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Record W2136521020 · doi:10.1093/nar/gkp994

Extensive mis-splicing of a bi-partite plant mitochondrial group II intron

2009· article· en· W2136521020 on OpenAlexafffund
Helen Elina, Gregory G. Brown

Bibliographic record

VenueNucleic Acids Research · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les TechnologiesUniversity of Ottawa
KeywordsIntronExonBiologyRNA splicingGroup II intronGeneticsExon trappingMinigeneGeneTrans-splicingExon shufflingAlternative splicingRNA

Abstract

fetched live from OpenAlex

Expression of the seed plant mitochondrial nad5 gene involves two trans-splicing events that remove fragmented group II introns and join the small, central exon c to exons b and d. We show that in both monocot and eudicot plants, extensive mis-splicing of the bi-partite intron 2 takes place, resulting in the formation of aberrantly spliced products in which exon c is joined to various sites within exon b. These mis-spliced products accumulate to levels comparable to or greater than that of the correctly spliced mRNA. We suggest that mis-splicing may result from folding constraints imposed on intron 2 by base-pairing between exon a and a portion of the bi-partite intron 3 downstream of exon c. Consistent with this hypothesis, we find that mis-splicing does not occur in Oenothera mitochondria, where intron 3 is further fragmented such that the predicted base-pairing region is not covalently linked to exon c. Our findings suggest that intron fragmentation may lead to mis-splicing, which may be corrected by further intron fragmentation.

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)0.000
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 score0.000
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.028
GPT teacher head0.307
Teacher spread0.280 · 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

Citations19
Published2009
Admission routes2
Has abstractyes

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