Identifying_bypass_suppressors_of_yeast_essential_genes

Recent genome sequencing efforts have identified healthy people that carry severe disease-causal mutations, which may indicate the existence of other genomic mutations that compensate for the deleterious effects of the disease-associated variant, a phenomenon referred to as genetic suppression. Identification of the protective mutations could highlight strategies for therapeutic intervention, but we currently lack the expertise to identify the suppressor mutations among the millions of variants scattered across the genomes of these resilient individuals. Mapping genetic suppression interactions in model organisms is an incredibly powerful approach for dissecting gene function and pathway connectivity, and for defining conserved properties of suppression. It has been under-utilised because of the difficulty associated with identifying suppressor variants. Two factors enabled the generation of global maps of suppression: the ability to create genome-wide mutant collections, and high-throughput genome sequencing. We aim to survey suppression interactions on a large scale, through genome-wide suppression analysis of temperature sensitive (TS) alleles of essential genes. We isolated thousands of mutations that suppress TS alleles of essential yeast genes, and are looking to identify the causal suppressor variants by whole-genome sequencing. This global analysis will accomplish three main goals: (i) map a comprehensive functional wiring diagram for essential genes, (ii) uncover suppression mechanisms that are specific to hypomorphic alleles, an allele-type that is especially relevant in the context of human genetic variation, and (iii) elucidate the rules underlying TS phenotypes, by identifying the mutations that cause temperature sensitivity. This work will generate the most extensive global suppression network for a eukaryotic cell and identify novel functional connections between genes, thereby improving our understanding of how mutations can interact to produce unexpected phenotypes, including those associated with human disease.