BAIT

PHO80

AGS3, TUP7, VAC5, phoR, L000001426, YOL001W
Cyclin; interacts with cyclin-dependent kinase Pho85p; regulates the response to nutrient levels and environmental conditions, including the response to phosphate limitation and stress-dependent calcium signaling
Saccharomyces cerevisiae (S288c)
PREY

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)

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

Rewiring of genetic networks in response to DNA damage.

Bandyopadhyay S, Mehta M, Kuo D, Sung MK, Chuang R, Jaehnig EJ, Bodenmiller B, Licon K, Copeland W, Shales M, Fiedler D, Dutkowski J, Guenole A, van Attikum H, Shokat KM, Kolodner RD, Huh WK, Aebersold R, Keogh MC, Krogan NJ, Ideker T

Although cellular behaviors are dynamic, the networks that govern these behaviors have been mapped primarily as static snapshots. Using an approach called differential epistasis mapping, we have discovered widespread changes in genetic interaction among yeast kinases, phosphatases, and transcription factors as the cell responds to DNA damage. Differential interactions uncover many gene functions that go undetected in static conditions. They ... [more]

Science Dec. 03, 2010; 330(6009);1385-9 [Pubmed: 21127252]

Quantitative Score

  • -4.117273 [SGA Score]

Throughput

  • High Throughput

Ontology Terms

  • colony size (APO:0000063)
  • resistance to chemicals (APO:0000087)

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 in MMS-treated conditions. Genetic interactions were considered significant if they had an S score >=2.0 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
BCK1 PHO80
Dosage Growth Defect
Dosage Growth Defect

A genetic interaction is inferred when over expression or increased dosage of one gene causes a growth defect in a strain that is mutated or deleted for another gene.

High-0.235BioGRID
908637
BCK1 PHO80
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-0.1415BioGRID
2135998

Curated By

  • BioGRID