Advertisement

The interpretation of mixed DNA profiles from a mother, father, and child trio

Published:October 11, 2019DOI:https://doi.org/10.1016/j.fsigen.2019.102175

      Highlights

      • Mixtures of a mother, father, child trio are examined using the software STRmix™.
      • Parent/child allele sharing often results in artificially high or low LRs.
      • User-informed mixture proportions and an assumed donor parent assists interpretation.
      • The distribution of LRs for true and false donors is reported.

      Abstract

      We report the interpretation of three-person mixed DNA profiles constructed from DNA from one mother, father, and child trio using the probabilistic genotyping software STRmix™. A total of 40 mixtures were examined, with varying total template and mixture proportions of the three contributors. In addition, mixtures were artificially degraded at four different rates to test the effects of degradation on the interpretation of mother, father and child trios. A total of 560 STRmix™ analyses were undertaken, examining four different interpretation strategies. Reasonable results were only achieved by conditioning on one parent as an assumed donor and applying a user-informed prior to the mixture proportion of both parents.
      For each of the 40 amplified mixtures, 10,000 non-donors were compared, conditioning on one parent and applying a user-informed prior to the mixture proportion of both parents. This leads to 800,000 non-donor tests.
      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Forensic Science International: Genetics
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Lindley D.V.
        A problem in forensic science.
        Biometrika. 1977; 64: 207-213
        • Evett I.W.
        What is the probability that this blood came from that person? A meaningful question.
        J. Forensic Sci. Soc. 1983; 23: 35-39
        • Robertson B.
        • Vignaux G.A.
        • Berger C.E.H.
        Interpreting Evidence: Evaluating Forensic Science in the Courtroom: Second Edition.
        2016
        • Evett I.W.
        Evaluating DNA profiles in a case where the defence is “it was my brother”.
        J. Forensic Sci. Soc. 1992; 32: 5-14
        • Evett I.W.
        • Weir B.S.
        Interpreting DNA Evidence – Statistical Genetics for Forensic Scientists.
        Sinauer Associates, Inc., Sunderland1998
        • Buckleton J.S.
        • Triggs C.M.
        • Walsh S.J.
        Forensic DNA Evidence Interpretation.
        CRC Press, Boca Raton, Florida2004
        • Puch-Solis R.
        • Pope S.
        • Evett I.
        Calculating likelihood ratios for a mixed DNA profile when a contribution from a genetic relative of a suspect is proposed.
        Sci. Justice. 2010; 50: 205-209
        • Egeland T.
        • Dørum G.
        • Vigeland M.D.
        • Sheehan N.A.
        Mixtures with relatives: a pedigree perspective.
        Forensic Sci. Int. Genet. 2014; 10: 49-54
        • Hu Y.-Q.
        • Fung W.K.
        Interpreting DNA mixtures with the presence of relatives.
        Int. J. Legal Med. 2003; 117: 39-45
        • Coble M.D.
        • Bright J.-A.
        Probabilistic genotyping software: an overview.
        Forensic Sci. Int. Genet. 2019; 38: 219-224
        • Taylor D.
        • Bright J.-A.
        • Buckleton J.
        Considering relatives when assessing the evidential strength of mixed DNA profiles.
        Forensic Sci. Int. Genet. 2014; 13: 259-263
        • Greenspoon S.A.
        • Schiermeier-Wood L.
        • Jenkins B.C.
        Establishing the limits of TrueAllele® casework: a validation study.
        J. Forensic Sci. 2015; 60: 1263-1276
        • Benschop C.C.G.
        • Nijveld A.
        • Duijs F.E.
        • Sijen T.
        An assessment of the performance of the probabilistic genotyping software EuroForMix: trends in likelihood ratios and analysis of Type I & II errors.
        Forensic Sci. Int. Genet. 2019; 42: 31-38
      1. SWGDAM, Guidelines for the Validation of Probabilistic Genotyping Systems http://media.wix.com/ugd/4344b0_22776006b67c4a32a5ffc04fe3b56515.pdf. Accessed 22nd August 2016.

        • Coble M.D.
        • Buckleton J.
        • Butler J.M.
        • Egeland T.
        • Fimmers R.
        • Gill P.
        • et al.
        DNA Commission of the International Society for Forensic Genetics: recommendations on the validation of software programs performing biostatistical calculations for forensic genetics applications.
        Forensic Sci. Int. Genet. 2016; 25: 191-197
        • President’s Council of Advisors on Science and Technology
        Forensic Science in Criminal Courts: Ensuring Scientific Validity of Feature-Comparison Methods.
        2016 (Accessed 22nd April 2017)
        • President’s Council of Advisors on Science and Technology
        An Addendum to the PCAST Report on Forensic Science in Criminal Courts.
        2016 (Accessed 20th July 2017)
        • Bright J.-A.
        • Richards R.
        • Kruijver M.
        • Kelly H.
        • McGovern C.
        • Magee A.
        • et al.
        Internal validation of STRmixTM; A multi laboratory response to PCAST.
        Forensic Sci. Int. Genet. 2018; 34: 11-24
        • McNevin D.
        • Wright K.
        • Chaseling J.
        • Barash M.
        • Commentary on: Bright
        • et al.
        Internal validation of STRmix; A multi laboratory response to PCAST.
        Forensic Sci. Int. Genet. 2018; 34 (Forensic Science International: Genetics): 11-24
        • Butler J.M.
        • Kline M.C.
        • Coble M.D.
        NIST interlaboratory studies involving DNA mixtures (MIX05 and MIX13): variation observed and lessons learned.
        Forensic Sci. Int. Genet. 2018; 37: 81-94
        • Buckleton J.S.
        • Bright J.-A.
        • Cheng K.
        • Budowle B.
        • Coble M.D.
        NIST interlaboratory studies involving DNA mixtures (MIX13): a modern analysis.
        Forensic Sci. Int. Genet. 2018; 37: 172-179
        • Walsh P.S.
        • Metzger D.A.
        • Higuchi R.
        Chelex® 100 as a medium for simple extraction of DNA for PCR-based typing from forensic material.
        Biotechniques. 1991; 10: 506-513
        • Taylor D.
        • Bright J.-A.
        • Buckleton J.
        The interpretation of single source and mixed DNA profiles.
        Forensic Sci. Int. Genet. 2013; 7: 516-528
        • Moretti T.R.
        • Moreno L.I.
        • Smerick J.B.
        • Pignone M.L.
        • Hizon R.
        • Buckleton J.S.
        • et al.
        Population data on the expanded CODIS core STR loci for eleven populations of significance for forensic DNA analyses in the United States.
        Forensic Sci. Int. Genet. 2016; 25: 175-181
        • Taylor D.
        • Buckleton J.
        • Bright J.-A.
        Does the use of probabilistic genotyping change the way we should view sub-threshold data?.
        Aust. J. Forensic Sci. 2017; 49: 78-92
        • Taylor D.
        • Buckleton J.
        • Evett I.
        Testing likelihood ratios produced from complex DNA profiles.
        Forensic Sci. Int. Genet. 2015; 16: 165-171
        • Bright J.-A.
        • Richards R.
        • Kruijver M.
        • Kelly H.
        • McGovern C.
        • Magee A.
        • et al.
        Internal validation of STRmix™ – a multi laboratory response to PCAST.
        Forensic Sci. Int. Genet. 2018; 34: 11-24
        • Scientific Working Group on DNA Analysis Methods
        Recommendations of the SWGDAM Ad Hoc Working Group on Genotyping Results Reported As Likelihood Ratios.
        2018 (Accessed 8th November 2018)

      Linked Article