四种不同QTL作图方法的比较研究

应用区间作图法(IM)、复合区间作图法(CIM)、基于混合线性模型的复合区间作图法(MCIM)和多重区间作图法(MIM)对水稻杂交组合（培矮64S×日本晴）F₂群体株高性状进行了QTL作图分析。结果表明，（1）在同一显著水平下(α=0.0023)，4种方法共发现10个QTLs，其中IM法7个，CIM法10个，MCIM法3个，MIM法1个。CIM法的发现能力最强。（2）CIM法发现了IM法发现的全部QTLs，和左端标记的距离也基本一致。（3）4种方法检测到了同一QTL，且共同检测到QTL的贡献率最大。（4）4种方法估计的QTL的平均加性效应ā和显性效应 无显著性差异，同一QTL在显性效应的方向上表现一致。（5）建议使用多种作图方法共同作图，并优先标定共同发现的QTL。     

大豆百粒重QTL定位

大豆百粒重是产量构成的重要因素之一,与产量呈正相关。本研究以溧水中子黄豆和南农493-1的504个F2正反交单株及其亲本间具有多态性的150个SSR标记信息构建连锁图谱,2008年分别在江苏南京和山东临沂两地种植其衍生的正反交F2:4家系,鉴定其百粒重,应用Win QTL CartographerV2.5复合区间作图法和两地正反交联合分析进行QTL定位。结果表明,复合区间作图法检测到16个主效QTL,联合分析检测到24个主效QTL、环境效应与细胞质效应、1个环境×QTL互作和12个细胞质×QTL互作。其中,两方法共同检测到10个主效QTL,正反交群体在两地中共同检测到3个主效QTL;Meta分析发现与其他研究一致的4个QTL。这些结果为大豆产量遗传与标记辅助育种实践提供理论基础。     

Efficiency of low heritability QTL mapping under high SNP density

The efficiency of quantitative trait locus (QTL) mapping methods needs to be investigated assuming high single nucleotide polymorphism (SNP) density and low heritability QTLs. This study assessed the efficiency of the least squares, maximum likelihood, and Bayesian approaches for QTL mapping assuming high SNP density and low heritability QTLs. We simulated 50 samples of 400 F₂ individuals, which were genotyped for 1000 SNPs (average density of one SNP/centiMorgan) and phenotyped for three traits controlled by 12 QTLs and 88 minor genes. The genes were randomly distributed in the regions covered by the SNPs along ten chromosomes. The QTL heritabilities ranged from approximately 1–2% and the sample sizes were 200 and 400. The power of QTL detection ranged from 30 to 60%, the false discovery rate (FDR) ranged from only 0.5–1.2%, and the bias in the QTL position ranged from 4 to 6 cM. The QTL mapping efficiency was not influenced by the degree of dominance. The statistical approaches were comparable regarding the FDR. Regression-based and simple interval mapping methods showed equivalent power of QTL detection and mapping precision. Compared to interval mapping, the inclusive composite interval mapping provided slightly greater QTL detection power and mapping precision only for the intermediate and high heritability QTLs. By maximizing the prior number of QTLs, the Bayesian analysis provided the greatest power of QTL detection. No method proved to be superior.     

数量性状基因的完备区间作图方法

结合分子标记和表型数据的QTL作图已成为数量性状遗传分析的常规方法。复合区间作图是近10多年来广泛应用的一种QTL定位方法,但它在算法上有一些缺陷,致使QTL效应可能会被侧连标记区间之外的标记变量吸收,同时不同的背景标记选择方法对作图结果的影响较大,并且难以推广到上位型互作QTL的定位。针对这些问题,笔者提出完备区间作图方法。本文介绍了该方法的遗传和统计原理,并通过一个大麦加倍单倍体群体说明其在定位加性QTL和加性×加性互作QTL中的应用。完备区间作图包含两个步骤：首先利用所有标记的信息,通过逐步回归选择重要的标记变量并估计其效应;然后利用逐步回归得到的线性模型校正表型数据,通过一维扫描定位加(显)性效应QTL,通过二维扫描定位上位型互作QTL。这种作图策略简化了复合区间作图中控制背景遗传变异的过程,提高了对QTL的检测功效。     

