Literature DB >> 27037078

Synthetic Genetic Arrays: Automation of Yeast Genetics.

Elena Kuzmin1, Michael Costanzo1, Brenda Andrews1, Charles Boone1.   

Abstract

Genome-sequencing efforts have led to great strides in the annotation of protein-coding genes and other genomic elements. The current challenge is to understand the functional role of each gene and how genes work together to modulate cellular processes. Genetic interactions define phenotypic relationships between genes and reveal the functional organization of a cell. Synthetic genetic array (SGA) methodology automates yeast genetics and enables large-scale and systematic mapping of genetic interaction networks in the budding yeast,Saccharomyces cerevisiae SGA facilitates construction of an output array of double mutants from an input array of single mutants through a series of replica pinning steps. Subsequent analysis of genetic interactions from SGA-derived mutants relies on accurate quantification of colony size, which serves as a proxy for fitness. Since its development, SGA has given rise to a variety of other experimental approaches for functional profiling of the yeast genome and has been applied in a multitude of other contexts, such as genome-wide screens for synthetic dosage lethality and integration with high-content screening for systematic assessment of morphology defects. SGA-like strategies can also be implemented similarly in a number of other cell types and organisms, includingSchizosaccharomyces pombe,Escherichia coli, Caenorhabditis elegans, and human cancer cell lines. The genetic networks emerging from these studies not only generate functional wiring diagrams but may also play a key role in our understanding of the complex relationship between genotype and phenotype.
© 2016 Cold Spring Harbor Laboratory Press.

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Year:  2016        PMID: 27037078     DOI: 10.1101/pdb.top086652

Source DB:  PubMed          Journal:  Cold Spring Harb Protoc        ISSN: 1559-6095


  6 in total

1.  Trigenic Synthetic Genetic Array (τ-SGA) Technique for Complex Interaction Analysis.

Authors:  Elena Kuzmin; Brenda J Andrews; Charles Boone
Journal:  Methods Mol Biol       Date:  2021

2.  Exploring whole-genome duplicate gene retention with complex genetic interaction analysis.

Authors:  Elena Kuzmin; Benjamin VanderSluis; Alex N Nguyen Ba; Wen Wang; Elizabeth N Koch; Matej Usaj; Anton Khmelinskii; Mojca Mattiazzi Usaj; Jolanda van Leeuwen; Oren Kraus; Amy Tresenrider; Michael Pryszlak; Ming-Che Hu; Brenda Varriano; Michael Costanzo; Michael Knop; Alan Moses; Chad L Myers; Brenda J Andrews; Charles Boone
Journal:  Science       Date:  2020-06-26       Impact factor: 47.728

3.  A Deep-sequencing-assisted, Spontaneous Suppressor Screen in the Fission Yeast Schizosaccharomyces pombe.

Authors:  Bahjat F Marayati; James B Pease; Ke Zhang
Journal:  J Vis Exp       Date:  2019-03-07       Impact factor: 1.355

4.  τ-SGA: synthetic genetic array analysis for systematically screening and quantifying trigenic interactions in yeast.

Authors:  Elena Kuzmin; Mahfuzur Rahman; Benjamin VanderSluis; Michael Costanzo; Chad L Myers; Brenda J Andrews; Charles Boone
Journal:  Nat Protoc       Date:  2021-01-18       Impact factor: 17.021

5.  Bacterial Signaling Nucleotides Inhibit Yeast Cell Growth by Impacting Mitochondrial and Other Specifically Eukaryotic Functions.

Authors:  Andy Hesketh; Marta Vergnano; Chris Wan; Stephen G Oliver
Journal:  mBio       Date:  2017-07-25       Impact factor: 7.867

6.  Genetic interaction analysis comes to the diploid human pathogen Candida albicans.

Authors:  Virginia E Glazier; Damian J Krysan
Journal:  PLoS Pathog       Date:  2020-04-23       Impact factor: 6.823

  6 in total

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