Overexpression of AtGolS3 and CsRFS in poplar enhances ROS tolerance and represses defense response to leaf rust disease
Bibliographic record
Abstract
Plants respond to pathogens through an orchestration of signaling events that coordinate modifications to transcriptional profiles and physiological processes. Resistance to necrotrophic pathogens often requires jasmonic acid, which antagonizes the salicylic acid dependent biotrophic defense response. Recently, myo-inositol has been shown to negatively impact salicylic acid (SA) levels and signaling, while galactinol enhances jasmonic acid (JA)-dependent induced systemic resistance to necrotrophic pathogens. To investigate the function of these compounds in biotrophic pathogen defense, we characterized the defense response of Populus alba × grandidentata overexpressing Arabidopsis GALACTINOL SYNTHASE3 (AtGolS) and Cucumber sativus RAFFINOSE SYNTHASE (CsRFS) challenged with Melampsora aecidiodes, a causative agent of poplar leaf rust disease. Relative to wild-type leaves, the overexpression of AtGolS3 and CsRFS increased accumulation of galactinol and raffinose and led to increased leaf rust infection. During the resistance response, inoculated wild-type leaves displayed reduced levels of galactinol and repressed transcript abundance of two endogenous GolS genes compared to un-inoculated wild-type leaves prior to the up-regulation of NON-EXPRESSOR OF PR1 and PATHOGENESIS-RELATED1. Transcriptome analysis and qRT-PCR validation also revealed the repression of genes participating in calcium influx, phosphatidic acid biosynthesis and signaling, and salicylic acid signaling in the transgenic lines. In contrast, enhanced tolerance to H2O2 and up-regulation of antioxidant biosynthesis genes were exhibited in the overexpression lines. Thus, we conclude that overexpression of AtGolS and CsRFS antagonizes the defense response to poplar leaf rust disease through repressing reactive oxygen species and attenuating calcium and phosphatidic acid signaling events that lead to SA defense.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".