Revealing the gene regulatory systems among DNA and proteins in living cells is one of the central aims of systems biology. In this study, I used Structural Equation Modeling (SEM) in combination with stepwise factor analysis to infer the protein-DNA interactions for gene expression control from only gene expression profiles, in the absence of protein information. I applied my approach to infer the causalities within the well-studied serial transcriptional regulation composed of GAL-related genes in yeast. This allowed me to reveal the hierarchy of serial transcriptional regulation, including previously unclear protein-DNA interactions. The validity of the constructed model was demonstrated by comparing the results with previous reports describing the regulation of the transcription factors. Furthermore, the model revealed combinatory regulation by Gal4p and Gal80p. In this study, the target genes were divided into three types: those regulated by one factor and those controlled by a combination of two factors.
|Evidence ID||Analyze ID||Interactor||Interactor Systematic Name||Interactor||Interactor Systematic Name||Type||Assay||Annotation||Action||Modification||Phenotype||Source||Reference||Note|
|Evidence ID||Analyze ID||Gene||Gene Systematic Name||Gene Ontology Term||Gene Ontology Term ID||Qualifier||Aspect||Method||Evidence||Source||Assigned On||Reference||Annotation Extension|
|Evidence ID||Analyze ID||Gene||Gene Systematic Name||Phenotype||Experiment Type||Experiment Type Category||Mutant Information||Strain Background||Chemical||Details||Reference|
|Evidence ID||Analyze ID||Regulator||Regulator Systematic Name||Target||Target Systematic Name||Experiment||Conditions||Strain||Source||Reference|