Distinct and overlapping control of 5-methylcytosine and 5-hydroxymethylcytosine by the TET proteins in human cancer cells
© Putiri et al.; licensee BioMed Central Ltd. 2014
Received: 21 February 2014
Accepted: 23 June 2014
Published: 23 June 2014
The TET family of dioxygenases catalyze conversion of 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC), but their involvement in establishing normal 5mC patterns during mammalian development and their contributions to aberrant control of 5mC during cellular transformation remain largely unknown. We depleted TET1, TET2, and TET3 in a pluripotent embryonic carcinoma cell model and examined the impact on genome-wide 5mC, 5hmC, and transcriptional patterns.
TET1 depletion yields widespread reduction of 5hmC, while depletion of TET2 and TET3 reduces 5hmC at a subset of TET1 targets suggesting functional co-dependence. TET2 or TET3 depletion also causes increased 5hmC, suggesting these proteins play a major role in 5hmC removal. All TETs prevent hypermethylation throughout the genome, a finding dramatically illustrated in CpG island shores, where TET depletion results in prolific hypermethylation. Surprisingly, TETs also promote methylation, as hypomethylation was associated with 5hmC reduction. TET function is highly specific to chromatin environment: 5hmC maintenance by all TETs occurs at polycomb-marked chromatin and genes expressed at moderate levels; 5hmC removal by TET2 is associated with highly transcribed genes enriched for H3K4me3 and H3K36me3. Importantly, genes prone to hypermethylation in cancer become depleted of 5hmC with TET deficiency, suggesting that TETs normally promote 5hmC at these loci. Finally, all three TETs, but especially TET2, are required for 5hmC enrichment at enhancers, a condition necessary for expression of adjacent genes.
These results provide novel insight into the division of labor among TET proteins and reveal important connections between TET activity, the chromatin landscape, and gene expression.
Vertebrate cellular identity arises through intricate differentiation events orchestrated by epigenetic regulation of gene expression. One key epigenetic mechanism is methylation of DNA. DNA is covalently modified by methylation of the carbon-5 position within cytosine nucleotides (5mC), an epigenetic mark that, when occurring in gene promoters, is associated with transcriptional repression. DNA methylation primarily occurs in the context of cytosine followed by guanine (CpG), and normal CpG methylation patterns have been extensively characterized in human cells [1, 2]. Throughout the human genome, CpG dinucleotides tend to be methylated, except in GC-dense CpG islands (CGIs) [3–6]. For transcriptionally active genes, promoter CGIs remain unmethylated whereas intragenic domains and repetitive sequences are enriched for CpG methylation, a state that promotes genomic stability. These patterns are reversed in the cancer genome, which exhibits widespread hypomethylation and aberrant promoter CGI hypermethylation resulting in transcriptional silencing. CGI 'shores', defined as 2 kb regions that flank CGIs, also bear important epigenetic regulatory function in that they exhibit tissue-specific differential methylation that appears to regulate gene expression . Furthermore, cancer genomes lose these tissue-specific patterns of CGI shore methylation, becoming either hyper- or hypomethylated in CGI shores relative to normal tissue .
The DNA methyltransferases (DNMTs) function in the establishment and maintenance of CpG methylation patterns. DNMT1, the 'maintenance' methyltransferase, recognizes hemi-methylated DNA for proper replication of methylation upon nascent DNA strand synthesis [8, 9]. DNMT3A and DNMT3B are 'de novo' methyltransferases, which establish new methylation patterns, especially during cellular differentiation [10–12]. Recently, the Ten-eleven translocation (TET) family of dioxygenases, TET1, TET2, and TET3, were discovered for their capacity to modulate DNA methylation patterns. The TET hydroxylases catalyze the conversion of 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC) in an α-ketoglutarate- and Fe(II)-dependent manner [13, 14]. In the process of demethylating DNA, TET enzymes further act on 5hmC to generate 5-formylcytosine and 5-carboxylcytosine (5caC), both of which can be removed by thymine DNA glycosylase via base excision repair [15–17]. The hydroxymethyl modification of cytosine is, however, not a rare or transient modification in the mammalian genome, with 5hmC comprising an estimated 0.6%, 0.2%, and 0.03% of total nucleotides in mouse Purkinje cells, granule neurons, and embryonic stem cells (ESCs), respectively [13, 18]. This suggests that 5hmC is a stable mark, rather than a transient intermediate of cytosine demethylation. In support of this, specific genomic regions, particularly gene promoters, enhancers, and exons, are enriched for 5hmC [19–26], and binding of 5hmC by cell-specific binding partners (for example, the MBD3/NURD complex and MeCP2) shapes chromatin structure and gene expression [27–29]. Thus, if 5hmC is a stable, functional mark of the epigenome, how do the three TET proteins contribute to the patterning of 5hmC and 5mC and what is the role of this process in cancer initiation and progression?
