International Mammalian Genome Society

The 15th International Mouse Genome Conference (2001)

Table of Contents * Complex Genetics * Developmental Genetics * Gene Annotation * Gene Discovery * Genome Sequencing * Functional Genomics * Mutagenesis * Presentations * Verne Chapman Memorial Lecture

POSTER 6 - BODY WEIGHT, FAT CONTENT, AND SERUM PROTEIN CONCENTRATIONS ARE DETERMINED BY A COMPLEX WEB OF INTERACTING GENES

Dr Gudrun A Brockmann
Research Institute for the Biology of Farm Animals
Wilhelm-Stahl-Allee 2
Dummerstorf 18196 Germany

Co-Authors: 2) Kratzsch J, 3) Haley S, 1) Renne U, 1) Karle S, 1) Schwerin M
Research Institute for the Biology of Farm Animals, 2)University of Leipzig, Departments of Clinical Chemistry and Pathobiochemistry, 3)Roslin Institute

Genes influencing body composition as well as serum concentrations of leptin, insulin, and IGF-I were mapped in an intercross of the extreme high growth mouse line DU6i and the inbred line DBA/2. The body weight in the selected line DU6i is 3.7-fold and the relative fat content is 2-fold increased compared with DBA/2 mice. QTL with major gene effects for body weight, obesity, and muscle weight were found on eight chromosomes, the net effects of all detected QTLs explained 35%, 34%, and 28% of the phenotypic variance in the F2 population, respectively. Loci influencing leptin, insulin, and IGF-I serum concentrations were identified on three chromosomes, together, these loci accounted for 25%, 9%, and 21% of the phenotypic F2 variance, respectively. For the examination of interaction between QTLs the model included the effects of sex, subfamily, parity, pupsize, the single effects of the QTL identified for the specific trait at two selected loci, and the interaction between these loci. The interaction analyses provided evidence for epistasis and pleiotropy. The net effects of identified QTLs, epistasis, and pleiotropy accounted for about two thirds of the phenotypic variance of body weight, fat accumulation, and serum proteins. These results emphasize that the consideration of QTL interaction effects may significantly contribute to more efficient utilization of QTL information in the search for underlying genes.