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Record W2969895325 · doi:10.1038/s41467-019-11791-9

Pioneer and nonpioneer factor cooperation drives lineage specific chromatin opening

2019· article· en· W2969895325 on OpenAlexafffund
Alexandre Mayran, Kevin Sochodolsky, Konstantin Khetchoumian, Juliette Harris, Yves Gauthier, Amandine Bemmo, Aurélio Balsalobre, Jacques Drouin

Bibliographic record

VenueNature Communications · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Chromatin Dynamics
Canadian institutionsMcGill UniversityUniversité de MontréalMontreal Clinical Research Institute
FundersCanadian Institutes of Health ResearchGovernment of CanadaCompute Canada
KeywordsChromatinEnhancerHeterochromatinScaffold/matrix attachment regionTranscription factorBiologyChIA-PETPioneer factorChromatin remodelingCell biologyHistoneGeneticsComputational biologyGene

Abstract

fetched live from OpenAlex

Pioneer transcription factors are characterized by having the unique property of enabling the opening of closed chromatin sites, for implementation of cell fates. We previously found that the pioneer Pax7 specifies melanotrope cells through deployment of an enhancer repertoire, which allows binding of Tpit, a nonpioneer factor that determines the related lineages of melanotropes and corticotropes. Here, we investigate the relation between these two factors in the pioneer mechanism. Cell-specific gene expression and chromatin landscapes are defined by scRNAseq and chromatin accessibility profiling. We find that in vivo deployment of the melanotrope enhancer repertoire and chromatin opening requires both Pax7 and Tpit. In cells, binding of heterochromatin targets by Pax7 is independent of Tpit but Pax7-dependent chromatin opening requires Tpit. The present work shows that pioneer core properties are limited to the ability to recognize heterochromatin targets and facilitate nonpioneer binding. Chromatin opening per se may be provided through cooperation with nonpioneer factors.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.886
Threshold uncertainty score0.448

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 head0.008
GPT teacher head0.251
Teacher spread0.243 · 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

Citations144
Published2019
Admission routes2
Has abstractyes

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