Genetic architecture of divergence: the selfing syndrome in <i>Ipomoea lacunosa</i>
Bibliographic record
Abstract
PREMISE: Highly selfing plant species frequently display a distinctive suite of traits termed the selfing syndrome. Here we tested the hypothesis that these traits are grouped into correlated evolutionary modules and determined the degree of independence between such modules. METHODS: We evaluated phenotypic correlations and QTL overlaps in F2 offspring of a cross between the morning glories Ipomoea lacunosa and I. cordatotriloba and investigated how traits clustered into modules at both the phenotypic and genetic level. We then compared our findings to other QTL studies of the selfing syndrome. RESULTS: In the I. lacunosa selfing syndrome, traits grouped into modules that displayed correlated evolution within but not between modules. QTL overlap predicted phenotypic correlations, and QTLs affecting the same trait module were significantly physically clustered in the genome. The genetic architecture of the selfing syndrome varied across systems, but the pattern of stronger within- than between-module correlation was widespread. CONCLUSIONS: The genetic architecture we observe in the selfing syndrome is consistent with a growing understanding of floral morphological integration achieved via pleiotropy in clustered traits. This view of floral evolution is consistent with resource limitation or predation driving the evolution of the selfing syndrome, but invites further research into both the selective causes of the selfing syndrome and how genetic architecture itself evolves in response to changes in mating system.
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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".