Trans-eQTL mapping in gene sets identifies network effects of genetic variants

被引：4

作者：

Wang, Lili ^{[1
,2
]}

Babushkin, Nikita ^{[2
]}

Liu, Zhonghua ^{[3
]}

Liu, Xuanyao ^{[1
,2
,4
]}

机构：

[1] Univ Chicago, Comm Genet Genom & Syst Biol, Chicago, IL 60637 USA

[2] Univ Chicago, Dept Med, Sect Genet Med, Chicago, IL 60637 USA

[3] Columbia Univ, Dept Biostat, New York, NY 10032 USA

[4] Univ Chicago, Dept Human Genet, Chicago, IL 60637 USA

来源：

CELL GENOMICS | 2024年 / 4卷 / 04期

关键词：

GENOME-WIDE ASSOCIATION; DISEASE; LOCI; EXPRESSION; NLRC5;

D O I：

10.1016/j.xgen.2024.100538

中图分类号：

Q2 [细胞生物学];

学科分类号：

071009 ; 090102 ;

摘要：

Nearly all trait -associated variants identified in genome-wide association studies (GWASs) are noncoding. The cis regulatory effects of these variants have been extensively characterized, but how they affect gene regulation in trans has been the subject of fewer studies because of the difficulty in detecting trans -expression quantitative loci (eQTLs). We developed trans -PCO for detecting trans effects of genetic variants on gene networks. Our simulations demonstrate that trans -PCO substantially outperforms existing trans -eQTL mapping methods. We applied trans -PCO to two gene expression datasets from whole blood, DGN (N = 913) and eQTLGen (N = 31,684), and identified 14,985 high -quality trans -eSNP-module pairs associated with 197 coexpression gene modules and biological processes. We performed colocalization analyses between GWAS loci of 46 complex traits and the trans -eQTLs. We demonstrated that the identified trans effects can help us understand how trait -associated variants affect gene regulatory networks and biological pathways.

引用

页数：17

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