Confirmation of quantitative trait loci for resistance to multiple-HG types of soybean cyst nematode (<Emphasis Type="Italic">Heterodera glycines</Emphasis> Ichinohe)

Genetic analysis of resistance of plant introduction (PI) 438489B to soybean cyst nematode (SCN) have shown that this PI is highly resistant to many SCN HG types. However, validation of the previously detected quantitative trait loci (QTL) has not been done. In this study, 250 F_2:3 progeny of a Magellan (susceptible) × PI 438489B (resistant) cross were used for primary genetic mapping to detect putative QTL for resistance to five SCN HG types. QTL confirmation study was subsequently conducted using F_6:7 recombinant inbred lines (RILs) derived from the same cross. Simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers were employed for molecular genotyping. Interval mapping (IM), permutation tests, cofactor selection, and composite interval mapping (CIM) were performed to identify and map QTL. Results showed that five QTL intervals were associated with resistance to either multiple- or single-HG types of SCN. Among these, two major QTL for resistance to multiple-SCN HG types were mapped to chromosomes (Chr.) 8 and 18, consistent with the known rhg1 and Rhg4 locations. The other QTL were mapped to Chr. 4. The results of our study confirmed earlier reported SCN resistance QTL in this PI. Moreover, SSR and SNP molecular markers tightly linked to these QTL can be useful for the near-isogenic lines (NILs) development aiming to fine-mapping of these QTL regions and map-based cloning of SCN resistance candidate genes.     

Quantitative trait locus mapping of floral and related traits using an F2 population of Aquilegia

The objective of this study was to determine quantitative trait loci (QTL) underlying ten floral and related traits in Aquilegia. The traits assessed were calyx diameter, corolla diameter, petal length, petal blade length, sepal length, sepal width, spur length, spur width, plant height and flower number. These are important traits for ornamental value and reproductive isolation of Aquilegia. QTL analysis of these traits was conducted using single‐marker analysis and composite interval mapping (CIM). We used an F₂ population consisting of 148 individuals derived from a cross between the Chinese wild species Aquilegia oxysepala and the cultivar Aquilegia flabellata ‘pumila’. Resulting CIM analysis identified 39 QTLs associated with these traits, which were mapped on seven linkage groups. These QTLs could explain 1.22–53.28% of the phenotypic variance. Thirty‐one QTLs, which explained more than 10% of the phenotypic variation, were classified as major QTLs. Graphical representations of the QTLs on seven linkage groups were made. Our research provides the potential for future molecular assisted selection breeding programmes and the cloning of target genes through fine mapping.     

Genetics and mapping of quantitative traits for nodule number, weight, and size in soybean (Glycine max L.[Merr.])

Soybean research has found that nodule traits, especially nodule biomass, are associated with N₂ fixation ability. Two genotypes, differing in nodule number per plant and individual nodule weight, KS4895 and Jackson, were mated to create 17 F₃- and 80 F₅-derived RILs. The population was mapped with 664 informative markers with an average distance of less than 20 cM between adjacent markers. Nodule traits were evaluated in 3-year field trials. Broad-sense heritability for nodule number (no. plant^?1), individual nodule dry weight (mg nodule^?1), individual nodule size (mm nodule^?1), and total nodule dry weight (g plant^?1) was 0.41, 0.42, 0.45, and 0.27, respectively. Nodule number was negatively correlated with individual nodule weight and size. Nodule number, individual nodule weight, and size are major components which likely contributed to increased total nodule weight per plant. Composite interval mapping (CIM) identified eight QTLs for nodule number with R² values ranging from 0.14 to 0.20. Multiple interval mapping (MIM) identified two QTLs for nodule number, one of which was located close to the QTL identified with CIM. Six QTLs for individual nodule weight were detected with CIM, and one QTL was identified with MIM. For nodule size, CIM identified seven QTLs with R² values ranging from 0.14 to 0.27. Five QTLs for total nodule weight were detected with CIM, one of which was located close to a QTL identified with MIM. These results document the first QTL information on nodule traits in soybean from field experiments utilizing a dense, complete linkage map.     

