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Aged Differentiated Cells Reverse into Native Stemness-Like State by Niche Cytokines to Sustain Lifelong Homeostasis and Tissue Repair

GSE303805 Mus musculus Expression profiling by high throughput sequencing 5 samples Submitted 2026/03/12 Platform GPL30172
Summary
To study the molecular mechanisms driving dedifferentiation and stem cell plasticity during tissue regeneration, we performed single-cell RNA sequencing at multiple time points-Day 2, Day 5, Day 10, and Day 40,following complete ablation of the limbal stem cell (LSC) population. The primary goal was to characterize the transcriptional reprogramming processes that enable differentiated epithelial cells to reacquire stem cell-like properties and restore the LSC pool. Specifically, we aimed to determine (1) the extent to which dedifferentiated cells recapture native stem cell phenotypes, (2) whether this plasticity is maintained in late differentiated and aged cells, and (3) the niche signals that regulate this process. Our data reveal that differentiated cells undergo extensive transcriptional remodeling, becoming virtually indistinguishable from native LSCs, and functionally sustain long-term tissue homeostasis and repair after repeated injury. Remarkably, this plasticity is retained even in late differentiated and aged cells. Mechanistically, we identify macrophage-derived cytokines as key niche factors promoting dedifferentiation and stemness reacquisition. This dataset provides a comprehensive transcriptional resource of corneal regeneration, offering insights into stem cell plasticity and immune-niche interactions with implications for regenerative medicine and limbal stem cell deficiency therapies.
Published in
Aged differentiated cells reverse into native stemness-like state by niche cytokines to sustain lifelong homeostasis and tissue repair
Dimri-Wagh S, Bhattacharya S, Yassen G et al. · Nature communications 2026 · PMID 42034629 · doi:10.1038/s41467-026-72331-w
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Also filed as BioProject PRJNA1297714 and SRA study SRP604028. Searching any of these in the dataset finder brings you back here.

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