Demographic insights into paternal genetic diversity and regional substructure in the Spanish Roma

The Iberian (Calé) Roma constitute one of the largest Roma communities in Europe, yet their internal genetic structure and connections to other Roma groups remain understudied. This study explores the microgeographical structure of the Iberian Roma and their relationships with other Roma groups by analysing paternal lineages using 17 Y-chromosome short tandem repeat markers in a geographically stratified sample of 173 Spanish Roma individuals.

The haplogroup distribution patterns indicate that the paternal genetic profile of the Spanish Roma is shaped by founder effects, population bottlenecks, and multiple admixture events with non-Roma groups. Haplogroups H and J2a1b dominate the genetic landscape, reflecting their South Asian origin and subsequent dispersal patterns through West Asia into Europe. A distinctive feature of the Spanish Roma is the high frequency of haplogroup R1b, indicating significant gene flow from non-Roma Iberian populations. The absence of North African or Jewish genetic influences rules out the possibility of a North African migration route for the Calé Roma into the Iberian Peninsula. Microgeographical analyses (AMOVA) reveal substantial genetic substructure among Calé Roma across Spanish regions, consistent with historical isolation and localised gene flow. Additionally, a striking sex-biased admixture is observed when comparing the current results with previous mitochondrial DNA (mtDNA) data, with paternal South Asian ancestry being twice as high as maternal contributions, suggesting that Roma communities have historically been more inclined to integrate non-Roma women.

The genetic landscape of the Iberian Roma is shaped by a complex history of founder effects, admixture, and isolation. The observed genetic substructure and sex-biased admixture reflect historical social dynamics. These results contribute to the broader understanding of Roma genetic diversity and demography in Spain and underscore the importance of integrating Y chromosome, autosomal, and mtDNA data in future studies.