In silico identification of miRNAs from the Asian rice gall midge (Orseolia oryzae) - a major pest of rice

miRNAs are small, generally 22 nucleotide(nt) long non-coding RNAs (ncRNAs) that bind to ORFs or the 3’-untranslated region (UTR) of the target messenger RNA and regulate gene expression at post-transcriptional level. Similarly, expression of many genes is regulated by other ncRNAs. This regulation can occur either in cis or trans. Together, this set of ncRNAs plays a crucial regulatory role in many cellular and developmental processes. As miRNA expression is spatially and temporally regulated, it poses many limitations and difficulties in their experimental identification. Hence, many computational approaches have been employed for their prediction. In the present study, we present a computational approach for the prediction of bonafide miRNAs and other ncRNAs from Asian rice gall midge for the first time. High throughput 454 pyrosequencing was used to deep sequence an O.oryzae EST library and the sequencing data was then analyzed. This enabled us to identify 7 miRNAs from the Asian rice gall midge. Further, analysis was carried out to study their phylogenetic conservation. In addition, an attempt was also made to predict the putative targets of these miRNAs. These newly identified miRNAs and their targets will serve as useful tools to decipher the molecular events inside the midge when it infects the rice plant. Also, it will enable us to understand the role of miRNAs in the rice-gall midge interaction.