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

The interpretation of DNA evidence can entail analysis of challenging STR typing results. Genotypes inferred from low quality or quantity specimens, or mixed DNA samples originating from multiple contributors, can result in weak or inconclusive match probabilities when a binary interpretation method and necessary thresholds (such as a stochastic threshold) are employed. Probabilistic genotyping approaches, such as fully continuous methods that incorporate empirically determined biological parameter models, enable usage of more of the profile information and reduce subjectivity in interpretation. As a result, software-based probabilistic analyses tend to produce more consistent and more informative results regarding potential contributors to DNA evidence. Studies to assess and internally validate the probabilistic genotyping software STRmix™ for casework usage at the Federal Bureau of Investigation Laboratory were conducted using lab-specific parameters and more than 300 single-source and mixed contributor profiles. Simulated forensic specimens, including constructed mixtures that included DNA from two to five donors across a broad range of template amounts and contributor proportions, were used to examine the sensitivity and specificity of the system via more than 60,000 tests comparing hundreds of known contributors and non-contributors to the specimens. Conditioned analyses, concurrent interpretation of amplification replicates, and application of an incorrect contributor number were also performed to further investigate software performance and probe the limitations of the system. In addition, the results from manual and probabilistic interpretation of both prepared and evidentiary mixtures were compared.The findings support that STRmix™ is sufficiently robust for implementation in forensic laboratories, offering numerous advantages over historical methods of DNA profile analysis and greater statistical power for the estimation of evidentiary weight, and can be used reliably in human identification testing. With few exceptions, likelihood ratio results reflected intuitively correct estimates of the weight of the genotype possibilities and known contributor genotypes. This comprehensive evaluation provides a model in accordance with SWGDAM recommendations for internal validation of a probabilistic genotyping system for DNA evidence interpretation     

Extended PCR conditions to reduce drop-out frequencies in low template STR typing including unequal mixtures

Forensic laboratories employ various approaches to obtain short tandem repeat (STR) profiles from minimal traces (<100 pg DNA input). Most approaches aim to sensitize DNA profiling by increasing the amplification level by a higher cycle number or enlarging the amount of PCR products analyzed during capillary electrophoresis. These methods have limitations when unequal mixtures are genotyped, since the major component will be over-amplified or over-loaded. This study explores an alternative strategy for improved detection of the minor components in low template (LT) DNA typing that may be better suited for the detection of the minor component in mixtures. The strategy increases the PCR amplification efficiency by extending the primer annealing time several folds. When the AmpF?STR(?) Identifiler(?) amplification parameters are changed to an annealing time of 20 min during all 28 cycles, the drop-out frequency is reduced for both pristine DNA and single or multiple donor mock case work samples. In addition, increased peak heights and slightly more drop-ins are observed while the heterozygous peak balance remains similar as with the conventional Identifiler protocol. By this extended protocol, full DNA profiles were obtained from only 12 sperm heads (which corresponds to 36 pg of DNA) that were collected by laser micro dissection. Notwithstanding the improved detection, allele drop-outs do persist, albeit in lower frequencies. Thus a LT interpretation strategy such as deducing consensus profiles from multiple independent amplifications is appropriate. The use of extended PCR conditions represents a general approach to improve detection of unequal mixtures as shown using four commercially available kits (AmpF?STR(?) Identifiler, SEfiler Plus, NGM and Yfiler). The extended PCR protocol seems to amplify more of the molecules in LT samples during PCR, which results in a lower drop-out frequency.     

Euroforgen-NoE collaborative exercise on LRmix to demonstrate standardization of the interpretation of complex DNA profiles

