The advent of massively parallel sequencing (MPS) in the past decade has opened the doors to mitochondrial whole-genome sequencing. Mitochondrial (mt) DNA is used in forensics due to its high copy number per cell and maternal mode of inheritance. Consequently, we have implemented the Thermo Fisher Precision ID mtDNA Whole Genome panel coupled with the Ion Chef™ and Ion S5™ for MPS analysis in the California Department of Justice, Missing Persons DNA Program. Thirty-one mostly challenging samples (degraded, inhibited, low template, or mixed) were evaluated for this study. The majority of these samples generated single source full or partial genome sequences with MPS, providing information in cases where previously there was none. The quantitative and sensitive nature of MPS analysis was beneficial, but also led to detection of low-level contaminants. In addition, we found Precision ID to be more susceptible to inhibition than our legacy Sanger assay. Overall, the success rate (full single source hypervariable regions I and II (HVI/HVII) for Sanger and control region for MPS result) for these challenging samples increased from 32.3% with Sanger sequencing to 74.2% with the Precision ID assay. Considering the increase in success rate, the simple workflow and the higher discriminating potential of whole genome data, the Precision ID platform is a significant improvement for the CA Department of Justice Missing Persons DNA Program.

Points of view in this document are those of the authors and do not necessarily represent the official position or policies of their organizations.Names of commercial manufacturers are provided for identification purposes only, and inclusion does not imply endorsement of the manufacturer, or its products or services by the FBI.

In cases where multiple questioned individuals are separately supported as contributors to a mixed DNA profile, guidance documents recommend performing a comparison to see if there is support for their joint contribution. Anecdotal observations suggest the summed log of the individual likelihood ratios (LR), termed the simple LR product, should be roughly equivalent to or less than the log(LR) for the joint likelihood ratio, termed the compound LR. To assist casework analysts in evaluating statistical weights applied to a case at hand, this study assessed how consistently compound LRs conform to an additive behavior when compared to the simple LR product counterparts. Two-, three-, and four-person DNA mixture data, of various mixture proportions and DNA inputs, were interpreted by STRmix® version 2.8 Probabilistic Genotyping Software. Relative magnitudes of LR increases were found to be dependent on both template level and mixture composition. The distribution of log(LR) differences between all compound/simple LR comparisons was ~−2.7 to ~28.3. This level of information gain was similar to that for compound LR comparisons, with and without interpretation conditioning (~−3.2 to ~27.7). In both scenarios, the probability density peaked at approximately 0.5, indicating the information gain from constrained genotype combinations has a comparable impact on the outcome of LR calculations whether the restriction is applied before or after interpretation.

Distributions of the variance parameter values developed during the validation process. Comparisons of these prior distributions to the run-specific average are one measure used by analysts to assess the reliability of a STRmix deconvolution. This study examined the behavior of three different STRmix variance parameters under standard amplification and interpretation conditions, as well as under a variety of challenging conditions, with the goal of making comparisons to the prior distributions more practical and meaningful. Using information found in STRmix v2.8 Interpretation Reports, we plotted the log10 of each variance parameter against the log10 of the template amount of the highest-level contributor (Tc) for a large set of mixture data amplified under standard conditions. We observed nonlinear trends in these plots, which we regressed to fourth-order polynomials, and used the regression data to establish typical ranges for the variance parameters over the Tc range. We then compared the typical variance parameter ranges to log10(variance parameter) v log10(Tc) plots for mixtures amplified and interpreted under a variety of challenging conditions. We observed several distinct patterns to variance parameter shifts in the challenged data interpretations in comparison to the unchallenged data interpretations, as well as distinct shifts in the unchallenged variance parameters away from their prior gamma distribution modes over specific ranges of Tc. These findings suggest that employing empirically determined working ranges for variance parameters may be an improved means of detecting whether aberrations in the interpretation were meaningful enough to trigger greater scrutiny of the electropherogram and genotype interpretation.