Collaborative Research: Integrative Modeling, Prediction, and Validation of Multi-Scale Dynamics for Three-Dimensional Chromatin Structures in Cell Differentiation

This interdisciplinary award develops mathematical models and computational algorithms to dissect the mechanisms of how different types of cells are formed from stem cells. The formation of specific cell types plays pivotal roles in all aspects of life, and different tissues are composed of hundreds of types of cells. As one of the underlying mechanisms, the 3D structure of DNA undergoes dynamic reshaping and instructs this complex process.

However, it is under-studied and quantitative models are lacking due to the complexity of the system and large amounts of noisy data. The project will establish a novel mathematical framework to understand the dynamics of DNA structures and its effects on new cell type formation. Efficient computational and statistical algorithms will also be designed to discover the molecular drivers, which will be interrogated by cutting-edge experiments.

The integrative strategy will lead to new systems-level insights into the molecular mechanisms of the formation of diverse cell types, with broad impacts on human health, synthetic biology and disease analyses, including neurodegenerative diseases and cancer. To expand the societal impacts, the project will integrate the scientific discoveries with a series of outreach activities for public engagement, including new interactive educational modules and platforms.

Interdisciplinary hands-on training will be developed for both undergraduate and graduate students, with an emphasis on increasing the diversity and participation of under-represented groups of students for STEM education.

The overall goal is to theoretically and quantitatively delineate the functional roles of dynamic 3D genome structures in the process of multi-lineage cell differentiation. Due to the complexity of multi-scale 3D organizations of chromatin, the coupled dynamics of transcription and epigenetic factors, and the high rates of missing data in genome-wide experiments, systems-level modeling of the temporal dynamics of 3D chromatin through specific cell differentiation trajectory has been challenging.

The project tackles this fundamental problem using an integrative strategy by combining mathematical, computational, statistical and experimental approaches. Specifically, the project will: 1) establish a new multi-scale mathematical model for the dynamics of 3D chromatin architecture through cell differentiation, by integrating different experimental observations; 2) design novel computational algorithms to reconstruct the trajectories across cell differentiation from large-scale noisy data; and 3) develop efficient statistical inference tools to discover the underlying molecular events of cell fate determination.

Both theoretical and computational predictions will be thoroughly analyzed by experimental techniques, including 3C-HTGTS and 3D FISH. The new methodology generated by the project, along with the genome-wide predictions across diverse panels of cell types, will have broad impacts on multiple scientific fields in both mathematics and biology, and will significantly improve the mechanistic understandings, predictive capacities and experimental engineering of cell differentiation.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.