Bibliographic record
Abstract
Lateral gene transfer has emerged as an important force in bacterial evolution. A substantial number of genes can be inserted into or deleted from genomes through the process of lateral transfer. In this study, we looked for atypical occurrence of genes among related organisms to detect laterally transferred genes. We have analyzed 50 bacterial complete genomes from nine groups. For each group we use a 16s rRNA phylogeny and a comparison of protein similarity to map gene insertions/deletions onto their species phylogeny. The results reveal that there is poor correlation of genes inserted, deleted, and duplicated with evolutionary branch length. In addition, the numbers of genes inserted, deleted, or duplicated within the same branch are not always correlated with each other. Nor is there any similarity within groups. For example, in the Rhizobiales group, the ratio of insertions to deletions in the evolutionary branch leading to Agrobacterium tumefaciens str. C58 (Cereon) is 0.52, but it is 39.52 for Mesorhizobium loti. Most strikingly, the number of insertions of foreign genes is much larger in the external branches of the trees. These insertions also greatly outnumber the occurrence of deletions, and yet the genome sizes of these bacteria remain roughly constant. This indicates that many of the insertions are specific to each organism and are lost before related species can evolve. Simulations of the process of insertion and deletion, tailored to each phylogeny, support this conclusion.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".