Identification and validation of major QTL for grain size and weight in bread wheat(Triticum aestivum L.)

Grain size and weight are key components of wheat yield.Exploitation of major underlying quantitative trait loci(QTL)can improve yield potential in wheat breeding.A recombinant inbred line(RIL)population was constructed to detect QTL for thousand-grain weight(TGW),grain length(GL)and grain width(GW)across eight environments.Genomic regions associated with grain size and grain weight were identified on chromosomes 4A and 6A using bulked segregant exome sequencing(BSE-Seq)analysis.After constructing genetic maps,six major QTL detected in at least four individual environments and in best linear unbiased estimator(BLUE)datasets,explained 7.50%-23.45%of the phenotypic variation.Except for QGl.cib-4A,the other five QTL were co-located in two regions,namely QTgw/Gw.cib-4A and QTgw/Gw/Gl.cib-6A.Interactions of these QTL were analyzed.Unlike QTgw/Gw/Gl.cib-6A,QTgw/Gw.cib-4A and QGl.cib-4A had no effect on grain number per spike(GNS).The QTL were validated in a second cross using Kompetitive Allele Specific PCR(KASP)markers.Since QTgw/Gw.cib-4A was probably a novel locus,it and the KASP markers reported here can be used in wheat breeding.TraesCS4A03G0191200 was predicted to be potential candidate gene for QTgw/Gw.cib-4A based on the sequence differences,spatiotemporal expression patterns,gene annotation and haplotype analysis.Our findings will be useful for fine mapping and for marker-assisted selection in wheat grain yield improvement.

Analysis of Rice Grain Quality-Associated Quantitative Trait Loci by Using Genetic Mapping

The main objective of this research was to identify quantitative trait loci associated with rice qualities to provide reliable information for marker-assisted selection and development of new varieties. In total, 120 doubled haploid (DH) lines developed by another culture from the F1 hybrid of a cross between “Cheongcheong”, a Tongil variety, and “Nagdong”, a japonica variety, were used. A microsatellite linkage map of 222 markers spanned 2082.4 centimorgans (cM) and covered 12 rice chromosomes with an average interval of 9.4cM between markers. Eight quantitative trait loci (QTLs) were associated with rice quality, consisting of two QTLs on chromosomes 1 and 9 for amylose content;three QTLs on chromosomes 8, 9, and 10 for protein content;and three QTLs on chromosomes 2, 3, and 6 for lipid content. PCR expression levels measured using the SSR markers RM23914 for proteins and RM6266 for lipids, and RM586 showed a higher degree of amplification. The present study should be useful for improving the nutritional quality of rice by means of marker-assisted selection.

Fine Mapping of qTGW3-1,a QTL for 1000-Grain Weight on Chromosome 3 in Rice

The QTL qTGW3-1 was located on chromosome 3 of rice （Oryza sativa L.） and associated with the 1 000-grain weight （TGW） according to the result of our earlier study. With the objective of fine mapping of this locus, we developed a F2 population consisting of 3 428 plants derived from the cross between TGW-related near isogenic line DL017 （BC3F4 generation of GSL 156×Nipponbare） and the recurrent parent Nipponbare. Using six microsatellites, this QTL was delimited between RM5477 and RM6417. Markers MM 1455 and MM 1456 within this region were used for further mapping of this QTL. Finally, qTGW3-1 was fine-mapped into a 89-kb interval between RM5477 and MM1456, which locates in the BAC clone AC107226 harboring five putative candidate genes.

QTL Mapping of Grain Weight Trait in Rice

To provide new experimental materials for QTL analysis of rice yield trait, we constructed a mapping population of 150 1ines （recombination inbred lines, R1L） derived from a cross between rice varieties V20B and CPSLO17, and localized QTLs and evaluated the genetic effects in the two parents and 150 RILs for thousand-grain weight trait by using internal mapping method of software MapQTL5 combining thousand-grain weight phenotypic data of the RILs. The results showed that a new QTL （qTGW-3） related to thousand-grain weight trait was detected. Individual QTL （LOD=4.14） explained 11.9% of the observed phenotypic variance. And the QTL alleles came from the parent V20B.

