EST-SSR标记在木本植物中的开发和应用

本文简述EST-SSR的开发策略,重点就其在木本植物遗传研究中的遗传多样性分析、遗传连锁图谱构建、比较作图以及种质资源鉴定的应用现状和存在问题作介绍,并对其应用前景作了展望。     

贝叶斯统计在QTL作图中的应用研究进展

在许多复杂情况下, 贝叶斯统计方法比经典数理统计方法能更直接解决问题, 且可有效整合部分先验信息, 但其需要高强度计算的特性曾限制了其广泛应用。近几十年来, 随着高速计算机的发展以及MCMC算法的不断提出, 贝叶斯方法已被用于群体遗传学、分子进化、连锁作图和数量遗传学等研究领域, 文章综述了数量遗传学中QTL作图的贝叶斯方法从简单到复杂的发展历程。     

RFLP及其在植物育种中的应用

限制性片段长度多态性(RestrictionFragment Length Polymorphism,简为RFLP)作为遗传标记和连锁分析工具首先出现于人类遗传学,并得到了广泛应用。近几年来,RFLP方法在植物遗传育种的理论研究和实践应用两方面都取得了很大进展。本文介绍了RFLR的方法在育种中的应用、现状及其未来发展方向。     

林木全同胞群体的多位点连锁分析

多位点连锁分析是构建人类以及动植物的遗传连锁图谱的关键步骤之一。但是由于林木遗传背景的复杂性,多位点连锁分析在林木的全同胞群体中还没有得到应用．本文将多位点连锁分析应用到林木的F1代全同胞群体中．对于全同胞群体的任意分离比的两个位点,给出了在不同的连锁相下从一个位点到另一个位点的转移概率矩阵．对于给定的一列标记位点,考虑了不同分离比位点以及两位点间的连锁相信息,采用隐马尔可夫链模型计算极大似然函数和相邻位点间的重组率．本文的方法有助于构建完整的高密度的林木遗传连锁图谱．     

家畜全基因组选择中的单步贝叶斯方法

随着标记信息可以被越来越多的应用在家畜育种中,许多基因组选择(GS)方法使得育种工作者可以利用家畜早期的基因型数据提前对其进行选择。结合系谱、表型和基因型数据,我们可以缩短家畜的世代间隔,提高家畜遗传价值估计的准确性,进而加速其遗传改良速度。近年来,和广泛使用的多步基因组选择策略相比,业界更推崇基于在系谱关系矩阵中增加基因组信息的单步遗传评估方法。即使通常的基因组选择方法依然是多步方法,如GBLUP法,但是基于单步基因组模型进行的基因组评估能提供更为准确的结果。本研究的目的是引入单步贝叶斯方法,此方法可以用贝叶斯回归模型直接计算单核苷酸多态性(SNP)的效应,同时我们使用模拟方法评估模型的性能。研究结果显示:QTL数目对单步贝叶斯方法的准确性无影响,但其准确性受遗传力的影响。同时,其准确性随着测序个体数的增加而增加。我们也讨论了与使用单步贝叶斯方法相关的问题,并详细描述了一些与之有关的统计理论和算法问题。     

关联分析及其在植物中的应用

关联分析是新近开始在植物数量性状研究和植物育种中应用的一种分析方法.它以连锁不平衡为基础鉴定某一群体内性状与遗传标记或候选基因间的关系,是对分子育种中QTL分析的补充和提高.本文在介绍连锁不平衡的定义和度量方法的基础上,讨论连锁不平衡程度和群体结构对关联分析的影响,综述了关联分析在植物方面的研究进展,并最后讨论了关联分析在植物数量性状和分子育种研究中可能的应用.     

关联分析及其在真菌遗传学研究中的应用

近年来,基于连锁不平衡的关联分析被逐渐应用于解析真菌数量性状的遗传基础。本文在介绍关联分析方法的基础上,综述了关联分析在真菌遗传学中的研究进展,并对其未来的应用前景进行了展望。     

微卫星DNA标记及其在鱼类遗传多样性研究中的应用

微卫星DNA作为第二代分子遗传标记是高等真核生物基因组中种类多、分布广、具有高度的多态性和杂合度的分子标记,由于其具有多态性检出率高、信息含量大、共显性标记、实验操作简单、结果稳定可靠等优点,已经成为种群遗传学研究中被广泛应用的分子遗传标记。微卫星DNA标记技术在鱼类的群体遗传结构的分析、物种遗传多样性的鉴定以及遗传基因连锁图谱的构建等方面已初步得到应用。该文就微卫星技术的原理方法,在鱼类遗传多样性研究中的应用概况以及应用范围和注意事项等方面进行综述。为微卫星技术在鱼类遗传多样性研究中应用提供了理论参考。     

