大豆高蛋白种质中引1106蛋白质含量的QTL分析

大豆籽粒蛋白质含量由多基因控制且易受环境条件的影响,发掘高蛋白基因是促进大豆优质分子育种的重要手段。本研究选用综合性状优良、蛋白质含量较低的黑河50为轮回亲本,以引进的高蛋白种质中引1106为供体亲本,构建了由384个家系组成的回交高代群体。利用近红外光谱仪测定回交群体的蛋白质含量,使用SSR分子标记技术鉴定回交群体BC1F6基因型,通过QTL ICIMapping4.1的区间作图法(IM-ADD)和完备区间作图法(ICIM-ADD)定位蛋白含量QTL,共获得9个蛋白含量QTL,其中IM定位到7个蛋白含量QTL,而ICIM定位到3个蛋白含量QTL,两种方法同时在8号染色体上定位到一个QTL(q Pro-8-1),该QTL两侧的分子标记是SSR_50和SSR_51,可解释表型变异分别是2.26%和7.85%,定位区间物理距离大小为218.71 kb,该QTL尚未见报道,是一个与蛋白质含量相关的新QTL位点,为高蛋白大豆品种选育提供了材料和理论依据。     

控制大豆油分含量和百粒重的QTL定位

油分含量和百粒重是大豆中两个重要的性状。本研究利用东农46和L-100衍生的重组自交系(RIL)群体,经过两年3个地点种植,通过分子标记技术定位与大豆油分含量和百粒重相关的QTL(quantitative trait locus)。结果表明,检测到6个与油分含量相关的QTL,分别位于E、H、G和I连锁群上,可解释的表型贡献率范围为2.12%~2.77%;检测到5个与百粒重相关的QTL,分别位于K、H、B2和G连锁群上,可解释的表型贡献率范围为2.30%~7.59%,在H连锁群上有2个QTL两年均被检测到,标记区间分别为Satt279-Sat_122和Satt192-Satt568。在H连锁群上Satt192-Satt568标记区间内同时检测到与油分含量和百粒重相关的QTL。研究结果为大豆油分含量和百粒重等性状的分子辅助育种提供了理论依据。     

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.     

水稻红莲型CMS育性恢复QTL分析

红莲型CMS是在我国杂交水稻生产中被广泛利用的雄性不育细胞质之一。为了同时定位红莲型CMS育性恢复主效和微效QTL,利用红莲型CMS不育系粤泰A(YTA)与“Lemont／特青”RIL群体测交,结合1张含有198个DNA分子标记的高密度遗传图谱,对测交F1群体的小穗育性和花粉育性进行复合区间作图。在对YTA的育性恢复性方面,该。RIL群体的2个亲本之间具有明显差异,特青的恢复性较强,其测交F1的小穗育性和花粉育性分别为72％和51％;而Lemont测交F1的小穗育性和花粉育性分别为32％和9％。复合区间作图定位到4个育性恢复QTL,分别位于水稻第1、2和10号染色体上,单个QTL的贡献率在5％～24％之间。其中,除1个QTL的增效基因来源于Lemont外,其余3个QTL的增效基因均来源于特青。效应最大的QTL为qRF-10-1,该QTL位于10号染色体RM258-C16标记区间,对小穗育性表型变异的贡献率为24％,对花粉育性的贡献率为17％,且该QTL被检测到的LOD值显著较高,因此是1个主效QTL,其增效基因来源于特青。除了主效QTLqRF-10-1外,其它3个QTL对性状的贡献率均在10％以下(5％～8％)。由此表明,该RIL群体对红莲型CMS的育性恢复由1个主效QTL控制,并受其它几个微效QTL的影响。该QTL定位结果与小穗育性在测交F1群体中呈连续的双峰分布的结果相一致。与主效QTL qRF-10-1紧密连锁的SSR标记为RM258,该主效QTL可作为分子标记辅助育种的操作目标之一,用于杂交稻分子育种中培育红莲型CMS的强恢复系。     

