TitleA DNA microarray survey of gene expression in normal human tissues.
Publication TypeJournal Article
Year of Publication2005
AuthorsShyamsundar, R, Kim, YH, Higgins, JP, Montgomery, K, Jorden, M, Sethuraman, A, van de Rijn, M, Botstein, D, Brown, PO, Pollack, JR
JournalGenome Biol
Volume6
Issue3
PaginationR22
Date Published2005
KeywordsCluster Analysis, Gene Expression Profiling, Genomics, Humans, Oligonucleotide Array Sequence Analysis, RNA, Messenger, Tissue Distribution
Abstract

BACKGROUND: Numerous studies have used DNA microarrays to survey gene expression in cancer and other disease states. Comparatively little is known about the genes expressed across the gamut of normal human tissues. Systematic studies of global gene-expression patterns, by linking variation in the expression of specific genes to phenotypic variation in the cells or tissues in which they are expressed, provide clues to the molecular organization of diverse cells and to the potential roles of the genes.

RESULTS: Here we describe a systematic survey of gene expression in 115 human tissue samples representing 35 different tissue types, using cDNA microarrays representing approximately 26,000 different human genes. Unsupervised hierarchical cluster analysis of the gene-expression patterns in these tissues identified clusters of genes with related biological functions and grouped the tissue specimens in a pattern that reflected their anatomic locations, cellular compositions or physiologic functions. In unsupervised and supervised analyses, tissue-specific patterns of gene expression were readily discernable. By comparative hybridization to normal genomic DNA, we were also able to estimate transcript abundances for expressed genes.

CONCLUSIONS: Our dataset provides a baseline for comparison to diseased tissues, and will aid in the identification of tissue-specific functions. In addition, our analysis identifies potential molecular markers for detection of injury to specific organs and tissues, and provides a foundation for selection of potential targets for selective anticancer therapy.

Alternate JournalGenome Biol.