Common lilac (Syringa vulgaris L.) is a popular landscaping plant. In the present study, its genotypes were investigated using genotyping-by-sequencing (GBS) methodology. Our aim was to obtain a large set of SNP markers, to reveal the precise identities of the investigated S. vulgaris accessions, and to discover genetic relationships among them. The studied plant material included local Finnish, previously unidentified accessions, known reference cultivars, and so-called historical accessions i.e., old shrubs growing in historic cultural landscapes. We intended to verify cultivar names for some valuable local common lilac accessions and to provide insights into the history of common lilac cultivation in Finland. In the analyses, we used a set of 15,007 SNP markers. First, polymorphic information contents (PIC) were calculated (mean 0.190, range 0.012–0.500 per marker). Then, to investigate genetic relationships among genotypes, a phylogenetic tree was constructed, and a principal coordinate analysis (PCoA) was conducted. A Bayesian analysis of population structure was carried out to determine the number and distribution of genetic clusters among samples. Genetic marker data combined with existing historical and phenotypic knowledge revealed novel information on the unidentified cultivars and on the genetic relationships among studied accessions, and solved the arrival and early history of common lilac in Finland. Overall, such comprehensive genomic characterization and deep understanding of genetic relationships of S. vulgaris can be used when utilizing present cultivars and developing new ones in future breeding programs.

Genotyping by sequencing of 85 S. vulgaris samples was conducted by using a genome profiling service by Diversity Arrays Technology Pty Ltd. (Canberra, Australia, http://www.diversityarrays.com), following the DArT genotyping protocol. Pairwise genetic distances between S. vulgaris genotypes were calculated by GenAlEx 6.5. Based on the distance values, a phylogenetic tree was constructed and visualized using the Neighbor-Joining method with Mega 6. GenAlEx was also used to conduct a principal coordinate analysis (PCoA) to investigate genetic relationships among genotypes. A Bayesian analysis of population structure using software Structure 2.3.4. was carried out to determine the number and distribution of genetic clusters among samples.

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