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Record W6910847265 · doi:10.5061/dryad.8pk0p2ns4

First unravelling of the hidden and intricate evolutionary history of a bacterial group II intron family

2023· dataset· en· W6910847265 on OpenAlexaff

Bibliographic record

VenueOpen MIND · 2023
Typedataset
Languageen
Field
Topic
Canadian institutionsMcGill University
Fundersnot available
KeywordsNucleofectionTubulopathyTSG101Gestational periodCircumstantial evidenceArticular cartilage damage

Abstract

fetched live from OpenAlex

Bacterial group II introns are large RNA enzymes that self-splice from primary transcripts. Following excision, they can invade various DNA target sites using RNA-based mobility pathways. As fast-evolving retromobile elements that move between genetic loci within and across species, their evolutionary history was proved difficult to study and infer. Here we identified several homologs of Ll.LtrB, the model group II intron from Lactococcus lactis, and traced back their evolutionary relationship through phylogenetic analyses. Our data demonstrate that the Ll.LtrB homologs in Lactococci originate from a single and recent lateral transfer event of Ef.PcfG from Enterococcus faecalis. We also show that these introns disseminated in Lactococci following recurrent episodes of independent mobility events in conjunction with occurences of lateral transfer. Our phylogenies identified additional lateral transfer events from the environmental clade of the more diverged Lactococci introns to a series of low GC gram-positive bacterial species including E. faecalis. We also determined that functional intron adaptation occurred early in Lactococci following Ef.PcfG acquisition from E. faecalis and that two of the more diverged Ll.LtrB homologs remain proficient mobile elements despite the significant number of mutations acquired. This study describes the first comprehensive evolutionary history of a bacterial group II intron family.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.013
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.009

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 head0.042
GPT teacher head0.261
Teacher spread0.220 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2023
Admission routes1
Has abstractyes

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