Bioinformatics analysis on structural features of microRNA precursors in insects

Abstract

To date, thousands of microRNAs (miRNAs) and their precursors (pre-miRNAs) have been identified in insects and their nucleotide sequences deposited in the miRBase database. In the present work, we have systematically analyzed, utilizing bioinformatics tools, the featural differences between human and insect pre-miRNAs, as well as differences across 24 insect species. Results showed that the nucleotide composition, sequence length, nucleotides preference and secondary structure features between human and insects were different. Subsequently, with the aid of three available SVM-based prediction programs, pre-miRNA sequences were evaluated and given corresponding scores. Thus it was found that of 2633 sequences from the 24 chosen insect species, 2229 (84.7%) were successfully recognized by the Mirident classifier, higher than Triplet-SVM (72.5%) and PMirP (72.6%). In contrast, four species, including the domesticated silkworm, Bombyx mori L., the fruit fly, Drosophila melanogaster Meigen, the honeybee, Apis mellifera L. and the red flour beetle, Tribolium castaneum (Herbst), were found to be largely responsible for the poor performance of some sequence matching. Compared with other species, B. mori especially showed the worst performance with the lowest average MFE index (0.73). Collectively these results pave the way for understanding specificity and diversity of miRNA precursors in insects, and lay the foundation for the further development of more suitable algorisms for insects.

Keywords

• structural features
• bioinformatics
• insects
• microrna precursors