A new statistical method for mapping QTLs underlying endosperm traits

Genetic expression for an endosperm trait in seeds of cereal crops may be controlled simultaneously by the triploid endosperm genotypes and the diploid maternal genotypes. However, current statistical methods for mapping quantitative trait loci （QTLs） underlying endosperm traits have not been effective in dealing with the putative maternal genetic effects. Combining the quantitative genetic model for diploid maternal traits with triploid endosperm traits, here we propose a new statistical method for mapping QTLs controlling endosperm traits with maternal genetic effects. This method applies the data set of both DNA molecular marker genotypes of each plant in segregation population and the quantitative observations of single endosperms in each plant to map QTL. The maximum likelihood method implemented via the expectation-maximization algorithm was used to the estimate parameters of a putative QTL. Since this method involves the maternal effect that may contribute to endosperm traits, it might be more congruent with the genetics of endosperm traits and more helpful to increasing the precision of QTL mapping. The simulation results show the proposed method provides accurate estimates of the QTL effects and locations with high statistical power.     

Framework for dissection of complex cytonuclear epistasis by a two-dimensional genome scan

Epistasis between cytoplasmic and nuclear genes is the primary genetic component of complex quantitative traits.Genetic dissection of cytonuclear epistasis is fundamentally important to understand the genetic architecture of complex traits.In this study,a two-dimensional genome scan strategy was employed to evaluate the contribution of cytoplasm,quantitative trait loci (QTL),QTL×QTL interactions and QTL×QTL×cytoplasm interactions to the phenotypic variation.The p-value and parameter value for each genetic effect were calculated by multiple regression analysis.A stepwise approach was suggested to build confidence in candidate QTL on the basis of q-value estimation,false discovery rate calculation and Bonferroni adjustment.A fine-scale grid scan strategy was proposed for further analysis of peaks of interest.Plant height in maize was used as an example to illustrate the efficiency of the two-dimensional genome scan strategy.     

Dissecting the architecture of a quantitative trait locus in yeast

Most phenotypic diversity in natural populations is characterized by differences in degree rather than in kind. Identification of the actual genes underlying these quantitative traits has proved difficult. As a result, little is known about their genetic architecture. The failures are thought to be due to the different contributions of many underlying genes to the phenotype and the ability of different combinations of genes and environmental factors to produce similar phenotypes. This study combined genome-wide mapping and a new genetic technique named reciprocal-hemizygosity analysis to achieve the complete dissection of a quantitative trait locus (QTL) in Saccharomyces cerevisiae. A QTL architecture was uncovered that was more complex than expected. Functional linkages both in cis and in trans were found between three tightly linked quantitative trait genes that are neither necessary nor sufficient in isolation. This arrangement of alleles explains heterosis (hybrid vigour), the increased fitness of the heterozygote compared with homozygotes. It also demonstrates a deficiency in current approaches to QTL dissection with implications extending to traits in other organisms, including human genetic diseases.     

Resolution of quantitative traits into Mendelian factors by using a complete linkage map of restriction fragment length polymorphisms

The conflict between the Mendelian theory of particulate inheritance and the observation of continuous variation for most traits in nature was resolved in the early 1900s by the concept that quantitative traits can result from segregation of multiple genes, modified by environmental effects. Although pioneering experiments showed that linkage could occasionally be detected to such quantitative trait loci (QTLs), accurate and systematic mapping of QTLs has not been possible because the inheritance of an entire genome could not be studied with genetic markers. The use of restriction fragment length polymorphisms (RFLPs) has made such investigations possible, at least in principle. Here, we report the first use of a complete RFLP linkage map to resolve quantitative traits into discrete Mendelian factors, in an interspecific back-cross of tomato. Applying new analytical methods, we mapped at least six QTLs controlling fruit mass, four QTLs for the concentration of soluble solids and five QTLs for fruit pH. This approach is broadly applicable to the genetic dissection of quantitative inheritance of physiological, morphological and behavioural traits in any higher plant or animal.     

