Internal validation of STRmix™ for the interpretation of single source and mixed DNA profiles

A collaborative study on the precision of the Markov chain Monte Carlo algorithms used for DNA profile interpretation

Several fully continuous probabilistic genotyping software (PGS) use Markov chain Monte Carlo algorithms (MCMC) to assign weights to different proposed genotype combinations at a locus. Replicate interpretations of the same profile in these software are expected not to produce identical weights and likelihood ratio (LR) values due to the Monte Carlo aspect. This paper reports a detailed precision study under reproducibility conditions conducted as a collaborative exercise across the National Institute of Standards and Technology (NIST), Federal Bureau of Investigation (FBI), and Institute of Environmental Science and Research (ESR). Replicate interpretations generated across the three laboratories used the same input files, software version, and settings but different random number seed and different computers. This work demonstrates that using different computers to analyze replicate interpretations does not contribute to any variations in LR values. The study quantifies the magnitude of differences in the assigned LRs that is only due to run-to-run MCMC variability and addresses the potential explanations for the observed differences.

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.

Carrying out common DNA donor analysis using DBLR™ on two or five-cell mini-mixture subsamples for improved discrimination power in complex DNA mixtures

Probabilistic genotyping systems are able to analyse complex mixed DNA profiles and show good power to discriminate contributors from non-contributors. However, the abilities of the statistical analyses are still unavoidably bound by the quality of information being analysed. If a profile has a high number of contributors, or a contributor that is present in trace amounts, then the amount of information about those individuals in the DNA profile is limited. Recent work has shown the ability to gain better resolution of the genotypes of contributors to complex profiles using cell subsampling. This is the process of taking many sets of a limited number of cells and individually profiling each set. These 'mini-mixtures' can provide greater information about the genotypes of underlying contributors. In our work we take the resulting profiles from multiple subsamplings of complex DNA profiles in equal amounts and show how testing for, and then assuming, a common DNA donor can further improve the ability to resolve the genotypes of contributors. Using direct cell sub-sampling and statistical analysis software DBLR™, we were able to recover single source profiles of uploadable quality from five out of the six contributors of an equally proportioned mixture. Through the analysis of mixtures in this work we provide a template for carrying out common donor analysis for maximum effect.

A lights-out forensic DNA analysis workflow for no-suspect crime

An automated system of DNA profile processing (termed a 'lights-out' workflow) was trialled for no-suspect cases over a three-month period at Forensic Science SA (FSSA). The lights-out workflow utilised automated DNA profile reading using the neural network reading feature in FaSTR™ DNA with no analytical threshold. The profile information from FaSTR™ DNA was then processed in STRmix™ using a top-down analysis and automatically compared to a de-identified South Australian searchable DNA database. Computer scripts were used to generate link reports and upload reports and these were compared to the links and uploads that were obtained for the cases during their standard processing within the laboratory. The results of the lights-out workflow was an increase in both uploads and links compared to the standard workflow, with minimal adventitious links or erroneous uploads. Overall, the proof-of-concept study shows the potential for using automated DNA profile reading and top-down analysis to improve workflow efficiency in a no-suspect workflow.

Applications of artificial intelligence in forensic sciences: Current potential benefits, limitations and perspectives

In recent years, new studies based on artificial intelligence (AI) have been conducted in the forensic field, posing new challenges and demonstrating the advantages and disadvantages of using AI methodologies to solve forensic well-known problems. Specifically, AI technology has tried to overcome the human subjective bias limitations of the traditional approach of the forensic sciences, which include sex prediction and age estimation from morphometric measurements in forensic anthropology or evaluating the third molar stage of development in forensic odontology. Likewise, AI has been studied as an assisting tool in forensic pathology for a quick and easy identification of the taxonomy of diatoms. The present systematic review follows the PRISMA 2020 statements and aims to explore an emerging topic that has been poorly analyzed in the forensic literature. Benefits, limitations, and forensic implications concerning AI are therefore highlighted, by providing an extensive critical review of its current applications on forensic sciences as well as its future directions. Results are divided into 5 subsections which included forensic anthropology, forensic odontology, forensic pathology, forensic genetics, and other forensic branches. The discussion offers a useful instrument to investigate the potential benefits of AI in the forensic fields as well as to point out the existing open questions and issues concerning its application on real-life scenarios. Procedural notes and technical aspects are also provided to the readers.

