Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Nondestructive, base-resolution sequencing of 5-hydroxymethylcytosine using a DNA deaminase

Nature Biotechnology volume 36, pages 1083–1090 (2018)Cite this article

Subjects

Abstract

Here we present APOBEC-coupled epigenetic sequencing (ACE-seq), a bisulfite-free method for localizing 5-hydroxymethylcytosine (5hmC) at single-base resolution with low DNA input. The method builds on the observation that AID/APOBEC family DNA deaminase enzymes can potently discriminate between cytosine modification states and exploits the non-destructive nature of enzymatic, rather than chemical, deamination. ACE-seq yielded high-confidence 5hmC profiles with at least 1,000-fold less DNA input than conventional methods. Applying ACE-seq to generate a base-resolution map of 5hmC in tissue-derived cortical excitatory neurons, we found that 5hmC was almost entirely confined to CG dinucleotides. The whole-genome map permitted cytosine, 5-methylcytosine (5mC) and 5hmC to be parsed and revealed genomic features that diverged from global patterns, including enhancers and imprinting control regions with high and low 5hmC/5mC ratios, respectively. Enzymatic deamination overcomes many challenges posed by bisulfite-based methods, thus expanding the scope of epigenome profiling to include scarce samples and opening new lines of inquiry regarding the role of cytosine modifications in genome biology.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Reactivities of modified cytosines in sequencing approaches.
Figure 2: Development and validation of ACE-seq.
Figure 3: ACE-seq is non-destructive.
Figure 4: Generation of whole-genome base-resolution maps of 5hmC using ACE-seq.
Figure 5: Genomic distribution of 5hmC and 5mC in adult cortical excitatory neurons.

Similar content being viewed by others

Accession codes

Primary accessions

Gene Expression Omnibus

Referenced accessions

GenBank/EMBL/DDBJ

References

  1. Schübeler, D. Function and information content of DNA methylation. Nature 517, 321–326 (2015).

    Article  PubMed  CAS  Google Scholar 

  2. Tahiliani, M. et al. Conversion of 5-methylcytosine to 5-hydroxymethylcytosine in mammalian DNA by MLL partner TET1. Science 324, 930–935 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Ito, S. et al. Tet proteins can convert 5-methylcytosine to 5-formylcytosine and 5-carboxylcytosine. Science 333, 1300–1303 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. He, Y.F. et al. Tet-mediated formation of 5-carboxylcytosine and its excision by TDG in mammalian DNA. Science 333, 1303–1307 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Pfaffeneder, T. et al. The discovery of 5-formylcytosine in embryonic stem cell DNA. Angew. Chem. Int. Edn Engl. 50, 7008–7012 (2011).

    Article  CAS  Google Scholar 

  6. Kohli, R.M. & Zhang, Y. TET enzymes, TDG and the dynamics of DNA demethylation. Nature 502, 472–479 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Wagner, M. et al. Age-dependent levels of 5-methyl-, 5-hydroxymethyl-, and 5-formylcytosine in human and mouse brain tissues. Angew. Chem. Int. Edn Engl. 54, 12511–12514 (2015).

    Article  CAS  Google Scholar 

  8. Bachman, M. et al. 5-Formylcytosine can be a stable DNA modification in mammals. Nat. Chem. Biol. 11, 555–557 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Wu, H. & Zhang, Y. Charting oxidized methylcytosines at base resolution. Nat. Struct. Mol. Biol. 22, 656–661 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Huang, Y. et al. The behavior of 5-hydroxymethylcytosine in bisulfite sequencing. PLoS One 5, e8888 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  11. Yu, M. et al. Base-resolution analysis of 5-hydroxymethylcytosine in the mammalian genome. Cell 149, 1368–1380 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Booth, M.J. et al. Quantitative sequencing of 5-methylcytosine and 5-hydroxymethylcytosine at single-base resolution. Science 336, 934–937 (2012).

