Characterization and mapping of QTLs on chromosome 2D for grain size and yield traits using a mutant line induced by EMS in wheat

Production of mutants with altered phenotypes is a powerful approach for determining the biological functions of genes in an organism. In this study, a high-grain-weight mutant line M8008 was identified from a library of mutants of the common wheat cultivar YN15 treated with ethylmethane sulfonate(EMS). F2 and F2:3generations produced from crosses of M8008 × YN15(MY) and M8008 × SJZ54(MS) were used for genetic analysis. There were significant differences between M8008 and YN15 in plant height(PH), spike length(SL),fertile spikelet number per spike(FSS), grain width(GW), grain length(GL), GL/GW ratio(GLW), and thousand-grain weight(TGW). Most simple correlation coefficients were significant for the investigated traits, suggesting that the correlative mutations occurred in M8008. Approximately 21% of simple sequence repeat(SSR) markers showed polymorphisms between M8008 and YN15, indicating that EMS can induce a large number of mutated loci. Twelve quantitative trait loci(QTLs) forming QTL clusters(one in MY and two in MS) were detected. The QTL clusters coinciding with(MY population) or near(MS population) the marker wmc41 were associated mainly with grain-size traits, among which the M8008 locus led to decreases in GW, factor form density(FFD), and TGW and to increases in GLW. The cluster in the wmc25–barc168 interval in the MS population was associated with yield traits, for which the M8008 locus led to decreased PH, spike number per plant(SN), and SL.

Identification of quantitative trait loci for the dead leaf rate and the seedling dead rate under alkaline stress in rice

The quantitative trait loci （QTLs） for the dead leaf rate （DLR） and the dead seedling rate （DSR） at the different rice growing periods after transplanting under alkaline stress were identified using an F2：3 population, which included 200 individuals and lines derived from a cross between two japonica rice cultivars Gaochan 106 and Changbai 9 with microsatellite markers. The DLR detected at 20 days to 62 days after transplanting under alkaline stress showed continuous normal or near normal distributions in F3 lines, which was the quantitative trait controlled by multiple genes. The DSR showed a continuous distribution with 3 or 4 peaks and was the quantitative trait controlled by main and multiple genes when rice was grown for 62 days after transplanting under alkaline stress. Thirteen QTLs associated with DLR were detected at 20 days to 62 days after transplanting under alkaline stress. Among these, qDLR9-2 located in RM5786-RM160 on chromosome 9 was detected at 34 days, 41 days, 48 days, 55 days, and 62 days, respectively; qDLR4 located in RM3524-RM3866 on chromosome 4 was detected at 34 days, 41 days, and 48 days, respectively; qDLR7-1 located in RM3859-RM320 on chromosome 7 was detected at 20 days and 27 days; and qDLR6-2 in RM1340-RM5957 on chromosome 6 was detected at 55 days and 62 days, respectively. The alleles of both qDLR9-2 and qDLR4 were derived from alkaline sensitive parent ＂Gaochanl06＂. The alleles of both qDLR7-1 and qDLR6-2 were from alkaline tolerant parent Changbai 9. These gene actions showed dominance and over dominance primarily. Six QTLs associated with DSR were detected at 62 days after transplanting under alkaline stress. Among these, qDSR6-2 and qDSR8 were located in RM1340-RM5957 on chromosome 6 and in RM3752-RM404 on chromosome 8, respectively, which were associated with DSR and accounted for 20.32% and 18.86% of the observed phenotypic variation, respectively; qDSR11-2 and qDSR11-3 were located in RM536-RM479 and RM2596-RM286 on chromosome 11, respectively, which were associated with DSR explaining 25.85% and 15.41% of the observed phenotypic variation, respectively. The marker flanking distances of these QTLs were quite far except that of qDSR6-2, which should be researched further.

