The Experts below are selected from a list of 1569 Experts worldwide ranked by ideXlab platform
Charles Boone - One of the best experts on this subject based on the ideXlab platform.
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Trigenic Synthetic Genetic Array (τ-SGA) Technique for Complex Interaction Analysis.
Methods in molecular biology (Clifton N.J.), 2021Co-Authors: Elena Kuzmin, Brenda J Andrews, Charles BooneAbstract:Complex Genetic interactions occur when mutant alleles of multiple genes combine to elicit an unexpected phenotype, which could not be predicted given the expectation based on the combination of phenotypes associated with individual mutant alleles. Trigenic Synthetic Genetic Array (τ-SGA) methodology was developed for the systematic analysis of complex interactions involving combinations of three gene perturbations. With a series of replica pinning steps of the τ-SGA procedure, haploid triple mutants are constructed through automated mating and meiotic recombination. For example, a double-mutant query strain carrying two mutant alleles of interest, such as a deletion allele of a nonessential gene and a conditional temperature-sensitive allele of an essential gene, is crossed to an input Array of yeast mutants, such as the diagnostic Array set of ~1200 mutants, to generate an output Array of triple mutants. The colony-size measurements of the resulting triple mutants are used to estimate cellular fitness and quantify trigenic interactions by incorporating corresponding single- and double-mutant fitness estimates. Trigenic interaction networks can be further analyzed for functional modules using various clustering and enrichment analysis tools. Complex Genetic interactions are rich in functional information and provide insight into the genotype-to-phenotype relationship, genome size, and speciation.
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τ-SGA: Synthetic Genetic Array analysis for systematically screening and quantifying trigenic interactions in yeast.
Nature protocols, 2021Co-Authors: Elena Kuzmin, Michael Costanzo, Brenda J Andrews, Chad L. Myers, Benjamin Vandersluis, Mahfuzur Rahman, Charles BooneAbstract: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.
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τ-SGA: Synthetic Genetic Array analysis for systematically screening and quantifying trigenic interactions in yeast
Nature Protocols, 2021Co-Authors: Elena Kuzmin, Michael Costanzo, Brenda J Andrews, Chad L. Myers, Benjamin Vandersluis, Mahfuzur Rahman, Charles BooneAbstract: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. This protocol describes procedures for high-throughput analysis of trigenic interactions in yeast. Triple-mutant strains generated in a series of automated replica-pinning steps are grown on agar plates as individual colonies, and interactions are quantified with the trigenic Synthetic Genetic Array scoring method.
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TheCellMap.org: A Web-Accessible Database for Visualizing and Mining the Global Yeast Genetic Interaction Network.
G3: Genes|Genomes|Genetics, 2017Co-Authors: Matej Usaj, Michael Costanzo, Brenda J Andrews, Chad L. Myers, Yizhao Tan, Wen Wang, Benjamin Vandersluis, Albert Zou, Charles BooneAbstract:Providing access to quantitative genomic data is key to ensure large-scale data validation and promote new discoveries. TheCellMap.org serves as a central repository for storing and analyzing quantitative Genetic interaction data produced by genome-scale Synthetic Genetic Array (SGA) experiments with the budding yeast Saccharomyces cerevisiae In particular, TheCellMap.org allows users to easily access, visualize, explore, and functionally annotate Genetic interactions, or to extract and reorganize subnetworks, using data-driven network layouts in an intuitive and interactive manner.
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RESEARCH ARTICLE Genetic Interactions Implicating Postreplicative Repair in Okazaki Fragment Processing
2016Co-Authors: Jordan R. Becker, Michael Costanzo, Charles Boone, Chad L. Myers, Carles Pons, Hai Dang Nguyen, Anja-katrin BielinskyAbstract:Ubiquitination of the replication clamp proliferating cell nuclear antigen (PCNA) at the con-served residue lysine (K)164 triggers postreplicative repair (PRR) to fill single-stranded gaps that result from stalled DNA polymerases. However, it has remained elusive as to whether cells engage PRR in response to replication defects that do not directly impair DNA synthesis. To experimentally address this question, we performed Synthetic Genetic Array (SGA) analysis with a ubiquitination-deficient K164 to arginine (K164R) mutant of PCNA against a library of S. cerevisiae temperature-sensitive alleles. The SGA signature of the K164R allele showed a striking correlation with profiles of mutants deficient in various aspects of lagging strand replication, including rad27Δ and elg1Δ. Rad27 is the primary flap endonuclease that processes 5 ’ flaps generated during lagging strand replication, whereas Elg1 has been implicated in unloading PCNA from chromatin. We observed chronic ubiquiti-nation of PCNA at K164 in both rad27Δ and elg1Δmutants. Notably, only rad27Δ cells exhibited a decline in cell viability upon elimination of PRR pathways, whereas elg1Δ mutants were not affected. We further provide evidence that K164 ubiquitination sup
Brenda J Andrews - One of the best experts on this subject based on the ideXlab platform.
