Network analysis of transcriptional regulation of acinar cell identity using transcription factor footprinting inference from ATAC-seq data
Cell identity can be considered an important tumor suppressor mechanism. In this context, the clarification of the regulatory mechanisms of said identity, fundamentally of the activity of the transcription factors that regulate the expression of different transcriptional programs, is essential. Taki...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universitat Oberta de Catalunya (UOC) |
| Repositorio: | O2, repositorio institucional de la UOC |
| OAI Identifier: | oai:openaccess.uoc.edu:10609/147684 |
| Acceso en línea: | http://hdl.handle.net/10609/147684 |
| Access Level: | acceso abierto |
| Palabra clave: | transcriptional regulation acinar identity bioinformatics bioinformática regulación transcripcional identidad acinar bioinformàtica regulació transcripcional identitat acinar Bioinformatics -- TFM Bioinformàtica -- TFM Bioinformática -- TFM |
| Sumario: | Cell identity can be considered an important tumor suppressor mechanism. In this context, the clarification of the regulatory mechanisms of said identity, fundamentally of the activity of the transcription factors that regulate the expression of different transcriptional programs, is essential. Taking the three-dimensional structure of the chromatin as a starting point from the data provided by the technique Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq), the aim is to clarify the transcriptional networks involved in the maintenance of homeostatic conditions in the murine pancreas to later recognize those transcriptional programs involved in the loss of necessary cellular identity in the carcinogenic process. For this, data are available from genetically modified animals used as models in the study of pancreatic ductal adenocarcinoma (PDAC). With this work, it is expected to have a better understanding of gene regulation networks and therefore of the relationship between transcription factors, their binding sites and the genes involved in the studied cancer. With the creation of these networks, results obtained experimentally can be confi rmed as well as serve as a basis for new research, establishing a bidirectional relationship between computational work and that carried out in the laboratory. Likewise, it is expected that the information obtained can be presented as a resource that can be used by other researchers for their work. All of this has the ultimate goal of better understanding and combating pancreatic cancer. |
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