Enhancing Our Genetic Knowledge of Human Iris Pigmentation and Facial Morphology

• NCJ Number: 309929
• Author(s): Ryan Eller
• Date Published: 2019
• Length: 185 pages
• Grant Number(s): 2015-R2-CX-0023
• Agencies: NIJ-Sponsored
• Publication Type: Thesis/Dissertation; Research (Applied/Empirical)

Annotation

This study designs a bioinformatic pipeline to enhance genetic knowledge of iris pigmentation and facial morphology.

Abstract

This study investigates the genetics of iris pigmentation and facial morphology by designing a bioinformatic pipeline, Odyssey, that bridges the communication gaps between various data preparation programs and the programs that analyze genomic data. With this program, genome-wide association studies (GWAS) could be conducted in a quicker, more efficient, and easier manner. The researcher also redefined iris color as a quantitative measurement of pre-defined color classes, allowing for the definition and quantification of the unique and intricate mixtures of color, hence permitting the identification of known and novel variants that affect individual iris color. The researcher improved upon current prediction models by developing a neural network model capable of predicting a quantitative output to four pre-defined classes; blue/grey, light brown (hazel), perceived green, and dark brown. The study examined the effects of defining a simple facial morphology phenotype that more accurately captures the lower face and jaw shape. The researcher then analyzed this phenotype via a GWAS and found several novel variants that may be associated with a square and diamond shaped face. Lastly, the study demonstrated that structural equation modeling can be used in combination with traditional GWAS to examine interactions amongst associated variants, which unearths potential biological relationships that impact the multifaceted phenotype of facial morphology.