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      Large-scale functional RNAi screen in C. elegans identifies genes that regulate the dysfunction of mutant polyglutamine neurons

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          Abstract

          Background

          A central goal in Huntington's disease (HD) research is to identify and prioritize candidate targets for neuroprotective intervention, which requires genome-scale information on the modifiers of early-stage neuron injury in HD.

          Results

          Here, we performed a large-scale RNA interference screen in C. elegans strains that express N-terminal huntingtin (htt) in touch receptor neurons. These neurons control the response to light touch. Their function is strongly impaired by expanded polyglutamines (128Q) as shown by the nearly complete loss of touch response in adult animals, providing an in vivo model in which to manipulate the early phases of expanded-polyQ neurotoxicity. In total, 6034 genes were examined, revealing 662 gene inactivations that either reduce or aggravate defective touch response in 128Q animals. Several genes were previously implicated in HD or neurodegenerative disease, suggesting that this screen has effectively identified candidate targets for HD. Network-based analysis emphasized a subset of high-confidence modifier genes in pathways of interest in HD including metabolic, neurodevelopmental and pro-survival pathways. Finally, 49 modifiers of 128Q-neuron dysfunction that are dysregulated in the striatum of either R/2 or CHL2 HD mice, or both, were identified.

          Conclusions

          Collectively, these results highlight the relevance to HD pathogenesis, providing novel information on the potential therapeutic targets for neuroprotection in HD.

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          Most cited references34

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            Automatic clustering of orthologs and in-paralogs from pairwise species comparisons.

            Orthologs are genes in different species that originate from a single gene in the last common ancestor of these species. Such genes have often retained identical biological roles in the present-day organisms. It is hence important to identify orthologs for transferring functional information between genes in different organisms with a high degree of reliability. For example, orthologs of human proteins are often functionally characterized in model organisms. Unfortunately, orthology analysis between human and e.g. invertebrates is often complex because of large numbers of paralogs within protein families. Paralogs that predate the species split, which we call out-paralogs, can easily be confused with true orthologs. Paralogs that arose after the species split, which we call in-paralogs, however, are bona fide orthologs by definition. Orthologs and in-paralogs are typically detected with phylogenetic methods, but these are slow and difficult to automate. Automatic clustering methods based on two-way best genome-wide matches on the other hand, have so far not separated in-paralogs from out-paralogs effectively. We present a fully automatic method for finding orthologs and in-paralogs from two species. Ortholog clusters are seeded with a two-way best pairwise match, after which an algorithm for adding in-paralogs is applied. The method bypasses multiple alignments and phylogenetic trees, which can be slow and error-prone steps in classical ortholog detection. Still, it robustly detects complex orthologous relationships and assigns confidence values for both orthologs and in-paralogs. The program, called INPARANOID, was tested on all completely sequenced eukaryotic genomes. To assess the quality of INPARANOID results, ortholog clusters were generated from a dataset of worm and mammalian transmembrane proteins, and were compared to clusters derived by manual tree-based ortholog detection methods. This study led to the identification with a high degree of confidence of over a dozen novel worm-mammalian ortholog assignments that were previously undetected because of shortcomings of phylogenetic methods.A WWW server that allows searching for orthologs between human and several fully sequenced genomes is installed at http://www.cgb.ki.se/inparanoid/. This is the first comprehensive resource with orthologs of all fully sequenced eukaryotic genomes. Programs and tables of orthology assignments are available from the same location. Copyright 2001 Academic Press.
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              A map of the interactome network of the metazoan C. elegans.

              To initiate studies on how protein-protein interaction (or "interactome") networks relate to multicellular functions, we have mapped a large fraction of the Caenorhabditis elegans interactome network. Starting with a subset of metazoan-specific proteins, more than 4000 interactions were identified from high-throughput, yeast two-hybrid (HT=Y2H) screens. Independent coaffinity purification assays experimentally validated the overall quality of this Y2H data set. Together with already described Y2H interactions and interologs predicted in silico, the current version of the Worm Interactome (WI5) map contains approximately 5500 interactions. Topological and biological features of this interactome network, as well as its integration with phenome and transcriptome data sets, lead to numerous biological hypotheses.
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                Author and article information

                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central
                1471-2164
                2012
                13 March 2012
                : 13
                : 91
                Affiliations
                [1 ]INSERM, Unit 894, Laboratory of Neuronal Cell Biology and Pathology, 75014 Paris, France
                [2 ]University of Paris Descartes, EA 4059, 75014 Paris, France
                [3 ]Université de Montreal, CRCHUM Centre d'excellence en neuromique, Hôpital Notre-Dame, Montreal, QC,H2W 1T8 Canada
                [4 ]Mines ParisTech, CBIO, Fontainebleau, 75006 Paris, France
                [5 ]Curie Institute, Research Center, 75005 Paris, France
                [6 ]INSERM, Unit 900, Paris, 75005 France
                [7 ]Buck Institute, Novato, CA 94945, USA
                Article
                1471-2164-13-91
                10.1186/1471-2164-13-91
                3331833
                22413862
                47490470-4724-4318-8f10-0586928dace2
                Copyright ©2012 Lejeune et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 20 October 2011
                : 13 March 2012
                Categories
                Research Article

                Genetics
                Genetics

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