Linear models for joint association and linkage QTL mapping

Background

Populational linkage disequilibrium and within-family linkage are commonly used for QTL mapping and marker assisted selection. The combination of both results in more robust and accurate locations of the QTL, but models proposed so far have been either single marker, complex in practice or well fit to a particular family structure.

Results

We herein present linear model theory to come up with additive effects of the QTL alleles in any member of a general pedigree, conditional to observed markers and pedigree, accounting for possible linkage disequilibrium among QTLs and markers. The model is based on association analysis in the founders; further, the additive effect of the QTLs transmitted to the descendants is a weighted (by the probabilities of transmission) average of the substitution effects of founders'' haplotypes. The model allows for non-complete linkage disequilibrium QTL-markers in the founders. Two submodels are presented: a simple and easy to implement Haley-Knott type regression for half-sib families, and a general mixed (variance component) model for general pedigrees. The model can use information from all markers. The performance of the regression method is compared by simulation with a more complex IBD method by Meuwissen and Goddard. Numerical examples are provided.

Conclusion

The linear model theory provides a useful framework for QTL mapping with dense marker maps. Results show similar accuracies but a bias of the IBD method towards the center of the region. Computations for the linear regression model are extremely simple, in contrast with IBD methods. Extensions of the model to genomic selection and multi-QTL mapping are straightforward.     

Mixed linear model approach for mapping quantitative trait loci underlying crop seed traits

The crop seed is a complex organ that may be composed of the diploid embryo, the triploid endosperm and the diploid maternal tissues. According to the genetic features of seed characters, two genetic models for mapping quantitative trait loci (QTLs) of crop seed traits are proposed, with inclusion of maternal effects, embryo or endosperm effects of QTL, environmental effects and QTL-by-environment (QE) interactions. The mapping population can be generated either from double back-cross of immortalized F₂ (IF₂) to the two parents, from random-cross of IF₂ or from selfing of IF₂ population. Candidate marker intervals potentially harboring QTLs are first selected through one-dimensional scanning across the whole genome. The selected candidate marker intervals are then included in the model as cofactors to control background genetic effects on the putative QTL(s). Finally, a QTL full model is constructed and model selection is conducted to eliminate false positive QTLs. The genetic main effects of QTLs, QE interaction effects and the corresponding P-values are computed by Markov chain Monte Carlo algorithm for Gaussian mixed linear model via Gibbs sampling. Monte Carlo simulations were performed to investigate the reliability and efficiency of the proposed method. The simulation results showed that the proposed method had higher power to accurately detect simulated QTLs and properly estimated effect of these QTLs. To demonstrate the usefulness, the proposed method was used to identify the QTLs underlying fiber percentage in an upland cotton IF₂ population. A computer software, QTLNetwork-Seed, was developed for QTL analysis of seed traits.     

Mapping of Genomic Regions (Quantitative Trait Loci) Controlling Production and Quality in Industrial Cultures of the Edible Basidiomycete Pleurotus ostreatus

Industrial production of the edible basidiomycete Pleurotus ostreatus (oyster mushroom) is based on a solid fermentation process in which a limited number of selected strains are used. Optimization of industrial mushroom production depends on improving the culture process and breeding new strains with higher yields and productivities. Traditionally, fungal breeding has been carried out by an empirical trial and error process. In this study, we used a different approach by mapping quantitative trait loci (QTLs) controlling culture production and quality within the framework of the genetic linkage map of P. ostreatus. Ten production traits and four quality traits were studied and mapped. The production QTLs identified explain nearly one-half of the production variation. More interestingly, a single QTL mapping to the highly polymorphic chromosome VII appears to be involved in control of all the productivity traits studied. Quality QTLs appear to be scattered across the genome and to have less effect on the variation of the corresponding traits. Moreover, some of the new hybrid strains constructed in the course of our experiments had production or quality values higher than those of the parents or other commercial strains. This approach opens the possibility of marker-assisted selection and breeding of new industrial strains of this fungus.     

