The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Defining genetic interaction
Open accessAbstract
Sometimes mutations in two genes produce a phenotype that is surprising in light of each mutation's individual effects. This phenomenon, which defines genetic interaction, can reveal functional relationships between genes and pathways. For example, double mutants with surprisingly slow growth define synergistic interactions that can identify compensatory pathways or protein complexes. Recent studies have used four mathematically distinct definitions of genetic interaction (here termed Product, Additive, Log, and Min). Whether this choice holds practical consequences has not been clear, because the definitions yield identical results under some conditions. Here, we show that the choice among alternative definitions can have profound consequences. Although 52% of known synergistic genetic interactions in Saccharomyces cerevisiae were inferred according to the Min definition, we find that both Product and Log definitions (shown here to be practically equivalent) are better than Min for identifying functional relationships. Additionally, we show that the Additive and Log definitions, each commonly used in population genetics, lead to differing conclusions related to the selective advantages of sexual reproduction.
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Cites
Gene Ontology: tool for the unification of biology
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BioGRID: a general repository for interaction datasets
Stark, C. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkj109 · Cited by 3,960
Systematic Genetic Analysis with Ordered Arrays of Yeast Deletion Mutants
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Exploring genetic interactions and networks with yeast
Boone, C., Bussey, H., & Andrews, B. J. (2007) · Nature Reviews Genetics · doi:10.1038/nrg2085 · Cited by 661
Modular epistasis in yeast metabolism
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Cited by
The Genetic Landscape of a Cell
Costanzo, M., Baryshnikova, A., Bellay, J., Kim, Y., Spear, E. D., Sevier, C. S., Ding, H., Koh, J. L. Y., Toufighi, K., Mostafavi, S., et al. (2010) · Science · doi:10.1126/science.1180823 · Cited by 2,162
Self-citationInteractome Networks and Human Disease
Vidal, M., Cusick, M. E., & Barabási, A.-L. (2011) · Cell · doi:10.1016/j.cell.2011.02.016 · Cited by 1,771
A Comprehensive Biophysical Description of Pairwise Epistasis throughout an Entire Protein Domain
Olson, C. A., Wu, N. C., & Sun, R. (2014) · Current Biology · doi:10.1016/j.cub.2014.09.072 · Cited by 408
Combinatorial CRISPR–Cas9 screens for de novo mapping of genetic interactions
Shen, J. P., Zhao, D., Sasik, R., Luebeck, J., Birmingham, A., Bojorquez-Gomez, A., Licon, K., Klepper, K., Pekin, D., Beckett, A. N., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4225 · Cited by 359
“This method [1] detects and removes gRNA constructs with insufficient read coverage; [2] fits growth curves to the measured log2 abundances of each construct over time, the slopes of which reflect fitness; and [3] integrates data from the multiple gRNA constructs to derive a robust fitness value for disruption of each…”
MethodDrug interactions and the evolution of antibiotic resistance
Yeh, P. J., Hegreness, M. J., Aiden, A. P., & Kishony, R. (2009) · Nature Reviews Microbiology · doi:10.1038/nrmicro2133 · Cited by 350
Metadata
- Authors
- Mani, R., St.Onge, R. P., Hartman, J. L., Giaever, G., & Roth, F. P.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2008-03-04
- Volume
- 105
- Issue
- 9
- Pages
- 3461-3466
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2130139983
- Cited by
- 473
- References
- 7
- FWCI
- 10.55
- Type
- journal article
- Language
- en
- Open access
- green
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