Arabidopsis Transcriptomics Reveals the Role of Lipoxygenase2 (AtLOX2) in Wound-Induced Responses
Bibliographic record
Abstract
In wounded Arabidopsis thaliana leaves, four 13S-lipoxygenases (AtLOX2, AtLOX3, AtLOX4, AtLOX6) act in a hierarchical manner to contribute to the jasmonate burst. This leads to defense responses with LOX2 playing an important role in plant resistance against caterpillar herb-ivory. In this study, we sought to characterize the impact of AtLOX2 on wound-induced phytohormonal and transcriptional responses to foliar mechanical damage using wildtype (WT) and lox2 mutant plants. Compared with WT, the lox2 mutant had higher constitutive levels of the phytohormone salicylic acid (SA) and enhanced expression of SA-responsive genes. This suggests that AtLOX2 may be involved in the biosynthesis of jasmonates that are involved in the antagonism of SA biosynthesis. As expected, the jasmonate burst in response to wounding was dampened in lox2 plants. Generally, 1 h after wounding, genes linked to jasmonate biosynthesis, jasmonate signaling attenuation and abscisic acid-responsive genes, which are primarily involved in wound sealing and healing, were differentially regulated between WT and lox2 mutants. Twelve h after wounding, WT plants showed stronger expression of genes associated with plant protection against insect herbivory. This study highlights the dynamic nature of jasmonate-responsive gene expression and the contribution of AtLOX2 to this pathway and plant resistance against insects.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".