TET1 and TET2 have been implicated in establishment and maintenance of ESC pluripotency and demethylation of the genome during somatic cell reprogramming [14, 30]. Genetic disruption of Tet1 in mouse ESCs skews differentiation toward extraembryonic lineages, but mice with a deficiency of Tet1 and/or Tet2 are viable, likely due to functional redundancy with Tet3[30–32]. Tet3 conditional null zygotes develop to term, but neonates die postnatally at day 1 . In the mouse, Tet3 is responsible for global demethylation of the male pronucleus and for zygotic epigenetic reprogramming [33–35]. Tet2 and Tet3 are also largely responsible for enrichment of 5hmC at neurodevelopmental genes during vertebrate neurogenesis, and in Xenopus, Tet3 is essential for expression of a set of eye developmental genes and for expression of neuronal and neural crest markers [36, 37]. Taken together, the TET proteins are clearly important regulators of developmental gene expression programs and in defining normal cell identity, albeit with unique and distinct functions for each family member, which have yet to be fully characterized.
The differential functions for TET family members are also apparent in the distinct outcomes of TET mutations in human disease. Catalytic mutations in TET2, but not TET1, are commonly identified in patients with hematopoietic disorders and malignancies such as myelodysplastic syndrome, myeloproliferative neoplasms, acute myelogenous leukemia, chronic myelomonocytic leukemia, and B-cell and T-cell lymphomas [38–42]. Common among TET family members is the finding that TET1, TET2, or TET3 mRNA and 5hmC levels are reduced across a broad spectrum of solid tumors [43–46]. Despite the revelation of widespread TET mutations and deregulated TET expression in human cancer, the effect on 5mC in these malignancies is still debated, as Ko et al.  and Figueroa et al.  observed conflicting results of 5mC changes in TET2 mutant acute myelogenous leukemias. Likewise, our knowledge of the gene targets of TET catalytic activity is still limited. Collectively, these deficiencies hamper our understanding of the role of the TETs and 5hmC in tumor initiation and progression. In this study we systematically identify the epigenetic targets and determine the genome-wide 5mC and 5hmC patterning activities of each TET family member in human embryonic carcinoma cells by specifically depleting each TET family member using small interfering RNA (siRNA). Genes and CGIs targeted for 5hmC maintenance by TET1, TET2, and TET3 overlap extensively among the three family members, with TET1 targeting the most loci. TET1 exerts greater influence at high CpG density promoters (HCPs), while TET2 functions more prominently at low CpG density promoters (LCPs). These results reveal that TET2 and TET3 actively eliminate 5hmC, particularly in introns of highly expressed genes. The differential functions of TETs in promoting or removing 5hmC are chromatin modification specific: TET1, TET2, and TET3 enrich 5hmC at polycomb-marked H3K27me3 (histone H3 lysine 27 trimethylation) and H2AK119ub (histone H2A lysine 119 monoubiquitination) promoters and genes with moderate expression; TET2 targets H3K4me3-rich promoters and highly active genes for 5hmC removal. Depletion of the TETs resulted in large-scale hypermethylation changes, particularly within promoters and CGI shores, but TET depletion also more frequently caused hypomethylation changes of smaller magnitude in promoters and CGIs, implicating TETs in removing and promoting methylation. Importantly, enhancer enrichment of 5hmC is mediated by all three TETs and is required to promote gene expression. This study yields a comprehensive genome-wide view of TET-targeted loci in human cancer cells, revealing for the first time loci that are particularly susceptible to TET-regulated cytosine modifications and identification of distinct and overlapping functions of TET1, TET2, and TET3.
5hmC enrichment is associated with robust gene activation during cellular differentiation
Notably, most genes (approximately 80% with 5hmC changes) show a decrease of 5hmC upon induction of differentiation, but a discrete subset gain 5hmC across promoters and gene bodies based on 5hmC enrichment and deep sequencing (Figure 1E). This is consistent with the overall levels of 5hmC, which decline during NCCIT differentiation, accompanied by modest changes in TET expression. During an extended timecourse of RA-induced NCCIT differentiation, some global reduction in 5hmC was observed at day 7, the timepoint analyzed here, and 5hmC continued to decline as differentiation proceeded (Figure S1A,B in Additional file 1). Several of these changes, identified through deep sequencing, were examined at base-pair resolution by TET-assisted bisulfite conversion (TAB) coupled with Sanger sequencing , confirming the overall trends illustrated by the 5hmC-seq results (Figure S3A in Additional file 1). The TAB-seq results reiterate the estimate by Yu et al.  that 5hmC comprises a low amount (estimated to be 3 to 4%) of total intragenic cytosines. Expression microarrays were used to identify relationships between 5hmC and expression upon induction of the differentiation program. Genes that gain 5hmC in DF cells are significantly (P < 0.0001) prone to activation upon differentiation and are enriched for genes involved in patterning and differentiation of ectodermal derivatives (for example, hindbrain, nerve, and epithelium development) (Figure 1F,G). Genes with 5hmC depletion after differentiation showed a slight (but not significant: P = 0.1419) trend toward downregulated expression. 5hmC-depleted genes can be classified into two subsets: those with variable loss and/or redistribution of 5hmC and genes with complete loss of 5hmC (Figure 1H; Figure S4 in Additional file 1). Together, these data suggest that 5hmC is enriched at genes primed for differentiation-induced upregulation, potentially contributing to a poised chromatin state.
