Abstract
Inheritance of 5-methylcytosine from one cell generation to the next by DNA methyltransferase 1 (DNMT1) plays a key role in regulating cellular identity. While recent work has shown that the activity of DNMT1 is imprecise, it remains unclear how the fidelity of DNMT1 is tuned in different genomic and cell state contexts. Here we describe Dyad-seq, a method to quantify the genome-wide methylation status of cytosines at the resolution of individual CpG dinucleotides to find that the fidelity of DNMT1-mediated maintenance methylation is related to the local density of DNA methylation and the landscape of histone modifications. To gain deeper insights into methylation/demethylation turnover dynamics, we first extended Dyad-seq to quantify all combinations of 5-methylcytosine and 5-hydroxymethylcytosine at individual CpG dyads. Next, to understand how cell state transitions impact maintenance methylation, we scaled the method down to jointly profile genome-wide methylation levels, maintenance methylation fidelity and the transcriptome from single cells (scDyad&T-seq). Using scDyad&T-seq, we demonstrate that, while distinct cell states can substantially impact the activity of the maintenance methylation machinery, locally there exists an intrinsic relationship between DNA methylation density, histone modifications and DNMT1-mediated maintenance methylation fidelity that is independent of cell state.
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Data availability
Sequencing data have been deposited in the Gene Expression Omnibus (GEO) database accession code GEO GSE197501. Source data are provided with this paper.
Code availability
Custom codes for analyzing Dyad-seq data and the accompanying documentation are provided with this work (Supplementary Software or via GitHub at https://github.com/alexchialastri/scDyad-T-seq (ref. 59)).
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Acknowledgements
We thank members of the Dey lab for helpful discussions. We thank A. Clark at UCLA for the wild-type and Uhrf1-knockout E14 cell line. We thank J. Smith at the Biological Nanostructures Laboratory in the California NanoSystems Institute (CNSI), supported by UCSB and UC Office of the President, for help with Illumina sequencing. Computational work was supported by the Center for Scientific Computing at CNSI and Materials Research Laboratory (MRL) at UCSB: an NSF MRSEC (DMR-1720256) and NSF CNS-1725797. E.E.S. was supported by an NSF GRFP fellowship (NSF 2139319). This work was supported by the NIH grants R01HD099517 and R01HG011013 to S.S.D.
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Contributions
Conceptualization, A.C. and S.S.D.; methodology, A.C. and S.S.D.; investigation, A.C., S.S., E.E.S. and S.L.; formal analysis, A.C.; writing—original draft, A.C.; writing—review and editing, A.C. and S.S.D.; funding acquisition, S.S.D.; resources, S.S.D; supervision, S.S.D.
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Competing interests
A.C. and S.S.D. are co-inventors on a patent describing Dyad-seq. The remaining authors declare no competing interests.
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Nature Structural & Molecular Biology thanks Maxim Greenberg and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Carolina Perdigoto and Dimitris Typas were the primary editors on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team. Peer reviewer reports are available.
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Extended data
Extended Data Fig. 1 Overview of Dyad-seq.
(a) In H-H-Dyad-seq, the schematic shows that hydroxymethylated cytosines at CpG dyads are detected using AbaSI digestion followed by the appropriate nucleobase conversion to interrogate the hydroxymethylation status of the cytosine on the opposing strand of the dyad. For a schematic of M-M-Dyad-seq, see Fig. 1a. (b) Schematic shows that following restriction enzyme digestion and adapter ligation, methylated cytosines can be quantified by sequencing the ‘direct’ or ‘indirect’ capture molecules. (c) Bar plots show the percentage of reads that lead to quantification of 5mC by MspJI in M-M-Dyad-seq and scMspJI-seq. (d) Bar plots show the percentage of ‘direct’ and ‘indirect’ reads that lead to unique detection of 5mC by MspJI in M-M-Dyad-seq and scMspJI-seq. (e) Nucleotide composition downstream of MspJI cut site obtained from sequenced unique direct capture reads in M-M-Dyad-seq. (f) Summary of DNA modifications recognized by restriction enzymes and the cytosine conversion reactions performed in different variants of Dyad-seq. (g) Distribution of the percentage of symmetrical methylation at individual CpG dyads in a background model where DNA strands methylate and demethylate independently. (h) Distribution of the percentage of symmetrical methylation at individual CpG dyads obtained from experimental M-M-Dyad-seq data. In panels (g,h), only CpG sites with a coverage of greater than 10 were included in the analysis.
