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DNA methylation dynamics of the human preimplantation embryo


In mammals, cytosine methylation is predominantly restricted to CpG dinucleotides and stably distributed across the genome, with local, cell-type-specific regulation directed by DNA binding factors1,2,3. This comparatively static landscape is in marked contrast with the events of fertilization, during which the paternal genome is globally reprogrammed. Paternal genome demethylation includes the majority of CpGs, although methylation remains detectable at several notable features4,5,6,7. These dynamics have been extensively characterized in the mouse, with only limited observations available in other mammals, and direct measurements are required to understand the extent to which early embryonic landscapes are conserved8,9,10. We present genome-scale DNA methylation maps of human preimplantation development and embryonic stem cell derivation, confirming a transient state of global hypomethylation that includes most CpGs, while sites of residual maintenance are primarily restricted to gene bodies. Although most features share similar dynamics to those in mouse, maternally contributed methylation is divergently targeted to species-specific sets of CpG island promoters that extend beyond known imprint control regions. Retrotransposon regulation is also highly diverse, and transitions from maternally to embryonically expressed elements. Together, our data confirm that paternal genome demethylation is a general attribute of early mammalian development that is characterized by distinct modes of epigenetic regulation.

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Figure 1: Human preimplantation embryos are globally hypomethylated.
Figure 2: Human preimplantation dynamics are globally similar to mouse.
Figure 3: Transient maternal DMRs target a divergent set of CpG island promoters.
Figure 4: LTR subfamily dynamics are divided into early and late preimplantation phases.
Figure 5: Emergent L1PA subfamilies escape DNA methylation-associated repression during preimplantation.

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Gene Expression Omnibus

Data deposits

RRBS data is deposited at the Gene Expression Omnibus under accession number GSE51239.


  1. Suzuki, M. M. & Bird, A. DNA methylation landscapes: provocative insights from epigenomics. Nature Rev. Genet. 9, 465–476 (2008)

    Article  CAS  Google Scholar 

  2. Stadler, M. B. et al. DNA-binding factors shape the mouse methylome at distal regulatory regions. Nature 480, 490–495 (2011)

    Article  ADS  CAS  Google Scholar 

  3. Ziller, M. J. et al. Charting a dynamic DNA methylation landscape of the human genome. Nature 500, 477–481 (2013)

    Article  ADS  CAS  Google Scholar 

  4. Lane, N. et al. Resistance of IAPs to methylation reprogramming may provide a mechanism for epigenetic inheritance in the mouse. Genesis 35, 88–93 (2003)

    Article  CAS  Google Scholar 

  5. Smallwood, S. A. et al. Dynamic CpG island methylation landscape in oocytes and preimplantation embryos. Nature Genet. 43, 811–814 (2011)

    Article  CAS  Google Scholar 

  6. Kobayashi, H. et al. Contribution of intragenic DNA methylation in mouse gametic DNA methylomes to establish oocyte-specific heritable marks. PLoS Genet. 8, e1002440 (2012)

    Article  CAS  Google Scholar 

  7. Smith, Z. D. et al. A unique regulatory phase of DNA methylation in the early mammalian embryo. Nature 484, 339–344 (2012)

    Article  ADS  CAS  Google Scholar 

  8. Fulka, H., Mrazek, M., Tepla, O. & Fulka, J. Jr. DNA methylation pattern in human zygotes and developing embryos. Reproduction 128, 703–708 (2004)

    Article  CAS  Google Scholar 

  9. Santos, F. et al. Evaluation of epigenetic marks in human embryos derived from IVF and ICSI. Hum. Reprod. 25, 2387–2395 (2010)

    Article  CAS  Google Scholar 

  10. Lepikhov, K. et al. Evidence for conserved DNA and histone H3 methylation reprogramming in mouse, bovine and rabbit zygotes. Epigenetics Chromatin 1, 8 (2008)

    Article  Google Scholar 

  11. Molaro, A. et al. Sperm methylation profiles reveal features of epigenetic inheritance and evolution in primates. Cell 146, 1029–1041 (2011)

