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A conserved H3K14ub-driven H3K9me3 for chromatin compartmentalization

GSE202148 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 24 samples Submitted 2025/08/18 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 24 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
24 samples: 8 conditions, mostly in triplicateGroups 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
A conserved H3K14ub-driven H3K9me3 for chromatin compartmentalizationNature · 2025
Summary (written by the submitters)
To delineate the relationship between G2E3-catalyzed H3K14ub and H3K9me3 in genome-wide, we performed chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) for H3K14ub, H3K9me3 and H3K4me3 in Parental (sgG2E3) control HeLa cells and G2E3 KO-10 HeLa cells. Our data demonstrated that G2E3-catalyzed H3K14ub potentiates H3K9 trimethylation (H3K9me3) by SUV39H and is specifically required for SUV39H compartmentalization and H3K9me3 in pericentromeric heterochromatin.
Read the full summary ↓
Loss ofG2E3 severely impairs not only pericentromeric heterochromatin organization, but also results in aberrant accumulation of SUV39H and H3K9me3 in numerous euchromatin regions and a widespread transcriptional repression (combined with RNA-seq data).
Published in
A conserved H3K14ub-driven H3K9me3 for chromatin compartmentalization
Huang Y, Sun Y, Qi H et al. · Nature 2025 · PMID 41094145 · doi:10.1038/s41586-025-09624-5
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 GSE202148_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 PRJNA834797 and SRA study SRP373414. Searching any of these in the dataset finder brings you back here.

Study design
8 conditions, mostly in triplicate
HeLa, G2E3_KO_10, H3K4me3, ×3 HeLa, G2E3_KO_10, H3K9me3, ×3 HeLa, G2E3_KO_10, H3K14Ub, ×3 HeLa, G2E3_KO_10, Input, ×3 HeLa, sgG2E3, H3K4me3, ×3 HeLa, sgG2E3, H3K9me3, ×3 HeLa, sgG2E3, H3K14Ub, ×3 HeLa, sgG2E3, Input, ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 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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