A collaborative study on the precision of the Markov chain Monte Carlo algorithms used for DNA profile interpretation.

Several fully continuous probabilistic genotyping software (PGS) use Markov chain Monte Carlo algorithms (MCMC) to assign weights to different proposed genotype combinations at a locus. Replicate interpretations of the same profile in these software are expected not to produce identical weights and likelihood ratio (LR) values due to the Monte Carlo aspect. This paper reports a detailed precision study under reproducibility conditions conducted as a collaborative exercise across the National Institute of Standards and Technology (NIST), Federal Bureau of Investigation (FBI), and Institute of Environmental Science and Research (ESR). Replicate interpretations generated across the three laboratories used the same input files, software version, and settings but different random number seed and different computers. This work demonstrates that using different computers to analyze replicate interpretations does not contribute to any variations in LR values. The study quantifies the magnitude of differences in the assigned LRs that is only due to run-to-run MCMC variability and addresses the potential explanations for the observed differences.

Single cell genomics applications in forensic science: Current state and future directions.

Standard methods of mixture analysis involve subjecting a dried crime scene sample to a "bulk" DNA extraction method such that the resulting isolate compromises a homogenized DNA mixture from the individual donors. If, however, instead of bulk DNA extraction, a sufficient number of individual cells from the mixed stain are subsampled prior to genetic analysis then it should be possible to recover highly probative single source, non-mixed scDNA profiles from each of the donors. This approach can detect low DNA level minor donors to a mixture that otherwise would not be identified using standard methods and can also resolve rare mixtures comprising first degree relatives and thereby also prevent the false inclusion of non-donor relatives. This literature landscape review and associated commentary reports on the history and increasing interest in current and potential future applications of scDNA in forensic genomics, and critically evaluates opportunities and impediments to further progress.

Carrying out common DNA donor analysis using DBLR™ on two or five-cell mini-mixture subsamples for improved discrimination power in complex DNA mixtures.

Probabilistic genotyping systems are able to analyse complex mixed DNA profiles and show good power to discriminate contributors from non-contributors. However, the abilities of the statistical analyses are still unavoidably bound by the quality of information being analysed. If a profile has a high number of contributors, or a contributor that is present in trace amounts, then the amount of information about those individuals in the DNA profile is limited. Recent work has shown the ability to gain better resolution of the genotypes of contributors to complex profiles using cell subsampling. This is the process of taking many sets of a limited number of cells and individually profiling each set. These 'mini-mixtures' can provide greater information about the genotypes of underlying contributors. In our work we take the resulting profiles from multiple subsamplings of complex DNA profiles in equal amounts and show how testing for, and then assuming, a common DNA donor can further improve the ability to resolve the genotypes of contributors. Using direct cell sub-sampling and statistical analysis software DBLR™, we were able to recover single source profiles of uploadable quality from five out of the six contributors of an equally proportioned mixture. Through the analysis of mixtures in this work we provide a template for carrying out common donor analysis for maximum effect.

Validation of Probabilistic Genotyping Software for Single Cell STR Analysis.

Probabilistic genotyping (PG) and its associated software has greatly aided in forensic DNA mixture analysis, with it primarily being applied to mixed DNA profiles obtained from bulk cellular extracts. However, these software applications do not always result in probative information about the identity of all donors to said mixtures/extracts. This is primarily due to mixture complexity caused by overlapping alleles and the presence of artifacts and minor donors. One way of reducing mixture complexity is to perform direct single cell subsampling of the bulk mixture prior to genotyping and interpretation. The analysis of low template DNA samples, including from single or few cells, has also benefited from the application of PG methods. With the application of PG, multiple cell subsamples originating from the same donor can be combined into a single analysis using the software replicate analysis function often resulting in full DNA profile donor information. In the present work, we demonstrate how two PG software systems, STRmixTM and EuroForMix, were successfully validated for single or few cell applications.

Y-STR mixture deconvolution by single-cell analysis.

Since Y-STR typing only amplifies male Y chromosomal DNA, it can simplify the interpretation of some DNA mixtures that contain female DNA. However, if there are multiple male contributors, mixed Y-STR DNA profiles will often be obtained. Y-STR mixture analysis cases are particularly challenging though as, currently, there are no validated probabilistic genotyping (PG) software solutions commercially available to aid in their interpretation. One approach to fully deconvoluting these challenging mixtures into their individual donors is to conduct single-cell genotyping by isolating individual cells from a mixture prior to conducting DNA typing. In this work, a physical micromanipulation technique involving a tungsten needle and direct PCR with decreased reaction volume and increased cycle number was applied to equimolar 2- and 3-person buccal cell male DNA mixtures and a mock touch DNA case scenario involving the consecutive firing of a handgun by two males. A consensus DNA profiling approach was then utilized to obtain YFiler™ Plus Y-STR haplotypes. Buccal cells were used to optimize and test the direct single-cell subsampling approach, and 2-3 person male buccal cell mixtures were fully deconvoluted into their individual donor Y-STR haplotypes. Single-cell (or agglomerated cell clump) subsampling from the gun's trigger recovered single-source Y-STR profiles from both individuals who fired the gun, the owner, and the other unrelated male. Only the non-owner's DNA was found in the cells recovered from the handle. In summary, direct single-cell subsampling as described represents a potential simple way to analyze and interpret Y-STR mixtures.

Probabilistic Genotyping of Single Cell Replicates from Mixtures Involving First-Degree Relatives Prevents the False Inclusions of Non-Donor Relatives.

