Massively parallel analysis of nucleic acid strucure

Abstract

A goal amongst modern biologists is to “compute” cellular and organismal function. This “computation” necessitates a holistic understanding of the biochemical mechanisms underlying different cellular states. Methods that pair massively parallel sequencing and biochemical analyses of cells have brought us much closer to this ultimate goal, enabling genome-wide mapping and quantification of molecules responsible for cellular function. My thesis work has focused on developing methods to measure the structure of RNA and DNA molecules in cells, a parameter thought to play a critical role in regulating the expression of genes, and thus cellular state. In this thesis, I describe novel methods for studying i.) intramolecular RNA structure, ii.) genome-wide chromosomal structure in populations of mammalian cells, and iii.) genome-wide chromosomal structure in single mammalian cells. Importantly, these cutting-edge approaches enable scalable, genome-wide, and high-resolution analyses of intramolecular nucleic acid structure in populations of cells, and within single cells.