The Tryptophan decarboxylase 1 Gene From Aegilops variabilis No.1 Regulate the Resistance Against Cereal Cyst Nematode by Altering the Downstream Secondary Metabolite Contents Rather Than Auxin Synthesis
Bibliographic record
Abstract
Cereal cyst nematode (CCN, Heterodera avenae) is a most important pathogen of wheat and causes tremendous yield loss annually over the world. Since the lack of resistance materials among wheat cultivars, identification and characterization of the resistance-related genes from the relatives of wheat is a necessary and efficient way. As a close relative of wheat with high resistance against CCN, Aegilops variabilis No.1 is believed to be a valuable source for wheat breeding against this devastating disease. However so far, very few resistance-associated genes have been characterized from this species. In this study, we present that the tryptophan decarboxylase genes from Ae.variabilis No.1 (AeVTDC1 and AeVTDC2) were both induced by CCN juveniles at the early stage of resistance response (30 hours post inoculation), with AeVTDC1 more sensitive to CCN infection than AeVTDC2. Silencing of AeVTDC1 led to compromised immunity to CCN with more CCN intrusion into roots; while overexpression AeVTDC1 in Nicotiana tobaccum dramatically enhanced the resistance of plants by reducing the knots formed on roots. Metabolism analysis showed that the contents of secondary metabolites with activity of resistance to varied pathogens correlated with the expression level of AeVTDC1 in both Ae.variabilis No.1 and the transgenic tobacco plants. In addition, the content of IAA was not affected by either silencing or overexpressing of AeVTDC1. Hence, our research provided AeVTDC1 a valuable target that mediates resistance to CCN and root knot nematode (RKN, Meloidogyne naasi) without influencing the auxin biosynthesis.
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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".