    Article  CAS  Google Scholar 

  12. Hirasawa, R. et al. Maternal and zygotic Dnmt1 are necessary and sufficient for the maintenance of DNA methylation imprints during preimplantation development. Genes Dev. 22, 1607–1616 (2008)

    Article  CAS  Google Scholar 

  13. Yan, L. et al. Single-cell RNA-Seq profiling of human preimplantation embryos and embryonic stem cells. Nature Struct. Mol. Biol. 20, 1131–1139 (2013)

    Article  CAS  Google Scholar 

  14. Wu, G. et al. Establishment of totipotency does not depend on Oct4A. Nature Cell Biol. 15, 1089–1097 (2013)

    Article  CAS  Google Scholar 

  15. Hackett, J. A. & Surani, M. A. DNA methylation dynamics during the mammalian life cycle. Phil. Trans. R. Soc. Lond. B 368, 20110328 (2013)

    Article  Google Scholar 

  16. Borgel, J. et al. Targets and dynamics of promoter DNA methylation during early mouse development. Nature Genet. 42, 1093–1100 (2010)

    Article  CAS  Google Scholar 

  17. Mertineit, C. et al. Sex-specific exons control DNA methyltransferase in mammalian germ cells. Development 125, 889–897 (1998)

    CAS  PubMed  Google Scholar 

  18. Smits, G. et al. Conservation of the H19 noncoding RNA and H19IGF2 imprinting mechanism in therians. Nature Genet. 40, 971–976 (2008)

    Article  CAS  Google Scholar 

  19. Kelley, D. & Rinn, J. Transposable elements reveal a stem cell-specific class of long noncoding RNAs. Genome Biol. 13, R107 (2012)

    Article  Google Scholar 

  20. Fuchs, N. V. et al. Human endogenous retrovirus K (HML-2) RNA and protein expression is a marker for human embryonic and induced pluripotent stem cells. Retrovirology 10, 115 (2013)

    Article  Google Scholar 

  21. Lu, X. et al. The retrovirus HERVH is a long noncoding RNA required for human embryonic stem cell identity. Nature Struct. Mol. Biol. 21, 423–425 (2014)

    Article  CAS  Google Scholar 

  22. Khan, H., Smit, A. & Boissinot, S. Molecular evolution and tempo of amplification of human LINE-1 retrotransposons since the origin of primates. Genome Res. 16, 78–87 (2006)

    Article  CAS  Google Scholar 

  23. Boissinot, S., Entezam, A. & Furano, A. V. Selection against deleterious LINE-1-containing loci in the human lineage. Mol. Biol. Evol. 18, 926–935 (2001)

    Article  CAS  Google Scholar 

  24. Kelsey, G. & Feil, R. New insights into establishment and maintenance of DNA methylation imprints in mammals. Phil. Trans. R. Soc. Lond. B 368, 20110336 (2013)

    Article  Google Scholar 

  25. Hancks, D. C. & Kazazian, H. H. Jr. Active human retrotransposons: variation and disease. Curr. Opin. Genet. Dev. 22, 191–203 (2012)

    Article  CAS  Google Scholar 

  26. Chen, A. E. et al. Optimal timing of inner cell mass isolation increases the efficiency of human embryonic stem cell derivation and allows generation of sibling cell lines. Cell Stem Cell 4, 103–106 (2009)

    Article  CAS  Google Scholar 

  27. Chenoweth, J. G. & Tesar, P. J. Isolation and maintenance of mouse epiblast stem cells. Methods Mol. Biol. 636, 25–44 (2010)

    Article  Google Scholar 

  28. Meissner, A. et al. Genome-scale DNA methylation maps of pluripotent and differentiated cells. Nature 454 766–770 10.1038/nature07107 (2008)

    Article  ADS  CAS  Google Scholar 

  29. Creyghton, M. P. et al. Histone H3K27ac separates active from poised enhancers and predicts developmental state. Proc. Natl Acad. Sci. USA 107, 21931–21936 (2010)

