Roberts Justin T, Borchert Glen M
Department of Biology, University of South Alabama, Mobile, AL, 36688, USA.
Department of Pharmacology, University of South Alabama, Mobile, AL, 36688, USA.
Methods Mol Biol. 2017;1617:109-122. doi: 10.1007/978-1-4939-7046-9_8.
MicroRNA (miRNA) mediated silencing and repression of mRNA molecules requires complementary base pairing between the "seed" region of the miRNA and the "seed match" region of target mRNAs. While this mechanism is fairly well understood, accurate prediction of valid miRNA targets remains challenging due to factors such as imperfect sequence specificity, target site availability, and the thermodynamic stability of the mRNA structure itself. As knowledge of what genes are being targeted by each miRNA is arguably the most important facet of miRNA biology, many approaches have been developed to address the need for reliable prediction and ranking of putative targets, with most using a combination of various strategies such as evolutionary conservation, statistical inference, and distinct features of the target sequences themselves. This chapter reviews the pros and cons of a number of different prediction algorithms, showcases some databases that store experimentally validated miRNA targets, and also provides a case study that profiles some of the potential microRNA-mRNA interactions predicted by each methodology for various human genes.
微小RNA(miRNA)介导的mRNA分子沉默和抑制需要miRNA的“种子”区域与靶mRNA的“种子匹配”区域之间进行互补碱基配对。虽然这种机制已得到相当充分的理解,但由于诸如不完全的序列特异性、靶位点可用性以及mRNA结构本身的热力学稳定性等因素,准确预测有效的miRNA靶标仍然具有挑战性。鉴于了解每个miRNA靶向哪些基因可以说是miRNA生物学最重要的方面,人们已经开发了许多方法来满足可靠预测和对假定靶标进行排名的需求,其中大多数方法结合了各种策略,如进化保守性、统计推断以及靶序列本身的独特特征。本章回顾了多种不同预测算法的优缺点,展示了一些存储经过实验验证的miRNA靶标的数据库,还提供了一个案例研究,概述了每种方法针对各种人类基因预测的一些潜在微小RNA-信使核糖核酸相互作用。