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Genes to Cells (2009) 14, 69-77. doi:10.1111/j.1365-2443.2008.01252.x
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Genome-wide histone methylation profile for heart failure

 Ruri Kaneda1,2, Shuji Takada1, Yoshihiro Yamashita1, Young Lim Choi1, Mutsuko Nonaka-Sarukawa2, Manabu Soda1, Yoshio Misawa3, Tadashi Isomura4, Kazuyuki Shimada2 and Hiroyuki Mano1,5,*

Divisions of
1 Functional Genomics, Jichi Medical University, Tochigi 329-0498, Japan
2 Cardiovascular Medicine, Jichi Medical University, Tochigi 329-0498, Japan
3 Cardiovascular Surgery, Jichi Medical University, Tochigi 329-0498, Japan
4 Hayama Heart Center, Kanagawa 240-0116, Japan
5 CREST, Japan Science and Technology Agency, Saitama 332-0012, Japan


   Abstract
Top
 Abstract
Introduction
 Results
 Discussion
 Experimental procedures
 References
 
Epigenetic alterations are implicated in the development of cardiac hypertrophy and heart failure, but little is known of which epigenetic changes in which regions of the genome play such a role. We now show that trimethylation of histone H3 on lysine-4 (K4TM) or lysine-9 (K9TM) is markedly affected in cardiomyocytes in association with the development of heart failure in a rat disease model. High-throughput pyrosequencing performed with ChIP products for K4TM or K9TM prepared from human left ventricular tissue with retained or damaged function also revealed that protein-coding genes located in the vicinity of K4TM marks differ between functional and disabled myocytes, yet both sets of genes encode proteins that function in the same signal transduction pathways for cardiac function, indicative of differential K4TM marking during the development of heart failure. However, K9TM mark-profile was less dependent on the disease status compared to that of K4TM. Our data collectively reveal global epigenetic changes in cardiac myocytes associated with heart failure.


   Introduction
Top
 Abstract
 Introduction
Results
 Discussion
 Experimental procedures
 References
 
A variety of conditions, including pressure or volume overload in the cardiovascular system and remodeling of the left ventricle of the heart after ischemic damage, result in heart failure, which is characterized by a reduction in contractile ability and a decrease in the number of viable myocytes in the heart (James et al. 2000). Treatment of heart failure remains problematic, and this condition is thus still one of the leading causes of human death (Braunwald 1997).

Epigenetic status has been linked to cardiac hypertrophy and heart failure. The histone acetyltransferase activity of CREB-binding protein (CBP) and p300 is thus required for the induction of hypertrophic changes in cardiac muscle cells by phenylephrine (Gusterson et al. 2003). Consistent with this observation, inhibition of histone deacetylase (HDAC) activity results in an increase in the size of cardiac muscle cells (Iezzi et al. 2004). Furthermore, HDACs of class II (HDAC4, -5, -7, and -9) suppress cardiac hypertrophy in part by binding to and inhibiting the activity of myocyte enhancer factor 2 (Zhang et al. 2002). Induction of the atrial natriuretic peptide gene is associated with acetylation of histones (H3 and H4) located in the 3' untranslated region of the gene (Kuwahara et al. 2001). Histones bound to the β-myosin heavy chain gene have also been shown to be targeted by histone acetyltransferases in cardiomyocytes (Zhang et al. 2002). Moreover, dynamic regulation of other histone modifications has been demonstrated in cardiac myocytes (Illi et al. 2005; Bingham et al. 2007).

It remains to be established, however, (i) which epigenetic marks are dysregulated in association with heart failure in vivo, (ii) which regions of the human genome are susceptible to such epigenetic changes, and (iii) how epigenetic dysregulation affects the expression of protein-coding or other genes. To address these issues, we have now studied an animal model of congestive heart failure (CHF), the Dahl salt-sensitive rat (Rapp et al. 1989), and found that two histone modifications are markedly affected in cardiac myocytes during the development of CHF. We further confirmed our findings in human left ventricular (LV) myocytes with the use of chromatin immunoprecipitation (ChIP) coupled to pyrosequencing. Our results have revealed dynamic histone modifications in the vicinity of a subset of protein-coding genes in the human genome, which directly participate in regulation of the contraction of cardiac myocytes.


