Premium
Single step genomic evaluation for female fertility in Nordic Red dairy cattle
Author(s) -
Matilainen Kaarina,
Strandén Ismo,
Aamand Gert Pedersen,
Mäntysaari Esa A.
Publication year - 2018
Publication title -
journal of animal breeding and genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.689
H-Index - 51
eISSN - 1439-0388
pISSN - 0931-2668
DOI - 10.1111/jbg.12353
Subject(s) - best linear unbiased prediction , insemination , fertility , ice calving , artificial insemination , biology , dairy cattle , trait , selection (genetic algorithm) , restricted maximum likelihood , heritability , sire , statistics , zoology , genetics , mathematics , demography , pregnancy , maximum likelihood , lactation , population , computer science , artificial intelligence , sociology , programming language
Joint Nordic (Denmark, Finland, Sweden) genetic evaluation of female fertility is currently based on the multiple trait multilactation animal model ( BLUP ). Here, single step genomic model (ss GBLUP ) was applied for the Nordic Red dairy cattle fertility evaluation. The 11 traits comprised of nonreturn rate and days from first to last insemination in heifers and first three parities, and days from calving to first insemination in the first three parities. Traits had low heritabilities (0.015–0.04), but moderately high genetic correlations between the parities (0.60–0.88). Phenotypic data included 4,226,715 animals with records and pedigree 5,445,392 animals. Unknown parents were assigned into 332 phantom parent groups ( PPG ). In mixed model equations animals were associated with PPG effects through the pedigree or both the pedigree and genomic information. Genotype information of 46,914 SNP s was available for 33,969 animals in the pedigree. When PPG used pedigree information only, BLUP converged after 2,420 iterations whereas the ss GBLUP evaluation needed over ten thousand iterations. When the PPG effects were solved accounting both the pedigree and the genomic information, the ss GBLUP model converged after 2,406 iterations. Also, with the latter model breeding values by ss GBLUP and BLUP became more consistent and genetic trends followed each other well. Models were validated using forward prediction of the young bulls. Reliabilities and variance inflation of predicted genomic breeding values (values for parent averages in brackets) for the 11 traits ranged 0.22–0.31 (0.10–0.27) and 0.81–0.95 (0.83–1.06), respectively. The ss GBLUP model gave always higher validation reliabilities than BLUP , but largest increases were for the cow fertility traits.