New molecular markers for distinguishing the main phylogenetic lineages within <i>Alternaria</i> section <i>Alternaria</i>
Bibliographic record
Abstract
Several members of Alternaria section Alternaria are economically important plant-pathogenic fungi that cause disease on a wide range of host types and plant tissues. The production of Alternaria-derived mycotoxins can lead to significant post-harvest losses due to contamination of agricultural products. Multiple Alternaria species are listed as regulated organisms, which are monitored by international plant protection programmes. These taxa often share high levels of both morphological and phylogenetic similarity, and the establishment of molecular markers that are able to distinguish among them unambiguously has proven to be quite challenging. Previously, we examined fine-scale genome-wide phylogenetic patterns and proposed a list of candidate genes for development into informative markers that are diagnostic for the main section Alternaria lineages. Here, we design primer sets and sequence three new markers (ASA-05, ASA-10, ASA-19) in order to evaluate their diagnostic performance. Sequence data for 49 new independent test taxa were combined with existing data for 38 taxa, and phylogenetic analyses revealed that, in general, the new molecular markers consistently classified section Alternaria strains into one of the main lineages. A discrepancy among the three markers for lineage assignment was observed only for one strain. We also sequenced a commonly used marker in molecular phylogenetics of fungi (rpb2, RNA polymerase II second largest su bunit) and found it was outperformed by all three of the new markers. We suggest that an ASA marker presented here could form the basis of a convenient one-locus test for rapid and routine diagnostic screening of unknown section Alternaria strains.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".