利用置换系检测棉花第22染色体短臂的产量相关性状QTLs

CSB22sh为以陆地棉(Gossypium.hirsutum L.)遗传标准系TM-1为背景的第22染色体短臂被海岛棉(Gossypium.barbadense L.)Pima3-79置换的海陆置换系。TM-1与CSB22sh杂交,构建了104个F2单株的作图群体,应用6748对SSR引物对亲本进行分子标记筛选,获得90个多态性标记位点。其中85个标记位点构建了总长85.24 cM的遗传图谱,标记间平均距离1.0 cM,覆盖棉花基因组的1.8%。通过复合区间作图法对F2:3和F2:4家系的7个产量相关性状(衣分、铃重、子指、株高、第一果枝节位、单株铃数、单株果枝数)进行QTL检测,共检出28个不同QTLs,解释性状表型变异的3.5%～44.8%。仅在一个环境中检测到的QTLs有17个,2个环境同时检测到的QTLs有8个,3个环境同时检测到的QTLs有3个。不同的QTL在相同区段的成簇分布表明,控制不同性状的基因可能紧密连锁或一因多效。检测到的稳定的QTL可以用于相应性状的分子标记辅助选择。     

渝棉1号优质纤维QTL的标记与定位

利用陆地棉遗传标准系TM-1和优质品种渝棉1号组建了(TM-1×渝棉1号) F₂和F_2:3分离群体。通过5 544对SSR引物对亲本进行筛选,获得178个多态性标记,用其中138个构建了总长为959.7 cM的遗传图谱,覆盖棉花基因组的19%。应用复合区间作图法分析了该组合的F₂单株和F₃家系纤维品质性状,共检测到12个纤维品质数量性状基因座(QTL),包括1个纤维长度的、4个纤维强度的、3个马克隆值的、3个整齐度的和1个伸长率的,分别解释各性状表型变异的6.1%、5.31%~14.62%、7.88%~19.17%、7.4%~11.71%和8.26%。研究还发现Chr.23和Chr.24是优质纤维QTLs的富集区。     

杂交棉‘冀1518’纤维品质性状的QTL定位及遗传分析

‘冀1518’是以优质品种‘冀228’为母本,丰产品系‘冀567’为父本配制的适机采杂交棉新品种,为挖掘‘冀1518’的优异纤维品质相关分子标记,本研究利用杂交棉‘冀1518’的亲本构建了F_2、F_(2:3)和F_(2:9)(重组近交系)(recombinant inbred lines, RILs)三个世代的分离群体,并利用SSR分子标记分别以F_2群体和RIL(F_(2:9))群体构建遗传连锁图谱,并对纤维品质性状进行定位。结果表明,F_2作图群体共有15个标记位点连锁,包含4个连锁群,全长覆盖237.10 cM,RIL (F_(2:9))作图群体共有45个标记位点连锁,包含11个连锁群,全长覆盖554.42 cM。利用QTL IciMapping 4.1对F_2、F_(2:3)和RIL (F_(2:9))群体的纤维品质性状进行复合区间作图法分析,在F_2及F_(2:3)分离群体能同时检测到15个与纤维品质相关的QTLs,其中,与马克隆值相关的QTL位点q FM-4-2解释表型变异率最高,为21.10%,显性或超显性效应的QTLs占总数的66.7%,表明显性基因是‘冀1518’纤维品质杂种优势的主要来源。在RIL (F_(2:9))群体定位到6个与纤维品质性状相关的QTLs,解释表型变异率在5.10%～10.26%之间。F_2、F_(2:3)和RIL (F_(2:9))群体均能在HAU2349附近(F_(2:9)作图, 0.31 cM)检测到与断裂比强度和马克隆值相关的QTL位点,在HAU2710附近(F_(2:9)作图, 0.84 cM)检测到与整齐度相关的QTL位点,且上述两标记连锁,连锁区段被定位在A6染色体上。本研究获得在多世代中稳定表达的QTLs,有望用于纤维品质分子标记辅助选择,提高育种效率。     

