<i>Cis-</i>regulatory Variation in Relation to Sex and Sexual Dimorphism in <i>Drosophila melanogaster</i>
Bibliographic record
Abstract
Much of sexual dimorphism is likely due to sex-biased gene expression, which results from differential regulation of a genome that is largely shared between males and females. Here, we use allele-specific expression to explore cis-regulatory variation in Drosophila melanogaster in relation to sex. We develop a Bayesian framework to infer the transcriptome-wide joint distribution of cis-regulatory effects across the sexes. We also examine patterns of cis-regulatory variation with respect to two other levels of variation in sexual dimorphism: (i) across genes that vary in their degree of sex-biased expression and (ii) among tissues that vary in their degree of dimorphism (e.g. relatively low dimorphism in heads vs. high dimorphism in gonads). We uncover evidence of widespread cis-regulatory variation in all tissues examined, with female-biased genes being especially enriched for this variation. A sizeable proportion of cis-regulatory variation is inferred to have sex-specific effects, with sex-dependent cis effects being much more frequent in gonads than in heads. Finally, we find some genes where 1 allele contributes to more than 50% of a gene's expression in heterozygous males but <50% of its expression in heterozygous females. Such variants could provide a mechanism for sex-specific dominance reversals, a phenomenon important for sexually antagonistic balancing selection. However, tissue differences in allelic imbalance are approximately as frequent as sex differences, perhaps suggesting that sexual conflict may not be particularly unique in shaping patterns of expression variation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".