All cells constantly adjust their gene expression programs in response to environmental and genetic perturbations. The changes in gene expression are mediated by a complex regulatory network, of which transcriptional regulation is a major component. Cellular transcription networks regulate essentially all biological processes, from development to cancer and aging. The goal of the proposed research is to develop novel theoretical and experimental approaches to systematically analyze the structure, function, and evolution of transcription networks, using yeast as a model organism. Building on the significant progress we have made in the previous granting period, we will continue our efforts to reconstruct yeast transcription networks at a genomic scale. To understand the physiological importance of the network structure, we will quantitatively analyze the growth phenotypes of the deletion mutants of all the transcription factors in the genome under a variety of conditions, and connect global gene expression program to the fitness of the cell. We will expand the scope of our study to incorporate genome- wide nucleosome positioning information, to better understand the relationship between nucleosome positioning and transcriptional regulation. We will systematically perform comparative analysis of transcriptional circuits in different yeast species, in order to derive basic principles governing their evolution. Together these systems-level studies will reveal the basic functional and evolutionary constraints and design principles of transcription networks beyond the yeast system. In addition, specific knowledge of transcriptional regulation in yeast can be transferred to higher eukaryotes including humans, since many biological processes are highly conserved.
Cellular transcription networks regulate essentially all biological processes, including development, cancer and aging. Mis-regulation of these processes leads to human diseases. A global understanding of the structure, function and evolution of the transcription networks in yeast will likely lead to general principles applicable to humans and have a significant impact on human health.
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