The slow:fast substitution ratio reveals changing patterns of natural selection in γ-proteobacterial genomes
Bibliographic record
Abstract
Different microbial species are thought to occupy distinct ecological niches, subjecting each species to unique selective constraints, which may leave a recognizable signal in their genomes. Thus, it may be possible to extract insight into the genetic basis of ecological differences among lineages by identifying unusual patterns of substitutions in orthologous gene or protein sequences. We used the ratio of substitutions in slow- versus fast-evolving sites (nucleotides in DNA, or amino acids in protein sequence) to quantify deviations from the typical pattern of selective constraint observed across bacterial lineages. We propose that elevated S:F in one branch (an excess of slow-site substitutions) can indicate a functionally relevant change, due to either positive selection or relaxed evolutionary constraint. In a genome-wide comparative study of gamma-proteobacterial proteins, we find that cell-surface proteins involved with motility and secretion functions often have high S:F ratios, whereas information-processing genes do not. Change in evolutionary constraints in some species is evidenced by increased S:F ratios within functionally related sets of genes (for example, energy production in Pseudomonas fluorescens), whereas other species apparently evolve mostly by drift (for example, uniformly elevated S:F across most genes in Buchnera spp.). Overall, S:F reveals several species-specific, protein-level changes with potential functional/ecological importance. As microbial genome projects yield more species-rich gene trees, the S:F ratio will become an increasingly powerful tool for uncovering functional genetic differences among species.
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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 | 0.002 | 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) | 0.000 | 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 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".