Pairwise kinship analysis of 17 pedigrees using massively parallel sequencing

With the tremendous development of massively parallel sequencing (MPS) in the last decade, it has been widely applied in basic science, clinical diagnostics, microbial genomics, as well as forensic genetics. MPS has lots of advantages that may facilitate the kinship analysis. In this study, 243 Chinese Han individuals from 17 families were involved and sequenced using the ForenSeq™ DNA Signature Prep Kit (Verogen, Inc., San Diego, USA), which provided the sequence information of 27 autosomal STRs (A-STRs), 7 X chromosomal STRs (X-STRs), 24 Y chromosomal STRs (Y-STRs) and 94 identity-informative SNPs (iSNPs). A total of 275 pairs of parent-child, 123 pairs of full siblings, 1 pair of twins, 1 pair of half siblings, 158 pairs of grandparent-grandchild, 222 pairs of uncle/aunt-nephew/niece and 121 pairs of first cousins, as well as 701 pairs of unrelated individuals were identified. Using both likelihood ratio (LR) and identical by state (IBS) methods, the kinship analysis was conducted among these relative and non-relative pairs based on the A-STRs and SNPs. As a result, the ForenSeq Signature Kit could solve the analysis of parent-child (t1 = −4, t2 = 4), full siblings (t1 = −2, t2 = 2) and most second-degree kinships (t1 = −1, t2 = 1) using the LR method. When the IBS method was applied, 123 full sibling pairs had a higher average IBS value than other kinship groups in this study. And the IBS method could play a role in the testing of parent-child and full siblings.     

Improved pairwise kinship analysis using massively parallel sequencing

In the present study, 67 individuals from two families were analyzed to explore the efficacy of the ForenSeq^™ DNA Signature Prep Kit for pairwise kinship analysis. Six types of pairwise relationships including 81 parent-offspring, 60 full siblings, 48 grandparent-grandchildren, 147 uncle/aunt-nephew/nieces, 97 first cousins and 190 non-relatives were generated from these two families and the corresponding likelihood ratio (LR) was calculated using either sequence-based or length-based STR genotype data (i.e., LR_sequence and LR_length). In addition, 10,000 pairs of different relationships were simulated to estimate the system powers of the STRs and SNPs in this panel. The results showed that 54, 9 and 5 additional alleles were observed based on sequence for 27 autosomal STRs, 24 Y-STRs and 7 X-STRs, respectively, compared to those based on length information and 11 novel alleles were identified. Five mutations were found for 58 STRs in 81 parent-offspring but no mutations were observed for SNPs. For 27 autosomal STR loci, the LRs were increased from 9.20, 7.87, 2.01, 2.07, 0.42 for log₁₀LR_length to 11.52, 10.12, 2.61, 2.60, 0.52 for log₁₀LR_sequence for paternity index (PI), full siblings index (FSI), grandparent-grandchild index (GI), uncle/aunt-nephew/niece index (UNI) and first cousins index (FCI), respectively. PI values for 94 SNPs separated more than those of 27 STRs if two individuals were non parent-offspring relatives. For the simulation study, the effectiveness was 1 for the parent-offspring relationship at the thresholds of t₁ = − 4 and t₂ = 4 and was 0.9998 for full siblings (t₁ = − 2, t₂ = 2). With an error rate of 0.42%, 93.02% of second degree relatives could be identified at the thresholds of t₁ = − 1 and t₂ = 1. However, the effectiveness was only 0.4300 for first cousins with a relatively high error rate of 2.68% (t₁ = − 1, t₂ = 1). In conclusion, STR typing according to the sequence information is more polymorphic, which increases the discrimination power for kinship testing. Compared to these 27 STR markers, 94 SNP markers in this panel have advantages in paternity testing especially when mutated STRs are involved or when a relative is an alleged parent. This panel is powerful enough to resolve paternity and full sibling testing. Most of the second degree relationships could be identified with low error rate while more markers are still needed for first cousins testing.     

