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Quantitative trait loci (QTL) mapping projects have been implemented mainly in the Holstein dairy cattle breed for several traits. The aim of this study is to map QTL for milk yield (MY) and milk protein percent (PP) in the Brown Swiss cattle populations of Austria, Germany, and Italy, considered in this study as a single population. A selective DNA pooling approach using milk samples was applied to map QTL in 10 paternal half-sib daughter families with offspring spanning from 1,000 to 3,600 individuals per family. Three families were sampled in Germany, 3 in Italy, 1 in Austria and 3 jointly in Austria and Italy. The pools comprised the 200 highest and 200 lowest performing daughters, ranked by dam-corrected estimated breeding value for each sire-trait combination. For each tail, 2 independent pools, each of 100 randomly chosen daughters, were constructed. Sire marker allele frequencies were obtained by densitometry and shadow correction analyses of 172 genome-wide allocated autosomal markers. Particular emphasis was placed on Bos taurus chromosomes 3, 6, 14, and 20. Marker association for MY and PP with a 10% false discovery rate resulted in nominal P-values of 0.071 and 0.073 for MY and PP, respectively. Sire marker association tested at a 20% false discovery rate (within significant markers) yielded nominal P-values of 0.031 and 0.036 for MY and PP, respectively. There were a total of 36 significant markers for MY, 33 for PP, and 24 for both traits; 75 markers were not significant for any of the traits. Of the 43 QTL regions found in the present study, 10 affected PP only, 8 affected MY only, and 25 affected MY and PP. Remarkably, all 8 QTL regions that affected only MY in the Brown Swiss, also affected MY in research reported in 3 Web-based QTL maps used for comparison with the findings of this study (http://www.vetsci.usyd.edu.au/reprogen/QTL_Map/; http://www.animalgenome.org/QTLdb/cattle.html; http://bovineqtl.tamu.edu/). Similarly, all 10 QTL regions in the Brown Swiss that affected PP only, affected only PP in the databases. Thus, many QTL appear to be common to Brown Swiss and other breeds in the databases (mainly Holstein), and an appreciable fraction of QTL appears to affect MY or PP primarily or exclusively, with little or no effect on the other trait. Although QTL information available today in the Brown Swiss population can be utilized only in a within family marker-assisted selection approach, knowledge of QTL segregating in the whole population should boost gene identification and ultimately the implementation and efficiency of an individual genomic program.

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.