Transcriptome-wide analysis of RNA m6A methylation regulation of muscle development in Queshan Black pigs

BackgroundN(6)-methyladenosine (m(6)A) refers to the methylation modification of N-6 position of RNA adenine, a dynamic reversible RNA epigenetic modification that plays an important regulatory role in a variety of life processes. In this study, we used MeRIP-Seq and RNA-Seq of the longissimus dorsi (LD) muscle of adult (QA) and newborn (QN) Queshan Black pigs to screen key genes with m(6)A modification involved in muscle growth by bioinformatics analysis. ResultsA total of 23,445 and 25,465 m(6)A peaks were found in the whole genomes of QA and QN, respectively. Among them, 613 methylation peaks were significantly different (DMPs) and 579 genes were defined as differentially methylated genes (DMGs). Compared with the QN group, there were 1,874 significantly differentially expressed genes (DEGs) in QA group, including 620 up-regulated and 1,254 down-regulated genes. In order to investigate the relationship between m(6)A and mRNA expression in the muscle of Queshan Black pigs at different periods, a combined analysis of MeRIP-Seq and RNA-Seq showed that 88 genes were significantly different at both levels. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes results showed that DEGs and DMGs were mainly involved in skeletal muscle tissue development, FoxO signaling pathway, MAPK signaling pathway, insulin signaling pathway, PI3K-Akt signaling pathway, and Wnt signaling pathway. Four DEGs (IGF1R, CCND2, MYOD1 and FOS) and four DMGs (CCND2, PHKB, BIN1 and FUT2), which are closely related to skeletal muscle development, were selected as candidate genes for verification, and the results were consistent with the sequencing results, which indicated the reliability of the sequencing results. ConclusionsThese results lay the foundation for understanding the specific regulatory mechanisms of growth in Queshan Black pigs, and provide theoretical references for further research on the role of m(6)A in muscle development and breed optimization selection.