Myf6/MRF4 is a myogenic niche regulator required for the maintenance of the muscle stem cell pool.

The function and maintenance of muscle stem cells (MuSCs) are tightly regulated by signals originating from their niche environment. Skeletal myofibers are a principle component of the MuSC niche and are in direct contact with the muscle stem cells. Here, we show that Myf6 establishes a ligand/receptor interaction between muscle stem cells and their associated muscle fibers. Our data show that Myf6 transcriptionally regulates a broad spectrum of myokines and muscle-secreted proteins in skeletal myofibers, including EGF. EGFR signaling blocks p38 MAP kinase-induced differentiation of muscle stem cells. Homozygous deletion of Myf6 causes a significant reduction in the ability of muscle to produce EGF, leading to a deregulation in EGFR signaling. Consequently, although Myf6-knockout mice are born with a normal muscle stem cell compartment, they undergo a progressive reduction in their stem cell pool during postnatal life due to spontaneous exit from quiescence. Taken together, our data uncover a novel role for Myf6 in promoting the expression of key myokines, such as EGF, in the muscle fiber which prevents muscle stem cell exhaustion by blocking their premature differentiation.

High-resolution genome-wide expression analysis of single myofibers using SMART-Seq.

Skeletal muscle is a heterogeneous tissue. Individual myofibers that make up muscle tissue exhibit variation in their metabolic and contractile properties. Although biochemical and histological assays are available to study myofiber heterogeneity, efficient methods to analyze the whole transcriptome of individual myofibers are lacking. Here, we report on a single-myofiber RNA-sequencing (smfRNA-Seq) approach to analyze the whole transcriptome of individual myofibers by combining single-fiber isolation with Switching Mechanism at 5' end of RNA Template (SMART) technology. Using smfRNA-Seq, we first determined the genes that are expressed in the whole muscle, including in nonmyogenic cells. We also analyzed the differences in the transcriptome of myofibers from young and old mice to validate the effectiveness of this new method. Our results suggest that aging leads to significant changes in the expression of metabolic genes, such as Nos1, and structural genes, such as Myl1, in myofibers. We conclude that smfRNA-Seq is a powerful tool to study developmental, disease-related, and age-related changes in the gene expression profile of skeletal muscle.