Node features of chromosome structure networks and their connections to genome annotation.

The 3D conformations of chromosomes can encode biological significance, and the implications of such structures have been increasingly appreciated recently. Certain chromosome structural features, such as A/B compartmentalization, are frequently extracted from Hi-C pairwise genome contact information (physical association between different regions of the genome) and compared with linear annotations of the genome, such as histone modifications and lamina association. We investigate how additional properties of chromosome structure can be deduced using an abstract graph representation of the contact heatmap, and describe specific network properties that can have a strong connection with some of these biological annotations. We constructed chromosome structure networks (CSNs) from bulk Hi-C data and calculated a set of site-resolved (node-based) network properties. These properties are useful for characterizing certain aspects of chromosomal structure. We examined the ability of network properties to differentiate several scenarios, such as haploid vs diploid cells, partially inverted nuclei vs conventional architecture, depletion of chromosome architectural proteins, and structural changes during cell development. We also examined the connection between network properties and a series of other linear annotations, such as histone modifications and chromatin states including poised promoter and enhancer labels. We found that semi-local network properties exhibit greater capability in characterizing genome annotations compared to diffusive or ultra-local node features. For example, the local square clustering coefficient can be a strong classifier of lamina-associated domains. We demonstrated that network properties can be useful for highlighting large-scale chromosome structure differences that emerge in different biological situations.

Chromosome compartmentalization: causes, changes, consequences, and conundrums.

The spatial segregation of the genome into compartments is a major feature of 3D genome organization. New data on mammalian chromosome organization across different conditions reveal important information about how and why these compartments form and change. A combination of epigenetic state, nuclear body tethering, physical forces, gene expression, and replication timing (RT) can all influence the establishment and alteration of chromosome compartments. We review the causes and implications of genomic regions undergoing a 'compartment switch' that changes their physical associations and spatial location in the nucleus. About 20-30% of genomic regions change compartment during cell differentiation or cancer progression, whereas alterations in response to a stimulus within a cell type are usually much more limited. However, even a change in 1-2% of genomic bins may have biologically relevant implications. Finally, we review the effects of compartment changes on gene regulation, DNA damage repair, replication, and the physical state of the cell.

Differential contributions of nuclear lamina association and genome compartmentalization to gene regulation.

Chromatin regions that interact with the nuclear lamina are often heterochromatic, repressed in gene expression, and in the spatial B compartment. However, exceptions to this trend allow us to examine the relative impact of lamin association and spatial compartment on gene regulation. Here, we compared lamin association, gene expression, Hi-C, and histone mark datasets from cell lines representing different states of differentiation across different cell-type lineages. With these data, we compare, for example, gene expression differences when a B compartment region is associated with the nuclear lamina in one cell type but not in another. In general, we observed an additive rather than redundant effect of lamin association and compartment status. But, whether compartment status or lamin association had a dominant influence on gene expression varied by cell type. Finally, we identified how compartment and lamin association influence the likelihood of gene induction or repression in response to physicochemical treatment.

Amorphous calcium phosphate-coated surfaces as a model for bone microenvironment in prostate cancer.

Bone metastasis remains one of the biggest challenges in the treatment of prostate cancer, and other solid tumors such as breast, lung, and colon. Modeling a complex microenvironment in-vitro, such as the bone niche, requires interrogation of cell-cell interactions, specific extracellular matrix proteins and a high calcium environment. Here, we present a fast and cost-effective system in which commercially available, non-adhesive, cell culture vessels are coated with amorphous calcium phosphate (ACP) as a surrogate for bone matrix. We further present modified protocols for subculturing cells, as well as nucleic acid and protein collection in high calcium samples. We find that prostate epithelial cell lines show increased adhesion and proliferation when cultured in these surfaces, as well as independence from androgen starvation. We observe gene expression changes on ACP surfaces in early adenocarcinoma cell lines which may reflect alterations relevant to prostate cancer progression. Summary statement: To model the role of calcium in the microenvironment of the metastatic bone niche, we developed a cost-effective way to coat cell culture vessels in bioavailable calcium, and show that it has an effect on prostate cancer cell survival.

