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Record W1881546577 · doi:10.4238/2015.october.21.4

Single nucleotide polymorphisms of Δ6-desaturase and Elovl5 segments and their associations with common carp (Cyprinus carpio) growth traits

2015· article· en· W1881546577 on OpenAlexaff
Hong Ren, Jing Yu, Pan Xu, Yongkai Tang

Bibliographic record

VenueGenetics and Molecular Research · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsMinistry of Agriculture
FundersEducation Department of Henan ProvinceHenan UniversityHenan University of Science and Technology
KeywordsCommon carpBiologyCyprinusIntronGeneticsSingle-nucleotide polymorphismGeneSNPCarpGenotypeFisheryFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Highly unsaturated fatty acids (HUFAs) are crucial for the nutritional health, physiology, and reproduction of vertebrates. The Δ6-desaturase and Elovl5 elongase genes produce essential enzymes in the biosynthetic pathway of HUFAs. Single nucleotide polymorphism (SNP) analysis of genes functionally related to the growth traits of the common carp (Cyprinus carpio var. Jian) can provide useful information for common carp molecular breeding. In this study, we isolated two Δ6 Fad genes and two Elovl5 genes from the common carp. Polymerase chain reaction-restriction fragment length polymorphism was performed, and the genotypes of three SNPs (Δ6Fad-a intron 10_C73T, Δ6Fad-b intron 10_A56G, and Elovl5-a intron 5_C64A) in 712 individuals (383 females and 329 males) were detected. Correlation analysis between the genotypes and weight gain revealed that intron 10_C73T of Δ6Fad-a, intron 10_A56G of Δ6Fad-b, and intron 5_ C64A of Elovl5-a were significantly associated with common carp weight gain. Weight gain increased with the enrichment of molecular SNP markers, consistent with the characteristics of quantitative traits. Our results indicate that Δ6Fad and Elovl5 elongase genes could be candidate genes for the molecular breeding of the common carp. This study provides useful information for the improvement of this species.

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 score0.392
Threshold uncertainty score0.178

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)0.0000.000

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 head0.054
GPT teacher head0.275
Teacher spread0.221 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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