Elucidating the mechanisms or interactions involved in differing hair color follicles

Abstract

Forensic DNA phenotyping is an up and coming area in forensic DNA analyses that enables the prediction of physical appearance of an individual from DNA left at a crime scene. At present, there has been substantial work performed in understanding what genes/markers are required to produce a reliable prediction of categorical eye and hair color from the DNA of an individual of interest. These pigmentation markers (variants from HERC2, OCA2, TYR, SLC24A4, SLC45A2, IRF4 to name a few) are at the core of several prediction systems for eye and hair color such as IrisPlex, HIrisPlex, and the Snipper 2.5 suite. The contribution of these markers towards prediction in most cases however, only factors in an independent effect and do not take into account potential interactions or epistasis in the production of the final phenotypic color. Epistasis is a phenomenon that occurs when a gene’s effect relies on the presence of ‘modifier genes’, and can display different effects (enhance/repress a particular color) in genotype combinations rather than individually.

In an effort to detect such epistatic interactions and their influence on hair color prediction models, for this current study, 872 individuals were genotyped at 61 associative and predictive pigmentation markers from several diverse population subsets. Individuals were phenotypically evaluated for eye and hair color by three separate independent assessments. Several analyses were performed using statistical approaches such as multifactor dimensionality reduction (MDR) for example, in an effort to detect if there are any SNP- SNP epistatic interactions present that could potentially enhance eye and hair color prediction model performances. The ultimate goal of this study was to assess what SNP-SNP combinations amongst these known pigmentation genes should be included as an additional variable in future prediction models and how much they can potentially enhance overall pigmentation prediction model performance.

The second part of the project involved the analyses of several differentially expressed candidate genes between different hair color follicles of the same individual using quantitative Real Time PCR. We looked at 26 different genes identified through a concurrent non-human primate study being performed in the laboratory. The purpose of this study was to gain more insight on the level of differentially expressed mRNA between different hair color follicles within the same human individual. Data generated from this part of the project will act as a pilot study or ‘proof of principle’ on the mRNA expression of several pigmentation associated genes on individual beard hair of varying phenotypic colors. This analysis gives a first glimpse at expression levels that remain constant or differentiate between hairs of the same individual, therefore limiting the contribution of individual variation.