Roles for TET1, TET2, and TET3 in patterning methylcytosine across intragenic regions
NCCIT ECCs serve as a model for understanding the function of TET dioxygenases in patterning the methylome because all three TET enzymes are abundantly expressed. TET3 expression is about 1.7-fold that of TET2, and TET1 is the most abundant of the three TETs, with about 30-fold the expression of TET2, a ratio similar to that observed in human ESCs (Figure S1B, right panel in Additional file 1). To investigate their functions, we depleted TET1, TET2, and TET3 by siRNA transfection in UD NCCIT cells. This method generates transient, acute depletion of each TET, allowing us to observe the most immediate, direct epigenetic effects of the functional depletion and avoiding potential compensatory changes that have been shown to occur with other methods such as transgenic small hairpin RNA or gene knockouts [53, 54]. A non-targeting control (NTC) siRNA was utilized for comparison. Transcript levels for TET1, TET2, and TET3 were depleted by 60 to 70% over 72 hours (Figure S5 in Additional file 1). No phenotypic changes were observed in siTET-treated cells relative to siNTC-treated cells during the 72 hour experiment (not shown). These depletions had little effect on the transcript abundance of DNMT1, DNMT3A, or DNMT3B or of the other TETs. Likewise, transcription of the housekeeping genes TUBA1C, DYNLL, and RPL30 was unaffected, showing no off-target effects and no defects in major cell processes or viability. Since 5hmC abundance was loosely connected with gene expression during differentiation in NCCIT, we asked whether TET1, TET2, or TET3 regulate the expression of pluripotency or differentiation markers. Depletion of TET transcripts did not impact lineage marker expression, except for the trophectodermal marker HAND1 (Figure S5 in Additional file 1). This result is consistent with prior studies in Tet1-deficient mouse ESCs that showed skewing toward trophectodermal fate [14, 30, 31]. To determine the impact of TET depletion, total levels of 5mC and 5hmC were assayed with 5mC- and 5hmC-specific antibodies in an ELISA-like detection assay. The genomic abundance of 5mC was not significantly affected by TET depletion (although there was a trend toward hypermethylation in TET2 and TET3 depletions; Figure S6 in Additional file 1). siTET1 cells showed approximately 60% loss of 5hmC, but siTET2 and siTET3 did not significantly impact total 5hmC (Figure S6 in Additional file 1). Thus, do each of the TETs have region-specific or site-specific impacts on 5hmC and 5mC?
Peaks of differential 5hmC and 5mC across intragenic regions were used to assess the site-specific epigenetic effects of each TET depletion . Genes with at least two-fold increase or decrease within promoters, UTRs, exons, introns, and regions 1 kb downstream of the transcription termination site (TTS) were counted (Figure 2B; Figure S7C in Additional file 1). siTET1 yielded predominantly hypo-hydroxymethylation. siTET2 and siTET3 cells developed loci with both hypo- and hyper-hydroxymethylation. Notably, in siTET2, intragenic regions tended to lose 5hmC, except introns. This effect was even more apparent when 5hmC changes were stratified by magnitude. Introns most affected by siTET2 and siTET3 (more than four-fold 5hmC changes) gained 5hmC (Figure S8A in Additional file 1). Select loci predicted to lose 5hmC based on the sequencing data were confirmed by independent 5hmC pull-down coupled with qPCR (Figure S9 in Additional file 1). Analysis of differential 5mC peaks confirmed our earlier observation (Figure S7B in Additional file 1) that both hypermethylation and hypomethylation result from siTET depletion (Figure S8B in Additional file 1). Intriguingly, the most robust (more than four-fold) 5mC changes were hypermethylation events. Numerous smaller 5mC changes of less than four-fold were most frequently hypomethylation events (Figure S8B in Additional file 1; Additional file 2). Thus, depletion of TET1, TET2, or TET3 caused hypomethylation events of small magnitude and hypermethylation events of larger magnitude. Both hypomethylation and hypermethylation changes were significantly enriched at loci that lost 5hmC in siTET1, siTET2, and siTET3 cells (Figure 2C), linking the two opposing outcomes. These results, taken together with the results in Figure S6 in Additional file 1 showing no net gain or loss of total 5mC, suggest that 5hmC depletion in siTET knockdown cells leads not to global hypermethylation but instead to a redistribution of global 5mC.
