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Record W2801959553 · doi:10.3389/fpls.2018.00589

Integration of the Pokeweed miRNA and mRNA Transcriptomes Reveals Targeting of Jasmonic Acid-Responsive Genes

2018· article· en· W2801959553 on OpenAlexafffund
Kira C. M. Neller, Alexander Klenov, Juan Carlos Torres Guzmán, Katalin A. Hudak

Bibliographic record

VenueFrontiers in Plant Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of CanadaSunnybrook Research Institute
KeywordsBiologyTranscriptomeJasmonic acidmicroRNAGeneGene expressionGeneticsSmall RNAPlant hormoneRegulation of gene expression

Abstract

fetched live from OpenAlex

The American pokeweed plant, Phytolacca americana, displays broad-spectrum resistance to plant viruses and is a heavy metal hyperaccumulator. However, little is known about the regulation of biotic and abiotic stress responses in this non-model plant. To investigate the control of miRNAs in gene expression, we sequenced the small RNA transcriptome of pokeweed treated with jasmonic acid (JA), a hormone that mediates pathogen defense and stress tolerance. We predicted 145 miRNAs responsive to JA, most of which were unique to pokeweed. These miRNAs were low in abundance and condition-specific, with discrete expression change. Integration of paired mRNA-Seq expression data enabled us to identify correlated, novel JA-responsive targets that mediate hormone biosynthesis, signal transduction, and pathogen defense. The expression of approximately half the pairs was positively correlated, an uncommon finding that we functionally validated by mRNA cleavage. Importantly, we report that a pokeweed specific miRNA targets the transcript of OPR3, novel evidence that a miRNA regulates a JA biosynthesis enzyme. This first large-scale small RNA study of a Phytolaccaceae family member shows that miRNA-mediated control is a significant component of the JA response, associated with widespread changes in expression of genes required for stress adaptation.

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 score0.315
Threshold uncertainty score0.170

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 head0.010
GPT teacher head0.213
Teacher spread0.203 · 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

Citations18
Published2018
Admission routes2
Has abstractyes

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