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Applied Microbiology
Volume 5
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10.3390/applmicrobiol5010013
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

In Silico Identification of Banana High-Confidence MicroRNA Binding Sites Targeting Banana Streak GF Virus

by
Muhammad Aleem Ashraf
1,2,*,†,
Babar Ali
3,†,
Maryam Fareed
4,
Ahsan Sardar
4,
Eisha Saeed
4,
Samaa Islam
4,
Shaher Bano
4 and
Naitong Yu
1,*
1
Institute of Tropical Biosciences and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China
2
Department of Biosciences and Technology, Faculty of Sciences, Emerson University, Multan 60000, Pakistan
3
Department of Biosciences, COMSTAS University Islamabad, Park Road, Tarlai Kalan, Islamabad 45550, Pakistan
4
Institute of Biological Sciences, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan 64200, Pakistan
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Appl. Microbiol. 2025, 5(1), 13; https://doi.org/10.3390/applmicrobiol5010013
Submission received: 27 December 2024 / Revised: 17 January 2025 / Accepted: 24 January 2025 / Published: 27 January 2025
(This article belongs to the Special Issue Microbial Evolutionary Genomics and Bioinformatics)
Versions Notes

Abstract

Banana streak GF virus (BSGFV) is the extremely dangerous monopartite badnavirus (genus, Badnavirus; family, Caulimoviridae) of banana (Musa acuminata AAA Group) that imposes a serious threat to global banana production. The BSGFV causes a devastating pandemic in banana crops, transmitted by deadly insect pest mealybug vectors and replicated through an RNA intermediate. The BSGFV is a reverse-transcribing DNA virus that has a monopartite open circular double-stranded DNA (dsDNA) genome with a length of 7325 bp. RNA interference (RNAi) is a natural mechanism that has revolutionized the target gene regulation of various organisms to combat virus infection. The current study aims to locate the potential target binding sites of banana-encoded microRNAs (mac-miRNAs) on the BSGFV-dsDNA-encoded mRNAs based on three algorithms, RNA22, RNAhybrid and TAPIR. Mature banana (2n = 3x = 33) miRNAs (n = 32) were selected and hybridized to the BSGFV genome (MN296502). Among the 32 targeted mature locus-derived mac-miRNAs investigated, two banana mac-miRNA homologs (mac-miR162a and mac-miR172b) were identified as promising naturally occurring biomolecules to have binding affinity at nucleotide positions 5502 and 9 of the BSGFV genome. The in silico banana-genome-encoded mac-miRNA/mbg-miRNA-regulatory network was developed with the BSGFV—ORFs using Circos software (version 0.69-9) to identify potential therapeutic target proteins. Therefore, the current work provides useful biological material and opens a new range of opportunities for generating BSGFV-resistant banana plants through the genetic manipulation of the selected miRNAs.
Keywords: Badnavirus; Banana streak GF virus; binding affinity; in silico tools; gene silencing; microRNA; RNAi; R-language; target prediction Badnavirus; Banana streak GF virus; binding affinity; in silico tools; gene silencing; microRNA; RNAi; R-language; target prediction

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MDPI and ACS Style

Ashraf, M.A.; Ali, B.; Fareed, M.; Sardar, A.; Saeed, E.; Islam, S.; Bano, S.; Yu, N. In Silico Identification of Banana High-Confidence MicroRNA Binding Sites Targeting Banana Streak GF Virus. Appl. Microbiol. 2025, 5, 13. https://doi.org/10.3390/applmicrobiol5010013

AMA Style

Ashraf MA, Ali B, Fareed M, Sardar A, Saeed E, Islam S, Bano S, Yu N. In Silico Identification of Banana High-Confidence MicroRNA Binding Sites Targeting Banana Streak GF Virus. Applied Microbiology. 2025; 5(1):13. https://doi.org/10.3390/applmicrobiol5010013

Chicago/Turabian Style

Ashraf, Muhammad Aleem, Babar Ali, Maryam Fareed, Ahsan Sardar, Eisha Saeed, Samaa Islam, Shaher Bano, and Naitong Yu. 2025. "In Silico Identification of Banana High-Confidence MicroRNA Binding Sites Targeting Banana Streak GF Virus" Applied Microbiology 5, no. 1: 13. https://doi.org/10.3390/applmicrobiol5010013

APA Style

Ashraf, M. A., Ali, B., Fareed, M., Sardar, A., Saeed, E., Islam, S., Bano, S., & Yu, N. (2025). In Silico Identification of Banana High-Confidence MicroRNA Binding Sites Targeting Banana Streak GF Virus. Applied Microbiology, 5(1), 13. https://doi.org/10.3390/applmicrobiol5010013

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