Correcting forensic DNA errors

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

Forensic identification of an individual in complex DNA mixtures

The identification of a suspect in a complex DNA mixture typed with standard short tandem repeat (STR) kits has proved difficult. In the current study we present the theoretical framework of a method aimed to resolve this problem in forensic cases. The method suggests genotyping a specially designed panel of 1000–3000 single nucleotide polymorphisms (SNPs), each with a relatively low (<0.1) minor allele frequency (MAF). The rationale of this method is that any individual will carry a specific set of dozens of rare alleles and the complex DNA mixture will carry this particular set only if the one individual is represented in the DNA mixture. The efficiency of the method is evaluated by estimating the probability that a random man will not be excluded (RMNE) from the mixture. When this probability, P(RMNE), is low, one can conclude that the suspect's DNA is present in the DNA mixture. Essentially, a P(RMNE) < 10⁻⁹ is considered as proof, whereas a P(RMNE) < 10⁻⁶ is considered strong evidence. For completeness, we also analyzed the method using the likelihood ratio (LR) approach. We have analyzed the method for a variety of conditions and found that generally the method will provide highly significant results even for complex mixtures combining up to 10 individuals. The method performs well even when close relatives (one or two brothers) are present in the complex DNA mixture and when contributors or suspects come from different populations. We have also found that the method can accurately identify the number of contributors to the mixture, something that in some instances has significant forensic value on its own.     

Development and validation of InnoQuant™, a sensitive human DNA quantitation and degradation assessment method for forensic samples using high copy number mobile elements Alu and SVA

There is a constant need in forensic casework laboratories for an improved way to increase the first-pass success rate of forensic samples. The recent advances in mini STR analysis, SNP, and Alu marker systems have now made it possible to analyze highly compromised samples, yet few tools are available that can simultaneously provide an assessment of quantity, inhibition, and degradation in a sample prior to genotyping. Currently there are several different approaches used for fluorescence-based quantification assays which provide a measure of quantity and inhibition. However, a system which can also assess the extent of degradation in a forensic sample will be a useful tool for DNA analysts. Possessing this information prior to genotyping will allow an analyst to more informatively make downstream decisions for the successful typing of a forensic sample without unnecessarily consuming DNA extract. Real-time PCR provides a reliable method for determining the amount and quality of amplifiable DNA in a biological sample.Alu are Short Interspersed Elements (SINE), approximately 300 bp insertions which are distributed throughout the human genome in large copy number. The use of an internal primer to amplify a segment of an Alu element allows for human specificity as well as high sensitivity when compared to a single copy target. The advantage of an Alu system is the presence of a large number (>1000) of fixed insertions in every human genome, which minimizes the individual specific variation possible when using a multi-copy target quantification system. This study utilizes two independent retrotransposon genomic targets to obtain quantification of an 80 bp “short” DNA fragment and a 207 bp “long” DNA fragment in a degraded DNA sample in the multiplex system InnoQuant™. The ratio of the two quantitation values provides a “Degradation Index”, or a qualitative measure of a sample's extent of degradation. The Degradation Index was found to be predictive of the observed loss of STR markers and alleles as degradation increases. Use of a synthetic target as an internal positive control (IPC) provides an additional assessment for the presence of PCR inhibitors in the test sample.In conclusion, a DNA based qualitative/quantitative/inhibition assessment system that accurately predicts the status of a biological sample, will be a valuable tool for deciding which DNA test kit to utilize and how much target DNA to use, when processing compromised forensic samples for DNA testing.     

Fast and accurate kinship estimation using sparse SNPs in relatively large database searches

