Cell type- and transcription-independent spatial proximity between enhancers and promoters.

Cell type-specific enhancers are critically important for lineage specification. The mechanisms that determine cell-type specificity of enhancer activity, however, are not fully understood. Most current models for how enhancers function invoke physical proximity between enhancer elements and their target genes. Here, we use an imaging-based approach to examine the spatial relationship of cell type-specific enhancers and their target genes with single-cell resolution. Using high-throughput microscopy, we measure the spatial distance from target promoters to their cell type-specific active and inactive enhancers in individual pancreatic cells derived from distinct lineages. We find increased proximity of all promoter-enhancer pairs relative to non-enhancer pairs separated by similar genomic distances. Strikingly, spatial proximity between enhancers and target genes was unrelated to tissue-specific enhancer activity. Furthermore, promoter-enhancer proximity did not correlate with the expression status of target genes. Our results suggest that promoter-enhancer pairs exist in a distinctive chromatin environment but that genome folding is not a universal driver of cell-type specificity in enhancer function.

Nuclear position modulates long-range chromatin interactions.

The human genome is non-randomly organized within the cell nucleus. Spatial mapping of genome folding by biochemical methods and imaging has revealed extensive variation in locus interaction frequencies between cells in a population and between homologs within an individual cell. Commonly used mapping approaches typically examine either the relative position of genomic sites to each other or the position of individual loci relative to nuclear landmarks. Whether the frequency of specific chromatin-chromatin interactions is affected by where in the nuclear space a locus is located is unknown. Here, we have simultaneously mapped at the single cell level the interaction frequencies and radial position of more than a hundred locus pairs using high-throughput imaging to ask whether the location within the nucleus affects interaction frequency. We find strong enrichment of many interactions at specific radial positions. Position-dependency of interactions was cell-type specific, correlated with local chromatin type, and cell-type-specific enriched associations were marked by increased variability, sometimes without a significant decrease in mean spatial distance. These observations demonstrate that the folding of the chromatin fiber, which brings genomically distant loci into proximity, and the position of that chromatin fiber relative to nuclear landmarks, are closely linked.

Integrative genome modeling platform reveals essentiality of rare contact events in 3D genome organizations.

A multitude of sequencing-based and microscopy technologies provide the means to unravel the relationship between the three-dimensional organization of genomes and key regulatory processes of genome function. Here, we develop a multimodal data integration approach to produce populations of single-cell genome structures that are highly predictive for nuclear locations of genes and nuclear bodies, local chromatin compaction and spatial segregation of functionally related chromatin. We demonstrate that multimodal data integration can compensate for systematic errors in some of the data and can greatly increase accuracy and coverage of genome structure models. We also show that alternative combinations of different orthogonal data sources can converge to models with similar predictive power. Moreover, our study reveals the key contributions of low-frequency ('rare') interchromosomal contacts to accurately predicting the global nuclear architecture, including the positioning of genes and chromosomes. Overall, our results highlight the benefits of multimodal data integration for genome structure analysis, available through the Integrative Genome Modeling software package.

Large-scale mapping of positional changes of hypoxia-responsive genes upon activation.

Chromosome structure and nuclear organization are important factors in the regulation of gene expression. Transcription of a gene is influenced by local and global chromosome features such as chromatin condensation status. The relationship between the 3D position of a gene in the nucleus and its activity is less clear. Here we used high-throughput imaging to perform a large-scale analysis of the spatial location of nearly 100 hypoxia-responsive genes to determine whether their location and activity state are correlated. Radial distance analysis demonstrated that the majority of Hypoxia-Inducible Factor (HIF)- and CREB-dependent hypoxia-responsive genes are located in the intermediate region of the nucleus, and some of them changed their radial position in hypoxia. Analysis of the relative distances among a subset of HIF target genes revealed that some gene pairs altered their relative location to each other on hypoxic treatment, suggesting higher-order chromatin rearrangements. While these changes in location occurred in response to hypoxic activation of the target genes, they did not correlate with the extent of their activation. These results suggest that induction of the hypoxia-responsive gene expression program is accompanied by spatial alterations of the genome, but that radial and relative gene positions are not directly related to gene activity.

A high-throughput DNA FISH protocol to visualize genome regions in human cells.

Here, we describe an end-to-end high-throughput imaging protocol to visualize genomic loci in cells at high throughput using DNA fluorescence in situ hybridization, automated microscopy, and computational analysis. This is particularly useful for quantifying patterns of heterogeneity in relative gene positioning or differences within subpopulations of cells. We focus on important experimental design and execution steps in this one-week protocol, suggest ways to ensure and verify data quality, and provide practical solutions to common problems. For complete details on the generation and use of this protocol, please refer to Finn et al. (2019).

Molecular basis and biological function of variability in spatial genome organization.

The complex three-dimensional organization of genomes in the cell nucleus arises from a wide range of architectural features including DNA loops, chromatin domains, and higher-order compartments. Although these features are universally present in most cell types and tissues, recent single-cell biochemistry and imaging approaches have demonstrated stochasticity in transcription and high variability of chromatin architecture in individual cells. We review the occurrence, mechanistic basis, and functional implications of stochasticity in genome organization. We summarize recent observations on cell- and allele-specific variability of genome architecture, discuss the nature of extrinsic and intrinsic sources of variability in genome organization, and highlight potential implications of structural heterogeneity for genome function.

