| Literature DB >> 24714719 |
Allen W Cowley1, Carol Moreno2, Howard J Jacob2, Christine B Peterson3, Francesco C Stingo4, Kwang Woo Ahn5, Pengyuan Liu6, Marina Vannucci3, Purushottam W Laud5, Prajwal Reddy7, Jozef Lazar7, Louise Evans8, Chun Yang8, Theresa Kurth8, Mingyu Liang8.
Abstract
The goal of the present study was to narrow a region of chromosome 13 to only several genes and then apply unbiased statistical approaches to identify molecular networks and biological pathways relevant to blood-pressure salt sensitivity in Dahl salt-sensitive (SS) rats. The analysis of 13 overlapping subcongenic strains identified a 1.37 Mbp region on chromosome 13 that influenced the mean arterial blood pressure by at least 25 mmHg in SS rats fed a high-salt diet. DNA sequencing and analysis filled genomic gaps and provided identification of five genes in this region, Rfwd2, Fam5b, Astn1, Pappa2, and Tnr. A cross-platform normalization of transcriptome data sets obtained from our previously published Affymetrix GeneChip dataset and newly acquired RNA-seq data from renal outer medullary tissue provided 90 observations for each gene. Two Bayesian methods were used to analyze the data: 1) a linear model analysis to assess 243 biological pathways for their likelihood to discriminate blood pressure levels across experimental groups and 2) a Bayesian graphical modeling of pathways to discover genes with potential relationships to the candidate genes in this region. As none of these five genes are known to be involved in hypertension, this unbiased approach has provided useful clues to be experimentally explored. Of these five genes, Rfwd2, the gene most strongly expressed in the renal outer medulla, was notably associated with pathways that can affect blood pressure via renal transcellular Na(+) and K(+) electrochemical gradients and tubular Na(+) transport, mitochondrial TCA cycle and cell energetics, and circadian rhythms.Entities:
Keywords: Bayesian analysis; Dahl S rats; chromosome 13; pathway analysis; salt-sensitive hypertension
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Year: 2014 PMID: 24714719 PMCID: PMC4042181 DOI: 10.1152/physiolgenomics.00179.2013
Source DB: PubMed Journal: Physiol Genomics ISSN: 1094-8341 Impact factor: 3.107