A reference single-cell transcriptomic atlas of human skeletal muscle tissue reveals bifurcated muscle stem cell populations

Abstract

Single-cell RNA-sequencing (scRNA-seq) facilitates the unbiased reconstruction of multicellular tissue systems in health and disease. Here, we present a curated scRNA-seq dataset of human muscle samples from 10 adult donors with diverse anatomical locations. We integrated ~ 22,000 single-cell transcriptomes using Scanorama to account for technical and biological variation and resolved 16 distinct populations of muscle-resident cells using unsupervised clustering of the data compendium. These cell populations included muscle stem/progenitor cells (MuSCs), which bifurcated into discrete "quiescent" and "early-activated" MuSC subpopulations. Differential expression analysis identified transcriptional profiles altered in the activated MuSCs including genes associated with aging, obesity, diabetes, and impaired muscle regeneration, as well as long non-coding RNAs previously undescribed in human myogenic cells. Further, we modeled ligand-receptor cell-communication interactions and observed enrichment of the TWEAK-FN14 pathway in activated MuSCs, a characteristic signature of muscle wasting diseases. In contrast, the quiescent MuSCs have enhanced expression of the EGFR receptor, a recognized human MuSC marker. This work provides a new benchmark reference resource to examine human muscle tissue heterogeneity and identify potential targets in MuSC diversity and dysregulation in disease contexts.

Fig. 1

Single-cell transcriptomic map of human muscle tissue biopsies. a Metadata (sex, age, anatomical site, and the number of single-cell transcriptomes after quality control (QC) filtering) from n = 10 donors. Colors indicate sample anatomical sites. b Scanorama-integrated and batch-effect corrected transcriptomic atlas revealing a consensus description of 16 distinct muscle-tissue cell populations. c Transcriptomic atlas colored by donor and anatomical location. d Dot-plot showing differentially expressed genes that distinguish the cell populations. Grouped in four compartments: muscle, endothelial/vascular, stromal, and immune. e Cell type proportions as annotated in (b) across the 10 donors and grouped by body sections. L, leg (donors 02, 07, 08); T, trunk (donors 01, 05, 06, 09, 10); F, face (donors 03, 04)

Fig. 2

Gene expression and pathway analysis comparison between two MuSC subpopulations. a Volcano plot from comparing transcript levels between all cells within the “MuSC1” and “MuSC2” subpopulations. Log₂ fold-change in normalized gene expression versus −log₁₀ adjusted p value plotted. Differentially expressed genes (adjusted p value <0.05) are colored dark or light blue (based on their enrichment in MuSC1 or MuSC2, respectively). Genes with log₂ fold-change > 0.75 are labeled. b Normalized expression values of select differentially expressed genes. q values reported in inset. c Top activated canonical pathways by Ingenuity Pathway Analysis (IPA) based on differentially expressed genes and ranked by p value. Pathways significantly enriched in either population with |z score| > 1 are indicated in blue. d Select gene ontology (GO) terms and hallmark pathways enriched between the MuSC subpopulations as identified by gene set enrichment analysis (GSEA) and ranked by enrichment score (ES)

Fig. 3

Differentially expressed receptors and ligand-receptor interaction between cell populations. a Chord plot of all ligand-receptor (LR) interactions across cell populations/types within the consensus atlas based on co-expression. Each cell type is color-coded with its receptor genes more displaced from the perimeter than its ligand genes. All interactions not involving MuSC1 or MuSC2 are presented in gray. b List of differentially expressed genes between the MuSC1 and MuSC2 subpopulation ranked by log₂ fold-change in expression. Positive average values correspond to genes that are upregulated in MuSC1, whereas negative values are upregulated in MuSC2. Receptors that are statistically significant (FDR-corrected q value < 0.05) are colored in blue. Receptors that are not statistically significant are in gray. c Heatmap representing row-normalized (Z-score) LR interaction scores. Rows represent ligand-receptor interaction pairs in the format LIGAND_RECEPTOR, where the receptor is either differentially expressed in the MuSC1 or MuSC2 populations compared to all the other cell types. Columns identify cell types expressing the ligand. Asterisks after the pair name also indicate that the ligand is differentially expressed by the other cell type and that interaction is likely cell-type specific. Red pairs involve the EGFR receptor, purple pairs the NOTCH3 receptor. A positive value indicates that the interaction has a high score for a particular ligand and cell type compared to other cell types