Original Article

Interaction Between Chromosome 2 and 3 Regulates Pulse Pressure in the Stroke-Prone Spontaneously Hypertensive RatNovelty and Significance

H.H. Caline Koh-Tan, Martin W. McBride, John D. McClure, Elisabeth Beattie, Barbara Young, Anna F. Dominiczak, Delyth Graham
https://doi.org/10.1161/HYPERTENSIONAHA.111.00814
Hypertension. 2013;62:33-40
Originally published June 12, 2013

Jump to

Abstract

In an F2 cross between stroke-prone spontaneously hypertensive (SHRSP) and Wistar Kyoto (WKY) rats, we previously identified blood pressure quantitative trait loci (QTL) on rat chromosome (RNO) 2 and a pulse pressure QTL on RNO3. The aims of this study were to confirm the QTL on RNO3 and to investigate interaction between RNO2 and RNO3 loci through the generation and phenotypic assessment of single RNO3 congenic (SP.WKYGla3a) and bicongenic (SP.WKYGla2a/3a) strains. Hemodynamic profiling, vascular function, and renal histology were examined in these newly generated strains along with the previously reported RNO2 congenic strain (SP.WKYGla2a). Our results demonstrate significant equivalent reduction in systolic, diastolic, and pulse pressure phenotypes in SP.WKYGla3a and SP.WKYGla2a rats, whereas greater reductions were observed with the SP.WKYGla2a/3a bicongenic strain achieving blood pressure levels similar to normotensive WKY rats. Epistasis was observed between pulse pressure QTL on RNO2 and 3 at baseline and during 1% salt challenge. Vascular function and renal pathology studies indicate that QTL on RNO3 are responsible for salt-induced kidney pathology, whereas QTL on RNO2 seem to have greater impact on vascular function. RNO3 congenic and bicongenic strains have confirmed the importance of SHRSP alleles in the RNO3 congenic interval on pulse pressure variability and end-organ damage. These strains will allow interrogation of complex gene–gene and gene–environment interactions contributing to salt-sensitive hypertension and renal pathology in the SHRSP rat.

Introduction

Human essential hypertension is a complex, multifactorial, quantitative trait under polygenic control, with inherited factors contributing ≤30% of the variation in blood pressure (BP).1 The search for the specific genetic variations contributing to this heritability remains challenging. Recent genome-wide association studies collectively explain only a very small proportion of the total variation in systolic BP (SBP) or diastolic BP (DBP; ≈2.2%),2,3 which suggests the existence of many more undiscovered BP-related variants.

Genetic detection of complex polygenic diseases is complicated by potential gene–gene, gene–environment interactions, and nonsequence epigenetic modifications. In particular, there is growing evidence for epistasis among BP quantitative trait loci (QTL) in inbred rat models of hypertension.4–11

We have previously identified BP QTL on rat chromosomes (RNO) 2 and RNO3 in a linkage analysis of an F2 cross between stroke-prone spontaneously hypertensive (SHRSP) and Wistar Kyoto (WKY) rats.12 We subsequently confirmed the RNO2 loci with the production of congenic strains and identified candidate genes for baseline BP and response to salt loading.13–15 The aims of this study were to confirm the RNO3 QTL and to investigate interaction between the loci on RNO2 and RNO3 through the generation and phenotypic assessment of single and bicongenic strains.

Methods

Animal Strains

Inbred colonies of SHRSP and WKY have been developed and maintained at the University of Glasgow since 1991, as described previously.12 All animals were housed under controlled environmental conditions, fed standard rat chow (rat and mouse no No. 1 maintenance diet, Special Diet Services) and water provided ad libitum. At 18 weeks of age, rats were given a salt challenge (1% NaCl in drinking water) for 3 weeks. All animal procedures performed were approved by the Home Office according to regulations regarding experiments with animals in the United Kingdom.

The single RNO3 congenic strain, SP.WKYGla3a (D3Mgh16-D3Rat114), was generated using a previously described marker-assisted speed congenic strategy where WKY (donor strain) segments were introgressed into the SHRSP (recipient strain) genetic background.16 The SP.WKYGla2a congenic strain (D2Rat13-D2Rat157) is a previously published strain.15,16 The SP.WKYGla2a/3a bicongenic strain, (D2Rat13-D2Rat157/D3Mgh16-D3Wox28) was generated as follows: F1 rats, bred by crossing SP.WKYGla3a and SP.WKYGla2a congenic rats, were backcrossed with SP.WKYGla2a rats. Progeny heterozygous for RNO3 and homozygous for RNO2 congenic segments were crossed. Progeny homozygous for both congenic intervals were bred to establish the bicongenic strain. A full list of microsatellite markers used for genotyping is shown in Table S1 in the online-only Data Supplement. The nomenclature of the strains consists of the first abbreviation belonging to the recipient strain and the second to the donor: Gla denotes that strains originate from the Glasgow colonies, and the number 2 or 3 refers to the particular rat chromosome. All the studies were conducted in male rats only.

