Reduced Efficacy of Natural Selection on Codon Usage Bias in Selfing Arabidopsis and Capsella Species
Why this work is in the frame
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Bibliographic record
Abstract
Population genetic theory predicts that the efficacy of natural selection in a self-fertilizing species should be lower than its outcrossing relatives because of the reduction in the effective population size (N(e)) in the former brought about by inbreeding. However, previous analyses comparing Arabidopsis thaliana (selfer) with A. lyrata (outcrosser) have not found conclusive support for this prediction. In this study, we addressed this issue by examining silent site polymorphisms (synonymous and intronic), which are expected to be informative about changes in N(e). Two comparisons were made: A. thaliana versus A. lyrata and Capsella rubella (selfer) versus C. grandiflora (outcrosser). Extensive polymorphism data sets were obtained by compiling published data from the literature and by sequencing 354 exon loci in C. rubella and 89 additional loci in C. grandiflora. To extract information from the data effectively for studying these questions, we extended two recently developed models in order to investigate detailed selective differences between synonymous codons, mutational biases, and biased gene conversion (BGC), taking into account the effects of recent changes in population size. We found evidence that selection on synonymous codons is significantly weaker in the selfers compared with the outcrossers and that this difference cannot be fully accounted for by mutational biases or BGC.
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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 it