遗传与基因表达数据的整合——eQTL的方法及应用

Integrating genetic and gene expression data: methods and applications of eQTL mapping

高通量的基因型分析和芯片技术的发展使人们能够进一步研究哪些遗传差异最终影响基因的表达。通过表达数量性状座位(eQTL)作图方法可对基因表达水平的遗传基础进行解析。与传统的QTL分析方法一样,eQTL的主要目标是鉴别表达性状座位所在的染色体区域。但由于表达谱数据成千上万,而传统的QTL分析方法最多分析几十个性状,因此需要考虑这类实验设计的特点以及统计分析方法。本文详细介绍了eQTL定位过程及其研究方法,重点从个体选择、基因芯片实验设计、基因表达数据的获得与标准化、作图方法及结果分析等方面进行了综述,指出了当前eQTL研究存在的问题和局限性。最后介绍了eQTL研究在估计基因表达遗传率、挖掘候选基因、构建基因调控网络、理解基因间及基因与环境的互作的应用进展。

The availability of high-throughput genotyping technologies and microarray assays has allowed researchers to investigate genetic variations that influence levels of gene expression. Expression Quantitative Trait Locus （eQTL） mapping methods have been used to identify the genetic basis of gene expression. Similar to traditional QTL studies, the main goal of eQTL is to identify the genomic locations to which the expression traits are linked. Although microarrays provide the ex- pression data of thousands of transcripts, standard QTL mapping methods, which are able to handle at most tens of traits, cannot be applied directly. As a result, it is necessary to consider the statistical principles involved in the design and analysis of these experiments. In this paper, we reviewed individual selection, experimental design of microarray, normalization of gene expression data, mapping methods, and explaining of results and proposed potential methodological problems for such analyses. Finally, we discussed the applications of this integrative genomic approach to estimate heritability of transcripts, identify candidate genes, construct gene networks, and understand interactions between genes, genes and environments.