Selective sweeps in populations of the broad host range plant pathogenic fungus <i>Sclerotinia sclerotiorum</i>
Bibliographic record
Abstract
Abstract The pathogenic fungus Sclerotinia sclerotiorum infects over 600 species of plant. It is present in numerous environments throughout the world and causes significant damage to many agricultural crops. Fragmentation and lack of gene flow between populations may lead to population sub-structure. Within discrete recombining populations, positive selection may lead to a ‘selective sweep’. This is characterised by an increase in frequency of a favourable allele leading to reduction in genotypic diversity in a localised genomic region due to the phenomenon of genetic hitchhiking. We aimed to assess whether isolates of S. sclerotiorum from around the world formed genotypic clusters associated with geographical origin and to determine whether signatures of population-specific positive selection could be detected. To do this, we sequenced the genomes of 25 isolates of S. sclerotiorum collected from four different continents - Australia, Africa (north and south), Europe and North America (Canada and the northen United States) and conducted SNP based analyses of population structure and selective sweeps. Among the 25 isolates, there was evidence for four population clusters. One of these consisted of 11 isolates from Canada, the USA and France (population 1), another consisted of five isolates from Australia and one from Morocco (population 2). A further cluster was made up of Australian isolates, and the single South African isolate appeared to be from a separate population. We found that there was evidence of distinct selective sweeps between population 1 and population 2. Many of these sweeps overlapped genes involved in transcriptional regulation, such as transcription factors. It is possible that distinct populations of S. sclerotiorum from differing global environments have undergone selective sweeps at different genomic loci. This study lays the foundation for further work into investigation of the differing selective pressures that S. sclerotiorum populations are subjected to on a global scale.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".