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Mapping Genetic Interaction Networks in Yeast

Global quantitative analysis of genetic interactions provides a powerful approach for deciphering the roles of genes and mapping functional relationships amongst path-ways. Using colony size as a proxy for fitness, I developed a method for measuring ge-netic interactions from high-density arrays of yeast double mutants generated by synthet-ic genetic array (SGA) technology. I identified several experimental sources of systematic variation and developed normalization strategies to obtain accurate fitness measurements. I used this scoring method to map quantitative genetic interactions among 5.4 million yeast double mutants and generated the first functionally unbiased genetic interaction map of a eukaryotic cell. My map produced an unprecedented view of the cell in which genes of similar biological processes cluster together in coherent subsets and functionally interconnected bioprocesses map next to each other. We discovered several physiological and evolutionary gene features that are characteristic of genetic interaction hubs, and explored the relationship between genetic and protein-protein interaction networks. In particular, by comparing quantitative single and double mutant phenotypes, we identified specific cases of positive genetic interactions, termed genetic suppression, and constructed a global network of suppression interactions among protein complexes. I also demonstrated that an extensive and unbiased mapping of genetic interactions provides a key for interpreting chemical-genetic interactions and identifying drug targets. In addition, I used genome-wide SGA data to map profiles of genetic linkage along all sixteen yeast chromosomes. These linkage profiles recapitulated previously identified recombination patterns and uncovered an unexpected correlation between chromosome length and the extent of centromere-related recombination repression. These findings suggest a chromosome size-dependent mechanism for ensuring proper chromosome segregation and highlight the SGA methodology as a unique approach for systematic analysis of yeast meiotic recombination.

Identiferoai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OTU.1807/35167
Date19 March 2013
CreatorsBaryshnikova, Anastasija
ContributorsBoone, Charles, Bader, Gary D.
Source SetsLibrary and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada
Languageen_ca
Detected LanguageEnglish
TypeThesis

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