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Full-Text Articles in Dairy Science
Comparing Strategies For Selection Of Low-Density Snps For Imputation-Mediated Genomic Prediction In U.S. Holsteins, Jun He, Jiaqi Xu, Xiao-Lin Wu, Stewart Bauck, Jungjae Lee, Gota Morota, Stephen D. Kachman, Matthew L. Spangler
Comparing Strategies For Selection Of Low-Density Snps For Imputation-Mediated Genomic Prediction In U.S. Holsteins, Jun He, Jiaqi Xu, Xiao-Lin Wu, Stewart Bauck, Jungjae Lee, Gota Morota, Stephen D. Kachman, Matthew L. Spangler
Department of Animal Science: Faculty Publications
SNP chips are commonly used for genotyping animals in genomic selection but strategies for selecting low-density (LD) SNPs for imputation-mediated genomic selection have not been addressed adequately. The main purpose of the present study was to compare the performance of eight LD (6K) SNP panels, each selected by a different strategy exploiting a combination of three major factors: evenly-spaced SNPs, increased minor allele frequencies, and SNP-trait associations either for single traits independently or for all the three traits jointly. The imputation accuracies from 6K to 80K SNP genotypes were between 96.2 and 98.2%. Genomic prediction accuracies obtained using imputed 80K …