title: National single-step genomic method that integrates multi-national genomic information.
abstract: The aim of this paper was to develop a national single-step genomic BLUP that integrates multi-national genomic estimated breeding values (EBV) and associated reliabilities without double counting dependent data contributions from the different evaluations. Simultaneous use of all data, including phenotypes, pedigree, and genotypes, is a condition to obtain unbiased EBV. However, this condition is not always fully met, mainly due to unavailability of foreign raw data for imported animals. In dairy cattle genetic evaluations, this issue is traditionally tackled through the multiple across-country evaluation (MACE) of sires, performed by Interbull Centre (Uppsala, Sweden). Multiple across-country evaluation regresses all the available national information onto a joint pedigree to obtain country-specific rankings of all sires without sharing the raw data. In the context of genomic selection, the issue is handled by exchanging sire genotypes and by using MACE information (i.e., MACE EBV and reliabilities), as a valuable source of "phenotypic" data. Although all the available data are considered, these "multi-national" genomic evaluations use multi-step methods assuming independence of various sources of information, which is not met in all situations. We developed a method that handles this by single-step genomic evaluation that jointly (1) uses national phenotypic, genomic, and pedigree data; (2) uses multi-national genomic information; and (3) avoids double counting dependent data contributions from an animal's own records and relatives' records. The method was demonstrated by integrating multi-national genomic EBV and reliabilities of Brown Swiss sires, included in the InterGenomics consortium at Interbull Centre, into the national evaluation in Slovenia. The results showed that the method could (1) increase reliability of a national (genomic) evaluation; (2) provide consistent ranking of all animals: bulls, cows, and young animals; and (3) increase the size of a genomic training population. These features provide more efficient and transparent selection throughout a breeding program.
authors.affiliation: Agriculture, Bio-engineering and Chemistry Department, Gembloux Agro-Bio Tech, University of Liege, 5030 Gembloux, Belgium; National Fund for Scientific Research, 1000 Brussels, Belgium. Electronic address: jeremie.vandenplas@wur.nl.
authors.forename: J
authors.initials: J
authors.lastname: Vandenplas
authors.affiliation: Croatian Agricultural Agency, 10000 Zagreb, Croatia; Biotechnical Faculty, University of Ljubljana, 1000 Ljubljana, Slovenia.
authors.forename: M
authors.initials: M
authors.lastname: Spehar
authors.affiliation: Biotechnical Faculty, University of Ljubljana, 1000 Ljubljana, Slovenia.
authors.forename: K
authors.initials: K
authors.lastname: Potocnik
authors.affiliation: Agriculture, Bio-engineering and Chemistry Department, Gembloux Agro-Bio Tech, University of Liege, 5030 Gembloux, Belgium.
authors.forename: N
authors.initials: N
authors.lastname: Gengler
authors.affiliation: Biotechnical Faculty, University of Ljubljana, 1000 Ljubljana, Slovenia; The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush Research Centre, Midlothian EH25 9RG, United Kingdom.
authors.forename: G
authors.initials: G
authors.lastname: Gorjanc
mesh_terms: D000818:Animals; D001947:Breeding; D002417:Cattle; D003612:Dairying; D005260:Female; D016678:Genome; D023281:Genomics; D005838:Genotype; D008297:Male; D008957:Models, Genetic; D010375:Pedigree; D015203:Reproducibility of Results
keywords: combination; genomically enhanced estimated breeding values; multi-national; single-step genomic BLUP