Techniques for estimating genetically variable peptides and semi-continuous likelihoods from massively parallel sequencing data

Forensic genetic investigations typically rely on analysis of DNA for attribution purposes. There are times, however, when the amount and/or the quality of the DNA is limited, and thus little or no information can be obtained regarding the source of the sample. An alternative biochemical target that also contains genetic signatures is protein. One class of genetic signatures is protein polymorphisms that are a direct consequence of simple/single/short nucleotide polymorphisms (SNPs) in DNA. However, to interpret protein polymorphisms in a forensic context, certain complexities must be understood and addressed. These complexities include: 1) SNPs can generate 0, 1, or arbitrarily many polymorphisms in a polypeptide; and 2) as an object of expression that is modulated by alleles, genes and interactions with the environment, proteins may be present or absent in a given sample. To address these issues, a novel approach was taken to generate the expected protein alleles in a reference sample based on whole genome (or exome) sequence data and assess the significance of the evidence using a haplotype-based semi-continuous likelihood algorithm that leverages whole proteome data. Converting the genomic information into the proteomic information allows for the zero-to-many relationship between SNPs and GVPs to be abstracted away. When viewed as a haplotype, many GVPs that correspond to the same SNP is equivalent to many SNPs in perfect linkage disequilibrium (LD). As long as the likelihood formulation correctly accounts for LD, the correspondence between the SNP and the proteome can be safely neglected. Tests were performed on simulated samples, including single-source and two-person mixtures, and the power of using a classical semi-continuous likelihood versus one that has been adapted to neglect drop-out was compared. Additionally, summary statistics and a rudimentary set of decision guidelines were introduced to help identify mixtures from protein data.     

Degradation in forensic trace DNA samples explored by massively parallel sequencing

Routine forensic analysis using STRs will fail if the DNA is too degraded. The DNA degradation process in biological stain material is not well understood. In this study we sequenced old semen and blood stains by massively parallel sequencing. The sequence data coverage was used to measure degradation across the genome. The results supported the contention that degradation is uniform across the genome, showing no evidence of regions with increased or decreased resistance towards degradation. Thus the lack of genetic regions robust to degradation removes the possibility of using such regions to further optimize analysis performance for degraded DNA.     

Extended kinship analysis of historical remains using SNP capture

DNA-assisted identification of historical remains requires the genetic analysis of highly degraded DNA, along with a comparison to DNA from known relatives. This can be achieved by targeting single nucleotide polymorphisms (SNPs) using a hybridization capture and next-generation sequencing approach suitable for degraded skeletal samples. In the present study, two SNP capture panels were designed to target ~ 25,000 (25 K) and ~ 95,000 (95 K) nuclear SNPs, respectively, to enable distant kinship estimation (up to 4th degree relatives). Low-coverage SNP data were successfully recovered from 14 skeletal elements 75 years postmortem using an Illumina MiSeq benchtop sequencer. All samples contained degraded DNA but were of varying quality with mean fragment lengths ranging from 32 bp to 170 bp across the 14 samples. SNP comparison with DNA from known family references was performed in the Parabon Fx Forensic Analysis Platform, which utilizes a likelihood approach for kinship prediction that was optimized for low-coverage sequencing data with cytosine deamination. The 25 K panel produced 15,000 SNPs on average, which allowed for accurate kinship prediction with strong statistical support in 16 of the 21 pairwise comparisons. The 95 K panel increased the average SNPs to 42,000 and resulted in an additional accurate kinship prediction with strong statistical support (17 of 21 pairwise comparisons). This study demonstrates that SNP capture combined with massively parallel sequencing on a benchtop platform can yield sufficient SNP recovery from compromised samples, enabling accurate, extended kinship predictions.     

Evaluation of mitogenome sequence concordance,heteroplasmy detection,and haplogrouping in a worldwide lineage study using the Precision ID mtDNA Whole Genome Panel

The emergence of Massively Parallel Sequencing technologies enabled the analysis of full mitochondrial (mt)DNA sequences from forensically relevant samples that have, so far, only been typed in the control region or its hypervariable segments. In this study, we evaluated the performance of a commercially available multiplex-PCR-based assay, the Precision ID mtDNA Whole Genome Panel (Thermo Fisher Scientific), for the amplification and sequencing of the entire mitochondrial genome (mitogenome) from even degraded forensic specimens. For this purpose, more than 500 samples from 24 different populations were selected to cover the vast majority of established superhaplogroups. These are known to harbor different signature sequence motifs corresponding to their phylogenetic background that could have an effect on primer binding and, thus, could limit a broad application of this molecular genetic tool. The selected samples derived from various forensically relevant tissue sources and were DNA extracted using different methods. We evaluated sequence concordance and heteroplasmy detection and compared the findings to conventional Sanger sequencing as well as an orthogonal MPS platform. We discuss advantages and limitations of this approach with respect to forensic genetic workflow and analytical requirements.     