    Article  ADS  CAS  Google Scholar 

  30. Woodfine, K., Huddleston, J. E. & Murrell, A. Quantitative analysis of DNA methylation at all human imprinted regions reveals preservation of epigenetic stability in adult somatic tissue. Epigenet. Chromatin 4, 1 (2011)

    Article  CAS  Google Scholar 

  31. Storey, J. D. & Tibshirani, R. Statistical significance for genomewide studies. Proc. Natl Acad. Sci. USA 100, 9440–9445 (2003)

    Article  ADS  MathSciNet  CAS  Google Scholar 

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We would like to thank all members of the Meissner, Regev and Eggan laboratories, in particular M. Ziller for critical reading of the text and K. Koszka for supervising human embryo thawing. We also thank D. Sakkas and R. Holmes of Boston IVF for clinical assessment of embryo morphology and viability, as well as S. Levine, M. Gravina and K. Thai from the MIT BioMicro Center. Finally, we thank T. S. Mikkelsen, H. Gu, and A. Gnirke from the Broad Institute for their guidance and expertise. A.R. is an investigator of the Merkin Foundation for Stem Cell Research at the Broad Institute. This work was supported by the Harvard Stem Cell Institute (K.E.), and NIH Pioneer Award (5DP1OD003958), the Burroughs Wellcome Career Award at the Scientific Interface and HHMI (to A.R. and K.E.), P01GM099117 (to A.M. and K. E.) and a Center for Excellence in Genome Science from the NHGRI (1P50HG006193-01, to A.R. and A.M.). A.M. is a New York Stem Cell Foundation Robertson Investigator. This research was supported by The New York Stem Cell Foundation.

Author information

Authors and Affiliations



Z.D.S., K.E. and A.M. conceived the study and Z.D.S., M.M.C., K.C.H., A.R., K.E. and A.M. facilitated its design. Z.D.S., K.C.H. and S.M. collected samples and Z.D.S. performed methylation profiling, M.M.C. and R.K. performed all analysis with assistance from Z.D.S. Z.D.S., M.M.C. and A.M. interpreted the data and wrote the paper with the assistance of the other authors.

Corresponding authors

Correspondence to Kevin Eggan or Alexander Meissner.

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Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Isolation of human preimplantation embryos for DNA methylation mapping.

a, Three replicates of D6 embryos, ranging in inputs from three to five embryos, were thawed, screened for proper morphology, independently isolated from the zona pellucida and pooled before RRBS profiling. Embryos are displayed before purification. b, Two replicates of 18 and 19 human D3 cleavage stage embryos were thawed, screened for proper morphology, assessed for embryonic stage and cell number, and purified from the zona pellucida before RRBS profiling. Embryos are displayed before purification. c, Cell numbers from thawed cleavage stage embryos ranged from 4 to 11 cells per embryo with a median of 8 (±1.6 standard deviation) cells. Within each replicate, only three embryos demonstrated onset of compaction at the time of collection. Red line signifies the median, boxes and whiskers the 25th and 75th, and 2.5th and 97.5th percentiles, respectively.

Extended Data Figure 2 Assembly of a genome-scale DNA methylation time series through human early development and over ES cell derivation.

