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。     

数量性状基因座的动态定位策略

分子标记辅助数量性状基因（QTL）定位和效应分析技术为深入研究数量性状的遗传基础提供了一个有力手段．但目前的QTL定位策略是静态的,只估计各QTL在某观察时刻的累积效应,无法了解QTL的表达动态．本文提出一种新的QTL定位策略,称为“动态定位”,能够揭示QTI表达的动态过程,并能极大地提高QTL定位的统计功效.     

作物数量性状(QTL)基因研究进展

从作物数量性状基因座QTL(quantitative trait locus)作图群体类型及特点,QTL定位的原理和方法,作物QTL研究现状,以及QTL精细定位、克隆、利用等方面进行了综述。对作物QTL分子标记辅助选择育种进行了探讨,并对目前QTL定位中存在的问题和今后QTL的研究方向提出了一些思考。     

水稻产量相关QTL研究现状

产量是最为复杂的数量性状,对它的遗传机理了解甚微。近15年来,许多学者利用随机分离群体定位了许多影响水稻产量及其组分的QTL,即以QTL定位的方法对产量潜力进行遗传剖析。试验证明上位性效应对产量及其组分性状遗传变异起着重要作用,但目前大多数QTL研究仍侧重于发掘和克隆单个主效QTL,然而对单一基因／QTL的深入了解还不足以诠释复杂性状遗传基础的全貌,还没有为育种家提供足够的可应用于分子标记辅助育种的遗传信息并用于提高水稻产量。笔者认为今后的数量性状研究尚需加强复杂性状QTL遗传网络的发掘,在改良水稻品种性状的同时发展并完善QTL研究。     

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。     

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.     

我国农作物QTL定位研究的现状和进展

植物大多数重要的经济性状都是数量性状,研究植物数量性状遗传对植物育种具有十分重要的意义。近十几年来,分子生物学特别是分子标记技术的飞速发展,许多植物高饱和的分子连锁图谱的构建,使得我们可以更深入地进行数量性状的研究。本文综述了近年来我国在农作物数量性状遗传研究方面的进展及发展动态。列举了我国利用DNA分子标记进行数量性状QTL定位的47个实例。总结了控制数量性状的QTL的数目、类别、效应及其互作和 QTL与环境间的互作关系。讨论了当前在该研究领域中存在的问题,展望了该领域的发展前 景。     

我国农作物QTL定位研究的现状和进展

植物大多数重要的经济性状都是数量性状,研究植物数量性状遗传对植物育种具有十分重要的意义。近十几年来,分子生物学特别是分子标记技术的飞速发展,许多植物高饱和的分子连锁图谱的构建,使得我们可以更深入地进行数量性状的研究。本文综述了近年来我国在农作物数量性状遗传研究方面的进展及发展动态。列举了我国利用DNA分子标记进行数量性状QTL定位的47个实例。总结了控制数量性状的QTL的数目、类别、效应及其互作和QTL与环境间的互作关系。讨论了当前在该研究领域中存在的问题,展望了该领域的发展前景。     

鲤饲料转化率性状的QTL 定位及遗传效应分析

数量性状(QTL)定位是实现分子标记辅助育种、基因选择和定位、培育新品种及加快性状遗传研究进展的重要手段。饲料转化率是鲤鱼的重要经济性状和遗传改良的主要目标, 而通过QTL 定位获得与饲料转化率性状紧密连锁的分子标记以及相关基因是遗传育种的重要工具。研究利用SNP、SSR、EST-SSR 等分子标记构建鲤鱼(Cyprinus carpio L.)遗传连锁图谱并对重要经济性状进行QTL 定位。选用174 个SSR 标记、41 个EST-SSR 标记、345 个SNP 标记对德国镜鲤F2 代群体68 个个体进行基因型检测, 用JoinMap4.0 软件包构建鲤鱼遗传连锁图谱。再用MapQTL5.0 的区间作图法(Interval mapping, IM)和多QTL 区间定位法(MQMMapping, MQM)对饲料转化率性状进行QTL 区间检测, 通过置换实验(1000 次重复)确定连锁群显著性水平阈值。结果显示, 在对饲料转化率性状的多QTL 区间定位中, 共检测到15 个QTLs 区间, 分布在9 个连锁群上, 解释表型变异范围为17.70%—52.20%, 解释表型变异最大的QTLs 区间在第48 连锁群上, 为52.20%。HLJE314-SNP0919(LG25)区间标记覆盖的图距最小, 为0.164 cM; 最大的是HLJ1439-HLJ1438(LG39)区间,覆盖图距为24.922 cM。其中区间HLJ1439-HLJ1438、HLJ922 -SNP0711 解释表型变异均超过50.00%, 可能是影响饲料转化率性状的主效QTLs 区间。与饲料转化率相关的15 个QTLs 的加性效应方向并不一致, 有3个区间具有负向加性效应, 平均为?0.027; 12 个正向加性效应, 平均值为0.06。研究检测出的与鲤鱼饲料转化率性状相关的QTL 位点可为鲤鱼分子标记辅助育种和更进一步的QTL 精细定位打下基础。       