Extended Data Fig. 2 Genomic and epigenomic contexts associated with quantification of the methylome in M-M-Dyad-seq.
(a) Genomic nucleotide composition in the vicinity of symmetrically methylated CpG dyads detected by M-M-Dyad-seq. (b) Genomic nucleotide composition in the vicinity of asymmetrically methylated CpG dyads detected by M-M-Dyad-seq. (c) Schematic of synthetic molecules with different combinations of DNA modifications at the central CpG dyad. All other nucleotides in these molecules are unmodified. The amplification handles are cytosine depleted. (d) Ratio of the top to bottom cytosine detected by M-M-Dyad-seq for different combinations of DNA modifications at the central CpG dyad (hemimethylated, symmetrically methylated and hemi-hydroxy methylated CpG dyads). Data is represented as mean values and the error bars represent standard deviation. Points represent individual measurements from two independent replicates.
Extended Data Fig. 3 M-M-Dyad-seq can accurately quantify DNA methylation levels and DNMT1-mediated maintenance methylation activity on a genome-wide scale.
(a) Number of unique CpG sites detected as a function of sequencing depth for all four variants of Dyad-seq (M-M-Dyad-seq, M-H-Dyad-seq, H-H-Dyad-seq, and H-M-Dyad-seq). (b) M-M-Dyad-seq shows similar 5mCpG maintenance levels as hairpin bisulfite sequencing in SL cultured mES cells8. Each point corresponds to a 100 kb bin the genome. (c) Genome-wide 5mCpG levels quantified by M-M-Dyad-seq correlates well with results obtained from bisulfite sequencing for SL cultured mESCs (Pearson r = 0.94, Spearman \(\rho\) = 0.94)24. Each point corresponds to a 100 kb bin of the genome. (d) Genome-wide 5mCpG levels quantified by H-M-Dyad-seq correlates well with results obtained from bisulfite sequencing for SL cultured mESCs (Pearson r = 0.90, Spearman \(\rho\) = 0.90)24. Each point corresponds to a 100 kb bin of the genome. (e) Ratio of coverage of CpG sites in M-M-Dyad-seq to that in whole-genome bisulfite sequencing (WGBS) over genomic regions of varying 5mCpG levels. (f) Relative coverage of CpG sites within ATAC-seq peaks in M-M-Dyad-seq and whole-genome bisulfite sequencing25. (g-j) Pie chart shows that the distribution of 5mCpG sites detected over promoters, 5′ UTRs, exons, introns and 3′ UTRs is similar between M-M-Dyad-seq (panels g,h) and other techniques, such as scMspJI-seq (panel i) and whole-genome bisulfite sequencing (panel j)6,26. (k) Violin plots show the distribution of DNA methylation over 3′ UTRs, 5′ UTRs, promoters, exons, introns, and CpG islands in M-M-Dyad-seq and whole-genome bisulfite sequencing. The data are plotted over 15,616 regions in M-M-Dyad-seq and 16,718 regions in WGBS for 3′ UTRs, 29,516 regions in M-M-Dyad-seq and 31,090 regions in WGBS for 5′ UTRs, 35,125 regions in M-M-Dyad-seq and 35,415 regions in WGBS for promoters, 170,205 regions in M-M-Dyad-seq and 217,098 regions in WGBS for exons, 188,606 regions in M-M-Dyad-seq and 203,123 regions in WGBS for introns, and 15,700 regions in M-M-Dyad-seq and 15,882 regions in WGBS for CpG islands. Data in these panels corresponds to SL cultured mESCs.
