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

Charles D. Johnson, Yoganand Balagurunathan, Mahlet G. Tadesse, M. Hadi Falahatpisheh, Marcel Brun, Mary K. Walker, Edward R. Dougherty, Kenneth S. Ramos

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

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 (Ahr). To maximize the number of possible gene-gene combinations, data sets from murine embryonic kidney, fetal heart, and vascular smooth muscle cells challenged in vitro with ligands of the Ahr were used to create predictor/training data sets. Biologically relevant gene predictor sets were calculated for Ahr, 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 Ahr ligands.

Original languageEnglish (US)
Pages (from-to)403-412
Number of pages10
JournalEnvironmental health perspectives
Volume112
Issue number4
DOIs
StatePublished - Mar 2004
Externally publishedYes

Keywords

  • Aryl hydrocarbon receptor
  • Bioinformatics
  • Gene networks
  • Genomics

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health
  • Health, Toxicology and Mutagenesis

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