Non-genotoxic carcinogen exposure induces defined changes in the 5-hydroxymethylome
© Thomson et al.; licensee BioMed Central Ltd. 2012
Received: 30 May 2012
Accepted: 3 October 2012
Published: 3 October 2012
Induction and promotion of liver cancer by exposure to non-genotoxic carcinogens coincides with epigenetic perturbations, including specific changes in DNA methylation. Here we investigate the genome-wide dynamics of 5-hydroxymethylcytosine (5hmC) as a likely intermediate of 5-methylcytosine (5mC) demethylation in a DNA methylation reprogramming pathway. We use a rodent model of non-genotoxic carcinogen exposure using the drug phenobarbital.
Exposure to phenobarbital results in dynamic and reciprocal changes to the 5mC/5hmC patterns over the promoter regions of a cohort of genes that are transcriptionally upregulated. This reprogramming of 5mC/5hmC coincides with characteristic changes in the histone marks H3K4me2, H3K27me3 and H3K36me3. Quantitative analysis of phenobarbital-induced genes that are involved in xenobiotic metabolism reveals that both DNA modifications are lost at the transcription start site, while there is a reciprocal relationship between increasing levels of 5hmC and loss of 5mC at regions immediately adjacent to core promoters.
Collectively, these experiments support the hypothesis that 5hmC is a potential intermediate in a demethylation pathway and reveal precise perturbations of the mouse liver DNA methylome and hydroxymethylome upon exposure to a rodent hepatocarcinogen.
Methylation of the fifth carbon of a cytosine base (5-methylcytosine (5mC)) in the dinucleotide sequence CpG is a well-established epigenetic modification of vertebrate DNA thought to have important roles in the preservation of genomic integrity, allele-specific expression of imprinted genes, maintenance of X-chromosome inactivation in females, tissue-specific gene regulation and long-term silencing of genes and retrotransposable elements [1, 2]. Until recently, incorporation of a methyl group was thought to be the only form of direct DNA modification in the mammalian genome. However, landmark studies by two groups in 2009 re-discovered the modified base 5-hydroxymethylcytosine (5hmC) in mouse purkinje cells and granule neurons [3, 4], a mark initially found over 50 years ago in T2 phage . Shortly after this work, it was shown that a group of enzymes belonging to the TET family (TET1,2 & 3) of Fe(II) and α-KG-dependent dioxygenases utilize molecular oxygen to transfer a hydroxyl group to 5mC to form 5hmC [4, 6–9]. In human cancers, the TET genes were found to exhibit a substantial reduction in their expression levels with global loss of 5hmC in tumors relative to surrounding tissue . Recently, several studies have focused on one of these enzymes, TET2. Not only was this enzyme found to be frequently mutated or inhibited in many human acute myeloid leukemias, but its inactivation correlates with a hypermethylation phenotype [11–13]. These observations fit with a mechanism whereby the deposition of 5hmC at promoters can subsequently lead to demethylation of DNA, in a dynamic cycle of DNA demethylation and re-methylation, perhaps mediated by DNA glycosylases [14, 15]. In support of this, inhibition of TET1 function in embryonic stem cells also leads to accumulation of DNA methylation at CpG-rich regions [16–18].
The genome-wide patterns of 5hmC have been described for both cultured cells [16–25] and tissues [26–29] with the general consensus that 5hmC-marked DNA is enriched over the bodies of expressed genes as well as at enhancer elements. When dynamically present at CpG-abundant promoter regions 5hmC may function as part of a demethylation pathway that promotes a methylation-free state, possibly through base excision repair pathways [30, 31]. Recent work investigating epigenetic reprogramming events in the mouse zygote support this hypothesis through the finding that the rapid active demethylation seen in the paternal pro-nuclei is accompanied by an accumulation of genome-wide 5hmC and its derivatives in the absence of cell division [6, 32, 33].
A reprogramming mechanism for DNA methylation may also underpin the molecular changes that occur during the development of non-genotoxic carcinogen (NGC)-induced carcinogenesis [34–36] via the mis-expression of genes that promote liver tumor formation [34, 35, 37–39]. Several NGCs directly regulate nuclear receptors, including the constitutive androstane receptor (CAR; also known as nuclear receptor subfamily 1 group I member 3 (Nr1i3)) and peroxisome proliferator activated receptor alpha (Ppara), which mediate the transcriptional regulation of enzymes involved in response to drug exposure . Many nuclear receptors, including PPARγ, interact with the DNA repair protein thymine DNA glycosylase (TDG), which can potentially mediate DNA demethylation at target genes by base excision repair mechanisms [15, 33, 41, 42].