   Results
Top
 Abstract
 Introduction
 Results
Discussion
 Experimental procedures
 References
 
Histone modifications in the heart of Dahl rats

We prepared LV myocytes from Dahl salt-sensitive rats, which are genetically intolerant to excessive salt intake (Rapp et al. 1989). A high-sodium diet thus induces systemic hypertension and cardiac hypertrophy in Dahl rats within a few weeks. These changes are followed within a few months by the development of CHF and death. We isolated cardiac myocytes from rats with CHF (fed a high-sodium diet) as well as from age-matched animals with a normal heart (fed a low-sodium diet), and we subjected these cells to ChIP with antibodies to acetylated histone H3 (H3Ac), acetylated histone H4 (H4Ac), histone H3 dimethylated on lysine-4 (K4DM), histone H3 trimethylated on lysine-4 (K4TM), histone H3 dimethylated on lysine-9 (K9DM), histone H3 trimethylated on lysine-9 (K9TM), histone H4 trimethylated on lysine-20 (K20TM), or histone H3 dimethylated on lysine-27 (K27DM). The ChIP products as well as cRNA prepared from the normal or failed hearts were then individually subjected to hybridization with high-density oligonucleotide microarrays (Affymetrix Rat Genome 230 2.0 GeneChip) originally developed for expression profiling of rat genes.

Pearson's correlation coefficient for the signal intensity of all probe sets with a "Present" call (by Affymetrix GCOS software) in the normal heart (n = 13 914) was 0.873 in the cRNA hybridizations for normal and failed hearts (Fig. 1), indicative of a strong correlation in the expression level of most genes between the two samples. Consistent with this observation, the signal intensity for all probe sets with a positive value in the H3Ac ChIP products from the normal heart (n = 12 027) was highly correlated between these products from normal and failed hearts (r = 0.724). A similar strong correlation between the two groups was observed for H4Ac.


Figure 1
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  		Figure 1  Comparison of epigenetic profiles between normal and failed rat hearts. The expression level of each probe set on oligonucleotide microarrays was compared between total cRNA from normal (x axis) or failed (y axis) hearts by calculation of Pearson's correlation coefficient (r). ChIP-on-chip data for H3Ac, H4Ac, K4DM, K4TM, K9DM, K9TM, K20TM, and K27DM are similarly compared.

 
Unexpectedly, however, despite the strong correlation (r = 0.856) apparent for K4DM, only a weak negative correlation (r = –0.097) was detected for the K4TM mark between normal and failed hearts, indicative of marked differences in the associated gene sets. Similarly, although a strong correlation was observed for K9DM (r = 0.558), a weak negative correlation (r = –0.251) was apparent for K9TM. Hybridization levels were positively correlated between normal and failed hearts for K20TM and K27DM.

Thus, among the epigenetic marks examined, K4TM and K9TM were the histone modifications most affected in heart failure. Although differences in functional roles and genomic distributions between K4DM and K4TM have been described (Santos-Rosa et al. 2002; Bernstein et al. 2005), little has been known of such differential roles for the methylation level of lysine-9 of histone H3.

K4TM and K9TM profiles in the human heart

We next attempted to identify the genomic regions associated with the K4TM and K9TM marks in human cardiac myocytes. ChIP products for K4TM or K9TM were prepared from a mixture of LV tissue specimens from four individuals with retained pumping function [LV ejection fraction (EF) of 65.5 ± 7.6%, mean ± SD] or from four individuals with CHF (LVEF of 19.8 ± 5.7%) caused by dilated cardiomyopathy (Table 1). The ChIP products were subjected to pyrosequencing with the Genome Sequencer 20 system (Roche). In this "ChIP-to-seq" experiment, 96 069, 95 596, 116 267, and 96 734 reads were obtained for the K4TM products for specimens with retained LV ejection fraction (HighEF), the K4TM products for CHF, the K9TM products for HighEF, and the K9TM products for CHF, respectively. After quality-filtering, we isolated an average of 36 279 reads per sample, for each of which a single hit with a highest matching score was identified in the human genome sequence (the hg18 assembly of the Genome Bioinformatics Group, University of California at Santa Cruz) (Table S1 in Supporting Information). We thus focused on these reads for further analysis.


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  		Table 1  Clinical characteristics of the subjects who provided specimens for the study
 
Many regions of the genome were identified in which multiple sequence reads mapped closely to each other. We therefore defined a "cluster" as a group of sequence reads localized within a distance of 1 kbp in the human genome (Fig. 2A). A total of 94 202 clusters was identified for all four samples, and 18 725 of these clusters, referred to as "high clusters," contained ≥ 2 sequence reads in ≥ 1 sample (see Table S2 in Supporting Information).