a, Summary of RRBS libraries generated, with number of biological replicates (n), number CpGs captured at 1×, 5× and 10×, mean and median methylation values for 100-bp tiles estimated from CpGs covered at ≥5×, and mean Euclidean distance and Pearson correlation across biological replicates for these tiles. b, Pearson correlation matrix for sperm, early embryonic and fetal tissue samples. c, Clustering of gametic, somatic and preimplantation methylation profiles segregate according to their global DNA methylation landscape, with sperm and fetal tissue forming a somatic methylation cluster that contrasts the unique epigenetic landscape present in preimplantation embryos. d, Summary of RRBS libraries generated for ES cell derivation, with number of biological replicates (n), number CpGs captured at 1×, 5× and 10×, mean and median methylation values for 100-bp tiles estimated from CpGs covered at ≥5×, and mean Euclidean distance and Pearson correlation across biological replicates for these tiles. ‘ES cell ref’ refers to a reference collection of previously assayed ES cell lines as part of the NIH Roadmap Epigenomics Project (Methods). Human ICM and trophectoderm (TE) were isolated through laser-assisted microdissection. e, Pearson correlation matrix for human samples used to model ES cell derivation. A consistent signature is rapidly acquired by the outgrowth stage (p0) and stably maintained over additional passages. f, Methylation histograms for 100-bp tiles for human blastocysts and dissected ICM and TE tissue show minimal global difference, which is also observed when comparing previously assayed, immunosurgically purified mouse ICM to mechanically dissected ICM and TE. g, Boxplots of the change in methylation (Δ methylation) for 100-bp tiles from cleavage to the blastocyst stage show passive demethylation of DNA methylation, particularly for regions that exhibit the highest methylation levels at this stage. The red line signifies the median, boxes and whiskers the 25th and 75th, and 2.5th and 97.5th percentiles, respectively.

Extended Data Figure 3 Comparison of human ES cell derivation to in vivo mouse pluripotent tissues.

a, Global methylation histograms of 100-bp tiles for human ICM and p5 ES cells (rows) compared against mouse preimplantation and postimplantation embryos (ICM, E6.5 Epi), as well as with extraembryonic ectoderm (ExE) (columns), demonstrate the rapid acquisition of an epiblast-like, somatic methylation pattern upon ES cell derivation in human. b, Regions that discriminate mouse ICM from E6.5 epiblast were used to assign human ICM and ES cells to an equivalent in vivo pluripotent state for orthologous features. The position along the axis from preimplantation (ICM) to postimplantation (Epi) pluripotency represents the proportion of regions in a set that resemble one state versus the other. For all feature sets, human ES cells rapidly establish an epiblast identity, maintaining this signature from the outgrowth stage over ensuing passages. ‘ES cell ref’ refers to a reference collection of previously assayed ES cell lines as part of the NIH Roadmap Epigenomics Project (Methods).

Extended Data Figure 4 Inverse correlation between expression and promoter methylation is retained during human preimplantation.

a, Scatterplots of oocyte, preimplantation embryo and ES cell derivation gene expression compared to promoter methylation display a canonical negative correlation, even during preimplantation where the range of promoter methylation values is contracted by global hypomethylation. b, Box plots of gene expression values for genes significantly upregulated by ≥twofold from oocyte to 8 cell compared to non-dynamic genes and categorized by promoter methylation dynamics. Genes that are both demethylated and upregulated are associated with induction from a silenced state, while those that are demethylated but not upregulated display only basal level transcription that is significantly lower than observed in promoters that are not demethylated. Bold line signifies the median, boxes and whiskers the 25th and 75th, and 2.5th and 97.5th percentiles, respectively. c, Gene expression dynamics following fertilization for hypermethylated sperm promoters demethylated ≥0.5 by the cleavage stage compared to the rest of promoters (Other). 123 of 541 (22%) demethylated promoters demonstrate significant upregulation (≥twofold) compared to only 13.6% of other promoters. Moreover, the ratio of upregulated to downregulated genes in the demethylated set substantially favours zygotic activation, while other promoters include a higher proportion of downregulated maternal transcripts (odds ratio = 1.877, P = 1.344 × 10−8, hypergeometric test). d, RNA-seq track of the pluripotency promoting, zygotically induced gene POU5F1, whose promoter is demethylated from 0.59 in sperm to 0.02 in cleavage, concurrent with its transcriptional induction.