There has been very little work published on the variation of reporting practices of mixtures between laboratories, but it has been previously demonstrated that there is little consistency. This is because there is no current uniformity of practice, so different laboratories will operate using different rules. The interpretation of mixtures is not solely a matter of using some software to provide ‘an answer’. An assessment of a case will usually begin with a consideration of the circumstances of a crime. Assumptions made about the numbers of contributors follow from an examination of the electropherogram(s) – and these may differ between the prosecution and the defence hypotheses. There may be a necessity to evaluate several sets of hypotheses for any given case if the circumstances are uncertain. Once the hypotheses are formulated, the mathematical analysis is complex and can only be accomplished by the use of specialist software. In order to obtain meaningful results, it is essential that scientists are trained, not only in the use of the software, but also in the methodology to understand the likelihood ratio concept that is used. The Euroforgen-NoE initiative has developed a training course that utilizes the LRmix program to carry out the calculations. This software encompasses the recommendations of the ISFG DNA commissions on mixture interpretation and is able to interpret samples that may come from two or more contributors and may also be partial profiles. Recently, eighteen different laboratories were trained in the methodology. Afterwards they were asked to independently analyze two different cases with partial mixture DNA evidence and to write a statement court-report. We show that by introducing a structured training programme, it is possible to demonstrate, for the first time, that a high degree of standardization, leading to uniformity of results can be achieved by participating laboratories.     

Analysis of uni and bi-parental markers in mixture samples: Lessons from the 22nd GHEP-ISFG Intercomparison Exercise

Since 1992, the Spanish and Portuguese-Speaking Working Group of the ISFG (GHEP-ISFG) has been organizing annual Intercomparison Exercises (IEs) coordinated by the Quality Service at the National Institute of Toxicology and Forensic Sciences (INTCF) from Madrid, aiming to provide proficiency tests for forensic DNA laboratories. Each annual exercise comprises a Basic (recently accredited under ISO/IEC 17043: 2010) and an Advanced Level, both including a kinship and a forensic module. Here, we show the results for both autosomal and sex-chromosomal STRs, and for mitochondrial DNA (mtDNA) in two samples included in the forensic modules, namely a mixture 2:1 (v/v) saliva/blood (M4) and a mixture 4:1 (v/v) saliva/semen (M8) out of the five items provided in the 2014 GHEP-ISFG IE. Discrepancies, other than typos or nomenclature errors (over the total allele calls), represented 6.5% (M4) and 4.7% (M8) for autosomal STRs, 15.4% (M4) and 7.8% (M8) for X-STRs, and 1.2% (M4) and 0.0% (M8) for Y-STRs. Drop-out and drop-in alleles were the main cause of errors, with laboratories using different criteria regarding inclusion of minor peaks and stutter bands. Commonly used commercial kits yielded different results for a micro-variant detected at locus D12S391. In addition, the analysis of electropherograms revealed that the proportions of the contributors detected in the mixtures varied among the participants. In regards to mtDNA analysis, besides important discrepancies in reporting heteroplasmies, there was no agreement for the results of sample M4. Thus, while some laboratories documented a single control region haplotype, a few reported unexpected profiles (suggesting contamination problems). For M8, most laboratories detected only the haplotype corresponding to the saliva. Although the GHEP-ISFG has already a large experience in IEs, the present multi-centric study revealed challenges that still exist related to DNA mixtures interpretation. Overall, the results emphasize the need for further research and training actions in order to improve the analysis of mixtures among the forensic practitioners.     

Species identification in forensic samples using the SPInDel approach: A GHEP-ISFG inter-laboratory collaborative exercise

DNA is a powerful tool available for forensic investigations requiring identification of species. However, it is necessary to develop and validate methods able to produce results in degraded and or low quality DNA samples with the high standards obligatory in forensic research. Here, we describe a voluntary collaborative exercise to test the recently developed Species Identification by Insertions/Deletions (SPInDel) method. The SPInDel kit allows the identification of species by the generation of numeric profiles combining the lengths of six mitochondrial ribosomal RNA (rRNA) gene regions amplified in a single reaction followed by capillary electrophoresis. The exercise was organized during 2014 by a Working Commission of the Spanish and Portuguese-Speaking Working Group of the International Society for Forensic Genetics (GHEP-ISFG), created in 2013. The 24 participating laboratories from 10 countries were asked to identify the species in 11 DNA samples from previous GHEP-ISFG proficiency tests using a SPInDel primer mix and control samples of the 10 target species. A computer software was also provided to the participants to assist the analyses of the results. All samples were correctly identified by 22 of the 24 laboratories, including samples with low amounts of DNA (hair shafts) and mixtures of saliva and blood. Correct species identifications were obtained in 238 of the 241 (98.8%) reported SPInDel profiles. Two laboratories were responsible for the three cases of misclassifications. The SPInDel was efficient in the identification of species in mixtures considering that only a single laboratory failed to detect a mixture in one sample. This result suggests that SPInDel is a valid method for mixture analyses without the need for DNA sequencing, with the advantage of identifying more than one species in a single reaction. The low frequency of wrong (5.0%) and missing (2.1%) alleles did not interfere with the correct species identification, which demonstrated the advantage of using a method based on the analysis of multiple loci. Overall, the SPInDel method was easily implemented by laboratories using different genotyping platforms, the interpretation of results was straightforward and the SPInDel software was used without any problems. The results of this collaborative exercise indicate that the SPInDel method can be applied successfully in forensic casework investigations.     

