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Hum Mol Genet. 2018 Sep 1;27(17):3099-3112. doi: 10.1093/hmg/ddy217.

A collective diabetes cross in combination with a computational framework to dissect the genetics of human obesity and Type 2 diabetes.

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Department of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal D-14558, Germany.
German Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.
Medical Faculty, Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Düsseldorf D-40225, Germany.
Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig, Leipzig D-04303, Germany.
Chair for Molecular Animal Breeding and Biotechnology, Gene Center.
Department of Veterinary Sciences, Center for Innovative Medical Models (CiMM), LMU Munich, D-81377 Munich, Germany.
Institute for Diabetes and Obesity, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg D-85764, Germany.
Division of Metabolic Diseases, Department of Medicine, Technische Universität München, Munich D-80333, Germany.
Department of Medicine, University of Leipzig, Leipzig D-04103, Germany.
Institute of Nutritional Science, University of Potsdam, Nuthetal D-14558, Germany.


To explore the genetic determinants of obesity and Type 2 diabetes (T2D), the German Center for Diabetes Research (DZD) conducted crossbreedings of the obese and diabetes-prone New Zealand Obese mouse strain with four different lean strains (B6, DBA, C3H, 129P2) that vary in their susceptibility to develop T2D. Genome-wide linkage analyses localized more than 290 quantitative trait loci (QTL) for obesity, 190 QTL for diabetes-related traits and 100 QTL for plasma metabolites in the outcross populations. A computational framework was developed that allowed to refine critical regions and to nominate a small number of candidate genes by integrating reciprocal haplotype mapping and transcriptome data. The efficiency of the complex procedure was demonstrated for one obesity QTL. The genomic interval of 35 Mb with 502 annotated candidate genes was narrowed down to six candidates. Accordingly, congenic mice retained the obesity phenotype owing to an interval that contains three of the six candidate genes. Among these the phospholipase PLA2G4A exhibited an elevated expression in adipose tissue of obese human subjects and is therefore a critical regulator of the obesity locus. Together, our broad and complex approach demonstrates that combined- and comparative-cross analysis exhibits improved mapping resolution and represents a valid tool for the identification of disease genes.

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