Understanding the Relationship between Genetic Markers and Skeletal Remains: Implications for Forensic Anthropology and Phenotype-Genotype Studies.

Abstract

Human identification techniques have been a leading tool to hold perpetrators accountable, give families closure, and approximate faces on skulls. This project is a pilot study to critically examine three disciplines that fall under the human identification umbrella: forensic anthropology, forensic genetics, and forensic art. Current facial research in genetics focuses on data from living individuals, identifying specific single-nucleotide polymorphisms (SNPs) that influence specific regions of the face. This study assesses the translation of these regions to craniometric dimensions (interlandmark distances) of the underlying skull itself. The goal of this project is to provide information regarding the correlation of craniometric measurements and SNPs, as well as to encourage interdisciplinary work within the forensic sciences. We examined a selection of candidate SNPs currently identified in the literature to examine correlations between interlandmark distances and these SNPs within the same individual. A series of 99 craniometric landmarks were collected from 17 documented skulls from the Texas State Donated Skeletal Collection using a three-dimensional Microscribe digitizer. Criteria for inclusion in this study included European American ancestry, presence of intact skulls, and presence of associated donor blood cards collected at the time of body donation. Using these blood cards, DNA from each individual was extracted, amplified, and sequenced through next-generation sequencing for the chosen SNPs. Bioinformatics tests were then applied to observe the presence or absence of the major or minor alleles in specific locations on the genome. After determining the presence or absence of an SNP (minor allele), a set of statistical tests were performed, including Spearman's correlation between the craniometric measurements and the individual's genetic data variables; two-way hierarchical clustering and bootstrap forest modeling between variables that demonstrated significant correlation; a principal components analysis on the craniometric data (interlandmark measurements) and genetic data (SNP presence/absence) to check homogeneity of each data set; and a pairwise Procrustes analysis on the correlation of the two data sets as different groups. The results indicate correlations of varying degrees between the targeted craniofacial regions and the targeted SNPs. Eleven SNPs showed significant correlation (p < 0.05), but the correlations were not as expected and showed some interesting results. By group level there was no significant correlation, but there was correlation at the individual level. While some SNPs affected the soft tissues only, others showed correlations with the skull (hard tissue), a finding not previously reported. Combining craniometric and DNA analyses to leverage genotype-phenotype associations has great potential to expand the discourse of current facial approximation and thereby to provide new investigative tools for human identification in forensic anthropology.