Cardiovascular diseases, specifically coronary heart disease and myocardial infarction, are the leading cause of morbidity and mortality in developed countries. Most cardiac phenotypes, including cardiac mass, infarct size, and susceptibility to heart failure, are quantitative traits determined by genetic and environmental factors such as diet and stress. Additional "extra-cardiac" factors that predispose humans to coronary heart disease include proatherogenic factors such as high blood pressure, abnormal lipid profiles, and insulin resistance. These cardiovascular risk factors often cluster in the so-called metabolic syndrome. To understand the pathophysiology of cardiovascular diseases, it is essential to identify genes associated with increased risk. Comparative genomics is an indispensable tool for dissecting the genetics of multifactorial diseases in humans. The availability of genome sequences and genome-scale technologies has led to new strategies for identifying the genes that underlie complex phenotypes and has greatly accelerated progress in this field. The high heritability of variation in gene expression suggests that identifying the genetic determinants of gene expression may shed light on the molecular basis of complex traits. Another justification for studying the genetics of gene expression is that transcript abundance may act as an intermediate phenotype between genomic DNA sequence variation and more complex whole-body phenotypes.
Much of our knowledge about the genes that regulate clinically important pathophysiological traits has been derived from rodents. The spontaneously hypertensive rat (SHR) is a widely studied model of human hypertension and the highly prevalent metabolic syndrome. The recent availability of the rat genome sequence has made it feasible to study gene expression at the level of the genome alongside well-characterized rat phenotypes. Compared with control strains, the SHR strain also exhibits differences in a number of important cardiac phenotypes, including cardiac mass, infarct size in response to ischemia-reperfusion injury, and susceptibility to cardiac arrhythmias or heart failure. Numerous genetic linkage studies have shown the location, but not the identity, of major predisposing quantitative trait loci. Despite a wealth of physiological and genetic data available in the SHR, the pathogenic events leading to the development of hypertension and related cardiovascular and metabolic phenotypes in this model remain largely unclear.
The BXH/HXB panel of recombinant inbred (RI) strains was derived from the SHR and Brown Norway strains for genetic studies of hypertension and related cardiovascular and metabolic phenotypes. At present, 30 BXH/HXB RI strains are available. The current map of RI strains contains more than 3,000 gene markers, and RI strains are characterized in multiple physiological phenotypes (see WebQTL at www.genenetwork.org). This RI strain panel is a powerful and permanent resource for genetic mapping, combining the advantages of a genetically segregating population with the opportunity to accumulate genetic and physiological data over time. Recently, we applied integrated gene expression profiling and linkage analysis to the regulation of gene expression in fat, kidney, adrenal, left ventricle, and skeletal muscle tissues in the BXH/HXB panel of RI strains. Using this unique resource, we identified a data set of hundreds of robustly mapped cis- and trans-acting quantitative trait loci (QTLs) that regulate gene expression levels (expression QTLs or eQTLs); we demonstrated that the BXH/HXB RI strains are a suitable genetic system for large-scale identification of positional candidates and regulatory pathways for previously mapped physiological QTLs (pQTLs). On the basis of these findings, we propose using RI strain linkage analysis of gene expression levels and of specific cardiovascular traits to investigate the pathogenesis of cardiovascular phenotypes in the SHR. Specifically, we will test the hypothesis that eQTLs regulated in cis, essentially as monogenic traits, represent attractive candidate genes for QTLs regulating complex cardiovascular phenotypes. The ultimate goal of the project is to identify some of these cardiovascular QTLs at the molecular level.
The goals of our project are to (1) characterize clinically important hemodynamic and cardiac phenotypes and determine left ventricular transcript levels in recombinant inbred and progenitor strains; (2) map hemodynamic and cardiac phenotypes and transcript levels to discrete regions of the genome as physiological QTLs and expression QTLs respectively, and determine the functional networks of cardiovascular traits; (3) analyze cis-acting expression QTLs that colocalize to physiological QTLs for sequence variants; and (4) assign functional relevance to selected eQTLs/pQTLs using functional genomic complementation studies.
Last updated August 2009