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Record W2096257780 · doi:10.1093/nar/gks748

The slicing activity of miRNA-specific Argonautes is essential for the miRNA pathway in C. elegans

2012· article· en· W2096257780 on OpenAlexafffund
Samir Bouasker, Martin J. Simard

Bibliographic record

VenueNucleic Acids Research · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsUniversité LavalHôtel-Dieu de Québec
FundersCanadian Institutes of Health ResearchCancer Research Society
KeywordsArgonauteBiologyDicermicroRNAGene silencingCaenorhabditis elegansRibonuclease IIIRNACell biologyComputational biologySmall interfering RNAGeneticsRNA interferenceGene

Abstract

fetched live from OpenAlex

Among the set of Argonautes proteins encoded by metazoan genomes, some have conserved amino acids important for catalytic or slicing activity. The functional significance of these residues in microRNA (miRNA)-specific Argonautes in animals is still unclear since miRNAs do not induce site-specific cleavage of targeted messenger RNAs (mRNAs), unlike small interfering RNAs (siRNAs). Here, we report that miRNA-specific ALG-1 and ALG-2 Argonautes from Caenorhabditis elegans possess the slicing activity normally implicated in the siRNA-silencing pathway. We also find that ALG-1/2 can bind and use a Dicer-processed miRNA duplex to target mRNAs, suggesting an ability to displace RNA strands. Importantly, the slicing activity of ALG-1 or ALG-2 is essential for the miRNA pathway in vivo, as shown by the accumulation of truncated miRNA precursors and altered miRNA-induced silencing complex (miRISC) formation. Taken together, our data demonstrate that the slicing activity of Argonautes contributes to a new and unexpected step in the canonical miRNA pathway that occurs prior to miRISC loading in animals.

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)0.003
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 score0.137
Threshold uncertainty score0.410

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.044
GPT teacher head0.348
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 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

Citations47
Published2012
Admission routes2
Has abstractyes

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