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Global chromatin landscapes identify candidate noncoding modifiers of cardiac rhythm
Samadrita Bhattacharyya, Rahul K. Kollipara, Gabriela Orquera-Tornakian, Sean Goetsch, Minzhe Zhang, Cameron Perry, Boxun Li, John M. Shelton, Minoti Bhakta, Jialei Duan, Yang Xie, Guanghua Xiao, Bret M. Evers, Gary C. Hon, Ralf Kittler, Nikhil V. Munshi
Samadrita Bhattacharyya, Rahul K. Kollipara, Gabriela Orquera-Tornakian, Sean Goetsch, Minzhe Zhang, Cameron Perry, Boxun Li, John M. Shelton, Minoti Bhakta, Jialei Duan, Yang Xie, Guanghua Xiao, Bret M. Evers, Gary C. Hon, Ralf Kittler, Nikhil V. Munshi
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Research Article Cardiology

Global chromatin landscapes identify candidate noncoding modifiers of cardiac rhythm

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Abstract

Comprehensive cis-regulatory landscapes are essential for accurate enhancer prediction and disease variant mapping. Although cis-regulatory element (CRE) resources exist for most tissues and organs, many rare — yet functionally important — cell types remain overlooked. Despite representing only a small fraction of the heart’s cellular biomass, the cardiac conduction system (CCS) unfailingly coordinates every life-sustaining heartbeat. To globally profile the mouse CCS cis-regulatory landscape, we genetically tagged CCS component–specific nuclei for comprehensive assay for transposase-accessible chromatin–sequencing (ATAC-Seq) analysis. Thus, we established a global CCS-enriched CRE database, referred to as CCS-ATAC, as a key resource for studying CCS-wide and component-specific regulatory functions. Using transcription factor (TF) motifs to construct CCS component–specific gene regulatory networks (GRNs), we identified and independently confirmed several specific TF sub-networks. Highlighting the functional importance of CCS-ATAC, we also validated numerous CCS-enriched enhancer elements and suggested gene targets based on CCS single–cell RNA-Seq data. Furthermore, we leveraged CCS-ATAC to improve annotation of existing human variants related to cardiac rhythm and nominated a potential enhancer-target pair that was dysregulated by a specific SNP. Collectively, our results established a CCS-regulatory compendium, identified novel CCS enhancer elements, and illuminated potential functional associations between human genomic variants and CCS component–specific CREs.

Authors

Samadrita Bhattacharyya, Rahul K. Kollipara, Gabriela Orquera-Tornakian, Sean Goetsch, Minzhe Zhang, Cameron Perry, Boxun Li, John M. Shelton, Minoti Bhakta, Jialei Duan, Yang Xie, Guanghua Xiao, Bret M. Evers, Gary C. Hon, Ralf Kittler, Nikhil V. Munshi

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Figure 3

CCS-ATAC enables construction of CCS component-specific GRNs.

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CCS-ATAC enables construction of CCS component-specific GRNs.
(A) TF sub...
(A) TF subnetworks were compared to assess SAN enrichment (blue). Inset: Heatmap shows fold enrichment in TF gene expression for SAN relative to CM. Solid black indicates undetectable. (B) Diagram representing a SAN-enriched EWSR1-FLI1 sub-network with selective labeling of highly connected genes. Central EWSR1-FLI1 node is shown in yellow, and individual downstream genes are depicted by light blue ovals. Proximity to the central node indicates greater connectivity. (C) Enriched GO terms for SAN EWSR1-FLI1 subnetwork target genes. (D) TF subnetworks were compared to assess enrichment in AVN (red). Inset: Heatmap shows fold enrichment in TF gene expression for AVN relative to CM. Solid black indicates undetectable expression. (E) Diagram of the AVN EWSR1-FLI1 subnetwork with selective labeling of highly connected genes as in (B). (F) Enriched GO terms for the AVN EWSR1-FLI1 subnetwork target genes. ECM, Extracellular matrix. (G) Examples of SAN and AVN EWSR1-FLI1 target gene loci with EWSR1-FLI1 consensus motifs, relative location, and number of GGAA microsatellite repeats. Genome browser view is shown for the Myh6 gene locus, with ENCODE mouse H-H3K27Ac ChIP-Seq at various time points (1, E10.5; 2, E12.5; 3, E16.5; 4, P0; 5, 8 weeks) as well as other ENCODE mouse adult tissue H3K27Ac ChIP-Seq (6, cortex; 7, cerebellum; 8, spleen. (H) Table of predicted and known target genes for EWSR1-FLI1, FLI1, Etv1, and Onecut1. (I) Experimental workflow for TF subnetwork validation in NRVMs. (J and K) Bar graphs showing target gene induction for each overexpressed TF. Error bars illustrate SE. of target gene expression among 3 independent experiments. Nppa served as a negative control. (L and M) Bar graphs showing genomic localization by ChIP-qPCR fold-enrichment for EWSR1-FLI1 (L) and Etv1 (M) compared with IgG control. Error bars illustrate SEM of target gene expression among 3 independent experiments. Tubb3 served as a negative control. (N) Bar graphs showing genomic localization by ChIP-qPCR fold-enrichment for Onecut1 compared with IgG control. Error bars illustrate SEM target gene expression among 3 independent experiments. Tubb3 served as a negative control. Significance determined by 2-tailed t test. *P < 0.05; **P < 0.01; ***P < 0.005.

Copyright © 2026 American Society for Clinical Investigation
ISSN: 0021-9738 (print), 1558-8238 (online)

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