Mining Plutella xylostella’s expressed sequence tags (EST) for a functionally annotated candidate gene index

DOI: 10.18805/ijare.v50i1.8584    | Article Id: A-4313 | Page : 33-38
Citation :- Mining Plutella xylostella’s expressed sequence tags (EST) for a functionally annotated candidate gene index .Indian Journal Of Agricultural Research.2016.(50):33-38

Dinakar R. Ampasala, M. Pritika, Mohane Selvaraj Coumar and Amouda Venkatsan*

amouda@yahoo.com
Address :

Centre for Bioinformatics, Pondicherry University, Kalapet, Pondicherry-605 014, India.

Submitted Date : 29-11-2014
Accepted Date : 27-07-2015

Abstract

Diamondback moths, Plutella xylostella (Linnaeus) are one of the major pests of cruciferous plants such as cabbage and cauliflower (Brassica oleracea) in India. These insect show resistance against commonly used pest management practices such as, chemical insecticides and bacterial pathogens, including Bacillus thuringiensis (Bt). To overcome the resistance problem, develop new pesticides that can act through specific drug targets. To identify such drug targets specific to this insect, data mining and annotation of Expressed Sequence Tags (ESTs) were performed in this study. Expressed Sequence Tags (ESTs, 37,915) of the insect obtained from GenBank were clustered and consensus sequences (4224) were constructed using mining tool (CAP3). Out of it 256 sequences were functionally annotated using three Gene Ontologies (GO) terms, molecular function, biological process and cellular component using similarity search methods (BLASTOGO). By mapping the candidate genes to KEGG Pathway, 38 insect metabolic pathways, inclusive of xenobiotic metabolism by Cytochrome P450 were generated. One of the mapped candidate gene codes for aldehyde dehydrogenase enzyme, which is potentially involved in xenobiotic detoxification of synthetic insecticides, and play a role in the development of resistance to pesticides. Data mining and functional annotation helped to narrow down the choices for potential drug targets, which could aid in the development of new pesticides to overcome resistance in Diamondback moths. This methodology can be extended to other agriculturally important pests to identify the drug targets using EST data. 

Keywords

Data mining EST Functional annotation Gene ontology KEGG.

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