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.

Public Health Relevance

We will study two lines of rat that differ significantly in untrained running capacity and a wide range of phenotypes related to blood pressure, body weight, insulin and glucose content in blood, inflammation, lung capacity, and natural life span. Our goal is to discover the gene differences responsible for these health-related differences and provide insights into the biology that underlie similar conditions in humans, including diabetes, cardiovascular disorders, obesity, and metabolic syndrome.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project (R01)
Project #
5R01DK099034-02
Application #
8853276
Study Section
Genetics of Health and Disease Study Section (GHD)
Program Officer
Castle, Arthur
Project Start
2014-06-01
Project End
2017-05-31
Budget Start
2015-06-01
Budget End
2016-05-31
Support Year
2
Fiscal Year
2015
Total Cost
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Genetics
Type
Schools of Medicine
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
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