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H3F3A K27M Mutations Drive a Repressive Transcriptome by Modulating Chromatin Accessibility, Independent of H3K27me3 in Diffuse Midline Glioma [RNA-seq]

GSE293771 Homo sapiens (human) RNA-seq (gene expression) 36 samples Submitted 2025/04/30 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 36 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
36 samples: 8 conditions, mostly with about 6 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.
Paper
H3F3A K27M mutations drive a repressive transcriptome by modulating chromatin accessibility independent of H3K27me3 in Diffuse Midline GliomaEpigenetics & chromatin · 2025
Summary (written by the submitters)
Heterozygous histone H3.3K27M mutation is a primary oncogenic driver of Diffuse Midline Glioma (DMG). H3.3K27M inhibits the Polycomb Repressive Complex 2 (PRC2) methyltransferase complex, leading to a global reduction and redistributing of the repressive H3 lysine 27 tri-methylation. This rewiring of the epigenome is thought to promote gliomagenesis.
Read the full summary ↓
We established novel, isogenic DMG patient-derived cell lines that have been CRISPR-Cas9 edited to H3.3 WT or H3.3K27M alone and in combination with EZH2 and EZH1 co-deletion, inactivating PRC2 methyltransferase activity of PRC2 and eliminating H3K27me3. RNA-seq and ATAC-seq analysis of these cells revealed that K27M has a novel epigenetic effect that appears entirely independent of its effects on PRC2 function. While the loss of the PRC2 complex led to a systemic induction of gene expression (including HOX gene clusters) and upregulation of biological pathways, K27M led to a balanced gene deregulation but having an overall repressive effect on the biological pathways. Importantly, the genes uniquely deregulated by the K27M mutation, independent of methylation loss, are closely associated with changes in chromatin accessibility, with upregulated genes becoming more accessible. Notably, the PRC2-independent function of K27M appears necessary for tumorigenesis as xenografts of our H3.3K27M/EZH1/2 WT cells developed into tumors, while H3.3/EZH1/2 KO cells did not. We demonstrate that K27M mutation alters chromatin accessibility and uniquely deregulates genes, independent of K27 methylation. We further show the mutation's role in altering biological pathways and its necessity for tumor development.
Published in
H3F3A K27M mutations drive a repressive transcriptome by modulating chromatin accessibility independent of H3K27me3 in Diffuse Midline Glioma
Bhattarai S, Hakkim FL, Day CA et al. · Epigenetics & chromatin 2025 · PMID 40287708 · doi:10.1186/s13072-025-00585-7
This dataset
Open GSE293771 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 GSE293771_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 PRJNA1246196 and SRA study SRP576392. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40287708) ↗
Study design
8 conditions, mostly with about 6 replicates each
SF-8628-K27M-PRC2KO ×6 SF-8628-K27WT ×6 SF-8628-K27WT-PRC2KO ×6 SF-9427-K27WT-PRC2KO ×6 SF-8628-K27M ×4 SF-9427-K27WT ×4 DIPG17-K27M ×2 DIPG17-K27WT ×2

Supports a between-group comparison across 36 samples.

How we read this: 8 replicated groups read from 36 sample titles; they account for 36 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

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