| 多环境条件下大豆倒伏性相关形态性状的QTL分析 |
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| 引用本文： | 范冬梅,杨振,马占洲,曾庆力,杜翔宇,蒋洪蔚,刘春燕,韩冬伟,栾怀海,裴宇峰,陈庆山,胡国华.多环境条件下大豆倒伏性相关形态性状的QTL分析[J].中国农业科学,2012,45(15):3029-3039. |
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| 作者姓名： | 范冬梅 杨振 马占洲 曾庆力 杜翔宇 蒋洪蔚 刘春燕 韩冬伟 栾怀海 裴宇峰 陈庆山 胡国华 |
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| 作者单位： | 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.黑龙江省农业科学院齐齐哈尔分院，黑龙江齐齐哈尔 161041
4.国家大豆工程技术研究中心，哈尔滨 150050 |
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| 基金项目： | 国家现代农业产业技术体系建设专项资金(CARS-04-02A);农业部转基因专项(2011ZX08004-001);“大豆新品种培育与扩繁”国家“十二五”科技支撑计划(2011BAD35B06-1);黑龙江省普通高等学校新世纪优秀人才培养计划(1252-NCET-004) |
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| 摘 要： | 【目的】定位大豆倒伏性相关形态性状的QTL为培育抗倒伏性高的品种提供依据。【方法】以美国大豆品种Charleston为母本，东北农业大学大豆品系东农594为父本及其F2:16-F2:18的重组自交系的147个株系为试验材料，164个SSR引物经亲本筛选后用于群体扩增，并构建遗传图谱。在三年两个地点对大豆的主茎节数、茎粗和茎秆重性状进行调查及QTL分析。【结果】共检测到16个主茎节数QTL，分别位于A1、B1、C2、D1a、D2、F、G、H和N连锁群上；检测到10个茎粗QTL,分别位于A1、B1、C2、D1a、E和G连锁群上；检测到15个茎秆重QTL，分别位于A1、A2、C2、D1a、D1b和G连锁群上。在得到的这些QTL中，2种算法都能检测到5个主茎节数QTL，解释表型变异范围为8.6%-27.0%；1个茎粗QTL，解释表型变异范围为9.0%-11.0%；6个茎秆重QTL，解释表型变异范围为6.0%-39.0%。在2年以上能被检测到3个主茎节数QTL，解释表型变异范围为8.0%-60.2%；2个茎秆重QTL，解释表型变异范围为10.0%-23.0%；2年以上未重复检测到茎粗QTL。【结论】通过比较定位的主茎节数、茎粗和茎秆重QTL，发现这些性状之间存在较大的遗传相关性。
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| 关 键 词： | 大豆 倒伏性 QTL分析 |
| 收稿时间： | 2012-02-27 |
QTL Analysis of Lodging-Resistance Related Traits in Soybean in Different Environments |
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| FAN Dong-mei,YANG Zhen,MA Zhan-zhou,ZENG Qing-li,DU Xiang-yu,JIANG Hong-wei,LIU Chun-yan,HAN Dong-wei,LUAN Huai-hai,PEI Yu-feng,CHEN Qing-shan,HU Guo-hua.QTL Analysis of Lodging-Resistance Related Traits in Soybean in Different Environments[J].Scientia Agricultura Sinica,2012,45(15):3029-3039. |
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| Authors: | FAN Dong-mei YANG Zhen MA Zhan-zhou ZENG Qing-li DU Xiang-yu JIANG Hong-wei LIU Chun-yan HAN Dong-wei LUAN Huai-hai PEI Yu-feng CHEN Qing-shan HU Guo-hua |
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| Institution: | 2,4(1College of Agriculture,Northeast Agricultural University,Harbin 150030;2The Crop Research and Breeding Center of Land-Reclamation,Harbin 150090;3Qiqihaer Institute,Heilongjiang Academy of Agricultural Sciences,Qiqihaer 161041,Heilongjiang;4The National Research Center of Soybean Engineering and Technology,Harbin 150050) |
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| Abstract: | 【Objective】The objective of this study is to locate consensus QTLs of lodging-resistance related traits of soybean for breeding lodging-resistance varieties and increase yield of soybean, and convenience for mechanization harvest.【Method】In order to find out the steady and repeatable QTLs of these traits, a F2:16-F2:18 RIL population containing 147 lines derived from a cross between Charleston as female and Dongnong 594 as male parent were used in this experiment. A genetic linkage map was constructed with 164 SSR primers screened in two parents and amplified in 147 lines population. Nodes in main stem, stem thickness and stem weight QTLs of soybean were analyzed in two sites in three years. 【Result】 Sixteen nodes in main stem QTLs were detected in A1, B1, C2, D1a, D2, F, G, H and N linkage group, respectively. Ten stem thickness QTLs were detected in A1, B1, C2, D1a, E and G linkage group, respectively. Fifteen stem weight QTLs were detected in A1, A2, C2, D1a, D1b and G linkage group, respectively. In these QTLs, five QTLs for nodes in main stem, one QTLs for stem thickness and six QTLs for stem weight could be detected together by CIM and MIM, accounting for 8.6%-27.0%, 9.0%-11.0%, and 6.0%-39.0% of the general phenotypic variation, respectively. Three QTLs for nodes in main stem QTLs and two QTLs for stem weight could be detected together in more than two years, accounting for 8.0%-60.2% and 10.0%-23.0% of the general phenotypic variation, respectively. 【Conclusion】 Compared with QTLs mapped for nodes in main stem, stem thickness and stem weight, relatively large genetic correlation was found among lodging-resistance related traits of soybean. |
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| Keywords: | soybean lodging QTL analysis |
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