BAIT

RPS11B

ribosomal 40S subunit protein S11B, S17, rp41B, YS12, S18B, S11B, L000001758, YBR048W
Protein component of the small (40S) ribosomal subunit; homologous to mammalian ribosomal protein S11 and bacterial S17; RPS11B has a paralog, RPS11A, that arose from the whole genome duplication
Saccharomyces cerevisiae (S288c)
PREY

DOM34

ribosome dissociation factor DOM34, L000000517, YNL001W
Protein that facilitates ribosomal subunit dissociation; Dom34-Hbs1 complex and Rli1p have roles in dissociating inactive ribosomes to facilitate translation restart, particularly ribosomes stalled in 3' UTRs; required for RNA cleavage in no-go decay, but reports conflict on endonuclease activity; Pelota ortholog; protein abundance increases in response to DNA replication stress; DOM34 has a paralog, YCL001W-B, that arose from the whole genome duplication
Kinome Project (Sc)
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

  • -22.31 [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).

Related interactions

InteractionExperimental Evidence CodeDatasetThroughputScoreCurated ByNotes
RPS11B DOM34
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-0.4341BioGRID
357142
RPS11B DOM34
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-0.4594BioGRID
2080149
DOM34 RPS11B
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-0.3455BioGRID
2166728
DOM34 RPS11B
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
483823

Curated By

  • BioGRID