水稻粒长QTL定位与主效基因的遗传分析

该研究利用短粒普通野生稻矮杆突变体和长粒栽培稻品种KJ01组配杂交组合F_1,构建分离群体F_2;并对该群体粒长进行性状遗传分析,利用平均分布于水稻的12条染色体上的132对多态分子标记对该群体进行QTL定位及主效QTLs遗传分析,为进一步克隆新的主效粒长基因奠定基础,并为水稻粒形育种提供理论依据。结果表明:(1)所构建的水稻杂交组合分离群体F_2的粒长性状为多基因控制的数量性状。(2)对543株F_2分离群体进行QTL连锁分析,构建了控制水稻粒长的连锁遗传图谱,总长为1 713.94 cM,共检测出24个QTLs,只有3个表现为加性遗传效应,其余位点均表现为遗传负效应。(3)检测到的3个主效QTLs分别位于3号染色体的分子标记PSM379～RID24455、RID24455～RM15689和RM571～RM16238之间,且三者对表型的贡献率分别为54.85%、31.02%和7.62%。(4)在标记PSM379～RID24455之间已克隆到的粒长基因为该研究新发现的主效QTL位点。     

Quantitative Trait Loci Mapping of Flag-leaf Ligule Length in Rice and Alignment with ZmLG1 Gene

A doubled haploid （DH） population, which consists of 120 lines derived from anther culture of a typical indica and japonica hybrid‘CJ06＇/‘TNI＇, was used in this study. Ligule lengths of flag leaf were investigated for quantitative trait loci （QTL） mapping using the DH population. Five QTLs （qLL-2, qLL.4, qLL-6, qLL-IO and qLL-12） controlling the ligule length （LL） were detected on chromosomes 2, 4, 6, 10 and 12, with the variances explained 11.4%, 13.6%, 27.8%, 22.1% and 11.0%, respectively. Using four known genes of ZmGL1, ZmGL2, ZmGL3 and ZmGL4 in maize from the MaizeGDB, their homologs in rice were aligned and integrated into the existing simple sequence repeats linkage map by in silico mapping. A ZmLG1 homolog gene, OsLG1 encoding a squamosa promoter binding protein, was located between the markers RM255 and RM280, which is just identical to the interval of qLL.4 on the long arm of chromosome 4. The results are beneficial to dissection of the ligule molecular mechanism and the study of cereal evolution.     

基于单片段代换系的水稻穗长QTL加性及其上位性效应

穗长是影响水稻(Oryza sativa)产量的重要因子之一, 研究水稻穗长QTL间的上位性效应对于发掘水稻产量潜力具有重要意义。该研究以16个单片段代换系(single segment substitution lines, SSSLs)和15个双片段聚合系(double segment pyramiding lines, DSPLs)为材料研究了水稻穗长QTL的加性及上位性效应。以P<0.01为阈值, 共检测到6个穗长QTL和9对基因互作座位。其中2个(Pl-2和Pl-10)是尚未报道的穗长QTL。穗长QTL互作后, 一些互作对的上位性效应与单个QTL的作用方式及效应大小各不相同, 预示着基因聚合后会产生不同的互作效应。该研究结果对于通过分子聚合育种手段改良穗长具有重要意义。     

构建数量性状基因图谱的几种统计方法

以线性数学模型为线索,概述了用于构建数量性状基因图谱的几种主要统计方法,包括方差分析法、标记回归法、区间作图法、复合区间作图法、Jansen的复合区间作图法、双侧标记回归法以及新近发展的多区间作图法和多亲本作图法等.讨论了各种方法的优缺点. Abstract:Statistical methods for mapping QTLs were summarized, including one marker analysis, arker regression analysis,interval mapping (IM),composite interval mapping (CIM),Jansen's composite interval mapping, flanking marker regression analysis,multiple interval mapping (MIM) and multiple families mapping.Their advantages and disadvantages were discussed.     

基于单片段代换系的水稻穗长QTL加性及其上位性效应

穗长是影响水稻（Oryza sativa）产量的重要因子之一,研究水稻穗长QTL间的上位性效应对于发掘水稻产量潜力具有重要意义。该研究以16个单片段代换系（single segment substitution lines,SSSLs）和15个双片段聚合系（double segment pyramiding lines,DSPLs）为材料研究了水稻穗长QTL的加性及上位性效应。以P〈0.01为阈值,共检测到6个穗长QTL和9对基因互作座位。其中2个（Pl-2和Pl-10）是尚未报道的穗长QTL。穗长QTL互作后,一些互作对的上位性效应与单个QTL的作用方式及效应大小各不相同,预示着基因聚合后会产生不同的互作效应。该研究结果对于通过分子聚合育种手段改良穗长具有重要意义。     

