Genomic prediction based on data from three layer lines using non-linear regression models.

PubMed

Huang, Heyun; Windig, Jack J; Vereijken, Addie; Calus, Mario P L

2014-11-06

Most studies on genomic prediction with reference populations that include multiple lines or breeds have used linear models. Data heterogeneity due to using multiple populations may conflict with model assumptions used in linear regression methods. In an attempt to alleviate potential discrepancies between assumptions of linear models and multi-population data, two types of alternative models were used: (1) a multi-trait genomic best linear unbiased prediction (GBLUP) model that modelled trait by line combinations as separate but correlated traits and (2) non-linear models based on kernel learning. These models were compared to conventional linear models for genomic prediction for two lines of brown layer hens (B1 and B2) and one line of white hens (W1). The three lines each had 1004 to 1023 training and 238 to 240 validation animals. Prediction accuracy was evaluated by estimating the correlation between observed phenotypes and predicted breeding values. When the training dataset included only data from the evaluated line, non-linear models yielded at best a similar accuracy as linear models. In some cases, when adding a distantly related line, the linear models showed a slight decrease in performance, while non-linear models generally showed no change in accuracy. When only information from a closely related line was used for training, linear models and non-linear radial basis function (RBF) kernel models performed similarly. The multi-trait GBLUP model took advantage of the estimated genetic correlations between the lines. Combining linear and non-linear models improved the accuracy of multi-line genomic prediction. Linear models and non-linear RBF models performed very similarly for genomic prediction, despite the expectation that non-linear models could deal better with the heterogeneous multi-population data. This heterogeneity of the data can be overcome by modelling trait by line combinations as separate but correlated traits, which avoids the occasional occurrence of large negative accuracies when the evaluated line was not included in the training dataset. Furthermore, when using a multi-line training dataset, non-linear models provided information on the genotype data that was complementary to the linear models, which indicates that the underlying data distributions of the three studied lines were indeed heterogeneous.

A Source Area Approach Demonstrates Moderate Predictive Ability but Pronounced Variability of Invasive Species Traits

PubMed Central

Essl, Franz; Dullinger, Stefan

2016-01-01

The search for traits that make alien species invasive has mostly concentrated on comparing successful invaders and different comparison groups with respect to average trait values. By contrast, little attention has been paid to trait variability among invaders. Here, we combine an analysis of trait differences between invasive and non-invasive species with a comparison of multidimensional trait variability within these two species groups. We collected data on biological and distributional traits for 1402 species of the native, non-woody vascular plant flora of Austria. We then compared the subsets of species recorded and not recorded as invasive aliens anywhere in the world, respectively, first, with respect to the sampled traits using univariate and multiple regression models; and, second, with respect to their multidimensional trait diversity by calculating functional richness and dispersion metrics. Attributes related to competitiveness (strategy type, nitrogen indicator value), habitat use (agricultural and ruderal habitats, occurrence under the montane belt), and propagule pressure (frequency) were most closely associated with invasiveness. However, even the best multiple model, including interactions, only explained a moderate fraction of the differences in invasive success. In addition, multidimensional variability in trait space was even larger among invasive than among non-invasive species. This pronounced variability suggests that invasive success has a considerable idiosyncratic component and is probably highly context specific. We conclude that basing risk assessment protocols on species trait profiles will probably face hardly reducible uncertainties. PMID:27187616

A Source Area Approach Demonstrates Moderate Predictive Ability but Pronounced Variability of Invasive Species Traits.

PubMed

Klonner, Günther; Fischer, Stefan; Essl, Franz; Dullinger, Stefan

2016-01-01

The search for traits that make alien species invasive has mostly concentrated on comparing successful invaders and different comparison groups with respect to average trait values. By contrast, little attention has been paid to trait variability among invaders. Here, we combine an analysis of trait differences between invasive and non-invasive species with a comparison of multidimensional trait variability within these two species groups. We collected data on biological and distributional traits for 1402 species of the native, non-woody vascular plant flora of Austria. We then compared the subsets of species recorded and not recorded as invasive aliens anywhere in the world, respectively, first, with respect to the sampled traits using univariate and multiple regression models; and, second, with respect to their multidimensional trait diversity by calculating functional richness and dispersion metrics. Attributes related to competitiveness (strategy type, nitrogen indicator value), habitat use (agricultural and ruderal habitats, occurrence under the montane belt), and propagule pressure (frequency) were most closely associated with invasiveness. However, even the best multiple model, including interactions, only explained a moderate fraction of the differences in invasive success. In addition, multidimensional variability in trait space was even larger among invasive than among non-invasive species. This pronounced variability suggests that invasive success has a considerable idiosyncratic component and is probably highly context specific. We conclude that basing risk assessment protocols on species trait profiles will probably face hardly reducible uncertainties.

A Macroevolutionary Perspective on Multiple Sexual Traits in the Phasianidae (Galliformes)

PubMed Central

Kimball, Rebecca T.; Mary, Colette M. St.; Braun, Edward L.

2011-01-01

Traits involved in sexual signaling are ubiquitous among animals. Although a single trait appears sufficient to convey information, many sexually dimorphic species exhibit multiple sexual signals, which may be costly to signalers and receivers. Given that one signal may be enough, there are many microevolutionary hypotheses to explain the evolution of multiple signals. Here we extend these hypotheses to a macroevolutionary scale and compare those predictions to the patterns of gains and losses of sexual dimorphism in pheasants and partridges. Among nine dimorphic characters, including six intersexual signals and three indicators of competitive ability, all exhibited both gains and losses of dimorphism within the group. Although theories of intersexual selection emphasize gain and elaboration, those six characters exhibited greater rates of loss than gain; in contrast, the competitive traits showed a slight bias towards gains. The available models, when examined in a macroevolutionary framework, did not yield unique predictions, making it difficult to distinguish among them. Even with this limitation, when the predictions of these alternative models were compared with the heterogeneous patterns of evolution of dimorphism in phasianids, it is clear that many different selective processes have been involved in the evolution of sexual signals in this group. PMID:21716735

Novel Applications of Multi-task Learning and Multiple Output Regression to Multiple Genetic Trait Prediction

USDA-ARS?s Scientific Manuscript database

Given a set of biallelic molecular markers, such as SNPs, with genotype values encoded numerically on a collection of plant, animal or human samples, the goal of genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Genetic trait predicti...

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.

Models of Cultural Niche Construction with Selection and Assortative Mating

PubMed Central

Feldman, Marcus W.

2012-01-01

Niche construction is a process through which organisms modify their environment and, as a result, alter the selection pressures on themselves and other species. In cultural niche construction, one or more cultural traits can influence the evolution of other cultural or biological traits by affecting the social environment in which the latter traits may evolve. Cultural niche construction may include either gene-culture or culture-culture interactions. Here we develop a model of this process and suggest some applications of this model. We examine the interactions between cultural transmission, selection, and assorting, paying particular attention to the complexities that arise when selection and assorting are both present, in which case stable polymorphisms of all cultural phenotypes are possible. We compare our model to a recent model for the joint evolution of religion and fertility and discuss other potential applications of cultural niche construction theory, including the evolution and maintenance of large-scale human conflict and the relationship between sex ratio bias and marriage customs. The evolutionary framework we introduce begins to address complexities that arise in the quantitative analysis of multiple interacting cultural traits. PMID:22905167

Identification of Immune Traits Correlated with Dairy Cow Health, Reproduction and Productivity

PubMed Central

Banos, Georgios; Wall, Eileen; Coffey, Michael P.; Bagnall, Ainsley; Gillespie, Sandra; Russell, George C.; McNeilly, Tom N.

2013-01-01

Detailed biological analyses (e.g. epidemiological, genetic) of animal health and fitness in the field are limited by the lack of large-scale recording of individual animals. An alternative approach is to identify immune traits that are associated with these important functions and can be subsequently used in more detailed studies. We have used an experimental dairy herd with uniquely dense phenotypic data to identify a range of potentially useful immune traits correlated with enhanced (or depressed) health and fitness. Blood samples from 248 dairy cows were collected at two-monthly intervals over a 10-month period and analysed for a number of immune traits, including levels of serum proteins associated with the innate immune response and circulating leukocyte populations. Immune measures were matched to individual cow records related to productivity, fertility and disease. Correlations between traits were calculated using bivariate analyses based on animal repeatability and random regression models with a Bonferroni correction to account for multiple testing. A number of significant correlations were found between immune traits and other recorded traits including: CD4+:CD8+ T lymphocyte ratio and subclinical mastitis; % CD8+ lymphocytes and fertility; % CD335+ natural killer cells and lameness episodes; and serum haptoglobin levels and clinical mastitis. Importantly these traits were not associated with reduced productivity and, in the case of cellular immune traits, were highly repeatable. Moreover these immune traits displayed significant between-animal variation suggesting that they may be altered by genetic selection. This study represents the largest simultaneous analysis of multiple immune traits in dairy cattle to-date and demonstrates that a number of immune traits are associated with health events. These traits represent useful selection markers for future programmes aimed at improving animal health and fitness. PMID:23776543

The role of dispositional traits in accounting for country and ethnic group differences on adjustment.

PubMed

Matsumoto, David; Nakagawa, Sanae; Estrada, Aaron

2009-02-01

Country and ethnic group differences on adjustment have been demonstrated numerous times, and the source of these differences has been typically interpreted as cultural. We report two studies in which country (Study 1) and ethnic group (Study 2) differences on depression, anxiety, optimism versus pessimism, well-being, and self-esteem are mediated by dispositional traits. These findings provide an alternative explanation for previously reported country and ethnic group differences on these variables and encourage researchers to consider multiple sources, including traits, in their models and studies.

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

PubMed

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

2016-12-01

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

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.

Multiple correlation analyses of metabolic and endocrine profiles with fertility in primiparous and multiparous cows.

PubMed

Wathes, D C; Bourne, N; Cheng, Z; Mann, G E; Taylor, V J; Coffey, M P

2007-03-01

Results from 4 studies were combined (representing a total of 500 lactations) to investigate the relationships between metabolic parameters and fertility in dairy cows. Information was collected on blood metabolic traits and body condition score at 1 to 2 wk prepartum and at 2, 4, and 7 wk postpartum. Fertility traits were days to commencement of luteal activity, days to first service, days to conception, and failure to conceive. Primiparous and multiparous cows were considered separately. Initial linear regression analyses were used to determine relationships among fertility, metabolic, and endocrine traits at each time point. All metabolic and endocrine traits significantly related to fertility were included in stepwise multiple regression analyses alone (model 1), including peak milk yield and interval to commencement of luteal activity (model 2), and with the further addition of dietary group (model 3). In multiparous cows, extended calving to conception intervals were associated prepartum with greater concentrations of leptin and lesser concentrations of nonesterified fatty acids and urea, and postpartum with reduced insulin-like growth factor-I at 2 wk, greater urea at 7 wk, and greater peak milk yield. In primiparous cows, extended calving to conception intervals were associated with more body condition and more urea prepartum, elevated urea postpartum, and more body condition loss by 7 wk. In conclusion, some metabolic measurements were associated with poorer fertility outcomes. Relationships between fertility and metabolic and endocrine traits varied both according to the lactation number of the cow and with the time relative to calving.

Identifying and exploiting trait-relevant tissues with multiple functional annotations in genome-wide association studies

PubMed Central

Zhang, Shujun

2018-01-01

Genome-wide association studies (GWASs) have identified many disease associated loci, the majority of which have unknown biological functions. Understanding the mechanism underlying trait associations requires identifying trait-relevant tissues and investigating associations in a trait-specific fashion. Here, we extend the widely used linear mixed model to incorporate multiple SNP functional annotations from omics studies with GWAS summary statistics to facilitate the identification of trait-relevant tissues, with which to further construct powerful association tests. Specifically, we rely on a generalized estimating equation based algorithm for parameter inference, a mixture modeling framework for trait-tissue relevance classification, and a weighted sequence kernel association test constructed based on the identified trait-relevant tissues for powerful association analysis. We refer to our analytic procedure as the Scalable Multiple Annotation integration for trait-Relevant Tissue identification and usage (SMART). With extensive simulations, we show how our method can make use of multiple complementary annotations to improve the accuracy for identifying trait-relevant tissues. In addition, our procedure allows us to make use of the inferred trait-relevant tissues, for the first time, to construct more powerful SNP set tests. We apply our method for an in-depth analysis of 43 traits from 28 GWASs using tissue-specific annotations in 105 tissues derived from ENCODE and Roadmap. Our results reveal new trait-tissue relevance, pinpoint important annotations that are informative of trait-tissue relationship, and illustrate how we can use the inferred trait-relevant tissues to construct more powerful association tests in the Wellcome trust case control consortium study. PMID:29377896

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-02-01

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

Association analysis and marker development for grain quality traits using USDA diverse rice germplasm collections

USDA-ARS?s Scientific Manuscript database

New molecular markers are being designed and validated for grain quality improvement based on computationally assisted analysis of genome wide association study (GWAS) findings across multiple panels and multiple grain quality traits. The traits include grain dimensions, apparent amylose content (A...

Framework for analyzing ecological trait-based models in multidimensional niche spaces

NASA Astrophysics Data System (ADS)

Biancalani, Tommaso; DeVille, Lee; Goldenfeld, Nigel

2015-05-01

We develop a theoretical framework for analyzing ecological models with a multidimensional niche space. Our approach relies on the fact that ecological niches are described by sequences of symbols, which allows us to include multiple phenotypic traits. Ecological drivers, such as competitive exclusion, are modeled by introducing the Hamming distance between two sequences. We show that a suitable transform diagonalizes the community interaction matrix of these models, making it possible to predict the conditions for niche differentiation and, close to the instability onset, the asymptotically long time population distributions of niches. We exemplify our method using the Lotka-Volterra equations with an exponential competition kernel.

Modeling lactation curves and estimation of genetic parameters in Holstein cows using multiple-trait random regression models.

PubMed

Kheirabadi, Khabat; Rashidi, Amir; Alijani, Sadegh; Imumorin, Ikhide

2014-11-01

We compared the goodness of fit of three mathematical functions (including: Legendre polynomials, Lidauer-Mäntysaari function and Wilmink function) for describing the lactation curve of primiparous Iranian Holstein cows by using multiple-trait random regression models (MT-RRM). Lactational submodels provided the largest daily additive genetic (AG) and permanent environmental (PE) variance estimates at the end and at the onset of lactation, respectively, as well as low genetic correlations between peripheral test-day records. For all models, heritability estimates were highest at the end of lactation (245 to 305 days) and ranged from 0.05 to 0.26, 0.03 to 0.12 and 0.04 to 0.24 for milk, fat and protein yields, respectively. Generally, the genetic correlations between traits depend on how far apart they are or whether they are on the same day in any two traits. On average, genetic correlations between milk and fat were the lowest and those between fat and protein were intermediate, while those between milk and protein were the highest. Results from all criteria (Akaike's and Schwarz's Bayesian information criterion, and -2*logarithm of the likelihood function) suggested that a model with 2 and 5 coefficients of Legendre polynomials for AG and PE effects, respectively, was the most adequate for fitting the data. © 2014 Japanese Society of Animal Science.

Locally Dependent Latent Trait Model and the Dutch Identity Revisited.

ERIC Educational Resources Information Center

Ip, Edward H.

2002-01-01

Proposes a class of locally dependent latent trait models for responses to psychological and educational tests. Focuses on models based on a family of conditional distributions, or kernel, that describes joint multiple item responses as a function of student latent trait, not assuming conditional independence. Also proposes an EM algorithm for…

Construction of multiple linear regression models using blood biomarkers for selecting against abdominal fat traits in broilers.

PubMed

Dong, J Q; Zhang, X Y; Wang, S Z; Jiang, X F; Zhang, K; Ma, G W; Wu, M Q; Li, H; Zhang, H

2018-01-01

Plasma very low-density lipoprotein (VLDL) can be used to select for low body fat or abdominal fat (AF) in broilers, but its correlation with AF is limited. We investigated whether any other biochemical indicator can be used in combination with VLDL for a better selective effect. Nineteen plasma biochemical indicators were measured in male chickens from the Northeast Agricultural University broiler lines divergently selected for AF content (NEAUHLF) in the fed state at 46 and 48 d of age. The average concentration of every parameter for the 2 d was used for statistical analysis. Levels of these 19 plasma biochemical parameters were compared between the lean and fat lines. The phenotypic correlations between these plasma biochemical indicators and AF traits were analyzed. Then, multiple linear regression models were constructed to select the best model used for selecting against AF content. and the heritabilities of plasma indicators contained in the best models were estimated. The results showed that 11 plasma biochemical indicators (triglycerides, total bile acid, total protein, globulin, albumin/globulin, aspartate transaminase, alanine transaminase, gamma-glutamyl transpeptidase, uric acid, creatinine, and VLDL) differed significantly between the lean and fat lines (P < 0.01), and correlated significantly with AF traits (P < 0.05). The best multiple linear regression models based on albumin/globulin, VLDL, triglycerides, globulin, total bile acid, and uric acid, had higher R2 (0.73) than the model based only on VLDL (0.21). The plasma parameters included in the best models had moderate heritability estimates (0.21 ≤ h2 ≤ 0.43). These results indicate that these multiple linear regression models can be used to select for lean broiler chickens. © 2017 Poultry Science Association Inc.

Random regression analysis for body weights and main morphological traits in genetically improved farmed tilapia (Oreochromis niloticus).

PubMed

He, Jie; Zhao, Yunfeng; Zhao, Jingli; Gao, Jin; Xu, Pao; Yang, Runqing

2018-02-01

To genetically analyse growth traits in genetically improved farmed tilapia (GIFT), the body weight (BWE) and main morphological traits, including body length (BL), body depth (BD), body width (BWI), head length (HL) and length of the caudal peduncle (CPL), were measured six times in growth duration on 1451 fish from 45 mixed families of full and half sibs. A random regression model (RRM) was used to model genetic changes of the growth traits with days of age and estimate the heritability for any growth point and genetic correlations between pairwise growth points. Using the covariance function based on optimal RRMs, the heritabilities were estimated to be from 0.102 to 0.662 for BWE, 0.157 to 0.591 for BL, 0.047 to 0.621 for BD, 0.018 to 0.577 for BWI, 0.075 to 0.597 for HL and 0.032 to 0.610 for CPL between 60 and 140 days of age. All genetic correlations exceeded 0.5 between pairwise growth points. Moreover, the traits at initial days of age showed less correlation with those at later days of age. With phenotypes observed repeatedly, the model choice showed that the optimal RRMs could more precisely predict breeding values at a specific growth time than repeatability models or multiple trait animal models, which enhanced the efficiency of selection for the BWE and main morphological traits.

Multilevel Higher-Order Item Response Theory Models

ERIC Educational Resources Information Center

Huang, Hung-Yu; Wang, Wen-Chung

2014-01-01

In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…

Evolution in leaps: The punctuated accumulation and loss of cultural innovations

PubMed Central

Kolodny, Oren; Creanza, Nicole; Feldman, Marcus W.

2015-01-01

Archaeological accounts of cultural change reveal a fundamental conflict: Some suggest that change is gradual, accelerating over time, whereas others indicate that it is punctuated, with long periods of stasis interspersed by sudden gains or losses of multiple traits. Existing models of cultural evolution, inspired by models of genetic evolution, lend support to the former and do not generate trajectories that include large-scale punctuated change. We propose a simple model that can give rise to both exponential and punctuated patterns of gain and loss of cultural traits. In it, cultural innovation comprises several realistic interdependent processes that occur at different rates. The model also takes into account two properties intrinsic to cultural evolution: the differential distribution of traits among social groups and the impact of environmental change. In our model, a population may be subdivided into groups with different cultural repertoires leading to increased susceptibility to cultural loss, whereas environmental change may lead to rapid loss of traits that are not useful in a new environment. Taken together, our results suggest the usefulness of a concept of an effective cultural population size. PMID:26598675

Evolution in leaps: The punctuated accumulation and loss of cultural innovations.

PubMed

Kolodny, Oren; Creanza, Nicole; Feldman, Marcus W

2015-12-08

Archaeological accounts of cultural change reveal a fundamental conflict: Some suggest that change is gradual, accelerating over time, whereas others indicate that it is punctuated, with long periods of stasis interspersed by sudden gains or losses of multiple traits. Existing models of cultural evolution, inspired by models of genetic evolution, lend support to the former and do not generate trajectories that include large-scale punctuated change. We propose a simple model that can give rise to both exponential and punctuated patterns of gain and loss of cultural traits. In it, cultural innovation comprises several realistic interdependent processes that occur at different rates. The model also takes into account two properties intrinsic to cultural evolution: the differential distribution of traits among social groups and the impact of environmental change. In our model, a population may be subdivided into groups with different cultural repertoires leading to increased susceptibility to cultural loss, whereas environmental change may lead to rapid loss of traits that are not useful in a new environment. Taken together, our results suggest the usefulness of a concept of an effective cultural population size.

A fully traits-based approach to modeling global vegetation distribution.

PubMed

van Bodegom, Peter M; Douma, Jacob C; Verheijen, Lieneke M

2014-09-23

Dynamic Global Vegetation Models (DGVMs) are indispensable for our understanding of climate change impacts. The application of traits in DGVMs is increasingly refined. However, a comprehensive analysis of the direct impacts of trait variation on global vegetation distribution does not yet exist. Here, we present such analysis as proof of principle. We run regressions of trait observations for leaf mass per area, stem-specific density, and seed mass from a global database against multiple environmental drivers, making use of findings of global trait convergence. This analysis explained up to 52% of the global variation of traits. Global trait maps, generated by coupling the regression equations to gridded soil and climate maps, showed up to orders of magnitude variation in trait values. Subsequently, nine vegetation types were characterized by the trait combinations that they possess using Gaussian mixture density functions. The trait maps were input to these functions to determine global occurrence probabilities for each vegetation type. We prepared vegetation maps, assuming that the most probable (and thus, most suited) vegetation type at each location will be realized. This fully traits-based vegetation map predicted 42% of the observed vegetation distribution correctly. Our results indicate that a major proportion of the predictive ability of DGVMs with respect to vegetation distribution can be attained by three traits alone if traits like stem-specific density and seed mass are included. We envision that our traits-based approach, our observation-driven trait maps, and our vegetation maps may inspire a new generation of powerful traits-based DGVMs.

Multiple-trait estimates of genetic parameters for metabolic disease traits, fertility disorders, and their predictors in Canadian Holsteins.

PubMed

Jamrozik, J; Koeck, A; Kistemaker, G J; Miglior, F

2016-03-01

Producer-recorded health data for metabolic disease traits and fertility disorders on 35,575 Canadian Holstein cows were jointly analyzed with selected indicator traits. Metabolic diseases included clinical ketosis (KET) and displaced abomasum (DA); fertility disorders were metritis (MET) and retained placenta (RP); and disease indicators were fat-to-protein ratio, milk β-hydroxybutyrate, and body condition score (BCS) in the first lactation. Traits in first and later (up to fifth) lactations were treated as correlated in the multiple-trait (13 traits in total) animal linear model. Bayesian methods with Gibbs sampling were implemented for the analysis. Estimates of heritability for disease incidence were low, up to 0.06 for DA in first lactation. Among disease traits, the environmental herd-year variance constituted 4% of the total variance for KET and less for other traits. First- and later-lactation disease traits were genetically correlated (from 0.66 to 0.72) across all traits, indicating different genetic backgrounds for first and later lactations. Genetic correlations between KET and DA were relatively strong and positive (up to 0.79) in both first- and later-lactation cows. Genetic correlations between fertility disorders were slightly lower. Metritis was strongly genetically correlated with both metabolic disease traits in the first lactation only. All other genetic correlations between metabolic and fertility diseases were statistically nonsignificant. First-lactation KET and MET were strongly positively correlated with later-lactation performance for these traits due to the environmental herd-year effect. Indicator traits were moderately genetically correlated (from 0.30 to 0.63 in absolute values) with both metabolic disease traits in the first lactation. Smaller and mostly nonsignificant genetic correlations were among indicators and metabolic diseases in later lactations. The only significant genetic correlations between indicators and fertility disorders were those between BCS and MET in both first and later lactations. Results indicated a limited value of a joint genetic evaluation model for metabolic disease traits and fertility disorders in Canadian Holsteins. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Genetic relationships between detailed reproductive traits and performance traits in Holstein-Friesian dairy cattle.

PubMed

Carthy, T R; Ryan, D P; Fitzgerald, A M; Evans, R D; Berry, D P

2016-02-01

The objective of the study was to estimate the genetic relationships between detailed reproductive traits derived from ultrasound examination of the reproductive tract and a range of performance traits in Holstein-Friesian dairy cows. The performance traits investigated included calving performance, milk production, somatic cell score (i.e., logarithm transformation of somatic cell count), carcass traits, and body-related linear type traits. Detailed reproductive traits included (1) resumed cyclicity at the time of examination, (2) multiple ovulations, (3) early ovulation, (4) heat detection, (5) ovarian cystic structures, (6) embryo loss, and (7) uterine score, measured on a 1 (little or no fluid with normal tone) to 4 (large quantity of fluid with a flaccid tone) scale, based on the tone of the uterine wall and the quantity of fluid present in the uterus. (Co)variance components were estimated using a repeatability animal linear mixed model. Genetic merit for greater milk, fat, and protein yield was associated with a reduced ability to resume cyclicity postpartum (genetic correlations ranged from -0.25 to -0.15). Higher genetic merit for milk yield was also associated with a greater genetic susceptibility to multiple ovulations. Genetic predisposition to elevated somatic cell score was associated with a decreased likelihood of cyclicity postpartum (genetic correlation of -0.32) and a greater risk of both multiple ovulations (genetic correlation of 0.25) and embryo loss (genetic correlation of 0.32). Greater body condition score was genetically associated with an increased likelihood of resumption of cyclicity postpartum (genetic correlation of 0.52). Genetically heavier, fatter carcasses with better conformation were also associated with an increased likelihood of resumed cyclicity by the time of examination (genetic correlations ranged from 0.24 to 0.41). Genetically heavier carcasses were associated with an inferior uterine score as well as a greater predisposition to embryo loss. Despite the overall antagonistic relationship between reproductive performance and both milk and carcass traits, not all detailed aspects of reproduction performance exhibited an antagonistic relationship. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. 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

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.

Drinking motives as mediators of the impulsivity-substance use relation: pathways for negative urgency, lack of premeditation, and sensation seeking.

PubMed

Adams, Zachary W; Kaiser, Alison J; Lynam, Donald R; Charnigo, Richard J; Milich, Richard

2012-07-01

Trait impulsivity is a reliable, robust predictor of risky, problematic alcohol use. Mounting evidence supports a multidimensional model of impulsivity, whereby several distinct traits serve as personality pathways to rash action. Different impulsivity-related traits may predispose individuals to drink for different reasons (e.g., to enhance pleasure, to cope with distress) and these different motives may, in turn, influence drinking behavior. Previous findings support such a mediational model for two well-studied traits: sensation seeking and lack of premeditation. This study addresses other impulsivity-related traits, including negative urgency. College students (N=432) completed questionnaires assessing personality, drinking motives, and multiple indicators of problematic drinking. Negative urgency, sensation seeking, and lack of premeditation were all significantly related to problematic drinking. When drinking motives were included in the model, direct effects for sensation seeking and lack of premeditation remained significant, and indirect effects of sensation seeking and lack of premeditation on problematic drinking were observed through enhancement motives. A distinct pathway was observed for negative urgency. Negative urgency bore a significant total effect on problematic drinking through both coping and enhancement motives. This study highlights unique motivational pathways through which different impulsive traits may operate, suggesting that interventions aimed at preventing or reducing problematic drinking should be tailored to individuals' personalities. For instance, individuals high in negative urgency may benefit from learning healthier strategies for coping with distress. Copyright © 2012 Elsevier Ltd. All rights reserved.

Drinking Motives as Mediators of the Impulsivity-Substance Use Relation: Pathways for Negative Urgency, Lack of Premeditation, and Sensation Seeking

PubMed Central

Adams, Zachary W.; Kaiser, Alison J.; Lynam, Donald R.; Charnigo, Richard J.; Milich, Richard

2012-01-01

Trait impulsivity is a reliable, robust predictor of risky, problematic alcohol use. Mounting evidence supports a multidimensional model of impulsivity, whereby several distinct traits serve as personality pathways to rash action. Different impulsivity-related traits may predispose individuals to drink for different reasons (e.g., to enhance pleasure, to cope with distress) and these different motives may, in turn, influence drinking behavior. Previous findings support such a mediational model for two well-studied traits: sensation seeking and lack of premeditation. This study addresses other impulsivity-related traits, including negative urgency. College students (N = 432) completed questionnaires assessing personality, drinking motives, and multiple indicators of problematic drinking. Negative urgency, sensation seeking, and lack of premeditation were all significantly related to problematic drinking. When drinking motives were included in the model, direct effects for sensation seeking and lack of premeditation remained significant, and indirect effects of sensation seeking and lack of premeditation on problematic drinking were observed through enhancement motives. A distinct pathway was observed for negative urgency. Negative urgency bore a significant total effect on problematic drinking through both coping and enhancement motives. This study highlights unique motivational pathways through which different impulsive traits may operate, suggesting that interventions aimed at preventing or reducing problematic drinking should be tailored to individuals' personalities. For instance, individuals high in negative urgency may benefit from learning healthier strategies for coping with distress. PMID:22472524

Leaf and stem economics spectra drive diversity of functional plant traits in a dynamic global vegetation model.

PubMed

Sakschewski, Boris; von Bloh, Werner; Boit, Alice; Rammig, Anja; Kattge, Jens; Poorter, Lourens; Peñuelas, Josep; Thonicke, Kirsten

2015-01-22

Functional diversity is critical for ecosystem dynamics, stability and productivity. However, dynamic global vegetation models (DGVMs) which are increasingly used to simulate ecosystem functions under global change, condense functional diversity to plant functional types (PFTs) with constant parameters. Here, we develop an individual- and trait-based version of the DGVM LPJmL (Lund-Potsdam-Jena managed Land) called LPJmL- flexible individual traits (LPJmL-FIT) with flexible individual traits) which we apply to generate plant trait maps for the Amazon basin. LPJmL-FIT incorporates empirical ranges of five traits of tropical trees extracted from the TRY global plant trait database, namely specific leaf area (SLA), leaf longevity (LL), leaf nitrogen content (N area ), the maximum carboxylation rate of Rubisco per leaf area (vcmaxarea), and wood density (WD). To scale the individual growth performance of trees, the leaf traits are linked by trade-offs based on the leaf economics spectrum, whereas wood density is linked to tree mortality. No preselection of growth strategies is taking place, because individuals with unique trait combinations are uniformly distributed at tree establishment. We validate the modeled trait distributions by empirical trait data and the modeled biomass by a remote sensing product along a climatic gradient. Including trait variability and trade-offs successfully predicts natural trait distributions and achieves a more realistic representation of functional diversity at the local to regional scale. As sites of high climatic variability, the fringes of the Amazon promote trait divergence and the coexistence of multiple tree growth strategies, while lower plant trait diversity is found in the species-rich center of the region with relatively low climatic variability. LPJmL-FIT enables to test hypotheses on the effects of functional biodiversity on ecosystem functioning and to apply the DGVM to current challenges in ecosystem management from local to global scales, that is, deforestation and climate change effects. © 2015 John Wiley & Sons Ltd.

Mediation of the relationship between callous-unemotional traits and proactive aggression by amygdala response to fear among children with conduct problems.

PubMed

Lozier, Leah M; Cardinale, Elise M; VanMeter, John W; Marsh, Abigail A

2014-06-01

Among youths with conduct problems, callous-unemotional (CU) traits are known to be an important determinant of symptom severity, prognosis, and treatment responsiveness. But positive correlations between conduct problems and CU traits result in suppressor effects that may mask important neurobiological distinctions among subgroups of children with conduct problems. To assess the unique neurobiological covariates of CU traits and externalizing behaviors in youths with conduct problems and determine whether neural dysfunction linked to CU traits mediates the link between callousness and proactive aggression. This cross-sectional case-control study involved behavioral testing and neuroimaging that were conducted at a university research institution. Neuroimaging was conducted using a 3-T Siemens magnetic resonance imaging scanner. It included 46 community-recruited male and female juveniles aged 10 to 17 years, including 16 healthy control participants and 30 youths with conduct problems with both low and high levels of CU traits. Blood oxygenation level-dependent signal as measured via functional magnetic resonance imaging during an implicit face-emotion processing task and analyzed using whole-brain and region of interest-based analysis of variance and multiple-regression analyses. Analysis of variance revealed no group differences in the amygdala. By contrast, consistent with the existence of suppressor effects, multiple-regression analysis found amygdala responses to fearful expressions to be negatively associated with CU traits (x = 26, y = 0, z = -12; k = 1) and positively associated with externalizing behavior (x = 24, y = 0, z = -14; k = 8) when both variables were modeled simultaneously. Reduced amygdala responses mediated the relationship between CU traits and proactive aggression. The results linked proactive aggression in youths with CU traits to hypoactive amygdala responses to emotional distress cues, consistent with theories that externalizing behaviors, particularly proactive aggression, in youths with these traits stem from deficient empathic responses to distress. Amygdala hypoactivity may represent an intermediate phenotype, offering new insights into effective treatment strategies for conduct problems.

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.

Multiplicative Measurements of a Trait Anxiety Scale as Predictors of Burnout

ERIC Educational Resources Information Center

Cremades, J. Gualberto; Wated, Guillermo; Wiggins, Matthew S.

2011-01-01

The purpose of the present study was to investigate whether combining the two dimensions of anxiety (i.e., intensity and direction) by using a multiplicative model would strengthen the prediction of burnout. Collegiate athletes (N = 157) completed the Athlete Burnout Questionnaire as well as a trait version of the Competitive State Anxiety…

Do gamblers eat more salt? Testing a latent trait model of covariance in consumption

PubMed Central

Goodwin, Belinda C.; Browne, Matthew; Rockloff, Matthew; Donaldson, Phillip

2015-01-01

A diverse class of stimuli, including certain foods, substances, media, and economic behaviours, may be described as ‘reward-oriented’ in that they provide immediate reinforcement with little initial investment. Neurophysiological and personality concepts, including dopaminergic dysfunction, reward sensitivity and rash impulsivity, each predict the existence of a latent behavioural trait that leads to increased consumption of all stimuli in this class. Whilst bivariate relationships (co-morbidities) are often reported in the literature, to our knowledge, a multivariate investigation of this possible trait has not been done. We surveyed 1,194 participants (550 male) on their typical weekly consumption of 11 types of reward-oriented stimuli, including fast food, salt, caffeine, television, gambling products, and illicit drugs. Confirmatory factor analysis was used to compare models in a 3×3 structure, based on the definition of a single latent factor (none, fixed loadings, or estimated loadings), and assumed residual covariance structure (none, a-priori / literature based, or post-hoc / data-driven). The inclusion of a single latent behavioural ‘consumption’ factor significantly improved model fit in all cases. Also confirming theoretical predictions, estimated factor loadings on reward-oriented indicators were uniformly positive, regardless of assumptions regarding residual covariances. Additionally, the latent trait was found to be negatively correlated with the non-reward-oriented indicators of fruit and vegetable consumption. The findings support the notion of a single behavioural trait leading to increased consumption of reward-oriented stimuli across multiple modalities. We discuss implications regarding the concentration of negative lifestyle-related health behaviours. PMID:26551907

Do gamblers eat more salt? Testing a latent trait model of covariance in consumption.

PubMed

Goodwin, Belinda C; Browne, Matthew; Rockloff, Matthew; Donaldson, Phillip

2015-09-01

A diverse class of stimuli, including certain foods, substances, media, and economic behaviours, may be described as 'reward-oriented' in that they provide immediate reinforcement with little initial investment. Neurophysiological and personality concepts, including dopaminergic dysfunction, reward sensitivity and rash impulsivity, each predict the existence of a latent behavioural trait that leads to increased consumption of all stimuli in this class. Whilst bivariate relationships (co-morbidities) are often reported in the literature, to our knowledge, a multivariate investigation of this possible trait has not been done. We surveyed 1,194 participants (550 male) on their typical weekly consumption of 11 types of reward-oriented stimuli, including fast food, salt, caffeine, television, gambling products, and illicit drugs. Confirmatory factor analysis was used to compare models in a 3×3 structure, based on the definition of a single latent factor (none, fixed loadings, or estimated loadings), and assumed residual covariance structure (none, a-priori / literature based, or post-hoc / data-driven). The inclusion of a single latent behavioural 'consumption' factor significantly improved model fit in all cases. Also confirming theoretical predictions, estimated factor loadings on reward-oriented indicators were uniformly positive, regardless of assumptions regarding residual covariances. Additionally, the latent trait was found to be negatively correlated with the non-reward-oriented indicators of fruit and vegetable consumption. The findings support the notion of a single behavioural trait leading to increased consumption of reward-oriented stimuli across multiple modalities. We discuss implications regarding the concentration of negative lifestyle-related health behaviours.

Multitrait successional forest dynamics enable diverse competitive coexistence

PubMed Central

Brännström, Åke; Westoby, Mark; Dieckmann, Ulf

2017-01-01

To explain diversity in forests, niche theory must show how multiple plant species coexist while competing for the same resources. Although successional processes are widespread in forests, theoretical work has suggested that differentiation in successional strategy allows only a few species stably to coexist, including only a single shade tolerant. However, this conclusion is based on current niche models, which encode a very simplified view of plant communities, suggesting that the potential for niche differentiation has remained unexplored. Here, we show how extending successional niche models to include features common to all vegetation—height-structured competition for light under a prevailing disturbance regime and two trait-mediated tradeoffs in plant function—enhances the diversity of species that can be maintained, including a diversity of shade tolerants. We identify two distinct axes of potential niche differentiation, corresponding to the traits leaf mass per unit leaf area and height at maturation. The first axis allows for coexistence of different shade tolerances and the second axis for coexistence among species with the same shade tolerance. Addition of this second axis leads to communities with a high diversity of shade tolerants. Niche differentiation along the second axis also generates regions of trait space wherein fitness is almost equalized, an outcome we term “evolutionarily emergent near-neutrality.” For different environmental conditions, our model predicts diverse vegetation types and trait mixtures, akin to observations. These results indicate that the outcomes of successional niche differentiation are richer than previously thought and potentially account for mixtures of traits and species observed in forests worldwide. PMID:28283658

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

PubMed

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

2015-01-08

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

The TERRA-PNW Dataset: A New Source for Standardized Plant Trait, Forest Carbon Cycling, and Soil Properties Measurements from the Pacific Northwest US, 2000-2014.

NASA Astrophysics Data System (ADS)

Berner, L. T.; Law, B. E.

2015-12-01

Plant traits include physiological, morphological, and biogeochemical characteristics that in combination determine a species sensitivity to environmental conditions. Standardized, co-located, and geo-referenced species- and plot-level measurements are needed to address variation in species sensitivity to climate change impacts and for ecosystem process model development, parameterization and testing. We present a new database of plant trait, forest carbon cycling, and soil property measurements derived from multiple TERRA-PNW projects in the Pacific Northwest US, spanning 2000-2014. The database includes measurements from over 200 forest plots across Oregon and northern California, where the data were explicitly collected for scaling and modeling regional terrestrial carbon processes with models such as Biome-BGC and the Community Land Model. Some of the data are co-located at AmeriFlux sites in the region. The database currently contains leaf trait measurements (specific leaf area, leaf longevity, leaf carbon and nitrogen) from over 1,200 branch samples and 30 species, as well as plot-level biomass and productivity components, and soil carbon and nitrogen. Standardized protocols were used across projects, as summarized in an FAO protocols document. The database continues to expand and will include agricultural crops. The database will be hosted by the Oak Ridge National Laboratory (ORLN) Distributed Active Archive Center (DAAC). We hope that other regional databases will become publicly available to help enable Earth System Modeling to simulate species-level sensitivity to climate at regional to global scales.

Evaluating the Dimensionality of Pornography.

PubMed

Busby, Dean M; Chiu, Hsin-Yao; Olsen, Joseph A; Willoughby, Brian J

2017-08-01

Pornography may be a construct with a single trait or one with many traits. Research in the past was inconsistent in this regard with most researchers assuming that pornography was unidimensional (with one single trait of pornography). However, the considerable amounts of residual variation found in these studies beyond that explained by the single trait hints at what might be a multidimensional construct (with multiple traits such as sensitization and differentiation). Consequently, in this study, we intended to address the question of whether pornography consisted of a single trait or if it was multidimensional. Using MTurk, 2173 participants from the United States and the Commonwealth of Nations (in which pornography is not strictly illegal) were recruited and asked to rate how pornographic they thought a list of different depictions were. The data were analyzed utilizing the cross-validation procedure in which two subsamples were created from the main sample and one was used to establish the model building and the other to validate the model. Various models, including first-order and higher-order exploratory and confirmatory factor models, were tested. Results indicated that a bi-factor (multidimensional) model generated the best model fit, and that it was most appropriate to consider pornography multidimensional. The final model contained two dimensions ("Sensitization" and "Differentiation"). While sensitization revealed the participants' general tendency to rate all items to be more or less pornographic, differentiation revealed the participants' tendency to differentiate highly pornographic items from less pornographic items. Based on the findings of this study, we suggest that future research on the usage and effects of pornography be conducted while taking into consideration the multidimensional nature of pornography.

Inclusion of ecologically based trait variation in plant functional types reduces the projected land carbon sink in an earth system model.

PubMed

Verheijen, Lieneke M; Aerts, Rien; Brovkin, Victor; Cavender-Bares, Jeannine; Cornelissen, Johannes H C; Kattge, Jens; van Bodegom, Peter M

2015-08-01

Earth system models demonstrate large uncertainty in projected changes in terrestrial carbon budgets. The lack of inclusion of adaptive responses of vegetation communities to the environment has been suggested to hamper the ability of modeled vegetation to adequately respond to environmental change. In this study, variation in functional responses of vegetation has been added to an earth system model (ESM) based on ecological principles. The restriction of viable mean trait values of vegetation communities by the environment, called 'habitat filtering', is an important ecological assembly rule and allows for determination of global scale trait-environment relationships. These relationships were applied to model trait variation for different plant functional types (PFTs). For three leaf traits (specific leaf area, maximum carboxylation rate at 25 °C, and maximum electron transport rate at 25 °C), relationships with multiple environmental drivers, such as precipitation, temperature, radiation, and CO2 , were determined for the PFTs within the Max Planck Institute ESM. With these relationships, spatiotemporal variation in these formerly fixed traits in PFTs was modeled in global change projections (IPCC RCP8.5 scenario). Inclusion of this environment-driven trait variation resulted in a strong reduction of the global carbon sink by at least 33% (2.1 Pg C yr(-1) ) from the 2nd quarter of the 21st century onward compared to the default model with fixed traits. In addition, the mid- and high latitudes became a stronger carbon sink and the tropics a stronger carbon source, caused by trait-induced differences in productivity and relative respirational costs. These results point toward a reduction of the global carbon sink when including a more realistic representation of functional vegetation responses, implying more carbon will stay airborne, which could fuel further climate change. © 2015 John Wiley & Sons Ltd.

Born to Burnout: A Meta-Analytic Path Model of Personality, Job Burnout, and Work Outcomes

ERIC Educational Resources Information Center

Swider, Brian W.; Zimmerman, Ryan D.

2010-01-01

We quantitatively summarized the relationship between Five-Factor Model personality traits, job burnout dimensions (emotional exhaustion, depersonalization, and personal accomplishment), and absenteeism, turnover, and job performance. All five of the Five-Factor Model personality traits had multiple true score correlations of 0.57 with emotional…

Genetic variation and gene expression across multiple tissues and developmental stages in a nonhuman primate.

PubMed

Jasinska, Anna J; Zelaya, Ivette; Service, Susan K; Peterson, Christine B; Cantor, Rita M; Choi, Oi-Wa; DeYoung, Joseph; Eskin, Eleazar; Fairbanks, Lynn A; Fears, Scott; Furterer, Allison E; Huang, Yu S; Ramensky, Vasily; Schmitt, Christopher A; Svardal, Hannes; Jorgensen, Matthew J; Kaplan, Jay R; Villar, Diego; Aken, Bronwen L; Flicek, Paul; Nag, Rishi; Wong, Emily S; Blangero, John; Dyer, Thomas D; Bogomolov, Marina; Benjamini, Yoav; Weinstock, George M; Dewar, Ken; Sabatti, Chiara; Wilson, Richard K; Jentsch, J David; Warren, Wesley; Coppola, Giovanni; Woods, Roger P; Freimer, Nelson B

2017-12-01

By analyzing multitissue gene expression and genome-wide genetic variation data in samples from a vervet monkey pedigree, we generated a transcriptome resource and produced the first catalog of expression quantitative trait loci (eQTLs) in a nonhuman primate model. This catalog contains more genome-wide significant eQTLs per sample than comparable human resources and identifies sex- and age-related expression patterns. Findings include a master regulatory locus that likely has a role in immune function and a locus regulating hippocampal long noncoding RNAs (lncRNAs), whose expression correlates with hippocampal volume. This resource will facilitate genetic investigation of quantitative traits, including brain and behavioral phenotypes relevant to neuropsychiatric disorders.

Gene flow from single and stacked herbicide-resistant rice (Oryza sativa): modeling occurrence of multiple herbicide-resistant weedy rice.

PubMed

Dauer, Joseph; Hulting, Andrew; Carlson, Dale; Mankin, Luke; Harden, John; Mallory-Smith, Carol

2018-02-01

Provisia™ rice (PV), a non-genetically engineered (GE) quizalofop-resistant rice, will provide growers with an additional option for weed management to use in conjunction with Clearfield ® rice (CL) production. Modeling compared the impact of stacking resistance traits versus single traits in rice on introgression of the resistance trait to weedy rice (also called red rice). Common weed management practices were applied to 2-, 3- and 4-year crop rotations, and resistant and multiple-resistant weedy rice seeds, seedlings and mature plants were tracked for 15 years. Two-year crop rotations resulted in resistant weedy rice after 2 years with abundant populations (exceeding 0.4 weedy rice plants m -2 ) occurring after 7 years. When stacked trait rice was rotated with soybeans in a 3-year rotation and with soybeans and CL in a 4-year rotation, multiple-resistance occurred after 2-5 years with abundant populations present in 4-9 years. When CL rice, PV rice, and soybeans were used in 3- and 4-year rotations, the median time of first appearance of multiple-resistance was 7-11 years and reached abundant levels in 10-15 years. Maintaining separate CL and PV rice systems, in rotation with other crops and herbicides, minimized the evolution of multiple herbicide-resistant weedy rice through gene flow compared to stacking herbicide resistance traits. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

The genetic basis of traits regulating sperm competition and polyandry: can selection favour the evolution of good- and sexy-sperm?

PubMed

Evans, Jonathan P; Simmons, Leigh W

2008-09-01

The good-sperm and sexy-sperm (GS-SS) hypotheses predict that female multiple mating (polyandry) can fuel sexual selection for heritable male traits that promote success in sperm competition. A major prediction generated by these models, therefore, is that polyandry will benefit females indirectly via their sons' enhanced fertilization success. Furthermore, like classic 'good genes' and 'sexy son' models for the evolution of female preferences, GS-SS processes predict a genetic correlation between genes for female mating frequency (analogous to the female preference) and those for traits influencing fertilization success (the sexually selected traits). We examine the premise for these predictions by exploring the genetic basis of traits thought to influence fertilization success and female mating frequency. We also highlight recent debates that stress the possible genetic constraints to evolution of traits influencing fertilization success via GS-SS processes, including sex-linked inheritance, nonadditive effects, interacting parental genotypes, and trade-offs between integrated ejaculate components. Despite these possible constraints, the available data suggest that male traits involved in sperm competition typically exhibit substantial additive genetic variance and rapid evolutionary responses to selection. Nevertheless, the limited data on the genetic variation in female mating frequency implicate strong genetic maternal effects, including X-linkage, which is inconsistent with GS-SS processes. Although the relative paucity of studies on the genetic basis of polyandry does not allow us to draw firm conclusions about the evolutionary origins of this trait, the emerging pattern of sex linkage in genes for polyandry is more consistent with an evolutionary history of antagonistic selection over mating frequency. We advocate further development of GS-SS theory to take account of the complex evolutionary dynamics imposed by sexual conflict over mating frequency.

Modelling biological invasions: species traits, species interactions, and habitat heterogeneity.

PubMed

Cannas, Sergio A; Marco, Diana E; Páez, Sergio A

2003-05-01

In this paper we explore the integration of different factors to understand, predict and control ecological invasions, through a general cellular automaton model especially developed. The model includes life history traits of several species in a modular structure interacting multiple cellular automata. We performed simulations using field values corresponding to the exotic Gleditsia triacanthos and native co-dominant trees in a montane area. Presence of G. triacanthos juvenile bank was a determinant condition for invasion success. Main parameters influencing invasion velocity were mean seed dispersal distance and minimum reproductive age. Seed production had a small influence on the invasion velocity. Velocities predicted by the model agreed well with estimations from field data. Values of population density predicted matched field values closely. The modular structure of the model, the explicit interaction between the invader and the native species, and the simplicity of parameters and transition rules are novel features of the model.

The China Plant Trait Database: toward a comprehensive regional compilation of functional traits for land plants.

PubMed

Wang, Han; Harrison, Sandy P; Prentice, Iain C; Yang, Yanzheng; Bai, Fan; Togashi, Henrique F; Wang, Meng; Zhou, Shuangxi; Ni, Jian

2018-02-01

Plant functional traits provide information about adaptations to climate and environmental conditions, and can be used to explore the existence of alternative plant strategies within ecosystems. Trait data are also increasingly being used to provide parameter estimates for vegetation models. Here we present a new database of plant functional traits from China. Most global climate and vegetation types can be found in China, and thus the database is relevant for global modeling. The China Plant Trait Database contains information on morphometric, physical, chemical, and photosynthetic traits from 122 sites spanning the range from boreal to tropical, and from deserts and steppes through woodlands and forests, including montane vegetation. Data collection at each site was based either on sampling the dominant species or on a stratified sampling of each ecosystem layer. The database contains information on 1,215 unique species, though many species have been sampled at multiple sites. The original field identifications have been taxonomically standardized to the Flora of China. Similarly, derived photosynthetic traits, such as electron-transport and carboxylation capacities, were calculated using a standardized method. To facilitate trait-environment analyses, the database also contains detailed climate and vegetation information for each site. The data set is released under a Creative Commons BY license. When using the data set, we kindly request that you cite this article, recognizing the hard work that went into collecting the data and the authors' willingness to make it publicly available. © 2017 by the Ecological Society of America.

Identity Processes and Personality Traits and Types in Adolescence: Directionality of Effects and Developmental Trajectories

ERIC Educational Resources Information Center

Luyckx, Koen; Teppers, Eveline; Klimstra, Theo A.; Rassart, Jessica

2014-01-01

Personality traits are hypothesized to be among the most important factors contributing to individual differences in identity development. However, longitudinal studies linking Big Five personality traits to contemporary identity models (in which multiple exploration and commitment processes are distinguished) are largely lacking. To gain more…

Prediction of Multiple-Trait and Multiple-Environment Genomic Data Using Recommender Systems.

PubMed

Montesinos-López, Osval A; Montesinos-López, Abelardo; Crossa, José; Montesinos-López, José C; Mota-Sanchez, David; Estrada-González, Fermín; Gillberg, Jussi; Singh, Ravi; Mondal, Suchismita; Juliana, Philomin

2018-01-04

In genomic-enabled prediction, the task of improving the accuracy of the prediction of lines in environments is difficult because the available information is generally sparse and usually has low correlations between traits. In current genomic selection, although researchers have a large amount of information and appropriate statistical models to process it, there is still limited computing efficiency to do so. Although some statistical models are usually mathematically elegant, many of them are also computationally inefficient, and they are impractical for many traits, lines, environments, and years because they need to sample from huge normal multivariate distributions. For these reasons, this study explores two recommender systems: item-based collaborative filtering (IBCF) and the matrix factorization algorithm (MF) in the context of multiple traits and multiple environments. The IBCF and MF methods were compared with two conventional methods on simulated and real data. Results of the simulated and real data sets show that the IBCF technique was slightly better in terms of prediction accuracy than the two conventional methods and the MF method when the correlation was moderately high. The IBCF technique is very attractive because it produces good predictions when there is high correlation between items (environment-trait combinations) and its implementation is computationally feasible, which can be useful for plant breeders who deal with very large data sets. Copyright © 2018 Montesinos-Lopez et al.

Prediction of Multiple-Trait and Multiple-Environment Genomic Data Using Recommender Systems

PubMed Central

Montesinos-López, Osval A.; Montesinos-López, Abelardo; Crossa, José; Montesinos-López, José C.; Mota-Sanchez, David; Estrada-González, Fermín; Gillberg, Jussi; Singh, Ravi; Mondal, Suchismita; Juliana, Philomin

2018-01-01

In genomic-enabled prediction, the task of improving the accuracy of the prediction of lines in environments is difficult because the available information is generally sparse and usually has low correlations between traits. In current genomic selection, although researchers have a large amount of information and appropriate statistical models to process it, there is still limited computing efficiency to do so. Although some statistical models are usually mathematically elegant, many of them are also computationally inefficient, and they are impractical for many traits, lines, environments, and years because they need to sample from huge normal multivariate distributions. For these reasons, this study explores two recommender systems: item-based collaborative filtering (IBCF) and the matrix factorization algorithm (MF) in the context of multiple traits and multiple environments. The IBCF and MF methods were compared with two conventional methods on simulated and real data. Results of the simulated and real data sets show that the IBCF technique was slightly better in terms of prediction accuracy than the two conventional methods and the MF method when the correlation was moderately high. The IBCF technique is very attractive because it produces good predictions when there is high correlation between items (environment–trait combinations) and its implementation is computationally feasible, which can be useful for plant breeders who deal with very large data sets. PMID:29097376

Mediation of the Relationship Between Callous-Unemotional Traits and Proactive Aggression by Amygdala Response to Fear Among Children With Conduct Problems

PubMed Central

Lozier, Leah M.; Cardinale, Elise M.; VanMeter, John W.; Marsh, Abigail A.

2015-01-01

Importance Among youths with conduct problems, callous-unemotional (CU) traits are known to be an important determinant of symptom severity, prognosis, and treatment responsiveness. But positive correlations between conduct problems and CU traits result in suppressor effects that may mask important neurobiological distinctions among subgroups of children with conduct problems. Objective To assess the unique neurobiological covariates of CU traits and externalizing behaviors in youths with conduct problems and determine whether neural dysfunction linked to CU traits mediates the link between callousness and proactive aggression. Design, Setting, and Participants This cross-sectional case-control study involved behavioral testing and neuroimaging that were conducted at a university research institution. Neuroimaging was conducted using a 3-T Siemens magnetic resonance imaging scanner. It included 46 community-recruited male and female juveniles aged 10 to 17 years, including 16 healthy control participants and 30 youths with conduct problems with both low and high levels of CU traits. Main Outcomes and Measures Blood oxygenation level–dependent signal as measured via functional magnetic resonance imaging during an implicit face-emotion processing task and analyzed using whole-brain and region of interest–based analysis of variance and multiple-regression analyses. Results Analysis of variance revealed no group differences in the amygdala. By contrast, consistent with the existence of suppressor effects, multiple-regression analysis found amygdala responses to fearful expressions to be negatively associated with CU traits (x = 26, y = 0, z = −12; k = 1) and positively associated with externalizing behavior (x = 24, y = 0, z = −14; k = 8) when both variables were modeled simultaneously. Reduced amygdala responses mediated the relationship between CU traits and proactive aggression. Conclusions and Relevance The results linked proactive aggression in youths with CU traits to hypoactive amygdala responses to emotional distress cues, consistent with theories that externalizing behaviors, particularly proactive aggression, in youths with these traits stem from deficient empathic responses to distress. Amygdala hypoactivity may represent an intermediate phenotype, offering new insights into effective treatment strategies for conduct problems. PMID:24671141

Seasonal variability of multiple leaf traits captured by leaf spectroscopy at two temperate deciduous forests

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

Yang, Xi; Tang, Jianwu; Mustard, John F.

Understanding the temporal patterns of leaf traits is critical in determining the seasonality and magnitude of terrestrial carbon, water, and energy fluxes. However, we lack robust and efficient ways to monitor the temporal dynamics of leaf traits. Here we assessed the potential of leaf spectroscopy to predict and monitor leaf traits across their entire life cycle at different forest sites and light environments (sunlit vs. shaded) using a weekly sampled dataset across the entire growing season at two temperate deciduous forests. In addition, the dataset includes field measured leaf-level directional-hemispherical reflectance/transmittance together with seven important leaf traits [total chlorophyll (chlorophyllmore » a and b), carotenoids, mass-based nitrogen concentration (N mass), mass-based carbon concentration (C mass), and leaf mass per area (LMA)]. All leaf traits varied significantly throughout the growing season, and displayed trait-specific temporal patterns. We used a Partial Least Square Regression (PLSR) modeling approach to estimate leaf traits from spectra, and found that PLSR was able to capture the variability across time, sites, and light environments of all leaf traits investigated (R 2 = 0.6–0.8 for temporal variability; R 2 = 0.3–0.7 for cross-site variability; R 2 = 0.4–0.8 for variability from light environments). We also tested alternative field sampling designs and found that for most leaf traits, biweekly leaf sampling throughout the growing season enabled accurate characterization of the seasonal patterns. Compared with the estimation of foliar pigments, the performance of N mass, C mass and LMA PLSR models improved more significantly with sampling frequency. Our results demonstrate that leaf spectra-trait relationships vary with time, and thus tracking the seasonality of leaf traits requires statistical models calibrated with data sampled throughout the growing season. In conclusion, our results have broad implications for future research that use vegetation spectra to infer leaf traits at different growing stages.« less

Seasonal variability of multiple leaf traits captured by leaf spectroscopy at two temperate deciduous forests

DOE PAGES

Yang, Xi; Tang, Jianwu; Mustard, John F.; ...

2016-04-02

Understanding the temporal patterns of leaf traits is critical in determining the seasonality and magnitude of terrestrial carbon, water, and energy fluxes. However, we lack robust and efficient ways to monitor the temporal dynamics of leaf traits. Here we assessed the potential of leaf spectroscopy to predict and monitor leaf traits across their entire life cycle at different forest sites and light environments (sunlit vs. shaded) using a weekly sampled dataset across the entire growing season at two temperate deciduous forests. In addition, the dataset includes field measured leaf-level directional-hemispherical reflectance/transmittance together with seven important leaf traits [total chlorophyll (chlorophyllmore » a and b), carotenoids, mass-based nitrogen concentration (N mass), mass-based carbon concentration (C mass), and leaf mass per area (LMA)]. All leaf traits varied significantly throughout the growing season, and displayed trait-specific temporal patterns. We used a Partial Least Square Regression (PLSR) modeling approach to estimate leaf traits from spectra, and found that PLSR was able to capture the variability across time, sites, and light environments of all leaf traits investigated (R 2 = 0.6–0.8 for temporal variability; R 2 = 0.3–0.7 for cross-site variability; R 2 = 0.4–0.8 for variability from light environments). We also tested alternative field sampling designs and found that for most leaf traits, biweekly leaf sampling throughout the growing season enabled accurate characterization of the seasonal patterns. Compared with the estimation of foliar pigments, the performance of N mass, C mass and LMA PLSR models improved more significantly with sampling frequency. Our results demonstrate that leaf spectra-trait relationships vary with time, and thus tracking the seasonality of leaf traits requires statistical models calibrated with data sampled throughout the growing season. In conclusion, our results have broad implications for future research that use vegetation spectra to infer leaf traits at different growing stages.« less

Adaptive testing for multiple traits in a proportional odds model with applications to detect SNP-brain network associations.

PubMed

Kim, Junghi; Pan, Wei

2017-04-01

There has been increasing interest in developing more powerful and flexible statistical tests to detect genetic associations with multiple traits, as arising from neuroimaging genetic studies. Most of existing methods treat a single trait or multiple traits as response while treating an SNP as a predictor coded under an additive inheritance mode. In this paper, we follow an earlier approach in treating an SNP as an ordinal response while treating traits as predictors in a proportional odds model (POM). In this way, it is not only easier to handle mixed types of traits, e.g., some quantitative and some binary, but it is also potentially more robust to the commonly adopted additive inheritance mode. More importantly, we develop an adaptive test in a POM so that it can maintain high power across many possible situations. Compared to the existing methods treating multiple traits as responses, e.g., in a generalized estimating equation (GEE) approach, the proposed method can be applied to a high dimensional setting where the number of phenotypes (p) can be larger than the sample size (n), in addition to a usual small P setting. The promising performance of the proposed method was demonstrated with applications to the Alzheimer's Disease Neuroimaging Initiative (ADNI) data, in which either structural MRI driven phenotypes or resting-state functional MRI (rs-fMRI) derived brain functional connectivity measures were used as phenotypes. The applications led to the identification of several top SNPs of biological interest. Furthermore, simulation studies showed competitive performance of the new method, especially for p>n. © 2017 WILEY PERIODICALS, INC.

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.

Within-species patterns challenge our understanding of the causes and consequences of trait variation with implications for trait-based models

NASA Astrophysics Data System (ADS)

Anderegg, L. D.; Berner, L. T.; Badgley, G.; Hillerislambers, J.; Law, B. E.

2017-12-01

Functional traits could facilitate ecological prediction by provide scale-free tools for modeling ecosystem function. Yet much of their utility lies in three key assumptions: 1) that global patterns of trait covariation are the result of universal trade-offs independent of taxonomic scale, so empirical trait-trait relationships can be used to constrain vegetation models 2) that traits respond predictably to environmental gradients and can therefore be reliably quantified to parameterize models and 3) that well sampled traits influence productivity. We use an extensive dataset of within-species leaf trait variation in North American conifers combined with global leaf trait datasets to test these assumptions. We examine traits central to the `leaf economics spectrum', and quantify patterns of trait variation at multiple taxonomic scales. We also test whether site environment explains geographic trait variation within conifers, and ask whether foliar traits explain geographic variation in relative growth rates. We find that most leaf traits vary primarily between rather than within species globally, but that a large fraction of within-PFT trait variation is within-species. We also find that some leaf economics spectrum relationships differ in sign within versus between species, particularly the relationship between leaf lifespan and LMA. In conifers, we find weak and inconsistent relationships between site environment and leaf traits, making it difficult capture within-species leaf trait variation for regional model parameterization. Finally, we find limited relationships between tree relative growth rate and any foliar trait other than leaf lifespan, with leaf traits jointly explaining 42% of within-species growth variation but environmental factors explaining 77% of variation. We suggest that additional traits, particularly whole plant allometry/allocation traits may be better than leaf traits for improving vegetation model performance at smaller taxonomic and spatial scales.

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 variation and gene expression across multiple tissues and developmental stages in a non-human primate

PubMed Central

Jasinska, Anna J.; Zelaya, Ivette; Service, Susan K.; Peterson, Christine B.; Cantor, Rita M.; Choi, Oi-Wa; DeYoung, Joseph; Eskin, Eleazar; Fairbanks, Lynn A.; Fears, Scott; Furterer, Allison E.; Huang, Yu S.; Ramensky, Vasily; Schmitt, Christopher A.; Svardal, Hannes; Jorgensen, Matthew J.; Kaplan, Jay R.; Villar, Diego; Aken, Bronwen L.; Flicek, Paul; Nag, Rishi; Wong, Emily S.; Blangero, John; Dyer, Thomas D.; Bogomolov, Marina; Benjamini, Yoav; Weinstock, George M.; Dewar, Ken; Sabatti, Chiara; Wilson, Richard K.; Jentsch, J. David; Warren, Wesley; Coppola, Giovanni; Woods, Roger P.; Freimer, Nelson B.

2017-01-01

By analyzing multi-tissue gene expression and genome-wide genetic variation data in samples from a vervet monkey pedigree, we generated a transcriptome resource and produced the first catalogue of expression quantitative trait loci (eQTLs) in a non-human primate model. This catalogue contains more genome-wide significant eQTLs, per sample, than comparable human resources, and reveals sex and age-related expression patterns. Findings include a master regulatory locus that likely plays a role in immune function, and a locus regulating hippocampal long non-coding RNAs (lncRNAs), whose expression correlates with hippocampal volume. This resource will facilitate genetic investigation of quantitative traits, including brain and behavioral phenotypes relevant to neuropsychiatric disorders. PMID:29083405

Development and validation of Big Four personality scales for the Schedule for Nonadaptive and Adaptive Personality--Second Edition (SNAP-2).

PubMed

Calabrese, William R; Rudick, Monica M; Simms, Leonard J; Clark, Lee Anna

2012-09-01

Recently, integrative, hierarchical models of personality and personality disorder (PD)--such as the Big Three, Big Four, and Big Five trait models--have gained support as a unifying dimensional framework for describing PD. However, no measures to date can simultaneously represent each of these potentially interesting levels of the personality hierarchy. To unify these measurement models psychometrically, we sought to develop Big Five trait scales within the Schedule for Nonadaptive and Adaptive Personality--Second Edition (SNAP-2). Through structural and content analyses, we examined relations between the SNAP-2, the Big Five Inventory (BFI), and the NEO Five-Factor Inventory (NEO-FFI) ratings in a large data set (N = 8,690), including clinical, military, college, and community participants. Results yielded scales consistent with the Big Four model of personality (i.e., Neuroticism, Conscientiousness, Introversion, and Antagonism) and not the Big Five, as there were insufficient items related to Openness. Resulting scale scores demonstrated strong internal consistency and temporal stability. Structural validity and external validity were supported by strong convergent and discriminant validity patterns between Big Four scale scores and other personality trait scores and expectable patterns of self-peer agreement. Descriptive statistics and community-based norms are provided. The SNAP-2 Big Four Scales enable researchers and clinicians to assess personality at multiple levels of the trait hierarchy and facilitate comparisons among competing big-trait models. PsycINFO Database Record (c) 2012 APA, all rights reserved.

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.

ICD-11 and DSM-5 personality trait domains capture categorical personality disorders: Finding a common ground.

PubMed

Bach, Bo; Sellbom, Martin; Skjernov, Mathias; Simonsen, Erik

2018-05-01

The five personality disorder trait domains in the proposed International Classification of Diseases, 11th edition and the Diagnostic and Statistical Manual of Mental Disorders, 5th edition are comparable in terms of Negative Affectivity, Detachment, Antagonism/Dissociality and Disinhibition. However, the International Classification of Diseases, 11th edition model includes a separate domain of Anankastia, whereas the Diagnostic and Statistical Manual of Mental Disorders, 5th edition model includes an additional domain of Psychoticism. This study examined associations of International Classification of Diseases, 11th edition and Diagnostic and Statistical Manual of Mental Disorders, 5th edition trait domains, simultaneously, with categorical personality disorders. Psychiatric outpatients ( N = 226) were administered the Structured Clinical Interview for DSM-IV Axis II Personality Disorders Interview and the Personality Inventory for DSM-5. International Classification of Diseases, 11th edition and Diagnostic and Statistical Manual of Mental Disorders, 5th edition trait domain scores were obtained using pertinent scoring algorithms for the Personality Inventory for DSM-5. Associations between categorical personality disorders and trait domains were examined using correlation and multiple regression analyses. Both the International Classification of Diseases, 11th edition and the Diagnostic and Statistical Manual of Mental Disorders, 5th edition domain models showed relevant continuity with categorical personality disorders and captured a substantial amount of their information. As expected, the International Classification of Diseases, 11th edition model was superior in capturing obsessive-compulsive personality disorder, whereas the Diagnostic and Statistical Manual of Mental Disorders, 5th edition model was superior in capturing schizotypal personality disorder. These preliminary findings suggest that little information is 'lost' in a transition to trait domain models and potentially adds to narrowing the gap between Diagnostic and Statistical Manual of Mental Disorders, 5th edition and the proposed International Classification of Diseases, 11th edition model. Accordingly, the International Classification of Diseases, 11th edition and Diagnostic and Statistical Manual of Mental Disorders, 5th edition domain models may be used to delineate one another as well as features of familiar categorical personality disorder types. A preliminary category-to-domain 'cross walk' is provided in the article.

Alternative Strategies in Response to Saline Stress in Two Varieties of Portulaca oleracea (Purslane).

PubMed

Mulry, Kristina R; Hanson, Bryan A; Dudle, Dana A

2015-01-01

Purslane (Portulaca oleracea) is a globally-distributed plant with a long history of use in folk medicine and cooking. We have developed purslane as a model system for exploring plant responses to stress. We exposed two varieties of purslane to saline stress with the objective of identifying differences between the varieties in the plasticity of morphological and physiological traits. The varieties responded to saline stress with significantly different changes in the measured traits, which included inter alia biomass, flower counts, proline concentrations and betalain pigment concentrations. The alternative responses of the two varieties consisted of complex, simultaneous changes in multiple traits. In particular, we observed that while both varieties increased production of betalain pigments and proline under saline stress, one variety invested more in betalain pigments while the other invested more in proline. Proline and betalain pigments undoubtedly play multiple roles in plant tissues, but in this case their role as antioxidants deployed to ameliorate saline stress appears to be important. Taken holistically, our results suggest that the two varieties employ different strategies in allocating resources to cope with saline stress. This conclusion establishes purslane as a suitable model system for the study of saline stress and the molecular basis for differential responses.

Alternative Strategies in Response to Saline Stress in Two Varieties of Portulaca oleracea (Purslane)

PubMed Central

Mulry, Kristina R.; Hanson, Bryan A.; Dudle, Dana A.

2015-01-01

Purslane (Portulaca oleracea) is a globally-distributed plant with a long history of use in folk medicine and cooking. We have developed purslane as a model system for exploring plant responses to stress. We exposed two varieties of purslane to saline stress with the objective of identifying differences between the varieties in the plasticity of morphological and physiological traits. The varieties responded to saline stress with significantly different changes in the measured traits, which included inter alia biomass, flower counts, proline concentrations and betalain pigment concentrations. The alternative responses of the two varieties consisted of complex, simultaneous changes in multiple traits. In particular, we observed that while both varieties increased production of betalain pigments and proline under saline stress, one variety invested more in betalain pigments while the other invested more in proline. Proline and betalain pigments undoubtedly play multiple roles in plant tissues, but in this case their role as antioxidants deployed to ameliorate saline stress appears to be important. Taken holistically, our results suggest that the two varieties employ different strategies in allocating resources to cope with saline stress. This conclusion establishes purslane as a suitable model system for the study of saline stress and the molecular basis for differential responses. PMID:26398279

When does female multiple mating evolve to adjust inbreeding? Effects of inbreeding depression, direct costs, mating constraints, and polyandry as a threshold trait

PubMed Central

Duthie, A. Bradley; Bocedi, Greta; Reid, Jane M.

2016-01-01

Polyandry is often hypothesized to evolve to allow females to adjust the degree to which they inbreed. Multiple factors might affect such evolution, including inbreeding depression, direct costs, constraints on male availability, and the nature of polyandry as a threshold trait. Complex models are required to evaluate when evolution of polyandry to adjust inbreeding is predicted to arise. We used a genetically explicit individual‐based model to track the joint evolution of inbreeding strategy and polyandry defined as a polygenic threshold trait. Evolution of polyandry to avoid inbreeding only occurred given strong inbreeding depression, low direct costs, and severe restrictions on initial versus additional male availability. Evolution of polyandry to prefer inbreeding only occurred given zero inbreeding depression and direct costs, and given similarly severe restrictions on male availability. However, due to its threshold nature, phenotypic polyandry was frequently expressed even when strongly selected against and hence maladaptive. Further, the degree to which females adjusted inbreeding through polyandry was typically very small, and often reflected constraints on male availability rather than adaptive reproductive strategy. Evolution of polyandry solely to adjust inbreeding might consequently be highly restricted in nature, and such evolution cannot necessarily be directly inferred from observed magnitudes of inbreeding adjustment. PMID:27464756

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

PubMed

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

2015-08-01

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

Variant-aware saturating mutagenesis using multiple Cas9 nucleases identifies regulatory elements at trait-associated loci.

PubMed

Canver, Matthew C; Lessard, Samuel; Pinello, Luca; Wu, Yuxuan; Ilboudo, Yann; Stern, Emily N; Needleman, Austen J; Galactéros, Frédéric; Brugnara, Carlo; Kutlar, Abdullah; McKenzie, Colin; Reid, Marvin; Chen, Diane D; Das, Partha Pratim; A Cole, Mitchel; Zeng, Jing; Kurita, Ryo; Nakamura, Yukio; Yuan, Guo-Cheng; Lettre, Guillaume; Bauer, Daniel E; Orkin, Stuart H

2017-04-01

Cas9-mediated, high-throughput, saturating in situ mutagenesis permits fine-mapping of function across genomic segments. Disease- and trait-associated variants identified in genome-wide association studies largely cluster at regulatory loci. Here we demonstrate the use of multiple designer nucleases and variant-aware library design to interrogate trait-associated regulatory DNA at high resolution. We developed a computational tool for the creation of saturating-mutagenesis libraries with single or multiple nucleases with incorporation of variants. We applied this methodology to the HBS1L-MYB intergenic region, which is associated with red-blood-cell traits, including fetal hemoglobin levels. This approach identified putative regulatory elements that control MYB expression. Analysis of genomic copy number highlighted potential false-positive regions, thus emphasizing the importance of off-target analysis in the design of saturating-mutagenesis experiments. Together, these data establish a widely applicable high-throughput and high-resolution methodology to identify minimal functional sequences within large disease- and trait-associated regions.

