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R-loop maintains the deposition of H3K36me3 to prevent invasion of H3K4me3 during SN-oocyte development [4]

GSE313733 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 20 samples Submitted 2026/07/13 Platform GPL28330
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 20 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
20 samples: 10 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.
Summary (written by the submitters)
Establishment of epigenetic modifications in an orderly manner is crucial for oocyte maturation and embryonic development. R-loop (DNA/RNA hybrids) plays an important role in regulating genome stability, epigenetic modifications and gene expression. However, the specific functions and regulatory mechanisms of R-loop on the crosstalk between histone modifications during oocyte development remain unclear.
Read the full summary ↓
Here, we find that loss of R-loop by overexpressing Rnaseh1 significantly slow down oocyte development. R-loop loss in germinal vesicle (GV) oocyte leads to downregulation of H3K36me3 at key oocyte developmental gene bodies, aberrant invasion of H3K4me3 into H3K36me3-marked regions, resulting in dysregulated gene expression and ultimately hindering oocyte development. Importantly, this dysregulated gene expression can be rescued by histone H3K36me3 methyltransferase SETD2 targeting on specific R-loop-dependent H3K36me3-marked regions. Together, this finding reveals that R-loop acts as a crucial regulator in controlling epigenetic crosstalk of H3K36me3 and H3K4me3 in maternal genome, ensuring normal oocyte development.
This dataset
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.

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 GSE313733_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1381512 and SRA study SRP655196. Searching any of these in the dataset finder brings you back here.

Study design
10 conditions, mostly in duplicate
oeSPT6_H3K36me3 ×2 oeSPT6_H3K4me3 ×2 SN oocyte_oeSPT6_KASseq ×2 SN oocyte_oeRnaseh1_KASseq ×2 oeRnaseh1_Supt6_SN_SETD2 ×2 oeSupt6_SN_SETD2 ×2 oemCherry_batch2_SN ×2 oeRnaseh1_wkkd_SN ×2 +2 more

Supports a between-group comparison across 20 samples.

How we read this: 10 replicated groups read from 20 sample titles; they account for 20 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
Datasets on a similar topic

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