Stringent Mating-Type-Regulated Auxotrophy Increases the Accuracy of Systematic Genetic Interaction Screens with Saccharomyces cerevisiae Mutant Arrays

Abstract

A genomic collection of haploid Saccharomyces cerevisiae deletion strains provides a unique resource for systematic analysis of gene interactions. Double-mutant haploid strains can be constructed by the synthetic genetic array (SGA) method, wherein a query mutation is introduced by mating to mutant arrays, selection of diploid double mutants, induction of meiosis, and selection of recombinant haploid doublemutant progeny. The mechanism of haploid selection is mating-type-regulated auxotrophy (MRA), by which prototrophy is restricted to a particular haploid genotype generated only as a result of meiosis. MRA escape leads to false-negative genetic interaction results because postmeiotic haploids that are supposed to be under negative selection instead proliferate and mate, forming diploids that are heterozygous at interacting loci, masking phenotypes that would be observed in a pure haploid double-mutant culture. This work identified factors that reduce MRA escape, including insertion of terminator and repressor sequences upstream of the MRA cassette, deletion of silent mating-type loci, and utilization of a-type instead of a-type MRA. Modifications engineered to reduce haploid MRA escape reduced false negative results in SGA-type analysis, resulting in .95% sensitivity for detecting gene-gene interactions.

Genomewide Analysis Reveals Novel Pathways Affecting Endoplasmic Reticulum Homeostasis, Protein Modification and Quality Control

“…We employed a synthetic genetic array approach to systematically introduce Erd2-GFP and the hac1D allele into the MATa collection of Kar2p secretors. The parental query strain [MATa, hmrD0TURA3 (C. albicans), leu2D0, his3D1, can1D0TPGAL1-TDH1-MFA1pr-his5 1 (S. pombe), lyp1D0] was constructed by transforming Y15578-1.2b (Singh et al 2009) with PCR products to integrate GFPTLEU2 at the ERD2 locus or replace the HAC1 locus with the NATMX selection cassette to generate LMY446 and LMY445, respectively. These query strains were then mated to the haploid MATa strains that showed significant Kar2p secretion.…”

Bioinformatic identification of genes suppressing genome instability

“…To find genes that had been missed but with related functions, we scored all the genes in the genome on the basis of their genetic similarity or "congruence" (25) with previously identified genes using reported growth-based genetic interactions. The growth-based genetic data also have imperfect concordance; the mean overlap for a reported subset of genetic interactions in S. cerevisiae by different groups has been estimated at less than 50% (26), potentially due to errors in scoring growth phenotypes, escape of diploids during haploid selection (27,28), additional mutations present in strains in the deletion collection (29,30), and/or the presence of an incorrect mutation due to cross-contamination, which we have tested for and corrected in our copy of the genome deletion collection. Therefore, our strategy to improve the robustness of this step was to score the genetic congruence of each candidate mutation using the combined genetic signature of the interactions of the 75 mutations causing increased GCR rates and the 928 mutations causing DNA damaging agent sensitivity with each gene in the rest of the genome (∼6,000 genes; SI Appendix, SI Materials and Methods).…”

Phenomic Assessment of Genetic Buffering by Kinetic Analysis of Cell Arrays

“…SGA can be done quantitatively, where phenotypes are measured as colony outgrowth area at a selected time point, and a multiplicative neutrality function is used (6, 14, 18–20). However, if using Q-HTCP to quantify gene-gene interaction, a variation of the SGA procedure works better, where the mutation of interest is conditionally expressed, frozen stocks are made at the final step of SGA, and quantitative growth curve analysis is carried out as a subsequent step (16, 21). By utilizing conditional (e.g., tetracycline-regulated) expression of the query gene, interactions can be assessed at multiple levels of query gene expression by shifting cells to media containing different concentrations of tetracycline (22).…”

“…Kinetic phenotyping and gradations of perturbation rigorously assess gene interaction, but in doing so, reduce the overall throughput in exchange for increased quantitative precision. Nevertheless, robust measurement of gene interaction can be performed on a phenomic scale (3, 15, 16, 21–23). …”