Gene interaction network suggests dioxin induces a significant linkage between aryl hydrocarbon receptor and retinoic acid receptor beta

Environmental Health Perspectives
Hiroyoshi ToyoshibaChristopher J Portier

Abstract

Gene expression arrays (gene chips) have enabled researchers to roughly quantify the level of mRNA expression for a large number of genes in a single sample. Several methods have been developed for the analysis of gene array data including clustering, outlier detection, and correlation studies. Most of these analyses are aimed at a qualitative identification of what is different between two samples and/or the relationship between two genes. We propose a quantitative, statistically sound methodology for the analysis of gene regulatory networks using gene expression data sets. The method is based on Bayesian networks for direct quantification of gene expression networks. Using the gene expression changes in HPL1A lung airway epithelial cells after exposure to 2,3,7,8-tetrachlorodibenzo-(Italic)p(/Italic)-dioxin at levels of 0.1, 1.0, and 10.0 nM for 24 hr, a gene expression network was hypothesized and analyzed. The method clearly demonstrates support for the assumed network and the hypothesis linking the usual dioxin expression changes to the retinoic acid receptor system. Simulation studies demonstrated the method works well, even for small samples.

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Jul 3, 2010·Redox Report : Communications in Free Radical Research·H SoneT Fukuda
Mar 28, 2008·Journal of Toxicology and Environmental Health. Part B, Critical Reviews·Karen P Phillips, Nongnuj Tanphaichitr
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Dec 16, 2004·Environmental Health Perspectives·Takeharu YamanakaChristopher J Portier
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Jun 24, 2008·Journal of Toxicology and Environmental Health. Part a·Marco Grzegorczyk
Jan 8, 2010·Gene Regulation and Systems Biology·Simon Rosenfeld

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