QTL consistency for agronomic traits across three generations and potential applications in popcorn

Favorable agronomic traits are important to improve productivity of popcorn. In this study, a recombinant inbred line（RIL） population consisting of 258 lines was evaluated to identify quantitative trait loci（QTLs） for nine agronomic traits（plant height, ear height, top height（plant height subtracted ear height）, top height/plant height, number of leaves above the top ear, leaf area, stalk diameter, number of tassel branches and the length of tassel） under three environments. Meta-analysis was conducted then to integrate QTLs identified across three generations（RIL, F2：3 and BC2F2） developed from the same crosses. In total, 179 QTLs and 36 meta-QTLs（m QTL） were identified. The percentage of phenotypic variation（R2） explained by any single QTL varied from 3.86 to 28.4%, and 24 QTLs with contributions over 15%. Nine common QTLs located in the same or similar chromosome regions were detected across three generations. Five meta-QTLs were identified including QTLs in three independent studies. Seven important m QTLs were composed of 11–26 QTLs for 4–7 traits, respectively. Only 11 m QTLs were commonly identified in the same or similar chromosome regions across agronomic traits, popping characteristics（popping fold, popping volume and popping rate） and grain yield components（ear weight per plant, grain weight per plant, 100-grain weight, ear length, kernel number per row, ear diameter, row number per ear and kernel ratio） by meta-QTL analysis. In conclusion, we identified a list of QTLs, some of which with much higher contributions to agronomic traits should be valuable for further study in improving both popping characteristics and grain yield components in popcorn.

Genetic architecture of maize yield traits dissected by QTL mapping and GWAS in maize

The study of yield traits can reveal the genetic architecture of grain yield for improving maize production.In this study, an association panel comprising 362 inbred lines and a recombinant inbred line population derived from X178 × 9782 were used to identify candidate genes for nine yield traits. High-priority overlap(HPO) genes, which are genes prioritized in a genome-wide association study(GWAS), were investigated using coexpression networks. The GWAS identified 51 environmentally stable SNPs in two environments and 36 pleiotropic SNPs, including three SNPs with both attributes. Seven hotspots containing 41 trait-associated SNPs were identified on six chromosomes by permutation. Pyramiding of superior alleles showed a highly positive effect on all traits, and the phenotypic values of ear diameter and ear weight consistently corresponded with the number of superior alleles in tropical and temperate germplasm. A total of 61 HPO genes were detected after trait-associated SNPs were combined with the coexpression networks. Linkage mapping identified 16 environmentally stable and 16 pleiotropic QTL.Seven SNPs that were located in QTL intervals were assigned as consensus SNPs for the yield traits.Among the candidate genes predicted by our study, some genes were confirmed to function in seed development. The gene Zm00001 d016656 encoding a serine/threonine protein kinase was associated with five different traits across multiple environments. Some genes were uniquely expressed in specific tissues and at certain stages of seed development. These findings will provide genetic information and resources for molecular breeding of maize grain yield.

Genetic background effects on QTL and QTL × environment interaction for yield and its component traits as revealed by reciprocal introgression lines in rice

QTLs for quantitative traits are influenced by genetic background(GB) and environment.Identification of QTL with GB independency and environmental stability is prerequisite for effective marker-assisted selection(MAS). In this study, QTLs and QTL × environment interactions affecting grain yield per plant(GY) and its component traits, filled grain number per panicle(FGN), panicle number per plant(PN) and 1000-grain weight(TGW) across six environments were dissected using two sets of reciprocal introgression lines(ILs) derived from the cross Lemont × Teqing and SNP genotypic data. ANOVA indicated that the differences among genotypes and environments within each set of ILs were highly significant for all traits. A total of 72 distinct QTLs for GY and its component traits including 15 for GY, 25 for FGN, 18 for PN, and 29 for TGW were detected over the six environments. Most QTLs(87.4%) showed significant QTL × environment interactions(QEIs) and appeared to be more or less environment-specific. Among 72 QTLs, 15(20.8%) QTLs and 12(16.7%) QEIs were commonly identified in both backgrounds, indicating QTL especially QEI for yield and its component traits had strong GB effects. Four QTL regions affecting GY and its component traits, including S1269707–S4288071, S16661497–S17511092, and S35861863–S36341768 on chromosome 3, and S4134205–S7643153 on chromosome 5, were detected in both backgrounds and coincided with cloned genes for yield-related traits. These regions can be the targeted in rice breeding for high yield potential through MAS. Application of QTL main effects and their environmental interaction effects in MAS was discussed in detail.

