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                            Library & Multimedia
 Novel Quantitative Pigmentation Phenotyping Enhances Genetic Association, Epistasis, and Prediction of Human Eye Colour
NCJ Number
              252456
Journal

*Scientific Reports* Volume: 7 Dated: 2017
Author(s)
          Andreas Wollstein;
                        Susan Walsh;
                        Fan Liu;
                        Usha Chakravarthy;
                        Mati Rahu;
                        Johan H. Seland;
                        Gisele Soubrane;
                        Laura Tomazzoli;
                        Fotis Topouzis;
                        Johannes R. Vingerling;
                        Jesus Vioque;
                        Stefan Bohringer;
                        Astrid E. Fletcher;
                        Manfred Kayser
Date Published

2017
Length
              1 page
Annotation
              In order to overcome limitations in the characterization of human iris pigmentation, this project designed a fully automated approach that specifies the areal proportions proposed to represent differing pigmentation types, such as pheomelanin, eumelanin, and non-pigmented areas within the iris.
Abstract
              The success of genetic association and the prediction of phenotypic traits from DNA are known to depend on the accuracy of phenotype characterization, among other parameters. The current study demonstrated the utility of this approach by using high-resolution digital eye imagery and genotype data from 12 selected SNPs from over 3,000 European samples of seven populations that are part of the EUREYE study. Compared to previous quantification approaches, the current study achieved an overall improvement in eye color phenotyping, which provides a better separation of manually defined eye color categories. Single nucleotide polymorphisms (SNPs) known to be involved in human eye color variation showed stronger associations with the developed approach. The project also found new and confirmed previously noted SNP-SNP interactions; and it increased SNP-based prediction accuracy of quantitative eye color. These findings show that precise quantification using the perceived biological basis of pigmentation leads to improved genetic association and prediction of eye color. The researchers anticipate that this approach will deliver new pigmentation genes when applied to genome-wide association testing. (publisher abstract modified)
      
  
          Additional Details
Grant Number(s)
        2014-DN-BX-K031


  
  
        
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        NIJ-Sponsored


  
  
        
  Publication Type
        Research (Applied/Empirical)
                                Report (Study/Research)
                                Report (Grant Sponsored)
                                Program/Project Description


  
  
        
  Award
        Improving the prediction of human quantitative pigmentation traits such as eye, hair and skin color using a worldwide representation panel of US and European individuals
    
  
  
Date Published: January 1, 2017
    
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