Untitled

Abstract

Sugarcane Bacilliform Guadeloupe A Virus (SCBGAV, genus Badnavirus, family Caulimoviridae) is an emerging, deleterious pathogen of sugarcane which presents a substantial barrier to producing high sugarcane earnings. The circular, double-stranded (ds) DNA genome of SCBGAV (7.4 Kb) is composed of three open reading frames (ORF) that replicate by a reverse transcriptase. In the current study, we used miRNA target prediction algorithms to identify and comprehensively analyze the genome-wide sugarcane (Saccharum officinarum L.)-encoded microRNA (miRNA) targets against the SCBGAV. A total of 28 potential mature target miRNAs were retrieved from the miRBase database and were further analyzed for hybridization to the SCBGAV genome. Multiple computational approaches-including miRNA-target seed pairing, multiple target positions, minimum free energy, target site accessibility, maximum complementarity, pattern recognition and minimum folding energy for attachments-were considered by all algorithms. Only 4 sugarcane miRNAs are selected for SCBGAV silencing. Among those 4, sof-miR396 was identified as the top effective candidate, capable of targeting the vital ORF3 which encodes polyprotein of the SCBGAV genome. miRanda, RNA22 and RNAhybrid algorithms predicted hybridization of sof-miR396 at common locus position 3394. A Circos plot was created to study the network visualization of sugarcane-encoded miRNAs with SCBGAV genes determines detailed evidence for any ideal targets of SCBGAV ORFs by precise miRNAs. The present study concludes a comprehensive report towards the creation of SCBGAV-resistant sugarcane through the expression analysis of the identified miRNAs.