Genome-Scale Gene Expression Pro les
Mapped onto the Pathway and Genome Maps in KEGG
Mitsuteru Nakao 1
Kazushige Sato 2
nakao@kuicr.kyoto-u.ac.jp
kazs@scl.kyoto-u.ac.jp
Tomomi Kamiya 1
Yoshiko Kimura 1
Minoru Kanehisa 1

tomomi@scl.kyoto-u.ac.jp
12

yoshiko@scl.kyoto-u.ac.jp

kanehisa@kuicr.kyoto-u.ac.jp

Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan
Nihon SiliconGraphics K.K., Umeda, Kita-ku, Osaka 530-0001, Japan

1 Introduction
The emerging technology of DNA chips and microarrays makes it possible to simultaneously analyze
the expression of many genes, such as the whole set of genes in the completely sequenced genome. We
have been developing a system for network oriented analysis and visualization of such genome-scale
gene expression data. It projects the time-series data of gene expression pro les on the functional
relations map (KEGG pathway map) and the positional neighbors map (KEGG genome map), anduncovers underlying events in di erential gene expression patterns between the reference and theperturbed state (e.g., the wild-type and a disruptant, or the control and an environmental shift)

2 Data and Methods
We have developed interfaces to the tools to adapt to any gene expression pro les data. In this report
we use the numerical data for the microarray gene expression pro les of Saccharomyces cerevisiae [1]obtained by anonymous ftp [2]. The experiments involve two types of data, the environmental changeof diauxic shift and the genetic change of deletion or overexpression of a transcription factor.
We use a part of KEGG (Kyoto Encyclopedia of Genes and Geneomes) [3] database; the positional
neighbor data as represented by the GENOME graphical maps and the functional relation data asrepresented by the PATHWAY graphical maps. The basic colorization tool has been developed and it
is made available in KEGG.
URL http://www.genome.ad.jp/kegg-bin/mk point pathway multi html for pathway maps
URL http://www.genome.ad.jp/kegg-bin/mk point genome multi html for genome maps
The coloring strategy is as follows. The qualitative information in the data is represented by thedi erence in color, and the quantitative information is represented by the color depth. The changeof two gene expression pro les between the reference state and the perturbed state is represented by
two alternative colors for increased and decreased expression, a third color for no change, and a fourthcolor for no expression in both states. The time-series data representation is investigated such as GIF
animation.

3 Results and Discussions
The publicly released microarray data of Saccharomyces cerevisiae was investigated. It contained ametabolic shift with genetic reprogramming, referred to as the diauxic shift from fermentation torespiration. This genetic reprogramming involved in basic cellular processes such as carbohydrate
metabolism, nucleic acid and protein synthesis and energy metabolism. Fig. 1 shows the diauxic
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Figure 1: Gene expression pro le mapped onto the PATHWAY (left) map and GENOME (right) map.
change that is automatically mapped on the pathway map of TCA cycle in KEGG. It is interesting tonote that although there is no operon structure for the TCA cycle genes in Saccharomyces cerevisiae
the bacterial genomes contain two separate operons, whenever they do have operons, that correspondto the upper and lower portions of the cycle as represented by di erent colors in Fig. 1. This suggeststhat there is a mechanism to cooperatively regulate the expression of genes that are far apart in thegenome.
In general the correlation of gene expression patterns suggests functional relations and would assist
to assign functions to hypothetical genes. By analyzing the positional correlation of synchronizedexpression of genes, common upstream activating sequences may also be found.

Acknowledgements
This work was supported in part by a Grant-in-Aid \Genome Science" for Scienti c Research on
Priority Areas from the Ministry of Education, Science, Sports and Culture in Japan. The computation time was provided by the Supercomputer Laboratory, Institute for Chemical Research, Kyoto
University.

References[1] DeRisi, J.L., Lyer, V.R., and Brown, P.O., Exploring the Metabolic and Genetic Control of Gene
Expression on a Genomic Scale, Science, 278:680{686, 1997.
[2] URL http://cmgm.stanford.edu/pbrown/explore/index.html[3] Kanehisa, M., KEGG - from genes to biochemical pathways, Molecular Biology Databases(Letovsky, S., ed.), in press, Kluwer Academic Press, 1998.

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