TY - JOUR
T1 - Across-countries genomic prediction using national breeding values or multitrait across-countries evaluation breeding values
AU - Mohammed Abdallah, Sallam
AU - Benhajali, Haifa
AU - Savoia, Simone
AU - de Koning, Dirk-Jan
AU - Strandberg, Erling
PY - 2022
Y1 - 2022
N2 - In across-country genomic predictions for dairy cattle, 2 kinds of bull information can be used as dependent variables. The first is estimated breeding value (EBV) from the national genetic evaluations, assuming genetic correlations between countries are less than 1. The second is EBV from multitrait across-countries evaluation (MACE), assuming genetic correlations between countries equal 1. In the present study, the level of bias and reliability of a cross-countries genomic prediction using national EBV or MACE EBV as the dependent variable were investigated. Data from Brown Swiss Organizations joining the InterGenomics Service by Inter bull Centre (Uppsala, Sweden) were used. National and MACE EBV of 3 traits (protein yield, cow conception rate, and calving interval) from 7, 5, and 4 countries, respectively, were used, resulting in 16 trait-country combinations. Genotypes for 45,473 SNP markers and deregressed (national or MACE) EBV of 7,490; 5,833; and 5,177 bulls were used in analysis of protein yield, cow conception rate, and calving interval, respectively. For most of trait-country combinations, the use of MACE EBV via single-trait approach resulted in less biased and more reliable across-countries genomic predictions. In case some of the MACE EBV might have been inflated, the resulting single-trait genomic predictions were inflated as well. For these specific cases, the use of national EBV via multitrait approach provided less bias and more reliable across-countries genomic predictions.
AB - In across-country genomic predictions for dairy cattle, 2 kinds of bull information can be used as dependent variables. The first is estimated breeding value (EBV) from the national genetic evaluations, assuming genetic correlations between countries are less than 1. The second is EBV from multitrait across-countries evaluation (MACE), assuming genetic correlations between countries equal 1. In the present study, the level of bias and reliability of a cross-countries genomic prediction using national EBV or MACE EBV as the dependent variable were investigated. Data from Brown Swiss Organizations joining the InterGenomics Service by Inter bull Centre (Uppsala, Sweden) were used. National and MACE EBV of 3 traits (protein yield, cow conception rate, and calving interval) from 7, 5, and 4 countries, respectively, were used, resulting in 16 trait-country combinations. Genotypes for 45,473 SNP markers and deregressed (national or MACE) EBV of 7,490; 5,833; and 5,177 bulls were used in analysis of protein yield, cow conception rate, and calving interval, respectively. For most of trait-country combinations, the use of MACE EBV via single-trait approach resulted in less biased and more reliable across-countries genomic predictions. In case some of the MACE EBV might have been inflated, the resulting single-trait genomic predictions were inflated as well. For these specific cases, the use of national EBV via multitrait approach provided less bias and more reliable across-countries genomic predictions.
KW - across-countries international genomic prediction evaluation
KW - estimation of single nucleotide polymorphism effect
KW - multitrait across-countries evaluation
KW - national proof
KW - Brown Swiss
KW - across-countries international genomic prediction evaluation
KW - estimation of single nucleotide polymorphism effect
KW - multitrait across-countries evaluation
KW - national proof
KW - Brown Swiss
UR - https://res.slu.se/id/publ/118368
U2 - 10.3168/jds.2021-20877
DO - 10.3168/jds.2021-20877
M3 - Journal article
SN - 0022-0302
VL - 105
SP - 3282
EP - 3295
JO - Journal of Dairy Science
JF - Journal of Dairy Science
IS - 4
ER -