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Record W2235069458 · doi:10.1093/nar/gkv1080

Slx4 and Rtt107 control checkpoint signalling and DNA resection at double-strand breaks

2015· article· en· W2235069458 on OpenAlexaff
Diego Dibitetto, Matteo Ferrari, Chetan C. Rawal, Attila Balint, Tae‐Hyung Kim, Zhaolei Zhang, Marcus B. Smolka, Grant W. Brown, F. Marini, Achille Pellicioli

Bibliographic record

VenueNucleic Acids Research · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsUniversity of Toronto
FundersNational Institute of General Medical Sciences
KeywordsG2-M DNA damage checkpointBiologyCheckpoint Kinase 2DNA damageCell biologyDNA repairCell cycle checkpointHomologous recombinationDNAScaffold proteinTelomereDNA replicationGeneticsCell cycleCellSignal transduction

Abstract

fetched live from OpenAlex

The DNA damage checkpoint pathway is activated in response to DNA lesions and replication stress to preserve genome integrity. However, hyper-activation of this surveillance system is detrimental to the cell, because it might prevent cell cycle re-start after repair, which may also lead to senescence. Here we show that the scaffold proteins Slx4 and Rtt107 limit checkpoint signalling at a persistent double-strand DNA break (DSB) and at uncapped telomeres. We found that Slx4 is recruited within a few kilobases of an irreparable DSB, through the interaction with Rtt107 and the multi-BRCT domain scaffold Dpb11. In the absence of Slx4 or Rtt107, Rad9 binding near the irreparable DSB is increased, leading to robust checkpoint signalling and slower nucleolytic degradation of the 5' strand. Importantly, in slx4Δ sae2Δ double mutant cells these phenotypes are exacerbated, causing a severe Rad9-dependent defect in DSB repair. Our study sheds new light on the molecular mechanism that coordinates the processing and repair of DSBs with DNA damage checkpoint signalling, preserving genome integrity.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.576

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 head0.048
GPT teacher head0.320
Teacher spread0.272 · 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

Citations47
Published2015
Admission routes1
Has abstractyes

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