Extended Data Fig. 4 Global DNA methylation and transcriptome reprogramming of mESCs transitioned from SL to different media conditions after 48 hours.
(a) Principal component analysis (PCA) of genome-wide DNA methylation and DNA maintenance methylation levels of mESCs grown in different culture conditions for 48 hours. M-M-Dyad-seq was performed on three independent replicates for each culture condition. (b) Loss of DNA methylation after culturing mESCs in 2iL conditions for 48 hours is associated with a reduction in 5mCpG maintenance levels. Each point represents genomic tilling of 100 kb. (c) Genome-wide 5mCpG levels quantified using H-M-Dyad-seq for mESCs grown under different conditions. The violin plots are made over 2,599 genomic bins. (d) Genome-wide 5hmCpG levels quantified using H-H-Dyad-seq for mESCs grown under different conditions. The violin plots are made over 2,605 genomic bins. (e) The first two principal components show distinct transcriptomes of mESCs grown under different conditions. Bulk RNA-seq was performed in triplicate. (f) Heatmap of the expression level of genes related to de novo methylation, maintenance methylation, and demethylation pathways. (g,h) Gene pathway enrichment analysis for differentially expressed genes (hypergeometric test with Benjamini-Hochberg correction) was performed using Metascape33. Panel (g) shows gene sets associated with specific pathways that are highly expressed in 2iL and ML conditions, lowly expressed in No, and not differentially expressed across SL, BL, and GL conditions. Panel (h) shows gene sets associated with specific pathways that are highly expressed in the No condition, lowly expressed in 2iL and ML, and not differentially expressed across SL, BL, and GL.
Extended Data Fig. 5 Local density of the methylome and specific histone marks alter 5mCpG maintenance activity.
(a) Box plot of 5mCpG maintenance levels in 1 kb genomic bins categorized based on the number of CpG sites in the bin and the absolute methylation levels. ‘Low 5mC’ indicates methylation levels lower than 20%, ‘Medium 5mC’ indicates methylation levels between 20% and 80%, and ‘High 5mC’ indicates methylation levels greater than 80%. N.D. stands for “Not detected”. 1 kb regions in which at least 5 unique CpG dyads are detected were included in this panel. The number of bins in each category is denoted above each boxplot. Data in this panel corresponds to mESCs grown in SL condition and profiled using M-M-Dyad-seq. (b) 5mCpG maintenance levels at fully methylated regions (FMR), lowly methylated regions (LMR), and unmethylated regions (UMR) as stratified by Stadler et al.53. Data in this panel corresponds to mESCs grown in SL condition and profiled using M-M-Dyad-seq. Dots indicate independent biological replicates (n = 3). (c-k) Box plots of 5mCpG maintenance levels as a function of absolute 5mCpG levels at individual loci enriched for a histone mark (‘I’) or a meta-region (‘M’) containing all enriched loci corresponding to a histone mark for all 1kb bins in the genome (c), H3K9me2 (d), H3K9ac (e), H3K36me3 (f), H3K27me3 (g), H3K27ac (h), H3K9me3 (i), H3K4me3 (j), H3K4me1 (k). Distributions for the meta-regions were obtained using bootstrapping, where resampling was performed 1,000 times per histone mark. Blue dots indicate average values found in genome-wide 1kb bins (same as data presented in panel (c)). (l) Standard error for the meta-regions in panels (c-k) and Fig. 3e.
Extended Data Fig. 6 Genome-wide distribution of 5mCpG over various features and the distribution of 5hmC over TET1 binding sites.
