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Record W4391838012 · doi:10.1101/2024.02.14.580383

Protein UFMylation regulates early events of ribosomal DNA double-stranded break response

2024· preprint· en· W4391838012 on OpenAlexaff
Pudchalaluck Panichnantakul, Lisbeth C. Aguilar, Evan Daynard, Mackenzie Guest, Colten Peters, Jackie Vogel, Marlene Oeffinger

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsMcGill UniversityUniversité de MontréalMontreal Clinical Research Institute
Fundersnot available
KeywordsBiologyRibosomal DNAChromatinRibosomal proteinDNA damageGeneticsGene silencingNucleolusDNAMolecular biologyCell biologyGeneRibosomeRNA

Abstract

fetched live from OpenAlex

ABSTRACT The highly repetitive and transcriptionally active ribosomal DNA (rDNA) genes are exceedingly susceptible to genotoxic stress. Induction of DNA double-strand breaks (DSBs) in rDNA repeats is associated with ATM-dependent rDNA silencing and nucleolar reorganization where rDNA is segregated into nucleolar caps. However, the regulatory events underlying this response remain elusive. Here, we identify protein UFMylation as essential for rDNA damage response in human cells. We further show the only UFM1-E3-ligase UFL1 and its binding partner DDRGK1 localize to nucleolar caps upon rDNA damage, and that UFL1 loss impairs ATM activation and rDNA transcriptional silencing, leading to reduced rDNA segregation. A first-ever analysis of nuclear and nucleolar UFMylation targets in response to DSBs induction further identified key DNA repair factors including ATM, in addition to chromatin and actin network regulators. Taken together, our data provides the first evidence of an essential role for UFMylation in orchestrating rDNA DSB 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 score0.002
Threshold uncertainty score0.005

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)0.0020.001

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 head0.010
GPT teacher head0.222
Teacher spread0.212 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

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