← BioTransfer GEO Dataset Finder
GEO series

BRD4 O-GlcNAcylation attenuates phase separation to regulate transcription

GSE282031 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 38 samples Submitted 2026/07/29 Platform GPL29480Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 38 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
38 samples: 18 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)
BRD4 undergoes liquid-liquid phase separation (LLPS) at super-enhancers (SEs) to facilitate gene control. However, the regulatory mechanisms and transcriptional consequences of BRD4 condensation remain elusive. Here, we show that the BRD4 C-terminal intrinsically disordered region (IDR) is a primary interacting region for O-GlcNAc transferase (OGT), enabling O-GlcNAc modifications at 12 potential sites.
Read the full summary ↓
O-GlcNAcylation attenuates BRD4 LLPS, leading to small puncta and increased fluidity, which significantly declines occupancy and transcription at SEs. We further demonstrate that loss of O-GlcNAcylation on BRD4 led to elevated gene expression relating to cell cycle and DNA damage, allowing cells less sensitive to DNA damage and promoting faster growth. Therefore, we identify an O-GlcNAc–mediated regulatory mechanism for BRD4 LLPS that governs gene control at SEs, showcasing how O-GlcNAc modifications can influence transcriptional activities at SEs through a phase separation model.
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 GSE282031_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 PRJNA1186685 and SRA study SRP545492. Searching any of these in the dataset finder brings you back here.

Study design
18 conditions, mostly in duplicate
HeLa cells, Total RNA-seq, WT, ×2 HeLa cells, Total RNA-seq, 12A, ×2 HeLa cells, Chr RNA-seq, WT, ×2 HeLa cells, Chr RNA-seq, 12A, ×2 HeLa cells, Nuc RNA-seq, WT, ×2 HeLa cells, Nuc RNA-seq, 12A, ×2 HeLa cells, Cyto RNA-seq, WT, ×2 HeLa cells, Cyto RNA-seq, 12A, ×2 +12 more

Supports a between-group comparison across 36 samples.

How we read this: 18 replicated groups read from 38 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

Search all human 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.