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Epigenetic restriction of extraembryonic lineages mirrors the somatic transition to cancer

In mammals, the canonical somatic DNA methylation landscape is established upon specification of the embryo proper and subsequently disrupted within many cancer types1-4. However, the underlying mechanisms that direct this genome-scale transformation remain elusive, with no clear model for its systematic acquisition or potential developmental utility5,6. Here we analyzed global remethylation from the mouse preimplantation embryo into the early epiblast and extraembryonic ectoderm. We show that these two states acquire highly divergent genomic distributions with substantial disruption of bimodal, CpG density-dependent methylation in the placental progenitor7,8. The extraembryonic epigenome includes specific de novo methylation at hundreds of embryonically-protected CpG island promoters particularly those that are associated with key developmental regulators and orthologously methylated across most human cancer types9. Our data suggest that the evolutionary innovation of extraembryonic tissues may have required cooption of DNA methylation-based suppression as an alternative to the embryonically utilized Polycomb group proteins, which coordinate germlayer formation in response to extraembryonic cues10. Moreover, we establish that this decision is made deterministically downstream of promiscuously utilized, and frequently oncogenic, signaling pathways via a novel combination of epigenetic cofactors. Methylation of developmental gene promoters during tumorigenesis may therefore reflect the misappropriation of an innate trajectory and the spontaneous reacquisition of a latent, developmentally-encoded epigenetic landscape.

