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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Animal Genomics and Improvement Laboratory » Research » Publications at this Location » Publication #351509
Research Project: Improving Dairy Animals by Increasing Accuracy of Genomic Prediction, Evaluating New Traits, and Redefining Selection Goals

Location: Animal Genomics and Improvement Laboratory

Title: Genomic predictability of single-step GBLUP for production traits in US Holstein

Author
item MASUDA, YATAKA - University Of Georgia
item MISZTAL, IGNACY - University Of Georgia
item Vanraden, Paul
item LAWLOR, THOMAS - Holstein Association Usa, Inc

Submitted to: American Dairy Science Association Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 3/8/2018
Publication Date: 6/24/2018
Citation: Masuda, Y., Misztal, I.M., Van Raden, P.M., Lawlor, T.J. 2018. Genomic predictability of single-step GBLUP for production traits in US Holstein. Journal of Dairy Science. 101 (Suppl. 2):182(abstr. 171).

Interpretive Summary:

Technical Abstract: The objective of this study was to validate genomic predictability of single-step genomic BLUP for 305-day protein yield for US Holsteins. The genomic relationship matrix was created with the Algorithm of Proven and Young (APY) with 18,359 core animals. The full data set consisted of phenotypes collected from 1989 through 2015 and pedigrees limited to 3 generations back from phenotyped or genotyped animals. The predictor data set was created by cutting off the phenotypes, pedigree animals, and genotypes in the last 4 years from the full data set. Genomic predictions (GPTA2011) were calculated for predicted bulls that had no recorded-daughters in 2011 but had at least 50 such daughters in 2015. We calculated the daughter yield deviations with the full data (DYD2015) for the predicted bulls (N=3,797). We also used the official GPTA published in 2011 with a multi-step method as a comparison, although the official methods have changed since then. Coefficient of determination (R^2) and slope (b_1) were calculated from a linear regression of DYD2015 on GPTA2011. We investigated the effect of different unknown parent groups (UPGs) and a weight (omega) on the inverse of the pedigree relationship matrix for genotyped animals (A_22^-1) to compensate incomplete pedigree. When applying QP-transformation to A^-1, the R^2 was 0.52 with omega=1 compared to 0.51 from the official GPTA. The b_1 was similar (0.78) to 0.81 from the official GPTA. Using omega=0.90, the R^2 was still similar (0.50) but the b_1 was greatly improved (0.96). With QP-transformation in H^-1, the R^2 was less than 0.4 and the b_1 was smaller regardless of omega. Without any UPGs, the predictability and the inflation showed the same level as the official GPTA. The GPTA of a young animal is equivalent to the direct genomic value when many genotypes are included in the evaluation. Fixed UPGs in H^-1 added an extra value to GPTA of young animal but this additions is likely redundant in genomic prediction. An option is indirect prediction of direct genomic value using the marker effects. An essential solution may be from metafounders that modify the pedigree relationships according to the genomic relationship matrix.