A method for exploring Tissue-Specific functions based on information content of gene ontology terms using CAGE tags

Abstract

Gene expressions are different depending on tissue types and developmental stages. It is important to analyze how each gene is expressed. One way of analyzing the gene expression pattern is to find the tissue-specific functions. It is useful to understand how vital activities go on. Nowadays, DNA microarray has been widely used to observe gene expressions exhaustively. However, it is impossible to compare the expression value of a gene to that of the other genes because the gene expression value of a condition is measured as a proportion of that of the same gene at a control condition. Therefore, we cannot determine whether one gene is more expressed than the other genes or not and what is the tissue-specific function. Cap Analysis Gene Expression (CAGE) allows high throughput analysis of gene expressions by counting the number of cDNAs of expressed genes. CAGE enables us to compare the expression value of the gene to that of the other genes in the same tissue. In this research, we propose a method for exploring tissue-specific functions by using the data measured by CAGE. To find out tissue-specificity, one of the simplest ways is to assume that the function of the most expressed gene is regarded as the most tissue-specific. However, the most expressed gene in a tissue might highly express in all tissues such as house keeping genes. Function of such genes cannot be tissue-specific. In order to remove them, we propose a measurement of tissue specificity of the functions that is based on information contents of Gene Ontology terms. We apply our method to the data of 14 tissues of human and 22 tissues of mouse. We picked up the results of mouse and human livers and that well-known functions of liver such as immune function became high rank.