A bioinformatics resource for crop functional genomics: GFSelector module in automated annotation system, riceGAAS

GFSelector (Gene Function Selector, http://alnilam.mi.mss.co.jp/rgadb/) has been developed to perform computational classification of gene models and assignment of unique biological function. It has been incorporated in RiceGAAS (http://ricegaas.dna.affrc.go.jp/usr/) which was designed to provide an...

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Bibliographic Details
Published in:JARQ. Japan agricultural research quarterly 2009, Vol.43(2), pp.103-113
Main Authors: Sakata, K.(Mitsubishi Space Software Co., Ltd., Tsukuba, Ibaraki (Japan). Genome Informatics Department), Ikawa, H, Watanabe, H, Ashikawa, I, Shimizu, Y, Horiuchi, I, Antonio, B,A, Numa, H, Nagamura, Y, Matsumoto, T
Format: Article
Language:English
Subjects:
ADN
AUTOMATION
AUTOMATISATION
AUTOMATIZACION
BANQUE DE DONNEES
BASES DE DATOS
BIBLIOTECAS
BIBLIOTHEQUE
DNA
gene ontology
GENOMAS
GENOME
GENOMES
LIBRARIES
MODELE
MODELOS
NUCLEOTIDE SEQUENCE
ORYZA SATIVA
SECUENCIA NUCLEOTIDICA
SEQUENCE NUCLEOTIDIQUE
web-based system
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Summary:GFSelector (Gene Function Selector, http://alnilam.mi.mss.co.jp/rgadb/) has been developed to perform computational classification of gene models and assignment of unique biological function. It has been incorporated in RiceGAAS (http://ricegaas.dna.affrc.go.jp/usr/) which was designed to provide an analysis pipeline for user submitted genome sequences and comprehensive database for all rice gene models. The combined system facilitates accurate modelling of predicted rice genes, classification of gene structure, and assigning of function and GO (gene ontology) terms to the gene models. The reliability and accuracy are enhanced by integrating several reference databases into the system and generating multiple candidates for determining the function of the gene models. The pipeline is also fully automated thereby facilitating regularly updates of the rice gene models using the latest reference databases. Annotation of soybean, wheat and banana BAC (bacterial artificial chromosome) sequences was performed to test the applicability of the pipeline to other crops. As compared with the GenBank CDS (coding sequence) features, more than 83% of nucleotide-level sensitivity was obtained for the gene modelling by the pipeline. It was also confirmed that 95% of functional annotation by the pipeline was nearly equal or better than the corresponding GenBank CDS feature.
ISSN:0021-3551
2185-8896
DOI:10.6090/jarq.43.103