Magnetic bead-based separation of sperm cells from semen-vaginal fluid mixed stains using an anti-ACRBP antibody

Forensic DNA analysis of semen-vaginal fluid mixed stains is essential and necessary in sexual assault cases. Here, we used a magnetic bead conjugated acrosin binding protein (ACRBP) antibody to separate and enrich sperm cells from mixed stains. Previously, western blotting indicated that ACRBP was specifically expressed in sperm cells, but not in female blood and epithelial cells, while immunofluorescence data showed ACRBP was localized to the acrosome in sperm cells. In our study, sperm were separated from mixed samples at three sperm cell/female buccal epithelial cell ratios (10³:10³; 10³:10⁴; and 10³:10⁵) using a magnetic bead conjugated ACRBP antibody. Subsequently, 23 autosomal short tandem repeat (STR) loci were amplified using the Huaxia™ Platinum PCR Amplification System and genotyped using capillary electrophoresis. The genotyping success rate for STR loci was 90% when the sperm to female buccal epithelial cell ratio was > 1:100 in mixed samples. Our results suggest that the magnetic bead conjugated ACRBP antibody is effective for isolating sperm cells in sexual assault cases.

Uncertainty in probabilistic genotyping of low template DNA: A case study comparing STRMix™ and TrueAllele™

Two probabilistic genotyping (PG) programs, STRMix™ and TrueAllele™, were used to assess the strength of the same item of DNA evidence in a federal criminal case, with strikingly different results. For STRMix, the reported likelihood ratio in favor of the non-contributor hypothesis was 24; for TrueAllele it ranged from 1.2 million to 16.7 million, depending on the reference population. This case report seeks to explain why the two programs produced different results and to consider what the difference tells us about the reliability and trustworthiness of these programs. It uses a locus-by-locus breakdown to trace the differing results to subtle differences in modeling parameters and methods, analytic thresholds, and mixture ratios, as well as TrueAllele's use of an ad hoc procedure for assigning LRs at some loci. These findings illustrate the extent to which PG analysis rests on a lattice of contestable assumptions, highlighting the importance of rigorous validation of PG programs using known-source test samples that closely replicate the characteristics of evidentiary samples. The article also points out misleading aspects of the way STRMix and TrueAllele results are routinely presented in reports and testimony and calls for clarification of forensic reporting standards to address those problems.

Y-STR mixture deconvolution by single-cell analysis

Since Y-STR typing only amplifies male Y chromosomal DNA, it can simplify the interpretation of some DNA mixtures that contain female DNA. However, if there are multiple male contributors, mixed Y-STR DNA profiles will often be obtained. Y-STR mixture analysis cases are particularly challenging though as, currently, there are no validated probabilistic genotyping (PG) software solutions commercially available to aid in their interpretation. One approach to fully deconvoluting these challenging mixtures into their individual donors is to conduct single-cell genotyping by isolating individual cells from a mixture prior to conducting DNA typing. In this work, a physical micromanipulation technique involving a tungsten needle and direct PCR with decreased reaction volume and increased cycle number was applied to equimolar 2- and 3-person buccal cell male DNA mixtures and a mock touch DNA case scenario involving the consecutive firing of a handgun by two males. A consensus DNA profiling approach was then utilized to obtain YFiler™ Plus Y-STR haplotypes. Buccal cells were used to optimize and test the direct single-cell subsampling approach, and 2-3 person male buccal cell mixtures were fully deconvoluted into their individual donor Y-STR haplotypes. Single-cell (or agglomerated cell clump) subsampling from the gun's trigger recovered single-source Y-STR profiles from both individuals who fired the gun, the owner, and the other unrelated male. Only the non-owner's DNA was found in the cells recovered from the handle. In summary, direct single-cell subsampling as described represents a potential simple way to analyze and interpret Y-STR mixtures.

