Skip to main content

ORIGINAL RESEARCH article

Front. Plant Sci.
Sec. Plant Pathogen Interactions
Volume 15 - 2024 | doi: 10.3389/fpls.2024.1460540

Predicting Candidate miRNAs for Targeting Begomovirus to Induce Sequence-Specific Gene Silencing in Chilli Plants

Provisionally accepted
VINEETA PANDEY VINEETA PANDEY 1Aarshi Srivastava Aarshi Srivastava 1AKHTAR ALI AKHTAR ALI 2Ramwant Gupta Ramwant Gupta 1RAJARSHI K. Gaur RAJARSHI K. Gaur 1*
  • 1 Deen Dayal Upadhyay Gorakhpur University, Gorakhpur, India
  • 2 University of Tulsa, Tulsa, Oklahoma, United States

The final, formatted version of the article will be published soon.

    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.

    Keywords: Begomovirus, Chilli leaf curl disease, Chilli, miRNA, miRNA-mRNA Interaction, Target prediction algorithms

    Received: 06 Jul 2024; Accepted: 30 Aug 2024.

    Copyright: © 2024 PANDEY, Srivastava, ALI, Gupta and Gaur. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: RAJARSHI K. Gaur, Deen Dayal Upadhyay Gorakhpur University, Gorakhpur, India

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.