Mapping of genomic regions (quantitative trait loci) controlling production and quality in industrial cultures of the edible basidiomycete Pleurotus ostreatus

Industrial production of the edible basidiomycete Pleurotus ostreatus (oyster mushroom) is based on a solid fermentation process in which a limited number of selected strains are used. Optimization of industrial mushroom production depends on improving the culture process and breeding new strains with higher yields and productivities. Traditionally, fungal breeding has been carried out by an empirical trial and error process. In this study, we used a different approach by mapping quantitative trait loci (QTLs) controlling culture production and quality within the framework of the genetic linkage map of P. ostreatus. Ten production traits and four quality traits were studied and mapped. The production QTLs identified explain nearly one-half of the production variation. More interestingly, a single QTL mapping to the highly polymorphic chromosome VII appears to be involved in control of all the productivity traits studied. Quality QTLs appear to be scattered across the genome and to have less effect on the variation of the corresponding traits. Moreover, some of the new hybrid strains constructed in the course of our experiments had production or quality values higher than those of the parents or other commercial strains. This approach opens the possibility of marker-assisted selection and breeding of new industrial strains of this fungus.     

A mixed-model approach to association mapping using pedigree information with an illustration of resistance to Phytophthora infestans in potato

Association or linkage disequilibrium (LD)-based mapping strategies are receiving increased attention for the identification of quantitative trait loci (QTL) in plants as an alternative to more traditional, purely linkage-based approaches. An attractive property of association approaches is that they do not require specially designed crosses between inbred parents, but can be applied to collections of genotypes with arbitrary and often unknown relationships between the genotypes. A less obvious additional attractive property is that association approaches offer possibilities for QTL identification in crops with hard to model segregation patterns. The availability of candidate genes and targeted marker systems facilitates association approaches, as will appropriate methods of analysis. We propose an association mapping approach based on mixed models with attention to the incorporation of the relationships between genotypes, whether induced by pedigree, population substructure, or otherwise. Furthermore, we emphasize the need to pay attention to the environmental features of the data as well, i.e., adequate representation of the relations among multiple observations on the same genotypes. We illustrate our modeling approach using 25 years of Dutch national variety list data on late blight resistance in the genetically complex crop of potato. As markers, we used nucleotide binding-site markers, a specific type of marker that targets resistance or resistance-analog genes. To assess the consistency of QTL identified by our mixed-model approach, a second independent data set was analyzed. Two markers were identified that are potentially useful in selection for late blight resistance in potato.     

<Emphasis Type="Italic">In silico</Emphasis>discovery of gene-coding variants in murine quantitative trait loci using strain-specific genome sequence databases

Background  

The identification of genes underlying complex traits has been aided by quantitative trait locus (QTL) mapping approaches, which in turn have benefited from advances in mammalian genome research. Most recently, whole-genome draft sequences and assemblies have been generated for mouse strains that have been used for a large fraction of QTL mapping studies. Here we show how such strain-specific mouse genome sequence databases can be used as part of a high-throughput pipeline for the in silico discovery of gene-coding variations within murine QTLs. As a test of this approach we focused on two QTLs on mouse chromosomes 1 and 13 that are involved in physical dependence on alcohol.     

Efficient QTL detection for nonhost resistance in wild lettuce: backcross inbred lines versus F2 population

In plants, several population types [F₂, recombinant inbred lines, backcross inbred lines (BILs), etc.] are used for quantitative trait locus (QTL) analyses. However, dissection of the trait of interest and subsequent confirmation by introgression of QTLs for breeding purposes has not been as successful as that predicted from theoretical calculations. More practical knowledge of different QTL mapping approaches is needed. In this recent study, we describe the detection and mapping of quantitative resistances to downy mildew in a set of 29 BILs of cultivated lettuce (L. sativa) containing genome segments introgressed from wild lettuce (L. saligna). Introgression regions that are associated with quantitative resistance are considered to harbor a QTL. Furthermore, we compare this with results from an already existing F₂ population derived from the same parents. We identified six QTLs in our BIL approach compared to only three in the F₂ approach, while there were two QTLs in common. We performed a simulation study based on our actual data to help us interpret them. This revealed that two newly detected QTLs in the BILs had gone unnoticed in the F₂, due to a combination of recessiveness of the trait and skewed segregation, causing a deficit of the wild species alleles. This study clearly illustrates the added value of extended genetic studies on two different population types (BILs and F₂) to dissect complex genetic traits.     

