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Genome function requires regulated genome motion. However, tools to directly observe this motion in vivo have been limited in coverage and resolution. Here we introduce an approach to tile mammalian chromosomes with self-mapping fluorescent labels and track them at ultraresolution. We find that sequences separated by submegabase distances transition to proximity in tens of seconds. This rapid search is dependent on cohesin and is exhibited only within domains. Domain borders act as kinetic impediments to this search process, rather than structural boundaries. The genomic separation–dependent scaling of the search time for cis interactions violated predictions of diffusion, suggesting motor-driven folding. We also uncover cohesin-dependent processive motion at 2.7 kilobases per second. Together, these multiscale dynamics reveal the organization of the genome into kinetically associated domains. 

Abstract The 3D organization of the genome—in particular, which two regions of DNA are in contact with each other—plays a role in regulating gene expression. Several factors influence genome 3D organization. Nucleosomes (where ∼100 base pairs of DNA wrap around histone proteins) bend, twist, and compactify chromosomal DNA, altering its polymer mechanics. How much does the positioning of nucleosomes between gene loci influence contacts between those gene loci? And to what extent are polymer mechanics responsible for this? To address this question, we combine a stochastic polymer mechanics model of chromosomal DNA including twists and wrapping induced by nucleosomes with two data-driven pipelines. The first estimates nucleosome positioning from ATAC-seq data in regions of high accessibility. Most of the genome is low accessibility, so we combine this with a novel image analysis method that estimates the distribution of nucleosome spacing from electron microscopy data. There are no fit parameters in the biophysical model. We apply this method to IL-6, IL-15, CXCL9, and CXCL10, inflammatory marker genes in macrophages, before and after inflammatory stimulation, and compare the predictions with contacts measured by conformation capture experiments (4C-seq). We find that within a 500-kb genomic region, polymer mechanics with nucleosomes can explain 71% of close contacts. These results suggest that, while genome contacts on 100 kb scales are multifactorial, they may be amenable to mechanistic, physical explanation. Our work also highlights the role of nucleosomes, not just at the loci of interest, but between them, and not just the total number of nucleosomes, but their specific placement. The method generalizes to other genes, and can be used to address whether a contact is under active regulation by the cell (e.g. a macrophage during inflammatory stimulation). 

DNA methylation is a crucial epigenetic modification that orchestrates chromatin remodelers that suppress transcription, and aberrations in DNA methylation result in a variety of conditions such as cancers and developmental disorders. While it is understood that methylation occurs at CpG-rich DNA regions, it is less understood how distinct methylation profiles are established within various cell types. In this work, we develop a molecular-transport model that depicts the genomic exploration of DNA methyltransferase within a multiscale DNA environment, incorporating biologically relevant factors like methylation rate and CpG density to predict how patterns are established. Our model predicts DNA methylation-state correlation distributions arising from the transport and kinetic properties that are crucial for the establishment of unique methylation profiles. We model the methylation correlation distributions of nine cancerous human cell types to determine how these properties affect the epigenetic profile. Our theory is capable of recapitulating experimental methylation patterns, suggesting the importance of DNA methyltransferase transport in epigenetic regulation. Through this work, we propose a mechanistic description for the establishment of methylation profiles, capturing the key behavioral characteristics of methyltransferase that lead to aberrant methylation. 

Euchromatin is an accessible phase of genetic material containing genes that encode proteins with increased expression levels. The structure of euchromatin in vitro has been described as a 30-nm fiber formed from ordered nucleosome arrays. However, recent advances in microscopy have revealed an in vivo euchromatin architecture that is much more disordered, characterized by variable-length linker DNA and sporadic nucleosome clusters. In this work, we develop a theoretical model to elucidate factors contributing to the disordered in vivo architecture of euchromatin. We begin by developing a 1D model of nucleosome positioning that captures the interactions between bound epigenetic reader proteins to predict the distribution of DNA linker lengths between adjacent nucleosomes. We then use the predicted linker lengths to construct 3D chromatin configurations consistent with the physical properties of DNA within the nucleosome array, and we evaluate the distribution of nucleosome cluster sizes in those configurations. Our model reproduces experimental cluster-size distributions, which are dramatically influenced by the local pattern of epigenetic marks and the concentration of reader proteins. Based on our model, we attribute the disordered arrangement of euchromatin to the heterogeneous binding of reader proteins and subsequent short-range interactions between bound reader proteins on adjacent nucleosomes. By replicating experimental results with our physics-based model, we propose a mechanism for euchromatin organization in the nucleus that impacts gene regulation and the maintenance of epigenetic marks. 

A grand challenge in materials science is to identify the impact of molecular composition and structure across a range of length scales on macroscopic properties. We demonstrate a unified experimental–theoretical framework that coordinates experimental measurements of mesoscale structure with molecular-level physical modeling to bridge multiple scales of physical behavior. Here we apply this framework to understand charge transport in a semiconducting polymer. Spatially-resolved nanodiffraction in a transmission electron microscope is combined with a self-consistent framework of the polymer chain statistics to yield a detailed picture of the polymer microstructure ranging from the molecular to device relevant scale. Using these data as inputs for charge transport calculations, the combined multiscale approach highlights the underrepresented role of defects in existing transport models. Short-range transport is shown to be more chaotic than is often pictured, with the drift velocity accounting for a small portion of overall charge motion. Local transport is sensitive to the alignment and geometry of polymer chains. At longer length scales, large domains and gradual grain boundaries funnel charges preferentially to certain regions, creating inhomogeneous charge distributions. While alignment generally improves mobility, these funneling effects negatively impact mobility. The microstructure is modified in silico to explore possible design rules, showing chain stiffness and alignment to be beneficial while local homogeneity has no positive effect. This combined approach creates a flexible and extensible pipeline for analyzing multiscale functional properties and a general strategy for extending the accesible length scales of experimental and theoretical probes by harnessing their combined strengths.