Extended Data Figure 5 Local retention of DNA methylation is similar for introns over human and mouse preimplantation.

a, Introns are clustered according to their dynamics in human and the methylation of orthologous regions are tracked in mouse. Divergence is predominantly restricted to intermediately methylated features in human sperm that are generally hypermethylated in mouse. The Δ methylation heatmap displays the difference in methylation values between equivalent preimplantation time points, with ES cells in human serving as a proxy for comparison to the E6.5 epiblast in mouse. Deviation is most apparent for intermediately methylated human sperm introns, where they are less methylated than in mouse sperm. RMSK included, repeat masker annotated regions included. n shows the number of introns available for cross species comparison. b, When repetitive elements are removed from the calculation of intron methylation, the apparent divergence between mouse and human values in sperm is diminished. Methylation and Δ methylation heatmaps are as in a. Gray denotes missing values (m.v.) where estimates for intronic methylation were exclusively derived from repetitive elements. RMSK-free: repeat masker annotated regions excluded. c, Violin plots of the two main dynamics (maintained versus demethylated, top two clusters in b) for sperm hypermethylated introns over human and mouse preimplantation after repetitive elements are removed. As observed for orthologous exons, regions that retain high methylation throughout human preimplantation are conserved, hypermethylated in both mouse gametes, and display maintained regulation as early as the zygote stage.

Extended Data Figure 6 Genomic characterization of transient maternally contributed imprint-like regions.

a, Heatmap of 100-bp tiles in mouse preimplantation identified using the same criteria as applied to human (Methods). This criteria, which assumes limited de novo methylation, identifies 2,044 tiles in mouse where methylation is ≥0.2 in both 8 cell and the ICM, there is ≥0.2 methylation difference between the ICM and sperm, and this difference is significant via t-test, (q value <0.05). 89% of those tiles that are captured in the mouse oocyte are monoallelically inherited and show significant differences between the gametes by t-test, providing an empirical upper bound on the false discovery rate for this strategy when applied to human of ≤0.11, assuming the underlying principles of imprint regulation are the same as in mouse during this developmental stage. b, The proportion of 100-bp tiles, classified according to their resolution in ES cells, for each genomic feature presented in Fig. 3a. c, Cumulative density function (CDF) plot of the distance to the nearest annotated TSS for CGI DMRs that resolve to hypomethylation, intermediate or variable methylation, or hypermethylation. There is a discrepancy in genomic location between those that resolve to hypomethylation, of which a sizable fraction are in the TSS, and those that do not, which are generally enriched further downstream. d, Boxplots of CpG density for CGI DMRs that resolve to hypomethylation, intermediate or variable methylation, or hypermethylation paired with comparable non-DMR CGIs (Somatic). Those resolving to hypomethylation have higher CpG densities than those that resolve to intermediate or variable, or hypermethylation, but have slightly lower CpG density than non-DMR, constitutively hypomethylated CGIs. Alternatively, while CGIs that resolve to hypermethylation show a lower CpG density than other DMRs, they show higher density than non-DMR hypermethylated islands, suggesting some level of protection against deamination as an attribute of their uniquely hypomethylated status in the male germline. e, Pie charts of cross species alignment and CGI status of human CGI DMRs into mouse. Those that resolve to hypomethylation are more often conserved in mouse and more frequently retain their CGI status, whereas those resolving to hypermethylation are less conserved. Moreover, intermediate/variable and hypermethylation-resolving regions that do align are less frequently retained as CGIs. 368, 166 and 260 CGIs comprise the hypo, intermediate or variable, and hyper methylation sets, respectively.

Extended Data Figure 7 Generation of single blastocyst libraries confirm the monoallelic behaviour of putative maternal DMRs.

a, Summary of two single blastocyst RRBS libraries. Number of CpGs captured at 1×, 5× and 10×, mean and median methylation values for 100-bp tiles estimated from CpGs covered at ≥5×, and mean Euclidean distance and Pearson correlation when single blastocyst replicates are compared to the pooled blastocyst time point. b, Histograms of DNA methylation for 100-bp regions captured for each single blastocyst replicate. c, The ratio of reference allele to alternative allele for single nucleotide polymorphisms (SNPs) called as heterozygous in each blastocyst replicate. d, For the 4,492 and 5,118 SNPs that were considered as heterozygous within each single blastocyst, 10,068 and 11,415 single CpGs could be assigned to alleles. Scatterplots depict untracked methylation values for these CpGs against their normalized methylation values, which are the average of their monoallelic methylation states.

