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Mitochondrial L-2-hydroxyglutarate is a physiologic signaling metabolite [ChIP-seq]

GSE273473 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 14 samples Submitted 2026/04/02 Platform GPL30172
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 14 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
Mus musculus (mouse)
Samples
14 samples: 14 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
Mitochondrial L-2-hydroxyglutarate is a physiological signalling metaboliteNature · 2026
Summary (written by the submitters)
L-2-hydroxyglutarate (L-2-HG) is a low-abundance metabolite in mammals, due to the mitochondrial enzyme L-2-HG dehydrogenase (L2HGDH), which oxidizes L-2-HG to 2-oxoglutarate (2-OG) to prevent its accumulation1. In humans lacking L2HGDH activity, L-2-HG builds up, leading to L-2-HG aciduria, a rare childhood neurometabolic disorder2. Thus, L-2-HG is classified as a toxic metabolite2–5.
Read the full summary ↓
Furthermore, L-2-HG is produced in response to hypoxia, acidic pH, and electron transport chain (ETC) impairment6–10. We investigated the regulation of L-2-HG levels, its impact on gene expression, and whether it has a physiological role in mice. Here, we report that elevated mitochondrial NADH/NAD+ triggers malate dehydrogenase 2 (MDH2) to produce L-2-HG from 2-OG. By contrast, L2HGDH converts L-2-HG to 2-OG in the mitochondrial matrix without requiring a functional ETC. Nascent gene expression analysis in mouse embryonic stem cells (mESCs) demonstrated that the majority of genes were downregulated by elevated L-2-HG levels. To identify proteins involved in L-2-HG-dependent gene regulation, we used proteome integral solubility alteration assays (PISA), which showed that L-2-HG engages the RNA demethylase FTO and H3K9 demethylases KDM4A/B/C in mESC nuclear extracts. The L-2-HG-dependent accumulation of m6A in mRNAs and H3K9me3 at the gene loci negatively correlated with gene expression. Importantly, mitochondrial L2HGDH overexpression during early embryogenesis lowered basal L-2-HG levels and resulted in viable mice at birth but triggered reduced growth, impaired kidney function, and post-natal mortality. Thus, L-2-HG primarily downregulates gene expression and is a signaling metabolite necessary for post-natal mammalian growth and survival. These findings suggest that other previously considered toxic metabolites might also play physiological roles.
Published in
Mitochondrial L-2-hydroxyglutarate is a physiological signalling metabolite
Chakrabarty RP, Van Vranken JG, Aoi Y et al. · Nature 2026 · PMID 42162436 · doi:10.1038/s41586-026-10564-x
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 GSE273473_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1141987 and SRA study SRP523281. Searching any of these in the dataset finder brings you back here.

Study design
14 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 14 sample titles: 14 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
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