Integrating Genetic and Functional Genomic Data to Elucidate Common Disease Tra

NASA Astrophysics Data System (ADS)

Schadt, Eric

2005-03-01

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

[Fine mapping of complex disease susceptibility loci].

PubMed

Song, Qingfeng; Zhang, Hongxing; Ma, Yilong; Zhou, Gangqiao

2014-01-01

Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers have identified more than 3800 susceptibility loci for more than 660 diseases or traits. However, the most significantly associated variants or causative variants in these loci and their biological functions have remained to be clarified. These causative variants can help to elucidate the pathogenesis and discover new biomarkers of complex diseases. One of the main goals in the post-GWAS era is to identify the causative variants and susceptibility genes, and clarify their functional aspects by fine mapping. For common variants, imputation or re-sequencing based strategies were implemented to increase the number of analyzed variants and help to identify the most significantly associated variants. In addition, functional element, expression quantitative trait locus (eQTL) and haplotype analyses were performed to identify functional common variants and susceptibility genes. For rare variants, fine mapping was carried out by re-sequencing, rare haplotype analysis, family-based analysis, burden test, etc.This review summarizes the strategies and problems for fine mapping.

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

PubMed

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

2017-02-01

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

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

PubMed Central

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

2017-01-01

Common diseases often show sex differences in prevalence, onset, symptomology, treatment, or prognosis. Although studies have been performed to evaluate sex differences at specific SNP associations, this work aims to comprehensively survey a number of complex heritable diseases and anthropometric traits. Potential genetically encoded sex differences we investigated include differential genetic liability thresholds or distributions, gene–sex interaction at autosomal loci, major contribution of the X-chromosome, or gene–environment interactions reflected in genes responsive to androgens or estrogens. Finally, we tested the overlap between sex-differential association with anthropometric traits and disease risk. We utilized complementary approaches of assessing GWAS association enrichment and SNP-based heritability estimation to explore explicit sex differences, as well as enrichment in sex-implicated functional categories. We do not find consistent increased genetic load in the lower-prevalence sex, or a disproportionate role for the X-chromosome in disease risk, despite sex-heterogeneity on the X for several traits. We find that all anthropometric traits show less than complete correlation between the genetic contribution to males and females, and find a convincing example of autosome-wide genome-sex interaction in multiple sclerosis (P = 1 × 10−9). We also find some evidence for hormone-responsive gene enrichment, and striking evidence of the contribution of sex-differential anthropometric associations to common disease risk, implying that general mechanisms of sexual dimorphism determining secondary sex characteristics have shared effects on disease risk. PMID:27974502

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.

Exome sequencing-driven discovery of coding polymorphisms associated with common metabolic phenotypes.

PubMed

Albrechtsen, A; Grarup, N; Li, Y; Sparsø, T; Tian, G; Cao, H; Jiang, T; Kim, S Y; Korneliussen, T; Li, Q; Nie, C; Wu, R; Skotte, L; Morris, A P; Ladenvall, C; Cauchi, S; Stančáková, A; Andersen, G; Astrup, A; Banasik, K; Bennett, A J; Bolund, L; Charpentier, G; Chen, Y; Dekker, J M; Doney, A S F; Dorkhan, M; Forsen, T; Frayling, T M; Groves, C J; Gui, Y; Hallmans, G; Hattersley, A T; He, K; Hitman, G A; Holmkvist, J; Huang, S; Jiang, H; Jin, X; Justesen, J M; Kristiansen, K; Kuusisto, J; Lajer, M; Lantieri, O; Li, W; Liang, H; Liao, Q; Liu, X; Ma, T; Ma, X; Manijak, M P; Marre, M; Mokrosiński, J; Morris, A D; Mu, B; Nielsen, A A; Nijpels, G; Nilsson, P; Palmer, C N A; Rayner, N W; Renström, F; Ribel-Madsen, R; Robertson, N; Rolandsson, O; Rossing, P; Schwartz, T W; Slagboom, P E; Sterner, M; Tang, M; Tarnow, L; Tuomi, T; van't Riet, E; van Leeuwen, N; Varga, T V; Vestmar, M A; Walker, M; Wang, B; Wang, Y; Wu, H; Xi, F; Yengo, L; Yu, C; Zhang, X; Zhang, J; Zhang, Q; Zhang, W; Zheng, H; Zhou, Y; Altshuler, D; 't Hart, L M; Franks, P W; Balkau, B; Froguel, P; McCarthy, M I; Laakso, M; Groop, L; Christensen, C; Brandslund, I; Lauritzen, T; Witte, D R; Linneberg, A; Jørgensen, T; Hansen, T; Wang, J; Nielsen, R; Pedersen, O

2013-02-01

Human complex metabolic traits are in part regulated by genetic determinants. Here we applied exome sequencing to identify novel associations of coding polymorphisms at minor allele frequencies (MAFs) >1% with common metabolic phenotypes. The study comprised three stages. We performed medium-depth (8×) whole exome sequencing in 1,000 cases with type 2 diabetes, BMI >27.5 kg/m(2) and hypertension and in 1,000 controls (stage 1). We selected 16,192 polymorphisms nominally associated (p < 0.05) with case-control status, from four selected annotation categories or from loci reported to associate with metabolic traits. These variants were genotyped in 15,989 Danes to search for association with 12 metabolic phenotypes (stage 2). In stage 3, polymorphisms showing potential associations were genotyped in a further 63,896 Europeans. Exome sequencing identified 70,182 polymorphisms with MAF >1%. In stage 2 we identified 51 potential associations with one or more of eight metabolic phenotypes covered by 45 unique polymorphisms. In meta-analyses of stage 2 and stage 3 results, we demonstrated robust associations for coding polymorphisms in CD300LG (fasting HDL-cholesterol: MAF 3.5%, p = 8.5 × 10(-14)), COBLL1 (type 2 diabetes: MAF 12.5%, OR 0.88, p = 1.2 × 10(-11)) and MACF1 (type 2 diabetes: MAF 23.4%, OR 1.10, p = 8.2 × 10(-10)). We applied exome sequencing as a basis for finding genetic determinants of metabolic traits and show the existence of low-frequency and common coding polymorphisms with impact on common metabolic traits. Based on our study, coding polymorphisms with MAF above 1% do not seem to have particularly high effect sizes on the measured metabolic traits.

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

Bioenergetic Constraints on the Evolution of Complex Life

PubMed Central

Lane, Nick

2014-01-01

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

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

Clinical Applications of Molecular Genetic Discoveries

PubMed Central

Marian, A.J.

2015-01-01

Genome-wide association studies (GWAS) of complex traits have mapped more than 15,000 common single nucleotide variants (SNVs). Likewise, applications of massively parallel nucleic acid sequencing technologies often referred to as Next Generation Sequencing, to molecular genetic studies of complex traits have catalogued a large number of rare variants (population frequency of <0.01) in cases with complex traits. Moreover, high throughput nucleic acid sequencing, variant burden analysis, and linkage studies are illuminating the presence of large number of SNVs in cases and families with single gene disorders. The plethora of the genetic variants has exposed the formidable challenge of identifying the causal and pathogenic variants from the enormous number of innocuous common and rare variants that exist in the population as well as in an individual genome. The arduous task of identifying the causal and pathogenic variants is further compounded by the pleiotropic effects of the variants, complexity of cis and trans interactions in the genome, variability in phenotypic expression of the disease, as well as phenotypic plasticity, and the multifarious determinants of the phenotype. Population genetic studies offer the initial roadmaps and have the potential to elucidate novel pathways involved in the pathogenesis of the disease. However, the genome of an individual is unique, rendering unambiguous identification of the causal or pathogenic variant in a single individual exceedingly challenging. Yet, the focus of the practice of medicine is on the individual, as Sir William Osler elegantly expressed in his insightful quotation: “The good physician treats the disease; the great physician treats the patient who has the disease.” The daunting task facing physicians, patients, and researchers alike is to apply the modern genetic discoveries to care of the individual with or at risk of the disease. PMID:26548329

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.

Genomic Analyses Reveal the Influence of Geographic Origin, Migration, and Hybridization on Modern Dog Breed Development.

PubMed

Parker, Heidi G; Dreger, Dayna L; Rimbault, Maud; Davis, Brian W; Mullen, Alexandra B; Carpintero-Ramirez, Gretchen; Ostrander, Elaine A

2017-04-25

There are nearly 400 modern domestic dog breeds with a unique histories and genetic profiles. To track the genetic signatures of breed development, we have assembled the most diverse dataset of dog breeds, reflecting their extensive phenotypic variation and heritage. Combining genetic distance, migration, and genome-wide haplotype sharing analyses, we uncover geographic patterns of development and independent origins of common traits. Our analyses reveal the hybrid history of breeds and elucidate the effects of immigration, revealing for the first time a suggestion of New World dog within some modern breeds. Finally, we used cladistics and haplotype sharing to show that some common traits have arisen more than once in the history of the dog. These analyses characterize the complexities of breed development, resolving longstanding questions regarding individual breed origination, the effect of migration on geographically distinct breeds, and, by inference, transfer of trait and disease alleles among dog breeds. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Joint QTL linkage mapping for multiple-cross mating design sharing one common parent

USDA-ARS?s Scientific Manuscript database

Nested association mapping (NAM) is a novel genetic mating design that combines the advantages of linkage analysis and association mapping. This design provides opportunities to study the inheritance of complex traits, but also requires more advanced statistical methods. In this paper, we present th...

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

PubMed

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

2010-12-01

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

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.

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

PubMed Central

Monir, Md. Mamun; Zhu, Jun

2017-01-01

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

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

PubMed

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

2018-01-01

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

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.

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

Population- and individual-specific regulatory variation in Sardinia.

PubMed

Pala, Mauro; Zappala, Zachary; Marongiu, Mara; Li, Xin; Davis, Joe R; Cusano, Roberto; Crobu, Francesca; Kukurba, Kimberly R; Gloudemans, Michael J; Reinier, Frederic; Berutti, Riccardo; Piras, Maria G; Mulas, Antonella; Zoledziewska, Magdalena; Marongiu, Michele; Sorokin, Elena P; Hess, Gaelen T; Smith, Kevin S; Busonero, Fabio; Maschio, Andrea; Steri, Maristella; Sidore, Carlo; Sanna, Serena; Fiorillo, Edoardo; Bassik, Michael C; Sawcer, Stephen J; Battle, Alexis; Novembre, John; Jones, Chris; Angius, Andrea; Abecasis, Gonçalo R; Schlessinger, David; Cucca, Francesco; Montgomery, Stephen B

2017-05-01

Genetic studies of complex traits have mainly identified associations with noncoding variants. To further determine the contribution of regulatory variation, we combined whole-genome and transcriptome data for 624 individuals from Sardinia to identify common and rare variants that influence gene expression and splicing. We identified 21,183 expression quantitative trait loci (eQTLs) and 6,768 splicing quantitative trait loci (sQTLs), including 619 new QTLs. We identified high-frequency QTLs and found evidence of selection near genes involved in malarial resistance and increased multiple sclerosis risk, reflecting the epidemiological history of Sardinia. Using family relationships, we identified 809 segregating expression outliers (median z score of 2.97), averaging 13.3 genes per individual. Outlier genes were enriched for proximal rare variants, providing a new approach to study large-effect regulatory variants and their relevance to traits. Our results provide insight into the effects of regulatory variants and their relationship to population history and individual genetic risk.

Multidimensional assessment of severe asthma: A systematic review and meta-analysis.

PubMed

Clark, Vanessa L; Gibson, Peter G; Genn, Grayson; Hiles, Sarah A; Pavord, Ian D; McDonald, Vanessa M

2017-10-01

The management of severe asthma is complex. Multidimensional assessment (MDA) of specific traits has been proposed as an effective strategy to manage severe asthma, although it is supported by few prospective studies. We aimed to systematically review the literature published on MDA in severe asthma, to identify the traits included in MDA and to determine the effect of MDA on asthma-related outcomes. We identified 26 studies and classified these based on study type (cohort/cross-sectional studies; experimental/outcome studies; and severe asthma disease registries). Study type determined the comprehensiveness of the assessment. Assessed traits were classified into three domains (airways, co-morbidities and risk factors). The airway domain had the largest number of traits assessed (mean ± SD = 4.2 ± 1.7) compared with co-morbidities (3.6 ± 2.2) and risk factors (3.9 ± 2.1). Bronchodilator reversibility and airflow limitation were assessed in 92% of studies, whereas airway inflammation was only assessed in 50%. Commonly assessed co-morbidities were psychological dysfunction, sinusitis (both 73%) and gastro-oesophageal reflux disease (GORD; 69%). Atopic and smoking statuses were the most commonly assessed risk factors (85% and 86%, respectively). There were six outcome studies, of which five concluded that MDA is effective at improving asthma-related outcomes. Among these studies, significantly more traits were assessed than treated. MDA studies have assessed a variety of different traits and have shown evidence of improved outcomes. This promising model of care requires more research to inform which traits should be assessed, which traits should be treated and what effect MDA has on patient outcomes. © 2017 Asian Pacific Society of Respirology.

Estimation of (co)variances for genomic regions of flexible sizes: application to complex infectious udder diseases in dairy cattle

PubMed Central

2012-01-01

Background Multi-trait genomic models in a Bayesian context can be used to estimate genomic (co)variances, either for a complete genome or for genomic regions (e.g. per chromosome) for the purpose of multi-trait genomic selection or to gain further insight into the genomic architecture of related traits such as mammary disease traits in dairy cattle. Methods Data on progeny means of six traits related to mastitis resistance in dairy cattle (general mastitis resistance and five pathogen-specific mastitis resistance traits) were analyzed using a bivariate Bayesian SNP-based genomic model with a common prior distribution for the marker allele substitution effects and estimation of the hyperparameters in this prior distribution from the progeny means data. From the Markov chain Monte Carlo samples of the allele substitution effects, genomic (co)variances were calculated on a whole-genome level, per chromosome, and in regions of 100 SNP on a chromosome. Results Genomic proportions of the total variance differed between traits. Genomic correlations were lower than pedigree-based genetic correlations and they were highest between general mastitis and pathogen-specific traits because of the part-whole relationship between these traits. The chromosome-wise genomic proportions of the total variance differed between traits, with some chromosomes explaining higher or lower values than expected in relation to chromosome size. Few chromosomes showed pleiotropic effects and only chromosome 19 had a clear effect on all traits, indicating the presence of QTL with a general effect on mastitis resistance. The region-wise patterns of genomic variances differed between traits. Peaks indicating QTL were identified but were not very distinctive because a common prior for the marker effects was used. There was a clear difference in the region-wise patterns of genomic correlation among combinations of traits, with distinctive peaks indicating the presence of pleiotropic QTL. Conclusions The results show that it is possible to estimate, genome-wide and region-wise genomic (co)variances of mastitis resistance traits in dairy cattle using multivariate genomic models. PMID:22640006

Network morphospace

PubMed Central

Avena-Koenigsberger, Andrea; Goñi, Joaquín; Solé, Ricard; Sporns, Olaf

2015-01-01

The structure of complex networks has attracted much attention in recent years. It has been noted that many real-world examples of networked systems share a set of common architectural features. This raises important questions about their origin, for example whether such network attributes reflect common design principles or constraints imposed by selectional forces that have shaped the evolution of network topology. Is it possible to place the many patterns and forms of complex networks into a common space that reveals their relations, and what are the main rules and driving forces that determine which positions in such a space are occupied by systems that have actually evolved? We suggest that these questions can be addressed by combining concepts from two currently relatively unconnected fields. One is theoretical morphology, which has conceptualized the relations between morphological traits defined by mathematical models of biological form. The second is network science, which provides numerous quantitative tools to measure and classify different patterns of local and global network architecture across disparate types of systems. Here, we explore a new theoretical concept that lies at the intersection between both fields, the ‘network morphospace’. Defined by axes that represent specific network traits, each point within such a space represents a location occupied by networks that share a set of common ‘morphological’ characteristics related to aspects of their connectivity. Mapping a network morphospace reveals the extent to which the space is filled by existing networks, thus allowing a distinction between actual and impossible designs and highlighting the generative potential of rules and constraints that pervade the evolution of complex systems. PMID:25540237

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

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.

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

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

PubMed Central

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

2016-01-01

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

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

PubMed Central

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

2013-01-01

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

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.

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

PubMed

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

2016-04-01

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

Influence of resistance breeding in common bean on rhizosphere microbiome composition and function.

PubMed

Mendes, Lucas William; Raaijmakers, Jos M; de Hollander, Mattias; Mendes, Rodrigo; Tsai, Siu Mui

2018-01-01

The rhizosphere microbiome has a key role in plant growth and health, providing a first line of defense against root infections by soil-borne pathogens. Here, we investigated the composition and metabolic potential of the rhizobacterial community of different common bean (Phaseolus vulgaris) cultivars with variable levels of resistance to the fungal root pathogen Fusarium oxysporum (Fox). For the different bean cultivars grown in two soils with contrasting physicochemical properties and microbial diversity, rhizobacterial abundance was positively correlated with Fox resistance. Pseudomonadaceae, bacillaceae, solibacteraceae and cytophagaceae were more abundant in the rhizosphere of the Fox-resistant cultivar. Network analyses showed a modular topology of the rhizosphere microbiome of the Fox-resistant cultivar, suggesting a more complex and highly connected bacterial community than in the rhizosphere of the Fox-susceptible cultivar. Metagenome analyses further revealed that specific functional traits such as protein secretion systems and biosynthesis genes of antifungal phenazines and rhamnolipids were more abundant in the rhizobacterial community of the Fox-resistant cultivar. Our findings suggest that breeding for Fox resistance in common bean may have co-selected for other unknown plant traits that support a higher abundance of specific beneficial bacterial families in the rhizosphere with functional traits that reinforce the first line of defense.

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

A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis.

PubMed

Ishikawa, Akira

2017-11-27

Large numbers of quantitative trait loci (QTL) affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs) for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

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

PubMed

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

2009-01-01

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

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.

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.

Rare-Variant Association Analysis: Study Designs and Statistical Tests

PubMed Central

Lee, Seunggeung; Abecasis, Gonçalo R.; Boehnke, Michael; Lin, Xihong

2014-01-01

Despite the extensive discovery of trait- and disease-associated common variants, much of the genetic contribution to complex traits remains unexplained. Rare variants can explain additional disease risk or trait variability. An increasing number of studies are underway to identify trait- and disease-associated rare variants. In this review, we provide an overview of statistical issues in rare-variant association studies with a focus on study designs and statistical tests. We present the design and analysis pipeline of rare-variant studies and review cost-effective sequencing designs and genotyping platforms. We compare various gene- or region-based association tests, including burden tests, variance-component tests, and combined omnibus tests, in terms of their assumptions and performance. Also discussed are the related topics of meta-analysis, population-stratification adjustment, genotype imputation, follow-up studies, and heritability due to rare variants. We provide guidelines for analysis and discuss some of the challenges inherent in these studies and future research directions. PMID:24995866

Generation time, life history and the substitution rate of neutral mutations.

PubMed

Lehtonen, Jussi; Lanfear, Robert

2014-11-01

Our understanding of molecular evolution is hampered by a lack of quantitative predictions about how life-history (LH) traits should correlate with substitution rates. Comparative studies have shown that neutral substitution rates vary substantially between species, and evidence shows that much of this diversity is associated with variation in LH traits. However, while these studies often agree, some unexplained and contradictory results have emerged. Explaining these results is difficult without a clear theoretical understanding of the problem. In this study, we derive predictions for the relationships between LH traits and substitution rates in iteroparous species by using demographic theory to relate commonly measured life-history traits to genetic generation time, and by implication to neutral substitution rates. This provides some surprisingly simple explanations for otherwise confusing patterns, such as the association between fecundity and substitution rates. The same framework can be applied to more complex life histories if full life-tables are available. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

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

Size of Food Resource Determines Brood Placement in Reticulitermes flavipes (Isoptera: Rhimtermitidae)

Treesearch

Michael Lenzl; Bradford Kara; Joe K. Mauldin; Theodore A. Evans; Joel L. Etheridge; Hilda M. Abbey

2000-01-01

Most species of subterranean termite house and care for larvae in specialised chambers or complex nurseries. In addition to these chambers, the genus Reticulitermes also keeps larvae at sites where foragers are feeding, a trait more commonly found in damp wood and dry wood termites. This phenomenon of holding larvae at foraging sites is quite well...

Genetics of pediatric obesity.

PubMed

Manco, Melania; Dallapiccola, Bruno

2012-07-01

Onset of obesity has been anticipated at earlier ages, and prevalence has dramatically increased worldwide over the past decades. Epidemic obesity is mainly attributable to modern lifestyle, but family studies prove the significant role of genes in the individual's predisposition to obesity. Advances in genotyping technologies have raised great hope and expectations that genetic testing will pave the way to personalized medicine and that complex traits such as obesity will be prevented even before birth. In the presence of the pressing offer of direct-to-consumer genetic testing services from private companies to estimate the individual's risk for complex phenotypes including obesity, the present review offers pediatricians an update of the state of the art on genomics obesity in childhood. Discrepancies with respect to genomics of adult obesity are discussed. After an appraisal of findings from genome-wide association studies in pediatric populations, the rare variant-common disease hypothesis, the theoretical soil for next-generation sequencing techniques, is discussed as opposite to the common disease-common variant hypothesis. Next-generation sequencing techniques are expected to fill the gap of "missing heritability" of obesity, identifying rare variants associated with the trait and clarifying the role of epigenetics in its heritability. Pediatric obesity emerges as a complex phenotype, modulated by unique gene-environment interactions that occur in periods of life and are "permissive" for the programming of adult obesity. With the advent of next-generation sequencing techniques and advances in the field of exposomics, sensitive and specific tools to predict the obesity risk as early as possible are the challenge for the next decade.

Simple versus complex models of trait evolution and stasis as a response to environmental change

NASA Astrophysics Data System (ADS)

Hunt, Gene; Hopkins, Melanie J.; Lidgard, Scott

2015-04-01

Previous analyses of evolutionary patterns, or modes, in fossil lineages have focused overwhelmingly on three simple models: stasis, random walks, and directional evolution. Here we use likelihood methods to fit an expanded set of evolutionary models to a large compilation of ancestor-descendant series of populations from the fossil record. In addition to the standard three models, we assess more complex models with punctuations and shifts from one evolutionary mode to another. As in previous studies, we find that stasis is common in the fossil record, as is a strict version of stasis that entails no real evolutionary changes. Incidence of directional evolution is relatively low (13%), but higher than in previous studies because our analytical approach can more sensitively detect noisy trends. Complex evolutionary models are often favored, overwhelmingly so for sequences comprising many samples. This finding is consistent with evolutionary dynamics that are, in reality, more complex than any of the models we consider. Furthermore, the timing of shifts in evolutionary dynamics varies among traits measured from the same series. Finally, we use our empirical collection of evolutionary sequences and a long and highly resolved proxy for global climate to inform simulations in which traits adaptively track temperature changes over time. When realistically calibrated, we find that this simple model can reproduce important aspects of our paleontological results. We conclude that observed paleontological patterns, including the prevalence of stasis, need not be inconsistent with adaptive evolution, even in the face of unstable physical environments.

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.

The multiscale backbone of the human phenotype network based on biological pathways.

PubMed

Darabos, Christian; White, Marquitta J; Graham, Britney E; Leung, Derek N; Williams, Scott M; Moore, Jason H

2014-01-25

Networks are commonly used to represent and analyze large and complex systems of interacting elements. In systems biology, human disease networks show interactions between disorders sharing common genetic background. We built pathway-based human phenotype network (PHPN) of over 800 physical attributes, diseases, and behavioral traits; based on about 2,300 genes and 1,200 biological pathways. Using GWAS phenotype-to-genes associations, and pathway data from Reactome, we connect human traits based on the common patterns of human biological pathways, detecting more pleiotropic effects, and expanding previous studies from a gene-centric approach to that of shared cell-processes. The resulting network has a heavily right-skewed degree distribution, placing it in the scale-free region of the network topologies spectrum. We extract the multi-scale information backbone of the PHPN based on the local densities of the network and discarding weak connection. Using a standard community detection algorithm, we construct phenotype modules of similar traits without applying expert biological knowledge. These modules can be assimilated to the disease classes. However, we are able to classify phenotypes according to shared biology, and not arbitrary disease classes. We present examples of expected clinical connections identified by PHPN as proof of principle. We unveil a previously uncharacterized connection between phenotype modules and discuss potential mechanistic connections that are obvious only in retrospect. The PHPN shows tremendous potential to become a useful tool both in the unveiling of the diseases' common biology, and in the elaboration of diagnosis and treatments.

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

PubMed

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

2016-01-01

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

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

PubMed Central

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

2016-01-01

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

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

PubMed Central

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

2018-01-01

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

Incremental Validity of the DSM-5 Section III Personality Disorder Traits With Respect to Psychosocial Impairment.

PubMed

Simms, Leonard J; Calabrese, William R

2016-02-01

Traditional personality disorders (PDs) are associated with significant psychosocial impairment. DSM-5 Section III includes an alternative hybrid personality disorder (PD) classification approach, with both type and trait elements, but relatively little is known about the impairments associated with Section III traits. Our objective was to study the incremental validity of Section III traits--compared to normal-range traits, traditional PD criterion counts, and common psychiatric symptomatology--in predicting psychosocial impairment. To that end, 628 current/recent psychiatric patients completed measures of PD traits, normal-range traits, traditional PD criteria, psychiatric symptomatology, and psychosocial impairments. Hierarchical regressions revealed that Section III PD traits incrementally predicted psychosocial impairment over normal-range personality traits, PD criterion counts, and common psychiatric symptomatology. In contrast, the incremental effects for normal-range traits, PD symptom counts, and common psychiatric symptomatology were substantially smaller than for PD traits. These findings have implications for PD classification and the impairment literature more generally.

How important are rare variants in common disease?

PubMed

Saint Pierre, Aude; Génin, Emmanuelle

2014-09-01

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

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

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.

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

Molecular genetic contributions to socioeconomic status and intelligence

PubMed Central

Marioni, Riccardo E.; Davies, Gail; Hayward, Caroline; Liewald, Dave; Kerr, Shona M.; Campbell, Archie; Luciano, Michelle; Smith, Blair H.; Padmanabhan, Sandosh; Hocking, Lynne J.; Hastie, Nicholas D.; Wright, Alan F.; Porteous, David J.; Visscher, Peter M.; Deary, Ian J.

2014-01-01

Education, socioeconomic status, and intelligence are commonly used as predictors of health outcomes, social environment, and mortality. Education and socioeconomic status are typically viewed as environmental variables although both correlate with intelligence, which has a substantial genetic basis. Using data from 6815 unrelated subjects from the Generation Scotland study, we examined the genetic contributions to these variables and their genetic correlations. Subjects underwent genome-wide testing for common single nucleotide polymorphisms (SNPs). DNA-derived heritability estimates and genetic correlations were calculated using the ‘Genome-wide Complex Trait Analyses’ (GCTA) procedures. 21% of the variation in education, 18% of the variation in socioeconomic status, and 29% of the variation in general cognitive ability was explained by variation in common SNPs (SEs ~ 5%). The SNP-based genetic correlations of education and socioeconomic status with general intelligence were 0.95 (SE 0.13) and 0.26 (0.16), respectively. There are genetic contributions to intelligence and education with near-complete overlap between common additive SNP effects on these traits (genetic correlation ~ 1). Genetic influences on socioeconomic status are also associated with the genetic foundations of intelligence. The results are also compatible with substantial environmental contributions to socioeconomic status. PMID:24944428

Molecular genetic contributions to socioeconomic status and intelligence.

PubMed

Marioni, Riccardo E; Davies, Gail; Hayward, Caroline; Liewald, Dave; Kerr, Shona M; Campbell, Archie; Luciano, Michelle; Smith, Blair H; Padmanabhan, Sandosh; Hocking, Lynne J; Hastie, Nicholas D; Wright, Alan F; Porteous, David J; Visscher, Peter M; Deary, Ian J

2014-05-01

Education, socioeconomic status, and intelligence are commonly used as predictors of health outcomes, social environment, and mortality. Education and socioeconomic status are typically viewed as environmental variables although both correlate with intelligence, which has a substantial genetic basis. Using data from 6815 unrelated subjects from the Generation Scotland study, we examined the genetic contributions to these variables and their genetic correlations. Subjects underwent genome-wide testing for common single nucleotide polymorphisms (SNPs). DNA-derived heritability estimates and genetic correlations were calculated using the 'Genome-wide Complex Trait Analyses' (GCTA) procedures. 21% of the variation in education, 18% of the variation in socioeconomic status, and 29% of the variation in general cognitive ability was explained by variation in common SNPs (SEs ~ 5%). The SNP-based genetic correlations of education and socioeconomic status with general intelligence were 0.95 (SE 0.13) and 0.26 (0.16), respectively. There are genetic contributions to intelligence and education with near-complete overlap between common additive SNP effects on these traits (genetic correlation ~ 1). Genetic influences on socioeconomic status are also associated with the genetic foundations of intelligence. The results are also compatible with substantial environmental contributions to socioeconomic status.

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.

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.

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...

Contribution of Large Region Joint Associations to Complex Traits Genetics

PubMed Central

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

2015-01-01

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

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

PubMed Central

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

2003-01-01

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

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.

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.

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

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

The evolution of human warfare.

PubMed

Pitman, George R

2011-01-01

Here we propose a new theory for the origins and evolution of human warfare as a complex social phenomenon involving several behavioral traits, including aggression, risk taking, male bonding, ingroup altruism, outgroup xenophobia, dominance and subordination, and territoriality, all of which are encoded in the human genome. Among the family of great apes only chimpanzees and humans engage in war; consequently, warfare emerged in their immediate common ancestor that lived in patrilocal groups who fought one another for females. The reasons for warfare changed when the common ancestor females began to immigrate into the groups of their choice, and again, during the agricultural revolution.

Unusual Sleep Experiences, Dissociation, and Schizotypy: Evidence for a Common Domain

PubMed Central

Koffel, Erin; Watson, David

2009-01-01

This paper reviews studies that have examined associations between unusual sleep experiences (including nightmares, vivid dreaming, narcolepsy symptoms, and complex nighttime behaviors) and dissociation and schizotypy. Using correlational studies and structural analyses, evidence is provided that unusual sleep experiences, dissociation, and schizotypy belong to a common domain. It is demonstrated that unusual sleep experiences show specificity to dissociation and schizotypy compared to other daytime symptoms (e.g., anxiety, depression, substance use) and other sleep disturbances (e.g., insomnia, lassitude/fatigue). The paper also outlines the methodological limitations of the existing evidence and makes suggestions for future research. Finally, three models for the overlap of daytime and nighttime symptoms are reviewed, including biological abnormalities, trauma, and personality traits. Although further research is needed, it is suggested that daytime and nighttime symptoms result from problems with sleep-wake state boundaries, which may be precipitated by stress or trauma. In addition, association between daytime and nighttime symptoms can be attributed to the higher order personality trait of Oddity. PMID:19581031

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.

Effect of genetic architecture on the prediction accuracy of quantitative traits in samples of unrelated individuals.

PubMed

Morgante, Fabio; Huang, Wen; Maltecca, Christian; Mackay, Trudy F C

2018-06-01

Predicting complex phenotypes from genomic data is a fundamental aim of animal and plant breeding, where we wish to predict genetic merits of selection candidates; and of human genetics, where we wish to predict disease risk. While genomic prediction models work well with populations of related individuals and high linkage disequilibrium (LD) (e.g., livestock), comparable models perform poorly for populations of unrelated individuals and low LD (e.g., humans). We hypothesized that low prediction accuracies in the latter situation may occur when the genetics architecture of the trait departs from the infinitesimal and additive architecture assumed by most prediction models. We used simulated data for 10,000 lines based on sequence data from a population of unrelated, inbred Drosophila melanogaster lines to evaluate this hypothesis. We show that, even in very simplified scenarios meant as a stress test of the commonly used Genomic Best Linear Unbiased Predictor (G-BLUP) method, using all common variants yields low prediction accuracy regardless of the trait genetic architecture. However, prediction accuracy increases when predictions are informed by the genetic architecture inferred from mapping the top variants affecting main effects and interactions in the training data, provided there is sufficient power for mapping. When the true genetic architecture is largely or partially due to epistatic interactions, the additive model may not perform well, while models that account explicitly for interactions generally increase prediction accuracy. Our results indicate that accounting for genetic architecture can improve prediction accuracy for quantitative traits.

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.

Effects of rearing environment and population origin on responses to repeated behavioural trials in cane toads (Rhinella marina).

PubMed

Gruber, Jodie; Whiting, Martin J; Brown, Gregory; Shine, Richard

2018-05-02

Behavioural response to repeated trials in captivity can be driven by many factors including rearing environment, population of origin, habituation to captivity/trial conditions and an individual's behavioural type (e.g., bold versus shy). We tested the effect of rearing environment (captive raised common-garden versus wild-caught) and population origin (range-edge versus range-front) on the responses of invasive cane toads (Rhinella marina) to repeated exploration and risk-taking assays in captivity. We found that behavioural responses to identical assays performed on two occasions were complex and showed few consistent patterns based on rearing environment or population of origin. However, behavioural traits were repeatable across Trial Blocks when all sample populations were grouped together, indicating general consistency in individual toad behaviour across repeated behavioural assays. Our findings exemplify the complexity and unpredictability of behavioural responses and their effects on the repeatability and interpretation of behavioural traits across repeated behavioural assays in captivity. To meaningfully interpret the results from repeated behavioural assays, we need to consider how multiple factors may affect behavioural responses to these tests and importantly, how these responses may affect the repeatability of behavioural traits across time. Copyright © 2018. Published by Elsevier B.V.

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.

Network-based integration of systems genetics data reveals pathways associated with lignocellulosic biomass accumulation and processing

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

Mizrachi, Eshchar; Verbeke, Lieven; Christie, Nanette

As a consequence of their remarkable adaptability, fast growth, and superior wood properties, eucalypt tree plantations have emerged as key renewable feedstocks (over 20 million ha globally) for the production of pulp, paper, bioenergy, and other lignocellulosic products. However, most biomass properties such as growth, wood density, and wood chemistry are complex traits that are hard to improve in long-lived perennials. Systems genetics, a process of harnessing multiple levels of component trait information (e.g., transcript, protein, and metabolite variation) in populations that vary in complex traits, has proven effective for dissecting the genetics and biology of such traits. We havemore » applied a network-based data integration (NBDI) method for a systems-level analysis of genes, processes and pathways underlying biomass and bioenergy-related traits using a segregating Eucalyptus hybrid population. We show that the integrative approach can link biologically meaningful sets of genes to complex traits and at the same time reveal the molecular basis of trait variation. Gene sets identified for related woody biomass traits were found to share regulatory loci, cluster in network neighborhoods, and exhibit enrichment for molecular functions such as xylan metabolism and cell wall development. These findings offer a framework for identifying the molecular underpinnings of complex biomass and bioprocessing-related traits. Furthermore, a more thorough understanding of the molecular basis of plant biomass traits should provide additional opportunities for the establishment of a sustainable bio-based economy.« less

Network-based integration of systems genetics data reveals pathways associated with lignocellulosic biomass accumulation and processing

DOE PAGES

Mizrachi, Eshchar; Verbeke, Lieven; Christie, Nanette; ...

2017-01-17

As a consequence of their remarkable adaptability, fast growth, and superior wood properties, eucalypt tree plantations have emerged as key renewable feedstocks (over 20 million ha globally) for the production of pulp, paper, bioenergy, and other lignocellulosic products. However, most biomass properties such as growth, wood density, and wood chemistry are complex traits that are hard to improve in long-lived perennials. Systems genetics, a process of harnessing multiple levels of component trait information (e.g., transcript, protein, and metabolite variation) in populations that vary in complex traits, has proven effective for dissecting the genetics and biology of such traits. We havemore » applied a network-based data integration (NBDI) method for a systems-level analysis of genes, processes and pathways underlying biomass and bioenergy-related traits using a segregating Eucalyptus hybrid population. We show that the integrative approach can link biologically meaningful sets of genes to complex traits and at the same time reveal the molecular basis of trait variation. Gene sets identified for related woody biomass traits were found to share regulatory loci, cluster in network neighborhoods, and exhibit enrichment for molecular functions such as xylan metabolism and cell wall development. These findings offer a framework for identifying the molecular underpinnings of complex biomass and bioprocessing-related traits. Furthermore, a more thorough understanding of the molecular basis of plant biomass traits should provide additional opportunities for the establishment of a sustainable bio-based economy.« less

Network-based integration of systems genetics data reveals pathways associated with lignocellulosic biomass accumulation and processing.

PubMed

Mizrachi, Eshchar; Verbeke, Lieven; Christie, Nanette; Fierro, Ana C; Mansfield, Shawn D; Davis, Mark F; Gjersing, Erica; Tuskan, Gerald A; Van Montagu, Marc; Van de Peer, Yves; Marchal, Kathleen; Myburg, Alexander A

2017-01-31

As a consequence of their remarkable adaptability, fast growth, and superior wood properties, eucalypt tree plantations have emerged as key renewable feedstocks (over 20 million ha globally) for the production of pulp, paper, bioenergy, and other lignocellulosic products. However, most biomass properties such as growth, wood density, and wood chemistry are complex traits that are hard to improve in long-lived perennials. Systems genetics, a process of harnessing multiple levels of component trait information (e.g., transcript, protein, and metabolite variation) in populations that vary in complex traits, has proven effective for dissecting the genetics and biology of such traits. We have applied a network-based data integration (NBDI) method for a systems-level analysis of genes, processes and pathways underlying biomass and bioenergy-related traits using a segregating Eucalyptus hybrid population. We show that the integrative approach can link biologically meaningful sets of genes to complex traits and at the same time reveal the molecular basis of trait variation. Gene sets identified for related woody biomass traits were found to share regulatory loci, cluster in network neighborhoods, and exhibit enrichment for molecular functions such as xylan metabolism and cell wall development. These findings offer a framework for identifying the molecular underpinnings of complex biomass and bioprocessing-related traits. A more thorough understanding of the molecular basis of plant biomass traits should provide additional opportunities for the establishment of a sustainable bio-based economy.

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

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.

Patients with Gilles de la Tourette syndrome have widespread personality differences.

PubMed

Trillini, Morounke O; Müller-Vahl, Kirsten R

2015-08-30

Only little is known about pathological personality traits in patients with Gilles de la Tourette syndrome (GTS). The aim of this study was to further investigate the prevalence of personality traits in adults with GTS. We used a variety of rating scales to assess not only personality traits, but also severity of tics, quality of life, and comorbidities (obsessive-compulsive disorder (OCD), attention deficit hyperactivity disorder (ADHD), depression), in a large group (n=50) of patients. Our major finding was that pathological personality traits are very common in patients with GTS encompassing a wide range of different personality traits, but most typically personality traits related to cluster C. Demand-anxious was the most common personality trait, while histrionic personality trait was absent. Patients' quality of life was more impaired by personality traits than comorbidities. Personality traits were more common in patients with comorbid OCD and depression, while comorbid ADHD had no influence. Our findings, therefore, corroborate the hypothesis that GTS plus OCD represents a more severe subtype of GTS, and support the assumption that OCD and depression, but not ADHD, are part of the GTS spectrum. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The genetic architecture of Drosophila sensory bristle number.

PubMed Central

Dilda, Christy L; Mackay, Trudy F C

2002-01-01

We have mapped quantitative trait loci (QTL) for Drosophila mechanosensory bristle number in six recombinant isogenic line (RIL) mapping populations, each of which was derived from an isogenic chromosome extracted from a line selected for high or low, sternopleural or abdominal bristle number and an isogenic wild-type chromosome. All RILs were evaluated as male and female F(1) progeny of crosses to both the selected and the wild-type parental chromosomes at three developmental temperatures (18 degrees, 25 degrees, and 28 degrees ). QTL for bristle number were mapped separately for each chromosome, trait, and environment by linkage to roo transposable element marker loci, using composite interval mapping. A total of 53 QTL were detected, of which 33 affected sternopleural bristle number, 31 affected abdominal bristle number, and 11 affected both traits. The effects of most QTL were conditional on sex (27%), temperature (14%), or both sex and temperature (30%). Epistatic interactions between QTL were also common. While many QTL mapped to the same location as candidate bristle development loci, several QTL regions did not encompass obvious candidate genes. These features are germane to evolutionary models for the maintenance of genetic variation for quantitative traits, but complicate efforts to understand the molecular genetic basis of variation for complex traits. PMID:12524340

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

Comparison of gene-based rare variant association mapping methods for quantitative traits in a bovine population with complex familial relationships.

PubMed

Zhang, Qianqian; Guldbrandtsen, Bernt; Calus, Mario P L; Lund, Mogens Sandø; Sahana, Goutam

2016-08-17

There is growing interest in the role of rare variants in the variation of complex traits due to increasing evidence that rare variants are associated with quantitative traits. However, association methods that are commonly used for mapping common variants are not effective to map rare variants. Besides, livestock populations have large half-sib families and the occurrence of rare variants may be confounded with family structure, which makes it difficult to disentangle their effects from family mean effects. We compared the power of methods that are commonly applied in human genetics to map rare variants in cattle using whole-genome sequence data and simulated phenotypes. We also studied the power of mapping rare variants using linear mixed models (LMM), which are the method of choice to account for both family relationships and population structure in cattle. We observed that the power of the LMM approach was low for mapping a rare variant (defined as those that have frequencies lower than 0.01) with a moderate effect (5 to 8 % of phenotypic variance explained by multiple rare variants that vary from 5 to 21 in number) contributing to a QTL with a sample size of 1000. In contrast, across the scenarios studied, statistical methods that are specialized for mapping rare variants increased power regardless of whether multiple rare variants or a single rare variant underlie a QTL. Different methods for combining rare variants in the test single nucleotide polymorphism set resulted in similar power irrespective of the proportion of total genetic variance explained by the QTL. However, when the QTL variance is very small (only 0.1 % of the total genetic variance), these specialized methods for mapping rare variants and LMM generally had no power to map the variants within a gene with sample sizes of 1000 or 5000. We observed that the methods that combine multiple rare variants within a gene into a meta-variant generally had greater power to map rare variants compared to LMM. Therefore, it is recommended to use rare variant association mapping methods to map rare genetic variants that affect quantitative traits in livestock, such as bovine populations.

Mapping complex traits as a dynamic system

PubMed Central

Sun, Lidan; Wu, Rongling

2017-01-01

Despite increasing emphasis on the genetic study of quantitative traits, we are still far from being able to chart a clear picture of their genetic architecture, given an inherent complexity involved in trait formation. A competing theory for studying such complex traits has emerged by viewing their phenotypic formation as a “system” in which a high-dimensional group of interconnected components act and interact across different levels of biological organization from molecules through cells to whole organisms. This system is initiated by a machinery of DNA sequences that regulate a cascade of biochemical pathways to synthesize endophenotypes and further assemble these endophenotypes toward the end-point phenotype in virtue of various developmental changes. This review focuses on a conceptual framework for genetic mapping of complex traits by which to delineate the underlying components, interactions and mechanisms that govern the system according to biological principles and understand how these components function synergistically under the control of quantitative trait loci (QTLs) to comprise a unified whole. This framework is built by a system of differential equations that quantifies how alterations of different components lead to the global change of trait development and function, and provides a quantitative and testable platform for assessing the multiscale interplay between QTLs and development. The method will enable geneticists to shed light on the genetic complexity of any biological system and predict, alter or engineer its physiological and pathological states. PMID:25772476

Relating belowground microbial composition to the taxonomic, phylogenetic, and functional trait distributions of trees in a tropical forest.

PubMed

Barberán, Albert; McGuire, Krista L; Wolf, Jeffrey A; Jones, F Andrew; Wright, Stuart Joseph; Turner, Benjamin L; Essene, Adam; Hubbell, Stephen P; Faircloth, Brant C; Fierer, Noah

2015-12-01

The complexities of the relationships between plant and soil microbial communities remain unresolved. We determined the associations between plant aboveground and belowground (root) distributions and the communities of soil fungi and bacteria found across a diverse tropical forest plot. Soil microbial community composition was correlated with the taxonomic and phylogenetic structure of the aboveground plant assemblages even after controlling for differences in soil characteristics, but these relationships were stronger for fungi than for bacteria. In contrast to expectations, the species composition of roots in our soil core samples was a poor predictor of microbial community composition perhaps due to the patchy, ephemeral, and highly overlapping nature of fine root distributions. Our ability to predict soil microbial composition was not improved by incorporating information on plant functional traits suggesting that the most commonly measured plant traits are not particularly useful for predicting the plot-level variability in belowground microbial communities. © 2015 John Wiley & Sons Ltd/CNRS.

Trait complexes and academic achievement: old and new ways of examining personality in educational contexts.

PubMed

Ackerman, Phillip L; Chamorro-Premuzic, Tomas; Furnham, Adrian

2011-03-01

BACKGROUND. Although recent research has provided evidence for the predictive validity of personality traits in academic settings, the path to an improved understanding of the nature of personality influences on academic achievement involves a reconceptualization of both criterion and predictor construct spaces. AIMS. For the criterion space, one needs to consider student behaviours beyond grades and level of educational attainment, and include what the student does among other things outside of the classroom. For the predictor space, it is possible to bring some order to the myriad personality constructs that have been developed over the last century, by focusing on common variance among personality and other non-ability traits. METHODS. We review these conceptual issues and several empirical studies. CONCLUSIONS. We demonstrate the possible increments in understanding non-ability determinants of academic achievement that may be obtained by focusing on areas where there is a theoretical convergence between predictor and criterion spaces. 2010 The British Psychological Society.

What can genes tell us about the relationship between education and health?

PubMed

Boardman, Jason D; Domingue, Benjamin W; Daw, Jonathan

2015-02-01

We use genome wide data from respondents of the Health and Retirement Study (HRS) to evaluate the possibility that common genetic influences are associated with education and three health outcomes: depression, self-rated health, and body mass index. We use a total of 1.7 million single nucleotide polymorphisms obtained from the Illumina HumanOmni2.5-4v1 chip from 4233 non-Hispanic white respondents to characterize genetic similarities among unrelated persons in the HRS. We then used the Genome Wide Complex Trait Analysis (GCTA) toolkit, to estimate univariate and bivariate heritability. We provide evidence that education (h(2) = 0.33), BMI (h(2) = 0.43), depression (h(2) = 0.19), and self-rated health (h(2) = 0.18) are all moderately heritable phenotypes. We also provide evidence that some of the correlation between depression and education as well as self-rated health and education is due to common genetic factors associated with one or both traits. We find no evidence that the correlation between education and BMI is influenced by common genetic factors. Copyright © 2014 Elsevier Ltd. All rights reserved.

QTL variations for growth-related traits in eight distinct families of common carp (Cyprinus carpio).