(a-j) Panels show the distribution of DNA methylation over 1kb bins in the genome (a), various histone modifications, such as H3K9me2 (b), H3K9ac (c), H3K36me3 (d), H3K27me3 (e), H3K27ac (f), H3K9me3 (g), H3K4me3 (h), H3K4me1 (i), and TET1-binding sites (j). (k) Box plot shows the percentage of 5hmC that is paired with 5mC at CpG dyads as a function of absolute 5mCpG levels at individual loci (‘I’) or a meta-region (‘M’) (l,m) Box plot shows the percentage of 5hmC that is paired with 5mC at CpG dyads as a function of absolute 5mCpG levels at individual loci enriched for TET1 binding (‘I’) or a meta-region (‘M’) containing all enriched loci corresponding to TET1 binding sites. Distributions for the meta-regions were obtained using bootstrapping, where resampling was performed 1,000 times. Blue dots indicate average values found in genome-wide 1kb bins. M-H-Dyad-seq data was used in the analysis of panels (k-m).
Extended Data Fig. 7 scDyad&T-seq enables combined measurement of DNA methylation levels, 5mCpG maintenance levels and the transcriptome from the same cell.
(a) Genome-wide methylation and 5mCpG maintenance levels of single K562 cells treated with (+) or without (–) 0.6 µM Decitabine for 24 hours. (b) 5mCpHpG maintenance levels of single K562 cells treated with (+) or without (–) 0.6 µM Decitabine for 24 hours. Data is based on 134 cells treated with Decitabine and 143 cells not treated with Decitabine. (c) Number of genes detected as a function of transcriptome-derived reads sequenced per cell in scDyad&T-seq. Data corresponds to SL grown single E14 cells. (d) Coverage of CpG sites as a function of genomic DNA-derived reads sequenced per cell in scDyad&T-seq. Data corresponds to SL grown single E14 cells. (e,f) Coverage of individual CpG sites in scDyad&T-seq. Data corresponds to SL grown single E14 cells. (g,h) Coverage of individual CpG sites in M-M-Dyad-seq. Data corresponds to SL grown E14 mESCs. (i) Coverage of CpG sites and the number of genes detected per cell in scDyad&T-seq (blue) and scM&T-seq (red)45. The diameter of each circle corresponds to the read depth at which a cell was sequenced. Data in this panel corresponds to SL cultured E14 mESCs. (j) Distribution of CpG sites that are detected by different methods (scDyad&T-seq, scMspJI-seq and scBS-seq) over genomic regions of varying GpC density.
Extended Data Fig. 8 Serum grown mESCs contain two distinct transcriptomic subpopulations with Nanog high cells exhibiting decreased DNA methylation and 5mCpG maintenance levels across a broad range of histone modifications.
(a) Comparison of chromosome-wide 5mCpG strand bias scores, estimated using techniques such as scMspJI-seq, to 5mCpG maintenance percent estimated using scDyad&T-seq. The color of the data points correspond to the absolute methylation levels estimated using scDyad&T-seq. (b) Comparison of genome-wide concordance of methylation calls to 5mCpG maintenance percent estimated using scDyad&T-seq for single cells46. Concordance is defined as the fraction of reads (with at least 5 CpG sites covered) where 90% or more of the sites are methylated. The color of the data points correspond to the absolute methylation levels estimated using scDyad&T-seq. (c) Expression level of pluripotency related genes NANOG, REX1, and ESRRB in the two transcriptional clusters (NANOG high (‘NanHi’) and NANOG low (‘NanLo’)) identified in Fig. 5d using scDyad&T-seq for serum grown mESCs. (d,e) DNA methylation levels at genomic regions with 0-40% 5mCpG (d) and 40–100% 5mCpG (e) marked by different histone modifications. (f,g) 5mCpG maintenance percent at genomic regions with 0–40% 5mCpG (f) and 40–100% 5mCpG (g) marked by different histone modifications. From bulk measurements (see Fig. 3e), regions were previously categorized as less than (panels (d,f)) or greater than (panels (e,g)) 40% methylated. Data in panels (d-f) are based on 42 NanHi and 55 NanLo cells.
