Comparative Analysis of the Genetic Composition of Minorities in the Carpathian Basin Through Genome-Wide Autosomal Data

Abstract

Background/Objectives: The Carpathian Basin is a genetically and culturally diverse region shaped by complex historical migrations and various ethnic groups. While studies based on Y-chromosomal and mitochondrial DNA have provided valuable insights into the genetic diversity of these populations, genome-wide autosomal SNP data remain underutilized in understanding the genetic structure of these groups. This study presents the first genome-wide autosomal SNP-based analysis of key Hungarian-speaking ethnic groups in the region, focusing on admixture patterns and the extent of preserved historical genetic components. Methods: We analyzed genome-wide autosomal SNP data from 597 individuals representing several ethnic groups in the Carpathian Basin. Standard population genetic methods were applied to assess genetic structure, admixture and differentiation, with comparisons to broader European reference populations. Results: Most ethnic groups displayed genetic affinities with Eastern European populations, consistent with historical and geographical proximity. The Swabian group, of German descent, exhibited a distinct Western European genetic component, likely due to historical isolation. Transylvanian populations appeared relatively homogeneous, indicating a shared ancestral background. In contrast, Csangos showed distinct sub-clusters, suggesting population isolation and distinct histories. Overall, genetic homogeneity characterizes the region, though certain isolated groups retain distinct ancestral signatures. Conclusions: Autosomal SNP analysis revealed mild overall genetic structuring among Carpathian Basin ethnic groups. However, historical isolation has preserved unique genetic components in specific groups, highlighting the value of genome-wide data in uncovering fine-scale population structure. These findings contribute to a deeper understanding of regional genetic diversity, which has implications for both population history and health-related genetic research.