Abstract
Precise deposition of CpG methylation is critical for mammalian development and tissue homeostasis and is often dysregulated in human diseases. The localization of de novo DNA methyltransferase DNMT3A is facilitated by its PWWP domain recognizing histone H3 lysine 36 (H3K36) methylation1,2 and is normally depleted at CpG islands (CGIs)3. However, methylation of CGIs regulated by Polycomb repressive complexes (PRCs) has also been observed4,5,6,7,8. Here, we report that DNMT3A PWWP domain mutations identified in paragangliomas9 and microcephalic dwarfism10 promote aberrant localization of DNMT3A to CGIs in a PRC1-dependent manner. DNMT3A PWWP mutants accumulate at regions containing PRC1-mediated formation of monoubiquitylated histone H2A lysine 119 (H2AK119ub), irrespective of the amounts of PRC2-catalyzed formation of trimethylated histone H3 lysine 27 (H3K27me3). DNMT3A interacts with H2AK119ub-modified nucleosomes through a putative amino-terminal ubiquitin-dependent recruitment region, providing an alternative form of DNMT3A genomic targeting that is augmented by the loss of PWWP reader function. Ablation of PRC1 abrogates localization of DNMT3A PWWP mutants to CGIs and prevents aberrant DNA hypermethylation. Our study implies that a balance between DNMT3A recruitment by distinct reader domains guides de novo CpG methylation and may underlie the abnormal DNA methylation landscapes observed in select human cancer subtypes and developmental disorders.
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Data availability
The ChIP–seq and RRBS data have been deposited in the GEO database under accession number GSE147879. Additional ChIP–seq data from GSE118785 and GSE69291 were also used in this study. Source data are provided with this paper.
Code availability
Custom scripts (R, AWK and Bash) used to compute delta score correlation, generate scatterplots, H3K36me2-ranked intergenic regions, enrichment by genomic annotation and DNMT3A1 enrichment tests are available in the following GitHub repository: https://github.com/pr-gen/dnmt3a_h2ak119ub.
References
Baubec, T. et al. Genomic profiling of DNA methyltransferases reveals a role for DNMT3B in genic methylation. Nature 520, 243–247 (2015).
Weinberg, D. N. et al. The histone mark H3K36me2 recruits DNMT3A and shapes the intergenic DNA methylation landscape. Nature 573, 281–286 (2019).
Wu, H. et al. Dnmt3a-dependent nonpromoter DNA methylation facilitates transcription of neurogenic genes. Science 329, 444–448 (2010).
Chen, Z., Yin, Q., Inoue, A., Zhang, C. & Zhang, Y. Allelic H3K27me3 to allelic DNA methylation switch maintains noncanonical imprinting in extraembryonic cells. Sci. Adv. 5, eaay7246 (2019).
Mohn, F. et al. Lineage-specific Polycomb targets and de novo DNA methylation define restriction and potential of neuronal progenitors. Mol. Cell 30, 755–766 (2008).
Ohm, J. E. et al. A stem cell-like chromatin pattern may predispose tumor suppressor genes to DNA hypermethylation and heritable silencing. Nat. Genet. 39, 237–242 (2007).
Schlesinger, Y. et al. Polycomb-mediated methylation of Lys27 of histone H3 pre-marks genes for de novo methylation in cancer. Nat. Genet. 39, 232–236 (2007).
Widschwendter, M. et al. Epigenetic stem cell signature in cancer. Nat. Genet. 38, 157–158 (2007).
Remacha, L. et al. Gain-of-function mutations in DNMT3A in patients with paraganglioma. Genet. Med. 20, 1644–1651 (2018).
Heyn, P. et al. Gain-of-function DNMT3A mutations cause microcephalic dwarfism and hypermethylation of Polycomb-regulated regions. Nat. Genet. 51, 96–105 (2019).
Dukatz, M. et al. H3K36me2/3 binding and DNA binding of the DNA methyltransferase DNMT3A PWWP domain both contribute to its chromatin interaction. J. Mol. Biol. 431, 5063–5074 (2019).
