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Reprogramming of epidermal keratinocytes by PITX1 transforms the cutaneous cellular landscape and promotes wound healing [CUT&Tag]

GSE279042 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 30 samples Submitted 2026/04/27 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 30 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
30 samples: 10 conditions, mostly in triplicateGroups 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
Reprogramming of epidermal keratinocytes by PITX1 transforms the cutaneous cellular landscape and promotes wound healingJCI insight · 2024
Summary (written by the submitters)
Skin injuries heal slowly, compared to oral epithelial tissues, and often do not regenerate lost adnexa. Using a murine mouse model expressing the oral epithelial transcription factor PITX1 in the skin, we performed CUT&Tag-seq analysis in healthy skin to delinate PITX1 and histone occupancies in the skin.
Published in
Reprogramming of epidermal keratinocytes by PITX1 transforms the cutaneous cellular landscape and promotes wound healing
Overmiller AM, Uchiyama A, Hope ED et al. · JCI insight 2024 · PMID 39480496 · doi:10.1172/jci.insight.182844
This dataset
Open GSE279042 in finder → Find more mouse ChIP / ATAC / CUT&Tag 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 GSE279042_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 PRJNA1170234 and SRA study SRP537302. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39480496) ↗
Study design
10 conditions, mostly in triplicate
Control Skin IgG ×3 Control Skin Pitx1 ×3 Control Skin H3K4me3 ×3 Control Skin H3K27ac ×3 Control Skin H3K27me3 ×3 PITX1+ Skin IgG ×3 PITX1+ Skin Pitx1 ×3 PITX1+ Skin H3K4me3 ×3 +2 more

Supports a between-group comparison across 30 samples.

How we read this: 10 replicated groups read from 30 sample titles; they account for 30 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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