Bibliographic record
Abstract
Recombination, the shuffling of alleles during meiosis, is a fundamental evolutionary process that is nearly ubiquitous across eukaryotes. By uncoupling linkage disequilibrium between harmful and beneficial mutations, recombination promotes more effective selection. However, recombination rate varies at multiple scales across nature, which has important implications for genome evolution at large. Here, I report four chapters that investigate recombination and genome evolution using the unicellular and facultatively sexual chlorophyte Chlamydomonas reinhardtii. I examine recombination rate variation at the level of populations, individuals, and across the genome itself. I show that recombination rates are consistent between populations and individuals, demonstrate evidence that recombination plays a role in reducing the effects of selection at linked sites, and estimate the rate of sexual reproduction in a wild population of C. reinhardtii. I also investigate recombination in a crossover-suppressed sex-determining region of the genome, and show how noncrossover recombination can still maintain effective selection, thus preventing long-term degeneration of these loci. Finally, I close off with a study pertaining to mutational biases introduced by environmental stressors in C. reinhardtii and demonstrate the effects of the former on adaptation. Altogether, my thesis addresses fundamental questions regarding recombination rate variation and adaptation in C. reinhardtii, and alongside existing detailed work on spontaneous mutation in the system, provides an empirical framework for understanding how these processes affect genome evolution over evolutionary time.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".