Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm

PubMed Central

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene × gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene × gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms. PMID:18466570

Functional traits determine formation of mutualism and predation interactions in seed-rodent dispersal system of a subtropical forest

NASA Astrophysics Data System (ADS)

Chang, Gang; Zhang, Zhibin

2014-02-01

Network structure in plant-animal systems has been widely investigated but the roles of functional traits of plants and animals in formation of mutualism and predation interactions and community structure are still not fully understood. In this study, we quantitatively assessed interaction strength of mutualism and predation between 5 tree species and 7 rodent species by using semi-natural enclosures in a subtropical forest in southwest China. Seeds with high handling-time and nutrition traits (for both rat and mouse species) or high tannin trait (for mouse species) show high mutualism but low predation with rodents; while seeds with low handling-time and low nutrition traits show high predation but low mutualism with rodents. Large-sized rat species are more linked to seeds with high handling-time and high nutrition traits, while small-sized mouse species are more connected with seeds with low handling-time, low nutrition value and high tannin traits. Anti-predation seed traits tend to increase chance of mutualism instead of reducing predation by rodents, suggesting formation of mutualism may be connected with that of predation. Our study demonstrates that seed and animal traits play significant roles in the formation of mutualism and predation and network structure of the seed-rodent dispersal system.

Quantitative genetic methods depending on the nature of the phenotypic trait.

PubMed

de Villemereuil, Pierre

2018-01-24

A consequence of the assumptions of the infinitesimal model, one of the most important theoretical foundations of quantitative genetics, is that phenotypic traits are predicted to be most often normally distributed (so-called Gaussian traits). But phenotypic traits, especially those interesting for evolutionary biology, might be shaped according to very diverse distributions. Here, I show how quantitative genetics tools have been extended to account for a wider diversity of phenotypic traits using first the threshold model and then more recently using generalized linear mixed models. I explore the assumptions behind these models and how they can be used to study the genetics of non-Gaussian complex traits. I also comment on three recent methodological advances in quantitative genetics that widen our ability to study new kinds of traits: the use of "modular" hierarchical modeling (e.g., to study survival in the context of capture-recapture approaches for wild populations); the use of aster models to study a set of traits with conditional relationships (e.g., life-history traits); and, finally, the study of high-dimensional traits, such as gene expression. © 2018 New York Academy of Sciences.

Genetic interactions contribute less than additive effects to quantitative trait variation in yeast

PubMed Central

Bloom, Joshua S.; Kotenko, Iulia; Sadhu, Meru J.; Treusch, Sebastian; Albert, Frank W.; Kruglyak, Leonid

2015-01-01

Genetic mapping studies of quantitative traits typically focus on detecting loci that contribute additively to trait variation. Genetic interactions are often proposed as a contributing factor to trait variation, but the relative contribution of interactions to trait variation is a subject of debate. Here we use a very large cross between two yeast strains to accurately estimate the fraction of phenotypic variance due to pairwise QTL–QTL interactions for 20 quantitative traits. We find that this fraction is 9% on average, substantially less than the contribution of additive QTL (43%). Statistically significant QTL–QTL pairs typically have small individual effect sizes, but collectively explain 40% of the pairwise interaction variance. We show that pairwise interaction variance is largely explained by pairs of loci at least one of which has a significant additive effect. These results refine our understanding of the genetic architecture of quantitative traits and help guide future mapping studies. PMID:26537231

Identification of quantitative trait loci (QTL) for fruit quality traits and number of weeks of flowering in the cultivated strawberry

USDA-ARS?s Scientific Manuscript database

Fruit quality traits and dayneutrality are two major foci of several strawberry breeding programs. The identification of quantitative trait loci (QTL) and molecular markers linked to these traits could improve breeding efficiency. In this work, an F1 population derived from the cross ‘Delmarvel’ × ...

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.

Determination of quantitative trait variants by concordance via application of the a posteriori granddaughter design to the U.S. Holstein population

USDA-ARS?s Scientific Manuscript database

Experimental designs that exploit family information can provide substantial predictive power in quantitative trait variant discovery projects. Concordance between quantitative trait locus genotype as determined by the a posteriori granddaughter design and marker genotype was determined for 29 trai...

Classification of cassava genotypes based on qualitative and quantitative data.

PubMed

Oliveira, E J; Oliveira Filho, O S; Santos, V S

2015-02-02

We evaluated the genetic variation of cassava accessions based on qualitative (binomial and multicategorical) and quantitative traits (continuous). We characterized 95 accessions obtained from the Cassava Germplasm Bank of Embrapa Mandioca e Fruticultura; we evaluated these accessions for 13 continuous, 10 binary, and 25 multicategorical traits. First, we analyzed the accessions based only on quantitative traits; next, we conducted joint analysis (qualitative and quantitative traits) based on the Ward-MLM method, which performs clustering in two stages. According to the pseudo-F, pseudo-t2, and maximum likelihood criteria, we identified five and four groups based on quantitative trait and joint analysis, respectively. The smaller number of groups identified based on joint analysis may be related to the nature of the data. On the other hand, quantitative data are more subject to environmental effects in the phenotype expression; this results in the absence of genetic differences, thereby contributing to greater differentiation among accessions. For most of the accessions, the maximum probability of classification was >0.90, independent of the trait analyzed, indicating a good fit of the clustering method. Differences in clustering according to the type of data implied that analysis of quantitative and qualitative traits in cassava germplasm might explore different genomic regions. On the other hand, when joint analysis was used, the means and ranges of genetic distances were high, indicating that the Ward-MLM method is very useful for clustering genotypes when there are several phenotypic traits, such as in the case of genetic resources and breeding programs.

Bayesian B-spline mapping for dynamic quantitative traits.

PubMed

Xing, Jun; Li, Jiahan; Yang, Runqing; Zhou, Xiaojing; Xu, Shizhong

2012-04-01

Owing to their ability and flexibility to describe individual gene expression at different time points, random regression (RR) analyses have become a popular procedure for the genetic analysis of dynamic traits whose phenotypes are collected over time. Specifically, when modelling the dynamic patterns of gene expressions in the RR framework, B-splines have been proved successful as an alternative to orthogonal polynomials. In the so-called Bayesian B-spline quantitative trait locus (QTL) mapping, B-splines are used to characterize the patterns of QTL effects and individual-specific time-dependent environmental errors over time, and the Bayesian shrinkage estimation method is employed to estimate model parameters. Extensive simulations demonstrate that (1) in terms of statistical power, Bayesian B-spline mapping outperforms the interval mapping based on the maximum likelihood; (2) for the simulated dataset with complicated growth curve simulated by B-splines, Legendre polynomial-based Bayesian mapping is not capable of identifying the designed QTLs accurately, even when higher-order Legendre polynomials are considered and (3) for the simulated dataset using Legendre polynomials, the Bayesian B-spline mapping can find the same QTLs as those identified by Legendre polynomial analysis. All simulation results support the necessity and flexibility of B-spline in Bayesian mapping of dynamic traits. The proposed method is also applied to a real dataset, where QTLs controlling the growth trajectory of stem diameters in Populus are located.

Analysis of Sequence Data Under Multivariate Trait-Dependent Sampling.

PubMed

Tao, Ran; Zeng, Donglin; Franceschini, Nora; North, Kari E; Boerwinkle, Eric; Lin, Dan-Yu

2015-06-01

High-throughput DNA sequencing allows for the genotyping of common and rare variants for genetic association studies. At the present time and for the foreseeable future, it is not economically feasible to sequence all individuals in a large cohort. A cost-effective strategy is to sequence those individuals with extreme values of a quantitative trait. We consider the design under which the sampling depends on multiple quantitative traits. Under such trait-dependent sampling, standard linear regression analysis can result in bias of parameter estimation, inflation of type I error, and loss of power. We construct a likelihood function that properly reflects the sampling mechanism and utilizes all available data. We implement a computationally efficient EM algorithm and establish the theoretical properties of the resulting maximum likelihood estimators. Our methods can be used to perform separate inference on each trait or simultaneous inference on multiple traits. We pay special attention to gene-level association tests for rare variants. We demonstrate the superiority of the proposed methods over standard linear regression through extensive simulation studies. We provide applications to the Cohorts for Heart and Aging Research in Genomic Epidemiology Targeted Sequencing Study and the National Heart, Lung, and Blood Institute Exome Sequencing Project.

Adaptive Differentiation of Quantitative Traits in the Globally Distributed Weed, Wild Radish (Raphanus raphanistrum)

PubMed Central

Sahli, Heather F.; Conner, Jeffrey K.; Shaw, Frank H.; Howe, Stephen; Lale, Allison

2008-01-01

Weedy species with wide geographical distributions may face strong selection to adapt to new environments, which can lead to adaptive genetic differentiation among populations. However, genetic drift, particularly due to founder effects, will also commonly result in differentiation in colonizing species. To test whether selection has contributed to trait divergence, we compared differentiation at eight microsatellite loci (measured as FST) to differentiation of quantitative floral and phenological traits (measured as QST) of wild radish (Raphanus raphanistrum) across populations from three continents. We sampled eight populations: seven naturalized populations and one from its native range. By comparing estimates of QST and FST, we found that petal size was the only floral trait that may have diverged more than expected due to drift alone, but inflorescence height, flowering time, and rosette formation have greatly diverged between the native and nonnative populations. Our results suggest the loss of a rosette and the evolution of early flowering time may have been the key adaptations enabling wild radish to become a major agricultural weed. Floral adaptation to different pollinators does not seem to have been as necessary for the success of wild radish in new environments. PMID:18854585

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

Modeling development and quantitative trait mapping reveal independent genetic modules for leaf size and shape.

PubMed

Baker, Robert L; Leong, Wen Fung; Brock, Marcus T; Markelz, R J Cody; Covington, Michael F; Devisetty, Upendra K; Edwards, Christine E; Maloof, Julin; Welch, Stephen; Weinig, Cynthia

2015-10-01

Improved predictions of fitness and yield may be obtained by characterizing the genetic controls and environmental dependencies of organismal ontogeny. Elucidating the shape of growth curves may reveal novel genetic controls that single-time-point (STP) analyses do not because, in theory, infinite numbers of growth curves can result in the same final measurement. We measured leaf lengths and widths in Brassica rapa recombinant inbred lines (RILs) throughout ontogeny. We modeled leaf growth and allometry as function valued traits (FVT), and examined genetic correlations between these traits and aspects of phenology, physiology, circadian rhythms and fitness. We used RNA-seq to construct a SNP linkage map and mapped trait quantitative trait loci (QTL). We found genetic trade-offs between leaf size and growth rate FVT and uncovered differences in genotypic and QTL correlations involving FVT vs STPs. We identified leaf shape (allometry) as a genetic module independent of length and width and identified selection on FVT parameters of development. Leaf shape is associated with venation features that affect desiccation resistance. The genetic independence of leaf shape from other leaf traits may therefore enable crop optimization in leaf shape without negative effects on traits such as size, growth rate, duration or gas exchange. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

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

PubMed Central

Lorenz, Kim; Cohen, Barak A.

2012-01-01

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

A Maximum Likelihood Approach to Functional Mapping of Longitudinal Binary Traits

PubMed Central

Wang, Chenguang; Li, Hongying; Wang, Zhong; Wang, Yaqun; Wang, Ningtao; Wang, Zuoheng; Wu, Rongling

2013-01-01

Despite their importance in biology and biomedicine, genetic mapping of binary traits that change over time has not been well explored. In this article, we develop a statistical model for mapping quantitative trait loci (QTLs) that govern longitudinal responses of binary traits. The model is constructed within the maximum likelihood framework by which the association between binary responses is modeled in terms of conditional log odds-ratios. With this parameterization, the maximum likelihood estimates (MLEs) of marginal mean parameters are robust to the misspecification of time dependence. We implement an iterative procedures to obtain the MLEs of QTL genotype-specific parameters that define longitudinal binary responses. The usefulness of the model was validated by analyzing a real example in rice. Simulation studies were performed to investigate the statistical properties of the model, showing that the model has power to identify and map specific QTLs responsible for the temporal pattern of binary traits. PMID:23183762

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

PubMed Central

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

2016-01-01

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

Maternal genetic effects on adaptive divergence between anadromous and resident brook charr during early life history.

PubMed

Perry, G M L; Audet, C; Bernatchez, L

2005-09-01

The importance of directional selection relative to neutral evolution may be determined by comparing quantitative genetic variation in phenotype (Q(ST)) to variation at neutral molecular markers (F(ST)). Quantitative divergence between salmonid life history types is often considerable, but ontogenetic changes in the significance of major sources of genetic variance during post-hatch development suggest that selective differentiation varies by developmental stage. In this study, we tested the hypothesis that maternal genetic differentiation between anadromous and resident brook charr (Salvelinus fontinalis Mitchill) populations for early quantitative traits (embryonic size/growth, survival, egg number and developmental time) would be greater than neutral genetic differentiation, but that the maternal genetic basis for differentiation would be higher for pre-resorption traits than post-resorption traits. Quantitative genetic divergence between anadromous (seawater migratory) and resident Laval River (Québec) brook charr based on maternal genetic variance was high (Q(ST) > 0.4) for embryonic length, yolk sac volume, embryonic growth rate and time to first response to feeding relative to neutral genetic differentiation [F(ST) = 0.153 (0.071-0.214)], with anadromous females having positive genetic coefficients for all of the above characters. However, Q(ST) was essentially zero for all traits post-resorption of the yolk sac. Our results indicate that the observed divergence between resident and anadromous brook charr has been driven by directional selection, and may therefore be adaptive. Moreover, they provide among the first evidence that the relative importance of selective differentiation may be highly context-specific, and varies by genetic contributions to phenotype by parental sex at specific points in offspring ontogeny. This in turn suggests that interpretations of Q(ST)-F(ST) comparisons may be improved by considering the structure of quantitative genetic architecture by age category and the sex of the parent used in estimation.

Joint analysis of binary and quantitative traits with data sharing and outcome-dependent sampling.

PubMed

Zheng, Gang; Wu, Colin O; Kwak, Minjung; Jiang, Wenhua; Joo, Jungnam; Lima, Joao A C

2012-04-01

We study the analysis of a joint association between a genetic marker with both binary (case-control) and quantitative (continuous) traits, where the quantitative trait values are only available for the cases due to data sharing and outcome-dependent sampling. Data sharing becomes common in genetic association studies, and the outcome-dependent sampling is the consequence of data sharing, under which a phenotype of interest is not measured for some subgroup. The trend test (or Pearson's test) and F-test are often, respectively, used to analyze the binary and quantitative traits. Because of the outcome-dependent sampling, the usual F-test can be applied using the subgroup with the observed quantitative traits. We propose a modified F-test by also incorporating the genotype frequencies of the subgroup whose traits are not observed. Further, a combination of this modified F-test and Pearson's test is proposed by Fisher's combination of their P-values as a joint analysis. Because of the correlation of the two analyses, we propose to use a Gamma (scaled chi-squared) distribution to fit the asymptotic null distribution for the joint analysis. The proposed modified F-test and the joint analysis can also be applied to test single trait association (either binary or quantitative trait). Through simulations, we identify the situations under which the proposed tests are more powerful than the existing ones. Application to a real dataset of rheumatoid arthritis is presented. © 2012 Wiley Periodicals, Inc.

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

USDA-ARS?s Scientific Manuscript database

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

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

PubMed Central

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

2008-01-01

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

Comparison of GWAS models to identify non-additive genetic control of flowering time in sunflower hybrids.

PubMed

Bonnafous, Fanny; Fievet, Ghislain; Blanchet, Nicolas; Boniface, Marie-Claude; Carrère, Sébastien; Gouzy, Jérôme; Legrand, Ludovic; Marage, Gwenola; Bret-Mestries, Emmanuelle; Munos, Stéphane; Pouilly, Nicolas; Vincourt, Patrick; Langlade, Nicolas; Mangin, Brigitte

2018-02-01

This study compares five models of GWAS, to show the added value of non-additive modeling of allelic effects to identify genomic regions controlling flowering time of sunflower hybrids. Genome-wide association studies are a powerful and widely used tool to decipher the genetic control of complex traits. One of the main challenges for hybrid crops, such as maize or sunflower, is to model the hybrid vigor in the linear mixed models, considering the relatedness between individuals. Here, we compared two additive and three non-additive association models for their ability to identify genomic regions associated with flowering time in sunflower hybrids. A panel of 452 sunflower hybrids, corresponding to incomplete crossing between 36 male lines and 36 female lines, was phenotyped in five environments and genotyped for 2,204,423 SNPs. Intra-locus effects were estimated in multi-locus models to detect genomic regions associated with flowering time using the different models. Thirteen quantitative trait loci were identified in total, two with both model categories and one with only non-additive models. A quantitative trait loci on LG09, detected by both the additive and non-additive models, is located near a GAI homolog and is presented in detail. Overall, this study shows the added value of non-additive modeling of allelic effects for identifying genomic regions that control traits of interest and that could participate in the heterosis observed in hybrids.

Estimating the potential for adaptation of corals to climate warming.

PubMed

Császár, Nikolaus B M; Ralph, Peter J; Frankham, Richard; Berkelmans, Ray; van Oppen, Madeleine J H

2010-03-18

The persistence of tropical coral reefs is threatened by rapidly increasing climate warming, causing a functional breakdown of the obligate symbiosis between corals and their algal photosymbionts (Symbiodinium) through a process known as coral bleaching. Yet the potential of the coral-algal symbiosis to genetically adapt in an evolutionary sense to warming oceans is unknown. Using a quantitative genetics approach, we estimated the proportion of the variance in thermal tolerance traits that has a genetic basis (i.e. heritability) as a proxy for their adaptive potential in the widespread Indo-Pacific reef-building coral Acropora millepora. We chose two physiologically different populations that associate respectively with one thermo-tolerant (Symbiodinium clade D) and one less tolerant symbiont type (Symbiodinium C2). In both symbiont types, pulse amplitude modulated (PAM) fluorometry and high performance liquid chromatography (HPLC) analysis revealed significant heritabilities for traits related to both photosynthesis and photoprotective pigment profile. However, quantitative real-time polymerase chain reaction (qRT-PCR) assays showed a lack of heritability in both coral host populations for their own expression of fundamental stress genes. Coral colony growth, contributed to by both symbiotic partners, displayed heritability. High heritabilities for functional key traits of algal symbionts, along with their short clonal generation time and high population sizes allow for their rapid thermal adaptation. However, the low overall heritability of coral host traits, along with the corals' long generation time, raise concern about the timely adaptation of the coral-algal symbiosis in the face of continued rapid climate warming.

Estimating the Potential for Adaptation of Corals to Climate Warming

PubMed Central

Császár, Nikolaus B. M.; Ralph, Peter J.; Frankham, Richard; Berkelmans, Ray; van Oppen, Madeleine J. H.

2010-01-01

The persistence of tropical coral reefs is threatened by rapidly increasing climate warming, causing a functional breakdown of the obligate symbiosis between corals and their algal photosymbionts (Symbiodinium) through a process known as coral bleaching. Yet the potential of the coral-algal symbiosis to genetically adapt in an evolutionary sense to warming oceans is unknown. Using a quantitative genetics approach, we estimated the proportion of the variance in thermal tolerance traits that has a genetic basis (i.e. heritability) as a proxy for their adaptive potential in the widespread Indo-Pacific reef-building coral Acropora millepora. We chose two physiologically different populations that associate respectively with one thermo-tolerant (Symbiodinium clade D) and one less tolerant symbiont type (Symbiodinium C2). In both symbiont types, pulse amplitude modulated (PAM) fluorometry and high performance liquid chromatography (HPLC) analysis revealed significant heritabilities for traits related to both photosynthesis and photoprotective pigment profile. However, quantitative real-time polymerase chain reaction (qRT-PCR) assays showed a lack of heritability in both coral host populations for their own expression of fundamental stress genes. Coral colony growth, contributed to by both symbiotic partners, displayed heritability. High heritabilities for functional key traits of algal symbionts, along with their short clonal generation time and high population sizes allow for their rapid thermal adaptation. However, the low overall heritability of coral host traits, along with the corals' long generation time, raise concern about the timely adaptation of the coral-algal symbiosis in the face of continued rapid climate warming. PMID:20305781

Recent advancements to study flowering time in almond and other Prunus species

PubMed Central

Sánchez-Pérez, Raquel; Del Cueto, Jorge; Dicenta, Federico; Martínez-Gómez, Pedro

2014-01-01

Flowering time is an important agronomic trait in almond since it is decisive to avoid the late frosts that affect production in early flowering cultivars. Evaluation of this complex trait is a long process because of the prolonged juvenile period of trees and the influence of environmental conditions affecting gene expression year by year. Consequently, flowering time has to be studied for several years to have statistical significant results. This trait is the result of the interaction between chilling and heat requirements. Flowering time is a polygenic trait with high heritability, although a major gene Late blooming (Lb) was described in “Tardy Nonpareil.” Molecular studies at DNA level confirmed this polygenic nature identifying several genome regions (Quantitative Trait Loci, QTL) involved. Studies about regulation of gene expression are scarcer although several transcription factors have been described as responsible for flowering time. From the metabolomic point of view, the integrated analysis of the mechanisms of accumulation of cyanogenic glucosides and flowering regulation through transcription factors open new possibilities in the analysis of this complex trait in almond and in other Prunus species (apricot, cherry, peach, plum). New opportunities are arising from the integration of recent advancements including phenotypic, genetic, genomic, transcriptomic, and metabolomics studies from the beginning of dormancy until flowering. PMID:25071812

Evidences of local adaptation in quantitative traits in Prosopis alba (Leguminosae).

PubMed

Bessega, C; Pometti, C; Ewens, M; Saidman, B O; Vilardi, J C

2015-02-01

Signals of selection on quantitative traits can be detected by the comparison between the genetic differentiation of molecular (neutral) markers and quantitative traits, by multivariate extensions of the same model and by the observation of the additive covariance among relatives. We studied, by three different tests, signals of occurrence of selection in Prosopis alba populations over 15 quantitative traits: three economically important life history traits: height, basal diameter and biomass, 11 leaf morphology traits that may be related with heat-tolerance and physiological responses and spine length that is very important from silvicultural purposes. We analyzed 172 G1-generation trees growing in a common garden belonging to 32 open pollinated families from eight sampling sites in Argentina. The multivariate phenotypes differ significantly among origins, and the highest differentiation corresponded to foliar traits. Molecular genetic markers (SSR) exhibited significant differentiation and allowed us to provide convincing evidence that natural selection is responsible for the patterns of morphological differentiation. The heterogeneous selection over phenotypic traits observed suggested different optima in each population and has important implications for gene resource management. The results suggest that the adaptive significance of traits should be considered together with population provenance in breeding program as a crucial point prior to any selecting program, especially in Prosopis where the first steps are under development.

Quantitative Analysis of Cotton Canopy Size in Field Conditions Using a Consumer-Grade RGB-D Camera.

PubMed

Jiang, Yu; Li, Changying; Paterson, Andrew H; Sun, Shangpeng; Xu, Rui; Robertson, Jon

2017-01-01

Plant canopy structure can strongly affect crop functions such as yield and stress tolerance, and canopy size is an important aspect of canopy structure. Manual assessment of canopy size is laborious and imprecise, and cannot measure multi-dimensional traits such as projected leaf area and canopy volume. Field-based high throughput phenotyping systems with imaging capabilities can rapidly acquire data about plants in field conditions, making it possible to quantify and monitor plant canopy development. The goal of this study was to develop a 3D imaging approach to quantitatively analyze cotton canopy development in field conditions. A cotton field was planted with 128 plots, including four genotypes of 32 plots each. The field was scanned by GPhenoVision (a customized field-based high throughput phenotyping system) to acquire color and depth images with GPS information in 2016 covering two growth stages: canopy development, and flowering and boll development. A data processing pipeline was developed, consisting of three steps: plot point cloud reconstruction, plant canopy segmentation, and trait extraction. Plot point clouds were reconstructed using color and depth images with GPS information. In colorized point clouds, vegetation was segmented from the background using an excess-green (ExG) color filter, and cotton canopies were further separated from weeds based on height, size, and position information. Static morphological traits were extracted on each day, including univariate traits (maximum and mean canopy height and width, projected canopy area, and concave and convex volumes) and a multivariate trait (cumulative height profile). Growth rates were calculated for univariate static traits, quantifying canopy growth and development. Linear regressions were performed between the traits and fiber yield to identify the best traits and measurement time for yield prediction. The results showed that fiber yield was correlated with static traits after the canopy development stage ( R 2 = 0.35-0.71) and growth rates in early canopy development stages ( R 2 = 0.29-0.52). Multi-dimensional traits (e.g., projected canopy area and volume) outperformed one-dimensional traits, and the multivariate trait (cumulative height profile) outperformed univariate traits. The proposed approach would be useful for identification of quantitative trait loci (QTLs) controlling canopy size in genetics/genomics studies or for fiber yield prediction in breeding programs and production environments.

Detecting Genetic Interactions for Quantitative Traits Using m-Spacing Entropy Measure

PubMed Central

Yee, Jaeyong; Kwon, Min-Seok; Park, Taesung; Park, Mira

2015-01-01

A number of statistical methods for detecting gene-gene interactions have been developed in genetic association studies with binary traits. However, many phenotype measures are intrinsically quantitative and categorizing continuous traits may not always be straightforward and meaningful. Association of gene-gene interactions with an observed distribution of such phenotypes needs to be investigated directly without categorization. Information gain based on entropy measure has previously been successful in identifying genetic associations with binary traits. We extend the usefulness of this information gain by proposing a nonparametric evaluation method of conditional entropy of a quantitative phenotype associated with a given genotype. Hence, the information gain can be obtained for any phenotype distribution. Because any functional form, such as Gaussian, is not assumed for the entire distribution of a trait or a given genotype, this method is expected to be robust enough to be applied to any phenotypic association data. Here, we show its use to successfully identify the main effect, as well as the genetic interactions, associated with a quantitative trait. PMID:26339620

Germplasm-regression-combined (GRC) marker-trait association identification in plant breeding: a challenge for plant biotechnological breeding under soil water deficit conditions.

PubMed

Ruan, Cheng-Jiang; Xu, Xue-Xuan; Shao, Hong-Bo; Jaleel, Cheruth Abdul

2010-09-01

In the past 20 years, the major effort in plant breeding has changed from quantitative to molecular genetics with emphasis on quantitative trait loci (QTL) identification and marker assisted selection (MAS). However, results have been modest. This has been due to several factors including absence of tight linkage QTL, non-availability of mapping populations, and substantial time needed to develop such populations. To overcome these limitations, and as an alternative to planned populations, molecular marker-trait associations have been identified by the combination between germplasm and the regression technique. In the present preview, the authors (1) survey the successful applications of germplasm-regression-combined (GRC) molecular marker-trait association identification in plants; (2) describe how to do the GRC analysis and its differences from mapping QTL based on a linkage map reconstructed from the planned populations; (3) consider the factors that affect the GRC association identification, including selections of optimal germplasm and molecular markers and testing of identification efficiency of markers associated with traits; and (4) finally discuss the future prospects of GRC marker-trait association analysis used in plant MAS/QTL breeding programs, especially in long-juvenile woody plants when no other genetic information such as linkage maps and QTL are available.

Detection of QTL for forage yield, lodging resistance and spring vigor traits in alfalfa (Medicago sativa L.)

USDA-ARS?s Scientific Manuscript database

Alfalfa (Medicago sativa L.) is an internationally significant forage crop. Forage yield, lodging resistance and spring vigor are important agronomic traits conditioned by quantitative genetic and environmental effects. The objective of this study was to identify quantitative trait loci (QTL) and mo...

A Quantitative Study of Grit as a Predictor of Online Course Success at a Suburban Michigan Community College

ERIC Educational Resources Information Center

Climer, Steven L.

2017-01-01

The purpose of this quantitative correlational study was to examine the relationships between a student's personality traits of grit (persistence, goal-setting, passion, tenacity, time management, goal achievement, and perseverance), a student's self-reported satisfaction in the course, and the final grade a student receives in an online course.…

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

Evaluation of breeding strategies for polledness in dairy cattle using a newly developed simulation framework for quantitative and Mendelian traits.

PubMed

Scheper, Carsten; Wensch-Dorendorf, Monika; Yin, Tong; Dressel, Holger; Swalve, Herrmann; König, Sven

2016-06-29

Intensified selection of polled individuals has recently gained importance in predominantly horned dairy cattle breeds as an alternative to routine dehorning. The status quo of the current polled breeding pool of genetically-closely related artificial insemination sires with lower breeding values for performance traits raises questions regarding the effects of intensified selection based on this founder pool. We developed a stochastic simulation framework that combines the stochastic simulation software QMSim and a self-designed R program named QUALsim that acts as an external extension. Two traits were simulated in a dairy cattle population for 25 generations: one quantitative (QMSim) and one qualitative trait with Mendelian inheritance (i.e. polledness, QUALsim). The assignment scheme for qualitative trait genotypes initiated realistic initial breeding situations regarding allele frequencies, true breeding values for the quantitative trait and genetic relatedness. Intensified selection for polled cattle was achieved using an approach that weights estimated breeding values in the animal best linear unbiased prediction model for the quantitative trait depending on genotypes or phenotypes for the polled trait with a user-defined weighting factor. Selection response for the polled trait was highest in the selection scheme based on genotypes. Selection based on phenotypes led to significantly lower allele frequencies for polled. The male selection path played a significantly greater role for a fast dissemination of polled alleles compared to female selection strategies. Fixation of the polled allele implies selection based on polled genotypes among males. In comparison to a base breeding scenario that does not take polledness into account, intensive selection for polled substantially reduced genetic gain for this quantitative trait after 25 generations. Reducing selection intensity for polled males while maintaining strong selection intensity among females, simultaneously decreased losses in genetic gain and achieved a final allele frequency of 0.93 for polled. A fast transition to a completely polled population through intensified selection for polled was in contradiction to the preservation of high genetic gain for the quantitative trait. Selection on male polled genotypes with moderate weighting, and selection on female polled phenotypes with high weighting, could be a suitable compromise regarding all important breeding aspects.

Identification of seedling vigor-associated quantitative trait loci in temperate japonica rice

USDA-ARS?s Scientific Manuscript database

A quantitative trait loci (QTL) analysis of seedling vigor traits was conducted under dry-seeded conditions using 176 recombinant inbred lines developed from a cross of two California temperate japonica rice varieties M-203 and M-206. Height at early seedling (HES) and late seedling (HLS) stage, gro...

Quantitative trait loci analysis for net ginning energy requirements in upland cotton (Gossypium hirsutum L.)

USDA-ARS?s Scientific Manuscript database

Cotton cultivars with reduced fiber-seed attachment force have the potential to be ginned faster with less energy. The objective of this study was to identify quantitative trait loci (QTL) for net ginning energy (NGE) requirement, and its relationship with other fiber quality traits in upland cotton...

Comprehensive Comparison of Self-Administered Questionnaires for Measuring Quantitative Autistic Traits in Adults

ERIC Educational Resources Information Center

Nishiyama, Takeshi; Suzuki, Masako; Adachi, Katsunori; Sumi, Satoshi; Okada, Kensuke; Kishino, Hirohisa; Sakai, Saeko; Kamio, Yoko; Kojima, Masayo; Suzuki, Sadao; Kanne, Stephen M.

2014-01-01

We comprehensively compared all available questionnaires for measuring quantitative autistic traits (QATs) in terms of reliability and construct validity in 3,147 non-clinical and 60 clinical subjects with normal intelligence. We examined four full-length forms, the Subthreshold Autism Trait Questionnaire (SATQ), the Broader Autism Phenotype…

Quantitative and Qualitative Differences in Morphological Traits Revealed between Diploid Fragaria Species

PubMed Central

SARGENT, DANIEL J.; GEIBEL, M.; HAWKINS, J. A.; WILKINSON, M. J.; BATTEY, N. H.; SIMPSON, D. W.

2004-01-01

• Background and Aims The aims of this investigation were to highlight the qualitative and quantitative diversity apparent between nine diploid Fragaria species and produce interspecific populations segregating for a large number of morphological characters suitable for quantitative trait loci analysis. • Methods A qualitative comparison of eight described diploid Fragaria species was performed and measurements were taken of 23 morphological traits from 19 accessions including eight described species and one previously undescribed species. A principal components analysis was performed on 14 mathematically unrelated traits from these accessions, which partitioned the species accessions into distinct morphological groups. Interspecific crosses were performed with accessions of species that displayed significant quantitative divergence and, from these, populations that should segregate for a range of quantitative traits were raised. • Key Results Significant differences between species were observed for all 23 morphological traits quantified and three distinct groups of species accessions were observed after the principal components analysis. Interspecific crosses were performed between these groups, and F2 and backcross populations were raised that should segregate for a range of morphological characters. In addition, the study highlighted a number of distinctive morphological characters in many of the species studied. • Conclusions Diploid Fragaria species are morphologically diverse, yet remain highly interfertile, making the group an ideal model for the study of the genetic basis of phenotypic differences between species through map-based investigation using quantitative trait loci. The segregating interspecific populations raised will be ideal for such investigations and could also provide insights into the nature and extent of genome evolution within this group. PMID:15469944

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

PubMed

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

2017-10-01

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

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

PubMed Central

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

2017-01-01

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

Congruent climate-related genecological responses from molecular markers and quantitative traits for western white pine (Pinus monticola)

Treesearch

Bryce A. Richardson; Gerald E. Rehfeldt; Mee-Sook Kim

2009-01-01

Analyses of molecular and quantitative genetic data demonstrate the existence of congruent climate-related patterns in western white pine (Pinus monticola). Two independent studies allowed comparisons of amplified fragment length polymorphism (AFLP) markers with quantitative variation in adaptive traits. Principal component analyses...

Genetics Home Reference: prostate cancer

MedlinePlus

... prostate cancer Genetic Testing Registry: Prostate cancer aggressiveness quantitative trait locus on chromosome 19 Genetic Testing Registry: ... OMIM (25 links) PROSTATE CANCER PROSTATE CANCER AGGRESSIVENESS QUANTITATIVE TRAIT LOCUS ON CHROMOSOME 19 PROSTATE CANCER ANTIGEN ...

Searching for an Accurate Marker-Based Prediction of an Individual Quantitative Trait in Molecular Plant Breeding

PubMed Central

Fu, Yong-Bi; Yang, Mo-Hua; Zeng, Fangqin; Biligetu, Bill

2017-01-01

Molecular plant breeding with the aid of molecular markers has played an important role in modern plant breeding over the last two decades. Many marker-based predictions for quantitative traits have been made to enhance parental selection, but the trait prediction accuracy remains generally low, even with the aid of dense, genome-wide SNP markers. To search for more accurate trait-specific prediction with informative SNP markers, we conducted a literature review on the prediction issues in molecular plant breeding and on the applicability of an RNA-Seq technique for developing function-associated specific trait (FAST) SNP markers. To understand whether and how FAST SNP markers could enhance trait prediction, we also performed a theoretical reasoning on the effectiveness of these markers in a trait-specific prediction, and verified the reasoning through computer simulation. To the end, the search yielded an alternative to regular genomic selection with FAST SNP markers that could be explored to achieve more accurate trait-specific prediction. Continuous search for better alternatives is encouraged to enhance marker-based predictions for an individual quantitative trait in molecular plant breeding. PMID:28729875

A Brassica rapa Linkage Map of EST-based SNP Markers for Identification of Candidate Genes Controlling Flowering Time and Leaf Morphological Traits

PubMed Central

Li, Feng; Kitashiba, Hiroyasu; Inaba, Kiyofumi; Nishio, Takeshi

2009-01-01

For identification of genes responsible for varietal differences in flowering time and leaf morphological traits, we constructed a linkage map of Brassica rapa DNA markers including 170 EST-based markers, 12 SSR markers, and 59 BAC sequence-based markers, of which 151 are single nucleotide polymorphism (SNP) markers. By BLASTN, 223 markers were shown to have homologous regions in Arabidopsis thaliana, and these homologous loci covered nearly the whole genome of A. thaliana. Synteny analysis between B. rapa and A. thaliana revealed 33 large syntenic regions. Three quantitative trait loci (QTLs) for flowering time were detected. BrFLC1 and BrFLC2 were linked to the QTLs for bolting time, budding time, and flowering time. Three SNPs in the promoter, which may be the cause of low expression of BrFLC2 in the early-flowering parental line, were identified. For leaf lobe depth and leaf hairiness, one major QTL corresponding to a syntenic region containing GIBBERELLIN 20 OXIDASE 3 and one major QTL containing BrGL1, respectively, were detected. Analysis of nucleotide sequences and expression of these genes suggested possible involvement of these genes in leaf morphological traits. PMID:19884167

A test for selection employing quantitative trait locus and mutation accumulation data.

PubMed

Rice, Daniel P; Townsend, Jeffrey P

2012-04-01

Evolutionary biologists attribute much of the phenotypic diversity observed in nature to the action of natural selection. However, for many phenotypic traits, especially quantitative phenotypic traits, it has been challenging to test for the historical action of selection. An important challenge for biologists studying quantitative traits, therefore, is to distinguish between traits that have evolved under the influence of strong selection and those that have evolved neutrally. Most existing tests for selection employ molecular data, but selection also leaves a mark on the genetic architecture underlying a trait. In particular, the distribution of quantitative trait locus (QTL) effect sizes and the distribution of mutational effects together provide information regarding the history of selection. Despite the increasing availability of QTL and mutation accumulation data, such data have not yet been effectively exploited for this purpose. We present a model of the evolution of QTL and employ it to formulate a test for historical selection. To provide a baseline for neutral evolution of the trait, we estimate the distribution of mutational effects from mutation accumulation experiments. We then apply a maximum-likelihood-based method of inference to estimate the range of selection strengths under which such a distribution of mutations could generate the observed QTL. Our test thus represents the first integration of population genetic theory and QTL data to measure the historical influence of selection.

Genomic Rearrangements in Arabidopsis Considered as Quantitative Traits.

PubMed

Imprialou, Martha; Kahles, André; Steffen, Joshua G; Osborne, Edward J; Gan, Xiangchao; Lempe, Janne; Bhomra, Amarjit; Belfield, Eric; Visscher, Anne; Greenhalgh, Robert; Harberd, Nicholas P; Goram, Richard; Hein, Jotun; Robert-Seilaniantz, Alexandre; Jones, Jonathan; Stegle, Oliver; Kover, Paula; Tsiantis, Miltos; Nordborg, Magnus; Rätsch, Gunnar; Clark, Richard M; Mott, Richard

2017-04-01

To understand the population genetics of structural variants and their effects on phenotypes, we developed an approach to mapping structural variants that segregate in a population sequenced at low coverage. We avoid calling structural variants directly. Instead, the evidence for a potential structural variant at a locus is indicated by variation in the counts of short-reads that map anomalously to that locus. These structural variant traits are treated as quantitative traits and mapped genetically, analogously to a gene expression study. Association between a structural variant trait at one locus, and genotypes at a distant locus indicate the origin and target of a transposition. Using ultra-low-coverage (0.3×) population sequence data from 488 recombinant inbred Arabidopsis thaliana genomes, we identified 6502 segregating structural variants. Remarkably, 25% of these were transpositions. While many structural variants cannot be delineated precisely, we validated 83% of 44 predicted transposition breakpoints by polymerase chain reaction. We show that specific structural variants may be causative for quantitative trait loci for germination and resistance to infection by the fungus Albugo laibachii , isolate Nc14. Further we show that the phenotypic heritability attributable to read-mapping anomalies differs from, and, in the case of time to germination and bolting, exceeds that due to standard genetic variation. Genes within structural variants are also more likely to be silenced or dysregulated. This approach complements the prevalent strategy of structural variant discovery in fewer individuals sequenced at high coverage. It is generally applicable to large populations sequenced at low-coverage, and is particularly suited to mapping transpositions. Copyright © 2017 by the Genetics Society of America.

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

PubMed

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

2008-12-01

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

Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas-fir.II. Spring and fall cold-hardiness

Treesearch

K.D. Jermstad; D.L. Bassoni; N.C. Wheeler; T.S. Anekonda; S.N. Aitken; W.T. Adams; D.B. Neale

2001-01-01

Abstract Quantitative trait loci (QTLs) affecting fall and spring cold-hardiness were identified in a three-generation outbred pedigree of coastal Douglas-fir [Pseudotsuga meniziesii (Mirb.) Franco var. menziesii]. Eleven QTLs controlling fall cold-hardiness were detected on four linkage groups, and 15 QTLs controlling spring cold-hardiness were detected on four...

QTL analysis of root morphology, flowering time, and yield reveals trade-offs in response to drought in Brassica napus.

PubMed

Fletcher, Richard S; Mullen, Jack L; Heiliger, Annie; McKay, John K

2015-01-01

Drought escape and dehydration avoidance represent alternative strategies for drought adaptation in annual crops. The mechanisms underlying these two strategies are reported to have a negative correlation, suggesting a trade-off. We conducted a quantitative trait locus (QTL) analysis of flowering time and root mass, traits representing each strategy, in Brassica napus to understand if a trade-off exists and what the genetic basis might be. Our field experiment used a genotyped population of doubled haploid lines and included both irrigated and rainfed treatments, allowing analysis of plasticity in each trait. We found strong genetic correlations among all traits, suggesting a trade-off among traits may exist. Summing across traits and treatments we found 20 QTLs, but many of these co-localized to two major QTLs, providing evidence that the trade-off is genetically constrained. To understand the mechanistic relationship between root mass, flowering time, and QTLs, we analysed the data by conditioning upon correlated traits. Our results suggest a causal model where such QTLs affect root mass directly as well as through their impacts on flowering time. Additionally, we used draft Brassica genomes to identify orthologues of well characterized Arabidopsis thaliana flowering time genes as candidate genes. This research provides valuable clues to breeding for drought adaptation as it is the first to analyse the inheritance of the root system in B. napus in relation to drought. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Genetic Variants Associated With Quantitative Glucose Homeostasis Traits Translate to Type 2 Diabetes in Mexican Americans: The GUARDIAN (Genetics Underlying Diabetes in Hispanics) Consortium.

PubMed

Palmer, Nicholette D; Goodarzi, Mark O; Langefeld, Carl D; Wang, Nan; Guo, Xiuqing; Taylor, Kent D; Fingerlin, Tasha E; Norris, Jill M; Buchanan, Thomas A; Xiang, Anny H; Haritunians, Talin; Ziegler, Julie T; Williams, Adrienne H; Stefanovski, Darko; Cui, Jinrui; Mackay, Adrienne W; Henkin, Leora F; Bergman, Richard N; Gao, Xiaoyi; Gauderman, James; Varma, Rohit; Hanis, Craig L; Cox, Nancy J; Highland, Heather M; Below, Jennifer E; Williams, Amy L; Burtt, Noel P; Aguilar-Salinas, Carlos A; Huerta-Chagoya, Alicia; Gonzalez-Villalpando, Clicerio; Orozco, Lorena; Haiman, Christopher A; Tsai, Michael Y; Johnson, W Craig; Yao, Jie; Rasmussen-Torvik, Laura; Pankow, James; Snively, Beverly; Jackson, Rebecca D; Liu, Simin; Nadler, Jerry L; Kandeel, Fouad; Chen, Yii-Der I; Bowden, Donald W; Rich, Stephen S; Raffel, Leslie J; Rotter, Jerome I; Watanabe, Richard M; Wagenknecht, Lynne E

2015-05-01

Insulin sensitivity, insulin secretion, insulin clearance, and glucose effectiveness exhibit strong genetic components, although few studies have examined their genetic architecture or influence on type 2 diabetes (T2D) risk. We hypothesized that loci affecting variation in these quantitative traits influence T2D. We completed a multicohort genome-wide association study to search for loci influencing T2D-related quantitative traits in 4,176 Mexican Americans. Quantitative traits were measured by the frequently sampled intravenous glucose tolerance test (four cohorts) or euglycemic clamp (three cohorts), and random-effects models were used to test the association between loci and quantitative traits, adjusting for age, sex, and admixture proportions (Discovery). Analysis revealed a significant (P < 5.00 × 10(-8)) association at 11q14.3 (MTNR1B) with acute insulin response. Loci with P < 0.0001 among the quantitative traits were examined for translation to T2D risk in 6,463 T2D case and 9,232 control subjects of Mexican ancestry (Translation). Nonparametric meta-analysis of the Discovery and Translation cohorts identified significant associations at 6p24 (SLC35B3/TFAP2A) with glucose effectiveness/T2D, 11p15 (KCNQ1) with disposition index/T2D, and 6p22 (CDKAL1) and 11q14 (MTNR1B) with acute insulin response/T2D. These results suggest that T2D and insulin secretion and sensitivity have both shared and distinct genetic factors, potentially delineating genomic components of these quantitative traits that drive the risk for T2D. © 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

Construction of a high-density genetic map by specific locus amplified fragment sequencing (SLAF-seq) and its application to Quantitative Trait Loci (QTL) analysis for boll weight in upland cotton (Gossypium hirsutum.).

PubMed

Zhang, Zhen; Shang, Haihong; Shi, Yuzhen; Huang, Long; Li, Junwen; Ge, Qun; Gong, Juwu; Liu, Aiying; Chen, Tingting; Wang, Dan; Wang, Yanling; Palanga, Koffi Kibalou; Muhammad, Jamshed; Li, Weijie; Lu, Quanwei; Deng, Xiaoying; Tan, Yunna; Song, Weiwu; Cai, Juan; Li, Pengtao; Rashid, Harun or; Gong, Wankui; Yuan, Youlu

2016-04-11

Upland Cotton (Gossypium hirsutum) is one of the most important worldwide crops it provides natural high-quality fiber for the industrial production and everyday use. Next-generation sequencing is a powerful method to identify single nucleotide polymorphism markers on a large scale for the construction of a high-density genetic map for quantitative trait loci mapping. In this research, a recombinant inbred lines population developed from two upland cotton cultivars 0-153 and sGK9708 was used to construct a high-density genetic map through the specific locus amplified fragment sequencing method. The high-density genetic map harbored 5521 single nucleotide polymorphism markers which covered a total distance of 3259.37 cM with an average marker interval of 0.78 cM without gaps larger than 10 cM. In total 18 quantitative trait loci of boll weight were identified as stable quantitative trait loci and were detected in at least three out of 11 environments and explained 4.15-16.70 % of the observed phenotypic variation. In total, 344 candidate genes were identified within the confidence intervals of these stable quantitative trait loci based on the cotton genome sequence. These genes were categorized based on their function through gene ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis and eukaryotic orthologous groups analysis. This research reported the first high-density genetic map for Upland Cotton (Gossypium hirsutum) with a recombinant inbred line population using single nucleotide polymorphism markers developed by specific locus amplified fragment sequencing. We also identified quantitative trait loci of boll weight across 11 environments and identified candidate genes within the quantitative trait loci confidence intervals. The results of this research would provide useful information for the next-step work including fine mapping, gene functional analysis, pyramiding breeding of functional genes as well as marker-assisted selection.

Cloning of DOG1, a quantitative trait locus controlling seed dormancy in Arabidopsis.

PubMed

Bentsink, Leónie; Jowett, Jemma; Hanhart, Corrie J; Koornneef, Maarten

2006-11-07

Genetic variation for seed dormancy in nature is a typical quantitative trait controlled by multiple loci on which environmental factors have a strong effect. Finding the genes underlying dormancy quantitative trait loci is a major scientific challenge, which also has relevance for agriculture and ecology. In this study we describe the identification of the DELAY OF GERMINATION 1 (DOG1) gene previously identified as a quantitative trait locus involved in the control of seed dormancy. This gene was isolated by a combination of positional cloning and mutant analysis and is absolutely required for the induction of seed dormancy. DOG1 is a member of a small gene family of unknown molecular function, with five members in Arabidopsis. The functional natural allelic variation present in Arabidopsis is caused by polymorphisms in the cis-regulatory region of the DOG1 gene and results in considerable expression differences between the DOG1 alleles of the accessions analyzed.

Divergent selection along climatic gradients in a rare central European endemic species, Saxifraga sponhemica

PubMed Central

Walisch, Tania J.; Colling, Guy; Bodenseh, Melanie; Matthies, Diethart

2015-01-01

Background and Aims The effects of habitat fragmentation on quantitative genetic variation in plant populations are still poorly known. Saxifraga sponhemica is a rare endemic of Central Europe with a disjunct distribution, and a stable and specialized habitat of treeless screes and cliffs. This study therefore used S. sponhemica as a model species to compare quantitative and molecular variation in order to explore (1) the relative importance of drift and selection in shaping the distribution of quantitative genetic variation along climatic gradients; (2) the relationship between plant fitness, quantitative genetic variation, molecular genetic variation and population size; and (3) the relationship between the differentiation of a trait among populations and its evolvability. Methods Genetic variation within and among 22 populations from the whole distribution area of S. sponhemica was studied using RAPD (random amplified polymorphic DNA) markers, and climatic variables were obtained for each site. Seeds were collected from each population and germinated, and seedlings were transplanted into a common garden for determination of variation in plant traits. Key Results In contrast to previous results from rare plant species, strong evidence was found for divergent selection. Most population trait means of S. sponhemica were significantly related to climate gradients, indicating adaptation. Quantitative genetic differentiation increased with geographical distance, even when neutral molecular divergence was controlled for, and QST exceeded FST for some traits. The evolvability of traits was negatively correlated with the degree of differentiation among populations (QST), i.e. traits under strong selection showed little genetic variation within populations. The evolutionary potential of a population was not related to its size, the performance of the population or its neutral genetic diversity. However, performance in the common garden was lower for plants from populations with reduced molecular genetic variation, suggesting inbreeding depression due to genetic erosion. Conclusions The findings suggest that studies of molecular and quantitative genetic variation may provide complementary insights important for the conservation of rare species. The strong differentiation of quantitative traits among populations shows that selection can be an important force for structuring variation in evolutionarily important traits even for rare endemic species restricted to very specific habitats. PMID:25862244

Slow erosion of a quantitative apple resistance to Venturia inaequalis based on an isolate-specific Quantitative Trait Locus.

PubMed

Caffier, Valérie; Le Cam, Bruno; Al Rifaï, Mehdi; Bellanger, Marie-Noëlle; Comby, Morgane; Denancé, Caroline; Didelot, Frédérique; Expert, Pascale; Kerdraon, Tifenn; Lemarquand, Arnaud; Ravon, Elisa; Durel, Charles-Eric

2016-10-01

Quantitative plant resistance affects the aggressiveness of pathogens and is usually considered more durable than qualitative resistance. However, the efficiency of a quantitative resistance based on an isolate-specific Quantitative Trait Locus (QTL) is expected to decrease over time due to the selection of isolates with a high level of aggressiveness on resistant plants. To test this hypothesis, we surveyed scab incidence over an eight-year period in an orchard planted with susceptible and quantitatively resistant apple genotypes. We sampled 79 Venturia inaequalis isolates from this orchard at three dates and we tested their level of aggressiveness under controlled conditions. Isolates sampled on resistant genotypes triggered higher lesion density and exhibited a higher sporulation rate on apple carrying the resistance allele of the QTL T1 compared to isolates sampled on susceptible genotypes. Due to this ability to select aggressive isolates, we expected the QTL T1 to be non-durable. However, our results showed that the quantitative resistance based on the QTL T1 remained efficient in orchard over an eight-year period, with only a slow decrease in efficiency and no detectable increase of the aggressiveness of fungal isolates over time. We conclude that knowledge on the specificity of a QTL is not sufficient to evaluate its durability. Deciphering molecular mechanisms associated with resistance QTLs, genetic determinants of aggressiveness and putative trade-offs within pathogen populations is needed to help in understanding the erosion processes. Copyright © 2016 Elsevier B.V. All rights reserved.

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

PubMed

Georges, Michel

2007-01-01

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

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

PubMed

Ishikawa, Akira

2017-11-27

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

Exploring and Harnessing Haplotype Diversity to Improve Yield Stability in Crops.

PubMed

Qian, Lunwen; Hickey, Lee T; Stahl, Andreas; Werner, Christian R; Hayes, Ben; Snowdon, Rod J; Voss-Fels, Kai P

2017-01-01

In order to meet future food, feed, fiber, and bioenergy demands, global yields of all major crops need to be increased significantly. At the same time, the increasing frequency of extreme weather events such as heat and drought necessitates improvements in the environmental resilience of modern crop cultivars. Achieving sustainably increase yields implies rapid improvement of quantitative traits with a very complex genetic architecture and strong environmental interaction. Latest advances in genome analysis technologies today provide molecular information at an ultrahigh resolution, revolutionizing crop genomic research, and paving the way for advanced quantitative genetic approaches. These include highly detailed assessment of population structure and genotypic diversity, facilitating the identification of selective sweeps and signatures of directional selection, dissection of genetic variants that underlie important agronomic traits, and genomic selection (GS) strategies that not only consider major-effect genes. Single-nucleotide polymorphism (SNP) markers today represent the genotyping system of choice for crop genetic studies because they occur abundantly in plant genomes and are easy to detect. SNPs are typically biallelic, however, hence their information content compared to multiallelic markers is low, limiting the resolution at which SNP-trait relationships can be delineated. An efficient way to overcome this limitation is to construct haplotypes based on linkage disequilibrium, one of the most important features influencing genetic analyses of crop genomes. Here, we give an overview of the latest advances in genomics-based haplotype analyses in crops, highlighting their importance in the context of polyploidy and genome evolution, linkage drag, and co-selection. We provide examples of how haplotype analyses can complement well-established quantitative genetics frameworks, such as quantitative trait analysis and GS, ultimately providing an effective tool to equip modern crops with environment-tailored characteristics.

Genetic and environmental control of the Verticillium syndrome in Arabidopsis thaliana.

PubMed

Häffner, Eva; Karlovsky, Petr; Diederichsen, Elke

2010-11-02

Verticillium spp. are major pathogens of dicotyledonous plants such as cotton, tomato, olive or oilseed rape. Verticillium symptoms are often ambiguous and influenced by development and environment. The aim of the present study was to define disease and resistance traits of the complex Verticillium longisporum syndrome in Arabidopsis thaliana (L.) Heynh. A genetic approach was used to determine genetic, developmental and environmental factors controlling specific disease and resistance traits and to study their interrelations. A segregating F2/F3 population originating from ecotypes 'Burren' (Bur) and 'Landsberg erecta' (Ler) was established. Plants were root-dip inoculated and tested under greenhouse conditions. The Verticillium syndrome was dissected into components like systemic spread, stunting, development time and axillary branching. Systemic spread of V. longisporum via colonisation of the shoot was extensive in Ler; Bur showed a high degree of resistance against systemic spread. Fungal colonisation of the shoot apex was determined by (a) determining the percentage of plants from which the fungus could be re-isolated and (b) measuring fungal DNA content with quantitative real-time PCR (qPCR). Four quantitative trait loci (QTL) controlling systemic spread were identified for the percentage of plants showing fungal outgrowth, two of these QTL were confirmed with qPCR data. The degree of colonisation by V. longisporum was negatively correlated with development time. QTL controlling development time showed some overlap with QTL for resistance to systemic spread. Stunting depended on host genotype, development time and seasonal effects. Five QTL controlling this trait were identified which did not co-localize with QTL controlling systemic spread. V. longisporum induced increased axillary branching in Bur; two QTL controlling this reaction were found. Systemic spread of V. longisporum in the host as well as resistance to this major disease trait are described for the first time in natural A. thaliana accessions. This creates the possibility to study a major resistance mechanism against vascular pathogens in this model plant and to clone relevant genes of the involved pathways. Stunting resistance and resistance to systemic spread were controlled by different QTL and should be treated as separate traits. Developmental and environmental effects on pathogenesis and resistance need to be considered when designing and interpreting experiments in research and breeding.

Identification of downy mildew resistance gene candidates by positional cloning in maize (Zea mays subsp. mays; Poaceae)1

PubMed Central

Kim, Jae Yoon; Moon, Jun-Cheol; Kim, Hyo Chul; Shin, Seungho; Song, Kitae; Kim, Kyung-Hee; Lee, Byung-Moo

2017-01-01

Premise of the study: Positional cloning in combination with phenotyping is a general approach to identify disease-resistance gene candidates in plants; however, it requires several time-consuming steps including population or fine mapping. Therefore, in the present study, we suggest a new combined strategy to improve the identification of disease-resistance gene candidates. Methods and Results: Downy mildew (DM)–resistant maize was selected from five cultivars using a spreader row technique. Positional cloning and bioinformatics tools were used to identify the DM-resistance quantitative trait locus marker (bnlg1702) and 47 protein-coding gene annotations. Eventually, five DM-resistance gene candidates, including bZIP34, Bak1, and Ppr, were identified by quantitative reverse-transcription PCR (RT-PCR) without fine mapping of the bnlg1702 locus. Conclusions: The combined protocol with the spreader row technique, quantitative trait locus positional cloning, and quantitative RT-PCR was effective for identifying DM-resistance candidate genes. This cloning approach may be applied to other whole-genome-sequenced crops or resistance to other diseases. PMID:28224059

Quantitative genetic versions of Hamilton's rule with empirical applications

PubMed Central

McGlothlin, Joel W.; Wolf, Jason B.; Brodie, Edmund D.; Moore, Allen J.

2014-01-01

Hamilton's theory of inclusive fitness revolutionized our understanding of the evolution of social interactions. Surprisingly, an incorporation of Hamilton's perspective into the quantitative genetic theory of phenotypic evolution has been slow, despite the popularity of quantitative genetics in evolutionary studies. Here, we discuss several versions of Hamilton's rule for social evolution from a quantitative genetic perspective, emphasizing its utility in empirical applications. Although evolutionary quantitative genetics offers methods to measure each of the critical parameters of Hamilton's rule, empirical work has lagged behind theory. In particular, we lack studies of selection on altruistic traits in the wild. Fitness costs and benefits of altruism can be estimated using a simple extension of phenotypic selection analysis that incorporates the traits of social interactants. We also discuss the importance of considering the genetic influence of the social environment, or indirect genetic effects (IGEs), in the context of Hamilton's rule. Research in social evolution has generated an extensive body of empirical work focusing—with good reason—almost solely on relatedness. We argue that quantifying the roles of social and non-social components of selection and IGEs, in addition to relatedness, is now timely and should provide unique additional insights into social evolution. PMID:24686930

‘Particle genetics’: treating every cell as unique

PubMed Central

Yvert, Gaël

2014-01-01

Genotype-phenotype relations are usually inferred from a deterministic point of view. For example, quantitative trait loci (QTL), which describe regions of the genome associated with a particular phenotype, are based on a mean trait difference between genotype categories. However, living systems comprise huge numbers of cells (the ‘particles’ of biology). Each cell can exhibit substantial phenotypic individuality, which can have dramatic consequences at the organismal level. Now, with technology capable of interrogating individual cells, it is time to consider how genotypes shape the probability laws of single cell traits. The possibility of mapping single cell probabilistic trait loci (PTL), which link genomic regions to probabilities of cellular traits, is a promising step in this direction. This approach requires thinking about phenotypes in probabilistic terms, a concept that statistical physicists have been applying to particles for a century. Here, I describe PTL and discuss their potential to enlarge our understanding of genotype-phenotype relations. PMID:24315431

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

PubMed

Lehtonen, Jussi; Lanfear, Robert

2014-11-01

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

Modelling the co-evolution of indirect genetic effects and inherited variability.

