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A High-Resolution C. elegans Essential Gene Network Based on Phenotypic Profiling of a Complex Tissue ! t1 I I% Y" ~" x- v$ x* Y5 W% A5 Y( {4 @1 k I
High-content screening for gene profiling has generally been limited to single cells. Here, we explore an alternative approachprofiling 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 eukaryotespinpointing subunits of macromolecular complexes and components functioning in common cellular processes. ) l- X" l# {3 U) R$ }: x/ F 3 q1 a; P, X" C来源：(http://www.ebiotrade.com/)$ h/ o% G" p! ~3 i4 V' M( i