Allele frequencies and minor contributor match statistic convergence using simulated population replicates.

Probabilistic genotyping permits a comparison of forensic evidence given hypotheses regarding the origin of observed short tandem repeat alleles in a mixed DNA profile. Using the publicly available R package forensim, it has been proposed that mixtures with non-contributors from low genetic diversity populations are more likely to be mistakenly identified as contributors to a mixture than non-contributors from high genetic diversity populations. We hypothesized that these observations are attributed to the unique distribution of alleles in the reference population and may not generalize to other samplings of the same population. We used forensim to simulate 200 US populations (50 each of self-reported African-American, Asian-American, European-American, and Hispanic descent). We compared likelihood ratios for 2400 mixtures to those derived from published data and identified stark differences. A minimum of ten population replicates were required to reduce observed differences relative to published data. Deviations from Hardy-Weinberg equilibrium and allele frequency distributions suggest that simulated populations should be sufficiently evaluated for expectations of population genetic parameters prior to use in DNA mixture modeling experiments. Overall, our findings support the utility of forensim and further describe its suitability to model population genetic parameters but suggest that a single population replicate (directly ascertained or simulated) may be insufficient to make conclusions about a given DNA mixture.

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.

Supervised Classification of CYP2D6 Genotype and Metabolizer Phenotype With Postmortem Tramadol-Exposed Finns.

Cytochrome p450 family 2, subfamily D, polypeptide 6 (CYP2D6) may be used to infer the metabolizer phenotype (MP) of an individual as poor, intermediate, extensive/normal, or ultrarapid. Metabolizer phenotypes may suggest idiosyncratic drug responses as contributing factors to cause and/or manner of death in postmortem investigations. Application of CYP2D6 has used long-range amplification of the locus and restriction enzyme digestion to detect single-nucleotide variants (SNVs) associated with MPs. This process can be cumbersome and requires knowledge of genotype phase. Phase may be achieved using long-read DNA sequencing and/or computational methods; however, both can be error prone, which may make it difficult or impractical for implementation into medicolegal practice. CYP2D6 was interrogated in postmortem autopsied Finns using supervised machine learning and feature selection to identify SNVs indicative of MP and/or rate of tramadol O-demethylation (T:M1). A subset of 18 CYP2D6 SNVs could predict MP/T:M1 with up to 96.3% accuracy given phased data. These data indicate that phase contributes to classification accuracy when using CYP2D6 data. Of these 18 SNVs, 3 are novel loci putatively associated with T:M1. These findings may enable design of small multiplexes for easy forensic application of MP prediction when cause and/or manner of death is unknown.

Assessing DNA recovery and profile determination from bloody snow.

Successful DNA typing of forensically relevant evidence is reliant on both the quality and quantity of biological material recovered from a crime scene. In geographical areas of the world exposed to cold climates, it is not uncommon for biological evidence to encounter a diversity of challenging surfaces and environments, including snowy surfaces. Currently, there is no standard protocol for recovery of bloodstain evidence in snow and very few publications exploring adequate methods of recovering biological evidence from snowy surfaces. In this study, three common substrates (e.g., cotton swabs, FTA paper, and untreated filter paper) utilized by investigators for evidence recovery were evaluated for their ability to recover human blood (DNA) evidence from snow that would be viable for traditional forensic DNA typing. Each biological sample was extracted and quantified to evaluate the quality and quantity of DNA recovered. All samples yielded sufficient non-degraded DNA to proceed with DNA profiling, where complete DNA profiles were generated from each collection substrate. The experimental findings presented herein demonstrate that the ability to recover viable DNA from human blood collected on surface snow is possible using all three collection methods tested.

A pathway-driven predictive model of tramadol pharmacogenetics.

Predicting metabolizer phenotype (MP) is typically performed using data from a single gene. Cytochrome p450 family 2 subfamily D polypeptide 6 (CYP2D6) is considered the primary gene for predicting MP in reference to approximately 30% of marketed drugs and endogenous toxins. CYP2D6 predictions have proven clinically effective but also have well-documented inaccuracies due to relatively high genotype-phenotype discordance in certain populations. Herein, a pathway-driven predictive model employs genetic data from uridine diphosphate glucuronosyltransferase, family 1, polypeptide B7 (UGT2B7), adenosine triphosphate (ATP)-binding cassette, subfamily B, number 1 (ABCB1), opioid receptor mu 1 (OPRM1), and catechol-O-methyltransferase (COMT) to predict the tramadol to primary metabolite ratio (T:M1) and the resulting toxicologically inferred MP (t-MP). These data were then combined with CYP2D6 data to evaluate performance of a fully combinatorial model relative to CYP2D6 alone. These data identify UGT2B7 as a potentially significant explanatory marker for T:M1 variability in a population of tramadol-exposed individuals of Finnish ancestry. Supervised machine learning and feature selection were used to demonstrate that a set of 16 loci from 5 genes can predict t-MP with over 90% accuracy, depending on t-MP category and algorithm, which was significantly greater than predictions made by CYP2D6 alone.

