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Polycomb erasers BAP1 and UTX are dispensable for rapid bivalent gene activation but essential for enhancer establishment [RNA-seq]

GSE329245 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2026/04/29 Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 24 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
Mus musculus (mouse)
Samples
24 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.
Summary (written by the submitters)
Polycomb group (PcG) proteins safeguard cell identity by maintaining target genes in a transcriptionally repressed state through depositing two histone marks, H2A lysine-119 ubiquitination (H2AK119ub1) and H3 lysine-27 trimethylation (H3K27me3). BAP1 and UTX are thought to erase these marks during transcription activation, but their exact roles remain unclear.
Read the full summary ↓
Here we observe a rapid loss of H2AK119ub1, followed by a reduction in H3K27me3 levels at promoters upon transcription induction, coinciding with a swift dissociation of PRCs. With an acute degradation system, we show that BAP1 and UTX are dispensable for transcription activation or the dissolution of PcG repressive marks. Instead, they promote enhancer establishment during cell fate transition independent of their eraser enzymatic activity. Therefore, our study provides novel mechanistic insights that the dissolution of PcG-marks is transcription-dependent while UTX and BAP1 primarily function as bridging factors to construct enhancers, rather than as erasers of PcG memory.
This dataset
Open GSE329245 in finder → Find more mouse 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 GSE329245_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 PRJNA1458196 and SRA study SRP695310. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 conditions, mostly in duplicate
UTX,+IAA,-0, ×2 UTX,+IAA,-3, ×2 UTX,+IAA,-6, ×2 UTX,-IAA,-0, ×2 UTX,-IAA,-3, ×2 UTX,-IAA,-6, ×2 BAP1,+IAA,-0, ×2 BAP1,+IAA,-3, ×2 +4 more

Supports a between-group comparison across 24 samples.

How we read this: 12 replicated groups read from 24 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

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