QTL定位的研究方法

QTL 定位就是采用类似单基因定位的方法将QTL定位在遗传图谱上 ,确定 QTL与遗传标记间的距离 (以重组率表示 ) [1]。根据标记数目的不同 ,可分为单标记、双标记和多标记几种方法。根据统计分析方法的不同 ,可分为方差与均值分析法、回归及相关分析法、矩估计及最大似然法等。根据标记区间数可分为零区间作图、单区间作图和多区间作图。此外 ,还有将不同方法结合起来的综合分析方法 ,如 QTL复合区间作图 (CIM)、多区间作图 (MIM)、多 QTL作图、多性状作图 (MTM)等等。建立在标记与数量性状之间相互关联基础上的关联分析方法主要有…     

海岛棉产量和早熟性相关性状的QTLs定位

对海岛棉产量和早熟性状进行QTL初步定位,为分子标记辅助育种提供依据。利用5200多对SSR引物筛选海岛棉品种新海3号和Giza82间的多态性引物,获得107对。以多态性引物检测新海3号×Giza82的190个F2:3家系,获得120个多态性位点。利用JoinMap3.0分析软件构建了一个包含22个连锁群,74个标记,标记间平均距离12.06 cM,全长893 cM,覆盖海岛棉基因组20.12%的分子标记遗传连锁图谱。采用复合区间作图法检测到21个与海岛棉产量性状和早熟性状有关的QTL,其中早熟性状检测到12个QTL,分别位于1、3、5、6、11、17、22共7个连锁群上;产量性状检测到9个QTL,分别位于1、4、5、6、7、16、22共7个连锁群上。研究结果为海岛棉产量性状和早熟性状的分子设计育种提供了有用的信息。     

QTL mapping of yield and fiber traits based on a four-way cross population in <Emphasis Type="Italic">Gossypium hirsutum</Emphasis> L.

Four-way cross (4WC) involving four different inbred lines frequently appears in the cotton breeding programs. However, linkage analysis and quantitative trait loci (QTL) mapping with molecular markers in cotton has largely been applied to populations derived from a cross between two inbred lines, and few results of QTL dissection were conducted in a 4WC population. In this study, an attempt was made to construct a linkage map and identify QTL for yield and fiber quality traits in 4WC derived from four different inbred lines in Gossypium hirsutum L. A linkage map was constructed with 285 SSR loci and one morphological locus, covering 2113.3 cM, approximately 42% of the total recombination length of the cotton genome. A total of 31 QTL with 5.1–25.8% of the total phenotypic variance explained were detected. Twenty-four common QTL across environments showed high stability, and six QTL were environment-specific. Several genomic segments affecting multiple traits were identified. The advantage of QTL mapping using a 4WC were discussed. This study presents the first example of QTL mapping using a 4WC population in upland cotton. The results presented here will enhance the understanding of the genetic basis of yield and fiber quality traits and enable further marker-assisted selection in cultivar populations in upland cotton.     

Quantitative trait loci mapping for yield and its components by using two immortalized populations of a heterotic hybrid in Gossypium hirsutum L.

