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Bioinformatics Advance Access published online on September 13, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti666
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received June 7, 2005
Revised September 5, 2005
Accepted September 6, 2005

Article

Prediction of glycan structures from gene expression data based on glycosyltransferase reactions

Shin Kawano 1, Kosuke Hashimoto 1, Takashi Miyama 1, Susumu Goto 1, and Minoru Kanehisa 1*

1 Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan

* To whom correspondence should be addressed.
Minoru Kanehisa, E-mail: kanehisa{at}kuicr.kyoto-u.ac.jp


  Abstract

Motivation: Glycan chains are synthesized by a combination of several kinds of glycosyltransferases. Thus, once we know the repertoire of glycosyltransferases in the genome, in the transcriptome or in the proteome, it should in principle be possible to predict the repertoire of possible glycan structures in an organism or at a specific stage of the cell. Here, we show that a repertoire of glycan structures can be predicted from the set of glycosyltransferases in the transcriptome. That is, using knowledge about glycan structure characteristics, we can predict glycan structure from incomplete or noisy data such as DNA microarray data.

Results: First, we constructed a reaction pattern library consisting of bond-formation patterns of glycosyltransferase reactions and investigated the co-occurrence frequencies of all reaction patterns in the glycan database. Then, glycan structures were predicted using this library and a co-occurrence score. A penalty score was also implemented in the prediction method. Next, we examined the performance of prediction by the leave-one-out cross validation method using individual reaction pattern profiles in the KEGG GLYCAN database as virtual expression profiles. The accuracy of prediction was 81%. Finally, we applied the prediction method to real expression data. Using expression profiles from the human carcinoma cell, glycan structures with sialic acid and sialyl Lewis X epitope were predicted, which corresponded well with experimental results.

Supplementaly Information: http://web.kuicr.kyoto-u.ac.jp/~kawano/suppl/bioinfo2005/.


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