Prevalence of isomeric plastomes and effectiveness of plastome super-barcodes in yews (Taxus) worldwide
Bibliographic record
Abstract
Taxus (yew) is both the most species-rich and taxonomically difficult genus in Taxaceae. To date, no study has elucidated the complexities of the plastid genome (plastome) or examined the possibility of whole plastomes as super-barcodes across yew species worldwide. In this study, we sequenced plastomes from two to three individuals for each of the 16 recognized yew species (including three potential cryptics) and Pseudotaxus chienii. Our comparative analyses uncovered several gene loss events that independently occurred in yews, resulting in a lower plastid gene number than other Taxaceous genera. In Pseudotaxus and Taxus, we found two isomeric arrangements that differ by the orientation of a 35 kb fragment flanked by "trnQ-IRs". These two arrangements exist in different ratios within each sampled individual, and intraspecific shifts in major isomeric arrangements are first reported here in Taxus. Moreover, we demonstrate that entire plastomes can be used to successfully discriminate all Taxus species with 100% support, suggesting that they are useful as super-barcodes for species identification. We also propose that accD and rrn16-rrn23 are promising special barcodes to discriminate yew species. Our newly developed Taxus plastomic sequences provide a resource for super-barcodes and conservation genetics of several endangered yews and serve as comprehensive data to improve models of plastome complexity in Taxaceae as a whole and authenticate Taxus species.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".