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Record W2053183062 · doi:10.1101/gr.5703406

Characterization of intron loss events in mammals

2006· article· en· W2053183062 on OpenAlexafffund
Jasmin Coulombe‐Huntington, Jacek Majewski

Bibliographic record

VenueGenome Research · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsMcGill University
FundersCanada Research Chairs
KeywordsIntronBiologyGeneGeneticsGenomeExonLineage (genetic)Evolutionary biology

Abstract

fetched live from OpenAlex

The exon/intron structure of eukaryotic genes differs extensively across species, but the mechanisms and relative rates of intron loss and gain are still poorly understood. Here, we used whole-genome sequence alignments of human, mouse, rat, and dog to perform a genome-wide analysis of intron loss and gain events in >17,000 mammalian genes. We found no evidence for intron gain and 122 cases of intron loss, most of which occurred within the rodent lineage. The majority (68%) of the deleted introns were extremely small (<150 bp), significantly smaller than average. The intron losses occurred almost exclusively within highly expressed, housekeeping genes, supporting the hypothesis that intron loss is mediated via germline recombination of genomic DNA with intronless cDNA. This study constitutes the largest scale analysis for intron dynamics in vertebrates to date and allows us to confirm and extend several hypotheses previously based on much smaller samples. Our results in mammals show that intron gain has not been a factor in the evolution of gene structure during the past 95 Myr and has likely been restricted to more ancient history.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.325
Teacher spread0.304 · 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
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

Citations153
Published2006
Admission routes2
Has abstractyes

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