RESUMEN
BACKGROUND: Contrary to the traditional biology approach, where the expression patterns of a handful of genes are studied at a time, microarray experiments enable biologists to study the expression patterns of many genes simultaneously from gene expression profile data and decipher the underlying hidden biological mechanism from the observed gene expression changes. While the statistical significance of the gene expression data can be deduced by various methods, the biological interpretation of the data presents a challenge. RESULTS: A method, called CisTransMine, is proposed to help infer the underlying biological mechanisms for the observed gene expression changes in microarray experiments. Specifically, this method will predict potential cis-regulatory elements in promoter regions which could regulate gene expression changes. This approach builds on the MotifADE method published in 2004 and extends it with two modifications: up-regulated genes and down-regulated genes are tested separately and in addition, tests have been implemented to identify combinations of transcription factors that work synergistically. The method has been applied to a genome wide expression dataset intended to study myogenesis in a mouse C2C12 cell differentiation model. The results shown here both confirm the prior biological knowledge and facilitate the discovery of new biological insights. CONCLUSION: The results validate that the CisTransMine approach is a robust method to uncover the hidden transcriptional regulatory mechanisms that can facilitate the discovery of mechanisms of transcriptional regulation.
RESUMEN
The potential therapeutic value of resveratrol in age-related disease settings including cancer, diabetes, and Alzheimer's has emerged from a rapidly growing body of experimental evidence. Protection from oxidative stress appears to be a common feature of resveratrol that may be mediated through SirT1, though more specific molecular mechanisms by which resveratrol mediates its effects remain unclear. This has prompted an upsurge in cell-based mechanistic studies, often incorporating reporter assays for pathway elucidation in response to resveratrol treatment. Here, we report that resveratrol potently inhibits firefly luciferase with a K(i) value of 2microM, and caution that this confounding element may lead to compromised data interpretation.