利用杉木的F1代群体构建遗传连锁图谱

对于杉木11分离的分子标记位点,提出了一种新的构建遗传连锁图谱的策略.通过二点连锁分析,任意两个位点的连锁相和重组率可以得到推断和估计.对于一个连锁群中的最优排序,采用隐马尔可夫链模型的方法进行多位点的连锁分析.该作图方法比通常林木上所用的"拟测交"作图方法更有效.采用该作图策略,利用句容0号无性系(♀)×柔叶杉(♂)的F1代群体的AFLP分子标记数据重建了句容0号无性系和柔叶杉的遗传连锁图谱.在句容0号无性系的连锁图谱中,有101个标记分布在11个连锁群上,图谱的总长度为2 282.6 cM,平均图距为22.6 cM,单个连锁群上最多含有17个标记,最少含有5个标记;在柔叶杉的连锁图谱中,有94个标记分布在11个连锁群上,图谱的总长度为2 565.8 cM,平均图距为27.3 cM,单个连锁群上最多含有16个标记,最少含有4个标记.构建的句容0号无性系和柔叶杉的遗传连锁图谱比原有的图谱分别增加了26个标记和28个标记,双亲的图谱共增加了54个AFLP标记,使图谱上的分子标记总数达到195个,双亲遗传图谱的跨度均超过了2 000 cM,基本上达到了杉木基因组的长度,图谱的覆盖率接近于100%.利用新的作图方法可以较大提高分子标记在图谱上的分辨率,得到可认为是覆盖了整个基因组的遗传连锁框架图.     

多个遗传标记情形下的RFLP的可诊断率估计

限制性酶切片段长度多态性(RFLP)作为共显性的遗传标记,已广泛应用于遗传病的产前诊断。为评价各遗传标记的适用性,本文给出了在多个遗传标记情形下的RFLP的可诊断率的估计方法,即在使用若干个遗传标记时,群体中可被诊断后代罹病与否的婚配类型的比例的估计方法,包括致病基因为常染色体显性、常染色体隐性、X连锁显性和X连锁隐性的情况,并认为增加遗传标记的个数和选择具较多等位基因的遗传标记,是提高产前诊断可诊断率的有效途径。同时,根据各遗传标记在群体中的多态性分布,可估计各遗传标记及其各种不同组合的可诊断率,以此选择在该群体中最为适合的遗传标记或其组合,以指导RFLP在产前诊断中的应用。     

Bayesian analysis of linkage between genetic markers and quantitative trait loci. II. Combining prior knowledge with experimental evidence

Summary A Bayesian method was developed for identifying genetic markers linked to quantitative trait loci (QTL) by analyzing data from daughter or granddaughter designs and single markers or marker pairs. Traditional methods may yield unrealistic results because linkage tests depend on number of markers and QTL gene effects associated with selected markers are overestimated. The Bayesian or posterior probability of linkage combines information from a daughter or granddaughter design with the prior probability of linkage between a marker locus and a QTL. If the posterior probability exceeds a certain quantity, linkage is declared. Upon linkage acceptance, Bayesian estimates of marker-QTL recombination rate and QTL gene effects and frequencies are obtained. The Bayesian estimates of QTL gene effects account for different amounts of information by shrinking information from data toward the mean or mode of a prior exponential distribution of gene effects. Computation of the Bayesian analysis is feasible. Exact results are given for biallelic QTL, and extensions to multiallelic QTL are suggested.     

Approaches to mapping genetically correlated complex traits

Our Markov chain Monte Carlo (MCMC) methods were used in linkage analyses of the Framingham Heart Study data using all available pedigrees. Our goal was to detect and map loci associated with covariate-adjusted traits log triglyceride (lnTG) and high-density lipoprotein cholesterol (HDL) using multipoint LOD score analysis, Bayesian oligogenic linkage analysis and identity-by-descent (IBD) scoring methods. Each method used all marker data for all markers on a chromosome. Bayesian linkage analysis detected a linkage signal on chromosome 7 for lnTG and HDL, corroborating previously published results. However, these results were not replicated in a classical linkage analysis of the data or by using IBD scoring methods.We conclude that Bayesian linkage analysis provides a powerful paradigm for mapping trait loci but interpretation of the Bayesian linkage signals is subjective. In the absence of a LOD score method accommodating genetically complex traits and linkage heterogeneity, validation of these signals remains elusive.     