Estimation of genetic variance components and heritabilities for cut-flower yield in gerbera using least squares and maximum likelihood methods

Summary Genetic variance components and heritability were estimated for cut-flower yield of gerbera in the Davis population using ordinary least squares and maximum likelihood methods. The overall estimate of narrow-sense heritability is 0.33 based on least squares (LS) and 0.31 based on maximum likelihood (ML). The results of the study indicate that (1) ML and LS provide very similar results if sample size is large enough, suggesting both are useful for plant breeding programs; (2) about one third of the variation in gerbera cut-flower yield is additive, implying selection in cut-flower will be successful; and (3) although additive variation gradually decreased, heritability remained near 0.27 suggesting there is still potential variation in the population for further selection.     

四向杂交设计QTL分析的极大似然方法

四向杂交（four-way cross）设计是指4个纯系亲本参与杂交衍生分离群体的一种交配设计。尽管国际上已经提出基于四向杂交设计的迭代重新加权最小平方（iteratively reweighed least squares，IRWLS）QTL作图方法，但该方法忽略了双侧标记基因型内QTL基因型的混合分布特性，当QTL位置和标记的位置不重合时作图精度较低。本文根据四向杂交设计的数量遗传模型，发展出基于四向杂交设计和混合分布理论的QTL作图的极大似然估计方法。首先利用染色体上所有标记基因型联合计算该染色体上任一假定位置QTL的条件概率，然后根据混合分布理论建立基于EM算法实现的QTL作图的极大似然估计方法。以计算机模拟数据研究了QTL遗传力、样本容量和分子标记信息含量3个因素对方法的影响，结果表明,（1）在QTL的被发现能力上，标记信息不完全的四向杂交设计仅略低于信息完全时的四向杂交设计；（2）随着QTL遗传力、样本容量和标记信息含量的增大，QTL位置以及效应估计值的准确度和精确度逐步提高。     

QTL mapping of resistance in lentil (Lens culinaris ssp. culinaris) to ascochyta blight (Ascochyta lentis)

Quantitative trait locus (QTL) analysis of ascochyta blight resistance in lentil was conducted using genomic maps developed from two F₂ populations, viz. ILL5588/ILL7537 and ILL7537/ILL6002. Five QTLs for ascochyta blight resistance were identified by composite interval mapping (CIM) across four linkage groups (LG) in population ILL5588/ILL7537. Three QTLs were identified by CIM in population ILL7537/ILL6002 (two in close proximity on LGI and one on LGII). Two of these coincided with regions identified using multiple interval mapping (MIM) and were shown to be conditioned by dominant and partial dominant gene action. Together, they accounted for approximately 50% of the phenotypic variance of disease severity. Comparison between the two populations revealed a potentially common QTL and several common regions that contained markers significantly associated with resistance. This study demonstrated the transferability of QTLs among populations and identified markers closely linked to the major QTL that may be useful for future marker‐assisted selection for disease resistance.     

发掘人工合成小麦中千粒重QTL的有利等位基因

以人工合成小麦Am3为供体亲本,普通小麦莱州953为轮回亲本,经5次回交然后自交,培育出含85个株系的F_2:3群体。以该群体为材料,用348对多态性SSR标记,进行全基因组扫描,发掘人工合成小麦中千粒重QTL的有利等位基因。利用复合区间作图法检测到3个千粒重QTL,其对表型变异的贡献率为10.9%~33.79%。其中,Am3的等位基因能够增加千粒重2.3~4.8 g。相关分析表明,该导入系群体的千粒重与穗粒数、穗数和株高无显著相关性。千粒重QTL与穗粒数、穗数性状的QTL不在同一位置,这有利于高千粒重基因与其他产量性状基因的聚合。采用混合线性模型作图法检测到1个千粒重QTL(QGw.caas-3D),该QTL与环境互作效应小,而且与复合区间作图法在3个环境中都检测到的QTL相同,表明QGw.caas-3D是一个稳定的主效QTL。     

Identification of novel QTL for leaf traits in soybean

Several leaf traits of soybean (Glycine max L. Merr.), including leaf area (LA), leaf shape (LS) and specific leaf weight (SLW) may be related to soybean yield. The objective of this study was to identify novel quantitative trait loci (QTL) for LA, LS and SLW in a recombinant inbred line (RIL) population. The phenotype data were collected in 2011 and 2012 for 93 F_7:10 RILs using a randomized complete block design with 2 replicates each year. Five hundred and sixteen single‐nucleotide polymorphism (SNP) markers and the phenotype data were used to detect QTL using single marker analysis (SMA) and composite interval mapping (CIM). Single markers analysis identified 26 QTL for the three traits, of which 17 were novel and the rests were previously reported QTL. Most of these QTL were also identified by CIM. Most QTL reported in this study were in close proximity (<1 cM) of one or more SNP markers. These publicly available SNP markers with close linkage to LA, LS and SLW should be useful for marker‐assisted breeding for these traits.     

