Multi-Omics Analysis of a Rat Model of Aerobic Exercise Capacity and Metabolic Fitness.

Rat model of aerobic exercise capacity;Genetics;Science;Human Genetics

Ren, YangsuShedden, Kerby A ;

University of Michigan

关键词: Rat model of aerobic exercise capacity;    Genetics;    Science;    Human Genetics;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/120695/renyulb_1.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

We have previously established two lines of rat for studying the functional of aerobic exercise capacity (AEC) and its impact on metabolic health. The two lines, high capacity runners (HCR) and low capacity runners (LCR), have been selectively bred for high and low intrinsic AEC, respectively. They were started from the same genetically heterogeneous population and have now diverged in both AEC and many other physiological measures, including weight, body composition, blood pressure, body mass index, lung capacity, lipid and glucose metabolism, and natural life span. In order to exploit this rat model to understand the biological basis of metabolic traits I conducted four related studies. First, I performed a genetic characterization of both pedigrees, with ~30 generations and >6,000 animals in each, showing that AEC has high heritability in both lines, and that the lines have diverged at expected rates. Second, I performed gene expression analysis in skeletal muscle with a 2-2-2 design to compare HCR and LCR, aged and young, and rest and exhaustion. I found that mitochondrial function is the primary differences between the lines; and extracellular matrix components underlie the aging effect. Third, I used SNP genotype and whole genome sequencing data to identify signatures of selection using three different statistics (runs of homozygosity, fixation index, and aberrant allele frequency spectrum), and developed a composite score that combined the three signals. I found several pathways (ATP transport and fatty acid metabolism) are enriched in regions under differential selection. Fourth, I complemented the selection signals with a direct analysis of genotype-phenotype relationship in an HCR-LCR intercross F2 cohort (n>600). We have completed breeding and phenotyping of F2s for running distance, body weight, percent body fat, muscle mass, etc., and have genotyped them for ~625K SNPs using a custom genotyping panel that I designed to utilize ancestral informative markers. My preliminary QTL results highlight a candidate region on chromosome 18 with three biologically relevant genes, one of which is a potential candidate from the selection signature results. Ancestry haplotype-based fine mapping are ongoing and will be integrated with the expression results and the selection scan.