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Record W3204335694 · doi:10.1101/gad.348671.121

Dynamics in Fip1 regulate eukaryotic mRNA 3′ end processing

2021· article· en· W3204335694 on OpenAlexfundno aff
Ananthanarayanan Kumar, C. Yu, Juan B. Rodríguez‐Molina, Xiaohan Li, Stefan M.V. Freund, Lori A. Passmore

Bibliographic record

VenueGenes & Development · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsnot available
FundersH2020 Marie Skłodowska-Curie ActionsMedical Research CouncilMedical Research Council CanadaEuropean CommissionGates Cambridge TrustUK Research and InnovationWellcome TrustFrancis Crick InstituteCancer Research UK
KeywordsBiologyMessenger RNACell biologyDynamics (music)Rna processingComputational biologyGeneticsEvolutionary biologyGene

Abstract

fetched live from OpenAlex

Cleavage and polyadenylation factor (CPF/CPSF) is a multiprotein complex essential for mRNA 3' end processing in eukaryotes. It contains an endonuclease that cleaves pre-mRNAs, and a polymerase that adds a poly(A) tail onto the cleaved 3' end. Several CPF subunits, including Fip1, contain intrinsically disordered regions (IDRs). IDRs within multiprotein complexes can be flexible, or can become ordered upon interaction with binding partners. Here, we show that yeast Fip1 anchors the poly(A) polymerase Pap1 onto CPF via an interaction with zinc finger 4 of another CPF subunit, Yth1. We also reconstitute a fully recombinant 850-kDa CPF. By incorporating selectively labeled Fip1 into recombinant CPF, we could study the dynamics of Fip1 within the megadalton complex using nuclear magnetic resonance (NMR) spectroscopy. This reveals that a Fip1 IDR that connects the Yth1- and Pap1-binding sites remains highly dynamic within CPF. Together, our data suggest that Fip1 dynamics within the 3' end processing machinery are required to coordinate 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 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 score0.342
Threshold uncertainty score0.483

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 head0.011
GPT teacher head0.256
Teacher spread0.245 · 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

Citations20
Published2021
Admission routes1
Has abstractyes

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