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Zuoxiang Liang
Department of Animal Science, University of Minnesota, Saint Paul, USA
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Commentary
Large-Sample Genomic Data Mining for Quantitative Traits in U.S. Holstein Cows
Author(s): Yang Da*, Dzianis Prakapenka and Zuoxiang Liang
The U.S. Holstein cattle have unprecedentedly large samples for genomic evaluation with genotypes of Single Nucleotide Polymorphism (SNP) markers and phenotypic observations of dairy quantitative traits. Such large samples provided unprecedented opportunities for the discovery of genetic variants and mechanisms affecting quantitative traits in Holstein cattle. Recent studies using the Holstein large samples on finding genetic variants affecting quantitative traits included a fat percentage study and two studies on reproductive traits. The fat percentage study confirmed that a chromosome region interacted with all chromosomes and the reproductive studies detected sharply negative homozygous recessive genotypes that were recommended for heifer culling. These novel findings provided examples showing the power of large-sample genomic mining for quantitative traits... View more»