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Genome Profiling (GP) Method Based Classification of Insects: Congruence with That of Classical Phenotype-Based One

BACKGROUND: Ribosomal RNAs have been widely used for identification and classification of species, and have produced data giving new insights into phylogenetic relationships. Recently, multilocus genotyping and even whole genome sequencing-based technologies have been adopted in ambitious comparativ...

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Detalles Bibliográficos
Autores principales: Ahmed, Shamim, Komori, Manabu, Tsuji-Ueno, Sachika, Suzuki, Miho, Kosaku, Akinori, Miyamoto, Kiyoshi, Nishigaki, Koichi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3166070/
https://www.ncbi.nlm.nih.gov/pubmed/21912611
http://dx.doi.org/10.1371/journal.pone.0023963
Descripción
Sumario:BACKGROUND: Ribosomal RNAs have been widely used for identification and classification of species, and have produced data giving new insights into phylogenetic relationships. Recently, multilocus genotyping and even whole genome sequencing-based technologies have been adopted in ambitious comparative biology studies. However, such technologies are still far from routine-use in species classification studies due to their high costs in terms of labor, equipment and consumables. METHODOLOGY/PRINCIPAL FINDINGS: Here, we describe a simple and powerful approach for species classification called genome profiling (GP). The GP method composed of random PCR, temperature gradient gel electrophoresis (TGGE) and computer-aided gel image processing is highly informative and less laborious. For demonstration, we classified 26 species of insects using GP and 18S rDNA-sequencing approaches. The GP method was found to give a better correspondence to the classical phenotype-based approach than did 18S rDNA sequencing employing a congruence value. To our surprise, use of a single probe in GP was sufficient to identify the relationships between the insect species, making this approach more straightforward. CONCLUSION/SIGNIFICANCE: The data gathered here, together with those of previous studies show that GP is a simple and powerful method that can be applied for actually universally identifying and classifying species. The current success supported our previous proposal that GP-based web database can be constructible and effective for the global identification/classification of species.