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Widespread impact of nucleosome remodelers on transcription at cis-regulatory elements [TT-seq]

GSE256312 Mus musculus (mouse) RNA-seq (gene expression) 97 samples Submitted 2025/05/08 Platform GPL30172
At a glance

RNA-seq (gene expression) · mouse · 97 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
97 samples: 97 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
Widespread impact of nucleosome remodelers on transcription at cis-regulatory elementsCell reports · 2025
Summary (written by the submitters)
Nucleosome remodeling complexes and other regulatory factors work in concert to build a chromatin environment that directs the expression of a distinct set of genes in each cell using cis-regulatory elements (CREs) such as promoters and enhancers which drive transcription of both mRNAs and CRE-associated non-coding RNAs (ncRNAs). Two classes of CRE-associated ncRNAs include upstream antisense RNAs (uaRNAs), which are transcribed divergently from a shared mRNA promoter element, and enhancer RNAs (eRNAs), which are transcribed bidirectionally from active enhancers.
Read the full summary ↓
The complicated network of CRE regulation by nucleosome remodelers remains only partially explored, with a focus on a select, limited number of remodelers. We endeavored to elucidate a remodeler-based regulatory network governing CRE-associated transcription (mRNA, eRNA, and uaRNA) in murine embryonic stem (ES) cells to test the hypothesis that many SNF2-family nucleosome remodelers collaborate to regulate the coding and non-coding transcriptome. Using depletion followed by transient transcriptome sequencing (TT-seq), we identified thousands of misregulated mRNAs and CRE-associated ncRNAs across the remodelers examined, identifying novel contributions by understudied remodelers in the regulation of coding and non-coding transcription. Our findings suggest that transcription of paired mRNAs and eRNAs are coordinately co-regulated, while mRNAs and uaRNAs sharing a promoter are independently regulated by remodelers. Our mechanistic studies suggest that while SRCAP and CHD8 modulate transcription through classical mechanisms such as transcription factors and histone variants, a broad set of remodelers including SMARCAL1 indirectly contribute to transcription regulation through maintenance of genomic stability and accurate Integrator complex activity. This study systematically examines the contribution of SNF2-remodelers to the CRE-associated transcriptome, identifying at least two classes for remodeler action.
Published in
Widespread impact of nucleosome remodelers on transcription at cis-regulatory elements
Patty BJ, Dhungana R, Hainer SJ · Cell reports 2025 · PMID 40450687 · doi:10.1016/j.celrep.2025.115767
This dataset
Open GSE256312 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 GSE256312_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 PRJNA1078989 and SRA study SRP490899. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40450687) ↗
Study design
97 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 97 sample titles: 97 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

+ 57 more — browse all 97 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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