Statistical method for mapping QTLs for complex traits based on two backcross populations

Most important agronomic and quality traits of crops are quantitative in nature.The genetic variations in such traits are usually controlled by sets of genes called quantitative trait loci (QTLs),and the interactions between QTLs and the environment.It is crucial to understand the genetic architecture of complex traits to design efficient strategies for plant breeding.In the present study,a new experimental design and the corresponding statistical method are presented for QTL mapping.The proposed mapping population is composed of double backcross populations derived from backcrossing both homozygous parents to DH (double haploid) or RI (recombinant inbreeding) lines separately.Such an immortal mapping population allows for across-environment replications,and can be used to estimate dominance effects,epistatic effects,and QTL-environment interactions,remedying the drawbacks of a single backcross population.In this method,the mixed linear model approach is used to estimate the positions of QTLs and their various effects including the QTL additive,dominance,and epistatic effects,and QTL-environment interaction effects (QE).Monte Carlo simulations were conducted to investigate the performance of the proposed method and to assess the accuracy and efficiency of its estimations.The results showed that the proposed method could estimate the positions and the genetic effects of QTLs with high efficiency.     

小麦品质性状的QTL定位研究进展

本文系统地总结了国内外小麦品质性状QTL定位研究的主要性状、所用群体、标记类型、QTL定位所在的染色体位置及贡献率的大小,提出了小麦品质性状QTL定位中存在的问题,展望了小麦品质性状QTL定位的发展方向。     

Molecular dissection of genetic basis of significant correlation among five morphological traits in rice (Oryza sativa L.)

To enhance understanding of the genetic basis of trait correlation in rice, a recombinant inbred line (RIL) population (F₆ and F₇) from a cross between Zhenshan97 and HR5 was employed to identify main quantitative trait loci (QTLs) and epistatic QTL (E-QTL). Highly significant positive correlations were detected among five traits of heading date (HD), plant height (PH), panicle length (PL), flag leaf length (FLL) and flag leaf width (FLW) in 2 environments. Four to 8 main QTLs were detected for an individual trait. No E-QTL was detected for PH. One, 4, 4 and 5 E-QTLs were detected for FLL, HD, FLW and PL, respectively. Each E-QTL individually explained less than 3% of trait variation except E-QFll1. Comparison of QTL results was made in order to dissect the genetic basis of trait correlation. We found that main QTLs with pleiotropic effects and QTL clusters were the main genetic basis of trait correlation. No E-QTL had pleiotropic effects. E-QTL played an important role in the genetic basis of individual trait, but it made a little contribution to trait correlation.     

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.     

Methods for mapping QTLs underlying endosperm traits based on random hybridization design

Cereal grains are mainly composed of endosperms, which are humans’ staple food containing rich nutri- tious substances such as starch, protein and lipid. Many endosperm traits are related to grain yield and quality. Therefore, studying the genetic basis …     

The comparative analysis based on maize integrated QTL map and meta-analysis of plant height QTLs

Since the first publication of quantitative trait locus (QTL) localization using molecular markers[1], a large number of QTLs have been identified in different ge- netic backgrounds and environments. Affected by many factors, such as marker sets, experime…     

Primary analysis of QTG contribution to heterosis in upland cotton

In this paper, we analyzed the contribution of pure DNA factors to heterosis using quantitative trait genes (QTG) in two randomly selected strains from a recombinant inbred line of Gossypium hirsutum. According to a set of QTL mapping results, combined with analysis of DNA recombinant fragment sources in the two strains and QTL association analysis with their field traits, we hypothesize a view of “dominance + overdominance + epistasis”. That is, additive and additive epistasis may be the genetic basis of heterosis, and dominance, overdominance and epistasis may be the modes of heterosis action. Based on the heterosis results of this study, we also suggest a molecular mechanism for heterosis, and explain, in detail, with two randomly selected strains as examples. The male and female parent-derived additive epistatic QTLs of upper half mean length in LG01 and LG03 produced a trait variance of 2.99–3.52 compared with the female parent-derived loci. The trait of bolls per plant was controlled by two pairs of additive epistatic QTLs in LG02 and LG07, which were derived from both female and male parents. The QTLs were reciprocally interacted and produced a trait variance of 0.86. An initial concept of “super-hybrid cotton” was raised according to the nature of additive effect, that is genetic stability.     

