Genetic diversity and population structure of Leptosphaeria maculans isolates in Western Canada
Bibliographic record
Abstract
Leptosphaeria maculans is a serious concern for canola production worldwide. For effective disease management, knowledge of the pathogen's genetic variability and population structure is a prerequisite. In this study, whole-genome sequencing was performed for 162 of 1590 L. maculans isolates collected in the years 2007-2008 and 2012-2014 in Western Canada. DNA variants in genome-wide and specific regions including avirulence (Avr) genes were characterized. A total of 31,870 high-quality polymorphic DNA variants were used to study L. maculans genetic diversity and population structure. Cluster analysis showed that 150 isolates were clustered into 2 main groups and 4 subgroups by DNA variants located in either Avr or small secreted protein-encoding genes and into 2 main groups and 6 subgroups by genome-wide variants. The analysis of nucleotide diversity and differentiation also confirmed genetic variation within a population and among populations. Principal component analysis with genome-wide variants showed that the isolates collected in 2012-2014 were more genetically diverse than those collected in 2007-2008. Population structure analysis discovered three distinct sub-populations. Although isolates from Saskatchewan and Alberta were of similar genetic composition, Manitoba isolates were highly diverse. Genome-wide association study detected DNA variants in genes AvrLm4-7, Lema_T86300, and Lema_T86310 associated with the years of collection.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".