Analysis of complex DNA mixtures comprised of related individuals requires a great degree of care due to the increased risk of falsely including non-donor first-degree relatives. Although alternative likelihood ratio (LR) propositions that may aid in the analysis of these difficult cases can be employed, the prior information required for their use is not always known, nor do these alternative propositions always prevent false inclusions. For example, with a father/mother/child mixture, conditioning the mixture on the presence of one of the parents is recommended. However, the definitive presence of the parent(s) is not always known and an assumption of their presence in the mixture may not be objectively justifiable. Additionally, the high level of allele sharing seen with familial mixtures leads to an increased risk of underestimating the number of contributors (NOC) to a mixture. Therefore, fully resolving and identifying each of the individuals present in familial mixtures and excluding related non-donors is an important goal of the mixture deconvolution process and can be of great investigative value. Here, firstly, we further investigated and confirmed the problems encountered with standard bulk analysis of familial mixtures and demonstrated the ability of single cell analysis to fully distinguish first-degree relatives (FDR). Then, separation of each of the individual donors via single cell analysis was carried out by a combination of direct single cell subsampling (DSCS), enhanced DNA typing, and probabilistic genotyping, and applied to three complex familial 4-person mixtures resulting in a probative gain of LR for all donors and an accurate determination of the NOC. Significantly, non-donor first-degree relatives that were falsely included (LRs > 102−108) by a standard bulk sampling and analysis approach were no longer falsely included using DSCS.

Cell Subsampling Recovers Probative DNA Profile Information from Unresolvable/Undetectable Minor Donors in Mixtures.

When a minor DNA component to a binary mixture is present at a weight ratio of approximately 1:50 or less, the presence of this minor donor is undetectable (or barely detectable) by standard mixture deconvolution approaches. In an attempt to retrieve probative minor donor DNA profile information, multiple quintuple cell subsamples were collected from a 1:50 DNA mixture using direct single cell subsampling (DSCS) paired with probabilistic genotyping (PG), the latter validated for use with single or few cells. DSCS employs a simplified micromanipulation technique paired with an enhanced DNA profiling approach, involving direct cell lysis and a sensitive PCR process, to genotype individual cells. Multiple five-cell subsamples were used to interrogate sufficient cells from the mixture such that some of the created 5-cell "mini-mixture" subsamples contained a cell from the minor donor. The latter mini-mixture subsamples, which now comprised weight ratios of 1:4 as opposed to the bulk mixture 1:50, were analyzed with the PG systems STRmixTM and EuroForMix resulting in a significant probative gain of information, (LR ≅ 1011, compared to standard bulk mixture PG methods, LR ≅ 101-102).

Probabilistic genotyping of single cell replicates from complex DNA mixtures recovers higher contributor LRs than standard analysis.

DNA mixtures are a common source of crime scene evidence and are often one of the more difficult sources of biological evidence to interpret. With the implementation of probabilistic genotyping (PG), mixture analysis has been revolutionized allowing previously unresolvable mixed profiles to be analyzed and probative genotype information from contributors to be recovered. However, due to allele overlap, artifacts, or low-level minor contributors, genotype information loss inevitably occurs. In order to reduce the potential loss of significant DNA information from donors in complex mixtures, an alternative approach is to physically separate individual cells from mixtures prior to performing DNA typing thus obtaining single source profiles from contributors. In the present work, a simplified micro-manipulation technique combined with enhanced single-cell DNA typing was used to collect one or few cells, referred to as direct single-cell subsampling (DSCS). Using this approach, single and 2-cell subsamples were collected from 2 to 6 person mixtures. Single-cell subsamples resulted in single source DNA profiles while the 2-cell subsamples returned either single source DNA profiles or new mini-mixtures that are less complex than the original mixture due to the presence of fewer contributors. PG (STRmix™) was implemented, after appropriate validation, to analyze the original bulk mixtures, single source cell subsamples, and the 2-cell mini mixture subsamples from the original 2-6-person mixtures. PG further allowed replicate analysis to be employed which, in many instances, resulted in a significant gain of genotype information such that the returned donor likelihood ratios (LRs) were comparable to that seen in their single source reference profiles (i.e., the reciprocal of their random match probabilities). In every mixture, the DSCS approach gave improved results for each donor compared to standard bulk mixture analysis. With the 5- and 6- person complex mixtures, DSCS recovered highly probative LRs (≥1020) from donors that had returned non-probative LRs (<103) by standard methods.

Recovery of single source DNA profiles from mixtures by direct single cell subsampling and simplified micromanipulation.

Deconvolution of forensic DNA mixtures into their individual component DNA (geno)types is of great investigative value, though often complex and difficult. Two-person mixtures comprising a major and minor contributor are often easily interpreted although, when the DNA ratio of the two individuals is approximately equal (~1:1), deconvolution and interpretation becomes much more difficult. To address this issue, a physical separation of individual-, two- or three- cell subsamples prior to autosomal STR analysis was performed using a simplified micromanipulation technique paired with a decreased reaction volume and increased cycle number PCR. Using this method, single and multiple buccal epithelial cells were collected from a 1:1 two-person mixture (i.e. from individual 'A' and 'B') and directly amplified, omitting standard DNA extraction and purification steps. Single cell subsamples resulted in partial single-source profiles for both contributors while, in accordance with expectations of a quasi-binomial sampling schema, two- and three-cell subsamples resulted in single source informative partial profiles of individual A and individual B as well as complete consensus profiles, and equally mixed 1:1 (2-cell subsamples) and 2:1 (3-cell subsamples) admixed profiles of individual A and B.This proof-of-concept approach shows promise in permitting the DNA deconvolution of mixed samples where the individual contributors are present in similar amounts that would otherwise be difficult to interpret, resulting in an increase in evidentiary value. The subsampling approach can be readily investigated for DNA casework applications without additional investment in costly, new equipment, requiring only a stereo microscope and a tungsten needle.