Determination of nitric oxide-donor effects on tissue gene expression in vivo using low-density gene arrays

Gene array technology has been used to examine gene expression changes following drug treatments, including administration of nitric oxide (NO) donors. High-density arrays represent a powerful and popular method to analyze a large number of genes simultaneously. On the other hand, low-density arrays, available commercially at a lower cost, allow for the use of gene-specific primers, which reduces the risk of cross-hybridization among genes with similar sequence. For certain experiments in which the hypothesis is focused on a selected set of genes, use of low-density arrays might be more productive and cost-effective. Here, we describe our experience using low-density arrays to examine the effect of exposure to the NO-donor isobutyl nitrite on the expression of 23 cancer- and angiogenesis-related genes in mouse tissues. Detailed descriptions of data capture procedures, statistical tests, and confirmation studies using real-time quantitative (RTQ) reverse transcription polymerase chain reaction (RT-PCR) are presented. Three simple statistical methods, namely Student's t test, significant analysis of microarrays (SAM), and permutation adjusted t statistics (PATS), were applied on our gene array data, and their utilities were compared. All three methods yielded concordant results for the most significant genes, namely vascular endothelial growth factor (VEGF), VEGF receptor 3, Smad5, and Smad7. RT-PCR confirmed VEGF upregulation as observed via gene arrays. PATS appeared to be more robust than SAM in handling our small gene array data set. This statistical method, therefore, appears more suited for analyzing low-density gene array data. We conclude that low-density gene array is a useful screening method that can be performed with lower cost and less cumbersome data treatment.