GEO series

A cellular cross-species RNA-seq atlas captures the transcriptional dynamics of myogenesis

GSE324958 Homo sapiens (human) Single-cell RNA-seq 24 samples Submitted 2026/03/16 Platform GPL24676Platform GPL24247

At a glance

Single-cell RNA-seq · human · 24 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: Homo sapiens (human)
Samples: 24 samples: 6 conditions, mostly with about 4 replicates eachGroups 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)

Skeletal muscle formation and regeneration is a tightly regulated process involving extensive transcriptional reprogramming as proliferating myoblasts fuse into mature myotubes. However, a comparative comprehensive analysis of the transcriptional landscape of humans and mouse myogenesis is missing. Here, we present a high-quality RNA-sequencing dataset profiling this transition in both mouse (C2C12) and human (LHCN-M2) myogenic cells.

Read the full summary ↓

Samples were collected from proliferating myoblasts, the early differentiation phase, and from mature myocytes using identical protocols, ensuring stringent comparability. This unified dataset captures the major transcriptional shifts occurring in myoblasts, marking the onset of differentiation. Quality metrics, including PCA, read distribution, and clustering, confirmed high internal consistency across samples and species. Comparative analyses revealed shared global features of myogenesis but also distinct regulatory trajectories. Human differentiation showed early upregulation followed by suppression of metabolic and stress-related pathways, while structural and ECM-associated programs remained persistently elevated. In contrast, mouse C2C12 cells displayed early inflammatory activation and later enrichment of metabolic and contractile pathways typical of mature myotubes. Ortholog-based integration demonstrated decreasing cross-species correlation over time, indicating progressive reinforcement of species-specific differentiation programs. We additionally compared this bulk RNA-seq with tissue-derived myotubes from single-cell muscle datasets to determine which transcriptional programs are conserved in the in vitro models or which emerge only in vivo. This analysis delineates the conserved and context-specific features of myogenesis, identifying pathways that reflect culture-specific artifacts in both human and mouse muscle cells.

This dataset

Open GSE324958 in finder → Find more 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 GSE324958_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 PRJNA1438151 and SRA study SRP684092. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

6 conditions, mostly with about 4 replicates each

C2C12, day0 ×4 C2C12, day1 ×4 C2C12, day6 ×4 LHCNM2, day0 ×4 LHCNM2, day1 ×4 LHCNM2, day12 ×4

Supports a between-group comparison across 24 samples.

How we read this: 6 replicated groups read from 24 sample titles; they account for 24 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

GSM9589326 C2C12, day0-1 C2C12, day0
GSM9589327 C2C12, day0-2 C2C12, day0
GSM9589328 C2C12, day0-3 C2C12, day0
GSM9589329 C2C12, day0-4 C2C12, day0
GSM9589330 C2C12, day1-1 C2C12, day1
GSM9589331 C2C12, day1-2 C2C12, day1
GSM9589332 C2C12, day1-3 C2C12, day1
GSM9589333 C2C12, day1-4 C2C12, day1
GSM9589334 C2C12, day6-1 C2C12, day6
GSM9589335 C2C12, day6-2 C2C12, day6
GSM9589336 C2C12, day6-3 C2C12, day6
GSM9589337 C2C12, day6-4 C2C12, day6
GSM9589338 LHCNM2, day0-1 LHCNM2, day0
GSM9589339 LHCNM2, day0-2 LHCNM2, day0
GSM9589340 LHCNM2, day0-3 LHCNM2, day0
GSM9589341 LHCNM2, day0-4 LHCNM2, day0
GSM9589342 LHCNM2, day1-1 LHCNM2, day1
GSM9589343 LHCNM2, day1-2 LHCNM2, day1
GSM9589344 LHCNM2, day1-3 LHCNM2, day1
GSM9589345 LHCNM2, day1-4 LHCNM2, day1
GSM9589346 LHCNM2, day12-1 LHCNM2, day12
GSM9589347 LHCNM2, day12-2 LHCNM2, day12
GSM9589348 LHCNM2, day12-3 LHCNM2, day12
GSM9589349 LHCNM2, day12-4 LHCNM2, day12

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