Variation in assessments of suitability and number of contributors for DNA mixtures

The interpretation of a DNA mixture (a sample that contains DNA from two or more people) depends on a laboratory/analyst’s assessment of the suitability of the sample for comparison/analysis, and an assessment of the number of contributors (NoC) present in the sample. In this study, 134 participants from 67 forensic laboratories provided a total of 2272 assessments of 29 DNA mixtures (provided as electropherograms). The laboratories’ responses were evaluated in terms of the variability of suitability assessments, and the accuracy and variability of NoC assessments. Policies and procedures related to suitability and NoC varied notably among labs. We observed notable variation in whether labs would assess a given mixture as suitable or not, predominantly due to differences in lab policies: if two labs following their standard operating procedures (SOPs) were given the same mixture, they agreed on whether the mixture was suitable for comparison 66% of the time. Differences in suitability assessments have a direct effect on variability in interpretations among labs, since mixtures assessed as not suitable would not result in reported interpretations. For labs following their SOPs, 79% of assessments of NoC were correct. When two different labs provided NoC responses, 63% of the time both labs were correct, and 7% of the time both labs were incorrect. Incorrect NoC assessments have been shown to affect statistical analyses in some cases, but do not necessarily imply inaccurate interpretations or conclusions. Most incorrect NoC estimates were overestimates, which previous research has shown have less of an effect on likelihood ratios than underestimates.     

Separation of uncompromised whole blood mixtures for single source STR profiling using fluorescently-labeled human leukocyte antigen (HLA) probes and fluorescence activated cell sorting (FACS)

Analysis of biological mixtures is a significant problem for forensic laboratories, particularly when the mixture contains only one cell type. Contributions from multiple individuals to biologic evidence can complicate DNA profile interpretation and often lead to a reduction in the probative value of DNA evidence or worse, its total loss. To address this, we have utilized an analytical technique that exploits the intrinsic immunological variation among individuals to physically separate cells from different sources in a mixture prior to DNA profiling. Specifically, we applied a fluorescently labeled antibody probe to selectively bind to one contributor in a mixture through allele-specific interactions with human leukocyte antigen (HLA) proteins that are expressed on the surfaces of most nucleated cells. Once the contributor’s cells were bound to the probe, they were isolated from the mixture using fluorescence activated cell sorting (FACS)—a high throughput technique for separating cell populations based on their optical properties—and then subjected to STR analysis.We tested this approach on two-person and four-person whole blood mixtures where one contributor possessed an HLA allele (A*02) that was not shared by other contributors to the mixture. Results showed that hybridization of the mixture with a fluorescently-labeled antibody probe complimentary to the A*02 allele’s protein product created a cell population with a distinct optical profile that could be easily differentiated from other cells in the mixture. After sorting the cells with FACS, genetic analysis showed that the STR profile of this cell population was consistent with that of the contributor who possessed the A*02 allele. Minor peaks from the A*02 negative contributor(s) were observed but could be easily distinguished from the profile generated from A*02 positive cells. Overall, this indicates that HLA antibody probes coupled to FACS may be an effective approach for generating STR profiles of individual contributors from forensic mixtures.     

SNP-microarrays can accurately identify the presence of an individual in complex forensic DNA mixtures

Common forensic and mass disaster scenarios present DNA evidence that comprises a mixture of several contributors. Identifying the presence of an individual in such mixtures has proven difficult. In the current study, we evaluate the practical usefulness of currently available “off-the-shelf” SNP microarrays for such purposes. We found that a set of 3000 SNPs specifically selected for this purpose can accurately identify the presence of an individual in complex DNA mixtures of various compositions. For example, individuals contributing as little as 5% to a complex DNA mixture can be robustly identified even if the starting DNA amount was as little as 5.0 ng and had undergone whole-genome amplification (WGA) prior to SNP analysis. The work presented in this study represents proof-of-principle that our previously proposed approach, can work with real “forensic-type” samples. Furthermore, in the absence of a low-density focused forensic SNP microarray, the use of standard, currently available high-density SNP microarrays can be similarly used and even increase statistical power due to the larger amount of available information.     

