Utilização da bioinformática na busca de novos genes em osteogênese imperfeita

• Ano de defesa: 2018
• Autor(a) principal: Coutinho, Amanda Silva
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Espírito Santo; BR; Mestrado em Biotecnologia; Centro de Ciências da Saúde; UFES; Programa de Pós-Graduação em Biotecnologia
• Palavras-chave em Português: Next generation sequencing; Bioinformatics; Osteogenesis imperfecta; Bioinformática; Osteogênese imperfeita; Gene ALX1; Gene RYR1; Biotecnologia; 61
• Link de acesso: http://repositorio.ufes.br/handle/10/7116

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.