GEO series

TRIM37 interacts with TRIM28 to maintain primordial germ cell identity during migration [bulkRNA-seq, scRNA-seq]

GSE289335 Mus musculus (mouse) Single-cell RNA-seq 127 samples Submitted 2026/06/26 Platform GPL24247

At a glance

Single-cell RNA-seq · mouse · 127 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: 127 samples: 9 conditions, mostly with about 18 replicates eachGroups 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.

Summary (written by the submitters)

During embryo development, germ cells segregate from soma to ensure the genome transmission of a species. Although the repression of somatic programs in germline specification is well studied, the molecular mechanisms that protect primordial germ cell (PGC) fate thereafter remain poorly understood. Here, we show that the ubiquitin ligase TRIM37 suppresses the somatic programs during PGC migration.

Read the full summary ↓

Trim37 mutant embryos exhibit PGC developmental defects from embryonic day 9.5 (E9.5) and depletion at E12.5, with Trim37-deficient PGCs transdifferentiating into somatic cells. Mechanistically, TRIM37 interacts with TRIM28 through its MATH domain to repress somatic gene expression in the nucleus. Forcing TRIM37 out of the nucleus causes PGC depletion. Additionally, the K27-linked polyubiquitination of TRIM28 catalyzed by TRIM37 augments their interaction and promotes the nucleus location of TRIM37. The impairment of TRIM37 ubiquitin ligase activity and mutations in TRIM28 ubiquitination sites both hinder PGC development. Furthermore, TRIM37 deficiency disrupts the DNA binding of TRIM28, which is mostly guided by AP2γ, leading to enhanced chromatin accessibility and increased H3K27ac levels, resulting in the upregulation of somatic genes. Our results shed light on the TRIM37-mediated epigenetic suppression mechanisms controlling germ cell fate maintenance and are relevant for the infertility of Mulibrey nanism patients.

This dataset

Open GSE289335 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 GSE289335_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 PRJNA1222436 and SRA study SRP563299. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

9 conditions, mostly with about 18 replicates each

E9.5-scRNA-T37KO-PGC ×30 E8.5-scRNA-T37KO-PGC ×18 E9.25-bulk-T37KO-PGC ×18 E9.5-scRNA-con-PGC ×15 E9.25-bulk-control-PGC ×13 E8.5-scRNA-con-PGC ×12 E9.5-scRNA-con-SC ×10 E9.5-scRNA-T37KO-SC ×9 +1 more

Supports a between-group comparison across 127 samples.

How we read this: 9 replicated groups read from 127 sample titles; they account for 127 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

