Development of microsatellite loci from a reference genome for the Neotropical butterfly <i><scp>H</scp>eliconius numata</i> and its close relatives
Bibliographic record
Abstract
Abstract The Neotropical butterfly Heliconius numata (Lepidoptera: Nymphalidae: Heliconiinae) is known for its striking diversity of wing color patterns driven by the Müllerian mimicry of multiple local models and controlled by a single supergene locus. Such fine‐scale variation of traits under strong selection offers a unique opportunity for the study of the ecology and genetics of adaptation. However, little is still known of the population processes driving geographical variation in wing‐pattern phenotypes. We report the characterization of 26 microsatellite markers for the butterfly H. numata, including six located inside the wing color‐pattern supergene region. All markers are polymorphic, with allele numbers ranging from 2 to 21 per locus, an observed heterozygosity of 0.111 to 0.848 and an expected heterozygosity of 0.126 to 0.942. A subset of 18 of these markers was tested on five closely related sympatric Heliconius species with an amplification success ranging from 88% to 94%. The obtained set of microsatellite markers provides a new and useful set of tools to investigate patterns of differentiation and selection in populations of mimetic Heliconius butterflies. Moreover, markers developed within the color‐pattern supergene will facilitate characterization of the association between the genetic architecture and the functional diversity of wing patterns. Finally, the cross‐species amplification success of the described markers extends their utility to also encompass comparative population genetic studies of closely related species within a clade of rapidly diversifying 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 | 0.001 | 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) | 0.002 | 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".