Análise bioinformática de RNAs não-codificantes no genoma de coffea canephora

• Ano de defesa: 2018
• Autor(a) principal: Lemos, Samara Mireza Correia de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso embargado
• Idioma: por
• Instituição de defesa: Universidade Tecnológica Federal do Paraná; Cornelio Procopio; Brasil; Programa de Pós-Graduação em Bioinformática; UTFPR
• Palavras-chave em Português: Genômica; Café; Bioinformática; Genomics; Coffee; Bioinformatics; CNPQ::CIENCIAS EXATAS E DA TERRA; Genética
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/3421

Coffea canephora, also known as Robusta coffee, has great commercial importance and belongs to genus Coffea (Rubiaceae family). Its grains are highly traded commodities worldwide and its production corresponds to approximately 40% of world production and 24% of Brazilian production. It is the only species of the genus with public genome data released so far. Noncoding RNAs (ncRNAs) are important transcriptional products involved in genome regulation, environmental responses and organism development. Compared to animals, there are few studies on plant ncRNAs; almost none of these studies addresses ncRNAs at the genomic level, and genomic studies are limited to specific classes of ncRNAs in model plant species. This study aims to make the computational identification of ncRNAs in C. canephora genome. We performed the identification of six ncRNAs classes - tRNAs, rRNAs, miRNAs, snRNAs, snoRNAs and lncRNAs - using nucleotide identity and structural similarity, with validation in transcriptome data. We identified 589 transporter RNAs, 86 ribosomal RNAs, 3 microRNAs, 115 small nuclear RNAs, 99 small nucleolar RNAs and 3176 long non-coding RNAs. This data is the largest genomic catalog of ncRNAs in Coffea with curation to date. Data is comparable to other angiosperm species, but there is still big differences in identifying ncRNAs among plant genomes. The main contribution of this work is that this data will help the elaboration of more robust hypotheses in future comparative genomic studies as well as, gene regulation and genome dynamics studies. This information may help understanding the molecular basis of domestication, environmental adaptation, resistance to pests and diseases, and coffee productivity.