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Record W4414870992 · doi:10.1101/cshperspect.a041700

Telomerase RNA Shapes the Evolutionary Diversity of Telomerase Ribonucleoproteins (RNPs)

2025· article· en· W4414870992 on OpenAlexaff
Julian J.‐L. Chen, Raymund J. Wellinger

Bibliographic record

VenueCold Spring Harbor Perspectives in Biology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversité de Sherbrooke
FundersNational Institute of General Medical Sciences
KeywordsTelomeraseTelomerase RNA componentTelomereRibonucleoproteinRNABiogenesisNon-coding RNATelomerase reverse transcriptaseRNA-dependent RNA polymerase

Abstract

fetched live from OpenAlex

Telomerase emerged in early eukaryotes as a highly specialized reverse transcriptase for maintaining chromosome integrity. The telomerase enzyme contains an integral RNA, providing the template for DNA repeat synthesis. This central telomerase RNA not only provides the template but also contributes to the enzyme's catalytic function and the biogenesis of the ribonucleoprotein. Remarkably, telomerase RNA exhibits significant diversity in sequence, structure, and biogenesis across eukaryotic lineages, a feature that sets it apart from other functional RNAs. In ciliates and plants, telomerase RNA is transcribed by RNA polymerase III, whereas in animals and fungi, it is predominantly transcribed by RNA polymerase II. These differences result in distinct pathways for RNA synthesis, maturation, and trafficking. This work highlights how the diversity in size and structure of telomerase RNAs impacts the complexity and evolution of telomerase ribonucleoproteins, spanning from unicellular eukaryotes to multicellular plants and animals, highlighting telomerase RNA's critical role in telomere biology.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.007
GPT teacher head0.296
Teacher spread0.288 · 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 designObservational
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

Citations3
Published2025
Admission routes1
Has abstractyes

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