The effect of close relatives on unsupervised Bayesian clustering algorithms in population genetic structure analysis

The inference of population genetic structures is essential in many research areas in population genetics, conservation biology and evolutionary biology. Recently, unsupervised Bayesian clustering algorithms have been developed to detect a hidden population structure from genotypic data, assuming among others that individuals taken from the population are unrelated. Under this assumption, markers in a sample taken from a subpopulation can be considered to be in Hardy-Weinberg and linkage equilibrium. However, close relatives might be sampled from the same subpopulation, and consequently, might cause Hardy-Weinberg and linkage disequilibrium and thus bias a population genetic structure analysis. In this study, we used simulated and real data to investigate the impact of close relatives in a sample on Bayesian population structure analysis. We also showed that, when close relatives were identified by a pedigree reconstruction approach and removed, the accuracy of a population genetic structure analysis can be greatly improved. The results indicate that unsupervised Bayesian clustering algorithms cannot be used blindly to detect genetic structure in a sample with closely related individuals. Rather, when closely related individuals are suspected to be frequent in a sample, these individuals should be first identified and removed before conducting a population structure analysis.     

Maximum likelihood haplotyping for general pedigrees

Haplotype data is valuable in mapping disease-susceptibility genes in the study of Mendelian and complex diseases. We present algorithms for inferring a most likely haplotype configuration for general pedigrees, implemented in the newest version of the genetic linkage analysis system SUPERLINK. In SUPERLINK, genetic linkage analysis problems are represented internally using Bayesian networks. The use of Bayesian networks enables efficient maximum likelihood haplotyping for more complex pedigrees than was previously possible. Furthermore, to support efficient haplotyping for larger pedigrees, we have also incorporated a novel algorithm for determining a better elimination order for the variables of the Bayesian network. The presented optimization algorithm also improves likelihood computations. We present experimental results for the new algorithms on a variety of real and semiartificial data sets, and use our software to evaluate MCMC approximations for haplotyping.     

Three-point appraisal of genetic linkage maps

This paper develops a simple diagnostic for the investigation of uncertainty within genetic linkage maps using a Bayesian procedure. The method requires only the genotyping data and the proposed genetic map, and calculates the posterior probability for the possible orders of any set of three markers, accounting for the presence of genotyping error (mistyping) and for missing genotype data. The method uses a Bayesian approach to give insight into conflicts between the order in the proposed map and the genotype scores. The method can also be used to assess the accuracy of a genetic map at different genomic scales and to assess alternative potential marker orders. Simulation and two case studies were used to illustrate the method. In the first case study, the diagnostic revealed conflicts in map ordering for short inter-marker distances that were resolved at a distance of 8–12?cM, except for a set of markers at the end of the linkage group. In the second case study, the ordering did not resolve as distances increase, which could be attributed to regions of the map where many individuals were untyped.     

A comparison of single‐sample effective size estimators using empirical toad (Bufo calamita) population data: genetic compensation and population size‐genetic diversity correlations

The accuracy and precision of four single‐sample estimators of effective population size, N_e (heterozygote excess, linkage disequilibrium, Bayesian partial likelihood and sibship analysis) were compared using empirical data (microsatellite genotypes) from multiple natterjack toad (Bufo calamita) populations in Britain (n = 16) and elsewhere in Europe (n = 10). Census size data were available for the British populations. Because toads have overlapping generations, all of these methods estimated the number of effective breeders N_b rather than N_e. The heterozygote excess method only provided results, without confidence limits, for nine of the British populations. Linkage disequilibrium gave estimates for 10 British populations, but only six had finite confidence limits. The Bayesian and sibship methods both produced estimates with finite confidence limits for all the populations. Although the Bayesian method was the most precise, on most criteria (insensitivity to locus number, correlation with other effective and census size estimates and correlation with genetic diversity) the sibship method performed best. The results also provided evidence of genetic compensation in natterjack toads, and highlighted how the relationship between effective size and genetic diversity can vary as a function of geographical scale.     

