Genome skimming is a novel approach that enables obtaining large-scale genomic information based on high-copy DNA fractions from shallow whole-genome sequencing. The simplicity of this method, low analysis costs, and large amounts of generated data have made it widely used in plant research, including species identification, especially in the case of protected or endangered taxa. This task is particularly difficult in the case of closely related taxa. The Pinus mugo complex includes several dozen closely related taxa occurring in the most important mountain ranges in Europe. The taxonomic rank, origin, or distribution of many of these taxa have been debated for years. In this study, we used genome skimming and multilocus DNA barcoding approaches to obtain different sequence data sets and also to determine their genetic diversity and suitability for distinguishing closely related taxa in the Pinus mugo complex. We generated seven different data sets, which were then analyzed using three discrimination methods, i.e., tree based, distance based, and assembling species by automatic partitioning. Genetic diversity among populations and taxa was also investigated using haplotype network analysis and principal coordinate analysis. The proposed data set based on divergence hotspots is even twenty-times more variable than the other analyzed sets and improves the phylogenetic resolution of the Pinus mugo complex. In light of the obtained results, Pinus × rhaetica does not belong to the Pinus mugo complex and should not be identified with either Pinus uliginosa or Pinus rotundata. It seems to represent a fixed hybrid or introgressant between Pinus sylvestris and Pinus mugo. In turn, Pinus mugo and Pinus uncinata apparently played an important role in the origins of Pinus uliginosa and Pinus rotundata.
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