. We construct a likelihood function that properly reflects the sampling mechanism and utilizes all available data. We implement a computationally efficient EM algorithm and establish the theoretical properties of the resulting maximum likelihood estimators. Our methods can be used to perform separate inference on each trait or simultaneous inference on multiple traits. We pay special attention to gene-level association tests for rare variants. We demonstrate the superiority of the proposed methods over standard linear regression through extensive simulation studies. We provide applications to the Cohorts for Heart and Aging Research in Genomic Epidemiology Targeted Sequencing Study and the National Heart, Lung, and Blood Institute Exome Sequencing Project.

Genomic Characterization of the Evolutionary Potential of the Sea Urchin Strongylocentrotus droebachiensis Facing Ocean Acidification

PubMed Central

Dorey, Narimane; Garfield, David A.; Stumpp, Meike; Dupont, Sam; Wray, Gregory A.

2016-01-01

Abstract Ocean acidification (OA) is increasing due to anthropogenic CO2 emissions and poses a threat to marine species and communities worldwide. To better project the effects of acidification on organisms’ health and persistence, an understanding is needed of the 1) mechanisms underlying developmental and physiological tolerance and 2) potential populations have for rapid evolutionary adaptation. This is especially challenging in nonmodel species where targeted assays of metabolism and stress physiology may not be available or economical for large-scale assessments of genetic constraints. We used mRNA sequencing and a quantitative genetics breeding design to study mechanisms underlying genetic variability and tolerance to decreased seawater pH (-0.4 pH units) in larvae of the sea urchin Strongylocentrotus droebachiensis. We used a gene ontology-based approach to integrate expression profiles into indirect measures of cellular and biochemical traits underlying variation in larval performance (i.e., growth rates). Molecular responses to OA were complex, involving changes to several functions such as growth rates, cell division, metabolism, and immune activities. Surprisingly, the magnitude of pH effects on molecular traits tended to be small relative to variation attributable to segregating functional genetic variation in this species. We discuss how the application of transcriptomics and quantitative genetics approaches across diverse species can enrich our understanding of the biological impacts of climate change. PMID:28082601

No boundaries: genomes, organisms, and ecological interactions responsible for divergence and reproductive isolation.

PubMed

Etges, William J

2014-01-01

Revealing the genetic basis of traits that cause reproductive isolation, particularly premating or sexual isolation, usually involves the same challenges as most attempts at genotype-phenotype mapping and so requires knowledge of how these traits are expressed in different individuals, populations, and environments, particularly under natural conditions. Genetic dissection of speciation phenotypes thus requires understanding of the internal and external contexts in which underlying genetic elements are expressed. Gene expression is a product of complex interacting factors internal and external to the organism including developmental programs, the genetic background including nuclear-cytotype interactions, epistatic relationships, interactions among individuals or social effects, stochasticity, and prevailing variation in ecological conditions. Understanding of genomic divergence associated with reproductive isolation will be facilitated by functional expression analysis of annotated genomes in organisms with well-studied evolutionary histories, phylogenetic affinities, and known patterns of ecological variation throughout their life cycles. I review progress and prospects for understanding the pervasive role of host plant use on genetic and phenotypic expression of reproductive isolating mechanisms in cactophilic Drosophila mojavensis and suggest how this system can be used as a model for revealing the genetic basis for species formation in organisms where speciation phenotypes are under the joint influences of genetic and environmental factors. © The American Genetic Association. 2014. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Localization of canine brachycephaly using an across breed mapping approach.

PubMed

Bannasch, Danika; Young, Amy; Myers, Jeffrey; Truvé, Katarina; Dickinson, Peter; Gregg, Jeffrey; Davis, Ryan; Bongcam-Rudloff, Eric; Webster, Matthew T; Lindblad-Toh, Kerstin; Pedersen, Niels

2010-03-10

The domestic dog, Canis familiaris, exhibits profound phenotypic diversity and is an ideal model organism for the genetic dissection of simple and complex traits. However, some of the most interesting phenotypes are fixed in particular breeds and are therefore less tractable to genetic analysis using classical segregation-based mapping approaches. We implemented an across breed mapping approach using a moderately dense SNP array, a low number of animals and breeds carefully selected for the phenotypes of interest to identify genetic variants responsible for breed-defining characteristics. Using a modest number of affected (10-30) and control (20-60) samples from multiple breeds, the correct chromosomal assignment was identified in a proof of concept experiment using three previously defined loci; hyperuricosuria, white spotting and chondrodysplasia. Genome-wide association was performed in a similar manner for one of the most striking morphological traits in dogs: brachycephalic head type. Although candidate gene approaches based on comparable phenotypes in mice and humans have been utilized for this trait, the causative gene has remained elusive using this method. Samples from nine affected breeds and thirteen control breeds identified strong genome-wide associations for brachycephalic head type on Cfa 1. Two independent datasets identified the same genomic region. Levels of relative heterozygosity in the associated region indicate that it has been subjected to a selective sweep, consistent with it being a breed defining morphological characteristic. Genotyping additional dogs in the region confirmed the association. To date, the genetic structure of dog breeds has primarily been exploited for genome wide association for segregating traits. These results demonstrate that non-segregating traits under strong selection are equally tractable to genetic analysis using small sample numbers.

The curvilinear relationship between work pressure and momentary task performance: the role of state and trait core self-evaluations

PubMed Central

Hofmans, Joeri; Debusscher, Jonas; Dóci, Edina; Spanouli, Andromachi; De Fruyt, Filip

2015-01-01

Whereas several studies have demonstrated that core self-evaluations (CSE)–or one’s appraisals about one’s own self-worth, capabilities, and competences–relate to job outcomes, less is known about the mechanisms underlying these relationships. In the present study, we address this issue by examining the role of within- and between-person variation in CSE in the relationship between work pressure and task performance. We hypothesized that (a) work pressure relates to task performance in a curvilinear way, (b) state CSE mediates the curvilinear relationship between work pressure and task performance, and (c) the relationship between work pressure and state CSE is moderated by trait CSE. Our hypotheses were tested via a 10-day daily diary study with 55 employees in which trait CSE was measured at baseline, while work pressure, task performance, and state CSE were assessed on a daily basis. Bayesian multilevel path analysis showed that work pressure affects task performance via state CSE, with state CSE increasing as long as the employee feels that (s)he is able to handle the work pressure, while it decreases when the level of work pressure exceeds the employees’ coping abilities. Moreover, we found that for people low on trait CSE, the depleting effect of work pressure via state CSE happens for low levels of work pressure, while for people high in trait CSE the depleting effect is located at high levels of work pressure. Together, our findings suggest that the impact of work pressure on task performance is driven by a complex interplay of between- and within-person differences in CSE. PMID:26579053

Linking vegetation structure, function and physiology through spectroscopic remote sensing

NASA Astrophysics Data System (ADS)

Serbin, S.; Singh, A.; Couture, J. J.; Shiklomanov, A. N.; Rogers, A.; Desai, A. R.; Kruger, E. L.; Townsend, P. A.

