Environmental influence on the genetic correlations between life-history traits in Caenorhabditis elegans

Empirical evidence is mounting to suggesting that genetic correlations between life-history traits are environment specific. However, detailed knowledge about the loci underlying genetic correlations in different environments is scant. Here, we studied the influence of temperature (12 degrees C and 24 degrees C) on the genetic correlations between egg size, egg number and body mass in the nematode Caenorhabditis elegans. We used a quantitative trait loci (QTL) approach based on a genetic map with evenly spaced single nucleotide polymorphism markers in an N2 x CB4856 recombinant inbred panel. Significant genetic correlations between various traits were found at both temperatures. We detected pleiotropic or closely linked QTL, which supported the negative correlation between egg size and egg number at 12 degrees C, the positive correlation across temperatures for body mass, and the positive correlation between body mass and egg size at 12 degrees C. The results indicate that specific loci control the covariation in these life-history traits and the locus control is prone to environmental conditions.     

Mitochondrial genetic effects on latent class variables associated with susceptibility to alcoholism

We report the results of statistical genetic analyses of data from the Collaborative Study on the Genetics of Alcoholism prepared for the Genetic Analysis Workshop 14 to detect and characterize maternally inherited mitochondrial genetic effects on variation in latent class psychiatric/behavioral variables employed in the diagnosis of alcoholism. Using published extensions to variance decomposition methods for statistical genetic analysis of continuous and discrete traits we: 1) estimated the proportion of the variance in each trait due to the effects of mitochondrial DNA (mtDNA), 2) tested for pleiotropy, both mitochondrial genetic and residual additive genetic, between trait pairs, and 3) evaluated whether the simultaneous estimation of mitochondrial genetic effects on these traits improves our ability to detect and localize quantitative trait loci (QTL) in the nuclear genome. After correction for multiple testing, we find significant (p < 0.009) mitochondrial genetic contributions to the variance for two latent class variables. Although we do detect significant residual additive genetic correlations between the two traits, there is no evidence of a residual mitochondrial genetic correlation between them. Evidence for autosomal QTL for these traits is improved when linkage screens are conditioned on significant mitochondrial genetic effects. We conclude that mitochondrial genes may contribute to variation in some latent class psychiatric/behavioral variables associated with alcoholism.     

利用双单倍体群体剖析水稻产量及其相关性状的遗传基础

主效QTL、上位性效应和它们与环境的互作(QE)都是数量性状的重要遗传因素。利用籼粳交珍汕97／武育粳2号F1植株上的花药进行组织培养得到的190个双单倍体群体和179个微卫星标记,通过两年两重复田间试验,采用混合线性模型方法分析了9个控制水稻产量及其相关性状的遗传效应,得到57个主效QTL,41对上位性互作,8对QTL与环境的互作和7对上位性效应与环境的互作。单个主效QTL解释这些性状1．3％～25．8％的表型方差。各性状QTL的累积表型贡献率达11．5％～66．8％。大多数性状之间具有显著的表型相关性,相关性较高的性状之间常具有较多共同或紧密连锁的QTL。结果表明,基因的多效性或紧密连锁可能是性状相关的重要遗传基础。     

Simultaneous mapping of epistatic QTL in chickens reveals clusters of QTL pairs with similar genetic effects on growth

We used simultaneous mapping of interacting quantitative trait locus (QTL) pairs to study various growth traits in a chicken F2 intercross. The method was shown to increase the number of detected QTLs by 30 % compared with a traditional method detecting QTLs by their marginal genetic effects. Epistasis was shown to be an important contributor to the genetic variance of growth, with the largest impact on early growth (before 6 weeks of age). There is also evidence for a discrete set of interacting loci involved in early growth, supporting the previous findings of different genetic regulation of early and late growth in chicken. The genotype-phenotype relationship was evaluated for all interacting QTL pairs and 17 of the 21 evaluated QTL pairs could be assigned to one of four clusters in which the pairs in a cluster have very similar genetic effects on growth. The genetic effects of the pairs indicate commonly occurring dominance-by-dominance, heterosis and multiplicative interactions. The results from this study clearly illustrate the increase in power obtained by using this novel method for simultaneous detection of epistatic QTL, and also how visualization of genotype-phenotype relationships for epistatic QTL pairs provides new insights to biological mechanisms underlying complex traits.     