Developmental validation of STRmix™ NGS, a probabilistic genotyping tool for the interpretation of autosomal STRs from forensic profiles generated using NGS

We describe the developmental validation of the probabilistic genotyping software - STRmix™ NGS - developed for the interpretation of forensic DNA profiles containing autosomal STRs generated using next generation sequencing (NGS) also known as massively parallel sequencing (MPS) technologies. Developmental validation was carried out in accordance with the Scientific Working Group on DNA Analysis Methods (SWGDAM) Guidelines for the Validation of Probabilistic Genotyping Systems and the International Society for Forensic Genetics (ISFG) recommendations and included sensitivity and specificity testing, accuracy, precision, and the interpretation of case-types samples. The results of developmental validation demonstrate the appropriateness of the software for the interpretation of profiles developed using NGS technology.

The potential for investigator-mediated contamination to occur during routine search activities

The sensitivity and discrimination power of modern DNA profiling systems means that very small amounts of DNA from an individual can be detected on an item leading to large inclusionary statistics for that person. The sensitivity of these systems has significant benefits in the investigation of crime but also can be highly sensitive to contamination of exhibits or crime scenes. It becomes critical to distinguish between deposition during commission of a crime or deposition via some other method unrelated to the crime. This study investigates methodologies used in crime scene examination and the potential for them to cause non-crime-related transfer of DNA. Factors assessed include the source of DNA, the handling time, the amount of movement during contact, and the substrate type. The amount of movement and the number of transfer steps are the most critical in determining whether, and how much, DNA is transferred. This study provides information for crime scene examiners and also scientists assessing transfer scenarios.

Internal Validation of MaSTR™ Probabilistic Genotyping Software for the Interpretation of 2–5 Person Mixed DNA Profiles

Mixed human deoxyribonucleic acid (DNA) samples present one of the most challenging pieces of evidence that a forensic analyst can encounter. When multiple contributors, stochastic amplification, and allele drop-out further complicate the mixture profile, interpretation by hand becomes unreliable and statistical analysis problematic. Probabilistic genotyping software has provided a tool to address complex mixture interpretation and provide likelihood ratios for defined sets of propositions. The MaSTR™ software is a fully continuous probabilistic system that considers a wide range of STR profile data to provide likelihood ratios on DNA mixtures. Mixtures with two to five contributors and a range of component ratios and allele peak heights were created to test the validity of MaSTR™ with data similar to real casework. Over 280 different mixed DNA profiles were used to perform more than 2600 analyses using different sets of propositions and numbers of contributors. The results of the analyses demonstrated that MaSTR™ provided accurate and precise statistical data on DNA mixtures with up to five contributors, including minor contributors with stochastic amplification effects. Tests for both Type I and Type II errors were performed. The findings in this study support that MaSTR™ is a robust tool that meets the current standards for probabilistic genotyping.

A tool for simulating single source and mixed DNA profiles

Simulation studies play an important role in the study of probabilistic genotyping systems, as a low cost and fast alternative to in vitro studies. With ongoing calls for further study of the behaviour of probabilistic genotyping systems, there is a continuous need for such studies. In most cases, researchers use simplified models, for example ignoring complexities such as peak height variability due to lack of availability of advanced tools. We fill this void and describe a tool that can simulate DNA profiles in silico for the validation and investigation of probabilistic genotyping software. Contributor genotypes are simulated by randomly sampling alleles from selected allele frequencies. Some or all contributors may be related to a pedigree and the genotypes of non-founders are obtained by random gene dropping. The number of contributors per profile, and ranges for parameters such as DNA template amount and degradation parameters can be configured. Peak height variability is modelled using a lognormal distribution or a gamma distribution. Profile behaviour of simulated profiles is shown to be broadly similar to laboratory generated profiles though the latter shows more variation. Simulation studies do not remove the need for experimental data. The tool has been made available as an R-package named simDNAmixtures.