2015-12-01

Terrestrial ecosystem process models require detailed information on ecosystem states and canopy properties to properly simulate the fluxes of carbon (C), water and energy from the land to the atmosphere and assess the vulnerability of ecosystems to perturbations. Current models fail to adequately capture the magnitude, spatial variation, and seasonality of terrestrial C uptake and storage, leading to significant uncertainties in the size and fate of the terrestrial C sink. By and large, these parameter and process uncertainties arise from inadequate spatial and temporal representation of plant traits, vegetation structure, and functioning. With increases in computational power and changes to model architecture and approaches, it is now possible for models to leverage detailed, data rich and spatially explicit descriptions of ecosystems to inform parameter distributions and trait tradeoffs. In this regard, spectroscopy and imaging spectroscopy data have been shown to be invaluable observational datasets to capture broad-scale spatial and, eventually, temporal dynamics in important vegetation properties. We illustrate the linkage of plant traits and spectral observations to supply key data constraints for model parameterization. These constraints can come either in the form of the raw spectroscopic data (reflectance, absorbtance) or physiological traits derived from spectroscopy. In this presentation we highlight our ongoing work to build ecological scaling relationships between critical vegetation characteristics and optical properties across diverse and complex canopies, including temperate broadleaf and conifer forests, Mediterranean vegetation, Arctic systems, and agriculture. We focus on work at the leaf, stand, and landscape scales, illustrating the importance of capturing the underlying variability in a range of parameters (including vertical variation within canopies) to enable more efficient scaling of traits related to functional diversity of ecosystems.

Identifying traits for genotypic adaptation using crop models.

PubMed

Ramirez-Villegas, Julian; Watson, James; Challinor, Andrew J

2015-06-01

Genotypic adaptation involves the incorporation of novel traits in crop varieties so as to enhance food productivity and stability and is expected to be one of the most important adaptation strategies to future climate change. Simulation modelling can provide the basis for evaluating the biophysical potential of crop traits for genotypic adaptation. This review focuses on the use of models for assessing the potential benefits of genotypic adaptation as a response strategy to projected climate change impacts. Some key crop responses to the environment, as well as the role of models and model ensembles for assessing impacts and adaptation, are first reviewed. Next, the review describes crop-climate models can help focus the development of future-adapted crop germplasm in breeding programmes. While recently published modelling studies have demonstrated the potential of genotypic adaptation strategies and ideotype design, it is argued that, for model-based studies of genotypic adaptation to be used in crop breeding, it is critical that modelled traits are better grounded in genetic and physiological knowledge. To this aim, two main goals need to be pursued in future studies: (i) a better understanding of plant processes that limit productivity under future climate change; and (ii) a coupling between genetic and crop growth models-perhaps at the expense of the number of traits analysed. Importantly, the latter may imply additional complexity (and likely uncertainty) in crop modelling studies. Hence, appropriately constraining processes and parameters in models and a shift from simply quantifying uncertainty to actually quantifying robustness towards modelling choices are two key aspects that need to be included into future crop model-based analyses of genotypic adaptation. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

SCOPA and META-SCOPA: software for the analysis and aggregation of genome-wide association studies of multiple correlated phenotypes.

PubMed

Mägi, Reedik; Suleimanov, Yury V; Clarke, Geraldine M; Kaakinen, Marika; Fischer, Krista; Prokopenko, Inga; Morris, Andrew P

2017-01-11

Genome-wide association studies (GWAS) of single nucleotide polymorphisms (SNPs) have been successful in identifying loci contributing genetic effects to a wide range of complex human diseases and quantitative traits. The traditional approach to GWAS analysis is to consider each phenotype separately, despite the fact that many diseases and quantitative traits are correlated with each other, and often measured in the same sample of individuals. Multivariate analyses of correlated phenotypes have been demonstrated, by simulation, to increase power to detect association with SNPs, and thus may enable improved detection of novel loci contributing to diseases and quantitative traits. We have developed the SCOPA software to enable GWAS analysis of multiple correlated phenotypes. The software implements "reverse regression" methodology, which treats the genotype of an individual at a SNP as the outcome and the phenotypes as predictors in a general linear model. SCOPA can be applied to quantitative traits and categorical phenotypes, and can accommodate imputed genotypes under a dosage model. The accompanying META-SCOPA software enables meta-analysis of association summary statistics from SCOPA across GWAS. Application of SCOPA to two GWAS of high-and low-density lipoprotein cholesterol, triglycerides and body mass index, and subsequent meta-analysis with META-SCOPA, highlighted stronger association signals than univariate phenotype analysis at established lipid and obesity loci. The META-SCOPA meta-analysis also revealed a novel signal of association at genome-wide significance for triglycerides mapping to GPC5 (lead SNP rs71427535, p = 1.1x10 -8 ), which has not been reported in previous large-scale GWAS of lipid traits. The SCOPA and META-SCOPA software enable discovery and dissection of multiple phenotype association signals through implementation of a powerful reverse regression approach.

Occam's shadow: levels of analysis in evolutionary ecology - where to next?

USGS Publications Warehouse

Cooch, E.G.; Cam, E.; Link, W.A.

2002-01-01

Evolutionary ecology is the study of evolutionary processes, and the ecological conditions that influence them. A fundamental paradigm underlying the study of evolution is natural selection. Although there are a variety of operational definitions for natural selection in the literature, perhaps the most general one is that which characterizes selection as the process whereby heritable variation in fitness associated with variation in one or more phenotypic traits leads to intergenerational change in the frequency distribution of those traits. The past 20 years have witnessed a marked increase in the precision and reliability of our ability to estimate one or more components of fitness and characterize natural selection in wild populations, owing particularly to significant advances in methods for analysis of data from marked individuals. In this paper, we focus on several issues that we believe are important considerations for the application and development of these methods in the context of addressing questions in evolutionary ecology. First, our traditional approach to estimation often rests upon analysis of aggregates of individuals, which in the wild may reflect increasingly non-random (selected) samples with respect to the trait(s) of interest. In some cases, analysis at the aggregate level, rather than the individual level, may obscure important patterns. While there are a growing number of analytical tools available to estimate parameters at the individual level, and which can cope (to varying degrees) with progressive selection of the sample, the advent of new methods does not reduce the need to consider carefully the appropriate level of analysis in the first place. Estimation should be motivated a priori by strong theoretical analysis. Doing so provides clear guidance, in terms of both (i) assisting in the identification of realistic and meaningful models to include in the candidate model set, and (ii) providing the appropriate context under which the results are interpreted. Second, while it is true that selection (as defined) operates at the level of the individual, the selection gradient is often (if not generally) conditional on the abundance of the population. As such, it may be important to consider estimating transition rates conditional on both the parameter values of the other individuals in the population (or at least their distribution), and population abundance. This will undoubtedly pose a considerable challenge, for both single- and multi-strata applications. It will also require renewed consideration of the estimation of abundance, especially for open populations. Thirdly, selection typically operates on dynamic, individually varying traits. Such estimation may require characterizing fitness in terms of individual plasticity in one or more state variables, constituting analysis of the norms of reaction of individuals to variable environments. This can be quite complex, especially for traits that are under facultative control. Recent work has indicated that the pattern of selection on such traits is conditional on the relative rates of movement among and frequency of spatially heterogeneous habitats, suggesting analyses of evolution of life histories in open populations can be misleading in some cases.

Plasticity Regulators Modulate Specific Root Traits in Discrete Nitrogen Environments

PubMed Central

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

2013-01-01

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

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

PubMed Central

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

2011-01-01

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

Four Linked Genes Participate in Controlling Sporulation Efficiency in Budding Yeast

PubMed Central

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

2006-01-01

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

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

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

Busov, Victor

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

Enhancing Integrated Pest Management in GM Cotton Systems Using Host Plant Resistance

PubMed Central

Trapero, Carlos; Wilson, Iain W.; Stiller, Warwick N.; Wilson, Lewis J.