data suggest that the evolutionary innovation of extraembryonic tissues may have required cooption of DNA methylation-based suppression as an alternative to the embryonically utilized Polycomb group proteins, which coordinate germlayer formation in response to extraembryonic cues 10 . Moreover, we establish that this decision is made deterministically downstream of promiscuously utilized, and frequently oncogenic, signaling pathways via a novel combination of epigenetic cofactors. Methylation of developmental gene promoters during tumorigenesis may therefore reflect the misappropriation of an innate trajectory and the spontaneous reacquisition of a latent, developmentally-encoded epigenetic landscape.
To compare how epigenetic landscapes subsequently evolve during early mammalian development, we generated whole genome bisulfite sequencing (WGBS) and RNA-seq datasets from mouse precompacted 8-cell stage embryos, Inner Cell Mass (ICM) and Trophectoderm from E3.5 blastocysts, as well as Epiblast and Extraembryonic Ectoderm (E×E) from E6.5 conceptuses, the latest stage where these major developmental progenitors remain largely homogeneous and undifferentiated (Fig. 1a, Extended Data Fig. 1, Supplementary Tables 1 and 2). Holistically, our time series captures the expected transition through the indistinguishably hypomethylated, but transcriptionally distinct, blastocyst-stage tissues, followed by a considerable departure at implantation, where ∼80% of the genome becomes differentially methylated (Extended Data Fig. 2a). Specifically, the extraembryonic lineage lacks canonical bimodality: most CpGs are moderately less methylated than in epiblast, while 1.36% are specifically methylated (Extended Data Fig. 2b). E×E-specific hypo or hypermethylation segregate into distinct genomic compartments by CpG density and location, with de novo methylation preferentially enriched for CGIs near transcription start sites (TSSs) and 5′ exons (Fig. 1c, Extended Data Fig. 2c-f). Once established, these alternative landscapes are largely preserved across embryonic tissues and placenta, respectively 11,12 (Extended Data Fig. 2g).
Intriguingly, E×E-methylated CGIs (E×E Hyper CGIs) frequently overlap with PRC2regulated genes, including master transcription factors that direct germlayer and body-axis formation (Fig. 1e, Extended Data Fig. 3a,b, Supplementary Table 1). Although the majority are not yet expressed in the epiblast, E×E-specific promoter methylation is generally associated with repression, including of many pluripotency-specific regulators, as well as concurrent loss of chromatin accessibility (Fig. 1e, Extended Data Fig. 3, 4). The lower global methylation in E×E also results in a more abrupt relationship between promotermethylation and gene-repression that is apparent at levels as low as 0.1 (Extended Data Fig.  4c). DNA methylation surrounding these promoters is largely dispersive, with flanking regions less methylated in E×E than Epiblast, but a maximal increase specifically at the TSS (Fig. 1d). Moreover, while de novo CGI methylation only reaches ∼0.25, methylated CpGs are distributed across 80% of the unique sequencing reads that fall within them, with a median per read methylation status of 0.25 (Extended Data Fig. 4d). The consistency between per molecule and aggregate methylation measurements can only be explained by population-wide recruitment of de novo methyltransferases, followed by stochastic gains at individual CpGs in phase, similar to a variety of cancer systems 13,14 . Importantly, the higher CpG density of E×E-targeted regions invariably leads to a higher local methylation density, even though the per-CpG methylation status is intermediate (Fig. 1e).
Suppression overlaps with WNT pathway effectors that are induced in the proximal epiblast to promote primitive streak formation (Fig. 2a). However, E×E expresses alternative Wnt proteins, suppresses Fgf loci by de novo methylation, and specifically expresses receptors for epiblast-secreted factors (Fig. 2b, Extended Data Fig. 5a). The extraembryonic landscape may proceed deterministically from these two major signaling pathways, which are promiscuously utilized in many downstream developmental processes and frequently misregulated in cancers. To investigate this hypothesis, we selected the ICM as a model because it is indistinguishably hypomethylated from TE and can be cultured independently of FGF, whereas extraembryonic development rapidly attenuates 15 . ICMs were cultured in four conditions using combinations of FGF4, the Mitogen-Activated Protein Kinase Kinase (MAPKK or MEK) inhibitor PD0325901 (PD), and the GSK3β inhibitor, WNT agonist CHIR99021 (CHIR) (Fig. 2c, Extended Data Fig. 5b). Isolated outgrowths were dually assayed by a combined RNA-seq and reduced representation bisulfite sequencing (RRBS) approach (Extended Data Fig. 6, Methods). Those cultured in FGF4+CHIR progressively diverged into two separate, morphologically distinguishable interior and exterior tissues that were independently isolated.
In combination, PD and CHIR comprise the "2i" condition, an FGF-impeded, WNTactivated state that maintains preimplantation-like global hypomethylation 16 . Alternatively, exogenous FGF is sufficient to drive genome and CGI methylation to nonphysiologically high levels (Fig. 2d). Surprisingly, when coupled with FGF, WNT agonism effectively blocks genome remethylation but redirects CGI-level methylation to a broader subset of extraembryonic targets (Fig. 2e, f). Targeting is specific to the FGF+CHIR outgrowth exterior, which establishes an asymmetric Fgfr2 and Fgf4 expression pattern with the interior, similar to what occurs in vivo (Supplementary Tables 3, 4). The specific overlap between in vitro methylated CGIs and E×E appears to reflect progressive restriction of potential targets over early development: those shared across conditions have early developmental functions and are often expressed in the ICM and 2i condition, those methylated in E×E and FGF+CHIR, but not in FGF alone, generally encompass neuroectodermal regulators, and E×E-exclusive islands are often endodermal and induced by dual FGF and WNT activity (Extended Data Fig. 5c). Seemingly, E×E-like global hypomethylation and CGI methylation can be recapitulated in vitro by WNT and FGF, but target-specificity can be modulated to include multiple discrete developmental programs.
We next sought to investigate the configuration of epigenetic regulators that specifically E×Ecute this transition. While Dnmt1 and Dnmt3b are expressed in both tissues, Dnmt3l and Dnmt3a isoform 2 (Dnmt3a2) are reciprocally expressed in either the E×E or epiblast and regulated by de novo methylation in the alternate (Extended Data Fig. 7a-d). A truncated, non-catalytic isoform of the H3K36 demethylase Kdm2b is expressed over preimplantation and within E×E, while a longer Jumonji (JMJ) demethylase domaincontaining isoform is specifically induced in epiblast 17 (Extended Data Fig. 7e). Otherwise, epigenetic regulator expression is relatively stable between the two tissues at this time, such that their specific integration could explain the assembly of such profoundly different landscapes. To compare their capacity to direct both global and CGI methylation, we acutely disrupted Dnmt1, 3a, 3b, and 3l, the essential PRC2 component Eed, and Kdm2b by Dnmt1, 3b and 3l ablation substantially disrupt the E×E methylome, including at CGI targets, but show no specificity for these regions or corresponding changes to expression (Fig. 3a, b, Extended Data Fig. 7f). The near complete loss of methylation in Dnmt1-null E×E compared to epiblast indicates diminished de novo activity, and greater reliance on epigenetic maintenance, despite prolonged Dnmt3l expression (Fig. 3a, b). Alternatively, Eed-null E×E disrupts CGI methylation without affecting global levels, suggesting that PRC2 specifically coordinates repression upstream of DNMT3B as part of a novel developmental pathway (Fig. 3c, d, Extended Data Fig. 7g). Consistently, Eed-null E×E fails to suppress associated genes, which are induced to levels similar to those of sample-matched epiblast (Extended Data Fig. 7h).
Our data indicate a point in early development where sensitivity to promiscuously utilized growth factors instructs a novel epigenome that is not observed during ontogeny. However, de novo CGI methylation is also a general feature of tissue culture, cancer cell lines, and primary tumors, suggesting that somatic cells remain vulnerable 5,18 (Fig. 4a 4a, b). The signal is surprisingly robust and segregates tumor and normal tissue when measured as a feature across patients or when examining CGI-level changes (Fig. 4b, c, Extended Data Fig. 8). 84% of E×E Hyper CGIs are methylated in at least one cancer type, and they are more frequently shared as conserved, pan-cancer targets (Fig. 4d). We find some direct and indirect evidence that CGI methylation can be influenced by FGF sensing. For example, matched mutational and methylation analyses of the entire TCGA data set (n=10,629 tumors) shows a 5.3 percentage point increase in the average methylation of E×E Hyper CGIs when any FGF pathway member is mutated (Extended Data Fig. 10). Similarly, statistical assessment of the connectivity between our E×E Hyper CGIs and the ten most mutated pathways in cancer reveals a striking enrichment for FGFR signaling in disease (Enrichment Z-score=3.88, Extended Data Fig. 10). Over the more expansive, but less internally controlled, ENCODE and ROADMAP data, cancers and immortalized cell lines clearly separate from primary tissues by E×E Hyper CGI methylation status (Fig. 4e,  Supplementary Table 7). Intriguingly, mature adaptive immune cells and endodermal lineages are generally more susceptible to low level methylation within these regions, suggesting a preexisting heterogeneity even in normal populations.
We present the developmental acquisition of a novel epigenetic landscape that partitions extraembryonic tissues within the embryo and resembles a frequent, global departure in genome regulation in human cancers. This landscape cooccurs with the establishment of the first major signaling axes, can be partially directed from hypomethylated ICM in vitro, and appears to be determined by disparate regulation of the DNMTs and associated cofactors. Notably, de novo methylation of CGIs in the E×E requires PRC2, which indicates either a transient, biochemical interaction with the DNMTs or an upstream, primary silencing role. The coordination of this alternative, and presumably more permanent, repressive mechanism warrants further investigation and shares notable parallels to the somatic transition to cancer. Most obviously, FGF sensing passes through RAS/MAPK/ERK signaling, which has extensive oncogenic potential and putative roles in cancer methylome establishment [22][23][24] . Similarly, the E×E displays attenuated de novo methylation activity directed wholly by DNMT3B, broadly resembling the high frequency of somatic DNMT3A mutations in Acute Myeloid Leukemia (AML) and Myelodysplastic Syndrome (MDS) or DNMT3B-directed CGI methylation during colorectal transformation [25][26][27][28] . Transgenic mouse cancer models confirm conserved E×E Hyper CGI methylation in similar contexts (Extended Data Fig. 10). The extraembryonic landscape depends on extrinsic cues with numerous downstream developmental functions, which may provide a latent opportunity for spontaneous state transition without genetic perturbation in later development. If so, the likelihood for such a transition may relate to how closely a given regulatory network resembles the one governing extraembryonic specification. Whether or not additional morphological and molecular features of placental development that appear analogous to cancer hallmarks 29,30 -such as immunosuppression, tissue invasion, and angiogenesis -proceed as part or downstream of this primary epigenetic switch remains unexplored, but would provide a parsimonious developmental foundation to their systematic emergence during transformation.

