Harmonizing the forensic nomenclature for STR loci D6S474 and DYS612.

The autosomal STR D6S474 and the Y-chromosomal STR DYS612 have been reported in multiple ways in the forensic literature, with differences in both the bracketed repeat structures and counting of numerical length-based capillary electrophoresis (CE) alleles. These issues often come to light when STR loci are introduced in commercial assays and results compared with historical publications of allele frequency data, or multiple assays are characterized with reference materials. We review the forensic literature and other relevant information, and provide suggestions for the future treatment of each STR.

Identifying distant relatives using benchtop-scale sequencing.

The genetic component of forensic genetic genealogy (FGG) is an estimate of kinship, often conducted at genome scales between a great number of individuals. The promise of FGG is substantial: in concert with genealogical records and other nongenetic information, it can indirectly identify a person of interest. A downside of FGG is cost, as it is currently expensive and requires chemistries uncommon to forensic genetic laboratories (microarrays and high throughput sequencing). The more common benchtop sequencers can be coupled with a targeted PCR assay to conduct FGG, though such approaches have limited resolution for kinship. This study evaluates low-pass sequencing, an alternative strategy that is accessible to benchtop sequencers and can produce resolutions comparable to high-pass sequencing. Samples from a three-generation pedigree were augmented to include up to 7th degree relatives (using whole genome pedigree simulations) and the ability to recover the true kinship coefficient was assessed using algorithms qualitatively similar to those found in GEDmatch. We show that up to 7th degree relatives can be reliably inferred from 1 × whole genome sequencing obtainable from desktop sequencers.

Mixture detection with Demixtify.

The de facto genetic markers of forensics are short tandem repeats (STRs). There are many analytical tools designed to work with STRs, including techniques for analyzing and assessing DNA mixtures. In contrast, the nascent field of forensic genetic genealogy often relies on biallelic single nucleotide polymorphisms (SNPs). Tools designed for the forensic assessment of SNPs are somewhat lacking, especially for DNA mixtures. In this paper we introduce Demixtify, a program that detects DNA mixtures using biallelic SNPs. Demixtify is quite powerful; highly imbalanced mixtures can be detected (≤1:99, considering in silico and in vitro mixtures) when coverage is ample. Demixtify can also detect mixtures in low coverage (∼1×) samples (when the mixture is relatively balanced). Demixtify includes an empirical estimator of sequence error that is specific to the markers assayed, making it especially relevant to the forensic community. Orthogonal techniques are also developed to characterize in vitro mixtures, as well as samples thought to be single source, and the results of these approaches serve to validate the techniques presented.

Bioinspired Switchable Passive Daytime Radiative Cooling Coatings.

Passive daytime radiative cooling (PDRC) relies on simultaneous reflection of sunlight and radiation toward cold outer space. Current designs of PDRC coatings have demonstrated potential as eco-friendly alternatives to traditional electrical air conditioning (AC). While many features of PDRC have been individually optimized in different studies, for practical impact, it is essential for a system to demonstrate excellence in all essential aspects, like the materials that nature has created. We propose a bioinspired PDRC structure templated by bicontinuous interfacially jammed emulsion gels (bijels) that possesses excellent cooling, thinness, tunability, scalability, and mechanical robustness. The unique bicontinuous disordered structure captures key features of Cyphochilus beetle scales, enabling a thin (130 µm) bijel PDRC coating to achieve high solar reflectance (≳0.97) and high longwave-infrared (LWIR) emissivity (≳0.93), resulting in a subambient temperature drop of ∼5.6 °C under direct sunlight. We further demonstrate switchable cooling inspired by the exoskeleton of the Hercules beetle and mechanical robustness in analogy to spongy bone structures.

Using unique molecular identifiers to improve allele calling in low-template mixtures.

PCR artifacts are an ever-present challenge in sequencing applications. These artifacts can seriously limit the analysis and interpretation of low-template samples and mixtures, especially with respect to a minor contributor. In medicine, molecular barcoding techniques have been employed to decrease the impact of PCR error and to allow the examination of low-abundance somatic variation. In principle, it should be possible to apply the same techniques to the forensic analysis of mixtures. To that end, several short tandem repeat loci were selected for targeted sequencing, and a bioinformatic pipeline for analyzing the sequence data was developed. The pipeline notes the relevant unique molecular identifiers (UMIs) attached to each read and, using machine learning, filters the noise products out of the set of potential alleles. To evaluate this pipeline, DNA from pairs of individuals were mixed at different ratios (1-1, 1-9) and sequenced with different starting amounts of DNA (10, 1 and 0.1 ng). Naïvely using the information in the molecular barcodes led to increased performance, with the machine learning resulting in an additional benefit. In concrete terms, using the UMI data results in less noise for a given amount of drop out. For instance, if thresholds are selected that filter out a quarter of the true alleles, using read counts accepts 2381 noise alleles and using raw UMI counts accepts 1726 noise alleles, while the machine learning approach only accepts 307.

