Genotype-Phenotype relationships underlying aerobic capacity and metabolic health

描述（由申请人提供）：人体有氧代谢能力的降低与疾病风险增加相关，包括肥胖、胰岛素抵抗、高血压和2型糖尿病。此外，氧化能力与预期寿命密切相关。为了理解连接有氧能力和代谢健康的生物学机制，我们将采用由通过对高和低先天性（即，未经训练的）运行能力，与控制育种，以最大限度地发挥其远系繁殖的性质。高能力跑步者（HCR）和低能力跑步者（LCR）在遗传上是异质的，并且在>32代之后在有氧能力上高度分化。他们在体重增加、血压、体重指数、肺活量、脂质和葡萄糖代谢、炎症和氧化应激的测量以及寿命方面表现出很大的差异。尽管进行了广泛的研究，但HCR健康状况改善和LCR疾病风险增加的潜在分子基础尚不清楚。我们的初步数据已经揭示了每个品系内跑步能力的强遗传性，以及在各种条件下增加的遗传分化以及mRNA和代谢物水平的稳健HCR-LCR差异。在这个建议中，我们测试的假设，在有限数量的基因的功能性DNA变异的贡献的八个创始人菌株，和他们的频率越来越多地驱动除了在两个线通过选择，占两个线的分子和生理变异。我们建议确定这些致病基因与以下特定目标（SA）：SA 1。在HCR-LCR互交群体（n~650）中鉴定跑步距离、相关代谢性状和基因表达变异的数量性状基因座（QTL）。SA 2.使用遗传和功能基因组方法的组合发现致病基因/变体，包括eQTL（SA 1），来自创始品系的祖先单倍型，32代后的正选择特征，基于选择改变的功能变体的测序发现，基因表达网络分析，以及使用创始品系的已知变体的计算机精细定位。候选基因的功能相关性将在多年来获得的丰富先验知识HCR-LCR的背景下进行解释。这项为期三年的研究将利用HCR/LCR系统的几个独特优势：这两个品系在很大程度上保持远交以保持遗传多样性;系谱是完全已知的，组织样本存档以供分析，过去的重组事件导致了2-3 cM分辨率的可识别单倍型结构，非常适合精细作图。我们期望在多个基因座上找到功能等位基因，这些基因座已经手拉手进化，并且与品系之间的健康差异相关。这些基因中的许多可能与相应的人类表型直接相关，或者至少为改善人类代谢健康的重要途径提供了线索。我们的最终目标是获得对代谢健康的更深入的机械理解，并将这种理解转化为改善患者的治疗方法。

DESCRIPTION (provided by applicant): A decrease in aerobic capacity in humans is associated with increased risk of disease, including obesity, insulin resistance, hypertension, and type 2 diabetes. Further, oxidative capacity is strongly correlated with life expectancy. To understand the biological mechanisms linking aerobic capacity and metabolic health we will employ a model system consisting of two lines of rat established through divergent selection for high and low inborn (i.e., untrained) running capacity, with controlled breeding to maximize their outbred nature. The high capacity runners (HCRs) and low capacity runners (LCRs) are genetically heterogeneous and highly differentiated in aerobic capacity after >32 generations. They display large differences in weight gain, blood pressure, body mass index, lung capacity, lipid and glucose metabolism, measures of inflammation and oxidative stress and lifespan. Despite extensive studies, the underlying molecular basis for the enhanced health of the HCRs and increased disease risk of LCRs is not known. Our preliminary data have revealed strong heritability of running capacity within each line, and increasing genetic differentiation as well a robust HCR-LCR differences in mRNA and metabolite levels under a variety of condition. In this proposal, we test the hypothesis that functional DNA variants in a limited number of genes were contributed by the eight founder strains, and their frequencies were driven increasingly apart in the two lines through selection, accounting for the molecular and physiological variation of the two lines. We propose to identify these causal genes with the following specific aims (SAs): SA1. Identify quantitative trait loci (QTL) for running distance, related metabolic traits, and gen expression variation in an HCR-LCR intercross population (n~650). SA2. Discover causal genes/variants using a combination of genetic and functional genomic approaches, including eQTLs (SA1), ancestral haplotype from the funder lines, signatures of positive selection after 32 generations, sequencing-based discovery of functional variants altered by selection, gene expression network analysis, and in silico fine mapping using known variants from founder strains. Functional relevance of candidate genes will be interpreted in the context of rich prior knowledge HCR-LCR gained over the years. This proposed three-year study will leverage several unique advantages of the HCR/LCR system: the two lines have been kept largely outbred to maintain genetic diversity; the pedigree is completely known, with tissue samples archived for analysis, and past recombination events have led to recognizable haplotype structure at 2-3 cM resolution, ideal for fine mapping. We expect to find functional alleles at multiple loci that have evolved hand-in-hand and are relevant for the health differences between lines. Many of these genes may be directly relevant for the corresponding human phenotypes or, at a minimum, provide clues to important pathways that could be targeted for improving human metabolic health. Our ultimate goal is to gain a deeper mechanistic understanding of metabolic health, and translate this understanding to improved therapies for patients.