? Data Analysis and Modeling Despite the growing quantity and resolution of chromosome interaction data our understanding of physical principles underling chromosomal organization and its connection with genomic function remain limited. Mapping of chromosomal interactions proposed in Component 2, will provide large amounts of data from a variety of methods that each address its own aspect and range of scales of chromosomal organization. Further progress, however, relies on our ability to bridge between these new data and 3D physical models of chromosomes that can reveal principles of genome folding. We will continue development of methods for processing, correction and analysis of data from Hi-C- based technologies, as well as development of polymer models of chromosomal organization that have been successful in reproducing Hi-C and microscopy data for human and bacterial chromosomes, and have been able to reveal structural elements not immediately visible in the data. Here we propose to take a full advantage of the new mapping technologies and further develop our physics-based approach to address several challenges in understanding biological mechanisms and physical principles of chromosomes folding. Modeling will also provide a natural platform for integration of interaction and imaging data. First, we will develop computational tools for processing data produced by new Hi-C-based technologies, (micro-C, high-resolution Hi-C, allele-specific Hi-C and single-cell Hi-C), and integrate data across scales into Integrated Interaction Maps. Second, we will develop computational tools to analyze Interaction Maps produced by new Hi-C-based technologies, aiming to reveal structural elements of human chromosomes at different scales. Third, we will develop polymer models that will allow validation of Hi-C interaction maps by HIPMap microscopy data, as proposed in Component 2. Finally, we will develop a comprehensive multi-scale polymer model of human chromosomal organization, comparing it to new interaction data at every scale. All models and discovered principles of organization will be systematically validated using imaging, genome engineering, and micromechanical experiments as outlined in Components 4 and 5.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54DK107980-03
Application #
9353819
Study Section
Special Emphasis Panel (ZRG1)
Project Start
Project End
Budget Start
2017-08-01
Budget End
2018-07-31
Support Year
3
Fiscal Year
2017
Total Cost
Indirect Cost
Name
University of Massachusetts Medical School Worcester
Department
Type
DUNS #
603847393
City
Worcester
State
MA
Country
United States
Zip Code
01655
Adriaens, Carmen; Serebryannyy, Leonid A; Feric, Marina et al. (2018) Blank spots on the map: some current questions on nuclear organization and genome architecture. Histochem Cell Biol 150:579-592
Brahmachari, Sumitabha; Dittmore, Andrew; Takagi, Yasuharu et al. (2018) Defect-facilitated buckling in supercoiled double-helix DNA. Phys Rev E 97:022416
Dixon, Jesse R; Xu, Jie; Dileep, Vishnu et al. (2018) Integrative detection and analysis of structural variation in cancer genomes. Nat Genet 50:1388-1398
Kundu, Sharmistha; Ji, Fei; Sunwoo, Hongjae et al. (2018) Polycomb Repressive Complex 1 Generates Discrete Compacted Domains that Change during Differentiation. Mol Cell 71:191
Gao, Xin D; Tu, Li-Chun; Mir, Aamir et al. (2018) C-BERST: defining subnuclear proteomic landscapes at genomic elements with dCas9-APEX2. Nat Methods 15:433-436
Hansen, Anders S; Woringer, Maxime; Grimm, Jonathan B et al. (2018) Robust model-based analysis of single-particle tracking experiments with Spot-On. Elife 7:
Chong, Shasha; Dugast-Darzacq, Claire; Liu, Zhe et al. (2018) Imaging dynamic and selective low-complexity domain interactions that control gene transcription. Science 361:
Gibcus, Johan H; Samejima, Kumiko; Goloborodko, Anton et al. (2018) A pathway for mitotic chromosome formation. Science 359:
Andrews, J O; Conway, W; Cho, W -K et al. (2018) qSR: a quantitative super-resolution analysis tool reveals the cell-cycle dependent organization of RNA Polymerase I in live human cells. Sci Rep 8:7424
Skoruppa, Enrico; Nomidis, Stefanos K; Marko, John F et al. (2018) Bend-Induced Twist Waves and the Structure of Nucleosomal DNA. Phys Rev Lett 121:088101

Showing the most recent 10 out of 49 publications