玉米叶部性状的QTL定位与候选基因分析

叶片在玉米生长过程中发挥着重要作用,它能够有效地进行光合作用,为玉米提供营养物质,通过影响耐密性等影响产量提升。本研究选用QR273和T32为亲本,构建150份F2、F2∶3家系材料,结合基因型和不同环境中叶部性状的表型评价数据,利用完备区间作图法进行数量性状座位(QTL)定位。结果发现,2个环境下共检测到85个叶部性状相关QTL,其中有12个全株叶片数相关QTL、14个穗上叶片数相关QTL、22个叶长相关QTL、17个叶宽相关QTL、20个叶夹角相关QTL。结合公共数据库和生物信息学分析方法共筛选出7个候选基因。其中Zm00001d013612编码微管蛋白,参与调控细胞骨架结构组成;Zm00001d053543参与油菜素甾醇介导的信号通路;Zm00001d031291编码的蛋白质具有组蛋白乙酰化功能;Zm00001d031292参与富含羟脯氨酸糖蛋白家族基因表达的调控;Zm00001d031296调控钾离子跨膜转运蛋白活性;Zm00001d031300、Zm00001d031303参与碳水化合物代谢过程。蛋白质功能分析结果表明,这7个候选基因均参与细胞分化,与植物的生长发育息息相关。本研究结果将为深度揭示玉米叶部性状变异的遗传基础提供更丰富的理论支持。

糯玉米茎秆穿刺强度QTL分析与基因组选择

茎秆穿刺强度是衡量玉米茎秆机械强度和抗倒伏能力的重要指标之一,本研究以衍生于糯玉米自交系衡白522和通系5的198个重组自交系为试验材料,对茎秆穿刺强度进行数量性状位点(QTL)分析和基因组选择研究。单个环境QTL分析共检测到4个控制糯玉米茎秆穿刺强度的QTL,每个QTL的表型变异贡献率均小于10.00%,且仅在单个环境中被检测到;多个环境QTL分析共检测到8个QTL与环境互作,其加性效应总共可解释24.64%的表型变异,加性效应与环境互作贡献率为17.51%;上位性QTL分析共检测到4对QTL与QTL互作,可解释8.25%的表型变异。基因组选择中,当训练群体占群体总数的80%,随机选择500个标记即可获得较高的预测准确性;但是根据单个环境QTL分析结果,选择机率常用对数值排名前200的标记,即可大幅度提高基因组选择预测准确性。

Location of Vibrio anguillarum resistance-associated trait loci in half-smooth tongue sole Cynoglossus semilaevis at its microsatellite linkage map

A cultured female half-smooth tongue sole(C ynoglossus semilaevis) was crossed with a wild male, yielding the fi rst fi lial generation of pseudo-testcrossing from which 200 fi sh were randomly selected to locate the V ibrio anguillarum resistance trait in half-smooth tongue sole at its microsatellite linkage map. In total, 129 microsatellites were arrayed into 18 linkage groups, ≥4 each. The map reconstructed was 852.85 c M in length with an average spacing of 7.68 c M, covering 72.07% of that expected(1 183.35 cM). The V. anguillarum resistance trait was a composite rather than a unit trait, which was tentatively partitioned into Survival time in Hours After V. anguillarum Infection(SHAVI) and Immunity of V. A nguillarum Infection(IVAI). Above a logarithm of the odds(LOD) threshold of 2.5, 18 loci relative to SHAVI and 3 relative to IVAI were identifi ed. The 3 loci relative to IVAI explained 18.78%, 5.87% and 6.50% of the total phenotypic variation in immunity. The microsatellites bounding the 3 quantitative trait loci(QTLs) of IVAI may in future aid to the selection of V. anguillarum-immune half-smooth tongue sole varieties, and facilitate cloning the gene(s) controlling such immunity.