Sample isolation and library preparation
Preparation of preimplantation and postimplantation samples was performed as described in Ref 31. Briefly, B6D2F1 hybrid females between 5-8 weeks old (Charles River) were serially primed with 5 IU Pregnant Mare Gonadotropin (Sigma) followed by 5 IU Human Chorionic Gonadotrophin (HCG, Millipore) after 46 hours, and subsequently mated with B6D2F1 male mice ≤6 months old. For preimplantation time points, zygotes from mated females were isolated from the oviduct the following morning (E0.5) and cultured in KSOM media (Millipore) droplets under mineral oil until E2. 25. The 8 cell sample was collected by careful monitoring of 4 cell embryos from ∼E2 onwards and emergent 8 cell embryos were swapped into KSOM supplemented with 1 μg/ml aphidicolin (Sigma) to ensure synchronization and minimal entry into the fourth replication cycle. 8 cell embryos were collected within 4 hours of the first apparent embryo of this stage. Prior to collection, embryos were serially transferred through Acid Tyrode's solution (Sigma) to remove the Zona Pellucida and carefully pipetted with a drawn glass capillary through 0.25% Trypsin-EDTA (Life Technologies) to remove maternal polar bodies. E3.5 blastocysts were also treated with Acid Tyrode's solution to remove the Zona and the ICM and TE of matched samples were dissected using standard micromanipulation equipment (Eppendorf) and a Hamilton Thorne XYClone laser with 300 μs pulsing at 100% intensity. Isolation of postimplantation tissues was performed as described 32 . The decidua of mated female mice were isolated on the morning of E6.5 and the conceptus removed. Then, under a stereomicroscope, the embryo was carefully bisected along the extraembryonic/embryonic axis, removing the ectoplacental cone from the extraembryonic ectoderm when apparent. After separation, Epiblast and Extraembryonic Ectoderm (E×E) were incubated for 15 min at 4°C in 0.5% Trypsin, 2.5% Pancreatin dissolved in PBS and allowed to rest for 5-10 minutes in KSOM at room temperature. Finally, visceral endoderm was removed by drawing the embryo through a narrow, flame drawn glass capillary and only samples with no apparent contamination were collected. On average, matched E×E and Epiblast or ICM and TE samples from 5-10 embryos or from 20 or more 8 cell embryos were collected per assay.
DNA for Whole Genome Bisulfite Sequencing was isolated according to Ref 33 and libraries were prepared using the Accel-NGS™ Bisulfite DNA library kit (Swift Biosciences) according to the manufacturers protocol. Final libraries were generated from 10-12 PCR cycles. RNA was purified using the RNAeasy Micro Kit (Qiagen) and RNA-seq libraries generated using the SMRT-seq v4 Ultralow Input Kit (Clontech) according to the manufacturer's protocol with 10-11 LD PCR cycles. Libraries were generated from 150 pg of the subsequent cDNA using the Nextera XT DNA library preparation kit (Illumina) and 12 PCR cycles. ATAC-seq libraries were generated according to Ref 34 using a 10 μl reaction and incubation with the TN5 transposase mixture (Nextera DNA library preparation kit, Illumina) for 45 minutes. Reaction was stopped according to the protocol described in Ref 35 and purified using silane beads (Thermo Fisher). Tagmented DNA was amplified for 12-14 cycles to generate the library. WGBS libraries were sequenced as a pool using the HiSeq × ten platform (Illumina), while RNA-seq and ATAC-seq data were sequenced using the HiSeq 2500 (Illumina).