Mixture IRT Model with a Higher-Order Structure for Latent Traits

ERIC Educational Resources Information Center

Huang, Hung-Yu

2017-01-01

Mixture item response theory (IRT) models have been suggested as an efficient method of detecting the different response patterns derived from latent classes when developing a test. In testing situations, multiple latent traits measured by a battery of tests can exhibit a higher-order structure, and mixtures of latent classes may occur on…

A Semiparametric Approach for Composite Functional Mapping of Dynamic Quantitative Traits

PubMed Central

Yang, Runqing; Gao, Huijiang; Wang, Xin; Zhang, Ji; Zeng, Zhao-Bang; Wu, Rongling

2007-01-01

Functional mapping has emerged as a powerful tool for mapping quantitative trait loci (QTL) that control developmental patterns of complex dynamic traits. Original functional mapping has been constructed within the context of simple interval mapping, without consideration of separate multiple linked QTL for a dynamic trait. In this article, we present a statistical framework for mapping QTL that affect dynamic traits by capitalizing on the strengths of functional mapping and composite interval mapping. Within this so-called composite functional-mapping framework, functional mapping models the time-dependent genetic effects of a QTL tested within a marker interval using a biologically meaningful parametric function, whereas composite interval mapping models the time-dependent genetic effects of the markers outside the test interval to control the genome background using a flexible nonparametric approach based on Legendre polynomials. Such a semiparametric framework was formulated by a maximum-likelihood model and implemented with the EM algorithm, allowing for the estimation and the test of the mathematical parameters that define the QTL effects and the regression coefficients of the Legendre polynomials that describe the marker effects. Simulation studies were performed to investigate the statistical behavior of composite functional mapping and compare its advantage in separating multiple linked QTL as compared to functional mapping. We used the new mapping approach to analyze a genetic mapping example in rice, leading to the identification of multiple QTL, some of which are linked on the same chromosome, that control the developmental trajectory of leaf age. PMID:17947431

Quality of Life as a Mediator between Behavioral Challenges and Autistic Traits for Adults with Intellectual Disabilities

ERIC Educational Resources Information Center

Garcia-Villamisar, Domingo; Dattilo, John; Matson, Johnny L.

2013-01-01

A multiple mediation model was proposed to integrate core concepts of challenging behaviors with autistic traits to increase understanding of their relationship to quality of life (QoL). It was hypothesized that QoL is a possible mediator between the severity of challenging behaviors and autistic traits in adults with intellectual disability.…

Costs of reproduction can explain the correlated evolution of semelparity and egg size: theory and a test with salmon.

PubMed

Kindsvater, Holly K; Braun, Douglas C; Otto, Sarah P; Reynolds, John D

2016-06-01

Species' life history traits, including maturation age, number of reproductive bouts, offspring size and number, reflect adaptations to diverse biotic and abiotic selection pressures. A striking example of divergent life histories is the evolution of either iteroparity (breeding multiple times) or semelparity (breed once and die). We analysed published data on salmonid fishes and found that semelparous species produce larger eggs, that egg size and number increase with salmonid body size among populations and species and that migratory behaviour and parity interact. We developed three hypotheses that might explain the patterns in our data and evaluated them in a stage-structured modelling framework accounting for different growth and survival scenarios. Our models predict the observation of small eggs in iteroparous species when egg size is costly to maternal survival or egg number is constrained. By exploring trait co-variation in salmonids, we generate new hypotheses for the evolution of trade-offs among life history traits. © 2016 John Wiley & Sons Ltd/CNRS.

Eating disorders and the serotonin connection: state, trait and developmental effects

PubMed Central

Steiger, Howard

2004-01-01

Alterations in brain serotonin (5-hydroxytryptamine [5-HT]) function are thought to contribute to diverse aspects of eating disorders, including binge eating, perfectionism, impulsivity and mood-regulation problems. In addition, 5-HT anomalies in individuals with eating disorders are believed to have multiple determinants associated with secondary (state-related) effects of their nutritional status, hereditary effects (related to such trait variations as impulsivity or perfectionism) and, possibly, long-term neurobiologic sequelae of developmental stressors (such as childhood abuse). On the strength of the available neurobiologic and genetic data, this paper presents the idea that 5-HT variations in those with eating disorders represent (1) a structured coaggregation of biologic, psychologic and social influences and (2) converging state, trait and developmental effects. Data are taken to support a multidimensional model of 5-HT function in eating disorders that, it is argued, can serve as a prototype for etiologic modelling, diagnostic classification and clinical decision-making bearing not only upon eating disorders but also upon other psychiatric disturbances. PMID:14719047

Multiple metrics of diversity have different effects on temperate forest functioning over succession.

PubMed

Yuan, Zuoqiang; Wang, Shaopeng; Gazol, Antonio; Mellard, Jarad; Lin, Fei; Ye, Ji; Hao, Zhanqing; Wang, Xugao; Loreau, Michel

2016-12-01

Biodiversity can be measured by taxonomic, phylogenetic, and functional diversity. How ecosystem functioning depends on these measures of diversity can vary from site to site and depends on successional stage. Here, we measured taxonomic, phylogenetic, and functional diversity, and examined their relationship with biomass in two successional stages of the broad-leaved Korean pine forest in northeastern China. Functional diversity was calculated from six plant traits, and aboveground biomass (AGB) and coarse woody productivity (CWP) were estimated using data from three forest censuses (10 years) in two large fully mapped forest plots (25 and 5 ha). 11 of the 12 regressions between biomass variables (AGB and CWP) and indices of diversity showed significant positive relationships, especially those with phylogenetic diversity. The mean tree diversity-biomass regressions increased from 0.11 in secondary forest to 0.31 in old-growth forest, implying a stronger biodiversity effect in more mature forest. Multi-model selection results showed that models including species richness, phylogenetic diversity, and single functional traits explained more variation in forest biomass than other candidate models. The models with a single functional trait, i.e., leaf area in secondary forest and wood density in mature forest, provided better explanations for forest biomass than models that combined all six functional traits. This finding may reflect different strategies in growth and resource acquisition in secondary and old-growth forests.

Methods for simultaneous control of lignin content and composition, and cellulose content in plants

DOEpatents

Chiang, Vincent Lee C.; Li, Laigeng

2005-02-15

The present invention relates to a method of concurrently introducing multiple genes into plants and trees is provided. The method includes simultaneous transformation of plants with multiple genes from the phenylpropanoid pathways including 4CL, CAld5H, AldOMT, SAD and CAD genes and combinations thereof to produce various lines of transgenic plants displaying altered agronomic traits. The agronomic traits of the plants are regulated by the orientation of the specific genes and the selected gene combinations, which are incorporated into the plant genome.

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 trait-based framework for stream algal communities.

PubMed

Lange, Katharina; Townsend, Colin Richard; Matthaei, Christoph David

2016-01-01

The use of trait-based approaches to detect effects of land use and climate change on terrestrial plant and aquatic phytoplankton communities is increasing, but such a framework is still needed for benthic stream algae. Here we present a conceptual framework of morphological, physiological, behavioural and life-history traits relating to resource acquisition and resistance to disturbance. We tested this approach by assessing the relationships between multiple anthropogenic stressors and algal traits at 43 stream sites. Our "natural experiment" was conducted along gradients of agricultural land-use intensity (0-95% of the catchment in high-producing pasture) and hydrological alteration (0-92% streamflow reduction resulting from water abstraction for irrigation) as well as related physicochemical variables (total nitrogen concentration and deposited fine sediment). Strategic choice of study sites meant that agricultural intensity and hydrological alteration were uncorrelated. We studied the relationships of seven traits (with 23 trait categories) to our environmental predictor variables using general linear models and an information-theoretic model-selection approach. Life form, nitrogen fixation and spore formation were key traits that showed the strongest relationships with environmental stressors. Overall, FI (farming intensity) exerted stronger effects on algal communities than hydrological alteration. The large-bodied, non-attached, filamentous algae that dominated under high farming intensities have limited dispersal abilities but may cope with unfavourable conditions through the formation of spores. Antagonistic interactions between FI and flow reduction were observed for some trait variables, whereas no interactions occurred for nitrogen concentration and fine sediment. Our conceptual framework was well supported by tests of ten specific hypotheses predicting effects of resource supply and disturbance on algal traits. Our study also shows that investigating a fairly comprehensive set of traits can help shed light on the drivers of algal community composition in situations where multiple stressors are operating. Further, to understand non-linear and non-additive effects of such drivers, communities need to be studied along multiple gradients of natural variation or anthropogenic stressors.

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

High-Performance Mixed Models Based Genome-Wide Association Analysis with omicABEL software

PubMed Central

Fabregat-Traver, Diego; Sharapov, Sodbo Zh.; Hayward, Caroline; Rudan, Igor; Campbell, Harry; Aulchenko, Yurii; Bientinesi, Paolo

2014-01-01

To raise the power of genome-wide association studies (GWAS) and avoid false-positive results in structured populations, one can rely on mixed model based tests. When large samples are used, and when multiple traits are to be studied in the ’omics’ context, this approach becomes computationally challenging. Here we consider the problem of mixed-model based GWAS for arbitrary number of traits, and demonstrate that for the analysis of single-trait and multiple-trait scenarios different computational algorithms are optimal. We implement these optimal algorithms in a high-performance computing framework that uses state-of-the-art linear algebra kernels, incorporates optimizations, and avoids redundant computations, increasing throughput while reducing memory usage and energy consumption. We show that, compared to existing libraries, our algorithms and software achieve considerable speed-ups. The OmicABEL software described in this manuscript is available under the GNU GPL v. 3 license as part of the GenABEL project for statistical genomics at http: //www.genabel.org/packages/OmicABEL. PMID:25717363

High-Performance Mixed Models Based Genome-Wide Association Analysis with omicABEL software.

PubMed

Fabregat-Traver, Diego; Sharapov, Sodbo Zh; Hayward, Caroline; Rudan, Igor; Campbell, Harry; Aulchenko, Yurii; Bientinesi, Paolo

2014-01-01

To raise the power of genome-wide association studies (GWAS) and avoid false-positive results in structured populations, one can rely on mixed model based tests. When large samples are used, and when multiple traits are to be studied in the 'omics' context, this approach becomes computationally challenging. Here we consider the problem of mixed-model based GWAS for arbitrary number of traits, and demonstrate that for the analysis of single-trait and multiple-trait scenarios different computational algorithms are optimal. We implement these optimal algorithms in a high-performance computing framework that uses state-of-the-art linear algebra kernels, incorporates optimizations, and avoids redundant computations, increasing throughput while reducing memory usage and energy consumption. We show that, compared to existing libraries, our algorithms and software achieve considerable speed-ups. The OmicABEL software described in this manuscript is available under the GNU GPL v. 3 license as part of the GenABEL project for statistical genomics at http: //www.genabel.org/packages/OmicABEL.

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.

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

Leaf economics and hydraulic traits are decoupled in five species-rich tropical-subtropical forests.

PubMed

Li, Le; McCormack, M Luke; Ma, Chengen; Kong, Deliang; Zhang, Qian; Chen, Xiaoyong; Zeng, Hui; Niinemets, Ülo; Guo, Dali

2015-09-01

Leaf economics and hydraulic traits are critical to leaf photosynthesis, yet it is debated whether these two sets of traits vary in a fully coordinated manner or there is room for independent variation. Here, we tested the relationship between leaf economics traits, including leaf nitrogen concentration and leaf dry mass per area, and leaf hydraulic traits including stomatal density and vein density in five tropical-subtropical forests. Surprisingly, these two suites of traits were statistically decoupled. This decoupling suggests that independent trait dimensions exist within a leaf, with leaf economics dimension corresponding to light capture and tissue longevity, and the hydraulic dimension to water-use and leaf temperature maintenance. Clearly, leaf economics and hydraulic traits can vary independently, thus allowing for more possible plant trait combinations. Compared with a single trait dimension, multiple trait dimensions may better enable species adaptations to multifarious niche dimensions, promote diverse plant strategies and facilitate species coexistence. © 2015 John Wiley & Sons Ltd/CNRS.

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.

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

PubMed

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

2014-09-01

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

Genetic Diversity and Association Studies in US Hispanic/Latino Populations: Applications in the Hispanic Community Health Study/Study of Latinos

PubMed Central

Conomos, Matthew P.; Laurie, Cecelia A.; Stilp, Adrienne M.; Gogarten, Stephanie M.; McHugh, Caitlin P.; Nelson, Sarah C.; Sofer, Tamar; Fernández-Rhodes, Lindsay; Justice, Anne E.; Graff, Mariaelisa; Young, Kristin L.; Seyerle, Amanda A.; Avery, Christy L.; Taylor, Kent D.; Rotter, Jerome I.; Talavera, Gregory A.; Daviglus, Martha L.; Wassertheil-Smoller, Sylvia; Schneiderman, Neil; Heiss, Gerardo; Kaplan, Robert C.; Franceschini, Nora; Reiner, Alex P.; Shaffer, John R.; Barr, R. Graham; Kerr, Kathleen F.; Browning, Sharon R.; Browning, Brian L.; Weir, Bruce S.; Avilés-Santa, M. Larissa; Papanicolaou, George J.; Lumley, Thomas; Szpiro, Adam A.; North, Kari E.; Rice, Ken; Thornton, Timothy A.; Laurie, Cathy C.

2016-01-01

US Hispanic/Latino individuals are diverse in genetic ancestry, culture, and environmental exposures. Here, we characterized and controlled for this diversity in genome-wide association studies (GWASs) for the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). We simultaneously estimated population-structure principal components (PCs) robust to familial relatedness and pairwise kinship coefficients (KCs) robust to population structure, admixture, and Hardy-Weinberg departures. The PCs revealed substantial genetic differentiation within and among six self-identified background groups (Cuban, Dominican, Puerto Rican, Mexican, and Central and South American). To control for variation among groups, we developed a multi-dimensional clustering method to define a “genetic-analysis group” variable that retains many properties of self-identified background while achieving substantially greater genetic homogeneity within groups and including participants with non-specific self-identification. In GWASs of 22 biomedical traits, we used a linear mixed model (LMM) including pairwise empirical KCs to account for familial relatedness, PCs for ancestry, and genetic-analysis groups for additional group-associated effects. Including the genetic-analysis group as a covariate accounted for significant trait variation in 8 of 22 traits, even after we fit 20 PCs. Additionally, genetic-analysis groups had significant heterogeneity of residual variance for 20 of 22 traits, and modeling this heteroscedasticity within the LMM reduced genomic inflation for 19 traits. Furthermore, fitting an LMM that utilized a genetic-analysis group rather than a self-identified background group achieved higher power to detect previously reported associations. We expect that the methods applied here will be useful in other studies with multiple ethnic groups, admixture, and relatedness. PMID:26748518

Recapitulation of Ayurveda constitution types by machine learning of phenotypic traits.

PubMed

Tiwari, Pradeep; Kutum, Rintu; Sethi, Tavpritesh; Shrivastava, Ankita; Girase, Bhushan; Aggarwal, Shilpi; Patil, Rutuja; Agarwal, Dhiraj; Gautam, Pramod; Agrawal, Anurag; Dash, Debasis; Ghosh, Saurabh; Juvekar, Sanjay; Mukerji, Mitali; Prasher, Bhavana

2017-01-01

In Ayurveda system of medicine individuals are classified into seven constitution types, "Prakriti", for assessing disease susceptibility and drug responsiveness. Prakriti evaluation involves clinical examination including questions about physiological and behavioural traits. A need was felt to develop models for accurately predicting Prakriti classes that have been shown to exhibit molecular differences. The present study was carried out on data of phenotypic attributes in 147 healthy individuals of three extreme Prakriti types, from a genetically homogeneous population of Western India. Unsupervised and supervised machine learning approaches were used to infer inherent structure of the data, and for feature selection and building classification models for Prakriti respectively. These models were validated in a North Indian population. Unsupervised clustering led to emergence of three natural clusters corresponding to three extreme Prakriti classes. The supervised modelling approaches could classify individuals, with distinct Prakriti types, in the training and validation sets. This study is the first to demonstrate that Prakriti types are distinct verifiable clusters within a multidimensional space of multiple interrelated phenotypic traits. It also provides a computational framework for predicting Prakriti classes from phenotypic attributes. This approach may be useful in precision medicine for stratification of endophenotypes in healthy and diseased populations.

Adaptation to seasonality and the winter freeze

PubMed Central

Preston, Jill C.; Sandve, Simen R.

2013-01-01

Flowering plants initially diversified during the Mesozoic era at least 140 million years ago in regions of the world where temperate seasonal environments were not encountered. Since then several cooling events resulted in the contraction of warm and wet environments and the establishment of novel temperate zones in both hemispheres. In response, less than half of modern angiosperm families have members that evolved specific adaptations to cold seasonal climates, including cold acclimation, freezing tolerance, endodormancy, and vernalization responsiveness. Despite compelling evidence for multiple independent origins, the level of genetic constraint on the evolution of adaptations to seasonal cold is not well understood. However, the recent increase in molecular genetic studies examining the response of model and crop species to seasonal cold offers new insight into the evolutionary lability of these traits. This insight has major implications for our understanding of complex trait evolution, and the potential role of local adaptation in response to past and future climate change. In this review, we discuss the biochemical, morphological, and developmental basis of adaptations to seasonal cold, and synthesize recent literature on the genetic basis of these traits in a phylogenomic context. We find evidence for multiple genetic links between distinct physiological responses to cold, possibly reinforcing the coordinated expression of these traits. Furthermore, repeated recruitment of the same or similar ancestral pathways suggests that land plants might be somewhat pre-adapted to dealing with temperature stress, perhaps making inducible cold traits relatively easy to evolve. PMID:23761798

Makeup of the genetic correlation between milk production traits using genome-wide single nucleotide polymorphism information.

PubMed

van Binsbergen, R; Veerkamp, R F; Calus, M P L

2012-04-01

The correlated responses between traits may differ depending on the makeup of genetic covariances, and may differ from the predictions of polygenic covariances. Therefore, the objective of the present study was to investigate the makeup of the genetic covariances between the well-studied traits: milk yield, fat yield, protein yield, and their percentages in more detail. Phenotypic records of 1,737 heifers of research farms in 4 different countries were used after homogenizing and adjusting for management effects. All cows had a genotype for 37,590 single nucleotide polymorphisms (SNP). A bayesian stochastic search variable selection model was used to estimate the SNP effects for each trait. About 0.5 to 1.0% of the SNP had a significant effect on 1 or more traits; however, the SNP without a significant effect explained most of the genetic variances and covariances of the traits. Single nucleotide polymorphism correlations differed from the polygenic correlations, but only 10 regions were found with an effect on multiple traits; in 1 of these regions the DGAT1 gene was previously reported with an effect on multiple traits. This region explained up to 41% of the variances of 4 traits and explained a major part of the correlation between fat yield and fat percentage and contributes to asymmetry in correlated response between fat yield and fat percentage. Overall, for the traits in this study, the infinitesimal model is expected to be sufficient for the estimation of the variances and covariances. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Epigenetics and developmental programming of welfare and production traits in farm animals.

PubMed

Sinclair, K D; Rutherford, K M D; Wallace, J M; Brameld, J M; Stöger, R; Alberio, R; Sweetman, D; Gardner, D S; Perry, V E A; Adam, C L; Ashworth, C J; Robinson, J E; Dwyer, C M

2016-07-21

The concept that postnatal health and development can be influenced by events that occur in utero originated from epidemiological studies in humans supported by numerous mechanistic (including epigenetic) studies in a variety of model species. Referred to as the 'developmental origins of health and disease' or 'DOHaD' hypothesis, the primary focus of large-animal studies until quite recently had been biomedical. Attention has since turned towards traits of commercial importance in farm animals. Herein we review the evidence that prenatal risk factors, including suboptimal parental nutrition, gestational stress, exposure to environmental chemicals and advanced breeding technologies, can determine traits such as postnatal growth, feed efficiency, milk yield, carcass composition, animal welfare and reproductive potential. We consider the role of epigenetic and cytoplasmic mechanisms of inheritance, and discuss implications for livestock production and future research endeavours. We conclude that although the concept is proven for several traits, issues relating to effect size, and hence commercial importance, remain. Studies have also invariably been conducted under controlled experimental conditions, frequently assessing single risk factors, thereby limiting their translational value for livestock production. We propose concerted international research efforts that consider multiple, concurrent stressors to better represent effects of contemporary animal production systems.

Short communication: Estimates of genetic parameters for dairy fertility in New Zealand.

PubMed

Amer, P R; Stachowicz, K; Jenkins, G M; Meier, S

2016-10-01

Reproductive performance of dairy cows in a seasonal calving system is especially important as cows are required to achieve a 365-d calving interval. Prior research with a small data set has identified that the genetic evaluation model for fertility could be enhanced by replacing the binary calving rate trait (CR42), which gives the probability of a cow calving within the first 42d since the planned start of calving at second, third, and fourth calving, with a continuous version, calving season day (CSD), including a heifer calving season day trait expressed at first calving, removing milk yield, retaining a probability of mating trait (PM21) which gives the probability of a cow being mated within the first 21d from the planned start of mating, and first lactation body condition score (BCS), and including gestation length (GL). The aim of this study was to estimate genetic parameters for the proposed new model using a larger data set and compare these with parameters used in the current system. Heritability estimates for CSD and PM21 ranged from 0.013 to 0.019 and from 0.031 to 0.058, respectively. For the 2 traits that correspond with the ones used in the current genetic evaluation system (mating trait, PM21 and BCS) genetic correlations were lower in this study compared with previous estimates. Genetic correlations between CSD and PM21 across different parities were also lower than the correlations between CR42 and PM21 reported previously. The genetic correlation between heifer CSD and CSD in first parity was 0.66. Estimates of genetic correlations of BCS with CSD were higher than those with PM21. For GL, direct heritability was estimated to be 0.67, maternal heritability was 0.11, and maternal repeatability was 0.22. Direct GL had moderate to high and favorable genetic correlations with evaluated fertility traits, whereas corresponding residual correlations remain low, which makes GL a useful candidate predictor trait for fertility in a multiple trait evaluation. The superiority of direct GL genetic component over the maternal GL component for predicting fertility was demonstrated. Future work planned in this area includes the implementation and testing of this new model on national fertility data. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Hormonal, behavioral, and life-history traits exhibit correlated shifts in relation to population establishment in a novel environment.

PubMed

Atwell, Jonathan W; Cardoso, Gonçalo C; Whittaker, Danielle J; Price, Trevor D; Ketterson, Ellen D

2014-12-01

Climate change, habitat alteration, range expansions, and biological invasions are all predicted to require rapid shifts in multiple traits including behavior and life history, both for initial population establishment and subsequent adaptation. Hormonal mechanisms likely play a key role in facilitating or constraining plastic and genetic responses for suites of traits, but few studies have evaluated their role in shaping contemporary adaptation or diversification. We examined multiple phenotypic adjustments and associated hormonal changes following a recent (early 1980s) colonization event, in which a temperate-breeding songbird, the dark-eyed junco (Junco hyemalis), became established in the Mediterranean climate of San Diego, California. The milder climate has led to an extended breeding season and year-round residency, and we document shifts in multiple sexually selected behaviors and plumage traits. Testosterone titers in San Diego were elevated for longer but with a lower peak value compared to a nearby native-range population, and correlations between testosterone and related traits were similar within and among populations. A common garden study indicated that changes in testosterone likely represent plastic responses to the less seasonal environment of the city, providing the context against which subsequent genetic changes in morphology likely occurred. We argue that correlated shifts in multiple traits, organized by underlying physiology, may be a generally important element of many successful adjustments to changing environments.

Evaluation of the Multiple Sclerosis Walking Scale-12 (MSWS-12) in a Dutch sample: Application of item response theory.

PubMed

Mokkink, Lidwine Brigitta; Galindo-Garre, Francisca; Uitdehaag, Bernard Mj

2016-12-01

The Multiple Sclerosis Walking Scale-12 (MSWS-12) measures walking ability from the patients' perspective. We examined the quality of the MSWS-12 using an item response theory model, the graded response model (GRM). A total of 625 unique Dutch multiple sclerosis (MS) patients were included. After testing for unidimensionality, monotonicity, and absence of local dependence, a GRM was fit and item characteristics were assessed. Differential item functioning (DIF) for the variables gender, age, duration of MS, type of MS and severity of MS, reliability, total test information, and standard error of the trait level (θ) were investigated. Confirmatory factor analysis showed a unidimensional structure of the 12 items of the scale, explaining 88% of the variance. Item 2 did not fit into the GRM model. Reliability was 0.93. Items 8 and 9 (of the 11 and 12 item version respectively) showed DIF on the variable severity, based on the Expanded Disability Status Scale (EDSS). However, the EDSS is strongly related to the content of both items. Our results confirm the good quality of the MSWS-12. The trait level (θ) scores and item parameters of both the 12- and 11-item versions were highly comparable, although we do not suggest to change the content of the MSWS-12. © The Author(s), 2016.

A network of amygdala connections predict individual differences in trait anxiety.

PubMed

Greening, Steven G; Mitchell, Derek G V

2015-12-01

In this study we demonstrate that the pattern of an amygdala-centric network contributes to individual differences in trait anxiety. Individual differences in trait anxiety were predicted using maximum likelihood estimates of amygdala structural connectivity to multiple brain targets derived from diffusion-tensor imaging (DTI) and probabilistic tractography on 72 participants. The prediction was performed using a stratified sixfold cross validation procedure using a regularized least square regression model. The analysis revealed a reliable network of regions predicting individual differences in trait anxiety. Higher trait anxiety was associated with stronger connections between the amygdala and dorsal anterior cingulate cortex, an area implicated in the generation of emotional reactions, and inferior temporal gyrus and paracentral lobule, areas associated with perceptual and sensory processing. In contrast, higher trait anxiety was associated with weaker connections between amygdala and regions implicated in extinction learning such as medial orbitofrontal cortex, and memory encoding and environmental context recognition, including posterior cingulate cortex and parahippocampal gyrus. Thus, trait anxiety is not only associated with reduced amygdala connectivity with prefrontal areas associated with emotion modulation, but also enhanced connectivity with sensory areas. This work provides novel anatomical insight into potential mechanisms behind information processing biases observed in disorders of emotion. © 2015 Wiley Periodicals, Inc.

Multivariate random regression analysis for body weight and main morphological traits in genetically improved farmed tilapia (Oreochromis niloticus).

PubMed

He, Jie; Zhao, Yunfeng; Zhao, Jingli; Gao, Jin; Han, Dandan; Xu, Pao; Yang, Runqing

2017-11-02

Because of their high economic importance, growth traits in fish are under continuous improvement. For growth traits that are recorded at multiple time-points in life, the use of univariate and multivariate animal models is limited because of the variable and irregular timing of these measures. Thus, the univariate random regression model (RRM) was introduced for the genetic analysis of dynamic growth traits in fish breeding. We used a multivariate random regression model (MRRM) to analyze genetic changes in growth traits recorded at multiple time-point of genetically-improved farmed tilapia. Legendre polynomials of different orders were applied to characterize the influences of fixed and random effects on growth trajectories. The final MRRM was determined by optimizing the univariate RRM for the analyzed traits separately via penalizing adaptively the likelihood statistical criterion, which is superior to both the Akaike information criterion and the Bayesian information criterion. In the selected MRRM, the additive genetic effects were modeled by Legendre polynomials of three orders for body weight (BWE) and body length (BL) and of two orders for body depth (BD). By using the covariance functions of the MRRM, estimated heritabilities were between 0.086 and 0.628 for BWE, 0.155 and 0.556 for BL, and 0.056 and 0.607 for BD. Only heritabilities for BD measured from 60 to 140 days of age were consistently higher than those estimated by the univariate RRM. All genetic correlations between growth time-points exceeded 0.5 for either single or pairwise time-points. Moreover, correlations between early and late growth time-points were lower. Thus, for phenotypes that are measured repeatedly in aquaculture, an MRRM can enhance the efficiency of the comprehensive selection for BWE and the main morphological traits.

Synthesizing trait correlations and functional relationships across multiple scales: A Hierarchical Bayes approach

NASA Astrophysics Data System (ADS)

Shiklomanov, A. N.; Cowdery, E.; Dietze, M.

2016-12-01

Recent syntheses of global trait databases have revealed that although the functional diversity among plant species is immense, this diversity is constrained by trade-offs between plant strategies. However, the use of among-trait and trait-environment correlations at the global scale for both qualitative ecological inference and land surface modeling has several important caveats. An alternative approach is to preserve the existing PFT-based model structure while using statistical analyses to account for uncertainty and variability in model parameters. In this study, we used a hierarchical Bayesian model of foliar traits in the TRY database to test the following hypotheses: (1) Leveraging the covariance between foliar traits will significantly constrain our uncertainty in their distributions; and (2) Among-trait covariance patterns are significantly different among and within PFTs, reflecting differences in trade-offs associated with biome-level evolution, site-level community assembly, and individual-level ecophysiological acclimation. We found that among-trait covariance significantly constrained estimates of trait means, and the additional information provided by across-PFT covariance led to more constraint still, especially for traits and PFTs with low sample sizes. We also found that among-trait correlations were highly variable among PFTs, and were generally inconsistent with correlations within PFTs. The hierarchical multivariate framework developed in our study can readily be enhanced with additional levels of hierarchy to account for geographic, species, and individual-level variability.

Genetic parameters and environmental effects on temperament score and reproductive traits of Nellore cattle.

PubMed

Barrozo, D; Buzanskas, M E; Oliveira, J A; Munari, D P; Neves, H H R; Queiroz, S A

2012-01-01

Animal temperament is a trait of economic relevance and its use as a selection criterion requires the identification of environmental factors that influence this trait, as well as the estimation of its genetic variability and interrelationship with other traits. The objectives of this study were to evaluate the effect of the covariates dam age at calving (ADC), long yearling age (YA) and long yearling weight (YW) on temperament score (T) and to estimate genetic parameters for T, scrotal circumference (SC) at long YA and age at first calving (AFC) in Nellore cattle participating in a selection program. The traits were analyzed by the restricted maximum likelihood method under a multiple-trait animal model. For all traits, contemporary group was included as a fixed effect and additive genetic and residual as random effects. In addition to these effects, YA, YW and ADC were considered for analyzing T. In the case of SC and AFC, the effect of long YW was included as a covariate. Genetic parameters were estimated for and between traits. The three covariates significantly influenced T. The heritability estimates for T, SC and AFC were 0.18 ± 0.02, 0.53 ± 0.04 and 0.23 ± 0.08, respectively. The genetic correlations between T and SC, and T and AFC were -0.07 ± 0.17 and -0.06 ± 0.19, respectively. The genetic correlation estimated between SC and AFC was -0.57 ± 0.16. In conclusion, a response to selection for T, SC and AFC is expected and selection for T does not imply correlated responses with the other traits.

The Heterogeneity in Retrieved Relations between the Personality Trait ‘Harm Avoidance’ and Gray Matter Volumes Due to Variations in the VBM and ROI Labeling Processing Settings

PubMed Central

Van Schuerbeek, Peter; Baeken, Chris; De Mey, Johan

2016-01-01

Concerns are raising about the large variability in reported correlations between gray matter morphology and affective personality traits as ‘Harm Avoidance’ (HA). A recent review study (Mincic 2015) stipulated that this variability could come from methodological differences between studies. In order to achieve more robust results by standardizing the data processing procedure, as a first step, we repeatedly analyzed data from healthy females while changing the processing settings (voxel-based morphology (VBM) or region-of-interest (ROI) labeling, smoothing filter width, nuisance parameters included in the regression model, brain atlas and multiple comparisons correction method). The heterogeneity in the obtained results clearly illustrate the dependency of the study outcome to the opted analysis settings. Based on our results and the existing literature, we recommended the use of VBM over ROI labeling for whole brain analyses with a small or intermediate smoothing filter (5-8mm) and a model variable selection step included in the processing procedure. Additionally, it is recommended that ROI labeling should only be used in combination with a clear hypothesis and that authors are encouraged to report their results uncorrected for multiple comparisons as supplementary material to aid review studies. PMID:27096608

Childhood trauma is not a confounder of the overlap between autistic and schizotypal traits: A study in a non-clinical adult sample.

PubMed

Gong, Jing-Bo; Wang, Ya; Lui, Simon S Y; Cheung, Eric F C; Chan, Raymond C K

2017-11-01

Childhood trauma has been shown to be a robust risk factor for mental disorders, and may exacerbate schizotypal traits or contribute to autistic trait severity. However, little is known whether childhood trauma confounds the overlap between schizotypal traits and autistic traits. This study examined whether childhood trauma acts as a confounding variable in the overlap between autistic and schizotypal traits in a large non-clinical adult sample. A total of 2469 participants completed the Autism Spectrum Quotient (AQ), the Schizotypal Personality Questionnaire (SPQ), and the Childhood Trauma Questionnaire-Short Form. Correlation analysis showed that the majority of associations between AQ variables and SPQ variables were significant (p < 0.05). In the multiple regression models predicting scores on the AQ total, scores on the three SPQ subscales were significant predictors(Ps < 0.05). Scores on the Positive schizotypy and Negative schizotypy subscales were significant predictors in the multiple regression model predicting scores on the AQ Social Skill, AQ Attention Switching, AQ Attention to Detail, AQ Communication, and AQ Imagination subscales. The association between autistic and schizotypal traits could not be explained by shared variance in terms of exposure to childhood trauma. The findings point to important overlaps in the conceptualization of ASD and SSD, independent of childhood trauma. Copyright © 2017 Elsevier B.V. All rights reserved.

When does female multiple mating evolve to adjust inbreeding? Effects of inbreeding depression, direct costs, mating constraints, and polyandry as a threshold trait.

PubMed

Duthie, A Bradley; Bocedi, Greta; Reid, Jane M

2016-09-01

Polyandry is often hypothesized to evolve to allow females to adjust the degree to which they inbreed. Multiple factors might affect such evolution, including inbreeding depression, direct costs, constraints on male availability, and the nature of polyandry as a threshold trait. Complex models are required to evaluate when evolution of polyandry to adjust inbreeding is predicted to arise. We used a genetically explicit individual-based model to track the joint evolution of inbreeding strategy and polyandry defined as a polygenic threshold trait. Evolution of polyandry to avoid inbreeding only occurred given strong inbreeding depression, low direct costs, and severe restrictions on initial versus additional male availability. Evolution of polyandry to prefer inbreeding only occurred given zero inbreeding depression and direct costs, and given similarly severe restrictions on male availability. However, due to its threshold nature, phenotypic polyandry was frequently expressed even when strongly selected against and hence maladaptive. Further, the degree to which females adjusted inbreeding through polyandry was typically very small, and often reflected constraints on male availability rather than adaptive reproductive strategy. Evolution of polyandry solely to adjust inbreeding might consequently be highly restricted in nature, and such evolution cannot necessarily be directly inferred from observed magnitudes of inbreeding adjustment. © 2016 The Author(s). Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.

Multi-trait, multi-breed conception rate evaluations

USDA-ARS?s Scientific Manuscript database

Heifer and cow conception rates (HCR and CCR) were evaluated with multi-trait, multi-breed models including crossbred cows instead of the previous single-trait, single-breed models. Fertility traits benefit from multi-trait processing because of high genetic correlations and many missing observation...

Multi-environment QTL analysis of grain morphology traits and fine mapping of a kernel-width QTL in Zheng58 × SK maize population.

PubMed

Raihan, Mohammad Sharif; Liu, Jie; Huang, Juan; Guo, Huan; Pan, Qingchun; Yan, Jianbing

2016-08-01

Sixteen major QTLs regulating maize kernel traits were mapped in multiple environments and one of them, qKW - 9.2 , was restricted to 630 Kb, harboring 28 putative gene models. To elucidate the genetic basis of kernel traits, a quantitative trait locus (QTL) analysis was conducted in a maize recombinant inbred line population derived from a cross between two diverse parents Zheng58 and SK, evaluated across eight environments. Construction of a high-density linkage map was based on 13,703 single-nucleotide polymorphism markers, covering 1860.9 cM of the whole genome. In total, 18, 26, 23, and 19 QTLs for kernel length, width, thickness, and 100-kernel weight, respectively, were detected on the basis of a single-environment analysis, and each QTL explained 3.2-23.7 % of the phenotypic variance. Sixteen major QTLs, which could explain greater than 10 % of the phenotypic variation, were mapped in multiple environments, implying that kernel traits might be controlled by many minor and multiple major QTLs. The major QTL qKW-9.2 with physical confidence interval of 1.68 Mbp, affecting kernel width, was then selected for fine mapping using heterogeneous inbred families. At final, the location of the underlying gene was narrowed down to 630 Kb, harboring 28 putative candidate-gene models. This information will enhance molecular breeding for kernel traits and simultaneously assist the gene cloning underlying this QTL, helping to reveal the genetic basis of kernel development in maize.

Escaping the snare of chronological growth and launching a free curve alternative: general deviance as latent growth model.

PubMed

Wood, Phillip Karl; Jackson, Kristina M

2013-08-01

Researchers studying longitudinal relationships among multiple problem behaviors sometimes characterize autoregressive relationships across constructs as indicating "protective" or "launch" factors or as "developmental snares." These terms are used to indicate that initial or intermediary states of one problem behavior subsequently inhibit or promote some other problem behavior. Such models are contrasted with models of "general deviance" over time in which all problem behaviors are viewed as indicators of a common linear trajectory. When fit of the "general deviance" model is poor and fit of one or more autoregressive models is good, this is taken as support for the inhibitory or enhancing effect of one construct on another. In this paper, we argue that researchers consider competing models of growth before comparing deviance and time-bound models. Specifically, we propose use of the free curve slope intercept (FCSI) growth model (Meredith & Tisak, 1990) as a general model to typify change in a construct over time. The FCSI model includes, as nested special cases, several statistical models often used for prospective data, such as linear slope intercept models, repeated measures multivariate analysis of variance, various one-factor models, and hierarchical linear models. When considering models involving multiple constructs, we argue the construct of "general deviance" can be expressed as a single-trait multimethod model, permitting a characterization of the deviance construct over time without requiring restrictive assumptions about the form of growth over time. As an example, prospective assessments of problem behaviors from the Dunedin Multidisciplinary Health and Development Study (Silva & Stanton, 1996) are considered and contrasted with earlier analyses of Hussong, Curran, Moffitt, and Caspi (2008), which supported launch and snare hypotheses. For antisocial behavior, the FCSI model fit better than other models, including the linear chronometric growth curve model used by Hussong et al. For models including multiple constructs, a general deviance model involving a single trait and multimethod factors (or a corresponding hierarchical factor model) fit the data better than either the "snares" alternatives or the general deviance model previously considered by Hussong et al. Taken together, the analyses support the view that linkages and turning points cannot be contrasted with general deviance models absent additional experimental intervention or control.

Escaping the snare of chronological growth and launching a free curve alternative: General deviance as latent growth model

PubMed Central

WOOD, PHILLIP KARL; JACKSON, KRISTINA M.

2014-01-01

Researchers studying longitudinal relationships among multiple problem behaviors sometimes characterize autoregressive relationships across constructs as indicating “protective” or “launch” factors or as “developmental snares.” These terms are used to indicate that initial or intermediary states of one problem behavior subsequently inhibit or promote some other problem behavior. Such models are contrasted with models of “general deviance” over time in which all problem behaviors are viewed as indicators of a common linear trajectory. When fit of the “general deviance” model is poor and fit of one or more autoregressive models is good, this is taken as support for the inhibitory or enhancing effect of one construct on another. In this paper, we argue that researchers consider competing models of growth before comparing deviance and time-bound models. Specifically, we propose use of the free curve slope intercept (FCSI) growth model (Meredith & Tisak, 1990) as a general model to typify change in a construct over time. The FCSI model includes, as nested special cases, several statistical models often used for prospective data, such as linear slope intercept models, repeated measures multivariate analysis of variance, various one-factor models, and hierarchical linear models. When considering models involving multiple constructs, we argue the construct of “general deviance” can be expressed as a single-trait multimethod model, permitting a characterization of the deviance construct over time without requiring restrictive assumptions about the form of growth over time. As an example, prospective assessments of problem behaviors from the Dunedin Multidisciplinary Health and Development Study (Silva & Stanton, 1996) are considered and contrasted with earlier analyses of Hussong, Curran, Moffitt, and Caspi (2008), which supported launch and snare hypotheses. For antisocial behavior, the FCSI model fit better than other models, including the linear chronometric growth curve model used by Hussong et al. For models including multiple constructs, a general deviance model involving a single trait and multimethod factors (or a corresponding hierarchical factor model) fit the data better than either the “snares” alternatives or the general deviance model previously considered by Hussong et al. Taken together, the analyses support the view that linkages and turning points cannot be contrasted with general deviance models absent additional experimental intervention or control. PMID:23880389

Climate change and functional traits affect population dynamics of a long-lived seabird.

PubMed

Jenouvrier, Stéphanie; Desprez, Marine; Fay, Remi; Barbraud, Christophe; Weimerskirch, Henri; Delord, Karine; Caswell, Hal

2018-07-01

Recent studies unravelled the effect of climate changes on populations through their impact on functional traits and demographic rates in terrestrial and freshwater ecosystems, but such understanding in marine ecosystems remains incomplete. Here, we evaluate the impact of the combined effects of climate and functional traits on population dynamics of a long-lived migratory seabird breeding in the southern ocean: the black-browed albatross (Thalassarche melanophris, BBA). We address the following prospective question: "Of all the changes in the climate and functional traits, which would produce the biggest impact on the BBA population growth rate?" We develop a structured matrix population model that includes the effect of climate and functional traits on the complete BBA life cycle. A detailed sensitivity analysis is conducted to understand the main pathway by which climate and functional trait changes affect the population growth rate. The population growth rate of BBA is driven by the combined effects of climate over various seasons and multiple functional traits with carry-over effects across seasons on demographic processes. Changes in sea surface temperature (SST) during late winter cause the biggest changes in the population growth rate, through their effect on juvenile survival. Adults appeared to respond to changes in winter climate conditions by adapting their migratory schedule rather than by modifying their at-sea foraging activity. However, the sensitivity of the population growth rate to SST affecting BBA migratory schedule is small. BBA foraging activity during the pre-breeding period has the biggest impact on population growth rate among functional traits. Finally, changes in SST during the breeding season have little effect on the population growth rate. These results highlight the importance of early life histories and carry-over effects of climate and functional traits on demographic rates across multiple seasons in population response to climate change. Robust conclusions about the roles of various phases of the life cycle and functional traits in population response to climate change rely on an understanding of the relationships of traits to demographic rates across the complete life cycle. © 2018 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd oxn behalf of British Ecological Society.

Genealogies and ages of cultural traits: An application of the theory of duality to the research on cultural evolution.

PubMed

Kobayashi, Yutaka; Wakano, Joe Yuichiro; Ohtsuki, Hisashi

2018-05-09

A finite-population, discrete-generation model of cultural evolution is described, in which multiple discrete traits are transmitted independently. In this model, each newborn may inherit a trait from multiple cultural parents. Transmission fails with a positive probability unlike in population genetics. An ancestral process simulating the cultural genealogy of a sample of individuals is derived for this model. This ancestral process, denoted by M - , is shown to be dual to a process M + describing the change in the frequency of a trait. The age-frequency spectrum is defined as a two-dimensional array whose (i,k) element is the expected number of distinct cultural traits introduced k generations ago and now carried by i individuals in a sample of a particular size n. Numerical calculations reveal that the age-frequency spectrum and related metrics undergo a critical transition from a phase with a moderate number of young, rare traits to a phase with numerous very old, common traits when the expected number of cultural parents per individual exceeds one. It is shown that M + and M - converge to branching or deterministic processes, depending on the way population size tends to infinity, and these limiting processes bear some duality relationships. The critical behavior of the original processes M + and M - is explained in terms of a phase transition of the branching processes. Using the results of the limiting processes in combination, we derive analytical formulae that well approximate the age-frequency spectrum and also other metrics. Copyright © 2018 Elsevier Inc. All rights reserved.

Recent progress in the genetics of spontaneously hypertensive rats.

PubMed

Pravenec, M; Křen, V; Landa, V; Mlejnek, P; Musilová, A; Šilhavý, J; Šimáková, M; Zídek, V

2014-01-01

The spontaneously hypertensive rat (SHR) is the most widely used animal model of essential hypertension and accompanying metabolic disturbances. Recent advances in sequencing of genomes of BN-Lx and SHR progenitors of the BXH/HXB recombinant inbred (RI) strains as well as accumulation of multiple data sets of intermediary phenotypes in the RI strains, including mRNA and microRNA abundance, quantitative metabolomics, proteomics, methylomics or histone modifications, will make it possible to systematically search for genetic variants involved in regulation of gene expression and in the etiology of complex pathophysiological traits. New advances in manipulation of the rat genome, including efficient transgenesis and gene targeting, will enable in vivo functional analyses of selected candidate genes to identify QTL at the molecular level or to provide insight into mechanisms whereby targeted genes affect pathophysiological traits in the SHR.

Genome-wide association analysis of seedling root development in maize (Zea mays L.).

PubMed

Pace, Jordon; Gardner, Candice; Romay, Cinta; Ganapathysubramanian, Baskar; Lübberstedt, Thomas

2015-02-05

Plants rely on the root system for anchorage to the ground and the acquisition and absorption of nutrients critical to sustaining productivity. A genome wide association analysis enables one to analyze allelic diversity of complex traits and identify superior alleles. 384 inbred lines from the Ames panel were genotyped with 681,257 single nucleotide polymorphism markers using Genotyping-by-Sequencing technology and 22 seedling root architecture traits were phenotyped. Utilizing both a general linear model and mixed linear model, a GWAS study was conducted identifying 268 marker trait associations (p ≤ 5.3×10(-7)). Analysis of significant SNP markers for multiple traits showed that several were located within gene models with some SNP markers localized within regions of previously identified root quantitative trait loci. Gene model GRMZM2G153722 located on chromosome 4 contained nine significant markers. This predicted gene is expressed in roots and shoots. This study identifies putatively associated SNP markers associated with root traits at the seedling stage. Some SNPs were located within or near (<1 kb) gene models. These gene models identify possible candidate genes involved in root development at the seedling stage. These and respective linked or functional markers could be targets for breeders for marker assisted selection of seedling root traits.

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

PubMed Central

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

2014-01-01

Leaf litter decomposability is an important effect trait for ecosystem functioning. However, it is unknown how this effect trait evolved through plant history as a leaf ‘afterlife’ integrator of the evolution of multiple underlying traits upon which adaptive selection must have acted. Did decomposability evolve in a Brownian fashion without any constraints? Was evolution rapid at first and then slowed? Or was there an underlying mean-reverting process that makes the evolution of extreme trait values unlikely? Here, we test the hypothesis that the evolution of decomposability has undergone certain mean-reverting forces due to strong constraints and trade-offs in the leaf traits that have afterlife effects on litter quality to decomposers. In order to test this, we examined the leaf litter decomposability and seven key leaf traits of 48 tree species in the temperate area of China and fitted them to three evolutionary models: Brownian motion model (BM), Early burst model (EB), and Ornstein-Uhlenbeck model (OU). The OU model, which does not allow unlimited trait divergence through time, was the best fit model for leaf litter decomposability and all seven leaf traits. These results support the hypothesis that neither decomposability nor the underlying traits has been able to diverge toward progressively extreme values through evolutionary time. These results have reinforced our understanding of the relationships between leaf litter decomposability and leaf traits in an evolutionary perspective and may be a helpful step toward reconstructing deep-time carbon cycling based on taxonomic composition with more confidence. PMID:25535551

Use of a quality trait index to increase the reliability of phenotypic evaluations in broccoli

USDA-ARS?s Scientific Manuscript database

Selection of superior broccoli hybrids involves multiple considerations, including optimization of head quality traits. Quality assessment of broccoli heads is often confounded by relatively subjective human preferences for optimal appearance of heads. To assist the selection process, we assessed fi...

Association Genetics of Wood Physical Traits in the Conifer White Spruce and Relationships With Gene Expression

PubMed Central

Beaulieu, Jean; Doerksen, Trevor; Boyle, Brian; Clément, Sébastien; Deslauriers, Marie; Beauseigle, Stéphanie; Blais, Sylvie; Poulin, Pier-Luc; Lenz, Patrick; Caron, Sébastien; Rigault, Philippe; Bicho, Paul; Bousquet, Jean; MacKay, John

2011-01-01

Marker-assisted selection holds promise for highly influencing tree breeding, especially for wood traits, by considerably reducing breeding cycles and increasing selection accuracy. In this study, we used a candidate gene approach to test for associations between 944 single-nucleotide polymorphism markers from 549 candidate genes and 25 wood quality traits in white spruce. A mixed-linear model approach, including a weak but nonsignificant population structure, was implemented for each marker–trait combination. Relatedness among individuals was controlled using a kinship matrix estimated either from the known half-sib structure or from the markers. Both additive and dominance effect models were tested. Between 8 and 21 single-nucleotide polymorphisms (SNPs) were found to be significantly associated (P ≤ 0.01) with each of earlywood, latewood, or total wood traits. After controlling for multiple testing (Q ≤ 0.10), 13 SNPs were still significant across as many genes belonging to different families, each accounting for between 3 and 5% of the phenotypic variance in 10 wood characters. Transcript accumulation was determined for genes containing SNPs associated with these traits. Significantly different transcript levels (P ≤ 0.05) were found among the SNP genotypes of a 1-aminocyclopropane-1-carboxylate oxidase, a β-tonoplast intrinsic protein, and a long-chain acyl-CoA synthetase 9. These results should contribute toward the development of efficient marker-assisted selection in an economically important tree species. PMID:21385726

A Rigorous Test of the Fit of the Circumplex Model to Big Five Personality Data: Theoretical and Methodological Issues and Two Large Sample Empirical Tests.

PubMed

DeGeest, David Scott; Schmidt, Frank

2015-01-01

Our objective was to apply the rigorous test developed by Browne (1992) to determine whether the circumplex model fits Big Five personality data. This test has yet to be applied to personality data. Another objective was to determine whether blended items explained correlations among the Big Five traits. We used two working adult samples, the Eugene-Springfield Community Sample and the Professional Worker Career Experience Survey. Fit to the circumplex was tested via Browne's (1992) procedure. Circumplexes were graphed to identify items with loadings on multiple traits (blended items), and to determine whether removing these items changed five-factor model (FFM) trait intercorrelations. In both samples, the circumplex structure fit the FFM traits well. Each sample had items with dual-factor loadings (8 items in the first sample, 21 in the second). Removing blended items had little effect on construct-level intercorrelations among FFM traits. We conclude that rigorous tests show that the fit of personality data to the circumplex model is good. This finding means the circumplex model is competitive with the factor model in understanding the organization of personality traits. The circumplex structure also provides a theoretically and empirically sound rationale for evaluating intercorrelations among FFM traits. Even after eliminating blended items, FFM personality traits remained correlated.

Fitting models of continuous trait evolution to incompletely sampled comparative data using approximate Bayesian computation.

PubMed

Slater, Graham J; Harmon, Luke J; Wegmann, Daniel; Joyce, Paul; Revell, Liam J; Alfaro, Michael E

2012-03-01

In recent years, a suite of methods has been developed to fit multiple rate models to phylogenetic comparative data. However, most methods have limited utility at broad phylogenetic scales because they typically require complete sampling of both the tree and the associated phenotypic data. Here, we develop and implement a new, tree-based method called MECCA (Modeling Evolution of Continuous Characters using ABC) that uses a hybrid likelihood/approximate Bayesian computation (ABC)-Markov-Chain Monte Carlo approach to simultaneously infer rates of diversification and trait evolution from incompletely sampled phylogenies and trait data. We demonstrate via simulation that MECCA has considerable power to choose among single versus multiple evolutionary rate models, and thus can be used to test hypotheses about changes in the rate of trait evolution across an incomplete tree of life. We finally apply MECCA to an empirical example of body size evolution in carnivores, and show that there is no evidence for an elevated rate of body size evolution in the pinnipeds relative to terrestrial carnivores. ABC approaches can provide a useful alternative set of tools for future macroevolutionary studies where likelihood-dependent approaches are lacking. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Dispositional optimism and sleep quality: a test of mediating pathways

PubMed Central

Cribbet, Matthew; Kent de Grey, Robert G.; Cronan, Sierra; Trettevik, Ryan; Smith, Timothy W.

2016-01-01

Dispositional optimism has been related to beneficial influences on physical health outcomes. However, its links to global sleep quality and the psychological mediators responsible for such associations are less studied. This study thus examined if trait optimism predicted global sleep quality, and if measures of subjective well-being were statistical mediators of such links. A community sample of 175 participants (93 men, 82 women) completed measures of trait optimism, depression, and life satisfaction. Global sleep quality was assessed using the Pittsburgh Sleep Quality Index. Results indicated that trait optimism was a strong predictor of better PSQI global sleep quality. Moreover, this association was mediated by depression and life satisfaction in both single and multiple mediator models. These results highlight the importance of optimism for the restorative process of sleep, as well as the utility of multiple mediator models in testing distinct psychological pathways. PMID:27592128

Dispositional optimism and sleep quality: a test of mediating pathways.

PubMed

Uchino, Bert N; Cribbet, Matthew; de Grey, Robert G Kent; Cronan, Sierra; Trettevik, Ryan; Smith, Timothy W

2017-04-01

Dispositional optimism has been related to beneficial influences on physical health outcomes. However, its links to global sleep quality and the psychological mediators responsible for such associations are less studied. This study thus examined if trait optimism predicted global sleep quality, and if measures of subjective well-being were statistical mediators of such links. A community sample of 175 participants (93 men, 82 women) completed measures of trait optimism, depression, and life satisfaction. Global sleep quality was assessed using the Pittsburgh Sleep Quality Index. Results indicated that trait optimism was a strong predictor of better PSQI global sleep quality. Moreover, this association was mediated by depression and life satisfaction in both single and multiple mediator models. These results highlight the importance of optimism for the restorative process of sleep, as well as the utility of multiple mediator models in testing distinct psychological pathways.

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.

Suicidality as a Function of Impulsivity, Callous/Unemotional Traits, and Depressive Symptoms in Youth

PubMed Central

Javdani, Shabnam; Sadeh, Naomi; Verona, Edelyn

2012-01-01

Suicidality represents one of the most important areas of risk for adolescents, with both internalizing (e.g., depression, anxiety) and externalizing/antisocial (e.g., substance use, conduct) disorders conferring risk for suicidal ideation and attempts (e.g., Bridge et al., 2006). However, no study has attended to gender differences in relationships between suicidality and different facets of psychopathic tendencies in youth. Further, very little research has focused on disentangling the multiple manifestations of suicide risk in the same study, including behaviors (suicide attempts with intent to die, self- injurious behavior) and general suicide risk marked by suicidal ideation/plans. To better understand these relationships, we recruited 184 adolescents from the community and those in treatment. As predicted, psychopathic traits and depressive symptoms in youth showed differential associations with components of suicidality. Specifically, impulsive traits uniquely contributed to suicide attempts and self- injurious behaviors, above the influence of depression. Indeed, once psychopathic tendencies were entered in the model, depressive symptoms only explained general suicide risk marked by ideation/plans but not behaviors. Further, callous/unemotional traits conferred protection from suicide attempts selectively in girls. These findings have important implications for developing integrative models that incorporate differential relationships between 1) depressed mood and 2) personality risk factors (i.e., impulsivity and callous-unemotional traits) for suicidality in youth. PMID:21280931

Prognostic model for psychological outcomes in ambulatory surgery patients: A prospective study using a structural equation modeling framework.

PubMed

Mijderwijk, Hendrik-Jan; Stolker, Robert Jan; Duivenvoorden, Hugo J; Klimek, Markus; Steyerberg, Ewout W

2018-01-01

Surgical procedures are increasingly carried out in a day-case setting. Along with this increase, psychological outcomes have become prominent. The objective was to evaluate prospectively the prognostic effects of sociodemographic, medical, and psychological variables assessed before day-case surgery on psychological outcomes after surgery. The study was carried out between October 2010 and September 2011. We analyzed 398 mixed patients, from a randomized controlled trial, undergoing day-case surgery at a university medical center. Structural equation modeling was used to jointly study presurgical prognostic variables relating to sociodemographics (age, sex, nationality, marital status, having children, religion, educational level, employment), medical status (BMI, heart rate), and psychological status associated with anxiety (State-Trait Anxiety Inventory (STAI), Hospital Anxiety and Depression Scale (HADS-A)), fatigue (Multidimensional Fatigue Inventory (MFI)), aggression (State-Trait Anger Scale (STAS)), depressive moods (HADS-D), self-esteem, and self-efficacy. We studied psychological outcomes on day 7 after surgery, including anxiety, fatigue, depressive moods, and aggression regulation. The final prognostic model comprised the following variables: anxiety (STAI, HADS-A), fatigue (MFI), depression (HADS-D), aggression (STAS), self-efficacy, sex, and having children. The corresponding psychological variables as assessed at baseline were prominent (i.e. standardized regression coefficients ≥ 0.20), with STAI-Trait score being the strongest predictor overall. STAI-State (adjusted R2 = 0.44), STAI-Trait (0.66), HADS-A (0.45) and STAS-Trait (0.54) were best predicted. We provide a prognostic model that adequately predicts multiple postoperative outcomes in day-case surgery. Consequently, this enables timely identification of vulnerable patients who may require additional medical or psychological preventive treatment or-in a worst-case scenario-could be unselected for day-case surgery.

Coevolution can reverse predator–prey cycles

PubMed Central

Cortez, Michael H.; Weitz, Joshua S.

2014-01-01

A hallmark of Lotka–Volterra models, and other ecological models of predator–prey interactions, is that in predator–prey cycles, peaks in prey abundance precede peaks in predator abundance. Such models typically assume that species life history traits are fixed over ecologically relevant time scales. However, the coevolution of predator and prey traits has been shown to alter the community dynamics of natural systems, leading to novel dynamics including antiphase and cryptic cycles. Here, using an eco-coevolutionary model, we show that predator–prey coevolution can also drive population cycles where the opposite of canonical Lotka–Volterra oscillations occurs: predator peaks precede prey peaks. These reversed cycles arise when selection favors extreme phenotypes, predator offense is costly, and prey defense is effective against low-offense predators. We present multiple datasets from phage–cholera, mink–muskrat, and gyrfalcon–rock ptarmigan systems that exhibit reversed-peak ordering. Our results suggest that such cycles are a potential signature of predator–prey coevolution and reveal unique ways in which predator–prey coevolution can shape, and possibly reverse, community dynamics. PMID:24799689

Coevolution can reverse predator-prey cycles.

PubMed

Cortez, Michael H; Weitz, Joshua S

2014-05-20

A hallmark of Lotka-Volterra models, and other ecological models of predator-prey interactions, is that in predator-prey cycles, peaks in prey abundance precede peaks in predator abundance. Such models typically assume that species life history traits are fixed over ecologically relevant time scales. However, the coevolution of predator and prey traits has been shown to alter the community dynamics of natural systems, leading to novel dynamics including antiphase and cryptic cycles. Here, using an eco-coevolutionary model, we show that predator-prey coevolution can also drive population cycles where the opposite of canonical Lotka-Volterra oscillations occurs: predator peaks precede prey peaks. These reversed cycles arise when selection favors extreme phenotypes, predator offense is costly, and prey defense is effective against low-offense predators. We present multiple datasets from phage-cholera, mink-muskrat, and gyrfalcon-rock ptarmigan systems that exhibit reversed-peak ordering. Our results suggest that such cycles are a potential signature of predator-prey coevolution and reveal unique ways in which predator-prey coevolution can shape, and possibly reverse, community dynamics.

Testing for measurement invariance and latent mean differences across methods: interesting incremental information from multitrait-multimethod studies

PubMed Central

Geiser, Christian; Burns, G. Leonard; Servera, Mateu

2014-01-01

Models of confirmatory factor analysis (CFA) are frequently applied to examine the convergent validity of scores obtained from multiple raters or methods in so-called multitrait-multimethod (MTMM) investigations. We show that interesting incremental information about method effects can be gained from including mean structures and tests of MI across methods in MTMM models. We present a modeling framework for testing MI in the first step of a CFA-MTMM analysis. We also discuss the relevance of MI in the context of four more complex CFA-MTMM models with method factors. We focus on three recently developed multiple-indicator CFA-MTMM models for structurally different methods [the correlated traits-correlated (methods – 1), latent difference, and latent means models; Geiser et al., 2014a; Pohl and Steyer, 2010; Pohl et al., 2008] and one model for interchangeable methods (Eid et al., 2008). We demonstrate that some of these models require or imply MI by definition for a proper interpretation of trait or method factors, whereas others do not, and explain why MI may or may not be required in each model. We show that in the model for interchangeable methods, testing for MI is critical for determining whether methods can truly be seen as interchangeable. We illustrate the theoretical issues in an empirical application to an MTMM study of attention deficit and hyperactivity disorder (ADHD) with mother, father, and teacher ratings as methods. PMID:25400603

Structural Equation Modelling of Multiple Facet Data: Extending Models for Multitrait-Multimethod Data

ERIC Educational Resources Information Center

Bechger, Timo M.; Maris, Gunter

2004-01-01

This paper is about the structural equation modelling of quantitative measures that are obtained from a multiple facet design. A facet is simply a set consisting of a finite number of elements. It is assumed that measures are obtained by combining each element of each facet. Methods and traits are two such facets, and a multitrait-multimethod…

The relationship between parenting factors and trait anxiety: mediating role of cognitive errors and metacognition.

PubMed

Gallagher, Bridie; Cartwright-Hatton, Sam

2008-05-01

Research examining parenting factors in the development of anxiety has focused largely on the concepts of parental warmth and overcontrolling or intrusive parenting, This study investigated the relationship between these factors, and also parental discipline style and anxiety using self-report methodology with a sample of 16-18 year olds. In order to try to explain the relationship between parenting and anxiety, measures of cognition were also included. A multiple regression was conducted including all parenting factors as predictors of trait anxiety. The regression was a modest fit (R(2)=22%) and the model was significant (F(4, 141)=9.90, p<0.0001). Only the effect of Over-reactivity was significant, (t=3.72, p<0.0001). Furthermore, Over-reactive discipline was significantly associated with increased cognitive distortions (r=0.361 p<0.0001) and metacognition (r=0.396 p<0.0001). Both cognitive distortions and metacognition were found to partially mediate the relationship between discipline style and trait anxiety. The implications of these findings and areas for future research are discussed.

Maternal factors predicting cognitive and behavioral characteristics of children with fetal alcohol spectrum disorders.

PubMed

May, Philip A; Tabachnick, Barbara G; Gossage, J Phillip; Kalberg, Wendy O; Marais, Anna-Susan; Robinson, Luther K; Manning, Melanie A; Blankenship, Jason; Buckley, David; Hoyme, H Eugene; Adnams, Colleen M

2013-06-01

To provide an analysis of multiple predictors of cognitive and behavioral traits for children with fetal alcohol spectrum disorders (FASDs). Multivariate correlation techniques were used with maternal and child data from epidemiologic studies in a community in South Africa. Data on 561 first-grade children with fetal alcohol syndrome (FAS), partial FAS (PFAS), and not FASD and their mothers were analyzed by grouping 19 maternal variables into categories (physical, demographic, childbearing, and drinking) and used in structural equation models (SEMs) to assess correlates of child intelligence (verbal and nonverbal) and behavior. A first SEM using only 7 maternal alcohol use variables to predict cognitive/behavioral traits was statistically significant (B = 3.10, p < .05) but explained only 17.3% of the variance. The second model incorporated multiple maternal variables and was statistically significant explaining 55.3% of the variance. Significantly correlated with low intelligence and problem behavior were demographic (B = 3.83, p < .05) (low maternal education, low socioeconomic status [SES], and rural residence) and maternal physical characteristics (B = 2.70, p < .05) (short stature, small head circumference, and low weight). Childbearing history and alcohol use composites were not statistically significant in the final complex model and were overpowered by SES and maternal physical traits. Although other analytic techniques have amply demonstrated the negative effects of maternal drinking on intelligence and behavior, this highly controlled analysis of multiple maternal influences reveals that maternal demographics and physical traits make a significant enabling or disabling contribution to child functioning in FASD.

The taming of the neural crest: a developmental perspective on the origins of morphological covariation in domesticated mammals

NASA Astrophysics Data System (ADS)

Sánchez-Villagra, Marcelo R.; Geiger, Madeleine; Schneider, Richard A.

2016-06-01

Studies on domestication are blooming, but the developmental bases for the generation of domestication traits and breed diversity remain largely unexplored. Some phenotypic patterns of human neurocristopathies are suggestive of those reported for domesticated mammals and disrupting neural crest developmental programmes have been argued to be the source of traits deemed the `domestication syndrome'. These character changes span multiple organ systems and morphological structures. But an in-depth examination within the phylogenetic framework of mammals including domesticated forms reveals that the distribution of such traits is not universal, with canids being the only group showing a large set of predicted features. Modularity of traits tied to phylogeny characterizes domesticated mammals: through selective breeding, individual behavioural and morphological traits can be reordered, truncated, augmented or deleted. Similarly, mammalian evolution on islands has resulted in suites of phenotypic changes like those of some domesticated forms. Many domesticated mammals can serve as valuable models for conducting comparative studies on the evolutionary developmental biology of the neural crest, given that series of their embryos are readily available and that their phylogenetic histories and genomes are well characterized.

Development and Validation of Big Four Personality Scales for the Schedule for Nonadaptive and Adaptive Personality-2nd Edition (SNAP-2)

PubMed Central

Calabrese, William R.; Rudick, Monica M.; Simms, Leonard J.; Clark, Lee Anna

2012-01-01

Recently, integrative, hierarchical models of personality and personality disorder (PD)—such as the Big Three, Big Four and Big Five trait models—have gained support as a unifying dimensional framework for describing PD. However, no measures to date can simultaneously represent each of these potentially interesting levels of the personality hierarchy. To unify these measurement models psychometrically, we sought to develop Big Five trait scales within the Schedule for Adaptive and Nonadaptive Personality–2nd Edition (SNAP-2). Through structural and content analyses, we examined relations between the SNAP-2, Big Five Inventory (BFI), and NEO-Five Factor Inventory (NEO-FFI) ratings in a large data set (N = 8,690), including clinical, military, college, and community participants. Results yielded scales consistent with the Big Four model of personality (i.e., Neuroticism, Conscientiousness, Introversion, and Antagonism) and not the Big Five as there were insufficient items related to Openness. Resulting scale scores demonstrated strong internal consistency and temporal stability. Structural and external validity was supported by strong convergent and discriminant validity patterns between Big Four scale scores and other personality trait scores and expectable patterns of self-peer agreement. Descriptive statistics and community-based norms are provided. The SNAP-2 Big Four Scales enable researchers and clinicians to assess personality at multiple levels of the trait hierarchy and facilitate comparisons among competing “Big Trait” models. PMID:22250598

Mapping quantitative trait loci for yield, yield components and morphological traits in an advanced backcross population between Oryza rufipogon and the Oryza sativa cultivar Jefferson.

PubMed

Thomson, M J; Tai, T H; McClung, A M; Lai, X-H; Hinga, M E; Lobos, K B; Xu, Y; Martinez, C P; McCouch, S R

2003-08-01

An advanced backcross population between an accession of Oryza rufipogon (IRGC 105491) and the U.S. cultivar Jefferson (Oryza sativa ssp. japonica) was developed to identify quantitative trait loci (QTLs) for yield, yield components and morphological traits. The genetic linkage map generated for this population consisted of 153 SSR and RFLP markers with an average interval size of 10.3 cM. Thirteen traits were examined, nine of which were measured in multiple environments. Seventy-six QTLs above an experiment-wise significance threshold of P<0.01 (corresponding to an interval mapping LOD>3.6 or a composite interval mapping LOD>3.9) were identified. For the traits measured in multiple environments, 47% of the QTLs were detected in at least two environments. The O. rufipogon allele was favorable for 53% of the yield and yield component QTLs, including loci for yield, grains per panicle, panicle length, and grain weight. Morphological traits related to the domestication process and/or weedy characteristics, including plant height, shattering, tiller type and awns, were found clustered on chromosomes 1 and 4. Comparisons to previous studies involving wild x cultivated crosses revealed O. rufipogon alleles with stable effects in multiple genetic backgrounds and environments, several of which have not been detected in studies between Oryza sativa cultivars, indicating potentially novel alleles from O. rufipogon. Some O. rufipogon-derived QTLs, however, were in similar regions as previously reported QTLs from Oryza sativa cultivars, providing evidence for conservation of these QTLs across the Oryza genus. In addition, several QTLs for grain weight, plant height, and flowering time were localized to putative homeologous regions in maize where QTLs for these traits have been previously reported, supporting the hypothesis of functional conservation of QTLs across the grasses.

A trait-based approach for predicting species responses to environmental change from sparse data: how well might terrestrial mammals track climate change?

PubMed

Santini, Luca; Cornulier, Thomas; Bullock, James M; Palmer, Stephen C F; White, Steven M; Hodgson, Jenny A; Bocedi, Greta; Travis, Justin M J

2016-07-01

Estimating population spread rates across multiple species is vital for projecting biodiversity responses to climate change. A major challenge is to parameterise spread models for many species. We introduce an approach that addresses this challenge, coupling a trait-based analysis with spatial population modelling to project spread rates for 15 000 virtual mammals with life histories that reflect those seen in the real world. Covariances among life-history traits are estimated from an extensive terrestrial mammal data set using Bayesian inference. We elucidate the relative roles of different life-history traits in driving modelled spread rates, demonstrating that any one alone will be a poor predictor. We also estimate that around 30% of mammal species have potential spread rates slower than the global mean velocity of climate change. This novel trait-space-demographic modelling approach has broad applicability for tackling many key ecological questions for which we have the models but are hindered by data availability. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Multiple filters affect tree species assembly in mid-latitude forest communities.

PubMed

Kubota, Y; Kusumoto, B; Shiono, T; Ulrich, W

2018-05-01

Species assembly patterns of local communities are shaped by the balance between multiple abiotic/biotic filters and dispersal that both select individuals from species pools at the regional scale. Knowledge regarding functional assembly can provide insight into the relative importance of the deterministic and stochastic processes that shape species assembly. We evaluated the hierarchical roles of the α niche and β niches by analyzing the influence of environmental filtering relative to functional traits on geographical patterns of tree species assembly in mid-latitude forests. Using forest plot datasets, we examined the α niche traits (leaf and wood traits) and β niche properties (cold/drought tolerance) of tree species, and tested non-randomness (clustering/over-dispersion) of trait assembly based on null models that assumed two types of species pools related to biogeographical regions. For most plots, species assembly patterns fell within the range of random expectation. However, particularly for cold/drought tolerance-related β niche properties, deviation from randomness was frequently found; non-random clustering was predominant in higher latitudes with harsh climates. Our findings demonstrate that both randomness and non-randomness in trait assembly emerged as a result of the α and β niches, although we suggest the potential role of dispersal processes and/or species equalization through trait similarities in generating the prevalence of randomness. Clustering of β niche traits along latitudinal climatic gradients provides clear evidence of species sorting by filtering particular traits. Our results reveal that multiple filters through functional niches and stochastic processes jointly shape geographical patterns of species assembly across mid-latitude forests.

Linking hydraulic traits to tropical forest function in a size-structured and trait-driven model (TFS v.1-Hydro)

NASA Astrophysics Data System (ADS)

Christoffersen, Bradley O.; Gloor, Manuel; Fauset, Sophie; Fyllas, Nikolaos M.; Galbraith, David R.; Baker, Timothy R.; Kruijt, Bart; Rowland, Lucy; Fisher, Rosie A.; Binks, Oliver J.; Sevanto, Sanna; Xu, Chonggang; Jansen, Steven; Choat, Brendan; Mencuccini, Maurizio; McDowell, Nate G.; Meir, Patrick

2016-11-01

Forest ecosystem models based on heuristic water stress functions poorly predict tropical forest response to drought partly because they do not capture the diversity of hydraulic traits (including variation in tree size) observed in tropical forests. We developed a continuous porous media approach to modeling plant hydraulics in which all parameters of the constitutive equations are biologically interpretable and measurable plant hydraulic traits (e.g., turgor loss point πtlp, bulk elastic modulus ɛ, hydraulic capacitance Cft, xylem hydraulic conductivity ks,max, water potential at 50 % loss of conductivity for both xylem (P50,x) and stomata (P50,gs), and the leaf : sapwood area ratio Al : As). We embedded this plant hydraulics model within a trait forest simulator (TFS) that models light environments of individual trees and their upper boundary conditions (transpiration), as well as providing a means for parameterizing variation in hydraulic traits among individuals. We synthesized literature and existing databases to parameterize all hydraulic traits as a function of stem and leaf traits, including wood density (WD), leaf mass per area (LMA), and photosynthetic capacity (Amax), and evaluated the coupled model (called TFS v.1-Hydro) predictions, against observed diurnal and seasonal variability in stem and leaf water potential as well as stand-scaled sap flux. Our hydraulic trait synthesis revealed coordination among leaf and xylem hydraulic traits and statistically significant relationships of most hydraulic traits with more easily measured plant traits. Using the most informative empirical trait-trait relationships derived from this synthesis, TFS v.1-Hydro successfully captured individual variation in leaf and stem water potential due to increasing tree size and light environment, with model representation of hydraulic architecture and plant traits exerting primary and secondary controls, respectively, on the fidelity of model predictions. The plant hydraulics model made substantial improvements to simulations of total ecosystem transpiration. Remaining uncertainties and limitations of the trait paradigm for plant hydraulics modeling are highlighted.

