Simulated approach to estimate the number and combination of known/unknown contributors in mixed DNA samples using 15 short tandem repeat loci

The calculation of likelihood ratios (LRs) for DNA mixture analysis is necessary to establish an appropriate hypothesis based on the estimated number of contributors and known contributor genotypes. In this paper, we recommend a relevant analytical method from the 15 short tandem repeat typing system (the Identifiler multiplex), which is used as a standard in Japanese forensic practice and incorporates a flowchart that facilitates hypothesis formulation. We postulate that: (1) all detected alleles need to be above the analytical threshold (e.g., 150 relative fluorescence unit (RFU)); (2) alleles of all known contributors should be detected in the mixture profile; (3) there should be no contribution from close relatives. Furthermore, we deduce that mixtures of four or more persons should not be interpreted by Identifiler as the LR values of 100,000 simulated cases have a lower expectation of exceeding our temporal LR threshold (10,000) which strongly supports the prosecution hypothesis. We validated the method using various computer-based simulations. The estimated number of contributors is most likely equal to the actual number if all alleles detected in the mixture can be assigned to those from the known contributors. By contrast, if an unknown contributor(s) needs to be designated, LRs should be calculated from both two-person and three-person contributions. We also consider some cases in which the unknown contributor(s) is genetically related to the known contributor(s).     

Estimating the Number of Contributors to Forensic DNA Mixtures: Does Maximum Likelihood Perform Better Than Maximum Allele Count?

Abstract: Determining the number of contributors to a forensic DNA mixture using maximum allele count is a common practice in many forensic laboratories. In this paper, we compare this method to a maximum likelihood estimator, previously proposed by Egeland et al., that we extend to the cases of multiallelic loci and population subdivision. We compared both methods’ efficiency for identifying mixtures of two to five individuals in the case of uncertainty about the population allele frequencies and partial profiles. The proportion of correctly resolved mixtures was >90% for both estimators for two‐ and three‐person mixtures, while likelihood maximization yielded success rates 2‐ to 15‐fold higher for four‐ and five‐person mixtures. Comparable results were obtained in the cases of uncertain allele frequencies and partial profiles. Our results support the use of the maximum likelihood estimator to report the number of contributors when dealing with complex DNA mixtures.     

Matching and partially-matching DNA profiles

The DNA profiles of two individuals can have 0, 1, or 2 pairs of alleles that are the same at each locus. These events may be called mismatches, partial matches or matches, respectively, and they have probabilities that depend on the population proportions of alleles as well as the population structure parameter theta. The observed and expected numbers of pairs of individuals with various numbers of matching or partially matching loci in FBI and Australian databases are found to be in good agreement provided theta is set equal to some small value greater than zero. The likelihood ratios for two individuals having a specified degree of relationship versus being unrelated also depend on the numbers of matching and partially matching loci, but even unrelated pairs of individuals can have likelihood ratios that support hypotheses of relatedness. Matching probabilities allow predictions to be made for the sizes of databases that are expected to contain a pair of individuals with high numbers of matching loci. It is very likely that two individuals with at least 9 matching loci among the 13 CODIS loci have already been typed.     

Chromosomal duplications along the Y-chromosome and their potential impact on Y-STR interpretation

Y-chromosome short tandem repeat (Y-STR) markers are being used as potential tools for distinguishing low levels of male DNA in the presence of excess female DNA as is present in many sexual assault samples. Usually single copy Y-STR loci produce a single amplicon in single source samples, and thus the observation of multiple peaks at such a locus could suggest to an analyst that a mixture of more than one male contributor is present in the tested sample. However, many regions of the Y-chromosome are duplicated or even triplicated in some individuals and this fact can thus complicate potential mixture interpretation. Reasons for the presence of duplications at multiple loci within a single sample are explored in the context of Y-STR marker location along the chromosome. True male-male mixtures commonly exhibit more than one locus-specific PCR product across multiple Y-STR loci that are not adjacent to one another on the Y-chromosome. In addition, duplicated loci typically possess alleles that differ by only a single repeat unit and possess similar peak heights.     

Interpreting simple STR mixtures using allele peak areas

Although existing statistical models can interpret mixtures qualitatively based upon the alleles present, the use of automated sequencers opens the opportunity to take account of quantitative aspects embodied by the peak area. One step in understanding simple mixtures consisting of just two donors is to estimate the mixture ratio. This is relatively easy to do when four-allele mixtures are evident at a given locus. However, if the mixture consists of three or fewer alleles, the process it is not straightforward. We demonstrate that mixture estimates are consistent across all loci in a multiplex system. Once the mixture ratio is known, then the expected peak areas for any given combination of alleles can be estimated using a simple spreadsheet analysis.     

