NIH Knockout Mouse Phenotyping Program (KOMP2) and IMPC: Database to Discover New Roles of Genes in Cardiovascular Physiology and Disease
The collaborative goal of NIH Knockout Mouse Phenotyping Program (KOMP2) and International Knockout Mouse Phenotyping Consortium (IMPC) is to discover functional insight for every gene in the mouse genome by 2021, by generating and systematically phenotyping approximately 20,000 unique knockout (KO)...
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Veröffentlicht in: | Physiological genomics 2019-11 |
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Sprache: | eng |
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Zusammenfassung: | The collaborative goal of NIH Knockout Mouse Phenotyping Program (KOMP2) and International Knockout Mouse Phenotyping Consortium (IMPC) is to discover functional insight for every gene in the mouse genome by 2021, by generating and systematically phenotyping approximately 20,000 unique knockout (KO) mouse strains. The purpose of the present study is to introduce the KOMP2/IMPC program and its publicly-accessible gene-phenotype database to the research community and to specifically illustrate its utility for the identification of novel gene candidates in cardiovascular (CV) disease. In this report, we have focused on single gene deletions found associated with CV phenotype as part of the KOMP2/IMPC phenotyping of broad physiological domains in more than 5,500 single gene KO mice. Among the 694 single genes found to result in a CV phenotype, we identified about one third (36%, n=248) that had not been previously associated with the CV system. We also searched the remainder of more than 5,500 genes that had not been previously associated with the CV system. We used the results of gene-disease relationship analysis from Medline sentences with an algorithm called Ensemble Biclustering for Classification (EBC), which uncovers relationships between biomedical entities. In addition, we studied their interactions in protein-protein interaction networks. These genes may present opportunities for new CV research and may provide new targets for therapeutic intervention for various CV diseases. |
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ISSN: | 1531-2267 |
DOI: | 10.1152/physiolgenomics.00011.2019 |