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Record W3091225033 · doi:10.1002/csc2.20362

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

2020· article· en· W3091225033 on OpenAlexaff
Zhengshe Zhang, Jiyu Zhang, Wenxian Liu

Bibliographic record

VenueCrop Science · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid metabolism and biosynthesis
Canadian institutionsInnovation, Science and Economic Development Canada
Fundersnot available
KeywordsBiologyLinolenic acidGermplasmFatty acidBiochemistryalpha-Linolenic acidFood scienceBotanyPolyunsaturated fatty acidLinoleic acid

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score0.202

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.042
GPT teacher head0.273
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations22
Published2020
Admission routes1
Has abstractyes

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