Evolutionary genetic consequences of facultative sex and outcrossing
Bibliographic record
Abstract
Explaining the selective forces that underlie different reproductive modes forms a major part of evolution research. Many organisms are facultative sexuals, with the ability to reproduce both sexually and asexually. Reduced sequencing costs means it is now possible to start investigating genome sequences of a wider number of these organisms in depth, but teasing apart the genetic forces underlying the maintenance of facultative sexual reproduction remains a challenge. An analogous problem exists when determining the genetic consequences of a degree of outcrossing (and recombination) in otherwise self-fertilizing organisms. Here, I provide an overview of existing research on the evolutionary basis behind different reproductive modes, with a focus on explaining the population genetic effects favouring low outcrossing rates in either partially selfing or asexual species. I review the outcomes that both self-fertilization and asexuality have on either purging deleterious mutations or fixing beneficial alleles, and what empirical data exist to support these theories. In particular, a greater application of mathematical models to genomic data has provided insight into the numerous effects that transitions to self-fertilization from outcrossing have on genetic architecture. Similar modelling approaches could be used to determine the forces shaping genetic diversity of facultative sexual species. Hence, a further unification of mathematical models with next-generation sequence data will prove important in exploring the genetic influences on reproductive system evolution.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.002 | 0.001 |
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".