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:10.7717/peerj.8359

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

PeerJ. 2020 Jan 13:8:e8359. doi: 10.7717/peerj.8359. eCollection 2020.

Authors

Fakiha Ashraf^#¹, Muhammad Aleem Ashraf^#^{2

3}, Xiaowen Hu⁴, Shuzhen Zhang¹

Affiliations

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, Islamia University of Bahawalpur, Baghdad-Ul-Jadeed Campus, Bahwalpur, Pakistan.
⁴ Zhanjiang Experimental Station, Chinese Academy of Tropical Agricultural Sciences, Zhanjiang, Guandong, China.

^# Contributed equally.

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. Sugarcane bacilliform viruses (SCBVs) are one of the main species that infect sugarcane. During the last 30 years, significant genetic changes in SCBV strains have been observed with a high risk of disease incidence associated with crop damage. SCBV infection may lead to significant losses in biomass production in susceptible sugarcane cultivars. The circular, double-stranded (ds) DNA genome of SCBGAV (7.4 Kb) is composed of three open reading frames (ORFs) on the positive strand that replicate by a reverse transcriptase. SCBGAV can infect sugarcane in a semipersistent manner via the insect vectors sugarcane mealybug species. 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. Mature miRNA target sequences were retrieved from the miRBase (miRNA 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. Among them, sof-miR396 was identified as the top effective candidate, capable of targeting the vital ORF3 of the SCBGAV genome. miRanda, RNA22 and RNAhybrid algorithms predicted hybridization of sof-miR396 at common locus position 3394. The predicted sugarcane miRNAs against viral mRNA targets possess antiviral activities, leading to translational inhibition by mRNA cleavage. Interaction network of sugarcane-encoded miRNAs with SCBGAV genes, created using Circos, allow analyze new targets. The finding of the present study acts as a first step towards the creation of SCBGAV-resistant sugarcane through the expression of the identified miRNAs.

Keywords: Computational algorithms; Gene silencing; R language; RNA interference; Saccharum officinarum; Sugarcane Bacilliform Guadeloupe A Virus; Target prediction; Virus-host interaction; miRNA; miRanda.

Grants and funding

This study is supported by the National Natural Science Foundation of China (No. 31771865), the Sugar Crop Research System (CARS-170301) and the “Talented Young Scientist Program” (TYSP-4th Batch 2017-2018) of China Project ID (Pakistan-18-004). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.