A strategy for distant kinship analysis using historical human remains: First identifications of Stalinist terror...

The identification of human remains from historical and post-conflict contexts remains a major challenge due to DNA degradation and limited availability of close relatives. This study presents an integrative approach combining biogeographical ancestry inference, multiple genetic marker systems (standard and non-standard STRs, iiSNPs) and biostatistical evaluation to support kinship inference within a large-scale human rights investigation in Georgia. The aim of the study was to maximise the number of individuals who could be reliably identified despite DNA degradation and distant kinship, while simultaneously assessing the evidential value of different marker systems-including determining the suitability of the KinFinder panel for historical casework-and evaluating whether extended STR-based approaches can offer a viable alternative to large, cost-intensive SNP panels.

Samples from 28 victims and 20 families of missing persons were analysed using autosomal STRs (GlobalFiler), Y-STRs (YFiler Plus), additional kinship-focused STRs (KinFinder), and iiSNPs (Precision ID Identity Panel). Y-STRs and Y-SNPs were used for BGA. LR distribution simulations were performed to estimate expected LRs for kiships initially appointed by the DVI module of Familias. LR calculations were conducted under both independence and linkage-corrected assumptions.

Successful identification was achieved for all historically supported victim candidates with available comparative family material, corresponding to 17 of the 28 individuals recovered from the burial site. Linkage effects were minimal and small-scale SNP-based analyses were not the most informative for distant kinships.

This study represents the first successful application of such a strategy in large-scale human rights investigations in the Caucasus region and, to the best of our knowledge, one of the first globally. The results demonstrate that integrating multiple marker systems with advanced statistical modelling can substantially improve identification outcomes in long-term post-conflict contexts.