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  • Identification of genetic elements in metabolism by high-throughput mouse phenotyping.

Identification of genetic elements in metabolism by high-throughput mouse phenotyping.

Nature communications (2018-01-20)
Jan Rozman, Birgit Rathkolb, Manuela A Oestereicher, Christine Schütt, Aakash Chavan Ravindranath, Stefanie Leuchtenberger, Sapna Sharma, Martin Kistler, Monja Willershäuser, Robert Brommage, Terrence F Meehan, Jeremy Mason, Hamed Haselimashhadi, Tertius Hough, Ann-Marie Mallon, Sara Wells, Luis Santos, Christopher J Lelliott, Jacqueline K White, Tania Sorg, Marie-France Champy, Lynette R Bower, Corey L Reynolds, Ann M Flenniken, Stephen A Murray, Lauryl M J Nutter, Karen L Svenson, David West, Glauco P Tocchini-Valentini, Arthur L Beaudet, Fatima Bosch, Robert B Braun, Michael S Dobbie, Xiang Gao, Yann Herault, Ala Moshiri, Bret A Moore, K C Kent Lloyd, Colin McKerlie, Hiroshi Masuya, Nobuhiko Tanaka, Paul Flicek, Helen E Parkinson, Radislav Sedlacek, Je Kyung Seong, Chi-Kuang Leo Wang, Mark Moore, Steve D Brown, Matthias H Tschöp, Wolfgang Wurst, Martin Klingenspor, Eckhard Wolf, Johannes Beckers, Fausto Machicao, Andreas Peter, Harald Staiger, Hans-Ulrich Häring, Harald Grallert, Monica Campillos, Holger Maier, Helmut Fuchs, Valerie Gailus-Durner, Thomas Werner, Martin Hrabe de Angelis
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.

MATERIALS
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Supelco
3,5,6-Trichloro-2-pyridinol, PESTANAL®, analytical standard