Elevated mutation near crossovers inhibits the evolution of recombination
Bibliographic record
Abstract
Recombination diversifies offspring genomes and helps ensure chromosome segregation during meiosis. Mutation rates are elevated near crossovers due to the induction of double-strand breaks and their imperfect repair, a byproduct of recombination typically ignored by theory designed to explain its evolution. To examine the evolutionary role of mutagenic recombination, we analyze a population genetic model in which a modifier locus controls both the rate of recombination between two loci experiencing viability selection and the rate of mutation at those loci. Analytical and numerical results demonstrate that the advantage of recombination conferred by its capacity to remove epistatic, deleterious variants is overcome by the selective cost of even small increases in the mutation rate. By incorporating the mutagenic effects of recombination, our analysis extends a rich body of theory to acknowledge a molecular feature inherent in the formation of crossovers. Our findings suggest that higher recombination rate evolves by altering steps in the crossover pathway that are less likely to inflict mutational damage.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".