IRTA-LLEIDA, Lleida, Spain.
J Anim Breed Genet. 2010 Feb;127(1):16-25. doi: 10.1111/j.1439-0388.2009.00826.x.
After quantitative trait loci (QTL) detection, one of the main objectives of research is to identify the causal mutation explaining phenotypic differences. Candidate genes are usually selected according to the physiological mechanism of the trait and their location within the same region of the QTL. After detection of any polymorphism at the candidate gene sequence, it is important to determine whether the detected mutation is the one that causes the phenotypic variation. This is not, however, an easy task, because of the linkage disequilibrium between the genes located in the same region. Several methods have been proposed that consider the neutral marker information in validating the involvement of candidate genes. However, some statistical information may be lost because of the presence of both the QTL and candidate gene effects in the model of analysis. Here, the Bayes factor is suggested as an alternative and a procedure for its calculation between candidate gene and QTL models is presented. The procedure is illustrated with a simulation study and with an example consisting of three SNPs detected at the leptin receptor (LEPR) in an experimental intercross between Iberian and Landrace pigs. The results indicate that the Bayes factor procedure is more powerful than the classical approach.
在定量性状基因座（QTL）检测之后，研究的主要目标之一是确定解释表型差异的因果突变。候选基因通常根据性状的生理机制及其在 QTL 同一区域内的位置进行选择。在候选基因序列中检测到任何多态性后，重要的是要确定检测到的突变是否是引起表型变异的突变。然而，由于位于同一区域的基因之间存在连锁不平衡，这并非易事。已经提出了几种方法，这些方法考虑了中性标记信息，以验证候选基因的参与。然而，由于分析模型中存在 QTL 和候选基因效应，一些统计信息可能会丢失。在这里，贝叶斯因子被提议作为替代方法，并提出了候选基因和 QTL 模型之间计算贝叶斯因子的过程。该过程通过模拟研究和一个由三个 SNP 组成的示例进行说明，这些 SNP 是在伊比利亚和长白猪的实验杂交中在瘦素受体（LEPR）上检测到的。结果表明，贝叶斯因子过程比经典方法更有效。
