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后生动物物种中两种类型的 miRNA 前体之间的特征比较。

Characteristic comparison between two types of miRNA precursors in metazoan species.

作者信息

Zhang Xiaobai, Song Xiaofeng, Wang Huinan

机构信息

Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Jiangsu, PR China.

出版信息

Biosystems. 2010 May;100(2):144-9. doi: 10.1016/j.biosystems.2010.02.009. Epub 2010 Mar 6.

Abstract

MicroRNAs (miRNAs) are a class of small non-coding RNAs discovered in recent years, which are found to play important regulatory roles in various organisms. As the number of experimentally validated miRNAs is rapidly increasing, systematic analysis on the characteristics of these known miRNAs is necessary and indispensable, especially for computational prediction of new miRNAs. We extensively analyzed precursor sequences for all experimentally validated mature miRNAs in metazoan species, focusing on the characteristics at the level of primary sequences and secondary structures. An observation over the secondary structures of 2729 miRNA precursors (pre-miRNAs) reveals that these hairpin structures can be approximately classified into two types: one with a hairpin loop, and the other with multiple loops. Interestingly, the two types of pre-miRNAs show significant differences in both sequence and structure characteristics, and our study indicates that separate consideration on each type of pre-miRNAs is more reasonable, especially in computational prediction. Besides, we develop a new criterion called mAMFE which shows robust discriminative power in distinguishing pre-miRNAs against other RNAs, thus can potentially serve as a discriminative feature in prediction of new pre-miRNAs.

摘要

微小RNA(miRNA)是近年来发现的一类小型非编码RNA,它们在各种生物体中发挥着重要的调控作用。随着实验验证的miRNA数量迅速增加,对这些已知miRNA的特征进行系统分析是必要且不可或缺的,特别是对于新miRNA的计算预测。我们广泛分析了后生动物物种中所有经实验验证的成熟miRNA的前体序列,重点关注一级序列和二级结构水平的特征。对2729个miRNA前体(pre-miRNA)二级结构的观察表明,这些发夹结构大致可分为两类:一类带有发夹环,另一类带有多个环。有趣的是,这两类pre-miRNA在序列和结构特征上都存在显著差异,我们的研究表明,对每种类型的pre-miRNA进行单独考虑更为合理,尤其是在计算预测中。此外,我们开发了一种名为mAMFE的新准则,它在区分pre-miRNA与其他RNA方面具有强大的判别能力,因此有可能作为预测新pre-miRNA的判别特征。

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