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Published on: July 27, 2021
Large-Sample Genomic Data Mining for Quantitative Traits in U.S. Holstein Cows
Yang Da1, Dzianis Prakapenka1, Zuoxiang Liang1
1Department of Animal Science, University of Minnesota, Saint Paul, USA.
Abstract:
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.
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