Figure 2
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  		Figure 2  High clusters in K4TM and K9TM ChIP-to-seq data. (A) Groups of sequence reads that map to the human genome within a distance of 1 kbp are defined as "clusters," which are further denoted as "high clusters" when the read number in the cluster is ≥ 2 in ≥ 1 sample. (B) Numbers of high clusters with a read number of ≥ 5 for K4TM or K9TM in HighEF or CHF samples (shaded boxes). The numbers of such clusters shared between any pair of samples is also indicated (open boxes).

 
We then examined histone modification at the high clusters for specificity of the epigenetic mark (K4TM or K9TM) and disease status (HighEF or CHF). Among the high clusters, 875 had ≥ 5 reads in the K4TM product for HighEF, 818 had ≥ 5 reads in the K4TM product for CHF, 269 had ≥ 5 reads in the K9TM product for HighEF, and 229 had ≥ 5 reads in the K9TM product for CHF (Fig. 2B). Only a few dozen of such high clusters were shared between any pair of samples, indicating the existence of disease-specific as well as methylation site-specific epigenetic profiles. Therefore, despite the heterogeneity in the cause of CHF (sustained systemic hypertension or dilated cardiomyopathy), both the Dahl rat and human data sets revealed a marked difference in the K4TM and K9TM epigenetic profiles between normal and failed hearts. Such specificity is further visualized for human chromosome 1 in Fig. S1 in Supporting Information. In contrast, the profile of read number per cluster was similar among the four groups of human ChIP products (see Fig. S2 in Supporting Information).

Genes mapped closely to disease-dependent clusters

We then isolated disease status-specific high clusters from the data set. A total of 836 high clusters was found to contain ≥ 5 reads in the K4TM products for HighEF but ≤ 1 read in those for CHF (HighEF-specific K4TM clusters); 407 RefSeq genes mapped to within ≤ 5 kbp of these clusters (Table 2). Similarly, 786 high clusters were found to be specific for K4TM and CHF (≤ 1 read in the K4TM products for HighEF but ≥ 5 reads in those for CHF). Smaller numbers of disease-dependent clusters were identified for the K9TM mark (220 HighEF-specific and 196 CHF-specific). These disease-dependent clusters were widely distributed throughout human chromosomes and showed little overlap (see Fig. S3 in Supporting Information).


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  		Table 2  Disease-specific high clusters
 
We examined whether the protein products of RefSeq genes that mapped in the vicinity (a distance of ≤ 5 kbp) of disease-dependent clusters function in canonical intracellular signaling pathways with the use of Ingenuity Pathway Analysis software (Ingenuity Systems; http://www.ingenuity.com). Analysis of the RefSeq genes associated with the disease-dependent K4TM clusters identified 12 canonical pathways that were significantly overrepresented (P < 0.05, Fisher's exact test) in HighEF-specific clusters and 20 pathways overrepresented in CHF-specific clusters. Many of the pathways (n = 10) were overrepresented in both HighEF-K4TM and CHF-K4TM clusters, almost all of which (including those for calcium signaling, synaptic long-term regulation, and nitric oxide signaling) are related to cardiac function (Fig. 3A).


Figure 3
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  		Figure 3  Analysis of genes that map in the vicinity of disease-dependent high clusters. (A) Canonical signaling pathways overrepresented in the HighEF-specific or CHF-specific high clusters for the K4TM ChIP products are listed with the corresponding –log(P value) score. (B) Canonical signaling pathways overrepresented in the HighEF-specific or CHF-specific high clusters for the K9TM ChIP products are listed with the corresponding –log(P value) score. (C) Venn diagram for comparison of transcripts associated specifically with HighEF or CHF status and those encoded by genes that map within a distance of < 5 kbp relative to a high cluster.

 
Consistent with the disease-dependent selection of the clusters, the HighEF-associated and CHF-associated genes were distinct even within the same pathways. The canonical pathway for synaptic long-term potentiation, for example, contains the products of eight HighEF-associated and 12 CHF-associated genes, the interactions among which are shown in Fig. S4 in Supporting Information. Although genes corresponding to the calmodulin complex are present in both gene sets, these genes differ between the HighEF set (CALM1) and the CHF set (CALM3).

In addition to the proteins of the canonical signaling pathways, many products of the genes in the vicinity of disease-dependent high clusters for K4TM are functionally or physically networked. One such network comprises 34 proteins, 18 of which are encoded by HighEF-associated genes and 16 by CHF-associated genes (Fig. S5 in Supporting Information). Again, the genes for some complexes associated with both gene sets are distinct; those for the ATPase complex, for instance, include that for ATP1B1 in the HighEF-associated set and that for ATP5C1 in the CHF-associated set. Gene products in this network are substantially enriched in those implicated in cardiovascular disease.