PubMed

Marjanovic, Jovana; Mulder, Han A; Rönnegård, Lars; Bijma, Piter

2018-03-28

When individuals interact, their phenotypes may be affected not only by their own genes but also by genes in their social partners. This phenomenon is known as Indirect Genetic Effects (IGEs). In aquaculture species and some plants, however, competition not only affects trait levels of individuals, but also inflates variability of trait values among individuals. In the field of quantitative genetics, the variability of trait values has been studied as a quantitative trait in itself, and is often referred to as inherited variability. Such studies, however, consider only the genetic effect of the focal individual on trait variability and do not make a connection to competition. Although the observed phenotypic relationship between competition and variability suggests an underlying genetic relationship, the current quantitative genetic models of IGE and inherited variability do not allow for such a relationship. The lack of quantitative genetic models that connect IGEs to inherited variability limits our understanding of the potential of variability to respond to selection, both in nature and agriculture. Models of trait levels, for example, show that IGEs may considerably change heritable variation in trait values. Currently, we lack the tools to investigate whether this result extends to variability of trait values. Here we present a model that integrates IGEs and inherited variability. In this model, the target phenotype, say growth rate, is a function of the genetic and environmental effects of the focal individual and of the difference in trait value between the social partner and the focal individual, multiplied by a regression coefficient. The regression coefficient is a genetic trait, which is a measure of cooperation; a negative value indicates competition, a positive value cooperation, and an increasing value due to selection indicates the evolution of cooperation. In contrast to the existing quantitative genetic models, our model allows for co-evolution of IGEs and variability, as the regression coefficient can respond to selection. Our simulations show that the model results in increased variability of body weight with increasing competition. When competition decreases, i.e., cooperation evolves, variability becomes significantly smaller. Hence, our model facilitates quantitative genetic studies on the relationship between IGEs and inherited variability. Moreover, our findings suggest that we may have been overlooking an entire level of genetic variation in variability, the one due to IGEs.

EM Algorithm for Mapping Quantitative Trait Loci in Multivalent Tetraploids

USDA-ARS?s Scientific Manuscript database

Multivalent tetraploids that include many plant species, such as potato, sugarcane and rose, are of paramount importance to agricultural production and biological research. Quantitative trait locus (QTL) mapping in multivalent tetraploids is challenged by their unique cytogenetic properties, such ...

Population structure and strong divergent selection shape phenotypic diversification in maize landraces.

PubMed

Pressoir, G; Berthaud, J

2004-02-01

To conserve the long-term selection potential of maize, it is necessary to investigate past and present evolutionary processes that have shaped quantitative trait variation. Understanding the dynamics of quantitative trait evolution is crucial to future crop breeding. We characterized population differentiation of maize landraces from the State of Oaxaca, Mexico for quantitative traits and molecular markers. Qst values were much higher than Fst values obtained for molecular markers. While low values of Fst (0.011 within-village and 0.003 among-villages) suggest that considerable gene flow occurred among the studied populations, high levels of population differentiation for quantitative traits were observed (ie an among-village Qst value of 0.535 for kernel weight). Our results suggest that although quantitative traits appear to be under strong divergent selection, a considerable amount of gene flow occurs among populations. Furthermore, we characterized nonproportional changes in the G matrix structure both within and among villages that are consequences of farmer selection. As a consequence of these differences in the G matrix structure, the response to multivariate selection will be different from one population to another. Large changes in the G matrix structure could indicate that farmers select for genes of major and pleiotropic effect. Farmers' decision and selection strategies have a great impact on phenotypic diversification in maize landraces.

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

PubMed

Stearns, Frank W; Fenster, Charles B

2016-12-01

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

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

PubMed

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

2011-01-01

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

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

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

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

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

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

DOE PAGES

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

2016-08-15

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

Molecularly tagged genes and quantitative trait loci in cucumber

USDA-ARS?s Scientific Manuscript database

Since the release of the cucumber draft genome, significant progress has been made in molecular mapping, tagging or cloning of horticulturally important genes and quantitative trait loci (QTLs) in cucumber, which provides the foundation for practicing marker-assisted selection in cucumber breeding. ...

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

PubMed Central

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

2017-01-01

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

Quantitative trait loci and metabolic pathways

PubMed Central

McMullen, M. D.; Byrne, P. F.; Snook, M. E.; Wiseman, B. R.; Lee, E. A.; Widstrom, N. W.; Coe, E. H.

1998-01-01

The interpretation of quantitative trait locus (QTL) studies is limited by the lack of information on metabolic pathways leading to most economic traits. Inferences about the roles of the underlying genes with a pathway or the nature of their interaction with other loci are generally not possible. An exception is resistance to the corn earworm Helicoverpa zea (Boddie) in maize (Zea mays L.) because of maysin, a C-glycosyl flavone synthesized in silks via a branch of the well characterized flavonoid pathway. Our results using flavone synthesis as a model QTL system indicate: (i) the importance of regulatory loci as QTLs, (ii) the importance of interconnecting biochemical pathways on product levels, (iii) evidence for “channeling” of intermediates, allowing independent synthesis of related compounds, (iv) the utility of QTL analysis in clarifying the role of specific genes in a biochemical pathway, and (v) identification of a previously unknown locus on chromosome 9S affecting flavone level. A greater understanding of the genetic basis of maysin synthesis and associated corn earworm resistance should lead to improved breeding strategies. More broadly, the insights gained in relating a defined genetic and biochemical pathway affecting a quantitative trait should enhance interpretation of the biological basis of variation for other quantitative traits. PMID:9482823

Quantitative trait loci associated with anthracnose resistance in sorghum

USDA-ARS?s Scientific Manuscript database

With an aim to develop a durable resistance to the fungal disease anthracnose, two unique genetic sources of resistance were selected to create genetic mapping populations to identify regions of the sorghum genome that encode anthracnose resistance. A series of quantitative trait loci were identifi...

Quantitative trait loci associated with the tocochromanol (vitamin E) pathway in barley

USDA-ARS?s Scientific Manuscript database

In this study, the Genome-Wide Association Studies approach was used to detect Quantitative Trait Loci associated with tocochromanol concentrations using a panel of 1,466 barley accessions. All major tocochromanol types- alpha-, beta-, delta-, gamma-tocopherol and tocotrienol- were assayed. We found...

A simple bias correction in linear regression for quantitative trait association under two-tail extreme selection.

PubMed

Kwan, Johnny S H; Kung, Annie W C; Sham, Pak C

2011-09-01

Selective genotyping can increase power in quantitative trait association. One example of selective genotyping is two-tail extreme selection, but simple linear regression analysis gives a biased genetic effect estimate. Here, we present a simple correction for the bias.

Effects of normalization on quantitative traits in association test

PubMed Central

2009-01-01

Background Quantitative trait loci analysis assumes that the trait is normally distributed. In reality, this is often not observed and one strategy is to transform the trait. However, it is not clear how much normality is required and which transformation works best in association studies. Results We performed simulations on four types of common quantitative traits to evaluate the effects of normalization using the logarithm, Box-Cox, and rank-based transformations. The impact of sample size and genetic effects on normalization is also investigated. Our results show that rank-based transformation gives generally the best and consistent performance in identifying the causal polymorphism and ranking it highly in association tests, with a slight increase in false positive rate. Conclusion For small sample size or genetic effects, the improvement in sensitivity for rank transformation outweighs the slight increase in false positive rate. However, for large sample size and genetic effects, normalization may not be necessary since the increase in sensitivity is relatively modest. PMID:20003414

Quantitative trait loci and candidate genes associated with starch pasting viscosity characteristics in cassava (Manihot esculenta Crantz).

PubMed

Thanyasiriwat, T; Sraphet, S; Whankaew, S; Boonseng, O; Bao, J; Lightfoot, D A; Tangphatsornruang, S; Triwitayakorn, K

2014-01-01

Starch pasting viscosity is an important quality trait in cassava (Manihot esculenta Crantz) cultivars. The aim here was to identify loci and candidate genes associated with the starch pasting viscosity. Quantitative trait loci (QTL) mapping for seven pasting viscosity parameters was carried out using 100 lines of an F1 mapping population from a cross between two cassava cultivars Huay Bong 60 and Hanatee. Starch samples were obtained from roots of cassava grown in 2008 and 2009 at Rayong, and in 2009 at Lop Buri province, Thailand. The traits showed continuous distribution among the F1 progeny with transgressive variation. Fifteen QTL were identified from mean trait data, with Logarithm of Odds (LOD) values from 2.77-13.01 and phenotype variations explained (PVE) from10.0-48.4%. In addition, 48 QTL were identified in separate environments. The LOD values ranged from 2.55-8.68 and explained 6.6-43.7% of phenotype variation. The loci were located on 19 linkage groups. The most important QTL for pasting temperature (PT) (qPT.1LG1) from mean trait values showed largest effect with highest LOD value (13.01) and PVE (48.4%). The QTL co-localised with PT and pasting time (PTi) loci that were identified in separate environments. Candidate genes were identified within the QTL peak regions. However, the major genes of interest, encoding the family of glycosyl or glucosyl transferases and hydrolases, were located at the periphery of QTL peaks. The loci identified could be effectively applied in breeding programmes to improve cassava starch quality. Alleles of candidate genes should be further studied in order to better understand their effects on starch quality traits. © 2013 German Botanical Society and The Royal Botanical Society of the Netherlands.

Association mapping of seed quality traits using the Canadian flax (Linum usitatissimum L.) core collection.

PubMed

Soto-Cerda, Braulio J; Duguid, Scott; Booker, Helen; Rowland, Gordon; Diederichsen, Axel; Cloutier, Sylvie

2014-04-01

The identification of stable QTL for seed quality traits by association mapping of a diverse panel of linseed accessions establishes the foundation for assisted breeding and future fine mapping in linseed. Linseed oil is valued for its food and non-food applications. Modifying its oil content and fatty acid (FA) profiles to meet market needs in a timely manner requires clear understanding of their quantitative trait loci (QTL) architectures, which have received little attention to date. Association mapping is an efficient approach to identify QTL in germplasm collections. In this study, we explored the quantitative nature of seed quality traits including oil content (OIL), palmitic acid, stearic acid, oleic acid, linoleic acid (LIO) linolenic acid (LIN) and iodine value in a flax core collection of 390 accessions assayed with 460 microsatellite markers. The core collection was grown in a modified augmented design at two locations over 3 years and phenotypic data for all seven traits were obtained from all six environments. Significant phenotypic diversity and moderate to high heritability for each trait (0.73-0.99) were observed. Most of the candidate QTL were stable as revealed by multivariate analyses. Nine candidate QTL were identified, varying from one for OIL to three for LIO and LIN. Candidate QTL for LIO and LIN co-localized with QTL previously identified in bi-parental populations and some mapped nearby genes known to be involved in the FA biosynthesis pathway. Fifty-eight percent of the QTL alleles were absent (private) in the Canadian cultivars suggesting that the core collection possesses QTL alleles potentially useful to improve seed quality traits. The candidate QTL identified herein will establish the foundation for future marker-assisted breeding in linseed.

Genetic and Developmental Basis for Increased Leaf Thickness in the Arabidopsis Cvi Ecotype.

PubMed

Coneva, Viktoriya; Chitwood, Daniel H

2018-01-01

Leaf thickness is a quantitative trait that is associated with the ability of plants to occupy dry, high irradiance environments. Despite its importance, leaf thickness has been difficult to measure reproducibly, which has impeded progress in understanding its genetic basis, and the associated anatomical mechanisms that pattern it. Here, we used a custom-built dual confocal profilometer device to measure leaf thickness in the Arabidopsis Ler × Cvi recombinant inbred line population and found statistical support for four quantitative trait loci (QTL) associated with this trait. We used publically available data for a suite of traits relating to flowering time and growth responses to light quality and show that three of the four leaf thickness QTL coincide with QTL for at least one of these traits. Using time course photography, we quantified the relative growth rate and the pace of rosette leaf initiation in the Ler and Cvi ecotypes. We found that Cvi rosettes grow slower than Ler, both in terms of the rate of leaf initiation and the overall rate of biomass accumulation. Collectively, these data suggest that leaf thickness is tightly linked with physiological status and may present a tradeoff between the ability to withstand stress and rapid vegetative growth. To understand the anatomical basis of leaf thickness, we compared cross-sections of Cvi and Ler leaves and show that Cvi palisade mesophyll cells elongate anisotropically contributing to leaf thickness. Flow cytometry of whole leaves show that endopolyploidy accompanies thicker leaves in Cvi. Overall, our data suggest that mechanistically, an altered schedule of cellular events affecting endopolyploidy and increasing palisade mesophyll cell length contribute to increase of leaf thickness in Cvi. Ultimately, knowledge of the genetic basis and developmental trajectory leaf thickness will inform the mechanisms by which natural selection acts to produce variation in this adaptive trait.

Genetic and Developmental Basis for Increased Leaf Thickness in the Arabidopsis Cvi Ecotype

PubMed Central

Coneva, Viktoriya; Chitwood, Daniel H.

2018-01-01

Leaf thickness is a quantitative trait that is associated with the ability of plants to occupy dry, high irradiance environments. Despite its importance, leaf thickness has been difficult to measure reproducibly, which has impeded progress in understanding its genetic basis, and the associated anatomical mechanisms that pattern it. Here, we used a custom-built dual confocal profilometer device to measure leaf thickness in the Arabidopsis Ler × Cvi recombinant inbred line population and found statistical support for four quantitative trait loci (QTL) associated with this trait. We used publically available data for a suite of traits relating to flowering time and growth responses to light quality and show that three of the four leaf thickness QTL coincide with QTL for at least one of these traits. Using time course photography, we quantified the relative growth rate and the pace of rosette leaf initiation in the Ler and Cvi ecotypes. We found that Cvi rosettes grow slower than Ler, both in terms of the rate of leaf initiation and the overall rate of biomass accumulation. Collectively, these data suggest that leaf thickness is tightly linked with physiological status and may present a tradeoff between the ability to withstand stress and rapid vegetative growth. To understand the anatomical basis of leaf thickness, we compared cross-sections of Cvi and Ler leaves and show that Cvi palisade mesophyll cells elongate anisotropically contributing to leaf thickness. Flow cytometry of whole leaves show that endopolyploidy accompanies thicker leaves in Cvi. Overall, our data suggest that mechanistically, an altered schedule of cellular events affecting endopolyploidy and increasing palisade mesophyll cell length contribute to increase of leaf thickness in Cvi. Ultimately, knowledge of the genetic basis and developmental trajectory leaf thickness will inform the mechanisms by which natural selection acts to produce variation in this adaptive trait. PMID:29593772

General quantitative genetic methods for comparative biology: phylogenies, taxonomies and multi-trait models for continuous and categorical characters.

PubMed

Hadfield, J D; Nakagawa, S

2010-03-01

Although many of the statistical techniques used in comparative biology were originally developed in quantitative genetics, subsequent development of comparative techniques has progressed in relative isolation. Consequently, many of the new and planned developments in comparative analysis already have well-tested solutions in quantitative genetics. In this paper, we take three recent publications that develop phylogenetic meta-analysis, either implicitly or explicitly, and show how they can be considered as quantitative genetic models. We highlight some of the difficulties with the proposed solutions, and demonstrate that standard quantitative genetic theory and software offer solutions. We also show how results from Bayesian quantitative genetics can be used to create efficient Markov chain Monte Carlo algorithms for phylogenetic mixed models, thereby extending their generality to non-Gaussian data. Of particular utility is the development of multinomial models for analysing the evolution of discrete traits, and the development of multi-trait models in which traits can follow different distributions. Meta-analyses often include a nonrandom collection of species for which the full phylogenetic tree has only been partly resolved. Using missing data theory, we show how the presented models can be used to correct for nonrandom sampling and show how taxonomies and phylogenies can be combined to give a flexible framework with which to model dependence.

A Simple Test Identifies Selection on Complex Traits.

PubMed

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

2018-05-01

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

Four Linked Genes Participate in Controlling Sporulation Efficiency in Budding Yeast

PubMed Central

Ben-Ari, Giora; Zenvirth, Drora; Sherman, Amir; David, Lior; Klutstein, Michael; Lavi, Uri; Hillel, Jossi; Simchen, Giora

2006-01-01

Quantitative traits are conditioned by several genetic determinants. Since such genes influence many important complex traits in various organisms, the identification of quantitative trait loci (QTLs) is of major interest, but still encounters serious difficulties. We detected four linked genes within one QTL, which participate in controlling sporulation efficiency in Saccharomyces cerevisiae. Following the identification of single nucleotide polymorphisms by comparing the sequences of 145 genes between the parental strains SK1 and S288c, we analyzed the segregating progeny of the cross between them. Through reciprocal hemizygosity analysis, four genes, RAS2, PMS1, SWS2, and FKH2, located in a region of 60 kilobases on Chromosome 14, were found to be associated with sporulation efficiency. Three of the four “high” sporulation alleles are derived from the “low” sporulating strain. Two of these sporulation-related genes were verified through allele replacements. For RAS2, the causative variation was suggested to be a single nucleotide difference in the upstream region of the gene. This quantitative trait nucleotide accounts for sporulation variability among a set of ten closely related winery yeast strains. Our results provide a detailed view of genetic complexity in one “QTL region” that controls a quantitative trait and reports a single nucleotide polymorphism-trait association in wild strains. Moreover, these findings have implications on QTL identification in higher eukaryotes. PMID:17112318

Comparing Bayesian estimates of genetic differentiation of molecular markers and quantitative traits: an application to Pinus sylvestris.

PubMed

Waldmann, P; García-Gil, M R; Sillanpää, M J

2005-06-01

Comparison of the level of differentiation at neutral molecular markers (estimated as F(ST) or G(ST)) with the level of differentiation at quantitative traits (estimated as Q(ST)) has become a standard tool for inferring that there is differential selection between populations. We estimated Q(ST) of timing of bud set from a latitudinal cline of Pinus sylvestris with a Bayesian hierarchical variance component method utilizing the information on the pre-estimated population structure from neutral molecular markers. Unfortunately, the between-family variances differed substantially between populations that resulted in a bimodal posterior of Q(ST) that could not be compared in any sensible way with the unimodal posterior of the microsatellite F(ST). In order to avoid publishing studies with flawed Q(ST) estimates, we recommend that future studies should present heritability estimates for each trait and population. Moreover, to detect variance heterogeneity in frequentist methods (ANOVA and REML), it is of essential importance to check also that the residuals are normally distributed and do not follow any systematically deviating trends.

Pleiotropy Analysis of Quantitative Traits at Gene Level by Multivariate Functional Linear Models

PubMed Central

Wang, Yifan; Liu, Aiyi; Mills, James L.; Boehnke, Michael; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Xiong, Momiao; Wu, Colin O.; Fan, Ruzong

2015-01-01

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests 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 in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. PMID:25809955

Pleiotropy analysis of quantitative traits at gene level by multivariate functional linear models.

PubMed

Wang, Yifan; Liu, Aiyi; Mills, James L; Boehnke, Michael; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao; Wu, Colin O; Fan, Ruzong

2015-05-01

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests 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 in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. © 2015 WILEY PERIODICALS, INC.

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

Evaluation and Quantitative trait loci mapping of resistance to powdery mildew in lettuce

USDA-ARS?s Scientific Manuscript database

Lettuce (Lactuca sativa L.) is the major leafy vegetable that is susceptible to powdery mildew disease under greenhouse and field conditions. We mapped quantitative trait loci (QTLs) for resistance to powdery mildew under greenhouse conditions in an interspecific population derived from a cross betw...

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

PubMed

Hallsson, Lára R; Björklund, Mats

2012-01-01

Knowledge of heritability and genetic correlations are of central importance in the study of adaptive trait evolution and genetic constraints. We use a paternal half-sib-full-sib breeding design to investigate the genetic architecture of three life-history and morphological traits in the seed beetle, Callosobruchus maculatus. Heritability was significant for all traits under observation and genetic correlations between traits (r(A)) were low. Interestingly, we found substantial sex-specific genetic effects and low genetic correlations between sexes (r(MF)) in traits that are only moderately (weight at emergence) to slightly (longevity) sexually dimorphic. Furthermore, we found an increased sire ([Formula: see text]) compared to dam ([Formula: see text]) variance component within trait and sex. Our results highlight that the genetic architecture even of the same trait should not be assumed to be the same for males and females. Furthermore, it raises the issue of the presence of unnoticed environmental effects that may inflate estimates of heritability. Overall, our study stresses the fact that estimates of quantitative genetic parameters are not only population, time, environment, but also sex specific. Thus, extrapolation between sexes and studies should be treated with caution.

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

PubMed Central

Hallsson, Lára R; Björklund, Mats

2012-01-01

Knowledge of heritability and genetic correlations are of central importance in the study of adaptive trait evolution and genetic constraints. We use a paternal half-sib-full-sib breeding design to investigate the genetic architecture of three life-history and morphological traits in the seed beetle, Callosobruchus maculatus. Heritability was significant for all traits under observation and genetic correlations between traits (rA) were low. Interestingly, we found substantial sex-specific genetic effects and low genetic correlations between sexes (rMF) in traits that are only moderately (weight at emergence) to slightly (longevity) sexually dimorphic. Furthermore, we found an increased sire () compared to dam () variance component within trait and sex. Our results highlight that the genetic architecture even of the same trait should not be assumed to be the same for males and females. Furthermore, it raises the issue of the presence of unnoticed environmental effects that may inflate estimates of heritability. Overall, our study stresses the fact that estimates of quantitative genetic parameters are not only population, time, environment, but also sex specific. Thus, extrapolation between sexes and studies should be treated with caution. PMID:22408731

Longitudinal trends in climate drive flowering time clines in North American Arabidopsis thaliana.

PubMed

Samis, Karen E; Murren, Courtney J; Bossdorf, Oliver; Donohue, Kathleen; Fenster, Charles B; Malmberg, Russell L; Purugganan, Michael D; Stinchcombe, John R

2012-06-01

Introduced species frequently show geographic differentiation, and when differentiation mirrors the ancestral range, it is often taken as evidence of adaptive evolution. The mouse-ear cress (Arabidopsis thaliana) was introduced to North America from Eurasia 150-200 years ago, providing an opportunity to study parallel adaptation in a genetic model organism. Here, we test for clinal variation in flowering time using 199 North American (NA) accessions of A. thaliana, and evaluate the contributions of major flowering time genes FRI, FLC, and PHYC as well as potential ecological mechanisms underlying differentiation. We find evidence for substantial within population genetic variation in quantitative traits and flowering time, and putatively adaptive longitudinal differentiation, despite low levels of variation at FRI, FLC, and PHYC and genome-wide reductions in population structure relative to Eurasian (EA) samples. The observed longitudinal cline in flowering time in North America is parallel to an EA cline, robust to the effects of population structure, and associated with geographic variation in winter precipitation and temperature. We detected major effects of FRI on quantitative traits associated with reproductive fitness, although the haplotype associated with higher fitness remains rare in North America. Collectively, our results suggest the evolution of parallel flowering time clines through novel genetic mechanisms.

Investigation of the Genetic Diversity and Quantitative Trait Loci Accounting for Important Agronomic and Seed Quality Traits in Brassica carinata

PubMed Central

Zhang, Wenshan; Hu, Dandan; Raman, Rosy; Guo, Shaomin; Wei, Zili; Shen, Xueqi; Meng, Jinling; Raman, Harsh; Zou, Jun

2017-01-01

Brassica carinata (BBCC) is an allotetraploid in Brassicas with unique alleles for agronomic traits and has huge potential as source for biodiesel production. To investigate the genome-wide molecular diversity, population structure and linkage disequilibrium (LD) pattern in this species, we genotyped a panel of 81 accessions of B. carinata with genotyping by sequencing approach DArTseq, generating a total of 54,510 polymorphic markers. Two subpopulations were exhibited in the B. carinata accessions. The average distance of LD decay (r2 = 0.1) in B subgenome (0.25 Mb) was shorter than that of C subgenome (0.40 Mb). Genome-wide association analysis (GWAS) identified a total of seven markers significantly associated with five seed quality traits in two experiments. To further identify the quantitative trait loci (QTL) for important agronomic and seed quality traits, we phenotyped a doubled haploid (DH) mapping population derived from the “YW” cross between two parents (Y-BcDH64 and W-BcDH76) representing from the two subpopulations. The YW DH population and its parents were grown in three contrasting environments; spring (Hezheng and Xining, China), semi-winter (Wuhan, China), and spring (Wagga Wagga, Australia) across 5 years for QTL mapping. Genetic bases of phenotypic variation in seed yield and its seven related traits, and six seed quality traits were determined. A total of 282 consensus QTL accounting for these traits were identified including nine major QTL for flowering time, oleic acid, linolenic acid, pod number of main inflorescence, and seed weight. Of these, 109 and 134 QTL were specific to spring and semi-winter environment, respectively, while 39 consensus QTL were identified in both contrasting environments. Two QTL identified for linolenic acid (B3) and erucic acid (C7) were validated in the diverse lines used for GWAS. A total of 25 QTL accounting for flowering time, erucic acid, and oleic acid were aligned to the homologous QTL or candidate gene regions in the C genome of B. napus. These results would not only provide insights for genetic improvement of this species, but will also identify useful genetic variation hidden in the Cc subgenome of B. carinata to improve canola cultivars. PMID:28484482

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

PubMed Central

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

2012-01-01

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

Exploring the interaction among EPHX1, GSTP1, SERPINE2, and TGFB1 contributing to the quantitative traits of chronic obstructive pulmonary disease in Chinese Han population.

PubMed

An, Li; Lin, Yingxiang; Yang, Ting; Hua, Lin

2016-05-18

Currently, the majority of genetic association studies on chronic obstructive pulmonary disease (COPD) risk focused on identifying the individual effects of single nucleotide polymorphisms (SNPs) as well as their interaction effects on the disease. However, conventional genetic studies often use binary disease status as the primary phenotype, but for COPD, many quantitative traits have the potential correlation with the disease status and closely reflect pathological changes. Here, we genotyped 44 SNPs from four genes (EPHX1, GSTP1, SERPINE2, and TGFB1) in 310 patients and 203 controls which belonged to the Chinese Han population to test the two-way and three-way genetic interactions with COPD-related quantitative traits using recently developed generalized multifactor dimensionality reduction (GMDR) and quantitative multifactor dimensionality reduction (QMDR) algorithms. Based on the 310 patients and the whole samples of 513 subjects, the best gene-gene interactions models were detected for four lung-function-related quantitative traits. For the forced expiratory volume in 1 s (FEV1), the best interaction was seen from EPHX1, SERPINE2, and GSTP1. For FEV1%pre, the forced vital capacity (FVC), and FEV1/FVC, the best interactions were seen from SERPINE2 and TGFB1. The results of this study provide further evidence for the genotype combinations at risk of developing COPD in Chinese Han population and improve the understanding on the genetic etiology of COPD and COPD-related quantitative traits.

Quantitative trait loci mapping for flowering time in a switchgrass pseudo-F2 population

USDA-ARS?s Scientific Manuscript database

Flowering is an important developmental event in switchgrass (Panicum virgatum) because the onset of flowering causes the cessation of vegetative growth and biomass accumulation. The objective of this study was to generate a linkage map using single nucleotide polymorphism (SNP) markers to identify ...

Allelic analysis of sheath blight resistance with association mapping in rice

USDA-ARS?s Scientific Manuscript database

Sheath blight is one of the most devastating diseases world-wide in rice. For the first time, we adopted association mapping to identify quantitative trait loci for sheath blight resistance from the USDA rice mini-core collection. The phenotyping was conducted with a newly developed micro-chamber me...

Genetic dissection of powdery mildew resistance in interspecific half-sib grapevine families using SNP-based maps

USDA-ARS?s Scientific Manuscript database

Quantitative trait locus (QTL) identification in perennial fruit crops is impeded largely by their lengthy generation time, resulting in costly and labor-intensive maintenance of breeding programs. In a grapevine (genus Vitis) breeding program, although experimental populations are typically unrepli...

Genetic dissection of powdery mildew resistance in interspecific half-sib grapevine families using SNP-based maps

USDA-ARS?s Scientific Manuscript database

Quantitative trait locus (QTL) identification in perennial fruit crops is impeded largely by their lengthy generation time, resulting in costly and labor-intensive maintenance of breeding programs. In a grapevine (genus Vitis) breeding program, although experimental families are typically unreplicat...

Potential of promotion of alleles by genome editing to improve quantitative traits in livestock breeding programs.

PubMed

Jenko, Janez; Gorjanc, Gregor; Cleveland, Matthew A; Varshney, Rajeev K; Whitelaw, C Bruce A; Woolliams, John A; Hickey, John M

2015-07-02

Genome editing (GE) is a method that enables specific nucleotides in the genome of an individual to be changed. To date, use of GE in livestock has focussed on simple traits that are controlled by a few quantitative trait nucleotides (QTN) with large effects. The aim of this study was to evaluate the potential of GE to improve quantitative traits that are controlled by many QTN, referred to here as promotion of alleles by genome editing (PAGE). Multiple scenarios were simulated to test alternative PAGE strategies for a quantitative trait. They differed in (i) the number of edits per sire (0 to 100), (ii) the number of edits per generation (0 to 500), and (iii) the extent of use of PAGE (i.e. editing all sires or only a proportion of them). The base line scenario involved selecting individuals on true breeding values (i.e., genomic selection only (GS only)-genomic selection with perfect accuracy) for several generations. Alternative scenarios complemented this base line scenario with PAGE (GS + PAGE). The effect of different PAGE strategies was quantified by comparing response to selection, changes in allele frequencies, the number of distinct QTN edited, the sum of absolute effects of the edited QTN per generation, and inbreeding. Response to selection after 20 generations was between 1.08 and 4.12 times higher with GS + PAGE than with GS only. Increases in response to selection were larger with more edits per sire and more sires edited. When the total resources for PAGE were limited, editing a few sires for many QTN resulted in greater response to selection and inbreeding compared to editing many sires for a few QTN. Between the scenarios GS only and GS + PAGE, there was little difference in the average change in QTN allele frequencies, but there was a major difference for the QTN with the largest effects. The sum of the effects of the edited QTN decreased across generations. This study showed that PAGE has great potential for application in livestock breeding programs, but inbreeding needs to be managed.

Mapping loci influencing blood pressure in the Framingham pedigrees using model-free LOD score analysis of a quantitative trait.

PubMed

Knight, Jo; North, Bernard V; Sham, Pak C; Curtis, David

2003-12-31

This paper presents a method of performing model-free LOD-score based linkage analysis on quantitative traits. It is implemented in the QMFLINK program. The method is used to perform a genome screen on the Framingham Heart Study data. A number of markers that show some support for linkage in our study coincide substantially with those implicated in other linkage studies of hypertension. Although the new method needs further testing on additional real and simulated data sets we can already say that it is straightforward to apply and may offer a useful complementary approach to previously available methods for the linkage analysis of quantitative traits.

Mapping loci influencing blood pressure in the Framingham pedigrees using model-free LOD score analysis of a quantitative trait

PubMed Central

Knight, Jo; North, Bernard V; Sham, Pak C; Curtis, David

2003-01-01

This paper presents a method of performing model-free LOD-score based linkage analysis on quantitative traits. It is implemented in the QMFLINK program. The method is used to perform a genome screen on the Framingham Heart Study data. A number of markers that show some support for linkage in our study coincide substantially with those implicated in other linkage studies of hypertension. Although the new method needs further testing on additional real and simulated data sets we can already say that it is straightforward to apply and may offer a useful complementary approach to previously available methods for the linkage analysis of quantitative traits. PMID:14975142

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.

Genome-wide QTL analysis for anxiety trait in bipolar disorder type I.

PubMed

Contreras, J; Hare, E; Chavarría-Soley, G; Raventós, H

2018-07-01

Genetic studies have been consistent that bipolar disorder type I (BPI) runs in families and that this familial aggregation is strongly influenced by genes. In a preliminary study, we proved that anxiety trait meets endophenotype criteria for BPI. We assessed 619 individuals from the Central Valley of Costa Rica (CVCR) who have received evaluation for anxiety following the same methodological procedure used for the initial pilot study. Our goal was to conduct a multipoint quantitative trait linkage analysis to identify quantitative trait loci (QTLs) related to anxiety trait in subjects with BPI. We conducted the statistical analyses using Quantitative Trait Loci method (Variance-components models), implemented in Sequential Oligogenic Linkage Analysis Routines (SOLAR), using 5606 single nucleotide polymorphism (SNPs). We identified a suggestive linkage signal with a LOD score of 2.01 at chromosome 2 (2q13-q14). Since confounding factors such as substance abuse, medical illness and medication history were not assessed in our study, these conclusions should be taken as preliminary. We conclude that region 2q13-q14 may harbor a candidate gene(s) with an important role in the pathophysiology of BPI and anxiety. Published by Elsevier B.V.

Genetic and Quantitative Trait Locus Analysis for Bio-Oil Compounds after Fast Pyrolysis in Maize Cobs.

PubMed

Jeffrey, Brandon; Kuzhiyil, Najeeb; de Leon, Natalia; Lübberstedt, Thomas

2016-01-01

Fast pyrolysis has been identified as one of the biorenewable conversion platforms that could be a part of an alternative energy future, but it has not yet received the same attention as cellulosic ethanol in the analysis of genetic inheritance within potential feedstocks such as maize. Ten bio-oil compounds were measured via pyrolysis/gas chromatography-mass spectrometry (Py/GC-MS) in maize cobs. 184 recombinant inbred lines (RILs) of the intermated B73 x Mo17 (IBM) Syn4 population were analyzed in two environments, using 1339 markers, for quantitative trait locus (QTL) mapping. QTL mapping was performed using composite interval mapping with significance thresholds established by 1000 permutations at α = 0.05. 50 QTL were found in total across those ten traits with R2 values ranging from 1.7 to 5.8%, indicating a complex quantitative inheritance of these traits.

Detecting QTLs and putative candidate genes involved in budbreak and flowering time in an apple multiparental population

PubMed Central

Allard, Alix; Bink, Marco C.A.M.; Martinez, Sébastien; Kelner, Jean-Jacques; Legave, Jean-Michel; di Guardo, Mario; Di Pierro, Erica A.; Laurens, François; van de Weg, Eric W.; Costes, Evelyne

2016-01-01

In temperate trees, growth resumption in spring time results from chilling and heat requirements, and is an adaptive trait under global warming. Here, the genetic determinism of budbreak and flowering time was deciphered using five related full-sib apple families. Both traits were observed over 3 years and two sites and expressed in calendar and degree-days. Best linear unbiased predictors of genotypic effect or interaction with climatic year were extracted from mixed linear models and used for quantitative trait locus (QTL) mapping, performed with an integrated genetic map containing 6849 single nucleotide polymorphisms (SNPs), grouped into haplotypes, and with a Bayesian pedigree-based analysis. Four major regions, on linkage group (LG) 7, LG10, LG12, and LG9, the latter being the most stable across families, sites, and years, explained 5.6–21.3% of trait variance. Co-localizations for traits in calendar days or growing degree hours (GDH) suggested common genetic determinism for chilling and heating requirements. Homologs of two major flowering genes, AGL24 and FT, were predicted close to LG9 and LG12 QTLs, respectively, whereas Dormancy Associated MADs-box (DAM) genes were near additional QTLs on LG8 and LG15. This suggests that chilling perception mechanisms could be common among perennial and annual plants. Progenitors with favorable alleles depending on trait and LG were identified and could benefit new breeding strategies for apple adaptation to temperature increase. PMID:27034326

Quantitative Trait Loci for Yield and Yield-Related Traits in Spring Barley Populations Derived from Crosses between European and Syrian Cultivars

PubMed Central

Krystkowiak, Karolina; Sawikowska, Aneta; Frohmberg, Wojciech; Górny, Andrzej; Kędziora, Andrzej; Jankowiak, Janusz; Józefczyk, Damian; Karg, Grzegorz; Andrusiak, Joanna; Krajewski, Paweł; Szarejko, Iwona; Surma, Maria; Adamski, Tadeusz; Guzy-Wróbelska, Justyna; Kuczyńska, Anetta

2016-01-01

In response to climatic changes, breeding programmes should be aimed at creating new cultivars with improved resistance to water scarcity. The objective of this study was to examine the yield potential of barley recombinant inbred lines (RILs) derived from three cross-combinations of European and Syrian spring cultivars, and to identify quantitative trait loci (QTLs) for yield-related traits in these populations. RILs were evaluated in field experiments over a period of three years (2011 to 2013) and genotyped with simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers; a genetic map for each population was constructed and then one consensus map was developed. Biological interpretation of identified QTLs was achieved by reference to Ensembl Plants barley gene space. Twelve regions in the genomes of studied RILs were distinguished after QTL analysis. Most of the QTLs were identified on the 2H chromosome, which was the hotspot region in all three populations. Syrian parental cultivars contributed alleles decreasing traits' values at majority of QTLs for grain weight, grain number, spike length and time to heading, and numerous alleles increasing stem length. The phenomic and molecular approaches distinguished the lines with an acceptable grain yield potential combining desirable features or alleles from their parents, that is, early heading from the Syrian breeding line (Cam/B1/CI08887//CI05761) and short plant stature from the European semidwarf cultivar (Maresi). PMID:27227880

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

PubMed

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

2016-01-01

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

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

PubMed Central

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

2016-01-01

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

Mapping of quantitative trait loci associated with partial resistance to phytophthora sojae and flooding tolerance in soybean

USDA-ARS?s Scientific Manuscript database

Phytophthora root rot (PRR) caused by Phytophthora sojae Kaufm. & Gerd. and flooding can limit growth and productivity, of soybean [Glycine max (L.) Merr.], especially on poorly drained soils. The primary objective of this research project was to map quantitative trait loci (QTL) associated with f...

CBCL Pediatric Bipolar Disorder Profile and ADHD: Comorbidity and Quantitative Trait Loci Analysis

ERIC Educational Resources Information Center

McGough, James J.; Loo, Sandra K.; McCracken, James T.; Dang, Jeffery; Clark, Shaunna; Nelson, Stanley F.; Smalley, Susan L.

2008-01-01

The pediatric bipolar disorder profile of the Child Behavior checklist is used to differentiate patterns of comorbidity and to search for quantitative trait loci in multiple affected ADHD sibling pairs. The CBCL-PBD profiling identified 8 percent of individuals with severe psychopathology and increased rates of oppositional defiant, conduct and…

Multi-ethnic meta-analysis identifies RAI1 as a possible obstructive sleep apnea related quantitative trait locus in men

USDA-ARS?s Scientific Manuscript database

Obstructive sleep apnea (OSA) is a common heritable disorder displaying marked sexual dimorphism in disease prevalence and progression. Previous genetic association studies have identified a few genetic loci associated with OSA and related quantitative traits, but they have only focused on single et...

Genes and quantitative trait loci (QTL) controlling trace element concentrations in perennial grasses grown on phytotoxic soil contaminated with heavy metals

USDA-ARS?s Scientific Manuscript database

Perennial grasses cover diverse soils throughout the world, including sites contaminated with heavy metals, producing forages that must be safe for livestock and wildlife. Chromosome regions known as quantitative trait loci (QTLs) controlling forage mineral concentrations were mapped in a populatio...

Mapping of quantitative trait loci for resistance to fall armyworm and southwestern corn borer leaf-feeding damage in maize.

USDA-ARS?s Scientific Manuscript database

Fall armyworm (FAW), Spodoptera frugiperda (J. E. Smith), and southwestern corn borer (SWCB), Diatraea grandiosella Dyar are damaging insect pests of maize resulting in significant yield and economic losses. A previous study identified quantitative trait loci (QTL) that contribute to reduced leaf-fe...

Confirmatory Factor Analytic Structure and Measurement Invariance of Quantitative Autistic Traits Measured by the Social Responsiveness Scale-2

ERIC Educational Resources Information Center

Frazier, Thomas W.; Ratliff, Kristin R.; Gruber, Chris; Zhang, Yi; Law, Paul A.; Constantino, John N.

2014-01-01

Understanding the factor structure of autistic symptomatology is critical to the discovery and interpretation of causal mechanisms in autism spectrum disorder. We applied confirmatory factor analysis and assessment of measurement invariance to a large ("N" = 9635) accumulated collection of reports on quantitative autistic traits using…

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

Functional traits and ecological affinities of riparian plants along the Colorado River in Grand Canyon

USGS Publications Warehouse

Palmquist, Emily C.; Ralston, Barbara E.; Sarr. Daniel,; Merritt, David; Shafroth, Patrick B; Scott, Julian

2017-01-01

Trait-based approaches to vegetation analyses are becoming more prevalent in studies of riparian vegetation dynamics, including responses to flow regulation, groundwater pumping, and climate change. These analyses require species trait data compiled from the literature and floras or original field measurements. Gathering such data makes trait-based research time intensive at best and impracticable in some cases. To support trait-based analysis of vegetation along the Colorado River through Grand Canyon, a data set of 20 biological traits and ecological affinities for 179 species occurring in that study area was compiled. This diverse flora shares species with many riparian areas in the western USA and includes species that occur across a wide moisture gradient. Data were compiled from published scientific papers, unpublished reports, plant fact sheets, existing trait databases, regional floras, and plant guides. Data for ordinal environmental tolerances were more readily available than were quantitative traits. More publicly available data are needed for traits of both common and rare southwestern U.S. plant species to facilitate comprehensive, trait-based research. The trait data set is free to use and can be downloaded from ScienceBase: https://www.sciencebase.gov/catalog/item/58af41dee4b01ccd54f9f2ff and https://dx.doi.org/10.5066/F7QV3JN1

Quantitative autistic trait measurements index background genetic risk for ASD in Hispanic families.

PubMed

Page, Joshua; Constantino, John Nicholas; Zambrana, Katherine; Martin, Eden; Tunc, Ilker; Zhang, Yi; Abbacchi, Anna; Messinger, Daniel

2016-01-01

Recent studies have indicated that quantitative autistic traits (QATs) of parents reflect inherited liabilities that may index background genetic risk for clinical autism spectrum disorder (ASD) in their offspring. Moreover, preferential mating for QATs has been observed as a potential factor in concentrating autistic liabilities in some families across generations. Heretofore, intergenerational studies of QATs have focused almost exclusively on Caucasian populations-the present study explored these phenomena in a well-characterized Hispanic population. The present study examined QAT scores in siblings and parents of 83 Hispanic probands meeting research diagnostic criteria for ASD, and 64 non-ASD controls, using the Social Responsiveness Scale-2 (SRS-2). Ancestry of the probands was characterized by genotype, using information from 541,929 single nucleotide polymorphic markers. In families of Hispanic children with an ASD diagnosis, the pattern of quantitative trait correlations observed between ASD-affected children and their first-degree relatives (ICCs on the order of 0.20), between unaffected first-degree relatives in ASD-affected families (sibling/mother ICC = 0.36; sibling/father ICC = 0.53), and between spouses (mother/father ICC = 0.48) were in keeping with the influence of transmitted background genetic risk and strong preferential mating for variation in quantitative autistic trait burden. Results from analysis of ancestry-informative genetic markers among probands in this sample were consistent with that from other Hispanic populations. Quantitative autistic traits represent measurable indices of inherited liability to ASD in Hispanic families. The accumulation of autistic traits occurs within generations, between spouses, and across generations, among Hispanic families affected by ASD. The occurrence of preferential mating for QATs-the magnitude of which may vary across cultures-constitutes a mechanism by which background genetic liability for ASD can accumulate in a given family in successive generations.

Quantitative trait loci analyses and RNA-seq identify genes affecting stress response in rainbow trout

USDA-ARS?s Scientific Manuscript database

Genomic analyses have the potential to impact aquaculture production traits by identifying markers as proxies for traits which are expensive or difficult to measure and characterizing genetic variation and biochemical mechanisms underlying phenotypic variation. One such trait is the response of rai...

A traits-based approach for prioritizing species for monitoring and surrogacy selection

DOE PAGES

Pracheil, Brenda M.; McManamay, Ryan A.; Bevelhimer, Mark S.; ...

2016-11-28

The bar for justifying the use of vertebrate animals for study is being increasingly raised, thus requiring increased rigor for species selection and study design. Although we have power analyses to provide quantitative backing for the numbers of organisms used, quantitative backing for selection of study species is not frequently employed. This can be especially important when measuring the impacts of ecosystem alteration, when study species must be chosen that are both sensitive to the alteration and of sufficient abundance for study. Just as important is providing justification for designation of surrogate species for study, especially when the species ofmore » interest is rare or of conservation concern and selection of an appropriate surrogate can have legal implications. In this study, we use a combination of GIS, a fish traits database and multivariate statistical analyses to quantitatively prioritize species for study and to determine potential study surrogate species. We provide two case studies to illustrate our quantitative, traits-based approach for designating study species and surrogate species. In the first case study, we select broadly representative fish species to understand the effects of turbine passage on adult fishes based on traits that suggest sensitivity to turbine passage. In our second case study, we present a framework for selecting a surrogate species for an endangered species. Lastly, we suggest that our traits-based framework can provide quantitative backing and added justification to selection of study species while expanding the inference space of study results.« less

A traits-based approach for prioritizing species for monitoring and surrogacy selection

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

Pracheil, Brenda M.; McManamay, Ryan A.; Bevelhimer, Mark S.

The bar for justifying the use of vertebrate animals for study is being increasingly raised, thus requiring increased rigor for species selection and study design. Although we have power analyses to provide quantitative backing for the numbers of organisms used, quantitative backing for selection of study species is not frequently employed. This can be especially important when measuring the impacts of ecosystem alteration, when study species must be chosen that are both sensitive to the alteration and of sufficient abundance for study. Just as important is providing justification for designation of surrogate species for study, especially when the species ofmore » interest is rare or of conservation concern and selection of an appropriate surrogate can have legal implications. In this study, we use a combination of GIS, a fish traits database and multivariate statistical analyses to quantitatively prioritize species for study and to determine potential study surrogate species. We provide two case studies to illustrate our quantitative, traits-based approach for designating study species and surrogate species. In the first case study, we select broadly representative fish species to understand the effects of turbine passage on adult fishes based on traits that suggest sensitivity to turbine passage. In our second case study, we present a framework for selecting a surrogate species for an endangered species. Lastly, we suggest that our traits-based framework can provide quantitative backing and added justification to selection of study species while expanding the inference space of study results.« less

An eQTL Analysis of Partial Resistance to Puccinia hordei in Barley

PubMed Central

Chen, Xinwei; Hackett, Christine A.; Niks, Rients E.; Hedley, Peter E.; Booth, Clare; Druka, Arnis; Marcel, Thierry C.; Vels, Anton; Bayer, Micha; Milne, Iain; Morris, Jenny; Ramsay, Luke; Marshall, David; Cardle, Linda; Waugh, Robbie

2010-01-01

Background Genetic resistance to barley leaf rust caused by Puccinia hordei involves both R genes and quantitative trait loci. The R genes provide higher but less durable resistance than the quantitative trait loci. Consequently, exploring quantitative or partial resistance has become a favorable alternative for controlling disease. Four quantitative trait loci for partial resistance to leaf rust have been identified in the doubled haploid Steptoe (St)/Morex (Mx) mapping population. Further investigations are required to study the molecular mechanisms underpinning partial resistance and ultimately identify the causal genes. Methodology/Principal Findings We explored partial resistance to barley leaf rust using a genetical genomics approach. We recorded RNA transcript abundance corresponding to each probe on a 15K Agilent custom barley microarray in seedlings from St and Mx and 144 doubled haploid lines of the St/Mx population. A total of 1154 and 1037 genes were, respectively, identified as being P. hordei-responsive among the St and Mx and differentially expressed between P. hordei-infected St and Mx. Normalized ratios from 72 distant-pair hybridisations were used to map the genetic determinants of variation in transcript abundance by expression quantitative trait locus (eQTL) mapping generating 15685 eQTL from 9557 genes. Correlation analysis identified 128 genes that were correlated with resistance, of which 89 had eQTL co-locating with the phenotypic quantitative trait loci (pQTL). Transcript abundance in the parents and conservation of synteny with rice allowed us to prioritise six genes as candidates for Rphq11, the pQTL of largest effect, and highlight one, a phospholipid hydroperoxide glutathione peroxidase (HvPHGPx) for detailed analysis. Conclusions/Significance The eQTL approach yielded information that led to the identification of strong candidate genes underlying pQTL for resistance to leaf rust in barley and on the general pathogen response pathway. The dataset will facilitate a systems appraisal of this host-pathogen interaction and, potentially, for other traits measured in this population. PMID:20066049

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

PubMed

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

2013-12-01

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

Novel Autism Subtype-Dependent Genetic Variants Are Revealed by Quantitative Trait and Subphenotype Association Analyses of Published GWAS Data

PubMed Central

Hu, Valerie W.; Addington, Anjene; Hyman, Alexander

2011-01-01

The heterogeneity of symptoms associated with autism spectrum disorders (ASDs) has presented a significant challenge to genetic analyses. Even when associations with genetic variants have been identified, it has been difficult to associate them with a specific trait or characteristic of autism. Here, we report that quantitative trait analyses of ASD symptoms combined with case-control association analyses using distinct ASD subphenotypes identified on the basis of symptomatic profiles result in the identification of highly significant associations with 18 novel single nucleotide polymorphisms (SNPs). The symptom categories included deficits in language usage, non-verbal communication, social development, and play skills, as well as insistence on sameness or ritualistic behaviors. Ten of the trait-associated SNPs, or quantitative trait loci (QTL), were associated with more than one subtype, providing partial replication of the identified QTL. Notably, none of the novel SNPs is located within an exonic region, suggesting that these hereditary components of ASDs are more likely related to gene regulatory processes (or gene expression) than to structural or functional changes in gene products. Seven of the QTL reside within intergenic chromosomal regions associated with rare copy number variants that have been previously reported in autistic samples. Pathway analyses of the genes associated with the QTL identified in this study implicate neurological functions and disorders associated with autism pathophysiology. This study underscores the advantage of incorporating both quantitative traits as well as subphenotypes into large-scale genome-wide analyses of complex disorders. PMID:21556359

Genetic Architecture of Micro-Environmental Plasticity in Drosophila melanogaster.

PubMed

Morgante, Fabio; Sørensen, Peter; Sorensen, Daniel A; Maltecca, Christian; Mackay, Trudy F C

2015-05-06

Individuals of the same genotype do not have the same phenotype for quantitative traits when reared under common macro-environmental conditions, a phenomenon called micro-environmental plasticity. Genetic variation in micro-environmental plasticity is assumed in models of the evolution of phenotypic variance, and is important in applied breeding and personalized medicine. Here, we quantified genetic variation for micro-environmental plasticity for three quantitative traits in the inbred, sequenced lines of the Drosophila melanogaster Genetic Reference Panel. We found substantial genetic variation for micro-environmental plasticity for all traits, with broad sense heritabilities of the same magnitude or greater than those of trait means. Micro-environmental plasticity is not correlated with residual segregating variation, is trait-specific, and has genetic correlations with trait means ranging from zero to near unity. We identified several candidate genes associated with micro-environmental plasticity of startle response, including Drosophila Hsp90, setting the stage for future genetic dissection of this phenomenon.

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.

The evolution of labile traits in sex- and age-structured populations.

PubMed

Childs, Dylan Z; Sheldon, Ben C; Rees, Mark

2016-03-01

Many quantitative traits are labile (e.g. somatic growth rate, reproductive timing and investment), varying over the life cycle as a result of behavioural adaptation, developmental processes and plastic responses to the environment. At the population level, selection can alter the distribution of such traits across age classes and among generations. Despite a growing body of theoretical research exploring the evolutionary dynamics of labile traits, a data-driven framework for incorporating such traits into demographic models has not yet been developed. Integral projection models (IPMs) are increasingly being used to understand the interplay between changes in labile characters, life histories and population dynamics. One limitation of the IPM approach is that it relies on phenotypic associations between parents and offspring traits to capture inheritance. However, it is well-established that many different processes may drive these associations, and currently, no clear consensus has emerged on how to model micro-evolutionary dynamics in an IPM framework. We show how to embed quantitative genetic models of inheritance of labile traits into age-structured, two-sex models that resemble standard IPMs. Commonly used statistical tools such as GLMs and their mixed model counterparts can then be used for model parameterization. We illustrate the methodology through development of a simple model of egg-laying date evolution, parameterized using data from a population of Great tits (Parus major). We demonstrate how our framework can be used to project the joint dynamics of species' traits and population density. We then develop a simple extension of the age-structured Price equation (ASPE) for two-sex populations, and apply this to examine the age-specific contributions of different processes to change in the mean phenotype and breeding value. The data-driven framework we outline here has the potential to facilitate greater insight into the nature of selection and its consequences in settings where focal traits vary over the lifetime through ontogeny, behavioural adaptation and phenotypic plasticity, as well as providing a potential bridge between theoretical and empirical studies of labile trait variation. © 2016 The Authors Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.

SOME USES OF MODELS OF QUANTITATIVE GENETIC SELECTION IN SOCIAL SCIENCE.

PubMed

Weight, Michael D; Harpending, Henry

2017-01-01

The theory of selection of quantitative traits is widely used in evolutionary biology, agriculture and other related fields. The fundamental model known as the breeder's equation is simple, robust over short time scales, and it is often possible to estimate plausible parameters. In this paper it is suggested that the results of this model provide useful yardsticks for the description of social traits and the evaluation of transmission models. The differences on a standard personality test between samples of Old Order Amish and Indiana rural young men from the same county and the decline of homicide in Medieval Europe are used as illustrative examples of the overall approach. It is shown that the decline of homicide is unremarkable under a threshold model while the differences between rural Amish and non-Amish young men are too large to be a plausible outcome of simple genetic selection in which assortative mating by affiliation is equivalent to truncation selection.

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

PubMed

Careau, Vincent; Wolak, Matthew E; Carter, Patrick A; Garland, Theodore

2013-11-01

Replicated selection experiments provide a powerful way to study how "multiple adaptive solutions" may lead to differences in the quantitative-genetic architecture of selected traits and whether this may translate into differences in the timing at which evolutionary limits are reached. We analyze data from 31 generations (n=17,988) of selection on voluntary wheel running in house mice. The rate of initial response, timing of selection limit, and height of the plateau varied significantly between sexes and among the four selected lines. Analyses of litter size and realized selection differentials seem to rule out counterposing natural selection as a cause of the selection limits. Animal-model analyses showed that although the additive genetic variance was significantly lower in selected than control lines, both before and after the limits, the decrease was not sufficient to explain the limits. Moreover, directional selection promoted a negative covariance between additive and maternal genetic variance over the first 10 generations. These results stress the importance of replication in selection studies of higher-level traits and highlight the fact that long-term predictions of response to selection are not necessarily expected to be linear because of the variable effects of selection on additive genetic variance and maternal effects. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

Quantitative genetic bases of anthocyanin variation in grape (Vitis vinifera L. ssp. sativa) berry: a quantitative trait locus to quantitative trait nucleotide integrated study.

PubMed

Fournier-Level, Alexandre; Le Cunff, Loïc; Gomez, Camila; Doligez, Agnès; Ageorges, Agnès; Roux, Catherine; Bertrand, Yves; Souquet, Jean-Marc; Cheynier, Véronique; This, Patrice

2009-11-01

The combination of QTL mapping studies of synthetic lines and association mapping studies of natural diversity represents an opportunity to throw light on the genetically based variation of quantitative traits. With the positional information provided through quantitative trait locus (QTL) mapping, which often leads to wide intervals encompassing numerous genes, it is now feasible to directly target candidate genes that are likely to be responsible for the observed variation in completely sequenced genomes and to test their effects through association genetics. This approach was performed in grape, a newly sequenced genome, to decipher the genetic architecture of anthocyanin content. Grapes may be either white or colored, ranging from the lightest pink to the darkest purple tones according to the amount of anthocyanin accumulated in the berry skin, which is a crucial trait for both wine quality and human nutrition. Although the determinism of the white phenotype has been fully identified, the genetic bases of the quantitative variation of anthocyanin content in berry skin remain unclear. A single QTL responsible for up to 62% of the variation in the anthocyanin content was mapped on a Syrah x Grenache F(1) pseudo-testcross. Among the 68 unigenes identified in the grape genome within the QTL interval, a cluster of four Myb-type genes was selected on the basis of physiological evidence (VvMybA1, VvMybA2, VvMybA3, and VvMybA4). From a core collection of natural resources (141 individuals), 32 polymorphisms revealed significant association, and extended linkage disequilibrium was observed. Using a multivariate regression method, we demonstrated that five polymorphisms in VvMybA genes except VvMybA4 (one retrotransposon, three single nucleotide polymorphisms and one 2-bp insertion/deletion) accounted for 84% of the observed variation. All these polymorphisms led to either structural changes in the MYB proteins or differences in the VvMybAs promoters. We concluded that the continuous variation in anthocyanin content in grape was explained mainly by a single gene cluster of three VvMybA genes. The use of natural diversity helped to reduce one QTL to a set of five quantitative trait nucleotides and gave a clear picture of how isogenes combined their effects to shape grape color. Such analysis also illustrates how isogenes combine their effect to shape a complex quantitative trait and enables the definition of markers directly targeted for upcoming breeding programs.

General Methods for Evolutionary Quantitative Genetic Inference from Generalized Mixed Models.

