Degradation of forensic DNA profiles

Half-volume validation of the NGM Detect™ PCR Amplification Kit and its application on degraded casework samples

The NGM Detect™ PCR Amplification Kit was designed particularly for genotyping degraded casework samples. This study aimed to validate the half-volume amplification of the kit and to present its successful long-term application. The validation was performed in accordance to the corresponding guidelines of the Scientific Working Group on DNA analysis methods and the European Network of Forensic Science Institutes. For validation parameters, such as sensitivity, reproducibility, and repeatability, polymerase chain reactions (PCR) were set up both manually and robotically, applying 29 cycles. For PCRs with sub-optimal DNA input (≤0.5 ng) the cycle numbers were increased to 31. Regardless of the PCR preparation method, the optimal 0.5 ng DNA input produced optimal allelic peak heights with no allelic dropout. The first alleles that failed to amplify started to appear at the level of 0.0375 ng input DNA, although the manually prepared PCRs produced fewer missing alleles. In this case, the raised cycle number produced 1.9% and 4.4% of dropout for manually and for robotically set up PCRs, respectively. In the case of 84 degraded casework samples, PCRs were prepared only by hand. The kit was able to provide informative profiles for 78.57%, 70.37%, and 69.77% for lowly, moderately, and highly degraded samples, respectively. Allelic dropouts were 26.05%, 44.88%, and 51.23% for the same groups. According to our results, we strongly recommend using the NGM Detect™ Kit in half-volume PCR system and encourage the usage of the kit in the particular cases when other kits fail to produce a complete DNA profile.

The Influence of Tanning Chemical Agents on DNA Degradation: A Robust Procedure for the Analysis of Tanned Animal Hide-A Pilot Study

Illegal wildlife trade is currently on the rise, and it is becoming one of the most lucrative crime sectors. The rarer the species, the higher the demand. Wildlife trade falls under international regulations, such as the CITES convention. Proving that this convention has been violated is a complex process and can be very difficult to do. DNA analysis methods remain (in many cases) the only way to determine whether a certain specimen originated from a protected animal species, a specific individual, or a species in which it is legal to trade. Tanned animal hides are a specific type of specimen. With this type of biological material, obtaining amplifiable DNA is often difficult. This pilot study aimed to map the effect of the chemicals used in the tanning process on the degradation of the DNA yielded from such samples. The DNA was quantified using two different approaches: qPCR and Qubit fluorometry. The degree of DNA fragmentation was assessed by determining the degradation index. The results indicate that reagents containing chromium have the greatest influence on DNA degradation. However, by using the presented protocol, enough amplifiable DNA can be obtained from hides treated with aluminum-based reagents.

DNA degradation of bloodstains on cotton fabric caused by different washing procedures

DNA degradation in biological material needs to be better understood. Bloodstains on washed clothing are disturbed by washing procedures, sometimes transferred to other fabrics, often with latent bloodstains and usually with significantly degraded DNA. The samples (cotton fabric with bloodstains) are divided into six main groups, depending on the washing method regarding water temperature (95, 60, and 30 °C) and the detergent use. After completing the washing process, samples were stored for a certain period (1 day to 6 months) and subsequently analyzed. Analyses were performed using standard protocols and commercial kits to measure the remaining DNA quantity (concentration) and DNA degradation index in the processed samples. Our results revealed that the high washing temperature (60 and 95 °C) and the application of detergent have a synergic action on DNA degradation, while at 30 °C this effect is absent. Furthermore, the effect of detergent on accelerated DNA degradation is observed about a month after the washing. This delayed effect of detergent has no explanation in current literature data. To obtain optimal results from the bloodstains, we recommended that the period from the crime event and attempted cleaning by a perpetrator to the laboratory analysis should be less than 1 month.