A genotype likelihood function for DNA mixtures

The recent advent of genetic genealogy has brought about a renewed interest in genome-scale forensic analyses, of which kinship estimation is a critical component. Most genomic kinship estimators consider SNPs (single nucleotide polymorphisms), often leveraging the co-inheritance of shared alleles to inform their analyses. While current estimators cannot directly evaluate mixed samples, there exist well-established SNP-based kinship estimators tailored to considering challenged samples, including low-pass whole genome sequencing. As an example, several studies have shown remarkable success in imputing genotype posterior probabilities in low template samples when linked sites are considered. Critical to these approaches is the ability to account for genotype uncertainty; the lack of an expression for a genotype likelihood in imbalanced mixtures has prevented direct application. This work develops such an expression. The formulation is fully compatible with genotype imputation software, suggesting a genomic pipeline that estimates genotype likelihoods, performs imputation, and then estimates kinship when the sample is a mixture. Further, when framed as an imbalanced mixture, the problem of mixture deconvolution is reducible to the problem of genotyping mixed samples. Herein, the ability to genotype two-person mixtures is assessed through example and in silico settings. While certain mixture scenarios and classes of sites are inherently inseparable, simulations of read depths between 60 and 190 appear to produce likelihoods of sufficient magnitude to deconvolve two-person mixtures whenever the mixture fraction is moderately imbalanced. The described approach and results suggest a path forward for estimating the kinship coefficient (and similar inferences on relatedness) when the sample is a mixture.     

Evaluating 130 microhaplotypes across a global set of 83 populations

Today the primary DNA markers used in forensics are short tandem repeat (STR) polymorphisms (STRPs), initially selected because they are highly polymorphic. However, the increasingly common need to deal with samples with a mixture of DNA from two or more individuals sometimes is complicated by the inherent stutter involved with PCR amplification, especially in strongly unbalanced mixtures when the minor component coincides with the stutter range of the major component. Also, the STRPs in use provide little evidence of ancestry of a single source sample beyond broad “continental” resolution. Methodologies for analyzing DNA have become much more powerful in recent years. Massively parallel sequencing (MPS) is a new method being considered for routine use in forensics. Primarily to aid in mixture deconvolution and avoid the issue of stutter, we have begun to investigate a new type of forensic marker, microhaplotype loci, that will provide useful information on mixtures of DNA and on ancestry when typed using massively parallel sequencing (MPS). We have identified 130 loci and estimated their haplotype (allele) frequencies in 83 different population samples. Many of these loci are shown to be highly informative for individual identification and for mixture identification and deconvolution.     

Evaluation of microhaplotype panels for complex kinship analysis using massively parallel sequencing

In recent years, microhaplotypes (MHs) have become a research hotspot within the field of forensic genetics. Traditional MHs contain only SNPs that are closely linked within short fragments. Herein, we broaden the concept of general MHs to include short InDels. Complex kinship identification plays an important role in disaster victim identification and criminal investigations. For distant relatives (e.g., 3rd-degree), many genetic markers are required to enhance power of kinship testing. We performed genome-wide screening for new MH markers composed of two or more variants (InDel or SNP) within 220 bp based on the Chinese Southern Han from the 1000 Genomes Project. An NGS-based 67plex MH panel (Panel B) was successfully developed, and 124 unrelated individual samples were sequenced to obtain population genetic data, including alleles and allele frequencies. Of the 67 genetic markers, 65 MHs were, as far as we know, newly discovered, and 32 MHs had effective number of allele (A_e) values greater than 5.0. The average A_e and heterozygosity of the panel were 5.34 and 0.7352, respectively. Next, 53 MHs from a previous study were collected as Panel A (average A_e of 7.43), and Panel C with 87 MHs (average A_e of 7.02) was formed by combining Panels A and B. We investigated the utility of these three panels in kinship analysis (parent-child, full siblings, 2nd-degree, 3rd-degree, 4th-degree, and 5th-degree relatives), with Panel C exhibiting better performance than the two other panels. Panel C was able to separate parent-child, full-sibling, and 2nd-degree relative duos from unrelated controls in real pedigree data, with a small false testing level (FTL) of 0.11% in simulated 2nd-degree duos. For more distant relationships, the FTL was much higher: 8.99% for 3rd-degree, 35.46% for 4th-degree, and 61.55% for 5th-degree. When a carefully chosen extra relative was known, this may enhance the testing power for distant kinship analysis. Two twins from the Q family (2–5 and 2–7) and W family (3–18 and 3–19) shared the same genotypes in all tested MHs, which led to the incorrect conclusion that an uncle-nephew duo was classified as a parent-child duo. In addition, Panel C showed great capacity for excluding close relatives (2nd-degree and 3rd-degree relatives) during paternity tests. Among 18,246 real and 10,000 simulated unrelated pairs, none were misinterpreted as a relative within 2nd-degree at a log₁₀(LR) cutoff of 4. The panels presented herein could provide supplementary power for the analysis of complex kinship.     

