Tejaas: reverse regression increases power for detecting trans-eQTLs

Abstract

Trans-acting expression quantitative trait loci (trans-eQTLs) account for ≥70% expression heritability and could therefore facilitate uncovering mechanisms underlying the origination of complex diseases. Identifying trans-eQTLs is challenging because of small effect sizes, tissue specificity, and a severe multiple-testing burden. Tejaas predicts trans-eQTLs by performing L2-regularized “reverse” multiple regression of each SNP on all genes, aggregating evidence from many small trans-effects while being unaffected by the strong expression correlations. Combined with a novel unsupervised k-nearest neighbor method to remove confounders, Tejaas predicts 18851 unique trans-eQTLs across 49 tissues from GTEx. They are enriched in open chromatin, enhancers, and other regulatory regions. Many overlap with disease-associated SNPs, pointing to tissue-specific transcriptional regulation mechanisms.Fil: Banerjee, Saikat. Max Planck Institute For Biophysical Chemistry; AlemaniaFil: Simonetti, Franco Lucio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentina. Max Planck Institute For Biophysical Chemistry; AlemaniaFil: Detrois, Kira E.. Max Planck Institute For Biophysical Chemistry; Alemania. Universität Göttingen; AlemaniaFil: Kaphle, Anubhav. Universität Göttingen; Alemania. Max Planck Institute For Biophysical Chemistry; AlemaniaFil: Mitra, Raktim. Indian Institute of Technology; IndiaFil: Nagial, Rahul. Indian Institute of Technology; IndiaFil: Söding, Johannes. Max Planck Institute For Biophysical Chemistry; Alemania. University of Göttingen; Alemani