Hemodynamic and Phenotypic Measurements

The Dataquest IV telemetry system (Data Sciences International) was used for the direct measurement of SBP, DBP, and pulse pressure (PP).12,16 Male rats were implanted at 12 weeks of age with 1-week recovery, 5 weeks of baseline measurements, followed by 3 weeks of 1% NaCl in the drinking water. Twenty-four–hour urine samples were collected from all animals using metabolic cages before sacrifice. At sacrifice, weights for cardiac mass index (CMI), left ventricular mass index (LVMI), and renal mass index (RMI) were measured, thoracic aorta were excised for ex vivo vascular function, and harvested tissues were snap frozen in liquid nitrogen and stored at –80°C or fixed in 4% buffered formaldehyde and paraffin embedded. CMI, LVMI, RMI, renal histology, and urinary biochemistry were also assessed in age-matched control animals, not receiving salt in their drinking water.

Vascular Function

Thoracic aortas from salt-loaded 21-week-old rats were cleaned of connective tissue and suspended in organ baths, as previously described for measurement of NO bioavailability.17 Krebs’ buffer in which aortas were maintained, contained indomethacin (0.02 mmol/L) to inhibit any prostanoid-mediated effects. Isometric tension studies were performed using a force transducer and recorded using MacLab. Contractile responses to 10 mmol/L KCl were examined, the baths washed out, and tissues allowed to relax. Cumulative concentration–response curves to phenylephrine (10 nmol/L–100 μmol/L) were constructed, first in the absence and again after washout, in the presence of 100 μmol/L NG-nitro-l-arginine methyl ester (L-NAME) to inhibit NO synthase. The increase in tension in the presence of L-NAME provides a measure of the effect of NO on basal tone, and was calculated for each ring over the full dose-response curve and expressed as area under the curve. In addition, the rings were preconstricted to the EC50 of phenylephrine, and a concentration-response curve for carbachol (10 nmol/L–100 μmol/L) was obtained which provides a measure of stimulated NO release. Responses to phenylephrine were standardized against the initial contractile response to KCl.

Renal Histology

For renal histology, adjacent transverse sections of kidney (3-μm thick) were stained with hematoxylin and eosin, elastin muscle fibrin stain, or periodic acid schiff and scored for renal changes according to a previously described scoring system.18 Images shown were taken with Olympus DP72 attached to Olympus BX51 microscope, using DP2-BSW software.

Urinary Biochemistry Analysis

Urinary protein was measured using Thermo Pierce Protein Assay 660 (no. 22662, Thermo Fisher Scientific Inc) according to manufacturer’s instructions. Urine samples were diluted 1 in 5 for assay.

Statistical Analysis

All results are shown as mean±SEM, unless otherwise stated. Previously generated data from an F2 cross between SHRSP and WKY12 were analyzed using Pseudomarker statistical software.19,20 Interaction analysis between QTL on RNO2 and RNO3 was performed using a Pseudomarker 2-dimensional pairscan with a 2-QTL model. This is a simultaneous search for pairs of interacting loci, which tests all pairs of genomic locations for associations with the trait. The 2-dimensional scan calculated logarithm of odds ratio (LOD) scores for the full model (LODfull; 2-QTL model plus interaction) and the interaction model (LODint; calculated by subtracting the LODfull value from the LODadd [additive] value). Hemodynamic parameters for WKY or congenic strains were compared with SHRSP, using repeated measures ANOVA, general linear model. The night–day PP difference was calculated as night PP (mm Hg)-day PP (mm Hg). Interactions between RNO2 and RNO3 congenic intervals were investigated using 1-way ANOVA with contrasts (SHRSP versus SP.WKYGla2a; SHRSP versus SP.WKYGla3a) and the interaction (SHRSP and SP.WKYGla2a/3a versus SP.WKYGla2a and SP.WKYGla3a). The phenotypic measurements were analyzed using 1-way ANOVA with Tukey comparison for 95% confidence interval. The histology scores for each group were compared using the Kruskal–Wallis test, adjusted for ties. Bonferroni-corrected Mann–Whitney tests were then used for testing significance between group pairs.

Results

Interaction Between RNO2 and RNO3 QTLs

Analysis of the F2 PP data using Pseudomarker statistical software identified an interaction between the lower BP QTL region on RNO2 (peak near marker D2Rat239)16 and the QTL on RNO3 (peak near marker D3Rat50; Figure 1B). The full LOD score (LODfull; 2 QTL model plus interaction)=7.66 and the interaction LOD score (LODint)=4.17; P=0.0007.

Figure 1.
Figure 1.

