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Novel SNP in 5′ flanking region of <i>EDG1</i> associated with marbling in Japanese Black beef cattle

2009· article· en· W1983621792 on OpenAlexaff
Takahisa Yamada, Seiki Sasaki, Shin Sukegawa, Takeshi Miyake, Tatsuo Fujita, Hiroyuki Kose, Mitsuo MORITA, Youichi Takahagi, Hiroshi Murakami, Fumiki Morimatsu, Yoshiyuki Sasaki

Bibliographic record

VenueAnimal Science Journal · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid metabolism and biosynthesis
Canadian institutionsConestoga Meat Packers (Canada)
FundersJapan Society for the Promotion of Science
KeywordsMarbled meatSingle-nucleotide polymorphismSNPBiologyBeef cattleGeneticsThree prime untranslated regionIntramuscular fatPopulationUntranslated regionGeneGenotypeAnimal scienceMedicineMessenger RNA

Abstract

fetched live from OpenAlex

Marbling, defined by the amount and distribution of intramuscular fat, is an economically important trait of beef cattle in Japan. The endothelial differentiation, sphingolipid G-protein-coupled receptor, 1 (EDG1) gene has been considered as a positional functional candidate for the gene responsible for marbling. We have recently reported that 2 single nucleotide polymorphisms (SNPs), c.-312A>G in the 5' untranslated region (UTR) and c.*446G>A in the 3' UTR in EDG1 were associated with marbling in Japanese Black beef cattle, but this was not functional and a causal mutation for marbling. In the present study, we detected 2 novel SNPs, referred to as g.1475435G>A and g.1471620G>T, in the 5' flanking region of the EDG1 between low-marbled and high-marbled steer groups, which were previously shown to have EDG1 expression differences in musculus longissimus muscle. The g.1475435G>A SNP seemed not to segregate in Japanese Black beef cattle. The g.1471620G>T SNP was associated with the predicted breeding value for beef marbling standard number by the analyses using Japanese Black beef cattle population. Based on these findings, we hypothesized that the g.1471620G>T SNP might have an impact on EDG1 expression and also marbling.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.633
Threshold uncertainty score0.277

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 head0.018
GPT teacher head0.254
Teacher spread0.236 · 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

Citations24
Published2009
Admission routes1
Has abstractyes

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