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Elongin B orchestrates chromatin and transcriptional programs in H3K27M‑mutant diffuse midline glioma [XIII_K27MKO_CUTandRUN]

GSE324873 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 10 samples Submitted 2026/04/27 Platform GPL20795
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 10 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
10 samples: 2 × XIII_CTL2_K27M vs 2 × XIII_K27MKO_K27M vs 2 × XIII_CTL2_IgG vs 2 × XIII_K27MKO_IgGGroups 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.
Summary (written by the submitters)
Recurrent driver mutations in genes encoding histone H3 (H3.3K27M and H3.1K27M) are observed in ~80% of diffuse midline gliomas (DMG), which lead to aberrant gene regulation, yet the specific RNA polymerase 2 (Pol2) regulators inducing aberrant DMG transcription are not fully defined. We identified multiple regulators of Pol2 elongation as DMG genetic dependencies in a chromatin-focused CRISPR screen.
Read the full summary ↓
Additional studies confirm that knockout (KO) of the Pol2 SIII complex gene Elongin B (ELOB) inhibits DMG cell proliferation in tissue culture and tumor growth in xenograft models. Further genomic analyses reveal that ELOB binding sites are enriched in H3K27M oncohistones and that ELOB knockout alters H3K27me3 and H3K27M incorporation at thousands of genomic regions, suggesting a role for ELOB in maintaining dysfunctional chromatin states in DMG. Correspondingly, ELOB loss disrupts Pol2 transcriptional activity and alters the expression of transcripts involved in metabolism, proliferation, and brain development. These findings suggest that Pol2 elongation factors cooperate with H3K27M oncohistones to maintain the epigenetic and transcriptional landscape driving DMG malignancy.
This dataset
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.

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 GSE324873_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1438030 and SRA study SRP684004. Searching any of these in the dataset finder brings you back here.

Study design
2 × XIII_CTL2_K27M vs 2 × XIII_K27MKO_K27M vs 2 × XIII_CTL2_IgG vs 2 × XIII_K27MKO_IgG

Supports a between-group comparison across 8 samples.

How we read this: 4 replicated groups read from 10 sample titles; they account for 8 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
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