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In the meat industry, correct labeling of beef origins or breed is required to assure quality and safety. This paper describes the development of discrimination markers between Japanese domestic and imported beef from the United States (US) and Australia (AUS) based on a bovine 50K single nucleotide polymorphism (SNP) array using a total of 110 samples: Japanese Black (n = 50), Japanese Holstein (n = 50) and US cattle (n = 10). Genotyping information revealed 1081 SNPs as candidate markers that were polymorphic only in US cattle. The genotyping results by PCR-restriction length polymorphism in Japanese Black (n = 300) and Holstein cattle (n = 146) revealed that 11 SNPs had alleles specific to US cattle. Their allelic frequencies in US cattle (n = 108) ranged from 0.097 to 0.250 with an average of 0.178 and the combined identification probability of US cattle was 0.987. In addition, we also verified the applicability of these US-specific markers to AUS cattle. Their allelic frequencies in AUS cattle (n = 280) ranged from 0.063 to 0.224 with an average of 0.137 and the combined identification probability of AUS cattle was 0.963. In conclusion, a set of these markers could be useful for discriminating between Japanese domestic and imported beef and would contribute to identify origins and prevent falsified labeling of beef.

Differences between average allelic frequencies of genes that relate to traits suggest that it would be evidence of artificial selections. Sliding window approach is a useful method to identify genomic regions that have been differently selected between two breeds. The objective of this study was to identify the divergently selected regions between Japanese Black (JB) and Japanese Holstein (JH) cattle based on genotypic information obtained through a high-density single nucleotide polymorphism (SNP) panel. After genotyping of 54 001 SNP markers on 100 animals (50 JB and 50 JH), 40 635 SNPs were suitable for the analysis. For each of these SNPs, the absolute difference between allelic frequencies of JB and JH was calculated. In the current study, 10 consecutive SNPs were defined as components of a window. For each window, the average difference in allelic frequency was calculated. This was termed sliding window average difference (SWAD). Among 40 055 windows, we focused on 39 windows with the largest SWAD. This was equivalent to 0.1% of all windows and the SWAD was more than 0.435. Some of these windows overlapped and were distributed in 11 regions. These regions were in good agreement with reported quantitative trait locus, therefore would be selection signatures and good candidates that harbor the causative mutations.

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