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. 2010 Jan;38(Database issue):D814-21.
doi: 10.1093/nar/gkp978. Epub 2009 Nov 11.

PRGdb: a bioinformatics platform for plant resistance gene analysis

Walter Sanseverino  1 , Guglielmo Roma, Marco De Simone, Luigi Faino, Sara Melito, Elia Stupka, Luigi Frusciante, Maria Raffaella Ercolano
Affiliations

PRGdb: a bioinformatics platform for plant resistance gene analysis

Walter Sanseverino et al. Nucleic Acids Res. 2010 Jan.

Abstract

PRGdb is a web accessible open-source (http://www.prgdb.org) database that represents the first bioinformatic resource providing a comprehensive overview of resistance genes (R-genes) in plants. PRGdb holds more than 16,000 known and putative R-genes belonging to 192 plant species challenged by 115 different pathogens and linked with useful biological information. The complete database includes a set of 73 manually curated reference R-genes, 6308 putative R-genes collected from NCBI and 10463 computationally predicted putative R-genes. Thanks to a user-friendly interface, data can be examined using different query tools. A home-made prediction pipeline called Disease Resistance Analysis and Gene Orthology (DRAGO), based on reference R-gene sequence data, was developed to search for plant resistance genes in public datasets such as Unigene and Genbank. New putative R-gene classes containing unknown domain combinations were discovered and characterized. The development of the PRG platform represents an important starting point to conduct various experimental tasks. The inferred cross-link between genomic and phenotypic information allows access to a large body of information to find answers to several biological questions. The database structure also permits easy integration with other data types and opens up prospects for future implementations.

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Figures

Figure 1.
Figure 1.
A schematic view of the PRG database showing the origin of dataset used and the sequences characterization. (A) The manually curated dataset that contains 73 literature cited R-genes from 22 different plants. (B) The NCBI dataset containing 6308 sequences related to reference R-genes retrieved by the NCBI database. (C) The computationally predicted dataset using the DRAGO pipeline containing 10 463 putative R-genes. (D) Workflow of conserved domain analysis and sequence classification.
Figure 2.
Figure 2.
A PRGdb web page reporting an R-gene description. The following information is displayed: gene name; CDS, RNA, protein sequences and domains position; Genbank ID; original resistant species (donor organism); related molecular markers; literature; disease description, related pathogen and corresponding avirulence gene. Words in green and red represent hypertext links.
Figure 3.
Figure 3.
DRAGO predicted sequences divided by domains and identified by class. (A) Number of sequences containing an R-gene specific domain; LRR, leucine-rich repeat; NBS, nucleotide binding site; TIR, Toll interleukine receptor-like; KIN, kinase; Ser–Thr, serine–threonine. (B) Domain patterns identified according to functional R-gene classes.
Figure 4.
Figure 4.
(A) A Venn diagram showing all possible combinations among domain classes produced by DRAGO pipeline. Each intersection represents a new or know domains association. Proteins numbers falling in each class are reported. (B) Examples of three unknown putative classes containing new domain combinations.
See this image and copyright information in PMC

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