机构地区:[1]东北农业大学农学院,哈尔滨150030 [2]黑龙江省农垦科研育种中心,哈尔滨150090 [3]大连工业大学,辽宁大连116034 [4]国家大豆工程技术研究中心,哈尔滨150050
出 处:《中国农业科学》2014年第13期2680-2689,共10页Scientia Agricultura Sinica
基 金:黑龙江省普通高等学校新世纪优秀人才培养计划(1252-NCET-004);国家"863"计划(2012AA101106);现代农业产业体系--国家大豆产业体系(CARS-04-02A)
摘 要:【目的】定位大豆蛋白质和油分含量QTL及互作分析,为大豆品质性状QTL精细定位和分子辅助育种提供基础。【方法】以Charleston和东农594为亲本,构建了含147个株系的重组自交系,以F2:19—F2:20代重组自交系为试验材料,利用Windows QTL Cartographer V.2.5软件的复合区间作图法和多重区间作图法,对该群体的蛋白质和油分含量进行QTL定位分析,并利用QTL Network 2.1软件分析QTL间的上位性效应及环境互作效应。【结果】采用CIM和MIM 2种算法在2011和2012年哈尔滨、红兴隆、佳木斯和牡丹江每年3个地点共6个种植环境下共定位了9个蛋白质和11个油分含量QTL。蛋白质含量QTL分布在6个连锁群,分别在A1、C2、D1a、G、H和O连锁群上,对表型效应的贡献率为5.3%—18.6%,在H连锁群上的qPro-H-1贡献率最大,为18.6%,在D1a连锁群上的qPro-D1a-2贡献率最小,为5.3%,在单种植环境下有5个蛋白质含量QTL被2种算法同时检测到,分别是qPro-O-1、qPro-A1-1、qPro-D1a-1、qPro-D1a-2和qPro-C2-2。油分含量QTL分布在8个连锁群,分别在A1、A2、B1、C2、D1a、E、L和M连锁群上,对表型效应的贡献率为7.1%—24.4%,在B1连锁群上的qOil-B1-2贡献率最大,为24.4%,在C2连锁上的qOil-C2-3贡献率最小,为7.1%,在单种植环境下有2个油分含量的QTL被2种算法同时检测到,分别为qOil-C2-1和qOil-M-1。另外,有2个油分含量QTL在2个以上种植环境重复检测到,为2011年哈尔滨和2011年红兴隆2个种植环境下同时检测出的qOil-A1-1,2011红兴隆、2011牡丹江和2012哈尔滨3个地点同时被检测出的qOil-B1-2。在互作效应分析中,共检测出3对蛋白质上位效应QTL和4对油分上位效应QTL,在蛋白质上位性分析中,上位效应值在0.2068—0.3124,贡献率在0.0227%—0.0265%,分布在A1、C2、D1和E连锁群上,其中,qPro-A1-3与qPro-C2-1效应值为负,其余2对效应值为正,连锁群A1,D1a均有2个QTL发生互作。在油分上位性分析中,�[Objective] Quantitative trait loci associated with protein and oil contents were identified and epistatic interactions in soybean. The results will offer a clue for quality gene mining and molecular breeding in soybean. [Method] Total 147 recombination inbred lines(RIL) were derived from a cross of Charleston and Dongnong 594, the F2:19-F2:20 generation of RIL was used as experimental materials. Using CIM and MIM model method by Windows QTL Cartographer V.2.5, QTL associated with protein and oil contents were identified. The epistatic effect and environmental effect between QTLs were analyzed by QTL Network 2.1. [Result] Under six planting environments including Harbin, Hongxinglong, Jiamusi, and Mudanjiang in 2011 and 2012, a total of nine QTLs for protein content and eleven QTLs for oil content were mapped. Protein content QTLs were mapped on six linkage groups A1, C2, D1a, G, H, and O. The QTLs explained 5.3%-18.6% of phenotypic variation, the maximum rate of qPro-H-1 on linkage group H was 18.6%, the minimum rate of qPro-D1a-2 on linkage group D1a was 5.3%. Five protein content QTLs in single planting environment were simultaneously detected by two methods, which were qPro-O-1, qPro-A1-1, qPro-D1a-1, qPro-D1a-2, and qPro-C2-2. Oil content QTL were mapped on eight groups A1, A2, B1, C2, D1a, E, L, and M. The QTLs explained 7.1%-24.4% of phenotypic variation, the maximum rate of qOil-B1-2 on linkage group B1 was 24.4%, the minimum rate of qOil-C2-3 on linkage group C2 was 7.1%. Two oil content QTLs qOil-C2-1, qOil-M-1 were detected in single planting environment. Besides, two oil content QTLs were detected in over 2 environments, qOil-A1-1 was indentified in 2011 in Harbin and in 2011 in Hongxinglong two planting environments, qOil-B1-2 was indentified in 2011 in Hongxinglong, in 2011 in Mudanjiang and in 2012 in Harbin three planting environments. A total of three pairs protein epistatic effect QTL and four pairs oil content epistatic QTL were found. Protein epistatic effect was 0.2068-0.3124, the QTL
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