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Self-Renewing Presomitic Mesoderm Progenitor Lines Reprogrammed from human urine cells [induced cell type bulk RNA-seq]

GSE185135 Homo sapiens Expression profiling by high throughput sequencing 6 samples Submitted 2024/07/26 Platform GPL24676
Summary
Vertebrae formation is the defining feature of all vertebrates1,2. Yet, each vertebrate species appears to have a unique timing mechanism for forming somites along the vertebral column3-5. Human vertebrate formation remains poorly studied due to technical and ethical limitations. Here we report the generation of self-renewing stem cells with characteristic presomitic mesoderm (PSM) features by reprogramming epithelial cells isolated from human urine. These induced expandable presomitic mesoderm progenitor cells (UiPSM) proliferated extensively for more than 30 passages in chemically defined conditions, robustly producing 1040 UiPSM cells. UiPSM established presomitic mesodermal transcription profile, not detected pluripotency, ectoderm and endoderm related genes. UiPSM developed into presomitic mesodermal lineage cells, such as skeletal muscle cells(skm), osteoblast and chrondroblast cells in vivo and vitro, when transplanted UiPSM derived human skm cells in muscle injury model, the skm cells can survive in vivo and contribute to muscle regeneration up to one month. Thus, UiPSM is a powerful system to study human somite development and provide strategies for regenerative medicine in musculoskeletal system
Published in
Generation of musculoskeletal cells from human urine epithelium-derived presomitic mesoderm cells
Gao H, Huang X, Cai Z et al. · Cell & bioscience 2024 · PMID 39010176 · doi:10.1186/s13578-024-01274-w
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Direct links to NCBI, no account and no request form: the whole study as GSE185135_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 6 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA767708 and SRA study SRP339586. Searching any of these in the dataset finder brings you back here.

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