Predicting candidate miRNAs for targeting begomovirus to induce sequence-specific gene silencing in chilli plants.

The begomoviruses are the most economically damaging pathogens that pose a serious risk to India's chilli crop and have been associated with the chilli leaf curl disease (ChiLCD). Chilli cultivars infected with begomovirus have suffered significant decreases in biomass output, negatively impacting their economic characteristics. We used the C-mii tool to predict twenty plant miRNA families from SRA chilli transcriptome data (retrieved from the NCBI and GenBank databases). Five target prediction algorithms, i.e., C-mii, miRanda, psRNATarget, RNAhybrid, and RNA22, were applied to identify and evaluate chilli miRNAs (microRNAs) as potential therapeutic targets against ten begomoviruses that cause ChiLCD. In this study, the top five chilli miRNAs which were identified by all five algorithms were thoroughly examined. Moreover, we also noted strong complementarities between these miRNAs and the AC1 (REP), AC2 (TrAP) and betaC1 genes. Three computational approaches (miRanda, RNA22, and psRNATarget) identified the consensus hybridization site for CA-miR838 at locus 2052. The top predicted targets within ORFs were indicated by CA-miR2673 (a and b). Through Circos algorithm, we identified novel targets and create the miRNA-mRNA interaction network using the R program. Furthermore, free energy calculation of the miRNA-target duplex revealed that thermodynamic stability was optimal for miR838 and miR2673 (a and b). To the best of our knowledge, this was the first instance of miRNA being predicted from chilli transcriptome information that had not been reported in miRbase previously. Consequently, the anticipated biological results substantially assist in developing chilli plants resistant to ChiLCD.