Promoters with decreased 5hmC overlapped extensively among the TET knockdowns (58 to 90% overlap), showing overlapping function of TET1, TET2, and TET3 at these loci (Figure S10A, left in Additional file 1); TET1 showed the largest number of unique targets with hypo-hydroxymethylation. 5hmC-depleted promoters in siTET1, siTET2, or siTET3 cells represented genes with roles in embryonic development, cell adhesion, motility, and proliferation (Figure S10B in Additional file 1) and corresponded highly with those promoters that lose 5hmC upon differentiation of NCCIT cells (approximately 60% of siTET targets overlap with DF-induced 5hmC changes; P < 0.0001; Figure S10A, right in Additional file 1). Thus, TET1, TET2, and TET3 co-regulate cytosine modifications at many of the same target sites, and these co-regulated targets control embryonic development and basic cellular physiology. In addition, our results clearly show that neither DNA hypermethylation nor hypo-hydroxymethylation is the sole outcome of TET depletion, suggesting that the role of the TETs in regulating DNA methylation is more complex than previously thought.We next asked how loss of 5hmC impacts 5mC distribution around the TSS by plotting the tag density for only genes with 5hmC loss in siTET1-treated cells. These loci showed a large trough of 5mC across the TSS, but TET depletion did not impact the overall 5mC distribution at these promoters that lose 5hmC (Figure 2D(i)). Similarly, we plotted the 5mC distribution for subsets of genes that lose (Figure 2D(ii)) and gain (Figure 2D(iii)) 5mC in all siTET cells (Figure 2D). Hypomethylated promoters display peaks of 5mC at -1 kb upstream of the TSS and immediately downstream of the TSS (Figure 2D(ii), orange arrows). Hypomethylation at these promoters is subtle and occurs in the immediate vicinity of the TSS (Figure 2D(ii)), whereas promoter hypermethylation is much more dramatic and occurs across a >6 kb region flanking the TSS (Figure 2D(iii)). Hypermethylated promoters also have a peak of 5mC at -1 kb (albeit, not as pronounced as that in hypomethylated promoters) but display a distinct depression of 5mC between -250 bp to +750 bp surrounding the TSS (Figure 2D(iii), blue arrow). In the siTET-treated cells, the peak of 5mC at -1 kb increases, and the depression across the TSS regains a peak of 5mC. Thus, the methylation landscape in promoters is dramatically different for those loci that become hypomethylated versus those that become hypermethylated upon TET depletion. Since TET2 depletion resulted in 5hmC enrichment particularly in introns, we plotted the 5hmC and 5mC tag density for introns with hyper-5hmC. These genes showed substantial redistribution of 5hmC patterns (Figure 2E). siNTC and siTET1 introns had low invariable 5hmC across introns, but siTET2 and to a lesser extent siTET3 showed a striking peak of 5hmC across introns typically associated with 5hmC depletion in flanking exons.
TET proteins control cytosine modifications at enhancers and prevent hypermethylation of promoter CGI shores
CGIs experienced 5hmC depletion in siTET1-, siTET2-, and siTET3-treated cells, but a large proportion of shores had elevated 5hmC levels in siTET2- and siTET3-treated cells (Figure 3B(i); Figure S12A(i) in Additional file 1). The median 5mC changes in CGIs for siTET1 and siTET2 were hypomethylation (Figure 3B(ii); Figure S12A(ii) in Additional file 1). This is in stark contrast to CGI shores, which were robustly hypermethylated in siTET1, siTET2, and siTET3 cells (Figure 3B(ii)). CGI methylation patterns occurred irrespective of intragenic versus intergenic location (Figure 3C); however CGI shore hypermethylation was most abundant in shores associated with promoters, as 26%, 10%, and 11% of gene promoters with CGIs had hypermethylated shores upon TET1, TET2, and TET3 depletion, respectively (Figure 3D). CGIs that lose 5mC or 5hmC significantly overlap among the TET knockdowns (Figure 3E; Figure S12B,C in Additional file 1), but analysis of CGI and CGI shore hypermethylation events reveals unique targets between TET1 and TET2 (Figure 3E). A significant proportion of hypermethylated CGI shores in siTET1 cells had decreased 5hmC (Figure 3F). On the other hand, CGI shore hypermethylation in siTET2 cells was associated with increased 5hmC (Figure 3F). TET1 targets promoter CGI shore hypermethylation at genes involved in basic cellular processes such as intracellular transport, transcription, and cell death (Figure S12D in Additional file 1). TET2 targets promoter CGI shore hypermethylation at genes involved in cytoskeletal organization, cell signal transduction pathways, and morphogenesis (Figure S12D in Additional file 1). Thus, again, TET1 and TET2 demonstrate a functional divergence in their impact on the epigenome. In summary, TET1, TET2, and TET3 preferentially remove methylation at CGI shores, particularly those within promoters, suggesting that TET activity is heavily influenced by CpG density, and TET1 and TET2 target separate sets of CGI shores where they function exclusively of one another in 5mC removal.
