Large-scale mapping of genetic interactions in Saccharomyces cerevisiae.
Published: 2005
Language: eng
Number of pages: 237
Description: In chapter four, I describe the application of SGA analysis to the large-scale mapping of genetic interactions. A genetic interaction network containing &sim;1000 genes and &sim;4000 interactions was mapped by crossing mutations in 132 different query genes into a set of &sim;4700 viable gene deletion mutants and scoring the double mutant progeny for fitness defects. Network connectivity is predictive of function because interactions often occur among functionally related genes. Genetic interactions are largely orthogonal (non-overlapping) with protein-protein interactions, but genes coding for proteins that occur in the same pathway or complex display similar patterns of genetic interactions. The genetic network shows dense local neighbourhoods, implying the position of a gene on a partially mapped network is predictive of interactions. Because genetic networks are likely conserved, synthetic genetic interactions may underlie the complex genetics associated with inherited phenotypes in other organisms.In chapter three, I describe the development of a new method for automated identification of genetic interactions, termed synthetic genetic array (SGA) analysis. SGA analysis allows systematic construction of double mutants and examination of their fitness on a genome-wide scale.Functional genomics approaches have provided the opportunity for systematic examination of all genes in a genome, generating functional information such as gene expression profiles, protein expression and localization profiles, protein-protein interaction networks, and systematic characterization of mutants. Budding yeast has been the organism of choice for many of these pioneering studies because of its facile genetics. Large-scale studies have made significant contributions to our understanding of complex biological systems, and this trend is continuously fueled by new development of high-throughput technologies.In this thesis, I describe a general strategy to study protein-protein interaction modules (chapter two). A protein-protein interaction network was generated by focusing on yeast SH3 domains and combining data derived from phage-display ligand consensus sequences and large-scale two-hybrid physical interactions. This study produced a network that is depleted of most false positive interactions and enriched for biologically relevant interactions.
Notes: Thesis (Ph.D.)--University of Toronto, 2005.

Electronic version licensed for access by U. of T. users.

Source: Dissertation Abstracts International, Volume: 66-06, Section: B, page: 2972.