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Evolutionary Analysis Predicts Sensitive Positions of MMP20 and Validates Newly- and Previously-Identified MMP20 Mutations Causing Amelogenesis Imperfecta

Amelogenesis imperfecta (AI) designates a group of genetic diseases characterized by a large range of enamel disorders causing important social and health problems. These defects can result from mutations in enamel matrix proteins or protease encoding genes. A range of mutations in the enamel cleava...

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Autores principales: Gasse, Barbara, Prasad, Megana, Delgado, Sidney, Huckert, Mathilde, Kawczynski, Marzena, Garret-Bernardin, Annelyse, Lopez-Cazaux, Serena, Bailleul-Forestier, Isabelle, Manière, Marie-Cécile, Stoetzel, Corinne, Bloch-Zupan, Agnès, Sire, Jean-Yves
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5469888/
https://www.ncbi.nlm.nih.gov/pubmed/28659819
http://dx.doi.org/10.3389/fphys.2017.00398
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author Gasse, Barbara
Prasad, Megana
Delgado, Sidney
Huckert, Mathilde
Kawczynski, Marzena
Garret-Bernardin, Annelyse
Lopez-Cazaux, Serena
Bailleul-Forestier, Isabelle
Manière, Marie-Cécile
Stoetzel, Corinne
Bloch-Zupan, Agnès
Sire, Jean-Yves
author_facet Gasse, Barbara
Prasad, Megana
Delgado, Sidney
Huckert, Mathilde
Kawczynski, Marzena
Garret-Bernardin, Annelyse
Lopez-Cazaux, Serena
Bailleul-Forestier, Isabelle
Manière, Marie-Cécile
Stoetzel, Corinne
Bloch-Zupan, Agnès
Sire, Jean-Yves
author_sort Gasse, Barbara
collection PubMed
description Amelogenesis imperfecta (AI) designates a group of genetic diseases characterized by a large range of enamel disorders causing important social and health problems. These defects can result from mutations in enamel matrix proteins or protease encoding genes. A range of mutations in the enamel cleavage enzyme matrix metalloproteinase-20 gene (MMP20) produce enamel defects of varying severity. To address how various alterations produce a range of AI phenotypes, we performed a targeted analysis to find MMP20 mutations in French patients diagnosed with non-syndromic AI. Genomic DNA was isolated from saliva and MMP20 exons and exon-intron boundaries sequenced. We identified several homozygous or heterozygous mutations, putatively involved in the AI phenotypes. To validate missense mutations and predict sensitive positions in the MMP20 sequence, we evolutionarily compared 75 sequences extracted from the public databases using the Datamonkey webserver. These sequences were representative of mammalian lineages, covering more than 150 million years of evolution. This analysis allowed us to find 324 sensitive positions (out of the 483 MMP20 residues), pinpoint functionally important domains, and build an evolutionary chart of important conserved MMP20 regions. This is an efficient tool to identify new- and previously-identified mutations. We thus identified six functional MMP20 mutations in unrelated families, finding two novel mutated sites. The genotypes and phenotypes of these six mutations are described and compared. To date, 13 MMP20 mutations causing AI have been reported, making these genotypes and associated hypomature enamel phenotypes the most frequent in AI.
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spelling pubmed-54698882017-06-28 Evolutionary Analysis Predicts Sensitive Positions of MMP20 and Validates Newly- and Previously-Identified MMP20 Mutations Causing Amelogenesis Imperfecta Gasse, Barbara Prasad, Megana Delgado, Sidney Huckert, Mathilde Kawczynski, Marzena Garret-Bernardin, Annelyse Lopez-Cazaux, Serena Bailleul-Forestier, Isabelle Manière, Marie-Cécile Stoetzel, Corinne Bloch-Zupan, Agnès Sire, Jean-Yves Front Physiol Physiology Amelogenesis imperfecta (AI) designates a group of genetic diseases characterized by a large range of enamel disorders causing important social and health problems. These defects can result from mutations in enamel matrix proteins or protease encoding genes. A range of mutations in the enamel cleavage enzyme matrix metalloproteinase-20 gene (MMP20) produce enamel defects of varying severity. To address how various alterations produce a range of AI phenotypes, we performed a targeted analysis to find MMP20 mutations in French patients diagnosed with non-syndromic AI. Genomic DNA was isolated from saliva and MMP20 exons and exon-intron boundaries sequenced. We identified several homozygous or heterozygous mutations, putatively involved in the AI phenotypes. To validate missense mutations and predict sensitive positions in the MMP20 sequence, we evolutionarily compared 75 sequences extracted from the public databases using the Datamonkey webserver. These sequences were representative of mammalian lineages, covering more than 150 million years of evolution. This analysis allowed us to find 324 sensitive positions (out of the 483 MMP20 residues), pinpoint functionally important domains, and build an evolutionary chart of important conserved MMP20 regions. This is an efficient tool to identify new- and previously-identified mutations. We thus identified six functional MMP20 mutations in unrelated families, finding two novel mutated sites. The genotypes and phenotypes of these six mutations are described and compared. To date, 13 MMP20 mutations causing AI have been reported, making these genotypes and associated hypomature enamel phenotypes the most frequent in AI. Frontiers Media S.A. 2017-06-14 /pmc/articles/PMC5469888/ /pubmed/28659819 http://dx.doi.org/10.3389/fphys.2017.00398 Text en Copyright © 2017 Gasse, Prasad, Delgado, Huckert, Kawczynski, Garret-Bernardin, Lopez-Cazaux, Bailleul-Forestier, Manière, Stoetzel, Bloch-Zupan and Sire. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Physiology
Gasse, Barbara
Prasad, Megana
Delgado, Sidney
Huckert, Mathilde
Kawczynski, Marzena
Garret-Bernardin, Annelyse
Lopez-Cazaux, Serena
Bailleul-Forestier, Isabelle
Manière, Marie-Cécile
Stoetzel, Corinne
Bloch-Zupan, Agnès
Sire, Jean-Yves
Evolutionary Analysis Predicts Sensitive Positions of MMP20 and Validates Newly- and Previously-Identified MMP20 Mutations Causing Amelogenesis Imperfecta
title Evolutionary Analysis Predicts Sensitive Positions of MMP20 and Validates Newly- and Previously-Identified MMP20 Mutations Causing Amelogenesis Imperfecta
title_full Evolutionary Analysis Predicts Sensitive Positions of MMP20 and Validates Newly- and Previously-Identified MMP20 Mutations Causing Amelogenesis Imperfecta
title_fullStr Evolutionary Analysis Predicts Sensitive Positions of MMP20 and Validates Newly- and Previously-Identified MMP20 Mutations Causing Amelogenesis Imperfecta
title_full_unstemmed Evolutionary Analysis Predicts Sensitive Positions of MMP20 and Validates Newly- and Previously-Identified MMP20 Mutations Causing Amelogenesis Imperfecta
title_short Evolutionary Analysis Predicts Sensitive Positions of MMP20 and Validates Newly- and Previously-Identified MMP20 Mutations Causing Amelogenesis Imperfecta
title_sort evolutionary analysis predicts sensitive positions of mmp20 and validates newly- and previously-identified mmp20 mutations causing amelogenesis imperfecta
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5469888/
https://www.ncbi.nlm.nih.gov/pubmed/28659819
http://dx.doi.org/10.3389/fphys.2017.00398
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