Linking functionally related genes by sensitive and quantitative characterization of genetic interaction profiles

Abstract

Describing at a genomic scale how mutations in different genes influence one another is essential to the understanding of how genotype correlates with phenotype and remains a major challenge in biology. Previous studies pointed out the need for accurate measurements of not only synthetic but also buffering interactions in the characterization of genetic networks and functional modules. We developed a sensitive and efficient method that allows such measurements at a genomic scale in yeast. In a pilot experiment (41 genome-wide screens), we quantified the fitness of 140,000 double deletion strains relative to the corresponding single mutants and identified many genetic interactions. In addition to synthetic growth defects (validated experimentally with factors newly identified as genetically interfering with mRNA degradation), most of the identified genetic interactions measured weak epistatic effects. These weak effects, rarely meaningful when considered individually, were crucial to defining specific signatures for many gene deletions and had a major contribution in defining clusters of functionally related genes.epistasis ͉ functional genomics ͉ genetic screen ͉ mRNA decapping ͉ Saccharomyces cerevisiae F ollowing the completion of the genomic sequence for Saccharomyces cerevisiae, a systematic gene deletion library was built as a tool to link genes to functions and phenotypes. Yet, the phenotypic consequences of single deletions are rarely sufficient to define the function of genes. Moreover, very little is known of the phenotypic influences that different mutations have on each other. A large panel of responses can be observed when combining mutations, from aggravating to neutral, buffering, and even alleviating effects. Several high-throughput genetic screen methods, such as SGA (synthetic genetic array), dSLAM, and SLAM (synthetic lethality analyzed by microarray) (1-3), analyze the growth defect of combining a given query mutation with every gene deletion from the library of tagged nonessential yeast knockouts. These approaches are useful in identifying the strong synthetic defects that are seen for only a minor fraction of all of the possible gene deletion pairs (Ϸ0.5%) (4). However, they are not suited to evaluating more general buffering relationships between genes. Yet, recent studies have demonstrated the importance of accurate measurements of the complete spectrum of genetic interactions to define functional gene modules (5, 6). Broader quantitative measurements of genetic interactions are obtained in epistatic miniarrays (E-MAPs) (5, 7) but at the expense of coverage, because the E-MAP results depend on high-density genetic interaction matrixes made possible by focusing on logically connected gene subsets. Here, we present a method that we call GIM for ''genetic interaction mapping,'' which is not limited to a subset of genes, and allows sensitive and quantitative measurements of the complete spectrum of genetic interactions.Double mutant populations are efficiently obtained by mating and sporulatio...

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