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Record W2156016589 · doi:10.1093/nar/gkr759

Regulation of conditional gene expression by coupled transcription repression and RNA degradation

2011· article· en· W2156016589 on OpenAlexafffund
Mathieu Lavoie, Dongling Ge, Sherif Abou Elela

Bibliographic record

VenueNucleic Acids Research · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsBiologyTranscription (linguistics)Gene expressionRNARNA silencingRNA-induced transcriptional silencingMolecular biologyPsychological repressionRegulation of gene expressionGeneTranscriptional regulationRibonucleaseRNA polymerase IICell biologyPromoterNon-coding RNARNA interferenceGenetics

Abstract

fetched live from OpenAlex

Gene expression is determined by a combination of transcriptional and post-transcriptional regulatory events that were thought to occur independently. This report demonstrates that the genes associated with the Snf3p-Rgt2p glucose-sensing pathway are regulated by interconnected transcription repression and RNA degradation. Deletion of the dsRNA-specific ribonuclease III Rnt1p increased the expression of Snf3p-Rgt2p-associated transcription factors in vivo and the recombinant enzyme degraded their messenger RNA in vitro. Surprisingly, Rnt1ps effect on gene expression in vivo was both RNA and promoter dependent, thus linking RNA degradation to transcription. Strikingly, deletion of RNT1-induced promoter-specific transcription of the glucose sensing genes even in the absence of RNA cleavage signals. Together, the results presented here support a model in which co-transcriptional RNA degradation increases the efficiency of gene repression, thereby allowing an effective cellular response to the continuous changes in nutrient concentrations.

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.046
GPT teacher head0.317
Teacher spread0.271 · 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

Citations11
Published2011
Admission routes2
Has abstractyes

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