ABSTRACT
A majority of human genes produce non-protein-coding RNA (ncRNA), and some have roles in development and disease. Neither ncRNA nor human skeletal muscle is ideally studied using short-read sequencing, so we used a customised RNA pipeline and network modelling to study cell-type specific ncRNA responses during muscle growth at scale. We completed five human resistance-training studies (n=144 subjects), identifying 61% who successfully accrued muscle-mass. We produced 288 transcriptome-wide profiles and found 110 ncRNAs linked to muscle growth in vivo, while a transcriptome-driven network model demonstrated interactions via a number of discrete functional pathways and single-cell types. This analysis included established hypertrophy-related ncRNAs, including CYTOR – which was leukocyte-associated (FDR = 4.9 x10-7). Novel hypertrophy-linked ncRNAs included PPP1CB-DT (myofibril assembly genes, FDR = 8.15 x 10-8), and EEF1A1P24 and TMSB4XP8 (vascular remodelling and angiogenesis genes, FDR = 2.77 x 10-5). We also discovered that hypertrophy lncRNA MYREM shows a specific myonuclear expression pattern in vivo. Our multi-layered analyses established that single-cell-associated ncRNA are identifiable from bulk muscle transcriptomic data and that hypertrophy-linked ncRNA genes mediate their association with muscle growth via multiple cell types and a set of interacting pathways.
One Sentence Summary We used an optimised transcriptomic strategy to identify a set of ncRNA genes regulated during skeletal muscle hypertrophy in one hundred and forty-four people, with network modelling and spatial imaging providing biological context.
Competing Interest Statement
SMP reports grants or research contracts from the US National Dairy Council, Canadian Institutes for Health Research, Cargill, Friesland Campina, Dairy Farmers of Canada, Roquette Freres, Ontario Center of Innovation, Nestle Health Sciences, National Science and Engineering Research Council, and the US NIH during the conduct of the study; personal fees from Nestle Health Sciences; and nonfinancial support from Enhanced Recovery, outside the submitted work. SMP holds patents licensed to Exerkine but reports no financial gains from patents or related work. All other authors report no conflicts of interest.
Footnotes
↵* Joint senior authors
The manuscript has been revised to address referee comments at the journal for which this manuscript has been submitted to. The largest revision pertains to our recent discovery that there was a fault with one R packaged used in the original submission (aPEAR), it yielded a false negative result, and so replaced its use with ClusterProfiler, which directly compares common components of module gene lists. This analysis generated new network based pathway statistics establishing that our discrete set of ncRNA containing modules actually represented numerous interrelated biological functions (qvalue threshold of 1%). We propose that this analysis greatly enhances the level of evidence, over and above our original submission, that tissue growth related ncRNA modules interact via discrete cell types and pathways that we identified using other methods in the manuscript.