CLA4
Gene Ontology Biological Process
Gene Ontology Molecular Function
Gene Ontology Cellular Component
SLT2
Gene Ontology Biological Process
- UFP-specific transcription factor mRNA processing involved in endoplasmic reticulum unfolded protein response [IMP]
- barrier septum assembly [IGI]
- endoplasmic reticulum unfolded protein response [IDA, IMP]
- fungal-type cell wall biogenesis [IGI]
- peroxisome degradation [IMP]
- protein phosphorylation [IDA, IMP]
- regulation of cell size [IMP]
- regulation of fungal-type cell wall organization [IGI, IMP]
- regulation of transcription factor import into nucleus [IMP]
- response to acidic pH [IMP]
- signal transduction [IMP]
Gene Ontology Molecular Function
Gene Ontology Cellular Component
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
Rewiring of genetic networks in response to DNA damage.
Although cellular behaviors are dynamic, the networks that govern these behaviors have been mapped primarily as static snapshots. Using an approach called differential epistasis mapping, we have discovered widespread changes in genetic interaction among yeast kinases, phosphatases, and transcription factors as the cell responds to DNA damage. Differential interactions uncover many gene functions that go undetected in static conditions. They ... [more]
Quantitative Score
- -9.050979 [SGA Score]
Throughput
- High Throughput
Ontology Terms
- phenotype: resistance to chemicals (APO:0000087)
- 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 in MMS-treated conditions. 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).
- 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 >= 2.0 for positive interactions (epistatic or suppressor interactions) and S score <= -2.5 for negative interactions (synthetic sick/lethal interactions).
Related interactions
| Interaction | Experimental Evidence Code | Dataset | Throughput | Score | Curated By | Notes |
|---|---|---|---|---|---|---|
| CLA4 SLT2 | 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 | -7.3818 | BioGRID | 514962 | |
| CLA4 SLT2 | 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 | -7.3818 | BioGRID | 321984 | |
| SLT2 CLA4 | 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 | -5.43 | BioGRID | 2355818 | |
| SLT2 CLA4 | 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 | 450474 | |
| CLA4 SLT2 | 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 | 80931 | |
| CLA4 SLT2 | 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 | 450161 |
Curated By
- BioGRID