Saturday, April 20, 2024
4/20/2024
Abstract The overall goal of this multi-principal investigator proposal is to facilitate the transition from implication of genetic variants identified in extensive genome wide association studies (GWAS) of Atrial Fibrillation (AF) to the molecular mechanisms underlying AF risk. We hypothesize that a novel genomic and analytic pipeline interrogating regulatory function of genetic variation will identify candidate causative variants and their target genes, enabling the transition from simple associations to causative mechanisms for the arrhythmia. In preliminary studies, we have applied novel single cell approaches to generate cell-type-resolved high-resolution chromosome accessibility maps and taken advantage of coordinated genomic signals to link AF risk variants to candidate causative AF genes. The results describe a highly interconnected gene regulatory network for cardiac atrial gene expression. In our first aim we propose to generate multi-modal single-cell genomics data to provide higher-resolution annotation of variant effects. We will improve our computational procedure to better leverage these datasets for AF variant and gene discovery. In our second aim, we will interrogate the interconnected gene regulatory network in molecular enhancer assays and genomic chromatin conformation capture experiments, to directly examine the impact of nominated genetic variants and their physical association with candidate target genes. In our third aim, we will examine the functionality of high confidence variant SNPs in depth, including their impact on gene regulation in cis, their impact on human cardiomyocyte electrophysiology, and their impact on cardiomyocyte gene expression and chromatin status in trans. We have established a tractable strategy that will help enable the transition from AF risk variants to molecular mechanisms. We anticipate that our approach will help translate the promise of AF genetics into meaningful biological insights for AF and establish a paradigm for the molecular understanding of genetic association studies in any system.
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