The effects of losing sex on the molecular evolution of plant defense
Bibliographic record
Abstract
Abstract It is hypothesized that the loss of sexual reproduction and reduced recombination rates decrease the ability for hosts to evolve in response to selection by parasites. Using transcriptomes from 32 species, we test whether repeated losses of sex in the plant genus Oenothera has resulted in changes to the evolution of defense genes against herbivores and pathogens. To achieve this, the function of 2,431 Oenothera orthologous genes was determined based on GO annotations from Arabidopsis thaliana . Phylogenetic Analysis by Maximum Likelihood (PAML) was then used to examine how the patterns of molecular evolution in 721 defense and 1,710 non-defense genes differ between sexual (16 spp.) and asexual (16 spp.) taxa. We test whether the relative rates of nonsynonymous to synonymous substitutions (ω = dN/dS) in proteins with defensive function were higher in lineages with sexual reproduction (ω sexual > ω a-sexual ), and we asked if such patterns were exclusive for defense genes or not. We detected variability in the rate of amino acid replacements of proteins in >50% of genes and positive selection on 3% of the genes examined. Nevertheless, our results clearly show that on average, signatures of positive and purifying selection on defense and non-defense genes are similar and only a small number of specific genes related to plant immune function may be affected by a loss of sex.
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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 | 0.001 |
| 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) | 0.001 | 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".