Sendžikaitė, G. et al. A DNMT3A PWWP mutation leads to methylation of bivalent chromatin and growth retardation in mice. Nat. Commun. 10, 1884 (2019).
Chen, T., Ueda, Y., Xie, S. & Li, E. A novel Dnmt3a isoform produced from an alternative promoter localizes to euchromatin and its expression correlates with active de novo methylation. J. Biol. Chem. 277, 38746–38754 (2002).
Manzo, M. et al. Isoform-specific localization of DNMT3A regulates DNA methylation fidelity at bivalent CpG islands. EMBO J. 36, 3421–3434 (2017).
Lu, C. et al. Histone H3K36 mutations promote sarcomagenesis through altered histone methylation landscape. Science 352, 844–849 (2016).
Tavares, L. et al. RYBP-PRC1 complexes mediate H2A ubiquitylation at polycomb target sites independently of PRC2 and H3K27me3. Cell 148, 664–678 (2012).
Wu, X., Johansen, J. V. & Helin, K. Fbxl10/Kdm2b recruits polycomb repressive complex 1 to CpG islands and regulates H2A ubiquitylation. Mol. Cell 49, 1134–1146 (2013).
Blackledge, N. P. et al. Variant PRC1 complex-dependent H2A ubiquitylation drives PRC2 recruitment and Polycomb domain formation. Cell 157, 1445–1459 (2014).
de Napoles, M. et al. Polycomb group proteins Ring1A/B link ubiquitylation of histone H2A to heritable gene silencing and X inactivation. Dev. Cell 7, 663–676 (2004).
Wang, H. et al. Role of histone H2A ubiquitination in Polycomb silencing. Nature 431, 873–878 (2004).
Margueron, R. et al. Ezh1 and Ezh2 maintain repressive chromatin through different mechanisms. Mol. Cell. 32, 503–518 (2008).
Cooper, S. et al. Targeting polycomb to pericentric heterochromatin in embryonic stem cells reveals a role for H2AK119u1 in PRC2 recruitment. Cell Rep. 7, 1456–1470 (2014).
Cooper, S. et al. Jarid2 binds mono-ubiquitylated H2A lysine 119 to mediate crosstalk between Polycomb complexes PRC1 and PRC2. Nat. Commun. 7, 13661 (2016).
Fradet-Turcotte, A. et al. 53BP1 is a reader of the DNA-damage-induced histone H2A Lys 15 ubiquitin mark. Nature 499, 50–54 (2013).
Wilson, M. D. et al. The structural basis of modified nucleosome recognition by 53BP1. Nature 536, 100–103 (2016).
Goldknopf, I. L. & Busch, H. Isopeptide linkage between nonhistone and histone 2A polypeptides of chromosomal conjugate-protein A24. Proc. Natl Acad. Sci. USA 74, 864–868 (1977).
West, M. H. & Bonner, W. M. Histone 2B can be modified by the attachment of ubiquitin. Nucleic Acids Res. 8, 4671–4680 (1980).
Spencer, D. H. et al. CpG Island hypermethylation mediated by DNMT3A is a consequence of AML progression. Cell 168, 801–816 (2017).
Deplus, R. et al. Regulation of DNA methylation patterns by CK2-mediated phosphorylation of Dnmt3a. Cell Rep. 8, 743–753 (2014).
Kumar, D. & Lassar, A. B. Fibroblast growth factor maintains chondrogenic potential of limb bud mesenchymal cells by modulating DNMT3A recruitment. Cell Rep. 8, 1419–1431 (2014).
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).
Harutyunyan, A. S. et al. H3K27M induces defective chromatin spread of PRC2-mediated repressive H3K27me2/me3 and is essential for glioma tumorigenesis. Nat. Commun. 10, 1262 (2019).
Orlando, D. A. et al. Quantitative ChIP–seq normalization reveals global modulation of the epigenome. Cell Rep. 9, 1163–1170 (2014).
Ramírez, F. et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 44, W160–W165 (2016).
Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
Neph, S. et al. BEDOPS: high-performance genomic feature operations. Bioinformatics 28, 1919–1920 (2012).
Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).
Robinson, J. T. et al. Integrative genomics viewer. Nat. Biotechnol. 29, 24–26 (2011).
