Cardiac regeneration occurs primarily through proliferation of existing cardiomyocytes, but also involves complex interactions between distinct cardiac cell types including non-cardiomyocytes (non-CMs). However, the subpopulations, distinguishing molecular features, cellular functions, and intercellular interactions of non-CMs in heart regeneration remain largely unexplored. Using the LIGER algorithm, we assemble an atlas of cell states from 61,977 individual non-CM scRNA-seq profiles isolated at multiple time points during regeneration. This analysis reveals extensive non-CM cell diversity, including multiple macrophage (MC), fibroblast (FB), and endothelial cell (EC) subpopulations with unique spatiotemporal distributions, and suggests an important role for MC in inducing the activated FB and EC subpopulations. Indeed, pharmacological perturbation of MC function compromises the induction of the unique FB and EC subpopulations. Furthermore, we developed computational algorithm Topologizer to map the topological relationships and dynamic transitions between functional states. We uncover dynamic transitions between MC functional states and identify factors involved in mRNA processing and transcriptional regulation associated with the transition. Together, our single-cell transcriptomic analysis of non-CMs during cardiac regeneration provides a blueprint for interrogating the molecular and cellular basis of this process.
Keywords: Topologizer; heart regeneration; non-myocytes; scRNA-Seq; zebrafish.
© 2021 The Authors.