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DNA Research Advance Access originally published online on October 21, 2008
DNA Research 2008 15(6):387-396; doi:10.1093/dnares/dsn027
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© The Author 2008. Kazusa DNA Research Institute
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org

MetaGeneAnnotator: Detecting Species-Specific Patterns of Ribosomal Binding Site for Precise Gene Prediction in Anonymous Prokaryotic and Phage Genomes

Hideki Noguchi*, Takeaki Taniguchi and Takehiko Itoh

Advanced Science and Technology Research Group, Mitsubishi Research Institute, Inc., 2-3-6 Otemachi, Chiyoda-ku, Tokyo 100-8141, Japan

Received 19 August 2008 ; accepted 24 September 2008.

Recent advances in DNA sequencers are accelerating genome sequencing, especially in microbes, and complete and draft genomes from various species have been sequenced in rapid succession. Here, we present a comprehensive gene prediction tool, the MetaGeneAnnotator (MGA), which precisely predicts all kinds of prokaryotic genes from a single or a set of anonymous genomic sequences having a variety of lengths. The MGA integrates statistical models of prophage genes, in addition to those of bacterial and archaeal genes, and also uses a self-training model from input sequences for predictions. As a result, the MGA sensitively detects not only typical genes but also atypical genes, such as horizontally transferred and prophage genes in a prokaryotic genome. In this paper, we also propose a novel approach for analyzing the ribosomal binding site (RBS), which enables us to detect species-specific patterns of the RBSs. The MGA has the ingenious RBS model based on this approach, and precisely predicts translation starts of genes. The MGA also succeeds in improving prediction accuracies for short sequences by using the adapted RBS models (96% sensitivity and 93% specificity for 700 bp fragments). These features of the MGA expedite wide ranges of microbial genome studies, such as genome annotations and metagenome analyses.

Key words: bioinformatics; gene-finding; prokaryote; phage; ribosomal binding site

* To whom correspondence should be addressed. Tel. +81 3-3277-0556. Fax. +81 3-3277-0568. E-mail: nog{at}mri.co.jp

Edited by Masahira Hattori


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