Identifying and Characterizing Alternative Molecular Markers for the Symbiotic and Free-Living Dinoflagellate Genus Symbiodinium
Bibliographic record
Abstract
Dinoflagellates in the genus Symbiodinium are best known as endosymbionts of corals and other invertebrate as well as protist hosts, but also exist free-living in coastal environments. Despite their importance in marine ecosystems, less than 10 loci have been used to explore phylogenetic relationships in this group, and only the multi-copy nuclear ribosomal Internal Transcribed Spacer (ITS) regions 1 and 2 have been used to characterize fine-scale genetic diversity within the nine clades (A-I) that comprise the genus. Here, we describe a three-step molecular approach focused on 1) identifying new candidate genes for phylogenetic analysis of Symbiodinium spp., 2) characterizing the phylogenetic relationship of these candidate genes from DNA samples spanning eight Symbiodinium clades (A-H), and 3) conducting in-depth phylogenetic analyses of candidate genes displaying genetic divergences equal or higher than those within the ITS-2 of Symbiodinium clade C. To this end, we used bioinformatics tools and reciprocal comparisons to identify homologous genes from 55,551 cDNA sequences representing two Symbiodinium and six additional dinoflagellate EST libraries. Of the 84 candidate genes identified, 7 Symbiodinium genes (elf2, coI, coIII, cob, calmodulin, rad24, and actin) were characterized by sequencing 23 DNA samples spanning eight Symbiodinium clades (A-H). Four genes displaying higher rates of genetic divergences than ITS-2 within clade C were selected for in-depth phylogenetic analyses, which revealed that calmodulin has limited taxonomic utility but that coI, rad24, and actin behave predictably with respect to Symbiodinium lineage C and are potential candidates as new markers for this group. The approach for targeting candidate genes described here can serve as a model for future studies aimed at identifying and testing new phylogenetically informative genes for taxa where transcriptomic and genomics data are available.
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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 | 0.000 |
| 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) | 0.000 | 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".