Gene body hypomethylation in siTET depletion conditions is associated with gene repression
TET functions in cytosine modification at active and repressed chromatin
Hypomethylation and hypermethylation outcomes were also closely connected with chromatin domains. H3K27me3-marked promoters and H2AK119ub-marked promoters were susceptible to hypomethylation upon TET depletion (Figure S14A in Additional file 1). Intriguingly, promoter hypermethylation also tended to occur at H2AK119ub-marked promoters (but not H3K27me3, H3K4me3, or bivalent promoters), suggesting that TETs actively demethylate 5mC at H2AK119ub-marked promoters. H3K4me3-marked promoters were protected from hypo- and hypermethylation under TET-depletion conditions, and genes marked with exon H3K36me3 were prone to intragenic hypermethylation (Figure S14B in Additional file 1). Generally, bivalent promoters and H3K9me3-marked genes were not targeted for hypo- or hypermethylation by TET proteins (in fact, H3K9me3-marked genes were significantly protected from methylation changes; Figure S14C in Additional file 1). In summary, H3K27me3- and H2K119Aub-marked genes tend to lose both 5hmC and 5mC when TETs are depleted. Active H3K4me3- and H3K36me3-marked genes become enriched for 5hmC in promoters and exons and become hypermethylated in gene bodies upon TET depletion. Thus, polycomb-repressed genes and highly active, H3K4me3/H3K36me3-marked genes exhibit opposing epigenetic fates under TET depletion conditions, and both epigenetic fates impact pathways associated with cancer phenotypes.
Loss of 5hmC in TET-depleted cells coincides with genes susceptible to aberrant hypermethylation in cancer
This study represents the first comprehensive genome-wide analysis of the role of TET1, TET2, and TET3 in patterning the distribution of 5mC and 5hmC in human cancer cells. Depletion of only one TET family member yielded robust reduction of 5hmC across intragenic regions, enhancers, and CGIs, and many of the same loci were affected by siTET1, siTET2, or siTET3 depletion conditions, suggesting a synergistic role for the TETs in establishment of 5hmC patterns in NCCIT cells. Loci uniquely affected by depletion of each TET family member were also identified. Importantly, our results reveal that TET2 and TET3, but not TET1, actively eliminate 5hmC throughout the genome, particularly at introns, as evidenced by hyper-hydroxymethylation in TET2- and TET3-depleted cells. Thus, our results suggest that all TETs, especially TET1, target loci for hydroxylation of 5mC to 5hmC, but only TET2 and TET3 are responsible for subsequent removal of 5hmC in the cytosine demethylation cascade. TET function in demethylation was particularly prominent at CGI shores, which became disproportionately hypermethylated relative to CGIs and surrounding regions. In addition to the role of the TETs in DNA demethylation, the results of this study unexpectedly implicate TETs in promoting DNA methylation, and show that TET activity is also closely connected with specific chromatin domains. The finding that TETs have a role in promoting 5hmC at loci targeted for aberrant methylation in cancer is consistent with an overall observation that TET establishment of intragenic 5hmC enrichment is associated with a state of transcriptional permissiveness. Likewise, TET-mediated 5hmC at enhancers is crucial for expression of neighboring highly active genes.
One key finding from our results was that genes and CGIs targeted for 5hmC maintenance by TET1, TET2, and TET3 overlap extensively among the three family members, but the impact of each TET on target gene DNA methylation was CpG density-dependent. Promoter 5hmC levels are inversely correlated with CpG density, as low CpG density promoters show the most abundant 5hmC in UD NCCIT cells, similar to murine ESCs . Depletion of TET1 had the greatest impact on 5hmC loss at HCPs, also consistent with results in murine ESCs where Tet1 was genetically inactivated . TET2 depletion in our system, however, had the greatest impact on 5hmC loss at LCPs, suggesting that TET1 and TET2 function more prominently at HCPs and LCPs, respectively. Such functional divergence between TET1 and TET2 likely relates to their protein structure. TET1 contains a CXXC zinc finger domain and possesses high affinity for non-methylated CpG-dense regions [20, 60, 61], whereas TET2 lacks this motif, perhaps allowing it to function more readily at or be specifically targeted to regions of low CpG density.
Reduction of TET2 or TET3 levels caused 5hmC accumulation in many regions of the genome. The simplest explanation for this observation is that TET2 and TET3 are primarily responsible for the formation of downstream cytosine intermediates (that is, 5-formylcytosine and 5-carboxylcytosine) within the demethylation cascade and disruption of either TET2 or TET3 yields accumulation of 5hmC, although this hypothesis has yet to be tested directly. An alternative explanation is that TET2 and TET3 limit each other’s 5mC to 5hmC hydroxylation activity. Within gene bodies, 5hmC accumulation was particularly evident in introns. In UD NCCIT cells, exons are enriched for 5hmC over introns, and these results suggest a role for TET2 and TET3 in the removal of 5hmC from introns. The potential impact of this function on maintaining the rate of transcription, preventing spurious transcription initiation, or preserving splicing fidelity is intriguing but unknown.
