Author:
Chen Weihao,Gu Xinyu,Lv Xiaoyang,Cao Xiukai,Yuan Zehu,Wang Shanhe,Sun Wei
Abstract
Sheep milk production is a dynamic and multifactorial trait regulated by diverse biological mechanisms. To improve the quality and production of sheep milk, it is necessary to understand the underlying non-coding transcriptomic mechanisms. In this study, ribonucleic acid-sequencing (RNA-seq) was used to profile the expression of microRNAs (miRNAs) and circular RNAs (circRNAs) in the sheep mammary gland at three key lactation time points (perinatal period, PP; early lactation, EL; and peak lactation, PL). A total of 2,369 novel circRNAs and 272 miRNAs were profiled, of which 348, 373, and 36 differentially expressed (DE) circRNAs and 30, 34, and 7 DE miRNAs were detected in the comparison of EL vs. PP, PL vs. PP, and PL vs. EL, respectively. A series of bioinformatics analyses including functional enrichment, machine learning prediction, and competing endogenous RNA (ceRNA) network analyses were conducted to identify subsets of the potential candidate miRNAs (e.g., oar_miR_148a, oar_miR_362, and oar_miR_432) and circRNAs (e.g., novel_circ_0011066, novel_circ_0010460, and novel_circ_0006589) involved in sheep mammary gland development. Taken together, this study offers a window into the dynamics of non-coding transcriptomes that occur during sheep lactation and may provide further insights into miRNA and circRNA that influence sheep mammary gland development.
Funder
National Natural Science Foundation of China
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献