Tremellomycetes Yeasts in Kernel Ecological Niche: Early Indicators of Enhanced Competitiveness of Endophytic and Mycoparasitic Symbionts against Wheat Pathobiota
Bibliographic record
Abstract
Tremellomycetes rDNA sequences previously detected in wheat kernels by MiSeq were not reliably assigned to a genus or clade. From comparisons of ribosomal internal transcribed spacer region (ITS) and subsequent phylogenetic analyses, the following three basidiomycetous yeasts were resolved and identified: Vishniacozymavictoriae, V. tephrensis, and an undescribed Vishniacozyma rDNA variant. The Vishniacozyma variant’s clade is evolutionarily close to, but phylogenetically distinct from, the V. carnescens clade. These three yeasts were discovered in wheat kernel samples from the Canadian prairies. Variations in relative Vishniacozyma species abundances coincided with altered wheat kernel weight, as well as host resistance to chemibiotrophic Tilletia (Common bunt—CB) and necrotrophic Fusarium (Fusarium head blight—FHB) pathogens. Wheat kernel weight was influenced by the coexistence of Vishniacozyma with endophytic plant growth-promoting and mycoparasitic biocontrol fungi that were acquired by plants. Kernels were coated with beneficial Penicillium endophyte and Sphaerodes mycoparasite, each of which had different influences on the wild yeast population. Its integral role in the kernel microbiome renders Vishniacozyma a measurable indicator of the microbiome–plant interaction. The ability of NGS technology to detect specific endophytic DNA variants and early changes in dynamics among symbionts within the kernel ecological niche enables the prediction of crop disease emergence, suggesting that advanced microbiological testing may be a potentially useful tool for both phytoprotection and more efficient wheat 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".