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Mitochondrial metabolism sustains DNMT3A-R882-mutant clonal haematopoiesis

GSE259404 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/02/06 Platform GPL16417
At a glance

RNA-seq (gene expression) · mouse · 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
Mus musculus (mouse)
Samples
12 samples: 6 × Mouse1_day vs 6 × Mouse2_dayGroups 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
Mitochondrial metabolism sustains DNMT3A-R882-mutant clonal haematopoiesisNature · 2025
Summary (written by the submitters)
Somatic DNMT3A R882 codon mutations drive the most common form of clonal haematopoiesis (CH) and are associated with increased acute myeloid leukaemia (AML) risk. Preventing expansion of DNMT3A-R882-mutant haematopoietic stem/progenitor cells (HSPCs) may therefore avert progression to AML. To identify DNMT3A-R882-mutant-specific vulnerabilities, we conducted a genome-wide CRISPR screen on primary mouse Dnmt3aR882H/+ HSPCs.
Read the full summary ↓
Amongst the 640 vulnerability genes identified, many were involved in mitochondrial metabolism and metabolic flux analysis confirmed enhanced oxidative phosphorylation usage in Dnmt3aR882H/+ vs Dnmt3a+/+ (WT) HSPCs. We selected citrate/malate transporter Slc25a1 and complex I component Ndufb11, for which pharmacological inhibitors are available, for downstream studies. In vivo administration of SLC25A1 inhibitor CTPI2 and complex I inhibitors IACS-010759 and metformin, suppressed post-transplantation clonal expansion of Dnmt3aR882H/+, but not WT, LT-HSCs. The effect of metformin was recapitulated using a primary human DNMT3A-R882 CH sample. Notably, analysis of 412,234 UK Biobank participants revealed that individuals taking metformin had markedly lower prevalence of DNMT3A-R882-mutant CH, after controlling for potential confounders including glycated haemoglobin, diabetes and body mass index. Collectively, our data propose that modulation of mitochondrial metabolism as a therapeutic strategy for prevention of DNMT3A-R882-mutant AML.
Published in
Mitochondrial metabolism sustains DNMT3A-R882-mutant clonal haematopoiesis
Gozdecka M, Dudek M, Wen S et al. · Nature 2025 · PMID 40239706 · doi:10.1038/s41586-025-08980-6
This dataset
Open GSE259404 in finder → Find more mouse 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 GSE259404_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 PRJNA1081425 and SRA study SRP492113. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40239706) ↗
Study design
6 × Mouse1_day vs 6 × Mouse2_day

Supports a between-group comparison across 12 samples.

How we read this: 2 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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