MétaCan
Menu
Back to cohort
Record W2044673786 · doi:10.1093/nar/28.6.1489

Species-specific regulation of alternative splicing in the C-terminal region of the p53 tumor suppressor gene

2000· article· en· W2044673786 on OpenAlexaff
Michél Laverdière

Bibliographic record

VenueNucleic Acids Research · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsBiologyAlternative splicingRNA splicingIntronMinigeneGenesplicePrecursor mRNAMolecular biologyTransfectionGeneticsCell cultureCell biologyExonRNA

Abstract

fetched live from OpenAlex

Alternative splicing occurs in the C-terminal region of the p53 tumor suppressor gene between two alternative 3' splice sites in intron 10. This alternative splicing event has been detected in murine cells, but not in rat or human tissues. In this paper, we have characterized the pattern of p53 alternative splicing in cell lines from five different species. Our results confirm that p53 alternative splicing is species-specific, being detected only in cell lines of rodent origin. Using transient transfection assays, we have established that the rat p53 gene undergoes efficient alternative splicing in both mouse and rat cell lines, thus demonstrating that it has all the necessary cis -acting sequences to be alternatively spliced. In contrast, we were unable to detect any usage of the human alternative 3' splice site under the same experimental conditions. Thus, the low levels or absence of alternatively spliced p53 mRNA in rat and human cell lines seems to be the result of different mechanisms. Our results support the hypothesis that there are species-specific mechanisms implicated in the regulation of p53 activity.

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 score0.003

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)0.0010.000

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 head0.045
GPT teacher head0.320
Teacher spread0.276 · 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

Citations25
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueNucleic Acids ResearchSame topicRNA Research and SplicingFrench-language works237,207