Mapping eQTLs in the Norfolk Island Genetic Isolate Identifies Candidate Genes for CVD Risk Traits

PubMed Central

Benton, Miles C.; Lea, Rod A.; Macartney-Coxson, Donia; Carless, Melanie A.; Göring, Harald H.; Bellis, Claire; Hanna, Michelle; Eccles, David; Chambers, Geoffrey K.; Curran, Joanne E.; Harper, Jacquie L.; Blangero, John; Griffiths, Lyn R.

2013-01-01

Cardiovascular disease (CVD) affects millions of people worldwide and is influenced by numerous factors, including lifestyle and genetics. Expression quantitative trait loci (eQTLs) influence gene expression and are good candidates for CVD risk. Founder-effect pedigrees can provide additional power to map genes associated with disease risk. Therefore, we identified eQTLs in the genetic isolate of Norfolk Island (NI) and tested for associations between these and CVD risk factors. We measured genome-wide transcript levels of blood lymphocytes in 330 individuals and used pedigree-based heritability analysis to identify heritable transcripts. eQTLs were identified by genome-wide association testing of these transcripts. Testing for association between CVD risk factors (i.e., blood lipids, blood pressure, and body fat indices) and eQTLs revealed 1,712 heritable transcripts (p < 0.05) with heritability values ranging from 0.18 to 0.84. From these, we identified 200 cis-acting and 70 trans-acting eQTLs (p < 1.84 × 10−7) An eQTL-centric analysis of CVD risk traits revealed multiple associations, including 12 previously associated with CVD-related traits. Trait versus eQTL regression modeling identified four CVD risk candidates (NAAA, PAPSS1, NME1, and PRDX1), all of which have known biological roles in disease. In addition, we implicated several genes previously associated with CVD risk traits, including MTHFR and FN3KRP. We have successfully identified a panel of eQTLs in the NI pedigree and used this to implicate several genes in CVD risk. Future studies are required for further assessing the functional importance of these eQTLs and whether the findings here also relate to outbred populations. PMID:24314549

Cognitive and affective empathy in children with conduct problems: additive and interactive effects of callous-unemotional traits and autism spectrum disorders symptoms.

PubMed

Pasalich, Dave S; Dadds, Mark R; Hawes, David J

2014-11-30

Callous-unemotional (CU) traits and autism spectrum disorders (ASD) symptoms are characterized by problems in empathy; however, these behavioral features are rarely examined together in children with conduct problems. This study investigated additive and interactive effects of CU traits and ASD symptoms in relation to cognitive and affective empathy in a non-ASD clinic-referred sample. Participants were 134 children aged 3 to 9 years (M=5.60; 79% boys) with oppositional defiant/conduct disorder, and their parents. Clinicians, teachers, and parents reported on dimensions of child behavior, and parental reports of family dysfunction and direct observations of parental warmth/responsiveness assessed quality of family relationships. Results from multiple regression analysis showed that, over and above the effects of child conduct problem severity and quality of family relationships, both ASD symptoms and CU traits were uniquely associated with deficits in cognitive empathy. Moreover, CU traits demonstrated an independent association with affective empathy, and this relationship was moderated by ASD symptoms. That is, there was a stronger negative association between CU traits and affective empathy at higher versus lower levels of ASD symptoms. These findings suggest including both CU traits and ASD-related social impairments in models delineating the atypical development of empathy in children with conduct problems. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Automated body weight prediction of dairy cows using 3-dimensional vision.

PubMed

Song, X; Bokkers, E A M; van der Tol, P P J; Groot Koerkamp, P W G; van Mourik, S

2018-05-01

The objectives of this study were to quantify the error of body weight prediction using automatically measured morphological traits in a 3-dimensional (3-D) vision system and to assess the influence of various sources of uncertainty on body weight prediction. In this case study, an image acquisition setup was created in a cow selection box equipped with a top-view 3-D camera. Morphological traits of hip height, hip width, and rump length were automatically extracted from the raw 3-D images taken of the rump area of dairy cows (n = 30). These traits combined with days in milk, age, and parity were used in multiple linear regression models to predict body weight. To find the best prediction model, an exhaustive feature selection algorithm was used to build intermediate models (n = 63). Each model was validated by leave-one-out cross-validation, giving the root mean square error and mean absolute percentage error. The model consisting of hip width (measurement variability of 0.006 m), days in milk, and parity was the best model, with the lowest errors of 41.2 kg of root mean square error and 5.2% mean absolute percentage error. Our integrated system, including the image acquisition setup, image analysis, and the best prediction model, predicted the body weights with a performance similar to that achieved using semi-automated or manual methods. Moreover, the variability of our simplified morphological trait measurement showed a negligible contribution to the uncertainty of body weight prediction. We suggest that dairy cow body weight prediction can be improved by incorporating more predictive morphological traits and by improving the prediction model structure. The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Joint evolution of multiple social traits: a kin selection analysis

PubMed Central

Brown, Sam P.; Taylor, Peter D.

2010-01-01

General models of the evolution of cooperation, altruism and other social behaviours have focused almost entirely on single traits, whereas it is clear that social traits commonly interact. We develop a general kin-selection framework for the evolution of social behaviours in multiple dimensions. We show that whenever there are interactions among social traits new behaviours can emerge that are not predicted by one-dimensional analyses. For example, a prohibitively costly cooperative trait can ultimately be favoured owing to initial evolution in other (cheaper) social traits that in turn change the cost–benefit ratio of the original trait. To understand these behaviours, we use a two-dimensional stability criterion that can be viewed as an extension of Hamilton's rule. Our principal example is the social dilemma posed by, first, the construction and, second, the exploitation of a shared public good. We find that, contrary to the separate one-dimensional analyses, evolutionary feedback between the two traits can cause an increase in the equilibrium level of selfish exploitation with increasing relatedness, while both social (production plus exploitation) and asocial (neither) strategies can be locally stable. Our results demonstrate the importance of emergent stability properties of multidimensional social dilemmas, as one-dimensional stability in all component dimensions can conceal multidimensional instability. PMID:19828549

A database of whole-body action videos for the study of action, emotion, and untrustworthiness.

PubMed

Keefe, Bruce D; Villing, Matthias; Racey, Chris; Strong, Samantha L; Wincenciak, Joanna; Barraclough, Nick E

2014-12-01

We present a database of high-definition (HD) videos for the study of traits inferred from whole-body actions. Twenty-nine actors (19 female) were filmed performing different actions-walking, picking up a box, putting down a box, jumping, sitting down, and standing and acting-while conveying different traits, including four emotions (anger, fear, happiness, sadness), untrustworthiness, and neutral, where no specific trait was conveyed. For the actions conveying the four emotions and untrustworthiness, the actions were filmed multiple times, with the actor conveying the traits with different levels of intensity. In total, we made 2,783 action videos (in both two-dimensional and three-dimensional format), each lasting 7 s with a frame rate of 50 fps. All videos were filmed in a green-screen studio in order to isolate the action information from all contextual detail and to provide a flexible stimulus set for future use. In order to validate the traits conveyed by each action, we asked participants to rate each of the actions corresponding to the trait that the actor portrayed in the two-dimensional videos. To provide a useful database of stimuli of multiple actions conveying multiple traits, each video name contains information on the gender of the actor, the action executed, the trait conveyed, and the rating of its perceived intensity. All videos can be downloaded free at the following address: http://www-users.york.ac.uk/~neb506/databases.html. We discuss potential uses for the database in the analysis of the perception of whole-body actions.

Exploring the genetic architecture and improving genomic prediction accuracy for mastitis and milk production traits in dairy cattle by mapping variants to hepatic transcriptomic regions responsive to intra-mammary infection.

PubMed

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

2017-05-12

A better understanding of the genetic architecture of complex traits can contribute to improve genomic prediction. We hypothesized that genomic variants associated with mastitis and milk production traits in dairy cattle are enriched in hepatic transcriptomic regions that are responsive to intra-mammary infection (IMI). Genomic markers [e.g. single nucleotide polymorphisms (SNPs)] from those regions, if included, may improve the predictive ability of a genomic model. We applied a genomic feature best linear unbiased prediction model (GFBLUP) to implement the above strategy by considering the hepatic transcriptomic regions responsive to IMI as genomic features. GFBLUP, an extension of GBLUP, includes a separate genomic effect of SNPs within a genomic feature, and allows differential weighting of the individual marker relationships in the prediction equation. Since GFBLUP is computationally intensive, we investigated whether a SNP set test could be a computationally fast way to preselect predictive genomic features. The SNP set test assesses the association between a genomic feature and a trait based on single-SNP genome-wide association studies. We applied these two approaches to mastitis and milk production traits (milk, fat and protein yield) in Holstein (HOL, n = 5056) and Jersey (JER, n = 1231) cattle. We observed that a majority of genomic features were enriched in genomic variants that were associated with mastitis and milk production traits. Compared to GBLUP, the accuracy of genomic prediction with GFBLUP was marginally improved (3.2 to 3.9%) in within-breed prediction. The highest increase (164.4%) in prediction accuracy was observed in across-breed prediction. The significance of genomic features based on the SNP set test were correlated with changes in prediction accuracy of GFBLUP (P < 0.05). GFBLUP provides a framework for integrating multiple layers of biological knowledge to provide novel insights into the biological basis of complex traits, and to improve the accuracy of genomic prediction. The SNP set test might be used as a first-step to improve GFBLUP models. Approaches like GFBLUP and SNP set test will become increasingly useful, as the functional annotations of genomes keep accumulating for a range of species and traits.

An efficient Bayesian meta-analysis approach for studying cross-phenotype genetic associations

PubMed Central

Majumdar, Arunabha; Haldar, Tanushree; Bhattacharya, Sourabh; Witte, John S.

2018-01-01

Simultaneous analysis of genetic associations with multiple phenotypes may reveal shared genetic susceptibility across traits (pleiotropy). For a locus exhibiting overall pleiotropy, it is important to identify which specific traits underlie this association. We propose a Bayesian meta-analysis approach (termed CPBayes) that uses summary-level data across multiple phenotypes to simultaneously measure the evidence of aggregate-level pleiotropic association and estimate an optimal subset of traits associated with the risk locus. This method uses a unified Bayesian statistical framework based on a spike and slab prior. CPBayes performs a fully Bayesian analysis by employing the Markov Chain Monte Carlo (MCMC) technique Gibbs sampling. It takes into account heterogeneity in the size and direction of the genetic effects across traits. It can be applied to both cohort data and separate studies of multiple traits having overlapping or non-overlapping subjects. Simulations show that CPBayes can produce higher accuracy in the selection of associated traits underlying a pleiotropic signal than the subset-based meta-analysis ASSET. We used CPBayes to undertake a genome-wide pleiotropic association study of 22 traits in the large Kaiser GERA cohort and detected six independent pleiotropic loci associated with at least two phenotypes. This includes a locus at chromosomal region 1q24.2 which exhibits an association simultaneously with the risk of five different diseases: Dermatophytosis, Hemorrhoids, Iron Deficiency, Osteoporosis and Peripheral Vascular Disease. We provide an R-package ‘CPBayes’ implementing the proposed method. PMID:29432419

Three-pronged assessment and diagnosis of personality disorder and its consequences: personality functioning, pathological traits, and psychosocial disability.

PubMed

Clark, Lee Anna; Ro, Eunyoe

2014-01-01

The alternative dimensional model of personality disorder (PD) in the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5; American Psychiatric Association, 2013), Section III, has two main criteria: impairment in personality functioning and one or more pathological personality traits. The former is defined as disturbances in self-functioning (viz., identity, self-direction), and/or interpersonal functioning (viz., empathy, intimacy). Distinguishing personality functioning and traits is important conceptually, because simply having extreme traits is not necessarily pathological. However, adding personality functioning to PD diagnosis represents an empirical challenge, because the constructs overlap conceptually. Further, there is debate regarding whether diagnosis of mental disorder requires either distress or disability, concepts that also overlap with maladaptive-range personality traits and personality dysfunction. We investigated interrelations among these constructs using multiple self-report measures of each domain in a mixed community-patient sample (N = 402). We examined the structures of functioning (psychosocial disability and personality) and personality traits, first independently, then jointly. The disability/functioning measures yielded the 3 dimensions we have found previously (Ro & Clark, 2013). Trait measures had a hierarchical structure which, at the 5-factor level, reflected neuroticism/negative affectivity (N/NA), (low) sociability, disinhibition, (dis)agreeableness, and rigid goal engagement. When all measures were cofactored, a hierarchical structure again emerged which, at the 5-factor level, included (a) internalizing (N/NA and self-pathology vs. quality-of-life/satisfaction); (b) externalizing (social/interpersonal dysfunction, low sociability, and disagreeableness); (c) disinhibition; (d) poor basic functioning; and (e) rigid goal engagement. Results are discussed in terms of developing an integrated PD diagnostic model.

Three-Pronged Assessment and Diagnosis of Personality Disorder and its Consequences: Personality Functioning, Pathological Traits, and Psychosocial Disability

PubMed Central

Clark, Lee Anna; Ro, Eunyoe

2014-01-01

The alternative dimensional model of personality disorder (PD) in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5; American Psychiatric Association, 2013), Section III, has two main criteria: Impairment in personality functioning and one or more pathological personality traits. The former is defined as disturbances in self functioning (viz., identity, self-direction), and/or interpersonal functioning (viz., empathy, intimacy). Distinguishing personality functioning and traits is important conceptually, because simply having extreme traits is not necessarily pathological. However, adding personality functioning to PD diagnosis represents an empirical challenge, because the constructs overlap conceptually. Further, there is debate regarding whether diagnosis of mental disorder requires either distress or disability, concepts that also overlap with maladaptive-range personality traits and personality dysfunction. We investigated interrelations among these constructs using multiple self-report measures of each domain in a mixed community-patient sample (N = 402). We examined the structures of functioning (psychosocial disability and personality), and personality traits, first independently, then jointly. The disability/functioning measures yielded the three dimensions we have found previously (Ro & Clark, 2013). Trait measures had a hierarchical structure which, at the five-factor level, reflected neuroticism/negative affectivity (N/NA), (low) sociability, disinhibition, (dis)agreeableness, and rigid goal engagement. When all measures were co-factored, a hierarchical structure again emerged which, at the five-factor level, included (1) internalizing (N/NA and self-pathology vs. quality-of-life/satisfaction), (2) externalizing (social/interpersonal dysfunction, low sociability, and disagreeableness), (3) disinhibition, (4) poor basic functioning, and (5) rigid goal engagement. Results are discussed in terms of developing an integrated PD diagnostic model. PMID:24588062

Tolerance to multiple climate stressors: A case study of Douglas-fir drought and cold hardiness

USGS Publications Warehouse

Bansal, Sheel; Harrington, Constance A; St. Clair, John Bradley

2016-01-01

Summary: 1. Drought and freeze events are two of the most common forms of climate extremes which result in tree damage or death, and the frequency and intensity of both stressors may increase with climate change. Few studies have examined natural covariation in stress tolerance traits to cope with multiple stressors among wild plant populations. 2. We assessed the capacity of coastal Douglas-fir (Pseudotsuga menziesii var. menziesii), an ecologically and economically important species in the northwestern USA, to tolerate both drought and cold stress on 35 populations grown in common gardens. We used principal components analysis to combine drought and cold hardiness trait data into generalized stress hardiness traits to model geographic variation in hardiness as a function of climate across the Douglas-fir range. 3. Drought and cold hardiness converged among populations along winter temperature gradients and diverged along summer precipitation gradients. Populations originating in regions with cold winters had relatively high tolerance to both drought and cold stress, which is likely due to overlapping adaptations for coping with winter desiccation. Populations from regions with dry summers had increased drought hardiness but reduced cold hardiness, suggesting a trade-off in tolerance mechanisms. 4. Our findings highlight the necessity to look beyond bivariate trait–climate relationships and instead consider multiple traits and climate variables to effectively model and manage for the impacts of climate change on widespread species.

Personality Correlates of Midlife Cardiometabolic Risk: The Explanatory Role of Higher-Order Factors of the Five Factor Model

PubMed Central

Dermody, Sarah S.; Wright, Aidan G.C.; Cheong, JeeWon; Miller, Karissa G.; Muldoon, Matthew F.; Flory, Janine D.; Gianaros, Peter J.; Marsland, Anna L.; Manuck, Stephen B.

2015-01-01

Objective Varying associations are reported between Five Factor Model (FFM) personality traits and cardiovascular diseaabolic risk within a hierarchical model of personality that posits higherse risk. Here, we further examine dispositional correlates of cardiomet -order traits of Stability (shared variance of Agreeableness, Conscientiousness, inverse Neuroticism) and Plasticity (Extraversion, Openness), and test hypothesized mediation via biological and behavioral factors. Method In an observational study of 856 community volunteers aged 30–54 years (46% male, 86% Caucasian), latent variable FFM traits (using multiple-informant reports) and aggregated cardiometabolic risk (indicators: insulin resistance, dyslipidemia, blood pressure, adiposity) were estimated using confirmatory factor analysis (CFA). The cardiometabolic factor was regressed on each personality factor or higher-order trait. Cross-sectional indirect effects via systemic inflammation, cardiac autonomic control, and physical activity were tested. Results CFA models confirmed the Stability “meta-trait,” but not Plasticity. Lower Stability was associated with heightened cardiometabolic risk. This association was accounted for by inflammation, autonomic function, and physical activity. Among FFM traits, only Openness was associated with risk over and above Stability and, unlike Stablity, this relationship was unexplained by the intervening variables. Conclusions A Stability meta-trait covaries with midlife cardiometabolic risk, and this association is accounted for by three candidate biological and behavioral factors. PMID:26249259

Personality traits predict perceived health-related quality of life in persons with multiple sclerosis.

PubMed

Zarbo, Ignazio Roberto; Minacapelli, Eleonora; Falautano, Monica; Demontis, Silvia; Carpentras, Giovanni; Pugliatti, Maura

2016-04-01

Personality traits can affect health-related quality of life (HRQoL) in different disorders. In multiple sclerosis (MS), personality traits can determine patients' willingness to take on more risky treatment options, predispose to neuropsychiatric symptoms and affect coping strategies. We investigated the role of personality traits as possible predictors of HRQoL in a large cohort of persons with MS (PwMS). In total, 253 consecutively recruited PwMS were screened for intellectual deficits with Raven Colour Progressive Matrices (RCPM), state anxiety with STAI-X1 and major depression on a clinical basis. PwMS' self-perceived mental and physical health status was measured with the 36-Item Short Form Health Survey (SF-36), and the personality profile with the Eysenck Personality Questionnaire (EPQ-R). The correlation between HRQoL and personality traits was investigated by means of analysis of variance, adjusting for possible confounders. Of the 253 MS patients, 195 (F:M=2.75), aged 41.7±10.2 years were included in the analysis. The variance of SF-36 mental and physical composite score was largely explained by extraversion and neuroticism. Our data confirm that PwMS' HRQoL is largely influenced by personality traits, which may therefore act as predictors of perceived quality of life and should be included in clinical and experimental settings focusing on HRQoL. © The Author(s), 2015.

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

Traits, properties, and performance: how woody plants combine hydraulic and mechanical functions in a cell, tissue, or whole plant.

PubMed

Lachenbruch, Barbara; McCulloh, Katherine A

2014-12-01

This review presents a framework for evaluating how cells, tissues, organs, and whole plants perform both hydraulic and mechanical functions. The morphological alterations that affect dual functionality are varied: individual cells can have altered morphology; tissues can have altered partitioning to functions or altered cell alignment; and organs and whole plants can differ in their allocation to different tissues, or in the geometric distribution of the tissues they have. A hierarchical model emphasizes that morphological traits influence the hydraulic or mechanical properties; the properties, combined with the plant unit's environment, then influence the performance of that plant unit. As a special case, we discuss the mechanisms by which the proxy property wood density has strong correlations to performance but without direct causality. Traits and properties influence multiple aspects of performance, and there can be mutual compensations such that similar performance occurs. This compensation emphasizes that natural selection acts on, and a plant's viability is determined by, its performance, rather than its contributing traits and properties. Continued research on the relationships among traits, and on their effects on multiple aspects of performance, will help us better predict, manage, and select plant material for success under multiple stresses in the future. © 2014 The Authors. New Phytologist © 2014 New Phytologist Trust.

Regression and Data Mining Methods for Analyses of Multiple Rare Variants in the Genetic Analysis Workshop 17 Mini-Exome Data

PubMed Central

Bailey-Wilson, Joan E.; Brennan, Jennifer S.; Bull, Shelley B; Culverhouse, Robert; Kim, Yoonhee; Jiang, Yuan; Jung, Jeesun; Li, Qing; Lamina, Claudia; Liu, Ying; Mägi, Reedik; Niu, Yue S.; Simpson, Claire L.; Wang, Libo; Yilmaz, Yildiz E.; Zhang, Heping; Zhang, Zhaogong

2012-01-01

Group 14 of Genetic Analysis Workshop 17 examined several issues related to analysis of complex traits using DNA sequence data. These issues included novel methods for analyzing rare genetic variants in an aggregated manner (often termed collapsing rare variants), evaluation of various study designs to increase power to detect effects of rare variants, and the use of machine learning approaches to model highly complex heterogeneous traits. Various published and novel methods for analyzing traits with extreme locus and allelic heterogeneity were applied to the simulated quantitative and disease phenotypes. Overall, we conclude that power is (as expected) dependent on locus-specific heritability or contribution to disease risk, large samples will be required to detect rare causal variants with small effect sizes, extreme phenotype sampling designs may increase power for smaller laboratory costs, methods that allow joint analysis of multiple variants per gene or pathway are more powerful in general than analyses of individual rare variants, population-specific analyses can be optimal when different subpopulations harbor private causal mutations, and machine learning methods may be useful for selecting subsets of predictors for follow-up in the presence of extreme locus heterogeneity and large numbers of potential predictors. PMID:22128066

Association between Personality Traits and Sleep Quality in Young Korean Women

PubMed Central

Kim, Han-Na; Cho, Juhee; Chang, Yoosoo; Ryu, Seungho

2015-01-01

Personality is a trait that affects behavior and lifestyle, and sleep quality is an important component of a healthy life. We analyzed the association between personality traits and sleep quality in a cross-section of 1,406 young women (from 18 to 40 years of age) who were not reporting clinically meaningful depression symptoms. Surveys were carried out from December 2011 to February 2012, using the Revised NEO Personality Inventory and the Pittsburgh Sleep Quality Index (PSQI). All analyses were adjusted for demographic and behavioral variables. We considered beta weights, structure coefficients, unique effects, and common effects when evaluating the importance of sleep quality predictors in multiple linear regression models. Neuroticism was the most important contributor to PSQI global scores in the multiple regression models. By contrast, despite being strongly correlated with sleep quality, conscientiousness had a near-zero beta weight in linear regression models, because most variance was shared with other personality traits. However, conscientiousness was the most noteworthy predictor of poor sleep quality status (PSQI≥6) in logistic regression models and individuals high in conscientiousness were least likely to have poor sleep quality, which is consistent with an OR of 0.813, with conscientiousness being protective against poor sleep quality. Personality may be a factor in poor sleep quality and should be considered in sleep interventions targeting young women. PMID:26030141

Methods and consequences of including feed intake and efficiency in genetic selection for multiple-trait merit.

PubMed

Barwick, Stephen A; Henzell, Anthony L; Walmsley, Brad J; Johnston, David J; Banks, Robert G

2018-05-04

Methods are presented for including feed intake and efficiency in genetic selection for multiple-trait merit when commercial production is from any combination of pasture or concentrates. Consequences for the production system and for individual animals are illustrated with a beef cattle example. Residual feed intake at pasture (RFI-p), residual feed intake in the feedlot (RFI-f), and cow condition score are additional traits of the breeding objective. Feed requirement change is costed in the economic values of other objective traits. Selection responses are examined when feed costs are ignored, partially or fully included in the breeding objective, and when net feed intake (NFI) EBVs are added to the index. When all feed cost was included and NFI EBVs were in the index, selection (with selection intensity, i = 1) increased production system $ net return by 6.0%, $ per unit of product by 5.2%, $ per unit of feed by 6.6%, total product by 0.7% and product per unit of feed by 1.3%. There was little change in production system total feed. When feed cost was ignored, selection decreased production system $ net return, $ per unit of product, and $ per unit of feed. At the individual trait level, when feed was fully included there were increases in weaning weight-direct (0.8 kg), feedlot entry weight (1.4 kg), dressing % (0.04%), carcass meat % (0.36%), carcase fat depth (0.12 mm), carcass marbling score (0.02 score), cow condition score (0.01 score), calving ease-direct (0.97%), calving ease-maternal (0.22%) and cow weaning rate (1.3%), and decreases in weaning weight-maternal (-0.9 kg), RFI-p (-0.09 kg DM/d), RFI-f (-0.11 kg DM/d), sale weight (-1.6 kg) and cow weight (-8.7 kg). Gains were evident over a range of feed price. Selection for $ net return also increased $ net return per unit of feed, suggesting that $ net return per unit area would increase in grazing industries. Feed cost for trait change was the source of a major genotype × environment interaction affecting animal rankings. Where industry production environments vary, and feed cost for trait change varies with the environment, we recommend that industry indexes be derived for more than one level of feed cost. Cow condition score did not decline while biological and economic efficiency of the production system and individual animal were improving, suggesting that efficiency can be improved under multiple-trait selection without compromising breeding cow welfare.

Humanizing Outgroups Through Multiple Categorization

PubMed Central

Prati, Francesca; Crisp, Richard J.; Meleady, Rose; Rubini, Monica

2016-01-01

In three studies, we examined the impact of multiple categorization on intergroup dehumanization. Study 1 showed that perceiving members of a rival university along multiple versus simple categorical dimensions enhanced the tendency to attribute human traits to this group. Study 2 showed that multiple versus simple categorization of immigrants increased the attribution of uniquely human emotions to them. This effect was explained by the sequential mediation of increased individuation of the outgroup and reduced outgroup threat. Study 3 replicated this sequential mediation model and introduced a novel way of measuring humanization in which participants generated attributes corresponding to the outgroup in a free response format. Participants generated more uniquely human traits in the multiple versus simple categorization conditions. We discuss the theoretical implications of these findings and consider their role in informing and improving efforts to ameliorate contemporary forms of intergroup discrimination. PMID:26984016

Testing Genetic Pleiotropy with GWAS Summary Statistics for Marginal and Conditional Analyses.

PubMed

Deng, Yangqing; Pan, Wei

2017-12-01

There is growing interest in testing genetic pleiotropy, which is when a single genetic variant influences multiple traits. Several methods have been proposed; however, these methods have some limitations. First, all the proposed methods are based on the use of individual-level genotype and phenotype data; in contrast, for logistical, and other, reasons, summary statistics of univariate SNP-trait associations are typically only available based on meta- or mega-analyzed large genome-wide association study (GWAS) data. Second, existing tests are based on marginal pleiotropy, which cannot distinguish between direct and indirect associations of a single genetic variant with multiple traits due to correlations among the traits. Hence, it is useful to consider conditional analysis, in which a subset of traits is adjusted for another subset of traits. For example, in spite of substantial lowering of low-density lipoprotein cholesterol (LDL) with statin therapy, some patients still maintain high residual cardiovascular risk, and, for these patients, it might be helpful to reduce their triglyceride (TG) level. For this purpose, in order to identify new therapeutic targets, it would be useful to identify genetic variants with pleiotropic effects on LDL and TG after adjusting the latter for LDL; otherwise, a pleiotropic effect of a genetic variant detected by a marginal model could simply be due to its association with LDL only, given the well-known correlation between the two types of lipids. Here, we develop a new pleiotropy testing procedure based only on GWAS summary statistics that can be applied for both marginal analysis and conditional analysis. Although the main technical development is based on published union-intersection testing methods, care is needed in specifying conditional models to avoid invalid statistical estimation and inference. In addition to the previously used likelihood ratio test, we also propose using generalized estimating equations under the working independence model for robust inference. We provide numerical examples based on both simulated and real data, including two large lipid GWAS summary association datasets based on ∼100,000 and ∼189,000 samples, respectively, to demonstrate the difference between marginal and conditional analyses, as well as the effectiveness of our new approach. Copyright © 2017 by the Genetics Society of America.

When should we expect early bursts of trait evolution in comparative data? Predictions from an evolutionary food web model.

PubMed

Ingram, T; Harmon, L J; Shurin, J B

2012-09-01

Conceptual models of adaptive radiation predict that competitive interactions among species will result in an early burst of speciation and trait evolution followed by a slowdown in diversification rates. Empirical studies often show early accumulation of lineages in phylogenetic trees, but usually fail to detect early bursts of phenotypic evolution. We use an evolutionary simulation model to assemble food webs through adaptive radiation, and examine patterns in the resulting phylogenetic trees and species' traits (body size and trophic position). We find that when foraging trade-offs result in food webs where all species occupy integer trophic levels, lineage diversity and trait disparity are concentrated early in the tree, consistent with the early burst model. In contrast, in food webs in which many omnivorous species feed at multiple trophic levels, high levels of turnover of species' identities and traits tend to eliminate the early burst signal. These results suggest testable predictions about how the niche structure of ecological communities may be reflected by macroevolutionary patterns. © 2012 The Authors. Journal of Evolutionary Biology © 2012 European Society For Evolutionary Biology.

Evaluation of an ensemble of genetic models for prediction of a quantitative trait.

PubMed

Milton, Jacqueline N; Steinberg, Martin H; Sebastiani, Paola

2014-01-01

Many genetic markers have been shown to be associated with common quantitative traits in genome-wide association studies. Typically these associated genetic markers have small to modest effect sizes and individually they explain only a small amount of the variability of the phenotype. In order to build a genetic prediction model without fitting a multiple linear regression model with possibly hundreds of genetic markers as predictors, researchers often summarize the joint effect of risk alleles into a genetic score that is used as a covariate in the genetic prediction model. However, the prediction accuracy can be highly variable and selecting the optimal number of markers to be included in the genetic score is challenging. In this manuscript we present a strategy to build an ensemble of genetic prediction models from data and we show that the ensemble-based method makes the challenge of choosing the number of genetic markers more amenable. Using simulated data with varying heritability and number of genetic markers, we compare the predictive accuracy and inclusion of true positive and false positive markers of a single genetic prediction model and our proposed ensemble method. The results show that the ensemble of genetic models tends to include a larger number of genetic variants than a single genetic model and it is more likely to include all of the true genetic markers. This increased sensitivity is obtained at the price of a lower specificity that appears to minimally affect the predictive accuracy of the ensemble.

Specific personality traits and general personality dysfunction as predictors of the presence and severity of personality disorders in a clinical sample.

PubMed

Berghuis, Han; Kamphuis, Jan H; Verheul, Roel

2014-01-01

This study examined the associations of specific personality traits and general personality dysfunction in relation to the presence and severity of Diagnostic and Statistical Manual of Mental Disorders (4th ed. [DSM-IV]; American Psychiatric Association, 1994) personality disorders in a Dutch clinical sample. Two widely used measures of specific personality traits were selected, the Revised NEO Personality Inventory as a measure of normal personality traits, and the Dimensional Assessment of Personality Pathology-Basic Questionnaire as a measure of pathological traits. In addition, 2 promising measures of personality dysfunction were selected, the General Assessment of Personality Disorder and the Severity Indices of Personality Problems. Theoretically predicted associations were found between the measures, and all measures predicted the presence and severity of DSM-IV personality disorders. The combination of general personality dysfunction models and personality traits models provided incremental information about the presence and severity of personality disorders, suggesting that an integrative approach of multiple perspectives might serve comprehensive assessment of personality disorders.

Maternal Factors Predicting Cognitive and Behavioral Characteristics of Children with Fetal Alcohol Spectrum Disorders

PubMed Central

May, Philip A.; Tabachnick, Barbara G.; Gossage, J. Phillip; Kalberg, Wendy O.; Marais, Anna-Susan; Robinson, Luther K.; Manning, Melanie A.; Blankenship, Jason; Buckley, David; Hoyme, H. Eugene; Adnams, Colleen M.

2013-01-01

Objective To provide an analysis of multiple predictors of cognitive and behavioral traits for children with fetal alcohol spectrum disorders (FASD). Method Multivariate correlation techniques were employed with maternal and child data from epidemiologic studies in a community in South Africa. Data on 561 first grade children with fetal alcohol syndrome (FAS), partial FAS (PFAS), and not FASD and their mothers were analyzed by grouping 19 maternal variables into categories (physical, demographic, childbearing, and drinking) and employed in structural equation models (SEM) to assess correlates of child intelligence (verbal and non-verbal) and behavior. Results A first SEM utilizing only seven maternal alcohol use variables to predict cognitive/behavioral traits was statistically significant (B = 3.10, p < .05), but explained only 17.3% of the variance. The second model incorporated multiple maternal variables and was statistically significant explaining 55.3% of the variance. Significantly correlated with low intelligence and problem behavior were demographic (B = 3.83, p < .05) (low maternal education, low socioeconomic status (SES), and rural residence) and maternal physical characteristics (B = 2.70, p < .05) (short stature, small head circumference, and low weight). Childbearing history and alcohol use composites were not statistically significant in the final complex model, and were overpowered by SES and maternal physical traits. Conclusions While other analytic techniques have amply demonstrated the negative effects of maternal drinking on intelligence and behavior, this highly-controlled analysis of multiple maternal influences reveals that maternal demographics and physical traits make a significant enabling or disabling contribution to child functioning in FASD. PMID:23751886

The correlations and sequence of plant stomatal, hydraulic, and wilting responses to drought

PubMed Central

Bartlett, Megan K.; Klein, Tamir; Jansen, Steven; Choat, Brendan; Sack, Lawren

2016-01-01

Climate change is expected to exacerbate drought for many plants, making drought tolerance a key driver of species and ecosystem responses. Plant drought tolerance is determined by multiple traits, but the relationships among traits, either within individual plants or across species, have not been evaluated for general patterns across plant diversity. We synthesized the published data for stomatal closure, wilting, declines in hydraulic conductivity in the leaves, stems, and roots, and plant mortality for 262 woody angiosperm and 48 gymnosperm species. We evaluated the correlations among the drought tolerance traits across species, and the general sequence of water potential thresholds for these traits within individual plants. The trait correlations across species provide a framework for predicting plant responses to a wide range of water stress from one or two sampled traits, increasing the ability to rapidly characterize drought tolerance across diverse species. Analyzing these correlations also identified correlations among the leaf and stem hydraulic traits and the wilting point, or turgor loss point, beyond those expected from shared ancestry or independent associations with water stress alone. Further, on average, the angiosperm species generally exhibited a sequence of drought tolerance traits that is expected to limit severe tissue damage during drought, such as wilting and substantial stem embolism. This synthesis of the relationships among the drought tolerance traits provides crucial, empirically supported insight into representing variation in multiple traits in models of plant and ecosystem responses to drought. PMID:27807136

The correlations and sequence of plant stomatal, hydraulic, and wilting responses to drought.

PubMed

Bartlett, Megan K; Klein, Tamir; Jansen, Steven; Choat, Brendan; Sack, Lawren

2016-11-15

Climate change is expected to exacerbate drought for many plants, making drought tolerance a key driver of species and ecosystem responses. Plant drought tolerance is determined by multiple traits, but the relationships among traits, either within individual plants or across species, have not been evaluated for general patterns across plant diversity. We synthesized the published data for stomatal closure, wilting, declines in hydraulic conductivity in the leaves, stems, and roots, and plant mortality for 262 woody angiosperm and 48 gymnosperm species. We evaluated the correlations among the drought tolerance traits across species, and the general sequence of water potential thresholds for these traits within individual plants. The trait correlations across species provide a framework for predicting plant responses to a wide range of water stress from one or two sampled traits, increasing the ability to rapidly characterize drought tolerance across diverse species. Analyzing these correlations also identified correlations among the leaf and stem hydraulic traits and the wilting point, or turgor loss point, beyond those expected from shared ancestry or independent associations with water stress alone. Further, on average, the angiosperm species generally exhibited a sequence of drought tolerance traits that is expected to limit severe tissue damage during drought, such as wilting and substantial stem embolism. This synthesis of the relationships among the drought tolerance traits provides crucial, empirically supported insight into representing variation in multiple traits in models of plant and ecosystem responses to drought.

Intimate partner violence and anxiety disorders in pregnancy: the importance of vocational training of the nursing staff in facing them1

PubMed Central

Fonseca-Machado, Mariana de Oliveira; Monteiro, Juliana Cristina dos Santos; Haas, Vanderlei José; Abrão, Ana Cristina Freitas de Vilhena; Gomes-Sponholz, Flávia

2015-01-01

Objective: to identify the relationship between posttraumatic stress disorder, trait and state anxiety, and intimate partner violence during pregnancy. Method: observational, cross-sectional study developed with 358 pregnant women. The Posttraumatic Stress Disorder Checklist - Civilian Version was used, as well as the State-Trait Anxiety Inventory and an adapted version of the instrument used in the World Health Organization Multi-country Study on Women's Health and Domestic Violence. Results: after adjusting to the multiple logistic regression model, intimate partner violence, occurred during pregnancy, was associated with the indication of posttraumatic stress disorder. The adjusted multiple linear regression models showed that the victims of violence, in the current pregnancy, had higher symptom scores of trait and state anxiety than non-victims. Conclusion: recognizing the intimate partner violence as a clinically relevant and identifiable risk factor for the occurrence of anxiety disorders during pregnancy can be a first step in the prevention thereof. PMID:26487135

Disruptions in Emotion Regulation as a Mechanism Linking Community Violence Exposure to Adolescent Internalizing Problems

PubMed Central

Heleniak, Charlotte; King, Kevin M.; Monahan, Kathryn C.; McLaughlin, Katie A.

2017-01-01

Although community violence is an established risk factor for youth aggression, less research has examined its relation with internalizing psychopathology. This study examined associations of community violence exposure with internalizing symptoms, and state and trait emotion dysregulation as mechanisms underlying these associations, in 287 adolescents aged 16–17 (45.6% male; 40.8% White). Community violence exposure was associated with internalizing symptoms, negative affect during peer evaluation, trait emotional reactivity, and infrequent problem solving. Multiple emotion dysregulation indices were also associated with internalizing symptoms. In simultaneous multiple mediator models, indirect effects of community violence on internalizing problems were significantly explained by state and trait emotion dysregulation. Findings implicate emotion dysregulation as one mechanism linking community violence exposure to adolescent internalizing symptoms. PMID:28646545

Influence of Family Communication Structure and Vanity Trait on Consumption Behavior: A Case Study of Adolescent Students in Taiwan

ERIC Educational Resources Information Center

Chang, Wei-Lung; Liu, Hsiang-Te; Lin, Tai-An; Wen, Yung-Sung

2008-01-01

The purpose of this research was to study the relationship between family communication structure, vanity trait, and related consumption behavior. The study used an empirical method with adolescent students from the northern part of Taiwan as the subjects. Multiple statistical methods and the SEM model were used for testing the hypotheses. The…

Genetic analysis of milk production traits of Tunisian Holsteins using random regression test-day model with Legendre polynomials

PubMed Central

2018-01-01

Objective The objective of this study was to estimate genetic parameters of milk, fat, and protein yields within and across lactations in Tunisian Holsteins using a random regression test-day (TD) model. Methods A random regression multiple trait multiple lactation TD model was used to estimate genetic parameters in the Tunisian dairy cattle population. Data were TD yields of milk, fat, and protein from the first three lactations. Random regressions were modeled with third-order Legendre polynomials for the additive genetic, and permanent environment effects. Heritabilities, and genetic correlations were estimated by Bayesian techniques using the Gibbs sampler. Results All variance components tended to be high in the beginning and the end of lactations. Additive genetic variances for milk, fat, and protein yields were the lowest and were the least variable compared to permanent variances. Heritability values tended to increase with parity. Estimates of heritabilities for 305-d yield-traits were low to moderate, 0.14 to 0.2, 0.12 to 0.17, and 0.13 to 0.18 for milk, fat, and protein yields, respectively. Within-parity, genetic correlations among traits were up to 0.74. Genetic correlations among lactations for the yield traits were relatively high and ranged from 0.78±0.01 to 0.82±0.03, between the first and second parities, from 0.73±0.03 to 0.8±0.04 between the first and third parities, and from 0.82±0.02 to 0.84±0.04 between the second and third parities. Conclusion These results are comparable to previously reported estimates on the same population, indicating that the adoption of a random regression TD model as the official genetic evaluation for production traits in Tunisia, as developed by most Interbull countries, is possible in the Tunisian Holsteins. PMID:28823122

Genetic analysis of milk production traits of Tunisian Holsteins using random regression test-day model with Legendre polynomials.

PubMed

Ben Zaabza, Hafedh; Ben Gara, Abderrahmen; Rekik, Boulbaba

2018-05-01

The objective of this study was to estimate genetic parameters of milk, fat, and protein yields within and across lactations in Tunisian Holsteins using a random regression test-day (TD) model. A random regression multiple trait multiple lactation TD model was used to estimate genetic parameters in the Tunisian dairy cattle population. Data were TD yields of milk, fat, and protein from the first three lactations. Random regressions were modeled with third-order Legendre polynomials for the additive genetic, and permanent environment effects. Heritabilities, and genetic correlations were estimated by Bayesian techniques using the Gibbs sampler. All variance components tended to be high in the beginning and the end of lactations. Additive genetic variances for milk, fat, and protein yields were the lowest and were the least variable compared to permanent variances. Heritability values tended to increase with parity. Estimates of heritabilities for 305-d yield-traits were low to moderate, 0.14 to 0.2, 0.12 to 0.17, and 0.13 to 0.18 for milk, fat, and protein yields, respectively. Within-parity, genetic correlations among traits were up to 0.74. Genetic correlations among lactations for the yield traits were relatively high and ranged from 0.78±0.01 to 0.82±0.03, between the first and second parities, from 0.73±0.03 to 0.8±0.04 between the first and third parities, and from 0.82±0.02 to 0.84±0.04 between the second and third parities. These results are comparable to previously reported estimates on the same population, indicating that the adoption of a random regression TD model as the official genetic evaluation for production traits in Tunisia, as developed by most Interbull countries, is possible in the Tunisian Holsteins.

[Analysis of genetic models and gene effects on main agronomy characters in rapeseed].

PubMed

Li, J; Qiu, J; Tang, Z; Shen, L

1992-01-01

According to four different genetic models, the genetic patterns of 8 agronomy traits were analysed by using the data of 24 generations which included positive and negative cross of 81008 x Tower, both of the varieties are of good quality. The results showed that none of 8 characters could fit in with additive-dominance models. Epistasis was found in all of these characters, and it has significant effect on generation means. Seed weight/plant and some other main yield characters are controlled by duplicate interaction genes. The interaction between triple genes or multiple genes needs to be utilized in yield heterosis.

Pathways to Identity: Aiding Law Enforcement in Identification Tasks With Visual Analytics

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

Bruce, Joseph R.; Scholtz, Jean; Hodges, Duncan

The nature of identity has changed dramatically in recent years, and has grown in complexity. Identities are defined in multiple domains: biological and psychological elements strongly contribute, but also biographical and cyber elements are necessary to complete the picture. Law enforcement is beginning to adjust to these changes, recognizing its importance in criminal justice. The SuperIdentity project seeks to aid law enforcement officials in their identification tasks through research of techniques for discovering identity traits, generation of statistical models of identity and analysis of identity traits through visualization. We present use cases compiled through user interviews in multiple fields, includingmore » law enforcement, as well as the modeling and visualization tools design to aid in those use cases.« less

Pathways to Identity. Using Visualization to Aid Law Enforcement in Identification Tasks

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

Bruce, Joseph R.; Scholtz, Jean; Hodges, Duncan

The nature of identity has changed dramatically in recent years and has grown in complexity. Identities are defined in multiple domains: biological and psychological elements strongly contribute, but biographical and cyber elements also are necessary to complete the picture. Law enforcement is beginning to adjust to these changes, recognizing identity’s importance in criminal justice. The SuperIdentity project seeks to aid law enforcement officials in their identification tasks through research of techniques for discovering identity traits, generation of statistical models of identity and analysis of identity traits through visualization. We present use cases compiled through user interviews in multiple fields, includingmore » law enforcement, and describe the modeling and visualization tools design to aid in those use cases.« less

Longitudinal analysis of large social networks: Estimating the effect of health traits on changes in friendship ties

PubMed Central

O'Malley, A James; Christakis, Nicholas A

2011-01-01

We develop novel mixed effects models to examine the role of health traits on the status of peoples' close friendship nominations in the Framingham Heart Study. The health traits considered are both mutable (body mass index (BMI), smoking, blood pressure, body proportion, muscularity, and depression) and, for comparison, basically immutable (height, birth order, personality type, only child, and handedness); and the traits have varying degrees of observability. We test the hypotheses that existing ties (i.e. close friendship nominations) are more likely to dissolve between people with dissimilar (mutable and observable) health traits whereas new ties are more likely to form between those with similar (mutable and observable) traits while controlling for persons' age, gender, geographic separation, and education. The mixed effects models contain random effects for both the nominator (ego) and nominated (alter) persons in a tie to account for the fact that people were involved in multiple relationships and contributed observations at multiple exams. Results for BMI support the hypotheses that people of similar BMI are less likely to dissolve existing ties and more likely to form ties, while smoker to non-smoker ties were the least likely to dissolve and smoker to smoker ties were the most likely to form. We also validated previously known findings regarding homophily on age and gender, and found evidence that homophily also depends upon geographic separation. Copyright © 2011 John Wiley & Sons, Ltd. PMID:21287589

Longitudinal analysis of large social networks: estimating the effect of health traits on changes in friendship ties.

PubMed

O'Malley, A James; Christakis, Nicholas A

2011-04-30

We develop novel mixed effects models to examine the role of health traits on the status of peoples' close friendship nominations in the Framingham Heart Study. The health traits considered are both mutable (body mass index (BMI), smoking, blood pressure, body proportion, muscularity, and depression) and, for comparison, basically immutable (height, birth order, personality type, only child, and handedness); and the traits have varying degrees of observability. We test the hypotheses that existing ties (i.e. close friendship nominations) are more likely to dissolve between people with dissimilar (mutable and observable) health traits whereas new ties are more likely to form between those with similar (mutable and observable) traits while controlling for persons' age, gender, geographic separation, and education. The mixed effects models contain random effects for both the nominator (ego) and nominated (alter) persons in a tie to account for the fact that people were involved in multiple relationships and contributed observations at multiple exams. Results for BMI support the hypotheses that people of similar BMI are less likely to dissolve existing ties and more likely to form ties, while smoker to non-smoker ties were the least likely to dissolve and smoker to smoker ties were the most likely to form. We also validated previously known findings regarding homophily on age and gender, and found evidence that homophily also depends upon geographic separation. Copyright © 2011 John Wiley & Sons, Ltd.

Genome-Assisted Prediction of Quantitative Traits Using the R Package sommer.

PubMed

Covarrubias-Pazaran, Giovanny

2016-01-01

Most traits of agronomic importance are quantitative in nature, and genetic markers have been used for decades to dissect such traits. Recently, genomic selection has earned attention as next generation sequencing technologies became feasible for major and minor crops. Mixed models have become a key tool for fitting genomic selection models, but most current genomic selection software can only include a single variance component other than the error, making hybrid prediction using additive, dominance and epistatic effects unfeasible for species displaying heterotic effects. Moreover, Likelihood-based software for fitting mixed models with multiple random effects that allows the user to specify the variance-covariance structure of random effects has not been fully exploited. A new open-source R package called sommer is presented to facilitate the use of mixed models for genomic selection and hybrid prediction purposes using more than one variance component and allowing specification of covariance structures. The use of sommer for genomic prediction is demonstrated through several examples using maize and wheat genotypic and phenotypic data. At its core, the program contains three algorithms for estimating variance components: Average information (AI), Expectation-Maximization (EM) and Efficient Mixed Model Association (EMMA). Kernels for calculating the additive, dominance and epistatic relationship matrices are included, along with other useful functions for genomic analysis. Results from sommer were comparable to other software, but the analysis was faster than Bayesian counterparts in the magnitude of hours to days. In addition, ability to deal with missing data, combined with greater flexibility and speed than other REML-based software was achieved by putting together some of the most efficient algorithms to fit models in a gentle environment such as R.

Cross-Informant Symptoms from CBCL, TRF, and YSR: Trait and Method Variance in a Normative Sample of Russian Youths

PubMed Central

Grigorenko, Elena L.; Geiser, Christian; Slobodskaya, Helena R.; Francis, David J.

2015-01-01

A large community-based sample of Russian youths (n = 847, mean age = 13.17, sd = 2.51) was assessed with the Child Behavior Checklist (mothers and fathers separately), Teacher’s Report Form, and Youth Self-Report. The multiple indicator-version of the Correlated Trait-Correlated (Method Minus One) [CT-C(M-1)] model was applied to analyze (1) the convergent and divergent validity of these instruments in Russia, (2) the degree of trait-specificity of rater biases, and (3) potential predictors of rater-specific effects. As expected, based on the published results from different countries and in different languages, the convergent validity of the instruments was rather high between mother and father reports, but rather low for parent, teacher, and self reports. For self- and teacher reports, rater-specific effects were related to age and gender of the children for some traits. These results, once again, attest to the importance of incorporating information from multiple observers when psychopathological traits are evaluated in children and adolescents. PMID:21133549

Multitrait, Random Regression, or Simple Repeatability Model in High-Throughput Phenotyping Data Improve Genomic Prediction for Wheat Grain Yield.

PubMed

Sun, Jin; Rutkoski, Jessica E; Poland, Jesse A; Crossa, José; Jannink, Jean-Luc; Sorrells, Mark E

2017-07-01

High-throughput phenotyping (HTP) platforms can be used to measure traits that are genetically correlated with wheat ( L.) grain yield across time. Incorporating such secondary traits in the multivariate pedigree and genomic prediction models would be desirable to improve indirect selection for grain yield. In this study, we evaluated three statistical models, simple repeatability (SR), multitrait (MT), and random regression (RR), for the longitudinal data of secondary traits and compared the impact of the proposed models for secondary traits on their predictive abilities for grain yield. Grain yield and secondary traits, canopy temperature (CT) and normalized difference vegetation index (NDVI), were collected in five diverse environments for 557 wheat lines with available pedigree and genomic information. A two-stage analysis was applied for pedigree and genomic selection (GS). First, secondary traits were fitted by SR, MT, or RR models, separately, within each environment. Then, best linear unbiased predictions (BLUPs) of secondary traits from the above models were used in the multivariate prediction models to compare predictive abilities for grain yield. Predictive ability was substantially improved by 70%, on average, from multivariate pedigree and genomic models when including secondary traits in both training and test populations. Additionally, (i) predictive abilities slightly varied for MT, RR, or SR models in this data set, (ii) results indicated that including BLUPs of secondary traits from the MT model was the best in severe drought, and (iii) the RR model was slightly better than SR and MT models under drought environment. Copyright © 2017 Crop Science Society of America.

Trait-based Modeling of Larval Dispersal in the Gulf of Maine

NASA Astrophysics Data System (ADS)

Jones, B.; Richardson, D.; Follows, M. J.; Hill, C. N.; Solow, A.; Ji, R.

2016-02-01

Population connectivity of marine species is the inter-generational movement of individuals among geographically separated subpopulations and is a crucial determinant of population dynamics, community structure, and optimal management strategies. For many marine species, population connectivity is largely determined by the dispersal patterns that emerge from a pelagic larval phase. These dispersal patterns are a result of interactions between the physical environment, adult spawning strategy, and larval ecology. Using a generalized trait-based model that represents the adult spawning strategy as a distribution of larval releases in time and space and the larval trait space with the pelagic larval duration, vertical swimming behavior, and settlement habitat preferences, we simulate dispersal patterns in the Gulf of Maine and surrounding regions. We implement this model as an individual-based simulation that tracks Lagrangian particles on a graphics processing unit as they move through hourly archived output from the Finite-Volume Community Ocean Model. The particles are released between the Hudson Canyon and Nova Scotia and the release distributions are determined using a novel method that minimizes the number of simulations required to achieve a predetermined level of precision for the connectivity matrices. The simulated larvae have a variable pelagic larval duration and exhibit multiple forms of dynamic depth-keeping behavior. We describe how these traits influence the dispersal trajectories and connectivity patterns among regions in the northwest Atlantic. Our description includes the probability of successful recruitment, patchiness of larval distributions, and the variability of these properties in time and space under a variety of larval dispersal strategies.

Quantitative Trait Loci for Light Sensitivity, Body Weight, Body Size, and Morphological Eye Parameters in the Bumblebee, Bombus terrestris.

PubMed

Maebe, Kevin; Meeus, Ivan; De Riek, Jan; Smagghe, Guy

2015-01-01

Bumblebees such as Bombus terrestris are essential pollinators in natural and managed ecosystems. In addition, this species is intensively used in agriculture for its pollination services, for instance in tomato and pepper greenhouses. Here we performed a quantitative trait loci (QTL) analysis on B. terrestris using 136 microsatellite DNA markers to identify genes linked with 20 traits including light sensitivity, body size and mass, and eye and hind leg measures. By composite interval mapping (IM), we found 83 and 34 suggestive QTLs for 19 of the 20 traits at the linkage group wide significance levels of p = 0.05 and 0.01, respectively. Furthermore, we also found five significant QTLs at the genome wide significant level of p = 0.05. Individual QTLs accounted for 7.5-53.3% of the phenotypic variation. For 15 traits, at least one QTL was confirmed with multiple QTL model mapping. Multivariate principal components analysis confirmed 11 univariate suggestive QTLs but revealed three suggestive QTLs not identified by the individual traits. We also identified several candidate genes linked with light sensitivity, in particular the Phosrestin-1-like gene is a primary candidate for its phototransduction function. In conclusion, we believe that the suggestive and significant QTLs, and markers identified here, can be of use in marker-assisted breeding to improve selection towards light sensitive bumblebees, and thus also the pollination service of bumblebees.

Genome-Wide Association Mapping for Kernel and Malting Quality Traits Using Historical European Barley Records

PubMed Central

Röder, Marion S.; van Eeuwijk, Fred

2014-01-01

Malting quality is an important trait in breeding barley (Hordeum vulgare L.). It requires elaborate, expensive phenotyping, which involves micro-malting experiments. Although there is abundant historical information available for different cultivars in different years and trials, that historical information is not often used in genetic analyses. This study aimed to exploit historical records to assist in identifying genomic regions that affect malting and kernel quality traits in barley. This genome-wide association study utilized information on grain yield and 18 quality traits accumulated over 25 years on 174 European spring and winter barley cultivars combined with diversity array technology markers. Marker-trait associations were tested with a mixed linear model. This model took into account the genetic relatedness between cultivars based on principal components scores obtained from marker information. We detected 140 marker-trait associations. Some of these associations confirmed previously known quantitative trait loci for malting quality (on chromosomes 1H, 2H, and 5H). Other associations were reported for the first time in this study. The genetic correlations between traits are discussed in relation to the chromosomal regions associated with the different traits. This approach is expected to be particularly useful when designing strategies for multiple trait improvements. PMID:25372869

Personality Traits Predict the Developmental Course of Externalizing: A Four-wave Longitudinal Study Spanning Age 17 to Age 29

PubMed Central

Walton, Kate E.; Krueger, Robert F.; Elkins, Irene; D’Accordo, Cassandra; McGue, Matt; Iacono, William G.

2016-01-01

Objective The objective of the present study was to determine whether and how personality predicts the developmental course of externalizing problems, including antisocial behavior and substance dependence. Method In a large population-based longitudinal study (N=1252), the 11 personality traits assessed by the Multidimensional Personality Questionnaire were measured at age 17, and DSM diagnoses of adult antisocial behavior, alcohol dependence, and drug dependence were obtained at ages 17, 20, 24, and 29. We fit a quadratic multiple indicator latent growth model where the three diagnoses loaded onto an externalizing factor. Results This model fit the data well, and externalizing increased until it started to decline at age 24. High aggression and low control were the most significant predictors of the development of externalizing, with aggression playing a significant role in the development of externalizing across the 12-year time span, and control predicting the development from age 17 to 24. Conclusions The findings highlight the importance of considering the developmental course of externalizing in the context of personality and suggest that the specific personality traits of aggression and control might be targeted in externalizing prevention and intervention programs. PMID:26808279

Personality Traits Predict the Developmental Course of Externalizing: A Four-Wave Longitudinal Study Spanning Age 17 to Age 29.

PubMed

Walton, Kate E; Krueger, Robert F; Elkins, Irene; D'Accordo, Cassandra; McGue, Matt; Iacono, William G

2017-06-01

The objective of the present study was to determine whether and how personality predicts the developmental course of externalizing problems, including antisocial behavior and substance dependence. In a large, population-based longitudinal study (N = 1,252), the 11 personality traits assessed by the Multidimensional Personality Questionnaire were measured at age 17, and DSM diagnoses of adult antisocial behavior, alcohol dependence, and drug dependence were obtained at ages 17, 20, 24, and 29. We fit a quadratic multiple indicator latent growth model where the three diagnoses loaded onto an externalizing factor. This model fit the data well, and externalizing increased until it started to decline at age 24. High aggression and low control were the most significant predictors of the development of externalizing, with aggression playing a significant role in the development of externalizing across the 12-year time span, and control predicting the development from age 17 to 24. The findings highlight the importance of considering the developmental course of externalizing in the context of personality and suggest that the specific personality traits of aggression and control might be targeted in externalizing prevention and intervention programs. © 2016 Wiley Periodicals, Inc.

Filling the gap in functional trait databases: use of ecological hypotheses to replace missing data.

PubMed

Taugourdeau, Simon; Villerd, Jean; Plantureux, Sylvain; Huguenin-Elie, Olivier; Amiaud, Bernard

2014-04-01

Functional trait databases are powerful tools in ecology, though most of them contain large amounts of missing values. The goal of this study was to test the effect of imputation methods on the evaluation of trait values at species level and on the subsequent calculation of functional diversity indices at community level using functional trait databases. Two simple imputation methods (average and median), two methods based on ecological hypotheses, and one multiple imputation method were tested using a large plant trait database, together with the influence of the percentage of missing data and differences between functional traits. At community level, the complete-case approach and three functional diversity indices calculated from grassland plant communities were included. At the species level, one of the methods based on ecological hypothesis was for all traits more accurate than imputation with average or median values, but the multiple imputation method was superior for most of the traits. The method based on functional proximity between species was the best method for traits with an unbalanced distribution, while the method based on the existence of relationships between traits was the best for traits with a balanced distribution. The ranking of the grassland communities for their functional diversity indices was not robust with the complete-case approach, even for low percentages of missing data. With the imputation methods based on ecological hypotheses, functional diversity indices could be computed with a maximum of 30% of missing data, without affecting the ranking between grassland communities. The multiple imputation method performed well, but not better than single imputation based on ecological hypothesis and adapted to the distribution of the trait values for the functional identity and range of the communities. Ecological studies using functional trait databases have to deal with missing data using imputation methods corresponding to their specific needs and making the most out of the information available in the databases. Within this framework, this study indicates the possibilities and limits of single imputation methods based on ecological hypothesis and concludes that they could be useful when studying the ranking of communities for their functional diversity indices.

Filling the gap in functional trait databases: use of ecological hypotheses to replace missing data

PubMed Central

Taugourdeau, Simon; Villerd, Jean; Plantureux, Sylvain; Huguenin-Elie, Olivier; Amiaud, Bernard

2014-01-01

Functional trait databases are powerful tools in ecology, though most of them contain large amounts of missing values. The goal of this study was to test the effect of imputation methods on the evaluation of trait values at species level and on the subsequent calculation of functional diversity indices at community level using functional trait databases. Two simple imputation methods (average and median), two methods based on ecological hypotheses, and one multiple imputation method were tested using a large plant trait database, together with the influence of the percentage of missing data and differences between functional traits. At community level, the complete-case approach and three functional diversity indices calculated from grassland plant communities were included. At the species level, one of the methods based on ecological hypothesis was for all traits more accurate than imputation with average or median values, but the multiple imputation method was superior for most of the traits. The method based on functional proximity between species was the best method for traits with an unbalanced distribution, while the method based on the existence of relationships between traits was the best for traits with a balanced distribution. The ranking of the grassland communities for their functional diversity indices was not robust with the complete-case approach, even for low percentages of missing data. With the imputation methods based on ecological hypotheses, functional diversity indices could be computed with a maximum of 30% of missing data, without affecting the ranking between grassland communities. The multiple imputation method performed well, but not better than single imputation based on ecological hypothesis and adapted to the distribution of the trait values for the functional identity and range of the communities. Ecological studies using functional trait databases have to deal with missing data using imputation methods corresponding to their specific needs and making the most out of the information available in the databases. Within this framework, this study indicates the possibilities and limits of single imputation methods based on ecological hypothesis and concludes that they could be useful when studying the ranking of communities for their functional diversity indices. PMID:24772273

Linking hydraulic traits to tropical forest function in a size-structured and trait-driven model (TFS v.1-Hydro)

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

Christoffersen, Bradley O.; Gloor, Manuel; Fauset, Sophie

Forest ecosystem models based on heuristic water stress functions poorly predict tropical forest response to drought partly because they do not capture the diversity of hydraulic traits (including variation in tree size) observed in tropical forests. We developed a continuous porous media approach to modeling plant hydraulics in which all parameters of the constitutive equations are biologically interpretable and measurable plant hydraulic traits (e.g., turgor loss point π tlp, bulk elastic modulus ε, hydraulic capacitance C ft, xylem hydraulic conductivity k s,max, water potential at 50 % loss of conductivity for both xylem ( P 50,x) and stomata ( Pmore » 50,gs), and the leaf : sapwood area ratio A l: A s). We embedded this plant hydraulics model within a trait forest simulator (TFS) that models light environments of individual trees and their upper boundary conditions (transpiration), as well as providing a means for parameterizing variation in hydraulic traits among individuals. We synthesized literature and existing databases to parameterize all hydraulic traits as a function of stem and leaf traits, including wood density (WD), leaf mass per area (LMA), and photosynthetic capacity ( A max ), and evaluated the coupled model (called TFS v.1-Hydro) predictions, against observed diurnal and seasonal variability in stem and leaf water potential as well as stand-scaled sap flux. Our hydraulic trait synthesis revealed coordination among leaf and xylem hydraulic traits and statistically significant relationships of most hydraulic traits with more easily measured plant traits. Using the most informative empirical trait–trait relationships derived from this synthesis, TFS v.1-Hydro successfully captured individual variation in leaf and stem water potential due to increasing tree size and light environment, with model representation of hydraulic architecture and plant traits exerting primary and secondary controls, respectively, on the fidelity of model predictions. The plant hydraulics model made substantial improvements to simulations of total ecosystem transpiration. As a result, remaining uncertainties and limitations of the trait paradigm for plant hydraulics modeling are highlighted.« less

Linking hydraulic traits to tropical forest function in a size-structured and trait-driven model (TFS v.1-Hydro)

DOE PAGES

Christoffersen, Bradley O.; Gloor, Manuel; Fauset, Sophie; ...

2016-11-24

Forest ecosystem models based on heuristic water stress functions poorly predict tropical forest response to drought partly because they do not capture the diversity of hydraulic traits (including variation in tree size) observed in tropical forests. We developed a continuous porous media approach to modeling plant hydraulics in which all parameters of the constitutive equations are biologically interpretable and measurable plant hydraulic traits (e.g., turgor loss point π tlp, bulk elastic modulus ε, hydraulic capacitance C ft, xylem hydraulic conductivity k s,max, water potential at 50 % loss of conductivity for both xylem ( P 50,x) and stomata ( Pmore » 50,gs), and the leaf : sapwood area ratio A l: A s). We embedded this plant hydraulics model within a trait forest simulator (TFS) that models light environments of individual trees and their upper boundary conditions (transpiration), as well as providing a means for parameterizing variation in hydraulic traits among individuals. We synthesized literature and existing databases to parameterize all hydraulic traits as a function of stem and leaf traits, including wood density (WD), leaf mass per area (LMA), and photosynthetic capacity ( A max ), and evaluated the coupled model (called TFS v.1-Hydro) predictions, against observed diurnal and seasonal variability in stem and leaf water potential as well as stand-scaled sap flux. Our hydraulic trait synthesis revealed coordination among leaf and xylem hydraulic traits and statistically significant relationships of most hydraulic traits with more easily measured plant traits. Using the most informative empirical trait–trait relationships derived from this synthesis, TFS v.1-Hydro successfully captured individual variation in leaf and stem water potential due to increasing tree size and light environment, with model representation of hydraulic architecture and plant traits exerting primary and secondary controls, respectively, on the fidelity of model predictions. The plant hydraulics model made substantial improvements to simulations of total ecosystem transpiration. As a result, remaining uncertainties and limitations of the trait paradigm for plant hydraulics modeling are highlighted.« less

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

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.

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.

Baseline Levels, and Changes Over Time in Body Mass Index and Fasting Insulin, and Their Relationship to Change in Metabolic Trait Clustering

PubMed Central

Sullivan, Lisa M.; Fox, Caroline S.; Wilson, Peter W.F.; Nathan, David M.; Vasan, Ramachandran S.; D'Agostino, Ralph B.; Meigs, James B.

2014-01-01

Abstract Background: Multiple abnormal metabolic traits are found together or “cluster” within individuals more often than is predicted by chance. The individual and combined role of adiposity and insulin resistance (IR) on metabolic trait clustering is uncertain. We tested the hypothesis that change in trait clustering is a function of both baseline level and change in these measures. Methods: In 2616 nondiabetic Framingham Offspring Study participants, body mass index (BMI) and fasting insulin were related to a within-person 7-year change in a trait score of 0–4 Adult Treatment Panel III metabolic syndrome traits (hypertension, high triglycerides, low high-density lipoprotein cholesterol, hyperglycemia). Results: At baseline assessment, mean trait score was 1.4 traits, and 7-year mean (SEM) change in trait score was +0.25 (0.02) traits, P<0.0001. In models with BMI predictors only, for every quintile difference in baseline BMI, the 7-year trait score increase was 0.14 traits, and for every quintile increase in BMI during 7-year follow-up, the trait score increased by 0.3 traits. Baseline level and change in fasting insulin were similarly related to trait score change. In models adjusted for age–sex–baseline cluster score, 7-year change in trait score was significantly related to both a 1-quintile difference in baseline BMI (0.07 traits) and fasting insulin (0.18 traits), and to both a 1-quintile 7-year increase in BMI (0.21 traits) and fasting insulin (0.18 traits). Conclusions: Change in metabolic trait clustering was significantly associated with baseline levels and changes in both BMI and fasting insulin, highlighting the importance of both obesity and IR in the clustering of metabolic traits. PMID:25007010

Analyzing latent state-trait and multiple-indicator latent growth curve models as multilevel structural equation models

PubMed Central

Geiser, Christian; Bishop, Jacob; Lockhart, Ginger; Shiffman, Saul; Grenard, Jerry L.

2013-01-01

Latent state-trait (LST) and latent growth curve (LGC) models are frequently used in the analysis of longitudinal data. Although it is well-known that standard single-indicator LGC models can be analyzed within either the structural equation modeling (SEM) or multilevel (ML; hierarchical linear modeling) frameworks, few researchers realize that LST and multivariate LGC models, which use multiple indicators at each time point, can also be specified as ML models. In the present paper, we demonstrate that using the ML-SEM rather than the SL-SEM framework to estimate the parameters of these models can be practical when the study involves (1) a large number of time points, (2) individually-varying times of observation, (3) unequally spaced time intervals, and/or (4) incomplete data. Despite the practical advantages of the ML-SEM approach under these circumstances, there are also some limitations that researchers should consider. We present an application to an ecological momentary assessment study (N = 158 youths with an average of 23.49 observations of positive mood per person) using the software Mplus (Muthén and Muthén, 1998–2012) and discuss advantages and disadvantages of using the ML-SEM approach to estimate the parameters of LST and multiple-indicator LGC models. PMID:24416023

Genetic parameters for different growth scales in GIFT strain of Nile tilapia (Oreochromis niloticus).

PubMed

He, J; Gao, H; Xu, P; Yang, R

2015-12-01

Body weight, length, width and depth at two growth stages were observed for a total of 5015 individuals of GIFT strain, along with a pedigree including 5588 individuals from 104 sires and 162 dams was collected. Multivariate animal models and a random regression model were used to genetically analyse absolute and relative growth scales of these growth traits. In absolute growth scale, the observed growth traits had moderate heritabilities ranging from 0.321 to 0.576, while pairwise ratios between body length, width and depth were lowly inherited and maximum heritability was only 0.146 for length/depth. All genetic correlations were above 0.5 between pairwise growth traits and genetic correlation between length/width and length/depth varied between both growth stages. Based on those estimates, selection index of multiple traits of interest can be formulated in future breeding program to improve genetically body weight and morphology of the GIFT strain. In relative growth scale, heritabilities in relative growths of body length, width and depth to body weight were 0.257, 0.412 and 0.066, respectively, while genetic correlations among these allometry scalings were above 0.8. Genetic analysis for joint allometries of body weight to body length, width and depth will contribute to genetically regulate the growth rate between body shape and body weight. © 2015 Blackwell Verlag GmbH.

Testing Associations of Plant Functional Diversity with Carbon and Nitrogen Storage along a Restoration Gradient of Sandy Grassland

PubMed Central

Zuo, Xiaoan; Zhou, Xin; Lv, Peng; Zhao, Xueyong; Zhang, Jing; Wang, Shaokun; Yue, Xiyuan

2016-01-01

The trait-based approach shows that ecosystem function is strongly affected by plant functional diversity as reflected by the traits of the most abundant species (community-weighted mean, CWM) and functional dispersion (FDis). Effects of CWM and FDis individually support the biomass ratio hypothesis and the niche complementarity hypothesis. However, there is little empirical evidence on the relative roles of CWM traits and FDis in explaining the carbon (C) and nitrogen (N) storage in grassland ecosystems. We measured plant functional traits in the 34 most abundant species across 24 sites along a restoration gradient of sandy grassland (mobile dune, semi-fixed dune, fixed dune, and grassland) in Horqin Sand Land, northern China. Thereafter, we calculated the CWM traits, the functional divergence of each single trait (FDvar) and the trait dispersion of multiple traits (FDis). We also measured the C and N storage in plant, litter, root, and soil. Using a stepwise multiple regression analysis, we further assessed which of the functional diversity components best explained C and N storage in the sandy grassland restoration. We found consistent links between C or N storage and leaf traits related to plant resource use strategy. However, the CWM of plant height was retained as an important predictor of C and N storage in plant, litter, soil, and total ecosystem in the final multiple models. CWMs of specific leaf area and plant height best predicted soil C and N storage and total ecosystem N storage. FDis was one of good predictors of litter C and N storage as well as total ecosystem C storage. These results suggest that ecosystem C and N pools in the sandy grassland restoration are primarily associated with the traits of the most abundant species in communities, thereby supporting the biomass ratio hypothesis. The positive associations of FDis with C storage in litter and total ecosystem provide evidence to support the niche complementarity hypothesis. Both functional traits of dominant species and traits’ dispersion in plant communities could contribute to explaining total ecosystem C storage. Thus, single- and multi-trait indices of functional composition play a crucial role in predicting C storage in sandy grasslands. PMID:26925089

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

PubMed Central

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

2016-01-01

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

SCOPA and META-SCOPA: software for the analysis and aggregation of genome-wide association studies of multiple correlated phenotypes.

