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
GO Process (3)
GO Function (1)
GO Component (1)

Gene Ontology Molecular Function

Gene Ontology Cellular Component

Saccharomyces cerevisiae (S288c)
PREY

VAC14

YLR386W
Enzyme regulator; involved in synthesis of phosphatidylinositol 3,5-bisphosphate, in control of trafficking of some proteins to the vacuole lumen via the MVB, and in maintenance of vacuole size and acidity; binds negative (Fig4p) and positive (Fab1p) regulators of PtdIns(3,5)P(2) to control endolysosome function; similar to mammalian Vac14p
GO Process (2)
GO Function (1)
GO Component (3)
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 Network of Conserved Synthetic Lethal Interactions for Exploration of Precision Cancer Therapy.

Srivas R, Shen JP, Yang CC, Sun SM, Li J, Gross AM, Jensen J, Licon K, Bojorquez-Gomez A, Klepper K, Huang J, Pekin D, Xu JL, Yeerna H, Sivaganesh V, Kollenstart L, van Attikum H, Aza-Blanc P, Sobol RW, Ideker T

An emerging therapeutic strategy for cancer is to induce selective lethality in a tumor by exploiting interactions between its driving mutations and specific drug targets. Here we use a multi-species approach to develop a resource of synthetic lethal interactions relevant to cancer therapy. First, we screen in yeast ∼169,000 potential interactions among orthologs of human tumor suppressor genes (TSG) and ... [more]

Mol. Cell Aug. 04, 2016; 63(3);514-25 [Pubmed: 27453043]

Quantitative Score

  • -3.1 [Confidence Score]

Throughput

  • High Throughput

Ontology Terms

  • phenotype: colony size (APO:0000063)

Additional Notes

  • Untreated conditions. SGA was used to score genetic interactions based on 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).

Curated By

  • BioGRID