This study also reveals a dynamic interplay between TET activity and different chromatin marks. Previous work elucidated an association between TET1/5hmC occupancy and polycomb-/trithorax-mediated histone marks in ESCs [19–21], but our study is the first to provide a functional assessment of TET1, TET2, and TET3 activities within different chromatin domains in cancer cells for which extensive chromatin mark mapping is also available. These results indicate two opposing functions for TETs at H3K4me3-marked promoters and polycomb-marked (H3K27me3 and H2AK119ub) promoters: removal of 5hmC and enrichment of 5hmC, respectively (Figure 7B). H3K4me3-marked promoters are enriched for TET1 binding but are devoid of 5mC or 5hmC [19–21]. H3K4me3-marks are also characteristic of highly expressed genes and are typically associated with gene body H3K36me3 enrichment. The results herein reveal that TET2, in particular, is responsible for eliminating 5hmC at promoters of these highly expressed, H3K4me3- and H3K36me3-marked loci (Figure 7B(i)), providing an explanation for the paradoxical observation that H3K4me3-marked promoters are TET1-rich but 5hmC-deficient. TET1 was proposed to protect active H3K4me3 monovalent promoters from aberrant hypermethylation [19–21]. In our study, however, even with depletion of TET1, TET2, or TET3, H3K4me3-marked sites remained protected from DNA hypermethylation, suggesting that each of the TETs is dispensable for maintaining hypomethylation at H3K4me3 loci or that there is functional redundancy among the TETs in this protective role. 5hmC-rich H3K4me3- and H3K27me3-marked bivalent promoters showed significant 5hmC loss and gain in response to depletion of each of the TETs. Interestingly, bivalent promoters did not significantly accumulate or lose 5mC in response to TET depletion. One possible explanation for this is that TETs stabilize 5hmC (and possibly the other demethylation intermediates) but do not actively convert 5mC to 5hmC at bivalent promoters. This is further substantiated by unpublished data from our laboratory that DNMTs have no or low activity at bivalent promoters in the pluripotent state, suggesting that bivalent promoters have neither a propensity for 5mC accumulation nor a basis for active demethylation.
Polycomb repressive complex 2 (PRC2) recruits TET1 to bivalent H3K4me3- and H3K27me3-marked promoters, which are 5hmC-rich . H2AK119ub- and H3K27me3-marked promoters showed a disproportionate loss of 5hmC and 5mC under TET knockdown conditions, suggesting that TET1, TET2, and TET3 establish these cytosine modifications at polycomb repressed loci, perhaps as a means of mediating repression of PcG target genes by supporting 5mC accumulation (Figure 7B(ii,iii)). The facilitation of DNA methylation by TETs may occur indirectly and independently of their catalytic activity by facilitating a repressive chromatin state. Along these lines, TET1 recruits SIN3A, a known DNMT3B-interacting partner, to a subset of TET1 target genes (including H3K27me3-positive loci), thereby mediating transcriptional repression and possibly potentiating DNMT3B-dependent methylation [20, 64]. This model is supported by our laboratory’s observation that TET-depletion-induced hypomethylation occurred at a subset of promoters occupied by DNMT1 or DNMT3B (data not shown), again, pointing to a role for TETs in facilitating cytosine methylation. Since many promoters with loss of 5mC also exhibited loss of 5hmC in siTET cells, TETs might promote cytosine methylation through establishment of 5hmC. Intriguingly, UHRF1 binds 5hmC with high affinity, and UHRF1 is required for maintenance of DNA methylation by DNMT1 during DNA replication [29, 65]; thus, UHRF1 may provide a mechanistic link in this relationship in that 5hmC accumulation acts not as a precursor for active DNA demethylation, but rather is a signal for de novo DNA methylation. It will be critical in future experiments to determine the turnover rate of methyl groups and their derivatives in different chromatin domains of the genome, and correlate this with the presence or absence of DNMTs and TETs. Regions may exist where methyl group turnover promotes DNA demethylation, perhaps due to a lack of DNMTs, high TET-directed oxidation activity, and/or a particular combination of histone modifications. Alternatively, loci may exist where methyl group turnover combined with high DNMT activity, repressive chromatin signatures, and as yet uncharacterized TET activities (perhaps independent of their known catalytic functions), is essential for new or more extensive DNA methylation marks. If methyl group turnover is common even in constitutively methylated regions of the genome, then deregulation of any of the steps in this pathway (DNMTs, TETs, interacting factors, and substrate availability) could contribute to the hypo- and hypermethylation events that typify cancer cells.
Our expression analyses revealed both transcriptional activation and repression events resulting from depletion of each TET. Other examples of Tet1 depletion in murine ESCs have demonstrated upregulation and downregulation of target genes, indicating both transcriptional activation and repression roles for Tet1 [20, 59]. In all siTET depletions, transcriptional repression was significantly linked with loss of 5hmC at adjacent H3K27ac-marked enhancers, providing direct evidence that maintenance of 5hmC in enhancers is required to drive gene expression, particularly for highly expressed genes. Expression changes induced by TET deficiency did not show a clear relationship with promoter methylation changes (that is, gene repression did not significantly correspond with promoter hypermethylation). This is not completely unexpected, given previous studies showing that expression changes in siTet1-treated DNMT triple knockout cells, which have no 5mC or 5hmC, were similar to expression effects in siTet1-treated DNMT wild-type cells, suggesting that, for some genes, the impact of Tet1 on expression is independent of its catalytic activity  and may be due to the TET1 protein itself or other uncharacterized ‘activities’ of TET1. Thus, we suspect that some of the expression changes observed in our siTET1-, siTET2-, and siTET3-treated NCCIT cells (those not accounted for by 5hmC loss in enhancers) are related to functions separate from the TET roles in cytosine methylation patterning described here. The exact nature of these functions is currently unknown, but might be mediated through altered 5hmC levels, changes in 5hmC reader protein localization, or non-enzymatic activities of the TET proteins. Given the lack of knowledge of TET and 5hmC roles in the genome, cancer-specific TET mutations could potentially be directing pathogenic gene expression patterns via any of these routes, something that will be important to examine in future studies. Nonetheless, a link between 5hmC accumulation and gene activation was observed during differentiation of NCCIT cells. Genes with high 5hmC enrichment during differentiation were often abundantly expressed. This was especially true for some ectodermal and mesodermal patterning genes, which were enriched with large peaks of 5hmC during differentiation. Furthermore, genes that were robustly activated during induction of differentiation also tended to be repressed in TET1, TET2, or TET3 depleted cells. Taken together, we propose that TET-mediated enrichment of 5hmC promotes a transcriptionally permissive chromatin environment, and that disruption of this state represents a crucial step toward permanent gene silencing by aberrant DNA methylation in cancer cells.
