Quality Indicators Increase the Reliability of Microarray Data

Large-scale gene expression profiling with DNA microarrays opens new dimensions to molecular biology but still lacks the overall precision of traditional low-scale techniques. We developed a novel strategy of data processing linking search stringency to quality indicators for efficient detection of low-level, regulated genes. Using retinoid-induced differentiation of NB-4 promyelocytic cells, the variation of expression profiles between biological duplicates was studied and compared with the changes induced by all-trans retinoic acid (atRA) treatment. An analysis of 4320 genes showed that retinoic acid has mainly geneactivating function in NB-4 cells. Treatment with atRA for 18 hours induced metabolic genes that may be associated with cell differentiation and signaling factors triggering later events leading to apoptosis; cytokine genes were among the highest stimulated by atRA. Notably, we identified a regulatory loop inhibiting MYC action: as MYC was downregulated, a cognate repressor of MYC was upregulated.