Localização de regiões potenciais para integração do kDNA de Trypanosoma cruzi no genoma humano

• Ano de defesa: 2016
• Autor(a) principal: Santana, Jhonne Pedro Pedott
• Orientador(a): Leonardecz, Eduardo
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Genética Evolutiva e Biologia Molecular - PPGGEv
• Palavras-chave em Português: Transferência Horizontal de Genes; Análise Bioinformática; Genoma Humano; Doença de Chagas; Trypanosoma cruzi; kDNA
• Palavras-chave em Inglês: Horizontal Gene Transfer; Bioinformatics Analysis; Human Genome; Chagas Disease; Trypanosoma cruzi; kDNA
• Área do conhecimento CNPq: CIENCIAS BIOLOGICAS
• Link de acesso: https://repositorio.ufscar.br/handle/ufscar/7537

Knowledge about horizontal gene transfer has been proposed even before the determination of the molecular structure of DNA. It has been experimentally shown that micro-homologies rich in adenine and cytosine mediates the integration of Trypanosoma cruzi’s kDNA minicircle, in the vertebrate genome. After human genome sequencing, the genome characterization of different organisms has been one of the main driving forces of science, providing a quantity of biological data for modern biomedical research, unprecedented in the history of science. However, even though traditional DNA mapping algorithms are highly accurate, they operate at a much lower rate than that needed for the next generation sequencers to accumulate new data. This great asymmetry between data generation and analysis capability requires the rapid evolution of mapping and reading algorithms so that this large volume of information can be worked through targeted searches. Thus, this work proposes an efficient, fast and easy way to search and locate multiple signatures of indicators that allow exogenous kDNA integration in the human genome, by creating a set of scripts for in silico analysis adapted to large files sequences. Three scripts based in R language were developed: to permute the elements (nucleic acids or amino acids codes); for search, grouping and plotting matches in genome; and for counting total matches and chromosomal window. All adenine and cytosine signatures were properly identified in the human genome, but no point more susceptible to T. cruzi kDNA integration was identified. With the obtained data, a genetic map was created, listing all matchings in each cytogenetic band, but it was not possible to identify which chromosome was more prone to mutations, since the bigger the chromosome is, the higher the quantity of matches are.