作物数量性状基因座定位及分析研究进展

近年来,分子数量遗传学的快速发展,使作物复杂数量性状尤其是经济性状的QTL研究取得了巨大进展,大大促进了复杂数量性状的遗传改良和分子操纵。本文从分子标记连锁图谱的构建、QTL定位力方法及效应分析、精细定位和QTL验证及应用等方面综述了二十多年来作物QTL的研究进展,讨论当前QTL研究中存在的问题,并展望了作物QTL研究的发展前景。     

Genome-wide quantitative trait locus association scan of general cognitive ability using pooled DNA and 500K single nucleotide polymorphism microarrays

General cognitive ability ( g ), which refers to what cognitive abilities have in common, is an important target for molecular genetic research because multivariate quantitative genetic analyses have shown that the same set of genes affects diverse cognitive abilities as well as learning disabilities. In this first autosomal genome-wide association scan of g , we used a two-stage quantitative trait locus (QTL) design with pooled DNA to screen more than 500 000 single nucleotide polymorphisms (SNPs) on microarrays, selecting from a sample of 7000 7-year-old children. In stage 1, we screened for allele frequency differences between groups pooled for low and high g . In stage 2, 47 SNPs nominated in stage 1 were tested by individually genotyping an independent sample of 3195 individuals, representative of the entire distribution of g scores in the full 7000 7-year-old children. Six SNPs yielded significant associations across the normal distribution of g , although only one SNP remained significant after a false discovery rate of 0.05 was imposed. However, none of these SNPs accounted for more than 0.4% of the variance of g , despite 95% power to detect associations of that size. It is likely that QTL effect sizes, even for highly heritable traits such as cognitive abilities and disabilities, are much smaller than previously assumed. Nonetheless, an aggregated 'SNP set' of the six SNPs correlated 0.11 ( P  < 0.00000003) with g . This shows that future SNP sets that will incorporate many more SNPs could be useful for predicting genetic risk and for investigating functional systems of effects from genes to brain to behavior.     

Generalist genes and cognitive neuroscience

Multivariate genetic research suggests that a single set of genes affects most cognitive abilities and disabilities. This finding already has far-reaching implications for cognitive neuroscience, and will become even more revealing when this - presumably large - set of generalist genes is identified. Similar to other complex disorders and dimensions, molecular genetic research on cognitive abilities and disabilities is adopting genome-wide association strategies. These strategies involve very large samples to detect DNA associations of small effect size using microarrays that simultaneously assess hundreds of thousands of DNA markers. When this set of generalist genes is identified, it can be used to provide solid footholds in the climb towards a systems-level understanding of how genetically driven brain processes work together to affect diverse cognitive abilities and disabilities.     

Finding the molecular basis of quantitative traits: successes and pitfalls

Understanding the molecular basis of quantitative genetic variation is a principal goal for biomedicine. Although the complex genetic architecture of quantitative traits has so far largely frustrated attempts to identify genes in humans by standard linkage methodologies, quantitative trait loci (QTL) have been mapped in plants, insects and rodents. However, identifying the molecular bases of QTL remains a challenge. Here, we discuss why this is and how new experimental strategies and analytical techniques, combined with the fruits of the genome projects, are beginning to identify candidate genes for QTL studies in several model organisms.     

An update on molecular genetic studies of human personality traits

Personality is a complex phenotype and people differ considerably when they are evaluated by self-report questionnaires. There is convincing evidence from twin studies that basic personality dimensions in men and women have a considerable genetic component. However, only recently have common genetic polymorphisms been associated with particular personality traits, especially the dopamine D4 receptor with novelty seeking and the serotonin transporter with anxiety-related traits or neuroticism. The current review examines progress in the past few years in molecular personality genetics and focuses on the reasons for difficulties in replicating first findings as well as the prospects for future studies in this area. The molecular genetic structure of human personality is worth studying both for its intrinsic interest in helping us to understand individual differences in human behaviour and the light it will shed on more complex behavioural disorders that are likely to partially share some common genetic variants.     

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。     

种子休眠与萌发的分子生物学的研究进展

休眠与萌发是植物种子对环境变化的适应特征,受许多基因调控和环境因子的影响.利用数量遗传学方法(如QTL分析)和突变等手段已对休眠和萌发特性进行了深入的遗传学研究.近些年来,随着分子生物学的快速发展,种子休眠和萌发研究已经深入到分子水平.分子生物学技术的运用,特别是基因表达、基因组测序和以双向凝胶电泳及质谱分析为技术基础的蛋白质组学分析,已成为研究种子休眠和萌发的新工具和新方向.本文主要就利用分子生物学方法研究种子休眠与萌发的进展给予简要综述.     

