Organellar Genomes of Three Globally Important Nanoplanktonic Diatoms Refine Their Taxon‐Specific Distribution and Succession Patterns in the Northwest Atlantic
Bibliographic record
Abstract
Nanoplanktonic diatoms (2-20 μm) are a significant yet historically understudied component of marine ecosystems. We investigated three recently isolated nanoplanktonic diatoms from the Northwest Atlantic Ocean (NWA): Minidiscus spinulatus, Mediolabrus comicus, and Minidiscus trioculatus. Using Oxford Nanopore sequencing, we assembled and annotated their complete chloroplast and mitochondrial genomes. Pangenome analyses revealed that Minidiscus species consistently clustered more closely with select Thalassiosira species, whereas M. comicus formed a sister clade with Skeletonema. Circularized chloroplast genomes allowed us to characterize the full-length 16S ribosomal RNAs for each isolate, thereby leading to higher resolution of these taxa in preexisting 16S metabarcoding data. During our study, M. spinulatus was primarily restricted to the Bedford Basin. In contrast, both M. trioculatus and M. comicus had larger geographic ranges extending to the Labrador Sea, and in the case of M. comicus, to the Canadian Arctic Gateway. Weekly metabarcoding from the coastal Bedford Basin, N.S., Canada (2014-2022), revealed a seasonal succession of nanoplanktonic taxa, with Minidiscus trioculatus dominating in the early months, followed by M. comicus and M. spinulatus. Our results highlight the critical value of phytoplankton isolations and organelle genomics for expanding our understanding of the diversity and biogeography of nanoplanktonic diatoms.
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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 | 0.001 | 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 | 0.000 |
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".