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      Ribosome Deficiency Protects Against ER Stress in Saccharomyces cerevisiae

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          Abstract

          In Saccharomyces cerevisiae, 59 of the 78 ribosomal proteins are encoded by duplicated genes that, in most cases, encode identical or very similar protein products. However, different sets of ribosomal protein genes have been identified in screens for various phenotypes, including life span, budding pattern, and drug sensitivities. Due to potential suppressors of growth rate defects among this set of strains in the ORF deletion collection, we regenerated the entire set of haploid ribosomal protein gene deletion strains in a clean genetic background. The new strains were used to create double deletions lacking both paralogs, allowing us to define a set of 14 nonessential ribosomal proteins. Replicative life-span analysis of new strains corresponding to ORF deletion collection strains that likely carried suppressors of growth defects identified 11 new yeast replicative aging genes. Treatment of the collection of ribosomal protein gene deletion strains with tunicamycin revealed a significant correlation between slow growth and resistance to ER stress that was recapitulated by reducing translation of wild-type yeast with cycloheximide. Interestingly, enhanced tunicamycin resistance in ribosomal protein gene deletion mutants was independent of the unfolded protein response transcription factor Hac1. These data support a model in which reduced translation is protective against ER stress by a mechanism distinct from the canonical ER stress response pathway and further add to the diverse yet specific phenotypes associated with ribosomal protein gene deletions.

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          The genetic landscape of a cell.

          A genome-scale genetic interaction map was constructed by examining 5.4 million gene-gene pairs for synthetic genetic interactions, generating quantitative genetic interaction profiles for approximately 75% of all genes in the budding yeast, Saccharomyces cerevisiae. A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function. The global network identifies functional cross-connections between all bioprocesses, mapping a cellular wiring diagram of pleiotropy. Genetic interaction degree correlated with a number of different gene attributes, which may be informative about genetic network hubs in other organisms. We also demonstrate that extensive and unbiased mapping of the genetic landscape provides a key for interpretation of chemical-genetic interactions and drug target identification.
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            Regulation of yeast replicative life span by TOR and Sch9 in response to nutrients.

            Calorie restriction increases life span in many organisms, including the budding yeast Saccharomyces cerevisiae. From a large-scale analysis of 564 single-gene-deletion strains of yeast, we identified 10 gene deletions that increase replicative life span. Six of these correspond to genes encoding components of the nutrient-responsive TOR and Sch9 pathways. Calorie restriction of tor1D or sch9D cells failed to further increase life span and, like calorie restriction, deletion of either SCH9 or TOR1 increased life span independent of the Sir2 histone deacetylase. We propose that the TOR and Sch9 kinases define a primary conduit through which excess nutrient intake limits longevity in yeast.
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              Functional Characterization of the S. cerevisiae Genome by Gene Deletion and Parallel Analysis

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                Author and article information

                Journal
                Genetics
                Genetics
                Genetics Society of America
                0016-6731
                1943-2631
                May 03 2012
                May 2012
                May 2012
                February 29 2012
                : 191
                : 1
                : 107-118
                Article
                10.1534/genetics.111.136549
                3338253
                22377630
                4d0b923a-9daf-4938-9631-16c8becd3f20
                © 2012
                History

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