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Deciphering the heterogeneity of differentiating hPSC-derived corneal limbal stem cells through single-cell RNA-sequencing [Bulk-seq]

GSE248495 Homo sapiens Expression profiling by high throughput sequencing 4 samples Submitted 2024/06/26 Platform GPL18573
Summary
A comprehensive understanding of the human pluripotent stem cell (hPSC) differentiation process stands as a prerequisite for the development hPSC-based therapeutics. In this study, single-cell RNA-sequencing (scRNA-seq) was performed to decipher the heterogeneity during differentiation of three hPSC lines towards corneal limbal stem cells (LSCs). The scRNA-seq data revealed the presence of nine clusters, among which five clusters followed the anticipated differentiation path of LSCs. The remaining four clusters were linked to previously undescribed cell states that were annotated as either mesodermal or undifferentiated subpopulations, and their prevalence was hPSC line-dependent. Distinct cluster-specific marker genes identified in this study were confirmed by immunofluorescence analysis and employed to purify hPSC-derived LSCs, which effectively minimized the variation in the line-dependent differentiation efficiency. In summary, scRNA-seq offered molecular insights into the heterogeneity of hPSC-LSC differentiation, allowing a data-driven strategy to be adopted for consistent and robust generation of LSCs, essential for future advancement toward clinical translation.
Published in
Deciphering the heterogeneity of differentiating hPSC-derived corneal limbal stem cells through single-cell RNA sequencing
Vattulainen M, Smits JGA, Arts JA et al. · Stem cell reports 2024 · PMID 38942029 · doi:10.1016/j.stemcr.2024.06.001
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Direct links to NCBI, no account and no request form: the whole study as GSE248495_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 4 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1044130 and SRA study SRP473767. Searching any of these in the dataset finder brings you back here.

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