New Computational Tools for Brassica Genome Research. Issue 3 (2004)

• Record Type: Journal Article
• Authors: Love, Christopher G.; Batley, Jacqueline; Lim, Geraldine; Robinson, Andrew J.; Savage, David; Singh, Daniel; Spangenberg, German C.; Edwards, David
• Is Part Of: Comparative and functional genomics. Volume 5:Issue 3(2004)
• Page Start: 276
• Page End: 280
• Publication Date: 2004
• Subjects: Genomics -- Periodicals; Genomes -- Periodicals; Cytogenetics -- Periodicals; 572.86
• DOI: 10.1002/cfg.394
• Languages: English
• ISSNs: 1531-6912

Abstract

Abstract : With the increasing quantities of Brassica genomic data being entered into the public domain and in preparation for the complete Brassica genome sequencing effort, there is a growing requirement for the structuring and detailed bioinformatic analysis of Brassica genomic information within a user-friendly database. At the Plant Biotechnology Centre, Melbourne, Australia, we have developed a series of tools and computational pipelines to assist in the processing and structuring of genomic data, to aid its application to agricultural biotechnology research. These tools include a sequence database, ASTRA, a sequence processing pipeline incorporating annotation against GenBank, SwissProt and Arabidopsis Gene Ontology (GO) data and tools for molecular marker discovery and comparative genome analysis. All sequences are mined for simple sequence repeat (SSR) molecular markers using 'SSR primer' and mapped onto the complete Arabidopsis thaliana genome by sequence comparison. The database may be queried using a text-based search of sequence annotation or GO terms, BLAST comparison against resident sequences, or by the position of candidate orthologues within the Arabidopsis genome. Tools have also been developed and applied to the discovery of single nucleotide polymorphism (SNP) molecular markers and the in silico mapping of Brassica BAC end sequences onto the Arabidopsis genome. Planned extensions to this resource include the integration of gene expression data and the development of an EnsEMBL-based genome viewer.