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Dynamic Multi-omics Profiling Unveils Bimodal Epigenetic Roles of Chromatin O-GlcNAc modification in Premature Senescence Program [ChIP-seq]

GSE295087 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 48 samples Submitted 2025/05/20 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 48 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
48 samples: 48 samples, each with a distinct title — no replicated groupsGroups 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
Time-resolved multiomics profiling reveals chromatin O-GlcNAc modification promotes senescence-associated transcriptional programNature communications · 2026
Summary (written by the submitters)
Cellular senescence, a recognized instigator of tumorigenesis and age-associated disorders, can be precipitated by characteristic alterations in gene expression profiles. However, the underlying mechanisms that precise orchestrate the expression of senescence-related genes are still elusive. Here, we employed a time-series approach using a chemical genomics multi-omics strategy to panoramically investigate the role of O-GlcNAc chromatin-associated proteins (OCPs) throughout the process of oncogene-induced senescence (OIS) in human primary fibroblasts.
Read the full summary ↓
The progression of OIS is associated with the dynamic accumulation of chromatin O-GlcNAc modification, which facilitates cells commitment to senescence. Through the integration of dynamic analyses of transcriptome and epigenome profiles, we can demonstrate that OCPs experience genomic occupation shifts across diverse epigenetic chromatin states, and display bimodal sequential regulatory activity within the senescence transcriptome. Mechanistically, O-GlcNAc aids in the formation of bimodal epigenetic regulatory complexes (TF-SWI/SNF and NuRD), which dictate the gene expression patterns related to both the senescence-associated secretory phenotype (SASP) and cell cycle arrest. Additionally, we pinpointed O-GlcNAc JUN and GATAD2A as key regulators affecting the phenotypes of OIS in both in vitro and in vivo models of senescence and tumorigenesis. Our findings on the dynamic behavior and chromatin organization principles of O-GlcNAc epigenetic factors provide insights into the senescence process and enable potential therapeutic manipulation of the senescence phenotype.
Published in
Time-resolved multiomics profiling reveals chromatin O-GlcNAc modification promotes senescence-associated transcriptional program
Zhang N, Zhao R, Zhong X et al. · Nature communications 2026 · PMID 41507163 · doi:10.1038/s41467-025-68143-z
This dataset
Open GSE295087 in finder → Find more human ChIP / ATAC / CUT&Tag 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 GSE295087_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1252784 and SRA study SRP580180. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41507163) ↗
Study design
48 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 48 sample titles: 48 distinct titles with little repetition. 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

+ 8 more — browse all 48 samples with per-sample file links →

Datasets on a similar topic

Search all human ChIP / ATAC / CUT&Tag datasets in GEO →

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