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Pivotal Role of the NuRD Complex in Remodeling Chromatin Environment and Maintaining Genome Architecture at CTCF Sites [mESC_d0246_DMSO_BPK25_IAA_RNA_Seq]

GSE253693 Mus musculus (mouse) RNA-seq (gene expression) 36 samples Submitted 2026/05/04 Platform GPL30215
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: 12 conditions, mostly in triplicateGroups 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
NuRD-enabled CTCF-TET crosstalk orchestrates epigenome reprogramming and genome architectureMolecular cell · 2026
Summary (written by the submitters)
CCCTC-binding factor (CTCF) is an evolutionarily conserved transcription factor with diverse regulatory roles. Around stable CTCF binding sites, nucleosomes are highly ordered and DNA methylation is reduced, yet the mechanisms establishing and maintaining this epigenetic environment remain unclear. Utilizing an innovative eBioID method, we identified that virtually all subunits of the nucleosome remodeling and deacetylase (NuRD) complex are associated with CTCF in cells.
Read the full summary ↓
Further analyses revealed that the NuRD complex is necessary for the chromatin binding of CTCF, and emerges as a novel regulator of the genome architecture. Additionally, we discovered that MBD3-NuRD facilitates the recruitment of TET demethylases to CTCF sites, initiating local DNA demethylation essential for the activation of adjacent gene expression. Embryonic stem cells deficient in the NuRD complex showed impaired lineage commitment. In summary, this study elucidates a mechanism illustrating the interplay between CTCF binding and the epigenome including 3D genome organization and DNA methylation, with the NuRD complex serving as an indispensable mediator.
Published in
NuRD-enabled CTCF-TET crosstalk orchestrates epigenome reprogramming and genome architecture
Sun W, Wu N, Xia M et al. · Molecular cell 2026 · PMID 42225060 · doi:10.1016/j.molcel.2026.05.010
This dataset
Open GSE253693 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 GSE253693_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 PRJNA1066783 and SRA study SRP484808. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42225060) ↗
Study design
12 conditions, mostly in triplicate
mESC_d0_BPK25 ×3 mESC_d0_DMSO ×3 mESC_d0_IAA ×3 mESC_d2_BPK25 ×3 mESC_d2_DMSO ×3 mESC_d2_IAA ×3 mESC_d4_BPK25 ×3 mESC_d4_DMSO ×3 +4 more

Supports a between-group comparison across 36 samples.

How we read this: 12 replicated groups read from 36 sample titles; they account for 36 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
Datasets on a similar topic

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