DNA commission of the International Society of Forensic Genetics: Recommendations on the evaluation of STR typing results that may include drop-out and/or drop-in using probabilistic methods

Interpretation and reporting considerations of low-level DNA profiles following MinElute® purification of PowerPlex® 21 amplified products

The generation of high-quality DNA profiles from trace amounts of DNA continues to be an issue in forensic casework. Several methods have been proposed over the years to increase recovery rates for low input DNA, including purification of PCR products, an increase in PCR cycle numbers and increasing injection time or voltage during electrophoresis. In this study, the characteristics of DNA profiles generated using QIAGEN MinElute® purification of Promega PowerPlex® 21 amplified products for low DNA input samples, ranging from 80 pg down to 4 pg, were evaluated. MinElute® purification was found to be a simple, effective and time efficient method, which can greatly improve the resolution of amplified PCR products, recovering 100% of donor concordant alleles from as little 16 pg of input template DNA and generating sufficient allelic information for interpretation from as low as 4 pg inputs. However, as is commonly observed with low template DNA samples, the results exhibited extensive disparity in the effects of stochastic variation in amplification, including increased heterozygote peak height imbalance, stutter ratios and instances of allelic drop-in and drop-out, both within and between replicates. As such, it is important that the extent and variability of these stochastic effects are appropriately incorporated in the development of robust profile interpretation guidelines for DNA profiles generated from purified PCR products.

Improved individual identification in DNA mixtures of unrelated or related contributors through massively parallel sequencing

DNA mixtures are a common sample type in forensic genetics, and we typically assume that contributors to the mixture are unrelated when calculating the likelihood ratio (LR). However, scenarios involving mixtures with related contributors, such as in family murder or incest cases, can also be encountered. Compared to the mixtures with unrelated contributors, the kinship within the mixture would bring additional challenges for the inference of the number of contributors (NOC) and the construction of probabilistic genotyping models. To evaluate the influence of potential kinship on the individual identification of the person of interest (POI), we conducted simulations of two-person (2 P) and three-person (3 P) DNA mixtures containing unrelated or related contributors (parent-child, full-sibling, and uncle-nephew) at different mixing ratios (for 2 P: 1:1, 4:1, 9:1, and 19:1; for 3 P: 1:1:1, 2:1:1, 5:4:1, and 10:5:1), and performed massively parallel sequencing (MPS) using MGIEasy Signature Identification Library Prep Kit on MGI platform. In addition, in silico simulations of mixtures with unrelated and related contributors were also performed. In this study, we evaluated 1): the MPS performance; 2) the influence of multiple genetic markers on determining the presence of related contributors and inferring the NOC within the mixture; 3) the probability distribution of MAC (maximum allele count) and TAC (total allele count) based on in silico mixture profiles; 4) trends in LR values with and without considering kinship in mixtures with related and unrelated contributors; 5) trends in LR values with length- and sequence-based STR genotypes. Results indicated that multiple numbers and types of genetic markers positively influenced kinship and NOC inference in a mixture. The LR values of POI were strongly dependent on the mixing ratio. Non- and correct-kinship hypotheses essentially did not affect the individual identification of the major POI; the correct kinship hypothesis yielded more conservative LR values; the incorrect kinship hypothesis did not necessarily lead to the failure of POI individual identification. However, it is noteworthy that these considerations could lead to uncertain outcomes in the identification of minor contributors. Compared to length-based STR genotyping, using sequence-based STR genotype increases the individual identification power of the POI, concurrently improving the accuracy of mixing ratio inference using EuroForMix. In conclusion, the MGIEasy Signature Identification Library Prep kit demonstrated robust individual identification power, which is a viable MPS panel for forensic DNA mixture interpretations, whether involving unrelated or related contributors.

Assessing DNA Degradation through Differential Amplification Efficiency of Total Human and Human Male DNA in a Forensic qPCR Assay

The assessment of degradation is crucial for the analysis of human DNA samples isolated from forensic specimens. Forensic quantitative PCR (qPCR) assays can include multiple targets of varying amplicon size that display differential amplification efficiency, and thus different concentrations, in the presence of degradation. The possibility of deriving information on DNA degradation was evaluated in a forensic qPCR assay not specifically designed to detect DNA fragmentation, the Plexor HY (Promega), by calculating the ratio between the estimated concentrations of autosomal (99 bp) and Y-chromosomal (133 bp) targets ("[Auto]/[Y]"). The [Auto]/[Y] ratio measured in 57 formalin-fixed, paraffin-embedded samples was compared to a quality score (QS) calculated for corresponding STR profiles using quantitative data (allele peak height). A statistically significant inverse correlation was observed between [Auto]/[Y] and QS (R = -0.65, p < 0.001). The [Auto]/[Y] values were highly correlated (R = 0.75, p < 0.001) with the "[Auto]/[D]" values obtained using the PowerQuant (Promega) assay, expressly designed to detect DNA degradation through simultaneous quantification of a short (Auto) and a long (D) autosomal target. These results indicate that it is possible to estimate DNA degradation in male samples through Plexor HY data and suggest an alternative strategy for laboratories lacking the equipment required for the assessment of DNA integrity through dedicated qPCR assays.

