Sequence analysis of single-copy genes in two wild olive subspecies: nucleotide diversity and potential use for testing admixture
Bibliographic record
Abstract
The wild olive distribution extends from the Mediterranean region to south Asia and Austral Africa. The species is also invasive, particularly in Australia. Here, we investigated the sequence variation at five nuclear single-copy genes in 41 native and invasive accessions of the Mediterranean and African olive subspecies. The nucleotide diversity was assessed and the phylogenetic relationships between alleles were depicted with haplotype networks. A Bayesian clustering method (STRUCTURE) was applied to identify the main gene pools. We found an average of 18.4 alleles per locus. Native Mediterranean and African olives only share one allele, which testifies for ancient admixture on the Red Sea hills. The presence of divergent alleles in the Mediterranean olive, as well as the identification of two main genetic clusters, suggests a complex origin with two highly differentiated gene pools from the eastern and western Mediterranean that recently admixed. In the invasive range, relatively high nucleotide diversity is observed as a consequence of the introduction of alleles from two subspecies. Our data confirm that four invasive individuals are early-generation hybrids. Finally, the utility of single-copy gene sequences in olive population genomic and phylogenetic studies is briefly discussed.
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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 | 0.000 |
| 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".