The Use of Multiple Markers in a Bayesian Method for Mapping Quantitative Trait Loci

Information on multiple linked genetic markers was used in a Bayesian method for the statistical mapping of quantitative trait loci (QTL). Bayesian parameter estimation and hypothesis testing were implemented via Markov chain Monte Carlo algorithms. Variables sampled were the augmented data (marker-QTL genotypes, polygenic effects), an indicator variable for linkage or nonlinkage, and the parameters. The parameter vector included allele frequencies at the markers and the QTL, map distances of the markers and the QTL, QTL substitution effect, and polygenic and residual variances. The criterion for QTL detection was the marginal posterior probability of a QTL being located on the chromosome carrying the markers. The method was evaluated empirically by analyzing simulated granddaughter designs consisting of 2000 sons, 20 related sires, and their ancestors.     

Fine mapping of complex trait genes combining pedigree and linkage disequilibrium information: a Bayesian unified framework

We present a Bayesian method that combines linkage and linkage disequilibrium (LDL) information for quantitative trait locus (QTL) mapping. This method uses jointly all marker information (haplotypes) and all available pedigree information; i.e., it is not restricted to any specific experimental design and it is not required that phases are known. Infinitesimal genetic effects or environmental noise ("fixed") effects can equally be fitted. A diallelic QTL is assumed and both additive and dominant effects can be estimated. We have implemented a combined Gibbs/Metropolis-Hastings sampling to obtain the marginal posterior distributions of the parameters of interest. We have also implemented a Bayesian variant of usual disequilibrium measures like D' and r(2) between QTL and markers. We illustrate the method with simulated data in "simple" (two-generation full-sib families) and "complex" (four-generation) pedigrees. We compared the estimates with and without using linkage disequilibrium information. In general, using LDL resulted in estimates of QTL position that were much better than linkage-only estimates when there was complete disequilibrium between the mutant QTL allele and the marker. This advantage, however, decreased when the association was only partial. In all cases, additive and dominant effects were estimated accurately either with or without disequilibrium information.     

Simultaneous detection of linkage disequilibrium and genetic differentiation of subdivided populations

We propose a new method for simultaneously detecting linkage disequilibrium and genetic structure in subdivided populations. Taking subpopulation structure into account with a hierarchical model, we estimate the magnitude of genetic differentiation and linkage disequilibrium in a metapopulation on the basis of geographical samples, rather than decompose a population into a finite number of random-mating subpopulations. We assume that Hardy-Weinberg equilibrium is satisfied in each locality, but do not assume independence between marker loci. Linkage states remain unknown. Genetic differentiation and linkage disequilibrium are expressed as hyperparameters describing the prior distribution of genotypes or haplotypes. We estimate related parameters by maximizing marginal-likelihood functions and detect linkage equilibrium or disequilibrium by the Akaike information criterion. Our empirical Bayesian model analyzes genotype and haplotype frequencies regardless of haploid or diploid data, so it can be applied to most commonly used genetic markers. The performance of our procedure is examined via numerical simulations in comparison with classical procedures. Finally, we analyze isozyme data of ayu, a severely exploited fish species, and single-nucleotide polymorphisms in human ALDH2.     

Population genetic variation and structure of the invasive weed Mikania micrantha in southern China: consequences of rapid range expansion

Invasive plants such as Mikania micrantha provide valuable opportunities for studying population genetic consequences of rapid range expansion. Twenty-eight populations of M. micrantha throughout its introduced range in southern China were examined by using intersimple sequence repeat markers. Population genetic parameters were estimated by Bayesian approaches as well as conventional methods. Bottleneck signature, multilocus linkage disequilibrium, character compatibility, and cluster analyses were conducted to assay the factors that may act to shape population variability. High levels of genetic variation and differentiation were detected in the introduced populations of M. micrantha. All populations experienced severe bottlenecks. Most of them demonstrated significant linkage disequilibrium and matrix compatibility. Populations were mainly clustered into 2 groups, and those from different regions intermingled in the unweighted pair group method with arithmetic mean (UPGMA) dendrogram. No geographical signature was found in the pattern of population genetic variation. This research indicates that during M. micrantha invasion, multiple introductions mitigated the loss of genetic variation associated with bottlenecks. Nonetheless, bottlenecks enhanced the population differentiation. Human-mediated long-distance dispersal events of seeds or propagules explain the lack of geographic structure in genetic variation. Although asexual reproduction is the predominant mating mode in M. micrantha, it has little effect on the population genetic composition.