GSM8789333 E8.5-scRNA-con-SC-1 E8.5-scRNA-con-SC
GSM8789334 E8.5-scRNA-con-SC-2 E8.5-scRNA-con-SC
GSM8789335 E8.5-scRNA-con-PGC-1 E8.5-scRNA-con-PGC
GSM8789336 E8.5-scRNA-con-PGC-2 E8.5-scRNA-con-PGC
GSM8789337 E8.5-scRNA-con-PGC-3 E8.5-scRNA-con-PGC
GSM8789338 E8.5-scRNA-con-PGC-4 E8.5-scRNA-con-PGC
GSM8789339 E8.5-scRNA-con-PGC-5 E8.5-scRNA-con-PGC
GSM8789340 E8.5-scRNA-con-PGC-6 E8.5-scRNA-con-PGC
GSM8789341 E8.5-scRNA-con-PGC-7 E8.5-scRNA-con-PGC
GSM8789342 E8.5-scRNA-con-PGC-8 E8.5-scRNA-con-PGC
GSM8789343 E8.5-scRNA-con-PGC-9 E8.5-scRNA-con-PGC
GSM8789344 E8.5-scRNA-con-PGC-10 E8.5-scRNA-con-PGC
GSM8789345 E8.5-scRNA-con-PGC-11 E8.5-scRNA-con-PGC
GSM8789346 E8.5-scRNA-con-PGC-12 E8.5-scRNA-con-PGC
GSM8789347 E8.5-scRNA-T37KO-PGC-1 E8.5-scRNA-T37KO-PGC
GSM8789348 E8.5-scRNA-T37KO-PGC-2 E8.5-scRNA-T37KO-PGC
GSM8789349 E8.5-scRNA-T37KO-PGC-3 E8.5-scRNA-T37KO-PGC
GSM8789350 E8.5-scRNA-T37KO-PGC-4 E8.5-scRNA-T37KO-PGC
GSM8789351 E8.5-scRNA-T37KO-PGC-5 E8.5-scRNA-T37KO-PGC
GSM8789352 E8.5-scRNA-T37KO-PGC-6 E8.5-scRNA-T37KO-PGC
GSM8789353 E8.5-scRNA-T37KO-PGC-7 E8.5-scRNA-T37KO-PGC
GSM8789354 E8.5-scRNA-T37KO-PGC-8 E8.5-scRNA-T37KO-PGC
GSM8789355 E8.5-scRNA-T37KO-PGC-9 E8.5-scRNA-T37KO-PGC
GSM8789356 E8.5-scRNA-T37KO-PGC-10 E8.5-scRNA-T37KO-PGC
GSM8789357 E8.5-scRNA-T37KO-PGC-11 E8.5-scRNA-T37KO-PGC
GSM8789358 E8.5-scRNA-T37KO-PGC-12 E8.5-scRNA-T37KO-PGC
GSM8789359 E8.5-scRNA-T37KO-PGC-13 E8.5-scRNA-T37KO-PGC
GSM8789360 E8.5-scRNA-T37KO-PGC-14 E8.5-scRNA-T37KO-PGC
GSM8789361 E8.5-scRNA-T37KO-PGC-15 E8.5-scRNA-T37KO-PGC
GSM8789362 E8.5-scRNA-T37KO-PGC-16 E8.5-scRNA-T37KO-PGC
GSM8789363 E8.5-scRNA-T37KO-PGC-17 E8.5-scRNA-T37KO-PGC
GSM8789364 E8.5-scRNA-T37KO-PGC-18 E8.5-scRNA-T37KO-PGC
GSM8789365 E9.5-scRNA-con-SC-1 E9.5-scRNA-con-SC
GSM8789366 E9.5-scRNA-con-SC-2 E9.5-scRNA-con-SC
GSM8789367 E9.5-scRNA-con-SC-3 E9.5-scRNA-con-SC
GSM8789368 E9.5-scRNA-con-SC-4 E9.5-scRNA-con-SC
GSM8789369 E9.5-scRNA-con-SC-5 E9.5-scRNA-con-SC
GSM8789370 E9.5-scRNA-con-SC-6 E9.5-scRNA-con-SC
GSM8789371 E9.5-scRNA-con-SC-7 E9.5-scRNA-con-SC
GSM8789372 E9.5-scRNA-con-SC-8 E9.5-scRNA-con-SC

+ 87 more — browse all 127 samples with per-sample file links →

Datasets on a similar topic

GSE289334 TRIM37 interacts with TRIM28 to maintain primordial germ cell identity during migration 18 samples shares trim37, trim28, primordial, interacts, migration, maintain
GSE289333 TRIM37 interacts with TRIM28 to maintain primordial germ cell identity during migration [ATAC-seq] 6 samples shares trim37, trim28, primordial, interacts, migration, maintain
GSE299728 Urolithin A maintains primordial follicle dormancy and prevents cyclophosphamide-induced follicle loss by inhibiting the PI3K/Akt signaling 12 samples shares primordial, maintain
GSE334845 Discovery of Tcf7 regulators with clonally-resolved CRISPR screens identifies Trim28 as a mediator of CD8 T cell differentiation in tumors [RNA-Seq] 86 samples shares trim28
GSE266176 Tranposable Element Control by TRIM28 Safeguards PGC Sex Determination Program [RNA-Seq] 42 samples shares trim28
GSE263021 TRIM28-dependent developmental heterogeneity determines cancer susceptibility through distinct epigenetic states [RNA-seq - matched healthy and tumor tissues] 41 samples shares trim28
GSE297361 Loss of NOTCH2 Creates a TRIM28-Dependent Vulnerability in Small Cell Lung Cancer [bulk_murine_RNA_seq] 36 samples shares trim28
GSE298402 RNA-Seq analysis of Trim28-deleted NPp53 mouse prostate tissue 19 samples shares trim28

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.