Genetic Diversity and Evolution of Chinese Traditional Medicinal Fungus Polyporus umbellatus (Polyporales, Basidiomycota)
Bibliographic record
Abstract
BACKGROUND: Polyporus umbellatus is an important medicinal fungus distributed throughout most area of China. Its wide distribution may have resulted in substantial intraspecific genetic diversity for the fungus, potentially creating variation in its medical value. To date, we know little about the intraspecific genetic diversity of P. umbellatus. METHODOLOGY/PRINCIPAL FINDINGS: The objective of this research was to assess genetic differences of P. umbellatus from geographically diverse regions of China based on nrDNA ITS and 28S rRNA (LSU, large subunit) sequences. Significant sequence variations in the ITS and LSU sequences were detected. All sclerotial samples were clustered into four clades based on phylogenetic analysis of ITS, LSU and a combined data set of both regions. Heterogeneity of ITS and LSU sequences was detected in 5 and 7 samples respectively. All clone sequences clustered into the same clade except for one LSU clone sequences (from Henan province) which clustered into two clades (Clade I and Clade II). Significant genetic divergence in P. umbellatus was observed and the genetic diversification was greater among sclerotial samples from Shaanxi, Henan and Gansu provinces than among other provinces. Polymorphism of ITS and LSU sequences indicated that in China, P. umbellatus may spread from a center (Shaanxi, Henan and Gansu province) to other regions. CONCLUSIONS/SIGNIFICANCE: We found sclerotial samples of P. umbellatus contained levels of intraspecific genetic diversity. These findings suggested that P. umbellatus populations in Shaanxi, Henan and Gansu are important resources of genetic diversity and should be conserved accordingly.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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".