Confirmation and fine-mapping of clinical mastitis and somatic cell score QTL in Nordic Holstein cattle G. Sahana, B. Guldbrandtsen, B. Thomsen and M. S. Lund Department of Molecular Biology and Genetics, Faculty of Science and Technology, Aarhus University, DK-8830, Tjele, Denmark. Summary A genome-wide association study of 2098 progeny-tested Nordic Holstein bulls genotyped for 36 387 SNPs on 29 autosomes was conducted to confirm and fine-map quantitative trait loci (QTL) for mastitis traits identified earlier using linkage analysis with sparse microsatellite markers in the same population. We used linear mixed model analysis where a polygenic genetic effect was fitted as a random effect and single SNPs were successively included as fixed effects in the model. We detected 143 SNP-by-trait significant associations (P < 0.0001) on 20 chromosomes affecting mastitis-related traits. Among them, 21 SNP- by-trait combinations exceeded the genome-wide significant threshold. For 12 chromo- somes, both the present association study and the previous linkage study detected QTL, and of these, six were in the same chromosomal locations. Strong associations of SNPs with mastitis traits were observed on bovine autosomes 6, 13, 14 and 20. Possible candidate genes for these QTL were identified. Identification of SNPs in linkage disequilibrium with QTL will enable marker-based selection for mastitis resistance. The candidate genes identified should be further studied to detect candidate polymorphisms underlying these QTL. Keywords confirmation study, dairy cattle, gene mapping, genome-wide association study Introduction Until recently, genome-wide linkage analysis was the method of choice for quantitative trait loci (QTL) detection in cattle, due to the availability of large half-sib family structures, as well as for identifying genes for phenotypes exhibiting Mendelian inheritance (Jimenez-Sanchez et al. 2001). Linkage analysis generally results in relatively low mapping resolution, because only few recombination events occur within families and pedigrees with known ancestry. This limits the resolution of candidate polymor- phism searches. In contrast, association mapping (linkage disequilibrium mapping) has emerged as a powerful tool to resolve complex trait variation down to the sequence level by exploiting historical recombination events at the population level for high-resolution mapping (Risch & Merikangas 1996; Nordborg & Tavare ´ 2002). In this approach, markers or haplotypes associated with a trait of interest at the population level are identified. Such markers and haplotypes could be used directly for marker-based selection. Typically, genome scans are used to map QTL for which some test statistic exceeds a pre-defined threshold value. Even when the threshold level is chosen to be very conservative, a risk of the QTL representing a type I error remains. The confirmation of linkage analysis results by an association study will add to the credibility of detected QTL. Lund et al. (2008) mapped QTL for clinical mastitis and somatic cell score in Danish Holstein cattle using linkage analysis. These authors used data on 356 microsatellite markers spread across all autosomes with an average marker spacing of 8.6 cM. Nonetheless, the QTL regions reported were quite long (more than 20 cM for some QTL). Such large QTL regions, along with family speci- ficity of marker–QTL associations, limit the usability of their result for practical animal breeding as well as for candidate polymorphism searches. Thus, a need to confirm these QTL and refine their position estimates remains in order to include QTL information in selection decisions. In the present study, association mapping was carried out for six mastitis traits in cattle using dense SNP markers. The aim of this study was to confirm and fine-map the QTL for mastitis traits previously reported in the Danish Holstein dairy cattle population by Lund et al. (2008). Address for correspondence G. Sahana, Department of Molecular Biology and Genetics, Faculty of Science and Technology, Aarhus University, Blichers Alle ´ 20, Post Box 50, DK-8830, Tjele, Denmark. E-mail: goutam.sahana@agrsci.dk Accepted for publication 18 March 2013 doi: 10.1111/age.12053 1 © 2013 Aarhus University, Animal Genetics © 2013 Stichting International Foundation for Animal Genetics