Impact of SNP microarray analysis of compromised DNA on kinship classification success in the context of investigative genetic genealogy

Single nucleotide polymorphism (SNP) data generated with microarray technologies have been used to solve murder cases via investigative leads obtained from identifying relatives of the unknown perpetrator included in accessible genomic databases, an approach referred to as investigative genetic genealogy (IGG). However, SNP microarrays were developed for relatively high input DNA quantity and quality, while DNA typically obtainable from crime scene stains is of low DNA quantity and quality, and SNP microarray data obtained from compromised DNA are largely missing. By applying the Illumina Global Screening Array (GSA) to 264 DNA samples with systematically altered quantity and quality, we empirically tested the impact of SNP microarray analysis of compromised DNA on kinship classification success, as relevant in IGG. Reference data from manufacturer-recommended input DNA quality and quantity were used to estimate genotype accuracy in the compromised DNA samples and for simulating data of different degree relatives. Although stepwise decrease of input DNA amount from 200 ng to 6.25 pg led to decreased SNP call rates and increased genotyping errors, kinship classification success did not decrease down to 250 pg for siblings and 1st cousins, 1 ng for 2nd cousins, while at 25 pg and below kinship classification success was zero. Stepwise decrease of input DNA quality via increased DNA fragmentation resulted in the decrease of genotyping accuracy as well as kinship classification success, which went down to zero at the average DNA fragment size of 150 base pairs. Combining decreased DNA quantity and quality in mock casework and skeletal samples further highlighted possibilities and limitations. Overall, GSA analysis achieved maximal kinship classification success from 800 to 200 times lower input DNA quantities than manufacturer-recommended, although DNA quality plays a key role too, while compromised DNA produced false negative kinship classifications rather than false positive ones.     

A nomenclature for sequence-based forensic DNA analysis

Forensic DNA analysis of casework samples using massively parallel sequencing (MPS) technology requires a system of nomenclature for uniquely labeling sequence-based alleles and artifacts. The DNA Commission of the ISFG has published considerations concerning a nomenclature format that addresses the requirement for unique labeling of sequences. Nomenclatures based on this format can be used in databasing, or communicating sequence types, but the format is lengthy for software interfaces. The sequence identifier (SID) nomenclature addresses this gap by generating short labels able to uniquely identify all sequences (allelic and artifactual) in single-source or casework profiles. Sequences in casework profiles can be uniquely labeled with only two or three SID characters, making the format compact. SID labels can be used in algorithms for identifying and filtering artifacts, and for expressing associations between artifacts and their likely parent alleles. The nomenclature is suitable for use in downstream mixture analysis by any software able to accept character values rather than numeral values. The SID nomenclature is described, and its ability to discriminate sequence-based alleles and artifacts is demonstrated, and its applicability to forensic mixture analysis is demonstrated.     

