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Statistical methods for detecting expression quantitative trait loci (EQTL).

机译：用于检测表达数量性状基因座（EQTL）的统计方法。

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摘要

Treating mRNA transcript abundances as quantitative traits and mapping gene expression quantitative trait loci for these traits has been studied in many species from yeast to human. There has been significant success in finding associations between gene expression and genetic markers. These eQTL studies have been used to identify candidate causal regulators, to construct gene regulation networks, to identify hot spot regions, and to better understand clinical phenotypes. 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 (most likely 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 a latent indicator variable. The latent variable represents a combination of the genetic and phenotypic effect, conditional on which the markers and expression of genes are independently distributed. 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 much 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 (Brem and Kruglyak 2005). 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 different causal regulators or primary and secondary responses to causal perturbations. In addition, we identified nine modules associated with pairs of eQTLs, of which two have been previously reported, including the mating module (Brem et al. 2005) and the ZAP1 target module (Lee et al. 2006). We demonstrated that one of the novel modules containing many daughter-cell expressed genes is regulated by AMN1 and BPH1.
机译：从酵母到人类的许多物种已经研究了将mRNA转录丰度视为定量性状并绘制基因表达定量性状位点以用于这些性状。在发现基因表达与遗传标记之间的关联方面取得了重大成功。这些eQTL研究已用于鉴定候选因果调节剂，构建基因调控网络，鉴定热点区域以及更好地了解临床表型。由于此类分析中存在大量基因和遗传标记，因此发现少量eQTL如何相互作用以影响一组（很可能是共同调控的）基因的mRNA表达水平极具挑战性。为了解决这一问题，作者提出了一种贝叶斯方法，该方法将映射到一组共同标记的共表达基因作为以潜在指示变量为特征的模块。潜在变量代表遗传效应和表型效应的组合，条件是标记和基因表达独立分布。设计了马尔可夫链蒙特卡洛算法，以同时搜索模块基因及其链接的标记。通过仿真显示，与传统QTL定位方法相比，该方法对检测真正的eQTL及其靶基因的功能要强大得多。;我们将该程序应用于由112个酿酒酵母（Brem和克鲁格里亚克（2005）。我们的方法确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，这些模块对应于不同的因果调节因子或因果扰动的主要和次要响应。此外，我们确定了与eQTL对相关的九个模块，其中两个以前已被报道，包括配对模块（Brem等，2005）和ZAP1目标模块（Lee等，2006）。我们证明，包含许多子细胞表达基因的新型模块之一受AMN1和BPH1调控。

著录项

  • 作者

    Zhang, Wei.;

  • 作者单位

    Harvard University.;

  • 授予单位 Harvard University.;
  • 学科 Biology Biostatistics.;Statistics.;Biology Genetics.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 112 p.
  • 总页数 112
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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