Analysis Of DNA Mixtures Research Articles

Casework applications of probabilistic genotyping methods for DNA mixtures that allow relationships between contributors

In both criminal cases and civil cases there is an increasing demand for the analysis of DNA mixtures involving relationships. The goal might be, for example, to identify the contributors to a DNA mixture where the unknown donors may be related, or to infer the relationship between individuals based on a DNA mixture. This paper applies a new approach to modelling and computation for DNA mixtures involving contributors with arbitrarily complex relationships to two real cases from the Spanish Forensic Police.

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.

Identification and sequencing of 59 highly polymorphic microhaplotypes for analysis of DNA mixtures.

Mixture detection remains one of the major challenges within a forensic science context. In recent years, microhaplotypes were proposed to have great potential in mixture detection, although many of them are not as polymorphic as widely used short tandem repeat (STR) markers. In this study, 59 new highly polymorphic microhaplotypes were identified and sequenced with the NextSeq 500 Sequencer. Based on the whole 1000 Genomes Project dataset, the average effective number of alleles (Ae) of the 59 microhaplotypes was 5.44, and the Ae values of 36 of these microhaplotypes were > 5.00. Their genetic variations in 187 Han Chinese individuals were evaluated. The average allele coverage ratio (ACR) of heterozygotes across all loci was 0.96 ± 0.05. The number of observed alleles varied from 4 to 23, with an average of 8.8 alleles per microhaplotype locus. The average observed heterozygosity (Ho) of 59 loci was 0.77 ± 0.05, and the Ho values of 15 of these loci were > 0.80. All loci showed high polymorphisms with a discrimination power (DP) ranging from 0.80 to 0.97, and the average DP was 0.92 ± 0.03. The analysis of simulated mixtures demonstrated that the microhaplotypes reported here were highly polymorphic and performed well in forensic DNA mixture analysis. This study not only demonstrated the applicability of microhaplotypes in mixture analysis but also provided new choices for highly polymorphic microhaplotypes because after adding the markers identified here, the number of microhaplotypes with Ae values of > 4.00 will increase from ~ 50 to ~ 110.

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

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

A sequence-based 74plex microhaplotype assay for analysis of forensic DNA mixtures

Microhaplotypes are emerging biomarkers for forensic applications. In this study, a sequence-based multiplex assay of 74 microhaplotypes (230 SNPs) was developed on the Ion Torrent S5™ (Thermo Fisher Scientific) system and the potential for its application to mixture deconvolution was explored. The 74 loci are distributed across the autosomal human genome and have Ae (i.e., effective number of alleles) values ranging from 1.307 to 6.010 (median = 2.706) and In (i.e., informativeness) values ranging from 0.096 to 0.660 (median = 0.251); the amplicon sizes range between 157 and 325 bp. The typing performance of the panel was evaluated on a series of in-silico two to five-person DNA mixtures and results were compared to fragment and sequence-based STRs. The 74plex-locus assay was found sensitive down to 0.05 ng of input DNA and effective for the analysis of mixtures at different contributor ratios and input DNA amounts. As expected, none or very partial minor CE-STR profile(s) were reported for highly imbalanced two-person and high-order DNA mixtures while sequencing of STRs enabled the detection of more individual minor alleles. For microhaplotypes, a full minor profile was detected down to a 20:1 ratio at 10 ng and minimal allele dropout at 1 ng of input DNA. A higher rate of allele dropout from the minor donor(s) was reported at 1 ng than 10 ng for three-person mixtures while for four- and five-person mixtures, the same number of dropouts was observed for almost all minor donors. Overall this microhaplotype panel is a powerful tool that can complement and enhance size- and sequence-based STR analysis of forensic DNA mixtures.