Mapping Quantitative Trait Loci in Crosses between Outbred Lines Using Least Squares

The use of genetic maps based upon molecular markers has allowed the dissection of some of the factors underlying quantitative variation in crosses between inbred lines. For many species crossing inbred lines is not a practical proposition, although crosses between genetically very different outbred lines are possible. Here we develop a least squares method for the analysis of crosses between outbred lines which simultaneously uses information from multiple linked markers. The method is suitable for crosses where the lines may be segregating at marker loci but can be assumed to be fixed for alternative alleles at the major quantitative trait loci (QTLs) affecting the traits under analysis (e.g., crosses between divergent selection lines or breeds with different selection histories). The simultaneous use of multiple markers from a linkage group increases the sensitivity of the test statistic, and thus the power for the detection of QTLs, compared to the use of single markers or markers flanking an interval. The gain is greater for more closely spaced markers and for markers of lower information content. Use of multiple markers can also remove the bias in the estimated position and effect of a QTL which may result when different markers in a linkage group vary in their heterozygosity in the F(1) (and thus in their information content) and are considered only singly or a pair at a time. The method is relatively simple to apply so that more complex models can be fitted than is currently possible by maximum likelihood. Thus fixed effects and effects of background genotype can be fitted simultaneously with the exploration of a single linkage group which will increase the power to detect QTLs by reducing the residual variance. More complex models with several QTLs in the same linkage group and two-locus interactions between QTLs can similarly be examined. Thus least squares provides a powerful tool to extend the range of crosses from which QTLs can be dissected whilst at the same time allowing flexible and realistic models to be explored.     

水稻QTL定位研究进展

水稻的许多重要农艺性状均属于数量性状,研究水稻数量性状遗传对水稻育种具有十分重要的意义.近年来大量的研究揭示了水稻QTL的基本特征,剖析了重要农艺性状的遗传基础,给水稻遗传改良带来了新策略,不断深入的研究已经完成了水稻特定数量基因的精细定位和克隆,到目前为止已经有一万多个水稻QTL进行了定位,其中有19个进行了克隆,这对水稻育种具有十分重要的意义.本文主要综述了QTL定位的理论基础,水稻QTL定位的研究进展,并对水稻QTL研究的趋势进行了展望.     

Multiple Trait Analysis of Genetic Mapping for Quantitative Trait Loci

We present in this paper models and statistical methods for performing multiple trait analysis on mapping quantitative trait loci (QTL) based on the composite interval mapping method. By taking into account the correlated structure of multiple traits, this joint analysis has several advantages, compared with separate analyses, for mapping QTL, including the expected improvement on the statistical power of the test for QTL and on the precision of parameter estimation. Also this joint analysis provides formal procedures to test a number of biologically interesting hypotheses concerning the nature of genetic correlations between different traits. Among the testing procedures considered are those for joint mapping, pleiotropy, QTL by environment interaction, and pleiotropy vs. close linkage. The test of pleiotropy (one pleiotropic QTL at a genome position) vs. close linkage (multiple nearby nonpleiotropic QTL) can have important implications for our understanding of the nature of genetic correlations between different traits in certain regions of a genome and also for practical applications in animal and plant breeding because one of the major goals in breeding is to break unfavorable linkage. Results of extensive simulation studies are presented to illustrate various properties of the analyses.     

林木数量性状基因定位中的若干问题

随着ＤＮＡ分子标记技术的迅速发展,ＱＴＬ定位已成为当前生物学研究领域的前沿。迄今已对许多种动、植物定位了许多重要性状的ＱＴＬ。这些研究促进了遗传学的发展,并将作为育种的新策略应用。与作物相比,林木ＱＴＬ定位有其特性。本文详细讨论了林木的生物学特性对ＱＴＬ定位的影响、ＱＴＬ定位的系谱设计和统计分析方法。     

A Nonparametric Approach for Mapping Quantitative Trait Loci

Genetic mapping of quantitative trait loci (QTLs) is performed typically by using a parametric approach, based on the assumption that the phenotype follows a normal distribution. Many traits of interest, however, are not normally distributed. In this paper, we present a nonparametric approach to QTL mapping applicable to any phenotypic distribution. The method is based on a statistic Z(w), which generalizes the nonparametric Wilcoxon rank-sum test to the situation of whole-genome search by interval mapping. We determine the appropriate significance level for the statistic Z(w), by showing that its asymptotic null distribution follows an Ornstein-Uhlenbeck process. These results provide a robust, distribution-free method for mapping QTLs.     

