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Retrotransposon expression analysis for mouse spermatogonia defficient in Dnmt3l and Pld6.

GSE296268 Mus musculus (mouse) RNA-seq (gene expression) 19 samples Submitted 2025/12/04 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 19 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
19 samples: 6 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
DNA methylation dictates histone modifications in developing male germ cells in the mouseNucleic acids research · 2025
Summary (written by the submitters)
In the male germline of mammals, the expression of retrotransposons is restricted by DNA methylation, trimethylation of histone H3 at lysin-9 (H3K9me3) and PIWI-interacting small RNAs (piRNAs). To elucidate their relative importance in regulating retrotransposons during germ-cell development as well as relationships between these mechanisms, we performed mRNA, DNA methylation, and histone methylation analyses using mouse spermatogonia from Dnmt3l and Pld6 mutants deficient in de novo DNA methylation and piRNA production, respectively.
Read the full summary ↓
The results revealed that a loss of DNA methylation results in decreased H3K9me3 and increased H3K4me3, suggesting a pivotal role of DNA methylation in maintaining the epigenome integrity.
Published in
DNA methylation dictates histone modifications in developing male germ cells in the mouse
Sugimoto H, Kawase M, Ichiyanagi K · Nucleic acids research 2025 · PMID 41273173 · doi:10.1093/nar/gkaf1240
This dataset
Open GSE296268 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 GSE296268_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 PRJNA1258307 and SRA study SRP582891. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41273173) ↗
Study design
6 conditions, mostly in triplicate
mRNA Pld6-/- KO, ×5 mRNA Dnmt3l+/- heterozygous, ×3 mRNA Dnmt3l-/- KO, ×3 mRNA Pld6+/+ wild-type, ×3 mRNA Pld6+/- heterozygous, ×3 mRNA Dnmt3l+/+ wild-type, ×2

Supports a between-group comparison across 19 samples.

How we read this: 6 replicated groups read from 19 sample titles; they account for 19 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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