An assessment of the performance of the probabilistic genotyping software EuroForMix: Trends in likelihood ratios and analysis of Type I & II errors

Continuous probabilistic genotyping software enables the interpretation of highly complex DNA profiles that are prone to stochastic effects and/or consist of multiple contributions. The process of introducing probabilistic genotyping into an accredited forensic laboratory requires testing, validation, documentation and training. Documents that include guidelines and/or requirements have been published in order to guide forensic laboratories through this extensive process and there has been encouragements to share the results obtained from internal laboratory studies. To this end, we present the results obtained from the quantitative probabilistic genotyping system EuroForMix applied to mixed DNA profiles with known contributions mixed in known proportions, levels of allele sharing and levels of allelic drop-out. The mixtures were profiled using the PowerPlex® Fusion 6C (PPF6C) kit. Using these mixtures, 427 Hp-true tests and 408 Hd-true tests were performed. In the Hd-true tests, non-contributors were selected deliberately to a have large overlap with the alleles within the mixture and worst-case scenarios were examined in which a simulated relative of one of the true donors was considered as the person of interest under the prosecution hypothesis. The effects of selecting different EuroForMix modelling options, the use of PCR replicates, allelic drop-out, and varying the assigned number of contributors were examined. Instances of Type I and Type II errors are discussed. In addition 330 likelihood ratio results from EuroForMix are compared to the semi-continuous model LRmix Studio. Results demonstrate the performance and trends of EuroForMix when applied to PPF6C profiles.     

Factors affecting the detection and quantification of mitochondrial point heteroplasmy using Sanger sequencing and SNaPshot minisequencing

Mitochondrial DNA analysis plays an important role in forensic science as well as in the diagnosis of mitochondrial diseases. The occurrence of two different nucleotides at the same sequence position can be caused either by heteroplasmy or by a mix of samples. The detection of superimposed positions in forensic samples and their quantification can provide additional information and might also be useful to identify a mixed sample. Therefore, the detection and visualization of heteroplasmy has to be robust and sensitive at the same time to allow for reliable interpretation of results and to avoid a loss of information. In this study, different factors influencing the analysis of mitochondrial heteroplasmy (DNA polymerases, PCR and sequencing primers, nucleotide incorporation, and sequence context) were examined. BigDye Sanger sequencing and the SNaPshot minisequencing were compared as to the accuracy of detection using artificially created mitochondrial DNA mixtures. Both sequencing strategies showed to be robust, and the parameters tested showed to have a variable impact on the display of nucleotide ratios. However, experiments revealed a high correlation between the expected and the measured nucleotide ratios in cell mixtures. Compared to the SNaPshot minisequencing, Sanger sequencing proved to be the more robust and reliable method for quantification of nucleotide ratios but showed a lower detection sensitivity of minor cytosine components.     

Evaluation of large-scale highly polymorphic microhaplotypes in complex DNA mixtures analysis using RMNE method

DNA mixture interpretation is one of the most challenging problems in forensics. Complex DNA mixtures are more difficult to analyze when there are more than two contributors or related contributors. Microhaplotypes (MHs) are polymorphic genetic markers recently discovered and employed in DNA mixture analysis. However, the evidentiary interpretation of the MH genotyping data needs more debate. The Random Man Not Excluded (RMNE) method analyzes DNA mixtures without using allelic peak height data or the number of contributors (NoC) assumptions. This study aimed to assess how well RMNE interpreted mixed MH genotyping data. We classified the MH loci from the 1000 Genomes Project database into groups based on their Ae values. Then we performed simulations of DNA mixtures with 2–10 unrelated contributors and DNA mixtures with a pair of sibling contributors. For each simulated DNA mixture, incorrectly included ratios were estimated for three types of non-contributors: random men, parents of contributors, and siblings of contributors. Meanwhile, RMNE probability was calculated for contributors and three types of non-contributors, allowing loci mismatch. The results showed that the MH number, the MH Ae values, and the NoC affected the RMNE probability of the mixture and the incorrectly included ratio of non-contributors. When there were more MHs, MHs with higher Ae values, and a mixture with less NoC, the RMNE probability, and the incorrectly included ratio decreased. The existence of kinship in mixtures complicated the mixture interpretation. Contributors’ relatives as non-contributors and related contributors in the mixture increased the demands on the genetic markers to identify the contributors correctly. When 500 highly polymorphic MHs with Ae values higher than 5 were used, the four individual types could be distinguished according to the RMNE probabilities. This study reveals the promising potential of MH as a genetic marker for mixed DNA interpretation and the broadening of RMNE as a parameter indicating the relationship of a specific individual with a DNA mixture in the DNA database search.     

