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H2AK119ub1-MLL2 counteraction underlies heritable H3K27me3 formation in oocytes

GSE292237 Mus musculus (mouse) RNA-seq (gene expression) 43 samples Submitted 2026/04/01 Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 43 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
43 samples: 8 conditions, mostly with about 10 replicates eachGroups 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
H2AK119ub1-MLL2 counteraction underlies heritable H3K27me3 formation in oocytesMolecular cell · 2026
Summary (written by the submitters)
Polycomb group (PcG) and Trithorax group (TrxG) proteins establish bivalent chromatin marked by H3K27me3, H2AK119ub1, and H3K4me3. However, how bivalent chromatin is formed in vivo in mammals is poorly understood. In mouse oocytes, it arises at thousands of promoters, including noncanonical imprinted loci whose H3K27me3 is intergenerationally inherited by early embryos.
Read the full summary ↓
Here, we show that H3K27me3 is deposited at H3K4me3-premarked promoters in an H2AK119ub1-dependent manner during oogenesis. We find that H2AK119ub1 deficiency causes transcriptional derepression and loss of H3K27me3 proportional to preexisting H3K4me3 levels in oocytes. Importantly, concomitant deficiency of H2AK119ub1 and MLL2-mediated H3K4me3 substantially restores transcriptional silencing and H3K27me3 deposition, leading to partial restoration of noncanonical imprinting in offspring. Taken together, we propose that H2AK119ub1 antagonizes MLL2 function to repress bivalent genes during oogenesis, thereby conferring heritable H3K27me3. This study reveals how PcG and TrxG counteraction shapes the maternal epigenome for the next generation’s development.
Published in
H2AK119ub1-MLL2 counteraction underlies heritable H3K27me3 formation in oocytes
Mei H, Kozuka C, Kumon M et al. · Molecular cell 2026 · PMID 41980776 · doi:10.1016/j.molcel.2026.03.014
This dataset
Open GSE292237 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 GSE292237_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 PRJNA1237709 and SRA study SRP571264. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41980776) ↗
Study design
8 conditions, mostly with about 10 replicates each
P1P6MLL_WT_morula_embryos ×10 P1P6MLL_matDKO_morula_embryos ×10 P1P6MLL_matTKO_morula_embryos ×10 P1P6MLL_WT_FGO ×3 P1P6MLL_DKO_FGO ×3 P1P6MLL_TKO_FGO ×3 PRC1-WT_FGO ×2 PRC1-CD_FGO ×2

Supports a between-group comparison across 43 samples.

How we read this: 8 replicated groups read from 43 sample titles; they account for 43 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

+ 3 more — browse all 43 samples with per-sample file links →

Datasets on a similar topic

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