SEQ Mapper: A DNA sequence searching tool for massively parallel sequencing data

The development of massively parallel sequencing (MPS) has increased greatly the scale of DNA sequencing. The analysis of massive data-files from single MPS analysis can be a major challenge if examining the data for potential polymorphic loci. To aid in the analysis of both short tandem repeat (STR) and single nucleotide polymorphisms (SNP), we have designed a new program called SEQ Mapper to search for genetic polymorphisms within a large number of reads generated by MPS. This new program has been designed to perform sequence mapping between reference data and generated reads. As a proof-of-concept, sequences derived from the allelic ladders of five STR loci and data from the amelogenin locus were used as reference data sets. Detecting and recording the polymorphic nature of each STR loci was performed using four levels of search criteria: the entire STR locus spanning the two primers; the STR region plus the two primer sequences; the STR region only; and the two primers only. All the genotypes of 5 STR loci and the amelogenin gene were identified correctly using SEQ Mapper when compared to results obtained from capillary electrophoresis based on 10 test samples in this study. SEQ Mapper is a useful tool to detect STR or SNP alleles generated by MPS in both clinical medicine and forensic genetics.     

Multiplex Y-STRs analysis using the ion torrent personal genome machine (PGM)

Massively parallel sequencing (MPS) technologies allow parallel sequencing analyses of many targeted regions of multiple samples at desirable depth of coverage. Routine use of MPS for forensic genetics is on the horizon. In this study, we explore the application of MPS technology in forensic Y-STR analysis. We designed a multiplex assay with 13 Y-STR loci (DYS19, DYS389 I, DYS389 II, DYS390, DYS391, DYS392, DYS437, DYS438, DYS439, DYS448, DYS456, DYS635, GATA-H4) for the purpose of MPS. The multiplex Y-STR assay was amplified in 42 unrelated male individuals and amplicons were sequenced simultaneously using the ion torrent personal genome machine (PGM) system. All loci were detected successfully, except for DYS389 II that exhibited a failure rate of 1.8% due to the relatively long amplicon sizes. We observed 7, 3, 2, 6 and 5 new alleles, respectively in DYS389 II, DYS390, DYS437, DYS448 and DYS635 due to the presence of sub-repeat composition differences, and a new allele in DYS438 because of nucleotide substitution. One allele of DYS390 was inconsistent with allele call from conventional capillary electrophoresis (CE) because of 4 bp deletions upstream of the core repeat unit. This study demonstrates that Y-STR typing by MPS can provide more genetic information, holding the promise for high discriminatory power.     

Predicting eye and hair colour in a Norwegian population using Verogen’s ForenSeq™ DNA signature prep kit

Prediction of eye and hair colour from DNA can be an important investigative tool in forensic cases if conventional DNA profiling fails to match DNA from any known suspects or cannot obtain a hit in a DNA database. The HIrisPlex model for simultaneous eye and hair colour predictions was developed for forensic usage. To genotype a DNA sample, massively parallel sequencing (MPS) has brought new possibilities to the analysis of forensic DNA samples. As part of an in-house validation, this study presents the genotyping and predictive performance of the HIrisPlex SNPs in a Norwegian study population, using Verogen’s ForenSeq™ DNA Signature Prep Kit on the MiSeq FGx system and the HIrisPlex webtool. DNA-profiles were successfully typed with DNA input down to 125 pg. In samples with DNA input < 125 pg, false homozygotes were observed with as many as 92 reads. Prediction accuracies in terms of AUC were high for red (0.97) and black (0.93) hair colours, as well as blue (0.85) and brown (0.94) eye colours. The AUCs for blond (0.72) and brown (0.70) hair colour were considerably lower. None of the individuals was predicted to have intermediate eye colour. Therefore, the error rates of the overall eye colour predictions were 37% with no predictive probability threshold (pmax) and 26% with a probability threshold of 0.7. We also observed that more than half of the incorrect predictions were for individuals carrying the rs12913832 GG genotype. For hair colour, 65% of the individuals were correctly predicted when using the highest probability category approach. The main error was observed for individuals with brown hair colour that were predicted to have blond hair. Utilising the prediction guide approach increased the correct predictions to 75%. Assessment of phenotype-genotype associations of eye colours using a quantitative eye colour score (PIE-score), revealed that rs12913832 AA individuals of Norwegian descent had statistically significantly higher PIE-score (less brown eye colour) than individuals of non-northern European descent. To our knowledge, this has not been reported in other studies. Our study suggests that careful assessment of the target population prior to the implementation of forensic DNA phenotyping to case work is beneficial.     