A, Congenic interval mapping based on physical locations of polymorphic microsatellite markers in SP.WKYGla2a, SP.WKYGla3a, and SP.WKYGla2a/3a strains. Light gray bars indicate regions of stroke-prone spontaneously hypertensive allelic homozygosity, dark gray bars indicate regions of Wistar Kyoto (WKY) allelic homozygosity, and hatched bars indicate areas containing a recombination. B, Interaction between rat chromosome (RNO)2 and RNO3 quantitative trait loci (QTLs) identified by pseudomarker 2-dimensional pairscan analysis. Interaction data are presented as a matrix (chromosome location × chromosome location) where the lower triangle represents the proportion of variance explained by a 2-QTL model with interactions (logarithm of odds ratio [LOD] full), and the upper triangle represents the difference of the variance explained by a 2-QTL model with interactions and an additive model (LODint). The bright red area represents high LOD score values resulting from interaction between D3Rat50 and D2Rat239. Color codes for LOD scores for both triangles are given in the scale to the right of the matrix.

It should be noted that the lower RNO3 boundaries between the single RNO3 and the bicongenic strain differ by approximately by 1.9 Mbp. This region is distinct (a distance of ≈132.8 Mbp) from the RNO3 QTL peak.

Hemodynamic Parameters of Congenic Strains

SP.WKYGla2a and SP.WKYGla3a rats demonstrated significantly reduced SBP and DBP at baseline (normal salt) and during 1% salt challenge (Figure 2A and 2B, Table S2). The SP.WKYGla3a strain confirmed the presence of the PP QTL previously identified by linkage analysis (Figure 2C), as evidenced by its significantly lower PP compared with SHRSP rats. PP in SP.WKYGla2a rats was also significantly lower than in SHRSP. The SP.WKYGla2a/3a bicongenic strain demonstrated a greater reduction in SBP and DBP than either of the single congenic strains, with BP levels similar to that of the normotensive WKY strain both at baseline and during salt challenge (Figure 2A and 2B). SP.WKYGla3a and SP.WKYGla2a/3a animals also demonstrated significantly reduced night–day PP difference during baseline and salt challenge compared with SHRSP (Figure 2C–2E). Night–day PP difference in SP.WKYGla2a animals during baseline was similar to SHRSP, but was significantly attenuated during salt challenge.

Figure 2.
Figure 2.

A, Systolic blood pressure (SBP), (B) diastolic BP (DBP), and (C) pulse pressure (PP) in stroke-prone spontaneously hypertensive (SHRSP), SP.WKYGla2a, SP.WKYGla3a, SP.WKYGla2a/3a, and Wistar Kyoto (WKY) rats measured by radiotelemetry. Data illustrated are weekly averaged night-time and daytime data points. D, Baseline and (E) salt-challenged night–day difference in PP. *P≤0.001 vs SHRSP.

Analysis of data using 1-way ANOVA with contrasts between SHRSP versus SP.WKYGla2a, SHRSP versus SP.WKYGla3a, and the interaction (SHRSP and SP.WKYGla2a/3a versus SP.WKYGla2a and SP.WKYGla3a) indicates that reduced SBP and DBP at baseline (Figure 3A and 3C) and during salt challenge (Figure 3B and 3D) observed in SP.WKYGla2a/3a rats were because of additive effects from RNO2 and RNO3. Statistically significant epistasis between RNO2 and RNO3 was observed for PP during baseline (Figure 3E) and salt challenge (Figure 3F).

Figure 3.
Figure 3.

Additive effects for systolic blood pressure (SBP) and diastolic blood pressure (DBP) during baseline (A and C) and 1% salt challenge (B and D). Greater-than-additive epistasis for pulse pressure (PP) during (E) baseline and (F) salt challenge.

Vascular Function

NO bioavailability in SHRSP and single congenic strains SP.WKYGla2a and SP.WKYGla3a were significantly lower than WKY rats (Figure 4A). NO bioavailability in the SP.WKYGla2a/3a strain was not significantly different compared with either SHRSP or WKY or between the single congenic strains and SHRSP. Relaxation responses to carbachol in SHRSP, SP.WKYGla2a, SP.WKYGla3a, and SP.WKYGla2a/3a strains were significantly less than WKY (Figure 4B). Relaxation response to carbachol in the SP.WKYGla2a strain was significantly improved compared with SHRSP.

Figure 4.
Figure 4.

Thoracic aorta NO bioavailability (A) and relaxation to carbachol (B) from 21-week-old salt-challenged animals. *P<0.001 compared with Wistar Kyoto (WKY); †P<0.001 compared with stroke-prone spontaneously hypertensive (SHRSP); n= 6 to 17/group.

Cardiac, Left Ventricular, and Renal Mass Indexes

CMI, LVMI, and RMI of 21-week-old salt-loaded rats are shown in Figure S1B, S1D, and S1F whereas the respective indices of control rats are shown in Figure S1A, S1C, and S1E. Control and salt-loaded SHRSP demonstrated significantly greater CMI, LVMI, and RMI compared with their respective treatment WKY rats. In parallel with observed BP reductions, the single and bicongenic strains demonstrated intermediate CMI and LVMI phenotypes compared with SHRSP and WKY parental strains. RMI was not significantly different between SHRSP and SP.WKYGla2a strains, but was significantly reduced in SP.WKYGla3a and SP.WKYGla2a/3a strains at baseline and during salt loading.

