Proteomic Genotyping of Fingermark Donors With Genetically Variant Peptides

• NCJ Number: 254172
• Author(s): Trevor Borja; Noreen Karim; Zachary Goecker; Michelle Salemi; Brett Phinney; Muhammad Naeem; Robert Rice; Glendon Parker
• Date Published: September 2019
• Length: 10 pages
• Grant Number(s): DX-BN-K065
• Agencies: NIJ-Sponsored
• Publication Type: Research (Applied/Empirical); Report (Study/Research); Report (Grant Sponsored); Program/Project Description

Annotation

Since genetically variant peptides from fingermarks that contain single amino acid polymorphisms are an additional source of identifying genetic information, this study sought to discover these peptide biomarkers epidermal corneocytes from nine subjects, isolating, processing, and digesting the peptide biomarkers with trypsin and applying them to mass spectrometry.

Abstract

Proteomic genotyping detects single amino acid polymorphisms to infer the genotype of corresponding non-synonymous SNPs. Like any DNA genotype, these inferences can be used to estimate random match probability. Fingermarks are a common source of biological evidence that is sample limited and a highly variable source of identifying DNA. In the current study, the resulting proteomic and matching exome datasets were used to discover, characterize, and validate 60 genetically variant peptides. An average of 28.8 +/- 4.4 genetically variant peptides were detected from each subject, resulting in a total of 264 SNP allele inferences with 260 true and 4 false positives, a false discovery rate of 1.5 percent. Random match probabilities were estimated using the genotype frequencies from the matching major populations in the 1000 Genomes Project. Estimates ranged up to a value of 1 in 1.7108, with a median probability of 1 in 2.4106. Furthermore, the proteomically-inferred genotypes are likely to be compatible with the STR-based random match probability estimates, since the closest STR locus was 2.2 Mb from the nearest GVP-inferred SNP. This project represents a novel mode of genetic information that can be obtained from fingermarks and has the potential to complement other methods of human identification, including analysis of ridge patterns or touch DNA. (publisher abstract modified)