An exploratory view into allelic drop-out of sequenced autosomal STRs

As massively parallel sequencing is implemented in forensic genetics, an understanding of sequence data must accompany these advancements, that is, accurate modeling of data for proper statistical analysis. Allelic drop-out, a common stochastic effect seen in genetic data, is often modeled in statistical analysis of STR results. This proof-of-concept study sequenced several serial dilutions of a standard sample ranging from 4 ng to 7.82 pg to evaluate allelic drop-out trends on a select panel of autosomal STRs using the ForenSeq™ DNA Signature Prep Kit, Primer Set A on the Illumina MiSeq FGx. Parameters assessed included locus, profile, and run specific information. A majority of the allelic drop-out occurred in DNA concentrations less than 31.25 pg. Statistical results indicated a need for locus-specific modeling based on STR descriptors, like simple versus compound repeat patterns. No correlation was seen between average read count of scored alleles and allelic drop-out at a locus. A statistical correlation was observed between the amount of allelic drop-out and the starting amount of DNA in a sample, average read count of a sample, and total read count generated on a flow cell. This study supports using common allelic drop-out factors used in fragment length analysis on sequenced STRs while including additional locus, sample, and run specific information. Results demonstrate multiple factors that can be considered when developing probability of allelic drop-out models for sequenced autosomal STRs including locus-specific analysis, total read count of a profile, and total read count sequenced on a flow cell.

A practical treatment of sensitivity analyses in activity level evaluations

Evaluations of forensic observations considering activity level propositions are becoming more common place in forensic institutions. A measure that can be taken to interrogate the evaluation for robustness is called sensitivity analysis. A sensitivity analysis explores the sensitivity of the evaluation to the data used when assigning probabilities, or to the level of uncertainty surrounding a probability assignment, or to the choice of various assumptions within the model. There have been a number of publications that describe sensitivity analysis in technical terms, and demonstrate their use, but limited literature on how that theory can be applied in practice. In this work we provide some simplified examples of how sensitivity analyses can be carried out, when they are likely to show that the evaluation is sensitive to underlying data, knowledge or assumptions, how to interpret the results of sensitivity analysis, and how the outcome can be reported. We also provide access to an application to conduct sensitivity analysis.

Assessment of mitochondrial DNA copy number variation relative to nuclear DNA quantity between different tissues

Mitochondrial DNA is a widely tested genetic marker in various fields of research and diagnostics. Nonetheless, there is still little understanding on its abundance and quality within different tissues. Aiming to obtain deeper knowledge about the content and quality of mtDNA, we investigated nine tissues including blood, bone, brain, hair (root and shaft), cardiac muscle, liver, lung, skeletal muscle, and buccal mucosa of 32 deceased individuals using two real-time quantitative PCR-based assays with differently sized mtDNA and nDNA targets. The results revealed that the quantity of nDNA is a weak surrogate to estimate mtDNA quantities among tissues of an individual, as well as tissues across individuals. Especially hair showed extreme variation, depicting a range of multiple magnitudes of mtDNA molecules per hair fragment. Furthermore, degradation can lead to fewer fragments being available for PCR. The results call for parallel determination of the quantity and quality of mtDNA prior to downstream genotyping assays.

Single cell genomics applications in forensic science: Current state and future directions

Standard methods of mixture analysis involve subjecting a dried crime scene sample to a "bulk" DNA extraction method such that the resulting isolate compromises a homogenized DNA mixture from the individual donors. If, however, instead of bulk DNA extraction, a sufficient number of individual cells from the mixed stain are subsampled prior to genetic analysis then it should be possible to recover highly probative single source, non-mixed scDNA profiles from each of the donors. This approach can detect low DNA level minor donors to a mixture that otherwise would not be identified using standard methods and can also resolve rare mixtures comprising first degree relatives and thereby also prevent the false inclusion of non-donor relatives. This literature landscape review and associated commentary reports on the history and increasing interest in current and potential future applications of scDNA in forensic genomics, and critically evaluates opportunities and impediments to further progress.

Short Tandem Repeat (STR) Profiling of Earwax DNA Obtained from Healthy Volunteers

The present study aimed to establish human earwax as a potential source of DNA evidence that could be effectively used in human identification. Sixty earwax samples were obtained from 15 healthy male and female Saudi volunteers living in Riyadh, Saudi Arabia. Four consecutive earwax swab samples were obtained from each volunteer and stored for 1, 15, 30 and 60 days. Earwax samples were stored at room temperature (20-22 °C). Reference oral swab was also taken from each volunteer. DNA was extracted by QIAamp DNA Mini kit and quantified by real-time polymerase chain reaction (RT-PCR) on 7500 Thermal Cycler. Autosomal STR loci were amplified using AmpFLSTR™ Identifiler™ Plus PCR Amplification Kit (Thermo Fisher Scientific, Carlsbad, CA, USA). Amplified fragments were size separated and analyzed on a 3500 Genetic Analyzer. Complete autosomal STR profiles were obtained from the earwax swabs of all the volunteers stored up to 30 days after the collection. Some STR profiles were partially obtained 60 days after the earwax collection. Allelic drop-out, allelic drop-in, and stutters were seen in earwax samples analyzed 60 days after the collection. The results have shown that human earwax can be a potential source of DNA evidence for human identification up to 30 days after the earwax collection. It is recommended to quickly analyze earwax samples or store them at room temperature or at -10 °C after their recovery from the crime scene.

