BAIT

DUN1

serine/threonine protein kinase DUN1, L000000531, YDL101C
Cell-cycle checkpoint serine-threonine kinase; required for DNA damage-induced transcription of certain target genes, phosphorylation of Rad55p and Sml1p, and transient G2/M arrest after DNA damage; Mec1p and Dun1p function in same pathway to regulate both dNTP pools and telomere length; also regulates postreplicative DNA repair
Kinome Project (Sc)
GO Process (3)
GO Function (1)
GO Component (1)

Gene Ontology Biological Process

Gene Ontology Molecular Function

Gene Ontology Cellular Component

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

Functional organization of the S. cerevisiae phosphorylation network.

Fiedler D, Braberg H, Mehta M, Chechik G, Cagney G, Mukherjee P, Silva AC, Shales M, Collins SR, van Wageningen S, Kemmeren P, Holstege FC, Weissman JS, Keogh MC, Koller D, Shokat KM, Krogan NJ

Reversible protein phosphorylation is a signaling mechanism involved in all cellular processes. To create a systems view of the signaling apparatus in budding yeast, we generated an epistatic miniarray profile (E-MAP) comprised of 100,000 pairwise, quantitative genetic interactions, including virtually all protein and small-molecule kinases and phosphatases as well as key cellular regulators. Quantitative genetic interaction mapping reveals factors working ... [more]

Cell Mar. 06, 2009; 136(5);952-63 [Pubmed: 19269370]

Quantitative Score

  • -2.7552 [SGA 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 > 2.0 for positive interactions (suppression) and S score < -2.5 for negative interactions (synthetic sick/lethality).

Related interactions

InteractionExperimental Evidence CodeDatasetThroughputScoreCurated ByNotes
SWI6 DUN1
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-5.1625BioGRID
541265
DUN1 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-0.1751BioGRID
2090007
DUN1 SWI6
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
455446

Curated By

  • BioGRID