In a recent study, we reported that liver-specific changes at the DNA methylation level occur in a subset of mouse gene promoters following 28-day exposure to the well-studied NGC phenobarbital (PB) . Locus-specific changes in histone modifications and loss of 5mC was observed at some of these promoter regions, which was coupled to an increase in the transcriptional activity of associated genes. Together this suggests that PB exposure can transduce an epigenetic switch from a repressive to an active chromatin state at selected target genes. Here, we map on tiled arrays the 5mC and 5hmC genomic patterns in both control and 28-day PB exposed mouse livers to examine the dynamic relationship between these two marks and their perturbation upon NGC exposure. In addition, we performed genome wide chromatin immunoprecipitation (ChIP) sequencing (ChIP-seq) to investigate PB-induced changes of three histone modifications, H3K4me2 (histone H3 lysine 4 di-methylation), H3K27me3 (histone H3 lysine 27 tri-methylation) and H3K36me3 (histone H3 lysine 36 tri-methylation). Our hypothesis is that changes in 5hmC profiles may be associated with PB-induced transcriptional remodeling in the liver. We find that chromatin modifications and the profiles of 5hmC and 5mC are pharmacologically perturbed over a subset of genes in a transcription-associated manner following continuous 28-day PB exposure. Together, these integrated epigenomic and transcriptomic profiling data provide novel insight into the molecular responses to a rodent hepatocarcinogen and may ultimately underpin the identification of novel early biomarkers for NGCs.
Results and discussion
Genomic distribution of 5mC- and 5hmC-marked DNA in the mouse liver
A 5hmC DNA immunoprecipitation assay (HmeDIP) was carried out on DNA from groups of control and PB-treated animals (each n = 5) using a highly specific anti-5hmC antibody (Additional file 1a,b). Enrichment was validated using quantitative PCR (qPCR) at candidate loci previously identified as being marked by the 5hmC modification  (Additional files 2 and 3). The 5hmC-enriched fractions were then applied to a large-scale promoter tiling-array (Nimblegen 2.1M Deluxe Promoter Array) to generate a representative pattern of the 5hmC landscape in mouse liver. The same procedure was repeated on the same DNA samples with an anti-5mC antibody (methylated DNA immunoprecipitation (MeDIP)) , allowing a direct comparison of the two DNA modifications. The 28-day 5hmC and 5mC raw data files have been deposited with Gene Expression Omnibus (GEO series number [GSE40540]).
As studies have shown that 5hmC-modified DNA is particularly enriched at enhancer elements in cultured cells [19, 22, 23], we expanded our analysis to investigate such sites present on our array. Of the 23,556 probes covering defined enhancers on our array, 15.4% overlapped with peaks of 5hmC whilst only 1.5% overlapped with peaks of 5mC (Additional file 6). Extension of this analysis revealed that, on average, 1 kb long enhancer regions present on the array contained significantly more 5hmC than was found over the defined promoter regions (Figure 1d; P-value < 0.001) whilst no such difference was observed for the 5mC mark. Finally, as the array does not contain repetitive DNA, we also tested these regions directly by standard qPCR to determine the relative enrichment of both 5hmC and 5mC over major satellites, LINEs and intracisternal A-particle (IAP) elements (Additional file 7). As expected from previously published work [18, 28] major satellites, LINEs and IAP elements are enriched for 5mC, but not 5hmC, confirming that the 5hmC genomic fraction is limited to non-repetitive regions.
5hmC enrichment at promoters and gene bodies is linked to transcriptional state
Recent studies have revealed that the levels of 5hmC over promoters and within gene bodies correlate with transcriptional activity in embryonic stem cells [16, 17, 20, 21] and both human and mouse tissue [26–29]. To test this for the first time in the mouse liver, average 5hmC profiles were plotted around the TSS and flanking regions (TSS ± 1.5 kb) of genes with high, medium and low levels of expression (Figure 1e). On average, promoters associated with low levels of gene expression marked with higher levels of the 5hmC modification directly over the TSS than was found over the promoters of highly expressed genes, indicating that the distribution of promoter 5hmC in the mouse liver is associated with the relative levels of transcriptional activity. Although the majority of the probes on the array map specially to promoter regions, a series of short genes (n = 775, <3 kb in total length) were also covered in their entirety, which allowed for the analysis of 5hmC patterns through the bodies of genes. The distribution of 5hmC at the TSS of this subset of short genes is consistent with the genome-wide distribution, whilst an enrichment of 5hmC is seen in the body of these genes in a transcription-associated manner (Figure 1e; Additional file 8).
5hmC is enriched at the TSS of a subset of intermediate CpG promoters
Although the majority of genes reveal depletion of 5hmC in the regions surrounding their TSS, a subset (n = 508 genes) was found to contain an enrichment of the modification over these regions (Additional files 9 and 10). Independent verification by 'EpiMark' qPCR revealed that the levels of 5hmC enrichment at two unique TSS regions (H19 and Tspan10) surpass those observed over the upstream and intra-genic regions tested (Figure 1c). Based on expression profiling data, these genes exhibit lower levels of transcription than the average of all genes on the array (Additional file 11), which is in agreement with the earlier observation that genes with higher levels of 5hmC over their TSS tended to be lowly expressed (Figure 1e; Additional file 8). Furthermore, genes with 5hmC-marked TSS regions also contain a slight but significant (Fisher's exact test, P < 0.001) enrichment for genes involved in tissue-specific patterns of expression (Additional file 12). In agreement with earlier studies, sequences associated with 5hmC-marked TSS regions were largely (56.5%) found to be of an intermediate CpG density (these sequences are termed ICPs; 1 to 5 CpGs per 100 bp; Figure 1f) [16, 21]. Interestingly, the 5hmC-enriched TSS regions are also marked with higher levels of 5mC than is found at all genes (Willcox test, P < 0.001; Additional file 11). Although the biological relationship between CpG density and 5hmC levels is unclear, it may reflect the fact that CpG-rich regions tend to be largely maintained in a non-modified state (such as at CpG islands; 'CGIs') whilst ICPs are often methylated in a tissue-specific manner .
