Computational Identification of 99 Insect MicroRNAs Using Comparative Genomics

In recent years, much effort has been made in identifying microRNA (miRNA) genes from mammals, insects, worms, plants, and viruses. Continuing the search for more miRNA genes is still important but difficult. This paper presents a computational strategy based on comparative genomics analysis. The algorithm was used to scan four invertebrate genomes, Drosophila melangoster, Bombyx mori, Apis mellifera, and Anopheles gambiae, which are either model organisms or medically/economically important insects. 99 new miRNA genes were predicted from the four insect species which can be grouped into 17 miRNA gene families, of which 10 of the miRNA families are insect-specific. Sequence similarity analysis showed that 16 of the newly predicted insect miRNAs belong to the K-box, GY-box, and Brd-box miRNA families which are important participators in Notch-related pathways. To test the validity of the algorithm, 39 predicted insect miRNA genes from D. melangoster and A. mellifera were selected for further biological validation. 34 (87%) predicted miRNA genes’ transcripts were successfully detected by reverse transcription-polymerase chain reaction experiments. Thus, this strategy can be used to efficiently screen for miRNA genes conserved cross