Core genes can have higher recombination rates than accessory genes within global microbial populations
Bibliographic record
Abstract
Abstract Recombination is essential to microbial evolution 1–4 , and is involved in the spread of antibiotic resistance, antigenic variation, and adaptation to the host niche 5–8 . Yet quantifying the impact of homologous recombination on different gene classes, which is critical to understanding how selection acts on variation to shape species diversity and genome structure, remains challenging. This is largely due to the dynamic nature of bacterial genomes, whose high intraspecies genome content diversity 9 and complex phylogenetic relationships 10–12 present difficulties for inferring rates of recombination, particularly for rare genes. In this work, we apply a computationally efficient, non-phylogenetic approach 13,14 to measure homologous recombination rates in the core and accessory genome (genes present in all strains and only a subset of strains, respectively) using >100,000 whole genome sequences from 12 microbial species. Our analysis suggests that even well-resolved sequence clusters sampled from global populations interact with overlapping gene pools, which has implications for the role of population structure in genome evolution. We show that in a majority of species, core genes have shorter coalescence times and higher recombination rates than accessory genes, and that gene frequency is often positively correlated with increased recombination. Our results provide a new line of population genomic evidence supporting the hypothesis that core genes are under strong, purifying selection 15–17 , and indicate that homologous recombination may play a key role in increasing the efficiency of selection in those parts of the genome most conserved within each 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 | 0.001 | 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 | 0.001 | 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".