Rooting the Eukaryotic Tree with Mitochondrial and Bacterial Proteins
Bibliographic record
Abstract
By exploiting the large body of genome data and the considerable progress in phylogenetic methodology, recent phylogenomic studies have provided new insights into the relationships among major eukaryotic groups. However, confident placement of the eukaryotic root remains a major challenge. This is due to the large evolutionary distance separating eukaryotes from their closest relatives, the Archaea, implying a weak phylogenetic signal and strong long-branch attraction artifacts. Here, we apply a new approach to the rooting of the eukaryotic tree by using a subset of genomic information with more recent evolutionary origin-mitochondrial sequences, whose closest relatives are α-Proteobacteria. For this, we identified and assembled a data set of 42 mitochondrial proteins (mainly encoded by the nuclear genome) and performed Bayesian and maximum likelihood analyses. Taxon sampling includes the recently sequenced Thecamonas trahens, a member of the phylogenetically elusive Apusozoa. This data set confirms the relationships of several eukaryotic supergroups seen before and places the eukaryotic root between the monophyletic "unikonts" and "bikonts." We further show that T. trahens branches sister to Opisthokonta with significant statistical support and question the bikont/excavate affiliation of Malawimonas species. The mitochondrial data set developed here (to be expanded in the future) constitutes a unique alternative means in resolving deep eukaryotic relationships.
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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".