Extended Data Figure 8 The somatic promoter of DNMT1 is maternally methylated in human and mouse.

a, Plots of single CpG methylation for DNMT1, including a CGI over the somatic promoter that behaves as a transient, preimplantation-specific DMR in both human and mouse. In mouse, hypermethylation of this island corresponds to its transcriptional readthrough and exclusion as part of an oocyte-specific isoform (Dnmt1-o) that is not annotated in human. Annotated CGIs and species conservation tracks are included for reference below. b, Heatmap of orthologous ICR dynamics over human and mouse preimplantation. Of those that map between species and are captured by RRBS, all but one (PEG10) behave identically.

Extended Data Figure 9 Repetitive element regulation during human and mouse preimplantation.

a, Violin plots for LTRs over human and mouse development. In human, LTRs demonstrate a bimodal distribution in sperm. Hypermethylated LTRs display a range of demethylation in the early embryo that reflects the dynamics of subfamilies. Upon ES cell derivation, and within fetal tissues, LTRs become stably hypermethylated. Alternatively, during mouse preimplantation, LTRs are consistently hypermethylated in sperm and generally retain methylation over preimplantation. E6.5 Epi and E6.5 ExE refer to dissected epiblast and extraembryonic tissue from E6.5 embryos. b, Violin plots for LINEs over human and mouse development. In human sperm, LINEs are unstably hypermethylated, with discrete populations methylated with a mean of 0.75, ≥0.9, and a small subpopulation showing gametic escape from high methylation. Alternatively, LINEs are indiscriminately hypermethylated in mouse sperm. In both species, several populations of elements demonstrate different extents of demethylation during preimplantation, including many that retain higher levels in cleavage and only minor, passive depletion into blastocyst. Upon human ES cell derivation or during mouse implantation, elements are generally remethylated, though only partially for those elements that are demethylated after fertilization. Hypermethylation is complete in fetal tissue. In human, these discrete dynamics can be attributed to the unstable methylation for L1HS-L1PA3a subfamilies while, in mouse, subsets of L1Md_Tf and L1Md_Gf subfamilies are similarly demethylated and elements of the independently emerging L1Md_A lineage remain largely methylated. c, Violin plots for SINEs highlight intermediate methylation in sperm in both species, though more so for humans. After fertilization, SINE methylation rapidly diminishes to near complete hypomethylation over preimplantation, similar to what is observed for intergenic sequence, before complete hypermethylation during ES cell derivation in human or in postimplantation mouse E6.5 embryos. Taken globally, SINEs appear to be uniformly regulated regardless of subfamily, though differences in regulatory status for specific SINE elements may be reflected by their surrounding genomic context. Unfortunately, such inferences require higher genomic resolution than is currently available to distinguish the dynamics of specific integrations. dg, Violin plots of the four major LTR families present in mouse over the complete preimplantation timeline. ERV1 elements (d) are hypermethylated in sperm and display a range of demethylation following fertilization and prompt remethylation upon implantation. In mouse, ERVK elements (e) are emergent and largely consist of the dominating, constitutively hypermethylated IAP subfamilies. ERVL and MalR (ERVL-MalR) elements (f and g), the evolutionarily oldest mammalian LTRs, are hypermethylated in sperm and rapidly demethylated after fertilization, frequently in association with their rapid zygotic induction. h, Distribution (as boxplots) of per element expression and CpG density at different methylation levels for LTR12c demonstrates negative correlation between methylation and expression. On average, LTR12C is hypomethylated in sperm and the early embryo, but demonstrates a consistent range of values at the level of single elements, with least methylated elements contributing the most to LTR12c expression. The CpG density of these elements corresponds to their degree of hypomethylation, suggesting that escape from de novo methylation during spermatogenesis and preimplantation is maintained for specific elements over generations. Once targeted, element expression is apparently restricted and its CpG density decays correspondingly. During ES cell derivation, the kinetics of LTR12c methylation is more rapid for those of lower CpG density, as evident from p0 to p5 in the ES cell lines. DNA methylation in the early embryo is therefore not exclusive to the regulation of different ERV1 subfamilies, but also affects the contribution of single elements to the broader transcriptional pattern. Bold line signifies the median, boxes and whiskers the 25th and 75th, and 2.5th and 97.5th percentiles, respectively. Expression is calculated as the number of fragments per million that align to a given element divided by its length in kb (FPKM).