大豆重组自交系群体荚粒性状的QTL分析

利用大豆重组自交系soy01群体中的255个家系进行2年田间试验，采用两种作图方法，寻找一粒荚、四粒荚、每荚粒数等5个荚粒性状稳定的QTL。结果表明，利用区间作图法，2年共找到24个荚粒性状QTL，解释的遗传变异为5%~80%；利用复合区间作图法，2年共找到27个荚粒性状QTL，解释的遗传变异为4%~73%。利用复合区间作图法，2年找到2个重复出现、稳定的四粒荚QTL和2个每荚粒数QTL，为大豆荚粒性状QTL的精细定位和分子标记辅助育种提供了基础和依据。     

玉米出籽率、籽粒深度和百粒重的QTL分析

为研究玉米出籽率、籽粒深度、百粒重的遗传机制,以豫82×沈137组配的229个F_2:3家系为试验材料,采用复合区间作图法进行QTL定位分析。在3个环境下共检测到10个QTL。其中,控制出籽率、籽粒深度、百粒重相关QTL分别为3个、3个和4个,它们的联合贡献率分别为35.5%、28.1%和39.0%。位于第1染色体上介于标记umc1335与umc2236之间控制出籽率的QTL qKR1b和位于第9染色体上介于标记bnlg1209–umc2095之间控制百粒重QTL q100-KW9b,分别解释18.9%和11.7%的表型变异,且作用方式为加性效应,分析表明这些区域可能包含调控玉米籽粒性状关键基因,对剖析玉米产量形成机制具有重要的参考价值。     

陆地棉早熟基因来源的遗传分析

棉花早熟性相关的性状多为复杂的数量性状,是由多个基因和环境共同作用的结果,其遗传基础研究比较困难。利用连锁作图和关联分析方法,对目标性状进行基因定位,找出与性状相关联的位点,为解析复杂性状的基因来源提供了新的手段。本文分别以早熟亲本新陆早8号和新陆早10号为母本,以陆地棉标准系TM-1为父本构建F₂作图群体,利用在亲本间筛选出的多态性SSR引物,通过JoinMap 3.0软件构建了2张遗传图谱,以Win QTLCart 2.5复合区间作图法在F₂~F_2:3中定位到控制全生育期、苗期、蕾期、花铃期和霜前铃数等早熟性相关性状的37个QTL。控制早熟性的有利等位基因多来自早熟祖先611波和金字棉。多数性状在两类材料中由不同的基因控制,且以加性遗传为主。在由43个陆地棉品种材料构成的自然群体中通过关联分析检测到54个与这些早熟性相关性状极显著关联的位点。研究表明连锁作图和关联分析的检测结果具有较高的可比性。本研究为早熟陆地棉聚合改良以及分子标记辅助育种打下了基础。     

T1 locus in cotton is the candidate gene affecting lint percentage, fiber quality and spiny bollworm (Earias spp.) resistance

A genetic linkage map of chromosome 6 was constructed by using 270 recombinant inbred lines originated from an upland cotton cross (Yumian 1 × T586) F₂ population. The genetic map included one morphological (T₁) and 18 SSR loci, covering 96.2 cM with an average distance of 5.34 cM between two markers. Based on composite interval mapping (CIM), QTL(s) affecting lint percentage, fiber length, fiber length uniformity, fiber strength and spiny bollworm resistance (Earias spp.) were identified in the t₁ locus region on chromosome 6. The allele(s) originating from T586 of QTLs controlling lint percentage increased the trait phenotypic value while the alleles originating from Yumian 1 of QTLs affecting fiber length, fiber length uniformity, fiber strength and spiny bollworm resistance increased the trait phenotypic value.     

