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Publication
Identification of genetic elements in metabolism by high-throughput mouse
phenotyping.
Authors Rozman J, Rathkolb B, Oestereicher MA, Schütt C, Ravindranath AC, Leuchtenberger
S, Sharma S, Kistler M, Willershäuser M, Brommage R, Meehan TF, Mason J,
Haselimashhadi H, Hough T, Mallon AM, Wells S, Santos L, Lelliott CJ, White JK,
Sorg T, Champy MF, Bower LR, Reynolds CL, Flenniken AM, Murray SA, Nutter LMJ,
Svenson KL, West D, Tocchini-Valentini GP, Beaudet AL, Bosch F, Braun RB, Dobbie
MS, Gao X, Herault Y, Moshiri A, Moore BA, Kent Lloyd KC, McKerlie C, Masuya H,
Tanaka N, Flicek P, Parkin
Submitted By Submitted Externally on 5/25/2018
Status Published
Journal Nature communications
Year 2018
Date Published 1/1/2018
Volume : Pages 9 : 288
PubMed Reference 29348434
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.




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