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Deletion of P311 enhances regeneration in aged skeletal muscle

GSE329069 Mus musculus (mouse) Single-cell RNA-seq 9 samples Submitted 2026/06/01 Platform GPL34290
At a glance

Single-cell RNA-seq · mouse · 9 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. 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
9 samples: 3 × Muscle_old_KO vs 3 × Muscle_old_WT vs 3 × Muscle_young_WTGroups 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.
Summary (written by the submitters)
While aging results in marked decreases in the capacity of skeletal muscle to repair following injury, as well as increases in fibrosis, the pathways and factors that regulate these processes are poorly defined. P311/Nrep (P311) is a highly conserved protein known to promote fibrosis through TGF-beta production in non-muscle tissues. Considering the over-production of TGF-beta in aged muscle, especially in the context of regeneration, we aimed to determine if the loss of P311 would enhance aged muscle regeneration.
Read the full summary ↓
To test this hypothesis, we utilized a chemical injury (BaCl2) model to injure the tibialis anterior (TA) muscle in young (4-7 months) and old (24 months) wild-type and global P311 knockout mice (P311-/-). In wild-type mice, P311 expression increased in response to injury in young muscle and to an even greater extent in aged muscle. P311-deficiency decreased TGF-β production, particularly in old muscle tissue. P311-deficiency also decreased fibrosis in old mice, including improved histology and reductions in fibrotic gene markers. Regeneration as assessed by fiber regrowth and force generation was increased in old mice with P311-deficiency, and genetic programs that drive skeletal muscle regeneration were enriched in old P311-/- mice relative to old wild-type mice. Single-cell transcriptomic analysis revealed P311 was found to be highly expressed in skeletal muscle fibroblast and fibroadipogenic progenitor (FAP) populations. The loss of P311 in aged muscle FAPs was sufficient to reduce their fibrogenic capacity. These findings establish P311 as a therapeutic target to enhance aged muscle regeneration through reductions in fibrosis and related fibrogenic pathways.
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 GSE329069_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: 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 PRJNA1457493 and SRA study SRP694587. Searching any of these in the dataset finder brings you back here.

Study design
3 × Muscle_old_KO vs 3 × Muscle_old_WT vs 3 × Muscle_young_WT

Supports a between-group comparison across 9 samples.

How we read this: 3 replicated groups read from 9 sample titles; they account for 9 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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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.