大豆脂肪及脂肪酸组分含量的QTL定位

脂肪及脂肪酸组分的改良是大豆油脂品质育种的主要方面。本研究旨在构建遗传图谱,定位大豆脂肪及脂肪酸组分的QTL,为大豆油脂品质育种提供参考。以Essex×ZDD2315的114个BC₁F₁单株为作图群体,构建了250个SSR标记和1个形态标记,具有25个连锁群的遗传图谱,覆盖大豆基因组2 963.5 cM,平均每个连锁群上10.0个标记,标记平均间距11.8 cM。用BC₁F₃家系3个重复的表型平均值代表相对应的BC₁F₁单株表型值,采用Win QTL Cartographer 2.5复合区间作图法（CIM）检测到18个控制脂肪及脂肪酸组分含量的QTL,位于9个不同的连锁群上,表型贡献率为9.6%~34.5%;多区间作图法（MIM）检测到与CIM区间相同的7个QTL（fat-1, pal-1, st-1, ole-1, lin-1, lin-4和lio-2）,区间相近的2个QTL（ole-4和lin-5）,位于6个不同的连锁群上,表型贡献率为8.2%~39.3%。CIM法检测到的其他9个QTL有待进一步验证。大豆脂肪及脂肪酸组分含量的主效QTL数量不多,效应大的不多,可能还受许多未能检测出来的微效基因控制,育种中既要注意主效QTL的利用,又要考虑微效多基因的积聚。     

质量—数量性状的遗传分析 Ⅳ.极大似然法的应用

应用极大似然法分析质量—数量性状的遗传。假定分离世代中的同一主基因基因型因多基因和环境的变异而呈正态分布,不同主基因基因型则为具不同平均数和相同方差的混合正态分布。提出以EM算法对主基因的分离比率、基因效应、微基因的遗传方差等进行极大似然估计以及以似然比方法测验有关遗传假设的程序。以大麦一个杂交组合的F_2代株高资料为例演示了分析过程。结果表明该组合的株高遗传涉及一个主基因和一组微基因;主基因杂合体为完全显性,显性效应达 14.97cm;微基因的遗传方差为65.14cm~2;环境方差为 14.80cm~2。本文的原理和方法可以推广于多个分离世代的联合分析以及利用分子标记构建数量性状基因图谱等。     

大豆粒形性状QTL的精细定位

在溧水中子黄豆×南农493-1衍生的504个F_2:6家系中选择Satt331~Satt592目标区间7个杂合单株和168个重组单株,衍生成356株RHL-F₂个体(群体I)和168个重组体家系(群体II)。群体II来自142个F_2:6家系,若每个F_2:6家系只保留1个重组家系则构成群体III。采用lasso和复合区间作图(CIM)法检测3个群体粒形性状2种指标的QTL。结果表明, lasso法检测到的粒长关联标记是O19和S21/Satt331,而CIM检测到的QTL区间是S21~S22和O23~O19;lasso法检测到的粒宽关联标记是O19/O21,而CIM检测到的QTL区间是O23~O19/O19~O21;长宽比与S21~S22关联是由于粒长QTL引起的,与O23~O19 /O19~O21关联是由于粒长和粒宽QTL引起的。将原Satt331~Satt592目标区间的粒长QTL剖分为与标记S21~S22和O23~O19/O19~O21关联的2个多效性QTL。根据大豆基因注释数据库,Glyma10g35240和Glyma10g34980可能是控制粒形性状发育的候选基因。     

玉米丝裂病的抗性QTL定位

选用感丝裂病的玉米自交系R08与抗丝裂病的自交系Es40组配F₂群体共348个单株,构建了包含115个SSR标记的分子遗传连锁图谱,覆盖玉米基因组2 178.6 cM,平均图距为18.9 cM。采用复合区间作图法,对F_2:4家系丝裂病数据进行抗性QTL分析,共检测到12个QTL,分别位于第1、2、4、5和7染色体,贡献率为4.22%~37.95%。其中在第1、3染色体上检测到主效QTL,贡献率均大于30%,基因作用方式均为显性,其余10个QTL的作用方式多为加性或部分显性。