The pathogenic mechanisms of Tilletia horrida as revealed by comparative and functional genomics
Bibliographic record
Abstract
Tilletia horrida is a soil-borne, mononucleate basidiomycete fungus with a biotrophic lifestyle that causes rice kernel smut, a disease that is distributed throughout hybrid rice growing areas worldwide. Here we report on the high-quality genome sequence of T. horrida; it is composed of 23.2 Mb that encode 7,729 predicted genes and 6,973 genes supported by RNA-seq. The genome contains few repetitive elements that account for 8.45% of the total. Evolutionarily, T. horrida lies close to the Ustilago fungi, suggesting grass species as potential hosts, but co-linearity was not observed between T. horrida and the barley smut Ustilago hordei. Genes and functions relevant to pathogenicity were presumed. T. horrida possesses a smaller set of carbohydrate-active enzymes and secondary metabolites, which probably reflect the specific characteristics of its infection and biotrophic lifestyle. Genes that encode secreted proteins and enzymes of secondary metabolism, and genes that are represented in the pathogen-host interaction gene database genes, are highly expressed during early infection; this is consistent with their potential roles in pathogenicity. Furthermore, among the 131 candidate pathogen effectors identified according to their expression patterns and functionality, we validated two that trigger leaf cell death in Nicotiana benthamiana. In summary, we have revealed new molecular mechanisms involved in the evolution, biotrophy, and pathogenesis of T. horrida.
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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 | 0.001 | 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 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".