Computational Approaches for the Analysis of Chromosome Conformation Capture Data and Their Application to Study Long-Range Gene Regulation: A Dissertation
AuthorsLajoie, Bryan R.
Faculty AdvisorJob Dekker
Academic ProgramBioinformatics and Computational Biology
UMass Chan AffiliationsProgram in Systems Biology
Document TypeDoctoral Dissertation
Dosage Compensation, Genetic
Gene Expression Regulation
Sequence Analysis, RNA
chromosome conformation capture
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AbstractOver the last decade, development and application of a set of molecular genomic approaches based on the chromosome conformation capture method (3C), combined with increasingly powerful imaging approaches have enabled high resolution and genome-wide analysis of the spatial organization of chromosomes. The aim of this thesis is two-fold; 1), to provide guidelines for analyzing and interpreting data obtained from genome-wide 3C methods such as Hi-C and 3C-seq and 2), to leverage the 3C technology to solve genome function, structure, assembly, development and dosage problems across a broad range of organisms and disease models. First, through the introduction of cWorld, a toolkit for manipulating genome structure data, I accelerate the pace at which *C experiments can be performed, analyzed and biological insights inferred. Next I discuss a set of practical guidelines one should consider while planning an experiment to study the structure of the genome, a simple workflow for data processing unique to *C data and a set of considerations one should be aware of while attempting to gain insights from the data. Next, I apply these guidelines and leverage the cWorld toolkit in the context of two dosage compensation systems. The first is a worm condensin mutant which shows a reduction in dosage compensation in the hermaphrodite X chromosomes. The second is an allele-specific study consisting of genome wide Hi-C, RNA-Seq and ATAC-Seq which can measure the state of the active (Xa) and inactive (Xi) X chromosome. Finally I turn to studying specific gene – enhancer looping interactions across a panel of ENCODE cell-lines. These studies, when taken together, further our understanding of how genome structure relates to genome function.
Permanent Link to this Itemhttp://hdl.handle.net/20.500.14038/32205
Table 3.1, RNA-Seq Table for all genes, is available only via GEO due to size, under accession number GSE72697.
Brian Lajoie was in the GSBS Bioinformatics and Computational Biology academic program, not the Interdisciplinary Graduate Program as stated on page 2.
RightsCopyright is held by the author, with all rights reserved.
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