Deep coverage proteome analysis of hair shaft for forensic individual identification

Abstract

Hair shaft is one of the most common biological evidence found at crime scenes. However, due to the biogenic degradation of nuclear DNA in hair shaft, it is difficult to achieve individual identification through routine DNA analysis. In contrast, the proteins in hair shaft are stable and contain genetic polymorphisms in the form of single amino acid polymorphisms (SAPs), translated from non-synonymous single nucleotide polymorphisms (nsSNPs) in the genome. However, the number of SAPs detected still cannot meet the requirements of practical applications. This paper developed a deep coverage proteome analysis method by combining a three-step sequential ionic liquid-based protein extraction and 2D-RPLC-MS/MS with high and low pH to identify both variant and reference SAPs from 2-cm-long hair shafts. We identified 632 ± 243 protein groups from 10 individuals, with the average number of SAPs reaching 167 ± 21/person. These were further used to calculate random match probabilities (RMPs), a widely accepted forensic statistical term for human identification. The RMPs ranged from 6.53 × 10–4 to 3.10 × 10–14 (median = 2.62 × 10–8) when calculated with frequency of matching nsSNP genotype data from exomes, and ranged from 2.62 × 10–3 to 2.07 × 10–10 (median = 4.88 × 10–6) with SAP genotype frequency. All these results indicate that the deep coverage proteomics method is beneficial for improving SAP-based forensic individual identification in hair shaft, with great potential in crime investigation.