A supergene in seaweed flies modulates male traits and female perception
Bibliographic record
Abstract
Summary Supergenes, tightly linked allelic combinations that underlie complex adaptive phenotypes represent a critical mechanism protecting intra-specific polymorphism [1, 2]. Supergenes represent some of the best examples of balancing selection in nature and there is increasing evidence that disassortative mating, when individuals preferentially mate with dissimilar phenotypes, is a key force stabilizing supergene polymorphisms. Yet, the underlying biological mechanisms and genetic basis of disassortative mating remain poorly known. Here, we examine a possible mechanism of disassortative mating driven by female mate choice in relation to the overdominant Cf-Inv(1) supergene in the seaweed fly Coelopa frigida by investigating chemical communication and its genomic architecture. We show that Cf-Inv(1) strongly affects chemical signaling; cuticular hydrocarbon (CHC) composition differed between genotypes in males but not females across two continents. In tandem, Cf-Inv(1) affected female perception of these compounds; females are able to sense 36 compounds from the male CHC cocktail but show differential perception between genotypes for almost half of them. This indicates that the genetic underpinnings of male traits and female perceptions are tightly linked within Cf-Inv(1) which likely facilitates disassortative mating [3]. A differential expression approach based on candidate genes for CHC biosynthesis and odorant detection revealed differential expression for CHC biosynthesis in males alone but broad changes in odorant receptors across both sexes. Furthermore, odorant genes clustered together within Cf-Inv(1) , with some of them differing between arrangements by 8.3% at the protein level, suggesting evolution via tandem duplication then divergence. We propose that the tight linkage between overdominant loci, male traits, and female perception has helped to maintain the Cf-Inv(1) polymorphism across its range in the face of supergene degeneration.
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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 | 0.000 | 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) | 0.001 | 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".