Selection and validation of microarray candidate genes from subregions and subnuclei of the brain

DNA array technology now allows an enormous amount of expression data to be obtained. For large-scale gene profiling enterprises, this is of course welcome. However, the scientist interested in follow-up studies of a handful of differentially expressed genes may find it hard to sift through the vast datasets to pinpoint genes with the most desirable and reliable behaviors. Here, we present the methodology we have employed to discover genes differentially expressed in the adult mouse brain. We first used Affymetrix microarrays to compare gene expression from five different brain regions: the amygdala, cerebellum, hippocampus, olfactory bulb, and periaqueductal gray. Second, we identified genes differentially expressed within three distinct amygdala subnuclei. In this case, the tissue was microdissected by laser-capture to minimize contamination from adjacent subnuclei, and extracted RNA was subjected to three rounds of linear amplification prior to hybridization to the microarrays. To select candidate genes, we developed a custom algorithm to identify those genes with the most robust changes in expression across different replicate samples. Confirmation of expression patterns with in situ hybridization uncovered further criteria to consider in the selection process.