Genetic and genomic studies on milk production and composition, and longevity in New Zealand dairy goats : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Animal Science at Massey University, Manawatu, New Zealand

Abstract

The New Zealand dairy goat industry is important for producing and exporting high-quality specialised dairy products aimed at niche markets. Efforts to increase the quantity and composition of goat milk will improve profits for farmers and deliver significant economic benefits to New Zealand. However, no formal program exists for the genetic improvement of dairy goats. Therefore, the general aim of this thesis was to perform genetic and genomic studies that contribute to the design of the breeding program for New Zealand dairy goats. The first studies estimated variance components and genetic parameters of total lactation yields of milk, fat and protein, somatic cell score and longevity. The main findings suggest sufficient variation and favourable genetic correlations between these traits, supporting their inclusion into a selection index that predicts profit per animal. A random regression test-day model was then used to predict lactation curves of milk, fat, protein and somatic cell score. Using this model for genetic evaluation will enable the dairy goat industry to move from total yields into the prediction of lactation curves, enabling more accurate predictions and the opportunity of selecting for extended lactations. The first genome-wide association study of dairy goats in New Zealand was conducted using 3,732 animals genotyped with the Caprine 50K SNP chip. A highly significant region on chromosome 19 was associated with yields of milk, fat and protein, and somatic cell score, and a region on chromosome 29 was associated with somatic cell score. A prototype single-step BayesC model was developed to predict genomic breeding values and demonstrated that including genomic information into the evaluation can increase the accuracy of predictions compared to the traditional methods based on pedigrees alone, which is currently implemented in the New Zealand dairy goat industry. This thesis demonstrates that a single-step prediction model that uses genomic information would put the New Zealand dairy goat industry in a very good position to implement a genomic selection scheme. Further studies are required to define clearer breeding objectives and to systematically design a breeding program for the genetic improvement of New Zealand dairy goats.