Extended Data Fig. 9 Epigenetic and transcriptional reprogramming of mESCs transitioning from SL to 2iL conditions.
(a) Hierarchical clustering based on genome-wide 5mCpG levels show that cells transitioning from SL to 2iL conditions can be classified into two major groups – a 5mCpG low (mCLo) or a 5mCpG high (mCHi) state. (b) Hierarchical clustering based on genome-wide 5mCpG maintenance levels show that cells transitioning from SL to 2iL conditions can be classified into two major groups – a lowly maintained (MntLo) or a highly maintained (MntHi) state. (c) UMAP visualization of cells transiting from SL to 2iL conditions, based on the single-cell transcriptomes obtained from scDyad&T-seq, shows that cells can be classified into two broad transcriptional clusters. The cluster names, 2iL-like and SL-like were assigned based on expression of key marker genes in mESCs grown in 2iL or SL conditions, respectively. (d) Expression of key pluripotency genes that have previously been shown to be similar between SL and 2iL culture49. (e) Expression of genes known to be transcribed at higher levels in 2iL mESCs compared to those grown in SL conditions49. (f) Expression of genes known to be transcribed at higher levels in SL mESCs compared to those grown in 2iL culture49. (g) Bar plot shows the percentage of 2iL and SL grown mESCs that are assigned to the 2iL-like or SL-like transcriptional clusters. The number in the parenthesis indicates the total number of cells in that cluster.
Extended Data Fig. 10 scDyad&T-seq directly relates transcriptional cell identity to demethylation dynamics in single cells transitioning from SL to 2iL.
(a,b) Genome-wide DNA methylation (panel a) and 5mCpG maintenance (panel b) levels of 2iL-D3 cells in the two broad transcriptional groups – 2iL-like and SL-like – described in Extended Data Fig. 9c. (c,d) Expression levels of the pluripotency marker POU5F1 (also known as OCT4) (panel c) and early neuroectoderm lineage marker SOX1 (panel d) in 2iL-D3 cells. (e) Heatmap of differentially expressed genes between the 2iL-1 and 2iL-2 population. (f,g) Absolute DNA methylation levels vs. the corresponding 5mCpG maintenance levels within 100 kb bins for cells in sub-population 2iL-1 (panel f) or 2iL-2 (panel g). (h) Bar plot shows how cells cultured in the 2iL condition for different number of days are distributed between the 2iL-1 and 2iL-2 sub-populations. The number in the parenthesis indicates the total number of cells in that sub-population. (i) Panel shows the coverage of CpG dinucleotides providing information on 5mCpG maintenance (dyad coverage), and the coverage of CpG sites providing information on the absolute levels of DNA methylation in single cells (CpG coverage). The color of the data points indicate the total number of unique transcripts detected in single cells grown in SL and 2iL conditions. (j) Heatmap of 5mCpG maintenance for individual chromosomes in single cells indicates increased sensitivity in quantifying DNMT1-mediated maintenance fidelity and demethylation compared to the strand bias score obtained from methods such as scMspJI-seq. The panel also shows the culture conditions and genome-wide 5mCpG methylation levels for the same cells.
Supplementary information
Supplementary Information
Supplementary Fig. 1, Note 1 and Tables 1–4.
Supplementary Software
Scripts to process bulk and single-cell Dyad-seq data.
Supplementary Data 1
Metadata of all single cells processed by scDyad&T-seq.
Supplementary Data 2
Source data for Supplementary Fig. 1.
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Chialastri, A., Sarkar, S., Schauer, E.E. et al. Combinatorial quantification of 5mC and 5hmC at individual CpG dyads and the transcriptome in single cells reveals modulators of DNA methylation maintenance fidelity. Nat Struct Mol Biol (2024). https://doi.org/10.1038/s41594-024-01291-w
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DOI: https://doi.org/10.1038/s41594-024-01291-w
