GEO series

A Mechanistic basis of fast myofiber vulnerability in neuromuscular diseases [snRNA-seq]

GSE298187 Mus musculus (mouse) Single-nucleus RNA-seq 2 samples Submitted 2025/05/29 Platform GPL30172

At a glance

Single-nucleus RNA-seq · mouse · 2 samples

What it is: Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue).
Organism: Mus musculus (mouse)
Samples: 2 samples
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 mechanistic basis of fast myofiber vulnerability to neuromuscular diseasesCell reports · 2025

Summary (written by the submitters)

Skeletal muscle denervation is a characteristic feature of neuromuscular diseases such as amyotrophic lateral sclerosis (ALS) and sarcopenia, leading to atrophy, loss of muscle strength, and poor patient outcomes. Myofibers are typically classified into slow oxidative and fast glycolytic types based on their contractile and metabolic properties.

Read the full summary ↓

Neuromuscular diseases predominantly affect fast myofibers, while slow myofibers are relatively spared. However, the mechanisms underlying the heightened susceptibility of fast myofibers to disease and atrophy remain unclear. To investigate this, we analyzed the transcriptional profiles of innervated and denervated myonuclei. Our findings revealed that the fast muscle gene program and the transcription factor Maf are repressed during denervation. Notably, overexpression of Maf in the skeletal muscles of mice prevented loss of muscle mass and myofiber atrophy caused by denervation. Single-nucleus RNA sequencing and ATAC sequencing demonstrated that Maf overexpression reprogrammed denervated myonuclei by repressing atrophic gene programs and reactivating fast muscle gene expression. Similar repression of fast muscle genes and Maf was observed in muscles from mice and humans with ALS. Consistent with these findings, Maf overexpression in human skeletal muscle cells induced the expression of fast muscle genes while suppressing atrophic gene expression. Our findings highlight a key role for Maf in maintaining muscle mass and demonstrate that its repression contributes to the progression of neuromuscular diseases in both mice and humans. Modulating Maf activity could offer a promising therapeutic strategy to preserve skeletal muscle function during disease, aging, or injury.

Published in

A mechanistic basis of fast myofiber vulnerability to neuromuscular diseases

Dos Santos M, Bezprozvannaya S, McAnally JR et al. · Cell reports 2025 · PMID 40632651 · doi:10.1016/j.celrep.2025.115959

This dataset

Open GSE298187 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 GSE298187_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1268492 and SRA study SRP587901. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40632651) ↗

Samples in this study

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+ 2 more — browse all 2 samples with per-sample file links →

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