Xu, S., Grullon, S., Ge, K. & Peng, W. Spatial clustering for identification of ChIP-enriched regions (SICER) to map regions of histone methylation patterns in embryonic stem cells. Methods Mol. Biol. 1150, 97–111 (2014).
Cavalcante, R. G. & Sartor, M. A. annotatr: genomic regions in context. Bioinformatics 33, 2381–2383 (2017).
Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, 2016).
Kim, S. ppcor: an R package for a fast calculation to semi-partial correlation coefficients. Commun. Stat. Appl. Methods 22, 665–674 (2015).
Amemiya, H. M., Kundaje, A. & Boyle, A. P. The ENCODE blacklist: identification of problematic regions of the genome. Sci. Rep. 9, 9354 (2019).
Garrett-Bakelman, F. E. et al. Enhanced reduced representation bisulfite sequencing for assessment of DNA methylation at base pair resolution. J. Vis. Exp. 96, e52246 (2015).
Krueger, F. & Andrews, S. R. Bismark: a flexible aligner and methylation caller for Bisulfite-seq applications. Bioinformatics 27, 1571–1572 (2011).
Condon, D. E. et al. Defiant: (DMRs: easy, fast, identification and ANnoTation) identifies differentially methylated regions from iron-deficient rat hippocampus. BMC Bioinf. 19, 31 (2018).
Acknowledgements
We thank members of the Lu, Majewski and Allis laboratories for critical reading of the manuscript. We thank the Epigenomics Core at Weill Cornell Medicine for generating RRBS libraries, sequencing, data alignment and methylation calls. This research was supported by the United States National Institutes of Health (NIH) grants (P01CA196539 to C.D.A. and J.M.; R00CA212257 to C.L.; T32GM007739 and F30CA224971 to D.N.W.; R44GM116584 and R44GM117683 to M.-C.K.); St. Jude Children’s Research Hospital and the Rockefeller University (to C.D.A.); Genome Canada, Genome Quebec, Canadian Institutes of Health Research, and computational infrastructure from Compute Canada and Calcul Quebec (to J.M.). C.L. is the Giannandrea Family Dale F. Frey Breakthrough Scientist of the Damon Runyon Foundation (DFS-28–18), a Pew-Stewart Scholar for Cancer Research and supported by an AACR Gertrude B. Elion Cancer Research Grant.
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Contributions
D.N.W., P.R., C.L., J.M. and C.D.A. conceived and designed the experiments. D.N.W. and C.H. performed cell-based experiments and analyzed data. P.R., X.C., D.B. and J.M. performed bioinformatic analysis on sequencing-based data. M.R.M., I.K.P., Z.B.G. and M.-C.K. performed in vitro experiments with recombinant protein and analyzed data. All authors contributed to the written manuscript.
Corresponding authors
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Competing interests
M.R.M., I.K.P., Z.B.G. and M.-C.K. declare competing interests. EpiCypher is a commercial developer and supplier of platforms used in this study: recombinant semisynthetic modified nucleosomes and the dCypher nucleosome binding assay. The remaining authors declare no competing interests.
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Peer review information Nature Genetics thanks Alexander Meissner, Albert Jeltsch, Robert Klose and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Extended data
Extended Data Fig. 1 Profiling DNMT3A PWWP mutant genomic targeting genome-wide.
a) Genome browser representation of ChIP-seq normalized reads for H3K36me2, H2AK119ub, H3K27me3, and replicates of DNMT3A1 wild-type and DNMT3A1 PWWP mutants in mouse MSCs at chromosome 4: 3.90-3.99 Mb and chromosome 14: 45.1-45.4 Mb. CGIs (green) and genes from the RefSeq database are annotated at the bottom. The shaded areas indicate H2AK119ub-enriched genomic regions. b) Heat map showing genome-wide, pairwise Pearson correlations across 10-kb bins (n = 245,842) between H3K36me2, H3K36me3, H3K27me3, GC content, and RING1B with replicates of H2AK119ub, DNMT3A1 wild-type, and DNMT3A1 PWWP mutants. c) Scatterplots showing genome-wide, pairwise Pearson correlations across 10-kb bins (n = 245,842) for ChIP-seq normalized reads between H3K36me2, H3K36me3, H3K27me3, H2AK119ub, GC content, DNMT3A1 wild-type, DNMT3A1 PWWP mutants, and RING1B. Pearson’s correlation coefficients are indicated. d) Immunoblots of lysates generated from parental and sgDnmt3a mouse MSCs. Vinculin was used as a loading control. Data are representative of two independent experiments. e) Scatterplot showing genome-wide Pearson correlation across 10-kb bins (n = 245,842) for ChIP-seq normalized reads of DNMT3A1 ∆PWWP between parental and sgDnmt3a cells. Pearson’s correlation coefficient is indicated.
