||Erin B Styles, Karen J Founk, Lee A Zamparo, Tina L Sing, Dogus Altintas, Cyril Ribeyre, Virginie Ribaud, Jacques Rougemont, David Mayhew, Michael Costanzo, Matej Usaj, Adrian J Verster, Elizabeth N Koch, Daniele Novarina, Marco Graf, Brian Luke, Marco Muzi-Falconi, Chad L Myers, Robi David Mitra, David Shore, Grant W Brown, Zhaolei Zhang, Charles Boone, Brenda J Andrews
||A significant challenge of functional genomics is to develop methods for genome-scale acquisition and analysis of cell biological data. Here, we present an integrated method that combines genome-wide genetic perturbation of Saccharomyces cerevisiae with high-content screening to facilitate the genetic description of sub-cellular structures and compartment morphology. As proof of principle, we used a Rad52-GFP marker to examine DNA damage foci in ∼20 million single cells from ∼5,000 different mutant backgrounds in the context of selected genetic or chemical perturbations. Phenotypes were classified using a machine learning-based automated image analysis pipeline. 345 mutants were identified that had elevated numbers of DNA damage foci, almost half of which were identified only in sensitized backgrounds. Subsequent analysis of Vid22, a protein implicated in the DNA damage response, revealed that it acts together with the Sgs1 helicase at sites of DNA damage and preferentially binds G-quadruplex regions of the genome. This approach is extensible to numerous other cell biological markers and experimental systems.