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Roles of 3'UTR and IDR in regulating activity and chromatin localization of JMJD3 [ChIP-seq]

GSE301136 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 17 samples Submitted 2025/07/02 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 17 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
17 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
mRNA 3'UTRs chaperone intrinsically disordered regions to control protein activitybioRxiv : the preprint server for biology · 2025
Summary (written by the submitters)
JMJD3 cellular activity can be regulated by altered chromatin localization to genomic targets or by protein conformation changes that alter its catalytic activity. We found that the 3'UTR in the KDM6B mRNA template is required for the JMJD3 protein to achive full demethylase activity in cells and that 3'UTR dependent regulation requires its intrinsically disordered region (IDR).
Read the full summary ↓
In order to dissect the mechanism underlying 3'UTR- and IDR-coordinated control of JMJD3 protein activity in cells, we used ChIP-seq to identify localization and demethylase activity of full-length JMJD3 expressed from constructs with or without its 3'UTR and a IDR-deleted mutant.
Published in
mRNA 3'UTRs chaperone intrinsically disordered regions to control protein activity
Luo Y, Zhong Y, Basu S et al. · bioRxiv : the preprint server for biology 2025 · PMID 40631257 · doi:10.1101/2025.07.02.662873
This dataset
Open GSE301136 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 GSE301136_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 PRJNA1284099 and SRA study SRP596014. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40631257) ↗
Study design
8 conditions, mostly in duplicate
Hela, HA-KDM6B-NU, HA (ChIP), ×2 Hela, HA-KDM6B-NU, H3K27me3 (ChIP), ×2 Hela, HA-KDM6B-U, HA (ChIP), ×2 Hela, HA-KDM6B-U, H3K27me3 (ChIP), ×2 Hela, HA-KDM6B-IDRdel-NU, HA (ChIP), ×2 Hela, HA-KDM6B-IDRdel-NU, H3K27me3 (ChIP), ×2 HeLa, Control, HA (ChIP), ×2 HeLa, Control, H3K27me3 (ChIP), ×2 +1 more

Supports a between-group comparison across 16 samples.

How we read this: 8 replicated groups read from 17 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
Datasets on a similar topic

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