Synthetic Genetic Array Analysis for Global Mapping of Genetic Networks in Yeast

Abstract

Genetic interactions occur when mutant alleles of two or more genes collaborate to generate an unusual composite phenotype, one that would not be predicted based on the expected combined effects of the individual mutant alleles. Synthetic Genetic Array (SGA) methodology was developed to automate yeast genetic analysis and enable systematic genetic interaction studies. In its simplest form, SGA consists of a series of replica pinning steps, which enable the construction of haploid double mutants through mating and meiotic recombination. For example, a strain carrying a query mutation, such as a deletion allele of a nonessential gene or a conditional temperature sensitive allele of an essential gene, could be crossed to an input array of yeast mutants, such as the complete set of ~5,000 viable deletion mutants, to generate an output array of double mutants, that can be scored for genetic interactions based on estimates of cellular fitness derived from colony-size measurements. A simple quantitative measure of genetic interactions can be derived from colony size, which serves as a proxy for fitness. Furthermore, SGA can be applied in a variety of other contexts, such as Synthetic Dosage Lethality (SDL), in which a query mutation is crossed into an array of yeast strains, each of which overexpresses a different gene, thus making use of SGA to probe for gain-of-function phenotypes in specific genetic backgrounds. High-Content Screening (HCS) also integrates SGA to perform genome-wide screens for quantitative analysis of morphological phenotypes or pathway activity based upon fluorescent markers, extending genetic interaction analysis beyond fitness-based measurements. Genetic interaction studies offer insight into gene function, pathway structure, and buffering, and thus a complete genetic interaction network of yeast will generate a global functional wiring diagram for a eukaryotic cell.

TheCellMap.org: A Web-Accessible Database for Visualizing and Mining the Global Yeast Genetic Interaction Network

“…In a typical SGA screen, a haploid MAT α query mutant strain is crossed to an input array of haploid MAT a yeast mutants to generate an array of heterozygous diploid double mutants. Ultimately, an output array of haploid double mutants is generated through mating, meiosis, and the subsequent selection of haploid double mutant MAT a meiotic progeny (Kuzmin et al 2014). Computational methods have been developed to correct sources of systematic variability associated with high-density yeast colony arrays, providing accurate haploid single and double mutant colony size measurements that serve as a proxy for cell fitness and the basis for quantitative genetic interaction analysis (Baryshnikova et al 2010).…”

“…SGA genetic interaction screens and analyses were conducted as described elsewhere (Baryshnikova et al 2010; Kuzmin et al 2014; Costanzo et al 2016). …”

Mutant power: using mutant allele collections for yeast functional genomics

“…Several gene collections utilizing conditional mutations have been created to facilitate analyses of essential genes ( Figure 3). These collections can be used on a small scale to study individual genes or on a large scale to explore genetic interactions utilizing techniques such as synthetic genetic array (SGA) analysis [25,26]. Morphological phenotypes resulting from research with these collections has been compiled and can be viewed using the database PhenoM [27].…”

“…The ts collection contains specific nucleotides that can be used as molecular barcodes for the identification and analysis of individual strains within a pool of mutants [25]. Since its completion in 2011 by the Boone laboratory, this collection has been utilized for high-throughput studies of chemical-genetic interactions [40], SGA analyses to identify gene networks [26], and projects to determine the role of Parkinson's related genes in cellular pathways [41]. The Stirling laboratory recently constructed an additional barcoded ts allele collection, generating a 'diploid-shuffle' allele set that spans 600 essential genes [42].…”

Identifying pathogenicity of human variants via paralog-based yeast complementation

“…Yeast remains an extremely useful model organism for studying gene functions [2, 3], genetic interactions [4], protein-protein interactions [5–7], and genotype-phenotype relationships [8, 9]. The scale of experiments in yeast ranges from individual assays to high-throughput genome-wide experiments [10–12].…”