PubMed

de Villemereuil, Pierre; Schielzeth, Holger; Nakagawa, Shinichi; Morrissey, Michael

2016-11-01

Methods for inference and interpretation of evolutionary quantitative genetic parameters, and for prediction of the response to selection, are best developed for traits with normal distributions. Many traits of evolutionary interest, including many life history and behavioral traits, have inherently nonnormal distributions. The generalized linear mixed model (GLMM) framework has become a widely used tool for estimating quantitative genetic parameters for nonnormal traits. However, whereas GLMMs provide inference on a statistically convenient latent scale, it is often desirable to express quantitative genetic parameters on the scale upon which traits are measured. The parameters of fitted GLMMs, despite being on a latent scale, fully determine all quantities of potential interest on the scale on which traits are expressed. We provide expressions for deriving each of such quantities, including population means, phenotypic (co)variances, variance components including additive genetic (co)variances, and parameters such as heritability. We demonstrate that fixed effects have a strong impact on those parameters and show how to deal with this by averaging or integrating over fixed effects. The expressions require integration of quantities determined by the link function, over distributions of latent values. In general cases, the required integrals must be solved numerically, but efficient methods are available and we provide an implementation in an R package, QGglmm. We show that known formulas for quantities such as heritability of traits with binomial and Poisson distributions are special cases of our expressions. Additionally, we show how fitted GLMM can be incorporated into existing methods for predicting evolutionary trajectories. We demonstrate the accuracy of the resulting method for evolutionary prediction by simulation and apply our approach to data from a wild pedigreed vertebrate population. Copyright © 2016 de Villemereuil et al.

Validation of a major quantitative trait locus associated with host response to experimental infection with Porcine Reproductive and Respiratory Syndrome virus

USDA-ARS?s Scientific Manuscript database

Infectious diseases are costly to the swine industry and porcine reproductive and respiratory syndrome virus (PRRSV) is the most devastating. In earlier work, a quantitative trait locus associated with resistance/susceptibility to PRRSV was identified on Sus scrofa chromosome 4 (SSC4) using ~560 exp...

Use of single nucleotide polymorphisms (SNP) to fine-map quantitative trait loci (QTL) in swine

USDA-ARS?s Scientific Manuscript database

Mapping quantitative trait loci (QTL) in swine at the US Meat Animal Research Center has relied heavily on linkage mapping in either F2 or Backcross families. QTL identified in the initial scans typically have very broad confidence intervals and further refinement of the QTL’s position is needed bef...

Educational Software for Mapping Quantitative Trait Loci (QTL)

ERIC Educational Resources Information Center

Helms, T. C.; Doetkott, C.

2007-01-01

This educational software was developed to aid teachers and students in their understanding of how the process of identifying the most likely quantitative trait loci (QTL) position is determined between two flanking DNA markers. The objective of the software that we developed was to: (1) show how a QTL is mapped to a position on a chromosome using…

The IQ Quantitative Trait Loci Project: A Critique.

ERIC Educational Resources Information Center

King, David

1998-01-01

Describes the IQ Quantitative Trait Loci (QTL) project, an attempt to identify genes underlying IQ score variations using maps from the Human Genome Project. The essay argues against funding the IQ QTL project because it will end the debates about the genetic basis of intelligence and may lead directly to eugenic programs of genetic testing. (SLD)

Mapping and validation of quantitative trait loci associated with concentrations of 16 elements in unmilled rice grain

USDA-ARS?s Scientific Manuscript database

In this study, quantitative trait loci (QTLs) affecting the concentrations of 16 elements in whole, unmilled rice (Oryza sativa L.) grain were identified. Two rice mapping populations, the ‘Lemont’ x ‘TeQing’ recombinant inbred lines (LT-RILs), and the TeQing-into-Lemont backcross introgression lin...

Validation and Estimation of Additive Genetic Variation Associated with DNA Tests for Quantitative Beef Cattle Traits

USDA-ARS?s Scientific Manuscript database

The U.S. National Beef Cattle Evaluation Consortium (NBCEC) has been involved in the validation of commercial DNA tests for quantitative beef quality traits since their first appearance on the U.S. market in the early 2000s. The NBCEC Advisory Council initially requested that the NBCEC set up a syst...

Quantitative trait loci for seed isoflavones contents in 'MD96-5722' by 'Spencer' recombinant inbred lines of soybean

USDA-ARS?s Scientific Manuscript database

Isoflavones from soybeans (Glycine max L. Merr.) have significant impact on human health in reducing the risk of several major diseases. Breeding soybean for high isoflavones content in the seed is possible through marker assisted selection (MAS), which can be based on quantitative trait loci (QTL)....

Identification of quantitative trait loci (QTL) controlling protein, oil, and five major fatty acids’ contents in soybean

USDA-ARS?s Scientific Manuscript database

Improved seed composition in soybean (Glycine max L. Merr.) for protein and oil quality is one of the major goals of soybean breeders. A group of genes that act as quantitative traits with their effects can alter protein, oil, palmitic, stearic, oleic, linoleic, and linolenic acids percentage in soy...

The relationship between nature relatedness and anxiety.

PubMed

Martyn, Patricia; Brymer, Eric

2016-07-01

This study investigated the relationship between anxiety and feelings of being connected to nature. Two standardised self-report scales, the Nature Relatedness Scale and the State Trait Inventory for Cognitive and Somatic Anxiety, were used in tandem with a qualitative question. Quantitative results indicated that connection to nature was significantly related to lower levels of overall, state cognitive and trait cognitive anxiety. Qualitative results revealed seven themes: relaxation, time out, enjoyment, connection, expanse, sensory engagement and a healthy perspective. Taken together, these results suggest that opportunities that enhance experiences of being connected to nature may reduce unhelpful anxiety. © The Author(s) 2014.

Mapping complex traits as a dynamic system

PubMed Central

Sun, Lidan; Wu, Rongling

2017-01-01

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

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...

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

QTL mapping for flowering-time and photoperiod insensitivity of wild cotton Gossypium darwinii Watt

USDA-ARS?s Scientific Manuscript database

Most wild and semi-wild species of the genus Gossypium are sensitive to photoperiodism. The wild germplasm cotton collection is a valuable source of genes for genetic improvement of current cotton cultivars. For the purpose of identifying quantitative trait loci (QTLs) controlling flowering, a bi-pa...

A large scale joint analysis of flowering time reveals independent temperate adaptations in maize

USDA-ARS?s Scientific Manuscript database

Modulating days to flowering is a key mechanism in plants for adapting to new environments, and variation in days to flowering drives population structure by limiting mating. To elucidate the genetic architecture of flowering across maize, a quantitative trait, we mapped flowering in five global pop...

Detection of linkage between a quantitative trait and a marker locus by the lod score method: sample size and sampling considerations.

PubMed

Demenais, F; Lathrop, G M; Lalouel, J M

1988-07-01

A simulation study is here conducted to measure the power of the lod score method to detect linkage between a quantitative trait and a marker locus in various situations. The number of families necessary to detect such linkage with 80% power is assessed for different sets of parameters at the trait locus and different values of the recombination fraction. The effects of varying the mode of sampling families and the sibship size are also evaluated.

Genetic Dissection of Leaf Development in Brassica rapa Using a Genetical Genomics Approach1[W

PubMed Central

Xiao, Dong; Wang, Huange; Basnet, Ram Kumar; Zhao, Jianjun; Lin, Ke; Hou, Xilin; Bonnema, Guusje

2014-01-01

The paleohexaploid crop Brassica rapa harbors an enormous reservoir of morphological variation, encompassing leafy vegetables, vegetable and fodder turnips (Brassica rapa, ssp. campestris), and oil crops, with different crops having very different leaf morphologies. In the triplicated B. rapa genome, many genes have multiple paralogs that may be regulated differentially and contribute to phenotypic variation. Using a genetical genomics approach, phenotypic data from a segregating doubled haploid population derived from a cross between cultivar Yellow sarson (oil type) and cultivar Pak choi (vegetable type) were used to identify loci controlling leaf development. Twenty-five colocalized phenotypic quantitative trait loci (QTLs) contributing to natural variation for leaf morphological traits, leaf number, plant architecture, and flowering time were identified. Genetic analysis showed that four colocalized phenotypic QTLs colocalized with flowering time and leaf trait candidate genes, with their cis-expression QTLs and cis- or trans-expression QTLs for homologs of genes playing a role in leaf development in Arabidopsis (Arabidopsis thaliana). The leaf gene BRASSICA RAPA KIP-RELATED PROTEIN2_A03 colocalized with QTLs for leaf shape and plant height; BRASSICA RAPA ERECTA_A09 colocalized with QTLs for leaf color and leaf shape; BRASSICA RAPA LONGIFOLIA1_A10 colocalized with QTLs for leaf size, leaf color, plant branching, and flowering time; while the major flowering time gene, BRASSICA RAPA FLOWERING LOCUS C_A02, colocalized with QTLs explaining variation in flowering time, plant architectural traits, and leaf size. Colocalization of these QTLs points to pleiotropic regulation of leaf development and plant architectural traits in B. rapa. PMID:24394778

Genetic basis of climatic adaptation in scots pine by bayesian quantitative trait locus analysis.

PubMed Central

Hurme, P; Sillanpää, M J; Arjas, E; Repo, T; Savolainen, O

2000-01-01

We examined the genetic basis of large adaptive differences in timing of bud set and frost hardiness between natural populations of Scots pine. As a mapping population, we considered an "open-pollinated backcross" progeny by collecting seeds of a single F(1) tree (cross between trees from southern and northern Finland) growing in southern Finland. Due to the special features of the design (no marker information available on grandparents or the father), we applied a Bayesian quantitative trait locus (QTL) mapping method developed previously for outcrossed offspring. We found four potential QTL for timing of bud set and seven for frost hardiness. Bayesian analyses detected more QTL than ANOVA for frost hardiness, but the opposite was true for bud set. These QTL included alleles with rather large effects, and additionally smaller QTL were supported. The largest QTL for bud set date accounted for about a fourth of the mean difference between populations. Thus, natural selection during adaptation has resulted in selection of at least some alleles of rather large effect. PMID:11063704

How fast is fisheries-induced evolution? Quantitative analysis of modelling and empirical studies

PubMed Central

Audzijonyte, Asta; Kuparinen, Anna; Fulton, Elizabeth A

2013-01-01

A number of theoretical models, experimental studies and time-series studies of wild fish have explored the presence and magnitude of fisheries-induced evolution (FIE). While most studies agree that FIE is likely to be happening in many fished stocks, there are disagreements about its rates and implications for stock viability. To address these disagreements in a quantitative manner, we conducted a meta-analysis of FIE rates reported in theoretical and empirical studies. We discovered that rates of phenotypic change observed in wild fish are about four times higher than the evolutionary rates reported in modelling studies, but correlation between the rate of change and instantaneous fishing mortality (F) was very similar in the two types of studies. Mixed-model analyses showed that in the modelling studies traits associated with reproductive investment and growth evolved slower than rates related to maturation. In empirical observations age-at-maturation was changing faster than other life-history traits. We also found that, despite different assumption and modelling approaches, rates of evolution for a given F value reported in 10 of 13 modelling studies were not significantly different. PMID:23789026

Quantitative genetics

USDA-ARS?s Scientific Manuscript database

The majority of economically important traits targeted for cotton improvement are quantitatively inherited. In this chapter, the current state of cotton quantitative genetics is described and separated into four components. These components include: 1) traditional quantitative inheritance analysis, ...

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

PubMed

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

2014-01-01

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

Exploiting induced variation to dissect quantitative traits in barley.

PubMed

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

2010-04-01

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

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

PubMed

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

2017-08-01

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

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

PubMed

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

2009-10-01

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

On normality, ethnicity, and missing values in quantitative trait locus mapping

PubMed Central

Labbe, Aurélie; Wormald, Hanna

2005-01-01

Background This paper deals with the detection of significant linkage for quantitative traits using a variance components approach. Microsatellite markers were obtained for the Genetic Analysis Workshop 14 Collaborative Study on the Genetics of Alcoholism data. Ethnic heterogeneity, highly skewed quantitative measures, and a high rate of missing values are all present in this dataset and well known to impact upon linkage analysis. This makes it a good candidate for investigation. Results As expected, we observed a number of changes in LOD scores, especially for chromosomes 1, 7, and 18, along with the three factors studied. A dramatic example of such changes can be found in chromosome 7. Highly significant linkage to one of the quantitative traits became insignificant when a proper normalizing transformation of the trait was used and when analysis was carried out on an ethnically homogeneous subset of the original pedigrees. Conclusion In agreement with existing literature, transforming a trait to ensure normality using a Box-Cox transformation is highly recommended in order to avoid false-positive linkages. Furthermore, pedigrees should be sorted by ethnic groups and analyses should be carried out separately. Finally, one should be aware that the inclusion of covariates with a high rate of missing values reduces considerably the number of subjects included in the model. In such a case, the loss in power may be large. Imputation methods are then recommended. PMID:16451664

Is the child 'father of the man'? evaluating the stability of genetic influences across development.

PubMed

Ronald, Angelica

2011-11-01

This selective review considers findings in genetic research that have shed light on how genes operate across development. We will address the question of whether the child is 'father of the Man' from a genetic perspective. In other words, do the same genetic influences affect the same traits across development? Using a 'taster menu' approach and prioritizing newer findings on cognitive and behavioral traits, examples from the following genetic disciplines will be discussed: (a) developmental quantitative genetics (such as longitudinal twin studies), (b) neurodevelopmental genetic syndromes with known genetic causes (such as Williams syndrome), (c) developmental candidate gene studies (such as those that link infant and adult populations), (d) developmental genome-wide association studies (GWAS), and (e) DNA resequencing. Evidence presented here suggests that there is considerable genetic stability of cognitive and behavioral traits across development, but there is also evidence for genetic change. Quantitative genetic studies have a long history of assessing genetic continuity and change across development. It is now time for the newer, more technology-enabled fields such as GWAS and DNA resequencing also to take on board the dynamic nature of human behavior. 2011 Blackwell Publishing Ltd.

Inbreeding Depression and Male Survivorship in Drosophila: Implications for Senescence Theory

PubMed Central

Swindell, William R.; Bouzat, Juan L.

2006-01-01

The extent to which inbreeding depression affects longevity and patterns of survivorship is an important issue from several research perspectives, including evolutionary biology, conservation biology, and the genetic analysis of quantitative traits. However, few previous inbreeding depression studies have considered longevity as a focal life-history trait. We maintained laboratory populations of Drosophila melanogaster at census population sizes of 2 and 10 male-female pairs for up to 66 generations and performed repeated assays of male survivorship throughout this time period. On average, significant levels of inbreeding depression were observed for median life span and age-specific mortality. For age-specific mortality, the severity of inbreeding depression increased over the life span. We found that a baseline inbreeding load of 0.307 lethal equivalents per gamete affected age-specific mortality, and that this value increased at a rate of 0.046 per day of the life span. With respect to some survivorship parameters, the differentiation of lineages was nonlinear with respect to the inbreeding coefficient, which suggested that nonadditive genetic variation contributed to variation among lineages. These findings provide insights into the genetic basis of longevity as a quantitative trait and have implications regarding the mutation-accumulation evolutionary explanation of senescence. PMID:16204222

Detecting QTLs and putative candidate genes involved in budbreak and flowering time in an apple multiparental population.

PubMed

Allard, Alix; Bink, Marco C A M; Martinez, Sébastien; Kelner, Jean-Jacques; Legave, Jean-Michel; di Guardo, Mario; Di Pierro, Erica A; Laurens, François; van de Weg, Eric W; Costes, Evelyne

2016-04-01

In temperate trees, growth resumption in spring time results from chilling and heat requirements, and is an adaptive trait under global warming. Here, the genetic determinism of budbreak and flowering time was deciphered using five related full-sib apple families. Both traits were observed over 3 years and two sites and expressed in calendar and degree-days. Best linear unbiased predictors of genotypic effect or interaction with climatic year were extracted from mixed linear models and used for quantitative trait locus (QTL) mapping, performed with an integrated genetic map containing 6849 single nucleotide polymorphisms (SNPs), grouped into haplotypes, and with a Bayesian pedigree-based analysis. Four major regions, on linkage group (LG) 7, LG10, LG12, and LG9, the latter being the most stable across families, sites, and years, explained 5.6-21.3% of trait variance. Co-localizations for traits in calendar days or growing degree hours (GDH) suggested common genetic determinism for chilling and heating requirements. Homologs of two major flowering genes, AGL24 and FT, were predicted close to LG9 and LG12 QTLs, respectively, whereas Dormancy Associated MADs-box (DAM) genes were near additional QTLs on LG8 and LG15. This suggests that chilling perception mechanisms could be common among perennial and annual plants. Progenitors with favorable alleles depending on trait and LG were identified and could benefit new breeding strategies for apple adaptation to temperature increase. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Identification of quantitative trait loci affecting resistance to gastro-intestinal parasites in a double backcross population of Red Maasai and Dorper sheep

USDA-ARS?s Scientific Manuscript database

A genome-wide scan for quantitative trait loci (QTL) affecting gastrointestinal (GI) nematode resistance was completed using a double backcross sheep population derived from Red Maasai and Dorper ewes bred to F1 rams. These breeds were chosen, because Red Maasai sheep are known to be more tolerant ...

Quantitative Autism Traits in First Degree Relatives: Evidence for the Broader Autism Phenotype in Fathers, but Not in Mothers and Siblings

ERIC Educational Resources Information Center

De la Marche, Wouter; Noens, Ilse; Luts, Jan; Scholte, Evert; Van Huffel, Sabine; Steyaert, Jean

2012-01-01

Autism spectrum disorder (ASD) symptoms are present in unaffected relatives and individuals from the general population. Results are inconclusive, however, on whether unaffected relatives have higher levels of quantitative autism traits (QAT) or not. This might be due to differences in research populations, because behavioral data and molecular…

Identification of quantitative trait loci influencing wood specific gravity in an outbred pedigree of loblolly pine

Treesearch

A. Groover; M. Devey; T. Fiddler; J. Lee; R. Megraw; T. Mitchel-Olds; B. Sherman; S. Vujcic; C. Williams; D. Neale

1994-01-01

We report the identification of quantitative trait loci (QTL) influencing wood specific gravity (WSG) in an outbred pedigree of loblolly pine (Pinus taeda L.) . QTL mapping in an outcrossing species is complicated by the presence of multiple alleles (>2) at QTL and marker loci. Multiple alleles at QTL allow the examination of interaction among...

Quantitative traits and diversification.

PubMed

FitzJohn, Richard G

2010-12-01

Quantitative traits have long been hypothesized to affect speciation and extinction rates. For example, smaller body size or increased specialization may be associated with increased rates of diversification. Here, I present a phylogenetic likelihood-based method (quantitative state speciation and extinction [QuaSSE]) that can be used to test such hypotheses using extant character distributions. This approach assumes that diversification follows a birth-death process where speciation and extinction rates may vary with one or more traits that evolve under a diffusion model. Speciation and extinction rates may be arbitrary functions of the character state, allowing much flexibility in testing models of trait-dependent diversification. I test the approach using simulated phylogenies and show that a known relationship between speciation and a quantitative character could be recovered in up to 80% of the cases on large trees (500 species). Consistent with other approaches, detecting shifts in diversification due to differences in extinction rates was harder than when due to differences in speciation rates. Finally, I demonstrate the application of QuaSSE to investigate the correlation between body size and diversification in primates, concluding that clade-specific differences in diversification may be more important than size-dependent diversification in shaping the patterns of diversity within this group.

Mapping Quantitative Traits in Unselected Families: Algorithms and Examples

PubMed Central

Dupuis, Josée; Shi, Jianxin; Manning, Alisa K.; Benjamin, Emelia J.; Meigs, James B.; Cupples, L. Adrienne; Siegmund, David

2009-01-01

Linkage analysis has been widely used to identify from family data genetic variants influencing quantitative traits. Common approaches have both strengths and limitations. Likelihood ratio tests typically computed in variance component analysis can accommodate large families but are highly sensitive to departure from normality assumptions. Regression-based approaches are more robust but their use has primarily been restricted to nuclear families. In this paper, we develop methods for mapping quantitative traits in moderately large pedigrees. Our methods are based on the score statistic which in contrast to the likelihood ratio statistic, can use nonparametric estimators of variability to achieve robustness of the false positive rate against departures from the hypothesized phenotypic model. Because the score statistic is easier to calculate than the likelihood ratio statistic, our basic mapping methods utilize relatively simple computer code that performs statistical analysis on output from any program that computes estimates of identity-by-descent. This simplicity also permits development and evaluation of methods to deal with multivariate and ordinal phenotypes, and with gene-gene and gene-environment interaction. We demonstrate our methods on simulated data and on fasting insulin, a quantitative trait measured in the Framingham Heart Study. PMID:19278016

Additive QTLs on three chromosomes control flowering time in woodland strawberry (Fragaria vesca L.)

PubMed Central

Samad, Samia; Kurokura, Takeshi; Koskela, Elli; Toivainen, Tuomas; Patel, Vipul; Mouhu, Katriina; Sargent, Daniel James; Hytönen, Timo

2017-01-01

Flowering time is an important trait that affects survival, reproduction and yield in both wild and cultivated plants. Therefore, many studies have focused on the identification of flowering time quantitative trait locus (QTLs) in different crops, and molecular control of this trait has been extensively investigated in model species. Here we report the mapping of QTLs for flowering time and vegetative traits in a large woodland strawberry mapping population that was phenotyped both under field conditions and in a greenhouse after flower induction in the field. The greenhouse experiment revealed additive QTLs in three linkage groups (LG), two on both LG4 and LG7, and one on LG6 that explain about half of the flowering time variance in the population. Three of the QTLs were newly identified in this study, and one co-localized with the previously characterized FvTFL1 gene. An additional strong QTL corresponding to previously mapped PFRU was detected in both field and greenhouse experiments indicating that gene(s) in this locus can control the timing of flowering in different environments in addition to the duration of flowering and axillary bud differentiation to runners and branch crowns. Several putative flowering time genes were identified in these QTL regions that await functional validation. Our results indicate that a few major QTLs may control flowering time and axillary bud differentiation in strawberries. We suggest that the identification of causal genes in the diploid strawberry may enable fine tuning of flowering time and vegetative growth in the closely related octoploid cultivated strawberry. PMID:28580150

Quantitative Trait Loci Differentiating the Outbreeding Mimulus Guttatus from the Inbreeding M. Platycalyx

PubMed Central

Lin, J. Z.; Ritland, K.

1997-01-01

Theoretical predictions about the evolution of selfing depend on the genetic architecture of loci controlling selfing (monogenic vs. polygenic determination, large vs. small effect of alleles, dominance vs. recessiveness), and studies of such architecture are lacking. We inferred the genetic basis of mating system differences between the outbreeding Mimulus guttatus and the inbreeding M. platycalyx by quantitative trait locus (QTL) mapping using random amplified polymorphic DNA and isozyme markers. One to three QTL were detected for each of five mating system characters, and each QTL explained 7.6-28.6% of the phenotypic variance. Taken together, QTL accounted for up to 38% of the variation in mating system characters, and a large proportion of variation was unaccounted for. Inferred QTL often affected more than one trait, contributing to the genetic correlation between those traits. These results are consistent with the hypothesis that quantitative variation in plant mating system characters is primarily controlled by loci with small effect. PMID:9215912

Replication of linkage to quantitative trait loci: variation in location and magnitude of the lod score.

PubMed

Hsueh, W C; Göring, H H; Blangero, J; Mitchell, B D

2001-01-01

Replication of linkage signals from independent samples is considered an important step toward verifying the significance of linkage signals in studies of complex traits. The purpose of this empirical investigation was to examine the variability in the precision of localizing a quantitative trait locus (QTL) by analyzing multiple replicates of a simulated data set with the use of variance components-based methods. Specifically, we evaluated across replicates the variation in both the magnitude and the location of the peak lod scores. We analyzed QTLs whose effects accounted for 10-37% of the phenotypic variance in the quantitative traits. Our analyses revealed that the precision of QTL localization was directly related to the magnitude of the QTL effect. For a QTL with effect accounting for > 20% of total phenotypic variation, > 90% of the linkage peaks fall within 10 cM from the true gene location. We found no evidence that, for a given magnitude of the lod score, the presence of interaction influenced the precision of QTL localization.

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 ...

Intercontinental convergence of stream fish community traits along geomorphic and hydraulic gradients

USGS Publications Warehouse

Lamouroux, N.; Poff, N.L.; Angermeier, P.L.

2002-01-01

Community convergence across biogeographically distinct regions suggests the existence of key, repeated, evolutionary mechanisms relating community characteristics to the environment. However, convergence studies at the community level often involve only qualitative comparisons of the environment and may fail to identify which environmental variables drive community structure. We tested the hypothesis that the biological traits of fish communities on two continents (Europe and North America) are similarly related to environmental conditions. Specifically, from observations of individual fish made at the microhabitat scale (a few square meters) within French streams, we generated habitat preference models linking traits of fish species to local scale hydraulic conditions (Froude number), Using this information, we then predicted how hydraulics and geomorphology at the larger scale of stream reaches (several pool-riffle sequences) should quantitatively influence the trait composition of fish communities. Trait composition for fishes in stream reaches with low Froude number at low flow or high proportion of pools was predicted as nonbenthic, large, fecund, long-lived, nonstreamlined, and weak swimmers. We tested our predictions in contrasting stream reaches in France (n = 11) and Virginia, USA (n = 76), using analyses of covariance to quantify the relative influence of continent vs. physical habitat variables on fish traits. The reach-scale convergence analysis indicated that trait proportions in the communities differed between continents (up to 55% of the variance in each trait was explained by "continent"), partly due to distinct evolutionary histories. However, within continents, trait proportions were comparably related to the hydraulic and geomorphic variables (up to 54% of the variance within continents explained). In particular, a synthetic measure of fish traits in reaches was well explained (50% of its variance) by the Froude number independently of the continent. The effect of physical variables did not differ across continents for most traits, confirming our predictions qualitatively and quantitatively. Therefore, despite phylogenetic and historical differences between continents, fish communities of France and Virginia exhibit convergence in biological traits related to hydraulics and geomorphology. This convergence reflects morphological and behavioral adaptations to physical stress in streams. This study supports the existence of a habitat template for ecological strategies. Some key quantitative variables that define this habitat template can be identified by characterizing how individual organisms use their physical environment, and by using dimensionless physical variables that reveal common energetic properties in different systems. Overall, quantitative tests of community convergence are efficient tools to demonstrate that some community traits are predictable from environmental features.

Mapping of a quantitative trait locus for resistance against infectious salmon anaemia in Atlantic salmon (Salmo Salar): comparing survival analysis with analysis on affected/resistant data

PubMed Central

Moen, Thomas; Sonesson, Anna K; Hayes, Ben; Lien, Sigbjørn; Munck, Hege; Meuwissen, Theo HE

2007-01-01

Background Infectious Salmon Anaemia (ISA) is a viral disease affecting farmed Atlantic salmon (Salmo salar) worldwide. The identification of Quantitative Trait Loci (QTL) affecting resistance to the disease could improve our understanding of the genetics underlying the trait and provide a means for Marker-Assisted Selection. We previously performed a genome scan on commercial Atlantic salmon families challenge tested for ISA resistance, identifying several putative QTL. In the present study, we set out to validate the strongest of these QTL in a larger family material coming from the same challenge test, and to determine the position of the QTL by interval mapping. We also wanted to explore different ways of performing QTL analysis within a survival analysis framework (i.e. using time-to-event data), and to compare results using survival analysis with results from analysis on the dichotomous trait 'affected/resistant'. Results The QTL, located on Atlantic salmon linkage group 8 (following SALMAP notation), was confirmed in the new data set. Its most likely position was at a marker cluster containing markers BHMS130, BHMS170 and BHMS553. Significant segregation distortion was observed in the same region, but was shown to be unrelated to the QTL. A maximum likelihood procedure for identifying QTL, based on the Cox proportional hazard model, was developed. QTL mapping was also done using the Haley-Knott method (affected/resistant data), and within a variance-component framework (affected/resistant data and time-to-event data). In all cases, analysis using affected/resistant data gave stronger evidence for a QTL than did analysis using time-to-event data. Conclusion A QTL for resistance to Infectious Salmon Anaemia in Atlantic salmon was validated in this study, and its more precise location on linkage group eight was determined. The QTL explained 6% of the phenotypic variation in resistance to the disease. The linkage group also displayed significant segregation distortion. Survival models proved in this case not to be more suitable than models based on the dichotomous trait 'affected/resistant' for analysing the data. PMID:17697344

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

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

PubMed

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

2018-06-01

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

Molecular Dissection of a Major Gene Effect on a Quantitative Trait: The Level of Alcohol Dehydrogenase Expression in Drosophila Melanogaster

PubMed Central

Stam, L. F.; Laurie, C. C.

1996-01-01

A molecular mapping experiment shows that a major gene effect on a quantitative trait, the level of alcohol dehydrogenase expression in Drosophila melanogaster, is due to multiple polymorphisms within the Adh gene. These polymorphisms are located in an intron, the coding sequence, and the 3' untranslated region. Because of nonrandom associations among polymorphisms at different sites, the individual effects combine (in some cases epistatically) to produce ``superalleles'' with large effect. These results have implications for the interpretation of major gene effects detected by quantitative trait locus mapping methods. They show that large effects due to a single locus may be due to multiple associated polymorphisms (or sequential fixations in isolated populations) rather than individual mutations of large effect. PMID:8978044

Retrospective genomic analysis of sorghum adaptation to temperate-zone grain production.

PubMed

Thurber, Carrie S; Ma, Justin M; Higgins, Race H; Brown, Patrick J

2013-06-26

Sorghum is a tropical C4 cereal that recently adapted to temperate latitudes and mechanized grain harvest through selection for dwarfism and photoperiod-insensitivity. Quantitative trait loci for these traits have been introgressed from a dwarf temperate donor into hundreds of diverse sorghum landraces to yield the Sorghum Conversion lines. Here, we report the first comprehensive genomic analysis of the molecular changes underlying this adaptation. We apply genotyping-by-sequencing to 1,160 Sorghum Conversion lines and their exotic progenitors, and map donor introgressions in each Sorghum Conversion line. Many Sorghum Conversion lines carry unexpected haplotypes not found in either presumed parent. Genome-wide mapping of introgression frequencies reveals three genomic regions necessary for temperate adaptation across all Sorghum Conversion lines, containing the Dw1, Dw2, and Dw3 loci on chromosomes 9, 6, and 7 respectively. Association mapping of plant height and flowering time in Sorghum Conversion lines detects significant associations in the Dw1 but not the Dw2 or Dw3 regions. Subpopulation-specific introgression mapping suggests that chromosome 6 contains at least four loci required for temperate adaptation in different sorghum genetic backgrounds. The Dw1 region fractionates into separate quantitative trait loci for plant height and flowering time. Generating Sorghum Conversion lines has been accompanied by substantial unintended gene flow. Sorghum adaptation to temperate-zone grain production involves a small number of genomic regions, each containing multiple linked loci for plant height and flowering time. Further characterization of these loci will accelerate the adaptation of sorghum and related grasses to new production systems for food and fuel.

Current and future developments in patents for quantitative trait loci in dairy cattle.

PubMed

Weller, Joel I

2007-01-01

Many studies have proposed that rates of genetic gain in dairy cattle can be increased by direct selection on the individual quantitative loci responsible for the genetic variation in these traits, or selection on linked genetic markers. The development of DNA-level genetic markers has made detection of QTL nearly routine in all major livestock species. The studies that attempted to detect genes affecting quantitative traits can be divided into two categories: analysis of candidate genes, and genome scans based on within-family genetic linkage. To date, 12 patent cooperative treaty (PCT) and US patents have been registered for DNA sequences claimed to be associated with effects on economic traits in dairy cattle. All claim effects on milk production, but other traits are also included in some of the claims. Most of the sequences found by the candidate gene approach are of dubious validity, and have been repeated in only very few independent studies. The two missense mutations on chromosomes 6 and 14 affecting milk concentration derived from genome scans are more solidly based, but the claims are also disputed. A few PCT in dairy cattle are commercialized as genetic tests where commercial dairy farmers are the target market.

Sunflower Hybrid Breeding: From Markers to Genomic Selection

PubMed Central

Dimitrijevic, Aleksandra; Horn, Renate

2018-01-01

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

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

PubMed Central

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

2015-01-01

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

Genetic Architecture of Micro-Environmental Plasticity in Drosophila melanogaster

PubMed Central

Morgante, Fabio; Sørensen, Peter; Sorensen, Daniel A.; Maltecca, Christian; Mackay, Trudy F. C.

2015-01-01

Individuals of the same genotype do not have the same phenotype for quantitative traits when reared under common macro-environmental conditions, a phenomenon called micro-environmental plasticity. Genetic variation in micro-environmental plasticity is assumed in models of the evolution of phenotypic variance, and is important in applied breeding and personalized medicine. Here, we quantified genetic variation for micro-environmental plasticity for three quantitative traits in the inbred, sequenced lines of the Drosophila melanogaster Genetic Reference Panel. We found substantial genetic variation for micro-environmental plasticity for all traits, with broad sense heritabilities of the same magnitude or greater than those of trait means. Micro-environmental plasticity is not correlated with residual segregating variation, is trait-specific, and has genetic correlations with trait means ranging from zero to near unity. We identified several candidate genes associated with micro-environmental plasticity of startle response, including Drosophila Hsp90, setting the stage for future genetic dissection of this phenomenon. PMID:25943032

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

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

PubMed

Zhang, Xuehai; Huang, Chenglong; Wu, Di; Qiao, Feng; Li, Wenqiang; Duan, Lingfeng; Wang, Ke; Xiao, Yingjie; Chen, Guoxing; Liu, Qian; Xiong, Lizhong; Yang, Wanneng; Yan, Jianbing

2017-03-01

With increasing demand for novel traits in crop breeding, the plant research community faces the challenge of quantitatively analyzing the structure and function of large numbers of plants. A clear goal of high-throughput phenotyping is to bridge the gap between genomics and phenomics. In this study, we quantified 106 traits from a maize ( Zea mays ) recombinant inbred line population ( n = 167) across 16 developmental stages using the automatic phenotyping platform. Quantitative trait locus (QTL) mapping with a high-density genetic linkage map, including 2,496 recombinant bins, was used to uncover the genetic basis of these complex agronomic traits, and 988 QTLs have been identified for all investigated traits, including three QTL hotspots. Biomass accumulation and final yield were predicted using a combination of dissected traits in the early growth stage. These results reveal the dynamic genetic architecture of maize plant growth and enhance ideotype-based maize breeding and prediction. © 2017 American Society of Plant Biologists. All Rights Reserved.

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

PubMed Central

Huang, Chenglong; Wu, Di; Qiao, Feng; Li, Wenqiang; Duan, Lingfeng; Wang, Ke; Xiao, Yingjie; Chen, Guoxing; Liu, Qian; Yang, Wanneng

2017-01-01

With increasing demand for novel traits in crop breeding, the plant research community faces the challenge of quantitatively analyzing the structure and function of large numbers of plants. A clear goal of high-throughput phenotyping is to bridge the gap between genomics and phenomics. In this study, we quantified 106 traits from a maize (Zea mays) recombinant inbred line population (n = 167) across 16 developmental stages using the automatic phenotyping platform. Quantitative trait locus (QTL) mapping with a high-density genetic linkage map, including 2,496 recombinant bins, was used to uncover the genetic basis of these complex agronomic traits, and 988 QTLs have been identified for all investigated traits, including three QTL hotspots. Biomass accumulation and final yield were predicted using a combination of dissected traits in the early growth stage. These results reveal the dynamic genetic architecture of maize plant growth and enhance ideotype-based maize breeding and prediction. PMID:28153923

Autism traits in the RASopathies.

PubMed

Adviento, Brigid; Corbin, Iris L; Widjaja, Felicia; Desachy, Guillaume; Enrique, Nicole; Rosser, Tena; Risi, Susan; Marco, Elysa J; Hendren, Robert L; Bearden, Carrie E; Rauen, Katherine A; Weiss, Lauren A

2014-01-01

Mutations in Ras/mitogen-activated protein kinase (Ras/MAPK) pathway genes lead to a class of disorders known as RASopathies, including neurofibromatosis type 1 (NF1), Noonan syndrome (NS), Costello syndrome (CS), and cardio-facio-cutaneous syndrome (CFC). Previous work has suggested potential genetic and phenotypic overlap between dysregulation of Ras/MAPK signalling and autism spectrum disorders (ASD). Although the literature offers conflicting evidence for association of NF1 and autism, there has been no systematic evaluation of autism traits in the RASopathies as a class to support a role for germline Ras/MAPK activation in ASDs. We examined the association of autism traits with NF1, NS, CS and CFC, comparing affected probands with unaffected sibling controls and subjects with idiopathic ASDs using the qualitative Social Communication Questionnaire (SCQ) and the quantitative Social Responsiveness Scale (SRS). Each of the four major RASopathies showed evidence for increased qualitative and quantitative autism traits compared with sibling controls. Further, each RASopathy exhibited a distinct distribution of quantitative social impairment. Levels of social responsiveness show some evidence of correlation between sibling pairs, and autism-like impairment showed a male bias similar to idiopathic ASDs. Higher prevalence and severity of autism traits in RASopathies compared to unaffected siblings suggests that dysregulation of Ras/MAPK signalling during development may be implicated in ASD risk. Evidence for sex bias and potential sibling correlation suggests that autism traits in the RASopathies share characteristics with autism traits in the general population and clinical ASD population and can shed light on idiopathic ASDs.

Allelic-based gene-gene interaction associated with quantitative traits.

PubMed

Jung, Jeesun; Sun, Bin; Kwon, Deukwoo; Koller, Daniel L; Foroud, Tatiana M

2009-05-01

Recent studies have shown that quantitative phenotypes may be influenced not only by multiple single nucleotide polymorphisms (SNPs) within a gene but also by the interaction between SNPs at unlinked genes. We propose a new statistical approach that can detect gene-gene interactions at the allelic level which contribute to the phenotypic variation in a quantitative trait. By testing for the association of allelic combinations at multiple unlinked loci with a quantitative trait, we can detect the SNP allelic interaction whether or not it can be detected as a main effect. Our proposed method assigns a score to unrelated subjects according to their allelic combination inferred from observed genotypes at two or more unlinked SNPs, and then tests for the association of the allelic score with a quantitative trait. To investigate the statistical properties of the proposed method, we performed a simulation study to estimate type I error rates and power and demonstrated that this allelic approach achieves greater power than the more commonly used genotypic approach to test for gene-gene interaction. As an example, the proposed method was applied to data obtained as part of a candidate gene study of sodium retention by the kidney. We found that this method detects an interaction between the calcium-sensing receptor gene (CaSR), the chloride channel gene (CLCNKB) and the Na, K, 2Cl cotransporter gene (CLC12A1) that contributes to variation in diastolic blood pressure.

Parallel and serial computing tools for testing single-locus and epistatic SNP effects of quantitative traits in genome-wide association studies

PubMed Central

Ma, Li; Runesha, H Birali; Dvorkin, Daniel; Garbe, John R; Da, Yang

2008-01-01

Background Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers provide opportunities to detect epistatic SNPs associated with quantitative traits and to detect the exact mode of an epistasis effect. Computational difficulty is the main bottleneck for epistasis testing in large scale GWAS. Results The EPISNPmpi and EPISNP computer programs were developed for testing single-locus and epistatic SNP effects on quantitative traits in GWAS, including tests of three single-locus effects for each SNP (SNP genotypic effect, additive and dominance effects) and five epistasis effects for each pair of SNPs (two-locus interaction, additive × additive, additive × dominance, dominance × additive, and dominance × dominance) based on the extended Kempthorne model. EPISNPmpi is the parallel computing program for epistasis testing in large scale GWAS and achieved excellent scalability for large scale analysis and portability for various parallel computing platforms. EPISNP is the serial computing program based on the EPISNPmpi code for epistasis testing in small scale GWAS using commonly available operating systems and computer hardware. Three serial computing utility programs were developed for graphical viewing of test results and epistasis networks, and for estimating CPU time and disk space requirements. Conclusion The EPISNPmpi parallel computing program provides an effective computing tool for epistasis testing in large scale GWAS, and the epiSNP serial computing programs are convenient tools for epistasis analysis in small scale GWAS using commonly available computer hardware. PMID:18644146

Identification of Candidate Genes Underlying an Iron Efficiency Quantitative Trait Locus in Soybean1

PubMed Central

Peiffer, Gregory A.; King, Keith E.; Severin, Andrew J.; May, Gregory D.; Cianzio, Silvia R.; Lin, Shun Fu; Lauter, Nicholas C.; Shoemaker, Randy C.

2012-01-01

Prevalent on calcareous soils in the United States and abroad, iron deficiency is among the most common and severe nutritional stresses in plants. In soybean (Glycine max) commercial plantings, the identification and use of iron-efficient genotypes has proven to be the best form of managing this soil-related plant stress. Previous studies conducted in soybean identified a significant iron efficiency quantitative trait locus (QTL) explaining more than 70% of the phenotypic variation for the trait. In this research, we identified candidate genes underlying this QTL through molecular breeding, mapping, and transcriptome sequencing. Introgression mapping was performed using two related near-isogenic lines in which a region located on soybean chromosome 3 required for iron efficiency was identified. The region corresponds to the previously reported iron efficiency QTL. The location was further confirmed through QTL mapping conducted in this study. Transcriptome sequencing and quantitative real-time-polymerase chain reaction identified two genes encoding transcription factors within the region that were significantly induced in soybean roots under iron stress. The two induced transcription factors were identified as homologs of the subgroup lb basic helix-loop-helix (bHLH) genes that are known to regulate the strategy I response in Arabidopsis (Arabidopsis thaliana). Resequencing of these differentially expressed genes unveiled a significant deletion within a predicted dimerization domain. We hypothesize that this deletion disrupts the Fe-DEFICIENCY-INDUCED TRANSCRIPTION FACTOR (FIT)/bHLH heterodimer that has been shown to induce known iron acquisition genes. PMID:22319075

Orderly Change in a Stable World: The Antisocial Trait as a Chimera.

ERIC Educational Resources Information Center

Patterson, Gerald R.

1993-01-01

Used longitudinal data from Oregon Youth Study to examine quantitative and qualitative change. Used latent growth models to demonstrate changes in form and systematic changes in mean level for subgroup of boys. Factor analyses carried out at three ages showed that, over time, changes in form and addition of new problems were quantifiable and thus…

Genetic mapping and QTL analysis of agronomic traits in Indian Mucuna pruriens using an intraspecific F₂population.

PubMed

Mahesh, S; Leelambika, M; Jaheer, Md; Anithakumari, A M; Sathyanarayana, N

2016-03-01

Mucuna pruriens is a well-recognized agricultural and horticultural crop with important medicinal use. However, antinutritional factors in seed and adverse morphological characters have negatively affected its cultivation. To elucidate the genetic control of agronomic traits, an intraspecific genetic linkage map of Indian M. pruriens has been developed based on amplified fragment length polymorphism (AFLP) markers using 200 F₂ progenies derived from a cross between wild and cultivated genotypes. The resulting linkage map comprised 129 AFLP markers dispersed over 13 linkage groups spanning a total distance of 618.88 cM with an average marker interval of 4.79 cM. For the first time, three QTLs explaining about 6.05-14.77% of the corresponding total phenotypic variation for three quantitative (seed) traits and, eight QTLs explaining about 25.96% of the corresponding total phenotypic variation for three qualitative traits have been detected on four linkage groups. The map presented here will pave a way for mapping of genes/QTLs for the important agronomic and horticultural traits contrasting between the parents used in this study.

A three-component system incorporating Ppd-D1, copy number variation at Ppd-B1, and numerous small-effect quantitative trait loci facilitates adaptation of heading time in winter wheat cultivars of worldwide origin.

PubMed

Würschum, Tobias; Langer, Simon M; Longin, C Friedrich H; Tucker, Matthew R; Leiser, Willmar L

2018-06-01

The broad adaptability of heading time has contributed to the global success of wheat in a diverse array of climatic conditions. Here, we investigated the genetic architecture underlying heading time in a large panel of 1,110 winter wheat cultivars of worldwide origin. Genome-wide association mapping, in combination with the analysis of major phenology loci, revealed a three-component system that facilitates the adaptation of heading time in winter wheat. The photoperiod sensitivity locus Ppd-D1 was found to account for almost half of the genotypic variance in this panel and can advance or delay heading by many days. In addition, copy number variation at Ppd-B1 was the second most important source of variation in heading, explaining 8.3% of the genotypic variance. Results from association mapping and genomic prediction indicated that the remaining variation is attributed to numerous small-effect quantitative trait loci that facilitate fine-tuning of heading to the local climatic conditions. Collectively, our results underpin the importance of the two Ppd-1 loci for the adaptation of heading time in winter wheat and illustrate how the three components have been exploited for wheat breeding globally. © 2018 John Wiley & Sons Ltd.

A journey from a SSR-based low density map to a SNP-based high density map for identification of disease resistance quantitative trait loci in peanut

USDA-ARS?s Scientific Manuscript database

Mapping and identification of quantitative trait loci (QTLs) are important for efficient marker-assisted breeding. Diseases such as leaf spots and Tomato spotted wilt virus (TSWV) cause significant loses to peanut growers. The U.S. Peanut Genome Initiative (PGI) was launched in 2004, and expanded to...

Mapping quantitative trait loci controlling early growth in a (longleaf pine × slash pine) × slash pine BC1 family

Treesearch

C. Weng; Thomas L. Kubisiak; C. Dana Nelson; M. Stine

2002-01-01

Random amplified polymorphic DNA (RAPD) markers were employed to map the genome and quantitative trait loci controlling the early growth of a pine hybrid F1 tree (Pinus palustris Mill. × P. elliottii Engl.) and a recurrent slash pine tree (P. ellottii Engl.) in a (longleaf pine × slash pine...

Comparison of Maximum Likelihood Estimation Approach and Regression Approach in Detecting Quantitative Trait Lco Using RAPD Markers

Treesearch

Changren Weng; Thomas L. Kubisiak; C. Dana Nelson; James P. Geaghan; Michael Stine

1999-01-01

Single marker regression and single marker maximum likelihood estimation were tied to detect quantitative trait loci (QTLs) controlling the early height growth of longleaf pine and slash pine using a ((longleaf pine x slash pine) x slash pine) BC, population consisting of 83 progeny. Maximum likelihood estimation was found to be more power than regression and could...

Quantitative Trait Loci Mapping in Brassica rapa Revealed the Structural and Functional Conservation of Genetic Loci Governing Morphological and Yield Component Traits in the A, B, and C Subgenomes of Brassica Species

PubMed Central

Li, Xiaonan; Ramchiary, Nirala; Dhandapani, Vignesh; Choi, Su Ryun; Hur, Yoonkang; Nou, Ill-Sup; Yoon, Moo Kyoung; Lim, Yong Pyo

2013-01-01

Brassica rapa is an important crop species that produces vegetables, oilseed, and fodder. Although many studies reported quantitative trait loci (QTL) mapping, the genes governing most of its economically important traits are still unknown. In this study, we report QTL mapping for morphological and yield component traits in B. rapa and comparative map alignment between B. rapa, B. napus, B. juncea, and Arabidopsis thaliana to identify candidate genes and conserved QTL blocks between them. A total of 95 QTL were identified in different crucifer blocks of the B. rapa genome. Through synteny analysis with A. thaliana, B. rapa candidate genes and intronic and exonic single nucleotide polymorphisms in the parental lines were detected from whole genome resequenced data, a few of which were validated by mapping them to the QTL regions. Semi-quantitative reverse transcriptase PCR analysis showed differences in the expression levels of a few genes in parental lines. Comparative mapping identified five key major evolutionarily conserved crucifer blocks (R, J, F, E, and W) harbouring QTL for morphological and yield components traits between the A, B, and C subgenomes of B. rapa, B. juncea, and B. napus. The information of the identified candidate genes could be used for breeding B. rapa and other related Brassica species. PMID:23223793

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

Genetic linkage map construction and QTL mapping of salt tolerance traits in Zoysiagrass (Zoysia japonica).

PubMed

Guo, Hailin; Ding, Wanwen; Chen, Jingbo; Chen, Xuan; Zheng, Yiqi; Wang, Zhiyong; Liu, Jianxiu

2014-01-01

Zoysiagrass (Zoysia Willd.) is an important warm season turfgrass that is grown in many parts of the world. Salt tolerance is an important trait in zoysiagrass breeding programs. In this study, a genetic linkage map was constructed using sequence-related amplified polymorphism markers and random amplified polymorphic DNA markers based on an F1 population comprising 120 progeny derived from a cross between Zoysia japonica Z105 (salt-tolerant accession) and Z061 (salt-sensitive accession). The linkage map covered 1211 cM with an average marker distance of 5.0 cM and contained 24 linkage groups with 242 marker loci (217 sequence-related amplified polymorphism markers and 25 random amplified polymorphic DNA markers). Quantitative trait loci affecting the salt tolerance of zoysiagrass were identified using the constructed genetic linkage map. Two significant quantitative trait loci (qLF-1 and qLF-2) for leaf firing percentage were detected; qLF-1 at 36.3 cM on linkage group LG4 with a logarithm of odds value of 3.27, which explained 13.1% of the total variation of leaf firing and qLF-2 at 42.3 cM on LG5 with a logarithm of odds value of 2.88, which explained 29.7% of the total variation of leaf firing. A significant quantitative trait locus (qSCW-1) for reduced percentage of dry shoot clipping weight was detected at 44.1 cM on LG5 with a logarithm of odds value of 4.0, which explained 65.6% of the total variation. This study provides important information for further functional analysis of salt-tolerance genes in zoysiagrass. Molecular markers linked with quantitative trait loci for salt tolerance will be useful in zoysiagrass breeding programs using marker-assisted selection.

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

PubMed

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

2017-08-01

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

Functional mapping of quantitative trait loci associated with rice tillering.

PubMed

Liu, G F; Li, M; Wen, J; Du, Y; Zhang, Y-M

2010-10-01

Several biologically significant parameters that are related to rice tillering are closely associated with rice grain yield. Although identification of the genes that control rice tillering and therefore influence crop yield would be valuable for rice production management and genetic improvement, these genes remain largely unidentified. In this study, we carried out functional mapping of quantitative trait loci (QTLs) for rice tillering in 129 doubled haploid lines, which were derived from a cross between IR64 and Azucena. We measured the average number of tillers in each plot at seven developmental stages and fit the growth trajectory of rice tillering with the Wang-Lan-Ding mathematical model. Four biologically meaningful parameters in this model--the potential maximum for tiller number (K), the optimum tiller time (t(0)), and the increased rate (r), or the reduced rate (c) at the time of deviation from t(0)--were our defined variables for multi-marker joint analysis under the framework of penalized maximum likelihood, as well as composite interval mapping. We detected a total of 27 QTLs that accounted for 2.49-8.54% of the total phenotypic variance. Nine common QTLs across multi-marker joint analysis and composite interval mapping showed high stability, while one QTL was environment-specific and three were epistatic. We also identified several genomic segments that are associated with multiple traits. Our results describe the genetic basis of rice tiller development, enable further marker-assisted selection in rice cultivar development, and provide useful information for rice production management.

Analysis of genetic effects of nuclear-cytoplasmic interaction on quantitative traits: genetic model for diploid plants.

PubMed

Han, Lide; Yang, Jian; Zhu, Jun

2007-06-01

A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction (NCI) as well as their genotype by environment (GE) interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction (AUP) method. Data on four quantitative traits (boll number, lint percentage, fiber length, and micronaire) in Upland cotton (Gossypium hirsutum L.) were analyzed as a worked example to show the effectiveness of the model.

Quantitative trait locus mapping and functional genomics of an organophosphate resistance trait in the western corn rootworm, Diabrotica virgifera virgifera

USDA-ARS?s Scientific Manuscript database

The western corn rootworm (WCR), Diabrotica virgifera virgifera, is an insect pest of corn, and population suppression with chemical insecticides is an important management tool. Traits conferring organophosphate insecticide resistance have increased in frequency among WCR populations, resulting in...

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

PubMed

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

2016-01-01

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

Robust LOD scores for variance component-based linkage analysis.

PubMed

Blangero, J; Williams, J T; Almasy, L

2000-01-01

The variance component method is now widely used for linkage analysis of quantitative traits. Although this approach offers many advantages, the importance of the underlying assumption of multivariate normality of the trait distribution within pedigrees has not been studied extensively. Simulation studies have shown that traits with leptokurtic distributions yield linkage test statistics that exhibit excessive Type I error when analyzed naively. We derive analytical formulae relating the deviation from the expected asymptotic distribution of the lod score to the kurtosis and total heritability of the quantitative trait. A simple correction constant yields a robust lod score for any deviation from normality and for any pedigree structure, and effectively eliminates the problem of inflated Type I error due to misspecification of the underlying probability model in variance component-based linkage analysis.

Quantitative genetic models of sexual selection by male choice.

PubMed

Nakahashi, Wataru

2008-09-01

There are many examples of male mate choice for female traits that tend to be associated with high fertility. I develop quantitative genetic models of a female trait and a male preference to show when such a male preference can evolve. I find that a disagreement between the fertility maximum and the viability maximum of the female trait is necessary for directional male preference (preference for extreme female trait values) to evolve. Moreover, when there is a shortage of available male partners or variance in male nongenetic quality, strong male preference can evolve. Furthermore, I also show that males evolve to exhibit a stronger preference for females that are more feminine (less resemblance to males) than the average female when there is a sexual dimorphism caused by fertility selection which acts only on females.

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

PubMed

Ensslin, Andreas; Fischer, Markus

2015-08-01

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

Quantitative Trait Loci for High-Temperature Adult-Plant Resistance to Stripe Rust (Puccinia Striiformis f. sp. tritici) in a Hard Red Winter Wheat Germplasm IDO444

USDA-ARS?s Scientific Manuscript database

High-temperature adult-plant (HTAP) resistance to stripe rust (Puccinia striiformis f. sp. tritici) is a durable type of resistance in wheat. The objective of this study was to identify quantitative trait loci (QTL) conferring the HTAP resistance to stripe rust in a population consisted of 179 F7:8...

Identification of QTLs for fruit quality traits in Japanese apples: QTLs for early ripening are tightly related to preharvest fruit drop

PubMed Central

Kunihisa, Miyuki; Moriya, Shigeki; Abe, Kazuyuki; Okada, Kazuma; Haji, Takashi; Hayashi, Takeshi; Kim, Hoytaek; Nishitani, Chikako; Terakami, Shingo; Yamamoto, Toshiya

2014-01-01

Many important apple (Malus × domestica Borkh.) fruit quality traits are regulated by multiple genes, and more information about quantitative trait loci (QTLs) for these traits is required for marker-assisted selection. In this study, we constructed genetic linkage maps of the Japanese apple cultivars ‘Orin’ and ‘Akane’ using F1 seedlings derived from a cross between these cultivars. The ‘Orin’ map consisted of 251 loci covering 17 linkage groups (LGs; total length 1095.3 cM), and the ‘Akane’ map consisted of 291 loci covering 18 LGs (total length 1098.2 cM). We performed QTL analysis for 16 important traits, and found that four QTLs related to harvest time explained about 70% of genetic variation, and these will be useful for marker-assisted selection. The QTL for early harvest time in LG15 was located very close to the QTL for preharvest fruit drop. The QTL for skin color depth was located around the position of MYB1 in LG9, which suggested that alleles harbored by ‘Akane’ are regulating red color depth with different degrees of effect. We also analyzed soluble solids and sugar component contents, and found that a QTL for soluble solids content in LG16 could be explained by the amount of sorbitol and fructose. PMID:25320559

Comparison of multipoint linkage analyses for quantitative traits in the CEPH data: parametric LOD scores, variance components LOD scores, and Bayes factors.

PubMed

Sung, Yun Ju; Di, Yanming; Fu, Audrey Q; Rothstein, Joseph H; Sieh, Weiva; Tong, Liping; Thompson, Elizabeth A; Wijsman, Ellen M

2007-01-01

We performed multipoint linkage analyses with multiple programs and models for several gene expression traits in the Centre d'Etude du Polymorphisme Humain families. All analyses provided consistent results for both peak location and shape. Variance-components (VC) analysis gave wider peaks and Bayes factors gave fewer peaks. Among programs from the MORGAN package, lm_multiple performed better than lm_markers, resulting in less Markov-chain Monte Carlo (MCMC) variability between runs, and the program lm_twoqtl provided higher LOD scores by also including either a polygenic component or an additional quantitative trait locus.

Comparison of multipoint linkage analyses for quantitative traits in the CEPH data: parametric LOD scores, variance components LOD scores, and Bayes factors

PubMed Central

Sung, Yun Ju; Di, Yanming; Fu, Audrey Q; Rothstein, Joseph H; Sieh, Weiva; Tong, Liping; Thompson, Elizabeth A; Wijsman, Ellen M

2007-01-01

We performed multipoint linkage analyses with multiple programs and models for several gene expression traits in the Centre d'Etude du Polymorphisme Humain families. All analyses provided consistent results for both peak location and shape. Variance-components (VC) analysis gave wider peaks and Bayes factors gave fewer peaks. Among programs from the MORGAN package, lm_multiple performed better than lm_markers, resulting in less Markov-chain Monte Carlo (MCMC) variability between runs, and the program lm_twoqtl provided higher LOD scores by also including either a polygenic component or an additional quantitative trait locus. PMID:18466597

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.

Preliminary evidence for associations between molecular markers and quantitative traits in a set of bread wheat (Triticum aestivum L.) cultivars and breeding lines.

PubMed

Abdollahi Mandoulakani, Babak; Nasri, Shilan; Dashchi, Sahar; Arzhang, Sorour; Bernousi, Iraj; Abbasi Holasou, Hossein

The identification of polymorphic markers associated with various quantitative traits allows us to test their performance for the exploitation of the extensive quantitative variation maintained in gene banks. In the current study, a set of 97 wheat germplasm accessions including 48 cultivars and 49 breeding lines were evaluated for 18 agronomic traits. The accessions were also genotyped with 23 ISSR, nine IRAP and 20 REMAP markers, generating a total of 658 clear and scorable bands, 86% of which were polymorphic. Both neighbor-joining dendrogram and Bayesian analysis of clustering of individuals revealed that the accessions could be divided into four genetically distinct groups, indicating the presence of a population structure in current wheat germplasm. Associations between molecular markers and 18 agronomic traits were analyzed using the mixed linear model (MLM) approach. A total of 94 loci were found to be significantly associated with agronomic traits (P≤0.01). The highest number of bands significantly associated with the 18 traits varied from 11 for number of spikelets spike -1 (NSS) to two for grain yield in row (GRY). Loci ISSR16-9 and REMAP13-10 were associated with three different traits. The results of the current study provide useful information about the performance of retrotransposon-based and ISSR molecular markers that could be helpful in selecting potentially elite gene bank samples for wheat-breeding programs. Copyright © 2017 Académie des sciences. Published by Elsevier Masson SAS. All rights reserved.

