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SUMOylation enhances DNMT1 function to repress mega-intergenic RNAs and viral mimicry [ChIP_gUHRF1-and-WT-vs-RFTS]

GSE329304 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 13 samples Submitted 2026/05/17 Platform GPL30173
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 13 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
13 samples: 12 distinct titles, 1 of them repeatedGroups 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.
Summary (written by the submitters)
DNA methyltransferase 1 (DNMT1) is essential for mammalian development and is frequently dysregulated in cancer. While its recruitment to hemi-methylated DNA by UHRF1 is well established, its broader chromatin occupancy and regulation remain unclear. We show that DNMT1 is enriched at unmethylated CpG islands of actively transcribed genes largely by its CXXC domain.
Read the full summary ↓
Upon selective catalytic inhibition, DNMT1 redistributes to partially methylated, inaccessible regions in a UHRF1- and RFTS-dependent manner. Despite minimal changes in coding gene expression, sustained DNMT1 inhibition and subsequent global DNA hypomethylation trigger reactivation of a previously uncharacterised class of dsRNA mega-intergenic transcripts (mintRNAs) driving a cell-intrinsic viral mimicry response. We identify RNF4 as a major regulator of DNMT1 catalytic function that, beyond its canonical role in DNA–protein crosslink resolution, controls the levels of SUMOylated DNMT1, establishing SUMOylation as a rheostat that regulates DNMT1 activity to maintain DNA methylation and safeguard against viral mimicry.
This dataset
Open GSE329304 in finder → Find more human 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 GSE329304_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 PRJNA1458614 and SRA study SRP695537. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 distinct titles, 1 of them repeated
MV411, gDNMT1, ectopic overexpression of GFP-… ×2

Supports a case/control comparison: 2 samples read as cases, 2 as controls.

How we read this: Read from 13 sample titles: 12 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
Datasets on a similar topic

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.