Renal Histopathology and Proteinuria

Extensive histopathologic changes, including vascular changes consistent with accelerated hypertension, were observed in kidneys from SHRSP and SP.WKYGla2a strains (Figure 5A). A range of mainly vascular changes was evident in these 2 strains, including hyperplasia, smooth muscle cell vaccuolation, hyalinosis, fibrinoid necrosis, hemorrhage, and thrombosis of both arteries and arterioles. Tubular atrophy and interstital fibrosis were commonly seen in conjunction with these vascular changes. Glomerular changes were rare and usually consisted of mild ischemic collapse of the glomerular tuft in the presence of the abovementioned vascular changes.

Figure 5.
Figure 5.

A, Representative renal histology of salt-challenged animals. Hematoxylin and eosin stained sections of kidneys from Wistar Kyoto (WKY), SP.WKYGla3a, and SP.WKYGla2a/3a rats show normal glomeruli (G), tubules (T), and arteries (A). Normal arterioles are not identifiable at this magnification. In contrast, sections of the kidneys of stroke-prone spontaneously hypertensive (SHRSP) and SP.WKYGla2a rats show arteries with fibrinoid necrosis and hemorrhage (A) as well as arterioles with hyperplasia (h) and hyalinosis (a). There is tubular atrophy (T), but the glomeruli (G) show only mild ischemic collapse. Magnification, ×100; scale bar, 100 μm. Renal histopathologic scores (n=8–11/group) during (B) baseline and (C) salt challenge; and proteinuria (n=5–11/group) during (D) baseline and (E) salt challenge. *P<0.001.

Renal pathology scores for single and bicongenic strains at baseline (Figure 5B) and during salt challenge (Figure 5C) were lower than SHRSP but only reached statistical significance in SP.WKYGla3a and SP.WKYGla2a/3a rats. The scores of congenic strains were significantly higher than WKY when salt challenged. SP.WKYGla2a rats also had significantly higher scores compared with SP.WKYGla3a and SP.WKYGla2a/3a rats.

At baseline, there was no significant difference in proteinuria between the parental and congenic strains. During salt challenge, SHRSP and SP.WKYGla2a rats demonstrated higher levels of proteinuria compared with SP.WKYGla3a, SP.WKYGla2a/3a, and WKY strains, reaching significance onlyin SHRSP. There were no differences in proteinuria between SHRSP and SP.WKYGla2a rats or among SP.WKYGla3a, SP.WKYGla2a/3a, and WKY rats.

Discussion

In this study, phenotypic analysis of the SP.WKYGla3a congenic strain has confirmed the PP and SBP QTLs previously identified by linkage analysis on RNO3. We have also shown that interactions between PP QTL on RNO2 and RNO3 are epistatic at baseline and during 1% salt challenge. Further phenotypic assessment of the single and bicongenic strains indicates that QTL on RNO3 are responsible for salt-induced renal pathology, whereas QTL on RNO2 seem to have greater impact on vascular function.

RNO3 has previously been shown to contain loci, which significantly impact BP regulation particularly in the Dahl S rat,21–25 and also in other rat strains.26,27 Although much of the genetic variation underlying hypertension is likely to be distinct between independently generated inbred rat strains, the overlap between the salt-induced renal pathology observed in the Dahl S model and the salt-loaded SHRSP described here suggests common implicated loci. Our data therefore confirm the importance of this region, and also for the first time, demonstrate an important role in the regulation of PP variability during salt loading. Monitoring of PP by radiotelemetry allows assessment of daytime and night-time (diurnal) fluctuations in PP. Our results identified striking PP variability during salt challenge in the SHRSP, which was significantly reduced in the RNO3 congenic and bicongenic strains. The inability of the SHRSP to tightly regulate diurnal PP variation may impact on end-organ damage,28,29 because adverse cardiovascular consequences are shown to depend not only on absolute BP values, but also on BP variability.30 In particular, the development, progression, and severity of renal damage have been associated with BP variation and instability.29,31 It is suggested that long-term increase in PP results in higher-than-normal dissipation of pulsatile energy in the microcirculation of the kidney. Consequently, the relatively high level of pressure required within the glomerular arterioles to ensure high glomerular filtration rate may expose the glomerular capillaries to potentially damaging effects of increased PP,29 leading to renal vascular damage.

The greater-than-additive interactions observed for PP in the bicongenic strain highlight the complex gene–environment relationships that exist in complex cardiovascular traits. Evidence for epistasis has previously been demonstrated for BP QTL located on different genetic regions of the same chromosome8,32 and among loci located on different chromosomes.4,6,7,9–11 The identification of such interactions can be used to infer genetic networks affecting complex traits and greatly assist in the detection of the underlying biological mechanisms.33,34 The combined effects of introgressing RNO2 and RNO3 genetic intervals essentially normalizes SBP, DBP, and PP parameters in the bicongenic strain. This result, however, does not provide conclusive evidence that RNO2 and RNO3 QTL are entirely responsible for BP elevation in the SHRSP strain. Because of complex interactive relationships, the sum of the phenotypic effects of individual QTLs rarely explain the actual differences between the parental strains.29,35,36 Moreover, because the introgressed congenic intervals encompass almost the whole of each respective chromosome, making the strains almost consomic, it is highly likely that the observed phenotypic effects are the result of several interacting loci. Dissection of these large regions will be an essential next step to identify and localize these potential interactions. One caveat to the interpretation of our results is that the lower RNO3 boundaries between the single RNO3 and the bicongenic strain differ by ≈1.9 Mbp. Although this difference has the potential to explain the observed phenotypic differences, our pairscan interaction analysis confirms the location of the RNO3 QTL to ≈16.6 Mbp, which is distinct from the differential lower boundary segment (between 149.5 and 151.4 Mbp). Further dissection of the congenic interval will allow the potential impact of this region to be confirmed or discounted.