The Power to Detect Linkage Disequilibrium with Quantitative Traits in Selected Samples

PubMed Central

Abecasis, Gonçalo R.; Cookson, William O. C.; Cardon, Lon R.

2001-01-01

Results from power studies for linkage detection have led to many ongoing and planned collections of phenotypically extreme nuclear families. Given the great expense of collecting these families and the imminent availability of a dense diallelic marker map, the families are likely to be used in allelic-association as well as linkage studies. However, optimal selection strategies for linkage may not be equally powerful for association. We examine the power to detect linkage disequilibrium for quantitative traits after phenotypic selection. The results encompass six selection strategies that are in widespread use, including single selection (two designs), affected sib pairs, concordant and discordant pairs, and the extreme-concordant and -discordant design. Selection of sibships on the basis of one extreme proband with high or low trait scores provides as much power as discordant sib pairs but requires the screening and phenotyping of substantially fewer initial families from which to select. Analysis of the role of allele frequencies within each selection design indicates that common trait alleles generally offer the most power, but similarities between the marker- and trait-allele frequencies are much more important than the trait-locus frequency alone. Some of the most widespread selection designs, such as single selection, yield power gains only when both the marker and quantitative trait loci (QTL) are relatively rare in the population. In contrast, discordant pairs and the extreme-proband design provide power for the broadest range of QTL–marker-allele frequency differences. Overall, proband selection from either tail provides the best balance of power, robustness, and simplicity of ascertainment for family-based association analysis. PMID:11349228

A novel 3D imaging system for strawberry phenotyping.

PubMed

He, Joe Q; Harrison, Richard J; Li, Bo

2017-01-01

Accurate and quantitative phenotypic data in plant breeding programmes is vital in breeding to assess the performance of genotypes and to make selections. Traditional strawberry phenotyping relies on the human eye to assess most external fruit quality attributes, which is time-consuming and subjective. 3D imaging is a promising high-throughput technique that allows multiple external fruit quality attributes to be measured simultaneously. A low cost multi-view stereo (MVS) imaging system was developed, which captured data from 360° around a target strawberry fruit. A 3D point cloud of the sample was derived and analysed with custom-developed software to estimate berry height, length, width, volume, calyx size, colour and achene number. Analysis of these traits in 100 fruits showed good concordance with manual assessment methods. This study demonstrates the feasibility of an MVS based 3D imaging system for the rapid and quantitative phenotyping of seven agronomically important external strawberry traits. With further improvement, this method could be applied in strawberry breeding programmes as a cost effective phenotyping technique.

Responses of leaf traits to climatic gradients: adaptive variation versus compositional shifts

NASA Astrophysics Data System (ADS)

Meng, T.-T.; Wang, H.; Harrison, S. P.; Prentice, I. C.; Ni, J.; Wang, G.

2015-09-01

Dynamic global vegetation models (DGVMs) typically rely on plant functional types (PFTs), which are assigned distinct environmental tolerances and replace one another progressively along environmental gradients. Fixed values of traits are assigned to each PFT; modelled trait variation along gradients is thus driven by PFT replacement. But empirical studies have revealed "universal" scaling relationships (quantitative trait variations with climate that are similar within and between species, PFTs and communities); and continuous, adaptive trait variation has been proposed to replace PFTs as the basis for next-generation DGVMs. Here we analyse quantitative leaf-trait variation on long temperature and moisture gradients in China with a view to understanding the relative importance of PFT replacement vs. continuous adaptive variation within PFTs. Leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC) and nitrogen content of dry matter were measured on all species at 80 sites ranging from temperate to tropical climates and from dense forests to deserts. Chlorophyll fluorescence traits and carbon, phosphorus and potassium contents were measured at 47 sites. Generalized linear models were used to relate log-transformed trait values to growing-season temperature and moisture indices, with or without PFT identity as a predictor, and to test for differences in trait responses among PFTs. Continuous trait variation was found to be ubiquitous. Responses to moisture availability were generally similar within and between PFTs, but biophysical traits (LA, SLA and LDMC) of forbs and grasses responded differently from woody plants. SLA and LDMC responses to temperature were dominated by the prevalence of evergreen PFTs with thick, dense leaves at the warm end of the gradient. Nutrient (N, P and K) responses to climate gradients were generally similar within all PFTs. Area-based nutrients generally declined with moisture; Narea and Karea declined with temperature, but Parea increased with temperature. Although the adaptive nature of many of these trait-climate relationships is understood qualitatively, a key challenge for modelling is to predict them quantitatively. Models must take into account that community-level responses to climatic gradients can be influenced by shifts in PFT composition, such as the replacement of deciduous by evergreen trees, which may run either parallel or counter to trait variation within PFTs. The importance of PFT shifts varies among traits, being important for biophysical traits but less so for physiological and chemical traits. Finally, models should take account of the diversity of trait values that is found in all sites and PFTs, representing the "pool" of variation that is locally available for the natural adaptation of ecosystem function to environmental change.

Case-Deletion Diagnostics for Maximum Likelihood Multipoint Quantitative Trait Locus Linkage Analysis

PubMed Central

Mendoza, Maria C.B.; Burns, Trudy L.; Jones, Michael P.

2009-01-01

Objectives Case-deletion diagnostic methods are tools that allow identification of influential observations that may affect parameter estimates and model fitting conclusions. The goal of this paper was to develop two case-deletion diagnostics, the exact case deletion (ECD) and the empirical influence function (EIF), for detecting outliers that can affect results of sib-pair maximum likelihood quantitative trait locus (QTL) linkage analysis. Methods Subroutines to compute the ECD and EIF were incorporated into the maximum likelihood QTL variance estimation components of the linkage analysis program MAPMAKER/SIBS. Performance of the diagnostics was compared in simulation studies that evaluated the proportion of outliers correctly identified (sensitivity), and the proportion of non-outliers correctly identified (specificity). Results Simulations involving nuclear family data sets with one outlier showed EIF sensitivities approximated ECD sensitivities well for outlier-affected parameters. Sensitivities were high, indicating the outlier was identified a high proportion of the time. Simulations also showed the enormous computational time advantage of the EIF. Diagnostics applied to body mass index in nuclear families detected observations influential on the lod score and model parameter estimates. Conclusions The EIF is a practical diagnostic tool that has the advantages of high sensitivity and quick computation. PMID:19172086

Identification of quantitative trait Loci for resistance to southern leaf blight and days to anthesis in a maize recombinant inbred line population.

PubMed

Balint-Kurti, P J; Krakowsky, M D; Jines, M P; Robertson, L A; Molnár, T L; Goodman, M M; Holl, J B

2006-10-01

ABSTRACT A recombinant inbred line population derived from a cross between the maize lines NC300 (resistant) and B104 (susceptible) was evaluated for resistance to southern leaf blight (SLB) disease caused by Cochliobolus heterostrophus race O and for days to anthesis in four environments (Clayton, NC, and Tifton, GA, in both 2004 and 2005). Entry mean and average genetic correlations between disease ratings in different environments were high (0.78 to 0.89 and 0.9, respectively) and the overall entry mean heritability for SLB resistance was 0.89. When weighted mean disease ratings were fitted to a model using multiple interval mapping, seven potential quantitative trait loci (QTL) were identified, the two strongest being on chromosomes 3 (bin 3.04) and 9 (bin 9.03-9.04). These QTL explained a combined 80% of the phenotypic variation for SLB resistance. Some time-point-specific SLB resistance QTL were also identified. There was no significant correlation between disease resistance and days to anthesis. Six putative QTL for time to anthesis were identified, none of which coincided with any SLB resistance QTL.

Linkage disequilibrium interval mapping of quantitative trait loci.

PubMed

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

2006-03-16

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

The First Genetic and Comparative Map of White Lupin (Lupinus albus L.): Identification of QTLs for Anthracnose Resistance and Flowering Time, and a Locus for Alkaloid Content

PubMed Central

Phan, Huyen T. T.; Ellwood, Simon R.; Adhikari, Kedar; Nelson, Matthew N.; Oliver, Richard P.

2007-01-01

Abstract We report the first genetic linkage map of white lupin (Lupinus albus L.). An F8 recombinant inbred line population developed from Kiev mutant × P27174 was mapped with 220 amplified fragment length polymorphism and 105 gene-based markers. The genetic map consists of 28 main linkage groups (LGs) that varied in length from 22.7 cM to 246.5 cM and spanned a total length of 2951 cM. There were seven additional pairs and 15 unlinked markers, and 12.8% of markers showed segregation distortion at P < 0.05. Syntenic relationships between Medicago truncatula and L. albus were complex. Forty-five orthologous markers that mapped between M. truncatula and L. albus identified 17 small syntenic blocks, and each M. truncatula chromosome aligned to between one and six syntenic blocks in L. albus. Genetic mapping of three important traits: anthracnose resistance, flowering time, and alkaloid content allowed loci governing these traits to be defined. Two quantitative trait loci (QTLs) with significant effects were identified for anthracnose resistance on LG4 and LG17, and two QTLs were detected for flowering time on the top of LG1 and LG3. Alkaloid content was mapped as a Mendelian trait to LG11. PMID:17526914

In-Silico Genomic Approaches To Understanding Lactation, Mammary Development, And Breast Cancer

USDA-ARS?s Scientific Manuscript database

Lactation-related traits are influenced by genetics. From a quantitative standpoint, these traits have been well studied in dairy species, but there has also been work on the genetics of lactation in humans and mice. In addition, there is evidence to support the notion that other mammary gland trait...

Fine phenotyping of pod and seed traits in Arachis germplasm accessions using digital image analysis

USDA-ARS?s Scientific Manuscript database

Reliable and objective phenotyping of peanut pod and seed traits is important for cultivar selection and genetic mapping of yield components. To develop useful and efficient methods to quantitatively define peanut pod and seed traits, a group of peanut germplasm with high levels of phenotypic varia...

Harvesting the Pea Genome: Association Mapping of the Pisum Single Plant Plus Collection

USDA-ARS?s Scientific Manuscript database

Yield per se is a difficult trait to improve due to the quantitative nature and low heritability of this trait. Nevertheless, yield is the most important trait for crop improvement. Development of higher yielding pea cultivars will depend on harvesting allelic diversity harbored in ex situ germpla...

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

USDA-ARS?s Scientific Manuscript database

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

A comparative meta-analysis of QTL between intraspecific Gossypium hirsutum interspecific populations and Gossypium hirsutum x Gossypium barbadense populations

USDA-ARS?s Scientific Manuscript database

Recent Meta-analysis of quantitative trait loci (QTL) in tetraploid cotton (Gossypium spp.) has identified regions of the genome with high concentrations of various trait QTL called clusters, and specific trait QTL called hotspots. The Meta-analysis included all population types of Gossypium mixing ...

A simple linear regression method for quantitative trait loci linkage analysis with censored observations.

PubMed

Anderson, Carl A; McRae, Allan F; Visscher, Peter M

2006-07-01

Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.

Quantitative trait nucleotide analysis using Bayesian model selection.

PubMed

Blangero, John; Goring, Harald H H; Kent, Jack W; Williams, Jeff T; Peterson, Charles P; Almasy, Laura; Dyer, Thomas D

2005-10-01

Although much attention has been given to statistical genetic methods for the initial localization and fine mapping of quantitative trait loci (QTLs), little methodological work has been done to date on the problem of statistically identifying the most likely functional polymorphisms using sequence data. In this paper we provide a general statistical genetic framework, called Bayesian quantitative trait nucleotide (BQTN) analysis, for assessing the likely functional status of genetic variants. The approach requires the initial enumeration of all genetic variants in a set of resequenced individuals. These polymorphisms are then typed in a large number of individuals (potentially in families), and marker variation is related to quantitative phenotypic variation using Bayesian model selection and averaging. For each sequence variant a posterior probability of effect is obtained and can be used to prioritize additional molecular functional experiments. An example of this quantitative nucleotide analysis is provided using the GAW12 simulated data. The results show that the BQTN method may be useful for choosing the most likely functional variants within a gene (or set of genes). We also include instructions on how to use our computer program, SOLAR, for association analysis and BQTN analysis.

Quantitative Trait Loci Controlling Vegetative Growth Rate in the Edible Basidiomycete Pleurotus ostreatus

PubMed Central

Larraya, Luis M.; Idareta, Eneko; Arana, Dani; Ritter, Enrique; Pisabarro, Antonio G.; Ramírez, Lucia

2002-01-01

Mycelium growth rate is a quantitative characteristic that exhibits continuous variation. This trait has applied interest, as growth rate is correlated with production yield and increased advantage against competitors. In this work, we studied growth rate variation in the edible basidiomycete Pleurotus ostreatus growing as monokaryotic or dikaryotic mycelium on Eger medium or on wheat straw. Our analysis resulted in identification of several genomic regions (quantitative trait loci [QTLs]) involved in the control of growth rate that can be mapped on the genetic linkage map of this fungus. In some cases monokaryotic and dikaryotic QTLs clustered at the same map position, indicating that there are principal genomic areas responsible for growth rate control. The availability of this linkage map of growth rate QTLs can help in the design of rational strain breeding programs based on genomic information. PMID:11872457

Identification of Quantitative Trait Loci Controlling Gene Expression during the Innate Immunity Response of Soybean1[W][OA

PubMed Central

Valdés-López, Oswaldo; Thibivilliers, Sandra; Qiu, Jing; Xu, Wayne Wenzhong; Nguyen, Tran H.N.; Libault, Marc; Le, Brandon H.; Goldberg, Robert B.; Hill, Curtis B.; Hartman, Glen L.; Diers, Brian; Stacey, Gary

2011-01-01

Microbe-associated molecular pattern-triggered immunity (MTI) is an important component of the plant innate immunity response to invading pathogens. However, most of our knowledge of MTI comes from studies of model systems with relatively little work done with crop plants. In this work, we report on variation in both the microbe-associated molecular pattern-triggered oxidative burst and gene expression across four soybean (Glycine max) genotypes. Variation in MTI correlated with the level of pathogen resistance for each genotype. A quantitative trait locus analysis on these traits identified four loci that appeared to regulate gene expression during MTI in soybean. Likewise, we observed that both MTI variation and pathogen resistance were quantitatively inherited. The approach utilized in this study may have utility for identifying key resistance loci useful for developing improved soybean cultivars. PMID:21963820

Genetic architecture and temporal patterns of biomass accumulation in spring barley revealed by image analysis.

PubMed

Neumann, Kerstin; Zhao, Yusheng; Chu, Jianting; Keilwagen, Jens; Reif, Jochen C; Kilian, Benjamin; Graner, Andreas

2017-08-10

Genetic mapping of phenotypic traits generally focuses on a single time point, but biomass accumulates continuously during plant development. Resolution of the temporal dynamics that affect biomass recently became feasible using non-destructive imaging. With the aim to identify key genetic factors for vegetative biomass formation from the seedling stage to flowering, we explored growth over time in a diverse collection of two-rowed spring barley accessions. High heritabilities facilitated the temporal analysis of trait relationships and identification of quantitative trait loci (QTL). Biomass QTL tended to persist only a short period during early growth. More persistent QTL were detected around the booting stage. We identified seven major biomass QTL, which together explain 55% of the genetic variance at the seedling stage, and 43% at the booting stage. Three biomass QTL co-located with genes or QTL involved in phenology. The most important locus for biomass was independent from phenology and is located on chromosome 7HL at 141 cM. This locus explained ~20% of the genetic variance, was significant over a long period of time and co-located with HvDIM, a gene involved in brassinosteroid synthesis. Biomass is a dynamic trait and is therefore orchestrated by different QTL during early and late growth stages. Marker-assisted selection for high biomass at booting stage is most effective by also including favorable alleles from seedling biomass QTL. Selection for dynamic QTL may enhance genetic gain for complex traits such as biomass or, in the future, even grain yield.

Determining Phenological Patterns Associated with the Onset of Senescence in a Wheat MAGIC Mapping Population.

PubMed

Camargo, Anyela V; Mott, Richard; Gardner, Keith A; Mackay, Ian J; Corke, Fiona; Doonan, John H; Kim, Jan T; Bentley, Alison R

2016-01-01

The appropriate timing of developmental transitions is critical for adapting many crops to their local climatic conditions. Therefore, understanding the genetic basis of different aspects of phenology could be useful in highlighting mechanisms underpinning adaptation, with implications in breeding for climate change. For bread wheat ( Triticum aestivum ), the transition from vegetative to reproductive growth, the start and rate of leaf senescence and the relative timing of different stages of flowering and grain filling all contribute to plant performance. In this study we screened under Smart house conditions a large, multi-founder "NIAB elite MAGIC" wheat population, to evaluate the genetic elements that influence the timing of developmental stages in European elite varieties. This panel of recombinant inbred lines was derived from eight parents that are or recently have been grown commercially in the UK and Northern Europe. We undertook a detailed temporal phenotypic analysis under Smart house conditions of the population and its parents, to try to identify known or novel Quantitative Trait Loci associated with variation in the timing of key phenological stages in senescence. This analysis resulted in the detection of QTL interactions with novel traits such the time between "half of ear emergence above flag leaf ligule" and the onset of senescence at the flag leaf as well as traits associated with plant morphology such as stem height. In addition, strong correlations between several traits and the onset of senescence of the flag leaf were identified. This work establishes the value of systematically phenotyping genetically unstructured populations to reveal the genetic architecture underlying morphological variation in commercial wheat.

Relationship between leukocyte telomere length and personality traits in healthy subjects.

PubMed

Sadahiro, R; Suzuki, A; Enokido, M; Matsumoto, Y; Shibuya, N; Kamata, M; Goto, K; Otani, K

2015-02-01

It has been shown that certain personality traits are related to mortality and disease morbidity, but the biological mechanism linking them remains unclear. Telomeres are tandem repeat DNA sequences located at the ends of chromosomes, and shorter telomere length is a predictor of mortality and late-life disease morbidity. Thus, it is possible that personality traits influence telomere length. In the present study, we examined the relationship of leukocyte telomere length with personality traits in healthy subjects. The subjects were 209 unrelated healthy Japanese who were recruited from medical students at 4th-5th grade. Assessment of personality traits was performed by the Revised NEO Personality Inventory (NEO-PI-R) and the Temperament and Character Inventory (TCI). Leukocyte relative telomere length was determined by a quantitative real-time PCR method for a ratio of telomere/single copy gene. In the stepwise multiple regression analysis, shorter telomere length was related to lower scores of neuroticism (P<0.01) and conscientiousness (P<0.05) of the NEO-PI-R, and lower scores of harm avoidance (P<0.05) and reward dependence (P<0.05) of the TCI. The present study suggests that leukocyte telomere length is associated with some personality traits, and this association may be implicated in the relationship between personality traits and mortality. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

The quantitative LOD score: test statistic and sample size for exclusion and linkage of quantitative traits in human sibships.

PubMed

Page, G P; Amos, C I; Boerwinkle, E

1998-04-01

We present a test statistic, the quantitative LOD (QLOD) score, for the testing of both linkage and exclusion of quantitative-trait loci in randomly selected human sibships. As with the traditional LOD score, the boundary values of 3, for linkage, and -2, for exclusion, can be used for the QLOD score. We investigated the sample sizes required for inferring exclusion and linkage, for various combinations of linked genetic variance, total heritability, recombination distance, and sibship size, using fixed-size sampling. The sample sizes required for both linkage and exclusion were not qualitatively different and depended on the percentage of variance being linked or excluded and on the total genetic variance. Information regarding linkage and exclusion in sibships larger than size 2 increased as approximately all possible pairs n(n-1)/2 up to sibships of size 6. Increasing the recombination (theta) distance between the marker and the trait loci reduced empirically the power for both linkage and exclusion, as a function of approximately (1-2theta)4.

A Novel Quantitative Trait Locus on Mouse Chromosome 18, “era1,” Modifies the Entrainment of Circadian Rhythms

PubMed Central

Wisor, Jonathan P.; Striz, Martin; DeVoss, Jason; Murphy, Greer M.; Edgar, Dale M.; O'Hara, Bruce F.

2007-01-01

Study Objectives: The mammalian circadian clock in the suprachiasmatic nuclei (SCN) of the hypothalamus conveys 24-h rhythmicity to sleep-wake cycles, locomotor activity, and other behavioral and physiological processes. The timing of rhythms relative to the light/dark (LD12:12) cycle is influenced in part by the endogenous circadian period and the time of day specific sensitivity of the clock to light. We now describe a novel circadian rhythm phenotype, and a locus influencing that phenotype, in a segregating population of mice. Methods: By crossbreeding 2 genetically distinct nocturnal strains of mice (Cast/Ei and C57BL/6J) and backcrossing the resulting progeny to Cast/Ei, we have produced a novel circadian phenotype, called early runner mice. Results: Early runner mice entrain to a light/dark cycle at an advanced phase, up to 9 hours before dark onset. This phenotype is not significantly correlated with circadian period in constant darkness and is not associated with disruption of molecular circadian rhythms in the SCN, as assessed by analysis of period gene expression. We have identified a genomic region that regulates this phenotype—a major quantitative trait locus on chromosome 18 (near D18Mit184) that we have named era1 for Early Runner Activity locus one. Phase delays caused by light exposure early in the subjective night were of smaller magnitude in backcross offspring that were homozygous Cast/Ei at D18Mit184 than in those that were heterozygous at this locus. Conclusion: Genetic variability in the circadian response to light may, in part, explain the variance in phase angle of entrainment in this segregating mouse population. Citation: Wisor JP; Striz M; DeVoss J; Murphy GM; Edgar DM; O'Hara BF. A novel quantitative trait locus on mouse chromosome 18, “era1,” modifies the entrainment of circadian rhythms. SLEEP 2007;30(10):1255-1263. PMID:17969459

Efficient and accurate causal inference with hidden confounders from genome-transcriptome variation data

PubMed Central

2017-01-01

Mapping gene expression as a quantitative trait using whole genome-sequencing and transcriptome analysis allows to discover the functional consequences of genetic variation. We developed a novel method and ultra-fast software Findr for higly accurate causal inference between gene expression traits using cis-regulatory DNA variations as causal anchors, which improves current methods by taking into consideration hidden confounders and weak regulations. Findr outperformed existing methods on the DREAM5 Systems Genetics challenge and on the prediction of microRNA and transcription factor targets in human lymphoblastoid cells, while being nearly a million times faster. Findr is publicly available at https://github.com/lingfeiwang/findr. PMID:28821014

An optimal strategy for functional mapping of dynamic trait loci.

PubMed

Jin, Tianbo; Li, Jiahan; Guo, Ying; Zhou, Xiaojing; Yang, Runqing; Wu, Rongling

2010-02-01

As an emerging powerful approach for mapping quantitative trait loci (QTLs) responsible for dynamic traits, functional mapping models the time-dependent mean vector with biologically meaningful equations and are likely to generate biologically relevant and interpretable results. Given the autocorrelation nature of a dynamic trait, functional mapping needs the implementation of the models for the structure of the covariance matrix. In this article, we have provided a comprehensive set of approaches for modelling the covariance structure and incorporated each of these approaches into the framework of functional mapping. The Bayesian information criterion (BIC) values are used as a model selection criterion to choose the optimal combination of the submodels for the mean vector and covariance structure. In an example for leaf age growth from a rice molecular genetic project, the best submodel combination was found between the Gaussian model for the correlation structure, power equation of order 1 for the variance and the power curve for the mean vector. Under this combination, several significant QTLs for leaf age growth trajectories were detected on different chromosomes. Our model can be well used to study the genetic architecture of dynamic traits of agricultural values.

Identification of QTL controlling domestication-related traits in cowpea (Vigna unguiculata L. Walp).

PubMed

Lo, Sassoum; Muñoz-Amatriaín, María; Boukar, Ousmane; Herniter, Ira; Cisse, Ndiaga; Guo, Yi-Ning; Roberts, Philip A; Xu, Shizhong; Fatokun, Christian; Close, Timothy J

2018-04-19

Cowpea (Vigna unguiculata L. Walp) is a warm-season legume with a genetically diverse gene-pool composed of wild and cultivated forms. Cowpea domestication involved considerable phenotypic changes from the wild progenitor, including reduction of pod shattering, increased organ size, and changes in flowering time. Little is known about the genetic basis underlying these changes. In this study, 215 recombinant inbred lines derived from a cross between a cultivated and a wild cowpea accession were used to evaluate nine domestication-related traits (pod shattering, peduncle length, flower color, days to flowering, 100-seed weight, pod length, leaf length, leaf width and seed number per pod). A high-density genetic map containing 17,739 single nucleotide polymorphisms was constructed and used to identify 16 quantitative trait loci (QTL) for these nine traits. Based on annotations of the cowpea reference genome, genes within these regions are reported. Four regions with clusters of QTL were identified, including one on chromosome 8 related to increased organ size. This study provides new knowledge of the genomic regions controlling domestication-related traits in cowpea as well as candidate genes underlying those QTL. This information can help to exploit wild relatives in cowpea breeding programs.

Functional Multi-Locus QTL Mapping of Temporal Trends in Scots Pine Wood Traits

PubMed Central

Li, Zitong; Hallingbäck, Henrik R.; Abrahamsson, Sara; Fries, Anders; Gull, Bengt Andersson; Sillanpää, Mikko J.; García-Gil, M. Rosario

2014-01-01

Quantitative trait loci (QTL) mapping of wood properties in conifer species has focused on single time point measurements or on trait means based on heterogeneous wood samples (e.g., increment cores), thus ignoring systematic within-tree trends. In this study, functional QTL mapping was performed for a set of important wood properties in increment cores from a 17-yr-old Scots pine (Pinus sylvestris L.) full-sib family with the aim of detecting wood trait QTL for general intercepts (means) and for linear slopes by increasing cambial age. Two multi-locus functional QTL analysis approaches were proposed and their performances were compared on trait datasets comprising 2 to 9 time points, 91 to 455 individual tree measurements and genotype datasets of amplified length polymorphisms (AFLP), and single nucleotide polymorphism (SNP) markers. The first method was a multilevel LASSO analysis whereby trend parameter estimation and QTL mapping were conducted consecutively; the second method was our Bayesian linear mixed model whereby trends and underlying genetic effects were estimated simultaneously. We also compared several different hypothesis testing methods under either the LASSO or the Bayesian framework to perform QTL inference. In total, five and four significant QTL were observed for the intercepts and slopes, respectively, across wood traits such as earlywood percentage, wood density, radial fiberwidth, and spiral grain angle. Four of these QTL were represented by candidate gene SNPs, thus providing promising targets for future research in QTL mapping and molecular function. Bayesian and LASSO methods both detected similar sets of QTL given datasets that comprised large numbers of individuals. PMID:25305041

Functional multi-locus QTL mapping of temporal trends in Scots pine wood traits.

PubMed

Li, Zitong; Hallingbäck, Henrik R; Abrahamsson, Sara; Fries, Anders; Gull, Bengt Andersson; Sillanpää, Mikko J; García-Gil, M Rosario

2014-10-09

Quantitative trait loci (QTL) mapping of wood properties in conifer species has focused on single time point measurements or on trait means based on heterogeneous wood samples (e.g., increment cores), thus ignoring systematic within-tree trends. In this study, functional QTL mapping was performed for a set of important wood properties in increment cores from a 17-yr-old Scots pine (Pinus sylvestris L.) full-sib family with the aim of detecting wood trait QTL for general intercepts (means) and for linear slopes by increasing cambial age. Two multi-locus functional QTL analysis approaches were proposed and their performances were compared on trait datasets comprising 2 to 9 time points, 91 to 455 individual tree measurements and genotype datasets of amplified length polymorphisms (AFLP), and single nucleotide polymorphism (SNP) markers. The first method was a multilevel LASSO analysis whereby trend parameter estimation and QTL mapping were conducted consecutively; the second method was our Bayesian linear mixed model whereby trends and underlying genetic effects were estimated simultaneously. We also compared several different hypothesis testing methods under either the LASSO or the Bayesian framework to perform QTL inference. In total, five and four significant QTL were observed for the intercepts and slopes, respectively, across wood traits such as earlywood percentage, wood density, radial fiberwidth, and spiral grain angle. Four of these QTL were represented by candidate gene SNPs, thus providing promising targets for future research in QTL mapping and molecular function. Bayesian and LASSO methods both detected similar sets of QTL given datasets that comprised large numbers of individuals. Copyright © 2014 Li et al.

A functional-structural model of rice linking quantitative genetic information with morphological development and physiological processes.

PubMed

Xu, Lifeng; Henke, Michael; Zhu, Jun; Kurth, Winfried; Buck-Sorlin, Gerhard

2011-04-01

Although quantitative trait loci (QTL) analysis of yield-related traits for rice has developed rapidly, crop models using genotype information have been proposed only relatively recently. As a first step towards a generic genotype-phenotype model, we present here a three-dimensional functional-structural plant model (FSPM) of rice, in which some model parameters are controlled by functions describing the effect of main-effect and epistatic QTLs. The model simulates the growth and development of rice based on selected ecophysiological processes, such as photosynthesis (source process) and organ formation, growth and extension (sink processes). It was devised using GroIMP, an interactive modelling platform based on the Relational Growth Grammar formalism (RGG). RGG rules describe the course of organ initiation and extension resulting in final morphology. The link between the phenotype (as represented by the simulated rice plant) and the QTL genotype was implemented via a data interface between the rice FSPM and the QTLNetwork software, which computes predictions of QTLs from map data and measured trait data. Using plant height and grain yield, it is shown how QTL information for a given trait can be used in an FSPM, computing and visualizing the phenotypes of different lines of a mapping population. Furthermore, we demonstrate how modification of a particular trait feeds back on the entire plant phenotype via the physiological processes considered. We linked a rice FSPM to a quantitative genetic model, thereby employing QTL information to refine model parameters and visualizing the dynamics of development of the entire phenotype as a result of ecophysiological processes, including the trait(s) for which genetic information is available. Possibilities for further extension of the model, for example for the purposes of ideotype breeding, are discussed.

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.

Integrated genomic approaches to identification of candidate genes underlying metabolic and cardiovascular phenotypes in the spontaneously hypertensive rat.

PubMed

Morrissey, Catherine; Grieve, Ian C; Heinig, Matthias; Atanur, Santosh; Petretto, Enrico; Pravenec, Michal; Hubner, Norbert; Aitman, Timothy J

2011-11-07

The spontaneously hypertensive rat (SHR) is a widely used rodent model of hypertension and metabolic syndrome. Previously we identified thousands of cis-regulated expression quantitative trait loci (eQTLs) across multiple tissues using a panel of rat recombinant inbred (RI) strains derived from Brown Norway and SHR progenitors. These cis-eQTLs represent potential susceptibility loci underlying physiological and pathophysiological traits manifested in SHR. We have prioritized 60 cis-eQTLs and confirmed differential expression between the parental strains by quantitative PCR in 43 (72%) of the eQTL transcripts. Quantitative trait transcript (QTT) analysis in the RI strains showed highly significant correlation between cis-eQTL transcript abundance and clinically relevant traits such as systolic blood pressure and blood glucose, with the physical location of a subset of the cis-eQTLs colocalizing with "physiological" QTLs (pQTLs) for these same traits. These colocalizing correlated cis-eQTLs (c3-eQTLs) are highly attractive as primary susceptibility loci for the colocalizing pQTLs. Furthermore, sequence analysis of the c3-eQTL genes identified single nucleotide polymorphisms (SNPs) that are predicted to affect transcription factor binding affinity, splicing and protein function. These SNPs, which potentially alter transcript abundance and stability, represent strong candidate factors underlying not just eQTL expression phenotypes, but also the correlated metabolic and physiological traits. In conclusion, by integration of genomic sequence, eQTL and QTT datasets we have identified several genes that are strong positional candidates for pathophysiological traits observed in the SHR strain. These findings provide a basis for the functional testing and ultimate elucidation of the molecular basis of these metabolic and cardiovascular phenotypes.

A functional–structural model of rice linking quantitative genetic information with morphological development and physiological processes

PubMed Central

Xu, Lifeng; Henke, Michael; Zhu, Jun; Kurth, Winfried; Buck-Sorlin, Gerhard

2011-01-01

Background and Aims Although quantitative trait loci (QTL) analysis of yield-related traits for rice has developed rapidly, crop models using genotype information have been proposed only relatively recently. As a first step towards a generic genotype–phenotype model, we present here a three-dimensional functional–structural plant model (FSPM) of rice, in which some model parameters are controlled by functions describing the effect of main-effect and epistatic QTLs. Methods The model simulates the growth and development of rice based on selected ecophysiological processes, such as photosynthesis (source process) and organ formation, growth and extension (sink processes). It was devised using GroIMP, an interactive modelling platform based on the Relational Growth Grammar formalism (RGG). RGG rules describe the course of organ initiation and extension resulting in final morphology. The link between the phenotype (as represented by the simulated rice plant) and the QTL genotype was implemented via a data interface between the rice FSPM and the QTLNetwork software, which computes predictions of QTLs from map data and measured trait data. Key Results Using plant height and grain yield, it is shown how QTL information for a given trait can be used in an FSPM, computing and visualizing the phenotypes of different lines of a mapping population. Furthermore, we demonstrate how modification of a particular trait feeds back on the entire plant phenotype via the physiological processes considered. Conclusions We linked a rice FSPM to a quantitative genetic model, thereby employing QTL information to refine model parameters and visualizing the dynamics of development of the entire phenotype as a result of ecophysiological processes, including the trait(s) for which genetic information is available. Possibilities for further extension of the model, for example for the purposes of ideotype breeding, are discussed. PMID:21247905

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.

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.

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.

Genetic divergence in northern Benin sorghum (Sorghum bicolor L. Moench) landraces as revealed by agromorphological traits and selection of candidate genotypes.

PubMed

Dossou-Aminon, Innocent; Loko, Laura Yêyinou; Adjatin, Arlette; Ewédjè, Eben-Ezer B K; Dansi, Alexandre; Rakshit, Sujay; Cissé, Ndiaga; Patil, Jagannath Vishnu; Agbangla, Clément; Sanni, Ambaliou; Akoègninou, Akpovi; Akpagana, Koffi

2015-01-01

Sorghum [Sorghum bicolor (L.) Moench] is an important staple food crop in northern Benin. In order to assess its diversity in Benin, 142 accessions of landraces collected from Northern Benin were grown in Central Benin and characterised using 10 qualitative and 14 quantitative agromorphological traits. High variability among both qualitative and quantitative traits was observed. Grain yield (0.72-10.57 tons/ha), panicle weight (15-215.95 g), days to 50% flowering (57-200 days), and plant height (153.27-636.5 cm) were among traits that exhibited broader variability. Correlations between quantitative traits were determined. Grain yield for instance exhibited highly positive association with panicle weight (r = 0.901, P = 0.000) and 100 seed weight (r = 0.247, P = 0.000). UPGMA cluster analysis classified the 142 accessions into 89 morphotypes. Based on multivariate analysis, twenty promising sorghum genotypes were selected. Among them, AT41, AT14, and AT29 showed early maturity (57 to 66 days to 50% flowering), high grain yields (4.85 to 7.85 tons/ha), and shorter plant height (153.27 to 180.37 cm). The results obtained will help enhancing sorghum production and diversity and developing new varieties that will be better adapted to the current soil and climate conditions in Benin.

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

PubMed

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

2010-02-01

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

The effects of dominance, regular inbreeding and sampling design on Q(ST), an estimator of population differentiation for quantitative traits.

PubMed

Goudet, Jérôme; Büchi, Lucie

2006-02-01

To test whether quantitative traits are under directional or homogenizing selection, it is common practice to compare population differentiation estimates at molecular markers (F(ST)) and quantitative traits (Q(ST)). If the trait is neutral and its determinism is additive, then theory predicts that Q(ST) = F(ST), while Q(ST) > F(ST) is predicted under directional selection for different local optima, and Q(ST) < F(ST) is predicted under homogenizing selection. However, nonadditive effects can alter these predictions. Here, we investigate the influence of dominance on the relation between Q(ST) and F(ST) for neutral traits. Using analytical results and computer simulations, we show that dominance generally deflates Q(ST) relative to F(ST). Under inbreeding, the effect of dominance vanishes, and we show that for selfing species, a better estimate of Q(ST) is obtained from selfed families than from half-sib families. We also compare several sampling designs and find that it is always best to sample many populations (>20) with few families (five) rather than few populations with many families. Provided that estimates of Q(ST) are derived from individuals originating from many populations, we conclude that the pattern Q(ST) > F(ST), and hence the inference of directional selection for different local optima, is robust to the effect of nonadditive gene actions.

Quantitative genetics of immunity and life history under different photoperiods.

PubMed

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

2012-05-01

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

Major Quantitative Trait Loci Affecting Honey Bee Foraging Behavior

PubMed Central

Hunt, G. J.; Page-Jr., R. E.; Fondrk, M. K.; Dullum, C. J.

1995-01-01

We identified two genomic regions that affect the amount of pollen stored in honey bee colonies and influence whether foragers will collect pollen or nectar. We selected for the amount of pollen stored in combs of honey bee colonies, a colony-level trait, and then used random amplified polymorphic DNA (RAPD) markers and interval mapping procedures with data from backcross colonies to identify two quantitative trait loci (pln1 and pln2, LOD 3.1 and 2.3, respectively). Quantitative trait loci effects were confirmed in a separate cross by demonstrating the cosegregation of marker alleles with the foraging behavior of individual workers. Both pln1 and pln2 had an effect on the amount of pollen carried by foragers returning to the colony, as inferred by the association between linked RAPD marker alleles, D8-.3f and 301-.55, and the individual pollen load weights of returning foragers. The alleles of the two marker loci were nonrandomly distributed with respect to foraging task. The two loci appeared to have different effects on foraging behavior. Individuals with alternative alleles for the marker linked to pln2 (but not pln1) differed with respect to the nectar sugar concentration of their nectar loads. PMID:8601492

Quantitative trait loci from the host genetic background modulate the durability of a resistance gene: a rational basis for sustainable resistance breeding in plants.

PubMed

Quenouille, J; Paulhiac, E; Moury, B; Palloix, A

2014-06-01

The combination of major resistance genes with quantitative resistance factors is hypothesized as a promising breeding strategy to preserve the durability of resistant cultivar, as recently observed in different pathosystems. Using the pepper (Capsicum annuum)/Potato virus Y (PVY, genus Potyvirus) pathosystem, we aimed at identifying plant genetic factors directly affecting the frequency of virus adaptation to the major resistance gene pvr2(3) and at comparing them with genetic factors affecting quantitative resistance. The resistance breakdown frequency was a highly heritable trait (h(2)=0.87). Four loci including additive quantitative trait loci (QTLs) and epistatic interactions explained together 70% of the variance of pvr2(3) breakdown frequency. Three of the four QTLs controlling pvr2(3) breakdown frequency were also involved in quantitative resistance, strongly suggesting that QTLs controlling quantitative resistance have a pleiotropic effect on the durability of the major resistance gene. With the first mapping of QTLs directly affecting resistance durability, this study provides a rationale for sustainable resistance breeding. Surprisingly, a genetic trade-off was observed between the durability of PVY resistance controlled by pvr2(3) and the spectrum of the resistance against different potyviruses. This trade-off seemed to have been resolved by the combination of minor-effect durability QTLs under long-term farmer selection.

Two Novel SNPs of PPARγ Significantly Affect Weaning Growth Traits of Nanyang Cattle.

PubMed

Huang, Jieping; Chen, Ningbo; Li, Xin; An, Shanshan; Zhao, Minghui; Sun, Taihong; Hao, Ruijie; Ma, Yun

2018-01-02

Peroxisome-proliferator-activated receptor gamma (PPARγ) is a key transcription factor that controls adipocyte differentiation and energy in mammals. Therefore, PPARγ is a potential factor influencing animal growth traits. This study primarily evaluates PPARγ as candidate gene for growth traits of cattle and identifies potential molecular marker for cattle breeding. Per previous studies, PPARγ mRNA was mainly expressed at extremely high levels in adipose tissues as shown by quantitative real-time polymerase chain reaction analysis. Three novel SNPs of the bovine PPARγ gene were identified in 514 individuals from six Chinese cattle breeds: SNP1 (AC_000179.1 g.57386668 C > G) in intron 2 and SNP2 (AC_000179.1 g.57431964 C > T) and SNP3 (AC_000179.1 g.57431994 T > C) in exon 7. The present study also investigated genetic characteristics of these SNP loci in six populations. Association analysis showed that SNP1 and SNP3 loci significantly affect weaning growth traits, especially body weight of Nanyang cattle. These results revealed that SNP1 and SNP3 are potential molecular markers for cattle breeding.

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

Quantitative variation in water-use efficiency across water regimes and its relationship with circadian, vegetative, reproductive, and leaf gas-exchange traits.

PubMed

Edwards, Christine E; Ewers, Brent E; McClung, C Robertson; Lou, Ping; Weinig, Cynthia

2012-05-01

Drought limits light harvesting, resulting in lower plant growth and reproduction. One trait important for plant drought response is water-use efficiency (WUE). We investigated (1) how the joint genetic architecture of WUE, reproductive characters, and vegetative traits changed across drought and well-watered conditions, (2) whether traits with distinct developmental bases (e.g. leaf gas exchange versus reproduction) differed in the environmental sensitivity of their genetic architecture, and (3) whether quantitative variation in circadian period was related to drought response in Brassica rapa. Overall, WUE increased in drought, primarily because stomatal conductance, and thus water loss, declined more than carbon fixation. Genotypes with the highest WUE in drought expressed the lowest WUE in well-watered conditions, and had the largest vegetative and floral organs in both treatments. Thus, large changes in WUE enabled some genotypes to approach vegetative and reproductive trait optima across environments. The genetic architecture differed for gas-exchange and vegetative traits across drought and well-watered conditions, but not for floral traits. Correlations between circadian and leaf gas-exchange traits were significant but did not vary across treatments, indicating that circadian period affects physiological function regardless of water availability. These results suggest that WUE is important for drought tolerance in Brassica rapa and that artificial selection for increased WUE in drought will not result in maladaptive expression of other traits that are correlated with WUE.

Genetic approaches in comparative and evolutionary physiology

PubMed Central

Bridgham, Jamie T.; Kelly, Scott A.; Garland, Theodore

2015-01-01

Whole animal physiological performance is highly polygenic and highly plastic, and the same is generally true for the many subordinate traits that underlie performance capacities. Quantitative genetics, therefore, provides an appropriate framework for the analysis of physiological phenotypes and can be used to infer the microevolutionary processes that have shaped patterns of trait variation within and among species. In cases where specific genes are known to contribute to variation in physiological traits, analyses of intraspecific polymorphism and interspecific divergence can reveal molecular mechanisms of functional evolution and can provide insights into the possible adaptive significance of observed sequence changes. In this review, we explain how the tools and theory of quantitative genetics, population genetics, and molecular evolution can inform our understanding of mechanism and process in physiological evolution. For example, lab-based studies of polygenic inheritance can be integrated with field-based studies of trait variation and survivorship to measure selection in the wild, thereby providing direct insights into the adaptive significance of physiological variation. Analyses of quantitative genetic variation in selection experiments can be used to probe interrelationships among traits and the genetic basis of physiological trade-offs and constraints. We review approaches for characterizing the genetic architecture of physiological traits, including linkage mapping and association mapping, and systems approaches for dissecting intermediary steps in the chain of causation between genotype and phenotype. We also discuss the promise and limitations of population genomic approaches for inferring adaptation at specific loci. We end by highlighting the role of organismal physiology in the functional synthesis of evolutionary biology. PMID:26041111

Genetic approaches in comparative and evolutionary physiology.

PubMed

Storz, Jay F; Bridgham, Jamie T; Kelly, Scott A; Garland, Theodore

2015-08-01

Whole animal physiological performance is highly polygenic and highly plastic, and the same is generally true for the many subordinate traits that underlie performance capacities. Quantitative genetics, therefore, provides an appropriate framework for the analysis of physiological phenotypes and can be used to infer the microevolutionary processes that have shaped patterns of trait variation within and among species. In cases where specific genes are known to contribute to variation in physiological traits, analyses of intraspecific polymorphism and interspecific divergence can reveal molecular mechanisms of functional evolution and can provide insights into the possible adaptive significance of observed sequence changes. In this review, we explain how the tools and theory of quantitative genetics, population genetics, and molecular evolution can inform our understanding of mechanism and process in physiological evolution. For example, lab-based studies of polygenic inheritance can be integrated with field-based studies of trait variation and survivorship to measure selection in the wild, thereby providing direct insights into the adaptive significance of physiological variation. Analyses of quantitative genetic variation in selection experiments can be used to probe interrelationships among traits and the genetic basis of physiological trade-offs and constraints. We review approaches for characterizing the genetic architecture of physiological traits, including linkage mapping and association mapping, and systems approaches for dissecting intermediary steps in the chain of causation between genotype and phenotype. We also discuss the promise and limitations of population genomic approaches for inferring adaptation at specific loci. We end by highlighting the role of organismal physiology in the functional synthesis of evolutionary biology. Copyright © 2015 the American Physiological Society.

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

Callous-Unemotional (CU) Traits in Adolescent Boys and Response to Teacher Reward and Discipline Strategies

ERIC Educational Resources Information Center

Allen, Jennifer L.; Morris, Amy; Chhoa, Celine Y.

2016-01-01

The aim of this study was to investigate the relationship between callous-unemotional (CU) traits and response to rewards and discipline in adolescent boys using a mixed-methods approach. Participants comprised 39 boys aged between 12 and 13 years and 8 teachers. Quantitative findings showed that CU traits were significantly related to punishment…

Quantitative trait loci affecting oil content, oil composition, and other agronomically important traits in Oat (Avena sativa L.)

USDA-ARS?s Scientific Manuscript database

Groat oil content and composition are important determinants of oat quality. We investigated these traits in a population of 146 recombinant inbred lines from a cross between 'Dal' (high oil) and 'Exeter' (low oil). A linkage map consisting of 475 DArT markers spanning 1271.8 cM across 40 linkage gr...

New QTL alleles for quality-related traits in spring wheat revealed by RIL population derived from supernumerary x non-supernumerary spikelet genotypes

USDA-ARS?s Scientific Manuscript database

Identifying new quantitative trait loci (QTLs) and alleles in exotic germplasm is paramount for further improvement of quality traits in wheat. In the present study, a population of recombinant inbred lines (RILs) developed from a cross between an elite wheat line (WCB414) and an exotic genotype wi...

Distribution of lod scores in oligogenic linkage analysis.

PubMed

Williams, J T; North, K E; Martin, L J; Comuzzie, A G; Göring, H H; Blangero, J

2001-01-01

In variance component oligogenic linkage analysis it can happen that the residual additive genetic variance bounds to zero when estimating the effect of the ith quantitative trait locus. Using quantitative trait Q1 from the Genetic Analysis Workshop 12 simulated general population data, we compare the observed lod scores from oligogenic linkage analysis with the empirical lod score distribution under a null model of no linkage. We find that zero residual additive genetic variance in the null model alters the usual distribution of the likelihood-ratio statistic.

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

PubMed

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

2009-01-01

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

Genomic approaches for the elucidation of genes and gene networks underlying cardiovascular traits.

PubMed

Adriaens, M E; Bezzina, C R

2018-06-22

Genome-wide association studies have shed light on the association between natural genetic variation and cardiovascular traits. However, linking a cardiovascular trait associated locus to a candidate gene or set of candidate genes for prioritization for follow-up mechanistic studies is all but straightforward. Genomic technologies based on next-generation sequencing technology nowadays offer multiple opportunities to dissect gene regulatory networks underlying genetic cardiovascular trait associations, thereby aiding in the identification of candidate genes at unprecedented scale. RNA sequencing in particular becomes a powerful tool when combined with genotyping to identify loci that modulate transcript abundance, known as expression quantitative trait loci (eQTL), or loci modulating transcript splicing known as splicing quantitative trait loci (sQTL). Additionally, the allele-specific resolution of RNA-sequencing technology enables estimation of allelic imbalance, a state where the two alleles of a gene are expressed at a ratio differing from the expected 1:1 ratio. When multiple high-throughput approaches are combined with deep phenotyping in a single study, a comprehensive elucidation of the relationship between genotype and phenotype comes into view, an approach known as systems genetics. In this review, we cover key applications of systems genetics in the broad cardiovascular field.

Distributions of Mutational Effects and the Estimation of Directional Selection in Divergent Lineages of Arabidopsis thaliana.

PubMed

Park, Briton; Rutter, Matthew T; Fenster, Charles B; Symonds, V Vaughan; Ungerer, Mark C; Townsend, Jeffrey P

2017-08-01

Mutations are crucial to evolution, providing the ultimate source of variation on which natural selection acts. Due to their key role, the distribution of mutational effects on quantitative traits is a key component to any inference regarding historical selection on phenotypic traits. In this paper, we expand on a previously developed test for selection that could be conducted assuming a Gaussian mutation effect distribution by developing approaches to also incorporate any of a family of heavy-tailed Laplace distributions of mutational effects. We apply the test to detect directional natural selection on five traits along the divergence of Columbia and Landsberg lineages of Arabidopsis thaliana , constituting the first test for natural selection in any organism using quantitative trait locus and mutation accumulation data to quantify the intensity of directional selection on a phenotypic trait. We demonstrate that the results of the test for selection can depend on the mutation effect distribution specified. Using the distributions exhibiting the best fit to mutation accumulation data, we infer that natural directional selection caused divergence in the rosette diameter and trichome density traits of the Columbia and Landsberg lineages. Copyright © 2017 by the Genetics Society of America.

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.

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

PubMed

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

2018-04-21

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

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

PubMed Central

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

2014-01-01

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

DRIFTSEL: an R package for detecting signals of natural selection in quantitative traits.

PubMed

Karhunen, M; Merilä, J; Leinonen, T; Cano, J M; Ovaskainen, O

2013-07-01

Approaches and tools to differentiate between natural selection and genetic drift as causes of population differentiation are of frequent demand in evolutionary biology. Based on the approach of Ovaskainen et al. (2011), we have developed an R package (DRIFTSEL) that can be used to differentiate between stabilizing selection, diversifying selection and random genetic drift as causes of population differentiation in quantitative traits when neutral marker and quantitative genetic data are available. Apart from illustrating the use of this method and the interpretation of results using simulated data, we apply the package on data from three-spined sticklebacks (Gasterosteus aculeatus) to highlight its virtues. DRIFTSEL can also be used to perform usual quantitative genetic analyses in common-garden study designs. © 2013 John Wiley & Sons Ltd.

P Element Transposition Contributes Substantial New Variation for a Quantitative Trait in Drosophila Melanogaster

PubMed Central

Torkamanzehi, A.; Moran, C.; Nicholas, F. W.

1992-01-01

The P-M system of transposition in Drosophila melanogaster is a powerful mutator for many visible and lethal loci. Experiments using crosses between unrelated P and M stocks to assess the importance of transposition-mediated mutations affecting quantitative loci and reponse to selection have yielded unrepeatable or ambiguous results. In a different approach, we have used a P stock produced by microinjection of the ry(506) M stock. Selection responses were compared between transposition lines that were initiated by crossing M strain females with males from the ``co-isogenic'' P strain, and ry(506) M control lines. Unlike previous attempts to quantify the effects of P element transposition, there is no possibility of P transposition in the controls. During 10 generations of selection for the quantitative trait abdominal bristle number, none of the four control lines showed any response to selection, indicative of isogenicity for those loci affecting abdominal bristle number. In contrast, three of the four transposition lines showed substantial response, with regression of cumulative response on cumulative selection differential ranging from 15% to 25%. Transposition of P elements has produced new additive genetic variance at a rate which is more than 30 times greater than the rate expected from spontaneous mutation. PMID:1317317

Quantitative trait loci controlling leaf appearance and curd initiation of cauliflower in relation to temperature.

PubMed

Hasan, Yaser; Briggs, William; Matschegewski, Claudia; Ordon, Frank; Stützel, Hartmut; Zetzsche, Holger; Groen, Simon; Uptmoor, Ralf

2016-07-01

QTL regions on chromosomes C06 and C09 are involved in temperature dependent time to curd induction in cauliflower. Temperature is the main environmental factor influencing curding time of cauliflower (Brassica oleracea var. botrytis). Temperatures above 20-22 °C inhibit development towards curding even in many summer cultivars. To identify quantitative trait loci (QTL) controlling curding time and its related traits in a wide range of different temperature regimes from 12 to 27 °C, a doubled haploid (DH) mapping population segregating for curding time was developed and days to curd initiation (DCI), leaf appearance rate (LAR), and final leaf number (FLN) were measured. The population was genotyped with 176 single nucleotide polymorphism (SNP) markers. Composite interval mapping (CIM) revealed repeatedly detected QTL for DCI on C06 and C09. The estimated additive effect increased at high temperatures. Significant QTL × environment interactions (Q × E) for FLN and DCI on C06 and C09 suggest that these hotspot regions have major influences on temperature mediated curd induction. 25 % of the DH lines did not induce curds at temperatures higher than 22 °C. Applying a binary model revealed a QTL with LOD >15 on C06. Nearly all lines carrying the allele of the reliable early maturing parental line (PL) on that locus induced curds at high temperatures while only half of the DH lines carrying the allele of the unreliable PL reached the generative phase during the experiment. Large variation in LAR was observed. QTL for LAR were detected repeatedly in several environments on C01, C04 and C06. Negative correlations between LAR and DCI and QTL co-localizations on C04 and C06 suggest that LAR has also effects on development towards curd induction.

QEEG and LORETA in Teenagers With Conduct Disorder and Psychopathic Traits.

PubMed

Calzada-Reyes, Ana; Alvarez-Amador, Alfredo; Galán-García, Lídice; Valdés-Sosa, Mitchell

2017-05-01

Few studies have investigated the impact of the psychopathic traits on the EEG of teenagers with conduct disorder (CD). To date, there is no other research studying low-resolution brain electromagnetic tomography (LORETA) technique using quantitative EEG (QEEG) analysis in adolescents with CD and psychopathic traits. To find electrophysiological differences specifically related to the psychopathic traits. The current investigation compares the QEEG and the current source density measures between adolescents with CD and psychopathic traits and adolescents with CD without psychopathic traits. The resting EEG activity and LORETA for the EEG fast spectral bands were evaluated in 42 teenagers with CD, 25 with and 17 without psychopathic traits according to the Antisocial Process Screening Device. All adolescents were assessed using the DSM-IV-TR criteria. The EEG visual inspection characteristics and the use of frequency domain quantitative analysis techniques (narrow band spectral parameters) are described. QEEG analysis showed a pattern of beta activity excess on the bilateral frontal-temporal regions and decreases of alpha band power on the left central-temporal and right frontal-central-temporal regions in the psychopathic traits group. Current source density calculated at 17.18 Hz showed an increase within fronto-temporo-striatal regions in the psychopathic relative to the nonpsychopathic traits group. These findings indicate that QEEG analysis and techniques of source localization may reveal differences in brain electrical activity among teenagers with CD and psychopathic traits, which was not obvious to visual inspection. Taken together, these results suggest that abnormalities in a fronto-temporo-striatal network play a relevant role in the neurobiological basis of psychopathic behavior.

The influence of genetic drift and selection on quantitative traits in a plant pathogenic fungus.

PubMed

Stefansson, Tryggvi S; McDonald, Bruce A; Willi, Yvonne

2014-01-01

Genetic drift and selection are ubiquitous evolutionary forces acting to shape genetic variation in populations. While their relative importance has been well studied in plants and animals, less is known about their relative importance in fungal pathogens. Because agro-ecosystems are more homogeneous environments than natural ecosystems, stabilizing selection may play a stronger role than genetic drift or diversifying selection in shaping genetic variation among populations of fungal pathogens in agro-ecosystems. We tested this hypothesis by conducting a QST/FST analysis using agricultural populations of the barley pathogen Rhynchosporium commune. Population divergence for eight quantitative traits (QST) was compared with divergence at eight neutral microsatellite loci (FST) for 126 pathogen strains originating from nine globally distributed field populations to infer the effects of genetic drift and types of selection acting on each trait. Our analyses indicated that five of the eight traits had QST values significantly lower than FST, consistent with stabilizing selection, whereas one trait, growth under heat stress (22°C), showed evidence of diversifying selection and local adaptation (QST>FST). Estimates of heritability were high for all traits (means ranging between 0.55-0.84), and average heritability across traits was negatively correlated with microsatellite gene diversity. Some trait pairs were genetically correlated and there was significant evidence for a trade-off between spore size and spore number, and between melanization and growth under benign temperature. Our findings indicate that many ecologically and agriculturally important traits are under stabilizing selection in R. commune and that high within-population genetic variation is maintained for these traits.

Harnessing quantitative genetics and genomics for understanding and improving complex traits in crops

USDA-ARS?s Scientific Manuscript database

Classical quantitative genetics aids crop improvement by providing the means to estimate heritability, genetic correlations, and predicted responses to various selection schemes. Genomics has the potential to aid quantitative genetics and applied crop improvement programs via large-scale, high-thro...

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

PubMed

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

2017-01-01

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

Impact of Sickle Cell Trait and Naturally Acquired Immunity on Uncomplicated Malaria after Controlled Human Malaria Infection in Adults in Gabon.

