Sources of genomic diversity in the self-fertile plant pathogen, Sclerotinia sclerotiorum, and consequences for resistance breeding
Bibliographic record
Abstract
The ascomycete, Sclerotinia sclerotiorum, has a broad host range and causes yield loss in dicotyledonous crops world wide. Genomic diversity was determined in a population of 127 isolates obtained from individual canola (Brassica napus) fields in western Canada. Genotyping with 39 simple sequence repeat (SSR) markers revealed each isolate was a unique haplotype. Analysis of molecular variance showed 97% was due to isolate and 3% due to geographical location. Testing of mycelium compatibility among 133 isolates identified clones of mutually compatible isolates with 86-95% similar SSR haplotype, whereas incompatible isolates were highly diverse. In the Province of Manitoba, 61% of isolates were compatible forming clones and stings of pairwise compatible isolates not described before. In contrast, only 35% of isolates were compatible in Alberta without forming clones and strings, while 39% were compatible in Saskatchewan with a single clone, but no strings. These difference can be explained by wetter growing seasons and more susceptible crop species in Manitoba favouring frequent mycelium interaction and more life cycles over time, which might also explain similar differences observed in other geographical areas and host crops. Analysis of linkage disequilibrium rejected random recombination, consistent with a self-fertile fungus, restricted outcrossing due to mycelium incompatibility, and only a single annual opportunity for genomic recombination during meiosis in the ascospore stage between non-sister chromatids in the rare event nuclei from different isolates come together. More probable sources of genomic diversity is slippage during DNA replication and point mutation affecting single nucleotides that accumulate and likely increase mycelium incompatibility in a population over time. A phylogenetic tree based on SSR haplotype grouped isolates into 17 sub-populations. Aggressiveness was tested by inoculating one isolate from each sub-population onto B. napus lines with quantitative resistance. Analysis of variance was significant for isolate, line, and isolate by line interaction. These isolates represent the genomic and pathogenic diversity in western Canada, and are suitable for resistance screening in canola 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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".