CpG islands marked by 5hmC tend to be non-promoter-associated
As CpG density appears to be important in the marking of promoter regions with the 5hmC modification, the CGIs covered on the array (16,002) were analyzed for their association with peaks of 5hmC. Although the majority of CGIs are largely non-methylated, a subset did contain at least one peak of 5hmC (601 peaks aligned to CGIs). Of these, the vast majority (78%) were found to correspond to intra-genic CGIs, which were not associated with promoter regions (Figure 1g; Additional file 13). It is possible that the intra-genic CGIs contain higher levels of the 5hmC mark simply due to the fact that they reside within the bodies of genes, which themselves are regions of 5hmC enrichment. As the regions upstream of CGIs (termed 'CGI shores') have been implicated as regions of differential methylation between tissues and cancers , we investigated regions 1 kb upstream of annotated CGIs. Similarly to the CGIs themselves, we find no strong enrichment in both the 5hmC and 5mC marks at these loci (Additional file 14).
5hmC-marked regions are associated with an active chromatin state
Phenobarbital induces perturbations of 5hmC and 5mC at selective promoter regions in liver
The epigenetic landscape is highly dynamic and often found to be perturbed by xenobiotics, including NGCs [34, 35, 43, 47]. We previously investigated the effects of 28-day exposure to the widely studied NGC PB on 5mC levels over promoter regions (TSS -800/+100 bp), and found that promoter 5mC levels were reduced over a small subset of PB-induced genes in the mouse liver . Given the proposed role for the 5hmC modification as an intermediate in a demethylation pathway, we used the high coverage promoter arrays to investigate if 28-day exposure to PB alters 5hmC patterns globally and specifically over promoter proximal regions (PPRs; Figure 1a). To characterize chromatin dynamics and their perturbations upon PB exposure, we also performed ChIP-seq for H3K4me2, H3K27me3 and H3K36me3 histone modifications along with Affymetrix gene expression analysis on the same tissue samples.
To better understand the dynamics of 5hmC and 5mC levels across PPRs following PB-induced gene activation, the changes in the DNA and histone modifications were plotted against 30 genes that did show a clear increase in their expression levels following 28-day PB exposure (>log2 1.5-fold induction; Figure 3b; Additional file 16, red boxes). This analysis revealed a relationship between a gain of 5hmC levels (Pearson correlation = 0.35, P-value = 0.019) over the PPRs of induced genes along with a loss of 5mC (Pearson correlation = 0.61, P-value = < 0.001). This reciprocal gain in 5hmC/loss in 5mC also corresponds to a general change in the chromatin configuration over these induced genes with increases seen in PPR H3K4me2 levels (Pearson correlation = 0.32, P-value = 0.030) and gene body H3K36me3 levels (Pearson correlation = 0.45, P-value = 0.0063). In contrast, gene body levels of the H3K27me3 modification, often associated with silencing events [43, 48, 49], are reduced at many PB-induced genes (Pearson correlation = -0.55, P-value < 0.001). As a control, the relationships between these marks and the expression levels of 30 genes that exhibited no transcriptional change following PB exposure revealed far lower Pearson correlation scores and no significant P-value scores (Additional file 20). From this analysis we conclude that an epigenetic switch takes place at the PPRs of genes activated by 28-day PB treatment in liver. Typically, PB induction of gene expression is accompanied by a loss of promoter 5mC, with an associated gain in promoter 5hmC levels (Additional file 21), which may represent an intermediate in a demethylation pathway.
To more accurately determine where the changes in both 5hmC and 5mC occur over the PPRs of the PB-induced genes, the average signal changes were plotted relative to the TSS over a ±3 kb window. The induced genes reveal a striking pattern of 5mC loss over the entire region, as well as a strong enrichment in 5hmC signal (Figure 3c, top panel). The changes in the two modifications were often seen to directly oppose each other, which may represent a replacement of the 5mC modification by the 5hmC form. Although regions outside of the core promoter experience a large increase in 5hmC, the regions surrounding the TSS show both a dramatic loss in both 5hmC and 5mC levels. As the promoters of active genes are typically non-methylated, this may represent a complete demethylation event. In contrast, the promoter regions of unaffected genes do not reveal any significant change in either mark upon PB exposure (Figure 3c, lower panel). It will be important through subsequent work to evaluate the functional significance of these changes in both 5hmC and 5mC over the regions that span the core of the promoter.
