Phylogenetic Analyses of Nuclear, Mitochondrial, and Plastid Multigene Data Sets Support the Placement of Mesostigma in the Streptophyta
Bibliographic record
Abstract
All extant green plants belong to 1 of 2 major lineages, commonly known as the Chlorophyta (most of the green algae) and the Streptophyta (land plants and their closest green algal relatives). The scaly green flagellate Mesostigma viride has an important place in the debate on the origin of green plants. However, there have been conflicting results from molecular systematics as to whether Mesostigma diverges before the Chlorophyta/Streptophyta split or is an early diverging flagellate member of the Streptophyta. Previous studies employed either a limited taxon sampling (plastid and mitochondrial genomes) or a small number of phylogenetically informative sites (single nuclear genes). Here, we use large data sets from the nuclear (125 proteins; 29,319 positions), mitochondrial (33 proteins; 6,622 positions), and plastid (50 proteins; 10,137 positions) genomes with an expanded taxon sampling (21, 13, and 28 species, respectively) to reevaluate the phylogenetic position of Mesostigma. Our study supports the placement of Mesostigma in the Streptophyta (as an early diverging lineage) and provides evidence that systematic biases have played a role in generating some of the previous conflicting results. Importantly, we demonstrate that using an increased taxon sampling as well as more realistic models of evolution allows increasing congruence among the nuclear, mitochondrial, and plastid data sets.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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 | 0.001 |
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".