Interpreting Y chromosome STR haplotype mixture

Ge, Jianye; Budowle, Bruce; Chakraborty, Ranajit

doi:10.1016/j.legalmed.2010.02.003

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Volume 12, Issue 3 , Pages 137-143, May 2010

Interpreting Y chromosome STR haplotype mixture

Jianye Ge
- Institute of Investigative Genetics, University of North Texas Health Science Center, Fort Worth, TX 76107, USA
- Department of Forensic and Investigative Genetics, University of North Texas Health Science Center, Ft Worth, TX 76107, USA
- Corresponding author. Tel.: +1 817 735 2773; fax: +1 817 735 5016.
Bruce Budowle
- Institute of Investigative Genetics, University of North Texas Health Science Center, Fort Worth, TX 76107, USA
- Department of Forensic and Investigative Genetics, University of North Texas Health Science Center, Ft Worth, TX 76107, USA
Ranajit Chakraborty
- Institute of Investigative Genetics, University of North Texas Health Science Center, Fort Worth, TX 76107, USA
- Department of Forensic and Investigative Genetics, University of North Texas Health Science Center, Ft Worth, TX 76107, USA
- Center for Genome Information, Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, OH, 45267, USA

Received 4 September 2009; received in revised form 9 November 2009; accepted 3 February 2010. published online 26 March 2010.

Abstract

Mixture interpretation is a challenging problem in forensic DNA analyses. The interpretation of Y short tandem repeat (STR) haplotype mixtures, due to a lack of recombination, differs somewhat from that of the autosomal DNA markers and is more complex. We describe approaches for calculating the probability of exclusion (PE) and likelihood ratio (LR) methods to interpret Y-STR mixture evidence with population substructure incorporated. For a mixture sample, first, all possible contributor haplotypes in a reference database are listed as a candidate list. The PE is the complement of the summation of the frequencies of haplotypes in the candidate list. The LR method compares the probabilities of the evidence given alternative hypotheses. The hypotheses are possible explanations for the mixture. Population substructure may be further incorporated in likelihood calculation. The maximum number of contributors is based on the candidate list and the computing complexity is polynomial. Additionally, mixtures were simulated by combining two or three 16 Y-STR marker haplotypes derived from the US forensic Y-STR database. The average PE was related to the size of database. With a database comprised of 500 haplotypes an average PE value of at least 0.995 can be obtained for two-person mixtures. The PE decreases with an increasing number of contributors to the mixture. Using the total sample population, the average number of candidate haplotypes of two-person mixtures is 3.73 and 95% mixtures have less than or equal to 10 candidate haplotypes. More than 98.7% of two-person mixtures can only be explained by the haplotype combinations that mixtures are composed. These values are generally higher for three-person mixtures. A small proportion of three-person mixture can also be explained by only two haplotypes.

Keywords: Y chromosome, Short tandem repeats, DNA mixture, Likelihood ratio, Probability of exclusion, Evidence interpretation