An introgression approach to mapping differences in mating success and sperm competitive ability in <i>Drosophila simulans</i> and<i> D. sechellia</i>
Bibliographic record
Abstract
The progeny of Drosophila females doubly-mated to males from the same and a closely related species are mostly sired by conspecific males. We examined the genetic basis for conspecific mating preference and sperm precedence by using 186 Drosophila lines in which random chromosomal fragments of D. sechellia were introgressed into D. simulans. Sperm competition was measured for each of these lines by crossing ebony D. simulans female with ebony D. simulans males followed by wild-type males from the introgressed lines. Variation in sperm competition (proportion of progeny sired by the second male), mating discrimination (proportion of introgressed males that failed to remate), and male fecundity (proportion of progeny sired by introgressed males) were scored. The introgressed lines exhibited highly significant heterogeneity in the three phenotypes scored, motivating an analysis to locate quantitative trait loci (QTLs) responsible for the differences. Applying composite interval mapping, we found eight QTLs that explain a significant level of variation among introgressed lines in the phenotypes scored. Cytological position overlapped among some QTLs suggesting possible pleiotropic effects. Analysis of the joint effects of simulans/sechellia genetic composition at different QTLs and markers suggests that complex interactions among alleles are partially responsible for interspecific differences in sexual traits.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".