PubMed

Mägi, Reedik; Suleimanov, Yury V; Clarke, Geraldine M; Kaakinen, Marika; Fischer, Krista; Prokopenko, Inga; Morris, Andrew P

2017-01-11

Genome-wide association studies (GWAS) of single nucleotide polymorphisms (SNPs) have been successful in identifying loci contributing genetic effects to a wide range of complex human diseases and quantitative traits. The traditional approach to GWAS analysis is to consider each phenotype separately, despite the fact that many diseases and quantitative traits are correlated with each other, and often measured in the same sample of individuals. Multivariate analyses of correlated phenotypes have been demonstrated, by simulation, to increase power to detect association with SNPs, and thus may enable improved detection of novel loci contributing to diseases and quantitative traits. We have developed the SCOPA software to enable GWAS analysis of multiple correlated phenotypes. The software implements "reverse regression" methodology, which treats the genotype of an individual at a SNP as the outcome and the phenotypes as predictors in a general linear model. SCOPA can be applied to quantitative traits and categorical phenotypes, and can accommodate imputed genotypes under a dosage model. The accompanying META-SCOPA software enables meta-analysis of association summary statistics from SCOPA across GWAS. Application of SCOPA to two GWAS of high-and low-density lipoprotein cholesterol, triglycerides and body mass index, and subsequent meta-analysis with META-SCOPA, highlighted stronger association signals than univariate phenotype analysis at established lipid and obesity loci. The META-SCOPA meta-analysis also revealed a novel signal of association at genome-wide significance for triglycerides mapping to GPC5 (lead SNP rs71427535, p = 1.1x10 -8 ), which has not been reported in previous large-scale GWAS of lipid traits. The SCOPA and META-SCOPA software enable discovery and dissection of multiple phenotype association signals through implementation of a powerful reverse regression approach.

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...

Brassinosteroid and gibberellin control of seedling traits in maize (Zea mays L.).

PubMed

Hu, Songlin; Sanchez, Darlene L; Wang, Cuiling; Lipka, Alexander E; Yin, Yanhai; Gardner, Candice A C; Lübberstedt, Thomas

2017-10-01

In this study, we established two doubled haploid (DH) libraries with a total of 207 DH lines. We applied BR and GA inhibitors to all DH lines at seedling stage and measured seedling BR and GA inhibitor responses. Moreover, we evaluated field traits for each DH line (untreated). We conducted genome-wide association studies (GWAS) with 62,049 genome wide SNPs to explore the genetic control of seedling traits by BR and GA. In addition, we correlate seedling stage hormone inhibitor response with field traits. Large variation for BR and GA inhibitor response and field traits was observed across these DH lines. Seedling stage BR and GA inhibitor response was significantly correlate with yield and flowering time. Using three different GWAS approaches to balance false positive/negatives, multiple SNPs were discovered to be significantly associated with BR/GA inhibitor responses with some localized within gene models. SNPs from gene model GRMZM2G013391 were associated with GA inhibitor response across all three GWAS models. This gene is expressed in roots and shoots and was shown to regulate GA signaling. These results show that BRs and GAs have a great impact for controlling seedling growth. Gene models from GWAS results could be targets for seeding traits improvement. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed Central

Bergman, Juraj; Mitrikeski, Petar T.

2015-01-01

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

Hydrological and environmental variables outperform spatial factors in structuring species, trait composition, and beta diversity of pelagic algae.

PubMed

Wu, Naicheng; Qu, Yueming; Guse, Björn; Makarevičiūtė, Kristė; To, Szewing; Riis, Tenna; Fohrer, Nicola

2018-03-01

There has been increasing interest in algae-based bioassessment, particularly, trait-based approaches are increasingly suggested. However, the main drivers, especially the contribution of hydrological variables, of species composition, trait composition, and beta diversity of algae communities are less studied. To link species and trait composition to multiple factors (i.e., hydrological variables, local environmental variables, and spatial factors) that potentially control species occurrence/abundance and to determine their relative roles in shaping species composition, trait composition, and beta diversities of pelagic algae communities, samples were collected from a German lowland catchment, where a well-proven ecohydrological modeling enabled to predict long-term discharges at each sampling site. Both trait and species composition showed significant correlations with hydrological, environmental, and spatial variables, and variation partitioning revealed that the hydrological and local environmental variables outperformed spatial variables. A higher variation of trait composition (57.0%) than species composition (37.5%) could be explained by abiotic factors. Mantel tests showed that both species and trait-based beta diversities were mostly related to hydrological and environmental heterogeneity with hydrological contributing more than environmental variables, while purely spatial impact was less important. Our findings revealed the relative importance of hydrological variables in shaping pelagic algae community and their spatial patterns of beta diversities, emphasizing the need to include hydrological variables in long-term biomonitoring campaigns and biodiversity conservation or restoration. A key implication for biodiversity conservation was that maintaining the instream flow regime and keeping various habitats among rivers are of vital importance. However, further investigations at multispatial and temporal scales are greatly needed.

Continuity between DSM-5 Categorical Criteria and Traits Criteria for Borderline Personality Disorder.

PubMed

Bach, Bo; Sellbom, Martin

2016-08-01

Borderline personality disorder (BPD) includes a heterogeneous constellation of symptoms operationalized with 9 categorical criteria. As the field of personality disorder (PD) research moves to emphasize dimensional traits in its operationalization, it is important to delineate continuity between the 9 DSM-IV/Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) categorical criteria for BPD and the trait dimensions in DSM-5 Section III. To date, no study has attempted such validation. We examined the associations between the 9 categorical DSM-IV/DSM-5 criteria for BPD and the trait dimensions of the alternative DSM-5 model for PDs in consecutively recruited psychiatric outpatients (N = 142; 68% female; age: mean 29.02, SD 8.38). This was investigated by means of bivariate correlations, followed by multiple logistic regression analysis. The categorical BPD criteria were associated with conceptually related DSM-5 Section III traits (P > 0.001), except for the criterion of chronic feelings of emptiness. Consistent with the proposed traits criteria for BPD in DSM-5 Section III, we found Emotional lability, Anxiousness, Separation insecurity, Depressivity, Impulsivity, Risk taking, and Hostility to capture conceptually coherent BPD categorical criteria, while Suspiciousness was also strongly associated with BPD criteria. At the domain level, this applied to Negative affectivity, Disinhibition, and Psychoticism. Notably, Emotional lability, Impulsivity, and Suspiciousness emerged as unique predictors of BPD (P > 0.05). In addition to the proposed BPD traits criteria, Suspiciousness and features of Psychoticism also augment BPD features. Provided that these findings are replicated in forthcoming research, a modified traits operationalization of BPD is warranted. © The Author(s) 2016.

Correlative responses for carcass and meat quality traits to selection for ovulation rate or prenatal survival in French Large White pigs.

PubMed

Rosendo, A; Druet, T; Péry, C; Bidanel, J P

2010-03-01

Correlated effects of selection for components of litter size on carcass and meat quality traits were estimated using data from 3 lines of pigs derived from the same Large White base population. Two lines were selected for 6 generations on high ovulation rate at puberty (OR) or high prenatal survival corrected for ovulation rate in the first 2 parities (PS). The third line was an unselected control (CON). The 3 lines were kept for a 7th generation, but without any selection. Carcass and meat quality traits were recorded on the 5th to 7th generation of the experiment. Carcass traits included dressing percentage, carcass length (LGTH), average backfat thickness (ABT), estimated lean meat content, and 8 carcass joint weight traits. Meat quality traits included pH recorded 24 h after slaughter (pH24) of LM, gluteus superficialis (GS), biceps femoris (BF), and adductor femoris (AD) muscles, as well as reflectance and water-holding capacity (WHC) of GS and BF muscles. Heritabilities of carcass and meat quality traits and their genetic correlations with OR and PS were estimated using REML methodology applied to a multiple trait animal model. Correlated responses to selection were then estimated by computing differences between OR or PS and CON lines at generations 5 to 7 using least squares and mixed model methodology. Heritability (h(2)) estimates were 0.08 +/- 0.04, 0.58 +/- 0.10, 0.70 +/- 0.10, and 0.74 +/- 0.10 for dressing percentage, LGTH, ABT, and lean meat content, respectively, ranged from 0.28 to 0.72 for carcass joint traits, from 0.28 to 0.45 for pH24 and reflectance measurements, and from 0.03 to 0.11 for WHC measurements. Both OR and PS had weak genetic correlations with carcass (r(G) = -0.09 to 0.17) and most meat quality traits. Selection for OR did not affect any carcass composition or meat quality trait. Correlated responses to selection for PS were also limited, with the exception of a decrease in pH24 of GS and BF muscles (-0.12 to -0.14 after 6 generations; P < 0.05), in WHC of GS muscle (-18.9 s after 6 generations; P < 0.05) and a tendency toward an increase in loin weight (0.44 kg after 6 generations; P < 0.10) .

Leaf aging of Amazonian canopy trees as revealed by spectral and physiochemical measurements.

PubMed

Chavana-Bryant, Cecilia; Malhi, Yadvinder; Wu, Jin; Asner, Gregory P; Anastasiou, Athanasios; Enquist, Brian J; Cosio Caravasi, Eric G; Doughty, Christopher E; Saleska, Scott R; Martin, Roberta E; Gerard, France F

2017-05-01

Leaf aging is a fundamental driver of changes in leaf traits, thereby regulating ecosystem processes and remotely sensed canopy dynamics. We explore leaf reflectance as a tool to monitor leaf age and develop a spectra-based partial least squares regression (PLSR) model to predict age using data from a phenological study of 1099 leaves from 12 lowland Amazonian canopy trees in southern Peru. Results demonstrated monotonic decreases in leaf water (LWC) and phosphorus (P mass ) contents and an increase in leaf mass per unit area (LMA) with age across trees; leaf nitrogen (N mass ) and carbon (C mass ) contents showed monotonic but tree-specific age responses. We observed large age-related variation in leaf spectra across trees. A spectra-based model was more accurate in predicting leaf age (R 2  = 0.86; percent root mean square error (%RMSE) = 33) compared with trait-based models using single (R 2  = 0.07-0.73; %RMSE = 7-38) and multiple (R 2  = 0.76; %RMSE = 28) predictors. Spectra- and trait-based models established a physiochemical basis for the spectral age model. Vegetation indices (VIs) including the normalized difference vegetation index (NDVI), enhanced vegetation index 2 (EVI2), normalized difference water index (NDWI) and photosynthetic reflectance index (PRI) were all age-dependent. This study highlights the importance of leaf age as a mediator of leaf traits, provides evidence of age-related leaf reflectance changes that have important impacts on VIs used to monitor canopy dynamics and productivity and proposes a new approach to predicting and monitoring leaf age with important implications for remote sensing. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

The Impact of Taiwanese College Students' Learning Motivation from Self-Determination Perspective on Learning Outcomes: Moderating Roles of Multi-Traits

ERIC Educational Resources Information Center

Ho, Sophia Shi-Huei

2017-01-01

The purpose of this study is to explore the associations among learning motivation, engagement and outcomes, and the moderating role of various traits in the relationship between deep approaches to learning and outcomes. Based on data from 2,340 students in multiple universities in Taiwan, this study proposes two alternative models, tested by…

Multiple interval QTL mapping and searching for PSTOL1 homologs associated with root morphology, biomass accumulation and phosphorus content in maize seedlings under low-P.

PubMed

Azevedo, Gabriel C; Cheavegatti-Gianotto, Adriana; Negri, Bárbara F; Hufnagel, Bárbara; E Silva, Luciano da Costa; Magalhaes, Jurandir V; Garcia, Antonio Augusto F; Lana, Ubiraci G P; de Sousa, Sylvia M; Guimaraes, Claudia T

2015-07-07

Modifications in root morphology are important strategies to maximize soil exploitation under phosphorus starvation in plants. Here, we used two multiple interval models to map QTLs related to root traits, biomass accumulation and P content in a maize RIL population cultivated in nutrient solution. In addition, we searched for putative maize homologs to PSTOL1, a gene responsible to enhance early root growth, P uptake and grain yield in rice and sorghum. Based on path analysis, root surface area was the root morphology component that most strongly contributed to total dry weight and to P content in maize seedling under low-P availability. Multiple interval mapping models for single (MIM) and multiple traits (MT-MIM) were combined and revealed 13 genomic regions significantly associated with the target traits in a complementary way. The phenotypic variances explained by all QTLs and their epistatic interactions using MT-MIM (23.4 to 35.5 %) were higher than in previous studies, and presented superior statistical power. Some of these QTLs were coincident with QTLs for root morphology traits and grain yield previously mapped, whereas others harbored ZmPSTOL candidate genes, which shared more than 55 % of amino acid sequence identity and a conserved serine/threonine kinase domain with OsPSTOL1. Additionally, four ZmPSTOL candidate genes co-localized with QTLs for root morphology, biomass accumulation and/or P content were preferentially expressed in roots of the parental lines that contributed the alleles enhancing the respective phenotypes. QTL mapping strategies adopted in this study revealed complementary results for single and multiple traits with high accuracy. Some QTLs, mainly the ones that were also associated with yield performance in other studies, can be good targets for marker-assisted selection to improve P-use efficiency in maize. Based on the co-localization with QTLs, the protein domain conservation and the coincidence of gene expression, we selected novel maize genes as putative homologs to PSTOL1 that will require further validation studies.

Leaf Aging of Amazonian Canopy Trees: Insights to Tropical Ecological Processes and Satellited Detected Canopy Dynamics

NASA Astrophysics Data System (ADS)

Chavana-Bryant, C.; Malhi, Y.; Gerard, F.

2015-12-01

Leaf aging is a fundamental driver of changes in leaf traits, thereby, regulating ecosystem processes and remotely-sensed canopy dynamics. Leaf age is particularly important for carbon-rich tropical evergreen forests, as leaf demography (leaf age distribution) has been proposed as a major driver of seasonal productivity in these forests. We explore leaf reflectance as a tool to monitor leaf age and develop a novel spectra-based (PLSR) model to predict age using data from a phenological study of 1,072 leaves from 12 lowland Amazonian canopy tree species in southern Peru. Our results demonstrate monotonic decreases in LWC and Pmass and increase in LMA with age across species; Nmass and Cmassshowed monotonic but species-specific age responses. Spectrally, we observed large age-related variation across species, with the most age-sensitive spectral domains found to be: green peak (550nm), red edge (680-750 nm), NIR (700-850 nm), and around the main water absorption features (~1450 and ~1940 nm). A spectra-based model was more accurate in predicting leaf age (R2= 0.86; %RMSE= 33) compared to trait-based models using single (R2=0.07 to 0.73; %RMSE=7 to 38) and multiple predictors (step-wise analysis; R2=0.76; %RMSE=28). Spectral and trait-based models established a physiochemical basis for the spectral age model. The relative importance of the traits modifying the leaf spectra of aging leaves was: LWC>LMA>Nmass>Pmass,&Cmass. Vegetation indices (VIs), including NDVI, EVI2, NDWI and PRI were all age-dependent. This study highlights the importance of leaf age as a mediator of leaf traits, provides evidence of age-related leaf reflectance changes that have important impacts on VIs used to monitor canopy dynamics and productivity, and proposes a new approach to predicting and monitoring leaf age with important implications for remote sensing.

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 ...

Measuring striving for understanding and learning value of geometry: a validity study

NASA Astrophysics Data System (ADS)

Ubuz, Behiye; Aydınyer, Yurdagül

2017-11-01

The current study aimed to construct a questionnaire that measures students' personality traits related to striving for understanding and learning value of geometry and then examine its psychometric properties. Through the use of multiple methods on two independent samples of 402 and 521 middle school students, two studies were performed to address this issue to provide support for its validity. In Study 1, exploratory factor analysis indicated the two-factor model. In Study 2, confirmatory factor analysis indicated the better fit of two-factor model compared to one or three-factor model. Convergent and discriminant validity evidence provided insight into the distinctiveness of the two factors. Subgroup validity evidence revealed gender differences for striving for understanding geometry trait favouring girls and grade level differences for learning value of geometry trait favouring the sixth- and seventh-grade students. Predictive validity evidence demonstrated that the striving for understanding geometry trait but not learning value of geometry trait was significantly correlated with prior mathematics achievement. In both studies, each factor and the entire questionnaire showed satisfactory reliability. In conclusion, the questionnaire was psychometrically sound.

mizer: an R package for multispecies, trait-based and community size spectrum ecological modelling.

PubMed

Scott, Finlay; Blanchard, Julia L; Andersen, Ken H

2014-10-01

Size spectrum ecological models are representations of a community of individuals which grow and change trophic level. A key emergent feature of these models is the size spectrum; the total abundance of all individuals that scales negatively with size. The models we focus on are designed to capture fish community dynamics useful for assessing the community impacts of fishing.We present mizer , an R package for implementing dynamic size spectrum ecological models of an entire aquatic community subject to fishing. Multiple fishing gears can be defined and fishing mortality can change through time making it possible to simulate a range of exploitation strategies and management options. mizer implements three versions of the size spectrum modelling framework: the community model, where individuals are only characterized by their size; the trait-based model, where individuals are further characterized by their asymptotic size; and the multispecies model where additional trait differences are resolved.A range of plot, community indicator and summary methods are available to inspect the results of the simulations.

Speed breeding for multiple quantitative traits in durum wheat.

PubMed

Alahmad, Samir; Dinglasan, Eric; Leung, Kung Ming; Riaz, Adnan; Derbal, Nora; Voss-Fels, Kai P; Able, Jason A; Bassi, Filippo M; Christopher, Jack; Hickey, Lee T

2018-01-01

Plant breeding requires numerous generations to be cycled and evaluated before an improved cultivar is released. This lengthy process is required to introduce and test multiple traits of interest. However, a technology for rapid generation advance named 'speed breeding' was successfully deployed in bread wheat ( Triticum aestivum L.) to achieve six generations per year while imposing phenotypic selection for foliar disease resistance and grain dormancy. Here, for the first time the deployment of this methodology is presented in durum wheat ( Triticum durum Desf.) by integrating selection for key traits, including above and below ground traits on the same set of plants. This involved phenotyping for seminal root angle (RA), seminal root number (RN), tolerance to crown rot (CR), resistance to leaf rust (LR) and plant height (PH). In durum wheat, these traits are desirable in environments where yield is limited by in-season rainfall with the occurrence of CR and epidemics of LR. To evaluate this multi-trait screening approach, we applied selection to a large segregating F 2 population (n = 1000) derived from a bi-parental cross (Outrob4/Caparoi). A weighted selection index (SI) was developed and applied. The gain for each trait was determined by evaluating F 3 progeny derived from 100 'selected' and 100 'unselected' F 2 individuals. Transgressive segregation was observed for all assayed traits in the Outrob4/Caparoi F 2 population. Application of the SI successfully shifted the population mean for four traits, as determined by a significant mean difference between 'selected' and 'unselected' F 3 families for CR tolerance, LR resistance, RA and RN. No significant shift for PH was observed. The novel multi-trait phenotyping method presents a useful tool for rapid selection of early filial generations or for the characterization of fixed lines out-of-season. Further, it offers efficient use of resources by assaying multiple traits on the same set of plants. Results suggest that when performed in parallel with speed breeding in early generations, selection will enrich recombinant inbred lines with desirable alleles and will reduce the length and number of years required to combine these traits in elite breeding populations and therefore cultivars.

Dynamic Latent Trait Models with Mixed Hidden Markov Structure for Mixed Longitudinal Outcomes.

PubMed

Zhang, Yue; Berhane, Kiros

2016-01-01

We propose a general Bayesian joint modeling approach to model mixed longitudinal outcomes from the exponential family for taking into account any differential misclassification that may exist among categorical outcomes. Under this framework, outcomes observed without measurement error are related to latent trait variables through generalized linear mixed effect models. The misclassified outcomes are related to the latent class variables, which represent unobserved real states, using mixed hidden Markov models (MHMM). In addition to enabling the estimation of parameters in prevalence, transition and misclassification probabilities, MHMMs capture cluster level heterogeneity. A transition modeling structure allows the latent trait and latent class variables to depend on observed predictors at the same time period and also on latent trait and latent class variables at previous time periods for each individual. Simulation studies are conducted to make comparisons with traditional models in order to illustrate the gains from the proposed approach. The new approach is applied to data from the Southern California Children Health Study (CHS) to jointly model questionnaire based asthma state and multiple lung function measurements in order to gain better insight about the underlying biological mechanism that governs the inter-relationship between asthma state and lung function development.

Are Fearless Dominance Traits Superfluous in Operationalizing Psychopathy? Incremental Validity and Sex Differences

PubMed Central

Murphy, Brett; Lilienfeld, Scott; Skeem, Jennifer; Edens, John

2016-01-01

Researchers are vigorously debating whether psychopathic personality includes seemingly adaptive traits, especially social and physical boldness. In a large sample (N=1565) of adult offenders, we examined the incremental validity of two operationalizations of boldness (Fearless Dominance traits in the Psychopathy Personality Inventory, Lilienfeld & Andrews, 1996; Boldness traits in the Triarchic Model of Psychopathy, Patrick et al, 2009), above and beyond other characteristics of psychopathy, in statistically predicting scores on four psychopathy-related measures, including the Psychopathy Checklist-Revised (PCL-R). The incremental validity added by boldness traits in predicting the PCL-R’s representation of psychopathy was especially pronounced for interpersonal traits (e.g., superficial charm, deceitfulness). Our analyses, however, revealed unexpected sex differences in the relevance of these traits to psychopathy, with boldness traits exhibiting reduced importance for psychopathy in women. We discuss the implications of these findings for measurement models of psychopathy. PMID:26866795

Assessing the Basic Traits Associated with Psychopathy: Development and Validation of the Elemental Psychopathy Assessment

ERIC Educational Resources Information Center

Lynam, Donald R.; Gaughan, Eric T.; Miller, Joshua D.; Miller, Drew J.; Mullins-Sweatt, Stephanie; Widiger, Thomas A.

2011-01-01

A new self-report assessment of the basic traits of psychopathy was developed with a general trait model of personality (five-factor model [FFM]) as a framework. Scales were written to assess maladaptive variants of the 18 FFM traits that are robustly related to psychopathy across a variety of perspectives including empirical correlations, expert…

Maternal risk factors predicting child physical characteristics and dysmorphology in fetal alcohol syndrome and partial fetal alcohol syndrome.

PubMed

May, Philip A; Tabachnick, Barbara G; Gossage, J Phillip; Kalberg, Wendy O; Marais, Anna-Susan; Robinson, Luther K; Manning, Melanie; Buckley, David; Hoyme, H Eugene

2011-12-01

Previous research in South Africa revealed very high rates of fetal alcohol syndrome (FAS), of 46-89 per 1000 among young children. Maternal and child data from studies in this community summarize the multiple predictors of FAS and partial fetal alcohol syndrome (PFAS). Sequential regression was employed to examine influences on child physical characteristics and dysmorphology from four categories of maternal traits: physical, demographic, childbearing, and drinking. Then, a structural equation model (SEM) was constructed to predict influences on child physical characteristics. Individual sequential regressions revealed that maternal drinking measures were the most powerful predictors of a child's physical anomalies (R² = .30, p < .001), followed by maternal demographics (R² = .24, p < .001), maternal physical characteristics (R²=.15, p < .001), and childbearing variables (R² = .06, p < .001). The SEM utilized both individual variables and the four composite categories of maternal traits to predict a set of child physical characteristics, including a total dysmorphology score. As predicted, drinking behavior is a relatively strong predictor of child physical characteristics (β = 0.61, p < .001), even when all other maternal risk variables are included; higher levels of drinking predict child physical anomalies. Overall, the SEM model explains 62% of the variance in child physical anomalies. As expected, drinking variables explain the most variance. But this highly controlled estimation of multiple effects also reveals a significant contribution played by maternal demographics and, to a lesser degree, maternal physical and childbearing variables. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Additive-Multiplicative Approximation of Genotype-Environment Interaction

PubMed Central

Gimelfarb, A.

1994-01-01

A model of genotype-environment interaction in quantitative traits is considered. The model represents an expansion of the traditional additive (first degree polynomial) approximation of genotypic and environmental effects to a second degree polynomial incorporating a multiplicative term besides the additive terms. An experimental evaluation of the model is suggested and applied to a trait in Drosophila melanogaster. The environmental variance of a genotype in the model is shown to be a function of the genotypic value: it is a convex parabola. The broad sense heritability in a population depends not only on the genotypic and environmental variances, but also on the position of the genotypic mean in the population relative to the minimum of the parabola. It is demonstrated, using the model, that GXE interaction rectional may cause a substantial non-linearity in offspring-parent regression and a reversed response to directional selection. It is also shown that directional selection may be accompanied by an increase in the heritability. PMID:7896113

Multiple-Line Inference of Selection on Quantitative Traits

PubMed Central

Riedel, Nico; Khatri, Bhavin S.; Lässig, Michael; Berg, Johannes

2015-01-01

Trait differences between species may be attributable to natural selection. However, quantifying the strength of evidence for selection acting on a particular trait is a difficult task. Here we develop a population genetics test for selection acting on a quantitative trait that is based on multiple-line crosses. We show that using multiple lines increases both the power and the scope of selection inferences. First, a test based on three or more lines detects selection with strongly increased statistical significance, and we show explicitly how the sensitivity of the test depends on the number of lines. Second, a multiple-line test can distinguish between different lineage-specific selection scenarios. Our analytical results are complemented by extensive numerical simulations. We then apply the multiple-line test to QTL data on floral character traits in plant species of the Mimulus genus and on photoperiodic traits in different maize strains, where we find a signature of lineage-specific selection not seen in two-line tests. PMID:26139839

Five factor model personality traits relate to adult attention-deficit/hyperactivity disorder but not to their distinct neurocognitive profiles.

PubMed

Van Dijk, Fiona E; Mostert, Jeannette; Glennon, Jeffrey; Onnink, Marten; Dammers, Janneke; Vasquez, Alejandro Arias; Kan, Cornelis; Verkes, Robbert Jan; Hoogman, Martine; Franke, Barbara; Buitelaar, Jan K

2017-12-01

Deficits in multiple neuropsychological domains and specific personality profiles have been observed in attention-deficit/hyperactivity disorder (ADHD). In this study we investigated whether personality traits are related to neurocognitive profiles in adults with ADHD. Neuropsychological performance and Five Factor Model (FFM) personality traits were measured in adults with ADHD (n = 133) and healthy controls (n = 132). Three neuropsychological profiles, derived from previous community detection analyses, were investigated for personality trait differences. Irrespective of cognitive profile, participants with ADHD showed significantly higher Neuroticism and lower Extraversion, Agreeableness, and Conscientiousness than healthy controls. Only the FFM personality factor Openness differed significantly between the three profiles. Higher Openness was more common in those with aberrant attention and inhibition than those with increased delay discounting and atypical working memory / verbal fluency. The results suggest that the personality trait Openness, but not any other FFM factor, is linked to neurocognitive profiles in ADHD. ADHD symptoms rather than profiles of cognitive impairment have associations with personality traits. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Cognitive and affective trait and state factors influencing the long-term symptom course in remitted depressed patients.

PubMed

Timm, Christina; Ubl, Bettina; Zamoscik, Vera; Ebner-Priemer, Ulrich; Reinhard, Iris; Huffziger, Silke; Kirsch, Peter; Kuehner, Christine

2017-01-01

Major depressive disorder (MDD) is characterized by a high risk for relapses and chronic developments. Clinical characteristics such as residual symptoms have been shown to negatively affect the long-term course of MDD. However, it is unclear so far how trait repetitive negative thinking (RNT) as well as cognitive and affective momentary states, the latter experienced during daily-life, affect the long-term course of MDD. We followed up 57 remitted depressed (rMDD) individuals six (T2) and 36 (T3) months after baseline. Clinical outcomes were time to relapse, time spent with significant symptoms as a marker of chronicity, and levels of depressive symptoms at T2 and T3. Predictors assessed at baseline included residual symptoms and trait RNT. Furthermore, momentary daily life affect and momentary rumination, and their variation over the day were assessed at baseline using ambulatory assessment (AA). In multiple models, residual symptoms and instability of daily-life affect at baseline independently predicted a faster time to relapse, while chronicity was significantly predicted by trait RNT. Multilevel models revealed that depressive symptom levels during follow-up were predicted by baseline residual symptom levels and by instability of daily-life rumination. Both instability features were linked to a higher number of anamnestic MDD episodes. Our findings indicate that trait RNT, but also affective and cognitive processes during daily life impact the longer-term course of MDD. Future longitudinal research on the role of respective AA-phenotypes as potential transdiagnostic course-modifiers is warranted.

Testing projected wild bee distributions in agricultural habitats: predictive power depends on species traits and habitat type.

PubMed

Marshall, Leon; Carvalheiro, Luísa G; Aguirre-Gutiérrez, Jesús; Bos, Merijn; de Groot, G Arjen; Kleijn, David; Potts, Simon G; Reemer, Menno; Roberts, Stuart; Scheper, Jeroen; Biesmeijer, Jacobus C

2015-10-01

Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is maintained across distinct habitats and for species with different functional traits. Highly mobile species, such as bees, can be particularly challenging to model. Here, we use independent sets of occurrence data collected systematically in several agricultural habitats to test how the predictive performance of SDMs for wild bee species depends on species traits, habitat type, and sampling technique. We used a species distribution modeling approach parametrized for the Netherlands, with presence records from 1990 to 2010 for 193 Dutch wild bees. For each species, we built a Maxent model based on 13 climate and landscape variables. We tested the predictive performance of the SDMs with independent datasets collected from orchards and arable fields across the Netherlands from 2010 to 2013, using transect surveys or pan traps. Model predictive performance depended on species traits and habitat type. Occurrence of bee species specialized in habitat and diet was better predicted than generalist bees. Predictions of habitat suitability were also more precise for habitats that are temporally more stable (orchards) than for habitats that suffer regular alterations (arable), particularly for small, solitary bees. As a conservation tool, SDMs are best suited to modeling rarer, specialist species than more generalist and will work best in long-term stable habitats. The variability of complex, short-term habitats is difficult to capture in such models and historical land use generally has low thematic resolution. To improve SDMs' usefulness, models require explanatory variables and collection data that include detailed landscape characteristics, for example, variability of crops and flower availability. Additionally, testing SDMs with field surveys should involve multiple collection techniques.

easyGWAS: A Cloud-Based Platform for Comparing the Results of Genome-Wide Association Studies.

PubMed

Grimm, Dominik G; Roqueiro, Damian; Salomé, Patrice A; Kleeberger, Stefan; Greshake, Bastian; Zhu, Wangsheng; Liu, Chang; Lippert, Christoph; Stegle, Oliver; Schölkopf, Bernhard; Weigel, Detlef; Borgwardt, Karsten M

2017-01-01

The ever-growing availability of high-quality genotypes for a multitude of species has enabled researchers to explore the underlying genetic architecture of complex phenotypes at an unprecedented level of detail using genome-wide association studies (GWAS). The systematic comparison of results obtained from GWAS of different traits opens up new possibilities, including the analysis of pleiotropic effects. Other advantages that result from the integration of multiple GWAS are the ability to replicate GWAS signals and to increase statistical power to detect such signals through meta-analyses. In order to facilitate the simple comparison of GWAS results, we present easyGWAS, a powerful, species-independent online resource for computing, storing, sharing, annotating, and comparing GWAS. The easyGWAS tool supports multiple species, the uploading of private genotype data and summary statistics of existing GWAS, as well as advanced methods for comparing GWAS results across different experiments and data sets in an interactive and user-friendly interface. easyGWAS is also a public data repository for GWAS data and summary statistics and already includes published data and results from several major GWAS. We demonstrate the potential of easyGWAS with a case study of the model organism Arabidopsis thaliana , using flowering and growth-related traits. © 2016 American Society of Plant Biologists. All rights reserved.

Turning over a new 'leaf': multiple functional significances of leaves versus phyllodes in Hawaiian Acacia koa.

PubMed

Pasquet-Kok, Jessica; Creese, Christine; Sack, Lawren

2010-12-01

Hawaiian endemic tree Acacia koa is a model for heteroblasty with bipinnately compound leaves and phyllodes. Previous studies suggested three hypotheses for their functional differentiation: an advantage of leaves for early growth or shade tolerance, and an advantage of phyllodes for drought tolerance. We tested the ability of these hypotheses to explain differences between leaf types for potted plants in 104 physiological and morphological traits, including gas exchange, structure and composition, hydraulic conductance, and responses to varying light, intercellular CO(2) , vapour pressure deficit (VPD) and drought. Leaf types were similar in numerous traits including stomatal pore area per leaf area, leaf area-based gas exchange rates and cuticular conductance. Each hypothesis was directly supported by key differences in function. Leaves had higher mass-based gas exchange rates, while the water storage tissue in phyllodes contributed to greater capacitance per area; phyllodes also showed stronger stomatal closure at high VPD, and higher maximum hydraulic conductance per area, with stronger decline during desiccation and recovery with rehydration. While no single hypothesis completely explained the differences between leaf types, together the three hypotheses explained 91% of differences. These findings indicate that the heteroblasty confers multiple benefits, realized across different developmental stages and environmental contexts. © 2010 Blackwell Publishing Ltd.

Indirect genetic effects and sexual conflicts: Partner genotype influences multiple morphological and behavioral reproductive traits in a flatworm.

PubMed

Marie-Orleach, Lucas; Vogt-Burri, Nadja; Mouginot, Pierick; Schlatter, Aline; Vizoso, Dita B; Bailey, Nathan W; Schärer, Lukas

2017-05-01

The expression of an individual's phenotypic traits can be influenced by genes expressed in its social partners. Theoretical models predict that such indirect genetic effects (IGEs) on reproductive traits should play an important role in determining the evolutionary outcome of sexual conflict. However, empirical tests of (i) whether reproductive IGEs exist, (ii) how they vary among genotypes, and (iii) whether they are uniform for different types of reproductive traits are largely lacking. We addressed this in a series of experiments in the simultaneously hermaphroditic flatworm Macrostomum lignano. We found strong evidence for IGEs on both morphological and behavioral reproductive traits. Partner genotype had a significant impact on the testis size of focal individuals-varying up to 2.4-fold-suggesting that IGEs could mediate sexual conflicts that target the male sex function. We also found that time to first copulation was affected by a genotype × genotype interaction between mating partners, and that partner genotype affected the propensity to copulate and perform the postcopulatory suck behavior, which may mediate conflicts over the fate of received ejaculate components. These findings provide clear empirical evidence for IGEs on multiple behavioral and morphological reproductive traits, which suggests that the evolutionary dynamics of these traits could be altered by genes contained in the social environment. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Modelling the multidimensional niche by linking functional traits to competitive performance

PubMed Central

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

2015-01-01

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

The mediator effect of personality traits on the relationship between childhood abuse and depressive symptoms in schizophrenia.

PubMed

Okubo, Ryo; Inoue, Takeshi; Hashimoto, Naoki; Suzukawa, Akio; Tanabe, Hajime; Oka, Matsuhiko; Narita, Hisashi; Ito, Koki; Kako, Yuki; Kusumi, Ichiro

2017-11-01

Previous studies indicated that personality traits have a mediator effect on the relationship between childhood abuse and depressive symptoms in major depressive disorder and nonclinical general adult subjects. In the present study, we aimed to test the hypothesis that personality traits mediate the relationship between childhood abuse and depressive symptoms in schizophrenia. We used the following questionnaires to evaluate 255 outpatients with schizophrenia: the Child Abuse and Trauma Scale, temperament and character inventory, and Patients Health Questionnire-9. Univariate analysis, multiple regression analysis, and structured equation modeling (SEM) were used to analyze the data. The relationship between neglect and sexual abuse and the severity of depressive symptoms was mostly mediated by the personality traits of high harm avoidance, low self-directedness, and low cooperativeness. This finding was supported by the results of stepwise multiple regression analysis and the acceptable fit indices of SEM. Thus, our results suggest that personality traits mediate the relationship between childhood abuse and depressive symptoms in schizophrenia. The present study and our previous studies also suggest that this mediator effect could occur independent of the presence or type of mental disorder. Clinicians should routinely assess childhood abuse history, personality traits, and their effects in schizophrenia. Copyright © 2017. Published by Elsevier B.V.

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.

Parameter-based stochastic simulation of selection and breeding for multiple traits

Treesearch

Jennifer Myszewski; Thomas Byram; Floyd Bridgwater

2006-01-01

To increase the adaptability and economic value of plantations, tree improvement professionals often manage multiple traits in their breeding programs. When these traits are unfavorably correlated, breeders must weigh the economic importance of each trait and select for a desirable aggregate phenotype. Stochastic simulation allows breeders to test the effects of...

Gene-Based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions.

PubMed

Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y; Chen, Wei

2016-02-01

Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, here we develop Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT), which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. © 2016 WILEY PERIODICALS, INC.

Gene-based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions

PubMed Central

Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E.; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y.; Chen, Wei

2015-01-01

Summary Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, we develop here Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT) which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. PMID:26782979

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

ERIC Educational Resources Information Center

Simonton, Dean Keith

2005-01-01

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

Cross-Informant Symptoms from CBCL, TRF, and YSR : Trait and Method Variance in a Normative Sample of Russian Youths

ERIC Educational Resources Information Center

Grigorenko, Elena L.; Geiser, Christian; Slobodskaya, Helena R.; Francis, David J.

2010-01-01

A large community-based sample of Russian youths (n = 841, age M = 13.17 years, SD = 2.51) was assessed with the Child Behavior Checklist (mothers and fathers separately), Teacher's Report Form, and Youth Self-Report. The multiple indicator-version of the correlated trait-correlated method minus one, or CT-C(M-1), model was applied to analyze (a)…

Unusual Configurations of Personality Traits Indicate Multiple Patterns of Their Coalescence

PubMed Central

Allik, Jüri; Hřebíčková, Martina; Realo, Anu

2018-01-01

It is widely accepted that the Five Factor Model (FFM) is a satisfactory description of the pattern of covariations among personality traits, which supposedly fits, more or less adequately, every individual. As an amendment to the FFM, we propose that the customary five-factor structure is only a near-universal, because it does not fit all individuals but only a large majority of them. Evidences reveal a small minority of participants who have an unusual configuration of personality traits, which is clearly recognizable, both in self- and observer-ratings. We identified three types of atypical configurations of personality traits, characterized mainly by a scatter of subscale scores within each of the FFM factors. How different configurations of personality traits are formed, persist, and function needs further investigation. PMID:29515499

The DSM-5 alternative model of personality disorders from the perspective of adult attachment: a study in community-dwelling adults.

PubMed

Fossati, Andrea; Krueger, Robert F; Markon, Kristian E; Borroni, Serena; Maffei, Cesare; Somma, Antonella

2015-04-01

To assess how the maladaptive personality domains and facets that were included in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) Alternative Model of Personality Disorders relate to adult attachment styles, 480 Italian nonclinical adults were administered the Personality Inventory for DSM-5 (PID-5) and the Attachment Style Questionnaire (ASQ). To evaluate the uniqueness of the associations between the PID-5 scales and the ASQ scales, the participants were also administered the Big Five Inventory (BFI). Multiple regression analyses showed that the ASQ scales significantly predicted both PID-5 domain scales and BFI scales; however, the relationships were different both qualitatively and quantitatively. With the exception of the PID-5 risk taking scale (adjusted R(2) = 0.02), all other PID-5 trait scales were significantly predicted by the ASQ scales, median adjusted R(2) value = 0.25, all ps < 0.001. Our findings suggest that the maladaptive personality domains and traits listed in the DSM-5 Alternative Model of Personality Disorders show meaningful associations with adult attachment styles.

Analyzing Association Mapping in Pedigree-Based GWAS Using a Penalized Multitrait Mixed Model

PubMed Central

Liu, Jin; Yang, Can; Shi, Xingjie; Li, Cong; Huang, Jian; Zhao, Hongyu; Ma, Shuangge

2017-01-01

Genome-wide association studies (GWAS) have led to the identification of many genetic variants associated with complex diseases in the past 10 years. Penalization methods, with significant numerical and statistical advantages, have been extensively adopted in analyzing GWAS. This study has been partly motivated by the analysis of Genetic Analysis Workshop (GAW) 18 data, which have two notable characteristics. First, the subjects are from a small number of pedigrees and hence related. Second, for each subject, multiple correlated traits have been measured. Most of the existing penalization methods assume independence between subjects and traits and can be suboptimal. There are a few methods in the literature based on mixed modeling that can accommodate correlations. However, they cannot fully accommodate the two types of correlations while conducting effective marker selection. In this study, we develop a penalized multitrait mixed modeling approach. It accommodates the two different types of correlations and includes several existing methods as special cases. Effective penalization is adopted for marker selection. Simulation demonstrates its satisfactory performance. The GAW 18 data are analyzed using the proposed method. PMID:27247027

Affective traits and history of depression are related to ventral striatum connectivity.

PubMed

DelDonno, Sophie R; Jenkins, Lisanne M; Crane, Natania A; Nusslock, Robin; Ryan, Kelly A; Shankman, Stewart A; Phan, K Luan; Langenecker, Scott A

2017-10-15

Studying remitted Major Depressive Disorder (rMDD) facilitates a better understanding of neural mechanisms for risk, given that confounding effects of active symptoms are removed. Disrupted functional connectivity has been reported in multiple networks in MDD. However, no study to date of rMDD has specifically examined connectivity of the ventral striatum (VS), a region highly implicated in reward and motivation. We investigated functional connectivity of the VS in individuals with and without a history of MDD, and in relation to affective personality traits. Forty-two individuals with rMDD and 28 healthy controls across two sites completed resting-state fMRI and the Behavioral Inhibition System/Behavioral Activation System Scale. Voxel-wise, whole-brain comparisons were conducted across and between groups for four seeds: left and right inferior VS (VSi), left and right superior VS (VSs). VSs connectivity to temporal and subcortical regions including the putamen and amygdala was positive and greater in HCs compared to rMDD individuals. Across groups, VSi connectivity was positively correlated with trait reward-responsiveness in somatomotor regions. Across groups, VSs connectivity was positively correlated with trait drive, particularly in the putamen, parahippocampal, and inferior temporal gyrus, and was negatively associated with trait behavioral inhibition in the anterior cingulate, frontal gyri, and insula. Limitations include scanning at two sites and using multiple comparisons. Group connectivity differences emerged from the VSs rather than VSi. VSs showed associations with trait drive and behavioral inhibition, whereas VSi corrrelated with reward-responsiveness. Depression history and affective traits contribute meaningful and specific information about VS connectivity in understanding risk for MDD. Copyright © 2017 Elsevier B.V. All rights reserved.

Genomic Prediction of Testcross Performance in Canola (Brassica napus)

PubMed Central

Jan, Habib U.; Abbadi, Amine; Lücke, Sophie; Nichols, Richard A.; Snowdon, Rod J.

2016-01-01

Genomic selection (GS) is a modern breeding approach where genome-wide single-nucleotide polymorphism (SNP) marker profiles are simultaneously used to estimate performance of untested genotypes. In this study, the potential of genomic selection methods to predict testcross performance for hybrid canola breeding was applied for various agronomic traits based on genome-wide marker profiles. A total of 475 genetically diverse spring-type canola pollinator lines were genotyped at 24,403 single-copy, genome-wide SNP loci. In parallel, the 950 F1 testcross combinations between the pollinators and two representative testers were evaluated for a number of important agronomic traits including seedling emergence, days to flowering, lodging, oil yield and seed yield along with essential seed quality characters including seed oil content and seed glucosinolate content. A ridge-regression best linear unbiased prediction (RR-BLUP) model was applied in combination with 500 cross-validations for each trait to predict testcross performance, both across the whole population as well as within individual subpopulations or clusters, based solely on SNP profiles. Subpopulations were determined using multidimensional scaling and K-means clustering. Genomic prediction accuracy across the whole population was highest for seed oil content (0.81) followed by oil yield (0.75) and lowest for seedling emergence (0.29). For seed yieId, seed glucosinolate, lodging resistance and days to onset of flowering (DTF), prediction accuracies were 0.45, 0.61, 0.39 and 0.56, respectively. Prediction accuracies could be increased for some traits by treating subpopulations separately; a strategy which only led to moderate improvements for some traits with low heritability, like seedling emergence. No useful or consistent increase in accuracy was obtained by inclusion of a population substructure covariate in the model. Testcross performance prediction using genome-wide SNP markers shows considerable potential for pre-selection of promising hybrid combinations prior to resource-intensive field testing over multiple locations and years. PMID:26824924

Automatic prediction of facial trait judgments: appearance vs. structural models.

PubMed

Rojas, Mario; Masip, David; Todorov, Alexander; Vitria, Jordi

2011-01-01

Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions.

Use of the preconditioned conjugate gradient algorithm as a generic solver for mixed-model equations in animal breeding applications.

PubMed

Tsuruta, S; Misztal, I; Strandén, I

2001-05-01

Utility of the preconditioned conjugate gradient algorithm with a diagonal preconditioner for solving mixed-model equations in animal breeding applications was evaluated with 16 test problems. The problems included single- and multiple-trait analyses, with data on beef, dairy, and swine ranging from small examples to national data sets. Multiple-trait models considered low and high genetic correlations. Convergence was based on relative differences between left- and right-hand sides. The ordering of equations was fixed effects followed by random effects, with no special ordering within random effects. The preconditioned conjugate gradient program implemented with double precision converged for all models. However, when implemented in single precision, the preconditioned conjugate gradient algorithm did not converge for seven large models. The preconditioned conjugate gradient and successive overrelaxation algorithms were subsequently compared for 13 of the test problems. The preconditioned conjugate gradient algorithm was easy to implement with the iteration on data for general models. However, successive overrelaxation requires specific programming for each set of models. On average, the preconditioned conjugate gradient algorithm converged in three times fewer rounds of iteration than successive overrelaxation. With straightforward implementations, programs using the preconditioned conjugate gradient algorithm may be two or more times faster than those using successive overrelaxation. However, programs using the preconditioned conjugate gradient algorithm would use more memory than would comparable implementations using successive overrelaxation. Extensive optimization of either algorithm can influence rankings. The preconditioned conjugate gradient implemented with iteration on data, a diagonal preconditioner, and in double precision may be the algorithm of choice for solving mixed-model equations when sufficient memory is available and ease of implementation is essential.

Longitudinal analyses of correlated response efficiencies of fillet traits in Nile tilapia.

PubMed

Turra, E M; Fernandes, A F A; de Alvarenga, E R; Teixeira, E A; Alves, G F O; Manduca, L G; Murphy, T W; Silva, M A

2018-03-01

Recent studies with Nile tilapia have shown divergent results regarding the possibility of selecting on morphometric measurements to promote indirect genetic gains in fillet yield (FY). The use of indirect selection for fillet traits is important as these traits are only measurable after harvesting. Random regression models are a powerful tool in association studies to identify the best time point to measure and select animals. Random regression models can also be applied in a multiple trait approach to analyze indirect response to selection, which would avoid the need to sacrifice candidate fish. Therefore, the aim of this study was to investigate the genetic relationships between several body measurements, weight and fillet traits throughout the growth period and to evaluate the possibility of indirect selection for fillet traits in Nile tilapia. Data were collected from 2042 fish and was divided into two subsets. The first subset was used to estimate genetic parameters, including the permanent environmental effect for BW and body measurements (8758 records for each body measurement, as each fish was individually weighed and measured a maximum of six times). The second subset (2042 records for each trait) was used to estimate genetic correlations and heritabilities, which enabled the calculation of correlated response efficiencies between body measurements and the fillet traits. Heritability estimates across ages ranged from 0.05 to 0.5 for height, 0.02 to 0.48 for corrected length (CL), 0.05 to 0.68 for width, 0.08 to 0.57 for fillet weight (FW) and 0.12 to 0.42 for FY. All genetic correlation estimates between body measurements and FW were positive and strong (0.64 to 0.98). The estimates of genetic correlation between body measurements and FY were positive (except for CL at some ages), but weak to moderate (-0.08 to 0.68). These estimates resulted in strong and favorable correlated response efficiencies for FW and positive, but moderate for FY. These results indicate the possibility of achieving indirect genetic gains for FW and by selecting for morphometric traits, but low efficiency for FY when compared with direct selection.

Accounting for dominance to improve genomic evaluations of dairy cows for fertility and milk production traits.

PubMed

Aliloo, Hassan; Pryce, Jennie E; González-Recio, Oscar; Cocks, Benjamin G; Hayes, Ben J

2016-02-01

Dominance effects may contribute to genetic variation of complex traits in dairy cattle, especially for traits closely related to fitness such as fertility. However, traditional genetic evaluations generally ignore dominance effects and consider additive genetic effects only. Availability of dense single nucleotide polymorphisms (SNPs) panels provides the opportunity to investigate the role of dominance in quantitative variation of complex traits at both the SNP and animal levels. Including dominance effects in the genomic evaluation of animals could also help to increase the accuracy of prediction of future phenotypes. In this study, we estimated additive and dominance variance components for fertility and milk production traits of genotyped Holstein and Jersey cows in Australia. The predictive abilities of a model that accounts for additive effects only (additive), and a model that accounts for both additive and dominance effects (additive + dominance) were compared in a fivefold cross-validation. Estimates of the proportion of dominance variation relative to phenotypic variation that is captured by SNPs, for production traits, were up to 3.8 and 7.1 % in Holstein and Jersey cows, respectively, whereas, for fertility, they were equal to 1.2 % in Holstein and very close to zero in Jersey cows. We found that including dominance in the model was not consistently advantageous. Based on maximum likelihood ratio tests, the additive + dominance model fitted the data better than the additive model, for milk, fat and protein yields in both breeds. However, regarding the prediction of phenotypes assessed with fivefold cross-validation, including dominance effects in the model improved accuracy only for fat yield in Holstein cows. Regression coefficients of phenotypes on genetic values and mean squared errors of predictions showed that the predictive ability of the additive + dominance model was superior to that of the additive model for some of the traits. In both breeds, dominance effects were significant (P < 0.01) for all milk production traits but not for fertility. Accuracy of prediction of phenotypes was slightly increased by including dominance effects in the genomic evaluation model. Thus, it can help to better identify highly performing individuals and be useful for culling decisions.

Multiple OPR genes influence personality traits in substance dependent and healthy subjects in two American populations

PubMed Central

Luo, Xingguang; Zuo, Lingjun; Kranzler, Henry; Zhang, Huiping; Wang, Shuang; Gelernter, Joel

2011-01-01

Background Personality traits are among the most complex quantitative traits. Certain personality traits are associated with substance dependence (SD); genetic factors may influence both. Associations between opioid receptor (OPR) genes and SD have been reported. This study investigated the relationship between OPR genes and personality traits in a case-control sample. Methods We assessed dimensions of the five-factor model of personality in 556 subjects: 250 with SD [181 European-Americans (EAs) and 69 African-Americans (AAs)] and 306 healthy subjects (266 EAs and 40 AAs). We genotyped 20 OPRM1 markers, 8 OPRD1 markers, and 7 OPRK1 markers, and 38 unlinked ancestry-informative markers in these subjects. The relationships between OPR genes and personality traits were examined using MANCOVA, controlling for gene-gene interaction effects and potential confounders. Associations were decomposed by Roy-Bargmann Stepdown ANCOVA. Results Personality traits were associated as main or interaction effects with the haplotypes, diplotypes, alleles and genotypes at the three OPR genes (0.002

The pain of a model in the personality of an onlooker: influence of state-reactivity and personality traits on embodied empathy for pain.

PubMed

Avenanti, Alessio; Minio-Paluello, Ilaria; Bufalari, Ilaria; Aglioti, Salvatore M

2009-01-01

The study of inter-individual differences at behavioural and neural levels represents a new avenue for neuroscience. The response to socio-emotional stimuli varies greatly across individuals. For example, identification with the feelings of a movie character may be total for some people or virtually absent for others. Inter-individual differences may reflect both the on-line effect (state) of the observed stimuli and more stable personal characteristics (trait). Here we show that somatomotor mirror responses when viewing others' pain are modulated by both state- and trait-differences in empathy. We recorded motor-evoked potentials (MEPs) induced by Transcranial Magnetic Stimulation (TMS) in healthy individuals observing needles penetrating a model's hand. We found a reduction of corticospinal excitability that was specific for the muscle that subjects observed being penetrated. This inhibition correlated with sensory qualities of the pain ascribed to the model. Moreover, it was greater in subjects with high trait-cognitive empathy and lower in subjects with high trait-personal distress and in those with high aversion for the observed movies. Results indicate that somatomotor responses to others' pain are influenced by specific onlookers' personality traits and self-oriented emotional reactions. Our findings suggest that multiple distinct mechanisms shape mirror mapping of others' pain.

Using genetic markers to orient the edges in quantitative trait networks: the NEO software.

PubMed

Aten, Jason E; Fuller, Tova F; Lusis, Aldons J; Horvath, Steve

2008-04-15

Systems genetic studies have been used to identify genetic loci that affect transcript abundances and clinical traits such as body weight. The pairwise correlations between gene expression traits and/or clinical traits can be used to define undirected trait networks. Several authors have argued that genetic markers (e.g expression quantitative trait loci, eQTLs) can serve as causal anchors for orienting the edges of a trait network. The availability of hundreds of thousands of genetic markers poses new challenges: how to relate (anchor) traits to multiple genetic markers, how to score the genetic evidence in favor of an edge orientation, and how to weigh the information from multiple markers. We develop and implement Network Edge Orienting (NEO) methods and software that address the challenges of inferring unconfounded and directed gene networks from microarray-derived gene expression data by integrating mRNA levels with genetic marker data and Structural Equation Model (SEM) comparisons. The NEO software implements several manual and automatic methods for incorporating genetic information to anchor traits. The networks are oriented by considering each edge separately, thus reducing error propagation. To summarize the genetic evidence in favor of a given edge orientation, we propose Local SEM-based Edge Orienting (LEO) scores that compare the fit of several competing causal graphs. SEM fitting indices allow the user to assess local and overall model fit. The NEO software allows the user to carry out a robustness analysis with regard to genetic marker selection. We demonstrate the utility of NEO by recovering known causal relationships in the sterol homeostasis pathway using liver gene expression data from an F2 mouse cross. Further, we use NEO to study the relationship between a disease gene and a biologically important gene co-expression module in liver tissue. The NEO software can be used to orient the edges of gene co-expression networks or quantitative trait networks if the edges can be anchored to genetic marker data. R software tutorials, data, and supplementary material can be downloaded from: http://www.genetics.ucla.edu/labs/horvath/aten/NEO.

Effects of selection for blood serum IGF-I concentration on reproductive performance of female Angus beef cattle.

PubMed

Zhang, X; Davis, M E; Moeller, S J; Ottobre, J S

2013-09-01

Reproductive performance of animals affects lifetime productivity. However, improvement of reproductive traits via direct selection is generally slow due to low heritability. Therefore, identification of indicator traits for reproductive performance may enhance genetic response. Previous studies showed that serum IGF-I concentration is a candidate indicator for growth and reproductive traits. The objective of our study was to estimate the variances or covariances of IGF-I concentration with reproductive traits. Data were collected from a divergent selection experiment for serum IGF-I concentration at the Eastern Agricultural Research Station owned by The Ohio State University. The study included a total of 2,662 calves in the 1989 to 2005 calf crops. Variance or covariance components were estimated for direct and maternal genetic effects, maternal environment effects, environment effects, and phenotypic effects using an animal model in a multiple-trait, derivative-free, restricted maximum likelihood (MTDFREML, Boldman et al., 1995) computer program. Direct additive genetic correlations suggest that selection for greater IGF-I concentration (heritability = 0.50 ± 0.07) could lead to increased conception rate (heritability = 0.11 ± 0.06, r = 0.32, P < 0.001) and calving rate (heritability = 0.13 ± 0.06, r = 0.43, P < 0.001) and decreased age at first calving in heifers (heritability = 0.35 ± 0.20, r = -0.40, P < 0.001).

Measurement and control of bias in patient reported outcomes using multidimensional item response theory.

PubMed

Dowling, N Maritza; Bolt, Daniel M; Deng, Sien; Li, Chenxi

2016-05-26

Patient-reported outcome (PRO) measures play a key role in the advancement of patient-centered care research. The accuracy of inferences, relevance of predictions, and the true nature of the associations made with PRO data depend on the validity of these measures. Errors inherent to self-report measures can seriously bias the estimation of constructs assessed by the scale. A well-documented disadvantage of self-report measures is their sensitivity to response style (RS) effects such as the respondent's tendency to select the extremes of a rating scale. Although the biasing effect of extreme responding on constructs measured by self-reported tools has been widely acknowledged and studied across disciplines, little attention has been given to the development and systematic application of methodologies to assess and control for this effect in PRO measures. We review the methodological approaches that have been proposed to study extreme RS effects (ERS). We applied a multidimensional item response theory model to simultaneously estimate and correct for the impact of ERS on trait estimation in a PRO instrument. Model estimates were used to study the biasing effects of ERS on sum scores for individuals with the same amount of the targeted trait but different levels of ERS. We evaluated the effect of joint estimation of multiple scales and ERS on trait estimates and demonstrated the biasing effects of ERS on these trait estimates when used as explanatory variables. A four-dimensional model accounting for ERS bias provided a better fit to the response data. Increasing levels of ERS showed bias in total scores as a function of trait estimates. The effect of ERS was greater when the pattern of extreme responding was the same across multiple scales modeled jointly. The estimated item category intercepts provided evidence of content independent category selection. Uncorrected trait estimates used as explanatory variables in prediction models showed downward bias. A comprehensive evaluation of the psychometric quality and soundness of PRO assessment measures should incorporate the study of ERS as a potential nuisance dimension affecting the accuracy and validity of scores and the impact of PRO data in clinical research and decision making.

Predictors of psychological distress after diagnosis in breast cancer patients and patients with benign breast problems.

PubMed

Ando, Noriko; Iwamitsu, Yumi; Kuranami, Masaru; Okazaki, Shigemi; Nakatani, Yuki; Yamamoto, Kenji; Watanabe, Masahiko; Miyaoka, Hitoshi

2011-01-01

The objective of this study was to determine how age and psychological characteristics assessed prior to diagnosis could predict psychological distress in outpatients immediately after disclosure of their diagnosis. This is a longitudinal and prospective study, and participants were breast cancer patients and patients with benign breast problems (BBP). Patients were asked to complete questionnaires to determine levels of the following: trait anxiety (State-Trait Anxiety Inventory), negative emotional suppression (Courtauld Emotional Control Scale), life stress events (Life Experiences Survey), and psychological distress (Profile of Mood Status) prior to diagnosis. They were asked to complete a questionnaire measuring psychological distress after being told their diagnosis. We analyzed a total of 38 women diagnosed with breast cancer and 95 women diagnosed with a BBP. A two-way analysis of variance (prior to, after diagnosis × cancer, benign) showed that psychological distress after diagnosis among breast cancer patients was significantly higher than in patients with a BBP. The multiple regression model accounted for a significant amount of variance in the breast cancer group (model adjusted R(2) = 0.545, p < 0.001), and only trait anxiety was statistically significant (β = 0.778, p < 0.001). In the BBP group, the multiple regression analysis yielded a significant result (model adjusted R(2) = 0.462, p < 0.001), with trait anxiety and negative life changes as statistically significant factors (β = 0.449 and 0.324 respectively; p < 0.01). In both groups, trait anxiety assessed prior to diagnosis was the significant predictor of psychological distress after diagnosis, and might have prospects as a screening method for psychologically vulnerable women. Copyright © 2011 The Academy of Psychosomatic Medicine. Published by Elsevier Inc. All rights reserved.

Ecogeography, genetics, and the evolution of human body form.

PubMed

Roseman, Charles C; Auerbach, Benjamin M

2015-01-01

Genetic resemblances among groups are non-randomly distributed in humans. This population structure may influence the correlations between traits and environmental drivers of natural selection thus complicating the interpretation of the fossil record when modern human variation is used as a referential model. In this paper, we examine the effects of population structure and natural selection on postcranial traits that reflect body size and shape with application to the more general issue of how climate - using latitude as a proxy - has influenced hominin morphological variation. We compare models that include terms reflecting population structure, ascertained from globally distributed microsatellite data, and latitude on postcranial phenotypes derived from skeletal dimensions taken from a large global sample of modern humans. We find that models with a population structure term fit better than a model of natural selection along a latitudinal cline in all cases. A model including both latitude and population structure terms is a good fit to distal limb element lengths and bi-iliac breadth, indicating that multiple evolutionary forces shaped these morphologies. In contrast, a model that included only a population structure term best explained femoral head diameter and the crural index. The results demonstrate that population structure is an important part of human postcranial variation, and that clinally distributed natural selection is not sufficient to explain among-group differentiation. The distribution of human body form is strongly influenced by the contingencies of modern human origins, which calls for new ways to approach problems in the evolution of human variation, past and present. Copyright © 2014 Elsevier Ltd. All rights reserved.

The influence of emotional intelligence (EI) on coping and mental health in adolescence: divergent roles for trait and ability EI.

PubMed

Davis, Sarah K; Humphrey, Neil

2012-10-01

Theoretically, trait and ability emotional intelligence (EI) should mobilise coping processes to promote adaptation, plausibly operating as personal resources determining choice and/or implementation of coping style. However, there is a dearth of research deconstructing if/how EI impacts mental health via multiple coping strategies in adolescence. Using path analysis, the current study specified a series of multiple-mediation and conditional effects models to systematically explore interrelations between coping, EI, depression and disruptive behaviour in 748 adolescents (mean age = 13.52 years; SD = 1.22). Results indicated that whilst ability EI influences mental health via flexible selection of coping strategies, trait EI modifies coping effectiveness; specifically, high levels of trait EI amplify the beneficial effects of active coping and minimise the effects of avoidant coping to reduce symptomotology. However, effects were selective with respect to coping style and outcome. Implications for interventions are discussed alongside directions for future research. Copyright © 2012 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

IRT-ZIP Modeling for Multivariate Zero-Inflated Count Data

ERIC Educational Resources Information Center

Wang, Lijuan

2010-01-01

This study introduces an item response theory-zero-inflated Poisson (IRT-ZIP) model to investigate psychometric properties of multiple items and predict individuals' latent trait scores for multivariate zero-inflated count data. In the model, two link functions are used to capture two processes of the zero-inflated count data. Item parameters are…

Eco-genetic modeling of contemporary life-history evolution.

PubMed

Dunlop, Erin S; Heino, Mikko; Dieckmann, Ulf

2009-10-01

We present eco-genetic modeling as a flexible tool for exploring the course and rates of multi-trait life-history evolution in natural populations. We build on existing modeling approaches by combining features that facilitate studying the ecological and evolutionary dynamics of realistically structured populations. In particular, the joint consideration of age and size structure enables the analysis of phenotypically plastic populations with more than a single growth trajectory, and ecological feedback is readily included in the form of density dependence and frequency dependence. Stochasticity and life-history trade-offs can also be implemented. Critically, eco-genetic models permit the incorporation of salient genetic detail such as a population's genetic variances and covariances and the corresponding heritabilities, as well as the probabilistic inheritance and phenotypic expression of quantitative traits. These inclusions are crucial for predicting rates of evolutionary change on both contemporary and longer timescales. An eco-genetic model can be tightly coupled with empirical data and therefore may have considerable practical relevance, in terms of generating testable predictions and evaluating alternative management measures. To illustrate the utility of these models, we present as an example an eco-genetic model used to study harvest-induced evolution of multiple traits in Atlantic cod. The predictions of our model (most notably that harvesting induces a genetic reduction in age and size at maturation, an increase or decrease in growth capacity depending on the minimum-length limit, and an increase in reproductive investment) are corroborated by patterns observed in wild populations. The predicted genetic changes occur together with plastic changes that could phenotypically mask the former. Importantly, our analysis predicts that evolutionary changes show little signs of reversal following a harvest moratorium. This illustrates how predictions offered by eco-genetic models can enable and guide evolutionarily sustainable resource management.

Pregnant women with the sickle cell trait are not at increased risk for developing preeclampsia.

PubMed

Stamilio, David M; Sehdev, Harish M; Macones, George A

2003-01-01

The primary objective of this study was to determine whether having the sickle cell trait is independently associated with preeclampsia. We performed a retrospective cohort study of 1998 pregnant patients who either did or did not have the sickle cell trait. All patients were screened for the sickle trait using the "Sickledex" test. Data on neonatal and maternal outcome, including preeclampsia, and potential confounding variables were abstracted from medical records. Unadjusted, stratified, and multiple logistic regression analyses were used to identify interactions, and confounding between multiple variables and the association between sickle cell trait and preeclampsia. With an anticipated 6.5% rate of preeclampsia, and alpha = 0.05, this cohort study has 80% power to detect a relative risk (RR) of 2.3 for preeclampsia. Univariate analysis revealed that the two cohorts were similar with regard to primiparity, maternal age, chronic diseases, birth weight, and gestational age at delivery, but the sickle cell trait cohort was more likely to have gestational diabetes and had a higher mean body mass index (BMI). In the univariate analysis, the sickle cell trait cohort was not at increased risk for preeclampsia [unadjusted RR = 0.5, 95% CI (0.2-1.6)]. After controlling for potential confounding variables with logistic regression analysis, sickle trait was not independently associated with preeclampsia [adjusted RR = 0.5, 95% CI (0.2- 1.6)]. In contrast to prior work, these data suggest that the sickle cell trait is not an independent risk factor for preeclampsia or postpartum complications. In fact, the data are more consistent with the sickle trait being protective for developing preeclampsia.

Heritabilities and genetic correlations in the same traits across different strata of herds created according to continuous genomic, genetic, and phenotypic descriptors.

PubMed

Yin, Tong; König, Sven

2018-03-01

The most common approach in dairy cattle to prove genotype by environment interactions is a multiple-trait model application, and considering the same traits in different environments as different traits. We enhanced such concepts by defining continuous phenotypic, genetic, and genomic herd descriptors, and applying random regression sire models. Traits of interest were test-day traits for milk yield, fat percentage, protein percentage, and somatic cell score, considering 267,393 records from 32,707 first-lactation Holstein cows. Cows were born in the years 2010 to 2013, and kept in 52 large-scale herds from 2 federal states of north-east Germany. The average number of genotyped cows per herd (45,613 single nucleotide polymorphism markers per cow) was 133.5 (range: 45 to 415 genotyped cows). Genomic herd descriptors were (1) the level of linkage disequilibrium (r 2 ) within specific chromosome segments, and (2) the average allele frequency for single nucleotide polymorphisms in close distance to a functional mutation. Genetic herd descriptors were the (1) intra-herd inbreeding coefficient, and (2) the percentage of daughters from foreign sires. Phenotypic herd descriptors were (1) herd size, and (2) the herd mean for nonreturn rate. Most correlations among herd descriptors were close to 0, indicating independence of genomic, genetic, and phenotypic characteristics. Heritabilities for milk yield increased with increasing intra-herd linkage disequilibrium, inbreeding, and herd size. Genetic correlations in same traits between adjacent levels of herd descriptors were close to 1, but declined for descriptor levels in greater distance. Genetic correlation declines were more obvious for somatic cell score, compared with test-day traits with larger heritabilities (fat percentage and protein percentage). Also, for milk yield, alterations of herd descriptor levels had an obvious effect on heritabilities and genetic correlations. By trend, multiple trait model results (based on created discrete herd classes) confirmed the random regression estimates. Identified alterations of breeding values in dependency of herd descriptors suggest utilization of specific sires for specific herd structures, offering new possibilities to improve sire selection strategies. Regarding genomic selection designs and genetic gain transfer into commercial herds, cow herds for the utilization in cow training sets should reflect the genomic, genetic, and phenotypic pattern of the broad population. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Childhood Maltreatment as Predictor of Pathological Personality Traits Using PSY-5 in an Adult Psychiatric Sample.

PubMed

Choi, Ji Young; Park, Soo Hyun

2018-02-01

Extant literature indicates that childhood maltreatment is significantly associated with personality disorders. With the recent call for a more dimensional approach to understanding personality and pathological personality traits, the aim of the present study was to examine whether the experience of childhood maltreatment is associated with pathological personality traits as measured by the Personality Psychopathology Five (PSY-5). We analyzed data from 557 adult psychiatric patients with diverse psychiatric diagnoses, including mood disorders, schizophrenia spectrum disorders, and anxiety disorders. Hierarchical multiple regression analyses were conducted to determine the degree to which childhood maltreatment explained the five trait dimensions after controlling for demographic variables, presence of psychotic symptoms, and degree of depressive symptoms. Childhood maltreatment significantly predicted all of the five trait dimensions of the PSY-5. This suggests that childhood maltreatment may negatively affect the development of an adaptive adjustment system, thereby potentially contributing to the emergence of pathological personality traits.

Cardiomyopathies in Noonan syndrome and the other RASopathies

PubMed Central

Gelb, Bruce D.; Roberts, Amy E.; Tartaglia, Marco

2015-01-01

Noonan syndrome and related disorders (Noonan syndrome with multiple lentigines, Costello syndrome, cardiofaciocutaneous syndrome, Noonan syndrome with loose anagen hair, and other related traits) are autosomal dominant traits. Mutations causing these disorders alter proteins relevant for signaling through RAS. Thus, these traits are now collectively called the RASopathies. While the RASopathies have pleiomorphic features, this review will focus on the hypertrophic cardiomyopathy observed in varying percentages of all of these traits. In addition, inherited abnormalities in one pathway gene, RAF1, cause pediatric-onset dilated cardiomyopathy. The pathogeneses for the RASopathy-associated cardiomyopathies are being elucidated, principally using animal models, leading to genotype-specific insights into how signal transduction is perturbed. Based on those findings, small molecule therapies seem possible for RASopathy-associated cardiomyopathies. PMID:26380542

The genetic links between the big five personality traits and general interest domains.

PubMed

Kandler, Christian; Bleidorn, Wiebke; Riemann, Rainer; Angleitner, Alois; Spinath, Frank M

2011-12-01

This is the first genetically informative study in which multiple informants were used to quantify the genetic and environmental sources of individual differences in general interests as well as the phenotypic and genetic links between general interests and Big Five personality traits. Self-reports and two peer ratings from 844 individuals, including 225 monozygotic and 113 dizygotic complete twin pairs, were collected. Multiple-rater scores (composites) revealed that the averaged levels of genetic and environmental effects on seven broad interest domains were similar to those on personality traits. Multivariate analyses showed that about 35% of the genetic and 9% of the environmental variance in interests were explained by personality domains, in particular by Openness. The findings suggest that interests cannot easily be considered as a byproduct of the interactions between personality genotypes and the environmental influences but rather as an internal regulation of behavior with an own genetic basis.

Improved Genetic Profiling of Anthropometric Traits Using a Big Data Approach.

PubMed

Canela-Xandri, Oriol; Rawlik, Konrad; Woolliams, John A; Tenesa, Albert

2016-01-01

Genome-wide association studies (GWAS) promised to translate their findings into clinically beneficial improvements of patient management by tailoring disease management to the individual through the prediction of disease risk. However, the ability to translate genetic findings from GWAS into predictive tools that are of clinical utility and which may inform clinical practice has, so far, been encouraging but limited. Here we propose to use a more powerful statistical approach, the use of which has traditionally been limited due to computational requirements and lack of sufficiently large individual level genotyped cohorts, but which improve the prediction of multiple medically relevant phenotypes using the same panel of SNPs. As a proof of principle, we used a shared panel of 319,038 common SNPs with MAF > 0.05 to train the prediction models in 114,264 unrelated White-British individuals for height and four obesity related traits (body mass index, basal metabolic rate, body fat percentage, and waist-to-hip ratio). We obtained prediction accuracies that ranged between 46% and 75% of the maximum achievable given the captured heritable component. For height, this represents an improvement in prediction accuracy of up to 68% (184% more phenotypic variance explained) over SNPs reported to be robustly associated with height in a previous GWAS meta-analysis of similar size. Across-population predictions in White non-British individuals were similar to those in White-British whilst those in Asian and Black individuals were informative but less accurate. We estimate that the genotyping of circa 500,000 unrelated individuals will yield predictions between 66% and 82% of the SNP-heritability captured by common variants in our array. Prediction accuracies did not improve when including rarer SNPs or when fitting multiple traits jointly in multivariate models.

Functional linear models for association analysis of quantitative traits.

PubMed

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

2013-11-01

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

Protective personality traits: High openness and low neuroticism linked to better memory in multiple sclerosis.

PubMed

Leavitt, Victoria M; Buyukturkoglu, Korhan; Inglese, Matilde; Sumowski, James F

2017-11-01

Memory impairment in multiple sclerosis (MS) is common, although few risk/protective factors are known. To examine relationships of personality to memory/non-memory cognition in MS. 80 patients completed a cognitive battery and a personality scale measuring the "Big 5" traits: openness, neuroticism, agreeableness, extraversion, and conscientiousness. Memory was most related to openness, with higher openness linked to better memory and lower risk for memory impairment, controlling for age, atrophy, education, and intelligence quotient (IQ). Lower neuroticism was also related to better memory, and lower conscientiousness to memory impairment. Non-memory cognition was unrelated to personality. Personality may inform predictive models of memory impairment in MS.

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

PubMed

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

2015-09-01

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

Prediction of bovine milk technological traits from mid-infrared spectroscopy analysis in dairy cows.

