Genomic analysis of dominance effects on milk production and conformation traits in Fleckvieh cattle

Abstract

BackgroundEstimates of dominance variance in dairy cattle based on pedigree data vary considerably across traits and amount to up to 50% of the total genetic variance for conformation traits and up to 43% for milk production traits. Using bovine SNP (single nucleotide polymorphism) genotypes, dominance variance can be estimated both at the marker level and at the animal level using genomic dominance effect relationship matrices. Yield deviations of high-density genotyped Fleckvieh cows were used to assess cross-validation accuracy of genomic predictions with additive and dominance models. The potential use of dominance variance in planned matings was also investigated.ResultsVariance components of nine milk production and conformation traits were estimated with additive and dominance models using yield deviations of 1996 Fleckvieh cows and ranged from 3.3% to 50.5% of the total genetic variance. REML and Gibbs sampling estimates showed good concordance. Although standard errors of estimates of dominance variance were rather large, estimates of dominance variance for milk, fat and protein yields, somatic cell score and milkability were significantly different from 0. Cross-validation accuracy of predicted breeding values was higher with genomic models than with the pedigree model. Inclusion of dominance effects did not increase the accuracy of the predicted breeding and total genetic values. Additive and dominance SNP effects for milk yield and protein yield were estimated with a BLUP (best linear unbiased prediction) model and used to calculate expectations of breeding values and total genetic values for putative offspring. Selection on total genetic value instead of breeding value would result in a larger expected total genetic superiority in progeny, i.e. 14.8% for milk yield and 27.8% for protein yield and reduce the expected additive genetic gain only by 4.5% for milk yield and 2.6% for protein yield.ConclusionsEstimated dominance variance was substantial for most of the analyzed traits. Due to small dominance effect relationships between cows, predictions of individual dominance deviations were very inaccurate and including dominance in the model did not improve prediction accuracy in the cross-validation study. Exploitation of dominance variance in assortative matings was promising and did not appear to severely compromise additive genetic gain.

Genomic prediction for additive and dominance effects of censored traits in pigs

“…When including the dominance effect, the predictive abilities of the GBVs in the evaluated models did not increase. Similar results were obtained by Ertl et al (2014) in dairy cattle. According to Nishio and Satoh (2014), this was due to the low and null dominance effects that were obtained in the evaluated models.…”

“…Ertl et al (2014), when evaluating the inclusion of dominance effects in dairy cattle, found that LRT was not significant for four of the nine evaluated traits.…”

“…The statistics of the test follow a Chi-square distribution with degrees of freedom based on the difference between the number of parameters (variance components). The P value for the test is given by Ertl et al, 2014). Thus, the LRT was used to compare the following models: AL vs ADL, AC vs ADC, and AUC vs ADUC.…”

On the Additive and Dominant Variance and Covariance of Individuals Within the Genomic Selection Scope

“…With dominant effects, accuracy from MGD was higher (32.5%) than from MADped (Table 2). In addition, the genomic models including dominance have the advantage that they provide a simple framework, compared with pedigree models, to estimate dominance effects (i.e., Su et al 2012;Ertl et al 2013).…”

Invited review: Genome-wide association analysis for quantitative traits in livestock – a selective review of statistical models and experimental designs

“…In this parametrization, the SNP effect represents the gene substitution effect (Falconer and Mackay, 1996). The term e i de-notes the random residual and u i the random polygenic effect of the individual.…”