Detecting and profiling tissue-selective genes

Abstract

The widespread use of DNA microarray technologies has generated large amounts of data from various tissue and/or cell types. These data set the stage to answer the question of tissue specificity of human transcriptome in a comprehensive manner. Our focus is to uncover the tissue-gene relationship by identifying genes that are preferentially expressed in a small number of tissue types. The tissue selectivity would shed light on the potential physiological functions of these genes and provides an indispensable reference to compare against disease pathophysiology and to identify or validate tissue-specific drug targets. Here we describe a systematic computational and statistical approach to profile gene expression data to identify tissue-selective genes with the use of a more extensive data set and a well-established multiple-comparison procedure with error rate control. Expression data of 35,152 probe sets in 97 normal human tissue types were analyzed, and 3,919 genes were identified to be selective to one or a few tissue types. We presented results of these tissue-selective genes and compared them to those identified by other studies.