Identification of genetic elements in metabolism by high-throughput mouse phenotyping
| dc.contributor.author | Rozman, Jan | |
| dc.contributor.author | Rathkolb, Birgit | |
| dc.contributor.author | Oestereicher, Manuela A | |
| dc.contributor.author | Schutt, Christine | |
| dc.contributor.author | Ravindranath, Aakash Chavan | |
| dc.contributor.author | Leuchtenberger, Stefanie | |
| dc.contributor.author | Sharma, Sapna | |
| dc.contributor.author | Kistler, Martin | |
| dc.contributor.author | Willershauser, Monja | |
| dc.contributor.author | Brommage, Robert | |
| dc.contributor.author | Meehan, Terrence F | |
| dc.contributor.author | Dobbie, Michael | |
| dc.date.accessioned | 2019-04-21T11:08:02Z | |
| dc.date.available | 2019-04-21T11:08:02Z | |
| dc.date.issued | 2018 | |
| dc.date.updated | 2019-03-12T07:33:49Z | |
| dc.description.abstract | Metabolic diseases are a worldwide problem but the underlying genetic factors and their relevance to metabolic disease remain incompletely understood. Genome-wide research is needed to characterize so-far unannotated mammalian metabolic genes. Here, we generate and analyze metabolic phenotypic data of 2016 knockout mouse strains under the aegis of the International Mouse Phenotyping Consortium (IMPC) and find 974 gene knockouts with strong metabolic phenotypes. 429 of those had no previous link to metabolism and 51 genes remain functionally completely unannotated. We compared human orthologues of these uncharacterized genes in five GWAS consortia and indeed 23 candidate genes are associated with metabolic disease. We further identify common regulatory elements in promoters of candidate genes. As each regulatory element is composed of several transcription factor binding sites, our data reveal an extensive metabolic phenotype-associated network of co-regulated genes. Our systematic mouse phenotype analysis thus paves the way for full functional annotation of the genome. | en_AU |
| dc.format.mimetype | application/pdf | en_AU |
| dc.identifier.issn | 2041-1723 | en_AU |
| dc.identifier.uri | http://hdl.handle.net/1885/160571 | |
| dc.language.iso | en_AU | en_AU |
| dc.publisher | Macmillan Publishers Ltd | en_AU |
| dc.rights | The Author/s | en_AU |
| dc.rights.license | This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. | |
| dc.rights.uri | http://creativecommons.org/ licenses/by/4.0/ | |
| dc.source | Nature Communications | en_AU |
| dc.title | Identification of genetic elements in metabolism by high-throughput mouse phenotyping | en_AU |
| dc.type | Journal article | en_AU |
| dcterms.accessRights | Open Access | en_AU |
| local.contributor.affiliation | Rozman, Jan, German Research Center for Environmental Health | en_AU |
| local.contributor.affiliation | Rathkolb, Birgit, German Research Center for Environmental Health | en_AU |
| local.contributor.affiliation | Oestereicher, Manuela A, German Research Center for Environmental Health | en_AU |
| local.contributor.affiliation | Schutt, Christine, German Research Center for Environmental Health | en_AU |
| local.contributor.affiliation | Ravindranath, Aakash Chavan, German Center for Diabetes Research (DZD) | en_AU |
| local.contributor.affiliation | Leuchtenberger, Stefanie, German Research Center for Environmental Health | en_AU |
| local.contributor.affiliation | Sharma, Sapna, German Center for Diabetes Research (DZD) | en_AU |
| local.contributor.affiliation | Kistler, Martin, German Research Center for Environmental Health | en_AU |
| local.contributor.affiliation | Willershauser, Monja, Technical University of Munich | en_AU |
| local.contributor.affiliation | Brommage, Robert, German Research Center for Environmental Health | en_AU |
| local.contributor.affiliation | Meehan, Terrence F, European Bioinformatics Institute | en_AU |
| local.contributor.affiliation | Dobbie, Michael, College of Health and Medicine, ANU | en_AU |
| local.contributor.authoruid | Dobbie, Michael, u4384816 | en_AU |
| local.description.notes | Imported from ARIES | en_AU |
| local.identifier.absfor | 060408 - Genomics | en_AU |
| local.identifier.absfor | 110107 - Metabolic Medicine | en_AU |
| local.identifier.absseo | 970111 - Expanding Knowledge in the Medical and Health Sciences | en_AU |
| local.identifier.absseo | 970106 - Expanding Knowledge in the Biological Sciences | en_AU |
| local.identifier.ariespublication | u4485658xPUB2311 | en_AU |
| local.identifier.citationvolume | 9 | en_AU |
| local.identifier.doi | 10.1038/s41467-017-01995-2 | en_AU |
| local.identifier.thomsonID | 000422745800023 | |
| local.type.status | Published Version | en_AU |
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