PubMed

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

2016-05-05

Comparing QTL analyses of multiple pair-mating families can provide a better understanding of important allelic variations and distributions. However, most QTL mapping studies in common carp have been based on analyses of individual families. In order to improve our understanding of heredity and variation of QTLs in different families and identify important QTLs, we performed QTL analysis of growth-related traits in multiple segregating families. We completed a genome scan for QTLs that affect body weight (BW), total length (TL), and body thickness (BT) of 522 individuals from eight full-sib families using 250 microsatellites evenly distributed across 50 chromosomes. Sib-pair and half-sib model mapping identified 165 QTLs on 30 linkage groups. Among them, 10 (genome-wide P <0.01 or P < 0.05) and 28 (chromosome-wide P < 0.01) QTLs exhibited significant evidence of linkage, while the remaining 127 exhibited a suggestive effect on the above three traits at a chromosome-wide (P < 0.05) level. Multiple QTLs obtained from different families affect BW, TL, and BT and locate at close or identical positions. It suggests that same genetic factors may control variability in these traits. Furthermore, the results of the comparative QTL analysis of multiple families showed that one QTL was common in four of the eight families, nine QTLs were detected in three of the eight families, and 26 QTLs were found common to two of the eight families. These common QTLs are valuable candidates in marker-assisted selection. A large number of QTLs were detected in the common carp genome and associated with growth-related traits. Some of the QTLs of different growth-related traits were identified at similar chromosomal regions, suggesting a role for pleiotropy and/or tight linkage and demonstrating a common genetic basis of growth trait variations. The results have set up an example for comparing QTLs in common carp and provided insights into variations in the identified QTLs affecting body growth. Discovery of these common QTLs between families and growth-related traits represents an important step towards understanding of quantitative genetic variation in common carp.

The epigenomic interface between genome and environment in common complex diseases.

PubMed

Bell, Christopher G; Beck, Stephan

2010-12-01

The epigenome plays the pivotal role as interface between genome and environment. True genome-wide assessments of epigenetic marks, such as DNA methylation (methylomes) or chromatin modifications (chromatinomes), are now possible, either through high-throughput arrays or increasingly by second-generation DNA sequencing methods. The ability to collect these data at this level of resolution enables us to begin to be able to propose detailed questions, and interrogate this information, with regards to changes that occur due to development, lineage and tissue-specificity, and significantly those caused by environmental influence, such as ageing, stress, diet, hormones or toxins. Common complex traits are under variable levels of genetic influence and additionally epigenetic effect. The detection of pathological epigenetic alterations will reveal additional insights into their aetiology and how possible environmental modulation of this mechanism may occur. Due to the reversibility of these marks, the potential for sequence-specific targeted therapeutics exists. This review surveys recent epigenomic advances and their current and prospective application to the study of common diseases.

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.

The genetic variance but not the genetic covariance of life-history traits changes towards the north in a time-constrained insect.

PubMed

Sniegula, Szymon; Golab, Maria J; Drobniak, Szymon M; Johansson, Frank

2018-06-01

Seasonal time constraints are usually stronger at higher than lower latitudes and can exert strong selection on life-history traits and the correlations among these traits. To predict the response of life-history traits to environmental change along a latitudinal gradient, information must be obtained about genetic variance in traits and also genetic correlation between traits, that is the genetic variance-covariance matrix, G. Here, we estimated G for key life-history traits in an obligate univoltine damselfly that faces seasonal time constraints. We exposed populations to simulated native temperatures and photoperiods and common garden environmental conditions in a laboratory set-up. Despite differences in genetic variance in these traits between populations (lower variance at northern latitudes), there was no evidence for latitude-specific covariance of the life-history traits. At simulated native conditions, all populations showed strong genetic and phenotypic correlations between traits that shaped growth and development. The variance-covariance matrix changed considerably when populations were exposed to common garden conditions compared with the simulated natural conditions, showing the importance of environmentally induced changes in multivariate genetic structure. Our results highlight the importance of estimating variance-covariance matrixes in environments that mimic selection pressures and not only trait variances or mean trait values in common garden conditions for understanding the trait evolution across populations and environments. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

Genetics of Adiposity in Large Animal Models for Human Obesity-Studies on Pigs and Dogs.

PubMed

Stachowiak, M; Szczerbal, I; Switonski, M

2016-01-01

The role of domestic mammals in the development of human biomedical sciences has been widely documented. Among these model species the pig and dog are of special importance. Both are useful for studies on the etiology of human obesity. Genome sequences of both species are known and advanced genetic tools [eg, microarray SNP for genome wide association studies (GWAS), next generation sequencing (NGS), etc.] are commonly used in such studies. In the domestic pig the accumulation of adipose tissue is an important trait, which influences meat quality and fattening efficiency. Numerous quantitative trait loci (QTLs) for pig fatness traits were identified, while gene polymorphisms associated with these traits were also described. The situation is different in dog population. Generally, excessive accumulation of adipose tissue is considered, similar to humans, as a complex disease. However, research on the genetic background of canine obesity is still in its infancy. Between-breed differences in terms of adipose tissue accumulation are well known in both animal species. In this review we show recent advances of studies on adipose tissue accumulation in pigs and dogs, and their potential importance for studies on human obesity. Copyright © 2016 Elsevier Inc. All rights reserved.

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

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.

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

PubMed

McCarthy, Mark I

2009-07-03

Identification of common-variant associations for many common disorders has been highly effective, but the loci detected so far typically explain only a small proportion of the genetic predisposition to disease. Extending explained genetic variance is one of the major near-term goals of human genetic research. Next-generation sequencing technologies offer great promise, but optimal strategies for their deployment remain uncertain, not least because we lack a clear view of the characteristics of the variants being sought. Here, I discuss what can and cannot be inferred about complex trait disease architecture from the information currently available and review the implications for future research strategies.

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

DOE PAGES

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

2016-11-28

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

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

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

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

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

Relevance of genetic relationship in GWAS and genomic prediction.

PubMed

Pereira, Helcio Duarte; Soriano Viana, José Marcelo; Andrade, Andréa Carla Bastos; Fonseca E Silva, Fabyano; Paes, Geísa Pinheiro

2018-02-01

The objective of this study was to analyze the relevance of relationship information on the identification of low heritability quantitative trait loci (QTLs) from a genome-wide association study (GWAS) and on the genomic prediction of complex traits in human, animal and cross-pollinating populations. The simulation-based data sets included 50 samples of 1000 individuals of seven populations derived from a common population with linkage disequilibrium. The populations had non-inbred and inbred progeny structure (50 to 200) with varying number of members (5 to 20). The individuals were genotyped for 10,000 single nucleotide polymorphisms (SNPs) and phenotyped for a quantitative trait controlled by 10 QTLs and 90 minor genes showing dominance. The SNP density was 0.1 cM and the narrow sense heritability was 25%. The QTL heritabilities ranged from 1.1 to 2.9%. We applied mixed model approaches for both GWAS and genomic prediction using pedigree-based and genomic relationship matrices. For GWAS, the observed false discovery rate was kept below the significance level of 5%, the power of detection for the low heritability QTLs ranged from 14 to 50%, and the average bias between significant SNPs and a QTL ranged from less than 0.01 to 0.23 cM. The QTL detection power was consistently higher using genomic relationship matrix. Regardless of population and training set size, genomic prediction provided higher prediction accuracy of complex trait when compared to pedigree-based prediction. The accuracy of genomic prediction when there is relatedness between individuals in the training set and the reference population is much higher than the value for unrelated individuals.

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.

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.

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

Trait space of rare plants in a fire-dependent ecosystem.

PubMed

Ames, Gregory M; Wall, Wade A; Hohmann, Matthew G; Wright, Justin P

2017-08-01

The causes of species rarity are of critical concern because of the high extinction risk associated with rarity. Studies examining individual rare species have limited generality, whereas trait-based approaches offer a means to identify functional causes of rarity that can be applied to communities with disparate species pools. Differences in functional traits between rare and common species may be indicative of the functional causes of species rarity and may therefore be useful in crafting species conservation strategies. However, there is a conspicuous lack of studies comparing the functional traits of rare species and co-occurring common species. We measured 18 important functional traits for 19 rare and 134 common understory plant species from North Carolina's Sandhills region and compared their trait distributions to determine whether there are significant functional differences that may explain species rarity. Flowering, fire, and tissue-chemistry traits differed significantly between rare and common, co-occurring species. Differences in specific traits suggest that fire suppression has driven rarity in this system and that changes to the timing and severity of prescribed fire may improve conservation success. Our method provides a useful tool to prioritize conservation efforts in other systems based on the likelihood that rare species are functionally capable of persisting. © 2016 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

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

PubMed Central

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

2016-01-01

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

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.

Unique aspects of impulsive traits in substance use and overeating: specific contributions of common assessments of impulsivity.

PubMed

Beaton, Derek; Abdi, Hervé; Filbey, Francesca M

2014-11-01

Abstract Background: Impulsivity is a complex trait often studied in substance abuse and overeating disorders, but the exact nature of impulsivity traits and their contribution to these disorders are still debated. Thus, understanding how to measure impulsivity is essential for comprehending addictive behaviors. Identify unique impulsivity traits specific to substance use and overeating. Impulsive Sensation Seeking (ImpSS) and Barratt's Impulsivity scales (BIS) Scales were analyzed with a non-parametric factor analytic technique (discriminant correspondence analysis) to identify group-specific traits on 297 individuals from five groups: Marijuana (n = 88), Nicotine (n = 82), Overeaters (n = 27), Marijuauna + Nicotine (n = 63), and CONTROLs (n = 37). A significant overall factor structure revealed three components of impulsivity that explained respectively 50.19% (pperm < 0.0005), 24.18% (pperm < 0.0005), and 15.98% (pperm < 0.0005) of the variance. All groups were significantly different from one another. When analyzed together, the BIS and ImpSS produce a multi-factorial structure that identified the impulsivity traits specific to these groups. The group specific traits are (1) CONTROL: low impulse, avoids thrill-seeking behaviors; (2) Marijuana: seeks mild sensation, is focused and attentive; (3) Marijuana + Nicotine: pursues thrill-seeking, lacks focus and attention; (4) Nicotine: lacks focus and planning; (5) Overeating: lacks focus, but plans (short and long term). Our results reveal impulsivity traits specific to each group. This may provide better criteria to define spectrums and trajectories - instead of categories - of symptoms for substance use and eating disorders. Defining symptomatic spectrums could be an important step forward in diagnostic strategies.

Unique aspects of impulsive traits in substance use and overeating: specific contributions of common assessments of impulsivity

PubMed Central

Beaton, Derek; Abdi, Hervé; Filbey, Francesca M.

2015-01-01

Background Impulsivity is a complex trait often studied in substance abuse and overeating disorders, but the exact nature of impulsivity traits and their contribution to these disorders are still debated. Thus, understanding how to measure impulsivity is essential for comprehending addictive behaviors. Objectives Identify unique impulsivity traits specific to substance use and overeating. Methods Impulsive Sensation Seeking (ImpSS) and Barratt’s Impulsivity scales (BIS) Scales were analyzed with a non-parametric factor analytic technique (discriminant correspondence analysis) to identify group-specific traits on 297 individuals from five groups: Marijuana (n = 88), Nicotine (n = 82), Overeaters (n = 27), Marijuauna + Nicotine (n = 63), and Controls (n = 37). Results A significant overall factor structure revealed three components of impulsivity that explained respectively 50.19% (pperm<0.0005), 24.18% (pperm<0.0005), and 15.98% (pperm<0.0005) of the variance. All groups were significantly different from one another. When analyzed together, the BIS and ImpSS produce a multi-factorial structure that identified the impulsivity traits specific to these groups. The group specific traits are (1) Control: low impulse, avoids thrill-seeking behaviors; (2) Marijuana: seeks mild sensation, is focused and attentive; (3) Marijuana + Nicotine: pursues thrill-seeking, lacks focus and attention; (4) Nicotine: lacks focus and planning; (5) Overeating: lacks focus, but plans (short and long term). Conclusions Our results reveal impulsivity traits specific to each group. This may provide better criteria to define spectrums and trajectories – instead of categories – of symptoms for substance use and eating disorders. Defining symptomatic spectrums could be an important step forward in diagnostic strategies. PMID:25115831

A change in climate causes rapid evolution of multiple life-history traits and their interactions in an annual plant.

PubMed

Franks, S J; Weis, A E

2008-09-01

Climate change is likely to spur rapid evolution, potentially altering integrated suites of life-history traits. We examined evolutionary change in multiple life-history traits of the annual plant Brassica rapa collected before and after a recent 5-year drought in southern California. We used a direct approach to examining evolutionary change by comparing ancestors and descendants. Collections were made from two populations varying in average soil moisture levels, and lines propagated from the collected seeds were grown in a greenhouse and experimentally subjected to conditions simulating either drought (short growing season) or high precipitation (long growing season) years. Comparing ancestors and descendants, we found that the drought caused many changes in life-history traits, including a shift to earlier flowering, longer duration of flowering, reduced peak flowering and greater skew of the flowering schedule. Descendants had thinner stems and fewer leaf nodes at the time of flowering than ancestors, indicating that the drought selected for plants that flowered at a smaller size and earlier ontogenetic stage rather than selecting for plants to develop more rapidly. Thus, there was not evidence for absolute developmental constraints to flowering time evolution. Common principal component analyses showed substantial differences in the matrix of trait covariances both between short and long growing season treatments and between populations. Although the covariances matrices were generally similar between ancestors and descendants, there was evidence for complex evolutionary changes in the relationships among the traits, and these changes depended on the population and treatment. These results show that a full appreciation of the impacts of global change on phenotypic evolution will entail an understanding of how changes in climatic conditions affect trait values and the structure of relationships among traits.

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.

A High-Density Genetic Map with Array-Based Markers Facilitates Structural and Quantitative Trait Locus Analyses of the Common Wheat Genome

PubMed Central

Iehisa, Julio Cesar Masaru; Ohno, Ryoko; Kimura, Tatsuro; Enoki, Hiroyuki; Nishimura, Satoru; Okamoto, Yuki; Nasuda, Shuhei; Takumi, Shigeo

2014-01-01

The large genome and allohexaploidy of common wheat have complicated construction of a high-density genetic map. Although improvements in the throughput of next-generation sequencing (NGS) technologies have made it possible to obtain a large amount of genotyping data for an entire mapping population by direct sequencing, including hexaploid wheat, a significant number of missing data points are often apparent due to the low coverage of sequencing. In the present study, a microarray-based polymorphism detection system was developed using NGS data obtained from complexity-reduced genomic DNA of two common wheat cultivars, Chinese Spring (CS) and Mironovskaya 808. After design and selection of polymorphic probes, 13,056 new markers were added to the linkage map of a recombinant inbred mapping population between CS and Mironovskaya 808. On average, 2.49 missing data points per marker were observed in the 201 recombinant inbred lines, with a maximum of 42. Around 40% of the new markers were derived from genic regions and 11% from repetitive regions. The low number of retroelements indicated that the new polymorphic markers were mainly derived from the less repetitive region of the wheat genome. Around 25% of the mapped sequences were useful for alignment with the physical map of barley. Quantitative trait locus (QTL) analyses of 14 agronomically important traits related to flowering, spikes, and seeds demonstrated that the new high-density map showed improved QTL detection, resolution, and accuracy over the original simple sequence repeat map. PMID:24972598

A high-density genetic map with array-based markers facilitates structural and quantitative trait locus analyses of the common wheat genome.

PubMed

Iehisa, Julio Cesar Masaru; Ohno, Ryoko; Kimura, Tatsuro; Enoki, Hiroyuki; Nishimura, Satoru; Okamoto, Yuki; Nasuda, Shuhei; Takumi, Shigeo

2014-10-01

The large genome and allohexaploidy of common wheat have complicated construction of a high-density genetic map. Although improvements in the throughput of next-generation sequencing (NGS) technologies have made it possible to obtain a large amount of genotyping data for an entire mapping population by direct sequencing, including hexaploid wheat, a significant number of missing data points are often apparent due to the low coverage of sequencing. In the present study, a microarray-based polymorphism detection system was developed using NGS data obtained from complexity-reduced genomic DNA of two common wheat cultivars, Chinese Spring (CS) and Mironovskaya 808. After design and selection of polymorphic probes, 13,056 new markers were added to the linkage map of a recombinant inbred mapping population between CS and Mironovskaya 808. On average, 2.49 missing data points per marker were observed in the 201 recombinant inbred lines, with a maximum of 42. Around 40% of the new markers were derived from genic regions and 11% from repetitive regions. The low number of retroelements indicated that the new polymorphic markers were mainly derived from the less repetitive region of the wheat genome. Around 25% of the mapped sequences were useful for alignment with the physical map of barley. Quantitative trait locus (QTL) analyses of 14 agronomically important traits related to flowering, spikes, and seeds demonstrated that the new high-density map showed improved QTL detection, resolution, and accuracy over the original simple sequence repeat map. © The Author 2014. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

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.

Phenotypic integration and the evolution of signal repertoires: A case study of treefrog acoustic communication.

PubMed

Reichert, Michael S; Höbel, Gerlinde

2018-03-01

Animal signals are inherently complex phenotypes with many interacting parts combining to elicit responses from receivers. The pattern of interrelationships between signal components reflects the extent to which each component is expressed, and responds to selection, either in concert with or independently of others. Furthermore, many species have complex repertoires consisting of multiple signal types used in different contexts, and common morphological and physiological constraints may result in interrelationships extending across the multiple signals in species' repertoires. The evolutionary significance of interrelationships between signal traits can be explored within the framework of phenotypic integration, which offers a suite of quantitative techniques to characterize complex phenotypes. In particular, these techniques allow for the assessment of modularity and integration, which describe, respectively, the extent to which sets of traits covary either independently or jointly. Although signal and repertoire complexity are thought to be major drivers of diversification and social evolution, few studies have explicitly measured the phenotypic integration of signals to investigate the evolution of diverse communication systems. We applied methods from phenotypic integration studies to quantify integration in the two primary vocalization types (advertisement and aggressive calls) in the treefrogs Hyla versicolor , Hyla cinerea, and Dendropsophus ebraccatus . We recorded male calls and calculated standardized phenotypic variance-covariance ( P ) matrices for characteristics within and across call types. We found significant integration across call types, but the strength of integration varied by species and corresponded with the acoustic similarity of the call types within each species. H. versicolor had the most modular advertisement and aggressive calls and the least acoustically similar call types. Additionally, P was robust to changing social competition levels in H. versicolor . Our findings suggest new directions in animal communication research in which the complex relationships among the traits of multiple signals are a key consideration for understanding signal evolution.

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

PubMed Central

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

2016-01-01

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

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.

HaploReg v4: systematic mining of putative causal variants, cell types, regulators and target genes for human complex traits and disease.

PubMed

Ward, Lucas D; Kellis, Manolis

2016-01-04

More than 90% of common variants associated with complex traits do not affect proteins directly, but instead the circuits that control gene expression. This has increased the urgency of understanding the regulatory genome as a key component for translating genetic results into mechanistic insights and ultimately therapeutics. To address this challenge, we developed HaploReg (http://compbio.mit.edu/HaploReg) to aid the functional dissection of genome-wide association study (GWAS) results, the prediction of putative causal variants in haplotype blocks, the prediction of likely cell types of action, and the prediction of candidate target genes by systematic mining of comparative, epigenomic and regulatory annotations. Since first launching the website in 2011, we have greatly expanded HaploReg, increasing the number of chromatin state maps to 127 reference epigenomes from ENCODE 2012 and Roadmap Epigenomics, incorporating regulator binding data, expanding regulatory motif disruption annotations, and integrating expression quantitative trait locus (eQTL) variants and their tissue-specific target genes from GTEx, Geuvadis, and other recent studies. We present these updates as HaploReg v4, and illustrate a use case of HaploReg for attention deficit hyperactivity disorder (ADHD)-associated SNPs with putative brain regulatory mechanisms. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

PubMed Central

Robinson, Elise B.; Kirby, Andrew; Ruparel, Kosha; Yang, Jian; McGrath, Lauren; Anttila, Verneri; Neale, Benjamin M.; Merikangas, Kathleen; Lehner, Thomas; Sleiman, Patrick M.A.; Daly, Mark J.; Gur, Ruben; Gur, Raquel; Hakonarson, Hakon

2014-01-01

The objective of this analysis was to examine the genetic architecture of diverse cognitive abilities in children and adolescents, including the magnitude of common genetic effects and patterns of shared and unique genetic influences. Subjects included 3,689 members of the Philadelphia Neurodevelopmental Cohort, a general population sample of ages 8-21 years who completed an extensive battery of cognitive tests. We used genome-wide complex trait analysis (GCTA) to estimate the SNP-based heritability of each domain, as well as the genetic correlation between all domains that showed significant genetic influence. Several of the individual domains suggested strong influence of common genetic variants (e.g. reading ability, h2g=0.43, p=4e-06; emotion identification, h2g=0.36, p=1e-05; verbal memory, h2g=0.24, p=0.005). The genetic correlations highlighted trait domains that are candidates for joint interrogation in future genetic studies (e.g. language reasoning and spatial reasoning, r(g)=0.72, p=0.007). These results can be used to structure future genetic and neuropsychiatric investigations of diverse cognitive abilities. PMID:25023143

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.

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

PubMed Central

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

2006-01-01

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

Multimodal signalling in estrildid finches: song, dance and colour are associated with different ecological and life-history traits.

PubMed

Gomes, A C R; Funghi, C; Soma, M; Sorenson, M D; Cardoso, G C

2017-07-01

Sexual traits (e.g. visual ornaments, acoustic signals, courtship behaviour) are often displayed together as multimodal signals. Some hypotheses predict joint evolution of different sexual signals (e.g. to increase the efficiency of communication) or that different signals trade off with each other (e.g. due to limited resources). Alternatively, multiple signals may evolve independently for different functions, or to communicate different information (multiple message hypothesis). We evaluated these hypotheses with a comparative study in the family Estrildidae, one of the largest songbird radiations, and one that includes many model species for research in sexual selection and communication. We found little evidence for either joint evolution or trade-offs between song and colour ornamentation. Some negative correlations between dance repertoire and song traits may suggest a functional compromise, but generally courtship dance also evolved independently from other signals. Instead of correlated evolution, we found that song, dance and colour are each related to different socio-ecological traits. Song complexity evolved together with ecological generalism, song performance with investment in reproduction, dance with commonness and habitat type, whereas colour ornamentation was shown previously to correlate mostly with gregariousness. We conclude that multimodal signals evolve in response to various socio-ecological traits, suggesting the accumulation of distinct signalling functions. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

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.

When Homoplasy Is Not Homoplasy: Dissecting Trait Evolution by Contrasting Composite and Reductive Coding.

PubMed

Torres-Montúfar, Alejandro; Borsch, Thomas; Ochoterena, Helga

2018-05-01

The conceptualization and coding of characters is a difficult issue in phylogenetic systematics, no matter which inference method is used when reconstructing phylogenetic trees or if the characters are just mapped onto a specific tree. Complex characters are groups of features that can be divided into simpler hierarchical characters (reductive coding), although the implied hierarchical relational information may change depending on the type of coding (composite vs. reductive). Up to now, there is no common agreement to either code characters as complex or simple. Phylogeneticists have discussed which coding method is best but have not incorporated the heuristic process of reciprocal illumination to evaluate the coding. Composite coding allows to test whether 1) several characters were linked resulting in a structure described as a complex character or trait or 2) independently evolving characters resulted in the configuration incorrectly interpreted as a complex character. We propose that complex characters or character states should be decomposed iteratively into simpler characters when the original homology hypothesis is not corroborated by a phylogenetic analysis, and the character or character state is retrieved as homoplastic. We tested this approach using the case of fruit types within subfamily Cinchonoideae (Rubiaceae). The iterative reductive coding of characters associated with drupes allowed us to unthread fruit evolution within Cinchonoideae. Our results show that drupes and berries are not homologous. As a consequence, a more precise ontology for the Cinchonoideae drupes is required.

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

Personality disorder traits, family environment, and alcohol misuse: a multivariate behavioural genetic analysis.

PubMed

Jang, K L; Vernon, P A; Livesley, W J

2000-06-01

This study seeks to estimate the extent to which a common genetic and environmental basis is shared between (i) traits delineating specific aspects of antisocial personality and alcohol misuse, and (ii) childhood family environments, traits delineating broad domains of personality pathology and alcohol misuse. Postal survey data were collected from monozygotic and dizygotic twin pairs. Twin pairs were recruited from Vancouver, British Columbia and London, Ontario, Canada using newspaper advertisements, media stories and twin clubs. Data obtained from 324 monozygotic and 335 dizygotic twin pairs were used to estimate the extent to which traits delineating specific antisocial personality traits and alcohol misuse shared a common genetic and environmental aetiology. Data from 81 monozygotic and 74 dizygotic twin pairs were used to estimate the degree to which traits delineating personality pathology, childhood family environment and alcohol misuse shared a common aetiology. Current alcohol misuse and personality pathology were measured using scales contained in the self-report Dimensional Assessment of Personality Pathology. Perceptions of childhood family environment were measured using the self-report Family Environment Scale. Multivariate genetic analyses showed that a subset of traits delineating components of antisocial personality (i.e. grandiosity, attention-seeking, failure to adopt social norms, interpersonal violence and juvenile antisocial behaviours) are influenced by genetic factors in common to alcohol misuse. Genetically based perceptions of childhood family environment had little relationship with alcohol misuse. Heritable personality factors that influence the perception of childhood family environment play only a small role in the liability to alcohol misuse. Instead, liability to alcohol misuse is related to genetic factors common a specific subset of antisocial personality traits describing conduct problems, narcissistic and stimulus-seeking behaviour.

Genome-wide epigenetic perturbation jump-starts patterns of heritable variation found in nature.

PubMed

Roux, Fabrice; Colomé-Tatché, Maria; Edelist, Cécile; Wardenaar, René; Guerche, Philippe; Hospital, Frédéric; Colot, Vincent; Jansen, Ritsert C; Johannes, Frank

2011-08-01

We extensively phenotyped 6000 Arabidopsis plants with experimentally perturbed DNA methylomes as well as a diverse panel of natural accessions in a common garden. We found that alterations in DNA methylation not only caused heritable phenotypic diversity but also produced heritability patterns closely resembling those of the natural accessions. Our findings indicate that epigenetically induced and naturally occurring variation in complex traits share part of their polygenic architecture and may offer complementary adaptation routes in ecological settings.

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.

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

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.

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.

Cat-Map: putting cataract on the map

PubMed Central

Bennett, Thomas M.; Hejtmancik, J. Fielding

2010-01-01

Lens opacities, or cataract(s), may be inherited as a classic Mendelian disorder usually with early-onset or, more commonly, acquired with age as a multi-factorial or complex trait. Many genetic forms of cataract have been described in mice and other animal models. Considerable progress has been made in mapping and identifying the genes and mutations responsible for inherited forms of cataract, and genetic determinants of age-related cataract are beginning to be discovered. To provide a convenient and accurate summary of current information focused on the increasing genetic complexity of Mendelian and age-related cataract we have created an online chromosome map and reference database for cataract in humans and mice (Cat-Map). PMID:21042563

A new way to protect privacy in large-scale genome-wide association studies.

PubMed

Kamm, Liina; Bogdanov, Dan; Laur, Sven; Vilo, Jaak

2013-04-01

Increased availability of various genotyping techniques has initiated a race for finding genetic markers that can be used in diagnostics and personalized medicine. Although many genetic risk factors are known, key causes of common diseases with complex heritage patterns are still unknown. Identification of such complex traits requires a targeted study over a large collection of data. Ideally, such studies bring together data from many biobanks. However, data aggregation on such a large scale raises many privacy issues. We show how to conduct such studies without violating privacy of individual donors and without leaking the data to third parties. The presented solution has provable security guarantees. Supplementary data are available at Bioinformatics online.

Power and Autistic Traits

PubMed Central

Overskeid, Geir

2016-01-01

Autistic traits can help people gain and sustain power, and has probably done so throughout history, says the present paper. A number of testable claims follow from this assumption. First, the powerful should have more autistic traits than others – which they do appear to have. Among other things, powerful people, and those with many autistic traits, tend to prefer solitary activities and are often aloof. Moreover, they are often rigid and socially insensitive, low on empathy and with low scores on the trait of agreeableness – and as a rule they do not have many friends. Both groups are also more self-centered than others, more honest, less submissive, more sensitive to slights, and with a stronger tendency to engage in abstract thinking. They tend to behave in bossy or dominant ways, and their moral judgment is more based on rules than on feelings. In addition to experimental evidence, I cite biographies showing that a surprising number of presidents, prime ministers and other powerful people seem to have had traits like those in question – and interestingly, in animals, leaders are often rigid and insensitive to group members’ needs and feelings, mostly acting the way they are themselves inclined to, not responding much to others. Problem solving is important in leadership, and people with many autistic traits appear often to be better thinkers than typical subjects with similar IQs. However, these and other congruities could be coincidences. Hence the question of whether traits the two groups have in common also have a common cause constitutes a strong test of the paper’s thesis – and a common cause does appear to exist, in the form of testosterone’s effects on the central nervous system. Finally, there is evidence that, other things equal, powerful men have more reproductive success than others. If men wielding power do indeed have more autistic traits than those less powerful, this will lead to, other things equal, such traits becoming more common – which can help explain the prevalence of autistic traits. PMID:27630593

Selection for sow longevity.

PubMed

Serenius, T; Stalder, K J

2006-04-01

Sow longevity plays an important role in economically efficient piglet production because sow longevity is related to the number of piglets produced during its productive lifetime; however, selection for sow longevity is not commonly practiced in any pig breeding program. There is relatively little scientific literature concerning the genetic parameters (genetic variation and genetic correlations) or methods available for breeding value estimation for effective selection for sow longevity. This paper summarizes the current knowledge about the genetics of sow longevity and discusses the available breeding value estimation methods for sow longevity traits. The studies in the literature clearly indicate that sow longevity is a complex trait, and even the definition of sow longevity is variable depending on the researcher and research objective. In general, the measures and analyses of sow longevity can be divided into 1) continuous traits (e.g., productive lifetime) analyzed with proportional hazard models; and 2) more simple binary traits such as stayability until some predetermined fixed parity. Most studies have concluded that sufficient genetic variation exists for effective selection on sow longevity, and heritability estimates have ranged between 0.02 and 0.25. Moreover, sow longevity has shown to be genetically associated with prolificacy and leg conformation traits. Variable results from previous research have led to a lack of consensus among swine breeders concerning the valid methodology of estimating breeding values for longevity traits. One can not deny the superiority of survival analysis in the modeling approach of longevity data; however, multiple-trait analyses are not possible using currently available survival analysis software. Less sophisticated approaches have the advantage of evaluating multiple traits simultaneously, and thus, can use the genetic associations between sow longevity and other traits. Additional research is needed to identify the most efficient selection methods for sow longevity. Future research needs to concentrate on multiple trait analysis of sow longevity traits. Moreover, because longevity is a fitness trait, the nonadditive genetic effects (e.g., dominance) may play important role in the inheritance of sow longevity. Currently, not a single estimate for dominance variance of sow longevity could be identified from the scientific literature.

Adaptive introgression of abiotic tolerance traits in the sunflower Helianthus annuus.

PubMed

Whitney, Kenneth D; Randell, Rebecca A; Rieseberg, Loren H

2010-07-01

*Adaptive trait introgression is increasingly recognized as common. However, it is unclear whether adaptive genetic exchanges typically affect only a single trait, or instead affect multiple aspects of the phenotype. Here, we examine introgression of abiotic tolerance traits between two hybridizing North American sunflower species, Helianthus annuus and Helianthus debilis. *In two common gardens in the hybrid range, we measured 10 ecophysiological, phenological, and architectural traits for parents and their natural and artificial hybrids, and examined how fitness covaried with trait values. *Eight of the 10 traits showed patterns consistent with introgression from H. debilis into H. annuus, and suggested that H. debilis-like traits allowing rapid growth and reproduction before summer heat and drought have been favored in the hybrid range. Natural selection currently favors BC(1) hybrids with H. debilis-like branching traits. *We demonstrate that introgression has altered multiple aspects of the H. annuus phenotype in an adaptive manner, has affected traits relevant to both biotic and abiotic environments, and may have aided expansion of the H. annuus range into central Texas, USA.

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

PubMed Central

Zas, R; Sampedro, L

2015-01-01

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

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.

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.

Variation in a Host-Parasitoid Interaction across Independent Populations.

PubMed

van Nouhuys, Saskya; Niemikapee, Suvi; Hanski, Ilkka

2012-12-05

Antagonistic relationships between parasitoids and their insect hosts involve multiple traits and are shaped by their ecological and evolutionary context. The parasitoid wasp Cotesia melitaearum and its host butterfly Melitaea cinxia occur in several locations around the Baltic sea, with differences in landscape structure, population sizes and the histories of the populations. We compared the virulence of the parasitoid and the susceptibility of the host from five populations in a reciprocal transplant-style experiment using the progeny of five independent host and parasitoid individuals from each population. The host populations showed significant differences in the rate of encapsulation and parasitoid development rate. The parasitoid populations differed in brood size, development rate, pupal size and adult longevity. Some trait differences depended on specific host-parasitoid combinations, but neither species performed systematically better or worse in experiments involving local versus non-local populations of the other species. Furthermore, individuals from host populations with the most recent common ancestry did not perform alike, and there was no negative effect due to a history of inbreeding in the parasitoid. The complex pattern of variation in the traits related to the vulnerability of the host and the ability of the parasitoid to exploit the host may reflect multiple functions of the traits that would hinder simple local adaptation.

Competition drives trait evolution and character displacement between Mimulus species along an environmental gradient.

PubMed

Kooyers, Nicholas J; James, Brooke; Blackman, Benjamin K

2017-05-01

Closely related species may evolve to coexist stably in sympatry through niche differentiation driven by in situ competition, a process termed character displacement. Alternatively, past evolution in allopatry may have already sufficiently reduced niche overlap to permit establishment in sympatry, a process called ecological sorting. The relative importance of each process to niche differentiation is contentious even though they are not mutually exclusive and are both mediated via multivariate trait evolution. We explore how competition has impacted niche differentiation in two monkeyflowers, Mimulus alsinoides and M. guttatus, which often co-occur. Through field observations, common gardens, and competition experiments, we demonstrate that M. alsinoides is restricted to marginal habitats in sympatry and that the impacts of character displacement on niche differentiation are complex. Competition with M. guttatus alters selection gradients and has favored taller M. alsinoides with earlier seasonal flowering at low elevation and floral shape divergence at high elevation. However, no trait exhibits the pattern typically associated with character displacement, higher divergence between species in sympatry than allopatry. Thus, although character displacement was unlikely the process driving initial divergence along niche axes necessary for coexistence, we conclude that competition in sympatry has likely driven trait evolution along additional niche axes. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

The genetic architecture of economic and political preferences

PubMed Central

Benjamin, Daniel J.; Cesarini, David; van der Loos, Matthijs J. H. M.; Dawes, Christopher T.; Koellinger, Philipp D.; Magnusson, Patrik K. E.; Chabris, Christopher F.; Conley, Dalton; Laibson, David; Johannesson, Magnus; Visscher, Peter M.

2012-01-01

Preferences are fundamental building blocks in all models of economic and political behavior. We study a new sample of comprehensively genotyped subjects with data on economic and political preferences and educational attainment. We use dense single nucleotide polymorphism (SNP) data to estimate the proportion of variation in these traits explained by common SNPs and to conduct genome-wide association study (GWAS) and prediction analyses. The pattern of results is consistent with findings for other complex traits. First, the estimated fraction of phenotypic variation that could, in principle, be explained by dense SNP arrays is around one-half of the narrow heritability estimated using twin and family samples. The molecular-genetic–based heritability estimates, therefore, partially corroborate evidence of significant heritability from behavior genetic studies. Second, our analyses suggest that these traits have a polygenic architecture, with the heritable variation explained by many genes with small effects. Our results suggest that most published genetic association studies with economic and political traits are dramatically underpowered, which implies a high false discovery rate. These results convey a cautionary message for whether, how, and how soon molecular genetic data can contribute to, and potentially transform, research in social science. We propose some constructive responses to the inferential challenges posed by the small explanatory power of individual SNPs. PMID:22566634

The genetic architecture of economic and political preferences.

PubMed

Benjamin, Daniel J; Cesarini, David; van der Loos, Matthijs J H M; Dawes, Christopher T; Koellinger, Philipp D; Magnusson, Patrik K E; Chabris, Christopher F; Conley, Dalton; Laibson, David; Johannesson, Magnus; Visscher, Peter M

2012-05-22

Preferences are fundamental building blocks in all models of economic and political behavior. We study a new sample of comprehensively genotyped subjects with data on economic and political preferences and educational attainment. We use dense single nucleotide polymorphism (SNP) data to estimate the proportion of variation in these traits explained by common SNPs and to conduct genome-wide association study (GWAS) and prediction analyses. The pattern of results is consistent with findings for other complex traits. First, the estimated fraction of phenotypic variation that could, in principle, be explained by dense SNP arrays is around one-half of the narrow heritability estimated using twin and family samples. The molecular-genetic-based heritability estimates, therefore, partially corroborate evidence of significant heritability from behavior genetic studies. Second, our analyses suggest that these traits have a polygenic architecture, with the heritable variation explained by many genes with small effects. Our results suggest that most published genetic association studies with economic and political traits are dramatically underpowered, which implies a high false discovery rate. These results convey a cautionary message for whether, how, and how soon molecular genetic data can contribute to, and potentially transform, research in social science. We propose some constructive responses to the inferential challenges posed by the small explanatory power of individual SNPs.

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

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

PubMed Central

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

2008-01-01

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

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.

Predator attack rate evolution in space: the role of ecology mediated by complex emergent spatial structure and self-shading.

PubMed

Messinger, Susanna M; Ostling, Annette

2013-11-01

Predation interactions are an important element of ecological communities. Population spatial structure has been shown to influence predator evolution, resulting in the evolution of a reduced predator attack rate; however, the evolutionary role of traits governing predator and prey ecology is unknown. The evolutionary effect of spatial structure on a predator's attack rate has primarily been explored assuming a fixed metapopulation spatial structure, and understood in terms of group selection. But endogenously generated, emergent spatial structure is common in nature. Furthermore, the evolutionary influence of ecological traits may be mediated through the spatial self-structuring process. Drawing from theory on pathogens, the evolutionary effect of emergent spatial structure can be understood in terms of self-shading, where a voracious predator limits its long-term invasion potential by reducing local prey availability. Here we formalize the effects of self-shading for predators using spatial moment equations. Then, through simulations, we show that in a spatial context self-shading leads to relationships between predator-prey ecology and the predator's attack rate that are not expected in a non-spatial context. Some relationships are analogous to relationships already shown for host-pathogen interactions, but others represent new trait dimensions. Finally, since understanding the effects of ecology using existing self-shading theory requires simplifications of the emergent spatial structure that do not apply well here, we also develop metrics describing the complex spatial structure of the predator and prey populations to help us explain the evolutionary effect of predator and prey ecology in the context of self-shading. The identification of these metrics may provide a step towards expansion of the predictive domain of self-shading theory to more complex spatial dynamics. Copyright © 2013 Elsevier Inc. All rights reserved.

Investigating genetic loci that encode plant-derived paleoclimate proxies

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Genome-wide copy number variation analysis identified deletions in SFMBT1 associated with fasting plasma glucose in a Han Chinese population.

PubMed

Chung, Ren-Hua; Chiu, Yen-Feng; Hung, Yi-Jen; Lee, Wen-Jane; Wu, Kwan-Dun; Chen, Hui-Ling; Lin, Ming-Wei; Chen, Yii-Der I; Quertermous, Thomas; Hsiung, Chao A

2017-08-08

Fasting glucose and fasting insulin are glycemic traits closely related to diabetes, and understanding the role of genetic factors in these traits can help reveal the etiology of type 2 diabetes. Although single nucleotide polymorphisms (SNPs) in several candidate genes have been found to be associated with fasting glucose and fasting insulin, copy number variations (CNVs), which have been reported to be associated with several complex traits, have not been reported for association with these two traits. We aimed to identify CNVs associated with fasting glucose and fasting insulin. We conducted a genome-wide CNV association analysis for fasting plasma glucose (FPG) and fasting plasma insulin (FPI) using a family-based genome-wide association study sample from a Han Chinese population in Taiwan. A family-based CNV association test was developed in this study to identify common CNVs (i.e., CNVs with frequencies ≥ 5%), and a generalized estimating equation approach was used to test the associations between the traits and counts of global rare CNVs (i.e., CNVs with frequencies <5%). We found a significant genome-wide association for common deletions with a frequency of 5.2% in the Scm-like with four mbt domains 1 (SFMBT1) gene with FPG (association p-value = 2×10 -4 and an adjusted p-value = 0.0478 for multiple testing). No significant association was observed between global rare CNVs and FPG or FPI. The deletions in 20 individuals with DNA samples available were successfully validated using PCR-based amplification. The association of the deletions in SFMBT1 with FPG was further evaluated using an independent population-based replication sample obtained from the Taiwan Biobank. An association p-value of 0.065, which was close to the significance level of 0.05, for FPG was obtained by testing 9 individuals with CNVs in the SFMBT1 gene region and 11,692 individuals with normal copies in the replication cohort. Previous studies have found that SNPs in SFMBT1 are associated with blood pressure and serum urate concentration, suggesting that SFMBT1 may have functional implications in some metabolic-related traits.

We can be heroes: MLA's leadership journey(s).

PubMed

Tooey, Mary Joan M J

2017-01-01

Are there key attributes of leaders? Extrovert versus introvert? Charismatic? Detail oriented? Visionary? How do past leaders of the Medical Library Association (MLA) stack up? What leadership skills will MLA's leaders need in a complex information future? Leadership attributes of MLA's past and current presidents were studied to determine the common characteristics shared among these leaders. An examination of the leadership literature identified critical leadership characteristics essential to successful future leaders. MLA's past, current, and future leadership development efforts were examined. Finally, all members were encouraged to consider leadership with a small "l" and become leaders based on their own strengths, interests, and environments. A text analysis was performed on past presidential profiles, the past twenty-five years of MLA presidents were surveyed, and conversations with MLA's current presidents were held to determine commonalities among leadership characteristics. These were compared and contrasted with characteristics in the current leadership literature regarding the qualities of future leaders. The text analysis of past presidential profiles was not particularly revelatory regarding leadership qualities of early MLA presidents although several generalized traits emerged including collaborative traits; management traits such as effectiveness and efficiency, innovation, and vision; personal traits such as humor and energy; and finally, a passion for the work were revealed. These aligned with traits identified in the survey of the past twenty-five years of MLA presidents and with the thoughts of the president-elect, president, and past president. Additional qualities identified were communication skills, political acumen, creativity, courage, and respect for the opinions and concerns of all members. MLA's current leadership programs were reviewed in the context of examining traits needed by leaders of the future. A lack of focus on the needs of middle managers and the development of individual leadership skills was identified. As an organization, MLA should focus on leadership development in contrast to management training to prepare members as leaders in careers and work that may be vastly different than current situations. Equipping members with the skills enabling them to lead and thrive in these diverse situations, whether as the heads of programs or middle managers, or exploring and empowering individual leadership development while maintaining a passion for the profession, will be essential.

Clinical and evoked pain, personality traits, and emotional states: can familial confounding explain the associations?

PubMed

Strachan, Eric; Poeschla, Brian; Dansie, Elizabeth; Succop, Annemarie; Chopko, Laura; Afari, Niloofar

2015-01-01

Pain is a complex phenomenon influenced by context and person-specific factors. Affective dimensions of pain involve both enduring personality traits and fleeting emotional states. We examined how personality traits and emotional states are linked with clinical and evoked pain in a twin sample. 99 female twin pairs were evaluated for clinical and evoked pain using the McGill Pain Questionnaire (MPQ) and dolorimetry, and completed the 120-item International Personality Item Pool (IPIP), the Positive and Negative Affect Scale (PANAS), and ratings of stress and mood. Using a co-twin control design we examined a) the relationship of personality traits and emotional states with clinical and evoked pain and b) whether genetics and common environment (i.e. familial factors) may account for the associations. Neuroticism was associated with the sensory component of the MPQ; this relationship was not confounded by familial factors. None of the emotional state measures was associated with the MPQ. PANAS negative affect was associated with lower evoked pressure pain threshold and tolerance; these associations were confounded by familial factors. There were no associations between IPIP traits and evoked pain. A relationship exists between neuroticism and clinical pain that is not confounded by familial factors. There is no similar relationship between negative emotional states and clinical pain. In contrast, the relationship between negative emotional states and evoked pain is strong while the relationship with enduring personality traits is weak. The relationship between negative emotional states and evoked pain appears to be non-causal and due to familial factors. Copyright © 2014 Elsevier Inc. All rights reserved.

Morphology, sociality, and ecology: can morphology predict pairing behavior in coral reef fishes?

NASA Astrophysics Data System (ADS)

Brandl, S. J.; Bellwood, D. R.

2013-09-01

Morphology can contain valuable information about the ecological performance of reef fishes, but it has rarely been used in combination with social traits. Social behavior is known to influence the ecological role of fishes; however, the ecological basis for pairing in reef fishes is not well understood. Field observations of 2,753 individuals, in 47 species in six families of biting reef fishes (Acanthuridae, Chaetodontidae, Kyphosidae, Labridae, Pomacanthidae, Siganidae), were used in combination with six morphological measurements, to examine the morphology of fishes in different social systems. A principal components analysis of morphological traits segregated species with high proportions of pairing individuals from non-pairing species along principal component 1, explaining 40.8 % of the variation. Pairing species were characterized by large eyes, concave foreheads, pointed snouts, deep bodies, and small maximum sizes. There was a significant positive relationship between these morphological traits (i.e., scores on PC1) and the prevalence of pairing within the Chaetodontidae ( r 2 = 0.59; P = 0.026), Siganidae ( r 2 = 0.72; P = 0.004), and Acanthuridae ( r 2 = 0.82; P < 0.001). This was consistent when traits were corrected for phylogenetic effects. No pattern was evident in the scarine Labridae ( r 2 = 0.15; P = 0.17). The morphological characteristics found among pairing species suggest that pairing species share common ecological traits, including foraging for small prey items in micro-topographically complex environments such as reef crevices. These ecological traits may have played a role in the evolution of pairing behavior and subsequently led to the development of reproductive patterns based on monogamy.

On the relationship between phylogenetic diversity and trait diversity.

PubMed

Tucker, Caroline M; Davies, T Jonathan; Cadotte, Marc W; Pearse, William D

2018-05-21

Niche differences are key to understanding the distribution and structure of biodiversity. To examine niche differences, we must first characterize how species occupy niche space, and two approaches are commonly used in the ecological literature. The first uses species traits to estimate multivariate trait space (so-called functional trait diversity, FD); the second quantifies the amount of time or evolutionary history captured by a group of species (phylogenetic diversity, PD). It is often-but controversially-assumed that these putative measures of niche space are at a minimum correlated and perhaps redundant, since more evolutionary time allows for greater accumulation of trait changes. This theoretical expectation remains surprisingly poorly evaluated, particularly in the context of multivariate measures of trait diversity. We evaluated the relationship between phylogenetic diversity and trait diversity using analytical and simulation-based methods across common models of trait evolution. We show that PD correlates with FD increasingly strongly as more traits are included in the FD measure. Our results indicate that phylogenetic diversity can be a useful surrogate for high-dimensional trait diversity, but we also show that the correlation weakens when the underlying process of trait evolution includes variation in rate and optima. © 2018 by the Ecological Society of America.