PB treatment leads to dynamic transcriptional and DNA methylation (5mC/5hmC) changes at xenobiotic metabolism genes in liver
To better understand the functions of PB-induced genes, Gene Ontology term analysis was carried out on all genes with >1.5-fold increase in expression upon PB exposure (n = 30). This revealed enrichment for genes involved in xenobiotic metabolism (Additional file 22), including those encoding cytochrome P450s and glutathione S-transferases, as described previously for PB exposure [43, 50]. Both of these gene families are involved in the detoxification of electrophilic compounds, including carcinogens [51–53]. CAR plays an essential role in phenobarbital-induced hepatocarcinogenesis in rodents . Although Cyp2b gene induction is a ubiquitous downstream effect of CAR activation in rodent liver, and occurs in parallel to increased cell proliferation, it is uncertain whether increased cytochrome P450 enzyme activity itself plays a direct role in hepatocarcinogenesis . Nevertheless, Cyp2b10 mis-expression is observed in a subset of liver tumors that occur after the initial inducer compound has been withdrawn or arose in the absence of exposure to PB [54, 56, 57]. Liver tumors that are glutamine synthetase-positive and mutated in β-catenin show concomitantly elevated Cyp2b10 expression . We previously reported that the promoter region of Cyp2b10 is hypomethylated and associated with strong transcriptional induction following 28-day treatment with PB . Here we find that the promoter region not only becomes hypomethylated (Figure 3d, red) upon PB treatment, but that these regions display a reciprocal increase in the levels of 5hmC (Figure 3d, purple). These reciprocal changes are also seen outside of promoter regions as far as 7 kb upstream of the TSS and 2 kb downstream (Figure 3d). In addition, the chromatin environment around this locus is dramatically altered upon PB exposure with histone marks conducive to gene activation events, such as promoter H3K4me2 (Figure 3d, blue) and gene body H3K36me3 (Figure 3d, green), increasing over the Cyp2b10 locus, whilst gene body H3K27me3 levels decrease (Figure 3d, orange). This locus appears to be one of the most dynamic regions in terms of 5hmC, 5mC and histone modification changes, and taken together with the finding that this gene shows the largest increase in gene expression, may correspond to the catalytic conversion of 5mC to 5hmC as part of a potential demethylation process.
To further investigate where the changes in the levels of 5hmC, 5mC and histone modification occur over the Gst and Cyp2b and 2c families, average changes for these marks were calculated across the genomic regions outlined earlier (Figure 1a) and compared to genes displaying no change in gene expression upon PB exposure (Figure 3e). Using this approach we found significant increases in 5hmC levels at the upstream, promoter and gene body regions of the two gene families, with the most striking examples of epigenetic change observed over the Cyp family of genes (Figure 3e; Additional files 23 and 24). Through this analysis we discovered that the largest perturbation of the 5hmC mark occurred at the intra-genic regions of the Cyp2b and 2c genes (36-fold enriched compared to gene body 5hmC levels over a similar number of genes unaffected by PB exposure, Willcox test, P-value 2.44E-10). Additionally, there was a significant reduction in both 5hmC and 5mC levels over the DNA around the TSS, which may represent a total demethylation event (Willcox test, P-value = 5.37E-06; Figure 3b). Analysis of the histone modifications changes over these two gene families revealed that H3K4me2 levels were increased across the upstream, promoter and intra-genic regions of both families upon PB treatment, whilst H3K27me3 levels were reduced over the promoters of both families and strongly reduced over the bodies of the Cyp2b and 2c genes. Finally, PB-induced increases in H3K36me3 levels were largely observed over the upstream and intra-genic regions of the Cyp2b/2c and Gst genes. Together, these data reveal extensive pharmacologic perturbation of the mouse liver epigenome by a non-genotoxic carcinogen and identify reciprocal changes in 5mC and 5hmC patterns over the promoter regions of a subset of genes induced by PB.
Prolonged stimulation by PB reciprocally perturbs 5hmC and 5mC patterns at the Cyp2b10 promoter, resulting in a demethylation event
The re-discovery of DNA modified by 5-hydroxymethylation in mammalian cells has changed the way in which we view the mammalian epigenome [3, 4]. Here we present the first study of 5hmC patterns in the mouse liver and compare these to both 5mC patterns and associated gene transcription. Additionally, we report, for the first time, perturbations in 5hmC patterns over a set of genes that are induced upon exposure to PB, a well characterized rodent non-genotoxic carcinogen. Our results suggest that liver DNA has a similar but distinct distribution of 5hmC to that of embryonic stem cells [16–18, 20, 21] and mouse cerebellum tissue [26, 28]. We also observe a correlation between the levels of the 5hmC modification and gene expression levels. We hypothesize that this may be due either to the modification of gene body 5mC marks to facilitate transcription by allowing the progression of polymerase complex or to stabilization of open chromatin by repelling methyl-CpG binding proteins and the maintenance methyltransferase Dnmt1 [4, 59]. As such, this implies that distinct tissue-specific patterns of 5hmC are partly dependent on transcriptional differences.
