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http://dx.doi.org/10.5713/ajas.16.0263

Detection of superior genotype of fatty acid synthase in Korean native cattle by an environment-adjusted statistical model  

Lee, Jea-Young (Department of Statistics, Yeungnam University)
Oh, Dong-Yep (Livestock Research institute)
Kim, Hyun-Ji (Department of Statistics, Yeungnam University)
Jang, Gab-Sue (Department of Life Sciences, Yeungnam University)
Lee, Seung-Uk (Department of Civil and Environmental Engineering, National University of Singapore)
Publication Information
Asian-Australasian Journal of Animal Sciences / v.30, no.6, 2017 , pp. 765-772 More about this Journal
Abstract
Objective: This study examines the genetic factors influencing the phenotypes (four economic traits:oleic acid [C18:1], monounsaturated fatty acids, carcass weight, and marbling score) of Hanwoo. Methods: To enhance the accuracy of the genetic analysis, the study proposes a new statistical model that excludes environmental factors. A statistically adjusted, analysis of covariance model of environmental and genetic factors was developed, and estimated environmental effects (covariate effects of age and effects of calving farms) were excluded from the model. Results: The accuracy was compared before and after adjustment. The accuracy of the best single nucleotide polymorphism (SNP) in C18:1 increased from 60.16% to 74.26%, and that of the two-factor interaction increased from 58.69% to 87.19%. Also, superior SNPs and SNP interactions were identified using the multifactor dimensionality reduction method in Table 1 to 4. Finally, high- and low-risk genotypes were compared based on their mean scores for each trait. Conclusion: The proposed method significantly improved the analysis accuracy and identified superior gene-gene interactions and genotypes for each of the four economic traits of Hanwoo.
Keywords
Adjusted Model; Analysis of Covariance (ANCOVA) Model; Environmental Factor; Fatty Acid Synthase; Genetic Factor;
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Times Cited By KSCI : 2  (Citation Analysis)
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