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Trigenic Synthetic Genetic Array (τ-SGA) Technique for Complex Interaction Analysis.
Methods in molecular biology (Clifton N.J.), 2021Co-Authors: Elena Kuzmin, Brenda J Andrews, Charles BooneAbstract:Complex Genetic interactions occur when mutant alleles of multiple genes combine to elicit an unexpected phenotype, which could not be predicted given the expectation based on the combination of phenotypes associated with individual mutant alleles. Trigenic Synthetic Genetic Array (τ-SGA) methodology was developed for the systematic analysis of complex interactions involving combinations of three gene perturbations. With a series of replica pinning steps of the τ-SGA procedure, haploid triple mutants are constructed through automated mating and meiotic recombination. For example, a double-mutant query strain carrying two mutant alleles of interest, such as a deletion allele of a nonessential gene and a conditional temperature-sensitive allele of an essential gene, is crossed to an input Array of yeast mutants, such as the diagnostic Array set of ~1200 mutants, to generate an output Array of triple mutants. The colony-size measurements of the resulting triple mutants are used to estimate cellular fitness and quantify trigenic interactions by incorporating corresponding single- and double-mutant fitness estimates. Trigenic interaction networks can be further analyzed for functional modules using various clustering and enrichment analysis tools. Complex Genetic interactions are rich in functional information and provide insight into the genotype-to-phenotype relationship, genome size, and speciation.
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τ-SGA: Synthetic Genetic Array analysis for systematically screening and quantifying trigenic interactions in yeast.
Nature protocols, 2021Co-Authors: Elena Kuzmin, Michael Costanzo, Brenda J Andrews, Chad L. Myers, Benjamin Vandersluis, Mahfuzur Rahman, Charles BooneAbstract: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.
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τ-SGA: Synthetic Genetic Array analysis for systematically screening and quantifying trigenic interactions in yeast
Nature Protocols, 2021Co-Authors: Elena Kuzmin, Michael Costanzo, Brenda J Andrews, Chad L. Myers, Benjamin Vandersluis, Mahfuzur Rahman, Charles BooneAbstract: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. This protocol describes procedures for high-throughput analysis of trigenic interactions in yeast. Triple-mutant strains generated in a series of automated replica-pinning steps are grown on agar plates as individual colonies, and interactions are quantified with the trigenic Synthetic Genetic Array scoring method.
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Reporter-Based Synthetic Genetic Array Analysis: A Functional Genomics Approach for Investigating Transcript or Protein Abundance Using Fluorescent Proteins in Saccharomyces cerevisiae
Genome Instability, 2018Co-Authors: Hendrikje Göttert, Adam P. Rosebrock, Mojca Mattiazzi Usaj, Brenda J AndrewsAbstract:Fluorescent reporter genes have long been used to quantify various cell features such as transcript and protein abundance. Here, we describe a method, reporter Synthetic Genetic Array (R-SGA) analysis, which allows for the simultaneous quantification of any fluorescent protein readout in thousands of yeast strains using an automated pipeline. R-SGA combines a fluorescent reporter system with standard SGA analysis and can be used to examine any Array-based strain collection available to the yeast community. This protocol describes the R-SGA methodology for screening different Arrays of yeast mutants including the deletion collection, a collection of temperature-sensitive strains for the assessment of essential yeast genes and a collection of inducible overexpression strains. We also present an alternative pipeline for the analysis of R-SGA output strains using flow cytometry of cells in liquid culture. Data normalization for both pipelines is discussed.
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TheCellMap.org: A Web-Accessible Database for Visualizing and Mining the Global Yeast Genetic Interaction Network.
