The human heart is a vital organ with complex functions and clinical importance. Understanding its development, physiology, and disease mechanisms is key to advancing cardiovascular care. Studying cardiac chromatin accessibility helps reveal epigenetic regulation and therapeutic targets. While single-cell sequencing has generated multiple datasets, issues like data dispersion, quality variation, and batch effects hinder their utility. A unified, high-quality human heart chromatin accessibility database is urgently needed to support systematic epigenomic research.

Recently, the research team led by Rui Jiang at Tsinghua University’s Department of Automation published a study titled “CASHeart: A database of single-cell chromatin accessibility for the human heart” in Quantitative Biology. This work systematically integrates and processes publicly available datasets to reveal cellular heterogeneity in the human heart, thereby advancing molecular insights into cardiac development, functional maintenance, disease pathogenesis, and therapeutic responses.

CASHeart is a comprehensive human heart single-cell chromatin accessibility database that integrates large-scale datasets and provides an online analysis platform. It includes data collected from nine heart tissue samples representing adult and infant hearts (HGCA and FCA) and 47 spatial multi-omics samples from human cardiac microenvironments, all standardized to the GRCh38 genome assembly. Using SnapATAC2 and MACS3, the team performed uniform peak calling, and gene activity scores were calculated with EpiScanpy, resulting in a normalized single-cell chromatin accessibility dataset. The CASHeart web platform features multiple interfaces for browsing, searching, downloading data, tutorials, and analysis tools, facilitating exploration through UMAP visualizations and differential accessibility analyses. CASHeart effectively reveals cell type heterogeneity in the heart, with improved clustering accuracy and batch effect correction compared to original datasets, distinguishing cardiomyocytes from other cell types more reliably. It supports multi-level analyses of differential chromatin accessibility and gene activation, identifying heart disease-related regulatory regions and cell type-specific genes. As a reference dataset, CASHeart enhances clustering and subtype resolution in other heart single-cell chromatin and transcriptome data. Furthermore, it advances heart-specific gene regulation and genetic variation studies by uncovering co-accessibility networks and enrichment of disease-associated variants. Overall, CASHeart fills a critical gap in cardiac epigenomics research and offers valuable tools for understanding heart development, disease mechanisms, and therapeutic targets.
DOI: 10.1002/qub2.90