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作物学报 ›› 2007, Vol. 33 ›› Issue (12): 1943-1948.

• 研究论文 • 上一篇    下一篇

F2:3设计全基因组标记的Bayesian分析

万素琴1;邵艳华2;袁有禄2;章元明1,*   

  1. 1南京农业大学作物遗传与种质创新国家重点实验室/国家大豆改良中心,江苏南京210095;2中国农业科学院棉花研究所/农业部棉花遗传改良重点实验室,河南安阳455004
  • 收稿日期:2007-03-26 修回日期:1900-01-01 出版日期:2007-12-12 网络出版日期:2007-12-12
  • 通讯作者: 章元明

Bayesian Analysis of All Markers on the Entire Genome in the F2:3 Design

WAN Su-Qin1,SHAO Yan-Hua2,YUAN You-Lu2,ZHANG Yuan-Ming1*   

  1. 1 State Key Laboratory of Crop Genetics and Germplasm Enhancement / National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing 210095, Jiangsu; 2 Cotton Research Institute, Chinese Academy of Agricultural Sciences/Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang 455004, Henan, China
  • Received:2007-03-26 Revised:1900-01-01 Published:2007-12-12 Published online:2007-12-12
  • Contact: ZHANG Yuan-Ming

摘要: 数量性状的遗传率低时,常采用F2:3设计进行遗传分析,但往往忽略异质家系内QTL的混合分布特性。同时,用多QTL模型检测QTL会提高QTL检测的功效。因此,本文在利用F2:3设计异质F2:3家系内QTL混合分布特性基础上,提出F2:3设计全基因组多标记联合分析新方法。该方法充分利用了异质F2:3家系内的QTL混合分布,并采用多QTL遗传模型。Monte Carlo模拟研究表明,新方法能获得精确的QTL效应和位置的估计。此外,还比较了QTL效应抽样的两种策略。研究表明,新策略能显著提高QTL检测的功效。

关键词: 贝叶斯压缩估计, 数量性状基因座, 多标记, F2:3设计

Abstract: In the inheritance analysis of quantitative traits with relatively low heritability, the precision is relatively low. In this situation, an F2:3 design, which is genotyped in F2 plants and phenotyped in the F2:3 progeny, is applied to increase the precision in the detection of quantitative trait loci (QTL). However, there are two issues needed to be further considered. One is to take full advantage of the mixture distribution for F2:3 families of heterozygous F2 plants, and the other to adopt multi-QTL genetic model. In this article, therefore, we extended our previous method from a single-QTL genetic analysis to joint analysis of all markers on the entire genome in the F2:3 design. The proposed method here is on the basis of multi-QTL genetic model, and also takes full advantage of the mixture distribution mentioned above. Results of simulated studies showed that the new method provides accurate estimates for both the effects and the positions of QTL. Moreover, two strategies for sampling QTL effects were compared and the new one is better than the old one. In conclusion, the new method may is more suitable for mapping QTL for complex traits with low heritability.

Key words: Bayesian shrinkage estimation, Quantitative trait locus, multiple marker analysis, F2:3 design

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