Mitochondrial phylogenomics of liverworts
Bibliographic record
Abstract
Abstract Premise: Liverworts, with approximately 7,300 species worldwide, exhibit remarkable morphological diversity, in terms of growth form, ontogeny and architecture. Based on phylogenetic inferences drawn from DNA data, including recent genomic-scale data, the relationships among families and orders have been constantly revised and refined, although new topological incongruences have emerged. The liverwort mitochondrial genome exhibits lower average substitution rates compared to their nuclear and plastid genomes, and shows less structural variation, suggesting its suitability for inferring relationships at higher taxonomic levels. Methods: The mitochondrial genomes of 112 liverworts were sequenced, covering 105 species, 52 families and 18 orders. We analysed the structures of the liverwort mitogenomes using Mauve alignment. Maximum likelihood and Bayesian inference methods were used to infer a family-level phylogeny of liverworts. Results: We assembled the complete mitochondrial genome for 23 species and identified four new structural variants. Phylogenetic inferences from mitochondrial genome sequences confirmed the monophyly of most suprafamilial taxa, with the expectations of Porellales, Ptilidiales, and Pelliidae. Herzogianthus (Ptilidiales) was well-supported as a sister group to Jungermanniales sensu lato, rather than forming a monophyletic lineage with Ptilidium (Ptilidiales). Given its distinct morphological traits, this genus should be singled out and elevated to a new order. Conclusions: The overall architecture of liverwort mitogenomes remains highly conserved, with taxa that diverged over 470 Mya still having co-linear mitogenomes. This study provides a genetic resource for future evolutionary research across the liverworts and highlights the utility of mitogenome across lineages diversifying for 470 Mya, including for family‐level classification.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".