Extended Data Figure 10 L1PA subfamily dynamics during human early development.

a, Expression composite averaged by genomic representation for L1HS through L1PA7 from oocyte through preimplantation and ES cell derivation. Dynamic expression within the L1PA phylogeny is restricted to the same subfamilies that are demethylated by cleavage. The position of each respective 5′ UTR, the functional promoter for LINEs, is highlighted in the legend. Beneath these composites is the genomic representation to the full-length consensus for each annotated L1PA subfamily, which demonstrates relative equivalence of 5′ UTR representation across different subfamilies, but an increasing proportion of truncated 3′ fragments with subfamily age (Methods). b, The frequency of CpGs within aligned L1PA subfamilies, including 5′ UTR, ORF1 and ORF2, and 3′ UTR. CpGs are primarily enriched within the 5′ UTR promoter and become progressively CpG depleted with element age. c, Complete composite plot of cleavage stage methylation values across aligned 5′ UTRs from L1HS through L1PA7 as in Fig. 5d. The multiple sequence alignment for each subfamily to the assembled consensus is visualized below each composite, with blue corresponding to conservation, black to divergence, and white to gaps or deletions. The x axis represents position along the 5′ UTR and a portion of ORF1 for the L1HS consensus. CpG Frequency describes the level of conservation for individual CpGs found within single elements to the consensus. The 130-bp sequence present from L1PA7 to L1PA3b and absent from L1PA3a to L1HS is highlighted in pink, while two older sequences specific to L1PA7 are highlighted in grey. d, Percent identity to the consensus for the extracted 130-bp insert sequence in elements from L1PA7 through L1PA3b. Mean nucleotide identity to the consensus is 85%, with a median of 89%.

Supplementary information

Supplementary Table 1

Promoter methylation and gene expression values over human preimplantation development and ESC derivation: Methylation of promoters and corresponding gene expression dynamics across human early development and during ESC derivation. Expression is calculated as the fragments per kb per million (FPKM). (XLS 6199 kb)

Supplementary Table 2

Methylation dynamics of orthologous human and mouse CpG islands: Methylation values in human CGI promoters over preimplantation development. Nearest gene refers to the TSS that is most proximal to the CGI. Human CGIs that aligned to mouse but did not maintain CGI status are indicated under the mouse proximal gene annotation and methylation over the orthologous region is reported when captured (Methods). (XLS 9111 kb)

Supplementary Table 3

Mean LTR subfamily methylation and expression dynamics over human preimplantation development: Family and subfamily designations, genomic representation as indicated by repeat masker, and the number of members captured by RRBS are included. Mean methylation is reported for subfamilies over the human preimplantation and ESC derivation timeline. Expression is calculated as the fragments per kb per million (FPKM), which accounts for differences in genomic representation. Total expression refers to the fragments per million (FPM) and indicates the total contribution of a given family to the transcriptome (Methods). (XLS 280 kb)

Supplementary Table 4

Mean LINE subfamily methylation and expression dynamics over human preimplantation development: Subfamily level mean methylation and expression, including both mean and total, dynamics for LINEs over human preimplantation and ESC derivation, organized as in Supplementary Table 3. (XLS 87 kb)

Supplementary Table 5

Mean SINE subfamily methylation and expression dynamics over human preimplantation development: Subfamily level mean methylation and expression, including both mean and total, dynamics for SINEs over human preimplantation and ESC derivation, organized as in Supplementary Table 3. (XLS 47 kb)

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Smith, Z., Chan, M., Humm, K. et al. DNA methylation dynamics of the human preimplantation embryo. Nature 511, 611–615 (2014).

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