Expanding beyond the current core STR loci: An exploration of 73 STR markers with increased diversity for enhanced DNA mixture deconvolution.

Current approaches to mixture deconvolution of complex biological samples at times do not have the capability to resolve component contributors in DNA evidence. Additional short tandem repeat (STR) loci were sought that may improve the forensic genetic analysis of mixtures. This study presents exploratory data of a multiplex comprised of 73 highly polymorphic STRs (referred herein as the 73Plex) that were selected because of their high diversity due to sequence variation. These STRs (or a subset of them) may be considered as candidates that may augment current core markers capabilities for DNA mixture deconvolution. Population genetics analyses were performed for each locus using DNA samples from 451 individuals comprising three U.S. populations. Sequence-based heterozygosities ranged from 72% to 98%, where only two loci (D10A97 and D6A7) fell below 80%. Mixture deconvolution capabilities for two-person mixtures were assessed based on complete allele resolution per locus (i.e., four alleles observed) of pairwise mixtures using in silico methods. A subset of 20 highly informative loci (referred herein as the 20Plex) from the 73Plex was compared to the 20 CODIS core loci on all population samples with full DNA profiles for both panels (i.e., no locus dropout; n = 443). Based on proportion of loci displaying four alleles, the 20Plex outperformed the CODIS core loci with increases of 82.6% and 89.3% using length-based and sequence-based alleles, respectively. A combination of 17 STR from the 20Plex and 3 CODIS loci gave the highest capacity for resolving allelic components per locus. These data illustrate the increased value of utilizing sequenced-based alleles of additional STR loci. Furthermore, there are a number of candidate STR loci that could notably augment the current core STR loci and enhance mixture interpretation capabilities.

Forensic human identification with targeted microbiome markers using nearest neighbor classification.

From the perspective of forensics genetics, the human microbiome is a rich, relatively untapped resource for human identity testing. Since it varies within and among people, and perhaps temporally, the potential forensic applications of the use of the microbiome can exceed that of human identification. However, the same inherent variability in microbial distributions may pose a substantial barrier to forming predictions on an individual as the source of the microbial sample unless stable signatures of the microbiome are identified and targeted. One of the more commonly adopted strategies for microbial human identification relies on quantifying which taxa are present and their respective abundance levels. It remains an open question if such microbial signatures are more individualizing than estimates of the degree of genetic relatedness between microbial samples. This study attempts to address this question by contrasting two prediction strategies. The first approach uses phylogenetic distance to predict the host individual; thus it operates under the premise that microbes within individuals are more closely related than microbes between/among individuals. The second approach uses population genetic measures of diversity at clade-specific markers, serving as a fine-grained assessment of microbial composition and quantification. Both assessments were performed using targeted sequencing of 286 markers from 22 microbial taxa sampled in 51 individuals across three body sites measured in triplicate. Nearest neighbor and reverse nearest neighbor classifiers were constructed based on the pooled data and yielded 71% and 78% accuracy, respectively, when diversity was considered, and performed significantly worse when a phylogenetic distance was used (54% and 63% accuracy, respectively). However, empirical estimates of classification accuracy were 100% when conditioned on a maximum nearest neighbor distance when diversity was used, while identification based on a phylogenetic distance failed to reach saturation. These findings suggest that microbial strain composition is more individualizing than that of a phylogeny, perhaps indicating that microbial composition may be more individualizing than recent common ancestry. One inference that may be drawn from these findings is that host-environment interactions may maintain the targeted microbial profile and that this maintenance may not necessarily be repopulated by intra-individual microbial strains.

Potential highly polymorphic short tandem repeat markers for enhanced forensic identity testing.

