Race structure and frequency of avirulence genes in the western Canadian <i>Leptosphaeria maculans</i> pathogen population, the causal agent of blackleg in brassica species
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Leptosphaeria maculans is the causal agent of blackleg, a serious disease on canola/rapeseed in western Canada, Australia and Europe. Genetic resistance and extended crop rotation provided effective disease control in western Canada for years but the emergence of new pathogen races has reduced the effectiveness of current management strategies. The objective of this study was to analyse L. maculans isolates derived from canola stubble in commercial fields collected in 2010 and 2011 across western Canada for the presence and frequency of avirulence ( Avr ) genes. A total of 674 isolates were examined for the presence of Avr alleles AvrLm1 , AvrLm2 , AvrLm3 , AvrLm4 , AvrLm6 , AvrLm7 , AvrLm9 , AvrLepR1 , AvrLepR2 and AvrLmS using a set of differential host genotypes carrying known resistance genes or PCR amplification of AvrLm1 , AvrLm6 and AvrLm4–Lm7 . Certain alleles were more prevalent in the pathogen population, with AvrLm6 and AvrLm7 present in >85% of isolates, while AvrLm3 , AvrLm9 and AvrLepR2 were present in <10% of isolates. A total of 55 races (different combinations of Avr alleles) were detected, with the two most common ones being AvrLm2–Lm4–Lm6–Lm7 and AvrLm2–Lm4–Lm6–Lm7–LmS . Races carrying as many as seven and as few as one known Avr allele were detected. Selection pressure from the race‐specific resistance genes carried in canola cultivars has probably played a significant role in the current Avr profile, which may have also contributed to the recent increase in blackleg observed in western Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it