Evolution and classification of hornworts: new insights from the first plastome‐based phylogeny
Bibliographic record
Abstract
Hornworts (Anthocerotophyta) represent a key lineage for understanding fundamental questions in land plant evolution, but their phylogeny and evolutionary history are still not well understood, primarily due to limited genomic resources and insufficient taxon sampling. We conducted comparative genomic analyses of 106 hornwort plastid genomes, including 91 newly generated ones. RNA editing sites were identified by integrating transcriptome data and in silico predictions. Additionally, a new method inspired by marker-capture strategies was proposed to estimate the total number of U-to-C editing sites. Hornwort plastomes are larger than those of liverworts and mosses, with rare gene loss or pseudogenization. Both C-to-U and U-to-C RNA editing occur across all lineages except Leiosporoceros. Diversification rate analyses indicate a major shift between c. 100 and 50 million years ago, possibly linked to the Cretaceous-Paleogene extinction event. Both morphological and molecular evidence support the merging of Folioceros into Anthoceros, and the recognition of two new species in the small genera Paraphymatoceros and Phymatoceros, respectively. This study presents the first large-scale plastome phylogeny of hornworts, introduces a DNA-only method for estimating the number of U-to-C RNA editing sites, and updates the classification. These results contribute broadly to our understanding of early land plant evolution.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".