BAIT

RPN4

SON1, UFD5, stress-regulated transcription factor RPN4, L000001984, YDL020C
Transcription factor that stimulates expression of proteasome genes; Rpn4p levels are in turn regulated by the 26S proteasome in a negative feedback control mechanism; RPN4 is transcriptionally regulated by various stress responses; relative distribution to the nucleus increases upon DNA replication stress
Saccharomyces cerevisiae (S288c)
PREY

RPN10

MCB1, SUN1, proteasome regulatory particle base subunit RPN10, L000003108, YHR200W
Non-ATPase base subunit of the 19S RP of the 26S proteasome; N-terminus plays a role in maintaining the structural integrity of the regulatory particle (RP); binds selectively to polyubiquitin chains; homolog of the mammalian S5a protein
GO Process (1)
GO Function (2)
GO Component (2)
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 genetic interaction map of RNA-processing factors reveals links between Sem1/Dss1-containing complexes and mRNA export and splicing.

Wilmes GM, Bergkessel M, Bandyopadhyay S, Shales M, Braberg H, Cagney G, Collins SR, Whitworth GB, Kress TL, Weissman JS, Ideker T, Guthrie C, Krogan NJ

We used a quantitative, high-density genetic interaction map, or E-MAP (Epistatic MiniArray Profile), to interrogate the relationships within and between RNA-processing pathways. Due to their complexity and the essential roles of many of the components, these pathways have been difficult to functionally dissect. Here, we report the results for 107,155 individual interactions involving 552 mutations, 166 of which are hypomorphic ... [more]

Mol. Cell Dec. 05, 2008; 32(5);735-46 [Pubmed: 19061648]

Quantitative Score

  • -8.148395 [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 > 2.5 for positive interactions (suppression) and S score < -2.5 for negative interactions (synthetic sick/lethality).

Related interactions

InteractionExperimental Evidence CodeDatasetThroughputScoreCurated ByNotes
RPN4 RPN10
Affinity Capture-Western
Affinity Capture-Western

An interaction is inferred when a bait protein is affinity captured from cell extracts by either polyclonal antibody or epitope tag and the associated interaction partner identified by Western blot with a specific polyclonal antibody or second epitope tag. This category is also used if an interacting protein is visualized directly by dye stain or radioactivity. Note that this differs from any co-purification experiment involving affinity capture in that the co-purification experiment involves at least one extra purification step to get rid of potential contaminating proteins.

Low-BioGRID
-
RPN4 RPN10
Affinity Capture-Western
Affinity Capture-Western

An interaction is inferred when a bait protein is affinity captured from cell extracts by either polyclonal antibody or epitope tag and the associated interaction partner identified by Western blot with a specific polyclonal antibody or second epitope tag. This category is also used if an interacting protein is visualized directly by dye stain or radioactivity. Note that this differs from any co-purification experiment involving affinity capture in that the co-purification experiment involves at least one extra purification step to get rid of potential contaminating proteins.

Low-BioGRID
-
RPN10 RPN4
Co-fractionation
Co-fractionation

Interaction inferred from the presence of two or more protein subunits in a partially purified protein preparation. If co-fractionation is demonstrated between 3 or more proteins, then add them as a complex.

Low-BioGRID
-
RPN10 RPN4
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-8.1848BioGRID
214988
RPN10 RPN4
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-0.472BioGRID
386973
RPN4 RPN10
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-0.472BioGRID
364753
RPN10 RPN4
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-0.3944BioGRID
2129995
RPN4 RPN10
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-0.4928BioGRID
2088824
RPN4 RPN10
Synthetic Lethality
Synthetic Lethality

A genetic interaction is inferred when mutations or deletions in separate genes, each of which alone causes a minimal phenotype, result in lethality when combined in the same cell under a given condition.

Low-BioGRID
160926
RPN10 RPN4
Synthetic Lethality
Synthetic Lethality

A genetic interaction is inferred when mutations or deletions in separate genes, each of which alone causes a minimal phenotype, result in lethality when combined in the same cell under a given condition.

High-BioGRID
456705
RPN4 RPN10
Synthetic Lethality
Synthetic Lethality

A genetic interaction is inferred when mutations or deletions in separate genes, each of which alone causes a minimal phenotype, result in lethality when combined in the same cell under a given condition.

High-BioGRID
456276

Curated By

  • BioGRID