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.

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

Methods for meta-analysis of multiple traits using GWAS summary statistics.

PubMed

Ray, Debashree; Boehnke, Michael

2018-03-01

Genome-wide association studies (GWAS) for complex diseases have focused primarily on single-trait analyses for disease status and disease-related quantitative traits. For example, GWAS on risk factors for coronary artery disease analyze genetic associations of plasma lipids such as total cholesterol, LDL-cholesterol, HDL-cholesterol, and triglycerides (TGs) separately. However, traits are often correlated and a joint analysis may yield increased statistical power for association over multiple univariate analyses. Recently several multivariate methods have been proposed that require individual-level data. Here, we develop metaUSAT (where USAT is unified score-based association test), a novel unified association test of a single genetic variant with multiple traits that uses only summary statistics from existing GWAS. Although the existing methods either perform well when most correlated traits are affected by the genetic variant in the same direction or are powerful when only a few of the correlated traits are associated, metaUSAT is designed to be robust to the association structure of correlated traits. metaUSAT does not require individual-level data and can test genetic associations of categorical and/or continuous traits. One can also use metaUSAT to analyze a single trait over multiple studies, appropriately accounting for overlapping samples, if any. metaUSAT provides an approximate asymptotic P-value for association and is computationally efficient for implementation at a genome-wide level. Simulation experiments show that metaUSAT maintains proper type-I error at low error levels. It has similar and sometimes greater power to detect association across a wide array of scenarios compared to existing methods, which are usually powerful for some specific association scenarios only. When applied to plasma lipids summary data from the METSIM and the T2D-GENES studies, metaUSAT detected genome-wide significant loci beyond the ones identified by univariate analyses. Evidence from larger studies suggest that the variants additionally detected by our test are, indeed, associated with lipid levels in humans. In summary, metaUSAT can provide novel insights into the genetic architecture of a common disease or traits. © 2017 WILEY PERIODICALS, INC.

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.

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.

Limited genetic covariance between autistic traits and intelligence: findings from a longitudinal twin study.

PubMed

Hoekstra, Rosa A; Happé, Francesca; Baron-Cohen, Simon; Ronald, Angelica

2010-07-01

Intellectual disability is common in individuals with autism spectrum conditions. However, the strength of the association between both conditions and its relevance to finding the underlying (genetic) causes of autism is unclear. This study aimed to investigate the longitudinal association between autistic traits and intelligence in a general population twin sample and to examine the etiology of this association. Parental ratings of autistic traits and performance on intelligence tests were collected in a sample of 8,848 twin pairs when the children were 7/8, 9, and 12 years old. Phenotypic and longitudinal correlations in the sample as a whole were compared to the associations in the most extreme scoring 5% of the population. The genetic and environmental influences on the overlap between autistic traits and IQ and on the stability of this relationship over time were estimated using structural equation modeling. Autistic traits were modestly negatively correlated to intellectual ability, both in the extreme scoring groups and among the full-range scores. The correlation was stable over time and was mainly explained by autistic trait items assessing communication difficulties. Genetic model fitting showed that autistic traits and IQ were influenced by a common set of genes and a common set of environmental influences that continuously affect these traits throughout childhood. The genetic correlation between autistic traits and IQ was only modest. These findings suggest that individual differences in autistic traits are substantially genetically independent of intellectual functioning. The relevance of these findings to future studies is discussed. (c) 2010 Wiley-Liss, Inc.

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

Physiological breeding.

PubMed

Reynolds, Matthew; Langridge, Peter

2016-06-01

Physiological breeding crosses parents with different complex but complementary traits to achieve cumulative gene action for yield, while selecting progeny using remote sensing, possibly in combination with genomic selection. Physiological approaches have already demonstrated significant genetic gains in Australia and several developing countries of the International Wheat Improvement Network. The techniques involved (see Graphical Abstract) also provide platforms for research and refinement of breeding methodologies. Recent examples of these include screening genetic resources for novel expression of Calvin cycle enzymes, identification of common genetic bases for heat and drought adaptation, and genetic dissection of trade-offs among yield components. Such information, combined with results from physiological crosses designed to test novel trait combinations, lead to more precise breeding strategies, and feed models of genotype-by-environment interaction to help build new plant types and experimental environments for future climates. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

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

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

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...

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

Treesearch

Kathleen D. Jermstad; Daniel L. Bassoni; Keith S. Jech; Gary A. Ritchie; Nicholas C. Wheeler; David B. Neale

2003-01-01

Quantitative trait loci (QTL) were mapped in the woody perennial Douglas fir (Pseudotsuga menziesii var. menziesii [Mirb.] Franco) for complex traits controlling the timing of growth initiation and growth cessation. QTL were estimated under controlled environmental conditions to identify QTL interactions with photoperiod, moisture stress, winter chilling, and spring...

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.

Using genomics to characterize evolutionary potential for conservation of wild populations

PubMed Central

Harrisson, Katherine A; Pavlova, Alexandra; Telonis-Scott, Marina; Sunnucks, Paul

2014-01-01

Genomics promises exciting advances towards the important conservation goal of maximizing evolutionary potential, notwithstanding associated challenges. Here, we explore some of the complexity of adaptation genetics and discuss the strengths and limitations of genomics as a tool for characterizing evolutionary potential in the context of conservation management. Many traits are polygenic and can be strongly influenced by minor differences in regulatory networks and by epigenetic variation not visible in DNA sequence. Much of this critical complexity is difficult to detect using methods commonly used to identify adaptive variation, and this needs appropriate consideration when planning genomic screens, and when basing management decisions on genomic data. When the genomic basis of adaptation and future threats are well understood, it may be appropriate to focus management on particular adaptive traits. For more typical conservations scenarios, we argue that screening genome-wide variation should be a sensible approach that may provide a generalized measure of evolutionary potential that accounts for the contributions of small-effect loci and cryptic variation and is robust to uncertainty about future change and required adaptive response(s). The best conservation outcomes should be achieved when genomic estimates of evolutionary potential are used within an adaptive management framework. PMID:25553064

Selective predation for low body condition at the larval-juvenile transition of a coral reef fish.

PubMed

Hoey, Andrew S; McCormick, Mark I

2004-03-01

Mortality is known to be high during the transition from larval to juvenile life stages in organisms that have complex life histories. We are only just beginning to understand the processes that influence which individuals survive this period of high mortality, and which traits may be beneficial. Here we document a field experiment that examines the selectivity of predation immediately following settlement to the juvenile population in a common tropical fish, Pomacentrus amboinensis (Pomacentridae). Newly metamorphosed fish were tagged and randomly placed onto replicated patches of natural habitat cleared of resident fishes. After exposure to transient predators for 3 days, fish were recollected and the attributes of survivors from patch reefs that sustained high mortality were compared to individuals from patch reefs that experienced low mortality. Seven characteristics of individuals, which were indicative of previous and present body condition, were compared between groups. Predation was found to be selective for fish that grew slowly in the latter third of their larval phase, were low in total lipids, and had a high standardized weight (Fulton's K). Traits developed in the larval phase can strongly influence the survival of individuals over this critical transition period for organisms with complex life cycles.

Not just black and white: pigment pattern development and evolution in vertebrates

PubMed Central

Mills, Margaret G.; Patterson, Larissa B.

2009-01-01

Animals display diverse colors and patterns that vary within and between species. Similar phenotypes appear in both closely related and widely divergent taxa. Pigment patterns thus provide an opportunity to explore how development is altered to produce differences in form and whether similar phenotypes share a common genetic basis. Understanding the development and evolution of pigment patterns requires knowledge of the cellular interactions and signaling pathways that produce those patterns. These complex traits provide unparalleled opportunities for integrating studies from ecology and behavior to molecular biology and biophysics. PMID:19073271

Chitosan-induced antiviral activity and innate immunity in plants.

PubMed

Iriti, Marcello; Varoni, Elena Maria

2015-02-01

Immunity represents a trait common to all living organisms, and animals and plants share some similarities. Therefore, in susceptible host plants, complex defence machinery may be stimulated by elicitors. Among these, chitosan deserves particular attention because of its proved efficacy. This survey deals with the antiviral activity of chitosan, focusing on its perception by the plant cell and mechanism of action. Emphasis has been paid to benefits and limitations of this strategy in crop protection, as well as to the potential of chitosan as a promising agent in virus disease control.

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

Uses of the Twins UK genetic database.

PubMed

Spector, Tim D

2007-11-01

Tim Spector is a Professor of Genetic Epidemiology at King's College London and Director of the Twin Research and Genetic Epidemiology Unit at St Thomas' Hospital, London. Professor Spector graduated from St Bartholomew's Hospital Medical School, London, in 1982. After working in General Medicine, he completed a MSc in Epidemiology, and his MD degree at the University of London in 1989. He founded the UK Twins Registry of 10,000 twins in 1993, which is one of the largest collections of genotype and phenotype information on twins worldwide, whose breadth of research has expanded to cover a wide range of common complex traits many of which were previously thought to be mainly due to aging and the environment. He has published over 350 research articles on common diseases. He has written several original articles on the genetics of a wide range of diseases and traits including back pain, acne, inflammation, obesity, memory, musical ability and sexuality. He is the principal investigator of the EU Euroclot and Treat OA study, and a partner in five others. He has written several books, focusing on osteoporosis and genetics and, in 2003, he published a popular book on genetics: Your Genes Unzipped.

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...

Identification of genetic loci shared between schizophrenia and the Big Five personality traits.

PubMed

Smeland, Olav B; Wang, Yunpeng; Lo, Min-Tzu; Li, Wen; Frei, Oleksandr; Witoelar, Aree; Tesli, Martin; Hinds, David A; Tung, Joyce Y; Djurovic, Srdjan; Chen, Chi-Hua; Dale, Anders M; Andreassen, Ole A

2017-05-22

Schizophrenia is associated with differences in personality traits, and recent studies suggest that personality traits and schizophrenia share a genetic basis. Here we aimed to identify specific genetic loci shared between schizophrenia and the Big Five personality traits using a Bayesian statistical framework. Using summary statistics from genome-wide association studies (GWAS) on personality traits in the 23andMe cohort (n = 59,225) and schizophrenia in the Psychiatric Genomics Consortium cohort (n = 82,315), we evaluated overlap in common genetic variants. The Big Five personality traits neuroticism, extraversion, openness, agreeableness and conscientiousness were measured using a web implementation of the Big Five Inventory. Applying the conditional false discovery rate approach, we increased discovery of genetic loci and identified two loci shared between neuroticism and schizophrenia and six loci shared between openness and schizophrenia. The study provides new insights into the relationship between personality traits and schizophrenia by highlighting genetic loci involved in their common genetic etiology.

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.

Identification of genotyping-by-sequencing sequence tags associated with milling performance and end-use quality traits in hard red spring wheat (Triticum aestivum L.)

USDA-ARS?s Scientific Manuscript database

Wheat quality is defined by culinary end-uses and processing characteristics. Wheat breeders are interested to identify quantitative trait loci for grain, milling, and end-use quality traits because it is imperative to understand the genetic complexity underlying quantitatively inherited traits to ...

Quantitative trait loci for live animal and carcass composition traits in Jersey and Limousin back-cross cattle finished on pasture or feedlot.

PubMed

Morris, C A; Pitchford, W S; Cullen, N G; Esmailizadeh, A K; Hickey, S M; Hyndman, D; Dodds, K G; Afolayan, R A; Crawford, A M; Bottema, C D K

2009-10-01

A quantitative trait locus (QTL) study was carried out in two countries, recording live animal and carcass composition traits. Back-cross calves (385 heifers and 398 steers) were generated, with Jersey and Limousin breed backgrounds. The New Zealand cattle were reared on pasture to carcass weights averaging 229 kg, whilst the Australian cattle were reared on grass and finished on grain (for at least 180 days) to carcass weights averaging 335 kg. From 11 live animal traits and 31 carcass composition traits respectively, 5 and 22 QTL were detected in combined-sire analyses, which were significant (P < 0.05) on a genome-wise basis. Fourteen significant traits for carcass composition QTL were on chromosome 2 and these were traits associated with muscling and fatness. This chromosome carried a variant myostatin allele (F94L), segregating from the Limousin ancestry. Despite very different cattle management systems between the two countries, the two populations had a large number of QTL in common. Of the 18 traits which were common to both countries, and which had significant QTL at the genome-wise level, eight were significant in both countries.

Outcrossing and crossbreeding recovers deteriorated traits in laboratory cultured Steinernema carpocapsae nematodes

PubMed Central

Chaston, John M.; Dillman, Adler R.; Shapiro-Ilan, David I.; Bilgrami, Anwar L.; Gaugler, Randy; Hopper, Keith R.; Adams, Byron J.

2011-01-01

The nematode Steinernema carpocapsae infects and kills many pest insects in agroecosystems and is commonly used in biocontrol of these pests. Growth of the nematodes prior to distribution for biocontrol commonly results in deterioration of traits that are essential for nematode persistence in field applications. To better understand the mechanisms underlying trait deterioration of the efficacy of natural parasitism in entomopathogenic nematodes, we explored the maintenance of fitness related traits including reproductive capacity, heat tolerance, virulence to insects and `tail standing' (formerly called nictation) among laboratory-cultured lines derived from natural, randomly mating populations of S. carpocapsae. Laboratory cultured nematode lines with fitness-related trait values below wild-type levels regained wild-type levels of reproductive and heat tolerance traits when outcrossed with a non-deteriorated line, while virulence and `tail standing' did not deteriorate in our experiments. Crossbreeding two trait-deteriorated lines with each other also resulted in restoration of trait means to wild-type levels in most crossbred lines. Our results implicate inbreeding depression as the primary cause of trait deterioration in the laboratory cultured S. carpocapsae. We further suggest the possibility of creating inbred lines purged of deleterious alleles as founders in commercial nematode growth. PMID:21447341

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.

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.

CNV-association meta-analysis in 191,161 European adults reveals new loci associated with anthropometric traits.

PubMed

Macé, Aurélien; Tuke, Marcus A; Deelen, Patrick; Kristiansson, Kati; Mattsson, Hannele; Nõukas, Margit; Sapkota, Yadav; Schick, Ursula; Porcu, Eleonora; Rüeger, Sina; McDaid, Aaron F; Porteous, David; Winkler, Thomas W; Salvi, Erika; Shrine, Nick; Liu, Xueping; Ang, Wei Q; Zhang, Weihua; Feitosa, Mary F; Venturini, Cristina; van der Most, Peter J; Rosengren, Anders; Wood, Andrew R; Beaumont, Robin N; Jones, Samuel E; Ruth, Katherine S; Yaghootkar, Hanieh; Tyrrell, Jessica; Havulinna, Aki S; Boers, Harmen; Mägi, Reedik; Kriebel, Jennifer; Müller-Nurasyid, Martina; Perola, Markus; Nieminen, Markku; Lokki, Marja-Liisa; Kähönen, Mika; Viikari, Jorma S; Geller, Frank; Lahti, Jari; Palotie, Aarno; Koponen, Päivikki; Lundqvist, Annamari; Rissanen, Harri; Bottinger, Erwin P; Afaq, Saima; Wojczynski, Mary K; Lenzini, Petra; Nolte, Ilja M; Sparsø, Thomas; Schupf, Nicole; Christensen, Kaare; Perls, Thomas T; Newman, Anne B; Werge, Thomas; Snieder, Harold; Spector, Timothy D; Chambers, John C; Koskinen, Seppo; Melbye, Mads; Raitakari, Olli T; Lehtimäki, Terho; Tobin, Martin D; Wain, Louise V; Sinisalo, Juha; Peters, Annette; Meitinger, Thomas; Martin, Nicholas G; Wray, Naomi R; Montgomery, Grant W; Medland, Sarah E; Swertz, Morris A; Vartiainen, Erkki; Borodulin, Katja; Männistö, Satu; Murray, Anna; Bochud, Murielle; Jacquemont, Sébastien; Rivadeneira, Fernando; Hansen, Thomas F; Oldehinkel, Albertine J; Mangino, Massimo; Province, Michael A; Deloukas, Panos; Kooner, Jaspal S; Freathy, Rachel M; Pennell, Craig; Feenstra, Bjarke; Strachan, David P; Lettre, Guillaume; Hirschhorn, Joel; Cusi, Daniele; Heid, Iris M; Hayward, Caroline; Männik, Katrin; Beckmann, Jacques S; Loos, Ruth J F; Nyholt, Dale R; Metspalu, Andres; Eriksson, Johan G; Weedon, Michael N; Salomaa, Veikko; Franke, Lude; Reymond, Alexandre; Frayling, Timothy M; Kutalik, Zoltán

2017-09-29

There are few examples of robust associations between rare copy number variants (CNVs) and complex continuous human traits. Here we present a large-scale CNV association meta-analysis on anthropometric traits in up to 191,161 adult samples from 26 cohorts. The study reveals five CNV associations at 1q21.1, 3q29, 7q11.23, 11p14.2, and 18q21.32 and confirms two known loci at 16p11.2 and 22q11.21, implicating at least one anthropometric trait. The discovered CNVs are recurrent and rare (0.01-0.2%), with large effects on height (>2.4 cm), weight (>5 kg), and body mass index (BMI) (>3.5 kg/m 2 ). Burden analysis shows a 0.41 cm decrease in height, a 0.003 increase in waist-to-hip ratio and increase in BMI by 0.14 kg/m 2 for each Mb of total deletion burden (P = 2.5 × 10 -10 , 6.0 × 10 -5 , and 2.9 × 10 -3 ). Our study provides evidence that the same genes (e.g., MC4R, FIBIN, and FMO5) harbor both common and rare variants affecting body size and that anthropometric traits share genetic loci with developmental and psychiatric disorders.Individual SNPs have small effects on anthropometric traits, yet the impact of CNVs has remained largely unknown. Here, Kutalik and co-workers perform a large-scale genome-wide meta-analysis of structural variation and find rare CNVs associated with height, weight and BMI with large effect sizes.

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.

Late acquisition of mitochondria by a host with chimaeric prokaryotic ancestry.

PubMed

Pittis, Alexandros A; Gabaldón, Toni

2016-03-03

The origin of eukaryotes stands as a major conundrum in biology. Current evidence indicates that the last eukaryotic common ancestor already possessed many eukaryotic hallmarks, including a complex subcellular organization. In addition, the lack of evolutionary intermediates challenges the elucidation of the relative order of emergence of eukaryotic traits. Mitochondria are ubiquitous organelles derived from an alphaproteobacterial endosymbiont. Different hypotheses disagree on whether mitochondria were acquired early or late during eukaryogenesis. Similarly, the nature and complexity of the receiving host are debated, with models ranging from a simple prokaryotic host to an already complex proto-eukaryote. Most competing scenarios can be roughly grouped into either mito-early, which consider the driving force of eukaryogenesis to be mitochondrial endosymbiosis into a simple host, or mito-late, which postulate that a significant complexity predated mitochondrial endosymbiosis. Here we provide evidence for late mitochondrial endosymbiosis. We use phylogenomics to directly test whether proto-mitochondrial proteins were acquired earlier or later than other proteins of the last eukaryotic common ancestor. We find that last eukaryotic common ancestor protein families of alphaproteobacterial ancestry and of mitochondrial localization show the shortest phylogenetic distances to their closest prokaryotic relatives, compared with proteins of different prokaryotic origin or cellular localization. Altogether, our results shed new light on a long-standing question and provide compelling support for the late acquisition of mitochondria into a host that already had a proteome of chimaeric phylogenetic origin. We argue that mitochondrial endosymbiosis was one of the ultimate steps in eukaryogenesis and that it provided the definitive selective advantage to mitochondria-bearing eukaryotes over less complex forms.

Genome-wide association analysis of symbiotic nitrogen fixation in common bean

USDA-ARS?s Scientific Manuscript database

A genome-wide association study (GWAS) was conducted to explore the genetic basis of variation for symbiotic nitrogen fixation (SNF) and related traits in the Andean diversity panel (ADP) comprised of 259 common bean (Phaseolus vulgaris) genotypes. The ADP was evaluated for SNF and related traits in...

The genome revolution and its role in understanding complex diseases.

PubMed

Hofker, Marten H; Fu, Jingyuan; Wijmenga, Cisca

2014-10-01

The completion of the human genome sequence in 2003 clearly marked the beginning of a new era for biomedical research. It spurred technological progress that was unprecedented in the life sciences, including the development of high-throughput technologies to detect genetic variation and gene expression. The study of genetics has become "big data science". One of the current goals of genetic research is to use genomic information to further our understanding of common complex diseases. An essential first step made towards this goal was by the identification of thousands of single nucleotide polymorphisms showing robust association with hundreds of different traits and diseases. As insight into common genetic variation has expanded enormously and the technology to identify more rare variation has become available, we can utilize these advances to gain a better understanding of disease etiology. This will lead to developments in personalized medicine and P4 healthcare. Here, we review some of the historical events and perspectives before and after the completion of the human genome sequence. We also describe the success of large-scale genetic association studies and how these are expected to yield more insight into complex disorders. We show how we can now combine gene-oriented research and systems-based approaches to develop more complex models to help explain the etiology of common diseases. This article is part of a Special Issue entitled: From Genome to Function. Copyright © 2014 Elsevier B.V. All rights reserved.

Lumpy species coexistence arises robustly in fluctuating resource environments.

PubMed

Sakavara, Athanasia; Tsirtsis, George; Roelke, Daniel L; Mancy, Rebecca; Spatharis, Sofie

2018-01-23

The effect of life-history traits on resource competition outcomes is well understood in the context of a constant resource supply. However, almost all natural systems are subject to fluctuations of resources driven by cyclical processes such as seasonality and tidal hydrology. To understand community composition, it is therefore imperative to study the impact of resource fluctuations on interspecies competition. We adapted a well-established resource-competition model to show that fluctuations in inflow concentrations of two limiting resources lead to the survival of species in clumps along the trait axis, consistent with observations of "lumpy coexistence" [Scheffer M, van Nes EH (2006) Proc Natl Acad Sci USA 103:6230-6235]. A complex dynamic pattern in the available ambient resources arose very early in the self-organization process and dictated the locations of clumps along the trait axis by creating niches that promoted the growth of species with specific traits. This dynamic pattern emerged as the combined result of fluctuations in the inflow of resources and their consumption by the most competitive species that accumulated the bulk of biomass early in assemblage organization. Clumps emerged robustly across a range of periodicities, phase differences, and amplitudes. Given the ubiquity in the real world of asynchronous fluctuations of limiting resources, our findings imply that assemblage organization in clumps should be a common feature in nature. Copyright © 2018 the Author(s). Published by PNAS.

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?

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.

Complex Adaptive System Models and the Genetic Analysis of Plasma HDL-Cholesterol Concentration

PubMed Central

Rea, Thomas J.; Brown, Christine M.; Sing, Charles F.

2006-01-01

Despite remarkable advances in diagnosis and therapy, ischemic heart disease (IHD) remains a leading cause of morbidity and mortality in industrialized countries. Recent efforts to estimate the influence of genetic variation on IHD risk have focused on predicting individual plasma high-density lipoprotein cholesterol (HDL-C) concentration. Plasma HDL-C concentration (mg/dl), a quantitative risk factor for IHD, has a complex multifactorial etiology that involves the actions of many genes. Single gene variations may be necessary but are not individually sufficient to predict a statistically significant increase in risk of disease. The complexity of phenotype-genotype-environment relationships involved in determining plasma HDL-C concentration has challenged commonly held assumptions about genetic causation and has led to the question of which combination of variations, in which subset of genes, in which environmental strata of a particular population significantly improves our ability to predict high or low risk phenotypes. We document the limitations of inferences from genetic research based on commonly accepted biological models, consider how evidence for real-world dynamical interactions between HDL-C determinants challenges the simplifying assumptions implicit in traditional linear statistical genetic models, and conclude by considering research options for evaluating the utility of genetic information in predicting traits with complex etiologies. PMID:17146134

Patterns in root traits of woody species hosting arbuscular and ectomycorrhizas: implications for the evolution of belowground strategies

USDA-ARS?s Scientific Manuscript database

Despite large variation in root traits among species, we have limited understanding of how traits are related to diverse soil resource acquisition strategies. We examined root trait variation among 33 species co-existing in Northeastern US forests that form the two most common mutualisms with mycorr...

Psychometric Properties of the ASPeCT-DD: Measuring Positive Traits in Persons with Developmental Disabilities

ERIC Educational Resources Information Center

Woodard, Cooper

2009-01-01

Background: The Assessment Scale for Positive Character Traits-Developmental Disabilities (ASPeCT-DD) was designed to measure the presence and strength of selected positive or strength-based traits in persons with developmental disabilities. These traits may help to determine level of happiness or value associated with the more commonly measured…

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.

Metabolic syndrome-related composite factors over 5 years in the STANISLAS family study: genetic heritability and common environmental influences.

PubMed

Herbeth, Bernard; Samara, Anastasia; Ndiaye, Coumba; Marteau, Jean-Brice; Berrahmoune, Hind; Siest, Gérard; Visvikis-Siest, Sophie

2010-06-03

We estimated genetic heritability and common environmental influences for various traits related to metabolic syndrome in young families from France. At entrance and after 5 years, nineteen traits related to metabolic syndrome were measured in a sample of families drawn from the STANISLAS study. In addition, 5 aggregates of these traits were identified using factor analysis. At entrance, genetic heritability was high (20 to 44%) for plasma lipids and lipoproteins, uric acid, fasting glucose, and the related clusters "risk lipids" and "protective lipids". Intermediate or low genetic heritability (less than 20%) was shown for triglycerides, adiposity indices, blood pressure, hepatic enzyme activity, inflammatory makers and the related clusters: "liver enzymes", "adiposity/blood pressure" and "inflammation". Moreover, common environmental influences were significant for all the parameters. With regard to 5-year changes, polygenic variance was low and not statistically significant for any of the individual variables or clusters whereas shared environment influence was significant. In these young families, genetic heritability of metabolic syndrome-related traits was generally lower than previously reported while the common environmental influences were greater. In addition, only shared environment contributed to short-term changes of these traits. Copyright 2010 Elsevier B.V. All rights reserved.

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

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

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.

Sleep in childhood and adolescence: age-specific sleep characteristics, common sleep disturbances and associated difficulties.

PubMed

Barclay, Nicola L; Gregory, Alice M

2014-01-01

Sleep changes throughout the lifespan, with particularly salient alterations occurring during the first few years of life, as well as during the transition from childhood to adolescence. Such changes are partly the result of brain maturation; complex changes in the organisation of the circadian system; as well as changes in daily routine, environmental demands and responsibilities. Despite the automaticity of sleep, given that it is governed by a host of complex mechanisms, there are times when sleep becomes disturbed. Sleep disturbances in childhood are common and may stem from behavioural difficulties or abnormalities in physiological processes-and, in some cases manifest into diagnosable sleep disorders. As well as occurring exclusively, childhood sleep disturbances often co-occur with other difficulties. The purpose of this chapter is to outline the neurobiology of typical sleep/wake processes, and describe changes in sleep physiology and architecture from birth to adulthood. Furthermore, common childhood sleep disorders are described as are their associations with other traits, including all of the syndromes presented in this handbook: ASDs, ADHD, schizophrenia and emotional/behavioural difficulties. Throughout, we attempt to explain possible mechanisms underlying these disorders and their associations.

The Genetics of Asthma and Allergic Disease: A 21st Century Perspective

PubMed Central

Ober, Carole; Yao, Tsung-Chieh

2011-01-01

Summary Asthma and allergy are common conditions with complex etiologies involving both genetic and environmental contributions. Recent genome-wide association studies (GWAS) and meta-analyses of GWAS have begun to shed light on both common and distinct pathways that contribute to asthma and allergic diseases. Associations with variation in genes encoding the epithelial cell-derived cytokines, interleukin-33 (IL-33) and thymic stromal lymphopoietin (TSLP), and the IL1RL1 gene encoding the IL-33 receptor, ST2, highlight the central roles for innate immune response pathways that promote the activation and differentiation of T-helper 2 (Th2) cells in the pathogenesis of both asthma and allergic diseases. In contrast, variation at the 17q21 asthma locus, encoding the ORMDL3 and GSDML genes, is specifically associated with risk for childhood onset asthma. These and other genetic findings are providing a list of well-validated asthma and allergy susceptibility genes that are expanding our understanding of the common and unique biological pathways that are dysregulated in these related conditions. Ongoing studies will continue to broaden our understanding of asthma and allergy and unravel the mechanisms for the development of these complex traits. PMID:21682736

Heteroscedastic Latent Trait Models for Dichotomous Data.

PubMed

Molenaar, Dylan

2015-09-01

Effort has been devoted to account for heteroscedasticity with respect to observed or latent moderator variables in item or test scores. For instance, in the multi-group generalized linear latent trait model, it could be tested whether the observed (polychoric) covariance matrix differs across the levels of an observed moderator variable. In the case that heteroscedasticity arises across the latent trait itself, existing models commonly distinguish between heteroscedastic residuals and a skewed trait distribution. These models have valuable applications in intelligence, personality and psychopathology research. However, existing approaches are only limited to continuous and polytomous data, while dichotomous data are common in intelligence and psychopathology research. Therefore, in present paper, a heteroscedastic latent trait model is presented for dichotomous data. The model is studied in a simulation study, and applied to data pertaining alcohol use and cognitive ability.

A critical issue in model-based inference for studying trait-based community assembly and a solution.

PubMed

Ter Braak, Cajo J F; Peres-Neto, Pedro; Dray, Stéphane

2017-01-01

Statistical testing of trait-environment association from data is a challenge as there is no common unit of observation: the trait is observed on species, the environment on sites and the mediating abundance on species-site combinations. A number of correlation-based methods, such as the community weighted trait means method (CWM), the fourth-corner correlation method and the multivariate method RLQ, have been proposed to estimate such trait-environment associations. In these methods, valid statistical testing proceeds by performing two separate resampling tests, one site-based and the other species-based and by assessing significance by the largest of the two p -values (the p max test). Recently, regression-based methods using generalized linear models (GLM) have been proposed as a promising alternative with statistical inference via site-based resampling. We investigated the performance of this new approach along with approaches that mimicked the p max test using GLM instead of fourth-corner. By simulation using models with additional random variation in the species response to the environment, the site-based resampling tests using GLM are shown to have severely inflated type I error, of up to 90%, when the nominal level is set as 5%. In addition, predictive modelling of such data using site-based cross-validation very often identified trait-environment interactions that had no predictive value. The problem that we identify is not an "omitted variable bias" problem as it occurs even when the additional random variation is independent of the observed trait and environment data. Instead, it is a problem of ignoring a random effect. In the same simulations, the GLM-based p max test controlled the type I error in all models proposed so far in this context, but still gave slightly inflated error in more complex models that included both missing (but important) traits and missing (but important) environmental variables. For screening the importance of single trait-environment combinations, the fourth-corner test is shown to give almost the same results as the GLM-based tests in far less computing time.

Confirming Testlet Effects

ERIC Educational Resources Information Center

DeMars, Christine E.

2012-01-01

A testlet is a cluster of items that share a common passage, scenario, or other context. These items might measure something in common beyond the trait measured by the test as a whole; if so, the model for the item responses should allow for this testlet trait. But modeling testlet effects that are negligible makes the model unnecessarily…

RNAi and retroviruses: are they in RISC?

PubMed

Vasselon, Thierry; Bouttier, Manuella; Saumet, Anne; Lecellier, Charles-Henri

2013-02-01

RNA interference (RNAi) is a potent cellular system against viruses in various organisms. Although common traits are observed in plants, insects, and nematodes, the situation observed in mammals appears more complex. In mammalian somatic cells, RNAi is implicated in endonucleolytic cleavage mediated by artificially delivered small interfering RNAs (siRNAs) as well as in translation repression mediated by microRNAs (miRNAs). Because siRNAs and miRNAs recognize viral mRNAs, RNAi inherently limits virus production and participates in antiviral defense. However, several observations made in the cases of hepatitis C virus and retroviruses (including the human immunodeficiency virus and the primate foamy virus) bring evidence that this relationship is much more complex and that certain components of the RNAi effector complex [called the RNA-induced silencing complex (RISC)], such as AGO2, are also required for viral replication. Here, we summarize recent discoveries that have revealed this dual implication in virus biology. We further discuss their potential implications for the functions of RNAi-related proteins, with special emphasis on retrotransposition and genome stability.

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.

DSM-5 pathological personality traits and the personality assessment inventory.

PubMed

Hopwood, Christopher J; Wright, Aidan G C; Krueger, Robert F; Schade, Nick; Markon, Kristian E; Morey, Leslie C

2013-06-01

Section 3 of the DSM-5 will include a pathological personality trait system rooted in the quantitative epistemology of personality and clinical psychology. This system has the potential to enhance the clinical utility of the diagnostic nosology by providing a means for the dimensional assessment of individuals with psychopathology. However, there is limited research on the associations of DSM-5 traits with common mental disorders and related clinical phenomena as measured by currently popular assessment instruments. The purpose of this article was to evaluate the convergence of the DSM-5 trait system with a well-validated broadband clinical instrument, the Personality Assessment Inventory (PAI). Bivariate correlations were examined and factor analytic methods were used to examine the degree to which the DSM-5 traits and PAI capture common variance in personality and mental health. In a student sample (N = 1,001), we found broad convergence between the DSM-5 traits and PAI, which could be organized effectively using five factors. The implications of these findings for using traits to address issues related to diagnostic co-occurrence and heterogeneity in routine clinical assessment are discussed.

Nonmetric traits of permanent posterior teeth in Kerala population: A forensic overview

PubMed Central

Baby, Tibin K; Sunil, S; Babu, Sharlene Sara

2017-01-01

Introduction: Dental morphology is a highly heritable characteristic which is stable with time and has a fairly high state of preservation. Nonmetric dental traits have crucial role in ethnic classifications of a population that helps in forensic racial identification purposes. Aims and Objectives: To determine the frequency and variability of possible nonmetric tooth traits using extracted permanent posterior teeth from Kerala population for discerning racial ethnicity. Materials and Methods: This qualitative, cross-sectional study was carried out using 1743 extracted intact permanent posterior teeth collected from different dental clinics situated all over Kerala. Results: The more common features on premolars were multiple lingual cusps (31.21%), distal accessary ridges (16.28%) and Tom's root (17.9%). In upper first molars, Carabelli trait expression was 17.78% and other common features included metaconulo, cusp 5 and enamel extensions. Conclusion: Posterior tooth traits had variable expression in the study population. Low prevalence rate of Carabelli trait in this study is characteristic of Asian population. This research explored new elements of invaluable tooth traits values to understand racial ethnicity of Kerala population. PMID:28932045

Differences in forest plant functional trait distributions across land-use and productivity gradients

Treesearch

Margaret M. Mayfield; John M. Dwyer; Loic Chalmandrier; Jessie A. Wells; Stephen P. Bonser; Carla P. Catterall; Fabrice DeClerck; Yi Ding; Jennifer M. Fraterrigo; Daniel J. Metcalfe; Cibele Queiroz; Peter A. Vesk; John W. Morgan

2013-01-01

• Premise of study: Plant functional traits are commonly used as proxies for plant responses to environmental challenges, yet few studies have explored how functional trait distributions differ across gradients of land-use change. By comparing trait distributions in intact forests with those across land-use change gradients, we can improve our understanding of the ways...

Identifying Specific Genes Controlling Complex Traits Through A Genome-Wide Screen For cis-Acting Regulatory Elements - An Example Using Marek's Disease

USDA-ARS?s Scientific Manuscript database

The identification of specific genes underlying phenotypic variation of complex traits 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 depend on linkage. One altern...

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

USDA-ARS?s Scientific Manuscript database

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

Genetic Architecture of Atherosclerosis in Mice: A Systems Genetics Analysis of Common Inbred Strains

PubMed Central

Bennett, Brian J.; Davis, Richard C.; Civelek, Mete; Orozco, Luz; Wu, Judy; Qi, Hannah; Pan, Calvin; Packard, René R. Sevag; Eskin, Eleazar; Yan, Mujing; Kirchgessner, Todd; Wang, Zeneng; Li, Xinmin; Gregory, Jill C.; Hazen, Stanley L.; Gargalovic, Peter S.; Lusis, Aldons J.

2015-01-01

Common forms of atherosclerosis involve multiple genetic and environmental factors. While human genome-wide association studies have identified numerous loci contributing to coronary artery disease and its risk factors, these studies are unable to control environmental factors or examine detailed molecular traits in relevant tissues. We now report a study of natural variations contributing to atherosclerosis and related traits in over 100 inbred strains of mice from the Hybrid Mouse Diversity Panel (HMDP). The mice were made hyperlipidemic by transgenic expression of human apolipoprotein E-Leiden (APOE-Leiden) and human cholesteryl ester transfer protein (CETP). The mice were examined for lesion size and morphology as well as plasma lipid, insulin and glucose levels, and blood cell profiles. A subset of mice was studied for plasma levels of metabolites and cytokines. We also measured global transcript levels in aorta and liver. Finally, the uptake of acetylated LDL by macrophages from HMDP mice was quantitatively examined. Loci contributing to the traits were mapped using association analysis, and relationships among traits were examined using correlation and statistical modeling. A number of conclusions emerged. First, relationships among atherosclerosis and the risk factors in mice resemble those found in humans. Second, a number of trait-loci were identified, including some overlapping with previous human and mouse studies. Third, gene expression data enabled enrichment analysis of pathways contributing to atherosclerosis and prioritization of candidate genes at associated loci in both mice and humans. Fourth, the data provided a number of mechanistic inferences; for example, we detected no association between macrophage uptake of acetylated LDL and atherosclerosis. Fifth, broad sense heritability for atherosclerosis was much larger than narrow sense heritability, indicating an important role for gene-by-gene interactions. Sixth, stepwise linear regression showed that the combined variations in plasma metabolites, including LDL/VLDL-cholesterol, trimethylamine N-oxide (TMAO), arginine, glucose and insulin, account for approximately 30 to 40% of the variation in atherosclerotic lesion area. Overall, our data provide a rich resource for studies of complex interactions underlying atherosclerosis. PMID:26694027

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.

We can be heroes: MLA’s leadership journey(s)*

PubMed Central

Tooey, Mary Joan (M.J.)

2017-01-01

Objective Are there key attributes of leaders? Extrovert versus introvert? Charismatic? Detail oriented? Visionary? How do past leaders of the Medical Library Association (MLA) stack up? What leadership skills will MLA’s leaders need in a complex information future? Leadership attributes of MLA’s past and current presidents were studied to determine the common characteristics shared among these leaders. An examination of the leadership literature identified critical leadership characteristics essential to successful future leaders. MLA’s past, current, and future leadership development efforts were examined. Finally, all members were encouraged to consider leadership with a small “l” and become leaders based on their own strengths, interests, and environments. Methods A text analysis was performed on past presidential profiles, the past twenty-five years of MLA presidents were surveyed, and conversations with MLA’s current presidents were held to determine commonalities among leadership characteristics. These were compared and contrasted with characteristics in the current leadership literature regarding the qualities of future leaders. Results The text analysis of past presidential profiles was not particularly revelatory regarding leadership qualities of early MLA presidents although several generalized traits emerged including collaborative traits; management traits such as effectiveness and efficiency, innovation, and vision; personal traits such as humor and energy; and finally, a passion for the work were revealed. These aligned with traits identified in the survey of the past twenty-five years of MLA presidents and with the thoughts of the president-elect, president, and past president. Additional qualities identified were communication skills, political acumen, creativity, courage, and respect for the opinions and concerns of all members. MLA’s current leadership programs were reviewed in the context of examining traits needed by leaders of the future. A lack of focus on the needs of middle managers and the development of individual leadership skills was identified. Conclusions As an organization, MLA should focus on leadership development in contrast to management training to prepare members as leaders in careers and work that may be vastly different than current situations. Equipping members with the skills enabling them to lead and thrive in these diverse situations, whether as the heads of programs or middle managers, or exploring and empowering individual leadership development while maintaining a passion for the profession, will be essential. PMID:28096752

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.

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.

Outcrossing and crossbreeding recovers deteriorated traits in laboratory cultured Steinernema carpocapsae nematodes.

PubMed

Chaston, John M; Dillman, Adler R; Shapiro-Ilan, David I; Bilgrami, Anwar L; Gaugler, Randy; Hopper, Keith R; Adams, Byron J

2011-06-01

The nematode Steinernema carpocapsae infects and kills many pest insects in agro-ecosystems and is commonly used in biocontrol of these pests. Growth of the nematodes prior to distribution for biocontrol commonly results in deterioration of traits that are essential for nematode persistence in field applications. To better understand the mechanisms underlying trait deterioration of the efficacy of natural parasitism in entomopathogenic nematodes, we explored the maintenance of fitness related traits including reproductive capacity, heat tolerance, virulence to insects and 'tail standing' (formerly called nictation) among laboratory-cultured lines derived from natural, randomly mating populations of S. carpocapsae. Laboratory cultured nematode lines with fitness-related trait values below wild-type levels regained wild-type levels of reproductive and heat tolerance traits when outcrossed with a non-deteriorated line, while virulence and 'tail standing' did not deteriorate in our experiments. Crossbreeding two trait-deteriorated lines with each other also resulted in restoration of trait means to wild-type levels in most crossbred lines. Our results implicate inbreeding depression as the primary cause of trait deterioration in the laboratory cultured S. carpocapsae. We further suggest the possibility of creating inbred lines purged of deleterious alleles as founders in commercial nematode growth. Copyright © 2011 Australian Society for Parasitology Inc. All rights reserved.

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

PubMed

Alvares, R C; Silva, F C; Melo, L C; Melo, P G S; Pereira, H S

2016-11-21

Slow seed coat darkening is desirable in common bean cultivars and genetic parameters are important to define breeding strategies. The aims of this study were to estimate genetic parameters for plant architecture, grain yield, grain size, and seed-coat darkening in common bean; identify any genetic association among these traits; and select lines that associate desirable phenotypes for these traits. Three experiments were set up in the winter 2012 growing season, in Santo Antônio de Goiás and Brasília, Brazil, including 220 lines obtained from four segregating populations and five parents. A triple lattice 15 x 15 experimental design was used. The traits evaluated were plant architecture, grain yield, grain size, and seed-coat darkening. Analyses of variance were carried out and genetic parameters such as heritability, gain expected from selection, and correlations, were estimated. For selection of superior lines, a "weight-free and parameter-free" index was used. The estimates of genetic variance, heritability, and gain expected from selection were high, indicating good possibility for success in selection of the four traits. The genotype x environment interaction was proportionally more important for yield than for the other traits. There was no strong genetic correlation observed among the four traits, which indicates the possibility of selection of superior lines with many traits. Considering simultaneous selection, it was not possible to join high genetic gains for the four traits. Forty-four lines that combined high yield, more upright plant architecture, slow darkening grains, and commercial grade size were selected.

Species climate range influences hydraulic and stomatal traits in Eucalyptus species.

PubMed

Bourne, Aimee E; Creek, Danielle; Peters, Jennifer M R; Ellsworth, David S; Choat, Brendan

2017-07-01

Plant hydraulic traits influence the capacity of species to grow and survive in water-limited environments, but their comparative study at a common site has been limited. The primary aim of this study was to determine whether selective pressures on species originating in drought-prone environments constrain hydraulic traits among related species grown under common conditions. Leaf tissue water relations, xylem anatomy, stomatal behaviour and vulnerability to drought-induced embolism were measured on six Eucalyptus species growing in a common garden to determine whether these traits were related to current species climate range and to understand linkages between the traits. Hydraulically weighted xylem vessel diameter, leaf turgor loss point, the water potential at stomatal closure and vulnerability to drought-induced embolism were significantly ( P < 0·05) correlated with climate parameters from the species range. There was a co-ordination between stem and leaf parameters with the water potential at turgor loss, 12 % loss of conductivity and the point of stomatal closure significantly correlated. The correlation of hydraulic, stomatal and anatomical traits with climate variables from the species' original ranges suggests that these traits are genetically constrained. The conservative nature of xylem traits in Eucalyptus trees has important implications for the limits of species responses to changing environmental conditions and thus for species survival and distribution into the future, and yields new information for physiological models. © The Author 2017. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Phenotypic and genetic relations between the HEXACO dimensions and trait emotional intelligence.

PubMed

Veselka, Livia; Petrides, K V; Schermer, Julie Aitken; Cherkas, Lynn F; Spector, Tim D; Vernon, Philip A

2010-02-01

The present study investigated the location of trait emotional intelligence (trait EI or trait emotional self-efficacy) within the context of the HEXACO model - a more comprehensive personality framework than the conventional Big Five structure. A total of 666 MZ and 526 DZ adult twin pairs from the United Kingdom completed the short form of the Trait Emotional Intelligence Questionnaire (TEIQue-SF) and the short form of the HEXACO Personality Inventory (HEXACO-60). Many significant phenotypic correlations between the TEIQue-SF and the HEXACO-60 were obtained, which were strongest for HEXACO Extraversion, and weakest for HEXACO Honesty-Humility. As was expected, Emotionality was the only HEXACO dimension to correlate negatively with TEIQue-SF scores. Bivariate behavioral genetic analyses revealed that all phenotypic correlations were attributable to common genetic and common nonshared environmental factors. The study confirms the validity of trait EI as a constellation of emotional self-perceptions located at the lower levels of personality.

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.

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

Testing the lexical hypothesis: are socially important traits more densely reflected in the English lexicon?

PubMed

Wood, Dustin

2015-02-01

Using a set of 498 English words identified by Saucier (1997) as common person-descriptor adjectives or trait terms, I tested 3 instantiations of the lexical hypothesis, which posit that more socially important person descriptors show greater density in the lexicon. Specifically, I explored whether trait terms that have greater relational impact (i.e., more greatly influence how others respond to a person) have more synonyms, are more frequently used, and are more strongly correlated with other trait terms. I found little evidence to suggest that trait terms rated as having greater relational impact were more frequently used or had more synonyms. However, these terms correlated more strongly with other trait terms in the set. Conversely, a trait term's loadings on structural factors (e.g., the Big Five, HEXACO) were extremely good predictors of the term's relational impact. The findings suggest that the lexical hypothesis may not be strongly supported in some ways it is commonly understood but is supported in the manner most important to investigations of trait structure. Specifically, trait terms with greater relational impact tend to more strongly correlate with other terms in lexical sets and thus have a greater role in driving the location of factors in analyses of trait structure. Implications for understanding the meaning of lexical factors such as the Big Five are discussed. PsycINFO Database Record (c) 2015 APA, all rights reserved.

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.

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...

Systems genetics: a paradigm to improve discovery of candidate genes and mechanisms underlying complex traits.

