Utilização da bioinformática na busca de novos genes em osteogênese imperfeita

Detalhes bibliográficos
Autor(a) principal: Coutinho, Amanda Silva
Data de Publicação: 2018
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Repositório Institucional da Universidade Federal do Espírito Santo (riUfes)
Texto Completo: http://repositorio.ufes.br/handle/10/7116
Resumo: Osteogenesis imperfecta (OI) is a rare genetic disease of connective tissue caused by mutations in genes that generally participate in bone formation. Most patients carry mutations in the genes encoding type 1 collagen, but mutations in more than 17 other genes causing OI have been described and there is still a constant search for new genes in the scientific field. Among the molecular diagnostic strategies, the new generation sequencing method (NGS) stands out, which can sequence several genes present in a customized platform generating a large amount of genomic data. These data become precious sources of information in the search for new genes related to diseases. The objective of this research was to perform the search for new genes potentially causing OI through bioinformatics resources. We used filtering strategies by the Microsoft Office Excel 2013 program, as well as mutation prediction analyzes. As a genomic reference, the Ensembl and National Center for Biotechnology Information databases were used. We selected four patients diagnosed clinically with OI who were submitted to the NGS technique and presented normal results for the known genes. In order to select a list of candidate genes in the NGS custom platform that were related to OI symptoms, a search of genes in the Ensembl database involved with the metabolic pathways of bone, cartilage or collagen formation was performed, which identified 643 genes. The list of candidate genes was compared to the sequenced genes of the patients, where 70 genes in common were selected for analysis. In silico, filtrations were performed in order to select rare changes in the population, predicted as pathogenic and that effectively encode a functional RNA protein or molecule. The results showed that patient P.1 carries a potentially pathogenic heterozygous mutation in the ALX1 gene. Patient P.2 presented only one alteration in the COL6A3 gene that was predicted as polymorphism. Patient P.3 presented pathogenic mutations in heterozygosity in the ALPL and FKBP10 genes. In patient P.4, pathogenic mutations in heterozygosis were found in the P3H1 and RYR1 genes. Among the five genes identified, two of them, FKBP10 and P3H1, are known to be related to autosomal recessive OI. It has also been described that mutations in the ALPL gene cause clinical symptoms similar to OI, which may confuse the diagnosis. Thus, the present study identified two genes, ALX1 and RYR1, potentially causing OI. The ALX1 gene plays an important role in cranial and limb development, as it acts on the formation of cartilage. RYR1 encodes ryanodine, an important calcium receptor in osteoblasts. Functional studies of the identified genes are necessary to validate this hypothesis in future research. The results of this work suggest that bioinformatics tools may direct the search for new genes related to genetic diseases. The characterization of new mutations in OI-related genes enables the planning of more efficient strategies that allow molecular diagnosis of the disease and genetic counseling.
id UFES_b8e0c093a95b3b3d5b397155ce5e6187
oai_identifier_str oai:repositorio.ufes.br:10/7116
network_acronym_str UFES
network_name_str Repositório Institucional da Universidade Federal do Espírito Santo (riUfes)
repository_id_str 2108
spelling Paula, Flávia deCoutinho, Amanda SilvaErrera, Flavia Imbroisi ValleMaranduba, Carlos Magno da Costa2018-08-01T21:35:03Z2018-08-012018-08-01T21:35:03Z2018-02-26Osteogenesis imperfecta (OI) is a rare genetic disease of connective tissue caused by mutations in genes that generally participate in bone formation. Most patients carry mutations in the genes encoding type 1 collagen, but mutations in more than 17 other genes causing OI have been described and there is still a constant search for new genes in the scientific field. Among the molecular diagnostic strategies, the new generation sequencing method (NGS) stands out, which can sequence several genes present in a customized platform generating a large amount of genomic data. These data become