Exploring likelihood ratios assigned for siblings of the true mixture contributor as an alternate contributor

Relatives tend to have more DNA in common than unrelated people. The closer the biological relationship, the higher the chance of alleles being identical by descent between the individuals. Therefore, when considering a mixed DNA profile, close relatives of the true contributor may not always be excluded as a possible contributor to a mixture due to allele sharing. In these situations, it might be more appropriate under the alternate proposition to consider that the DNA could have originated from a relative of the person of interest rather than an unrelated individual. The probabilistic genotyping software STRmix™ automatically provides LRs considering close biological relatives as alternate sources of the DNA. In this paper, we investigate the support for siblings of the true contributor to a mixture (who are not present in the mixture themselves). We interpret the mixtures and assign LRs using STRmix™ and investigate whether the resulting LRs could be used to indicate whether the true contributor could be a sibling of the POI. Most siblings will have one or more alleles that are not observed in the mixture profile. Support for siblings to have contributed can only occur when allelic dropout is a possibility at the loci where the siblings have alleles that are not observed in the profile. In these data, that was only observed in components with assigned template of 588 rfu or less.

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.

A new approach for forensic analysis of saliva-containing body fluid mixtures based on SNPs and methylation patterns of nearby CpGs

Saliva samples obtained from crime scenes often contain body fluids from other people, which makes it difficult to not only interpret the obtained DNA profiles, but also interpret saliva identification test results. α-amylase activity, an indicator of most saliva identification methods, can be slightly detected in other body fluids. This study aimed to overcome these difficulties. Here, we identified 13 saliva-specific methylated regions and five saliva-specific unmethylated regions neighboring common single nucleotide polymorphisms (SNPs) by array-based genome-wide methylation analysis of pooled saliva, blood, semen, or vaginal swab samples. Bisulfite sequencing by massively parallel sequencing (MPS) technology was then performed using individual body fluid samples to evaluate the saliva-specificity of each CpG of the three regions selected from the identified candidates. Although no single CpG demonstrated complete saliva-specificity, we found that the reads that were simultaneously (un)methylated at the selected neighboring two to three CpGs of each region were highly specific for saliva DNA. Based on these findings, we then designed MPS-based bisulfite sequencing assays for each region to analyze the selected CpGs and SNP(s) on the same read. These assays could identify the saliva of a target person from body fluid mixtures of known contributors (individual-specific saliva identification) by calculating the ratios of simultaneous (un)methylation at the selected CpGs within the reads containing SNP alleles unique to the target person. Moreover, these assays could indicate the SNP types of saliva DNA (saliva-specific genotyping) from body fluid mixtures by analyzing the alleles of the reads simultaneously (un)methylated at the selected CpGs, while careful attention should be paid to interpret the results of heterologous genotypes. Although further regions should be identified, especially for saliva-specific individual identification, the CpG-SNP approach may be an effective method to interpret the complicated results obtained from saliva-containing body fluid mixtures.

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.

Examining performance and likelihood ratios for two likelihood ratio systems using the PROVEDIt dataset

A likelihood ratio (LR) system is defined as the entire pipeline of the measurement and interpretation processes where probabilistic genotyping software (PGS) is a piece of the whole LR system. To gain understanding on how two LR systems perform, a total of 154 two-person, 147 three-person, and 127 four-person mixture profiles of varying DNA quality, DNA quantity, and mixture ratios were obtained from the filtered (.CSV) files of the GlobalFiler 29 cycles 15s PROVEDIt dataset and deconvolved in two independently developed fully continuous programs, STRmix v2.6 and EuroForMix v2.1.0. Various parameters were set in each software and LR computations obtained from the two software were based on same/fixed EPG features, same pair of propositions, number of contributors, theta, and population allele frequencies. The ability of each LR system to discriminate between contributor (H1-true) and non-contributor (H2-true) scenarios was evaluated qualitatively and quantitatively. Differences in the numeric LR values and their corresponding verbal classifications between the two LR systems were compared. The magnitude of the differences in the assigned LRs and the potential explanations for the observed differences greater than or equal to 3 on the log10 scale were described. Cases of LR < 1 for H1-true tests and LR > 1 for H2-true tests were also discussed. Our intent is to demonstrate the value of using a publicly available ground truth known mixture dataset to assess discrimination performance of any LR system and show the steps used to understand similarities and differences between different LR systems. We share our observations with the forensic community and describe how examining more than one PGS with similar discrimination power can be beneficial, help analysts compare interpretation especially with low-template profiles or minor contributor cases, and be a potential additional diagnostic check even if software in use does contain certain diagnostic statistics as part of the output.

