Published online 7 January 2005
Methods Online |
ArrayOme: a program for estimating the sizes of microarray-visualized bacterial genomes
1 Department of Infection, Immunity and Inflammation, Leicester Medical School, University of Leicester Leicester LE1 9HN, UK 2 Department of Clinical Microbiology, University Hospitals of Leicester NHS Trust Leicester LE1 5WW, UK 3 Molecular Microbiology Group, Institute of Food Research Norwich Research Park, Norwich NR4 7UA, UK 4 Bacterial Pathogenesis and Genomics Unit, Division of Immunity and Infection, Medical School, University of Birmingham Birmingham B15 2TT, UK
*To whom correspondence should be addressed at Department of Infection, Immunity and Inflammation, Leicester Medical School, University of Leicester, Maurice Shock Building, University Road, PO Box 138, Leicester LE1 9HN, UK. Tel: +44 0 116 2231498; Fax: +44 0 116 2525030; Email: kr46{at}le.ac.uk
Received November 5, 2004. Revised December 13, 2004. Accepted December 13, 2004.
ArrayOme is a new program that calculates the size of genomes represented by microarray-based probes and facilitates recognition of key bacterial strains carrying large numbers of novel genes. Protein-coding sequences (CDS) that are contiguous on annotated reference templates and classified as ‘Present’ in the test strain by hybridization to microarrays are merged into ICs (ICs). These ICs are then extended to account for flanking intergenic sequences. Finally, the lengths of all extended ICs are summated to yield the ‘microarray-visualized genome (MVG)’ size. We tested and validated ArrayOme using both experimental and in silico-generated genomic hybridization data. MVG sizing of five sequenced Escherichia coli and Shigella strains resulted in an accuracy of 97–99%, as compared to true genome sizes, when the comprehensive ShE.coli meta-array gene sequences (6239 CDS) were used for in silico hybridization analysis. However, the E.coli CFT073 genome size was underestimated by 14% as this meta-array lacked probes for many CFT073 CDS. ArrayOme permits rapid recognition of discordances between PFGE-measured genome and MVG sizes, thereby enabling high-throughput identification of strains rich in novel genes. Gene discovery studies focused on these strains will greatly facilitate characterization of the global gene pool accessible to individual bacterial species.
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