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Extensive multiplexing of protein nucleic-acid interactions to comprehensively study gene expression regulation from chromatin to mRNA degradation

$77,619R01FY2023HGNIH

Columbia Univ New York Morningside, New York NY

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Abstract

Although every cell in the body contains the same DNA sequence, mammalian organisms consist of thousands of cell types defined by distinct gene expression programs. How molecular components, including DNA, RNA and proteins, act to control gene expression is a long-standing question. The model whereby regulatory factors diffuse through the nucleus and engage with their cognate DNA and RNA targets through high affinity interactions cannot explain many of the quantitative features required for gene regulation. The observation that many transcription factors and chromatin regulators organize into higher-order structures within the nucleus may explain the quantitative aspects. Yet, we don’t know (i) the DNA binding and spatial organization of most regulators, (ii) what specific components are present within these compartments, and (iii) what role spatial organization plays in gene regulation. The challenge is that we lack methods to measure combinatorial organization of these molecular components and the ability to disrupt compartmentalization and measure its impact on gene regulation. To address this, we are developing cutting-edge genome-scale methods that allow us to measure multiplexed protein binding and spatial organization of DNA. Specifically, we will create genome-wide maps of hundreds of DNA binding proteins including transcription factors, chromatin regulators, histones (with various modifications) and RNA polymerases. We will then explore the RNA-dependence of regulatory proteins localization by comparing spatial organization in the presence and absence of RNase treatment. Finally, we will then disrupt formation of specific regulatory compartments (using Locked Nucleic Acid and/or CRISPR approaches) to understand possible mechanisms of spatial organization in regulation of specific genes. Our results will provide novel capabilities and a framework for understanding how DNA, RNA, and protein molecules work together in 3D space to efficiently regulate gene expression.

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