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MAPK/ERK signaling regulates H3K9me3 heterochromatin reorganization to confer mesendoderm developmental competence

GSE289666 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 52 samples Submitted 2026/02/26 Platform GPL24676Platform GPL34281
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 52 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
52 samples: 25 conditions, mostly in duplicateGroups 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
MAPK/ERK signaling blocks ectopic H3K9me3 heterochromatin formation to confer mesoderm and endoderm developmental competencebioRxiv : the preprint server for biology · 2025
Summary (written by the submitters)
During gastrulation, dynamic interplay among cell signaling pathways dictates cell fate decisions. While extensive studies have elucidated their critical roles in morphological regulation, how these signals orchestrate the epigenome to confer developmental competence remains unclear.
Read the full summary ↓
In this study, we demonstrate that H3K9me3-marked facultative heterochromatin domains undergo global reorganization during differentiation of human pluripotent stem cells (hPSCs) into mesendoderm (ME) and definitive endoderm (DE), which arise through epithelial-mesenchymal transition (EMT), but not into early neural ectoderm (NE), which retains epithelial state. We identify the MAPK/ERK pathway, acting downstream of FGF signaling, as a key mediator of this reorganization within a critical temporal window during hPSC-to-ME differentiation. Mechanistically, phosphorylated-ERK is enriched across chromatin domains spanning key developmental gene loci and exhibits a reciprocal genomic pattern with H3K9me3, which becomes ectopically accumulated upon MAPK/ERK inhibition. Furthermore, using CRISPRi-mediated perturbation of H3K9me3 methyltransferases, we reveal that proper establishment of H3K9me3 domains plays a dual role in repressing off-target genes and enabling robust activation of lineage-specific programs. Collectively, our findings reveal a previously unrecognized role for MAPK/ERK signaling in reorganizing the H3K9me3 landscape to confer developmental competence, providing mechanistic insight into how signaling pathways shape the epigenetic landscape during development.
Published in
MAPK/ERK signaling blocks ectopic H3K9me3 heterochromatin formation to confer mesoderm and endoderm developmental competence
Matsui S, Granitto M, Sampson S et al. · bioRxiv : the preprint server for biology 2025 · PMID 40909741 · doi:10.1101/2025.08.25.672203
This dataset
Open GSE289666 in finder → Find more human ChIP / ATAC / CUT&Tag 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 GSE289666_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 PRJNA1223914 and SRA study SRP564023. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40909741) ↗
Study design
25 conditions, mostly in duplicate
hPSC_Ctrl_ChIP_H3K9me3 ×2 hPSC_Ctrl_ChIP_Input ×2 DE_Ctrl_ChIP_H3K9me3 ×2 DE_Ctrl_ChIP_Input ×2 NE_Ctrl_ChIP_H3K9me3 ×2 NE_Ctrl_ChIP_Input ×2 NE_MEKi.d2_ChIP_H3K9me3 ×2 DE_MEKi.d2_ChIP_H3K9me3 ×2 +19 more

Supports a between-group comparison across 50 samples.

How we read this: 25 replicated groups read from 52 sample titles; they account for 50 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

+ 12 more — browse all 52 samples with per-sample file links →

Datasets on a similar topic

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