scAF_multiome - Single-nucleus Multiome (paired RNA+ATACseq) Analysis in Atrial Fibrillation

Abstract

The dysregulation of gene expression programs in the human atria during persistent atrial fibrillation (AF) is not completely understood. Here, we reanalyze bulk RNA-sequencing datasets from two studies (N = 242) and identified 755 differentially expressed genes in left atrial appendages of individuals with persistent AF and non-AF controls. We combined the bulk RNA-sequencing differentially expressed genes with a left atrial appendage single-nucleus multi-omics dataset to assign genes to specific atrial cell types. We found noncoding genes at the IFNG locus (LINC01479, IFNG-AS1) strongly dysregulated in cardiomyocytes. We defined a gene expression signature potentially driven by androgen receptor signaling in cardiomyocytes from individuals with AF. Cell-type-specific gene expression modules suggested an increase in T cell and a decrease in adipocyte and neuronal cell gene expression in AF. Lastly, we showed that reducing NR4A1 expression, a marker of a poorly characterized human atrial fibroblast subtype, fibroblast activation markers, extracellular matrix remodeling and cell proliferation decreased.

Paper Reference

Leblanc FJA, Yiu CHK, Moreira LM, et al. Single-nucleus multi-omics implicates androgen receptor signaling in cardiomyocytes and NR4A1 regulation in fibroblasts during atrial fibrillation. Nat Cardiovasc Res (2025). https://doi.org/10.1038/s44161-025-00626-0

Key Findings

• Identification of cell type-specific gene dysregulation in atrial fibrillation
• Discovery of androgen receptor signaling alterations in cardiomyocytes during AF
• Characterization of a novel fibroblast subtype marked by NR4A1 expression
• Experimentally validated the role of NR4A1 in fibroblast activation and extracellular matrix remodeling

Analysis Workflow

The analysis is organized into sequential R Markdown files:

1. 00.external_data.rmd: Download/set up of external datasets
2. 01.make_seurat.rmd: Create main Seurat object from this study
3. 02.QC_filters.rmd: Quality control and filtering of single-nucleus data
4. 03.celltype_summary_stats.rmd: Summary statistics for identified cell types
5. 04.peaks_summary_stats.rmd: Summary statistics for identified ATAC-seq peaks
6. 05.chromvar.rmd: Transcription factor motif enrichment analysis using ChromVAR
7. 06.bulk_qc_deg.rmd: Differential expression analysis of independant bulk RNA-seq data
8. 07.pseudo_deg.rmd: Pseudobulk differential expression analysis of single-nucleus data
9. 08.WCGNA.rmd: Weighted gene co-expression network analysis
10. 09.metacells.rmd: Metacell creation
11. 10.AF_CM_signature.rmd: Identifying a cardiomyocyte gene signature of persistent AF
12. 11.FB_subclustering.rmd: This study's fibroblast state identification
13. 12.FB_atlas_map.rmd: Multi-dataset integration of cardiac fibroblasts
14. 13.aFB3_validation.rmd: Validation of fibroblast 3 state in an other AF dataset

Installation and Setup

This repository uses renv for package management. To set up the environment:

# Install renv if not already installed
install.packages("renv")

# Initialize the project with renv
renv::restore()

Data Availability

Raw single-nucleus multiome sequencing data is available at GSE238242. A bulk RNA-seq gene count matrix is available at http://www.mhi-humangenetics.org/en/resources/.