Brief Report
Version 1
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Trans-eQTLs Can Be Used to Untangle the Problem of Coexpression-Causality
Version 1
: Received: 22 February 2024 / Approved: 22 February 2024 / Online: 23 February 2024 (08:37:34 CET)
How to cite: Nikpay, M. Trans-eQTLs Can Be Used to Untangle the Problem of Coexpression-Causality. Preprints 2024, 2024021325. https://doi.org/10.20944/preprints202402.1325.v1 Nikpay, M. Trans-eQTLs Can Be Used to Untangle the Problem of Coexpression-Causality. Preprints 2024, 2024021325. https://doi.org/10.20944/preprints202402.1325.v1
Abstract
Following the era of GWAS studies, efforts are being made to identify genes underlying complex traits by merging eQTL and GWAS data and assessing the colocalization of eQTLs and GWAS signals. A problem that sometimes occurs in this context is the observation of association between several genes in a genomic region with a trait. This happens because genes in a region could be under the regulatory impact of common elements and coexpress. As such, computational approaches that rely on cis-eQTL information can not exactly pinpoint the causal gene. Here, I report an alternative solution, based on trans-eQTLs to test the association between a gene and a trait. Through the analyses applied to adjacent genes that coexpress and concordantly impact blood traits, I provide evidence that trans-eQTLs can resolve the problem of coexpression-causality without the interference of shared cis-regulatory SNPs.
Keywords
trans-eQTLs; coexpression; causality; TWAS; multiomics; GWAS
Subject
Biology and Life Sciences, Biochemistry and Molecular Biology
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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