Abstract
Chronic kidney disease is a major health issue, with hypertension playing a significant role in progression of kidney injury and decline in kidney function. Previously, genetic studies utilized the Dahl salt-sensitive (S) rat, a model of hypertensive related kidney disease and the spontaneously hypertensive rat (hypertensive, but resistant to kidney injury) to identify genomic regions associated with kidney injury. To confirm identified genomic intervals, congenic strains were developed for several chromosomes (RNO) by transfer of SHR genome to the genetic background of the S, including RNO2, 6, 8, 9, 10, 11, 13 and 19. Several of these congenic strains, with the exception of RNO6 and 19 have been extensively investigated. Here, we report that S.SHR(6) and (19) demonstrate significantly improved proteinuria (53±2.5 and 54±2.5 mg/24hr, respectively) compared to control S (116±7.2) and improved measures of kidney function (BUN= 24.3±0.6 and 24.6±0.6 vs. 28±1.3 mg/dl). To facilitate the identification of genetic variants that underlie each genomic region, especially on RNO6 and RNO19, comparative genome hybridization (CGH) was performed (NimbleGen and Agilent) to identify copy number variation (CNV) between the S and SHR. CNV was identified on RNO6 and RNO19 (as well as other chromosomes) which could be linked to the development of kidney injury. In addition, recent sequencing of the entire genomes of the S and SHR has identified essentially all genetic variation (SNP and INDEL) between the two inbred models. The 95% confidence interval of each causative locus spans ~10 Mb. The region on RNO6 contains 54 annotated genes (24 nonsynonymous SNP) and RNO19 contains 101 genes and/or miRNA (68 nonsynonymous SNP). The majority of SNP (>95%) are within intergenic or intronic regions, regardless of the genomic locus. A modest number of SNP (~5%) fall within the putative promoter region of genes which could impact gene expression. In summary, CGH and high quality genome sequence analysis will help guide upcoming congenic substrain analysis to expedite identification of the causative genetic variation(s) that underlie each genomic locus.
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