A comprehensive strategy enabling high-resolution functional analysis of the yeast genome

Abstract

Functional genomic studies in Saccharomyces cerevisiae have contributed enormously to our understanding of cellular processes. Their full potential, however, has been hampered by the limited availability of reagents to systematically study essential genes and the inability to quantify the small effects of most gene deletions on growth. Here we describe the construction of a library of hypomorphic alleles of essential genes and a high-throughput growth competition assay to measure fitness with unprecedented sensitivity. These tools dramatically increase the breadth and precision with which quantitative genetic analysis can be performed in yeast. We illustrate the value of these approaches by using genetic interactions to reveal new relationships between chromatin-modifying factors and to create a functional map of the proteasome. Finally, by measuring the fitness of strains in the yeast deletion library, we addressed an enigma regarding the apparent prevalence of gene dispensability and found that most genes do contribute to growth.A fundamental challenge of the post-genomic era is to assign functions to genes and to understand how gene networks are organized to execute diverse cellular processes. The budding yeast S. cerevisiae has served as a premier eukaryotic model system for this task [1][2][3][4][5] , and a library of strains in which each nonessential yeast gene is deleted has been an important tool for these efforts 1 . This resource has made it possible to assess the contribution of each nonessential gene to any measurable phenotype.These genomic approaches can be extended by systematically measuring genetic interactions 5 . Genetic interactions describe how the phenotype associated with compromising one gene is modulated by perturbing a second gene. Such effects can be defined quantitatively Correspondence should be addressed to J.S.W. (weissman@cmp.ucsf.edu). 6 These authors contributed equally to this work.Note: Supplementary information is available on the Nature Methods website. HHMI Author Manuscript HHMI Author Manuscript HHMI Author Manuscriptas the difference between the observed magnitude of a phenotype for a double mutant and that expected if the genes do not interact, as given by ε= W AB − W A × W B , where ε is the interaction score and W X refers to the phenotype seen in genetic background X (refs. 6,7 ). Theoretical considerations and empirical experience have established the utility of genetic interactions in defining functional relationships between genes 2,3,6,8 . Early studies focused on 'synthetic sick or lethal' or 'negative' interactions 3 , in which the phenotype associated with perturbing two genes simultaneously is more severe than expected given the phenotypes of the individual gene perturbations (ε < 0). More recently, interactions in which the phenotype of a double mutant is less severe than expected (ε > 0, 'alleviating' or 'positive' interactions) have proven highly valuable as they often occur between genes that have closely related functions-for example, between ...

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