Performance comparison of four qPCR and three autosomal STR commercial kits from degraded skeletal remains

This research evaluates the current DNA quantification (Quantifiler™ Trio, PowerQuant®, Investigator® Quantiplex® Pro and InnoQuant® HY Fast) and autosomal STRs amplification kits (GlobalFiler™, PowerPlex® Fusion 6 C, Investigator® 24Plex QS) using 62 degraded skeletal remains from armed conflicts (petrous bone, femur, tibia, and tooth) with several parameters (autosomal small, large, and male target, degradation index, probability of degradation, number of alleles above analytical threshold, number of alleles above stochastic threshold, RFU, peak height ratio, number of reportable loci). The best qPCR/autosomal STRs amplification tandem was determined by comparing quantification results by a DNA quantity estimation based on sample average RFU. InnoQuant® HY Fast was the most sensitive kit, and no significative differences were observed among amplification kits; however, Investigator® 24 Plex QS was found to be the most sensitive in our samples. That is why InnoQuant™ and Investigator® 24Plex QS were determined to be the best tandem.

Using unique molecular identifiers to improve allele calling in low-template mixtures

PCR artifacts are an ever-present challenge in sequencing applications. These artifacts can seriously limit the analysis and interpretation of low-template samples and mixtures, especially with respect to a minor contributor. In medicine, molecular barcoding techniques have been employed to decrease the impact of PCR error and to allow the examination of low-abundance somatic variation. In principle, it should be possible to apply the same techniques to the forensic analysis of mixtures. To that end, several short tandem repeat loci were selected for targeted sequencing, and a bioinformatic pipeline for analyzing the sequence data was developed. The pipeline notes the relevant unique molecular identifiers (UMIs) attached to each read and, using machine learning, filters the noise products out of the set of potential alleles. To evaluate this pipeline, DNA from pairs of individuals were mixed at different ratios (1-1, 1-9) and sequenced with different starting amounts of DNA (10, 1 and 0.1 ng). Naïvely using the information in the molecular barcodes led to increased performance, with the machine learning resulting in an additional benefit. In concrete terms, using the UMI data results in less noise for a given amount of drop out. For instance, if thresholds are selected that filter out a quarter of the true alleles, using read counts accepts 2381 noise alleles and using raw UMI counts accepts 1726 noise alleles, while the machine learning approach only accepts 307.

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

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

Assessing the utility of quantitative and qualitative metrics in the DNA quantification process of skeletal remains for autosomal and Y-chromosome STR amplification purposes

In historical cases, ancient DNA investigations and missing persons identification, teeth or bone samples are often the only and almost always the best biological material available for DNA typing. On the other hand, DNA obtained from bone material may be characterized by a high degradation index (DI) or its low content, or DNA tests cannot be repeated due to bone piece size limitation. That is often the effect of the environment in which the material was placed and the time during which exposure to unfavorable environmental factors took place. Therefore, it is very important to use appropriate procedures related to STR analysis. For our study, we selected 80 challenging bone samples. The amount of DNA was compared in qPCR using Quantifiler™ Trio DNA Quantification Kit and Investigator® Quantiplex® Pro RGQ. All qPCR results were confirmed by PCR-CE. The results of DNA concentrations and the assigned degradation index (DI) differed significantly within analyzed samples (~10%). Additionally, the Y-chromosome DI also differed from the autosomal DI in the samples. The difference in degradation indexes could explain the lower Y-chromosome amplification success rate compared to autosomal e.g. during human identification process. The results indicate that performing two DNA quantifications with the use of two different kits (primers sets) allows for a much more precise evaluation of the DNA quality and quantity in the isolate. We suggest that at least one of two suggested DNA concentration measurements should be based on an additional determination of the Y chromosome degradation index. Altogether, it allows for rational isolate management, especially when the volume is limited and the sample is unique.

High-quality data from a forensically relevant single-cell pipeline enabled by low PBS and proteinase K concentrations

