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Record W2311871742 · doi:10.1186/s12870-016-0760-1

Transcriptome and metabolite profiling reveals that prolonged drought modulates the phenylpropanoid and terpenoid pathway in white grapes (Vitis vinifera L.)

2016· article· en· W2311871742 on OpenAlexafffund
Stefania Savoi, Darren C. J. Wong, Panagiotis Arapitsas, Mara Miculan, Barbara Bucchetti, E. Peterlunger, Aaron Fait, Fulvio Mattivi, Simone D. Castellarin

Bibliographic record

VenueBMC Plant Biology · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHorticultural and Viticultural Research
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaFondazione Edmund Mach
KeywordsPhenylpropanoidBiologyRipeningVeraisonSecondary metabolismAnthocyaninFlavonoid biosynthesisFlavonoidBotanyPrimary metaboliteTranscriptomeWineSecondary metaboliteCarotenoidWine grapeMetabolismGeneGene expressionFood scienceBiochemistryCultivarBiosynthesis

Abstract

fetched live from OpenAlex

BACKGROUND: Secondary metabolism contributes to the adaptation of a plant to its environment. In wine grapes, fruit secondary metabolism largely determines wine quality. Climate change is predicted to exacerbate drought events in several viticultural areas, potentially affecting the wine quality. In red grapes, water deficit modulates flavonoid accumulation, leading to major quantitative and compositional changes in the profile of the anthocyanin pigments; in white grapes, the effect of water deficit on secondary metabolism is still largely unknown. RESULTS: In this study we investigated the impact of water deficit on the secondary metabolism of white grapes using a large scale metabolite and transcript profiling approach in a season characterized by prolonged drought. Irrigated grapevines were compared to non-irrigated grapevines that suffered from water deficit from early stages of berry development to harvest. A large effect of water deficit on fruit secondary metabolism was observed. Increased concentrations of phenylpropanoids, monoterpenes, and tocopherols were detected, while carotenoid and flavonoid accumulations were differentially modulated by water deficit according to the berry developmental stage. The RNA-sequencing analysis carried out on berries collected at three developmental stages-before, at the onset, and at late ripening-indicated that water deficit affected the expression of 4,889 genes. The Gene Ontology category secondary metabolic process was overrepresented within up-regulated genes at all the stages of fruit development considered, and within down-regulated genes before ripening. Eighteen phenylpropanoid, 16 flavonoid, 9 carotenoid, and 16 terpenoid structural genes were modulated by water deficit, indicating the transcriptional regulation of these metabolic pathways in fruit exposed to water deficit. An integrated network and promoter analyses identified a transcriptional regulatory module that encompasses terpenoid genes, transcription factors, and enriched drought-responsive elements in the promoter regions of those genes as part of the grapes response to drought. CONCLUSION: Our study reveals that grapevine berries respond to drought by modulating several secondary metabolic pathways, and particularly, by stimulating the production of phenylpropanoids, the carotenoid zeaxanthin, and of volatile organic compounds such as monoterpenes, with potential effects on grape and wine antioxidant potential, composition, and sensory features.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.036
GPT teacher head0.242
Teacher spread0.206 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations351
Published2016
Admission routes2
Has abstractyes

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