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Cell. 2011 Apr 29;145(3):470-82. doi: 10.1016/j.cell.2011.03.037.

A high-resolution C. elegans essential gene network based on phenotypic profiling of a complex tissue.

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1
Ludwig Institute for Cancer Research, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, 92093, USA.

Abstract

High-content screening for gene profiling has generally been limited to single cells. Here, we explore an alternative approach-profiling gene function by analyzing effects of gene knockdowns on the architecture of a complex tissue in a multicellular organism. We profile 554 essential C. elegans genes by imaging gonad architecture and scoring 94 phenotypic features. To generate a reference for evaluating methods for network construction, genes were manually partitioned into 102 phenotypic classes, predicting functions for uncharacterized genes across diverse cellular processes. Using this classification as a benchmark, we developed a robust computational method for constructing gene networks from high-content profiles based on a network context-dependent measure that ranks the significance of links between genes. Our analysis reveals that multi-parametric profiling in a complex tissue yields functional maps with a resolution similar to genetic interaction-based profiling in unicellular eukaryotes-pinpointing subunits of macromolecular complexes and components functioning in common cellular processes.

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PMID:
21529718
PMCID:
PMC3086541
DOI:
10.1016/j.cell.2011.03.037
[Indexed for MEDLINE]
Free PMC Article

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