Interpreting forensic DNA signal is arduous since the total intensity is a cacophony of signal from noise, artifact, and allele from an unknown number of contributors (NOC). An alternate to traditional bulk-processing pipelines is a single-cell one, where the sample is collected, and each cell is sequestered resulting in n single-source, single-cell EPGs (scEPG) that must be interpreted using applicable strategies. As with all forensic DNA interpretation strategies, high quality electropherograms are required; thus, to enhance the credibility of single-cell forensics, it is necessary to produce an efficient direct-to-PCR treatment that is compatible with prevailing downstream laboratory processes. We incorporated the semi-automated micro-fluidic DEPArray™ technology into the single-cell laboratory and optimized its implementation by testing the effects of four laboratory treatments on single-cell profiles. We focused on testing effects of phosphate buffer saline (PBS) since it is an important reagent that mitigates cell rupture but is also a PCR inhibitor. Specifically, we explored the effect of decreasing PBS concentrations on five electropherogram-quality metrics from 241 leukocytes: profile drop-out, allele drop-out, allele peak heights, peak height ratios, and scEPG sloping. In an effort to improve reagent use, we also assessed two concentrations of proteinase K. The results indicate that decreasing PBS concentrations to 0.5X or 0.25X improves scEPG quality, while modest modifications to proteinase K concentrations did not significantly impact it. We, therefore, conclude that a lower than recommended proteinase K concentration coupled with a lower than recommended PBS concentration results in enhanced scEPGs within the semi-automated single-cell pipeline.

A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™

Probabilistic genotyping has become widespread. EuroForMix and DNAStatistX are both based upon maximum likelihood estimation using a γ model, whereas STRmix™ is a Bayesian approach that specifies prior distributions on the unknown model parameters. A general overview is provided of the historical development of probabilistic genotyping. Some general principles of interpretation are described, including: the application to investigative vs. evaluative reporting; detection of contamination events; inter and intra laboratory studies; numbers of contributors; proposition setting and validation of software and its performance. This is followed by details of the evolution, utility, practice and adoption of the software discussed.

DNA degradation in human teeth exposed to thermal stress

Human identification from burned remains poses a challenge to forensic laboratories, and DNA profiling is widely used for this purpose. Our aim was to evaluate the effect of temperature on DNA degradation in human teeth. Thirty teeth were exposed to temperatures of 100, 200, or 400 °C for 60 min. DNA was quantified by Real-Time qPCR (Quantifiler Human DNA Quantification Kit) and fluorescence spectroscopy (Qubit 3.0 Fluorometer). DNA degradation was evaluated by using STR markers (AmpFLSTR Identifiler Plus PCR Amplification Kit) to determine the allele and locus dropout, inter-locus balance, and degradation slope (observed (Oa) to expected (Ea) locus peak height ratio against the molecular weight). Most of the genomic DNA was degraded between 100 °C and 200 °C. At 100 °C, locus dropout ratios showed significant differences between the largest loci (FGA, D7S820, D18S51, D16S539, D2S1338 and CSF1PO) and amelogenin. Inter-locus balance values significantly differed between all dye channels except between NED and PET. The dropout ratio between D18S51 (NED) and amelogenin (PET) can be recommended for the evaluation of DNA degradation. The Oa/Ea regression model can predict locus peak heights in DNA degradation (R2 = 0.7881). These findings may be useful to assess the reliability of DNA typing for human identification in teeth subjected to prolonged incineration.

Evaluating DNA evidence possibly involving multiple (mixed) samples, common donors and related contributors

Forensic DNA profiling is used in various circumstances to evaluate support for two competing propositions with the assignment of a likelihood ratio. Many software implementations exist that tackle a range of inference problems spanning identification and relationship testing. We propose a flexible likelihood ratio framework that caters to inference problems in forensic genetics. The framework allows for investigation of the degree of support for the contribution of multiple persons to multiple samples allowing for persons to be related according to a pedigree, including inbred relationships. We explain how a number of routine as well as more complex problems can be treated within this framework.

Modeling allelic analyte signals for aSTRs in NGS DNA profiles

We describe an adaption of Bright et al.'s work modeling peak height variability in CE-DNA profiles to the modeling of allelic aSTR (autosomal short tandem repeats) read counts from NGS-DNA profiles, specifically for profiles generated from the ForenSeq™ DNA Signature Prep Kit, DNA Primer Mix B. Bright et al.'s model consists of three key components within the estimation of total allelic product-template, locus-specific amplification efficiencies, and degradation. In this work, we investigated the two mass parameters-template and locus-specific amplification efficiencies-and used MLE (maximum likelihood estimation) and MCMC (Markov chain Monte Carlo) methods to obtain point estimates to calculate the total allelic product. The expected read counts for alleles were then calculated after proportioning some of the expected stutter product from the total allelic product. Due to preferential amplicon selection introduced by the sample purification beads, degradation is difficult to model from the aSTR outputs alone. Improved modeling of the locus-specific amplification efficiencies may mask the effects of degradation. Whilst this model could be improved by introducing locus specific variances in addition to locus specific priors, our results demonstrate the suitability of adapting Bright et al.'s allele peak height model for NGS-DNA profiles. This model could be incorporated into continuous probabilistic interpretation approaches for mixed DNA profiles.