TrueAllele® Genotype Identification on DNA Mixtures Containing up to Five Unknown Contributors

Computer methods have been developed for mathematically interpreting mixed and low‐template DNA. The genotype modeling approach computationally separates out the contributors to a mixture, with uncertainty represented through probability. Comparison of inferred genotypes calculates a likelihood ratio (LR), which measures identification information. This study statistically examined the genotype modeling performance of Cybergenetics TrueAllele^® computer system. High‐ and low‐template DNA mixtures of known randomized composition containing 2, 3, 4, and 5 contributors were tested. Sensitivity, specificity, and reproducibility were established through LR quantification in each of these eight groups. Covariance analysis found LR behavior to be relatively invariant to DNA amount or contributor number. Analysis of variance found that consistent solutions were produced, once a sufficient number of contributors were considered. This study demonstrates the reliability of TrueAllele interpretation on complex DNA mixtures of representative casework composition. The results can help predict an information outcome for a DNA mixture analysis.     

A mixed DNA profile controversy revisited

Semaan et al. (J Forensic Res, 2020, 11, 453) discuss a mock case “where eight different individuals [P₁ through P₈] could not be excluded in a mixed DNA analysis. Even though … expert DNA mixture analysis software was used.” Two of these are the true donors. The LRs reported are incorrect due to the incorrect entry of propositions into LRmix Studio. This forced the software to account for most of the alleles as drop-in, resulting in LRs 60–70 orders of magnitude larger than expected. P₁, P₂, P₄, P₅, and P₈ can be manually excluded using peak heights. This has relevance when using LRmix which does not use peak heights. We extend the work using the same two reference genotypes who were the true contributors as Semaan et al. (J Forensic Res, 2020, 11, 453). We simulate three two-donor mixtures with peak heights using these two genotypes and analyze using STRmix?. For the simulated 1:1 mixture, one of the non-donors’ LRs supported him being a contributor when no conditioning was used. When considered in combination with any other potential donors (i.e., with conditioning), this non-donor was correctly eliminated. For the 3:1 mixture, all results correctly supported that the non-donors were not contributors. The low-template 4:1 mixture LRs with no conditioning showed support for all eight profiles as donors. However, the results from pair-wise conditioning showed that only the two ground truth donors had LRs supporting that they were contributors to the mixture. We recommend the use of peak heights and conditioning profiles, as this allows better sensitivity and specificity even when the persons share many alleles.     

Validating TrueAllele® Interpretation of DNA Mixtures Containing up to Ten Unknown Contributors

Most DNA evidence is a mixture of two or more people. Cybergenetics TrueAllele^® system uses Bayesian computing to separate genotypes from mixture data and compare genotypes to calculate likelihood ratio (LR) match statistics. This validation study examined the reliability of TrueAllele computing on laboratory-generated DNA mixtures containing up to ten unknown contributors. Using log(LR) match information, the study measured sensitivity, specificity, and reproducibility. These reliability metrics were assessed under different conditions, including varying the number of assumed contributors, statistical sampling duration, and setting known genotypes. The main determiner of match information and variability was how much DNA a person contributed to a mixture. Observed contributor number based on data peaks gave better results than the number known from experimental design. The study found that TrueAllele is a reliable method for analyzing DNA mixtures containing up to ten unknown contributors.     

Results of the 2018 Rapid DNA Maturity Assessment

Three commercially available integrated rapid DNA instruments were tested as a part of a rapid DNA maturity assessment in July of 2018. The assessment was conducted with sets of blinded single-source reference samples provided to participants for testing on the individual rapid platforms within their laboratories. The data were returned to the National Institute of Standards and Technology (NIST) for review and analysis. Both FBI-defined automated review (Rapid DNA Analysis) and manual review (Modified Rapid DNA Analysis) of the datasets were conducted to assess the success of genotyping the 20 Combined DNA Index System (CODIS) core STR loci and full profiles generated by the instruments. Genotype results from the multiple platforms, participating laboratories, and STR typing chemistries were combined into a single analysis. The Rapid DNA Analysis resulted in a success rate of 80% for full profiles (85% for the 20 CODIS core loci) with automated analysis. Modified Rapid DNA Analysis resulted in a success rate of 90% for both the CODIS 20 core loci and full profiles (all attempted loci per chemistry). An analysis of the peak height ratios demonstrated that 95% of all heterozygous alleles were above 59% heterozygote balance. For base-pair sizing precision, the precision was below the standard 0.5 bp deviation for both the ANDE 6C System and the RapidHIT 200.     