深水稻全生育期耐盐性状的QTL定位

盐胁迫是许多沿海地区水稻生产的主要制约因素,尤其是沿海地区的咸淡水交汇区域。耐盐性是一种复杂的性状,可以通过QTL定位来帮助耐盐育种,以培育更高耐盐性的水稻品种。本研究供体亲本为沿海深水稻品种赤禾,受体亲本为美国水稻品种Lemont,杂交获得174份F9代的重组自交系,在芽期、苗期和生殖生长期分别利用浓度为15 g L^(-1)、5 g L^(-1)和5~6 g L^(-1)的NaCl进行胁迫,通过芽期相对发芽率、苗期耐盐性评级和生殖生长期的7个表型性状为基础数据,利用142个SSR分子标记绘制连锁遗传图并进行QTL分析。鉴定结果发现,赤禾在芽期表现敏盐,在苗期和生殖生长期表现耐盐;Lemont相反。3个生长时期分别有70.11%、50.57%和60.34%的品系表现为弱耐盐性,而且耐盐性为弱的负相关。本研究共鉴定出33个LOD值为2.52~10.32的QTL,解释0.06%~13.68%的表型遗传变异,解释最大遗传变异的QTL均由耐盐亲本贡献,其中芽期4个、苗期6个和生殖生长期23个位点,并在生殖生长期发现4个QTL重叠区域。这些QTL可以进一步研究,不仅为提高水稻育种的耐盐性提供了新的遗传资源,还有助于在水稻耐盐育种中,提高水稻品种的耐盐性。

不同氮水平下玉米苗期生长性状及成熟期产量的QTL定位

【目的】研究玉米苗期氮素利用效率相关性状与成熟期产量之间的遗传关系。【方法】以优良杂交种豫玉22两亲本Z3和87-1为基础构建的一套F8家系的RIL群体为研究材料,在高、低氮两种条件下,通过苗期水培试验和成熟期田间试验,利用复合区间作图法对玉米苗期地上部干重、根干重、总根长、根冠比以及成熟期产量性状进行了QTL定位。【结果】利用Windows QTL Cartographer2.5软件,在LOD>2.5条件下共定位到22个QTL位点,其中高氮下定位到10个QTL,低氮下定位到12个QTL,两种氮水平下共位或紧密连锁的QTL位点很少,表明不同氮水平下的遗传机制不同。在第5和第7染色体上发现了苗期根系相关性状与成熟期产量之间存在连锁关系。【结论】苗期根系性状对成熟期的产量形成具有重要的作用,在氮高效遗传育种中可以把苗期根系性状作为一个重要的选择指标。

不同环境条件下水稻生育期和株高的QTL分析

利用籼稻品种窄叶青 8号 (ZYQ8)和粳稻品种京系 17(JX17)为亲本构建的加倍单倍体 (doubled haploid,DH)群体及其分子连锁图谱 ,在 5个环境中对生育期和株高进行 QTL 比较分析。结果表明 ,共检测到 10个 QTL,两种环境以上能重复检出的 QTL9个 ,这些 QTL 在不同的环境中的加性效应方向一致 ,但遗传效应差异较大 ;其中没有 1个QTL 在 5种环境中均能定位 ,表明数量性状基因的表达易受环境的影响。根据不同环境条件的主要差异和 QTL 表现 ,初步确定第 8染色体上影响生育期的 QTL q H D8和株高相关的 QTL q PH8在长日条件下表现遗传效应 ;第 1和第 10染色体上分别控制生育期和株高的 QTL q H D1和 q PH10在短日下发挥作用。

黄瓜果实相关性状QTL定位分析

【目的】果实性状对黄瓜的商品性及产量具有重要影响,对黄瓜果实性状进行QTL定位分析将有助于了解其遗传机制,为黄瓜果实性状改良以及高产、稳产育种提供有益参考和帮助,同时也可为基因的精细定位及克隆奠定基础。【方法】利用华北保护地类型黄瓜材料9930和欧洲温室类型黄瓜材料9110Gt为亲本构建的遗传图谱,结合不同年份、不同季节4次表型鉴定数据,采用MapQTL4.0软件对12个黄瓜果实相关性状进行多座位QTL模型(MQM)检测。【结果】检测到与8个商品瓜性状相关的QTLs 18个:瓜长Fl(3个)、把长Fsl(1个)、瓜粗Fd(1个)、瓜长/把长Lsr(5个)、瓜长/瓜粗Ldr(1个)、刺色Fsc(4个)、刺密度Fsd(1个)、果瘤大小Fws(2个);与4个种瓜性状(种瓜长Sfl、种瓜粗Sfd、种瓜重Sfw、种瓜果皮颜色Sfc)相关的QTLs 14个。其中表型贡献率≥10.0%的主效QTL有27个,占QTL总数的84.4%,这些QTL大都分布在Chr.5和Chr.6上。各QTLs的LOD值在3.53—42.21,可解释8.4%—73.1%的表型变异。【结论】本研究检测到与12个黄瓜果实性状相关的QTL共32个,其中刺色和果瘤大小2个性状在2006—2009年春秋两季均检测到主效QTL位点,并获得紧密连锁的特异标记(SSR02697、SSR19256、SSR15818、SSR06003、SSR00116、SSR05321、SSR00004、SSR02309),可用于基因精细定位研究。

