Abstract
BackgroundIdentifying associations between genetic markers and traits of economic importance will provide practical benefits for the dairy goat industry, enabling genomic prediction of the breeding value of individuals, and facilitating discovery of the underlying genes and mutations. Genome-wide association studies were implemented to detect genetic regions that are significantly associated with effects on lactation yields of milk (MY), fat (FY), protein (PY) and somatic cell score (SCS) in New Zealand dairy goats.MethodsA total of 4,840 goats were genotyped with the Caprine 50 K SNP chip (Illumina Inc., San Diego, CA). After quality filtering, 3,732 animals and 41,989 SNPs were analysed assuming an additive linear model. Four GWAS models were performed, a single-SNP additive linear model and three multi-SNP BayesC models. For the single-SNP GWAS, SNPs were fitted individually as fixed covariates, while the BayesC models fit all SNPs simultaneously as random effects. A cluster of significant SNPs were used to define a haplotype block whose alleles were fitted as covariates in a Bayesian model. The corresponding diplotypes of the haplotype block were then fit as class variables in another Bayesian model.ResultsAcross all four traits, a total of 43 genome-wide significant SNPs were detected from the SNP GWAS. At a genome-wide significance level, the single-SNP analysis identified a cluster of variants on chromosome 19 associated with MY, FY, PY, and another cluster on chromosome 29 associated with SCS. Significant SNPs mapped in introns of candidate genes (45%), in intergenic regions (36%), were 0–5 kb upstream or downstream of the closest gene (14%) or were synonymous substitutions (5%). The most significant genomic window was located on chromosome 19 explaining up to 9.6% of the phenotypic variation for MY, 8.1% for FY, 9.1% for PY and 1% for SCS.ConclusionsThe quantitative trait loci for yield traits on chromosome 19 confirms reported findings in other dairy goat populations. There is benefit to be gained from using these results for genomic selection to improve milk production in New Zealand dairy goats.
Highlights
Identifying associations between genetic markers and traits of economic importance will provide practical benefits for the dairy goat industry, enabling genomic prediction of the breeding value of individuals, and facilitating discovery of the underlying genes and mutations
26 Singlenucleotide polymorphism (SNP) are associated with Milk yield (MY), 24 SNPs associated with Fat yield (FY) and Protein yield (PY) and 11 SNPs associated with somatic cell score (SCS)
Another significant region was identified on chromosome 29 (29:24,850,418–29:25,328, 810) with 11 SNPs associated with SCS
Summary
Identifying associations between genetic markers and traits of economic importance will provide practical benefits for the dairy goat industry, enabling genomic prediction of the breeding value of individuals, and facilitating discovery of the underlying genes and mutations. Genome-wide association studies were implemented to detect genetic regions that are significantly associated with effects on lactation yields of milk (MY), fat (FY), protein (PY) and somatic cell score (SCS) in New Zealand dairy goats. There are estimated to be 92 farms in New Zealand milking 66,100 dairy goats. Farms that supply DGC, and undertake herd testing, participate in an annual genetic evaluation for lactation yields of milk (MY), fat (FY) and protein (PY) and for somatic cell score (SCS). Breeding values for these traits were estimated for each animal from a multi-trait repeatability animal model using available pedigree [1]
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