Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Research, Society and Development |
Texto Completo: | https://rsdjournal.org/index.php/rsd/article/view/20955 |
Resumo: | 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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Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil Fenotipado de DNA Forense: un punto de partida para el modelo de predicción de población de Pernambuco, BrasilFenotipagem por DNA Forense: um ponto de partida para o modelo de predição na população de Pernambuco, BrasilGenes de pigmentaçãoPopulação miscigenadaBrasilSNPsPreditores fenotípicosInteligência artificial.Pigmentation genesMiscigenated PopulationBrazilSNPsPhenotypic predictionArtificial intelligence.Genes de pigmentaciónPoblación mixtaBrasilSNPPredictores fenotípicosInteligencia artificial.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.El estudio de las Características Externamente Visibles (CEV) de la pigmentación asociada a los SNP (Single Nucleotide Polymorphisms) se ha convertido en un objetivo en el área forense debido a la posibilidad de caracterizar fenotípicamente a un individuo. En Brasil, hay pocos datos que muestren la evaluación de algunos de estos marcadores, por lo que se necesitan más estudios para comprender mejor el proceso de pigmentación relacionado con los marcadores genéticos. El objetivo de este estudio fue probar la asociación entre 8 SNP presentes en la herramienta HIrisplex y el CEV para proporcionar un punto de partida para el desarrollo de modelos de predicción para poblaciones heterogéneas como la de Pernambuco. Se evaluaron 176 individuos a través de asociaciones entre los datos autoinformados sobre el color de ojos, cabello y piel y polimorfismos. Se utilizaron herramientas de inteligencia artificial para los modelos de predicción. Se encontraron asociaciones significativas entre rs1800404 (OCA2), rs6058017 (ASIP), rs16891982 (SLC45A2) y rs1426654 (SLC24A5) con CEV. Los modelos de predicción evaluados presentaron tasas de predicción satisfactorias, superiores al 60% para el color de piel y superiores al 70% para ojos y cabello. Las asociaciones encontradas en nuestros datos muestran la importancia de evaluar los SNP utilizados en el fenotipado de DNA, debido a su capacidad para aportar nueva información en el contexto de las investigaciones penales. Nuestros datos indican que es posible utilizar información molecular para predecir fenotipos en poblaciones mixtas, como la brasileña. Estos polimorfismos pueden ser posibles predictores fenotípicos para la población de Pernambuco.O estudo das Características Externamente Visíveis (CEV) da pigmentação associada a SNPs (Single Nucleotide Polymorphisms) tornou-se um alvo na área forense devido à possibilidade de caracterizar fenotipicamente um indivíduo. No Brasil, poucos são os dados que mostram a avaliação de alguns desses marcadores, portanto, mais estudos são necessários para entender melhor o processo de pigmentação relacionado aos marcadores genéticos. O objetivo deste estudo foi testar a associação entre 8 SNPs presentes na ferramenta HIrisplex e as CEV para fornecer um ponto de partida para o desenvolvimento de modelos de predição para populações heterogêneas como a de Pernambuco. 176 indivíduos foram avaliados por meio de associações entre dados autorreferidos de cor dos olhos, cabelo e pele e os polimorfismos. Ferramentas de inteligência artificial foram utilizadas para os modelos de predição. Foram encontradas associações significativas entre rs1800404 (OCA2), rs6058017 (ASIP), rs16891982 (SLC45A2) e rs1426654 (SLC24A5) com as CEV. Os modelos de predição avaliados apresentaram índices de predição satisfatórios, acima de 60% para cor da pele e acima de 70% para olhos e cabelos. As associações encontradas em nossos dados mostram a importância da avaliação de SNPs utilizados na Fenotipagem por DNA, por sua capacidade de fornecer novas informações no contexto de investigações criminais. Os dados encontrados indicam que é possível usar informações moleculares para predizer fenótipos em populações miscigenadas, como a brasileira. Esses polimorfismos podem ser possíveis preditores fenotípicos para a população de Pernambuco.Research, Society and Development2021-10-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/2095510.33448/rsd-v10i13.20955Research, Society and Development; Vol. 10 No. 13; e262101320955Research, Society and Development; Vol. 10 Núm. 13; e262101320955Research, Society and Development; v. 10 n. 13; e2621013209552525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIenghttps://rsdjournal.org/index.php/rsd/article/view/20955/18898Copyright (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 Munizhttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessSouza, Juliana Maria de Bastos, Michael LopesSilva, Bárbara de OliveiraLima, Karla Giselle Gomes deAlbuquerque, Giwellington Silva de Oliveira, Renata Santos de Lima, Luísa Priscilla Oliveira deDellalibera, Edileine Lins , Anthony José da Cunha CarneiroMuniz, Maria Tereza Cartaxo 2021-11-21T18:26:28Zoai:ojs.pkp.sfu.ca:article/20955Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:40:28.569100Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false |
