Background: The heterogeneity of mesenchymal stem cells (MSCs) is poorly understood, thus limiting clinical application and basic research reproducibility. Advanced single-cell RNA sequencing (scRNA-seq) is a robust tool used to analyse for dissecting cellular heterogeneity. However, the comprehensive single-cell atlas for human MSCs has not been achieved. Methods: This study used massive parallel multiplexing scRNA-seq to construct an atlas of > 130 000 single-MSC transcriptomes across multiple tissues and donors to assess their heterogeneity. The most widely clinically utilised tissue resources for MSCs were collected, including normal bone marrow (n = 3), adipose (n = 3), umbilical cord (n = 2), and dermis (n = 3). Results: Seven tissue-specific and five conserved MSC subpopulations with distinct gene-expression signatures were identified from multiple tissue origins based on the high-quality data, which has not been achieved previously. This study showed that extracellular matrix (ECM) highly contributes to MSC heterogeneity. Notably, tissue-specific MSC subpopulations were substantially heterogeneous on ECM-associated immune regulation, antigen processing/presentation, and senescence, thus promoting inter-donor and intra-tissue heterogeneity. The variable dynamics of ECM-associated genes had discrete trajectory patterns across multiple tissues. Additionally, the conserved and tissue-specific transcriptomic-regulons and protein-protein interactions were identified, potentially representing common or tissue-specific MSC functional roles. Furthermore, the umbilical-cord-specific subpopulation possessed advantages in immunosuppressive properties. Conclusion: In summary, this work provides timely and great insights into MSC heterogeneity at multiple levels. This MSC atlas taxonomy also provides a comprehensive understanding of cellular heterogeneity, thus revealing the potential improvements in MSC-based therapeutic efficacy. Keywords: extracellular matrix; heterogeneity; mesenchymal stem cells; single-cell RNA sequencing.