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τ-SGA: synthetic genetic array analysis for systematically screening and quantifying trigenic interactions in yeast.
Kuzmin, Elena; Rahman, Mahfuzur; VanderSluis, Benjamin; Costanzo, Michael; Myers, Chad L; Andrews, Brenda J; Boone, Charles.
Afiliação
  • Kuzmin E; The Donnelly Centre, University of Toronto, Toronto, Ontario, Canada. kuzmin.elena@gmail.com.
  • Rahman M; Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada. kuzmin.elena@gmail.com.
  • VanderSluis B; Rosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, Quebec, Canada. kuzmin.elena@gmail.com.
  • Costanzo M; Department of Computer Science and Engineering, University of Minnesota-Twin Cities, Minneapolis, MN, USA.
  • Myers CL; Department of Computer Science and Engineering, University of Minnesota-Twin Cities, Minneapolis, MN, USA.
  • Andrews BJ; The Donnelly Centre, University of Toronto, Toronto, Ontario, Canada.
  • Boone C; Department of Computer Science and Engineering, University of Minnesota-Twin Cities, Minneapolis, MN, USA. chadm@umn.edu.
Nat Protoc ; 16(2): 1219-1250, 2021 02.
Article em En | MEDLINE | ID: mdl-33462440
Systematic complex genetic interaction studies have provided insight into high-order functional redundancies and genetic network wiring of the cell. Here, we describe a method for screening and quantifying trigenic interactions from ordered arrays of yeast strains grown on agar plates as individual colonies. The protocol instructs users on the trigenic synthetic genetic array analysis technique, τ-SGA, for high-throughput screens. The steps describe construction of the double-mutant query strains and the corresponding single-mutant control query strains, which are screened in parallel in two replicates. The screening experimental set-up consists of sequential replica-pinning steps that enable automated mating, meiotic recombination and successive haploid selection steps for the generation of triple mutants, which are scored for colony size as a proxy for fitness, which enables the calculation of trigenic interactions. The procedure described here was used to conduct 422 trigenic interaction screens, which generated ~460,000 yeast triple mutants for trigenic interaction analysis. Users should be familiar with robotic equipment required for high-throughput genetic interaction screens and be proficient at the command line to execute the scoring pipeline. Large-scale screen computational analysis is achieved by using MATLAB pipelines that score raw colony size data to produce τ-SGA interaction scores. Additional recommendations are included for optimizing experimental design and analysis of smaller-scale trigenic interaction screens by using a web-based analysis system, SGAtools. This protocol provides a resource for those who would like to gain a deeper, more practical understanding of trigenic interaction screening and quantification methodology.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Leveduras / Sequenciamento de Nucleotídeos em Larga Escala Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Leveduras / Sequenciamento de Nucleotídeos em Larga Escala Idioma: En Ano de publicação: 2021 Tipo de documento: Article