Literature DB >> 31542706

Target prediction of candidate miRNAs from Oryza sativa for silencing the RYMV genome.

Basit Jabbar1, Muhammad Shahzad Iqbal2, Anicet A Batcho3, Idrees A Nasir4, Bushra Rashid5, Tayyab Husnain6, Robert J Henry7.   

Abstract

In order to maintain a consistent supply of rice globally, control of pathogens affecting crop production is a matter of due concern. Rice yellow mottle virus(RYMV) is known to cause a variety of symptoms which can result in reduced yield. Four ORFs can be identified in the genome of RYMV encoding for P1 (ORF1), Polyprotein (processed to produce VPg, protease, helicase, RdRp4) (ORF2), putative RdRp (ORF3) and capsid/coat protein (ORF4). This research was aimed at identifying genome encoded miRNAs of O. sativa that are targeted to the genome of Rice Yellow Mottle Virus (RYMV). A consensus of four miRNA target prediction algorithms (RNA22, miRanda, TargetFinder and psRNATarget) was computed, followed by calculation of free energies of miRNA-mRNA duplex formation. A phylogenetic tree was constructed to portray the evolutionary relationships between RYMV strains isolated to date. From the consensus of algorithms used, a total of seven O. sativa miRNAs were predicted and conservation of target site was finally evaluated. Predicted miRNAs can be further evaluated by experiments involving the testing of the success of in vitro gene silencing of RYMV genome; this can pave the way for development of RYMV resistant rice varieties in the future.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Gene silencing; Oryza sativa; Rice yellow mottle virus; Target prediction; miRNAs

Year:  2019        PMID: 31542706     DOI: 10.1016/j.compbiolchem.2019.107127

Source DB:  PubMed          Journal:  Comput Biol Chem        ISSN: 1476-9271            Impact factor:   2.877


  3 in total

1.  Diagnostic model of combined ceRNA and DNA methylation related genes in esophageal carcinoma.

Authors:  Xiaojiao Guan; Yao Yao; Guangyao Bao; Yue Wang; Aimeng Zhang; Xinwen Zhong
Journal:  PeerJ       Date:  2020-03-31       Impact factor: 2.984

2.  Novel targets for engineering Physostegia chlorotic mottle and tomato brown rugose fruit virus-resistant tomatoes: in silico prediction of tomato microRNA targets.

Authors:  Yahya Zakaria Abdou Gaafar; Heiko Ziebell
Journal:  PeerJ       Date:  2020-10-27       Impact factor: 2.984

3.  In silico identification of sugarcane (Saccharum officinarum L.) genome encoded microRNAs targeting sugarcane bacilliform virus.

Authors:  Muhammad Aleem Ashraf; Xiaoyan Feng; Xiaowen Hu; Fakiha Ashraf; Linbo Shen; Muhammad Shahzad Iqbal; Shuzhen Zhang
Journal:  PLoS One       Date:  2022-01-20       Impact factor: 3.240

  3 in total

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