Evaluation of Forensic Efficiency Parameters of 19 Autosomal STR Markers in a Population Sample of Arabs Residing in Voronezh, Russia
Keywords:
STR, TPOX locus, Genetic diversity, Arab populationsAbstract
The accuracy of DNA profile identification is significantly enhanced by increasing the number of STR markers that are examined. Forensic markers' usefulness depends on the population, necessitating regional studies. This study aims to provide a better understanding of the effectiveness of autosomal STR loci as a forensic tool by comparing the genetic factors found in Arabs living in Voronezh, Russia, to published datasets from other Arab groups. Blood samples were collected from 98 unrelated Arab volunteers. Using a 3130XL Genetic Analyzer, DNA typing was conducted for 19 polymorphic STR loci and the Amelogenin locus with the use of the GOrDIS Plus kit. The analysis revealed a high degree of polymorphism, with the number of alleles per locus ranging from 6 to 36. The highest allele frequency observed was 0.5816 at the TPOX locus. The observed heterozygosity (Ho) and expected heterozygosity (He) values were generally consistent, indicating that the population is largely in Hardy–Weinberg equilibrium (HWE). The forensic parameters demonstrated high discriminatory power: the Power of Discrimination (PD) ranged from 0.813 to 0.962, the Polymorphism Information Content (PIC) from 0.58 to 0.86, and the Power of Exclusion (PE) from 0.388 to 0.689. High Ho was observed at FGA and D21S11 loci (87.76% and 87.8%, respectively), while TPOX showed the lowest Ho (63.27%).In conclusion, the Analysis of Molecular Variance (AMOVA) and pairwise FST analysis indicated that Arabs residing in Voronezh, Russia, show strong genetic similarities with Arab populations in Europe and Arab countries. These findings underscore the robustness of the selected STR markers for forensic applications within this population and contribute valuable data to the global forensic genetic database.
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Copyright (c) 2025 Jaber M. M. T., Mohammed M. Al-Zubaidi, Miriam Jasim Shehab, Zahraa Mustafa AL-Jumaa, Nisred Klichkhanov

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