基于高密度遗传图谱定位水稻籽粒性状QTL

籽粒性状直接影响水稻的产量和品质,因此,解析水稻籽粒性状的遗传机制对提高水稻产量和品质至关重要。本研究以籽粒性状差异较大的穞稻和广百香占为亲本构建定位群体,利用水稻1 K mGPS SNP芯片对定位群体进行基因分型,构建了包含770个Bin标记的高密度遗传图谱,通过QTL定位分析,最终鉴定出17个调控籽粒性状的QTLs,其中粒长QTL 4个,粒宽QTL 3个,粒厚QTL 3个,长宽比QTL 2个,千粒重QTL 5个,LOD值介于2.55~42.44之间,表型贡献率介于4.73%~29.63%之间。在这17个QTLs中,9个为已知粒型基因位点,8个可能是新鉴定位点,分别为粒长qGL6,粒宽qGW5、qGW10和qGW12,粒厚qGT10,长宽比qGLWR5-2,千粒重qTGW10和qTGW11。根据新发现粒宽QTL(qGW5)定位区间内的基因注释、与拟南芥的同源基因比对、时空表达分析、激素响应分析和序列分析,最终筛选到1个编码CCCH类锌指蛋白的调控水稻粒宽的候选基因Os05g0195101。本研究为进一步开展水稻籽粒性状基因的克隆和遗传调控的解析奠定了基础。

基于55K芯片小麦籽粒相关性状的QTL定位分析

为了进一步挖掘小麦籽粒相关性状的主效QTL位点,探索籽粒性状之间的遗传关系,利用籽粒性状差异较大的小麦品种安农859和武农988构建的124份DH群体为研究材料,分别测定2 a 7个环境下的粒长、粒宽及千粒质量表型值,开展籽粒性状多元回归分析,并基于DH群体的55K芯片数据进行籽粒相关性状QTL检测。结果表明,多元回归分析中,粒宽对千粒质量的贡献最大。通过完备区间作图对籽粒性状进行QTL定位,除6D和7B染色体外,其他19条染色体上共检测到69个有关籽粒性状的QTL,包括24个千粒质量QTL、28个粒长QTL、17个粒宽QTL,单个QTL的表型解释率为6.87%~27.74%。其中,7A染色体上粒长相关的Qgl.ahau-7A.1在7个环境及BLUP下均被检测到,表型解释率为9.48%~22.26%,加性效应为0.11~0.21 mm,物理区间4.91 Mb(AX-110430243~AX-110442528),可能为新的主效QTL。因此,Qgl.ahau-7A.1位点可作为后续精细定位和分子标记辅助育种重点关注的区域。

QTL Mapping for Important Agronomic Traits in Synthetic Hexaploid Wheat Derived from Aegiliops tauschii ssp. tauschii

Aegiliops tauschii is classified into two subspecies： Ae. tauschii ssp. tauschii and Ae. tauschii ssp. strangulata. Novel genetic variations exist in Ae. tauschii ssp. tauschii that can be utilized in wheat improvement. We synthesized a hexaploid wheat genotype（SHW-L1） by crossing an Ae. tauschii ssp. tauschii accession（AS60） with a tetraploid wheat genotype（AS2255）. A population consisting of 171 F8 recombinant inbred lines was developed from SHW-L1 and Chuanmai 32 to identify QTLs associated with agronomic traits. A new genetic map with high density was constructed and used to detect the QTLs for heading date, kernel width, spike length, spikelet number, and thousand kernel weight. A total of 30 putative QTLs were identified for five investigated traits. Thirteen QTLs were located on D genomes of SHW-L1, six of them showed positive effect on agronomic traits. Chromosome region flanked by wPt-6133–wPt-8134 on 2D carried five environment-independent QTLs. Each QTL accounted for more than 10% phenotypic variance. These QTLs were highly consistent across environments and should be used in wheat breeding.

