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Record W2992442581 · doi:10.3390/ani9121090

A Functional 3′ UTR Polymorphism of FADS2 Affects Cow Milk Composition through Modifying Mir-744 Binding

2019· article· en· W2992442581 on OpenAlexaff
Mingxun Li, Xubin Lu, Qisong Gao, Mengqi Wang, Abdelaziz Adam Idriss Arbab, Yujia Sun, Zhi Chen, Huimin Zhang, Niel A. Karrow, Zhangping Yang, Yongjiang Mao

Bibliographic record

VenueAnimals · 2019
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsUniversity of Guelph
FundersChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsFADS2Linoleic acidAlleleGenotypeBiologyFatty acid desaturaseChemistryMolecular biologyPolyunsaturated fatty acidBiochemistryGeneFatty acid

Abstract

fetched live from OpenAlex

This study determined the associations of FADS2 c.1571G>A with milk FAs content and revealed that cows with the GG genotype had improved levels of delta-6 desaturase substrates (linoleic acid, C18:2n-6; p < 0.001) and decreased levels of desaturase products (gamma-linolenic acid, C18:3n-6; p < 0.001), indicating a reduction in FADS2 expression or delta-6 desaturase activity caused by this polymorphism. Computer alignment demonstrated that c.1571G>A occurred within a potential miR-744 binding site. When the c.1571G allele was present, the luciferase activity of reporter constructs was significantly suppressed by miR-744, while no such effect was observed with the A allele. Overexpression of miR-744 in bovine mammary epithelial cells (with the 1571GG genotype) downregulated FADS2 expression at both mRNA and protein levels. In contrast, inhibition of endogenous miR-744 with a specific inhibitor dramatically upregulated FADS2 expression. Taken together, these lines of evidence indicated that the c.1571A minor allele abolished the ability of miR-744 to bind FADS2, with a consequent increase in FADS2 expression levels and synthesis of omega-6 LC-PUFAs.

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)0.000
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 score0.121
Threshold uncertainty score0.763

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.050
GPT teacher head0.315
Teacher spread0.265 · 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

Citations14
Published2019
Admission routes1
Has abstractyes

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