Architecture of energy balance traits in emerging lines of the Collaborative Cross

Author:

Mathes Wendy Foulds1,Aylor David L.1,Miller Darla R.1,Churchill Gary A.2,Chesler Elissa J.2,de Villena Fernando Pardo-Manuel1,Threadgill David W.3,Pomp Daniel14

Affiliation:

1. Department of Genetics, University of North Carolina, Chapel Hill, North Carolina;

2. The Center for Genome Dynamics, The Jackson Laboratory, Bar Harbor, Maine;

3. Department of Genetics, North Carolina State University, Raleigh; and

4. Departments of Nutrition, Cell and Molecular Physiology, University of North Carolina, Chapel Hill, North Carolina

Abstract

The potential utility of the Collaborative Cross (CC) mouse resource was evaluated to better understand complex traits related to energy balance. A primary focus was to examine if genetic diversity in emerging CC lines (pre-CC) would translate into equivalent phenotypic diversity. Second, we mapped quantitative trait loci (QTL) for 15 metabolism- and exercise-related phenotypes in this population. We evaluated metabolic and voluntary exercise traits in 176 pre-CC lines, revealing phenotypic variation often exceeding that seen across the eight founder strains from which the pre-CC was derived. Many phenotypic correlations existing within the founder strains were no longer significant in the pre-CC population, potentially representing reduced linkage disequilibrium (LD) of regions harboring multiple genes with effects on energy balance or disruption of genetic structure of extant inbred strains with substantial shared ancestry. QTL mapping revealed five significant and eight suggestive QTL for body weight (Chr 4, 7.54 Mb; CI 3.32–10.34 Mb; Bwq14), body composition, wheel running (Chr 16, 33.2 Mb; CI 32.5–38.3 Mb), body weight change in response to exercise (1: Chr 6, 77.7Mb; CI 72.2–83.4 Mb and 2: Chr 6, 42.8 Mb; CI 39.4–48.1 Mb), and food intake during exercise (Chr 12, 85.1 Mb; CI 82.9–89.0 Mb). Some QTL overlapped with previously mapped QTL for similar traits, whereas other QTL appear to represent novel loci. These results suggest that the CC will be a powerful, high-precision tool for examining the genetic architecture of complex traits such as those involved in regulation of energy balance.

Publisher

American Physiological Society

Subject

Physiology (medical),Physiology,Endocrinology, Diabetes and Metabolism

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