PubMed

Feltus, F Alex

2014-06-01

Understanding the control of any trait optimally requires the detection of causal genes, gene interaction, and mechanism of action to discover and model the biochemical pathways underlying the expressed phenotype. Functional genomics techniques, including RNA expression profiling via microarray and high-throughput DNA sequencing, allow for the precise genome localization of biological information. Powerful genetic approaches, including quantitative trait locus (QTL) and genome-wide association study mapping, link phenotype with genome positions, yet genetics is less precise in localizing the relevant mechanistic information encoded in DNA. The coupling of salient functional genomic signals with genetically mapped positions is an appealing approach to discover meaningful gene-phenotype relationships. Techniques used to define this genetic-genomic convergence comprise the field of systems genetics. This short review will address an application of systems genetics where RNA profiles are associated with genetically mapped genome positions of individual genes (eQTL mapping) or as gene sets (co-expression network modules). Both approaches can be applied for knowledge independent selection of candidate genes (and possible control mechanisms) underlying complex traits where multiple, likely unlinked, genomic regions might control specific complex traits. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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.

Analysis of the Gli-D2 locus identifies a genetic target for simultaneously improving the breadmaking and health-related traits of common wheat.

PubMed

Li, Da; Jin, Huaibing; Zhang, Kunpu; Wang, Zhaojun; Wang, Faming; Zhao, Yue; Huo, Naxin; Liu, Xin; Gu, Yong Q; Wang, Daowen; Dong, Lingli

2018-05-11

Gliadins are a major component of wheat seed proteins. However, the complex homoeologous Gli-2 loci (Gli-A2, -B2 and -D2) that encode the α-gliadins in commercial wheat are still poorly understood. Here we analyzed the Gli-D2 locus of Xiaoyan 81 (Xy81), a winter wheat cultivar. A total of 421.091 kb of the Gli-D2 sequence was assembled from sequencing multiple bacterial artificial clones, and 10 α-gliadin genes were annotated. Comparative genomic analysis showed that Xy81 carried only eight of the α-gliadin genes of the D genome donor Aegilops tauschii, with two of them each experiencing a tandem duplication. A mutant line lacking Gli-D2 (DLGliD2) consistently exhibited better breadmaking quality and dough functionalities than its progenitor Xy81, but without penalties in other agronomic traits. It also had an elevated lysine content in the grains. Transcriptome analysis verified the lack of Gli-D2 α-gliadin gene expression in DLGliD2. Furthermore, the transcript and protein levels of protein disulfide isomerase were both upregulated in DLGliD2 grains. Consistent with this finding, DLGliD2 had increased disulfide content in the flour. Our work sheds light on the structure and function of Gli-D2 in commercial wheat, and suggests that the removal of Gli-D2 and the gliadins specified by it is likely to be useful for simultaneously enhancing the end-use and health-related traits of common wheat. Because gliadins and homologous proteins are widely present in grass species, the strategy and information reported here may be broadly useful for improving the quality traits of diverse cereal crops. © 2018 The Authors The Plant Journal © 2018 John Wiley & Sons Ltd.

Genetic parameters for linear type traits and milk, fat, and protein production in holstein cows in Brazil.

PubMed

Campos, Rafael Viegas; Cobuci, Jaime Araujo; Kern, Elisandra Lurdes; Costa, Cláudio Napolis; McManus, Concepta Margaret

2015-04-01

The objective of this study was to estimate genetic and phenotypic parameters for linear type traits, as well as milk yield (MY), fat yield (FY) and protein yield (PY) in 18,831 Holstein cows reared in 495 herds in Brazil. Restricted maximum likelihood with a bivariate model was used for estimation genetic parameters, including fixed effects of herd-year of classification, period of classification, classifier and stage of lactation for linear type traits and herd-year of calving, season of calving and lactation order effects for production traits. The age of cow at calving was fitted as a covariate (with linear and quadratic terms), common to both models. Heritability estimates varied from 0.09 to 0.38 for linear type traits and from 0.17 to 0.24 for production traits, indicating sufficient genetic variability to achieve genetic gain through selection. In general, estimates of genetic correlations between type and production traits were low, except for udder texture and angularity that showed positive genetic correlations (>0.29) with MY, FY, and PY. Udder depth had the highest negative genetic correlation (-0.30) with production traits. Selection for final score, commonly used by farmers as a practical selection tool to improve type traits, does not lead to significant improvements in production traits, thus the use of selection indices that consider both sets of traits (production and type) seems to be the most adequate to carry out genetic selection of animals in the Brazilian herd.

Genetic Parameters for Linear Type Traits and Milk, Fat, and Protein Production in Holstein Cows in Brazil

PubMed Central

Campos, Rafael Viegas; Cobuci, Jaime Araujo; Kern, Elisandra Lurdes; Costa, Cláudio Napolis; McManus, Concepta Margaret

2015-01-01

The objective of this study was to estimate genetic and phenotypic parameters for linear type traits, as well as milk yield (MY), fat yield (FY) and protein yield (PY) in 18,831 Holstein cows reared in 495 herds in Brazil. Restricted maximum likelihood with a bivariate model was used for estimation genetic parameters, including fixed effects of herd-year of classification, period of classification, classifier and stage of lactation for linear type traits and herd-year of calving, season of calving and lactation order effects for production traits. The age of cow at calving was fitted as a covariate (with linear and quadratic terms), common to both models. Heritability estimates varied from 0.09 to 0.38 for linear type traits and from 0.17 to 0.24 for production traits, indicating sufficient genetic variability to achieve genetic gain through selection. In general, estimates of genetic correlations between type and production traits were low, except for udder texture and angularity that showed positive genetic correlations (>0.29) with MY, FY, and PY. Udder depth had the highest negative genetic correlation (−0.30) with production traits. Selection for final score, commonly used by farmers as a practical selection tool to improve type traits, does not lead to significant improvements in production traits, thus the use of selection indices that consider both sets of traits (production and type) seems to be the most adequate to carry out genetic selection of animals in the Brazilian herd. PMID:25656190

Exploring the Robustness of a Unidimensional Item Response Theory Model with Empirically Multidimensional Data

ERIC Educational Resources Information Center

Anderson, Daniel; Kahn, Joshua D.; Tindal, Gerald

2017-01-01

Unidimensionality and local independence are two common assumptions of item response theory. The former implies that all items measure a common latent trait, while the latter implies that responses are independent, conditional on respondents' location on the latent trait. Yet, few tests are truly unidimensional. Unmodeled dimensions may result in…

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.

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

PubMed Central

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

2014-01-01

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

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

Choosing and using diversity indices: insights for ecological applications from the German Biodiversity Exploratories.

PubMed

Morris, E Kathryn; Caruso, Tancredi; Buscot, François; Fischer, Markus; Hancock, Christine; Maier, Tanja S; Meiners, Torsten; Müller, Caroline; Obermaier, Elisabeth; Prati, Daniel; Socher, Stephanie A; Sonnemann, Ilja; Wäschke, Nicole; Wubet, Tesfaye; Wurst, Susanne; Rillig, Matthias C

2014-09-01

Biodiversity, a multidimensional property of natural systems, is difficult to quantify partly because of the multitude of indices proposed for this purpose. Indices aim to describe general properties of communities that allow us to compare different regions, taxa, and trophic levels. Therefore, they are of fundamental importance for environmental monitoring and conservation, although there is no consensus about which indices are more appropriate and informative. We tested several common diversity indices in a range of simple to complex statistical analyses in order to determine whether some were better suited for certain analyses than others. We used data collected around the focal plant Plantago lanceolata on 60 temperate grassland plots embedded in an agricultural landscape to explore relationships between the common diversity indices of species richness (S), Shannon's diversity (H'), Simpson's diversity (D1), Simpson's dominance (D2), Simpson's evenness (E), and Berger-Parker dominance (BP). We calculated each of these indices for herbaceous plants, arbuscular mycorrhizal fungi, aboveground arthropods, belowground insect larvae, and P. lanceolata molecular and chemical diversity. Including these trait-based measures of diversity allowed us to test whether or not they behaved similarly to the better studied species diversity. We used path analysis to determine whether compound indices detected more relationships between diversities of different organisms and traits than more basic indices. In the path models, more paths were significant when using H', even though all models except that with E were equally reliable. This demonstrates that while common diversity indices may appear interchangeable in simple analyses, when considering complex interactions, the choice of index can profoundly alter the interpretation of results. Data mining in order to identify the index producing the most significant results should be avoided, but simultaneously considering analyses using multiple indices can provide greater insight into the interactions in a system.

Choosing and using diversity indices: insights for ecological applications from the German Biodiversity Exploratories

PubMed Central

Morris, E Kathryn; Caruso, Tancredi; Buscot, François; Fischer, Markus; Hancock, Christine; Maier, Tanja S; Meiners, Torsten; Müller, Caroline; Obermaier, Elisabeth; Prati, Daniel; Socher, Stephanie A; Sonnemann, Ilja; Wäschke, Nicole; Wubet, Tesfaye; Wurst, Susanne; Rillig, Matthias C

2014-01-01

Biodiversity, a multidimensional property of natural systems, is difficult to quantify partly because of the multitude of indices proposed for this purpose. Indices aim to describe general properties of communities that allow us to compare different regions, taxa, and trophic levels. Therefore, they are of fundamental importance for environmental monitoring and conservation, although there is no consensus about which indices are more appropriate and informative. We tested several common diversity indices in a range of simple to complex statistical analyses in order to determine whether some were better suited for certain analyses than others. We used data collected around the focal plant Plantago lanceolata on 60 temperate grassland plots embedded in an agricultural landscape to explore relationships between the common diversity indices of species richness (S), Shannon’s diversity (H’), Simpson’s diversity (D1), Simpson’s dominance (D2), Simpson’s evenness (E), and Berger–Parker dominance (BP). We calculated each of these indices for herbaceous plants, arbuscular mycorrhizal fungi, aboveground arthropods, belowground insect larvae, and P. lanceolata molecular and chemical diversity. Including these trait-based measures of diversity allowed us to test whether or not they behaved similarly to the better studied species diversity. We used path analysis to determine whether compound indices detected more relationships between diversities of different organisms and traits than more basic indices. In the path models, more paths were significant when using H’, even though all models except that with E were equally reliable. This demonstrates that while common diversity indices may appear interchangeable in simple analyses, when considering complex interactions, the choice of index can profoundly alter the interpretation of results. Data mining in order to identify the index producing the most significant results should be avoided, but simultaneously considering analyses using multiple indices can provide greater insight into the interactions in a system. PMID:25478144

Quantifying full phenological event distributions reveals simultaneous advances, temporal stability and delays in spring and autumn migration timing in long-distance migratory birds.

PubMed

Miles, Will T S; Bolton, Mark; Davis, Peter; Dennis, Roy; Broad, Roger; Robertson, Iain; Riddiford, Nick J; Harvey, Paul V; Riddington, Roger; Shaw, Deryk N; Parnaby, David; Reid, Jane M

2017-04-01

Phenological changes in key seasonally expressed life-history traits occurring across periods of climatic and environmental change can cause temporal mismatches between interacting species, and thereby impact population and community dynamics. However, studies quantifying long-term phenological changes have commonly only measured variation occurring in spring, measured as the first or mean dates on which focal traits or events were observed. Few studies have considered seasonally paired events spanning spring and autumn or tested the key assumption that single convenient metrics accurately capture entire event distributions. We used 60 years (1955-2014) of daily bird migration census data from Fair Isle, Scotland, to comprehensively quantify the degree to which the full distributions of spring and autumn migration timing of 13 species of long-distance migratory bird changed across a period of substantial climatic and environmental change. In most species, mean spring and autumn migration dates changed little. However, the early migration phase (≤10th percentile date) commonly got earlier, while the late migration phase (≥90th percentile date) commonly got later. Consequently, species' total migration durations typically lengthened across years. Spring and autumn migration phenologies were not consistently correlated within or between years within species and hence were not tightly coupled. Furthermore, different metrics quantifying different aspects of migration phenology within seasons were not strongly cross-correlated, meaning that no single metric adequately described the full pattern of phenological change. These analyses therefore reveal complex patterns of simultaneous advancement, temporal stability and delay in spring and autumn migration phenologies, altering species' life-history structures. Additionally, they demonstrate that this complexity is only revealed if multiple metrics encompassing entire seasonal event distributions, rather than single metrics, are used to quantify phenological change. Existing evidence of long-term phenological changes detected using only one or two metrics should consequently be interpreted cautiously because divergent changes occurring simultaneously could potentially have remained undetected. © 2016 John Wiley & Sons Ltd.

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.

The Quantitative-MFG Test: A Linear Mixed Effect Model to Detect Maternal-Offspring Gene Interactions.

PubMed

Clark, Michelle M; Blangero, John; Dyer, Thomas D; Sobel, Eric M; Sinsheimer, Janet S

2016-01-01

Maternal-offspring gene interactions, aka maternal-fetal genotype (MFG) incompatibilities, are neglected in complex diseases and quantitative trait studies. They are implicated in birth to adult onset diseases but there are limited ways to investigate their influence on quantitative traits. We present the quantitative-MFG (QMFG) test, a linear mixed model where maternal and offspring genotypes are fixed effects and residual correlations between family members are random effects. The QMFG handles families of any size, common or general scenarios of MFG incompatibility, and additional covariates. We develop likelihood ratio tests (LRTs) and rapid score tests and show they provide correct inference. In addition, the LRT's alternative model provides unbiased parameter estimates. We show that testing the association of SNPs by fitting a standard model, which only considers the offspring genotypes, has very low power or can lead to incorrect conclusions. We also show that offspring genetic effects are missed if the MFG modeling assumptions are too restrictive. With genome-wide association study data from the San Antonio Family Heart Study, we demonstrate that the QMFG score test is an effective and rapid screening tool. The QMFG test therefore has important potential to identify pathways of complex diseases for which the genetic etiology remains to be discovered. © 2015 John Wiley & Sons Ltd/University College London.

XPAT: a toolkit to conduct cross-platform association studies with heterogeneous sequencing datasets.

PubMed

Yu, Yao; Hu, Hao; Bohlender, Ryan J; Hu, Fulan; Chen, Jiun-Sheng; Holt, Carson; Fowler, Jerry; Guthery, Stephen L; Scheet, Paul; Hildebrandt, Michelle A T; Yandell, Mark; Huff, Chad D

2018-04-06

High-throughput sequencing data are increasingly being made available to the research community for secondary analyses, providing new opportunities for large-scale association studies. However, heterogeneity in target capture and sequencing technologies often introduce strong technological stratification biases that overwhelm subtle signals of association in studies of complex traits. Here, we introduce the Cross-Platform Association Toolkit, XPAT, which provides a suite of tools designed to support and conduct large-scale association studies with heterogeneous sequencing datasets. XPAT includes tools to support cross-platform aware variant calling, quality control filtering, gene-based association testing and rare variant effect size estimation. To evaluate the performance of XPAT, we conducted case-control association studies for three diseases, including 783 breast cancer cases, 272 ovarian cancer cases, 205 Crohn disease cases and 3507 shared controls (including 1722 females) using sequencing data from multiple sources. XPAT greatly reduced Type I error inflation in the case-control analyses, while replicating many previously identified disease-gene associations. We also show that association tests conducted with XPAT using cross-platform data have comparable performance to tests using matched platform data. XPAT enables new association studies that combine existing sequencing datasets to identify genetic loci associated with common diseases and other complex traits.

Non-equilibrium dynamics and floral trait interactions shape extant angiosperm diversity

PubMed Central

O'Meara, Brian C.; Smith, Stacey D.; Armbruster, W. Scott; Harder, Lawrence D.; Hardy, Christopher R.; Hileman, Lena C.; Hufford, Larry; Litt, Amy; Magallón, Susana; Smith, Stephen A.; Stevens, Peter F.; Fenster, Charles B.; Diggle, Pamela K.

2016-01-01

Why are some traits and trait combinations exceptionally common across the tree of life, whereas others are vanishingly rare? The distribution of trait diversity across a clade at any time depends on the ancestral state of the clade, the rate at which new phenotypes evolve, the differences in speciation and extinction rates across lineages, and whether an equilibrium has been reached. Here we examine the role of transition rates, differential diversification (speciation minus extinction) and non-equilibrium dynamics on the evolutionary history of angiosperms, a clade well known for the abundance of some trait combinations and the rarity of others. Our analysis reveals that three character states (corolla present, bilateral symmetry, reduced stamen number) act synergistically as a key innovation, doubling diversification rates for lineages in which this combination occurs. However, this combination is currently less common than predicted at equilibrium because the individual characters evolve infrequently. Simulations suggest that angiosperms will remain far from the equilibrium frequencies of character states well into the future. Such non-equilibrium dynamics may be common when major innovations evolve rarely, allowing lineages with ancestral forms to persist, and even outnumber those with diversification-enhancing states, for tens of millions of years. PMID:27147092

A metastructural model of mental disorders and pathological personality traits.

PubMed

Wright, A G C; Simms, L J

2015-08-01

Psychiatric co-morbidity is extensive in both psychiatric settings and the general population. Such co-morbidity challenges whether DSM-based mental disorders serve to effectively carve nature at its joints. In response, a substantial literature has emerged showing that a small number of broad dimensions - internalizing, externalizing and psychoticism - can account for much of the observed covariation among common mental disorders. However, the location of personality disorders within this emerging metastructure has only recently been studied, and no studies have yet examined where pathological personality traits fit within such a broad metastructural framework. We conducted joint structural analyses of common mental disorders, personality disorders and pathological personality traits in a sample of 628 current or recent psychiatric out-patients. Bridging across the psychopathology and personality trait literatures, the results provide evidence for a robust five-factor metastructure of psychopathology, including broad domains of symptoms and features related to internalizing, disinhibition, psychoticism, antagonism and detachment. These results reveal evidence for a psychopathology metastructure that (a) parsimoniously accounts for much of the observed covariation among common mental disorders, personality disorders and related personality traits, and (b) provides an empirical basis for the organization and classification of mental disorder.

Non-equilibrium dynamics and floral trait interactions shape extant angiosperm diversity.

PubMed

O'Meara, Brian C; Smith, Stacey D; Armbruster, W Scott; Harder, Lawrence D; Hardy, Christopher R; Hileman, Lena C; Hufford, Larry; Litt, Amy; Magallón, Susana; Smith, Stephen A; Stevens, Peter F; Fenster, Charles B; Diggle, Pamela K

2016-05-11

Why are some traits and trait combinations exceptionally common across the tree of life, whereas others are vanishingly rare? The distribution of trait diversity across a clade at any time depends on the ancestral state of the clade, the rate at which new phenotypes evolve, the differences in speciation and extinction rates across lineages, and whether an equilibrium has been reached. Here we examine the role of transition rates, differential diversification (speciation minus extinction) and non-equilibrium dynamics on the evolutionary history of angiosperms, a clade well known for the abundance of some trait combinations and the rarity of others. Our analysis reveals that three character states (corolla present, bilateral symmetry, reduced stamen number) act synergistically as a key innovation, doubling diversification rates for lineages in which this combination occurs. However, this combination is currently less common than predicted at equilibrium because the individual characters evolve infrequently. Simulations suggest that angiosperms will remain far from the equilibrium frequencies of character states well into the future. Such non-equilibrium dynamics may be common when major innovations evolve rarely, allowing lineages with ancestral forms to persist, and even outnumber those with diversification-enhancing states, for tens of millions of years. © 2016 The Author(s).

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

PubMed

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

2017-02-01

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

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.

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

[Progress in genetic research of human height].

PubMed

Chen, Kaixu; Wang, Weilan; Zhang, Fuchun; Zheng, Xiufen

2015-08-01

It is well known that both environmental and genetic factors contribute to adult height variation in general population. However, heritability studies have shown that the variation in height is more affected by genetic factors. Height is a typical polygenic trait which has been studied by traditional linkage analysis and association analysis to identify common DNA sequence variation associated with height, but progress has been slow. More recently, with the development of genotyping and DNA sequencing technologies, tremendous achievements have been made in genetic research of human height. Hundreds of single nucleotide polymorphisms (SNPs) associated with human height have been identified and validated with the application of genome-wide association studies (GWAS) methodology, which deepens our understanding of the genetics of human growth and development and also provides theoretic basis and reference for studying other complex human traits. In this review, we summarize recent progress in genetic research of human height and discuss problems and prospects in this research area which may provide some insights into future genetic studies of human height.

Personality disorder across the life course.

PubMed

Newton-Howes, Giles; Clark, Lee Anna; Chanen, Andrew

2015-02-21

The pervasive effect of personality disorder is often overlooked in clinical practice, both as an important moderator of mental state and physical disorders, and as a disorder that should be recognised and managed in its own right. Contemporary research has shown that maladaptive personality (when personality traits are extreme and associated with clinical distress or psychosocial impairment) is common, can be recognised early in life, evolves continuously across the lifespan, and is more plastic than previously believed. These new insights offer opportunities to intervene to support more adaptive development than before, and research shows that such intervention can be effective. Further research is needed to improve classification, assessment, and diagnosis of personality disorder across the lifespan; to understand the complex interplay between changes in personality traits and clinical presentation over time; and to promote more effective intervention at the earliest possible stage of the disorder than is done at present. Recognition of how personality disorder relates to age and developmental stage can improve care of all patients. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

Eating traits questionnaires as a continuum of a single concept. Uncontrolled eating.

PubMed

Vainik, Uku; Neseliler, Selin; Konstabel, Kenn; Fellows, Lesley K; Dagher, Alain

2015-07-01

Research on eating behaviour has identified several potentially relevant eating-related traits captured by different questionnaires. Often, these questionnaires predict Body Mass Index (BMI), but the relationship between them has not been explicitly studied. We studied the unity and diversity of questionnaires capturing five common eating-related traits: Power of Food, Eating Impulsivity, emotional eating, Disinhibition, and binge eating in women from Estonia (n = 740) and Canada (n = 456). Using bifactor analysis, we showed that a) these questionnaires are largely explained by a single factor, and b) relative to this shared factor, only some questionnaires offered additional variance in predicting BMI. Hence, these questionnaires seemed to characterise a common factor, which we label Uncontrolled Eating. Item Response Theory techniques were then applied to demonstrate that c) within this common factor, the questionnaires could be placed on a continuum of Uncontrolled Eating. That is, Eating Impulsivity focused on the milder degree, Power of Food Scale, emotional eating scales, and Disinhibition on intermediate degrees, and the Binge Eating Scale on the most severe degrees of Uncontrolled Eating. In sum, evidence from two samples showed that questionnaires capturing five common BMI-related traits largely reflected the same underlying latent trait - Uncontrolled Eating. In Estonia, some questionnaires focused on different severities of this common construct, supporting a continuum model of Uncontrolled Eating. These findings provide a starting point for developing better questionnaires of the neurobehavioural correlates of obesity, and provide a unifying perspective from which to view the existing literature. R scripts and data used for the analysis are provided. Copyright © 2015 Elsevier Ltd. All rights reserved.

Are Autistic Traits Measured Equivalently in Individuals with and without an Autism Spectrum Disorder? An Invariance Analysis of the Autism Spectrum Quotient Short Form

ERIC Educational Resources Information Center

Murray, Aja L.; Booth, Tom; McKenzie, Karen; Kuenssberg, Renate; O'Donnell, Michael

2014-01-01

It is common to administer measures of autistic traits to those without autism spectrum disorders (ASDs) with, for example, the aim of understanding autistic personality characteristics in non-autistic individuals. Little research has examined the extent to which measures of autistic traits actually measure the same traits in the same way across…

Do pioneers have r-selected traits? Life history patterns among colonizing terrestrial gastropods.

PubMed

Bengtsson, J; Baur, B

1993-05-01

We examine whether pioneer species of terrestrial gastropods (snails and slugs) possess particular life history traits commonly associated with r-selection, using data on gastropod colonization in four areas in north-west Europe (the Kvarken and Tvärminne archipelagos in the Baltic, polder woods in IJsselmeer, and a rehabilitated quarry near Maastricht). Data on age at first reproduction, longevity, clutch size, egg size and lifetime fecundity were gathered from the literature. In order to control for potentially confounding effects of body size on life history traits, we compared the residuals from the allometric relations between life history traits and body size for pioneers and non-pioneers. In snails, all life history traits examined were related to body size. In slugs, all traits except age at first reproduction scaled with body size. Body sizes did not differ between pioneers and non-pioneers in any area. In all four areas, there were no significant differences between pioneers and non-pioneers in any of the life history traits examined, after body size had been taken into account. This indicates that pioneer terrestrial gastropods generally cannot be regarded as r-selected. Pioneer species may possess any of several life history strategies, and the combinations of traits shown by them may have little in common with the r-K selection concept.

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.

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.

Efficient QTL detection for nonhost resistance in wild lettuce: backcross inbred lines versus F2 population

PubMed Central

Pelgrom, K.; Stam, P.; Lindhout, P.

2008-01-01

In plants, several population types [F2, recombinant inbred lines, backcross inbred lines (BILs), etc.] are used for quantitative trait locus (QTL) analyses. However, dissection of the trait of interest and subsequent confirmation by introgression of QTLs for breeding purposes has not been as successful as that predicted from theoretical calculations. More practical knowledge of different QTL mapping approaches is needed. In this recent study, we describe the detection and mapping of quantitative resistances to downy mildew in a set of 29 BILs of cultivated lettuce (L. sativa) containing genome segments introgressed from wild lettuce (L. saligna). Introgression regions that are associated with quantitative resistance are considered to harbor a QTL. Furthermore, we compare this with results from an already existing F2 population derived from the same parents. We identified six QTLs in our BIL approach compared to only three in the F2 approach, while there were two QTLs in common. We performed a simulation study based on our actual data to help us interpret them. This revealed that two newly detected QTLs in the BILs had gone unnoticed in the F2, due to a combination of recessiveness of the trait and skewed segregation, causing a deficit of the wild species alleles. This study clearly illustrates the added value of extended genetic studies on two different population types (BILs and F2) to dissect complex genetic traits. PMID:18251002

Fluctuating asymmetry in broiler chickens: a decision protocol for trait selection in seven measuring methods.

PubMed

Van Nuffel, A; Tuyttens, F A M; Van Dongen, S; Talloen, W; Van Poucke, E; Sonck, B; Lens, L

2007-12-01

Nonidentical development of bilateral traits due to disturbing genetic or developmental factors is called fluctuating asymmetry (FA) if such deviations are continuously distributed. Fluctuating asymmetry is believed to be a reliable indicator of the fitness and welfare of an animal. Despite an increasing body of research, the link between FA and animal performance or welfare is reported to be inconsistent, possibly, among other reasons, due to inaccurate measuring protocols or incorrect statistical analyses. This paper reviews problems of interpreting FA results in poultry and provides guidelines for the measurement and analysis of FA, applied to broilers. A wide range of morphological traits were measured by 7 different techniques (ranging from measurements on living broilers or intact carcasses to X-rays, bones, and digital images) and evaluated for their applicability to estimate FA. Following 4 selection criteria (significant FA, absence of directional asymmetry or antisymmetry, absence of between-trait correlation in signed FA values, and high signal-to-noise ratio), from 3 to 14 measurements per method were found suitable for estimating the degree of FA. The accuracy of FA estimates was positively related to the complexity and time investment of the measuring method. In addition, our study clearly shows the importance of securing adequate statistical power when designing FA studies. Repeatability analyses of FA estimates indicated the need for larger sample sizes, more repeated measurements, or both, than are commonly used in FA studies.

Phenotypic evaluation and genome wide association studies of two common bean (Phaseolus vulgaris) diversity panels in multiple locations highlight evaluation techniques, traits and lines useful for trait based selection

USDA-ARS?s Scientific Manuscript database

Common bean (Phaseolus vulgaris) productivity is constrained by abiotic soil conductions including drought and low fertility as well as by high temperature. High temperature primarily impacts pollen viability and growth. Soil water content and nutrients occur heterogeneously and often in a stratif...

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.

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

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.

Intraspecific variation in stomatal traits, leaf traits and physiology reflects adaptation along aridity gradients in a South African shrub.

PubMed

Carlson, Jane E; Adams, Christopher A; Holsinger, Kent E

2016-01-01

Trait-environment relationships are commonly interpreted as evidence for local adaptation in plants. However, even when selection analyses support this interpretation, the mechanisms underlying differential benefits are often unknown. This study addresses this gap in knowledge using the broadly distributed South African shrub Protea repens. Specifically, the study examines whether broad-scale patterns of trait variation are consistent with spatial differences in selection and ecophysiology in the wild. In a common garden study of plants sourced from 19 populations, associations were measured between five morphological traits and three axes describing source climates. Trait-trait and trait-environment associations were analysed in a multi-response model. Within two focal populations in the wild, selection and path analyses were used to test associations between traits, fecundity and physiological performance. Across 19 populations in a common garden, stomatal density increased with the source population's mean annual temperature and decreased with its average amount of rainfall in midsummer. Concordantly, selection analysis in two natural populations revealed positive selection on stomatal density at the hotter, drier site, while failing to detect selection at the cooler, moister site. Dry-site plants with high stomatal density also had higher stomatal conductances, cooler leaf temperatures and higher light-saturated photosynthetic rates than those with low stomatal density, but no such relationships were present among wet-site plants. Leaf area, stomatal pore index and specific leaf area in the garden also co-varied with climate, but within-population differences were not associated with fitness in either wild population. The parallel patterns of broad-scale variation, differences in selection and differences in trait-ecophysiology relationships suggest a mechanism for adaptive differentiation in stomatal density. Densely packed stomata may improve performance by increasing transpiration and cooling, but predominately in drier, hotter climates. This study uniquely shows context-dependent benefits of stomatal density--a trait rarely linked to local adaptation in plants. © The Author 2015. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Multi-breed and multi-trait co-association analysis of meat tenderness and other meat quality traits in three French beef cattle breeds.

PubMed

Ramayo-Caldas, Yuliaxis; Renand, Gilles; Ballester, Maria; Saintilan, Romain; Rocha, Dominique

2016-04-23

Studies to identify markers associated with beef tenderness have focused on Warner-Bratzler shear force (WBSF) but the interplay between the genes associated with WBSF has not been explored. We used the association weight matrix (AWM), a systems biology approach, to identify a set of interacting genes that are co-associated with tenderness and other meat quality traits, and shared across the Charolaise, Limousine and Blonde d'Aquitaine beef cattle breeds. Genome-wide association studies were performed using ~500K single nucleotide polymorphisms (SNPs) and 17 phenotypes measured on more than 1000 animals for each breed. First, this multi-trait approach was applied separately for each breed across 17 phenotypes and second, between- and across-breed comparisons at the AWM and functional levels were performed. Genetic heterogeneity was observed, and most of the variants that were associated with WBSF segregated within rather than across breeds. We identified 206 common candidate genes associated with WBSF across the three breeds. SNPs in these common genes explained between 28 and 30 % of the phenotypic variance for WBSF. A reduced number of common SNPs mapping to the 206 common genes were identified, suggesting that different mutations may target the same genes in a breed-specific manner. Therefore, it is likely that, depending on allele frequencies and linkage disequilibrium patterns, a SNP that is identified for one breed may not be informative for another unrelated breed. Well-known candidate genes affecting beef tenderness were identified. In addition, some of the 206 common genes are located within previously reported quantitative trait loci for WBSF in several cattle breeds. Moreover, the multi-breed co-association analysis detected new candidate genes, regulators and metabolic pathways that are likely involved in the determination of meat tenderness and other meat quality traits in beef cattle. Our results suggest that systems biology approaches that explore associations of correlated traits increase statistical power to identify candidate genes beyond the one-dimensional approach. Further studies on the 206 common genes, their pathways, regulators and interactions will expand our knowledge on the molecular basis of meat tenderness and could lead to the discovery of functional mutations useful for genomic selection in a multi-breed beef cattle context.

Transformation of Summary Statistics from Linear Mixed Model Association on All-or-None Traits to Odds Ratio.

PubMed

Lloyd-Jones, Luke R; Robinson, Matthew R; Yang, Jian; Visscher, Peter M

2018-04-01

Genome-wide association studies (GWAS) have identified thousands of loci that are robustly associated with complex diseases. The use of linear mixed model (LMM) methodology for GWAS is becoming more prevalent due to its ability to control for population structure and cryptic relatedness and to increase power. The odds ratio (OR) is a common measure of the association of a disease with an exposure ( e.g. , a genetic variant) and is readably available from logistic regression. However, when the LMM is applied to all-or-none traits it provides estimates of genetic effects on the observed 0-1 scale, a different scale to that in logistic regression. This limits the comparability of results across studies, for example in a meta-analysis, and makes the interpretation of the magnitude of an effect from an LMM GWAS difficult. In this study, we derived transformations from the genetic effects estimated under the LMM to the OR that only rely on summary statistics. To test the proposed transformations, we used real genotypes from two large, publicly available data sets to simulate all-or-none phenotypes for a set of scenarios that differ in underlying model, disease prevalence, and heritability. Furthermore, we applied these transformations to GWAS summary statistics for type 2 diabetes generated from 108,042 individuals in the UK Biobank. In both simulation and real-data application, we observed very high concordance between the transformed OR from the LMM and either the simulated truth or estimates from logistic regression. The transformations derived and validated in this study improve the comparability of results from prospective and already performed LMM GWAS on complex diseases by providing a reliable transformation to a common comparative scale for the genetic effects. Copyright © 2018 by the Genetics Society of America.

Quantitative trait loci affecting response to crowding stress in an F2 generation of rainbow trout produced through phenotypic selection

USDA-ARS?s Scientific Manuscript database

Selective breeding programs for salmonids typically aim to improve traits associated with growth and disease resistance. It has been established that stressors common to production environments can adversely affect these and other traits which are important to producers and consumers. Previously,...

Hard traits of three Bromus species in their source area explain their current invasive success

NASA Astrophysics Data System (ADS)

Fenesi, Annamária; Rédei, Tamás; Botta-Dukát, Zoltán

2011-09-01

We address two highly essential question using three Eurasian Bromus species with different invasion success in North America as model organisms: (1) why some species become invasive and others do not, and (2) which traits can confer pre-adaptation for species to become invasive elsewhere. While the morphology and phenology of the chosen bromes ( Bromus tectorum, Bromus sterilis and Bromus squarrosus) are highly similar, we measured complex traits often associated with invasive success: phenotypic plasticity, competitive ability and generalist-specialist character. We performed common-garden experiments, community- and landscape-level surveys in areas of co-occurrence in Central Europe (Hungary) that could have served as donor region for American introductions. According to our results, the three bromes are unequally equipped with trait that could enhance invasiveness. B. tectorum possesses several traits that may be especially relevant: it has uniquely high phenotypic plasticity, as demonstrated in a nitrogen addition experiment, and it is a habitat generalist, thriving in a wide range of habitats, from semi-natural to degraded ones, and having the widest co-occurrence based niche-breadth. The strength of B. sterilis lies in its ability to use resources unexploited by other species. It can become dominant, but only in one non-natural habitat type, namely the understorey of the highly allelopathic stands of the invasive Robinia pseudoacacia. B. squarrosus is a habitat specialist with low competitive ability, always occurring with low coverage. This ranking of the species' abilities can explain the current spreading success of the three bromes on the North American continent, and highlight the high potential of prehistoric invaders (European archaeophytes) to become invasive elsewhere.

Polygenicity and Epistasis Underlie Fitness-Proximal Traits in the Caenorhabditis elegans Multiparental Experimental Evolution (CeMEE) Panel.

PubMed

Noble, Luke M; Chelo, Ivo; Guzella, Thiago; Afonso, Bruno; Riccardi, David D; Ammerman, Patrick; Dayarian, Adel; Carvalho, Sara; Crist, Anna; Pino-Querido, Ania; Shraiman, Boris; Rockman, Matthew V; Teotónio, Henrique

2017-12-01

Understanding the genetic basis of complex traits remains a major challenge in biology. Polygenicity, phenotypic plasticity, and epistasis contribute to phenotypic variance in ways that are rarely clear. This uncertainty can be problematic for estimating heritability, for predicting individual phenotypes from genomic data, and for parameterizing models of phenotypic evolution. Here, we report an advanced recombinant inbred line (RIL) quantitative trait locus mapping panel for the hermaphroditic nematode Caenorhabditis elegans , the C. elegans multiparental experimental evolution (CeMEE) panel. The CeMEE panel, comprising 507 RILs at present, was created by hybridization of 16 wild isolates, experimental evolution for 140-190 generations, and inbreeding by selfing for 13-16 generations. The panel contains 22% of single-nucleotide polymorphisms known to segregate in natural populations, and complements existing C. elegans mapping resources by providing fine resolution and high nucleotide diversity across > 95% of the genome. We apply it to study the genetic basis of two fitness components, fertility and hermaphrodite body size at time of reproduction, with high broad-sense heritability in the CeMEE. While simulations show that we should detect common alleles with additive effects as small as 5%, at gene-level resolution, the genetic architectures of these traits do not feature such alleles. We instead find that a significant fraction of trait variance, approaching 40% for fertility, can be explained by sign epistasis with main effects below the detection limit. In congruence, phenotype prediction from genomic similarity, while generally poor ([Formula: see text]), requires modeling epistasis for optimal accuracy, with most variance attributed to the rapidly evolving chromosome arms. Copyright © 2017 by the Genetics Society of America.

Polygenicity and Epistasis Underlie Fitness-Proximal Traits in the Caenorhabditis elegans Multiparental Experimental Evolution (CeMEE) Panel

PubMed Central

Noble, Luke M.; Chelo, Ivo; Guzella, Thiago; Afonso, Bruno; Riccardi, David D.; Ammerman, Patrick; Dayarian, Adel; Carvalho, Sara; Crist, Anna; Pino-Querido, Ania; Shraiman, Boris; Rockman, Matthew V.; Teotónio, Henrique

2017-01-01

Understanding the genetic basis of complex traits remains a major challenge in biology. Polygenicity, phenotypic plasticity, and epistasis contribute to phenotypic variance in ways that are rarely clear. This uncertainty can be problematic for estimating heritability, for predicting individual phenotypes from genomic data, and for parameterizing models of phenotypic evolution. Here, we report an advanced recombinant inbred line (RIL) quantitative trait locus mapping panel for the hermaphroditic nematode Caenorhabditis elegans, the C. elegans multiparental experimental evolution (CeMEE) panel. The CeMEE panel, comprising 507 RILs at present, was created by hybridization of 16 wild isolates, experimental evolution for 140–190 generations, and inbreeding by selfing for 13–16 generations. The panel contains 22% of single-nucleotide polymorphisms known to segregate in natural populations, and complements existing C. elegans mapping resources by providing fine resolution and high nucleotide diversity across > 95% of the genome. We apply it to study the genetic basis of two fitness components, fertility and hermaphrodite body size at time of reproduction, with high broad-sense heritability in the CeMEE. While simulations show that we should detect common alleles with additive effects as small as 5%, at gene-level resolution, the genetic architectures of these traits do not feature such alleles. We instead find that a significant fraction of trait variance, approaching 40% for fertility, can be explained by sign epistasis with main effects below the detection limit. In congruence, phenotype prediction from genomic similarity, while generally poor (r2<10%), requires modeling epistasis for optimal accuracy, with most variance attributed to the rapidly evolving chromosome arms. PMID:29066469

Personality disorders as maladaptive, extreme variants of normal personality: borderline personality disorder and neuroticism in a substance using sample.

PubMed

Samuel, Douglas B; Carroll, Kathleen M; Rounsaville, Bruce J; Ball, Samuel A

2013-10-01

Although the current diagnostic manual conceptualizes personality disorders (PDs) as categorical entities, an alternative perspective is that PDs represent maladaptive extreme versions of the same traits that describe normal personality. Existing evidence indicates that normal personality traits, such as those assessed by the five-factor model (FFM), share a common structure and obtain reasonably predictable correlations with the PDs. However, very little research has investigated whether PDs are more extreme than normal personality traits. Utilizing item-response theory analyses, the authors of the current study extend previous research to demonstrate that the diagnostic criterion for borderline personality disorder and FFM neuroticism could be fit along a single latent dimension. Furthermore, the authors' findings indicate that the borderline criteria assessed the shared latent trait at a level that was more extreme (d = 1.11) than FFM neuroticism. This finding provides further evidence for dimensional understanding of personality pathology and suggests that a trait model in DSM-5 should span normal and abnormal personality functioning, but focus on the extremes of these common traits.

Common and distinct modulation of electrophysiological indices of feedback processing by autistic and psychopathic traits.

PubMed

Carter Leno, Virginia; Naples, Adam; Cox, Anthony; Rutherford, Helena; McPartland, James C

2016-01-01

Both autism spectrum disorder (ASD) and psychopathy are primarily characterized by social dysfunction; overlapping phenotypic features may reflect altered function in common brain mechanisms. The current study examined the degree to which neural response to social and nonsocial feedback is modulated by autistic versus psychopathic traits in a sample of typically developing adults (N = 31, 11 males, 18-52 years). Event-related potentials were recorded whilst participants completed a behavioral task and received feedback on task performance. Both autistic and psychopathic traits were associated with alterations in the neural correlates of feedback processing. Sensitivity to specific forms of feedback (social, nonsocial, positively valenced, negatively valenced) differed between the two traits. Autistic traits were associated with decreased sensitivity to social feedback. In contrast, the antisocial domain of psychopathic traits was associated with an overall decrease in sensitivity to feedback, and the interpersonal manipulation domain was associated with preserved processing of positively valenced feedback. Results suggest distinct alterations within specific mechanisms of feedback processing may underlie similar difficulties in social behavior.

To what extent is altitudinal variation of functional traits driven by genetic adaptation in European oak and beech?

PubMed

Bresson, Caroline C; Vitasse, Yann; Kremer, Antoine; Delzon, Sylvain

2011-11-01

The phenotypic responses of functional traits in natural populations are driven by genetic diversity and phenotypic plasticity. These two mechanisms enable trees to cope with rapid climate change. We studied two European temperate tree species (sessile oak and European beech), focusing on (i) in situ variations of leaf functional traits (morphological and physiological) along two altitudinal gradients and (ii) the extent to which these variations were under environmental and/or genetic control using a common garden experiment. For all traits, altitudinal trends tended to be highly consistent between species and transects. For both species, leaf mass per area displayed a positive linear correlation with altitude, whereas leaf size was negatively correlated with altitude. We also observed a significant increase in leaf physiological performance with increasing altitude: populations at high altitudes had higher maximum rates of assimilation, stomatal conductance and leaf nitrogen content than those at low altitudes. In the common garden experiment, genetic differentiation between populations accounted for 0-28% of total phenotypic variation. However, only two traits (leaf mass per area and nitrogen content) exhibited a significant cline. The combination of in situ and common garden experiments used here made it possible to demonstrate, for both species, a weaker effect of genetic variation than of variations in natural conditions, suggesting a strong effect of the environment on leaf functional traits. Finally, we demonstrated that intrapopulation variability was systematically higher than interpopulation variability, whatever the functional trait considered, indicating a high potential capacity to adapt to climate change.

The role of experiments in understanding fishery-induced evolution

PubMed Central

Conover, David O; Baumann, Hannes

2009-01-01

Evidence of fishery-induced evolution has been accumulating rapidly from various avenues of investigation. Here we review the knowledge gained from experimental approaches. The strength of experiments is in their ability to disentangle genetic from environmental differences. Common garden experiments have provided direct evidence of adaptive divergence in the wild and therefore the evolvability of various traits that influence production in numerous species. Most of these cases involve countergradient variation in physiological, life history, and behavioral traits. Selection experiments have provided examples of rapid life history evolution and, more importantly, that fishery-induced selection pressures cause simultaneous divergence of not one but a cluster of genetically and phenotypically correlated traits that include physiology, behavior, reproduction, and other life history characters. The drawbacks of experiments are uncertainties in the scale-up from small, simple environments to larger and more complex systems; the concern that taxons with short life cycles used for experimental research are atypical of those of harvested species; and the difficulty of adequately simulating selection due to fishing. Despite these limitations, experiments have contributed greatly to our understanding of fishery-induced evolution on both empirical and theoretical levels. Future advances will depend on integrating knowledge from experiments with those from modeling, field studies, and molecular genetic approaches. PMID:25567880

Dissociable patterns of brain activity for mentalizing about known others: a role for attachment

PubMed Central

Laurita, Anne C.; Hazan, Cindy

2017-01-01

Abstract The human brain tracks dynamic changes within the social environment, forming and updating representations of individuals in our social milieu. This mechanism of social navigation builds an increasingly complex map of persons with whom we are familiar and form attachments to guide adaptive social behaviors. We examined the neural representation of known others along a continuum of attachment using fMRI. Heterosexual adults (N = 29, 16 females), in romantic relationships for more than 2 years, made trait judgments for a romantic partner, parent, close friend, familiar acquaintance and self-during scanning. Multivariate analysis, partial least squares, was used to identify whole-brain patterns of brain activation associated with trait judgments of known others across a continuum of attachment. Across conditions, trait judgments engaged the default network and lateral prefrontal cortex. Judgments about oneself and a partner were associated with a common activation pattern encompassing anterior and middle cingulate, posterior superior temporal sulcus, as well as anterior insula. Parent and close friend judgments engaged medial and anterior temporal lobe regions. These results provide novel evidence that mentalizing about known familiar others results in differential brain activity. We provide initial evidence that the representation of adult attachment is a distinguishing feature of these differences. PMID:28407150

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

PubMed

Blackett, Piers R; Sanghera, Dharambir K

2013-01-01

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

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

PubMed Central

Blackett, Piers R; Sanghera, Dharambir K

2012-01-01

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

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.

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.

A novel iterative mixed model to remap three complex orthopedic traits in dogs

PubMed Central

Huang, Meng; Hayward, Jessica J.; Corey, Elizabeth; Garrison, Susan J.; Wagner, Gabriela R.; Krotscheck, Ursula; Hayashi, Kei; Schweitzer, Peter A.; Lust, George; Boyko, Adam R.; Todhunter, Rory J.

2017-01-01

Hip dysplasia (HD), elbow dysplasia (ED), and rupture of the cranial (anterior) cruciate ligament (RCCL) are the most common complex orthopedic traits of dogs and all result in debilitating osteoarthritis. We reanalyzed previously reported data: the Norberg angle (a quantitative measure of HD) in 921 dogs, ED in 113 cases and 633 controls, and RCCL in 271 cases and 399 controls and their genotypes at ~185,000 single nucleotide polymorphisms. A novel fixed and random model with a circulating probability unification (FarmCPU) function, with marker-based principal components and a kinship matrix to correct for population stratification, was used. A Bonferroni correction at p<0.01 resulted in a P< 6.96 ×10−8. Six loci were identified; three for HD and three for RCCL. An associated locus at CFA28:34,369,342 for HD was described previously in the same dogs using a conventional mixed model. No loci were identified for RCCL in the previous report but the two loci for ED in the previous report did not reach genome-wide significance using the FarmCPU model. These results were supported by simulation which demonstrated that the FarmCPU held no power advantage over the linear mixed model for the ED sample but provided additional power for the HD and RCCL samples. Candidate genes for HD and RCCL are discussed. When using FarmCPU software, we recommend a resampling test, that a positive control be used to determine the optimum pseudo quantitative trait nucleotide-based covariate structure of the model, and a negative control be used consisting of permutation testing and the identical resampling test as for the non-permuted phenotypes. PMID:28614352

Carbonatite magmatism in northeast India

NASA Astrophysics Data System (ADS)

Kumar, D.; Mamallan, R.; Dwivedy, K. K.

