Monolignol biosynthesis is associated with resistance to <i>Sclerotinia sclerotiorum</i> in <i>Camelina sativa</i>
Bibliographic record
Abstract
The ascomycete Sclerotinia sclerotiorum is a necrotrophic plant pathogen with an extremely broad host range. It causes stem rot in Camelina sativa, a crucifer with great potential as an alternative oilseed crop. Lignification is a common phenomenon in the expression of resistance against necrotrophs, but the molecular mechanisms underlying this defence response are poorly understood. We present histochemical, gene expression and biochemical data investigating the role of monolignols in the resistance of C. sativa to S. sclerotiorum. Comparative studies with resistant and susceptible lines of C. sativa revealed substantial differences in constitutive transcript levels and gene regulation patterns for members of the gene family encoding cinnamoyl-CoA reductase (CCR), the first enzyme specifically committed to the synthesis of lignin monomers. These differences were associated with anatomical and metabolic factors. While the induction of CsCCR2 expression after inoculation with S. sclerotiorum was associated with the deposition of lignin mainly derived from guaiacyl monomers, high constitutive levels of CsCCR4 paralleled a high syringyl lignin content in healthy stems of resistant plants. The results provide evidence that plant cell wall strengthening plays a role in the resistance of C. sativa to S. sclerotiorum, and that both constitutive and inducible defence mechanisms contribute to reduced symptom development in resistant germplasm. This study provides the first characterization of quantitative resistance in C. sativa to S. sclerotiorum.
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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 | 0.001 | 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".