Although the genetic heritage of aboriginal Siberians is mostly of eastern Asian ancestry, a substantial western Eurasian component is observed in the majority of northern Asian populations. Traces of at least two migrations into southern Siberia, one from eastern Europe and the other from western Asia/the Caucasus have been detected previously in mitochondrial gene pools of modern Siberians. We report here 166 new complete mitochondrial DNA (mtDNA) sequences that allow us to expand and re-analyze the available data sets of western Eurasian lineages found in northern Asian populations, define the phylogenetic status of Siberian-specific subclades and search for links between mtDNA haplotypes/subclades and events of human migrations. From a survey of 158 western Eurasian mtDNA genomes found in Siberia we estimate that nearly 40% of them most likely have western Asian and another 29% European ancestry. It is striking that 65 of northern Asian mitogenomes, i.e. ~41%, fall into 19 branches and subclades which can be considered as Siberian-specific being found so far only in Siberian populations. From the coalescence analysis it is evident that the sequence divergence of Siberian-specific subclades was relatively small, corresponding to only 0.6-9.5 kya (using the complete mtDNA rate) and 1-6 kya (coding region rate). The phylogeographic analysis implies that the western Eurasian founders, giving rise to Siberian specific subclades, may trace their ancestry only to the early and mid-Holocene, though some of genetic lineages may trace their ancestry back to the end of Last Glacial Maximum (LGM). We have not found the modern northern Asians to have western Eurasian genetic components of sufficient antiquity to indicate traces of pre-LGM expansions.

Data obtained with the use of massive parallel sequencing (MPS) can be valuable in population genetics studies. In particular, such data harbor the potential for distinguishing samples from different populations, especially from those coming from adjacent populations of common origin. Machine learning (ML) techniques seem to be especially well suited for analyzing large datasets obtained using MPS. The Slavic populations constitute about a third of the population of Europe and inhabit a large area of the continent, while being relatively closely related in population genetics terms. In this proof-of-concept study, various ML techniques were used to classify DNA samples from Slavic and non-Slavic individuals. The primary objective of this study was to empirically evaluate the feasibility of discerning the genetic provenance of individuals of Slavic descent who exhibit genetic similarity, with the overarching goal of categorizing DNA specimens derived from diverse Slavic population representatives. Raw sequencing data were pre-processed, to obtain a 1200 character-long binary vector. A total of three classifiers were used—Random Forest, Support Vector Machine (SVM), and XGBoost. The most-promising results were obtained using SVM with a linear kernel, with 99.9% accuracy and F1-scores of 0.9846–1.000 for all classes.