Extended Data Fig. 2 Disease-associated DNMT3A PWWP mutations alter recruitment to H3K36me2-enriched regions.
a) Genome browser representation of ChIP-seq normalized reads for H3K36me2, H3K36me3, H3K27me3, H2AK119bb, DNMT3A1 wild-type and DNMT3A1 PWWP mutants in mouse MSCs at chromosome 6: 50.9-51.2 Mb. The shaded areas indicate H3K36me2-enriched (orange) and H2AK119ub-enriched (red) genomic regions. b) ChIP-seq normalized reads for DNMT3A1 wild-type (gray) in mouse MSCs relative to H3K36me2 at intergenic regions. Intergenic regions greater than 10-kb (n = 13,990) were ranked and sorted by mean H3K36me2 enrichment in MSCs. The black line indicates mean H3K36me2 enrichment per bin. c) ChIP-seq normalized reads for DNMT3A1 ∆PWWP (orange) in mouse MSCs relative to H3K36me2 at intergenic regions. Intergenic regions greater than 10-kb (n = 13,990) were ranked and sorted by mean H3K36me2 enrichment in MSCs. The black line indicates mean H3K36me2 enrichment per bin. d) Ratio of observed-to-expected ChIP-seq reads for DNMT3A1 wild-type, ∆PWWP, and H2AK119ub in annotated genomic regions. Numbers of expected reads were generated assuming equivalent genomic distribution to input. e) Enrichment heat map depicting ChIP-seq normalized reads centered at H2AK119ub peaks ± 10-kb (n = 16,064), sorted by H3K27me3 levels for H3K36me2, H3K27me3, and GC content with replicates of DNMT3A1 wild-type, DNMT3A1 PWWP mutants, and H2AK119ub.
Extended Data Fig. 3 DNMT3A mutants colocalize with H2AK119ub independently of H3K27me3.
a) Genome browser representation of ChIP-seq normalized reads for H2AK119ub, H3K27me3, DNMT3A1 wild-type and DNMT3A1 PWWP mutants in mouse MSCs at chromosome 14: 122.6-123.1 Mb. Genes from the RefSeq database are annotated at the bottom. The shaded areas indicate H3K27me3-enriched (purple) and H2AK119ub-enriched (red) genomic regions. b) Genome-wide partial correlations of ChIP-seq normalized reads across 10-kb bins (n = 245,842) in parental MSCs. Left: relationships between DNMT3A1 PWWP mutants and H2AK119ub after controlling for H3K27me3 and H3K36me2. Right: relationships between DNMT3A1 PWWP mutants and H3K27me3 after controlling for H2AK119ub and H3K36me2. P values of partial correlations were determined using a Student’s t distribution42. c) Enrichment heat map depicting ChIP-seq normalized reads centered at H2AK119ub-depleted H3K27me3 peaks ± 10-kb (n = 34,361) for DNMT3A1 wild-type, DNMT3A1 PWWP mutants, RING1B, H2AK119ub, H3K27me3, H3K36me2, and H3K36me3. Regions are sorted by H3K36me2 enrichment. d) Enrichment heat map depicting ChIP-seq normalized reads centered at H3K27me3-enriched H2AK119ub peaks ± 10-kb (n = 9,868) for DNMT3A1 wild-type, DNMT3A1 PWWP mutants, RING1B, H2AK119ub, H3K27me3, H3K36me2, and H3K36me3. Regions are sorted by H3K36me2 enrichment. e) Enrichment heat map depicting ChIP-seq normalized reads centered at H3K27me3-depleted H2AK119ub peaks ± 10-kb (n = 6,837) for DNMT3A1 wild-type, DNMT3A1 PWWP mutants, RING1B, H2AK119ub, H3K27me3, H3K36me2, and H3K36me3. Regions are sorted by H3K36me2 enrichment.
