In silico identification of sugarcane (Saccharum officinarum L.) genome encoded microRNAs targeting sugarcane bacilliform virus.

Sugarcane bacilliform virus (SCBV) is considered one of the most economically damaging pathogens for sugarcane production worldwide. Three open reading frames (ORFs) are characterized in the circular, ds-DNA genome of the SCBV; these encode for a hypothetical protein (ORF1), a DNA binding protein (ORF2), and a polyprotein (ORF3). A comprehensive evaluation of sugarcane (Saccharum officinarum L.) miRNAs for the silencing of the SCBV genome using in silico algorithms were carried out in the present study using mature sugarcane miRNAs. miRNAs of sugarcane are retrieved from the miRBase database and assessed in terms of hybridization with the SCBV genome. A total of 14 potential candidate miRNAs from sugarcane were screened out by all used algorithms used for the silencing of SCBV. The consensus of three algorithms predicted the hybridization site of sof-miR159e at common locus 5534. miRNA-mRNA interactions were estimated by computing the free-energy of the miRNA-mRNA duplex using the RNAcofold algorithm. A regulatory network of predicted candidate miRNAs of sugarcane with SCBV-ORFs, generated using Circos-is used to identify novel targets. The predicted data provide useful information for the development of SCBV-resistant sugarcane plants.

Target prediction of candidate miRNAs from Oryza sativa for silencing the RYMV genome.

In order to maintain a consistent supply of rice globally, control of pathogens affecting crop production is a matter of due concern. Rice yellow mottle virus(RYMV) is known to cause a variety of symptoms which can result in reduced yield. Four ORFs can be identified in the genome of RYMV encoding for P1 (ORF1), Polyprotein (processed to produce VPg, protease, helicase, RdRp4) (ORF2), putative RdRp (ORF3) and capsid/coat protein (ORF4). This research was aimed at identifying genome encoded miRNAs of O. sativa that are targeted to the genome of Rice Yellow Mottle Virus (RYMV). A consensus of four miRNA target prediction algorithms (RNA22, miRanda, TargetFinder and psRNATarget) was computed, followed by calculation of free energies of miRNA-mRNA duplex formation. A phylogenetic tree was constructed to portray the evolutionary relationships between RYMV strains isolated to date. From the consensus of algorithms used, a total of seven O. sativa miRNAs were predicted and conservation of target site was finally evaluated. Predicted miRNAs can be further evaluated by experiments involving the testing of the success of in vitro gene silencing of RYMV genome; this can pave the way for development of RYMV resistant rice varieties in the future.