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Record W2161879504 · doi:10.1083/jcb.150.1.13

Mitotic Transcription Repression in Vivo in the Absence of Nucleosomal Chromatin Condensation

2000· article· en· W2161879504 on OpenAlexaff
Charlotte A. Spencer, Michael J. Kruhlak, Heather L. Jenkins, Xuejun Sun, David P. Bazett‐Jones

Bibliographic record

VenueThe Journal of Cell Biology · 2000
Typearticle
Languageen
FieldMedicine
TopicHerpesvirus Infections and Treatments
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsBiologyChromatinMitosisCell biologyRNA polymerase IITranscription (linguistics)ProphaseMolecular biologyTranscription coregulatorPromoterDNAGeneticsGene expressionGeneChromatin remodeling

Abstract

fetched live from OpenAlex

All nuclear RNA synthesis is repressed during the mitotic phase of the cell cycle. In addition, RNA polymerase II (RNAP II), nascent RNA and many transcription factors disengage from DNA during mitosis. It has been proposed that mitotic transcription repression and disengagement of factors are due to either mitotic chromatin condensation or biochemical modifications to the transcription machinery. In this study, we investigate the requirement for chromatin condensation in establishing mitotic transcription repression and factor loss, by analyzing transcription and RNAP II localization in mitotic cells infected with herpes simplex virus type 1. We find that virus-infected cells enter mitosis and that mitotic viral DNA is maintained in a nucleosome-free and noncondensed state. Our data show that RNAP II transcription is repressed on cellular genes that are condensed into mitotic chromosomes and on viral genes that remain nucleosome free and noncondensed. Although RNAP II may interact indirectly with viral DNA during mitosis, it remains transcriptionally unengaged. This study demonstrates that mitotic repression of transcription and loss of transcription factors from mitotic DNA can occur independently of nucleosomal chromatin condensation.

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 score0.510
Threshold uncertainty score0.469

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 head0.277
Teacher spread0.261 · 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

Citations92
Published2000
Admission routes1
Has abstractyes

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