Extended Data Fig. 4 Loss of PWWP reader domain function promotes DNMT3A targeting to CpG islands.
a) Observed DNMT3A1 wild-type and ∆PWWP enrichment at 10-kb bins overlapping CpG islands (n = 16,414) in MSCs compared to expected signal represented by enrichment at randomly-shuffled 10-kb regions (n = 16,414). b) Overlap analysis of H2AK119ub peaks, H3K27me3 peaks, and CpG islands in mouse MSCs. Jaccard index for pairwise comparisons are indicated. c) Overlap analysis of DNMT3A1 wild-type (top 5% of 10-kb bins), DNMT3A ∆PWWP (top 5% of 10-kb bins), and CpG islands in mouse MSCs. Jaccard index for pairwise comparisons are indicated. d) Enrichment heat map depicting ChIP-seq normalized reads centered at CpG islands ± 5-kb for DNMT3A1 wild-type, DNMT3A1 PWWP mutants, RING1B, H2AK119ub, H3K27me3, H3K36me2, and H3K36me3. Regions are sorted by H2AK119ub enrichment.
Extended Data Fig. 5 Perturbation of PRC1 and PRC2 in mouse MSCs.
a) Immunoblots of lysates generated from parental, sgRing1a/b, and sgEzh2 mouse MSCs. Vinculin and total H3 were used as loading controls. Data are representative of two independent experiments. b) Ratios of ChIP-seq reads for H2AK119ub and H3K27me3 between target chromatin (mouse) and reference spike-in chromatin (Drosophila) in parental, sgRing1a/b, and sgEzh2 mouse MSCs. c) Absolute number of ChIP-seq peaks for H2AK119ub and H3K27me3 called by SICER2 in parental (first replicate), sgRing1a/b, and sgEzh2 mouse mMSCs. d) Genome browser representation of ChIP-seq normalized reads for H2AK119ub and H3K27me3 in parental, sgRing1a/b, and sgEzh2 mouse MSCs at chromosome 14: 50.05-55.65 Mb and chromosome 3: 108.1-108.3 Mb. CGIs (green) and genes from the RefSeq database are annotated at the bottom. e) Rx-adjusted ratio of observed-to-expected ChIP-seq reads for H2AK119ub in annotated genomic regions in parental, sgRing1a/b, and sgEzh2 cells. Numbers of expected reads were generated assuming equivalent genomic distribution to input. f) Rx-adjusted ratio of observed-to-expected ChIP-seq reads for H3K27me3 in annotated genomic regions in parental, sgRing1a/b, and sgEzh2 cells. Numbers of expected reads were generated assuming equivalent genomic distribution to input.
Extended Data Fig. 6 Genetic ablation of PRC1 abrogates recruitment of DNMT3A mutants despite persistence of H3K27me3.
a) Immunoblots of lysates generated from parental and sgRing1a/b mouse MSCs that ectopically express HA-tagged DNMT3A1 PWWP mutants. Vinculin was used as a loading control. Data are representative of two independent experiments. b) Genome-wide partial correlations of ChIP-seq normalized reads across 10-kb bins (n = 245,842) between parental and sgRing1a/b MSCs. Left: relationships between changes in DNMT3A1 PWWP mutants and H2AK119ub after controlling for changes in H3K27me3. Right: relationships between changes in DNMT3A1 PWWP mutants and H3K27me3 after controlling for changes in H2AK119ub. P values of partial correlations were determined using a Student’s t distribution42. c) Genome browser representation of ChIP-seq normalized reads for H2AK119ub, H3K27me3, DNMT3A1 wild-type and DNMT3A1 PWWP mutants in parental and sgRing1a/b mouse MSCs at chromosome 11: 21.96-22.03 Mb and chromosome 16: 57.0-57.2 Mb. CGIs (green) and genes from the RefSeq database are annotated at the bottom. The shaded areas indicate H2AK119Ub-enriched (red) genomic regions. d) Difference in ChIP-seq normalized reads of DNMT3A1 K299I, R318W, W330R, and D333N between parental and sgRing1a/b mouse MSCs relative to that of H2AK119ub for 10-kb non-overlapping bins genome-wide (n = 245,842). Pearson’s correlation coefficient is indicated. e) Difference in ChIP-seq normalized reads of DNMT3A1 K299I, R318W, W330R, and D333N between parental and sgRing1a/b mouse MSCs relative to that of H3K27me3 for CGIs (n = 15,492). Pearson’s correlation coefficient is indicated.
