Přehled o publikaci

Plant genomes consist, to a considerable extent, of non-coding repetitive DNA. Several studies showed that phylogenetic signals can be extracted from such repeatome data by using among-species dissimilarities from the RepeatExplorer2 pipeline as distance measures. Here, we advanced this approach by adjusting the read input for comparative clustering indirectly proportional to genome size and by summarizing all clusters into a main distance matrix subjected to Neighbor Joining algorithms and Principal Coordinate Analyses. Thus, our multivariate statistical method works as a “repeatomic fingerprint,” and we proved its power and limitations by exemplarily applying it to the family Rosaceae at intrafamilial and, in the genera Fragaria and Rosa, at the intrageneric level. Since both taxa are prone to hybridization events, we wanted to show whether repeatome data are suitable to unravel the origin of natural and synthetic hybrids. In addition, we compared the results based on complete repeatomes with those from ribosomal DNA clusters only, because they represent one of the most widely used barcoding markers. Our results demonstrated that repeatome data contained a clear phylogenetic signal supporting the current subfamilial classification within Rosaceae. Accordingly, the well-accepted major evolutionary lineages within Fragaria were distinguished, and hybrids showed intermediate positions between parental species in data sets retrieved from both complete repeatomes and rDNA clusters. Within the taxonomically more complicated and particularly frequently hybridizing genus Rosa, we detected rather weak phylogenetic signals but surprisingly found a geographic pattern at a population scale. In sum, our method revealed promising results at larger taxonomic scales as well as within taxa with manageable levels of reticulation, but success remained rather taxon specific. Since repeatomes can be technically easy and comparably inexpensively retrieved even from samples of rather poor DNA quality, our phylogenomic method serves as a valuable alternative when high-quality genomes are unavailable, for example, in the case of old museum specimens.