Bayesian analysis of complex traits in pedigreed plant populations
Bayesian analysis of complex traits in pedigreed plant populations
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DOI：
10.1007/s10681-007-9516-1
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发表时间：
2008-05-01
期刊：
影响因子：
1.9
通讯作者：
de Weg, W. E. van
中科院分区：
文献类型：
--
作者：
Bink, M. C. A. M.;Boer, M. P.;de Weg, W. E. van
提出了一种分析复杂性状的贝叶斯方法，该方法可以帮助植物遗传学家和育种者利用正在进行的育种计划中可用的谱系群体的标记和表型数据。数量性状的统计模型可以包括非遗传成分和遗传成分。后者可分为已知标记连锁群上的QTL、主基因和多基因成分。给出了全概率模型、模型变量的先验假设，给出了模型选择和后验推断的准则。使用欧盟HiDRAS项目的已知家系种群结构的模拟数据来说明使用贝叶斯方法来分析复杂性状。结果表明，当模型中包含非遗传因素时，以及在不同时分析所有连锁群的情况下，当包含多基因成分时，QTL参数的估计更准确。贝叶斯方法已经被应用到软件包FlexQTL中，并允许植物育种者探索他们的系谱群体，以分离与他们的育种计划相关的QTL等位基因。
A Bayesian approach to analyze complex traits is presented that can help plant eneticists and breeders in exploiting the marker and phenotypic data on pedigreed populations as available from ongoing breeding programs. The statistical model for the quantitative trait may include non-genetic and genetic components. The latter component can be divided into QTL on known marker linkage groups, major genes and a polygenic component. The full probability model, prior assumptions on model variables are presented and criterion for model selection and posterior inferences are given. Simulated data on a known pedigreed population structure of the EU project HiDRAS was used to illustrate the use of the Bayesian approach to analyze complex traits. It was shown that estimates for QTL parameters were more accurate when non-genetic factors were included in the model and when a polygenic component was included when not all linkage groups were analyzed simultaneously. The Bayesian approach has been implemented into the software package FlexQTL and allows plant breeders explore their pedigreed populations for segregating QTL alleles that are relevant in their breeding program.