An Investigation into Compound Likelihood Ratios for Forensic DNA Mixtures

Simple propositions are defined as those with one POI and the remaining contributors unknown under Hp and all unknown contributors under Ha. Conditional propositions are defined as those with one POI, one or more assumed contributors, and the remaining contributors (if any) unknown under Hp, and the assumed contributor(s) and N unknown contributors under Ha. In this study, compound propositions are those with multiple POI and the remaining contributors unknown under Hp and all unknown contributors under Ha. We study the performance of these three proposition sets on thirty-two samples (two laboratories × four NOCs × four mixtures) consisting of four mixtures, each with N = 2, N = 3, N = 4, and N = 5 contributors using the probabilistic genotyping software, STRmix™. In this study, it was found that conditional propositions have a much higher ability to differentiate true from false donors than simple propositions. Compound propositions can misstate the weight of evidence given the propositions strongly in either direction.

Einsatz vollkontinuierlicher Modelle zur biostatistischen Bewertung forensischer DNA-analytischer Befunde

Die biostatistische Bewertung DNA-analytischer Befunde unterstützt Gerichte bei der Einschätzung des Beweiswertes einer Spur. In der Praxis werden dabei zunehmend Spuren mit minimaler DNA-Menge und möglichen „Drop-in“- und „Drop-out“-Ereignissen sowie komplexe Mischspuren analysiert. Solche Spuren sind mit einer klassischen „binären“ Berechnung biostatistisch häufig nicht oder nur eingeschränkt bewertbar.

Die Entwicklung vollkontinuierlicher Modelle (VKM) macht eine Vielzahl dieser bisher nicht berechenbaren Spuren einer biostatistischen Bewertung zugänglich. Dabei werden nahezu sämtliche verfügbaren Informationen einer DNA-Spur in die Berechnung einbezogen. Während diese probabilistischen Verfahren international bereits vielfach zum Einsatz kommen, liegen hierzu im deutschsprachigen Raum nur wenige Erfahrungen vor.

Um Funktionsweise, Möglichkeiten und Grenzen von VKM-Berechnungen zu erfassen, wurden Mischspuren bekannter Zusammensetzung mit 4 aktuell verfügbaren VKM-Programmen vergleichend analysiert. Bei der Auswertung wurden zentrale Aspekte betrachtet, wie beispielsweise die Konkordanz von Berechnungsergebnissen, der Einfluss von Drop-in- und Drop-out-Ereignissen auf die berechneten vollkontinuierlichen LR-Werte (LRfc) sowie die Ableitung recherchefähiger DNA-Profile mithilfe wahrscheinlichkeitsbasierter Prognosen (Deconvolution).

Die im Rahmen dieser Arbeit gewonnenen Erfahrungen bilden, zusammen mit weiteren bereits international publizierten Studien, eine Basis für Empfehlungen zum Einsatz von VKM-basierter Software bei der biostatistischen Bewertung DNA-analytischer Befunde.

Combining artificial neural network classification with fully continuous probabilistic genotyping to remove the need for an analytical threshold and electropherogram reading

Standard processing of electrophoretic data within a forensic DNA laboratory is for one (or two) analysts to designate peaks as either artefactual or non-artefactual in a process commonly referred to as profile 'reading'. Recently, FaSTR™ DNA has been developed to use artificial neural networks to automatically classify fluorescence within an electropherogram as baseline, allele, stutter or pull-up. These classifications are based on probabilities assigned to each timepoint (scan) within the electropherogram. Instead of using the probabilities to assign fluorescence into a category they can be used directly in the profile analysis. This has a number of advantages; increased objectivity in DNA profile processing, the removal for the need for analysts to read profiles, the removal for the need of an analytical threshold. Models within STRmix™ were extended to incorporate the peak label probabilities assigned by FaSTR™ DNA. The performance of the model extensions was tested on a DNA mixture dataset, comprising 2-4 person samples. This dataset was processed in a 'standard' manner using an analytical threshold of 50rfu, analyst peak designations and STRmix™ V2.9 models. The same dataset was then processed in an automated manner using no analytical threshold, no analysts reading the profile and using the STRmix™ models extended to incorporate peak label probabilities. Both datasets were compared to the known DNA donors and a set of non-donors. The result between the two processes was a very close performance, but with a large efficiency gain in the 0rfu process. Utilising peak label probabilities opens up the possibility for a range of workflow process efficiency gains, but beyond this allows full use of all data within an electropherogram.

GITAD 2020: quality assurance test through 20 years of experience

GITAD (Grupo Iberoamericano de Trabajo en Análisis de DNA) was founded in 1998 as the first operational group of AICEF (Academia Iberoamericana de Criminalística y Estudios Forenses), formally created in 1999. The mission and the vision of GITAD are to promote the development of forensic genetics in Ibero-American countries and to achieve the maximum level of innovation and quality in each country, and with that aim, a proficiency test was developed. Since 1999, the member laboratories receive four reference samples with the objective of obtaining the genetic profile with their routine protocols, a theoretical exercise since 2003, and since 2007, it was incorporated a forensic sample, which changes every year. The consensus results and the different discrepancies are discussed in an annual meeting. This article illustrates the evolution of the proficiency test through 20 years from different points of view: the increase of participant laboratories, the evolution of the different DNA typing techniques reported by the Ibero-American participant laboratories, the challenges that the proficiency test have met, and future perspectives for a continuous improvement of the proficiency test, especially regarding its accreditation under ISO 17043.

