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Demonstration of Protein-Based Human Identification Using the Hair Shaft Proteome

NCJ Number
Date Published
September 2016
26 pages
This project demonstrates that the genetic variation in protein in the form of single amino acid polymorphisms can be used to infer the status of non-synonymous single nucleotide polymorphism alleles.
This is significant for forensic science, because human identification from biological material is largely dependent on the ability to characterize genetic polymorphisms in DNA. DNA, however, can degrade in the environment, sometimes to below the level at which it can be amplified by PCR. Protein, on the other hand, is chemically more robust than DNA, persisting for longer periods. In order to test whether protein analysis can yield benefits for human identification, this project used mass spectrometry-based shotgun proteomics to characterize hair shaft proteins in 66 European-American subjects and in an additional 10 subjects with African ancestry. Genetically variant peptides were also identified in hair shaft datasets from six archaeological skeletal remains (up to 260 years old). This study succeeded in demonstrating that quantifiable measures of identity discrimination and biogeography background can be obtained from detecting genetically variant peptides in hair shaft protein, including hair from bioarchaeological contexts. For the European-American subjects, a total of 596 single nucleotide polymorphism alleles were correctly imputed in 32 loci from 22 genes of subjects’ DNA and directly validated using Sanger sequencing. Estimates of the probability of resulting individual non-synonymous single nucleotide polymorphism allelic profiles in the European population resulted in a maximum power of discrimination of 1 in 12,500, using the product rule. Imputed non-synonymous single nucleotide polymorphism profiles from European-American subjects were considerably less frequent in the African population (maximum likelihood ratio of 11,000). 5 figures and 94 references

Date Published: September 1, 2016