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Zhao J, Xu Z, Chen A, You X, Zhao Y, He W, Zhao L, Yang S. Identification of meat from yak and cattle using SNP markers with integrated allele-specific polymerase chain reaction-capillary electrophoresis method. Meat Sci 2018; 148:120-126. [PMID: 30388476 DOI: 10.1016/j.meatsci.2018.08.019] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2017] [Revised: 07/22/2018] [Accepted: 08/24/2018] [Indexed: 10/28/2022]
Abstract
Correct species identification is necessary for meat product quality assurance. Genetic markers are useful tools to accurately determine the animal source of meat products. To better protect yak meat and its products, ten single nucleotide polymorphism (SNP) loci from bovine meat-related genes and one positive control primer set were selected to discriminate meat sourced from yak or cattle. A multiplex allele-specific polymerase chain reaction and capillary electrophoresis method was employed for SNP genotyping. The samples were identified as from yak or cattle based on the number of amplicons. Yak samples generally produced one to three amplicon peaks, and the cattle samples yielded five or more peaks in the electropherogram. This method could be useful to distinguish yak meat from cattle beef, and would protect consumers and yak meat producers.
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Affiliation(s)
- Jie Zhao
- Institute of Quality Standard & Testing Technology for Agro-Products, Key Laboratory of Agro-product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing 100081, China; Key Laboratory of Agrifood Safety and Quality, Ministry of Agriculture of China, Beijing 100081, China
| | - Zhenzhen Xu
- Institute of Quality Standard & Testing Technology for Agro-Products, Key Laboratory of Agro-product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing 100081, China; Key Laboratory of Agrifood Safety and Quality, Ministry of Agriculture of China, Beijing 100081, China
| | - Ailiang Chen
- Institute of Quality Standard & Testing Technology for Agro-Products, Key Laboratory of Agro-product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing 100081, China; Key Laboratory of Agrifood Safety and Quality, Ministry of Agriculture of China, Beijing 100081, China
| | - Xinyong You
- Institute of Quality Standard & Testing Technology for Agro-Products, Key Laboratory of Agro-product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing 100081, China; Key Laboratory of Agrifood Safety and Quality, Ministry of Agriculture of China, Beijing 100081, China
| | - Yan Zhao
- Institute of Quality Standard & Testing Technology for Agro-Products, Key Laboratory of Agro-product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing 100081, China; Key Laboratory of Agrifood Safety and Quality, Ministry of Agriculture of China, Beijing 100081, China
| | - Wenjing He
- Institute of Quality Standard & Testing Technology for Agro-Products, Key Laboratory of Agro-product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing 100081, China; Key Laboratory of Agrifood Safety and Quality, Ministry of Agriculture of China, Beijing 100081, China
| | - Luyao Zhao
- Institute of Quality Standard & Testing Technology for Agro-Products, Key Laboratory of Agro-product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing 100081, China; Key Laboratory of Agrifood Safety and Quality, Ministry of Agriculture of China, Beijing 100081, China
| | - Shuming Yang
- Institute of Quality Standard & Testing Technology for Agro-Products, Key Laboratory of Agro-product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing 100081, China; Key Laboratory of Agrifood Safety and Quality, Ministry of Agriculture of China, Beijing 100081, China.
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Fontanesi L, Scotti E, Gallo M, Nanni Costa L, Dall'Olio S. Authentication of “mono-breed” pork products: Identification of a coat colour gene marker in Cinta Senese pigs useful to this purpose. Livest Sci 2016. [DOI: 10.1016/j.livsci.2015.12.007] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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