Genetic score omics regression and multitrait meta-analysis detect widespread cis-regulatory effects shaping bovine complex traits

Abstract

To complete the genome-to-phenome map, transcriptome-wide association studies (TWAS) are performed to correlate genetically predicted gene expression with observed phenotypic measurements. However, the relatively small training population assayed with gene expression could limit the accuracy of TWAS. We propose genetic score omics regression (GSOR) correlating observed gene expression with genetically predicted phenotype, i.e. estimated breeding values (EBVs) in agriculture or polygenic score (PGS) in medicine. The score, calculated using variants near genes with assayed expression (cis-EBV or cis-PGS), provides a powerful association test between cis-effects on gene expression and the trait..