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Across-countries genomic prediction using national breeding values or multitrait across-countries evaluation breeding

M Sallam1, H Benhajali1, S Savoia1

  • 1Interbull Centre, Department of Animal Breeding and Genetics, Swedish University of Agricultural Science, Box 7023, 75007 Uppsala, Sweden.

Journal of Dairy Science
|February 6, 2022
PubMed
Summary

Across-country genomic predictions for dairy cattle using multitrait across-countries evaluation (MACE) estimated breeding values (EBV) generally yield less bias and higher reliability. However, national EBV can be superior if MACE EBV are inflated.

Keywords:
Brown Swissacross-countries international genomic prediction evaluationestimation of single nucleotide polymorphism effectmultitrait across-countries evaluationnational proof

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Area of Science:

  • Animal Genetics and Breeding
  • Genomic Prediction
  • Dairy Cattle Evaluation

Background:

  • Across-country genomic predictions in dairy cattle utilize national estimated breeding values (EBV) or multitrait across-countries evaluation (MACE) EBV.
  • National EBV assume genetic correlations between countries are < 1, while MACE EBV assume they are = 1.
  • Investigating bias and reliability of these approaches is crucial for accurate international genetic evaluations.

Purpose of the Study:

  • To compare the bias and reliability of across-country genomic predictions using national EBV versus MACE EBV as dependent variables.
  • To evaluate the performance of single-trait versus multitrait approaches in cross-country genomic prediction.

Main Methods:

  • Utilized Brown Swiss data from InterGenomics Service, including national and MACE EBV for protein yield, cow conception rate, and calving interval across multiple countries.
  • Analyzed 16 trait-country combinations using genotypes for 45,473 SNP markers and deregressed EBV from thousands of bulls.
  • Compared single-trait genomic prediction using MACE EBV against multitrait genomic prediction using national EBV.

Main Results:

  • For most trait-country combinations, MACE EBV in a single-trait approach led to less biased and more reliable across-country genomic predictions.
  • When MACE EBV were potentially inflated, single-trait genomic predictions also showed inflation.
  • In cases of MACE EBV inflation, national EBV within a multitrait approach provided superior bias reduction and reliability.

Conclusions:

  • Multitrait across-countries evaluation (MACE) EBV generally enhance across-country genomic prediction accuracy in dairy cattle.
  • The choice between national EBV and MACE EBV depends on the potential for inflation in MACE estimates.
  • National EBV offer a robust alternative for genomic prediction when MACE EBV may be biased.