Quantitative analysis of fitness and genetic interactions in yeast on a genome scale
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Global quantitative analysis of genetic interactions is a powerful approach for deciphering the roles of genes and mapping functional relationships among pathways. Using colony size as a proxy for fitness, we developed a method for measuring fitness-based genetic interactions from high-density arrays of yeast double mutants generated by synthetic genetic array (SGA) analysis. We identified several experimental sources of systematic variation and developed normalization strategies to obtain accurate single- and double-mutant fitness measurements, which rival the accuracy of other high-resolution studies. We applied the SGA score to examine the relationship between physical and genetic interaction networks, and we found that positive genetic interactions connect across functionally distinct protein complexes revealing a network of genetic suppression among loss-of-function alleles.
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Protein complexes exhibited highly organized patterns of genetic interactions.
“Consistent with previous findings (1, 5, 28, 29), we found that protein complexes exhibited highly organized patterns of genetic interactions.”
From A global genetic interaction network maps a wiring diagram of cellular function (2016) · cites this paper as [5]
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- Authors
- Baryshnikova, A., Costanzo, M., Kim, Y., Ding, H., Koh, J., Toufighi, K., Youn, J.-Y., Ou, J., San Luis, B.-J., Bandyopadhyay, S., Hibbs, M., Hess, D., Gingras, A.-C., Bader, G. D., Troyanskaya, O. G., Brown, G. W., Andrews, B., Boone, C., & Myers, C. L.
- Affiliations
- University of Toronto (CA)
- University of Minnesota (US)
- Jackson Laboratory (US)
- Santa Clara University (US)
- Mount Sinai Hospital (CA)
- Princeton University (US)
- Corresponding author
- Andrews, Brenda
- Boone, Charles
- Myers, Chad L
- ORCID
- Venue
- Nature Methods
- Published
- 2010-11-14
- Volume
- 7
- Issue
- 12
- Pages
- 1017-1024
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- PMC
- PMC3117325
- OpenAlex
- W1967220526
- Cited by
- 364
- References
- 41
- Citations by year
- 2026: 10 · 2025: 16 · 2024: 19 · 2023: 15 · 2022: 20 · 2021: 23 · 2020: 26 · 2019: 18 · 2018: 26 · 2017: 38 · 2016: 29 · 2015: 15 · 2014: 26 · 2013: 40 · 2012: 21
- FWCI
- 10.81
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Methods (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- The Mouseion at the JAXlibrary (Jackson Laboratory) (submittedVersion)
- Funders
- Canadian Institutes of Health Research (MOP79368, GSP-415-67)
- National Human Genome Research Institute (R01HG005084)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- synthetic genetic array, genetic interactions, fitness measurement, double mutants, yeast, colony size, normalization, genetic suppression, protein complexes, loss-of-function alleles
- MeSH terms
- Algorithms, Mutation, Ultraviolet Rays, Yeasts, Gene Expression Regulation, Fungal, Mutagenesis, Genome, Fungal, Oligonucleotide Array Sequence Analysis, Genome-Wide Association Study, Genetic Fitness
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