Estimation of additive and dominance genetic parameters and identification of dominance markers for production and fertility traits in New Zealand dairy cattle : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Animal Science at Massey University, Palmerston North, New Zealand

Abstract

Traditional genomic evaluation models in dairy cattle only account for additive genetic effects and generally exclude dominance effects. However, dominance effects may contribute to phenotypic variation in economically important traits. The aim of this research was to estimate additive and dominance variance components for milk production traits, milk composition traits, and fertility traits and identify significant dominance marker effects through genome wide association studies (GWAS). This study used 5,686 lactation records from 1,667 spring calved cows across two Massey University research herds, and genotype data from 49,171 single nucleotide polymorphisms (SNPs). Genomic restricted maximum likelihood was used to estimate variance components under additive-only and additive + dominance models, with pedigree-based estimates included for comparison. Genome-wide association studies were performed for yields of milk, fat, protein, and lactose, percentages of fat, protein, and lactose, and fertility traits including days from the start of mating to first service (SMFS), pregnancy rate at first service (PRFS), 3-week submission rate (SR21), and 6-week pregnancy rate (PR42) where additive and dominance SNP effects were fitted simultaneously as covariates. Milk yield traits, including milk volume, fat, and protein, had moderate heritability estimates ranging between 0.22–0.28. Milk composition traits, including fat percentage, protein percentage, and lactose percentage, had high heritability estimates ranging between 0.45–0.69, and fertility traits SMFS, PRFS, SR21, and PR42 had low heritability estimates of less than 0.021. Dominance variance contributed between 8–12% of phenotypic variance for milk yield traits but was negligible for milk composition and fertility traits. These findings suggest that although additive variance accounted for a greater proportion of phenotypic variance, dominance may contribute to variation in economically important yield traits. Genome-wide association analyses identified significant additive associations on chromosome 14 for milk yield traits, and fat and protein percentage, as well as additive association signals on chromosome 5 for milk yield, lactose yield, and fat percentage. Dominance association signals were generally weaker, with a region on chromosome 9 identified for fat yield. Few significant additive and dominance markers were identified for fertility traits. The detection of dominance associations without significant additive associations highlights genomic regions that may not be detected using additive-only models. Although this study was limited by sample size, the results highlight the potential relevance of accounting for dominance effects in future genomic analyses of dairy cattle traits.