Classification of open chromantin regions based on ATAC-seq signal topography
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Abstract
Trabajo Fin de Máster en Análisis de Datos Ómicos y Biología de Sistemas. Tutores: Dr. D. José Carlos Reyes ; Dr. D. José Antonio Guerrero-Martínez. Chromatin accessibility is key for the regulation of DNA expression and studies about it help to map the different transcriptional landscapes the cell can have under determined circumstances. The ATAC-seq assay employs the transposase Tn5 to identify regions of accessible chromatin, however, the proper software or pipelines to analyze the ATAC-seq data are still very scarce. Here we show that peak-shape based clustering and analysis developed for ChIP-seq data is also valid for ATAC-seq datasets. Our study provided information about how clusters showed different distribution of promoter and enhancer regions as well as distinctive signatures of histone marks and transcription factors associated to motifs. We also developed a prediction model to specify how peak shape can be useful for determining DNA elements’ nature. These results show how peak shape provides useful information about the chromatinic state of the genes and reveal interesting biological insights about transcription regulation and up-regulated biological processes. This study can be the starting point for more ATAC-seq analysis studied in different cell lines, phases of the cell or pathologic circumstances in order to provide a general overview of the accessible chromatin regions, the transcriptional state of the cell and the epigenetic marks of DNA.
Trabajo Fin de Máster en Análisis de Datos Ómicos y Biología de Sistemas. Tutores: Dr. D. José Carlos Reyes ; Dr. D. José Antonio Guerrero-Martínez. Chromatin accessibility is key for the regulation of DNA expression and studies about it help to map the different transcriptional landscapes the cell can have under determined circumstances. The ATAC-seq assay employs the transposase Tn5 to identify regions of accessible chromatin, however, the proper software or pipelines to analyze the ATAC-seq data are still very scarce. Here we show that peak-shape based clustering and analysis developed for ChIP-seq data is also valid for ATAC-seq datasets. Our study provided information about how clusters showed different distribution of promoter and enhancer regions as well as distinctive signatures of histone marks and transcription factors associated to motifs. We also developed a prediction model to specify how peak shape can be useful for determining DNA elements’ nature. These results show how peak shape provides useful information about the chromatinic state of the genes and reveal interesting biological insights about transcription regulation and up-regulated biological processes. This study can be the starting point for more ATAC-seq analysis studied in different cell lines, phases of the cell or pathologic circumstances in order to provide a general overview of the accessible chromatin regions, the transcriptional state of the cell and the epigenetic marks of DNA.