BAIT

GET3

ARR4, guanine nucleotide exchange factor GET3, YDL100C
Guanine nucleotide exchange factor for Gpa1p; amplifies G protein signaling; functions as a chaperone under ATP-depleted oxidative stress conditions; subunit of the GET complex, which is involved in ATP dependent Golgi to ER trafficking and insertion of tail-anchored (TA) proteins into the ER membrane under non-stress conditions; has low-level ATPase activity; protein abundance increases in response to DNA replication stress
Saccharomyces cerevisiae (S288c)
PREY

RIC1

L000001638, YLR039C
Protein involved in retrograde transport to the cis-Golgi network; forms heterodimer with Rgp1p that acts as a GTP exchange factor for Ypt6p; involved in transcription of rRNA and ribosomal protein genes
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 plasma-membrane E-MAP reveals links of the eisosome with sphingolipid metabolism and endosomal trafficking.

Aguilar PS, Froehlich F, Rehman M, Shales M, Ulitsky I, Olivera-Couto A, Braberg H, Shamir R, Walter P, Mann M, Ejsing CS, Krogan NJ, Walther TC

The plasma membrane delimits the cell and controls material and information exchange between itself and the environment. How different plasma-membrane processes are coordinated and how the relative abundance of plasma-membrane lipids and proteins is homeostatically maintained are not yet understood. Here, we used a quantitative genetic interaction map, or E-MAP, to functionally interrogate a set of approximately 400 genes involved ... [more]

Nat. Struct. Mol. Biol. Jul. 01, 2010; 17(7);901-8 [Pubmed: 20526336]

Quantitative Score

  • -8.315371 [SGA Score]

Throughput

  • High Throughput

Ontology Terms

  • phenotype: colony size (APO:0000063)

Additional Notes

  • An Epistatic MiniArray Profile (E-MAP) approach 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 (epistatic or suppressor interactions) and S score < -2.5 for negative interactions (synthetic sick/lethal interactions).

Related interactions

InteractionExperimental Evidence CodeDatasetThroughputScoreCurated ByNotes
RIC1 GET3
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-0.3724BioGRID
2149419
GET3 RIC1
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-0.184BioGRID
2089950
RIC1 GET3
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-9.1213BioGRID
579501
RIC1 GET3
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-BioGRID
210598
GET3 RIC1
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-10.836BioGRID
206809
RIC1 GET3
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-19.8717BioGRID
900614
RIC1 GET3
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
450516

Curated By

  • BioGRID