Coevolutionary cycling in allele frequencies and the evolution of virulence
Bibliographic record
Abstract
Coevolutionary cycling in allele frequencies due to negative frequency-dependent selection-sometimes referred to as Red Queen Dynamics-is a key potential outcome of host-parasite coevolution. While many theoretical studies have focused on understanding the consequences of coevolutionary cycling for the evolution of sex and recombination, little is known about the impact of coevolutionary cycling on the evolution of other life history traits. It is therefore currently unknown how coevolutionary cycling in allele frequencies affects the evolution of key disease characteristics, such as virulence. Here, we combine population genetic and quantitative genetic approaches to theoretically determine the impacts of coevolutionary cycling in allele frequencies on the evolution of virulence in a free-living parasite. By varying the level of genetic specificity required for infection while controlling for the average infection rate, we induce coevolutionary cycles and examine their effects on virulence evolution. We show that coevolutionary cycling does indeed have a strong impact on virulence evolution, with more specific infection genetics and higher allelic diversity generally driving larger and more rapid cycles in allele frequencies, leading to selection for higher virulence. Our research provides new fundamental insights into the relationship between coevolutionary cycling and the evolution of virulence.
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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 | 0.000 |
| 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 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".