Sperm Cell Capture Based on ABH Antigen Differences to Separate Two Men in Mixed Seminal Stains

Personal identification of two individuals in mixed semen samples in forensic DNA testing in general usually involves analysis using autosomal and Y chromosome short tandem repeats (STRs). Results may exclude unrelated donors but cannot identify individuals. In this study, sperm cell capture based on ABH antigen differences was used to obtain the cells with the single ABO blood type. Immunohistochemical staining using labeled anti-A, anti-B, and anti-H antibodies and the laser microdissection system can be used to enrich sperm with different ABO types in mixed seminal stains from two individuals. Then, PCR amplification and capillary electrophoresis were performed to genotype the STR loci. To some extent, after sperm cell capture based on ABH antigen differences, autosomal STR typing using enriched single blood group cells can be utilized to partially identify different individuals in a mixed seminal stain sample from two individuals.

An in-field evaluation of rapid DNA instruments for disaster victim identification

In 2019 and 2020, disaster victim identification (DVI) simulations were conducted at the Australian Facility for Taphonomic Experimental Research. Whole and fragmented cadavers were positioned to replicate a building collapse scenario and left to decompose for up to 4 weeks. This study evaluated the utility of the ANDE™ 6C Rapid DNA System and the RapidHIT^TM ID System for DVI in the field and mortuary. Applying post-mortem nail and tissue biopsy samples showed promise, with the added benefit of minimally invasive collection procedures and limited preparation requirements. The preferred platform will depend on a number of factors, including its intended use and operating environment.

A novel computational strategy to predict the value of the evidence in the SNP-based forensic mixtures

This study introduces a methodology for inferring the weight of the evidence (WoE) in the single nucleotide polymorphism (SNP)-typed DNA mixtures of forensic interest. First, we redefined some algebraic formulae to approach the semi-continuous calculation of likelihoods and likelihood ratios (LRs). To address the allelic dropouts, a peak height ratio index (“h,” an index of heterozygous state plausibility) was incorporated into semi-continuous formulae to act as a proxy for the “split-drop” model of calculation. Second, the original ratio at which a person of interest (POI) has entered into the mixture was inferred by evaluating the DNA amounts conferred by unique genotypes to any possible permutation of any locus of the typing protocol (unique genotypes are genotypes that appear just once in the relevant permutation). We compared this expected ratio (MR_ex) to all the mixing ratios emerging at all other permutations of the mixture (MR_obs) using several (1 - χ²) tests to evaluate the probability of each permutation to exist in the mixture according to quantitative criteria. At the level of each permutation state, we multiplied the (1 - χ²) value to the genotype frequencies and the h index. All the products of all the permutation states were finally summed to give a likelihood value that accounts for three independent properties of the mixtures. Owing to the (1 - χ²) index and the h index, this approach qualifies as a fully continuous methodology of LR calculation. We compared the MRs and LRs emerging from our methodology to those generated by the EuroForMix software ver. 3.0.3. When the true contributors were tested as POIs, our procedure generated highly discriminant LRs that, unlike EuroForMix, never overcame the corresponding single-source LRs. When false contributors were tested as POIs, we obtained a much lower LR value than that from EuroForMix. These two findings indicate that our computational method is more reliable and realistic than EuroForMix.

A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™

Probabilistic genotyping has become widespread. EuroForMix and DNAStatistX are both based upon maximum likelihood estimation using a γ model, whereas STRmix™ is a Bayesian approach that specifies prior distributions on the unknown model parameters. A general overview is provided of the historical development of probabilistic genotyping. Some general principles of interpretation are described, including: the application to investigative vs. evaluative reporting; detection of contamination events; inter and intra laboratory studies; numbers of contributors; proposition setting and validation of software and its performance. This is followed by details of the evolution, utility, practice and adoption of the software discussed.

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).

Potential of Inter- and Intra-Species Variability of CHD1 Gene in Birds as a Forensic Tool

Nowadays, illegal trafficking and smuggling of animals are among the greatest threats to many avian species. Most commonly smuggled birds belong to parrots, song birds, raptor species and owls. All of these species are protected by national and international legislations. In order to prevent and reduce wildlife trafficking, DNA methods have become an important forensic tool in species and sex identification. In this study, CHD1R/CHD1F primer pair was used to amplify a part of the CHD1 gene from 65 birds that belong to 43 species. For 36 species this is the first time that the length of CHD1 amplicons was measured for the purpose of species determination. The results were visualized using capillary electrophoresis and enabled simultaneous determination of sex and species. Based on the number of amplicons (two in females, one in males) sex was successfully determined in all species, even in cases where gel electrophoresis failed to give results. Moreover, the species was successfully determined in most bird species based on the species-specific sizes of CHD1 amplicon. The method used in this study is of great importance for veterinary forensic medicine and the prevention of wildlife smuggling. Still, further work is necessary to confirm the effectiveness of the method in all bird species.

Can a reference 'match' an evidence profile if these have no loci in common?

