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.
Pubmed ID: 21529718 RIS Download
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Software tool for automated microscope acquisition, device control, and image analysis. Used for integrating dissimilar fluorescent microscope hardware and peripherals into a single custom workstation, while providing all the tools needed to perform analysis of acquired images. Offers user friendly application modules for analysis such as cell signaling, cell counting, and protein expression.
View all literature mentionsSoftware platform for complex network analysis and visualization. Used for visualization of molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.
View all literature mentionsIt provides access to results from RNAi interference studies in C. elegans, including images, movies, phenotypes, and graphical maps. RNAiDB contains all published RNAi experiments in C. elegans that have been deposited in WormBase, including data from the literature and published large-scale RNAi studies. RNAi to gene mappings for all experiments have been re-analyzed using ePCR and/or a sliding n-mer window method to identify all genes in different genomic locations that may potentially be inhibited by each experiment. Gene maps showing canonical and putative alternate mappings are displayed graphically on RNAi Experiment and Gene/ORF card pages.
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