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Skeletal muscle mRNA expression in 25 mice with or without genetic defects of mitochondrial fatty acid oxidation (Acadl and Acadvl knockout) using RNA sequencing.

GSE186648 Mus musculus (mouse) RNA-seq (gene expression) 25 samples Submitted 2024/10/26 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 25 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
25 samples: 22 distinct titles, 3 of them repeatedGroups 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
A Multiomic Network Approach to Uncover Disease Modifying Mechanisms of Inborn Errors of MetabolismJournal of inherited metabolic disease · 2025
Summary (written by the submitters)
A mitochondrial long-chain fatty acid oxidation defect leads to dysregulation of plasma long-chain acyl carnitines, dysregulation of plasma amino acids, and an increased reliance on glucocorticoid signaling to maintain euglycemia during fasting. [muscle] Skeletal muscle tissue relies on products of fatty acid oxidation (FAO) during conditions of metabolic stress: fasting, prolonged exercise, febrile illness.
Read the full summary ↓
Fasting-induced hypoglycemia and rhabdomyolysis are characteristic features of FAO disorders including very long chain acyl-CoA dehydrogenase (VLCAD) deficiency (VLCADD). However, the pathophysiological mechanisms that underlie the connection between FAO dysfunction and skeletal muscle dysfunction are not known. Here, we investigated the transcriptional response in skeletal muscle tissue (gastrocnemius) to the FAO defect in a model of VLCADD: the long-chain acyl-CoA dehydrogenase (LCAD) knockout (KO) mouse. We found that differentially expressed genes in the muscle were associated with molecular networks annotated for the cellular response to starvation from population-based models. To validate the association between the starvation response and FAO, we pharmacologically inhibited both glucocorticoid signaling and FAO in a model of fasting and observed that mice depleted in both pathways lost less weight during fasting and became hypoglycemic. These findings implicate glucocorticoid signaling as a candidate modifier of the cellular response to starvation in muscle tissue in the context of FAO disorders including VLCADD.
Published in
A Multiomic Network Approach to Uncover Disease Modifying Mechanisms of Inborn Errors of Metabolism
Bender A, Ranea-Robles P, Williams EG et al. · Journal of inherited metabolic disease 2025 · PMID 40443299 · doi:10.1002/jimd.70045
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 GSE186648_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 PRJNA774965 and SRA study SRP343392. Searching any of these in the dataset finder brings you back here.

Study design
22 distinct titles, 3 of them repeated
gastroc.KO.Het.VL23 ×2 gastroc.WT.WT.VL26 ×2 gastroc.WT.WT.VL38 ×2

How we read this: Read from 25 sample titles: 22 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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