Major transitions in dinoflagellate evolution unveiled by phylotranscriptomics
Bibliographic record
Abstract
Dinoflagellates are key species in marine environments, but they remain poorly understood in part because of their large, complex genomes, unique molecular biology, and unresolved in-group relationships. We created a taxonomically representative dataset of dinoflagellate transcriptomes and used this to infer a strongly supported phylogeny to map major morphological and molecular transitions in dinoflagellate evolution. Our results show an early-branching position of Noctiluca, monophyly of thecate (plate-bearing) dinoflagellates, and paraphyly of athecate ones. This represents unambiguous phylogenetic evidence for a single origin of the group's cellulosic theca, which we show coincided with a radiation of cellulases implicated in cell division. By integrating dinoflagellate molecular, fossil, and biogeochemical evidence, we propose a revised model for the evolution of thecal tabulations and suggest that the late acquisition of dinosterol in the group is inconsistent with dinoflagellates being the source of this biomarker in pre-Mesozoic strata. Three distantly related, fundamentally nonphotosynthetic dinoflagellates, Noctiluca, Oxyrrhis, and Dinophysis, contain cryptic plastidial metabolisms and lack alternative cytosolic pathways, suggesting that all free-living dinoflagellates are metabolically dependent on plastids. This finding led us to propose general mechanisms of dependency on plastid organelles in eukaryotes that have lost photosynthesis; it also suggests that the evolutionary origin of bioluminescence in nonphotosynthetic dinoflagellates may be linked to plastidic tetrapyrrole biosynthesis. Finally, we use our phylogenetic framework to show that dinoflagellate nuclei have recruited DNA-binding proteins in three distinct evolutionary waves, which included two independent acquisitions of bacterial histone-like proteins.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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".