Bioinformatics and Computational Biology
Department of Systems Biology
First Thesis Advisor
Hi-C 3.0, Method Comparison, 3D Methods, 3C-Based Methods
Understanding 3D genome structure is crucial to learn how chromatin folds and how genes are regulated through the spatial organization of regulatory elements. Various technologies have been developed to investigate genome architecture. These technologies include ligation-based 3C Methodologies such as Hi-C and Micro-C, ligation-based pull-down methods like Proximity Ligation-Assisted ChIP-seq (PLAC Seq) and Paired-end tag sequencing (ChIA PET), and ligation-free methods like Split-Pool Recognition of Interactions by Tag Extension (SPRITE) and Genome Architecture Mapping (GAM). Although these technologies have provided great insight into chromatin organization, a systematic evaluation of these technologies is lacking. Among these technologies, Hi-C has been one of the most widely used methods to map genome-wide chromatin interactions for over a decade. To understand how the choice of experimental parameters determines the ability to detect and quantify the features of chromosome folding, we have first systematically evaluated two critical parameters in the Hi-C protocol: cross-linking and digestion of chromatin. We found that different protocols capture distinct 3D genome features with different efficiencies depending on the cell type (Chapter 2). Use of the updated Hi-C protocol with new parameters, which we call Hi-C 3.0, was subsequently evaluated and found to provide the best loop detection compared to all previous Hi-C protocols as well as better compartment quantification compared to Micro-C (Chapter 3). Finally, to understand how the aforementioned technologies (Hi-C, Micro-C, PLAC-Seq, ChIA-PET, SPRITE, GAM) that measure 3D organization could provide a comprehensive understanding of the genome structure, we have performed a comparison of these technologies. We found that each of these methods captures different aspects of the chromatin folding (Chapter 4). Collectively, these studies suggest that improving the 3D methodologies and integrative analyses of these methods will reveal unprecedented details of the genome structure and function.
Akgol-Oksuz B. (2022). Detection of 3D Genome Folding at Multiple Scales. Morningside Graduate School of Biomedical Sciences Dissertations and Theses. https://doi.org/10.13028/28we-2b52. Retrieved from https://escholarship.umassmed.edu/gsbs_diss/1189
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