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Updated: Feb 8, 2026

Infinium Assay for Large-scale SNP Genotyping Applications
Published on: November 19, 2013
Selection and effectiveness of informative SNPs for paternity in Chinese Simmental cattle based on a high-density SNP
Tianliu Zhang1, Liping Guo1, Mingyan Shi2
1Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, PR China.
Abstract:
Incorrect paternity assignment in cattle can significantly influence the accuracy of genetic evaluation. Recent advances in high-throughput technology have facilitated the identification of single nucleotide polymorphism (SNP) markers and their applications for filiation and individual identification. We genotyped 1074 bulls from a reference population of Chinese Simmental cattle for genomic selection using a BovineSNP770K BeadChip. Among them, a total of 136 bulls were randomly selected to design a suitable low-density SNP panel for paternity testing in Simmental cattle. Our results showed that 50 SNPs were determined to be the most informative markers in parental testing, with an accuracy of 99.89% for CPE (cumulative probability of exclusion) in the unknown female parent case. The 50 highly informative SNP markers were distributed across 25 chromosomes, and the mean intermarker distance per chromosome was 26.72 Mb. The average minor allele frequency (MAF), expected heterozygosity (HE), and polymorphic information content (PIC) values were 0.3748, 0.4998, and 0.4818, respectively. Finally, the 50 identified SNPs were used to estimate paternity for the remaining 938 of 1074 bulls from 23 farms. Our results revealed that 76.75% of the 938 bulls were assigned parentage to the pedigree sires with 95% confidence, and the rate of pedigree record mistakes ranged from 9.52%-39.29% in different herds. Our study is the first attempt to provide valuable insights into the extraction of informative markers through the application of high-density SNP chips for paternity testing in Chinese Simmental cattle.
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