Next-generation ancient DNA technologies have the potential to assist in the analysis of degraded DNA extracted from forensic specimens. Mitochondrial genome (mitogenome) sequencing, specifically, may be of benefit to samples that fail to yield forensically relevant genetic information using conventional PCR-based techniques. This report summarizes the Armed Forces Medical Examiner System's Armed Forces DNA Identification Laboratory's (AFMES-AFDIL) performance evaluation of a Next-Generation Sequencing protocol for degraded and chemically treated past accounting samples. The procedure involves hybridization capture for targeted enrichment of mitochondrial DNA, massively parallel sequencing using Illumina chemistry, and an automated bioinformatic pipeline for forensic mtDNA profile generation. A total of 22 non-probative samples and associated controls were processed in the present study, spanning a range of DNA quantity and quality. Data were generated from over 100 DNA libraries by ten DNA analysts over the course of five months. The results show that the mitogenome sequencing procedure is reliable and robust, sensitive to low template (one ng control DNA) as well as degraded DNA, and specific to the analysis of the human mitogenome. Haplotypes were overall concordant between NGS replicates and with previously generated Sanger control region data. Due to the inherent risk for contamination when working with low-template, degraded DNA, a contamination assessment was performed. The consumables were shown to be void of human DNA contaminants and suitable for forensic use. Reagent blanks and negative controls were analyzed to determine the background signal of the procedure. This background signal was then used to set analytical and reporting thresholds, which were designated at 4.0X (limit of detection) and 10.0X (limit of quantiation) average coverage across the mitogenome, respectively. Nearly all human samples exceeded the reporting threshold, although coverage was reduced in chemically treated samples resulting in a ∼58% passing rate for these poor-quality samples. A concordance assessment demonstrated the reliability of the NGS data when compared to known Sanger profiles. One case sample was shown to be mixed with a co-processed sample and two reagent blanks indicated the presence of DNA above the analytical threshold. This contamination was attributed to sequencing crosstalk from simultaneously sequenced high-quality samples to include the positive control. Overall this study demonstrated that hybridization capture and Illumina sequencing provide a viable method for mitogenome sequencing of degraded and chemically treated skeletal DNA samples, yet may require alternative measures of quality control.

The FORensic Capture Enrichment (FORCE) panel is an all-in-one SNP panel for forensic applications. This panel of 5422 markers encompasses common, forensically relevant SNPs (identity, ancestry, phenotype, X- and Y-chromosomal SNPs), a novel set of 3931 autosomal SNPs for extended kinship analysis, and no clinically relevant/disease markers. The FORCE panel was developed as a custom hybridization capture assay utilizing ~20,000 baits to target the selected SNPs. Five non-probative, previously identified World War II (WWII) cases were used to assess the kinship panel. Each case included one bone sample and associated family reference DNA samples. Additionally, seven reference quality samples, two 200-year-old bone samples, and four control DNAs were processed for kit performance and concordance assessments. SNP recovery after capture resulted in a mean of ~99% SNPs exceeding 10X coverage for reference and control samples, and 44.4% SNPs for bone samples. The WWII case results showed that the FORCE panel could predict first to fifth degree relationships with strong statistical support (likelihood ratios over 10,000 and posterior probabilities over 99.99%). To conclude, SNPs will be important for further advances in forensic DNA analysis. The FORCE panel shows promising results and demonstrates the utility of a 5000 SNP panel for forensic applications.

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Next-generation sequencing (NGS) facilitates the rapid and high-throughput generation of human mitochondrial genome (mitogenome) data to build population and reference databases for forensic comparisons. To this end, long-range amplification provides an effective method of target enrichment that is amenable to library preparation assays employing DNA fragmentation. This study compared the Nextera XT DNA Library Preparation Kit (Illumina, San Diego, CA) and the KAPA HyperPlus Library Preparation Kit (Kapa Biosystems, Wilmington, MA) for enzymatic fragmentation and indexing of ∼8500bp mitogenome amplicons for Illumina sequencing. The Nextera XT libraries produced low-coverage regions that were consistent across all samples, while the HyperPlus libraries resulted in uniformly high coverage across the mitogenome, even with reduced-volume reaction conditions. The balanced coverage observed from KAPA HyperPlus libraries enables not only low-level variant calling across the mitogenome but also increased sample multiplexing for greater processing efficiency.

Nuclear mitochondrial DNA segments (NUMTs) have arisen because of the transposition of segments of the mitochondrial DNA genome (mitogenome) into the nuclear genome. When using a "mitotiling" strategy, NUMTs may be more readily amplified when targeting the entire mitogenome compared to the control region, as hundreds of primers are required for complete sequencing coverage. In samples with a high percentage of nuclear DNA copies per cell, such as whole blood, NUMT coenrichment may be exacerbated. The present study examined bioinformatic approaches for removing NUMTs and NUMT-associated variants (NAVs) from next-generation sequence data generated using two mitotiling kits (Precision ID and QIAseq). Across 16 samples with low mtDNA copy number, NUMT coenrichment produced 890 NAVs with >5% variant frequency. The use of the consensus sequence to eliminate NUMT reads proved to be effective for QIAseq data, and resulted in >85% NAV removal in Precision ID data. This method was bolstered by NAV filtering in Precision ID analysis. Alternative high stringency mapping to the revised Cambridge Reference Sequence (rCRS) and the human genome reference GRCh38 for the QIAseq data caused a reduction in mitogenome coverage without complete NUMT removal. These bioinformatic solutions facilitate mitotiling sequence data analysis for low-level variant detection.