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Multimodal profiling reveals a Notch-responsive regenerative subpopulation of cochlear supporting cells [1]

GSE310785 Mus musculus Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing 8 samples Submitted 2026/04/30 Platform GPL34290
Summary
Regeneration enables organisms to repair damaged tissues, yet this capacity is strikingly limited in the cochlear sensory epithelium, essential for sound detection. A major cause of hearing loss arises from the irreversible loss of sensory hair cells (HCs) in the cochlea. While supporting cells (SCs) have a latent ability to trans-differentiate into HCs, this regenerative potential is rapidly lost after development. Using live imaging and single-cell multiomics of cochlear explants, we uncovered the cellular and molecular heterogeneity underlying the limited regenerative capacity of the neonatal mouse cochlea. Notch repression broadly silenced key SC genes, yet only a rare subpopulation of Deiters cells (DC), termed responsive DCs, initiated the trans-differentiation into HC fate. These cells underwent coordinated transcriptional and enhancer remodeling, linking epigenetic priming with morphological plasticity, while other SCs remained refractory despite robust Notch targets downregulation. Our study provides a molecular definition of a fate-primed SC state, revealing Notch inhibition as a selective trigger that unmasks rare regenerative competence.
Published in
Live imaging and multimodal profiling reveal transdifferentiation of a cochlear supporting cell subpopulation upon Notch inhibition
Khalaily L, Kasirer S, Domb R et al. · Science advances 2026 · PMID 42308318 · doi:10.1126/sciadv.aed3887
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Direct links to NCBI, no account and no request form: the whole study as GSE310785_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 8 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1367073 and SRA study SRP647323. Searching any of these in the dataset finder brings you back here.

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