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Record W2126075909 · doi:10.3389/fgene.2012.00099

Modulation of microRNA Activity by Semi-microRNAs

2012· article· en· W2126075909 on OpenAlexafffund
Isabelle Plante, Hélène Plé, Patricia Landry, Preethi H. Gunaratne, Patrick Provost

Bibliographic record

VenueFrontiers in Genetics · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsUniversité LavalCentre hospitalier universitaire de Québec
FundersCanadian Institutes of Health ResearchCanadian Blood Services
KeywordsDicermicroRNAArgonauteBiologyDroshaGene silencingEffectorRNAMessenger RNARibonuclease IIISmall RNACell biologyTranslation (biology)RNA interferenceTrans-acting siRNAGene expressionRNA silencingRegulation of gene expressionRibonucleaseGeneGeneticsNon-coding RNA

Abstract

fetched live from OpenAlex

The ribonuclease Dicer plays a central role in the microRNA pathway by catalyzing the formation of 19-24-nucleotide (nt) long microRNAs. Subsequently incorporated into Argonaute 2 (Ago2) effector complexes, microRNAs are known to regulate messenger RNA (mRNA) translation. Whether shorter RNA species derived from microRNAs exist and play a role in mRNA regulation remains unknown. Here, we report the serendipitous discovery of a 12-nt long RNA species corresponding to the 5' region of the microRNA let-7, and tentatively termed semi-microRNA, or smiRNA. Using a smiRNA derived from the precursor of miR-223 as a model, we show that 12-nt long smiRNA species are devoid of any direct mRNA regulatory activity, as assessed in a reporter gene activity assay in transfected cultured human cells. However, smiR-223 was found to modulate the ability of the microRNA from which it derives to mediate translational repression or cleavage of reporter mRNAs. Our findings suggest that the 12-nt RNA species, generated along the microRNA pathway, may participate to the control of gene expression by regulating the activity of the related full-length mature microRNA in vivo.

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 score0.033
Threshold uncertainty score0.634

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 head0.007
GPT teacher head0.229
Teacher spread0.223 · 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

Citations19
Published2012
Admission routes2
Has abstractyes

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