Simple sequence repeat marker analysis reveals grouping of <i>Pyrenophora tritici-repentis</i> isolates based on geographic origin
Bibliographic record
Abstract
The population structure and genetic diversity of Pyrenophora tritici-repentis from hexaploid wheat were examined using 51 simple sequence repeat (SSR) markers designed to represent each chromosome of the pathogen. A total of 83 isolates representing races 1 and 2 of Ptr were analysed, including 35 isolates from Canada and 48 isolates from Iran. Isolates of the same two races but originating from different regions were compared in order to examine the effect of geographic origin on grouping. Most of the variation (91%) was observed within the examined populations and only 9% between populations. In addition, a moderate amount of gene flow (Nm = 2.8134) was found between populations. The average gene diversity and the percentage of polymorphic loci were estimated to be 0.2764 and 68.63%, respectively. Applying the unweighted pair group method with arithmetic mean procedure and Dice similarity coefficient revealed no obvious clustering of isolates based on race designation. In contrast, the grouping of isolates was consistent with geographic origin to some extent, with most isolates from Iran and Canada clustering separately regardless of race. These results indicate a link between geographic origin and the grouping of Ptr isolates, which could be detected by comparison of the same two races from two different regions. Previous research compared variable races, making it difficult to draw conclusions regarding the effect of geographic origin.
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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 | 0.000 | 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".