    Article  CAS  PubMed  Google Scholar 

  13. Tanaka, K. & Okamoto, A. Degradation of DNA by bisulfite treatment. Bioorg. Med. Chem. Lett. 17, 1912–1915 (2007).

    Article  CAS  PubMed  Google Scholar 

  14. Luo, C. et al. Single-cell methylomes identify neuronal subtypes and regulatory elements in mammalian cortex. Science 357, 600–604 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Clark, S.J., Lee, H.J., Smallwood, S.A., Kelsey, G. & Reik, W. Single-cell epigenomics: powerful new methods for understanding gene regulation and cell identity. Genome Biol. 17, 72 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  16. Booth, M.J., Raiber, E.A. & Balasubramanian, S. Chemical methods for decoding cytosine modifications in DNA. Chem. Rev. 115, 2240–2254 (2015).

    Article  CAS  PubMed  Google Scholar 

  17. Zahid, O.K., Zhao, B.S., He, C. & Hall, A.R. Quantifying mammalian genomic DNA hydroxymethylcytosine content using solid-state nanopores. Sci. Rep. 6, 29565 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Chavez, L. et al. Simultaneous sequencing of oxidized methylcytosines produced by TET/JBP dioxygenases in Coprinopsis cinerea. Proc. Natl. Acad. Sci. USA 111, E5149–E5158 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Sun, Z. et al. High-resolution enzymatic mapping of genomic 5-hydroxymethylcytosine in mouse embryonic stem cells. Cell Rep. 3, 567–576 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Sun, Z. et al. A sensitive approach to map genome-wide 5-hydroxymethylcytosine and 5-formylcytosine at single-base resolution. Mol. Cell 57, 750–761 (2015).

    Article  CAS  PubMed  Google Scholar 

  21. Mellén, M., Ayata, P. & Heintz, N. 5-hydroxymethylcytosine accumulation in postmitotic neurons results in functional demethylation of expressed genes. Proc. Natl. Acad. Sci. USA 114, E7812–E7821 (2017).

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  22. Gross, J.A. et al. Characterizing 5-hydroxymethylcytosine in human prefrontal cortex at single base resolution. BMC Genomics 16, 672 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Lister, R. et al. Global epigenomic reconfiguration during mammalian brain development. Science 341, 1237905 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. Siriwardena, S.U., Chen, K. & Bhagwat, A.S. Functions and malfunctions of mammalian DNA-cytosine deaminases. Chem. Rev. 116, 12688–12710 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Nabel, C.S. et al. AID/APOBEC deaminases disfavor modified cytosines implicated in DNA demethylation. Nat. Chem. Biol. 8, 751–758 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Wijesinghe, P. & Bhagwat, A.S. Efficient deamination of 5-methylcytosines in DNA by human APOBEC3A, but not by AID or APOBEC3G. Nucleic Acids Res. 40, 9206–9217 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Carpenter, M.A. et al. Methylcytosine and normal cytosine deamination by the foreign DNA restriction enzyme APOBEC3A. J. Biol. Chem. 287, 34801–34808 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Schutsky, E.K., Nabel, C.S., Davis, A.K.F., DeNizio, J.E. & Kohli, R.M. APOBEC3A efficiently deaminates methylated, but not TET-oxidized, cytosine bases in DNA. Nucleic Acids Res. 45, 7655–7665 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Bryson, A.L. et al. Covalent modification of bacteriophage T4 DNA inhibits CRISPR-Cas9. MBio 6, e00648–e15 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Mo, A. et al. Epigenomic signatures of neuronal diversity in the mammalian brain. Neuron 86, 1369–1384 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Warnecke, P.M. et al. Identification and resolution of artifacts in bisulfite sequencing. Methods 27, 101–107 (2002).

    Article  CAS  PubMed  Google Scholar 

  32. Johnson, B.S. et al. Biotin tagging of MeCP2 in mice reveals contextual insights into the Rett syndrome transcriptome. Nat. Med. 23, 1203–1214 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Hu, L. et al. Crystal structure of TET2-DNA complex: insight into TET-mediated 5mC oxidation. Cell 155, 1545–1555 (2013).