Applications of 1993 single nucleotide polymorphism loci in forensic pairwise kinship identifications and inferences

Kinship testing plays critical roles in criminal investigations, missing person searches, civil disputes, as well as identifying disaster victims. The existing commonly used short tandem repeat (STR) loci have limited effectiveness in the identification of second-degree and more distant kinships. In this study, a total of 1993 SNP loci of 119 Chinese Han individuals from eight families were sequenced on the MGISEQ-2000RS platform. The system powers of this panel for kinship identifications were evaluated based on both the likelihood ratio (LR) and identical by state (IBS) methods. The results indicated that this panel could be used as an effective tool to kinship analyses including paternity testing, full sibling testing, second-degree kinships, and first cousin kinship analyses. Both the LR and IBS methods could be applied in distinguishing first-degree and second-degree pairs from unrelated individuals. Based on the 1993 SNP loci, LR>1000 and LR<0.001 are recommended as the thresholds of identifying first-cousin kinships from unrelated individuals, and the system power of such thresholds was 0.9470. Besides, kinship coefficients for different kinship pairs were estimated and then were used to predict the kinships for pairwise individuals. This panel performs an effective kinship inference power for the predictions of first-degree, second-degree kinships and unrelated individual pairs, while presenting low sensitivity in the prediction of first-cousin kinships.     

Mitochondrial DNA heteroplasmy in the emerging field of massively parallel sequencing

Long an important and useful tool in forensic genetic investigations, mitochondrial DNA (mtDNA) typing continues to mature. Research in the last few years has demonstrated both that data from the entire molecule will have practical benefits in forensic DNA casework, and that massively parallel sequencing (MPS) methods will make full mitochondrial genome (mtGenome) sequencing of forensic specimens feasible and cost-effective. A spate of recent studies has employed these new technologies to assess intraindividual mtDNA variation. However, in several instances, contamination and other sources of mixed mtDNA data have been erroneously identified as heteroplasmy. Well vetted mtGenome datasets based on both Sanger and MPS sequences have found authentic point heteroplasmy in approximately 25% of individuals when minor component detection thresholds are in the range of 10–20%, along with positional distribution patterns in the coding region that differ from patterns of point heteroplasmy in the well-studied control region. A few recent studies that examined very low-level heteroplasmy are concordant with these observations when the data are examined at a common level of resolution. In this review we provide an overview of considerations related to the use of MPS technologies to detect mtDNA heteroplasmy. In addition, we examine published reports on point heteroplasmy to characterize features of the data that will assist in the evaluation of future mtGenome data developed by any typing method.     

Improving the system power of complex kinship analysis by combining multiple systems

Complex kinship analysis is a critical issue in forensic genetics. To address this issue, 55 STRs and 94 SNPs collected from four commercial forensic typing kits [three kits were based on a capillary electrophoresis (CE) platform and one was based on a next-generation sequencing (NGS) platform] were employed to test the system power for 2nd-degree and 3rd-degree kinship analysis. To measure the kinship index in related individuals, likelihood ratios (LRs) were calculated based on length and sequence polymorphism information (LR_length and LR_sequence, respectively) from simulation as well as true pedigree samples. LRs calculated based on sequence information are generally higher than those based on length information. The sensitivity, specificity, and effectiveness to distinguish the 2nd- and 3rd-degree kinship were estimated from four marker sets with different numbers of markers. As expected, system power for kinship analysis improved by increasing the number of markers and using LR_sequence, instead of LR_length. Furthermore, the system power based on 55 STRs from the CE platform is equal to the 40 STRs and 94 SNPs from one CE kit and the kit based on NGS platform for both 2nd-degree and 3rd-degree kinship analysis. For discrimination of 2nd-degree kinship, the system effectiveness is 86.63% with an error ratio < 0.01 using the 55 STRs from the CE platform. Using sequence information from the 55 STRs and 94 SNPs, the system effectiveness is 94.43%, with an error ratio < 0.001 for 2nd-degree kinship analysis and 64.34% with an error ratio < 0.05 for 3rd-degree kinship analysis, indicating that these markers are powerful for 2nd-degree kinship analysis and can be used for 3rd-degree kinship analysis.     

