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A database for the provisional identification of species using only genotypes: web-based genome profiling

Takehiro Watanabe, Ayumu Saito, Yusuke Takeuchi, Mohammed Naimuddin and Koichi Nishigaki*

Author Affiliations

Department of Functional Materials Science, Saitama University, 255 Shimo-Okubo, Saitama, Saitama 338-8570, Japan

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Genome Biology 2002, 3:research0010-research0010.8  doi:10.1186/gb-2002-3-2-research0010

Published: 28 January 2002



For a long time one could not imagine being able to identify species on the basis of genotype only as there were no technological means to do so. But conventional phenotype-based identification requires much effort and a high level of skill, making it almost impossible to analyze a huge number of organisms, as, for example, in microbe-related biological disciplines. Comparative analysis of 16S rRNA has been changing the situation, however. We report here an approach that will allow rapid and accurate phylogenetic comparison of any unknown strain to all known type strains, enabling tentative assignments of strains to species. The approach is based on two main technologies: genome profiling and Internet-based databases.


A complete procedure for provisional identification of species using only their genomes is presented, using random polymerase chain reaction, temperature-gradient gel electrophoresis, image processing to generate 'species-identification dots' (spiddos) and data processing. A database website for this purpose was also constructed and operated successfully. The protocol was standardized to make the system reproducible and reliable. The overall methodology thus established has remarkable aspects in that it enables non-experts to obtain an initial species identification without a lot of effort and is self-developing; that is, species can be determined more definitively as the database is used more and accumulates more genome profiles.


We have devised a methodology that enables provisional identification of species on the basis of their genotypes only. It is most useful for microbe-related disciplines as they face the most serious difficulties in species identification.