Extended Data Fig. 7 DNMT3A recruitment to H2AK119ub-enriched regions remains intact upon genetic ablation of PRC2.
a) Immunoblots of lysates generated from parental and sgEzh2 mouse MSCs that ectopically express HA-tagged DNMT3A1 PWWP mutants. Vinculin was used as a loading control. Data are representative of two independent experiments. b) Enrichment heat map depicting ChIP-seq normalized reads centered at H2AK119ub peaks ± 10-kb (n = 16,064) for DNMT3A1 wild-type, DNMT3A1 PWWP mutants, H2AK119ub, and H3K36me2 in sgEzh2 mouse MSCs. Regions are sorted by increasing H3K36me2 enrichment. c) Genome browser representation of ChIP-seq normalized reads for H2AK119ub, H3K27me3, DNMT3A1 wild-type and DNMT3A1 PWWP mutants in parental and sgEzh2 mouse MSCs at chromosome 2: 150.49-150.64 Mb and chromosome 9: 70.58-70.72 Mb. CGIs (green) and genes from the RefSeq database are annotated at the bottom. The shaded areas indicate genomic regions enriched for both H2AK119ub and H3K27me3. d) Violin plots for ChIP-seq normalized reads across 10-kb bins overlapping parental H3K36me2-depleted H2AK119ub peak regions (n = 16,436) of DNMT3A1 wild-type and PWWP mutants in parental (red), sgRing1a/b (green), and sgEzh2 (blue) mouse MSCs. The center line in the embedded boxplots represents the median, the box limits are the 25th and 75th percentiles, and the whiskers are the minimum to maximum values. Outliers beyond 1.5 times the value of the 25th and 75th percentile across all bins are excluded (n = 269 excluded). e) Violin plots for ChIP-seq normalized reads across 10-kb bins overlapping parental H3K36me2-depleted H2AK119ub-enriched CGIs (n = 4,621) of DNMT3A1 wild-type and PWWP mutants in parental (red), sgRing1a/b (green), and sgEzh2 (blue) mouse MSCs. The center line in the embedded boxplots represents the median, the box limits are the 25th and 75th percentiles, and the whiskers are the minimum to maximum values. Outliers beyond 1.5 times the value of the 25th and 75th percentile across all bins are excluded (n = 87 excluded).
Extended Data Fig. 8 H2AK119ub interaction potential is specific for DNMT3A and resides within putative N-terminal ubiquitin-dependent recruitment region.
