Novel genetic association with migratory diapause in Australian monarch butterflies
Bibliographic record
Abstract
Abstract Background Monarch butterflies (Danaus plexippus) are a charismatic and culturally important North American butterfly species famous for their unique, dramatic migratory life history. While non-migratory populations of the species are widespread and apparently stable, migratory populations in North America have recently seen declines, prompting concern that the migratory phenomenon in North America may be at risk of disappearing. In contrast, a relatively recently-established monarch population in Australia has rapidly re-acquired a migratory life history following hundreds of generations of residency and successive bottlenecks as the species island-hopped across the Pacific during the late 1800s and early 1900s. The process by which migration re-emerged in Australian monarchs is not currently known. Results We raised and sequenced individuals from Queensland, Australia under environmental conditions associated with migration initiation and found strong variance in reproductive diapause, a key migratory trait, between families which was associated with variation at the spectrin beta chain protein Karst. This protein is known to be involved in diapause termination in monarchs but has not previously been identified as associated with migratory life history variance. The most strongly associated migratory SNPs are also present at a low frequency in North America, suggesting that the Australian population is leveraging standing variation which persisted across repeated bottlenecks as Monarchs spread across the Pacific. Conclusions Our results provide an intriguing example of how the temporary loss of migration—in this case likely over hundreds of generations—may not entail the loss of genetic variation associated with this complex life history strategy.
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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) | 0.002 | 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".