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Advancement in Human Face Prediction Using DNA
The rapid improvements in identifying the genetic factors contributing to facial morphology have enabled the early identification of craniofacial syndromes. Similarly, this technology can be vital in forensic cases involving human identification from biological traces or human remains, especially wh...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9858985/ https://www.ncbi.nlm.nih.gov/pubmed/36672878 http://dx.doi.org/10.3390/genes14010136 |
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author | Alshehhi, Aamer Almarzooqi, Aliya Alhammadi, Khadija Werghi, Naoufel Tay, Guan K. Alsafar, Habiba |
author_facet | Alshehhi, Aamer Almarzooqi, Aliya Alhammadi, Khadija Werghi, Naoufel Tay, Guan K. Alsafar, Habiba |
author_sort | Alshehhi, Aamer |
collection | PubMed |
description | The rapid improvements in identifying the genetic factors contributing to facial morphology have enabled the early identification of craniofacial syndromes. Similarly, this technology can be vital in forensic cases involving human identification from biological traces or human remains, especially when reference samples are not available in the deoxyribose nucleic acid (DNA) database. This review summarizes the currently used methods for predicting human phenotypes such as age, ancestry, pigmentation, and facial features based on genetic variations. To identify the facial features affected by DNA, various two-dimensional (2D)- and three-dimensional (3D)-scanning techniques and analysis tools are reviewed. A comparison between the scanning technologies is also presented in this review. Face-landmarking techniques and face-phenotyping algorithms are discussed in chronological order. Then, the latest approaches in genetic to 3D face shape analysis are emphasized. A systematic review of the current markers that passed the threshold of a genome-wide association (GWAS) of single nucleotide polymorphism (SNP)-face traits from the GWAS Catalog is also provided using the preferred reporting items for systematic reviews and meta-analyses (PRISMA), approach. Finally, the current challenges in forensic DNA phenotyping are analyzed and discussed. |
format | Online Article Text |
id | pubmed-9858985 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98589852023-01-21 Advancement in Human Face Prediction Using DNA Alshehhi, Aamer Almarzooqi, Aliya Alhammadi, Khadija Werghi, Naoufel Tay, Guan K. Alsafar, Habiba Genes (Basel) Review The rapid improvements in identifying the genetic factors contributing to facial morphology have enabled the early identification of craniofacial syndromes. Similarly, this technology can be vital in forensic cases involving human identification from biological traces or human remains, especially when reference samples are not available in the deoxyribose nucleic acid (DNA) database. This review summarizes the currently used methods for predicting human phenotypes such as age, ancestry, pigmentation, and facial features based on genetic variations. To identify the facial features affected by DNA, various two-dimensional (2D)- and three-dimensional (3D)-scanning techniques and analysis tools are reviewed. A comparison between the scanning technologies is also presented in this review. Face-landmarking techniques and face-phenotyping algorithms are discussed in chronological order. Then, the latest approaches in genetic to 3D face shape analysis are emphasized. A systematic review of the current markers that passed the threshold of a genome-wide association (GWAS) of single nucleotide polymorphism (SNP)-face traits from the GWAS Catalog is also provided using the preferred reporting items for systematic reviews and meta-analyses (PRISMA), approach. Finally, the current challenges in forensic DNA phenotyping are analyzed and discussed. MDPI 2023-01-03 /pmc/articles/PMC9858985/ /pubmed/36672878 http://dx.doi.org/10.3390/genes14010136 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Alshehhi, Aamer Almarzooqi, Aliya Alhammadi, Khadija Werghi, Naoufel Tay, Guan K. Alsafar, Habiba Advancement in Human Face Prediction Using DNA |
title | Advancement in Human Face Prediction Using DNA |
title_full | Advancement in Human Face Prediction Using DNA |
title_fullStr | Advancement in Human Face Prediction Using DNA |
title_full_unstemmed | Advancement in Human Face Prediction Using DNA |
title_short | Advancement in Human Face Prediction Using DNA |
title_sort | advancement in human face prediction using dna |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9858985/ https://www.ncbi.nlm.nih.gov/pubmed/36672878 http://dx.doi.org/10.3390/genes14010136 |
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