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.     

Failure to replicate two mate preference QTLs across multiple strains of Drosophila pseudoobscura

Behavioral genetic mapping studies in model organisms predominantly use crosses originating from a single pair of inbred lines to determine the location of alleles that confer genetic variation in the trait of interest, and they often make sweeping generalizations about the genetic architecture of the trait based on these results. A previous study fine mapped mate preference variation between one pair of Drosophila pseudoobscura lines and identified 2 strong-effect behavioral quantitative trait loci (QTLs). Here, we replicated the previous study's mapping design to examine the extent of variation at these behavioral QTLs across 6 pairs of lines, but we were unable to detect effects of either QTL region in the pairs of lines studied. We suggest that the low-discrimination alleles at these 2 QTLs may occur at low frequency within D. pseudoobscura, although other explanations for the inconsistency are possible. These results underscore the need to examine multiple strains across a species when describing the genetic variation underlying behavioral traits.     

Pleiotropic effects on mandibular morphology II: differential epistasis and genetic variation in morphological integration

The evolution of morphological modularity through the sequestration of pleiotropy to sets of functionally and developmentally related traits requires genetic variation in the relationships between traits. Genetic variation in relationships between traits can result from differential epistasis, where epistatic relationships for pairs of loci are different for different traits. This study maps relationship quantitative trait loci (QTLs), specifically QTLs that affect the relationship between individual mandibular traits and mandible length, across the genome in an F2 intercross of the LG/J and SM/J inbred mouse strains (N = 1045). We discovered 23 relationship QTLs scattered throughout the genome. All mandibular traits were involved in one or more relationship QTL. When multiple traits were affected at a relationship QTL, the traits tended to come from a developmentally restricted region of the mandible, either the muscular processes or the alveolus. About one-third of the relationship QTLs correspond to previously located trait QTLs affecting the same traits. These results comprise examples of genetic variation necessary for an evolutionary response to selection on the range of pleiotropic effects.     

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。     

The Genetic Architecture of Quantitative Traits Cannot Be Inferred from Variance Component Analysis

Classical quantitative genetic analyses estimate additive and non-additive genetic and environmental components of variance from phenotypes of related individuals without knowing the identities of quantitative trait loci (QTLs). Many studies have found a large proportion of quantitative trait variation can be attributed to the additive genetic variance (V_A), providing the basis for claims that non-additive gene actions are unimportant. In this study, we show that arbitrarily defined parameterizations of genetic effects seemingly consistent with non-additive gene actions can also capture the majority of genetic variation. This reveals a logical flaw in using the relative magnitudes of variance components to indicate the relative importance of additive and non-additive gene actions. We discuss the implications and propose that variance component analyses should not be used to infer the genetic architecture of quantitative traits.     

The nature of quantittative genetic variation revisited: Lessons from Drosophila bristles

Most characters that distinguish one individual from another, like height or weight, vary continuously in populations. Continuous variation of these ‘quantitative’ traits is due to the simultaneous segregation of multiple quantitative trait loci (QTLs) as well as environmental influences. A major challenge in human medicine, animal and plant breeding and evolutionary genetics is to identify QTLs and determine their genetic properties. Studies of the classic quantitative traits, abdominal and sternopleural bristle numbers of Drosophila, have shown that: (1) many loci have small effects on bristle number, but a few have large effects and cause most of the genetic variation; (2) ‘candidate’ loci involved in bristle development often have large quantitative effects on bristle number; and (3) alleles at QTLs affecting bristle number have variable degrees of dominance, interact with each other, and affect other quantitative traits, including fitness. Lessons learned from this model system will be applicable to studies of the genetic basis of quantitative variation in other species.     

Large-scale in silico mapping of complex quantitative traits in inbred mice

Understanding the genetic basis of common disease and disease-related quantitative traits will aid in the development of diagnostics and therapeutics. The processs of gene discovery can be sped up by rapid and effective integration of well-defined mouse genome and phenome data resources. We describe here an in silico gene-discovery strategy through genome-wide association (GWA) scans in inbred mice with a wide range of genetic variation. We identified 937 quantitative trait loci (QTLs) from a survey of 173 mouse phenotypes, which include models of human disease (atherosclerosis, cardiovascular disease, cancer and obesity) as well as behavioral, hematological, immunological, metabolic, and neurological traits. 67% of QTLs were refined into genomic regions <0.5 Mb with approximately 40-fold increase in mapping precision as compared with classical linkage analysis. This makes for more efficient identification of the genes that underlie disease. We have identified two QTL genes, Adam12 and Cdh2, as causal genetic variants for atherogenic diet-induced obesity. Our findings demonstrate that GWA analysis in mice has the potential to resolve multiple tightly linked QTLs and achieve single-gene resolution. These high-resolution QTL data can serve as a primary resource for positional cloning and gene identification in the research community.     

