Abstract

A whole-genome association study of milk production traits: milk yield, protein yield, fat yield, protein percentage, and fat percentage, was performed on the population of Braunvieh cattle. Five hundred and fifty-four progeny-tested bulls and 36,219 autosomal single nucleotide polymorphism (SNP) markers on 29 Bos taurus autosomes (BTA) were included in the analysis. A principal component analysis was conducted to adjust for the effect of population stratification in the analyzed data set. For the principal component analysis, genome-wide relationships between individuals were calculated. Three different criteria (Horn’s test, Kaiser’s criterion, and Jolliffe’s criterion) were tested to determine the number of significant principal components. Estimation of putative associations between SNP and milk production traits was carried out using a linear regression model in R software (R Foundation for Statistical Computing, Vienna, Austria). Significant principal components, adjusting for population stratification separately for each criterion and family relationships and genotypes at individual SNP were included as fixed effects in the model. The inflation factor λ and quantile-quantile plots were calculated to compare how the different criteria deal with stratification in our mapping population. Based on the analyses on all of the aforementioned criteria, we can conclude that Jolliffe’s criterion deals the best with population stratification. Furthermore, significance thresholds for a given genome-wide false discovery rate of 5% were estimated and used for specific traits. Three of the analyzed traits showed genome-wide significant association with SNP. Two SNP had an effect on milk yield on BTA4, 2 SNP affected fat yield on BTA14 and BTA23, and 1 SNP was associated with fat percent on BTA1. Single nucleotide polymorphisms identified in this study as associated with milk production traits will further contribute to the mapping of corresponding quantitative trait loci and investigation of the genes responsible for polymorphisms in milk production traits in dairy cattle. Described comparison of different criteria for determination of significant principal components can provide important information for similar studies in stratified populations.

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