The biological basis of epistasis between quantitative trait loci for flavone and 3-deoxyanthocyanin synthesis in maize (<i>Zea mays</i>L.)
Bibliographic record
Abstract
A major weakness in our understanding of the genetic basis of complex traits has been that of defining the extent and biological basis of epistasis. Our research group has been studying the genetic control of the accumulation of maysin, a C-glycosyl flavone, in maize, Zea mays (L.), silks. Previously, we demonstrated the importance of the p1 locus as a QTL for maysin synthesis. The p1 locus often exhibits significant epistatic interactions with other loci. We developed a mapping population, (W23al x GT119)F2, specifically designed to test whether genes in an intersecting pathway might be detected as QTLs for maysin synthesis and result in epistatic interaction effects. The a1 gene is not required for the synthesis of flavones but is required for the synthesis of 3-deoxyanthocyanins, an intersecting pathway, in maize silks. The p1 locus (P < 0.0001) was a QTL for both flavones and 3-deoxyanthocyanins. The a1 locus was also highly significant (P < 0.0001) for both traits, as was the p1 x a1 epistatic interaction (P < 0.0001). Our results demonstrate that altering the flux of biochemical intermediates between pathways may be the biological basis of major QTL effects and epistatic interactions.
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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".