Abstract
This is an in silico analysis of quantitative trait loci (QTLs), genes, polymorphisms, and chromosomal regions regulating hypertension in the rat genome. Utilizing PGmapper, a program that matches phenoltypes to genes, we identified 266 essential hypertension-associated genes (HyperA), and 83 of these genes contain known hypertension-associated polymorphisms (HyperAP). The majority of HyperAP have been reported in recent years. Surprisingly, only a few of these HyperAP genes have been investigated for their candidacy as the QTL for hypertension. The frequency of candidate genes within peak regions of the QTL is higher than the rest of the QTL region. We also found that QTL located in both gene-rich regions and gene-rich chromosomes contained the most candidate genes. However, the number of candidate genes within a peak region is not associated with the number of total genes in a QTL region. This data could not only facilitate a more rapid and comprehensive identification for the causal genes underlying hypertension in rats, but also provides new insights into genomic structure in regulation of hypertension.
Highlights
Blood pressure and hypertension in humans are quantitative traits controlled by many genes [1,2,3]
Our investigation raises an important issue in the selection of candidate genes for specific QTLs, the consideration of the position of a gene in the QTL region
Our data suggests that a gene in the peak region of a QTL is of more relative importance than a gene further from the peak position
Summary
Blood pressure and hypertension in humans are quantitative traits controlled by many genes [1,2,3]. More than 300 Quantitative trait loci (QTLs) for blood pressure and hypertension are reported in the rat genome (see the Rat Genome Database web site at: http://rgd.mcw.edu/), and these QTLs are found in every rat chromosome [6]. More than 200 candidate genes relating to hypertension have been identified in rats and some of them, such as Kcnj and Drd, are positioned within a QTL [7,8]. Most of these identified genes are relatable to human chromosomes. Wang et al / Open Journal of Genetics 2 (2012) 136-154 possible to pinpoint accurately genes within a QTL and evaluate them much more efficiently
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