Upon 28-day exposure to PB a group of genes (approximately 300) exhibited small but significant changes in gene expression whilst a subset of these (n = 30), typically with roles in drug response, were highly induced. Here we show that there is a strong correlation between increasing levels of 5hmC and decreasing levels of 5mC over the promoters of highly induced genes. Furthermore, these induced genes show characteristic changes in histone marks representing a move to a euchromatic state, which would facilitate transcription. The observed changes in the levels of promoter 5hmC and 5mC reveal that they are frequently reciprocal and tend to occur outside of the core promoter (Figure 3c). Regional differences in promoter 5mC levels have also been noted by others during differentiation . Previous work reveals that, upon 28-day PB exposure, the 5mC modification is significantly reduced over regions spanning the TSS of the Cyp2b10 gene . In this study, we expand upon this observation to reveal that although dynamic changes in both 5hmC and 5mC are occurring over promoter proximal regions, both marks are lost over regions surrounding the TSS, representing complete demethylation. Furthermore, this loss is all the more striking following prolonged drug exposure (91-day PB treatment; Figure 4a). This result implies that TSS regions may be bound by specific factors capable of completing the demethylation pathway (from 5mC via 5hmC to C). These factors may largely be promoter specific as the majority of 5hmC is seen outside these regions, residing within the bodies of actively transcribed genes (Figure 4b). It is possible that the transcriptional machinery itself can in some way maintain the 5hmC levels in these genic regions; however, although studies have shown that transcriptional elongation efficiency is high in DNA marked by 5hmC , the direct relationship between the transcriptional machinery and the maintenance of the 5hmC mark remains untested. Aside from the replication machinery, a strong candidate for a promoter-specific factor capable of removing the 5hmC would be TDG, which is able to directly remove the newly formed 5-hydroxymethyluracil by base excision repair [30, 62] (Figure 4b). This would ultimately result in the conversion to a non-modified cytosine base (Figure 4a). Alternatively, further oxidation of 5hmC to 5-formylcytosine or 5-carboxylcytosine may provide suitable substrates for demethylation to non-modified cytosine via TDG-coupled base excision repair [9, 15, 33]. Although MBD4 and TDG could potentially remove 5-hydroxymethyluracil resulting from deamination of 5hmC, it has been recently shown that AID/APOBEC deaminases have substantially reduced activity toward 5hmC-containing templates compared to 5mC-containing counter parts, which would appear to rule out this pathway [63, 64]. TDG has also been shown to play a critical role in the regulation of transcription through its interaction with transcription factors, nuclear receptors and the histone acetyl-transferases Crebbp and Ep300 [42, 65, 66]. The potential targeting of TDG through its interaction with nuclear receptors such as CAR may account for the locus-specific changes in 5hmC that occur in concert with PB-induced expression changes in liver (Figures 3c and 4a). It will be of interest to study this further in CAR null mice and mutants that contain the human CAR .
In conclusion, changes in 5hmC- and 5mC-modified DNA upon transcriptional activation by PB may represent an intermediate step in a demethylation pathway resulting in the presence of unmodified CpGs over core promoter regions. Further analysis of the dynamic changes in epigenetic marks associated with early transcriptional responses to PB, their long-term plasticity and status in PB-induced liver tumors will lead to a greater understanding of mechanisms of non-genotoxic carcinogenesis. Ultimately, if our observations are replicated in other NGC exposure models, this may lead to the identification of candidate epigenetic biomarkers for enhanced cancer risk assessment.
Materials and methods
This study was performed in conformity with the Swiss Animal Welfare Law and specifically under the Animal Licenses No. 2345 by 'Kantonales Veterinäramt Basel-Stadt (Cantonal Veterinary Office, Basel) and No. 5041 by 'Kantonales Veterinäramt Baselland' (Cantonal Veterinary Office, Basel Land).
Animal treatment and sample preparation
Male B6C3F1/Crl (C57BL/6 ♂ × C3H/He ♀) mice 29 to 32 days old were obtained from Charles River Laboratories (Germany). Animals were allowed to acclimatize for 5 days prior to being randomly divided into two treatment groups of five animals each. 0.05% (w/v) PB (Sigma-Aldrich, St Louis, MO, USA) was administered to one group through ad libitum access to drinking water for either 1, 7, 28 or 91 days. Mice were checked daily for activity and behavior and sacrificed on the last day of dosing depending on the dosage group. Livers were removed prior to freezing in liquid nitrogen and -80°C storage.
Dot blot analysis of 5hmC antibodies
DNA from mouse liver and PCR products containing C, 5mC and 5hmC  were spotted onto a positively charged nitrocellulose membrane and immobilized with 0.4 M NaOH using a dot blot apparatus (Harvard Apperatus, Edenbridge, UK). The membranes were probed with anti-5mC monoclonal antibody 1.6 μg/μl (Diagenode, Liege, Belgium) diluted 1:4,000 in tris-buffered saline (TBS) and Western Blocking reagent (Roche Diagnostic, Mannheim, Germany), or with the anti-5hmC polyclonal antibody diluted 1:5,000 (Active Motif, La Hulpe, Belgium) followed by anti-rat horse radish peroxidase (Cell Signalling Technology, Boston, USA) and anti-mouse horse radish peroxidase (Sigma-Aldrich, Dorset, UK) prior to exposing the membrane to Image Quant (Image Quant LAS 4000; GE Healthcare, Bucks, UK). A duplicate membrane was produced for the DNA loading control and probed with anti-single stranded DNA 0.2 μg/μl (Demeditec Diagnostics, Kiel-Wellsee, Germany) diluted 1:3,000 raised against rabbit.
