Dataset Information

Hair Proteome Variation at Different Body Locations on Genetically Variant Peptide Detection for Protein-Based Human Identification.

ABSTRACT: Human hair contains minimal intact nuclear DNA for human identification in forensic and archaeological applications. In contrast, proteins offer a pathway to exploit hair evidence for human identification owing to their persistence, abundance, and derivation from DNA. Individualizing single nucleotide polymorphisms (SNPs) are often conserved as single amino acid polymorphisms in genetically variant peptides (GVPs). Detection of GVP markers in the hair proteome via high-resolution tandem mass spectrometry permits inference of SNPs with known statistical probabilities. To adopt this approach for forensic investigations, hair proteomic variation and its effects on GVP identification must first be characterized. This research aimed to assess variation in single-inch head, arm, and pubic hair, and discover body location-invariant GVP markers to distinguish individuals. Comparison of protein profiles revealed greater body location-specific variation in keratin-associated proteins and intracellular proteins, allowing body location differentiation. However, robust GVP markers derive primarily from keratins that do not exhibit body location-specific differential expression, supporting GVP identification independence from hair proteomic variation at the various body locations. Further, pairwise comparisons of GVP profiles with 8 SNPs demonstrated greatest interindividual variation and high intraindividual consistency, enabling similar differentiative potential of individuals using single hairs irrespective of body location origin.

SUBMITTER: Chu F

PROVIDER: S-EPMC6529471 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Publications

Hair Proteome Variation at Different Body Locations on Genetically Variant Peptide Detection for Protein-Based Human Identification.

Chu Fanny F Mason Katelyn E KE Anex Deon S DS Jones A Daniel AD Hart Bradley R BR

Scientific reports 20190521 1

Human hair contains minimal intact nuclear DNA for human identification in forensic and archaeological applications. In contrast, proteins offer a pathway to exploit hair evidence for human identification owing to their persistence, abundance, and derivation from DNA. Individualizing single nucleotide polymorphisms (SNPs) are often conserved as single amino acid polymorphisms in genetically variant peptides (GVPs). Detection of GVP markers in the hair proteome via high-resolution tandem mass spe ...[more]

PMID: 31113963

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Project description:This dataset results from the discovery, characterization and validation of 74 genetically variant peptides from fingermark protein. These peptides contain single amino acid polymorphisms, the result of non-synonymous SNPs. Detection of these peptide markers in fingermark proteomic datasets allows inferences to be made about the genotype status of corresponding SNP alleles. These inferences provide an individual genetic profile that may be used to calculate random match probabilities and provide information about potential genetic background. Epidermal corneocytes from five European and four South Asian subjects were isolated, processed, proteolytically digested with trypsin and 0.75 µg applied to a Q ExactiveTM hybrid quadrupole-Orbitrap mass spectrometer. The resulting datasets were used for discovery of genetically variant peptides by a “bottom-up” analysis of potential variants identified in X!Tandem datasets (thegpm.org) or by a “top-down” proteomic confirmation of non-synonymous SNP variants shown to be present in corresponding subject exome datasets. The later method resulted in discovery of a rare allele that was not observed in the 1000 Genome Project. The cumulative profiles of detected genetically variant peptides were obtained for each subject. Candidate genetically variant peptides were then validated by comparing proteomically inferred SNP alleles with matching genotypes in exome datasets. An average of 28.8 ± 4.4 genetically variant peptides were detected from each subject. Across the 9 subjects a total of 264 SNP allele inferences were made resulting in 260 true positives and 4 false positives, a false positive rate of 1.5%. Random match probabilities were calculated using the genotype frequencies of common genetically variant peptides from the matching major populations in the 1000 genome project. Estimates ranged up to a value of 1 in 1.7 x 108, with a median probability of 1 in 2.4 x 106. When probabilities were recalculated using values from other major genetic population groups African values were considerably less conservative, with resulting likelihood ratios (AFR/other populations) ranging up to 6 orders of magnitude. Conversely there was no resolution among estimates obtained from all non-African population groups, where resulting random match probabilities were within an order of magnitude. These genetically variant peptides are a starting point for the development of targeted mass spectrometry-based proteomic analyses that will increase the sensitivity of peptide detection. This project represents a novel mode of genetic information that can be obtained from fingermarks and has the potential to complement or confirm other methods of human identification including analysis of ridge patterns or touch DNA.

Project description:Recent reports highlight improved individual identification using proteomic information from human hair evidence. These reports have stimulated investigation of parameters that affect the utility of proteomic information. In addition to variables already studied relating to processing technique and the anatomic origin of hair shafts, an important variable is hair ageing. Present work focuses on the effect of age on protein profiling and analysis of genetically variant peptides GVPs. Hair protein profiles may be affected by developmental and physiological changes with age of the donor, exposure to different environmental conditions and intrinsic processes, including during storage. First, to explore whether general trends were evident in the population at different ages, hair samples were analyzed from groups of different subjects in their 20s, 40s and 60s. No significant differences were seen as a function of age, but consistent differences were evident between European American and African American hair profiles. Second, samples collected from single individuals at different ages were analyzed. In most cases, these showed few protein expression level differences over periods of 10 years or less, but samples from subjects at 44 and 65 year intervals were distinctly different in profile. The results indicate that use of protein profiling for personal identification, if practical, would be limited to decadal time intervals. Moreover, batch effects were clearly evident in samples processed by different staff. To investigate the contribution of storage at room temperature in affecting the outcomes, the same proteomic digests were analyzed for GVPs. In samples stored over 10 years, GVPs were reduced in number in parallel with the yield of identified proteins and unique peptides. However, a very different picture emerged with respect to personal identification. Numbers of GVPs sufficed to distinguish individuals despite the age differences of the samples. As a practical matter, three hair samples per person provided nearly the maximal number obtained from 5 or 6 samples. The random match probability where the log increased in proportion to the number of GVPs reached as high as 1 in 108. The data indicate that GVP results are dependent primarily on the donor genotype, and thus are consistent despite the ages of the donors and samples and batchwise effects in processing. This conclusion is critical for application to casework where the samples may be in storage for long periods and used to match samples recently collected.

Dataset Information

Hair Proteome Variation at Different Body Locations on Genetically Variant Peptide Detection for Protein-Based Human Identification.

Publications

Hair Proteome Variation at Different Body Locations on Genetically Variant Peptide Detection for Protein-Based Human Identification.

Similar Datasets

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