Investigating a common approach to DNA profile interpretation using probabilistic software

Recently there has been a drive for standardisation of DNA profile interpretation within and between different forensic laboratories. The continuous interpretation software STRmix⢢ has been adopted for use by laboratories in Australia and New Zealand for profile interpretation. Within this paper we examine the concordance in profile interpretation of three crime samples by twenty different analysts across twelve different international laboratories using STRmix⢢. The three profiles selected for this study exhibited a range of template and complexity. The use of probabilistic software has compelled a level of concordance between different analysts however there remain differences within profile interpretation, particularly with the objective assignment of the number of contributors to profiles.     

Does the use of probabilistic genotyping change the way we should view sub-threshold data?

The sensitivity and resolution of modern DNA profiling hardware is such that forensic laboratories generate more data than they have resources to analyse. One coping mechanism is to set a threshold, above the minimum required by instrument noise, so that weak peaks are screened out. In binary interpretations of forensic profiles, the impact of this threshold (sometimes called an analytical threshold – AT) was minimal as interpretations were often limited to a clear major component. With the introduction of continuous typing systems, the interpretation of weak minor components of mixed DNA profiles is possible and consequently the consideration of peaks just above or just below the analytical threshold becomes relevant. We investigate here the occurrence of low-level DNA profile information, specifically that which falls below the analytical threshold. We investigate how it can be dealt with and the consequences of each choice in the framework of continuous DNA profile interpretation systems. Where appropriate we illustrate how these can be implemented using the probabilistic interpretation software STRmix. We demonstrate a feature of STRmix that allows the analyst to guide the software, using human observation that there is a low-level contributor present, through user-designated prior distributions for contributor mixture proportions.     

Comparison of different interpretation strategies for low template DNA mixtures

DNA typing protocols have been improved over the last few years and even mixtures from minute and low grade DNA stains do not necessarily preclude typing. Nevertheless, in those cases stochastic phenomena tend to hamper interpretation. In order to supplement the current discussion about the interpretation of such challenging data, we focused on different combinations of analyses as an attempt to overcome stochastic problems.We analyzed mixtures of two types of degraded DNA in low template amounts (50 and 100 pg DNA per contributor) using four types of multiplex STR typing kits: PowerPlex^® ESX 17, PowerPlex^® ESI 17, Investigator^® ESSplex SE Kit and P11, a non-commercial kit. We employed the results of double or triple analyses for a comparison of different types of interpretation rules based on reporting either only reproducible alleles (consensus interpretation) or all alleles, even if they are only observed once (composite interpretation). The interpreted and composed profiles were compared to the known alleles of the contributors and a “degree of validity” was calculated.When only two single amplifications were taken into account, we observed a higher degree of validity for composite profiles. The difference for consensus interpretation could be compensated when a minimum of three amplifications were carried out.Using the same kit for repeat analyses increases the chances to yield reproducible results required for consensus interpretation. Combining different kits in a complementing approach, on the other hand, offers the opportunity to reduce the number of drop-out alleles: differences in amplicon lengths for specific markers between kits can increase the resulting information. In the case of a few amplifications available this effect might only be visible with the composite method. Several markers like SE33 are particularly affected by this.Based on our observations the consensus interpretation method may not reflect the original profile in an optimal way in some special cases like low template, degraded mixture stains. In those cases the composite interpretation could yield more complete results. However, such a composite profile should be used with caution and only for limited purposes. Generally recommending the consensus interpretation thus seems not to be justified: a more differentiated approach appears to be worthwhile, e.g. the amount of drop-outs, the number of replicates, choice and combination of kits and even a marker specific procedure might be taken into account.     

