Muhammad Farooq Rai1, Chia-Lung Wu2, Terence D Capellini3, Farshid Guilak2, Amanda R Dicks2, Pushpanathan Muthuirulan3, Fiorella Grandi4, Nidhi Bhutani4, Jennifer J Westendorf5. 1. Department of Orthopaedic Surgery, Washington University, St. Louis, MO, USA. 2. Department of Orthopaedic Surgery, Washington University and Shriners Hospitals for Children, St. Louis, MO, USA. 3. Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA. 4. Department of Orthopedic Surgery, Stanford University, Stanford, CA, USA. 5. Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA. westendorf.jennifer@mayo.edu.
Abstract
PURPOSE OF REVIEW: The ability to analyze the molecular events occurring within individual cells as opposed to populations of cells is revolutionizing our understanding of musculoskeletal tissue development and disease. Single cell studies have the great potential of identifying cellular subpopulations that work in a synchronized fashion to regenerate and repair damaged tissues during normal homeostasis. In addition, such studies can elucidate how these processes break down in disease as well as identify cellular subpopulations that drive the disease. This review highlights three emerging technologies: single cell RNA sequencing (scRNA-seq), Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq), and Cytometry by Time-Of-Flight (CyTOF) mass cytometry. RECENT FINDINGS: Technological and bioinformatic tools to analyze the transcriptome, epigenome, and proteome at the individual cell level have advanced rapidly making data collection relatively easy; however, understanding how to access and interpret the data remains a challenge for many scientists. It is, therefore, of paramount significance to educate the musculoskeletal community on how single cell technologies can be used to answer research questions and advance translation. This article summarizes talks given during a workshop on "Single Cell Omics" at the 2020 annual meeting of the Orthopedic Research Society. Studies that applied scRNA-seq, ATAC-seq, and CyTOF mass cytometry to cartilage development and osteoarthritis are reviewed. This body of work shows how these cutting-edge tools can advance our understanding of the cellular heterogeneity and trajectories of lineage specification during development and disease.
PURPOSE OF REVIEW: The ability to analyze the molecular events occurring within individual cells as opposed to populations of cells is revolutionizing our understanding of musculoskeletal tissue development and disease. Single cell studies have the great potential of identifying cellular subpopulations that work in a synchronized fashion to regenerate and repair damaged tissues during normal homeostasis. In addition, such studies can elucidate how these processes break down in disease as well as identify cellular subpopulations that drive the disease. This review highlights three emerging technologies: single cell RNA sequencing (scRNA-seq), Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq), and Cytometry by Time-Of-Flight (CyTOF) mass cytometry. RECENT FINDINGS: Technological and bioinformatic tools to analyze the transcriptome, epigenome, and proteome at the individual cell level have advanced rapidly making data collection relatively easy; however, understanding how to access and interpret the data remains a challenge for many scientists. It is, therefore, of paramount significance to educate the musculoskeletal community on how single cell technologies can be used to answer research questions and advance translation. This article summarizes talks given during a workshop on "Single Cell Omics" at the 2020 annual meeting of the Orthopedic Research Society. Studies that applied scRNA-seq, ATAC-seq, and CyTOF mass cytometry to cartilage development and osteoarthritis are reviewed. This body of work shows how these cutting-edge tools can advance our understanding of the cellular heterogeneity and trajectories of lineage specification during development and disease.
Entities:
Keywords:
ATAC-seq; Cartilage; CyTOF; Osteoarthritis; Single cell RNA-seq
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