Expanded and mega-plex STR panels as a tool for presumptive population assignment

Historically, forensic STR panels have been unsuccessful for population assignment due to the limited ancestry information that can be derived from the non-coding STR loci and the low number of loci included in the panel. However, given the recent adoption of expanded (16+ loci) and ‘mega-plex’ (23+ loci) STR panels, the ability to identify source population groups may be improved. This study assessed the impact of increasing locus number on population assignment under different analysis conditions using a published US population dataset comprised of individuals from the African American, Caucasian, Hispanic and Asian populations. The Bayesian clustering programme STRUCTURE was used to assess first, whether increasing the number of loci and the inclusion of known sample population data enabled greater resolution between the four populations in the dataset, and second, the utility for population assignment using criteria based on inferred ancestry scores. Results suggest that increasing the number of loci and including population of origin data allowed the identification of more distinct populations, with three primary populations being observed; African American, Asian, and Caucasian/Hispanic. The close grouping of the Caucasian and Hispanic populations is supported by their recently common ancestry from Western Europe. The ability of the programme to support population assignment to each of the four existing populations was assessed through the application of population and panel specific assignment thresholds based on the inferred ancestry scores obtained from the analysis programme. Predictive accuracy based on a training dataset of 984 individuals suggest that assignment accuracy is > 96% across the four populations and can reach 100% under some test conditions. The accuracy was > 90% when blind testing was performed on 40 ‘unknown’ individuals. As such, the approach described is considered within the acceptable range for a presumptive test and can be performed using data already collected as part of routine forensic investigations.