Predicting genome organisation and function with mechanistic modelling.

Fitting-free mechanistic models based on polymer simulations predict chromatin folding in 3D by focussing on the underlying biophysical mechanisms. This class of models has been increasingly used in conjunction with experiments to study the spatial organisation of eukaryotic chromosomes. Feedback from experiments to models leads to successive model refinement and has previously led to the discovery of new principles for genome organisation. Here, we review the basis of mechanistic polymer simulations, explain some of the more recent approaches and the contexts in which they have been useful to explain chromosome biology, and speculate on how they might be used in the future. Mechanistic models provide testable hypotheses on principles of genome folding. It is common to start from a basic model and gradually introduce more ingredients to account for more experimental findings. In the transcription factor (TF) model, multivalent chromatin-binding proteins cluster through positive feedback, resulting in phase separation. This 'bridging-induced attraction' explains the biogenesis of nuclear bodies and the formation of active and inactive chromosome compartments. In the loop extrusion (LE) model, structural maintenance of chromosomes (SMC) proteins drive the growth of chromatin loops. LE explains the formation of topologically associating domains and the bias favouring convergent CCCTC-binding factor (CTCF) loops. The highly predictive heteromorphic polymer (HiP-HoP) model combines the TF and LE models and includes chromatin heteromorphicity. It can be used to predict 3D chromatin structure genome-wide. [ABSTRACT FROM AUTHOR]