Original Article

International Journal of Obesity (2009) 33, 89–95; doi:10.1038/ijo.2008.215; published online 4 November 2008

Genetic influences on growth and body composition in mice: multilocus interactions

G A Ankra-Badu1, D Pomp2,3, D Shriner1, D B Allison1,4 and N Yi1,4

  1. 1Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, AL, USA
  2. 2Department of Nutrition, University of North Carolina, Chapel Hill, NC, USA
  3. 3Department of Cell and Molecular Physiology, University of North Carolina, Chapel Hill, NC, USA
  4. 4Clinical Nutrition Research Center, University of Alabama at Birmingham, Birmingham, AL, USA

Correspondence: Dr N Yi, Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, AL 35294, USA. E-mail: nyi@ms.soph.uab.edu

Received 27 November 2007; Revised 4 October 2008; Accepted 6 October 2008; Published online 4 November 2008.

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Abstract

Background:

 

The genetic architecture of body weight and body composition is complex because these traits are normally influenced by multiple genes and their interactions, even after controlling for the environment. Bayesian methodology provides an efficient way of estimating these interactions.

Subjects and measurements:

 

We used Bayesian model selection techniques to simultaneously estimate the main effects, epistasis and gene–sex interactions on age-related body weight (at 3, 6 and 10 weeks, denoted as WT3wk, WT6wk and WT10wk) and body composition (organ weights and fat-related traits) in an F2 sample obtained from a cross between high-growth (M16i) mice and low-growth (L6) mice.

Results:

 

We observed epistatic and main-effect quantitative trait loci (QTL) that controlled both body weight and body composition. Epistatic effects were generally more significant for WT6wk than WT10wk. Chromosomes 5 and 13 interacted strongly to control body weight at 3 weeks. A pleiotropic QTL on chromosome 2 was associated with body weight and some body composition phenotypes. Testis weight was regulated by a QTL on chromosome 13 with a significantly large main effect (2logeBF approx15).

Conclusion:

 

By analyzing epistatic interactions, we detected QTL not found in a previous analysis of this mouse population. Hence, the detection of gene–gene interactions may provide new information about the genetic architecture of complex obesity-related traits and may lead to the detection of additional obesity genes.

Keywords:

Bayesian methods, body weight, epistasis, quantitative trait loci

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