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Bayesian analyses of multiple epistatic QTL models for body weight and body composition in mice

Published online by Cambridge University Press:  01 February 2006

NENGJUN YI
Affiliation:
Department of Biostatistics, Section on Statistical Genetics, University of Alabama, Birmingham, AL 35294, USA Clinical Nutrition Research Center, University of Alabama, Birmingham, AL 35294, USA
DENISE K. ZINNIEL
Affiliation:
Department of Veterinary and Biomedical Sciences, University of Nebraska, Lincoln, NE 68583, USA
KYOUNGMI KIM
Affiliation:
Department of Biostatistics, Section on Statistical Genetics, University of Alabama, Birmingham, AL 35294, USA
EUGENE J. EISEN
Affiliation:
Department of Animal Science, North Carolina State University, Raleigh, NC 27695, USA
ALFRED BARTOLUCCI
Affiliation:
Department of Biostatistics, Section on Statistical Genetics, University of Alabama, Birmingham, AL 35294, USA
DAVID B. ALLISON
Affiliation:
Department of Biostatistics, Section on Statistical Genetics, University of Alabama, Birmingham, AL 35294, USA Clinical Nutrition Research Center, University of Alabama, Birmingham, AL 35294, USA
DANIEL POMP
Affiliation:
Departments of Nutrition, Cell and Molecular Physiology, University of North Carolina, Chapel Hill, NC 27599, USA
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Abstract

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To comprehensively investigate the genetic architecture of growth and obesity, we performed Bayesian analyses of multiple epistatic quantitative trait locus (QTL) models for body weights at five ages (12 days, 3, 6, 9 and 12 weeks) and body composition traits (weights of two fat pads and five organs) in mice produced from a cross of the F1 between M16i (selected for rapid growth rate) and CAST/Ei (wild-derived strain of small and lean mice) back to M16i. Bayesian model selection revealed a temporally regulated network of multiple QTL for body weight, involving both strong main effects and epistatic effects. No QTL had strong support for both early and late growth, although overlapping combinations of main and epistatic effects were observed at adjacent ages. Most main effects and epistatic interactions had an opposite effect on early and late growth. The contribution of epistasis was more pronounced for body weights at older ages. Body composition traits were also influenced by an interacting network of multiple QTLs. Several main and epistatic effects were shared by the body composition and body weight traits, suggesting that pleiotropy plays an important role in growth and obesity.

Type
Research Article
Copyright
2006 Cambridge University Press