Advances on methods for mapping QTL in plant

Advances on methods for mapping quantitative trait loci (QTL) are firstly summarized. Then, some new methods, including mapping multiple QTL, fine mapping of QTL, and mapping QTL for dynamic traits, are mainly described. Finally, some future prospects are proposed, including how to dig novel genes in the germplasm resource, map expression QTL (eQTL) by the use of all markers, phenotypes and micro-array data, identify QTL using genetic mating designs and detect viability loci. The purpose is to direct plant geneticists to choose a suitable method in the inheritance analysis of quantitative trait and in search of novel genes in germplasm resource so that more potential genetic information can be uncovered.     

Statistical approaches in QTL mapping and molecular breeding for complex traits

Most of the important agronomic traits in crops,such as yield and quality,are complex traits affected by multiple genes with gene × gene interaction as well as gene × environment interaction.Understanding the genetic architecture of complex traits is a long-term task for quantitative geneticists and plant breeders who wish to design efficient breeding programs.Conventionally,the genetic properties of traits can be revealed by partitioning the total variation into variation components caused by specific genetic effects.With recent advances in molecular genotyping and high-throughput technology,the unraveling of the genetic architecture of complex traits by analyzing quantitative trait locus (QTL) has become possible.The improvement of complex traits has also been achieved by pyramiding individual QTL.In this review,we describe some statistical methods for QTL mapping that can be used to analyze QTL × QTL interaction and QTL × environment interaction,and discuss their applications in crop breeding for complex traits.     

Towards a resolution of the lek paradox

Genetic benefits in the shape of 'good genes' have been invoked to explain costly female choice in the absence of direct fitness benefits. Little genetic variance in fitness traits is expected, however, because directional selection tends to drive beneficial alleles to fixation. There seems to be little potential, therefore, for female choice to result in genetic benefits, giving rise to the 'lek paradox'. Nevertheless, evidence shows that genetic variance persists despite directional selection and genetic benefits of female choice are frequently reported. A theoretical solution to the lek paradox has been proposed on the basis of two assumptions: that traits are condition-dependent, and that condition shows high genetic variance. The observed genetic variability in sexual traits will be accounted for, because a proportion of the genetic variance in condition will be captured and expressed in the trait. Here we report results from experiments showing that male courtship rate in the dung beetle Onthophagus taurus is a condition-dependent trait that is preferred by females. More importantly, male condition has high genetic variance and is genetically correlated with courtship rate. Our results thereby represent a significant step towards a resolution of the lek paradox.     

Epistasis and balanced polymorphism influencing complex trait variation

Complex traits such as human disease, growth rate, or crop yield are polygenic, or determined by the contributions from numerous genes in a quantitative manner. Although progress has been made in identifying major quantitative trait loci (QTL), experimental constraints have limited our knowledge of small-effect QTL, which may be responsible for a large proportion of trait variation. Here, we identified and dissected a one-centimorgan chromosome interval in Arabidopsis thaliana without regard to its effect on growth rate, and examined the signature of historical sequence polymorphism among Arabidopsis accessions. We found that the interval contained two growth rate QTL within 210 kilobases. Both QTL showed epistasis; that is, their phenotypic effects depended on the genetic background. This amount of complexity in such a small area suggests a highly polygenic architecture of quantitative variation, much more than previously documented. One QTL was limited to a single gene. The gene in question displayed a nucleotide signature indicative of balancing selection, and its phenotypic effects are reversed depending on genetic background. If this region typifies many complex trait loci, then non-neutral epistatic polymorphism may be an important contributor to genetic variation in complex traits.     

