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Investigating the Effects of Histone H3.3 Point Mutations in Neural Crest Cells and Craniofacial Development

2020· article· en· W3018597893 on OpenAlexaff
Nadine Nzirorera, Nada Jabado, Loydie Majewska

Bibliographic record

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Chromatin Dynamics
Canadian institutionsMcGill University
Fundersnot available
KeywordsBiologyNeural crestHistoneHistone H3Histone methylationHistone codeChromatinCell biologyEpigeneticsGeneticsNucleosomeDNA methylationGene expressionGene

Abstract

fetched live from OpenAlex

Craniofacial development is an intricate process that requires the meticulous and coordinated expression of many genes. Histone proteins which are fundamental to both the structural integrity and organization of DNA into nucleosomes and consequently, chromatin play an important role in coordinated gene expression. Furthermore, the modification of histone tails is now known to be an essential mechanism for coordinated expression of a large number of genes. Recently, a point mutation in the gene h3f3a which encodes the histone variant Histone H3.3, was identified in a forward genetic screen in zebrafish. H3.3A was found to be important for neural crest cell induction and generation of cranial neural crest cell derived head bones. The authors proposed that incorporation of histone H3.3 was required for expression of genes important for cranial neural crest cell specification, whereas remodelling of this histone tail may be important for later stages in neural crest cell differentiation. However, it remains to be confirmed if disrupted modification of histone tails is also important in neural crest cells. We postulate that modification of the H3.3 tail is required for coordinated expression of genes important for neural crest migration and/or differentiation. To test this hypothesis, we used CRISPR/Cas9 to generate a mouse line with a conditional missense mutation in H3f3a. The mutation generated was previously shown to result in an abnormal increase in methylation of K27 and a decrease in methylation of K36 of the histone H3.3 tail. In this poster, we will present preliminary data using the Wnt‐1 Cre2 mouse line to drive expression of this dominant negative mutation in neural crest cells. Alcian Blue Staining will be used to analyze cartilage in E14.5 embryos and alizarin red will be used to stain bones formed in heads of E17.5 embryos. Bones will be analyzed in control and mutant embryos. Our result will enable us to uncover if K27 or K36 methylation is important in neural crest cell formation, migration and/or differentiation. This work will begin to unravel the role of epigenetics in neural crest cell formation. Support or Funding Information

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.008
GPT teacher head0.228
Teacher spread0.220 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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