Search

The article discusses a research which examines the genetic determinants underlying the metabolic syndrome (MetS) in rats using systems biology methods. It reveals RGD1562963 as the most likely expression quantitative trait loci (eQTL) driver gene directly affected by genetic variation between Lyon normotensive and Lyon hypertensive rats. It indicates the aspect of systems biology with high-throughput sequencing as a powerful method for studying the pathogenesis of complex genetic diseases. more...

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., (© 2015 American Heart Association, Inc.) more...