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Disentangling the architectural and non-architectural functions of CTCF and cohesin in global gene regulation

GSE262521 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 68 samples Submitted 2025/08/27 Platform GPL30172
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 68 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
68 samples: 60 distinct titles, 8 of them repeatedGroups 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
Disentangling the architectural and non-architectural functions of CTCF and cohesin in gene regulationNature genetics · 2025
Summary (written by the submitters)
Cohesin- and CTCF-mediated chromatin loops shape enhancer-promoter interactions, but their global impact on gene regulation remains unclear. We show that cohesin and CTCF regulate hundreds of genes in mouse cells, though the magnitude of expression changes is modest. Acute loss of cohesin loops mainly downregulates CBP/p300-dependent enhancer targets, while CTCF depletion can both up- and downregulate putative enhancer targets.
Read the full summary ↓
Interestingly, beyond regulating enhancer-dependent transcription via loop anchoring, CTCF acts as a transcriptional activator or repressor of sense and antisense transcripts, depending on its binding position and orientation in promoters. Mechanistically, promoter-bound CTCF enhances DNA accessibility and RNA polymerase II recruitment, thereby activating housekeeping genes essential for mammalian cell proliferation. CTCF’s transcriptional activation function—but not its loop-anchoring role—is shared with its vertebrate-specific paralog, CTCFL. These findings resolve cohesin and CTCF’s roles in global gene regulation, offering a unified model that integrates their enhancer-dependent and -independent functions in transcription control.
Published in
Disentangling the architectural and non-architectural functions of CTCF and cohesin in gene regulation
Narita T, Kilic S, Higashijima Y et al. · Nature genetics 2025 · PMID 41254162 · doi:10.1038/s41588-025-02404-x
This dataset
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.

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 GSE262521_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1092101 and SRA study SRP497965. Searching any of these in the dataset finder brings you back here.

Study design
60 distinct titles, 8 of them repeated
ATAC-seq on GFP-dTAG-Ctcf ESC, control, ×2 ATAC-seq on GFP-dTAG-Ctcf ESC, dTAG13 100nM … ×2 Pol II ChIP-seq on GFP-dTAG-Ctcf ESC, control, ×2 Pol II ChIP-seq on GFP-dTAG-Ctcf ESC, dTAG13… ×2 Stranded EU-seq of bTAG-ΔN-CTCF/dTAG-CTCF-ΔC … ×2 Stranded EU-seq of bTAG-ΔN-CTCF/dTAG-CTCF-ΔC … ×2 Stranded EU-seq of bTAG-ΔN-CTCF/dTAG-CTCF-ΔC … ×2 Stranded EU-seq of bTAG-ΔN-CTCF/dTAG-CTCF-ΔC … ×2

Supports a case/control comparison: 30 samples read as cases, 26 as controls.

How we read this: Read from 68 sample titles: 60 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

+ 28 more — browse all 68 samples with per-sample file links →

Datasets on a similar topic

Search all mouse ChIP / ATAC / CUT&Tag datasets in GEO →

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