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

IF 11.1 Q1 CELL BIOLOGY Cell genomics Pub Date : 2024-04-10 Epub Date: 2024-04-01 DOI:10.1016/j.xgen.2024.100538
Lili Wang, Nikita Babushkin, Zhonghua Liu, Xuanyao Liu
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Abstract

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 co-expression 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.

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基因组中的 Trans-eQTL 图谱可识别遗传变异的网络效应。
在全基因组关联研究(GWAS)中发现的几乎所有性状相关变异都是非编码变异。这些变异的顺式调控效应已被广泛描述,但它们如何影响反式基因调控的研究却较少,因为反式表达定量位点(eQTLs)难以检测。我们开发了反式 PCO,用于检测基因变异对基因网络的反式影响。我们的模拟证明,trans-PCO大大优于现有的反式eQTL绘图方法。我们将 trans-PCO 应用于两个全血基因表达数据集:DGN(N = 913)和 eQTLGen(N = 31,684),发现了与 197 个共表达基因模块和生物过程相关的 14,985 个高质量反式-eSNP-模块对。我们在 46 个复杂性状的 GWAS 基因座与反式-eQTL 之间进行了共定位分析。我们证明,所发现的反式效应可以帮助我们了解性状相关变异是如何影响基因调控网络和生物通路的。
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