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Record W2810893906 · doi:10.1038/s41598-018-28233-z

Moth oviposition shapes the species-specific transcriptional and phytohormonal response of Nicotiana attenuata to larval feeding

2018· article· en· W2810893906 on OpenAlexaboutno aff
Sylvia Drok, Michele Bandoly, Sandra Stelzer, Tobias Lortzing, Anke Steppuhn

Bibliographic record

VenueScientific Reports · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Parasitism and Resistance
Canadian institutionsnot available
FundersDeutsche ForschungsgemeinschaftDeutsche Bundesstiftung Umwelt
KeywordsLarvaNicotianaBiologyBotanySolanaceaeGeneticsGene

Abstract

fetched live from OpenAlex

Oviposition by lepidopteran herbivores on Nicotiana attenuata primes plant defence responses that are induced by the feeding larvae. While oviposition by both the generalist Spodoptera exigua and the specialist Manduca sexta primes the production of defensive phenylpropanoids, their larvae are differentially affected. We investigate here the impact of prior oviposition on the transcriptome and phytohormone levels of plants that were later attacked by larvae to find regulatory signals of this priming. In a full-factorial design, we evaluated the effects of oviposition and herbivory by both species. Oviposition alone had only subtle effects at the transcriptional level. Laval feeding alone induced species-specific plant responses. Larvae of the generalist regulated phytohormones and gene expression stronger than larvae of the specialist. A day after larvae started to feed, we detected no significant alterations of the plant's response to larval feeding due to prior oviposition by conspecific moths. Yet, oviposition by each of the species profoundly influenced the plant's transcriptional and phytohormonal response to feeding larvae of the other species. Remarkably, the species-specific plant responses to larval feeding shifted towards the response normally elicited by larvae of the ovipositing species. Thus, plants may already recognise an insect's identity upon its oviposition.

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)0.001
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 score0.953
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.023
GPT teacher head0.220
Teacher spread0.197 · 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

Citations14
Published2018
Admission routes1
Has abstractyes

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