Pleiotropy or linkage? Their relative contributions to the genetic correlation of quantitative traits and detection by multitrait GWA studies

Genetic correlations between traits may cause correlated responses to selection. Previous models described the conditions under which genetic correlations are expected to be maintained. Selection, mutation, and migration are all proposed to affect genetic correlations, regardless of whether the underlying genetic architecture consists of pleiotropic or tightly linked loci affecting the traits. Here, we investigate the conditions under which pleiotropy and linkage have different effects on the genetic correlations between traits by explicitly modeling multiple genetic architectures to look at the effects of selection strength, degree of correlational selection, mutation rate, mutational variance, recombination rate, and migration rate. We show that at mutation-selection(-migration) balance, mutation rates differentially affect the equilibrium levels of genetic correlation when architectures are composed of pairs of physically linked loci compared to architectures of pleiotropic loci. Even when there is perfect linkage (no recombination within pairs of linked loci), a lower genetic correlation is maintained than with pleiotropy, with a lower mutation rate leading to a larger decrease. These results imply that the detection of causal loci in multitrait association studies will be affected by the type of underlying architectures, whereby pleiotropic variants are more likely to be underlying multiple detected associations. We also confirm that tighter linkage between nonpleiotropic causal loci maintains higher genetic correlations at the traits and leads to a greater proportion of false positives in association analyses.     

Incorporating pleiotropic quantitative trait loci in dissection of complex traits: seed yield in rapeseed as an example

Key message

A comprehensive linkage atlas for seed yield in rapeseed.

Abstract

Most agronomic traits of interest for crop improvement (including seed yield) are highly complex quantitative traits controlled by numerous genetic loci, which brings challenges for comprehensively capturing associated markers/genes. We propose that multiple trait interactions underlie complex traits such as seed yield, and that considering these component traits and their interactions can dissect individual quantitative trait loci (QTL) effects more effectively and improve yield predictions. Using a segregating rapeseed (Brassica napus) population, we analyzed a large set of trait data generated in 19 independent experiments to investigate correlations between seed yield and other complex traits, and further identified QTL in this population with a SNP-based genetic bin map. A total of 1904 consensus QTL accounting for 22 traits, including 80 QTL directly affecting seed yield, were anchored to the B. napus reference sequence. Through trait association analysis and QTL meta-analysis, we identified a total of 525 indivisible QTL that either directly or indirectly contributed to seed yield, of which 295 QTL were detected across multiple environments. A majority (81.5%) of the 525 QTL were pleiotropic. By considering associations between traits, we identified 25 yield-related QTL previously ignored due to contrasting genetic effects, as well as 31 QTL with minor complementary effects. Implementation of the 525 QTL in genomic prediction models improved seed yield prediction accuracy. Dissecting the genetic and phenotypic interrelationships underlying complex quantitative traits using this method will provide valuable insights for genomics-based crop improvement.

     

DIFFERENTIAL DOMINANCE OF PLEIOTROPIC LOCI FOR MOUSE SKELETAL TRAITS

The term "differential dominance" describes the situation in which the dominance effects at a pleiotropic locus vary between traits. Directional selection on the phenotype can lead to balancing selection on differentially dominant pleiotropic loci. Even without any individual overdominant traits, some linear combination of traits will display overdominance at a locus displaying differential dominance. Multivariate overdominance may be responsible, in part, for high levels of heterozygosity found in natural populations. We examine differential dominance of 70 mouse skeletal traits at 92 quantitative trait loci (QTL). Our results indicate moderate to strong additive and dominance effects at pleiotropic loci, low levels of individual-trait overdominance, and universal multivariate overdominance. Multivariate overdominance affects a range of 6% to 81% of morphospace, with a mean of 32%. Multivariate overdominance tends to affect a larger percentage of morphospace at pleiotropic loci with antagonistic effects on multiple traits (42%). We conclude that multivariate overdominance is common and should be considered in models and in empirical studies of the role of genetic variation in evolvability.     

