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Record W2209836010 · doi:10.1083/jcb.201503070

The nuclear basket mediates perinuclear mRNA scanning in budding yeast

2015· article· en· W2209836010 on OpenAlexafffund
Mark-Albert Saroufim, Pierre Bensidoun, Pascal Raymond, Samir Rahman, Matthew R. Krause, Marlene Oeffinger, Daniel Zenklusen

Bibliographic record

VenueThe Journal of Cell Biology · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsMcGill UniversityMontreal Neurological Institute and HospitalMontreal Clinical Research InstituteUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsNuclear poreBiologyNucleoplasmMessenger RNPNucleoporinNuclear export signalCell biologyNuclear laminaRibonucleoproteinLaminCytoplasmNuclear transportMessenger RNANuclear proteinCell nucleusRNARNA-binding proteinNucleusNucleolusGeneticsGeneTranscription factor

Abstract

fetched live from OpenAlex

After synthesis and transit through the nucleus, messenger RNAs (mRNAs) are exported to the cytoplasm through the nuclear pore complex (NPC). At the NPC, messenger ribonucleoproteins (mRNPs) first encounter the nuclear basket where mRNP rearrangements are thought to allow access to the transport channel. Here, we use single mRNA resolution live cell microscopy and subdiffraction particle tracking to follow individual mRNAs on their path toward the cytoplasm. We show that when reaching the nuclear periphery, RNAs are not immediately exported but scan along the nuclear periphery, likely to find a nuclear pore allowing export. Deletion or mutation of the nuclear basket proteins MLP1/2 or the mRNA binding protein Nab2 changes the scanning behavior of mRNPs at the nuclear periphery, shortens residency time at nuclear pores, and results in frequent release of mRNAs back into the nucleoplasm. These observations suggest a role for the nuclear basket in providing an interaction platform that keeps RNAs at the periphery, possibly to allow mRNP rearrangements before export.

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)0.002
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 score0.546
Threshold uncertainty score0.172

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.267
Teacher spread0.251 · 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

Citations78
Published2015
Admission routes2
Has abstractyes

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