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Record W4283010631 · doi:10.3389/fpls.2022.928729

The Mobile Small RNAs: Important Messengers for Long-Distance Communication in Plants

2022· review· en· W4283010631 on OpenAlexafffund
Yan Yan, Byung‐Kook Ham

Bibliographic record

VenueFrontiers in Plant Science · 2022
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsGlobal Institute for Water SecurityUniversity of Saskatchewan
FundersNational Science Foundation of Sri LankaNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsPlasmodesmaBiologyRNA interferenceEffectorCell biologySmall interfering RNASmall RNAmicroRNARNA silencingGene silencingRasiRNARNAComputational biologyGeneGeneticsCytoplasm

Abstract

fetched live from OpenAlex

Various species of small RNAs (sRNAs), notably microRNAs and small interfering RNAs (siRNAs), have been characterized as the major effectors of RNA interference in plants. Growing evidence supports a model in which sRNAs move, intercellularly, systemically, and between cross-species. These non-coding sRNAs can traffic cell-to-cell through plasmodesmata (PD), in a symplasmic manner, as well as from source to sink tissues, via the phloem, to trigger gene silencing in their target cells. Such mobile sRNAs function in non-cell-autonomous communication pathways, to regulate various biological processes, such as plant development, reproduction, and plant defense. In this review, we summarize recent progress supporting the roles of mobile sRNA in plants, and discuss mechanisms of sRNA transport, signal amplification, and the plant’s response, in terms of RNAi activity, within the recipient tissues. We also discuss potential research directions and their likely impact on engineering of crops with traits for achieving food security.

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)0.004
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.613

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0030.000
Research integrity0.0000.001
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 head0.050
GPT teacher head0.301
Teacher spread0.252 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations33
Published2022
Admission routes2
Has abstractyes

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