An Evaluation of the Effect Of Degradation on IrisPlex SNPs

Abstract

The information from short tandem repeats (STRs), the current standard forensic DNA typing technology, does not always result in identification. In these cases, there are other informative markers in DNA that can be used to help generate investigative leads, one of which is single nucleotide polymorphisms (SNPs). One of the uses of SNPs is for phenotype determination. Among the phenotypic characteristics that can be predicted is eye color. A commonly used tool for eye color prediction is the free, online statistical prediction model IrisPlex, which includes 6 SNPs known to control eye color. While SNPs can be useful, they, like all DNA, are susceptible to degradation. Research on the effect of degradation on SNPs has already been done, but much of it uses massively parallel sequencing (MPS), which is not currently feasible for most crime labs. A stronger consensus is needed regarding the value of SNPs with instrumentation and techniques available to crime labs, such as real-time PCR. Because SNPs are such small fragments, they will be highly resistant to the effects of degradation. Buccal swabs from 3 donors were degraded using two methods: UV exposure and burial in soil. Modern teeth and ancient remains found in the Gobi Desert were also analyzed to represent more natural degradation. DNA was extracted and quantified, and the degradation index was assessed. SNP profiles were generated using qPCR and input into IrisPlex to get an eye color prediction. The SNPs were found to be resistant to degradation and the degradation index was not an indicator of SNP assay success or IrisPlex prediction accuracy. The intermediate eye colors did not produce as many accurate predictions as the brown eyes, which reinforces the need to focus on improving prediction accuracy for intermediate eye colors. The TaqMan assays are an option to generate the SNP data; however, there are other methods that likely work better, such as sequencing via capillary electrophoresis

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