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Record W2782655012 · doi:10.1016/j.celrep.2017.12.047

RYBP Is a K63-Ubiquitin-Chain-Binding Protein that Inhibits Homologous Recombination Repair

2018· article· en· W2782655012 on OpenAlexafffund
Mohammad Ali, Hilmar Strickfaden, Brian L. Lee, Leo Spyracopoulos, Michael J. Hendzel

Bibliographic record

VenueCell Reports · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchAlberta Innovates - Health SolutionsAlberta Cancer Foundation
KeywordsUbiquitinHomologous recombinationDNA repairDNACell biologyBiologyChemistryMolecular biologyBiochemistryGene

Abstract

fetched live from OpenAlex

Ring1-YY1-binding protein (RYBP) is a member of the non-canonical polycomb repressive complex 1 (PRC1), and like other PRC1 members, it is best described as a transcriptional regulator. However, several PRC1 members were recently shown to function in DNA repair. Here, we report that RYBP preferentially binds K63-ubiquitin chains via its Npl4 zinc finger (NZF) domain. Since K63-linked ubiquitin chains are assembled at DNA double-strand breaks (DSBs), we examined the contribution of RYBP to DSB repair. Surprisingly, we find that RYBP is K48 polyubiquitylated by RNF8 and rapidly removed from chromatin upon DNA damage by the VCP/p97 segregase. High expression of RYBP competitively inhibits recruitment of BRCA1 repair complex to DSBs, reducing DNA end resection and homologous recombination (HR) repair. Moreover, breast cancer cell lines expressing high endogenous RYBP levels show increased sensitivity to DNA-damaging agents and poly ADP-ribose polymerase (PARP) inhibition. These data suggest that RYBP negatively regulates HR repair by competing for K63-ubiquitin chain binding.

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)0.0010.000

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 head0.012
GPT teacher head0.233
Teacher spread0.221 · 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

Citations28
Published2018
Admission routes2
Has abstractyes

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