2016-01-01

Cotton has lost many ancestral defensive traits against key invertebrate pests. This is suggested by the levels of resistance to some pests found in wild cotton genotypes as well as in cultivated landraces and is a result of domestication and a long history of targeted breeding for yield and fiber quality, along with the capacity to control pests with pesticides. Genetic modification (GM) allowed integration of toxins from a bacteria into cotton to control key Lepidopteran pests. Since the mid-1990s, use of GM cotton cultivars has greatly reduced the amount of pesticides used in many cotton systems. However, pests not controlled by the GM traits have usually emerged as problems, especially the sucking bug complex. Control of this complex with pesticides often causes a reduction in beneficial invertebrate populations, allowing other secondary pests to increase rapidly and require control. Control of both sucking bug complex and secondary pests is problematic due to the cost of pesticides and/or high risk of selecting for pesticide resistance. Deployment of host plant resistance (HPR) provides an opportunity to manage these issues in GM cotton systems. Cotton cultivars resistant to the sucking bug complex and/or secondary pests would require fewer pesticide applications, reducing costs and risks to beneficial invertebrate populations and pesticide resistance. Incorporation of HPR traits into elite cotton cultivars with high yield and fiber quality offers the potential to further reduce pesticide use and increase the durability of pest management in GM cotton systems. We review the challenges that the identification and use of HPR against invertebrate pests brings to cotton breeding. We explore sources of resistance to the sucking bug complex and secondary pests, the mechanisms that control them and the approaches to incorporate these defense traits to commercial cultivars. PMID:27148323

Occlusal traits and orthodontic treatment need in 7‐ to 10‐year‐olds in Estonia

PubMed Central

Saag, Mare; Svedström‐Oristo, Anna‐Liisa; Peltomäki, Timo; Vinkka‐Puhakka, Heli

2017-01-01

Abstract The aim of this study was to evaluate the distribution of occlusal traits and orthodontic treatment need and complexity in Estonian 7‐ to 10‐year‐old children. This data provides solid information for planning of orthodontic care. Data of 392 Estonian children (198 girls and 194 boys, mean age 9.0 years, range 7.1–10.4 years) was analysed in this cross‐sectional study. Assessed traits included first molar and canine sagittal relationship, overjet, overbite, crowding, midline diastema, crossbite, and scissor bite. Orthodontic treatment need and complexity were assessed using the Index of Complexity, Outcome, and Need. Parents' opinion regarding their child's teeth was determined using a questionnaire. The most prevalent occlusal traits were canine class I sagittal relationship (73.7%), midline diastema (73.0%), molar class I sagittal relationship (57.4%), and overbite ≥3.5 mm (51.8%). According to the Index of Complexity, Outcome, and Need, 64.3% of Estonian elementary school children were in need of orthodontic treatment. Treatment complexity was simple in 12.5%, mild in 38.8%, moderate in 22.7%, difficult in 14.0%, and very difficult in 12.0% of the children. Approximately 66.4% of the parents felt that their child needed orthodontic treatment. This study confirms earlier findings indicating that the most frequent sagittal relationship is class I in the first molars and class I in the canines. However, the sagittal relationship was asymmetric in more than half of the children. Correlation between objectively defined treatment need and parents' desire for treatment was high in Estonia. PMID:29744185

Genetic basis and fitness correlates of dynamic carotenoid-based ornamental coloration in male and female common kestrels Falco tinnunculus.

PubMed

Vergara, P; Fargallo, J A; Martínez-Padilla, J

2015-01-01

Knowledge of the genetic basis of sexual ornaments is essential to understand their evolution through sexual selection. Although carotenoid-based ornaments have been instrumental in the study of sexual selection, given the inability of animals to synthesize carotenoids de novo, they are generally assumed to be influenced solely by environmental variation. However, very few studies have directly estimated the role of genes and the environment in shaping variation in carotenoid-based traits. Using long-term individual-based data, we here explore the evolutionary potential of a dynamic, carotenoid-based ornament (namely skin coloration), in male and female common kestrels. We first estimate the amount of genetic variation underlying variation in hue, chroma and brightness. After correcting for sex differences, the chroma of the orange-yellow eye ring coloration was significantly heritable (h2±SE=0.40±0.17), whereas neither hue (h2=0) nor brightness (h2=0.02) was heritable. Second, we estimate the strength and shape of selection acting upon chromatic (hue and chroma) and achromatic (brightness) variation and show positive and negative directional selection on female but not male chroma and hue, respectively, whereas brightness was unrelated to fitness in both sexes. This suggests that different components of carotenoid-based signals traits may show different evolutionary dynamics. Overall, we show that carotenoid-based coloration is a complex and multifaceted trait. If we are to gain a better understanding of the processes responsible for the generation and maintenance of variation in carotenoid-based coloration, these complexities need to be taken into account. © 2014 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

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

PubMed Central

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

2012-01-01

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

Whole genome association study identifies regions of the bovine genome and biological pathways involved in carcass trait performance in Holstein-Friesian cattle.

PubMed

Doran, Anthony G; Berry, Donagh P; Creevey, Christopher J

2014-10-01

Four traits related to carcass performance have been identified as economically important in beef production: carcass weight, carcass fat, carcass conformation of progeny and cull cow carcass weight. Although Holstein-Friesian cattle are primarily utilized for milk production, they are also an important source of meat for beef production and export. Because of this, there is great interest in understanding the underlying genomic structure influencing these traits. Several genome-wide association studies have identified regions of the bovine genome associated with growth or carcass traits, however, little is known about the mechanisms or underlying biological pathways involved. This study aims to detect regions of the bovine genome associated with carcass performance traits (employing a panel of 54,001 SNPs) using measures of genetic merit (as predicted transmitting abilities) for 5,705 Irish Holstein-Friesian animals. Candidate genes and biological pathways were then identified for each trait under investigation. Following adjustment for false discovery (q-value < 0.05), 479 quantitative trait loci (QTL) were associated with at least one of the four carcass traits using a single SNP regression approach. Using a Bayesian approach, 46 QTL were associated (posterior probability > 0.5) with at least one of the four traits. In total, 557 unique bovine genes, which mapped to 426 human orthologs, were within 500kbs of QTL found associated with a trait using the Bayesian approach. Using this information, 24 significantly over-represented pathways were identified across all traits. The most significantly over-represented biological pathway was the peroxisome proliferator-activated receptor (PPAR) signaling pathway. A large number of genomic regions putatively associated with bovine carcass traits were detected using two different statistical approaches. Notably, several significant associations were detected in close proximity to genes with a known role in animal growth such as glucagon and leptin. Several biological pathways, including PPAR signaling, were shown to be involved in various aspects of bovine carcass performance. These core genes and biological processes may form the foundation for further investigation to identify causative mutations involved in each trait. Results reported here support previous findings suggesting conservation of key biological processes involved in growth and metabolism.

