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| Item Type: | Article |
|---|---|
| Title: | Identification of genetic elements in metabolism by high-throughput mouse phenotyping |
| Creators Name: | Rozman, J. and Rathkolb, B. and Oestereicher, M.A. and Schütt, C. and Ravindranath, A.C. and Leuchtenberger, S. and Sharma, S. and Kistler, M. and Willershäuser, M. and Brommage, R. and Meehan, T.F. and Mason, J. and Haselimashhadi, H. and Hough, T. and Mallon, A.M. and Wells, S. and Santos, L. and Lelliott, C.J. and White, J.K. and Sorg, T. and Champy, M.F. and Bower, L.R. and Reynolds, C. L. and Flenniken, A.M. and Murray, St.A. and Nutter, L.M.J. and Svenson, K.L. and West, D. and Tocchini-Valentini, G.P. and Beaudet, A.L. and Bosch, F. and Braun, R.B. and Dobbie, M.S. and Gao, X. and Herault, Y. and Moshiri, A. and Moore, B.A. and Kent Lloyd, K.C. and McKerlie, C. and Masuya, H. and Tanaka, N. and Flicek, P. and Parkinson, H.E. and Sedlacek, R. and Seong, J.K. and Wang, C.K.L. and Moore, M. and Brown, S.D. and Tschöp, M.H. and Wurst, W. and Klingenspor, M. and Wolf, E. and Beckers, J. and Machicao, F. and Peter, A. and Staiger, H. and Häring, H.U. and Grallert, H. and Campillos, M. and Maier, H. and Fuchs, H. and Gailus-Durner, V. and Werner, T. and Hrabe de Angelis, M. |
| 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. |
| Keywords: | Area Under Curve, Basal Metabolism, Blood Glucose, Body Weight, Type 2, Diabetes Mellitus, Gene Regulatory Networks, Genome-Wide Association Study, High-Throughput Screening Assays, Knockout, Mice, Metabolic Diseases, Obesity, Oxygen Consumption, Triglycerides, Phenotype, Animals, Mice |
| Source: | Nature Communications |
| ISSN: | 2041-1723 |
| Publisher: | Nature Publishing Group |
| Volume: | 9 |
| Number: | 1 |
| Page Range: | 288 |
| Date: | 18 January 2018 |
| Additional Information: | Ralf Kühn is a member of the IMPC Consortium. |
| Official Publication: | https://doi.org/10.1038/s41467-017-01995-2 |
| PubMed: | View item in PubMed |
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