PubMed

Lell, Bertrand; Mordmüller, Benjamin; Dejon Agobe, Jean-Claude; Honkpehedji, Josiane; Zinsou, Jeannot; Mengue, Juliana Boex; Loembe, Marguerite Massinga; Adegnika, Ayola Akim; Held, Jana; Lalremruata, Albert; Nguyen, The Trong; Esen, Meral; Kc, Natasha; Ruben, Adam J; Chakravarty, Sumana; Lee Sim, B Kim; Billingsley, Peter F; James, Eric R; Richie, Thomas L; Hoffman, Stephen L; Kremsner, Peter G

2018-02-01

Controlled human malaria infection (CHMI) by direct venous inoculation (DVI) with 3,200 cryopreserved Plasmodium falciparum sporozoites (PfSPZ) consistently leads to parasitemia and malaria symptoms in malaria-naive adults. We used CHMI by DVI to investigate infection rates, parasite kinetics, and malaria symptoms in lifelong malaria-exposed (semi-immune) Gabonese adults with and without sickle cell trait. Eleven semi-immune Gabonese with normal hemoglobin (IA), nine with sickle cell trait (IS), and five nonimmune European controls with normal hemoglobin (NI) received 3,200 PfSPZ by DVI and were followed 28 days for parasitemia by thick blood smear (TBS) and quantitative polymerase chain reaction (qPCR) and for malaria symptoms. End points were time to parasitemia and parasitemia plus symptoms. PfSPZ Challenge was well tolerated and safe. Five of the five (100%) NI, 7/11 (64%) IA, and 5/9 (56%) IS volunteers developed parasitemia by TBS, and 5/5 (100%) NI, 9/11 (82%) IA, and 7/9 (78%) IS by qPCR, respectively. The time to parasitemia by TBS was longer in IA (geometric mean 16.9 days) and IS (19.1 days) than in NA (12.6 days) volunteers ( P = 0.016, 0.021, respectively). Five of the five, 6/9, and 1/7 volunteers with parasitemia developed symptoms ( P = 0.003, NI versus IS). Naturally adaptive immunity (NAI) to malaria significantly prolonged the time to parasitemia. Sickle cell trait seemed to prolong it further. NAI plus sickle cell trait, but not NAI alone, significantly reduced symptom rate. Twenty percent (4/20) semi-immunes demonstrated sterile protective immunity. Standardized CHMI with PfSPZ Challenge is a powerful tool for dissecting the impact of innate and naturally acquired adaptive immunity on malaria.

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

PubMed

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

2017-03-17

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

Quantitative trait loci controlling leaf venation in Arabidopsis.

PubMed

Rishmawi, Louai; Bühler, Jonas; Jaegle, Benjamin; Hülskamp, Martin; Koornneef, Maarten

2017-08-01

Leaf veins provide the mechanical support and are responsible for the transport of nutrients and water to the plant. High vein density is a prerequisite for plants to have C4 photosynthesis. We investigated the genetic variation and genetic architecture of leaf venation traits within the species Arabidopsis thaliana using natural variation. Leaf venation traits, including leaf vein density (LVD) were analysed in 66 worldwide accessions and 399 lines of the multi-parent advanced generation intercross population. It was shown that there is no correlation between LVD and photosynthesis parameters within A. thaliana. Association mapping was performed for LVD and identified 16 and 17 putative quantitative trait loci (QTLs) in the multi-parent advanced generation intercross and worldwide sets, respectively. There was no overlap between the identified QTLs suggesting that many genes can affect the traits. In addition, linkage mapping was performed using two biparental recombinant inbred line populations. Combining linkage and association mapping revealed seven candidate genes. For one of the candidate genes, RCI2c, we demonstrated its function in leaf venation patterning. © 2017 John Wiley & Sons Ltd.

Quantitative traits for the tail suspension test: automation, optimization, and BXD RI mapping.

PubMed

Lad, Heena V; Liu, Lin; Payá-Cano, José L; Fernandes, Cathy; Schalkwyk, Leonard C

2007-07-01

Immobility in the tail suspension test (TST) is considered a model of despair in a stressful situation, and acute treatment with antidepressants reduces immobility. Inbred strains of mouse exhibit widely differing baseline levels of immobility in the TST and several quantitative trait loci (QTLs) have been nominated. The labor of manual scoring and various scoring criteria make obtaining robust data and comparisons across different laboratories problematic. Several studies have validated strain gauge and video analysis methods by comparison with manual scoring. We set out to find objective criteria for automated scoring parameters that maximize the biological information obtained, using a video tracking system on tapes of tail suspension tests of 24 lines of the BXD recombinant inbred panel and the progenitor strains C57BL/6J and DBA/2J. The maximum genetic effect size is captured using the highest time resolution and a low mobility threshold. Dissecting the trait further by comparing genetic association of multiple measures reveals good evidence for loci involved in immobility on chromosomes 4 and 15. These are best seen when using a high threshold for immobility, despite the overall better heritability at the lower threshold. A second trial of the test has greater duration of immobility and a completely different genetic profile. Frequency of mobility is also an independent phenotype, with a distal chromosome 1 locus.

Genetic Modifiers of Cardiovascular Phenotype Caused by Elastin Haploinsufficiency Act by Extrinsic Noncomplementation*

PubMed Central

Kozel, Beth A.; Knutsen, Russell H.; Ye, Li; Ciliberto, Christopher H.; Broekelmann, Thomas J.; Mecham, Robert P.

2011-01-01

Elastin haploinsufficiency causes the cardiovascular complications associated with Williams-Beuren syndrome and isolated supravalvular aortic stenosis. Significant variability exists in the vascular pathology in these individuals. Using the Eln+/− mouse, we sought to identify the source of this variability. Following outcrossing of C57Bl/6J Eln+/−, two backgrounds were identified whose cardiovascular parameters deviated significantly from the parental strain. F1 progeny of the C57Bl/6J; Eln+/−x129X1/SvJ were more hypertensive and their arteries less compliant. In contrast, Eln+/− animals crossed to DBA/2J were protected from the pathologic changes associated with elastin insufficiency. Among the crosses, aortic elastin and collagen content did not correlate with quantitative vasculopathy traits. Quantitative trait locus analysis performed on F2 C57; Eln+/−x129 intercrosses identified highly significant peaks on chromosome 1 (LOD 9.7) for systolic blood pressure and on chromosome 9 (LOD 8.7) for aortic diameter. Additional peaks were identified that affect only Eln+/−, including a region upstream of Eln on chromosome 5 (LOD 4.5). Bioinformatic analysis of the quantitative trait locus peaks revealed several interesting candidates, including Ren1, Ncf1, and Nos1; genes whose functions are unrelated to elastic fiber assembly, but whose effects may synergize with elastin insufficiency to predispose to hypertension and stiffer blood vessels. Real time RT-PCR studies show background-specific increased expression of Ncf1 (a subunit of the NOX2 NAPDH oxidase) that parallel the presence of increased oxidative stress in Eln+/− aortas. This finding raises the possibility that polymorphisms in genes affecting the generation of reactive oxygen species alter cardiovascular function in individuals with elastin haploinsufficiency through extrinsic noncomplementation. PMID:22049077

A Simple and Computationally Efficient Approach to Multifactor Dimensionality Reduction Analysis of Gene-Gene Interactions for Quantitative Traits

PubMed Central

Gui, Jiang; Moore, Jason H.; Williams, Scott M.; Andrews, Peter; Hillege, Hans L.; van der Harst, Pim; Navis, Gerjan; Van Gilst, Wiek H.; Asselbergs, Folkert W.; Gilbert-Diamond, Diane

2013-01-01

We present an extension of the two-class multifactor dimensionality reduction (MDR) algorithm that enables detection and characterization of epistatic SNP-SNP interactions in the context of a quantitative trait. The proposed Quantitative MDR (QMDR) method handles continuous data by modifying MDR’s constructive induction algorithm to use a T-test. QMDR replaces the balanced accuracy metric with a T-test statistic as the score to determine the best interaction model. We used a simulation to identify the empirical distribution of QMDR’s testing score. We then applied QMDR to genetic data from the ongoing prospective Prevention of Renal and Vascular End-Stage Disease (PREVEND) study. PMID:23805232

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

PubMed

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

2015-05-01

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

Mapping Late Leaf Spot Resistance in Peanut (Arachis hypogaea) Using QTL-seq Reveals Markers for Marker-Assisted Selection.

PubMed

Clevenger, Josh; Chu, Ye; Chavarro, Carolina; Botton, Stephanie; Culbreath, Albert; Isleib, Thomas G; Holbrook, C C; Ozias-Akins, Peggy

2018-01-01

Late leaf spot (LLS; Cercosporidium personatum ) is a major fungal disease of cultivated peanut ( Arachis hypogaea ). A recombinant inbred line population segregating for quantitative field resistance was used to identify quantitative trait loci (QTL) using QTL-seq. High rates of false positive SNP calls using established methods in this allotetraploid crop obscured significant QTLs. To resolve this problem, robust parental SNPs were first identified using polyploid-specific SNP identification pipelines, leading to discovery of significant QTLs for LLS resistance. These QTLs were confirmed over 4 years of field data. Selection with markers linked to these QTLs resulted in a significant increase in resistance, showing that these markers can be immediately applied in breeding programs. This study demonstrates that QTL-seq can be used to rapidly identify QTLs controlling highly quantitative traits in polyploid crops with complex genomes. Markers identified can then be deployed in breeding programs, increasing the efficiency of selection using molecular tools. Key Message: Field resistance to late leaf spot is a quantitative trait controlled by many QTLs. Using polyploid-specific methods, QTL-seq is faster and more cost effective than QTL mapping.

Mapping Late Leaf Spot Resistance in Peanut (Arachis hypogaea) Using QTL-seq Reveals Markers for Marker-Assisted Selection

PubMed Central

Clevenger, Josh; Chu, Ye; Chavarro, Carolina; Botton, Stephanie; Culbreath, Albert; Isleib, Thomas G.; Holbrook, C. C.; Ozias-Akins, Peggy

2018-01-01

Late leaf spot (LLS; Cercosporidium personatum) is a major fungal disease of cultivated peanut (Arachis hypogaea). A recombinant inbred line population segregating for quantitative field resistance was used to identify quantitative trait loci (QTL) using QTL-seq. High rates of false positive SNP calls using established methods in this allotetraploid crop obscured significant QTLs. To resolve this problem, robust parental SNPs were first identified using polyploid-specific SNP identification pipelines, leading to discovery of significant QTLs for LLS resistance. These QTLs were confirmed over 4 years of field data. Selection with markers linked to these QTLs resulted in a significant increase in resistance, showing that these markers can be immediately applied in breeding programs. This study demonstrates that QTL-seq can be used to rapidly identify QTLs controlling highly quantitative traits in polyploid crops with complex genomes. Markers identified can then be deployed in breeding programs, increasing the efficiency of selection using molecular tools. Key Message: Field resistance to late leaf spot is a quantitative trait controlled by many QTLs. Using polyploid-specific methods, QTL-seq is faster and more cost effective than QTL mapping. PMID:29459876

Teacher Perception of Principals' Leadership Traits and Middle School Math and Science Teachers' Job Satisfaction: A Causal-Comparative and Correlational Study

ERIC Educational Resources Information Center

Cousar, Theresa Ann

2017-01-01

The purpose of this quantitative study was to examine middle school teachers' job satisfaction (low vs. high) and how teachers perceive principals' leadership traits. The study used a causal-comparative and correlational design. The teachers were divided into two job satisfaction level groups. Teacher perception of principal leadership traits for…

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

PubMed Central

2010-01-01

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

Quantitative analysis of bristle number in Drosophila mutants identifies genes involved in neural development

NASA Technical Reports Server (NTRS)

Norga, Koenraad K.; Gurganus, Marjorie C.; Dilda, Christy L.; Yamamoto, Akihiko; Lyman, Richard F.; Patel, Prajal H.; Rubin, Gerald M.; Hoskins, Roger A.; Mackay, Trudy F.; Bellen, Hugo J.

2003-01-01

BACKGROUND: The identification of the function of all genes that contribute to specific biological processes and complex traits is one of the major challenges in the postgenomic era. One approach is to employ forward genetic screens in genetically tractable model organisms. In Drosophila melanogaster, P element-mediated insertional mutagenesis is a versatile tool for the dissection of molecular pathways, and there is an ongoing effort to tag every gene with a P element insertion. However, the vast majority of P element insertion lines are viable and fertile as homozygotes and do not exhibit obvious phenotypic defects, perhaps because of the tendency for P elements to insert 5' of transcription units. Quantitative genetic analysis of subtle effects of P element mutations that have been induced in an isogenic background may be a highly efficient method for functional genome annotation. RESULTS: Here, we have tested the efficacy of this strategy by assessing the extent to which screening for quantitative effects of P elements on sensory bristle number can identify genes affecting neural development. We find that such quantitative screens uncover an unusually large number of genes that are known to function in neural development, as well as genes with yet uncharacterized effects on neural development, and novel loci. CONCLUSIONS: Our findings establish the use of quantitative trait analysis for functional genome annotation through forward genetics. Similar analyses of quantitative effects of P element insertions will facilitate our understanding of the genes affecting many other complex traits in Drosophila.

A strategy to apply quantitative epistasis analysis on developmental traits.

PubMed

Labocha, Marta K; Yuan, Wang; Aleman-Meza, Boanerges; Zhong, Weiwei

2017-05-15

Genetic interactions are keys to understand complex traits and evolution. Epistasis analysis is an effective method to map genetic interactions. Large-scale quantitative epistasis analysis has been well established for single cells. However, there is a substantial lack of such studies in multicellular organisms and their complex phenotypes such as development. Here we present a method to extend quantitative epistasis analysis to developmental traits. In the nematode Caenorhabditis elegans, we applied RNA interference on mutants to inactivate two genes, used an imaging system to quantitatively measure phenotypes, and developed a set of statistical methods to extract genetic interactions from phenotypic measurement. Using two different C. elegans developmental phenotypes, body length and sex ratio, as examples, we showed that this method could accommodate various metazoan phenotypes with performances comparable to those methods in single cell growth studies. Comparing with qualitative observations, this method of quantitative epistasis enabled detection of new interactions involving subtle phenotypes. For example, several sex-ratio genes were found to interact with brc-1 and brd-1, the orthologs of the human breast cancer genes BRCA1 and BARD1, respectively. We confirmed the brc-1 interactions with the following genes in DNA damage response: C34F6.1, him-3 (ortholog of HORMAD1, HORMAD2), sdc-1, and set-2 (ortholog of SETD1A, SETD1B, KMT2C, KMT2D), validating the effectiveness of our method in detecting genetic interactions. We developed a reliable, high-throughput method for quantitative epistasis analysis of developmental phenotypes.

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

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

PubMed

Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao

2016-04-01

To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.

Genetic Map Construction and Quantitative Trait Locus (QTL) Detection of Growth-Related Traits in Litopenaeus vannamei for Selective Breeding Applications

PubMed Central

Andriantahina, Farafidy; Liu, Xiaolin; Huang, Hao

2013-01-01

Growth is a priority trait from the point of view of genetic improvement. Molecular markers linked to quantitative trait loci (QTL) have been regarded as useful for marker-assisted selection (MAS) in complex traits as growth. Using an intermediate F2 cross of slow and fast growth parents, a genetic linkage map of Pacific whiteleg shrimp, Litopenaeusvannamei , based on amplified fragment length polymorphisms (AFLP) and simple sequence repeats (SSR) markers was constructed. Meanwhile, QTL analysis was performed for growth-related traits. The linkage map consisted of 451 marker loci (429 AFLPs and 22 SSRs) which formed 49 linkage groups with an average marker space of 7.6 cM; they spanned a total length of 3627.6 cM, covering 79.50% of estimated genome size. 14 QTLs were identified for growth-related traits, including three QTLs for body weight (BW), total length (TL) and partial carapace length (PCL), two QTLs for body length (BL), one QTL for first abdominal segment depth (FASD), third abdominal segment depth (TASD) and first abdominal segment width (FASW), which explained 2.62 to 61.42% of phenotypic variation. Moreover, comparison of linkage maps between L . vannamei and Penaeus japonicus was applied, providing a new insight into the genetic base of QTL affecting the growth-related traits. The new results will be useful for conducting MAS breeding schemes in L . vannamei . PMID:24086466

Location of Vibrio anguillarum resistance-associated trait loci in half-smooth tongue sole Cynoglossus semilaevis at its microsatellite linkage map

NASA Astrophysics Data System (ADS)

Tang, Zhihong; Guo, Li; Liu, Yang; Shao, Changwei; Chen, Songlin; Yang, Guanpin

2016-11-01

A cultured female half-smooth tongue sole ( Cynoglossus semilaevis) was crossed with a wild male, yielding the first filial generation of pseudo-testcrossing from which 200 fish were randomly selected to locate the Vibrio anguillarum resistance trait in half-smooth tongue sole at its microsatellite linkage map. In total, 129 microsatellites were arrayed into 18 linkage groups, ≥4 each. The map reconstructed was 852.85 cM in length with an average spacing of 7.68 cM, covering 72.07% of that expected (1 183.35 cM). The V. anguillarum resistance trait was a composite rather than a unit trait, which was tentatively partitioned into Survival time in Hours After V. anguillarum Infection (SHAVI) and Immunity of V. Anguillarum Infection (IVAI). Above a logarithm of the odds (LOD) threshold of 2.5, 18 loci relative to SHAVI and 3 relative to IVAI were identified. The 3 loci relative to IVAI explained 18.78%, 5.87% and 6.50% of the total phenotypic variation in immunity. The microsatellites bounding the 3 quantitative trait loci (QTLs) of IVAI may in future aid to the selection of V. anguillarum-immune half-smooth tongue sole varieties, and facilitate cloning the gene(s) controlling such immunity.

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

PubMed

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

2017-04-01

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

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.

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

PubMed Central

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

2007-01-01

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

Quantile-based permutation thresholds for quantitative trait loci hotspots.

PubMed

Neto, Elias Chaibub; Keller, Mark P; Broman, Andrew F; Attie, Alan D; Jansen, Ritsert C; Broman, Karl W; Yandell, Brian S

2012-08-01

Quantitative trait loci (QTL) hotspots (genomic locations affecting many traits) are a common feature in genetical genomics studies and are biologically interesting since they may harbor critical regulators. Therefore, statistical procedures to assess the significance of hotspots are of key importance. One approach, randomly allocating observed QTL across the genomic locations separately by trait, implicitly assumes all traits are uncorrelated. Recently, an empirical test for QTL hotspots was proposed on the basis of the number of traits that exceed a predetermined LOD value, such as the standard permutation LOD threshold. The permutation null distribution of the maximum number of traits across all genomic locations preserves the correlation structure among the phenotypes, avoiding the detection of spurious hotspots due to nongenetic correlation induced by uncontrolled environmental factors and unmeasured variables. However, by considering only the number of traits above a threshold, without accounting for the magnitude of the LOD scores, relevant information is lost. In particular, biologically interesting hotspots composed of a moderate to small number of traits with strong LOD scores may be neglected as nonsignificant. In this article we propose a quantile-based permutation approach that simultaneously accounts for the number and the LOD scores of traits within the hotspots. By considering a sliding scale of mapping thresholds, our method can assess the statistical significance of both small and large hotspots. Although the proposed approach can be applied to any type of heritable high-volume "omic" data set, we restrict our attention to expression (e)QTL analysis. We assess and compare the performances of these three methods in simulations and we illustrate how our approach can effectively assess the significance of moderate and small hotspots with strong LOD scores in a yeast expression data set.

Air Pollution Exposure during Pregnancy and Childhood Autistic Traits in Four European Population-Based Cohort Studies: The ESCAPE Project

PubMed Central

Guxens, Mònica; Ghassabian, Akhgar; Gong, Tong; Garcia-Esteban, Raquel; Porta, Daniela; Giorgis-Allemand, Lise; Almqvist, Catarina; Aranbarri, Aritz; Beelen, Rob; Badaloni, Chiara; Cesaroni, Giulia; de Nazelle, Audrey; Estarlich, Marisa; Forastiere, Francesco; Forns, Joan; Gehring, Ulrike; Ibarluzea, Jesús; Jaddoe, Vincent W.V.; Korek, Michal; Lichtenstein, Paul; Nieuwenhuijsen, Mark J.; Rebagliato, Marisa; Slama, Rémy; Tiemeier, Henning; Verhulst, Frank C.; Volk, Heather E.; Pershagen, Göran; Brunekreef, Bert; Sunyer, Jordi

2015-01-01

Background Prenatal exposure to air pollutants has been suggested as a possible etiologic factor for the occurrence of autism spectrum disorder. Objectives We aimed to assess whether prenatal air pollution exposure is associated with childhood autistic traits in the general population. Methods Ours was a collaborative study of four European population-based birth/child cohorts—CATSS (Sweden), Generation R (the Netherlands), GASPII (Italy), and INMA (Spain). Nitrogen oxides (NO2, NOx) and particulate matter (PM) with diameters of ≤ 2.5 μm (PM2.5), ≤ 10 μm (PM10), and between 2.5 and 10 μm (PMcoarse), and PM2.5 absorbance were estimated for birth addresses by land-use regression models based on monitoring campaigns performed between 2008 and 2011. Levels were extrapolated back in time to exact pregnancy periods. We quantitatively assessed autistic traits when the child was between 4 and 10 years of age. Children were classified with autistic traits within the borderline/clinical range and within the clinical range using validated cut-offs. Adjusted cohort-specific effect estimates were combined using random-effects meta-analysis. Results A total of 8,079 children were included. Prenatal air pollution exposure was not associated with autistic traits within the borderline/clinical range (odds ratio = 0.94; 95% CI: 0.81, 1.10 per each 10-μg/m3 increase in NO2 pregnancy levels). Similar results were observed in the different cohorts, for the other pollutants, and in assessments of children with autistic traits within the clinical range or children with autistic traits as a quantitative score. Conclusions Prenatal exposure to NO2 and PM was not associated with autistic traits in children from 4 to 10 years of age in four European population-based birth/child cohort studies. Citation Guxens M, Ghassabian A, Gong T, Garcia-Esteban R, Porta D, Giorgis-Allemand L, Almqvist C, Aranbarri A, Beelen R, Badaloni C, Cesaroni G, de Nazelle A, Estarlich M, Forastiere F, Forns J, Gehring U, Ibarluzea J, Jaddoe VW, Korek M, Lichtenstein P, Nieuwenhuijsen MJ, Rebagliato M, Slama R, Tiemeier H, Verhulst FC, Volk HE, Pershagen G, Brunekreef B, Sunyer J. 2016. Air pollution exposure during pregnancy and childhood autistic traits in four European population-based cohort studies: the ESCAPE Project. Environ Health Perspect 124:133–140; http://dx.doi.org/10.1289/ehp.1408483 PMID:26068947

Quantitative trait locus mapping under irrigated and drought treatments based on a novel genetic linkage map in mungbean (Vigna radiata L.).

PubMed

Liu, Changyou; Wu, Jing; Wang, Lanfen; Fan, Baojie; Cao, Zhimin; Su, Qiuzhu; Zhang, Zhixiao; Wang, Yan; Tian, Jing; Wang, Shumin

2017-11-01

A novel genetic linkage map was constructed using SSR markers and stable QTLs were identified for six drought tolerance related-traits using single-environment analysis under irrigation and drought treatments. Mungbean (Vigna radiata L.) is one of the most important leguminous food crops. However, mungbean production is seriously constrained by drought. Isolation of drought-responsive genetic elements and marker-assisted selection breeding will benefit from the detection of quantitative trait locus (QTLs) for traits related to drought tolerance. In this study, we developed a full-coverage genetic linkage map based on simple sequence repeat (SSR) markers using a recombinant inbred line (RIL) population derived from an intra-specific cross between two drought-resistant varieties. This novel map was anchored with 313 markers. The total map length was 1010.18 cM across 11 linkage groups, covering the entire genome of mungbean with a saturation of one marker every 3.23 cM. We subsequently detected 58 QTLs for plant height (PH), maximum leaf area (MLA), biomass (BM), relative water content, days to first flowering, and seed yield (Yield) and 5 for the drought tolerance index of 3 traits in irrigated and drought environments at 2 locations. Thirty-eight of these QTLs were consistently detected two or more times at similar linkage positions. Notably, qPH5A and qMLA2A were consistently identified in marker intervals from GMES5773 to MUS128 in LG05 and from Mchr11-34 to the HAAS_VR_1812 region in LG02 in four environments, contributing 6.40-20.06% and 6.97-7.94% of the observed phenotypic variation, respectively. None of these QTLs shared loci with previously identified drought-related loci from mungbean. The results of these analyses might facilitate the isolation of drought-related genes and help to clarify the mechanism of drought tolerance in mungbean.

Quantitative genetics of disease traits.

PubMed

Wray, N R; Visscher, P M

2015-04-01

John James authored two key papers on the theory of risk to relatives for binary disease traits and the relationship between parameters on the observed binary scale and an unobserved scale of liability (James Annals of Human Genetics, 1971; 35: 47; Reich, James and Morris Annals of Human Genetics, 1972; 36: 163). These two papers are John James' most cited papers (198 and 328 citations, November 2014). They have been influential in human genetics and have recently gained renewed popularity because of their relevance to the estimation of quantitative genetics parameters for disease traits using SNP data. In this review, we summarize the two early papers and put them into context. We show recent extensions of the theory for ascertained case-control data and review recent applications in human genetics. © 2015 Blackwell Verlag GmbH.

Construction of a genetic linkage map and analysis of quantitative trait loci associated with the agronomically important traits of Pleurotus eryngii

Treesearch

Chak Han Im; Young-Hoon Park; Kenneth E. Hammel; Bokyung Park; Soon Wook Kwon; Hojin Ryu; Jae-San Ryu

2016-01-01

Breeding new strains with improved traits is a long-standing goal of mushroom breeders that can be expedited by marker-assisted selection (MAS). We constructed a genetic linkage map of Pleurotus eryngii based on segregation analysis of markers in postmeiotic monokaryons from KNR2312. In total, 256 loci comprising 226 simple sequence-repeat (SSR) markers, 2 mating-type...

A genome scan for selection signatures comparing farmed Atlantic salmon with two wild populations: Testing colocalization among outlier markers, candidate genes, and quantitative trait loci for production traits.

PubMed

Liu, Lei; Ang, Keng Pee; Elliott, J A K; Kent, Matthew Peter; Lien, Sigbjørn; MacDonald, Danielle; Boulding, Elizabeth Grace

2017-03-01

Comparative genome scans can be used to identify chromosome regions, but not traits, that are putatively under selection. Identification of targeted traits may be more likely in recently domesticated populations under strong artificial selection for increased production. We used a North American Atlantic salmon 6K SNP dataset to locate genome regions of an aquaculture strain (Saint John River) that were highly diverged from that of its putative wild founder population (Tobique River). First, admixed individuals with partial European ancestry were detected using STRUCTURE and removed from the dataset. Outlier loci were then identified as those showing extreme differentiation between the aquaculture population and the founder population. All Arlequin methods identified an overlapping subset of 17 outlier loci, three of which were also identified by BayeScan. Many outlier loci were near candidate genes and some were near published quantitative trait loci (QTLs) for growth, appetite, maturity, or disease resistance. Parallel comparisons using a wild, nonfounder population (Stewiacke River) yielded only one overlapping outlier locus as well as a known maturity QTL. We conclude that genome scans comparing a recently domesticated strain with its wild founder population can facilitate identification of candidate genes for traits known to have been under strong artificial selection.

Genetic Mapping of Quantitative Trait Loci Controlling Growth and Wood Quality Traits in Eucalyptus Grandis Using a Maternal Half-Sib Family and Rapd Markers

PubMed Central

Grattapaglia, D.; Bertolucci, FLG.; Penchel, R.; Sederoff, R. R.

1996-01-01

Quantitative trait loci (QTL) mapping of forest productivity traits was performed using an open pollinated half-sib family of Eucalyptus grandis. For volume growth, a sequential QTL mapping approach was applied using bulk segregant analysis (BSA), selective genotyping (SG) and cosegregation analysis (CSA). Despite the low heritability of this trait and the heterogeneous genetic background employed for mapping. BSA detected one putative QTL and SG two out of the three later found by CSA. The three putative QTL for volume growth were found to control 13.7% of the phenotypic variation, corresponding to an estimated 43.7% of the genetic variation. For wood specific gravity five QTL were identified controlling 24.7% of the phenotypic variation corresponding to 49% of the genetic variation. Overlapping QTL for CBH, WSG and percentage dry weight of bark were observed. A significant case of digenic epistasis was found, involving unlinked QTL for volume. Our results demonstrate the applicability of the within half-sib design for QTL mapping in forest trees and indicate the existence of major genes involved in the expression of economically important traits related to forest productivity in Eucalyptus grandis. These findings have important implications for marker-assisted tree breeding. PMID:8913761

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

PubMed Central

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

2015-01-01

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

MaGelLAn 1.0: a software to facilitate quantitative and population genetic analysis of maternal inheritance by combination of molecular and pedigree information.

PubMed

Ristov, Strahil; Brajkovic, Vladimir; Cubric-Curik, Vlatka; Michieli, Ivan; Curik, Ino

2016-09-10

Identification of genes or even nucleotides that are responsible for quantitative and adaptive trait variation is a difficult task due to the complex interdependence between a large number of genetic and environmental factors. The polymorphism of the mitogenome is one of the factors that can contribute to quantitative trait variation. However, the effects of the mitogenome have not been comprehensively studied, since large numbers of mitogenome sequences and recorded phenotypes are required to reach the adequate power of analysis. Current research in our group focuses on acquiring the necessary mitochondria sequence information and analysing its influence on the phenotype of a quantitative trait. To facilitate these tasks we have produced software for processing pedigrees that is optimised for maternal lineage analysis. We present MaGelLAn 1.0 (maternal genealogy lineage analyser), a suite of four Python scripts (modules) that is designed to facilitate the analysis of the impact of mitogenome polymorphism on quantitative trait variation by combining molecular and pedigree information. MaGelLAn 1.0 is primarily used to: (1) optimise the sampling strategy for molecular analyses; (2) identify and correct pedigree inconsistencies; and (3) identify maternal lineages and assign the corresponding mitogenome sequences to all individuals in the pedigree, this information being used as input to any of the standard software for quantitative genetic (association) analysis. In addition, MaGelLAn 1.0 allows computing the mitogenome (maternal) effective population sizes and probability of mitogenome (maternal) identity that are useful for conservation management of small populations. MaGelLAn is the first tool for pedigree analysis that focuses on quantitative genetic analyses of mitogenome data. It is conceived with the purpose to significantly reduce the effort in handling and preparing large pedigrees for processing the information linked to maternal lines. The software source code, along with the manual and the example files can be downloaded at http://lissp.irb.hr/software/magellan-1-0/ and https://github.com/sristov/magellan .

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

PubMed

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

2005-09-01

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

Differential contribution of two Ppd-1 homoeoalleles to early-flowering phenotype in Nepalese and Japanese varieties of common wheat.

PubMed

Nguyen, Anh T; Iehisa, Julio C M; Mizuno, Nobuyuki; Nitta, Miyuki; Nasuda, Shuhei; Takumi, Shigeo

2013-12-01

Wheat landraces carry abundant genetic variation in heading and flowering times. Here, we studied flowering-related traits of two Nepalese varieties, KU-4770 and KU-180 and a Japanese wheat cultivar, Shiroganekomugi (SGK). These three wheat varieties showed similar flowering time in a common garden experiment. In total, five significant quantitative trait loci (QTLs) for three examined traits, the heading, flowering and maturation times, were detected using an F2 population of SGK/KU-4770. The QTLs were found at the Ppd-1 loci on chromosomes 2B and 2D and the 2B QTL was also confirmed in another F2 population of SGK/KU-180. The Ppd-D1 allele from SGK and the Ppd-B1 alleles from the two Nepalese varieties might be causal for early-flowering phenotype. The SGK Ppd-D1 allele contained a 2-kb deletion in the 5' upstream region, indicating a photoperiod-insensitive Ppd-D1a allele. Real-time PCR analysis estimating the Ppd-B1 copy number revealed that the two Nepalese varieties included two intact Ppd-B1 copies, putatively resulting in photoperiod insensitivity and an early-flowering phenotype. The two photoperiod-insensitive Ppd-1 homoeoalleles could independently contribute to segregation of early-flowering individuals in the two F2 populations. Therefore, wheat landraces are genetic resources for discovery of alleles useful for improving wheat heading or flowering times.

Differential contribution of two Ppd-1 homoeoalleles to early-flowering phenotype in Nepalese and Japanese varieties of common wheat

PubMed Central

Nguyen, Anh T.; Iehisa, Julio C. M.; Mizuno, Nobuyuki; Nitta, Miyuki; Nasuda, Shuhei; Takumi, Shigeo

2013-01-01

Wheat landraces carry abundant genetic variation in heading and flowering times. Here, we studied flowering-related traits of two Nepalese varieties, KU-4770 and KU-180 and a Japanese wheat cultivar, Shiroganekomugi (SGK). These three wheat varieties showed similar flowering time in a common garden experiment. In total, five significant quantitative trait loci (QTLs) for three examined traits, the heading, flowering and maturation times, were detected using an F2 population of SGK/KU-4770. The QTLs were found at the Ppd-1 loci on chromosomes 2B and 2D and the 2B QTL was also confirmed in another F2 population of SGK/KU-180. The Ppd-D1 allele from SGK and the Ppd-B1 alleles from the two Nepalese varieties might be causal for early-flowering phenotype. The SGK Ppd-D1 allele contained a 2-kb deletion in the 5′ upstream region, indicating a photoperiod-insensitive Ppd-D1a allele. Real-time PCR analysis estimating the Ppd-B1 copy number revealed that the two Nepalese varieties included two intact Ppd-B1 copies, putatively resulting in photoperiod insensitivity and an early-flowering phenotype. The two photoperiod-insensitive Ppd-1 homoeoalleles could independently contribute to segregation of early-flowering individuals in the two F2 populations. Therefore, wheat landraces are genetic resources for discovery of alleles useful for improving wheat heading or flowering times. PMID:24399909

Genetic data analysis for plant and animal breeding

USDA-ARS?s Scientific Manuscript database

This book is an advanced textbook covering the application of quantitative genetics theory to analysis of actual data (both trait and DNA marker information) for breeding populations of crops, trees, and animals. Chapter 1 is an introduction to basic software used for trait data analysis. Chapter 2 ...

Genomic Studies in Soybean: Toward Understanding Seed Oil and Protein Production

USDA-ARS?s Scientific Manuscript database

The molecular mechanisms that influence soybean seed composition are not well understood. Insight into the genetic controls involved in these traits is important for future soybean improvement. In this study, we identified candidate genes at the major soybean protein quantitative trait locus at Link...

Phenotypic selection in natural populations: what limits directional selection?

PubMed

Kingsolver, Joel G; Diamond, Sarah E

2011-03-01

Studies of phenotypic selection document directional selection in many natural populations. What factors reduce total directional selection and the cumulative evolutionary responses to selection? We combine two data sets for phenotypic selection, representing more than 4,600 distinct estimates of selection from 143 studies, to evaluate the potential roles of fitness trade-offs, indirect (correlated) selection, temporally varying selection, and stabilizing selection for reducing net directional selection and cumulative responses to selection. We detected little evidence that trade-offs among different fitness components reduced total directional selection in most study systems. Comparisons of selection gradients and selection differentials suggest that correlated selection frequently reduced total selection on size but not on other types of traits. The direction of selection on a trait often changes over time in many temporally replicated studies, but these fluctuations have limited impact in reducing cumulative directional selection in most study systems. Analyses of quadratic selection gradients indicated stabilizing selection on body size in at least some studies but provided little evidence that stabilizing selection is more common than disruptive selection for most traits or study systems. Our analyses provide little evidence that fitness trade-offs, correlated selection, or stabilizing selection strongly constrains the directional selection reported for most quantitative traits.

The genetic architecture of photosynthesis and plant growth-related traits in tomato.

PubMed

de Oliveira Silva, Franklin Magnum; Lichtenstein, Gabriel; Alseekh, Saleh; Rosado-Souza, Laise; Conte, Mariana; Suguiyama, Vanessa Fuentes; Lira, Bruno Silvestre; Fanourakis, Dimitrios; Usadel, Björn; Bhering, Leonardo Lopes; DaMatta, Fábio M; Sulpice, Ronan; Araújo, Wagner L; Rossi, Magdalena; de Setta, Nathalia; Fernie, Alisdair R; Carrari, Fernando; Nunes-Nesi, Adriano

2018-02-01

To identify genomic regions involved in the regulation of fundamental physiological processes such as photosynthesis and respiration, a population of Solanum pennellii introgression lines was analyzed. We determined phenotypes for physiological, metabolic, and growth related traits, including gas exchange and chlorophyll fluorescence parameters. Data analysis allowed the identification of 208 physiological and metabolic quantitative trait loci with 33 of these being associated to smaller intervals of the genomic regions, termed BINs. Eight BINs were identified that were associated with higher assimilation rates than the recurrent parent M82. Two and 10 genomic regions were related to shoot and root dry matter accumulation, respectively. Nine genomic regions were associated with starch levels, whereas 12 BINs were associated with the levels of other metabolites. Additionally, a comprehensive and detailed annotation of the genomic regions spanning these quantitative trait loci allowed us to identify 87 candidate genes that putatively control the investigated traits. We confirmed 8 of these at the level of variance in gene expression. Taken together, our results allowed the identification of candidate genes that most likely regulate photosynthesis, primary metabolism, and plant growth and as such provide new avenues for crop improvement. © 2017 John Wiley & Sons Ltd.

Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes

PubMed Central

2013-01-01

Motivation Multivariate quantitative traits arise naturally in recent neuroimaging genetics studies, in which both structural and functional variability of the human brain is measured non-invasively through techniques such as magnetic resonance imaging (MRI). There is growing interest in detecting genetic variants associated with such multivariate traits, especially in genome-wide studies. Random forests (RFs) classifiers, which are ensembles of decision trees, are amongst the best performing machine learning algorithms and have been successfully employed for the prioritisation of genetic variants in case-control studies. RFs can also be applied to produce gene rankings in association studies with multivariate quantitative traits, and to estimate genetic similarities measures that are predictive of the trait. However, in studies involving hundreds of thousands of SNPs and high-dimensional traits, a very large ensemble of trees must be inferred from the data in order to obtain reliable rankings, which makes the application of these algorithms computationally prohibitive. Results We have developed a parallel version of the RF algorithm for regression and genetic similarity learning tasks in large-scale population genetic association studies involving multivariate traits, called PaRFR (Parallel Random Forest Regression). Our implementation takes advantage of the MapReduce programming model and is deployed on Hadoop, an open-source software framework that supports data-intensive distributed applications. Notable speed-ups are obtained by introducing a distance-based criterion for node splitting in the tree estimation process. PaRFR has been applied to a genome-wide association study on Alzheimer's disease (AD) in which the quantitative trait consists of a high-dimensional neuroimaging phenotype describing longitudinal changes in the human brain structure. PaRFR provides a ranking of SNPs associated to this trait, and produces pair-wise measures of genetic proximity that can be directly compared to pair-wise measures of phenotypic proximity. Several known AD-related variants have been identified, including APOE4 and TOMM40. We also present experimental evidence supporting the hypothesis of a linear relationship between the number of top-ranked mutated states, or frequent mutation patterns, and an indicator of disease severity. Availability The Java codes are freely available at http://www2.imperial.ac.uk/~gmontana. PMID:24564704

Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes.

PubMed

Wang, Yue; Goh, Wilson; Wong, Limsoon; Montana, Giovanni

2013-01-01

Multivariate quantitative traits arise naturally in recent neuroimaging genetics studies, in which both structural and functional variability of the human brain is measured non-invasively through techniques such as magnetic resonance imaging (MRI). There is growing interest in detecting genetic variants associated with such multivariate traits, especially in genome-wide studies. Random forests (RFs) classifiers, which are ensembles of decision trees, are amongst the best performing machine learning algorithms and have been successfully employed for the prioritisation of genetic variants in case-control studies. RFs can also be applied to produce gene rankings in association studies with multivariate quantitative traits, and to estimate genetic similarities measures that are predictive of the trait. However, in studies involving hundreds of thousands of SNPs and high-dimensional traits, a very large ensemble of trees must be inferred from the data in order to obtain reliable rankings, which makes the application of these algorithms computationally prohibitive. We have developed a parallel version of the RF algorithm for regression and genetic similarity learning tasks in large-scale population genetic association studies involving multivariate traits, called PaRFR (Parallel Random Forest Regression). Our implementation takes advantage of the MapReduce programming model and is deployed on Hadoop, an open-source software framework that supports data-intensive distributed applications. Notable speed-ups are obtained by introducing a distance-based criterion for node splitting in the tree estimation process. PaRFR has been applied to a genome-wide association study on Alzheimer's disease (AD) in which the quantitative trait consists of a high-dimensional neuroimaging phenotype describing longitudinal changes in the human brain structure. PaRFR provides a ranking of SNPs associated to this trait, and produces pair-wise measures of genetic proximity that can be directly compared to pair-wise measures of phenotypic proximity. Several known AD-related variants have been identified, including APOE4 and TOMM40. We also present experimental evidence supporting the hypothesis of a linear relationship between the number of top-ranked mutated states, or frequent mutation patterns, and an indicator of disease severity. The Java codes are freely available at http://www2.imperial.ac.uk/~gmontana.

Hd6, a rice quantitative trait locus involved in photoperiod sensitivity, encodes the α subunit of protein kinase CK2

PubMed Central

Takahashi, Yuji; Shomura, Ayahiko; Sasaki, Takuji; Yano, Masahiro

2001-01-01

Hd6 is a quantitative trait locus involved in rice photoperiod sensitivity. It was detected in backcross progeny derived from a cross between the japonica variety Nipponbare and the indica variety Kasalath. To isolate a gene at Hd6, we used a large segregating population for the high-resolution and fine-scale mapping of Hd6 and constructed genomic clone contigs around the Hd6 region. Linkage analysis with P1-derived artificial chromosome clone-derived DNA markers delimited Hd6 to a 26.4-kb genomic region. We identified a gene encoding the α subunit of protein kinase CK2 (CK2α) in this region. The Nipponbare allele of CK2α contains a premature stop codon, and the resulting truncated product is undoubtedly nonfunctional. Genetic complementation analysis revealed that the Kasalath allele of CK2α increases days-to-heading. Map-based cloning with advanced backcross progeny enabled us to identify a gene underlying a quantitative trait locus even though it exhibited a relatively small effect on the phenotype. PMID:11416158

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

PubMed

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

2016-01-01

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

Little effect of HSP90 inhibition on the quantitative wing traits variation in Drosophila melanogaster.

PubMed

Takahashi, Kazuo H

2017-02-01

Drosophila wings have been a model system to study the effect of HSP90 on quantitative trait variation. The effect of HSP90 inhibition on environmental buffering of wing morphology varies among studies while the genetic buffering effect of it was examined in only one study and was not detected. Variable results so far might show that the genetic background influences the environmental and genetic buffering effect of HSP90. In the previous studies, the number of the genetic backgrounds used is limited. To examine the effect of HSP90 inhibition with a larger number of genetic backgrounds than the previous studies, 20 wild-type strains of Drosophila melanogaster were used in this study. Here I investigated the effect of HSP90 inhibition on the environmental buffering of wing shape and size by assessing within-individual and among-individual variations, and as a result, I found little or very weak effects on environmental and genetic buffering. The current results suggest that the role of HSP90 as a global regulator of environmental and genetic buffering is limited at least in quantitative traits.

Mapping Quantitative Trait Loci in Crosses between Outbred Lines Using Least Squares

PubMed Central

Haley, C. S.; Knott, S. A.; Elsen, J. M.

1994-01-01

The use of genetic maps based upon molecular markers has allowed the dissection of some of the factors underlying quantitative variation in crosses between inbred lines. For many species crossing inbred lines is not a practical proposition, although crosses between genetically very different outbred lines are possible. Here we develop a least squares method for the analysis of crosses between outbred lines which simultaneously uses information from multiple linked markers. The method is suitable for crosses where the lines may be segregating at marker loci but can be assumed to be fixed for alternative alleles at the major quantitative trait loci (QTLs) affecting the traits under analysis (e.g., crosses between divergent selection lines or breeds with different selection histories). The simultaneous use of multiple markers from a linkage group increases the sensitivity of the test statistic, and thus the power for the detection of QTLs, compared to the use of single markers or markers flanking an interval. The gain is greater for more closely spaced markers and for markers of lower information content. Use of multiple markers can also remove the bias in the estimated position and effect of a QTL which may result when different markers in a linkage group vary in their heterozygosity in the F(1) (and thus in their information content) and are considered only singly or a pair at a time. The method is relatively simple to apply so that more complex models can be fitted than is currently possible by maximum likelihood. Thus fixed effects and effects of background genotype can be fitted simultaneously with the exploration of a single linkage group which will increase the power to detect QTLs by reducing the residual variance. More complex models with several QTLs in the same linkage group and two-locus interactions between QTLs can similarly be examined. Thus least squares provides a powerful tool to extend the range of crosses from which QTLs can be dissected whilst at the same time allowing flexible and realistic models to be explored. PMID:8005424

Genetic Architecture of Ear Fasciation in Maize (Zea mays) under QTL Scrutiny

PubMed Central

Mendes-Moreira, Pedro; Alves, Mara L.; Satovic, Zlatko; dos Santos, João Pacheco; Santos, João Nina; Souza, João Cândido; Pêgo, Silas E.; Hallauer, Arnel R.; Vaz Patto, Maria Carlota

2015-01-01

Maize ear fasciation Knowledge of the genes affecting maize ear inflorescence may lead to better grain yield modeling. Maize ear fasciation, defined as abnormal flattened ears with high kernel row number, is a quantitative trait widely present in Portuguese maize landraces. Material and Methods Using a segregating population derived from an ear fasciation contrasting cross (consisting of 149 F2:3 families) we established a two location field trial using a complete randomized block design. Correlations and heritabilities for several ear fasciation-related traits and yield were determined. Quantitative Trait Loci (QTL) involved in the inheritance of those traits were identified and candidate genes for these QTL proposed. Results and Discussion Ear fasciation broad-sense heritability was 0.73. Highly significant correlations were found between ear fasciation and some ear and cob diameters and row number traits. For the 23 yield and ear fasciation-related traits, 65 QTL were identified, out of which 11 were detected in both environments, while for the three principal components, five to six QTL were detected per environment. Detected QTL were distributed across 17 genomic regions and explained individually, 8.7% to 22.4% of the individual traits or principal components phenotypic variance. Several candidate genes for these QTL regions were proposed, such as bearded-ear1, branched silkless1, compact plant1, ramosa2, ramosa3, tasselseed4 and terminal ear1. However, many QTL mapped to regions without known candidate genes, indicating potential chromosomal regions not yet targeted for maize ear traits selection. Conclusions Portuguese maize germplasm represents a valuable source of genes or allelic variants for yield improvement and elucidation of the genetic basis of ear fasciation traits. Future studies should focus on fine mapping of the identified genomic regions with the aim of map-based cloning. PMID:25923975

Genetic Architecture of Ear Fasciation in Maize (Zea mays) under QTL Scrutiny.

PubMed

Mendes-Moreira, Pedro; Alves, Mara L; Satovic, Zlatko; Dos Santos, João Pacheco; Santos, João Nina; Souza, João Cândido; Pêgo, Silas E; Hallauer, Arnel R; Vaz Patto, Maria Carlota

2015-01-01

Knowledge of the genes affecting maize ear inflorescence may lead to better grain yield modeling. Maize ear fasciation, defined as abnormal flattened ears with high kernel row number, is a quantitative trait widely present in Portuguese maize landraces. Using a segregating population derived from an ear fasciation contrasting cross (consisting of 149 F2:3 families) we established a two location field trial using a complete randomized block design. Correlations and heritabilities for several ear fasciation-related traits and yield were determined. Quantitative Trait Loci (QTL) involved in the inheritance of those traits were identified and candidate genes for these QTL proposed. Ear fasciation broad-sense heritability was 0.73. Highly significant correlations were found between ear fasciation and some ear and cob diameters and row number traits. For the 23 yield and ear fasciation-related traits, 65 QTL were identified, out of which 11 were detected in both environments, while for the three principal components, five to six QTL were detected per environment. Detected QTL were distributed across 17 genomic regions and explained individually, 8.7% to 22.4% of the individual traits or principal components phenotypic variance. Several candidate genes for these QTL regions were proposed, such as bearded-ear1, branched silkless1, compact plant1, ramosa2, ramosa3, tasselseed4 and terminal ear1. However, many QTL mapped to regions without known candidate genes, indicating potential chromosomal regions not yet targeted for maize ear traits selection. Portuguese maize germplasm represents a valuable source of genes or allelic variants for yield improvement and elucidation of the genetic basis of ear fasciation traits. Future studies should focus on fine mapping of the identified genomic regions with the aim of map-based cloning.

Genetic regulation of bone metabolism in the chicken: similarities and differences to Mammalian systems.

PubMed

Johnsson, Martin; Jonsson, Kenneth B; Andersson, Leif; Jensen, Per; Wright, Dominic

2015-05-01

Birds have a unique bone physiology, due to the demands placed on them through egg production. In particular their medullary bone serves as a source of calcium for eggshell production during lay and undergoes continuous and rapid remodelling. We take advantage of the fact that bone traits have diverged massively during chicken domestication to map the genetic basis of bone metabolism in the chicken. We performed a quantitative trait locus (QTL) and expression QTL (eQTL) mapping study in an advanced intercross based on Red Junglefowl (the wild progenitor of the modern domestic chicken) and White Leghorn chickens. We measured femoral bone traits in 456 chickens by peripheral computerised tomography and femoral gene expression in a subset of 125 females from the cross with microarrays. This resulted in 25 loci for female bone traits, 26 loci for male bone traits and 6318 local eQTL loci. We then overlapped bone and gene expression loci, before checking for an association between gene expression and trait values to identify candidate quantitative trait genes for bone traits. A handful of our candidates have been previously associated with bone traits in mice, but our results also implicate unexpected and largely unknown genes in bone metabolism. In summary, by utilising the unique bone metabolism of an avian species, we have identified a number of candidate genes affecting bone allocation and metabolism. These findings can have ramifications not only for the understanding of bone metabolism genetics in general, but could also be used as a potential model for osteoporosis as well as revealing new aspects of vertebrate bone regulation or features that distinguish avian and mammalian bone.

Integration of genetic, genomic and transcriptomic information identifies putative regulators of adventitious root formation in Populus

DOE PAGES

Ribeiro, Cintia L.; Silva, Cynthia M.; Drost, Derek R.; ...

2016-03-16

In this study, adventitious roots (AR) develop from tissues other than the primary root, in a process physiologically regulated by phytohormones. Adventitious roots provide structural support and contribute to water and nutrient absorption, and are critical for commercial vegetative propagation of several crops. Here we quantified the number of AR, root architectural traits and root biomass in cuttings from a pseudo-backcross population of Populus deltoides and Populus trichocarpa. Quantitative trait loci (QTL) mapping and whole-transcriptome analysis of individuals with alternative QTL alleles for AR number were used to identify putative regulators of AR development. As a result, parental individuals andmore » progeny showed extensive segregation for AR developmental traits. Quantitative trait loci for number of AR mapped consistently in the same interval of linkage group (LG) II and LG XIV, explaining 7–10 % of the phenotypic variation. A time series transcriptome analysis identified 26,121 genes differentially expressed during AR development, particularly during the first 24 h after cuttings were harvested. Of those, 1929 genes were differentially regulated between individuals carrying alternative alleles for the two QTL for number of AR, in one or more time point. Eighty-one of these genes were physically located within the QTL intervals for number of AR, including putative homologs of the Arabidopsis genes SUPERROOT2 (SUR2) and TRYPTOPHAN SYNTHASE ALPHA CHAIN (TSA1), both of which are involved in the auxin indole-3-acetic acid (IAA) biosynthesis pathway. In conclusion, this study suggests the involvement of two genes of the tryptophan-dependent auxin biosynthesis pathway, SUR2 and TSA1, in the regulation of a critical trait for the clonal propagation of woody species. A possible model for this regulation is that poplar individuals that have poor AR formation synthesize auxin indole-3-acetic acid (IAA) primarily through the tryptophan (Trp) pathway. Much of the Trp pathway flux appears to be directed to the synthesis of indole glucosinolates (IG), as suggested by the over-expression of SUR2. Individuals that are efficient in AR formation may utilize alternative (non-Trp) pathways to synthesize IAA, based on the observation that they down-regulate the expression of TSA1, one of the critical steps in the synthesis of tryptophan.« less

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.

Deep machine learning provides state-of-the-art performance in image-based plant phenotyping.

PubMed

Pound, Michael P; Atkinson, Jonathan A; Townsend, Alexandra J; Wilson, Michael H; Griffiths, Marcus; Jackson, Aaron S; Bulat, Adrian; Tzimiropoulos, Georgios; Wells, Darren M; Murchie, Erik H; Pridmore, Tony P; French, Andrew P

2017-10-01

In plant phenotyping, it has become important to be able to measure many features on large image sets in order to aid genetic discovery. The size of the datasets, now often captured robotically, often precludes manual inspection, hence the motivation for finding a fully automated approach. Deep learning is an emerging field that promises unparalleled results on many data analysis problems. Building on artificial neural networks, deep approaches have many more hidden layers in the network, and hence have greater discriminative and predictive power. We demonstrate the use of such approaches as part of a plant phenotyping pipeline. We show the success offered by such techniques when applied to the challenging problem of image-based plant phenotyping and demonstrate state-of-the-art results (>97% accuracy) for root and shoot feature identification and localization. We use fully automated trait identification using deep learning to identify quantitative trait loci in root architecture datasets. The majority (12 out of 14) of manually identified quantitative trait loci were also discovered using our automated approach based on deep learning detection to locate plant features. We have shown deep learning-based phenotyping to have very good detection and localization accuracy in validation and testing image sets. We have shown that such features can be used to derive meaningful biological traits, which in turn can be used in quantitative trait loci discovery pipelines. This process can be completely automated. We predict a paradigm shift in image-based phenotyping bought about by such deep learning approaches, given sufficient training sets. © The Authors 2017. Published by Oxford University Press.

Application of Genome Wide Association and Genomic Prediction for Improvement of Cacao Productivity and Resistance to Black and Frosty Pod Diseases

PubMed Central

Romero Navarro, J. Alberto; Phillips-Mora, Wilbert; Arciniegas-Leal, Adriana; Mata-Quirós, Allan; Haiminen, Niina; Mustiga, Guiliana; Livingstone III, Donald; van Bakel, Harm; Kuhn, David N.; Parida, Laxmi; Kasarskis, Andrew; Motamayor, Juan C.

2017-01-01

Chocolate is a highly valued and palatable confectionery product. Chocolate is primarily made from the processed seeds of the tree species Theobroma cacao. Cacao cultivation is highly relevant for small-holder farmers throughout the tropics, yet its productivity remains limited by low yields and widespread pathogens. A panel of 148 improved cacao clones was assembled based on productivity and disease resistance, and phenotypic single-tree replicated clonal evaluation was performed for 8 years. Using high-density markers, the diversity of clones was expressed relative to 10 known ancestral cacao populations, and significant effects of ancestry were observed in productivity and disease resistance. Genome-wide association (GWA) was performed, and six markers were significantly associated with frosty pod disease resistance. In addition, genomic selection was performed, and consistent with the observed extensive linkage disequilibrium, high predictive ability was observed at low marker densities for all traits. Finally, quantitative trait locus mapping and differential expression analysis of two cultivars with contrasting disease phenotypes were performed to identify genes underlying frosty pod disease resistance, identifying a significant quantitative trait locus and 35 differentially expressed genes using two independent differential expression analyses. These results indicate that in breeding populations of heterozygous and recently admixed individuals, mapping approaches can be used for low complexity traits like pod color cacao, or in other species single gene disease resistance, however genomic selection for quantitative traits remains highly effective relative to mapping. Our results can help guide the breeding process for sustainable improved cacao productivity. PMID:29184558

A powerful test of parent-of-origin effects for quantitative traits using haplotypes

USDA-ARS?s Scientific Manuscript database

Imprinting is an epigenetic phenomenon where the same alleles have unequal transcriptions and thus contribute differently to a trait depending on their parent of origin. This mechanism has been found to affect a variety of human disorders. Although various methods for testing parent-of-origin effect...

Identification of quantitative trait loci for popping traits and kernel characteristics in sorghum grain

USDA-ARS?s Scientific Manuscript database

Popped grain sorghum has developed a niche among specialty snack-food consumers. In contrast to popcorn, sorghum has not benefited from persistent selective breeding for popping efficiency and kernel expansion ratio. While recent studies have already demonstrated that popping characteristics are h...

Mapping quantitative trait loci associated with chilling requirement, heat requirement and bloom date in peach [Prunus persica (L.) Batsch

USDA-ARS?s Scientific Manuscript database

Chilling requirement (CR), together with heat requirement (HR), determines blooming date (BD) and climatic distribution of genotypes of temperate tree species. However, information on the genetic components underlying these important traits remains unknown or fragmentary. Here the identification o...

Development of low temperature germinability markers for evaluation of rice (Oryza sativa L.) germplasm

USDA-ARS?s Scientific Manuscript database

Low temperature germinability (LTG) is an important trait for breeding of varieties for use in direct-seeding rice production systems. Although rice (Oryza sativa L.) is generally sensitive to low temperatures, genetic variation for LTG exists and several quantitative trait loci (QTLs) have been rep...

Integration of least angle regression with empirical Bayes for multi-locus genome-wide association studies

USDA-ARS?s Scientific Manuscript database

Multi-locus genome-wide association studies has become the state-of-the-art procedure to identify quantitative trait loci (QTL) associated with traits simultaneously. However, implementation of multi-locus model is still difficult. In this study, we integrated least angle regression with empirical B...

Genome-wide association mapping of qualitatively inherited traits in a germplasm collection

USDA-ARS?s Scientific Manuscript database

Genome-wide association (GWA) has been used as a tool for dissecting the genetic architecture of quantitatively inherited traits. We demonstrate here that GWA can also be highly useful for detecting the genomic locations of major genes governing categorically defined phenotype variants that exist fo...

Comprehensive comparison of self-administered questionnaires for measuring quantitative autistic traits in adults.

PubMed

Nishiyama, Takeshi; Suzuki, Masako; Adachi, Katsunori; Sumi, Satoshi; Okada, Kensuke; Kishino, Hirohisa; Sakai, Saeko; Kamio, Yoko; Kojima, Masayo; Suzuki, Sadao; Kanne, Stephen M

2014-05-01

We comprehensively compared all available questionnaires for measuring quantitative autistic traits (QATs) in terms of reliability and construct validity in 3,147 non-clinical and 60 clinical subjects with normal intelligence. We examined four full-length forms, the Subthreshold Autism Trait Questionnaire (SATQ), the Broader Autism Phenotype Questionnaire, the Social Responsiveness Scale2-Adult Self report (SRS2-AS), and the Autism-Spectrum Quotient (AQ). The SRS2-AS and the AQ each had several short forms that we also examined, bringing the total to 11 forms. Though all QAT questionnaires showed acceptable levels of test-retest reliability, the AQ and SRS2-AS, including their short forms, exhibited poor internal consistency and discriminant validity, respectively. The SATQ excelled in terms of classical test theory and due to its short length.