precious sources of information in the search for new genes related to diseases. The objective of this research was to perform the search for new genes potentially causing OI through bioinformatics resources. We used filtering strategies by the Microsoft Office Excel 2013 program, as well as mutation prediction analyzes. As a genomic reference, the Ensembl and National Center for Biotechnology Information databases were used. We selected four patients diagnosed clinically with OI who were submitted to the NGS technique and presented normal results for the known genes. In order to select a list of candidate genes in the NGS custom platform that were related to OI symptoms, a search of genes in the Ensembl database involved with the metabolic pathways of bone, cartilage or collagen formation was performed, which identified 643 genes. The list of candidate genes was compared to the sequenced genes of the patients, where 70 genes in common were selected for analysis. In silico, filtrations were performed in order to select rare changes in the population, predicted as pathogenic and that effectively encode a functional RNA protein or molecule. The results showed that patient P.1 carries a potentially pathogenic heterozygous mutation in the ALX1 gene. Patient P.2 presented only one alteration in the COL6A3 gene that was predicted as polymorphism. Patient P.3 presented pathogenic mutations in heterozygosity in the ALPL and FKBP10 genes. In patient P.4, pathogenic mutations in heterozygosis were found in the P3H1 and RYR1 genes. Among the five genes identified, two of them, FKBP10 and P3H1, are known to be related to autosomal recessive OI. It has also been described that mutations in the ALPL gene cause clinical symptoms similar to OI, which may confuse the diagnosis. Thus, the present study identified two genes, ALX1 and RYR1, potentially causing OI. The ALX1 gene plays an important role in cranial and limb development, as it acts on the formation of cartilage. RYR1 encodes ryanodine, an important calcium receptor in osteoblasts. Functional studies of the identified genes are necessary to validate this hypothesis in future research. The results of this work suggest that bioinformatics tools may direct the search for new genes related to genetic diseases. The characterization of new mutations in OI-related genes enables the planning of more efficient strategies that allow molecular diagnosis of the disease and genetic counseling.A osteogênese imperfeita (OI) é uma doença genética rara do tecido conjuntivo, causada por mutações em genes que participam, em geral, da formação óssea. A maioria dos pacientes é portadora de mutações nos genes que codificam o colágeno tipo 1, mas já foram descritas mutações em mais de 17 outros genes causando OI e ainda existe uma busca constante de novos genes na área cientifica. Entre as estratégias de diagnóstico molecular destaca-se a técnica de sequenciamento de nova geração (NGS), que pode sequenciar vários genes presentes em uma plataforma customizada, gerando uma grande quantidade de dados genômicos. Esses dados se tornam preciosas fontes de informação na busca de novos genes relacionados a doenças. O objetivo desta pesquisa foi realizar a busca de novos genes potencialmente causadores de OI por meio de recursos de bioinformática. Foram utilizadas estratégias de filtragem pelo programa Microsoft Office Excel 2013, bem como análises de predição de mutação. Como referência genômica foram utilizados os bancos de dados Ensembl e National Center for Biotechnology Information. Foram selecionados quatro pacientes diagnosticados clinicamente com OI que foram submetidos à técnica de NGS e apresentaram resultados normais para os genes conhecidos. Com o intuito de selecionar uma lista de genes candidatos na plataforma customizada de NGS que estivessem relacionados com os sintomas de OI, foi realizada uma busca de genes no banco de dados Ensembl envolvidos com as vias metabólicas de formação óssea, cartilaginosa ou de colágeno, que identificou 643 genes. A lista de genes candidatos foi comparada com os genes sequenciados dos pacientes, onde foram selecionados 70 genes em comum para análise. Foram realizadas filtragens in silico de forma a selecionar alterações raras na população, preditas como patogênicas e que efetivamente codifiquem uma proteína ou uma molécula de RNA funcional. Os resultados mostraram que o paciente P.1 é portador