GEO series

H3 citrullination cross-talk within the histone code

GSE316526 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 28 samples Submitted 2026/03/31 Platform GPL30173

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 28 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: 28 samples: 28 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.

Summary (written by the submitters)

Post translational modifications (PTMs) alter protein structure and function, thus impacting cellular dynamics. As an understudied protein post translational modification (PTM), positively charged arginine is converted to neutral citrulline (Rcit) by peptidylarginine deiminase (PAD) enzymes, with no known means of reversal. The PTM is particularly extensive in NETosis, a form of neutrophil programmed cell death with an extensive citrullinome characterized by Neutrophil Extracellular Traps (NETs).

Read the full summary ↓

Here the Citrullinome is extensive and includes the citrullination of histone tails neutralizes arginine charge and is linked to chromatin de-condensation during extracellular release. Given its assumed irreversibility, any role for histone citrullination outside of terminal NETosis is controversial. However, any investigation of site-specific histone Rcit(s) in combinatorial chromatin regulation is severely hindered by the lack of reliable detection reagents. To address, we used nucleosome-based screening to develop recombinant monoclonal antibodies that individually recognize histone H3R2cit, H3R8cit or H3R17cit independent of the cis PTM context. These show PAD4 citrullinates nucleosomal H3R17 and H3R8 more efficiently than H3R2; is inhibited at each position by pre-existing arginine methylation; but strikingly unaffected by neighboring lysine methylations or acetylations. As expected, each citrullination occurs in mouse primary neutrophils upon calcium ionophore induced NETosis. However, H3R8cit and H3R17cit also show broad genomic enrichment patterns in multiple cell lines, suggesting potential roles in epigenetic regulation.

This dataset

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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 GSE316526_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 PRJNA1403259 and SRA study SRP662629. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

28 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 28 sample titles: 28 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

GSM9455389 IgG Control K562 - CUT&RUN
GSM9455390 H3K4me3 K562 - CUT&RUN
GSM9455391 H3K27me3 K562 - CUT&RUN
GSM9455392 H3K9me3 K562 - CUT&RUN
GSM9455393 H3K36me3 K562 - CUT&RUN
GSM9455394 H3R2cit K562 - CUT&RUN
GSM9455395 H3R8cit_ab232939 K562 - CUT&RUN
GSM9455396 H3R8cit_2298-2B4 K562 - CUT&RUN
GSM9455397 H3Tricit K562 - CUT&RUN
GSM9455398 H3R17cit K562 - CUT&RUN
GSM9455399 IgG Control A549 - CUT&RUN
GSM9455400 H3K4me3 A549 - CUT&RUN
GSM9455401 H3K27me3 A549 - CUT&RUN
GSM9455402 H3K9me3 A549 - CUT&RUN
GSM9455403 H3R8cit_2298-2B4 A549 - CUT&RUN
GSM9455404 H3R17cit A549 - CUT&RUN
GSM9455405 IgG Control MCF7 - CUT&RUN
GSM9455406 H3K4me3 MCF7 - CUT&RUN
GSM9455407 H3K27me3 MCF7 - CUT&RUN
GSM9455408 H3K9me3 MCF7 - CUT&RUN
GSM9455409 H3R8cit_2298-2B4 MCF7 - CUT&RUN
GSM9455410 H3R17cit MCF7 - CUT&RUN
GSM9455411 IgG Control Jurkat - CUT&RUN
GSM9455412 H3K4me3 Jurkat - CUT&RUN
GSM9455413 H3K27me3 Jurkat - CUT&RUN
GSM9455414 H3K9me3 Jurkat - CUT&RUN
GSM9455415 H3R8cit_2298-2B4 Jurkat - CUT&RUN
GSM9455416 H3R17cit Jurkat - CUT&RUN

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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.