Comparative proteomic analysis of the moderately resistant and susceptible peanut cultivars during infestation by <i>Cylindrocladium parasiticum</i>
Bibliographic record
Abstract
Cylindrocladium parasiticum Crous, Wingfield & Alfenas, the causal agent of Cylindrocladium black rot of peanut, has led to economic losses in China. However, the response of peanut plant to C. parasiticum is poorly understood. Here, two contrasting peanut cultivars, T09 (C. parasiticum-moderately resistant) and P562 (C. parasiticum-susceptible) were used for comparative analysis of protein profiles in root segment of plant tissues in responses to C. parasiticum infection. Proteomic profiling identified 1647 and 391 differentially accumulated proteins (DAPs) in P562 and T09 relative to uninoculated control, respectively. A total of 350 and 1095 DAPs were identified between P562 and T09 after 9 day(s) post infection (dpi), respectively. Functional categorization showed that C. parasiticum-responsive proteins were mainly involved in catalytic activity and binding functions. KEGG pathway analysis indicated both moderately resistant and susceptible peanut cultivars can regulate gene expression in the phenylpropanoid pathway, terpenoid backbone biosynthesis, SA, and JA pathways to induce defensive genes and protein expression which enhances plant defence or susceptibility capacity. However, MAPK signal pathway was more pronounced in moderately resistant peanut cultivar T09. We also observed an increase of CYP73A100 involved in phenylpropanoid and flavonoid biosynthesis pathways in susceptible peanut ecotype P562, while decrease in moderately resistant interaction. Additionally, there was a marked activation of brassinosteroid biosynthesis in T09, which indicated a possible involvement of activation of plant immune response in moderately resistant responses of peanut to C. parasiticum. This study provides some insights into molecular networks involved in cellular and physiological responses to C. parasiticum in peanut.
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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".