Data files for: Hazardous loss of genetic diversity through selective sweeps in asexual populations
Bibliographic record
Abstract
With the two-fold cost of sex, derived asexual organisms have an immediate reproductive advantage over their sexual sisters. Yet the "twiggy'' phylogenetic distribution of asexual lineages implies that they go extinct relatively quickly over evolutionary time. Meanwhile, bacteria and archaea have persisted for billions of years without requiring sexual reproduction. A simple explanation for this difference is that prokaryotes have very large population sizes that are not subject to the accumulation of deleterious mutations, but this implies that drift and mutational meltdown dominate derived asexual populations. We explored a different hazard, quantifying the degree to which genetic variation is lost in asexual populations experiencing selective sweeps. Even though large populations generate diversity by mutation during sweeps, we find that populations that are safe from mutational meltdown may still be reduced to dangerous effective population sizes by sweeps. Thus, ironically, adaptation itself reduces further adaptive potential and may predispose asexual populations to extinction. Our data give results for the probability of mutational meltdown across various population sizes, the critical population size required to avoid meltdown, and the effect of selective sweeps on heterozygosity. Analytical predictions are confirmed by simulation. We also derive a simple approximation for the effective population size after a hard sweep, and quantify the impact of recent sweeps on evolutionary rescue. These factors may help to explain the phylogenetic twigginess of asexuals, the maintenance of sex and recombination, and the evolutionary persistence of prokaryotes.
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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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.803 | 0.375 |
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".