RESUMO
IFN-gamma, a cytokine promoting cell-mediated immunity and antiviral effects, regulates the expression of a large set of genes involved in the immune response. Based on logistic regression, an in silico model for predicting IFN-gamma regulated transcription has been developed by scoring the transcription factor binding sites on the putative promoters of regulated versus not regulated genes derived from the microarray data of IFN-gamma treated human macrophages. The model effectively discriminates the transcription factor binding sites that confer responsiveness to IFN-gamma from those that do not. The model has 65% true positive and 22% false positive rates when evaluated on a small validation set. In order to identify potential IFN-gamma regulated genes in the whole genome, the model has been used to screen 13,668 promoter pairs of human-mouse orthologs/homologs from Ensembl, and 1,387 of them were predicted to be potentially regulated by IFN-gamma. In the pilot experiment, the regulation pattern of a subset of predicted genes that were not detected by microarray approach was evaluated by quantitative PCR. The results for the four novel genes, which are up regulated by IFN-gamma in human macrophages and identified by this approach, are described in the present communication.