BAIT

PHO88

L000003995, YBR106W
Probable membrane protein; involved in phosphate transport; role in the maturation of secretory proteins; pho88 pho86 double null mutant exhibits enhanced synthesis of repressible acid phosphatase at high inorganic phosphate concentrations
GO Process (2)
GO Function (0)
GO Component (2)

Gene Ontology Biological Process

Gene Ontology Cellular Component

Saccharomyces cerevisiae (S288c)
PREY

VPS64

FAR9, YDR200C
Protein required for cytoplasm to vacuole targeting of proteins; forms a complex with Far3p and Far7p to Far11p involved in recovery from pheromone-induced cell cycle arrest; mutant has increased aneuploidy tolerance; VPS64 has a paralog, FAR10, that arose from the whole genome duplication
Saccharomyces cerevisiae (S288c)

Negative Genetic

Mutations/deletions in separate genes, each of which alone causes a minimal phenotype, but when combined in the same cell results in a more severe fitness defect or lethality under a given condition. This term is reserved for high or low throughput studies with scores.

Publication

A Lipid E-MAP Identifies Ubx2 as a Critical Regulator of Lipid Saturation and Lipid Bilayer Stress.

Surma MA, Klose C, Peng D, Shales M, Mrejen C, Stefanko A, Braberg H, Gordon DE, Vorkel D, Ejsing CS, Farese R, Simons K, Krogan NJ, Ernst R

Biological membranes are complex, and the mechanisms underlying their homeostasis are incompletely understood. Here, we present a quantitative genetic interaction map (E-MAP) focused on various aspects of lipid biology, including lipid metabolism, sorting, and trafficking. This E-MAP contains ∼250,000 negative and positive genetic interaction scores and identifies a molecular crosstalk of protein quality control pathways with lipid bilayer homeostasis. Ubx2p, ... [more]

Mol. Cell Aug. 22, 2013; 51(4);519-30 [Pubmed: 23891562]

Quantitative Score

  • -3.00275 [S score]

Throughput

  • High Throughput

Ontology Terms

  • phenotype: colony size (APO:0000063)

Additional Notes

  • An Epistatic MiniArray Profile (E-MAP) analysis was used to quantitatively score genetic interactions based on fitness defects estimated from the colony size of double versus single mutants. Genetic interactions were considered significant if they had an S score > 2.5 for positive interactions (suppression) and S score < -2.5 for negative interactions (synthetic sick/lethality).

Curated By

  • BioGRID