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.
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