Selection for low erucic acid and genetic mapping of loci affecting the accumulation of very long-chain fatty acids in meadowfoam seed storage lipids
Bibliographic record
Abstract
Erucic acid (22:113) has been identified as an anti-nutritional compound in meadowfoam ( Limnanthes alba ) and other oilseeds in the Brassicales, a classification which has necessitated the development of low erucic acid cultivars for human consumption. The erucic acid concentrations of meadowfoam wild types (8%–24%) surpass industry standards for human consumption (≤3%). The goals of the present study were to develop low erucic acid lines and identify loci affecting the accumulation of 22:113and other very long-chain fatty acids (VLCFAs) in meadowfoam seed storage lipids. LE76, a low erucic acid line, was developed by 3 cycles of selection in an ethyl methanesulfonate–treated wildtype population. LE76 produced 3% 22:113, threefold less than the M0population. Wildtype × LE76 F2populations produced continuous, approximately normal erucic and dienoic acid distributions. Loss-of-function mutations apparently did not segregate and individuals with low 22:113concentrations (≤3%) were observed only in F2populations from hybrids with L. alba subsp. alba wild types. The meadowfoam genome was mapped and scanned for quantitative trait loci (QTL) affecting VLCFA profiles in seed storage lipids by genotyping and phenotyping wildtype × low erucic acid F2progeny. Composite interval mapping identified 3 moderately large-effect erucic acid QTL. The low erucic acid parent transmitted favorable alleles for 2 of 3 QTL, suggesting low erucic acid cultivars can be developed by combining favorable alleles transmitted by wildtype and low erucic acid parents.
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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 | 0.000 | 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 | 0.000 |
| 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".