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Histone H4 lysine 20 monomethylation is not a mark of transcriptional silencers

GSE284058 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 16 samples Submitted 2025/02/19 Platform GPL34457Platform GPL34284
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 16 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
16 samples: 8 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.
Paper
Histone H4 lysine 20 monomethylation is not a mark of transcriptional silencersbioRxiv : the preprint server for biology · 2025
Summary (written by the submitters)
Silencers are cis-regulatory elements that down-regulate the expression of target genes. While thousands of silencers have been identified experimentally, a predictive chromatin signature has not been found. H4K20me1 was previously reported to be enriched in silencers, but through reanalysis we found that this enrichment is marginal and was primarily driven by the biased selection of elements used in the screen.
Read the full summary ↓
We generated H4K20me1 ChIP-seq in Drosophila S2 cells and confirmed that H4K20me1 does not mark transcriptional silencers but instead is associated with active transcription. Transcriptional silencers remain a poorly annotated and difficult to predict class of cis-regulatory elements.
Published in
Histone H4 lysine 20 monomethylation is not a mark of transcriptional silencers
Segert JA, Bulyk ML · bioRxiv : the preprint server for biology 2025 · PMID 39868205 · doi:10.1101/2025.01.09.632211
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 GSE284058_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 PRJNA1196916 and SRA study SRP550809. Searching any of these in the dataset finder brings you back here.

Study design
8 conditions, mostly in duplicate
S2 cells, H3K27me3 ChIP, ×2 S2 cells, H4K20me1 ChIP with Abcam ab9051 ant… ×2 S2 cells, H4K20me1 ChIP with Active Motif AB_… ×2 S2 cells, H4K20me1 ChIP with Thermo Fisher MA… ×2 S2 cells, ChIP INPUT, ×2 K562 cells, H4K20me1 ChIP with Active Motif A… ×2 K562 cells, H4K20me1 ChIP with Thermo Fisher … ×2 K562 cells, ChIP INPUT, ×2

Supports a between-group comparison across 16 samples.

How we read this: 8 replicated groups read from 16 sample titles; they account for 16 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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