Coping with Self-Threat and the Evaluation of Self-Related Traits: An fMRI Study

PubMed Central

Corcoran, Katja; Ebner, Franz

2015-01-01

A positive view of oneself is important for a healthy lifestyle. Self-protection mechanisms such as suppressing negative self-related information help us to maintain a positive view of ourselves. This is of special relevance when, for instance, a negative test result threatens our positive self-view. To date, it is not clear which brain areas support self-protective mechanisms under self-threat. In the present functional magnetic resonance imaging (fMRI) study the participants (N = 46) received a (negative vs. positive) performance test feedback before entering the scanner. In the scanner, the participants were instructed to ascribe personality traits either to themselves or to a famous other. Our results showed that participants responded slower to negative self-related traits compared to positive self-related traits. High self-esteem individuals responded slower to negative traits compared to low self-esteem individuals following a self-threat. This indicates that high self-esteem individuals engage more in self-enhancing strategies after a threat by inhibiting negative self-related information more successfully than low self-esteem individuals. This behavioral pattern was mirrored in the fMRI data as dACC correlated positively with trait self-esteem. Generally, ACC activation was attenuated under threat when participants evaluated self-relevant traits and even more for negative self-related traits. We also found that activation in the ACC was negatively correlated with response times, indicating that greater activation of the ACC is linked to better access (faster response) to positive self-related traits and to impaired access (slower response) to negative self-related traits. These results confirm the ACC function as important in managing threatened self-worth but indicate differences in trait self-esteem levels. The fMRI analyses also revealed a decrease in activation within the left Hippocampus and the right thalamus under threat. This indicates that a down-regulation of activation in these regions might also serve as coping mechanism in dealing with self-threat. PMID:26333130

A new tool called DISSECT for analysing large genomic data sets using a Big Data approach

PubMed Central

Canela-Xandri, Oriol; Law, Andy; Gray, Alan; Woolliams, John A.; Tenesa, Albert

2015-01-01

Large-scale genetic and genomic data are increasingly available and the major bottleneck in their analysis is a lack of sufficiently scalable computational tools. To address this problem in the context of complex traits analysis, we present DISSECT. DISSECT is a new and freely available software that is able to exploit the distributed-memory parallel computational architectures of compute clusters, to perform a wide range of genomic and epidemiologic analyses, which currently can only be carried out on reduced sample sizes or under restricted conditions. We demonstrate the usefulness of our new tool by addressing the challenge of predicting phenotypes from genotype data in human populations using mixed-linear model analysis. We analyse simulated traits from 470,000 individuals genotyped for 590,004 SNPs in ∼4 h using the combined computational power of 8,400 processor cores. We find that prediction accuracies in excess of 80% of the theoretical maximum could be achieved with large sample sizes. PMID:26657010

Exome sequencing of extreme phenotypes identifies DCTN4 as a modifier of chronic Pseudomonas aeruginosa infection in cystic fibrosis.

PubMed

Emond, Mary J; Louie, Tin; Emerson, Julia; Zhao, Wei; Mathias, Rasika A; Knowles, Michael R; Wright, Fred A; Rieder, Mark J; Tabor, Holly K; Nickerson, Deborah A; Barnes, Kathleen C; Gibson, Ronald L; Bamshad, Michael J

2012-07-08

Exome sequencing has become a powerful and effective strategy for the discovery of genes underlying Mendelian disorders. However, use of exome sequencing to identify variants associated with complex traits has been more challenging, partly because the sample sizes needed for adequate power may be very large. One strategy to increase efficiency is to sequence individuals who are at both ends of a phenotype distribution (those with extreme phenotypes). Because the frequency of alleles that contribute to the trait are enriched in one or both phenotype extremes, a modest sample size can potentially be used to identify novel candidate genes and/or alleles. As part of the National Heart, Lung, and Blood Institute (NHLBI) Exome Sequencing Project (ESP), we used an extreme phenotype study design to discover that variants in DCTN4, encoding a dynactin protein, are associated with time to first P. aeruginosa airway infection, chronic P. aeruginosa infection and mucoid P. aeruginosa in individuals with cystic fibrosis.

A haplotype map of genomic variations and genome-wide association studies of agronomic traits in foxtail millet (Setaria italica).

PubMed

Jia, Guanqing; Huang, Xuehui; Zhi, Hui; Zhao, Yan; Zhao, Qiang; Li, Wenjun; Chai, Yang; Yang, Lifang; Liu, Kunyan; Lu, Hengyun; Zhu, Chuanrang; Lu, Yiqi; Zhou, Congcong; Fan, Danlin; Weng, Qijun; Guo, Yunli; Huang, Tao; Zhang, Lei; Lu, Tingting; Feng, Qi; Hao, Hangfei; Liu, Hongkuan; Lu, Ping; Zhang, Ning; Li, Yuhui; Guo, Erhu; Wang, Shujun; Wang, Suying; Liu, Jinrong; Zhang, Wenfei; Chen, Guoqiu; Zhang, Baojin; Li, Wei; Wang, Yongfang; Li, Haiquan; Zhao, Baohua; Li, Jiayang; Diao, Xianmin; Han, Bin

2013-08-01

Foxtail millet (Setaria italica) is an important grain crop that is grown in arid regions. Here we sequenced 916 diverse foxtail millet varieties, identified 2.58 million SNPs and used 0.8 million common SNPs to construct a haplotype map of the foxtail millet genome. We classified the foxtail millet varieties into two divergent groups that are strongly correlated with early and late flowering times. We phenotyped the 916 varieties under five different environments and identified 512 loci associated with 47 agronomic traits by genome-wide association studies. We performed a de novo assembly of deeply sequenced genomes of a Setaria viridis accession (the wild progenitor of S. italica) and an S. italica variety and identified complex interspecies and intraspecies variants. We also identified 36 selective sweeps that seem to have occurred during modern breeding. This study provides fundamental resources for genetics research and genetic improvement in foxtail millet.

Successful Graduate Students: The Roles of Personality Traits and Emotional Intelligence

ERIC Educational Resources Information Center

Grehan, Patrick M.; Flanagan, Rosemary; Malgady, Robert G.

2011-01-01

Given the complex role of school psychologists, it is in the interest of stakeholders to identify characteristics related to student success in graduate training, which is suggestive of their effectiveness as practitioners. This study explores the relationship of personality traits and Emotional Intelligence (EI) to graduate students' performance…

QTLs detected for individual sugars and soluble solids content in apple

USDA-ARS?s Scientific Manuscript database

Sweetness is one of the most important fruit quality traits in breeding programs, determining the overall quality and flavor-perception of apples. Selecting for this trait using conventional breeding methods is challenging due to the complexity of its genetic control. In order to improve the efficie...

Dissecting genome-wide association signals for loss-of-function phenotypes in sorghum flavonoid pigmentation traits

USDA-ARS?s Scientific Manuscript database

Genome-wide association studies (GWAS) are a powerful method to dissect the genetic basis of traits, though in practice the effects of complex genetic architecture and population structure remain poorly understood. To compare mapping strategies we dissect the genetic control of flavonoid pigmentatio...

Ethnography in Educational Research: The Dynamics of Diffusion.

ERIC Educational Resources Information Center

Fetterman, David M.

1982-01-01

Ascribes difficulties associated with the use of ethnography in educational research to faulty or partial transmission of traits from one sociocultural system to another. Maintains that the appropriate use of ethnography demands that the whole trait complex be borrowed. Describes educational studies that used ethnographic methods. (Author/MJL)

Relationships between species feeding traits and environmental conditions in fish communities: a three-matrix approach.

