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International genomic evaluation methods for dairy cattle.

Paul M VanRaden1, Peter G Sullivan

  • 1Animal Improvement Programs Laboratory, USDA, Building 5 BARC-West, Beltsville, MD 20705-2350, USA. Paul.VanRaden@ars.usda.gov

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International genomic evaluations for dairy cattle selection offer higher reliabilities by accounting for cross-border data. Genomic multi-trait across-country evaluation (MACE) improves accuracy, especially for young bulls, through shared genotypes.

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Area of Science:

  • Animal breeding and genetics
  • Quantitative genetics
  • Genomic selection

Background:

  • Genomic evaluations are increasingly adopted for dairy cattle selection, surpassing traditional methods.
  • International cooperation is facilitated by higher reliabilities from larger genotype datasets.
  • Genomic data exchange across countries can be achieved through conversion equations or multi-trait analyses.

Purpose of the Study:

  • To compare methods for international genomic evaluations in dairy cattle.
  • To assess the impact of residual correlations on genomic evaluations across countries.
  • To evaluate the reliability gains from across-country genomic evaluations.

Main Methods:

  • Compared modified Multi-Trait Across-Country Evaluation (MACE) with direct multi-country genotype analysis.
  • Utilized simulated genomic and phenotypic data for 8,193 bulls across nine countries.
  • Incorporated daughter equivalents and shared bull proportions to account for residual correlations in genomic MACE.

Main Results:

  • Across-country genomic evaluations yielded significantly higher reliabilities for young bulls compared to within-country evaluations.
  • Genomic MACE provided reliability gains comparable to multi-trait genotype evaluation but with reduced computational demands.
  • Sharing reference genotypes among countries induced substantial residual correlations, particularly for young bulls, which were effectively managed by genomic MACE.

Conclusions:

  • International genomic evaluations can be effectively implemented using modified MACE or multi-trait analysis of combined genotypes.
  • The enhanced reliability justifies the computational increase, necessitating greater international collaboration in breeding programs.