← BioTransfer GEO Dataset Finder
GEO series

H3K27me3 spreading organizes canonical PRC1 chromatin architecture to regulate developmental programs [RNA-seq]

GSE205246 Homo sapiens (human) RNA-seq (gene expression) 25 samples Submitted 2026/03/09 Platform GPL24247Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 25 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
Homo sapiens (human)
Samples
25 samples: 12 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
H3K27me3 spreading organizes canonical PRC1 chromatin architecture to regulate developmental programsNature genetics · 2026
Summary (written by the submitters)
Polycomb Repressive Complex 2 (PRC2) deposits H3K27me3 to recruit canonical PRC1 (cPRC1) that establishes repressive heterochromatin. Higher order cPRC1-mediated chromatin interactions characterize early development and resolve during cell differentiation. Here, we use two opposing models of H3K27me3 dysregulation to elucidate how these long-range loops affect gene expression and cellular phenotypes.
Read the full summary ↓
Aggressive gliomas driven by histone H3 Lys-27-Met (H3K27M) mutations or EZH-Interacting Protein (EZHIP) expression confine H3K27me3 deposition to PRC2 nucleation sites, while loss of the H3K36 methyltransferase NSD1 in pluripotent stem cells leads to its unrestrained spread from these sites. In H3K27M mutant tumours, focal H3K27me3 deposition concentrates chromatin occupancy of cPRC1 complexes, which results in long-range chromatin interactions anchored in polycomb bodies, mirroring patterns found in stem cells. Conversely, spread of H3K27me3 due to NSD1 loss dilutes cPRC1 deposition and disrupts polycomb body architecture. In H3K27M cells, H3K27me3 confinement sustains repression of genes tethered to the polycomb bodies, promoting self-renewing progenitor states required for tumour development. Maintenance of progenitor states depends on cPRC1 interaction with H3K27me3, as chemical allosteric modulation of chromodomains alleviates repression of transcription and promotes differentiation. These results suggest that H3K27me3 spread from CGIs modulates cPRC1 gene expression programs to orchestrate developmental transitions through the maintenance or dissolution of repressive 3D loop architecture at polycomb bodies. Imbalances in the spread of H3K27me3 altering chromatin architecture in disease including H3K27M-expressing neoplasms or following NSD1 loss contribute to explain pathogenic states.
Published in
H3K27me3 spreading organizes canonical PRC1 chromatin architecture to regulate developmental programs
Krug B, Hu B, Chen H et al. · Nature genetics 2026 · PMID 42151415 · doi:10.1038/s41588-026-02586-y
This dataset
Open GSE205246 in finder → Find more 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 GSE205246_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: 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 PRJNA844276 and SRA study SRP377943. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42151415) ↗
Study design
12 conditions, mostly in duplicate
BT245, K27M, 4976, DM, ×2 BT245, K27M, DM, ×2 BT245, KO, DM, ×2 DIPGXIII, K27M, 4976, DM, ×2 DIPGXIII, K27M, DM, ×2 DIPGXIII, KO, DM, ×2 HSJ019, K27M, 4976, DM, ×2 HSJ019, KO, DM, ×2 +5 more

Supports a between-group comparison across 24 samples.

How we read this: 12 replicated groups read from 25 sample titles; they account for 24 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
Datasets on a similar topic

Search all 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.