Nucleic Acids Research, 2003, Vol. 31, No. 23 7041-7055
© 2003 Oxford University Press
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Improving gene annotation of complete viral genomes
1 School of Biology and 2 School of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0230, USA and 3 National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD 20894, USA
*To whom correspondence should be addressed. Tel: +1 404 894 8432; Fax: +1 404 894 0519; Email: mark.borodovsky{at}biology.gatech.edu
Gene annotation in viruses often relies upon similarity search methods. These methods possess high specificity but some genes may be missed, either those unique to a particular genome or those highly divergent from known homologs. To identify potentially missing viral genes we have analyzed all complete viral genomes currently available in GenBank with a specialized and augmented version of the gene finding program GeneMarkS. In particular, by implementing genome-specific self-training protocols we have better adjusted the GeneMarkS statistical models to sequences of viral genomes. Hundreds of new genes were identified, some in well studied viral genomes. For example, a new gene predicted in the genome of the Epstein–Barr virus was shown to encode a protein similar to 
-herpesvirus minor tegument protein UL14 with heat shock functions. Convincing evidence of this similarity was obtained after only 12 PSI-BLAST iterations. In another example, several iterations of PSI-BLAST were required to demonstrate that a gene predicted in the genome of Alcelaphine herpesvirus 1 encodes a BALF1-like protein which is thought to be involved in apoptosis regulation and, potentially, carcinogenesis. New predictions were used to refine annotations of viral genomes in the RefSeq collection curated by the National Center for Biotechnology Information. Importantly, even in those cases where no sequence similarities were detected, GeneMarkS significantly reduced the number of primary targets for experimental characterization by identifying the most probable candidate genes. The new genome annotations were stored in VIOLIN, an interactive database which provides access to similarity search tools for up-to-date analysis of predicted viral proteins.
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