QTL sequencing strategy to map genomic regions associated with resistance to ascochyta blight in chickpea

Whole‐genome sequencing‐based bulked segregant analysis (BSA) for mapping quantitative trait loci (QTL) provides an efficient alternative approach to conventional QTL analysis as it significantly reduces the scale and cost of analysis with comparable power to QTL detection using full mapping population. We tested the application of next‐generation sequencing (NGS)‐based BSA approach for mapping QTLs for ascochyta blight resistance in chickpea using two recombinant inbred line populations CPR‐01 and CPR‐02. Eleven QTLs in CPR‐01 and six QTLs in CPR‐02 populations were mapped on chromosomes Ca1, Ca2, Ca4, Ca6 and Ca7. The QTLs identified in CPR‐01 using conventional biparental mapping approach were used to compare the efficiency of NGS‐based BSA in detecting QTLs for ascochyta blight resistance. The QTLs on chromosomes Ca1, Ca4, Ca6 and Ca7 overlapped with the QTLs previously detected in CPR‐01 using conventional QTL mapping method. The QTLs on chromosome Ca4 were detected in both populations and overlapped with the previously reported QTLs indicating conserved region for ascochyta blight resistance across different chickpea genotypes. Six candidate genes in the QTL regions identified using NGS‐based BSA on chromosomes Ca2 and Ca4 were validated for their association with ascochyta blight resistance in the CPR‐02 population. This study demonstrated the efficiency of NGS‐based BSA as a rapid and cost‐effective method to identify QTLs associated with ascochyta blight in chickpea.     

Bayesian association mapping of multiple quantitative trait loci and its application to the analysis of genetic variation among <Emphasis Type="Italic">Oryza sativa</Emphasis> L. germplasms

One way to use a crop germplasm collection directly to map QTLs without using line-crossing experiments is the whole genome association mapping. A major problem with association mapping is the presence of population structure, which can lead to both false positives and failure to detect genuine associations (i.e., false negatives). Particularly in highly selfing species such as Asian cultivated rice, high levels of population structure are expected and therefore the efficiency of association mapping remains almost unknown. Here, we propose an approach that combines a Bayesian method for mapping multiple QTLs with a regression method that directly incorporates estimates of population structure. That is, the effects due to both multiple QTLs and population structure were included in our statistical model. We evaluated the efficiency of our approach in simulated- and real-trait analyses of a rice germplasm collection. Simulation analyses based on real marker data showed that our model could suppress both false-positive and false-negative rates and the error of estimation of genetic effects over single QTL models, indicating that our model has statistically desirable attributes over single QTL models. As real traits, we analyzed the size and shape of milled rice grains and found significant markers that may be linked to QTLs reported previously. Association mapping should have good prospects in highly selfing species such as rice if proper methods are adopted. Our approach will be useful for the whole genome association mapping of various selfing crop species.     

Mapping QTLs with epistatic effects and QTL×environment interactions for plant height using a doubled haploid population in cultivated wheat

Quantitative trait loci (QTLs) for plant height in wheat (Triticum aestivum L.) were studied using a set of 168 doubled haploid (DH) lines, which were derived from the cross Huapei 3/Yumai 57. A genetic linkage map was constructed using 283 SSR and 22 EST-SSR markers. The DH population and the parents were evaluated for wheat plant height in 2005 and 2006 in Tai'an and 2006 in Suzhou. QTL analyses were performed using the software of QTLNetwork version 2.0 based on the mixed linear model. Four additive QTLs and five pairs of epistatic effects were detected, which were distributed on chromosomes 3A, 4B, 4D, 5A, 6A, 7B, and 7D. Among them, three additive QTLs and three pairs of epistatic QTLs showed QTLxenvironment interactions (QEs). Two major QTLs, QphAB and Qph4D, which accounted for 14.51 % and 20.22% of the phenotypic variation, were located similar to the reported locations of the dwarfing genes Rhtl and Rht2, respectively. The Qph3A-2 with additive effect was not reported in previous linkage mapping studies. The total QTL ef fects detected for the plant height explained 85.04% of the phenotypic variation, with additive effects 46.07%, epistatic effects 19.89%, and QEs 19.09%. The results showed that both additive effects and epistatic effects were important genetic bases of wheat plant height, which were subjected to environmental modifications, and caused dramatic changes in phenotypic effects. The information obtained in this study will be useful for manipulating the QTLs for wheat plant height by molecular marker-assisted selection (MAS).     