陆海高代回交群体抗黄萎病QTL定位

【目的】定位棉花抗黄萎病数量性状位点(Quantitative trait loci, QTL)。【方法】以海7124和TM-1配制抗感组合F1,再以鲁棉研28为轮回亲本构建的137个BC4F1家系为作图群体,筛选出多态性重复序列(Simple sequence repeat, SSR)标记,并与已发表的整合高密度遗传连锁图谱相比对,构建遗传图谱。采用复合区间作图法(Composite interval mapping,CIM)进行大田和病圃两个环境下抗黄萎病QTL定位。【结果】216个多态性SSR位点分布在26条染色体上,可覆盖棉花基因组3 380 cM(centi Morgan),标记间平均距离15.77 cM。定位到6个QTLs,分布在6条染色体上,可解释表型变异8.56%~20.26%,其中5个QTLs与前人研究结果相一致,在第1染色体上新定位到一个QTL。本研究可为分子标记辅助选择抗病育种提供帮助。【结论】定位到6个黄萎病相关QTLs,其中1个是在第1染色体上新发现的QTL。     

短季棉早熟性的分子标记及QTL定位

以两个陆地棉品种中棉所36×TM-1的207个F2单株为作图群体,筛选出73个多态性引物,25个SSR标记、35个RAPD标记和13个SRAP标记,构建了第一张以研究短季棉为主的包含43个标记,标记间的最小遗传距离为11.8 cM,最大遗传距离为48.9 cM,总长1174.0 cM的遗传连锁图谱,覆盖棉花基因组总长度的23.48%。检测到与短季棉早熟性状相关的12个QTLs,其中有8个QTLs呈簇分布在LG1连锁群上,找到对表型变异的贡献率在30%以上与全生育期、霜前花率和开花期有关的QTL各1个。     

基于两个陆地棉低世代群体定位纤维品质相关QTL

【目的】定位棉花纤维品质性状相关的数量性状位点(Quantitative trait locus,QTL)。【方法】以陆地棉高强纤维品系中棉所679和纤维品质一般的农垦5号为亲本构建包含200个单株的F2群体及对应的F2:3家系群体,对2个群体的纤维长度、断裂比强度等5个纤维品质性状进行检测。用6 688对简单重复序列(Simple sequence repeat, SSR)引物在双亲间筛选,得到149对多态性引物,以F2为作图群体,使用QTL IciMapping软件进行连锁图谱构建,并对F2及F2:3群体进行QTL定位。【结果】根据F2群体基因型信息构建了1张包含119个标记、28个连锁群、总长为1 173.5 cM(centiMorgan)的遗传连锁图谱。分别在F_2、F2:3群体中检测到9个和11个与纤维品质性状相关的QTLs,这些QTLs分布在11个连锁群上。其中F2群体的qFL-D11-1、q BT-D11-1与F2:3群体的qFL-D11-1、q MIC-D11-1均定位在标记DPL0062与HAU0423之间,推测这些位点可能是控制纤维品质性状的重要QTL。【结论】利用多个群体进行QTL定位有益于发现稳定的QTL位点,控制纤维品质性状的基因可能成簇存在,为挖掘纤维品质性状相关基因及分子标记辅助育种奠定基础。     

利用大豆四向重组自交系群体定位产量相关性状QTL

为探明大豆产量与株高、主茎节数、单株荚数、单株粒数、百粒质量等产量构成因素间的相关性,定位控制这些性状的QTL进而提高大豆产量,以4个产量相关性状差异较大的大豆亲本配制双交组合(垦丰14×垦丰15)×(黑农48×垦丰19)衍生的包含160个株系的四向重组自交系群体(FW-RIL)为材料,在哈尔滨(2013-2015年)和克山(2013,2015年)种植,获得的株高、主茎节数、单株荚数、单株粒数、百粒质量的表型数据,结合已经构建的包含275个SSR标记的大豆遗传图谱对产量相关性状QTL进行定位。结果表明:在多个环境下重复稳定检测到产量相关性状的QTL 28个,其中10个株高QTL可解释表型变异率在3.20%～11.72%,3个主茎节数QTL可解释表型变异率分别为6.55%,5.70%,3.77%,9个单株荚数QTL可解释表型变异率在2.60%～11.25%,4个百粒质量QTL可解释表型变异率在3.83%～9.35%,2个单株粒数QTL可解释表型变异率分别为8.58%,7.52%;28个多环境重复检测到的产量性状QTL,其中16个QTL是本研究新检测到的,12个与国内外报道过的产量相关性状QTL位点一致,说明QTL检测准确率较高。利用分子标记遗传图谱,定位控制产量相关性状的QTL,为利用分子标记改良大豆产量潜力提供了有力手段。     