    Article  CAS  PubMed  Google Scholar 

  34. Xie, W. et al. Base-resolution analyses of sequence and parent-of-origin dependent DNA methylation in the mouse genome. Cell 148, 816–831 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Yin, Y. et al. Impact of cytosine methylation on DNA binding specificities of human transcription factors. Science 356, eaaj2239 (2017).

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  36. Buenrostro, J.D., Giresi, P.G., Zaba, L.C., Chang, H.Y. & Greenleaf, W.J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213–1218 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Eid, J. et al. Real-time DNA sequencing from single polymerase molecules. Science 323, 133–138 (2009).

    Article  CAS  PubMed  Google Scholar 

  38. Gabel, H.W. et al. Disruption of DNA-methylation-dependent long gene repression in Rett syndrome. Nature 522, 89–93 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Wang, H. et al. One-step generation of mice carrying mutations in multiple genes by CRISPR/Cas-mediated genome engineering. Cell 153, 910–918 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Lu, F., Liu, Y., Jiang, L., Yamaguchi, S. & Zhang, Y. Role of Tet proteins in enhancer activity and telomere elongation. Genes Dev. 28, 2103–2119 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Wu, H., Wu, X., Shen, L. & Zhang, Y. Single-base resolution analysis of active DNA demethylation using methylase-assisted bisulfite sequencing. Nat. Biotechnol. 32, 1231–1240 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Krueger, F. & Andrews, S.R. Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications. Bioinformatics 27, 1571–1572 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Bachman, M. et al. 5-Hydroxymethylcytosine is a predominantly stable DNA modification. Nat. Chem. 6, 1049–1055 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Qu, J., Zhou, M., Song, Q., Hong, E.E. & Smith, A.D. MLML: consistent simultaneous estimates of DNA methylation and hydroxymethylation. Bioinformatics 29, 2645–2646 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Thorvaldsdóttir, H., Robinson, J.T. & Mesirov, J.P. Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief. Bioinform. 14, 178–192 (2013).

    Article  PubMed  CAS  Google Scholar 

  46. Shen, L. et al. Genome-wide analysis reveals TET- and TDG-dependent 5-methylcytosine oxidation dynamics. Cell 153, 692–706 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We are grateful to Z. Zhou, M. Fasolino, A. Bryson and J.M. SanMiguel for discussion and reagents. This work was supported by the US National Institutes of Health through R21-HG009545 (to R.M.K.) and by the Penn Epigenetics Institute. Additional support included R00-HG007982 (to H.W.), DP2-HL142044 (to H.W.) and R01-GM118501 (to R.M.K.). E.K.S. and J.E.D. are NSF Graduate Research Fellows. J.E.D. and E.B.F. were supported by NIH training grant T32-GM07229, and M.Y.L. by F30-CA196097.

Author information

Authors and Affiliations

  1. Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    Emily K Schutsky, Jamie E DeNizio, Monica Yun Liu, Christopher S Nabel & Rahul M Kohli

  2. Department of Genetics, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    Peng Hu, Emily B Fabyanic & Hao Wu

  3. Department of Microbiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    Young Hwang & Frederic D Bushman

  4. Penn Epigenetics Institute, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    Hao Wu & Rahul M Kohli

Authors
  1. Emily K Schutsky
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jamie E DeNizio
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Peng Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Monica Yun Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Christopher S Nabel
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Emily B Fabyanic
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Young Hwang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Frederic D Bushman
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Hao Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Rahul M Kohli
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

E.K.S., C.S.N., R.M.K. and H.W. conceived of and developed the ACE-seq approach. E.K.S. conducted all of the experiments, with assistance from J.E.D., M.Y.L., E.B.F., P.H. and Y.H. F.D.B. contributed to phage experiment design. H.W. performed computational analysis. E.K.S., H.W. and R.M.K. analyzed the results and wrote the manuscript, with contributions from all of the authors.

Corresponding authors

Correspondence to Hao Wu or Rahul M Kohli.

Ethics declarations

Competing interests

Aspects of the ACE-seq protocol have been non-exclusively licensed.

