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Genome-association analysis of Korean Holstein milk traits using genomic estimated breeding value.


ABSTRACT: OBJECTIVE:Holsteins are known as the world's highest-milk producing dairy cattle. The purpose of this study was to identify genetic regions strongly associated with milk traits (milk production, fat, and protein) using Korean Holstein data. METHODS:This study was performed using single nucleotide polymorphism (SNP) chip data (Illumina BovineSNP50 Beadchip) of 911 Korean Holstein individuals. We inferred each genomic estimated breeding values based on best linear unbiased prediction (BLUP) and ridge regression using BLUPF90 and R. We then performed a genome-wide association study and identified genetic regions related to milk traits. RESULTS:We identified 9, 6, and 17 significant genetic regions related to milk production, fat and protein, respectively. These genes are newly reported in the genetic association with milk traits of Holstein. CONCLUSION:This study complements a recent Holstein genome-wide association studies that identified other SNPs and genes as the most significant variants. These results will help to expand the knowledge of the polygenic nature of milk production in Holsteins.

SUBMITTER: Shin D 

PROVIDER: S-EPMC5337909 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Genome-association analysis of Korean Holstein milk traits using genomic estimated breeding value.

Shin Donghyun D   Lee Chul C   Park Kyoung-Do KD   Kim Heebal H   Cho Kwang-Hyeon KH  

Asian-Australasian journal of animal sciences. 20151005 3


<h4>Objective</h4>Holsteins are known as the world's highest-milk producing dairy cattle. The purpose of this study was to identify genetic regions strongly associated with milk traits (milk production, fat, and protein) using Korean Holstein data.<h4>Methods</h4>This study was performed using single nucleotide polymorphism (SNP) chip data (Illumina BovineSNP50 Beadchip) of 911 Korean Holstein individuals. We inferred each genomic estimated breeding values based on best linear unbiased predictio  ...[more]

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