Specific adaptation of Ustilaginoidea virens in occupying host florets revealed by comparative and functional genomics
Bibliographic record
Abstract
Ustilaginoidea virens (Cooke) Takah is an ascomycetous fungus that causes rice false smut, a devastating emerging disease worldwide. Here we report a 39.4 Mb draft genome sequence of U. virens that encodes 8,426 predicted genes. The genome has ~25% repetitive sequences that have been affected by repeat-induced point mutations. Evolutionarily, U. virens is close to the entomopathogenic Metarhizium spp., suggesting potential host jumping across kingdoms. U. virens possesses reduced gene inventories for polysaccharide degradation, nutrient uptake and secondary metabolism, which may result from adaptations to the specific floret infection and biotrophic lifestyles. Consistent with their potential roles in pathogenicity, genes for secreted proteins and secondary metabolism and the pathogen–host interaction database genes are highly enriched in the transcriptome during early infection. We further show that 18 candidate effectors can suppress plant hypersensitive responses. Together, our analyses offer new insights into molecular mechanisms of evolution, biotrophy and pathogenesis of U. virens. Rice false smut, caused by the pathogenic ascomycete fungus Ustilaginoidea virens (Cooke) Takah, has a significant economic impact on crop production. Here, Zhang et al. report the draft genome sequence of U. virensand provide insight into the evolution of genes involved in pathogenicity and adaptation to a biotrophic and floret-infecting lifestyle.
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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) | 0.001 | 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".