Quantitative analysis of fitness and genetic interactions in yeast on a genome scale. Author Anastasia Baryshnikova, 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 Bader, Olga Troyanskaya, Grant Brown, Brenda Andrews, Charles Boone, Chad Myers Publication Year 2010 Type Journal Article 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. Keywords Mutation, Gene Expression Regulation, Fungal, Yeasts, Algorithms, Oligonucleotide Array Sequence Analysis, Genome-Wide Association Study, Genome, Fungal, Mutagenesis, Genetic Fitness, Ultraviolet Rays Journal Nat Methods Volume 7 Issue 12 Pages 1017-24 Date Published 12/2010 Alternate Journal Nat. Methods Google ScholarBibTeXEndNote X3 XML