PubMed

Brind'Amour, Anik; Boisclair, Daniel; Dray, Stéphane; Legendre, Pierre

2011-03-01

Understanding the relationships between species biological traits and the environment is crucial to predicting the effect of habitat perturbations on fish communities. It is also an essential step in the assessment of the functional diversity. Using two complementary three-matrix approaches (fourth-corner and RLQ analyses), we tested the hypothesis that feeding-oriented traits determine the spatial distributions of littoral fish species by assessing the relationship between fish spatial distributions, fish species traits, and habitat characteristics in two Laurentian Shield lakes. Significant associations between the feeding-oriented traits and the environmental characteristics suggested that fish communities in small lakes (displaying low species richness) can be spatially structured. Three groups of traits, mainly categorized by the species spatial and temporal feeding activity, were identified. The water column may be divided in two sections, each of them corresponding to a group of traits related to the vertical distribution of the prey coupled with the position of the mouth. Lake areas of low structural complexity were inhabited by functional assemblages dominated by surface feeders while structurally more complex areas were occupied by mid-water and benthic feeders. A third group referring to the time of feeding activity was observed. Our work could serve as a guideline study to evaluate species traits x environment associations at multiple spatial scales. Our results indicate that three-matrix statistical approaches are powerful tools that can be used to study such relationships. These recent statistical approaches open up new research directions such as the study of spatially based biological functions in lakes. They also provide new analytical tools for determining, for example, the potential size of freshwater protected areas.

Pedigree- and SNP-Associated Genetics and Recent Environment are the Major Contributors to Anthropometric and Cardiometabolic Trait Variation.

PubMed

Xia, Charley; Amador, Carmen; Huffman, Jennifer; Trochet, Holly; Campbell, Archie; Porteous, David; Hastie, Nicholas D; Hayward, Caroline; Vitart, Veronique; Navarro, Pau; Haley, Chris S

2016-02-01

Genome-wide association studies have successfully identified thousands of loci for a range of human complex traits and diseases. The proportion of phenotypic variance explained by significant associations is, however, limited. Given the same dense SNP panels, mixed model analyses capture a greater proportion of phenotypic variance than single SNP analyses but the total is generally still less than the genetic variance estimated from pedigree studies. Combining information from pedigree relationships and SNPs, we examined 16 complex anthropometric and cardiometabolic traits in a Scottish family-based cohort comprising up to 20,000 individuals genotyped for ~520,000 common autosomal SNPs. The inclusion of related individuals provides the opportunity to also estimate the genetic variance associated with pedigree as well as the effects of common family environment. Trait variation was partitioned into SNP-associated and pedigree-associated genetic variation, shared nuclear family environment, shared couple (partner) environment and shared full-sibling environment. Results demonstrate that trait heritabilities vary widely but, on average across traits, SNP-associated and pedigree-associated genetic effects each explain around half the genetic variance. For most traits the recently-shared environment of couples is also significant, accounting for ~11% of the phenotypic variance on average. On the other hand, the environment shared largely in the past by members of a nuclear family or by full-siblings, has a more limited impact. Our findings point to appropriate models to use in future studies as pedigree-associated genetic effects and couple environmental effects have seldom been taken into account in genotype-based analyses. Appropriate description of the trait variation could help understand causes of intra-individual variation and in the detection of contributing loci and environmental factors.

Advances in biotechnology and linking outputs to variation in complex traits: Plant and Animal Genome meeting January 2012.

PubMed

Appels, R; Barrero, R; Bellgard, M

2012-03-01

The Plant and Animal Genome (PAG, held annually) meeting in January 2012 provided insights into the advances in plant, animal, and microbe genome studies particularly as they impact on our understanding of complex biological systems. The diverse areas of biology covered included the advances in technologies, variation in complex traits, genome change in evolution, and targeting phenotypic changes, across the broad spectrum of life forms. This overview aims to summarize the major advances in research areas presented in the plenary lectures and does not attempt to summarize the diverse research activities covered throughout the PAG in workshops, posters, presentations, and displays by suppliers of cutting-edge technologies.

Exploring the links between personality traits and motivations to play online games.

PubMed

Park, Jowon; Song, Yosep; Teng, Ching-I

2011-12-01

The present study explores the links between personality traits and motivations to play online games. We identified the underlying dimensions of motivations to play online games, examined how personality traits predict motivation, and investigated how personality traits predict online gaming behavior (i.e., playing time and preference for game genres). Factor analyses identified five motivational factors: relationships, adventure, escapism, relaxation, and achievement. The regression analyses indicated that two personality traits, extraversion and agreeableness, predicted various motivations; however, personality traits did not affect the playing time and game genre preference.

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.

Proteins Encoded in Genomic Regions Associated with Immune-Mediated Disease Physically Interact and Suggest Underlying Biology

PubMed Central

Rossin, Elizabeth J.; Lage, Kasper; Raychaudhuri, Soumya; Xavier, Ramnik J.; Tatar, Diana; Benita, Yair

2011-01-01

Genome-wide association studies (GWAS) have defined over 150 genomic regions unequivocally containing variation predisposing to immune-mediated disease. Inferring disease biology from these observations, however, hinges on our ability to discover the molecular processes being perturbed by these risk variants. It has previously been observed that different genes harboring causal mutations for the same Mendelian disease often physically interact. We sought to evaluate the degree to which this is true of genes within strongly associated loci in complex disease. Using sets of loci defined in rheumatoid arthritis (RA) and Crohn's disease (CD) GWAS, we build protein–protein interaction (PPI) networks for genes within associated loci and find abundant physical interactions between protein products of associated genes. We apply multiple permutation approaches to show that these networks are more densely connected than chance expectation. To confirm biological relevance, we show that the components of the networks tend to be expressed in similar tissues relevant to the phenotypes in question, suggesting the network indicates common underlying processes perturbed by risk loci. Furthermore, we show that the RA and CD networks have predictive power by demonstrating that proteins in these networks, not encoded in the confirmed list of disease associated loci, are significantly enriched for association to the phenotypes in question in extended GWAS analysis. Finally, we test our method in 3 non-immune traits to assess its applicability to complex traits in general. We find that genes in loci associated to height and lipid levels assemble into significantly connected networks but did not detect excess connectivity among Type 2 Diabetes (T2D) loci beyond chance. Taken together, our results constitute evidence that, for many of the complex diseases studied here, common genetic associations implicate regions encoding proteins that physically interact in a preferential manner, in line with observations in Mendelian disease. PMID:21249183

Software errors and complexity: An empirical investigation

NASA Technical Reports Server (NTRS)

Basili, Victor R.; Perricone, Berry T.

1983-01-01

The distributions and relationships derived from the change data collected during the development of a medium scale satellite software project show that meaningful results can be obtained which allow an insight into software traits and the environment in which it is developed. Modified and new modules were shown to behave similarly. An abstract classification scheme for errors which allows a better understanding of the overall traits of a software project is also shown. Finally, various size and complexity metrics are examined with respect to errors detected within the software yielding some interesting results.

Software errors and complexity: An empirical investigation

NASA Technical Reports Server (NTRS)

Basili, V. R.; Perricone, B. T.

1982-01-01

The distributions and relationships derived from the change data collected during the development of a medium scale satellite software project show that meaningful results can be obtained which allow an insight into software traits and the environment in which it is developed. Modified and new modules were shown to behave similarly. An abstract classification scheme for errors which allows a better understanding of the overall traits of a software project is also shown. Finally, various size and complexity metrics are examined with respect to errors detected within the software yielding some interesting results.

Leaf traits show different relationships with shade tolerance in moist versus dry tropical forests.