Optimized variant calling for estimating kinship.

One of the fundamental goals of forensic genetics is sample attribution, i.e., whether an item of evidence can be associated with some person or persons. The most common scenario involves a direct comparison, e.g., between DNA profiles from an evidentiary item and a sample collected from a person of interest. Less common is an indirect comparison in which kinship is used to potentially identify the source of the evidence. Because of the sheer amount of information lost in the hereditary process for comparison purposes, sampling a limited set of loci may not provide enough resolution to accurately resolve a relationship. Instead, whole genome techniques can sample the entirety of the genome or a sufficiently large portion of the genome and as such they may effect better relationship determinations. While relatively common in other areas of study, whole genome techniques have only begun to be explored in the forensic sciences. As such, bioinformatic pipelines are introduced for estimating kinship by massively parallel sequencing of whole genomes using approaches adapted from the medical and population genomic literature. The pipelines are designed to characterize a person's entire genome, not just some set of targeted markers. Two different variant callers are considered, contrasting a classical variant calling algorithm (BCFtools) to a more modern deep convolution neural network (DeepVariant). Two different bioinformatic pipelines specific to each variant caller are introduced and evaluated in a titration series. Filters and thresholds are then optimized specifically for the purposes of estimating kinship as determined by the KING-robust algorithm. With the appropriate filtering and thresholds in place both tools perform similarly, with DeepVariant tending to produce more accurate genotypes, though the resultant types of inaccuracies tended to produce slightly less accurate overall estimates of relatedness.

Correcting thermal-emission-induced detector saturation in infrared spectroscopy.

We found that temperature-dependent infrared spectroscopy measurements (i.e., reflectance or transmittance) using a Fourier-transform spectrometer can have substantial errors, especially for elevated sample temperatures and collection using an objective lens. These errors can arise as a result of partial detector saturation due to thermal emission from the measured sample reaching the detector, resulting in nonphysical apparent reduction of reflectance or transmittance with increasing sample temperature. Here, we demonstrate that these temperature-dependent errors can be corrected by implementing several levels of optical attenuation that enable convergence testing of the measured reflectance or transmittance as the thermal-emission signal is reduced, or by applying correction factors that can be inferred by looking at the spectral regions where the sample is not expected to have a substantial temperature dependence.

Precision DNA Mixture Interpretation with Single-Cell Profiling.

Wet-lab based studies have exploited emerging single-cell technologies to address the challenges of interpreting forensic mixture evidence. However, little effort has been dedicated to developing a systematic approach to interpreting the single-cell profiles derived from the mixtures. This study is the first attempt to develop a comprehensive interpretation workflow in which single-cell profiles from mixtures are interpreted individually and holistically. In this approach, the genotypes from each cell are assessed, the number of contributors (NOC) of the single-cell profiles is estimated, followed by developing a consensus profile of each contributor, and finally the consensus profile(s) can be used for a DNA database search or comparing with known profiles to determine their potential sources. The potential of this single-cell interpretation workflow was assessed by simulation with various mixture scenarios and empirical allele drop-out and drop-in rates, the accuracies of estimating the NOC, the accuracies of recovering the true alleles by consensus, and the capabilities of deconvolving mixtures with related contributors. The results support that the single-cell based mixture interpretation can provide a precision that cannot beachieved with current standard CE-STR analyses. A new paradigm for mixture interpretation is available to enhance the interpretation of forensic genetic casework.

Reverse complement-PCR, an innovative and effective method for multiplexing forensically relevant single nucleotide polymorphism marker systems.

DNA analyses from challenging samples such as touch evidence, hairs and skeletal remains push the limits of the current forensic DNA typing technologies. Reverse complement PCR (RC-PCR) is a novel, single-step PCR target enrichment method adapted to amplify degraded DNA. The sample preparation process involves a limited number of steps, decreasing the labor required for library preparation and reducing the possibility of contamination due to less sample manipulation. These features of the RC-PCR make the technology a unique application to successfully target single nucleotide polymorphisms (SNPs) in fragmented and low copy number DNA and yield results from samples in which no or limited data are obtained with standard DNA typing methods. The developed RC-PCR short amplicon 85 SNP-plex panel is a substantial improvement over the previously reported 27-plex RC-PCR multiplex that will provide higher discrimination power for challenging DNA sample analyses.

