← BioTransfer GEO Dataset Finder
GEO series

Fine-tuning ERK activity enables proliferation-differentiation balance during lineage specification of human embryonic stem cells

GSE273286 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 24 samples Submitted 2026/02/23 Platform GPL24676Platform GPL16791
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 24 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Samples
24 samples: 24 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
Fine-tuning ERK activity enables proliferation-differentiation balance during lineage specification of human embryonic stem cellsPLoS biology · 2026
Summary (written by the submitters)
It is well documented that differentiation of stem cells is generally associated with and facilitated by an elongated cell cycle. However, for lineage specification requiring high ERK activity, which also promotes proliferation, it is unclear how stem cells simultaneously negotiate the “proliferation-differentiation” decision. Here we investigate this question using multiplex quantitative live-cell imaging to track embryonic stem cells (ESC) differentiation into mesendoderm (ME) lineage with high ERK activity.
Read the full summary ↓
We show that ERK activity increase manifested by a heightened ERK oscillation frequency drove robust ME differentiation accompanied by a modest cell cycle acceleration. We profile the responses of ME differentiation and cell cycle length as a function of a synthetic ERK oscillatory activity gradient. Our results reveal that these two processes took place in distinct ranges of ERK oscillation frequency, with ME differentiation requiring higher level for ERK oscillation to secure efficient ME protein translation. Interactions between gastrulation morphogens recapitulated an ERK oscillation gradient, potentiating heterogeneous ME fates while maintaining a comparable level of proliferation. Our study thus provides mechanistic insights into how ERK fine-tunes proliferation and differentiation during cell fate specification
Published in
Fine-tuning ERK activity enables proliferation-differentiation balance during lineage specification of human embryonic stem cells
Ma C, Meng W, Huang J et al. · PLoS biology 2026 · PMID 41843632 · doi:10.1371/journal.pbio.3003711
This dataset
Open GSE273286 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 GSE273286_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1141364 and SRA study SRP522754. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41843632) ↗
Study design
24 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 24 sample titles: 24 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
Datasets on a similar topic

Search all human 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.