Two or three contributors of DNA mixtures? – Some practical considerations

The number of contributors is hard to determine in DNA mixture profiles. Here, we deal with the special but frequent case that either two or three contributors are possible. In fact, it might happen that two contributors can explain the number of alleles seen but that three contributors are necessary if a specific person of interest is to be included in the mixture. Then the likelihood ratio assuming two contributors will be zero while the likelihood ratio for three contributors may be large. We evaluate this situation and offer suggestions on how to arrive at an overall likelihood ratio. To exemplify our line of reasoning we use an example proposed by Biedermann, Taroni and Thompson.     

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.     

Multiplexing of Y chromosome specific STRs and performance for mixed samples

A combination of four Y-specific polymorphic STR loci was amplified simultaneously using fluorescently labeled primers. Multiplex conditions required optimization to eliminate constant bands and amplification products for female DNA. A series of experiments was carried out for mixtures of DNA from two males, and from male and female individuals for the Y-specific STRs and an autosomal locus. For the male/male mixtures amplified with the Y specific system, and amplified for an autosomal locus, the minor component in the mixture could only be identified up to a ratio of 1:10, 1:50 respectively. In male/female DNA mixtures the Y STR alleles could be identified for the highest ratio tested, 400 pg male in DNA in 800 ng female DNA which amounts to a ratio of 1:2000.     

A multipurpose panel of microhaplotypes for casework

Microhaplotypes (MHs) are SNP-based multiallelic loci that have several advantages over individual SNPs and short tandem repeats (STRs). For several years we have been searching for better MHs based on the effective number of alleles at a locus (A_e) and the locus informativeness for population relationships (I_n) with thoughts of incorporating MHs into casework. We genotyped a multiplex of our best 90 MHs on 79 populations. We have ranked the 90 by A_e and analyzed the top 24 to evaluate their potential value in forensic casework. We chose 24 to compare with the popSTR dataset of 20 CODIS markers plus four other STRs commonly typed. PopSTR has full data on 32 populations; our 24 MHs have full data on 79 pops. We have compared the two sets of 24 loci (MH and STR) in four areas: individualization, biogeographic ancestry, kinship analysis, and mixture resolution.     

Validating TrueAllele® DNA mixture interpretation

Abstract: DNA mixtures with two or more contributors are a prevalent form of biological evidence. Mixture interpretation is complicated by the possibility of different genotype combinations that can explain the short tandem repeat (STR) data. Current human review simplifies this interpretation by applying thresholds to qualitatively treat STR data peaks as all‐or‐none events and assigning allele pairs equal likelihood. Computer review, however, can work instead with all the quantitative data to preserve more identification information. The present study examined the extent to which quantitative computer interpretation could elicit more identification information than human review from the same adjudicated two‐person mixture data. The base 10 logarithm of a DNA match statistic is a standard information measure that permits such a comparison. On eight mixtures having two unknown contributors, we found that quantitative computer interpretation gave an average information increase of 6.24 log units (min = 2.32, max = 10.49) over qualitative human review. On eight other mixtures with a known victim reference and one unknown contributor, quantitative interpretation averaged a 4.67 log factor increase (min = 1.00, max = 11.31) over qualitative review. This study provides a general treatment of DNA interpretation methods (including mixtures) that encompasses both quantitative and qualitative review. Validation methods are introduced that can assess the efficacy and reproducibility of any DNA interpretation method. An in‐depth case example highlights 10 reasons (at 10 different loci) why quantitative probability modeling preserves more identification information than qualitative threshold methods. The results validate TrueAllele^® DNA mixture interpretation and establish a significant information improvement over human review.     

Developmental validation of reduced-size STR Miniplex primer sets

This paper describes a developmental validation study of three Miniplex sets covering 12 of the 13 CODIS loci. As these new sets will be used for the analysis of degraded and low level DNA, the validation studies were performed using 100-125 pg of DNA, the lowest input level at which peak balance, peak intensity, and allele consistency were stable. To demonstrate the applicability of the Miniplex sets to forensic casework, these validation studies were completed in accordance with the Scientific Working Group on DNA Analysis Methods (SWGDAM). A range of tests were performed including studies of concordance with standard multiplex kits, sensitivity and reproducibility, and PCR amplification conditions. Additionally, studies of mixtures, nonhuman and environmentally degraded DNA, and simulated forensic samples were performed. Our results demonstrate that Miniplex STR amplification procedures are a robust and sensitive tool for the analysis of degraded DNA.     