大豆遗传图谱的构建和若干农艺性状的QTL定位分析

大豆许多重要农艺性状都是由微效多基因控制的数量性状,对这些数量性状进行QTL定位是大豆数量性状遗传研究领域的一个重要内容.本研究利用栽培大豆科新3号为父本、中黄20为母本杂交得到含192个单株的F2分离群体,构建了含122 个SSR标记、覆盖1719.6cM、由33个连锁群组成的连锁遗传图谱.利用复合区间作图法,对该群体的株高、主茎节数、单株粒重和蛋白质含量等农艺性状的调查数据进行QTL分析,共找到两个株高QTL,贡献率分别为9.15%和6.08%;两个主茎节数QTL,贡献率分别为10. 1%和8.6%;一个蛋白质含量QTL,贡献率为9.8%;一个单株粒重QTL,贡献率为11.4% .通过遗传作图共找到与所定位的4个农艺性状QTL连锁的6个SSR标记,这些标记可以应用于大豆种质资源的分子标记辅助选择,从而为大豆分子标记辅助育种提供理论依据.     

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。     

种子休眠与萌发的分子生物学的研究进展

休眠与萌发是植物种子对环境变化的适应特征,受许多基因调控和环境因子的影响。利用数量遗传学方法（如QTL 分析）和突变等手段已对休眠和萌发特性进行了深入的遗传学研究。近些年来,随着分子生物学的快速发展,种子休眠和萌发研究已经深入到分子水平。分子生物学技术的运用,特别是基因表达、基因组测序和以双向凝胶电泳及质谱分析为技术基础的蛋白质组学分析,已成为研究种子休眠和萌发的新工具和新方向。本文主要就利用分子生物学方法研究种子休眠与萌发的进展给予简要综述。     

Science and society: applications of behavioural genetics: outpacing the science?

Human behavioural genetics is an established research discipline of the genomic age, and applications for behavioural genetic information are most likely to emerge in areas such as criminal justice, education, employment and insurance. However, behavioural genetic research into personality traits and antisocial behaviour poses several risks; for example, tentative or preliminary research findings might be misused in legal and commercial settings. Scientific caution, public and media education, expert consultation and confidentiality protection are essential for the responsible use of behavioural genetics.     

Behavioural and physiological characterization of inbred mouse strains: prospects for elucidating the molecular mechanisms of mammalian learning and memory

With the advent of recombinant DNA methodology, it has become possible to dissect the molecular mechanisms of complex traits, including brain function and behaviour. The increasing amount of available information on the genomes of mammalian organisms, including our own, has facilitated this research. The present review focuses on a somewhat neglected area of genetics, one that involves the study of inbred mouse strains. It is argued that the use of inbred mice is complementary to transgenic approaches in the analysis of molecular mechanisms of complex traits. Whereas transgenic technology allows one to manipulate a single gene and investigate the in vivo effects of highly specific, artificially induced mutations, the study of inbred mouse strains should shed light on the roles of naturally occurring allelic variants in brain function and behaviour. Systematic characterization of the behavioural, electrophysiological, neurochemical, and neuroanatomical properties of a large number of inbred strains is required to elucidate mechanisms of mammalian brain function and behaviour. In essence, a 'mouse phenome' project is needed, entailing the construction of databases to investigate possible causal relationships amongst the phenotypical characteristics. This review focuses on electrophysiological and behavioural characterization of mouse strains. Nevertheless, it is emphasized that the full potential of the analysis of inbred mouse strains may be attained if techniques of numerous disciplines, including gene expression profiling, biochemical analysis, and quantitative trait loci (QTL) mapping, to name but a few, are also included.     

Combining population genomics and quantitative genetics: finding the genes underlying ecologically important traits

A central challenge in evolutionary biology is to identify genes underlying ecologically important traits and describe the fitness consequences of naturally occurring variation at these loci. To address this goal, several novel approaches have been developed, including 'population genomics,' where a large number of molecular markers are scored in individuals from different environments with the goal of identifying markers showing unusual patterns of variation, potentially due to selection at linked sites. Such approaches are appealing because of (1) the increasing ease of generating large numbers of genetic markers, (2) the ability to scan the genome without measuring phenotypes and (3) the simplicity of sampling individuals without knowledge of their breeding history. Although such approaches are inherently applicable to non-model systems, to date these studies have been limited in their ability to uncover functionally relevant genes. By contrast, quantitative genetics has a rich history, and more recently, quantitative trait locus (QTL) mapping has had some success in identifying genes underlying ecologically relevant variation even in novel systems. QTL mapping, however, requires (1) genetic markers that specifically differentiate parental forms, (2) a focus on a particular measurable phenotype and (3) controlled breeding and maintenance of large numbers of progeny. Here we present current advances and suggest future directions that take advantage of population genomics and quantitative genetic approaches - in both model and non-model systems. Specifically, we discuss advantages and limitations of each method and argue that a combination of the two provides a powerful approach to uncovering the molecular mechanisms responsible for adaptation.     

Genome-wide Introgression Lines and their Use in Genetic and Molecular Dissection of Complex Phenotypes in Rice (Oryza sativa L.)