HmeDIP and MeDIP protocol
Genomic DNA from mouse liver tissue samples was extracted by overnight proteinase K digestion (Sigma) in lysis buffer (50 mM Tris-HCl pH 8.0, 10 mM EDTA pH 8.0, 0.5% SDS) prior to phenol-chloroform extraction, ethanol precipitation and RNaseA digestion. Genomic DNA was sonicated (Bioruptor, Diagenode) to produce DNA fragments ranging in size from 300 to 1,000 bp, with a mean fragment size of around 500 bp. Fragmented DNA (4 μg for HmeDIP and 6 μg for MeDIP) was then denatured for 10 minutes at 95°C and immunoprecipitated for 3 h at 4°C either with 1 μl of rabbit polyclonal antibody against 5-hydroxymethylcytosine (Active motif, La Hulpe, Belgium; cat#39769) or with 15 μl mouse monoclonal antibody against 5-methylcytidine (Eurogentec, Seraing, Belgium; #BI-MECY-1000) in a final volume of 500 μl immunoprecipitation (IP) buffer (10 mM sodium phosphate (pH 7.0), 140 mM NaCl, 0.05% Triton X-100). This mixture was incubated with 60 μl of magnetic M-280 protein G Dynabeads (Invitrogen, Grand island, NY, USA; #100-03D) for 2 h prior to washing all unbound fragments three times with 1 ml IP buffer. Washed beads were then resuspended in 250 μl of lysis buffer and incubated with proteinase K for 2 h at 50°C. Immunoprecipitated DNA fragments were then purified by passing through DNA purification columns (Qiagen, Venlo, Netherlands) and eluting into 20 μl TE. For qPCR analysis, 10 μl were taken and diluted to 100 μl in TE with each qPCR reaction using 2 to 3 μl of diluted DNA. For microarray analysis, 10 μl of immunoprecipitated DNA was subjected to whole genome amplification (WGA) using the WGA2:GenomePlex Complete Whole Genome Kit (Sigma) and 6 μg of amplified material sent to Roche Nimblegen (Iceland) for Cy3 and Cy5 labeling and hybridization on 2.1M Deluxe mouse promoter tiling arrays.
H3K4me2/H3K27me3/H3K36me3 native ChIP for genome-wide sequencing
Frozen mouse liver (150 mg) was isolated and ground into a fine powder using with Covaris Cryoprep (Covaris Inc., woburn, Massachusetts, USA). Nuclei were isolated by centrifugation through a 1.2M sucrose cushion prior to micrococcal nuclease (Sigma) fractionation into primarily mono- and di-nucleosomal fragments. For each histone mark, 100 μg of chromatin was used and 10% of the input taken prior to immunoprecipitation.
The immunoprecipitation, washes and DNA purification were done with Magna ChIP™ A Chromatin Immunoprecipitation Kit (Millipore, Billerica, Massachusetts, USA; #17-610) following the manufacturer's protocol
DNA (0.9 μg) for the input samples and 0.018 μg for the K4 and K27 samples were end-repaired and ligated to Illumina genomic DNA adapters according to the manufacturer's protocol (Illumina, 2010). The samples were purified using Agencourt AMPure XP beads (Beckman Genomics, Danvers, Massachusetts) and then subjected to 12 cycles of PCR as per the manufacturer's protocol (Illumina, 2010). No sample indexing was performed. Their size distributions were checked on an Aglient Bioanalyzer (Agilent). Each sample was then loaded as a 6pM solution on an Illumina GAIIx v7 paired-end flowcell using a cluster station instrument (Illumina). The flowcell was then subjected to 2 × 55 bp of SBS chemistry v4 on an Illumina GAIIx instrument.
DNA (1 μg) for the L samples and 0.018 μg for the K36 samples was end-repaired and ligated to Illumina TruSeq adapters according to the manufacturer's protocol (Illumina, 2011). The samples were purified using Agencourt AMPure XP beads (Beckman Genomics) and then subjected to 12 cycles of PCR as per the manufacturer's protocol (Illumina, 2011). The samples were indexed using the Illumina TruSeq indexes and purified using Agencourt AMPure XP beads and their size distributions checked on an Aglient Bioanalyzer (Agilent). The indexed libraries were then quantitatively pooled and a 9pM solution of multiplexed library was denatured and loaded on an Illumina TruSeq SE v1.5 flowcell using a cBot instrument (Illumina). The flowcell was then subjected to 51 bp of SBS chemistry on an Illumina HiSeq2000 instrument using the Illumina Real Time Analysis 1.12 software. The base calling and sample demultiplexing was performed using the Illumina CASAVA 1.8 software.
Affymetrix gene expression analysis
Affymetrix expression arrays were performed following the methods outlined in earlier work , except that the dataset was normalized by robust multichip average (RMA) techniques  and the P-value for the log2 fold change was calculated with the R/Bioconductor LIMMA package using a moderated t-statistic.
Processing of Nimblegen promoter arrays
Nimblegen 2.1M delux mouse promoter arrays (mm9 build) contain 2,056,330 unique probes of 50 to 70 bp in length with approximately 50 bp spacing distributed over 21,562 tiled regions spanning 52,016 annotated TSS regions over 20,718 unique genes. In addition these arrays cover 15,969 annotated CpG islands over both promoter and 'non-promoter' (inter-/intra-genic). Signals for each probe of the 5hmC-enriched samples (Cy5 labeled) were compared to input samples (Cy3 labeled) to generate log2 (IP/Input) scores (fold changes). These log2 scores were then normalized to correct for both saturation effects within individual arrays by Loess normalization and between the arrays by scale normalization using the Limma package in R/Bioconductor . In order to remove individual variability the mean probe values were calculated for both the control and PB exposed group. Subsequent analysis was carried out by comparing the differences between the mean control and mean 28-day PB data sets and were plotted as changes in the probe values in PB mice relative to control mice. Raw data for the reciprocal 5mC HmeDIP and MeDIP experiments were processed the same way as 5hmC but were normalized separately. The 28-day 5hmC and 5mC raw data files have been deposited with Gene Expression Omnibus (GEO series number [GSE40540]; 28-day 5hmC [GSE40537], 28-day 5mC [GSE40538], and 28-day expression [GSE40773]).
