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    Cell Cycle. 2006 Mar;5(6):592-5. Epub 2006 Mar 15.

    Revealing hidden relationships among yeast genes involved in chromosome segregation using systematic synthetic lethal and synthetic dosage lethal screens.

    Source

    Ottawa Institute of Systems Biology, Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, Ontario, Canada.

    Abstract

    The vast accumulation of knowledge from genome sequencing projects and studies with model organisms has presented a remarkable challenge to biologists: to understand the functions of thousands of highly conserved genes and how they work together to regulate fundamental cellular processes. This challenge is compounded by the inescapable reality that most genes are 'buffered' by other genes that contribute to the same biological processes, limiting the impact of phenotypic studies with single mutants. In budding yeast, functional genomic methods have been developed for the systematic application of established genetic techniques. In particular, the Synthetic Genetic Array (SGA) method allows genome-wide synthetic lethal (SL) and synthetic dosage lethal (SDL) screens thus enabling an unbiased survey of genetic interactions. We have used genes encoding components of the yeast kinetochore as a biological testbed for assaying the utility of SGA-based SL and SDL screens for revealing new pathways and genes involved in chromosome segregation. We identified 211 nonessential deletion mutants that were unable to tolerate either overexpression or loss of function of kinetochore genes. Our study uncovered a wealth of relationships between gene products that functionally interact with the kinetochore, and also highlighted the value of performing genome-wide screens with both hypomorphic and hypermorphic alleles of query genes. Here, we will highlight our recent kinetochore SGA genomic screens, in the broader context of applying complementary genetic screening approaches in the systematic exploration of biological pathways or functional complexes.

    PMID:
    16582600
    [PubMed - indexed for MEDLINE]
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