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Record W4200177331 · doi:10.1038/s41467-021-27471-6

RNF219 attenuates global mRNA decay through inhibition of CCR4-NOT complex-mediated deadenylation

2021· article· en· W4200177331 on OpenAlexfundno aff
Fabian Poetz, Joshua Corbo, Yevgen Levdansky, Alexander Spiegelhalter, Doris Lindner, Vera Magg, Svetlana Lebedeva, Jörg Schweiggert, Johanna Schott, Eugene Valkov, Georg Stoecklin

Bibliographic record

VenueNature Communications · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsnot available
FundersAlbert-Ludwigs-Universität FreiburgNational Cancer InstituteNational Institutes of HealthMcGovern Medical SchoolBroad InstituteUniversité LavalDeutsche ForschungsgemeinschaftMassachusetts Institute of Technology
KeywordsUbiquitin ligaseAcetylationProtein subunitCell biologyMessenger RNAChemistryUbiquitinMolecular biologyBiologyBiochemistryGene

Abstract

fetched live from OpenAlex

The CCR4-NOT complex acts as a central player in the control of mRNA turnover and mediates accelerated mRNA degradation upon HDAC inhibition. Here, we explored acetylation-induced changes in the composition of the CCR4-NOT complex by purification of the endogenously tagged scaffold subunit NOT1 and identified RNF219 as an acetylation-regulated cofactor. We demonstrate that RNF219 is an active RING-type E3 ligase which stably associates with CCR4-NOT via NOT9 through a short linear motif (SLiM) embedded within the C-terminal low-complexity region of RNF219. By using a reconstituted six-subunit human CCR4-NOT complex, we demonstrate that RNF219 inhibits deadenylation through the direct interaction of the α-helical SLiM with the NOT9 module. Transcriptome-wide mRNA half-life measurements reveal that RNF219 attenuates global mRNA turnover in cells, with differential requirement of its RING domain. Our results establish RNF219 as an inhibitor of CCR4-NOT-mediated deadenylation, whose loss upon HDAC inhibition contributes to accelerated mRNA turnover.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.393

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 head0.036
GPT teacher head0.346
Teacher spread0.311 · 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

Citations41
Published2021
Admission routes1
Has abstractyes

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