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

PRE2

DOA3, PRG1, SRR2, proteasome core particle subunit beta 5, L000001484, YPR103W
Beta 5 subunit of the 20S proteasome; responsible for the chymotryptic activity of the proteasome
UPS Project
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 global genetic interaction network maps a wiring diagram of cellular function.

Costanzo M, VanderSluis B, Koch EN, Baryshnikova A, Pons C, Tan G, Wang W, Usaj M, Hanchard J, Lee SD, Pelechano V, Styles EB, Billmann M, van Leeuwen J, van Dyk N, Lin ZY, Kuzmin E, Nelson J, Piotrowski JS, Srikumar T, Bahr S, Chen Y, Deshpande R, Kurat CF, Li SC, Li Z, Usaj MM, Okada H, Pascoe N, San Luis BJ, Sharifpoor S, Shuteriqi E, Simpkins SW, Snider J, Suresh HG, Tan Y, Zhu H, Malod-Dognin N, Janjic V, Przulj N, Troyanskaya OG, Stagljar I, Xia T, Ohya Y, Gingras AC, Raught B, Boutros M, Steinmetz LM, Moore CL, Rosebrock AP, Caudy AA, Myers CL, Andrews B, Boone C

We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing more than 23 million double mutants, identifying about 550,000 negative and about 350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to ... [more]

Science Sep. 23, 2016; 353(6306); [Pubmed: 27708008]

Quantitative Score

  • -0.5219 [SGA Score]

Throughput

  • High Throughput

Ontology Terms

  • phenotype: colony size (APO:0000063)

Additional Notes

  • Genetic interactions were considered significant if they had a p-value < 0.05 and an SGA score > 0.16 for positive interactions and SGA score < -0.12 for negative interactions.
  • alleles: rpn4 - pre2-1-supp1 [SGA score = -0.5219, P-value = 2.223E-162]
  • alleles: rpn4 - pre2-127 [SGA score = -0.4710, P-value = 0]
  • alleles: rpn4 - pre2-2 [SGA score = -0.4206, P-value = 7.812E-53]
  • alleles: rpn4 - pre2-75 [SGA score = -0.4626, P-value = 2.764E-48]
  • alleles: rpn4 - pre2-v214a [SGA score = -0.3259, P-value = 1.22E-8]

Related interactions

InteractionExperimental Evidence CodeDatasetThroughputScoreCurated ByNotes
PRE2 RPN4
Co-purification
Co-purification

An interaction is inferred from the identification of two or more protein subunits in a purified protein complex, as obtained by classical biochemical fractionation or affinity purification and one or more additional fractionation steps.

Low-BioGRID
-
PRE2 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-0.3759BioGRID
2023622
RPN4 PRE2
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
163207

Curated By

  • BioGRID