Genomewide Gene Expression Analysis Using cDNA Microarrays

Abstract

Understanding when and where the constellation of genes in a genome are expressed provides important information about the state of a tissue. Changes in gene expression are a driving force in cell differentiation, proliferation, and death. Abnormal gene expression as a direct consequence of genomic amplification or deletion, or indirectly, owing to mutation in regulatory proteins, underlies many diseases. Cancer is the exemplar of this concept (see CGAP: http://www.ncbi.nlm.nih.gov/ncicgap/). RNA expression analysis can be broadly divided into two approaches: the monitoring of expression of an individual gene and parallel analysis of many genes. This distinction is not simply a matter of degree. Detailed expression analysis of an individual gene, usually cloned by some functional criteria, is performed as part of a systematic characterization of the gene. When many genes are analyzed in parallel, the aim is often to concentrate on differences in gene expression between two samples, such as tumor vs normal, which may contribute to phenotypic differences. Such studies can be a powerful means of systematically searching for new prognostic markers or for genes that are central to disease initiation or progression (1–6). Comprehensive profiling of RNA expression patterns can provide a “global” report on the state of a cell or tissue, e.g., the direction of metabolic processes in a cell (7) or its response to stress or other stimuli (8).