Nimblegen 2.1M mouse promoter array GPL14890
Two sets of data were created for each modification. The first contains the values for all 2,056,330 probes on the microarray and was used for all analysis techniques which did not require an association to a nearby gene. A second data set was created that links the probes to a nearby gene so as to include affymetrix expression data from the same mice. This gene list is reduced in the numbers of probes it contains (387,612) as gene names were associated to all probes ±1 kb of an annotated Refseq TSS.
Bioinformatic analysis of datasets
'Peak-based analysis' of 5hmC and 5mC
In order to better characterize regions of 5hmC and 5mC enrichment, peak finding was carried out across the data sets. Peaks were defined as regions containing at least four probes in a five probe window above the 90th percent score of the entire data set. Using these parameters, 96,003 peaks of 5hmC (representing 4.7% of all probes) and 47,876 peaks of 5mC (representing 2.3% of all probes) were identified. To ensure peak finding was returning acceptable results, peaks were compared to qPCR-validated control regions (chr7:149,763,602-149,763,942, covering the promoter of the H19 gene, which is positive for 5hmC and 5mC; and chr6:125,115,497-125,115,656, covering the promoter of Gapdh, which is negative for both marks). Peaks of both 5hmC and 5mC were then interrogated for their genomic locations and results plotted as pie charts along with the general distribution of all probes on the array.
Analysis of CpG densities over 5hmC-enriched TSS regions
To further investigate the hmC-enriched TSS regions, the DNA of such sites was extracted and the relative CpG densities calculated (as number of CpGs per 100 bp). The hmC-positive TSS regions were then ranked by these densities grouped by low CpG content (LCP; <1 CpG per 100 bp), ICP (1 to 5 CpGs per 100 bp) and HCP (>5 CpGs per 100 bp). Overlap between regions enriched in hmC and CGIs was carried out by crossing regions with peaks in hmC to CGIs. The total number of probes covering CGIs was 87,234, whilst the number of CGI probes enriched in hmC was 601. The distribution of CGI-positive hmC-positive probes was then plotted as a pie chart next to the distribution of all CGI probes.
Sliding window analysis
Sliding windows of hmC and 5mC profiles were characterized over both unique Refseq TSSs ±1,500 bp (n = 1,000) and 'small', 2 to 3 kb long, complete genes found on the array (n = 775). Sliding window analysis was carried out using tools on the University of Edinburgh's GALAXY sever . Sliding window analysis plots the average signal taken from data files of interest (for example, mean hmC normal probe values) and slides across regions of interest (chromosome, start, stop) in user-defined steps (in base pairs). Expression data from control and PB-treated mouse livers were generated on Affymetrix expression arrays similar to , and divided into three groups depending on levels of transcription (low = bottom 25% expression levels, high = top 25% expression levels, medium = remaining genes). These groups were then crossed to regions of interest for sliding window analysis (for example, TSS ±1.5 kb regions ranked by expression). Sliding window analysis was carried out using a window size of 200 bp and with a step size of 50 bp and average signals plotted.
Analysis of the tissue specificity of genes with 5hmC-enriched TSS regions
Box plots were generated comparing classes of genes (including all the genes on the deluxe promoter array to all 5hmC-marked TSS region genes). The specificity of a gene's expression pattern was measured by using a method based on information theory outlined by Martinez et al. . A low score (0) indicates that a gene is uniformly expressed, and a high score (6.2) indicates that it is expressed specifically in one tissue. A previously published brain-specific gene set and housekeeping gene set determined by serial analysis of gene expression (SAGE) are shown for comparison .
Preparation of ChIP-Seq data sets for analysis
Sequencing reads were mapped to the mouse genome (built mm9) using the bowtie software . For marks H3K4me2 and H3K27me3 bowtie was run in paired-end mode; for H3K36me3 it was run in single-end mode. As we investigated the enrichment in predefined regions of the genome (promoter and gene body), no peak finding was performed. From the mapped paired-end data the genomic locations of the inserts were calculated (from the forward and reverse read pairs). For the single-end data genomic locations were directly extracted from each mapped read. Duplicated locations were removed, yielding a non-redundant library of mapped genomic fragments. The number of fragments overlapping with pre-defined genomic regions such as gene bodies or promoters (see above) was counted. Within each histone mark the fragment counts per region were normalized by the total number of fragments and scaled to the mean of the libraries. The counts for each mark in each region were further normalized by the counts for the matching background sample to generate log2 fold changes (scores) between IP and background to avoid bias in genomic context. We report the mean score per group (n = 2) per region and mark.