LOD score exclusion analyses for candidate disease susceptibility genes using case-parents design

The focus of almost all the association studies of candidate genes is to test for their importance. We recently developed a LOD score approach that can be used to test against the importance of candidate genes for complex diseases and quantitative traits in random samples. As a complementary method to regular association analyses, our LOD score approach is powerful but still affected by the population admixture, though it is more conservative. To control the confounding effect of population heterogeneity, we develop here a LOD score exclusion analysis using case?parents design, the basic design of the transmission disequilibrium test (TDT) approach that is immune to population admixture. In the analysis, specific genetic effects and inheritance models at candidate genes can be analyzed and if a LOD score is ≤-2.0, the locus can be excluded from having an effect larger than that specified. Simulations show that this approach has reasonable power to exclude a candidate gene having small genetic effects if it is not a disease susceptibility locus (DSL) with sample size often employed in TDT studies. Similar to association analyses with the TDT in nuclear families, our exclusion analyses are generally not affected by population admixture. The exclusion analyses may be implemented to rule out candidate genes with no or minor genetic effects as supplemental analyses for the TDT. The utility of the approach is illustrated with an application to test the importance of vitamin D receptor (VDR) gene underlying the differential risk to osteoporosis.     

Bin-based model construction and analytical strategies for dissecting complex traits with chromosome segment substitution lines

Chromosome segment substitution lines have been created in several experimental models,including many plant and animal species,and are useful tools for the genetic analysis and mapping of complex traits.The traditional t-test is usually applied to identify a quantitative trait locus (QTL) that is contained within a chromosome segment to estimate the QTL’s effect.However,current methods cannot uncover the entire genetic structure of complex traits.For example,current methods cannot distinguish between main effects and epistatic effects.In this paper,a linear epistatic model was constructed to dissect complex traits.First,all the long substituted segments were divided into overlapping small bins,and each small bin was considered a unique independent variable.The genetic model for complex traits was then constructed.When considering all the possible main effects and epistatic effects,the dimensions of the linear model can become extremely high.Therefore,variable selection via stepwise regression (Bin-REG) was proposed for the epistatic QTL analysis in the present study.Furthermore,we tested the feasibility of using the LASSO (least absolute shrinkage and selection operator) algorithm to estimate epistatic effects,examined the fully Bayesian SSVS (stochastic search variable selection) approach,tested the empirical Bayes (E-BAYES) method,and evaluated the penalized likelihood (PENAL) method for mapping epistatic QTLs.Simulation studies suggested that all of the above methods,excluding the LASSO and PENAL approaches,performed satisfactorily.The Bin-REG method appears to outperform all other methods in terms of estimating positions and effects.     

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P?相似文献   

Variations in DNA elucidate molecular networks that cause disease

Identifying variations in DNA that increase susceptibility to disease is one of the primary aims of genetic studies using a forward genetics approach. However, identification of disease-susceptibility genes by means of such studies provides limited functional information on how genes lead to disease. In fact, in most cases there is an absence of functional information altogether, preventing a definitive identification of the susceptibility gene or genes. Here we develop an alternative to the classic forward genetics approach for dissecting complex disease traits where, instead of identifying susceptibility genes directly affected by variations in DNA, we identify gene networks that are perturbed by susceptibility loci and that in turn lead to disease. Application of this method to liver and adipose gene expression data generated from a segregating mouse population results in the identification of a macrophage-enriched network supported as having a causal relationship with disease traits associated with metabolic syndrome. Three genes in this network, lipoprotein lipase (Lpl), lactamase beta (Lactb) and protein phosphatase 1-like (Ppm1l), are validated as previously unknown obesity genes, strengthening the association between this network and metabolic disease traits. Our analysis provides direct experimental support that complex traits such as obesity are emergent properties of molecular networks that are modulated by complex genetic loci and environmental factors.     