Comparison of aortic vascular responses in SP.WKYGla2a and SP.WKYGla3a strains indicates that QTL on RNO2 have greater impact on vascular function than loci on RNO3. Our previous studies using RNO2 congenic and subcongenic strains,13–15 which encompass the implicated BP locus at D2Rat239 (Figure 1), showed reduced vascular oxidative stress14 and inflammation.15 These findings support the hypothesis that the RNO2 locus regulates BP through vascular functions, partly through vascular redox balance.

BP-independent QTL for CMI have previously been reported on RNO2 and RNO3.37–40 In the present study we observed significant equivalent reductions in CMI and LVMI in SP.WKYGla2a and SP.WKYGla3a strains compared with the SHRSP. However, these changes in heart mass occurred in parallel with the observed BP reductions during baseline and salt-loading periods. Dissection of the congenic intervals will be necessary to establish whether the reduction in cardiac hypertrophy is secondary to the lowered BP or whether it is determined by distinct QTL regulating cardiac mass. RMI and salt-induced renal damage (identified by histopathology scores and proteinuria) were significantly reduced in the SP.WKYGla3a and SP.WKYGla2a/3a strains, but not in the SP.WKYGla2a strain. The significant difference in renal pathology despite similar BP reduction suggests that the reduced renal pathological changes in RNO3 congenic strains are not simply because of hemodynamic changes. These results suggest that RNO3 QTL are more important for salt-induced renal damage than loci on RNO2. Dissection of the RNO3 congenic interval and identification of the underlying causative genetic elements will be necessary to determine the mechanistic basis of the observed PP epistasis and salt-induced renal damage in the SHRSP.

Perspectives

RNO3 congenic and bicongenic strains have confirmed the importance of the RNO3 congenic interval on PP variability and end-organ damage. These strains will allow interrogation of complex gene–gene and gene–environment interactions contributing to salt-sensitive hypertension and renal pathology in the SHRSP. Identification of the underlying pathological mechanisms will allow discovery of new therapeutic targets for human essential hypertension and salt-induced renal damage.

Sources of Funding

This work was supported by the British Heart Foundation Chair and Program Grant funding (CH98001 and RG/07/005), the Wellcome Trust Cardiovascular Functional Genomics Initiative (066780/Z/01/Z), and the European Union Sixth Framework Program Integrated Project (LSHG_CT 2005–019015 EURATools) awarded to A.F. Dominiczak.

Disclosures

None.

Footnotes

  • Received December 18, 2012.
  • Revision received January 15, 2013.
  • Accepted April 10, 2013.

