BAIT

SEC63

PTL1, protein-transporting protein SEC63, L000001854, L000001269, YOR254C
Essential subunit of Sec63 complex; with Sec61 complex, Kar2p/BiP and Lhs1p forms a channel competent for SRP-dependent and post-translational SRP-independent protein targeting and import into the ER; other members are Sec62p, Sec66p, and Sec72p
Saccharomyces cerevisiae (S288c)
PREY

VPS4

CSC1, DID6, END13, GRD13, VPL4, VPT10, AAA family ATPase VPS4, L000002956, YPR173C
AAA-ATPase involved in multivesicular body (MVB) protein sorting; ATP-bound Vps4p localizes to endosomes and catalyzes ESCRT-III disassembly and membrane release; ATPase activity is activated by Vta1p; regulates cellular sterol metabolism
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

Exploration of the function and organization of the yeast early secretory pathway through an epistatic miniarray profile.

Schuldiner M, Collins SR, Thompson NJ, Denic V, Bhamidipati A, Punna T, Ihmels J, Andrews B, Boone C, Greenblatt JF, Weissman JS, Krogan NJ

We present a strategy for generating and analyzing comprehensive genetic-interaction maps, termed E-MAPs (epistatic miniarray profiles), comprising quantitative measures of aggravating or alleviating interactions between gene pairs. Crucial to the interpretation of E-MAPs is their high-density nature made possible by focusing on logically connected gene subsets and including essential genes. Described here is the analysis of an E-MAP of genes ... [more]

Cell Nov. 04, 2005; 123(3);507-19 [Pubmed: 16269340]

Quantitative Score

  • -4.5865 [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
SEC63 VPS4
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-0.2794BioGRID
2018328
VPS4 SEC63
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-0.134BioGRID
2075019
SEC63 VPS4
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-4.8913BioGRID
589206
VPS4 SEC63
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
212363

Curated By

  • BioGRID