Cold case reinvestigations are a common occurrence. Occasionally some of the original work was conducted up to 30 years ago using profiling systems of the early 1990s, which targeted HLA-DQA1, ApoB, D1S80 and D17S5. When contemporary work is carried out, if a suspect is identified they will be profiled in contemporary profiling kits such as GlobalFiler. It would be common to then also attempt to profile the evidence profiles in the same contemporary profiling kit. Imagine a scenario where two evidence samples, E₁ and E₂, had previously produced single-source profiles, but only E₂ had any DNA extract left to re-profile with GlobalFiler. At the old loci E₁ matched E₂, and at the new loci E₂ matched the suspect reference. Of interest to the investigation was whether anything could be said about the suspect being a donor of DNA to E₁ even though the reference of the suspect and the profile from E₁ had no loci in common, by using the information from the profile of E₂. This paper explores that possibility.

An integrated system for forensic DNA testing of sexual assault cases in the Philippines

In the Philippines, more than 7000 cases of sexual assault are reported annually. DNA technology is a powerful tool in identifying assailants. However, it is not routinely used in sexual assault investigations due to insufficient government support to cover the high cost of DNA testing and the absence of a national system for sample collection, handling, storage, and DNA testing of biological evidence. In itself, the nature of sexual assault samples containing DNA mixtures presents challenges to laboratory methods and interpretation of results. The sample recovered from the victim may only contain trace amounts of the assailant’s DNA, may have degraded due to prolonged storage in ambient conditions which is warm and humid in the tropics, or contaminated with inhibitors, such as in anal swabs. Hence, a closer evaluation of the processes of evidence collection and DNA testing is needed to increase the likelihood of success in generating conclusive results. In this paper, we propose an integrated system for DNA testing of biological samples collected from sexual assault victims considering the limitations of resources and the prevailing warm climate. Recommendations in this work should provide basis for formulating national guidelines for DNA analysis in aid of criminal investigations. The proposed scheme can be adopted by forensic DNA laboratories in the Philippines and in other countries facing similar challenges.

A Novel SNP-STR System Based on a Capillary Electrophoresis Platform

Various compound markers encompassing two or more variants within a small region can be regarded as generalized microhaplotypes. Many of these markers have been investigated for various forensic purposes, such as individual identification, deconvolution of DNA mixtures, or forensic ancestry inference. SNP-STR is a compound biomarker composed of a single nucleotide polymorphism (SNP) and a closely linked short tandem repeat polymorphism (STR), and possess the advantages of both SNPs and STRs. In addition, in conjunction with a polymerase chain reaction (PCR) technique based on the amplification refractory mutation system (ARMS), SNP-STRs can be used for forensic unbalanced DNA mixture analysis based on capillary electrophoresis (CE), which is the most commonly used platform in worldwide forensic laboratories. Our previous research reported 11 SNP-STRs, but few of them are derived from the commonly used STR loci, for which existing STR databases can be used as a reference. For maximum compatibility with existing DNA databases, in this study, we screened 18 SNP-STR loci, of which 14 were derived from the expanded CODIS core loci set. Stable and sensitive SNP-STR multiplex PCR panels based on the CE platform were established. Assays on simulated two-person DNA mixtures showed that all allele-specific primers could detect minor DNA components in 1:500 mixtures. Population data based on 113 unrelated Chengdu Han individuals were investigated. A Bayesian framework was developed for the likelihood ratio (LR) evaluation of SNP-STR profiling results obtained from two-person mixtures. Furthermore, we report on the first use of SNP-STRs in casework to show the advantages and limitations for use in practice. Compared to 2.86 × 10³ for autosomal STR kits, the combined LR reached 7.14 × 10⁷ using the SNP-STR method in this casework example.

Rapid semen identification from mixed body fluids using methylation-sensitive high-resolution melting analysis of the DACT1 gene

In forensic genetics, a suspect is assigned to a component of a DNA mixture profile, and a probabilistic interpretation is then usually performed. However, it is difficult to determine what types of body fluid the component is from. Previous studies have reported that the fourth exon of the Dishevelled binding antagonist of beta catenin 1 (DACT1) gene is hypomethylated in a semen DNA-specific manner. In the present study, we evaluated whether the DACT1 gene could be effectively used to identify semen in body fluid mixtures and were able to semi-quantify the semen DNA content in mixed fluids. Our results showed that the DACT1 gene was useful in discriminating semen from venous blood and saliva. However, the amount of sperm in semen can affect semen identification. In addition, SI (the semen DNA content index), which we developed, was useful to determine whether the semen compromised majority, almost half, or was in the minority of the components in a mixed fluid. This technique is based on the methylation-sensitive high-resolution melting (MS-HRM) technology, which is time-, cost-, and labour-effective, and could be adopted in routine criminal investigations.