Dynamic analysis of QTL for plant height at different developmental stages in maize （Zea mays L.）

Plantheightisoneofimportantagronomictraitsinmaizebreeding.Inthepastfewyears,toincreasetheplantingdensityandpreventplantsfromlodging,studiesonthegeneticmechanismofplantheightweregivengreatattentionto.Sincethe1990s,molecularmarkershaveprovidedapowerfultooltostudythetraitofplantheightatthemolecularlevel[1—3].Butmostofresearchforplantheightonlyfocusedondataatmaturestage.Tillnow,about70genesorQTLshavebeenlocated[4].Moreover,somegeneshavebeenevencloned[5—7].Duringthevege-tativegrowthperiod,plant…     

Influence of outliers on QTL mapping for complex traits

A method was proposed for the detection of outliers and influential observations in the framework of a mixed linear model, prior to the quantitative trait locus （QTL） mapping analysis. We investigated the impact of outliers on QTL mapping for complex traits in a mouse BXD population, and observed that the dropping of outliers could provide the evidence of additional QTL and epistatic loci affecting the 1 stBrain-OB and the 2ndBrain-OB in a cross of the abovementioned population. The results could also reveal a remarkable increase in estimating heritabilities of QTL in the absence of outliers. In addition, simulations were conducted to investigate the detection powers and false discovery rates （FDRs） of QTLs in the presence and absence of outliers. The results suggested that the presence of a small proportion of outliers could increase the FDR and hence decrease the detection power of QTLs. A drastic increase could be obtained in the estimates of standard errors for position, additive and additive× environment interaction effects of QTLs in the presence of outliers.     

Quantitative trait loci （QTLs） for quality traits related to protein and starch in wheat

Quality traits in wheat （Triticum aestirum L.） were studied by quantitative trait locus （QTL） analysis in a recombinant inbred line （RIL） population, a set of 131 lines derived from Chuan 35050 × Shannong 483 cross （ChSh）. Grains from RILs were assayed for 21 quality traits related to protein and starch. A total of 35 putative QTLs for 19 traits with a single QTL explaining 7.99-40.52% of phenotypic variations were detected on 10 chromosomes, 1D, 2A, 2D, 3B, 3D, 5A, 6A, 6B, 6D, and 7B. The additive effects of 30 QTLs were positive, contributed by Chuan 35050, the remaining 5 QTLs were negative with the additive effect contributed by Shannong 483. For protein traits, 15 QTLs were obtained and most of them were located on chromosomes 1 D, 3B and 6D, while 20 QTLs for starch traits were detected and most of them were located on chromosomes 3D, 6B and 7B. Only 7 QTLs for protein and starch traits were co-located in three regions on chromosomes 1D, 2A and 2D. These protein and starch trait QTLs showed a distinct distribution pattern in certain regions and chromosomes. Twenty-two QTLs were clustered in 6 regions of 5 chromosomes. Two QTL clusters for protein traits were located on chromosomes 1D and 3B, respectively, three clusters for starch traits on chromosomes 3D, 6B and 7B, and one cluster including protein and starch traits on chromosome 1D.     

