BAIT

RPS10A

ribosomal 40S subunit protein S10A, S10e, S10A, L000004475, YOR293W
Protein component of the small (40S) ribosomal subunit; homologous to mammalian ribosomal protein S10, no bacterial homolog; RPS10A has a paralog, RPS10B, that arose from the whole genome duplication
GO Process (2)
GO Function (1)
GO Component (1)

Gene Ontology Biological Process

Gene Ontology Molecular Function

Gene Ontology Cellular Component

Saccharomyces cerevisiae (S288c)
PREY

FBP1

ACN8, fructose 1,6-bisphosphate 1-phosphatase, L000000605, YLR377C
Fructose-1,6-bisphosphatase; key regulatory enzyme in the gluconeogenesis pathway, required for glucose metabolism; undergoes either proteasome-mediated or autophagy-mediated degradation depending on growth conditions; glucose starvation results in redistribution to the periplasm; interacts with Vid30p
GO Process (2)
GO Function (1)
GO Component (2)

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

  • -2.54 [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