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Record W2601004377 · doi:10.1093/jxb/erx078

Translatome analysis of an NB-LRR immune response identifies important contributors to plant immunity in Arabidopsis

2017· article· en· W2601004377 on OpenAlexaff
Louis‐Valentin Méteignier, Mohamed El Oirdi, Mathias Cohen, Teura Barff, Dominick Matteau, Jean‐François Lucier, Sébastien Rodrigue, Pierre‐Étienne Jacques, Keiko Yoshioka, Peter Moffett

Bibliographic record

VenueJournal of Experimental Botany · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant-Microbe Interactions and Immunity
Canadian institutionsUniversity of TorontoCentre Hospitalier Universitaire de SherbrookeUniversité de Sherbrooke
FundersNational Science Council
KeywordsArabidopsisBiologyInnate immune systemPlant ImmunityImmunityTranslation (biology)GeneArabidopsis thalianaCell biologyLeucine-rich repeatTranslational regulationGeneticsImmune systemMutantMessenger RNA

Abstract

fetched live from OpenAlex

An important branch of plant immunity involves the recognition of pathogens by nucleotide-binding, leucine-rich repeat (NB-LRR) proteins. However, signaling events downstream of NB-LRR activation are poorly understood. We have analysed the Arabidopsis translatome using ribosome affinity purification and RNA sequencing. Our results show that the translational status of hundreds of transcripts is differentially affected upon activation of the NB-LRR protein RPM1, showing an overall pattern of a switch away from growth-related activities to defense. Among these is the central translational regulator and growth promoter, Target of Rapamycin (TOR) kinase. Suppression of TOR expression leads to increased resistance to pathogens while overexpression of TOR results in increased susceptibility, indicating an important role for translational control in the switch from growth to defense. Furthermore, we show that several additional genes whose mRNAs are translationally regulated, including BIG, CCT2, and CIPK5, are required for both NB-LRR-mediated and basal plant innate immunity, identifying novel actors in plant defense.

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 score0.547
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.022
GPT teacher head0.290
Teacher spread0.268 · 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

Citations119
Published2017
Admission routes1
Has abstractyes

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