Single Locus, Multiallelic Inheritance of Erucic Acid Content and Linkage Mapping of <i>FAE1</i> Gene in Yellow Mustard
Bibliographic record
Abstract
ABSTRACT With our objective to develop inbred lines as synthetic components in yellow mustard (Sinapis alba L.), we have isolated different erucic acid variants. The genetic basis of variation in erucic content was investigated using the four variants Y517, Y496, Y1130, and Y514 with high (approximately 50%), medium (approximately 24%), low (approximately 1.4%), and zero (<0.1%) erucic contents, respectively. The segregation of this trait in the BC1F1 and F2 populations of the two crosses Y514 × Y496 and Y514 × Y517 indicated that it was under monogenic control with partial dominance for the high content. To test the allelism of the genes for high, medium, and low erucic contents, crosses were made among Y517, Y496, and Y1130, respectively. The erucic content was also controlled by one gene and no transgressive segregant of zero erucic phenotype was observed in the resulting F2 populations. Therefore, it was concluded that the genes for high, medium, low, and zero erucic contents were different alleles of the same locus. Accordingly, we designated the erucic alleles in Y517, Y496, Y1130, and Y514, as “E1,” “E2,” “E3,” and “e,” respectively. The regional linkage maps of the high erucic gene FAE1.E1 and the medium erucic gene FAE1.E2 were constructed using intron length polymorphism markers. The two genes FAE1.E1 and FAE1.E2 were mapped to the same chromosomal position, further confirming the single locus, multiallelic control of erucic content in yellow mustard.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".