dc.title.none.fl_str_mv |
Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil Fenotipado de DNA Forense: un punto de partida para el modelo de predicción de población de Pernambuco, Brasil Fenotipagem por DNA Forense: um ponto de partida para o modelo de predição na população de Pernambuco, Brasil |
title |
Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil |
spellingShingle |
Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil Souza, Juliana Maria de Genes de pigmentação População miscigenada Brasil SNPs Preditores fenotípicos Inteligência artificial. Pigmentation genes Miscigenated Population Brazil SNPs Phenotypic prediction Artificial intelligence. Genes de pigmentación Población mixta Brasil SNP Predictores fenotípicos Inteligencia artificial. |
title_short |
Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil |
title_full |
Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil |
title_fullStr |
Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil |
title_full_unstemmed |
Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil |
title_sort |
Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil |
author |
Souza, Juliana Maria de |
author_facet |
Souza, Juliana Maria de Bastos, Michael Lopes Silva, Bárbara de Oliveira Lima, Karla Giselle Gomes de Albuquerque, Giwellington Silva de Oliveira, Renata Santos de Lima, Luísa Priscilla Oliveira de Dellalibera, Edileine Lins , Anthony José da Cunha Carneiro Muniz, Maria Tereza Cartaxo |
author_role |
author |
author2 |
Bastos, Michael Lopes Silva, Bárbara de Oliveira Lima, Karla Giselle Gomes de Albuquerque, Giwellington Silva de Oliveira, Renata Santos de Lima, Luísa Priscilla Oliveira de Dellalibera, Edileine Lins , Anthony José da Cunha Carneiro Muniz, Maria Tereza Cartaxo |
author2_role |
author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Souza, Juliana Maria de Bastos, Michael Lopes Silva, Bárbara de Oliveira Lima, Karla Giselle Gomes de Albuquerque, Giwellington Silva de Oliveira, Renata Santos de Lima, Luísa Priscilla Oliveira de Dellalibera, Edileine Lins , Anthony José da Cunha Carneiro Muniz, Maria Tereza Cartaxo |
dc.subject.por.fl_str_mv |
Genes de pigmentação População miscigenada Brasil SNPs Preditores fenotípicos Inteligência artificial. Pigmentation genes Miscigenated Population Brazil SNPs Phenotypic prediction Artificial intelligence. Genes de pigmentación Población mixta Brasil SNP Predictores fenotípicos Inteligencia artificial. |
topic |
Genes de pigmentação População miscigenada Brasil SNPs Preditores fenotípicos Inteligência artificial. Pigmentation genes Miscigenated Population Brazil SNPs Phenotypic prediction Artificial intelligence. Genes de pigmentación Población mixta Brasil SNP Predictores fenotípicos Inteligencia artificial. |
description |
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. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-10-11 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/20955 10.33448/rsd-v10i13.20955 |
url |
https://rsdjournal.org/index.php/rsd/article/view/20955 |
identifier_str_mv |
10.33448/rsd-v10i13.20955 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/20955/18898 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Research, Society and Development |
publisher.none.fl_str_mv |
Research, Society and Development |
dc.source.none.fl_str_mv |
Research, Society and Development; Vol. 10 No. 13; e262101320955 Research, Society and Development; Vol. 10 Núm. 13; e262101320955 Research, Society and Development; v. 10 n. 13; e262101320955 2525-3409 reponame:Research, Society and Development instname:Universidade Federal de Itajubá (UNIFEI) instacron:UNIFEI |
instname_str |
Universidade Federal de Itajubá (UNIFEI) |
instacron_str |
UNIFEI |
institution |
UNIFEI |
reponame_str |
Research, Society and Development |
collection |
Research, Society and Development |
repository.name.fl_str_mv |
Research, Society and Development - Universidade Federal de Itajubá (UNIFEI) |
repository.mail.fl_str_mv |
rsd.articles@gmail.com |
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1797052691301531648 |