优质蛋白玉米‘荃玉9号’主要营养品质性状的QTL定位

油分、蛋白质和淀粉是玉米籽粒的主要营养成分,同时也是玉米重要的品质性状。为探索更多玉米品质相关的QTL,本研究以优质蛋白玉米‘荃玉9号’构建的F2:3群体为材料,通过方差分析和QTL定位方法,对玉米籽粒品质性状(包括油分、蛋白质和淀粉含量)进行了遗传分析。在新都和简阳2地共检测到24个品质性状QTL,其中仅与油分含量、蛋白质含量和淀粉含量相关的QTL分别为9、9和2个,与多个品质性状相关的QTL为4个,QTL在10条染色体上均有分布,单个QTL可解释的表型贡献率为1.92%~34.43%。染色体上Bin7.01(6399330~8305989)的QTL在2个环境同时被检测到,可以解释12.68%~18.13%的表型变异且有加性效应,是控制玉米油分含量的主效QTL。本研究为玉米品质改良的分子辅助育种工作提供了基础数据资料,为后续的育种实践提供了有力支撑。

两个RIL群体中小麦籽粒品质相关性状QTL定位及KASP标记开发

本研究利用小麦55K SNP(55K single-nucleotide polymorphism)芯片和DArT(diversity array technology)标记对Avocet/Chilero和Avocet/Huites构建的两个F6重组自交系群体(recombinant inbred line,RIL)进行了小麦籽粒蛋白质含量(grain protein content,GPC)、湿面筋含量(wet gluten content,WGC)和沉降值(sedimentation value,SV)的QTL(quantitative trait loci)定位。共鉴定到68个与小麦籽粒蛋白质含量、湿面筋含量和沉降值相关的QTL,表型贡献率为3.60%~22.53%,其中,位于3A(2)、4D、5D(2)、6A(8)和7B染色体上的14个QTL可在多环境下被重复检测到。此外,在3A、3D、4B、5D、6A(2)和7B染色体上检测到7个QTL簇,位于3AS染色体9.32~60.01 Mb和6AS染色体38.47~82.95 Mb的稳定QTL簇C3A和C6A.2,同时与小麦籽粒蛋白质含量、湿面筋含量和沉降值显著相关,分别解释了6.55%~14.21%和3.83%~22.53%的表型变异。同时,在2个QTL簇中筛选到16个可能与籽粒蛋白质含量相关的候选基因,并根据候选基因开发了可供育种利用的KASP标记CGPC-6A-KASP-1和CGPC-6A-KASP-2。本研究为小麦籽粒品质相关性状的遗传改良提供了新的QTL位点和KASP标记,为分子标记辅助育种提供依据与参考。

QTL Mapping for Dough Mixing Characteristics in a Recombinant Inbred Population Derived from a Waxy×Strong Gluten Wheat (Triticum aestivum L.)

Protein and starch are the most important traits in determining processing quality in wheat. In order to understand the genetic basis of the influence of Waxy protein （Wx） and high molecular weight gluten subunit （HMW-GS） on processing quality, 256 recombinant inbred lines （RILs） derived from the cross of waxy wheat Nuomai 1 and Gaocheng 8901 were used as mapping population. DArT （diversity arrays technology）, SSR （simple sequence repeat）, HMW-GS, and Wx markers were used to construct the molecular genetic linkage map. QTLs for mixing peak time （MPT）, mixing peak value （MPV）, mixing peak width （MPW）, and mixing peak integral （MPI） of Mixograph parameters were evaluated in three different environments. The genetic map comprised 498 markers, including 479 DArT, 14 SSR, 2 HMW-GS, and 3 Wx protein markers, covering 4 229.7 cM with an average distance of 9.77 cM. These markers were identified on 21 chromosomes. Eighteen additive QTLs were detected in three different environments, which were distributed on chromosomes 1A, 1B, 1D, 4A, 6A, and 7D. QMPT-1D.1 and QMPT-1D.2 were close to the Glu-D1 marker accounting for 35.2, 22.22 and 36.57% of the phenotypic variance in three environments, respectively. QMPV-1D and QMPV-4A were detected in all environments, and QMPV-4A was the nearest to Wx-B1. One minor QTL, QMPI-1A, was detected under three environments with the genetic distances of 0.9 cM from the nearest marker Glu-A1, explaining from 5.31 to 6.67% of the phenotypic variance. Three pairs of epistatic QTLs were identified on chromosomes 2D and 4A. Therefore, this genetic map is very important and useful for quality trait related QTL mapping in wheat. In addition, the finding of several major QTLs, based on the genetic analyses, further suggested the importance of Glu-1 loci on dough mixing characteristics.

