Analysis of EST data of the marine protist Oxyrrhis marina, an emerging model for alveolate biology and evolution
Bibliographic record
Abstract
BACKGROUND: The alveolates include a large number of important lineages of protists and algae, among which are three major eukaryotic groups: ciliates, apicomplexans and dinoflagellates. Collectively alveolates are present in virtually every environment and include a vast diversity of cell shapes, molecular and cellular features and feeding modes including lifestyles such as phototrophy, phagotrophy/predation and intracellular parasitism, in addition to a variety of symbiotic associations. Oxyrrhis marina is a well-known model for heterotrophic protist biology, and is now emerging as a useful organism to explore the many changes that occurred during the origin and diversification of dinoflagellates by virtue of its phylogenetic position at the base of the dinoflagellate tree. RESULTS: We have generated and analysed expressed sequence tag (EST) sequences from the alveolate Oxyrrhis marina in order to shed light on the evolution of a number of dinoflagellate characteristics, especially regarding the emergence of highly unusual genomic features. We found that O. marina harbours extensive gene redundancy, indicating high rates of gene duplication and transcription from multiple genomic loci. In addition, we observed a correlation between expression level and copy number in several genes, suggesting that copy number may contribute to determining transcript levels for some genes. Finally, we analyze the genes and predicted products of the recently discovered Dinoflagellate Viral Nuclear Protein, and several cases of horizontally acquired genes. CONCLUSION: The dataset presented here has proven very valuable for studying this important group of protists. Our analysis indicates that gene redundancy is a pervasive feature of dinoflagellate genomes, thus the mechanisms involved in its generation must have arisen early in the evolution of the group.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".