二棱大麦数量性状相关遗传力和选择指数分析

以15个二棱大麦品种(系)为材料,用相关遗传力研究大麦数量性状的相关遗传,并计算分析籽粒产量和产量构成性状所组合的各种选择指数。结果表明:各性状与单株粒重的相关遗传力均低于单株粒重的遗传力,因而仅利用一个性状作间接选择的效率比对单株粒重作直接选择的效率低,在构成大麦产量的三要素中,着重提高单株穗数对产量的选择效率为最大;高产育种同时考虑与产量显著相关的性状比单纯对产量选择的效果好,其中以单株穗数、每穗粒数和籽粒产量结合起来选择的效果最佳。本文并对相关遗传力在相关遗传变异分析中的应用进行了讨论。     

用基因芯片技术分析干旱胁迫下生殖生长期大麦的基因表达

耐旱性是干旱地区稳定和增加大麦产量的一个关键因素。鉴定出与耐旱性相关的功能基因,一方面可了解大麦的耐旱机理,同时还可以促进利用生物技术来改良大麦的耐旱性。在研究中,2个在耐旱性上具有明显差异的大麦品种Tadmor(耐旱)和WI2291(干旱敏感)被选作材料,采用22000个ESTs(基因表达序列标签)的Affymetrix大麦基因芯片Barley1来分析生殖生长期干旱胁迫下2个大麦材料的差异表达基因。研究结果表明,干旱胁迫下2个大麦材料中有77个共调节基因,其中部分基因已被报道过可能与抗旱性相关。这些基因中已有功能注释的基因按其生物学功能被分为14组,猜测它们是干旱胁迫的响应基因,在抗旱性上可能不起重要作用,或者是必需的但单独不足以提高大麦的抗旱性。进一步比较2个材料差异表达的基因,发现二材料之间有372个受干旱调节基因的差异。这些基因中有功能注释基因的生物学功能中可分为15组,其中一些已被认为与抗旱性相关;而对那些未知功能的基因,推测可能亦在大麦的抗旱性上扮演一定的角色。研究所得结果可为阐述生殖生长期大麦的耐旱性机理提供新的认识。     

Evolutionary diversification of TTX-resistant sodium channels in a predator-prey interaction

Understanding the molecular genetic basis of adaptations provides incomparable insight into the genetic mechanisms by which evolutionary diversification takes place. Whether the evolution of common traits in different lineages proceeds by similar or unique mutations, and the degree to which phenotypic evolution is controlled by changes in gene regulation as opposed to gene function, are fundamental questions in evolutionary biology that require such an understanding of genetic mechanisms. Here we identify novel changes in the molecular structure of a sodium channel expressed in snake skeletal muscle, tsNa(V)1.4, that are responsible for differences in tetrodotoxin (TTX) resistance among garter snake populations coevolving with toxic newts. By the functional expression of tsNa(V)1.4, we show how differences in the amino-acid sequence of the channel affect TTX binding and impart different levels of resistance in four snake populations. These results indicate that the evolution of a physiological trait has occurred through a series of unique functional changes in a gene that is otherwise highly conserved among vertebrates.     

Genetic mechanisms of floral trait correlations in a natural population

Genetic correlations among traits are important in evolution, as they can constrain evolutionary change or reflect past selection for combinations of traits. Constraints and integration depend on whether the correlations are caused by pleiotropy or linkage disequilibrium, but these genetic mechanisms underlying correlations remain largely unknown in natural populations. Quantitative trait locus (QTL) mapping studies do not adequately address the mechanisms of within-population genetic correlations because they rely on crosses between distinct species, inbred lines or selected lines (see ref. 5), and they cannot distinguish moderate linkage disequilibrium from pleiotropy because they commonly rely on only one or two episodes of recombination. Here I report that after nine generations of enforced random mating (nine episodes of recombination), correlations between six floral traits in wild radish plants are unchanged, showing that pleiotropy generates the correlations. There is no evidence for linkage disequilibrium despite previous correlational selection acting on one functionally integrated pair of traits. This study provides direct evidence of the genetic mechanisms underlying correlations between quantitative traits in a natural population and suggests that there may be constraints on the independent evolution of pairs of highly correlated traits.