G3: Genes|Genomes|Genetics, 2017Co-Authors: Matej Usaj, Michael Costanzo, Brenda J Andrews, Chad L. Myers, Yizhao Tan, Wen Wang, Benjamin Vandersluis, Albert Zou, Charles BooneAbstract:Providing access to quantitative genomic data is key to ensure large-scale data validation and promote new discoveries. TheCellMap.org serves as a central repository for storing and analyzing quantitative Genetic interaction data produced by genome-scale Synthetic Genetic Array (SGA) experiments with the budding yeast Saccharomyces cerevisiae In particular, TheCellMap.org allows users to easily access, visualize, explore, and functionally annotate Genetic interactions, or to extract and reorganize subnetworks, using data-driven network layouts in an intuitive and interactive manner.
Franco J. Vizeacoumar - One of the best experts on this subject based on the ideXlab platform.
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systematic exploration of essential yeast gene function with temperature sensitive mutants
Nature Biotechnology, 2011Co-Authors: Franco J. Vizeacoumar, Benjamin Vandersluis, Sondra Bahr, Jonas Warringer, Renqiang Min, Jeremy Bellay, Michael Devit, James A Fleming, Andrew D StephensAbstract:Conditional temperature-sensitive (ts) mutations are valuable reagents for studying essential genes in the yeast Saccharomyces cerevisiae. We constructed 787 ts strains, covering 497 (∼45%) of the 1,101 essential yeast genes, with ∼30% of the genes represented by multiple alleles. All of the alleles are integrated into their native genomic locus in the S288C common reference strain and are linked to a kanMX selectable marker, allowing further Genetic manipulation by Synthetic Genetic Array (SGA)-based, high-throughput methods. We show two such manipulations: barcoding of 440 strains, which enables chemical-Genetic suppression analysis, and the construction of Arrays of strains carrying different fluorescent markers of subcellular structure, which enables quantitative analysis of phenotypes using high-content screening. Quantitative analysis of a GFP-tubulin marker identified roles for cohesin and condensin genes in spindle disassembly. This mutant collection should facilitate a wide range of systematic studies aimed at understanding the functions of essential genes.
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Systematic exploration of essential yeast gene function with temperature-sensitive mutants
Nature Biotechnology, 2011Co-Authors: Franco J. Vizeacoumar, Benjamin Vandersluis, Sondra Bahr, Jonas Warringer, Renqiang Min, Jeremy Bellay, Michael Devit, James A Fleming, Andrew StephensAbstract:Conditional temperature-sensitive (ts) mutations are valuable reagents for studying essential genes in the yeast Saccharomyces cerevisiae . We constructed 787 ts strains, covering 497 (∼45%) of the 1,101 essential yeast genes, with ∼30% of the genes represented by multiple alleles. All of the alleles are integrated into their native genomic locus in the S288C common reference strain and are linked to a kanMX selectable marker, allowing further Genetic manipulation by Synthetic Genetic Array (SGA)–based, high-throughput methods. We show two such manipulations: barcoding of 440 strains, which enables chemical-Genetic suppression analysis, and the construction of Arrays of strains carrying different fluorescent markers of subcellular structure, which enables quantitative analysis of phenotypes using high-content screening. Quantitative analysis of a GFP-tubulin marker identified roles for cohesin and condensin genes in spindle disassembly. This mutant collection should facilitate a wide range of systematic studies aimed at understanding the functions of essential genes. Essential genes have been effectively studied using temperature-sensitive alleles in yeast. Li et al . construct a large collection of temperature-sensitive yeast mutants and show how it enables high-throughput analyses of the function of essential genes.
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Integrating high-throughput Genetic interaction mapping and high-content screening to explore yeast spindle morphogenesis
Journal of Cell Biology, 2010Co-Authors: Franco J. Vizeacoumar, Yaroslav Sydorskyy, Nydia Van Dyk, Vincent Cheung, Nicolle Case, Alessandro DattiAbstract:We describe the application of a novel screening approach that combines automated yeast Genetics, Synthetic Genetic Array (SGA) analysis, and a high-content screening (HCS) system to examine mitotic spindle morphogenesis. We measured numerous spindle and cellular morphological parameters in thousands of single mutants and corresponding sensitized double mutants lacking genes known to be involved in spindle function. We focused on a subset of genes that appear to define a highly conserved mitotic spindle disassembly pathway, which is known to involve Ipl1p, the yeast aurora B kinase, as well as the cell cycle regulatory networks mitotic exit network (MEN) and fourteen early anaphase release (FEAR). We also dissected the function of the kinetochore protein Mcm21p, showing that sumoylation of Mcm21p regulates the enrichment of Ipl1p and other chromosomal passenger proteins to the spindle midzone to mediate spindle disassembly. Although we focused on spindle disassembly in a proof-of-principle study, our integrated HCS-SGA method can be applied to virtually any pathway, making it a powerful means for identifying specific cellular functions.
