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H3K79 methylation and H3K36 trimethylation synergistically regulate gene expression in pluripotent stem cells [ChIP-Seq]

GSE292287 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 42 samples Submitted 2025/07/04 Platform GPL34328
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 42 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
Mus musculus (mouse)
Samples
42 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
H3K79 methylation and H3K36 trimethylation synergistically regulate gene expression in pluripotent stem cellsScience advances · 2025
Summary (written by the submitters)
In metazoans, nucleosomes harboring H3K79 methylation (H3K79me) deposited by the histone methyltransferase DOT1L decorate actively transcribed genes. Although DOT1L is implicated in transcription regulation and pathogenesis of human diseases such as leukemia and neurological disorders, the role of H3K79me in these biological processes remains elusive.
Read the full summary ↓
Here, we reveal a novel functional synergism between H3K79me and H3K36 tri-methylation (H3K36me3), another histone modification enriched at active genes, in regulating gene expression and neural cell fate transition. Simultaneous catalytic inactivation of DOT1L and the H3K36 methyltransferase SETD2 via gene editing leads to the global loss of H3K79me and H3K36me3, hyperactive transcription, and failures in neural differentiation. Interestingly, the loss of H3K79me and H3K36me3 causes increased transcription elongation, gained chromatin accessibility at a group of enhancers, and increased binding of TEAD4 transcription factor and its co-activator YAP1 at these enhancers. Furthermore, YAP-TEAD inhibition partially restores the expression levels of hyperactivated genes upon H3K79me/H3K36me3 loss. Taken together, our study demonstrates a synergistic role of H3K79me and H3K36me3 in regulating transcription and cell fate transition, unveils novel mechanisms underlying such synergism, and provides insight into designing therapies that target diseases driven by misregulation or mutations of DOT1L and/or SETD2.
Published in
H3K79 methylation and H3K36 trimethylation synergistically regulate gene expression in pluripotent stem cells
Cooke EW, Zeng C, Nur SM et al. · Science advances 2025 · PMID 40614207 · doi:10.1126/sciadv.adt8765
This dataset
Open GSE292287 in finder → Find more mouse 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 GSE292287_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 PRJNA1237827 and SRA study SRP571388. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40614207) ↗
Study design
12 conditions, mostly in duplicate
WT_H3K79me ×3 SETD2CI_H3K79me ×3 DOT1LCI_H3K79me ×3 DCI_H3K79me ×3 WT_input ×2 WT_RNAPII ×2 DOT1LCI_input ×2 SETD2CI_input ×2 +18 more

Supports a between-group comparison across 28 samples.

How we read this: 12 replicated groups read from 42 sample titles; they account for 28 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

+ 2 more — browse all 42 samples with per-sample file links →

Datasets on a similar topic

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