Linkage analysis of quantitative traits in an interspecific cross of tomato (lycopersicon esculentum x lycopersicon pimpinellifolium) by means of genetic markers

Linkage relationships between loci affecting quantitative traits (QTL) and marker loci were examined in an interspecific cross between Lycopersicon esculentum and Lycopersicon pimpinellifolium. Parental lines differed for six morphological markers and for four electrophoretic markers. Almost 1700 F-2 plants were scored with respect to the genetic markers and also with respect to 18 quantitative traits. Major genes affecting the quantitative traits were not found, but out of 180 possible marker x trait combinations, 85 showed significant quantitative effects associated with the genetic markers. The average marker-associated main effect was on the order of 6% of the mean value of the trait. Most of the main effects were apparently due to linkage of QTL to the marker loci rather than to pleiotropy. Fourteen of the traits showed at least one highly significant effect of opposite sign to the overall difference between the parental lines, demonstrating the ability of this design to uncover cryptic genetic variation. Significant variance and skewness effects on the quantitative traits were found to be associated with the genetic markers, suggesting the possible presence of loci affecting the variance and shape of quantitative trait distribution in a population. Most marker-associated quantitative effects showed some degree of dominance, generally in the direction of the L. pimpinellifolium parent. When the significant marker-associated effects were examined in pairs, 12% showed significant interaction effects. The results of this study illustrate the potential usefulness of this type of analysis for the detailed genetic investigation of quantitative trait variation in suitably marked populations.     

THE GENOMIC ARCHITECTURE OF SEXUAL DIMORPHISM IN THE DIOECIOUS PLANT SILENE LATIFOLIA

Evaluating the genetic architecture of sexual dimorphism can aid our understanding of the extent to which shared genetic control of trait variation versus sex‐specific control impacts the evolutionary dynamics of phenotypic change within each sex. We performed a QTL analysis on Silene latifolia to evaluate the contribution of sex‐specific QTL to phenotypic variation in 46 traits, whether traits involved in trade‐offs had colocalized QTL, and whether the distribution of sex‐specific loci can explain differences between the sexes in their variance/covariance matrices. We used a backcross generation derived from two artificial‐selection lines. We found that sex‐specific QTL explained a significantly greater percent of the variation in sexually dimorphic traits than loci expressed in both sexes. Genetically correlated traits often had colocalized QTL, whose signs were in the expected direction. Lastly, traits with different genetic correlations within the sexes displayed a disproportionately high number of sex‐specific QTL, and more QTL co‐occurred in males than females, suggesting greater trait integration. These results show that sex differences in QTL patterns are congruent with theory on the resolution of sexual conflict and differences based on G ‐matrix results. They also suggest that trade‐offs and trait integration are likely to affect males more than females.     

Genetic basis of phenotypic correlations among growth traits in hybrid willow (Salix dasycladosxS. viminalis) grown under two water regimes

Phenotypic correlations and quantitative trait loci (QTL) for important growth traits and a surrogate of intrinsic water-use efficiency (leaf delta(13)C) were analysed in a willow pedigree of 92 full-sibling clones grown under two water regimes. The major objective was to examine the genetic basis of the phenotypic correlations. Cuttings of Salix were glasshouse-grown during one growing season. The relative growth rate (RGR) and underlying traits were assessed. QTL analysis was conducted based on an available linkage map for Salix. Leaf area productivity and leaf nitrogen productivity were more important in determining RGR than leaf area ratio and specific leaf area. However, phenotypic correlations among growth traits partly varied between the two environments. QTL were detected for most growth traits, among them many common QTL for different traits. The QTL pattern reflected the phenotypic correlation pattern. None of the QTL for the complex traits was consistent across the different environments. The results demonstrate a genetic basis for phenotypic correlations among growth traits in Salix, and provide evidence for the existence of 'master switches' regulating some of the traits.     

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

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.     

Simultaneous mapping of epistatic QTL in DU6i × DBA/2 mice

We have mapped epistatic quantitative trait loci (QTL) in an F₂ cross between DU6i × DBA/2 mice. By including these epistatic QTL and their interaction parameters in the genetic model, we were able to increase the genetic variance explained substantially (8.8%–128.3%) for several growth and body composition traits. We used an analysis method based on a simultaneous search for epistatic QTL pairs without assuming that the QTL had any effect individually. We were able to detect several QTL that could not be detected in a search for marginal QTL effects because the epistasis cancelled out the individual effects of the QTL. In total, 23 genomic regions were found to contain QTL affecting one or several of the traits and eight of these QTL did not have significant individual effects. We identified 44 QTL pairs with significant effects on the traits, and, for 28 of the pairs, an epistatic QTL model fit the data significantly better than a model without interactions. The epistatic pairs were classified by the significance of the epistatic parameters in the genetic model, and visual inspection of the two-locus genotype means identified six types of related genotype–phenotype patterns among the pairs. Five of these patterns resembled previously published patterns of QTL interactions.     

