Transcriptome Analysis Reveals the Profile of Long Non-Coding RNAs during Myogenic Differentiation in Goats.
Chenyu YangXinyi ZhouYanan XueDandan LiLinjie WangTao ZhongDinghui DaiJiaxue CaoJiazhong GuoLi LiHong-Ping ZhangSiyuan ZhanPublished in: International journal of molecular sciences (2023)
The long non-coding RNAs (lncRNAs) are emerging as essential regulators of the growth and development of skeletal muscles. However, little is known about the expression profiles of lncRNAs during the proliferation and differentiation of skeletal muscle satellite cells (MuSCs) in goats. In this study, we investigate potential regulatory lncRNAs that govern muscle development by performing lncRNA expression profiling analysis during the proliferation (cultured in the growth medium, GM) and differentiation (cultured in the differentiation medium, DM1/DM5) of MuSCs. In total, 1001 lncRNAs were identified in MuSC samples, and 314 differentially expressed (DE) (FDR < 0.05, |log2FC| > 1) lncRNAs were screened by pairwise comparisons from three comparison groups (GM-vs-DM1, GM-vs-DM5, DM1-vs-DM5). Moreover, we identified the cis-, trans-, and antisense-regulatory target genes of DE lncRNAs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that these target genes were significantly enriched in muscle development-related GO terms and KEGG pathways. In addition, the network of interactions between DE lncRNAs and their target genes was identified, which included well-known myogenesis regulators such as Myogenic differentiation 1 (MyoD), Myogenin (MyoG), and Myosin heavy chain (MyHC). Meanwhile, competing endogenous RNA (ceRNA) network analysis showed that 237 DE lncRNAs could bind to 329 microRNAs (miRNAs), while miRNAs could target 564 mRNAs. Together, our results provide a genome-wide resource of lncRNAs that may contribute to myogenic differentiation in goats and lay the groundwork for future investigation into their functions during skeletal muscle development.
Keyphrases
- genome wide identification
- network analysis
- skeletal muscle
- genome wide analysis
- transcription factor
- long non coding rna
- genome wide
- dna methylation
- poor prognosis
- insulin resistance
- endothelial cells
- glycemic control
- signaling pathway
- type diabetes
- risk assessment
- bioinformatics analysis
- oxidative stress
- cell proliferation