Extensive Heterogeneity and Intrinsic Variation in Spatial Genome Organization.

Several general principles of global 3D genome organization have recently been established, including non-random positioning of chromosomes and genes in the cell nucleus, distinct chromatin compartments, and topologically associating domains (TADs). However, the extent and nature of cell-to-cell and cell-intrinsic variability in genome architecture are still poorly characterized. Here, we systematically probe heterogeneity in genome organization. High-throughput optical mapping of several hundred intra-chromosomal interactions in individual human fibroblasts demonstrates low association frequencies, which are determined by genomic distance, higher-order chromatin architecture, and chromatin environment. The structure of TADs is variable between individual cells, and inter-TAD associations are common. Furthermore, single-cell analysis reveals independent behavior of individual alleles in single nuclei. Our observations reveal extensive variability and heterogeneity in genome organization at the level of individual alleles and demonstrate the coexistence of a broad spectrum of genome configurations in a cell population.

Blank spots on the map: some current questions on nuclear organization and genome architecture.

The past decades have provided remarkable insights into how the eukaryotic cell nucleus and the genome within it are organized. The combined use of imaging, biochemistry and molecular biology approaches has revealed several basic principles of nuclear architecture and function, including the existence of chromatin domains of various sizes, the presence of a large number of non-membranous intranuclear bodies, non-random positioning of genes and chromosomes in 3D space, and a prominent role of the nuclear lamina in organizing genomes. Despite this tremendous progress in elucidating the biological properties of the cell nucleus, many questions remain. Here, we highlight some of the key open areas of investigation in the field of nuclear organization and genome architecture with a particular focus on the mechanisms and principles of higher-order genome organization, the emerging role of liquid phase separation in cellular organization, and the functional role of the nuclear lamina in physiological processes.

Genome Architecture from a Different Angle.

The study of genome architecture has recently been advanced by new techniques combining nuclear proximity ligation and high-throughput sequencing, but independent methods to validate them have been lacking. Reporting in Nature, Beagrie et al. (2017) describe such an orthogonal technique, called genome architecture mapping, to map genomes in 3D space.

Comparative analysis of 2D and 3D distance measurements to study spatial genome organization.

The spatial organization of genomes is non-random, cell-type specific, and has been linked to cellular function. The investigation of spatial organization has traditionally relied extensively on fluorescence microscopy. The validity of the imaging methods used to probe spatial genome organization often depends on the accuracy and precision of distance measurements. Imaging-based measurements may either use 2 dimensional datasets or 3D datasets which include the z-axis information in image stacks. Here we compare the suitability of 2D vs 3D distance measurements in the analysis of various features of spatial genome organization. We find in general good agreement between 2D and 3D analysis with higher convergence of measurements as the interrogated distance increases, especially in flat cells. Overall, 3D distance measurements are more accurate than 2D distances, but are also more susceptible to noise. In particular, z-stacks are prone to error due to imaging properties such as limited resolution along the z-axis and optical aberrations, and we also find significant deviations from unimodal distance distributions caused by low sampling frequency in z. These deviations are ameliorated by significantly higher sampling frequency in the z-direction. We conclude that 2D distances are preferred for comparative analyses between cells, but 3D distances are preferred when comparing to theoretical models in large samples of cells. In general and for practical purposes, 2D distance measurements are preferable for many applications of analysis of spatial genome organization.

Painting a Clearer Picture of Chromatin.

Elucidating chromatin's 3D shape is critical to understanding its function, but the fine structure of chromatin domains remains poorly resolved. In a recent report in Nature, Boettiger et al. (2016) visualize chromatin in super-resolution, gaining unprecedented insight into chromatin architecture.

Maternal bias and escape from X chromosome imprinting in the midgestation mouse placenta.

To investigate the epigenetic landscape at the interface between mother and fetus, we provide a comprehensive analysis of parent-of-origin bias in the mouse placenta. Using F1 interspecies hybrids between mus musculus (C57BL/6J) and mus musculus castaneus, we sequenced RNA from 23 individual midgestation placentas, five late stage placentas, and two yolk sac samples and then used SNPs to determine whether transcripts were preferentially generated from the maternal or paternal allele. In the placenta, we find 103 genes that show significant and reproducible parent-of-origin bias, of which 78 are novel candidates. Most (96%) show a strong maternal bias which we demonstrate, via multiple mathematical models, pyrosequencing, and FISH, is not due to maternal decidual contamination. Analysis of the X chromosome also reveals paternal expression of Xist and several genes that escape inactivation, most significantly Alas2, Fhl1, and Slc38a5. Finally, sequencing individual placentas allowed us to reveal notable expression similarity between littermates. In all, we observe a striking preference for maternal transcription in the midgestation mouse placenta and a dynamic imprinting landscape in extraembryonic tissues, reflecting the complex nature of epigenetic pathways in the placenta.