MassIVE MSV000086665

Partial Public PXD023446

Elucidation of Familial Relationships Using Hair Shaft Proteomics

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Description

This study examines the potential of hair shaft proteomic analysis to delineate genetic relatedness. Proteomic profiling and amino acid sequence analysis provide information for quantitative and statistically based analysis of individualization and sample similarity. Protein expression levels are a function of cell specific transcriptional and translational programs. These programs are greatly influenced by an individuals genetic background, and are therefore influenced by familial relatedness as well as ancestry and genetic disease. Proteomic profiles should therefore be more similar among related individuals than unrelated individuals. Likewise, profiles of genetically variant peptides that contain single amino acid polymorphisms, the result of non-synonymous SNP alleles, should behave similarly. The proteomically-inferred SNP alleles should also provide a basis for calculation of combined paternity and sibship indices. We test these hypotheses using matching proteomic and genetic datasets from a family of two adults and four siblings, one of which has a genetic condition that perturbs hair structure and properties. We demonstrate that related individuals, compared to those who are unrelated, have more similar proteomic profiles, profiles of genetically variant peptides and higher combined paternity indices and combined sibship indices. This study builds on previous analyses of hair shaft protein profiling and genetically variant peptide profiles in different real-world scenarios including different human hair shaft body locations and pigmentation status. It also validates the inclusion of proteomic information with other biomolecular substrates in forensic hair shaft analysis, including mitochondrial and nuclear DNA. [doi:10.25345/C5HJ5K] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: Hair Shaft ; gvp ; genetically variant peptides ; human hair

Contact

Principal Investigators:
(in alphabetical order) 		Robert H. Rice, Department of Environmental Toxicology, University of California, Davis, USA, USA
Submitting User: brettsp1

Publications

Tiwari S, Mishra M, Salemi MR, Phinney BS, Newens JL, Gomes AV.
Gender-specific changes in energy metabolism and protein degradation as major pathways affected in livers of mice treated with ibuprofen.
Sci Rep. 2020 Feb 25;10(1):3386. Epub 2020 Feb 25.

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