International Mammalian Genome Society

17th International Mouse Genome Conference

9-12 November 2003, Braunschweig, Germany

Plenary Presentations * Oral Presentations *
Poster Presentations: Behavioural Genetics and Genomics * Development and Stem Cells * Functional Genome Analysis * Mouse Models of Human Disease * Mouse System Biology Bioinformatics * Multigenic and Multifactorial Trait Analysis * Nutrition and Metabolic Disease * Phenotyping Methods Imaging * The Genetics and Genomics of Infectious Disease *
Verne Chapman Memorial Lecture * Table of Contents * Sponsor/Exhibitor List * Awards * Photographs

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POSTER 157 - SELECTION OF POSITIONAL CANDIDATE GENES FOR GROWTH AND OBESITY BY DIFFERENTIAL GENE EXPRESSION IN ADIPOSE TISSUE

Aksu S
Research Institute for the Biology of Farm Animals Dummerstorf

Co-Authors: 2) Neuschl C, 1) Renne U, 3) Koczan D, 3) Thiesen H J, 1) Brockmann GA
Institutions: 1) Research Institute for the Biology of Farm Animals Dummerstorf, 2) Institute of Cell Biology, University of Rostock, 3) Institute for Immunology, University of Rostock

Obesity is a major health risk factor for several kinds of serious diseases and metabolic disorders. In this study, we used DU6i and DU6 mouse lines, which have been selected for high body weight. DU6 mice have the highest body weight known worldwide. DU6i is an inbred derivate of DU6. It is twice as heavy and three times as fat as unselected control mice. In addition, the selected mice are characterized by highly increased serum concentrations of leptin, insulin and IGF-1. QTL mapping analyses in crosses between selected and non-selected control lines showed the presence of different QTLs that affect body weight, obesity, and muscle weight, as well as serum concentrations of biological molecules and hormones on several different chromosomes. Microarray expression analyses showed, that 88 genes are differentially expressed in fat tissues between the selected and non-selected mouse lines. 14 out of 88 genes are located in chromosomal regions affecting growth and fatness. They might be positional candidate genes for the observed QTL effects. We confirmed the data obtained from Microarray analyses for these 14 genes by semi-quantitative real-time PCR. Therefore, comparative sequencing of these genes will be performed to identify polymorphisms. The combination of QTL mapping and the analysis of gene expression helps to select positional candidate genes, which might be responsible for the identified QTL effects.