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

SEM1

DSS1, HOD1, proteasome regulatory particle lid subunit SEM1, L000003539, L000004647, YDR363W-A
Component of lid subcomplex of 26S proteasome regulatory subunit; involved in mRNA export mediated by TREX-2 complex (Sac3p-Thp1p); assumes different conformations in different contexts, functions as molecular glue stabilizing the Rpn3p/Rpn7p regulatory heterodimer, and tethers it to lid helical bundle; ortholog of human DSS1; protein abundance increases in response to DNA replication stress
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

Epistatic relationships reveal the functional organization of yeast transcription factors.

Zheng J, Benschop JJ, Shales M, Kemmeren P, Greenblatt J, Cagney G, Holstege F, Li H, Krogan NJ

The regulation of gene expression is, in large part, mediated by interplay between the general transcription factors (GTFs) that function to bring about the expression of many genes and site-specific DNA-binding transcription factors (STFs). Here, quantitative genetic profiling using the epistatic miniarray profile (E-MAP) approach allowed us to measure 48 391 pairwise genetic interactions, both negative (aggravating) and positive (alleviating), ... [more]

Mol. Syst. Biol. Oct. 05, 2010; 6(0);420 [Pubmed: 20959818]

Quantitative Score

  • -13.02669055 [SGA Score]

Throughput

  • High Throughput

Ontology Terms

  • phenotype: colony size (APO:0000063)

Additional Notes

  • An Epistatic MiniArray Profile (E-MAP) approach 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 (epistatic or suppressor interactions) and S score < -2.5 for negative interactions (synthetic sick/lethal interactions).

Related interactions

InteractionExperimental Evidence CodeDatasetThroughputScoreCurated ByNotes
RPN4 SEM1
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
-
SEM1 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-10.3736BioGRID
214156
SEM1 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-0.6169BioGRID
369996
RPN4 SEM1
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-0.6401BioGRID
364732
RPN4 SEM1
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-0.5737BioGRID
2088810
SEM1 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-0.7264BioGRID
2100376
RPN4 SEM1
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-BioGRID
3395413
RPN4 SEM1
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-11.3861BioGRID
308701
SEM1 RPN4
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.

Low-BioGRID
667198

Curated By

  • BioGRID