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Record W3208000318 · doi:10.1038/s41467-021-26413-6

Arginine methylation and ubiquitylation crosstalk controls DNA end-resection and homologous recombination repair

2021· article· en· W3208000318 on OpenAlexfundno aff
María Pilar Sánchez-Bailón, Soo‐Youn Choi, Elizabeth R. Dufficy, Karan Sharma, Gavin S. McNee, Emma A. Gunnell, Kelly Chiang, Debashish Sahay, Sarah Maslen, Grant S. Stewart, Mark Skehel, Ingrid Dreveny, Clare C. Davies

Bibliographic record

VenueNature Communications · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related gene regulation
Canadian institutionsnot available
FundersMedical Research CouncilCancer Research UKMcGill University
KeywordsHomologous recombinationCrosstalkDNA repairMethylationDNAUbiquitinBiologyDNA methylationArginineDNA damageCell biologyHomologous chromosomeGeneticsChemistryBiochemistryGeneAmino acid

Abstract

fetched live from OpenAlex

Cross-talk between distinct protein post-translational modifications is critical for an effective DNA damage response. Arginine methylation plays an important role in maintaining genome stability, but how this modification integrates with other enzymatic activities is largely unknown. Here, we identify the deubiquitylating enzyme USP11 as a previously uncharacterised PRMT1 substrate, and demonstrate that the methylation of USP11 promotes DNA end-resection and the repair of DNA double strand breaks (DSB) by homologous recombination (HR), an event that is independent from another USP11-HR activity, the deubiquitylation of PALB2. We also show that PRMT1 is a ubiquitylated protein that it is targeted for deubiquitylation by USP11, which regulates the ability of PRMT1 to bind to and methylate MRE11. Taken together, our findings reveal a specific role for USP11 during the early stages of DSB repair, which is mediated through its ability to regulate the activity of the PRMT1-MRE11 pathway.

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)0.000
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 score0.599
Threshold uncertainty score0.582

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.010
GPT teacher head0.290
Teacher spread0.280 · 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

Citations44
Published2021
Admission routes1
Has abstractyes

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