GEO series

Teamwork of clustered low-affinity κB sites and accessory factors regulates transcriptional strength of NF-κB RelA dimers [RNA-seq]

GSE287360 Mus musculus (mouse) RNA-seq (gene expression) 36 samples Submitted 2025/01/22 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 36 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: 36 samples
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: Teamwork of clustered low-affinity κB sites and accessory factors regulates transcriptional strength of NF-κB RelA dimersNucleic acids research · 2025

Summary (written by the submitters)

Non-consensus binding sites of transcription factors are often observed within the promoters and enhancers of various genes; however, their effect on transcriptional strength is unclear. Within the promoters and enhancers of NF-κB-responsive genes, we identified clusters of non-consensus κB DNA sites, many exhibiting low affinity for NF-κB in vitro.

Read the full summary ↓

Deletion of these sites demonstrated their collective critical role in transcription. We explored how these “weak” κB sites exert their influence, especially given the typically low nuclear concentration of NF-κB. Using proteomics approaches, we identified additional nuclear factors, including other DNA-binding TFs, that could interact with κB site-bound NF-κB RelA without binding to DNA directly. ChIP-seq and RNA-seq analyses suggest that these accessory TFs, referred to as the cofactors of NF-κB, facilitate dynamic recruitment of NF-κB to the clustered κB sites. Overall, the occupancy of NF-κB at promoters and enhancers appears to be defined by a collective contribution from all κB sites, both weak and strong, in association with specific cofactors. This congregation of multiple factors within dynamic transcriptional complexes is likely a common feature of transcriptional programs.

Published in

Teamwork of clustered low-affinity κB sites and accessory factors regulates transcriptional strength of NF-κB RelA dimers

Shahabi S, Biswas T, Shen Y et al. · Nucleic acids research 2025 · PMID 41063342 · doi:10.1093/nar/gkaf846

This dataset

Open GSE287360 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 GSE287360_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 PRJNA1212211 and SRA study SRP558141. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41063342) ↗

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 36 more — browse all 36 samples with per-sample file links →

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