大豆叶绿素含量QTL定位及候选基因预测

叶绿素是调节光合作用的关键色素,对籽粒形成有着重要作用。本研究以美国半矮秆大豆Charleston为母本,东北地区主栽品种东农594为父本杂交衍生的147个重组自交系群体为材料,基于经SLAF测序获得的大豆高密度遗传图谱,利用复合区间作图法(CIM)、多重区间作图法(MIM)和完备区间作图法(ICIM)对大豆叶绿素含量进行QTL联合定位分析,并结合大豆基因组基因注释信息对QTL区段内的候选基因进行预测。利用CIM算法定位出2个QTL,表型遗传贡献率分别为6%和9.3%。利用MIM算法定位到了1个QTL,表型遗传贡献率为8.1%。利用ICIM算法定位到了1个QTL,表型遗传贡献率为7.76%。其中qchl-G-1被CIM和MIM两种算法同时检测到。在上述3个QTL区段内共含有151个基因,根据大豆基因组基因注释信息,筛选到了3个与叶绿素相关的候选基因,这些结果为叶绿素含量的遗传剖析和标记辅助育种提供理论基础,有利于分子辅助育种的发展。     

大豆倒伏性相关QTL的整合及Overview分析

倒伏性是影响大豆产量的重要因素,发掘与大豆倒伏相关的基因对于培育抗倒伏优良高产大豆品种具有重要意义。目前利用不同群体所构建的遗传图谱已经定位了大量与大豆倒伏性相关的QTLs。本研究在对已报道的QTLs进行物理整合的基础上,选择元分析方法将这些倒伏性相关的QTLs进一步整合,鉴定出位于C2(6号染色体)、F(13号染色体)、L(19号染色体)这3个连锁群上重复次数较多的QTL区间6个。选用基于统计学原理的Overview方法进行优化,获得了这些QTL在各个连锁群上的有效遗传位置,这些QTL的置信区间长度最小可缩至0.2 cM。通过在这些区间内进一步筛选,获得一个稳定性较好的标记Satt277。本研究可为大豆抗倒伏基因发掘及分子标记辅助选择育种提供理论依据。     

水稻条纹叶枯病抗性位点的检测和效应分析

利用111个家系组成的热研2号（Oryza sativa subsp．japonica‘Reyan2’）／Milyang23（Oryza sativa subsp．indica‘Milyang23’）重组自交系（recombinant inbred lines,RIL）群体（F7）,采用重病区田间自然接种方法,以病情指数作为条纹叶枯病的表型值,鉴定了2个亲本及111个RIL家系对条纹叶枯病的抗性。使用QTL Cartographer软件复合区间作图法,对水稻（Oryza sativa）条纹叶枯病抗性基因进行了QTL分析。结果检测到2个抗水稻条纹叶枯病的QTL,分别位于第2和第11染色体上,其中第11染色体上的QTL贡献率为19．58％,表明这是一个主效的QTL,该QTL及其附近的分子标记,可以用于水稻条纹叶枯病抗性分子标记辅助育种。     

大豆全基因组分枝相关基因发掘及与QTL共定位

大豆(Glycine max)分枝在个体和群体水平上均与大豆产量关系密切, 因此大豆分枝相关基因的发掘及利用对大豆高产分子育种具有重要意义。文章通过GO(Gene ontology)分类和文献检索共获得植物分枝发育相关基因183个。基于序列相似和结构域相同的原则, 从大豆基因组中发掘出大豆分枝相关的候选基因406个。通过收集已发表的大豆分枝相关QTL, 利用BioMercator2.1软件, 将符合映射条件的35个QTL映射到公共图谱的12个染色体。通过共定位分析发现, 在20个分枝相关的QTL区间内存在大豆分枝相关候选基因57个。本文发掘的分枝发育相关基因信息为大豆分枝相关QTL的精细定位和克隆以及大豆分枝发育的分子生物学基础研究提供了参考。     