Integrated supplementary information

Supplementary Figure 1 Chemical and/or enzymatic deamination across various sequencing methods to localize modified cytosines.

(a) Upon treatment with bisulfite under acidic conditions and at elevated temperatures, unmodified cytosine becomes sulfonated at the 6-position, which facilitates its hydrolytic deamination. Moving to alkaline conditions promotes desulfonation to yield uracil. In contrast, APOBEC3A catalyzes enzymatic hydrolytic deamination under physiological temperatures and pHs. (b) Workflows of various deamination-based sequencing methods to localize modified cytosines. Traditional bisulfite sequencing (BS-Seq) localizes 5mC and 5hmC together after deamination of unmodified C. TET-assisted bisulfite sequencing (TAB-Seq) changes reactivities to specifically localize 5hmC by first protecting 5hmC with a glucose moiety and then oxidizing 5mC with TET to form 5-formyl or 5-carboxylcytosine, which will be read as T following bisulfite conversion and sequencing. Oxidative bisulfite sequencing (oxBS-Seq) directly localizes 5mC by oxidizing 5hmC with potassium perruthenate before bisulfite treatment. When used in conjunction with standard bisulfite sequencing, 5hmC can be indirectly localized through subtraction of the oxBS signal from that of BS-Seq. Finally, APOBEC-Coupled Epigenetic Sequencing (ACE-Seq) does not rely on bisulfite, and instead utilizes enzymatic deamination of C and 5mC by APOBEC3A after protecting 5hmC with a glucose moiety. The sequencing readout therefore is comparable to TAB-Seq without the need for the destructive bisulfite treatment.

Supplementary Figure 2 Phenotypic validation of modifications in phage DNA.

(a-c) Validation of T4 mutant phenotypes by (a) restriction digest and (b,c) liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). (a) AluI cleaves only unmodified cytosine-containing DNA, while MspJI selectively cleaves 5hmC-containing DNA. Exogenous treatment of T4-hmC with a glucosyltransferase also causes a mass shift to generate a band the same size as T4-ghmC. The gels are adapted from Bryson, et al. mBio, 2015 (PMID: 26081634) with permission from mBio; specifically, only panel A of the original figure was used, and the labels were altered slightly to align with nomenclature used in this article. (b) Raw MS/MS traces of C, 5mC, 5hmC, and 5ghmC in T4-C, T4-hmC, and T4-ghmC phage stocks. α and β denote peaks representing α- and β-anomers of 5ghmC. The MS/MS transitions are provided in the methods. Note that the peak area does not directly correlate with abundance given different ionization efficiencies. Independent experiments were performed in triplicate; representative traces shown. (c) Levels of C and 5ghmC in each stock are quantified relative to the T4-C and T4-ghmC reference genomes. Mean values from triplicate experiments are listed above each bar; error bars report the standard deviation. The presence of 5ghmC in T4-C is likely from rare reversion of the phage during propagation. T4 phage can package some of its host E. coli gDNA (strain DH10B). The presence of C in T4-hmC and T4-ghmC correlates with the expected amount based on the frequency of sequencing reads that map to the E. coli DH10B (bottom table). Notably, the presence of small amounts of E. coli gDNA do not impact any of the ACE-Seq quality metrics, as these are derived from reads that map to the T4-hmC genome alone (as in Fig. 2d,f). (d,e) Validation of CG methylation of λ phage genomic DNA by (d) restriction digest and (e) LC-MS/MS. (d) 75 ng of λ phage DNA that was either untreated or treated with M.SssI was incubated in the presence of no restriction enzyme (-), MspI, or HpaII, with appropriate buffers. While MspI cleaves both unmethylated and methylated CG-containing sites, HpaII is blocked from cleavage by CG methylation. Experiments were performed several times with similar results; representative image shown. (e) Raw MS/MS traces of C, 5mC, 5hmC, and 5ghmC in the methylated λ phage stock. Experiment was performed in triplicate (n = 3); representative traces shown.