Quantitative trait loci (QTL) mapping provides a powerful tool for unraveling the genetic basis of yield and yield components as well as heterosis in upland cotton. In this research, a molecular linkage map of Xiangzamian 2 (Gossypium hirsutum L.)-derived recombinant inbred lines (RILs) was reconstructed based on increased expressed sequence tag–simple sequence repeat markers. Both the RILs and immortalized F2s (IF2) developed through intermating between RILs were grown under multiple environments. Yield and yield components including seed-cotton yield, lint yield, bolls/plant, boll weight, lint percentage, seed index, lint index and fruit branch number were measured and their QTL were repeatedly identified across environments by the composite interval mapping (CIM) method. From a total of 111 non-redundant QTL, 23 were detected in both two populations. In the meantime, multi-marker joint analyses showed that 16 of these QTL had significant environmental interaction. QTL for correlated traits tended to be collocated and most of the QTL for seed-cotton yield and lint yield were associated with QTL for at least one yield component, consistent with the results observed in correlation analyses. For many QTL with significant additive effects, positive alleles from CRI12, the inferior parent with lower yield performance, were associated with trait improvement. Trait performance of IF2s and the large number of QTL with positive dominant effects implied that dominance plays an important role in the genetic basis of heterosis in Xiangzamian 2 and that non-additive inheritance is also an important genetic mode for lint percentage in the population. These QTL can provide the bases for marker-assisted breeding programs of upland cotton.     

四倍体栽培棉种产量和纤维品质性状的QTL定位

陆地棉和海岛棉是两个不同的四倍体栽培种 ,但在生产上各有其特点 ,陆地棉丰产性强 ,海岛棉纤维品质优良 ,利用其种间杂交群体定位产量和品质性状的QTL ,对于分子标记辅助的海岛棉优质纤维向陆地棉转移很有意义。以SSR和RAPD为分子标记 ,陆地棉与海岛棉杂种 (邯郸 2 0 8×Pima90 )F2 群体为作图群体 ,构建了一张含 12 6个标记的遗传图谱 ,包括 6 8个SSR标记和 5 8个RAPD标记 ,可分为 2 9个连锁群 ,标记间平均距离为 13 7cM ,总长1717 0cM ,覆盖棉花总基因组约 34 34% ;以遗传图 12 6个标记为基础 ,对F2 :3 家系符合正态分布的 10个农艺性状及纤维品质性状进行全基因组QTL扫描 ,结果发现 2 9个QTL分别与产量和品质性状有关。其中与衣指、籽指、皮棉产量、子棉产量、衣分等产量性状相关的QTL分别有 1、3、5、6和 1个 ,与纤维长度、整齐度、强度、伸长率和马克隆值等品质性状相关的QTL分别有 2、4、2、4和 1个。各QTL解释的变异量在 12 4 2 %～ 47 0 1%之间。其中比强度有关的 2个QTL能够解释的表型变异率分别为 34 15 %和 13 86 %。     

Conditional QTL mapping of protein content in wheat with respect to grain yield and its components

Grain protein content in wheat (Triticum aestivum L.) is generally considered a highly heritable character that is negatively correlated with grain yield and yield-related traits. Quantitative trait loci (QTL) for protein content was mapped using data on protein content and protein content conditioned on the putatively interrelated traits to evaluate possible genetic interrelationships between protein content and yield, as well as yield-related traits. Phenotypic data were evaluated in a recombinant inbred line population with 302 lines derived from a cross between the Chinese cultivar Weimai 8 and Luohan 2. Inclusive composite interval mapping using IciMapping 3.0 was employed for mapping unconditional and conditional QTL with additives. A strong genetic relationship was found between protein content and grain yield, and yield-related traits. Unconditional QTL mapping analysis detected seven additive QTL for protein content, with additive effects ranging in absolute size from 0.1898% to 0.3407% protein content, jointly accounting for 43.45% of the trait variance. Conditional QTL mapping analysis indicated two QTL independent from yield, which can be used in marker-assisted selection for increasing yield without affecting grain protein content. Three additional QTL with minor effects were identified in the conditional mapping. Of the three QTLs, two were identified when protein content was conditioned on yield, which had pleiotropic effects on those two traits. Conditional QTL mapping can be used to dissect the genetic interrelationship between two traits at the individual QTL level for closely correlated traits. Further, conditional QTL mapping can reveal additional QTL with minor effects that are undetectable in unconditional mapping.     

