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United States Department of Agriculture

Agricultural Research Service

Title: A Large-Sample Qtl Study in Mice: Ii. Body Composition

Authors
item Rocha, Joao - UNIV. OF NEBR.-LINCOLN
item Eisen, Eugene - NORTH CAROLINA STATE UNIV
item Van Vleck, Lloyd
item Pomp, Daniel - UNIV. OF NEBR.-LINCOLN

Submitted to: Mammalian Genome
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: September 10, 2003
Publication Date: March 1, 2004
Citation: ROCHA, J.L., EISEN, E.J., VAN VLECK, L.D., POMP, D. A LARGE-SAMPLE QTL STUDY IN MICE: II. BODY COMPOSITION. MAMMALIAN GENOME. 2004. 14:100-113.

Interpretive Summary: An estimated 65% of U.S. adults are overweight and 31% are obese. Overweight and obesity substantially increase the risk of hypertension, dyslipidemia, type 2 diabetes, coronary heart disease, stroke, and many other diseases combining to form the single largest cause of death in developed countries. While molecular biology has contributed significantly to understanding weight regulation at the metabolic and physiological levels, an alarmingly few cases of obesity in humans can be attributed to mutations within genes exerting effects in well-characterized energy-balance pathways. Carcass and body composition traits are important considerations of modern livestock production systems where consumer health concerns and marketing perspectives play increasingly important roles. The problem of excess fat in livestock and poultry carcasses is ubiquitous and has serious consequences for the animal industry at least at four levels: consumer health perceptions; wasteful production of an undesired biological component; increased labor costs to trim waste fat; and lower biological efficiencies of fatter animals. Understanding the complex genetic architecture underlying quantitative trait variation for growth and fatness in mice may help to understand the same processes in livestock by localizing and defining the nature of quantitative trait loci (QTL) for these traits. While many QTL studies have focused on body fat as a biomedically and agriculturally relevant trait, fewer investigations have evaluated components of body weight with a more global approach encompassing body fatness as well as organ weights and estimates of lean mass. In this study, a large population from a cross between lines of mice that had undergone long-term selection for rapid growth rate and low body weight was created to evaluate quantitative trait loci for a variety of complex traits, including body weight and growth. Regions on mouse chromosomes 7, 15, and 17 emerged as 'hot spots' for genes for obesity and leanness. About 25% of QTL for growth were associated with chromosome 2. Similar results might be expected with livestock species.

Technical Abstract: Long-term selection lines for high and low growth were crossed to produce the mice for a large-sample of about 1,000 F2 mice to gain further understanding of the genetic architecture of complex polygenic traits. Through implementation of composite interval mapping on data from male F2 mice (n = 552), 50 QTL were detected on 15 chromosomes which impact weights of various organ and adipose subcomponents of growth, including heart, liver, kidney, spleen, testis, and subcutaneous and epididymal fat depots. Nearly all aggregate growth QTL could be interpreted in terms of the organ and fat subcomponents measured. More than 25% of the QTL detected map to mouse chromosome 2, which confirms the relevance of this chromosome to growth and fatness in this cross. In addition, regions of mouse chromosomes 7, 15 and 17 emerged as important obesity 'hot-spots.' Average degrees of directional dominance were close to additivity, matching expectations for body composition traits. A strong QTL-congruency is evident among heart, liver, kidney and spleen weights. Liver and testis are the organs with genetic architectures which are, respectively, most and least aligned with that for aggregate body weight. Synthesis and summarization of biological growth of the mouse are accomplished in this study, with growth interpreted in terms of the organ subcomponents underlying the macro aggregate traits, and anchored on the corresponding genomic locations.

Last Modified: 8/19/2014
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