多环境下的稻谷粒厚QTL定位分析

【目的】粒厚性状是影响水稻产量和稻米食味品质的控制因子之一,运用籼爪交(V20B/CPSLO17)遗传背景的重组自交系(RIL)开展稻谷粒厚QTL定位分析,获得粒厚性状主效QTL,为新的粒厚基因挖掘和开发功能分子标记提供科学依据。【方法】在水稻高密度遗传连锁图谱和籼爪交遗传背景的RIL群体基础上,结合3种不同生态环境(2020年贵州贵阳、2021年贵州贵定、2021年海南三亚)下RIL群体的稻谷粒厚性表型数据,运用IciMapping 4.0软件的ICIM-ADD方法进行粒厚QTL定位及其遗传效应分析。【结果】稻谷粒厚性状在3种生态环境下均呈现连续单峰分布,其受种植环境因子影响不显著。3种不同生态环境的水稻中共检测到分布在第3、5、8和10号染色体上的5个稻谷粒厚QTL(qGT3-1、qGT5-1、qGT5-2、qGT8-1和qGT10-1),它们的增效等位基因均来自亲本V20B,LOD值在3.431~14.081,表型贡献率变幅为5.479%~26.483%。2个QTL(qGT5-1和qGT5-2)的表型贡献率超过10%,其中qGT5-2是唯一在2种生态环境(2020年贵州贵阳、2021年海南三亚)下被反复检测到的,分别解释群体表型变异率的26.483%和14.933%。QTL qGT5-2位点在染色体上的物理距离约为3.9 kb,仅有1个候选基因(LOC_Os05g07920);qGT8-1位点的物理距离约为2.3 kb,仅有1个候选基因(LOC_Os08g10360)。【结论】稻谷粒厚性状呈现出受多基因调控的数量性状遗传特性。qGT5-2是1个稳定遗传且贡献率高的稻谷粒厚主效QTL,对粒厚调控基因挖掘和优质丰产稻新品种培育具有重要的应用潜力。

小麦粒重相关性状的QTL定位及分子标记的开发

【目的】小麦是世界总产量第二的粮食作物,而粒重是影响小麦产量的重要因素。以和尚头(HST)和陇春23(LC23)衍生的216个家系重组自交系(recombinant inbred lines,RIL)群体为材料,基于55K SNP基因型数据,针对小麦粒重相关性状进行QTL定位,开发和验证粒长主效QTL的共分离标记,为分子标记辅助选择育种提供参考。【方法】利用小麦55K SNP芯片对亲本和RIL群体进行基因分型,构建高密度遗传连锁图谱,并与中国春参考基因组IWGSC RefSeq v1.0进行相关性分析。基于完备区间作图法对多环境粒重相关性状进行QTL定位;通过对主效QTL进行方差分析,判断不同QTL间的加性互作效应,并分析其对粒重相关性状的影响。同时,根据粒长主效QTL的共分离SNP位点开发相应的竞争性等位基因特异性PCR标记(kompetitive allele specific PCR,KASP),并在242份国内外小麦种质构成的自然群体中进行验证。【结果】构建了和尚头/陇春23 RIL群体的高密度遗传图谱,全长4543 cM,共包含22个连锁群,覆盖小麦21条染色体,平均遗传距离为1.7 cM。遗传图谱与物理图谱具有显著相关性,Pearson相关系数为0.77—0.99(P<0.001)。共检测到51个粒重相关QTL,其中,有4个为3个及以上环境稳定表达的主效QTL,分布在2D、5A、6B和7D染色体。根据物理区间和功能标记分析主效QTL Qtkw.nwafu-2D.1和Qtkw.nwafu-7D分别为光周期基因Ppd-D1和开花基因FT-D1,方差分析表明,二者具有显著的互作效应;Qtkw.nwafu-2D.1和Qtkw.nwafu-7D优异等位基因的聚合显著提高了小麦的千粒重和粒宽。此外,根据粒长主效位点Qgl.nwafu-5A的共分离SNP开发了相应的KASP分子标记AX-111067709,该标记在242份小麦组成的自然群体中与粒长和粒重性状显著相关,在不同环境下能增加粒长3.33%—4.59%(P<0.001)和粒重5.70%—10.35%(P<0.05)。【结论】和尚头(HST)和陇春23(LC23)的粒重相关性状由多个遗传位点控制,其中,Qtkw.nwafu-2D.1和Qtkw.nwafu-7D通过加性互作效应可显著提高小麦的千粒重和粒宽。Qgl.nwafu-5A与粒重和粒长具有显著相关性,其共分离分子标记AX-11106770可应用于分子标记辅助选择育种。

