Jinkai Wang1, Man Chun John Ma1, Amanda K Mennie1, Janette M Pettus1, Yang Xu1, Lan Lin1, Matthew G Traxler1, Jessica Jakoubek1, Santosh S Atanur1, Timothy J Aitman1, Yi Xing2, Anne E Kwitek2. 1. From the Department of Internal Medicine (J.W., A.K.M., J.M.P., Y. Xu, L.L., Y. Xing, A.E.K.), Department of Pharmacology (M.C.J.M., A.K.M., J.M.P., Y. Xu, M.G.T., J.J., A.E.K.), and Iowa Institute of Human Genetics (A.E.K.), University of Iowa, Iowa City; Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles (J.W., L.L., Y. Xing); and Physiological Genomics and Medicine Group, Medical Research Council Clinical Sciences Centre, Faculty of Medicine, Imperial College London, Hammersmith Hospital, London, United Kingdom (S.S.A., T.J.A.). 2. From the Department of Internal Medicine (J.W., A.K.M., J.M.P., Y. Xu, L.L., Y. Xing, A.E.K.), Department of Pharmacology (M.C.J.M., A.K.M., J.M.P., Y. Xu, M.G.T., J.J., A.E.K.), and Iowa Institute of Human Genetics (A.E.K.), University of Iowa, Iowa City; Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles (J.W., L.L., Y. Xing); and Physiological Genomics and Medicine Group, Medical Research Council Clinical Sciences Centre, Faculty of Medicine, Imperial College London, Hammersmith Hospital, London, United Kingdom (S.S.A., T.J.A.). anne-kwitek@uiowa.edu yxing@ucla.edu.
Abstract
BACKGROUND: The metabolic syndrome (MetS) is a collection of co-occurring complex disorders including obesity, hypertension, dyslipidemia, and insulin resistance. The Lyon hypertensive and Lyon normotensive rats are models of MetS sensitivity and resistance, respectively. To identify genetic determinants and mechanisms underlying MetS, an F2 intercross between Lyon hypertensive and Lyon normotensive was comprehensively studied. METHODS AND RESULTS: Multidimensional data were obtained including genotypes of 1536 single-nucleotide polymorphisms, 23 physiological traits, and >150 billion nucleotides of RNA-seq reads from the livers of F2 intercross offspring and parental rats. Phenotypic and expression quantitative trait loci (eQTL) were mapped. Application of systems biology methods identified 17 candidate MetS genes. Several putative causal cis-eQTL were identified corresponding with phenotypic QTL loci. We found an eQTL hotspot on rat chromosome 17 that is causally associated with multiple MetS-related traits and found RGD1562963, a gene regulated in cis by this eQTL hotspot, as the most likely eQTL driver gene directly affected by genetic variation between Lyon hypertensive and Lyon normotensive rats. CONCLUSIONS: Our study sheds light on the intricate pathogenesis of MetS and demonstrates that systems biology with high-throughput sequencing is a powerful method to study the pathogenesis of complex genetic diseases.
BACKGROUND: The metabolic syndrome (MetS) is a collection of co-occurring complex disorders including obesity, hypertension, dyslipidemia, and insulin resistance. The Lyon hypertensive and Lyon normotensive rats are models of MetS sensitivity and resistance, respectively. To identify genetic determinants and mechanisms underlying MetS, an F2 intercross between Lyon hypertensive and Lyon normotensive was comprehensively studied. METHODS AND RESULTS: Multidimensional data were obtained including genotypes of 1536 single-nucleotide polymorphisms, 23 physiological traits, and >150 billion nucleotides of RNA-seq reads from the livers of F2 intercross offspring and parental rats. Phenotypic and expression quantitative trait loci (eQTL) were mapped. Application of systems biology methods identified 17 candidate MetS genes. Several putative causal cis-eQTL were identified corresponding with phenotypic QTL loci. We found an eQTL hotspot on rat chromosome 17 that is causally associated with multiple MetS-related traits and found RGD1562963, a gene regulated in cis by this eQTL hotspot, as the most likely eQTL driver gene directly affected by genetic variation between Lyon hypertensive and Lyon normotensive rats. CONCLUSIONS: Our study sheds light on the intricate pathogenesis of MetS and demonstrates that systems biology with high-throughput sequencing is a powerful method to study the pathogenesis of complex genetic diseases.
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