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Record W4313400082 · doi:10.1016/j.celrep.2022.111917

APLF and long non-coding RNA NIHCOLE promote stable DNA synapsis in non-homologous end joining

2022· article· en· W4313400082 on OpenAlexfundno aff
Sara de Bragança, Clara Aicart-Ramos, Raquel Arribas-Bosacoma, Ángel Rivera-Calzada, Juan P. Unfried, Laura Prats-Mari, Mikel Marín-Baquero, Puri Fortes, Óscar Llorca, Fernando Moreno‐Herrero

Bibliographic record

VenueCell Reports · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsnot available
FundersEuropean Social FundDivision of ChemistryInstituto de Salud Carlos IIIConsejo Superior de Investigaciones CientíficasAgencia Estatal de InvestigaciónInstitute for Advanced Studies in the Humanities, University of EdinburghAzrieli FoundationEuropean CommissionEuropean Regional Development FundFederación Española de Enfermedades RarasMinisterio de Ciencia e InnovaciónUniversity of SussexEuropean Molecular Biology Organization
KeywordsKu70SynapsisKu80DNABiologyCell biologyHomologous chromosomeGeneticsBiophysicsDNA repairChemistryDNA-binding protein

Abstract

fetched live from OpenAlex

The synapsis of DNA ends is a critical step for the repair of double-strand breaks by non-homologous end joining (NHEJ). This is performed by a multicomponent protein complex assembled around Ku70-Ku80 heterodimers and regulated by accessory factors, including long non-coding RNAs, through poorly understood mechanisms. Here, we use magnetic tweezers to investigate the contributions of core NHEJ proteins and APLF and lncRNA NIHCOLE to DNA synapsis. APLF stabilizes DNA end bridging and, together with Ku70-Ku80, establishes a minimal complex that supports DNA synapsis for several minutes under piconewton forces. We find the C-terminal acidic region of APLF to be critical for bridging. NIHCOLE increases the dwell time of the synapses by Ku70-Ku80 and APLF. This effect is further enhanced by a small and structured RNA domain within NIHCOLE. We propose a model where Ku70-Ku80 can simultaneously bind DNA, APLF, and structured RNAs to promote the stable joining of DNA ends.

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)0.001
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 score0.015
Threshold uncertainty score0.608

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.008
GPT teacher head0.238
Teacher spread0.231 · 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

Citations16
Published2022
Admission routes1
Has abstractyes

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