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Comparative single-cell multiomic analysis reveals evolutionarily conserved and species-specific cellular mechanisms mediating natural retinal aging

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NIAID Data Ecosystem2026-05-02 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE307031
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We performed integrated single-cell RNA- and ATAC-Seq analyses of the retina and retinal pigment epithelium (RPE) across the natural lifespan in zebrafish, mice, and humans. By profiling gene expression and chromatin accessibility, we identified extensive cell type- and species-specific aging-dependent changes, with a much smaller number of broadly expressed and conserved genes that include regulators of inflammation and autophagy. We constructed predictive aging clocks for retinal cell types and observed dynamic, reversible shifts in cellular age following acute injury. Spatial transcriptomic analysis revealed region-specific aging signatures and proximity effects, with Müller glia exhibiting pro-rejuvenative influences on neighboring neurons. Targeted Müller glia-specific induction of Yamanaka factors reduced molecular age in rod photoreceptors and bipolar cells without altering glial age. Our findings define conserved and divergent regulatory and signaling pathways mediating retinal aging, highlighting Müller glia as potential therapeutic targets for combating age-associated retinal degeneration. we generated mouse datasets by the Xenium 5k platform to analyze aging-dependent gene expression changes in the mouse retina in situ. This retina dataset consists of 4 ages of retina samples, at 5, 12, 55, and 112 weeks, and each age contains two sections (center and peripheral) from one male and one female. We directly tested whether constitutive, low level, Muller glia-specific expression of these factors resulted in rejuvenation of any retinal cell types, using the Muller glia-specific inducible Cre line GlastCreER 65 in conjunction with Cre-inducible rtTA and doxycycline-inducible Oct4, Sox2, Klf4, and mCherry. Doxycycline-treated retinas were analyzed using Xenium 5K spatial transcriptomics.
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2025-09-05
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