The interpretation of mixed DNA samples historical: Perspective and current developments

The interpretation of mixed DNA samples represents a very compelling research field for the forensic community. Modern short tandem repeat (STR)-based kits can sequence several markers with a high degree of diversity; in the same way, the analysis of STR sequence variation in sample population groups highlighted that several current STR loci lack the necessary sequence diversity. Moreover, in the past few years, new forensic DNA profiling methodologies have been developed based on the use of massively parallel sequencing (MPS), also referred to as nextgeneration sequencing (NGS). The current human STR kits use markers with different heterozygosities, showing some highly heterozygous loci, while others are only marginally heterozygous. New methods offer the opportunity to enhance human identification for forensic purposes in DNA mixtures: using new multiplex kits with highly heterozygous STRs, it is possible to solve more effectively the interpretation of many complex mixture samples. Regarding these concerns, MPS methods have improved the discrimination power by investigating genetic diversity through the analysis of both STRs and single-nucleotide polymorphisms (SNPs) located near the flanking region. Nevertheless, to date, the mixtures generated by more than two contributors (three or more persons) remain frequently unsolved because of the difficulties in the evaluation of stochastic effects and/or other technical problems, such as the differences between true alleles and stutter products. For these reasons, future studies are needed in order to overcome both these technical and interpretation difficulties. Finally, it is important to remark on the importance of statistical methods to establish the "weight of the evidence," particularly for the interpretation of MPS multiplex kits for forensic DNA analysis. The interpretation of MPS results remains another interesting research field for the forensic community, particularly in the application of statistical methodologies.