Abstract:
In eukaryotic cells, most genes are found to be regulated by various temporary andpermanent transcription factors whose activity levels change as response to perturbations.Discovering the underlying mechanism of complex cellular processes and responses to perturbations is a major challenge in post-genomic research. In this M.S. study, so-called-key' transcription factors (transcription factors around which the most significanttranscriptional changes occur) responding significantly to genetic and environmentalperturbations were identified in yeast Saccharomyces cerevisiae by an algorithm based on hypothesis-driven data analysis. In contrast to existing approaches, the proposed approachuses network topology for determining the activity levels of transcription factors. Theidentification of the perturbation-responsive key transcription factors provides a dynamicperspective of transcriptional regulation which has central role in cellular function andstructure. An extensive genome-scale map of transcriptional regulatory network in S. cerevisiae was constructed and integrated with gene expression data. The analysis of yeastdata suggests that the method is capable of successfully identifying perturbation-responsivekey transcription factors and it provides valuable information about transcription factors and their conditional/temporal behavior. In this study, it was also showed that once the keytranscription factors are identified, the perturbation-responsive subnetworks might berevealed by interconnecting the key transcription factors and their target genesdifferentially expressed when the same perturbation is introduced. Furthermore, for each key transcription factor, its best candidate target genes were predicted (their regulatoryinteractions are not experimentally justified yet), which are differentially expressed afterthe same perturbations and their promoter regions contain bindig site(s) for the keytranscription factor.
