Evaluation of the IrisPlex DNA-based eye color prediction assay in a United States population
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- 作者：Gina M. Dembinski ; Christine J. Picard
- 关键词：SNP ; DNA phenotyping ; Forensic ; Eye color prediction ; IrisPlex
- 刊名：Forensic Science International: Genetics
- 出版年：March, 2014
- 年：2014
- 卷：9
- 期：Complete
- 页码：111-117
- 全文大小：730 K
文摘
DNA phenotyping is a rapidly developing area of research in forensic biology. Externally visible characteristics (EVCs) can be determined based on genotype data, specifically based on single nucleotide polymorphisms (SNPs). These SNPs are chosen based on their association with genes related to the phenotypic expression of interest, with known examples in eye, hair, and skin color traits. DNA phenotyping has forensic importance when unknown biological samples at a crime scene do not result in a criminal database hit; a phenotypic profile of the sample can therefore be used to develop investigational leads. IrisPlex, an eye color prediction assay, has previously shown high prediction rates for blue and brown eye color in a Dutch European population. The objective of this work was to evaluate its utility in a North American population. We evaluated six SNPs included in the IrisPlex assay in population sample collected from a USA college campus. We used a quantitative method of eye color classification based on (RGB) color components of digital photographs of the eye taken from each study volunteer so that each eye was placed in one of three eye color categories: brown, intermediate, or blue. Objective color classification was shown to correlate with basic human visual determination making it a feasible option for use in future prediction assay development. Using these samples and various models, the maximum prediction accuracies of the IrisPlex system after allele frequency adjustment was 58% and 95% brown and blue eye color predictions, respectively, and 11% for intermediate eye colors. Future developments should include incorporation of additional informative SNPs, specifically related to the intermediate eye color, and we recommend the use of a Bayesian approach as a prediction model as likelihood ratios can be determined for reporting purposes.