Recovery of single source DNA profiles from mixtures by direct single cell subsampling and simplified micromanipulation

Deconvolution of forensic DNA mixtures into their individual component DNA (geno)types is of great investigative value, though often complex and difficult. Two-person mixtures comprising a major and minor contributor are often easily interpreted although, when the DNA ratio of the two individuals is approximately equal (~1:1), deconvolution and interpretation becomes much more difficult. To address this issue, a physical separation of individual-, two- or three- cell subsamples prior to autosomal STR analysis was performed using a simplified micromanipulation technique paired with a decreased reaction volume and increased cycle number PCR. Using this method, single and multiple buccal epithelial cells were collected from a 1:1 two-person mixture (i.e. from individual 'A' and 'B') and directly amplified, omitting standard DNA extraction and purification steps. Single cell subsamples resulted in partial single-source profiles for both contributors while, in accordance with expectations of a quasi-binomial sampling schema, two- and three-cell subsamples resulted in single source informative partial profiles of individual A and individual B as well as complete consensus profiles, and equally mixed 1:1 (2-cell subsamples) and 2:1 (3-cell subsamples) admixed profiles of individual A and B.This proof-of-concept approach shows promise in permitting the DNA deconvolution of mixed samples where the individual contributors are present in similar amounts that would otherwise be difficult to interpret, resulting in an increase in evidentiary value. The subsampling approach can be readily investigated for DNA casework applications without additional investment in costly, new equipment, requiring only a stereo microscope and a tungsten needle.

STRsearch: a new pipeline for targeted profiling of short tandem repeats in massively parallel sequencing data

BACKGROUND

Short tandem repeats (STRs) are important polymorphism makers for human identification and kinship analyses in forensic science. With the continuous development of massively parallel sequencing (MPS), more laboratories have utilized this technology for forensic applications. Existing STR genotyping tools, mostly developed for whole-genome sequencing data, are not effective for MPS data. More importantly, their backward compatibility with the conventional capillary electrophoresis (CE) technology has not been evaluated and guaranteed.

RESULTS

In this study, we developed a new end-to-end pipeline called STRsearch for STR-MPS data analysis. The STRsearch can not only determine the allele by counting repeat patterns and INDELs that are actually in the STR region, but it also translates MPS results into standard STR nomenclature (numbers and letters). We evaluated the performance of STRsearch in two forensic sequencing datasets, and the concordance with CE genotypes was 75.73 and 75.75%, increasing 12.32 and 9.05% than the existing tool named STRScan, respectively. Additionally, we trained a base classifier using sequence properties and used it to predict the probability of correct genotyping at a given locus, resulting in the highest accuracy of 96.13%.

CONCLUSIONS

All these results demonstrated that STRsearch was a better tool to protect the backward compatibility with CE for the targeted STR profiling in MPS data. STRsearch is available as open-source software at https://github.com/AnJingwd/STRsearch.

Using the Nondonor Distribution to Improve Communication and Inform Decision Making for Low LRs from Minor Contributors in Mixed DNA Profiles

The reporting of a likelihood ratio (LR) calculated from probabilistic genotyping software has become more popular since 2015 and has allowed for the use of more complex mixtures at court. The meaning of "inconclusive" LRs and how to communicate the significance of low LRs at court is now important. We present a method here using the distribution of LRs obtained from nondonors. The nondonor distribution is useful for examining calibration and discrimination for profiles that have produced LRs less than about 10⁴ . In this paper, a range of mixed DNA profiles of varying quantity were constructed and the LR distribution considering the minor contributor for a number of nondonors was compared to the expectation given a calibrated system. It is demonstrated that conditioning genotypes should be used where reasonable given the background information to decrease the rate of nondonor LRs above 1. In all 17 cases examined, the LR for the minor donor was higher than the nondonor LRs, and in 12 of the 17 cases, the 99.9 percentile of the nondonor distribution was lower when appropriate conditioning information was used. The output of the tool is a graph that can show the position of the LR for the person of interest set against the nondonor LR distribution. This may assist communication between scientists and the court.

DNA Recovery From Tape-Lifting Kits: Methodology and Practice

In the case of suspicious deaths, the technique of 1:1 taping is often used in Belgium. It consists of affixing a large number of adhesive tapes to the body of the victim. It is conventionally aimed at obtaining microtraces (e.g., fibers, hair) and is usually not used for DNA analysis. However, in some cases, DNA analysis of certain areas of interest identified on the 1:1 taping material can offer a last resort solution. The four-step method that is described in this article involves the selection of areas of interest on the body (Step 1), the selection of the corresponding tapes (Step 2), the decontamination of the tapes (Step 3), the selection of areas of interest on the tapes, for DNA sampling (Step 4). The method is illustrated by its successful application in four murder cases. In each case, DNA profiles of good quality could be identified, including profiles of persons different from the victim.

Secondary DNA transfer by working gloves

With the development of highly sensitive STR profiling methods, combined with sound statistical tools, DNA analysis on the (sub-)source level is hardly ever seriously questioned in court. More often, the exact mode of DNA transfer to the crime scene is questioned. In burglary cases, in particular when gloves are worn, secondary DNA transfer is often discussed as explanation for finding a DNA profile matching the accused because it is well known that gloves can act as a potential vector for indirect DNA transfer. In this study we investigated the shedder status as a possible factor influencing the extent of secondary DNA transfer to a crime scene, with the person committing the crime wearing working gloves. Firstly, the shedder status for 40 participants (20 male, 20 female) was determined, following a previously published procedure. Good shedders (n = 12) were found to deposit a higher amount and quality of DNA onto objects, compared to bad shedders (n = 25). Secondly, participants were paired into four groups (good with good; good with bad; bad with good; bad with bad), each group consisting of five pairs. The first participant (P1) of each pair used working gloves to pack and carry a box to simulate a house move. Two days later, the second participant (P2) of the pair wore the same pair of gloves to simulate a burglary, using a screwdriver as a break-in tool. After taking swabs of the outside and inside of a glove (primary DNA transfer) and the handle of the screwdriver (secondary DNA transfer), full DNA analysis was performed. Our experiments show that good shedders, overall, deposit more DNA than bad shedders, both onto the outside and the inside of the glove, regardless of being P1 or P2. When conducting the experiments with two participants sharing the same shedder status, no significant differences occurred in the number of deposited alleles. In six out of 19 cases a DNA profile matching P1 was found (binary LR>10⁶) on the screwdriver and in all six cases P1 was a good shedder. Our results indicate that the shedder status of an individual affects the extent of DNA transfer. They further confirm the possibility of an innocent person's DNA profile being found on an object they never handled.

