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      Y‐STR mixture deconvolution by single‐cell analysis

      1 , 1 , 2 , 3 , 1 , 2 , 3
      Journal of Forensic Sciences
      Wiley

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          Abstract

          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.

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          Most cited references42

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          Y chromosome haplotype reference database (YHRD): update.

          The freely accessible YHRD (Y Chromosome Haplotype Reference Database, www.yhrd.org) is designed to store Y chromosome haplotypes from global populations and had replaced three earlier database versions collecting European, Asian and US American Y chromosomes separately. The focus is to disseminate haplotype frequency data to forensic analysts, researchers, and to everyone who is interested in historical and family genetics. YHRD considers reduction of the available number of polymorphisms on the Y chromosome to a uniform data string of 11 highly variable Y-STR loci as an efficient way to rapidly screen many world populations and to make their Y chromosome profiles comparable. Typing of the YHRD 11-locus core set is facilitated by commercial products, namely diagnostic PCR kits, and endorsed by scientific and forensic analyst's societies as ISFG or SWGDAM. YHRD is structured by the assignment of each submitted population sample to a set of populations sharing a common linguistic, demographic, genetic or geographic background (metapopulations). This principle facilitates the statistical evaluation of haplotype matches due to a significant enlargement of sample sizes. With the rapid growth of the database the definition of homogeneous metapopulations is now also feasible solely on the basis of the genetic data as exemplified for the whole dataset of YHRD, release 19 (August 2006). Large sample numbers within genetically defined metapopulations also allows the development of biostatistical methods to estimate the frequency of unobserved or rare haplotypes ("haplotype frequency surveying method"). Essential for the YHRD project is its collaborative character relying on the engagement of individual laboratories to make their data accessible via YHRD and to share the YHRD standards regarding data quality.
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            EuroForMix: An open source software based on a continuous model to evaluate STR DNA profiles from a mixture of contributors with artefacts.

            We have released a software named EuroForMix to analyze STR DNA profiles in a user-friendly graphical user interface. The software implements a model to explain the allelic peak height on a continuous scale in order to carry out weight-of-evidence calculations for profiles which could be from a mixture of contributors. Through a properly parameterized model we are able to do inference on mixture proportions, the peak height properties, stutter proportion and degradation. In addition, EuroForMix includes models for allele drop-out, allele drop-in and sub-population structure. EuroForMix supports two inference approaches for likelihood ratio calculations. The first approach uses maximum likelihood estimation of the unknown parameters. The second approach is Bayesian based which requires prior distributions to be specified for the parameters involved. The user may specify any number of known and unknown contributors in the model, however we find that there is a practical computing time limit which restricts the model to a maximum of four unknown contributors. EuroForMix is the first freely open source, continuous model (accommodating peak height, stutter, drop-in, drop-out, population substructure and degradation), to be reported in the literature. It therefore serves an important purpose to act as an unrestricted platform to compare different solutions that are available. The implementation of the continuous model used in the software showed close to identical results to the R-package DNAmixtures, which requires a HUGIN Expert license to be used. An additional feature in EuroForMix is the ability for the user to adapt the Bayesian inference framework by incorporating their own prior information.
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              Is Open Access

              Validating TrueAllele® DNA mixture interpretation.

              DNA mixtures with two or more contributors are a prevalent form of biological evidence. Mixture interpretation is complicated by the possibility of different genotype combinations that can explain the short tandem repeat (STR) data. Current human review simplifies this interpretation by applying thresholds to qualitatively treat STR data peaks as all-or-none events and assigning allele pairs equal likelihood. Computer review, however, can work instead with all the quantitative data to preserve more identification information. The present study examined the extent to which quantitative computer interpretation could elicit more identification information than human review from the same adjudicated two-person mixture data. The base 10 logarithm of a DNA match statistic is a standard information measure that permits such a comparison. On eight mixtures having two unknown contributors, we found that quantitative computer interpretation gave an average information increase of 6.24 log units (min = 2.32, max = 10.49) over qualitative human review. On eight other mixtures with a known victim reference and one unknown contributor, quantitative interpretation averaged a 4.67 log factor increase (min = 1.00, max = 11.31) over qualitative review. This study provides a general treatment of DNA interpretation methods (including mixtures) that encompasses both quantitative and qualitative review. Validation methods are introduced that can assess the efficacy and reproducibility of any DNA interpretation method. An in-depth case example highlights 10 reasons (at 10 different loci) why quantitative probability modeling preserves more identification information than qualitative threshold methods. The results validate TrueAllele(®) DNA mixture interpretation and establish a significant information improvement over human review. © 2011 American Academy of Forensic Sciences.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Journal of Forensic Sciences
                Journal of Forensic Sciences
                Wiley
                0022-1198
                1556-4029
                January 2023
                October 2022
                January 2023
                : 68
                : 1
                : 275-288
                Affiliations
                [1 ] Graduate Program in Chemistry, Department of Chemistry University of Central Florida Orlando Florida USA
                [2 ] National Center for Forensic Science Orlando Florida USA
                [3 ] Department of Chemistry University of Central Florida Orlando Florida USA
                Article
                10.1111/1556-4029.15150
                36183153
                1a12c509-b9bf-43ac-823d-e27c6c908c62
                © 2023

                http://onlinelibrary.wiley.com/termsAndConditions#vor

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