QTL analysis for some quantitative traits in bread wheat

Quantitative trait loci (QTL) analysis was conducted in bread wheat for 14 important traits utilizing data from four different mapping populations involving different approaches of QTL analysis. Analysis for grain protein content (GPC) sug- gested that the major part of genetic variation for this trait is due to environmental interactions. In contrast, pre-harvest sprouting tolerance (PHST) was controlled mainly by main effect QTL (M-QTL) with very little genetic variation due to environmental interactions; a major QTL for PHST was detected on chromosome arm 3AL. For grain weight, one QTL each was detected on chromosome arms 1AS, 2BS and 7AS. QTL for 4 growth related traits taken together detected by different methods ranged from 37 to 40; nine QTL that were detected by single-locus as well as two-locus analyses were all M-QTL. Similarly, single-locus and two-locus QTL analyses for seven yield and yield contributing traits in two populations respectively allowed detection of 25 and 50 QTL by composite interval mapping (CIM), 16 and 25 QTL by multiple-trait composite interval mapping (MCIM) and 38 and 37 QTL by two-locus analyses. These studies should prove useful in QTL cloning and wheat improvement through marker aided selection.

Identification of stable quantitative trait loci underlying waterlogging tolerance post-anthesis in common wheat(Triticum aestivum)

Waterlogging is a growing threat to wheat production in high-rainfall areas.In this study,a doubled haploid(DH) population developed from a cross between Yangmai 16(waterlogging-tolerant) and Zhongmai895(waterlogging-sensitive) was used to map quantitative trait loci(QTL) for waterlogging tolerance using a high-density 660K single-nucleotide polymorphism(SNP) array.Two experimental designs,waterlogging concrete tank(CT) and waterlogging plastic tank(PT),were used to simulate waterlogging during anthesis in five environments across three growing seasons.Waterlogging significantly decreased thousand-kernel weight(TKW) relative to non-waterlogged controls,although the degree varied across lines.Three QTL for waterlogging tolerance were identified on chromosomes 4AL,5AS,and 7DL in at least two environments.All favorable alleles were contributed by the waterlogging-tolerant parent Yangmai16.QWTC.caas-4AL exhibited pleiotropic effects on both enhancing waterlogging tolerance and decreasing plant height.Six high-confidence genes were annotated within the QTL interval.The combined effects of QWTC.caas-4AL and QWTC.caas-5AS greatly improved waterlogging tolerance,while the combined effects of all three identified QTL(QWTC.caas-4AL,QWTC.caas-5AS,and QWTC.caas-7DL) exhibited the most significant effect on waterlogging tolerance.Breeder-friendly kompetitive allele-specific PCR(KASP) markers(K_AX_111523809,K_AX_108971224,and K_AX_110553316) flanking the interval of QWTC.caas-4AL,QWTC.caas-5AS,and QWTC.caas-7DL were produced.These markers were tested in a collection of 240 wheat accessions,and three superior polymorphisms of the markers distributed over 67elite cultivars in the test population,from the Chinese provinces of Jiangsu,Anhui,and Hubei.The three KASP markers could be used for marker-assisted selection(MAS) to improve waterlogging tolerance in wheat.

