GEO series

Mitophagy Mitigates Mitochondrial Fatty Acid β-oxidation Deficient Cardiomyopathy

GSE266487 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2025/05/02 Platform GPL21493

At a glance

RNA-seq (gene expression) · mouse · 16 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: 16 samples: 5 × wild type vs 5 × CPT2H-KO vs 3 × CPT2 single KO vs 3 × CPT2/USP30 double KOGroups 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: Mitophagy mitigates mitochondrial fatty acid β-oxidation deficient cardiomyopathyNature communications · 2025

Summary (written by the submitters)

Cardiomyocytes rely on mitochondrial fatty acid β-oxidation (FAO) for ATP production in the healthy heart but can exhibit marked metabolic flexibility in response to diverse physiological circumstances. Mutations or deficiencies in FAO enzymes can lead to a spectrum of symptoms, ranging from muscle weakness to severe cardiomyopathy, and, in some instances, culminate in neonatal/infantile mortality.

Read the full summary ↓

It is generally believed that under FAO deficit, mitochondria encounter stress, potentially triggering the initiation of mitophagy, a process crucial for maintaining mitochondrial quality. We explored the link between FAO deficiency and mitophagy utilizing FAO-deficient mice generated through cardiomyocyte-specific deletion of the Carnitine Palmitoyltransferase 2 (CPT2). Intriguingly, our findings contradicted the prevailing hypothesis, revealing an unexpected decline in mitophagy in FAO-deficient hearts. Employing an integrated approach involving quantitative proteomics, metabolomics, and transcriptomics assays, we identified suppressed a PINK1/Parkin signaling pathway in CPT2-deficient heart tissues. Our study demonstrated that the loss of cardiac FAO impairs the PINK1 pathway by modulating the mitochondrial rhomboid protease PARL (presenilin-associated rhomboid-like protein). Furthermore, inhibiting USP30, a mitochondrial deubiquitinating enzyme antagonizing PINK1/Parkin function, restored cardiac mitophagy, thereby alleviating FAO-associated cardiac dysfunction. Notably, the deletion of USP30 conferred a significant survival advantage to FAO-deficient animals, doubling the median survival and substantially improving the maximum survival rate. The study unveiled a novel connection between FAO and PINK1-dependent mitophagy, presenting a potential therapeutic avenue for addressing FAO-deficient cardiomyopathies.

Published in

Mitophagy mitigates mitochondrial fatty acid β-oxidation deficient cardiomyopathy

Sun N, Barta H, Chaudhuri S et al. · Nature communications 2025 · PMID 40593619 · doi:10.1038/s41467-025-60670-z

This dataset

Open GSE266487 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 GSE266487_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 PRJNA1107282 and SRA study SRP505461. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40593619) ↗

Study design

5 × wild type vs 5 × CPT2H-KO vs 3 × CPT2 single KO vs 3 × CPT2/USP30 double KO

Supports a between-group comparison across 16 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 16 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

GSM8248034 wild type bio rep 1 wild type
GSM8248035 wild type bio rep 2 wild type
GSM8248036 wild type bio rep 3 wild type
GSM8248037 wild type bio rep 4 wild type
GSM8248038 wild type bio rep 5 wild type
GSM8248039 CPT2H-KO bio rep 1 CPT2H-KO
GSM8248040 CPT2H-KO bio rep 2 CPT2H-KO
GSM8248041 CPT2H-KO bio rep 3 CPT2H-KO
GSM8248042 CPT2H-KO bio rep 4 CPT2H-KO
GSM8248043 CPT2H-KO bio rep 5 CPT2H-KO
GSM8248044 CPT2 single KO bio rep 1 CPT2 single KO
GSM8248045 CPT2 single KO bio rep 2 CPT2 single KO
GSM8248046 CPT2 single KO bio rep 3 CPT2 single KO
GSM8248047 CPT2/USP30 double KO bio rep1 CPT2/USP30 double KO
GSM8248048 CPT2/USP30 double KO bio rep2 CPT2/USP30 double KO
GSM8248049 CPT2/USP30 double KO bio rep3 CPT2/USP30 double KO

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.