PubMed

Poorter, Lourens

2009-03-01

Shade tolerance is the central paradigm for understanding forest succession and dynamics, but there is considerable debate as to what the salient features of shade tolerance are, whether adult leaves show similar shade adaptations to seedling leaves, and whether the same leaf adaptations are found in forests under different climatic control. Here, adult leaf and metamer traits were measured for 39 tree species from a tropical moist semi-evergreen forest (1580 mm rain yr(-1)) and 41 species from a dry deciduous forest (1160 mm yr(-1)) in Bolivia. Twenty-six functional traits were measured and related to species regeneration light requirements.Adult leaf traits were clearly associated with shade tolerance. Different, rather than stronger, shade adaptations were found for moist compared with dry forest species. Shade adaptations exclusively found in the evergreen moist forest were related to tough and persistent leaves, and shade adaptations in the dry deciduous forest were related to high light interception and water use.These results suggest that, for forests differing in rainfall seasonality, there is a shift in the relative importance of functional leaf traits and performance trade-offs that control light partitioning. In the moist evergreen forest leaf traits underlying the growth-survival trade-off are important, whereas in the seasonally deciduous forest leaf traits underlying the growth trade-off between low and high light might become important.

Estimating Non-Normal Latent Trait Distributions within Item Response Theory Using True and Estimated Item Parameters

ERIC Educational Resources Information Center

Sass, D. A.; Schmitt, T. A.; Walker, C. M.

2008-01-01

Item response theory (IRT) procedures have been used extensively to study normal latent trait distributions and have been shown to perform well; however, less is known concerning the performance of IRT with non-normal latent trait distributions. This study investigated the degree of latent trait estimation error under normal and non-normal…

Character convergence under competition for nutritionally essential resources.

PubMed

Fox, Jeremy W; Vasseur, David A

2008-11-01

Resource competition is thought to drive divergence in resource use traits (character displacement) by generating selection favoring individuals able to use resources unavailable to others. However, this picture assumes nutritionally substitutable resources (e.g., different prey species). When species compete for nutritionally essential resources (e.g., different nutrients), theory predicts that selection drives character convergence. We used models of two species competing for two essential resources to address several issues not considered by existing theory. The models incorporated either slow evolutionary change in resource use traits or fast physiological or behavioral change. We report four major results. First, competition always generates character convergence, but differences in resource requirements prevent competitors from evolving identical resource use traits. Second, character convergence promotes coexistence. Competing species always attain resource use traits that allow coexistence, and adaptive trait change stabilizes the ecological equilibrium. In contrast, adaptation in allopatry never preadapts species to coexist in sympatry. Third, feedbacks between ecological dynamics and trait dynamics lead to surprising dynamical trajectories such as transient divergence in resource use traits followed by subsequent convergence. Fourth, under sufficiently slow trait change, ecological dynamics often drive one of the competitors to near extinction, which would prevent realization of long-term character convergence in practice.

Genetic determinism of anatomical and hydraulic traits within an apple progeny.

PubMed

Lauri, Pierre-Éric; Gorza, Olivier; Cochard, Hervé; Martinez, Sébastien; Celton, Jean-Marc; Ripetti, Véronique; Lartaud, Marc; Bry, Xavier; Trottier, Catherine; Costes, Evelyne

2011-08-01

The apple tree is known to have an isohydric behaviour, maintaining rather constant leaf water potential in soil with low water status and/or under high evaporative demand. However, little is known on the xylem water transport from roots to leaves from the two perspectives of efficiency and safety, and on its genetic variability. We analysed 16 traits related to hydraulic efficiency and safety, and anatomical traits in apple stems, and the relationships between them. Most variables were found heritable, and we investigated the determinism underlying their genetic control through a quantitative trait loci (QTL) analysis on 90 genotypes from the same progeny. Principal component analysis (PCA) revealed that all traits related to efficiency, whether hydraulic conductivity, vessel number and area or wood area, were included in the first PC, whereas the second PC included the safety variables, thus confirming the absence of trade-off between these two sets of traits. Our results demonstrated that clustered variables were characterized by common genomic regions. Together with previous results on the same progeny, our study substantiated that hydraulic efficiency traits co-localized with traits identified for tree growth and fruit production. © 2011 Blackwell Publishing Ltd.

Effects of parental emotional warmth on the relationship between regional gray matter volume and depression-related personality traits.

PubMed

Yang, Junyi; Yin, Ping; Wei, Dongtao; Wang, Kangcheng; Li, Yongmei; Qiu, Jiang

2017-06-01

The depression-related personality trait is associated with the severity of patients' current depressive symptoms and with the vulnerability to depression within the nonclinical groups. However, little is known about the anatomical structure associated with the depression-related personality traits within the nonclinical sample. Parenting behavior is associated with the depression symptoms; however, whether or not parenting behavior influence the neural basis of the depression-related personality traits is unclear. Thus in current study, first, we used voxel-based morphometry to identify the brain regions underlying individual differences in depression-related personality traits, as measured by the revised Neuroticism-Extraversion-Openness Personality Inventory, in a large sample of young healthy adults. Second, we use mediation analysis to investigate the relationship between parenting behavior and neural basis of depression-related personality traits. The results revealed that depression-related personality traits were positively correlated with gray matter volume mainly in medial frontal gyrus (MFG) that is implicated in the self-referential processing and emotional regulation. Furthermore, parental emotional warmth acted as a mediational mechanism underlying the association between the MFG volume and the depression-related personality trait. Together, our findings suggested that the family environment might play an important role in the acquisition and process of the depression-related personality traits.

Identifying genes affectng stress response in rainbow trout

USDA-ARS?s Scientific Manuscript database

Genomic analyses have the potential to impact aquaculture production traits by identifying markers as proxies for traits which are expensive or difficult to measure and characterizing genetic variation and biochemical mechanisms underlying phenotypic variation. One such set of traits are the respon...

Alternative Strategies in Response to Saline Stress in Two Varieties of Portulaca oleracea (Purslane).

PubMed

Mulry, Kristina R; Hanson, Bryan A; Dudle, Dana A

2015-01-01

Purslane (Portulaca oleracea) is a globally-distributed plant with a long history of use in folk medicine and cooking. We have developed purslane as a model system for exploring plant responses to stress. We exposed two varieties of purslane to saline stress with the objective of identifying differences between the varieties in the plasticity of morphological and physiological traits. The varieties responded to saline stress with significantly different changes in the measured traits, which included inter alia biomass, flower counts, proline concentrations and betalain pigment concentrations. The alternative responses of the two varieties consisted of complex, simultaneous changes in multiple traits. In particular, we observed that while both varieties increased production of betalain pigments and proline under saline stress, one variety invested more in betalain pigments while the other invested more in proline. Proline and betalain pigments undoubtedly play multiple roles in plant tissues, but in this case their role as antioxidants deployed to ameliorate saline stress appears to be important. Taken holistically, our results suggest that the two varieties employ different strategies in allocating resources to cope with saline stress. This conclusion establishes purslane as a suitable model system for the study of saline stress and the molecular basis for differential responses.

Alternative Strategies in Response to Saline Stress in Two Varieties of Portulaca oleracea (Purslane)

PubMed Central

Mulry, Kristina R.; Hanson, Bryan A.; Dudle, Dana A.