Forensic genetic genealogy (FGG) has primarily relied upon dense single nucleotide polymorphism (SNP) profiles from forensic samples or unidentified human remains queried against online genealogy database(s) of known profiles generated with SNP microarrays or from whole genome sequencing (WGS). In these queries, SNPs are compared to database samples by locating contiguous stretches of shared SNP alleles that allow for detection of genomic segments that are identical by descent (IBD) among biological relatives (kinship). This segment-based approach, while robust for detecting distant relationships, generally requires DNA quantity and/or quality that are sometimes not available in forensic casework samples. By focusing on SNPs with maximal discriminatory power and using an algorithm designed for a sparser SNP set than those from microarray typing, performance similar to segment matching was reached even in difficult casework samples. This algorithm locates shared segments using kinship coefficients in “windows” across the genome. The windowed kinship algorithm is a modification of the PC-AiR and PC-Relate tools for genetic relatedness inference, referred to here as the “whole genome kinship” approach, that control for the presence of unknown or unspecified population substructure. Simulated and empirical data in this study, using DNA profiles comprised of 10,230 SNPs (10K multiplex) targeted by the ForenSeq™ Kintelligence Kit demonstrate that the windowed kinship approach performs comparably to segment matching for identifying first, second and third degree relationships, reasonably well for fourth degree relationships, and with fewer false kinship associations. Selection criteria for the 10K SNP PCR-based multiplex and functionality of the windowed kinship algorithm are described.     

Separation of SNP profiles from DNA mixtures with two contributors via massively parallel sequencing technology

ABSTRACT

Massively parallel sequencing technology offers the opportunity to analyse forensically challenging samples, such as degraded samples and mixtures. In the current study, we developed a perl-based pipeline to separate the DNA mixture into its components and to predict the most probable single nucleotide polymorphism (SNP) genotypes of each contributor to the mixed profile. We examined the usefulness of this method by detecting both artificially constructed DNA mixtures and mixtures from crime cases using the Precision ID Identity Panel on the Ion PGM platform. The separated genotypes of mixtures were validated by genotypes of each of the donors detected independently. The results indicate that the method performed well in identifications of both the artificially constructed mixtures and case-type mixtures, even when the two contributors are immediate relatives (mother and son), which demonstrated the practical usefulness of this method in forensic casework. Our research presents an efficient and different strategy for identification and paternity testing of DNA mixtures in forensic genetics.     

A mixture detection method based on separate amplification using primer specific alleles of INDELs-a study based on two person's DNA mixture

Samples containing unbalanced DNA mixtures from individuals often occur in forensic DNA examination and clinical detection. Because of the PCR amplification bias, the minor contributor DNA is often masked by the major contributor DNA when using traditional STR or SNP typing techniques. Here we propose a method based in allele-specific Insertion/Deletion (INDEL) genotyping to detect DNA mixtures in forensic samples. Fourteen INDELs were surveyed in the Chinese Han population of Shanxi Province. The INDELs were amplified using two separate primer-specific reactions by real-time PCR. The difference Ct value of the 2 reactions (D-value) were used for determination of the single source DNA. INDELs types and further confirmed by electrophoresis separation. The minor allele frequency (MAF) was above 0.2 in 10 INDELs. The detection limit was 0.3125 ng–1.25 ng template DNA for real-time PCR in all 14 INDEL markers. For single source 10 ng DNA, the average D-value was 0.31 ± 0.14 for LS type, 6.96 ± 1.05 for LL type and 7.20 ± 1.09 for SS type. For the series of simulated DNA mixture, the Ct value varied between the ranges of single source DNA, depending on their INDEL typing and mixture ratios. This method can detect the specific allele of the minor DNA contributor as little as 1:50 in rs397782455 and rs397696936; 1:100 in rs397832665, rs397822382 and rs397897230; the detection limit of the minor DNA contributor was as little as 1:500–1:1000 in the rest INDEL markers, a much higher sensitivity compared with traditional STR typing. The D-value variation depended on the alternation of dilution ratio and INDEL types. When the dilution was 1:1000, the maximum and minimum D-values were 8.84 ± 0.11 in rs397897230 and 4.27 ± 0.19 in rs397897239 for LL and SS type mixture, the maximum and minimum D-values were 9.32 ± 0.54 in rs397897230 and 4.38 ± 0.26 in rs 397897239 for LL(SS) and LS type mixture, separately. Any D-value between 0.86 and 5.11 in the 14 INDELs indicated the presence of mixture. The separate amplification strategy based on real-time PCR provides a promising and convenient method for detection of unbalanced DNA mixture for Chinese Han population.     