The recent elucidation of TET hydroxylation activities on 5mC has changed our view of the epigenome from that of a steady-state methylome to the realization that it is a dynamic and mutable landscape. The results described herein establish a compelling framework for how TET-driven 5hmC patterning impacts gene expression. TET patterning of the epigenome is clearly a common basis of both mammalian development and cellular transformation, and the findings presented here that TETs have multi-dimensional functions in mediating DNA methylation, hydroxymethylation, and gene expression patterns is a crucial step for advancing our mechanistic understanding of how the epigenome functions in both normal and disease states. Overall, this study expands our knowledge of how TET dioxygenases impact cytosine modifications across the cancer genome and reveals that the chromatin landscape and DNA sequence composition significantly influence TET function.
Materials and methods
Cell culture, siRNA transfections, and extractions
NCCIT cells (from ATCC) and human H9 (WA09) ESCs were cultured as described  and differentiation (NCCIT cells only) was induced by addition of 10 μM all-trans RA (Sigma, St. Louis, MO USA) for 7 days. A172 cells (glioma) were obtained from ATCC and cultured in McCoy’s 5a media containing 10% fetal calf serum. On-TARGETplus SMARTpools (Dharmacon, Thermo Scientific, Lafayette, CO USA) composed of a mixture of four individual siRNAs targeting a single gene were used against TET1 (L-014635-02), TET2 (L-013776-03), and TET3 (L-022722-02) in separate experiments. Transfection with a negative control non-targeting siRNA (D-001206-13-20; Dharmacon, Thermo Scientific) was performed in parallel. For siRNA transfections, approximately 4.5 × 104 NCCIT cells were seeded in each well of a six-well plate. At 24 and 48 hours post-seeding, cells were transfected using PepMute siRNA transfection reagent (SignaGen, Rockville, MD USA) prepared according to the manufacturer’s protocol. Fresh growth medium (900 μl) was added to cells 30 minutes prior to addition of 100 μl of transfection reagent mix. The siRNA transfection mix was composed of 100 μl of PepMute transfection buffer, 1 μl of 40 μM siRNA, and 1.5 μl of PepMute reagent. Fresh media was added to cells at 72 hours post-seeding, and cells were harvested at 96 hours post-seeding. Total RNA was extracted by Trizol homogenization and purified according to the manufacturer’s protocols (Life Technologies, Carlsbad, CA USA). Genomic DNA was extracted by proteinase K digestion and phenol:chloroform extraction as described .
Affinity-based capture of 5hmC and 5mC and sequencing library preparation
Prior to affinity pull-downs, 5 μg of genomic DNA in 130 μl TE was sheared to less than 400 bp on a Covaris S220 focused-ultrasonicator according to the manufacturer’s instructions. Sheared samples were ethanol precipitated and resuspended in TE to a concentration of approximately 350 ng/μl based on nanodrop spectrophometric measurements. Samples were then normalized to the control sample by qPCR standard curves. DNA concentrations were adjusted based on the standard curve. 5hmC enrichment was performed using 2.5 μg of sheared DNA per reaction with the Hydroxymethyl Collector kit according to the manufacturer’s instructions (Active Motif, Carlsbad, CA USA). Each sample was performed in quadruplicate and replicates were pooled after the pull-down prior to preparation of sequencing libraries. Independent 5hmC-capture experiments were performed for 5hmC-qPCR validation experiments. Primers for validation qPCR are from  or are listed in Additional file 3. For 5mC-capture, 2 μg of sheared DNA was used as input for the MethylMagnet methylated-CpG DNA isolation kit according to the manufacturer’s instructions (Ribomed, Carlsbad, CA USA) and reactions were performed in quadruplicate for each sample. DNA sequencing libraries were generated from the 5mC and 5hmC captured DNA with the TruSeq DNA sample preparation kit (Illumina, San Diego, CA USA) according to manufacturer’s instructions. Agencourt AMPure XP Beads (Beckman Coulter, Pasadena, CA USA) used during library preparation were calibrated for size selection of DNA fragments greater than 200 bp. PCR amplification of the libraries was performed for 11 cycles. After PCR amplification, the library was gel purified using SYBR gold for visualization of DNA, quantified by qPCR (KAPA Biosystems library quantification kit, Wilmington, MA USA), and analyzed on a bioanalyzer with a high sensitivity DNA chip (Agilent, Santa Clara, CA USA) for quality control and quantification. Libraries were sequenced on an Illumina HiSeq2000 (50 bp read length) at the Tufts University Genomics Core Facility.