de uma mutação em heterozigose potencialmente patogênica no gene ALX1. O paciente P.2 apresentou apenas uma alteração no gene COL6A3 que foi predita como polimorfismo. O paciente P.3 apresentou mutações patogênicas em heterozigose nos genes ALPL e FKBP10. No paciente P.4 foram encontradas mutações patogênicas em heterozigose nos genes P3H1 e RYR1. Entre os cinco genes identificados, sabese que dois deles, FKBP10 e P3H1, estão relacionados com a OI de herança autossômica recessiva. Também já é descrito que mutações no gene ALPL causam sintomas clínicos semelhantes a OI, podendo confundir o diagnóstico. Assim, o presente estudo identificou dois genes, ALX1 e RYR1, potencialmente causadores de OI. O gene ALX1 tem um papel importante no desenvolvimento craniano e dos membros, pois atua na formação da cartilagem. Já o RYR1 codifica a rianodina, um importante receptor de cálcio nos osteoblastos. Estudos funcionais dos genes identificados são necessários para validar esta hipótese em pesquisas futuras. Os resultados deste trabalho sugerem que ferramentas de bioinformática podem direcionar a busca por novos genes relacionados a doenças genéticas. A caracterização de novas mutações em genes relacionados com OI auxilia no planejamento de estratégias mais eficientes que permitam o diagnóstico molecular da doença e o aconselhamento genético.Texthttp://repositorio.ufes.br/handle/10/7116porUniversidade Federal do Espírito SantoMestrado em BiotecnologiaPrograma de Pós-Graduação em BiotecnologiaUFESBRCentro de Ciências da SaúdeNext generation sequencingBioinformaticsOsteogenesis imperfectaBioinformáticaOsteogênese imperfeitaGene ALX1Gene RYR1Biotecnologia61Utilização da bioinformática na busca de novos genes em osteogênese imperfeitainfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da Universidade Federal do Espírito Santo (riUfes)instname:Universidade Federal do Espírito Santo (UFES)instacron:UFESORIGINALtese_12056_Dissertação_Amanda Silva Coutinho.pdfapplication/pdf1166104http://repositorio.ufes.br/bitstreams/e7eb3f90-c711-47fb-b97e-00aaba1aeab9/downloadf4756c682c195491abc65c33b3ce87fcMD5110/71162024-06-27 11:03:32.556oai:repositorio.ufes.br:10/7116http://repositorio.ufes.brRepositório InstitucionalPUBhttp://repositorio.ufes.br/oai/requestopendoar:21082024-06-27T11:03:32Repositório Institucional da Universidade Federal do Espírito Santo (riUfes) - Universidade Federal do Espírito Santo (UFES)false
dc.title.none.fl_str_mv Utilização da bioinformática na busca de novos genes em osteogênese imperfeita
title Utilização da bioinformática na busca de novos genes em osteogênese imperfeita
spellingShingle Utilização da bioinformática na busca de novos genes em osteogênese imperfeita
Coutinho, Amanda Silva
Next generation sequencing
Bioinformatics
Osteogenesis imperfecta
Bioinformática
Osteogênese imperfeita
Gene ALX1
Gene RYR1
Biotecnologia
61
title_short Utilização da bioinformática na busca de novos genes em osteogênese imperfeita
title_full Utilização da bioinformática na busca de novos genes em osteogênese imperfeita
title_fullStr Utilização da bioinformática na busca de novos genes em osteogênese imperfeita
title_full_unstemmed Utilização da bioinformática na busca de novos genes em osteogênese imperfeita
title_sort Utilização da bioinformática na busca de novos genes em osteogênese imperfeita
author Coutinho, Amanda Silva
author_facet Coutinho, Amanda Silva
author_role author
dc.contributor.advisor1.fl_str_mv Paula, Flávia de
dc.contributor.author.fl_str_mv Coutinho, Amanda Silva
dc.contributor.referee1.fl_str_mv Errera, Flavia Imbroisi Valle
dc.contributor.referee2.fl_str_mv Maranduba, Carlos Magno da Costa
contributor_str_mv Paula, Flávia de
Errera, Flavia Imbroisi Valle
Maranduba, Carlos Magno da Costa
dc.subject.eng.fl_str_mv Next generation sequencing
Bioinformatics
Osteogenesis imperfecta
topic Next generation sequencing
Bioinformatics
Osteogenesis imperfecta
Bioinformática
Osteogênese imperfeita
Gene ALX1
Gene RYR1
Biotecnologia
61
dc.subject.por.fl_str_mv Bioinformática
Osteogênese imperfeita
Gene ALX1
Gene RYR1
dc.subject.cnpq.fl_str_mv Biotecnologia
dc.subject.udc.none.fl_str_mv 61
