Abstract 106: Identifying Cardiac Conduction System-specific Enhancers That Link Cell-type Specification With Human Conduction Defects

Abstract

The Cardiac Conduction System (CCS) is composed of a small set of specialized cardiomyocytes (CMs) that generate and propagate the electrical impulse required for contraction of the cardiac chambers. Genome Wide Association Studies (GWAS) have identified nearly fifty cardiac rhythm associated Single Nucleotide Polymorphisms (SNPs), and recent reports have characterized how selected SNPs impact CCS gene regulatory networks to influence cardiac conduction. However, a global view of CCS regulatory networks remains to be elucidated, and the vast majority of cardiac conduction associated SNPs remain uncharacterized. Such in-depth analyses have been hampered by our inability to specifically interrogate genome accessibility and RNA expression in the CCS. In order to identify genome-wide cis regulatory elements that correlate with CCS cell-type specification, we generated and rigorously characterized novel knock-in (KI) Cre driver lines that label the Atrio-Ventricular Node (AVN) and ventricular conduction system (VCS) to add to the limited CCS-specific genetic toolkit. In our study, we also used a previously characterized Shox2 KI-Cre driver to label the sinoatrial node (SAN), the primary pacemaker of the heart. Given a variety of issues associated with FACS and Laser Capture Microdissection, we optimized the INTACT (Isolation of Nuclei TAgged in specific Cell Types) method for mammalian heart tissue. To isolate cell-type-specific nuclei, we used Rosa26-Sun1-myc-sfGFP-Tag mice in combination with CCS-specific Cre driver lines. Following isolation and enrichment of CCS-specific nuclei, we performed Omni-ATAC-seq to identify open regions of chromatin (e.g. enhancer elements) and differentially enriched transcription factor motifs for individual CCS cellular sub-types without prior knowledge of cell-type specific regulators. Most cardiac transcriptomes in the literature do not distinguish between individual subtypes. Therefore, using bulk nuclear RNA-Seq, we also generated CCS-subtype specific transcriptomes. We anticipate that our datasets will provide an important starting point for establishing mechanistic links between CCS-specific enhancer elements and disease-associated SNPs identified by GWAS.