Reconstructing the Phylogeny of Corynebacteriales while Accounting for Horizontal Gene Transfer
Bibliographic record
Abstract
Horizontal gene transfer is a common mechanism in Bacteria that has contributed to the genomic content of existing organisms. Traditional methods for estimating bacterial phylogeny, however, assume only vertical inheritance in the evolution of homologous genes, which may result in errors in the estimated phylogenies. We present a new method for estimating bacterial phylogeny that accounts for the presence of genes acquired by horizontal gene transfer between genomes. The method identifies and corrects putative transferred genes in gene families, before applying a gene tree-based summary method to estimate bacterial species trees. The method was applied to estimate the phylogeny of the order Corynebacteriales, which is the largest clade in the phylum Actinobacteria. We report a collection of 14 phylogenetic trees on 360 Corynebacteriales genomes. All estimated trees display each genus as a monophyletic clade. The trees also display several relationships proposed by past studies, as well as new relevant relationships between and within the main genera of Corynebacteriales: Corynebacterium, Mycobacterium, Nocardia, Rhodococcus, and Gordonia. An implementation of the method in Python is available on GitHub at https://github.com/UdeS-CoBIUS/EXECT (last accessed April 2, 2020).
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".