Literature DB >> 23601717

DNA mixture genotyping by probabilistic computer interpretation of binomially-sampled laser captured cell populations: combining quantitative data for greater identification information.

Jack Ballantyne1, Erin K Hanson, Mark W Perlin.   

Abstract

Two person DNA admixtures are frequently encountered in criminal cases and their interpretation can be challenging, particularly if the amount of DNA contributed by both individuals is approximately equal. Due to an inevitable degree of uncertainty in the constituent genotypes, reduced statistical weight is given to the mixture evidence compared to that expected from the constituent single source contributors. The ultimate goal of mixture analysis, then, is to precisely discern the constituent genotypes and here we posit a novel strategy to accomplish this. We hypothesised that LCM-mediated isolation of multiple groups of cells ('binomial sampling') from the admixture would create separate cell sub-populations with differing constituent weight ratios. Furthermore we predicted that interpreting the resulting DNA profiling data by the quantitative computer-based TrueAllele® interpretation system would result in an efficient recovery of the constituent genotypes due to newfound abilities to compute a maximum LR from sub-samples with skewed weight ratios, and to jointly interpret all possible pairings of sub-samples using a joint likelihood function. As a proof of concept, 10 separate cell samplings of size 20 recovered by LCM from each of two 1:1 buccal cell mixtures were DNA-STR profiled using a specifically developed LCN methodology, with the data analyzed by the TrueAllele® Casework system. In accordance with the binomial sampling hypothesis, the sub-samples exhibited weight ratios that were well dispersed from the 50% center value (50±35% at the 95% level). The maximum log(LR) information for a genotype inferred from a single 20 cell sample was 18.5 ban, with an average log(LR) information of 11.7 ban. Co-inferring genotypes using a joint likelihood function with two sub-samples essentially recovered the full genotype information. We demonstrate that a similar gain in genotype information can be obtained with standard (28-cycle) PCR conditions using the same joint interpretation methods. Finally, we discuss the implications of this work for routine forensic practice.
Copyright © 2012 Forensic Science Society. Published by Elsevier Ireland Ltd. All rights reserved.

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Year:  2012        PMID: 23601717     DOI: 10.1016/j.scijus.2012.04.004

Source DB:  PubMed          Journal:  Sci Justice        ISSN: 1355-0306            Impact factor:   2.124


  9 in total

1.  Reduced reaction volumes and increased Taq DNA polymerase concentration improve STR profiling outcomes from a real-world low template DNA source: telogen hairs.

Authors:  Dennis McNevin; Janette Edson; James Robertson; Jeremy J Austin
Journal:  Forensic Sci Med Pathol       Date:  2015-05-22       Impact factor: 2.007

2.  Simplification of complex DNA profiles using front end cell separation and probabilistic modeling.

Authors:  Nancy A Stokes; Cristina E Stanciu; Emily R Brocato; Christopher J Ehrhardt; Susan A Greenspoon
Journal:  Forensic Sci Int Genet       Date:  2018-07-17       Impact factor: 4.882

3.  MaSTR™: an effective probabilistic genotyping tool for interpretation of STR mixtures associated with differentially degraded DNA.

Authors:  Mitchell M Holland; Teresa M Tiedge; Abigail J Bender; Sidney A Gaston-Sanchez; Jennifer A McElhoe
Journal:  Int J Legal Med       Date:  2022-01-29       Impact factor: 2.686

4.  Analysis of red autofluorescence (650-670nm) in epidermal cell populations and its potential for distinguishing contributors to 'touch' biological samples.

Authors:  Cristina E Stanciu; M Katherine Philpott; Eduardo E Bustamante; Ye Jin Kwon; Christopher J Ehrhardt
Journal:  F1000Res       Date:  2016-02-16

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

Authors:  Kaitlin Huffman; Erin Hanson; Jack Ballantyne
Journal:  Genes (Basel)       Date:  2022-06-22       Impact factor: 4.141

6.  TrueAllele casework on Virginia DNA mixture evidence: computer and manual interpretation in 72 reported criminal cases.

Authors:  Mark W Perlin; Kiersten Dormer; Jennifer Hornyak; Lisa Schiermeier-Wood; Susan Greenspoon
Journal:  PLoS One       Date:  2014-03-25       Impact factor: 3.240

7.  Verifying likelihoods for low template DNA profiles using multiple replicates.

Authors:  Christopher D Steele; Matthew Greenhalgh; David J Balding
Journal:  Forensic Sci Int Genet       Date:  2014-07-10       Impact factor: 4.882

8.  New York State TrueAllele ® casework validation study.

Authors:  Mark W Perlin; Jamie L Belrose; Barry W Duceman
Journal:  J Forensic Sci       Date:  2013-07-18       Impact factor: 1.832

9.  Inclusion probability for DNA mixtures is a subjective one-sided match statistic unrelated to identification information.

Authors:  Mark William Perlin
Journal:  J Pathol Inform       Date:  2015-10-28
  9 in total

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