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


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.

SUBMITTER: Shweta 

PROVIDER: S-EPMC4070032 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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

Shweta   Khan Jawaid A JA  

Bioinformation 20140520 5


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,  ...[more]

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