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Record W4311633668 · doi:10.3389/fcell.2022.1026406

Targets of histone H3 lysine 9 methyltransferases

2022· review· en· W4311633668 on OpenAlexaff
Aidan J. Levinsky, Gregor McEdwards, Nasha S. Sethna, Mark A. Currie

Bibliographic record

VenueFrontiers in Cell and Developmental Biology · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHistone methyltransferaseEZH2Histone methylationBiologyMethyltransferaseEpigenomicsHistone codeHeterochromatin protein 1Histone H3Histone H2AHeterochromatinHistoneChromatin remodelingChromatinGeneticsCell biologyDNA methylationMethylationNucleosomeDNAGene expressionGene

Abstract

fetched live from OpenAlex

Histone H3 lysine 9 di- and trimethylation are well-established marks of constitutively silenced heterochromatin domains found at repetitive DNA elements including pericentromeres, telomeres, and transposons. Loss of heterochromatin at these sites causes genomic instability in the form of aberrant DNA repair, chromosome segregation defects, replication stress, and transposition. H3K9 di- and trimethylation also regulate cell type-specific gene expression during development and form a barrier to cellular reprogramming. However, the role of H3K9 methyltransferases extends beyond histone methylation. There is a growing list of non-histone targets of H3K9 methyltransferases including transcription factors, steroid hormone receptors, histone modifying enzymes, and other chromatin regulatory proteins. Additionally, two classes of H3K9 methyltransferases modulate their own function through automethylation. Here we summarize the structure and function of mammalian H3K9 methyltransferases, their roles in genome regulation and constitutive heterochromatin, as well as the current repertoire of non-histone methylation targets including cases of automethylation.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.022
GPT teacher head0.305
Teacher spread0.284 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations15
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in Cell and Developmental BiologySame topicEpigenetics and DNA MethylationFrench-language works237,207