Coutinho, Vinicius Ramos Henriques MaracajáRamos, Thaís de Almeida Ratis2022-10-142022-10-142022-08-02RAMOS, Thaís de Almeida Ratis. Caracterização computacional de RNAs não codificantes longos a nível unicelular associados com o desenvolvimento do tecido cardíaco e com doenças cardiovasculares. Orientador: Vinicius Ramos Henriques Maracajá Coutinho. 2022. 149f. Tese (Doutorado em Bioinformática) - Instituto Metrópole Digital, Universidade Federal do Rio Grande do Norte, Natal, 2022.https://repositorio.ufrn.br/handle/123456789/49581Long non-coding RNAs (lncRNAs) comprise the most representative transcriptional units of the mammalian genome, and they’re associated with organ development that can be associated with the emergence of diseases, such as cardiovascular diseases. The World Health Organization (WHO), for example, has published that cardiovascular diseases are responsible for the death of 17.9 million people each year, corresponding to 31% of all deaths all around the world. In this work, a reference database of lncRNAs and coding transcripts was built: a combination of lncRNAs from the Gencode (M20), Ensembl (GRCm38.95) and Amaral et al. (2018) databases was used to define the set of non-redundant reference lncRNAs, i.e., lncRNAs that did not have an overlap above 50%; moreover, for the reference database of coding transcripts, the Gencode database (M20) was used. In addition, bioinformatics approaches were used (RNA-seq pipeline was adapted for single-cell data analysis), machine learning algorithms (Hierarchical, Silhouette, PCA and t-SNE) and statistical techniques to define lncRNAs involved in mammalian cardiac development in a single-cell perspective. For this, the single-cell database published by DeLaughter et al. (2016) was used, in which there were data from 4 embryonic stages (E9.5, E11.5, E14.5, E18.5) and 4 post -natals (P0, P3, P7, P21) of the mus musculus model organism. Our study identified 8 distinct cell types, novel marker transcripts (coding/lncRNAs) and also, differential expression and functional enrichment analysis revealed cardiomyocyte subpopulations associated with cardiac function; meanwhile modular co-expression analysis reveals cell-specific functional insights for lncRNAs during myocardial development, including a potential association with key genes related to disease and the “fetal gene program”. Our results evidence the role of particular lncRNAs in heart development, and highlights the usage of co-expression modular approaches in the cell-type functional definition. As future work, we intend to acquire the functional roles of these RNAs in the development of cardiac tissues and in cardiovascular diseases using experimental validation approaches.Acesso AbertoSingle cellDesenvolvimento do coraçãoDoenças cardiovascularesAprendizagem de máquinaSubpopulações de cardiomiócitodoctoralThesisCNPQ::CIENCIAS BIOLOGICAS