Supplementary Figure 3 ACE-Seq optimization to promote full deamination of a locus in the T4-C phage genome.

(a) Highlighter plot showing deamination events (red) and non-deamination events (cyan) compared to the non-deaminated master sequence. Clones from experiments without DMSO and with 10% DMSO are shown. Strong hairpin formation was predicted using secondary structure prediction software from position 363-378, likely contributing to lack of deamination in this area without DMSO. (b) Highlighter plot showing deamination events (red) and non-deamination events (cyan) compared to the non-deaminated master sequence. Clones from experiments performed at 25 °C, 37 °C, and under slow ramping conditions (4 °C to 50 °C over 2 hours) are shown.

Supplementary Figure 4 Phenotypic validation of modifications in phage DNA.

15 ng of a 1:1 pooled mixture of methylated λ phage gDNA and T4-hmC DNA was treated with or without βGT and then with or without A3A (4 samples, each in triplicate). These reactions were then digested to nucleosides, and analyzed via LC-MS/MS. Levels of (a) C, (b) 5mC, and (c) 5hmC were quantified using standard curves generated from purified nucleoside controls, and the relative amount of the base graphed relative to the untreated sample (-A3A, - bGT). Individual data points from triplicate experiments are overlaid on the bar graph; mean percentages are listed above each bar, and error bars represent standard deviations from the mean. (d) Representative raw traces of MS/MS counts for 5hmC and 5ghmC. Upon βGT treatment, 5hmC signal decreased significantly, accompanied by the conversion to 5ghmC. Mean percentages of 5hmC remaining from triplicate experiments (n = 3) are listed above the remaining peaks in the + βGT samples. (e) Chart outlining predicted/observed products for both spike-in controls under each condition tested.

Supplementary Figure 5 Quantitative PCR (qPCR) of bisulfite-treated versus A3A-treated samples.

ACE-Seq or BS-Seq samples of unsheared mESC DNA analyzed qualitatively in Fig. 3a were used to seed qPCR reactions. 0.5 μL of the treated samples were combined with 500 nM each of the forward and reverse primers (to amplify either (a) the 200-bp amplicon or (b) the 1-kb amplicon) and amplified using the KAPA SYBR Fast Rox low qPCR Mastermix kit (KAPA Biosystems). For the 200-bp amplicon, a two-step PCR protocol was used in which the samples were initially denatured at 95 °C for 3 minutes, and then cycled between 95 °C (15 seconds) and 63 °C (20 seconds) for a total of 35 cycles. For the 1-kb amplicon, a two-step PCR protocol was used in which the samples were initially denatured at 95 °C for 5 minutes, and then cycled between 95 °C (30 seconds) and 66 °C (90 seconds) for a total of 41 cycles. Resulting qPCR products were run on 1% agarose gels and stained with SybrSafe to confirm specific amplification. The gray dashed line in (b) represents the mean CT value from the no-template control due to primer dimer amplification. Notably, the signals from the no-template and bisulfite samples for the 1-kb amplicon were exclusively from primer dimer amplification and were not specific to the desired 1-kb product. Mean values from triplicate experiments (n = 3) are shown, with error bars representing standard deviation from the mean. The data from 1 μg input samples are the same as those presented in Fig. 3b. (c) Shown is the uncropped gel from Fig. 3b.

Supplementary Figure 6 Comparison of ACE-Seq as a function of gDNA input.

(a) Browser snapshot showing base-resolution 5hmCG (blue) maps near the Neurod6 gene (chr6:55,614,961-55,646,769; mm9). ACE-Seq raw signals of CGs on both strands were combined and only CG dyads sequenced to depth >=2 are shown. Gray tracks denote sequencing coverage for each CG dyad. Experiment was performed once each for 2 ng and 20 ng input of each gDNA (n = 2). (b) Correlation density plot between ACE-Seq experiments with 2 ng or 20 ng of DNA as input. Mean ACE-Seq raw signals were calculated for tiled 10-kb bins across the mouse genome. Correlation analysis was performed with 10-kb bins spanning the genome (n = 238,401 bins).

