Temporal Dynamics and Heterogeneity of Cell Populations during Skeletal Muscle Regeneration

• Published in: iScience Vol. 23; no. 4; p. 100993
• Main Authors: Oprescu, Stephanie N., Yue, Feng, Qiu, Jiamin, Brito, Luiz F., Kuang, Shihuan
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 24.04.2020; Elsevier
• Subjects: adipogenesis; Bioinformatics; cell communication; Developmental Biology; gene expression; mammals; muscle development; myoblasts; sequence analysis; skeletal muscle; Stem Cells Research; tissue repair; Developmental Biology; Bioinformatics; Stem Cells Research
• ISSN: 2589-0042; 2589-0042
• DOI: 10.1016/j.isci.2020.100993

Mammalian skeletal muscle possesses a unique ability to regenerate, which is primarily mediated by a population of resident muscle stem cells (MuSCs) and requires a concerted response from other supporting cell populations. Previous targeted analysis has described the involvement of various specific populations in regeneration, but an unbiased and simultaneous evaluation of all cell populations has been limited. Therefore, we used single-cell RNA-sequencing to uncover gene expression signatures of over 53,000 individual cells during skeletal muscle regeneration. Cells clustered into 25 populations and subpopulations, including a subpopulation of immune gene enriched myoblasts (immunomyoblasts) and subpopulations of fibro-adipogenic progenitors. Our analyses also uncovered striking spatiotemporal dynamics in gene expression, population composition, and cell-cell interaction during muscle regeneration. These findings provide insights into the cellular and molecular underpinning of skeletal muscle regeneration. [Display omitted] •scRNA-seq of 53,000 cells reveals known and new cell subsets in regenerating muscle•Immune cells exhibit early infiltration, pro- and anti-inflammation and slow resolution•Linear trajectory of activated FAPs to Dpp4+ and Cxcl14+ cells in non-injured muscle•A subset of MuSCs enriched for immune gene expression in regenerating muscle Stem Cells Research; Developmental Biology; Bioinformatics