The Shillong Plateau of northeast India is identified as an alkaline province in view of the development of several carbonatite complexes e.g. the Sung Valley (Jaintia Hills), Jasra (Karbi-Anglong), Samchampi and Barpung (Mikir Hills) and lamprophyre dyke swarms (Swangkre, Garo-Khasi Hills). On the basis of limited KAr data, magmatic activity appears to have taken place over a protracted period, ranging from the Late Jurassic to the Early Cretaceous. The carbonatite complexes of the Shillong Plateau share several common traits: they are emplaced along rift zones, either within Archaean gneisses or Proterozoic metasediments and granites, and exhibit enrichment in the light rare-earth elements, U, Th, Nb, Zr, Ti, K and Na. The enrichment in incompatible trace elements can best be accounted for if the parental magmas were of alkali basaltic type (e.g. mela-nephelinite or carbonate-rich alkali picrite).

Life history determines genetic structure and evolutionary potential of host–parasite interactions

PubMed Central

Barrett, Luke G.; Thrall, Peter H.; Burdon, Jeremy J.; Linde, Celeste C.

2009-01-01

Measures of population genetic structure and diversity of disease-causing organisms are commonly used to draw inferences regarding their evolutionary history and potential to generate new variation in traits that determine interactions with their hosts. Parasite species exhibit a range of population structures and life-history strategies, including different transmission modes, life-cycle complexity, off-host survival mechanisms and dispersal ability. These are important determinants of the frequency and predictability of interactions with host species. Yet the complex causal relationships between spatial structure, life history and the evolutionary dynamics of parasite populations are not well understood. We demonstrate that a clear picture of the evolutionary potential of parasitic organisms and their demographic and evolutionary histories can only come from understanding the role of life history and spatial structure in influencing population dynamics and epidemiological patterns. PMID:18947899

Life history determines genetic structure and evolutionary potential of host-parasite interactions.

PubMed

Barrett, Luke G; Thrall, Peter H; Burdon, Jeremy J; Linde, Celeste C

2008-12-01

Measures of population genetic structure and diversity of disease-causing organisms are commonly used to draw inferences regarding their evolutionary history and potential to generate new variation in traits that determine interactions with their hosts. Parasite species exhibit a range of population structures and life-history strategies, including different transmission modes, life-cycle complexity, off-host survival mechanisms and dispersal ability. These are important determinants of the frequency and predictability of interactions with host species. Yet the complex causal relationships between spatial structure, life history and the evolutionary dynamics of parasite populations are not well understood. We demonstrate that a clear picture of the evolutionary potential of parasitic organisms and their demographic and evolutionary histories can only come from understanding the role of life history and spatial structure in influencing population dynamics and epidemiological patterns.

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.

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

Hormones and the Evolution of Complex Traits: Insights from Artificial Selection on Behavior

PubMed Central

Garland, Theodore; Zhao, Meng; Saltzman, Wendy

2016-01-01

Although behavior may often be a fairly direct target of natural or sexual selection, it cannot evolve without changes in subordinate traits that cause or permit its expression. In principle, changes in endocrine function could be a common mechanism underlying behavioral evolution because they are well positioned to mediate integrated responses to behavioral selection. More specifically, hormones can influence both motivational (e.g., brain) and performance (e.g., muscles) components of behavior simultaneously and in a coordinated fashion. If the endocrine system is often “used” as a general mechanism to effect responses to selection, then correlated responses in other aspects of behavior, life history, and organismal performance (e.g., locomotor abilities) should commonly occur because any cell with appropriate receptors could be affected. Ways in which behavior coadapts with other aspects of the phenotype can be studied directly through artificial selection and experimental evolution. Several studies have targeted rodent behavior for selective breeding and reported changes in other aspects of behavior, life history, and lower-level effectors of these organismal traits, including endocrine function. One example involves selection for high levels of voluntary wheel running, one aspect of physical activity, in four replicate High Runner (HR) lines of mice. Circulating levels of several hormones (including insulin, testosterone, thyroxine, triiodothyronine) have been characterized, three of which—corticosterone, leptin, and adiponectin—differ between HR and control lines, depending on sex, age, and generation. Potential changes in circulating levels of other behaviorally and metabolically relevant hormones, as well as in other components of the endocrine system (e.g., receptors), have yet to be examined. Overall, results to date identify promising avenues for further studies on the endocrine basis of activity levels. PMID:27252193

Using extreme phenotype sampling to identify the rare causal variants of quantitative traits in association studies.

PubMed

Li, Dalin; Lewinger, Juan Pablo; Gauderman, William J; Murcray, Cassandra Elizabeth; Conti, David

2011-12-01

Variants identified in recent genome-wide association studies based on the common-disease common-variant hypothesis are far from fully explaining the hereditability of complex traits. Rare variants may, in part, explain some of the missing hereditability. Here, we explored the advantage of the extreme phenotype sampling in rare-variant analysis and refined this design framework for future large-scale association studies on quantitative traits. We first proposed a power calculation approach for a likelihood-based analysis method. We then used this approach to demonstrate the potential advantages of extreme phenotype sampling for rare variants. Next, we discussed how this design can influence future sequencing-based association studies from a cost-efficiency (with the phenotyping cost included) perspective. Moreover, we discussed the potential of a two-stage design with the extreme sample as the first stage and the remaining nonextreme subjects as the second stage. We demonstrated that this two-stage design is a cost-efficient alternative to the one-stage cross-sectional design or traditional two-stage design. We then discussed the analysis strategies for this extreme two-stage design and proposed a corresponding design optimization procedure. To address many practical concerns, for example measurement error or phenotypic heterogeneity at the very extremes, we examined an approach in which individuals with very extreme phenotypes are discarded. We demonstrated that even with a substantial proportion of these extreme individuals discarded, an extreme-based sampling can still be more efficient. Finally, we expanded the current analysis and design framework to accommodate the CMC approach where multiple rare-variants in the same gene region are analyzed jointly. © 2011 Wiley Periodicals, Inc.

Using Extreme Phenotype Sampling to Identify the Rare Causal Variants of Quantitative Traits in Association Studies

PubMed Central

Li, Dalin; Lewinger, Juan Pablo; Gauderman, William J.; Murcray, Cassandra Elizabeth; Conti, David

2014-01-01

Variants identified in recent genome-wide association studies based on the common-disease common-variant hypothesis are far from fully explaining the hereditability of complex traits. Rare variants may, in part, explain some of the missing hereditability. Here, we explored the advantage of the extreme phenotype sampling in rare-variant analysis and refined this design framework for future large-scale association studies on quantitative traits. We first proposed a power calculation approach for a likelihood-based analysis method. We then used this approach to demonstrate the potential advantages of extreme phenotype sampling for rare variants. Next, we discussed how this design can influence future sequencing-based association studies from a cost-efficiency (with the phenotyping cost included) perspective. Moreover, we discussed the potential of a two-stage design with the extreme sample as the first stage and the remaining nonextreme subjects as the second stage. We demonstrated that this two-stage design is a cost-efficient alternative to the one-stage cross-sectional design or traditional two-stage design. We then discussed the analysis strategies for this extreme two-stage design and proposed a corresponding design optimization procedure. To address many practical concerns, for example measurement error or phenotypic heterogeneity at the very extremes, we examined an approach in which individuals with very extreme phenotypes are discarded. We demonstrated that even with a substantial proportion of these extreme individuals discarded, an extreme-based sampling can still be more efficient. Finally, we expanded the current analysis and design framework to accommodate the CMC approach where multiple rare-variants in the same gene region are analyzed jointly. PMID:21922541

Idiosyncratic responses to climate-driven forest fragmentation and marine incursions in reed frogs from Central Africa and the Gulf of Guinea Islands.

PubMed

Bell, Rayna C; Parra, Juan L; Badjedjea, Gabriel; Barej, Michael F; Blackburn, David C; Burger, Marius; Channing, Alan; Dehling, Jonas Maximilian; Greenbaum, Eli; Gvoždík, Václav; Kielgast, Jos; Kusamba, Chifundera; Lötters, Stefan; McLaughlin, Patrick J; Nagy, Zoltán T; Rödel, Mark-Oliver; Portik, Daniel M; Stuart, Bryan L; VanDerWal, Jeremy; Zassi-Boulou, Ange Ghislain; Zamudio, Kelly R

2017-10-01

Organismal traits interact with environmental variation to mediate how species respond to shared landscapes. Thus, differences in traits related to dispersal ability or physiological tolerance may result in phylogeographic discordance among co-distributed taxa, even when they are responding to common barriers. We quantified climatic suitability and stability, and phylogeographic divergence within three reed frog species complexes across the Guineo-Congolian forests and Gulf of Guinea archipelago of Central Africa to investigate how they responded to a shared climatic and geological history. Our species-specific estimates of climatic suitability through time are consistent with temporal and spatial heterogeneity in diversification among the species complexes, indicating that differences in ecological breadth may partly explain these idiosyncratic patterns. Likewise, we demonstrated that fluctuating sea levels periodically exposed a land bridge connecting Bioko Island with the mainland Guineo-Congolian forest and that habitats across the exposed land bridge likely enabled dispersal in some species, but not in others. We did not find evidence that rivers are biogeographic barriers across any of the species complexes. Despite marked differences in the geographic extent of stable climates and temporal estimates of divergence among the species complexes, we recovered a shared pattern of intermittent climatic suitability with recent population connectivity and demographic expansion across the Congo Basin. This pattern supports the hypothesis that genetic exchange across the Congo Basin during humid periods, followed by vicariance during arid periods, has shaped regional diversity. Finally, we identified many distinct lineages among our focal taxa, some of which may reflect incipient or unrecognized species. © 2017 John Wiley & Sons Ltd.

Walking and talking the tree of life: Why and how to teach about biodiversity.

PubMed

Ballen, Cissy J; Greene, Harry W

2017-03-01

Taxonomic details of diversity are an essential scaffolding for biology education, yet outdated methods for teaching the tree of life (TOL), as implied by textbook content and usage, are still commonly employed. Here, we show that the traditional approach only vaguely represents evolutionary relationships, fails to denote major events in the history of life, and relies heavily on memorizing near-meaningless taxonomic ranks. Conversely, a clade-based strategy-focused on common ancestry, monophyletic groups, and derived functional traits-is explicitly based on Darwin's "descent with modification," provides students with a rational system for organizing the details of biodiversity, and readily lends itself to active learning techniques. We advocate for a phylogenetic classification that mirrors the TOL, a pedagogical format of increasingly complex but always hierarchical presentations, and the adoption of active learning technologies and tactics.

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.

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.

Comparative morphological analysis of two parallel mycoheterotrophic transitions reveals divergent and convergent traits in the genus Pyrola (Pyroleae, Ericaceae).

PubMed

Shutoh, Kohtaroh; Suetsugu, Kenji; Kaneko, Shingo; Kurosawa, Takahide

2018-05-15

The genus Pyrola includes species with different degree of mycoheterotrophy; some species possess individuals that rely on all carbon through their associations with fungi (full mycoheterotrophy, FM), whereas some species obtain carbon through both fungi and photosynthesis by itself (partial mycoheterotrophy, PM). To investigate how plant functional traits of photosynthesis and reproduction are related to the degree of mycoheterotrophy in the initial stage of the transition from PM to FM, we determined morphological traits in FM (or nearly FM) and PM species in two independent lineages, P. picta and P. japonica complexes. We used herbarium specimens and examined leaf number, leaf area, flower number, and scape length in FM or nearly FM species (P. aphylla and P. subaphylla) and PM species (P. picta s.l. and P. japonica). We found a leaf area reduction in FM (or nearly FM) species in both lineages, suggesting that this is a convergent trait. The number of flowers was not significantly different between FM (or nearly FM) and PM species in both lineages. On the other hand, differences in the variation between FM (or nearly FM) and PM species were found in some traits between the two lineages. The FM (or nearly FM) species in one lineage only possessed rudimentary leaves, whereas that in the other linage possessed a few small, ordinary leaves in addition to those with only rudimentary leaves. The scape length of the FM (or nearly FM) species was significantly longer than that of PM species in one lineage, whereas it was shorter in the other lineage. The different and common variations are divergent and convergent traits, respectively, that could be associated with the transition to FM in Pylora. In addition, shoots of both PM species occasionally lacked ordinary leaves, possibly indicating possession of these shoots is preadaptation for the transition to FM in Pyrola.

Marker-based linkage map of Andean common bean (Phaseolus vulgaris L.) and mapping of QTLs underlying popping ability traits

PubMed Central

2012-01-01

Background Nuña bean is a type of ancient common bean (Phaseolus vulgaris L.) native to the Andean region of South America, whose seeds possess the unusual property of popping. The nutritional features of popped seeds make them a healthy low fat and high protein snack. However, flowering of nuña bean only takes place under short-day photoperiod conditions, which means a difficulty to extend production to areas where such conditions do not prevail. Therefore, breeding programs of adaptation traits will facilitate the diversification of the bean crops and the development of new varieties with enhanced healthy properties. Although the popping trait has been profusely studied in maize (popcorn), little is known about the biology and genetic basis of the popping ability in common bean. To obtain insights into the genetics of popping ability related traits of nuña bean, a comprehensive quantitative trait loci (QTL) analysis was performed to detect single-locus and epistatic QTLs responsible for the phenotypic variance observed in these traits. Results A mapping population of 185 recombinant inbred lines (RILs) derived from a cross between two Andean common bean genotypes was evaluated for three popping related traits, popping dimension index (PDI), expansion coefficient (EC), and percentage of unpopped seeds (PUS), in five different environmental conditions. The genetic map constructed included 193 loci across 12 linkage groups (LGs), covering a genetic distance of 822.1 cM, with an average of 4.3 cM per marker. Individual and multi-environment QTL analyses detected a total of nineteen single-locus QTLs, highlighting among them the co-localized QTLs for the three popping ability traits placed on LGs 3, 5, 6, and 7, which together explained 24.9, 14.5, and 25.3% of the phenotypic variance for PDI, EC, and PUS, respectively. Interestingly, epistatic interactions among QTLs have been detected, which could have a key role in the genetic control of popping. Conclusions The QTLs here reported constitute useful tools for marker assisted selection breeding programs aimed at improving nuña bean cultivars, as well as for extending our knowledge of the genetic determinants and genotype x environment interaction involved in the popping ability traits of this bean crop. PMID:22873566

Generalized functional linear models for gene-based case-control association studies.

PubMed

Fan, Ruzong; Wang, Yifan; Mills, James L; Carter, Tonia C; Lobach, Iryna; Wilson, Alexander F; Bailey-Wilson, Joan E; Weeks, Daniel E; Xiong, Momiao

2014-11-01

By using functional data analysis techniques, we developed generalized functional linear models for testing association between a dichotomous trait and multiple genetic variants in a genetic region while adjusting for covariates. Both fixed and mixed effect models are developed and compared. Extensive simulations show that Rao's efficient score tests of the fixed effect models are very conservative since they generate lower type I errors than nominal levels, and global tests of the mixed effect models generate accurate type I errors. Furthermore, we found that the Rao's efficient score test statistics of the fixed effect models have higher power than the sequence kernel association test (SKAT) and its optimal unified version (SKAT-O) in most cases when the causal variants are both rare and common. When the causal variants are all rare (i.e., minor allele frequencies less than 0.03), the Rao's efficient score test statistics and the global tests have similar or slightly lower power than SKAT and SKAT-O. In practice, it is not known whether rare variants or common variants in a gene region are disease related. All we can assume is that a combination of rare and common variants influences disease susceptibility. Thus, the improved performance of our models when the causal variants are both rare and common shows that the proposed models can be very useful in dissecting complex traits. We compare the performance of our methods with SKAT and SKAT-O on real neural tube defects and Hirschsprung's disease datasets. The Rao's efficient score test statistics and the global tests are more sensitive than SKAT and SKAT-O in the real data analysis. Our methods can be used in either gene-disease genome-wide/exome-wide association studies or candidate gene analyses. © 2014 WILEY PERIODICALS, INC.

Generalized Functional Linear Models for Gene-based Case-Control Association Studies

PubMed Central

Mills, James L.; Carter, Tonia C.; Lobach, Iryna; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Weeks, Daniel E.; Xiong, Momiao

2014-01-01

By using functional data analysis techniques, we developed generalized functional linear models for testing association between a dichotomous trait and multiple genetic variants in a genetic region while adjusting for covariates. Both fixed and mixed effect models are developed and compared. Extensive simulations show that Rao's efficient score tests of the fixed effect models are very conservative since they generate lower type I errors than nominal levels, and global tests of the mixed effect models generate accurate type I errors. Furthermore, we found that the Rao's efficient score test statistics of the fixed effect models have higher power than the sequence kernel association test (SKAT) and its optimal unified version (SKAT-O) in most cases when the causal variants are both rare and common. When the causal variants are all rare (i.e., minor allele frequencies less than 0.03), the Rao's efficient score test statistics and the global tests have similar or slightly lower power than SKAT and SKAT-O. In practice, it is not known whether rare variants or common variants in a gene are disease-related. All we can assume is that a combination of rare and common variants influences disease susceptibility. Thus, the improved performance of our models when the causal variants are both rare and common shows that the proposed models can be very useful in dissecting complex traits. We compare the performance of our methods with SKAT and SKAT-O on real neural tube defects and Hirschsprung's disease data sets. The Rao's efficient score test statistics and the global tests are more sensitive than SKAT and SKAT-O in the real data analysis. Our methods can be used in either gene-disease genome-wide/exome-wide association studies or candidate gene analyses. PMID:25203683

Mining the LIPG Allelic Spectrum Reveals the Contribution of Rare and Common Regulatory Variants to HDL Cholesterol

PubMed Central

Raghavan, Avanthi; Neeli, Hemanth; Jin, Weijun; Badellino, Karen O.; Demissie, Serkalem; Manning, Alisa K.; DerOhannessian, Stephanie L.; Wolfe, Megan L.; Cupples, L. Adrienne; Li, Mingyao; Kathiresan, Sekar; Rader, Daniel J.

2011-01-01

Genome-wide association studies (GWAS) have successfully identified loci associated with quantitative traits, such as blood lipids. Deep resequencing studies are being utilized to catalogue the allelic spectrum at GWAS loci. The goal of these studies is to identify causative variants and missing heritability, including heritability due to low frequency and rare alleles with large phenotypic impact. Whereas rare variant efforts have primarily focused on nonsynonymous coding variants, we hypothesized that noncoding variants in these loci are also functionally important. Using the HDL-C gene LIPG as an example, we explored the effect of regulatory variants identified through resequencing of subjects at HDL-C extremes on gene expression, protein levels, and phenotype. Resequencing a portion of the LIPG promoter and 5′ UTR in human subjects with extreme HDL-C, we identified several rare variants in individuals from both extremes. Luciferase reporter assays were used to measure the effect of these rare variants on LIPG expression. Variants conferring opposing effects on gene expression were enriched in opposite extremes of the phenotypic distribution. Minor alleles of a common regulatory haplotype and noncoding GWAS SNPs were associated with reduced plasma levels of the LIPG gene product endothelial lipase (EL), consistent with its role in HDL-C catabolism. Additionally, we found that a common nonfunctional coding variant associated with HDL-C (rs2000813) is in linkage disequilibrium with a 5′ UTR variant (rs34474737) that decreases LIPG promoter activity. We attribute the gene regulatory role of rs34474737 to the observed association of the coding variant with plasma EL levels and HDL-C. Taken together, the findings show that both rare and common noncoding regulatory variants are important contributors to the allelic spectrum in complex trait loci. PMID:22174694

Positive Character Traits of Special Education Staff: Commonalities and Applications

ERIC Educational Resources Information Center

Korn, Maggie A.; Woodard, Cooper R.; Tucker, Chelsea A.

2016-01-01

The goal of the present study was to identify the positive character traits of staff working with a special education population and further understand how staff apply these traits in their work. Twenty-eight staff from a school/treatment program for students with autism and related developmental disorders completed the VIA Inventory of Strengths…

Higher Order Testlet Response Models for Hierarchical Latent Traits and Testlet-Based Items

ERIC Educational Resources Information Center

Huang, Hung-Yu; Wang, Wen-Chung

2013-01-01

Both testlet design and hierarchical latent traits are fairly common in educational and psychological measurements. This study aimed to develop a new class of higher order testlet response models that consider both local item dependence within testlets and a hierarchy of latent traits. Due to high dimensionality, the authors adopted the Bayesian…

Quantitative trait loci mapping for Gibberella ear rot resistance and associated agronomic traits using genotyping-by-sequencing in maize.

PubMed

Kebede, Aida Z; Woldemariam, Tsegaye; Reid, Lana M; Harris, Linda J

2016-01-01

Unique and co-localized chromosomal regions affecting Gibberella ear rot disease resistance and correlated agronomic traits were identified in maize. Dissecting the mechanisms underlying resistance to Gibberella ear rot (GER) disease in maize provides insight towards more informed breeding. To this goal, we evaluated 410 recombinant inbred lines (RIL) for GER resistance over three testing years using silk channel and kernel inoculation techniques. RILs were also evaluated for agronomic traits like days to silking, husk cover, and kernel drydown rate. The RILs showed significant genotypic differences for all traits with above average to high heritability estimates. Significant (P < 0.01) but weak genotypic correlations were observed between disease severity and agronomic traits, indicating the involvement of agronomic traits in disease resistance. Common QTLs were detected for GER resistance and kernel drydown rate, suggesting the existence of pleiotropic genes that could be exploited to improve both traits at the same time. The QTLs identified for silk and kernel resistance shared some common regions on chromosomes 1, 2, and 8 and also had some regions specific to each tissue on chromosomes 9 and 10. Thus, effective GER resistance breeding could be achieved by considering screening methods that allow exploitation of tissue-specific disease resistance mechanisms and include kernel drydown rate either in an index or as indirect selection criterion.

Gene flow does not prevent personality and morphological differentiation between two blue tit populations.

PubMed

Dubuc-Messier, Gabrielle; Caro, Samuel P; Perrier, Charles; van Oers, Kees; Réale, Denis; Charmantier, Anne

2018-05-23

Understanding the causes and consequences of population phenotypic divergence is a central goal in ecology and evolution. Phenotypic divergence among populations can result from genetic divergence, phenotypic plasticity or a combination of the two. However, few studies have deciphered these mechanisms for populations geographically close and connected by gene flow, especially in the case of personality traits. In this study, we used a common garden experiment to explore the genetic basis of the phenotypic divergence observed between two blue tit (Cyanistes caeruleus) populations inhabiting contrasting habitats separated by 25 km, for two personality traits (exploration speed and handling aggression), one physiological trait (heart rate during restraint) and two morphological traits (tarsus length and body mass). Blue tit nestlings were removed from their population and raised in a common garden for up to five years. We then compared adult phenotypes between the two populations, as well as trait-specific Q st and F st . Our results revealed differences between populations similar to those found in the wild, suggesting a genetic divergence for all traits. Q st - F st comparisons revealed that the traits divergences likely result from dissimilar selection patterns rather than from genetic drift. Our study is one of the first to report a Q st - F st comparison for personality traits and adds to the growing body of evidence that population genetic divergence is possible at a small scale for a variety of traits including behavioural traits. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

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.

Large-scale genomic analyses link reproductive aging to hypothalamic signaling, breast cancer susceptibility and BRCA1-mediated DNA repair.

PubMed

Day, Felix R; Ruth, Katherine S; Thompson, Deborah J; Lunetta, Kathryn L; Pervjakova, Natalia; Chasman, Daniel I; Stolk, Lisette; Finucane, Hilary K; Sulem, Patrick; Bulik-Sullivan, Brendan; Esko, Tõnu; Johnson, Andrew D; Elks, Cathy E; Franceschini, Nora; He, Chunyan; Altmaier, Elisabeth; Brody, Jennifer A; Franke, Lude L; Huffman, Jennifer E; Keller, Margaux F; McArdle, Patrick F; Nutile, Teresa; Porcu, Eleonora; Robino, Antonietta; Rose, Lynda M; Schick, Ursula M; Smith, Jennifer A; Teumer, Alexander; Traglia, Michela; Vuckovic, Dragana; Yao, Jie; Zhao, Wei; Albrecht, Eva; Amin, Najaf; Corre, Tanguy; Hottenga, Jouke-Jan; Mangino, Massimo; Smith, Albert V; Tanaka, Toshiko; Abecasis, Goncalo; Andrulis, Irene L; Anton-Culver, Hoda; Antoniou, Antonis C; Arndt, Volker; Arnold, Alice M; Barbieri, Caterina; Beckmann, Matthias W; Beeghly-Fadiel, Alicia; Benitez, Javier; Bernstein, Leslie; Bielinski, Suzette J; Blomqvist, Carl; Boerwinkle, Eric; Bogdanova, Natalia V; Bojesen, Stig E; Bolla, Manjeet K; Borresen-Dale, Anne-Lise; Boutin, Thibaud S; Brauch, Hiltrud; Brenner, Hermann; Brüning, Thomas; Burwinkel, Barbara; Campbell, Archie; Campbell, Harry; Chanock, Stephen J; Chapman, J Ross; Chen, Yii-Der Ida; Chenevix-Trench, Georgia; Couch, Fergus J; Coviello, Andrea D; Cox, Angela; Czene, Kamila; Darabi, Hatef; De Vivo, Immaculata; Demerath, Ellen W; Dennis, Joe; Devilee, Peter; Dörk, Thilo; Dos-Santos-Silva, Isabel; Dunning, Alison M; Eicher, John D; Fasching, Peter A; Faul, Jessica D; Figueroa, Jonine; Flesch-Janys, Dieter; Gandin, Ilaria; Garcia, Melissa E; García-Closas, Montserrat; Giles, Graham G; Girotto, Giorgia G; Goldberg, Mark S; González-Neira, Anna; Goodarzi, Mark O; Grove, Megan L; Gudbjartsson, Daniel F; Guénel, Pascal; Guo, Xiuqing; Haiman, Christopher A; Hall, Per; Hamann, Ute; Henderson, Brian E; Hocking, Lynne J; Hofman, Albert; Homuth, Georg; Hooning, Maartje J; Hopper, John L; Hu, Frank B; Huang, Jinyan; Humphreys, Keith; Hunter, David J; Jakubowska, Anna; Jones, Samuel E; Kabisch, Maria; Karasik, David; Knight, Julia A; Kolcic, Ivana; Kooperberg, Charles; Kosma, Veli-Matti; Kriebel, Jennifer; Kristensen, Vessela; Lambrechts, Diether; Langenberg, Claudia; Li, Jingmei; Li, Xin; Lindström, Sara; Liu, Yongmei; Luan, Jian'an; Lubinski, Jan; Mägi, Reedik; Mannermaa, Arto; Manz, Judith; Margolin, Sara; Marten, Jonathan; Martin, Nicholas G; Masciullo, Corrado; Meindl, Alfons; Michailidou, Kyriaki; Mihailov, Evelin; Milani, Lili; Milne, Roger L; Müller-Nurasyid, Martina; Nalls, Michael; Neale, Ben M; Nevanlinna, Heli; Neven, Patrick; Newman, Anne B; Nordestgaard, Børge G; Olson, Janet E; Padmanabhan, Sandosh; Peterlongo, Paolo; Peters, Ulrike; Petersmann, Astrid; Peto, Julian; Pharoah, Paul D P; Pirastu, Nicola N; Pirie, Ailith; Pistis, Giorgio; Polasek, Ozren; Porteous, David; Psaty, Bruce M; Pylkäs, Katri; Radice, Paolo; Raffel, Leslie J; Rivadeneira, Fernando; Rudan, Igor; Rudolph, Anja; Ruggiero, Daniela; Sala, Cinzia F; Sanna, Serena; Sawyer, Elinor J; Schlessinger, David; Schmidt, Marjanka K; Schmidt, Frank; Schmutzler, Rita K; Schoemaker, Minouk J; Scott, Robert A; Seynaeve, Caroline M; Simard, Jacques; Sorice, Rossella; Southey, Melissa C; Stöckl, Doris; Strauch, Konstantin; Swerdlow, Anthony; Taylor, Kent D; Thorsteinsdottir, Unnur; Toland, Amanda E; Tomlinson, Ian; Truong, Thérèse; Tryggvadottir, Laufey; Turner, Stephen T; Vozzi, Diego; Wang, Qin; Wellons, Melissa; Willemsen, Gonneke; Wilson, James F; Winqvist, Robert; Wolffenbuttel, Bruce B H R; Wright, Alan F; Yannoukakos, Drakoulis; Zemunik, Tatijana; Zheng, Wei; Zygmunt, Marek; Bergmann, Sven; Boomsma, Dorret I; Buring, Julie E; Ferrucci, Luigi; Montgomery, Grant W; Gudnason, Vilmundur; Spector, Tim D; van Duijn, Cornelia M; Alizadeh, Behrooz Z; Ciullo, Marina; Crisponi, Laura; Easton, Douglas F; Gasparini, Paolo P; Gieger, Christian; Harris, Tamara B; Hayward, Caroline; Kardia, Sharon L R; Kraft, Peter; McKnight, Barbara; Metspalu, Andres; Morrison, Alanna C; Reiner, Alex P; Ridker, Paul M; Rotter, Jerome I; Toniolo, Daniela; Uitterlinden, André G; Ulivi, Sheila; Völzke, Henry; Wareham, Nicholas J; Weir, David R; Yerges-Armstrong, Laura M; Price, Alkes L; Stefansson, Kari; Visser, Jenny A; Ong, Ken K; Chang-Claude, Jenny; Murabito, Joanne M; Perry, John R B; Murray, Anna

2015-11-01

Menopause timing has a substantial impact on infertility and risk of disease, including breast cancer, but the underlying mechanisms are poorly understood. We report a dual strategy in ∼70,000 women to identify common and low-frequency protein-coding variation associated with age at natural menopause (ANM). We identified 44 regions with common variants, including two regions harboring additional rare missense alleles of large effect. We found enrichment of signals in or near genes involved in delayed puberty, highlighting the first molecular links between the onset and end of reproductive lifespan. Pathway analyses identified major association with DNA damage response (DDR) genes, including the first common coding variant in BRCA1 associated with any complex trait. Mendelian randomization analyses supported a causal effect of later ANM on breast cancer risk (∼6% increase in risk per year; P = 3 × 10(-14)), likely mediated by prolonged sex hormone exposure rather than DDR mechanisms.

Large-scale genomic analyses link reproductive ageing to hypothalamic signaling, breast cancer susceptibility and BRCA1-mediated DNA repair

PubMed Central

Lunetta, Kathryn L.; Pervjakova, Natalia; Chasman, Daniel I.; Stolk, Lisette; Finucane, Hilary K.; Sulem, Patrick; Bulik-Sullivan, Brendan; Esko, Tõnu; Johnson, Andrew D.; Elks, Cathy E.; Franceschini, Nora; He, Chunyan; Altmaier, Elisabeth; Brody, Jennifer A.; Franke, Lude L.; Huffman, Jennifer E.; Keller, Margaux F.; McArdle, Patrick F.; Nutile, Teresa; Porcu, Eleonora; Robino, Antonietta; Rose, Lynda M.; Schick, Ursula M.; Smith, Jennifer A.; Teumer, Alexander; Traglia, Michela; Vuckovic, Dragana; Yao, Jie; Zhao, Wei; Albrecht, Eva; Amin, Najaf; Corre, Tanguy; Hottenga, Jouke-Jan; Mangino, Massimo; Smith, Albert V.; Tanaka, Toshiko; Abecasis, Goncalo; Andrulis, Irene L.; Anton-Culver, Hoda; Antoniou, Antonis C.; Arndt, Volker; Arnold, Alice M.; Barbieri, Caterina; Beckmann, Matthias W.; Beeghly-Fadiel, Alicia; Benitez, Javier; Bernstein, Leslie; Bielinski, Suzette J.; Blomqvist, Carl; Boerwinkle, Eric; Bogdanova, Natalia V.; Bojesen, Stig E.; Bolla, Manjeet K.; Borresen-Dale, Anne-Lise; Boutin, Thibaud S; Brauch, Hiltrud; Brenner, Hermann; Brüning, Thomas; Burwinkel, Barbara; Campbell, Archie; Campbell, Harry; Chanock, Stephen J.; Chapman, J. Ross; Chen, Yii-Der Ida; Chenevix-Trench, Georgia; Couch, Fergus J.; Coviello, Andrea D.; Cox, Angela; Czene, Kamila; Darabi, Hatef; De Vivo, Immaculata; Demerath, Ellen W.; Dennis, Joe; Devilee, Peter; Dörk, Thilo; dos-Santos-Silva, Isabel; Dunning, Alison M.; Eicher, John D.; Fasching, Peter A.; Faul, Jessica D.; Figueroa, Jonine; Flesch-Janys, Dieter; Gandin, Ilaria; Garcia, Melissa E.; García-Closas, Montserrat; Giles, Graham G.; Girotto, Giorgia G.; Goldberg, Mark S.; González-Neira, Anna; Goodarzi, Mark O.; Grove, Megan L.; Gudbjartsson, Daniel F.; Guénel, Pascal; Guo, Xiuqing; Haiman, Christopher A.; Hall, Per; Hamann, Ute; Henderson, Brian E.; Hocking, Lynne J.; Hofman, Albert; Homuth, Georg; Hooning, Maartje J.; Hopper, John L.; Hu, Frank B.; Huang, Jinyan; Humphreys, Keith; Hunter, David J.; Jakubowska, Anna; Jones, Samuel E.; Kabisch, Maria; Karasik, David; Knight, Julia A.; Kolcic, Ivana; Kooperberg, Charles; Kosma, Veli-Matti; Kriebel, Jennifer; Kristensen, Vessela; Lambrechts, Diether; Langenberg, Claudia; Li, Jingmei; Li, Xin; Lindström, Sara; Liu, Yongmei; Luan, Jian’an; Lubinski, Jan; Mägi, Reedik; Mannermaa, Arto; Manz, Judith; Margolin, Sara; Marten, Jonathan; Martin, Nicholas G.; Masciullo, Corrado; Meindl, Alfons; Michailidou, Kyriaki; Mihailov, Evelin; Milani, Lili; Milne, Roger L.; Müller-Nurasyid, Martina; Nalls, Michael; Neale, Ben M.; Nevanlinna, Heli; Neven, Patrick; Newman, Anne B.; Nordestgaard, Børge G.; Olson, Janet E.; Padmanabhan, Sandosh; Peterlongo, Paolo; Peters, Ulrike; Petersmann, Astrid; Peto, Julian; Pharoah, Paul D.P.; Pirastu, Nicola N.; Pirie, Ailith; Pistis, Giorgio; Polasek, Ozren; Porteous, David; Psaty, Bruce M.; Pylkäs, Katri; Radice, Paolo; Raffel, Leslie J.; Rivadeneira, Fernando; Rudan, Igor; Rudolph, Anja; Ruggiero, Daniela; Sala, Cinzia F.; Sanna, Serena; Sawyer, Elinor J.; Schlessinger, David; Schmidt, Marjanka K.; Schmidt, Frank; Schmutzler, Rita K.; Schoemaker, Minouk J.; Scott, Robert A.; Seynaeve, Caroline M.; Simard, Jacques; Sorice, Rossella; Southey, Melissa C.; Stöckl, Doris; Strauch, Konstantin; Swerdlow, Anthony; Taylor, Kent D.; Thorsteinsdottir, Unnur; Toland, Amanda E.; Tomlinson, Ian; Truong, Thérèse; Tryggvadottir, Laufey; Turner, Stephen T.; Vozzi, Diego; Wang, Qin; Wellons, Melissa; Willemsen, Gonneke; Wilson, James F.; Winqvist, Robert; Wolffenbuttel, Bruce B.H.R.; Wright, Alan F.; Yannoukakos, Drakoulis; Zemunik, Tatijana; Zheng, Wei; Zygmunt, Marek; Bergmann, Sven; Boomsma, Dorret I.; Buring, Julie E.; Ferrucci, Luigi; Montgomery, Grant W.; Gudnason, Vilmundur; Spector, Tim D.; van Duijn, Cornelia M; Alizadeh, Behrooz Z.; Ciullo, Marina; Crisponi, Laura; Easton, Douglas F.; Gasparini, Paolo P.; Gieger, Christian; Harris, Tamara B.; Hayward, Caroline; Kardia, Sharon L.R.; Kraft, Peter; McKnight, Barbara; Metspalu, Andres; Morrison, Alanna C.; Reiner, Alex P.; Ridker, Paul M.; Rotter, Jerome I.; Toniolo, Daniela; Uitterlinden, André G.; Ulivi, Sheila; Völzke, Henry; Wareham, Nicholas J.; Weir, David R.; Yerges-Armstrong, Laura M.; Price, Alkes L.; Stefansson, Kari; Visser, Jenny A.; Ong, Ken K.; Chang-Claude, Jenny; Murabito, Joanne M.; Perry, John R.B.; Murray, Anna

2015-01-01

Menopause timing has a substantial impact on infertility and risk of disease, including breast cancer, but the underlying mechanisms are poorly understood. We report a dual strategy in ~70,000 women to identify common and low-frequency protein-coding variation associated with age at natural menopause (ANM). We identified 44 regions with common variants, including two harbouring additional rare missense alleles of large effect. We found enrichment of signals in/near genes involved in delayed puberty, highlighting the first molecular links between the onset and end of reproductive lifespan. Pathway analyses revealed a major association with DNA damage-response (DDR) genes, including the first common coding variant in BRCA1 associated with any complex trait. Mendelian randomisation analyses supported a causal effect of later ANM on breast cancer risk (~6% risk increase per-year, P=3×10−14), likely mediated by prolonged sex hormone exposure, rather than DDR mechanisms. PMID:26414677

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).

Culture and the Behavioral Manifestations of Traits: An Application of the Act Frequency Approach

PubMed Central

Church, A. Timothy; Katigbak, Marcia S.; Miramontes, Lilia G.; del Prado, Alicia M.

2009-01-01

The behavioral manifestations of Big Five traits were compared across cultures using the Act Frequency Approach. American (n = 176) and Filipino (n = 195) students completed a Big Five measure and act frequency ratings for behaviors performed during the past month. Acts for specific traits cohered to an equivalent degree across cultures. In both cultures, the structure of act composites resembled the Big Five and the strength of trait-behavior relationships was very similar. Many acts were multidimensional and analyses revealed cultural commonalities and differences in the relevance and prevalence of acts for the Big Five traits. The results were more consistent with trait than cultural psychology perspectives, because traits predicted behavior equally well, on average, in the two cultures. PMID:19865595

Integrative analysis of omics summary data reveals putative mechanisms underlying complex traits.

PubMed

Wu, Yang; Zeng, Jian; Zhang, Futao; Zhu, Zhihong; Qi, Ting; Zheng, Zhili; Lloyd-Jones, Luke R; Marioni, Riccardo E; Martin, Nicholas G; Montgomery, Grant W; Deary, Ian J; Wray, Naomi R; Visscher, Peter M; McRae, Allan F; Yang, Jian

2018-03-02

The identification of genes and regulatory elements underlying the associations discovered by GWAS is essential to understanding the aetiology of complex traits (including diseases). Here, we demonstrate an analytical paradigm of prioritizing genes and regulatory elements at GWAS loci for follow-up functional studies. We perform an integrative analysis that uses summary-level SNP data from multi-omics studies to detect DNA methylation (DNAm) sites associated with gene expression and phenotype through shared genetic effects (i.e., pleiotropy). We identify pleiotropic associations between 7858 DNAm sites and 2733 genes. These DNAm sites are enriched in enhancers and promoters, and >40% of them are mapped to distal genes. Further pleiotropic association analyses, which link both the methylome and transcriptome to 12 complex traits, identify 149 DNAm sites and 66 genes, indicating a plausible mechanism whereby the effect of a genetic variant on phenotype is mediated by genetic regulation of transcription through DNAm.

Lessons learned from the dog genome.

PubMed

Wayne, Robert K; Ostrander, Elaine A

2007-11-01

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

Evolutionary and plastic responses of freshwater invertebrates to climate change: realized patterns and future potential.

PubMed

Stoks, Robby; Geerts, Aurora N; De Meester, Luc

2014-01-01

We integrated the evidence for evolutionary and plastic trait changes in situ in response to climate change in freshwater invertebrates (aquatic insects and zooplankton). The synthesis on the trait changes in response to the expected reductions in hydroperiod and increases in salinity indicated little evidence for adaptive, plastic, and genetic trait changes and for local adaptation. With respect to responses to temperature, there are many studies on temporal trait changes in phenology and body size in the wild that are believed to be driven by temperature increases, but there is a general lack of rigorous demonstration whether these trait changes are genetically based, adaptive, and causally driven by climate change. Current proof for genetic trait changes under climate change in freshwater invertebrates stems from a limited set of common garden experiments replicated in time. Experimental thermal evolution experiments and common garden warming experiments associated with space-for-time substitutions along latitudinal gradients indicate that besides genetic changes, also phenotypic plasticity and evolution of plasticity are likely to contribute to the observed phenotypic changes under climate change in aquatic invertebrates. Apart from plastic and genetic thermal adjustments, also genetic photoperiod adjustments are widespread and may even dominate the observed phenological shifts.

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.

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.

The Logic of Fashion Cycles

PubMed Central

Acerbi, Alberto; Ghirlanda, Stefano; Enquist, Magnus

2012-01-01

Many cultural traits exhibit volatile dynamics, commonly dubbed fashions or fads. Here we show that realistic fashion-like dynamics emerge spontaneously if individuals can copy others' preferences for cultural traits as well as traits themselves. We demonstrate this dynamics in simple mathematical models of the diffusion, and subsequent abandonment, of a single cultural trait which individuals may or may not prefer. We then simulate the coevolution between many cultural traits and the associated preferences, reproducing power-law frequency distributions of cultural traits (most traits are adopted by few individuals for a short time, and very few by many for a long time), as well as correlations between the rate of increase and the rate of decrease of traits (traits that increase rapidly in popularity are also abandoned quickly and vice versa). We also establish that alternative theories, that fashions result from individuals signaling their social status, or from individuals randomly copying each other, do not satisfactorily reproduce these empirical observations. PMID:22412887

The logic of fashion cycles.

PubMed

Acerbi, Alberto; Ghirlanda, Stefano; Enquist, Magnus

2012-01-01

Many cultural traits exhibit volatile dynamics, commonly dubbed fashions or fads. Here we show that realistic fashion-like dynamics emerge spontaneously if individuals can copy others' preferences for cultural traits as well as traits themselves. We demonstrate this dynamics in simple mathematical models of the diffusion, and subsequent abandonment, of a single cultural trait which individuals may or may not prefer. We then simulate the coevolution between many cultural traits and the associated preferences, reproducing power-law frequency distributions of cultural traits (most traits are adopted by few individuals for a short time, and very few by many for a long time), as well as correlations between the rate of increase and the rate of decrease of traits (traits that increase rapidly in popularity are also abandoned quickly and vice versa). We also establish that alternative theories, that fashions result from individuals signaling their social status, or from individuals randomly copying each other, do not satisfactorily reproduce these empirical observations.

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…

A high-resolution genetic linkage map and QTL fine mapping for growth-related traits and sex in the Yangtze River common carp (Cyprinus carpio haematopterus).

PubMed

Feng, Xiu; Yu, Xiaomu; Fu, Beide; Wang, Xinhua; Liu, Haiyang; Pang, Meixia; Tong, Jingou

2018-04-02

A high-density genetic linkage map is essential for QTL fine mapping, comparative genome analysis, identification of candidate genes and marker-assisted selection for economic traits in aquaculture species. The Yangtze River common carp (Cyprinus carpio haematopterus) is one of the most important aquacultured strains in China. However, quite limited genetics and genomics resources have been developed for genetic improvement of economic traits in such strain. A high-resolution genetic linkage map was constructed by using 7820 2b-RAD (2b-restriction site-associated DNA) and 295 microsatellite markers in a F2 family of the Yangtze River common carp (C. c. haematopterus). The length of the map was 4586.56 cM with an average marker interval of 0.57 cM. Comparative genome mapping revealed that a high proportion (70%) of markers with disagreed chromosome location was observed between C. c. haematopterus and another common carp strain (subspecies) C. c. carpio. A clear 2:1 relationship was observed between C. c. haematopterus linkage groups (LGs) and zebrafish (Danio rerio) chromosomes. Based on the genetic map, 21 QTLs for growth-related traits were detected on 12 LGs, and contributed values of phenotypic variance explained (PVE) ranging from 16.3 to 38.6%, with LOD scores ranging from 4.02 to 11.13. A genome-wide significant QTL (LOD = 10.83) and three chromosome-wide significant QTLs (mean LOD = 4.84) for sex were mapped on LG50 and LG24, respectively. A 1.4 cM confidence interval of QTL for all growth-related traits showed conserved synteny with a 2.06 M segment on chromosome 14 of D. rerio. Five potential candidate genes were identified by blast search in this genomic region, including a well-studied multi-functional growth related gene, Apelin. We mapped a set of suggestive and significant QTLs for growth-related traits and sex based on a high-density genetic linkage map using SNP and microsatellite markers for Yangtze River common carp. Several candidate growth genes were also identified from the QTL regions by comparative mapping. This genetic map would provide a basis for genome assembly and comparative genomics studies, and those QTL-derived candidate genes and genetic markers are useful genomic resources for marker-assisted selection (MAS) of growth-related traits in the Yangtze River common carp.

An eco-physiological model of the impact of temperature on Aedes aegypti life history traits.

PubMed

Padmanabha, Harish; Correa, Fabio; Legros, Mathieu; Nijhout, H Fredrick; Lord, Cynthia; Lounibos, L Philip

2012-12-01

Physiological processes mediate the impact of ecological conditions on the life histories of insect vectors. For the dengue/chikungunya mosquito, Aedes aegypti, three life history traits that are critical to urban population dynamics and control are: size, development rate and starvation mortality. In this paper we make use of prior laboratory experiments on each of these traits at 2°C intervals between 20 and 30°C, in conjunction with eco-evolutionary theory and studies on A.aegypti physiology, in order to develop a conceptual and mathematical framework that can predict their thermal sensitivity. Our model of reserve dependent growth (RDG), which considers a potential tradeoff between the accumulation of reserves and structural biomass, was able to robustly predict laboratory observations, providing a qualitative improvement over the approach most commonly used in other A.aegypti models. RDG predictions of reduced size at higher temperatures, but increased reserves relative to size, are supported by the available evidence in Aedes spp. We offer the potentially general hypothesis that temperature-size patterns in mosquitoes are driven by a net benefit of finishing the growing stage with proportionally greater reserves relative to structure at warmer temperatures. By relating basic energy flows to three fundamental life history traits, we provide a mechanistic framework for A.aegypti development to which ecological complexity can be added. Ultimately, this could provide a framework for developing and field testing hypotheses on how processes such as climate variation, density dependent regulation, human behavior or control strategies may influence A.aegypti population dynamics and disease risk. Copyright © 2012 Elsevier Ltd. All rights reserved.