Improving breeding efficiency in potato using molecular and quantitative genetics.

PubMed

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

2014-11-01

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

Investigation of four porcine candidate genes (H-FABP, MYOD1, UCP3 and MASTR) for meat quality traits in Large White pigs.

PubMed

Han, Xuelei; Jiang, Tengfei; Yang, Huawei; Zhang, Qingde; Wang, Weimin; Fan, Bin; Liu, Bang

2012-06-01

Meat quality traits are economically important traits of swine, and are controlled by multiple genes as complex quantitative traits. In the present study four genes, H-FABP (heart fatty acid-binding protein), MASTR (MEF2 activating motif and SAP domain containing transcriptional regulator), UCP3 (uncoupling protein 3) and MYOD1 (myogenic differentiation 1) were researched in Large White pigs. The polymorphisms H-FABP T/C of 5'UTR, MYOD1 g.257 A>C, UCP3 g.1406 G>A in exon 3 and MASTR c.187 C>T have been reported to be associated with meat quality traits in pigs. The aim of this study was to analyze the effect of single and multiple markers for single traits in Large White pigs. The single marker association analysis showed that the H-FABP and MASTR genes were associated with IMF (intramuscular fat content) (P < 0.05), and that the g.257 A>C of MYOD1 gene was most significantly related to muscle pH value (P < 0.01). The multiple markers for IMF were analyzed by combining the markers and quantitative trait modes into the linear regression. The results revealed that H-FABP and MASTR integrate gene networks for IMF. Thus, our study results suggested that H-FABP and MASTR polymorphisms could be used as genetic markers in the marker-assisted selection towards the improvement of IMF in Large White pigs.

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

PubMed Central

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

2013-01-01

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

Identification of Genetic Loci Jointly Influencing Schizophrenia Risk and the Cognitive Traits of Verbal-Numerical Reasoning, Reaction Time, and General Cognitive Function.

PubMed

Smeland, Olav B; Frei, Oleksandr; Kauppi, Karolina; Hill, W David; Li, Wen; Wang, Yunpeng; Krull, Florian; Bettella, Francesco; Eriksen, Jon A; Witoelar, Aree; Davies, Gail; Fan, Chun C; Thompson, Wesley K; Lam, Max; Lencz, Todd; Chen, Chi-Hua; Ueland, Torill; Jönsson, Erik G; Djurovic, Srdjan; Deary, Ian J; Dale, Anders M; Andreassen, Ole A

2017-10-01

Schizophrenia is associated with widespread cognitive impairments. Although cognitive deficits are one of the factors most strongly associated with functional outcome in schizophrenia, current treatment strategies largely fail to ameliorate these impairments. To develop more efficient treatment strategies in patients with schizophrenia, a better understanding of the pathogenesis of these cognitive deficits is needed. Accumulating evidence indicates that genetic risk of schizophrenia may contribute to cognitive dysfunction. To identify genomic regions jointly influencing schizophrenia and the cognitive domains of reaction time and verbal-numerical reasoning, as well as general cognitive function, a phenotype that captures the shared variation in performance across cognitive domains. Combining data from genome-wide association studies from multiple phenotypes using conditional false discovery rate analysis provides increased power to discover genetic variants and could elucidate shared molecular genetic mechanisms. Data from the following genome-wide association studies, published from July 24, 2014, to January 17, 2017, were combined: schizophrenia in the Psychiatric Genomics Consortium cohort (n = 79 757 [cases, 34 486; controls, 45 271]); verbal-numerical reasoning (n = 36 035) and reaction time (n = 111 483) in the UK Biobank cohort; and general cognitive function in CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) (n = 53 949) and COGENT (Cognitive Genomics Consortium) (n = 27 888). Genetic loci identified by conditional false discovery rate analysis. Brain messenger RNA expression and brain expression quantitative trait locus functionality were determined. Among the participants in the genome-wide association studies, 21 loci jointly influencing schizophrenia and cognitive traits were identified: 2 loci shared between schizophrenia and verbal-numerical reasoning, 6 loci shared between schizophrenia and reaction time, and 14 loci shared between schizophrenia and general cognitive function. One locus was shared between schizophrenia and 2 cognitive traits and represented the strongest shared signal detected (nearest gene TCF20; chromosome 22q13.2), and was shared between schizophrenia (z score, 5.01; P = 5.53 × 10-7), general cognitive function (z score, -4.43; P = 9.42 × 10-6), and verbal-numerical reasoning (z score, -5.43; P = 5.64 × 10-8). For 18 loci, schizophrenia risk alleles were associated with poorer cognitive performance. The implicated genes are expressed in the developmental and adult human brain. Replicable expression quantitative trait locus functionality was identified for 4 loci in the adult human brain. The discovered loci improve the understanding of the common genetic basis underlying schizophrenia and cognitive function, suggesting novel molecular genetic mechanisms.

Advances in Genetical Genomics of Plants

PubMed Central

Joosen, R.V.L.; Ligterink, W.; Hilhorst, H.W.M.; Keurentjes, J.J.B.

2009-01-01

Natural variation provides a valuable resource to study the genetic regulation of quantitative traits. In quantitative trait locus (QTL) analyses this variation, captured in segregating mapping populations, is used to identify the genomic regions affecting these traits. The identification of the causal genes underlying QTLs is a major challenge for which the detection of gene expression differences is of major importance. By combining genetics with large scale expression profiling (i.e. genetical genomics), resulting in expression QTLs (eQTLs), great progress can be made in connecting phenotypic variation to genotypic diversity. In this review we discuss examples from human, mouse, Drosophila, yeast and plant research to illustrate the advances in genetical genomics, with a focus on understanding the regulatory mechanisms underlying natural variation. With their tolerance to inbreeding, short generation time and ease to generate large families, plants are ideal subjects to test new concepts in genetics. The comprehensive resources which are available for Arabidopsis make it a favorite model plant but genetical genomics also found its way to important crop species like rice, barley and wheat. We discuss eQTL profiling with respect to cis and trans regulation and show how combined studies with other ‘omics’ technologies, such as metabolomics and proteomics may further augment current information on transcriptional, translational and metabolomic signaling pathways and enable reconstruction of detailed regulatory networks. The fast developments in the ‘omics’ area will offer great potential for genetical genomics to elucidate the genotype-phenotype relationships for both fundamental and applied research. PMID:20514216

[INVITED] Non-intrusive optical imaging of face to probe physiological traits in Autism Spectrum Disorder

NASA Astrophysics Data System (ADS)

Samad, Manar D.; Bobzien, Jonna L.; Harrington, John W.; Iftekharuddin, Khan M.

2016-03-01

Autism Spectrum Disorders (ASD) can impair non-verbal communication including the variety and extent of facial expressions in social and interpersonal communication. These impairments may appear as differential traits in the physiology of facial muscles of an individual with ASD when compared to a typically developing individual. The differential traits in the facial expressions as shown by facial muscle-specific changes (also known as 'facial oddity' for subjects with ASD) may be measured visually. However, this mode of measurement may not discern the subtlety in facial oddity distinctive to ASD. Earlier studies have used intrusive electrophysiological sensors on the facial skin to gauge facial muscle actions from quantitative physiological data. This study demonstrates, for the first time in the literature, novel quantitative measures for facial oddity recognition using non-intrusive facial imaging sensors such as video and 3D optical cameras. An Institutional Review Board (IRB) approved that pilot study has been conducted on a group of individuals consisting of eight participants with ASD and eight typically developing participants in a control group to capture their facial images in response to visual stimuli. The proposed computational techniques and statistical analyses reveal higher mean of actions in the facial muscles of the ASD group versus the control group. The facial muscle-specific evaluation reveals intense yet asymmetric facial responses as facial oddity in participants with ASD. This finding about the facial oddity may objectively define measurable differential markers in the facial expressions of individuals with ASD.

Social traits, social networks and evolutionary biology.

PubMed

Fisher, D N; McAdam, A G

2017-12-01

The social environment is both an important agent of selection for most organisms, and an emergent property of their interactions. As an aggregation of interactions among members of a population, the social environment is a product of many sets of relationships and so can be represented as a network or matrix. Social network analysis in animals has focused on why these networks possess the structure they do, and whether individuals' network traits, representing some aspect of their social phenotype, relate to their fitness. Meanwhile, quantitative geneticists have demonstrated that traits expressed in a social context can depend on the phenotypes and genotypes of interacting partners, leading to influences of the social environment on the traits and fitness of individuals and the evolutionary trajectories of populations. Therefore, both fields are investigating similar topics, yet have arrived at these points relatively independently. We review how these approaches are diverged, and yet how they retain clear parallelism and so strong potential for complementarity. This demonstrates that, despite separate bodies of theory, advances in one might inform the other. Techniques in network analysis for quantifying social phenotypes, and for identifying community structure, should be useful for those studying the relationship between individual behaviour and group-level phenotypes. Entering social association matrices into quantitative genetic models may also reduce bias in heritability estimates, and allow the estimation of the influence of social connectedness on trait expression. Current methods for measuring natural selection in a social context explicitly account for the fact that a trait is not necessarily the property of a single individual, something the network approaches have not yet considered when relating network metrics to individual fitness. Harnessing evolutionary models that consider traits affected by genes in other individuals (i.e. indirect genetic effects) provides the potential to understand how entire networks of social interactions in populations influence phenotypes and predict how these traits may evolve. By theoretical integration of social network analysis and quantitative genetics, we hope to identify areas of compatibility and incompatibility and to direct research efforts towards the most promising areas. Continuing this synthesis could provide important insights into the evolution of traits expressed in a social context and the evolutionary consequences of complex and nuanced social phenotypes. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

A genome-wide linkage scan for quantitative trait loci underlying obesity related phenotypes in 434 Caucasian families.

PubMed

Zhao, Lan-Juan; Xiao, Peng; Liu, Yong-Jun; Xiong, Dong-Hai; Shen, Hui; Recker, Robert R; Deng, Hong-Wen

2007-03-01

To identify quantitative trait loci (QTLs) that contribute to obesity, we performed a large-scale whole genome linkage scan (WGS) involving 4,102 individuals from 434 Caucasian families. The most pronounced linkage evidence was found at the genomic region 20p11-12 for fat mass (LOD = 3.31) and percentage fat mass (PFM) (LOD = 2.92). We also identified several regions showing suggestive linkage signals (threshold LOD = 1.9) for obesity phenotypes, including 5q35, 8q13, 10p12, and 17q11.

Analysis of conditional genetic effects and variance components in developmental genetics.

PubMed

Zhu, J

1995-12-01

A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.

Analysis of Conditional Genetic Effects and Variance Components in Developmental Genetics

PubMed Central

Zhu, J.

1995-01-01

A genetic model with additive-dominance effects and genotype X environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t - 1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects. PMID:8601500

Mapping genomic features to functional traits through microbial whole genome sequences.

PubMed

Zhang, Wei; Zeng, Erliang; Liu, Dan; Jones, Stuart E; Emrich, Scott

2014-01-01

Recently, the utility of trait-based approaches for microbial communities has been identified. Increasing availability of whole genome sequences provide the opportunity to explore the genetic foundations of a variety of functional traits. We proposed a machine learning framework to quantitatively link the genomic features with functional traits. Genes from bacteria genomes belonging to different functional traits were grouped to Cluster of Orthologs (COGs), and were used as features. Then, TF-IDF technique from the text mining domain was applied to transform the data to accommodate the abundance and importance of each COG. After TF-IDF processing, COGs were ranked using feature selection methods to identify their relevance to the functional trait of interest. Extensive experimental results demonstrated that functional trait related genes can be detected using our method. Further, the method has the potential to provide novel biological insights.

Image Harvest: an open-source platform for high-throughput plant image processing and analysis

PubMed Central

Knecht, Avi C.; Campbell, Malachy T.; Caprez, Adam; Swanson, David R.; Walia, Harkamal

2016-01-01

High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. PMID:27141917

Magnetic resonance imaging traits in siblings discordant for Alzheimer disease.

PubMed

Cuenco, Karen T; Green, Robert C; Zhang, J; Lunetta, Kathryn; Erlich, Porat M; Cupples, L Adrienne; Farrer, Lindsay A; DeCarli, Charles

2008-07-01

Magnetic resonance imaging (MRI) can aid clinical assessment of brain changes potentially correlated with Alzheimer disease (AD). MRI traits may improve our ability to identify genes associated with AD-outcomes. We evaluated semi-quantitative MRI measures as endophenotypes for genetic studies by assessing their association with AD in families from the Multi-Institutional Research in Alzheimer Genetic Epidemiology (MIRAGE) Study. Discordant siblings from multiple ethnicities were ascertained through a single affected proband. Semi-quantitative MRI measures were obtained for each individual. The association between continuous/ordinal MRI traits and AD were analyzed using generalized estimating equations. Medical history and Apolipoprotein E (APOE)epsilon4 status were evaluated as potential confounders. Comparisons of 214 affected and 234 unaffected subjects from 229 sibships revealed that general cerebral atrophy, white matter hyperintensities (WMH), and mediotemporal atrophy differed significantly between groups (each at P < .0001) and varied by ethnicity. Age at MRI and duration of AD confounded all associations between AD and MRI traits. Among unaffected sibs, the presence of at least one APOEepsilon4 allele and MRI infarction was associated with more WMH after adjusting for age at MRI. The strong association between MRI traits and AD suggests that MRI traits may be informative endophenotypes for basic and clinical studies of AD. In particular, WMH may be a marker of vascular disease that contributes to AD pathogenesis.

Quantitative Genetic Architecture at Latitudinal Range Boundaries: Reduced Variation but Higher Trait Independence.

PubMed

Paccard, Antoine; Van Buskirk, Josh; Willi, Yvonne

2016-05-01

Species distribution limits are hypothesized to be caused by small population size and limited genetic variation in ecologically relevant traits, but earlier studies have not evaluated genetic variation in multivariate phenotypes. We asked whether populations at the latitudinal edges of the distribution have altered quantitative genetic architecture of ecologically relevant traits compared with midlatitude populations. We calculated measures of evolutionary potential in nine Arabidopsis lyrata populations spanning the latitudinal range of the species in eastern and midwestern North America. Environments at the latitudinal extremes have reduced water availability, and therefore plants were assessed under wet and dry treatments. We estimated genetic variance-covariance (G-) matrices for 10 traits related to size, development, and water balance. Populations at southern and northern distribution edges had reduced levels of genetic variation across traits, but their G-matrices were more spherical; G-matrix orientation was unrelated to latitude. As a consequence, the predicted short-term response to selection was at least as strong in edge populations as in central populations. These results are consistent with genetic drift eroding variation and reducing the effectiveness of correlational selection at distribution margins. We conclude that genetic variation of isolated traits poorly predicts the capacity to evolve in response to multivariate selection and that the response to selection may frequently be greater than expected at species distribution margins because of genetic drift.

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

PubMed

Kooke, Rik; Kruijer, Willem; Bours, Ralph; Becker, Frank; Kuhn, André; van de Geest, Henri; Buntjer, Jaap; Doeswijk, Timo; Guerra, José; Bouwmeester, Harro; Vreugdenhil, Dick; Keurentjes, Joost J B

2016-04-01

Quantitative traits in plants are controlled by a large number of genes and their interaction with the environment. To disentangle the genetic architecture of such traits, natural variation within species can be explored by studying genotype-phenotype relationships. Genome-wide association studies that link phenotypes to thousands of single nucleotide polymorphism markers are nowadays common practice for such analyses. In many cases, however, the identified individual loci cannot fully explain the heritability estimates, suggesting missing heritability. We analyzed 349 Arabidopsis accessions and found extensive variation and high heritabilities for different morphological traits. The number of significant genome-wide associations was, however, very low. The application of genomic prediction models that take into account the effects of all individual loci may greatly enhance the elucidation of the genetic architecture of quantitative traits in plants. Here, genomic prediction models revealed different genetic architectures for the morphological traits. Integrating genomic prediction and association mapping enabled the assignment of many plausible candidate genes explaining the observed variation. These genes were analyzed for functional and sequence diversity, and good indications that natural allelic variation in many of these genes contributes to phenotypic variation were obtained. For ACS11, an ethylene biosynthesis gene, haplotype differences explaining variation in the ratio of petiole and leaf length could be identified. © 2016 American Society of Plant Biologists. All Rights Reserved.

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.

LABORATORY EVOLUTION OF LIFE-HISTORY TRAITS IN THE BEAN WEEVIL (ACANTHOSCELIDES OBTECTUS): THE EFFECTS OF DENSITY-DEPENDENT AND AGE-SPECIFIC SELECTION.

PubMed

Tucić, Nikola; Stojković, Oliver; Gliksman, Ivana; Milanović, Agana; Šešlija, Darka

1997-12-01

Four types of laboratory populations of the bean weevil (Acanthoscelides obtectus) have been developed to study the effects of density-dependent and age-specific selection. These populations have been selected at high (K) and low larval densities (r) as well as for reproduction early (Y) and late (O) in life. The results presented here suggest that the r- and K-populations (density-dependent selection regimes) have differentiated from each other with respect to the following life-history traits: egg-to-adult viability at high larval density (K > r), preadult developmental time (r > K), body weight (r > K), late fecundity (K > r), total realized fecundity (r > K), and longevity of males (r > K). It was also found that the following traits responded in statistically significant manner in populations subjected to different age-specific selection regimes: egg-to-adult viability (O > Y), body weight (O > Y), early fecundity (Y > O), late fecundity (O > Y), and longevity of females and males (O > Y). Although several life-history traits (viability, body weight, late fecundity) responded in similar manner to both density-dependent and age-specific selection regimes, it appears that underlying genetic and physiological mechanisms responsible for differentiation of the r/K and Y/O populations are different. We have also tested quantitative genetic basis of the bean weevil life-history traits in the populations experiencing density-dependent and age-specific selection. Among the traits traded-off within age-specific selection regimes, only early fecundity showed directional dominance, whereas late fecundity and longevity data indicated additive inheritance. In contrast to age-specific selecton regimes, three life-history traits (developmental time, body size, total fecundity) in the density-sependent regimes exhibited significant dominance effects. Lastly, we have tested the congruence between short-term and long-term effects of larval densities. The comparisons of the outcomes of the r/K selection regimes and those obtained from the low- and high-larval densities revealed that there is no congruence between the selection results and phenotypic plasticity for the analyzed life-history traits in the bean weevil. © 1997 The Society for the Study of Evolution.

Genome-Wide Association Mapping for Yield and Other Agronomic Traits in an Elite Breeding Population of Tropical Rice (Oryza sativa)

PubMed Central

Lalusin, Antonio; Borromeo, Teresita; Gregorio, Glenn; Hernandez, Jose; Virk, Parminder; Collard, Bertrand; McCouch, Susan R.

2015-01-01

Genome-wide association mapping studies (GWAS) are frequently used to detect QTL in diverse collections of crop germplasm, based on historic recombination events and linkage disequilibrium across the genome. Generally, diversity panels genotyped with high density SNP panels are utilized in order to assay a wide range of alleles and haplotypes and to monitor recombination breakpoints across the genome. By contrast, GWAS have not generally been performed in breeding populations. In this study we performed association mapping for 19 agronomic traits including yield and yield components in a breeding population of elite irrigated tropical rice breeding lines so that the results would be more directly applicable to breeding than those from a diversity panel. The population was genotyped with 71,710 SNPs using genotyping-by-sequencing (GBS), and GWAS performed with the explicit goal of expediting selection in the breeding program. Using this breeding panel we identified 52 QTL for 11 agronomic traits, including large effect QTLs for flowering time and grain length/grain width/grain-length-breadth ratio. We also identified haplotypes that can be used to select plants in our population for short stature (plant height), early flowering time, and high yield, and thus demonstrate the utility of association mapping in breeding populations for informing breeding decisions. We conclude by exploring how the newly identified significant SNPs and insights into the genetic architecture of these quantitative traits can be leveraged to build genomic-assisted selection models. PMID:25785447

kruX: matrix-based non-parametric eQTL discovery

PubMed Central

2014-01-01

Background 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. Results 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. Conclusion 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. PMID:24423115

Association of the expression levels in the skeletal muscle and a SNP in the CDC10 gene with growth-related traits in Japanese Black beef cattle.

PubMed

Tong, B; Li, G P; Sasaki, S; Muramatsu, Y; Ohta, T; Kose, H; Yamada, T

2015-04-01

Growth performance, as well as marbling, is the main breeding objective in Japanese Black (JB) cattle, the major beef breed in Japan. The septin 7 (CDC10) gene, involved in cellular proliferation, is located within a genomic region of a quantitative trait locus for growth-related traits. In this study, we first showed that the expression levels of the CDC10 gene in the skeletal muscle were higher in JB steers with extremely high growth performance than in JB steers with extremely low growth, using real-time PCR. Further, a single nucleotide polymorphism (SNP), NC_007302.5:g.63264949G>C, was detected in the promoter region of the CDC10 gene and genotyped in three Japanese cattle breeds (known as 'Wagyu' in Japan) and the Brown Swiss dairy cattle breed. All four cattle populations showed a moderate genetic diversity at the SNP of the CDC10 gene. An association analysis indicated that the SNP was associated with growth-related traits in JB cattle. These findings suggest possible effects of the expression levels in the skeletal muscle and the SNP of the CDC10 gene on growth-related traits in JB cattle. The CDC10 SNP may be useful for effective marker-assisted selection to increase beef productivity in JB beef cattle. © 2015 Stichting International Foundation for Animal Genetics.

Mapping quantitative trait loci controlling seed and grain production traits of intermediate wheatgrass (Thinopyrum intermedium)

USDA-ARS?s Scientific Manuscript database

Intermediate wheatgrass (Thinopyrum intermedium) is a cool-season perennial grass cultivated for seed used in forage production, conservation plantings, and consumable grain products such as flour. Intermediate wheatgrass (2n=6x=42) has a large, allohexploid genome (~13 GB) and is a distant relativ...

Brief Report: Autism-Like Traits Are Associated with Enhanced Ability to Disembed Visual Forms

ERIC Educational Resources Information Center

Sabatino DiCriscio, Antoinette; Troiani, Vanessa

2017-01-01

Atypical visual perceptual skills are thought to underlie unusual visual attention in autism spectrum disorders. We assessed whether individual differences in visual processing skills scaled with quantitative traits associated with the broader autism phenotype (BAP). Visual perception was assessed using the Figure-ground subtest of the Test of…

Mapping quantitative trait loci for a unique 'super soft' kernel trait in soft white wheat

USDA-ARS?s Scientific Manuscript database

Wheat (Triticum sp.) kernel texture is an important factor affecting milling, flour functionality, and end-use quality. Kernel texture is normally characterized as either hard or soft, the two major classes of texture. However, further variation is typically encountered in each class. Soft wheat var...

Candidate causative mutation on BTA18 associated with calving and conformation traits in Holstein bulls

USDA-ARS?s Scientific Manuscript database

Complementing quantitative methods with sequence data analysis is a major goal of the post-genome era of biology. In this study, we analyzed Illumina HiSeq sequence data derived from 11 US Holstein bulls in order to identify putative causal mutations associated with calving and conformation traits. ...

An Investigation of Personality Traits in Relation to Job Performance of Online Instructors

ERIC Educational Resources Information Center

Holmes, Charles; Kirwan, Jeral R.; Bova, Mark; Belcher, Trevor

2015-01-01

This quantitative study examined the relationship between the Big 5 personality traits and how they relate to online teacher effectiveness. The primary method of data collection for this study was through the use of surveys primarily building upon the Personality Style Inventory (PSI) (Lounsbury & Gibson, 2010), a work-based personality…

Linking "Big" Personality Traits to Anxiety, Depressive, and Substance Use Disorders: A Meta-Analysis

ERIC Educational Resources Information Center

Kotov, Roman; Gamez, Wakiza; Schmidt, Frank; Watson, David

2010-01-01

We performed a quantitative review of associations between the higher order personality traits in the Big Three and Big Five models (i.e., neuroticism, extraversion, disinhibition, conscientiousness, agreeableness, and openness) and specific depressive, anxiety, and substance use disorders (SUD) in adults. This approach resulted in 66…

Identification of Species, Quantitative Trait Loci (QTLs), and Hybrids Important for Low-Input Biomass Production and Hetersis in Semiarid Cold-Growing Environments

USDA-ARS?s Scientific Manuscript database

Interspecific hybrids of tall caespitose Leymus cinereus (Scribn. & Merr.) A. Love and strongly rhizomatous Leymus triticoides (Buckley) Pilg. display a heterotic combination of traits important for perennial grass biomass production. The objectives of this study were to: 1) compare seasonal biomas...

An Examination of Authentic Leadership Traits and Their Relation to Student Achievement Scores

ERIC Educational Resources Information Center

Hunter, Robin C.

2017-01-01

The purpose of this quantitative, single case study was to examine principal perceptions of their own leadership traits which may impact student achievement. Principals in one Florida district were invited to participate in an open ended interview, providing their own perceptions of their personal leadership behaviors. By examining the data…

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…

Identification of nutrient and physical seed trait QTLs in the model legume, Lotus japonicus

USDA-ARS?s Scientific Manuscript database

Legume seeds have the potential to provide a significant portion of essential micronutrients to the human diet. To identify the genetic basis for seed nutrient density, quantitative trait locus (QTL) analysis was conducted with the Gifu B-129 x Miyakojima MG-20 recombinant inbred population from th...

Experimental evidence for the evolution of indirect genetic effects: changes in the interaction effect coefficient, psi (Psi), due to sexual selection.

PubMed

Chenoweth, Stephen F; Rundle, Howard D; Blows, Mark W

2010-06-01

Indirect genetics effects (IGEs)--when the genotype of one individual affects the phenotypic expression of a trait in another--may alter evolutionary trajectories beyond that predicted by standard quantitative genetic theory as a consequence of genotypic evolution of the social environment. For IGEs to occur, the trait of interest must respond to one or more indicator traits in interacting conspecifics. In quantitative genetic models of IGEs, these responses (reaction norms) are termed interaction effect coefficients and are represented by the parameter psi (Psi). The extent to which Psi exhibits genetic variation within a population, and may therefore itself evolve, is unknown. Using an experimental evolution approach, we provide evidence for a genetic basis to the phenotypic response caused by IGEs on sexual display traits in Drosophila serrata. We show that evolution of the response is affected by sexual but not natural selection when flies adapt to a novel environment. Our results indicate a further mechanism by which IGEs can alter evolutionary trajectories--the evolution of interaction effects themselves.

Comparative mapping of quantitative trait loci sculpting the curd of Brassica oleracea.

PubMed

Lan, T H; Paterson, A H

2000-08-01

The enlarged inflorescence (curd) of cauliflower and broccoli provide not only a popular vegetable for human consumption, but also a unique opportunity for scientists who seek to understand the genetic basis of plant growth and development. By the comparison of quantitative trait loci (QTL) maps constructed from three different F(2) populations, we identified a total of 86 QTL that control eight curd-related traits in Brassica oleracea. The 86 QTL may reflect allelic variation in as few as 67 different genetic loci and 54 ancestral genes. Although the locations of QTL affecting a trait occasionally corresponded between different populations or between different homeologous Brassica chromosomes, our data supported other molecular and morphological data in suggesting that the Brassica genus is rapidly evolving. Comparative data enabled us to identify a number of candidate genes from Arabidopsis that warrant further investigation to determine if some of them might account for Brassica QTL. The Arabidopsis/Brassica system is an important example of both the challenges and opportunities associated with extrapolation of genomic information from facile models to large-genome taxa including major crops.

Heritabilities of Directional Asymmetry in the Fore- and Hindlimbs of Rabbit Fetuses

PubMed Central

Breno, Matteo; Bots, Jessica; Van Dongen, Stefan

2013-01-01

Directional asymmetry (DA), where at the population level symmetry differs from zero, has been reported in a wide range of traits and taxa, even for traits in which symmetry is expected to be the target of selection such as limbs or wings. In invertebrates, DA has been suggested to be non-adaptive. In vertebrates, there has been a wealth of research linking morphological asymmetry to behavioural lateralisation. On the other hand, the prenatal expression of DA and evidences for quantitative genetic variation for asymmetry may suggest it is not solely induced by differences in mechanic loading between sides. We estimate quantitative genetic variation of fetal limb asymmetry in a large dataset of rabbits. Our results showed a low but highly significant level of DA that is partially under genetic control for all traits, with forelimbs displaying higher levels of asymmetry. Genetic correlations were positive within limbs, but negative across bones of fore and hind limbs. Environmental correlations were positive for all, but smaller across fore and hind limbs. We discuss our results in light of the existence and maintenance of DA in locomotory traits. PMID:24130770

Combining quantitative trait loci analysis with physiological models to predict genotype-specific transpiration rates.

PubMed

Reuning, Gretchen A; Bauerle, William L; Mullen, Jack L; McKay, John K

2015-04-01

Transpiration is controlled by evaporative demand and stomatal conductance (gs ), and there can be substantial genetic variation in gs . A key parameter in empirical models of transpiration is minimum stomatal conductance (g0 ), a trait that can be measured and has a large effect on gs and transpiration. In Arabidopsis thaliana, g0 exhibits both environmental and genetic variation, and quantitative trait loci (QTL) have been mapped. We used this information to create a genetically parameterized empirical model to predict transpiration of genotypes. For the parental lines, this worked well. However, in a recombinant inbred population, the predictions proved less accurate. When based only upon their genotype at a single g0 QTL, genotypes were less distinct than our model predicted. Follow-up experiments indicated that both genotype by environment interaction and a polygenic inheritance complicate the application of genetic effects into physiological models. The use of ecophysiological or 'crop' models for predicting transpiration of novel genetic lines will benefit from incorporating further knowledge of the genetic control and degree of independence of core traits/parameters underlying gs variation. © 2014 John Wiley & Sons Ltd.

Signatures of Evolutionary Adaptation in Quantitative Trait Loci Influencing Trace Element Homeostasis in Liver

PubMed Central

Sabidó, Eduard; Bosch, Elena

2016-01-01

Essential trace elements possess vital functions at molecular, cellular, and physiological levels in health and disease, and they are tightly regulated in the human body. In order to assess variability and potential adaptive evolution of trace element homeostasis, we quantified 18 trace elements in 150 liver samples, together with the expression levels of 90 genes and abundances of 40 proteins involved in their homeostasis. Additionally, we genotyped 169 single nucleotide polymorphism (SNPs) in the same sample set. We detected significant associations for 8 protein quantitative trait loci (pQTL), 10 expression quantitative trait loci (eQTLs), and 15 micronutrient quantitative trait loci (nutriQTL). Six of these exceeded the false discovery rate cutoff and were related to essential trace elements: 1) one pQTL for GPX2 (rs10133290); 2) two previously described eQTLs for HFE (rs12346) and SELO (rs4838862) expression; and 3) three nutriQTLs: The pathogenic C282Y mutation at HFE affecting iron (rs1800562), and two SNPs within several clustered metallothionein genes determining selenium concentration (rs1811322 and rs904773). Within the complete set of significant QTLs (which involved 30 SNPs and 20 gene regions), we identified 12 SNPs with extreme patterns of population differentiation (FST values in the top 5% percentile in at least one HapMap population pair) and significant evidence for selective sweeps involving QTLs at GPX1, SELENBP1, GPX3, SLC30A9, and SLC39A8. Overall, this detailed study of various molecular phenotypes illustrates the role of regulatory variants in explaining differences in trace element homeostasis among populations and in the human adaptive response to environmental pressures related to micronutrients. PMID:26582562

Identification of Genomic Regions and the Isoamylase Gene for Reduced Grain Chalkiness in Rice

PubMed Central

Sun, Wenqian; Zhou, Qiaoling; Yao, Yue; Qiu, Xianjin; Xie, Kun; Yu, Sibin

2015-01-01

Grain chalkiness is an important grain quality related to starch granules in the endosperm. A high percentage of grain chalkiness is a major problem because it diminishes grain quality in rice. Here, we report quantitative trait loci identification for grain chalkiness using high-throughput single nucleotide polymorphism genotyping of a chromosomal segment substitution line population in which each line carried one or a few introduced japonica cultivar Nipponbare segments in the genetic background of the indica cultivar ZS97. Ten quantitative trait loci regions were commonly identified for the percentage of grain chalkiness and the degree of endosperm chalkiness. The allelic effects at nine of these quantitative trait loci reduced grain chalkiness. Furthermore, a quantitative trait locus (qPGC8-2) on chromosome 8 was validated in a chromosomal segment substitution line–derived segregation population, and had a stable effect on chalkiness in a multiple-environment evaluation of the near-isogenic lines. Residing on the qPGC8-2 region, the isoamylase gene (ISA1) was preferentially expressed in the endosperm and revealed some nucleotide polymorphisms between two varieties, Nipponbare and ZS97. Transgenic lines with suppression of ISA1 by RNA interference produced grains with 20% more chalkiness than the control. The results support that the gene may underlie qPGC8-2 for grain chalkiness. The multiple-environment trials of the near-isogenic lines also show that combination of the favorable alleles such as the ISA1 gene for low chalkiness and the GS3 gene for long grains considerably improved grain quality of ZS97, which proves useful for grain quality improvement in rice breeding programs. PMID:25790260

A population genetic interpretation of GWAS findings for human quantitative traits

PubMed Central

Bullaughey, Kevin; Hudson, Richard R.; Sella, Guy

2018-01-01

Human genome-wide association studies (GWASs) are revealing the genetic architecture of anthropomorphic and biomedical traits, i.e., the frequencies and effect sizes of variants that contribute to heritable variation in a trait. To interpret these findings, we need to understand how genetic architecture is shaped by basic population genetics processes—notably, by mutation, natural selection, and genetic drift. Because many quantitative traits are subject to stabilizing selection and because genetic variation that affects one trait often affects many others, we model the genetic architecture of a focal trait that arises under stabilizing selection in a multidimensional trait space. We solve the model for the phenotypic distribution and allelic dynamics at steady state and derive robust, closed-form solutions for summary statistics of the genetic architecture. Our results provide a simple interpretation for missing heritability and why it varies among traits. They predict that the distribution of variances contributed by loci identified in GWASs is well approximated by a simple functional form that depends on a single parameter: the expected contribution to genetic variance of a strongly selected site affecting the trait. We test this prediction against the results of GWASs for height and body mass index (BMI) and find that it fits the data well, allowing us to make inferences about the degree of pleiotropy and mutational target size for these traits. Our findings help to explain why the GWAS for height explains more of the heritable variance than the similarly sized GWAS for BMI and to predict the increase in explained heritability with study sample size. Considering the demographic history of European populations, in which these GWASs were performed, we further find that most of the associations they identified likely involve mutations that arose shortly before or during the Out-of-Africa bottleneck at sites with selection coefficients around s = 10−3. PMID:29547617

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

PubMed

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

2015-08-01

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

Genome-scan analysis for quantitative trait loci in an F2 tilapia hybrid.

PubMed

Cnaani, A; Zilberman, N; Tinman, S; Hulata, G; Ron, M

2004-09-01

We searched for genetic linkage between DNA markers and quantitative trait loci (QTLs) for innate immunity, response to stress, biochemical parameters of blood, and fish size in an F2 population derived from an interspecific tilapia hybrid (Oreochromis mossambicusx O. aureus). A family of 114 fish was scanned for 40 polymorphic microsatellite DNA markers and two polymorphic genes, covering approximately 80% of the tilapia genome. These fish had previously been phenotyped for seven immune-response traits and six blood parameters. Critical values for significance were P <0.05 with the false discovery rate (FDR) controlled at 40%. The genome-scan analysis resulted in 35 significant marker-trait associations, involving 26 markers in 16 linkage groups. In a second experiment, nine markers were re-sampled in a second family of 79 fish of the same species hybrid. Seven markers (GM180, GM553, MHC-I, UNH848, UNH868, UNH898 and UNH925) in five linkage groups (LG 1, 3, 4, 22 and 23) were associated with stress response traits. An additional six markers (GM47, GM552, UNH208, UNH881, UNH952, UNH998) in five linkage groups (LG 4, 16, 19, 20 and 23) were verified for their associations with immune response traits, by linkage to several different traits. The portion of variance explained by each QTL was 11% on average, with a maximum of 29%. The average additive effect of QTLs was 0.2 standard deviation units of stress response traits and fish size, with a maximum of 0.33. In three linkage groups (LG 1, 3 and 23) markers were associated with stress response, body weight and sex determination, confirming the location of QTLs reported by several other studies.

Genome-Wide Search for Quantitative Trait Loci Controlling Important Plant and Flower Traits in Petunia Using an Interspecific Recombinant Inbred Population of Petunia axillaris and Petunia exserta.

PubMed

Cao, Zhe; Guo, Yufang; Yang, Qian; He, Yanhong; Fetouh, Mohammed; Warner, Ryan M; Deng, Zhanao

2018-05-15

A major bottleneck in plant breeding has been the much limited genetic base and much reduced genetic diversity in domesticated, cultivated germplasm. Identification and utilization of favorable gene loci or alleles from wild or progenitor species can serve as an effective approach to increasing genetic diversity and breaking this bottleneck in plant breeding. This study was conducted to identify quantitative trait loci (QTL) in wild or progenitor petunia species that can be used to improve important horticultural traits in garden petunia. An F 7 recombinant inbred population derived between Petunia axillaris and P. exserta was phenotyped for plant height, plant spread, plant size, flower counts, flower diameter, flower length, and days to anthesis, in Florida in two consecutive years. Transgressive segregation was observed for all seven traits in both years. The broad-sense heritability estimates for the traits ranged from 0.20 (days to anthesis) to 0.62 (flower length). A genome-wide genetic linkage map consisting 368 single nucleotide polymorphism bins and extending over 277 cM was searched to identify QTL for these traits. Nineteen QTL were identified and localized to five linkage groups. Eleven of the loci were identified consistently in both years; several loci explained up to 34.0% and 24.1% of the phenotypic variance for flower length and flower diameter, respectively. Multiple loci controlling different traits are co-localized in four intervals in four linkage groups. These intervals contain desirable alleles that can be introgressed into commercial petunia germplasm to expand the genetic base and improve plant performance and flower characteristics in petunia. Copyright © 2018, G3: Genes, Genomes, Genetics.

Quantitative trait loci for magnitude of the plasma cortisol response to confinement in rainbow trout.

PubMed

Quillet, E; Krieg, F; Dechamp, N; Hervet, C; Bérard, A; Le Roy, P; Guyomard, R; Prunet, P; Pottinger, T G

2014-04-01

Better understanding of the mechanisms underlying interindividual variation in stress responses and their links with production traits is a key issue for sustainable animal breeding. In this study, we searched for quantitative trait loci (QTL) controlling the magnitude of the plasma cortisol stress response and compared them to body size traits in five F2 full-sib families issued from two rainbow trout lines divergently selected for high or low post-confinement plasma cortisol level. Approximately 1000 F2 individuals were individually tagged and exposed to two successive acute confinement challenges (1 month interval). Post-stress plasma cortisol concentrations were determined for each fish. A medium density genome scan was carried out (268 markers, overall marker spacing less than 10 cM). QTL detection was performed using qtlmap software, based on an interval mapping method (http://www.inra.fr/qtlmap). Overall, QTL of medium individual effects on cortisol responsiveness (<10% of phenotypic variance) were detected on 18 chromosomes, strongly supporting the hypothesis that control of the trait is polygenic. Although a core array of QTL controlled cortisol concentrations at both challenges, several QTL seemed challenge specific, suggesting that responses to the first and to a subsequent exposure to the confinement stressor are distinct traits sharing only part of their genetic control. Chromosomal location of the steroidogenic acute regulatory protein (STAR) makes it a good potential candidate gene for one of the QTL. Finally, comparison of body size traits QTL (weight, length and body conformation) with cortisol-associated QTL did not support evidence for negative genetic relationships between the two types of traits. © 2014 Stichting International Foundation for Animal Genetics.

Genetic dissection of fruiting body-related traits using quantitative trait loci mapping in Lentinula edodes.

PubMed

Gong, Wen-Bing; Li, Lei; Zhou, Yan; Bian, Yin-Bing; Kwan, Hoi-Shan; Cheung, Man-Kit; Xiao, Yang

2016-06-01

To provide a better understanding of the genetic architecture of fruiting body formation of Lentinula edodes, quantitative trait loci (QTLs) mapping was employed to uncover the loci underlying seven fruiting body-related traits (FBRTs). An improved L. edodes genetic linkage map, comprising 572 markers on 12 linkage groups with a total map length of 983.7 cM, was constructed by integrating 82 genomic sequence-based insertion-deletion (InDel) markers into a previously published map. We then detected a total of 62 QTLs for seven target traits across two segregating testcross populations, with individual QTLs contributing 5.5 %-30.2 % of the phenotypic variation. Fifty-three out of the 62 QTLs were clustered in six QTL hotspots, suggesting the existence of main genomic regions regulating the morphological characteristics of fruiting bodies in L. edodes. A stable QTL hotspot on MLG2, containing QTLs for all investigated traits, was identified in both testcross populations. QTLs for related traits were frequently co-located on the linkage groups, demonstrating the genetic basis for phenotypic correlation of traits. Meta-QTL (mQTL) analysis was performed and identified 16 mQTLs with refined positions and narrow confidence intervals (CIs). Nine genes, including those encoding MAP kinase, blue-light photoreceptor, riboflavin-aldehyde-forming enzyme and cyclopropane-fatty-acyl-phospholipid synthase, and cytochrome P450s, were likely to be candidate genes controlling the shape of fruiting bodies. The study has improved our understanding of the genetic architecture of fruiting body formation in L. edodes. To our knowledge, this is the first genome-wide QTL detection of FBRTs in L. edodes. The improved genetic map, InDel markers and QTL hotspot regions revealed here will assist considerably in the conduct of future genetic and breeding studies of L. edodes.

Natural Genetic Variation and Candidate Genes for Morphological Traits in Drosophila melanogaster

PubMed Central

Carreira, Valeria Paula; Mensch, Julián; Hasson, Esteban; Fanara, Juan José

2016-01-01

Body size is a complex character associated to several fitness related traits that vary within and between species as a consequence of environmental and genetic factors. Latitudinal and altitudinal clines for different morphological traits have been described in several species of Drosophila and previous work identified genomic regions associated with such variation in D. melanogaster. However, the genetic factors that orchestrate morphological variation have been barely studied. Here, our main objective was to investigate genetic variation for different morphological traits associated to the second chromosome in natural populations of D. melanogaster along latitudinal and altitudinal gradients in Argentina. Our results revealed weak clinal signals and a strong population effect on morphological variation. Moreover, most pairwise comparisons between populations were significant. Our study also showed important within-population genetic variation, which must be associated to the second chromosome, as the lines are otherwise genetically identical. Next, we examined the contribution of different candidate genes to natural variation for these traits. We performed quantitative complementation tests using a battery of lines bearing mutated alleles at candidate genes located in the second chromosome and six second chromosome substitution lines derived from natural populations which exhibited divergent phenotypes. Results of complementation tests revealed that natural variation at all candidate genes studied, invected, Fasciclin 3, toucan, Reticulon-like1, jing and CG14478, affects the studied characters, suggesting that they are Quantitative Trait Genes for morphological traits. Finally, the phenotypic patterns observed suggest that different alleles of each gene might contribute to natural variation for morphological traits. However, non-additive effects cannot be ruled out, as wild-derived strains differ at myriads of second chromosome loci that may interact epistatically with mutant alleles. PMID:27459710

The developmental genetics of biological robustness

PubMed Central

Mestek Boukhibar, Lamia; Barkoulas, Michalis

2016-01-01

Background Living organisms are continuously confronted with perturbations, such as environmental changes that include fluctuations in temperature and nutrient availability, or genetic changes such as mutations. While some developmental systems are affected by such challenges and display variation in phenotypic traits, others continue consistently to produce invariable phenotypes despite perturbation. This ability of a living system to maintain an invariable phenotype in the face of perturbations is termed developmental robustness. Biological robustness is a phenomenon observed across phyla, and studying its mechanisms is central to deciphering the genotype–phenotype relationship. Recent work in yeast, animals and plants has shown that robustness is genetically controlled and has started to reveal the underlying mechinisms behind it. Scope and Conclusions Studying biological robustness involves focusing on an important property of developmental traits, which is the phenotypic distribution within a population. This is often neglected because the vast majority of developmental biology studies instead focus on population aggregates, such as trait averages. By drawing on findings in animals and yeast, this Viewpoint considers how studies on plant developmental robustness may benefit from strict definitions of what is the developmental system of choice and what is the relevant perturbation, and also from clear distinctions between gene effects on the trait mean and the trait variance. Recent advances in quantitative developmental biology and high-throughput phenotyping now allow the design of targeted genetic screens to identify genes that amplify or restrict developmental trait variance and to study how variation propagates across different phenotypic levels in biological systems. The molecular characterization of more quantitative trait loci affecting trait variance will provide further insights into the evolution of genes modulating developmental robustness. The study of robustness mechanisms in closely related species will address whether mechanisms of robustness are evolutionarily conserved. PMID:26292993

Relationship between QTL for grain shape, grain weight, test weight, milling yield, and plant height in the spring wheat cross RL4452/'AC Domain'.

PubMed

Cabral, Adrian L; Jordan, Mark C; Larson, Gary; Somers, Daryl J; Humphreys, D Gavin; McCartney, Curt A

2018-01-01

Kernel morphology characteristics of wheat are complex and quantitatively inherited. A doubled haploid (DH) population of the cross RL4452/'AC Domain' was used to study the genetic basis of seed shape. Quantitative trait loci (QTL) analyses were conducted on a total of 18 traits: 14 grain shape traits, flour yield (Fyd), and three agronomic traits (Plant height [Plht], 1000 Grain weight [Gwt], Test weight [Twt]), using data from trial locations at Glenlea, Brandon, and Morden in Manitoba, Canada, between 1999 and 2004. Kernel shape was studied through digital image analysis with an Acurum® grain analyzer. Plht, Gwt, Twt, Fyd, and grain shape QTL were correlated with each other and QTL analysis revealed that QTL for these traits often mapped to the same genetic locations. The most significant QTL for the grain shape traits were located on chromosomes 4B and 4D, each accounting for up to 24.4% and 53.3% of the total phenotypic variation, respectively. In addition, the most significant QTL for Plht, Gwt, and Twt were all detected on chromosome 4D at the Rht-D1 locus. Rht-D1b decreased Plht, Gwt, Twt, and kernel width relative to the Rht-D1a allele. A narrow genetic interval on chromosome 4B contained significant QTL for grain shape, Gwt, and Plht. The 'AC Domain' allele reduced Plht, Gwt, kernel length and width traits, but had no detectable effect on Twt. The data indicated that this variation was inconsistent with segregation at Rht-B1. Numerous QTL were identified that control these traits in this population.

Relationship between QTL for grain shape, grain weight, test weight, milling yield, and plant height in the spring wheat cross RL4452/‘AC Domain’

PubMed Central

Cabral, Adrian L.; Jordan, Mark C.; Larson, Gary; Somers, Daryl J.; Humphreys, D. Gavin

2018-01-01

Kernel morphology characteristics of wheat are complex and quantitatively inherited. A doubled haploid (DH) population of the cross RL4452/‘AC Domain’ was used to study the genetic basis of seed shape. Quantitative trait loci (QTL) analyses were conducted on a total of 18 traits: 14 grain shape traits, flour yield (Fyd), and three agronomic traits (Plant height [Plht], 1000 Grain weight [Gwt], Test weight [Twt]), using data from trial locations at Glenlea, Brandon, and Morden in Manitoba, Canada, between 1999 and 2004. Kernel shape was studied through digital image analysis with an Acurum® grain analyzer. Plht, Gwt, Twt, Fyd, and grain shape QTL were correlated with each other and QTL analysis revealed that QTL for these traits often mapped to the same genetic locations. The most significant QTL for the grain shape traits were located on chromosomes 4B and 4D, each accounting for up to 24.4% and 53.3% of the total phenotypic variation, respectively. In addition, the most significant QTL for Plht, Gwt, and Twt were all detected on chromosome 4D at the Rht-D1 locus. Rht-D1b decreased Plht, Gwt, Twt, and kernel width relative to the Rht-D1a allele. A narrow genetic interval on chromosome 4B contained significant QTL for grain shape, Gwt, and Plht. The ‘AC Domain’ allele reduced Plht, Gwt, kernel length and width traits, but had no detectable effect on Twt. The data indicated that this variation was inconsistent with segregation at Rht-B1. Numerous QTL were identified that control these traits in this population. PMID:29357369

Smoothing of the bivariate LOD score for non-normal quantitative traits.

PubMed

Buil, Alfonso; Dyer, Thomas D; Almasy, Laura; Blangero, John

2005-12-30

Variance component analysis provides an efficient method for performing linkage analysis for quantitative traits. However, type I error of variance components-based likelihood ratio testing may be affected when phenotypic data are non-normally distributed (especially with high values of kurtosis). This results in inflated LOD scores when the normality assumption does not hold. Even though different solutions have been proposed to deal with this problem with univariate phenotypes, little work has been done in the multivariate case. We present an empirical approach to adjust the inflated LOD scores obtained from a bivariate phenotype that violates the assumption of normality. Using the Collaborative Study on the Genetics of Alcoholism data available for the Genetic Analysis Workshop 14, we show how bivariate linkage analysis with leptokurtotic traits gives an inflated type I error. We perform a novel correction that achieves acceptable levels of type I error.

Quantitative trait locus gene mapping: a new method for locating alcohol response genes.

PubMed

Crabbe, J C

1996-01-01

Alcoholism is a multigenic trait with important non-genetic determinants. Studies with genetic animal models of susceptibility to several of alcohol's effects suggest that several genes contributing modest effects on susceptibility (Quantitative Trait Loci, or QTLs) are important. A new technique of QTL gene mapping has allowed the identification of the location in mouse genome of several such QTLs. The method is described, and the locations of QTLs affecting the acute alcohol withdrawal reaction are described as an example of the method. Verification of these QTLs in ancillary studies is described and the strengths, limitations, and future directions to be pursued are discussed. QTL mapping is a promising method for identifying genes in rodents with the hope of directly extrapolating the results to the human genome. This review is based on a paper presented at the First International Congress of the Latin American Society for Biomedical Research on Alcoholism, Santiago, Chile, November 1994.

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.

Evolutionary Quantitative Genomics of Populus trichocarpa

PubMed Central

McKown, Athena D.; La Mantia, Jonathan; Guy, Robert D.; Ingvarsson, Pär K.; Hamelin, Richard; Mansfield, Shawn D.; Ehlting, Jürgen; Douglas, Carl J.; El-Kassaby, Yousry A.

2015-01-01

Forest trees generally show high levels of local adaptation and efforts focusing on understanding adaptation to climate will be crucial for species survival and management. Here, we address fundamental questions regarding the molecular basis of adaptation in undomesticated forest tree populations to past climatic environments by employing an integrative quantitative genetics and landscape genomics approach. Using this comprehensive approach, we studied the molecular basis of climate adaptation in 433 Populus trichocarpa (black cottonwood) genotypes originating across western North America. Variation in 74 field-assessed traits (growth, ecophysiology, phenology, leaf stomata, wood, and disease resistance) was investigated for signatures of selection (comparing Q ST -F ST) using clustering of individuals by climate of origin (temperature and precipitation). 29,354 SNPs were investigated employing three different outlier detection methods and marker-inferred relatedness was estimated to obtain the narrow-sense estimate of population differentiation in wild populations. In addition, we compared our results with previously assessed selection of candidate SNPs using the 25 topographical units (drainages) across the P. trichocarpa sampling range as population groupings. Narrow-sense Q ST for 53% of distinct field traits was significantly divergent from expectations of neutrality (indicating adaptive trait variation); 2,855 SNPs showed signals of diversifying selection and of these, 118 SNPs (within 81 genes) were associated with adaptive traits (based on significant Q ST). Many SNPs were putatively pleiotropic for functionally uncorrelated adaptive traits, such as autumn phenology, height, and disease resistance. Evolutionary quantitative genomics in P. trichocarpa provides an enhanced understanding regarding the molecular basis of climate-driven selection in forest trees and we highlight that important loci underlying adaptive trait variation also show relationship to climate of origin. We consider our approach the most comprehensive, as it uncovers the molecular mechanisms of adaptation using multiple methods and tests. We also provide a detailed outline of the required analyses for studying adaptation to the environment in a population genomics context to better understand the species’ potential adaptive capacity to future climatic scenarios. PMID:26599762

Gastrointestinal Traits: Individualizing Therapy for Obesity with Drugs and Devices

PubMed Central

Camilleri, Michael; Acosta, Andres

2015-01-01

Objectives The objectives were to review the discrepancy between numbers of people requiring weight loss treatment and results, and to assess the potential effects of pharmacological treatments (recently approved for obesity) and endoscopically deployed devices on quantitative gastrointestinal traits in development for obesity treatment. Methods We conducted a review of relevant literature to achieve our objectives. Results The 2013 guidelines increased the number of adults recommended for weight loss treatment by 20.9% (116.0 million to 140.2 million). There is an imbalance between efficacy and costs of commercial weight loss programs and drug therapy (average weight loss ~5 kg). The number of bariatric procedures performed in the United States has doubled in the past decade. The efficacy of bariatric surgery is attributed to reduction in the volume of the stomach, nutrient malabsorption with some types of surgery, increased postprandial incretin responses, and activation of farnesoid X receptor mechanisms. These gastrointestinal and behavioral traits identify sub-phenotypes of obesity based on recent research. Conclusions The mechanisms or traits targeted by drug and device treatments include centrally mediated alterations of appetite or satiation, diversion of nutrients, and alteration of stomach capacity, gastric emptying, or incretin hormones. Future treatment may be individualized based on quantitative gastrointestinal and behavioral traits measured in obese patients. PMID:26271184

Testing for a genetic response to sexual selection in a wild Drosophila population.

PubMed

Gosden, T P; Thomson, J R; Blows, M W; Schaul, A; Chenoweth, S F

2016-06-01

In accordance with the consensus that sexual selection is responsible for the rapid evolution of display traits on macroevolutionary scales, microevolutionary studies suggest sexual selection is a widespread and often strong form of directional selection in nature. However, empirical evidence for the contemporary evolution of sexually selected traits via sexual rather than natural selection remains weak. In this study, we used a novel application of quantitative genetic breeding designs to test for a genetic response to sexual selection on eight chemical display traits from a field population of the fly, Drosophila serrata. Using our quantitative genetic approach, we were able to detect a genetically based difference in means between groups of males descended from fathers who had either successfully sired offspring or were randomly collected from the same wild population for one of these display traits, the diene (Z,Z)-5,9-C27 : 2 . Our experimental results, in combination with previous laboratory studies on this system, suggest that both natural and sexual selection may be influencing the evolutionary trajectories of these traits in nature, limiting the capacity for a contemporary evolutionary response. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

The genetic architecture of Drosophila sensory bristle number.

PubMed Central

Dilda, Christy L; Mackay, Trudy F C

2002-01-01

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

A high-density genetic map and QTL analysis of agronomic traits in foxtail millet [Setaria italica (L.) P. Beauv.] using RAD-seq.

PubMed

Wang, Jun; Wang, Zhilan; Du, Xiaofen; Yang, Huiqing; Han, Fang; Han, Yuanhuai; Yuan, Feng; Zhang, Linyi; Peng, Shuzhong; Guo, Erhu

2017-01-01

Foxtail millet (Setaria italica), a very important grain crop in China, has become a new model plant for cereal crops and biofuel grasses. Although its reference genome sequence was released recently, quantitative trait loci (QTLs) controlling complex agronomic traits remains limited. The development of massively parallel genotyping methods and next-generation sequencing technologies provides an excellent opportunity for developing single-nucleotide polymorphisms (SNPs) for linkage map construction and QTL analysis of complex quantitative traits. In this study, a high-throughput and cost-effective RAD-seq approach was employed to generate a high-density genetic map for foxtail millet. A total of 2,668,587 SNP loci were detected according to the reference genome sequence; meanwhile, 9,968 SNP markers were used to genotype 124 F2 progenies derived from the cross between Hongmiaozhangu and Changnong35; a high-density genetic map spanning 1648.8 cM, with an average distance of 0.17 cM between adjacent markers was constructed; 11 major QTLs for eight agronomic traits were identified; five co-dominant DNA markers were developed. These findings will be of value for the identification of candidate genes and marker-assisted selection in foxtail millet.

A high-density genetic map and QTL analysis of agronomic traits in foxtail millet [Setaria italica (L.) P. Beauv.] using RAD-seq

PubMed Central

Wang, Zhilan; Du, Xiaofen; Yang, Huiqing; Han, Fang; Han, Yuanhuai; Yuan, Feng; Zhang, Linyi; Peng, Shuzhong; Guo, Erhu

2017-01-01

Foxtail millet (Setaria italica), a very important grain crop in China, has become a new model plant for cereal crops and biofuel grasses. Although its reference genome sequence was released recently, quantitative trait loci (QTLs) controlling complex agronomic traits remains limited. The development of massively parallel genotyping methods and next-generation sequencing technologies provides an excellent opportunity for developing single-nucleotide polymorphisms (SNPs) for linkage map construction and QTL analysis of complex quantitative traits. In this study, a high-throughput and cost-effective RAD-seq approach was employed to generate a high-density genetic map for foxtail millet. A total of 2,668,587 SNP loci were detected according to the reference genome sequence; meanwhile, 9,968 SNP markers were used to genotype 124 F2 progenies derived from the cross between Hongmiaozhangu and Changnong35; a high-density genetic map spanning 1648.8 cM, with an average distance of 0.17 cM between adjacent markers was constructed; 11 major QTLs for eight agronomic traits were identified; five co-dominant DNA markers were developed. These findings will be of value for the identification of candidate genes and marker-assisted selection in foxtail millet. PMID:28644843

From plant traits to plant communities: a statistical mechanistic approach to biodiversity.

PubMed

Shipley, Bill; Vile, Denis; Garnier, Eric

2006-11-03

We developed a quantitative method, analogous to those used in statistical mechanics, to predict how biodiversity will vary across environments, which plant species from a species pool will be found in which relative abundances in a given environment, and which plant traits determine community assembly. This provides a scaling from plant traits to ecological communities while bypassing the complications of population dynamics. Our method treats community development as a sorting process involving species that are ecologically equivalent except with respect to particular functional traits, which leads to a constrained random assembly of species; the relative abundance of each species adheres to a general exponential distribution as a function of its traits. Using data for eight functional traits of 30 herbaceous species and community-aggregated values of these traits in 12 sites along a 42-year chronosequence of secondary succession, we predicted 94% of the variance in the relative abundances.