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Synthetic Genetic Array (SGA) analysis in Saccharomyces cerevisiae and Schizosaccharomyces pombe.
Methods in Enzymology, 2010Co-Authors: Anastasia Baryshnikova, Michael Costanzo, Brenda J Andrews, Scott J. Dixon, Franco J. Vizeacoumar, Chad L. Myers, Charles BooneAbstract:A Genetic interaction occurs when the combination of two mutations leads to an unexpected phenotype. Screens for Synthetic Genetic interactions have been used extensively to identify genes whose products are functionally related. In particular, Synthetic lethal Genetic interactions often identify genes that buffer one another or impinge on the same essential pathway. For the yeast Saccharomyces cerevisiae, we developed a method termed Synthetic Genetic Array (SGA) analysis, which offers an efficient approach for the systematic construction of double mutants and enables a global analysis of Synthetic Genetic interactions. In a typical SGA screen, a query mutation is crossed to an ordered Array of ~ 5000 viable gene deletion mutants (representing ~ 80% of all yeast genes) such that meiotic progeny harboring both mutations can be scored for fitness defects. This approach can be extended to all ~ 6000 genes through the use of yeast Arrays containing mutants carrying conditional or hypomorphic alleles of essential genes. Estimating the fitness for the two single mutants and their corresponding double mutant enables a quantitative measurement of Genetic interactions, distinguishing negative (Synthetic lethal) and positive (within pathway and suppression) interactions. The profile of Genetic interactions represents a rich phenotypic signature for each gene and clustering Genetic interaction profiles group genes into functionally relevant pathways and complexes. This Array-based approach automates yeast Genetic analysis in general and can be easily adapted for a number of different Genetic screens or combined with high-content screening systems to quantify the activity of specific reporters in genome-wide sets of single or more complex multiple mutant backgrounds. Comparison of Genetic and chemical-Genetic interaction profiles offers the potential to link bioactive compounds to their targets. Finally, we also developed an SGA system for the fission yeast Schizosaccharomyces pombe, providing another model system for comparative analysis of Genetic networks and testing the conservation of Genetic networks over millions of years of evolution.
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A picture is worth a thousand words: Genomics to phenomics in the yeast Saccharomyces cerevisiae
FEBS Letters, 2009Co-Authors: Franco J. Vizeacoumar, Charles Boone, Yolanda T. Chong, Brenda J AndrewsAbstract:Large scale cell biological experiments are beginning to be applied as a systems-level approach to decipher mechanisms that govern cellular function in health and disease. The use of automated microscopes combined with digital imaging, machine learning and other analytical tools has enabled high-content screening (HCS) in a variety of experimental systems. Successful HCS screens demand careful attention to assay development, data acquisition methods and available genomic tools. In this minireview, we highlight developments in this field pertaining to yeast cell biology and discuss how we have combined HCS with methods for automated yeast Genetics (Synthetic Genetic Array (SGA) analysis) to enable systematic analysis of cell biological phenotypes in a variety of Genetic backgrounds.
Michael Costanzo - One of the best experts on this subject based on the ideXlab platform.
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τ-SGA: Synthetic Genetic Array analysis for systematically screening and quantifying trigenic interactions in yeast.
Nature protocols, 2021Co-Authors: Elena Kuzmin, Michael Costanzo, Brenda J Andrews, Chad L. Myers, Benjamin Vandersluis, Mahfuzur Rahman, Charles BooneAbstract: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.
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τ-SGA: Synthetic Genetic Array analysis for systematically screening and quantifying trigenic interactions in yeast
Nature Protocols, 2021Co-Authors: Elena Kuzmin, Michael Costanzo, Brenda J Andrews, Chad L. Myers, Benjamin Vandersluis, Mahfuzur Rahman, Charles BooneAbstract: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. This protocol describes procedures for high-throughput analysis of trigenic interactions in yeast. Triple-mutant strains generated in a series of automated replica-pinning steps are grown on agar plates as individual colonies, and interactions are quantified with the trigenic Synthetic Genetic Array scoring method.
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TheCellMap.org: A Web-Accessible Database for Visualizing and Mining the Global Yeast Genetic Interaction Network.
