Elevated Rates of Molecular Evolution Genome-wide in Mutualist Legumes and Rhizobia
Bibliographic record
Abstract
Rates of molecular evolution vary greatly among even closely related species. Although theory predicts that antagonistic interactions between species increase rates of molecular evolution, predictions for how mutualism affects evolutionary rates are mixed. We compared rates of molecular evolution between (i) mutualistic and non-mutualistic legumes, (ii) an independent set of symbiotic rhizobia and their non-symbiotic close relatives, and (iii) symbiotic and non-symbiotic clades within Ensifer, a diverse genus of bacteria with various lifestyles. We assembled transcriptomes de novo for 12 legume species and calculated dN/dS ratios at orthologous genes in all species to determine if genes in mutualistic plants evolve faster or slower than in their non-mutualistic relatives. We also calculated dN/dS ratios in genes known to be important for symbiosis. We found that mutualists have higher rates of molecular evolution genome-wide compared to non-mutualistic legumes, but this pattern did not hold in symbiosis genes. We next calculated dN/dS ratios in 14 bacteria species across the proteobacteria phylogeny that differ in whether they associate mutualistically with plants, using published data. In most pairs, symbiotic rhizobia show higher dN/dS values compared to their non-symbiotic relatives. Within a bacterial genus with many well-characterized mutualist species (Ensifer), we calculated dN/dS ratios in symbiotic and non-symbiotic clades and found that symbiotic lineages have higher rates of molecular evolution genome-wide, but not at genes on the symbiotic plasmid pSymB. Our results suggest that although mutualism between legumes and rhizobia is associated with elevated rates of molecular evolution genome-wide, symbiosis genes may be evolutionarily stagnant.
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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 | 0.001 | 0.001 |
| 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".