Background: Differences in linkage disequilibrium and in allele substitution effects of QTL (quantitative trait loci)
may hinder genomic prediction across populations. Our objective was to develop a deterministic formula to
estimate the accuracy of across-population genomic prediction, for which reference individuals and selection
candidates are from different populations, and to investigate the impact of differences in allele substitution
effects across populations and of the number of QTL underlying a trait on the accuracy.
Methods: A deterministic formula to estimate the accuracy of across-population genomic prediction was derived
based on selection index theory. Moreover, accuracies were deterministically predicted using a formula based on population parameters and empirically calculated using simulated phenotypes and a GBLUP (genomic best linear unbiased prediction) model. Phenotypes of 1033 Holstein-Friesian, 105 Groninger White Headed and 147
Meuse-Rhine-Yssel cows were simulated by sampling 3000, 300, 30 or 3 QTL from the available high-density
SNP (single nucleotide polymorphism) information of three chromosomes, assuming a correlation of 1.0, 0.8,
0.6, 0.4, or 0.2 between allele substitution effects across breeds. The simulated heritability was set to 0.95 to
resemble the heritability of deregressed proofs of bulls.
Results: Accuracies estimated with the deterministic formula based on selection index theory were similar
to empirical accuracies for all scenarios, while accuracies predicted with the formula based on population
parameters overestimated empirical accuracies by ~25 to 30%. When the between-breed genetic correlation
differed from 1, i.e. allele substitution effects differed across breeds, empirical and deterministic accuracies
decreased in proportion to the genetic correlation. Using a multi-trait model, it was possible to accurately
estimate the genetic correlation between the breeds based on phenotypes and high-density genotypes. The
number of QTL underlying the simulated trait did not affect the accuracy.
Conclusions: The deterministic formula based on selection index theory estimated the accuracy of across-population genomic predictions well. The deterministic formula using population parameters overestimated the across-population genomic accuracy, but may still be useful because of its simplicity. Both formulas could accommodate for genetic correlations between populations lower than 1. The number of QTL underlying a trait did not affect the accuracy of across-population genomic prediction using a GBLUP method
- dairy-cattle breeds
- linkage disequilibrium
- relationship matrix
- complex traits