Using mating designs to uncover QTL and the genetic architecture of complex traits

Analysis of quantitative trait loci (QTL) affecting complex traits is often pursued in single-cross experiments. For most purposes, including breeding, some assessment is desired of the generalizability of the QTL findings and of the overall genetic architecture of the trait. Single-cross experiments provide a poor basis for these purposes, as comparison across experiments is hampered by segregation of different allelic combinations among different parents and by context-dependent effects of QTL. To overcome this problem, we combined the benefits of QTL analysis (to identify genomic regions affecting trait variation) and classic diallel analysis (to obtain insight into the general inheritance of the trait) by analyzing multiple mapping families that are connected via shared parents. We first provide a theoretical derivation of main (general combining ability (GCA)) and interaction (specific combining ability (SCA)) effects on F(2) family means relative to variance components in a randomly mating reference population. Then, using computer simulations to generate F(2) families derived from 10 inbred parents in different partial-diallel designs, we show that QTL can be detected and that the residual among-family variance can be analyzed. Standard diallel analysis methods are applied in order to reveal the presence and mode of action (in terms of GCA and SCA) of undetected polygenes. Given a fixed experiment size (total number of individuals), we demonstrate that QTL detection and estimation of the genetic architecture of polygenic effects are competing goals, which should be explicitly accounted for in the experimental design. Our approach provides a general strategy for exploring the genetic architecture, as well as the QTL underlying variation in quantitative traits.     

Quantitative trait loci mapping of floral and leaf morphology traits in Arabidopsis thaliana: evidence for modular genetic architecture

Summary Morphological variation within organisms is integrated and often modular in nature. That is to say, the size and shape of traits tend to vary in a coordinated and structured manner across sets of organs or parts of an organism. The genetic basis of this morphological integration is largely unknown. Here, we report on quantitative trait loci (QTL) analysis of leaf and floral organ size in Arabidopsis thaliana. We evaluate patterns of genetic correlations among traits and perform whole-genome scans using QTL mapping methods. We detected significant genetic variation for the size and shape of each floral and leaf trait in our study. Moreover, we found large positive genetic correlations among sets of either flower or leaf traits, but low and generally nonsignificant genetic correlations between flower and leaf traits. These results support the hypothesis of independent floral and vegetative modules. We consider co-localization of QTL for different traits as support for a pleiotropic basis of morphological integration and modularity. A total of eight QTL affecting flower and three QTL affecting leaf traits were identified. Most QTL affected either floral or leaf traits, providing a general explanation for high correlations within and low correlations between modules. Only two genomic locations affected both flower and leaf growth. These results are discussed in the context of the evolution of modules, pleiotropy, and the putative homologous relationship between leaves and flowers.     

Quantitative traits in plants: beyond the QTL

Phenotypic variation for quantitative traits results from segregation at multiple quantitative trait loci (QTL), the effects of which are modified by the internal and external environments. Because of their favorable genetic attributes (e.g. short generation time, large families and tolerance to inbreeding), plants are often used to test new concepts in quantitative trait analysis. Thus far, the molecular basis underlying allelic variation at QTL is similar to the identified variation for simple mendelian loci; namely, alterations in gene expression or protein function. Further comprehensive dissection of complex phenotypes will depend on our ability to link genetic components of the QTL variation to genomic databases.     

Quantitative genetics and sex-specific selection on sexually dimorphic traits in bighorn sheep

Sexual conflict at loci influencing traits shared between the sexes occurs when sex-specific selection pressures are antagonistic relative to the genetic correlation between the sexes. To assess whether there is sexual conflict over shared traits, we estimated heritability and intersexual genetic correlations for highly sexually dimorphic traits (horn volume and body mass) in a wild population of bighorn sheep (Ovis canadensis) and quantified sex-specific selection using estimates of longevity and lifetime reproductive success. Body mass and horn volume showed significant additive genetic variance in both sexes, and intersexual genetic correlations were 0.24+/-0.28 for horn volume and 0.63+/-0.30 for body mass. For horn volume, selection coefficients did not significantly differ from zero in either sex. For body weight, selection coefficients were positive in females but did not differ from zero in males. The absence of detectable sexually antagonistic selection suggests that currently there are no sexual conflicts at loci influencing horn volume and body mass.     

