Accurate Digital Polymerase Chain Reaction Quantification of Challenging Samples Applying Inhibitor-Tolerant DNA Polymerases

Digital PCR (dPCR) enables absolute quantification of nucleic acids by partitioning of the sample into hundreds or thousands of minute reactions. By assuming a Poisson distribution for the number of DNA fragments present in each chamber, the DNA concentration is determined without the need for a standard curve. However, when analyzing nucleic acids from complex matrixes such as soil and blood, the dPCR quantification can be biased due to the presence of inhibitory compounds. In this study, we evaluated the impact of varying the DNA polymerase in chamber-based dPCR for both pure and impure samples using the common PCR inhibitor humic acid (HA) as a model. We compared the TaqMan Universal PCR Master Mix with two alternative DNA polymerases: ExTaq HS and Immolase. By using Bayesian modeling, we show that there is no difference among the tested DNA polymerases in terms of accuracy of absolute quantification for pure template samples, i.e., without HA present. For samples containing HA, there were great differences in performance: the TaqMan Universal PCR Master Mix failed to correctly quantify DNA with more than 13 pg/nL HA, whereas Immolase (1 U) could handle up to 375 pg/nL HA. Furthermore, we found that BSA had a moderate positive effect for the TaqMan Universal PCR Master Mix, enabling accurate quantification for 25 pg/nL HA. Increasing the amount of DNA polymerase from 1 to 5 U had a strong effect for ExTaq HS, elevating HA-tolerance four times. We also show that the average Cq values of positive reactions may be used as a measure of inhibition effects, e.g., to determine whether or not a dPCR quantification result is reliable. The statistical models developed to objectively analyze the data may also be applied in quality control. We conclude that the choice of DNA polymerase in dPCR is crucial for the accuracy of quantification when analyzing challenging samples

Collaborative EDNAP exercise on the IrisPlex system for DNA-based prediction of human eye colour

The IrisPlex system is a DNA-based test system for the prediction of human eye colour from biological samples and consists of a single forensically validated multiplex genotyping assay together with a statistical prediction model that is based on genotypes and phenotypes from thousands of individuals. IrisPlex predicts blue and brown human eye colour with, on average, >94% precision accuracy using six of the currently most eye colour informative single nucleotide polymorphisms (HERC2 rs12913832, OCA2 rs1800407, SLC24A4 rs12896399, SLC45A2 (MATP) rs16891982, TYR rs1393350, and IRF4 rs12203592) according to a previous study, while the accuracy in predicting non-blue and non-brown eye colours is considerably lower. In an effort to vigorously assess the IrisPlex system at the international level, testing was performed by 21 laboratories in the context of a collaborative exercise divided into three tasks and organised by the European DNA Profiling (EDNAP) Group of the International Society of Forensic Genetics (ISFG). Task 1 involved the assessment of 10 blood and saliva samples provided on F