基于两个陆地棉低世代群体定位纤维品质相关QTL

【目的】定位棉花纤维品质性状相关的数量性状位点(Quantitative trait locus,QTL)。【方法】以陆地棉高强纤维品系中棉所679和纤维品质一般的农垦5号为亲本构建包含200个单株的F2群体及对应的F2:3家系群体,对2个群体的纤维长度、断裂比强度等5个纤维品质性状进行检测。用6 688对简单重复序列(Simple sequence repeat, SSR)引物在双亲间筛选,得到149对多态性引物,以F2为作图群体,使用QTL IciMapping软件进行连锁图谱构建,并对F2及F2:3群体进行QTL定位。【结果】根据F2群体基因型信息构建了1张包含119个标记、28个连锁群、总长为1 173.5 cM(centiMorgan)的遗传连锁图谱。分别在F_2、F2:3群体中检测到9个和11个与纤维品质性状相关的QTLs,这些QTLs分布在11个连锁群上。其中F2群体的qFL-D11-1、q BT-D11-1与F2:3群体的qFL-D11-1、q MIC-D11-1均定位在标记DPL0062与HAU0423之间,推测这些位点可能是控制纤维品质性状的重要QTL。【结论】利用多个群体进行QTL定位有益于发现稳定的QTL位点,控制纤维品质性状的基因可能成簇存在,为挖掘纤维品质性状相关基因及分子标记辅助育种奠定基础。     

冀豆12遗传图谱初步构建

以优良大豆品种冀豆12与野生大豆ZYD02738杂交建立基础群体,利用F2为作图群体,研究SSR标记位点在该群体中的多态性、偏分离并构建遗传图谱.结果表明,两亲本间SSR位点多态性比例79.9%,偏分离位点比例9.7%,构建的遗传图谱包含25个连锁群,总长度837.1 cM,标记间平均距离11.2 cM,标记间排列顺序与公共连锁图一致性较强.该研究为国内学者研究冀豆12遗传网络和重要农艺性状的基因、QTL定位等研究奠定了初步基础.     

陆地棉高品质品系纤维品质性状QTL的分子标记及定位

为进一步挖掘利用高品质品系NM03102的优异纤维品质性状的基因,利用陆地棉鲁棉研21作为母本、NM03102为父本构建了F2和F2∶3分离群体。通过7892对SSR引物对亲本进行筛选,获得222对多态性引物,进一步对195个F2群体单株分析得到242个标记位点。其中,182个标记位点连锁构建37个连锁群,共覆盖1661.6 cM,每个连锁群平均包含4.9个标记位点,标记间平均相距9.1 cM,其中35个连锁群被定位到了20条染色体上。利用F2和F2∶3纤维品质数据,通过复合区间作图法,共检测到20个纤维品质性状QTL。其中,1个纤维强度的QTL和1个纤维整齐度的QTL与已有的报道一致,1个纤维强度的QTL和1个麦克隆值的QTL在两世代中稳定存在,这为标记辅助选择奠定了基础。     