绿豆5个产量相关性状的QTL分析

利用绿豆(Vigna radiata)品种苏绿16-10和潍绿11杂交构建的F₂和F₃群体发掘调控绿豆产量相关性状的遗传位点。同时对绿豆产量相关性状进行表型鉴定和相关性分析, 并利用构建的遗传连锁图谱进行QTL定位。结果表明, 单株产量与单株荚数、单荚粒数、百粒重和分枝数均呈正相关。单株产量与单株荚数的相关性最高, 这2个性状在F₂和F₃群体中的相关系数分别为0.950和0.914。在F₂群体中, 共检测到8个与产量性状相关的QTL位点, 其中与单株荚数、单荚粒数和单株产量相关的QTL位点各1个, 分别解释11.09% (qNPP3)、17.93% (qNSP3)和14.18% (qYP3)的表型变异; 2个与分枝数相关的QTL位点qBMS3和qBMS11, 分别解释18.51%和7.06%的表型变异; 3个与百粒重相关的QTL位点qHSW3、qHSW7和qHSW10, 分别解释5.33%、46.07%和4.24%的表型变异。在F₃群体中, qNSP3和qHSW7再次被检测到, 表明这2个QTLs有较好的遗传稳定性。同时, 开发了1个与百粒重主效QTL qHSW7紧密连锁的InDel标记R7-13.4, 并利用自然群体对该分子标记辅助筛选的有效性进行了验证。研究结果可为绿豆产量相关性状基因的定位、克隆及分子标记辅助育种提供参考。     

水稻抗白叶枯病基因Xa12区间连锁图的构建

利用SSR标记对143株Java14/珍珠矮F₂随机群体进行分析,构建了水稻第4染色体上抗白叶枯病基因Xa12高饱和度的SSR标记区间连锁图。该分子图谱整合了SSR标记RM349、RM348、RM255、MRG4611,为进一步利用SSR标记在Java14/珍珠矮F₂群体中精细定位Xa12以及克隆该基因奠定了基础。     

Validation and high-resolution mapping of a major quantitative trait locus for alkaline salt tolerance in soybean using residual heterozygous line

Alkaline soil restricts soybean plant growth and yield. In our previous study, a major alkaline salt tolerance quantitative trait locus (QTL) was identified in soybean on chromosome 17. In this study, the residual heterozygous line (RHL46), which was selected from a population of F6 recombinant inbred lines (RILs) derived from a cross between an alkaline salt-sensitive soybean cultivar Jackson and a tolerant wild soybean accession JWS156-1, was used for validation and high-resolution mapping of the QTL. In a large segregating population (n = 1,109), which was produced by self-pollinating heterozygotes of RHL46, segregation of alkaline salt tolerance showed a continuous distribution, and the tolerant plants were predominant. Linkage mapping analysis revealed a major QTL with a large dominant effect for alkaline salt tolerance, and the highest LOD score was detected between the single sequence repeat (SSR) markers GM17-12.2 and Satt447. Furthermore, 10 fixed recombinant lines carrying chromosome fragments of different lengths in the QTL region were selected from the RHL46 progeny. Phenotype evaluation and SSR marker analysis of the recombinant lines narrowed down the QTL to a 3.33-cM interval region between the markers GM17-11.6 and Satt447 with a physical map length of approximately 771 kb. High-resolution mapping of the alkaline salt tolerance QTL will be useful not only for marker-assisted selection in soybean breeding programs but also for map-based cloning of the alkaline salt tolerance gene in order to understand alkaline salt tolerance in soybean and other plant species.     

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。     

Efficient Method for Analysis of QTL Using F1 Progenies in an Outcrossing Species

In the present paper, we proposed a statistical procedure based on composite interval mapping for accurate analysis of quantitative trait loci (QTL) for individuals sampled from an outcrossing population with two-generation families consisting of the sampled individuals and F1 progenies obtained by crossing them as parental individuals. In the proposed procedure, haplotypes of markers of parental individuals were reconstructed based on the genotypes of F1 progenies and QTL analyses with composite interval mapping were conducted separately for each of parents as well as jointly for both parents. A least squares method was applied to the composite interval mapping, where some of markers were selected as cofactors to absorb the variation induced by QTL located elsewhere in the genome. The procedure was evaluated for the efficiency in detecting QTL and the precision of estimates of locations and effects of QTL using simulations. It was shown that QTL with interaction between paternal and maternal alleles was effectively detected by joint analysis of both parents, while a QTL segregating only in one parent, closely linked to a QTL segregating only in the other parent, was successfully detected by analyzing separately each of the parents with inclusion of markers of both parents. The proposed procedure can provide detailed genetic information useful for marker assisted breeding in an outcrossing species such as forest trees.     