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.

Selection on male sex pheromone composition contributes to butterfly reproductive isolation

PubMed Central

Bacquet, P. M. B.; Brattström, O.; Wang, H.-L.; Allen, C. E.; Löfstedt, C.; Brakefield, P. M.; Nieberding, C. M.

2015-01-01

Selection can facilitate diversification by inducing character displacement in mate choice traits that reduce the probability of maladaptive mating between lineages. Although reproductive character displacement (RCD) has been demonstrated in two-taxa case studies, the frequency of this process in nature is still debated. Moreover, studies have focused primarily on visual and acoustic traits, despite the fact that chemical communication is probably the most common means of species recognition. Here, we showed in a large, mostly sympatric, butterfly genus, a strong pattern of recurrent RCD for predicted male sex pheromone composition, but not for visual mate choice traits. Our results suggest that RCD is not anecdotal, and that selection for divergence in male sex pheromone composition contributed to reproductive isolation within the Bicyclus genus. We propose that selection may target olfactory mate choice traits as a more common sensory modality to ensure reproductive isolation among diverging lineages than previously envisaged. PMID:25740889

The dark cube: dark and light character profiles.

PubMed

Garcia, Danilo; Rosenberg, Patricia

2016-01-01

Background. Research addressing distinctions and similarities between people's malevolent character traits (i.e., the Dark Triad: Machiavellianism, narcissism, and psychopathy) has detected inconsistent linear associations to temperament traits. Additionally, these dark traits seem to have a common core expressed as uncooperativeness. Hence, some researchers suggest that the dark traits are best represented as one global construct (i.e., the unification argument) rather than as ternary construct (i.e., the uniqueness argument). We put forward the dark cube (cf. Cloninger's character cube) comprising eight dark profiles that can be used to compare individuals who differ in one dark character trait while holding the other two constant. Our aim was to investigate in which circumstances individuals who are high in each one of the dark character traits differ in Cloninger's "light" character traits: self-directedness, cooperativeness, and self-transcendence. We also investigated if people's dark character profiles were associated to their light character profiles. Method. A total of 997 participants recruited from Amazon's Mechanical Turk (MTurk) responded to the Short Dark Triad and the Short Character Inventory. Participants were allocated to eight different dark profiles and eight light profiles based on their scores in each of the traits and any possible combination of high and low scores. We used three-way interaction regression analyses and t-tests to investigate differences in light character traits between individuals with different dark profiles. As a second step, we compared the individuals' dark profile with her/his character profile using an exact cell-wise analysis conducted in the ROPstat software (http://www.ropstat.com). Results. Individuals who expressed high levels of Machiavellianism and those who expressed high levels of psychopathy also expressed low self-directedness and low cooperativeness. Individuals with high levels of narcissism, in contrast, scored high in self-directedness. Moreover, individuals with a profile low in the dark traits were more likely to end up with a profile high in cooperativeness. The opposite was true for those individuals with a profile high in the dark traits. The rest of the cross-comparisons revealed some of the characteristics of human personality as a non-linear complex dynamic system. Conclusions. Our study suggests that individuals who are high in Machiavellianism and psychopathy share a unified non-agentic and uncooperative character (i.e., irresponsible, low in self-control, unempathetic, unhelpful, untolerant), while individuals high in narcissism have a more unique character configuration expressed as high agency and, when the other dark traits are high, highly spiritual but uncooperative. In other words, based on differences in their associations to the light side of character, the Dark Triad seems to be a dyad rather than a triad.

The dark cube: dark and light character profiles

PubMed Central

2016-01-01

Background. Research addressing distinctions and similarities between people’s malevolent character traits (i.e., the Dark Triad: Machiavellianism, narcissism, and psychopathy) has detected inconsistent linear associations to temperament traits. Additionally, these dark traits seem to have a common core expressed as uncooperativeness. Hence, some researchers suggest that the dark traits are best represented as one global construct (i.e., the unification argument) rather than as ternary construct (i.e., the uniqueness argument). We put forward the dark cube (cf. Cloninger’s character cube) comprising eight dark profiles that can be used to compare individuals who differ in one dark character trait while holding the other two constant. Our aim was to investigate in which circumstances individuals who are high in each one of the dark character traits differ in Cloninger’s “light” character traits: self-directedness, cooperativeness, and self-transcendence. We also investigated if people’s dark character profiles were associated to their light character profiles. Method. A total of 997 participants recruited from Amazon’s Mechanical Turk (MTurk) responded to the Short Dark Triad and the Short Character Inventory. Participants were allocated to eight different dark profiles and eight light profiles based on their scores in each of the traits and any possible combination of high and low scores. We used three-way interaction regression analyses and t-tests to investigate differences in light character traits between individuals with different dark profiles. As a second step, we compared the individuals’ dark profile with her/his character profile using an exact cell-wise analysis conducted in the ROPstat software (http://www.ropstat.com). Results. Individuals who expressed high levels of Machiavellianism and those who expressed high levels of psychopathy also expressed low self-directedness and low cooperativeness. Individuals with high levels of narcissism, in contrast, scored high in self-directedness. Moreover, individuals with a profile low in the dark traits were more likely to end up with a profile high in cooperativeness. The opposite was true for those individuals with a profile high in the dark traits. The rest of the cross-comparisons revealed some of the characteristics of human personality as a non-linear complex dynamic system. Conclusions. Our study suggests that individuals who are high in Machiavellianism and psychopathy share a unified non-agentic and uncooperative character (i.e., irresponsible, low in self-control, unempathetic, unhelpful, untolerant), while individuals high in narcissism have a more unique character configuration expressed as high agency and, when the other dark traits are high, highly spiritual but uncooperative. In other words, based on differences in their associations to the light side of character, the Dark Triad seems to be a dyad rather than a triad. PMID:26966650

[Effect of an introgression from Aegilops cylindrica host on manifestation of productivity traits in winter common wheat F2 plants].

PubMed

Kozub, N A; Sozinov, I A; sozinov, A A

2004-12-01

The effect of introgression of a chromosome 1D segment from Aegilops cylindrica to winter common wheat on productivity traits in F2 plants was studied using storage protein loci as genetic markers. An allele of the gliadin-coding Gli-D1 locus served as a marker of the introgression. Using of two- and three-locus interaction models, it was shown that the introgression tagged with Gli-D1 affected the manifestation of productivity traits (productive tillering, grain weight per plant and grain number per plant) through interaction with other marker storage protein loci: Glu-B1, Glu-D1, and Gli-B2.

An ultra-high density linkage map and QTL mapping for sex and growth-related traits of common carp (Cyprinus carpio)

PubMed Central

Peng, Wenzhu; Xu, Jian; Zhang, Yan; Feng, Jianxin; Dong, Chuanju; Jiang, Likun; Feng, Jingyan; Chen, Baohua; Gong, Yiwen; Chen, Lin; Xu, Peng

2016-01-01

High density genetic linkage maps are essential for QTL fine mapping, comparative genomics and high quality genome sequence assembly. In this study, we constructed a high-density and high-resolution genetic linkage map with 28,194 SNP markers on 14,146 distinct loci for common carp based on high-throughput genotyping with the carp 250 K single nucleotide polymorphism (SNP) array in a mapping family. The genetic length of the consensus map was 10,595.94 cM with an average locus interval of 0.75 cM and an average marker interval of 0.38 cM. Comparative genomic analysis revealed high level of conserved syntenies between common carp and the closely related model species zebrafish and medaka. The genome scaffolds were anchored to the high-density linkage map, spanning 1,357 Mb of common carp reference genome. QTL mapping and association analysis identified 22 QTLs for growth-related traits and 7 QTLs for sex dimorphism. Candidate genes underlying growth-related traits were identified, including important regulators such as KISS2, IGF1, SMTLB, NPFFR1 and CPE. Candidate genes associated with sex dimorphism were also identified including 3KSR and DMRT2b. The high-density and high-resolution genetic linkage map provides an important tool for QTL fine mapping and positional cloning of economically important traits, and improving common carp genome assembly. PMID:27225429

Darwin's Difficulties and Students' Struggles with Trait Loss: Cognitive-Historical Parallelisms in Evolutionary Explanation

NASA Astrophysics Data System (ADS)

Ha, Minsu; Nehm, Ross H.

2014-05-01

Although historical changes in scientific ideas sometimes display striking similarities with students' conceptual progressions, some scholars have cautioned that such similarities lack meaningful commonalities. In the history of evolution, while Darwin and his contemporaries often used natural selection to explain evolutionary trait gain or increase, they struggled to use it to convincingly account for cases of trait loss or decrease. This study examines Darwin's evolutionary writings about trait gain and loss in the Origin of Species (On the origin of species by means of natural selection, or the preservation of favoured races in the struggle for life. D. Appleton, New York, 1859) and compares them to written evolutionary explanations for trait gain and loss in a large (n > 500), cross-cultural and cross-sectional sample (novices and experts from the USA and Korea). Findings indicate that significantly more students and experts applied natural selection to cases of trait gain, but like Darwin and his contemporaries, they more often applied `use and disuse' and `inheritance of acquired characteristics' to episodes of trait loss. Although the parallelism between Darwin's difficulties and students' struggles with trait loss are striking, significant differences also characterize explanatory model structure. Overall, however, students and scientists struggles to explain trait loss—which is a very common phenomenon in the history of life—appear to transcend time, place, and level of biological expertise. The significance of these findings for evolution education are discussed; in particular, the situated nature of biological reasoning, and the important role that the history of science can play in understanding cognitive constraints on science learning.

Quantifying the heritability of testicular germ cell tumour using both population-based and genomic approaches.

PubMed

Litchfield, Kevin; Thomsen, Hauke; Mitchell, Jonathan S; Sundquist, Jan; Houlston, Richard S; Hemminki, Kari; Turnbull, Clare

2015-09-09

A sizable fraction of testicular germ cell tumour (TGCT) risk is expected to be explained by heritable factors. Recent genome-wide association studies (GWAS) have successfully identified a number of common SNPs associated with TGCT. It is however, unclear how much common variation there is left to be accounted for by other, yet to be identified, common SNPs and what contribution common genetic variation makes to the heritable risk of TGCT. We approached this question using two complimentary analytical techniques. We undertook a population-based analysis of the Swedish family-cancer database, through which we estimated that the heritability of TGCT at 48.9% (CI:47.2%-52.3%). We also applied Genome-Wide Complex Trait Analysis to 922 cases and 4,842 controls to estimate the heritability of TGCT. The heritability explained by known common risk SNPs identified by GWAS was 9.1%, whereas the heritability explained by all common SNPs was 37.4% (CI:27.6%-47.2%). These complementary findings indicate that the known TGCT SNPs only explain a small proportion of the heritability and many additional common SNPs remain to be identified. The data also suggests that a fraction of the heritability of TGCT is likely to be explained by other classes of genetic variation, such as rare disease-causing alleles.

Common variants in Mendelian kidney disease genes and their association with renal function.

PubMed

Parsa, Afshin; Fuchsberger, Christian; Köttgen, Anna; O'Seaghdha, Conall M; Pattaro, Cristian; de Andrade, Mariza; Chasman, Daniel I; Teumer, Alexander; Endlich, Karlhans; Olden, Matthias; Chen, Ming-Huei; Tin, Adrienne; Kim, Young J; Taliun, Daniel; Li, Man; Feitosa, Mary; Gorski, Mathias; Yang, Qiong; Hundertmark, Claudia; Foster, Meredith C; Glazer, Nicole; Isaacs, Aaron; Rao, Madhumathi; Smith, Albert V; O'Connell, Jeffrey R; Struchalin, Maksim; Tanaka, Toshiko; Li, Guo; Hwang, Shih-Jen; Atkinson, Elizabeth J; Lohman, Kurt; Cornelis, Marilyn C; Johansson, Asa; Tönjes, Anke; Dehghan, Abbas; Couraki, Vincent; Holliday, Elizabeth G; Sorice, Rossella; Kutalik, Zoltan; Lehtimäki, Terho; Esko, Tõnu; Deshmukh, Harshal; Ulivi, Sheila; Chu, Audrey Y; Murgia, Federico; Trompet, Stella; Imboden, Medea; Kollerits, Barbara; Pistis, Giorgio; Harris, Tamara B; Launer, Lenore J; Aspelund, Thor; Eiriksdottir, Gudny; Mitchell, Braxton D; Boerwinkle, Eric; Schmidt, Helena; Hofer, Edith; Hu, Frank; Demirkan, Ayse; Oostra, Ben A; Turner, Stephen T; Ding, Jingzhong; Andrews, Jeanette S; Freedman, Barry I; Giulianini, Franco; Koenig, Wolfgang; Illig, Thomas; Döring, Angela; Wichmann, H-Erich; Zgaga, Lina; Zemunik, Tatijana; Boban, Mladen; Minelli, Cosetta; Wheeler, Heather E; Igl, Wilmar; Zaboli, Ghazal; Wild, Sarah H; Wright, Alan F; Campbell, Harry; Ellinghaus, David; Nöthlings, Ute; Jacobs, Gunnar; Biffar, Reiner; Ernst, Florian; Homuth, Georg; Kroemer, Heyo K; Nauck, Matthias; Stracke, Sylvia; Völker, Uwe; Völzke, Henry; Kovacs, Peter; Stumvoll, Michael; Mägi, Reedik; Hofman, Albert; Uitterlinden, Andre G; Rivadeneira, Fernando; Aulchenko, Yurii S; Polasek, Ozren; Hastie, Nick; Vitart, Veronique; Helmer, Catherine; Wang, Jie Jin; Stengel, Bénédicte; Ruggiero, Daniela; Bergmann, Sven; Kähönen, Mika; Viikari, Jorma; Nikopensius, Tiit; Province, Michael; Colhoun, Helen; Doney, Alex; Robino, Antonietta; Krämer, Bernhard K; Portas, Laura; Ford, Ian; Buckley, Brendan M; Adam, Martin; Thun, Gian-Andri; Paulweber, Bernhard; Haun, Margot; Sala, Cinzia; Mitchell, Paul; Ciullo, Marina; Vollenweider, Peter; Raitakari, Olli; Metspalu, Andres; Palmer, Colin; Gasparini, Paolo; Pirastu, Mario; Jukema, J Wouter; Probst-Hensch, Nicole M; Kronenberg, Florian; Toniolo, Daniela; Gudnason, Vilmundur; Shuldiner, Alan R; Coresh, Josef; Schmidt, Reinhold; Ferrucci, Luigi; van Duijn, Cornelia M; Borecki, Ingrid; Kardia, Sharon L R; Liu, Yongmei; Curhan, Gary C; Rudan, Igor; Gyllensten, Ulf; Wilson, James F; Franke, Andre; Pramstaller, Peter P; Rettig, Rainer; Prokopenko, Inga; Witteman, Jacqueline; Hayward, Caroline; Ridker, Paul M; Bochud, Murielle; Heid, Iris M; Siscovick, David S; Fox, Caroline S; Kao, W Linda; Böger, Carsten A

2013-12-01

Many common genetic variants identified by genome-wide association studies for complex traits map to genes previously linked to rare inherited Mendelian disorders. A systematic analysis of common single-nucleotide polymorphisms (SNPs) in genes responsible for Mendelian diseases with kidney phenotypes has not been performed. We thus developed a comprehensive database of genes for Mendelian kidney conditions and evaluated the association between common genetic variants within these genes and kidney function in the general population. Using the Online Mendelian Inheritance in Man database, we identified 731 unique disease entries related to specific renal search terms and confirmed a kidney phenotype in 218 of these entries, corresponding to mutations in 258 genes. We interrogated common SNPs (minor allele frequency >5%) within these genes for association with the estimated GFR in 74,354 European-ancestry participants from the CKDGen Consortium. However, the top four candidate SNPs (rs6433115 at LRP2, rs1050700 at TSC1, rs249942 at PALB2, and rs9827843 at ROBO2) did not achieve significance in a stage 2 meta-analysis performed in 56,246 additional independent individuals, indicating that these common SNPs are not associated with estimated GFR. The effect of less common or rare variants in these genes on kidney function in the general population and disease-specific cohorts requires further research.

Magnetocapacitance and the physics of solid state interfaces

NASA Astrophysics Data System (ADS)

Hebard, Arthur

2008-10-01

When Herbert Kroemer stated in his Nobel address [1] that ``the interface is the device,'' he was implicitly acknowledging the importance of understanding the physics of interfaces. If interfaces are to have character traits, then ``impedance'' (or complex capacitance) would be a commonly used descriptor. In this talk I will discuss the use of magnetic fields to probe the ``character'' of a variety of interfaces including planar capacitor structures with magnetic electrodes, simple metal/semiconductor contacts (Schottky barriers) and the interface-dominated competition on microscopic length scales between ferromagnetic metallic and charge-ordered insulating phases in complex oxides. I will show that seeking experimental answers to surprisingly simple questions often leads to striking results that seriously challenge theoretical understanding. Perhaps Herbert Kroemer should have said, ``the interface is the device with a magnetic personality that continually surprises.'' [3pt] [1] Herbert Kroemer, ``Quasielectric fields and band offsets: teaching electron s new tricks,'' Nobel Lecture, December 8, 2000:

What is the relationship between trait anxiety and depressive symptoms, fatigue, and low sleep quality following breast cancer surgery?

PubMed

Lockefeer, J P M; De Vries, J

2013-05-01

Depressive symptoms, fatigue, and low sleep quality are common symptoms during and after breast cancer (BC) treatment. In the present study, the relationship between trait anxiety and these symptoms in a long follow-up period was examined. This was a prospective study. Participants, composed of 163 women with BC and 224 women with benign breast problems (BBPs), completed questionnaires on depressive symptoms, fatigue, and sleep quality before diagnosis and 1, 3, 6, 12, and 24 months after diagnosis (BBP group) or surgical treatment (BC group). In addition, patients completed a questionnaire on trait anxiety before diagnosis. Trait anxiety was the most significant predictor for depressive symptoms (p < 0.001) and lower sleep quality (p = 0.040) at 2-year follow-up. For fatigue, fatigue at baseline and trait anxiety together was the most important predictor (p < 0.001). Linear mixed model analyses showed that there was an interaction effect of time with trait anxiety and with diagnosis for depressive symptoms (p = 0.001 and p < 0.001) and fatigue (p = 0.004 and p < 0.001). There was no interaction effect of time with trait anxiety or diagnosis for sleep quality (p = 0.055 and p = 0.225). Together with diagnosis, trait anxiety was an important determinant of depressive symptoms, fatigue, and low sleep quality following diagnosis of BBP or BC and seemed to be a common factor in these persisting symptoms. Copyright © 2012 John Wiley & Sons, Ltd.

Local selection modifies phenotypic divergence among Rana temporaria populations in the presence of gene flow.

PubMed

Richter-Boix, Alex; Teplitsky, Céline; Rogell, Björn; Laurila, Anssi

2010-02-01

In ectotherms, variation in life history traits among populations is common and suggests local adaptation. However, geographic variation itself is not a proof for local adaptation, as genetic drift and gene flow may also shape patterns of quantitative variation. We studied local and regional variation in means and phenotypic plasticity of larval life history traits in the common frog Rana temporaria using six populations from central Sweden, breeding in either open-canopy or partially closed-canopy ponds. To separate local adaptation from genetic drift, we compared differentiation in quantitative genetic traits (Q(ST)) obtained from a common garden experiment with differentiation in presumably neutral microsatellite markers (F(ST)). We found that R. temporaria populations differ in means and plasticities of life history traits in different temperatures at local, and in F(ST) at regional scale. Comparisons of differentiation in quantitative traits and in molecular markers suggested that natural selection was responsible for the divergence in growth and development rates as well as in temperature-induced plasticity, indicating local adaptation. However, at low temperature, the role of genetic drift could not be separated from selection. Phenotypes were correlated with forest canopy closure, but not with geographical or genetic distance. These results indicate that local adaptation can evolve in the presence of ongoing gene flow among the populations, and that natural selection is strong in this system.

Increased Transcript Complexity in Genes Associated with Chronic Obstructive Pulmonary Disease

PubMed Central

Lackey, Lela; McArthur, Evonne; Laederach, Alain

2015-01-01

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

Genetic and Functional Dissection of HTRA1 and LOC387715 in Age-Related Macular Degeneration

PubMed Central

Zeng, Jiexi; Lu, Fang; Sun, Xufang; Zhao, Chao; Wang, Kevin; Davey, Lisa; Chen, Haoyu; London, Nyall; Muramatsu, Daisuke; Salasar, Francesca; Carmona, Ruben; Kasuga, Daniel; Wang, Xiaolei; Bedell, Matthew; Dixie, Manjuxia; Zhao, Peiquan; Yang, Ruifu; Gibbs, Daniel; Liu, Xiaoqi; Li, Yan; Li, Cai; Li, Yuanfeng; Campochiaro, Betsy; Constantine, Ryan; Zack, Donald J.; Campochiaro, Peter; Fu, Yinbin; Li, Dean Y.; Katsanis, Nicholas; Zhang, Kang

2010-01-01

A common haplotype on 10q26 influences the risk of age-related macular degeneration (AMD) and encompasses two genes, LOC387715 and HTRA1. Recent data have suggested that loss of LOC387715, mediated by an insertion/deletion (in/del) that destabilizes its message, is causally related with the disorder. Here we show that loss of LOC387715 is insufficient to explain AMD susceptibility, since a nonsense mutation (R38X) in this gene that leads to loss of its message resides in a protective haplotype. At the same time, the common disease haplotype tagged by the in/del and rs11200638 has an effect on the transcriptional upregulation of the adjacent gene, HTRA1. These data implicate increased HTRA1 expression in the pathogenesis of AMD and highlight the importance of exploring multiple functional consequences of alleles in haplotypes that confer susceptibility to complex traits. PMID:20140183

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

PubMed

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

2010-06-10

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

Shoot and Root Traits Contribute to Drought Resistance in Recombinant Inbred Lines of MD 23–24 × SEA 5 of Common Bean

PubMed Central

Polania, Jose; Rao, Idupulapati M.; Cajiao, Cesar; Grajales, Miguel; Rivera, Mariela; Velasquez, Federico; Raatz, Bodo; Beebe, Stephen E.

2017-01-01

Drought is the major abiotic stress factor limiting yield of common bean (Phaseolus vulgaris L.) in smallholder systems in Latin America and eastern and southern Africa; where it is a main source of protein in the daily diet. Identification of shoot and root traits associated with drought resistance contributes to improving the process of designing bean genotypes adapted to drought. Field and greenhouse studies were conducted at the International Center for Tropical Agriculture (CIAT), Palmira, Colombia to determine the relationship between grain yield and different shoot and root traits using a recombinant inbred lines (RILs) population (MD23–24 × SEA 5) of common bean. The main objectives of this study were to identify: (i) specific shoot and root morpho-physiological traits that contribute to improved resistance to drought and that could be useful as selection criteria in breeding beans for drought resistance; and (ii) superior genotypes with desirable shoot and root traits that could serve as parents in breeding programs that are aimed at improving drought resistance. A set of 121 bean genotypes (111 RILs, 2 parents, 8 checks) belonging to the Mesoamerican gene pool and one cowpea variety were evaluated under field conditions with two levels of water supply (irrigated and rainfed) over three seasons. To complement field studies, a greenhouse study was conducted using plastic cylinders with soil inserted into PVC pipes, to determine the relationship between grain yield obtained under field conditions with different root traits measured under greenhouse conditions. Resistance to drought stress was positively associated with a deeper and vigorous root system, better shoot growth, and superior mobilization of photosynthates to pod and seed production. The drought resistant lines differed in their root characteristics, some of them with a vigorous and deeper root system while others with a moderate to shallow root system. Among the shoot traits measured, pod harvest index, and seed number per area could serve as useful selection criteria for assessing sink strength and for genetic improvement of drought resistance in common bean. PMID:28316609

Multienvironment Quantitative Trait Loci Analysis for Photosynthate Acquisition, Accumulation, and Remobilization Traits in Common Bean Under Drought Stress

PubMed Central

Asfaw, Asrat; Blair, Matthew W.; Struik, Paul C.

2012-01-01

Many of the world’s common bean (Phaseolus vulgaris L.) growing regions are prone to either intermittent or terminal drought stress, making drought the primary cause of yield loss under farmers’ field conditions. Improved photosynthate acquisition, accumulation, and then remobilization have been observed as important mechanisms for adaptation to drought stress. The objective of this study was to tag quantitative trait loci (QTL) for photosynthate acquisition, accumulation, and remobilization to grain by using a recombinant inbred line population developed from the Mesoamerican intragenepool cross of drought-susceptible DOR364 and drought-tolerant BAT477 grown under eight environments differing in drought stress across two continents: Africa and South America. The recombinant inbred line population expressed quantitative variation and transgressive segregation for 11 traits associated with drought tolerance. QTL were detected by both a mixed multienvironment model and by composite interval mapping for each environment using a linkage map constructed with 165 genetic markers that covered 11 linkage groups of the common bean genome. In the multienvironment, mixed model, nine QTL were detected for 10 drought stress tolerance mechanism traits found on six of the 11 linkage groups. Significant QTL × environment interaction was observed for six of the nine QTL. QTL × environment interaction was of the cross-over type for three of the six significant QTL with contrasting effect of the parental alleles across different environments. In the composite interval mapping, we found 69 QTL in total. The majority of these were found for Palmira (47) or Awassa (18), with fewer in Malawi (4). Phenotypic variation explained by QTL in single environments ranged up to 37%, and the most consistent QTL were for Soil Plant Analysis Development (SPAD) leaf chlorophyll reading and pod partitioning traits. QTL alignment between the two detection methods showed that yield QTL on b08 and stem carbohydrate QTL on b05 were most consistent between the multilocation model and the single environment detection. Our results indicate the relevance of QTL detection in the sites in which bean breeding will be undertaken and the importance of photosynthate accumulation as a trait for common bean drought tolerance. PMID:22670228

Shoot and Root Traits Contribute to Drought Resistance in Recombinant Inbred Lines of MD 23-24 × SEA 5 of Common Bean.

PubMed

Polania, Jose; Rao, Idupulapati M; Cajiao, Cesar; Grajales, Miguel; Rivera, Mariela; Velasquez, Federico; Raatz, Bodo; Beebe, Stephen E

2017-01-01

Drought is the major abiotic stress factor limiting yield of common bean ( Phaseolus vulgaris L.) in smallholder systems in Latin America and eastern and southern Africa; where it is a main source of protein in the daily diet. Identification of shoot and root traits associated with drought resistance contributes to improving the process of designing bean genotypes adapted to drought. Field and greenhouse studies were conducted at the International Center for Tropical Agriculture (CIAT), Palmira, Colombia to determine the relationship between grain yield and different shoot and root traits using a recombinant inbred lines (RILs) population (MD23-24 × SEA 5) of common bean. The main objectives of this study were to identify: (i) specific shoot and root morpho-physiological traits that contribute to improved resistance to drought and that could be useful as selection criteria in breeding beans for drought resistance; and (ii) superior genotypes with desirable shoot and root traits that could serve as parents in breeding programs that are aimed at improving drought resistance. A set of 121 bean genotypes (111 RILs, 2 parents, 8 checks) belonging to the Mesoamerican gene pool and one cowpea variety were evaluated under field conditions with two levels of water supply (irrigated and rainfed) over three seasons. To complement field studies, a greenhouse study was conducted using plastic cylinders with soil inserted into PVC pipes, to determine the relationship between grain yield obtained under field conditions with different root traits measured under greenhouse conditions. Resistance to drought stress was positively associated with a deeper and vigorous root system, better shoot growth, and superior mobilization of photosynthates to pod and seed production. The drought resistant lines differed in their root characteristics, some of them with a vigorous and deeper root system while others with a moderate to shallow root system. Among the shoot traits measured, pod harvest index, and seed number per area could serve as useful selection criteria for assessing sink strength and for genetic improvement of drought resistance in common bean.

Multienvironment quantitative trait Loci analysis for photosynthate acquisition, accumulation, and remobilization traits in common bean under drought stress.

PubMed

Asfaw, Asrat; Blair, Matthew W; Struik, Paul C

2012-05-01

Many of the world's common bean (Phaseolus vulgaris L.) growing regions are prone to either intermittent or terminal drought stress, making drought the primary cause of yield loss under farmers' field conditions. Improved photosynthate acquisition, accumulation, and then remobilization have been observed as important mechanisms for adaptation to drought stress. The objective of this study was to tag quantitative trait loci (QTL) for photosynthate acquisition, accumulation, and remobilization to grain by using a recombinant inbred line population developed from the Mesoamerican intragenepool cross of drought-susceptible DOR364 and drought-tolerant BAT477 grown under eight environments differing in drought stress across two continents: Africa and South America. The recombinant inbred line population expressed quantitative variation and transgressive segregation for 11 traits associated with drought tolerance. QTL were detected by both a mixed multienvironment model and by composite interval mapping for each environment using a linkage map constructed with 165 genetic markers that covered 11 linkage groups of the common bean genome. In the multienvironment, mixed model, nine QTL were detected for 10 drought stress tolerance mechanism traits found on six of the 11 linkage groups. Significant QTL × environment interaction was observed for six of the nine QTL. QTL × environment interaction was of the cross-over type for three of the six significant QTL with contrasting effect of the parental alleles across different environments. In the composite interval mapping, we found 69 QTL in total. The majority of these were found for Palmira (47) or Awassa (18), with fewer in Malawi (4). Phenotypic variation explained by QTL in single environments ranged up to 37%, and the most consistent QTL were for Soil Plant Analysis Development (SPAD) leaf chlorophyll reading and pod partitioning traits. QTL alignment between the two detection methods showed that yield QTL on b08 and stem carbohydrate QTL on b05 were most consistent between the multilocation model and the single environment detection. Our results indicate the relevance of QTL detection in the sites in which bean breeding will be undertaken and the importance of photosynthate accumulation as a trait for common bean drought tolerance.

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

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...

Mapping QTLs of yield-related traits using RIL population derived from common wheat and Tibetan semi-wild wheat.

PubMed

Liu, Gang; Jia, Lijia; Lu, Lahu; Qin, Dandan; Zhang, Jinping; Guan, Panfeng; Ni, Zhongfu; Yao, Yingyin; Sun, Qixin; Peng, Huiru

2014-11-01

QTLs controlling yield-related traits were mapped using a population derived from common wheat and Tibetan semi-wild wheat and they provided valuable information for using Tibetan semi-wild wheat in future wheat molecular breeding. Tibetan semi-wild wheat (Triticum aestivum ssp tibetanum Shao) is a kind of primitive hexaploid wheat and harbors several beneficial traits, such as tolerance to biotic and abiotic stresses. And as a wild relative of common wheat, heterosis of yield of the progeny between them was significant. This study focused on mapping QTLs controlling yield-related traits using a recombined inbred lines (RILs) population derived from a hybrid between a common wheat line NongDa3331 (ND3331) and the Tibetan semi-wild wheat accession Zang 1817. In nine location-year environments, a total of 148 putative QTLs controlling nine traits were detected, distributed on 19 chromosomes except for 1A and 2D. Single QTL explained the phenotypic variation ranging from 3.12 to 49.95%. Of these QTLs, 56 were contributed by Zang 1817. Some stable QTLs contributed by Zang 1817 were also detected in more than four environments, such as QPh-3A1, QPh-4B1 and QPh-4D for plant height, QSl-7A1 for spike length, QEp-4B2 for ears per plant, QGws-4D for grain weight per spike, and QTgw-4D for thousand grain weight. Several QTL-rich Regions were also identified, especially on the homoeologous group 4. The TaANT gene involved in floral organ development was mapped on chromosome 4A between Xksm71 and Xcfd6 with 0.8 cM interval, and co-segregated with the QTLs controlling floret number per spikelet, explaining 4.96-11.84% of the phenotypic variation. The current study broadens our understanding of the genetic characterization of Tibetan semi-wild wheat, which will enlarge the genetic diversity of yield-related traits in modern wheat breeding program.

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

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

Vegetable Grafting as a Tool to Improve Drought Resistance and Water Use Efficiency

PubMed Central

Kumar, Pradeep; Rouphael, Youssef; Cardarelli, Mariateresa; Colla, Giuseppe

2017-01-01

Drought is one of the most prevalent limiting factors causing considerable losses in crop productivity, inflicting economic as well as nutritional insecurity. One of the greatest challenges faced by the scientific community in the next few years is to minimize the yield losses caused by drought. Drought resistance is a complex quantitative trait controlled by many genes. Thus, introgression of drought resistance traits into high yielding genotypes has been a challenge to plant breeders. Vegetable grafting using rootstocks has emerged as a rapid tool in tailoring plants to better adapt to suboptimal growing conditions. This has induced changes in shoot physiology. Grafting applications have expanded mainly in Solanaceous crops and cucurbits, which are commonly grown in arid and semi-arid areas characterized by long drought periods. The current review gives an overview of the recent scientific literature on root-shoot interaction and rootstock-driven alteration of growth, yield, and fruit quality in grafted vegetable plants under drought stress. Further, we elucidate the drought resistance mechanisms of grafted vegetables at the morpho-physiological, biochemical, and molecular levels. PMID:28713405

Common and rare variants associated with kidney stones and biochemical traits

PubMed Central

Oddsson, Asmundur; Sulem, Patrick; Helgason, Hannes; Edvardsson, Vidar O.; Thorleifsson, Gudmar; Sveinbjörnsson, Gardar; Haraldsdottir, Eik; Eyjolfsson, Gudmundur I.; Sigurdardottir, Olof; Olafsson, Isleifur; Masson, Gisli; Holm, Hilma; Gudbjartsson, Daniel F.; Thorsteinsdottir, Unnur; Indridason, Olafur S.; Palsson, Runolfur; Stefansson, Kari

2015-01-01

Kidney stone disease is a complex disorder with a strong genetic component. We conducted a genome-wide association study of 28.3 million sequence variants detected through whole-genome sequencing of 2,636 Icelanders that were imputed into 5,419 kidney stone cases, including 2,172 cases with a history of recurrent kidney stones, and 279,870 controls. We identify sequence variants associating with kidney stones at ALPL (rs1256328[T], odds ratio (OR)=1.21, P=5.8 × 10−10) and a suggestive association at CASR (rs7627468[A], OR=1.16, P=2.0 × 10−8). Focusing our analysis on coding sequence variants in 63 genes with preferential kidney expression we identify two rare missense variants SLC34A1 p.Tyr489Cys (OR=2.38, P=2.8 × 10−5) and TRPV5 p.Leu530Arg (OR=3.62, P=4.1 × 10−5) associating with recurrent kidney stones. We also observe associations of the identified kidney stone variants with biochemical traits in a large population set, indicating potential biological mechanism. PMID:26272126

Common and rare variants associated with kidney stones and biochemical traits.

PubMed

Oddsson, Asmundur; Sulem, Patrick; Helgason, Hannes; Edvardsson, Vidar O; Thorleifsson, Gudmar; Sveinbjörnsson, Gardar; Haraldsdottir, Eik; Eyjolfsson, Gudmundur I; Sigurdardottir, Olof; Olafsson, Isleifur; Masson, Gisli; Holm, Hilma; Gudbjartsson, Daniel F; Thorsteinsdottir, Unnur; Indridason, Olafur S; Palsson, Runolfur; Stefansson, Kari

2015-08-14

Kidney stone disease is a complex disorder with a strong genetic component. We conducted a genome-wide association study of 28.3 million sequence variants detected through whole-genome sequencing of 2,636 Icelanders that were imputed into 5,419 kidney stone cases, including 2,172 cases with a history of recurrent kidney stones, and 279,870 controls. We identify sequence variants associating with kidney stones at ALPL (rs1256328[T], odds ratio (OR)=1.21, P=5.8 × 10(-10)) and a suggestive association at CASR (rs7627468[A], OR=1.16, P=2.0 × 10(-8)). Focusing our analysis on coding sequence variants in 63 genes with preferential kidney expression we identify two rare missense variants SLC34A1 p.Tyr489Cys (OR=2.38, P=2.8 × 10(-5)) and TRPV5 p.Leu530Arg (OR=3.62, P=4.1 × 10(-5)) associating with recurrent kidney stones. We also observe associations of the identified kidney stone variants with biochemical traits in a large population set, indicating potential biological mechanism.

Maintenance of genetic variation in human personality: Testing evolutionary models by estimating heritability due to common causal variants and investigating the effect of distant inbreeding

PubMed Central

Verweij, Karin J.H.; Yang, Jian; Lahti, Jari; Veijola, Juha; Hintsanen, Mirka; Pulkki-Råback, Laura; Heinonen, Kati; Pouta, Anneli; Pesonen, Anu-Katriina; Widen, Elisabeth; Taanila, Anja; Isohanni, Matti; Miettunen, Jouko; Palotie, Aarno; Penke, Lars; Service, Susan K.; Heath, Andrew C.; Montgomery, Grant W.; Raitakari, Olli; Kähönen, Mika; Viikari, Jorma; Räikkönen, Katri; Eriksson, Johan G; Keltikangas-Järvinen, Liisa; Lehtimäki, Terho; Martin, Nicholas G.; Järvelin, Marjo-Riitta; Visscher, Peter M.; Keller, Matthew C.; Zietsch, Brendan P.

2012-01-01

Personality traits are basic dimensions of behavioural variation, and twin, family, and adoption studies show that around 30% of the between-individual variation is due to genetic variation. There is rapidly-growing interest in understanding the evolutionary basis of this genetic variation. Several evolutionary mechanisms could explain how genetic variation is maintained in traits, and each of these makes predictions in terms of the relative contribution of rare and common genetic variants to personality variation, the magnitude of nonadditive genetic influences, and whether personality is affected by inbreeding. Using genome-wide SNP data from >8,000 individuals, we estimated that little variation in the Cloninger personality dimensions (7.2% on average) is due to the combined effect of common, additive genetic variants across the genome, suggesting that most heritable variation in personality is due to rare variant effects and/or a combination of dominance and epistasis. Furthermore, higher levels of inbreeding were associated with less socially-desirable personality trait levels in three of the four personality dimensions. These findings are consistent with genetic variation in personality traits having been maintained by mutation-selection balance. PMID:23025612

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

PubMed

Fawcett, Gloria L; Roseman, Charles C; Jarvis, Joseph P; Wang, Bing; Wolf, Jason B; Cheverud, James M

2008-08-01

We present here a detailed study of the genetic contributions to adult body size and adiposity in the LG,SM advanced intercross line (AIL), an obesity model. This study represents a first step in fine-mapping obesity quantitative trait loci (QTLs) in an AIL. QTLs for adiposity in this model were previously isolated to chromosomes 1, 6, 7, 8, 9, 12, 13, and 18. This study focuses on heritable contributions and the genetic architecture of fatpad and organ weights. We analyzed both the F(2) and F(3) generations of the LG,SM AIL population single-nucleotide polymorphism (SNP) genotyped with a marker density of approximately 4 cM. We replicate 88% of the previously identified obesity QTLs and identify 13 new obesity QTLs. Nearly half of the single-trait QTLs were sex-specific. Several broad QTL regions were resolved into multiple, narrower peaks. The 113 single-trait QTLs for organs and body weight clustered into 27 pleiotropic loci. A large number of epistatic interactions are described which begin to elucidate potential interacting molecular networks. We present a relatively rapid means to obtain fine-mapping details from AILs using dense marker maps and consecutive generations. Analysis of the complex genetic architecture underlying fatpad and organ weights in this model may eventually help to elucidate not only heritable contributions to obesity but also common gene sets for obesity and its comorbidities.

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

PubMed Central

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

2016-01-01

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

Defense traits in the long-lived Great Basin bristlecone pine and resistance to the native herbivore mountain pine beetle.

PubMed

Bentz, Barbara J; Hood, Sharon M; Hansen, E Matthew; Vandygriff, James C; Mock, Karen E

2017-01-01

Mountain pine beetle (MPB, Dendroctonus ponderosae) is a significant mortality agent of Pinus, and climate-driven range expansion is occurring. Pinus defenses in recently invaded areas, including high elevations, are predicted to be lower than in areas with longer term MPB presence. MPB was recently observed in high-elevation forests of the Great Basin (GB) region, North America. Defense and susceptibility in two long-lived species, GB bristlecone pine (Pinus longaeva) and foxtail pine (P. balfouriana), are unclear, although they are sympatric with a common MPB host, limber pine (P. flexilis). We surveyed stands with sympatric GB bristlecone-limber pine and foxtail-limber pine to determine relative MPB attack susceptibility and constitutive defenses. MPB-caused mortality was extensive in limber, low in foxtail and absent in GB bristlecone pine. Defense traits, including constitutive monoterpenes, resin ducts and wood density, were higher in GB bristlecone and foxtail than in limber pine. GB bristlecone and foxtail pines have relatively high levels of constitutive defenses which make them less vulnerable to climate-driven MPB range expansion relative to other high-elevation pines. Long-term selective herbivore pressure and exaptation of traits for tree longevity are potential explanations, highlighting the complexity of predicting plant-insect interactions under climate change. No claim to original US Government works. New Phytologist © 2016 New Phytologist Trust.

Identification of a novel locus associated with skin colour in African-admixed populations

PubMed Central

Hernandez-Pacheco, Natalia; Flores, Carlos; Alonso, Santos; Eng, Celeste; Mak, Angel C. Y.; Hunstman, Scott; Hu, Donglei; White, Marquitta J.; Oh, Sam S.; Meade, Kelley; Farber, Harold J.; Avila, Pedro C.; Serebrisky, Denise; Thyne, Shannon M.; Brigino-Buenaventura, Emerita; Rodriguez-Cintron, William; Sen, Saunak; Kumar, Rajesh; Lenoir, Michael; Rodriguez-Santana, Jose R.; Burchard, Esteban G.; Pino-Yanes, Maria

2017-01-01

Skin pigmentation is a complex trait that varies largely among populations. Most genome-wide association studies of this trait have been performed in Europeans and Asians. We aimed to uncover genes influencing skin colour in African-admixed individuals. We performed a genome-wide association study of melanin levels in 285 Hispanic/Latino individuals from Puerto Rico, analyzing 14 million genetic variants. A total of 82 variants with p-value ≤1 × 10−5 were followed up in 373 African Americans. Fourteen single nucleotide polymorphisms were replicated, of which nine were associated with skin colour at genome-wide significance in a meta-analysis across the two studies. These results validated the association of two previously known skin pigmentation genes, SLC24A5 (minimum p = 2.62 × 10−14, rs1426654) and SLC45A2 (minimum p = 9.71 × 10−10, rs16891982), and revealed the intergenic region of BEND7 and PRPF18 as a novel locus associated with this trait (minimum p = 4.58 × 10−9, rs6602666). The most significant variant within this region is common among African-descent populations but not among Europeans or Native Americans. Our findings support the advantages of analyzing African-admixed populations to discover new genes influencing skin pigmentation. PMID:28300201

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

PubMed

Morrow, Edward H; Connallon, Tim

2013-12-01

Mutation and selection are thought to shape the underlying genetic basis of many common human diseases. However, both processes depend on the context in which they occur, such as environment, genetic background, or sex. Sex has widely known effects on phenotypic expression of genotype, but an analysis of how it influences the evolutionary dynamics of disease-causing variants has not yet been explored. We develop a simple population genetic model of disease susceptibility and evaluate it using a biologically plausible empirically based distribution of fitness effects among contributing mutations. The model predicts that alleles under sex-differential selection, including sexually antagonistic alleles, will disproportionately contribute to genetic variation for disease predisposition, thereby generating substantial sexual dimorphism in the genetic architecture of complex (polygenic) diseases. This is because such alleles evolve into higher population frequencies for a given effect size, relative to alleles experiencing equally strong purifying selection in both sexes. Our results provide a theoretical justification for expecting a sexually dimorphic genetic basis for variation in complex traits such as disease. Moreover, they suggest that such dimorphism is interesting - not merely something to control for - because it reflects the action of natural selection in molding the evolution of common disease phenotypes.

Health and disease phenotyping in old age using a cluster network analysis.

PubMed

Valenzuela, Jesus Felix; Monterola, Christopher; Tong, Victor Joo Chuan; Ng, Tze Pin; Larbi, Anis

2017-11-15

Human ageing is a complex trait that involves the synergistic action of numerous biological processes that interact to form a complex network. Here we performed a network analysis to examine the interrelationships between physiological and psychological functions, disease, disability, quality of life, lifestyle and behavioural risk factors for ageing in a cohort of 3,270 subjects aged ≥55 years. We considered associations between numerical and categorical descriptors using effect-size measures for each variable pair and identified clusters of variables from the resulting pairwise effect-size network and minimum spanning tree. We show, by way of a correspondence analysis between the two sets of clusters, that they correspond to coarse-grained and fine-grained structure of the network relationships. The clusters obtained from the minimum spanning tree mapped to various conceptual domains and corresponded to physiological and syndromic states. Hierarchical ordering of these clusters identified six common themes based on interactions with physiological systems and common underlying substrates of age-associated morbidity and disease chronicity, functional disability, and quality of life. These findings provide a starting point for indepth analyses of ageing that incorporate immunologic, metabolomic and proteomic biomarkers, and ultimately offer low-level-based typologies of healthy and unhealthy ageing.

Epistasis in intra- and inter-gene pool crosses of the common bean.

PubMed

Borel, J C; Ramalho, M A P; Abreu, A F B

2016-02-26

Epistasis has been shown to have an important role in the genetic control of several quantitative traits in the common bean. This study aimed to investigate the occurrence of epistasis in intra- and inter-pool gene crosses of the common bean. Four elite lines adapted to Brazilian conditions were used as parents, two from the Andean gene pool (ESAL 686; BRS Radiante) and two from the Mesoamerican gene pool (BRSMG Majestoso; BRS Valente). Four F2 populations were obtained: "A" (ESAL 686 x BRS Radiante), "B" (BRSMG Majestoso x BRS Valente), "C" (BRS Radiante x BRSMG Majestoso), and "D" (BRS Valente x ESAL 686). A random sample of F2 plants from each population was backcrossed to parents and F1 individuals, according to the triple test cross. Three types of progenies from each population were evaluated in contiguous trials. Seed yield and 100-seed weight were evaluated. Dominance genetic variance was predominant in most cases. However, the estimates of genetic variance may be biased by the occurrence of linkage disequilibrium and epistasis. Epistasis was detected for both traits; however, the occurrence differed among the populations and between the two traits. The results of this study reinforce the hypothesis that epistasis is present in the genetic control of traits in the common bean and suggest that the phenomenon is more frequent in inter-gene pool crosses than in intra-gene pool crosses.

Estimation of heritability for nine common cancers using data from genome-wide association studies in Chinese population.