Identification and characterization of variant alleles at CODIS STR loci

Short tandem repeat (STR) profiles from 32,671 individuals generated by the ABI Profiler Plus and Cofiler systems were screened for variant alleles not represented within manufacturer-provided allelic ladders. A total of 85 distinct variants were identified at 12 of the 13 CODIS loci, most of which involve a truncated tetranucleotide repeat unit. Twelve novel alleles, identified at D3S1358, FGA, D18S51, D5S818, D7S820 and TPOX, were confirmed by nucleotide sequence analysis and include both insertions and deletions involving the repeat units themselves as well as DNA flanking the repeat regions. Population genetic data were collected for all variants and frequencies range from 0.0003 (many single observations) to 0.0042 (D7S820 '10.3' in North American Hispanics). In total, the variant alleles identified in this study are carried by 1.6% of the estimated 1 million individuals tested annually in the U.S. for the purposes of parentage resolution. A paternity case involving a recombination event of paternal origin is presented and demonstrates how variant alleles can significantly strengthen the genetic evidence in troublesome cases. In such instances, increased costs and turnaround time associated with additional testing may be eliminated.     

Complex mixtures: A critical examination of a paper by Homer et al.

DNA evidence in criminal cases may be challenging to interpret if several individuals have contributed to a DNA-mixture. The genetic markers conventionally used for forensic applications may be insufficient to resolve cases where there is a small fraction of DNA (say less than 10%) from some contributors or where there are several (say more than 4) contributors. Recently methods have been proposed that claim to substantially improve on existing approaches [1]. The basic idea is to use high-density single nucleotide polymorphism (SNP) genotyping arrays including as many as 500,000 markers or more and explicitly exploit raw allele intensity measures. It is claimed that trace fractions of less than 0.1% can be reliably detected in mixtures with a large number of contributors. Specific forensic issues pertaining to the amount and quality of DNA are not discussed in the paper and will not be addressed here. Rather our paper critically examines the statistical methods and the validity of the conclusions drawn in Homer et al. (2008) [1].We provide a mathematical argument showing that the suggested statistical approach will give misleading results for important cases. For instance, for a two person mixture an individual contributing less than 33% is expected to be declared a non-contributor. The quoted threshold 33% applies when all relative allele frequencies are 0.5. Simulations confirmed the mathematical findings and also provide results for more complex cases. We specified several scenarios for the number of contributors, the mixing proportions and allele frequencies and simulated as many as 500,000 SNPs.A controlled, blinded experiment was performed using the Illumina GoldenGate^® 360 SNP test panel. Twenty-five mixtures were created from 2 to 5 contributors with proportions ranging from 0.01 to 0.99. The findings were consistent with the mathematical result and the simulations.We conclude that it is not possible to reliably infer the presence of minor contributors to mixtures following the approach suggested in Homer et al. (2008) [1]. The basic problem is that the method fails to account for mixing proportions.     

Developmental Validation of the ANDE 6C System for Rapid DNA Analysis of Forensic Casework and DVI Samples

A developmental validation was performed to demonstrate reliability, reproducibility, and robustness of the ANDE Rapid DNA Identification System for processing of crime scene and disaster victim identification (DVI) samples. A total of 1705 samples were evaluated, including blood, oral epithelial samples from drinking containers, samples on FTA and untreated paper, semen, bone, and soft tissues. This study was conducted to address the FBI’s Quality Assurance Standards on developmental validation and to accumulate data from a sufficient number of unique donors and sample types to meet NDIS submission requirements for acceptance of the ANDE Expert System for casework use. To date, no Expert System has been approved for such samples, but the results of this study demonstrated that the automated Expert System performs similarly to conventional laboratory data analysis. Furthermore, Rapid DNA analysis demonstrated accuracy, precision, resolution, concordance, and reproducibility that were comparable to conventional processing along with appropriate species specificity, limit of detection, performance in the presence of inhibitors. No lane-to-lane or run-to-run contamination was observed, and the system correctly identified the presence of mixtures. Taken together, the ANDE instrument, I-Chip consumable, FlexPlex chemistry (a 27-locus STR assay compatible with all widely used global loci, including the CODIS core 20 loci), and automated Expert System successfully processed and interpreted more than 1200 unique samples with over 99.99% concordant CODIS alleles. This extensive developmental validation data provides support for broad use of the system by agencies and accredited forensic laboratories in single-source suspect-evidence comparisons, local database searches, and DVI.     

二组分混合DNA样品STR图谱解释

对混合样品STR图谱的结果进行解释。实验模拟二组分DNA混合样品 ,复合扩增荧光检测 10个基因座 ,比较混合样品谱带 ,计算等位基因峰面积比。结果发现 :二组分DNA混合样品的等位基因数增加 ,样品的混合比例不同就出现峰面积的不平衡。在等位基因峰面积比值与样品组分混合比例接近时 ,可由峰面积比值推断混合样品的混合比例。在混合比例为 1∶2 0时 ,基本上检测不到来自少量混合成分的等位基因 ,表现为单一组分图谱 ;在混合比例为 1∶10时 ,含量低的组分的等位基因峰面积接近与主要组分的“Stutter”峰面积 ,与来自主要组分的等位基因峰面积差异很明显。能检出混合样品中少量成分等位基因的最高混合比例为 1∶10