栽培种花生荚果大小相关性状QTL定位

以远杂9102为母本,徐州68-4为父本杂交衍生的F5和F6共188个家系,构建了一张包含365个标记,总长度713.07 c M,标记间平均距离1.96 c M的栽培种花生遗传图谱。图谱包含22个连锁群,各连锁群平均长度12.37~81.39 c M,连锁群上标记数量3~46个。结合2013和2014年采集的荚果表型数据,采用Win QTLcart 2.5软件的复合区间作图法(composite interval mapping,CIM)进行QTL定位和效应估计。2个环境下共检测到41个QTL,其中与荚果长、宽、厚和百果重相关的QTL分别为13、7、13和8个,表型变异解释率为3.14%~18.27%。有6个QTL在2种环境下被重复检测到,其中百果重相关的2个(q HPWLG13.1、q HPWLG14.1),分布在LG13和LG14连锁群,遗传贡献率为6.95%~14.60%;与荚果长相关的3个(q LPLG2.2、q LPLG13.1、q LPLG14.1),分布在LG2、LG13和LG14连锁群,遗传贡献率为3.14%~18.27%;与荚果厚相关的1个(q TPLG3.4),分布在LG3连锁群,遗传贡献率为8.24%~9.24%。本研究涉及性状存在9个QTL热点区,每个热点区涉及2~3个性状,表型贡献率为3.57%~18.27%。     

玉米幼胚愈伤组织的诱导和植株再生的QTL分析

以黄早四和Mo17为亲本组配的239个RIL群体，构建了101个SSR标记的遗传图谱，覆盖玉米基因组1 422.7 cM，标记间的平均距离为15.6 cM。以玉米幼胚为外植体、改良N6为基本培养基，对亲本及RIL群体的组培性状进行了评价。采用复合区间作图法在第2、3、5、6、8和9染色体上定位了控制出愈率、Ⅱ型愈伤组织诱导率、绿点及绿苗分化率的8个QTL，并对其遗传效应进行了分析，其基因加性效应能解释相应性状表型方差的4.78%~14.02%。     

海岛棉CSSLs分子评价及纤维品质、产量性状QTL定位

本课题组前期以陆地棉中棉所8号(CCRI8)为轮回亲本, 海岛棉Pima 90-53为供体亲本培育了一套陆地棉中棉所8号为背景的海岛棉染色体片段置换系(CSSLs), 本研究利用SSR标记对该置换系群体BC₃F₅进行基因型检测, 在3个不同环境下(河北保定、青县和新疆轮台)鉴定其纤维品质和产量相关性状并进行QTL定位。该置换系群体包含182个家系, 置换片段数在1~15个之间, 平均为6.6个; 导入片段长度在0.7~83.2 cM之间, 平均长度为16.8 cM; 置换片段总长度20 249.6 cM; 背景回复率在92.3%~99.6%之间, 平均为96.2%。共检测出59个相关的QTL, 其中与纤维品质性状相关的41个, 单个QTL的贡献率为1.27%~26.66%; 与产量性状相关的18个, 单个QTL的贡献率为2.03%~19.38%; 检测到14个稳定的QTL, 其中4个马克隆值和2个纤维伸长率相关的稳定QTL增效基因均来自高值亲本海岛棉Pima 90-53, 2个铃重相关的稳定QTL增效基因来自高值亲本陆地棉中棉所8号。研究结果为深入开展纤维品质和产量性状的QTL精细定位、QTL间互作和分子育种提供了理论依据。     

Identification of QTLs for rice grain size and shape of Iranian cultivars using SSR markers

Grain size is a main component of rice appearance quality. In this study, we performed the SSR mapping of quantitative trait loci (QTLs) controlling grain size (grain length and breadth) and shape (length/breadth ratio) using an F₂ population of a cross between two Iranian cultivars, Domsephid and Gerdeh, comprising of 192 individuals. A linkage map with 88 markers was constructed, which covered 1367.9 cM of the rice genome with an average distance of 18 cM between markers. Interval mapping procedure was used to identify the QTLs controlling three grain traits, and QTLs detected were further confirmed using composite interval mapping. A total of 11 intervals carrying 18 QTLs for three traits were identifed, that included five QTLs for grain length, seven QTLs for grain breadth, and six QTLs for grain shape. A major QTL for grain length was detected on chromosome 3, that explained 19.3% of the phenotypic variation. Two major QTLs for grain breadth were mapped on chromosomes 3 and 8, which explained 34.1% and 20% of the phenotypic variation, respectively. Another two major QTLs were identified for grain shape on chromosomes 3 and 8, which accounted for 27.1% and 20.5% of the phenotypic variance, respectively. The two QTLs that were mapped for grain shape coincided with the major QTLs detected for grain length and grain breadth. Intrestingly, gs2 QTL specific to grain shape was detected on chromosome 2 that explained 15% of the phenotypic variation.     

