Historical Differentiation and Recent Hybridization in Natural Populations of the Nematode-Trapping Fungus Arthrobotrys oligospora in China
Bibliographic record
Abstract
Maintaining the effects of nematode-trapping fungi (NTF) agents in order to control plant-parasitic nematodes (PPNs) in different ecological environments has been a major challenge in biological control applications. To achieve such an objective, it is important to understand how populations of the biocontrol agent NTF are geographically and ecologically structured. A previous study reported evidence for ecological adaptation in the model NTF species Arthrobotrys oligospora. However, their large-scale geographic structure, patterns of gene flow, their potential phenotypic diversification, and host specialization remain largely unknown. In this study, we developed a new panel of 20 polymorphic short tandem repeat (STR) markers and analyzed 239 isolates of A. oligospora from 19 geographic populations in China. In addition, DNA sequences at six nuclear gene loci and strain mating types (MAT) were obtained for these strains. Our analyses suggest historical divergence within the A. oligospora population in China. The genetically differentiated populations also showed phenotypic differences that may be related to their ecological adaptations. Interestingly, our analyses identified evidence for recent dispersion and hybridization among the historically subdivided geographic populations in nature. Together, our results indicate a changing population structure of A. oligospora in China and that care must be taken in selecting the appropriate strains as biocontrol agents that can effectively reproduce in agriculture soil while maintaining their nematode-trapping ability.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".