Highlights
- •Develop a deep-coverage proteome analysis strategy to identify both variant and reference SAPs present in the hair shaft.
- •Identify more than one hundred SAPs in a single hair shaft.
- •Demonstrate the practical value of genetic information coded in hair shaft SAPs.
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.
Graphical Abstract
Graphical Abstract
Keywords
Abbreviations:
SAP (Single amino acid polymorphism), GVP (Genetically variant peptide)To read this article in full you will need to make a payment
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Article info
Publication history
Published online: June 17, 2022
Accepted:
June 15,
2022
Received in revised form:
June 13,
2022
Received:
September 26,
2021
Identification
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