Towards developing forensically relevant single-cell pipelines by incorporating direct-to-PCR extraction: compatibility, signal quality, and allele detection

Current analysis of forensic DNA stains relies on the probabilistic interpretation of bulk-processed samples that represent mixed profiles consisting of an unknown number of potentially partial representations of each contributor. Single-cell methods, in contrast, offer a solution to the forensic DNA mixture problem by incorporating a step that separates cells before extraction. A forensically relevant single-cell pipeline relies on efficient direct-to-PCR extractions that are compatible with standard downstream forensic reagents. Here we demonstrate the feasibility of implementing single-cell pipelines into the forensic process by exploring four metrics of electropherogram (EPG) signal quality-i.e., allele detection rates, peak heights, peak height ratios, and peak height balance across low- to high-molecular-weight short tandem repeat (STR) markers-obtained with four direct-to-PCR extraction treatments and a common post-PCR laboratory procedure. Each treatment was used to extract DNA from 102 single buccal cells, whereupon the amplification reagents were immediately added to the tube and the DNA was amplified/injected using post-PCR conditions known to elicit a limit of detection (LoD) of one DNA molecule. The results show that most cells, regardless of extraction treatment, rendered EPGs with at least a 50% true positive allele detection rate and that allele drop-out was not cell independent. Statistical tests demonstrated that extraction treatments significantly impacted all metrics of EPG quality, where the Arcturus® PicoPure™ extraction method resulted in the lowest median allele drop-out rate, highest median average peak height, highest median average peak height ratio, and least negative median values of EPG sloping for GlobalFiler™ STR loci amplified at half volume. We, therefore, conclude the feasibility of implementing single-cell pipelines for casework purposes and demonstrate that inferential systems assuming cell independence will not be appropriate in the probabilistic interpretation of a collection of single-cell EPGs.

Systematic evaluation of STRmix™ performance on degraded DNA profile data

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

Data on likelihood ratios of two-person DNA mixtures interpreted using semi- and fully continuous systems

In the paper, "Probabilistic approaches to interpreting two-person DNA mixtures from post-coital specimens" [1], we analysed 102 two-person DNA samples from simulated mixtures and male-female and male-male post-coital specimens. We report here data on profile characteristics of these samples and likelihood ratios (LRs) generated using semi- and fully continuous systems. Both log10 LRs from true and non-contributor tests are presented. These data may supplement studies comparing performance of different probabilistic systems for DNA evidence interpretation.

Probabilistic approaches to interpreting two-person DNA mixtures from post-coital specimens

Biological samples submitted for sexual assault investigation typically involve mixtures of DNA from the victim and the assailant/s. Providing a statistical weight to such evidence may be mathematically complex and may be affected by subjective judgment of a human analyst. Software tools have been developed to address these issues. To contribute towards improving the system for routine DNA testing of sexual assault cases, we evaluated two likelihood ratio (LR) approaches: a semi-continuous model using LRmix Studio and a fully continuous approach employed in STRmix™ for interpreting two-person DNA mixtures. LRs conditioned on the presence of the receptive partner's DNA were calculated for a total of 102 two-person DNA samples from simulated mixtures and various post-coital samples. Our results highlight the importance of maximising information provided into the LR calculation to generate strong support for the true hypothesis. This can be achieved by recovering sufficient DNA from a sample to minimise risk of drop-out and increase peak intensities and by implementing a statistical model that utilises as much of the electropherogram information as possible. LRmix is open-source and can handle profiles with allelic drop-out and drop-ins, however stuttering is not modelled and requires manual removal by a DNA analyst especially for mixtures with low template components. STRmix™ makes effective use of all available information by incorporating into its biological model complicating aspects of a DNA profile such as degradation, allele drop-out and drop-in, stutters, and peak height variability.