Genetic mapping of yield traits using RIL population derived from Fuchuan Dahuasheng and ICG6375 of peanut (<Emphasis Type="Italic">Arachis hypogaea</Emphasis> L.)

The genetic architecture determinants of yield traits in peanut (Arachis hypogaea L.) are poorly understood. In the present study, an effort was made to map quantitative trait loci (QTLs) for yield traits using recombinant inbred lines (RIL). A genetic linkage map was constructed containing 609 loci, covering a total of 1557.48 cM with an average distance of 2.56 cM between adjacent markers. The present map exhibited good collinearity with the physical map of diploid species of Arachis. Ninety-two repeatable QTLs were identified for 11 traits including height of main stem, total branching number, and nine pod- and seed-related traits. Of the 92 QTLs, 15 QTLs were expressed across three environments and 65 QTLs were newly identified. Twelve QTLs for the height of main stem and the pod- and seed-related traits explaining more than 10 % of phenotypic variation showed a great potential for marker-assisted selection in improving these traits. 相似文献   

The genetic architecture of quantitative traits: lessons from Drosophila

Understanding the genetic architecture of quantitative traits begins with identifying the genes regulating these traits, mapping the subset of genetically varying quantitative trait loci (QTLs) in natural populations, and pinpointing the molecular polymorphisms defining QTL alleles. Studies in Drosophila have revealed large numbers of pleiotropic genes that interact epistatically to regulate quantitative traits, and large numbers of QTLs with sex-, environment- and genotype-specific effects. Multiple molecular polymorphisms in regulatory regions of candidate genes are often associated with variation for complex traits. These observations offer valuable lessons for understanding the genetic basis of variation for complex traits in other organisms, including humans.     

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

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.     

Natural variation in Arabidopsis thaliana revealed a genetic network controlling germination under salt stress

Plant responses to environmental stresses are polygenic and complex traits. In this study quantitative genetics using natural variation in Arabidopsis thaliana was used to investigate the genetic architecture of plant responses to salt stress. Eighty seven A. thaliana accessions were screened and showed a large variation for root development and seed germination under 125 and 200 mM NaCl, respectively. Twenty two quantitative trait loci for these traits have been detected by phenotyping two recombinants inbred line populations, Sha x Col and Sha x Ler. Four QTLs controlling germination under salt were detected in the Sha x Col population. Interestingly, only one allelic combination at these four QTLs inhibits germination under salt stress, implying strong epistatic interactions between them. In this interacting context, we confirmed the effect of one QTL by phenotyping selected heterozygous inbred families. We also showed that this QTL is involved in the control of germination under other stress conditions such as KCl, mannitol, cold, glucose and ABA. Our data highlights the presence of a genetic network which consists of four interacting QTLs and controls germination under limiting environmental conditions.     

The extent and genetic basis of phenotypic divergence in life history traits in Mimulus guttatus

Differential natural selection acting on populations in contrasting environments often results in adaptive divergence in multivariate phenotypes. Multivariate trait divergence across populations could be caused by selection on pleiotropic alleles or through many independent loci with trait‐specific effects. Here, we assess patterns of association between a suite of traits contributing to life history divergence in the common monkey flower, Mimulus guttatus, and examine the genetic architecture underlying these correlations. A common garden survey of 74 populations representing annual and perennial strategies from across the native range revealed strong correlations between vegetative and reproductive traits. To determine whether these multitrait patterns arise from pleiotropic or independent loci, we mapped QTLs using an approach combining high‐throughput sequencing with bulk segregant analysis on a cross between populations with divergent life histories. We find extensive pleiotropy for QTLs related to flowering time and stolon production, a key feature of the perennial strategy. Candidate genes related to axillary meristem development colocalize with the QTLs in a manner consistent with either pleiotropic or independent QTL effects. Further, these results are analogous to previous work showing pleiotropy‐mediated genetic correlations within a single population of M. guttatus experiencing heterogeneous selection. Our findings of strong multivariate trait associations and pleiotropic QTLs suggest that patterns of genetic variation may determine the trajectory of adaptive divergence.     

