Systems biology with high-throughput sequencing revealed genetic mechanisms underlying the Metabolic Syndrome in the Lyon Hypertensive Rat

The metabolic syndrome (MetS) is a collection of co-occurring complex disorders including obesity, hypertension, dyslipidemia, and insulin resistance. The Lyon Hypertensive (LH) and Lyon Normotensive (LN) rats are models of MetS sensitivity and resistance, respectively. To identify genetic determinants and mechanisms underlying MetS, 169 rats from an F2 intercross between LH and LN were studied. Multi-dimensional data were obtained including genotypes of 1536 SNPs, 23 physiological traits including blood pressure, plasma lipid and leptin levels, and body weight/adiposity, and more than 150 billion nucleotides of RNA-seq reads from the livers of 36 F2 individuals, 6 LH and 6 LN individuals. We identified 17 pQTLs (physiological quantitative trait loci) and 1200 eQTLs (gene expression quantitative trait loci). Systems biology methods were applied to identify 18 candidate MetS genes, including genes (Prcp and Aqp11) previously shown to be MetS-related. We found an eQTL hotspot on RNO17, which was also located within pQTLs for MetS-related traits. The genes regulated by this eQTL hotspot were mainly in two co-expression network modules (a mitochondria related module and a gene regulation related module) and were predicted to causally affect many MetS-related traits. Multiple evidences strongly and consistently support RGD1562963, a gene regulated in cis by this eQTL hotspot and possibly related to RNA stability, as the eQTL driver gene directly affected by genetic variation between LH and LN rats; the expression of this gene is also correlated with MetS-related traits. Our study sheds light on the intricate pathogenesis of MetS and proved that systems biology with high-throughput sequencing is a powerful method to study the etiology of complicated diseases. Overall design: RNA-Seq of the liver of 6 LH (Lyon Hypertensive) rats and 6 LN (Lyon Normotensive) rats and 36 F2 rats.

48

Wang J, Ma MC, Mennie AK, Pettus JM, Xu Y, Lin L, Traxler MG, Jakoubek J, Atanur SS, Aitman TJ, Xing Y, Kwitek AE