MMDIT: A tool for the deconvolution and interpretation of mitochondrial DNA mixtures.

Short tandem repeats of the nuclear genome have been the preferred markers for analyzing forensic DNA mixtures. However, when nuclear DNA in a sample is degraded or limited, mitochondrial DNA (mtDNA) markers provide a powerful alternative. Though historically considered challenging, the interpretation and analysis of mtDNA mixtures have recently seen renewed interest with the advent of massively parallel sequencing. However, there are only a few software tools available for mtDNA mixture interpretation. To address this gap, the Mitochondrial Mixture Deconvolution and Interpretation Tool (MMDIT) was developed. MMDIT is an interactive application complete with a graphical user interface that allows users to deconvolve mtDNA (whole or partial genomes) mixtures into constituent donor haplotypes and estimate random match probabilities on these resultant haplotypes. In cases where deconvolution might not be feasible, the software allows mixture analysis directly within a binary framework (i.e. qualitatively, only using data on allele presence/absence). This paper explains the functionality of MMDIT, using an example of an in vitro two-person mtDNA mixture with a ratio of 1:4. The uniqueness of MMDIT lies in its ability to resolve mixtures into complete donor haplotypes using a statistical phasing framework before mixture analysis and evaluating statistical weights employing a novel graph algorithm approach. MMDIT is the first available open-source software that can automate mtDNA mixture deconvolution and analysis. The MMDIT web application can be accessed online at https://www.unthsc.edu/mmdit/. The source code is available at https://github.com/SammedMandape/MMDIT_UI and archived on zenodo (https://doi.org/10.5281/zenodo.4770184).

Evaluation of Promega PowerSeq™ Auto/Y systems prototype on an admixed sample of Rio de Janeiro, Brazil: Population data, sensitivity, stutter and mixture studies.

Forensic DNA typing typically relies on the length-based (LB) separation of PCR products containing short tandem repeat loci (STRs). Massively parallel sequencing (MPS) elucidates an additional level of STR motif and flanking region variation. Also, MPS enables simultaneous analysis of different marker-types - autosomal STRs, SNPs for lineage and identification purposes, reducing both the amount of sample used and the turn-around-time of analysis. Therefore, MPS methodologies are being considered as an additional tool in forensic genetic casework. The PowerSeq™ Auto/Y System (Promega Corp), a multiplex forensic kit for MPS, enables analysis of the 22 autosomal STR markers (plus Amelogenin) from the PowerPlex® Fusion 6C kit and 23 Y-STR markers from the PowerPlex® Y23 kit. Population data were generated from 140 individuals from an admixed sample from Rio de Janeiro, Brazil. All samples were processed according to the manufacturers' recommended protocols. Raw data (FastQ) were generated for each indexed sample and analyzed using STRait Razor v2s and PowerSeqv2.config file. The subsequent population data showed the largest increase in expected heterozygosity (23%), from LB to sequence-based (SB) analyses at the D5S818 locus. Unreported allele was found at the D21S11 locus. The random match probability across all loci decreased from 5.9 × 10-28 to 7.6 × 10-33. Sensitivity studies using 1, 0.25, 0.062 and 0.016 ng of DNA input were analyzed in triplicate. Full Y-STR profiles were detected in all samples, and no autosomal allele drop-out was observed with 62 pg of input DNA. For mixture studies, 1 ng of genomic DNA from a male and female sample at 1:1, 1:4, 1:9, 1:19 and 1:49 proportions were analyzed in triplicate. Clearly resolvable alleles (i.e., no stacking or shared alleles) were obtained at a 1:19 male to female contributor ratio. The minus one stutter (-1) increased with the longest uninterrupted stretch (LUS) allele size reads and according to simple or compound/complex repeats. The haplotype-specific stutter rates add more information for mixed samples interpretation. These data support the use of the PowerSeqTM Auto/Y systems prototype kit (22 autosomal STR loci, 23 Y-STR loci and Amelogenin) for forensic genetics applications.

Autosomal STR and SNP characterization of populations from the Northeastern Peruvian Andes with the ForenSeq™ DNA Signature Prep Kit.