PubMed

Dai, Juncheng; Shen, Wei; Wen, Wanqing; Chang, Jiang; Wang, Tongmin; Chen, Haitao; Jin, Guangfu; Ma, Hongxia; Wu, Chen; Li, Lian; Song, Fengju; Zeng, YiXin; Jiang, Yue; Chen, Jiaping; Wang, Cheng; Zhu, Meng; Zhou, Wen; Du, Jiangbo; Xiang, Yongbing; Shu, Xiao-Ou; Hu, Zhibin; Zhou, Weiping; Chen, Kexin; Xu, Jianfeng; Jia, Weihua; Lin, Dongxin; Zheng, Wei; Shen, Hongbing

2017-01-15

The familial aggregation indicated the inheritance of cancer risk. Recent genome-wide association studies (GWASs) have identified a number of common single-nucleotide polymorphisms (SNPs). Following heritability analyses have shown that SNPs could explain a moderate amount of variance for different cancer phenotypes among Caucasians. However, little information was available in Chinese population. We performed a genome-wide complex trait analysis for common cancers at nine anatomical sites in Chinese population (14,629 cancer cases vs. 17,554 controls) and estimated the heritability of these cancers based on the common SNPs. We found that common SNPs explained certain amount of heritability with significance for all nine cancer sites: gastric cancer (20.26%), esophageal squamous cell carcinoma (19.86%), colorectal cancer (16.30%), lung cancer (LC) (15.17%), and epithelial ovarian cancer (13.31%), and a similar heritability around 10% for hepatitis B virus-related hepatocellular carcinoma, prostate cancer, breast cancer and nasopharyngeal carcinoma. We found that nearly or less than 25% change was shown when removing the regions expanding 250 kb or 500 kb upward and downward of the GWAS-reported SNPs. We also found strong linear correlations between variance partitioned by each chromosome and chromosomal length only for LC (R 2  = 0.641, p = 0.001) and esophageal squamous cell cancer (R 2  = 0.633, p = 0.002), which implied us the complex heterogeneity of cancers. These results indicate polygenic genetic architecture of the nine common cancers in Chinese population. Further efforts should be made to discover the hidden heritability of different cancer types among Chinese. © 2016 UICC.

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

A simple mathematical model of gradual Darwinian evolution: emergence of a Gaussian trait distribution in adaptation along a fitness gradient.

PubMed

Biktashev, Vadim N

2014-04-01

We consider a simple mathematical model of gradual Darwinian evolution in continuous time and continuous trait space, due to intraspecific competition for common resource in an asexually reproducing population in constant environment, while far from evolutionary stable equilibrium. The model admits exact analytical solution. In particular, Gaussian distribution of the trait emerges from generic initial conditions.

Perception of aesthetics and personality traits in orthognathic surgery patients: A comparison of still and moving images

PubMed Central

Tran, Ulrich S.; Wutzl, Arno; Seemann, Rudolf; Millesi, Gabriele; Jagsch, Reinhold

2018-01-01

It is common in practicing orthognathic surgery to evaluate faces with retruded or protruded chins (dysgnathic faces) using photographs. Because motion may alter how the face is perceived, we investigated the perception of faces presented via photographs and videos. Two hundred naïve raters (lay persons, without maxillo facial surgery background) evaluated 12 subjects with varying chin anatomy [so-called skeletal Class I (normal chin), Class II (retruded chin), and Class III (protruded chin)]. Starting from eight traits, with Factor analysis we found a two-Factor solution, i.e. an "aesthetics associated traits cluster" and a Factor "personality traits cluster" which appeared to be uncorrelated. Internal consistency of the Factors found for photographs and videos was excellent. Generally, female raters delivered better ratings than males, but the effect sizes were small. We analyzed differences and the respective effect magnitude between photograph and video perception. For each skeletal class the aesthetics associated dimensions were rated similarly between photographs and video clips. In contrast, specific personality traits were rated differently. Differences in the class-specific personality traits seen on photographs were "smoothed" in the assessment of videos, which implies that photos enhance stereotypes commonly attributed to a retruded or protruded chin. PMID:29775466

A trait-based approach to bacterial biofilms in soil.

PubMed

Lennon, Jay T; Lehmkuhl, Brent K

2016-09-01

A trait-based approach focuses on attributes of taxa that influence the structure and function of communities. Biofilm production is a common trait among microorganisms in a wide range of environmental, engineered, and host-associated ecosystems. Here, we used Pseudomonas aeruginosa to link biofilm production to moisture availability, a common stressor for microorganisms in soil. First, we demonstrate that biofilm production is a response trait that influences the desiccation phenotype by increasing survivorship, shifting the niche space, and reducing the minimum water potential needed to sustain a net-positive growth rate (Ψ*). Although the allocation of resources to biofilms is thought to be costly, we found no evidence for a trade-off between fitness and biofilm production along a soil moisture gradient. Second, we demonstrated that biofilm production is an effect trait. Specifically, biofilm production increased water retention in soils that were exposed to a series of drying and rewetting cycles. Although this form of niche construction should affect species interactions, we found no evidence that the benefits of biofilm production were extended to another co-occurring soil bacterium. Together, our results support the view that biofilm production is an important trait that may contribute to the distribution, abundance, and functioning of microorganisms in soils. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

Evolutionary and plastic responses of freshwater invertebrates to climate change: realized patterns and future potential

PubMed Central

Stoks, Robby; Geerts, Aurora N; De Meester, Luc

2014-01-01

We integrated the evidence for evolutionary and plastic trait changes in situ in response to climate change in freshwater invertebrates (aquatic insects and zooplankton). The synthesis on the trait changes in response to the expected reductions in hydroperiod and increases in salinity indicated little evidence for adaptive, plastic, and genetic trait changes and for local adaptation. With respect to responses to temperature, there are many studies on temporal trait changes in phenology and body size in the wild that are believed to be driven by temperature increases, but there is a general lack of rigorous demonstration whether these trait changes are genetically based, adaptive, and causally driven by climate change. Current proof for genetic trait changes under climate change in freshwater invertebrates stems from a limited set of common garden experiments replicated in time. Experimental thermal evolution experiments and common garden warming experiments associated with space-for-time substitutions along latitudinal gradients indicate that besides genetic changes, also phenotypic plasticity and evolution of plasticity are likely to contribute to the observed phenotypic changes under climate change in aquatic invertebrates. Apart from plastic and genetic thermal adjustments, also genetic photoperiod adjustments are widespread and may even dominate the observed phenological shifts. PMID:24454547

Divergence in Life History Traits between Two Populations of a Seed-Dimorphic Halophyte in Response to Soil Salinity

PubMed Central

Yang, Fan; Baskin, Jerry M.; Baskin, Carol C.; Yang, Xuejun; Cao, Dechang; Huang, Zhenying

2017-01-01

Production of heteromorphic seeds is common in halophytes growing in arid environments with strong spatial and temporal heterogeneity. However, evidence for geographic variation (reflecting local adaptation) is almost nonexistent. Our primary aims were to compare the life history traits of two desert populations of this halophytic summer annual Suaeda corniculata subsp. mongolica and to investigate the phenotypic response of its plant and heteromorphic seeds to different levels of salt stress. Dimorphic seeds (F1) of the halophyte S. corniculata collected from two distant populations (F0) that differ in soil salinity were grown in a common environment under different levels of salinity to minimize the carryover effects from the field environment and tested for variation in plant (F1) and seed (F2) traits. Compared to F1 plants grown in low soil salinity, those grown in high salinity (>0.2 mol⋅L-1) were smaller and produced fewer seeds but had a higher reproductive allocation and a higher non-dormant brown seed: dormant black seed ratio. High salinity during plant growth decreased germination percentage of F2 black seeds but had no effect on F2 brown seeds. Between population differences in life history traits in the common environment corresponded with those in the natural populations. Phenotypic differences between the two populations were retained in F1 plants and in F2 seeds in the common environment, which suggests that the traits are genetically based. Our results indicate that soil salinity plays an ecologically important role in population regeneration of S. corniculata by influencing heteromorphic seed production in the natural habitat. PMID:28670319

Genome-Wide Association Study among Four Horse Breeds Identifies a Common Haplotype Associated with In Vitro CD3+ T Cell Susceptibility/Resistance to Equine Arteritis Virus Infection ▿

PubMed Central

Go, Yun Young; Bailey, Ernest; Cook, Deborah G.; Coleman, Stephen J.; MacLeod, James N.; Chen, Kuey-Chu; Timoney, Peter J.; Balasuriya, Udeni B. R.

2011-01-01

Previously, we have shown that horses could be divided into susceptible and resistant groups based on an in vitro assay using dual-color flow cytometric analysis of CD3+ T cells infected with equine arteritis virus (EAV). Here, we demonstrate that the differences in in vitro susceptibility of equine CD3+ T lymphocytes to EAV infection have a genetic basis. To investigate the possible hereditary basis for this trait, we conducted a genome-wide association study (GWAS) to compare susceptible and resistant phenotypes. Testing of 267 DNA samples from four horse breeds that had a susceptible or a resistant CD3+ T lymphocyte phenotype using both Illumina Equine SNP50 BeadChip and Sequenom's MassARRAY system identified a common, genetically dominant haplotype associated with the susceptible phenotype in a region of equine chromosome 11 (ECA11), positions 49572804 to 49643932. The presence of a common haplotype indicates that the trait occurred in a common ancestor of all four breeds, suggesting that it may be segregated among other modern horse breeds. Biological pathway analysis revealed several cellular genes within this region of ECA11 encoding proteins associated with virus attachment and entry, cytoskeletal organization, and NF-κB pathways that may be associated with the trait responsible for the in vitro susceptibility/resistance of CD3+ T lymphocytes to EAV infection. The data presented in this study demonstrated a strong association of genetic markers with the trait, representing de facto proof that the trait is under genetic control. To our knowledge, this is the first GWAS of an equine infectious disease and the first GWAS of equine viral arteritis. PMID:21994447

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

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.

Seahorse Brood Pouch Transcriptome Reveals Common Genes Associated with Vertebrate Pregnancy.

PubMed

Whittington, Camilla M; Griffith, Oliver W; Qi, Weihong; Thompson, Michael B; Wilson, Anthony B

2015-12-01

Viviparity (live birth) has evolved more than 150 times in vertebrates, and represents an excellent model system for studying the evolution of complex traits. There are at least 23 independent origins of viviparity in fishes, with syngnathid fishes (seahorses and pipefish) unique in exhibiting male pregnancy. Male seahorses and pipefish have evolved specialized brooding pouches that provide protection, gas exchange, osmoregulation, and limited nutrient provisioning to developing embryos. Pouch structures differ widely across the Syngnathidae, offering an ideal opportunity to study the evolution of reproductive complexity. However, the physiological and genetic changes facilitating male pregnancy are largely unknown. We used transcriptome profiling to examine pouch gene expression at successive gestational stages in a syngnathid with the most complex brood pouch morphology, the seahorse Hippocampus abdominalis. Using a unique time-calibrated RNA-seq data set including brood pouch at key stages of embryonic development, we identified transcriptional changes associated with brood pouch remodeling, nutrient and waste transport, gas exchange, osmoregulation, and immunological protection of developing embryos at conception, development and parturition. Key seahorse transcripts share homology with genes of reproductive function in pregnant mammals, reptiles, and other live-bearing fish, suggesting a common toolkit of genes regulating pregnancy in divergent evolutionary lineages. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A common brain network among state, trait, and pathological anxiety from whole-brain functional connectivity.

PubMed

Takagi, Yu; Sakai, Yuki; Abe, Yoshinari; Nishida, Seiji; Harrison, Ben J; Martínez-Zalacaín, Ignacio; Soriano-Mas, Carles; Narumoto, Jin; Tanaka, Saori C

2018-05-15

Anxiety is one of the most common mental states of humans. Although it drives us to avoid frightening situations and to achieve our goals, it may also impose significant suffering and burden if it becomes extreme. Because we experience anxiety in a variety of forms, previous studies investigated neural substrates of anxiety in a variety of ways. These studies revealed that individuals with high state, trait, or pathological anxiety showed altered neural substrates. However, no studies have directly investigated whether the different dimensions of anxiety share a common neural substrate, despite its theoretical and practical importance. Here, we investigated a brain network of anxiety shared by different dimensions of anxiety in a unified analytical framework using functional magnetic resonance imaging (fMRI). We analyzed different datasets in a single scale, which was defined by an anxiety-related brain network derived from whole brain. We first conducted the anxiety provocation task with healthy participants who tended to feel anxiety related to obsessive-compulsive disorder (OCD) in their daily life. We found a common state anxiety brain network across participants (1585 trials obtained from 10 participants). Then, using the resting-state fMRI in combination with the participants' behavioral trait anxiety scale scores (879 participants from the Human Connectome Project), we demonstrated that trait anxiety shared the same brain network as state anxiety. Furthermore, the brain network between common to state and trait anxiety could detect patients with OCD, which is characterized by pathological anxiety-driven behaviors (174 participants from multi-site datasets). Our findings provide direct evidence that different dimensions of anxiety have a substantial biological inter-relationship. Our results also provide a biologically defined dimension of anxiety, which may promote further investigation of various human characteristics, including psychiatric disorders, from the perspective of anxiety. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Genetic risk for attention-deficit/hyperactivity disorder contributes to neurodevelopmental traits in the general population.

PubMed

Martin, Joanna; Hamshere, Marian L; Stergiakouli, Evangelia; O'Donovan, Michael C; Thapar, Anita

2014-10-15

Attention-deficit/hyperactivity disorder (ADHD) can be viewed as the extreme end of traits in the general population. Epidemiological and twin studies suggest that ADHD frequently co-occurs with and shares genetic susceptibility with autism spectrum disorder (ASD) and ASD-related traits. The aims of this study were to determine whether a composite of common molecular genetic variants, previously found to be associated with clinically diagnosed ADHD, predicts ADHD and ASD-related traits in the general population. Polygenic risk scores were calculated in the Avon Longitudinal Study of Parents and Children (ALSPAC) population sample (N = 8229) based on a discovery case-control genome-wide association study of childhood ADHD. Regression analyses were used to assess whether polygenic scores predicted ADHD traits and ASD-related measures (pragmatic language abilities and social cognition) in the ALSPAC sample. Polygenic scores were also compared in boys and girls endorsing any (rating ≥ 1) ADHD item (n = 3623). Polygenic risk for ADHD showed a positive association with ADHD traits (hyperactive-impulsive, p = .0039; inattentive, p = .037). Polygenic risk for ADHD was also negatively associated with pragmatic language abilities (p = .037) but not with social cognition (p = .43). In children with a rating ≥ 1 for ADHD traits, girls had a higher polygenic score than boys (p = .003). These findings provide molecular genetic evidence that risk alleles for the categorical disorder of ADHD influence hyperactive-impulsive and attentional traits in the general population. The results further suggest that common genetic variation that contributes to ADHD diagnosis may also influence ASD-related traits, which at their extreme are a characteristic feature of ASD. Copyright © 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

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

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

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

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.

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.

A methodology for multivariate phenotype-based genome-wide association studies to mine pleiotropic genes.

PubMed

Park, Sung Hee; Lee, Ji Young; Kim, Sangsoo

2011-01-01

Current Genome-Wide Association Studies (GWAS) are performed in a single trait framework without considering genetic correlations between important disease traits. Hence, the GWAS have limitations in discovering genetic risk factors affecting pleiotropic effects. This work reports a novel data mining approach to discover patterns of multiple phenotypic associations over 52 anthropometric and biochemical traits in KARE and a new analytical scheme for GWAS of multivariate phenotypes defined by the discovered patterns. This methodology applied to the GWAS for multivariate phenotype highLDLhighTG derived from the predicted patterns of the phenotypic associations. The patterns of the phenotypic associations were informative to draw relations between plasma lipid levels with bone mineral density and a cluster of common traits (Obesity, hypertension, insulin resistance) related to Metabolic Syndrome (MS). A total of 15 SNPs in six genes (PAK7, C20orf103, NRIP1, BCL2, TRPM3, and NAV1) were identified for significant associations with highLDLhighTG. Noteworthy findings were that the significant associations included a mis-sense mutation (PAK7:R335P), a frame shift mutation (C20orf103) and SNPs in splicing sites (TRPM3). The six genes corresponded to rat and mouse quantitative trait loci (QTLs) that had shown associations with the common traits such as the well characterized MS and even tumor susceptibility. Our findings suggest that the six genes may play important roles in the pleiotropic effects on lipid metabolism and the MS, which increase the risk of Type 2 Diabetes and cardiovascular disease. The use of the multivariate phenotypes can be advantageous in identifying genetic risk factors, accounting for the pleiotropic effects when the multivariate phenotypes have a common etiological pathway.

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).

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

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.

Intraspecific variation in stomatal traits, leaf traits and physiology reflects adaptation along aridity gradients in a South African shrub

PubMed Central

Carlson, Jane E.; Adams, Christopher A.; Holsinger, Kent E.

2016-01-01

Background and Aims Trait–environment relationships are commonly interpreted as evidence for local adaptation in plants. However, even when selection analyses support this interpretation, the mechanisms underlying differential benefits are often unknown. This study addresses this gap in knowledge using the broadly distributed South African shrub Protea repens. Specifically, the study examines whether broad-scale patterns of trait variation are consistent with spatial differences in selection and ecophysiology in the wild. Methods In a common garden study of plants sourced from 19 populations, associations were measured between five morphological traits and three axes describing source climates. Trait–trait and trait–environment associations were analysed in a multi-response model. Within two focal populations in the wild, selection and path analyses were used to test associations between traits, fecundity and physiological performance. Key Results Across 19 populations in a common garden, stomatal density increased with the source population’s mean annual temperature and decreased with its average amount of rainfall in midsummer. Concordantly, selection analysis in two natural populations revealed positive selection on stomatal density at the hotter, drier site, while failing to detect selection at the cooler, moister site. Dry-site plants with high stomatal density also had higher stomatal conductances, cooler leaf temperatures and higher light-saturated photosynthetic rates than those with low stomatal density, but no such relationships were present among wet-site plants. Leaf area, stomatal pore index and specific leaf area in the garden also co-varied with climate, but within-population differences were not associated with fitness in either wild population. Conclusions The parallel patterns of broad-scale variation, differences in selection and differences in trait–ecophysiology relationships suggest a mechanism for adaptive differentiation in stomatal density. Densely packed stomata may improve performance by increasing transpiration and cooling, but predominately in drier, hotter climates. This study uniquely shows context-dependent benefits of stomatal density – a trait rarely linked to local adaptation in plants. PMID:26424782

Heritability estimates of the Big Five personality traits based on common genetic variants.

PubMed

Power, R A; Pluess, M

2015-07-14

According to twin studies, the Big Five personality traits have substantial heritable components explaining 40-60% of the variance, but identification of associated genetic variants has remained elusive. Consequently, knowledge regarding the molecular genetic architecture of personality and to what extent it is shared across the different personality traits is limited. Using genomic-relatedness-matrix residual maximum likelihood analysis (GREML), we here estimated the heritability of the Big Five personality factors (extraversion, agreeableness, conscientiousness, neuroticism and openness for experience) in a sample of 5011 European adults from 527,469 single-nucleotide polymorphisms across the genome. We tested for the heritability of each personality trait, as well as for the genetic overlap between the personality factors. We found significant and substantial heritability estimates for neuroticism (15%, s.e. = 0.08, P = 0.04) and openness (21%, s.e. = 0.08, P < 0.01), but not for extraversion, agreeableness and conscientiousness. The bivariate analyses showed that the variance explained by common variants entirely overlapped between neuroticism and openness (rG = 1.00, P < 0.001), despite low phenotypic correlation (r = - 0.09, P < 0.001), suggesting that the remaining unique heritability may be determined by rare or structural variants. As far as we are aware of, this is the first study estimating the shared and unique heritability of all Big Five personality traits using the GREML approach. Findings should be considered exploratory and suggest that detectable heritability estimates based on common variants is shared between neuroticism and openness to experiences.

Analysis of QTLs for yield-related traits in Yuanjiang common wild rice (Oryza rufipogon Griff.).

PubMed

Fu, Qiang; Zhang, Peijiang; Tan, Lubin; Zhu, Zuofeng; Ma, Dan; Fu, Yongcai; Zhan, Xinchun; Cai, Hongwei; Sun, Chuanqing

2010-02-01

Using an accession of common wild rice (Oryza rufipogon Griff.) collected from Yuanjiang County, Yunnan Province, China, as the donor and an elite cultivar 93-11, widely used in two-line indica hybrid rice production in China, as the recurrent parent, an advanced backcross populations were developed. Through genotyping of 187 SSR markers and investigation of six yield-related traits of two generations (BC(4)F(2) and BC(4)F(4)), a total of 26 QTLs were detected by employing single point analysis and interval mapping in both generations. Of the 26 QTLs, the alleles of 10 (38.5%) QTLs originating from O. rufipogon had shown a beneficial effect for yield-related traits in the 93-11 genetic background. In addition, five QTLs controlling yield and its components were newly identified, indicating that there are potentially novel alleles in Yuanjiang common wild rice. Three regions underling significant QTLs for several yield-related traits were detected on chromosome 1, 7 and 12. The QTL clusters were founded and corresponding agronomic traits of those QTLs showed highly significant correlation, suggesting the pleiotropism or tight linkage. Fine-mapping and cloning of these yield-related QTLs from wild rice would be helpful to elucidating molecular mechanism of rice domestication and rice breeding in the future. Copyright 2010 Institute of Genetics and Developmental Biology and the Genetics Society of China. Published by Elsevier Ltd. All rights reserved.

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.

Assessing the genetic overlap between BMI and cognitive function

PubMed Central

Marioni, R E; Yang, J; Dykiert, D; Mõttus, R; Campbell, A; Ibrahim-Verbaas, Carla A; Bressler, Jan; Debette, Stephanie; Schuur, Maaike; Smith, Albert V; Davies, Gail; Bennett, David A; Deary, Ian J; Ikram, M Arfan; Launer, Lenore J; Fitzpatrick, Annette L; Seshadri, Sudha; van Duijn, Cornelia M; Mosely Jr, Thomas H; Davies, G; Hayward, C; Porteous, D J; Visscher, P M; Deary, I J

2016-01-01

Obesity and low cognitive function are associated with multiple adverse health outcomes across the life course. They have a small phenotypic correlation (r=−0.11; high body mass index (BMI)−low cognitive function), but whether they have a shared genetic aetiology is unknown. We investigated the phenotypic and genetic correlations between the traits using data from 6815 unrelated, genotyped members of Generation Scotland, an ethnically homogeneous cohort from five sites across Scotland. Genetic correlations were estimated using the following: same-sample bivariate genome-wide complex trait analysis (GCTA)–GREML; independent samples bivariate GCTA–GREML using Generation Scotland for cognitive data and four other samples (n=20 806) for BMI; and bivariate LDSC analysis using the largest genome-wide association study (GWAS) summary data on cognitive function (n=48 462) and BMI (n=339 224) to date. The GWAS summary data were also used to create polygenic scores for the two traits, with within- and cross-trait prediction taking place in the independent Generation Scotland cohort. A large genetic correlation of −0.51 (s.e. 0.15) was observed using the same-sample GCTA–GREML approach compared with −0.10 (s.e. 0.08) from the independent-samples GCTA–GREML approach and −0.22 (s.e. 0.03) from the bivariate LDSC analysis. A genetic profile score using cognition-specific genetic variants accounts for 0.08% (P=0.020) of the variance in BMI and a genetic profile score using BMI-specific variants accounts for 0.42% (P=1.9 × 10−7) of the variance in cognitive function. Seven common genetic variants are significantly associated with both traits at P<5 × 10−5, which is significantly more than expected by chance (P=0.007). All these results suggest there are shared genetic contributions to BMI and cognitive function. PMID:26857597

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

Job Performance: Improvement Needed

ERIC Educational Resources Information Center

Goodman, Jacob

1974-01-01

Personnel directors of 38 business firms responded to a questionnaire rating 24 employee traits related to competencies, attitudes, skills, and personality which needed improvement. Five traits were common among the rank order one to five to both retailer and commercial and service organization respondents: oral communication, initiative,…

Integrating competing dimensional models of personality: linking the SNAP, TCI, and NEO using Item Response Theory.

PubMed

Stepp, Stephanie D; Yu, Lan; Miller, Joshua D; Hallquist, Michael N; Trull, Timothy J; Pilkonis, Paul A

2012-04-01

Mounting evidence suggests that several inventories assessing both normal personality and personality disorders measure common dimensional personality traits (i.e., Antagonism, Constraint, Emotional Instability, Extraversion, and Unconventionality), albeit providing unique information along the underlying trait continuum. We used Widiger and Simonsen's (2005) pantheoretical integrative model of dimensional personality assessment as a guide to create item pools. We then used Item Response Theory (IRT) to compare the assessment of these five personality traits across three established dimensional measures of personality: the Schedule for Nonadaptive and Adaptive Personality (SNAP), the Temperament and Character Inventory (TCI), and the Revised NEO Personality Inventory (NEO PI-R). We found that items from each inventory map onto these five common personality traits in predictable ways. The IRT analyses, however, documented considerable variability in the item and test information derived from each inventory. Our findings support the notion that the integration of multiple perspectives will provide greater information about personality while minimizing the weaknesses of any single instrument.

Integrating Competing Dimensional Models of Personality: Linking the SNAP, TCI, and NEO Using Item Response Theory

PubMed Central

Stepp, Stephanie D.; Yu, Lan; Miller, Joshua D.; Hallquist, Michael N.; Trull, Timothy J.; Pilkonis, Paul A.

2013-01-01

Mounting evidence suggests that several inventories assessing both normal personality and personality disorders measure common dimensional personality traits (i.e., Antagonism, Constraint, Emotional Instability, Extraversion, and Unconventionality), albeit providing unique information along the underlying trait continuum. We used Widiger and Simonsen’s (2005) pantheoretical integrative model of dimensional personality assessment as a guide to create item pools. We then used Item Response Theory (IRT) to compare the assessment of these five personality traits across three established dimensional measures of personality: the Schedule for Nonadaptive and Adaptive Personality (SNAP), the Temperament and Character Inventory (TCI), and the Revised NEO Personality Inventory (NEO PI-R). We found that items from each inventory map onto these five common personality traits in predictable ways. The IRT analyses, however, documented considerable variability in the item and test information derived from each inventory. Our findings support the notion that the integration of multiple perspectives will provide greater information about personality while minimizing the weaknesses of any single instrument. PMID:22452759

An efficient genome-wide association test for multivariate phenotypes based on the Fisher combination function.

PubMed

Yang, James J; Li, Jia; Williams, L Keoki; Buu, Anne

2016-01-05

In genome-wide association studies (GWAS) for complex diseases, the association between a SNP and each phenotype is usually weak. Combining multiple related phenotypic traits can increase the power of gene search and thus is a practically important area that requires methodology work. This study provides a comprehensive review of existing methods for conducting GWAS on complex diseases with multiple phenotypes including the multivariate analysis of variance (MANOVA), the principal component analysis (PCA), the generalizing estimating equations (GEE), the trait-based association test involving the extended Simes procedure (TATES), and the classical Fisher combination test. We propose a new method that relaxes the unrealistic independence assumption of the classical Fisher combination test and is computationally efficient. To demonstrate applications of the proposed method, we also present the results of statistical analysis on the Study of Addiction: Genetics and Environment (SAGE) data. Our simulation study shows that the proposed method has higher power than existing methods while controlling for the type I error rate. The GEE and the classical Fisher combination test, on the other hand, do not control the type I error rate and thus are not recommended. In general, the power of the competing methods decreases as the correlation between phenotypes increases. All the methods tend to have lower power when the multivariate phenotypes come from long tailed distributions. The real data analysis also demonstrates that the proposed method allows us to compare the marginal results with the multivariate results and specify which SNPs are specific to a particular phenotype or contribute to the common construct. The proposed method outperforms existing methods in most settings and also has great applications in GWAS on complex diseases with multiple phenotypes such as the substance abuse disorders.

A comparison of graph- and kernel-based -omics data integration algorithms for classifying complex traits.

PubMed

Yan, Kang K; Zhao, Hongyu; Pang, Herbert

2017-12-06

High-throughput sequencing data are widely collected and analyzed in the study of complex diseases in quest of improving human health. Well-studied algorithms mostly deal with single data source, and cannot fully utilize the potential of these multi-omics data sources. In order to provide a holistic understanding of human health and diseases, it is necessary to integrate multiple data sources. Several algorithms have been proposed so far, however, a comprehensive comparison of data integration algorithms for classification of binary traits is currently lacking. In this paper, we focus on two common classes of integration algorithms, graph-based that depict relationships with subjects denoted by nodes and relationships denoted by edges, and kernel-based that can generate a classifier in feature space. Our paper provides a comprehensive comparison of their performance in terms of various measurements of classification accuracy and computation time. Seven different integration algorithms, including graph-based semi-supervised learning, graph sharpening integration, composite association network, Bayesian network, semi-definite programming-support vector machine (SDP-SVM), relevance vector machine (RVM) and Ada-boost relevance vector machine are compared and evaluated with hypertension and two cancer data sets in our study. In general, kernel-based algorithms create more complex models and require longer computation time, but they tend to perform better than graph-based algorithms. The performance of graph-based algorithms has the advantage of being faster computationally. The empirical results demonstrate that composite association network, relevance vector machine, and Ada-boost RVM are the better performers. We provide recommendations on how to choose an appropriate algorithm for integrating data from multiple sources.

Association between the serotonin transporter promoter polymorphism and personality traits in a primarily female population sample.

PubMed

Greenberg, B D; Li, Q; Lucas, F R; Hu, S; Sirota, L A; Benjamin, J; Lesch, K P; Hamer, D; Murphy, D L

2000-04-03

The serotonin transporter (5-HTT) regulates serotonergic neurotransmission and is thought to influence emotion. A 5-HTT-linked polymorphic region (5-HTTLPR) has two common variants, short (s) and long (l). We previously found population and within-family associations between the lower-expressing s allele and neuroticism, a trait related to anxiety, hostility, and depression, on a standard measure (the NEO Personality Inventory, Revised [NEO-PI-R]) in a primarily male population (n=505), and that the s allele was dominant. We investigated this association in a new sample (n=397, 84% female, primarily sib-pairs). The results robustly replicated the 5-HTTLPR neuroticism association, and the dominance of the s allele. Combined data from the two studies (n=902) showed a highly significant association between the s allele and higher NEO Neuroticism both across individuals and within families. Association between genotype and a related measure, Anxiety on the 16PF inventory, was replicated in the new population and within families in the combined sample. Association to another trait, estimated TPQ Harm Avoidance, was not replicated in the new sample but found only within the combined sibship group. Another association found in our original study, between the s allele and lower scores on NEO-PI-R Agreeableness, was also replicated and was more robust in the current and the combined samples. Associations between the functional 5-HTTLPR polymorphism were similar in women and men. These results help to define specific personality features reproducibly associated with 5-HTTLPR genotype. Such associations were strongest for traits defined by the NEO, enhancing the attractiveness of the five-factor personality model in genetic research on complex behavioral dimensions. Am. J. Med. Genet. (Neuropsychiatr. Genet.) 96:202-216, 2000. Published 2000 Wiley-Liss, Inc.

A trait based perspective on the biogeography of common and abundant marine bacterioplankton clades.

PubMed

Brown, Mark V; Ostrowski, Martin; Grzymski, Joseph J; Lauro, Federico M

2014-06-01

Marine microbial communities provide much of the energy upon which all higher trophic levels depend, particularly in open-ocean and oligotrophic systems, and play a pivotal role in biogeochemical cycling. How and why species are distributed in the global oceans, and whether net ecosystem function can be accurately predicted from community composition are fundamental questions for marine scientists. Many of the most abundant clades of marine bacteria, including the Prochlorococcus, Synechococcus, SAR11, SAR86 and Roseobacter, have a very broad, if not a cosmopolitan distribution. However this is not reflected in an underlying genetic identity. Rather, widespread distribution in these organisms is achieved by the existence of closely related but discrete ecotypes that display niche adaptations. Closely related ecotypes display specific nutritional or energy generating mechanisms and are adapted to different physical parameters including temperature, salinity, and hydrostatic pressure. Furthermore, biotic phenomena such as selective grazing and viral loss contribute to the success or failure of ecotypes allowing some to compete effectively in particular marine provinces but not in others. An additional layer of complexity is added by ocean currents and hydrodynamic specificity of water body masses that bound microbial dispersal and immigration. These vary in space and time with respect to intensity and direction, making the definition of large biogeographic provinces problematic. A deterministic theory aimed at understanding how all these factors shape microbial life in the oceans can only proceed through analysis of microbial traits, rather than pure phylogenetic assessments. Trait based approaches seek mechanistic explanations for the observed temporal and spatial patterns. This review will present successful recent advances in phylogenetic and trait based biogeographic analyses in some of the most abundant marine taxa. Copyright © 2014. Published by Elsevier B.V.

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

Autonomy and integration in complex parasite life cycles.

PubMed

Benesh, Daniel P

2016-12-01

Complex life cycles are common in free-living and parasitic organisms alike. The adaptive decoupling hypothesis postulates that separate life cycle stages have a degree of developmental and genetic autonomy, allowing them to be independently optimized for dissimilar, competing tasks. That is, complex life cycles evolved to facilitate functional specialization. Here, I review the connections between the different stages in parasite life cycles. I first examine evolutionary connections between life stages, such as the genetic coupling of parasite performance in consecutive hosts, the interspecific correlations between traits expressed in different hosts, and the developmental and functional obstacles to stage loss. Then, I evaluate how environmental factors link life stages through carryover effects, where stressful larval conditions impact parasites even after transmission to a new host. There is evidence for both autonomy and integration across stages, so the relevant question becomes how integrated are parasite life cycles and through what mechanisms? By highlighting how genetics, development, selection and the environment can lead to interdependencies among successive life stages, I wish to promote a holistic approach to studying complex life cycle parasites and emphasize that what happens in one stage is potentially highly relevant for later stages.

Spontaneous Trait Inferences on Social Media.

PubMed

Levordashka, Ana; Utz, Sonja

2017-01-01

The present research investigates whether spontaneous trait inferences occur under conditions characteristic of social media and networking sites: nonextreme, ostensibly self-generated content, simultaneous presentation of multiple cues, and self-paced browsing. We used an established measure of trait inferences (false recognition paradigm) and a direct assessment of impressions. Without being asked to do so, participants spontaneously formed impressions of people whose status updates they saw. Our results suggest that trait inferences occurred from nonextreme self-generated content, which is commonly found in social media updates (Experiment 1) and when nine status updates from different people were presented in parallel (Experiment 2). Although inferences did occur during free browsing, the results suggest that participants did not necessarily associate the traits with the corresponding status update authors (Experiment 3). Overall, the findings suggest that spontaneous trait inferences occur on social media. We discuss implications for online communication and research on spontaneous trait inferences.

Refining Trait Resilience: Identifying Engineering, Ecological, and Adaptive Facets from Extant Measures of Resilience

PubMed Central

Maltby, John; Day, Liz; Hall, Sophie

2015-01-01

The current paper presents a new measure of trait resilience derived from three common mechanisms identified in ecological theory: Engineering, Ecological and Adaptive (EEA) resilience. Exploratory and confirmatory factor analyses of five existing resilience scales suggest that the three trait resilience facets emerge, and can be reduced to a 12-item scale. The conceptualization and value of EEA resilience within the wider trait and well-being psychology is illustrated in terms of differing relationships with adaptive expressions of the traits of the five-factor personality model and the contribution to well-being after controlling for personality and coping, or over time. The current findings suggest that EEA resilience is a useful and parsimonious model and measure of trait resilience that can readily be placed within wider trait psychology and that is found to contribute to individual well-being. PMID:26132197

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

Evolution of plant growth and defense in a continental introduction.

PubMed

Agrawal, Anurag A; Hastings, Amy P; Bradburd, Gideon S; Woods, Ellen C; Züst, Tobias; Harvey, Jeffrey A; Bukovinszky, Tibor

2015-07-01

Substantial research has addressed adaptation of nonnative biota to novel environments, yet surprisingly little work has integrated population genetic structure and the mechanisms underlying phenotypic differentiation in ecologically important traits. We report on studies of the common milkweed Asclepias syriaca, which was introduced from North America to Europe over the past 400 years and which lacks most of its specialized herbivores in the introduced range. Using 10 populations from each continent grown in a common environment, we identified several growth and defense traits that have diverged, despite low neutral genetic differentiation between continents. We next developed a Bayesian modeling approach to account for relationships between molecular and phenotypic differences, confirming that continental trait differentiation was greater than expected from neutral genetic differentiation. We found evidence that growth-related traits adaptively diverged within and between continents. Inducible defenses triggered by monarch butterfly herbivory were substantially reduced in European populations, and this reduction in inducibility was concordant with altered phytohormonal dynamics, reduced plant growth, and a trade-off with constitutive investment. Freedom from the community of native and specialized herbivores may have favored constitutive over induced defense. Our replicated analysis of plant growth and defense, including phenotypically plastic traits, suggests adaptive evolution following a continental introduction.

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

Aberrant Gene Expression in Humans

PubMed Central

Yang, Ence; Ji, Guoli; Brinkmeyer-Langford, Candice L.; Cai, James J.

2015-01-01

Gene expression as an intermediate molecular phenotype has been a focus of research interest. In particular, studies of expression quantitative trait loci (eQTL) have offered promise for understanding gene regulation through the discovery of genetic variants that explain variation in gene expression levels. Existing eQTL methods are designed for assessing the effects of common variants, but not rare variants. Here, we address the problem by establishing a novel analytical framework for evaluating the effects of rare or private variants on gene expression. Our method starts from the identification of outlier individuals that show markedly different gene expression from the majority of a population, and then reveals the contributions of private SNPs to the aberrant gene expression in these outliers. Using population-scale mRNA sequencing data, we identify outlier individuals using a multivariate approach. We find that outlier individuals are more readily detected with respect to gene sets that include genes involved in cellular regulation and signal transduction, and less likely to be detected with respect to the gene sets with genes involved in metabolic pathways and other fundamental molecular functions. Analysis of polymorphic data suggests that private SNPs of outlier individuals are enriched in the enhancer and promoter regions of corresponding aberrantly-expressed genes, suggesting a specific regulatory role of private SNPs, while the commonly-occurring regulatory genetic variants (i.e., eQTL SNPs) show little evidence of involvement. Additional data suggest that non-genetic factors may also underlie aberrant gene expression. Taken together, our findings advance a novel viewpoint relevant to situations wherein common eQTLs fail to predict gene expression when heritable, rare inter-individual variation exists. The analytical framework we describe, taking into consideration the reality of differential phenotypic robustness, may be valuable for investigating complex traits and conditions. PMID:25617623

Genome-wide association analysis in dogs implicates 99 loci as risk variants for anterior cruciate ligament rupture

PubMed Central

Baker, Lauren A.; Kirkpatrick, Brian; Rosa, Guilherme J. M.; Gianola, Daniel; Valente, Bruno; Sumner, Julia P.; Baltzer, Wendy; Hao, Zhengling; Binversie, Emily E.; Volstad, Nicola; Piazza, Alexander; Sample, Susannah J.

2017-01-01

Anterior cruciate ligament (ACL) rupture is a common condition that can be devastating and life changing, particularly in young adults. A non-contact mechanism is typical. Second ACL ruptures through rupture of the contralateral ACL or rupture of a graft repair is also common. Risk of rupture is increased in females. ACL rupture is also common in dogs. Disease prevalence exceeds 5% in several dog breeds, ~100 fold higher than human beings. We provide insight into the genetic etiology of ACL rupture by genome-wide association study (GWAS) in a high-risk breed using 98 case and 139 control Labrador Retrievers. We identified 129 single nucleotide polymorphisms (SNPs) within 99 risk loci. Associated loci (P<5E-04) explained approximately half of phenotypic variance in the ACL rupture trait. Two of these loci were located in uncharacterized or non-coding regions of the genome. A chromosome 24 locus containing nine genes with diverse functions met genome-wide significance (P = 3.63E-0.6). GWAS pathways were enriched for c-type lectins, a gene set that includes aggrecan, a gene set encoding antimicrobial proteins, and a gene set encoding membrane transport proteins with a variety of physiological functions. Genotypic risk estimated for each dog based on the risk contributed by each GWAS locus showed clear separation of ACL rupture cases and controls. Power analysis of the GWAS data set estimated that ~172 loci explain the genetic contribution to ACL rupture in the Labrador Retriever. Heritability was estimated at 0.48. We conclude ACL rupture is a moderately heritable highly polygenic complex trait. Our results implicate c-type lectin pathways in ACL homeostasis. PMID:28379989

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

Recent Mitochondrial DNA Mutations Increase the Risk of Developing Common Late-Onset Human Diseases

PubMed Central

Hudson, Gavin; Gomez-Duran, Aurora; Wilson, Ian J.; Chinnery, Patrick F.

2014-01-01

Mitochondrial DNA (mtDNA) is highly polymorphic at the population level, and specific mtDNA variants affect mitochondrial function. With emerging evidence that mitochondrial mechanisms are central to common human diseases, it is plausible that mtDNA variants contribute to the “missing heritability” of several complex traits. Given the central role of mtDNA genes in oxidative phosphorylation, the same genetic variants would be expected to alter the risk of developing several different disorders, but this has not been shown to date. Here we studied 38,638 individuals with 11 major diseases, and 17,483 healthy controls. Imputing missing variants from 7,729 complete mitochondrial genomes, we captured 40.41% of European mtDNA variation. We show that mtDNA variants modifying the risk of developing one disease also modify the risk of developing other diseases, thus providing independent replication of a disease association in different case and control cohorts. High-risk alleles were more common than protective alleles, indicating that mtDNA is not at equilibrium in the human population, and that recent mutations interact with nuclear loci to modify the risk of developing multiple common diseases. PMID:24852434

Common Variant Burden Contributes to the Familial Aggregation of Migraine in 1,589 Families.

PubMed

Gormley, Padhraig; Kurki, Mitja I; Hiekkala, Marjo Eveliina; Veerapen, Kumar; Häppölä, Paavo; Mitchell, Adele A; Lal, Dennis; Palta, Priit; Surakka, Ida; Kaunisto, Mari Anneli; Hämäläinen, Eija; Vepsäläinen, Salli; Havanka, Hannele; Harno, Hanna; Ilmavirta, Matti; Nissilä, Markku; Säkö, Erkki; Sumelahti, Marja-Liisa; Liukkonen, Jarmo; Sillanpää, Matti; Metsähonkala, Liisa; Koskinen, Seppo; Lehtimäki, Terho; Raitakari, Olli; Männikkö, Minna; Ran, Caroline; Belin, Andrea Carmine; Jousilahti, Pekka; Anttila, Verneri; Salomaa, Veikko; Artto, Ville; Färkkilä, Markus; Runz, Heiko; Daly, Mark J; Neale, Benjamin M; Ripatti, Samuli; Kallela, Mikko; Wessman, Maija; Palotie, Aarno

2018-05-16

Complex traits, including migraine, often aggregate in families, but the underlying genetic architecture behind this is not well understood. The aggregation could be explained by rare, penetrant variants that segregate according to Mendelian inheritance or by the sufficient polygenic accumulation of common variants, each with an individually small effect, or a combination of the two hypotheses. In 8,319 individuals across 1,589 migraine families, we calculated migraine polygenic risk scores (PRS) and found a significantly higher common variant burden in familial cases (n = 5,317, OR = 1.76, 95% CI = 1.71-1.81, p = 1.7 × 10 -109 ) compared to population cases from the FINRISK cohort (n = 1,101, OR = 1.32, 95% CI = 1.25-1.38, p = 7.2 × 10 -17 ). The PRS explained 1.6% of the phenotypic variance in the population cases and 3.5% in the familial cases (including 2.9% for migraine without aura, 5.5% for migraine with typical aura, and 8.2% for hemiplegic migraine). The results demonstrate a significant contribution of common polygenic variation to the familial aggregation of migraine. Copyright © 2018 Elsevier Inc. All rights reserved.

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...

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.

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.

Functional traits determine tree growth and ecosystem productivity of a tropical montane forest: Insights from a long-term nutrient manipulation experiment.

PubMed

Báez, Selene; Homeier, Jürgen

2018-01-01

Trait-response effects are critical to forecast community structure and biomass production in highly diverse tropical forests. Ecological theory and few observation studies indicate that trees with acquisitive functional traits would respond more strongly to higher resource availability than those with conservative traits. We assessed how long-term tree growth in experimental nutrient addition plots (N, P, and N + P) varied as a function of morphological traits, tree size, and species identity. We also evaluated how trait-based responses affected stand scale biomass production considering the community structure. We found that tree growth depended on interactions between functional traits and the type or combination of nutrients added. Common species with acquisitive functional traits responded more strongly to nutrient addition, mainly to N + P. Phosphorous enhanced the growth rates of species with acquisitive and conservative traits, had mostly positive effects on common species and neutral or negative effects in rare species. Moreover, trees receiving N + P grew faster irrespective of their initial size relative to trees in control or to trees in other treatment plots. Finally, species responses were highly idiosyncratic suggesting that community processes including competition and niche dimensionality may be altered under increased resource availability. We found no statistically significant effects of nutrient additions on aboveground biomass productivity because acquisitive species had a limited potential to increase their biomass, possibly due to their generally lower wood density. In contrast, P addition increased the growth rates of species characterized by more conservative resource strategies (with higher wood density) that were poorly represented in the plant community. We provide the first long-term experimental evidence that trait-based responses, community structure, and community processes modulate the effects of increased nutrient availability on biomass productivity in a tropical forest. © 2017 John Wiley & Sons Ltd.

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.

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.

Traits as dimensions or categories? Developmental change in the understanding of trait terms.

PubMed

Gonzalez, Celia M; Zosuls, Kristina M; Ruble, Diane N

2010-09-01

Recent research has suggested that young children have relatively well-developed trait concepts. However, this literature overlooks potential age-related differences in children's appreciation of the fundamentally dimensional nature of traits. In Study 1, we presented 4-, 5-, and 7-year-old children and adults with sets of characters and asked them to indicate the preferences of a target character who shared appearance attributes with one character (appearance match) and shared a common trait with the other character (trait match). Traits were presented in a way that emphasized either their categorical or their dimensional nature. When the dimensional nature of trait terms was emphasized, the youngest children made fewer trait-based inferences, and the use of traits increased with age. In Study 2, we gave 4-year-old children and adults the same task except that the extent to which appearance cues could serve as a meaningful basis of judgment was varied. Results were consistent with the findings of Study 1, although children were more likely to rely on dimensional presentations of traits in the absence of strong appearance cues. (PsycINFO Database Record (c) 2010 APA, all rights reserved).