Molecular mapping of QTLs for resistance to the greenbug <Emphasis Type="Italic">Schizaphis graminum</Emphasis> (Rondani) in <Emphasis Type="Italic">Sorghum bicolor</Emphasis> (Moench)

Sorghum is a worldwide important cereal crop and widely cultivated for grain and forage production. Greenbug, Schizaphis graminum (Rondani) is one of the major insect pests of sorghum and can cause serious damage to sorghum plants, particularly in the US Great Plains. Identification of chromosomal regions responsible for greenbug resistance will facilitate both map-based cloning and marker-assisted breeding. Thus, a mapping experiment was conducted to dissect sorghum genetic resistance to greenbug biotype I into genomic regions. Two hundred and seventy-seven (277) F(2) progeny and their F(2:3) families from a cross between Westland A line (susceptible parent) and PI550610 (resistant parent) combined with 118 polymorphic simple sequence repeat (SSR) markers were used to map the greenbug resistance QTLs. Composite interval mapping (CIM) and multiple interval mapping (MIM) revealed two QTLs on sorghum chromosome nine (SBI-09) consistently conditioned the resistance of host plant to the greenbug. The two QTLs were designated as QSsgr-09-01 (major QTL) and QSsgr-09-02 (minor QTL), accounting for approximately 55-80%, and 1-6% of the phenotypic variation for the resistance to greenbug feeding, respectively. These resistance QTLs appeared to have additive and partially dominant effects. The markers Xtxp358, Xtxp289, Xtxp67 and Xtxp230 closely flanked the respective QTLs, and can be used in high-throughput marker-assisted selections (MAS) for breeding new resistant parents and producing commercial hybrids.     

Quantitative trait loci (QTL) mapping of blush skin and flowering time in a European pear (<Emphasis Type="Italic">Pyrus communis</Emphasis>) progeny of ‘Flamingo’ × ‘Abate Fetel’

Blush skin and flowering time are agronomic traits of interest to the Agricultural Research Council (ARC) Infruitec-Nietvoorbij pear breeding programme. The genetic control of these traits was investigated in the pear progeny derived from ‘Flamingo’ (blush cultivar) × ‘Abate Fetel’ (slightly blush) made up of 121 seedlings. Blush skin was scored phenotypically over three seasons and flowering time was scored over two seasons. A total of 160 loci from 137 simple sequence repeat (SSR) markers were scored in the progeny and used to construct parental genetic linkage maps. Quantitative trait loci (QTL) analysis revealed two QTLs for blush skin, a major QTL on linkage group (LG) 5 in ‘Flamingo’, and a major QTL on LG9 in ‘Abate Fetel’. Two SSR markers, NB101a and SAmsCO865954, were closely linked with the major QTL on LG5 in ‘Flamingo’, with alleles 139 bp and 462 bp in coupling, respectively. These markers were present in approximately 90% of the seedlings scored as good blush (class 4) based on the average data set. These two markers were used to genotype other pear accessions to validate the QTL on LG5 with the view of marker-assisted selection. Two candidate genes, MYB86 and UDP-glucosyl transferase, were associated with the QTL on LG5 and MYB21 and MYB39 were associated with the QTL on LG9. QTL analysis for flowering time revealed a major QTL located on LG9 in both parents. Marker GD142 with allele 161 bp from ‘Flamingo’ was present in approximately 88% of the seedlings that flowered earlier than either parent, based on the average data set. The QTLs and linked markers will facilitate marker-assisted selection for the improvement of these complex traits.     

QTL mapping of resistance to Fusarium ear rot using a RIL population in maize

Fusarium ear rot is a prevalent disease in maize, reducing grain yields and quality. Resistance breeding is an efficient way to minimize losses caused by the disease. In this study, 187 lines from a RIL population along with the resistant (87-1) and susceptible (Zong 3) parents were planted in Zhengzhou and Beijing with three replications in years 2004 and 2006. Each line was artificially inoculated using the nail-punch method. Significant genotypic variation in response to Fusarium ear rot was detected in both years. Based on a genetic map containing 246 polymorphic SSR markers with average genetic distances of 9.1 cM, the ear-rot resistance QTL were firstly analyzed by composite interval mapping (CIM). Three QTL were detected in both Zhengzhou and Beijing in 2004; and three and four QTL, respectively, were identified in 2006. The resistant parent contributed all resistance QTL. By using composite interval mapping and a mixed model (MCIM), significant epistatic effects on Fusarium ear rot as well as interactions between mapped loci and environments were observed across environments. Two QTL on chromosome 3 (3.04 bin) were consistently identified across all environments by the two methods. The major resistant QTL with the largest effect was flanked by markers umc1025 and umc1742 on chromosome 3 (3.04 bin), explaining 13–22% of the phenotypic variation. The SSR markers closely flanking the major resistance QTL will facilitate marker-assisted selection (MAS) of resistance to Fusarium ear rot in maize breeding programs.     

