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Dissecting the Role of Myf6 in Facilitating Fibroblast Conversion into Myogenic Progenitor and Differentiated Cells [RNA-Seq]

GSE291101 Mus musculus (mouse) RNA-seq (gene expression) 77 samples Submitted 2026/03/04 Platform GPL24247Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 77 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
77 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.
Summary (written by the submitters)
Conversion of fibroblasts into skeletal muscle cells by overexpression of the transcription factor MyoD has been widely employed over past decades in a multitude of experimental settings. However, the potential of additional myogenic regulatory factors such as Myf5, Myf6 and Myog to elicit a myogenic conversion has been significantly less studied.
Read the full summary ↓
To address this disparity, we set out to investigate the role of MRFs in fibroblast conversion into skeletal muscle stem and differentiated cells. Surprisingly, we found that Myf6, a transcription factor associated with postnatal late-stage myogenesis, efficiently converted fibroblasts into myotubes alone, or alternatively into expandable Pax7-expressing induced myogenic progenitor cells (iMPCs) in the presence of defined small molecules. To investigate reprogramming dynamics in a tightly regulated system, we generated an inducible Myf6 overexpression transgenic mouse model, which enabled dissection of transcription and epigenetic dynamics unique to iMPC formation. Mechanistically, we characterized the chromatin binding of Myf6, as well as its protein binding partners, during iMPC reprogramming and conventional transdifferentiation, revealing shared and different targets and binding partners. To further investigate its role, we surprisingly found that endogenous Myf6 is dispensable for iMPC formation by MyoD and small molecules. In accordance with this observation, we demonstrated that subjecting MyoD-KO fibroblasts to reprogramming with Myf6 and small molecules gave rise to expandable MyoD-KO iMPCs, indicating that MyoD is similarly dispensable for iMPC formation and self-renewal. Multi-omics analyses of Myf6-derived MyoD-KO iMPCs uncovered upregulated genes that compensated for the lack of MyoD, whose downregulation during iMPC production mitigated Pax7 expression, highlighting their roles as reprogramming regulators. Collectively, these results illustrate a redundancy between MRFs’ function in myogenic cellular conversions, highlighting an unexpected potency for Myf6 in the induction of a muscle stem cell fate in vitro.
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 GSE291101_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 PRJNA1231557 and SRA study SRP567910. Searching any of these in the dataset finder brings you back here.

Samples in this study

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