Single-cell transcriptomics using spliced leader PCR: Evidence for multiple losses of photosynthesis in polykrikoid dinoflagellates
Bibliographic record
Abstract
BACKGROUND: Most microbial eukaryotes are uncultivated and thus poorly suited to standard genomic techniques. This is the case for Polykrikos lebouriae, a dinoflagellate with ultrastructurally aberrant plastids. It has been suggested that these plastids stem from a novel symbiosis with either a diatom or haptophyte, but this hypothesis has been difficult to test as P. lebouriae dwells in marine sand rife with potential genetic contaminants. RESULTS: We applied spliced-leader targeted PCR (SLPCR) to obtain dinoflagellate-specific transcriptomes on single-cell isolates of P. lebouriae from marine sediments. Polykrikos lebouriae expressed nuclear-encoded photosynthetic genes that were characteristic of the peridinin-plastids of dinoflagellates, rather than those from a diatom of haptophyte. We confirmed these findings at the genomic level using multiple displacement amplification (MDA) to obtain a partial plastome of P. lebouriae. CONCLUSION: From these data, we infer that P. lebouriae has retained the peridinin plastids ancestral for dinoflagellates as a whole, while its closest relatives have lost photosynthesis multiple times independently. We discuss these losses with reference to mixotrophy in polykrikoid dinoflagellates. Our findings demonstrate new levels of variation associated with the peridinin plastids of dinoflagellates and the usefulness of SLPCR approaches on single cell isolates. Unlike other transcriptomic methods, SLPCR has taxonomic specificity, and can in principle be adapted to different splice-leader bearing groups.
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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".