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Record W4317746823 · doi:10.1038/s41467-023-36019-9

Mechanisms and function of de novo DNA methylation in placental development reveals an essential role for DNMT3B

2023· article· en· W4317746823 on OpenAlexaff
Simon Andrews, Christel Krueger, Maravillas Mellado-López, Myriam Hemberger, Wendy Dean, Vicente Pérez-García, Courtney W. Hanna

Bibliographic record

VenueNature Communications · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
FundersEuropean Regional Development FundGeneralitat ValencianaWellcomeRoyal SocietyUniversity of CambridgeMinisterio de Ciencia e InnovaciónWellcome Trust
KeywordsDNMT3BEpigeneticsBiologyDNA methylationMethyltransferaseGenomic imprintingEmbryoChromatinGeneticsTrophoblastMethylationEmbryogenesisCell biologyPlacentaGeneGene expressionFetusPregnancy

Abstract

fetched live from OpenAlex

DNA methylation is a repressive epigenetic modification that is essential for development, exemplified by the embryonic and perinatal lethality observed in mice lacking de novo DNA methyltransferases (DNMTs). Here we characterise the role for DNMT3A, 3B and 3L in gene regulation and development of the mouse placenta. We find that each DNMT establishes unique aspects of the placental methylome through targeting to distinct chromatin features. Loss of Dnmt3b results in de-repression of germline genes in trophoblast lineages and impaired formation of the maternal-foetal interface in the placental labyrinth. Using Sox2-Cre to delete Dnmt3b in the embryo, leaving expression intact in placental cells, the placental phenotype was rescued and, consequently, the embryonic lethality, as Dnmt3b null embryos could now survive to birth. We conclude that de novo DNA methylation by DNMT3B during embryogenesis is principally required to regulate placental development and function, which in turn is critical for embryo survival.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.133
Threshold uncertainty score0.291

Codex and Gemma teacher scores by category

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

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 head0.016
GPT teacher head0.309
Teacher spread0.292 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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".

Quick stats

Citations100
Published2023
Admission routes1
Has abstractyes

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