Eukaryotic cells grow and divide in an intricate series of events known collectively as the cell cycle, consisting of the ordered procession through DNA synthesis, mitosis and cell division, accompanied by complete reorganization of the cytoskeleton and organelles, and controlled growth of the daughter cell. In all, approx. 800 genes change expression over the course of the cell cycle, indicating the overall complexity of the process. Errors in cell cycle regulation play a fundamental role in a wide range of human diseases, including numerous cancers, hereditary disorders such as ataxia telangiectasia, and even chromosome missegregation diseases such as Down's syndrome. Most features of the cell cycle have been discovered one protein, mutant and gene at a time, but the complexity of this system argues that many new insights into cell cycle progression and regulation will come from an integrated examination of the hundreds of genes involved. We have developed novel methods ('computational genetics' methods) to reconstruct complex gene networks by using the information intrinsic in genomes and expression data about the relationships between the genes. In our preliminary work, we have demonstrated that we can reconstruct extensive gene networks with accuracies comparable to experimental techniques. We intend to apply these tools to reconstruct and characterize the network of genes controlling the yeast cell cycle. In the work proposed here, we will (A) integrate computational genetics methods and protein interactions to reconstruct a genome-wide network of yeast genes. Our initial results suggest we can reconstruct one of the most complete and most accurate gene networks known for any organism. (B) We will characterize the sub network derived for cell cycle-related genes, mapping connections between known ceil cycle systems and identifying new genes associated with these systems. (C) Finally, we will experimentally validate the computational results, characterizing the cell cycle related defects in yeast strains with deletions of genes linked in these networks to known cell cycle components. We anticipate that our nascent ability to reconstruct such extensive yeast gene networks will give us an interpretive framework for studies of the yeast cell cycle, allowing us to organize the hundreds of genes involved for more comprehensive analyses of their interplay, while also revealing the involvement of new genes and interactions between the cycle components.
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