Outgrowth experiments
To generate controlled outgrowth data, ICM were immunosurgically isolated from BDF1×129S1/SvImJ strain blastocysts at 96hpf as described 31 . Briefly, oocytes were isolated by hormone priming from B6D2F1 females 12-14 hours after administration of hCG and fertilized by Intracytoplasmic Sperm Injection using piezo actuated injection of 129S1/SvIMJ strain sperm 36 . At 96 hrs post-fertilization, blastocysts were stripped of their zona pellucida by brief incubation in Acid Tyrode's solution and incubated for 30 minutes in 1:10 diluted whole mouse antisera (Sigma) in CO 2 equilibrated KSOM, followed by destruction of the trophectoderm by culture in 1:10 diluted Guinea Pig Complement Sera (Sigma). After 15 minutes at 37°C, the ICM separates from the complement-lysed TE and could be cleanly isolated by brief pulsing through a narrow glass capillary. ICM were isolated in batches of ∼12 per drop. Once isolated, ICM were then plated into basal N2/B27 media supplemented with 1000 U/mL LIF (made in house) and one of the following conditions; '2i' supplemented with 1 μM PD0325901 and 3 μM CHIR99021(Reagents Direct) 37 ; 'PD' supplemented with 1 uM PD0325901 and 10 ng/mL BMP4 to promote outgrowth expansion (Peprotech) 38 ; 'FGF+CHIR' supplemented with 25ng/mL mouse recombinant FGF4 (R and D) and 3 μM CHIR99021; and 'FGF' supplemented with 25ng/mL FGF4 only. FGF4 was selected because it is the most highly expressed FGF family member in the preimplantation embryo and we sought to direct specific remethylation changes as is observed in vivo. ICM were plated in gelatin treated tissue culture dishes plated with irradiated CF-1 strain embryonic fibroblasts to promote attachment. The primary outgrowth from the ICM, characterized as a centrally expanding, three-dimensional mass, was isolated after 4 days of culture. In all cases but the 2i condition, an outer layer of differentiated cells was apparent and removed using an identical strategy to removal of the extraembryonic endoderm from E6.5 samples described above. However, under the FGF +CHIR condition, the 'outer layer' was often of the same size or larger than the internal outgrowth and only became defined during the latter portion of culture (see Extended Data Fig. 5b). As such, we collected both interior and exterior portions as they could clearly be distinguished as mutually ICM-derived. After incubation and either isolation or removal of external cells, outgrowths were serially washed through several KSOM drops under mineral oil before being snap frozen in minimal volume for RRBS and RNA-seq profiling.

