植物 miRNA 靶标的计算预测

Computational prediction of plant miRNA targets.

作者信息

Sun Ying-Hsuan, Lu Shanfa, Shi Rui, Chiang Vincent L

机构信息

Forest Biotechnology Group, Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC 27695-7247, USA.

出版信息

Methods Mol Biol. 2011;744:175-86. doi: 10.1007/978-1-61779-123-9_12.

DOI:10.1007/978-1-61779-123-9_12

PMID:21533693

Abstract

MicroRNAs (miRNAs) are a specific class of 21-nt small RNAs. They regulate the expression of specific target genes by various types of post-transcriptional regulation mechanisms, such as transcript cleavage and translation suppression. The biological function of an miRNA is therefore intimately associated with the function of their target genes. Target gene identification becomes an essential step towards understanding miRNA functions. In this protocol, we describe a computational procedure for plant miRNA target prediction. It involves two key steps: (1) search of transcript sequence databases for target sequences that have a near-perfect sequence complementarity to the miRNA sequence using the "scan_for_matches" program and (2) evaluation of the miRNA:target sequence pair for pairing complementarity using specific rules, such as positional dependent penalty score and minimum free energy ratio filter, to identify the most likely candidate targets.

摘要

微小RNA（miRNA）是一类特定的21个核苷酸的小RNA。它们通过多种类型的转录后调控机制来调节特定靶基因的表达，如转录本切割和翻译抑制。因此，miRNA的生物学功能与其靶基因的功能密切相关。靶基因鉴定成为理解miRNA功能的关键一步。在本方案中，我们描述了一种用于植物miRNA靶标预测的计算方法。它涉及两个关键步骤：（1）使用“scan_for_matches”程序在转录本序列数据库中搜索与miRNA序列具有近乎完美序列互补性的靶序列；（2）使用特定规则，如位置依赖性罚分和最小自由能比筛选，评估miRNA：靶序列对的配对互补性，以识别最有可能的候选靶标。