G3: Genes|Genomes|Genetics, 2017Co-Authors: Matej Usaj, Michael Costanzo, Brenda J Andrews, Chad L. Myers, Yizhao Tan, Wen Wang, Benjamin Vandersluis, Albert Zou, Charles BooneAbstract:Providing access to quantitative genomic data is key to ensure large-scale data validation and promote new discoveries. TheCellMap.org serves as a central repository for storing and analyzing quantitative Genetic interaction data produced by genome-scale Synthetic Genetic Array (SGA) experiments with the budding yeast Saccharomyces cerevisiae In particular, TheCellMap.org allows users to easily access, visualize, explore, and functionally annotate Genetic interactions, or to extract and reorganize subnetworks, using data-driven network layouts in an intuitive and interactive manner.
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RESEARCH ARTICLE Genetic Interactions Implicating Postreplicative Repair in Okazaki Fragment Processing
2016Co-Authors: Jordan R. Becker, Michael Costanzo, Charles Boone, Chad L. Myers, Carles Pons, Hai Dang Nguyen, Anja-katrin BielinskyAbstract:Ubiquitination of the replication clamp proliferating cell nuclear antigen (PCNA) at the con-served residue lysine (K)164 triggers postreplicative repair (PRR) to fill single-stranded gaps that result from stalled DNA polymerases. However, it has remained elusive as to whether cells engage PRR in response to replication defects that do not directly impair DNA synthesis. To experimentally address this question, we performed Synthetic Genetic Array (SGA) analysis with a ubiquitination-deficient K164 to arginine (K164R) mutant of PCNA against a library of S. cerevisiae temperature-sensitive alleles. The SGA signature of the K164R allele showed a striking correlation with profiles of mutants deficient in various aspects of lagging strand replication, including rad27Δ and elg1Δ. Rad27 is the primary flap endonuclease that processes 5 ’ flaps generated during lagging strand replication, whereas Elg1 has been implicated in unloading PCNA from chromatin. We observed chronic ubiquiti-nation of PCNA at K164 in both rad27Δ and elg1Δmutants. Notably, only rad27Δ cells exhibited a decline in cell viability upon elimination of PRR pathways, whereas elg1Δ mutants were not affected. We further provide evidence that K164 ubiquitination sup
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Synthetic Genetic Array Analysis.
Cold Spring Harbor Protocols, 2016Co-Authors: Elena Kuzmin, Michael Costanzo, Brenda J Andrews, Charles BooneAbstract:Genetic interaction studies have been used to characterize unknown genes, assign membership in pathway and complex, and build a comprehensive functional map of a eukaryotic cell. Synthetic Genetic Array (SGA) methodology automates yeast Genetic analysis and enables systematic mapping of Genetic interactions. In its simplest form, SGA consists of a series of replica pinning steps that enable construction of haploid double mutants through automated mating and meiotic recombination. Using this method, a strain carrying a query mutation, such as a deletion allele of a nonessential gene or a conditional temperature-sensitive allele of an essential gene, can be crossed to an input Array of yeast mutants, such as the complete set of approximately 5000 viable deletion mutants. The resulting output Array of double mutants can be scored for Genetic interactions based on estimates of cellular fitness derived from colony-size measurements. The SGA score method can be used to analyze large-scale data sets, whereas small-scale data sets can be analyzed using SGAtools, a simple web-based interface that includes all the necessary analysis steps for quantifying Genetic interactions.
Elena Kuzmin - One of the best experts on this subject based on the ideXlab platform.
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Trigenic Synthetic Genetic Array (τ-SGA) Technique for Complex Interaction Analysis.
Methods in molecular biology (Clifton N.J.), 2021Co-Authors: Elena Kuzmin, Brenda J Andrews, Charles BooneAbstract:Complex Genetic interactions occur when mutant alleles of multiple genes combine to elicit an unexpected phenotype, which could not be predicted given the expectation based on the combination of phenotypes associated with individual mutant alleles. Trigenic Synthetic Genetic Array (τ-SGA) methodology was developed for the systematic analysis of complex interactions involving combinations of three gene perturbations. With a series of replica pinning steps of the τ-SGA procedure, haploid triple mutants are constructed through automated mating and meiotic recombination. For example, a double-mutant query strain carrying two mutant alleles of interest, such as a deletion allele of a nonessential gene and a conditional temperature-sensitive allele of an essential gene, is crossed to an input Array of yeast mutants, such as the diagnostic Array set of ~1200 mutants, to generate an output Array of triple mutants. The colony-size measurements of the resulting triple mutants are used to estimate cellular fitness and quantify trigenic interactions by incorporating corresponding single- and double-mutant fitness estimates. Trigenic interaction networks can be further analyzed for functional modules using various clustering and enrichment analysis tools. Complex Genetic interactions are rich in functional information and provide insight into the genotype-to-phenotype relationship, genome size, and speciation.
