Single-nucleotide resolution profiling reveals dynamic and site-specific m⁶A regulation during human myogenesis

BackgroundMyogenic differentiation of muscle stem cells required for skeletal muscle growth and regeneration relies on the precise spatiotemporal coordination of multiple gene-expression programs. Over the past decades, considerable progress has been made in defining the transcriptional networks that govern myogenesis. In particular, myogenic transcription factors integrate extrinsic and intrinsic cues to drive skeletal muscle development and regeneration. In contrast, post-transcriptional layers of regulation have remained comparatively underexplored. Among these, the epitranscriptome - comprising more than 170 chemical RNA modifications - has recently emerged as a major regulatory axis in cellular differentiation. N-methyladenosine (mA), the most abundant internal modification of mRNA, is now recognized as a key regulator of stem-cell fate decisions across multiple biological systems. By dynamically modulating RNA stability, translation, and other processing steps, mA enables precise fine-tuning of gene-expression programs in response to physiological cues. These effects are mediated through mA-binding RNA-binding proteins (RBPs), also referred to as "readers", which selectively recognize methylated transcripts and translate the modification into functional cellular outcomes. Despite its central role in other tissue contexts, the contribution of mA to skeletal muscle physiology - and particularly to human muscle stem cell biology - remains poorly characterized. This gap represents a critical and largely unexplored frontier in muscle biology. MethodsTo define the epitranscriptome landscape during the myogenic differentiation of human skeletal muscle cells, we performed GLORI on proliferating and differentiated human primary myoblasts. This recently developed approach enables detection of mA at single-nucleotide resolution together with quantitative measurement of methylation stoichiometry at individual sites. mA-modified positions were mapped across the transcriptome in both cellular states and integrated with matched RNA-seq datasets data to contextualise mA features relative to transcript abundance. To place these findings in a broader context, we compared our human mA maps with previously published mouse muscle cell datasets and overlaid them with available CLIP-seq datasets of mA RNA-binding proteins. ResultsWe identified tens of thousands of high-confidence mA sites in proliferating and differentiated human myogenic cells. While many sites were shared between states, myogenic differentiation was accompanied by epitranscriptomic remodeling, affecting both the distribution and stoichiometry of mA marks. Transcripts exhibiting differential mA regulation were enriched for pathways related to myogenic development, cytoskeletal remodeling, signalling, nucleic-acid-associated processes and energy metabolism. Joint analysis of mA site number, methylation stoichiometry, and expression levels indicated the presence of distinct mA regulatory frameworks at the transcript level. Genes associated with myogenesis and regulatory pathways were distributed across these categories, consistent with the coexistence of multiple regulatory programs during myogenic differentiation. In addition, cross-species comparisons revealed the presence of human-specific methylation patterns. Integration with published mA RNA-binding protein datasets uncovered distinct subsets of mA sites with varying binding profiles, suggesting state-dependent interpretation of mA marks. Together, these data constitute, to our knowledge, the first single-nucleotide-resolution atlas of mA methylation in human skeletal muscle, revealing a previously uncharacterized epitranscriptomic landscape and providing a foundational resource for studies of human myogenesis.