Autosomal DNA data from Peru for human identity testing purposes are scarce in the scientific literature, which hinders obtaining an appropriate portrait of the genetic variation of the resident populations. In this study we genetically characterize five populations from the Northeastern Peruvian Andes (Chachapoyas, Awajún, Wampís, Huancas and Cajamarca). Autosomal short tandem repeat (aSTR) and identity informative single nucleotide polymorphism (iiSNP) data from a total of 233 unrelated individuals are provided, and forensic genetic parameters are calculated for each population and for the combined set Northeastern Peruvian Andes. After correction for multiple testing in the whole dataset of the Northeastern Peruvian Andes, the only departure from Hardy-Weinberg equilibrium was observed in locus rs2111980. Twenty one out of 27 aSTR loci exhibited an increased number of alleles due to sequence variation in the repeat motif and flanking regions. For iiSNPs 33% of the loci displayed flanking region variation. The combined random match probability (RMP), assuming independence of all loci (aSTRs and iiSNPs), in the Chachapoyas, the population with the largest samples size (N = 172), was 8.14 × 10-62 for length-based data while for sequence-based was 4.15 × 10-67. In the merged dataset (Northeastern Peruvian Andes; N = 233), the combined RMP when including all markers were 2.96 × 10-61 (length-based) and 3.21 × 10-66 (sequence-based). These new data help to fill up some of the gaps in the genetic canvas of South America and provide essential length- and sequence-based background information for other forensic genetic studies in Peru.

Graph Algorithms for Mixture Interpretation.

The scale of genetic methods are presently being expanded: forensic genetic assays previously were limited to tens of loci, but now technologies allow for a transition to forensic genomic approaches that assess thousands to millions of loci. However, there are subtle distinctions between genetic assays and their genomic counterparts (especially in the context of forensics). For instance, forensic genetic approaches tend to describe a locus as a haplotype, be it a microhaplotype or a short tandem repeat with its accompanying flanking information. In contrast, genomic assays tend to provide not haplotypes but sequence variants or differences, variants which in turn describe how the alleles apparently differ from the reference sequence. By the given construction, mitochondrial genetic assays can be thought of as genomic as they often describe genetic differences in a similar way. The mitochondrial genetics literature makes clear that sequence differences, unlike the haplotypes they encode, are not comparable to each other. Different alignment algorithms and different variant calling conventions may cause the same haplotype to be encoded in multiple ways. This ambiguity can affect evidence and reference profile comparisons as well as how "match" statistics are computed. In this study, a graph algorithm is described (and implemented in the MMDIT (Mitochondrial Mixture Database and Interpretation Tool) R package) that permits the assessment of forensic match statistics on mitochondrial DNA mixtures in a way that is invariant to both the variant calling conventions followed and the alignment parameters considered. The algorithm described, given a few modest constraints, can be used to compute the "random man not excluded" statistic or the likelihood ratio. The performance of the approach is assessed in in silico mitochondrial DNA mixtures.

A Continuous Statistical Phasing Framework for the Analysis of Forensic Mitochondrial DNA Mixtures.

Despite the benefits of quantitative data generated by massively parallel sequencing, resolving mitotypes from mixtures occurring in certain ratios remains challenging. In this study, a bioinformatic mixture deconvolution method centered on population-based phasing was developed and validated. The method was first tested on 270 in silico two-person mixtures varying in mixture proportions. An assortment of external reference panels containing information on haplotypic variation (from similar and different haplogroups) was leveraged to assess the effect of panel composition on phasing accuracy. Building on these simulations, mitochondrial genomes from the Human Mitochondrial DataBase were sourced to populate the panels and key parameter values were identified by deconvolving an additional 7290 in silico two-person mixtures. Finally, employing an optimized reference panel and phasing parameters, the approach was validated with in vitro two-person mixtures with differing proportions. Deconvolution was most accurate when the haplotypes in the mixture were similar to haplotypes present in the reference panel and when the mixture ratios were neither highly imbalanced nor subequal (e.g., 4:1). Overall, errors in haplotype estimation were largely bounded by the accuracy of the mixture's genotype results. The proposed framework is the first available approach that automates the reconstruction of complete individual mitotypes from mixtures, even in ratios that have traditionally been considered problematic.

STRait Razor Online: An enhanced user interface to facilitate interpretation of MPS data.