Molecular mapping of quantitative trait loci for domestication traits and β-glucan content in a wheat recombinant inbred line population

Genetic maps are useful for analysis of quantitative trait loci (QTLs) and for marker-assisted selection (MAS) in breeding. A simple sequence repeat (SSR) marker linkage map of common wheat was constructed based on recombination inbred lines (RILs) derived from a cross between Chinese Spring and spelt wheat. The map included 264 loci on all wheat chromosomes covering 2,345.2 cM with 962, 794.6, and 588.6 cM for the A, B, and D genomes, respectively. Using the RILs and the map, we detected 42 putative QTLs on 15 chromosomes for ear length, spikelet number, spike compactness, kernel length, kernel width, kernel height and β-glucan content. Each QTL explained 4–45% of the phenotypic variation. Five QTL cluster regions were detected on chromosomes 1A, 5AL, 2B, 2D, and 4D. The first QTLs for β-glucan content in wheat were identified on chromosomes 3A, 1B, 5B, and 6D.     

Identification of QTL for stalk sugar-related traits in a population of recombinant inbred lines of maize

Increasing sugar content in silage maize stalk improves its forage quality and palatability. The genetic mapping and characterization of quantitative trait loci (QTLs) is considered a valuable tool for trait enhancement, yet little information on QTL for stalk sugar content in maize has been reported. To this end, we investigated QTLs associated with stalk sugar traits including Brix, plant height (PHT), three ear leaves area (TELA), and days to silking (DTS) in two environments using a population of 202 recombinant inbred lines from a cross between YXD053, which has a high stalk sugar content, and Y6-1, which has a low stalk sugar content. A genetic map with 180 SSR and 10 AFLP markers was constructed, which spanned 1,648.6 cM of the maize genome with an average marker distance of 8.68 cM, and QTLs were detected using composite interval mapping. Seven QTLs controlling Brix were mapped on chromosomes 1, 2, 6 and 9 in the combined environments. These QTLs could explain 2.69–13.08 % of the phenotypic variance. One major QTL for Brix on chromosome 2 located between the markers bnlg1909 and umc1635 explained 13.08 % of the phenotypic variance. Y6-1 also contributed QTL allele for increased Brix on chromosome 6. One major QTLs controlling PHT on chromosome 1 and TELA on chromosome 4 were also identified and accounted for 13.68 and 12.49 % of the phenotypic variance, respectively. QTL alleles for increased DTS were located on chromosomes 1 and 5 of YXD053. Significant epistatic effects were identified in four traits, but no significant QTL × environment interactions were observed. The information presented here may be valuable for stalk sugar content improvement via marker-assisted selection in silage maize breeding programs.     

Quantitative Traits Locus Meta-analysis of Fiber Quality Traits in Cotton

Using bioinformatics methods and meta-analysis with BC₁ map as reference, 92 cotton fiber quality QTL collected from both BC₁ and BC₁F₂ populations constructed previously were used to construct a QTL integrated map for QTL analysis in this study. The five hundred ninety-nine loci were mapped into 26 chromosomes with an average distance between adjacent markers of 5.96 cM and covered 3,571.9 cM. Sixty-three QTL of fiber qualities related were integrated into the new reference map. The fifteen meta-QTL were mapped on 12 chromosomes by the meta-analysis method and also QTL clusters have been discovered on chromosome 9, 16 and 24. The major meta-QTL of Meta-QTL9-1 derived from five QTL on chromosome 9, could explain 17.16% of phenotypic variance. The meta-QTL16-1 derived from ten QTL on chromosome 16, could explain 12.28% of phenotypic variance. And three meta-QTL derived from nine QTLs on chromosome 24, could explain 16.12%,16.69% and 18.27% of phenotypic variance, respectively. On average, one meta-QTL derived from two QTLs on the other chromosomes. The results indicated that these meta-QTL could be used in improving fine QTL mapping and molecular-assisted selection of cotton fiber qualities in breeding.     