Estimating number of contributors in massively parallel sequencing data of STR loci

In recent years a number of computer-based algorithms have been developed for the deconvolution of complex DNA mixtures in forensic science. These procedures utilize likelihood ratios that quantify the evidence for a hypothesis for the presence of a person of interest in a DNA profile compared to an alternative hypothesis. Proper operation of these software systems requires an assumption regarding the total number of contributors present in the mixture. Unfortunately, estimates based on counting the number of alleles at a locus can be inaccurate due to the sharing and masking of alleles at individual loci. The effects of allele masking become increasingly severe as the number of contributors increases, rendering estimates about high-order mixtures uncertain. The accuracy of these estimates can be improved by increasing the number of STR markers in panels, and by using highly polymorphic markers. Increasing the number of STR markers from 13 to 20 (expanded CODIS panel) improves the accuracy of allele count-based estimation methods for low-order mixtures, but accuracy for high-order mixtures (> 3 contributors) remains poor due to allele masking. An alternative technique, massively parallel sequencing, holds great potential to improve the accuracy of the estimate of number of contributors due to its ability to detect sequence polymorphisms within alleles. This process results in an expansion of the number of alleles when compared to that obtained using capillary electrophoresis. Here, we show that the detection of these additional sequence-defined alleles in 22-marker panels improves number of contributor estimates in conceptual mixtures of 4 and 5 contributors.     

Genotyping polymorphic microhaplotype markers through the Illumina® MiSeq platform for forensics

Microhaplotype markers are emerging forensic genetic markers that have received broad attention in forensics and may supplement existing genetic marker panels. Short tandem repeat polymorphisms (STRPs) and single nucleotide polymorphisms (SNPs) are the general genetic markers at present. Stutter and the high mutation rate of STR markers and the low polymorphism of SNP markers obstruct the solving of certain cases. Kidd proposed microhaplotype markers that encompass 2–4 SNPs. In this study, we screened microhaplotype loci through three criteria, and chose the Illumina^® MiSeq platform to sequence the new markers. A new nomenclature was proposed and Perl-based tool FLfinder was designed to genotype the microhaplotype marker. After counting the number of haplotypes in samples that were sequenced and calculating common forensic parameters, 13 loci with high polymorphism were reported. Twelve of the 13 loci had an average allele coverage ratio (ACR) of 0.72 to 0.92. Structure analysis showed that 2504 samples (1000 genome project) could be divided into 5 groupings of populations, and each one representing a continental origin. The finding indicates that microhaplotype markers could be used for individual identification and ancestry inference, and a new choice is provided for forensic practice in the future.     

Development and inter-laboratory evaluation of the VISAGE Enhanced Tool for Appearance and Ancestry inference from DNA

Responding to the growing scientific and practical interest in forensic DNA phenotyping, the VISible Attributes through GEnomics (VISAGE) Consortium was founded in 2017 with the main goal of developing and validating new and reliable molecular and statistical tools to predict appearance, ancestry and age from DNA. Here, we describe the development and inter-laboratory evaluation and validation of the VISAGE Enhanced Tool for Appearance and Ancestry inference from DNA. The VISAGE Enhanced Tool for Appearance and Ancestry is the first forensic-driven genetic laboratory tool that comprises well-established markers for eye, hair and skin color with more recently discovered DNA markers for eyebrow color, freckling, hair shape and male pattern baldness and bio-geographic ancestry informative DNA markers. The bio-geographic ancestry markers include autosomal SNPs (bi- and tri-allelic SNPs), X-SNPs, Y-SNPs and autosomal Microhaplotypes. In total, primers targeting 524 SNPs (representing a 97.6% assay conversion rate) were successfully designed using AmpliSeq into a single primer pool (i.e., one multiplex assay) and sequenced with the Ion S5. In a collaborative framework, five VISAGE laboratories tested the VISAGE Enhanced Tool for Appearance and Ancestry on reproducibility, sensitivity, genotyping concordance, mixtures, species specificity and performance in relevant forensic conditions, including inhibitor-spiked, mock casework and artificially degraded samples. Based on our results, the VISAGE Enhanced Tool for Appearance and Ancestry is a robust, reproducible, and – for the large SNP number - fairly sensitive MPS assay with high concordance rates. With the VISAGE Enhanced Tool for Appearance and Ancestry introduced here, the VISAGE Consortium delivers the first single DNA-test for combined appearance prediction based on seven traits together with bio-geographic ancestry inference based on major continental regions for separated bi-parental and paternal ancestry, which represents the most comprehensive validated laboratory tool currently available for Forensic DNA Phenotyping.