QTL Analysis of High Thermotolerance with Superior and Downgraded Parental Yeast Strains Reveals New Minor QTLs and Converges on Novel Causative Alleles Involved in RNA Processing

Revealing QTLs with a minor effect in complex traits remains difficult. Initial strategies had limited success because of interference by major QTLs and epistasis. New strategies focused on eliminating major QTLs in subsequent mapping experiments. Since genetic analysis of superior segregants from natural diploid strains usually also reveals QTLs linked to the inferior parent, we have extended this strategy for minor QTL identification by eliminating QTLs in both parent strains and repeating the QTL mapping with pooled-segregant whole-genome sequence analysis. We first mapped multiple QTLs responsible for high thermotolerance in a natural yeast strain, MUCL28177, compared to the laboratory strain, BY4742. Using single and bulk reciprocal hemizygosity analysis we identified MKT1 and PRP42 as causative genes in QTLs linked to the superior and inferior parent, respectively. We subsequently downgraded both parents by replacing their superior allele with the inferior allele of the other parent. QTL mapping using pooled-segregant whole-genome sequence analysis with the segregants from the cross of the downgraded parents, revealed several new QTLs. We validated the two most-strongly linked new QTLs by identifying NCS2 and SMD2 as causative genes linked to the superior downgraded parent and we found an allele-specific epistatic interaction between PRP42 and SMD2. Interestingly, the related function of PRP42 and SMD2 suggests an important role for RNA processing in high thermotolerance and underscores the relevance of analyzing minor QTLs. Our results show that identification of minor QTLs involved in complex traits can be successfully accomplished by crossing parent strains that have both been downgraded for a single QTL. This novel approach has the advantage of maintaining all relevant genetic diversity as well as enough phenotypic difference between the parent strains for the trait-of-interest and thus maximizes the chances of successfully identifying additional minor QTLs that are relevant for the phenotypic difference between the original parents.     

Mapping QTLs with epistatic effects and QTL×environment interactions for plant height using a doubled haploid population in cultivated wheat

Quantitative trait loci (QTLs) for plant height in wheat (Triticum aestivum L.) were studied using a set of 168 doubled haploid (DH) lines, which were derived from the cross Huapei 3/Yumai 57. A genetic linkage map was constructed using 283 SSR and 22 EST-SSR markers. The DH population and the parents were evaluated for wheat plant height in 2005 and 2006 in Tai’an and 2006 in Suzhou. QTL analyses were performed using the software of QTLNetwork version 2.0 based on the mixed linear model. Four additive QTLs and five pairs of epistatic effects were detected, which were distributed on chromosomes 3A, 4B, 4D, 5A, 6A, 7B, and 7D. Among them, three additive QTLs and three pairs of epistatic QTLs showed QTL×environment interactions (QEs). Two major QTLs, Qph4B and Qph4D, which accounted for 14.51% and 20.22% of the phenotypic variation, were located similar to the reported locations of the dwarfing genes Rht1 and Rht2, respectively. The Qph3A-2 with additive effect was not reported in previous linkage mapping studies. The total QTL effects detected for the plant height explained 85.04% of the phenotypic variation, with additive effects 46.07%, epistatic effects 19.89%, and QEs 19.09%. The results showed that both additive effects and epistatic effects were important genetic bases of wheat plant height, which were subjected to environmental modifications, and caused dramatic changes in phenotypic effects. The information obtained in this study will be useful for manipulating the QTLs for wheat plant height by molecular marker-assisted selection (MAS).     

Quantitative genetic dissection of complex traits in a QTL-mapping pedigree

This paper summarizes and modifies quantitative genetic analyses on a pedigree used to map genetic factors (i.e., QTLs) underlying a complex trait. The total genetic variance can be exactly estimated based on the F₂ family derived from two homozygous parents for alternative alleles at all QTLs of interest. The parents, F₁ hybrids, and two backcrosses are combined to each parent, and the total number of QTLs and the number of dominant QTLs are estimated under the assumptions of gene association with the two parents, equal gene effect, no linkage, and no epistasis among QTLs. Further relaxation for each of the assumptions are made in detail. The biometric estimator for the QTL number and action mode averaged over the entire genome could provide some basic and complementary information to QTL mapping designed to detect the effect and location of specific genetic factors.     

