The cell nucleus is a heterogeneous organelle that consists of nuclear bodies such as nuclear lamina, speckles, nucleoli and PML bodies. These structures continuously tether and tug chromatin at the small and large scales to synergistically orchestrate dynamic functions in distinct spatio-temporal compartments. A major obstacle to the production of navigable 4D reference maps and relating structure to function in the nucleus remains understanding how these different scales of organization influence each other. In particular, we have a poor understanding of the large-scale genome organization. Growing evidence suggests that such nuclear compartmentalization is causally connected with vital genome functions in human health and disease. However, the principles of this nuclear compartmentalization, its dynamics during changes in cell conditions, and its functional relevance are poorly understood. One lesson from Phase 1 4DN was the huge gap in throughput between imaging methods, that directly measure large-scale multi-landmark relationships, and genomic methods, that aim for whole genome high-resolution maps but are indirect measurements and provide limited information about large-scale compartments. For this 4DN UM1 Center application, we propose to meet these needs through the following Aims: (1) Generate multi-modal imaging and genomic datasets to reveal the structure, dynamics, and function of nuclear compartmentalization; (2) Develop and apply computational tools for data-driven genome structure modeling and integrative analysis of nuclear compartmentalization; (3) Develop an integrative analysis and visualization platform with navigable 4D reference maps of nuclear organization. The combined datasets and results of our proposed approaches will advance our understanding of nuclear compartmentalization, the interwoven connections among different nuclear components, and their functional significance. Our new integrative analysis tools and data-driven predictive models will produce more complete nuclear organization reference maps that integrate large-scale chromosome structure data from live and super-resolution microscopy with multi-modal genomic data including smaller scale chromatin interaction maps and predict functional relationships and dynamic responses. Our navigable reference maps will be publicly accessible through an analysis platform that provides interactive visualization of multiple data types, thus enabling investigators with diverse expertise to simultaneously explore their own data and related datasets/tools and promoting collaborations that will open new horizons into the role of the 4D nucleome in human health and disease.

Public Health Relevance

The proposed research is relevant to public health because it will enhance our understanding of nuclear genome organization and functions that are increasingly being linked to health and disease. Because we develop tools to disseminate this information and enable others to work with our data and their own data, we will also bring nuclear architecture to bear on a broad range of ongoing health related research. Thus, the proposed research is relevant to NIH?s mission that seeks to obtain fundamental knowledge that will help to improve human health.

National Institute of Health (NIH)
National Human Genome Research Institute (NHGRI)
Research Project with Complex Structure Cooperative Agreement (UM1)
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Special Emphasis Panel (ZRG1)
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Pazin, Michael J
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Carnegie-Mellon University
Biostatistics & Other Math Sci
Schools of Arts and Sciences
United States
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