中文摘要：

【目的】芝麻是对湿害极其敏感的作物，湿害是影响中国芝麻生产发展和单产提高的主要障碍因素，然而，芝麻耐湿性分子生物学研究基础薄弱，迄今，国内外有关芝麻耐湿性基因定位的研究尚未见报道。利用重组自交系（RIL）群体进行芝麻耐湿性QTL定位，结合芝麻核心种质群体进行耐湿性相关分子标记研究，并挖掘优异耐湿基因资源。【方法】以高耐湿芝麻品种中芝13与极敏感种质宜阳白杂交后连续自交6代构建206个株系的RIL群体。利用113对多态性分子标记扫描RIL群体获得基因型数据，用MapMaker/EXP. 3.0软件构建遗传连锁图谱。2009年和2010年在武汉和鄂州2地点通过人工淹水胁迫获得RIL群体盛花期湿害后正常株率和存活株率的表型数据，用Microsoft Excel 2010软件进行表型数据方差分析，用QTLNetwork 2.0软件基于复合区间作图法进行QTL定位，利用主效QTL紧密连锁的分子标记扫描核心种质群体，并结合耐湿性表型数据分析得到相关有效分子标记。通过盛花期耐湿性表型重复鉴定筛选，结合分子标记辅助选择，获得优异耐湿基因资源。【结果】构建的遗传连锁图谱全长592.4 cM，共有70个标记位点进入15个连锁群，标记间的平均距离为8.46 cM。共检测到与盛花期耐湿性相关的6个QTL位点，定位在第7、9、13和15连锁群上，分别解释5.67%—17.19%的表型变异，加性效应值2.7190—9.7302，贡献率最大的QTL为qWH10CHL09，加性效应3.9394，其增效等位基因来源于母本中芝13，SSR标记ZM428与其紧密连锁（遗传距离为0.7 cM）。标记ZM428在186份芝麻核心种质中验证结果表明，该标记2种基因型的资源间在耐湿表型上存在显著差异（P=0.0163），因此，标记ZM428可作为芝麻耐湿性分子辅助选择的有效标记。还挖掘出8份优异耐湿基因资源，湿害后其正常株率均＞70%，存活株率均＞80%。【

英文摘要：

【Objective】Sesame is extremely sensitive to waterlogging and it is the main factor affecting the development of sesame production and the improvement of sesame yield in China, however, waterlogging tolerance related molecular biology research foundation is weak, so far, domestic and foreign studies on sesame waterlogging tolerance gene mapping has not yet been reported. This study focuses on mapping QTL related with waterlogging tolerance based on a sesame recombinant inbred lines （RIL） population, developing molecular marker related with waterlogging tolerance combining with analysis on sesame core collections, and identifying waterlogging tolerant germplasm. 【Method】RIL population was generated from 6 selfing generations after hybridization between Zhongzhi No.13 with high tolerance and Yiyangbai with extreme sensitivity to waterlogging. Based on molecular data of 113 polymorphism markers on RIL population, a genetic linkage map was constructed using MapMaker/EXP. 3.0 software. In 2009 and 2010, RIL population was tested by artificial waterlogging stress at flowering stage both at Wuhan and Ezhou, and phenotypic data of each line were obtained, including percentage of regular plants and percentage of live plants. Analysis of variance （ANOVA） on phenotypic data was carried out by Microsoft Excel 2010 software, then QTLs were mapped by QTLNetwork 2.0 software, using composite interval mapping （CIM） method. Subsequently, sesame core collections were scanned by markers linked with major QTL, their waterlogging tolerance phenotypic data were also collected and analyzed, the effective marker related with waterlogging tolerance was detected. Excellent germplasms with waterlogging tolerance were obtained by repeated identifying of waterlogging tolerance phenotype, and combined with the molecular marker assisted selection. 【Result】The length of genetic linkage map constructed in this study was 592.4 cM, a total of 70 marker loci were grouped into 15 linkage groups （LG）, the average distance b