Raw sequencing reads were mapped to the UCSC human genome hg19 build using BWA V0.5.9  with a default parameter setting. Multiply mapped reads and uniquely mapped reads with mismatches and indels >5% of read lengths were filtered out. SICER V1.1  was used to identify enriched regions (peaks) in a sample and differentially enriched regions between two samples relative to an input with the following parameters: redundancy allowed = 1, window size = 200, fragment size = 300, effective genome size = 0.854, gap size = 600, E-value = 1,000, false discovery rate = 0.01. In-house scripts annotated peaks and differentially enriched regions with RefSeq, CGIs, and repeats in the UCSC genome browser , and classified them as promoter (-1 kbp to +1 for TSS), body, and 3′ end (TTS + 1 kbp). In some cases, gene bodies were further classified into 5′ UTR, exon, protein coding exon, 3′ UTR, and intron. Genes were also stratified based on the CpG density within their promoter regions (HCPs, intermediate CpG density promoters (ICPs), and LCPs) using the criteria in . In this classification, HCPs are ‘strong’ CGIs while ICPs are ‘weak’ CGIs. LCPs are a distinct class. Gene lists in promoters and bodies were analyzed using in-house scripts via the DAVID server (default settings) for functional annotation using gene ontologies and pathways . After discarding more than two reads mapping to the same location, mapped reads were lengthened to the 3’ end to reflect their original length, and counted based on their midpoint for genomic features such as genes, CGIs, and repeats. A genomic feature was binned by relative positions including upstream and downstream regions. Different numbers of mapped reads per sample were taken into account by calculating FPKM (fragments per kilobase per million fragments mapped). To illustrate the change in tag densities around genes, we used a relative length window for gene bodies and measured the average of normalized read coverage in a window.
5mC and 5hmC quantification and TAB-seq
DNA methylation and hydroxymethylation quantification was performed using the MethylFlash methylated and hydroxymethylated colorimetric DNA quantification kits (P-1034; p-1036; Epigentek, Farmingdale, NY USA) according to the manufacturer’s instructions. All samples were run in triplicate. TAB conversion of DNA was performed as described . To accommodate for Sanger sequencing, DNA was sheared with a Covaris S220 to less than 10 kb in size and purified by ethanol precipitation prior to TAB conversion. Bisulfite conversion and sequencing of DNA were performed as previously described . Up to 12 independent clones were sequenced for each region. Primer sequences are listed in Additional file 3. TAB-seq plots were generated with QUMA .
Expression analysis by qRT-PCR and microarray
CDNA synthesis, qRT-PCR, and data analysis was performed as described previously [73, 74]. qRT-PCR primers were designed and selected for optimal efficiency based on their performance with a standard curve of cDNA template. qRT-PCR was performed with at least three replicates. Primer sequences are listed in Additional file 3. Gene expression profiling was performed using Affymetrix Human Gene 1.0 ST arrays. All samples were analyzed in duplicate at the Georgia Regents University Cancer Center Genomics Core facility as described previously .
Gene ontology analysis and statistical methods for data set comparisons
Ontology analysis was performed using the functional annotation tool within the DAVID bioinformatics database [70, 75]. Fisher exact test with a two-tailed P-value calculation was used for testing the significance of data set comparisons as described previously for similar data sets . For added stringency, a modified EASE score was applied to all Fisher exact tests [70, 75].
Sequencing and expression microarray data have been deposited into the NCBI Gene Expression Omnibus database under accession number GSE51903. Additional published datasets used in this analysis include: GSM747152, GSM605307, and GSE38938.
differentiated by retinoic acid
embryonic carcinoma cell
embryonic stem cell
histone H2A lysine 119 ubiquitination
histone H3 lysine 27 acetylation
histone H3 lysine 27 trimethylation
histone H3 lysine 36 trimethylation
histone H3 lysine 4 trimethylation
high CpG density promoter
intermediate CpG density promoter
low CpG density promoter
polymerase chain reaction
small interfering RNA
TET-assisted bisulfite conversion
transcription start site
transcription termination site
undifferentiated pluripotent state
We thank Joo Hee Kim for technical assistance, Kip Bodi and the Tufts University Genomics Core Facility for assistance with Illumina sequencing, Jonathan R Mathias for editing the manuscript and providing data analysis support, and Eiko Kitamura and the Georgia Regents University Cancer Center Genomics Core Facility for assistance with expression microarrays. This work was supported by NIH grants R01 CA114229 (KDR) and F32 CA163054 (ELP).
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