Genetic variation in pleiotropy: differential epistasis as a source of variation in the allometric relationship between long bone lengths and body weight

Pleiotropy is an aspect of genetic architecture underlying the phenotypic covariance structure. The presence of genetic variation in pleiotropy is necessary for natural selection to shape patterns of covariation between traits. We examined the contribution of differential epistasis to variation in the intertrait relationship and the nature of this variation. Genetic variation in pleiotropy was revealed by mapping quantitative trait loci (QTLs) affecting the allometry of mouse limb and tail length relative to body weight in the mouse-inbred strain LG/J by SM/J intercross. These relationship QTLs (rQTLs) modify relationships between the traits affected by a common pleiotropic locus. We detected 11 rQTLs, mostly affecting allometry of multiple bones. We further identified epistatic interactions responsible for the observed allometric variation. Forty loci that interact epistatically with the detected rQTLs were identified. We demonstrate how these epistatic interactions differentially affect the body size variance and the covariance of traits with body size. We conclude that epistasis, by differentially affecting both the canalization and mean values of the traits of a pleiotropic domain, causes variation in the covariance structure. Variation in pleiotropy maintains evolvability of the genetic architecture, in particular the evolvability of its modular organization.     

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

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

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.     

A dissection model for mapping complex traits

Many quantitative traits are composites of other traits that contribute differentially to genetic variation. Quantitative trait locus (QTL) mapping of these composite traits can benefit by incorporating the mechanistic process of how their formation is mediated by the underlying components. We propose a dissection model by which to map these interconnected components traits under a joint likelihood setting. The model can test how a composite trait is determined by pleiotropic QTLs for its component traits or jointly by different sets of QTLs each responsible for a different component. The model can visualize the pattern of time‐varying genetic effects for individual components and their impacts on composite traits. The dissection model was used to map two composite traits, stemwood volume growth decomposed into its stem height, stem diameter and stem form components for Euramerican poplar adult trees, and total lateral root length constituted by its average lateral root length and lateral root number components for Euphrates poplar seedlings. We found the pattern of how QTLs for different components contribute to phenotypic variation in composite traits. The detailed understanding of the genetic machineries of composite traits will not only help in the design of molecular breeding in plants and animals, but also shed light on the evolutionary processes of quantitative traits under natural selection.     

Genetic determinants of atherosclerosis,obesity, and energy balance in consomic mice

Metabolic diseases such as obesity and atherosclerosis result from complex interactions between environmental factors and genetic variants. A panel of chromosome substitution strains (CSSs) was developed to characterize genetic and dietary factors contributing to metabolic diseases and other biological traits and biomedical conditions. Our goal here was to identify quantitative trait loci (QTLs) contributing to obesity, energy expenditure, and atherosclerosis. Parental strains C57BL/6 and A/J together with a panel of 21 CSSs derived from these progenitors were subjected to chronic feeding of rodent chow and atherosclerotic (females) or diabetogenic (males) test diets, and evaluated for a variety of metabolic phenotypes including several traits unique to this report, namely fat pad weights, energy balance, and atherosclerosis. A total of 297 QTLs across 35 traits were discovered, two of which provided significant protection from atherosclerosis, and several dozen QTLs modulated body weight, body composition, and circulating lipid levels in females and males. While several QTLs confirmed previous reports, most QTLs were novel. Finally, we applied the CSS quantitative genetic approach to energy balance, and identified three novel QTLs controlling energy expenditure and one QTL modulating food intake. Overall, we identified many new QTLs and phenotyped several novel traits in this mouse model of diet-induced metabolic diseases.     

QTL mapping for sexually dimorphic fitness-related traits in wild bighorn sheep

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.     

Exploring the genetic characteristics of 93-11 and Nipponbare recombination inbred lines based on the GoldenGate SNP assay

Understanding genetic characteristics in rice populations will facilitate exploring evolutionary mechanisms and gene cloning. Numerous molecular markers have been utilized in linkage map construction and quantitative trait locus (QTL) mappings. However, segregation-distorted markers were rarely considered, which prevented understanding genetic characteristics in many populations. In this study, we designed a 384-marker GoldenGate SNP array to genotype 283 recombination inbred lines (RILs) derived from 93-11 and Nipponbare Oryza sativa crosses. Using 294 markers that were highly polymorphic between parents, a linkage map with a total genetic distance of 1,583.2 cM was constructed, including 231 segregation-distorted markers. This linkage map was consistent with maps generated by other methods in previous studies. In total, 85 significant quantitative trait loci (QTLs) with phenotypic variation explained (PVE) values≥5% were identified. Among them, 34 QTLs were overlapped with reported genes/QTLs relevant to corresponding traits, and 17 QTLs were overlapped with reported sterility-related genes/QTLs. Our study provides evidence that segregation-distorted markers can be used in linkage map construction and QTL mapping. Moreover, genetic information resulting from this study will help us to understand recombination events and segregation distortion. Furthermore, this study will facilitate gene cloning and understanding mechanism of inter-subspecies hybrid sterility and correlations with important agronomic traits in rice.