The efficacy of DNA mixture to mixture matching

Standard practice in forensic science is to compare a person of interest’s (POI) reference DNA profile with an evidence DNA profile and calculate a likelihood ratio that considers propositions including and excluding the POI as a DNA donor. A method has recently been published that provides the ability to compare two evidence profiles (of any number of contributors and of any level of resolution) comparing propositions that consider the profiles either have a common contributor, or do not have any common contributors. Using this method, forensic analysts can provide intelligence to law enforcement by linking crime scenes when no suspects may be available. The method could also be used as a quality assurance measure to identify potential sample to sample contamination. In this work we analyse a number of constructed mixtures, ranging from two to five contributors, and with known numbers of common contributors, in order to investigate the performance of using likelihood ratios for mixture to mixture comparisons. Our findings demonstrate the ability to identify common donors in DNA mixtures with the power of discrimination depending largely on the least informative mixture of the pair being considered. The ability to match mixtures to mixtures may provide intelligence information to investigators by identifying possible links between cases which otherwise may not have been considered connected.     

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. 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). 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). The basic problem is that the method fails to account for mixing proportions.     

Identification and characterization of novel DIP-STRs from whole-genome sequencing data

In an attempt to enhance forensic DNA mixture deconvolution several alternative DNA typing approaches have been developed. Among these, DIP-STR compound markers can resolve extremely unbalanced two-source DNA mixtures of same-or-opposite sex donors, up to a 1:1000 minor:major DNA ratio. A forensic set of 10 markers was validated for casework and a larger set of 23 DIP-STRs has proven suitable to biogeographic ancestry inference and for prenatal paternity testing. Yet, to promote the widespread use of this original approach, more markers and multiplex panels need to be developed.To this end, here we describe an extended set of forensic DIP-STRs identified using currently available whole-genome sequencing datasets. Complete lists of Indels and STRs were obtained from reported frequencies of genetic variants of 76,156 genomes. About 3000 identified DIP-STRs candidates were shorter than 200 bp and 500 showed high haplotype variability estimated using the genotypes of individuals homozygous for the DIP or the STR. Here, we present 23 additional DIP-STRs validated for sensitivity, specificity and Swiss population variability. Finally, a set of 30 markers comprising seven previously validated ones is proposed for the prospective development of a forensic DIP-STR multiplex panel.     

Evaluating 130 microhaplotypes across a global set of 83 populations

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

STRs vs. SNPs: thoughts on the future of forensic DNA testing

Largely due to technological progress coming from the Human Genome and International HapMap Projects, the issue has been raised in recent years within the forensic DNA typing community of the potential for single nucleotide polymorphism (SNP) markers as possible replacements of the currently used short tandem repeat (STR) loci. Our human identity testing project team at the U.S. National Institute of Standards and Technology (NIST) has explored numerous SNP and STR loci and assays as well as developing miniSTRs for degraded DNA samples. Based on their power of discrimination, use in deciphering mixture components, and ability to be combined in multiplex assays in order to recover information from low amounts of biological material, we believe that STRs rather than SNPs will fulfill the dominant role in human identity testing for the foreseeable future. However, SNPs may play a useful role in specialized applications such as mitochondrial DNA (mtDNA) testing, Y-SNPs as lineage markers, ancestry informative markers (AIMs), the prediction of phenotypic traits, and other potential niche forensic casework applications. Official disclaimer: Contribution of the U.S. National Institute of Standards and Technology. Not subject to copyright. Points of view in this document are those of the authors and do not necessarily represent the official position or policies of the U.S. Department of Justice. Certain commercial equipment, instruments and materials are identified in order to specify experimental procedures as completely as possible. In no case does such identification imply a recommendation or endorsement by the National Institute of Standards and Technology nor does it imply that any of the materials, instruments, or equipment identified are necessarily the best available for the purpose. This work was funded in part by the National Institute of Justice through interagency agreement 2003-IJ-R-029 with the NIST Office of Law Enforcement Standards.     