Inter-sample contamination detection using mixture deconvolution comparison

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

The Probabilistic Genotyping Software STRmix: Utility and Evidence for its Validity

Forensic DNA interpretation is transitioning from manual interpretation based usually on binary decision-making toward computer-based systems that model the probability of the profile given different explanations for it, termed probabilistic genotyping (PG). Decision-making by laboratories to implement probability-based interpretation should be based on scientific principles for validity and information that supports its utility, such as criteria to support admissibility. The principles behind STRmix™ are outlined in this study and include standard mathematics and modeling of peak heights and variability in those heights. All PG methods generate a likelihood ratio (LR) and require the formulation of propositions. Principles underpinning formulations of propositions include the identification of reasonably assumed contributors. Substantial data have been produced that support precision, error rate, and reliability of PG, and in particular, STRmix™. A current issue is access to the code and quality processes used while coding. There are substantial data that describe the performance, strengths, and limitations of STRmix™, one of the available PG software.

Development and validation of open-source software for DNA mixture interpretation based on a quantitative continuous model

In criminal investigations, forensic scientists need to evaluate DNA mixtures. The estimation of the number of contributors and evaluation of the contribution of a person of interest (POI) from these samples are challenging. In this study, we developed a new open-source software “Kongoh” for interpreting DNA mixture based on a quantitative continuous model. The model uses quantitative information of peak heights in the DNA profile and considers the effect of artifacts and allelic drop-out. By using this software, the likelihoods of 1–4 persons’ contributions are calculated, and the most optimal number of contributors is automatically determined; this differs from other open-source software. Therefore, we can eliminate the need to manually determine the number of contributors before the analysis. Kongoh also considers allele- or locus-specific effects of biological parameters based on the experimental data. We then validated Kongoh by calculating the likelihood ratio (LR) of a POI’s contribution in true contributors and non-contributors by using 2–4 person mixtures analyzed through a 15 short tandem repeat typing system. Most LR values obtained from Kongoh during true-contributor testing strongly supported the POI’s contribution even for small amounts or degraded DNA samples. Kongoh correctly rejected a false hypothesis in the non-contributor testing, generated reproducible LR values, and demonstrated higher accuracy of the estimated number of contributors than another software based on the quantitative continuous model. Therefore, Kongoh is useful in accurately interpreting DNA evidence like mixtures and small amounts or degraded DNA samples.

Characterization of degradation and heterozygote balance by simulation of the forensic DNA analysis process

Simulation experiments were used to show the impact of varying extraction efficiency, aliquot proportion, and PCR efficiency on the heterozygote balance of a range of diploid and haploid cells. Reducing either parameters introduces variance. It is well-known that the variance in heterozygote balance increases as the amount of DNA is reduced. Surprisingly the distribution is in fact diamond shaped — the variance start to decrease at very low amounts of DNA. Simulations suggest that pristine diluted DNA is an acceptable approximation in validations to infer heterozygote balance. However, the difference in distribution of the variance between diploid and haploid cell types may, under some circumstances, need to be considered in statistical models. Finally, we exemplify how simulations can be used to predict the outcome of PCR for degraded samples. Visualizing the predicted DNA profile as an electropherogram can help to identify the best approach for sample processing.

Evaluation of forensic DNA mixture evidence: protocol for evaluation, interpretation, and statistical calculations using the combined probability of inclusion

Background

The evaluation and interpretation of forensic DNA mixture evidence faces greater interpretational challenges due to increasingly complex mixture evidence. Such challenges include: casework involving low quantity or degraded evidence leading to allele and locus dropout; allele sharing of contributors leading to allele stacking; and differentiation of PCR stutter artifacts from true alleles. There is variation in statistical approaches used to evaluate the strength of the evidence when inclusion of a specific known individual(s) is determined, and the approaches used must be supportable. There are concerns that methods utilized for interpretation of complex forensic DNA mixtures may not be implemented properly in some casework. Similar questions are being raised in a number of U.S. jurisdictions, leading to some confusion about mixture interpretation for current and previous casework.