PubMed

Visentin, G; McDermott, A; McParland, S; Berry, D P; Kenny, O A; Brodkorb, A; Fenelon, M A; De Marchi, M

2015-09-01

Rapid, cost-effective monitoring of milk technological traits is a significant challenge for dairy industries specialized in cheese manufacturing. The objective of the present study was to investigate the ability of mid-infrared spectroscopy to predict rennet coagulation time, curd-firming time, curd firmness at 30 and 60min after rennet addition, heat coagulation time, casein micelle size, and pH in cow milk samples, and to quantify associations between these milk technological traits and conventional milk quality traits. Samples (n=713) were collected from 605 cows from multiple herds; the samples represented multiple breeds, stages of lactation, parities, and milking times. Reference analyses were undertaken in accordance with standardized methods, and mid-infrared spectra in the range of 900 to 5,000cm(-1) were available for all samples. Prediction models were developed using partial least squares regression, and prediction accuracy was based on both cross and external validation. The proportion of variance explained by the prediction models in external validation was greatest for pH (71%), followed by rennet coagulation time (55%) and milk heat coagulation time (46%). Models to predict curd firmness 60min from rennet addition and casein micelle size, however, were poor, explaining only 25 and 13%, respectively, of the total variance in each trait within external validation. On average, all prediction models tended to be unbiased. The linear regression coefficient of the reference value on the predicted value varied from 0.17 (casein micelle size regression model) to 0.83 (pH regression model) but all differed from 1. The ratio performance deviation of 1.07 (casein micelle size prediction model) to 1.79 (pH prediction model) for all prediction models in the external validation was <2, suggesting that none of the prediction models could be used for analytical purposes. With the exception of casein micelle size and curd firmness at 60min after rennet addition, the developed prediction models may be useful as a screening method, because the concordance correlation coefficient ranged from 0.63 (heat coagulation time prediction model) to 0.84 (pH prediction model) in the external validation. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Genetic parameters of ovarian and uterine reproductive traits in dairy cows.

PubMed

Carthy, T R; Ryan, D P; Fitzgerald, A M; Evans, R D; Berry, D P

2015-06-01

The objective of the study was to estimate genetic parameters of detailed reproductive traits derived from ultrasound examination of the reproductive tract as well as their genetic correlations with traditional reproductive traits. A total of 226,141 calving and insemination records as well as 74,134 ultrasound records from Irish dairy cows were used. Traditional reproductive traits included postpartum interval to first service, conception, and next calving, as well as the interval from first to last service; number of inseminations, pregnancy rate to first service, pregnant within 42 d of the herd breeding season, and submission in the first 21 d of the herd breeding season were also available. Detailed reproductive traits included resumed cyclicity at the time of ultrasound examination, incidence of multiple ovulations, incidence of early postpartum ovulation, heat detection, ovarian cystic structures, embryo loss, and uterine score; the latter was a subjectively assessed on a scale of 1 (little fluid with normal uterine tone) to 4 (large quantity of fluid with a flaccid uterine tone). Variance (and covariance) components were estimated using repeatability animal linear mixed models. Heritability for all reproductive traits were generally low (0.001-0.05), with the exception of traits related to cyclicity postpartum, regardless if defined traditionally (0.07; calving to first service) or from ultrasound examination [resumed cyclicity at the time of examination (0.07) or early postpartum ovulation (0.10)]. The genetic correlations among the detailed reproductive traits were generally favorable. The exception was the genetic correlation (0.29) between resumed cyclicity and uterine score; superior genetic merit for cyclicity postpartum was associated with inferior uterine score. Superior genetic merit for most traditional reproductive traits was associated with superior genetic merit for resumed cyclicity (genetic correlations ranged from -0.59 to -0.36 and from 0.56 to 0.70) and uterine score (genetic correlations ranged from -0.47 to 0.32 and from 0.25 to 0.52). Genetic predisposition to an increased incidence of embryo loss was associated with both an inferior uterine score (0.24) and inferior genetic merit for traditional reproductive traits (genetic correlations ranged from -0.52 to -0.42 and from 0.33 to 0.80). The results from the present study indicate that selection based on traditional reproductive traits, such as calving interval or days open, resulted in improved genetic merit of all the detailed reproductive traits evaluated in this study. Additionally, greater accuracy of selection for calving interval is expected for a relatively small progeny group size when detailed reproductive traits are included in a multitrait genetic evaluation. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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

PubMed Central

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

2016-01-01

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

Computational strategies for alternative single-step Bayesian regression models with large numbers of genotyped and non-genotyped animals.

PubMed

Fernando, Rohan L; Cheng, Hao; Golden, Bruce L; Garrick, Dorian J

2016-12-08

Two types of models have been used for single-step genomic prediction and genome-wide association studies that include phenotypes from both genotyped animals and their non-genotyped relatives. The two types are breeding value models (BVM) that fit breeding values explicitly and marker effects models (MEM) that express the breeding values in terms of the effects of observed or imputed genotypes. MEM can accommodate a wider class of analyses, including variable selection or mixture model analyses. The order of the equations that need to be solved and the inverses required in their construction vary widely, and thus the computational effort required depends upon the size of the pedigree, the number of genotyped animals and the number of loci. We present computational strategies to avoid storing large, dense blocks of the MME that involve imputed genotypes. Furthermore, we present a hybrid model that fits a MEM for animals with observed genotypes and a BVM for those without genotypes. The hybrid model is computationally attractive for pedigree files containing millions of animals with a large proportion of those being genotyped. We demonstrate the practicality on both the original MEM and the hybrid model using real data with 6,179,960 animals in the pedigree with 4,934,101 phenotypes and 31,453 animals genotyped at 40,214 informative loci. To complete a single-trait analysis on a desk-top computer with four graphics cards required about 3 h using the hybrid model to obtain both preconditioned conjugate gradient solutions and 42,000 Markov chain Monte-Carlo (MCMC) samples of breeding values, which allowed making inferences from posterior means, variances and covariances. The MCMC sampling required one quarter of the effort when the hybrid model was used compared to the published MEM. We present a hybrid model that fits a MEM for animals with genotypes and a BVM for those without genotypes. Its practicality and considerable reduction in computing effort was demonstrated. This model can readily be extended to accommodate multiple traits, multiple breeds, maternal effects, and additional random effects such as polygenic residual effects.

Collective-efficacy as a mediator of the relationship of leaders' personality traits and team performance: A cross-level analysis.

PubMed

Li, Xiaoshan; Zhou, Mingjie; Zhao, Na; Zhang, Shanshan; Zhang, Jianxin

2015-06-01

The relationship between a leader's personality and his team's performance has been established in organisational research, but the underlying process and mechanism responsible for this effect have not been fully explored. Both the traditional multiple linear regression and the multilevel structural equation model approaches were used in this study to test a proposed mediating model of subordinates' perception of collective efficacy between leader personality and team performance. The results show that the team leader's extraversion and conscientiousness personality traits were related positively to both the team-average (individual) perception of collective efficacy and team performance, and the collective efficacy mediated the relationship of the leader's personality traits and team performance. This study also discusses how Chinese cultural elements play a role in such a mediating model. © 2014 International Union of Psychological Science.

The Effect of Small Sample Size on Measurement Equivalence of Psychometric Questionnaires in MIMIC Model: A Simulation Study.

PubMed

Jamali, Jamshid; Ayatollahi, Seyyed Mohammad Taghi; Jafari, Peyman

2017-01-01

Evaluating measurement equivalence (also known as differential item functioning (DIF)) is an important part of the process of validating psychometric questionnaires. This study aimed at evaluating the multiple indicators multiple causes (MIMIC) model for DIF detection when latent construct distribution is nonnormal and the focal group sample size is small. In this simulation-based study, Type I error rates and power of MIMIC model for detecting uniform-DIF were investigated under different combinations of reference to focal group sample size ratio, magnitude of the uniform-DIF effect, scale length, the number of response categories, and latent trait distribution. Moderate and high skewness in the latent trait distribution led to a decrease of 0.33% and 0.47% power of MIMIC model for detecting uniform-DIF, respectively. The findings indicated that, by increasing the scale length, the number of response categories and magnitude DIF improved the power of MIMIC model, by 3.47%, 4.83%, and 20.35%, respectively; it also decreased Type I error of MIMIC approach by 2.81%, 5.66%, and 0.04%, respectively. This study revealed that power of MIMIC model was at an acceptable level when latent trait distributions were skewed. However, empirical Type I error rate was slightly greater than nominal significance level. Consequently, the MIMIC was recommended for detection of uniform-DIF when latent construct distribution is nonnormal and the focal group sample size is small.

The Effect of Small Sample Size on Measurement Equivalence of Psychometric Questionnaires in MIMIC Model: A Simulation Study

PubMed Central

Jafari, Peyman

2017-01-01

Evaluating measurement equivalence (also known as differential item functioning (DIF)) is an important part of the process of validating psychometric questionnaires. This study aimed at evaluating the multiple indicators multiple causes (MIMIC) model for DIF detection when latent construct distribution is nonnormal and the focal group sample size is small. In this simulation-based study, Type I error rates and power of MIMIC model for detecting uniform-DIF were investigated under different combinations of reference to focal group sample size ratio, magnitude of the uniform-DIF effect, scale length, the number of response categories, and latent trait distribution. Moderate and high skewness in the latent trait distribution led to a decrease of 0.33% and 0.47% power of MIMIC model for detecting uniform-DIF, respectively. The findings indicated that, by increasing the scale length, the number of response categories and magnitude DIF improved the power of MIMIC model, by 3.47%, 4.83%, and 20.35%, respectively; it also decreased Type I error of MIMIC approach by 2.81%, 5.66%, and 0.04%, respectively. This study revealed that power of MIMIC model was at an acceptable level when latent trait distributions were skewed. However, empirical Type I error rate was slightly greater than nominal significance level. Consequently, the MIMIC was recommended for detection of uniform-DIF when latent construct distribution is nonnormal and the focal group sample size is small. PMID:28713828

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.

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.

Detection of epistatic effects with logic regression and a classical linear regression model.

PubMed

Malina, Magdalena; Ickstadt, Katja; Schwender, Holger; Posch, Martin; Bogdan, Małgorzata

2014-02-01

To locate multiple interacting quantitative trait loci (QTL) influencing a trait of interest within experimental populations, usually methods as the Cockerham's model are applied. Within this framework, interactions are understood as the part of the joined effect of several genes which cannot be explained as the sum of their additive effects. However, if a change in the phenotype (as disease) is caused by Boolean combinations of genotypes of several QTLs, this Cockerham's approach is often not capable to identify them properly. To detect such interactions more efficiently, we propose a logic regression framework. Even though with the logic regression approach a larger number of models has to be considered (requiring more stringent multiple testing correction) the efficient representation of higher order logic interactions in logic regression models leads to a significant increase of power to detect such interactions as compared to a Cockerham's approach. The increase in power is demonstrated analytically for a simple two-way interaction model and illustrated in more complex settings with simulation study and real data analysis.

Breeding for better eye health in Finnish blue fox (Vulpes lagopus).

PubMed

Kempe, R; Strandén, I

2016-02-01

The frequency of eye infections in the Finnish blue fox population has increased during the past decade. Eye infection may incur economic losses to producers due to reduced selection intensity, but ethical aspects need to be considered as well because eye infection can be quite painful and reduce animal well-being. The purpose of this study was to determine the potential for genetic selection against susceptibility to eye infection. The data were collected from 2076 blue foxes at the MTT fur animal research station. Genetic parameters were estimated using single- and multiple-trait animal models. The heritability estimate for eye infection was analysed as a binary trait (EYE) and was moderate (0.24 ± 0.07). EYE had a moderate antagonistic genetic correlation (-0.49 ± 0.20) with grading density (thick underfur). The genetic correlation of EYE with grading size or body condition score was estimated without precision, but all size traits had a low antagonistic phenotypic correlation with EYE. Our results suggest that there is genetic variance in susceptibility to EYE, indicating that eye health can be improved through selection. The current recommendation is that the sick animals should be culled immediately. If more efficient selection is needed, the selection index and multiple-trait animal models can be applied in breeding for better eye health. © 2015 Blackwell Verlag GmbH.

Inter- and intraspecific variation in leaf economic traits in wheat and maize.

PubMed

Martin, Adam R; Hale, Christine E; Cerabolini, Bruno E L; Cornelissen, Johannes H C; Craine, Joseph; Gough, William A; Kattge, Jens; Tirona, Cairan K F

2018-02-01

Leaf Economics Spectrum (LES) trait variation underpins multiple agroecological processes and many prominent crop yield models. While there are numerous independent studies assessing trait variation in crops, to date there have been no comprehensive assessments of intraspecific trait variation (ITV) in LES traits for wheat and maize: the world's most widespread crops. Using trait databases and peer-reviewed literature, we compiled over 700 records of specific leaf area (SLA), maximum photosynthetic rates ( A max ) and leaf nitrogen (N) concentrations, for wheat and maize. We evaluated intraspecific LES trait variation, and intraspecific trait-environment relationships. While wheat and maize occupy the upper 90th percentile of LES trait values observed across a global species pool, ITV ranged widely across the LES in wheat and maize. Fertilization treatments had strong impacts on leaf N, while plant developmental stage (here standardized as the number of days since planting) had strong impacts on A max ; days since planting, N fertilization and irrigation all influenced SLA. When controlling for these factors, intraspecific responses to temperature and precipitation explained 39.4 and 43.7 % of the variation in A max and SLA, respectively, but only 5.4 % of the variation in leaf N. Despite a long history of domestication in these species, ITV in wheat and maize among and within cultivars remains large. Intraspecific trait variation is a critical consideration to refine regional to global models of agroecosystem structure, function and food security. Considerable opportunities and benefits exist for consolidating a crop trait database for a wider range of domesticated plant species.

An experimental test of fitness variation across a hydrologic gradient predicts willow and poplar species distributions.

PubMed

Wei, Xiaojing; Savage, Jessica A; Riggs, Charlotte E; Cavender-Bares, Jeannine

2017-05-01

Environmental filtering is an important community assembly process influencing species distributions. Contrasting species abundance patterns along environmental gradients are commonly used to provide evidence for environmental filtering. However, the same abundance patterns may result from alternative or concurrent assembly processes. Experimental tests are an important means to decipher whether species fitness varies with environment, in the absence of dispersal constraints and biotic interactions, and to draw conclusions about the importance of environmental filtering in community assembly. We performed an experimental test of environmental filtering in 14 closely related willow and poplar species (family Salicaceae) by transplanting cuttings of each species into 40 common gardens established along a natural hydrologic gradient in the field, where competition was minimized and herbivory was controlled. We analyzed species fitness responses to the hydrologic environment based on cumulative growth and survival over two years using aster fitness models. We also examined variation in nine drought and flooding tolerance traits expected to contribute to performance based on a priori understanding of plant function in relation to water availability and stress. We found substantial evidence that environmental filtering along the hydrologic gradient played a critical role in determining species distributions. Fitness variation of each species in the field experiment was used to model their water table depth optima. These optima predicted 68% of the variation in species realized hydrologic niches based on peak abundance in naturally assembled communities in the surrounding region. Multiple traits associated with water transport efficiency and water stress tolerance were correlated with species hydrologic niches, but they did not necessarily covary with each other. As a consequence, species occupying similar hydrologic niches had different combinations of trait values. Moreover, individual traits were less phylogenetically conserved than species hydrologic niches and integrated water stress tolerance as determined by multiple traits. We conclude that differential fitness among species along the hydrologic gradient was the consequence of multiple traits associated with water transport and water stress tolerance, expressed in different combinations by different species. Varying environmental tolerance, in turn, played a critical role in driving niche segregation among close relatives along the hydrologic gradient. © 2017 by the Ecological Society of America.

Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes.

PubMed

Borquis, Rusbel Raul Aspilcueta; Neto, Francisco Ribeiro de Araujo; Baldi, Fernando; Hurtado-Lugo, Naudin; de Camargo, Gregório M F; Muñoz-Berrocal, Milthon; Tonhati, Humberto

2013-09-01

In this study, genetic parameters for test-day milk, fat, and protein yield were estimated for the first lactation. The data analyzed consisted of 1,433 first lactations of Murrah buffaloes, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, with calvings from 1985 to 2007. Ten-month classes of lactation days were considered for the test-day yields. The (co)variance components for the 3 traits were estimated using the regression analyses by Bayesian inference applying an animal model by Gibbs sampling. The contemporary groups were defined as herd-year-month of the test day. In the model, the random effects were additive genetic, permanent environment, and residual. The fixed effects were contemporary group and number of milkings (1 or 2), the linear and quadratic effects of the covariable age of the buffalo at calving, as well as the mean lactation curve of the population, which was modeled by orthogonal Legendre polynomials of fourth order. The random effects for the traits studied were modeled by Legendre polynomials of third and fourth order for additive genetic and permanent environment, respectively, the residual variances were modeled considering 4 residual classes. The heritability estimates for the traits were moderate (from 0.21-0.38), with higher estimates in the intermediate lactation phase. The genetic correlation estimates within and among the traits varied from 0.05 to 0.99. The results indicate that the selection for any trait test day will result in an indirect genetic gain for milk, fat, and protein yield in all periods of the lactation curve. The accuracy associated with estimated breeding values obtained using multi-trait random regression was slightly higher (around 8%) compared with single-trait random regression. This difference may be because to the greater amount of information available per animal. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Obsessive, compulsive, and conscientious? The relationship between OCPD and personality traits.

PubMed

Mike, Anissa; King, Hannah; Oltmanns, Thomas F; Jackson, Joshua J

2017-12-22

Obsessive-compulsive personality disorder (OCPD) is defined as being overly controlling, rigid, orderly, and perfectionistic. At a definitional level, OCPD would appear to be highly related to the trait of Conscientiousness. The current study attempts to disentangle this relationship by examining the relationship at a facet level using multiple forms of OCPD assessment and using multiple reports of OCPD and personality. In addition, the relationship between OCPD and each Big Five trait was examined. The study relied on a sample of 1,630 adults who completed self-reports of personality and OCPD. Informants and interviewers also completed reports on the targets. Bifactor models were constructed in order to disentangle variance attributable to each facet and its general factors. Across four sets of analyses, individuals who scored higher on OCPD tended to be more orderly and achievement striving, and more set in their ways, but less generally conscientious. OCPD was also related to select facets under each Big Five trait. Notably, findings indicated that OCPD has a strong interpersonal component and that OCPD tendencies may interfere with one's relationships with others. Findings suggest that OCPD's relationship with personality can be more precisely explained through its relationships with specific tendencies rather than general, higher-order traits. © 2017 Wiley Periodicals, Inc.

Nonparametric evaluation of quantitative traits in population-based association studies when the genetic model is unknown.

PubMed

Konietschke, Frank; Libiger, Ondrej; Hothorn, Ludwig A

2012-01-01

Statistical association between a single nucleotide polymorphism (SNP) genotype and a quantitative trait in genome-wide association studies is usually assessed using a linear regression model, or, in the case of non-normally distributed trait values, using the Kruskal-Wallis test. While linear regression models assume an additive mode of inheritance via equi-distant genotype scores, Kruskal-Wallis test merely tests global differences in trait values associated with the three genotype groups. Both approaches thus exhibit suboptimal power when the underlying inheritance mode is dominant or recessive. Furthermore, these tests do not perform well in the common situations when only a few trait values are available in a rare genotype category (disbalance), or when the values associated with the three genotype categories exhibit unequal variance (variance heterogeneity). We propose a maximum test based on Marcus-type multiple contrast test for relative effect sizes. This test allows model-specific testing of either dominant, additive or recessive mode of inheritance, and it is robust against variance heterogeneity. We show how to obtain mode-specific simultaneous confidence intervals for the relative effect sizes to aid in interpreting the biological relevance of the results. Further, we discuss the use of a related all-pairwise comparisons contrast test with range preserving confidence intervals as an alternative to Kruskal-Wallis heterogeneity test. We applied the proposed maximum test to the Bogalusa Heart Study dataset, and gained a remarkable increase in the power to detect association, particularly for rare genotypes. Our simulation study also demonstrated that the proposed non-parametric tests control family-wise error rate in the presence of non-normality and variance heterogeneity contrary to the standard parametric approaches. We provide a publicly available R library nparcomp that can be used to estimate simultaneous confidence intervals or compatible multiplicity-adjusted p-values associated with the proposed maximum test.

Anger: cause or consequence of posttraumatic stress? A prospective study of Dutch soldiers.

PubMed

Lommen, Miriam J J; Engelhard, Iris M; van de Schoot, Rens; van den Hout, Marcel A

2014-04-01

Many studies have shown that individuals with posttraumatic stress disorder (PTSD) experience more anger over time and across situations (i.e., trait anger) than trauma-exposed individuals without PTSD. There is a lack of prospective research, however, that considers anger levels before trauma exposure. The aim of this study was to prospectively assess the relationship between trait anger and PTSD symptoms, with several known risk factors, including baseline symptoms, neuroticism, and stressor severity in the model. Participants were 249 Dutch soldiers tested approximately 2 months before and approximately 2 months and 9 months after their deployment to Afghanistan. Trait anger and PTSD symptom severity were measured at all assessments. Structural equation modeling including cross-lagged effects showed that higher trait anger before deployment predicted higher PTSD symptoms 2 months after deployment (β = .36), with stressor severity and baseline symptoms in the model, but not with neuroticism in the model. Trait anger at 2 months postdeployment did not predict PTSD symptom severity at 9 months, and PTSD symptom severity 2 months postdeployment did not predict subsequent trait anger scores. Findings suggest that trait anger may be a pretrauma vulnerability factor for PTSD symptoms, but does not add variance beyond the effect of neuroticism. Copyright © 2014 International Society for Traumatic Stress Studies.

Trait contributions to fish community assembly emerge from trophicinteractions in an individual-based model

USGS Publications Warehouse

Giacomini, Henrique C.; DeAngelis, Donald; Trexler, Joel C.; Petrere, Miguel

2013-01-01

Community ecology seeks to understand and predict the characteristics of communities that can develop under different environmental conditions, but most theory has been built on analytical models that are limited in the diversity of species traits that can be considered simultaneously. We address that limitation with an individual-based model to simulate assembly of fish communities characterized by life history and trophic interactions with multiple physiological tradeoffs as constraints on species performance. Simulation experiments were carried out to evaluate the distribution of 6 life history and 4 feeding traits along gradients of resource productivity and prey accessibility. These experiments revealed that traits differ greatly in importance for species sorting along the gradients. Body growth rate emerged as a key factor distinguishing community types and defining patterns of community stability and coexistence, followed by egg size and maximum body size. Dominance by fast-growing, relatively large, and fecund species occurred more frequently in cases where functional responses were saturated (i.e. high productivity and/or prey accessibility). Such dominance was associated with large biomass fluctuations and priority effects, which prevented richness from increasing with productivity and may have limited selection on secondary traits, such as spawning strategies and relative size at maturation. Our results illustrate that the distribution of species traits and the consequences for community dynamics are intimately linked and strictly dependent on how the benefits and costs of these traits are balanced across different conditions.

The five-factor model of personality and borderline personality disorder: a genetic analysis of comorbidity.

PubMed

Distel, Marijn A; Trull, Timothy J; Willemsen, Gonneke; Vink, Jacqueline M; Derom, Catherine A; Lynskey, Michael; Martin, Nicholas G; Boomsma, Dorret I

2009-12-15

Recently, the nature of personality disorders and their relationship with normal personality traits has received extensive attention. The five-factor model (FFM) of personality, consisting of the personality traits neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness, is one of the proposed models to conceptualize personality disorders as maladaptive variants of continuously distributed personality traits. The present study examined the phenotypic and genetic association between borderline personality and FFM personality traits. Data were available for 4403 monozygotic twins, 4425 dizygotic twins, and 1661 siblings from 6140 Dutch, Belgian, and Australian families. Broad-sense heritability estimates for neuroticism, agreeableness, conscientiousness, extraversion, openness to experience, and borderline personality were 43%, 36%, 43%, 47%, 54%, and 45%, respectively. Phenotypic correlations between borderline personality and the FFM personality traits ranged from .06 for openness to experience to .68 for neuroticism. Multiple regression analyses showed that a combination of high neuroticism and low agreeableness best predicted borderline personality. Multivariate genetic analyses showed the genetic factors that influence individual differences in neuroticism, agreeableness, conscientiousness, and extraversion account for all genetic liability to borderline personality. Unique environmental effects on borderline personality, however, were not completely shared with those for the FFM traits (33% is unique to borderline personality). Borderline personality shares all genetic variation with neuroticism, agreeableness, conscientiousness, and extraversion. The unique environmental influences specific to borderline personality may cause individuals with a specific pattern of personality traits to cross a threshold and develop borderline personality.

Impulsivity-related traits, college alcohol beliefs, and alcohol outcomes: Examination of a prospective multiple mediation model among college students in Spain, Argentina, and USA.

PubMed

Bravo, Adrian J; Pearson, Matthew R; Pilatti, Angelina; Read, Jennifer P; Mezquita, Laura; Ibáñez, Manuel I; Ortet, Generós

2018-06-01

The present study examined (both cross-sectionally and prospectively) the mediational role of college alcohol beliefs in the relationship between impulsivity-related traits and alcohol outcomes (i.e., alcohol use and negative consequences) among college student drinkers from the United States (U.S.), Spain, and Argentina. A sample of 1429 (U.S. = 733, Spain = 292, Argentina = 404) drinkers (at least one drinking episode within the previous month) completed the baseline survey, and 242 drinkers completed the follow-up. To test study aims, a cross-sectional model was first employed to examine whether the proposed double-mediated paths (i.e., each dimension of impulsivity → college alcohol beliefs → alcohol use → negative alcohol-related consequences) extends across samples with different cultural backgrounds (i.e., structural invariance testing). A longitudinal model was then conducted to assess if college alcohol beliefs prospectively mediate the associations between trait impulsivity and alcohol outcomes. College alcohol beliefs were concurrently and prospectively associated with both greater alcohol use and increased number of negative alcohol-related consequences. These internalized beliefs about college student drinking culture significantly mediated the effects of several distinct impulsivity-related traits on alcohol-related outcomes including urgency (positive and negative), sensation seeking, and perseverance. These findings were invariant across gender and across three countries (Argentina, Spain, and the U.S.). Our findings highlight the modulatory role of cognitive factors on problematic alcohol use among college students with different cultural backgrounds. Our results suggest that, despite the cultural differences exhibited by these three countries, the unique and mediational effects of college alcohol beliefs appear relatively universal. Copyright © 2018 Elsevier Ltd. All rights reserved.

The genetic basis of local adaptation for pathogenic fungi in agricultural ecosystems.

PubMed

Croll, Daniel; McDonald, Bruce A

2017-04-01

Local adaptation plays a key role in the evolutionary trajectory of host-pathogen interactions. However, the genetic architecture of local adaptation in host-pathogen systems is poorly understood. Fungal plant pathogens in agricultural ecosystems provide highly tractable models to quantify phenotypes and map traits to corresponding genomic loci. The outcome of crop-pathogen interactions is thought to be governed largely by gene-for-gene interactions. However, recent studies showed that virulence can be governed by quantitative trait loci and that many abiotic factors contribute to the outcome of the interaction. After introducing concepts of local adaptation and presenting examples from wild plant pathosystems, we focus this review on a major pathogen of wheat, Zymoseptoria tritici, to show how a multitude of traits can affect local adaptation. Zymoseptoria tritici adapted to different thermal environments across its distribution range, indicating that thermal adaptation may limit effective dispersal to different climates. The application of fungicides led to the rapid evolution of multiple, independent resistant populations. The degree of colony melanization showed strong pleiotropic effects with other traits, including trade-offs with colony growth rates and fungicide sensitivity. The success of the pathogen on its host can be assessed quantitatively by counting pathogen reproductive structures and measuring host damage based on necrotic lesions. Interestingly, these two traits can be weakly correlated and depend both on host and pathogen genotypes. Quantitative trait mapping studies showed that the genetic architecture of locally adapted traits varies from single loci with large effects to many loci with small individual effects. We discuss how local adaptation could hinder or accelerate the development of epidemics in agricultural ecosystems. © 2016 John Wiley & Sons Ltd.

Dissection of genetic architecture of rice plant height and heading date by multiple-strategy-based association studies

PubMed Central

Zhou, Liyuan; Liu, Shouye; Wu, Weixun; Chen, Daibo; Zhan, Xiaodeng; Zhu, Aike; Zhang, Yingxin; Cheng, Shihua; Cao, Liyong; Lou, Xiangyang; Xu, Haiming

2016-01-01

Xieyou9308 is a certified super hybrid rice cultivar with a high grain yield. To investigate its underlying genetic basis of high yield potential, a recombinant inbred line (RIL) population derived from the cross between the maintainer line XieqingzaoB (XQZB) and the restorer line Zhonghui9308 (ZH9308) was constructed for identification of quantitative trait SNPs (QTSs) associated with two important agronomic traits, plant height (PH) and heading date (HD). By re-sequencing of 138 recombinant inbred lines (RILs), a total of ~0.7 million SNPs were identified for the association studies on the PH and HD. Three association mapping strategies (including hypothesis-free genome-wide association and its two complementary hypothesis-engaged ones, QTL-based association and gene-based association) were adopted for data analysis. Using a saturated mixed linear model including epistasis and environmental interaction, we identified a total of 31 QTSs associated with either the PH or the HD. The total estimated heritability across three analyses ranged from 37.22% to 45.63% and from 37.53% to 55.96% for the PH and HD, respectively. In this study we examined the feasibility of association studies in an experimental population (RIL) and identified several common loci through multiple strategies which could be preferred candidates for further research. PMID:27406081

Machine learning of structural magnetic resonance imaging predicts psychopathic traits in adolescent offenders.

PubMed

Steele, Vaughn R; Rao, Vikram; Calhoun, Vince D; Kiehl, Kent A

2017-01-15

Classification models are becoming useful tools for finding patterns in neuroimaging data sets that are not observable to the naked eye. Many of these models are applied to discriminating clinical groups such as schizophrenic patients from healthy controls or from patients with bipolar disorder. A more nuanced model might be to discriminate between levels of personality traits. Here, as a proof of concept, we take an initial step toward developing prediction models to differentiate individuals based on a personality disorder: psychopathy. We included three groups of adolescent participants: incarcerated youth with elevated psychopathic traits (i.e., callous and unemotional traits and conduct disordered traits; n=71), incarcerated youth with low psychopathic traits (n=72), and non-incarcerated youth as healthy controls (n=21). Support vector machine (SVM) learning models were developed to separate these groups using an out-of-sample cross-validation method on voxel-based morphometry (VBM) data. Regions of interest from the paralimbic system, identified in an independent forensic sample, were successful in differentiating youth groups. Models seeking to classify incarcerated individuals to have high or low psychopathic traits achieved 69.23% overall accuracy. As expected, accuracy increased in models differentiating healthy controls from individuals with high psychopathic traits (82.61%) and low psychopathic traits (80.65%). Here we have laid the foundation for using neural correlates of personality traits to identify group membership within and beyond psychopathy. This is only the first step, of many, toward prediction models using neural measures as a proxy for personality traits. As these methods are improved, prediction models with neural measures of personality traits could have far-reaching impact on diagnosis, treatment, and prediction of future behavior. Copyright © 2015 Elsevier Inc. All rights reserved.

Machine Learning of Structural Magnetic Resonance Imaging Predicts Psychopathic Traits in Adolescent Offenders

PubMed Central

Steele, Vaughn R.; Rao, Vikram; Calhoun, Vince D.; Kiehl, Kent A.

2015-01-01

Classification models are becoming useful tools for finding patterns in neuroimaging data sets that are not observable to the naked eye. Many of these models are applied to discriminating clinical groups such as schizophrenic patients from healthy controls or from patients with bipolar disorder. A more nuanced model might be to discriminate between levels of personality traits. Here, as a proof-of-concept, we take an initial step toward developing prediction models to differentiate individuals based on a personality disorder: psychopathy. We included three groups of adolescent participants: incarcerated youth with elevated psychopathic traits (i.e., callous and unemotional traits and conduct disordered traits; n = 71), incarcerated youth with low psychopathic traits (n =72), and non-incarcerated youth as healthy controls (n = 21). Support vector machine (SVM) learning models were developed to separate these groups using an out-of-sample cross-validation method on voxel-based morphometry (VBM) data. Regions-of-interest from the paralimbic system, identified in an independent forensic sample, were successful in differentiating youth groups. Models seeking to classify incarcerated individuals to have high or low psychopathic traits achieved 69.23% overall accuracy. As expected, accuracy increased in models differentiating healthy controls from individuals with high psychopathic traits (82.61%) and low psychopathic traits (80.65%). Here we have laid the foundation for using neural correlates of personality traits to identify group membership within and beyond psychopathy. This is only the first step, of many, toward prediction models using neural measures as a proxy for personality traits. As these methods are improved, prediction models with neural measures of personality traits could have far-reaching impact on diagnosis, treatment, and prediction of future behavior. PMID:26690808

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

Building a better foundation: improving root-trait measurements to understand and model plant and ecosystem processes

DOE PAGES

McCormack, M. Luke; Guo, Dali; Iversen, Colleen M.; ...

2017-03-13

Trait-based approaches provide a useful framework to investigate plant strategies for resource acquisition, growth, and competition, as well as plant impacts on ecosystem processes. Despite significant progress capturing trait variation within and among stems and leaves, identification of trait syndromes within fine-root systems and between fine roots and other plant organs is limited. Here we discuss three underappreciated areas where focused measurements of fine-root traits can make significant contributions to ecosystem science. These include assessment of spatiotemporal variation in fine-root traits, integration of mycorrhizal fungi into fine-root-trait frameworks, and the need for improved scaling of traits measured on individual rootsmore » to ecosystem-level processes. Progress in each of these areas is providing opportunities to revisit how below-ground processes are represented in terrestrial biosphere models. Targeted measurements of fine-root traits with clear linkages to ecosystem processes and plant responses to environmental change are strongly needed to reduce empirical and model uncertainties. Further identifying how and when suites of root and whole-plant traits are coordinated or decoupled will ultimately provide a powerful tool for modeling plant form and function at local and global scales.« less

Building a better foundation: improving root-trait measurements to understand and model plant and ecosystem processes

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

McCormack, M. Luke; Guo, Dali; Iversen, Colleen M.

Trait-based approaches provide a useful framework to investigate plant strategies for resource acquisition, growth, and competition, as well as plant impacts on ecosystem processes. Despite significant progress capturing trait variation within and among stems and leaves, identification of trait syndromes within fine-root systems and between fine roots and other plant organs is limited. Here we discuss three underappreciated areas where focused measurements of fine-root traits can make significant contributions to ecosystem science. These include assessment of spatiotemporal variation in fine-root traits, integration of mycorrhizal fungi into fine-root-trait frameworks, and the need for improved scaling of traits measured on individual rootsmore » to ecosystem-level processes. Progress in each of these areas is providing opportunities to revisit how below-ground processes are represented in terrestrial biosphere models. Targeted measurements of fine-root traits with clear linkages to ecosystem processes and plant responses to environmental change are strongly needed to reduce empirical and model uncertainties. Further identifying how and when suites of root and whole-plant traits are coordinated or decoupled will ultimately provide a powerful tool for modeling plant form and function at local and global scales.« less

Mapping of quantitative trait loci for grain yield and its components in a US popular winter wheat TAM 111 using 90K SNPs.

PubMed

Assanga, Silvano O; Fuentealba, Maria; Zhang, Guorong; Tan, ChorTee; Dhakal, Smit; Rudd, Jackie C; Ibrahim, Amir M H; Xue, Qingwu; Haley, Scott; Chen, Jianli; Chao, Shiaoman; Baker, Jason; Jessup, Kirk; Liu, Shuyu

2017-01-01

Stable quantitative trait loci (QTL) are important for deployment in marker assisted selection in wheat (Triticum aestivum L.) and other crops. We reported QTL discovery in wheat using a population of 217 recombinant inbred lines and multiple statistical approach including multi-environment, multi-trait and epistatic interactions analysis. We detected nine consistent QTL linked to different traits on chromosomes 1A, 2A, 2B, 5A, 5B, 6A, 6B and 7A. Grain yield QTL were detected on chromosomes 2B.1 and 5B across three or four models of GenStat, MapQTL, and QTLNetwork while the QTL on chromosomes 5A.1, 6A.2, and 7A.1 were only significant with yield from one or two models. The phenotypic variation explained (PVE) by the QTL on 2B.1 ranged from 3.3-25.1% based on single and multi-environment models in GenStat and was pleiotropic or co-located with maturity (days to heading) and yield related traits (test weight, thousand kernel weight, harvest index). The QTL on 5B at 211 cM had PVE range of 1.8-9.3% and had no significant pleiotropic effects. Other consistent QTL detected in this study were linked to yield related traits and agronomic traits. The QTL on 1A was consistent for the number of spikes m-2 across environments and all the four analysis models with a PVE range of 5.8-8.6%. QTL for kernels spike-1 were found in chromosomes 1A, 2A.1, 2B.1, 6A.2, and 7A.1 with PVE ranged from 5.6-12.8% while QTL for thousand kernel weight were located on chromosomes 1A, 2B.1, 5A.1, 6A.2, 6B.1 and 7A.1 with PVEranged from 2.7-19.5%. Among the consistent QTL, five QTL had significant epistatic interactions (additive × additive) at least for one trait and none revealed significant additive × additive × environment interactions. Comparative analysis revealed that the region within the confidence interval of the QTL on 5B from 211.4-244.2 cM is also linked to genes for aspartate-semialdehyde dehydrogenase, splicing regulatory glutamine/lysine-rich protein 1 isoform X1, and UDP-glucose 6-dehydrogenase 1-like isoform X1. The stable QTL could be important for further validation, high throughput SNP development, and marker-assisted selection (MAS) in wheat.

Physiology-Based Modeling May Predict Surgical Treatment Outcome for Obstructive Sleep Apnea

PubMed Central

Li, Yanru; Ye, Jingying; Han, Demin; Cao, Xin; Ding, Xiu; Zhang, Yuhuan; Xu, Wen; Orr, Jeremy; Jen, Rachel; Sands, Scott; Malhotra, Atul; Owens, Robert

2017-01-01

Study Objectives: To test whether the integration of both anatomical and nonanatomical parameters (ventilatory control, arousal threshold, muscle responsiveness) in a physiology-based model will improve the ability to predict outcomes after upper airway surgery for obstructive sleep apnea (OSA). Methods: In 31 patients who underwent upper airway surgery for OSA, loop gain and arousal threshold were calculated from preoperative polysomnography (PSG). Three models were compared: (1) a multiple regression based on an extensive list of PSG parameters alone; (2) a multivariate regression using PSG parameters plus PSG-derived estimates of loop gain, arousal threshold, and other trait surrogates; (3) a physiological model incorporating selected variables as surrogates of anatomical and nonanatomical traits important for OSA pathogenesis. Results: Although preoperative loop gain was positively correlated with postoperative apnea-hypopnea index (AHI) (P = .008) and arousal threshold was negatively correlated (P = .011), in both model 1 and 2, the only significant variable was preoperative AHI, which explained 42% of the variance in postoperative AHI. In contrast, the physiological model (model 3), which included AHIREM (anatomy term), fraction of events that were hypopnea (arousal term), the ratio of AHIREM and AHINREM (muscle responsiveness term), loop gain, and central/mixed apnea index (control of breathing terms), was able to explain 61% of the variance in postoperative AHI. Conclusions: Although loop gain and arousal threshold are associated with residual AHI after surgery, only preoperative AHI was predictive using multivariate regression modeling. Instead, incorporating selected surrogates of physiological traits on the basis of OSA pathophysiology created a model that has more association with actual residual AHI. Commentary: A commentary on this article appears in this issue on page 1023. Clinical Trial Registration: ClinicalTrials.Gov; Title: The Impact of Sleep Apnea Treatment on Physiology Traits in Chinese Patients With Obstructive Sleep Apnea; Identifier: NCT02696629; URL: https://clinicaltrials.gov/show/NCT02696629 Citation: Li Y, Ye J, Han D, Cao X, Ding X, Zhang Y, Xu W, Orr J, Jen R, Sands S, Malhotra A, Owens R. Physiology-based modeling may predict surgical treatment outcome for obstructive sleep apnea. J Clin Sleep Med. 2017;13(9):1029–1037. PMID:28818154

Identification Problems in Personality Psychology1

PubMed Central

Borghans, Lex; Golsteyn, Bart H. H.; Heckman, James; Humphries, John Eric

2011-01-01

This paper discusses and illustrates identification problems in personality psychology. The measures used by psychologists to infer traits are based on behaviors, broadly defined. These behaviors are produced from multiple traits interacting with incentives in situations. In general, measures are determined by these multiple traits and do not identify any particular trait unless incentives and other traits are controlled for. Using two data sets, we show, as an example, that substantial portions of the variance in achievement test scores and grades, which are often used as measures of cognition, are explained by personality variables. PMID:21731170

Estimation of economic values for traits of dairy sheep: I. Model development.

PubMed

Wolfová, M; Wolf, J; Krupová, Z; Kica, J

2009-05-01

A bioeconomic model was developed to estimate effects of change in production and functional traits on profit of dairy or dual-purpose milked sheep under alternative management systems. The flock structure was described in terms of animal categories and probabilities of transitions among them, and a Markov chain approach was used to calculate the stationary state of the resultant ewe flock. The model included both deterministic and stochastic components. Performance for most traits was simulated as the population average, but variation in several traits was taken into account. Management options included lambing intervals, mating system, and culling strategy for ewes, weaning and marketing strategy for progeny, and feeding system. The present value of profit computed as the difference between total revenues and total costs per ewe per year, both discounted to the birth date of the animals, was used as the criterion for economic efficiency of the production system in the stationary state. Economic values (change in system profit per unit change in the trait) of up to 35 milk production, growth, carcass, wool, and functional traits may be estimated.

Pervasive gene expression responses to a fluctuating diet in Drosophila melanogaster: The importance of measuring multiple traits to decouple potential mediators of life span and reproduction.

PubMed

Zandveld, Jelle; van den Heuvel, Joost; Mulder, Maarten; Brakefield, Paul M; Kirkwood, Thomas B L; Shanley, Daryl P; Zwaan, Bas J

2017-11-01

Phenotypic plasticity is an important concept in life-history evolution, and most organisms, including Drosophila melanogaster, show a plastic life-history response to diet. However, little is known about how these life-history responses are mediated. In this study, we compared adult female flies fed an alternating diet (yoyo flies) with flies fed a constant low (CL) or high (CH) diet and tested how whole genome expression was affected by these diet regimes and how the transcriptional responses related to different life-history traits. We showed that flies were able to respond quickly to diet fluctuations throughout life span by drastically changing their transcription. Importantly, by measuring the response of multiple life-history traits we were able to decouple groups of genes associated with life span or reproduction, life-history traits that often covary with a diet change. A coexpression network analysis uncovered which genes underpin the separate and shared regulation of these life-history traits. Our study provides essential insights to help unravel the genetic architecture mediating life-history responses to diet, and it shows that the flies' whole genome transcription response is highly plastic. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Impulsivity traits and addiction-related behaviors in youth.

PubMed

Rømer Thomsen, Kristine; Callesen, Mette Buhl; Hesse, Morten; Kvamme, Timo Lehmann; Pedersen, Michael Mulbjerg; Pedersen, Mads Uffe; Voon, Valerie

2018-04-12

Background and aims Impulsivity is a risk factor for addictive behaviors. The UPPS-P impulsivity model has been associated with substance addiction and gambling disorder, but its role in other non-substance addiction-related behaviors is less understood. We sought to examine associations between UPPS-P impulsivity traits and indicators of multiple substance and non-substance addiction-related behaviors in youth with varying involvement in these behaviors. Methods Participants (N = 109, aged 16-26 years, 69% males) were selected from a national survey based on their level of externalizing problems to achieve a broad distribution of involvement in addiction-related behaviors. Participants completed the UPPS-P Questionnaire and standardized questionnaires assessing problematic use of substances (alcohol, cannabis, and other drugs) and non-substances (Internet gaming, pornography, and food). Regression analyses were used to assess associations between impulsivity traits and indicators of addiction-related behaviors. Results The UPPS-P model was positively associated with indicators of all addiction-related behaviors except problematic Internet gaming. In the fully adjusted models, sensation seeking and lack of perseverance were associated with problematic use of alcohol, urgency was associated with problematic use of cannabis, and lack of perseverance was associated with problematic use of other drugs than cannabis. Furthermore, urgency and lack of perseverance were associated with binge eating and lack of perseverance was associated with problematic use of pornography. Discussion and conclusions We emphasize the role of trait impulsivity across multiple addiction-related behaviors. Our findings in at-risk youth highlight urgency and lack of perseverance as potential predictors for the development of addictions and as potential preventative therapeutic targets.

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

SNP-based association analysis for seedling traits in durum wheat (Triticum turgidum L. durum (Desf.)).

PubMed

Sabiel, Salih A I; Huang, Sisi; Hu, Xin; Ren, Xifeng; Fu, Chunjie; Peng, Junhua; Sun, Dongfa

2017-03-01

In the present study, 150 accessions of worldwide originated durum wheat germplasm ( Triticum turgidum spp. durum ) were observed for major seedling traits and their growth. The accessions were evaluated for major seedling traits under controlled conditions of hydroponics at the 13 th , 20 th , 27 th and 34 th day-after germination. Biomass traits were measured at the 34 th day-after germination. Correlation analysis was conducted among the seedling traits and three field traits at maturity, plant height, grain weight and 1000-grain weight observed in four consecutive years. Associations of the measured seedling traits and SNP markers were analyzed based on the mixed linear model (MLM). The results indicated that highly significant genetic variation and robust heritability were found for the seedling and field mature traits. In total, 259 significant associations were detected for all the traits and four growth stages. The phenotypic variation explained (R2) by a single SNP marker is higher than 10% for most (84%) of the significant SNP markers. Forty-six SNP markers associated with multiple traits, indicating non-neglectable pleiotropy in seedling stage. The associated SNP markers could be helpful for genetic analysis of seedling traits, and marker-assisted breeding of new wheat varieties with strong seedling vigor.

A predictive assessment of genetic correlations between traits in chickens using markers.

PubMed

Momen, Mehdi; Mehrgardi, Ahmad Ayatollahi; Sheikhy, Ayoub; Esmailizadeh, Ali; Fozi, Masood Asadi; Kranis, Andreas; Valente, Bruno D; Rosa, Guilherme J M; Gianola, Daniel

2017-02-01

Genomic selection has been successfully implemented in plant and animal breeding programs to shorten generation intervals and accelerate genetic progress per unit of time. In practice, genomic selection can be used to improve several correlated traits simultaneously via multiple-trait prediction, which exploits correlations between traits. However, few studies have explored multiple-trait genomic selection. Our aim was to infer genetic correlations between three traits measured in broiler chickens by exploring kinship matrices based on a linear combination of measures of pedigree and marker-based relatedness. A predictive assessment was used to gauge genetic correlations. A multivariate genomic best linear unbiased prediction model was designed to combine information from pedigree and genome-wide markers in order to assess genetic correlations between three complex traits in chickens, i.e. body weight at 35 days of age (BW), ultrasound area of breast meat (BM) and hen-house egg production (HHP). A dataset with 1351 birds that were genotyped with the 600 K Affymetrix platform was used. A kinship kernel (K) was constructed as K = λ G + (1 - λ)A, where A is the numerator relationship matrix, measuring pedigree-based relatedness, and G is a genomic relationship matrix. The weight (λ) assigned to each source of information varied over the grid λ = (0, 0.2, 0.4, 0.6, 0.8, 1). Maximum likelihood estimates of heritability and genetic correlations were obtained at each λ, and the "optimum" λ was determined using cross-validation. Estimates of genetic correlations were affected by the weight placed on the source of information used to build K. For example, the genetic correlation between BW-HHP and BM-HHP changed markedly when λ varied from 0 (only A used for measuring relatedness) to 1 (only genomic information used). As λ increased, predictive correlations (correlation between observed phenotypes and predicted breeding values) increased and mean-squared predictive error decreased. However, the improvement in predictive ability was not monotonic, with an optimum found at some 0 < λ < 1, i.e., when both sources of information were used together. Our findings indicate that multiple-trait prediction may benefit from combining pedigree and marker information. Also, it appeared that expected correlated responses to selection computed from standard theory may differ from realized responses. The predictive assessment provided a metric for performance evaluation as well as a means for expressing uncertainty of outcomes of multiple-trait selection.

Convergent, discriminant, and criterion validity of DSM-5 traits.

PubMed

Yalch, Matthew M; Hopwood, Christopher J

2016-10-01

Section III of the Diagnostic and Statistical Manual of Mental Disorders (5th edi.; DSM-5; American Psychiatric Association, 2013) contains a system for diagnosing personality disorder based in part on assessing 25 maladaptive traits. Initial research suggests that this aspect of the system improves the validity and clinical utility of the Section II Model. The Computer Adaptive Test of Personality Disorder (CAT-PD; Simms et al., 2011) contains many similar traits as the DSM-5, as well as several additional traits seemingly not covered in the DSM-5. In this study we evaluate the convergent and discriminant validity between the DSM-5 traits, as assessed by the Personality Inventory for DSM-5 (PID-5; Krueger et al., 2012), and CAT-PD in an undergraduate sample, and test whether traits included in the CAT-PD but not the DSM-5 provide incremental validity in association with clinically relevant criterion variables. Results supported the convergent and discriminant validity of the PID-5 and CAT-PD scales in their assessment of 23 out of 25 DSM-5 traits. DSM-5 traits were consistently associated with 11 criterion variables, despite our having intentionally selected clinically relevant criterion constructs not directly assessed by DSM-5 traits. However, the additional CAT-PD traits provided incremental information above and beyond the DSM-5 traits for all criterion variables examined. These findings support the validity of pathological trait models in general and the DSM-5 and CAT-PD models in particular, while also suggesting that the CAT-PD may include additional traits for consideration in future iterations of the DSM-5 system. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A simple model clarifies the complicated relationships of complex networks

PubMed Central

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

2014-01-01

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

Association of udder traits with single nucleotide polymorphisms in crossbred Bos indicus-Bos taurus cows.

PubMed

Tolleson, M W; Gill, C A; Herring, A D; Riggs, P K; Sawyer, J E; Sanders, J O; Riley, D G

2017-06-01

The size, support, and health of udders limit the productive life of beef cows, especially those with background, because, in general, such cows have a reputation for problems with udders. Genomic association studies of bovine udder traits have been conducted in dairy cattle and recently in Continental European beef breeds but not in cows with background. The objective of this study was to determine associations of SNP and udder support scores, teat length, and teat diameter in half (Nellore), half (Angus) cows. Udders of cows ( = 295) born from 2003 to 2007 were evaluated for udder support and teat length and diameter ( = 1,746 records) from 2005 through 2014. These included a subjective score representing udder support (values of 1 indicated poorly supported, pendulous udders and values of 9 indicated very well-supported udders) and lengths and diameters of individual teats in the 4 udder quarters as well as the average. Cows were in full-sibling or half-sibling families. Residuals for each trait were produced from repeated records models with cow age category nested within birth year of cows. Those residuals were averaged to become the dependent variables for genomewide association analyses. Regression analyses of those dependent variables included genotypic values as explanatory variables for 34,980 SNP from a commercially available array and included the genomic relationship matrix. Fifteen SNP loci on BTA 5 were associated (false discovery rate controlled at 0.05) with udder support score. One of those was also detected as associated with average teat diameter. Three of those 15 SNP were located within genes, including one each in (), (), and (). These are notable for their functional role in some aspect of mammary gland formation or health. Other candidate genes for these traits in the vicinity of the SNP loci include () and (). Because these were detected in Nellore-Angus crossbred cows, which typically have very well-formed udders with excellent support across their productive lives, similar efforts in other breeds should be completed, because that may facilitate further refinement of genomic regions responsible for variation in udder traits important in multiple breeds.

A simple genetic architecture underlies morphological variation in dogs.

PubMed

Boyko, Adam R; Quignon, Pascale; Li, Lin; Schoenebeck, Jeffrey J; Degenhardt, Jeremiah D; Lohmueller, Kirk E; Zhao, Keyan; Brisbin, Abra; Parker, Heidi G; vonHoldt, Bridgett M; Cargill, Michele; Auton, Adam; Reynolds, Andy; Elkahloun, Abdel G; Castelhano, Marta; Mosher, Dana S; Sutter, Nathan B; Johnson, Gary S; Novembre, John; Hubisz, Melissa J; Siepel, Adam; Wayne, Robert K; Bustamante, Carlos D; Ostrander, Elaine A

2010-08-10

Domestic dogs exhibit tremendous phenotypic diversity, including a greater variation in body size than any other terrestrial mammal. Here, we generate a high density map of canine genetic variation by genotyping 915 dogs from 80 domestic dog breeds, 83 wild canids, and 10 outbred African shelter dogs across 60,968 single-nucleotide polymorphisms (SNPs). Coupling this genomic resource with external measurements from breed standards and individuals as well as skeletal measurements from museum specimens, we identify 51 regions of the dog genome associated with phenotypic variation among breeds in 57 traits. The complex traits include average breed body size and external body dimensions and cranial, dental, and long bone shape and size with and without allometric scaling. In contrast to the results from association mapping of quantitative traits in humans and domesticated plants, we find that across dog breeds, a small number of quantitative trait loci (< or = 3) explain the majority of phenotypic variation for most of the traits we studied. In addition, many genomic regions show signatures of recent selection, with most of the highly differentiated regions being associated with breed-defining traits such as body size, coat characteristics, and ear floppiness. Our results demonstrate the efficacy of mapping multiple traits in the domestic dog using a database of genotyped individuals and highlight the important role human-directed selection has played in altering the genetic architecture of key traits in this important species.

A Simple Genetic Architecture Underlies Morphological Variation in Dogs

PubMed Central

Schoenebeck, Jeffrey J.; Degenhardt, Jeremiah D.; Lohmueller, Kirk E.; Zhao, Keyan; Brisbin, Abra; Parker, Heidi G.; vonHoldt, Bridgett M.; Cargill, Michele; Auton, Adam; Reynolds, Andy; Elkahloun, Abdel G.; Castelhano, Marta; Mosher, Dana S.; Sutter, Nathan B.; Johnson, Gary S.; Novembre, John; Hubisz, Melissa J.; Siepel, Adam; Wayne, Robert K.; Bustamante, Carlos D.; Ostrander, Elaine A.

2010-01-01

Domestic dogs exhibit tremendous phenotypic diversity, including a greater variation in body size than any other terrestrial mammal. Here, we generate a high density map of canine genetic variation by genotyping 915 dogs from 80 domestic dog breeds, 83 wild canids, and 10 outbred African shelter dogs across 60,968 single-nucleotide polymorphisms (SNPs). Coupling this genomic resource with external measurements from breed standards and individuals as well as skeletal measurements from museum specimens, we identify 51 regions of the dog genome associated with phenotypic variation among breeds in 57 traits. The complex traits include average breed body size and external body dimensions and cranial, dental, and long bone shape and size with and without allometric scaling. In contrast to the results from association mapping of quantitative traits in humans and domesticated plants, we find that across dog breeds, a small number of quantitative trait loci (≤3) explain the majority of phenotypic variation for most of the traits we studied. In addition, many genomic regions show signatures of recent selection, with most of the highly differentiated regions being associated with breed-defining traits such as body size, coat characteristics, and ear floppiness. Our results demonstrate the efficacy of mapping multiple traits in the domestic dog using a database of genotyped individuals and highlight the important role human-directed selection has played in altering the genetic architecture of key traits in this important species. PMID:20711490

Inter- and intraspecific variation in leaf economic traits in wheat and maize

PubMed Central

Hale, Christine E; Cerabolini, Bruno E L; Cornelissen, Johannes H C; Craine, Joseph; Gough, William A; Kattge, Jens; Tirona, Cairan K F

2018-01-01

Abstract Leaf Economics Spectrum (LES) trait variation underpins multiple agroecological processes and many prominent crop yield models. While there are numerous independent studies assessing trait variation in crops, to date there have been no comprehensive assessments of intraspecific trait variation (ITV) in LES traits for wheat and maize: the world’s most widespread crops. Using trait databases and peer-reviewed literature, we compiled over 700 records of specific leaf area (SLA), maximum photosynthetic rates (Amax) and leaf nitrogen (N) concentrations, for wheat and maize. We evaluated intraspecific LES trait variation, and intraspecific trait–environment relationships. While wheat and maize occupy the upper 90th percentile of LES trait values observed across a global species pool, ITV ranged widely across the LES in wheat and maize. Fertilization treatments had strong impacts on leaf N, while plant developmental stage (here standardized as the number of days since planting) had strong impacts on Amax; days since planting, N fertilization and irrigation all influenced SLA. When controlling for these factors, intraspecific responses to temperature and precipitation explained 39.4 and 43.7 % of the variation in Amax and SLA, respectively, but only 5.4 % of the variation in leaf N. Despite a long history of domestication in these species, ITV in wheat and maize among and within cultivars remains large. Intraspecific trait variation is a critical consideration to refine regional to global models of agroecosystem structure, function and food security. Considerable opportunities and benefits exist for consolidating a crop trait database for a wider range of domesticated plant species. PMID:29484152

Personality Traits and Mental Symptoms are Associated with Impact of Chronic Obstructive Pulmonary Disease on Patients' Daily Life.

PubMed

Topp, Marie; Vestbo, Jørgen; Mortensen, Erik Lykke

2016-12-01

Previous research has shown that personality traits are associated with self-reported health status in the general population. COPD Assessment Test (CAT) is increasingly used to assess health status such as the impact of chronic obstructive pulmonary disease (COPD) on patients' daily life, but knowledge about the influence of personality traits on CAT score is lacking. The aim of this study was to examine the influence of Big Five personality traits on CAT score and the relation between personality traits and mental symptoms with respect to their influence on CAT score. A sample of 168 patients diagnosed with COPD was consecutively recruited in a secondary care outpatient clinic. All participants completed CAT, NEO Five-Factor Inventory, and Hospital Depression and Anxiety Scale. Multiple linear regression analysis was used to explore the association between personality traits and CAT scores and how this association was influenced by mental symptoms. The personality traits neuroticism, agreeableness and conscientiousness; and the mental symptoms depression and anxiety showed significant influence on CAT score when analysed in separate regression models. Identical R-square (R = 0.24) was found for personality traits and mental symptoms, but combining personality traits and mental symptoms in one regression model showed substantially reduced effect estimates of neuroticism, conscientiousness and anxiety, reflecting the strong correlations between personality traits and mental symptoms. We found that the impact of COPD on daily life measured by CAT was related to personality and mental symptoms, which illustrates the necessity of taking individual differences in personality and mental status into account in the management of COPD.

Understanding the nature of wealth and its effects on human fitness

PubMed Central

Mulder, Monique Borgerhoff; Beheim, Bret A.

2011-01-01

Studying fitness consequences of variable behavioural, physiological and cognitive traits in contemporary populations constitutes the specific contribution of human behavioural ecology to the study of human diversity. Yet, despite 30 years of evolutionary anthropological interest in the determinants of fitness, there exist few principled investigations of the diverse sources of wealth that might reveal selective forces during recent human history. To develop a more holistic understanding of how selection shapes human phenotypic traits, be these transmitted by genetic or cultural means, we expand the conventional focus on associations between socioeconomic status and fitness to three distinct types of wealth—embodied, material and relational. Using a model selection approach to the study of women's success in raising offspring in an African horticultural population (the Tanzanian Pimbwe), we find that the top performing models consistently include relational and material wealth, with embodied wealth as a less reliable predictor. Specifically, child mortality risk is increased with few household assets, parent nonresidency, child legitimacy, and one or more parents having been accused of witchcraft. The use of multiple models to test various hypotheses greatly facilitates systematic comparative analyses of human behavioural diversity in wealth accrual and investment across different kinds of societies. PMID:21199839

Issues and Perspectives in Species Delimitation using Phenotypic Data: Atlantean Evolution in Darwin's Finches.

PubMed

Cadena, Carlos Daniel; Zapata, Felipe; Jiménez, Iván

2018-03-01

Progress in the development and use of methods for species delimitation employing phenotypic data lags behind conceptual and practical advances in molecular genetic approaches. The basic evolutionary model underlying the use of phenotypic data to delimit species assumes random mating and quantitative polygenic traits, so that phenotypic distributions within a species should be approximately normal for individuals of the same sex and age. Accordingly, two or more distinct normal distributions of phenotypic traits suggest the existence of multiple species. In light of this model, we show that analytical approaches employed in taxonomic studies using phenotypic data are often compromised by three issues: 1) reliance on graphical analyses that convey little information on phenotype frequencies; 2) exclusion of characters potentially important for species delimitation following reduction of data dimensionality; and 3) use of measures of central tendency to evaluate phenotypic distinctiveness. We outline approaches to overcome these issues based on statistical developments related to normal mixture models (NMMs) and illustrate them empirically with a reanalysis of morphological data recently used to claim that there are no morphologically distinct species of Darwin's ground-finches (Geospiza). We found negligible support for this claim relative to taxonomic hypotheses recognizing multiple species. Although species limits among ground-finches merit further assessments using additional sources of information, our results bear implications for other areas of inquiry including speciation research: because ground-finches have likely speciated and are not trapped in a process of "Sisyphean" evolution as recently argued, they remain useful models to understand the evolutionary forces involved in speciation. Our work underscores the importance of statistical approaches grounded on appropriate evolutionary models for species delimitation. We discuss how NMMs offer new perspectives in the kind of inferences available to systematists, with significant repercussions on ideas about the phenotypic structure of biodiversity.

Dynamic Quantitative Trait Locus Analysis of Plant Phenomic Data.

PubMed

Li, Zitong; Sillanpää, Mikko J

2015-12-01

Advanced platforms have recently become available for automatic and systematic quantification of plant growth and development. These new techniques can efficiently produce multiple measurements of phenotypes over time, and introduce time as an extra dimension to quantitative trait locus (QTL) studies. Functional mapping utilizes a class of statistical models for identifying QTLs associated with the growth characteristics of interest. A major benefit of functional mapping is that it integrates information over multiple timepoints, and therefore could increase the statistical power for QTL detection. We review the current development of computationally efficient functional mapping methods which provide invaluable tools for analyzing large-scale timecourse data that are readily available in our post-genome era. Copyright © 2015 Elsevier Ltd. All rights reserved.

Ascertainment correction for Markov chain Monte Carlo segregation and linkage analysis of a quantitative trait.

PubMed

Ma, Jianzhong; Amos, Christopher I; Warwick Daw, E

2007-09-01

Although extended pedigrees are often sampled through probands with extreme levels of a quantitative trait, Markov chain Monte Carlo (MCMC) methods for segregation and linkage analysis have not been able to perform ascertainment corrections. Further, the extent to which ascertainment of pedigrees leads to biases in the estimation of segregation and linkage parameters has not been previously studied for MCMC procedures. In this paper, we studied these issues with a Bayesian MCMC approach for joint segregation and linkage analysis, as implemented in the package Loki. We first simulated pedigrees ascertained through individuals with extreme values of a quantitative trait in spirit of the sequential sampling theory of Cannings and Thompson [Cannings and Thompson [1977] Clin. Genet. 12:208-212]. Using our simulated data, we detected no bias in estimates of the trait locus location. However, in addition to allele frequencies, when the ascertainment threshold was higher than or close to the true value of the highest genotypic mean, bias was also found in the estimation of this parameter. When there were multiple trait loci, this bias destroyed the additivity of the effects of the trait loci, and caused biases in the estimation all genotypic means when a purely additive model was used for analyzing the data. To account for pedigree ascertainment with sequential sampling, we developed a Bayesian ascertainment approach and implemented Metropolis-Hastings updates in the MCMC samplers used in Loki. Ascertainment correction greatly reduced biases in parameter estimates. Our method is designed for multiple, but a fixed number of trait loci. Copyright (c) 2007 Wiley-Liss, Inc.

Comparative multi-goal tradeoffs in systems engineering of microbial metabolism

PubMed Central

2012-01-01

Background Metabolic engineering design methodology has evolved from using pathway-centric, random and empirical-based methods to using systems-wide, rational and integrated computational and experimental approaches. Persistent during these advances has been the desire to develop design strategies that address multiple simultaneous engineering goals, such as maximizing productivity, while minimizing raw material costs. Results Here, we use constraint-based modeling to systematically design multiple combinations of medium compositions and gene-deletion strains for three microorganisms (Escherichia coli, Saccharomyces cerevisiae, and Shewanella oneidensis) and six industrially important byproducts (acetate, D-lactate, hydrogen, ethanol, formate, and succinate). We evaluated over 435 million simulated conditions and 36 engineering metabolic traits, including product rates, costs, yields and purity. Conclusions The resulting metabolic phenotypes can be classified into dominant clusters (meta-phenotypes) for each organism. These meta-phenotypes illustrate global phenotypic variation and sensitivities, trade-offs associated with multiple engineering goals, and fundamental differences in organism-specific capabilities. Given the increasing number of sequenced genomes and corresponding stoichiometric models, we envisage that the proposed strategy could be extended to address a growing range of biological questions and engineering applications. PMID:23009214

Genetic dissection of sorghum grain quality traits using diverse and segregating populations.

PubMed

Boyles, Richard E; Pfeiffer, Brian K; Cooper, Elizabeth A; Rauh, Bradley L; Zielinski, Kelsey J; Myers, Matthew T; Brenton, Zachary; Rooney, William L; Kresovich, Stephen

2017-04-01

Coordinated association and linkage mapping identified 25 grain quality QTLs in multiple environments, and fine mapping of the Wx locus supports the use of high-density genetic markers in linkage mapping. There is a wide range of end-use products made from cereal grains, and these products often demand different grain characteristics. Fortunately, cereal crop species including sorghum [Sorghum bicolor (L.) Moench] contain high phenotypic variation for traits influencing grain quality. Identifying genetic variants underlying this phenotypic variation allows plant breeders to develop genotypes with grain attributes optimized for their intended usage. Multiple sorghum mapping populations were rigorously phenotyped across two environments (SC Coastal Plain and Central TX) in 2 years for five major grain quality traits: amylose, starch, crude protein, crude fat, and gross energy. Coordinated association and linkage mapping revealed several robust QTLs that make prime targets to improve grain quality for food, feed, and fuel products. Although the amylose QTL interval spanned many megabases, the marker with greatest significance was located just 12 kb from waxy (Wx), the primary gene regulating amylose production in cereal grains. This suggests higher resolution mapping in recombinant inbred line (RIL) populations can be obtained when genotyped at a high marker density. The major QTL for crude fat content, identified in both a RIL population and grain sorghum diversity panel, encompassed the DGAT1 locus, a critical gene involved in maize lipid biosynthesis. Another QTL on chromosome 1 was consistently mapped in both RIL populations for multiple grain quality traits including starch, crude protein, and gross energy. Collectively, these genetic regions offer excellent opportunities to manipulate grain composition and set up future studies for gene validation.

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

PubMed

Kwak, Il-Youp; Pan, Wei

2017-01-01

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

A global Fine-Root Ecology Database to address below-ground challenges in plant ecology

DOE PAGES

Iversen, Colleen M.; McCormack, M. Luke; Powell, A. Shafer; ...

2017-02-28

Variation and tradeoffs within and among plant traits are increasingly being harnessed by empiricists and modelers to understand and predict ecosystem processes under changing environmental conditions. And while fine roots play an important role in ecosystem functioning, fine-root traits are underrepresented in global trait databases. This has hindered efforts to analyze fine-root trait variation and link it with plant function and environmental conditions at a global scale. This Viewpoint addresses the need for a centralized fine-root trait database, and introduces the Fine-Root Ecology Database (FRED, http://roots.ornl.gov) which so far includes > 70 000 observations encompassing a broad range of rootmore » traits and also includes associated environmental data. FRED represents a critical step toward improving our understanding of below-ground plant ecology. For example, FRED facilitates the quantification of variation in fine-root traits across root orders, species, biomes, and environmental gradients while also providing a platform for assessments of covariation among root, leaf, and wood traits, the role of fine roots in ecosystem functioning, and the representation of fine roots in terrestrial biosphere models. There has been a continued input of observations into FRED to fill gaps in trait coverage will improve our understanding of changes in fine-root traits across space and time.« less

A global Fine-Root Ecology Database to address below-ground challenges in plant ecology

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

Iversen, Colleen M.; McCormack, M. Luke; Powell, A. Shafer

Variation and tradeoffs within and among plant traits are increasingly being harnessed by empiricists and modelers to understand and predict ecosystem processes under changing environmental conditions. And while fine roots play an important role in ecosystem functioning, fine-root traits are underrepresented in global trait databases. This has hindered efforts to analyze fine-root trait variation and link it with plant function and environmental conditions at a global scale. This Viewpoint addresses the need for a centralized fine-root trait database, and introduces the Fine-Root Ecology Database (FRED, http://roots.ornl.gov) which so far includes > 70 000 observations encompassing a broad range of rootmore » traits and also includes associated environmental data. FRED represents a critical step toward improving our understanding of below-ground plant ecology. For example, FRED facilitates the quantification of variation in fine-root traits across root orders, species, biomes, and environmental gradients while also providing a platform for assessments of covariation among root, leaf, and wood traits, the role of fine roots in ecosystem functioning, and the representation of fine roots in terrestrial biosphere models. There has been a continued input of observations into FRED to fill gaps in trait coverage will improve our understanding of changes in fine-root traits across space and time.« less

Uncovering the drivers of host-associated microbiota with joint species distribution modelling.

PubMed

Björk, Johannes R; Hui, Francis K C; O'Hara, Robert B; Montoya, Jose M

2018-06-01

In addition to the processes structuring free-living communities, host-associated microbiota are directly or indirectly shaped by the host. Therefore, microbiota data have a hierarchical structure where samples are nested under one or several variables representing host-specific factors, often spanning multiple levels of biological organization. Current statistical methods do not accommodate this hierarchical data structure and therefore cannot explicitly account for the effect of the host in structuring the microbiota. We introduce a novel extension of joint species distribution models (JSDMs) which can straightforwardly accommodate and discern between effects such as host phylogeny and traits, recorded covariates such as diet and collection site, among other ecological processes. Our proposed methodology includes powerful yet familiar outputs seen in community ecology overall, including (a) model-based ordination to visualize and quantify the main patterns in the data; (b) variance partitioning to assess how influential the included host-specific factors are in structuring the microbiota; and (c) co-occurrence networks to visualize microbe-to-microbe associations. © 2018 John Wiley & Sons Ltd.

Cultural macroevolution on neighbor graphs : vertical and horizontal transmission among Western North American Indian societies.

PubMed

Towner, Mary C; Grote, Mark N; Venti, Jay; Borgerhoff Mulder, Monique

2012-09-01

What are the driving forces of cultural macroevolution, the evolution of cultural traits that characterize societies or populations? This question has engaged anthropologists for more than a century, with little consensus regarding the answer. We develop and fit autologistic models, built upon both spatial and linguistic neighbor graphs, for 44 cultural traits of 172 societies in the Western North American Indian (WNAI) database. For each trait, we compare models including or excluding one or both neighbor graphs, and for the majority of traits we find strong evidence in favor of a model which uses both spatial and linguistic neighbors to predict a trait's distribution. Our results run counter to the assertion that cultural trait distributions can be explained largely by the transmission of traits from parent to daughter populations and are thus best analyzed with phylogenies. In contrast, we show that vertical and horizontal transmission pathways can be incorporated in a single model, that both transmission modes may indeed operate on the same trait, and that for most traits in the WNAI database, accounting for only one mode of transmission would result in a loss of information.

Applied genetic evaluations for production and functional traits in dairy cattle.

PubMed

Mark, T

2004-08-01

The objective of this study was to review the current status of genetic evaluation systems for production and functional traits as practiced in different Interbull member countries and to discuss that status in relation to research results and potential improvements. Thirty-one countries provided information. Substantial variation was evident for number of traits considered per country, trait definition, genetic evaluation procedure within trait, effects included, and how these were treated in genetic evaluation models. All countries lacked genetic evaluations for one or more economically important traits. Improvement in the genetic evaluation models, especially for many functional traits, could be achieved by closing the gaps between research and practice. More detailed and up to date information about national genetic evaluation systems for traits in different countries is available at www.interbull.org. Female fertility and workability traits were considered in many countries and could be next in line for international genetic evaluations.

Root architecture simulation improves the inference from seedling root phenotyping towards mature root systems

PubMed Central

Zhao, Jiangsan; Rewald, Boris; Leitner, Daniel; Nagel, Kerstin A.; Nakhforoosh, Alireza

2017-01-01

Abstract Root phenotyping provides trait information for plant breeding. A shortcoming of high-throughput root phenotyping is the limitation to seedling plants and failure to make inferences on mature root systems. We suggest root system architecture (RSA) models to predict mature root traits and overcome the inference problem. Sixteen pea genotypes were phenotyped in (i) seedling (Petri dishes) and (ii) mature (sand-filled columns) root phenotyping platforms. The RSA model RootBox was parameterized with seedling traits to simulate the fully developed root systems. Measured and modelled root length, first-order lateral number, and root distribution were compared to determine key traits for model-based prediction. No direct relationship in root traits (tap, lateral length, interbranch distance) was evident between phenotyping systems. RootBox significantly improved the inference over phenotyping platforms. Seedling plant tap and lateral root elongation rates and interbranch distance were sufficient model parameters to predict genotype ranking in total root length with an RSpearman of 0.83. Parameterization including uneven lateral spacing via a scaling function substantially improved the prediction of architectures underlying the differently sized root systems. We conclude that RSA models can solve the inference problem of seedling root phenotyping. RSA models should be included in the phenotyping pipeline to provide reliable information on mature root systems to breeding research. PMID:28168270

Analysis of Dynamic Data from Supersonic Retropropulsion Experiments in NASA Langley's Unitary Plan Wind Tunnel

NASA Technical Reports Server (NTRS)

Codoni, Joshua R.; Berry, Scott A.

