A predominant role of genotypic variation in both expression of sperm competition genes and paternity success in<i>Drosophila melanogaster</i>
Bibliographic record
Abstract
Sperm competition is a crucial aspect of male reproductive success in many species, includingDrosophila melanogaster,and seminal fluid proteins (Sfps) can influence sperm competitiveness. However, the combined effect of environmental and genotypic variation on sperm competition gene expression remains poorly understood. Here, we usedDrosophilaGenetic Reference Panel (DGRP) inbred lines and manipulated developmental population density (i.e. larval density) to test the effects of genotype, environment and genotype-by-environment interactions (GEI) on the expression of the known sperm competition genesSex Peptide,Acp36DEandCG9997. High larval density resulted in reduced adult body size, but expression of sperm competition genes remained unaffected. Furthermore, we found no significant GEI but genotypic effects in the expression ofSPandAcp36DE. Our results also revealed GEI for relative competitive paternity success (second male paternity; P2), with genes’ expression positively correlated with P2. Given the effect of genotype on the expression of genes, we conducted a genome-wide association study (GWAS) and identified polymorphisms in putativecis-regulatory elements as predominant factors regulating the expression ofSPandAcp36DE. The association of genotypic variation with sperm competition outcomes, and the resilience of sperm competition genes’ expression against environmental challenges, demonstrates the importance of genome variation background in reproductive fitness.
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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".