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。

玉米株高和穗位高遗传基础的QTL剖析

利用玉米强优势组合(Mo17×黄早四)自交衍生的191个F2单株构建了由SSR和AFLP标记组成的分子连锁图谱。F2进一步自交产生的184个F2∶3家系用于调查株高和穗位高的表型值。采用基于混合线性模型的复合区间作图法和相应的作图软件QTLmapper/V2.0,分别定位了7个株高和6个穗位高QTL;检测到18对控制株高和13对控制穗位高的上位性效应位点;同时发现了与环境存在显著互作的6个株高和8个穗位高单位点标记区域以及4对株高和4对穗位高上位性效应区域。分析了各种遗传因素在株高和穗位高遗传基础中的相对作用大小,指出了加性、显性和上位性是玉米株高和穗位高的重要遗传基础。并对所定位的QTL的真实性、株高和穗位高的关系以及研究结果对分子育种的启示予以讨论。

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。

基于SNP标记的玉米株高及穗位高QTL定位

为进一步明确玉米株高和穗位高的遗传机制,为育种生产提供服务,本研究以K22×CI7、K22×Dan340的F2群体为作图群体,利用覆盖玉米10条染色体的SNP标记构建了2个连锁图谱。并将这2个F2群体衍生的分别含237和218个家系的F2:3群体用于田间性状的鉴定。用复合区间作图模型对2个群体的株高、穗位高表型进行QTL定位分析。结果显示,在广西南宁和湖北武汉两种环境条件下共定位到21个株高QTL和27个穗位高QTL;单个QTL表型变异贡献率的变幅为4.9%～17.9%;株高和穗位高QTL的作用方式以加性和部分显性为主;第7染色体上可能存在控制株高和穗位高的主效QTL。

利用Mudgo／武育粳3号F2群体分析水稻抗灰飞虱QTL

灰飞虱是我国水稻生产上的重要害虫。Mudgo是一个高抗灰飞虱的籼稻品种,对灰飞虱具有强的排驱性和抗生性抗性。利用Mudgo/武育粳3号F2群体,构建了含有177个单株的F2群体的遗传连锁图谱。该连锁图包含104个SSR标记和3个Indel标记,覆盖整个水稻基因组1409.9cM,每两个标记之间的平均距离为13.2cM。采用改进的苗期集团筛选法对177个F2:3家系进行了抗性鉴定,通过Windows QTL Cartographer2.5进行复合区间作图分析,在第2、3、12染色体上分别检测到抗灰飞虱QTL Qsbph2b、Qsbph3d和Qsbph12a,分别位于标记RM5791～RM29、RM3199～RM5442和I12-17～RM3331之间,单个LOD值分别为3.25、3.11和6.82,贡献率分别为17.3%、15.6%和35.8%,各QTL增强抗性的等位基因效应均来自Mudgo。其中Qsbph12a与标记RM3331和I12-17紧密连锁。结合表型鉴定的结果,Qsbph12a应为抗灰飞虱主效QTL,与该位点紧密连锁的标记可用于抗灰飞虱快速选择辅助育种。

