Published April 1, 2024 | Version v1
Journal article Open

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

  • 1. University of Chicago
  • 2. Columbia University

Description

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.

Data availability

All trans-eQTL signals, with functional annotation of the gene sets, can be browsed and downloaded at http://www.networks-liulab.org/transPCO and has been deposited at Zenodo (https://zenodo.org/doi/10.5281/zenodo.10602699). Any additional data reported in this paper will be shared by the lead contact upon request. DOIs are listed in the key resources table.

All original code, related to the trans-PCO pipeline and code to reproduce analyses presented in this work are publicly available at https://github.com/liliw-w/Trans, and has been deposited at Zenodo (https://zenodo.org/doi/10.5281/zenodo.10602558). DOIs are listed in the key resources table.

Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

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

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Additional details

Identifiers

DOI
10.1016/j.xgen.2024.100538
Other
oai:uchicago.tind.io:11570

Funding

NIGMS
Maximizing Investigators’ Research Award

UChicago Information

Division(s)
Biological Sciences Division
Department(s)
Genetics, Genomics, and Systems Biology, Human Genetics, Medicine