GENE DUPLICATION IN THE EVOLUTION OF SEXUAL DIMORPHISM
Bibliographic record
Abstract
Males and females share most of the same genes, so selection in one sex will typically produce a correlated response in the other sex. Yet, the sexes have evolved to differ in a multitude of behavioral, morphological, and physiological traits. How did this sexual dimorphism evolve despite the presence of a common underlying genome? We investigated the potential role of gene duplication in the evolution of sexual dimorphism. Because duplication events provide extra genetic material, the sexes each might use this redundancy to facilitate sex-specific gene expression, permitting the evolution of dimorphism. We investigated this hypothesis at the genome-wide level in Drosophila melanogaster, using the presence of sex-biased expression as a proxy for the sex-specific specialization of gene function. We expected that if sexually antagonistic selection is a potent force acting upon individual genes, duplication will result in paralog families whose members differ in sex-biased expression. Gene members of the same duplicate family can have different expression patterns in males versus females. In particular, duplicate pairs containing a male-biased gene are found more frequently than expected, in agreement with previous studies. Furthermore, when the singleton ortholog is unbiased, duplication appears to allow one of the paralog copies to acquire male-biased expression. Conversely, female-biased expression is not common among duplicates; fewer duplicate genes are expressed in the female-soma and ovaries than in the male-soma and testes. Expression divergence exists more in older than in younger duplicates pairs, but expression divergence does not correlate with protein sequence divergence. Finally, genomic proximity may have an effect on whether paralogs differ in sex-biased expression. We conclude that the data are consistent with a role of gene duplication in fostering male-biased, but not female-biased, gene expression, thereby aiding the evolution of sexual dimorphism.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".