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

机译:协作十字架新兴线路中的能量平衡特征架构

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摘要

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.
机译:评价了潜在的效用协作十字(CC)鼠标资源,以更好地了解与能量平衡有关的复杂性状。主要重点是研究新兴CC品系(pre-CC)的遗传多样性是否会转化为同等的表型多样性。其次,我们绘制了该人群中15种与代谢和运动相关的表型的数量性状位点(QTL)。我们评估了176个前CC品系的代谢和自愿运动特征,发现其表型变异经常超过在其前CC来源的八种创始菌株中所见。始祖菌株中存在的许多表型相关在CC之前的种群中不再显着,这可能表示藏有多个基因的区域的连锁不平衡(LD)降低,从而影响能量平衡或现有同系近交近交菌株的遗传结构破坏。 QTL映射显示了体重的五个重要QTL和八个暗示性QTL(Chr 4,7.54 Mb; CI 3.32–10.34 Mb; Bwq14),身体成分,车轮行驶(Chr 16,33.2 Mb; CI 32.5–38.3 Mb),体重变化响应运动(1:Chr 6,77.7Mb; CI 72.2–83.4 Mb和2:Chr 6,42.8 Mb; CI 39.4–48.1 Mb)和运动过程中的食物摄入(Chr 12,85.1 Mb; CI 82.9–89.0) Mb)。一些QTL与先前映射的QTL有相似的性状,而其他QTL似乎代表了新的基因座。这些结果表明,CC将成为检测复杂性状(例如参与能量平衡调节的性状)遗传结构的强大,高精度工具。

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