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Hexokinase 3 enhances myeloid cell survival via non-glycolytic functions

GSE197164 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 20 samples Submitted 2024/08/31 Platform GPL18573
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 20 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
20 samples: 20 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.
Paper
Hexokinase 3 enhances myeloid cell survival via non-glycolytic functionsCell death & disease · 2022
Summary (written by the submitters)
Purpose: The goal was to compare transcriptome profiles of HL60 HK3-null and Cas9 expressing control cells treated with either ATRA or DMSO using RNA sequencing. In addition, to find accessible DNA regions by probing open chromatin with hyperactive mutant Tn5 Transposase using ATAC sequencing. Methods: HL60 HK3-null and Cas9 expressing control cells were treated with 1µM of ATRA or DMSO (0.01%) for 36h.
Read the full summary ↓
Treated cells were then harvested for RNA-Seq and ATAC-Seq analysis. Results: We mapped sequence reads per sample to the human genome (GRCh38 - hg38) and identified differentially expressed transcripts as well as open chromatin peaks in AML HL60 HK3-null and Cas9 expressing cells upon treatment with ATRA or DMSO as control. Differentially expressed genes, were identified with a fold change ≥1.5 and FDR p-value <0.05. Conclusions: Our results show that HK3 knockout (HK3-null) AML cells had an accumulation of reactive oxygen species (ROS) as well as DNA damage during ATRA-induced differentiation. RNA sequencing analysis confirmed pathway enrichment for programmed cell death, oxidative stress and DNA damage response in HK3-null AML cells. These signatures were confirmed in ATAC sequencing, showing that loss of HK3 leads to changes in chromatin configuration and increases accessibility of genes involved in apoptosis and stress response.
Published in
Hexokinase 3 enhances myeloid cell survival via non-glycolytic functions
Seiler K, Humbert M, Minder P et al. · Cell death & disease 2022 · PMID 35538058 · doi:10.1038/s41419-022-04891-w
This dataset
Open GSE197164 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 GSE197164_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 PRJNA809305 and SRA study SRP360944. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 35538058) ↗
Study design
20 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 20 sample titles: 20 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
Datasets on a similar topic

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