Identifier: TFG:1619
Authors: Campos Membrive, Lara
Abstract:
Pigmentation traits are a very visible feature among humans, including the color of eyes, hair and skin. This phenotypic trait is polygenic, and the genetic background is very different between populations. On the other hand, there are some molecular biology techniques that allow us to genotype certain sequences of an individual's DNA with relative ease. In addition, the study of Single Nucleotide Polymorphisms (SNPs) has allowed us to associate more specific regions of the genome with a certain phenotype, also for human pigmentation traits. Previous studies created a prediction model, IrisPlex, which is based on the genotype of a DNA sequence in which polymorphisms associated with pigmentation traits have been recognized. Subsequently, depending on the genotype of the biological sample analyzed, it gives a probability for the individual donor of the sample to possess a certain phenotype. IrisPlex has a very high predictive capacity for brown and blue eyes, but in the case of green eyes, it has a very low sensitivity. In this study we create a new prediction model, based on a logistic regression, which takes into account the genotype and sex of the individual to increase the prediction ability, especially for green eyes, major weakness of IrisPlex. On the other hand, an analysis of pigmented ring association, particularly characteristic of green and light eyes, is proposed. After the elaboration of the prediction model, it is concluded that taking sex and genotype into account in a prediction model of eye colour, based on logistic regression, improves the sensitivity of the model for green eyes. From the analysis of association, it is extracted that there are several genes related to the eye color that determine the presence or absence of pigmented ring, especially HERC2, greater determinant of clear eyes.
Repositori URV