Interspecies synteny mapping identifies a quantitative trait locus for bone mineral density on human chromosome Xp22.

PubMed

Parsons, Claire A; Mroczkowski, H Joel; McGuigan, Fiona E A; Albagha, Omar M E; Manolagas, Stavros; Reid, David M; Ralston, Stuart H; Shmookler Reis, Robert J

2005-11-01

Bone mineral density (BMD) is a complex trait with a strong genetic component and an important predictor of osteoporotic fracture risk. Here we report the use of a cross-species strategy to identify genes that regulate BMD, proceeding from quantitative trait mapping in mice to association mapping of the syntenic region in the human genome. We identified a quantitative trait locus (QTL) on the mouse X-chromosome for post-maturity change in spine BMD in a cross of SAMP6 and AKR/J mice and conducted association mapping of the syntenic region on human chromosome Xp22. We studied 76 single nucleotide polymorphisms (SNP) from the human region in two sets of DNA pools prepared from individuals with lumbar spine-BMD (LS-BMD) values falling into the top and bottom 13th percentiles of a population-based study of 3100 post-menopausal women. This procedure identified a region of significant association for two adjacent SNP (rs234494 and rs234495) within the Xp22 locus (P<0.001). Individual genotyping for rs234494 in the BMD pools confirmed the presence of an association for alleles (P=0.018) and genotypes (P=0.008). Analysis of rs234494 and rs234495 in 1053 women derived from the same population who were not selected for BMD values showed an association with LS-BMD for rs234495 (P=0.01) and for haplotypes defined by both SNP (P=0.002). Our study illustrates that interspecies synteny can be used to identify and refine QTL for complex traits and represents the first example where a human QTL for BMD regulation has been mapped using this approach.

Genetic variation maintained in multilocus models of additive quantitative traits under stabilizing selection.

PubMed Central

Bürger, R; Gimelfarb, A

1999-01-01

Stabilizing selection for an intermediate optimum is generally considered to deplete genetic variation in quantitative traits. However, conflicting results from various types of models have been obtained. While classical analyses assuming a large number of independent additive loci with individually small effects indicated that no genetic variation is preserved under stabilizing selection, several analyses of two-locus models showed the contrary. We perform a complete analysis of a generalization of Wright's two-locus quadratic-optimum model and investigate numerically the ability of quadratic stabilizing selection to maintain genetic variation in additive quantitative traits controlled by up to five loci. A statistical approach is employed by choosing randomly 4000 parameter sets (allelic effects, recombination rates, and strength of selection) for a given number of loci. For each parameter set we iterate the recursion equations that describe the dynamics of gamete frequencies starting from 20 randomly chosen initial conditions until an equilibrium is reached, record the quantities of interest, and calculate their corresponding mean values. As the number of loci increases from two to five, the fraction of the genome expected to be polymorphic declines surprisingly rapidly, and the loci that are polymorphic increasingly are those with small effects on the trait. As a result, the genetic variance expected to be maintained under stabilizing selection decreases very rapidly with increased number of loci. The equilibrium structure expected under stabilizing selection on an additive trait differs markedly from that expected under selection with no constraints on genotypic fitness values. The expected genetic variance, the expected polymorphic fraction of the genome, as well as other quantities of interest, are only weakly dependent on the selection intensity and the level of recombination. PMID:10353920

The chicken genome: some good news and some bad news.

PubMed

Dodgson, J B

2007-07-01

The sequencing of the chicken genome has generated a wealth of good news for poultry science. It allows the chicken to be a major player in 21st century biology by providing an entrée into an arsenal of new technologies that can be used to explore virtually any chicken phenotype of interest. The initial technological onslaught has been described in this symposium. The wealth of data available now or soon to be available cannot be explained by simplistic models and will force us to treat the inherent complexity of the chicken in ways that are more realistic but at the same time more difficult to comprehend. Initial single nucleotide polymorphism analyses suggest that broilers retain a remarkable amount of the genetic diversity of predomesticated Jungle Fowl, whereas commercial layer genomes display less diversity and broader linkage disequilibrium. Thus, intensive commercial selection has not fixed a genome rich in wide selective sweeps, at least within the broiler population. Rather, a complex assortment of combinations of ancient allelic diversity survives. Low levels of linkage disequilibrium will make association analysis in broilers more difficult. The wider disequilibrium observed in layers should facilitate the mapping of quantitative trait loci, and at the same time make it more difficult to identify the causative nucleotide change(s). In addition, many quantitative traits may be specific to the genetic background in which they arose and not readily transferable to, or detectable in, other line backgrounds. Despite the obstacles it presents, the genetic complexity of the chicken may also be viewed as good news because it insures that long-term genetic progress will continue via breeding using quantitative genetics, and it surely will keep poultry scientists busy for decades to come. It is now time to move from an emphasis on obtaining "THE" chicken genome sequence to obtaining multiple sequences, especially of foundation stocks, and a broader understanding of the full genetic and phenotypic diversity of the domesticated chicken.

The evolution of trade-offs: geographic variation in call duration and flight ability in the sand cricket, Gryllus firmus.

PubMed

Roff, D A; Crnokrak, P; Fairbairn, D J

2003-07-01

Quantitative genetic theory assumes that trade-offs are best represented by bivariate normal distributions. This theory predicts that selection will shift the trade-off function itself and not just move the mean trait values along a fixed trade-off line, as is generally assumed in optimality models. As a consequence, quantitative genetic theory predicts that the trade-off function will vary among populations in which at least one of the component traits itself varies. This prediction is tested using the trade-off between call duration and flight capability, as indexed by the mass of the dorsolateral flight muscles, in the macropterous morph of the sand cricket. We use four different populations of crickets that vary in the proportion of macropterous males (Lab = 33%, Florida = 29%, Bermuda = 72%, South Carolina = 80%). We find, as predicted, that there is significant variation in the intercept of the trade-off function but not the slope, supporting the hypothesis that trade-off functions are better represented as bivariate normal distributions rather than single lines. We also test the prediction from a quantitative genetical model of the evolution of wing dimorphism that the mean call duration of macropterous males will increase with the percentage of macropterous males in the population. This prediction is also supported. Finally, we estimate the probability of a macropterous male attracting a female, P, as a function of the relative time spent calling (P = time spent calling by macropterous male/(total time spent calling by both micropterous and macropterous male). We find that in the Lab and Florida populations the probability of a female selecting the macropterous male is equal to P, indicating that preference is due simply to relative call duration. But in the Bermuda and South Carolina populations the probability of a female selecting a macropterous male is less than P, indicating a preference for the micropterous male even after differences in call duration are accounted for.

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

PubMed Central

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

2012-01-01

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

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

PubMed

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

2012-05-01

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

An intersection network based on combining SNP co-association and RNA co-expression networks for feed utilization traits in Japanese Black cattle.

PubMed

Okada, D; Endo, S; Matsuda, H; Ogawa, S; Taniguchi, Y; Katsuta, T; Watanabe, T; Iwaisaki, H

2018-05-12

Genome-wide association studies (GWAS) of quantitative traits have detected numerous genetic associations, but they encounter difficulties in pinpointing prominent candidate genes and inferring gene networks. The present study used a systems genetics approach integrating GWAS results with external RNA-expression data to detect candidate gene networks in feed utilization and growth traits of Japanese Black cattle, which are matters of concern. A SNP co-association network was derived from significant correlations between SNPs with effects estimated by GWAS across seven phenotypic traits. The resulting network genes contained significant numbers of annotations related to the traits. Using bovine transcriptome data from a public database, an RNA co-expression network was inferred based on the similarity of expression patterns across different tissues. An intersection network was then generated by superimposing the SNP and RNA networks and extracting shared interactions. This intersection network contained four tissue-specific modules: nervous system, reproductive system, muscular system, and glands. To characterize the structure (topographical properties) of the three networks, their scale-free properties were evaluated, which revealed that the intersection network was the most scale-free. In the sub-network containing the most connected transcription factors (URI1, ROCK2 and ETV6), most genes were widely expressed across tissues, and genes previously shown to be involved in the traits were found. Results indicated that the current approach might be used to construct a gene network that better reflects biological information, providing encouragement for the genetic dissection of economically important quantitative traits.

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

PubMed Central

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

2012-01-01

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

QTL mapping for sexually dimorphic fitness-related traits in wild bighorn sheep

PubMed Central

Poissant, J; Davis, C S; Malenfant, R M; Hogg, J T; Coltman, D W

2012-01-01

Dissecting the genetic architecture of fitness-related traits in wild populations is key to understanding evolution and the mechanisms maintaining adaptive genetic variation. We took advantage of a recently developed genetic linkage map and phenotypic information from wild pedigreed individuals from Ram Mountain, Alberta, Canada, to study the genetic architecture of ecologically important traits (horn volume, length, base circumference and body mass) in bighorn sheep. In addition to estimating sex-specific and cross-sex quantitative genetic parameters, we tested for the presence of quantitative trait loci (QTLs), colocalization of QTLs between bighorn sheep and domestic sheep, and sex × QTL interactions. All traits showed significant additive genetic variance and genetic correlations tended to be positive. Linkage analysis based on 241 microsatellite loci typed in 310 pedigreed animals resulted in no significant and five suggestive QTLs (four for horn dimension on chromosomes 1, 18 and 23, and one for body mass on chromosome 26) using genome-wide significance thresholds (Logarithm of odds (LOD) >3.31 and >1.88, respectively). We also confirmed the presence of a horn dimension QTL in bighorn sheep at the only position known to contain a similar QTL in domestic sheep (on chromosome 10 near the horns locus; nominal P<0.01) and highlighted a number of regions potentially containing weight-related QTLs in both species. As expected for sexually dimorphic traits involved in male–male combat, loci with sex-specific effects were detected. This study lays the foundation for future work on adaptive genetic variation and the evolutionary dynamics of sexually dimorphic traits in bighorn sheep. PMID:21847139

Descriptive statistics and correlation analysis of agronomic traits in a maize recombinant inbred line population.

PubMed

Zhang, H M; Hui, G Q; Luo, Q; Sun, Y; Liu, X H

2014-01-21

Maize (Zea mays L.) is one of the most important crops in the world. In this study, 13 agronomic traits of a recombinant inbred line population that was derived from the cross between Mo17 and Huangzao4 were investigated in maize: ear diameter, ear length, ear axis diameter, ear weight, plant height, ear height, days to pollen shed (DPS), days to silking (DS), the interval between DPS and DS, 100-kernel weight, kernel test weight, ear kernel weight, and kernel rate. Furthermore, the descriptive statistics and correlation analysis of the 13 traits were performed using the SPSS 11.5 software. The results providing the phenotypic data here are needed for the quantitative trait locus mapping of these agronomic traits.

Quantitative analysis of production traits in saltwater crocodiles (Crocodylus porosus): II. age at slaughter.

PubMed

Isberg, S R; Thomson, P C; Nicholas, F W; Barker, S G; Moran, C

2005-12-01

Crocodile morphometric (head, snout-vent and total length) measurements were recorded at three stages during the production chain: hatching, inventory [average age (+/-SE) is 265.1 +/- 0.4 days] and slaughter (average age is 1037.8 +/- 0.4 days). Crocodile skins are used for the manufacture of exclusive leather products, with the most common-sized skin sold having 35-45 cm in belly width. One of the breeding objectives for inclusion into a multitrait genetic improvement programme for saltwater crocodiles is the time taken for a juvenile to reach this size or age at slaughter. A multivariate restricted maximum likelihood analysis provided (co)variance components for estimating the first published genetic parameter estimates for these traits. Heritability (+/-SE) estimates for the traits hatchling snout-vent length, inventory head length and age at slaughter were 0.60 (0.15), 0.59 (0.12) and 0.40 (0.10) respectively. There were strong negative genetic (-0.81 +/- 0.08) and phenotypic (-0.82 +/- 0.02) correlations between age at slaughter and inventory head length.

Fourteen Years of R/qtl: Just Barely Sustainable

PubMed Central

Broman, Karl W.

2014-01-01

R/qtl is an R package for mapping quantitative trait loci (genetic loci that contribute to variation in quantitative traits) in experimental crosses. Its development began in 2000. There have been 38 software releases since 2001. The latest release contains 35k lines of R code and 24k lines of C code, plus 15k lines of code for the documentation. Challenges in the development and maintenance of the software are discussed. A key to the success of R/qtl is that it remains a central tool for the chief developer's own research work, and so its maintenance is of selfish importance. PMID:25364504

[The study of tomato fruit weight quantitative trait locus and its application in genetics teaching].

PubMed

Wang, Hai-yan

2015-08-01

The classical research cases, which have greatly promoted the development of genetics in history, can be combined with the content of courses in genetics teaching to train students' ability of scientific thinking and genetic analysis. The localization and clone of gene controlling tomato fruit weight is a pioneer work in quantitative trait locus (QTL) studies and represents a complete process of QTL research in plants. Application of this integrated case in genetics teaching, which showed a wonderful process of scientific discovery and the fascination of genetic research, has inspired students' interest in genetics and achieved a good teaching effect.

Genetic variation affecting host-parasite interactions: major-effect quantitative trait loci affect the transmission of sigma virus in Drosophila melanogaster.

PubMed

Bangham, Jenny; Knott, Sara A; Kim, Kang-Wook; Young, Robert S; Jiggins, Francis M

2008-09-01

In natural populations, genetic variation affects resistance to disease. Whether that genetic variation comprises lots of small-effect polymorphisms or a small number of large-effect polymorphisms has implications for adaptation, selection and how genetic variation is maintained in populations. Furthermore, how much genetic variation there is, and the genes that underlie this variation, affects models of co-evolution between parasites and their hosts. We are studying the genetic variation that affects the resistance of Drosophila melanogaster to its natural pathogen--the vertically transmitted sigma virus. We have carried out three separate quantitative trait locus mapping analyses to map gene variants on the second chromosome that cause variation in the rate at which males transmit the infection to their offspring. All three crosses identified a locus in a similar chromosomal location that causes a large drop in the rate at which the virus is transmitted. We also found evidence for an additional smaller-effect quantitative trait locus elsewhere on the chromosome. Our data, together with previous experiments on the sigma virus and parasitoid wasps, indicate that the resistance of D. melanogaster to co-evolved pathogens is controlled by a limited number of major-effect polymorphisms.

Quantitative trait loci mapping of heat tolerance in broccoli (Brassica oleracea var. italica) using genotyping-by-sequencing.

PubMed

Branham, Sandra E; Stansell, Zachary J; Couillard, David M; Farnham, Mark W

2017-03-01

Five quantitative trait loci and one epistatic interaction were associated with heat tolerance in a doubled haploid population of broccoli evaluated in three summer field trials. Predicted rising global temperatures due to climate change have generated a demand for crops that are resistant to yield and quality losses from heat stress. Broccoli (Brassica oleracea var. italica) is a cool weather crop with high temperatures during production decreasing both head quality and yield. Breeding for heat tolerance in broccoli has potential to both expand viable production areas and extend the growing season but breeding efficiency is constrained by limited genetic information. A doubled haploid (DH) broccoli population segregating for heat tolerance was evaluated for head quality in three summer fields in Charleston, SC, USA. Multiple quantitative trait loci (QTL) mapping of 1,423 single nucleotide polymorphisms developed through genotyping-by-sequencing identified five QTL and one positive epistatic interaction that explained 62.1% of variation in heat tolerance. The QTL identified here can be used to develop markers for marker-assisted selection and to increase our understanding of the molecular mechanisms underlying plant response to heat stress.

Identifying the genes underlying quantitative traits: a rationale for the QTN programme.

PubMed

Lee, Young Wha; Gould, Billie A; Stinchcombe, John R

2014-01-01

The goal of identifying the genes or even nucleotides underlying quantitative and adaptive traits has been characterized as the 'QTN programme' and has recently come under severe criticism. Part of the reason for this criticism is that much of the QTN programme has asserted that finding the genes and nucleotides for adaptive and quantitative traits is a fundamental goal, without explaining why it is such a hallowed goal. Here we outline motivations for the QTN programme that offer general insight, regardless of whether QTNs are of large or small effect, and that aid our understanding of the mechanistic dynamics of adaptive evolution. We focus on five areas: (i) vertical integration of insight across different levels of biological organization, (ii) genetic parallelism and the role of pleiotropy in shaping evolutionary dynamics, (iii) understanding the forces maintaining genetic variation in populations, (iv) distinguishing between adaptation from standing variation and new mutation, and (v) the role of genomic architecture in facilitating adaptation. We argue that rather than abandoning the QTN programme, we should refocus our efforts on topics where molecular data will be the most effective for testing hypotheses about phenotypic evolution.

Identifying the genes underlying quantitative traits: a rationale for the QTN programme

PubMed Central

Lee, Young Wha; Gould, Billie A.; Stinchcombe, John R.

2014-01-01

The goal of identifying the genes or even nucleotides underlying quantitative and adaptive traits has been characterized as the ‘QTN programme’ and has recently come under severe criticism. Part of the reason for this criticism is that much of the QTN programme has asserted that finding the genes and nucleotides for adaptive and quantitative traits is a fundamental goal, without explaining why it is such a hallowed goal. Here we outline motivations for the QTN programme that offer general insight, regardless of whether QTNs are of large or small effect, and that aid our understanding of the mechanistic dynamics of adaptive evolution. We focus on five areas: (i) vertical integration of insight across different levels of biological organization, (ii) genetic parallelism and the role of pleiotropy in shaping evolutionary dynamics, (iii) understanding the forces maintaining genetic variation in populations, (iv) distinguishing between adaptation from standing variation and new mutation, and (v) the role of genomic architecture in facilitating adaptation. We argue that rather than abandoning the QTN programme, we should refocus our efforts on topics where molecular data will be the most effective for testing hypotheses about phenotypic evolution. PMID:24790125

Ascertainment bias from imputation methods evaluation in wheat.

PubMed

Brandariz, Sofía P; González Reymúndez, Agustín; Lado, Bettina; Malosetti, Marcos; Garcia, Antonio Augusto Franco; Quincke, Martín; von Zitzewitz, Jarislav; Castro, Marina; Matus, Iván; Del Pozo, Alejandro; Castro, Ariel J; Gutiérrez, Lucía

2016-10-04

Whole-genome genotyping techniques like Genotyping-by-sequencing (GBS) are being used for genetic studies such as Genome-Wide Association (GWAS) and Genomewide Selection (GS), where different strategies for imputation have been developed. Nevertheless, imputation error may lead to poor performance (i.e. smaller power or higher false positive rate) when complete data is not required as it is for GWAS, and each marker is taken at a time. The aim of this study was to compare the performance of GWAS analysis for Quantitative Trait Loci (QTL) of major and minor effect using different imputation methods when no reference panel is available in a wheat GBS panel. In this study, we compared the power and false positive rate of dissecting quantitative traits for imputed and not-imputed marker score matrices in: (1) a complete molecular marker barley panel array, and (2) a GBS wheat panel with missing data. We found that there is an ascertainment bias in imputation method comparisons. Simulating over a complete matrix and creating missing data at random proved that imputation methods have a poorer performance. Furthermore, we found that when QTL were simulated with imputed data, the imputation methods performed better than the not-imputed ones. On the other hand, when QTL were simulated with not-imputed data, the not-imputed method and one of the imputation methods performed better for dissecting quantitative traits. Moreover, larger differences between imputation methods were detected for QTL of major effect than QTL of minor effect. We also compared the different marker score matrices for GWAS analysis in a real wheat phenotype dataset, and we found minimal differences indicating that imputation did not improve the GWAS performance when a reference panel was not available. Poorer performance was found in GWAS analysis when an imputed marker score matrix was used, no reference panel is available, in a wheat GBS panel.

Deleterious Mutations, Apparent Stabilizing Selection and the Maintenance of Quantitative Variation

PubMed Central

Kondrashov, A. S.; Turelli, M.

1992-01-01

Apparent stabilizing selection on a quantitative trait that is not causally connected to fitness can result from the pleiotropic effects of unconditionally deleterious mutations, because as N. Barton noted, ``... individuals with extreme values of the trait will tend to carry more deleterious alleles ....'' We use a simple model to investigate the dependence of this apparent selection on the genomic deleterious mutation rate, U; the equilibrium distribution of K, the number of deleterious mutations per genome; and the parameters describing directional selection against deleterious mutations. Unlike previous analyses, we allow for epistatic selection against deleterious alleles. For various selection functions and realistic parameter values, the distribution of K, the distribution of breeding values for a pleiotropically affected trait, and the apparent stabilizing selection function are all nearly Gaussian. The additive genetic variance for the quantitative trait is kQa(2), where k is the average number of deleterious mutations per genome, Q is the proportion of deleterious mutations that affect the trait, and a(2) is the variance of pleiotropic effects for individual mutations that do affect the trait. In contrast, when the trait is measured in units of its additive standard deviation, the apparent fitness function is essentially independent of Q and a(2); and β, the intensity of selection, measured as the ratio of additive genetic variance to the ``variance'' of the fitness curve, is very close to s = U/k, the selection coefficient against individual deleterious mutations at equilibrium. Therefore, this model predicts appreciable apparent stabilizing selection if s exceeds about 0.03, which is consistent with various data. However, the model also predicts that β must equal V(m)/V(G), the ratio of new additive variance for the trait introduced each generation by mutation to the standing additive variance. Most, although not all, estimates of this ratio imply apparent stabilizing selection weaker than generally observed. A qualitative argument suggests that even when direct selection is responsible for most of the selection observed on a character, it may be essentially irrelevant to the maintenance of variation for the character by mutation-selection balance. Simple experiments can indicate the fraction of observed stabilizing selection attributable to the pleiotropic effects of deleterious mutations. PMID:1427047

The genetic basis of speciation in the Giliopsis lineage of Ipomopsis (Polemoniaceae)

USGS Publications Warehouse

Nakazato, Takuya; Rieseberg, Loren H.; Wood, Troy E.

2013-01-01

One of the most powerful drivers of speciation in plants is pollinator-mediated disruptive selection, which leads to the divergence of floral traits adapted to the morphology and behavior of different pollinators. Despite the widespread importance of this speciation mechanism, its genetic basis has been explored in only a few groups. Here, we characterize the genetic basis of pollinator-mediated divergence of two species in genus Ipomopsis, I. guttata and I. tenuifolia, using quantitative trait locus (QTL) analyses of floral traits and other variable phenotypes. We detected one to six QTLs per trait, with each QTL generally explaining small to modest amounts of the phenotypic variance of a backcross hybrid population. In contrast, flowering time and anthocyanin abundance (a metric of color variation) were controlled by a few QTLs of relatively large effect. QTLs were strongly clustered within linkage groups, with 26 of 37 QTLs localized to six marker-interval ‘hotspots,’ all of which harbored pleiotropic QTLs. In contrast to other studies that have examined the genetic basis of pollinator shifts, our results indicate that, in general, mutations of small to modest effect on phenotype were involved. Thus, the evolutionary transition between the distinct pollination modes of I. guttata and I. tenuifolia likely proceeded incrementally, rather than saltationally.

Tangled nature model of evolutionary dynamics reconsidered: Structural and dynamical effects of trait inheritance

NASA Astrophysics Data System (ADS)

Andersen, Christian Walther; Sibani, Paolo

2016-05-01

Based on the stochastic dynamics of interacting agents which reproduce, mutate, and die, the tangled nature model (TNM) describes key emergent features of biological and cultural ecosystems' evolution. While trait inheritance is not included in many applications, i.e., the interactions of an agent and those of its mutated offspring are taken to be uncorrelated, in the family of TNMs introduced in this work correlations of varying strength are parametrized by a positive integer K . We first show that the interactions generated by our rule are nearly independent of K . Consequently, the structural and dynamical effects of trait inheritance can be studied independently of effects related to the form of the interactions. We then show that changing K strengthens the core structure of the ecology, leads to population abundance distributions better approximated by log-normal probability densities, and increases the probability that a species extant at time tw also survives at t >tw . Finally, survival probabilities of species are shown to decay as powers of the ratio t /tw , a so-called pure aging behavior usually seen in glassy systems of physical origin. We find a quantitative dynamical effect of trait inheritance, namely, that increasing the value of K numerically decreases the decay exponent of the species survival probability.

Tangled nature model of evolutionary dynamics reconsidered: Structural and dynamical effects of trait inheritance.

PubMed

Andersen, Christian Walther; Sibani, Paolo

2016-05-01

Based on the stochastic dynamics of interacting agents which reproduce, mutate, and die, the tangled nature model (TNM) describes key emergent features of biological and cultural ecosystems' evolution. While trait inheritance is not included in many applications, i.e., the interactions of an agent and those of its mutated offspring are taken to be uncorrelated, in the family of TNMs introduced in this work correlations of varying strength are parametrized by a positive integer K. We first show that the interactions generated by our rule are nearly independent of K. Consequently, the structural and dynamical effects of trait inheritance can be studied independently of effects related to the form of the interactions. We then show that changing K strengthens the core structure of the ecology, leads to population abundance distributions better approximated by log-normal probability densities, and increases the probability that a species extant at time t_{w} also survives at t>t_{w}. Finally, survival probabilities of species are shown to decay as powers of the ratio t/t_{w}, a so-called pure aging behavior usually seen in glassy systems of physical origin. We find a quantitative dynamical effect of trait inheritance, namely, that increasing the value of K numerically decreases the decay exponent of the species survival probability.

Phenotypic variation and identification of quantitative trait loci for ozone injury in a Fiskeby III x Mandarin (Ottawa) soybean population

USDA-ARS?s Scientific Manuscript database

Ground-level ozone reduces yield in crops such as soybean (Glycine max (L.) Merr.). Phenotypic variation has been observed for this trait in multiple species; however, breeding for ozone tolerance has been limited. A recombinant inbred population was developed from soybean genotypes differing in tol...

The Relationship between Resilience and the Big Five Personality Traits in Emerging Adulthood

ERIC Educational Resources Information Center

Ercan, Hulya

2017-01-01

Purpose: The factors related with resilience, which is an important element of positive psychology, are still being discussed. The main purpose of this study is to examine the relationship between the resilience levels of individuals in emerging adulthood and the big five personality traits. Research Methods: Using a quantitative approach, the…

Selection for Reduced Fusarium Ear Rot and Fumonisin Content in Advanced Backcross Maize Lines and Their Topcross Hybrids

USDA-ARS?s Scientific Manuscript database

Backcross breeding is an important method to improve elite cultivars for traits controlled by a small number of loci but has been used less frequently to improve quantitatively controlled traits. Resistances to Fusarium ear rot and contamination by the associated mycotoxin fumonisin in maize are qua...

A genetic linkage map of tetraploid orchardgrass (Dactylis glomerata L.) a quantitative trait loci for heading date

USDA-ARS?s Scientific Manuscript database

Orchardgrass (Dactylis glomerata L.) is indigenous to Eurasia and northern Africa, has been naturalized on nearly every continent, and is one of the top perennial forage grasses grown worldwide. Despite its distribution and uses, there is a need for improvement of value added traits that are limite...

Genetic analysis of grain attributes, milling performance, and end-use quality traits in hard red spring wheat (Triticum aestivum L.)

USDA-ARS?s Scientific Manuscript database

Wheat kernel texture dictates U.S. wheat market class and culinary end-uses. Of interest to wheat breeders is to identify quantitative trait loci (QTL) for wheat kernel texture, milling performance, or end-use quality because it is imperative for wheat breeders to ascertain the genetic architecture ...

Construction of a Genetic Linkage Map and Identification of QTLs for Resistance to TSWV in Cultivated Peanut (Arachis hypagea L.)

USDA-ARS?s Scientific Manuscript database

A genetic linkage map is critical for identifying the QTL (quantitative trait loci) underling targeted traits. Over the last few years, progress has been made in marker development from multiple sources enabling the expansion of quality resources needed for genotyping applications in cultivated x cu...

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

PubMed Central

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

2008-01-01

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

The genetics of muscle atrophy and growth: the impact and implications of polymorphisms in animals and humans.

PubMed

Gordon, Erynn S; Gordish Dressman, Heather A; Hoffman, Eric P

2005-10-01

Much of the vast diversity we see in animals and people is governed by genetic loci that have quantitative effects of phenotype (quantitative trait loci; QTLs). Here we review the current knowledge of the genetics of atrophy and hypertrophy in both animal husbandry (meat quantity and quality), and humans (muscle size and performance). The selective breeding of animals for meat has apparently led to a few genetic loci with strong effects, with different loci in different animals. In humans, muscle quantitative trait loci (QTLs) appear to be more complex, with few "major" loci identified to date, although this is likely to change in the near future. We describe how the same phenotypic traits we see as positive, greater lean muscle mass in cattle or a better exercise results in humans, can also have negative "side effects" given specific environmental challenges. We also discuss the strength and limitations of single nucleotide polymorphisms (SNP) association studies; what the reader should look for and expect in a published study. Lastly we discuss the ethical and societal implications of this genetic information. As more and more research into the genetic loci that dictate phenotypic traits become available, the ethical implications of testing for these loci become increasingly important. As a society, most accept testing for genetic diseases or susceptibility, but do we as easily accept testing to determine one's athletic potential to be an Olympic endurance runner, or quarterback on the high school football team.

Improving power and robustness for detecting genetic association with extreme-value sampling design.

PubMed

Chen, Hua Yun; Li, Mingyao

2011-12-01

Extreme-value sampling design that samples subjects with extremely large or small quantitative trait values is commonly used in genetic association studies. Samples in such designs are often treated as "cases" and "controls" and analyzed using logistic regression. Such a case-control analysis ignores the potential dose-response relationship between the quantitative trait and the underlying trait locus and thus may lead to loss of power in detecting genetic association. An alternative approach to analyzing such data is to model the dose-response relationship by a linear regression model. However, parameter estimation from this model can be biased, which may lead to inflated type I errors. We propose a robust and efficient approach that takes into consideration of both the biased sampling design and the potential dose-response relationship. Extensive simulations demonstrate that the proposed method is more powerful than the traditional logistic regression analysis and is more robust than the linear regression analysis. We applied our method to the analysis of a candidate gene association study on high-density lipoprotein cholesterol (HDL-C) which includes study subjects with extremely high or low HDL-C levels. Using our method, we identified several SNPs showing a stronger evidence of association with HDL-C than the traditional case-control logistic regression analysis. Our results suggest that it is important to appropriately model the quantitative traits and to adjust for the biased sampling when dose-response relationship exists in extreme-value sampling designs. © 2011 Wiley Periodicals, Inc.

Quantitative differences detected in the histology of galls induced by the same aphid species in different varieties of the same host.

PubMed

Martinez, J-J I; Moreno-González, V; Jonas-Levi, A; Álvarez, R

2018-05-01

Plant galls are abnormal growths caused by an inducer that determines their morphology and anatomy. We qualitatively and quantitatively compared the histological anatomy of five aphid species (Paracletus cimiciformis, Forda marginata, Forda formicaria, Baizongia pistaciae and Geoica wertheimae) that induce galls in Pistacia terebinthus shrubs growing in Israel. We also quantitatively compared these galls to those that the aphids create on the same host in Spain. Histological study was conducted following methods described previously by the authors. Quantitative differences among the galls were found in five of 12 common anatomical traits: gall thickness, stomatal number in the epidermis-air, size of vascular bundles, distance of phloem ducts from the lumen and number of intraphloematic schizogenous ducts. Other structures were particular to one or some species: number of cracks in the epidermis-lumen, a sclereid layer, trichomes and microcrystal inclusions. Fisher's tests of combined probabilities showed that the galls induced in Israel were statistically different from those in Spain. In particular, the number of intraphloematic schizogenous ducts was higher in the galls induced in P. terebinthus in Israel. Such differences were also found in other traits related to defence of the gall inhabitant. In conclusion, while the gall shape and size are determined mainly by the cecidogenic insect, it seems that the host plant also plays an important role in determining the number/size of quantitative traits, in this case mainly protective structures. © 2018 German Society for Plant Sciences and The Royal Botanical Society of the Netherlands.

High Density Single Nucleotide Polymorphism (SNP) Mapping and Quantitative Trait Loci (QTL) Analysis in a Biparental Spring Triticale Population Localized Major and Minor Effect Fusarium Head Blight Resistance and Associated Traits QTL

PubMed Central

Dhariwal, Raman; Fedak, George; Dion, Yves; Pozniak, Curtis; Laroche, André; Eudes, François; Randhawa, Harpinder Singh

2018-01-01

Triticale (xTriticosecale Wittmack) is an important feed crop which suffers severe yield, grade and end-use quality losses due to Fusarium head blight (FHB). Development of resistant triticale cultivars is hindered by lack of effective genetic resistance sources. To dissect FHB resistance, a doubled haploid spring triticale population produced from the cross TMP16315/AC Ultima using a microspore culture method, was phenotyped for FHB incidence, severity, visual rating index (VRI), deoxynivalenol (DON) and some associated traits (ergot, grain protein content, test weight, yield, plant height and lodging) followed by single nucleotide polymorphism (SNP) genotyping. A high-density map consisting of 5274 SNPs, mapped on all 21 chromosomes with a map density of 0.48 cM/SNP, was constructed. Together, 17 major quantitative trait loci were identified for FHB on chromosomes 1A, 2B, 3A, 4A, 4R, 5A, 5R and 6B; two of incidence loci (on 2B and 5R) also co-located with loci for severity and VRI, and two other loci of VRI (on 1A and 4R) with DON accumulation. Major and minor loci were also identified for all other traits in addition to many epistasis loci. This study provides new insight into the genetic basis of FHB resistance and their association with other traits in triticale. PMID:29304028

Mapping quantitative trait loci affecting Arabidopsis thaliana seed morphology features extracted computationally from images.

PubMed

Moore, Candace R; Gronwall, David S; Miller, Nathan D; Spalding, Edgar P

2013-01-01

Seeds are studied to understand dispersal and establishment of the next generation, as units of agricultural yield, and for other important reasons. Thus, elucidating the genetic architecture of seed size and shape traits will benefit basic and applied plant biology research. This study sought quantitative trait loci (QTL) controlling the size and shape of Arabidopsis thaliana seeds by computational analysis of seed phenotypes in recombinant inbred lines derived from the small-seeded Landsberg erecta × large-seeded Cape Verde Islands accessions. On the order of 10(3) seeds from each recombinant inbred line were automatically measured with flatbed photo scanners and custom image analysis software. The eight significant QTL affecting seed area explained 63% of the variation, and overlapped with five of the six major-axis (length) QTL and three of the five minor-axis (width) QTL, which accounted for 57% and 38% of the variation in those traits, respectively. Because the Arabidopsis seed is exalbuminous, lacking an endosperm at maturity, the results are relatable to embryo length and width. The Cvi allele generally had a positive effect of 2.6-4.0%. Analysis of variance showed heritability of the three traits ranged between 60% and 73%. Repeating the experiment with 2.2 million seeds from a separate harvest of the RIL population and approximately 0.5 million seeds from 92 near-isogenic lines confirmed the aforementioned results. Structured for download are files containing phenotype measurements, all sets of seed images, and the seed trait measuring tool.

Image Harvest: an open-source platform for high-throughput plant image processing and analysis.

PubMed

Knecht, Avi C; Campbell, Malachy T; Caprez, Adam; Swanson, David R; Walia, Harkamal

2016-05-01

High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

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

PubMed Central

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

2012-01-01

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

Allelic variations and differential expressions detected at quantitative trait loci for salt stress tolerance in wheat.

PubMed

Oyiga, Benedict C; Sharma, Ram C; Baum, Michael; Ogbonnaya, Francis C; Léon, Jens; Ballvora, Agim

2018-05-01

The increasing salinization of agricultural lands is a threat to global wheat production. Understanding of the mechanistic basis of salt tolerance (ST) is essential for developing breeding and selection strategies that would allow for increased wheat production under saline conditions to meet the increasing global demand. We used a set that consists of 150 internationally derived winter and facultative wheat cultivars genotyped with a 90K SNP chip and phenotyped for ST across three growth stages and for ionic (leaf K + and Na +  contents) traits to dissect the genetic architecture regulating ST in wheat. Genome-wide association mapping revealed 187 Single Nucleotide Polymorphism (SNPs) (R 2  = 3.00-30.67%), representing 37 quantitative trait loci (QTL), significantly associated with the ST traits. Of these, four QTL on 1BS, 2AL, 2BS and 3AL were associated with ST across the three growth stages and with the ionic traits. Novel QTL were also detected on 1BS and 1DL. Candidate genes linked to these polymorphisms were uncovered, and expression analyses were performed and validated on them under saline and non-saline conditions using transcriptomics and qRT-PCR data. Expressed sequence comparisons in contrasting ST wheat genotypes identified several non-synonymous/missense mutation sites that are contributory to the ST trait variations, indicating the biological relevance of these polymorphisms that can be exploited in breeding for ST in wheat. © 2017 The Authors. Plant, Cell & Environment published by JohnWiley & Sons Ltd.

Positive Effects of a Stress Reduction Program Based on Mindfulness Meditation in Brazilian Nursing Professionals: Qualitative and Quantitative Evaluation.

PubMed

dos Santos, Teresa Maria; Kozasa, Elisa Harumi; Carmagnani, Isabel Sampaio; Tanaka, Luiza Hiromi; Lacerda, Shirley Silva; Nogueira-Martins, Luiz Antonio

2016-01-01

Mindfulness meditation has been shown to effectively mitigate the negative effects of stress among nursing professionals, but in countries like Brazil, these practices are relatively unexplored. To evaluate the effects of a Stress Reduction Program (SRP) including mindfulness and loving kindness meditation among nursing professionals working in a Brazilian hospital setting. Pilot study with a mixed model using quantitative and qualitative methods was used to evaluate a group of participants. The quantitative data were analyzed at three different time points: pre-intervention, post-intervention, and follow-up. The qualitative data were analyzed at post-intervention. Hospital São Paulo (Brazil). Sample 13 nursing professionals, including nurses, technicians, and nursing assistants working in a hospital. Participants underwent mindfulness and loving kindness meditation during a period of six weeks. Perceived Stress Scale (PSS), Maslach Burnout Inventory (MBI), Beck Depression Inventory (BDI), State-Trait Anxiety Inventory (STAI), Satisfaction With Life Scale (SWLS), Self-Compassion Scale (SCS), WHOQOL-BREF quality of life assessment, and Work Stress Scale (WSS). Qualitative data were collected via a group interview following six weeks participation in the SRP. The quantitative analyses revealed a significant reduction (P < .05) between pre-intervention and post-intervention scores for perceived stress, burnout, depression, and anxiety (trait). These variables showed no significant differences between post-intervention and follow-up scores. The WHOQOL-BREF revealed significant increase (P < .05) just in the physical and psychological domains at post-intervention scores, which remained at the follow-up. Qualitative results showed improvement in the reactivity to inner experience; a more attentive perception of internal and external experiences; greater attention and awareness of actions and attitudes at every moment; and a positive influence of the SRP in nursing activities. Copyright © 2016 Elsevier Inc. All rights reserved.

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

PubMed

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

2018-06-13

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

Quantitative genetic analysis of anxiety trait in bipolar disorder.

PubMed

Contreras, J; Hare, E; Chavarría, G; Raventós, H

2018-01-01

Bipolar disorder type I (BPI) affects approximately 1% of the world population. Although genetic influences on bipolar disorder are well established, identification of genes that predispose to the illness has been difficult. Most genetic studies are based on categorical diagnosis. One strategy to overcome this obstacle is the use of quantitative endophenotypes, as has been done for other medical disorders. We studied 619 individuals, 568 participants from 61 extended families and 51 unrelated healthy controls. The sample was 55% female and had a mean age of 43.25 (SD 13.90; range 18-78). Heritability and genetic correlation of the trait scale from the Anxiety State and Trait Inventory (STAI) was computed by using the general linear model (SOLAR package software). we observed that anxiety trait meets the following criteria for an endophenotype of bipolar disorder type I (BPI): 1) association with BPI (individuals with BPI showed the highest trait score (F = 15.20 [5,24], p = 0.009), 2) state-independence confirmed after conducting a test-retest in 321 subjects, 3) co-segregation within families 4) heritability of 0.70 (SE: 0.060), p = 2.33 × 10 -14 and 5) genetic correlation with BPI was 0.20, (SE = 0.17, p = 3.12 × 10 -5 ). Confounding factors such as comorbid disorders and pharmacological treatment could affect the clinical relationship between BPI and anxiety trait. Further research is needed to evaluate if anxiety traits are specially related to BPI in comparison with other traits such as anger, attention or response inhibition deficit, pathological impulsivity or low self-directedness. Anxiety trait is a heritable phenotype that follows a normal distribution when measured not only in subjects with BPI but also in unrelated healthy controls. It could be used as an endophenotype in BPI for the identification of genomic regions with susceptibility genes for this disorder. Published by Elsevier B.V.

Mapping in an apple (Malus x domestica) F1 segregating population based on physical clustering of differentially expressed genes.

PubMed

Jensen, Philip J; Fazio, Gennaro; Altman, Naomi; Praul, Craig; McNellis, Timothy W

2014-04-04

Apple tree breeding is slow and difficult due to long generation times, self-incompatibility, and complex genetics. The identification of molecular markers linked to traits of interest is a way to expedite the breeding process. In the present study, we aimed to identify genes whose steady-state transcript abundance was associated with inheritance of specific traits segregating in an apple (Malus × domestica) rootstock F1 breeding population, including resistance to powdery mildew (Podosphaera leucotricha) disease and woolly apple aphid (Eriosoma lanigerum). Transcription profiling was performed for 48 individual F1 apple trees from a cross of two highly heterozygous parents, using RNA isolated from healthy, actively-growing shoot tips and a custom apple DNA oligonucleotide microarray representing 26,000 unique transcripts. Genome-wide expression profiles were not clear indicators of powdery mildew or woolly apple aphid resistance phenotype. However, standard differential gene expression analysis between phenotypic groups of trees revealed relatively small sets of genes with trait-associated expression levels. For example, thirty genes were identified that were differentially expressed between trees resistant and susceptible to powdery mildew. Interestingly, the genes encoding twenty-four of these transcripts were physically clustered on chromosome 12. Similarly, seven genes were identified that were differentially expressed between trees resistant and susceptible to woolly apple aphid, and the genes encoding five of these transcripts were also clustered, this time on chromosome 17. In each case, the gene clusters were in the vicinity of previously identified major quantitative trait loci for the corresponding trait. Similar results were obtained for a series of molecular traits. Several of the differentially expressed genes were used to develop DNA polymorphism markers linked to powdery mildew disease and woolly apple aphid resistance. Gene expression profiling and trait-associated transcript analysis using an apple F1 population readily identified genes physically linked to powdery mildew disease resistance and woolly apple aphid resistance loci. This result was especially useful in apple, where extreme levels of heterozygosity make the development of reliable DNA markers quite difficult. The results suggest that this approach could prove effective in crops with complicated genetics, or for which few genomic information resources are available.

Joint analysis of quantitative trait loci and major-effect causative mutations affecting meat quality and carcass composition traits in pigs.

PubMed

Cherel, Pierre; Pires, José; Glénisson, Jérôme; Milan, Denis; Iannuccelli, Nathalie; Hérault, Frédéric; Damon, Marie; Le Roy, Pascale

2011-08-29

Detection of quantitative trait loci (QTLs) affecting meat quality traits in pigs is crucial for the design of efficient marker-assisted selection programs and to initiate efforts toward the identification of underlying polymorphisms. The RYR1 and PRKAG3 causative mutations, originally identified from major effects on meat characteristics, can be used both as controls for an overall QTL detection strategy for diversely affected traits and as a scale for detected QTL effects. We report on a microsatellite-based QTL detection scan including all autosomes for pig meat quality and carcass composition traits in an F2 population of 1,000 females and barrows resulting from an intercross between a Pietrain and a Large White-Hampshire-Duroc synthetic sire line. Our QTL detection design allowed side-by-side comparison of the RYR1 and PRKAG3 mutation effects seen as QTLs when segregating at low frequencies (0.03-0.08), with independent QTL effects detected from most of the same population, excluding any carrier of these mutations. Large QTL effects were detected in the absence of the RYR1 and PRKGA3 mutations, accounting for 12.7% of phenotypic variation in loin colour redness CIE-a* on SSC6 and 15% of phenotypic variation in glycolytic potential on SSC1. We detected 8 significant QTLs with effects on meat quality traits and 20 significant QTLs for carcass composition and growth traits under these conditions. In control analyses including mutation carriers, RYR1 and PRKAG3 mutations were detected as QTLs, from highly significant to suggestive, and explained 53% to 5% of the phenotypic variance according to the trait. Our results suggest that part of muscle development and backfat thickness effects commonly attributed to the RYR1 mutation may be a consequence of linkage with independent QTLs affecting those traits. The proportion of variation explained by the most significant QTLs detected in this work is close to the influence of major-effect mutations on the least affected traits, but is one order of magnitude lower than effect on variance of traits primarily affected by these causative mutations. This suggests that uncovering physiological traits directly affected by genetic polymorphisms would be an appropriate approach for further characterization of QTLs.

Joint analysis of quantitative trait loci and major-effect causative mutations affecting meat quality and carcass composition traits in pigs

PubMed Central

2011-01-01

Background Detection of quantitative trait loci (QTLs) affecting meat quality traits in pigs is crucial for the design of efficient marker-assisted selection programs and to initiate efforts toward the identification of underlying polymorphisms. The RYR1 and PRKAG3 causative mutations, originally identified from major effects on meat characteristics, can be used both as controls for an overall QTL detection strategy for diversely affected traits and as a scale for detected QTL effects. We report on a microsatellite-based QTL detection scan including all autosomes for pig meat quality and carcass composition traits in an F2 population of 1,000 females and barrows resulting from an intercross between a Pietrain and a Large White-Hampshire-Duroc synthetic sire line. Our QTL detection design allowed side-by-side comparison of the RYR1 and PRKAG3 mutation effects seen as QTLs when segregating at low frequencies (0.03-0.08), with independent QTL effects detected from most of the same population, excluding any carrier of these mutations. Results Large QTL effects were detected in the absence of the RYR1 and PRKGA3 mutations, accounting for 12.7% of phenotypic variation in loin colour redness CIE-a* on SSC6 and 15% of phenotypic variation in glycolytic potential on SSC1. We detected 8 significant QTLs with effects on meat quality traits and 20 significant QTLs for carcass composition and growth traits under these conditions. In control analyses including mutation carriers, RYR1 and PRKAG3 mutations were detected as QTLs, from highly significant to suggestive, and explained 53% to 5% of the phenotypic variance according to the trait. Conclusions Our results suggest that part of muscle development and backfat thickness effects commonly attributed to the RYR1 mutation may be a consequence of linkage with independent QTLs affecting those traits. The proportion of variation explained by the most significant QTLs detected in this work is close to the influence of major-effect mutations on the least affected traits, but is one order of magnitude lower than effect on variance of traits primarily affected by these causative mutations. This suggests that uncovering physiological traits directly affected by genetic polymorphisms would be an appropriate approach for further characterization of QTLs. PMID:21875434

Variation in trait trade-offs allows differentiation among predefined plant functional types: implications for predictive ecology.

PubMed

Verheijen, Lieneke M; Aerts, Rien; Bönisch, Gerhard; Kattge, Jens; Van Bodegom, Peter M

2016-01-01

Plant functional types (PFTs) aggregate the variety of plant species into a small number of functionally different classes. We examined to what extent plant traits, which reflect species' functional adaptations, can capture functional differences between predefined PFTs and which traits optimally describe these differences. We applied Gaussian kernel density estimation to determine probability density functions for individual PFTs in an n-dimensional trait space and compared predicted PFTs with observed PFTs. All possible combinations of 1-6 traits from a database with 18 different traits (total of 18 287 species) were tested. A variety of trait sets had approximately similar performance, and 4-5 traits were sufficient to classify up to 85% of the species into PFTs correctly, whereas this was 80% for a bioclimatically defined tree PFT classification. Well-performing trait sets included combinations of correlated traits that are considered functionally redundant within a single plant strategy. This analysis quantitatively demonstrates how structural differences between PFTs are reflected in functional differences described by particular traits. Differentiation between PFTs is possible despite large overlap in plant strategies and traits, showing that PFTs are differently positioned in multidimensional trait space. This study therefore provides the foundation for important applications for predictive ecology. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Neuropsychological Endophenotype Approach to Genome-wide Linkage Analysis Identifies Susceptibility Loci for ADHD on 2q21.1 and 13q12.11

PubMed Central

Rommelse, Nanda N.J.; Arias-Vásquez, Alejandro; Altink, Marieke E.; Buschgens, Cathelijne J.M.; Fliers, Ellen; Asherson, Philip; Faraone, Stephen V.; Buitelaar, Jan K.; Sergeant, Joseph A.; Oosterlaan, Jaap; Franke, Barbara

2008-01-01

ADHD linkage findings have not all been consistently replicated, suggesting that other approaches to linkage analysis in ADHD might be necessary, such as the use of (quantitative) endophenotypes (heritable traits associated with an increased risk for ADHD). Genome-wide linkage analyses were performed in the Dutch subsample of the International Multi-Center ADHD Genetics (IMAGE) study comprising 238 DSM-IV combined-type ADHD probands and their 112 affected and 195 nonaffected siblings. Eight candidate neuropsychological ADHD endophenotypes with heritabilities > 0.2 were used as quantitative traits. In addition, an overall component score of neuropsychological functioning was used. A total of 5407 autosomal single-nucleotide polymorphisms (SNPs) were used to run multipoint regression-based linkage analyses. Two significant genome-wide linkage signals were found, one for Motor Timing on chromosome 2q21.1 (LOD score: 3.944) and one for Digit Span on 13q12.11 (LOD score: 3.959). Ten suggestive linkage signals were found (LOD scores ≥ 2) on chromosomes 2p, 2q, 3p, 4q, 8q, 12p, 12q, 14q, and 17q. The suggestive linkage signal for the component score that was found at 2q14.3 (LOD score: 2.878) overlapped with the region significantly linked to Motor Timing. Endophenotype approaches may increase power to detect susceptibility loci in ADHD and possibly in other complex disorders. PMID:18599010

Evolutionary signals of symbiotic persistence in the legume–rhizobia mutualism

PubMed Central

Werner, Gijsbert D. A.; Cornwell, William K.; Cornelissen, Johannes H. C.; Kiers, E. Toby

2015-01-01

Understanding the origins and evolutionary trajectories of symbiotic partnerships remains a major challenge. Why are some symbioses lost over evolutionary time whereas others become crucial for survival? Here, we use a quantitative trait reconstruction method to characterize different evolutionary stages in the ancient symbiosis between legumes (Fabaceae) and nitrogen-fixing bacteria, asking how labile is symbiosis across different host clades. We find that more than half of the 1,195 extant nodulating legumes analyzed have a high likelihood (>95%) of being in a state of high symbiotic persistence, meaning that they show a continued capacity to form the symbiosis over evolutionary time, even though the partnership has remained facultative and is not obligate. To explore patterns associated with the likelihood of loss and retention of the N2-fixing symbiosis, we tested for correlations between symbiotic persistence and legume distribution, climate, soil and trait data. We found a strong latitudinal effect and demonstrated that low mean annual temperatures are associated with high symbiotic persistence in legumes. Although no significant correlations between soil variables and symbiotic persistence were found, nitrogen and phosphorus leaf contents were positively correlated with legumes in a state of high symbiotic persistence. This pattern suggests that highly demanding nutrient lifestyles are associated with more stable partnerships, potentially because they “lock” the hosts into symbiotic dependency. Quantitative reconstruction methods are emerging as a powerful comparative tool to study broad patterns of symbiont loss and retention across diverse partnerships. PMID:26041807

Evolutionary signals of symbiotic persistence in the legume-rhizobia mutualism.

PubMed

Werner, Gijsbert D A; Cornwell, William K; Cornelissen, Johannes H C; Kiers, E Toby

2015-08-18

Understanding the origins and evolutionary trajectories of symbiotic partnerships remains a major challenge. Why are some symbioses lost over evolutionary time whereas others become crucial for survival? Here, we use a quantitative trait reconstruction method to characterize different evolutionary stages in the ancient symbiosis between legumes (Fabaceae) and nitrogen-fixing bacteria, asking how labile is symbiosis across different host clades. We find that more than half of the 1,195 extant nodulating legumes analyzed have a high likelihood (>95%) of being in a state of high symbiotic persistence, meaning that they show a continued capacity to form the symbiosis over evolutionary time, even though the partnership has remained facultative and is not obligate. To explore patterns associated with the likelihood of loss and retention of the N2-fixing symbiosis, we tested for correlations between symbiotic persistence and legume distribution, climate, soil and trait data. We found a strong latitudinal effect and demonstrated that low mean annual temperatures are associated with high symbiotic persistence in legumes. Although no significant correlations between soil variables and symbiotic persistence were found, nitrogen and phosphorus leaf contents were positively correlated with legumes in a state of high symbiotic persistence. This pattern suggests that highly demanding nutrient lifestyles are associated with more stable partnerships, potentially because they "lock" the hosts into symbiotic dependency. Quantitative reconstruction methods are emerging as a powerful comparative tool to study broad patterns of symbiont loss and retention across diverse partnerships.

qEMF3, a novel QTL for the early-morning flowering trait from wild rice, Oryza officinalis, to mitigate heat stress damage at flowering in rice, O. sativa

PubMed Central

Hirabayashi, Hideyuki; Sasaki, Kazuhiro; Kambe, Takashi; Gannaban, Ritchel B.; Miras, Monaliza A.; Mendioro, Merlyn S.; Simon, Eliza V.; Lumanglas, Patrick D.; Fujita, Daisuke; Takemoto-Kuno, Yoko; Takeuchi, Yoshinobu; Kaji, Ryota; Kondo, Motohiko; Kobayashi, Nobuya; Ogawa, Tsugufumi; Ando, Ikuo; Jagadish, Krishna S. V.; Ishimaru, Tsutomu

2015-01-01

A decline in rice (Oryza sativa L.) production caused by heat stress is one of the biggest concerns resulting from future climate change. Rice spikelets are most susceptible to heat stress at flowering. The early-morning flowering (EMF) trait mitigates heat-induced spikelet sterility at the flowering stage by escaping heat stress during the daytime. We attempted to develop near-isogenic lines (NILs) for EMF in the indica-type genetic background by exploiting the EMF locus from wild rice, O. officinalis (CC genome). A stable quantitative trait locus (QTL) for flower opening time (FOT) was detected on chromosome 3. A QTL was designated as qEMF3 and it shifted FOT by 1.5–2.0h earlier for cv. Nanjing 11 in temperate Japan and cv. IR64 in the Philippine tropics. NILs for EMF mitigated heat-induced spikelet sterility under elevated temperature conditions completing flower opening before reaching 35°C, a general threshold value leading to spikelet sterility. Quantification of FOT of cultivars popular in the tropics and subtropics did not reveal the EMF trait in any of the cultivars tested, suggesting that qEMF3 has the potential to advance FOT of currently popular cultivars to escape heat stress at flowering under future hotter climates. This is the first report to examine rice with the EMF trait through marker-assisted breeding using wild rice as a genetic resource. PMID:25534925

pLARmEB: integration of least angle regression with empirical Bayes for multilocus genome-wide association studies.

PubMed

Zhang, J; Feng, J-Y; Ni, Y-L; Wen, Y-J; Niu, Y; Tamba, C L; Yue, C; Song, Q; Zhang, Y-M

2017-06-01

Multilocus genome-wide association studies (GWAS) have become the state-of-the-art procedure to identify quantitative trait nucleotides (QTNs) associated with complex traits. However, implementation of multilocus model in GWAS is still difficult. In this study, we integrated least angle regression with empirical Bayes to perform multilocus GWAS under polygenic background control. We used an algorithm of model transformation that whitened the covariance matrix of the polygenic matrix K and environmental noise. Markers on one chromosome were included simultaneously in a multilocus model and least angle regression was used to select the most potentially associated single-nucleotide polymorphisms (SNPs), whereas the markers on the other chromosomes were used to calculate kinship matrix as polygenic background control. The selected SNPs in multilocus model were further detected for their association with the trait by empirical Bayes and likelihood ratio test. We herein refer to this method as the pLARmEB (polygenic-background-control-based least angle regression plus empirical Bayes). Results from simulation studies showed that pLARmEB was more powerful in QTN detection and more accurate in QTN effect estimation, had less false positive rate and required less computing time than Bayesian hierarchical generalized linear model, efficient mixed model association (EMMA) and least angle regression plus empirical Bayes. pLARmEB, multilocus random-SNP-effect mixed linear model and fast multilocus random-SNP-effect EMMA methods had almost equal power of QTN detection in simulation experiments. However, only pLARmEB identified 48 previously reported genes for 7 flowering time-related traits in Arabidopsis thaliana.

Copy number variation identification and analysis of the chicken genome using a 60K SNP BeadChip.

PubMed

Rao, Y S; Li, J; Zhang, R; Lin, X R; Xu, J G; Xie, L; Xu, Z Q; Wang, L; Gan, J K; Xie, X J; He, J; Zhang, X Q

2016-08-01

Copy number variation (CNV) is an important source of genetic variation in organisms and a main factor that affects phenotypic variation. A comprehensive study of chicken CNV can provide valuable information on genetic diversity and facilitate future analyses of associations between CNV and economically important traits in chickens. In the present study, an F2 full-sib chicken population (554 individuals), established from a cross between Xinghua and White Recessive Rock chickens, was used to explore CNV in the chicken genome. Genotyping was performed using a chicken 60K SNP BeadChip. A total of 1,875 CNV were detected with the PennCNV algorithm, and the average number of CNV was 3.42 per individual. The CNV were distributed across 383 independent CNV regions (CNVR) and covered 41 megabases (3.97%) of the chicken genome. Seven CNVR in 108 individuals were validated by quantitative real-time PCR, and 81 of these individuals (75%) also were detected with the PennCNV algorithm. In total, 274 CNVR (71.54%) identified in the current study were previously reported. Of these, 147 (38.38%) were reported in at least 2 studies. Additionally, 109 of the CNVR (28.46%) discovered here are novel. A total of 709 genes within or overlapping with the CNVR was retrieved. Out of the 2,742 quantitative trait loci (QTL) collected in the chicken QTL database, 43 QTL had confidence intervals overlapping with the CNVR, and 32 CNVR encompassed one or more functional genes. The functional genes located in the CNVR are likely to be the QTG that are associated with underlying economic traits. This study considerably expands our insight into the structural variation in the genome of chickens and provides an important resource for genomic variation, especially for genomic structural variation related to economic traits in chickens. © 2016 Poultry Science Association Inc.

