UBS Equities, Stamford, Connecticut, United States of America.
PLoS Comput Biol. 2010 Jan 15;6(1):e1000642. doi: 10.1371/journal.pcbi.1000642.
Studies of the relationship between DNA variation and gene expression variation, often referred to as "expression quantitative trait loci (eQTL) mapping", have been conducted in many species and resulted in many significant findings. Because of the large number of genes and genetic markers in such analyses, it is extremely challenging to discover how a small number of eQTLs interact with each other to affect mRNA expression levels for a set of co-regulated genes. We present a Bayesian method to facilitate the task, in which co-expressed genes mapped to a common set of markers are treated as a module characterized by latent indicator variables. A Markov chain Monte Carlo algorithm is designed to search simultaneously for the module genes and their linked markers. We show by simulations that this method is more powerful for detecting true eQTLs and their target genes than traditional QTL mapping methods. We applied the procedure to a data set consisting of gene expression and genotypes for 112 segregants of S. cerevisiae. Our method identified modules containing genes mapped to previously reported eQTL hot spots, and dissected these large eQTL hot spots into several modules corresponding to possibly different biological functions or primary and secondary responses to regulatory perturbations. In addition, we identified nine modules associated with pairs of eQTLs, of which two have been previously reported. We demonstrated that one of the novel modules containing many daughter-cell expressed genes is regulated by AMN1 and BPH1. In conclusion, the Bayesian partition method which simultaneously considers all traits and all markers is more powerful for detecting both pleiotropic and epistatic effects based on both simulated and empirical data.
对 DNA 变异与基因表达变异之间关系的研究，通常被称为“表达数量性状基因座（eQTL）作图”，已经在许多物种中进行，并取得了许多重要发现。由于在这些分析中存在大量的基因和遗传标记，因此发现少数几个 eQTL 如何相互作用来影响一组共调控基因的 mRNA 表达水平极具挑战性。我们提出了一种贝叶斯方法来促进这项任务，即将映射到共同标记的共表达基因视为具有潜在指示变量的模块。设计了一种马尔可夫链蒙特卡罗算法来同时搜索模块基因及其相关标记。通过模拟，我们表明，与传统的 QTL 作图方法相比，该方法在检测真正的 eQTL 及其靶基因方面更具优势。我们将该程序应用于包含 112 个酿酒酵母分离物的基因表达和基因型数据集。我们的方法鉴定了包含映射到先前报道的 eQTL 热点的基因的模块，并将这些大的 eQTL 热点分解为几个模块，对应于可能不同的生物学功能或对调节扰动的主要和次要反应。此外，我们确定了与 9 对 eQTL 相关的 9 个模块，其中两个模块已被先前报道过。我们证明，包含许多子细胞表达基因的一个新模块受到 AMN1 和 BPH1 的调控。总之，基于模拟和经验数据，同时考虑所有性状和所有标记的贝叶斯分区方法在检测多效性和上位性效应方面更具优势。
