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作物学报 ›› 2008, Vol. 34 ›› Issue (09): 1500-1509.doi: 10.3724/SP.J.1006.2008.01500

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

应用导入系群体进行水稻产量相关性状的遗传剖析

康乐1,2,**;李宏3,**;孙勇1,2;卢德城3;张帆1,2;黄道强3;徐建龙1,2;王志东3;朱苓华1,2;高用明1,2;傅彬英1,2;李康活3;周永力1,2;周少川3,*;黎志康1,2,*
  

  1. 1 中国农业科学院作物科学研究所 / 国家农作物基因资源与基因改良重大科学工程, 北京100081; 2 International Rice Research Insti-tute, DAPO Box 7777, Metro Manila, The Philippines; 3 广东省农业科学院水稻研究所, 广东广州510640
  • 收稿日期:2008-01-04 修回日期:1900-01-01 出版日期:2008-09-12 网络出版日期:2008-09-12
  • 通讯作者: 黎志康

Genetic Dissection of Yield Potential in Rice (Oryza sativa L.) Using In-trogression Lines

KANG Le12**,LI Hong3**,SUN Yong12,LU De-Cheng3,ZHANG Fan12,HUANG Dao-Qiang3,XU Jian-Long12,WANG Zhi-Dong3,ZHU Ling-Hua12,GAO Yong-Ming12,FU Bin-Ying12,LI Kang-Huo3,ZHOU Yong-Li12,ZHOU Shao-Chuan3*,LI Zhi-Kang12*   

  1. 1 Institute of Crop Sciences, Chinese Academy of Agricultural Sciences / National Key Facility for Crop Gene Resources and Genetic Improvement, Beijing 100081, China; 2 International Rice Research Institute, DAPO Box 7777, Metro Manila, The Philippines; 3 Rice Research Institute of Guang-dong Academy of Agricultural Sciences, Guangzhou 510640, Guangdong, China
  • Received:2008-01-04 Revised:1900-01-01 Published:2008-09-12 Published online:2008-09-12
  • Contact: LI Zhi-Kang

摘要: 以优质高产水稻品种丰矮占为轮回亲本, 以Khazar和IR64作供体亲本, 经连续回交分别构建了2套导入系(introgression lines)群体。对导入系后代分别在广州早造和晚造两种环境下进行重复产量鉴定。对两环境下产量及其组分性状的相关分析表明, 在广州早造和晚造环境下水稻产量构成因素存在很大差异。在早造, 每穗实粒数对产量供献最大, 而在晚造, 单株有效穗数对产量供献最大。应用SSR分子标记对这些导入系的供体片段进行全基因组扫描并应用单向方差分析(one-way ANOVA)剖析了导入系基因型与其产量及其组分的关系, 共检测到27个染色体区段与产量及组分性状相关, 包括10个产量QTL、9个单株穗数QTL、9个每穗实粒数QTL和14个千粒重QTL。大多数QTL只在一个环境条件下表达。在第3、7和9染色体上有3个QTL区域与产量及其两个组分有较大的效应, 值得关注。最终, 本研究在同步进行复杂农艺性状的改良和遗传剖析的研究上做出了有益的尝试。

关键词: 水稻, 选择导入系, QTL, 产量, 单株穗数, 每穗实粒数, 千粒重

Abstract: To facilitate breeding for high grain yield potential in rice, two BC3F5 introgression populations, derived from two crosses between Fengaizhan (FAZ, the recurrent parent) and two donors (Khazar and IR64), were genotyped with 89 and 101 polymorphic SSR markers and evaluated in two environments (early and late seasons growing in Guangzhou) to identify and map QTL affecting grain yield (GY) and its components, panicle number per plant (PNP), filled grain number per panicle (GNP), and 1 000-grain weight (TGW). Regression analyses indicated that GY was largely determined by GNP followed by PNP in the early season, and by PNP in the late season. The contribution of TGW to GY was small in both seasons. ANOVA analyses revealed a total of 27 QTL regions associated with GY and its components across the rice genome, including 10 GY QTL, 9 PNP QTL, 9 GNP QTL, and 14 TGW QTL. Fifteen (35.7%) of the identified QTL mapped to the similar regions with previously reported QTL affecting the same traits, indicated the robustness of our results. The majority of the QTL were only detected in one of the envi-ronments, indicating a strong component of G × E interactions of the identified QTL. Three interesting genomic regions on chro-mosomes 3, 7, and 9 were noted, which were associated with GY and two of its components. Detailed analyses indicated that both pleiotropy and linkage might be responsible for the observed associations. Our results provided useful information to our current understanding of the genetic basis of GY in rice, and a new strategy of using IL populations for both QTL discovery and breeding.

Key words: Rice, Introgression lines, QTL, Grain yield and components, G ´, E interaction, Pleiotropy

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