Precise measurements of chromatin diffusion dynamics by modeling using Gaussian processes

The spatiotemporal organization of chromatin influences many nuclear processes: from chromo-some segregation to transcriptional regulation. To get a deeper understanding of these processes it is essential to go beyond static viewpoints of chromosome structures, and to accurately characterize chromatin mobility and its diffusion properties. Here, we present GP-FBM: a new computational framework based on Gaussian processes and fractional Brownian motion to analyze and extract diffusion properties from stochastic trajectories of labeled chromatin loci. GP-FBM is able to optimally use the higher-order correlations present in the data and therefore outperforms existing methods. Furthermore, GP-FBM is able to extrapolate trajectories from missing data and account for substrate movement automatically. Using our method we show that diffusive chromatin diffusion properties are surprisingly similar in interphase and mitosis in mouse embryonic stem cells. Moreover, we observe surprising heterogeneity in local chromatin dynamics, which correlates with transcriptional activity. We also present GP-Tool, a user-friendly graphical interface to facilitate the use of GP-FBM by the research community for future studies of nuclear dynamics.