Statistefix 4.0: A novel probabilistic software tool

Latest innovations indicate that continuous tools are promising DNA trace assessment methods. In this study, we present the continuous software solution Statistefix 4.0. The software supports DNA experts in deducing DNA profiles for database queries and can help to preselect DNA samples suitable for further processing using advanced probabilistic search engines. The novel tool weights genotype contributions and deduces major contributors from high- and low-quality DNA traces. Peak height, degradation, stutter as well as allelic drop-in/-out events are incorporated in the statistical model. We analyzed reference and casework samples as well as artificially generated mixture samples for software evaluation. The tool offers the completely automated assessment of reference and mixture samples. Deconvolution outcomes of mixtures are compared with EuroForMix, GenoProof Mixture 3 and STRmix™. Data show that Statistefix 4.0 is as successful as analogously tested and implemented software. Deduced DNA profiles from casework samples highlight the potential benefit in routine casework. Statistefix 4.0 is freely available, works with replicates of different autosomal kits and enables bulk sample processing. This inter-laboratory study includes a variety of sample types and indicates a timesaving, robust and easily implemented software that supports DNA analysts in evaluating DNA traces.

DNA on drugs! A preliminary investigation of DNA deposition during the handling of illicit drug capsules

DNA profiling from capsules and tablets offers a complementary tool to that of chemical profiling when investigating the manufacture and trade in illicit drugs. By sampling the outside of capsules, individuals who may have handled them during production, assembly or distribution may have deposited their DNA and can be identified if matched to a nominated profile or one on a relevant DNA database. The profiles can also be compared to those found on other capsules to potentially link various drug seizures. This study sampled the exterior of capsules after they had been handled in a controlled scenario to determine if informative DNA profiles could be generated from this brief contact. Two individuals of intermediate shedder status washed their hands and waited for 30 min before handling ten gelatine, vegetable, and enteric vegetable capsules each (n = 60). Contact was made for 15 s. Each capsule was swabbed and DNA isolated. The amount of recovered human DNA was quantified and profiled using the Verifiler Plus DNA profiling kit. Profiles were generated from 82% (49/60) of capsules tested with LR values above 1 × 10³ for the inclusion of the volunteer as a contributor. Inhibition of the PCR was detected in 24 of the 60 samples, however 16 of these still produced informative profiles when sufficient template DNA was available and only mild inhibition was detected, or by overcoming inhibition by dilution of the DNA extract. This pilot study demonstrates the potential for forensic science laboratories to recover human DNA from the exterior surface of capsules which are commonly used to encase illicit drugs such as MDMA, thus enabling both biological and chemical profiling methods to contribute to the investigation of clandestine drug production and distribution.

Validation of a top-down DNA profile analysis for database searching using a fully continuous probabilistic genotyping model

Slooten described a method of targeting major contributors in mixed DNA profiles and comparing them to individuals on a DNA database. The method worked by taking incrementally more peak information from the profile (based on the peak contribution), and using a semi-continuous model, calculating likelihood ratios for the comparison to database individuals. We describe the performance of this "top down approach" to profile interpretation within probabilistic genotyping software employing a fully continuous model. We interpret both complex constructed profiles where ground truth is known and casework profiles from non-suspect crimes. The interpretation of constructed four- and five- person mixtures demonstrated good discrimination power between contributors and non-contributors to the mixtures. Not all known contributors linked, and this is expected, particularly for minor contributors of DNA to the profile, or when the DNA from contributors was in relatively equal contributions. This finding was also reported by Slooten for the semi-continuous application of the approach. The maximum observed LR was shown to not exceed the LR obtained after a standard interpretation approach outside of that expected due to Monte Carlo variation. The interpretation of 91 complex profiles from no-suspect casework demonstrated that approximately 75% of profiles returned a link to someone on a database of known individuals. With a yearly average of 110 no-suspect cases that fall into this too-complex category at Forensic Science SA, the top down analysis, if applied to all such profiles, would represent an increase of 83 links per year of investigative information that could be provided to investigators.

