Complete plastome sequences from <i>Bertholletia excelsa</i> and 23 related species yield informative markers for Lecythidaceae
Bibliographic record
Abstract
Abstract Premise of the study: The tropical tree family Lecythidaceae has enormous ecological and economic importance in the Amazon basin. Lecythidaceae species can be difficult to identify without molecular data, however, and phylogenetic relationships within and among the most diverse genera are poorly resolved. Methods: To develop informative genetic markers for Lecythidaceae, we used genome skimming to assemble de novo the full plastome of the Brazil nut tree (Bertholletia excelsa) and 23 other Lecythidaceae species. Indices of nucleotide diversity and phylogenetic signal were used to identify regions suitable for genetic marker development. Results: The B. excelsa plastome contained 160,472 bp and was arranged in a quadripartite structure. Using the 24 plastome alignments, we developed primers for 10 coding and non-coding DNA regions containing exceptional nucleotide diversity and phylogenetic signal. We additionally developed 19 chloroplast simple sequence repeats (cpSSRs) for population-level studies. Discussion: The coding region ycf1 and the spacer rpl16-rps3 outperformed plastid DNA markers previously used for barcoding and phylogenetics. Used in a phylogenetic analysis, the matrix of 24 plastomes showed with 100% bootstrap support that Lecythis and Eschweilera are polyphyletic. The plastomes and primers presented in this study will facilitate a broad array of ecological and evolutionary studies in Lecythidaceae.
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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 | 0.001 |
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".