a) AlphaLISA counts for interaction of GST-tagged DNMT3APWWP titrated against modified (as indicated) or unmodified (rNuc) nucleosomes. Data are mean values from replicates and are representative of two independent experiments. b) Schematic of wild-type, deletion, and domain swap mutants of DNMT3A1, DNMT3A2, and DNMT3B. c) Immunoblots of lysates generated from parental mouse MSCs that ectopically express HA-tagged wild-type, deletion, and domain swap mutants of DNMT3A1, DNMT3A2, and DNMT3B. Vinculin was used as a loading control. Data are representative of two independent experiments. d) Fold enrichment of DNMT3A1, DNMT3A2, DNMT3B, and their corresponding deletion mutants at H2AK119ub-enriched regions in mouse MSCs, measured by ChIP–qPCR. Each data point represents signal at an individual locus (n = 6). Bar plots and whiskers are mean ± s.d. Data are representative of two independent experiments. P values were determined by one-way analysis of variance (ANOVA). e) Fold enrichment of DNMT3A1 ∆PWWP and co-deletion mutants of N-terminal disordered (∆1-159) and ordered (∆160-219) domains at H2AK119ub-enriched regions in mouse MSCs, measured by ChIP–qPCR. Each data point represents signal at an individual locus (n = 6). Bar plots and whiskers are mean ± s.d. Data are representative of two independent experiments. P values were determined by one-way analysis of variance (ANOVA). f) Enrichment heat map depicting ChIP-seq normalized reads centered at H2AK119ub peaks ± 10-kb (n = 16,064) for DNMT3A1 wild-type, DNMT3A1 ∆PWWP, H2AK119ub, and H3K27me3 in parental mouse MSCs compared to DNMT3A1 wild-type and H2AK119ub in sgNsd1/Nsd2/Setd2 mouse MSCs. Regions are sorted by H2AK119ub enrichment.
Extended Data Fig. 9
DNA methylation landscape changes associated with alterations in DNMT3A recruitment a) Boxplots for CpG methylation genome-wide (n = 2,115,198 CpGs) in parental and sgRing1a/b mouse MSCs expressing DNMT3A1 wild-type (gray), K299I (blue), or W330R (orange). The center line represents the median (indicated), the box limits are the 25th and 75th percentiles, the whiskers are the minimum to maximum values and discrete points represent outliers. b) Boxplots for CpG methylation at CpG islands (n = 718,611 CpGs) in parental and sgRing1a/b mouse MSCs expressing DNMT3A1 wild-type (gray), K299I (blue), or W330R (orange). The center line represents the median (indicated), the box limits are the 25th and 75th percentiles, the whiskers are the minimum to maximum values and discrete points represent outliers. c) Boxplots for CpG methylation outside parental H2AK119ub peak regions (n = 1,727,890 CpGs) in parental and sgRing1a/b mouse MSCs expressing DNMT3A1 wild-type (gray), K299I (blue), or W330R (orange). The center line represents the median (indicated), the box limits are the 25th and 75th percentiles, the whiskers are the minimum to maximum values and discrete points represent outliers. d) Boxplots for CpG methylation at CpG islands outside parental H2AK119ub peak regions (n = 442,516 CpGs) in parental and sgRing1a/b mouse MSCs expressing DNMT3A1 wild-type (gray), K299I (blue), or W330R (orange). The center line represents the median (indicated), the box limits are the 25th and 75th percentiles, the whiskers are the minimum to maximum values and discrete points represent outliers. e) Genome browser representation of ChIP-seq normalized reads for H2AK119ub and Reduced Representation Bisulfite Sequencing (RRBS) data for CpG methylation (black) in parental mouse MSCs expressing either wild-type or W330R DNMT3A1 at chromosome 1: 178,516-178,540 Kb and chromosome 15: 32,244-32,248 Kb. CGIs (green) and genes from the RefSeq database are annotated at the bottom. f) Averaged ChIP-seq Rx-normalized read signal at hypermethylated CpG islands in DNMT3A1 W330R-expressing cells ± 5-kb (n = 3,054, methylation difference >20%, FDR = 0.01), represented as Rx-adjusted CPM for H2AK119ub in parental mouse MSCs compared to cells expressing DNMT3A1 W330R.
Supplementary information
Supplementary Table 1
Primers used for ChIP–qPCR in this study
Source data
Source Data Fig. 3
Statistical source data.
Source Data Extended Data Fig. 1
Unprocessed western blots.
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Statistical source data.
Source Data Extended Data Fig. 5
Unprocessed western blots.
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Unprocessed western blots.
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Statistical source data.
Source Data Extended Data Fig. 8
Unprocessed western blots.
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Weinberg, D.N., Rosenbaum, P., Chen, X. et al. Two competing mechanisms of DNMT3A recruitment regulate the dynamics of de novo DNA methylation at PRC1-targeted CpG islands. Nat Genet 53, 794–800 (2021). https://doi.org/10.1038/s41588-021-00856-5
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DOI: https://doi.org/10.1038/s41588-021-00856-5
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