Development and characterization of chloroplast microsatellite markers in<i>Macaranga</i>(Euphorbiaceae)
Bibliographic record
Abstract
As part of our study on the phylogeography of the ant-plant genus Macaranga, we have screened for polymorphic regions in the chloroplast genome. Initially, ten universal PCR primer pairs targeted at chloroplast microsatellite loci were applied to a small set of specimens, covering various taxonomic levels from intrafamilial to intraspecific. Eight primer pairs produced PCR fragments that behaved as single and discrete bands on agarose gels. The five most promising candidate pairs were further analysed with an extended set of DNA templates, and PCR products were separated on sequencing gels. The number of size variants per locus varied from two to eight, combining into 17 haplotypes among 29 Macaranga accessions from 10 species. Comparative sequencing demonstrated that microsatellites were responsible for the observed size variation at three of five loci, whereas variation at the other loci was caused by larger insertions and (or) deletions (indels). In addition to poly(A) and poly(T) repeats, which are typically found in chloroplast DNA, we also identified a variable (CT)n repeat, with n = 4 to n = 8. Sequencing revealed three examples of size homoplasy, one of which was caused by a single base substitution that raised the actual number of haplotypes to 18. Relationships between haplotypes were assessed by phenetic analyses of size variants and by constructing a parsimony network based on sequence variation. For both types of analysis, the distribution of haplotypes correlated with geographically circumscribed regions rather than with taxonomic boundaries.
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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) | 0.000 | 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".