GEO series

Developmental origins of fibroblasts determine their scarring potential in wound healing

GSE248850 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 12 samples Submitted 2026/02/12 Platform GPL21103

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 12 samples

What it is: ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism: Mus musculus (mouse)
Samples: 12 samples: 12 samples, each with a distinct title — no replicated groupsGroups 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: Fibroblasts of disparate developmental origins harbor anatomically variant scarring potentialCell · 2026

Summary (written by the submitters)

Fibroblasts are the primary cells responsible for depositing extracellular matrix proteins during wound repair and fibrosis. Progress towards the development of treatments aimed at reducing scars has been hampered by our limited understanding of specific fibroblast populations responsible for fibrotic versus regenerative healing. Using a four-site wounding model in mice, we observed that neural crest-derived facial wounds heal with less scarring than cephalic mesoderm-derived scalp wounds, lateral plate mesoderm-derived ventral wounds, and paraxial mesoderm-derived dorsal wounds.

Read the full summary ↓

Single-cell RNA sequencing identified increased expression of Robo2 and downstream Eid1 in neural-crest derived facial fibroblasts compared to fibroblasts from other sites. Subsequent fibroblast transplantation experiments showed that Robo2 and Eid1 are required for facial fibroblasts’ intrinsic reduced fibrotic potential. This is maintained by the EID1-mediated inhibition of EP300 histone acetyltransferase, leading to a more transcriptionally silent chromatin landscape, including around extracellular matrix genes. Mimicking EID1’s endogenous activity, both small-molecule and transgenic repression of EP300 in dorsal wounds promoted facial-like healing with reduced scarring. Overall, these data highlight the importance of the ROBO2-EID1-EP300 signaling axis in facial wound healing, and demonstrate our ability to modulate the embryologically determined fibrogenic potential of fibroblasts as a therapeutic approach to minimize scar formation.

Published in

Fibroblasts of disparate developmental origins harbor anatomically variant scarring potential

Griffin MF, Li DJ, Chen K et al. · Cell 2026 · PMID 41576949 · doi:10.1016/j.cell.2025.12.014

This dataset

Open GSE248850 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 GSE248850_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1046108 and SRA study SRP474720. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41576949) ↗

Study design

12 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 12 sample titles: 12 distinct titles with little repetition. 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

GSM7921294 RNA FUW
GSM7921295 RNA FW PBS
GSM7921296 RNA FW EP300i
GSM7921297 RNA DUW
GSM7921298 RNA DW PBS
GSM7921299 RNA DW EP300i
GSM7921300 ATAC FUW
GSM7921301 ATAC FW PBS
GSM7921302 ATAC FW EP300i
GSM7921303 ATAC DUW
GSM7921304 ATAC DW PBS
GSM7921305 ATAC DW EP300i

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.