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Record W3211209509 · doi:10.15252/embr.202153679

Two redundant ubiquitin-dependent pathways of BRCA1 localization to DNA damage sites

2021· article· en· W3211209509 on OpenAlexafffund
Alana Sherker, Natasha Chaudhary, Salomé Adam, Anne Margriet Heijink, Sylvie M. Noordermeer, Amélie Fradet‐Turcotte, Daniel Durocher

Bibliographic record

VenueEMBO Reports · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsUniversité LavalLunenfeld-Tanenbaum Research InstituteUniversity of TorontoHôtel-Dieu de QuébecMount Sinai Hospital
FundersCanadian Institutes of Health ResearchKrembil FoundationGovernment of Canada
KeywordsMountLibrary scienceHistoryEngineeringComputer science

Abstract

fetched live from OpenAlex

The tumor suppressor BRCA1 accumulates at sites of DNA damage in a ubiquitin-dependent manner. In this work, we revisit the role of RAP80 in promoting BRCA1 recruitment to damaged chromatin. We find that RAP80 acts redundantly with the BRCA1 RING domain to promote BRCA1 recruitment to DNA damage sites. We show that that RNF8 E3 ligase acts upstream of both the RAP80- and RING-dependent activities, whereas RNF168 acts uniquely upstream of the RING domain. BRCA1 RING mutations that do not impact BARD1 interaction, such as the E2 binding-deficient I26A mutation, render BRCA1 unable to accumulate at DNA damage sites in the absence of RAP80. Cells that combine BRCA1 I26A and mutations that disable the RAP80-BRCA1 interaction are hypersensitive to PARP inhibition and are unable to form RAD51 foci. Our results suggest that in the absence of RAP80, the BRCA1 E3 ligase activity is necessary for recognition of histone H2A Lys13/Lys15 ubiquitylation by BARD1, although we cannot rule out the possibility that the BRCA1 RING facilitates ubiquitylated nucleosome recognition in other ways.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.253
Teacher spread0.240 · 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

Citations24
Published2021
Admission routes2
Has abstractno

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Same venueEMBO ReportsSame topicDNA Repair MechanismsFrench-language works237,207