Since 2013, STRait Razor has enabled analysis of massively parallel sequencing (MPS) data from various marker systems such as short tandem repeats, single nucleotide polymorphisms, insertion/deletions, and mitochondrial DNA. In this paper, STRait Razor Online (SRO), available at https://www.unthsc.edu/straitrazor, is introduced as an interactive, Shiny-based user interface for primary analysis of MPS data and secondary analysis of STRait Razor haplotype pileups. This software can be accessed from any common browser via desktop, tablet, or smartphone device. SRO is available also as a standalone application and open-source R script available at https://github.com/ExpectationsManaged/STRaitRazorOnline. The local application is capable of batch processing of both fastq files and primary analysis output. Processed batches generate individual report folders and summary reports at the locus- and haplotype-level in a matter of minutes. For example, the processing of data from ∼700 samples generated with the ForenSeq Signature Preparation Kit from allsequences.txt to a final table can be performed in ∼40 min whereas the Excel-based workbooks can take 35-60 h to compile a subset of the tables generated by SRO. To facilitate analysis of single-source, reference samples, a preliminary triaging system was implemented that calls potential alleles and flags loci suspected of severe heterozygote imbalance. When compared to published, manually curated data sets, 98.72 % of software-assigned allele calls without manual interpretation were consistent with curated data sets, 0.99 % loci were presented to the user for interpretation due to heterozygote imbalance, and the remaining 0.29 % of loci were inconsistent due to the analytical thresholds used across the studies.

Reducing noise and stutter in short tandem repeat loci with unique molecular identifiers.

Unique molecular identifiers (UMIs) are a promising approach to contend with errors generated during PCR and massively parallel sequencing (MPS). With UMI technology, random molecular barcodes are ligated to template DNA molecules prior to PCR, allowing PCR and sequencing error to be tracked and corrected bioinformatically. UMIs have the potential to be particularly informative for the interpretation of short tandem repeats (STRs). Traditional MPS approaches may simply lead to the observation of alleles that are consistent with the hypotheses of stutter, while with UMIs stutter products bioinformatically may be re-associated with their parental alleles and subsequently removed. Herein, a bioinformatics pipeline named strumi is described that is designed for the analysis of STRs that are tagged with UMIs. Unlike other tools, strumi is an alignment-free machine learning driven algorithm that clusters individual MPS reads into UMI families, infers consensus super-reads that represent each family and provides an estimate the resulting haplotype's accuracy. Super-reads, in turn, approximate independent measurements not of the PCR products, but of the original template molecules, both in terms of quantity and sequence identity. Provisional assessments show that naïve threshold-based approaches generate super-reads that are accurate (∼97 % haplotype accuracy, compared to ∼78 % when UMIs are not used), and the application of a more nuanced machine learning approach increases the accuracy to ∼99.5 % depending on the level of certainty desired. With these features, UMIs may greatly simplify probabilistic genotyping systems and reduce uncertainty. However, the ability to interpret alleles at trace levels also permits the interpretation, characterization and quantification of contamination as well as somatic variation (including somatic stutter), which may present newfound challenges.

Genetic assessment reveals no population substructure and divergent regional and sex-specific histories in the Chachapoyas from northeast Peru.

Many native populations in South America have been severely impacted by two relatively recent historical events, the Inca and the Spanish conquest. However decisive these disruptive events may have been, the populations and their gene pools have been shaped markedly also by the history prior to the conquests. This study focuses mainly on the Chachapoya peoples that inhabit the montane forests on the eastern slopes of the northern Peruvian Andes, but also includes three distinct neighboring populations (the Jívaro, the Huancas and the Cajamarca). By assessing mitochondrial, Y-chromosomal and autosomal diversity in the region, we explore questions that have emerged from archaeological and historical studies of the regional culture (s). These studies have shown, among others, that Chachapoyas was a crossroads for Coast-Andes-Amazon interactions since very early times. In this study, we examine the following questions: 1) was there pre-Hispanic genetic population substructure in the Chachapoyas sample? 2) did the Spanish conquest cause a more severe population decline on Chachapoyan males than on females? 3) can we detect different patterns of European gene flow in the Chachapoyas region? and, 4) did the demographic history in the Chachapoyas resemble the one from the Andean area? Despite cultural differences within the Chachapoyas region as shown by archaeological and ethnohistorical research, genetic markers show no significant evidence for past or current population substructure, although an Amazonian gene flow dynamic in the northern part of this territory is suggested. The data also indicates a bottleneck c. 25 generations ago that was more severe among males than females, as well as divergent population histories for populations in the Andean and Amazonian regions. In line with previous studies, we observe high genetic diversity in the Chachapoyas, despite the documented dramatic population declines. The diverse topography and great biodiversity of the northeastern Peruvian montane forests are potential contributing agents in shaping and maintaining the high genetic diversity in the Chachapoyas region.

