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Cohesin acts as a transcriptional gatekeeper by restraining pause–release to promote processive elongation

GSE336388 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 15 samples Submitted 2026/07/07 Platform GPL30882
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 15 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
Homo sapiens (human)
Samples
15 samples: 15 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.
Summary (written by the submitters)
Cohesin organizes 3D chromatin architecture, including promoter–enhancer loops, yet its loss has surprisingly modest effects on steady-state gene expression. We address this paradox by demonstrating that cohesin acts at different stages of transcription. First, it promotes Pol II promoter recruitment by facilitating enhancer–promoter communication that maintains active promoter chromatin states.
Read the full summary ↓
Second, it delays pause release by transiently associating with the transcriptional machinery during the pause–release transition. Kinetic modelling suggests that reduced Pol II recruitment and enhanced pause release have compensatory effects, contributing to minimal changes in steady-state gene expression across genes upon cohesin loss. In contrast, cohesin depletion impairs robust transcriptional induction in response to external stimuli. Moreover, cohesin ensures sufficient pausing duration as a quality-control-like step to promote elongation complex assembly and transcription processivity. Here, we show that cohesin regulates multiple steps of transcription, offering mechanistic insight into cohesin-related diseases, including cancers and cohesinopathies.
This dataset
Open GSE336388 in finder → Find more human 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 GSE336388_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 PRJNA1481507 and SRA study SRP712181. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
15 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 15 sample titles: 15 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
Datasets on a similar topic

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