Unraveling gene-gene interactions regulated by ligands of the aryl hydrocarbon receptor.

TLDR

The authors constructed predictor/training datasets from murine embryonic kidney, fetal heart, and vascular smooth muscle cells exposed in vitro to Ahr ligands, calculated biologically relevant gene predictor sets for Ahr, CYP1B1, IGFBP‑5, LOX, and OPN, categorized transcript levels into ternary expressions, and evaluated all possible gene‑gene combinations as predictors of transitional levels using a multivariate nonlinear coefficient of determination. The study demonstrates that co‑expressed gene sets with additive probabilistic relationships can predict and resolve Ahr‑ligand‑regulated gene‑gene interactions. Keywords: aryl hydrocarbon receptor, bioinformatics, gene networks, genomics; published in Environmental Health Perspectives, 112:403‑412 (2004).

Abstract

The co-expression of genes coupled to additive probabilistic relationships was used to identify gene sets predictive of the complex biological interactions regulated by ligands of the aryl hydrocarbon receptor ((Italic)Ahr(/Italic)). To maximize the number of possible gene-gene combinations, data sets from murine embryonic kidney, fetal heart, and vascular smooth muscle cells challenged (Italic)in vitro(/Italic) with ligands of the (Italic)Ahr(/Italic) were used to create predictor/training data sets. Biologically relevant gene predictor sets were calculated for (Italic)Ahr(/Italic), cytochrome P450 1B1, insulin-like growth factor-binding protein-5, lysyl oxidase, and osteopontin. Transcript levels were categorized into ternary expressions and target genes selected from the data set and tested for all possible combinations using three gene sets as predictors of transitional level. The goodness of prediction for each set was quantified using a multivariate nonlinear coefficient of determination. Evidence is presented that predictor gene combinations can be effectively used to resolve gene-gene interactions regulated by (Italic)Ahr(/Italic) ligands. (Italic)Key words:(/Italic) aryl hydrocarbon receptor, bioinformatics, gene networks, genomics. (Italic)Environ Health Perspect (/Italic)112:403-412 (2004). [Online 14 January 2004]