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Record W3198415129 · doi:10.1111/febs.16187

Nucleolar localization of c‐Jun

2021· article· en· W3198415129 on OpenAlexafffund
Tetsuaki Miyake, John C. McDermott

Bibliographic record

VenueFEBS Journal · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsNucleolusRibosome biogenesisNucleoplasmCell biologyBiologyNuclear localization sequencec-junStress granuleRibosomeMolecular biologyNucleusRNAGeneticsGeneMessenger RNATranscription factorTranslation (biology)

Abstract

fetched live from OpenAlex

Nucleoli are well defined for their function in ribosome biogenesis, but only a small fraction of the nucleolar proteome has been characterized. Here, we report that the proto-oncogene, c-Jun, is targeted to the nucleolus. Using live cell imaging in myogenic cells, we document that the c-Jun basic domain contains a unique, evolutionarily conserved motif that determines nucleolar targeting. Fos family Jun dimer partners, such as Fra2, while nuclear, do not co-localize with c-Jun in the nucleolus. A point mutation in c-Jun that mimics Fra2 (M260E) in its Nucleolar Localization sequence (NoLS) results in loss of c-Jun nucleolar targeting while still preserving nuclear localization. Fra2 can sequester c-Jun in the nucleoplasm, indicating that the stoichiometric ratio of heterodimeric partners regulates c-Jun nucleolar targeting. Finally, nucleolar localization of c-Jun modulates nucleolar architecture and ribosomal RNA accumulation. These studies highlight a novel role for Jun family proteins in the nucleolus, having potential implications for a diverse array of AP-1-regulated cellular processes.

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 score0.060
Threshold uncertainty score0.135

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 head0.010
GPT teacher head0.271
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

Citations17
Published2021
Admission routes2
Has abstractyes

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