Cross-Population Joint Analysis of eQTLs: Fine Mapping and Functional Annotation

被引：65

作者：

Wen, Xiaoquan ^{[1
]}

Luca, Francesca ^{[2
,3
]}

Pique-Regi, Roger ^{[2
,4
]}

机构：

[1] Univ Michigan, Dept Biostat, Ann Arbor, MI 48109 USA

[2] Wayne State Univ, Ctr Mol Med & Genet, Detroit, MI USA

[3] Wayne State Univ, Dept Obstet & Gynecol, Detroit, MI USA

[4] Wayne State Univ, Dept Clin & Translat Sci, Detroit, MI USA

来源：

PLOS GENETICS | 2015年 / 11卷 / 04期

关键词：

GENE-EXPRESSION; HUMAN GENOME; ARCHITECTURE;

D O I：

10.1371/journal.pgen.1005176

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

Mapping expression quantitative trait loci (eQTLs) has been shown as a powerful tool to uncover the genetic underpinnings of many complex traits at the molecular level. In this paper, we present an integrative analysis approach that leverages eQTL data collected from multiple population groups. In particular, our approach effectively identifies multiple independent cis-eQTL signals that are consistent across populations, accounting for population heterogeneity in allele frequencies and linkage disequilibrium patterns. Furthermore, by integrating genomic annotations, our analysis framework enables high-resolution functional analysis of eQTLs. We applied our statistical approach to analyze the GEUVADIS data consisting of samples from five population groups. From this analysis, we concluded that i) jointly analysis across population groups greatly improves the power of eQTL discovery and the resolution of fine mapping of causal eQTL ii) many genes harbor multiple independent eQTLs in their cis regions iii) genetic variants that disrupt transcription factor binding are significantly enriched in eQTLs (p-value = 4.93 x 10(-22)).

引用

页数：29

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