Abstract
We conducted genomic characterization based on SNP and SilicoDArT markers on the invasive Himalayan balsam (Impatiens glandulifera) plants originating from native and non-native regions of their distribution. When genetic relationships were explored by PCoA using SNP and SilicoDArT marker data, the first, second, and third principal coordinates explained altogether 37.4% and 31.0% of the variability, respectively. Samples from the UK, Canada, and Pakistan were grouped together, while Indian plants were clearly distinct based on SNP markers but relatively close to the UK-Canada-Pakistan group based on SilicoDArT markers. Constructed trees differentiated individuals into clusters resembling the PCoA patterns. The Bayesian BAPS analysis performed for the SNP data revealed that the individuals were distributed in seven clusters, representing samples from each of the four Finnish populations, India, Pakistan, and the combination of the UK and Canada. Similar clustering was visible in the UPGMA tree. The Indian cluster did not display any ancestral gene flow with the others, while the Pakistani cluster showed ancestral gene flow only with the combined UK and Canada cluster. Furthermore, the latter cluster displayed ancestral gene flow with the Finnish populations varying from 0% to 3.1%. The BAPS analyses conducted for the SilicoDArT data differ slightly: The individuals were distributed in nine clusters, and the Indian cluster exhibited ancestral gene flow with the mixed cluster including Canadian, Pakistani, and UK samples, and one Finnish sample. The AMOVA showed that 45% and 26% of variation was present among the I. glandulifera groups/populations and the rest within them based on SNP and SilicoDArT markers, respectively. The Bayesian BAPS analyses and the gene flow networks were the most informative tools for resolving relationships among native and introduced plants. It is notable that the small sample sizes for non-Finnish plant materials may affect the accuracy of the gene flow and other estimates.