Comparison of genetic diversity and population structure of Pacific Coast whitebark pine across multiple markers

Treesearch

Andrew D. Bower; Bryce A. Richardson; Valerie Hipkins; Regina Rochefort; Carol Aubry

2011-01-01

Analysis of "neutral" molecular markers and "adaptive" quantitative traits are common methods of assessing genetic diversity and population structure. Molecular markers typically reflect the effects of demographic and stochastic processes but are generally assumed to not reflect natural selection. Conversely, quantitative (or "adaptive")...

Genetic variation of growth dynamics in maize (Zea mays L.) revealed through automated non-invasive phenotyping.

PubMed

Muraya, Moses M; Chu, Jianting; Zhao, Yusheng; Junker, Astrid; Klukas, Christian; Reif, Jochen C; Altmann, Thomas

2017-01-01

Hitherto, most quantitative trait loci of maize growth and biomass yield have been identified for a single time point, usually the final harvest stage. Through this approach cumulative effects are detected, without considering genetic factors causing phase-specific differences in growth rates. To assess the genetics of growth dynamics, we employed automated non-invasive phenotyping to monitor the plant sizes of 252 diverse maize inbred lines at 11 different developmental time points; 50 k SNP array genotype data were used for genome-wide association mapping and genomic selection. The heritability of biomass was estimated to be over 71%, and the average prediction accuracy amounted to 0.39. Using the individual time point data, 12 main effect marker-trait associations (MTAs) and six pairs of epistatic interactions were detected that displayed different patterns of expression at various developmental time points. A subset of them also showed significant effects on relative growth rates in different intervals. The detected MTAs jointly explained up to 12% of the total phenotypic variation, decreasing with developmental progression. Using non-parametric functional mapping and multivariate mapping approaches, four additional marker loci affecting growth dynamics were detected. Our results demonstrate that plant biomass accumulation is a complex trait governed by many small effect loci, most of which act at certain restricted developmental phases. This highlights the need for investigation of stage-specific growth affecting genes to elucidate important processes operating at different developmental phases. © 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd.

Identification of quantitative trait loci controlling root and shoot traits associated to drought tolerance in a lentil (Lens culinaris Medik.) recombinant inbred line population

USDA-ARS?s Scientific Manuscript database

Drought is one of the major abiotic stresses limiting lentil productivity in rainfed production systems. Specific rooting patterns can be associated with drought avoidance mechanisms that can be used in lentil breeding. In all, 252 co-dominant and dominant markers were used for genetic linkage map c...

Clarifying sub-genomic positions of QTLs for flowering habit and fruit quality in U.S. strawberry (Fragaria ×ananassa) breeding populations using pedigree-based QTL analysis

USDA-ARS?s Scientific Manuscript database

Strawberry (Fragaria ×ananassa) is consumed worldwide for its flavor and nutritional health benefits. Several quantitative trait loci (QTL) were detected in the last two decades for fruit quality and flowering traits using low-density genetic maps. Recent discoveries in allo-octoploid strawberry gen...

Education on an Island: Oklahoma Correctional Educators' Views of Internal Teacher Traits and Successful Learning Environments on Incarcerated Adult Students in an Institutional Setting

ERIC Educational Resources Information Center

Ely, Jeana Dawn

2011-01-01

Scope and method of study. This inquiry, using survey and interview techniques, demonstrated both quantitative and qualitative research methodologies. In this study, effective teacher traits related to successful classroom structure in the correctional environment for adult students with a wide variety of issues, problems and learning difficulties…

Plasticity in physiological traits in conifers: implications for response to climate change in the western U.S

Treesearch

NE Grulke

2010-01-01

Population variation in ecophysiological traits of four co-occurring montane conifers was measured on a large latitudinal gradient to quantitatively assess their potential for response to environmental change. White fir (Abies concolor) had the highest variability, gross photosynthetic rate (Pg), and foliar carbon (C) and nitrogen (N) content. Despite low water use...

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

USDA-ARS?s Scientific Manuscript database

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

Situated Willingness to Communicate in an L2: Interplay of Individual Characteristics and Context

ERIC Educational Resources Information Center

Yashima, Tomoko; MacIntyre, Peter D.; Ikeda, Maiko

2018-01-01

Recently, situated willingness to communicate (WTC) has received increasing research attention in addition to traditional quantitative studies of trait-like WTC. This article is an addition to the former but unique in two ways. First, it investigates both trait and state WTC in a classroom context and explores ways to combine the two to reach a…

Identifying haplotypes for flowering and QTLs for fruit quality in the RosBREED Michigan and Oregon strawberry (Fragaria ×ananassa) breeding sets using pedigree-based analysis [abstract

USDA-ARS?s Scientific Manuscript database

Strawberry (Fragaria ×ananassa) is consumed for its flavor and health benefits. Over the last two decades, several quantitative trait loci (QTL) analysis studies for consumer traits were conducted using low-density genetic maps. The previous studies utilized low-throughput genotyping methodologies. ...

Identification of Quantitative Trait Loci Conditioning the Main Biomass Yield Components and Resistance to Melampsora spp. in Salix viminalis × Salix schwerinii Hybrids

PubMed Central

Sulima, Paweł; Przyborowski, Jerzy A.; Kuszewska, Anna; Załuski, Dariusz; Jędryczka, Małgorzata; Irzykowski, Witold

2017-01-01

The biomass of Salix viminalis is the most highly valued source of green energy, followed by S. schwerinii, S. dasyclados and other species. Significant variability in productivity and leaf rust resistance are noted both within and among willow species, which creates new opportunities for improving willow yield parameters through selection of desirable recombinants supported with molecular markers. The aim of this study was to identify quantitative trait loci (QTLs) linked with biomass yield-related traits and the resistance/susceptibility of Salix mapping population to leaf rust. The experimental material comprised a mapping population developed based on S. viminalis × S. schwerinii hybrids. Phenotyping was performed on plants grown in a field experiment that had a balanced incomplete block design with 10 replications. Based on a genetic map, 11 QTLs were identified for plant height, 9 for shoot diameter, 3 for number of shoots and 11 for resistance/susceptibility to leaf rust. The QTLs identified in our study explained 3%–16% of variability in the analyzed traits. Our findings make significant contributions to the development of willow breeding programs and research into shrubby willow crops grown for energy. PMID:28327519

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

PubMed

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

2011-01-01

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

The relationship between the UPPS-P impulsive personality traits and substance use psychotherapy outcomes: A meta-analysis.

PubMed

Hershberger, Alexandra R; Um, Miji; Cyders, Melissa A

2017-09-01

Although impulsive personality traits have been well implicated in substance use disorder (SUD) risk, little work has established how specific impulsive personality traits influence and are influenced by SUD psychotherapy outcomes. The purpose of this meta-analysis was to quantitatively review existing work to examine 1) how impulsive personality traits affect SUD psychotherapy outcomes and 2) reductions in impulsive personality traits during SUD psychotherapy. Studies were identified by conducting a comprehensive review of the literature. For aim one (k=6), significant effects were found for lack of premeditation (g=0.60, SE=0.30, 95% CI 0.01-1.20; z=1.99, p=0.05) and negative urgency (g=0.55, SE=0.17, 95% CI 0.22-0.88, z=3.30, p=0.001), with trait scores related to poorer SUD psychotherapy outcomes. For aim two (k=10), decreases in sensation seeking (g=-0.10, SE=0.05, 95% CI -0.20 to 0.004; z=-1.88, p=0.02) and negative urgency (g=-0.25, SE=0.14, 95% CI -0.53 to 0.03; z=-1.75, p=0.03) during SUD psychotherapy were significant. Overall, our quantitative synthesis suggests that lack of premeditation and negative urgency are related to poorer SUD psychotherapy outcomes. Although negative urgency and sensation seeking are decreasing during SUD psychotherapy, the magnitude of the change is quite small. Overall, we suggest that the measurement and targeting of impulsive personality traits in psychotherapy has strong potential to improve clinical outcomes across SUDs and a wide range of clinical problems and disorders. Copyright © 2017 Elsevier B.V. All rights reserved.

Estimating rice yield related traits and quantitative trait loci analysis under different nitrogen treatments using a simple tower-based field phenotyping system with modified single-lens reflex cameras

NASA Astrophysics Data System (ADS)

Naito, Hiroki; Ogawa, Satoshi; Valencia, Milton Orlando; Mohri, Hiroki; Urano, Yutaka; Hosoi, Fumiki; Shimizu, Yo; Chavez, Alba Lucia; Ishitani, Manabu; Selvaraj, Michael Gomez; Omasa, Kenji

2017-03-01

Application of field based high-throughput phenotyping (FB-HTP) methods for monitoring plant performance in real field conditions has a high potential to accelerate the breeding process. In this paper, we discuss the use of a simple tower based remote sensing platform using modified single-lens reflex cameras for phenotyping yield traits in rice under different nitrogen (N) treatments over three years. This tower based phenotyping platform has the advantages of simplicity, ease and stability in terms of introduction, maintenance and continual operation under field conditions. Out of six phenological stages of rice analyzed, the flowering stage was the most useful in the estimation of yield performance under field conditions. We found a high correlation between several vegetation indices (simple ratio (SR), normalized difference vegetation index (NDVI), transformed vegetation index (TVI), corrected transformed vegetation index (CTVI), soil-adjusted vegetation index (SAVI) and modified soil-adjusted vegetation index (MSAVI)) and multiple yield traits (panicle number, grain weight and shoot biomass) across a three trials. Among all of the indices studied, SR exhibited the best performance in regards to the estimation of grain weight (R2 = 0.80). Under our tower-based field phenotyping system (TBFPS), we identified quantitative trait loci (QTL) for yield related traits using a mapping population of chromosome segment substitution lines (CSSLs) and a single nucleotide polymorphism data set. Our findings suggest the TBFPS can be useful for the estimation of yield performance during early crop development. This can be a major opportunity for rice breeders whom desire high throughput phenotypic selection for yield performance traits.

Selection on domestication traits and quantitative trait loci in crop-wild sunflower hybrids.

PubMed

Baack, Eric J; Sapir, Yuval; Chapman, Mark A; Burke, John M; Rieseberg, Loren H

2008-01-01

The strength and extent of gene flow from crops into wild populations depends, in part, on the fitness of the crop alleles, as well as that of alleles at linked loci. Interest in crop-wild gene flow has increased with the advent of transgenic plants, but nontransgenic crop-wild hybrids can provide case studies to understand the factors influencing introgression, provided that the genetic architecture and the fitness effects of loci are known. This study used recombinant inbred lines (RILs) generated from a cross between crop and wild sunflowers to assess selection on domestication traits and quantitative trait loci (QTL) in two contrasting environments, in Indiana and Nebraska, USA. Only a small fraction of plants (9%) produced seed in Nebraska, due to adverse weather conditions, while the majority of plants (79%) in Indiana reproduced. Phenotypic selection analysis found that a mixture of crop and wild traits were favoured in Indiana (i.e. had significant selection gradients), including larger leaves, increased floral longevity, larger disk diameter, reduced ray flower size and smaller achene (seed) mass. Selection favouring early flowering was detected in Nebraska. QTLs for fitness were found at the end of linkage groups six (LG6) and nine (LG9) in both field sites, each explaining 11-12% of the total variation. Crop alleles were favoured on LG9, but wild alleles were favoured on LG6. QTLs for numerous domestication traits overlapped with the fitness QTLs, including flowering date, achene mass, head number, and disk diameter. It remains to be seen if these QTL clusters are the product of multiple linked genes, or individual genes with pleiotropic effects. These results indicate that crop trait values and alleles may sometimes be favoured in a noncrop environment and across broad geographical regions.

Mapping Quantitative Trait Loci (QTL) in sheep. III. QTL for carcass composition traits derived from CT scans and aligned with a meta-assembly for sheep and cattle carcass QTL.

PubMed

Cavanagh, Colin R; Jonas, Elisabeth; Hobbs, Matthew; Thomson, Peter C; Tammen, Imke; Raadsma, Herman W

2010-09-16

An (Awassi × Merino) × Merino single-sire backcross family with 165 male offspring was used to map quantitative trait loci (QTL) for body composition traits on a framework map of 189 microsatellite loci across all autosomes. Two cohorts were created from the experimental progeny to represent alternative maturity classes for body composition assessment. Animals were raised under paddock conditions prior to entering the feedlot for a 90-day fattening phase. Body composition traits were derived in vivo at the end of the experiment prior to slaughter at 2 (cohort 1) and 3.5 (cohort 2) years of age, using computed tomography. Image analysis was used to gain accurate predictions for 13 traits describing major fat depots, lean muscle, bone, body proportions and body weight which were used for single- and two-QTL mapping analysis. Using a maximum-likelihood approach, three highly significant (LOD ≥ 3), 15 significant (LOD ≥ 2), and 11 suggestive QTL (1.7 ≤ LOD < 2) were detected on eleven chromosomes. Regression analysis confirmed 28 of these QTL and an additional 17 suggestive (P < 0.1) and two significant (P < 0.05) QTL were identified using this method. QTL with pleiotropic effects for two or more tissues were identified on chromosomes 1, 6, 10, 14, 16 and 23. No tissue-specific QTL were identified.A meta-assembly of ovine QTL for carcass traits from this study and public domain sources was performed and compared with a corresponding bovine meta-assembly. The assembly demonstrated QTL with effects on carcass composition in homologous regions on OAR1, 2, 6 and 21.

Comparative quantitative trait locus mapping of maize flowering-related traits in an F2:3 and recombinant inbred line population.

PubMed

Liu, Y H; Yi, Q; Hou, X B; Zhang, X G; Zhang, J J; Liu, H M; Hu, Y F; Huang, Y B

2016-06-30

Flowering-related traits in maize are affected by complex factors and are important for the improvement of cropping systems in the maize zone. Quantitative trait loci (QTLs) detected using different materials and methods usually vary. In the present study, 266 maize (Zea mays) F2:3 families and 301 recombinant inbred lines (RIL) derived from a cross between 08-641 (founding parent from southeast China) and Ye478 (founding parent from China) were evaluated for four flowering-related traits, including days to tasseling (DTT), days to pollen shedding (DPS), days to silking (DTS), and anthesis-silking interval. Sixty-six QTLs controlling the target traits were detected in the F2:3 and RIL populations via single environment analysis and joint analysis across all environments (JAAE). The QTLs explained 0.8-13.47% of the phenotypic variation, with 12 QTLs explaining more than 10%. The results of meta-QTL (MQTL) analysis indicated that 41 QTLs could be integrated into 14 MQTLs. One MQTL included 2.9 QTLs, ranging from two to ten QTLs for one to three traits. QTLs, including MQTL1-1 and MQTL9-1, were detected across the F2:3 and RIL populations via SAE and JAAE. Among the MQTLs, nine QTLs were integrated into MQTL9-1 and affected DTT, DPS, and DTS, with the favored allele being derived from 08-641. MQTL3-2 showed high phenotypic variation and was suitable for fine mapping to determine the genetic mechanisms of flowering. MQTL3-2 could be applied to improve inbred lines using marker-assisted selection.

Effect prediction of identified SNPs linked to fruit quality and chilling injury in peach [Prunus persica (L.) Batsch].

PubMed

Martínez-García, Pedro J; Fresnedo-Ramírez, Jonathan; Parfitt, Dan E; Gradziel, Thomas M; Crisosto, Carlos H

2013-01-01

Single nucleotide polymorphisms (SNPs) are a fundamental source of genomic variation. Large SNP panels have been developed for Prunus species. Fruit quality traits are essential peach breeding program objectives since they determine consumer acceptance, fruit consumption, industry trends and cultivar adoption. For many cultivars, these traits are negatively impacted by cold storage, used to extend fruit market life. The major symptoms of chilling injury are lack of flavor, off flavor, mealiness, flesh browning, and flesh bleeding. A set of 1,109 SNPs was mapped previously and 67 were linked with these complex traits. The prediction of the effects associated with these SNPs on downstream products from the 'peach v1.0' genome sequence was carried out. A total of 2,163 effects were detected, 282 effects (non-synonymous, synonymous or stop codon gained) were located in exonic regions (13.04 %) and 294 placed in intronic regions (13.59 %). An extended list of genes and proteins that could be related to these traits was developed. Two SNP markers that explain a high percentage of the observed phenotypic variance, UCD_SNP_1084 and UCD_SNP_46, are associated with zinc finger (C3HC4-type RING finger) family protein and AOX1A (alternative oxidase 1a) protein groups, respectively. In addition, phenotypic variation suggests that the observed polymorphism for SNP UCD_SNP_1084 [A/G] mutation could be a candidate quantitative trait nucleotide affecting quantitative trait loci for mealiness. The interaction and expression of affected proteins could explain the variation observed in each individual and facilitate understanding of gene regulatory networks for fruit quality traits in peach.

Evaluative judgments are based on evaluative information: Evidence against meaning change in evaluative context effects.

PubMed

Kaplan, M F

1975-07-01

Trait adjectives commonly employed in person perception studies have both evaluative and denotative meanings. Evaluative ratings of single traits shift with variations in the context of other traits ascribed to the stimulus person; the extent to which denotative changes underlie these evaluative context effects has been a theoretical controversy. In the first experiment, it was shown that context effects on quantitative ratings of denotation can be largely accounted for by evaluative halo effects. In the second experiment, increasing the denotative relatedness of context traits to the test trait didnot increase the effect of the context. Only the evaluative meaning of the context affected evaluation of the rated test trait. These studies suggest that the denotative relationship between a test adjective and its context has little influence on context effects in person perception, and that denotative meaning changes do not mediate context effects. Instead, evaluative judgments appear to be based on evaluative meaning.

Genetic and genomic analyses for economically important traits and their applications in molecular breeding of cultured fish.

PubMed

Tong, JinGou; Sun, XiaoWen

2015-02-01

The traits of cultured fish must continually be genetically improved to supply high-quality animal protein for human consumption. Economically important fish traits are controlled by multiple gene quantitative trait loci (QTL), most of which have minor effects, but a few genes may have major effects useful for molecular breeding. In this review, we chose relevant studies on some of the most intensively cultured fish and concisely summarize progress on identifying and verifying QTLs for such traits as growth, disease and stress resistance and sex in recent decades. The potential applications of these major-effect genes and their associated markers in marker-assisted selection and molecular breeding, as well as future research directions are also discussed. These genetic and genomic analyses will be valuable for elucidating the mechanisms modulating economically important traits and to establish more effective molecular breeding techniques in fish.

Comparative mapping of quantitative trait loci associated with waterlogging tolerance in barley (Hordeum vulgare L.).

PubMed

Li, Haobing; Vaillancourt, René; Mendham, Neville; Zhou, Meixue

2008-08-27

Resistance to soil waterlogging stress is an important plant breeding objective in high rainfall or poorly drained areas across many countries in the world. The present study was conducted to identify quantitative trait loci (QTLs) associated with waterlogging tolerance (e.g. leaf chlorosis, plant survival and biomass reduction) in barley and compare the QTLs identified across two seasons and in two different populations using a composite map constructed with SSRs, RFLP and Diversity Array Technology (DArT) markers. Twenty QTLs for waterlogging tolerance related traits were found in the two barley double haploid (DH) populations. Several of these QTLs were validated through replication of experiments across seasons or by co-location across populations. Some of these QTLs affected multiple waterlogging tolerance related traits, for example, QTL Qwt4-1 contributed not only to reducing barley leaf chlorosis, but also increasing plant biomass under waterlogging stress, whereas other QTLs controlled both leaf chlorosis and plant survival. Improving waterlogging tolerance in barley is still at an early stage compared with other traits. QTLs identified in this study have made it possible to use marker assisted selection (MAS) in combination with traditional field selection to significantly enhance barley breeding for waterlogging tolerance. There may be some degree of homoeologous relationship between QTLs controlling barley waterlogging tolerance and that in other crops as discussed in this study.

Comparative mapping of quantitative trait loci for tassel-related traits of maize in F2:3 and RIL populations.

PubMed

Yi, Qiang; Liu, Yinghong; Zhang, Xiangge; Hou, Xianbin; Zhang, Junjie; Liu, Hanmei; Hu, Yufeng; Yu, Guowu; Huang, Yubi

2018-03-01

Tassel architecture is an important trait in maize breeding and hybrid seed production. In this study, we investigated total tassel length (TTL) and tassel branch number (TBN) in 266 F 2:3 families across six environments and in 301 recombinant inbred lines (RILs) across three environments, where all the plants were derived from a cross between 08-641 and Ye478. We compared the genetic architecture of the two traits across two generations through combined analysis. In total, 27 quantitative trait loci (QTLs) (15 in F 2:3 ; 16 in RIL), two QTL × environment interactions (both in F 2:3 ), 11 pairs of epistatic interactions (seven in F 2:3 ; four in RIL) and four stable QTLs in both the F 2:3 and RILs were detected. The RIL population had higher detection power than the F 2:3 population. Nevertheless, QTL × environment interactions and epistatic interactions could be more easily detected in the F 2:3 population than in the RILs. Overall, the QTL mapping results in the F 2:3 and RILs were greatly influenced by genetic generations and environments. Finally, fine mapping for a novel and major QTL, qTTL-2-3 (bin 2.07), which accounted for over 8.49% of the phenotypic variation across different environments and generations, could be useful in marker-assisted breeding.

Rootstock control of scion transpiration and its acclimation to water deficit are controlled by different genes.

PubMed

Marguerit, Elisa; Brendel, Oliver; Lebon, Eric; Van Leeuwen, Cornelis; Ollat, Nathalie

2012-04-01

The stomatal control of transpiration is one of the major strategies by which plants cope with water stress. Here, we investigated the genetic architecture of the rootstock control of scion transpiration-related traits over a period of 3 yr. The rootstocks studied were full sibs from a controlled interspecific cross (Vitis vinifera cv. Cabernet Sauvignon × Vitis riparia cv. Gloire de Montpellier), onto which we grafted a single scion genotype. After 10 d without stress, the water supply was progressively limited over a period of 10 d, and a stable water deficit was then applied for 15 d. Transpiration rate was estimated daily and a mathematical curve was fitted to its response to water deficit intensity. We also determined δ(13) C values in leaves, transpiration efficiency and water extraction capacity. These traits were then analysed in a multienvironment (year and water status) quantitative trait locus (QTL) analysis. Quantitative trait loci, independent of year and water status, were detected for each trait. One genomic region was specifically implicated in the acclimation of scion transpiration induced by the rootstock. The QTLs identified colocalized with genes involved in water deficit responses, such as those relating to ABA and hydraulic regulation. Scion transpiration rate and its acclimation to water deficit are thus controlled genetically by the rootstock, through different genetic architectures. © 2012 INRA. New Phytologist © 2012 New Phytologist Trust.

Trait differences between naturalized and invasive plant species independent of residence time and phylogeny.

PubMed

Gallagher, R V; Randall, R P; Leishman, M R

2015-04-01

The ability to predict which alien plants will transition from naturalized to invasive prior to their introduction to novel regions is a key goal for conservation and has the potential to increase the efficacy of weed risk assessment (WRA). However, multiple factors contribute to plant invasion success (e.g., functional traits, range characteristics, residence time, phylogeny), and they all must be taken into account simultaneously in order to identify meaningful correlates of invasion success. We compiled 146 pairs of phylogenetically paired (congeneric) naturalized and invasive plant species in Australia with similar minimum residence times (i.e., time since introduction in years). These pairs were used to test for differences in 5 functional traits (flowering duration, leaf size, maximum height, specific leaf area [SLA], seed mass) and 3 characteristics of species' native ranges (biome occupancy, mean annual temperature, and rainfall breadth) between naturalized and invasive species. Invasive species, on average, had larger SLA, longer flowering periods, and were taller than their congeneric naturalized relatives. Invaders also exhibited greater tolerance for different environmental conditions in the native range, where they occupied more biomes and a wider breadth of rainfall and temperature conditions than naturalized congeners. However, neither seed mass nor leaf size differed between pairs of naturalized and invasive species. A key finding was the role of SLA in distinguishing between naturalized and invasive pairs. Species with high SLA values were typically associated with faster growth rates, more rapid turnover of leaf material, and shorter lifespans than those species with low SLA. This suite of characteristics may contribute to the ability of a species to transition from naturalized to invasive across a wide range of environmental contexts and disturbance regimes. Our findings will help in the refinement of WRA protocols, and we advocate the inclusion of quantitative traits, in particular SLA, into the WRA schemes. © 2014 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Systems genetics approaches to understand complex traits

PubMed Central

Civelek, Mete; Lusis, Aldons J.

2014-01-01

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

Testing natural selection vs. genetic drift in phenotypic evolution using quantitative trait locus data.

PubMed Central

Orr, H A

1998-01-01

Evolutionary biologists have long sought a way to determine whether a phenotypic difference between two taxa was caused by natural selection or random genetic drift. Here I argue that data from quantitative trait locus (QTL) analyses can be used to test the null hypothesis of neutral phenotypic evolution. I propose a sign test that compares the observed number of plus and minus alleles in the "high line" with that expected under neutrality, conditioning on the known phenotypic difference between the taxa. Rejection of the null hypothesis implies a role for directional natural selection. This test is applicable to any character in any organism in which QTL analysis can be performed. PMID:9691061

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.

Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

PubMed Central

Tanger, Paul; Klassen, Stephen; Mojica, Julius P.; Lovell, John T.; Moyers, Brook T.; Baraoidan, Marietta; Naredo, Maria Elizabeth B.; McNally, Kenneth L.; Poland, Jesse; Bush, Daniel R.; Leung, Hei; Leach, Jan E.; McKay, John K.

2017-01-01

To ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. Here we demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor-intensive measures of flowering time, height, biomass, grain yield, and harvest index. Genetic mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution. PMID:28220807

Joint Transcriptomic and Metabolomic Analyses Reveal Changes in the Primary Metabolism and Imbalances in the Subgenome Orchestration in the Bread Wheat Molecular Response to Fusarium graminearum.

PubMed

Nussbaumer, Thomas; Warth, Benedikt; Sharma, Sapna; Ametz, Christian; Bueschl, Christoph; Parich, Alexandra; Pfeifer, Matthias; Siegwart, Gerald; Steiner, Barbara; Lemmens, Marc; Schuhmacher, Rainer; Buerstmayr, Hermann; Mayer, Klaus F X; Kugler, Karl G; Schweiger, Wolfgang

2015-10-04

Fusarium head blight is a prevalent disease of bread wheat (Triticum aestivum L.), which leads to considerable losses in yield and quality. Quantitative resistance to the causative fungus Fusarium graminearum is poorly understood. We integrated transcriptomics and metabolomics data to dissect the molecular response to the fungus and its main virulence factor, the toxin deoxynivalenol in near-isogenic lines segregating for two resistance quantitative trait loci, Fhb1 and Qfhs.ifa-5A. The data sets portrait rearrangements in the primary metabolism and the translational machinery to counter the fungus and the effects of the toxin and highlight distinct changes in the metabolism of glutamate in lines carrying Qfhs.ifa-5A. These observations are possibly due to the activity of two amino acid permeases located in the quantitative trait locus confidence interval, which may contribute to increased pathogen endurance. Mapping to the highly resolved region of Fhb1 reduced the list of candidates to few genes that are specifically expressed in presence of the quantitative trait loci and in response to the pathogen, which include a receptor-like protein kinase, a protein kinase, and an E3 ubiquitin-protein ligase. On a genome-scale level, the individual subgenomes of hexaploid wheat contribute differentially to defense. In particular, the D subgenome exhibited a pronounced response to the pathogen and contributed significantly to the overall defense response. Copyright © 2015 Nussbaumer et al.

An assessment of the reliability of quantitative genetics estimates in study systems with high rate of extra-pair reproduction and low recruitment.

PubMed

Bourret, A; Garant, D

2017-03-01

Quantitative genetics approaches, and particularly animal models, are widely used to assess the genetic (co)variance of key fitness related traits and infer adaptive potential of wild populations. Despite the importance of precision and accuracy of genetic variance estimates and their potential sensitivity to various ecological and population specific factors, their reliability is rarely tested explicitly. Here, we used simulations and empirical data collected from an 11-year study on tree swallow (Tachycineta bicolor), a species showing a high rate of extra-pair paternity and a low recruitment rate, to assess the importance of identity errors, structure and size of the pedigree on quantitative genetic estimates in our dataset. Our simulations revealed an important lack of precision in heritability and genetic-correlation estimates for most traits, a low power to detect significant effects and important identifiability problems. We also observed a large bias in heritability estimates when using the social pedigree instead of the genetic one (deflated heritabilities) or when not accounting for an important cause of resemblance among individuals (for example, permanent environment or brood effect) in model parameterizations for some traits (inflated heritabilities). We discuss the causes underlying the low reliability observed here and why they are also likely to occur in other study systems. Altogether, our results re-emphasize the difficulties of generalizing quantitative genetic estimates reliably from one study system to another and the importance of reporting simulation analyses to evaluate these important issues.

A compilation of quantitative functional traits for marine and freshwater crustacean zooplankton.

PubMed

Hébert, Marie-Pier; Beisner, Beatrix E; Maranger, Roxane

2016-04-01

This data compilation synthesizes 8609 individual observations and ranges of 13 traits from 201 freshwater and 191 marine crustacean taxa belonging to either Copepoda or Cladocera, two important zooplankton groups across all major aquatic habitats. Most data were gathered from the literature, with the balance being provided by zooplankton ecologists. With the aim of more fully assessing zooplankton effects on elemental processes such as nitrogen (N), phosphorus (P) and carbon (C) stocks and fluxes in aquatic ecosystems, this data set provides information on the following traits: body size (length and mass), trophic group, elemental and biochemical corporal composition (N, P, C, lipid and protein content), respiration rates, N- and P-excretion rates, as well as stoichiometric ratios. Although relationships for zooplankton metabolism as a function of body mass or requirements have been explored in the past three decades, data have not been systematically compiled nor examined from an integrative and large-scale perspective across crustacean taxa and habitat types. While this contribution likely represents the most comprehensive assembly of traits for both marine and freshwater species, this data set is not exhaustive either. As a result, this compilation also identifies knowledge gaps: a fact that should encourage researchers to disclose information they may have to help complete such databases. This trait matrix is made available for the first time in this data paper; prior to its release, the data set has been analyzed in a meta-analysis published as a companion paper. This data set should prove extremely valuable for aquatic ecologists for trait-based characterization of plankton community structure as well as biogeochemical modeling. These data are also well-suited for deriving shortcut relationships that predict more difficult to measure trait values, most of which can be directly related to ecosystem properties (i.e., effect traits), from simpler traits (e.g., body size), and for exploring patterns of trait variation within and amongst taxonomic units or ecosystem types. Overall, this data set is likely to provide new insights into the functional structure of zooplankton communities and increase our mechanistic understanding of the influence of these pivotal organisms on aquatic ecosystems. © 2016 by the Ecological Society of America.

Identification of QTL and Qualitative Trait Loci for Agronomic Traits Using SNP Markers in the Adzuki Bean.

PubMed

Li, Yuan; Yang, Kai; Yang, Wei; Chu, Liwei; Chen, Chunhai; Zhao, Bo; Li, Yisong; Jian, Jianbo; Yin, Zhichao; Wang, Tianqi; Wan, Ping

2017-01-01

The adzuki bean ( Vigna angularis ) is an important grain legume. Fine mapping of quantitative trait loci (QTL) and qualitative trait genes plays an important role in gene cloning, molecular-marker-assisted selection (MAS), and trait improvement. However, the genetic control of agronomic traits in the adzuki bean remains poorly understood. Single-nucleotide polymorphisms (SNPs) are invaluable in the construction of high-density genetic maps. We mapped 26 agronomic QTLs and five qualitative trait genes related to pigmentation using 1,571 polymorphic SNP markers from the adzuki bean genome via restriction-site-associated DNA sequencing of 150 members of an F 2 population derived from a cross between cultivated and wild adzuki beans. We mapped 11 QTLs for flowering time and pod maturity on chromosomes 4, 7, and 10. Six 100-seed weight (SD100WT) QTLs were detected. Two major flowering time QTLs were located on chromosome 4, firstly VaFld4.1 (PEVs 71.3%), co-segregating with SNP marker s690-144110, and VaFld4.2 (PEVs 67.6%) at a 0.974 cM genetic distance from the SNP marker s165-116310. Three QTLs for seed number per pod ( Snp3.1, Snp3.2 , and Snp4.1 ) were mapped on chromosomes 3 and 4. One QTL VaSdt4.1 of seed thickness (SDT) and three QTLs for branch number on the main stem were detected on chromosome 4. QTLs for maximum leaf width (LFMW) and stem internode length were mapped to chromosomes 2 and 9, respectively. Trait genes controlling the color of the seed coat, pod, stem and flower were mapped to chromosomes 3 and 1. Three candidate genes, VaAGL, VaPhyE , and VaAP2 , were identified for flowering time and pod maturity. VaAGL encodes an agamous-like MADS-box protein of 379 amino acids. VaPhyE encodes a phytochrome E protein of 1,121 amino acids. Four phytochrome genes ( VaPhyA1, VaPhyA2, VaPhyB , and VaPhyE ) were identified in the adzuki bean genome. We found candidate genes VaAP2/ERF.81 and VaAP2/ERF.82 of SD100WT, VaAP2-s4 of SDT, and VaAP2/ERF.86 of LFMW. A candidate gene VaUGT related to black seed coat color was identified. These mapped QTL and qualitative trait genes provide information helpful for future adzuki bean candidate gene cloning and MAS breeding to improve cultivars with desirable growth periods, yields, and seed coat color types.

A trait database for marine copepods

NASA Astrophysics Data System (ADS)

Brun, Philipp; Payne, Mark R.; Kiørboe, Thomas

2017-02-01

The trait-based approach is gaining increasing popularity in marine plankton ecology but the field urgently needs more and easier accessible trait data to advance. We compiled trait information on marine pelagic copepods, a major group of zooplankton, from the published literature and from experts and organized the data into a structured database. We collected 9306 records for 14 functional traits. Particular attention was given to body size, feeding mode, egg size, spawning strategy, respiration rate, and myelination (presence of nerve sheathing). Most records were reported at the species level, but some phylogenetically conserved traits, such as myelination, were reported at higher taxonomic levels, allowing the entire diversity of around 10 800 recognized marine copepod species to be covered with a few records. Aside from myelination, data coverage was highest for spawning strategy and body size, while information was more limited for quantitative traits related to reproduction and physiology. The database may be used to investigate relationships between traits, to produce trait biogeographies, or to inform and validate trait-based marine ecosystem models. The data can be downloaded from PANGAEA, doi:10.1594/PANGAEA.862968.

An Improved Method for Measuring Quantitative Resistance to the Wheat Pathogen Zymoseptoria tritici Using High-Throughput Automated Image Analysis.

PubMed

Stewart, Ethan L; Hagerty, Christina H; Mikaberidze, Alexey; Mundt, Christopher C; Zhong, Ziming; McDonald, Bruce A

2016-07-01

Zymoseptoria tritici causes Septoria tritici blotch (STB) on wheat. An improved method of quantifying STB symptoms was developed based on automated analysis of diseased leaf images made using a flatbed scanner. Naturally infected leaves (n = 949) sampled from fungicide-treated field plots comprising 39 wheat cultivars grown in Switzerland and 9 recombinant inbred lines (RIL) grown in Oregon were included in these analyses. Measures of quantitative resistance were percent leaf area covered by lesions, pycnidia size and gray value, and pycnidia density per leaf and lesion. These measures were obtained automatically with a batch-processing macro utilizing the image-processing software ImageJ. All phenotypes in both locations showed a continuous distribution, as expected for a quantitative trait. The trait distributions at both sites were largely overlapping even though the field and host environments were quite different. Cultivars and RILs could be assigned to two or more statistically different groups for each measured phenotype. Traditional visual assessments of field resistance were highly correlated with quantitative resistance measures based on image analysis for the Oregon RILs. These results show that automated image analysis provides a promising tool for assessing quantitative resistance to Z. tritici under field conditions.

Plasma cytokine profiling in sibling pairs discordant for autism spectrum disorder

PubMed Central

2013-01-01

Objective Converging lines of evidence point to the existence of immune dysfunction in autism spectrum disorder (ASD), which could directly affect several key neurodevelopmental processes. Previous studies have shown higher cytokine levels in patients with autism compared with matched controls or subjects with other developmental disorders. In the current study, we used plasma-cytokine profiling for 25 discordant sibling pairs to evaluate whether these alterations occur within families with ASD. Methods Plasma-cytokine profiling was conducted using an array-based multiplex sandwich ELISA for simultaneous quantitative measurement of 40 unique targets. We also analyzed the correlations between cytokine levels and clinically relevant quantitative traits (Vineland Adaptive Behavior Scale in Autism (VABS) composite score, Social Responsiveness Scale (SRS) total T score, head circumference, and full intelligence quotient (IQ)). In addition, because of the high phenotypic heterogeneity of ASD, we defined four subgroups of subjects (those who were non-verbal, those with gastrointestinal issues, those with regressive autism, and those with a history of allergies), which encompass common and/or recurrent endophenotypes in ASD, and tested the cytokine levels in each group. Results None of the measured parameters showed significant differences between children with ASD and their related typically developing siblings. However, specific target levels did correlate with quantitative clinical traits, and these were significantly different when the ASD subgroups were analyzed. It is notable that these differences seem to be attributable to a predisposing immunogenetic background, as no other significant differences were noticed between discordant sibling pairs. Interleukin-1β appears to be the cytokine most involved in quantitative traits and clinical subgroups of ASD. Conclusions In the present study, we found a lack of significant differences in plasma-cytokine levels between children with ASD and in their related non-autistic siblings. Thus, our results support the evidence that the immune profiles of children with autism do not differ from their typically developing siblings. However, the significant association of cytokine levels with the quantitative traits and the clinical subgroups analyzed suggests that altered immune responses may affect core feature of ASD. PMID:23497090

Wine yeast phenomics: A standardized fermentation method for assessing quantitative traits of Saccharomyces cerevisiae strains in enological conditions.

PubMed

Peltier, Emilien; Bernard, Margaux; Trujillo, Marine; Prodhomme, Duyên; Barbe, Jean-Christophe; Gibon, Yves; Marullo, Philippe

2018-01-01

This work describes the set up of a small scale fermentation methodology for measuring quantitative traits of hundreds of samples in an enological context. By using standardized screw cap vessels, the alcoholic fermentation kinetics of Saccharomyces cerevisiae strains were measured by following their weight loss over the time. This dispositive was coupled with robotized enzymatic assays for measuring metabolites of enological interest in natural grape juices. Despite the small volume used, kinetic parameters and fermentation end products measured are similar with those observed in larger scale vats. The vessel used also offers the possibility to assay 32 volatiles compounds using a headspace solid-phase micro-extraction coupled to gas chromatography and mass spectrometry. The vessel shaking applied strongly impacted most of the phenotypes investigated due to oxygen transfer occuring in the first hours of the alcoholic fermentation. The impact of grape must and micro-oxygenation was investigated illustrating some relevant genetic x environmental interactions. By phenotyping a wide panel of commercial wine starters in five grape juices, broad phenotypic correlations between kinetics and metabolic end products were evidentiated. Moreover, a multivariate analysis illustrates that some grape musts are more able than others to discriminate commercial strains since some are less robust to environmental changes.

Whole Genome Re-Sequencing Identifies a Quantitative Trait Locus Repressing Carbon Reserve Accumulation during Optimal Growth in Chlamydomonas reinhardtii

PubMed Central

Goold, Hugh Douglas; Nguyen, Hoa Mai; Kong, Fantao; Beyly-Adriano, Audrey; Légeret, Bertrand; Billon, Emmanuelle; Cuiné, Stéphan; Beisson, Fred; Peltier, Gilles; Li-Beisson, Yonghua

2016-01-01

Microalgae have emerged as a promising source for biofuel production. Massive oil and starch accumulation in microalgae is possible, but occurs mostly when biomass growth is impaired. The molecular networks underlying the negative correlation between growth and reserve formation are not known. Thus isolation of strains capable of accumulating carbon reserves during optimal growth would be highly desirable. To this end, we screened an insertional mutant library of Chlamydomonas reinhardtii for alterations in oil content. A mutant accumulating five times more oil and twice more starch than wild-type during optimal growth was isolated and named constitutive oil accumulator 1 (coa1). Growth in photobioreactors under highly controlled conditions revealed that the increase in oil and starch content in coa1 was dependent on light intensity. Genetic analysis and DNA hybridization pointed to a single insertional event responsible for the phenotype. Whole genome re-sequencing identified in coa1 a >200 kb deletion on chromosome 14 containing 41 genes. This study demonstrates that, 1), the generation of algal strains accumulating higher reserve amount without compromising biomass accumulation is feasible; 2), light is an important parameter in phenotypic analysis; and 3), a chromosomal region (Quantitative Trait Locus) acts as suppressor of carbon reserve accumulation during optimal growth. PMID:27141848

Wine yeast phenomics: A standardized fermentation method for assessing quantitative traits of Saccharomyces cerevisiae strains in enological conditions

PubMed Central

Bernard, Margaux; Trujillo, Marine; Prodhomme, Duyên; Barbe, Jean-Christophe; Gibon, Yves; Marullo, Philippe

2018-01-01

This work describes the set up of a small scale fermentation methodology for measuring quantitative traits of hundreds of samples in an enological context. By using standardized screw cap vessels, the alcoholic fermentation kinetics of Saccharomyces cerevisiae strains were measured by following their weight loss over the time. This dispositive was coupled with robotized enzymatic assays for measuring metabolites of enological interest in natural grape juices. Despite the small volume used, kinetic parameters and fermentation end products measured are similar with those observed in larger scale vats. The vessel used also offers the possibility to assay 32 volatiles compounds using a headspace solid-phase micro-extraction coupled to gas chromatography and mass spectrometry. The vessel shaking applied strongly impacted most of the phenotypes investigated due to oxygen transfer occuring in the first hours of the alcoholic fermentation. The impact of grape must and micro-oxygenation was investigated illustrating some relevant genetic x environmental interactions. By phenotyping a wide panel of commercial wine starters in five grape juices, broad phenotypic correlations between kinetics and metabolic end products were evidentiated. Moreover, a multivariate analysis illustrates that some grape musts are more able than others to discriminate commercial strains since some are less robust to environmental changes. PMID:29351285

Quantitative trait loci for a neurocranium deformity, lack of operculum, in gilthead seabream (Sparus aurata L.).

PubMed

Negrín-Báez, D; Navarro, A; Afonso, J M; Toro, M A; Zamorano, M J

2016-04-01

Lack of operculum, a neurocranial deformity, is the most common external abnormality to be found among industrially produced gilthead seabream (Sparus aurata L.), and this entails significant financial losses. This study conducts, for the first time in this species, a quantitative trait loci (QTL) analysis of the lack of operculum. A total of 142 individuals from a paternal half-sibling family (six full-sibling families) were selected for QTL mapping. They had previously shown a highly significant association with the prevalence of lack of operculum in a segregation analysis. All the fish were genotyped for 106 microsatellite markers using a set of multiplex PCRs (ReMsa1-ReMsa13). A linear regression methodology was used for the QTL analysis. Four QTL were detected for this deformity, two of which (QTLOP1 and QTLOP2) were significant. They were located at LG (linkage group) nine and LG10 respectively. Both QTL showed a large effect (about 27%), and furthermore, the association between lack of operculum and sire allelic segregation observed was statistically significant in the QTLOP1 analysis. These results represent a significant step towards including marker-assisted selection for this deformity in genetic breeding programmes to reduce the incidence of the deformity in the species. © 2016 Stichting International Foundation for Animal Genetics.

Genetic and agronomic assessment of cob traits in corn under low and normal nitrogen management conditions.

PubMed

Jansen, Constantin; Zhang, Yongzhong; Liu, Hongjun; Gonzalez-Portilla, Pedro J; Lauter, Nick; Kumar, Bharath; Trucillo-Silva, Ignacio; Martin, Juan Pablo San; Lee, Michael; Simcox, Kevin; Schussler, Jeff; Dhugga, Kanwarpal; Lübberstedt, Thomas

2015-07-01

Exploring and understanding the genetic basis of cob biomass in relation to grain yield under varying nitrogen management regimes will help breeders to develop dual-purpose maize. With rising energy demands and costs for fossil fuels, alternative energy from renewable sources such as maize cobs will become competitive. Maize cobs have beneficial characteristics for utilization as feedstock including compact tissue, high cellulose content, and low ash and nitrogen content. Nitrogen is quantitatively the most important nutrient for plant growth. However, the influence of nitrogen fertilization on maize cob production is unclear. In this study, quantitative trait loci (QTL) have been analyzed for cob morphological traits such as cob weight, volume, length, diameter and cob tissue density, and grain yield under normal and low nitrogen regimes. 213 doubled-haploid lines of the intermated B73 × Mo17 (IBM) Syn10 population have been resequenced for 8575 bins, based on SNP markers. A total of 138 QTL were found for six traits across six trials using composite interval mapping with ten cofactors and empirical comparison-wise thresholds (P = 0.001). Despite moderate to high repeatabilities across trials, few QTL were consistent across trials and overall levels of explained phenotypic variance were lower than expected some of the cob trait × trial combinations (R (2) = 7.3-43.1 %). Variation for cob traits was less affected by nitrogen conditions than by grain yield. Thus, the economics of cob usage under low nitrogen regimes is promising.

Quantitative trait loci controlling cyanogenic glucoside and dry matter content in cassava (Manihot esculenta Crantz) roots.

PubMed

Balyejusa Kizito, Elizabeth; Rönnberg-Wästljung, Ann-Christin; Egwang, Thomas; Gullberg, Urban; Fregene, Martin; Westerbergh, Anna

2007-09-01

Cassava (Manihot esculenta Crantz) is a starchy root crop grown in the tropics mainly by small-scale farmers even though agro-industrial processing is rapidly increasing. For this processing market improved varieties with high dry matter root content (DMC) is required. Potentially toxic cyanogenic glucosides are synthesized in the leaves and translocated to the roots. Selection for varieties with low cyanogenic glucoside potential (CNP) and high DMC is among the principal objectives in cassava breeding programs. However, these traits are highly influenced by the environmental conditions and the genetic control of these traits is not well understood. An S(1) population derived from a cross between two bred cassava varieties (MCOL 1684 and Rayong 1) that differ in CNP and DMC was used to study the heritability and genetic basis of these traits. A broad-sense heritability of 0.43 and 0.42 was found for CNP and DMC, respectively. The moderate heritabilities for DMC and CNP indicate that the phenotypic variation of these traits is explained by a genetic component. We found two quantitative trait loci (QTL) on two different linkage groups controlling CNP and six QTL on four different linkage groups controlling DMC. One QTL for CNP and one QTL for DMC mapped near each other, suggesting pleiotrophy and/or linkage of QTL. The two QTL for CNP showed additive effects while the six QTL for DMC showed additive effect, dominance or overdominance. This study is a first step towards developing molecular marker tools for efficient breeding of CNP and DMC in cassava.

Identification of Quantitative Trait Loci for Resistance to RSIVD in Red Sea Bream (Pagrus major).

PubMed

Sawayama, Eitaro; Tanizawa, Shiho; Kitamura, Shin-Ichi; Nakayama, Kei; Ohta, Kohei; Ozaki, Akiyuki; Takagi, Motohiro

2017-12-01

Red sea bream iridoviral disease (RSIVD) is a major viral disease in red sea bream farming in Japan. Previously, we identified one candidate male individual of red sea bream that was significantly associated with convalescent individuals after RSIVD. The purpose of this study is to identify the quantitative trait loci (QTL) linked to the RSIVD-resistant trait for future marker-assisted selection (MAS). Two test families were developed using the candidate male in 2014 (Fam-2014) and 2015 (Fam-2015). These test families were challenged with RSIV, and phenotypes were evaluated. Then, de novo genome sequences of red sea bream were obtained through next-generation sequencing, and microsatellite markers were searched and selected for linkage map construction. One immune-related gene, MHC class IIβ, was also used for linkage map construction. Of the microsatellite markers searched, 148 and 197 were mapped on 23 and 27 linkage groups in the female and male linkage maps, respectively, covering approximately 65% of genomes in both sexes. One QTL linked to an RSIVD-resistant trait was found in linkage group 2 of the candidate male in Fam-2014, and the phenotypic variance of the QTL was 31.1%. The QTL was closely linked to MHC class IIβ. Moreover, the QTL observed in Fam-2014 was also significantly linked to an RSIVD-resistant trait in the candidate male of Fam-2015. Our results suggest that the RSIVD-resistant trait in the candidate male was controlled by one major QTL closely linked to the MHC class IIβ gene and could be useful for MAS of red sea bream.

A Chromosome-Scale Assembly of the Bactrocera cucurbitae Genome Provides Insight to the Genetic Basis of white pupae

PubMed Central

Sim, Sheina B.; Geib, Scott M.

2017-01-01

Genetic sexing strains (GSS) used in sterile insect technique (SIT) programs are textbook examples of how classical Mendelian genetics can be directly implemented in the management of agricultural insect pests. Although the foundation of traditionally developed GSS are single locus, autosomal recessive traits, their genetic basis are largely unknown. With the advent of modern genomic techniques, the genetic basis of sexing traits in GSS can now be further investigated. This study is the first of its kind to integrate traditional genetic techniques with emerging genomics to characterize a GSS using the tephritid fruit fly pest Bactrocera cucurbitae as a model. These techniques include whole-genome sequencing, the development of a mapping population and linkage map, and quantitative trait analysis. The experiment designed to map the genetic sexing trait in B. cucurbitae, white pupae (wp), also enabled the generation of a chromosome-scale genome assembly by integrating the linkage map with the assembly. Quantitative trait loci analysis revealed SNP loci near position 42 MB on chromosome 3 to be tightly linked to wp. Gene annotation and synteny analysis show a near perfect relationship between chromosomes in B. cucurbitae and Muller elements A–E in Drosophila melanogaster. This chromosome-scale genome assembly is complete, has high contiguity, was generated using a minimal input DNA, and will be used to further characterize the genetic mechanisms underlying wp. Knowledge of the genetic basis of genetic sexing traits can be used to improve SIT in this species and expand it to other economically important Diptera. PMID:28450369

Differential gene expression of wheat progeny with contrasting levels of transpiration efficiency.

PubMed

Xue, Gang-Ping; McIntyre, C Lynne; Chapman, Scott; Bower, Neil I; Way, Heather; Reverter, Antonio; Clarke, Bryan; Shorter, Ray

2006-08-01

High water use efficiency or transpiration efficiency (TE) in wheat is a desirable physiological trait for increasing grain yield under water-limited environments. The identification of genes associated with this trait would facilitate the selection for genotypes with higher TE using molecular markers. We performed an expression profiling (microarray) analysis of approximately 16,000 unique wheat ESTs to identify genes that were differentially expressed between wheat progeny lines with contrasting TE levels from a cross between Quarrion (high TE) and Genaro 81 (low TE). We also conducted a second microarray analysis to identify genes responsive to drought stress in wheat leaves. Ninety-three genes that were differentially expressed between high and low TE progeny lines were identified. One fifth of these genes were markedly responsive to drought stress. Several potential growth-related regulatory genes, which were down-regulated by drought, were expressed at a higher level in the high TE lines than the low TE lines and are potentially associated with a biomass production component of the Quarrion-derived high TE trait. Eighteen of the TE differentially expressed genes were further analysed using quantitative RT-PCR on a separate set of plant samples from those used for microarray analysis. The expression levels of 11 of the 18 genes were positively correlated with the high TE trait, measured as carbon isotope discrimination (Delta(13)C). These data indicate that some of these TE differentially expressed genes are candidates for investigating processes that underlie the high TE trait or for use as expression quantitative trait loci (eQTLs) for TE.

Selective DNA Pooling for Determination of Linkage between a Molecular Marker and a Quantitative Trait Locus

PubMed Central

Darvasi, A.; Soller, M.

1994-01-01

Selective genotyping is a method to reduce costs in marker-quantitative trait locus (QTL) linkage determination by genotyping only those individuals with extreme, and hence most informative, quantitative trait values. The DNA pooling strategy (termed: ``selective DNA pooling'') takes this one step further by pooling DNA from the selected individuals at each of the two phenotypic extremes, and basing the test for linkage on marker allele frequencies as estimated from the pooled samples only. This can reduce genotyping costs of marker-QTL linkage determination by up to two orders of magnitude. Theoretical analysis of selective DNA pooling shows that for experiments involving backcross, F(2) and half-sib designs, the power of selective DNA pooling for detecting genes with large effect, can be the same as that obtained by individual selective genotyping. Power for detecting genes with small effect, however, was found to decrease strongly with increase in the technical error of estimating allele frequencies in the pooled samples. The effect of technical error, however, can be markedly reduced by replication of technical procedures. It is also shown that a proportion selected of 0.1 at each tail will be appropriate for a wide range of experimental conditions. PMID:7896115

Statistical correction of the Winner’s Curse explains replication variability in quantitative trait genome-wide association studies

PubMed Central

Pe’er, Itsik

2017-01-01

Genome-wide association studies (GWAS) have identified hundreds of SNPs responsible for variation in human quantitative traits. However, genome-wide-significant associations often fail to replicate across independent cohorts, in apparent inconsistency with their apparent strong effects in discovery cohorts. This limited success of replication raises pervasive questions about the utility of the GWAS field. We identify all 332 studies of quantitative traits from the NHGRI-EBI GWAS Database with attempted replication. We find that the majority of studies provide insufficient data to evaluate replication rates. The remaining papers replicate significantly worse than expected (p < 10−14), even when adjusting for regression-to-the-mean of effect size between discovery- and replication-cohorts termed the Winner’s Curse (p < 10−16). We show this is due in part to misreporting replication cohort-size as a maximum number, rather than per-locus one. In 39 studies accurately reporting per-locus cohort-size for attempted replication of 707 loci in samples with similar ancestry, replication rate matched expectation (predicted 458, observed 457, p = 0.94). In contrast, ancestry differences between replication and discovery (13 studies, 385 loci) cause the most highly-powered decile of loci to replicate worse than expected, due to difference in linkage disequilibrium. PMID:28715421

Annotated definition of BCL11A and HMIP-2 haplotypes through the analysis of sicilian β-thalassemia patients with high levels of fetal hemoglobin.

PubMed

Buccheri, Maria A; Spina, Sonia; Ruberto, Concetta; Lombardo, Turi; Labie, Dominique; Ragusa, And Angela

2013-01-01

Fetal hemoglobin (Hb F) is the principal ameliorating factor of β-thalassemia (β-thal) and sickle cell disease. Persistent production in adult life is a quantitative trait regulated by loci inside or outside the β-globin gene cluster. From genome-wide association studies, principal quantitative trait loci (QTL) (accounting for 50.0% of Hb F variability in different populations) have been identified in the BCL11A gene, HBS1L-MYB intergenic polymorphism and the β-globin gene cluster itself. In this study, we analyzed quantitative trait haplotypes in two Sicilian families with extremely mild β-thal and unusually high Hb F expression, in order to examine possible genetic background variations in a similar β-thalassemic phenotype. This study redefines the linkage disequilibrium blocks at these loci, but also shows slight differences between probands in haplotype combinations which could reflect different mechanisms of high Hb F production in patients with β-thal. We proposed a haplotype-based approach as a useful tool for the understanding of β-thal phenotype variation in patients with similar β-thalassemic backgrounds in an attempt to answer the recurring question of why patients with the same β-thalassemic genotype show different phenotypes.

A Unified Framework Integrating Parent-of-Origin Effects for Association Study

PubMed Central

Xiao, Feifei; Ma, Jianzhong; Amos, Christopher I.

2013-01-01

Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting is related to several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we generalize the natural and orthogonal interactions (NOIA) framework to allow for estimation of both main allelic effects and POEs. We develop a statistical (Stat-POE) model that has the orthogonal estimates of parameters including the POEs. We conducted simulation studies for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits. PMID:23991061

Analysis of Natural Allelic Variation of Arabidopsis Seed Germination and Seed Longevity Traits between the Accessions Landsberg erecta and Shakdara, Using a New Recombinant Inbred Line Population1

PubMed Central

Clerkx, Emile J.M.; El-Lithy, Mohamed E.; Vierling, Elizabeth; Ruys, Gerda J.; Vries, Hetty Blankestijn-De; Groot, Steven P.C.; Vreugdenhil, Dick; Koornneef, Maarten

2004-01-01

Quantitative trait loci (QTL) mapping was used to identify loci controlling various aspects of seed longevity during storage and germination. Similar locations for QTLs controlling different traits might be an indication for a common genetic control of such traits. For this analysis we used a new recombinant inbred line population derived from a cross between the accessions Landsberg erecta (Ler) and Shakdara (Sha). A set of 114 F9 recombinant inbred lines was genotyped with 65 polymerase chain reaction-based markers and the phenotypic marker erecta. The traits analyzed were dormancy, speed of germination, seed sugar content, seed germination after a controlled deterioration test, hydrogen peroxide (H2O2) treatment, and on abscisic acid. Furthermore, the effects of heat stress, salt (NaCl) stress, osmotic (mannitol) stress, and natural aging were analyzed. For all traits one or more QTLs were identified, with some QTLs for different traits colocating. The relevance of colocation for mechanisms underlying the various traits is discussed. PMID:15122038

Apparent directional selection by biased pleiotropic mutation.

PubMed

Tanaka, Yoshinari

2010-07-01

Pleiotropic effects of deleterious mutations are considered to be among the factors responsible for genetic constraints on evolution by long-term directional selection acting on a quantitative trait. If pleiotropic phenotypic effects are biased in a particular direction, mutations generate apparent directional selection, which refers to the covariance between fitness and the trait owing to a linear association between the number of mutations possessed by individuals and the genotypic values of the trait. The present analysis has shown how the equilibrium mean value of the trait is determined by a balance between directional selection and biased pleiotropic mutations. Assuming that genes act additively both on the trait and on fitness, the total variance-standardized directional selection gradient was decomposed into apparent and true components. Experimental data on mutation bias from the bristle traits of Drosophila and life history traits of Daphnia suggest that apparent selection explains a small but significant fraction of directional selection pressure that is observed in nature; the data suggest that changes induced in a trait by biased pleiotropic mutation (i.e., by apparent directional selection) are easily compensated for by (true) directional selection.