植物数量性状变异的分子基础与QTL克隆研究进展

探讨数量性状变异规律以便对其进行遗传操纵一直是植物遗传学的一个重要领域。DNA分子标记和QTL作图技术的发展以及拟南芥和水稻全基因组测序的完成极大地促进了植物数量性状分子基础的研究。现已克隆了拟南芥ED1、水稻Hdl、玉米Tb1、番茄fw2．2和Brii9-2-5等控制目标数量性状的基因。数量性状表型变异不仅源于多个数量性状基因（QTL）的分离．而且还受到内外环境的修饰。QTL等位基因变异与孟德尔基因变异具有类似的分子基础,即基因表达或蛋白质功能发生改变。通过分析已克隆的植物QTL的变异特征及分子基础,讨论了植物QTL克隆技术策略,并对QTL研究所面临的挑战和应用前景进行了展望。     

数量遗传学中一种新的求综合性状的方法

本文运用申农(Shannon)提供的最大熵原理,提出一种构成单一综合性状的新方法,并以此与数量遗传学中的多元统计法作了比较。在作多元遗传分析吋,常用多元统计法求出多个数量性状的综合性状,再对这些相互关联的基本性状作主成份分析或用典范相关进行遗传分析。本文提出了不同于多元统计学的另一种新的方法——最大熵法求出多个数量性状的单一综合性状值。它具有数学结构简单,过程明晰,结果简明等优点。     

作物数量性状研究进展

作物主要农艺性状和经济性状大多属于数量性状。传统数量遗传学采用数理统计方法,把控制数量性状的多基因系统作为一个整体进行研究。DNA分子标记技术的出现和发展,为数量性状研究提供了重要工具。自20世纪80年代以来,QTL定位的统计分析方法发展很快,先后提出单标记分析法、区间作图法及复合区间作图法等。目前,作物QTL研究取得了重要进展,一些重要作物、重要农艺性状的主效QTL基因已被相继克隆成功,作物数量性状的研究已经成为一个具有勃勃生机的热门领域。     

植物数量性状基因定位研究概述

植物重要的性状多为数量性状。长期以来,人类一直寻求解释植物数量性状的遗传规律以便对其进行遗传操纵。现代分子生物技术的发展为植物数量性状基因的定位、分离等研究提供了条件。本文从数量性状基因座(QTL)作图群体类型及其特点,QTL定位方法,植物QTL研究现状,以及QTL精细定位、克隆、利用等方面进行了综述,并对今后植物QTL研究进行了展望。     

数量性状主要基因随机效应的分析

数量性状主基因在不同环境或遗传背景中表现随机效应。本文提出数量性状基因随机效应分析的试验设计和统计模型,以及对基因的分离比、平均效应和随机方差进行假设测验的方法．所述方法可用于借助标记基因对数量性状基因效应作类似分析．     

试论生物中的兼性性状

生物界除了质量性状和数量性状外,还存在一种既可表现为质量性状、又可表现为数量性状的中介性状类型,称之兼性性状(或称“两性性状”)。兼性性状存在着三种可能的遗传基础:①由兼性基因控制的兼性性状。兼性基因是一种既具有主基因的显隐性特点,又具有微效基因的剂量累加效应的基因类型。②由并联式基因控制的兼性性状。某些抗性性状的多个基因K(K≥2)以并联方式协同控制性状的综合水平性表达,表现为数量性状的遗传特征。当K=1时,抗性基因系统中只有一个主基因——单个主基因控制性状的垂直性表达,表现为质量性状的遗传方式。③由主基因系统和微效多基因系统协同控制的兼性性状。其中微效基因系统参与性状数量表达     

植物数量性状基因定位研究概述

植物重要的性状多为数量性状。长期以来,人类一直寻求解释植物数量性状的遗传规律以便对其进行遗传操纵。现代分子生物技术的发展为植物数量性状基因的定位、分离等研究提供了条件。本文从数量性状基因座(QTL)作图群体类型及其特点,QTL定位方法,植物QTL研究现状,以及QTL精细定位、克隆、利用等方面进行了综述,并对今后植物QTL研究进行了展望。     