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τ-SGA: Synthetic Genetic Array analysis for systematically screening and quantifying trigenic interactions in yeast
Nature Protocols, 2021Co-Authors: Elena Kuzmin, Michael Costanzo, Brenda J Andrews, Chad L. Myers, Benjamin Vandersluis, Mahfuzur Rahman, Charles BooneAbstract: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. This protocol describes procedures for high-throughput analysis of trigenic interactions in yeast. Triple-mutant strains generated in a series of automated replica-pinning steps are grown on agar plates as individual colonies, and interactions are quantified with the trigenic Synthetic Genetic Array scoring method.
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τ-SGA: Synthetic Genetic Array analysis for systematically screening and quantifying trigenic interactions in yeast.
Nature protocols, 2021Co-Authors: Elena Kuzmin, Michael Costanzo, Brenda J Andrews, Chad L. Myers, Benjamin Vandersluis, Mahfuzur Rahman, Charles BooneAbstract: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.
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Synthetic Genetic Array Analysis.
Cold Spring Harbor Protocols, 2016Co-Authors: Elena Kuzmin, Michael Costanzo, Brenda J Andrews, Charles BooneAbstract:Genetic interaction studies have been used to characterize unknown genes, assign membership in pathway and complex, and build a comprehensive functional map of a eukaryotic cell. Synthetic Genetic Array (SGA) methodology automates yeast Genetic analysis and enables systematic mapping of Genetic interactions. In its simplest form, SGA consists of a series of replica pinning steps that enable construction of haploid double mutants through automated mating and meiotic recombination. Using this method, a strain carrying a query mutation, such as a deletion allele of a nonessential gene or a conditional temperature-sensitive allele of an essential gene, can be crossed to an input Array of yeast mutants, such as the complete set of approximately 5000 viable deletion mutants. The resulting output Array of double mutants can be scored for Genetic interactions based on estimates of cellular fitness derived from colony-size measurements. The SGA score method can be used to analyze large-scale data sets, whereas small-scale data sets can be analyzed using SGAtools, a simple web-based interface that includes all the necessary analysis steps for quantifying Genetic interactions.
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Synthetic Genetic Array Analysis for Global Mapping of Genetic Networks in Yeast
Methods in Molecular Biology, 2014Co-Authors: Elena Kuzmin, Michael Costanzo, Brenda J Andrews, Anastasia Baryshnikova, Chad L. Myers, Sara Sharifpoor, Charles BooneAbstract:Genetic interactions occur when mutant alleles of two or more genes collaborate to generate an unusual composite phenotype, one that would not be predicted based on the expected combined effects of the individual mutant alleles. Synthetic Genetic Array (SGA) methodology was developed to automate yeast Genetic analysis and enable systematic Genetic interaction studies. In its simplest form, SGA consists of a series of replica pinning steps, which enable the construction of haploid double mutants through mating and meiotic recombination. For example, a strain carrying a query mutation, such as a deletion allele of a nonessential gene or a conditional temperature sensitive allele of an essential gene, could be crossed to an input Array of yeast mutants, such as the complete set of ~5,000 viable deletion mutants, to generate an output Array of double mutants, that can be scored for Genetic interactions based on estimates of cellular fitness derived from colony-size measurements. A simple quantitative measure of Genetic interactions can be derived from colony size, which serves as a proxy for fitness. Furthermore, SGA can be applied in a variety of other contexts, such as Synthetic Dosage Lethality (SDL), in which a query mutation is crossed into an Array of yeast strains, each of which overexpresses a different gene, thus making use of SGA to probe for gain-of-function phenotypes in specific Genetic backgrounds. High-Content Screening (HCS) also integrates SGA to perform genome-wide screens for quantitative analysis of morphological phenotypes or pathway activity based upon fluorescent markers, extending Genetic interaction analysis beyond fitness-based measurements. Genetic interaction studies offer insight into gene function, pathway structure, and buffering, and thus a complete Genetic interaction network of yeast will generate a global functional wiring diagram for a eukaryotic cell.
