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Mol Biol Cell. 2016 Apr 15;27(8):1397-407. doi: 10.1091/mbc.E15-07-0467. Epub 2016 Feb 24.

A genetic interaction map of cell cycle regulators.

Author information

1
Division of Signaling and Functional Genomics, German Cancer Research Center, and Department of Cell and Molecular Biology, Heidelberg University, 69120 Heidelberg, Germany.
2
Genome Biology Unit, EMBL, 69118 Heidelberg, Germany Computational Genome Biology, German Cancer Research Center, 69120 Heidelberg, Germany.
3
Genome Biology Unit, EMBL, 69118 Heidelberg, Germany.
4
Division of Signaling and Functional Genomics, German Cancer Research Center, and Department of Cell and Molecular Biology, Heidelberg University, 69120 Heidelberg, Germany m.boutros@dkfz.de.

Abstract

Cell-based RNA interference (RNAi) is a powerful approach to screen for modulators of many cellular processes. However, resulting candidate gene lists from cell-based assays comprise diverse effectors, both direct and indirect, and further dissecting their functions can be challenging. Here we screened a genome-wide RNAi library for modulators of mitosis and cytokinesis inDrosophilaS2 cells. The screen identified many previously known genes as well as modulators that have previously not been connected to cell cycle control. We then characterized ∼300 candidate modifiers further by genetic interaction analysis using double RNAi and a multiparametric, imaging-based assay. We found that analyzing cell cycle-relevant phenotypes increased the sensitivity for associating novel gene function. Genetic interaction maps based on mitotic index and nuclear size grouped candidates into known regulatory complexes of mitosis or cytokinesis, respectively, and predicted previously uncharacterized components of known processes. For example, we confirmed a role for theDrosophilaCCR4 mRNA processing complex componentl(2)NC136during the mitotic exit. Our results show that the combination of genome-scale RNAi screening and genetic interaction analysis using process-directed phenotypes provides a powerful two-step approach to assigning components to specific pathways and complexes.

PMID:
26912791
PMCID:
PMC4831891
DOI:
10.1091/mbc.E15-07-0467
[Indexed for MEDLINE]
Free PMC Article

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