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

Rebecca A. Green, Huey Ling Kao, Anjon Audhya, Swathi Arur, Jonathan R. Mayers, Heidi N. Fridolfsson, Monty Schulman, Siegfried Schloissnig, Sherry Niessen, Kimberley Laband, Shaohe Wang, Daniel A. Starr, Anthony A. Hyman, Tim Schedl, Arshad Desai, Fabio Piano, Kristin C. Gunsalus, Karen Oegema

Research output: Contribution to journalArticlepeer-review

131 Scopus citations

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. PaperFlick:

Original languageEnglish
Pages (from-to)470-482
Number of pages13
JournalCell
Volume145
Issue number3
DOIs
StatePublished - Apr 29 2011

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