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Suppression of ERK signalling promotes pluripotent epiblast in the human blastocyst

GSE297052 Homo sapiens (human) Single-cell RNA-seq 100 samples Submitted 2025/06/11 Platform GPL34295
At a glance

Single-cell RNA-seq · human · 100 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
100 samples: 40 × Human_Ulix_6 vs 29 × Human_DMSO_6 vs 23 × Human_DMSO_5 vs 8 × Human_Ulix_7Groups 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
Suppression of ERK signalling promotes pluripotent epiblast in the human blastocystNature communications · 2025
Summary (written by the submitters)
Studies in the mouse demonstrate the importance of fibroblast growth factor (FGF) and extra-cellular receptor tyrosine kinase (ERK) in specification of embryo-fated epiblast and yolk-sac-fated hypoblast cells from uncommitted inner cell mass (ICM) cells prior to implantation. Molecular mechanisms regulating specification of early lineages in human development are comparatively unclear.
Read the full summary ↓
Here we show that exogenous FGF stimulation leads to expanded hypoblast molecular marker expression, at the expense of the epiblast. Conversely, we show that specifically inhibiting ERK activity leads to expansion of epiblast cells functionally capable of giving rise to naïve human pluripotent stem cells. Single-cell transcriptomic analysis indicates that these epiblast cells downregulate FGF signalling and maintain molecular markers of the epiblast. Our functional study demonstrates the molecular mechanisms governing ICM specification in human development, whereby segregation of the epiblast and hypoblast lineages occurs during maturation of the mammalian embryo in an ERK signal-dependent manner.
Published in
Suppression of ERK signalling promotes pluripotent epiblast in the human blastocyst
Simon CS, McCarthy A, Woods L et al. · Nature communications 2025 · PMID 40721412 · doi:10.1038/s41467-025-61830-x
This dataset
Open GSE297052 in finder → Find more human 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 GSE297052_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 PRJNA1262449 and SRA study SRP584946. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40721412) ↗
Study design
40 × Human_Ulix_6 vs 29 × Human_DMSO_6 vs 23 × Human_DMSO_5 vs 8 × Human_Ulix_7

Supports a between-group comparison across 100 samples.

How we read this: 4 replicated groups read from 100 sample titles; they account for 100 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

+ 60 more — browse all 100 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.