基于选择牵连效应的标记/性状关联分析方法简介

许多重要农艺性状如产量、品质、抗逆性等多表现为数量性状, 是由多个基因和环境共同作用的结果, 对其遗传基础的研究比较困难。近年发展起来的以选择牵连效应分析为基础, 通过标记/性状之间的关联分析方法为这些性状的作图和遗传解析提供了新的手段, 也为作物的分子设计育种提供了新的思路, 其与QTL作图结果互相验证、互相补充, 必将促进数量遗传学、应用基因组学和育种学的发展。文章对关联分析的思路、方法、优缺点及应用时应注意的问题进行了比较系统的介绍。     

番茄果重数量性状基因的研究进展及在遗传学教学中的应用

遗传学发展史上一系列经典的研究案例对学科的发展起了巨大的推动作用,将这些经典案例与教学内容相结合应用到遗传学课程教学中,对学生的科学思维和遗传分析能力是一个很好的训练。番茄果重基因的定位与克隆在数量性状基因座研究中是开创性的工作,完整的体现了植物数量性状基因的研究历程。将其作为一个综合案例应用于遗传学教学,可以生动直观地给学生展示一个精彩的科学发现过程,展现遗传学研究的魅力,激发学生的学习兴趣,收到了很好的教学效果。     

水稻QTL分析的研究进展

水稻许多重要的性状是由多基因控制的数量性状,经典的数量遗传学只能把数量性状作为一个整体进行研究。近年来．高密度分子标记连锁图的构建和有效的生物统计学方法的发展使人们对数量性状遗传基础的研究出现了革命性的变化。通过对不同群体内的个体或品系的分子标记基因型和表型数据的共分离分析,能对QTL进行检测和定位。本文对QTL定位的原理和方法进行了介绍,从QTL的数目和效应、上位性效应、QTL基因型与环境的互作、相关性状的QTL以及个体发育不同阶段的QTL等方面对水稻QTL分析的研究进展进行了综述。水稻基因组测序计划已经完成,本文还对基因组时代水稻QTL精细定位和克隆的方法进行了探讨,对QTL分析在水稻育种中的应用前景进行了展望。     

The evolution of genetic architectures underlying quantitative traits

In the classic view introduced by R. A. Fisher, a quantitative trait is encoded by many loci with small, additive effects. Recent advances in quantitative trait loci mapping have begun to elucidate the genetic architectures underlying vast numbers of phenotypes across diverse taxa, producing observations that sometimes contrast with Fisher''s blueprint. Despite these considerable empirical efforts to map the genetic determinants of traits, it remains poorly understood how the genetic architecture of a trait should evolve, or how it depends on the selection pressures on the trait. Here, we develop a simple, population-genetic model for the evolution of genetic architectures. Our model predicts that traits under moderate selection should be encoded by many loci with highly variable effects, whereas traits under either weak or strong selection should be encoded by relatively few loci. We compare these theoretical predictions with qualitative trends in the genetics of human traits, and with systematic data on the genetics of gene expression levels in yeast. Our analysis provides an evolutionary explanation for broad empirical patterns in the genetic basis for traits, and it introduces a single framework that unifies the diversity of observed genetic architectures, ranging from Mendelian to Fisherian.     

小麦抗旱相关生理性状的QTL分析

利用RIL群体131个系,在小麦中首次对超氧化物岐化酶活性、可溶性蛋白含量、脯氨酸含量、硝酸还原酶活性、气孔导度等5个抗旱相关生理性状进行了QTL定位,共检测到超氧化物岐化酶活性、可溶性蛋白含量、硝酸还原酶活性等3个性状5个加性QTL,涉及1D、2B、5A、7B共4条染色体,可解释表型变异的8.74％～36.96％。其中．3个QTL即QSDd,sdau-7B、Qspc,sdau-1D、QNra,sdau-1D贡献率较大,分别为29.28％、23.11％和36．96％,其加性效应都源于山农483。讨论了可能用于标记辅助选择的QTL及其分子标记。     

The candidate gene approach in plant genetics: a review

The candidate gene (CG) approach has been applied in plant genetics in the past decade for the characterisation and cloning of Mendelian and quantitative trait loci (QTLs). It constitutes a complementary strategy to map-based cloning and insertional mutagenesis. The goal of this paper is to present an overview of CG analyses in plant genetics. CG analysis is based on the hypothesis that known-function genes (the candidate genes) could correspond to loci controlling traits of interest. CGs refer either to cloned genes presumed to affect a given trait (`functional CGs') or to genes suggested by their close proximity on linkage maps to loci controlling the trait (`positional CGs'). In plant genetics, the most common way to identify a CG is to look for map co-segregation between CGs and loci affecting the trait. Statistical association analyses between molecular polymorphisms of the CG and variation in the trait of interest have also been carried out in a few studies. The final validation of a CG will be provided through physiological analyses, genetic transformation and/or sexual complementation. Theoretical and practical applications of validated CGs in plant genetics and breeding are discussed.     

