Genome Evolution of a Tertiary Dinoflagellate Plastid
Bibliographic record
Abstract
The dinoflagellates have repeatedly replaced their ancestral peridinin-plastid by plastids derived from a variety of algal lineages ranging from green algae to diatoms. Here, we have characterized the genome of a dinoflagellate plastid of tertiary origin in order to understand the evolutionary processes that have shaped the organelle since it was acquired as a symbiont cell. To address this, the genome of the haptophyte-derived plastid in Karlodinium veneficum was analyzed by Sanger sequencing of library clones and 454 pyrosequencing of plastid enriched DNA fractions. The sequences were assembled into a single contig of 143 kb, encoding 70 proteins, 3 rRNAs and a nearly full set of tRNAs. Comparative genomics revealed massive rearrangements and gene losses compared to the haptophyte plastid; only a small fraction of the gene clusters usually found in haptophytes as well as other types of plastids are present in K. veneficum. Despite the reduced number of genes, the K. veneficum plastid genome has retained a large size due to expanded intergenic regions. Some of the plastid genes are highly diverged and may be pseudogenes or subject to RNA editing. Gene losses and rearrangements are also features of the genomes of the peridinin-containing plastids, apicomplexa and Chromera, suggesting that the evolutionary processes that once shaped these plastids have occurred at multiple independent occasions over the history of the Alveolata.
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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 | 0.000 |
| 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) | 0.001 | 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".