RKN Lethal DB: A database for the identification of Root Knot Nematode (<i>Meloidogyne spp</i>.) candidate lethal genes

BACK TO CONTENTS | PDF | PREVIOUS | NEXT

Title	*RKN Lethal DB: A database for the identification of Root Knot Nematode (Meloidogyne spp.) candidate lethal genes*
Authors	Ahmed Ismail¹, Benjamin F Matthews² & Nadim W Alkharouf¹*
Affiliation	¹Department of Computer and Information Sciences, Towson University, 8000 York Road, Towson, MD 21252, USA; ²Soybean Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD 20705, USA.
Email	nalkharouf@towson.edu; *Corresponding author
Article Type	Database
Date	Received September 04, 2012; Accepted September 07, 2012; Published October 01, 2012
Abstract	Root Knot nematode (RKN; Meloidogyne spp.) is one of the most devastating parasites that infect the roots of hundreds of plant species. RKN cannot live independently from their hosts and are the biggest contributors to the loss of the world's primary foods. RNAi gene silencing studies have demonstrated that there are fewer galls and galls are smaller when RNAi constructs targeted to silence certain RKN genes are expressed in plant roots. We conducted a comparative genomics analysis, comparing RKN genes of six species: Meloidogyne Arenaria, Meloidogyne Chitwoodi, Meloidogyne Hapla, Meloidogyne Incognita, Meloidogyne Javanica, and Meloidogyne Paranaensis to that of the free living nematode Caenorhabditis elegans, to identify candidate genes that will be lethal to RKN when silenced or mutated. Our analysis yielded a number of such candidate lethal genes in RKN, some of which have been tested and proven to be effective in soybean roots. A web based database was built to house and allow scientists to search the data. This database will be useful to scientists seeking to identify candidate genes as targets for gene silencing to confer resistance in plants to RKN.
Availability	The database can be accessed from: http://bioinformatics.towson.edu/RKN/
Keywords	RKN, Meloidogyne, web based database, RNAi, C. elegans
Citation	Panda & Chandra, Bioinformation 8(19): 950-952 (2012)
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.