Diversity and Structure of <i>Diaporthe humulicola</i> Populations from Eastern North America
Bibliographic record
Abstract
Hop ( Humulus lupulus) production in the eastern United States has increased in recent years, prompting the need to understand emerging fungal pathogens in this region. This study is the first population genetics analysis of Diaporthe humulicola, a recently described pathogen causing halo blight. A total of 71 D. humulicola isolates from Michigan, New York, Minnesota, and Canada were sequenced and analyzed using Illumina 150 × 150-bp reads with 10× coverage. Single-nucleotide polymorphisms were discovered and filtered using the Genome Analysis Toolkit. After filtering and clone correction, 63 isolates remained for downstream analysis. Population structure was determined to have three clusters and was supported using STRUCTURE, principal component analysis, and discriminant analysis of principal components. Analyses showed that Michigan isolates closely clustered with isolates from Canada and New York, as well as one isolate from Minnesota. The rest of the Minnesota isolates clustered in an independent cluster. Minnesota isolates appear to have high levels of population differentiation when compared with the different populations exhibiting a high fixation index, a measure of population differentiation and low nucleotide diversity. Mating type was determined for each isolate, with Mat1-2-1 present in 61.9% of the whole population. We also detected signals of recombination in each of the fungal populations, with higher levels in Michigan and Canada. These findings highlight the genetic complexity and regional differentiation of D. humulicola populations, with implications for disease management and hop breeding programs.
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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) | 0.000 | 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".