Study for the DNA Profiling of Mixed Samples of Multiple Contributors and Suggested Procedures to Overcome Mixture Troubleshooting in Forensic Investigation

In modern forensic genetics, the analysis of DNA mixtures is a challenge because of the obstacles found in defining the number of contributors, especially when they exceed two. The goal of the present study was to find the most reliable method of detection for profiling the two-male and female-male mixtures obtained. Bloodstains, saliva, and body tissues from various crime scenes were obtained as samples. All samples for DNA profiling have been subjected to DNA extraction, amplification, separation, and detection. Results revealed that DNA profiling showed two-male and female-male mixtures. Results also showed the presence of a major and a minor male contributor in each genetic locus according to peak heights. Differential extraction provided a reliable method for separating female and male contributors from each other in the case of the female-male mixture. The profiling of the male donor in the female-male mixture was furtherly verified using the Y-STR profiling process. Eventually, we can infer that a good approach to identifying the two-male mixture is autosomal STR interpretation centered on major and minor differentiation. In addition, differential separation and Y-STR profiling proved to be the best processes for profiling mixed samples comprising female-male contributors as only the male profile was identified.

Construction of SNP-STR Multiplex Amplification System with Genetic Markers and Its Forensic Application.

Objective To select and develop a SNP-STR multiplex amplification system with genetic markers compatible with current STR databases. To understand its genetic polymorphisms in Sichuan Han population and its application value in DNA mixture analysis. Methods Based on the STR genetic markers in commercial kits, SNPs adjacent to these STR markers were selected to be SNP-STR genetic markers. A SNP-STR multiplex amplification system with genetic markers based on allele-specific amplification was constructed using allele-specific amplification primers. The genetic polymorphism of the system in the Sichuan Han population was investigated and the efficiency of systems with different numbers of loci to detect the two individual DNA mixture samples was evaluated. Results An allele-specific multiplex amplification system constituted of 13 SNP-STR genetic markers was selected and constructed. In Sichuan Han population, the heterozygosity of each locus ranged from 0.76 to 0.88, and the combined discrimination power reached 0.999 999 999 999 999 968. In the analysis of the two individual DNA mixture samples： for single-locus amplification, the genotype of the minor components can still be detected when the mixture ratio reaches 1 000∶1; for multiple loci multiplex amplification, the maximum mixture ratio can reach 500∶1. As the number of loci in the system increased, the detection efficiency of the minor components in the DNA mixture decreased. Conclusion SNP-STR genetic markers have a higher polymorphism than STR. The multiplex amplification system made of SNP-STR genetic markers has a better analysis efficiency for mixed samples than traditional STR multiplex amplification system.

Analysis of complex DNA mixtures using massively parallel sequencing of SNPs with low minor allele frequencies

DNA mixtures from 3 or more contributors have proven difficult to analyze using the current state-of-the-art method of short-tandem repeat (STR) amplification followed by capillary electrophoresis (CE). Here we analyze samples from both laboratory-defined mixtures and complex multi-contributor touch samples using a single nucleotide polymorphism (SNP) panel comprised of 2311 low-minor-allele-frequency loci, combined with massively parallel sequencing (MPS). This approach demonstrates that as many as 10 people can be identified in touch samples using a threshold of -Log P(RMNE) of 6, and a detection rate of 18–94 % across 10 different materials using a threshold of -Log P(RMNE) of 2. Thirty-two false positives were observed in 100 touch samples.

AI, Machine Learning, and International Criminal Investigations: The Lessons From Forensic Science