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.

When evaluating DNA evidence within a likelihood ratio framework, should the propositions be exhaustive?

We seek to develop a rational approach to forming propositions when little information is available from the outset, as this often happens in casework. If propositions used when evaluating evidence are not exhaustive (in the context of the case), then there is a theoretical risk that an LR greater than one may be associated with a proposition in the numerator that - if all meaningful propositions had been considered - would in fact have a lower posterior probability after consideration of the evidence. Ideally, all propositions should be considered. However, with multiple propositions, some terms will be larger than others and for simplification very small terms can be neglected without changing the order of magnitude of the value of the evidence (i.e. LR). Our analysis shows that mathematically a contributor's DNA can be assumed to be present under both prosecution and alternative propositions (H_p and H_a) if there is a reasonable prior probability of their DNA being present and their inclusion is supported by the profile. This is because the terms associated to these sub-propositions will dominate our LR. For example, in the absence of specific information, when considering two persons of interest (POI) as potential contributors to a mixed DNA profile we suggest the assumption of one when examining the presence of the other, after checking that both collectively explain the profile well. This represents more meaningful propositions and allows better discrimination. Slooten and Caliebe have shown that the overall LR is the weighted average of LRs with the same number of contributors (NoC) under both propositions. The weights involve both an assessment of the probability of the crime scene DNA profile and the probability of this NoC given the background information.

Interpol review of forensic biology and forensic DNA typing 2016-2019

This review paper covers the forensic-relevant literature in biological sciences from 2016 to 2019 as a part of the 19th Interpol International Forensic Science Managers Symposium. The review papers are also available at the Interpol website at: https://www.interpol.int/content/download/14458/file/Interpol%20Review%20Papers%202019.pdf.

Systematic evaluation of STRmix™ performance on degraded DNA profile data

This study examined the DNA degradation modeling capacity of STRmix™, a widely implemented DNA interpretation software program. As a part of the CAL DOJ STRmix™ v2.4 validation, a large volume of STR profile data was generated from intact template DNA exposed to DNase I for a series of increasing time intervals. The resulting degraded profile data was analyzed with STRmix™ v2.4, and the efficacy of the analysis was assessed, both in terms of how the degradation modeling parameter values from the STRmix™ analysis compared to ground truth values, and how the weight-of-evidence statistics calculated for degraded profiles compared to those calculated for corresponding intact profiles. An additional set of differentially degraded mixture data was generated in silico to further challenge the STRmix™ degradation model, as well as to determine the extent to which end-user adjustment of the model's application can assist in resolving analysis problems that arise when high levels of degradation are observed in a profile. This work demonstrates that the degradation model in STRmix™ is capable of addressing a wide range of degraded STR profile data. The assessment expands the range of samples that have been rigorously examined using probabilistic genotyping approaches, as called for by forensic advisory bodies such as the United States President's Council of Advisors on Science and Technology.

Assessment of the transfer, persistence, prevalence and recovery of DNA traces from clothing: An inter-laboratory study on worn upper garments

Among the various items recovered from crime scenes or persons involved in a crime event, clothing items are commonly encountered and submitted for forensic DNA sampling. Depending on the case circumstances and the activity-of-interest, sampling of the garment may concentrate on collecting DNA from the wearer, or from one or more offenders who have allegedly contacted the item and/or wearer. Relative to the targeted DNA, background DNA already residing on the item from previous contacts, or transferred during or after the crime event, may also be collected during sampling and observed in the resultant DNA profile. Given our limited understanding of how, and from where, background DNA is derived on clothing, research on the transfer, persistence, prevalence, and recovery (TPPR) of DNA traces from upper garments was conducted by four laboratories. Samples were collected from several areas of two garments, each worn on separate working or non-working days and individually owned by four individuals from each of the four laboratories, and processed from DNA extraction through to profiling. Questionnaires documented activities relating to the garment prior to and during wearing, and reference profiles were obtained from the wearer and their close associates identified in the questionnaire. Among the 448 profiles generated, variation in the DNA quantity, composition of the profiles, and inclusion/exclusion of the wearer and their close associates was observed among the collaborating laboratories, participants, garments worn on different occasions, and garment areas sampled.