Generation of KO embryos by CRISPR/Cas9 and zygotic injection
Zygotic injection was performed essentially as described 39 . To improve the efficiency with which null alleles were generated, three separate guide RNA sequences were designed per target, prioritizing highly scored protospacer sequences with no high scoring off target sites using the CHOPCHOP web tool 40 and at as 5′ most a coding exon as possible given these constraints. Protospacer sequences were input into the following oligonucleotide primer pair and used to amplify off of the pX300 plasmid (Addgene): Forward primer, AGTCAGTTAATACGACTCACTATAGN 19 GTTTTAGAGCTAGAAATAGCAAG; Reverse primer, AAAAAAAGCACCGACTCGGTGCCAC. Protospacer sequences that did not begin with a G to initiate T7 transcription were inserted and an additional 5′ G was added. 200 ng of gel purified, T7 promoter containing sgRNA templates were used to generate gRNAs by in vitro transcription using the MEGAshortscript™ T7 transcription kit (Thermo Fisher), followed by purification with phenol:chloroform and ethanol precipitation. Translation competent spCas9 RNA was in vitro transcribed off of a similarly designed, T7 promoter driven template amplified off of the pX300 plasmid using the mMessage mMachine™ T7 Ultra kit (Thermo Fisher) and purified using the RNA Clean and Concentrator Kit (Zymo Research). RNA was resuspended in an injection buffer comprised of 5 mM Tris-HCl, 0.1 mM EDTA, pH=7.4. Zygotes were isolated from hormone primed B6D2F1females mated with B6D2F1 males as described above. Shortly after the formation of visible pronuclei (Pronuclear Stage 3), zygotes were cytoplasmically injected with 100 ng/ul of all three targeted sgRNAs pooled 1:1:1 and 200 ng/ul Cas9 mRNA. At E3.5, cavitated blastocyts were transferred in clutches of 10-15 into one uterine horn of pseudopregnant CD-1 strain mice (Charles River) that had been mated with vasectomized male Swiss-Weber strain mice (Taconic) two days prior. To account for the ∼1 day offset in developmental progression that results from uterine transfer, appropriately E6.5 stage conceptuses were isolated four days after uterine transfer and epiblast and extraembryonic ectoderm tissue were isolated as described above prior to snap freezing in minimal tissue. Each replicate consisted of ≥4 embryos and all experimental series include replicates generated from at least two rounds of zygotic injection. Care was taken to ensure epiblast and extraembryonic ectoderm tissue from matched embryos were included for each replicate set and RRBS data where both fractions did not cover >1 million CpGs at ≥5× coverage each were excluded from further analysis. Disruption of the target allele was confirmed by PCR amplification from the primary cDNA using primers that flank all three protospacer sequences to capture multiple simultaneous perturbations in phase. ThermoFisher Scientific), 1% β-mercaptoethanol (Sigma-Aldrich), and were then transferred to one well in a 96-well DNA LoBind plate (Eppendorf). After adding 10 μl of M-280 streptavidin bead-conjugated RT primer to each sample, the reaction was incubated at 72°C for 3 min in a thermocycler followed by incubation at room temperature for 25 min with gentle rotation. The genomic DNA and mRNA were separated in a DynaMag™-96 Side Magnet (ThermoFisher Scientific). The bead-tagged mRNA was subjected to reverse transcription as described previously 41 and the genomic DNA in the supernatant was transferred to a fresh 96-well DNA LoBind plate. After reverse transcription, the cDNA was PCR amplified and RNA-seq library was generated according to the Smart-seq 2 protocol 42 . IndE×Ed RNA-seq libraries were pooled and sequenced in an Illumina Hiseq2500 sequencer.

Dual RRBS and RNA-seq profiling
Genomic DNA was isolated utilizing 1× Agencourt AMPure beads (Beckman Coulter) and was eluted to 15 μl of low TE buffer. RRBS library was generated as reported previously with modifications 43  For each sample, 10 μl of M-280 streptavidin beads (ThermoFisher Scientific) were prepared per the manufacturer's recommendations. Specifically, after washing with Solution A (0.1 N NaOH, 0.05 M NaCl) and B (0.1 M NaCl) sequentially, the beads were resuspended in 10 μl of 2× Washing and Binding buffer (10 mM Tris-HCl, 1 mM EDTA, 2 M NaCl) and then mixed with an equal volume of 2 μM of RT primer 41 . The mixture was incubated for 15 min at room temperature with gentle rotation. The bead-bound RT primer was collected in a magnate and was subsequently resuspended in 10 μl of binding buffer (10 mM Tris-HCl (PH 8.0), 167 mM NaCl, 0.05% Tween-20).

Estimating methylation levels
The methylation level of each sampled cytosine was estimated as the number of reads reporting a C, divided by the total number of reads reporting a C or T. Single CpG methylation levels were limited to those CpGs that had at least fivefold coverage. For 100 bp tiles, reads for all the CpGs that were covered more than fivefold within the tile were pooled and used to estimate the methylation level as described for single CpGs. The CpG density for a given single CpG is the number of CpGs 50 bp up-and downstream of that CpG. The CpG density for a 100 bp tile is the number of CpGs in the tile. The methylation level reported for a sample is the average methylation by pooling all reads across replicates.

Identification of differentially methylated loci and regions
For WGBS data, identification of differentially methylated loci was performed by DSS, which use biological replicates and information from CpG sites across the genome to stabilize the estimation of the dispersion parameters 44 . Only CpGs that were covered at least fivefold across all samples were considered for a given comparison. An FDR cutoff of 5% was used to identify differentially methylated CpGs. A CGI was called as differentially methylated if it was covered by at least 5 CpGs and 80% of them were significantly hyper/ hypo methylated. For TCGA Illumina Infinium HumanMethylation450K BeadChip data, given that most cancer types have more than 20 tumor and normal samples, Wilcoxon ranksum test was used to identify differentially methylated CpGs, with a FDR cutoff of 5%. All statistical tests throughout this study are two sided. A CGI was called as differentially methylated if 80% of covered CpGs were significantly hyper/hypo methylated. For RRBS data, a simple cutoff of 10% difference in CGI-level methylation was used to call differential methylation.

