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The heart maintains its essential role in human life by the highly orchestrated functioning of specialized cell types. Recent advances in single-cell and single-nuclei RNA sequencing (scRNA-seq and snRNA-seq) provides the possibility of profiling the molecular and cellular characteristics of heart cells. We collected scRNA-seq and snRNA-seq data of healthy human hearts from all available sources and built the first human ensemble heart cell atlas, uniHEART, using a unified information framework for cell-centric atlas assembly. The current version of uniHEART contains 1,025,739 cells from 65 human heart samples, covering 19 major cell types in adult and developing human heart. The samples are from 10 anatomic regions of the heart, with age of the donors ranging from 5 weeks of the fetus to 75 years old. With this ensemble cell atlas, we constructed the multifaceted cellular and molecular portraits of the human heart by its anatomic parts, cell types and interactions, gene expression and networks. A rich interactive portraiture web system is provided for users to explore the atlas. With uniHEART, we discovered the molecular changes in the heart endothelial cells during aging and explored the disease therapeutic target cell-types. These case examples showed that uniHEART provides a holographic cellular reference for future studies on the human heart.

Chromatin accessibility profiling methods such as assay for transposase-accessible chromatin using sequencing (ATAC-seq) have been promoting the identification of gene regulatory elements and the characterization of epigenetic landscapes. Unlike gene expression data, there is no consistent reference for chromatin accessibility data, which hinders large-scale integration analysis. By analyzing many more than 1000 ATAC-seq samples and 100 scATAC-seq samples, we found that cells share the same set of potential open regions. We thus proposed a reference called consensus peaks (cPeaks) to represent open regions across different cell types, and developed a deep-learning model to predict all potential open regions in the human genome. We showed that cPeaks can be regarded as a new set of epigenomic elements in the human genome, and using cPeaks can increase the performance of cell annotations and facilitate the discovery of rare cell types. cPeaks also performed well in analyzing dynamic biological processes and diseases. cPeaks can serve as a general reference for epigenetic studies, much like the reference genome for genomic studies, making the research faster, more accurate, and more scalable.