Genome‐wide identification of <i>FAD</i> gene family and functional analysis of <i>MsFAD3.1</i> involved in the accumulation of α‐linolenic acid in alfalfa
Bibliographic record
Abstract
Abstract As an important forage legume in the world, alfalfa (Medicago sativa L.) has high adaptability to various unfavorable climatic conditions and high biomass, and have been playing critical roles in animal husbandry and industrial applications. As α‐linolenic acid cannot be synthesized by animals, and most must be obtained from plants, the increasing of α‐linolenic acid content in alfalfa will greatly contribute to improve quality of livestock. However, the molecular mechanisms for α‐linolenic acid synthesis and accumulation in alfalfa are still limited. In this study, the importance of ω‐3 fatty acid desaturase (FAD) was demonstrated by analyzing α‐linolenic acid metabolic pathways, combined with the dynamics of accumulation of unsaturated fatty acids in alfalfa. Moreover, the FAD3.1 identified in alfalfa was located in the endoplasmic reticulum, and its expression level was consistent with the accumulation patterns of α‐linolenic acid in leaves. Heterologous expression in yeast cells proves that MsFAD3.1 was involved in the synthesis of α‐linolenic acid, and the α‐linolenic acid content in MsFAD3.1‐overexpression transgenic alfalfa lines was significantly increased. These results indicate that new alfalfa germplasm with high α‐linolenic acid content can be successfully created through biotechnology, providing a theoretical basis for further improving the quality of alfalfa and the nutritional value of dairy products.
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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 | 0.001 |
| 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) | 0.001 | 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".