Search

The recent development and broad application of sequencing techniques at the single-cell level is generating an unprecedented amount of data. The different techniques have their individual limits, but the datasets also offer unexpected possibilities when utilized collectively. Here, we applied snRNA-seq in whole adult murine hearts from an inbred (C57BL/6NRj) and an outbred (Fzt:DU) mouse strain to directly compare the data with the publicly available scRNA-seq data of the tabula muris project. Explicitly choosing a single-nucleus approach allowed us to pin down the typical heart tissue-specific technical bias, coming up with novel insights on the mammalian heart cell composition. For our integrated dataset, cardiomyocytes, fibroblasts, and endothelial cells constituted the three main cell populations accounting for about 75% of all cells. However, their numbers severely differed between the individual datasets, with cardiomyocyte proportions ranging from about 9% in the tabula muris data to around 23% for our BL6 data, representing the prime example for cell capture technique related bias when using a conventional single-cell approach for these large cells. Most strikingly in our comparison was the discovery of a minor population of cardiomyocytes characterized by proliferation markers that could not be identified by analyzing the datasets individually. It is now widely accepted that the heart has an, albeit very restricted, regenerative potential. However there is still an ongoing debate where new cardiomyocytes arise from. Our findings support the idea that the renewal of the cardiomyocyte pool is driven by cytokinesis of resident cardiomyocytes rather than differentiation of progenitor cells. We thus provide data that can contribute to an understanding of heart cell regeneration, which is a prerequisite for future applications to enhance the process of heart repair.

Analyses on the cellular level are indispensable to expand our understanding of complex tissues like the mammalian heart. Single-nucleus sequencing (snRNA-seq) allows for the exploration of cellular composition and cell features without major hurdles of single-cell sequencing. We used snRNA-seq to investigate for the first time an entire adult mammalian heart. Single-nucleus quantification and clustering led to an accurate representation of cell types, revealing 24 distinct clusters with endothelial cells (28.8%), fibroblasts (25.3%), and cardiomyocytes (22.8%) constituting the major cell populations. An additional RNA velocity analysis allowed us to study transcription kinetics and was utilized to visualize the transitions between mature and nascent cellular states of the cell types. We identified subgroups of cardiomyocytes with distinct marker profiles. For example, the expression of Hand2os1 distinguished immature cardiomyocytes from differentiated cardiomyocyte populations. Moreover, we found a cell population that comprises endothelial markers as well as markers clearly related to cardiomyocyte function. Our velocity data support the idea that this population is in a trans-differentiation process from an endothelial cell-like phenotype towards a cardiomyocyte-like phenotype. In summary, we present the first report of sequencing an entire adult mammalian heart, providing realistic cell-type distributions combined with RNA velocity kinetics hinting at interrelations.