2012-01-01

Recent experimental supersonic retropropulsion tests were conducted at the NASA Langley Research Center Unitary Plan Wind Tunnel Test Section 2 for a range of Mach numbers from 2.4 to 4.6. A 5-inch 70-degree sphere-cone forebody model with a 10-inch cylindrical aftbody experimental model was used which is capable of multiple retrorocket configurations. These configurations include a single central nozzle on the center point of the forebody, three nozzles at the forebody half-radius, and a combination of the first two configurations with no jets being plugged. A series of measurements were achieved through various instrumentation including forebody and aftbody pressure, internal pressures and temperatures, and high speed Schlieren visualization. Specifically, several high speed pressure transducers on the forebody and in the plenum were implemented to look at unsteady flow effects. The following work focuses on analyzing frequency traits due to the unsteady flow for a range of thrust coefficients for single, tri, and quad-nozzle test cases at freestream Mach 4.6 and angle of attack ranging from -8 degrees to +20 degrees. This analysis uses Matlab s fast Fourier transform, Welch's method (modified average of a periodogram), to create a power spectral density and analyze any high speed pressure transducer frequency traits due to the unsteady flow.

Pathways-Driven Sparse Regression Identifies Pathways and Genes Associated with High-Density Lipoprotein Cholesterol in Two Asian Cohorts

PubMed Central

Silver, Matt; Chen, Peng; Li, Ruoying; Cheng, Ching-Yu; Wong, Tien-Yin; Tai, E-Shyong; Teo, Yik-Ying; Montana, Giovanni

2013-01-01

Standard approaches to data analysis in genome-wide association studies (GWAS) ignore any potential functional relationships between gene variants. In contrast gene pathways analysis uses prior information on functional structure within the genome to identify pathways associated with a trait of interest. In a second step, important single nucleotide polymorphisms (SNPs) or genes may be identified within associated pathways. The pathways approach is motivated by the fact that genes do not act alone, but instead have effects that are likely to be mediated through their interaction in gene pathways. Where this is the case, pathways approaches may reveal aspects of a trait's genetic architecture that would otherwise be missed when considering SNPs in isolation. Most pathways methods begin by testing SNPs one at a time, and so fail to capitalise on the potential advantages inherent in a multi-SNP, joint modelling approach. Here, we describe a dual-level, sparse regression model for the simultaneous identification of pathways and genes associated with a quantitative trait. Our method takes account of various factors specific to the joint modelling of pathways with genome-wide data, including widespread correlation between genetic predictors, and the fact that variants may overlap multiple pathways. We use a resampling strategy that exploits finite sample variability to provide robust rankings for pathways and genes. We test our method through simulation, and use it to perform pathways-driven gene selection in a search for pathways and genes associated with variation in serum high-density lipoprotein cholesterol levels in two separate GWAS cohorts of Asian adults. By comparing results from both cohorts we identify a number of candidate pathways including those associated with cardiomyopathy, and T cell receptor and PPAR signalling. Highlighted genes include those associated with the L-type calcium channel, adenylate cyclase, integrin, laminin, MAPK signalling and immune function. PMID:24278029

Pathways-driven sparse regression identifies pathways and genes associated with high-density lipoprotein cholesterol in two Asian cohorts.

PubMed

Silver, Matt; Chen, Peng; Li, Ruoying; Cheng, Ching-Yu; Wong, Tien-Yin; Tai, E-Shyong; Teo, Yik-Ying; Montana, Giovanni

2013-11-01

Standard approaches to data analysis in genome-wide association studies (GWAS) ignore any potential functional relationships between gene variants. In contrast gene pathways analysis uses prior information on functional structure within the genome to identify pathways associated with a trait of interest. In a second step, important single nucleotide polymorphisms (SNPs) or genes may be identified within associated pathways. The pathways approach is motivated by the fact that genes do not act alone, but instead have effects that are likely to be mediated through their interaction in gene pathways. Where this is the case, pathways approaches may reveal aspects of a trait's genetic architecture that would otherwise be missed when considering SNPs in isolation. Most pathways methods begin by testing SNPs one at a time, and so fail to capitalise on the potential advantages inherent in a multi-SNP, joint modelling approach. Here, we describe a dual-level, sparse regression model for the simultaneous identification of pathways and genes associated with a quantitative trait. Our method takes account of various factors specific to the joint modelling of pathways with genome-wide data, including widespread correlation between genetic predictors, and the fact that variants may overlap multiple pathways. We use a resampling strategy that exploits finite sample variability to provide robust rankings for pathways and genes. We test our method through simulation, and use it to perform pathways-driven gene selection in a search for pathways and genes associated with variation in serum high-density lipoprotein cholesterol levels in two separate GWAS cohorts of Asian adults. By comparing results from both cohorts we identify a number of candidate pathways including those associated with cardiomyopathy, and T cell receptor and PPAR signalling. Highlighted genes include those associated with the L-type calcium channel, adenylate cyclase, integrin, laminin, MAPK signalling and immune function.

Functional identity and diversity of animals predict ecosystem functioning better than species-based indices

PubMed Central

Gagic, Vesna; Bartomeus, Ignasi; Jonsson, Tomas; Taylor, Astrid; Winqvist, Camilla; Fischer, Christina; Slade, Eleanor M.; Steffan-Dewenter, Ingolf; Emmerson, Mark; Potts, Simon G.; Tscharntke, Teja; Weisser, Wolfgang; Bommarco, Riccardo

2015-01-01

Drastic biodiversity declines have raised concerns about the deterioration of ecosystem functions and have motivated much recent research on the relationship between species diversity and ecosystem functioning. A functional trait framework has been proposed to improve the mechanistic understanding of this relationship, but this has rarely been tested for organisms other than plants. We analysed eight datasets, including five animal groups, to examine how well a trait-based approach, compared with a more traditional taxonomic approach, predicts seven ecosystem functions below- and above-ground. Trait-based indices consistently provided greater explanatory power than species richness or abundance. The frequency distributions of single or multiple traits in the community were the best predictors of ecosystem functioning. This implies that the ecosystem functions we investigated were underpinned by the combination of trait identities (i.e. single-trait indices) and trait complementarity (i.e. multi-trait indices) in the communities. Our study provides new insights into the general mechanisms that link biodiversity to ecosystem functioning in natural animal communities and suggests that the observed responses were due to the identity and dominance patterns of the trait composition rather than the number or abundance of species per se. PMID:25567651

Plant functional traits predict green roof ecosystem services.

PubMed

Lundholm, Jeremy; Tran, Stephanie; Gebert, Luke

2015-02-17

Plants make important contributions to the services provided by engineered ecosystems such as green roofs. Ecologists use plant species traits as generic predictors of geographical distribution, interactions with other species, and ecosystem functioning, but this approach has been little used to optimize engineered ecosystems. Four plant species traits (height, individual leaf area, specific leaf area, and leaf dry matter content) were evaluated as predictors of ecosystem properties and services in a modular green roof system planted with 21 species. Six indicators of ecosystem services, incorporating thermal, hydrological, water quality, and carbon sequestration functions, were predicted by the four plant traits directly or indirectly via their effects on aggregate ecosystem properties, including canopy density and albedo. Species average height and specific leaf area were the most useful traits, predicting several services via effects on canopy density or growth rate. This study demonstrates that easily measured plant traits can be used to select species to optimize green roof performance across multiple key services.

Identity processes and personality traits and types in adolescence: directionality of effects and developmental trajectories.

PubMed

Luyckx, Koen; Teppers, Eveline; Klimstra, Theo A; Rassart, Jessica

2014-08-01

Personality traits are hypothesized to be among the most important factors contributing to individual differences in identity development. However, longitudinal studies linking Big Five personality traits to contemporary identity models (in which multiple exploration and commitment processes are distinguished) are largely lacking. To gain more insight in the directionality of effect and the developmental interdependence of the Big Five and identity processes as forwarded in multilayered personality models, the present study assessed personality and identity in 1,037 adolescents 4 times over a period of 3 years. First, using cross-lagged path analysis, Big Five traits emerged as consistent predictors of identity exploration processes, whereas only one significant path from identity exploration to the Big Five was found. Second, using latent class growth analysis, 3 Big Five trajectory classes were identified, resembling the distinctions typically made between resilients, overcontrollers, and undercontrollers. These classes were characterized by different initial levels and (to a lesser extent) rates of change in commitment and exploration processes. In sum, important developmental associations linking personality traits to identity processes were uncovered, emphasizing the potential role of personality traits in identity development. Developmental implications and suggestions for future research are discussed. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Nutrient cycle benchmarks for earth system land model

NASA Astrophysics Data System (ADS)

Zhu, Q.; Riley, W. J.; Tang, J.; Zhao, L.

2017-12-01

Projecting future biosphere-climate feedbacks using Earth system models (ESMs) relies heavily on robust modeling of land surface carbon dynamics. More importantly, soil nutrient (particularly, nitrogen (N) and phosphorus (P)) dynamics strongly modulate carbon dynamics, such as plant sequestration of atmospheric CO2. Prevailing ESM land models all consider nitrogen as a potentially limiting nutrient, and several consider phosphorus. However, including nutrient cycle processes in ESM land models potentially introduces large uncertainties that could be identified and addressed by improved observational constraints. We describe the development of two nutrient cycle benchmarks for ESM land models: (1) nutrient partitioning between plants and soil microbes inferred from 15N and 33P tracers studies and (2) nutrient limitation effects on carbon cycle informed by long-term fertilization experiments. We used these benchmarks to evaluate critical hypotheses regarding nutrient cycling and their representation in ESMs. We found that a mechanistic representation of plant-microbe nutrient competition based on relevant functional traits best reproduced observed plant-microbe nutrient partitioning. We also found that for multiple-nutrient models (i.e., N and P), application of Liebig's law of the minimum is often inaccurate. Rather, the Multiple Nutrient Limitation (MNL) concept better reproduces observed carbon-nutrient interactions.

A General, Synthetic Model for Predicting Biodiversity Gradients from Environmental Geometry.

PubMed

Gross, Kevin; Snyder-Beattie, Andrew

2016-10-01

Latitudinal and elevational biodiversity gradients fascinate ecologists, and have inspired dozens of explanations. The geometry of the abiotic environment is sometimes thought to contribute to these gradients, yet evaluations of geometric explanations are limited by a fragmented understanding of the diversity patterns they predict. This article presents a mathematical model that synthesizes multiple pathways by which environmental geometry can drive diversity gradients. The model characterizes species ranges by their environmental niches and limits on range sizes and places those ranges onto the simplified geometries of a sphere or cone. The model predicts nuanced and realistic species-richness gradients, including latitudinal diversity gradients with tropical plateaus and mid-latitude inflection points and elevational diversity gradients with low-elevation diversity maxima. The model also illustrates the importance of a mid-environment effect that augments species richness at locations with intermediate environments. Model predictions match multiple empirical biodiversity gradients, depend on ecological traits in a testable fashion, and formally synthesize elements of several geometric models. Together, these results suggest that previous assessments of geometric hypotheses should be reconsidered and that environmental geometry may play a deeper role in driving biodiversity gradients than is currently appreciated.

Modelling the effect of temperament on BMI through appetite reactivity and self-regulation in eating: a Structural Equation Modelling approach in young adolescents.

PubMed

Godefroy, V; Trinchera, L; Romo, L; Rigal, N

2016-04-01

Appetitive traits and general temperament traits have both been correlated with adiposity and obesity in children. However, very few studies have tested structural models to identify the links between temperament, appetitive traits and adiposity in children. A validated structural model would help suggesting mechanisms to explain the impact of temperament on body mass index (BMI). In this study, we used Rothbart's heuristic definition of temperament as a starting point to define four appetitive traits, including two appetite reactivity dimensions (Appetite Arousal and Appetite Persistence) and two dimensions of self-regulation in eating (Self-regulation In Eating Without Hunger and Self-regulation in Eating Speed). We conducted a cross-sectional study in young adolescents to validate a structural model including these four appetitive traits, Effortful Control (a general temperament trait) and adiposity. A questionnaire assessing the four appetitive trait dimensions and Effortful Control was completed by adolescents from 10 to 14 years old (n=475), and their BMI-for-age was calculated (n=441). In total, 74% of the study participants were normal weight, 26% were overweight and 8% were obese. We then used structural equation modelling to test the structural model. We identified a well-fitting structural model (Comparative Fit Index=0.91; Root Mean Square Error of Approximation=0.04) that supports the hypothesis that Effortful Control impacts both dimensions of self-regulation in eating, which in turn are linked with both appetite reactivity dimensions. Moreover, Appetite Persistence is the only appetitive trait that was significantly related to adiposity (B=0.12; P<0.05). Our model shows that Effortful Control is related to adiposity through the mediation of an individual's 'eating temperament' (appetite reactivity and self-regulation in eating). Results suggest that young adolescents who exhibit high appetite reactivity but a low level of self-regulation in eating are at higher risk for excess adiposity.

The infinitesimal model: Definition, derivation, and implications.

PubMed

Barton, N H; Etheridge, A M; Véber, A

2017-12-01

Our focus here is on the infinitesimal model. In this model, one or several quantitative traits are described as the sum of a genetic and a non-genetic component, the first being distributed within families as a normal random variable centred at the average of the parental genetic components, and with a variance independent of the parental traits. Thus, the variance that segregates within families is not perturbed by selection, and can be predicted from the variance components. This does not necessarily imply that the trait distribution across the whole population should be Gaussian, and indeed selection or population structure may have a substantial effect on the overall trait distribution. One of our main aims is to identify some general conditions on the allelic effects for the infinitesimal model to be accurate. We first review the long history of the infinitesimal model in quantitative genetics. Then we formulate the model at the phenotypic level in terms of individual trait values and relationships between individuals, but including different evolutionary processes: genetic drift, recombination, selection, mutation, population structure, …. We give a range of examples of its application to evolutionary questions related to stabilising selection, assortative mating, effective population size and response to selection, habitat preference and speciation. We provide a mathematical justification of the model as the limit as the number M of underlying loci tends to infinity of a model with Mendelian inheritance, mutation and environmental noise, when the genetic component of the trait is purely additive. We also show how the model generalises to include epistatic effects. We prove in particular that, within each family, the genetic components of the individual trait values in the current generation are indeed normally distributed with a variance independent of ancestral traits, up to an error of order 1∕M. Simulations suggest that in some cases the convergence may be as fast as 1∕M. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

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.

Economic weights for maternal traits of sows, including sow longevity.

PubMed

Amer, P R; Ludemann, C I; Hermesch, S

2014-12-01

The objective of this study was to develop a transparent, comprehensive, and flexible model for each trait for the formulation of breeding objectives for sow traits in swine breeding programs. Economic values were derived from submodels considering a typical Australian pig production system. Differences in timing and expressions of traits were accounted for to derive economic weights that were compared on the basis of their relative size after multiplication by their corresponding genetic standard deviation to account for differences in scale and genetic variability present for each trait. The number of piglets born alive had the greatest contribution (27.1%) to a subindex containing only maternal traits, followed by daily gain (maternal; 22.0%) and sow mature weight (15.0%). Other traits considered in the maternal breeding objective were preweaning survival (11.8%), sow longevity (12.5%), gilt age at puberty (8.7%), and piglet survival at birth (3.1%). The economic weights for number of piglets born alive and preweaning piglet survival were found to be highly dependent on the definition of scale of enterprise, with each economic value increasing by approximately 100% when it was assumed that the value of extra output per sow could be captured, rather than assuming a consequent reduction in the number of sows to maintain a constant level of output from a farm enterprise. In the context of a full maternal line index that must account also for the expression of direct genetic traits by the growing piglet progeny of sows, the maternal traits contributed approximately half of the variation in the overall breeding objective. Deployment of more comprehensive maternal line indexes incorporating the new maternal traits described would lead to more balanced selection outcomes and improved survival of pigs. Future work could facilitate evaluation of the economic impacts of desired-gains indexes, which could further improve animal welfare through improved sow and piglet survival. The results justify further development of selection criteria and breeding value prediction systems for a wider range of maternal traits relevant to pig production systems.

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

Does weather shape rodents? Climate related changes in morphology of two heteromyid species

NASA Astrophysics Data System (ADS)

Wolf, Mosheh; Friggens, Michael; Salazar-Bravo, Jorge

2009-01-01

Geographical variation in morphometric characters in heteromyid rodents has often correlated with climate gradients. Here, we used the long-term database of rodents trapped in the Sevilleta National Wildlife Refuge in New Mexico, USA to test whether significant annual changes in external morphometric characters are observed in a region with large variations in temperature and precipitation. We looked at the relationships between multiple temperature and precipitation variables and a number of morphological traits (body mass, body, tail, hind leg, and ear length) for two heteromyid rodents, Dipodomys merriami and Perognathus flavescens. Because these rodents can live multiple years in the wild, the climate variables for the year of the capture and the previous 2 years were included in the analyses. Using multiple linear regressions, we found that all of our morphometric traits, with the exception of tail length in D. merriami, had a significant relationship with one or more of the climate variables used. Our results demonstrate that effects of climate change on morphological traits occur over short periods, even in noninsular mammal populations. It is unclear, though, whether these changes are the result of morphological plasticity or natural selection.

Freshwater Biological Traits Database (Traits)

EPA Pesticide Factsheets

The traits database was compiled for a project on climate change effects on river and stream ecosystems. The traits data, gathered from multiple sources, focused on information published or otherwise well-documented by trustworthy sources.

Improvement of Prediction Ability for Genomic Selection of Dairy Cattle by Including Dominance Effects

PubMed Central

Sun, Chuanyu; VanRaden, Paul M.; Cole, John B.; O'Connell, Jeffrey R.

2014-01-01

Dominance may be an important source of non-additive genetic variance for many traits of dairy cattle. However, nearly all prediction models for dairy cattle have included only additive effects because of the limited number of cows with both genotypes and phenotypes. The role of dominance in the Holstein and Jersey breeds was investigated for eight traits: milk, fat, and protein yields; productive life; daughter pregnancy rate; somatic cell score; fat percent and protein percent. Additive and dominance variance components were estimated and then used to estimate additive and dominance effects of single nucleotide polymorphisms (SNPs). The predictive abilities of three models with both additive and dominance effects and a model with additive effects only were assessed using ten-fold cross-validation. One procedure estimated dominance values, and another estimated dominance deviations; calculation of the dominance relationship matrix was different for the two methods. The third approach enlarged the dataset by including cows with genotype probabilities derived using genotyped ancestors. For yield traits, dominance variance accounted for 5 and 7% of total variance for Holsteins and Jerseys, respectively; using dominance deviations resulted in smaller dominance and larger additive variance estimates. For non-yield traits, dominance variances were very small for both breeds. For yield traits, including additive and dominance effects fit the data better than including only additive effects; average correlations between estimated genetic effects and phenotypes showed that prediction accuracy increased when both effects rather than just additive effects were included. No corresponding gains in prediction ability were found for non-yield traits. Including cows with derived genotype probabilities from genotyped ancestors did not improve prediction accuracy. The largest additive effects were located on chromosome 14 near DGAT1 for yield traits for both breeds; those SNPs also showed the largest dominance effects for fat yield (both breeds) as well as for Holstein milk yield. PMID:25084281

Accounting for standard errors of vision-specific latent trait in regression models.

PubMed

Wong, Wan Ling; Li, Xiang; Li, Jialiang; Wong, Tien Yin; Cheng, Ching-Yu; Lamoureux, Ecosse L

2014-07-11

To demonstrate the effectiveness of Hierarchical Bayesian (HB) approach in a modeling framework for association effects that accounts for SEs of vision-specific latent traits assessed using Rasch analysis. A systematic literature review was conducted in four major ophthalmic journals to evaluate Rasch analysis performed on vision-specific instruments. The HB approach was used to synthesize the Rasch model and multiple linear regression model for the assessment of the association effects related to vision-specific latent traits. The effectiveness of this novel HB one-stage "joint-analysis" approach allows all model parameters to be estimated simultaneously and was compared with the frequently used two-stage "separate-analysis" approach in our simulation study (Rasch analysis followed by traditional statistical analyses without adjustment for SE of latent trait). Sixty-six reviewed articles performed evaluation and validation of vision-specific instruments using Rasch analysis, and 86.4% (n = 57) performed further statistical analyses on the Rasch-scaled data using traditional statistical methods; none took into consideration SEs of the estimated Rasch-scaled scores. The two models on real data differed for effect size estimations and the identification of "independent risk factors." Simulation results showed that our proposed HB one-stage "joint-analysis" approach produces greater accuracy (average of 5-fold decrease in bias) with comparable power and precision in estimation of associations when compared with the frequently used two-stage "separate-analysis" procedure despite accounting for greater uncertainty due to the latent trait. Patient-reported data, using Rasch analysis techniques, do not take into account the SE of latent trait in association analyses. The HB one-stage "joint-analysis" is a better approach, producing accurate effect size estimations and information about the independent association of exposure variables with vision-specific latent traits. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

Evaluating alternate models to estimate genetic parameters of calving traits in United Kingdom Holstein-Friesian dairy cattle.

PubMed

Eaglen, Sophie A E; Coffey, Mike P; Woolliams, John A; Wall, Eileen

2012-07-28

The focus in dairy cattle breeding is gradually shifting from production to functional traits and genetic parameters of calving traits are estimated more frequently. However, across countries, various statistical models are used to estimate these parameters. This study evaluates different models for calving ease and stillbirth in United Kingdom Holstein-Friesian cattle. Data from first and later parity records were used. Genetic parameters for calving ease, stillbirth and gestation length were estimated using the restricted maximum likelihood method, considering different models i.e. sire (-maternal grandsire), animal, univariate and bivariate models. Gestation length was fitted as a correlated indicator trait and, for all three traits, genetic correlations between first and later parities were estimated. Potential bias in estimates was avoided by acknowledging a possible environmental direct-maternal covariance. The total heritable variance was estimated for each trait to discuss its theoretical importance and practical value. Prediction error variances and accuracies were calculated to compare the models. On average, direct and maternal heritabilities for calving traits were low, except for direct gestation length. Calving ease in first parity had a significant and negative direct-maternal genetic correlation. Gestation length was maternally correlated to stillbirth in first parity and directly correlated to calving ease in later parities. Multi-trait models had a slightly greater predictive ability than univariate models, especially for the lowly heritable traits. The computation time needed for sire (-maternal grandsire) models was much smaller than for animal models with only small differences in accuracy. The sire (-maternal grandsire) model was robust when additional genetic components were estimated, while the equivalent animal model had difficulties reaching convergence. For the evaluation of calving traits, multi-trait models show a slight advantage over univariate models. Extended sire models (-maternal grandsire) are more practical and robust than animal models. Estimated genetic parameters for calving traits of UK Holstein cattle are consistent with literature. Calculating an aggregate estimated breeding value including direct and maternal values should encourage breeders to consider both direct and maternal effects in selection decisions.

Evaluating alternate models to estimate genetic parameters of calving traits in United Kingdom Holstein-Friesian dairy cattle

PubMed Central

2012-01-01

Background The focus in dairy cattle breeding is gradually shifting from production to functional traits and genetic parameters of calving traits are estimated more frequently. However, across countries, various statistical models are used to estimate these parameters. This study evaluates different models for calving ease and stillbirth in United Kingdom Holstein-Friesian cattle. Methods Data from first and later parity records were used. Genetic parameters for calving ease, stillbirth and gestation length were estimated using the restricted maximum likelihood method, considering different models i.e. sire (−maternal grandsire), animal, univariate and bivariate models. Gestation length was fitted as a correlated indicator trait and, for all three traits, genetic correlations between first and later parities were estimated. Potential bias in estimates was avoided by acknowledging a possible environmental direct-maternal covariance. The total heritable variance was estimated for each trait to discuss its theoretical importance and practical value. Prediction error variances and accuracies were calculated to compare the models. Results and discussion On average, direct and maternal heritabilities for calving traits were low, except for direct gestation length. Calving ease in first parity had a significant and negative direct-maternal genetic correlation. Gestation length was maternally correlated to stillbirth in first parity and directly correlated to calving ease in later parities. Multi-trait models had a slightly greater predictive ability than univariate models, especially for the lowly heritable traits. The computation time needed for sire (−maternal grandsire) models was much smaller than for animal models with only small differences in accuracy. The sire (−maternal grandsire) model was robust when additional genetic components were estimated, while the equivalent animal model had difficulties reaching convergence. Conclusions For the evaluation of calving traits, multi-trait models show a slight advantage over univariate models. Extended sire models (−maternal grandsire) are more practical and robust than animal models. Estimated genetic parameters for calving traits of UK Holstein cattle are consistent with literature. Calculating an aggregate estimated breeding value including direct and maternal values should encourage breeders to consider both direct and maternal effects in selection decisions. PMID:22839757

Behavioral and Neurological Foundations for the Moral and Legal Implications of Intoxication, Addictive Behaviors and Disinhibition

PubMed Central

Leeman, Robert F.; Grant, Jon E.; Potenza, Marc N.

2009-01-01

Disinhibition and addictive behaviors are related and carry moral implications. Both typically involve diminished consideration of negative consequences, which may result in harm to oneself or others. Disinhibition may occur on state and trait levels, and addictive substances may elicit disinhibitory states, particularly when intoxication is reached. Data suggest that trait disinhibition and addictions may be conceptualized as involving misdirected motivation with underlying biological bases including genetic factors, alterations in neurotransmitter systems and differences in regional brain function. The influences of intoxication on the brain share similarities with cognitive impairments in individuals with chronic substance abuse and those with trait disinhibition related to frontal lobe injuries. These findings raise questions about volitional impairment and morality. Although impaired volition related to disinhibition and addictive behaviors has been studied from multiple perspectives, additional research is needed to further characterize mechanisms of impairment. Such findings may have important implications in multiple legal and psychiatric domains. PMID:19241397

The relationship between the Five-Factor Model personality traits and peptic ulcer disease in a large population-based adult sample.

PubMed

Realo, Anu; Teras, Andero; Kööts-Ausmees, Liisi; Esko, Tõnu; Metspalu, Andres; Allik, Jüri

2015-12-01

The current study examined the relationship between the Five-Factor Model personality traits and physician-confirmed peptic ulcer disease (PUD) diagnosis in a large population-based adult sample, controlling for the relevant behavioral and sociodemographic factors. Personality traits were assessed by participants themselves and by knowledgeable informants using the NEO Personality Inventory-3 (NEO PI-3). When controlling for age, sex, education, and cigarette smoking, only one of the five NEO PI-3 domain scales - higher Neuroticism - and two facet scales - lower A1: Trust and higher C1: Competence - made a small, yet significant contribution (p < 0.01) to predicting PUD in logistic regression analyses. In the light of these relatively modest associations, our findings imply that it is certain behavior (such as smoking) and sociodemographic variables (such as age, gender, and education) rather than personality traits that are associated with the diagnosis of PUD at a particular point in time. Further prospective studies with a longitudinal design and multiple assessments would be needed to fully understand if the FFM personality traits serve as risk factors for the development of PUD. © 2015 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

Inferring relationships between clinical mastitis, productivity and fertility: a recursive model application including genetics, farm associated herd management, and cow-specific antibiotic treatments.

PubMed

Rehbein, Pia; Brügemann, Kerstin; Yin, Tong; V Borstel, U König; Wu, Xiao-Lin; König, Sven

2013-10-01

A dataset of test-day records, fertility traits, and one health trait including 1275 Brown Swiss cows kept in 46 small-scale organic farms was used to infer relationships among these traits based on recursive Gaussian-threshold models. Test-day records included milk yield (MY), protein percentage (PROT-%), fat percentage (FAT-%), somatic cell score (SCS), the ratio of FAT-% to PROT-% (FPR), lactose percentage (LAC-%), and milk urea nitrogen (MUN). Female fertility traits were defined as the interval from calving to first insemination (CTFS) and success of a first insemination (SFI), and the health trait was clinical mastitis (CM). First, a tri-trait model was used which postulated the recursive effect of a test-day observation in the early period of lactation on liability to CM (LCM), and further the recursive effect of LCM on the following test-day observation. For CM and female fertility traits, a bi-trait recursive Gaussian-threshold model was employed to estimate the effects from CM to CTFS and from CM on SFI. The recursive effects from CTFS and SFI onto CM were not relevant, because CM was recorded prior to the measurements for CTFS and SFI. Results show that the posterior heritability for LCM was 0.05, and for all other traits, heritability estimates were in reasonable ranges, each with a small posterior SD. Lowest heritability estimates were obtained for female reproduction traits, i.e. h(2)=0.02 for SFI, and h(2)≈0 for CTFS. Posterior estimates of genetic correlations between LCM and production traits (MY and MUN), and between LCM and somatic cell score (SCS), were large and positive (0.56-0.68). Results confirm the genetic antagonism between MY and LCM, and the suitability of SCS as an indicator trait for CM. Structural equation coefficients describe the impact of one trait on a second trait on the phenotypic pathway. Higher values for FAT-% and FPR were associated with a higher LCM. The rate of change in FAT-% and in FPR in the ongoing lactation with respect to the previous LCM was close to zero. Estimated recursive effects between SCS and CM were positive, implying strong phenotypic impacts between both traits. Structural equation coefficients explained a detrimental impact of CM on female fertility traits CTFS and SFI. The cow-specific CM treatment had no significant impact on performance traits in the ongoing lactation. For most treatments, beta-lactam-antibiotics were used, but test-day SCS and production traits after the beta-lactam-treatment were comparable to those after other antibiotic as well as homeopathic treatments. Copyright © 2013 Elsevier B.V. All rights reserved.

A Model to Explain Plant Growth Promotion Traits: A Multivariate Analysis of 2,211 Bacterial Isolates

PubMed Central

da Costa, Pedro Beschoren; Granada, Camille E.; Ambrosini, Adriana; Moreira, Fernanda; de Souza, Rocheli; dos Passos, João Frederico M.; Arruda, Letícia; Passaglia, Luciane M. P.

2014-01-01

Plant growth-promoting bacteria can greatly assist sustainable farming by improving plant health and biomass while reducing fertilizer use. The plant-microorganism-environment interaction is an open and complex system, and despite the active research in the area, patterns in root ecology are elusive. Here, we simultaneously analyzed the plant growth-promoting bacteria datasets from seven independent studies that shared a methodology for bioprospection and phenotype screening. The soil richness of the isolate's origin was classified by a Principal Component Analysis. A Categorical Principal Component Analysis was used to classify the soil richness according to isolate's indolic compound production, siderophores production and phosphate solubilization abilities, and bacterial genera composition. Multiple patterns and relationships were found and verified with nonparametric hypothesis testing. Including niche colonization in the analysis, we proposed a model to explain the expression of bacterial plant growth-promoting traits according to the soil nutritional status. Our model shows that plants favor interaction with growth hormone producers under rich nutrient conditions but favor nutrient solubilizers under poor conditions. We also performed several comparisons among the different genera, highlighting interesting ecological interactions and limitations. Our model could be used to direct plant growth-promoting bacteria bioprospection and metagenomic sampling. PMID:25542031

DNA mismatch repair gene MSH6 implicated in determining age at natural menopause

PubMed Central

Perry, John R.B.; Hsu, Yi-Hsiang; Chasman, Daniel I.; Johnson, Andrew D.; Elks, Cathy; Albrecht, Eva; Andrulis, Irene L.; Beesley, Jonathan; Berenson, Gerald S.; Bergmann, Sven; Bojesen, Stig E.; Bolla, Manjeet K.; Brown, Judith; Buring, Julie E.; Campbell, Harry; Chang-Claude, Jenny; Chenevix-Trench, Georgia; Corre, Tanguy; Couch, Fergus J.; Cox, Angela; Czene, Kamila; D'adamo, Adamo Pio; Davies, Gail; Deary, Ian J.; Dennis, Joe; Easton, Douglas F.; Engelhardt, Ellen G.; Eriksson, Johan G.; Esko, Tõnu; Fasching, Peter A.; Figueroa, Jonine D.; Flyger, Henrik; Fraser, Abigail; Garcia-Closas, Montse; Gasparini, Paolo; Gieger, Christian; Giles, Graham; Guenel, Pascal; Hägg, Sara; Hall, Per; Hayward, Caroline; Hopper, John; Ingelsson, Erik; Kardia, Sharon L.R.; Kasiman, Katherine; Knight, Julia A.; Lahti, Jari; Lawlor, Debbie A.; Magnusson, Patrik K.E.; Margolin, Sara; Marsh, Julie A.; Metspalu, Andres; Olson, Janet E.; Pennell, Craig E.; Polasek, Ozren; Rahman, Iffat; Ridker, Paul M.; Robino, Antonietta; Rudan, Igor; Rudolph, Anja; Salumets, Andres; Schmidt, Marjanka K.; Schoemaker, Minouk J.; Smith, Erin N.; Smith, Jennifer A.; Southey, Melissa; Stöckl, Doris; Swerdlow, Anthony J.; Thompson, Deborah J.; Truong, Therese; Ulivi, Sheila; Waldenberger, Melanie; Wang, Qin; Wild, Sarah; Wilson, James F; Wright, Alan F.; Zgaga, Lina; Ong, Ken K.; Murabito, Joanne M.; Karasik, David; Murray, Anna

2014-01-01

The length of female reproductive lifespan is associated with multiple adverse outcomes, including breast cancer, cardiovascular disease and infertility. The biological processes that govern the timing of the beginning and end of reproductive life are not well understood. Genetic variants are known to contribute to ∼50% of the variation in both age at menarche and menopause, but to date the known genes explain <15% of the genetic component. We have used genome-wide association in a bivariate meta-analysis of both traits to identify genes involved in determining reproductive lifespan. We observed significant genetic correlation between the two traits using genome-wide complex trait analysis. However, we found no robust statistical evidence for individual variants with an effect on both traits. A novel association with age at menopause was detected for a variant rs1800932 in the mismatch repair gene MSH6 (P = 1.9 × 10−9), which was also associated with altered expression levels of MSH6 mRNA in multiple tissues. This study contributes to the growing evidence that DNA repair processes play a key role in ovarian ageing and could be an important therapeutic target for infertility. PMID:24357391

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

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.

Phenotypic and genetic relationships of residual feed intake measures and their component traits with fatty acid composition in subcutaneous adipose of beef cattle.

PubMed

Zhang, F; Ekine-Dzivenu, C; Vinsky, M; Basarab, J A; Aalhus, J L; Dugan, M E R; Li, C

2017-07-01

Feed efficiency is of particular interest to the beef industry because feed is the largest variable cost in production and fatty acid composition is emerging as an important trait, both economically and socially, due to the potential implications of dietary fatty acids on human health. Quantifying correlations between feed efficiency and fatty acid composition will contribute to construction of optimal multiple-trait selection indexes to maximize beef production profitability. In the present study, we estimated phenotypic and genetic correlations of feed efficiency measures including residual feed intake (RFI), RFI adjusted for final ultrasound backfat thickness (RFIf); their component traits ADG, DMI, and metabolic BW; and final ultrasound backfat thickness measured at the end of feedlot test with 25 major fatty acids in the subcutaneous adipose tissues of 1,366 finishing steers and heifers using bivariate animal models. The phenotypic correlations of RFI and RFIf with the 25 individual and grouped fatty acid traits were generally low (<0.25 in magnitude). However, relatively stronger genetic correlation coefficients of RFI and RFIf with PUFA traits including the -6:-3 ratio (0.52 ± 0.29 and 0.45 ± 0.31, respectively), 18:2-6 (0.45 ± 0.18 and 0.40 ± 0.19, respectively), -6 (0.43 ± 0.18 and 0.38 ± 0.19, respectively), PUFA (0.42 ± 0.18 and 0.36 ± 0.20, respectively), and 9-16:1 (-0.43 ± 0.20 and -0.33 ± 0.22, respectively) were observed. Hence, selection for low-RFI or more efficient beef cattle will improve fatty acid profiles by lowering the content of -6 PUFA, thus reducing the ratio of -6 to -3 along with increasing the amount of 9-16:1. Moderate to moderately high genetic correlations were also observed for DMI with 9-14:1 (-0.32 ± 0.17) and the sum of CLA analyzed (SumCLA; -0.45 ± 0.21), suggesting that selection of beef cattle with lower DMI will lead to an increase amount of 9-14:1 and SumCLA in the subcutaneous adipose tissue. However, unfavorable genetic correlations were detected for ADG with 11-18:1 (-0.38 ± 0.23) and SumCLA (-0.73 ± 0.26), implying that selection of beef cattle with a better growth rate will decrease the contents of healthy fatty acids 11-18:1 and SumCLA. Therefore, it is recommended that a multiple-trait selection index be used when genetic improvements of fatty acid composition, feed efficiency, feed intake, and growth are important in the breeding objective.

Assessing and Exploiting Functional Diversity in Germplasm Pools to Enhance Abiotic Stress Adaptation and Yield in Cereals and Food Legumes

PubMed Central

Dwivedi, Sangam L.; Scheben, Armin; Edwards, David; Spillane, Charles; Ortiz, Rodomiro

2017-01-01

There is a need to accelerate crop improvement by introducing alleles conferring host plant resistance, abiotic stress adaptation, and high yield potential. Elite cultivars, landraces and wild relatives harbor useful genetic variation that needs to be more easily utilized in plant breeding. We review genome-wide approaches for assessing and identifying alleles associated with desirable agronomic traits in diverse germplasm pools of cereals and legumes. Major quantitative trait loci and single nucleotide polymorphisms (SNPs) associated with desirable agronomic traits have been deployed to enhance crop productivity and resilience. These include alleles associated with variation conferring enhanced photoperiod and flowering traits. Genetic variants in the florigen pathway can provide both environmental flexibility and improved yields. SNPs associated with length of growing season and tolerance to abiotic stresses (precipitation, high temperature) are valuable resources for accelerating breeding for drought-prone environments. Both genomic selection and genome editing can also harness allelic diversity and increase productivity by improving multiple traits, including phenology, plant architecture, yield potential and adaptation to abiotic stresses. Discovering rare alleles and useful haplotypes also provides opportunities to enhance abiotic stress adaptation, while epigenetic variation has potential to enhance abiotic stress adaptation and productivity in crops. By reviewing current knowledge on specific traits and their genetic basis, we highlight recent developments in the understanding of crop functional diversity and identify potential candidate genes for future use. The storage and integration of genetic, genomic and phenotypic information will play an important role in ensuring broad and rapid application of novel genetic discoveries by the plant breeding community. Exploiting alleles for yield-related traits would allow improvement of selection efficiency and overall genetic gain of multigenic traits. An integrated approach involving multiple stakeholders specializing in management and utilization of genetic resources, crop breeding, molecular biology and genomics, agronomy, stress tolerance, and reproductive/seed biology will help to address the global challenge of ensuring food security in the face of growing resource demands and climate change induced stresses. PMID:28900432

Assessing and Exploiting Functional Diversity in Germplasm Pools to Enhance Abiotic Stress Adaptation and Yield in Cereals and Food Legumes.

PubMed

Dwivedi, Sangam L; Scheben, Armin; Edwards, David; Spillane, Charles; Ortiz, Rodomiro

2017-01-01

There is a need to accelerate crop improvement by introducing alleles conferring host plant resistance, abiotic stress adaptation, and high yield potential. Elite cultivars, landraces and wild relatives harbor useful genetic variation that needs to be more easily utilized in plant breeding. We review genome-wide approaches for assessing and identifying alleles associated with desirable agronomic traits in diverse germplasm pools of cereals and legumes. Major quantitative trait loci and single nucleotide polymorphisms (SNPs) associated with desirable agronomic traits have been deployed to enhance crop productivity and resilience. These include alleles associated with variation conferring enhanced photoperiod and flowering traits. Genetic variants in the florigen pathway can provide both environmental flexibility and improved yields. SNPs associated with length of growing season and tolerance to abiotic stresses (precipitation, high temperature) are valuable resources for accelerating breeding for drought-prone environments. Both genomic selection and genome editing can also harness allelic diversity and increase productivity by improving multiple traits, including phenology, plant architecture, yield potential and adaptation to abiotic stresses. Discovering rare alleles and useful haplotypes also provides opportunities to enhance abiotic stress adaptation, while epigenetic variation has potential to enhance abiotic stress adaptation and productivity in crops. By reviewing current knowledge on specific traits and their genetic basis, we highlight recent developments in the understanding of crop functional diversity and identify potential candidate genes for future use. The storage and integration of genetic, genomic and phenotypic information will play an important role in ensuring broad and rapid application of novel genetic discoveries by the plant breeding community. Exploiting alleles for yield-related traits would allow improvement of selection efficiency and overall genetic gain of multigenic traits. An integrated approach involving multiple stakeholders specializing in management and utilization of genetic resources, crop breeding, molecular biology and genomics, agronomy, stress tolerance, and reproductive/seed biology will help to address the global challenge of ensuring food security in the face of growing resource demands and climate change induced stresses.

Children's resilience and trauma-specific cognitive behavioral therapy: Comparing resilience as an outcome, a trait, and a process.

PubMed

Happer, Kaitlin; Brown, Elissa J; Sharma-Patel, Komal

2017-11-01

Resilience, which is associated with relatively positive outcomes following negative life experiences, is an important research target in the field of child maltreatment (Luthar et al., 2000). The extant literature contains multiple conceptualizations of resilience, which hinders development in research and clinical utility. Three models emerge from the literature: resilience as an immediate outcome (i.e., behavioral or symptom response), resilience as a trait, and resilience as a dynamic process. The current study compared these models in youth undergoing trauma-specific cognitive behavioral therapy. Results provide the most support for resilience as a process, in which increase in resilience preceded associated decrease in posttraumatic stress and depressive symptoms. There was partial support for resilience conceptualized as an outcome, and minimal support for resilience as a trait. Results of the models are compared and discussed in the context of existing literature and in light of potential clinical implications for maltreated youth seeking treatment. Copyright © 2017 Elsevier Ltd. All rights reserved.

Genetic analysis of semen production traits of Japanese Black and Holstein bulls: genome-wide marker-based estimation of genetic parameters and environmental effect trends.

PubMed

Atagi, Y; Onogi, A; Kinukawa, M; Ogino, A; Kurogi, K; Uchiyama, K; Yasumori, T; Adachi, K; Togashi, K; Iwata, H

2017-05-01

The semen production traits of bulls from 2 major cattle breeds in Japan, Holstein and Japanese Black, were analyzed comprehensively using genome-wide markers. Weaker genetic correlations were observed between the 2 age groups (1 to 3 yr old and 4 to 6 yr old) regarding semen volume and sperm motility compared with those observed for sperm number and motility after freeze-thawing. The preselection of collected semen for freezing had a limited effect. Given the increasing importance of bull proofs at a young age because of genomic selection and the results from preliminary studies, we used a multiple-trait model that included motility after freeze-thawing with records collected at young ages. Based on variations in contemporary group effects, accounting for both seasonal and management factors, Holstein bulls may be more sensitive than Japanese Black bulls to seasonal environmental variations; however, the seasonal variations of contemporary group effects were smaller than those of overall contemporary group effects. The improvement of motilities, recorded immediately after collection and freeze-thawing, was observed in recent years; thus, good management and better freeze-thawing protocol may alleviate seasonal phenotypic differences. The detrimental effects of inbreeding were observed in all traits of both breeds; accordingly, the selection of candidate bulls with high inbreeding coefficients should be avoided per general recommendations. Semen production traits have never been considered for bull selection. However, negative genetic trends were observed. The magnitudes of the estimated h were comparable to those of other economically important traits. A single-step genomic BLUP will provide more accurate predictions of breeding values compared with BLUP; thus, marker genotype information is useful for estimating the genetic merits of bulls for semen production traits. The selection of these traits would improve sperm viability, a component related to breeding success, and alleviate negative genetic trends.

The genomic architecture and association genetics of adaptive characters using a candidate SNP approach in boreal black spruce

PubMed Central

2013-01-01

Background The genomic architecture of adaptive traits remains poorly understood in non-model plants. Various approaches can be used to bridge this gap, including the mapping of quantitative trait loci (QTL) in pedigrees, and genetic association studies in non-structured populations. Here we present results on the genomic architecture of adaptive traits in black spruce, which is a widely distributed conifer of the North American boreal forest. As an alternative to the usual candidate gene approach, a candidate SNP approach was developed for association testing. Results A genetic map containing 231 gene loci was used to identify QTL that were related to budset timing and to tree height assessed over multiple years and sites. Twenty-two unique genomic regions were identified, including 20 that were related to budset timing and 6 that were related to tree height. From results of outlier detection and bulk segregant analysis for adaptive traits using DNA pool sequencing of 434 genes, 52 candidate SNPs were identified and subsequently tested in genetic association studies for budset timing and tree height assessed over multiple years and sites. A total of 34 (65%) SNPs were significantly associated with budset timing, or tree height, or both. Although the percentages of explained variance (PVE) by individual SNPs were small, several significant SNPs were shared between sites and among years. Conclusions The sharing of genomic regions and significant SNPs between budset timing and tree height indicates pleiotropic effects. Significant QTLs and SNPs differed quite greatly among years, suggesting that different sets of genes for the same characters are involved at different stages in the tree’s life history. The functional diversity of genes carrying significant SNPs and low observed PVE further indicated that a large number of polymorphisms are involved in adaptive genetic variation. Accordingly, for undomesticated species such as black spruce with natural populations of large effective size and low linkage disequilibrium, efficient marker systems that are predictive of adaptation should require the survey of large numbers of SNPs. Candidate SNP approaches like the one developed in the present study could contribute to reducing these numbers. PMID:23724860

Multitrophic functional diversity predicts ecosystem functioning in experimental assemblages of estuarine consumers.

PubMed

Lefcheck, Jonathan S; Duffy, J Emmett

2015-11-01

The use of functional traits to explain how biodiversity affects ecosystem functioning has attracted intense interest, yet few studies have a priori altered functional diversity, especially in multitrophic communities. Here, we manipulated multivariate functional diversity of estuarine grazers and predators within multiple levels of species richness to test how species richness and functional diversity predicted ecosystem functioning in a multitrophic food web. Community functional diversity was a better predictor than species richness for the majority of ecosystem properties, based on generalized linear mixed-effects models. Combining inferences from eight traits into a single multivariate index increased prediction accuracy of these models relative to any individual trait. Structural equation modeling revealed that functional diversity of both grazers and predators was important in driving final biomass within trophic levels, with stronger effects observed for predators. We also show that different species drove different ecosystem responses, with evidence for both sampling effects and complementarity. Our study extends experimental investigations of functional trait diversity to a multilevel food web, and demonstrates that functional diversity can be more accurate and effective than species richness in predicting community biomass in a food web context.

A Bending Willow Tree: A Japanese (Morita Therapy) Model of Human Nature and Client Change.

ERIC Educational Resources Information Center

Ishiyama, F. Ishu

2003-01-01

Japanese Morita therapy is discussed to highlight its culturally and theoretically unique perspectives on human nature and client change. Key features of this theory are: theory of the nervous trait; multiple-dimensional model of causes and treatment of nervous neurosis; theory of mental attachment; reframing anxiety into constructive desires; and…

ON MODEL SELECTION STRATEGIES TO IDENTIFY GENES UNDERLYING BINARY TRAITS USING GENOME-WIDE ASSOCIATION DATA.

PubMed

Wu, Zheyang; Zhao, Hongyu

2012-01-01

For more fruitful discoveries of genetic variants associated with diseases in genome-wide association studies, it is important to know whether joint analysis of multiple markers is more powerful than the commonly used single-marker analysis, especially in the presence of gene-gene interactions. This article provides a statistical framework to rigorously address this question through analytical power calculations for common model search strategies to detect binary trait loci: marginal search, exhaustive search, forward search, and two-stage screening search. Our approach incorporates linkage disequilibrium, random genotypes, and correlations among score test statistics of logistic regressions. We derive analytical results under two power definitions: the power of finding all the associated markers and the power of finding at least one associated marker. We also consider two types of error controls: the discovery number control and the Bonferroni type I error rate control. After demonstrating the accuracy of our analytical results by simulations, we apply them to consider a broad genetic model space to investigate the relative performances of different model search strategies. Our analytical study provides rapid computation as well as insights into the statistical mechanism of capturing genetic signals under different genetic models including gene-gene interactions. Even though we focus on genetic association analysis, our results on the power of model selection procedures are clearly very general and applicable to other studies.

ON MODEL SELECTION STRATEGIES TO IDENTIFY GENES UNDERLYING BINARY TRAITS USING GENOME-WIDE ASSOCIATION DATA

PubMed Central

Wu, Zheyang; Zhao, Hongyu

2013-01-01

For more fruitful discoveries of genetic variants associated with diseases in genome-wide association studies, it is important to know whether joint analysis of multiple markers is more powerful than the commonly used single-marker analysis, especially in the presence of gene-gene interactions. This article provides a statistical framework to rigorously address this question through analytical power calculations for common model search strategies to detect binary trait loci: marginal search, exhaustive search, forward search, and two-stage screening search. Our approach incorporates linkage disequilibrium, random genotypes, and correlations among score test statistics of logistic regressions. We derive analytical results under two power definitions: the power of finding all the associated markers and the power of finding at least one associated marker. We also consider two types of error controls: the discovery number control and the Bonferroni type I error rate control. After demonstrating the accuracy of our analytical results by simulations, we apply them to consider a broad genetic model space to investigate the relative performances of different model search strategies. Our analytical study provides rapid computation as well as insights into the statistical mechanism of capturing genetic signals under different genetic models including gene-gene interactions. Even though we focus on genetic association analysis, our results on the power of model selection procedures are clearly very general and applicable to other studies. PMID:23956610

A meta-analysis of zooplankton functional traits influencing ecosystem function.

PubMed

Hébert, Marie-Pier; Beisner, Beatrix E; Maranger, Roxane

2016-04-01

The use of functional traits to characterize community composition has been proposed as a more effective way to link community structure to ecosystem functioning. Organismal morphology, body stoichiometry, and physiology can be readily linked to large-scale ecosystem processes through functional traits that inform on interspecific and species-environment interactions; yet such effect traits are still poorly included in trait-based approaches. Given their key trophic position in aquatic ecosystems, individual zooplankton affect energy fluxes and elemental processing. We compiled a large database of zooplankton traits contributing to carbon, nitrogen, and phosphorus cycling and examined the effect of classification and habitat (marine vs. freshwater) on trait relationships. Respiration and nutrient excretion rates followed mass-dependent scaling in both habitats, with exponents ranging from 0.70 to 0.90. Our analyses revealed surprising differences in allometry and respiration between habitats, with freshwater species having lower length-specific mass and three times higher mass-specific respiration rates. These differences in traits point to implications for ecological strategies as well as overall carbon storage and fluxes based on habitat type. Our synthesis quantifies multiple trait relationships and links organisms to ecosystem processes they influence, enabling a more complete integration of aquatic community ecology and biogeochemistry through the promising use of effect traits.

Psychological traits underlying different killing methods among Malaysian male murderers.

PubMed

Kamaluddin, Mohammad Rahim; Shariff, Nadiah Syariani; Nurfarliza, Siti; Othman, Azizah; Ismail, Khaidzir H; Mat Saat, Geshina Ayu

2014-04-01

Murder is the most notorious crime that violates religious, social and cultural norms. Examining the types and number of different killing methods that used are pivotal in a murder case. However, the psychological traits underlying specific and multiple killing methods are still understudied. The present study attempts to fill this gap in knowledge by identifying the underlying psychological traits of different killing methods among Malaysian murderers. The study adapted an observational cross-sectional methodology using a guided self-administered questionnaire for data collection. The sampling frame consisted of 71 Malaysian male murderers from 11 Malaysian prisons who were selected using purposive sampling method. The participants were also asked to provide the types and number of different killing methods used to kill their respective victims. An independent sample t-test was performed to establish the mean score difference of psychological traits between the murderers who used single and multiple types of killing methods. Kruskal-Wallis tests were carried out to ascertain the psychological trait differences between specific types of killing methods. The results suggest that specific psychological traits underlie the type and number of different killing methods used during murder. The majority (88.7%) of murderers used a single method of killing. Multiple methods of killing was evident in 'premeditated' murder compared to 'passion' murder, and revenge was a common motive. Examples of multiple methods are combinations of stabbing and strangulation or slashing and physical force. An exception was premeditated murder committed with shooting, when it was usually a single method, attributed to the high lethality of firearms. Shooting was also notable when the motive was financial gain or related to drug dealing. Murderers who used multiple killing methods were more aggressive and sadistic than those who used a single killing method. Those who used multiple methods or slashing also displayed a higher level of minimisation traits. Despite its limitations, this study has provided some light on the underlying psychological traits of different killing methods which is useful in the field of criminology.

Associations of anger, anxiety, and depressive symptoms with carotid arterial wall thickness: the multi-ethnic study of atherosclerosis.

PubMed

Ohira, Tetsuya; Diez Roux, Ana V; Polak, Joseph F; Homma, Shunichi; Iso, Hiroyasu; Wasserman, Bruce A

2012-06-01

Carotid arterial wall thickness, measured as intima-media thickness (IMT), is an early subclinical indicator of cardiovascular disease. Few studies have investigated the association of psychological factors with IMT across multiple ethnic groups and by sex. We included 6561 men and women (2541 whites, 1790 African Americans, 1436 Hispanics, and 794 Chinese) aged 45 to 84 years who took part in the first examination of the Multi-Ethnic Study of Atherosclerosis. Associations of trait anger, trait anxiety, and depressive symptoms with mean values of common carotid artery (CCA) and internal carotid artery (ICA) IMTs were investigated using multivariable regression and logistic models. In age-, sex-, and race/ethnicity-adjusted analyses, the trait anger score was positively associated with CCA and ICA IMTs (mean differences per 1-standard deviation increment of trait anger score were 0.014 [95% confidence interval {CI} = 0.003-0.025, p = .01] and 0.054 [95% CI = 0.017-0.090, p = .004] for CCA and ICA IMTs, respectively). Anger was also associated with the presence of carotid plaque (age-, sex-, and race/ethnicity-adjusted odds ratio per 1-standard deviation increase in trait anger = 1.27 [95% CI = 1.06-1.52]). The associations of the anger score with thicker IMT were attenuated after adjustment for covariates but remained statistically significant. Associations were stronger in men than in women and in whites than in other race/ethnic groups, but heterogeneity was only marginally statistically significant by race/ethnicity. There was no association of depressive symptoms or trait anxiety with IMT. Only one of the three measures examined was associated with IMT, and the patterns seemed to be heterogeneous across race/ethnic groups.

High-throughput behavioral phenotyping of drug and alcohol susceptibility traits in the expanded panel of BXD recombinant inbred strains

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

Philip, Vivek M; Ansah, T; Blaha, C,

Genetic reference populations, particularly the BXD recombinant inbred strains, are a valuable resource for the discovery of the bio-molecular substrates and genetic drivers responsible for trait variation and co- ariation. This approach can be profitably applied in the analysis of susceptibility and mechanisms of drug and alcohol use disorders for which many predisposing behaviors may predict occurrence and manifestation of increased preference for these substances. Many of these traits are modeled by common mouse behavioral assays, facilitating the detection of patterns and sources of genetic co-regulation of predisposing phenotypes and substance consumption. Members of the Tennessee Mouse Genome Consortium havemore » obtained behavioral phenotype data from 260 measures related to multiple behavioral assays across several domains: self-administration, response to, and withdrawal from cocaine, MDMA, morphine and alcohol; novelty seeking; behavioral despair and related neurological phenomena; pain sensitivity; stress sensitivity; anxiety; hyperactivity; and sleep/wake cycles. All traits have been measured in both sexes and the recently expanded panel of 69 additional BXD recombinant inbred strains (N=69). Sex differences and heritability estimates were obtained for each trait, and a comparison of early (N = 32) and recent BXD RI lines was performed. Primary data is publicly available for heritability, sex difference and genetic analyses using www.GeneNetwork.org. These analyses include QTL detection and genetic analysis of gene expression. Stored results from these analyses are available at http://ontologicaldiscovery.org for comparison to other genomic analysis results. Together with the results of related studies, these data form a public resource for integrative systems genetic analysis of neurobehavioral traits.« less

Genetic control of complex traits, with a focus on reproduction in pigs.

PubMed

Zak, Louisa J; Gaustad, Ann Helen; Bolarin, Alfonso; Broekhuijse, Marleen L W J; Walling, Grant A; Knol, Egbert F

2017-09-01

Reproductive traits are complex, and desirable reproductive phenotypes, such as litter size or semen quality, are true polygenetic traits determined by multiple gene regulatory pathways. Each individual gene contributes to the overall variation in these traits, so genetic improvements can be achieved using conventional selection methodology. In the past, a pedigree-based-relationship matrix was used; this is now replaced by a combination of pedigree-based- and genomic-relationship matrices. The heritability of reproductive traits is low to moderate, so large-scale data recording is required to identify specific, selectable attributes. Male reproductive traits-including ejaculate volume and sperm progressive motility-are moderately heritable, and could be used in selection programs. A few high-merit artificial-insemination boars can impact many sow populations, so additional knowledge about male reproduction-specifically pre-pubertal detection of infertility and the technologies of semen cryopreservation and sex sorting-should further improve global breeding efforts. Conversely, female pig reproduction is currently a limiting factor of genetic improvement. Litter size and farrowing interval are the main obstacles to increasing selection intensity and to reducing generation interval in a breeding program. Age at puberty and weaning-to-estrus interval can be selected for, thereby reducing the number of non-productive days. The number of piglets born alive and litter weights are also reliably influenced by genetic selection. Characterization of genotype-environment interactions will provide opportunities to match genetics to specific farm systems. Continued investment to understand physiological models for improved phenotyping and the development of technologies to facilitate pig embryo production for genetic selection are warranted to ensure optimal breeding in future generations. © 2017 Wiley Periodicals, Inc.

Can multi-generational exposure to ocean warming and acidification lead to the adaptation of life history and physiology in a marine metazoan?

PubMed

Gibbin, Emma M; Chakravarti, Leela J; Jarrold, Michael D; Christen, Felix; Turpin, Vincent; Massamba N'Siala, Gloria; Blier, Pierre U; Calosi, Piero

2017-02-15

Ocean warming and acidification are concomitant global drivers that are currently threatening the survival of marine organisms. How species will respond to these changes depends on their capacity for plastic and adaptive responses. Little is known about the mechanisms that govern plasticity and adaptability or how global changes will influence these relationships across multiple generations. Here, we exposed the emerging model marine polychaete Ophryotrocha labronica to conditions simulating ocean warming and acidification, in isolation and in combination over five generations to identify: (i) how multiple versus single global change drivers alter both juvenile and adult life-history traits; (ii) the mechanistic link between adult physiological and fitness-related life-history traits; and (iii) whether the phenotypic changes observed over multiple generations are of plastic and/or adaptive origin. Two juvenile (developmental rate; survival to sexual maturity) and two adult (average reproductive body size; fecundity) life-history traits were measured in each generation, in addition to three physiological (cellular reactive oxygen species content, mitochondrial density, mitochondrial capacity) traits. We found that multi-generational exposure to warming alone caused an increase in juvenile developmental rate, reactive oxygen species production and mitochondrial density, decreases in average reproductive body size and fecundity, and fluctuations in mitochondrial capacity, relative to control conditions. Exposure to ocean acidification alone had only minor effects on juvenile developmental rate. Remarkably, when both drivers of global change were present, only mitochondrial capacity was significantly affected, suggesting that ocean warming and acidification act as opposing vectors of stress across multiple generations. © 2017. Published by The Company of Biologists Ltd.

Multivariate Bayesian analysis of Gaussian, right censored Gaussian, ordered categorical and binary traits using Gibbs sampling

PubMed Central

Korsgaard, Inge Riis; Lund, Mogens Sandø; Sorensen, Daniel; Gianola, Daniel; Madsen, Per; Jensen, Just

2003-01-01

A fully Bayesian analysis using Gibbs sampling and data augmentation in a multivariate model of Gaussian, right censored, and grouped Gaussian traits is described. The grouped Gaussian traits are either ordered categorical traits (with more than two categories) or binary traits, where the grouping is determined via thresholds on the underlying Gaussian scale, the liability scale. Allowances are made for unequal models, unknown covariance matrices and missing data. Having outlined the theory, strategies for implementation are reviewed. These include joint sampling of location parameters; efficient sampling from the fully conditional posterior distribution of augmented data, a multivariate truncated normal distribution; and sampling from the conditional inverse Wishart distribution, the fully conditional posterior distribution of the residual covariance matrix. Finally, a simulated dataset was analysed to illustrate the methodology. This paper concentrates on a model where residuals associated with liabilities of the binary traits are assumed to be independent. A Bayesian analysis using Gibbs sampling is outlined for the model where this assumption is relaxed. PMID:12633531

Anxiety and burnout in young athletes: The mediating role of cognitive appraisal.

PubMed

Gomes, A R; Faria, S; Vilela, C

2017-12-01

This study tested the relationship between trait anxiety, cognitive appraisal, and athletes' burnout proposing two hypotheses: (a) there is a direct relationship between athletes' trait anxiety and cognitive appraisal and burnout, and (b) cognitive appraisal mediates the relationship between trait anxiety and burnout, and this mediation occurs despite the competitive level and sport records of athletes. The study included 673 young athletes and provided measures of trait anxiety, cognitive appraisal, and burnout. Structural equation modeling indicated that cognitive appraisal mediates the relationship between trait anxiety and burnout, confirming hypothesis 2, and this model provided better fit than the direct model of hypothesis 1. However, the mediation also indicated that the direct relationship between trait anxiety and burnout should be considered. The mediating model was invariant according to competitive levels and sport records. In conclusion, cognitive appraisal is an important variable in explaining athletes' burnout. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Irrational exuberance for resolved species trees.

PubMed

Hahn, Matthew W; Nakhleh, Luay

2016-01-01

Phylogenomics has largely succeeded in its aim of accurately inferring species trees, even when there are high levels of discordance among individual gene trees. These resolved species trees can be used to ask many questions about trait evolution, including the direction of change and number of times traits have evolved. However, the mapping of traits onto trees generally uses only a single representation of the species tree, ignoring variation in the gene trees used to construct it. Recognizing that genes underlie traits, these results imply that many traits follow topologies that are discordant with the species topology. As a consequence, standard methods for character mapping will incorrectly infer the number of times a trait has evolved. This phenomenon, dubbed "hemiplasy," poses many problems in analyses of character evolution. Here we outline these problems, explaining where and when they are likely to occur. We offer several ways in which the possible presence of hemiplasy can be diagnosed, and discuss multiple approaches to dealing with the problems presented by underlying gene tree discordance when carrying out character mapping. Finally, we discuss the implications of hemiplasy for general phylogenetic inference, including the possible drawbacks of the widespread push for "resolved" species trees. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

The effects of heat stress in Italian Holstein dairy cattle.

PubMed

Bernabucci, U; Biffani, S; Buggiotti, L; Vitali, A; Lacetera, N; Nardone, A

2014-01-01

The data set for this study comprised 1,488,474 test-day records for milk, fat, and protein yields and fat and protein percentages from 191,012 first-, second-, and third-parity Holstein cows from 484 farms. Data were collected from 2001 through 2007 and merged with meteorological data from 35 weather stations. A linear model (M1) was used to estimate the effects of the temperature-humidity index (THI) on production traits. Least squares means from M1 were used to detect the THI thresholds for milk production in all parities by using a 2-phase linear regression procedure (M2). A multiple-trait repeatability test-model (M3) was used to estimate variance components for all traits and a dummy regression variable (t) was defined to estimate the production decline caused by heat stress. Additionally, the estimated variance components and M3 were used to estimate traditional and heat-tolerance breeding values (estimated breeding values, EBV) for milk yield and protein percentages at parity 1. An analysis of data (M2) indicated that the daily THI at which milk production started to decline for the 3 parities and traits ranged from 65 to 76. These THI values can be achieved with different temperature/humidity combinations with a range of temperatures from 21 to 36°C and relative humidity values from 5 to 95%. The highest negative effect of THI was observed 4 d before test day over the 3 parities for all traits. The negative effect of THI on production traits indicates that first-parity cows are less sensitive to heat stress than multiparous cows. Over the parities, the general additive genetic variance decreased for protein content and increased for milk yield and fat and protein yield. Additive genetic variance for heat tolerance showed an increase from the first to third parity for milk, protein, and fat yield, and for protein percentage. Genetic correlations between general and heat stress effects were all unfavorable (from -0.24 to -0.56). Three EBV per trait were calculated for each cow and bull (traditional EBV, traditional EBV estimated with the inclusion of THI covariate effect, and heat tolerance EBV) and the rankings of EBV for 283 bulls born after 1985 with at least 50 daughters were compared. When THI was included in the model, the ranking for 17 and 32 bulls changed for milk yield and protein percentage, respectively. The heat tolerance genetic component is not negligible, suggesting that heat tolerance selection should be included in the selection objectives. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Interactions between genetic variation and cellular environment in skeletal muscle gene expression.

PubMed

Taylor, D Leland; Knowles, David A; Scott, Laura J; Ramirez, Andrea H; Casale, Francesco Paolo; Wolford, Brooke N; Guan, Li; Varshney, Arushi; Albanus, Ricardo D'Oliveira; Parker, Stephen C J; Narisu, Narisu; Chines, Peter S; Erdos, Michael R; Welch, Ryan P; Kinnunen, Leena; Saramies, Jouko; Sundvall, Jouko; Lakka, Timo A; Laakso, Markku; Tuomilehto, Jaakko; Koistinen, Heikki A; Stegle, Oliver; Boehnke, Michael; Birney, Ewan; Collins, Francis S

2018-01-01

From whole organisms to individual cells, responses to environmental conditions are influenced by genetic makeup, where the effect of genetic variation on a trait depends on the environmental context. RNA-sequencing quantifies gene expression as a molecular trait, and is capable of capturing both genetic and environmental effects. In this study, we explore opportunities of using allele-specific expression (ASE) to discover cis-acting genotype-environment interactions (GxE)-genetic effects on gene expression that depend on an environmental condition. Treating 17 common, clinical traits as approximations of the cellular environment of 267 skeletal muscle biopsies, we identify 10 candidate environmental response expression quantitative trait loci (reQTLs) across 6 traits (12 unique gene-environment trait pairs; 10% FDR per trait) including sex, systolic blood pressure, and low-density lipoprotein cholesterol. Although using ASE is in principle a promising approach to detect GxE effects, replication of such signals can be challenging as validation requires harmonization of environmental traits across cohorts and a sufficient sampling of heterozygotes for a transcribed SNP. Comprehensive discovery and replication will require large human transcriptome datasets, or the integration of multiple transcribed SNPs, coupled with standardized clinical phenotyping.

A personality trait-based interactionist model of job performance.

PubMed

Tett, Robert P; Burnett, Dawn D

2003-06-01

Evidence for situational specificity of personality-job performance relations calls for better understanding of how personality is expressed as valued work behavior. On the basis of an interactionist principle of trait activation (R. P. Tett & H. A. Guterman, 2000), a model is proposed that distinguishes among 5 situational features relevant to trait expression (job demands, distracters, constraints, releasers, and facilitators), operating at task, social, and organizational levels. Trait-expressive work behavior is distinguished from (valued) job performance in clarifying the conditions favoring personality use in selection efforts. The model frames linkages between situational taxonomies (e.g., J. L. Holland's [1985] RIASEC model) and the Big Five and promotes useful discussion of critical issues, including situational specificity, personality-oriented job analysis, team building, and work motivation.

A global Fine-Root Ecology Database to address below-ground challenges in plant ecology.

PubMed

Iversen, Colleen M; McCormack, M Luke; Powell, A Shafer; Blackwood, Christopher B; Freschet, Grégoire T; Kattge, Jens; Roumet, Catherine; Stover, Daniel B; Soudzilovskaia, Nadejda A; Valverde-Barrantes, Oscar J; van Bodegom, Peter M; Violle, Cyrille

2017-07-01

Variation and tradeoffs within and among plant traits are increasingly being harnessed by empiricists and modelers to understand and predict ecosystem processes under changing environmental conditions. While fine roots play an important role in ecosystem functioning, fine-root traits are underrepresented in global trait databases. This has hindered efforts to analyze fine-root trait variation and link it with plant function and environmental conditions at a global scale. This Viewpoint addresses the need for a centralized fine-root trait database, and introduces the Fine-Root Ecology Database (FRED, http://roots.ornl.gov) which so far includes > 70 000 observations encompassing a broad range of root traits and also includes associated environmental data. FRED represents a critical step toward improving our understanding of below-ground plant ecology. For example, FRED facilitates the quantification of variation in fine-root traits across root orders, species, biomes, and environmental gradients while also providing a platform for assessments of covariation among root, leaf, and wood traits, the role of fine roots in ecosystem functioning, and the representation of fine roots in terrestrial biosphere models. Continued input of observations into FRED to fill gaps in trait coverage will improve our understanding of changes in fine-root traits across space and time. © 2017 UT-Battelle LLC. New Phytologist © 2017 New Phytologist Trust.

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

PubMed

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

2007-03-01

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

Breeding value accuracy estimates for growth traits using random regression and multi-trait models in Nelore cattle.

PubMed

Boligon, A A; Baldi, F; Mercadante, M E Z; Lobo, R B; Pereira, R J; Albuquerque, L G

2011-06-28

We quantified the potential increase in accuracy of expected breeding value for weights of Nelore cattle, from birth to mature age, using multi-trait and random regression models on Legendre polynomials and B-spline functions. A total of 87,712 weight records from 8144 females were used, recorded every three months from birth to mature age from the Nelore Brazil Program. For random regression analyses, all female weight records from birth to eight years of age (data set I) were considered. From this general data set, a subset was created (data set II), which included only nine weight records: at birth, weaning, 365 and 550 days of age, and 2, 3, 4, 5, and 6 years of age. Data set II was analyzed using random regression and multi-trait models. The model of analysis included the contemporary group as fixed effects and age of dam as a linear and quadratic covariable. In the random regression analyses, average growth trends were modeled using a cubic regression on orthogonal polynomials of age. Residual variances were modeled by a step function with five classes. Legendre polynomials of fourth and sixth order were utilized to model the direct genetic and animal permanent environmental effects, respectively, while third-order Legendre polynomials were considered for maternal genetic and maternal permanent environmental effects. Quadratic polynomials were applied to model all random effects in random regression models on B-spline functions. Direct genetic and animal permanent environmental effects were modeled using three segments or five coefficients, and genetic maternal and maternal permanent environmental effects were modeled with one segment or three coefficients in the random regression models on B-spline functions. For both data sets (I and II), animals ranked differently according to expected breeding value obtained by random regression or multi-trait models. With random regression models, the highest gains in accuracy were obtained at ages with a low number of weight records. The results indicate that random regression models provide more accurate expected breeding values than the traditionally finite multi-trait models. Thus, higher genetic responses are expected for beef cattle growth traits by replacing a multi-trait model with random regression models for genetic evaluation. B-spline functions could be applied as an alternative to Legendre polynomials to model covariance functions for weights from birth to mature age.

Comparisons of fish species traits from small streams to large rivers

USGS Publications Warehouse

Goldstein, R.M.; Meador, M.R.

2004-01-01

To examine the relations between fish community function and stream size, we classified 429 lotic freshwater fish species based on multiple categories within six species traits: (1) substrate preference, (2) geomorphic preference, (3) trophic ecology, (4) locomotion morphology, (5) reproductive strategy, and (6) stream size preference. Stream size categories included small streams, small, medium, and large rivers, and no size preference. The frequencies of each species trait category were determined for each stream size category based on life history information from the literature. Cluster analysis revealed the presence of covarying groups of species trait categories. One cluster (RUN) included the traits of planktivore and herbivore feeding ecology, migratory reproductive behavior and broadcast spawning, preferences for main-channel habitats, and a lack of preferences for substrate type. The frequencies of classifications for the RUN cluster varied significantly across stream size categories (P = 0.009), being greater for large rivers than for small streams and rivers. Another cluster (RIFFLE) included the traits of invertivore feeding ecology, simple nester reproductive behavior, a preference for riffles, and a preference for bedrock, boulder, and cobble-rubble substrate. No significant differences in the frequency of classifications among stream size categories were detected for the RIFFLE cluster (P = 0.328). Our results suggest that fish community function is structured by large-scale differences in habitat and is different for large rivers than for small streams and rivers. Our findings support theoretical predictions of variation in species traits among stream reaches based on ecological frameworks such as landscape filters, habitat templates, and the river continuum concept. We believe that the species trait classifications presented here provide an opportunity for further examination of fish species' relations to physical, chemical, and biological factors in lotic habitats ranging from small streams to large rivers.