Gene expression analysis
Alignment was performed using TopHat2 against mouse genome assembly mm9 with default settings. Isoform-level expression was quantified by kallisto, which performs pseudoalignment of reads against cDNA sequence of transcripts. Gene-level expression was estimated as sum of expression of associated isoforms. Refseq mRNA sequences were downloaded from UCSC genome browser. Expression levels were reported as Transcripts Per Million (TPM).

Pathway Enrichment
Pathway enrichment was performed by hypergeometric test using the GSEA online tool. Pvalue was adjusted for multiple hypothesis testing according to Benjamini and Hochberg, with 5% as a cutoff.

Connectivity analysis
We used GRAIL (Gene Relationships Among Implicated Loci, Ref 45) to test whether a query gene is functionally related a set of seed genes. GRAIL utilizes text-mining to quantify the relatedness between two genes in the genome, by which a global gene-network is built. It has been demonstrated that genes who function in the same pathway tend to distribute in a coherent sub-network. In this study, we built a sub-network using E×E Hyper CGI-associated genes, which were significantly enriched in several pathways. To predict whether a query gene is functionally related to the E×E Hyper subnetwork, we project this gene to the global network, and test whether connection of this gene to the subnetwork is random or statistically significant.

ATAC-seq data processing
Reads were aligned to mouse genome mm9 using BWA with default parameters. Duplicates were removed by function MarkDuplicates from Picard tool kit. Reads with low mapping quality (< 10) or in mitochondrial chromosome were removed. NucleoATAC was used to generate Insert density, which was normalized by the total number insertions in each sample 46 .

Orthology mapping between human and mouse
Mouse mm9 CGIs were mapped to human hg19 segments using liftOver with chain file mm9ToHg19.over.chain. Then human orthologous CGIs were defined as the nearest CGIs to the mapped segments.

Extended Data
Extended Data Figure 1. Tracking divergence in DNA methylation landscapes during mouse implantation a-f. Sequencing metrics and coverage information for WGBS, RNA-seq, and ATAC-seq data including hierarchical clustering and Pearson correlation for CpGs, genes, and gene promoters, respectively. WGBS data also includes Euclidean distance, which can be beneficial for examining sample similarity in globally hypomethylated samples, as well as similarity scores for 100 bp tiles, which locally merge the intrinsically higher variance of intermediately methylated CpGs to reduce noise. For RNA-seq and ATAC-seq data, biological replicates cluster together, as do 8 cell and post-implantation WGBS data, while tissues of the E3.5 blastocyst cluster together but not as discrete ICM and TE compartments.  Figure 4 and 7, respectively. g. Unsupervised hierarchical clustering of 11,780 genes over late preimplantation and early post-implantation development, partitioned into 20 distinct dynamics ("clusters"). Cluster 10 includes genes that are specifically induced within the Epiblast but not the E×E. Heatmap intensity reflects the row-normalized Z score. h. Significant Gene Ontology enrichment for the 20 gene expression dynamics characterized in e, including for those regulated by E×E-methylated CGI promoters, as calculated using the binomial test. Cluster 10 is enriched for both developmental functions and E×E promoter methylation.
Extended Data Figure 4. Unique bifurcation and epigenetic reinforcement of transcriptional regulators during postimplantation development a. Genome browser tracks for WGBS, ATAC-seq and RNA-seq data for transcriptional regulators associated with embryonic or extraembryonic development. CGIs are highlighted in green, and the positions of included TSSs are highlighted in red. Embryonic regulators include Pou5f1, Nanog, and Pdrm14, which are progressively expressed over preimplantation and for which Pou5f1 and Nanog remain expressed in the Epiblast. For these genes, repression in E×E is accompanied by differential methylation of their TSSs, which is strikingly apparent as a local hypermethylation "peak" at the Pou5f1 locus within an ∼5kb region that is otherwise hypomethylated in Epiblast. At the Nanog locus, an upstream region remains hypomethylated in both tissues. Finally, de novo methylation of the Prdm14 promoter is representative of the unique E×E-specific target of CGIs promoters that occurs at hundreds of genes with downstream developmental functions. Density refers to the projected number of methylated CpGs per 100 bp of primary sequence and highlights the extensive epigenetic signal present over these regions within E×E specifically (Δ Density refers to the difference compared to epiblast). b. Extraembryonic development is in part directed by the master regulator Elf5, which is not induced until implantation and is reciprocally methylated at its TSS in Epiblast. Intriguingly, many transcriptional regulators associated with pluripotency and germline development  a. Dnmt1 is not appreciably expressed in early cleavage, in part due to a transient maternal imprint over the somatically-utilized TSS (Dnmt1s) 33,55 , but shows moderate induction within the ICM. Then, at implantation, it is induced within both the Epiblast and E×E. Dnmt1 is expressed at higher levels within the E×E and displays persistent focal hypomethylation around the maternal-specific TSS (Dnmt1o) that is not observed in the Epiblast, which resolves an area of preimplantation-specific hypomethylation to the hypermethylated genomic average. b. The short Dnmt3a2 isoform is induced to high levels during implantation and is also expressed within embryonic stem cells (ESCs). Alternatively, the CGI-containing promoter of Dnmt3a2 is methylated in E×E and its transcription is suppressed. c. Like Dnmt1, the Dnmt3b promoter contains a CGI that is maternally imprinted during preimplantation 33,55 . Induction is apparent within the blastocyst, but becomes asymmetrically abundant within the epiblast following implantation.