[The forensic medical expertise of the holy relics of the righteous martyr Anastasiya of Uglich]

This article was designed to report the results of the comprehensive (historical-archival, forensic anthropological, and molecular-genetic) investigation into the holy relics of the righteous martyr Anastasiya of Uglich. The well-reasoned expert conclusion contains the scientifically sound data on the prescription of the martyr's corpse burial, age group and sexual identity of the relics, specific anthropological features of the skeleton, torture instruments, and the immediate cause of death. Taken together, the data thus obtained give evidence that the relics actually belong to one of the well-known saints of the Russian orthodox church.

Probabilistic approaches to interpreting two-person DNA mixtures from post-coital specimens

Biological samples submitted for sexual assault investigation typically involve mixtures of DNA from the victim and the assailant/s. Providing a statistical weight to such evidence may be mathematically complex and may be affected by subjective judgment of a human analyst. Software tools have been developed to address these issues. To contribute towards improving the system for routine DNA testing of sexual assault cases, we evaluated two likelihood ratio (LR) approaches: a semi-continuous model using LRmix Studio and a fully continuous approach employed in STRmix™ for interpreting two-person DNA mixtures. LRs conditioned on the presence of the receptive partner's DNA were calculated for a total of 102 two-person DNA samples from simulated mixtures and various post-coital samples. Our results highlight the importance of maximising information provided into the LR calculation to generate strong support for the true hypothesis. This can be achieved by recovering sufficient DNA from a sample to minimise risk of drop-out and increase peak intensities and by implementing a statistical model that utilises as much of the electropherogram information as possible. LRmix is open-source and can handle profiles with allelic drop-out and drop-ins, however stuttering is not modelled and requires manual removal by a DNA analyst especially for mixtures with low template components. STRmix™ makes effective use of all available information by incorporating into its biological model complicating aspects of a DNA profile such as degradation, allele drop-out and drop-in, stutters, and peak height variability.

Correcting forensic DNA errors

DNA mixture interpretation can produce opposing conclusions by qualified forensic analysts, even within the same laboratory. The long-delayed publication of the National Institutes of Standards and Technology (NIST) study of 109 North American crime laboratories in this journal demonstrates this most clearly. This latest study supports earlier work that shows common methods such as the Combined Probability of Inclusion (CPI) have wrongly included innocent people as contributors to DNA mixtures. The 2016 President's Council of Advisors on Science and Technology report concluded, "In summary, the interpretation of complex DNA mixtures with the CPI statistic has been an inadequately specified-and thus inappropriately subjective-method. As such, the method is clearly not foundationally valid" [7]. The adoption of probabilistic genotyping by many laboratories will certainly prevent some of these errors from occurring in the future, but the same laboratories that produced past errors can also now review old cases with their new software-without additional bench work. It is critical that laboratories adopt procedures and policies to do this.

Discrimination of haplotype in mitochondrial DNA mixtures using LNA-mediated PCR clamping

Locked nucleic acid (LNA) has been widely used for various genetic analyses, and has many benefits, in terms of the specificity or sensitivity of amplification, because LNA-containing primers/probes form more stable duplexes with template DNA than probes lacking LNA. Here, we developed a new method for discriminating HV1 haplotypes from mitochondrial DNA (mtDNA) mixtures by applying PCR clamping using LNA. PCR clamping is based on the selective inhibition of amplification using LNA-containing probes, which can discriminate single-nucleotide differences. Before designing probes, we selected 171 sequences with single-nucleotide variations from the HV1 region, and evaluated the specificity of LNA-containing probes for them by predicting Tm values. The differences of Tm between mismatched and exactly matched probe-template duplexes depended markedly on the type of LNA nucleotides for discriminating single-nucleotide differences, and the cytosine LNA nucleotide at the site of variations in the probes was most effective to discriminate these differences. For mixture analysis, each probe targeted one or two variations (16209C, 16217C, 16257A/16261T, 16297C/16298C, 16304C, 16362C, or 16362T) that are particularly common in the Japanese population, and seven designed probes completely inhibited the amplification of exactly matched templates. We prepared mixed samples by mixing DNA from two individuals at a ratio of 1:9, 1:4, 1:1, 4:1, or 9:1, and then performed Sanger sequencing analysis after PCR clamping with each probe. Our method distinguished each haplotype at lower ratios from two-person mixtures, and enabled sensitive detection at 12 pg of total DNA including 600 copies of mtDNA. Moreover, we analyzed three-person mixtures with representative sequences, and detected the minor haplotype of one individual present at a rate of 10% by adding two selected probes. The ability to discriminate haplotypes in mixed samples by using LNA-mediated PCR clamping indicates the potential value of mtDNA analysis in criminal investigations.

