Differential DNA methylation in aging: in silico exploration using high-throughput datasets

• Autor(a) principal: Conceição, Carolina Neves
• Data de Publicação: 2018
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10773/24223
• topic: Microarray tecnhnology; Next-generation sequencing; Epigenomics; Bioinformatics; DNA methylation; Genome-wide analysis; Bisulfite conversion; Epigenetic programming; Genetic regulation

The emergence of high-throughput methodologies after the conclusion of the Human Genome Project has brought genomic and epigenomic wide studies to the forefront of current research of biological and biomedical knowledge. Currently, the focus in genetic mutations as primary cause of certain disorders is not so relevant as before, since it was demonstrated that epigenetic mechanisms are involved in cellular programming and gene regulation providing adaptive variants of a given gene to a changing environment with an association to cellular differentiation. The research in the DNA methylation field has already revealed essential facts as the existence of methylation in CpG islands and alternative contexts that influence gene expression in tissue-specific manner. The influence of lifestyle choices in aging processes has also been related to methylome variations. And, in the case of cancer, the cooperation of epigenetic and genetic information is essential to understand the progress of cancer development as well as the silencing of key regulatory genes. An overall hypomethylation in cancer genome leads to oncogene activation whereas hypermethylation in specific regions is associated with silencing of tumour suppressor genes. For that reason, the research for new therapeutic approaches to cancer and aging is a current issue of the scientific community that work in the epigenomic field. In order to contribute to the study of mammalian epigenomes during lifespans, this research focused on the usage of public databases datasets to further investigation about DNA methylation across aged individuals in order to extract tissue-specific markers related with healthy aging. The validation of results was made through the usage of samples, form healthy individuals with good or bad cognitive performances, available in iBiMED. In both situations the genes ELOVL2 (cg16867657) and FHL2 (cg06639320) were identified as good markers of age