| Literature DB >> 27617677 |
Erin B Styles1, Karen J Founk1, Lee A Zamparo2, Tina L Sing3, Dogus Altintas4, Cyril Ribeyre4, Virginie Ribaud4, Jacques Rougemont5, David Mayhew6, Michael Costanzo7, Matej Usaj7, Adrian J Verster7, Elizabeth N Koch8, Daniele Novarina9, Marco Graf10, Brian Luke10, Marco Muzi-Falconi9, Chad L Myers8, Robi David Mitra6, David Shore4, Grant W Brown3, Zhaolei Zhang1, Charles Boone11, Brenda J Andrews12.
Abstract
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.Entities:
Mesh:
Substances:
Year: 2016 PMID: 27617677 PMCID: PMC5689480 DOI: 10.1016/j.cels.2016.08.008
Source DB: PubMed Journal: Cell Syst ISSN: 2405-4712 Impact factor: 10.304