Exploring Taxonomic and Genetic Relationships in the Complex Using Genome Skimming Data.

Int J Mol Sci

Department of Genetics, Institute of Experimental Biology, Faculty of Biology, School of Natural Sciences, Adam Mickiewicz University, Uniwersytetu Poznańskiego 6, 61-614 Poznań, Poland.

Published: September 2024

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 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 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 complex. In light of the obtained results, × does not belong to the complex and should not be identified with either or . It seems to represent a fixed hybrid or introgressant between and . In turn, and apparently played an important role in the origins of and .

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11432513PMC
http://dx.doi.org/10.3390/ijms251810178DOI Listing

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