Copan microFLOQ® Direct Swab collection of bloodstains, saliva, and semen on cotton cloth.

The microFLOQ® Direct Swab was tested by sampling diluted blood, semen, and saliva stains deposited on cotton cloth. DNA typing was performed using the PowerPlex® Fusion 6C System by direct PCR or a modified direct PCR. Direct PCR of swabs sampled the center of a stain, compared to their respective edge samplings, and had higher profile completeness and total relative fluorescent units (RFU) for all dilutions of blood and semen stains tested. The modified direct PCR used template DNA eluted from the swab head using the Casework Direct Kit, Custom and washes either contained 1-thioglycerol (TG) additive or no TG. Modified direct PCR had mixed results for blood, saliva, and semen stains, with semen stains showing significant differences in profile completeness (5% and 1%) and total RFU (neat, 5% and 1%) with the addition of TG to the Casework Direct Reagent. No significant difference was seen in any dilution of blood or saliva stains processed with the modified direct PCR, but profile completeness and total RFU were improved overall compared to stains swabbed with cotton swabs or 4N6FLOQSwabs™. This study supports the hypothesis that the microFLOQ® Direct Swab is able to collect minute amounts of DNA from cotton cloth and may be considered as an alternate pre-screening methodology in forensic biology casework.

A genome-wide association study of tramadol metabolism from post-mortem samples.

Phase I tramadol metabolism requires cytochrome p450 family 2, subfamily D, polypeptide 6 (CYP2D6) to form O-desmethyltramadol (M1). CYP2D6 genetic variants may infer metabolizer phenotype; however, drug ADME (absorption, distribution, metabolism, and excretion) and response depend on protein pathway(s), not CYP2D6 alone. There is a paucity of data regarding the contribution of trans-acting proteins to idiosyncratic phenotypes following drug exposure. A genome-wide association study identified five markers (rs79983226/kgp11274252, rs9384825, rs62435418/kgp10370907, rs72732317/kgp3743668, and rs184199168/exm1592932) associated with the conversion of tramadol to M1 (M1:T). These SNPs reside within five genes previously implicated with adverse reactions. Analysis of accompanying toxicological meta-data revealed a significant positive linear relationship between M1:T and degree of sample polypharmacy. Taken together, these data identify candidate loci for potential clinical inferences of phenotype following exposure to tramadol and highlight sample polypharmacy as a possible diagnostic covariate in post-mortem genetic studies.

Forensic genetic investigation of human skeletal remains recovered from the La Belle shipwreck.

In 1995, the historical shipwreck of La Belle was discovered off the coast of Texas. One partial human skeleton was recovered from alongside cargo in the rear portion of the ship; a second (complete) skeleton was found atop coiled anchor rope in the bow. In late 2015, comprehensive forensic genetic testing began on multiple samplings from each set of remains. For the partial skeleton recovered from the ship's rear cargo area, results were obtained for 26/27 Y-STRs using traditional CE; with MPS technology, results were obtained for 18/24 Y-STRs, 56/56 ancestry-informative SNPs (aiSNPs), 22/22 phenotype-informative SNPs (piSNPs), 22/27 autosomal STRs, 4/7 X-STRs, and 94/94 identity-informative SNPs (iiSNPs). For the complete skeleton of the second individual, results were obtained for 7/17 Y-STRs using traditional CE; with MPS technology, results were obtained for 5/24 Y-STRs, 49/56 aiSNPs, 18/22 piSNPs, 15/27 autosomal STRs, 1/7 X-STRs, and 66/94 iiSNPs. Biogeographic ancestry for each set of skeletal remains was predicted using the ancestry feature and metapopulation tool of the Y-STR Haplotype Reference Database (YHRD), Haplogroup Predictor, and the Forensic Research/Reference on Genetics knowledge base (FROG-kb). Phenotype prediction was performed using piSNP data and the HIrisplex eye color and hair color DNA phenotyping webtool. mtDNA whole genome sequencing also was performed successfully. This study highlights the sensitivity of current forensic laboratory methods in recovering DNA from historical and archaeological human remains. Using advanced sequencing technology provided by MiSeq™ FGx (Verogen) and Ion S5™ (Thermo Fisher Scientific) instrumentation, degraded skeletal remains can be characterized using a panel of diverse and highly informative markers, producing data which can be useful in both forensic and genealogical investigations.