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Large-scale transcriptomic analyses reveal downstream target genes of ZFY1 and ZFY2 transcription factors in male germ cells

GSE281037 Mus musculus (mouse) RNA-seq (gene expression) 48 samples Submitted 2026/01/02 Platform GPL30172
At a glance

RNA-seq (gene expression) · mouse · 48 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
48 samples: 48 samples, each with a distinct title — no replicated groupsGroups 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
Large-scale transcriptomic analyses reveal downstream target genes of ZFY1 and ZFY2 transcription factors in male germ cellsCell death and differentiation · 2026
Summary (written by the submitters)
The mouse zinc finger genes Zfy1 and Zfy2 are essential for male fertility. Recently, we produced Zfy1 knock-out (KO), Zfy2 KO, and Zfy1/2 double-knock-out (Zfy DKO) mice, and found that Zfy DKO males were infertile. The mechanism by which ZFY contributes to reproduction remains unknown but based on predicted protein sequence and in vitro assays we hypothesize that it controls expression of genes essential for spermatogenesis.
Read the full summary ↓
To identify which genes ZFY regulates, we performed comparative transcriptome analysis of sorted male germ cells at three different spermatogenesis stages from three Zfy KO models and control wild-type males. Significantly altered germ cell transcriptomes were identified with Zfy2 KO and Zfy DKO. Analyses of differentially expressed genes supported that Zfy loss altered spermatogenesis, DNA packaging/chromatin organization, and apoptosis pathways. Alternative splicing was deregulated in Zfy KO models, affecting sperm function and chromatin regulation pathways. In support of in-silico findings, Zfy DKO males were shown to have impaired sperm chromatin organization, functional sperm deficiencies, and increased germ cell apoptosis. ZFY regulation of apoptotic pathways was demonstrated also in transfected human cells. We conclude that Zfy is a critical regulator of meiosis and spermiogenesis in addition to its previously described function as a cell-cycle regulator.
Published in
Large-scale transcriptomic analyses reveal downstream target genes of ZFY1 and ZFY2 transcription factors in male germ cells
Holmlund H, Coulée M, Yamauchi Y et al. · Cell death and differentiation 2026 · PMID 40866672 · doi:10.1038/s41418-025-01569-6
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 GSE281037_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: 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 PRJNA1181871 and SRA study SRP543150. Searching any of these in the dataset finder brings you back here.

Study design
48 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 48 sample titles: 48 distinct titles with little repetition. 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

+ 8 more — browse all 48 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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