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Negative regulation of defense responses in Arabidopsis by two <i>NPR1</i> paralogs

2006· article· en· W2126302335 on OpenAlexaff
Yuelin Zhang, Yu Cheng, Na Qu, Qingguo Zhao, Dong-Lin Bi, Xin Li

Bibliographic record

VenueThe Plant Journal · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant-Microbe Interactions and Immunity
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
Fundersnot available
KeywordsArabidopsisEctopic expressionMutantNPR1OomyceteBiologyComplementationSalicylic acidSystemic acquired resistanceCell biologyGeneMicrobiologyGeneticsMedicine

Abstract

fetched live from OpenAlex

NPR1 is required for systemic acquired resistance, and there are five NPR1 paralogs in Arabidopsis. Here we report knockout analysis of two of these, NPR3 and NPR4. npr3 single mutants have elevated basal PR-1 expression and the npr3 npr4 double mutant shows even higher expression. The double mutant plants also display enhanced resistance against virulent bacterial and oomycete pathogens. This enhanced disease resistance is partially dependent on NPR1, can be in part complemented by either wild-type NPR3 or NPR4, and is not associated with an elevated level of salicylic acid. NPR3 and NPR4 interact with TGA2, TGA3, TGA5 and TGA6 in yeast two-hybrid assays. Using bimolecular fluorescence complementation analysis, we show that NPR3 interacts with TGA2 in the nucleus of onion epidermal cells and Arabidopsis mesophyll protoplasts. Combined with our previous finding that basal PR-1 levels are also elevated in the tga2 tga5 tga6 triple mutant, we propose that NPR3 and NPR4 negatively regulate PR gene expression and pathogen resistance through their association with TGA2 and its paralogs.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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)0.0010.001

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 head0.021
GPT teacher head0.226
Teacher spread0.205 · 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 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

Citations283
Published2006
Admission routes1
Has abstractyes

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