Abstract:DNA methylation is considered a stable epigenetic mark, yet methylation patterns can vary during differentiation and in diseases such as cancer. Local levels of DNA methylation result from opposing enzymatic activities, the rates of which remain largely unknown. Here we developed a theoretical and experimental framework enabling us to infer methylation and demethylation rates at 860,404 CpGs in mouse embryonic stem cells. We find that enzymatic rates can vary as much as two orders of magnitude between CpGs wit… Show more
“…These sites also show tissue-specific variability of DNA methylation and display altered methylation patterns in many diseases ( 3 , 8 , 17–20 ). These observations suggest that pathways that recruit de novo methylation vary from cell type to cell type and that the genome-wide methylation patterns are a composite picture resulting from combined activity of multiple DNMT-targeting mechanisms and mechanisms that actively or passively remove methylation ( 21 ). In previous work, we and others have shown that the de novo DNMTs associate with genomic regions that are marked by distinct chromatin modifications, resulting in enhanced deposition of methyl marks at these sites.…”
Mammalian de novo DNA methyltransferases (DNMT) are responsible for the establishment of cell-type-specific DNA methylation in healthy and diseased tissues. Through genome-wide analysis of de novo methylation activity in murine stem cells we uncover that DNMT3A prefers to methylate CpGs followed by cytosines or thymines, while DNMT3B predominantly methylates CpGs followed by guanines or adenines. These signatures are further observed at non-CpG sites, resembling methylation context observed in specialised cell types, including neurons and oocytes. We further show that these preferences result from structural differences in the catalytic domains of the two de novo DNMTs and are not a consequence of differential recruitment to the genome. Molecular dynamics simulations suggest that, in case of human DNMT3A, the preference is due to favourable polar interactions between the flexible Arg836 side chain and the guanine that base-pairs with the cytosine following the CpG. By exchanging arginine to a lysine, the corresponding side chain in DNMT3B, the sequence preference is reversed, confirming the requirement for arginine at this position. This context-dependent enzymatic activity provides additional insights into the complex regulation of DNA methylation patterns.
“…These sites also show tissue-specific variability of DNA methylation and display altered methylation patterns in many diseases ( 3 , 8 , 17–20 ). These observations suggest that pathways that recruit de novo methylation vary from cell type to cell type and that the genome-wide methylation patterns are a composite picture resulting from combined activity of multiple DNMT-targeting mechanisms and mechanisms that actively or passively remove methylation ( 21 ). In previous work, we and others have shown that the de novo DNMTs associate with genomic regions that are marked by distinct chromatin modifications, resulting in enhanced deposition of methyl marks at these sites.…”
Mammalian de novo DNA methyltransferases (DNMT) are responsible for the establishment of cell-type-specific DNA methylation in healthy and diseased tissues. Through genome-wide analysis of de novo methylation activity in murine stem cells we uncover that DNMT3A prefers to methylate CpGs followed by cytosines or thymines, while DNMT3B predominantly methylates CpGs followed by guanines or adenines. These signatures are further observed at non-CpG sites, resembling methylation context observed in specialised cell types, including neurons and oocytes. We further show that these preferences result from structural differences in the catalytic domains of the two de novo DNMTs and are not a consequence of differential recruitment to the genome. Molecular dynamics simulations suggest that, in case of human DNMT3A, the preference is due to favourable polar interactions between the flexible Arg836 side chain and the guanine that base-pairs with the cytosine following the CpG. By exchanging arginine to a lysine, the corresponding side chain in DNMT3B, the sequence preference is reversed, confirming the requirement for arginine at this position. This context-dependent enzymatic activity provides additional insights into the complex regulation of DNA methylation patterns.
