Abstract
Several experiments show that the three dimensional (3D) organization of chromosomes affects genetic processes such as transcription and gene regulation. To better understand this connection, researchers developed the Hi-C method that is able to detect the pairwise physical contacts of all chromosomal loci. The Hi-C data show that chromosomes are composed of 3D compartments that range over a variety of scales. However, it is challenging to systematically detect these cross-scale structures. Most studies have therefore designed methods for specific scales to study foremost topologically associated domains (TADs) and A/B compartments. To go beyond this limitation, we tailor a network community detection method that finds communities in compact fractal globule polymer systems. Our method allows us to continuously scan through all scales with a single resolution parameter. We found: (i) polymer segments belonging to the same 3D community do not have to be in consecutive order along the polymer chain. In other words, several TADs may belong to the same 3D community. (ii) CTCF proteins—a loop-stabilizing protein that is ascribed a big role in TAD formation—are well correlated with community borders only at one level of organization. (iii) TADs and A/B compartments are traditionally treated as two weakly related 3D structures and detected with different algorithms. With our method, we detect both by simply adjusting the resolution parameter. We therefore argue that they represent two specific levels of a continuous spectrum 3D communities, rather than seeing them as different structural entities.
Highlights
At the mega (106)-base-pair scale, two types of coexisting structures stand out
From Hi-C experiments, it is clear that inter-phase chromosomes are built up by a network of 3D compartments on various scales–from kilo(103)-base-pair sized loops to mega(106)-base-pair sized 3D structures
We have found that chromatin segments belonging to the same 3D community do not have to be in next to each other along the DNA
Summary
Received: 22 October 2018 Accepted: 22 March 2019 Published: xx xx xxxx capture data. Most studies have designed methods for specific scales to study foremost topologically associated domains (TADs) and A/B compartments To go beyond this limitation, we tailor a network community detection method that finds communities in compact fractal globule polymer systems. Based on the physics of compact polymer globules, we put forward a null model that is consistent with the average contact probabilities in real Hi-C data[1] This goes beyond previous Louvain-like studies[14,15] that treat the Hi-C data as a network with random connections. Most studies, such as Yan et al and Norton et al.[14,15], treat TADs as linear contiguous sequences of chromatin This restriction overrides the GenLouvain algorithm’s ability to find the (not necessarily contiguous) optimal community structure in the data set[19,20]. To reduce confusion, we will not use the term TAD, but rather the 3D community for the cluster of nodes that comes out of the GenLouvain algorithm since they are not necessarily linear contiguous sequences
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