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Pioneer factors orchestrate tissue-specific cohesin-NIPBL chromatin entry and 3D genome organization [ChIP-seq]

GSE293172 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 68 samples Submitted 2026/05/07 Platform GPL34284Platform GPL34290Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 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
Homo sapiens (human)
Samples
68 samples: 68 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
Pioneer transcription factors direct tissue-specific cohesin chromatin entry and three-dimensional genome organizationNature genetics · 2026
Summary (written by the submitters)
Cohesin complex shapes 3D genome organization by extruding DNA loops, yet the mechanisms underlying its chromatin entry remain poorly understood. Here, we reveal that the cohesin loader NIPBL exhibits highly tissue-specific chromatin binding, in stark contrast to the conserved binding profiles of CTCF and RAD21. We identify pioneer transcription factors (TFs), notably FOXA1, as key mediators of NIPBL recruitment to chromatin.
Read the full summary ↓
FOXA1 directs NIPBL to intra-TAD regions, enabling symmetric loop extrusion, while factors like ETS1 target NIPBL to TAD boundaries, supporting one-sided extrusion. Rapid depletion of FOXA1 disrupts NIPBL binding and intra-TAD loops, whereas loss of NIPBL impairs both intra-TAD and inter-TAD interactions, highlighting their roles in 3D genome folding. Strikingly, a recurrent FOXA1 mutation (R219S) in prostate cancer redirects NIPBL to TAD boundaries by recognizing a non-canonical motif, fostering a more insulated and tumor-aggressive genome. Evolutionary analysis points to a potential conserved role for TF-NIPBL cooperation in cohesin chromatin entry across species with tissue-specific adaptations. Our findings reveal that pioneer factors orchestrate cohesin loading to shape tissue-specific chromatin accessibility and 3D genome dynamics, a mechanism hijacked in diseases like cancer to rewire gene expression.
Published in
Pioneer transcription factors direct tissue-specific cohesin chromatin entry and three-dimensional genome organization
Wang S, Zhang X, Jia T et al. · Nature genetics 2026 · PMID 42463888 · doi:10.1038/s41588-026-02688-7
This dataset
Open GSE293172 in finder → Find more 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 GSE293172_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 PRJNA1243290 and SRA study SRP573850. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42463888) ↗
Study design
68 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 7 samples read as cases, 15 as controls.

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

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