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Author Manuscript d. Dnmt3l is a non-catalytic cofactor that enhances the de novo activity of Dnmt3a and b, with specific functions in the early embryo and germline 56 . During implantation, Dnmt3l is initially expressed in both ICM and TE, but it remains expressed in E×E and is silenced by de novo methylation in the Epiblast.
e. The Histone-3 lysine 36 (H3K36) demethylase Kdm2b has specific roles in establishing the boundary between promoters and actively transcribed gene bodies, as well as in PRC2 recruitment and the establishment of facultative heterochromatin [57][58][59][60] . A catalyticallyinactive isoform, Kdm2b2, initiates from an alternate TSS downstream of exons encoding the demethylating Jumonji (JMJ) domain of the catalytically active Kdm2b1 17 . Kdm2b2 is the most prevalent isoform during preimplantation development and remains expressed in the E×E. Alternatively, Kdm2b1 is only induced during implantation within the Epiblast, while its CGI-containing promoter gains methylation in E×E. Like Dnmt1s and Dnmt3b, the CGI promoter of Kdm2b1 is a maternally-methylated imprint that resolves to hypomethylation during implantation 33,55 . f. Extraembryonic genome remethylation is highly dependent on Dnmt3b and Dnmt1. Pairwise comparisons of 100 bp tiles as measured by RRBS for wild type Epiblast and E×E (y axis) versus matched CRISPR/Cas9 disrupted tissues (x axis). Extraembryonic methylation levels diminish genome-wide when Dnmt1, Dnmt3b and Dnmt3l are disrupted.
The epiblast is only sensitive to Dnmt1 and Dnmt3b disruption, both to a lesser extent than the E×E, presumably because of compensation from Dnmt3a. Intriguingly, the decrease in global methylation levels when Dnmt1 is deleted is greater for E×E than epiblast, indicating a higher dependence on maintenance and less efficient de novo methyltransferase activity in this tissue. The identity line is included in gray and the best fit by LOESS regression in red. The number of 100 bp tiles used in each comparison and the r 2 are included in the upper left of each plot. g. Composite plots of E×E Hyper CGI-containing promoters in CRISPR/Cas9 targeted Epiblast and E×E respectively. In general, only limited effects are observed in epiblast other than a slight increase in the peripheral methylation within the Eed-null sample.
Alternatively, both TSS proximal and peripheral methylation is decreased in Dnmt1, 3b, and 3l null samples. Specificity for diminished methylation at the TSS is observed in Eed-null E×E, particularly downstream within the first kilobase. In both Epiblast and E×E, the wild type median is included in gray for comparison. Line represents the median and shaded area the 25 th /75 th percentiles, respectively. For RRBS data, composite plots are of the median for 200 bp windows, taken at intervals of 50 bp. h. Statistical test for the derepression of E×E Hyper CGI associated genes demonstrates a comparable requirement for Eed in both epiblast and E×E. Gene expression of KO samples were compared to matched WT samples using DESeq2 with raw counts as input. Enrichment for E×E Hyper CGI associated genes were evaluated by Wilcoxon rank-sum test and represented as Z-scores, which were converted to p-values assuming a normal distribution. Bonferroni correction for multiple testing was applied to derive the FDR.  Figure 1 are included for reference. The median methylation difference between extraembryonic or cancerous tissue compared to Epiblast or normal tissue is also included. The general features of both cancer methylomes are similar to that of the E×E, with a maximal increase in DNA methylation centered at the TSS that steadily diminishes within the periphery. Alternatively, hypomethylated CGIs in extraembryonic or tumorigenic contexts are maximally different a distance away from the TSS, within the boundary or "CpG island shore," as previously reported for cancer 61 . Shaded area represents the 25 th and 75 th percentiles per 100 bp bin. b. Read level methylation of hypermethylated CGIs in E×E vs Epiblast, Colon Tumor vs Colon, and CLL vs B lymphocyte, with those islands that share differential methylation status between the cancer and extraembryonic development included as a subset. The methylation status for every sequencing read within a given hypermethylated CGI was ranked and binned into percentiles. Plotted are the median and 25 th /75 th percentile for these ranks across CGIs called as hypermethylated in each pairwise comparison. The E×E-Epiblast and CLL-B lymphocyte comparisons exhibit very similar distributions that indicate general discordance, meaning similar aggregate methylation across the feature as is observed in phase, which can only be obtained by dispersive de novo methylation across the majority of alleles within the population. Alternatively, Colon Tumor exhibits substantially higher read level methylation, with a median per read methylation of ∼0.7. However, the per-read methylation level of the non-tumorous, matched colon tissue is also quite high, with >50% of reads exhibiting some methylation. This could indicate a transition in the epigenetic status of these loci within colon tissue that precedes tumorigenesis, as has been noted for several other tissues in Extended Data Figure 9. Moreover, the extent to which E×E Hyper CGIs are methylated within each tumor reflects the read-level methylation distribution for the tumor. As such, the targeting to E×E Hyper CGIs is a conserved feature of human cancer types, but the extent to which they are methylated can be specific to the system. c. Data taken from ENCODE samples that reflect embryonic and extraembryonic identities in human in comparison to the well-characterized human cancer cell line HCT116. The human embryonic stem cell line HUES64, a proxy for the pluripotent epiblast, displays notable enrichment for both repressive, PRC2 deposited H3K27me3 and activating H3K4me3 modifications at orthologous E×E Hyper CGIs. Alternatively, human placenta exhibits diminished enrichment for both modifications at these regions, as does HCT116. Both systems display substantial methylation over these islands as presented in Figure 4, Extended Data Figure 9, and Supplementary  Figure 4, with notable additional features of each sample highlighted below. Notably, human extraembryonic tissues, including a trophoblastic cell line and primary placenta, also share conserved CGI methylation with mouse. Normal tissues that appear to exhibit higher mean methylation of E×E Hyper CGIs include numerous endodermal lineages, such as colonic mucosa, stomach and liver (mean methylation of 0.275, 0.185 and 0.179, respectively) as well as mature cell types of the adaptive immune system, such as CD8+ and CD4+ T lymphocytes and B lymphocytes (mean methylation of 0.199, 0.173 and 0.173, respectively). In contrast, ectodermal and epithelial cells are comparatively less methylated than other somatic tissues, although cancer cell lines and primary tumors derived from these tissues remain sensitive to hypermethylation. b. Genome browser tracks for orthologous loci as originally presented for mouse development in Figure 1 display high similar transitions during transformation. Loci include OTX2, GATA4, and the entire HOXC cluster in three human fetal tissues that represent each germ layer (Brain, Ectoderm; Heart, Mesoderm; Stomache, Endoderm), primary human B lymphocytes, and a Chronic Lymphocytic Leukemia (CLL) sample. CGIs around these loci are preserved in a hypomethylated state during embryonic development, where the bimodal architecture of the DNA methylation landscape is clearly maintained. In B lymphocytes, some low-level, encroaching methylation is already apparent over developmentally hypomethylated regions, as is also observed in the Roadmap sample in a. However, in the transition to CLL, extensive methylation is observed across these islands while methylation values drop in the surrounding areas. Red line and shaded area reflect the local mean and standardized deviation as calculated by local regression (LOESS) to compensate for the greater number of CpGs within the human orthologs versus mouse, which can complicate visual estimates of local methylation at these scales. CGIs are highlighted in green, and the positions of included TSSs are highlighted in red.
Extended Data Figure 10. Genetic features of E×E CGI methylation in cancers a. Intersection analysis as presented in Figure 4 for cancer-hypomethylated CGIs across the 14 TCGA tumor types and CLL that exhibit global loss of methylation in tandem with CGI hypermethylation. Generally, CGI hypomethylation is more specific, such that the intersection across cancers decays exponentially. Notably, even for hypomethylated CGI, the intersection across cancer types remains higher for those that are also hypomethylated in E×E, human placenta, or both (conserved). b. Intersection analysis for cancer-dysregulated genes across TCGA tumor types. Of genes significantly dysregulated in at least n (0 -14) TCGA cancer types, the fraction of genes

