The relationship between loci for mating system and fitness-related traits in<i>Mimulus</i>(Scrophulariaceae): A test for deleterious pleiotropy of QTLs with large effects
Bibliographic record
Abstract
Loci with large phenotypic effects are generally not thought to be important in the evolution of quantitative traits because of their deleterious pleiotropic effects, yet empirical studies of such pleiotropic effects are lacking. Here I use molecular markers to test the extent of deleterious pleiotropy of quantitative trait loci (QTLs) that have large effects on mating system differences between the wild plants Mimulus guttatus and M. platycalyx (Scrophulariaceae). Six fitness-related traits, namely germination rate (GR), number of nodes (NN), number of flowers (NF), plant height (HT), above-ground biomass (WT), and flowering time (FT) were examined in a growth chamber for a backcross population between M. guttatus and M. platycalyx (with M. platycalyx as recurrent parent). Interval mapping based upon a linkage map consisting of isozyme and random amplified polymorphic DNA (RAPD) markers detected no QTL for fitness-related traits near the mating system QTLs. Single-marker analysis based upon 13 markers flanking the mating system QTLs detected three significant marker-fitness trait associations, and these associations indicate beneficial effects of mating system loci. This suggests that QTLs with large effects on mating system traits do not have significant deleterious pleiotropic effects, and that they could be important factors in adaptive evolution of Mimulus.
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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 | 0.001 | 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 | 0.000 |
| 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".