BAIT

DBF2

serine/threonine-protein kinase DBF2, L000000487, YGR092W
Ser/Thr kinase involved in transcription and stress response; functions as part of a network of genes in exit from mitosis; localization is cell cycle regulated; activated by Cdc15p during the exit from mitosis; also plays a role in regulating the stability of SWI5 and CLB2 mRNAs; phosphorylates Chs2p to regulate primary septum formation and Hof1p to regulate cytokinesis; DBF2 has a paralog, DBF20, that arose from the whole genome duplication
Kinome Project (Sc)
Saccharomyces cerevisiae (S288c)
PREY

YND1

APY1, YEJ5, S000007428, YER005W
Apyrase with wide substrate specificity; helps prevent inhibition of glycosylation by hydrolyzing nucleoside tri- and diphosphates that inhibit glycotransferases; partially redundant with Gda1p; mediates adenovirus E4orf4-induced toxicity
GO Process (1)
GO Function (2)
GO Component (4)

Gene Ontology Biological Process

Gene Ontology Molecular Function

Gene Ontology Cellular Component

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

  • -7.6 [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