两个水稻骨干恢复系重要农艺性状的遗传基础研究

水稻骨干恢复系是指在杂交稻育种中广泛应用的一类恢复系。探明骨干恢复系的遗传基础,发掘其重要农艺性状基因/QTL,对分子标记辅助选择水稻恢复系育种具有重要应用价值。本研究以生产上广泛应用的三系骨干恢复系成恢727和两系骨干恢复系9311为亲本,培育了具有250个系的重组自交系群体。分别在2015年三亚和2016年合肥两个环境下进行了9个重要农艺性状表型和SSR分子标记基因型鉴定,用SAS9.2分析表型数据,用QTL Ici Mapping v4.1进行QTL定位分析。在三亚和合肥两个环境下共检测到39个QTL,三亚检测到16个,分布于第1、2、4、7、8、10、11和12染色体上;合肥检测24个,分布于第1、2、3、7、8、9、10和12染色体上。其中qPH1-1在三亚和合肥两个环境下都能检测到,加性效应分别为-1.75和-2.46。在检测到的39个QTL中,有24个QTL的增效等位基因来自恢复系成恢727,15个QTL的增效等位基因来自9311。共计有26个QTL曾被前人定位,13个属于尚未见文献报道的新QTL。另外,在RM279~RM521、RM336~RM3534、RM25~RM547、RM553~RM160、RM222~RM271区段内检测到5个多效性QTL位点。其中RM25~RM547位点与已经克隆的基因Ghd8位置相近。RM553~RM160位点是一个新的多效性位点,分别控制每穗实粒数、单株产量和结实率,而且效应和表型变异贡献率都较大。其余3个位点在前人的研究中分别有所报道,但其多效性则是在本研究中首次发现。在本研究新发掘到的QTL中,控制穗数的QTL qPN12-1,控制穗长的QTL qPL1-2和qPL10-1,控制总粒数的QTL qSNP2-1和qSNP10-1,控制结实率的QTL qSF3-1,控制千粒重QTL qTGW7-1和控制产量的QTL qGY1-1效应均比较大,解释的表型遗传变异比例也较高。本研究的结果将会为相关性状QTL的精细定位、克隆和育种应用奠定基础。     

A mixed model QTL analysis for sugarcane multiple-harvest-location trial data

Sugarcane-breeding programs take at least 12 years to develop new commercial cultivars. Molecular markers offer a possibility to study the genetic architecture of quantitative traits in sugarcane, and they may be used in marker-assisted selection to speed up artificial selection. Although the performance of sugarcane progenies in breeding programs are commonly evaluated across a range of locations and harvest years, many of the QTL detection methods ignore two- and three-way interactions between QTL, harvest, and location. In this work, a strategy for QTL detection in multi-harvest-location trial data, based on interval mapping and mixed models, is proposed and applied to map QTL effects on a segregating progeny from a biparental cross of pre-commercial Brazilian cultivars, evaluated at two locations and three consecutive harvest years for cane yield (tonnes per hectare), sugar yield (tonnes per hectare), fiber percent, and sucrose content. In the mixed model, we have included appropriate (co)variance structures for modeling heterogeneity and correlation of genetic effects and non-genetic residual effects. Forty-six QTLs were found: 13 QTLs for cane yield, 14 for sugar yield, 11 for fiber percent, and 8 for sucrose content. In addition, QTL by harvest, QTL by location, and QTL by harvest by location interaction effects were significant for all evaluated traits (30 QTLs showed some interaction, and 16 none). Our results contribute to a better understanding of the genetic architecture of complex traits related to biomass production and sucrose content in sugarcane.     

高丹草氢氰酸含量性状的QTL定位分析

为了深入开展高丹草低氢氰酸含量性状的QTL精细定位、基因图位克隆、功能解析及分子标记辅助育种,该研究以二倍体杂交高丹草F_2代群体500个分离单株无性系及其亲本为材料,在课题组前期已构建出的高丹草高密度分子遗传连锁图谱的基础上,利用区间作图法对两年两地测定的高丹草氢氰酸含量性状进行了QTL定位分析。结果显示:(1)在4个不同环境下高丹草氢氰酸含量性状的广义遗传率分别为61.70%、72.05%、40.16%和69.25%,表明氢氰酸含量是既受环境影响又受微效多基因控制的数量性状,而且其群体测定值频率呈明显单峰正态性分布特点,符合QTL定位要求。(2)在LOD2.5的条件下,共检测到16个与氢氰酸含量性状相关的QTLs,其分布在LG1、LG2、LG4、LG6、LG7、LG8和LG10连锁群上。(3)16个QTLs中能重复检测到的稳定QTLs有9个,遗传贡献率范围为1.17%～39.9%,其中贡献率大于20%的主效QTLs有Qcn2-2、Qcn4-1、Qcn6和Qcn6-1共4个。该研究结果明确了各QTLs的遗传效应和分子标记位点。     

Novel linkage mapping approach using DNA pooling in human and animal genetics. II. Detection of quantitative traits loci in dairy cattle

