Abstract
Screening genome-wide sets of mutants for fitness defects provides a simple but powerful approach for exploring gene function, mapping genetic networks and probing mechanisms of drug action. For yeast and other microorganisms with global mutant collections, genetic or chemical-genetic interactions can be effectively quantified by growing an ordered array of strains on agar plates as individual colonies, and then scoring the colony size changes in response to a genetic or environmental perturbation. To do so, requires efficient tools for the extraction and analysis of quantitative data. Here, we describe SGAtools (http://sgatools.ccbr.utoronto.ca), a web-based analysis system for designer genetic screens. SGAtools outlines a series of guided steps that allow the user to quantify colony sizes from images of agar plates, correct for systematic biases in the observations and calculate a fitness score relative to a control experiment. The data can also be visualized online to explore the colony sizes on individual plates, view the distribution of resulting scores, highlight genes with the strongest signal and perform Gene Ontology enrichment analysis.
Highlights
Screening for genetic or chemical-genetic interactions, which occur when a genetic or chemical perturbation leads to an extreme phenotype, provides a simple but powerful approach for revealing gene function and discovering the mode of action of bioactive molecules [1,2]
Projects aimed at large-scale screening for genetic interactions have identified several sources of experimental error, which led to the development of analysis methods that are tailored to the resulting large data sets
SGAtools was primarily developed for the yeast community with the Synthetic Genetic Array (SGA) analysis in mind, it can be useful for other types of colony size-based screens
Summary
Screening for genetic or chemical-genetic interactions, which occur when a genetic or chemical perturbation leads to an extreme phenotype, provides a simple but powerful approach for revealing gene function and discovering the mode of action of bioactive molecules [1,2]. Projects aimed at large-scale screening for genetic interactions have identified several sources of experimental error, which led to the development of analysis methods that are tailored to the resulting large data sets. SGAtools is a publicly available web server for common analysis tasks associated with low- to medium-throughput genetic screens. Raw digital images from the screen are processed to produce colony size measurements in a simple tab-delimited format.
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