Utilização de ferramentas bioinformáticas para busca, análise e compreensão de informações oriundas de Next Generation Sequencing e descoberta de miRNAs conservados utilizando mirDeep2

• Ano de defesa: 2021
• Autor(a) principal: Vargas, Roberta Moura Ramos
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Uberlândia; Brasil; Programa de Pós-graduação em Biotecnologia
• Palavras-chave em Português: Biotecnologia; Biotechnology; Bioinformática; Bioinformatics; NGS; miRNAs; mirDeep2; CNPQ::CIENCIAS BIOLOGICAS::BIOQUIMICA::BIOLOGIA MOLECULAR; Biologia molecular
• Link de acesso: https://repositorio.ufu.br/handle/123456789/33986; http://doi.org/10.14393/ufu.di.2022.36

In the 1970s, the first sequencing methods were created. A while later, new automated methods emerged, the next generation sequencing techniques (NGS). NGS is currently used for the generation of genomic data, producing increasing amounts of information at low cost. These techniques allow RNA sequencing, facilitating the acquisition of large transcriptomic sets. MicroRNAs are a subset of small molecules of non-coding RNAs, with approximately 22 nucleotides, considered post-transcriptional regulators that can cleave target mRNAs, repress their translation and lead to decreased mRNA stability, they play an important role in most biological processes that has not yet been fully revealed. An accurate quantification of miRNA is very important as a computational strategy to reduce or minimize potentially false mappings against the genome for its identification. The software most used in the quantification of miRNAs is mirDeep2. In this way, this research aims to apply Bioinformatics computational tools to data from Next Generation Sequencing in the search for important information that can contribute to the advancement of science, using only an in silico platform. From the analysis of samples performed by mirDeep2, it can be seen that there are possible miRNAs present in cancerous tissues. MiRNA targets were predicted and information was also gathered from raw sequencing data from NGS (SRRs); the first 10 targets of each miRNA were summarized and the order in which they appeared in the different programs used for this analysis was also shown.