BAIT

CLA4

ERC10, serine/threonine protein kinase CLA4, L000000564, L000002643, YNL298W
Cdc42p-activated signal transducing kinase; member of the PAK (p21-activated kinase) family, along with Ste20p and Skm1p; involved in septin ring assembly, vacuole inheritance, cytokinesis, sterol uptake regulation; phosphorylates Cdc3p and Cdc10p; CLA4 has a paralog, SKM1, that arose from the whole genome duplication
Saccharomyces cerevisiae (S288c)
PREY

SWI6

PSL8, SDS11, transcriptional regulator SWI6, L000002254, YLR182W
Transcription cofactor; forms complexes with Swi4p and Mbp1p to regulate transcription at the G1/S transition; involved in meiotic gene expression; also binds Stb1p to regulate transcription at START; cell wall stress induces phosphorylation by Mpk1p, which regulates Swi6p localization; required for the unfolded protein response, independently of its known transcriptional coactivators
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

  • -5.341573 [SGA Score]

Throughput

  • High Throughput

Ontology Terms

  • phenotype: resistance to chemicals (APO:0000087)
  • 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 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).
  • 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 >= 2.0 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
CLA4 SWI6
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-0.39BioGRID
909623
CLA4 SWI6
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-0.1266BioGRID
407870
CLA4 SWI6
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-0.2092BioGRID
2175180
CLA4 SWI6
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-7.0454BioGRID
324667
CLA4 SWI6
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-0.127BioGRID
912100

Curated By

  • BioGRID