Estimating allelic number and identity in state of QTLs in interconnected families
Estimating allelic number and identity in state of QTLs in interconnected families
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DOI：
10.1017/s0016672303006153
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发表时间：
2003-04-01
期刊：
影响因子：
--
通讯作者：
Wu, XL
中科院分区：
文献类型：
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作者：
Jannink, JL;Wu, XL
当对来自自交系的多个相关家系进行联合分析以检测数量性状位点（QTL）时，分析应尽可能准确地估计等位基因效应，并估计不同亲本携带状态相同的等位基因的概率。存在的分析假设所有的父母携带独特的等位基因，或者所有的父母，但一个携带相同的等位基因。在实践中，许多配置是可能的，分组不同的父母根据他们的身份保持条件在一个假定的QTL等位基因。在这里，我们提出了一个变量模型贝叶斯分析，选择可能的身份状态配置，并共同估计等位基因的影响相同的状态父母。我们将此分析与估计所有父母的独特等位基因效应的固定模型分析进行对比。我们分析了两个模拟交配设计：一个实验设计，其中三个自交系的父母进行了杂交，产生两个家庭的150个加倍的单倍体系;和一个育种设计，其中20个自交系的父母进行了杂交，产生60个家庭的20个加倍的单倍体系，每个父母贡献6个家庭。在所有的情况下，一些父母p模拟携带等位基因的相同效果（即，他们是相同的状态），变量分析估计等位基因的影响与较低的均方误差比固定的分析。变量分析表明，除非每个家系包含许多个体（超过100个），否则DNA标记和表型数据中的信息不足以以高概率确定QTL等位基因数。
When multiple related families derived from inbred lines are jointly analysed to detect quantitative trait loci (QTLs), the analysis should estimate allelic effects as accurately as possible and estimate the probability that different parents carry alleles that are identical in state. Analyses exist that assume that all parents carry unique alleles or that all parents but one carry the same allele. In practice, many configurations are possible that group different parents according to their identity-instate condition at a putative QTL allele. Here, we propose a variable model Bayesian analysis that selects among possible identity-in-state configurations and jointly estimates the allelic effects of identical-in-state parents. We contrast this analysis with a fixed model analysis that estimates unique allelic effects for all parents. We analyse two simulated mating designs: an experimental design in which three inbred parents were crossed to generate two families of 150 doubled haploid lines; and a breeding design in which 20 inbred parents were crossed to generate 60 families of 20 doubled haploid lines, with each parent contributing to six families. In all cases where some parents were p simulated to carry alleles of identical effect (that is, they were identical in state), the variable analysis estimated allelic effects with lower mean-squared error than the fixed analysis. The variable analysis showed that, unless each family contains many individuals (more than 100), there is insufficient information in DNA-marker and phenotypic data to determine with high probability the QTL allelic number.