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EZHIP-mediated PRC2 inhibition is required to maintain H3K27me3-dependent imprinting post fertilization [ChIP-Seq]

GSE278811 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 77 samples Submitted 2025/11/18 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 77 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
77 samples: 8 conditions, mostly with about 9 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.
Summary (written by the submitters)
Zygote inherits parental genomes with distinct chromatin structure. In eutherian mammals, this asymmetry is seen as crucial for embryonic development notably through its involvement in gene imprinting. Besides the well-established role of DNA methylation for gene imprinting, H3K27me3 has also been shown to mediate a transient form of imprinting in mice.
Read the full summary ↓
Here, we show that maternal deletion of Ezhip, a negative regulator of PRC2, while increasing the asymmetric distribution of H3K27me3 among the parental genomes at the zygotic stage, in fine, impairs H3K27me3-dependent imprinting and mitigates X Chromosome Inactivation in pre-implantation embryos. We show that EZHIP protein, translated from the maternal pool of RNAs, is present during the first cell divisions post-fertilization. It limits PRC2 enzymatic, avoiding the flattening of H3K27me3 deposition throughout the genome and the equalization of H3K27me3 deposition on the two parental genomes. Our study reveals the necessary inhibition of PRC2 activity post-fertilization for proper development in mice.
This dataset
Open GSE278811 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 GSE278811_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 PRJNA1168963 and SRA study SRP536636. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly with about 9 replicates each
blastocyst_ko_f_H3K27me3 ×16 2C_ko_H3K27me3 ×10 blastocyst_wt_m_H3K27me3 ×9 2C_wt_H3K27me3 ×9 oocytes_wt_H3K27me3 ×9 oocytes_ko_H3K27me3 ×9 blastocyst_ko_m_H3K27me3 ×8 blastocyst_wt_f_H3K27me3 ×7

Supports a between-group comparison across 77 samples.

How we read this: 8 replicated groups read from 77 sample titles; they account for 77 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

+ 37 more — browse all 77 samples with per-sample file links →

Datasets on a similar topic

Search all mouse ChIP / ATAC / CUT&Tag datasets in GEO →

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