Identification and validation of stable quantitative trait loci for yield component traits in wheat

Grain weight and grain number are important yield component traits in wheat and identification of underlying genetic loci is helpful for improving yield.Here,we identified eight stable quantitative trait loci(QTL)for yield component traits,including five loci for thousand grain weight(TGW)and three for grain number per spike(GNS)in a recombinant inbred line population derived from cross Yangxiaomai/Zhongyou 9507 across four environments.Since grain size is a major determinant of grain weight,we also mapped QTL for grain length(GL)and grain width(GW).QTGW.caas-2D,QTGW.caas-3B,QTGW.caas-5A and QTGW.caas-7A.2 for TGW co-located with those for grain size.QTGW.caas-2D also had a consistent genetic position with QGNS.caas-2D,suggesting that the pleiotropic locus is a modulator of trade-off effect between TGW and GNS.Sequencing and linkage mapping showed that TaGL3-5A and WAPO-A1 were candidate genes of QTGW.caas-5A and QTGW.caas-7A.2,respectively.We developed Kompetitive allele specific PCR(KASP)markers linked with the stable QTL for yield component traits and validated their genetic effects in a diverse panel of wheat cultivars from the Huang-Huai River Valley region.KASP-based genotyping analysis further revealed that the superior alleles of all stable QTL for TGW but not GNS were subject to positive selection,indicating that yield improvement in the region largely depends on increased TGW.Comparative analyses with previous studies showed that most of the QTL could be detected in different genetic backgrounds,and QTGW.caas-7A.1 is likely a new QTL.These findings provide not only valuable genetic information for yield improvement but also useful tools for marker-assisted selection.

利用基因芯片技术进行小麦遗传图谱构建及粒重QTL分析

[目的]小麦遗传图谱是进行小麦染色体分析和研究表型变异的遗传基础。通过利用传统分子标记和现代基因芯片技术相结合,构建高密度遗传图谱,重点开展主要产量主要构成要素——粒重的初级基因定位,确定影响粒重的主效QTL位点,为开发粒重CAPS分子标记及在分子标记辅助育种提供依据和指导,并为利用小麦粒重次级群体进行精细定位和基因挖掘奠定基础。[方法]利用90 K小麦SNP基因芯片、DArt芯片技术及传统的分子标记技术,以包含173个家系的RIL群体(F9:10重组自交系)为材料,构建高密度遗传图谱,并利用QTL network2.0进行了3年共4环境粒重QTL分析。[结果]构建了覆盖小麦21条染色体的高密度遗传图谱,该图谱共含有6 244个多态性标记,其中SNP标记6 001个、DAr T标记216个、SSR标记27个,覆盖染色体总长度4 875.29 c M,标记间平均距离0.78 c M。A、B、D染色体组分别有2 390、3 386和468个标记,分别占总标记数的38.3%、54.3%和7.5%;3个染色体组标记间平均距离分别为0.80、0.75和0.80 c M。用该分子遗传图谱对4个环境下粒重进行QTL分析,检测到位于1B、4B、5B、6A染色体上9个加性QTL,效应值大于10%的QTL位点有QGW4B-17、QGW4B-5、QGW4B-2、QGW6A-344、QGW6A-137;其中QGW4B-17在多个环境下检测到,其贡献率为16%—33.3%,可增加粒重效应值2.30-2.97g,该位点是稳定表达的主效QTL。9个QTL的加性效应均来自大粒母本山农01-35,单个QTL位点加性效应可增加千粒重1.09—2.97 g。[结论]构建的覆盖小麦21条染色体的分子遗传图谱共含有6 241个多态性标记,标记间平均距离为0.77 c M。利用该图谱检测到位于1B、4B、5B、6A染色体上9个控制粒重的加性QTL,其中QGW4B-17是稳定表达的主效QTL位点,贡献率为16.5%—33%,可增加粒重效应值2.30—2.97 g。

