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F2:3设计全基因组标记的Bayesian分析
引用本文:万素琴,邵艳华,袁有禄,章元明. F2:3设计全基因组标记的Bayesian分析[J]. 作物学报, 2007, 33(12): 1943-1948
作者姓名:万素琴  邵艳华  袁有禄  章元明
作者单位: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
基金项目:教育部高等学校博士学科点专项科研基金;国家自然科学基金;教育部长江学者和创新团队发展计划;教育部跨世纪优秀人才培养计划;国家高技术研究发展计划(863计划);国家重点基础研究发展计划(973计划)
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  
收稿时间:2007-03-26
修稿时间:2007-07-31

Bayesian Analysis of All Markers on the Entire Genome in the F2:3 Design
WAN Su-Qin,SHAO Yan-Hua,YUAN You-Lu,ZHANG Yuan-Ming. Bayesian Analysis of All Markers on the Entire Genome in the F2:3 Design[J]. Acta Agronomica Sinica, 2007, 33(12): 1943-1948
Authors:WAN Su-Qin  SHAO Yan-Hua  YUAN You-Lu  ZHANG Yuan-Ming
Affiliation: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
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 be more suitable for mapping QTL for complex traits with low heritability.
Keywords:Bayesian shrinkage estimation  Quantitative trait locus  multiple marker analysis  F2:3 design
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