A novel computational approach to the silencing of Sugarcane Bacilliform Guadeloupe A Virus determines potential host-derived MicroRNAs in sugarcane (Saccharum officinarum L.)

Fakiha Ashraf; Muhammad Aleem Ashraf; Xiaowen Hu; Shuzhen Zhang

doi:10.7287/peerj.preprints.27842v1

A novel computational approach to the silencing of Sugarcane Bacilliform Guadeloupe A Virus determines potential host-derived MicroRNAs in sugarcane (Saccharum officinarum L.)

Fakiha Ashraf¹, Muhammad Aleem Ashraf ^2,3, Xiaowen Hu⁴, Shuzhen Zhang ¹

1 Institute of Tropical Bioscience and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, Haikou, Hainan, China

2 Haikou Experimental Station, Chinese Academy of Tropical Agricultural Sciences, Haikou, Hainan, China

3 Department of Plant Breeding and Genetics, University College of Agriculture and Environmental Sciences, The Islamia University of Bahawalpur, Baghdad-Ul-Jadeed Campus, Bahawalpur, South Punjab, Pakistan

4 Zhanjiang Experimental Station, Chinese Academy of Tropical Agricultural Sciences, Zhanjiang, Guandong, China

DOI: 10.7287/peerj.preprints.27842v1

Published: 2019-07-04
Accepted: 2019-07-04

Subject Areas: Biotechnology, Computational Biology, Virology
Keywords: Computational algorithms, R language, miRNA, Saccharum officinarum, Sugarcane Bacilliform Guadeloupe A Virus, Target prediction

Copyright: © 2019 Ashraf et al.
Licence: This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.

Cite this article: Ashraf F, Ashraf MA, Hu X, Zhang S. 2019. A novel computational approach to the silencing of Sugarcane Bacilliform Guadeloupe A Virus determines potential host-derived MicroRNAs in sugarcane (Saccharum officinarum L.) PeerJ Preprints 7:e27842v1 https://doi.org/10.7287/peerj.preprints.27842v1

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.