Due to their polymorphic nature, short tandem repeats (STRs) are well-studied and routinely used genetic markers for forensic DNA typing. However, even the largest STR multiplexes are limited in their ability to parse out individuals in a DNA mixture sample, due to alleles shared by size detected by capillary electrophoresis and challenges in resolving minor alleles from stutter, and inherent heterozygote imbalance. In this study, STRs were explored in public datasets that displayed sequence variation and may have limited allele length spread. STRs were first selected using fundamental criteria of high heterozygosity, tetra-, penta-, or hexanucleotide repeat length, and overall relative narrow allele spread (based on length). All candidates were further scrutinized for chemistry compatibility. The resulting STRs were multiplexed and sequenced by massively parallel sequencing in a limited sample population set. Each candidate STR was evaluated for analytical performance and desired biological properties. The findings presented describe a refined set of 53 potential highly polymorphic STR markers (high sequence diversity and heterozygosity; reduced allele spread) that may be suitable to supplement the current core marker set(s) for possible enhanced characterization of complex DNA profiles.

Increasing the discrimination power of ancestry- and identity-informative SNP loci within the ForenSeq™ DNA Signature Prep Kit.

The use of single nucleotide polymorphisms (SNPs) in forensic genetics has been limited to challenged samples with low template and/or degraded DNA. The recent introduction of massively parallel sequencing (MPS) technologies has expanded the potential applications of these markers and increased the discrimination power of well-established loci by considering variation in the flanking regions of target loci. The ForenSeq Signature Preparation Kit contains 165 SNP amplicons for ancestry- (aiSNPs), identity- (iiSNPs), and phenotype-inference (piSNPs). In this study, 714 individuals from four major populations (African American, AFA; East Asian, ASN; US Caucasian, CAU; and Southwest US Hispanic, HIS) previously reported by Churchill et al. [Forensic Sci Int Genet. 30 (2017) 81-92; DOI: https://doi.org/10.1016/j.fsigen.2017.06.004] were assessed using STRait Razor v2s to determine the level of diversity in the flanking regions of these amplicons. The results show that nearly 70% of loci showed some level of flanking region variation with 22 iiSNPs and 8 aiSNPs categorized as microhaplotypes in this study. The heterozygosities of these microhaplotypes approached, and in one instance surpassed, those of some core STR loci. Also, the impact of the flanking region on other forensic parameters (e.g., power of exclusion and power of discrimination) was examined. Sixteen of the 94 iiSNPs had an effective allele number greater than 2.00 across the four populations. To assess what effect the flanking region information had on the ancestry inference, genotype probabilities and likelihood ratios were determined. Additionally, concordance with the ForenSeq UAS and Nextera Rapid Capture was evaluated, and patterns of heterozygote imbalance were identified. Pairwise comparison of the iiSNP diplotypes determined the probability of detecting a mixture (i.e., observing ≥ 3 haplotypes) using these loci alone was 0.9952. The improvement in random match probabilities for the full regions over the target iiSNPs was found to be significant. When combining the iiSNPs with the autosomal STRs, the combined match probabilities ranged from 6.40 × 10-73 (ASN) to 1.02 × 10-79 (AFA).

Targeted sequencing of clade-specific markers from skin microbiomes for forensic human identification.

The human skin microbiome is comprised of diverse communities of bacterial, eukaryotic, and viral taxa and contributes millions of additional genes to the repertoire of human genes, affecting human metabolism and immune response. Numerous genetic and environmental factors influence the microbiome composition and as such contribute to individual-specific microbial signatures which may be exploited for forensic applications. Previous studies have demonstrated the potential to associate skin microbial profiles collected from touched items to their individual owner, mainly using unsupervised methods from samples collected over short time intervals. Those studies utilize either targeted 16S rRNA or shotgun metagenomic sequencing to characterize skin microbiomes; however, these approaches have limited species and strain resolution and susceptibility to stochastic effects, respectively. Clade-specific markers from the skin microbiome, using supervised learning, can predict individual identity using skin microbiomes from their respective donors with high accuracy. In this study the hidSkinPlex is presented, a novel targeted sequencing method using skin microbiome markers developed for human identification. The hidSkinPlex (comprised of 286 bacterial (and phage) family-, genus-, species-, and subspecies-level markers), initially was evaluated on three bacterial control samples represented in the panel (i.e., Propionibacterium acnes, Propionibacterium granulosum, and Rothia dentocariosa) to assess the performance of the multiplex. The hidSkinPlex was further evaluated for prediction purposes. The hidSkinPlex markers were used to attribute skin microbiomes collected from eight individuals from three body sites (i.e., foot (Fb), hand (Hp) and manubrium (Mb)) to their host donor. Supervised learning, specifically regularized multinomial logistic regression and 1-nearest-neighbor classification were used to classify skin microbiomes to their hosts with up to 92% (Fb), 96% (Mb), and 100% (Hp) accuracy. All samples (n=72) regardless of body site origin were correctly classified with up to 94% accuracy, and body site origin could be predicted with up to 86% accuracy. Finally, human short tandem repeat and single-nucleotide polymorphism profiles were generated from skin swab extracts from a single subject to highlight the potential to use microbiome profiling in conjunction with low-biomass samples. The hidSkinPlex is a novel targeted enrichment approach to profile skin microbiomes for human forensic identification purposes and provides a method to further characterize the utility of skin microflora for human identification in future studies, such as the stability and diversity of the personal skin microbiome.