The evolving field of machine learning and artificial intelligence is frequently presented as a positively disruptive branch of data science whose expansion allows for improvements in the speed, efficiency, and reliability of decision-making, and whose potential is impacting across diverse zones of human activity. A particular focus for development is within the criminal justice sector, and more particularly the field of international criminal justice, where AI is presented as a means to filter evidence from digital media, to perform visual analyses of satellite data, or to conduct textual analyses of judicial reporting datasets. Nonetheless, for all of its myriad potentials, the deployment of forensic machine learning and AI may also generate seemingly insoluble challenges. The critical discourse attendant upon the expansion of automated decision-making, and its social and legal consequences, resolves around two interpenetrating issues; specifically, algorithmic bias, and algorithmic opacity, the latter phenomena being the focus of this study. It is posited that the seemingly intractable evidential challenges associated with the introduction of opaque computational machine learning algorithms, though global in nature, are neither novel nor unfamiliar. Indeed, throughout the past decade and across a multitude of jurisdictions, criminal justice systems have been required to respond to the implementation of opaque forensic algorithms, particularly in relation to complex DNA mixture analysis. Therefore, with the objective of highlighting the potential avenues of challenge which may follow from the introduction of forensic AI, this study focusses on the prior experience of litigating, and regulating, probabilistic genotyping algorithms within the forensic science and criminal justice fields. Crucially, the study proposes that machine learning opacity constitutes an enhanced form of algorithmic opacity. Therefore, the challenges to rational fact-finding generated through the use of probabilistic genotyping software may be encountered anew, and exacerbated, through the introduction of forensic AI. In anticipating these challenges, the paper explores the distinct categories of opacity, and suggests collaborative solutions which may empower contemporary legal academics – and both legal and forensic practitioners - to set more rigorous and usable standards. The paper concludes by considering the ways in which academics, forensic scientists, and legal practitioners, particularly those working in the field of international criminal justice, might re-conceptualize these opaque technologies, opening a new field of critique and analysis. Using findings from case analyses, overarching regulatory guidance, and data drawn from empirical research interviews, this article addresses the validity, transparency, and interpretability problems, leading to a comprehensive assessment of the current challenges facing the introduction of forensic AI. It builds upon work undertaken at the Nuffield Council on Bioethics Horizon Scanning Workshop: The future of science in crime and security (5th July 2019, London).

TranslucentID: analysis of complex DNA SNP mixtures with large numbers of donors

ABSTRACT Mixture analysis of complex forensic DNA mixtures can identify multiple individuals who cannot be excluded using massively parallel sequencing (MPS) with single-nucleotide polymorphism (SNP) panels. For a defined MPS SNP panel, large numbers of donors will result in higher fractions of the loci in the panel having a called minor allele; for these mixtures, proportional donor concentrations can be leveraged to infer major SNP alleles for higher concentration donors at positions with call minor alleles from lower concentration donors. For these mixtures, we propose creating paired derived mixtures using an increased minor allele calling analytical threshold for mixture analysis. We introduce TranslucentID as an investigative tool for extended mixture analysis of mixtures with large numbers of donors. TranslucentID produced 46 new true-positive identifications in 58% of the 26 of the complex mixtures evaluated plus eight true positives plus 11 familial results in a 20-person mixture with known relative profiles available.

Soil DNA: advances in DNA technology offer a powerful new tool for forensic science

Abstract Unsolved crimes add significant financial, legal and social costs to the community. Therefore, there is an urgent need to develop robust solutions to deal with this growing issue. Soil forensic analysis is an emerging cross-disciplinary science that can deliver powerful physical evidence with significant benefits to criminal, counter-terrorism and environmental crime investigations. Technologies currently used, which are largely dependent on the examination of inorganic soil components, are unable to successfully resolve approximately 20% of soil comparisons in cases due to a deficiency in spatial resolution. The organic component of soil includes a vast number of living organisms, and the combination of these organisms can provide a biological signature to assist with soil comparisons. Recent developments in DNA sequencing technology enable characterization, and comparison, of these complex soil communities, providing additional discriminatory information that could potentially assist in cases that cannot currently be resolved. DNA analysis is routinely applied in forensic science to answer human- and non-human-related questions. This paper provides a broad overview of forensic DNA analysis, and describes the differences between DNA analysis of single specimen and complex soil DNA mixtures. We also highlight key areas of future research required for this technique to be fully utilized in casework.

