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DNA Research Advance Access published online on October 3, 2009
DNA Research, doi:10.1093/dnares/dsp018
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© The Author 2009. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

A Novel Bioinformatics Strategy for Function Prediction of Poorly-Characterized Protein Genes Obtained from Metagenome Analyses

Takashi Abe1,*, Shigehiko Kanaya2, Hiroshi Uehara1 and Toshimichi Ikemura1

1 Nagahama Institute of Bio-Science and Technology, Tamura-cho 1266, Nagahama-shi, Shiga-ken 526-0829, Japan
2 Department of Bioinformatics and Genomes, Graduate School of Information Science, Nara Institute of Science and Technology, Takayama, Ikoma, Nara 630-0101, Japan

Received 16 July 2009 ; accepted 3 September 2009.

As a result of remarkable progresses of DNA sequencing technology, vast quantities of genomic sequences have been decoded. Homology search for amino acid sequences, such as BLAST, has become a basic tool for assigning functions of genes/proteins when genomic sequences are decoded. Although the homology search has clearly been a powerful and irreplaceable method, the functions of only 50% or fewer of genes can be predicted when a novel genome is decoded. A prediction method independent of the homology search is urgently needed. By analyzing oligonucleotide compositions in genomic sequences, we previously developed a modified Self-Organizing Map ‘BLSOM’ that clustered genomic fragments according to phylotype with no advance knowledge of phylotype. Using BLSOM for di-, tri- and tetrapeptide compositions, we developed a system to enable separation (self-organization) of proteins by function. Analyzing oligopeptide frequencies in proteins previously classified into COGs (clusters of orthologous groups of proteins), BLSOMs could faithfully reproduce the COG classifications. This indicated that proteins, whose functions are unknown because of lack of significant sequence similarity with function-known proteins, can be related to function-known proteins based on similarity in oligopeptide composition. BLSOM was applied to predict functions of vast quantities of proteins derived from mixed genomes in environmental samples.

Key words: batch learning SOM; oligopeptide frequency; protein function; metagenome; alignment-free clustering

* To whom correspondence should be addressed. Tel. +81 749-64-8126. Fax. +81 749-64-8126. E-mail: takaabe{at}nagahama-i-bio.ac.jp

Edited by Katsumi Isono


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