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Transcription Factors Form a Ternary Complex with NIPBL/MAU2 to Localize Cohesin at Enhancers

GSE282583 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2025/04/16 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 24 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Mus musculus (mouse)
Samples
24 samples: 12 conditions, mostly in duplicateGroups 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
Transcription factors form a ternary complex with NIPBL/MAU2 to localize cohesin at enhancersNucleic acids research · 2025
Summary (written by the submitters)
The cohesin complex is a key player in dynamic genome architecture adjustments. The loading of the cohesin complex on chromatin is believed to be achieved by the cohesin-loader Nipped-B homolog (NIPBL). Recently, we and others proposed that direct interactions with transcriptions factors (TFs) would lead to accurate positioning of NIPBL on the DNA.
Read the full summary ↓
In this study, we identified remarkable protein-protein interaction motifs (PPIMs) in the NIPBL sequence. Mutations of those motifs dramatically alters: (i) the global NIPBL chromatin binding, (ii) the NIPBL-dependent transcriptional program and (iii) the NIPBL proteome network including TFs. While we found that the MAU2/NIPBL interaction was relying on those PPIMs, we further discovered that MAU2 was directly interacting with dozens of TFs. Concomitantly, we found that numerous TFs were also able to interact with NIPBL through PPIMs. Finally, using nuclear receptors as models and then focusing on the Glucocorticoid Receptor (GR), we mechanistically dissect a trimeric complex formed by GR, NIPBL and MAU2 and investigate the importance of those interactions for GR transcriptional program.
Published in
Transcription factors form a ternary complex with NIPBL/MAU2 to localize cohesin at enhancers
Fettweis G, Wagh K, Stavreva DA et al. · Nucleic acids research 2025 · PMID 40377219 · doi:10.1093/nar/gkaf415
This dataset
Open GSE282583 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 GSE282583_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1189196 and SRA study SRP546882. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40377219) ↗
Study design
12 conditions, mostly in duplicate
noIPTG.EV.EtOH ×2 IPTG.EV.EtOH ×2 IPTG.WT.EtOH ×2 IPTG.C1.EtOH ×2 IPTG.C2.EtOH ×2 IPTG.C1C2.EtOH ×2 noIPTG.EV.Dex ×2 IPTG.EV.Dex ×2 +4 more

Supports a between-group comparison across 24 samples.

How we read this: 12 replicated groups read from 24 sample titles; they account for 24 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
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