Cells of the adult human heart
By Monika Litviňuková, Carlos Talavera-López, H. Maatz, D. Reichart, Catherine L. Worth, E. Lindberg, M. Kanda, Krzysztof Polanski, Matthias Heinig, Michael Lee and 23 more. Nature, 2020
1,417 citations recorded by the source corpus.
Cardiovascular disease is the leading cause of death worldwide. Advanced insights into disease mechanisms and therapeutic strategies require a deeper understanding of the molecular processes involved in the healthy heart. Knowledge of the full repertoire of cardiac cells and their gene expression profiles is a fundamental first step in this endeavour. Here, using state-of-the-art analyses of large-scale single-cell and single-nucleus transcriptomes, we characterize six anatomical adult heart regions. Our results highlight the cellular heterogeneity of cardiomyocytes, pericytes and fibroblasts, and reveal distinct atrial and ventricular subsets of cells with diverse developmental origins and specialized properties. We define the complexity of the cardiac vasculature and its changes along the arterio-venous axis. In the immune compartment, we identify cardiac-resident macrophages with inflammatory and protective transcriptional signatures. Furthermore, analyses of cell-to-cell interactions highlight different networks of macrophages, fibroblasts and cardiomyocytes between atria and ventricles that are distinct from those of skeletal muscle. Our human cardiac cell atlas improves our understanding of the human heart and provides a valuable reference for future studies. Single-cell and single-nucleus RNA sequencing are used to construct a cellular atlas of the human heart that will aid further research into cardiac physiology and disease.
Subfields: Molecular Biology
View Paper: https://www.semanticscholar.org/paper/20bec9010429f563aea42aed077f5ffa64c46275
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In Molecular Biology
- Malte D. Luecken
- Fabian J Theis
- Luke Zappia
- John C. Marioni
- Maren Büttner
- Marta Interlandi
- Rahul Satija
- Sarah A. Teichmann
Citations in the corpus
- Benchmarking atlas-level data integration in single-cell genomics (2020, methodology): “If cell identity labels are known, it is always beneficial to integrate scRNA-seq batches via scANVI or scGen (for example, as in the recent heart cell atlas 38 ).”
- Unsupervised removal of systematic background noise from droplet-based single-cell experiments using CellBender (2019, background): “[41] Monika Litviňuková, Carlos Talavera-López, Henrike Maatz, Daniel Reichart, Catherine L.”