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Record W4413691307 · doi:10.1038/s44319-025-00553-y

RNase III cleavage sites spread across splice junctions enforce sequential snoRNA processing

2025· article· en· W4413691307 on OpenAlexaff
Valérie Migeot, Yves Mary, Étienne Fafard-Couture, Pierre Lombard, François Bachand, Michelle S. Scott, Carlo Yague‐Sanz

Bibliographic record

VenueEMBO Reports · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsUniversité de Sherbrooke
FundersFonds De La Recherche Scientifique - FNRS
KeywordsSmall nucleolar RNABiologyIntronExonPolyadenylationRNA splicingRNase PRNAGeneticsNon-coding RNACell biologyGene

Abstract

fetched live from OpenAlex

Small nucleolar RNAs (snoRNAs) are a class of eukaryotic non-coding RNA molecules whose precursor transcripts are capped and polyadenylated. However, these end modifications are detrimental to snoRNA function and must be removed, a process typically involving excision from introns and/or endonucleolytic cleavage. For RNA precursors that host multiple snoRNAs, the sequence of maturation events is potentially important, but not well understood. Here, we report a new mode of maturation concerning snoRNA pairs that are co-hosted in the intron and the adjacent 3' exon of a precursor transcript. For a snoRNA pair with this arrangement in Schizosaccharomyces pombe, we found that the sequence surrounding an exon-exon junction within their precursor transcript folds into a hairpin after splicing of the intron. This hairpin recruits the RNase III ortholog Pac1, which participates in the maturation of the downstream snoRNA by cleaving the precursor. Our findings suggest that conditional RNase III cleavage signals hidden in an exon-exon junction evolved to enforce sequential snoRNA processing. Sequence analysis suggests that this mechanism is conserved in animals and plants.

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 score0.358
Threshold uncertainty score0.533

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 head0.014
GPT teacher head0.313
Teacher spread0.299 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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