不同生态环境下冬小麦籽粒大小相关性状的QTL分析

【目的】鉴定影响籽粒大小相关性状的QTL,并估计QTL的表型效应;分析不同环境下QTL的稳定性。【方法】以冬小麦小粒地方品种和尚麦为母本,大粒育成品种豫8679为父本及其F7:8重组自交系的142个株系为试验材料,分析籽粒长度、宽度、厚度、体积及千粒重在北京(2006、2007)、合肥(2007)和成都(2007)4个不同环境下的性状表现,并利用已构建的含有170个SSR标记和2个EST标记的遗传图谱,对这5个性状进行QTL定位分析。【结果】4个环境下共检测到93个影响籽粒长度、宽度、厚度、体积及千粒重的QTL,这些QTL分布在除1D和6A之外的所有小麦染色体上。在检测到的QTL中,与籽粒长度、宽度、厚度、体积和千粒重相关的QTL分别为17、16、18、21和21个。另外,本研究还在1A、1B、2A、2D、3A、3B、5A、5B、5D、6A、6D、7B和7D染色体上共发现了18个QTL富集区。【结论】获得93个影响小麦籽粒大小相关性状的QTL,这些QTL可作为利用分子标记辅助育种途径进行小麦遗传改良的依据。

小麦单株产量与株高的QTL分析

【目的】在QTL水平上揭示株高与产量的遗传关系及株高对产量的影响,为小麦高产育种株高的选择提供参考依据。【方法】利用分别包含229和485个家系的2个关联重组自交系群体(recombinant inbred lines,RIL)潍麦8号/烟农19(WY)和潍麦8号/济麦20(WJ),绘制2个较高密度遗传连锁图谱。在3个环境下对单株产量和株高性状进行测量评价及非条件和条件QTL分析,研究株高与产量QTL的相互关系及排除株高影响后单株产量QTL效应的变化,探讨群体大小对QTL定位精度和准确性的影响。【结果】在WY群体中检测到5个单株产量QTL和15个株高QTL,其中,8个QTL解释大于10%的表型变异,3个为一因多效QTL;条件QTL分析表明,3个单株产量QTL与株高QTL无关,2个单株产量QTL的效应完全或部分由株高QTL所贡献,1个单株产量QTL的效应被株高QTL抑制。在WJ群体中检测到7个单株产量QTL和11个株高QTL,其中1个主效株高QTL加性效应值为8.82 cm,可解释20.68%的表型变异;条件QTL分析表明,5个单株产量QTL与株高QTL无关,2个单株产量QTL的效应完全由株高QTL所贡献。大群体WJ检测到的QTL效应值比小群体WY小,但LOD值高。【结论】株高与产量的关系是多重因素共同作用的结果,包括一因多效或紧密连锁、株高QTL对产量QTL表达的贡献与抑制、环境效应以及与其它性状的互作等。不同遗传背景、不同生态环境下株高对产量的贡献是各个因素相协调的结果,高产育种中对株高的选择在不同背景下应该有所区别;与小群体相比,大群体检测QTL的精度和准确性更高。

不同生态环境条件下小麦籽粒灌浆速率及千粒重QTL分析

以142个和尚麦/豫8679的F7:8重组自交系及其亲本为试验材料,分析了籽粒平均灌浆速率、最高灌浆速率及千粒重在北京(2006,2007)、安徽合肥(2007)和四川成都(2007)4个生态环境下的性状表现,并利用已构建的含有170个SSR标记和2个EST标记的遗传图谱,对这3个性状进行了QTL定位分析。共检测到54个QTLs,涉及小麦1A、1B、2A、2D、3A、3B、3D、4A、4D、5A、5B、6D和7D染色体。其中,17个与平均灌浆速率相关,可解释表型变异的7.17%～ 20.83%;16个与最高灌浆速率相关,可解释表型变异的6.31%～ 15.95%;21个与千粒重相关,可解释表型变异的4.36%～ 16.80%。另外,在1A、1B、2A、3B、4D、6D和7D染色体上发现10个涉及"一因多效"或紧密连锁位点的基因组区段,有助于了解籽粒灌浆和籽粒产量相关性状的遗传基础。

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F2:3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10.90%～33.79%。其中,Am3的等位基因能够增加千粒重2.3～4.8g。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。