Genetic Variation within Clonal Lineages of Phytophthora infestans Revealed through Genotyping-By-Sequencing, and Implications for Late Blight Epidemiology
Bibliographic record
Abstract
Genotyping-by-sequencing (GBS) was performed on 257 Phytophthora infestans isolates belonging to four clonal lineages to study within-lineage diversity. The four lineages used in the study were US-8 (n = 28), US-11 (n = 27), US-23 (n = 166), and US-24 (n = 36), with isolates originating from 23 of the United States and Ontario, Canada. The majority of isolates were collected between 2010 and 2014 (94%), with the remaining isolates collected from 1994 to 2009, and 2015. Between 3,774 and 5,070 single-nucleotide polymorphisms (SNPs) were identified within each lineage and were used to investigate relationships among individuals. K-means hierarchical clustering revealed three clusters within lineage US-23, with US-23 isolates clustering more by collection year than by geographic origin. K-means hierarchical clustering did not reveal significant clustering within the smaller US-8, US-11, and US-24 data sets. Neighbor-joining (NJ) trees were also constructed for each lineage. All four NJ trees revealed evidence for pathogen dispersal and overwintering within regions, as well as long-distance pathogen transport across regions. In the US-23 NJ tree, grouping by year was more prominent than grouping by region, which indicates the importance of long-distance pathogen transport as a source of initial late blight inoculum. Our results support previous studies that found significant genetic diversity within clonal lineages of P. infestans and show that GBS offers sufficiently high resolution to detect sub-structuring within clonal populations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".