Supplementary Figure 7 Relationship of DNA modifications and chromatin states at representative loci.

Browser snapshot showing base-resolution CG (green), 5mCG (red), 5hmCG (blue) maps, as well as RNA-Seq, ATAC-Seq, and ChIP-Seq of major histone modifications near the (a) transcriptionally-active Neurod6 (chr6:55,667,934-55,690,102; mm10) gene and (b) the inactive Gad2 gene (chr2:22,607,043-22,660,967; mm10). Only CGs sequenced to depth ≥ 2 are shown. Gray tracks denote sequencing coverage for each position in each base-resolution map. ACE-Seq traces represent merged data sets from single experiments at 2 ng and 20 ng of input DNA (n = 2).

Supplementary Figure 8 Base-resolution analysis of 5hmCGs and 5mCGs at imprinted regions in mouse cortical excitatory neurons.

(a) The average 5hmC (left) or 5mC (right) levels are shown within two groups of imprinted regions (hmC-high: blue; hmC-low: green) and their flanking regions. (b) Snapshot of base-resolution C (green), 5mC (red), and 5hmC (blue) maps near the Kcnq1ot1 gene locus (chr7:143,290,000-143,300,000; genome build: mm10). Only CGs sequenced to depth >=2 are shown. Gray tracks denote sequencing coverage for each position. ACE-Seq traces represent merged data sets from single experiments at 2 ng and 20 ng of input DNA (n = 2). (c) Heat-map representation of normalized RNA-Seq, H3K4me3 (ChIP-Seq), H3K27me3 (ChIP-Seq), 5hmC (ACE-Seq), 5mC (derived from BS-Seq and ACE-Seq), and 5hmC/5mC ratios within 30 imprinted regions. Imprinted regions were ranked by their 5hmC levels in cortical excitatory neurons.

Supplementary Figure 9 Distribution of C, 5mC, and 5hmC levels at representative genomic elements.

Ternary plots show the levels of C, 5mC, and 5hmC within 1-kb bins overlapping with representative genomic elements.

Supplementary Figure 10 Enrichment of high-level 5hmCG sites.

(a) The distribution of abundances of called 5hmCG (blue) and 5mCG (red) at individual sites in cortical excitatory neurons. The dashed line denotes the signal level of 0.6, the cutoff used to select high-level 5hmCG sites. (b) The fraction of high-level 5hmCG (purple) and all 5hmCG (yellow) sites within various genomic elements (relative to total number of CG sites in each group).

Supplementary Figure 11 Possible applications of enzymatic deamination for 5mC localization.

(a) Comparison of chemical and enzymatic deamination. Chemical deamination is efficient on C, while 5mC is largely resistant to the reaction. Also, 5hmC is converted to a CMS adduct, while 5fC is inefficiently deaminated. Efforts to drive this reaction starts to increase aberrant 5mC deamination (see Wu et al., Nature Prot, 2016, 11:1081-1100). Enzymatic deamination is efficient on C and 5mC and discriminates against all ox-mCs (see Schutsky et al., NAR, 2017, 45:7655-7665.) (b) Schemes for detection of 5mC. Potential schemes for localizing 5mC and all ox-mCs involve TET-mediated oxidation with or without coupled protection with βGT, which would lead to conversion of C bases only. As another alternative, after bisulfite treatment, A3A can be used to deaminate 5mC but not CMS to differentiate 5hmC and 5mC, although such a method would carry forward the limitations of bisulfite.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–11 (PDF 1491 kb)

Life Sciences Reporting Summary (PDF 133 kb)

Supplementary Tables and Protocols

Supplementary Tables 1 and 2, and Supplementary Protocols 1 and 2 (PDF 208 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Schutsky, E., DeNizio, J., Hu, P. et al. Nondestructive, base-resolution sequencing of 5-hydroxymethylcytosine using a DNA deaminase. Nat Biotechnol 36, 1083–1090 (2018). https://doi.org/10.1038/nbt.4204

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nbt.4204

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing