Gene expression profiling of cerebellar development with high-throughput functional analysis.

Abstract

We measured the expression levels of 450 genes during mouse postnatal cerebellar development by quantitative PCR using RNA purified from layers of the cerebellar cortex. Principal component analysis of the data matrix demonstrated that the first and second components corresponded to general levels of gene expression and gene expression patterns, respectively. We introduced 288 of the 450 genes into PC12 cells using a high-throughput transfection assay based on atelocollagen and determined the ability of each gene to promote neurite outgrowth or cell proliferation. Five genes induced neurite outgrowth, and seven genes enhanced proliferation. Evaluation of the functional data and gene expression patterns showed that none of these genes exhibited elevated expression at maturation, suggesting that genes characteristic of mature neurons are not likely to participate in neuronal development. These results demonstrate that functional data can facilitate interpretation of expression profiles and identification of new molecules that participate in biological processes.