Improvement of Prediction Ability for Genomic Selection of Dairy Cattle by Including Dominance Effects

<div><p>Dominance may be an important source of non-additive genetic variance for many traits of dairy cattle. However, nearly all prediction models for dairy cattle have included only additive effects because of the limited number of cows with both genotypes and phenotypes. The role of dominance in the Holstein and Jersey breeds was investigated for eight traits: milk, fat, and protein yields; productive life; daughter pregnancy rate; somatic cell score; fat percent and protein percent. Additive and dominance variance components were estimated and then used to estimate additive and dominance effects of single nucleotide polymorphisms (SNPs). The predictive abilities of three models with both additive and dominance effects and a model with additive effects only were assessed using ten-fold cross-validation. One procedure estimated dominance values, and another estimated dominance deviations; calculation of the dominance relationship matrix was different for the two methods. The third approach enlarged the dataset by including cows with genotype probabilities derived using genotyped ancestors. For yield traits, dominance variance accounted for 5 and 7% of total variance for Holsteins and Jerseys, respectively; using dominance deviations resulted in smaller dominance and larger additive variance estimates. For non-yield traits, dominance variances were very small for both breeds. For yield traits, including additive and dominance effects fit the data better than including only additive effects; average correlations between estimated genetic effects and phenotypes showed that prediction accuracy increased when both effects rather than just additive effects were included. No corresponding gains in prediction ability were found for non-yield traits. Including cows with derived genotype probabilities from genotyped ancestors did not improve prediction accuracy. The largest additive effects were located on chromosome 14 near <i>DGAT1</i> for yield traits for both breeds; those SNPs also showed the largest dominance effects for fat yield (both breeds) as well as for Holstein milk yield.</p></div

Holstein and Jersey likelihood statistics (−2 log likelihood, <i>P</i>-value of <i>χ</i>²test^b using likelihood ratio) for milk, fat, and protein yields, productive life (PL), daughter pregnancy rate (DPR), somatic cell score (SCS), fat percent (fat%) and protein percent (protein%) using three different models.

a<p>MA = only additive effects included; MAD = additive and dominance (values) effects included; and MAD2 = additive and dominance (deviations) effects included.</p>b<p></p

Holstein and Jersey average correlations between estimated genetic effects and phenotypes for milk, fat, and protein yields, productive life (PL), daughter pregnancy rate (DPR), and somatic cell score (SCS) from training data for ten-fold cross-validation for four models.

a<p>MA = only additive effects included; MAD = additive and dominance (values) effects included; MAD2 = additive and dominance (deviations) effects included; and MAD3 = additive and dominance effects included as well as cows with genotype probabilities derived using genotyped ancestors.</p

Size and location of marker additive and dominance effects for milk yield of Holsteins and Jerseys.

<p>Holstein additive (A) and dominance (B) effects and Jersey additive (C) and dominance (D) effects were estimated with a model that included additive and dominance (values) effects.</p

Phenotypic statistics for Holstein and Jersey milk, fat, and protein yields based on cows with genotype probabilities derived using genotyped sire and dam (S-D) or genotyped sire and maternal grandsire (S-MGS).

a<p>Total number of daughters in S-MGS group in parentheses.</p

Characteristics of top ten single nucleotide polymorphisms for Holstein and Jersey milk, fat, and protein yields based on size of dominance effect from a model with additive and dominance (values) effects included.

a<p>UMD 3.1 assembly of the <i>Bos taurus</i> genome <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0103934#pone.0103934-Center1" target="_blank">[25]</a>.</p

Phenotypic, inbreeding and heterosis statistics for Holstein and Jersey milk, fat, and protein yields, productive life (PL), daughter pregnancy rate (DPR), somatic cell score (SCS), fat percent (fat%) and protein percent (protern%) based on genotyped cows.

a<p>Number of records,^bSD = Standard deviation, ^cregCoff was the regression coefficient for inbreeding or heterosis, which was estimated based on a multiple-trait and multiple-breed linear mixed model.</p

Characteristics of top ten single nucleotide polymorphisms with chromosome 14 excluded for Holstein and Jersey milk, fat, and protein yields based on size of additive effect from a model with additive and dominance (values) effects included.

a<p>UMD 3.1 assembly of the <i>Bos taurus</i> genome <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0103934#pone.0103934-Center1" target="_blank">[25]</a>.</p

Holstein and Jersey average correlations between estimated genetic effects and phenotypes for milk, fat, and protein yields, productive life (PL), daughter pregnancy rate (DPR), and somatic cell score (SCS) from testing data for ten-fold cross-validation for four models as well as <i>P</i>-values from paired t-tests based on differences between model correlations.

a<p>MA = only additive effects included; MAD = additive and dominance (values) effects included; MAD2 = additive and dominance (deviations) effects included; and MAD3 = additive and dominance effects included as well as cows with genotype probabilities derived using genotyped ancestors.</p

Size and location of marker additive and dominance effects for fat yield of Holsteins and Jerseys.

<p>Holstein additive (A) and dominance (B) effects and Jersey additive (C) and dominance (D) effects were estimated with a model that included additive and dominance (values) effects.</p