Results

Key elements necessary for the interpretation and statistical evaluation of forensic DNA mixtures are described. Given the most common method for statistical evaluation of DNA mixtures in many parts of the world, including the USA, is the Combined Probability of Inclusion/Exclusion (CPI/CPE). Exposition and elucidation of this method and a protocol for use is the focus of this article. Formulae and other supporting materials are provided.

Conclusions

Guidance and details of a DNA mixture interpretation protocol is provided for application of the CPI/CPE method in the analysis of more complex forensic DNA mixtures. This description, in turn, should help reduce the variability of interpretation with application of this methodology and thereby improve the quality of DNA mixture interpretation throughout the forensic community.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-016-0429-7) contains supplementary material, which is available to authorized users.

Stabbing simulations and DNA transfer

Technical developments have made it possible to analyze very low amounts of DNA. This has many advantages, but the drawback of this technological progress is that interpretation of the results becomes increasingly complex: the number of mixed DNA profiles increased relatively to single source DNA profiles and stochastic effects in the DNA profile, such as drop-in and drop-out, are more frequently observed. Moreover, the relevance of low template DNA material regarding the activities alleged is not as straightforward as it was a few years ago, when for example large quantities of blood were recovered. The possibility of secondary and tertiary transfer is now becoming an issue. The purpose of this research is twofold: first, to study the transfer of DNA from the handler and secondly, to observe if handlers would transfer DNA from persons closely connected to them. We chose to mimic cases where the offender would attack a person with a knife. As a first approach, we envisaged that the defense would not give an alternative explanation for the origin of the DNA. In our transfer experiments (4 donors, 16 experiments each, 64 traces), 3% of the traces were single DNA profiles. Most of the time, the DNA profile of the person handling the knife was present as the major profile: in 83% of the traces the major contributor profile corresponded to the stabber's DNA profile (in single stains and mixtures). Mixture with no clear major/minor fraction (12%) were observed. 5% of the traces were considered of insufficient quality (more than 3 contributors, presence of a few minor peaks). In that case, we considered that the stabber's DNA was absent. In our experiments, no traces allowed excluding the stabber, however it must be noted that precautions were taken to minimize background DNA as knives were cleaned before the experiments. DNA profiles of the stabber's colleagues were not observed. We hope that this study will allow for a better understanding of the transfer mechanism and of how to assess and describe results given activity level propositions. In this preliminary research, we have focused on the transfer of DNA on the hand of the person. Besides, more research is needed to assign the probability of the results given an alternative activity proposed by the defense, for instance when the source of the DNA is not contested, but that the activities are.

Uncertainty in the number of contributors in the proposed new CODIS set

The probability that multiple contributors are detected within a forensic DNA profile improves as more highly polymorphic loci are analysed. The assignment of the correct number of contributors to a profile is important when interpreting the DNA profiles. In this work we investigate the probability of a mixed DNA profile appearing as having originated from a fewer number of contributors for the African American, Asian, Caucasian and Hispanic US populations. We investigate a range of locus configurations from the proposed new CODIS set. These theoretical calculations are based on allele frequencies only and ignore peak heights. We show that the probability of a higher order mixture (five or six contributors) appearing as having originated from one less individual is high. This probability decreases as the number of loci tested increases.

The interpretation of single source and mixed DNA profiles

A method for interpreting autosomal mixed DNA profiles based on continuous modelling of peak heights is described. MCMC is applied with a model for allelic and stutter heights to produce a probability for the data given a specified genotype combination. The theory extends to handle any number of contributors and replicates, although practical implementation limits analyses to four contributors. The probability of the peak data given a genotype combination has proven to be a highly intuitive probability that may be assessed subjectively by experienced caseworkers. Whilst caseworkers will not assess the probabilities per se, they can broadly judge genotypes that fit the observed data well, and those that fit relatively less well. These probabilities are used when calculating a subsequent likelihood ratio. The method has been trialled on a number of mixed DNA profiles constructed from known contributors. The results have been assessed against a binary approach and also compared with the subjective judgement of an analyst.