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Record W3008874115 · doi:10.1093/pcp/pcaa022

ARGONAUTE5 Represses Age-Dependent Induction of Flowering through Physical and Functional Interaction with miR156 in Arabidopsis

2020· article· en· W3008874115 on OpenAlexafffund
Charles Roussin‐Léveillée, Guilherme Silva-Martins, Peter Moffett

Bibliographic record

VenuePlant and Cell Physiology · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsArabidopsisMeristemBiologyMutantEffectorCell biologyPsychological repressionTranscription factorPhenotypeGeneTranscription (linguistics)ArgonauteGeneticsBotanyGene expressionRNA interferenceRNA

Abstract

fetched live from OpenAlex

Flowering time is a finely tuned process in plants, in part controlled by the age-regulated microRNA156 (miR156), which functions by suppressing the transcripts of SQUAMOSA-PROMOTER BINDING LIKE (SPL) transcription factors. ARGONAUTE (AGO) proteins are essential effectors of miRNA-mediated gene regulation. However, which AGO(s) mediate(s) the control of flowering time remains unclear. Here, we demonstrate a role of AGO5 in controlling flowering time by modulating the expression of SPL transcription factors. We show that AGO5 interacts physically and functionally with miR156 and that ago5 mutants present an early flowering phenotype in Arabidopsis. Furthermore, in ago5 mutants, the repression of flowering caused by miR156 overexpression is largely reversed, whereas leaf morphology remains unaffected. Our results thus indicate a specific role for AGO5 in mediating miR156 activity in meristematic, but not vegetative, tissue. As such, our data suggest a spatiotemporal regulation of the miR156 aging pathway mediated through different AGO proteins in different tissues.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.657
Threshold uncertainty score0.141

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 head0.033
GPT teacher head0.226
Teacher spread0.193 · 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

Citations48
Published2020
Admission routes2
Has abstractyes

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