The advances in DNA mixture interpretation

In forensic genetics, the analysis of DNA in biological samples is a valuable tool for personal identification. There is an increasing demand in analyzing of the mixed DNA which may provide insightful investigative instructions. With the continuous effort for the improvement of individual identification, complicated mixed stains represent a growing fraction of the samples processed by forensic laboratories. Recent technological advances have enabled quantitative analysis of DNA mixture and emerging sequencing approaches to decipher the complicated DNA mixture. Here, we describe the use of different genetic markers, typing approaches and analytical methods in mixture analysis, and how useful information can be obtained from complicated DNA mixture.

Inter-sample contamination detection using mixture deconvolution comparison

A recent publication has provided the ability to compare two mixed DNA profiles and consider their probability of occurrence if they do, compared to if they do not, have a common contributor. This ability has applications to both quality assurance (to test for sample to sample contamination) and for intelligence gathering purposes (did the same unknown offender donate DNA to multiple samples). We use a mixture to mixture comparison tool to investigate the prevalence of sample to sample contamination that could occur from two laboratory mechanisms, one during DNA extraction and one during electrophoresis. By carrying out pairwise comparisons of all samples (deconvoluted using probabilistic genotyping software STRmix™) within extraction or run batches we identify any potential common DNA donors and investigate these with respect to their risk of contamination from the two proposed mechanisms. While not identifying any contamination, we inadvertently find a potential intelligence link between samples, showing the use of a mixture to mixture comparison tool for investigative purposes.

A comparative study for the isolation of exogenous trace DNA from fingernails

Often fingernails from a victim or suspect involved in a physical assault, such as murder or sexual assault, are submitted to crime laboratories for DNA testing of foreign/exogenous biological material; however, very few studies have been conducted comparing the effectiveness of different sampling methods on the removal of foreign/exogenous DNA while minimizing the fingernail endogenous DNA. In this study three different sampling methods (swabbing, PBS soak, and PrepFiler® lysis buffer soak) were compared in order to identify one that minimizes the amount of endogenous DNA removed and maximizes the amount of foreign/exogenous male DNA removed. The samples were processed using the Tecan HIDEVO150 robot in order to reduce analyst time and the DNA mixtures were interpreted using the probabilistic genotyping software STRmix™. For each sampling method the quantity of male DNA, the mixture proportions, the number of foreign/exogenous male alleles detected, the amount of DNA degradation, and the discrimination power via the likelihood ratio obtained for the foreign/exogenous male DNA donor were determined and compared. The PrepFiler® lysis buffer soak and swabbing sampling methods appear to be equally effective at removing foreign/exogenous DNA from fingernails; however, the lysis buffer soak sampling method extracts more female endogenous DNA from the fingernail and the female DNA is degraded. Marginally higher likelihood ratios were obtained for the swab samples versus the PrepFiler® lysis buffer soak samples; therefore, it was determined that the swabbing sampling method was the best sampling method for the recovery of foreign exogenous DNA from fingernails while minimizing the amount of endogenous DNA removed.

STRmix™ collaborative exercise on DNA mixture interpretation

An intra and inter-laboratory study using the probabilistic genotyping (PG) software STRmix™ is reported. Two complex mixtures from the PROVEDIt set, analysed on an Applied Biosystems™ 3500 Series Genetic Analyzer, were selected. 174 participants responded. For Sample 1 (low template, in the order of 200 rfu for major contributors) five participants described the comparison as inconclusive with respect to the POI or excluded him. Where LRs were assigned, the point estimates ranging from 2 × 10⁴ to 8 × 10⁶. For Sample 2 (in the order of 2000 rfu for major contributors), LRs ranged from 2 × 10²⁸ to 2 × 10²⁹. Where LRs were calculated, the differences between participants can be attributed to (from largest to smallest impact): This study demonstrates a high level of repeatability and reproducibility among the participants. For those results that differed from the mode, the differences in LR were almost always minor or conservative.

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.