In contrast to the K4TM-specific clusters, only a few canonical signaling pathways are linked to the RefSeq genes localized in the vicinity of K9TM-specific clusters. This difference is due in part to the small number of high clusters that contain disease-dependent reads for K9TM. Whereas the numbers of high clusters for HighEF specimens were similar between K4TM and K9TM products (n = 6547 and 5594, respectively), the numbers of disease-dependent clusters for the K9TM mark were only approximately 25% of those for the K4TM mark (Table 2). Seven canonical signaling pathways were overrepresented (P < 0.05, Fisher's exact test) in the genes associated with the HighEF-K9TM clusters, whereas only one such pathway was overrepresented in those associated with the CHF-K9TM clusters (Fig. 3B). The network containing the most disease-dependent K9TM-associated gene products is centered on transforming growth factor β1 (TGFB1) and the tumor suppressor p53 (TP53), implicating K9TM-related regulation in cell death in the heart (see Fig. S6 in Supporting Information).

Our analysis thus revealed differential regulation of K4TM modification for genes related to cardiac function. To examine whether such epigenetic regulation plays a direct role in gene transcription, we performed gene expression profiling with Human Genome U133 Plus 2.0 arrays (Affymetrix) for the individual specimens (four for HighEF and four for CHF) used in the ChIP experiments. From the data obtained for 54 675 probe sets and the eight specimens, we selected HighEF-specific probe sets according to the following criteria: (i) the ratio of the mean expression level between HighEF and CHF was ≥ 3, and (ii) the mean expression level in HighEF was ≥ 10 arbitrary units (U). These criteria resulted in the isolation of 67 probe sets (see Table S3 in Supporting Information). CHF-specific probe sets were also selected on the basis of a CHF/HighEF ratio for mean expression level of ≥ 3 and a mean expression level in CHF of ≥ 10 U, resulting in the identification of 80 probe sets (see Table S4 in Supporting Information). A total of 16 152 of the transcripts measured with the U133 Plus 2.0 arrays mapped within a distance of ≤ 5 kbp relative to the high clusters. A Venn diagram revealed that only 21 probe sets were shared between the HighEF-specific and high cluster–associated transcripts, whereas 25 probe sets were shared between the CHF-specific and high cluster–associated transcripts (Fig. 3C). The K4TM mark has been found to map preferentially to the transcription start sites of active genes (Bernstein et al. 2005). Although a typical correlation between the K4TM modification and selective gene expression was apparent for a subset of genes (Fig. 4), our results suggest that this dynamic epigenetic regulation in the heart may not always directly participate in transcriptional regulation of neighboring genes.


Figure 4
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  		Figure 4  Epigenetic profile and mRNA abundance for FER1L3. Six sequence reads were selectively identified in the first intron of the FER1L3 gene for the K4TM ChIP products of the HighEF sample (upper panel). E, exon. Consistent with this epigenetic profile, the amount of FER1L3 mRNA was higher in the HighEF specimens than in the CHF specimens, as judged from the microarray data (lower panel).

 

   Discussion
Top
 Abstract
 Introduction
 Results
 Discussion
Experimental procedures
 References
 
In the present study, we have revealed heart failure–dependent changes in the epigenetic profiles for K4TM and K9TM marks. The antibodies used in this study have been utilized in other reports for ChIP experiments, with those for K4TM and K9TM being especially employed in a genome-wide epigenetic profiling (Pokholok et al. 2005; Vakoc et al. 2006). Although it is difficult to extensively verify our data in this study (because of the lack of knowledge in epigenetic profiles in heart), our ChIP procedure could faithfully confirm the epigenetic data demonstrated in previous studies [You et al. have, for instance, revealed that an apicidin treatment decreases the K4TM level while increases the K9TM level in the exon 1 of DNMT1 in HeLa cells (You et al. 2008), and we could observe similar changes in the same experiment (data not shown)], supporting the reliability of our ChIP procedures.

Despite increasing evidence for a role of histone acetylation-deacetylation in the development of cardiac hypertrophy and heart failure, little information has been available for other histone modifications in these conditions (Illi et al. 2005; Phan et al. 2005; Bingham et al. 2007). Given the marked differences between the profiles of dimethylation and trimethylation for both K4 and K9 sites of histone H3, such trimethylation is likely under strict regulation in failed hearts.

