microRNA计算发现方法的研究进展

microRNA (miRNA)是近几年发现的一类长度为～21 nt的内源非编码小RNA, 在植物和动物中发挥着重要而广泛的调控功能。它的发现主要有cDNA克隆测序和计算发现两条途径。由于cDNA克隆测序方法受miRNA表达的时间和组织特异性以及表达水平的影响, 而计算发现可以弥补其不足, 因此miRNA的计算发现方法研究受到了广泛的重视。文章对近几年计算发现miRNA的研究进展进行了综述, 根据计算发现方法的本质, 将计算发现方法归纳为5类, 分别是同源片段搜索方法、基于比较基因组学的预测方法、基于序列和结构特征打分的预测方法、结合作用靶标的预测方法和基于机器学习的预测方法, 并对各类方法的原理、核心思想、优点和局限性进行了分析, 最后探讨了进一步的发展方向。

Computational approaches to microRNA discovery

microRNAs (miRNAs) are endogenous non-coding RNAs of ~21 nucleotides in length discovered in recent years. They are involved in diverse pathways and play an important role in gene regulation in plants and animals. There are two main groups of approaches to miRNA discovery, which are cDNA cloning and computational identification. Since some miRNAs are expressed at a low level and the expression of many miRNAs has spatio-temporal specificity, it is difficult to find them through cDNA cloning. However, computational approaches can predict the miRNAs specifically expressed or with low abundance, which is complement to cDNA cloning. Computational approaches have hence gained wide attention. In this review, the computational approaches to miRNA discovery were summarized. According to their intrinsic characteristics, computational approaches were categorized into five classes: (1) homology search; (2) prediction based on comparative genomics; (3) scoring candidates using the sequence and structure characteristics; (4) prediction combined with targets; and (5) prediction with machine learning. The principles of each class of the approaches and their advantages and limitations in miRNA discovery were discussed. Finally, the future direction in miRNA discovery was pointed out.