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Title

In silico prediction of cotton (Gossypium hirsutum) encoded microRNAs targets in the genome of Cotton leaf curl Allahabad virus

 

Authors

Shweta & Jawaid A Khan*

 

Affiliation

Plant Virus Laboratory, Department of Biosciences, Jamia Millia Islamia, New Delhi-110025, India

 

Email

jkhan1@jmi.ac.in; *Corresponding author

 

Article Type

Hypothesis

 

Date

Received March 24, 2014; Accepted April 02, 2014; Published May 20, 2014

 

Abstract

Cotton leaf curl Allahabad virus (CLCuAV) belongs to genus Begomovirus, family Geminiviridae. It has single stranded monopartite DNA genome transmitted by whitefly (Bemisia tabaci). MicroRNAs (miRNAs) belong to class of endogeneous small RNAs which suppress expression of genes following cleavage or translational inhibition of target messenger RNAs. They are demonstrated to be involved in a number of plant processes such as, development, biotic and abiotic stresses. Employing in silico approach, high scoring miRNA-target pairs satisfying rules of minimum free energy and maximum complementarity were selected to investigate if they possess the potential to bind the genome CLCuAV. Our results revealed that miRNA species viz., ghr-miR2950 can target all the viral genes, ghr-miR408 targets overlapping transcripts of AC1 and AC2 genes; while ghr-miR394 and ghr-miR395a and miR395d could bind overlapping transcripts of AC1 and AC4 genes. This is the first report of prediction of cotton miRNAs which have the potential to target CLCuAV genes including AC1 and AC4, involved in viral replication and gene silencing suppression, respectively. 

 

Keywords

MicroRNA, Gene regulation, Begomovirus, Cotton leaf curl disease, RNA Interference.

 

Citation

Shweta & Khan,   Bioinformation 10(5): 251-255 (2014)
 

Edited by

P Kangueane

 

ISSN

0973-2063

 

Publisher

Biomedical Informatics

 

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.