Population and performance analyses of four major populations with Illumina's FGx Forensic Genomics System.

The MiSeq FGx Forensic Genomics System (Illumina) enables amplification and massively parallel sequencing of 59 STRs, 94 identity informative SNPs, 54 ancestry informative SNPs, and 24 phenotypic informative SNPs. Allele frequency and population statistics data were generated for the 172 SNP loci included in this panel on four major population groups (Chinese, African Americans, US Caucasians, and Southwest Hispanics). Single-locus and combined random match probability values were generated for the identity informative SNPs. The average combined STR and identity informative SNP random match probabilities (assuming independence) across all four populations were 1.75E-67 and 2.30E-71 with length-based and sequence-based STR alleles, respectively. Ancestry and phenotype predictions were obtained using the ForenSeq™ Universal Analysis System (UAS; Illumina) based on the ancestry informative and phenotype informative SNP profiles generated for each sample. Additionally, performance metrics, including profile completeness, read depth, relative locus performance, and allele coverage ratios, were evaluated and detailed for the 725 samples included in this study. While some genetic markers included in this panel performed notably better than others, performance across populations was generally consistent. The performance and population data included in this study support that accurate and reliable profiles were generated and provide valuable background information for laboratories considering internal validation studies and implementation.

Flanking region variation of ForenSeq™ DNA Signature Prep Kit STR and SNP loci in Yavapai Native Americans.

Massively parallel sequencing (MPS) offers advantages over current capillary electrophoresis-based analysis of short tandem repeat (STR) loci for human identification testing. In particular STR repeat motif sequence information can be obtained, thereby increasing the discrimination power of some loci. While sequence variation within the repeat region is observed relatively frequently in some of the commonly used STRs, there is an additional degree of variation found in the flanking regions adjacent to the repeat motif. Repeat motif and flanking region sequence variation have been described for major population groups, however, not for more isolated populations. Flanking region sequence variation in STR and single nucleotide polymorphism (SNP) loci in the Yavapai population was analyzed using the ForenSeq™ DNA Signature Prep Kit and STRait Razor v2s. Seven and 14 autosomal STRs and identity-informative single nucleotide polymorphisms (iiSNPs), respectively, had some degree of flanking region variation. Three and four of these identity-informative loci, respectively, showed ≥5% increase in expected heterozygosity. The combined length- and sequence-based random match probabilities (RMPs) for 27 autosomal STRs were 6.11×10-26 and 2.79×10-29, respectively. When combined with 94 iiSNPs (a subset of which became microhaplotypes) the combined RMP was 5.49×10-63. Analysis of length-based and sequence-based autosomal STRs in STRUCTURE indicated that the Yavapai are most similar to the Hispanic population. While producing minimal increase in X- and Y-STR discrimination potential, access to flanking region data enabled identification of one novel X-STR and three Y-STR alleles relative to previous reports. Five ancestry-informative SNPs (aiSNPs) and two phenotype-informative SNPs (piSNPs) exhibited notable flanking region variation.

Characterization of genetic sequence variation of 58 STR loci in four major population groups.

Massively parallel sequencing (MPS) can identify sequence variation within short tandem repeat (STR) alleles as well as their nominal allele lengths that traditionally have been obtained by capillary electrophoresis. Using the MiSeq FGx Forensic Genomics System (Illumina), STRait Razor, and in-house excel workbooks, genetic variation was characterized within STR repeat and flanking regions of 27 autosomal, 7 X-chromosome and 24 Y-chromosome STR markers in 777 unrelated individuals from four population groups. Seven hundred and forty six autosomal, 227 X-chromosome, and 324 Y-chromosome STR alleles were identified by sequence compared with 357 autosomal, 107 X-chromosome, and 189 Y-chromosome STR alleles that were identified by length. Within the observed sequence variation, 227 autosomal, 156 X-chromosome, and 112 Y-chromosome novel alleles were identified and described. One hundred and seventy six autosomal, 123 X-chromosome, and 93 Y-chromosome sequence variants resided within STR repeat regions, and 86 autosomal, 39 X-chromosome, and 20 Y-chromosome variants were located in STR flanking regions. Three markers, D18S51, DXS10135, and DYS385a-b had 1, 4, and 1 alleles, respectively, which contained both a novel repeat region variant and a flanking sequence variant in the same nucleotide sequence. There were 50 markers that demonstrated a relative increase in diversity with the variant sequence alleles compared with those of traditional nominal length alleles. These population data illustrate the genetic variation that exists in the commonly used STR markers in the selected population samples and provide allele frequencies for statistical calculations related to STR profiling with MPS data.