Joint oligogenic segregation and linkage analysis using bayesian Markov chain Monte Carlo methods

One of the most challenging areas in human genetics is the dissection of quantitative traits. In this context, the efficient use of available data is important, including, when possible, use of large pedigrees and many markers for gene mapping. In addition, methods that jointly perform linkage analysis and estimation of the trait model are appealing because they combine the advantages of a model-based analysis with the advantages of methods that do not require prespecification of model parameters for linkage analysis. Here we review a Markov chain Monte Carlo approach for such joint linkage and segregation analysis, which allows analysis of oligogenic traits in the context of multipoint linkage analysis of large pedigrees. We provide an outline for practitioners of the salient features of the method, interpretation of the results, effect of violation of assumptions, and an example analysis of a two-locus trait to illustrate the method.     

Covariation of larval gene expression and adult body size in natural populations of Drosophila melanogaster

Understanding adaptive phenotypic variation is one of the most fundamental problems in evolutionary biology. Genes involved in adaptation are most likely those that affect traits most intimately connected to fitness: life-history traits. The genetics of quantitative trait variation (including life histories) is still poorly understood, but several studies suggest that (1) quantitative variation might be the result of variation in gene expression, rather than protein evolution, and (2) natural variation in gene expression underlies adaptation. The next step in studying the genetics of adaptive phenotypic variation is therefore an analysis of naturally occuring covariation of global gene expression and a life-history trait. Here, we report a microarray study addressing the covariation in larval gene expression and adult body weight, a life-history trait involved in adaptation. Natural populations of Drosophila melanogaster show adaptive geographic variation in adult body size, with larger animals at higher latitudes. Conditions during larval development also affect adult size with larger flies emerging at lower temperatures. We found statistically significant differences in normalized larval gene expression between geographic populations at one temperature (genetic variation) and within geographic populations between temperatures (developmental plasticity). Moreover, larval gene expression correlated highly with adult weight, explaining 81% of its natural variation. Of the genes that show a correlation of gene expression with adult weight, most are involved in cell growth or cell maintenance or are associated with growth pathways.     

Phenotyping mouse chromosome substitution strains reveal multiple QTLs for febrile seizure susceptibility

Febrile seizures (FS) are the most common seizure type in children and recurrent FS are a risk factor for developing temporal lobe epilepsy. Although the mechanisms underlying FS are largely unknown, recent family, twin and animal studies indicate that genetics are important in FS susceptibility. Here, a forward genetic strategy was used employing mouse chromosome substitution strains (CSS) to identify novel FS susceptibility quantitative trait loci (QTLs). FS were induced by exposure to warm air at postnatal day 14. Video electroencephalogram monitoring identified tonic–clonic convulsion onset, defined as febrile seizure latency (FSL), as a reliable phenotypic parameter to determine FS susceptibility. FSL was determined in both sexes of the host strain (C57BL/6J), the donor strain (A/J) and CSS. C57BL/6J mice were more susceptible to FS than A/J mice. Phenotypic screening of the CSS panel identified six strains (CSS1, -2, -6 -10, -13 and -X) carrying QTLs for FS susceptibility. CSS1, -10 and -13 were less susceptible (protective QTLs), whereas CSS2, -6 and -X were more susceptible (susceptibility QTLs) to FS than the C57BL/6J strain. Our data show that mouse FS susceptibility is determined by complex genetics, which is distinct from that for chemically induced seizures. This is the first data set using CSS to screen for a seizure trait in mouse pups. It provides evidence for common FS susceptibility QTLs that serve as starting points to fine map FS susceptibility QTLs and to identify FS susceptibility genes. This will increase our understanding of human FS, working toward the identification of new therapeutic targets.