Merging 1D and 3D genomic information: Challenges in modelling and validation

Abstract

Genome organization in eukaryotes during interphase stems from the delicate balance between non-random correlations present in the DNA polynucleotide linear sequence and the physico/chemical reactions which shape continuously the form and structure of DNA and chromatin inside the nucleus of the cell. It is now clear that these mechanisms have a key role in important processes like gene regulation, yet the detailed ways they act simultaneously and, eventually, come to influence each other even across very different length-scales remain largely unexplored. In this paper, we recapitulate some of the main results concerning gene regulatory and physical mechanisms, in relation to the information encoded in the 1D sequence and the 3D folding structure of DNA. In particular, we stress how reciprocal crossfeeding between 1D and 3D models may provide original insight into how these complex processes work and influence each other. arXiv:2005.06755v1 [q-bio.GN]

Toward understanding the dynamic state of 3D genome

“…Since Hi-C technology revealed the 3D genome organization within the nucleus, polymer modeling has bifurcated into two approaches: first-principles (or bottom-up, forward, mechanistic) models, and data-driven (or top-down, inverse, fitting-based) models [21] , [22] , [23] . The former consists of minimal physical assumptions and aims to reveal a set of minimal physical mechanisms underlying the 3D genome organization.…”

“…As live-cell imaging experiments with single nucleosomes have revealed [36] , [37] , the dynamic organization of chromatin domains occurs in a system experiencing stochastic thermal fluctuations, which inevitably drive the movements of the genome molecules present in the microscale cell environment. Polymer physics and polymer simulations are powerful ways to understand the relationship between chromatin dynamics and organization [38] , [39] , [21] , [22] , [23] . In our polymer modeling system, the interaction matrix also allows us to create simulations of 4D polymer dynamics featuring stochastic thermal fluctuations.…”