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作物学报 ›› 2013, Vol. 39 ›› Issue (06): 1021-1029.doi: 10.3724/SP.J.1006.2013.01021

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

多种环境下大豆单株粒重QTL的定位与互作分析

范冬梅1,马占洲1,刘春燕2,杨振1,曾庆力1,辛大伟1,蒋洪蔚2,邱鹏程3,陈庆山1,4,*,胡国华2,4,*   

  1. 1 东北农业大学农学院, 黑龙江哈尔滨 150030;2 黑龙江省农垦科研育种中心, 黑龙江哈尔滨 150090;3 鄂尔多斯市农牧业科学研究院, 内蒙古鄂尔多斯 017000;4 国家大豆工程技术研究中心, 黑龙江哈尔滨 150050
  • 收稿日期:2012-08-13 修回日期:2013-01-15 出版日期:2013-06-12 网络出版日期:2013-03-22
  • 通讯作者: 胡国华, E-mail: hugh757@vip.163.com, Tel: 0451-55199475; 陈庆山, E-mail: qshchen@126.com, Tel: 0451-55191945
  • 基金资助:

    本研究由黑龙江省自然科学基金重点项目(ZD201213),国家公益性行业(农业)科研专项(200903003),国家现代农业产业体系建设专项(CARS-04-02A),国家“十二五”科技支撑计划项目(2011BAD35B06-1)和黑龙江省普通高等学校新世纪优秀人才培养计划(1252-NCET-004)项目资助。

Analysis of Related Interactions and Mapping of QTLs for Seed Weight per Plant in Soybean in Different Years

FAN Dong-Mei1,MA Zhan-Zhou1,LIU Chun-Yan2,YANG Zhen1,ZENG Qing-Li1,XIN Da-Wei1,JIANG Hong-Wei2,QIU Peng-Cheng3,CHEN Qing-Shan1,4,*,HU Guo-Hua2,4,*   

  1. 1 College of Agriculture, Northeast Agricultural University, Harbin 150030, China; 2 The Crop Research and Breeding Center of Land-Reclamation, Harbin 150090, China; 3 Erdos Academy of Agriculture and Animal Husbandry Sciences, Inner Mongolia Erdos 017000, China; 4 The National Research Center of Soybean Engineering and Technology, Harbin 150050, China
  • Received:2012-08-13 Revised:2013-01-15 Published:2013-06-12 Published online:2013-03-22
  • Contact: 胡国华, E-mail: hugh757@vip.163.com, Tel: 0451-55199475; 陈庆山, E-mail: qshchen@126.com, Tel: 0451-55191945

摘要:

定位大豆单株粒重QTL、分析QTL间的上位效应及QTL与环境互作效应, 有利于大豆单株粒重遗传机理的深入研究。利用147F2:14~F2:18 RIL群体, 52点多环境下以CIMMIM方法同时定位大豆单株粒重QTL, 检测到17个控制单株粒重的QTL, 分别位于D1aB1B2C2FGA1连锁群上, 贡献率为6.0%~47.9%;用2种方法同时检测到3QTL, qSWPP-DIa-3qSWPP-F-1qSWPP-D1a-5, 贡献率为6.3%~38.3%2年以上同时检测到4QTL, qSWPP-DIa-1qSWPP-DIa-2qSWPP-B1-1qSWPP-G-1, 贡献率为8.1%~47.9%;利用QTLMapper分析QE互作效应和QTL间上位效应, 7种环境下的数据联合分析得到1QE互作QTL4对上位效应QTL, 贡献率和加性效应都较小。在分子标记辅助育种中应该同时考虑主效QTL及各微效QTL之间的互作

关键词: 大豆, 单株粒重, QTL分析, QE互作, 上位互作

Abstract:

QTL analysis of seed weight per plant, epistatic effects and the QE interaction, have a great contribution tothe promote study of genetic for seed weight per plant in soybean. The objective of this study was to investigate the major QTLs, epistatic effects, and QE interaction effects of QTLs for seed weight per plant in soybean. To find out the steady and repeatable QTLs of this trait, we used F2:14–F2:18 RIL population containing 147 lines in this experiment in two sites in five years by CIM and MIM. Seventeen QTLs for seed weight per plant were detected by CIM and MIM in D1a, B1, B2, C2, F, G, and A1 linkage groups, respectively, accounting for 6.0–47.9% of the general phenotypic variation. Three QTLs for seed weight per plant could be detected simultaneously by CIM and MIM, accounting for 6.3%–38.3% of the general phenotypic variation. Four QTLs for seed weight per plant could be detected simultaneously in more than two years, accounting for 8.1–47.9% of the general phenotypic variation. Data from seven environments were used to detecte by QTLMapper for QE interaction effects and epistatic effects of QTLs in this study. One QE QTL and four pairs of QTLs with epistatic effects were detected, but the additive effects contribution rate and the general contribution of interaction were not significant, indicating that both major and minor QTLs with epistatic effects and QE should be considered in the improvement in soybean breeding.

Key words: Soybean, Seed weight per plant, QTL analysis, QTL×environment interaction, Epistatic effects

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