Effects of DNA degradation and genotype imputation on high-density SNP microarray in pairwise kinship analysis

High-density single nucleotide polymorphisms (SNPs) can detect distant relatives even in the context of pairwise kinship analysis. Although DNA microarrays conveniently generate genome-wide SNP data, they require large quantities of high-quality DNA. Genotyping data obtained from low-quantity and low-quality samples are likely unreliable owing to the incidence of no-called or mistyped SNPs. In this study, we examined the effects of insufficient sample densities and sample degradation on the efficacy of kinship analysis. While low DNA amounts had a minor effect, DNA degradation led to a significant increase in no-call rates and error rates. Posterior probabilities of kinship determination, calculated using the index of chromosomal sharing, were markedly lower in proportion to the no-call rates and error rates. We also investigated the effect of genotype imputation to complement the no-called genome data utilizing SNPs reference panels. We found that the posterior probability of the relative-assumed person increased with genotype complementation in case of mild degradation, even with mistyped genotypes. Therefore, DNA microarray with imputation is a promising method for analyzing forensic DNA samples taken from situations where DNA quantity and quality may be compromised, such as disaster victim identification using pairwise kinship analysis.     

A novel set of DIP-STR markers for improved analysis of challenging DNA mixtures

Currently available molecular biology tools allow forensic scientists to characterize DNA evidence found at crime scenes for a large variety of samples, including those of limited quantity and quality, and achieve high levels of individualization. Yet, standard forensic markers provide limited or no results when applied to mixed DNA samples where the contributors are present in very different proportions (unbalanced DNA mixtures). This becomes an issue mostly for the analysis of trace samples collected on the victim or from touched objects.To this end, we recently proposed an innovative type of genetic marker, named DIP-STR that relies on pairing deletion/insertion polymorphisms (DIP) with standard short tandem repeats (STR). This novel compound marker allows detection of the minor DNA contributor in a DNA mixture of any gender and cellular origin with unprecedented resolution (beyond a DNA ratio of 1:1000).To provide a novel analytical tool useful in practice to common forensic laboratories, this article describes the first set of 10 DIP-STR markers selected according to forensic technical standards. The novel DIP-STR regions are short (between 146 and 271 bp), include only highly polymorphic tri-, tetra- and pentanucleotide tandem repeats and are located on different chromosomes or chromosomal arms to provide statistically independent results. This novel set of DIP-STR can target the amplification of 0.03–0.1 ng of DNA when mixed with a 1000-fold excess of major DNA. DIP-STR relative allele frequencies are estimated based on a survey of 103 Swiss individuals. Finally, this study provides an estimate of the occurrence of informative alleles and a calculation of the corresponding random match probability of the detected minor DIP-STR genotype assessed across 10,506 pairwise conceptual mixtures.     

Off-target phenotypes in forensic DNA phenotyping and biogeographic ancestry inference: A resource

With recent advances in DNA sequencing technologies it has become feasible and cost effective to genotype larger marker sets for forensic purposes. Two technologies that make use of the larger marker sets have come into focus in forensic research and applications; inference of biogeographic ancestry (BGA) and forensic DNA phenotyping (FDP). These methods hold the promise to reveal information about a yet unknown perpetrator from a DNA sample. In contrast, DNA-profiling, that is a standard practice in case work, relies on matching DNA-profiles between crime scene material and suspects on a database of DNA-profiles. Markers for DNA-profiling were developed under the premise to reveal as little additional information about the human source of the profile as possible, the rationale being that personal privacy rights have to be balanced against the public interest in solving a crime. The same argument holds for markers used in BGA and FDP; these markers might also reveal information on off-target phenotypes (OTPs), that go beyond BGA and the phenotypes targeted in FDP. In particular, health related OTPs might shift the balance between privacy protection and public interest. However, to our knowledge, there is currently no convenient resource available to incorporate knowledge on OTPs in BGA and FDP assay design and application.In order to provide such a resource, we performed a systematic search for OTPs associated with a comprehensive set of markers (1766 SNPs) used or suggested to be used for BGA inference and FDP. In this set, we identified a relatively small number of 27 SNPs (1.53%) that convey information on diverse health related OTPs such as cancer risk, induced asthma, or risk of alcoholism. Some of these SNPs are commonly used for FDP and BGA across different marker sets. We conclude that the effects of SNP markers used in FDP and BGA on OTPs are currently limited, with few exceptions that should be considered in a balanced decision on assay design and application.     