Tremendous efforts have been taken worldwide to develop genome-wide genetic stocks for rice functional genomic (FG) research since the rice genome was completely sequenced. To facilitate FG research of complex polygenic phenotypes in rice, we report the development of over 20 000 introgression lines (ILs) in three elite rice genetic backgrounds for a wide range of complex traits, including resistances/tolerances to many biotic and abiotic stresses, morpho-agronomic traits, physiological traits, etc., by selective introgression. ILs within each genetic background are phenotypically similar to their recurrent parent but each carries one or a few traits introgressed from a known donor. Together, these ILs contain a significant portion of loci affecting the selected complex phenotypes at which allelic diversity exists in the primary gene pool of rice. A forward genetics strategy was proposed and demonstrated with examples on how to use these ILs for large-scale FG research. Complementary to the genome-wide insertional mutants, these ILs opens a new way for highly efficient discovery, candidate gene identification and cloning of important QTLs for specific phenotypes based on convergent evidence from QTL position, expression profiling, functional and molecular diversity analyses of candidate genes, highlights the importance of genetic networks underlying complex phenotypes in rice that may ultimately lead to more complete understanding of the genetic and molecular bases of quantitative trait variation in rice. Supplementary material to this paper is available in electronic form at http://dx.doi.org/10.1007/s11103-005-8519-3     

数量性状由表型变异到基因发现的研究进展

分子生物学的快速发展为研究数量性状的遗传基础提供了更为有效的途径。我们可以沿着由表型变异去发现基因之路, 更准确地剖析数量性状的遗传基础; 尤其是对作物的许多重要的数量性状进行的QTL研究越来越受到重视。文章对数量遗传发展, QTL作图群体和方法的发展, QTL定位和QTG(quantitative traits genes)的鉴别方面的现状进行了综述。     

Genetic mapping of quantitative phenotypic traits in Saccharomyces cerevisiae

Saccharomyces cerevisiae has become a favorite production organism in industrial biotechnology presenting new challenges to yeast engineers in terms of introducing advantageous traits such as stress tolerances. Exploring subspecies diversity of S. cerevisiae has identified strains that bear industrially relevant phenotypic traits. Provided that the genetic basis of such phenotypic traits can be identified inverse engineering allows the targeted modification of production strains. Most phenotypic traits of interest in S. cerevisiae strains are quantitative, meaning that they are controlled by multiple genetic loci referred to as quantitative trait loci (QTL). A straightforward approach to identify the genetic basis of quantitative traits is QTL mapping which aims at the allocation of the genetic determinants to regions in the genome. The application of high-density oligonucleotide arrays and whole-genome re-sequencing to detect genetic variations between strains has facilitated the detection of large numbers of molecular markers thus allowing high-resolution QTL mapping over the entire genome. This review focuses on the basic principle and state of the art of QTL mapping in S. cerevisiae. Furthermore we discuss several approaches developed during the last decade that allow down-scaling of the regions identified by QTL mapping to the gene level. We also emphasize the particular challenges of QTL mapping in nonlaboratory strains of S. cerevisiae.     

Genetic contributions to behavioural diversity at the gene-environment interface

Recent work on behavioural variation within and between species has furthered our understanding of the genetic architecture of behavioural traits, the identities of relevant genes and the ways in which genetic variants affect neuronal circuits to modify behaviour. Here we review our understanding of the genetics of natural behavioural variation in non-human animals and highlight the implications of these findings for human genetics. We suggest that gene-environment interactions are central to natural genetic variation in behaviour and that genes affecting neuromodulatory pathways and sensory processing are preferred sites of naturally occurring mutations.     

关联分析及其在植物遗传学研究中的应用

植物的很多重要经济性状均属于复杂性状。基于连锁分析的QTL作图是研究复杂性状的有效手段, 但其尚存在一定的局限性。随着现代生物学的发展, 一种基于连锁不平衡的新剖分复杂性状方法--关联分析法, 开始应用于植物遗传学研究。与QTL作图法相比, 应用关联分析法具有不需要构建特殊的群体, 可同时对多个等位基因进行分析, 定位QTL精度可达到单基因水平等优势。该文介绍了关联分析方法学的基础和特性, 简述了其在植物遗传学研究中的进展情况, 并对其未来发展和在植物遗传学研究中的应用进行了展望。     

Mapping quantitative trait Loci interactions from the maternal and offspring genomes

The expression of most developmental or behavioral traits involves complex interactions between quantitative trait loci (QTL) from the maternal and offspring genomes. The maternal-offspring interactions play a pivotal role in shaping the direction and rate of evolution in terms of their substantial contribution to quantitative genetic (co)variation. To study the genetics and evolution of maternal-offspring interactions, a unifying statistical framework that embraces both the direct and indirect genetic effects of maternal and offspring QTL on any complex trait is developed. This model is derived for a simple backcross design within the maximum-likelihood context, implemented with the EM algorithm. Results from extensive simulations suggest that this model can provide reasonable estimation of additive and dominant effects of the QTL at different generations and their interaction effects derived from the maternal and offspring genomes. Although our model is framed to characterize the actions and interactions of maternal and offspring QTL affecting offspring traits, the idea can be readily extended to decipher the genetic machinery of maternal traits, such as maternal care. Our model provides a powerful means for studying the evolutionary significance of indirect genetic effects in any sexually reproductive organisms.