Differentiation of vaginal cells from epidermal cells using morphological and autofluorescence properties: Implications for sexual assault casework involving digital penetration

Analysis of DNA mixtures from sexual assault evidence is an ongoing challenge for DNA casework laboratories. To assist the forensic scientist address source and activity level propositions there is a significant need for new techniques that can provide information as to the source of DNA, particularly for sexual assault samples that do not involve semen. The goal of this study was to develop a new biological signature system that provides additional probative value to samples comprised of mixtures of epidermal and vaginal cells, as may be observed in cases involving digital penetration. Signatures were based on morphological and autofluorescence properties of individual cells collected through Imaging Flow Cytometry (IFC). Comparisons to reference cell populations from vaginal tissue and epidermal cells collected from hands showed strong multivariate differences across > 80 cellular measurements. These differences were used to build a predictive framework for classifying unknown cell populations as originating from epithelial cells associated with digital penetration or epidermal tissue. As part of the classification scheme, posterior probabilities of specific tissue group membership were calculated for each cell, along with multivariate similarity to that tissue type. We tested this approach on cell populations from reference tissue as well as mock casework samples involving hand swabbings following digital vaginal penetration. Many more cells classifying as non-epidermal tissue were detected in digital penetration hand swab samples than control hand swabbings. Minimum interpretation thresholds were developed to minimize false positives; these thresholds were also effective when screening licked hands, indicating the potential utility of this method for a variety of biological mixture types and depositional events relevant to forensic casework. Results showed that samples collected subsequent to digital penetration possessed markedly higher numbers of cells classifying as vaginal tissue as well as higher posterior probabilities for vaginal tissue (≥ 0.90) compared to cell populations collected from hands without prior contact with vaginal tissue. Additionally, digital penetration cell populations may be resolved from saliva cell populations and other non-target tissue types.     

Complex DNA mixture analysis in a forensic context: Evaluating the probative value using a likelihood ratio model

The interpretation of mixed DNA profiles obtained from low template DNA samples has proven to be a particularly difficult task in forensic casework. Newly developed likelihood ratio (LR) models that account for PCR-related stochastic effects, such as allelic drop-out, drop-in and stutters, have enabled the analysis of complex cases that would otherwise have been reported as inconclusive. In such samples, there are uncertainties about the number of contributors, and the correct sets of propositions to consider. Using experimental samples, where the genotypes of the donors are known, we evaluated the feasibility and the relevance of the interpretation of high order mixtures, of three, four and five donors.The relative risks of analyzing high order mixtures of three, four, and five donors, were established by comparison of a ‘gold standard’ LR, to the LR that would be obtained in casework. The ‘gold standard’ LR is the ideal LR: since the genotypes and number of contributors are known, it follows that the parameters needed to compute the LR can be determined per contributor. The ‘casework LR’ was calculated as used in standard practice, where unknown donors are assumed; the parameters were estimated from the available data. Both LRs were calculated using the basic standard model, also termed the drop-out/drop-in model, implemented in the LRmix module of the R package Forensim.We show how our results furthered the understanding of the relevance of analyzing high order mixtures in a forensic context. Limitations are highlighted, and it is illustrated how our study serves as a guide to implement likelihood ratio interpretation of complex DNA profiles in forensic casework.     

Assessment of mock cases involving complex low template DNA mixtures: A descriptive study

Complex DNA mixtures with low template (LT) components provide the most challenging cases to interpret and report. In this study, we designed such mixtures and we describe how reporting officers (ROs) at the Netherlands Forensic Institute (NFI) assess these when embedded in a mock case setting. DNA mixtures containing LT DNA from two to four contributors, sporadic contamination (mimicked by adding 6 pg of DNA, which represents once cell equivalent) and/or DNA of relatives (brothers), were amplified four-fold using the AmpFlSTR^® NGM? PCR Amplification Kit. Consensus profiles were then generated which included the alleles detected in at least half of the replicates. Four mock cases were created by including reference profiles of a hypothetical victim and suspect. The mock cases were assessed by eight ROs following the stepwise interpretation approach currently in use at the NFI. With this approach, the results of the comparisons between the DNA profiles of the evidentiary trace and the reference profiles are classified into four categories of evidential value [1]. The interpretations by the ROs were compared to the likelihood ratios (LRs) obtained from a probabilistic model that allows a calculation of LRs to assist the interpretation of LT DNA evidence and both were compared to the true composition of the designed mixtures.     

