Revealing gene–metabolite interactions in wheat defenses against <i>Pyrenophora tritici-repentis</i> in resistant and susceptible genotypes
Bibliographic record
Abstract
Wheat defenses against Pyrenophora tritici-repentis ( Ptr), the cause of tan spot disease, are complex and require further characterization. We previously identified two wheat genotypes, Robigus (resistant) and Hereward (susceptible), and characterized their differentially expressed genes (DEGs) and accumulated metabolites (DAMs) following challenge with Ptr. In this study we uncover coordinated shifts in gene expression and metabolism triggered by Ptr. The DEGs and DAMs from each genotype were integrated using regularized canonical correlation analysis, yielding scale-free networks with 69 745 edges in Robigus and 760 433 in Hereward. In Robigus, hub genes were upregulated at 48 and 96 h post-inoculation and included hst2 (encoding hydroxycinnamoyl-CoA:shikimate hydroxycinnamoyl transferase 2), located within a QTL for Ptr resistance (QTs.fcu-5D locus), a receptor-like kinase, and a late embryogenesis abundant protein (which play roles in cell wall organization). Pathway enrichment showed significant involvement of catalytic activity, chitinase activity, and cell wall metabolic processes. In contrast, Hereward hub genes were mostly downregulated, except for a hexosyltransferase, with enriched pathways related to energy metabolism, such as ATP binding and phosphorylation. These results suggest that cell wall modifications and chitinase activity are part of an effective defense response against Ptr, whereas costly energetic processes may contribute to tan spot susceptibility.
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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".