Positional Homology in Bacterial Genomes
Bibliographic record
Abstract
In comparative genomic studies, syntenic groups of homologous sequence in the same order have been used as supplementary information that can be used in helping to determine the orthology of the compared sequences. The assumption is that orthologous gene copies are more likely to share the same genome positions and share the same gene neighbors. In this study we have defined positional homologs as those that also have homologous neighboring genes and we investigated the usefulness of this distinction for bacterial comparative genomics. We considered the identification of positionaly homologous gene pairs in bacterial genomes using protein and DNA sequence level alignments and found that the positional homologs had on average relatively lower rates of substitution at the DNA level (synonymous substitutions) than duplicate homologs in different genomic locations, regardless of the level of protein sequence divergence (measured with non-synonymous substitution rate). Since gene order conservation can indicate accuracy of orthology assignments, we also considered the effect of imposing certain alignment quality requirements on the sensitivity and specificity of identification of protein pairs by BLAST and FASTA when neighboring information is not available and in comparisons where gene order is not conserved. We found that the addition of a stringency filter based on the second best hits was an efficient way to remove dubious ortholog identifications in BLAST and FASTA analyses. Gene order conservation and DNA sequence homology are useful to consider in comparative genomic studies as they may indicate different orthology assignments than protein sequence homology alone.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".