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PGC-1alpha pathway dysregulation disrupts myofiber specification in a mouse model of SBMA

GSE329198 Mus musculus (mouse) Single-nucleus RNA-seq 14 samples Submitted 2026/05/01 Platform GPL34328
At a glance

Single-nucleus RNA-seq · mouse · 14 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). Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
14 samples: 4 × R62.dz vs 4 × R62.WT vs 3 × SCA1.WT vs 2 × SCA1.dzGroups 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
PGC-1α pathway dysregulation disrupts myofiber specification in a mouse model of SBMAJCI insight · 2026
Summary (written by the submitters)
Skeletal muscle pathology is a critical but poorly understood contributor to neuromuscular degeneration in spinal and bulbar muscular atrophy (SBMA), a CAG/polyglutamine (polyQ) expansion disorder caused by mutation in the androgen receptor (AR). Using a gene-targeted SBMA mouse model, we applied single-nucleus RNA sequencing to identify a previously unrecognized, disease-specific population of skeletal muscle myonuclei that replace normal myonuclear subtypes.
Read the full summary ↓
This transition was driven by dysregulation of the PGC-1α pathway, a central regulator of myofiber specification and metabolic identity. PGC-1α dysfunction in SBMA muscle was age-, hormone-, and polyQ length–dependent and was partially rescued by subcutaneous delivery of AR-targeted antisense oligonucleotides. Integrated ChIP-seq and RNA-seq analyses revealed that aberrant PGC-1α activity promoted the expression of a distinct set of myofiber specification genes while downregulating those defining healthy Type IIb and Type IIx myonuclei. We propose a model in which this dysfunction arose downstream of polyQ-mediated sequestration of PGC-1α cofactors MEF2, CREB, and CBP, leading to transcriptional reprogramming and cellular dysfunction. These findings implicate PGC-1α dysregulation as a key event linking AR polyQ expansion to skeletal muscle degeneration and suggest a shared mechanism for polyQ-mediated muscle pathology across related neurodegenerative diseases.
Published in
PGC-1α pathway dysregulation disrupts myofiber specification in a mouse model of SBMA
Kuo CJ, Chopp LB, Yu Z et al. · JCI insight 2026 · PMID 42096288 · doi:10.1172/jci.insight.203215
This dataset
Open GSE329198 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 GSE329198_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 PRJNA1458138 and SRA study SRP695245. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42096288) ↗
Study design
4 × R62.dz vs 4 × R62.WT vs 3 × SCA1.WT vs 2 × SCA1.dz

Supports a between-group comparison across 13 samples.

How we read this: 4 replicated groups read from 14 sample titles; they account for 13 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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