GO Based Tissue Specific Functions of Mouse using Countable Gene Expression Profiles

Yoichi Takenaka[1] (takenaka@ist.osaka-u.ac.jp)
Akiko Matsumoto[2]
Hideo Matsuda[1] (matsuda@ist.osaka-u.ac.jp)

[1]Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University Machikaneyama 1-3, Toyonaka City, Osaka 560-8531, Japan
[2]JASTEC Co., Ltd.,Takanawa 3-5-23, Minato-ku, Tokyo Japan


Abstract

We present a new method to describe tissue-specific function that leverages the advantage of the Cap Analysis of Gene Expression (CAGE) data. The CAGE expression data represent the number of mRNAs of each gene in a sample. The feature enables us to compare or add the expression amount of genes in the sample. As usual methods compared the gene expression values among tissues for each gene respectively and ruled out to compare them among genes, they have not exploited the feature to reveal tissue specificity. To utilize the feature, we used Gene Ontology terms (GO-terms) as unit to sum up the expression values and described specificities of tissues by them. We regard GO-terms as events that occur in the tissue according to probabilities that are defined by means of the CAGE. Our method is applied to mouse CAGE data on 22 tissues. Among them, we show the results of molecular functions and cellular components on liver. We also show the most expressed genes in liver to compare with our method. The results agree well with well-known specific functions such as amino acid metabolisms of liver. Moreover, the difference of inter-cellular junction among liver, lung, heart, muscle and prostate gland are apparently observed. The results of our method provide researchers a clue to the further research of the tissue roles and the deeper functions of the tissue-specific genes. All the results and supplementary materials are available via our web site.

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Japanese Society for Bioinformatics