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Record W2792060056 · doi:10.1093/biolre/ioy026

Dynamics of DNA methylation reprogramming at the single-cell level in early human embryos†

2018· letter· en· W2792060056 on OpenAlexafffund
Lisa‐Marie Legault, Serge McGraw

Bibliographic record

VenueBiology of Reproduction · 2018
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersCanadian Institutes of Health Research
KeywordsReprogrammingBiologyDNA methylationEmbryoMethylationDNADynamics (music)Cell biologyGeneticsCellGeneGene expression

Abstract

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With boundaries in epigenetic mapping methods and technologies being constantly pushed further, major advances in our understanding of these regulatory mechanisms are being made. The investigation of DNA methylation has particularly benefited from these innovations, rendering genome-wide distribution of DNA methylation marks at a single-base resolution easily obtainable. DNA methylation plays a key role in cellular differentiation and development, and is mainly recognized for its involvement in processes such as transcriptional repression, genomic imprinting, and X-inactivation [1, 2]. DNA methylation marks are mediated by the combined action of mainly three DNA methyltransferases (DNMTs), the de novo enzymes DNMT3A and DNMT3B as well as the maintenance enzyme DNMT1. The absence of DNMT1 or DNMT3A/B during embryo development is lethal, as methylation profiles are not established or properly maintained. In somatic cells, tissue-specific DNA methylation patterns are relatively stable and inherited through cell divisions; however, during germ cell and early embryo development, these patterns are extensively dynamic. Efforts have been particularly devoted to defining how DNA methylation profiles are reprogrammed in mammalian cleavage stage embryos, as it is critical for normal and future development [3–6]. These studies have identified key features regarding the erasure process (i.e., demethylation) occurring after fertilization and the reestablishment of marks (i.e., remethylation) during peri-implantation. However, because of technical limitations, the precise dynamics and kinetics of DNA methylation profiles during this reprogramming wave remained elusive on a genome-wide scale of single blastomeres especially in human embryos. The emergence of single-cell approaches developed for whole-genome bisulfite sequencing has overcome the restrictions associated with the low cell number of early embryos [7, 8]. Using a post-bisulfite adaptor tagging strategy, a collaborative group led by Fuchou Tang, Jie Qiao, and Liying Yan recently established for the first time genome-wide and single-base resolution DNA methylomes of individual cells across the entire first week of human pregnancy [9]. They mapped DNA methylation profiles for 480 individual human preimplantation cells (i.e., paired male and female pronuclei from zygotes, 2-, 4- and 8-cell embryos, morula, blastocyst trophoblast (TE), and inner cell mass (ICM)), oocytes (i.e., germinal vesicle (GV), MII), and sperm cells. Their approach was innovative in many ways. First, compared to previous studies using pooled oocytes or embryos, the sequencing data obtained from a single oocyte or blastomere allowed them to detect aneuploid cells. Since they found that aneuploid cells contained abnormal levels of DNA methylation compared to euploid cells, they were excluded from future analyses to minimize disparity. Secondly, by sequencing the genome of each sperm donor they were able to determine the parental origin of tens of thousands of heterozygous CpG sites in the DNA methylome datasets for individual embryos and blastomeres produced by ICSI (intracytoplasmic sperm injection). The established DNA methylation roadmap revealed a much more complex reprogramming wave than the formerly presumed unidirectional demethylation process. In this landmark paper, Zhu et al. uncovered that the epigenetic reprogramming actually consists of three waves of demethylation interspersed between two remethylation waves with allele-specific variation in DNA methylation levels (Figure 1). The first wave of demethylation occurs independently of DNA replication within the first ∼12 h of fertilization and is especially directed towards CpGs located in enhancers and gene bodies. During this period, the oocyte-derived and sperm-derived pronucleus, respectively, lose ∼4% (54.5%–50.7%) and ∼30% (82.0%–52.9%) of their genomic methylation. A second wave of global demethylation is observed between the late zygote and the 4-cell stage embryo, followed by a third demethylation wave between the 8-cell embryo and ICM/TE of the blastocyst, settling genomic methylation levels to ∼24%. Here, CpGs located in introns and short interspersed nuclear elements were specially targeted. Interestingly, they found two notable and transitory waves of de novo methylation. The first one being a small but significant increase occurring in the male pronucleus of the zygote between the early to mid-pronuclei stages. The second one was a major surge ensuing from the 4-cell to 8-cell progression, similar to the one recently observed during the 2-cell to 8-cell transition in monkeys [5]. Although a very large amount of de novo methylated fragments (n = 73 000 of ≥300 bp in length) that were strongly enriched for major families of transposable elements were affected, most of these regions were rapidly demethylated in the following developmental stages. Subsequently, the authors established that a DNA methylation asymmetry in profiles exists between parental alleles following the first embryonic division until the blastocyst stage. The paternal derived genome is consistently and considerably less methylated than the maternal genome. Surprisingly, single-cell RNA sequencing identified very few genes with allele-specific expression even though asymmetry was clearly present in the ICM and TE cells of the blastocyst. Remarkably, this preferential hypermethylation of the maternal genome was further observed in both the embryonic and extra-embryonic derived lineages. Amongst other interesting findings, they found that single-cell DNA methylation patterns from single blastomeres of a 4-cell embryo could be linked with each parental cell from 2-cell embryos. Dynamics of DNA methylation reprogramming in the maternal and paternal genomes throughout early human embryogenesis. Adapted from Zhu et al. [9]. In this study, Zhu et al. provided clear evidence that the early human embryo reprogramming wave is a tightly regulated process that is even more dynamic than once believed. Curiously, this deep fundamental genome-wide demethylation phase is interrupted by short yet focused remethylation periods. However, it continues to be ambiguous how predetermine regions of the genome are targeted for demethylation or de novo methylation at specific embryonic stages and in an allele-specific manner. If de novo transposable elements targeted methylation potentially explains the maintenance of genome stability during the reprogramming process, the reasoning behind the methylation asymmetry between the maternal and paternal allele genomes and their long-term consequences on gene expression are still unclear. Future work derived from this epigenetic roadmap could determine using DNA methylation editing tools [10] if interfering with the kinetics or parental asymmetry of DNA methylation will lead to abnormal development. It will also be noteworthy to see how key differences between mammals in this epigenetic reprogramming wave contribute to species-specific particularities in early cell fate determination and development. We thank Maude Hoffmann-Belisle for figure design and Elizabeth Maurice-Elder for editing.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.279
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations3
Published2018
Admission routes2
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