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Scalable and Efficient Generation of Mouse Primordial Germ Cell-like Cells

GSE256104 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)
Primordial germ cells (PGCs) are the founder cells of the germline. The ability to generate PGC-like cells (PGCLCs) from pluripotent stem cells has advanced our knowledge of gametogenesis and holds promise for developing infertility treatments. However, generating an ample supply of PGCLCs for demanding applications such as high-throughput genetic screens has been a limitation.
Read the full summary ↓
Here, we demonstrated that simultaneous overexpressing 4 transcriptional factors – Nanog and three PGC master regulators Prdm1, Prdm14 and Tfap2c - in suspended mouse epiblast like cells (EpiLCs) and formative embryonic stem cells (ESCs) results in efficient and cost-effective production of PGCLCs. The overexpression of Nanog enhances the PGC regulatory network and suppresses differentiation of somatic lineages, enabling a significant improvement in the efficiency of PGCLC production. Transcriptomic analysis reveals that differentiated PGCLCs exhibit similarities to in vivo PGCs and are more advanced compared to cytokine-induced PGCLCs. These differentiated PGCLCs could be sustained over prolonged periods of culture, and could differentiate into spermatogonium-like cells in vitro. Importantly, the ability to produce PGCLC differentiation at scale enables biochemical and functional genomic screens to dissect mechanisms of germ cell development and infertility.
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
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 GSE256104_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 PRJNA1078246 and SRA study SRP490424. Searching any of these in the dataset finder brings you back here.

Study design
5 conditions, mostly in triplicate
ESC, 2i LIF, ×3 EpiLC, 48h, ×3 PGCLC, 4TF, day2, ×3 PGCLC, 4TF, day4, ×3 PGCLC, 4TF, 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
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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.