International Mammalian Genome Society

17th International Mouse Genome Conference

9-12 November 2003, Braunschweig, Germany


POSTER 176 - COMBINATION OF DATA FROM QTL MAPPING AND GENE EXPRESSION ANALYSES FOR THE SELECTION OF POSITIONAL CANDIDATE GENES FOR GROWTH AND OBESITY

Neuschl C
Institute for Cell Biology, University of Rostock

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

Obesity is a grave medical disease affecting approximately 8% of the adult world population. In most cases, obesity is a polygenic trait in humans as well as in farm animals. Therefore, mouse lines selected for obesity related traits are excellent models to identify single genetic factors contributing to the selection response. The mouse lines DU6 and its inbred derivate DU6i have been used repeatedly to map quantitative trait loci (QTLs) influencing growth and fat deposition. The objective of our research was the selection of potential candidate genes underlying QTLs for growth and obesity as complex traits in the high growth selected mouse model. The goal of this study was the identification of differentially expressed genes in the hypothalamus of selected and unselected mice by using gene chip microarrays. We mapped differentially expressed genes and verified the different expression of selected positional candidate genes using semi-quantitative real time PCR. Finally, we searched for DNA-variants in selected genes as potential reasons for the observed differences in the gene expression. We have selected and characterized 11 candidate genes for growth and high body weight in the hypothalamus of DU6i vs. DUKsi and DBA/2. The differential gene expression of 5 genes was verified. We comparatively sequenced the genomic DNA of fat and lean mice. Identified DNA-variants of the selected genes could contribute to the observed differences in gene expression and, thus, to the fat phenotype.


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