Identification of atrial fibrillation associated genes and functional non-coding variants

Abstract

Disease-associated genetic variants that lie in non-coding regions found by genome-wide association studies are thought to alter the functionality of transcription regulatory elements and target gene expression. To uncover causal genetic variants, variant regulatory elements and their target genes, here we cross-reference human transcriptomic, epigenomic and chromatin conformation datasets. Of 104 genetic variant regions associated with atrial fibrillation candidate target genes are prioritized. We optimize EMERGE enhancer prediction and use accessible chromatin profiles of human atrial cardiomyocytes to more accurately predict cardiac regulatory elements and identify hundreds of sub-threshold variants that co-localize with regulatory elements. Removal of mouse homologues of atrial fibrillation-associated regions in vivo uncovers a distal regulatory region involved in Gja1 (Cx43) expression. Our analyses provide a shortlist of genes likely affected by atrial fibrillation-associated variants and provide variant regulatory elements in each region that link genetic variation and target gene regulation, helping to focus future investigations.

Multicellular In vitro Models of Cardiac Arrhythmias: Focus on Atrial Fibrillation

“…These findings underscore the potential of iAM-1 cells as a model to study atrial arrhythmias. Due to the ease with which iAM-1 cells can be transfected, they have been used to investigate the impact of non-coding variants in AF-associated genes on the expression of these genes (236).…”

The contribution of non-coding regulatory elements to cardiovascular disease

“…More recently, several studies have also interrogated association signals at higher p -values (typically p < 1 × 10 −4 ), under the assumption that these may also include functionally relevant signals ( figure 1 a , bars with dash outline). Sub-threshold variants have been shown to include those at a false discovery rate lower than 5% [ 6 ], and to enrich for tissue-specific epigenetic signals [ 7 , 8 ]. Nevertheless, it is likely they are overall weaker in their functional significance when compared to variants at genome-wide significance, as suggested by their modest contribution to genetic risk scores [ 6 ].…”

“…Of note, an earlier study employing an enhancer-centric Hi-C approach on human coronary artery smooth muscle cells (HCASMCs) [ 99 ] reached similar conclusions for GWAS variants associated with CAD—89% of SNP-promoter contacts in HCASMCs skipped at least one gene, and 64% were mapped to more than a single gene target. More recently, an integrative analysis of genetic variants associated with AF has also made use of epigenome, transcriptome and promoter-capture Hi-C data to score and prioritize genomic loci for functional validation [ 8 ].…”

Human atlas of cardiac promoters and enhancers reveals important role of regulatory elements in heritable diseases

“…Signal data for epigenetic marks of Pol2, H3K27ac, H3K4me3, H3K4me1 was obtained from the ENCODE project. ATAC seq data for the human heart was obtained from Broad Institute's Cardiovascular Disease Knowledge Portal 52 . Conservation scores phastCons from 100-way alignment and CpG islands regions were accessed from UCSC for hg38.…”