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Record W4312053004 · doi:10.1016/j.devcel.2022.11.014

RNA degradation eliminates developmental transcripts during murine embryonic stem cell differentiation via CAPRIN1-XRN2

2022· article· en· W4312053004 on OpenAlexaff
Juliane Oliveira Viegas, Gajendra Kumar Azad, Yuan Lv, Lior Fishman, Tal Paltiel, Sundararaghavan Pattabiraman, Jung Eun Park, Daniel Kaganovich, Siu Kwan Sze, Michal Rabani, Miguel A. Esteban, Eran Meshorer

Bibliographic record

VenueDevelopmental Cell · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsBrock University
FundersH2020 Marie Skłodowska-Curie ActionsHORIZON EUROPE Framework ProgrammeIsrael Science FoundationHorizon 2020 Framework ProgrammeNational Natural Science Foundation of China
KeywordsBiologyEmbryonic stem cellCell biologyInduced pluripotent stem cellCellular differentiationRNAGeneticsMolecular biologyGene

Abstract

fetched live from OpenAlex

Embryonic stem cells (ESCs) are self-renewing and pluripotent. In recent years, factors that control pluripotency, mostly nuclear, have been identified. To identify non-nuclear regulators of ESCs, we screened an endogenously labeled fluorescent fusion-protein library in mouse ESCs. One of the more compelling hits was the cell-cycle-associated protein 1 (CAPRIN1). CAPRIN1 knockout had little effect in ESCs, but it significantly altered differentiation and gene expression programs. Using RIP-seq and SLAM-seq, we found that CAPRIN1 associates with, and promotes the degradation of, thousands of RNA transcripts. CAPRIN1 interactome identified XRN2 as the likely ribonuclease. Upon early ESC differentiation, XRN2 is located in the nucleus and colocalizes with CAPRIN1 in small RNA granules in a CAPRIN1-dependent manner. We propose that CAPRIN1 regulates an RNA degradation pathway operating during early ESC differentiation, thus eliminating undesired spuriously transcribed transcripts in ESCs.

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)0.001
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.009
GPT teacher head0.203
Teacher spread0.193 · 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

Citations25
Published2022
Admission routes1
Has abstractno

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