CDC73
Gene Ontology Biological Process
- mRNA 3'-end processing [IMP]
- negative regulation of DNA recombination [IMP]
- positive regulation of histone H3-K36 trimethylation [IMP]
- positive regulation of phosphorylation of RNA polymerase II C-terminal domain serine 2 residues [IMP]
- positive regulation of transcription elongation from RNA polymerase I promoter [IDA]
- positive regulation of transcription elongation from RNA polymerase II promoter [IMP]
- recruitment of 3'-end processing factors to RNA polymerase II holoenzyme complex [IMP]
- regulation of histone H2B conserved C-terminal lysine ubiquitination [IDA]
- regulation of transcription-coupled nucleotide-excision repair [IGI]
- transcription elongation from RNA polymerase I promoter [IMP]
- transcription elongation from RNA polymerase II promoter [IGI]
Gene Ontology Molecular Function
Gene Ontology Cellular Component
PGD1
Gene Ontology Biological Process
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
Functional dissection of protein complexes involved in yeast chromosome biology using a genetic interaction map.
Defining the functional relationships between proteins is critical for understanding virtually all aspects of cell biology. Large-scale identification of protein complexes has provided one important step towards this goal; however, even knowledge of the stoichiometry, affinity and lifetime of every protein-protein interaction would not reveal the functional relationships between and within such complexes. Genetic interactions can provide functional information that ... [more]
Quantitative Score
- -4.817458 [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).
Curated By
- BioGRID