Probabilistic genotyping software: An overview

The interpretation of mixed profiles from DNA evidentiary material is one of the more challenging duties of the forensic scientist. Traditionally, analysts have used a "binary" approach to interpretation where inferred genotypes are either included or excluded from the mixture using a stochastic threshold and other biological parameters such as heterozygote balance, mixture ratio, and stutter ratios. As the sensitivity of STR multiplexes and capillary electrophoresis instrumentation improved over the past 25 years, coupled with the change in the type of evidence being submitted for analysis (from high quality and quantity (often single-source) stains to low quality and quantity (often mixed) "touch" samples), the complexity of DNA profile interpretation has equally increased. This review provides a historical perspective on the movement from binary methods of interpretation to probabilistic methods of interpretation. We describe the two approaches to probabilistic genotyping (semi-continuous and fully continuous) and address issues such as validation and court acceptance. Areas of future needs for probabilistic software are discussed.

Four model variants within a continuous forensic DNA mixture interpretation framework: Effects on evidential inference and reporting

Continuous mixture interpretation methods that employ probabilistic genotyping to compute the Likelihood Ratio (LR) utilize more information than threshold-based systems. The continuous interpretation schemes described in the literature, however, do not all use the same underlying probabilistic model and standards outlining which probabilistic models may or may not be implemented into casework do not exist; thus, it is the individual forensic laboratory or expert that decides which model and corresponding software program to implement. For countries, such as the United States, with an adversarial legal system, one can envision a scenario where two probabilistic models are used to present the weight of evidence, and two LRs are presented by two experts. Conversely, if no independent review of the evidence is requested, one expert using one model may present one LR as there is no standard or guideline requiring the uncertainty in the LR estimate be presented. The choice of model determines the underlying probability calculation, and changes to it can result in non-negligible differences in the reported LR or corresponding verbal categorization presented to the trier-of-fact. In this paper, we study the impact of model differences on the LR and on the corresponding verbal expression computed using four variants of a continuous mixture interpretation method. The four models were tested five times each on 101, 1-, 2- and 3-person experimental samples with known contributors. For each sample, LRs were computed using the known contributor as the person of interest. In all four models, intra-model variability increased with an increase in the number of contributors and with a decrease in the contributor’s template mass. Inter-model variability in the associated verbal expression of the LR was observed in 32 of the 195 LRs used for comparison. Moreover, in 11 of these profiles there was a change from LR > 1 to LR < 1. These results indicate that modifications to existing continuous models do have the potential to significantly impact the final statistic, justifying the continuation of broad-based, large-scale, independent studies to quantify the limits of reliability and variability of existing forensically relevant systems.

A forensic visual aid: Traces versus knowledge

In this paper, I introduce the Forensic Field Map (FFM) that provides a two-dimensional view on the forensic field. This field is by definition very broad, encompassing a wide range of scientific areas and activities. The forensic work that supports solving criminal cases ranges from recognizing and preserving traces at crime scenes to explaining forensic results as expert witness in court. This goes hand in hand with the development of scientifically based methods and tooling as well as legal, forensic and laboratory procedures. Although the FFM came into being while developing a (visual) framework for digital forensic investigations, the framework turned out to be generically applicable to other forensic disciplines.

Sharing data on DNA transfer, persistence, prevalence and recovery: Arguments for harmonization and standardization

Sharing data between forensic scientists on DNA transfer, persistence, prevalence and recovery (TPPR) is crucial to advance the understanding of these issues in the criminal justice community. We present the results of a collaborative exercise on reporting forensic genetics findings given activity level propositions. This exercise outlined differences in the methodology that was applied by the participating laboratories, as well as limitations to the use of published data on DNA TPPR. We demonstrate how publication of experimental results in scientific journals can be further improved to allow for an adequate use of these data. Steps that can be taken to share and use these data for research and casework purposes are outlined, and the prospects for future sharing of data through publicly accessible databases are discussed. This paper also explores potential avenues to proceed with implementation and is intended to fuel the discussion on sharing data pertaining to DNA TPPR issues. It is further suggested that international standardization and harmonization on these topics will benefit the forensic DNA community as it has been achieved in the past with the harmonization of STR typing systems.

The Probabilistic Genotyping Software STRmix: Utility and Evidence for its Validity

Forensic DNA interpretation is transitioning from manual interpretation based usually on binary decision-making toward computer-based systems that model the probability of the profile given different explanations for it, termed probabilistic genotyping (PG). Decision-making by laboratories to implement probability-based interpretation should be based on scientific principles for validity and information that supports its utility, such as criteria to support admissibility. The principles behind STRmix™ are outlined in this study and include standard mathematics and modeling of peak heights and variability in those heights. All PG methods generate a likelihood ratio (LR) and require the formulation of propositions. Principles underpinning formulations of propositions include the identification of reasonably assumed contributors. Substantial data have been produced that support precision, error rate, and reliability of PG, and in particular, STRmix™. A current issue is access to the code and quality processes used while coding. There are substantial data that describe the performance, strengths, and limitations of STRmix™, one of the available PG software.