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1 Renal Division, Department of Medicine
2 Center for Neurologic Diseases, Brigham and Womens Hospital, Harvard Medical School, Boston 02115
3 Department of Physics, Wesleyan University, Middletown, Connecticut 06459
4 Bioinformatics and Metabolic Engineering Laboratory, Department of Chemical Engineering, Massachusetts Institutes of Technology, Cambridge, Massachusetts 01890
5 Bioinformatics Program
6 Department of Biomedical Engineering, Bioinformatics Program, Boston University, Boston 02215
7 Department of Pathology, Brigham and Womens Hospital, Harvard Medical School, Boston 02115
8 Center for Neurologic Diseases, and Division of Neuropathology, Department of Pathology, Brigham and Womens Hospital, Harvard Medical School, Boston 02115
9 Molecular Neurogenetics Unit, Massachusetts General Hospital, Charlestown Massachusetts 02129
10 Division of Womens and Perinatal Pathology, Department of Pathology
11 Division Thoracic Surgery
12 Cardiovascular Division, Brigham and Womens Hospital, Boston, Massachusetts 02115
13 Affymetrix, Inc., Santa Clara, California 95051
This study creates a compendium of gene expression in normal human tissues suitable as a reference for defining basic organ systems biology. Using oligonucleotide microarrays, we analyze 59 samples representing 19 distinct tissue types. Of
7,000 genes analyzed, 451 genes are expressed in all tissue types and designated as housekeeping genes. These genes display significant variation in expression levels among tissues and are sufficient for discerning tissue-specific expression signatures, indicative of fundamental differences in biochemical processes. In addition, subsets of tissue-selective genes are identified that define key biological processes characterizing each organ. This compendium highlights similarities and differences among organ systems and different individuals and also provides a publicly available resource (Human Gene Expression Index, the HuGE Index, http://www.hugeindex.org) for future studies of pathophysiology.
microarrays; human tissues; gene expression; bioinformatics
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