Short communication: Reliability of single-step genomic BLUP breeding values by multi-trait test-day model analysis

Abstract

The purpose of our study was to develop an approximation procedure to estimate reliabilities of single-step genomic BLUP breeding values in a test-day model for routine evaluation of milk yield in a dairy cattle population. Input data consisted of 20,220,047 first-, second-, and third-lactation test-day milk yield records of 1,126,102 Czech Holstein cows (each lactation being considered a separate trait), with 1,844,679 animals in the pedigree file and with genomic data from 2,236 bulls. Evaluation was according to a multi-lactation model. The procedure was based on the effective number of records per animal from milk recording as well as from genomic and pedigree relationships. Traits were analyzed individually, and genetic covariances among traits were subsequently taken into account. The use of genomic information increased average reliability in young bulls from 0.276 to 0.505, but increased reliability in proven bulls only from 0.828 to 0.855. The reliabilities of genomic breeding values in multi-trait evaluation for first, second and third lactations, respectively, averaged 0.652, 0.673, and 0.633 for young bulls and 0.907, 0.894, and 0.852 for proven bulls. For an index combining all 3 lactations, the average reliability of a single-step genomic BLUP prediction was 0.712 and 0.925 for younger and proven bulls, respectively. Increased reliability due to genotyping in the population of all genotyped and nongenotyped animals was very small (<0.01) because of the small proportion of genotyped animals in the population.

Genomic-polygenic and polygenic evaluations for milk yield and fat percentage using random regression models with Legendre polynomials in a Thai multibreed dairy population

“…Higher EBV accuracies for RRGM than for RRPM (3.6% for 305-MY and 2.5% for 305-d FP) indicated that including genomic information in genetic evaluations increased prediction accuracies over genetic evaluations based only on pedigree and phenotypic data in this population. This agreed with results from previous research showing that utilization of genomic information in addition to pedigree and phenotypic information to evaluate dairy cattle yielded higher prediction accuracies in various dairy populations (VanRaden et al, 2009;Van Doormaal et al, 2009;Wiggans et al, 2011;Su et al, 2012;Thomasen et al, 2012;Bauer et al, 2014Bauer et al, , 2015Přibyl et al, 2014;Jattawa et al, 2015). Mean accuracies of 305-d MY genomic-polygenic EBV computed with single-step cumulative 305-d models were 7.2% higher than the mean accuracy from polygenic EBV in this same Thai population (Jattawa et al, 2015).…”

“…Mean accuracies of 305-d MY genomic-polygenic EBV computed with single-step cumulative 305-d models were 7.2% higher than the mean accuracy from polygenic EBV in this same Thai population (Jattawa et al, 2015). Similarly, prediction accuracy for 305-d MY from a single-step random regression genomic-polygenic model was 6.8% higher than that from random regression polygenic evaluation in a population of 1,854,275 Czech Holstein using 40,653 SNP from 2236 genotyped sires (Bauer et al, 2015). This 6.8% increase in accuracy was higher than the value of 3.6% obtained here although the number of genotyped animals was smaller than the 2661 animals genotyped in this Thai population.…”

“…Rank correlations between animal EBV from RRGM and RRPM indicated that genotypic data had little impact on EBV rankings for 305-d MY, but somewhat higher impact on EBV rankings for 305-d FP. Inclusion of genomic information in dairy genetic evaluations had higher impact on the accuracy of EBV for animals without phenotypes than for animals with phenotypes (Schaeffer, 2006;Pollott et al, 2014;Bauer et al, 2015). All cows had 305-d MY records but 3942 cows had no 305-d FP records.…”

Determining Heat Stress Effects of Multiple Genetic Traits in Tropical Dairy Cattle Using Single-Step Genomic BLUP

“…The accuracy of predictions from the ssGBLUP method was better than that obtained with the BLUP method, with 32-54% for the ratio of accuracy and 60-80% for the methods. The accuracy values in this study were similar to those previously obtained [63,64]. Low accuracies can occur for a number of reasons: (1) A small reference population (number of animals with genotype data); therefore, the reference population should be greater than 1000 to significantly increase the accuracy [64].…”

Application of single‐step genomic best linear unbiased prediction with a multiple‐lactation random regression test‐day model for Japanese Holsteins

“…Increase of R 2 in later lactations may be caused by the genetic evaluation model considered genetic correlation among lactations. Bauer et al () reported that the approximated reliability of GEBV for genotyped young bulls by ssGBLUP with multiple‐trait test‐day model between the first three lactations was highest in the second lactation. An implementation of the multiple‐trait model improved R 2 of the trait with a limited number of records (Guo et al ; Bauer et al ).…”