Identification and characterization of circRNAs in the skin during wool follicle development in Aohan fine wool sheep

敖汉细毛羊毛囊发育过程中皮肤中环状RNA的鉴定与特性分析

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作者:Ranran Zhao, Nan Liu, Fuhui Han, Hegang Li, Jifeng Liu, Lanlan Li, Guoyi Wang, Jianning He

Background

Aohan fine wool sheep (AFWS) is a historically bred fine wool sheep, cultivated in China. The wool has excellent quality and good textile performance. Investigating the molecular mechanisms that regulate wool growth is important to improve wool quality and yield. Circular RNAs (circRNAs) are widely expressed non-coding RNAs that can act as competitive endogenous RNAs (ceRNAs) to bind to miRNAs. Although circRNAs have been studied in many fields, research on their activity in sheep wool follicles is limited. To understand the regulation of circRNAs in the growth of fine wool in sheep, we used RNA-Seq to identify circRNAs in sheep shoulder skin samples at three developmental stages: embryonic day 90 (E90d), embryonic day 120 (E120d), and at birth (Birth).

Conclusion

Our results provide more information about circRNAs regulation of wool follicle development in AFWS, and establish a solid foundation for future research.

Results

We identified 8753 circRNAs and found that 918 were differentially-expressed. We then analyzed the classification and characteristic of the circRNAs in sheep shoulder skin. Using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), we identified the source genes of circRNAs, which were mainly enriched in cellular component organization, regulation of primary metabolic processes, tight junctions, and the cGMP-PKG and AMPK signaling pathways. In addition, we predicted interactions between 17 circRNAs and eight miRNAs, using miRanda software. Based on the significant pathways, we speculate that circ_0005720, circ_0001754, circ_0008036, circ_0004032, circ_0005174, circ_0005519, and circ_0007826 might play an important role in regulating wool follicle growth in AFWS. Seven circRNAs were randomly selected to validate the RNA-Seq results, using qRT-PCR.

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