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Ageing-induced cell type-specific transcriptomic changes in the skin are associated with abnormal early healing responses to injury

GSE267091 Mus musculus (mouse) Single-cell RNA-seq 23 samples Submitted 2025/12/03 Platform GPL21103
At a glance

Single-cell RNA-seq · mouse · 23 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
23 samples: 10 conditions, mostly in duplicateGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Intrinsic changes in cell differentiation and identity drive impaired wound healing in aged female murine skinBiogerontology · 2025
Summary (written by the submitters)
The progression of wound healing is delayed in aged skin. Previous studies have demonstrated that early healing responses are the most impacted upon ageing. However, cellular changes that drive a perturbed wound microenvironment have not been fully defined. To glean a comprehensive understanding of cell-intrinsic changes that are acquired during ageing and may perhaps impact early responses to wounds, we performed single-cell RNA sequencing of 78670 cells from young and aged C57BL6/J wild-type mouse skin and Day 3 wounds.
Read the full summary ↓
Our data underscore substantial changes in the mean proportional distribution and transcriptomic state of skin resident subpopulations in aged but not young tissues. We found that in comparison to young skin, aged skin was characterised by a global increase in basal inflammation sustained by an altered signalling environment driven by impaired keratinocyte differentiation, loss of fibroblast identity and defective macrophage function. Further, we showed that acquired changes in aged skin resident cells persisted after injury resulting in impaired and exacerbated inflammatory responses.
Published in
Intrinsic changes in cell differentiation and identity drive impaired wound healing in aged female murine skin
Dube CT, Oguz G, Ong YHB et al. · Biogerontology 2025 · PMID 41175301 · doi:10.1007/s10522-025-10340-w
This dataset
Open GSE267091 in finder → Find more mouse RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE267091_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1109743 and SRA study SRP506735. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41175301) ↗
Study design
10 conditions, mostly in duplicate
YI-M ×3 AI-M4 ×2 AI-M6 ×2 AI-M2 ×2 AW-M4 ×2 AW-M6 ×2 AW-M2 ×2 YW-M1 ×2 +4 more

Supports a between-group comparison across 21 samples.

How we read this: 10 replicated groups read from 23 sample titles; they account for 21 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
Datasets on a similar topic

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