Three-dimensional chromatin ensemble reconstruction via stochastic embedding

Disrupted chromatin architecture in olfactory sensory neurons: looking for the link from COVID-19 infection to anosmia

We tackle here genomic mechanisms of a rapid onset and recovery from anosmia-a potential diagnostic indicator for early-stage COVID-19 infection. Based on previous observations on how olfactory receptor (OR) gene expression is regulated via chromatin structure in mice, we hypothesized that the disruption of the OR gene expression and, respectively, deficiency of the OR function can be caused by chromatin reorganization taking place upon SARS-CoV-2 infection. We obtained chromatin ensemble reconstructions from COVID-19 patients and control samples using our original computational framework for the whole-genome 3D chromatin ensemble reconstruction. Specifically, we used megabase-scale structural units and effective interactions between them obtained in the Markov State modelling of the Hi-C contact network as an unput in the stochastic embedding procedure of the whole-genome 3D chromatin ensemble reconstruction. We have also developed here a new procedure for analyzing fine structural hierarchy with (sub)TAD-size units in local chromatin regions, which we apply here to parts of chromosomes containing OR genes and corresponding regulatory elements. We observed structural modifications in COVID-19 patients on different levels of chromatin organization, from the alteration of whole genome structure and chromosomal intermingling to reorganization of contacts between chromatin loops at the level of topologically associating domains. While complementary data on known regulatory elements point to potential pathology-associated changes within the overall picture of chromatin alterations, further investigation using additional epigenetic factors mapped on 3D reconstructions with improved resolution will be required for better understanding of anosmia caused by SARS-CoV-2 infection.

Single-cell Hi-C data analysis: safety in numbers

Over the past decade, genome-wide assays for chromatin interactions in single cells have enabled the study of individual nuclei at unprecedented resolution and throughput. Current chromosome conformation capture techniques survey contacts for up to tens of thousands of individual cells, improving our understanding of genome function in 3D. However, these methods recover a small fraction of all contacts in single cells, requiring specialised processing of sparse interactome data. In this review, we highlight recent advances in methods for the interpretation of single-cell genomic contacts. After discussing the strengths and limitations of these methods, we outline frontiers for future development in this rapidly moving field.

Multiscale modeling of genome organization with maximum entropy optimization

Three-dimensional (3D) organization of the human genome plays an essential role in all DNA-templated processes, including gene transcription, gene regulation, and DNA replication. Computational modeling can be an effective way of building high-resolution genome structures and improving our understanding of these molecular processes. However, it faces significant challenges as the human genome consists of over 6 × 109 base pairs, a system size that exceeds the capacity of traditional modeling approaches. In this perspective, we review the progress that has been made in modeling the human genome. Coarse-grained models parameterized to reproduce experimental data via the maximum entropy optimization algorithm serve as effective means to study genome organization at various length scales. They have provided insight into the principles of whole-genome organization and enabled de novo predictions of chromosome structures from epigenetic modifications. Applications of these models at a near-atomistic resolution further revealed physicochemical interactions that drive the phase separation of disordered proteins and dictate chromatin stability in situ. We conclude with an outlook on the opportunities and challenges in studying chromosome dynamics.