Population Structure of <i>Pyrenophora teres</i> f. <i>teres</i> Barley Pathogens from Different Continents
Bibliographic record
Abstract
Net form net blotch disease, caused by Pyrenophora teres f. teres, results in significant yield losses to barley industries. Up-to-date knowledge of the genetic diversity and structure of pathogen populations is critical for elucidating the disease epidemiology and unraveling pathogen survival and dispersal mechanisms. Thus, this study investigated long-distance dispersal and adaptation by analyzing the genetic structure of 250 P. teres f. teres isolates collected from Australia, Canada, Hungary, and Republic of South Africa (RSA), and historical isolates from Canada, Denmark, Japan, and Sweden. The population genetic structure detected by discriminant analysis of principal components, with the use of 5,890 Diversity Arrays Technology markers, revealed the presence of four clusters. Two of these contained isolates from all regions, and all isolates from RSA were grouped in these two. Australia and Hungary showed three clusters each. One of the Australian clusters contained only Australian isolates. One of the Hungarian clusters contained only Hungarian isolates and one Danish isolate. STRUCTURE analysis indicated that some isolates from Australia and Hungary shared recent ancestry with RSA, Canada, and historical isolates and were thus admixed. Subdivisions of the neighbor joining network indicated that isolates from distinct countries were closely related, suggesting that multiple introduction events conferred genetic heterogeneity in these countries. Through a neighbor joining analysis and amplification with form-specific DNA markers, we detected two hybrid isolates, CBS 281.31 from Japan and H-919 from Hungary, collected in 1931 and 2018, respectively. These results provide a foundation for exploring improved management of disease incursions and pathogen control through strategic deployment of resistance.
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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 | 0.000 |
| 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".