玉米产量相关性状的QTL定位与剖析

玉米因其自身具有高产潜质而成为了当今世界最重要的粮食作物之一.玉米产量是复杂的数量性状,由许多主/微效基因控制,易受各种环境因素影响.果穗是玉米的主要收获器官,籽粒性状是玉米品质的重要体现,因此发掘玉米穗部性状和籽粒性状相关QTL对玉米的遗传改良,培育优质高产的玉米具有重要意义.本研究白刺包谷(P2)和妻染黄(P13)为亲本构建了包含152个家系的F2∶3作图群体,选择在两亲本间具有多态性的176个微卫星标记构建遗传图谱,对产量相关性状进行了单环境的QTL定位与分析.最终定位到了14个QTL,分布在除9号染色体外的其余9条染色体上,单个QTL可解释的表型变异率为4.9％～18.8％.值得注意的是,在6号染色体上的百粒重和穗行数的一致性QTL(qHKW06-1和qERN06-1)与8号染色体上的穗行数QTL(qERN08-1)是本研究中特有的,其中qERN08-1解释了12.4％的表型变异率.     

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.     

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.     

A genome scan for quantitative trait loci affecting grain yield and its components of maize both in single-and two-locus levels

Maize is one of the most important cereal crops in the world. The hybrid yield advantage is responsible for about 10 percent of the total global maize production of 550 Mt[1]. It is exigent to study the yield traits so as to improve the hybrids per se in …     

Mapping QTLs on BTA6 affecting milk production traits in a Chinese Holstein population

To make marker-assisted selection (MAS) more effi-cient in improving economically important traits for farm animals, one important factor is to find markers linked to the quantitative trait loci (QTL) as closely as possible. So it is best to use the gene per se underlying the QTL. A whole genome scan for QTL is the prerequisite in the be-ginning, then mapping on some special important chro-mosomes, and then fine mapping in some target region on given chromosome aiming at gene cloning and c…     

Comparative mapping of rice root traits in seedlings grown in nutrient or non-nutrient solution

The component and amount of nutrient in the growth medium are the major factors affecting root growth.For the systematic dissection of root gene expression,evaluation of nutrient and non-nutrient solutions was conducted for their effect on root traits and quantitative trait loci(QTL)mapping.Three rice root parameters,maximum root length(MRL),root dry weight(RDW),and root/ shoot ratio of dry weight(RSR),were characterized within a double haploid(DH)population from a cross of ZYQ8(indica)and JX17(japonica).The value of the three root traits in two parents all decreased under the nutrient condition compared to those under the nonnutrient condition,of which RSR decreased up to 2.6-fold on average.In the DH population,more than 70 % lines in MRL,94 % lines in RDW,and all the lines in RSR were scored lower.In total,eight QTLs were identified in nutrient system(5 from JX17 alleles and 3 from ZYQ8 alleles)while five QTLs were detected in non-nutrient system(4 from JX17 alleles and 1 from ZYQ8 alleles).Of them,one QTL for RSR was shared by both culturing systems,seven QTLs were specific in nutrient system and the other four QTLs were specific in non-nutrient system.All 13 QTLs were distributed over 7 rice chromosomes-2,3,4,5,6,9 and 10,respectively.     

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.     

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.     

Analysis of digenic epistatic effects and QE interaction effects QTL controlling grain weight in rice

Immortalized F(2) population of rice (Oryza sativa L.) was developed by randomly mating F(1) among recombinant inbred (RI) lines derived from (Zhenshan 97B x Minghui 63), which allowed replications within and across environments. QTL (quantitative trait loci) mapping analysis on kilo-grain weight of immortalized F(2) population was performed by using newly developed software for QTL mapping, QTLMapper 2.0. Eleven distinctly digenic epistatic loci included a total of 15 QTL were located on eight chromosomes. QTL main effects of additive, dominance, and additive x additive, additive x dominance, and dominance x dominance interactions were estimated. Interaction effects between QTL main effects and environments (QE) were predicted. Less than 40% of single effects, most of which were additive effects, for identified QTL were significant at 5% level. The directional difference for QTL main effects suggested that these QTL were distributed in parents in the repulsion phase. This should make it feasible to improve kilo-grain weight of both parents by selecting appropriate new recombinants. Only few of the QE interaction effects were significant. Application prospect for QTL mapping achievements in genetic breeding was discussed.