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SMYD2 methylates KDM5A restricting its demethylase activity on the genome (and driving proliferation

GSE297614 Homo sapiens (human) RNA-seq (gene expression) 10 samples Submitted 2026/05/27 Platform GPL20795
At a glance

RNA-seq (gene expression) · human · 10 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
10 samples
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
KDM5A methylation modulates its genomic demethylase and transcriptional actionsThe Journal of biological chemistry · 2026
Summary (written by the submitters)
Members of the KDM5 family of Jumonji histone demethylases have been implicated in a variety of human diseases including multiple cancers. The regulation of KDM5 enzyme levels and activity, however, is poorly understood. Here we report that KDM5A is methylated by SMYD2 and that this methylation impacts histone demethylase activity. A mutant KDM5A that can no longer be methylated at K1063 exhibits unique genomic sites of action, demethylates H3K4me3 more robustly and at new loci, has unique transcriptional effects and distinct protein-protein interactions.
Read the full summary ↓
As a result, a number of cell proliferation pathways are affected and cancer cell growth is blunted. This study illustrates the functional consequences of post-translational modifications of lysine residues in enzymes impacting genomic histone demethylation, gene expression and signaling.
Published in
KDM5A methylation modulates its genomic demethylase and transcriptional actions
Tran TA, Gopinathan G, Nuñez CG et al. · The Journal of biological chemistry 2026 · PMID 41962864 · doi:10.1016/j.jbc.2026.111436
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 GSE297614_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: 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 PRJNA1265264 and SRA study SRP586399. Searching any of these in the dataset finder brings you back here.

Samples in this study

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