2015-01-01

Purslane (Portulaca oleracea) is a globally-distributed plant with a long history of use in folk medicine and cooking. We have developed purslane as a model system for exploring plant responses to stress. We exposed two varieties of purslane to saline stress with the objective of identifying differences between the varieties in the plasticity of morphological and physiological traits. The varieties responded to saline stress with significantly different changes in the measured traits, which included inter alia biomass, flower counts, proline concentrations and betalain pigment concentrations. The alternative responses of the two varieties consisted of complex, simultaneous changes in multiple traits. In particular, we observed that while both varieties increased production of betalain pigments and proline under saline stress, one variety invested more in betalain pigments while the other invested more in proline. Proline and betalain pigments undoubtedly play multiple roles in plant tissues, but in this case their role as antioxidants deployed to ameliorate saline stress appears to be important. Taken holistically, our results suggest that the two varieties employ different strategies in allocating resources to cope with saline stress. This conclusion establishes purslane as a suitable model system for the study of saline stress and the molecular basis for differential responses. PMID:26398279

Combining a weed traits database with a population dynamics model predicts shifts in weed communities.

PubMed

Storkey, J; Holst, N; Bøjer, O Q; Bigongiali, F; Bocci, G; Colbach, N; Dorner, Z; Riemens, M M; Sartorato, I; Sønderskov, M; Verschwele, A

2015-04-01

A functional approach to predicting shifts in weed floras in response to management or environmental change requires the combination of data on weed traits with analytical frameworks that capture the filtering effect of selection pressures on traits. A weed traits database (WTDB) was designed, populated and analysed, initially using data for 19 common European weeds, to begin to consolidate trait data in a single repository. The initial choice of traits was driven by the requirements of empirical models of weed population dynamics to identify correlations between traits and model parameters. These relationships were used to build a generic model, operating at the level of functional traits, to simulate the impact of increasing herbicide and fertiliser use on virtual weeds along gradients of seed weight and maximum height. The model generated 'fitness contours' (defined as population growth rates) within this trait space in different scenarios, onto which two sets of weed species, defined as common or declining in the UK, were mapped. The effect of increasing inputs on the weed flora was successfully simulated; 77% of common species were predicted to have stable or increasing populations under high fertiliser and herbicide use, in contrast with only 29% of the species that have declined. Future development of the WTDB will aim to increase the number of species covered, incorporate a wider range of traits and analyse intraspecific variability under contrasting management and environments.

Mapping Quantitative Trait Loci in Crosses between Outbred Lines Using Least Squares

PubMed Central

Haley, C. S.; Knott, S. A.; Elsen, J. M.

1994-01-01

The use of genetic maps based upon molecular markers has allowed the dissection of some of the factors underlying quantitative variation in crosses between inbred lines. For many species crossing inbred lines is not a practical proposition, although crosses between genetically very different outbred lines are possible. Here we develop a least squares method for the analysis of crosses between outbred lines which simultaneously uses information from multiple linked markers. The method is suitable for crosses where the lines may be segregating at marker loci but can be assumed to be fixed for alternative alleles at the major quantitative trait loci (QTLs) affecting the traits under analysis (e.g., crosses between divergent selection lines or breeds with different selection histories). The simultaneous use of multiple markers from a linkage group increases the sensitivity of the test statistic, and thus the power for the detection of QTLs, compared to the use of single markers or markers flanking an interval. The gain is greater for more closely spaced markers and for markers of lower information content. Use of multiple markers can also remove the bias in the estimated position and effect of a QTL which may result when different markers in a linkage group vary in their heterozygosity in the F(1) (and thus in their information content) and are considered only singly or a pair at a time. The method is relatively simple to apply so that more complex models can be fitted than is currently possible by maximum likelihood. Thus fixed effects and effects of background genotype can be fitted simultaneously with the exploration of a single linkage group which will increase the power to detect QTLs by reducing the residual variance. More complex models with several QTLs in the same linkage group and two-locus interactions between QTLs can similarly be examined. Thus least squares provides a powerful tool to extend the range of crosses from which QTLs can be dissected whilst at the same time allowing flexible and realistic models to be explored. PMID:8005424

Invasion complexity at large spatial scales is an emergent property of interactions among landscape characteristics and invader traits

PubMed Central

Jordan, Nicholas R.; Forester, James D.

2018-01-01

Invasion potential should be part of the evaluation of candidate species for any species introduction. However, estimating invasion risks remains a challenging problem, particularly in complex landscapes. Certain plant traits are generally considered to increase invasive potential and there is an understanding that landscapes influence invasions dynamics, but little research has been done to explore how those drivers of invasions interact. We evaluate the relative roles of, and potential interactions between, plant invasiveness traits and landscape characteristics on invasions with a case study using a model parameterized for the potentially invasive biomass crop, Miscanthus × giganteus. Using that model we simulate invasions on 1000 real landscapes to evaluate how landscape characteristics, including both composition and spatial structure, affect invasion outcomes. We conducted replicate simulations with differing strengths of plant invasiveness traits (dispersal ability, establishment ability, population growth rate, and the ability to utilize dispersal corridors) to evaluate how the importance of landscape characteristics for predicting invasion patterns changes depending on the invader details. Analysis of simulations showed that the presence of highly suitable habitat (e.g., grasslands) is generally the strongest determinant of invasion dynamics but that there are also more subtle interactions between landscapes and invader traits. These effects can also vary between different aspects of invasion dynamics (short vs. long time scales and population size vs. spatial extent). These results illustrate that invasions are complex emergent processes with multiple drivers and effective management needs to reflect the ecology of the species of interest and the particular goals or risks for which efforts need to be optimized. PMID:29771923

The effect of flower position on variation and covariation in floral traits in a wild hermaphrodite plant

PubMed Central

2010-01-01

Background Floral traits within plants can vary with flower position or flowering time. Within an inflorescence, sexual allocation of early produced basal flowers is often female-biased while later produced distal flowers are male-biased. Such temporal adjustment of floral resource has been considered one of the potential advantages of modularity (regarding a flower as a module) in hermaphrodites. However, flowers are under constraints of independent evolution of a given trait. To understand flower diversification within inflorescences, here we examine variation and covariation in floral traits within racemes at the individual and the maternal family level respectively in an alpine herb Aconitum gymnandrum (Ranunculaceae). Results We found that floral traits varied significantly with flower position and among families, and position effects were family-specific. Most of the variance of floral traits was among individuals rather than among flowers within individuals or among families. Significant phenotypic correlations between traits were not affected by position, indicating trait integration under shared developmental regulation. In contrast, positive family-mean correlations in floral traits declined gradually from basal to distal flowers (nine significant correlations among floral traits in basal flowers and only three in distal flowers), showing position-specificity. Therefore, the pattern and magnitude of genetic correlations decreased with flower position. Conclusions This finding on covariation pattern in floral reproductive structures within racemes has not been revealed before, providing insights into temporal variation and position effects in floral traits within plants and the potential advantages of modularity in hermaphrodites. PMID:20482889

The effect of flower position on variation and covariation in floral traits in a wild hermaphrodite plant.

