Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil

Authors

DOI:

https://doi.org/10.33448/rsd-v10i13.20955

Keywords:

Pigmentation genes; Miscigenated Population; Brazil; SNPs; Phenotypic prediction; Artificial intelligence.

Abstract

The study of Externally Visible Characteristics (EVC) of pigmentation associated with SNPs (Single Nucleotide Polymorphisms) has become a target in the forensic field due to the possibility of phenotypically characterizing an individual. In Brazil, there are few data that shows the evaluation of some these markers, so further studies are necessary to understand better the pigmentation process related to genetic markers. The aim of this study was to test the association between 8 SNPs  present in HIrisplex tool and EVC to provide a starting point for the development of prediction models for heterogeneous populations like the one in Pernambuco. Were evaluated 176 individuals by associations between self-reported eye, hair and skin color data and polymorphisms. Artificial intelligence tools were used for the prediction models. Significant associations were found between rs1800404 (OCA2), rs6058017 (ASIP), rs16891982 (SLC45A2) and rs1426654 (SLC24A5) with (EVC). The prediction models evaluated showed satisfactory prediction rates, rates above 60% for skin color and above 70% for eyes and hair. The associations found in our data show the importance of SNPs evaluation used in DNA Phenotyping, because of its ability to provide new information in the context of criminal investigations. Our data indicate that is possible to use molecular information to predict phenotypes in miscigenated populations, like the Brazilian population. These polymorphisms could be possible phenotypic predictors for the Pernambuco population.

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11/10/2021

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SOUZA, J. M. de .; BASTOS, M. L.; SILVA, B. de O.; LIMA, K. G. G. de; ALBUQUERQUE, G. S. de .; OLIVEIRA, R. S. de .; LIMA, L. P. O. de; DELLALIBERA, E. .; LINS , A. J. da C. C.; MUNIZ, M. T. C. . Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil . Research, Society and Development, [S. l.], v. 10, n. 13, p. e262101320955, 2021. DOI: 10.33448/rsd-v10i13.20955. Disponível em: https://www.rsdjournal.org/index.php/rsd/article/view/20955. Acesso em: 19 apr. 2024.

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Vol. 10 No. 13

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Agrarian and Biological Sciences

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Copyright (c) 2021 Juliana Maria de Souza; Michael Lopes Bastos; Bárbara de Oliveira Silva; Karla Giselle Gomes de Lima; Giwellington Silva de Albuquerque; Renata Santos de Oliveira; Luísa Priscilla Oliveira de Lima; Edileine Dellalibera; Anthony José da Cunha Carneiro Lins ; Maria Tereza Cartaxo Muniz

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