Consensus and pool profiles to assist in the analysis and interpretation of complex low template DNA mixtures

Forensic analysis of low template (LT) DNA mixtures is particularly complicated when (1) LT components concur with high template components, (2) more than three contributors are present, or (3) contributors are related. In this study, we generated a set of such complex LT mixtures and examined two methods to assist in DNA profile analysis and interpretation: the “n/2” consensus method (Benschop et al. 2011) and the pool profile approach. N/2 consensus profiles include alleles that are reproducibly amplified in at least half of the replications. Pool profiles are generated by injecting a blend of independently amplified PCR products on a capillary electrophoresis instrument. Both approaches resulted in a similar increase in the percentage of detected alleles compared to individual profiles, and both rarely included drop-in alleles in case mixtures of pristine DNAs were used. Interestingly, the consensus and the pool profiles often showed differences for the actual alleles detected for the LT component(s). We estimated the number of contributors using different methods. Better approximations were obtained with data in the consensus and pool profiles compared to the data of the individual profiles. Consensus profiles contain allele calls only, while pool profiles consist of both allele calls and peak height information, which can be of use in (statistical) profile analysis. All advantages and limitations of the various types of profiles were assessed, and based on the results we infer that both consensus and pool profiles (or a combination thereof) are helpful in the interpretation of complex LT DNA mixtures.     

Safeguarding forensic DNA reference samples with nullomer barcodes

Unintended transfer of biological material containing DNA is a concern to all laboratories conducting PCR analysis. While forensic laboratories have protocols in place to reduce the possibility of contaminating casework samples, there is no way to detect when a reference sample is mislabeled as evidence, or contaminates a forensic sample. Thus there is public concern regarding the safeguarding of DNA submitted to crime labs. We demonstrate a method of introducing an internal amplification control to reference samples, in the form of a nullomer barcode which is based upon sequences absent or rare from publically accessible DNA databases. The detection of this barcode would indicate that the source of analyzed DNA was from a reference sample provided by an individual, and not from an evidence sample. We demonstrate that the nullomers can be added directly to collection devices (FTA paper) to allow tagging during the process of sample collection. We show that such nullomer oligonucleotides can be added to existing forensic typing and quantification kits, without affecting genotyping or quantification results. Finally, we show that even when diluted a million-fold and spilled on a knife, the nullomer tags can be clearly detected. These tags support the National Research Council of the National Academy recommendation that “Quality control procedures should be designed to identify mistakes, fraud, and bias” in forensic science (National Academy of Sciences, 2009).     

Validation of the PLEX-IDTM mass spectrometry mitochondrial DNA assay

For very challenged biological samples, mitochondrial DNA (mtDNA) analysis can often provide results when the more traditional nuclear DNA markers fail. While reliable, the current method of mtDNA analysis by Sanger sequencing is expensive, labor-intensive, and time-consuming and is limited by its inability to quantify mixed samples. The Abbott PLEX-ID? instrument, which enables analysis of mtDNA amplicons via electrospray ionization mass spectrometry (ESI-MS), produces comparable accuracy and sensitivity while offering a faster and less expensive alternative to Sanger sequencing. Unlike Sanger sequencing, this system is capable of quantifying DNA species and thus may be exploited for evaluating heteroplasmy and, possibly, mixture deconvolution. Validation studies of the PLEX-ID? mtDNA assay confirmed that the instrument is highly sensitive and capable of yielding reproducible results. Samples commonly encountered in a forensic setting, as well as population samples, were typed correctly. The PLEX-ID? mtDNA assay yields reliable results for single-source samples, which are the same sample types currently examined in forensic laboratories via Sanger sequencing, at a level that meets or exceeds that of the current method. While the instrument has the demonstrated capability to quantify mixed samples, the specific assay design for mtDNA analysis can be used only in a limited fashion to analyze mixtures due to the formation of chimeric mtDNA products.