Preliminary exploration of a novel method for the deconvolution of DNA mixtures by pyrosequencing

The deconvolution of DNA mixtures has been a thorny issue. Several kinds of genetic markers, such as STR, SNP, SNP/DIP-STR and microhaplotypes etc., as well as capillary electrophoresis, NGS and other technical platforms are used to solve this problem. In this study, we propose a novel method for the analysis of DNA mixtures. This method employed multiplex pyrosequencing to sequence several selected microhaplotypes. Employing a sparse representation-based AdvISER-MH-PYRO algorithm, the original pyrosequencing (PSQ) signals of the DNA mixtures were deciphered to determine the contributors of the mixtures. Our preliminary data show that this method can resolve the number of contributors to a DNA mixture composed of 2–4 individuals.

RelMix: An open source software for DNA mixtures with related contributors

In both criminal cases and relationship inference there is an increasing demand for analysis of DNA mixtures where relatives are involved. The goal might be to identify the contributors to a mixture where the donors may or may not be related, or to determine the relationship between individuals based on a mixture. relMix is an open source software for analysing DNA mixtures involving relatives, available as a graphical user interface in R. We explain the model behind relMix and give an overview of the new features (including improved checking of input) in the latest version.

Completion of the MIX 13 case study by evaluation of mock mixtures with the probabilistic genotyping software GenoProof® Mixture 3

Only recently, at the end of 2018, the results of the MIX 13 interlaboratory study, initiated by NIST in 2013, were published. Aiming to evaluate current available methods for DNA mixture analysis in the US and Canada, the complex DNA mixtures were reviewed from new perspectives, taking probabilistic genotyping methods into account. The presented scenarios were analysed with the software GenoProof® Mixture 3. For this purpose, the readily accessible sample data was used. The focus of the analysis was the evaluation of the results based on given references. With the fully continuous approach of GenoProof® Mixture 3 it was possible to include or exclude the suspects of the cases correctly.

Y chromosome sequence variation of common forensic STR markers and their flanking regions among Polish population

Y-chromosome STR markers’ analysis is widely used as a procedure with examination of sexual assault cases, kinship cases and identification of human remains. At present massively parallel sequencing (MPS) technology proves to be reliable method in analysis of DNA mixtures or low quality of DNA samples. In cases of frequent Y-STR haplotypes, sequence analysis of an allele and flanking region also gives a chance to distinguish microhaplotypes of the samples. In this study authors investigated DNA sequence variability within the Y-STR markers in polish population (reference samples and bone samples). MPS was carried on with Illumina’s ForenSeq kit on the MiSeq FGx instrument. Revealed microhaplotypes and their frequency differ between markers. Some of the analyzed sequences showed no variability in the analyzed set of samples. Confronting the population data with the case samples showed that this type of information can significantly improve kinship calculation and mixture analysis.

Five-year evaluation of forensic body fluid identification and DNA mixture analysis from the accredited GHEP-ISFG proficiency test

With 27 years experience as an external quality assurance control, the proficiency program coordinated by the Madrid Department of the INTCF and organized by the Spanish and Portuguese Speaking Working Group of the ISFG (GHEP-ISFG) offers its Basic level as a suitable accredited proficiency test since 2014.In this work we present the evaluation of results submitted by more than 70 laboratories, regarding one of the items (M4) provided in each edition over the past five years. The parameters evaluated were autosomal and Y- STRs together with body fluid identification Evaluation was performed against assigned values established by means of known values.It is observed that although good performance has increased over the years, main causes of discrepancies are recurrent each year.

