Identification of Putative SDHI Target Site Mutations in the SDHB, SDHC, and SDHD Subunits of the Grape Powdery Mildew Pathogen <i>Erysiphe necator</i>
Bibliographic record
Abstract
Succinate dehydrogenase inhibitors (SDHIs) are fungicides used in control of numerous fungal plant pathogens, including Erysiphe necator, the causal agent of grapevine powdery mildew (GPM). Here, the sdhb, sdhc, and sdhd genes of E. necator were screened for mutations that may be associated with SDHI resistance. GPM samples were collected from 2017 to 2020 from the U.S. states of California, Oregon, Washington, and Michigan, and the Canadian province of British Columbia. Forty-five polymorphisms were identified in the three sdh genes, 17 of which caused missense mutations. Of these, the SDHC-p.I244V substitution was shown in this study to reduce sensitivity of E. necator to boscalid and fluopyram, whereas the SDHC-p.G25R substitution did not affect SDHI sensitivity. Of the other 15 missense mutations, the SDHC-p.H242R substitution was shown in previous studies to reduce sensitivity of E. necator toward boscalid, whereas the equivalents of the SDHB-p.H242L, SDHC-p.A83V, and SDHD-p.I71F substitutions were shown to reduce sensitivity to SDHIs in other fungi. Generally, only a single amino acid substitution was present in the SDHB, SDHC, or SDHD subunit of E. necator isolates, but missense mutations putatively associated with SDHI resistance were widely distributed in the sampled areas and increased in frequency over time. Finally, isolates that had decreased sensitivity to boscalid or fluopyram were identified but with no or only the SDHC-p.G25R amino acid substitution present in SDHB, SDHC, and SDHD subunits. This suggests that target site mutations probably are not the only mechanism conferring resistance to SDHIs in E. necator.
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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".