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Targeted citrullination enables p53 binding to non-canonical sites [165]

GSE287871 Homo sapiens (human) RNA-seq (gene expression) 48 samples Submitted 2026/01/17 Platform GPL30882
At a glance

RNA-seq (gene expression) · human · 48 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
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.
Summary (written by the submitters)
TP53 encodes for the transcription factor p53, which binds to a diverse set of target genes in response to stress. Activation of p53 results in highly specific transcriptional responses, but the regulation of promoter selectivity by p53 is poorly understood. Here we report that sequence-specific binding of p53 is regulated by its target gene and binding partner PADI4.
Read the full summary ↓
PADI4 enzymatically converts peptidyl-arginine to peptidyl-citrulline in a process known as citrullination. We show p53 is citrullinated in vitro at the C-terminus by PADI4, and we confirm two citrullination events in vivo (R306, R363). ChIP-seq reveals that PADI4 expression causes a redirection of p53 away from canonical binding sites to target genes associated with the ETS transcription factor and the interferon response. Chromatin profiling using citrullination-specific p53 antibodies supports this conclusion. These findings link citrullination to p53 function and illustrate how chromatin modifiers like PADI4 can redirect the p53 transcriptional response.
This dataset
Open GSE287871 in finder → Find more human RNA-seq 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 GSE287871_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1214836 and SRA study SRP559483. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
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 RNA-seq datasets in GEO →

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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.