Genetic Structure of <i>Rhizoctonia solani</i> AG-2-2IIIB from Soybean in Illinois, Ohio, and Ontario
Bibliographic record
Abstract
Rhizoctonia solani AG-2-2IIIB is an important seedling pathogen of soybean in North America and other soybean-growing regions around the world. There is no information regarding the population genetics of field populations of R. solani associated with soybean seedling disease. More specifically, information regarding genetic diversity, the mode of reproduction, and the evolutionary factors that shape different R. solani populations separated in time and space are lacking. We exploited genotyping by sequencing as a tool to assess the genetic structure of R. solani AG-2-2IIIB populations from Illinois, Ohio, and Ontario and investigate the reproductive mode of this subgroup. Our results revealed differences in genotypic diversity among three populations, with the Ontario population having greatest diversity. An overrepresentation of multilocus genotypes (MLGs) and a rejection of the null hypothesis of random mating in all three populations suggested clonality within each population. However, phylogenetic analysis revealed long terminal multifurcating branches for most members of the Ontario population, suggesting a mixed reproductive mode for this population. Analysis of molecular variance revealed low levels of population differentiation, and sharing of similar MLGs among populations highlights the role of genotype flow as an evolutionary force shaping population structure of this subgroup.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".