Background controlled QTL mapping in pure-line genetic populations derived from four-way crosses

PubMed Central

Zhang, S; Meng, L; Wang, J; Zhang, L

2017-01-01

Pure lines derived from multiple parents are becoming more important because of the increased genetic diversity, the possibility to conduct replicated phenotyping trials in multiple environments and potentially high mapping resolution of quantitative trait loci (QTL). In this study, we proposed a new mapping method for QTL detection in pure-line populations derived from four-way crosses, which is able to control the background genetic variation through a two-stage mapping strategy. First, orthogonal variables were created for each marker and used in an inclusive linear model, so as to completely absorb the genetic variation in the mapping population. Second, inclusive composite interval mapping approach was implemented for one-dimensional scanning, during which the inclusive linear model was employed to control the background variation. Simulation studies using different genetic models demonstrated that the new method is efficient when considering high detection power, low false discovery rate and high accuracy in estimating quantitative trait loci locations and effects. For illustration, the proposed method was applied in a reported wheat four-way recombinant inbred line population. PMID:28722705

Background controlled QTL mapping in pure-line genetic populations derived from four-way crosses.

PubMed

Zhang, S; Meng, L; Wang, J; Zhang, L

2017-10-01

Pure lines derived from multiple parents are becoming more important because of the increased genetic diversity, the possibility to conduct replicated phenotyping trials in multiple environments and potentially high mapping resolution of quantitative trait loci (QTL). In this study, we proposed a new mapping method for QTL detection in pure-line populations derived from four-way crosses, which is able to control the background genetic variation through a two-stage mapping strategy. First, orthogonal variables were created for each marker and used in an inclusive linear model, so as to completely absorb the genetic variation in the mapping population. Second, inclusive composite interval mapping approach was implemented for one-dimensional scanning, during which the inclusive linear model was employed to control the background variation. Simulation studies using different genetic models demonstrated that the new method is efficient when considering high detection power, low false discovery rate and high accuracy in estimating quantitative trait loci locations and effects. For illustration, the proposed method was applied in a reported wheat four-way recombinant inbred line population.

The Role of Attention in Somatosensory Processing: A Multi-trait, Multi-method Analysis

PubMed Central

Puts, Nicolaas A. J.; Mahone, E. Mark; Edden, Richard A. E.; Tommerdahl, Mark; Mostofsky, Stewart H.

2016-01-01

Sensory processing abnormalities in autism have largely been described by parent report. This study used a multi-method (parent-report and measurement), multi-trait (tactile sensitivity and attention) design to evaluate somatosensory processing in ASD. Results showed multiple significant within-method (e.g., parent report of different traits)/cross-trait (e.g., attention and tactile sensitivity) correlations, suggesting that parent-reported tactile sensory dysfunction and performance-based tactile sensitivity describe different behavioral phenomena. Additionally, both parent-reported tactile functioning and performance-based tactile sensitivity measures were significantly associated with measures of attention. Findings suggest that sensory (tactile) processing abnormalities in ASD are multifaceted, and may partially reflect a more global deficit in behavioral regulation (including attention). Challenges of relying solely on parent-report to describe sensory difficulties faced by children/families with ASD are also highlighted. PMID:27448580

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

PubMed Central

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

2011-01-01

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

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

PubMed

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

2011-10-01

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

Environmental drivers defining linkages among life-history traits: mechanistic insights from a semiterrestrial amphipod subjected to macroscale gradients.

PubMed

Gómez, Julio; Barboza, Francisco R; Defeo, Omar

2013-10-01

Determining the existence of interconnected responses among life-history traits and identifying underlying environmental drivers are recognized as key goals for understanding the basis of phenotypic variability. We studied potentially interconnected responses among senescence, fecundity, embryos size, weight of brooding females, size at maturity and sex ratio in a semiterrestrial amphipod affected by macroscale gradients in beach morphodynamics and salinity. To this end, multiple modelling processes based on generalized additive mixed models were used to deal with the spatio-temporal structure of the data obtained at 10 beaches during 22 months. Salinity was the only nexus among life-history traits, suggesting that this physiological stressor influences the energy balance of organisms. Different salinity scenarios determined shifts in the weight of brooding females and size at maturity, having consequences in the number and size of embryos which in turn affected sex determination and sex ratio at the population level. Our work highlights the importance of analysing field data to find the variables and potential mechanisms that define concerted responses among traits, therefore defining life-history strategies.

The evolution of primate general and cultural intelligence

PubMed Central

Reader, Simon M.; Hager, Yfke; Laland, Kevin N.

2011-01-01

There are consistent individual differences in human intelligence, attributable to a single ‘general intelligence’ factor, g. The evolutionary basis of g and its links to social learning and culture remain controversial. Conflicting hypotheses regard primate cognition as divided into specialized, independently evolving modules versus a single general process. To assess how processes underlying culture relate to one another and other cognitive capacities, we compiled ecologically relevant cognitive measures from multiple domains, namely reported incidences of behavioural innovation, social learning, tool use, extractive foraging and tactical deception, in 62 primate species. All exhibited strong positive associations in principal component and factor analyses, after statistically controlling for multiple potential confounds. This highly correlated composite of cognitive traits suggests social, technical and ecological abilities have coevolved in primates, indicative of an across-species general intelligence that includes elements of cultural intelligence. Our composite species-level measure of general intelligence, ‘primate gS’, covaried with both brain volume and captive learning performance measures. Our findings question the independence of cognitive traits and do not support ‘massive modularity’ in primate cognition, nor an exclusively social model of primate intelligence. High general intelligence has independently evolved at least four times, with convergent evolution in capuchins, baboons, macaques and great apes. PMID:21357224

Root architecture simulation improves the inference from seedling root phenotyping towards mature root systems.

PubMed

Zhao, Jiangsan; Bodner, Gernot; Rewald, Boris; Leitner, Daniel; Nagel, Kerstin A; Nakhforoosh, Alireza

2017-02-01

Root phenotyping provides trait information for plant breeding. A shortcoming of high-throughput root phenotyping is the limitation to seedling plants and failure to make inferences on mature root systems. We suggest root system architecture (RSA) models to predict mature root traits and overcome the inference problem. Sixteen pea genotypes were phenotyped in (i) seedling (Petri dishes) and (ii) mature (sand-filled columns) root phenotyping platforms. The RSA model RootBox was parameterized with seedling traits to simulate the fully developed root systems. Measured and modelled root length, first-order lateral number, and root distribution were compared to determine key traits for model-based prediction. No direct relationship in root traits (tap, lateral length, interbranch distance) was evident between phenotyping systems. RootBox significantly improved the inference over phenotyping platforms. Seedling plant tap and lateral root elongation rates and interbranch distance were sufficient model parameters to predict genotype ranking in total root length with an RSpearman of 0.83. Parameterization including uneven lateral spacing via a scaling function substantially improved the prediction of architectures underlying the differently sized root systems. We conclude that RSA models can solve the inference problem of seedling root phenotyping. RSA models should be included in the phenotyping pipeline to provide reliable information on mature root systems to breeding research. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.

A single evolutionary innovation drives the deep evolution of symbiotic N2-fixation in angiosperms

PubMed Central

Werner, Gijsbert D. A.; Cornwell, William K.; Sprent, Janet I.; Kattge, Jens; Kiers, E. Toby

2014-01-01

Symbiotic associations occur in every habitat on earth, but we know very little about their evolutionary histories. Current models of trait evolution cannot adequately reconstruct the deep history of symbiotic innovation, because they assume homogenous evolutionary processes across millions of years. Here we use a recently developed, heterogeneous and quantitative phylogenetic framework to study the origin of the symbiosis between angiosperms and nitrogen-fixing (N2) bacterial symbionts housed in nodules. We compile the largest database of global nodulating plant species and reconstruct the symbiosis’ evolution. We identify a single, cryptic evolutionary innovation driving symbiotic N2-fixation evolution, followed by multiple gains and losses of the symbiosis, and the subsequent emergence of ‘stable fixers’ (clades extremely unlikely to lose the symbiosis). Originating over 100 MYA, this innovation suggests deep homology in symbiotic N2-fixation. Identifying cryptic innovations on the tree of life is key to understanding the evolution of complex traits, including symbiotic partnerships. PMID:24912610

Initial Construction of a Maladaptive Personality Trait Model and Inventory for DSM-5

PubMed Central

Krueger, Robert F.; Derringer, Jaime; Markon, Kristian E.; Watson, David; Skodol, Andrew E.

2012-01-01

Background DSM-IV-TR suggests that clinicians should assess clinically relevant personality traits that do not necessarily constitute a formal personality disorder, and should note these traits on Axis II, but DSM-IV-TR does not provide a trait model to guide the clinician. Our goal was to provide a provisional trait model and a preliminary corresponding assessment instrument, in our roles as members of the DSM-5 personality and personality disorders workgroup and workgroup advisors. Methods An initial list of specific traits and domains (broader groups of traits) was derived from DSM-5 literature reviews and workgroup deliberations, with a focus on capturing maladaptive personality characteristics deemed clinically salient, including those related to the criteria for DSM-IV-TR personality disorders (PDs). The model and instrument were then developed iteratively using data from community samples of treatment seeking participants. The analytic approach relied on tools of modern psychometrics (e.g., item response theory models). Results Twenty-five reliably measured core elements of personality description emerged that, together, delineate five broad domains of maladaptive personality variation: negative affect, detachment, antagonism, disinhibition, and psychoticism. Conclusions We developed a maladaptive personality trait model and corresponding instrument as a step on the path toward helping users of DSM-5 assess traits that may or may not constitute a formal PD. The inventory we developed is reprinted in its entirety in the supplementary materials, with the goal of encouraging additional refinement and development by other investigators prior to the finalization of DSM-5. Continuing discussion should focus on various options for integrating personality traits into DSM-5. PMID:22153017

Predicting recovery criteria for threatened and endangered plant species on the basis of past abundances and biological traits.

PubMed

Neel, Maile C; Che-Castaldo, Judy P

2013-04-01

Recovery plans for species listed under the U.S. Endangered Species Act are required to specify measurable criteria that can be used to determine when the species can be delisted. For the 642 listed endangered and threatened plant species that have recovery plans, we applied recursive partitioning methods to test whether the number of individuals or populations required for delisting can be predicted on the basis of distributional and biological traits, previous abundance at multiple time steps, or a combination of traits and previous abundances. We also tested listing status (threatened or endangered) and the year the recovery plan was written as predictors of recovery criteria. We analyzed separately recovery criteria that were stated as number of populations and as number of individuals (population-based and individual-based criteria, respectively). Previous abundances alone were relatively good predictors of population-based recovery criteria. Fewer populations, but a greater proportion of historically known populations, were required to delist species that had few populations at listing compared with species that had more populations at listing. Previous abundances were also good predictors of individual-based delisting criteria when models included both abundances and traits. The physiographic division in which the species occur was also a good predictor of individual-based criteria. Our results suggest managers are relying on previous abundances and patterns of decline as guidelines for setting recovery criteria. This may be justifiable in that previous abundances inform managers of the effects of both intrinsic traits and extrinsic threats that interact and determine extinction risk. © 2013 Society for Conservation Biology.

The relationship between online game addiction and aggression, self-control and narcissistic personality traits.

PubMed

Kim, Eun Joo; Namkoong, Kee; Ku, Taeyun; Kim, Se Joo

2008-04-01

This study aimed to explore the relationship between online game addiction and aggression, self-control, and narcissistic personality traits, which are known as the psychological characteristics linked to "at-risk" populations for online game addiction. A total of 1471 online game users (males 82.7%, females 17.3%, mean age 21.30+/-4.96) participated in this study and were asked to complete several self-report measures using an online response method. Questionnaires included demographic information and game use-related characteristics of the samples, the online game addiction scale (modified from Young's Internet addiction scale), the Buss-Perry aggression questionnaire, a self-control scale, and the narcissistic personality disorder scale. Our results indicated that aggression and narcissistic personality traits are positively correlated with online game addiction, whereas self-control is negatively correlated with online game addiction (p<0.001). In addition, a multiple regression analysis revealed that the extent of online game addiction could be predicted based on the person's narcissistic personality traits, aggression, self-control, interpersonal relationship, and occupation. However, only 20% of the variance in behavioral consequences was explained with the model. An interesting profile has emerged from the results of this study, suggesting that certain psychological characteristics such as aggression, self-control, and narcissistic personality traits may predispose some individuals to become addicted to online games. This result will deepen our understanding of the "at-risk" population for online game addiction and provide basic information that can contribute to developing a prevention program for people who are addicted to online games.

Whole Trait Theory

PubMed Central

Fleeson, William; Jayawickreme, Eranda

2014-01-01

Personality researchers should modify models of traits to include mechanisms of differential reaction to situations. Whole Trait Theory does so via five main points. First, the descriptive side of traits should be conceptualized as density distributions of states. Second, it is important to provide an explanatory account of the Big 5 traits. Third, adding an explanatory account to the Big 5 creates two parts to traits, an explanatory part and a descriptive part, and these two parts should be recognized as separate entities that are joined into whole traits. Fourth, Whole Trait Theory proposes that the explanatory side of traits consists of social-cognitive mechanisms. Fifth, social-cognitive mechanisms that produce Big-5 states should be identified. PMID:26097268

Advantages and limitations of multiple-trait genomic prediction for Fusarium head blight severity in hybrid wheat (Triticum aestivum L.).

PubMed

Schulthess, Albert W; Zhao, Yusheng; Longin, C Friedrich H; Reif, Jochen C

2018-03-01

Predictabilities for wheat hybrids less related to the estimation set were improved by shifting from single- to multiple-trait genomic prediction of Fusarium head blight severity. Breeding for improved Fusarium head blight resistance (FHBr) of wheat is a very laborious and expensive task. FHBr complexity is mainly due to its highly polygenic nature and because FHB severity (FHBs) is greatly influenced by the environment. Associated traits plant height and heading date may provide additional information related to FHBr, but this is ignored in single-trait genomic prediction (STGP). The aim of our study was to explore the benefits in predictabilities of multiple-trait genomic prediction (MTGP) over STGP of target trait FHBs in a population of 1604 wheat hybrids using information on 17,372 single nucleotide polymorphism markers along with indicator traits plant height and heading date. The additive inheritance of FHBs allowed accurate hybrid performance predictions using information on general combining abilities or average performance of both parents without the need of markers. Information on molecular markers and indicator trait(s) improved FHBs predictabilities for hybrids less related to the estimation set. Indicator traits must be observed on the predicted individuals to benefit from MTGP. Magnitudes of genetic and phenotypic correlations along with improvements in predictabilities made plant height a better indicator trait for FHBs than heading date. Thus, MTGP having only plant height as indicator trait already maximized FHBs predictabilities. Provided a good indicator trait was available, MTGP could reduce the impacts of genotype environment [Formula: see text] interaction on STGP for hybrids less related to the estimation set.

Multiple trait genetic evaluation of clinical mastitis in three dairy cattle breeds.

PubMed

Govignon-Gion, A; Dassonneville, R; Baloche, G; Ducrocq, V

2016-04-01

In 2010, a routine genetic evaluation on occurrence of clinical mastitis in three main dairy cattle breeds-- Montbéliarde (MO), Normande (NO) and Holstein (HO)--was implemented in France. Records were clinical mastitis events reported by farmers to milk recording technicians and the analyzed trait was the binary variable describing the occurrence of a mastitis case within the first 150 days of the first three lactations. Genetic parameters of clinical mastitis were estimated for the three breeds. Low heritability estimates were found: between 2% and 4% depending on the breed. Despite its low heritability, the trait exhibits genetic variation so efficient genetic improvement is possible. Genetic correlations with other traits were estimated, showing large correlations (often>0.50, in absolute value) between clinical mastitis and somatic cell score (SCS), longevity and some udder traits. Correlation with milk yield was moderate and unfavorable (ρ=0.26 to 0.30). High milking speed was genetically associated with less mastitis in MO (ρ=-0.14) but with more mastitis in HO (ρ=0.18). A two-step approach was implemented for routine evaluation: first, a univariate evaluation based on a linear animal model with permanent environment effect led to pre-adjusted records (defined as records corrected for all non-genetic effects) and associated weights. These data were then combined with similar pre-adjusted records for others traits in a multiple trait BLUP animal model. The combined breeding values for clinical mastitis obtained are the official (published) ones. Mastitis estimated breeding values (EBV) were then combined with SCSs EBV into an udder health index, which receives a weight of 14.5% to 18.5% in the French total merit index (ISU) of the three breeds. Interbull genetic correlations for mastitis occurrence were very high (ρ=0.94) with Nordic countries, where much stricter recording systems exist reflecting a satisfactory quality of phenotypes as reported by the farmers. They were lower (around 0.80) with countries supplying SCS as a proxy for the international evaluation on clinical mastitis.

Short communication: Genetic relationships of milk coagulation properties with body condition score and linear type traits in Holstein-Friesian cows.

PubMed

Cassandro, M; Battagin, M; Penasa, M; De Marchi, M

2015-01-01

Milk coagulation properties (MCP) are gaining popularity among dairy cattle producers and the improvement of traits associated with MCP is expected to result in a benefit for the dairy industry, especially in countries with a long tradition in cheese production. The objectives of this study were to estimate genetic correlations of MCP with body condition score (BCS) and type traits using data from first-parity Italian Holstein-Friesian cattle. The data analyzed consisted of 18,460 MCP records from 4,036 cows with information on both BCS and conformation traits. The cows were daughters of 246 sires and the pedigree file included a total of 37,559 animals. Genetic relationships of MCP with BCS and type traits were estimated using bivariate animal models. The model for MCP included fixed effects of stage of lactation, and random effects of herd-test-date, cow permanent environment, additive genetic animal, and residual. Fixed factors considered in the model for BCS and type traits were herd-date of evaluation and interaction between age at scoring and stage of lactation of the cow, and random terms were additive genetic animal, cow permanent environment, and residual. Genetic relationships between MCP and BCS, and MCP and type traits were generally low and significant only in a few cases, suggesting that MCP can be selected for without detrimental effects on BCS and linear type traits. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Genetic parameter estimation of reproductive traits of Litopenaeus vannamei

NASA Astrophysics Data System (ADS)

Tan, Jian; Kong, Jie; Cao, Baoxiang; Luo, Kun; Liu, Ning; Meng, Xianhong; Xu, Shengyu; Guo, Zhaojia; Chen, Guoliang; Luan, Sheng

2017-02-01

In this study, the heritability, repeatability, phenotypic correlation, and genetic correlation of the reproductive and growth traits of L. vannamei were investigated and estimated. Eight traits of 385 shrimps from forty-two families, including the number of eggs (EN), number of nauplii (NN), egg diameter (ED), spawning frequency (SF), spawning success (SS), female body weight (BW) and body length (BL) at insemination, and condition factor (K), were measured,. A total of 519 spawning records including multiple spawning and 91 no spawning records were collected. The genetic parameters were estimated using an animal model, a multinomial logit model (for SF), and a sire-dam and probit model (for SS). Because there were repeated records, permanent environmental effects were included in the models. The heritability estimates for BW, BL, EN, NN, ED, SF, SS, and K were 0.49 ± 0.14, 0.51 ± 0.14, 0.12 ± 0.08, 0, 0.01 ± 0.04, 0.06 ± 0.06, 0.18 ± 0.07, and 0.10 ± 0.06, respectively. The genetic correlation was 0.99 ± 0.01 between BW and BL, 0.90 ± 0.19 between BW and EN, 0.22 ± 0.97 between BW and ED, -0.77 ± 1.14 between EN and ED, and -0.27 ± 0.36 between BW and K. The heritability of EN estimated without a covariate was 0.12 ± 0.08, and the genetic correlation was 0.90 ± 0.19 between BW and EN, indicating that improving BW may be used in selection programs to genetically improve the reproductive output of L. vannamei during the breeding. For EN, the data were also analyzed using body weight as a covariate (EN-2). The heritability of EN-2 was 0.03 ± 0.05, indicating that it is difficult to improve the reproductive output by genetic improvement. Furthermore, excessive pursuit of this selection is often at the expense of growth speed. Therefore, the selection of high-performance spawners using BW and SS may be an important strategy to improve nauplii production.

Variation in heading date conceals quantitative trait loci for other traits of importance in breeding selection of rice

PubMed Central

Hori, Kiyosumi; Kataoka, Tomomori; Miura, Kiyoyuki; Yamaguchi, Masayuki; Saka, Norikuni; Nakahara, Takahiro; Sunohara, Yoshihiro; Ebana, Kaworu; Yano, Masahiro

2012-01-01

To identify quantitative trait loci (QTLs) associated with the primary target traits for selection in practical rice breeding programs, backcross inbred lines (BILs) derived from crosses between temperate japonica rice cultivars Nipponbare and Koshihikari were evaluated for 50 agronomic traits at six experimental fields located throughout Japan. Thirty-three of the 50 traits were significantly correlated with heading date. Using a linkage map including 647 single-nucleotide polymorphisms (SNPs), a total of 122 QTLs for 38 traits were mapped on all rice chromosomes except chromosomes 5 and 9. Fifty-eight of the 122 QTLs were detected near the heading date QTLs Hd16 and Hd17 and the remaining 64 QTLs were found in other chromosome regions. QTL analysis of 51 BILs having homozygous for the Koshihikari chromosome segments around Hd16 and Hd17 allowed us to detect 40 QTLs associated with 27 traits; 23 of these QTLs had not been detected in the original analysis. Among the 97 QTLs for the 30 traits measured in multiple environments, the genotype-by-environment interaction was significant for 44 QTLs and not significant for 53 QTLs. These results led us to propose a new selection strategy to improve agronomic performance in temperate japonica rice cultivars. PMID:23226082

Functional identity and diversity of animals predict ecosystem functioning better than species-based indices.

PubMed

Gagic, Vesna; Bartomeus, Ignasi; Jonsson, Tomas; Taylor, Astrid; Winqvist, Camilla; Fischer, Christina; Slade, Eleanor M; Steffan-Dewenter, Ingolf; Emmerson, Mark; Potts, Simon G; Tscharntke, Teja; Weisser, Wolfgang; Bommarco, Riccardo

2015-02-22

Drastic biodiversity declines have raised concerns about the deterioration of ecosystem functions and have motivated much recent research on the relationship between species diversity and ecosystem functioning. A functional trait framework has been proposed to improve the mechanistic understanding of this relationship, but this has rarely been tested for organisms other than plants. We analysed eight datasets, including five animal groups, to examine how well a trait-based approach, compared with a more traditional taxonomic approach, predicts seven ecosystem functions below- and above-ground. Trait-based indices consistently provided greater explanatory power than species richness or abundance. The frequency distributions of single or multiple traits in the community were the best predictors of ecosystem functioning. This implies that the ecosystem functions we investigated were underpinned by the combination of trait identities (i.e. single-trait indices) and trait complementarity (i.e. multi-trait indices) in the communities. Our study provides new insights into the general mechanisms that link biodiversity to ecosystem functioning in natural animal communities and suggests that the observed responses were due to the identity and dominance patterns of the trait composition rather than the number or abundance of species per se. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

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

PubMed

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

2016-11-01

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

Hormonal response to bidirectional selection on social behavior

USDA-ARS?s Scientific Manuscript database

Behavior is a quantitative trait determined through the actions of multiple genes. These genes form pleiotropic networks that are sensitive to environmental variation and genetic background. One aspect of behavioral gene networks that is of special interest includes effects during early development....

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.

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

PubMed

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

2010-09-01

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

Personality and mortality after myocardial infarction.

PubMed

Denollet, J; Sys, S U; Brutsaert, D L

1995-01-01

Previous research showed: a) emotional distress is a risk factor for mortality after myocardial infarction (MI) and b) emotional distress is linked to stable personality traits. In this study, we examined the role of these personality traits in mortality after MI. Subjects were 105 men, 45 to 60 years of age, who survived a recent MI. Baseline assessment included biomedical and psychosocial risk factors, as well as each patient's personality type. After 2 to 5 (mean, 3.8) years of follow-up, 15 patients (14%) had died. Rate of death for patients with a distressed personality type (11/28 = 39%) was significantly greater than that for patients with other personality types (4/77 = 5%) (p < .0001). Patients with this personality type tend simultaneously to experience distress and inhibit expression of emotions. Low exercise tolerance, previous MI (p < .005), anterior MI, smoking, and age (p < .05) were also associated with mortality. A logistic regression model including these biomedical factors had a sensitivity for mortality of only 27%. The addition of distressed personality type in this model more than doubled its sensitivity. Of note, among patients with poor physical health, those with a distressed personality type had a five-fold mortality risk (p < .005). Consistent with the findings of other investigators, depression (p < .005), life stress, use of benzodiazepines (p < .01), and somatization (p < .05) were also related to post-MI mortality. These psychosocial risk factors were more prevalent in the distressed personality type than in the other personality types (p < .001-.05). Multiple logistic regression indicated that these psychosocial factors did not add to the predictive value of the distressed personality type. Hence, an important personality effect was observed despite the low power. This suggests that personality traits may play a role in the detrimental effect of emotional distress in MI patients.

Studying Gene and Gene-Environment Effects of Uncommon and Common Variants on Continuous Traits: A Marker-Set Approach Using Gene-Trait Similarity Regression

PubMed Central

Tzeng, Jung-Ying; Zhang, Daowen; Pongpanich, Monnat; Smith, Chris; McCarthy, Mark I.; Sale, Michèle M.; Worrall, Bradford B.; Hsu, Fang-Chi; Thomas, Duncan C.; Sullivan, Patrick F.

2011-01-01

Genomic association analyses of complex traits demand statistical tools that are capable of detecting small effects of common and rare variants and modeling complex interaction effects and yet are computationally feasible. In this work, we introduce a similarity-based regression method for assessing the main genetic and interaction effects of a group of markers on quantitative traits. The method uses genetic similarity to aggregate information from multiple polymorphic sites and integrates adaptive weights that depend on allele frequencies to accomodate common and uncommon variants. Collapsing information at the similarity level instead of the genotype level avoids canceling signals that have the opposite etiological effects and is applicable to any class of genetic variants without the need for dichotomizing the allele types. To assess gene-trait associations, we regress trait similarities for pairs of unrelated individuals on their genetic similarities and assess association by using a score test whose limiting distribution is derived in this work. The proposed regression framework allows for covariates, has the capacity to model both main and interaction effects, can be applied to a mixture of different polymorphism types, and is computationally efficient. These features make it an ideal tool for evaluating associations between phenotype and marker sets defined by linkage disequilibrium (LD) blocks, genes, or pathways in whole-genome analysis. PMID:21835306

Genetic evaluation of claw health traits accounting for potential preselection of cows to be trimmed.

PubMed

Croué, Iola; Fikse, Freddy; Johansson, Kjell; Carlén, Emma; Thomas, Gilles; Leclerc, Hélène; Ducrocq, Vincent

2017-10-01

Claw lesions are one of the most important health issues in dairy cattle. Although the frequency of claw lesions depends greatly on herd management, the frequency can be lowered through genetic selection. A genetic evaluation could be developed based on trimming records collected by claw trimmers; however, not all cows present in a herd are usually selected by the breeder to be trimmed. The objectives of this study were to investigate the importance of the preselection of cows for trimming, to account for this preselection, and to estimate genetic parameters of claw health traits. The final data set contained 25,511 trimming records of French Holstein cows. Analyzed claw lesion traits were digital dermatitis, heel horn erosion, interdigital hyperplasia, sole hemorrhage circumscribed, sole hemorrhage diffused, sole ulcer, and white line fissure. All traits were analyzed as binary traits in a multitrait linear animal model. Three scenarios were considered: including only trimmed cows in a 7-trait model (scenario 1); or trimmed cows and contemporary cows not trimmed but present at the time of a visit (considering that nontrimmed cows were healthy) in a 7-trait model (scenario 2); or trimmed cows and contemporary cows not trimmed but present at the time of a visit (considering lesion records for trimmed cows only), in an 8-trait model, including a 0/1 trimming status trait (scenario 3). For scenario 3, heritability estimates ranged from 0.02 to 0.09 on the observed scale. Genetic correlations clearly revealed 2 groups of traits (digital dermatitis, heel horn erosion, and interdigital hyperplasia on the one hand, and sole hemorrhage circumscribed, sole hemorrhage diffused, sole ulcer, and white line fissure on the other hand). Heritabilities on the underlying scale did not vary much depending on the scenario: the effect of the preselection of cows for trimming on the estimation of heritabilities appeared to be negligible. However, including untrimmed cows as healthy caused bias in the estimation of genetic correlations. The use of a trimming status trait to account for preselection appears promising, as it allows consideration of the exhaustive population of cows present at the time a trimmer visited a farm without causing bias in genetic parameters. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Factorial Structure of the French Version of the Rosenberg Self-Esteem Scale among the Elderly

ERIC Educational Resources Information Center

Gana, Kamel; Alaphilippe, Daniel; Bailly, Nathalie

2005-01-01

Ten different confirmatory factor analysis models, including ones with correlated traits correlated methods, correlated traits correlated uniqueness, and correlated traits uncorrelated methods, were proposed to examine the factorial structure of the French version of the Rosenberg Self-Esteem Scale (Rosenberg, 1965). In line with previous studies…

Trait synergisms and the rarity, extirpation, and extinction risk of desert fishes.

PubMed

Olden, Julian D; Poff, N LeRoy; Bestgen, Kevin R

2008-03-01

Understanding the causes and consequences of species extinctions is a central goal in ecology. Faced with the difficult task of identifying those species with the greatest need for conservation, ecologists have turned to using predictive suites of ecological and life-history traits to provide reasonable estimates of species extinction risk. Previous studies have linked individual traits to extinction risk, yet the nonadditive contribution of multiple traits to the entire extinction process, from species rarity to local extirpation to global extinction, has not been examined. This study asks whether trait synergisms predispose native fishes of the Lower Colorado River Basin (USA) to risk of extinction through their effects on rarity and local extirpation and their vulnerability to different sources of threat. Fish species with "slow" life histories (e.g., large body size, long life, and delayed maturity), minimal parental care to offspring, and specialized feeding behaviors are associated with smaller geographic distribution, greater frequency of local extirpation, and higher perceived extinction risk than that expected by simple additive effects of traits in combination. This supports the notion that trait synergisms increase the susceptibility of native fishes to multiple stages of the extinction process, thus making them prone to the multiple jeopardies resulting from a combination of fewer individuals, narrow environmental tolerances, and long recovery times following environmental change. Given that particular traits, some acting in concert, may differentially predispose native fishes to rarity, extirpation, and extinction, we suggest that management efforts in the Lower Colorado River Basin should be congruent with the life-history requirements of multiple species over large spatial and temporal scales.

Intraspecific variability in functional traits matters: case study of Scots pine.

PubMed

Laforest-Lapointe, Isabelle; Martínez-Vilalta, Jordi; Retana, Javier

2014-08-01

Although intraspecific trait variability is an important component of species ecological plasticity and niche breadth, its implications for community and functional ecology have not been thoroughly explored. We characterized the intraspecific functional trait variability of Scots pine (Pinus sylvestris) in Catalonia (NE Spain) in order to (1) compare it to the interspecific trait variability of trees in the same region, (2) explore the relationships among functional traits and the relationships between them and stand and climatic variables, and (3) study the role of functional trait variability as a determinant of radial growth. We considered five traits: wood density (WD), maximum tree height (H max), leaf nitrogen content (Nmass), specific leaf area (SLA), and leaf biomass-to-sapwood area ratio (B L:A S). A unique dataset was obtained from the Ecological and Forest Inventory of Catalonia (IEFC), including data from 406 plots. Intraspecific trait variation was substantial for all traits, with coefficients of variation ranging between 8% for WD and 24% for B L:A S. In some cases, correlations among functional traits differed from those reported across species (e.g., H max and WD were positively related, whereas SLA and Nmass were uncorrelated). Overall, our model accounted for 47% of the spatial variability in Scots pine radial growth. Our study emphasizes the hierarchy of factors that determine intraspecific variations in functional traits in Scots pine and their strong association with spatial variability in radial growth. We claim that intraspecific trait variation is an important determinant of responses of plants to changes in climate and other environmental factors, and should be included in predictive models of vegetation dynamics.

Is specialization an evolutionary dead end? Testing for differences in speciation, extinction and trait transition rates across diverse phylogenies of specialists and generalists.

PubMed

Day, E H; Hua, X; Bromham, L

2016-06-01

Specialization has often been claimed to be an evolutionary dead end, with specialist lineages having a reduced capacity to persist or diversify. In a phylogenetic comparative framework, an evolutionary dead end may be detectable from the phylogenetic distribution of specialists, if specialists rarely give rise to large, diverse clades. Previous phylogenetic studies of the influence of specialization on macroevolutionary processes have demonstrated a range of patterns, including examples where specialists have both higher and lower diversification rates than generalists, as well as examples where the rates of evolutionary transitions from generalists to specialists are higher, lower or equal to transitions from specialists to generalists. Here, we wish to ask whether these varied answers are due to the differences in macroevolutionary processes in different clades, or partly due to differences in methodology. We analysed ten phylogenies containing multiple independent origins of specialization and quantified the phylogenetic distribution of specialists by applying a common set of metrics to all datasets. We compared the tip branch lengths of specialists to generalists, the size of specialist clades arising from each evolutionary origin of a specialized trait and whether specialists tend to be clustered or scattered on phylogenies. For each of these measures, we compared the observed values to expectations under null models of trait evolution and expected outcomes under alternative macroevolutionary scenarios. We found that specialization is sometimes an evolutionary dead end: in two of the ten case studies (pollinator-specific plants and host-specific flies), specialization is associated with a reduced rate of diversification or trait persistence. However, in the majority of studies, we could not distinguish the observed phylogenetic distribution of specialists from null models in which specialization has no effect on diversification or trait persistence. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

Genetic parameters and genetic trends in the Chinese × European Tiameslan composite pig line. II. Genetic trends

PubMed Central

Zhang, Siqing; Bidanel, Jean-Pierre; Burlot, Thierry; Legault, Christian; Naveau, Jean

2000-01-01

The Tiameslan line was created between 1983 and 1985 by mating Meishan × Jiaxing crossbred Chinese boars with sows from the Laconie composite male line. The Tiameslan line has been selected since then on an index combining average backfat thickness (ABT) and days from 20 to 100 kg (DT). Direct and correlated responses to 11 years of selection were estimated using BLUP methodology applied to a multiple trait animal model. A total of 11 traits were considered, i.e.: ABT, DT, body weight at 4 (W4w), 8 (W8w) and 22 (W22w) weeks of age, teat number (TEAT), number of good teats (GTEAT), total number of piglets born (TNB), born alive (NBA) and weaned (NW) per litter, and birth to weaning survival rate (SURV). Performance data from a total of 4 881 males and 4 799 females from 1 341 litters were analysed. The models included both direct and maternal effects for ABT, W4w and W8w. Male and female performances were considered as different traits for W22w, DT and ABT. Genetic parameters estimated in another paper (Zhang et al., Genet. Sel. Evol. 32 (2000) 41-56) were used to perform the analyses. Favourable phenotypic (ΔP) and direct genetic trends (ΔGd) were obtained for post-weaning growth traits and ABT. Trends for maternal effects were limited. Phenotypic and genetic trends were larger in females than in males for ABT (e.g. ΔGd = -0.48 vs. -0.38 mm/year), were larger in males for W22w (ΔGd = 0.90 vs. 0.58 kg/year) and were similar in both sexes for DT (ΔGd = -0.54 vs. -0.55 day/year). Phenotypic and genetic trends were slightly favourable for W4w, W8w, TEAT and GTEAT and close to zero for reproductive traits. PMID:14736407

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.

On the challenges of using field spectroscopy to measure the impact of soil type on leaf traits

NASA Astrophysics Data System (ADS)

Nunes, Matheus H.; Davey, Matthew P.; Coomes, David A.

2017-07-01

Understanding the causes of variation in functional plant traits is a central issue in ecology, particularly in the context of global change. Spectroscopy is increasingly used for rapid and non-destructive estimation of foliar traits, but few studies have evaluated its accuracy when assessing phenotypic variation in multiple traits. Working with 24 chemical and physical leaf traits of six European tree species growing on strongly contrasting soil types (i.e. deep alluvium versus nearby shallow chalk), we asked (i) whether variability in leaf traits is greater between tree species or soil type, and (ii) whether field spectroscopy is effective at predicting intraspecific variation in leaf traits as well as interspecific differences. Analysis of variance showed that interspecific differences in traits were generally much stronger than intraspecific differences related to soil type, accounting for 25 % versus 5 % of total trait variation, respectively. Structural traits, phenolic defences and pigments were barely affected by soil type. In contrast, foliar concentrations of rock-derived nutrients did vary: P and K concentrations were lower on chalk than alluvial soils, while Ca, Mg, B, Mn and Zn concentrations were all higher, consistent with the findings of previous ecological studies. Foliar traits were predicted from 400 to 2500 nm reflectance spectra collected by field spectroscopy using partial least square regression, a method that is commonly employed in chemometrics. Pigments were best modelled using reflectance data from the visible region (400-700 nm), while all other traits were best modelled using reflectance data from the shortwave infrared region (1100-2500 nm). Spectroscopy delivered accurate predictions of species-level variation in traits. However, it was ineffective at detecting intraspecific variation in rock-derived nutrients (with the notable exception of P). The explanation for this failure is that rock-derived elements do not have absorption features in the 400-2500 nm region, and their estimation is indirect, relying on elemental concentrations covarying with structural traits that do have absorption features in that spectral region (constellation effects). Since the structural traits did not vary with soil type, it was impossible for our regression models to predict intraspecific variation in rock-derived nutrients via constellation effects. This study demonstrates the value of spectroscopy for rapid, non-destructive estimation of foliar traits across species, but highlights problems with predicting intraspecific variation indirectly. We discuss the implications of these findings for mapping functional traits by airborne imaging spectroscopy.

Incremental Validity of the Durand Adaptive Psychopathic Traits Questionnaire Above Self-Report Psychopathy Measures in Community Samples.

PubMed

Durand, Guillaume

2018-05-03

Although highly debated, the notion of the existence of an adaptive side to psychopathy is supported by some researchers. Currently, 2 instruments assessing psychopathic traits include an adaptive component, which might not cover the full spectrum of adaptive psychopathic traits. The Durand Adaptive Psychopathic Traits Questionnaire (DAPTQ; Durand, 2017 ) is a 41-item self-reported instrument assessing adaptive traits known to correlate with the psychopathic personality. In this study, I investigated in 2 samples (N = 263 and N = 262) the incremental validity of the DAPTQ over the Psychopathic Personality Inventory-Short Form (PPI-SF) and the Triarchic Psychopathy Measure (TriPM) using multiple criterion measures. Results showed that the DAPTQ significantly increased the predictive validity over the PPI-SF on 5 factors of the HEXACO. Additionally, the DAPTQ provided incremental validity over both the PPI-SF and the TriPM on measures of communication adaptability, perceived stress, and trait anxiety. Overall, these results support the validity of the DAPTQ in community samples. Directions for future studies to further validate the DAPTQ are discussed.

A novel variational Bayes multiple locus Z-statistic for genome-wide association studies with Bayesian model averaging

PubMed Central

Logsdon, Benjamin A.; Carty, Cara L.; Reiner, Alexander P.; Dai, James Y.; Kooperberg, Charles

2012-01-01

Motivation: For many complex traits, including height, the majority of variants identified by genome-wide association studies (GWAS) have small effects, leaving a significant proportion of the heritable variation unexplained. Although many penalized multiple regression methodologies have been proposed to increase the power to detect associations for complex genetic architectures, they generally lack mechanisms for false-positive control and diagnostics for model over-fitting. Our methodology is the first penalized multiple regression approach that explicitly controls Type I error rates and provide model over-fitting diagnostics through a novel normally distributed statistic defined for every marker within the GWAS, based on results from a variational Bayes spike regression algorithm. Results: We compare the performance of our method to the lasso and single marker analysis on simulated data and demonstrate that our approach has superior performance in terms of power and Type I error control. In addition, using the Women's Health Initiative (WHI) SNP Health Association Resource (SHARe) GWAS of African-Americans, we show that our method has power to detect additional novel associations with body height. These findings replicate by reaching a stringent cutoff of marginal association in a larger cohort. Availability: An R-package, including an implementation of our variational Bayes spike regression (vBsr) algorithm, is available at http://kooperberg.fhcrc.org/soft.html. Contact: blogsdon@fhcrc.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22563072

MultiBLUP: improved SNP-based prediction for complex traits.

PubMed

Speed, Doug; Balding, David J

2014-09-01

BLUP (best linear unbiased prediction) is widely used to predict complex traits in plant and animal breeding, and increasingly in human genetics. The BLUP mathematical model, which consists of a single random effect term, was adequate when kinships were measured from pedigrees. However, when genome-wide SNPs are used to measure kinships, the BLUP model implicitly assumes that all SNPs have the same effect-size distribution, which is a severe and unnecessary limitation. We propose MultiBLUP, which extends the BLUP model to include multiple random effects, allowing greatly improved prediction when the random effects correspond to classes of SNPs with distinct effect-size variances. The SNP classes can be specified in advance, for example, based on SNP functional annotations, and we also provide an adaptive procedure for determining a suitable partition of SNPs. We apply MultiBLUP to genome-wide association data from the Wellcome Trust Case Control Consortium (seven diseases), and from much larger studies of celiac disease and inflammatory bowel disease, finding that it consistently provides better prediction than alternative methods. Moreover, MultiBLUP is computationally very efficient; for the largest data set, which includes 12,678 individuals and 1.5 M SNPs, the total analysis can be run on a single desktop PC in less than a day and can be parallelized to run even faster. Tools to perform MultiBLUP are freely available in our software LDAK. © 2014 Speed and Balding; Published by Cold Spring Harbor Laboratory Press.

The effect of cultural interaction on cumulative cultural evolution.

PubMed

Nakahashi, Wataru

2014-07-07

Cultural transmission and cultural evolution are important for animals, especially for humans. I developed a new analytical model of cultural evolution, in which each newborn learns cultural traits from multiple individuals (exemplars) in parental generation, individually explores around learned cultural traits, judges the utility of known cultural traits, and adopts a mature cultural trait. Cultural evolutionary speed increases when individuals explore a wider range of cultural traits, accurately judge the skill level of cultural traits (strong direct bias), do not strongly conform to the population mean, increase the exploration range according to the variety of socially learned cultural traits (condition dependent exploration), and make smaller errors in social learning. Number of exemplars, population size, similarity of cultural traits between exemplars, and one-to-many transmission have little effect on cultural evolutionary speed. I also investigated how cultural interaction between two populations with different mean skill levels affects their cultural evolution. A population sometimes increases in skill level more if it encounters a less skilled population than if it does not encounter anyone. A less skilled population sometimes exceeds a more skilled population in skill level by cultural interaction between both populations. The appropriateness of this analytical method is confirmed by individual-based simulations. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

A Unified Framework for Association Analysis with Multiple Related Phenotypes

PubMed Central

Stephens, Matthew

2013-01-01

We consider the problem of assessing associations between multiple related outcome variables, and a single explanatory variable of interest. This problem arises in many settings, including genetic association studies, where the explanatory variable is genotype at a genetic variant. We outline a framework for conducting this type of analysis, based on Bayesian model comparison and model averaging for multivariate regressions. This framework unifies several common approaches to this problem, and includes both standard univariate and standard multivariate association tests as special cases. The framework also unifies the problems of testing for associations and explaining associations – that is, identifying which outcome variables are associated with genotype. This provides an alternative to the usual, but conceptually unsatisfying, approach of resorting to univariate tests when explaining and interpreting significant multivariate findings. The method is computationally tractable genome-wide for modest numbers of phenotypes (e.g. 5–10), and can be applied to summary data, without access to raw genotype and phenotype data. We illustrate the methods on both simulated examples, and to a genome-wide association study of blood lipid traits where we identify 18 potential novel genetic associations that were not identified by univariate analyses of the same data. PMID:23861737

Drought, Fire and Insects in Western US Forests: Observations to Improve Regional Land System Modeling

NASA Astrophysics Data System (ADS)

Law, B. E.; Yang, Z.; Berner, L. T.; Hicke, J. A.; Buotte, P.; Hudiburg, T. W.

2015-12-01

Drought, fire and insects are major disturbances in the western US, and conditions are expected to get warmer and drier in the future. We combine multi-scale observations and modeling with CLM4.5 to examine the effects of these disturbances on forests in the western US. We modified the Community Land Model, CLM4.5, to improve simulated drought-related mortality in forests, and prediction of insect outbreaks under future climate conditions. We examined differences in plant traits that represent species variation in sensitivity to drought, and redefined plant groupings in PFTs. Plant traits, including sapwood area: leaf area ratio and stemwood density were strongly correlated with water availability during the ecohydrologic year. Our database of co-located observations of traits for 30 tree species was used to produce parameterization of the model by species groupings according to similar traits. Burn area predicted by the new fire model in CLM4.5 compares well with recent years of GFED data, but has a positive bias compared with Landsat-based MTBS. Biomass mortality over recent decades increased, and was captured well by the model in general, but missed mortality trends of some species. Comparisons with AmeriFlux data showed that the model with dynamic tree mortality only (no species trait improvements) overestimated GPP in dry years compared with flux data at semi-arid sites, and underestimated GPP at more mesic sites that experience dry summers. Simulations with both dynamic tree mortality and species trait parameters improved estimates of GPP by 17-22%; differences between predicted and observed NEE were larger. Future projections show higher productivity from increased atmospheric CO2 and warming that somewhat offsets drought and fire effects over the next few decades. Challenges include representation of hydraulic failure in models, and availability of species trait and carbon/water process data in disturbance- and drought-impacted regions.

The role of individual differences in the accuracy of confidence judgments.

PubMed

Pallier, Gerry; Wilkinson, Rebecca; Danthiir, Vanessa; Kleitman, Sabina; Knezevic, Goran; Stankov, Lazar; Roberts, Richard D

2002-07-01

Generally, self-assessment of accuracy in the cognitive domain produces overconfidence, whereas self-assessment of visual perceptual judgments results in underconfidence. Despite contrary empirical evidence, in models attempting to explain those phenomena, individual differences have often been disregarded. The authors report on 2 studies in which that shortcoming was addressed. In Experiment 1, participants (N= 520) completed a large number of cognitive-ability tests. Results indicated that individual differences provide a meaningful source of overconfidence and that a metacognitive trait might mediate that effect. In further analysis, there was only a relatively small correlation between test accuracy and confidence bias. In Experiment 2 (N = 107 participants), both perceptual and cognitive ability tests were included, along with measures of personality. Results again indicated the presence of a confidence factor that transcended the nature of the testing vehicle. Furthermore, a small relationship was found between that factor and some self-reported personality measures. Thus, personality traits and cognitive ability appeared to play only a small role in determining the accuracy of self-assessment. Collectively, the present results suggest that there are multiple causes of miscalibration, which current models of over- and underconfidence fail to encompass.

Physiological and fitness differences between cytotypes vary with stress in a grassland perennial herb

PubMed Central

Pavlíková, Zuzana; Holá, Dana; Vlasáková, Blanka; Procházka, Tomáš

2017-01-01

Background and aims Understanding the consequences of polyploidization is a major step towards assessing the importance of this mode of speciation. Most previous studies comparing different cytotypes, however, did so only within a single environment and considered only one group of traits. To take a step further, we need to explore multiple environments and a wide range of traits. The aim of this study was to assess response of diploid and autotetraploid individuals of Knautia arvensis (Dipsacaceae) to two stress conditions, shade or drought. Methods We studied eleven photosynthetic, morphological and fitness parameters of the plants over three years in a common garden under ambient conditions and two types of stress. Key results The results indicate strong differences in performance and physiology between cytotypes in ambient conditions. Interestingly, higher fitness in diploids contrasted with more efficient photosynthesis in tetraploids in ambient conditions. However, stress, especially drought, strongly reduced fitness and disrupted function of the photosystems in both cytotypes reducing the between cytotype differences. The results indicate that drought stress reduced function of the photosynthetic processes in both cytotypes but particularly in tetraploids, while fitness reduction was stronger in diploids. Conclusions The photosynthesis related traits show higher plasticity in polyploids as theoretically expected, while the fitness related traits show higher plasticity in diploids especially in response to drought. This suggests that between cytotype comparisons need to consider multiple traits and multiple environments to understand the breath of possible responses of different cytotypes to stress. They also show that integrating results based on different traits is not straightforward and call for better mechanistic understanding of the relationships between species photosynthetic activity and fitness. Still, considering multiple environments and multiple species traits is crucial for understanding the drivers of niche differentiation between cytotypes in future studies. PMID:29190749

Physiological and fitness differences between cytotypes vary with stress in a grassland perennial herb.

PubMed

Pavlíková, Zuzana; Holá, Dana; Vlasáková, Blanka; Procházka, Tomáš; Münzbergová, Zuzana

2017-01-01

Understanding the consequences of polyploidization is a major step towards assessing the importance of this mode of speciation. Most previous studies comparing different cytotypes, however, did so only within a single environment and considered only one group of traits. To take a step further, we need to explore multiple environments and a wide range of traits. The aim of this study was to assess response of diploid and autotetraploid individuals of Knautia arvensis (Dipsacaceae) to two stress conditions, shade or drought. We studied eleven photosynthetic, morphological and fitness parameters of the plants over three years in a common garden under ambient conditions and two types of stress. The results indicate strong differences in performance and physiology between cytotypes in ambient conditions. Interestingly, higher fitness in diploids contrasted with more efficient photosynthesis in tetraploids in ambient conditions. However, stress, especially drought, strongly reduced fitness and disrupted function of the photosystems in both cytotypes reducing the between cytotype differences. The results indicate that drought stress reduced function of the photosynthetic processes in both cytotypes but particularly in tetraploids, while fitness reduction was stronger in diploids. The photosynthesis related traits show higher plasticity in polyploids as theoretically expected, while the fitness related traits show higher plasticity in diploids especially in response to drought. This suggests that between cytotype comparisons need to consider multiple traits and multiple environments to understand the breath of possible responses of different cytotypes to stress. They also show that integrating results based on different traits is not straightforward and call for better mechanistic understanding of the relationships between species photosynthetic activity and fitness. Still, considering multiple environments and multiple species traits is crucial for understanding the drivers of niche differentiation between cytotypes in future studies.

Exploring the Assessment of the DSM-5 Alternative Model for Personality Disorders With the Personality Assessment Inventory.

PubMed

Busch, Alexander J; Morey, Leslie C; Hopwood, Christopher J

2017-01-01

Section III of the Diagnostic and Statistical Manual of Mental Disorders (5th ed. [DSM-5]; American Psychiatric Association, 2013) contains an alternative model for the diagnosis of personality disorder involving the assessment of 25 traits and a global level of overall personality functioning. There is hope that this model will be increasingly used in clinical and research settings, and the ability to apply established instruments to assess these concepts could facilitate this process. This study sought to develop scoring algorithms for these alternative model concepts using scales from the Personality Assessment Inventory (PAI). A multiple regression strategy used to predict scores in 2 undergraduate samples on DSM-5 alternative model instruments: the Personality Inventory for the DSM-5 (PID-5) and the General Personality Pathology scale (GPP; Morey et al., 2011 ). These regression functions resulted in scores that demonstrated promising convergent and discriminant validity across the alternative model concepts, as well as a factor structure in a cross-validation sample that was congruent with the putative structure of the alternative model traits. Results were linked to the PAI community normative data to provide normative information regarding these alternative model concepts that can be used to identify elevated traits and personality functioning level scores.

kruX: matrix-based non-parametric eQTL discovery.

PubMed

Qi, Jianlong; Asl, Hassan Foroughi; Björkegren, Johan; Michoel, Tom

2014-01-14

The Kruskal-Wallis test is a popular non-parametric statistical test for identifying expression quantitative trait loci (eQTLs) from genome-wide data due to its robustness against variations in the underlying genetic model and expression trait distribution, but testing billions of marker-trait combinations one-by-one can become computationally prohibitive. We developed kruX, an algorithm implemented in Matlab, Python and R that uses matrix multiplications to simultaneously calculate the Kruskal-Wallis test statistic for several millions of marker-trait combinations at once. KruX is more than ten thousand times faster than computing associations one-by-one on a typical human dataset. We used kruX and a dataset of more than 500k SNPs and 20k expression traits measured in 102 human blood samples to compare eQTLs detected by the Kruskal-Wallis test to eQTLs detected by the parametric ANOVA and linear model methods. We found that the Kruskal-Wallis test is more robust against data outliers and heterogeneous genotype group sizes and detects a higher proportion of non-linear associations, but is more conservative for calling additive linear associations. kruX enables the use of robust non-parametric methods for massive eQTL mapping without the need for a high-performance computing infrastructure and is freely available from http://krux.googlecode.com.

Information Commons for Rice (IC4R)

PubMed Central

2016-01-01

Rice is the most important staple food for a large part of the world's human population and also a key model organism for plant research. Here, we present Information Commons for Rice (IC4R; http://ic4r.org), a rice knowledgebase featuring adoption of an extensible and sustainable architecture that integrates multiple omics data through community-contributed modules. Each module is developed and maintained by different committed groups, deals with data collection, processing and visualization, and delivers data on-demand via web services. In the current version, IC4R incorporates a variety of rice data through multiple committed modules, including genome-wide expression profiles derived entirely from RNA-Seq data, resequencing-based genomic variations obtained from re-sequencing data of thousands of rice varieties, plant homologous genes covering multiple diverse plant species, post-translational modifications, rice-related literatures and gene annotations contributed by the rice research community. Unlike extant related databases, IC4R is designed for scalability and sustainability and thus also features collaborative integration of rice data and low costs for database update and maintenance. Future directions of IC4R include incorporation of other omics data and association of multiple omics data with agronomically important traits, dedicating to build IC4R into a valuable knowledgebase for both basic and translational researches in rice. PMID:26519466

Linking genotoxic responses and reproductive success in ecotoxicology

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

Anderson, S.L.; Wild, G.C.

1994-12-01

The potential of genotoxicity biomarkers as predictors of detrimental environmental effects, such as altered reproductive success of wild organisms, must be rigorously determined. Recent research to evaluate relationships between genotoxic responses and indicators of reproductive success in model animals is described from an ecotoxicological perspective. Genotoxicity can be correlated with reproductive effects such as gamete loss due to cell death; embryonic mortality; and heritable mutations in a range of model animals including polychaete worms, nematodes, sea urchins, amphibians, and fish. In preliminary studies, the polychaete worm, Neanthes arenaceodentata, and the nematode, Caenorhabditis elegans, have also shown the potential for cumulativemore » DNA damage in gametes. If DNA repair capacity is limited in gametes, then selected life history traits such as long and synchronous periods of gametogenesis may confer vulnerability to genotoxic substances in chronic exposures. Recommendations for future research include strategic development of animal models that can be used to elucidate multiple mechanisms of effect (multiend point) at varying levels of biological organization (multilevel). 27 refs., 2 tabs.« less

Terrestrial Feedbacks Incorporated in Global Vegetation Models through Observed Trait-Environment Responses

NASA Astrophysics Data System (ADS)

Bodegom, P. V.

2015-12-01

Most global vegetation models used to evaluate climate change impacts rely on plant functional types to describe vegetation responses to environmental stresses. In a traditional set-up in which vegetation characteristics are considered constant within a vegetation type, the possibility to implement and infer feedback mechanisms are limited as feedback mechanisms will likely involve a changing expression of community trait values. Based on community assembly concepts, we implemented functional trait-environment relationships into a global dynamic vegetation model to quantitatively assess this feature. For the current climate, a different global vegetation distribution was calculated with and without the inclusion of trait variation, emphasizing the importance of feedbacks -in interaction with competitive processes- for the prevailing global patterns. These trait-environmental responses do, however, not necessarily imply adaptive responses of vegetation to changing conditions and may locally lead to a faster turnover in vegetation upon climate change. Indeed, when running climate projections, simulations with trait variation did not yield a more stable or resilient vegetation than those without. Through the different feedback expressions, global and regional carbon and water fluxes were -however- strongly altered. At a global scale, model projections suggest an increased productivity and hence an increased carbon sink in the next decades to come, when including trait variation. However, by the end of the century, a reduced carbon sink is projected. This effect is due to a downregulation of photosynthesis rates, particularly in the tropical regions, even when accounting for CO2-fertilization effects. Altogether, the various global model simulations suggest the critical importance of including vegetation functional responses to changing environmental conditions to grasp terrestrial feedback mechanisms at global scales in the light of climate change.

Multiple transgene traits may create un-intended fitness effects in Brassica napus

EPA Science Inventory

Increasingly, genetically modified crops are being developed to express multiple “stacked” traits for different types of transgenes, for example, herbicide resistance, insect resistance, crop quality and resistance to environmental factors. The release of crops that express mult...

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.

Impact of Multiple Environmental Stresses on Wetland Vegetation Dynamics

NASA Astrophysics Data System (ADS)

Muneepeerakul, C. P.; Tamea, S.; Muneepeerakul, R.; Miralles-Wilhelm, F. R.; Rinaldo, A.; Rodriguez-Iturbe, I.

2009-12-01

This research quantifies the impacts of climate change on the dynamics of wetland vegetation under the effect of multiple stresses, such as drought, water-logging, shade and nutrients. The effects of these stresses are investigated through a mechanistic model that captures the co-evolving nature between marsh emergent plant species and their resources (water, nitrogen, light, and oxygen). The model explicitly considers the feedback mechanisms between vegetation, light and nitrogen dynamics as well as the specific dynamics of plant leaves, rhizomes, and roots. Each plant species is characterized by three independent traits, namely leaf nitrogen (N) content, specific leaf area, and allometric carbon (C) allocation to rhizome storage, which govern the ability to gain and maintain resources as well as to survive in a particular multi-stressed environment. The modeling of plant growth incorporates C and N into the construction of leaves and roots, whose amount of new biomass is determined by the dynamic plant allocation scheme. Nitrogen is internally recycled between pools of plants, litter, humus, microbes, and mineral N. The N dynamics are modeled using a parallel scheme, with the major modifications being the calculation of the aerobic and anoxic periods and the incorporation of the anaerobic processes. A simple hydrologic model with stochastic rainfall is used to describe the water level dynamics and the soil moisture profile. Soil water balance is evaluated at the daily time scale and includes rainfall, evapotranspiration and lateral flow to/from an external water body, with evapotranspiration loss equal to the potential value, governed by the daily average condition of atmospheric water demand. The resulting feedback dynamics arising from the coupled system of plant-soil-microbe are studied in details and species’ fitnesses in the 3-D trait space are compared across various rainfall patterns with different mean and fluctuations. The model results are then compared with those from experiments and field studies reported in the literature, providing insights about the physiological features that enable plants to thrive in different wetland environments and climate regimes.

Testing whether the DSM-5 personality disorder trait model can be measured with a reduced set of items: An item response theory investigation of the Personality Inventory for DSM-5.

PubMed

Maples, Jessica L; Carter, Nathan T; Few, Lauren R; Crego, Cristina; Gore, Whitney L; Samuel, Douglas B; Williamson, Rachel L; Lynam, Donald R; Widiger, Thomas A; Markon, Kristian E; Krueger, Robert F; Miller, Joshua D

2015-12-01

The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) includes an alternative model of personality disorders (PDs) in Section III, consisting in part of a pathological personality trait model. To date, the 220-item Personality Inventory for DSM-5 (PID-5; Krueger, Derringer, Markon, Watson, & Skodol, 2012) is the only extant self-report instrument explicitly developed to measure this pathological trait model. The present study used item response theory-based analyses in a large sample (n = 1,417) to investigate whether a reduced set of 100 items could be identified from the PID-5 that could measure the 25 traits and 5 domains. This reduced set of PID-5 items was then tested in a community sample of adults currently receiving psychological treatment (n = 109). Across a wide range of criterion variables including NEO PI-R domains and facets, DSM-5 Section II PD scores, and externalizing and internalizing outcomes, the correlational profiles of the original and reduced versions of the PID-5 were nearly identical (rICC = .995). These results provide strong support for the hypothesis that an abbreviated set of PID-5 items can be used to reliably, validly, and efficiently assess these personality disorder traits. The ability to assess the DSM-5 Section III traits using only 100 items has important implications in that it suggests these traits could still be measured in settings in which assessment-related resources (e.g., time, compensation) are limited. (c) 2015 APA, all rights reserved).

The Five-Factor Model of Personality Traits and Organizational Citizenship Behaviors: A Meta-Analysis

ERIC Educational Resources Information Center

Chiaburu, Dan S.; Oh, In-Sue; Berry, Christopher M.; Li, Ning; Gardner, Richard G.

2011-01-01

Using meta-analytic tests based on 87 statistically independent samples, we investigated the relationships between the five-factor model (FFM) of personality traits and organizational citizenship behaviors in both the aggregate and specific forms, including individual-directed, organization-directed, and change-oriented citizenship. We found that…

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…

Impact of Missing Data on Person-Model Fit and Person Trait Estimation

ERIC Educational Resources Information Center

Zhang, Bo; Walker, Cindy M.

2008-01-01

The purpose of this research was to examine the effects of missing data on person-model fit and person trait estimation in tests with dichotomous items. Under the missing-completely-at-random framework, four missing data treatment techniques were investigated including pairwise deletion, coding missing responses as incorrect, hotdeck imputation,…

Animal Models of Suicide Trait-Related Behaviors

PubMed Central

Malkesman, Oz; Pine, Daniel; Tragon, Tyson; Austin, Daniel R.; Henter, Ioline D.; Chen, Guang; Manji, Husseini K.

2009-01-01

Although antidepressants are at least moderately effective in treating major depressive disorder (MDD), concerns have arisen that selective serotonin reuptake inhibitors (SSRIs) are associated with suicidal thinking and behavior, especially in children, adolescents, and young adults. Virtually no experimental research in model systems has considered the mechanisms by which SSRIs may be associated with this potential side effect in some susceptible individuals. Suicide is a complex behavior that is, at best, complicated to study in humans and impossible to fully reproduce in an animal model. However, by investigating traits that show strong cross-species parallels as well as associations with suicide in humans, animal models may elucidate the mechanisms by which SSRIs are associated with suicidal thinking and behavior in the young. Traits linked with suicide in humans that can be successfully modeled in rodents include aggression, impulsivity, irritability, and hopelessness/helplessness. Differences in animal response to particular paradigms and to SSRIs across the lifespan are also discussed. Modeling these relevant traits in animals can help clarify the impact of SSRIs on these traits, suggesting avenues for reducing suicide risk in this vulnerable population. PMID:19269045

Genome wide association analyses based on a multiple trait approach for modeling feed efficiency

USDA-ARS?s Scientific Manuscript database

Genome wide association (GWA) of feed efficiency (FE) could help target important genomic regions influencing FE. Data provided by an international dairy FE research consortium consisted of phenotypic records on dry matter intakes (DMI), milk energy (MILKE), and metabolic body weight (MBW) on 6,937 ...

Adaptive versus Learner Control in a Multiple Intelligence Learning Environment

ERIC Educational Resources Information Center

Kelly, Declan

2008-01-01

Within the field of technology enhanced learning, adaptive educational systems offer an advanced form of learning environment that attempts to meet the needs of different students. Such systems capture and represent, for each student, various characteristics such as knowledge and traits in an individual learner model. Subsequently, using the…

Cultural hitchhiking on the wave of advance of beneficial technologies.

PubMed

Ackland, Graeme J; Signitzer, Markus; Stratford, Kevin; Cohen, Morrel H

2007-05-22

The wave-of-advance model was introduced to describe the spread of advantageous genes in a population. It can be adapted to model the uptake of any advantageous technology through a population, such as the arrival of neolithic farmers in Europe, the domestication of the horse, and the development of the wheel, iron tools, political organization, or advanced weaponry. Any trait that preexists alongside the advantageous one could be carried along with it, such as genetics or language, regardless of any intrinsic superiority. Decoupling of the advantageous trait from other "hitchhiking" traits depends on its adoption by the preexisting population. Here, we adopt a similar wave-of-advance model based on food production on a heterogeneous landscape with multiple populations. Two key results arise from geographic inhomogeneity: the "subsistence boundary," land so poor that the wave of advance is halted, and the temporary "diffusion boundary" where the wave cannot move into poorer areas until its gradient becomes sufficiently large. At diffusion boundaries, farming technology may pass to indigenous people already in those poorer lands, allowing their population to grow and resist encroachment by farmers. Ultimately, this adoption of technology leads to the halt in spread of the hitchhiking trait and establishment of a permanent "cultural boundary" between distinct cultures with equivalent technology.

Cultural hitchhiking on the wave of advance of beneficial technologies

PubMed Central

Ackland, Graeme J.; Signitzer, Markus; Stratford, Kevin; Cohen, Morrel H.

2007-01-01

The wave-of-advance model was introduced to describe the spread of advantageous genes in a population. It can be adapted to model the uptake of any advantageous technology through a population, such as the arrival of neolithic farmers in Europe, the domestication of the horse, and the development of the wheel, iron tools, political organization, or advanced weaponry. Any trait that preexists alongside the advantageous one could be carried along with it, such as genetics or language, regardless of any intrinsic superiority. Decoupling of the advantageous trait from other “hitchhiking” traits depends on its adoption by the preexisting population. Here, we adopt a similar wave-of-advance model based on food production on a heterogeneous landscape with multiple populations. Two key results arise from geographic inhomogeneity: the “subsistence boundary,” land so poor that the wave of advance is halted, and the temporary “diffusion boundary” where the wave cannot move into poorer areas until its gradient becomes sufficiently large. At diffusion boundaries, farming technology may pass to indigenous people already in those poorer lands, allowing their population to grow and resist encroachment by farmers. Ultimately, this adoption of technology leads to the halt in spread of the hitchhiking trait and establishment of a permanent “cultural boundary” between distinct cultures with equivalent technology. PMID:17517663

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

PubMed Central

Evans, Jonathan P; Gasparini, Clelia

2013-01-01

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

Changes in tree functional composition amplify the response of forest biomass to climate variability

NASA Astrophysics Data System (ADS)

Lichstein, Jeremy; Zhang, Tao; Niinemets, Ulo; Sheffield, Justin

2017-04-01

The response of forest carbon storage to climate change is highly uncertain, contributing substantially to the divergence among global climate model projections. Numerous studies have documented responses of forest ecosystems to climate change and variability, including drought-induced increases in tree mortality rates. However, the sensitivity of forests to climate variability - in terms of both biomass carbon storage and functional components of tree species composition - has yet to be quantified across a large region using systematically sampled data. Here, we combine systematic forest inventories across the eastern USA with a species-level drought-tolerance index, derived from a meta-analysis of published literature, to quantify changes in forest biomass and community-mean-drought-tolerance in one-degree grid cells from the 1980s to 2000s. We show that forest biomass responds to decadal-scale changes in water deficit and that this biomass response is amplified by concurrent changes in community-mean-drought-tolerance. The amplification of the direct effects of water stress on biomass occurs because water stress tends to induce a shift in tree species composition towards more drought-tolerant but lower-biomass species. Multiple plant functional traits are correlated with the above species-level drought-tolerance index, and likely contribute to the decrease in biomass with increasing drought-tolerance. These traits include wood density and P50 (the xylem water potential at which a plant loses 50% of its hydraulic conductivity). Simulations with a trait- and competition-based dynamic global vegetation model suggest that species differences in plant carbon allocation to wood, leaves, and fine roots also likely contribute to the observed decrease in biomass with increasing drought-tolerance, because competition drives plants to over-invest in fine roots when water is limiting. Thus, the most competitive species under dry conditions have greater root allocation but lower total biomass than productivity-maximizing plants. Amplification of the biomass-climate response due to shifts in species functional composition (temporal beta diversity) contrasts with evidence that local (alpha) diversity increases ecosystem stability, including increased resistance to climate extremes. These contrasting effects of alpha and beta diversity highlight the need to better understand how different components of biodiversity, including changes in the functional traits of the dominant plant species, affect ecosystem functioning.

Bioenergy Sorghum Crop Model Predicts VPD-Limited Transpiration Traits Enhance Biomass Yield in Water-Limited Environments

PubMed Central

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

2017-01-01

Bioenergy sorghum is targeted for production in water-limited annual cropland therefore traits that improve plant water capture, water use efficiency, and resilience to water deficit are necessary to maximize productivity. A crop modeling framework, APSIM, was adapted to predict the growth and biomass yield of energy sorghum and to identify potentially useful traits for crop improvement. APSIM simulations of energy sorghum development and biomass accumulation replicated results from field experiments across multiple years, patterns of rainfall, and irrigation schemes. Modeling showed that energy sorghum's long duration of vegetative growth increased water capture and biomass yield by ~30% compared to short season crops in a water-limited production region. Additionally, APSIM was extended to enable modeling of VPD-limited transpiration traits that reduce crop water use under high vapor pressure deficits (VPDs). The response of transpiration rate to increasing VPD was modeled as a linear response until a VPD threshold was reached, at which the slope of the response decreases, representing a range of responses to VPD observed in sorghum germplasm. Simulation results indicated that the VPD-limited transpiration trait is most beneficial in hot and dry regions of production where crops are exposed to extended periods without rainfall during the season or to a terminal drought. In these environments, slower but more efficient transpiration increases biomass yield and prevents or delays the exhaustion of soil water and onset of leaf senescence. The VPD-limited transpiration responses observed in sorghum germplasm increased biomass accumulation by 20% in years with lower summer rainfall, and the ability to drastically reduce transpiration under high VPD conditions could increase biomass by 6% on average across all years. This work indicates that the productivity and resilience of bioenergy sorghum grown in water-limited environments could be further enhanced by development of genotypes with optimized VPD-limited transpiration traits and deployment of these crops in water limited growing environments. The energy sorghum model and VPD-limited transpiration trait implementation are made available to simulate performance in other target environments. PMID:28377779

Bioenergy Sorghum Crop Model Predicts VPD-Limited Transpiration Traits Enhance Biomass Yield in Water-Limited Environments.

PubMed

Truong, Sandra K; McCormick, Ryan F; Mullet, John E

2017-01-01

Bioenergy sorghum is targeted for production in water-limited annual cropland therefore traits that improve plant water capture, water use efficiency, and resilience to water deficit are necessary to maximize productivity. A crop modeling framework, APSIM, was adapted to predict the growth and biomass yield of energy sorghum and to identify potentially useful traits for crop improvement. APSIM simulations of energy sorghum development and biomass accumulation replicated results from field experiments across multiple years, patterns of rainfall, and irrigation schemes. Modeling showed that energy sorghum's long duration of vegetative growth increased water capture and biomass yield by ~30% compared to short season crops in a water-limited production region. Additionally, APSIM was extended to enable modeling of VPD-limited transpiration traits that reduce crop water use under high vapor pressure deficits (VPDs). The response of transpiration rate to increasing VPD was modeled as a linear response until a VPD threshold was reached, at which the slope of the response decreases, representing a range of responses to VPD observed in sorghum germplasm. Simulation results indicated that the VPD-limited transpiration trait is most beneficial in hot and dry regions of production where crops are exposed to extended periods without rainfall during the season or to a terminal drought. In these environments, slower but more efficient transpiration increases biomass yield and prevents or delays the exhaustion of soil water and onset of leaf senescence. The VPD-limited transpiration responses observed in sorghum germplasm increased biomass accumulation by 20% in years with lower summer rainfall, and the ability to drastically reduce transpiration under high VPD conditions could increase biomass by 6% on average across all years. This work indicates that the productivity and resilience of bioenergy sorghum grown in water-limited environments could be further enhanced by development of genotypes with optimized VPD-limited transpiration traits and deployment of these crops in water limited growing environments. The energy sorghum model and VPD-limited transpiration trait implementation are made available to simulate performance in other target environments.

