Pathogen and Pest Responses Are Altered Due to RNAi-Mediated Knockdown of <i>GLYCOALKALOID METABOLISM 4</i> in <i>Solanum tuberosum</i>
Bibliographic record
Abstract
Steroidal glycoalkaloids (SGAs) are major secondary metabolites constitutively produced in cultivated potato Solanum tuberosum, and α-solanine and α-chaconine are the most abundant SGAs. SGAs are toxic to humans at high levels but their role in plant protection against pests and pathogens is yet to be established. In this study, levels of SGAs in potato were reduced by RNA interference (RNAi)-mediated silencing of GLYCOALKALOID METABOLISM 4 (GAME4)-a gene encoding cytochrome P450, involved in an oxidation step in the conversion of cholesterol to SGA aglycones. Two GAME4 RNAi lines, T8 and T9, were used to investigate the effects of manipulation of the SGA biosynthetic pathway in potato. Growth and development of an insect pest, Colorado potato beetle (CPB), were affected in these lines. While no effect on CPB leaf consumption or weight gain was observed, early instar larval death and accelerated development of the insect was found while feeding on leaves of GAME4 RNAi lines. Modulation of SGA biosynthetic pathway in GAME4 RNAi plants was associated with a larger alteration to the metabolite profile, including increased levels of one or both the steroidal saponins or phytoecdysteroids, which could affect insect mortality as well as development time. Colonization by Verticillium dahliae on GAME4 RNAi plants was also tested. There were increased pathogen levels in the T8 GAME4 RNAi line but not in the T9. Metabolite differences between T8 and T9 were found and may have contributed to differences in V. dahliae infection. Drought responses created by osmotic stress were not affected by modulation of SGA biosynthetic pathway in potato.
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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 | 0.001 |
| 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 | 0.001 | 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".