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High throughput CRISPR perturbation screens identify epigenetic regulators impacting primordial germ cell development [RNA-seq]

GSE259290 Mus musculus (mouse) RNA-seq (gene expression) 15 samples Submitted 2025/09/04 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 15 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
15 samples: 5 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
Scalable primordial germ cell-like-cell platform for functional genomics identifies epigenetic fertility modifiersbioRxiv : the preprint server for biology · 2025
Summary (written by the submitters)
There is concern that environmental factors underlie reported declines in fertility and reproductive parameters such as the number and quality of sperm and eggs. One possible mechanism is the perturbation of epigenetic landscapes in the germline. To explore this possibility, we utilized a highly scalable in vitro platform for the differentiation of embryonic stem cells (ESCs) into primordial germ cell-like cells (PGCLCs) to conduct a CRISPRi screen of epigenetic-related genes to identify those that specifically perturb the efficiency of PGCLC formation.
Read the full summary ↓
This platform leveraged an ESC line containing 4 inducible transcription factors (Prdm1, Prdm14, Tfap2c, and Nanog) and a PGC reporter (Stella-eGFP) that enabled highly efficient, cytokine-free differentiation and quantification en masse. A total of 701 genes with distinct sgRNAs were screened, and 53 genes were identified that decreased the efficiency of PGCLC formation. NCOR2, a transcriptional repressor that acts via recruitment of Class I and Class IIa histone deacetylases (HDACs) to gene targets, was particularly potent in suppressing PGCLC differentiation. Consistent with evidence that histone deacetylation is crucial for germline differentiation, we found that HDAC inhibitors (HDACi), including the anti-convulsive drug valproic acid (VPA) and widely-available dietary supplement sodium butyrate (SB), also suppressed ESC>PGCLC differentiation. Transcriptome analyses of HDACi-treated, differentiating ESC>PGCLC cultures revealed suppression of germline-associated pathways and enhancement of somatic pathways. Additionally, exposure of developing mouse embryos to SB or VPA caused hypospermatogenesis. This work demonstrates the feasibility of conducting large scale functional screens of genes, chemical agents and possibly genetic variants that impact germline development and epigenome.
Published in
Scalable primordial germ cell-like-cell platform for functional genomics identifies epigenetic fertility modifiers
Li L, Gao J, Yi D et al. · bioRxiv : the preprint server for biology 2025 · PMID 38405756 · doi:10.1101/2024.02.15.580543
This dataset
Open GSE259290 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 GSE259290_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 PRJNA1080592 and SRA study SRP491818. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38405756) ↗
Study design
5 conditions, mostly in triplicate
Embryoid bodies, no treatment, Stella pos, da… ×3 Embryoid bodies, SB, Stella pos, day6, ×3 Embryoid bodies, SB, Stella neg, day6, ×3 Embryoid bodies, VPA, Stella pos, day6, ×3 Embryoid bodies, VPA, Stella neg, day6, ×3

Supports a between-group comparison across 15 samples.

How we read this: 5 replicated groups read from 15 sample titles; they account for 15 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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