Sexual selection on non-ornamental traits is underpinned by evidence of genetic constraints on sex-biased expression in dusky pipefish
Bibliographic record
Abstract
Species without dimorphic secondary sex characteristics easily visible to humans, such as difference in size or morphology, are expected to experience low levels of sex-specific selection. However, monomorphism in classic visible traits could be a result of genetic or physiological constraints that prevent the sexes from reaching divergent fitness optima. Additionally, biochemical and molecular work has revealed a variety of less easily observed phenotypes that none-the-less exhibit profound dimorphism. Sex-specific selection could act on these more subtle, less visible, traits. We investigate sex-specific selection in the polygynandrous dusky pipefish (Syngnathus floridae), which lacks size, color, and morphological dimorphism. Using experimental breeding populations, we revealed that although males and females have similar opportunities for sexual selection, only males experience significant sexual selection pressures on body size. We also investigated patterns of sex-biased and sex-specific gene expression in gonads, livers, and gills, and tested whether genes with highly divergent expression patterns between the sexes are more likely to be tissue specific, and therefore relieved of genetic constraints. We. Sex-bias in gene expression was widespread, although the reproductive organs had the most sex-biased and sex-specific genes. Sex-specific selection on gene expression in gills was primarily related to immune response, whereas the liver and gonads had a wide variety of cellular processes, as well as reproductive proteins, showing sex-biased expression. These sex-biased genes are likely less constrained by pleiotropy, as they were more organ-specific in their expression patterns. Altogether, we find evidence for ongoing and historical sex-specific selection in the dusky pipefish.
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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".