Bioenergy sorghum crop model predicts VPD-limited transpiration traits enhance biomass yield in water-limited environments

DOE PAGES

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

2017-03-21

Bioenergy sorghum is targeted for production in water-limited annual cropland therefore traits that improve plant water capture, water use efficiency, and resilience to water deficit are necessary to maximize productivity. A crop modeling framework, APSIM, was adapted to predict the growth and biomass yield of energy sorghum and to identify potentially useful traits for crop improvement. APSIM simulations of energy sorghum development and biomass accumulation replicated results from field experiments across multiple years, patterns of rainfall, and irrigation schemes. Modeling showed that energy sorghum’s long duration of vegetative growth increased water capture and biomass yield by ~30% compared to shortmore » season crops in a water-limited production region. Additionally, APSIM was extended to enable modeling of VPD-limited transpiration traits that reduce crop water use under high vapor pressure deficits (VPDs). The response of transpiration rate to increasing VPD was modeled as a linear response until a VPD threshold was reached, at which the slope of the response decreases, representing a range of responses to VPD observed in sorghum germplasm. Simulation results indicated that the VPD-limited transpiration trait is most beneficial in hot and dry regions of production where crops are exposed to extended periods without rainfall during the season or to a terminal drought. In these environments, slower but more efficient transpiration increases biomass yield and prevents or delays the exhaustion of soil water and onset of leaf senescence. The VPD-limited transpiration responses observed in sorghum germplasm increased biomass accumulation by 20% in years with lower summer rainfall, and the ability to drastically reduce transpiration under high VPD conditions could increase biomass by 6% on average across all years. This work indicates that the productivity and resilience of bioenergy sorghum grown in water-limited environments could be further enhanced by development of genotypes with optimized VPD-limited transpiration traits and deployment of these crops in water limited growing environments. As a result, the energy sorghum model and VPD-limited transpiration trait implementation aremade available to simulate performance in other target environments.« less

Bioenergy sorghum crop model predicts VPD-limited transpiration traits enhance biomass yield in water-limited environments

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

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

Bioenergy sorghum is targeted for production in water-limited annual cropland therefore traits that improve plant water capture, water use efficiency, and resilience to water deficit are necessary to maximize productivity. A crop modeling framework, APSIM, was adapted to predict the growth and biomass yield of energy sorghum and to identify potentially useful traits for crop improvement. APSIM simulations of energy sorghum development and biomass accumulation replicated results from field experiments across multiple years, patterns of rainfall, and irrigation schemes. Modeling showed that energy sorghum’s long duration of vegetative growth increased water capture and biomass yield by ~30% compared to shortmore » season crops in a water-limited production region. Additionally, APSIM was extended to enable modeling of VPD-limited transpiration traits that reduce crop water use under high vapor pressure deficits (VPDs). The response of transpiration rate to increasing VPD was modeled as a linear response until a VPD threshold was reached, at which the slope of the response decreases, representing a range of responses to VPD observed in sorghum germplasm. Simulation results indicated that the VPD-limited transpiration trait is most beneficial in hot and dry regions of production where crops are exposed to extended periods without rainfall during the season or to a terminal drought. In these environments, slower but more efficient transpiration increases biomass yield and prevents or delays the exhaustion of soil water and onset of leaf senescence. The VPD-limited transpiration responses observed in sorghum germplasm increased biomass accumulation by 20% in years with lower summer rainfall, and the ability to drastically reduce transpiration under high VPD conditions could increase biomass by 6% on average across all years. This work indicates that the productivity and resilience of bioenergy sorghum grown in water-limited environments could be further enhanced by development of genotypes with optimized VPD-limited transpiration traits and deployment of these crops in water limited growing environments. As a result, the energy sorghum model and VPD-limited transpiration trait implementation aremade available to simulate performance in other target environments.« less

A Genome-Wide mQTL Analysis in Human Adipose Tissue Identifies Genetic Variants Associated with DNA Methylation, Gene Expression and Metabolic Traits

PubMed Central

Volkov, Petr; Olsson, Anders H.; Gillberg, Linn; Jørgensen, Sine W.; Brøns, Charlotte; Eriksson, Karl-Fredrik; Groop, Leif; Jansson, Per-Anders; Nilsson, Emma; Rönn, Tina; Vaag, Allan; Ling, Charlotte

2016-01-01

Little is known about the extent to which interactions between genetics and epigenetics may affect the risk of complex metabolic diseases and/or their intermediary phenotypes. We performed a genome-wide DNA methylation quantitative trait locus (mQTL) analysis in human adipose tissue of 119 men, where 592,794 single nucleotide polymorphisms (SNPs) were related to DNA methylation of 477,891 CpG sites, covering 99% of RefSeq genes. SNPs in significant mQTLs were further related to gene expression in adipose tissue and obesity related traits. We found 101,911 SNP-CpG pairs (mQTLs) in cis and 5,342 SNP-CpG pairs in trans showing significant associations between genotype and DNA methylation in adipose tissue after correction for multiple testing, where cis is defined as distance less than 500 kb between a SNP and CpG site. These mQTLs include reported obesity, lipid and type 2 diabetes loci, e.g. ADCY3/POMC, APOA5, CETP, FADS2, GCKR, SORT1 and LEPR. Significant mQTLs were overrepresented in intergenic regions meanwhile underrepresented in promoter regions and CpG islands. We further identified 635 SNPs in significant cis-mQTLs associated with expression of 86 genes in adipose tissue including CHRNA5, G6PC2, GPX7, RPL27A, THNSL2 and ZFP57. SNPs in significant mQTLs were also associated with body mass index (BMI), lipid traits and glucose and insulin levels in our study cohort and public available consortia data. Importantly, the Causal Inference Test (CIT) demonstrates how genetic variants mediate their effects on metabolic traits (e.g. BMI, cholesterol, high-density lipoprotein (HDL), hemoglobin A1c (HbA1c) and homeostatic model assessment of insulin resistance (HOMA-IR)) via altered DNA methylation in human adipose tissue. This study identifies genome-wide interactions between genetic and epigenetic variation in both cis and trans positions influencing gene expression in adipose tissue and in vivo (dys)metabolic traits associated with the development of obesity and diabetes. PMID:27322064

Evidence for adaptive radiation from a phylogenetic study of plant defenses

PubMed Central

Agrawal, Anurag A.; Fishbein, Mark; Halitschke, Rayko; Hastings, Amy P.; Rabosky, Daniel L.; Rasmann, Sergio

2009-01-01

One signature of adaptive radiation is a high level of trait change early during the diversification process and a plateau toward the end of the radiation. Although the study of the tempo of evolution has historically been the domain of paleontologists, recently developed phylogenetic tools allow for the rigorous examination of trait evolution in a tremendous diversity of organisms. Enemy-driven adaptive radiation was a key prediction of Ehrlich and Raven's coevolutionary hypothesis [Ehrlich PR, Raven PH (1964) Evolution 18:586–608], yet has remained largely untested. Here we examine patterns of trait evolution in 51 North American milkweed species (Asclepias), using maximum likelihood methods. We study 7 traits of the milkweeds, ranging from seed size and foliar physiological traits to defense traits (cardenolides, latex, and trichomes) previously shown to impact herbivores, including the monarch butterfly. We compare the fit of simple random-walk models of trait evolution to models that incorporate stabilizing selection (Ornstein-Ulenbeck process), as well as time-varying rates of trait evolution. Early bursts of trait evolution were implicated for 2 traits, while stabilizing selection was implicated for several others. We further modeled the relationship between trait change and species diversification while allowing rates of trait evolution to vary during the radiation. Species-rich lineages underwent a proportionately greater decline in latex and cardenolides relative to species-poor lineages, and the rate of trait change was most rapid early in the radiation. An interpretation of this result is that reduced investment in defensive traits accelerated diversification, and disproportionately so, early in the adaptive radiation of milkweeds. PMID:19805160

Comparison of three models to estimate breeding values for percentage of loin intramuscular fat in Duroc swine.

PubMed

Newcom, D W; Baas, T J; Stalder, K J; Schwab, C R

2005-04-01

Three selection models were evaluated to compare selection candidate rankings based on EBV and to evaluate subsequent effects of model-derived EBV on the selection differential and expected genetic response in the population. Data were collected from carcass- and ultrasound-derived estimates of loin i.m. fat percent (IMF) in a population of Duroc swine under selection to increase IMF. The models compared were Model 1, a two-trait animal model used in the selection experiment that included ultrasound IMF from all pigs scanned and carcass IMF from pigs slaughtered to estimate breeding values for both carcass (C1) and ultrasound IMF (U1); Model 2, a single-trait animal model that included ultrasound IMF values on all pigs scanned to estimate breeding values for ultrasound IMF (U2); and Model 3, a multiple-trait animal model including carcass IMF from slaughtered pigs and the first three principal components from a total of 10 image parameters averaged across four longitudinal ultrasound images to estimate breeding values for carcass IMF (C3). Rank correlations between breeding value estimates for U1 and C1, U1 and U2, and C1 and C3 were 0.95, 0.97, and 0.92, respectively. Other rank correlations were 0.86 or less. In the selection experiment, approximately the top 10% of boars and 50% of gilts were selected. Selection differentials for pigs in Generation 3 were greatest when ranking pigs based on C1, followed by U1, U2, and C3. In addition, selection differential and estimated response were evaluated when simulating selection of the top 1, 5, and 10% of sires and 50% of dams. Results of this analysis indicated the greatest selection differential was for selection based on C1. The greatest loss in selection differential was found for selection based on C3 when selecting the top 10 and 1% of boars and 50% of gilts. The loss in estimated response when selecting varying percentages of boars and the top 50% of gilts was greatest when selection was based on C3 (16.0 to 25.8%) and least for selection based on U1 (1.3 to 10.9%). Estimated genetic change from selection based on carcass IMF was greater than selection based on ultrasound IMF. Results show that selection based on a combination of ultrasonically predicted IMF and sib carcass IMF produced the greatest selection differentials and should lead to the greatest genetic change.

An expressed sequence tag (EST) library for Drosophila serrata, a model system for sexual selection and climatic adaptation studies.

PubMed

Frentiu, Francesca D; Adamski, Marcin; McGraw, Elizabeth A; Blows, Mark W; Chenoweth, Stephen F

2009-01-21

The native Australian fly Drosophila serrata belongs to the highly speciose montium subgroup of the melanogaster species group. It has recently emerged as an excellent model system with which to address a number of important questions, including the evolution of traits under sexual selection and traits involved in climatic adaptation along latitudinal gradients. Understanding the molecular genetic basis of such traits has been limited by a lack of genomic resources for this species. Here, we present the first expressed sequence tag (EST) collection for D. serrata that will enable the identification of genes underlying sexually-selected phenotypes and physiological responses to environmental change and may help resolve controversial phylogenetic relationships within the montium subgroup. A normalized cDNA library was constructed from whole fly bodies at several developmental stages, including larvae and adults. Assembly of 11,616 clones sequenced from the 3' end allowed us to identify 6,607 unique contigs, of which at least 90% encoded peptides. Partial transcripts were discovered from a variety of genes of evolutionary interest by BLASTing contigs against the 12 Drosophila genomes currently sequenced. By incorporating into the cDNA library multiple individuals from populations spanning a large portion of the geographical range of D. serrata, we were able to identify 11,057 putative single nucleotide polymorphisms (SNPs), with 278 different contigs having at least one "double hit" SNP that is highly likely to be a real polymorphism. At least 394 EST-associated microsatellite markers, representing 355 different contigs, were also found, providing an additional set of genetic markers. The assembled EST library is available online at http://www.chenowethlab.org/serrata/index.cgi. We have provided the first gene collection and largest set of polymorphic genetic markers, to date, for the fly D. serrata. The EST collection will provide much needed genomic resources for this model species and facilitate comparative evolutionary studies within the montium subgroup of the D. melanogaster lineage.

TRY – a global database of plant traits

PubMed Central

Kattge, J; Díaz, S; Lavorel, S; Prentice, I C; Leadley, P; Bönisch, G; Garnier, E; Westoby, M; Reich, P B; Wright, I J; Cornelissen, J H C; Violle, C; Harrison, S P; Van Bodegom, P M; Reichstein, M; Enquist, B J; Soudzilovskaia, N A; Ackerly, D D; Anand, M; Atkin, O; Bahn, M; Baker, T R; Baldocchi, D; Bekker, R; Blanco, C C; Blonder, B; Bond, W J; Bradstock, R; Bunker, D E; Casanoves, F; Cavender-Bares, J; Chambers, J Q; Chapin, F S; Chave, J; Coomes, D; Cornwell, W K; Craine, J M; Dobrin, B H; Duarte, L; Durka, W; Elser, J; Esser, G; Estiarte, M; Fagan, W F; Fang, J; Fernández-Méndez, F; Fidelis, A; Finegan, B; Flores, O; Ford, H; Frank, D; Freschet, G T; Fyllas, N M; Gallagher, R V; Green, W A; Gutierrez, A G; Hickler, T; Higgins, S I; Hodgson, J G; Jalili, A; Jansen, S; Joly, C A; Kerkhoff, A J; Kirkup, D; Kitajima, K; Kleyer, M; Klotz, S; Knops, J M H; Kramer, K; Kühn, I; Kurokawa, H; Laughlin, D; Lee, T D; Leishman, M; Lens, F; Lenz, T; Lewis, S L; Lloyd, J; Llusià, J; Louault, F; Ma, S; Mahecha, M D; Manning, P; Massad, T; Medlyn, B E; Messier, J; Moles, A T; Müller, S C; Nadrowski, K; Naeem, S; Niinemets, Ü; Nöllert, S; Nüske, A; Ogaya, R; Oleksyn, J; Onipchenko, V G; Onoda, Y; Ordoñez, J; Overbeck, G; Ozinga, W A; Patiño, S; Paula, S; Pausas, J G; Peñuelas, J; Phillips, O L; Pillar, V; Poorter, H; Poorter, L; Poschlod, P; Prinzing, A; Proulx, R; Rammig, A; Reinsch, S; Reu, B; Sack, L; Salgado-Negret, B; Sardans, J; Shiodera, S; Shipley, B; Siefert, A; Sosinski, E; Soussana, J-F; Swaine, E; Swenson, N; Thompson, K; Thornton, P; Waldram, M; Weiher, E; White, M; White, S; Wright, S J; Yguel, B; Zaehle, S; Zanne, A E; Wirth, C

2011-01-01

Plant traits – the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs – determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services and provide a link from species richness to ecosystem functional diversity. Trait data thus represent the raw material for a wide range of research from evolutionary biology, community and functional ecology to biogeography. Here we present the global database initiative named TRY, which has united a wide range of the plant trait research community worldwide and gained an unprecedented buy-in of trait data: so far 93 trait databases have been contributed. The data repository currently contains almost three million trait entries for 69 000 out of the world's 300 000 plant species, with a focus on 52 groups of traits characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and persistence. A first data analysis shows that most plant traits are approximately log-normally distributed, with widely differing ranges of variation across traits. Most trait variation is between species (interspecific), but significant intraspecific variation is also documented, up to 40% of the overall variation. Plant functional types (PFTs), as commonly used in vegetation models, capture a substantial fraction of the observed variation – but for several traits most variation occurs within PFTs, up to 75% of the overall variation. In the context of vegetation models these traits would better be represented by state variables rather than fixed parameter values. The improved availability of plant trait data in the unified global database is expected to support a paradigm shift from species to trait-based ecology, offer new opportunities for synthetic plant trait research and enable a more realistic and empirically grounded representation of terrestrial vegetation in Earth system models.

Genome-Enabled Estimates of Additive and Nonadditive Genetic Variances and Prediction of Apple Phenotypes Across Environments

PubMed Central

Kumar, Satish; Molloy, Claire; Muñoz, Patricio; Daetwyler, Hans; Chagné, David; Volz, Richard

2015-01-01

The nonadditive genetic effects may have an important contribution to total genetic variation of phenotypes, so estimates of both the additive and nonadditive effects are desirable for breeding and selection purposes. Our main objectives were to: estimate additive, dominance and epistatic variances of apple (Malus × domestica Borkh.) phenotypes using relationship matrices constructed from genome-wide dense single nucleotide polymorphism (SNP) markers; and compare the accuracy of genomic predictions using genomic best linear unbiased prediction models with or without including nonadditive genetic effects. A set of 247 clonally replicated individuals was assessed for six fruit quality traits at two sites, and also genotyped using an Illumina 8K SNP array. Across several fruit quality traits, the additive, dominance, and epistatic effects contributed about 30%, 16%, and 19%, respectively, to the total phenotypic variance. Models ignoring nonadditive components yielded upwardly biased estimates of additive variance (heritability) for all traits in this study. The accuracy of genomic predicted genetic values (GEGV) varied from about 0.15 to 0.35 for various traits, and these were almost identical for models with or without including nonadditive effects. However, models including nonadditive genetic effects further reduced the bias of GEGV. Between-site genotypic correlations were high (>0.85) for all traits, and genotype-site interaction accounted for <10% of the phenotypic variability. The accuracy of prediction, when the validation set was present only at one site, was generally similar for both sites, and varied from about 0.50 to 0.85. The prediction accuracies were strongly influenced by trait heritability, and genetic relatedness between the training and validation families. PMID:26497141

Genetic parameters of egg quality traits in long-term pedigree recorded Japanese quail.

PubMed

Sari, M; Tilki, M; Saatci, M

2016-08-01

This study was conducted to determine the genetic parameters of internal and external quality traits of Japanese quail eggs. Two statistical models were used in the calculation of genetic parameters and variance components. While 286 eggs were used based on model 1, 1,524 eggs were used based on model 2. Genetic parameters of the first eggs were calculated with direct genetic effect included in the analysis as random factors by using model 1. Model 2 was used for all eggs (5 to 6 eggs from each hen for six rearing groups). As different from model 1, their permanent environmental effects were also included in the model 2. Heritability of egg weight, egg length, egg width, shape index, shell weight, shell thickness, and shell ratio among the external quality traits of the eggs was respectively found to be 0.44, 0.53, 0.51, 0.70, 0.19, 0.16, and 0.05, respectively, according to model 1. These values were found to be 0.46, 0.40, 0.74, 0.48, 0.60, 0.28, and 0.21, respectively, according to model 2. Yolk weight, yolk diameter, yolk height, yolk index, yolk ratio, albumen weight, albumen height, albumen ratio, and Haugh unit values among the internal quality traits of the egg were found to be 0.22, 0.32, 0.02, 0.16, 0.19, 0.34, 0.19, 0.17, and 0.17, respectively, according to model 1. These internal quality traits were found to be 0.27, 0.18, 0.38, 0.06, 0.20, 0.41, 0.15, 0.15, and 0.12, respectively, according to model 2. Consequently, in this study, strong genetic correlations were detected between albumen height and Haugh unit, and also between albumen height and albumen weight. Additionally, a high and positive correlation was observed between some yolk traits (yolk weight and diameter) and albumen traits (weight and height). All these genetic correlations can be used to improve egg quality with a selection according to albumen weight. © 2016 Poultry Science Association Inc.

Extracting Behaviorally Relevant Traits from Natural Stimuli: Benefits of Combinatorial Representations at the Accessory Olfactory Bulb

PubMed Central

Kahan, Anat; Ben-Shaul, Yoram

2016-01-01

For many animals, chemosensation is essential for guiding social behavior. However, because multiple factors can modulate levels of individual chemical cues, deriving information about other individuals via natural chemical stimuli involves considerable challenges. How social information is extracted despite these sources of variability is poorly understood. The vomeronasal system provides an excellent opportunity to study this topic due to its role in detecting socially relevant traits. Here, we focus on two such traits: a female mouse’s strain and reproductive state. In particular, we measure stimulus-induced neuronal activity in the accessory olfactory bulb (AOB) in response to various dilutions of urine, vaginal secretions, and saliva, from estrus and non-estrus female mice from two different strains. We first show that all tested secretions provide information about a female’s receptivity and genotype. Next, we investigate how these traits can be decoded from neuronal activity despite multiple sources of variability. We show that individual neurons are limited in their capacity to allow trait classification across multiple sources of variability. However, simple linear classifiers sampling neuronal activity from small neuronal ensembles can provide a substantial improvement over that attained with individual units. Furthermore, we show that some traits are more efficiently detected than others, and that particular secretions may be optimized for conveying information about specific traits. Across all tested stimulus sources, discrimination between strains is more accurate than discrimination of receptivity, and detection of receptivity is more accurate with vaginal secretions than with urine. Our findings highlight the challenges of chemosensory processing of natural stimuli, and suggest that downstream readout stages decode multiple behaviorally relevant traits by sampling information from distinct but overlapping populations of AOB neurons. PMID:26938460

Extracting Behaviorally Relevant Traits from Natural Stimuli: Benefits of Combinatorial Representations at the Accessory Olfactory Bulb.

PubMed

Kahan, Anat; Ben-Shaul, Yoram

2016-03-01

For many animals, chemosensation is essential for guiding social behavior. However, because multiple factors can modulate levels of individual chemical cues, deriving information about other individuals via natural chemical stimuli involves considerable challenges. How social information is extracted despite these sources of variability is poorly understood. The vomeronasal system provides an excellent opportunity to study this topic due to its role in detecting socially relevant traits. Here, we focus on two such traits: a female mouse's strain and reproductive state. In particular, we measure stimulus-induced neuronal activity in the accessory olfactory bulb (AOB) in response to various dilutions of urine, vaginal secretions, and saliva, from estrus and non-estrus female mice from two different strains. We first show that all tested secretions provide information about a female's receptivity and genotype. Next, we investigate how these traits can be decoded from neuronal activity despite multiple sources of variability. We show that individual neurons are limited in their capacity to allow trait classification across multiple sources of variability. However, simple linear classifiers sampling neuronal activity from small neuronal ensembles can provide a substantial improvement over that attained with individual units. Furthermore, we show that some traits are more efficiently detected than others, and that particular secretions may be optimized for conveying information about specific traits. Across all tested stimulus sources, discrimination between strains is more accurate than discrimination of receptivity, and detection of receptivity is more accurate with vaginal secretions than with urine. Our findings highlight the challenges of chemosensory processing of natural stimuli, and suggest that downstream readout stages decode multiple behaviorally relevant traits by sampling information from distinct but overlapping populations of AOB neurons.

Independent evolution of complex life history adaptations in two families of fishes, live-bearing halfbeaks (zenarchopteridae, beloniformes) and poeciliidae (cyprinodontiformes).

PubMed

Reznick, David; Meredith, Robert; Collette, Bruce B

2007-11-01

We have previously documented multiple, independent origins of placentas in the fish family Poeciliidae. Here we summarize similar analyses of fishes in the family Zenarchopteridae. This family includes three live-bearing genera. Earlier studies documented the presence of superfetation, or the ability to carry multiple litters of young in different stages of development in the same ovary, in some species in all three genera. There is also one earlier report of matrotrophy, or extensive postfertilization maternal provisioning, in two of these genera. We present detailed life-history data for approximately half of the species in all three genera and combine them with the best available phylogeny to make inferences about the pattern of life-history evolution within this family. Three species of Hemirhamphodon have superfetation but lack matrotrophy. Most species in Nomorhamphus and Dermogenys either lack superfetation and matrotrophy or have both superfetation and matrotrophy. Our phylogenetic analysis shows that matrotrophy may have evolved independently in each genus. In Dermogenys, matrotrophic species produce fewer, larger offspring than nonmatrotrophic species. In Nomorhamphus; matrotrophic species instead produce more and smaller offspring than lecithotrophic species. However, the matrotrophic species in both genera have significantly smaller masses of reproductive tissue relative to their body sizes. All aspects of these results are duplicated in the fish family Poeciliidae. We discuss the possible adaptive significance of matrotrophy in the light of these new results. The two families together present a remarkable opportunity to study the evolution of a complex trait because they contain multiple, independent origins of the trait that often include close relatives that vary in either the presence or absence of the matrotrophy or in the degree to which matrotrophy is developed. These are the raw materials that are required for either an analysis of the adaptive significance of the trait or for studies of the genetic mechanisms that underlie the evolution of the trait.

Linking hard and soft traits: Physiology, morphology and anatomy interact to determine habitat affinities to soil water availability in herbaceous dicots.

PubMed

Belluau, Michaël; Shipley, Bill

2018-01-01

Species' habitat affinities along environmental gradients should be determined by a combination of physiological (hard) and morpho-anatomical (soft) traits. Using a gradient of soil water availability, we address three questions: How well can we predict habitat affinities from hard traits, from soft traits, and from a combination of the two? How well can we predict species' physiological responses to drought (hard traits) from their soft traits? Can we model a causal sequence as soft traits → hard traits → species distributions? We chose 25 species of herbaceous dicots whose affinities for soil moisture have already been linked to 5 physiological traits (stomatal conductance and net photosynthesis measured at soil field capacity, water use efficiency, stomatal conductance and soil water potential measured when leaves begin to wilt). Under controlled conditions in soils at field capacity, we measured five soft traits (leaf dry matter content, specific leaf area, leaf nitrogen content, stomatal area, specific root length). Soft traits alone were poor predictors (R2 = 0.129) while hard traits explained 48% of species habitat affinities. Moreover, hard traits were significantly related to combinations of soft traits. From a priori biological knowledge and hypothesized ecological links we built a path model showing a sequential pattern soft traits → hard traits → species distributions and accounting for 59.6% (p = 0.782) of habitat wetness. Both direct and indirect causal relationships existed between soft traits, hard traits and species' habitat preferences. The poor predictive abilities of soft traits alone were due to the existence of antagonistic and synergistic direct and indirect effects of soft traits on habitat preferences mediated by the hard traits. To obtain a more realistic model applicable to a population level, it has to be tested in an experiment including species competition for water supply.

Multiple Hypnotizabilities: Differentiating the Building Blocks of Hypnotic Response

ERIC Educational Resources Information Center

Woody, Erik Z.; Barnier, Amanda J.; McConkey, Kevin M.

2005-01-01

Although hypnotizability can be conceptualized as involving component subskills, standard measures do not differentiate them from a more general unitary trait, partly because the measures include limited sets of dichotomous items. To overcome this, the authors applied full-information factor analysis, a sophisticated analytic approach for…

Ear leaf photosynthesis and related parameters of transgenic and non-GMO maize hybrids

USDA-ARS?s Scientific Manuscript database

Hybrid maize (Zea mays L.) has undergone transformation by using transgenic technology to include d-endotoxins for insect control and tolerance for the herbicides glyphosate and glufosinate . Maize hybrids are being grown with multiple transgenic traits into their genotype (stacked-gene). Limited...

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.

Combining landscape variables and species traits can improve the utility of climate change vulnerability assessments

USGS Publications Warehouse

Nadeau, Christopher P.; Fuller, Angela K.

2016-01-01

Conservation organizations worldwide are investing in climate change vulnerability assessments. Most vulnerability assessment methods focus on either landscape features or species traits that can affect a species vulnerability to climate change. However, landscape features and species traits likely interact to affect vulnerability. We compare a landscape-based assessment, a trait-based assessment, and an assessment that combines landscape variables and species traits for 113 species of birds, herpetofauna, and mammals in the northeastern United States. Our aim is to better understand which species traits and landscape variables have the largest influence on assessment results and which types of vulnerability assessments are most useful for different objectives. Species traits were most important for determining which species will be most vulnerable to climate change. The sensitivity of species to dispersal barriers and the species average natal dispersal distance were the most important traits. Landscape features were most important for determining where species will be most vulnerable because species were most vulnerable in areas where multiple landscape features combined to increase vulnerability, regardless of species traits. The interaction between landscape variables and species traits was important when determining how to reduce climate change vulnerability. For example, an assessment that combines information on landscape connectivity, climate change velocity, and natal dispersal distance suggests that increasing landscape connectivity may not reduce the vulnerability of many species. Assessments that include landscape features and species traits will likely be most useful in guiding conservation under climate change.

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.

Identification of milling and baking quality QTL in multiple soft wheat mapping populations.

PubMed

Cabrera, Antonio; Guttieri, Mary; Smith, Nathan; Souza, Edward; Sturbaum, Anne; Hua, Duc; Griffey, Carl; Barnett, Marla; Murphy, Paul; Ohm, Herb; Uphaus, Jim; Sorrells, Mark; Heffner, Elliot; Brown-Guedira, Gina; Van Sanford, David; Sneller, Clay

2015-11-01

Two mapping approaches were use to identify and validate milling and baking quality QTL in soft wheat. Two LG were consistently found important for multiple traits and we recommend the use marker-assisted selection on specific markers reported here. Wheat-derived food products require a range of characteristics. Identification and understanding of the genetic components controlling end-use quality of wheat is important for crop improvement. We assessed the underlying genetics controlling specific milling and baking quality parameters of soft wheat including flour yield, softness equivalent, flour protein, sucrose, sodium carbonate, water absorption and lactic acid, solvent retention capacities in a diversity panel and five bi-parental mapping populations. The populations were genotyped with SSR and DArT markers, with markers specific for the 1BL.1RS translocation and sucrose synthase gene. Association analysis and composite interval mapping were performed to identify quantitative trait loci (QTL). High heritability was observed for each of the traits evaluated, trait correlations were consistent over populations, and transgressive segregants were common in all bi-parental populations. A total of 26 regions were identified as potential QTL in the diversity panel and 74 QTL were identified across all five bi-parental mapping populations. Collinearity of QTL from chromosomes 1B and 2B was observed across mapping populations and was consistent with results from the association analysis in the diversity panel. Multiple regression analysis showed the importance of the two 1B and 2B regions and marker-assisted selection for the favorable alleles at these regions should improve quality.

Universal Algorithms for Plant Phenotyping: Are we there yet?

NASA Astrophysics Data System (ADS)

Kakani, V. G.; Kambham, R. R.; Zhao, D.; Foster, A. J.; Gowda, P. H.

2017-12-01

Hyperspectral remote sensing offers ability to capture spectral signatures of plant morpho-physio-biochemical traits at multiple scales (leaf to canopy to aerial). Experimental results on plant phenotype from pot, growth chamber and field studies at multiple location were used in this study. Pigment, leaf/plant water status, plant nutrient status, plant height, leaf area, fresh and dry weights of biomass and its components are correlated with hyperspectral reflectance signatures. Leaf reflectance was collected with spectroradiometer having a light source. Canopy hyperspectral reflectance was collected from 1.5 m above the canopy using a spectroradiometer, while multispectral images were acquired from aerial platforms ( 400m). Several statistical methods including simple ratios, principal component analysis, and partial least squares regression were used to identify hyperspectral reflectance bands that were tightly associated with plant phenotypic traits. Leaf level spectra best described the morpho-physio-biochemical traits (R2 = 0.6-0.9), while canopy reflectance best described plant height (R2 = 0.65), leaf area index (R2 = 0.67-0.74) and biomass (R2 = 0.69-0.78), while aerial spectra improved canopy level regression coefficients for plant height (R2 = 0.93) and leaf area index (R2 = 0.89). The comparison of multi-level spectra and resolution, clearly showed the advantage of hyperspectral reflectance data over the multispectral reflectance data, particularly for understanding the basis for spectral reflectance differences among species and traits. In conclusion, high resolution (1-2 cm) spectral imagery can help to bridge the gap across multiple levels of phenotype measurement.

Locus-specific view of flax domestication history

PubMed Central

Fu, Yong-Bi; Diederichsen, Axel; Allaby, Robin G

2012-01-01

Crop domestication has been inferred genetically from neutral markers and increasingly from specific domestication-associated loci. However, some crops are utilized for multiple purposes that may or may not be reflected in a single domestication-associated locus. One such example is cultivated flax (Linum usitatissimum L.), the earliest oil and fiber crop, for which domestication history remains poorly understood. Oil composition of cultivated flax and pale flax (L. bienne Mill.) indicates that the sad2 locus is a candidate domestication locus associated with increased unsaturated fatty acid production in cultivated flax. A phylogenetic analysis of the sad2 locus in 43 pale and 70 cultivated flax accessions established a complex domestication history for flax that has not been observed previously. The analysis supports an early, independent domestication of a primitive flax lineage, in which the loss of seed dispersal through capsular indehiscence was not established, but increased oil content was likely occurred. A subsequent flax domestication process occurred that probably involved multiple domestications and includes lineages that contain oil, fiber, and winter varieties. In agreement with previous studies, oil rather than fiber varieties occupy basal phylogenetic positions. The data support multiple paths of flax domestication for oil-associated traits before selection of the other domestication-associated traits of seed dispersal loss and fiber production. The sad2 locus is less revealing about the origin of winter tolerance. In this case, a single domestication-associated locus is informative about the history of domesticated forms with the associated trait while partially informative on forms less associated with the trait. PMID:22408732

High-Resolution Inflorescence Phenotyping Using a Novel Image-Analysis Pipeline, PANorama1[W][OPEN

PubMed Central

Crowell, Samuel; Falcão, Alexandre X.; Shah, Ankur; Wilson, Zachary; Greenberg, Anthony J.; McCouch, Susan R.

2014-01-01

Variation in inflorescence development is an important target of selection for numerous crop species, including many members of the Poaceae (grasses). In Asian rice (Oryza sativa), inflorescence (panicle) architecture is correlated with yield and grain-quality traits. However, many rice breeders continue to use composite phenotypes in selection pipelines, because measuring complex, branched panicles requires a significant investment of resources. We developed an open-source phenotyping platform, PANorama, which measures multiple architectural and branching phenotypes from images simultaneously. PANorama automatically extracts skeletons from images, allows users to subdivide axes into individual internodes, and thresholds away structures, such as awns, that normally interfere with accurate panicle phenotyping. PANorama represents an improvement in both efficiency and accuracy over existing panicle imaging platforms, and flexible implementation makes PANorama capable of measuring a range of organs from other plant species. Using high-resolution phenotypes, a mapping population of recombinant inbred lines, and a dense single-nucleotide polymorphism data set, we identify, to our knowledge, the largest number of quantitative trait loci (QTLs) for panicle traits ever reported in a single study. Several areas of the genome show pleiotropic clusters of panicle QTLs, including a region near the rice Green Revolution gene SEMIDWARF1. We also confirm that multiple panicle phenotypes are distinctly different among a small collection of diverse rice varieties. Taken together, these results suggest that clusters of small-effect QTLs may be responsible for varietal or subpopulation-specific panicle traits, representing a significant opportunity for rice breeders selecting for yield performance across different genetic backgrounds. PMID:24696519

Genetic correlation and genome-wide association study (GWAS) of the length of productive life, days open, and 305-days milk yield in crossbred Holstein dairy cattle.

PubMed

Saowaphak, P; Duangjinda, M; Plaengkaeo, S; Suwannasing, R; Boonkum, W

2017-06-29

In this study, we estimated the genetic parameters and identified the putative quantitative trait loci (QTL) associated with the length of productive life (LPL), days open (DO), and 305-day milk yield for the first lactation (FM305) of crossbred Holstein dairy cattle. Data comprising 4,739 records collected between 1986 and 2004 were used to estimate the variance-covariance components using the multiple-trait animal linear mixed models based on the average information restricted maximum likelihood (AI-REML) algorithm. Thirty-six animals were genotyped using the Illumina BovineSNP50 Bead Chip [>50,000 single nucleotide polymorphisms (SNPs)] to identify the putative QTL in a genome-wide association study. The heritability of the production trait FM305 was 0.25 and that of the functional traits, LPL and DO, was low (0.10 and 0.06, respectively). The genetic correlation estimates demonstrated favorable negative correlations between LPL and DO (-0.02). However, we observed a favorable positive correlation between FM305 and LPL (0.43) and an unfavorable positive correlation between FM305 and DO (0.1). The GWAS results indicated that 23 QTLs on bovine chromosomes 1, 4, 5, 8, 15, 26, and X were associated with the traits of interest, and the putative QTL regions were identified within seven genes (SYT1, DOCK11, KLHL13, IL13RA1, PRKG1, GNA14, and LRRC4C). In conclusion, the heritability estimates of the LPL and DO were low. Therefore, the approach of multiple-trait selection indexes should be applied, and the QTL identified here should be considered for use in marker-assisted selection in the future.

Spirituality and positive psychology go hand in hand: an investigation of multiple empirically derived profiles and related protective benefits.

PubMed

Barton, Yakov A; Miller, Lisa

2015-06-01

We investigate the relationship between personal spirituality and positive psychology traits as potentially presented in multiple profiles, rather than monolithically across a full sample. A sample of 3966 adolescents and emerging adults (aged 18-25, mean = 20.19, SD = 2.08) and 2014 older adults (aged 26-82, mean = 38.41, SD = 11.26) completed a survey assessing daily spiritual experiences (relationship with a Higher Power and sense of a sacred world), forgiveness, gratitude, optimism, grit, and meaning. To assess the relative protective benefits of potential profiles, we also assessed the level of depressive symptoms and frequency of substance use (tobacco, marijuana, alcohol, and heavy alcohol use). Latent class analysis (LCA) was used to examine common subgroupings of study participants across report on personal spirituality and positive psychology scales in each age cohort, with potential difference between latent classes then tested in level of depressive symptoms and degree of substance use. LCA determined a four-class and a three-class best-fitting models for the younger and older cohorts, respectively. Level of personal spirituality and level of positive psychology traits were found to coincide in 83 % of adolescents and emerging adults and in 71 % of older adults, suggesting personal spirituality and positive psychology traits go hand in hand. A minority subgroup of "virtuous humanists" showed high levels of positive psychology traits but low levels of personal spirituality, across both age cohorts. Whereas level of depression was found to be inversely associated with positive psychology traits and personal spirituality, uniquely personal spirituality was protective against degree of substance use across both age cohorts. Overall interpretation of the study findings suggests that personal spirituality may be foundational to positive psychology traits in the majority of people.

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

PubMed Central

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

2015-01-01

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

Development of a Short Form of the Abridged Big Five-Dimensional Circumplex Model to Aid with the Organization of Personality Traits.

PubMed

Bucher, Meredith A; Samuel, Douglas B

2018-02-01

Although there has been widespread consensus on the use of the Five-Factor Model (FFM) of general personality functioning in personality research, there are various, diverse models of the lower order traits of the FFM domains. Given the usefulness of these finer grained traits, it is imperative to integrate facets proposed across a variety of models and eventually reach consensus on the lower level traits of the FFM. Due to its depth and coverage, the Abridged Big Five-Dimensional Circumplex (AB5C) model potentially provides a useful framework for organizing various faceted models due to its conceptual organization and inclusiveness. The only measure of this model-the IPIP-AB5C-has shown promise, but is limited by its length (i.e., 485 items). This study developed an abbreviated version of the IPIP-AB5C using an iterative process including item response theory methods. The shorter version maintained key features of the long form including a factor structure that matched the full form as well as facets that correlated in expected ways with other FFM measures. Building on this support, the short form was used to contextualize and organize the facets from 2 commonly used measures.

Intraspecific Trait Variation and Coordination: Root and Leaf Economics Spectra in Coffee across Environmental Gradients

PubMed Central

Isaac, Marney E.; Martin, Adam R.; de Melo Virginio Filho, Elias; Rapidel, Bruno; Roupsard, Olivier; Van den Meersche, Karel

2017-01-01

Hypotheses on the existence of a universal “Root Economics Spectrum” (RES) have received arguably the least attention of all trait spectra, despite the key role root trait variation plays in resource acquisition potential. There is growing interest in quantifying intraspecific trait variation (ITV) in plants, but there are few studies evaluating (i) the existence of an intraspecific RES within a plant species, or (ii) how a RES may be coordinated with other trait spectra within species, such as a leaf economics spectrum (LES). Using Coffea arabica (Rubiaceae) as a model species, we measured seven morphological and chemical traits of intact lateral roots, which were paired with information on four key LES traits. Field collections were completed across four nested levels of biological organization. The intraspecific trait coefficient of variation (cv) ranged from 25 to 87% with root diameter and specific root tip density showing the lowest and highest cv, respectively. Between 27 and 68% of root ITV was explained by site identity alone for five of the seven traits measured. A single principal component explained 56.2% of root trait covariation, with plants falling along a RES from resource acquiring to conserving traits. Multiple factor analysis revealed significant orthogonal relationships between root and leaf spectra. RES traits were strongly orthogonal with respect to LES traits, suggesting these traits vary independently from one another in response to environmental cues. This study provides among the first evidence that plants from the same species differentiate from one another along an intraspecific RES. We find that in one of the world’s most widely cultivated crops, an intraspecific RES is orthogonal to an intraspecific LES, indicating that above and belowground responses of plants to managed (or natural) environmental gradients are likely to occur independently from one another. PMID:28747919

Intraspecific Trait Variation and Coordination: Root and Leaf Economics Spectra in Coffee across Environmental Gradients.

PubMed

Isaac, Marney E; Martin, Adam R; de Melo Virginio Filho, Elias; Rapidel, Bruno; Roupsard, Olivier; Van den Meersche, Karel

2017-01-01

Hypotheses on the existence of a universal "Root Economics Spectrum" (RES) have received arguably the least attention of all trait spectra, despite the key role root trait variation plays in resource acquisition potential. There is growing interest in quantifying intraspecific trait variation (ITV) in plants, but there are few studies evaluating (i) the existence of an intraspecific RES within a plant species, or (ii) how a RES may be coordinated with other trait spectra within species, such as a leaf economics spectrum (LES). Using Coffea arabica (Rubiaceae) as a model species, we measured seven morphological and chemical traits of intact lateral roots, which were paired with information on four key LES traits. Field collections were completed across four nested levels of biological organization. The intraspecific trait coefficient of variation (cv) ranged from 25 to 87% with root diameter and specific root tip density showing the lowest and highest cv, respectively. Between 27 and 68% of root ITV was explained by site identity alone for five of the seven traits measured. A single principal component explained 56.2% of root trait covariation, with plants falling along a RES from resource acquiring to conserving traits. Multiple factor analysis revealed significant orthogonal relationships between root and leaf spectra. RES traits were strongly orthogonal with respect to LES traits, suggesting these traits vary independently from one another in response to environmental cues. This study provides among the first evidence that plants from the same species differentiate from one another along an intraspecific RES. We find that in one of the world's most widely cultivated crops, an intraspecific RES is orthogonal to an intraspecific LES, indicating that above and belowground responses of plants to managed (or natural) environmental gradients are likely to occur independently from one another.

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.

A scanner system for high-resolution quantification of variation in root growth dynamics of Brassica rapa genotypes.

PubMed

Adu, Michael O; Chatot, Antoine; Wiesel, Lea; Bennett, Malcolm J; Broadley, Martin R; White, Philip J; Dupuy, Lionel X

2014-05-01

The potential exists to breed for root system architectures that optimize resource acquisition. However, this requires the ability to screen root system development quantitatively, with high resolution, in as natural an environment as possible, with high throughput. This paper describes the construction of a low-cost, high-resolution root phenotyping platform, requiring no sophisticated equipment and adaptable to most laboratory and glasshouse environments, and its application to quantify environmental and temporal variation in root traits between genotypes of Brassica rapa L. Plants were supplied with a complete nutrient solution through the wick of a germination paper. Images of root systems were acquired without manual intervention, over extended periods, using multiple scanners controlled by customized software. Mixed-effects models were used to describe the sources of variation in root traits contributing to root system architecture estimated from digital images. It was calculated that between one and 43 replicates would be required to detect a significant difference (95% CI 50% difference between traits). Broad-sense heritability was highest for shoot biomass traits (>0.60), intermediate (0.25-0.60) for the length and diameter of primary roots and lateral root branching density on the primary root, and lower (<0.25) for other root traits. Models demonstrate that root traits show temporal variations of various types. The phenotyping platform described here can be used to quantify environmental and temporal variation in traits contributing to root system architecture in B. rapa and can be extended to screen the large populations required for breeding for efficient resource acquisition.

Leveraging contemporary species introductions to test phylogenetic hypotheses of trait evolution.

PubMed

Lu-Irving, Patricia; Marx, Hannah E; Dlugosch, Katrina M

2018-05-10

Plant trait evolution is a topic of interest across disciplines and scales. Phylogenetic studies are powerful for generating hypotheses about the mechanisms that have shaped plant traits and their evolution. Introduced plants are a rich source of data on contemporary trait evolution. Introductions could provide especially useful tests of a variety of evolutionary hypotheses because the environments selecting on evolving traits are still present. We review phylogenetic and contemporary studies of trait evolution and identify areas of overlap and areas for further integration. Emerging tools which can promote integration include broadly focused repositories of trait data, and comparative models of trait evolution that consider both intra and interspecific variation. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Lande-Kirkpatrick mechanism is the null model of evolution by intersexual selection: implications for meaning, honesty, and design in intersexual signals.

PubMed

Prum, Richard O

2010-11-01

The Fisher-inspired, arbitrary intersexual selection models of Lande (1981) and Kirkpatrick (1982), including both stable and unstable equilibrium conditions, provide the appropriate null model for the evolution of traits and preferences by intersexual selection. Like the Hardy–Weinberg equilibrium, the Lande–Kirkpatrick (LK) mechanism arises as an intrinsic consequence of genetic variation in trait and preference in the absence of other evolutionary forces. The LK mechanism is equivalent to other intersexual selection mechanisms in the absence of additional selection on preference and with additional trait-viability and preference-viability correlations equal to zero. The LK null model predicts the evolution of arbitrary display traits that are neither honest nor dishonest, indicate nothing other than mating availability, and lack any meaning or design other than their potential to correspond to mating preferences. The current standard for demonstrating an arbitrary trait is impossible to meet because it requires proof of the null hypothesis. The LK null model makes distinct predictions about the evolvability of traits and preferences. Examples of recent intersexual selection research document the confirmationist pitfalls of lacking a null model. Incorporation of the LK null into intersexual selection will contribute to serious examination of the extent to which natural selection on preferences shapes signals.

Personality Correlates of Aggression: Evidence from Measures of the Five-Factor Model, UPPS Model of Impulsivity, and BIS/BAS

ERIC Educational Resources Information Center

Miller, Joshua D.; Zeichner, Amos; Wilson, Lauren F.

2012-01-01

Although many studies of personality and aggression focus on multidimensional traits and higher order personality disorders (e.g., psychopathy), lower order, unidimensional traits may provide more precision in identifying specific aspects of personality that relate to aggression. The current study includes a comprehensive measurement of lower…

Genetic parameters between feed-intake-related traits and conformation in 2 separate dairy populations--the Netherlands and United States.

PubMed

Manzanilla-Pech, C I V; Veerkamp, R F; Tempelman, R J; van Pelt, M L; Weigel, K A; VandeHaar, M; Lawlor, T J; Spurlock, D M; Armentano, L E; Staples, C R; Hanigan, M; De Haas, Y

2016-01-01

To include feed-intake-related traits in the breeding goal, accurate estimates of genetic parameters of feed intake, and its correlations with other related traits (i.e., production, conformation) are required to compare different options. However, the correlations between feed intake and conformation traits can vary depending on the population. Therefore, the objective was to estimate genetic correlations between 6 feed-intake-related traits and 7 conformation traits within dairy cattle from 2 countries, the Netherlands (NL) and the United States (US). The feed-intake-related traits were dry matter intake (DMI), residual feed intake (RFI), milk energy output (MilkE), milk yield (MY), body weight (BW), and metabolic body weight (MBW). The conformation traits were stature (ST), chest width (CW), body depth (BD), angularity (ANG), rump angle (RA), rump width (RW), and body condition score (BCS). Feed intake data were available for 1,665 cows in NL and for 1,920 cows in US, from 83 nutritional experiments (48 in NL and 35 in US) conducted between 1991 and 2011 in NL and between 2007 and 2013 in US. Additional conformation records from relatives of the animals with DMI records were added to the database, giving a total of 37,241 cows in NL and 28,809 in US with conformation trait information. Genetic parameters were estimated using bivariate animal model analyses. The model included the following fixed effects for feed-intake-related traits: location by experiment-ration, age of cow at calving modeled with a second order polynomial by parity class, location by year-season, and days in milk, and these fixed effects for the conformation traits: herd by classification date, age of cow at classification, and lactation stage at classification. Both models included additive genetic and residual random effects. The highest estimated genetic correlations involving DMI were with CW in both countries (NL=0.45 and US=0.61), followed by ST (NL=0.33 and US=0.57), BD (NL=0.26 and US=0.49), and BCS (NL=0.24 and US=0.46). The MilkE and MY were moderately correlated with ANG in both countries (0.33 and 0.47 in NL, and 0.36 and 0.48 in US). Finally, BW was highly correlated with CW (0.77 in NL and 0.84 in US) and with BCS (0.83 in NL and 0.85 in US). Feed-intake-related traits were moderately to highly genetically correlated with conformation traits (ST, CW, BD, and BCS) in both countries, making them potentially useful as predictors of DMI. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Conscientiousness and obsessive-compulsive personality disorder.

PubMed

Samuel, Douglas B; Widiger, Thomas A

2011-07-01

A dimensional perspective on personality disorder hypothesizes that the current diagnostic categories represent maladaptive variants of general personality traits. However, a fundamental foundation of this viewpoint is that dimensional models can adequately account for the pathology currently described by these categories. While most of the personality disorders have well established links to dimensional models that buttress this hypothesis, obsessive-compulsive personality disorder (OCPD) has obtained only inconsistent support. The current study administered multiple measures of 1) conscientiousness-related personality traits, 2) DSM-IV OCPD, and 3) specific components of OCPD (e.g., compulsivity and perfectionism) to a sample of 536 undergraduates who were oversampled for elevated OCPD scores. Six existing measures of conscientiousness-related personality traits converged strongly with each other supporting their assessment of a common trait. These measures of conscientiousness correlated highly with scales assessing specific components of OCPD, but obtained variable relationships with measures of DSM-IV OCPD. More specifically, there were differences within the conscientiousness instruments such that those designed to assess general personality functioning had small to medium relationships with OCPD, but those assessing more maladaptive variants obtained large effect sizes. These findings support the view that OCPD does represent a maladaptive variant of normal-range conscientiousness.

Climatic drivers of leaf traits and genetic divergence in the tree Annona crassiflora: a broad spatial survey in the Brazilian savannas.

PubMed

Ribeiro, Priciane C; Souza, Matheus L; Muller, Larissa A C; Ellis, Vincenzo A; Heuertz, Myriam; Lemos-Filho, José P; Lovato, Maria Bernadete

2016-11-01

The Cerrado is the largest South American savanna and encompasses substantial species diversity and environmental variation. Nevertheless, little is known regarding the influence of the environment on population divergence of Cerrado species. Here, we searched for climatic drivers of genetic (nuclear microsatellites) and leaf trait divergence in Annona crassiflora, a widespread tree in the Cerrado. The sampling encompassed all phytogeographic provinces of the continuous area of the Cerrado and included 397 individuals belonging to 21 populations. Populations showed substantial genetic and leaf trait divergence across the species' range. Our data revealed three spatially defined genetic groups (eastern, western and southern) and two morphologically distinct groups (eastern and western only). The east-west split in both the morphological and genetic data closely mirrors previously described phylogeographic patterns of Cerrado species. Generalized linear mixed effects models and multiple regression analyses revealed several climatic factors associated with both genetic and leaf trait divergence among populations of A. crassiflora. Isolation by environment (IBE) was mainly due to temperature seasonality and precipitation of the warmest quarter. Populations that experienced lower precipitation summers and hotter winters had heavier leaves and lower specific leaf area. The southwestern area of the Cerrado had the highest genetic diversity of A. crassiflora, suggesting that this region may have been climatically stable. Overall, we demonstrate that a combination of current climate and past climatic changes have shaped the population divergence and spatial structure of A. crassiflora. However, the genetic structure of A. crassiflora reflects the biogeographic history of the species more strongly than leaf traits, which are more related to current climate. © 2016 John Wiley & Sons Ltd.

The effects of trait and state affect on diurnal cortisol slope among children affected by parental HIV/AIDS in rural China.

PubMed

Chen, Lihua; Chi, Peilian; Li, Xiaoming; Zilioli, Samuele; Zhao, Junfeng; Zhao, Guoxiang; Lin, Danhua

2017-08-01

Affect is believed to be one of the most prominent proximal psychological pathway through which more distal psychosocial factors influence physiology and ultimately health. The current study examines the relative contributions of trait affect and state affect to the hypothalamic-pituitary-adrenal axis activity, with particular focus on cortisol slope, in children affected by parental HIV/AIDS. A sample of 645 children (8-15 years old) affected by parental HIV/AIDS in rural China completed a multiple-day naturalistic salivary cortisol protocol. Trait and state affect, demographics, and psychosocial covariates were assessed via self-report. Hierarchical linear modeling was used for estimating the effects of trait affect and state affect on cortisol slope. Confidence intervals for indirect effects were estimated using the Monte Carlo method. Our results indicated that both trait and state negative affect (NA) predicted flatter (less "healthy") diurnal cortisol slopes. Subsequent analyses revealed that children's state NA mediated the effect of their trait NA on diurnal cortisol slope. The same relationships did not emerge for trait and state positive affect. These findings provide a rationale for future interventions that target NA as a modifiable antecedent of compromised health-related endocrine processes among children affected by parental HIV/AIDS.

A reciprocal model of face recognition and autistic traits: evidence from an individual differences perspective.

PubMed

Halliday, Drew W R; MacDonald, Stuart W S; Scherf, K Suzanne; Sherf, Suzanne K; Tanaka, James W

2014-01-01

Although not a core symptom of the disorder, individuals with autism often exhibit selective impairments in their face processing abilities. Importantly, the reciprocal connection between autistic traits and face perception has rarely been examined within the typically developing population. In this study, university participants from the social sciences, physical sciences, and humanities completed a battery of measures that assessed face, object and emotion recognition abilities, general perceptual-cognitive style, and sub-clinical autistic traits (the Autism Quotient (AQ)). We employed separate hierarchical multiple regression analyses to evaluate which factors could predict face recognition scores and AQ scores. Gender, object recognition performance, and AQ scores predicted face recognition behaviour. Specifically, males, individuals with more autistic traits, and those with lower object recognition scores performed more poorly on the face recognition test. Conversely, university major, gender and face recognition performance reliably predicted AQ scores. Science majors, males, and individuals with poor face recognition skills showed more autistic-like traits. These results suggest that the broader autism phenotype is associated with lower face recognition abilities, even among typically developing individuals.

A Reciprocal Model of Face Recognition and Autistic Traits: Evidence from an Individual Differences Perspective

PubMed Central

Halliday, Drew W. R.; MacDonald, Stuart W. S.; Sherf, Suzanne K.; Tanaka, James W.

2014-01-01

Although not a core symptom of the disorder, individuals with autism often exhibit selective impairments in their face processing abilities. Importantly, the reciprocal connection between autistic traits and face perception has rarely been examined within the typically developing population. In this study, university participants from the social sciences, physical sciences, and humanities completed a battery of measures that assessed face, object and emotion recognition abilities, general perceptual-cognitive style, and sub-clinical autistic traits (the Autism Quotient (AQ)). We employed separate hierarchical multiple regression analyses to evaluate which factors could predict face recognition scores and AQ scores. Gender, object recognition performance, and AQ scores predicted face recognition behaviour. Specifically, males, individuals with more autistic traits, and those with lower object recognition scores performed more poorly on the face recognition test. Conversely, university major, gender and face recognition performance reliably predicted AQ scores. Science majors, males, and individuals with poor face recognition skills showed more autistic-like traits. These results suggest that the broader autism phenotype is associated with lower face recognition abilities, even among typically developing individuals. PMID:24853862

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

PubMed

Thoen, Manus P M; Davila Olivas, Nelson H; Kloth, Karen J; Coolen, Silvia; Huang, Ping-Ping; Aarts, Mark G M; Bac-Molenaar, Johanna A; Bakker, Jaap; Bouwmeester, Harro J; Broekgaarden, Colette; Bucher, Johan; Busscher-Lange, Jacqueline; Cheng, Xi; Fradin, Emilie F; Jongsma, Maarten A; Julkowska, Magdalena M; Keurentjes, Joost J B; Ligterink, Wilco; Pieterse, Corné M J; Ruyter-Spira, Carolien; Smant, Geert; Testerink, Christa; Usadel, Björn; van Loon, Joop J A; van Pelt, Johan A; van Schaik, Casper C; van Wees, Saskia C M; Visser, Richard G F; Voorrips, Roeland; Vosman, Ben; Vreugdenhil, Dick; Warmerdam, Sonja; Wiegers, Gerrie L; van Heerwaarden, Joost; Kruijer, Willem; van Eeuwijk, Fred A; Dicke, Marcel

2017-02-01

Plants are exposed to combinations of various biotic and abiotic stresses, but stress responses are usually investigated for single stresses only. Here, we investigated the genetic architecture underlying plant responses to 11 single stresses and several of their combinations by phenotyping 350 Arabidopsis thaliana accessions. A set of 214 000 single nucleotide polymorphisms (SNPs) was screened for marker-trait associations in genome-wide association (GWA) analyses using tailored multi-trait mixed models. Stress responses that share phytohormonal signaling pathways also share genetic architecture underlying these responses. After removing the effects of general robustness, for the 30 most significant SNPs, average quantitative trait locus (QTL) effect sizes were larger for dual stresses than for single stresses. Plants appear to deploy broad-spectrum defensive mechanisms influencing multiple traits in response to combined stresses. Association analyses identified QTLs with contrasting and with similar responses to biotic vs abiotic stresses, and below-ground vs above-ground stresses. Our approach allowed for an unprecedented comprehensive genetic analysis of how plants deal with a wide spectrum of stress conditions. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

The Multiple Relations between Creativity and Personality

ERIC Educational Resources Information Center

Chávez-Eakle, Rosa Aurora; Eakle, A. Jonathan; Cruz-Fuentes, Carlos

2012-01-01

The aims of this article are to review the multiple relations between creativity and personality, exploring the measurement instruments that have been used to identify them. Specific personality characteristics and traits found in highly creative individuals and the interaction of these traits with the creative process are described. In addition,…

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.

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

Adaptive Horizontal Gene Transfers between Multiple Cheese-Associated Fungi.

PubMed

Ropars, Jeanne; Rodríguez de la Vega, Ricardo C; López-Villavicencio, Manuela; Gouzy, Jérôme; Sallet, Erika; Dumas, Émilie; Lacoste, Sandrine; Debuchy, Robert; Dupont, Joëlle; Branca, Antoine; Giraud, Tatiana

2015-10-05

Domestication is an excellent model for studies of adaptation because it involves recent and strong selection on a few, identified traits [1-5]. Few studies have focused on the domestication of fungi, with notable exceptions [6-11], despite their importance to bioindustry [12] and to a general understanding of adaptation in eukaryotes [5]. Penicillium fungi are ubiquitous molds among which two distantly related species have been independently selected for cheese making-P. roqueforti for blue cheeses like Roquefort and P. camemberti for soft cheeses like Camembert. The selected traits include morphology, aromatic profile, lipolytic and proteolytic activities, and ability to grow at low temperatures, in a matrix containing bacterial and fungal competitors [13-15]. By comparing the genomes of ten Penicillium species, we show that adaptation to cheese was associated with multiple recent horizontal transfers of large genomic regions carrying crucial metabolic genes. We identified seven horizontally transferred regions (HTRs) spanning more than 10 kb each, flanked by specific transposable elements, and displaying nearly 100% identity between distant Penicillium species. Two HTRs carried genes with functions involved in the utilization of cheese nutrients or competition and were found nearly identical in multiple strains and species of cheese-associated Penicillium fungi, indicating recent selective sweeps; they were experimentally associated with faster growth and greater competitiveness on cheese and contained genes highly expressed in the early stage of cheese maturation. These findings have industrial and food safety implications and improve our understanding of the processes of adaptation to rapid environmental changes. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Adaptive Horizontal Gene Transfers between Multiple Cheese-Associated Fungi

PubMed Central

Ropars, Jeanne; Rodríguez de la Vega, Ricardo C.; López-Villavicencio, Manuela; Gouzy, Jérôme; Sallet, Erika; Dumas, Émilie; Lacoste, Sandrine; Debuchy, Robert; Dupont, Joëlle; Branca, Antoine; Giraud, Tatiana

2015-01-01

Summary Domestication is an excellent model for studies of adaptation because it involves recent and strong selection on a few, identified traits [1–5]. Few studies have focused on the domestication of fungi, with notable exceptions [6–11], despite their importance to bioindustry [12] and to a general understanding of adaptation in eukaryotes [5]. Penicillium fungi are ubiquitous molds among which two distantly related species have been independently selected for cheese making—P. roqueforti for blue cheeses like Roquefort and P. camemberti for soft cheeses like Camembert. The selected traits include morphology, aromatic profile, lipolytic and proteolytic activities, and ability to grow at low temperatures, in a matrix containing bacterial and fungal competitors [13–15]. By comparing the genomes of ten Penicillium species, we show that adaptation to cheese was associated with multiple recent horizontal transfers of large genomic regions carrying crucial metabolic genes. We identified seven horizontally transferred regions (HTRs) spanning more than 10 kb each, flanked by specific transposable elements, and displaying nearly 100% identity between distant Penicillium species. Two HTRs carried genes with functions involved in the utilization of cheese nutrients or competition and were found nearly identical in multiple strains and species of cheese-associated Penicillium fungi, indicating recent selective sweeps; they were experimentally associated with faster growth and greater competitiveness on cheese and contained genes highly expressed in the early stage of cheese maturation. These findings have industrial and food safety implications and improve our understanding of the processes of adaptation to rapid environmental changes. PMID:26412136

Profiling pathological narcissism according to DSM-5 domains and traits: A study on consecutively admitted Italian psychotherapy patients.

PubMed

Fossati, Andrea; Somma, Antonella; Borroni, Serena; Pincus, Aaron L; Markon, Kristian E; Krueger, Robert F

2017-11-01

[Correction Notice: An Erratum for this article was reported in Vol 29(11) of Psychological Assessment (see record 2016-56886-001). In the article, several values were reversed and the mean was misreported in Table 2. The corrected table is present in the erratum.] Pathological narcissism represents a clinically relevant, albeit controversial personality construct, with multiple conceptualizations that are operationalized by different measures. Even in the recently published Diagnostic and Statistical Manual for Mental Disorders-Fifth Edition (DSM-5), 2 different views of narcissistic personality disorder (NPD) are formulated (i.e., Section II and Section III). The DSM-5 Section III alternative PD model diagnosis of NPD is based on self and interpersonal dysfunction (Criterion A) and a profile of maladaptive personality traits (Criterion B), specifically elevated scores on Attention Seeking and Grandiosity. Given the diversity of conceptualizations of pathological narcissism, we evaluated the convergences and divergences in DSM-5 trait profiles characterizing multiple measures of narcissism in a clinical sample of 278 consecutively admitted Italian psychotherapy patients. Patients were administered the Italian versions of the Personality Inventory for DSM-5 (PID-5) and 4 measures of NPD, (a) the Narcissistic Personality Inventory (NPI); (b) the NPD scale of the Personality Diagnostic Questionnaire-4+; (c) the Structured Clinical Interview for Axis II Personality Disorders, Version 2.0 (SCID-II) as an observer-rated measure of NPD; and (d) the Pathological Narcissism Inventory (PNI). Multiple regression analyses showed that PID-5 traits explained from 13% to more than 60% of the variance in the different NPD measures. Attention Seeking was consistently associated with all measures of NPD, whereas Grandiosity was associated with some of the NPD measures. All measures of NPD were also significantly related to additional DSM-5 maladaptive traits. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Juvenile hormone mediates developmental integration between exaggerated traits and supportive traits in the horned flour beetle Gnatocerus cornutus.

PubMed

Okada, Yasukazu; Gotoh, Hiroki; Miura, Toru; Miyatake, Takahisa; Okada, Kensuke

2012-07-01

Sexually selected exaggerated traits are often coupled with modifications in other nontarget traits. In insects with weapons, enlargements of nontarget characters that functionally support the weapon often occur (i.e. supportive traits). The support of sexual traits requires developmental coordination among functionally related multiple traits-an explicit example of morphological integration. The genetic theory predicts that developmental integration among different body modules, for which development is regulated via different sets of genes, is likely to be coordinated by pleiotropic factors. However, the developmental backgrounds of morphological integrations are largely unknown. We tested the hypothesis that the juvenile hormone (JH), as a pleiotropic factor, mediates the integration between exaggerated and supportive traits in an armed beetle Gnatocerus cornutus. During combat, males of this beetle use exaggerated mandibles to lift up their opponents with the supportive traits, that is, the head and prothoracic body parts. Application of methoprene, a JH analog (JHA), during the larval to prepupal period, induced the formation of large mandibles relative to the body sizes in males. Morphometric examination of nontarget traits elucidated an increase in the relative sizes of supportive traits, including the head and prothoracic body parts. In addition, reductions in the hind wing area and elytra length, which correspond to flight and reproductive abilities, were detected. Our findings are consistent with the genetic theory and support the idea that JH is a key pleiotropic factor that coordinates the developmental integration of exaggerated traits and supportive characters, as well as resource allocation trade-offs. © 2012 Wiley Periodicals, Inc.

Are there differential relationships between different types of childhood maltreatment and different types of adult personality pathology?

PubMed

Cohen, Lisa Janet; Tanis, Thachell; Bhattacharjee, Reetuparna; Nesci, Christina; Halmi, Winter; Galynker, Igor

2014-01-30

While considerable data support the relationship between childhood trauma and adult personality pathology in general, there is little research investigating the specific relationships between different types of childhood maltreatment and adult personality disorders. The present study tested a model incorporating five a priori hypotheses regarding the association between distinct forms of childhood maltreatment and personality pathology in 231 psychiatric patients using multiple self-report measures (Personality Diagnostic Questionnaire-4th Edition, Child Trauma Questionnaire, Conflict in Tactics Scale Parent-Child Child-Adult, and Multidimensional Neglectful Behavior Scale). Step-wise linear regressions supported three out of five hypotheses, suggesting independent relationships between: physical abuse and antisocial personality disorder traits; emotional abuse and Cluster C personality disorder traits; and maternal neglect and Cluster A personality disorder traits after controlling for co-occurring maltreatment types and personality disorder traits. Results did not support an independent relationship between sexual abuse and borderline personality traits nor between emotional abuse and narcissistic personality disorder traits. Additionally, there were three unexpected findings: physical abuse was independently and positively associated with narcissistic and paranoid traits and negatively associated with Cluster C traits. These findings can help refine our understanding of adult personality pathology and support the future development of clinical tools for survivors of childhood maltreatment. © 2013 Published by Elsevier Ireland Ltd.

CITRATE 1.0: Phytoplankton continuous trait-distribution model with one-dimensional physical transport applied to the North Pacific

NASA Astrophysics Data System (ADS)

Chen, Bingzhang; Smith, Sherwood Lan

2018-02-01

Diversity plays critical roles in ecosystem functioning, but it remains challenging to model phytoplankton diversity in order to better understand those roles and reproduce consistently observed diversity patterns in the ocean. In contrast to the typical approach of resolving distinct species or functional groups, we present a ContInuous TRAiT-basEd phytoplankton model (CITRATE) that focuses on macroscopic system properties such as total biomass, mean trait values, and trait variance. This phytoplankton component is embedded within a nitrogen-phytoplankton-zooplankton-detritus-iron model that itself is coupled with a simplified one-dimensional ocean model. Size is used as the master trait for phytoplankton. CITRATE also incorporates trait diffusion for sustaining diversity and simple representations of physiological acclimation, i.e., flexible chlorophyll-to-carbon and nitrogen-to-carbon ratios. We have implemented CITRATE at two contrasting stations in the North Pacific where several years of observational data are available. The model is driven by physical forcing including vertical eddy diffusivity imported from three-dimensional general ocean circulation models (GCMs). One common set of model parameters for the two stations is optimized using the Delayed-Rejection Adaptive Metropolis-Hasting Monte Carlo (DRAM) algorithm. The model faithfully reproduces most of the observed patterns and gives robust predictions on phytoplankton mean size and size diversity. CITRATE is suitable for applications in GCMs and constitutes a prototype upon which more sophisticated continuous trait-based models can be developed.

Trait inferences in goal-directed behavior: ERP timing and localization under spontaneous and intentional processing

PubMed Central

Van den Eede, Sofie; Baetens, Kris; Vandekerckhove, Marie

2009-01-01

This study measured event-related potentials (ERPs) during multiple goal and trait inferences, under spontaneous or intentional instructions. Participants read sentences describing several goal-implying behaviors of a target person from which also a strong trait could be inferred or not. The last word of each sentence determined the consistency with the inference induced during preceding sentences. In comparison with behaviors that implied only a goal, stronger waveforms beginning at ∼150 ms were obtained when the behaviors additionally implied a trait. These ERPs showed considerable parallels between spontaneous and intentional inferences. This suggests that traits embedded in a stream of goal-directed behaviors were detected more rapidly and automatically than mere goals, irrespective of the participants’ spontaneous or intentional instructions. In line with this, source localization (LORETA) of the ERPs show predominantly activation in the temporo-parietal junction (TPJ) during 150–200 ms, suggesting that goals were detected at that time interval. During 200–300 ms, activation was stronger at the medial prefrontal cortex (mPFC) for multiple goals and traits as opposed to goals only, suggesting that traits were inferred during this time window. A cued recall measure taken after the presentation of the stimulus material support the occurrence of goal and trait inferences and shows significant correlations with the neural components, indicating that these components are valid neural indices of spontaneous and intentional social inferences. The early detection of multiple goal and trait inferences is explained in terms of their greater social relevance, leading to privileged attention allocation and processing in the brain. PMID:19270041

How Do DSM-5 Personality Traits Align With Schema Therapy Constructs?

PubMed

Bach, Bo; Lee, Christopher; Mortensen, Erik Lykke; Simonsen, Erik

2016-08-01

DSM-5 offers an alternative model of personality pathology that includes 25 traits. Although personality disorders are mostly treated with psychotherapy, the correspondence between DSM-5 traits and concepts in evidence-based psychotherapy has not yet been evaluated adequately. Suitably, schema therapy was developed for treating personality disorders, and it has achieved promising evidence. The authors examined associations between DSM-5 traits and schema therapy constructs in a mixed sample of 662 adults, including 312 clinical participants. Associations were investigated in terms of factor loadings and regression coefficients in relation to five domains, followed by specific correlations among all constructs. The results indicated conceptually coherent associations, and 15 of 25 traits were strongly related to relevant schema therapy constructs. Conclusively, DSM-5 traits may be considered expressions of schema therapy constructs, which psychotherapists might take advantage of in terms of case formulation and targets of treatment. In turn, schema therapy constructs add theoretical understanding to DSM-5 traits.

Five-Factor Model of Personality and Organizational Commitment: The Mediating Role of Positive and Negative Affective States

ERIC Educational Resources Information Center

Panaccio, Alexandra; Vandenberghe, Christian

2012-01-01

Using a one-year longitudinal study of four components of organizational commitment (affective, normative, continuance-sacrifices, and continuance-alternatives) on a sample of employees from multiple organizations (N=220), we examined the relationships of employee Big-Five personality traits to employee commitment components, and the mediating…

Adaptive variation in Pinus ponderosa from Intermountain regions. II. Middle Columbia River system

Treesearch

Gerald Rehfeldt

1986-01-01

Seedling populations were grown and compared in common environments. Statistical analyses detected genetic differences between populations for numerous traits reflecting growth potential and periodicity of shoot elongation. Multiple regression models described an adaptive landscape in which populations from low elevations have a high growth potential while those from...

Temperament and Attention Deficit Hyperactivity Disorder: The Development of a Multiple Pathway Model

ERIC Educational Resources Information Center

Nigg, Joel T.; Goldsmith, H. Hill; Sachek, Jennifer

2004-01-01

This article outlines the parallels between major theories of attention deficit hyperactivity disorder (ADHD) and relevant temperament domains, summarizing recent research from our laboratories on (a) child temperament and (b) adult personality traits related to ADHD symptoms. These data are convergent in suggesting a role of effortful control and…

Simulation-based Bayesian inference for latent traits of item response models: Introduction to the ltbayes package for R.

PubMed

Johnson, Timothy R; Kuhn, Kristine M

2015-12-01

This paper introduces the ltbayes package for R. This package includes a suite of functions for investigating the posterior distribution of latent traits of item response models. These include functions for simulating realizations from the posterior distribution, profiling the posterior density or likelihood function, calculation of posterior modes or means, Fisher information functions and observed information, and profile likelihood confidence intervals. Inferences can be based on individual response patterns or sets of response patterns such as sum scores. Functions are included for several common binary and polytomous item response models, but the package can also be used with user-specified models. This paper introduces some background and motivation for the package, and includes several detailed examples of its use.

QTLs for heading date and plant height under multiple environments in rice.

PubMed

Han, Zhongmin; Hu, Wei; Tan, Cong; Xing, Yongzhong

2017-02-01

Both heading date and plant height are important traits related to grain yield in rice. In this study, a recombinant inbred lines (RILs) population was used to map quantitative trait loci (QTLs) for both traits under 3 long-day (LD) environments and 1 short-day (SD) environment. A total of eight QTLs for heading date and three QTLs for plant height were detected by composite interval mapping under LD conditions. Additional one QTL for heading date and three QTLs for plant height were identified by Two-QTL model under LD conditions. Among them, major QTLs qHd7.1, qHd7.2 and qHd8 for heading date, and qPh1 and qPh7.1 for plant height were commonly detected. qHd7.1 and qHd7.2 were mapped to small regions of less than 1 cM. Genome position comparison of previously cloned genes with QTLs detected in this study revealed that qHd5 and qPh3.1 were two novel QTLs. The alleles of these QTLs increasing trait values were dispersed in both parents, which well explained the transgressive segregation observed in this population. In addition, the interaction between qHd7.1 and qHd8 was detected under all LD conditions. Multiple-QTL model analysis revealed that all QTLs and their interactions explained over 80% of heading date variation and 50% of plant height variation. Two heading date QTLs were detected under SD condition. Of them, qHd10 were commonly identified under LD condition. The difference in QTL detection between LD and SD conditions indicated most heading date QTLs are sensitive to photoperiod. These findings will benefit breeding design for heading date and plant height in rice.

Partially incorrect fossil data augment analyses of discrete trait evolution in living species.

PubMed

Puttick, Mark N

2016-08-01

Ancestral state reconstruction of discrete character traits is often vital when attempting to understand the origins and homology of traits in living species. The addition of fossils has been shown to alter our understanding of trait evolution in extant taxa, but researchers may avoid using fossils alongside extant species if only few are known, or if the designation of the trait of interest is uncertain. Here, I investigate the impacts of fossils and incorrectly coded fossils in the ancestral state reconstruction of discrete morphological characters under a likelihood model. Under simulated phylogenies and data, likelihood-based models are generally accurate when estimating ancestral node values. Analyses with combined fossil and extant data always outperform analyses with extant species alone, even when around one quarter of the fossil information is incorrect. These results are especially pronounced when model assumptions are violated, such as when there is a trend away from the root value. Fossil data are of particular importance when attempting to estimate the root node character state. Attempts should be made to include fossils in analysis of discrete traits under likelihood, even if there is uncertainty in the fossil trait data. © 2016 The Authors.