Interrogation of changes in epigenetic marks over PPRs upon PB treatment
The mean log2 probe values over a 2 kb window (TSS ±1 kb; PPRs) were calculated for the hmC, 5mC and H3K4me2 data sets over each gene for both control, PB exposed and changes observed in PB mice. The expression changes upon PB were represented as fold change expression relative to the control mice. Average H3K27me3 and H3K36me3 levels in control, PB-exposed mice as well as changes seen in PB mice were calculated over the entire gene body and related to associated promoter regions (see Additional file 21 for an example).
Initial analysis was carried out using the entire hmC or 5mC data set, plotting the average changes in promoter hmC levels against changes in gene expression. Subsequent plots for changes in promoter hmC, 5mC, H3K4me2 as well as gene body H3K27me3 and H3K36me3 only include genes with at least 1.5-fold induction in gene expression (n = 30). Trend lines were then calculated over the resulting scatter graphs along with R2 values.
Regions spanning the promoters (±3 kb) of the PB-induced genes (>log2 1.5-fold) showing induction along with 30 PB 'unaffected' genes were then selected and sliding window analysis carried out to plot the average changes in 5hmC and 5mC over these loci (see above for more on sliding window analysis). Coordinates of the PB unaffected genes are available on request.
Plots of the average changes in hmC, 5mC, H3K4me2, H3K27me3 and H3K36me3 were then carried out across two families of genes as well as 26 genes unaffected by PB exposure. Average values for changes in the epigenetic modifications were calculated across the defined regions (Figure 1). Error bars represent standard errors and data points with significant P-values are represented by an asterisk. Coordinates of the PB unaffected genes are available on request.
Heat map analysis of PB-driven 5hmC perturbation
Average 5hmC levels were calculated as explained above for each PPR. These were then separated based on the chromosome of origin and then plotted either for each individual liver (five controls, five PB treated; Figure 3a) or for the average of these control or PB exposed livers (Additional file 15). Heat maps were drawn using R with colors taken using the Colour Brewer package ('RdYlBu') ranging from values of -2.5 to +2.5 with a 0.5 interval. PPRs were ordered by the first query (that is, WT in Additional file 15) and clustered by both Euclidian and Ward methods.
Analysis of enhancer elements
We took 38,112 regions defined as mouse liver enhancers from datasets generated by Yim Shen et al. . Midpoints of enhancer regions were then taken and expanded to create 1 kb stretches of DNA sequence before restricting the dataset to those present on the 2.1M mouse deluxe promoter array used for 5hmC and 5mC analysis. This resulted in 23,556 probes that corresponded to 1.15% of all probes on the array. Overlap between 5hmC/5mC-enriched peaks was then carried out and any probe residing in a peak of a mark as well as an enhancer region was scored. Box plots of 5hmC/5mC levels were then calculated over the 1 kb array enhancers as well as 1 kb promoter regions (TSS to -1 kb upstream).
5hmC-sensitive restriction digest-qPCR
The EpiMark kit (New England BioLabs, Ipswich, Massachusetts, USA) was used to quantify absolute levels of 5hmC and 5mC between the control and PB mouse livers as well as DNA from mouse brain. For the full protocol see the manufacturer's instructions. Typically, 10 μg of genomic DNA was taken and half treated with T4- phage β-glucosyltransferase for 12 to 16 h at 37°C. Both the β-glucosyltransferase treated and untreated samples were then divided into three PCR tubes and digested with either Msp1, HpaII or left uncut for a further 12 to 16 h at 37°C. Samples were proteinase K treated for 10 minutes at 40°C prior to dilution to 100 μl final volume in H20 and heating to 95°C for 5 minutes. qPCR was carried out on 5 μl (approximately 0.8 μg DNA) of each sample on a Roche Lightcycler 480 PCR machine. Relative enrichments of the modifications were then calculated following formulae provided by New England BioLabs.
For primers used for qPCR validation and 'EpiMark' analysis please see Additional file 25.
Raw and processed data have been deposited into the Gene Expression Omnibus (GEO series number [GSE40540]).
constitutive androstane receptor (Nr1i3)
Gene Expression Omnibus
histone H3 lysine 27 tri-methylation
histone H3 lysine 36 tri-methylation
histone H3 lysine 4 di-methylation
5hmC DNA immunoprecipitation assay
intermediate CpG content
long interspersed nuclear element
methylated DNA immunoprecipitation
promoter proximal region
robust multichip average
thymine DNA glycosylase
transcription start site.
The research leading to these results is partly funded by the Innovative Medicine Initiative Joint Undertaking (IMI JU) under grant agreement number 115001 (MARCAR project). Novartis and the MRC are full participants in the IMI consortium. Novartis provide in kind financial contribution to the scientific program. All IMI-MARCAR consortium partners had a role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. JT and JH are recipients of IMI-MARCAR funded career development fellowships at the MRC HGU. RM and DR are supported by Medical Research Council. CN is supported by Breakthrough Breast Cancer (BBC). Work in RM's lab is supported by IMI-MARCAR, MRC, BBSRC and BBC. HL is the recipient of a NIBR Postdoctoral Fellowship. Thanks also for contributions from, Tulipan Zollinger, Christian Kohler, Nicole Cheung, Olivier Grenet, Florian Hahne, Ieuan Clay, Ulrich Laengle, Frank Staedtler, Pierre Moulin, David Heard, Virginie Petitjean, Anita Fernandez and Duncan Sproul.
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