References

  1. 1.↵
    1. Marteau JB,
    2. Zaiou M,
    3. Siest G,
    4. Visvikis-Siest S
    . Genetic determinants of BP regulation. J Hypertens. 2005; 23:2127–2143.
    OpenUrlPubMed
  2. 2.↵
    1. Ehret GB,
    2. Munroe PB,
    3. Rice KM,
    4. Bochud M,
    5. Johnson AD,
    6. Chasman DI,
    7. et al
    . Genetic variants in novel pathways influence BP and cardiovascular disease risk. Nature. 2011;478:103–109.
    OpenUrlCrossRefPubMed
  3. 3.↵
    1. Wang X,
    2. Prins BP,
    3. Sõber S,
    4. Laan M,
    5. Snieder H
    . Beyond genome-wide association studies: new strategies for identifying genetic determinants of hypertension. Curr Hypertens Rep. 2011;13:442–451.
    OpenUrlCrossRefPubMed
  4. 4.↵
    1. Deng Y,
    2. Rapp JP
    . Cosegregation of BP with angiotensin converting enzyme and atrial natriuretic peptide receptor genes using Dahl salt-sensitive rats. Nat Genet. 1992; 1:267–272.
    OpenUrlCrossRefPubMed
  5. 5.↵
    1. Dutil J,
    2. Eliopoulos V,
    3. Tremblay J,
    4. Hamet P,
    5. Charron S,
    6. Deng AY
    . Multiple quantitative trait loci for BP interacting epistatically and additively on Dahl rat chromosome 2. Hypertension. 2005;45:557–564.
    OpenUrlAbstract/FREE Full Text
  6. 6.↵
    1. Rapp JP,
    2. Garrett MR,
    3. Deng AY
    . Construction of a double congenic strain to prove an epistatic interaction on BP between rat chromosomes 2 and 10. J Clin Invest. 1998;101:1591–1595.
    OpenUrlCrossRefPubMed
  7. 7.↵
    1. Monti J,
    2. Plehm R,
    3. Schulz H,
    4. Ganten D,
    5. Kreutz R,
    6. Hübner N
    . Interaction between blood pressure quantitative trait loci in rats in which trait variation at chromosome 1 is conditional upon a specific allele at chromosome 10. Hum Mol Genet. 2003;12:435–439.
    OpenUrlAbstract/FREE Full Text
  8. 8.↵
    1. Chauvet C,
    2. Charron S,
    3. Menard A,
    4. Xiao C,
    5. Roy J,
    6. Deng AY
    . Submegabase resolution of epistatically interacting quantitative trait loci for BP applicable for essential hypertension. J Hypertens. 2008;26:893–901.
    OpenUrlCrossRefPubMed
  9. 9.↵
    1. Cicila GT,
    2. Morgan EE,
    3. Lee SJ,
    4. Farms P,
    5. Yerga-Woolwine S,
    6. Toland EJ,
    7. Ramdath RS,
    8. Gopalakrishnan K,
    9. Bohman K,
    10. Nestor-Kalinoski AL,
    11. Khuder SA,
    12. Joe B
    . Epistatic genetic determinants of blood pressure and mortality in a salt-sensitive hypertension model. Hypertension. 2009;53:725–732.
    OpenUrlAbstract/FREE Full Text
  10. 10.↵
    1. Kreutz R,
    2. Struk B,
    3. Rubattu S,
    4. Hübner N,
    5. Szpirer J,
    6. Szpirer C,
    7. Ganten D,
    8. Lindpaintner K
    . Role of the α-, β-, and γ-subunits of epithelial sodium channel in a model of polygenic hypertension. Hypertension. 1997;29:131–136.
    OpenUrlAbstract/FREE Full Text
  11. 11.↵
    1. Kreutz R,
    2. Stock P,
    3. Struk B,
    4. Lindpaintner K
    . The Y chromosome. Epistatic and ecogenetic interactions in genetic hypertension. Hypertension. 1996;28:895–897.
    OpenUrlAbstract/FREE Full Text
  12. 12.↵
    1. Clark JS,
    2. Jeffs B,
    3. Davidson AO,
    4. Lee WK,
    5. Anderson NH,
    6. Bihoreau MT,
    7. Brosnan MJ,
    8. Devlin AM,
    9. Kelman AW,
    10. Lindpaintner K,
    11. Dominiczak AF
    . Quantitative trait loci in genetically hypertensive rats. Possible sex specificity. Hypertension. 1996;28:898–906.
    OpenUrlAbstract/FREE Full Text
  13. 13.↵
    1. McBride MW,
    2. Carr FJ,
    3. Graham D,
    4. Anderson NH,
    5. Clark JS,
    6. Lee WK,
    7. Charchar FJ,
    8. Brosnan MJ,
    9. Dominiczak AF
    . Microarray analysis of rat chromosome 2 congenic strains. Hypertension. 2003;41:847–853.
    OpenUrlAbstract/FREE Full Text
  14. 14.↵
    1. McBride MW,
    2. Brosnan MJ,
    3. Mathers J,
    4. McLellan LI,
    5. Miller WH,
    6. Graham D,
    7. Hanlon N,
    8. Hamilton CA,
    9. Polke JM,
    10. Lee WK,
    11. Dominiczak AF
    . Reduction of Gstm1 expression in the stroke-prone spontaneously hypertension rat contributes to increased oxidative stress. Hypertension. 2005;45:786–792.
    OpenUrlAbstract/FREE Full Text
  15. 15.↵
    1. Graham D,
    2. McBride MW,
    3. Gaasenbeek M,
    4. Gilday K,
    5. Beattie E,
    6. Miller WH,
    7. McClure JD,
    8. Polke JM,
    9. Montezano A,
    10. Touyz RM,
    11. Dominiczak AF
    . Candidate genes that determine response to salt in the stroke-prone spontaneously hypertensive rat: congenic analysis. Hypertension. 2007;50:1134–1141.
    OpenUrlAbstract/FREE Full Text
  16. 16.↵
    1. Jeffs B,
    2. Negrin CD,
    3. Graham D,
    4. Clark JS,
    5. Anderson NH,
    6. Gauguier D,
    7. Dominiczak AF
    . Applicability of a “speed” congenic strategy to dissect BP quantitative trait loci on rat chromosome 2. Hypertension. 2000;35:179–187.
    OpenUrlAbstract/FREE Full Text
  17. 17.↵
    1. Kerr S,
    2. Brosnan MJ,
    3. McIntyre M,
    4. Reid JL,
    5. Dominiczak AF,
    6. Hamilton CA
    . Superoxide anion production is increased in a model of genetic hypertension: role of the endothelium. Hypertension. 1999;33:1353–1358.
    OpenUrlAbstract/FREE Full Text
  18. 18.↵
    1. Mandal AK,
    2. Bell RD,
    3. Parker D,
    4. Nordquist JA,
    5. Lindeman RD
    . An analysis of the relationship of malignant lesions of the kidney to hypertension. Microvasc Res. 1977;14:279–292.
    OpenUrlCrossRefPubMed
  19. 19.↵
    1. Sen S,
    2. Churchill GA
    . A statistical framework for quantitative trait mapping. Genetics. 2001;159:371–387.
    OpenUrlAbstract/FREE Full Text
  20. 20.↵
    1. Jagodic M,
    2. Marta M,
    3. Becanovic K,
    4. Sheng JR,
    5. Nohra R,
    6. Olsson T,
    7. Lorentzen JC