Selective DNA pooling is an advanced methodology for linkage mapping of quantitative trait loci (QTL) in farm animals. The principle is based on densitometric estimates of marker allele frequency in pooled DNA samples of phenotypically extreme individuals from half-sib, backcross and F(2) experimental designs in farm animals. This methodology provides a rapid and efficient analysis of a large number of individuals with short tandem repeat markers that are essential to detect QTL through the genome - wide searching approach. Several strategies involving whole genome scanning with a high statistical power have been developed for systematic search to detect the quantitative traits loci and linked loci of complex traits. In recent studies, greater success has been achieved in mapping several QTLs in Israel-Holstein cattle using selective DNA pooling. This paper outlines the currently emerged novel strategies of linkage mapping to identify QTL based on selective DNA pooling with more emphasis on its theoretical pre-requisite to detect linked QTLs, applications, a general theory for experimental half-sib designs, the power of statistics and its feasibility to identify genetic markers linked QTL in dairy cattle. The study reveals that the application of selective DNA pooling in dairy cattle can be best exploited in the genome-wide detection of linked loci with small and large QTL effects and applied to a moderately sized half-sib family of about 500 animals.     

3FunMap: full-sib family functional mapping of dynamic traits

MOTIVATION: Functional mapping that embeds the developmental mechanisms of complex traits shows great power to study the dynamic pattern of genetic effects triggered by individual quantitative trait loci (QTLs). A full-sib family, produced by crossing two heterozygous parents, is characteristic of uncertainties about cross-type at a locus and linkage phase between different loci. Integrating functional mapping into a full-sib family requires a model selection procedure capable of addressing these uncertainties. 3FunMap, written in VC++ 6.0, provides a flexible and extensible platform to perform full-sib functional mapping of dynamic traits. Functions in the package encompass linkage phase determination, marker map construction and the pattern identification of QTL segregation, dynamic tests of QTL effects, permutation tests and numerical simulation. We demonstrate the features of 3FunMap through real data analysis and computer simulation. AVAILABILITY: http://statgen.psu.edu/software.     

Mapping the genetic architecture of complex traits in experimental populations

SUMMARY: Understanding how interactions among set of genes affect diverse phenotypes is having a greater impact on biomedical research, agriculture and evolutionary biology. Mapping and characterizing the isolated effects of single quantitative trait locus (QTL) is a first step, but we also need to assemble networks of QTLs and define non-additive interactions (epistasis) together with a host of potential environmental modulators. In this article, we present a full-QTL model with which to explore the genetic architecture of complex trait in multiple environments. Our model includes the effects of multiple QTLs, epistasis, QTL-by-environment interactions and epistasis-by-environment interactions. A new mapping strategy, including marker interval selection, detection of marker interval interactions and genome scans, is used to evaluate putative locations of multiple QTLs and their interactions. All the mapping procedures are performed in the framework of mixed linear model that are flexible to model environmental factors regardless of fix or random effects being assumed. An F-statistic based on Henderson method III is used for hypothesis tests. This method is less computationally greedy than corresponding likelihood ratio test. In each of the mapping procedures, permutation testing is exploited to control for genome-wide false positive rate, and model selection is used to reduce ghost peaks in F-statistic profile. Parameters of the full-QTL model are estimated using a Bayesian method via Gibbs sampling. Monte Carlo simulations help define the reliability and efficiency of the method. Two real-world phenotypes (BXD mouse olfactory bulb weight data and rice yield data) are used as exemplars to demonstrate our methods. AVAILABILITY: A software package is freely available at http://ibi.zju.edu.cn/software/qtlnetwork     

植物QTL定位方法的研究进展

本文系统地介绍了QTL定位的单一标记分析法、区间作图法以及复合区间作图法、混合显性模型的分析方法,概述了一些主要定位方法的分析原理、存在的主要优缺点。单一标记分析法可以采用方差分析、回归分析或似然比检验的方法分析。区间作图法和复合区间作图法是基于两个相邻标记的QTL定位方法,可采用回归分析或最大似然法分析。复合区间作图法在模型中包括了与其他QTL连锁的标记,可以提高作图的精度和效率。混合线性模型的QTL定位方法可以包括复杂的遗传效应及QTL与环境的互作效应,具有更广阔的应用前景。 Abstract:QTL mapping methods are reviewed for single-marker mapping,interval mapping,composite interval mapping,and mixed-model based method.Statistical approaches along with their properties are discussed for the mapping methods.ANOVA,regression method and likelihood ratio test can be applied in single-marker mapping.Interval mapping and composite interval mapping can be conducted,based on two interval markers,by regression method and maximum likelihood method.Since markers linked with other QTLs are include in the model,composite interval mapping is more precision and powerful.Mapping QTL by mixed-model approaches is more applicable when complicated QTL effects as well as QTL by environment interaction are analyzed.