中国农业科学 ›› 2009, Vol. 42 ›› Issue (12): 4155-4165 .doi: 10.3864/j.issn.0578-1752.2009.12.005

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

大豆产量有关性状QTL的检测

黄中文,赵团结,喻德跃,陈受宜,盖钧镒

  

  1. (国家大豆改良中心/南京农业大学大豆研究所/作物遗传与种质创新国家重点实验室)
  • 收稿日期:2008-12-15 修回日期:2009-08-07 出版日期:2009-12-10 发布日期:2009-12-10
  • 通讯作者: 盖钧镒

Detection of QTLs of Yield Related Traits in Soybean

HUANG Zhong-wen, ZHAO Tuan-jie, YU De-yue, CHEN Shou-yi, GAI Jun-yi
  

  1. (国家大豆改良中心/南京农业大学大豆研究所/作物遗传与种质创新国家重点实验室)
  • Received:2008-12-15 Revised:2009-08-07 Online:2009-12-10 Published:2009-12-10
  • Contact: GAI Jun-yi

摘要:

【目的】研究大豆产量和生物量、叶面积指数、冠层以及产量构成因素间的相关性,定位控制这些性状的QTL。【方法】以地理和遗传来源均有较大差异的北方亲本科丰1号和南方亲本南农1138-2所衍生的184个重组自交家系2年有重复的田间试验结果进行产量有关性状的QTL分析。【结果】(1)产量与地上部生物量、叶面积指数、根重、冠层宽和高等均有极显著正相关,相关系数0.5~0.7。(2)地上部生物量检测到7个QTL,贡献率6.2%~21.1%,其中2年重复检出1个(qSBO-1);根重8个QTL,贡献率5.2%~20.1%,重复检出1个(qRTB1-1)。(3)开花期叶面积指数5个QTL,贡献率6.4%~17.2%;结荚期叶面积指数5个QTL,贡献率7.3%~26.2%,重复检出1个(qLAIR3A2);冠层宽4个QTL,贡献率6.3%~13.1%,重复检出1个(qCWD1b-2);冠层高11个QTL,贡献率5.2%~9.2%,重复检出4个(qCHH-1、qCHO-1、qCHO-2和qCHO-3)。(4)百粒重6个,荚粒数2个,荚数1个QTL,贡献率6.9%~15.7%;分枝荚数5个,主茎荚数3个QTL,贡献率6.3%~11.1%;主茎节数8个QTL,有效分枝数3个QTL,贡献率4.7%~15.2%。(5)根重和地上部生物量各有1个,R1(始花期)和R3(始荚期)叶面积指数各有2个,冠层宽和高各有2个,产量与荚数各有1个,百粒重和分枝荚数各有1个,荚粒数和主茎节数各有1个,分枝荚数与有效分枝数各有1个共享的QTL。【结论】大豆产量有关的13个性状共检测到68个QTL;年份间有重复检出的,但不多,其表达较大程度上与环境有关;尽管性状间普遍有相关、有共享的QTL,但不多,各有其遗传体系;产量有关性状中很少有贡献率大的主效QTL,产量育种要考虑多数基因聚合的技术。

关键词: 大豆, 产量, 生物量, 叶部性状, 产量组分, 相关, QTL定位

Abstract:

【Objective】 The present study was aimed to reveal the correlation between yield and biomass, leaf area and yield components, and to detect and map the QTLs of the yield-related traits. 【Method】 The 184 recombinant inbred lines derived from a cross between geographically and genetically distant parents, Kefeng 1 from northern China and Nannong 1138-2 from southern China, were tested in two years and then analyzed for detecting and mapping QTLs of the traits related to yield. 【Result】 A very significant positive correlation was observed between yield and above ground biomass, leaf area index, root weight, canopy width and canopy height with r values of 0.5-0.7. Seven QTLs of above ground biomass were mapped with contribution rate of 6.2%-21.1% and one QTL (qSBO-1) repeatedly detected in both years while eight QTLs of root weight mapped with contribution rate of 5.2%-20.1% and one QTL (qRTB1-1) repeatedly detected. Five QTLs of R1 leaf area index were mapped with contribution rate of 6.4%-17.2% while five QTLs of R3 leaf area index mapped with contribution rate of 7.3%-26.2% and one QTL (qLAIR3A2) repeatedly detected. Four QTLs of canopy width were mapped with contribution rate of 6.3%-13.1% and one QTL (qCWD1b-2) repeatedly detected while 11 QTLs of canopy height mapped with contribution rate of 5.2%-9.2% and four QTLs repeatedly detected. Six, two and one QTL of 100-seed weight, number of seeds per pod and number of pods per plant, respectively, were mapped with their contribution rate of 6.9%-15.7%. Five and three QTLs of number of pods on branches and number of pods on main stem, respectively, were mapped with their contribution rate of 6.3%-11.1%. Eight and three QTLs of number of nodes on main stem and effective number of branches, respectively, were mapped with their contribution rate of 4.7%-15.2%. There was one QTL shared by above ground biomass and root weight, two QTLs shared by R1 and R3 leaf area index, two QTLs by canopy width and height, one by yield and number of pods per plant, one by 100-seed weight and number of pods on branches, one by number of seeds per pod and number of nodes on main stem, and one by number of pods on branches and effective number of branches. 【Conclusion】 A total of 68 QTLs were mapped for 13 yield-related traits. Among them, only a small part was repeatedly detected in both years, implied their expression depended on years or environmental conditions. Although significant correlations existed among the traits extensively, only a small part of the QTLs was shared between the traits, which indicted different gene systems for various traits. There were few QTLs with large contribution found in the yield-related traits, thus breeding technology for pyramiding multiple genes should be considered for yield improvement.

Key words: soybean, yield, biomass, leaf trait, yield component, correlation, QTL mapping