Massively parallel sequencing of 68 insertion/deletion markers identifies novel microhaplotypes for utility in human identity testing.

Short tandem repeat (STR) loci are the traditional markers used for kinship, missing persons, and direct comparison human identity testing. These markers hold considerable value due to their highly polymorphic nature, amplicon size, and ability to be multiplexed. However, many STRs are still too large for use in analysis of highly degraded DNA. Small bi-allelic polymorphisms, such as insertions/deletions (INDELs), may be better suited for analyzing compromised samples, and their allele size differences are amenable to analysis by capillary electrophoresis. The INDEL marker allelic states range in size from 2 to 6 base pairs, enabling small amplicon size. In addition, heterozygote balance may be increased by minimizing preferential amplification of the smaller allele, as is more common with STR markers. Multiplexing a large number of INDELs allows for generating panels with high discrimination power. The Nextera™ Rapid Capture Custom Enrichment Kit (Illumina, Inc., San Diego, CA) and massively parallel sequencing (MPS) on the Illumina MiSeq were used to sequence 68 well-characterized INDELs in four major US population groups. In addition, the STR Allele Identification Tool: Razor (STRait Razor) was used in a novel way to analyze INDEL sequences and detect adjacent single nucleotide polymorphisms (SNPs) and other polymorphisms. This application enabled the discovery of unique allelic variants, which increased the discrimination power and decreased the single-locus random match probabilities (RMPs) of 22 of these well-characterized INDELs which can be considered as microhaplotypes. These findings suggest that additional microhaplotypes containing human identification (HID) INDELs may exist elsewhere in the genome.

Genetic analysis of the Yavapai Native Americans from West-Central Arizona using the Illumina MiSeq FGx™ forensic genomics system.

Forensically-relevant genetic markers were typed for sixty-two Yavapai Native Americans using the ForenSeq™ DNA Signature Prep Kit.These data are invaluable to the human identity community due to the greater genetic differentiation among Native American tribes than among other subdivisions within major populations of the United States. Autosomal, X-chromosomal, and Y-chromosomal short tandem repeat (STR) and identity-informative (iSNPs), ancestry-informative (aSNPs), and phenotype-informative (pSNPs) single nucleotide polymorphism (SNP) allele frequencies are reported. Sequence-based allelic variants were observed in 13 autosomal, 3 X, and 3 Y STRs. These observations increased observed and expected heterozygosities for autosomal STRs by 0.081±0.068 and 0.073±0.063, respectively, and decreased single-locus random match probabilities by 0.051±0.043 for 13 autosomal STRs. The autosomal random match probabilities (RMPs) were 2.37×10-26 and 2.81×10-29 for length-based and sequence-based alleles, respectively. There were 22 and 25 unique Y-STR haplotypes among 26 males, generating haplotype diversities of 0.95 and 0.96, for length-based and sequencebased alleles, respectively. Of the 26 haplotypes generated, 17 were assigned to haplogroup Q, three to haplogroup R1b, two each to haplogroups E1b1b and L, and one each to haplogroups R1a and I1. Male and female sequence-based X-STR random match probabilities were 3.28×10-7 and 1.22×10-6, respectively. The average observed and expected heterozygosities for 94 iSNPs were 0.39±0.12 and 0.39±0.13, respectively, and the combined iSNP RMP was 1.08×10-32. The combined STR and iSNP RMPs were 2.55×10-58 and 3.02×10-61 for length-based and sequence-based STR alleles, respectively. Ancestry and phenotypic SNP information, performed using the ForenSeq™ Universal Analysis Software, predicted black hair, brown eyes, and some probability of East Asian ancestry for all but one sample that clustered between European and Admixed American ancestry on a principal components analysis. These data serve as the first population assessment using the ForenSeq™ panel and highlight the value of employing sequence-based alleles for forensic DNA typing to increase heterozygosity, which is beneficial for identity testing in populations with reduced genetic diversity.