A genome-wide analysis of courting and mating responses in<i>Drosophila melanogaster</i>females
Bibliographic record
Abstract
In Drosophila melanogaster, seminal fluid proteins influence several components of female physiology and behavior, including re-mating rates, ovulation and oviposition, and sperm use. It is well-known that female flies are not simply passive vessels and that female-mediated interactions with male products are important to female (and thus male) reproductive success. While the population genetics, molecular evolution and physiological effects of seminal fluid proteins have been examined, the genetics and evolution of the female side of these post-mating interactions is unexplored in spite of work showing that female genotype and female-by-male genotype interactions are important determinants of sperm competition outcomes. Here we use microarrays to identify candidate genes involved in the female side of post-mating sexual interactions. We report the results of a whole-genome oligonucleotide chip experiment that reveals 23 genes differentially expressed between virgin females exposed and unexposed to courting males, and 38 genes differentially expressed between virgin and recently mated females. Immune related genes are overrepresented among the mating-influenced candidates. We use quantitative reverse-transcriptase PCR to independently assess gene expression changes for roughly half of the mating-affected candidate genes.
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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".