Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/201567
Type: Artigo de periódico
Title: Exploring Iris Colour Prediction And Ancestry Inference In Admixed Populations Of South America.
Author: Freire-Aradas, A
Ruiz, Y
Phillips, C
Maroñas, O
Söchtig, J
Tato, A Gómez
Dios, J Álvarez
de Cal, M Casares
Silbiger, V N
Luchessi, A D
Chiurillo, M A
Carracedo, Á
Lareu, M V
Abstract: New DNA-based predictive tests for physical characteristics and inference of ancestry are highly informative tools that are being increasingly used in forensic genetic analysis. Two eye colour prediction models: a Bayesian classifier - Snipper and a multinomial logistic regression (MLR) system for the Irisplex assay, have been described for the analysis of unadmixed European populations. Since multiple SNPs in combination contribute in varying degrees to eye colour predictability in Europeans, it is likely that these predictive tests will perform in different ways amongst admixed populations that have European co-ancestry, compared to unadmixed Europeans. In this study we examined 99 individuals from two admixed South American populations comparing eye colour versus ancestry in order to reveal a direct correlation of light eye colour phenotypes with European co-ancestry in admixed individuals. Additionally, eye colour prediction following six prediction models, using varying numbers of SNPs and based on Snipper and MLR, were applied to the study populations. Furthermore, patterns of eye colour prediction have been inferred for a set of publicly available admixed and globally distributed populations from the HGDP-CEPH panel and 1000 Genomes databases with a special emphasis on admixed American populations similar to those of the study samples.
Subject: Admixture
America
Genetic Ancestry
Iris Colour Prediction
Snps
Rights: fechado
Identifier DOI: 10.1016/j.fsigen.2014.06.007
Address: http://www.ncbi.nlm.nih.gov/pubmed/25051225
Date Issue: 2014
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

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