Estimation of the number of contributors of theoretical mixture profiles based on allele counting: Does increasing the number of loci increase success rate of estimates?

DNA mixtures are more frequently encountered in casework due to increased kit sensitivity, protocols with increased cycle number, and requests for low copy number DNA samples to be tested. Generally, the first step in mixture interpretation is determining the number of contributors, with the most common approach of maximum allele count. Although there are previous studies regarding the accuracy of this approach, none have evaluated the accuracy with the newly expanded U.S. core STR loci. In this work, 4,976,355 theoretical mixture combinations were generated with the PowerPlex® Fusion 6C system which includes 23 autosomal STR loci and three Y-STR loci. The number of contributors could be correctly assumed for 100% two-person and 99.99% three-person mixtures, whereas, four-, five-, and six-person mixtures were correctly assumed in 89.7%, 57.3%, and 7.8% of mixtures, respectively. Y-STR analysis showed the 3 Y-STR markers are only accurate for two-person male mixtures (96.7%). This work demonstrates that maximum allele count using the expanded U.S. core loci is not much improved from previous smaller panels, reiterating that this method is not as accurate beyond three contributors.

Effects of microbial DNA on human DNA profiles generated using the PowerPlex® 16 HS system.

Most crime scenes are not sterile and therefore may be contaminated with environmental DNA, especially if a decomposing body is found. Collecting biological evidence from this individual will yield DNA samples mixed with microbial DNA. This also becomes important if postmortem swabs are collected from sexually assaulted victims. Although genotyping kits undergo validation tests, including bacterial screens, they do not account for the diverse microbial load during decomposition. We investigated the effect of spiking human DNA samples with known concentrations of DNA from 17 microbe species associated with decomposition on DNA profiles produced using the Promega PowerPlex® HS system. Two species, Bacillus subtilis and Mycobacterium smegmatis, produced an extraneous allele at the TPOX locus. When repeated with the PowerPlex® Fusion kit, the extra allele no longer amplified with these two species. This experiment demonstrates that caution should be exhibited if microbial load is high and the PowerPlex® 16HS system is used.

Evaluation of the IrisPlex DNA-based eye color prediction assay in a United States population.

DNA phenotyping is a rapidly developing area of research in forensic biology. Externally visible characteristics (EVCs) can be determined based on genotype data, specifically based on single nucleotide polymorphisms (SNPs). These SNPs are chosen based on their association with genes related to the phenotypic expression of interest, with known examples in eye, hair, and skin color traits. DNA phenotyping has forensic importance when unknown biological samples at a crime scene do not result in a criminal database hit; a phenotypic profile of the sample can therefore be used to develop investigational leads. IrisPlex, an eye color prediction assay, has previously shown high prediction rates for blue and brown eye color in a Dutch European population. The objective of this work was to evaluate its utility in a North American population. We evaluated six SNPs included in the IrisPlex assay in population sample collected from a USA college campus. We used a quantitative method of eye color classification based on (RGB) color components of digital photographs of the eye taken from each study volunteer so that each eye was placed in one of three eye color categories: brown, intermediate, or blue. Objective color classification was shown to correlate with basic human visual determination making it a feasible option for use in future prediction assay development. Using these samples and various models, the maximum prediction accuracies of the IrisPlex system after allele frequency adjustment was 58% and 95% brown and blue eye color predictions, respectively, and 11% for intermediate eye colors. Future developments should include incorporation of additional informative SNPs, specifically related to the intermediate eye color, and we recommend the use of a Bayesian approach as a prediction model as likelihood ratios can be determined for reporting purposes.