A Circular RNA Generated from Nebulin (NEB) Gene Splicing Promotes Skeletal Muscle Myogenesis in Cattle as Detected by a Multi-Omics Approach.
Kongwei HuangZhipeng LiDandan ZhongYufeng YangXiuying YanTong FengXiaobo WangLiyin ZhangXinyue ShenMengjie ChenXier LuoKuiqing CuiJieping HuangSaif Ur RehmanYu JiangDeshun ShiAlfredo PauciulloXiangfang TangQingyou LiuHui LiPublished in: Advanced science (Weinheim, Baden-Wurttemberg, Germany) (2023)
Cattle and the draught force provided by its skeletal muscle have been integral to agro-ecosystems of agricultural civilization for millennia. However, relatively little is known about the cattle muscle functional genomics (including protein coding genes, non-coding RNA, etc.). Circular RNAs (circRNAs), as a new class of non-coding RNAs, can be effectively translated into detectable peptides, which enlightened us on the importance of circRNAs in cattle muscle physiology function. Here, RNA-seq, Ribosome profiling (Ribo-seq), and peptidome data are integrated from cattle skeletal muscle, and detected five encoded peptides from circRNAs. It is further identified and functionally characterize a 907-amino acids muscle-specific peptide that is named circNEB-peptide because derived by the splicing of Nebulin (NEB) gene. This peptide localizes to the nucleus and cytoplasm and directly interacts with SKP1 and TPM1, key factors regulating physiological activities of myoblasts, via ubiquitination and myoblast fusion, respectively. The circNEB-peptide is found to promote myoblasts proliferation and differentiation in vitro, and induce muscle regeneration in vivo. These findings suggest circNEB-peptide is an important regulator of skeletal muscle regeneration and underscore the possibility that more encoding polypeptides derived by RNAs currently annotated as non-coding exist.
Keyphrases
- skeletal muscle
- single cell
- rna seq
- insulin resistance
- amino acid
- genome wide
- stem cells
- climate change
- genome wide identification
- copy number
- risk assessment
- signaling pathway
- small molecule
- metabolic syndrome
- binding protein
- adipose tissue
- gene expression
- human health
- machine learning
- big data
- protein protein
- quality control
- high throughput sequencing