Comparative Genomics of a Plant-Pathogenic Fungus,<i>Pyrenophora tritici-repentis</i>, Reveals Transduplication and the Impact of Repeat Elements on Pathogenicity and Population Divergence
Bibliographic record
Abstract
Pyrenophora tritici-repentis is a necrotrophic fungus causal to the disease tan spot of wheat, whose contribution to crop loss has increased significantly during the last few decades. Pathogenicity by this fungus is attributed to the production of host-selective toxins (HST), which are recognized by their host in a genotype-specific manner. To better understand the mechanisms that have led to the increase in disease incidence related to this pathogen, we sequenced the genomes of three P. tritici-repentis isolates. A pathogenic isolate that produces two known HSTs was used to assemble a reference nuclear genome of approximately 40 Mb composed of 11 chromosomes that encode 12,141 predicted genes. Comparison of the reference genome with those of a pathogenic isolate that produces a third HST, and a nonpathogenic isolate, showed the nonpathogen genome to be more diverged than those of the two pathogens. Examination of gene-coding regions has provided candidate pathogen-specific proteins and revealed gene families that may play a role in a necrotrophic lifestyle. Analysis of transposable elements suggests that their presence in the genome of pathogenic isolates contributes to the creation of novel genes, effector diversification, possible horizontal gene transfer events, identified copy number variation, and the first example of transduplication by DNA transposable elements in fungi. Overall, comparative analysis of these genomes provides evidence that pathogenicity in this species arose through an influx of transposable elements, which created a genetically flexible landscape that can easily respond to environmental changes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 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".