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Record W2104174145 · doi:10.1091/mbc.e07-12-1254

Deletion of Many Yeast Introns Reveals a Minority of Genes that Require Splicing for Function

2008· article· en· W2104174145 on OpenAlexaff
Julie Parenteau, Mathieu Durand, Steeve Véronneau, Andrée-Anne Lacombe, Geneviève Morin, Valérie Guérin, Bojana Cecez, Julien Gervais-Bird, ChuShin Koh, David Brunelle, Raymund J. Wellinger, Benoı̂t Chabot, Sherif Abou Elela

Bibliographic record

VenueMolecular Biology of the Cell · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsIntronBiologyRNA splicingGeneGeneticsGroup II intronMinor spliceosomeSaccharomyces cerevisiaeGroup I catalytic intronRNA

Abstract

fetched live from OpenAlex

Splicing regulates gene expression and contributes to proteomic diversity in higher eukaryotes. However, in yeast only 283 of the 6000 genes contain introns and their impact on cell function is not clear. To assess the contribution of introns to cell function, we initiated large-scale intron deletions in yeast with the ultimate goal of creating an intron-free model eukaryote. We show that about one-third of yeast introns are not essential for growth. Only three intron deletions caused severe growth defects, but normal growth was restored in all cases by expressing the intronless mRNA from a heterologous promoter. Twenty percent of the intron deletions caused minor phenotypes under different growth conditions. Strikingly, the combined deletion of all introns from the 15 cytoskeleton-related genes did not affect growth or strain fitness. Together, our results show that although the presence of introns may optimize gene expression and provide benefit under stress, a majority of introns could be removed with minor consequences on growth under laboratory conditions, supporting the view that many introns could be phased out of Saccharomyces cerevisiae without blocking cell growth.

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 score0.027
Threshold uncertainty score0.313

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 head0.017
GPT teacher head0.261
Teacher spread0.243 · 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

Citations130
Published2008
Admission routes1
Has abstractyes

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