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H3K9 di-methylation dynamics underlies mouse minor zygotic genome activation [spike-in ChIP-seq of mESC]

GSE297574 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 64 samples Submitted 2026/04/19 Platform GPL34290
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 64 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
64 samples: 24 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
Dynamic regulation of H3K9 dimethylation drives mouse minor zygotic genome activationNature structural & molecular biology · 2026
Summary (written by the submitters)
Minor zygotic genome activation (ZGA) is crucial for early development and totipotency acquisition, yet the regulatory mechanisms driving minor ZGA genes remain elusive. Here we show that dynamic regulation of H3K9me2 is essential for minor ZGA. H3K9me2 levels at minor ZGA gene loci are reduced at early 2-cell and are re-established by morula.
Read the full summary ↓
Maternal depletion of the H3K9 demethylases KDM3A and KDM3B leads to increased H3K9me2 and impaired minor ZGA in early 2-cell, followed by developmental arrest at 2- to 4-cell. In mESCs, H3K9 at minor ZGA loci is highly di-methylated; combined loss of the H3K9 methyltransferases G9a and SETDB1 leads to synergistic de-repression of minor ZGA genes. Mechanistically, SETDB1 specifically targets Dux, while G9a broadly represses minor ZGA genes through H3K9 di-methylation linked to lamina-associated heterochromatin formation. These findings establish H3K9me2 dynamics as a key regulator for minor ZGA, highlighting the indispensable role of epigenetic control in early embryogenesis.
Published in
Dynamic regulation of H3K9 dimethylation drives mouse minor zygotic genome activation
Maeda R, Kuroki S, Shimojo H et al. · Nature structural & molecular biology 2026 · PMID 42191875 · doi:10.1038/s41594-026-01811-w
This dataset
Open GSE297574 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 GSE297574_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 PRJNA1265210 and SRA study SRP586419. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42191875) ↗
Study design
24 conditions, mostly in triplicate
mESC_33-6_NT_control_H3K9me2_spike-in_lot ×3 mESC_33-6_NT_control_Input_spike-in_lot ×3 mESC_33-6_OHT_Setdb1-KO_H3K9me2_spike-in_lot ×3 mESC_33-6_OHT_Setdb1-KO_Input_spike-in_lot ×3 mESC_SG_NT_G9a-KO_H3K9me2_spike-in_lot ×3 mESC_SG_NT_G9a-KO_Input_spike-in_lot ×3 mESC_SG_OHT_G9a;Setdb1-DKO_H3K9me2_spike-in_l… ×3 mESC_SG_OHT_G9a;Setdb1-DKO_Input_spike-in_lot ×3 +16 more

Supports a between-group comparison across 64 samples.

How we read this: 24 replicated groups read from 64 sample titles; they account for 64 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

+ 24 more — browse all 64 samples with per-sample file links →

Datasets on a similar topic

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