Discovery of novel and differentially expressed microRNAs between fetal and adult backfat in cattle
The posttranscriptional gene regulation mediated by microRNA (miRNA) plays an important role in various species. Recently, a large number of miRNAs and their expression patterns have been identified. However, to date, limited miRNAs have been reported to modulate adipogenesis and lipid deposition in beef cattle. Total RNAs from Chinese Qinchuan bovine backfat at fetal and adult stages were used to construct small RNA libraries for Illumina next-generation sequencing. A total of 13,915,411 clean reads were obtained from a fetal library and 14,244,946 clean reads from an adult library. In total, 475 known and 36 novel miRNA candidates from backfat were identified. The nucleotide bias, base editing, and family of the known miRNAs were also analyzed. Based on stem-loop qPCR, 15 specific miRNAs were detected, and the results showed that bta-miRNAn25 and miRNAn26 were highly expressed in backfat tissue, suggesting these small RNAs play a role in the development and maintenance of bovine subcutaneous fat tissue. Putative targets for miRNAn25 and miRNAn26 were predicted, and the 61 most significant target transcripts were related to lipid and fatty acid metabolism. Of interest, the canonical pathway and gene networks analyses revealed that PPARa/RXRa activation and LXR/RXR activation were important components of the gene interaction hierarchy results. In the present study, we explored the backfat miRNAome differences between cattle of different developmental stages, expanding the expression repertoire of bovine miRNAs that could contribute to further studies on the fat development of cattle. The expression analysis of the differential target genes of miRNAn25 and miRNAn26 showed potential gene networks that affect lipid and fatty acid metabolism. These results may help in the design of new intervention strategies to improve beef quality. Overall design: Examination of Chinese Qinchuan bovine backfat miRNAs by deep sequencing.