“…To further test if the observed difference could be influenced by the genomic context or different library representation of the queried sequences, we re-calculated the methylation scores only on the same CpGpNs that were covered in both, the TKO-DNMT3A2 and the TKO-DNMT3B libraries (Supplementary Figure 1d), and also on CpGpNs that were at least 80% methylated in wild type ES cells (Supplementary Figure 1e). The latter was necessary to exclude that active promoters and enhancers with elevated levels of DNA methylation turnover due to active DNA de-methylation (3, 4, 38) could have a potential influence on the calculated methylation scores. In both cases, the same sequence preference was observed when using these refined CpG sites (Supplementary Figure 1d-e), suggesting that different sequence composition in the WGBS libraries or genomics localisation is not the cause for the observed differences.…”
16Mammalian de novo DNA methyltransferases (DNMT) are responsible for the establishment of 17 cell-type-specific DNA methylation in healthy and diseased tissues. Through genome-wide 18 analysis of de novo methylation activity in murine stem cells we uncover that DNMT3A prefers 19 to methylate CpGs followed by cytosines or thymines, while DNMT3B predominantly methylates 20 CpGs followed by guanines or adenines. These signatures are further observed at non-CpG 21 sites, resembling methylation context observed in specialised cell types, including neurons and 22 oocytes. We further show that these preferences are not mediated by the differential recruitment 23 of the two de novo DNMTs to the genome but are resulting from structural differences in their 24 catalytic domains. Molecular dynamics simulations suggest that, in case of DNMT3A, the 25 preference is due to favourable polar interactions between the flexible Arg836 side chain and 26 the guanine that base-pairs with the cytosine following the CpG. This context-dependent de 27 novo DNA methylation provides additional insights into the complex regulation of methylation 28 patterns in different cell types. 29 34 replication, the maintenance methyltransferase DNMT1 ensures correct propagation of the 35 methyl mark (1, 2). Numerous genome-wide studies identified the exact position and tissue-36 specific dynamics of individual methyl groups on DNA. These revealed that the majority of CpGs 37 in mammalian genomes are fully methylated, with the exception of active promoters and cell-38 type-specific enhancer elements (3, 4). In addition to CpG methylation, non-CpG (or CpH) 39 methylation has been identified in numerous tissues (3, 5, 6), with highest levels found in brain 40 where it is suggested to potentially contribute to gene regulation and neuronal function through 41 readout by the methyl-CpG-binding protein MeCP2 (7-10).
43Nevertheless, the mechanisms governing the precise deposition of DNA methylation to 44 the genome remain to be fully understood. Although the mammalian genome is almost entirely 45 methylated (3, 4), several regions rely on active recruitment of de novo DNA methylation 46 activity, including promoters, enhancers and CpG islands (11-13), repetitive elements (14, 15),
47and transcribed gene bodies (16, 17). These sites also show tissue-specific variability of DNA 48 methylation and display altered methylation patterns in many diseases (4, 9,(18)(19)(20)(21). These 49 observations suggest that pathways that recruit de novo methylation vary from cell type to cell 50 type and that the genome-wide methylation patterns are a composite picture resulting from 51 combined activity of multiple DNMT targeting mechanisms and mechanisms that actively or 52 passively remove methylation. In previous work, we and others have shown that the de novo 53 DNMTs associate with genomic regions that are marked by distinct chromatin modifications, 54 resulting in enhanced deposition of methyl marks at these sites. For example, readout of 55 4 H3K36me3 by DNMT3B targe...
“…Moreover, female cells turned out to be more sensitive to the long-term effects of MEK inhibition, consistent with the expression of MEK inhibitory factors from the two active X chromosomes. Transcriptional mechanisms have been proposed to connect MEK-inhibition with DNA demethylation, specifically through upregulation of PRDM14, a transcriptional repressor of the DNA methyl-transferase DNMT3 gene family, and activity of the Tet-family of dioxygenases [ 83 , 84 , 86 , 87 , 90 ]. Fig.…”
Section: Dna Methylation Separates Cdk8/19i From 2imentioning
Human naïve pluripotent stem cells (PSCs) represent an optimal homogenous starting point for molecular interventions and differentiation strategies. This is in contrast to the standard primed PSCs which fluctuate in identity and are transcriptionally heterogeneous. However, despite many efforts, the maintenance and expansion of human naïve PSCs remains a challenge. Here, we discuss our recent strategy for the stabilization of human PSC in the naïve state based on the use of a single chemical inhibitor of the related kinases CDK8 and CDK19. These kinases phosphorylate and negatively regulate the multiprotein Mediator complex, which is critical for enhancer-driven recruitment of RNA Pol II. The net effect of CDK8/19 inhibition is a global stimulation of enhancers, which in turn reinforces transcriptional programs including those related to cellular identity. In the case of pluripotent cells, the presence of CDK8/19i efficiently stabilizes the naïve state. Importantly, in contrast to previous chemical methods to induced the naïve state based on the inhibition of the FGF-MEK-ERK pathway, CDK8/19i-naïve human PSCs are chromosomally stable and retain developmental potential after long-term expansion. We suggest this could be related to the fact that CDK8/19 inhibition does not induce DNA demethylation. These principles may apply to other fate decisions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