Meta-analysis of polyploid cotton QTL shows unequal contributions of subgenomes to a complex network of genes and gene clusters implicated in lint fiber development

QTL mapping experiments yield heterogeneous results due to the use of different genotypes, environments, and sampling variation. Compilation of QTL mapping results yields a more complete picture of the genetic control of a trait and reveals patterns in organization of trait variation. A total of 432 QTL mapped in one diploid and 10 tetraploid interspecific cotton populations were aligned using a reference map and depicted in a CMap resource. Early demonstrations that genes from the non-fiber-producing diploid ancestor contribute to tetraploid lint fiber genetics gain further support from multiple populations and environments and advanced-generation studies detecting QTL of small phenotypic effect. Both tetraploid subgenomes contribute QTL at largely non-homeologous locations, suggesting divergent selection acting on many corresponding genes before and/or after polyploid formation. QTL correspondence across studies was only modest, suggesting that additional QTL for the target traits remain to be discovered. Crosses between closely-related genotypes differing by single-gene mutants yield profoundly different QTL landscapes, suggesting that fiber variation involves a complex network of interacting genes. Members of the lint fiber development network appear clustered, with cluster members showing heterogeneous phenotypic effects. Meta-analysis linked to synteny-based and expression-based information provides clues about specific genes and families involved in QTL networks.     

A review of statistical methods for expression quantitative trait loci mapping

With high-throughput technologies now widely available, investigators can easily measure thousands of phenotypes for quantitative trait loci (QTL) mapping. Microarray measurements are particularly amenable to QTL mapping, as evidenced by a number of recent studies demonstrating utility across a broad range of biological endeavors. The early success stories have impelled a rapid increase in both the number and complexity of expression QTL (eQTL) experiments. Consequently, there is a need to consider the statistical principles involved in the design and analysis of these experiments and the methods currently being used. In this article we review these principles and methods and discuss the open questions most likely to yield significant progress toward increasing the amount of meaningful information obtained from eQTL mapping experiments.     

利用重组自交系进行陆地棉产量及产量构成因子性状的QTL定位

以高产陆地棉栽培品种中棉所12和8891的杂交组合湘杂棉2号为材料,采用单粒传法构建了含有180个家系的重组自交系(RILs)群体。本研究的目的是分析产量及其构成因子的相互关系并进行相应的QTL定位。重组自交系群体、两亲本和F1于2002年、2003年分别种植于南京农业大学江浦实验农场和江苏省灌云棉花基地。收获每行中间五株的籽棉并考察产量及产量构成因子性状。调查的产量及产量构成因子性状包括单株籽棉产量、单株皮棉产量、单株铃数、铃重、衣分、衣指和籽指。筛选了4,106对SSR引物和384个AFLP引物组合,分别得到127和18个多态位点;此外,2个RAPD引物、1个SRAP引物组合以及来自亲本8891的显性黄花药基因P1也被用来作为标记检测群体基因型。最终共获得149个多态位点,其中132个位点分布于26个染色体/连锁群,覆盖865.20cM,约占棉花基因组的18.57%,标记间平均距离6.55cM。利用此遗传图谱结合重组自交系群体3个环境下的产量及产量构成因子性状,应用QTLCartographer2.0的复合区间作图法进行单位点QTL定位。对各环境资料的分离分析共定位出34个QTL,而利用三环境平均值的联合分析定位出15个QTL。本研究定位的QTL可为棉花产量育种提供信息,其中衣分QTLqLP-A10-1在联合分析及分离分析下的两个环境都能检测到,可能对标记辅助选择有实际应用价值。通径分析结果表明,各产量构成因子中,铃数对皮棉产量贡献最大,这与产量构成因素性状在F1的杂种优势表现一致;因此,在棉花育种上,可优先考虑单株铃数并结合其它产量构成因素进行品种选育和杂交组合选配。     

Quantitative Trait Loci Mapping of Leaf Morphological Traits and Chlorophyll Content in Cultivated Tetraploid Cotton

Genetic mapping provides a powerful tool for quantitative trait loci （QTL） analysis at the molecular level. A simple sequence repeat （SSR） genetic map containing 590 markers and a BCI population from two cultivated tetraploid cotton （Gossypium hirsutum L.） cultivars, namely TM-1 and Hai 7124 （G. barbadense L.）, were used to map and analyze QTL using the composite interval mapping （CIM） method. Thirty one QTLs, 10 for lobe length, 13 for lobe width, six for lobe angle, and two for leaf chlorophyll content, were detected on 15 chromosomes or linkage groups at logarithm of odds （LOD）≥2.0, of which 15 were found for leaf morphology at LOD≥3.0. The genetic effects of the QTL were estimated. These results are fundamental for marker-assisted selection （MAS） of these traits in tetraploid cotton breeding.