PubMed

Zhao, Zhi-Gang; Du, Guo-Zhen; Huang, Shuang-Quan

2010-05-20

Floral traits within plants can vary with flower position or flowering time. Within an inflorescence, sexual allocation of early produced basal flowers is often female-biased while later produced distal flowers are male-biased. Such temporal adjustment of floral resource has been considered one of the potential advantages of modularity (regarding a flower as a module) in hermaphrodites. However, flowers are under constraints of independent evolution of a given trait. To understand flower diversification within inflorescences, here we examine variation and covariation in floral traits within racemes at the individual and the maternal family level respectively in an alpine herb Aconitum gymnandrum (Ranunculaceae). We found that floral traits varied significantly with flower position and among families, and position effects were family-specific. Most of the variance of floral traits was among individuals rather than among flowers within individuals or among families. Significant phenotypic correlations between traits were not affected by position, indicating trait integration under shared developmental regulation. In contrast, positive family-mean correlations in floral traits declined gradually from basal to distal flowers (nine significant correlations among floral traits in basal flowers and only three in distal flowers), showing position-specificity. Therefore, the pattern and magnitude of genetic correlations decreased with flower position. This finding on covariation pattern in floral reproductive structures within racemes has not been revealed before, providing insights into temporal variation and position effects in floral traits within plants and the potential advantages of modularity in hermaphrodites.

Dissection of the genetic architecture underlying the plant density response by mapping plant height-related traits in maize (Zea mays L.).

PubMed

Ku, Lixia; Zhang, Liangkun; Tian, Zhiqiang; Guo, Shulei; Su, Huihui; Ren, Zhenzhen; Wang, Zhiyong; Li, Guohui; Wang, Xiaobo; Zhu, Yuguang; Zhou, Jinlong; Chen, Yanhui

2015-08-01

Plant height is one of the most heritable traits in maize (Zea mays L.). Understanding the genetic control of plant height is important for elucidating the molecular mechanisms that regulate maize development. To investigate the genetic basis of the plant height response to density in maize, we evaluated the effects of two different plant densities (60,000 and 120,000 plant/hm(2)) on three plant height-related traits (plant height, ear height, and ear height-to-plant height ratio) using four sets of recombinant inbred line populations. The phenotypes observed under the two-plant density treatments indicated that high plant density increased the phenotypic performance values of the three measured traits. Twenty-three quantitative trait loci (QTLs) were detected under the two-plant density treatments, and five QTL clusters were located. Nine QTLs were detected under the low plant density treatment, and seven QTLs were detected under the high plant density treatment. Our results suggested that plant height may be controlled mainly by a common set of genes that could be influenced by additional genetic mechanisms when the plants were grown under high plant density. Fine mapping for genetic regions of the stable QTLs across different plant density environments may provide additional information about their different responses to density. The results presented here provide useful information for further research and will help to reveal the molecular mechanisms related to plant height in response to density.

Genetic architecture underlying convergent evolution of egg-laying behavior in a seed-feeding beetle.

PubMed

Fox, Charles W; Wagner, James D; Cline, Sara; Thomas, Frances Ann; Messina, Frank J

2009-05-01

Independent populations subjected to similar environments often exhibit convergent evolution. An unresolved question is the frequency with which such convergence reflects parallel genetic mechanisms. We examined the convergent evolution of egg-laying behavior in the seed-feeding beetle Callosobruchus maculatus. Females avoid ovipositing on seeds bearing conspecific eggs, but the degree of host discrimination varies among geographic populations. In a previous experiment, replicate lines switched from a small host to a large one evolved reduced discrimination after 40 generations. We used line crosses to determine the genetic architecture underlying this rapid response. The most parsimonious genetic models included dominance and/or epistasis for all crosses. The genetic architecture underlying reduced discrimination in two lines was not significantly different from the architecture underlying differences between geographic populations, but the architecture underlying the divergence of a third line differed from all others. We conclude that convergence of this complex trait may in some cases involve parallel genetic mechanisms.

The bidirectional associations between state anger and rumination and the role of trait mindfulness.

PubMed

Borders, Ashley; Lu, Shou-En

2017-07-01

Rumination is associated with exacerbated angry mood. Angry moods may also trigger rumination. However, research has not empirically tested the bidirectional associations of state rumination and anger, as experience sampling methodology can do. We predicted that state anger and rumination would be bi-directionally associated, both concurrently and over time, even controlling for trait anger and rumination. In addition, because mindfulness is associated with rumination and anger at the bivariate level, we examined the effect of trait mindfulness on the bidirectional association between state rumination and anger. We examined two hypotheses: (i) state rumination mediates the effect of trait mindfulness on state anger; and (ii) trait mindfulness weakens, or moderates, the bidirectional associations between state rumination and anger. In an experience-sampling study, 200 college students reported their current ruminative thinking and angry mood several times a day for 7 days. Mixed model analyses indicated that state anger and rumination predicted each other concurrently. In cross-lagged analyses, previous anger did not uniquely predict current rumination; previous rumination predicted current anger, although the effect was small. In support of our hypothesis, state rumination mediated the association between trait mindfulness and state anger. Additionally, trait mindfulness moderated the concurrent and cross-lagged associations between state rumination and anger, although the results were complex. This study contributes new information about the complex interplay of rumination and anger. Findings also add support to the theory that mindfulness decreases emotional reactivity. Aggr. Behav. 43:342-351, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Anger and the ABC model underlying Rational-Emotive Behavior Therapy.

PubMed

Ziegler, Daniel J; Smith, Phillip N

2004-06-01

The ABC model underlying Ellis's Rational-Emotive Behavior Therapy predicts that people who think more irrationally should display greater trait anger than do people who think less irrationally. This study tested this prediction regarding the ABC model. 186 college students were administered the Survey of Personal Beliefs and the State-Trait Anger Expression Inventory-Second Edition to measure irrational thinking and trait anger, respectively. Students who scored higher on Overall Irrational Thinking and Low Frustration Tolerance scored significantly higher on Trait Anger than did those who scored lower on Overall Irrational Thinking and Low Frustration Tolerance. This indicates support for the ABC model, especially Ellis's construct of irrational beliefs which is central to the model.

Trait-based plant ecology: moving towards a unifying species coexistence theory : Features of the Special Section.

PubMed

Escudero, Adrián; Valladares, Fernando

2016-04-01

Functional traits are the center of recent attempts to unify key ecological theories on species coexistence and assembling in populations and communities. While the plethora of studies on the role of functional traits to explain patterns and dynamics of communities has rendered a complex picture due to the idiosyncrasies of each study system and approach, there is increasing evidence on their actual relevance when aspects such as different spatial scales, intraspecific variability and demography are considered.

The interplay of trait worry and trait anxiety in determining episodic retrieval: The role of cognitive control.

PubMed

Pajkossy, Péter; Keresztes, Attila; Racsmány, Mihály

2017-11-01

Worrying is a key concept in describing the complex relationship between anxiety and cognitive control. On the one hand, cognitive control processes might underlie the specific tendency to engage in worrying (i.e., trait worry), conceptualized as a future-oriented mental problem-solving activity. On the other hand, the general tendency to experience the signs and symptoms of anxiety (i.e., trait anxiety) is suggested to impair cognitive control because worrisome thoughts interfere with task-relevant processing. Based on these opposing tendencies, we predicted that the effect of the two related constructs, trait anxiety and trait worry, might cancel out one another. In statistics, such instances have been termed suppressor situations. In four experiments, we found evidence for such a suppressor situation: When their shared variance was controlled, trait worry was positively whereas trait anxiety was negatively related to performance in a memory task requiring strategic, effortful retrieval. We also showed that these opposing effects are related to temporal context reinstatement. Our results suggest that trait worry and trait anxiety possess unique sources of variance, which differently relate to performance in memory tasks requiring cognitive control.