    . Resolution of a 16.8-Mb autoimmunity-regulating rat chromosome 4 region into multiple encephalomyelitis quantitative trait loci and evidence for epistasis. J Immunol. 2005;174:918–924.
    OpenUrlAbstract/FREE Full Text
  21. 21.↵
    1. Cicila GT,
    2. Choi C,
    3. Dene H,
    4. Lee SJ,
    5. Rapp JP
    . Two BP/cardiac mass quantitative trait loci on chromosome 3 in Dahl rats. Mamm Genome. 1999; 10:112–116.
    OpenUrlCrossRefPubMed
  22. 22.↵
    1. Palijan A,
    2. Dutil J,
    3. Deng AY
    . Quantitative trait loci with opposing BP effects demonstrating epistasis on Dahl rat chromosome 3. Physiol Genomics. 2003; 15:1–8.
    OpenUrlAbstract/FREE Full Text
  23. 23.↵
    1. Lee SJ,
    2. Liu J,
    3. Westcott AM,
    4. Vieth JA,
    5. DeRaedt SJ,
    6. Yang S,
    7. Joe B,
    8. Cicila GT
    . Substitution mapping in dahl rats identifies two distinct BP quantitative trait loci within 1.12- and 1.25-mb intervals on chromosome 3. Genetics. 2006; 174:2203–2213.
    OpenUrlAbstract/FREE Full Text
  24. 24.↵
    1. Stoll M,
    2. Cowley AW Jr.,
    3. Tonellato PJ,
    4. Greene AS,
    5. Kaldunski ML,
    6. Roman RJ,
    7. Dumas P,
    8. Schork NJ,
    9. Wang Z,
    10. Jacob HJ
    . A genomic-systems biology map for cardiovascular function. Science. 2001;294:1723–1726.
    OpenUrlAbstract/FREE Full Text
  25. 25.↵
    1. Moreno C,
    2. Dumas P,
    3. Kaldunski ML,
    4. Tonellato PJ,
    5. Greene AS,
    6. Roman RJ,
    7. Cheng Q,
    8. Wang Z,
    9. Jacob HJ,
    10. Cowley AW Jr.
    . Genomic map of cardiovascular phenotypes of hypertension in female Dahl S rats. Physiol Genomics. 2003;15:243–257.
    OpenUrlAbstract/FREE Full Text
  26. 26.↵
    1. O’Meara CC,
    2. Lazar J,
    3. Hoffman M,
    4. Moreno C,
    5. Jacob HJ
    . Refined mapping of the renal failure RF-3 quantitative trait locus. J Am Soc Nephrol. 2011;22:518–525.
    OpenUrlAbstract/FREE Full Text
  27. 27.↵
    1. Hamet P,
    2. Pausova Z,
    3. Dumas P,
    4. Sun YL,
    5. Tremblay J,
    6. Pravenec M,
    7. Kunes J,
    8. Krenova D,
    9. Kren V
    . Newborn and adult recombinant inbred strains: a tool to search for genetic determinants of target organ damage in hypertension. Kidney Int. 1998;53:1488–1492.
    OpenUrlCrossRefPubMed
  28. 28.↵
    1. Safar ME,
    2. Lacolley P
    . Disturbance of macro- and microcirculation: relations with pulse pressure and cardiac organ damage. Am J Physiol Heart Circ Physiol. 2007;293:H1–H7.
    OpenUrlAbstract/FREE Full Text
  29. 29.↵
    1. Safar ME,
    2. Nilsson PM,
    3. Blacher J,
    4. Mimran A
    . Pulse pressure, arterial stiffness, and end-organ damage. Curr Hypertens Rep. 2012;14:339–344.
    OpenUrlCrossRefPubMed
  30. 30.↵
    1. Rothwell PM,
    2. Does BP
    variability modulate cardiovascular risk? Curr Hypertens Rep. 2011; 13:177–186.
    OpenUrlCrossRefPubMed
  31. 31.↵
    1. Parati G,
    2. Ochoa JE,
    3. Bilo G
    . BP variability, cardiovascular risk, and risk for renal disease progression. Curr Hypertens Rep. 2012; 14:421–431.
    OpenUrlCrossRefPubMed
  32. 32.↵
    1. Charron S,
    2. Duong C,
    3. Ménard A,
    4. Roy J,
    5. Eliopoulos V,
    6. Lambert R,
    7. Deng AY
    . Epistasis, not numbers, regulates functions of clustered Dahl rat quantitative trait loci applicable to human hypertension. Hypertension. 2005;46:1300–1308.
    OpenUrlAbstract/FREE Full Text
  33. 33.↵
    1. Huang W,
    2. Richards S,
    3. Carbone MA,
    4. et al
    . Epistasis dominates the genetic architecture of Drosophila quantitative traits. Proc Natl Acad Sci U S A. 2012;109:15553–15559.
    OpenUrlAbstract/FREE Full Text
  34. 34.↵
    1. Phillips PC
    . Epistasis–the essential role of gene interactions in the structure and evolution of genetic systems. Nat Rev Genet. 2008;9:855–867.
    OpenUrlCrossRefPubMed
  35. 35.↵
    1. Shao H,
    2. Burrage LC,
    3. Sinasac DS,
    4. Hill AE,
    5. Ernest SR,
    6. O’Brien W,
    7. Courtland HW,
    8. Jepsen KJ,
    9. Kirby A,
    10. Kulbokas EJ,
    11. Daly MJ,
    12. Broman KW,
    13. Lander ES,
    14. Nadeau JH
    . Genetic architecture of complex traits: large phenotypic effects and pervasive epistasis. Proc Natl Acad Sci U S A. 2008;105:19910–19914.
    OpenUrlAbstract/FREE Full Text
  36. 36.↵
    1. Romano GH,
    2. Gurvich Y,
    3. Lavi O,
    4. Ulitsky I,
    5. Shamir R,
    6. Kupiec M
    . Different sets of QTLs influence fitness variation in yeast. Mol Syst Biol. 2010;6:346.
    OpenUrlAbstract/FREE Full Text
  37. 37.↵
    1. Innes BA,
    2. McLaughlin MG,
    3. Kapuscinski MK,
    4. Jacob HJ,
    5. Harrap SB
    . Independent genetic susceptibility to cardiac hypertrophy in inherited hypertension. Hypertension. 1998;31:741–746.
    OpenUrlAbstract/FREE Full Text
  38. 38.↵
    1. Siegel AK,
    2. Planert M,
    3. Rademacher S,
    4. Mehr AP,
    5. Kossmehl P,
    6. Wehland M,
    7. Stoll M,
    8. Kreutz R
    . Genetic loci contribute to the progression of vascular and cardiac hypertrophy in salt-sensitive spontaneous hypertension. Arterioscler Thromb Vasc Biol. 2003;23:1211–1217.
    OpenUrlAbstract/FREE Full Text
  39. 39.↵
    1. Inomata H,
    2. Watanabe T,
    3. Iizuka Y,
    4. Liang YQ,
    5. Mashimo T,
    6. Nabika T,
    7. Ikeda K,
    8. Yanai K,
    9. Gotoda T,
    10. Yamori Y,
    11. Isobe M,
    12. Kato N
    . Identification of quantitative trait loci for cardiac hypertrophy in two different strains of the spontaneously hypertensive rat. Hypertens Res. 2005;28:273–281.
    OpenUrlCrossRefPubMed
  40. 40.↵
    1. McDermott-Roe C,
    2. Ye J,
    3. Ahmed R,
    4. et al
    . Endonuclease G is a novel determinant of cardiac hypertrophy and mitochondrial function. Nature. 2011;478:114–118.
    OpenUrlCrossRefPubMed

