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Record W2649583764 · doi:10.1083/jcb.201610071

Cell cycle–dependent spatial segregation of telomerase from sites of DNA damage

2017· article· en· W2649583764 on OpenAlexafffund
Faissal Ouenzar, Maxime Lalonde, Hadrien Laprade, Geneviève Morin, Franck Gallardo, Samuel Tremblay‐Belzile, Pascal Chartrand

Bibliographic record

VenueThe Journal of Cell Biology · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsUniversité de Montréal
FundersFonds de Recherche du Québec - SantéNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchTerry Fox Foundation
KeywordsBiologyNucleoplasmNucleolusTelomereRAD52RNATelomeraseTelomerase RNA componentCell biologyDNAMolecular biologyDNA repairTelomerase reverse transcriptaseGeneticsGeneCytoplasmRAD51

Abstract

fetched live from OpenAlex

Telomerase can generate a novel telomere at DNA double-strand breaks (DSBs), an event called de novo telomere addition. How this activity is suppressed remains unclear. Combining single-molecule imaging and deep sequencing, we show that the budding yeast telomerase RNA (TLC1 RNA) is spatially segregated to the nucleolus and excluded from sites of DNA repair in a cell cycle–dependent manner. Although TLC1 RNA accumulates in the nucleoplasm in G1/S, Pif1 activity promotes TLC1 RNA localization in the nucleolus in G2/M. In the presence of DSBs, TLC1 RNA remains nucleolar in most G2/M cells but accumulates in the nucleoplasm and colocalizes with DSBs in rad52Δ cells, leading to de novo telomere additions. Nucleoplasmic accumulation of TLC1 RNA depends on Cdc13 localization at DSBs and on the SUMO ligase Siz1, which is required for de novo telomere addition in rad52Δ cells. This study reveals novel roles for Pif1, Rad52, and Siz1-dependent sumoylation in the spatial exclusion of telomerase from sites of DNA repair.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.009
GPT teacher head0.242
Teacher spread0.233 · 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 source (direct Gemma or distilled Codex), 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

Citations18
Published2017
Admission routes2
Has abstractyes

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