Three-dimensional connectivity and chromatin environment mediate the activation efficiency of mammalian DNA replication origins

Abstract

share the first authorship; #R.A. and M.R. share the second authorship. ABSTRACTIn mammalian cells, chromosomal replication starts at thousands of origins at which replisomes are assembled and bidirectional DNA synthesis is established. The slowdown of DNA polymerases at endogenous or exogenous obstacles triggers the activation of additional 'dormant' origins whose genomic positions and regulation are not well understood. Here we report a comparative study of origin activity in mouse embryonic stem cells growing in control conditions or in the presence of mild replication stress. While stress-responsive origins can be identified, we find that the majority of them are also active, albeit with lower frequency, in the control population. To gain insights into the molecular and structural determinants of origin efficiency, we have analyzed the genetic and epigenetic features of origins stratified according to their frequency of activation. We have also integrated the linear origin maps into three-dimensional (3D) chromatin interaction networks, revealing a hierarchical organization in which clusters of connected origins are brought together by longer-range chromatin contacts. Origin efficiency is proportional to the number of connections established with other origin-containing fragments. Interacting origins tend to be activated with similar efficiency and share their timing of replication even when located in different topologically associated domains. Our results are consistent with a model in which clusters of origins are arranged in 3D in replication factories. Within each factory, 'main' and 'dormant' origins are functionally defined by a combination of chromatin environment and 3D connectivity.

GARDEN-NET and ChAseR: a suite of tools for the analysis of chromatin networks

“…The assortative patterns of marks related to gene regulation and of the expression levels themselves suggest a relationship between gene regulation and 3D structure at a global level. Moreover, the strong assortativity of Replication timing, suggesting that replication is also strongly connected to 3D structure, as recently suggested 25 .…”

“…ChAseR is a stand-alone computational tool implemented as an R package, which provides functions to efficiently build and analyse chromatin interaction networks, integrate different epigenomic features on the network, and investigate the relation between chromatin structure and other genomic properties. For example, we have recently introduced the concept of Chromatin Assortativity (ChAs) which allows us to identify whether chromatin with specific features (chromatin marks, binding of transcription factors and replication timing amongst others) tends to form preferential 3D contacts in the nucleus 23,25,26 . ChAseR provides extremely efficient calculations of ChAs and other related measures, including cross-feature assortativity, local assortativity defined in linear or 3D space and tools to explore these patterns ( Figure 1A ).…”

Clustering of strong replicators associated with active promoters is sufficient to establish an early‐replicating domain

“…Interactions between active promoters have been observed by several methods, including the recent production of an ultrahigh‐resolution Hi‐C map during neural differentiation in mice (Li et al , 2012; Bonev et al , 2017). Moreover, a recent study proposed that origins of replication tend to cluster even more efficiently than promoters themselves (preprint: Jodkowska et al , 2019). These results are consistent with our observations, because our construct shown to act synergically contains the constitutive β‐actin promoter.…”

TAD cliques predict key features of chromatin organization

“…These have been utilized to establish functional long-range chromatin interaction networks [ 15 – 17 ], and to unravel TAD and sub-TAD structure and their nested hierarchies [ 18 ]. Graph-based approaches have also enabled modeling of TAD networks explaining the synchrony of replication timing over long genomic distances [ 19 ], and modeling network architecture within TADs to demonstrate that a subset of TADs are structured as core-periphery networks [ 20 ]. These networks are interestingly shown to be partially disrupted upon altered CTCF protein levels [ 20 ].…”