Novelty and Significance

What Is New?

  • This is the first study to investigate and confirm epistasis between previously identified blood pressure quantitative trait loci on rat chromosome (RNO)2 and RNO3 in the stroke-prone spontaneously hypertensive rat.

  • We identify, for the first time, an important role for an RNO3 locus on regulation of pulse pressure variability during salt loading.

What Is Relevant?

  • Our data suggest that RNO3 blood pressure quantitative trait loci have a greater impact on salt-induced renal pathological changes than the quantitative trait loci on RNO2.

  • Dissection of the RNO3 congenic interval and identification of the underlying causative genetic elements will allow the mechanistic basis of the observed blood pressure epistasis and salt-induced renal pathological changes to be determined.

Summary

RNO3 congenic and bicongenic strains confirm the genetic complexity of blood pressure regulation and salt-induced renal changes.

View Abstract

This Issue

Jump to

Article Tools

Share this Article

  • Email
  • Interaction Between Chromosome 2 and 3 Regulates Pulse Pressure in the Stroke-Prone Spontaneously Hypertensive RatNovelty and Significance
    H.H. Caline Koh-Tan, Martin W. McBride, John D. McClure, Elisabeth Beattie, Barbara Young, Anna F. Dominiczak and Delyth Graham
    Hypertension. 2013;62:33-40, originally published June 12, 2013
    https://doi.org/10.1161/HYPERTENSIONAHA.111.00814
    del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo

Related Articles

Cited By...

Subjects