Noise genetics: inferring protein function by correlating phenotype with protein levels and localization in individual human cells.

• Main Authors: Shlomit Farkash-Amar, Anat Zimmer, Eran Eden, Ariel Cohen, Naama Geva-Zatorsky, Lydia Cohen, Ron Milo, Alex Sigal, Tamar Danon, Uri Alon
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2014-03-01
• Series: PLoS Genetics
• Online Access: http://europepmc.org/articles/PMC3945223?pdf=render

To understand gene function, genetic analysis uses large perturbations such as gene deletion, knockdown or over-expression. Large perturbations have drawbacks: they move the cell far from its normal working point, and can thus be masked by off-target effects or compensation by other genes. Here, we offer a complementary approach, called noise genetics. We use natural cell-cell variations in protein level and localization, and correlate them to the natural variations of the phenotype of the same cells. Observing these variations is made possible by recent advances in dynamic proteomics that allow measuring proteins over time in individual living cells. Using motility of human cancer cells as a model system, and time-lapse microscopy on 566 fluorescently tagged proteins, we found 74 candidate motility genes whose level or localization strongly correlate with motility in individual cells. We recovered 30 known motility genes, and validated several novel ones by mild knockdown experiments. Noise genetics can complement standard genetics for a variety of phenotypes.