Genome-Wide Atlas of Promoter Expression Reveals Contribution of Transcribed Regulatory Elements to Genetic Control of Disuse-Mediated Atrophy of Skeletal Muscle

Abstract

The prevention of muscle atrophy carries with it clinical significance for the control of increased morbidity and mortality following physical inactivity. While major transcriptional events associated with muscle atrophy-recovery processes are the subject of active research on the gene level, the contribution of non-coding regulatory elements and alternative promoter usage is a major source for both the production of alternative protein products and new insights into the activity of transcription factors. We used the cap-analysis of gene expression (CAGE) to create a genome-wide atlas of promoter-level transcription in fast (m. EDL) and slow (m. soleus) muscles in rats that were subjected to hindlimb unloading and subsequent recovery. We found that the genetic regulation of the atrophy-recovery cycle in two types of muscle is mediated by different pathways, including a unique set of non-coding transcribed regulatory elements. We showed that the activation of “shadow” enhancers is tightly linked to specific stages of atrophy and recovery dynamics, with the largest number of specific regulatory elements being transcriptionally active in the muscles on the first day of recovery after a week of disuse. The developed comprehensive database of transcription of regulatory elements will further stimulate research on the gene regulation of muscle homeostasis in mammals.

Special Issue on Differential Gene Expression and Coexpression

“…Yoon et al [ 2 ] revealed that high levels of procollagen C-endopeptidase enhancer 2 (PCOLCE2) in Tonsil-Derived Mesenchymal Stem Cells (TMSCs) were highly effective in potentiating ROS generation in co-cultured differentiated HL-60 (dHL-60) cells through an RNA-seq-based DGEA. By performing CAGE-seq on two types of atrophic rat muscle samples and through a bioinformatics pipeline centred on Transcription Start Site (TSS) analysis, Pintus et al [ 3 ] identified non-coding transcribed regulatory elements controlling the skeletal muscle disuse-mediated atrophy. Otálora-Otálora et al [ 4 ] used a bioinformatics workflow which includes differential expression, and coexpression network and coregulatory network analyses of microarray samples to discover possible unique lung cancer biomarkers, as well as possible common biomarkers in tumours (lung, breast, and leukaemia).…”