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Leukemia risk factor ARID5B Coordinates HDAC-Mediated Transcriptional Repression [RNA-Seq]

GSE297397 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/05/19 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 3 × NALM6_Cas9_RNA-seq vs 3 × NALM6_ARID5B_KO_RNA-seq vs 3 × NALM6_Cas9_DMSO_RNA-seq vs 3 × NALM6_Cas9_Entino_RNA-seqGroups 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
Leukemia risk factor ARID5B coordinates HDAC-mediated transcriptional repressionNucleic acids research · 2026
Summary (written by the submitters)
We employed a combination of proteomics, genomics and transcriptomics to describe the molecular mechanisms of ARID5B. We identify that ARID5B interacts with MIER1, C16ORF87, HDAC1 and HDAC2 forming a repressor complex. The former localizes to active regions of the genome, tethering HDAC1 and HDAC2 to enhancers and promoters. Genes actively repressed by the ARID5B repressor complex are involved in B cell-specific signaling.
Published in
Leukemia risk factor ARID5B coordinates HDAC-mediated transcriptional repression
Kutschat AP, Frommelt F, Santini BL et al. · Nucleic acids research 2026 · PMID 42328790 · doi:10.1093/nar/gkag628
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 GSE297397_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 PRJNA1263761 and SRA study SRP586027. Searching any of these in the dataset finder brings you back here.

Study design
3 × NALM6_Cas9_RNA-seq vs 3 × NALM6_ARID5B_KO_RNA-seq vs 3 × NALM6_Cas9_DMSO_RNA-seq vs 3 × NALM6_Cas9_Entino_RNA-seq

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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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