Shrinkage Estimation Method for Mapping Multiple Quantitative Trait Loci

In this article, shrinkage estimation method for multiple-marker analysis and for mapping multiple quantitative trait loci (QTL) was reviewed. For multiple-marker analysis, Xu (Genetics, 2003, 163:789-801) developed a Bayesian shrinkage estimation (BSE) method. The key to the success of this method is to allow each marker effect have its own variance parameter, which in turn has its own prior distribution so that the variance can be estimated from the data. Under this hierarchical model, a large number of markers can be handled although most of them may have negligible effects. Under epistatic genetic model, however, the running time is very long. To overcome this problem, a novel method of incorporating the idea described above into maximum likelihood, known as penalized likelihood method, was proposed. A simulated study showed that this method can handle a model with multiple effects, which are ten times larger than the sample size. For multiple QTL analysis, two modified versions for the BSE method were introduced: one is the fixed-interval method and another is the variable-interval method. The former deals with markers with intermediate density, and the latter can handle markers with extremely high density as well as model with epistatic effects. For the detection of epistatic effects, penalized likelihood method and the variable-interval approach of the BSE method are available.     

多QTL定位的压缩估计方法

本文综述了多标记分析和多QTL定位的压缩估计方法。对于前者,Xu（Genetics,2003,163：789—801）首先提出了Bayesian压缩估计方法。其关键在于让每个效应有一个特定的方差参数,而该方差又服从一定的先验分布,以致能从资料中估计之。由此,能够同时估计大量分子标记基因座的遗传效应,即使大多数标记的效应是可忽略的。然而,对于上位性遗传模型,其运算时间还是过长。为此,笔者将上述思想嵌入极大似然法,提出了惩罚最大似然方法。模拟研究显示：该方法能处理变量个数大于样本容量10倍左右的线性遗传模型。对于后者,本文详细介绍了基于固定区间和可变区间的Bayesian压缩估计方法。固定区间方法可处理中等密度的分子标记资料;可变区间方法则可分析高密度分子标记资料,甚至是上位性遗传模型。对于上位性检测,已介绍的惩罚最大似然方法和可变区间Bayesian压缩估计方法可供利用。应当指出,压缩估计方法在今后的eQTL和QTN定位以及基因互作网络分析等研究中也是有应用价值的。     

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.     

利用染色体片段置换系定位水稻落粒性主效QTL

水稻落粒性是与其生产密切相关的重要性状之一。以7个染色体片段置换系为材料, 采用重叠群代换作图法对控制落粒性的2个主效QTL进行定位。结果表明, 104个SSR标记在亲本间具有多态性, 多态率为68.0%; 4个置换系的落粒性与亲本日本晴的落粒性相似, 表现难落粒。3个置换系与亲本93-11的落粒性相似, 表现易落粒; 7个染色体片段置换系在第1和第6染色体上检出7个置换片段, 其长度分别为23.6、16.5、 6.6、 9.9、 10.4、 20.2和7.1 cM; qSH-1-1被定位在第1染色体RM472－RM1387之间, 遗传距离约为6.6 cM。qSH-6-1为新发现的落粒性主效QTL, 被定位在第6染色体RM6782－RM3430之间,遗传距离约为4.2 cM。利用染色体片段置换系能准确地定位水稻落粒性QTL, qSH-1-1与qSH-6-1的鉴定和初步定位为其进一步的精细定位、图位克隆及分子标记辅助选择奠定了基础。     

Combination of Eight Alleles at Four Quantitative Trait Loci Determines Grain Length in Rice

Grain length is an important quantitative trait in rice (Oryza sativa L.) that influences both grain yield and exterior quality. Although many quantitative trait loci (QTLs) for grain length have been identified, it is still unclear how different alleles from different QTLs regulate grain length coordinately. To explore the mechanisms of QTL combination in the determination of grain length, five mapping populations, including two F₂ populations, an F₃ population, an F₇ recombinant inbred line (RIL) population, and an F₈ RIL population, were developed from the cross between the U.S. tropical japonica variety ‘Lemont’ and the Chinese indica variety ‘Yangdao 4’ and grown under different environmental conditions. Four QTLs (qGL-3-1, qGL-3-2, qGL-4, and qGL-7) for grain length were detected using both composite interval mapping and multiple interval mapping methods in the mapping populations. In each locus, there was an allele from one parent that increased grain length and another allele from another parent that decreased it. The eight alleles in the four QTLs were analyzed to determine whether these alleles act additively across loci, and lead to a linear relationship between the predicted breeding value of QTLs and phenotype. Linear regression analysis suggested that the combination of eight alleles determined grain length. Plants carrying more grain length-increasing alleles had longer grain length than those carrying more grain length-decreasing alleles. This trend was consistent in all five mapping populations and demonstrated the regulation of grain length by the four QTLs. Thus, these QTLs are ideal resources for modifying grain length in rice.     