Energetics and genetics across the prokaryote-eukaryote divide

PubMed Central

2011-01-01

Background All complex life on Earth is eukaryotic. All eukaryotic cells share a common ancestor that arose just once in four billion years of evolution. Prokaryotes show no tendency to evolve greater morphological complexity, despite their metabolic virtuosity. Here I argue that the eukaryotic cell originated in a unique prokaryotic endosymbiosis, a singular event that transformed the selection pressures acting on both host and endosymbiont. Results The reductive evolution and specialisation of endosymbionts to mitochondria resulted in an extreme genomic asymmetry, in which the residual mitochondrial genomes enabled the expansion of bioenergetic membranes over several orders of magnitude, overcoming the energetic constraints on prokaryotic genome size, and permitting the host cell genome to expand (in principle) over 200,000-fold. This energetic transformation was permissive, not prescriptive; I suggest that the actual increase in early eukaryotic genome size was driven by a heavy early bombardment of genes and introns from the endosymbiont to the host cell, producing a high mutation rate. Unlike prokaryotes, with lower mutation rates and heavy selection pressure to lose genes, early eukaryotes without genome-size limitations could mask mutations by cell fusion and genome duplication, as in allopolyploidy, giving rise to a proto-sexual cell cycle. The side effect was that a large number of shared eukaryotic basal traits accumulated in the same population, a sexual eukaryotic common ancestor, radically different to any known prokaryote. Conclusions The combination of massive bioenergetic expansion, release from genome-size constraints, and high mutation rate favoured a protosexual cell cycle and the accumulation of eukaryotic traits. These factors explain the unique origin of eukaryotes, the absence of true evolutionary intermediates, and the evolution of sex in eukaryotes but not prokaryotes. Reviewers This article was reviewed by: Eugene Koonin, William Martin, Ford Doolittle and Mark van der Giezen. For complete reports see the Reviewers' Comments section. PMID:21714941

Divergent trait and environment relationships among parallel radiations in Pelargonium (Geraniaceae): a role for evolutionary legacy?

PubMed

Moore, Timothy E; Schlichting, Carl D; Aiello-Lammens, Matthew E; Mocko, Kerri; Jones, Cynthia S

2018-05-11

Functional traits in closely related lineages are expected to vary similarly along common environmental gradients as a result of shared evolutionary and biogeographic history, or legacy effects, and as a result of biophysical tradeoffs in construction. We test these predictions in Pelargonium, a relatively recent evolutionary radiation. Bayesian phylogenetic mixed effects models assessed, at the subclade level, associations between plant height, leaf area, leaf nitrogen content and leaf mass per area (LMA), and five environmental variables capturing temperature and rainfall gradients across the Greater Cape Floristic Region of South Africa. Trait-trait integration was assessed via pairwise correlations within subclades. Of 20 trait-environment associations, 17 differed among subclades. Signs of regression coefficients diverged for height, leaf area and leaf nitrogen content, but not for LMA. Subclades also differed in trait-trait relationships and these differences were modulated by rainfall seasonality. Leave-one-out cross-validation revealed that whether trait variation was better predicted by environmental predictors or trait-trait integration depended on the clade and trait in question. Legacy signals in trait-environment and trait-trait relationships were apparently lost during the earliest diversification of Pelargonium, but then retained during subsequent subclade evolution. Overall, we demonstrate that global-scale patterns are poor predictors of patterns of trait variation at finer geographic and taxonomic scales. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

The implications of Big Five standing for the distribution of trait manifestation in behavior: fifteen experience-sampling studies and a meta-analysis.

PubMed

Fleeson, William; Gallagher, Patrick

2009-12-01

One of the fundamental questions in personality psychology is whether and how strongly trait standing relates to the traits that people actually manifest in their behavior when faced with real pressures and real consequences of their actions. One reason this question is fundamental is the common belief that traits do not predict how individuals behave, which leads to the reasonable conclusion that traits are not important to study. However, this conclusion is surprising given that there is almost no data on the ability of traits to predict distributions of naturally occurring, representative behaviors of individuals (and that there are many studies showing that traits do indeed predict specific behaviors). The authors describe a meta-analysis of 15 experience-sampling studies, conducted over the course of 8 years, amassing over 20,000 reports of trait manifestation in behavior. Participants reported traits on typical self-report questionnaires, then described their current behavior multiple times per day for several days as the behavior was occurring. Results show that traits, contrary to expectations, were strongly predictive of individual differences in trait manifestation in behavior, predicting average levels with correlations between .42 and .56 (approaching .60 for stringently restricted studies). Several other ways of summarizing trait manifestation in behavior were also predicted from traits. These studies provide evidence that traits are powerful predictors of actual manifestation of traits in behavior.

Ecology of zoonotic infectious diseases in bats: current knowledge and future directions

USGS Publications Warehouse

Hayman, D.T.; Bowen, R.A.; Cryan, P.M.; McCracken, G.F.; O'Shea, T.J.; Peel, A.J.; Gilbert, A.; Webb, C.T.; Wood, J.L.

2013-01-01

Bats are hosts to a range of zoonotic and potentially zoonotic pathogens. Human activities that increase exposure to bats will likely increase the opportunity for infections to spill over in the future. Ecological drivers of pathogen spillover and emergence in novel hosts, including humans, involve a complex mixture of processes, and understanding these complexities may aid in predicting spillover. In particular, only once the pathogen and host ecologies are known can the impacts of anthropogenic changes be fully appreciated. Cross-disciplinary approaches are required to understand how host and pathogen ecology interact. Bats differ from other sylvatic disease reservoirs because of their unique and diverse lifestyles, including their ability to fly, often highly gregarious social structures, long lifespans and low fecundity rates. We highlight how these traits may affect infection dynamics and how both host and pathogen traits may interact to affect infection dynamics. We identify key questions relating to the ecology of infectious diseases in bats and propose that a combination of field and laboratory studies are needed to create data-driven mechanistic models to elucidate those aspects of bat ecology that are most critical to the dynamics of emerging bat viruses. If commonalities can be found, then predicting the dynamics of newly emerging diseases may be possible. This modelling approach will be particularly important in scenarios when population surveillance data are unavailable and when it is unclear which aspects of host ecology are driving infection dynamics.

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

PubMed

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

2015-08-01

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

Ecology of Zoonotic Infectious Diseases in Bats: Current Knowledge and Future Directions

PubMed Central

Hayman, D T S; Bowen, R A; Cryan, P M; McCracken, G F; O’Shea, T J; Peel, A J; Gilbert, A; Webb, C T; Wood, J L N

2013-01-01

Bats are hosts to a range of zoonotic and potentially zoonotic pathogens. Human activities that increase exposure to bats will likely increase the opportunity for infections to spill over in the future. Ecological drivers of pathogen spillover and emergence in novel hosts, including humans, involve a complex mixture of processes, and understanding these complexities may aid in predicting spillover. In particular, only once the pathogen and host ecologies are known can the impacts of anthropogenic changes be fully appreciated. Cross-disciplinary approaches are required to understand how host and pathogen ecology interact. Bats differ from other sylvatic disease reservoirs because of their unique and diverse lifestyles, including their ability to fly, often highly gregarious social structures, long lifespans and low fecundity rates. We highlight how these traits may affect infection dynamics and how both host and pathogen traits may interact to affect infection dynamics. We identify key questions relating to the ecology of infectious diseases in bats and propose that a combination of field and laboratory studies are needed to create data-driven mechanistic models to elucidate those aspects of bat ecology that are most critical to the dynamics of emerging bat viruses. If commonalities can be found, then predicting the dynamics of newly emerging diseases may be possible. This modelling approach will be particularly important in scenarios when population surveillance data are unavailable and when it is unclear which aspects of host ecology are driving infection dynamics. PMID:22958281

Imaging-Genetics in Dyslexia: Connecting risk genetic variants to brain neuroimaging and ultimately to reading impairments

PubMed Central

Eicher, John D.; Gruen, Jeffrey R.

2013-01-01

Dyslexia is a common pediatric disorder that affects 5-17% of schoolchildren in the United States. It is marked by unexpected difficulties in fluent reading despite adequate intelligence, opportunity, and instruction. Classically, neuropsychologists have studied dyslexia using a variety of neurocognitive batteries to gain insight into the specific deficits and impairments in affected children. Since dyslexia is a complex genetic trait with high heritability, analyses conditioned on performance on these neurocognitive batteries have been used to try to identify associated genes. This has led to some successes in identifying contributing genes, although much of the heritability remains unexplained. Additionally, the lack of relevant human brain tissue for analysis and the challenges of modeling a uniquely human trait in animals are barriers to advancing our knowledge of the underlying pathophysiology. In vivo imaging technologies, however, present new opportunities to examine dyslexia and reading skills in a clearly relevant context in human subjects. Recent investigations have started to integrate these imaging data with genetic data in attempts to gain a more complete and complex understanding of reading processes. In addition to bridging the gap from genetic risk variant to a discernible neuroimaging phenotype and ultimately to the clinical impairments in reading performance, the use of neuroimaging phenotypes will reveal novel risk genes and variants. In this article, we briefly discuss the genetic and imaging investigations and take an in-depth look at the recent imaging-genetics investigations of dyslexia. PMID:23916419

Congenic Mice Provide In Vivo Evidence for a Genetic Locus that Modulates Intrinsic TGF-b1-mediated Signaling and Bone Acquisition

PubMed Central

Mukherjee, Aditi; Larson, Emily A.; Carlos, Amy S.; Belknap, John K.; Rotwein, Peter; Klein, Robert F.

2016-01-01

Osteoporosis, the most common skeletal disorder, is characterized by low bone mineral density (BMD) and an increased risk of fragility fractures. BMD is the best clinical predictor of future osteoporotic fracture risk, but is a complex trait controlled by multiple environmental and genetic determinants with individually modest effects. Quantitative trait locus (QTL) mapping is a powerful method for identifying chromosomal regions encompassing genes involved in shaping complex phenotypes, such as BMD. Here we have applied QTL analysis to male and female genetically-heterogeneous F2 mice derived from a cross between C57BL/6 and DBA/2 strains, and have identified 11 loci contributing to femoral BMD. Further analysis of a QTL on mouse chromosome 7 following the generation of reciprocal congenic strains has allowed us to determine that the high BMD trait, which tracks with the DBA/2 chromosome and exerts equivalent effects on male and female mice, is manifested by enhanced osteogenic differentiation of mesenchymal stem cells (MSCs) in vitro and by increased growth of metatarsal bones in short-term primary culture. An insertion/deletion DNA polymorphism in Ltbp4 exon 12 that causes the in-frame removal of 12 codons in the DBA/2-derived gene maps within 0.6 Mb of the marker most tightly linked to the QTL. LTBP4, one of four paralogous mouse proteins that modify the bioavailability of the TGF-b family of growth factors, is expressed in differentiating MSC-derived osteoblasts and in long bones, and reduced responsiveness to TGF-b1 is observed in MSCs of mice homozygous for the DBA/2 chromosome 7. Taken together, our results identify a potential genetic and biochemical relationship between decreased TGF-b1-mediated signaling and enhanced femoral BMD that may be regulated by a variant LTBP4 molecule. PMID:22407846

Common Variants in Mendelian Kidney Disease Genes and Their Association with Renal Function

PubMed Central

Fuchsberger, Christian; Köttgen, Anna; O’Seaghdha, Conall M.; Pattaro, Cristian; de Andrade, Mariza; Chasman, Daniel I.; Teumer, Alexander; Endlich, Karlhans; Olden, Matthias; Chen, Ming-Huei; Tin, Adrienne; Kim, Young J.; Taliun, Daniel; Li, Man; Feitosa, Mary; Gorski, Mathias; Yang, Qiong; Hundertmark, Claudia; Foster, Meredith C.; Glazer, Nicole; Isaacs, Aaron; Rao, Madhumathi; Smith, Albert V.; O’Connell, Jeffrey R.; Struchalin, Maksim; Tanaka, Toshiko; Li, Guo; Hwang, Shih-Jen; Atkinson, Elizabeth J.; Lohman, Kurt; Cornelis, Marilyn C.; Johansson, Åsa; Tönjes, Anke; Dehghan, Abbas; Couraki, Vincent; Holliday, Elizabeth G.; Sorice, Rossella; Kutalik, Zoltan; Lehtimäki, Terho; Esko, Tõnu; Deshmukh, Harshal; Ulivi, Sheila; Chu, Audrey Y.; Murgia, Federico; Trompet, Stella; Imboden, Medea; Kollerits, Barbara; Pistis, Giorgio; Harris, Tamara B.; Launer, Lenore J.; Aspelund, Thor; Eiriksdottir, Gudny; Mitchell, Braxton D.; Boerwinkle, Eric; Schmidt, Helena; Hofer, Edith; Hu, Frank; Demirkan, Ayse; Oostra, Ben A.; Turner, Stephen T.; Ding, Jingzhong; Andrews, Jeanette S.; Freedman, Barry I.; Giulianini, Franco; Koenig, Wolfgang; Illig, Thomas; Döring, Angela; Wichmann, H.-Erich; Zgaga, Lina; Zemunik, Tatijana; Boban, Mladen; Minelli, Cosetta; Wheeler, Heather E.; Igl, Wilmar; Zaboli, Ghazal; Wild, Sarah H.; Wright, Alan F.; Campbell, Harry; Ellinghaus, David; Nöthlings, Ute; Jacobs, Gunnar; Biffar, Reiner; Ernst, Florian; Homuth, Georg; Kroemer, Heyo K.; Nauck, Matthias; Stracke, Sylvia; Völker, Uwe; Völzke, Henry; Kovacs, Peter; Stumvoll, Michael; Mägi, Reedik; Hofman, Albert; Uitterlinden, Andre G.; Rivadeneira, Fernando; Aulchenko, Yurii S.; Polasek, Ozren; Hastie, Nick; Vitart, Veronique; Helmer, Catherine; Wang, Jie Jin; Stengel, Bénédicte; Ruggiero, Daniela; Bergmann, Sven; Kähönen, Mika; Viikari, Jorma; Nikopensius, Tiit; Province, Michael; Colhoun, Helen; Doney, Alex; Robino, Antonietta; Krämer, Bernhard K.; Portas, Laura; Ford, Ian; Buckley, Brendan M.; Adam, Martin; Thun, Gian-Andri; Paulweber, Bernhard; Haun, Margot; Sala, Cinzia; Mitchell, Paul; Ciullo, Marina; Vollenweider, Peter; Raitakari, Olli; Metspalu, Andres; Palmer, Colin; Gasparini, Paolo; Pirastu, Mario; Jukema, J. Wouter; Probst-Hensch, Nicole M.; Kronenberg, Florian; Toniolo, Daniela; Gudnason, Vilmundur; Shuldiner, Alan R.; Coresh, Josef; Schmidt, Reinhold; Ferrucci, Luigi; van Duijn, Cornelia M.; Borecki, Ingrid; Kardia, Sharon L.R.; Liu, Yongmei; Curhan, Gary C.; Rudan, Igor; Gyllensten, Ulf; Wilson, James F.; Franke, Andre; Pramstaller, Peter P.; Rettig, Rainer; Prokopenko, Inga; Witteman, Jacqueline; Hayward, Caroline; Ridker, Paul M.; Bochud, Murielle; Heid, Iris M.; Siscovick, David S.; Fox, Caroline S.; Kao, W. Linda; Böger, Carsten A.

2013-01-01

Many common genetic variants identified by genome-wide association studies for complex traits map to genes previously linked to rare inherited Mendelian disorders. A systematic analysis of common single-nucleotide polymorphisms (SNPs) in genes responsible for Mendelian diseases with kidney phenotypes has not been performed. We thus developed a comprehensive database of genes for Mendelian kidney conditions and evaluated the association between common genetic variants within these genes and kidney function in the general population. Using the Online Mendelian Inheritance in Man database, we identified 731 unique disease entries related to specific renal search terms and confirmed a kidney phenotype in 218 of these entries, corresponding to mutations in 258 genes. We interrogated common SNPs (minor allele frequency >5%) within these genes for association with the estimated GFR in 74,354 European-ancestry participants from the CKDGen Consortium. However, the top four candidate SNPs (rs6433115 at LRP2, rs1050700 at TSC1, rs249942 at PALB2, and rs9827843 at ROBO2) did not achieve significance in a stage 2 meta-analysis performed in 56,246 additional independent individuals, indicating that these common SNPs are not associated with estimated GFR. The effect of less common or rare variants in these genes on kidney function in the general population and disease-specific cohorts requires further research. PMID:24029420

Genome-wide association study identifies common and low-frequency variants at the AMH gene locus that strongly predict serum AMH levels in males.

PubMed

Perry, John R B; McMahon, George; Day, Felix R; Ring, Susan M; Nelson, Scott M; Lawlor, Debbie A

2016-01-15

Anti-Müllerian hormone (AMH) is an essential messenger of sexual differentiation in the foetus and is an emerging biomarker of postnatal reproductive function in females. Due to a paucity of adequately sized studies, the genetic determinants of circulating AMH levels are poorly characterized. In samples from 2815 adolescents aged 15 from the ALSPAC study, we performed the first genome-wide association study of serum AMH levels across a set of ∼9 m '1000 Genomes Reference Panel' imputed genetic variants. Genetic variants at the AMH protein-coding gene showed considerable allelic heterogeneity, with both common variants [rs4807216 (P(Male) = 2 × 10(-49), Beta: ∼0.9 SDs per allele), rs8112524 (P(Male) = 3 × 10(-8), Beta: ∼0.25)] and low-frequency variants [rs2385821 (P(Male) = 6 × 10(-31), Beta: ∼1.2, frequency 3.6%)] independently associated with apparently large effect sizes in males, but not females. For all three SNPs, we highlight mechanistic links to AMH gene function and demonstrate highly significant sex interactions (P(Het) 0.0003-6.3 × 10(-12)), culminating in contrasting estimates of trait variance explained (24.5% in males versus 0.8% in females). Using these SNPs as a genetic proxy for AMH levels, we found no evidence in additional datasets to support a biological role for AMH in complex traits and diseases in men. © The Author 2015. Published by Oxford University Press.

Genome-Wide Copy Number Variation Association Analyses for Age at Menarche

PubMed Central

Li, Jian; Pan, Rong; Shen, Hui; Tian, Qing; Zhou, Yu; Liu, Yong-Jun

2012-01-01

Context: Menarche is a significant physiological event for women. Age at menarche (AAM) is a heritable trait associated with many common female diseases. The genetic basis and the mechanism for AAM are largely unknown. Copy number variation (CNV) is a common type of genetic variation underlying human complex traits. The importance of CNV to AAM variation is unclear. Objective: The objective of the study was to identify CNV important to AAM variation. Design: We performed the first genome-wide CNV study of AAM in 1654 Caucasian females using Affymetrix human single-nucleotide polymorphism 6.0 array. We also replicated our findings in another Chinese cohort containing 752 women. Results: We identified a CNV, variation_38399, in the 2q14.2 region, for association with AAM (P = 1.03 × 10−3). The CNV has two variants (one copy and two copy), with a mean AAM of 14.00 yr and 12.90 yr, respectively. Interestingly, in a Chinese sample containing 752 women, this CNV has been replicated both with a marginally significant P = 0.090 and with a same direction of effect (a lower copy number for a later AAM). The CNV is located approximately 75 kb upstream of the diazepam binding inhibitor (DBI), a gene known to regulate estrogen levels, a key factor for menarche. Conclusion: Our findings for the first time identified a novel CNV and suggested the DBI-mediated endocrinological pathway as a potential mechanism for AAM regulation. PMID:22904172

Broad Bandwidth or High Fidelity? Evidence from the Structure of Genetic and Environmental Effects on the Facets of the Five Factor Model

PubMed Central

Briley, Daniel A.; Tucker-Drob, Elliot M.

2017-01-01

The Five Factor Model (FFM) of personality is well-established at the phenotypic level, but much less is known about the coherence of the genetic and environmental influences within each personality domain. Univariate behavioral genetic analyses have consistently found the influence of additive genes and nonshared environment on multiple personality facets, but the extent to which genetic and environmental influences on specific facets reflect more general influences on higher order factors is less clear. We applied a multivariate quantitative-genetic approach to scores on the CPI-Big Five facets for 490 monozygotic and 317 dizygotic twins who took part in the National Merit Twin Study. Our results revealed a complex genetic structure for facets composing all five factors, with both domain-general and facet-specific genetic and environmental influences. Models that required common genetic and environmental influences on each facet to occur by way of effects on a higher order trait did not fit as well as models allowing for common genetic and environmental effects to act directly on the facets for three of the Big Five domains. These results add to the growing body of literature indicating that important variation in personality occurs at the facet level which may be overshadowed by aggregating to the trait level. Research at the facet level, rather than the factor level, is likely to have pragmatic advantages in future research on the genetics of personality. PMID:22695681

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

Genome-wide association implicates numerous genes and pleiotropy underlying ecological trait variation in natural populations of Populus trichocarpa

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

McKown, Athena; Klapste, Jaroslav; Guy, Robert

2014-01-01

To uncover the genetic basis of phenotypic trait variation, we used 448 unrelated wild accessions of black cottonwood (Populus trichocarpa Torr. & Gray) from natural populations throughout western North America. Extensive information from large-scale trait phenotyping (with spatial and temporal replications within a common garden) and genotyping (with a 34K Populus SNP array) of all accessions were used for gene discovery in a genome-wide association study (GWAS).

Dispositional Affect Moderates the Stress-Buffering Effect of Social Support on Risk for Developing the Common Cold.

PubMed

Janicki Deverts, Denise; Cohen, Sheldon; Doyle, William J

2017-10-01

The aim was to examine whether trait positive and negative affect (PA, NA) moderate the stress-buffering effect of perceived social support on risk for developing a cold subsequent to being exposed to a virus that causes mild upper respiratory illness. Analyses were based on archival data from 694 healthy adults (M age  = 31.0 years, SD = 10.7 years; 49.0% female; 64.6% Caucasian). Perceived social support and perceived stress were assessed by self-report questionnaire and trait affect by aggregating responses to daily mood items administered by telephone interview across several days. Subsequently, participants were exposed to a virus that causes the common cold and monitored for 5 days for clinical illness (infection + objective signs of illness). Two 3-way interactions emerged-Support × Stress × PA and Support × Stress × NA. The nature of these effects was such that among persons with high trait PA or low trait NA, greater social support attenuated the risk of developing a cold when under high but not low perceived stress; this stress-buffering effect did not emerge among persons with low trait PA or high trait NA. Dispositional affect might be used to identify individuals who may be most responsive to social support and support-based interventions. © 2016 Wiley Periodicals, Inc.

The relationship between cavum septum pellucidum and psychopathic traits in female offenders.

PubMed

Crooks, Dana; Anderson, Nathaniel E; Widdows, Matthew; Petseva, Nia; Decety, Jean; Pluto, Charles; Kiehl, Kent A

2018-06-22

Cavum Septum Pellucidum (CSP) is a common anatomical variant of the septum pellucidum. CSP is considered a marker for abnormal limbic brain development, but its functional consequences are non-specific. In a recent report [1], CSP size was significantly positively correlated with the affective/interpersonal traits of psychopathy in male offenders (N = 1742). Here we test the hypothesis that CSP is related to psychopathic traits in incarcerated females (N = 355). We examine continuous relationships as well as categorical assignments for CSP size corresponding to a number of prior reports. We also compare female offenders to healthy female controls (N = 385). Consistent with our reported findings in males, a positive association was observed between the interpersonal psychopathic traits and CSP size. In contrast to findings among males, an association between CSP and antisocial psychopathic traits was apparent in females. There was no significant difference in CSP size (in mm) or CSP presence/absence between incarcerated and non-incarcarated groups. However, categorical rates of medium and large CSP were more common in female inmates than in controls. This is the first systematic investigation of these variables in a female inmate sample. In combination with our prior study, these findings demonstrate that limbic abnormalities, as indexed by CSP, are related to psychopathic traits in both female and male inmates. Copyright © 2018. Published by Elsevier B.V.

Variation in leaf and twig CO2 flux as a function of plant size: a comparison of seedlings, saplings and trees.

PubMed

Sendall, Kerrie M; Reich, Peter B

2013-07-01

Rates of tissue-level function have been hypothesized to decline as trees grow older and larger, but relevant evidence to assess such changes remains limited, especially across a wide range of sizes from saplings to large trees. We measured functional traits of leaves and twigs of three cold-temperate deciduous tree species in Minnesota, USA, to assess how these vary with tree height. Individuals ranging from 0.13 to 20 m in height were sampled in both relatively open and closed canopy environments to minimize light differences as a potential driver of size-related differences in leaf and twig properties. We hypothesized that (H1) gas-exchange rates, tissue N concentration and leaf mass per unit area (LMA) would vary with tree size in a pattern reflecting declining function in taller trees, yet maintaining (H2) bivariate trait relations, common among species as characterized by the leaf economics spectrum. Taking these two ideas together yielded a third, integrated hypothesis that (H3) nitrogen (N) content and gas-exchange rates should decrease monotonically with tree size and LMA should increase. We observed increasing LMA and decreasing leaf and twig Rd with increasing size, which matched predictions from H1 and H3. However, opposite to our predictions, leaf and twig N generally increased with size, and thus had inverse relations with respiration, rather than the predicted positive relations. Two exceptions were area-based leaf N of Prunus serotina Ehrh. in gaps and mass-based leaf N of Quercus ellipsoidalis E. J. Hill in gaps, both of which showed qualitatively hump-shaped patterns. Finally, we observed hump-shaped relationships between photosynthetic capacity and tree height, not mirroring any of the other traits, except in the two cases highlighted above. Bivariate trait relations were weak intra-specifically, but were generally significant and positive for area-based traits using the pooled dataset. Results suggest that different traits vary with tree size in different ways that are not consistent with a universal shift towards a lower 'return on investment' strategy. Instead, species traits vary with size in patterns that likely reflect complex variation in water, light, nitrogen and carbon availability, storage and use.

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.

Alcohol-related Genes Show an Enrichment of Associations with a Persistent Externalizing Factor

PubMed Central

Ashenhurst, James R.; Harden, K. Paige; Corbin, William R.; Fromme, Kim

2016-01-01

Research using twins has found that much of the variability in externalizing phenotypes – including alcohol and drug use, impulsive personality traits, risky sex and property crime – is explained by genetic factors. Nevertheless, identification of specific genes and variants associated with these traits has proven to be difficult, likely because individual differences in externalizing are explained by many genes of small individual effect. Moreover, twin research indicates that heritable variance in externalizing behaviors is mostly shared across the externalizing spectrum rather than specific to any behavior. We use a longitudinal, “deep phenotyping” approach to model a general externalizing factor reflecting persistent engagement in a variety of socially problematic behaviors measured at eleven assessment occasions spanning early adulthood (ages 18 to 28). In an ancestrally homogenous sample of non-Hispanic Whites (N = 337), we then tested for enrichment of associations between the persistent externalizing factor and a set of 3,281 polymorphisms within 104 genes that were previously identified as associated with alcohol-use behaviors. Next we tested for enrichment among domain-specific factors (e.g., property crime) composed of residual variance not accounted for by the common factor. Significance was determined relative to bootstrapped empirical thresholds derived from permutations of phenotypic data. Results indicated significant enrichment of genetic associations for persistent externalizing, but not for domain-specific factors. Consistent with twin research findings, these results suggest that genetic variants are broadly associated with externalizing behaviors rather than unique to specific behaviors. General Scientific Summary This study shows that variation in 104 genes is associated with socially problematic “externalizing” behavior, including substance misuse, property crime, risky sex, and aspects of impulsive personality. Importantly, this association was with the common variation across these behaviors rather than with the variation unique to any given behavior. The manuscript demonstrates a potentially advantageous technique for relating sets of hypothesized genes to complex traits or behaviors. PMID:27505405

Hormones and the Evolution of Complex Traits: Insights from Artificial Selection on Behavior.

PubMed

Garland, Theodore; Zhao, Meng; Saltzman, Wendy

2016-08-01

Although behavior may often be a fairly direct target of natural or sexual selection, it cannot evolve without changes in subordinate traits that cause or permit its expression. In principle, changes in endocrine function could be a common mechanism underlying behavioral evolution because they are well positioned to mediate integrated responses to behavioral selection. More specifically, hormones can influence both motivational (e.g., brain) and performance (e.g., muscles) components of behavior simultaneously and in a coordinated fashion. If the endocrine system is often "used" as a general mechanism to effect responses to selection, then correlated responses in other aspects of behavior, life history, and organismal performance (e.g., locomotor abilities) should commonly occur because any cell with appropriate receptors could be affected. Ways in which behavior coadapts with other aspects of the phenotype can be studied directly through artificial selection and experimental evolution. Several studies have targeted rodent behavior for selective breeding and reported changes in other aspects of behavior, life history, and lower-level effectors of these organismal traits, including endocrine function. One example involves selection for high levels of voluntary wheel running, one aspect of physical activity, in four replicate High Runner (HR) lines of mice. Circulating levels of several hormones (including insulin, testosterone, thyroxine, triiodothyronine) have been characterized, three of which-corticosterone, leptin, and adiponectin-differ between HR and control lines, depending on sex, age, and generation. Potential changes in circulating levels of other behaviorally and metabolically relevant hormones, as well as in other components of the endocrine system (e.g., receptors), have yet to be examined. Overall, results to date identify promising avenues for further studies on the endocrine basis of activity levels. © The Author 2016. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Variation in life-history traits and their plasticities to elevational transplantation among seed families suggests potential for adaptative evolution of 15 tropical plant species to climate change.

PubMed

Ensslin, Andreas; Fischer, Markus

2015-08-01

• Because not all plant species will be able to move in response to global warming, adaptive evolution matters largely for plant persistence. As prerequisites for adaptive evolution, genetic variation in and selection on phenotypic traits are needed, but these aspects have not been studied in tropical species. We studied how plants respond to transplantation to different elevations on Mt. Kilimanjaro, Tanzania, and whether there is quantitative genetic (among-seed family) variation in and selection on life-history traits and their phenotypic plasticity to the different environments.• We reciprocally transplanted seed families of 15 common tropical, herbaceous species of the montane and savanna vegetation zone at Mt. Kilimanjaro to a watered experimental garden in the montane (1450 m) and in the savanna (880 m) zone at the mountain's slope and measured performance, reproductive, and phenological traits.• Plants generally performed worse in the savanna garden, indicating that the savanna climate was more stressful and thus that plants may suffer from future climate warming. We found significant quantitative genetic variation in all measured performance and reproductive traits in both gardens and for several measures of phenotypic plasticity in response to elevational transplantation. Moreover, we found positive selection on traits at low and intermediate trait values levelling to neutral or negative selection at high values.• We conclude that common plants at Mt. Kilimanjaro express quantitative genetic variation in fitness-relevant traits and in their plasticities, suggesting potential to adapt evolutionarily to future climate warming and increased temperature variability. © 2015 Botanical Society of America, Inc.

SNP-Based QTL Mapping of 15 Complex Traits in Barley under Rain-Fed and Well-Watered Conditions by a Mixed Modeling Approach.

PubMed

Mora, Freddy; Quitral, Yerko A; Matus, Ivan; Russell, Joanne; Waugh, Robbie; Del Pozo, Alejandro

2016-01-01

This study identified single nucleotide polymorphism (SNP) markers associated with 15 complex traits in a breeding population of barley (Hordeum vulgare L.) consisting of 137 recombinant chromosome substitution lines (RCSL), evaluated under contrasting water availability conditions in the Mediterranean climatic region of central Chile. Given that markers showed a very strong segregation distortion, a quantitative trait locus/loci (QTL) mapping mixed model was used to account for the heterogeneity in genetic relatedness between genotypes. Fifty-seven QTL were detected under rain-fed conditions, which accounted for 5-22% of the phenotypic variation. In full irrigation conditions, 84 SNPs were significantly associated with the traits studied, explaining 5-35% of phenotypic variation. Most of the QTL were co-localized on chromosomes 2H and 3H. Environment-specific genomic regions were detected for 12 of the 15 traits scored. Although most QTL-trait associations were environment and trait specific, some important and stable associations were also detected. In full irrigation conditions, a relatively major genomic region was found underlying hectoliter weight (HW), on chromosome 1H, which explained between 27% (SNP 2711-234) and 35% (SNP 1923-265) of the phenotypic variation. Interestingly, the locus 1923-265 was also detected for grain yield at both environmental conditions, accounting for 9 and 18%, in the rain-fed and irrigation conditions, respectively. Analysis of QTL in this breeding population identified significant genomic regions that can be used for marker-assisted selection (MAS) of barley in areas where drought is a significant constraint.

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

PubMed

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

2018-03-01

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

SNP-Based QTL Mapping of 15 Complex Traits in Barley under Rain-Fed and Well-Watered Conditions by a Mixed Modeling Approach

PubMed Central

Mora, Freddy; Quitral, Yerko A.; Matus, Ivan; Russell, Joanne; Waugh, Robbie; del Pozo, Alejandro

2016-01-01

This study identified single nucleotide polymorphism (SNP) markers associated with 15 complex traits in a breeding population of barley (Hordeum vulgare L.) consisting of 137 recombinant chromosome substitution lines (RCSL), evaluated under contrasting water availability conditions in the Mediterranean climatic region of central Chile. Given that markers showed a very strong segregation distortion, a quantitative trait locus/loci (QTL) mapping mixed model was used to account for the heterogeneity in genetic relatedness between genotypes. Fifty-seven QTL were detected under rain-fed conditions, which accounted for 5–22% of the phenotypic variation. In full irrigation conditions, 84 SNPs were significantly associated with the traits studied, explaining 5–35% of phenotypic variation. Most of the QTL were co-localized on chromosomes 2H and 3H. Environment-specific genomic regions were detected for 12 of the 15 traits scored. Although most QTL-trait associations were environment and trait specific, some important and stable associations were also detected. In full irrigation conditions, a relatively major genomic region was found underlying hectoliter weight (HW), on chromosome 1H, which explained between 27% (SNP 2711-234) and 35% (SNP 1923-265) of the phenotypic variation. Interestingly, the locus 1923-265 was also detected for grain yield at both environmental conditions, accounting for 9 and 18%, in the rain-fed and irrigation conditions, respectively. Analysis of QTL in this breeding population identified significant genomic regions that can be used for marker-assisted selection (MAS) of barley in areas where drought is a significant constraint. PMID:27446139

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

PubMed Central

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

2018-01-01

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

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.

sPlot - the new global vegetation-plot database for addressing trait-environment relationships across the world's biomes

NASA Astrophysics Data System (ADS)

Purschke, Oliver; Dengler, Jürgen; Bruelheide, Helge; Chytrý, Milan; Jansen, Florian; Hennekens, Stephan; Jandt, Ute; Jiménez-Alfaro, Borja; Kattge, Jens; De Patta Pillar, Valério; Sandel, Brody; Winter, Marten

2015-04-01

The trait composition of plant communities is determined by abiotic, biotic and historical factors, but the importance of macro-climatic factors in explaining trait-environment relationships at the local scale remains unclear. Such knowledge is crucial for biogeographical and ecological theory but also relevant to devise management measures to mitigate the negative effects of climate change. To address these questions, an iDiv Working Group has established the first global vegetation-plot database (sPlot). sPlot currently contains ~700,000 plots from over 50 countries and all biomes, and is steadily growing. Approx. 70% of the most frequent species are represented by at least one trait in the global trait database TRY and gap-filled data will become available for the most common traits. We will give an overview about the structure and present content of sPlot in terms of spatial distribution, data properties and trait coverage. We will explain next steps and perspectives, present first cross-biome analyses of community-weighted mean traits and trait variability, and highlight some ecological questions that can be addressed with sPlot.

Distinct Genetic Architectures for Male and Female Inflorescence Traits of Maize

PubMed Central

Brown, Patrick J.; Upadyayula, Narasimham; Mahone, Gregory S.; Tian, Feng; Bradbury, Peter J.; Myles, Sean; Holland, James B.; Flint-Garcia, Sherry; McMullen, Michael D.; Buckler, Edward S.; Rocheford, Torbert R.

2011-01-01

We compared the genetic architecture of thirteen maize morphological traits in a large population of recombinant inbred lines. Four traits from the male inflorescence (tassel) and three traits from the female inflorescence (ear) were measured and studied using linkage and genome-wide association analyses and compared to three flowering and three leaf traits previously studied in the same population. Inflorescence loci have larger effects than flowering and leaf loci, and ear effects are larger than tassel effects. Ear trait models also have lower predictive ability than tassel, flowering, or leaf trait models. Pleiotropic loci were identified that control elongation of ear and tassel, consistent with their common developmental origin. For these pleiotropic loci, the ear effects are larger than tassel effects even though the same causal polymorphisms are likely involved. This implies that the observed differences in genetic architecture are not due to distinct features of the underlying polymorphisms. Our results support the hypothesis that genetic architecture is a function of trait stability over evolutionary time, since the traits that changed most during the relatively recent domestication of maize have the largest effects. PMID:22125498

Phenotype traits of bermudagrass ecotypes from pastures stocked at different intensities during a 40-year period

USDA-ARS?s Scientific Manuscript database

Stocking intensities can affect persistence of bermudagrass pastures. The objectives of this study were to compare phenotype traits of bermudagrass [Cynodon dactylon (L) Pers] (BG) ecotypes (ECOT) selected from both ‘Coastal’ (COS) and common (COM) BG pastures stocked at different, controlled intens...

Implementing meta-analysis from genome-wide association studies for pork quality traits

USDA-ARS?s Scientific Manuscript database

Pork quality plays an important role in the meat processing industry, thus different methodologies have been implemented to elucidate the genetic architecture of traits affecting meat quality. One of the most common and widely used approaches is to perform genome-wide association (GWA) studies. Howe...

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.

Heritability, covariation and natural selection on 24 traits of common evening primrose (Oenothera biennis) from a field experiment.

PubMed

Johnson, M T J; Agrawal, A A; Maron, J L; Salminen, J-P

2009-06-01

This study explored genetic variation and co-variation in multiple functional plant traits. Our goal was to characterize selection, heritabilities and genetic correlations among different types of traits to gain insight into the evolutionary ecology of plant populations and their interactions with insect herbivores. In a field experiment, we detected significant heritable variation for each of 24 traits of Oenothera biennis and extensive genetic covariance among traits. Traits with diverse functions formed several distinct groups that exhibited positive genetic covariation with each other. Genetic variation in life-history traits and secondary chemistry together explained a large proportion of variation in herbivory (r(2) = 0.73). At the same time, selection acted on lifetime biomass, life-history traits and two secondary compounds of O. biennis, explaining over 95% of the variation in relative fitness among genotypes. The combination of genetic covariances and directional selection acting on multiple traits suggests that adaptive evolution of particular traits is constrained, and that correlated evolution of groups of traits will occur, which is expected to drive the evolution of increased herbivore susceptibility. As a whole, our study indicates that an examination of genetic variation and covariation among many different types of traits can provide greater insight into the evolutionary ecology of plant populations and plant-herbivore interactions.

Personality Disorders and Psychological Functioning Among Latina Women with Eating Disorders.

PubMed

Minnick, Alyssa M; Cachelin, Fary M; Durvasula, Ramani S

2017-01-01

Little is known about personality disorders (PD) and comorbidities among Latinas with eating disorders (ED). The dysregulation and chronicity of PDs can complicate and augment the symptomatology of EDs. This set of analyses provides a preliminary examination of PD and psychopathology in a sample of Latina women with ED. Participants (N = 34) were administered the Structured Clinical Interview for the Diagnostic and Statistical Manual, Eating Disorders Examination, and Millon Clinical Multiaxial Inventory-III to assess personality pathology, and questionnaires (Beck Depression Inventory-II and Brief Symptom Inventory) to assess psychological functioning. Results indicated the most common clinically significant trait in the sample was depressive personality (50% of the sample had a score of 75 or higher on this trait). For Bulimia Nervosa (BN) and Binge Eating Disorder (BED), avoidant (41%) and depressive (65%) personalities, respectively, were the most common clinically significant traits. Anxiety disorders were the most common psychiatric diagnoses, and 52.9% of the sample reported both clinically significant PD traits and other major psychopathology. There were no significant differences between the BED and BN groups on prevalence of PD traits and psychopathology. This pilot study highlights the need for further examination of PD and psychopathology in Latinas with ED. Unlike previous research with White women, we found no differences on PD and psychopathology between BED and BN, and the most prevalent PDs among Latinas were different than White women. Personality and psychological functioning should be assessed in all patients with ED, with ongoing research focused on identifying patterns in understudied groups such as Latinas, a practice that may improve treatment for this underserved population.

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

PubMed

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

2018-06-13

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

Characterizing Male–Female Interactions Using Natural Genetic Variation in Drosophila melanogaster

PubMed Central

Reinhart, Michael; Carney, Tara; Clark, Andrew G.

2015-01-01

Drosophila melanogaster females commonly mate with multiple males establishing the opportunity for pre- and postcopulatory sexual selection. Traits impacting sexual selection can be affected by a complex interplay of the genotypes of the competing males, the genotype of the female, and compatibilities between the males and females. We scored males from 96 2nd and 94 3rd chromosome substitution lines for traits affecting reproductive success when mated with females from 3 different genetic backgrounds. The traits included male-induced female refractoriness, male remating ability, the proportion of offspring sired under competitive conditions and male-induced female fecundity. We observed significant effects of male line, female genetic background, and strong male by female interactions. Some males appeared to be “generalists” and performed consistently across the different females; other males appeared to be “specialists” and performed very well with a particular female and poorly with others. “Specialist” males did not, however, prefer to court those females with whom they had the highest reproductive fitness. Using 143 polymorphisms in male reproductive genes, we mapped several genes that had consistent effects across the different females including a derived, high fitness allele in Acp26Aa that may be the target of adaptive evolution. We also identified a polymorphism upstream of PebII that may interact with the female genetic background to affect male-induced refractoriness to remating. These results suggest that natural variation in PebII might contribute to the observed male–female interactions. PMID:25425680

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

Recent genomic heritage in Scotland.

PubMed

Amador, Carmen; Huffman, Jennifer; Trochet, Holly; Campbell, Archie; Porteous, David; Wilson, James F; Hastie, Nick; Vitart, Veronique; Hayward, Caroline; Navarro, Pau; Haley, Chris S

2015-06-06

The Generation Scotland Scottish Family Health Study (GS:SFHS) includes 23,960 participants from across Scotland with records for many health-related traits and environmental covariates. Genotypes at ~700 K SNPs are currently available for 10,000 participants. The cohort was designed as a resource for genetic and health related research and the study of complex traits. In this study we developed a suite of analyses to disentangle the genomic differentiation within GS:SFHS individuals to describe and optimise the sample and methods for future analyses. We combined the genotypic information of GS:SFHS with 1092 individuals from the 1000 Genomes project and estimated their genomic relationships. Then, we performed Principal Component Analyses of the resulting relationships to investigate the genomic origin of different groups. We characterised two groups of individuals: those with a few sparse rare markers in the genome, and those with several large rare haplotypes which might represent relatively recent exogenous ancestors. We identified some individuals with likely Italian ancestry and a group with some potential African/Asian ancestry. An analysis of homozygosity in the GS:SFHS sample revealed a very similar pattern to other European populations. We also identified an individual carrying a chromosome 1 uniparental disomy. We found evidence of local geographic stratification within the population having impact on the genomic structure. These findings illuminate the history of the Scottish population and have implications for further analyses such as the study of the contributions of common and rare variants to trait heritabilities and the evaluation of genomic and phenotypic prediction of disease.

Inter-individual differences in the impulsive/compulsive dimension: deciphering related dopaminergic and serotonergic metabolisms at rest.

PubMed

Dellu-Hagedorn, Françoise; Rivalan, Marion; Fitoussi, Aurélie; De Deurwaerdère, Philippe

2018-04-19

Several impulse control disorders such as ADHD, mania, personality disorders or substance abuse share common behavioural traits, like impulsiveness, risk-taking or inflexible behaviour. These disorders are treated with drugs targeting dopamine (DA) and/or serotonin (5-HT). However, the patient's monoamine imbalance that these neurotransmitters compensate is unclear. This study aims to investigate the patterns of DA and 5-HT metabolisms at rest within selected brain regions related to inter-individual variability in six main components of impulsivity/compulsivity (anticipatory hyperactivity, premature responses, delay discounting, risk-taking, perseveration, flexibility). Rats with adaptive and highly inadaptive behaviours were identified in each task and a sensitive biochemical approach allowed mapping of post-mortem endogenous monoamine tissue content in 20 brain areas. Distinct patterns of 5-HT and DA metabolisms were revealed according to the behavioural traits. Except for hyperactive responses, lower control of actions was mainly associated with a lower DA or 5-HT metabolism in prefrontal and/or subcortical areas (i.e. in orbitofrontal cortex (DA), amygdala and anterior cingulate cortex (5-HT) for inflexible and risk-prone rats). Our results reveal the complex nature of behavioural traits related to impulse control disorders through their associated monoaminergic networks at rest, paving the way for understanding the link between mental disorders and drug therapeutic actions.This article is part of the theme issue 'Diverse perspectives on diversity: multi-disciplinary approaches to taxonomies of individual differences'. © 2018 The Author(s).

GWAS and fine-mapping of 35 production, reproduction and conformation traits with imputed sequences of 27K Holstein bulls

USDA-ARS?s Scientific Manuscript database

Fine-mapping of causal variants is becoming feasible for complex traits in livestock GWAS, as an increasing number of animals are sequenced. Imputation has been routinely applied to ascertain sequence variants in large genotyped populations based on small reference populations of sequenced animals. ...

The Relationship between Confidence and Self-Concept--Towards a Model of Response Confidence

ERIC Educational Resources Information Center

Kroner, Stephan; Biermann, Antje

2007-01-01

According to Stankov [Stankov, L. (2000). Complexity, metacognition and fluid intelligence. Intelligence, 28, 121-143.] response confidence in cognitive tests reflects a trait on the boundary of personality and abilities. However, several studies failed in relating confidence scores to other known traits, including self-concept. A model of…

Approaches for geospatial processing of field-based high-throughput plant phenomics data from ground vehicle platforms

USDA-ARS?s Scientific Manuscript database

Understanding the genetic basis of complex plant traits requires connecting genotype to phenotype information, known as the “G2P question.” In the last three decades, genotyping methods have become highly developed. Much less innovation has occurred for measuring plant traits (phenotyping), particul...

Multimedia Case-Based Instruction in Literacy: Pedagogy, Effectiveness, and Perceptions

ERIC Educational Resources Information Center

Baker, Elizabeth A.

2009-01-01

Effective literacy teachers share a variety of instructional traits such as the ability to kidwatch, pedagogically reflect, and make informed decisions based on ill-structured and complex data. Teacher educators face the challenge of helping preservice teachers develop such traits so as to prepare them to be successful literacy teachers. One…

Association genetics in Pinus taeda L. I. wood property traits

Treesearch

Santiago C. Gonzalez-Martinez; Nicholas C. Wheeler; Elhan Ersoz; C. Dana Nelson; David B. Neale

2007-01-01

Genetic association is a powerful method for dissecting complex adaptive traits due to (i) fine-scale mapping resulting from historical recombination, (ii) wide coverage of phenotypic and genotypic variation within a single experiment, and (iii) the simultaneous discovery of loci and alleles. In this article, genetic association among single nucleotide polymorphisms (...

Accounting for genotype–by-environment interactions and non-additive genetic variation in genomic selection for water-soluble carbohydrate concentration in wheat

USDA-ARS?s Scientific Manuscript database

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 un...