The genes positioned close to the K4TM or K9TM marks were highly enriched in those that encode components of signaling pathways related to cardiac function. The HighEF-specific K4TM modification was, for instance, associated with RYR2, CACNA2D1, and CACNB2 genes, the products of which directly participate in the regulation of intracellular calcium concentration and in muscle contraction (Cataldi et al. 1999; Marx et al. 2000). However, such disease-dependent histone methylation was not always linked to the induction or repression of neighboring genes. The expression level of the above three genes thus did not differ significantly between HighEF and CHF specimens (data not shown). Furthermore, only ~30% of HighEF- or CHF-specific transcripts were derived from genes associated with disease-dependent K4TM or K9TM modification (Fig. 3C). Consistent with such observations, the expression ratio for probe sets between normal and failed hearts of Dahl rats was not significantly correlated with the intensity ratio for any of the examined histone modifications, including H3Ac and H4Ac (data not shown). Therefore, despite the marked association between disease status and both transcript abundance and a subset of histone modifications, none of the latter can directly account for the former.

The epigenetic changes associated with heart failure may regulate gene transcription not through a single modification but through a combination of various marks (the "histone code" hypothesis) (Strahl & Allis 2000). The disease-dependent epigenetic changes also may alter the conformation of chromosomes, inducing an open or closed chromatin structure that indirectly affects the targets of subsequent regulation, such as the binding of transcription factors or additional chromatin remodeling. The subsequent regulation step would then play an important role in transcription of neighboring genes. In either case, our epigenetic profiles should facilitate further investigations into the roles of epigenetic changes in the development of heart failure.


   Experimental procedures
Top
 Abstract
 Introduction
 Results
 Discussion
 Experimental procedures
References
 
ChIP-on-chip experiments

Dahl salt-sensitive rats (Japan SLC) at 6 weeks of age were maintained on a low-sodium diet (0.3% NaCl) or switched to a high-sodium diet (8% NaCl); the latter animals developed heart failure, as detected by echocardiography, after 13 weeks, as described previously (Ueno et al. 2003). ChIP products were prepared from the LV myocytes of 19-week-old Dahl rats with antibodies specific to H3Ac (Upstate, #17-245), H4Ac (Upstate, #17-229), K4DM (Abcam, #ab7766), K4TM (Abcam, #ab8580), K9DM (Upstate, #07-441), K9TM (Upstate, #07-442), K20TM (Abcam, #ab9053) or K27DM (Upstate, #07-452). The products were amplified by T7 RNA polymerase and subjected to hybridization with Affymetrix Rat Genome 230 2.0 microarrays as described previously (Takayama et al. 2007). Total genomic DNA (Pre-ChIP) and cRNA prepared from the LV tissue were also hybridized to the same arrays. The mean expression intensity of all probe sets was set to 500 U in each hybridization, and the fluorescence intensity of each test gene was normalized accordingly. Microarray data for rat and human hearts are available at the Gene Expression Omnibus web site (http://www.ncbi.nlm.nih.gov/geo) under the accession numbers GSE8341 and GSE8331, respectively. For the ChIP data, the signal intensity of each probe set in the Pre-ChIP analysis was then subtracted from that of the corresponding probe set in each ChIP experiment.

ChIP-to-seq experiments

All clinical specimens were obtained with written informed consent, and the study was approved by the ethics committees of Jichi Medical University and Hayama Heart Center. ChIP products were prepared from pooled samples for HighEF or CHF (each derived from four specimens) with antibodies to K4TM or K9TM. The products were converted to cRNA and amplified as described above for ChIP-on-chip experiments. The cRNA was then used to generate double-stranded DNA, which was subjected to pyrosequencing with a Genome Sequencer 20 system (Roche Diagnostics). Keypass wells occupied 82.7% to 87.0% of original Raw wells. Homology searches with the BLAST program were performed against the human genome sequence (the hg18 assembly) for each readout with the following parameter set: –e 2e-19 –v 50 –b 500 –T F –F F –m 8.


   Acknowledgements
 
This work was supported in part by a Grant-in-Aid for Scientific Research on Priority Areas (C) "Medical Genome Science" from the Ministry of Education, Culture, Sports, Science and Technology of Japan and by a grant (#04C7) from Salt Science Research Foundation (Tokyo, Japan).


   Footnotes
 
Communicated by: Kohei Miyazono

* Correspondence: hmano{at}jichi.ac.jp


   References
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 Discussion
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Received: 26 June 2008
Accepted: 10 October 2008




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J. Am. Coll. Cardiol., May 12, 2009; 53(19): 1752 - 1759.
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