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Record W2898159486 · doi:10.1093/nar/gky1011

Human MARF1 is an endoribonuclease that interacts with the DCP1:2 decapping complex and degrades target mRNAs

2018· article· en· W2898159486 on OpenAlexafffund
Tamiko Nishimura, Hana Fakim, Tobias Brandmann, Ji‐Young Youn, Anne‐Claude Gingras, Martin Jínek, Marc R. Fabian

Bibliographic record

VenueNucleic Acids Research · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsMcGill UniversitySinai Health SystemLunenfeld-Tanenbaum Research InstituteUniversity of TorontoJewish General Hospital
FundersEuropean Research CouncilNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsBiologyEndoribonucleaseCell biologyRNA-binding proteinMessenger RNAGeneticsRNA interferenceRNASomatic cellPsychological repressionGeneMolecular biologyGene expressionRNase P

Abstract

fetched live from OpenAlex

Meiosis arrest female 1 (MARF1) is a cytoplasmic RNA binding protein that is essential for meiotic progression of mouse oocytes, in part by limiting retrotransposon expression. MARF1 is also expressed in somatic cells and tissues; however, its mechanism of action has yet to be investigated. Human MARF1 contains a NYN-like domain, two RRMs and eight LOTUS domains. Here we provide evidence that MARF1 post-transcriptionally silences targeted mRNAs. MARF1 physically interacts with the DCP1:DCP2 mRNA decapping complex but not with deadenylation machineries. Importantly, we provide a 1.7 Å resolution crystal structure of the human MARF1 NYN domain, which we demonstrate is a bona fide endoribonuclease, the activity of which is essential for the repression of MARF1-targeted mRNAs. Thus, MARF1 post-transcriptionally represses gene expression by serving as both an endoribonuclease and as a platform that recruits the DCP1:DCP2 decapping complex to targeted mRNAs.

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 score0.006

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 head0.084
GPT teacher head0.371
Teacher spread0.287 · 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

Citations33
Published2018
Admission routes2
Has abstractyes

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