大豆油份含量QTL的定位

以大豆杂交组合皖82-178×通山薄皮黄豆甲衍生的重组自交系群体(RIL)为材料, 以该群体所构建的遗传连锁图谱为基础, 以2004和2005年油份含量为指标, 利用软件Cartgrapher(V. 2.0)采用复合区间作图法进行了QTL分析, 结果表明, 利用两年资料对油份含量QTL的定位结果基本一致。两年资料所检测到的QTL均位于wt-11连锁群的satt331附近, 分别可以解释13.95%和15.01%遗传变异。此外, 利用软件QTL Mapper 1.6, 采用复合区间作图法直接对两年的油份含量进行QTL联合分析, 结果表明, 控制油份的QTL也位于wt-11连锁群的satt331附近。     

Identification of quantitative trait loci (QTL) for fruit-quality traits and number of weeks of flowering in the cultivated strawberry

Fruit quality and repeat flowering are two major foci of several strawberry breeding programs. The identification of quantitative trait loci (QTL) and molecular markers linked to these traits could improve breeding efficiency. In this work, an F₁ population derived from the cross ‘Delmarvel’ × ‘Selva’ was used to develop a genetic linkage map for QTL analyses of fruit-quality traits and number of weeks of flowering. Some QTL for fruit-quality traits were identified on the same homoeologous groups found in previous studies, supporting trait association in multiple genetic backgrounds and utility in multiple breeding programs. None of the QTL for soluble solids colocated with a QTL for titratable acids, and, although the total soluble solid contents were significantly and positively correlated with titratable acids, the correlation coefficient value of 0.2452 and independence of QTL indicate that selection for high soluble solids can be practiced independently of selection for low acidity. One genomic region associated with the total number of weeks of flowering was identified quantitatively on LG IV-S-1. The most significant marker, FxaACAO2I8C-145S, explained 43.3 % of the phenotypic variation. The repeat-flowering trait, scored qualitatively, mapped to the same region as the QTL. Dominance of the repeat-flowering allele was demonstrated by the determination that the repeat-flowering parent was heterozygous. This genomic region appears to be the same region identified in multiple mapping populations and testing environments. Markers linked in multiple populations and testing environments to fruit-quality traits and repeat flowering should be tested widely for use in marker-assisted breeding.     

QTL detection and MAS selection efficiency for lipid content in brown rice (Oryza sativa L.)

Rice lipid content as one of important ingredients of functional food and industrial products has become an entirely new target in the rice breeding programs worldwide. A genetic linkage map spanning 12 rice chromosomes with an average interval of 10.51 cM between markers was created using 172 DNA markers, which intended to elucidate genetic basis of lipid content in brown rice by QTL detection. Eight QTLs related to lipid content with LOD from 2.52 to 7.86 were mapped on chromosome1, 2, 3, 5, 6, 7 and 9 using a doubled haploid (DH) population from a cross of ‘Samgang/Nagdong’ with field experiments for five years. Two QTLs of qLC5.1 and qLC6.1 in the intervals 5014-5024 and 6011-RM19696 were repeatedly detected over four years at average LOD scores of 4.85 and 4.21, respectively. Five of eight QTLs tend to increase the lipid content from ‘Samgang’ alleles. Epistatic and environmental effects played important roles and explained 42.20% of phenotype variations. Three QTLs of qLC6.1, qLC7.1 and qLC9.1 collectively explained much than 27% of phenotype variations and increased 0.25% of lipid content and, showed much than 85% of selection efficiency for the lines with high lipid contents in the F7 population from a cross of ‘Samgang/Nagdong’. Thus it provides the sufficient possibility to realize QTLs pyramiding and to promote process of rice breeding.