A microhaplotypes panel for massively parallel sequencing analysis of DNA mixtures

Massively parallel sequencing (MPS) technology enables the simultaneous analysis of different kinds of forensic genetic markers as well as the detection of the alleles with minor contributions in a highly unbalanced DNA mixture. In our previous study, we presented a novel set of microhaplotype loci and evaluated their application value in analyzing the DNA mixtures. However, several issues remain unclear, for example (i) whether the major or the minor donor in an unbalanced DNA mixture can be compared with a known suspect, (ii) whether the proportion of each contributor in a DNA mixture can be inferred, (iii) whether the captured alleles can be assigned to the major or the minor donor. To further address these issues, during the present study, we increased the number of loci in a single multiplex system to 25 (all the microhaplotypes have a length less than 50 bp). The DNA samples of 60 unrelated Han Chinese individuals, 40 artificially made DNA mixtures with different mixing proportions were analyzed with MPS by using the microhaplotypes panel. By comparing the population genetic data of the 25 microhaplotypes in 26 populations from 1000 Genome Project (1000 G), the microhaplotypes were found to have similar high Ae values in different populations. The likelihood ratios were further employed to compare the mixtures and known suspects. The major contributor could be well identified in both balanced and unbalanced samples. The minor contributor could also be identified if capturing enough loci. When we divided the microhaplotypes into different subgroups, significant correlation was found between the allele depth ratio and the gradual mixing ratios. The allele depth patterns in balanced, mildly imbalanced and severely imbalanced mixtures were clarified, and we found that certain loci could be discriminated from the contributors and they could be used for direct individual identification.

Fast P(RMNE): Fast forensic DNA probability of random man not excluded calculation

High throughput sequencing (HTS) of DNA forensic samples is expanding from the sizing of short tandem repeats (STRs) to massively parallel sequencing (MPS). HTS panels are expanding from the FBI 20 core Combined DNA Index System (CODIS) loci to include SNPs. The calculation of random man not excluded, P(RMNE), is used in DNA mixture analysis to estimate the probability that a person is present in a DNA mixture. This calculation encounters calculation artifacts with expansion to larger panel sizes. Increasing the floating-point precision of the calculations allows for increased panel sizes but with a corresponding increase in computation time. The Taylor series higher precision libraries used fail on some input data sets leading to algorithm unreliability. Herein, a new formula is introduced for calculating P(RMNE) that scales to larger SNP panel sizes while being computationally efficient (patent pending).

A novel multiplex assay of SNP-STR markers for forensic purpose.

Like DIP-STR markers (deletion/insertion polymorphism-short tandem repeat combinations), SNP-STR markers (single nucleotide polymorphism-STR combinations) are also valuable in forensic DNA mixture analysis. In this study, eight SNP-STRs were selected, and a stable and sensitive multiplex polymerase chain reaction (PCR) assay was developed for amplifying these SNP-STRs and the Amelogenin gender marker according to the principle of amplification refractory mutation system (ARMS). This novel multiplex set allows detection of the minor DNA contributor in a DNA mixture of any gender and cellular origin with high resolution (beyond a DNA ratio of 1:20). In addition, SNP-STR haplotype frequencies were estimated based on a survey of 350 unrelated individuals from Chinese Han population, and the combined power of discrimination (PD) and power of exclusion (PE) of the eight SNP-STRs were calculated as 0.99999999965 and 0.9996, which were obviously higher than that of the eight STR loci: 0.9999999954 and 0.9989 respectively. The results indicated that the SNP-STR compound markers have higher application value in forensic identification compared to standard autosomal STRs, especially in the analysis of imbalanced DNA mixtures.

Separation/extraction, detection, and interpretation of DNA mixtures in forensic science (review).

Interpreting mixed DNA samples containing material from multiple contributors has long been considered a major challenge in forensic casework, especially when encountering low-template DNA (LT-DNA) or high-order mixtures that may involve missing alleles (dropout) and unrelated alleles (drop-in), among others. In the last decades, extraordinary progress has been made in the analysis of mixed DNA samples, which has led to increasing attention to this research field. The advent of new methods for the separation and extraction of DNA from mixtures, novel or jointly applied genetic markers for detection and reliable interpretation approaches for estimating the weight of evidence, as well as the powerful massively parallel sequencing (MPS) technology, has greatly extended the range of mixed samples that can be correctly analyzed. Here, we summarized the investigative approaches and progress in the field of forensic DNA mixture analysis, hoping to provide some assistance to forensic practitioners and to promote further development involving this issue.