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Record W2971484369 · doi:10.1016/j.sbi.2019.08.001

Mechanistic insights into mRNA 3′-end processing

2019· review· en· W2971484369 on OpenAlexfundno aff
Ananthanarayanan Kumar, Marcello Clerici, Lena M. Muckenfuss, Lori A. Passmore, Martin Jínek

Bibliographic record

VenueCurrent Opinion in Structural Biology · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsnot available
FundersEuropean Research CouncilMedical Research CouncilMedical Research Council CanadaGates Cambridge TrustBoehringer Ingelheim FondsEuropean CommissionVallee FoundationHoward Hughes Medical Institute
KeywordsComputational biologyMessenger RNABiologyChemistryGeneticsGene

Abstract

fetched live from OpenAlex

The polyadenosine (poly(A)) tail found on the 3'-end of almost all eukaryotic mRNAs is important for mRNA stability and regulation of translation. mRNA 3'-end processing occurs co-transcriptionally and involves more than 20 proteins to specifically recognize the polyadenylation site, cleave the pre-mRNA, add a poly(A) tail, and trigger transcription termination. The polyadenylation site (PAS) defines the end of the 3'-untranslated region (3'-UTR) and, therefore, selection of the cleavage site is a critical event in regulating gene expression. Integrated structural biology approaches including biochemical reconstitution of multi-subunit complexes, cross-linking mass spectrometry, and structural analyses by X- ray crystallography and single-particle electron cryo-microscopy (cryoEM) have enabled recent progress in understanding the molecular mechanisms of the mRNA 3'-end processing machinery. Here, we describe new molecular insights into pre-mRNA recognition, cleavage and polyadenylation.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.081
GPT teacher head0.424
Teacher spread0.342 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations112
Published2019
Admission routes1
Has abstractyes

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