Supplementary Material
Refer to Web version on PubMed Central for supplementary material.   Epiblast-produced Fibroblast Growth Factors (FGFs) promote E×E development, which expresses Bone Morphogenic Protein 4 (BMP4) to induce Wingless (WNT) proteins in Epiblast. Epiblast secreted pro-Nodal is processed by the E×E to establish a proximal-distal gradient and the primitive streak 10 . b. Expression and differential promoter methylation of key signaling components. Many FGFs and associated receptors exhibit reciprocal expression and promoter methylation between Epiblast and E×E. Wnt3 induction is apparent in epiblast, while Wnt6 and 7b are highly expressed in both TE and E×E. Differential promoter methylation refers to the annotated TSS (+ or -1 kb) with the greatest absolute difference (Supplementary Table 2   respectively, compared to 35% for all CGIs) and are more frequently methylated across them. Inter-tumor enrichment for conserved DMRs is greater than for extraembryonic DMRs from each individual species, and 94% are methylated in at least one cancer type. e. Boxplots of orthologous E×E Hyper CGIs across 107 ENCODE/Roadmap samples, ranked by mean methylation and with cancer or cancer-cell line assignment highlighted (red). "Normal" assigned samples that sort with cancer include the trophoblast cell line HTR8svn, primary colon and colonic mucosa, placenta, and CD8+ T lymphocytes, in descending order. Extended Data Fig. 9 or Supplementary Table 7 includes additional sample characteristics.