TY - JOUR
T1 - Noise Genetics
T2 - Inferring Protein Function by Correlating Phenotype with Protein Levels and Localization in Individual Human Cells
AU - Farkash-Amar, Shlomit
AU - Zimmer, Anat
AU - Eden, Eran
AU - Cohen, Ariel
AU - Geva Zatorsky, Zatorsky, Naama
AU - Cohen, Lydia
AU - Milo, Ron
AU - Sigal, Alex
AU - Danon, Tamar
AU - Alon, Uri
N1 - European Research Council under the European Union's Seventh Framework Programme (FP7)/ERC [249919]; European Union's Seventh Framework Programme (FP7) [258068]; EU-FP7-Systems Microscopy NoE; Human Frontiers Science ProgramThe research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013)/ERC Grant agreement no 249919; the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement no258068; EU-FP7-Systems Microscopy NoE; and the Human Frontiers Science Program. UA is the incumbent of the Abisch-Frenkel Professorial Chair. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
PY - 2014/3
Y1 - 2014/3
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84897399093&partnerID=8YFLogxK
U2 - 10.1371/journal.pgen.1004176
DO - 10.1371/journal.pgen.1004176
M3 - مقالة
C2 - 24603725
SN - 1553-7390
VL - 10
JO - PLoS Genetics
JF - PLoS Genetics
IS - 3
M1 - e1004176
ER -
