TY - JOUR
T1 - Identification of genetic elements in metabolism by high-throughput mouse phenotyping
AU - IMPC Consortium
AU - Rozman, Jan
AU - Rathkolb, Birgit
AU - Oestereicher, Manuela A
AU - Schütt, Christine
AU - Ravindranath, Aakash Chavan
AU - Leuchtenberger, Stefanie
AU - Sharma, Sapna
AU - Kistler, Martin
AU - Willershäuser, Monja
AU - Brommage, Robert
AU - Meehan, Terrence F
AU - Mason, Jeremy
AU - Haselimashhadi, Hamed
AU - Hough, Tertius
AU - Mallon, Ann-Marie
AU - Wells, Sara
AU - Santos, Luis
AU - Lelliott, Christopher J
AU - White, Jacqueline K
AU - Sorg, Tania
AU - Champy, Marie-France
AU - Bower, Lynette R
AU - Reynolds, Corey L
AU - Flenniken, Ann M
AU - Murray, Stephen A
AU - Nutter, Lauryl M J
AU - Svenson, Karen L
AU - West, David
AU - Tocchini-Valentini, Glauco P
AU - Beaudet, Arthur L
AU - Bosch, Fatima
AU - Braun, Robert B
AU - Dobbie, Michael S
AU - Gao, Xiang
AU - Herault, Yann
AU - Moshiri, Ala
AU - Moore, Bret A
AU - Kent Lloyd, K C
AU - McKerlie, Colin
AU - Masuya, Hiroshi
AU - Tanaka, Nobuhiko
AU - Flicek, Paul
AU - Parkinson, Helen E
AU - Sedlacek, Radislav
AU - Seong, Je Kyung
AU - Wang, Chi-Kuang Leo
AU - Moore, Mark
AU - Brown, Steve D
AU - Tschöp, Matthias H
AU - Wurst, Wolfgang
PY - 2018/1/18
Y1 - 2018/1/18
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85040788526&partnerID=8YFLogxK
U2 - 10.1038/s41467-017-01995-2
DO - 10.1038/s41467-017-01995-2
M3 - Article
C2 - 29348434
SN - 2041-1723
VL - 9
SP - 1
EP - 16
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 288
ER -
