BAIT

BCK1

LAS3, SAP3, SLK1, SSP31, mitogen-activated protein kinase kinase kinase BCK1, L000000162, YJL095W
MAPKKK acting in the protein kinase C signaling pathway; the kinase C signaling pathway controls cell integrity; upon activation by Pkc1p phosphorylates downstream kinases Mkk1p and Mkk2p; MAPKKK is an acronym for mitogen-activated protein (MAP) kinase kinase kinase
Saccharomyces cerevisiae (S288c)
PREY

ALG8

YOR29-18, dolichyl-P-Glc:Glc1Man(9)GlcNAc(2)-PP-dolichol alpha-1,3-glucosyltransferase, L000000079, YOR067C
Glucosyl transferase; involved in N-linked glycosylation; adds glucose to the dolichol-linked oligosaccharide precursor prior to transfer to protein during lipid-linked oligosaccharide biosynthesis; similar to Alg6p
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

  • -5.892978 [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).

Related interactions

InteractionExperimental Evidence CodeDatasetThroughputScoreCurated ByNotes
ALG8 BCK1
Negative Genetic
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.

High-0.1492BioGRID
2183025
BCK1 ALG8
Negative Genetic
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.

High-0.2198BioGRID
2136003
ALG8 BCK1
Synthetic Growth Defect
Synthetic Growth Defect

A genetic interaction is inferred when mutations in separate genes, each of which alone causes a minimal phenotype, result in a significant growth defect under a given condition when combined in the same cell.

High-BioGRID
452319

Curated By

  • BioGRID