Quantitative trait loci (QTL) mapping of silique length and petal colour in Brassica rapa

Recombinant inbred lines (RILs) derived from a cross between Brassica rapa L. cv. ‘Sampad’, and an inbred line 3‐0026.027 was used to map the loci controlling silique length and petal colour. The RILs were evaluated under four environments. Variation for silique length in the RILs ranged from normal, such as ‘Sampad’, to short silique, such as 3‐0026.027. Three QTL, SLA3, SLA5 and SLA7, were detected on the linkage groups A3, A5 and A7, respectively. These QTL explained 36.0 to 42.3% total phenotypic variance in the individual environments and collectively 32.5% phenotypic variance. No additive × additive epistatic interaction was detected between the three QTL. Moreover, no QTL × environment interaction was detected in any of the four environments. The number of loci for silique length detected based on QTL mapping agrees well with the results from segregation analysis of the RILs. In case of petal colour, a single locus governing this trait was detected on the linkage group A2.     

QTL Mapping of Boll Weight Trait Based on Recombinant Inbred Lines in Gossypium hirsutum L.

[Objective] The aim of this study was to explore the quantitative trait locus (QTL) related to the boll weight. [Method] A single seed descended population of 137 recombinant inbred lines (RILs) was developed from the cross of upland cotton (Gossypium hirsutum L.) CCRI 36 and G2005, an introgression inbred line introgressed from G. barbadense. Using restriction-site associated DNA sequencing (RAD-seq), a genetic linkage map composed of 6 434 makers, including 6 295 single nucleotide polymorphisms (SNP) and 139 simple sequence repeat (SSR) markers, was developed from the RILs population. [Result] This map spanned 4 071.98 cM with an average distance of 0.63 cM between adjacent markers. QTL mapping was performed by using boll weight data of five environments through WinQTLCart 2.5 software. Thirty-two QTL, with 4.46%-15.84% explained phenotypic variation related boll weight, were detected and found distributing on 15 chromosomes. qBW-A4-1, qBW-A4-2, qBW-A5-2, qBW-D9-1, and qBW-D9-2 were detected in two environments, which explained 5.07%-15.84% of the phenotypic variation. [Conclusion] Major QTLs detected in this study will provide an important reference for analysis of the genetic mechanism of boll weight.     

QTL analysis for grain weight in common wheat

Quantitative trait loci (QTL) analysis for grain weight (GW = 1000 grain weight) in common wheat was conducted using a set of 100 recombinant inbred lines (RILs) derived from a cross ‘Rye Selection 111 (high GW) × Chinese Spring (low GW)’. The RILs and their two parental genotypes were evaluated for GW in six different environments (three locations × two years). Genotyping of RILs was carried out using 449 (30 SSRs, 299 AFLP and 120 SAMPL) polymorphic markers. Using the genotyping data of RILs, framework linkage maps were prepared for three chromosomes (1A, 2B, 7A), which were earlier identified by us to carry important/major genes for GW following monosomic analysis. QTL analysis for GW was conducted following genome-wide single marker regression analysis (SMA) and composite interval mapping (CIM) using molecular maps for the three chromosomes. Following SMA, 12 markers showed associations with GW, individual markers explaining 6.57% to 10.76% PV (phenotypic variation) for GW in individual environments. The high grain weight parent, Rye Selection111, which is an agronomically superior genotype, contributed favourable alleles for GW at six of the 12 marker loci identified through SMA. The CIM identified two stable and definitive QTLs, one each on chromosome arms 2BS and 7AS, which were also identified through SMA, and a third suggestive QTL on 1AS. These QTLs explained 9.06% to 19.85% PV for GW in different environments. The QTL for GW on 7AS is co-located with a QTL for heading date suggesting the occurrence of a QTL having a positive pleiotropic effect on the two traits. Some of the markers identified during the present study may prove useful for marker-assisted selection, while breeding for high GW in common wheat.