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  • 1
    Online Resource
    Online Resource
    Phenotypic overlap in the contribution of individual genes to CNV pathogenicity revealed by cross-species computational analysis of single-gene mutations in humans, mice and zebrafish
    The Company of Biologists ; 2013
    In:  Disease Models & Mechanisms
    Details
    In: Disease Models & Mechanisms, The Company of Biologists
    Abstract: Numerous disease syndromes are associated with regions of copy number variation (CNV) in the human genome and, in most cases, the pathogenicity of the CNV is thought to be related to altered dosage of the genes contained within the affected segment. However, establishing the contribution of individual genes to the overall pathogenicity of CNV syndromes is difficult and often relies on the identification of potential candidates through manual searches of the literature and online resources. We describe here the development of a computational framework to comprehensively search phenotypic information from model organisms and single-gene human hereditary disorders, and thus speed the interpretation of the complex phenotypes of CNV disorders. There are currently more than 5000 human genes about which nothing is known phenotypically but for which detailed phenotypic information for the mouse and/or zebrafish orthologs is available. Here, we present an ontology-based approach to identify similarities between human disease manifestations and the mutational phenotypes in characterized model organism genes; this approach can therefore be used even in cases where there is little or no information about the function of the human genes. We applied this algorithm to detect candidate genes for 27 recurrent CNV disorders and identified 802 gene-phenotype associations, approximately half of which involved genes that were previously reported to be associated with the individual phenotypic features and half of which were novel candidates. A total of 431 associations were made solely on the basis of model organism phenotype data. Additionally, we observed a striking, statistically significant tendency for individual disease phenotypes to be associated with multiple genes located within a single CNV region, a phenomenon that we denote as pheno-clustering. Many of the clusters also display statistically significant similarities in protein function or vicinity within the protein-protein interaction network. Our results provide a basis for understanding previously un-interpretable genotype-phenotype correlations in pathogenic CNVs and for mobilizing the large amount of model organism phenotype data to provide insights into human genetic disorders.
    Type of Medium: Online Resource
    ISSN: 1754-8411 , 1754-8403
    URL: Article
    DOI: 10.1242/dmm.010322
    Language: English
    Publisher: The Company of Biologists
    Publication Date: 2013
    detail.hit.zdb_id: 2451104-3
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  • 2
    Online Resource
    Online Resource
    Phenotype ontologies for mouse and man: bridging the semantic gap
    The Company of Biologists ; 2010
    In:  Disease Models & Mechanisms Vol. 3, No. 5-6 ( 2010-04-28), p. 281-289
    Details
    In: Disease Models & Mechanisms, The Company of Biologists, Vol. 3, No. 5-6 ( 2010-04-28), p. 281-289
    Abstract: A major challenge of the post-genomic era is coding phenotype data from humans and model organisms such as the mouse, to permit the meaningful translation of phenotype descriptions between species. This ability is essential if we are to facilitate phenotype-driven gene function discovery and empower comparative pathobiology. Here, we review the current state of the art for phenotype and disease description in mice and humans, and discuss ways in which the semantic gap between coding systems might be bridged to facilitate the discovery and exploitation of new mouse models of human diseases.
    Type of Medium: Online Resource
    ISSN: 1754-8411 , 1754-8403
    URL: Article
    DOI: 10.1242/dmm.002790
    Language: English
    Publisher: The Company of Biologists
    Publication Date: 2010
    detail.hit.zdb_id: 2451104-3
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  • 3
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    Online Resource
    Exploring the elephant: histopathology in high-throughput phenotyping of mutant mice
    The Company of Biologists ; 2012
    In:  Disease Models & Mechanisms Vol. 5, No. 1 ( 2012-01-01), p. 19-25
    Details
    In: Disease Models & Mechanisms, The Company of Biologists, Vol. 5, No. 1 ( 2012-01-01), p. 19-25
    Abstract: Recent advances in gene knockout techniques and the in vivo analysis of mutant mice, together with the advent of large-scale projects for systematic mouse mutagenesis and genome-wide phenotyping, have allowed the creation of platforms for the most complete and systematic analysis of gene function ever undertaken in a vertebrate. The development of high-throughput phenotyping pipelines for these and other large-scale projects allows investigators to search and integrate large amounts of directly comparable phenotype data from many mutants, on a genomic scale, to help develop and test new hypotheses about the origins of disease and the normal functions of genes in the organism. Histopathology has a venerable history in the understanding of the pathobiology of human and animal disease, and presents complementary advantages and challenges to in vivo phenotyping. In this review, we present evidence for the unique contribution that histopathology can make to a large-scale phenotyping effort, using examples from past and current programmes at Lexicon Pharmaceuticals and The Jackson Laboratory, and critically assess the role of histopathology analysis in high-throughput phenotyping pipelines.
    Type of Medium: Online Resource
    ISSN: 1754-8411 , 1754-8403
    URL: Article
    DOI: 10.1242/dmm.008334
    Language: English
    Publisher: The Company of Biologists
    Publication Date: 2012
    detail.hit.zdb_id: 2451104-3
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