SGAM: An Array-Based Approach for High-Resolution Genetic Mapping in Saccharomyces cerevisiae

Part of the Methods in Molecular Biology book series (MIMB, volume 548)


The development of genome-scale resources and high-throughput methodologies has enabled systematic assessment of gene function in vivo. Synthetic genetic array (SGA) analysis automates yeast genetic manipulation, permitting diverse analysis of ∼5,000 viable deletion mutants in Saccharomyces cerevisiae. SGA methodology has enabled genome-wide synthetic lethal screening and construction of a large-scale genetic interaction network for yeast. Genetic networks often reveal new components of specific pathways and functional relationships between genes whose products buffer one another or impinge on a common essential pathway. Because SGA analysis can be used to manipulate any genetic element linked to a selectable marker, it is a highly versatile approach that can be adapted for a variety of different genetic screens, including synthetic lethality, dosage suppression, and dosage lethality. This chapter focuses on a specific SGA application for high-resolution genetic mapping, referred to as SGA mapping (SGAM), which enables the identification of suppressor mutations and thus provides a powerful means for interrogating gene function and pathway order.

Key words

Yeast Genetics Genetic mapping Synthetic lethal SGA SGAM Deletion mutant Double mutant Suppression 



We thank Anastasia Baryshnikova, Renee Brost, Julie Guzzo, and Corey Nislow for help with figures and comments on the manuscript. This work was supported by grants to CB from the Canadian Institutes for Health Research and Genome Canada through the Ontario Genomics Institute.


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Copyright information

© Humana Press, a part of Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Terrence Donnelly Centre for Cellular and Biomolecular ResearchUniversity of TorontoTorontoCanada

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