Massively parallel sequencing (MPS) is a powerful tool that transforms DNA analysis in multiple fields, ranging from medicine to environmental science and evolutionary biology. In forensic applications, MPS can significantly increase the discriminatory power of human identification, as well as aid in mixture deconvolution; however, before the benefits of any new technology can be realized, its quality, consistency, sensitivity, and specificity must be rigorously evaluated in order to gain a detailed understanding of the technique, including sources of error, error rates, and other restrictions/limitations. The current study used In-depth data analysis to evaluate the consequences of different assay conditions on test results. Variables included sample numbers per run, targets per run, DNA input per sample, and replications. Results are presented as heat maps that show patterns for each locus. Data analysis focused on read numbers (allele coverage), drop-outs, drop-ins, and sequence analysis. The study found that loci with high read numbers performed better and resulted in fewer drop-outs and well balanced heterozygous alleles. Several loci were prone to drop-outs, which led to falsely typed homozygotes and, therefore, to genotype errors. Sequence analysis of allele drop-in typically revealed a single nucleotide change (deletion, insertion, or substitution). Analyses of sequences, no template controls, and spurious alleles suggest no contamination occurred during library preparation, pooling, and sequencing, but indicate that sequencing or PCR errors may have occurred due to DNA polymerase infidelities. Finally, the evaluation found that using Illumina's FGx System at recommended conditions does not guarantee 100-percent outcomes for all samples tested, including the positive control, and required manual editing due to low read numbers and/or allele drop-in. These findings are important for progress toward implementation of MPS in forensic DNA testing. 3 figures (publisher abstract modified)
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