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The prediction accuracies of linear-type traits in Czech Holstein cattle when using ssGBLUP or wssGBLUP

. 2022 Dec 01 ; 100 (12) : .

Language English Country United States Media print

Document type Journal Article

Grant support
LTAUSA19117 Ministry of Education, Youth and Sport
NAZV QK1910156 Ministry of Agriculture of the Czech Republic

The aim of this study was to assess the contribution of the weighted single-step genomic best linear unbiased prediction (wssGBLUP) method compared to the single-step genomic best linear unbiased prediction (ssGBLUP) method for genomic evaluation of 25 linear-type traits in the Czech Holstein cattle population. The nationwide database of linear-type traits with 6,99,681 records combined with deregressed proofs from Interbull (MACE method) was used as the input data. Genomic breeding values (GEBVs) were predicted based on these phenotypes using ssGBLUP and wssGBLUP methods using the BLUPF90 software. The bull validation test was employed which was based on comparing GEBVs of young bulls (N = 334) with no progeny in 2016. A minimum of 50 daughters with their own performance in 2020 was chosen to verify the contribution to the GEBV prediction, GEBV reliability, validation reliabilities (R2), and regression coefficients (b1). The results showed that the differences between the two methods were negligible. The low benefit of wssGBLUP may be due to the inclusion of a small number of SNPs; therefore, most predictions rely on polygenic relationships between animals. Nevertheless, the benefits of wssGBLUP analysis should be assessed with respect to specific population structures and given traits.

Animal breeding is based on statistical and mathematical approaches. With the development of computer technology, these procedures have become more efficient and have shed light upon an increasing amount of information, particularly in the field of molecular genetics. This results in a more accurate prediction of the breeding value. The single-step approach is the most popular genomic breeding value-prediction method. Single-step genomic BLUP (ssGBLUP) assumes that all single nucleotide polymorphisms (SNPs) explain the same fraction of genetic variance. In contrast, unequal variance and SNP weights were considered in weighted ssGBLUP (wssGBLUP). The aim of this study was to assess the contribution of wssGBLUP compared to ssGBLUP for the genomic evaluation of 25 linear-type traits in Czech Holstein cattle. We can conclude that no significant differences were found between these methods for the evaluated traits, probably because of the low number of included SNPs, which may not cover all significant SNPs in the genome.

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