基于掖478导入系的玉米产量性状QTL鉴定

【目的】鉴定玉米产量相关性状基因位点及包含有利等位基因的导入系,为了解产量性状形成的遗传基础及针对玉米自交系产量性状的分子设计提供参考和依据。【方法】以QB80和Qi319为供体亲本,掖478为轮回亲本,采用回交结合定向选择,分别构建含有61和72个家系的基础导入系群体。通过2年4点田间试验,利用完备复合区间作图进行产量及其相关性状的QTL(quantitative trait locus,QTL)分析。【结果】4个环境下,在QB80为供体的导入系群体中,共检测到9个性状的49个QTL;在Qi319为供体的导入系群体中,检测到9个性状的42个QTL。在2个及以上环境中均检测到的QTL有16个。同一性状在不同环境下所检测的QTL定位在相同的染色体区域,不同性状的QTL也定位在相同或临近的染色体区域,形成多个QTL富集区。2个群体所检测的QTL位点具有较少的一致性,说明2个供体材料中含有不同的有利基因位点。同时,导入片段中含有利基因的导入系,其相关性状明显得以改良,这些导入系可用于QTL聚合以改良掖478的产量相关性状。【结论】QB80较Qi319与掖478间的遗传差异更大,能检测更多的产量性状QTL;2个导入系群体中含有优良等位基因的导入系可用于QTL聚合改良掖478;QTL富集区是为产量性状基因的克隆提供可供参考的重要染色体区域。

水稻分蘖角度的QTL定位和主效基因的遗传分析

利用水稻籼粳亚种间组合Asominori×IR24重组自交系(RIL)群体71个株系和相应的全基因组染色体片段置换系(Chromosome segment substitution line,CSSL)群体65个株系,在2种环境下对分蘖角度性状进行了数量性状基因座(QTL)定位和上位性效应的遗传分析.在两种群体中都出现了分蘖角度的超亲分离.在RIL群体中发现了5个主效QTLs和3对上位性双位点互作标记基因座,控制水稻分蘖角度.其中在第9染色体上位于XNpb108～C506 RFLP分子标记区间的qTA-9基因座在2种环境中同时出现,其贡献率平均为28.6%,增加分蘖角度的等位基因来自籼稻品种IR24.利用CSSL群体图示基因型分析,证实在第9染色体上含有RFLP标记C609和C506约15 cM的染色体区段,存在增加分蘖角度的基因,来源于染色体片段供体亲本IR24,在Asominori的遗传背景中能增加分蘖角度约15°,该基因的位置与RIL群体在第9染色体上定位的QTL相同,证实了qTA-9的存在.F1表型测定及F2代遗传分析表明,来自IR24的等位基因是一个不完全显性基因.除一对上位性位点存在显著的环境互作效应外,未发现其他位点存在与环境的互作效应.不同基因的加性效应和双位点的上位性效应的共同作用可能是造成水稻分蘖角度超亲分离的主要原因.

水稻品种IR24抗条纹叶枯病相关QTL的检测

为探明籼稻品种IR24是否携有新的抗条纹叶枯病基因,利用衍生于Asominori/IR24的重组自交系(RIL)群体和以Asominori为遗传背景IR24插入片段的染色体片段置换系(CSSL)群体,进行抗条纹叶枯病相关QTL的检测。利用疫区田间自然条件鉴定的方法,在RIL群体中共检测到4个控制条纹叶枯病的QTL,分别位于第3、5、7、11染色体上(qSTV3、qSTV5、qSTV7、qSTV11),其中qSTV3、qSTV7和qSTV11增强抗性的等位基因来自抗性亲本IR24。采用图示基因型比较法,在CSSL群体中将4个抗条纹叶枯病相关基因位点分别定位在染色体片段置换系CSSL4、L17、L39、L61、L62的IR24插入片段上。对比分析RIL群体和CSSL群体的分子连锁图谱,发现qSTV3所在的标记区间与CSSL17的IR24片段相吻合,qSTV7所在的标记区间与CSSL4的杂合片段、CSSL39的IR24片段相吻合,qSTV11所在的标记区间与CSSL61的IR24片段以及CSSL62的杂合片段相吻合,表明确实存在这3个位点。与前人的研究结果相比较,发现位于第3染色体上的qSTV3区域存在抗刺吸性害虫的基因簇,是一个表达稳定的抗灰飞虱基因座;位于第7染色体上的qSTV7不同于已报道的抗性基因座,表明IR24携有新的抗性基因,这些基因不同于主基因Stvbi-,为防止广泛使用单一基因而造成的遗传脆弱性提供了新的抗性基因源,并且为利用分子标记辅助选择,聚合不同抗性基因培育抗性稳定的条纹叶枯病抗性品种创造了条件。