利用染色体片段置换系定位水稻落粒性主效QTL

水稻落粒性是与其生产密切相关的重要性状之一。以7个染色体片段置换系为材料,采用重叠群代换作图法对控制落粒性的2个主效QTL进行定位。结果表明,104个SSR标记在亲本间具有多态性,多态率为68.0%;4个置换系的落粒性与亲本日本晴的落粒性相似,表现难落粒。3个置换系与亲本93-11的落粒性相似,表现易落粒;7个染色体片段置换系在第1和第6染色体上检出7个置换片段,其长度分别为23.6、16.5、6.6、9.9、10.4、20.2和7.1 cM;qSH-1-1被定位在第1染色体RM472-RM1387之间,遗传距离约为6.6 cM。qSH-6-1为新发现的落粒性主效QTL,被定位在第6染色体RM6782-RM3430之间,遗传距离约为4.2 cM。利用染色体片段置换系能准确地定位水稻落粒性QTL,qSH-1-1与qSH-6-1的鉴定和初步定位为其进一步的精细定位、图位克隆及分子标记辅助选择奠定了基础。     

Multiple-Interval Mapping for Quantitative Trait Loci With a Spike in the Trait Distribution

For phenotypic distributions where many individuals share a common value—such as survival time following a pathogenic infection—a spike occurs at that common value. This spike affects quantitative trait loci (QTL) mapping methodologies and causes standard approaches to perform suboptimally. In this article, we develop a multiple-interval mapping (MIM) procedure based on mixture generalized linear models (GLIMs). An extended Bayesian information criterion (EBIC) is used for model selection. To demonstrate its utility, this new approach is compared to single-QTL models that appropriately handle the phenotypic distribution. The method is applied to data from Listeria infection as well as data from simulation studies. Compared to the single-QTL model, the findings demonstrate that the MIM procedure greatly improves the efficiency in terms of positive selection rate and false discovery rate. The method developed has been implemented using functions in R and is freely available to download and use.     

Mapping and Isolation of Quantitative Trait Loci Controlling Plant Height and Heading Date in Rice

Quantitative trait loci (QTL) were identified for heading date and plant height in rice ( Oryza sativa L.) using a recombinant inbred line population consisting of 241 lines. Totally 4 QTLs for heading date and 4 QTLs for plant height were detected in three years. The QTL with large effects located in the interval C1023-R1440 on chromosome 7 was simultaneously detected in three years for both traits. In order to distinguished the interval whether contained one QTL with pleiotropy effect or two close linked QTLs, a recombinant line RIL50, whose genetic background was high similar to Zhenshan 97 except the regions covered the major QTL from Minghui 63, was selected to cross with Zhenshan 97. A BC1F2 population from the cross, which could be regarded as near isogenic lines (NIL) with the targeted QTL (QTL-NIL), was used to collect heading date and plant height data. The frequency distribution of the two traits in the BC1F2 population was bimodal, and their segregation ratios were in accordance with the expected Mendelian inheritance ratios. Normally, the short plants flowered early in the population, the high plants with late heading date, but the relationships between the plant height and the heading date of 6 plants conflicted with the case. The above results clearly demonstrated that QTL could be treated as single Mendelian factor. Moreover, there are two close linked genes controlling the heading date and the plant height on chromosome 7, respectively.     

Mapping Quantitative Trait Loci Associated with Toot Traits Using Sequencing-Based Genotyping Chromosome Segment Substitution Lines Derived from 9311 and Nipponbare in Rice (Oryza sativa L.)

Identification of quantitative trait loci (QTLs) associated with rice root morphology provides useful information for avoiding drought stress and maintaining yield production under the irrigation condition. In this study, a set of chromosome segment substitution lines derived from 9311 as the recipient and Nipponbare as donor, were used to analysis root morphology. By combining the resequencing-based bin-map with a multiple linear regression analysis, QTL identification was conducted on root number (RN), total root length (TRL), root dry weight (RDW), maximum root length (MRL), root thickness (RTH), total absorption area (TAA) and root vitality (RV), using the CSSL population grown under hydroponic conditions. A total of thirty-eight QTLs were identified: six for TRL, six for RDW, eight for the MRL, four for RTH, seven for RN, two for TAA, and five for RV. Phenotypic effect variance explained by these QTLs ranged from 2.23% to 37.08%, and four single QTLs had more than 10% phenotypic explanations on three root traits. We also detected the correlations between grain yield (GY) and root traits, and found that TRL, RTH and MRL had significantly positive correlations with GY. However, TRL, RDW and MRL had significantly positive correlations with biomass yield (BY). Several QTLs identified in our population were co-localized with some loci for grain yield or biomass. This information may be immediately exploited for improving rice water and fertilizer use efficiency for molecular breeding of root system architectures.