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Record W2001869111 · doi:10.1074/jbc.c500328200

An Intron-encoded Protein Assists RNA Splicing of Multiple Similar Introns of Different Bacterial Genes

2005· article· en· W2001869111 on OpenAlexaff
Meng Qing, Yanfei Wang, Xiang‐Qin Liu

Bibliographic record

VenueJournal of Biological Chemistry · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsDalhousie University
Fundersnot available
KeywordsIntronGroup II intronRNA splicingBiologyGroup I catalytic intronGeneGeneticsMinor spliceosomeExonSplicing factorExonic splicing enhancerRNA

Abstract

fetched live from OpenAlex

Four group II introns were found in an unusually intron-rich dnaN gene (encoding the beta subunit of DNA polymerase III) of the cyanobacterium Trichodesmium erythraeum, and they have strong similarities to two introns of the RIR gene (encoding ribonucleotide reductase) of the same organism. Of these six introns, only the RIR-3 intron encodes a maturase protein and showed efficient RNA splicing when expressed in Escherichia coli cells. The other five introns do not encode a maturase protein and did not show RNA splicing in E. coli. But these maturase-less introns showed efficient RNA splicing when the RIR-3 intron-encoded maturase protein was co-expressed from a freestanding gene in the same cell. These findings demonstrated that an intron-encoded protein could function as a general maturase for multiple introns of different genes. Major implications may include an intron-mediated co-regulation of the different genes and a resemblance of the evolutionary origin of spliceosomal introns.

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 score0.001
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)0.0010.001

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 head0.016
GPT teacher head0.246
Teacher spread0.231 · 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

Citations33
Published2005
Admission routes1
Has abstractyes

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