Bayesian determination of static chromatin structure from Hi-C data and DCS studies of chromatin dynamics in ESCs and derived neurons

Center for Soft Matter Research, Department of Physics, NYU

Recent advances in experimental techniques allow insight into the spatial organization of the genome in unprecedented detail. Hi-C, a generalization of Chromosome Conformation Capture (3C), is a crosslinking experiment that yields contact matrices from which the three-dimensional conformation of chromosomes can be reconstructed. In the first part of my talk, I will present the application of Inferential Structure Determination (ISD), a Bayesian method for macromolecular structure determination, to this novel data. I illustrate advantages over previous approaches and discuss possible extensions. Hi-C data only yields a static snapshot of chromatin organization. But it is becoming more and more clear that chromatin is in fact a highly dynamic system, which is out of equilibrium and participates in active processes. In the second part of my presentation I will give an outlook on my ongoing work in Prof. Zidovska's lab, where I investigate the dynamics of chromatin in embryonic stem cells (ESCs) and differentiated cells. This work is based on data obtained with Displacement Correlation Spectroscopy (DCS), a recently developed, unique approach to study chromatin dynamics with high spatio-temporal resolution.