Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.
Int J Mol Sci. 2022 Mar 28;23(7):3695. doi: 10.3390/ijms23073695.
Plant transcriptomes encompass a large number of functional non-coding RNAs (ncRNAs), only some of which have protein-coding capacity. Since their initial discovery, ncRNAs have been classified into two broad categories based on their biogenesis and mechanisms of action, housekeeping ncRNAs and regulatory ncRNAs. With advances in RNA sequencing technology and computational methods, bioinformatics resources continue to emerge and update rapidly, including workflow for in silico ncRNA analysis, up-to-date platforms, databases, and tools dedicated to ncRNA identification and functional annotation. In this review, we aim to describe the biogenesis, biological functions, and interactions with DNA, RNA, protein, and microorganism of five major regulatory ncRNAs (miRNA, siRNA, tsRNA, circRNA, lncRNA) in plants. Then, we systematically summarize tools for analysis and prediction of plant ncRNAs, as well as databases. Furthermore, we discuss the silico analysis process of these ncRNAs and present a protocol for step-by-step computational analysis of ncRNAs. In general, this review will help researchers better understand the world of ncRNAs at multiple levels.
植物转录组包含大量具有蛋白质编码能力的功能非编码 RNA(ncRNA)。自最初发现以来,ncRNA 根据其生物发生和作用机制被分为两大类,管家 ncRNA 和调节性 ncRNA。随着 RNA 测序技术和计算方法的进步,生物信息学资源不断涌现并快速更新,包括 ncRNA 分析的计算工作流程、最新平台、数据库和专门用于 ncRNA 鉴定和功能注释的工具。在这篇综述中,我们旨在描述五种主要调节性 ncRNA(miRNA、siRNA、tsRNA、circRNA、lncRNA)在植物中的生物发生、生物学功能以及与 DNA、RNA、蛋白质和微生物的相互作用。然后,我们系统地总结了用于分析和预测植物 ncRNA 的工具以及数据库。此外,我们还讨论了这些 ncRNA 的计算机分析过程,并提出了 ncRNA 计算分析的分步协议。总的来说,这篇综述将帮助研究人员从多个层面更好地理解 ncRNA 的世界。