| Literature DB >> 21076421 |
Anastasia Baryshnikova1, Michael Costanzo, Yungil Kim, Huiming Ding, Judice Koh, Kiana Toufighi, Ji-Young Youn, Jiongwen Ou, Bryan-Joseph San Luis, Sunayan Bandyopadhyay, Matthew Hibbs, David Hess, Anne-Claude Gingras, Gary D Bader, Olga G Troyanskaya, Grant W Brown, Brenda Andrews, Charles Boone, Chad L Myers.
Abstract
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.Entities:
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Year: 2010 PMID: 21076421 PMCID: PMC3117325 DOI: 10.1038/nmeth.1534
Source DB: PubMed Journal: Nat Methods ISSN: 1548-7091 Impact factor: 28.547