description Osteogenesis imperfecta (OI) is a rare genetic disease of connective tissue caused by mutations in genes that generally participate in bone formation. Most patients carry mutations in the genes encoding type 1 collagen, but mutations in more than 17 other genes causing OI have been described and there is still a constant search for new genes in the scientific field. Among the molecular diagnostic strategies, the new generation sequencing method (NGS) stands out, which can sequence several genes present in a customized platform generating a large amount of genomic data. These data become precious sources of information in the search for new genes related to diseases. The objective of this research was to perform the search for new genes potentially causing OI through bioinformatics resources. We used filtering strategies by the Microsoft Office Excel 2013 program, as well as mutation prediction analyzes. As a genomic reference, the Ensembl and National Center for Biotechnology Information databases were used. We selected four patients diagnosed clinically with OI who were submitted to the NGS technique and presented normal results for the known genes. In order to select a list of candidate genes in the NGS custom platform that were related to OI symptoms, a search of genes in the Ensembl database involved with the metabolic pathways of bone, cartilage or collagen formation was performed, which identified 643 genes. The list of candidate genes was compared to the sequenced genes of the patients, where 70 genes in common were selected for analysis. In silico, filtrations were performed in order to select rare changes in the population, predicted as pathogenic and that effectively encode a functional RNA protein or molecule. The results showed that patient P.1 carries a potentially pathogenic heterozygous mutation in the ALX1 gene. Patient P.2 presented only one alteration in the COL6A3 gene that was predicted as polymorphism. Patient P.3 presented pathogenic mutations in heterozygosity in the ALPL and FKBP10 genes. In patient P.4, pathogenic mutations in heterozygosis were found in the P3H1 and RYR1 genes. Among the five genes identified, two of them, FKBP10 and P3H1, are known to be related to autosomal recessive OI. It has also been described that mutations in the ALPL gene cause clinical symptoms similar to OI, which may confuse the diagnosis. Thus, the present study identified two genes, ALX1 and RYR1, potentially causing OI. The ALX1 gene plays an important role in cranial and limb development, as it acts on the formation of cartilage. RYR1 encodes ryanodine, an important calcium receptor in osteoblasts. Functional studies of the identified genes are necessary to validate this hypothesis in future research. The results of this work suggest that bioinformatics tools may direct the search for new genes related to genetic diseases. The characterization of new mutations in OI-related genes enables the planning of more efficient strategies that allow molecular diagnosis of the disease and genetic counseling.
publishDate 2018
dc.date.accessioned.fl_str_mv 2018-08-01T21:35:03Z
dc.date.available.fl_str_mv 2018-08-01
2018-08-01T21:35:03Z
dc.date.issued.fl_str_mv 2018-02-26
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://repositorio.ufes.br/handle/10/7116
url http://repositorio.ufes.br/handle/10/7116
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv Text
dc.publisher.none.fl_str_mv Universidade Federal do Espírito Santo
Mestrado em Biotecnologia
dc.publisher.program.fl_str_mv Programa de Pós-Graduação em Biotecnologia
dc.publisher.initials.fl_str_mv UFES
dc.publisher.country.fl_str_mv BR
dc.publisher.department.fl_str_mv Centro de Ciências da Saúde
publisher.none.fl_str_mv Universidade Federal do Espírito Santo
Mestrado em Biotecnologia
dc.source.none.fl_str_mv reponame:Repositório Institucional da Universidade Federal do Espírito Santo (riUfes)
instname:Universidade Federal do Espírito Santo (UFES)
instacron:UFES
instname_str Universidade Federal do Espírito Santo (UFES)
instacron_str UFES
institution UFES
reponame_str Repositório Institucional da Universidade Federal do Espírito Santo (riUfes)
collection Repositório Institucional da Universidade Federal do Espírito Santo (riUfes)
bitstream.url.fl_str_mv http://repositorio.ufes.br/bitstreams/e7eb3f90-c711-47fb-b97e-00aaba1aeab9/download
bitstream.checksum.fl_str_mv f4756c682c195491abc65c33b3ce87fc
bitstream.checksumAlgorithm.fl_str_mv MD5
repository.name.fl_str_mv Repositório Institucional da Universidade Federal do Espírito Santo (riUfes) - Universidade Federal do Espírito Santo (UFES)
repository.mail.fl_str_mv
_version_ 1804309179100299264