4.6 Article

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

期刊

出版社

AMER PHYSIOLOGICAL SOC
DOI: 10.1152/ajpendo.00707.2010

关键词

genetics; wheel running; adiposity; body weight; quantitative trait loci

资金

  1. National Institutes of Health (NIH) [DK-076050, U01-CA-105417, U01-CA-134240, GM-076468, MH-090338, T32-MH-07669403, K12-HD-01441]
  2. Ellison Medical Foundation [AG-IA-0202-05]
  3. National Institute of General Medical Sciences [F32-GM-090667]
  4. state of North Carolina
  5. National Institute of Diabetes and Digestive and Kidney Diseases [DK-056350]
  6. US Department of Energy, Office of Biological and Environmetnal Research [AC05-00OR22725]

向作者/读者索取更多资源

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.

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