Variation in phosphorus and sulfur content shapes the genetic architecture and phenotypic associations within the wheat grain ionome

Dissection of the genetic basis of wheat ionome is crucial for understanding the physiological and biochemical processes underlying mineral accumulation in seeds, as well as for efficient crop breeding. Most of the elements essential for plants are metals stored in seeds as chelate complexes with phytic acid or sulfur‐containing compounds. We assume that the involvement of phosphorus and sulfur in metal chelation is the reason for strong phenotypic correlations within ionome. Adjustment of element concentrations for the effect of variation in phosphorus and sulfur seed content resulted in drastic change of phenotypic correlations between the elements. The genetic architecture of wheat grain ionome was characterized by quantitative trait loci (QTL) analysis using a cross between durum and wild emmer wheat. QTL analysis of the adjusted traits and two‐trait analysis of the initial traits paired with either P or S considerably improved QTL detection power and accuracy, resulting in the identification of 105 QTLs and 617 QTL effects for 11 elements. Candidate gene search revealed some potential functional associations between QTLs and corresponding genes within their intervals. Thus, we have shown that accounting for variation in P and S is crucial for understanding of the physiological and genetic regulation of mineral composition of wheat grain ionome and can be implemented for other plants.     

Quantitative trait loci affecting delta13C and response to differential water availibility in Arabidopsis thaliana

Phenotypic plasticity is an important response mechanism of plants to environmental heterogeneity. Here, we explored the genetic basis of plastic responses of Arabidopsis thaliana to water deficit by experimentally mapping quantitative trait loci (QTL) in two recombinant inbred populations (Cvi x Ler and Ler x Col). We detected genetic variation and significant genotype-by-environment interactions for many traits related to water use. We also mapped 26 QTL, including six for carbon isotope composition (delta13C). Negative genetic correlations between fruit length and fruit production as well as between flowering time and branch production were corroborated by QTL colocalization, suggesting these correlations are due to pleiotropy or physical linkage. Water-limited plants were more apically dominant with greater root:shoot ratios and higher delta13C (higher water-use efficiency) when compared to well-watered plants. Many of the QTL effects for these traits interacted significantly with the irrigation treatment, suggesting that the observed phenotypic plasticity is genetically based. We specifically searched for epistatic (QTL-QTL) interactions using a two-dimensional genome scan, which allowed us to detect epistasis regardless of additive genetic effects. We found several significant QTL-QTL interactions including three that exhibited environmental dependence. These results provide preliminary evidence for proposed genetic mechanisms underlying phenotypic plasticity.     

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

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

Molecular-Marker-Facilitated Investigations of Quantitative-Trait Loci in Maize. I. Numbers, Genomic Distribution and Types of Gene Action

Individual genetic factors which underlie variation in quantitative traits of maize were investigated in each of two F2 populations by examining the mean trait expressions of genotypic classes at each of 17-20 segregating marker loci. It was demonstrated that the trait expression of marker locus classes could be interpreted in terms of genetic behavior at linked quantitative trait loci (QTLs). For each of 82 traits evaluated, QTLs were detected and located to genomic sites. The numbers of detected factors varied according to trait, with the average trait significantly influenced by almost two-thirds of the marked genomic sites. Most of the detected associations between marker loci and quantitative traits were highly significant, and could have been detected with fewer than the 1800-1900 plants evaluated in each population. The cumulative, simple effects of marker-linked regions of the genome explained between 8 and 40% of the phenotypic variation for a subset of 25 traits evaluated. Single marker loci accounted for between 0.3% and 16% of the phenotypic variation of traits. Individual plant heterozygosity, as measured by marker loci, was significantly associated with variation in many traits. The apparent types of gene action at the QTLs varied both among traits and between loci for given traits, although overdominance appeared frequently, especially for yield-related traits. The prevalence of apparent overdominance may reflect the effects of multiple QTLs within individual marker-linked regions, a situation which would tend to result in overestimation of dominance. Digenic epistasis did not appear to be important in determining the expression of the quantitative traits evaluated. Examination of the effects of marked regions on the expression of pairs of traits suggests that genomic regions vary in the direction and magnitudes of their effects on trait correlations, perhaps providing a means of selecting to dissociate some correlated traits. Marker-facilitated investigations appear to provide a powerful means of examining aspects of the genetic control of quantitative traits. Modifications of the methods employed herein will allow examination of the stability of individual gene effects in varying genetic backgrounds and environments.