Allele-specific expression analysis for complex genetic phenotypes applied to a unique dilated cardiomyopathy cohort

Abstract

Abstract Allele-specific expression (ASE) analysis detects the relative abundance of alleles at heterozygous loci as a proxy for cis-regulatory variation, which affects the personal transcriptome and proteome. This study describes the development and application of an ASE analysis pipeline on a unique cohort of 87 well phenotyped and RNA sequenced patients from the Maastricht Cardiomyopathy Registry with dilated cardiomyopathy (DCM), a complex genetic disorder with a remaining gap in explained heritability. Regulatory processes for which ASE is a proxy might explain this gap. We found an overrepresentation of known DCM-associated genes among the significant results across the cohort. In addition, we were able to find genes of interest that have not been associated with DCM through conventional methods such as genome-wide association or differential gene expression studies. The pipeline offers RNA sequencing data processing, individual and population level ASE analyses as well as group comparisons and several intuitive visualizations such as Manhattan plots and protein–protein interaction networks. With this pipeline, we found evidence supporting the case that cis-regulatory variation contributes to the phenotypic heterogeneity of DCM. Additionally, our results highlight that ASE analysis offers an additional layer to conventional genomic and transcriptomic analyses for candidate gene identification and biological insight.