FACS separation of non-compromised forensically relevant biological mixtures

Although focusing attention on the statistical analysis of complex mixture profiles is important, the forensic science community will also benefit from directing research to improving the reduction of the incidence of mixtures before DNA extraction. This preliminary study analysed the use of fluorescence assisted cell sorting (FACS) for separation of cellular mixtures before DNA extraction, specifically mixtures of relatively fresh blood and saliva from two donors, prepared in 14 different mixture ratios. Improvements in the number of detectable alleles from the targeted cell type and overall profile quality were seen when compared to the results from unseparated samples. STRmix calculations revealed increases in likelihood ratios after separation, demonstrating the potential for higher probative values to be obtained from forensically relevant mixtures after subjecting them to FACS than from unsorted samples.     

Sensitive DIP-STR markers for the analysis of unbalanced mixtures from “touch” DNA samples

Casework samples collected for forensic DNA analysis can produce genomic mixtures in which the DNA of the alleged offender is masked by high quantities of DNA coming from the victim. DIP-STRs are novel genetic markers specifically developed to enable the target analysis of a DNA of interest in the presence of exceeding quantities of a second DNA (up to 1000-fold). The genotyping system, which is based on allele-specific amplifications of haplotypes formed by a deletion/insertion polymorphism (DIP) and a short tandem repeat (STR), combines the capacity of targeting the DNA of an individual with a strong identification power. Finally, DIP-STRs are autosomal markers therefore they can be applied to any combination of major and minor DNA.In this study we aimed to assess the ability of DIP-STRs to detect the minor contributor on challenging “touch” DNA samples simulated with representative crime-associated substrates and to compare their performance to commonly used male-specific markers (Y-STRs). As part of a comprehensive study on the relative DNA contribution of two persons handling the same object, we selected 71 unbalanced contact traces of which 14 comprised a male minor DNA contributor mixed to a female major DNA contributor. Using a set of six DIP-STRs, one to four markers were found to be informative for the minor DNA detection across traces. When compared to Y-STRs (14 traces), the DIP-STRs showed similar sensitivity in detecting the minor DNA across substrate materials with a similar occurrence of allele drop-out. Conversely, because of the sex combination of the two users of the object, 57 remaining traces could only be investigated by DIP-STRs. Of these, 30 minor DNA contributors could be detected by all informative markers while 12 traces showed events of allele drop-out. Finally, 15 traces showed no amplification of the minor DNA. These last 15 samples were mostly characterized by a combination of short handling time of the object, low DNA recovery and/or one single informative DIP-STR.In conclusion, the DIP-STRs represent alternative markers to help solving unbalanced two-source DNA mixtures, and also those produced from contact stains. These markers, in addition to a novel set of 10 DIP-STRs specifically developed according to forensic technical standards, will offer a valuable tool complementary to Y-STR markers.     

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.     

Evaluating forensic DNA profiles using peak heights,allowing for multiple donors,allelic dropout and stutters

Increases in the sensitivity of DNA profiling technology now allow profiles to be obtained from smaller and more degraded DNA samples than was previously possible. The resulting profiles can be highly informative, but the subjective elements in the interpretation make it problematic to achieve the valid and efficient evaluation of evidential strength required in criminal cases. The problems arise from stochastic phenomena such as “dropout” (absence of an allele in the profile that is present in the underlying DNA) and experimental artefacts such as “stutter” that can generate peaks of ambiguous allelic status. Currently in the UK, evidential strength evaluation uses an approach in which the complex signals in the DNA profiles are interpreted in a semi-manual fashion by trained experts aided by a set of guidelines, but also relying substantially on professional judgment. We introduce a statistical model to calculate likelihood ratios for evaluating DNA evidence arising from multiple known and unknown contributors that allows for such stochastic phenomena by incorporating peak heights. Efficient use of peak heights allows for more crime scene profiles to be reported to courts than is currently possible. The model parameters are estimated from experimental data incorporating multiple sources of variability in the profiling system. We report and analyse experimental results from the SGMPlus system, run at 28 amplification cycles with no enhancements, currently used in the UK. Our methods are readily adapted to other DNA profiling systems provided that the experimental data for the parameter estimation is available.