Development and characterization of microsatellite markers of the fungal plant pathogen <i>Sclerotinia trifoliorum</i>
Bibliographic record
Abstract
Sclerotinia trifoliorum is an important pathogen of forage legumes and some grain legumes. Attempts to study its population biology using microsatellite markers developed for Sclerotinia sclerotiorum and Sclerotinia subarctica resulted in no amplification or low levels of polymorphism. This study reports the development and characterization of 33 microsatellite loci developed from a microsatellite-enriched library of S. trifoliorum. Based on a population of 42 isolates of S. trifoliorum, these microsatellite markers are highly polymorphic, with a mean of 6.5 alleles per locus (range 3-12) and a mean expected heterozygosity of 0.63 (range 0.26-0.9). Based on locations of these marker sequences in the S. sclerotiorum genome, these microsatellite loci are dispersed throughout the genome. However, 50% (265 of 528) of pairwise comparisons of the 33 microsatellite loci had significant linkage disequilibrium, which could be explained by the mixed mating systems (homothallism and heterothallism) and clonal reproduction of S. trifoliorum. Thirty of the 33 loci were successfully applied to S. sclerotiorum, and 28 loci were polymorphic. However, only 10 loci are applicable to Sclerotinia minor and 1 locus to Sclerotinia homoeocarpa. These markers are therefore useful for population structure assessment, QTL mapping, and ecological analyses in S. trifoliorum and potentially in other Sclerotinia species.
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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 | 0.000 | 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) | 0.000 | 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 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".