Reconstructing the Global Epistasis Network for Aging

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Project Summary Research in the biology of aging has seen rapid advance since the introduction of molecular genetics to the field. In the past few decades, genetic analyses of model organisms have led to the discovery of a number of genes/pathways that regulate lifespan, leading to important insight into the mechanisms of aging. However a global picture of the gene network that regulates lifespan is still elusive. To classify longevity mutants based on their mechanisms of action, to place genes influencing lifespan into pathways, and to delineate the downstream effectors of the lifespan extension for the longevity mutants, it is necessary to systematically analyze the epistatic relations between genes for the lifespan phenotype. So far this has not been possible in any model organism due to the sheer number of double mutants that need to be analyzed and the low throughput nature of the traditional lifespan assays. Here we propose to systematically reconstruct the global epistasis network for aging using budding yeast as the model organism and replicative lifespan as the phenotype. We will develop a high throughput approach to generate all possible single and double mutants and measure their lifespan simultaneously (Aim 1). Our approach will be based on a number of new technologies: 1) a novel genetically engineered strain that makes it possible to measure lifespan based on cell counting in liquid culture; 2) CRISPR/dCas9 based technology to generate a pooled library of single and double mutants, each carrying a unique DNA sequence identifier; 3) high throughput sequencing to count the number of cells of the pooled mutants simultaneously. We will use the comprehensive lifespan data to reconstruct the global epistasis map through computational analysis. We will also test some of the discovered epistatic relations both in yeast and in worms (Aim 2). We expect that this project will produce unprecedented and comprehensive data on the epistasis network that controls lifespan in a canonical model organism. The analysis of this data will lead to important insights into the functional organization of genes in the context of aging and mechanisms for the lifespan extension in long-lived mutants. Such insights might be transferrable to higher eukaryotes, in which a systematic reconstruction of the epistasis network for aging is not feasible.