Genetic diversity and differentiation in reef-building<i>Millepora</i>species, as revealed by cross-species amplification of fifteen novel microsatellite loci
Bibliographic record
Abstract
Quantifying the genetic diversity in natural populations is crucial to address ecological and evolutionary questions. Despite recent advances in whole-genome sequencing, microsatellite markers have remained one of the most powerful tools for a myriad of population genetic approaches. Here, we used the 454 sequencing technique to develop microsatellite loci in the fire coralMillepora platyphylla, an important reef-builder of Indo-Pacific reefs.We tested the cross-species amplification of these loci in five other species of the genusMilleporaand analysed its success in correlation with the genetic distances between species using mitochondrial 16S sequences. We succeeded in discovering fifteen microsatellite loci in our target speciesM. platyphylla,among which twelve were polymorphic with 2–13 alleles and a mean observed heterozygosity of 0.411. Cross-species amplification in the five otherMilleporaspecies revealed a high probability of amplification success (71%) and polymorphism (59%) of the loci. Our results show no evidence of decreased heterozygosity with increasing genetic distance. However, only one locus enabled measures of genetic diversity in the Caribbean speciesM. complanatadue to high proportions of null alleles for most of the microsatellites. This result indicates that our novel markers may only be useful for the Indo-Pacific species ofMillepora.Measures of genetic diversity revealed significant linkage disequilibrium, moderate levels of observed heterozygosity (0.323–0.496) and heterozygote deficiencies for the Indo-Pacific species. The accessibility to new polymorphic microsatellite markers for hydrozoanMilleporaspecies creates new opportunities for future research on processes driving the complexity of their colonisation success on many Indo-Pacific reefs.
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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 | 0.000 |
| 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".