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Multi-omics analysis reveals single-cell meiotic hotspot dynamics and epigenomic regulations in female mammals

GSE226475 Mus musculus (mouse) Single-cell RNA-seq 280 samples Submitted 2025/07/08 Platform GPL24247Platform GPL21626
At a glance

Single-cell RNA-seq · mouse · 280 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
280 samples: 94 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
Multi-omics analysis reveals single-cell meiotic hotspot dynamics and epigenomic regulations in female mammalsCell reports · 2025
Summary (written by the submitters)
Meiotic recombination initiates via DNA double-strand breaks (DSBs) at specialized hotspots, while the regulation of meiotic recombination hotspots in females remain elusive due to the scarcity of embryonic stage germ cells (EGCs). Here, we mapped genome-wide active recombination hotspots and estimated their activities in female EGCs at single-cell resolution, revealing the high variability in hotspot usage frequency among individual germ cells.
Read the full summary ↓
Further investigation of nucleosome positioning and histone modifications at recombination hotspots revealed that PRDM9-mediated open chromatin and flanking H3K4me3 established earlier at high-frequency hotspots compared with less frequently used ones. Unexpectedly, although recombination hotspots usually distributed outside of heterochromatin, H3K9me3 was clearly enriched around hotspots in females, forming a unique H3K4me3/H3K9me3 bivalent state. And we showed that appropriate H3K9me3 level may be required for downstream DSB repairs. Together, our results provided novel understanding about the landscape and epigenomic regulation of recombination hotspots in females.
Published in
Multi-omics analysis reveals single-cell meiotic hotspot dynamics and epigenomic regulations in female mammals
Li J, Lu J, Chen J et al. · Cell reports 2025 · PMID 40737127 · doi:10.1016/j.celrep.2025.116082
This dataset
Open GSE226475 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 GSE226475_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA940410 and SRA study SRP425404. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40737127) ↗
Study design
94 conditions, mostly in duplicate
scATAC_E13_5_F ×8 scATAC_E14_5_F ×8 scATAC_E16_5_F ×7 scATAC_E16_5_F_S ×7 scATAC_E13_5_M ×6 scATAC_E15_5_F ×6 scATAC_E15_5_M ×6 scATAC_E16_5_M ×6 +97 more

Supports a between-group comparison across 269 samples.

How we read this: 94 replicated groups read from 280 sample titles; they account for 269 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

+ 240 more — browse all 280 samples with per-sample file links →

Datasets on a similar topic

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