Background Analyses of population structure and breed diversity have provided insight into the origin and evolution of cattle. represent the phylogenetic relationship among these breeds. Conclusion The whole-genome SNP panel identified several levels of population substructure in the set of examined cattle breeds. The greatest level of genetic differentiation was detected between the Bos taurus and Bos indicus breeds. When the Bos indicus breeds were excluded from the analysis, genetic differences among beef versus dairy and European versus Asian breeds were detected among the Bos taurus breeds. Exploration of the number of SNP loci required to differentiate between breeds showed that for 100 SNP loci, individuals could only be correctly clustered into breeds 50% of the time, thus a large number of SNP markers are required to replace the 30 microsatellite markers that are currently commonly used in genetic diversity studies. Background Population structure and diversity within and between breeds of cattle have been studied to learn more about the origin, history and evolution of cattle [1-3]. Diversity studies and subsequent investigations concerning domestication events of Bos taurus and Bos indicus cattle have included sequencing from the displacement loop of mitochondrial DNA (mtDNA)[1]. Bradley et al. [1] used mtDNA sequence variation in 90 extant bovines from Africa, Europe and India to identify patterns of genetic variation consistent with the demographics of the domestication process. When nuclear marker have been used to study diversity in cattle, they have principally entailed microsatellite markers [2]. MacHugh et al. [2] used 20 microsatellites to help clarify the genetic relationships between cattle populations from Africa, Europe and Asia and provided support for a separate origin of domestication for Bos taurus and Bos indicus cattle. Analysis of allelic variation has been used to characterize the genetic BAPTA relationships BAPTA between breeds [4-7]. Kumar et al. [4] used 20 microsatellite markers to estimate the extent of genetic differentiation among breeds of cattle from India, Europe and the Near East. Assuming two ancestral populations, the mean admixture coefficients ranged from 0.0 to 0.1 in Indian Bos Rabbit polyclonal to CBL.Cbl an adapter protein that functions as a negative regulator of many signaling pathways that start from receptors at the cell surface. indicus breeds, 0.9 to 1 1.0 in European Bos taurus breeds and from 0.1 to 0.9 in hybrid breeds from the Near East. This variation in admixture coefficients reflects the ancestral divergence between the Bos taurus and Bos indicus subspecies. Similarly, Wiener et al. [5] characterized the diversity within and between eight British breeds of cattle using 30 microsatellite markers and found that the majority of the allelic variation (87%) was found within breeds. In addition, the studied breeds of cattle did not cluster according to their current geographic location, suggesting that the genetic origin of breeds was from different geographical regions. In a study of the origin of Chirikof Island cattle, MacNeil et al. [6] also found that 86% of the genetic variation in 34 microsatellite loci was found within Bos taurus breeds while the remaining 14% of genetic variation was found between breeds. However, the indigenous Chirikof Island cattle were strongly differentiated from the European Bos taurus cattle suggesting that a comparison between Asian Bos taurus breeds might next be appropriate. On the other hand, no significant divergence appears to exist between geographically separated populations of Holstein cattle probably BAPTA due to historic occurrences of gene flow between populations and selection for similar traits [8]. Up to now most studies have focused on a small set of microsatellite loci, typically the 30 suggested by the FAO [9]. The true extent of autosomal diversity among cattle breeds has yet to be extensively explored. Here, we examine population substructure and interbreed diversity among eight breeds of cattle using 2,641 autosomal genome-wide SNPs. Results and Discussion Preliminary analyses were performed using the STRUCTURE software. We first explored the appropriate number of iterations for the initial burn-in and estimation phases of the analysis. These preliminary analyses indicated that the probability of the number of ancestral populations (the K parameter from STRUCTURE) being greater than five was very small and therefore we restricted our analyses of all datasets to K 5 to limit computation time (data not shown). Analyses were performed on three datasets which used the full complement of markers but varied according to breed representation. The first analysis included data for all.