Transcriptional profiling of Hutchinson-Gilford Progeria syndrome fibroblasts reveals deficits in mesenchymal stem cell commitment to differentiation related to early events in endochondral ossification.

The expression of a mutant Lamin A, progerin, in Hutchinson-Gilford Progeria Syndrome leads to alterations in genome architecture, nuclear morphology, epigenetic states, and altered phenotypes in all cells of the mesenchymal lineage. Here, we report a comprehensive analysis of the transcriptional status of patient derived HGPS fibroblasts, including nine cell lines not previously reported, in comparison with age-matched controls, adults, and old adults. We find that Progeria fibroblasts carry abnormal transcriptional signatures, centering around several functional hubs: DNA maintenance and epigenetics, bone development and homeostasis, blood vessel maturation and development, fat deposition and lipid management, and processes related to muscle growth. Stratification of patients by age revealed misregulated expression of genes related to endochondral ossification and chondrogenic commitment in children aged 4-7 years old, where this differentiation program starts in earnest. Hi-C measurements on patient fibroblasts show weakening of genome compartmentalization strength but increases in TAD strength. While the majority of gene misregulation occurs in regions which do not change spatial chromosome organization, some expression changes in key mesenchymal lineage genes coincide with lamin associated domain misregulation and shifts in genome compartmentalization.

Constricted migration is associated with stable 3D genome structure differences in cancer cells.

To spread from a localized tumor, metastatic cancer cells must squeeze through constrictions that cause major nuclear deformations. Since chromosome structure affects nucleus stiffness, gene regulation, and DNA repair, here, we investigate the relationship between 3D genome structure and constricted migration in cancer cells. Using melanoma (A375) cells, we identify phenotypic differences in cells that have undergone multiple rounds of constricted migration. These cells display a stably higher migration efficiency, elongated morphology, and differences in the distribution of Lamin A/C and heterochromatin. Hi-C experiments reveal differences in chromosome spatial compartmentalization specific to cells that have passed through constrictions and related alterations in expression of genes associated with migration and metastasis. Certain features of the 3D genome structure changes, such as a loss of B compartment interaction strength, are consistently observed after constricted migration in clonal populations of A375 cells and in MDA-MB-231 breast cancer cells. Our observations suggest that consistent types of chromosome structure changes are induced or selected by passage through constrictions and that these may epigenetically encode stable differences in gene expression and cellular migration phenotype.

Characterizing the variation in chromosome structure ensembles in the context of the nuclear microenvironment.

Inside the nucleus, chromosomes are subjected to direct physical interaction between different components, active forces, and thermal noise, leading to the formation of an ensemble of three-dimensional structures. However, it is still not well understood to what extent and how the structural ensemble varies from one chromosome region or cell-type to another. We designed a statistical analysis technique and applied it to single-cell chromosome imaging data to reveal the heterogeneity of individual chromosome structures. By analyzing the resulting structural landscape, we find that the largest dynamic variation is the overall radius of gyration of the chromatin region, followed by domain reorganization within the region. By comparing different human cell-lines and experimental perturbation data using this statistical analysis technique and a network-based similarity quantification approach, we identify both cell-type and condition-specific features of the structural landscapes. We identify a relationship between epigenetic state and the properties of chromosome structure fluctuation and validate this relationship through polymer simulations. Overall, our study suggests that the types of variation in a chromosome structure ensemble are cell-type as well as region-specific and can be attributed to constraints placed on the structure by factors such as variation in epigenetic state.

SnapShot: Chromosome organization.

Chromosomes in higher eukaryotes are folded at different length scales into loop extrusion domains, spatial compartments, and chromosome territories and exhibit interactions with nuclear structures such as the lamina. Microscopic methods can probe this structure by measuring positions of chromosomes in the nuclear space in individual cells, while sequencing-based contact capture approaches can report the frequency of contacts of different regions within these structural layers. To view this SnapShot, open or download the PDF.

Loops, topologically associating domains, compartments, and territories are elastic and robust to dramatic nuclear volume swelling.

Layers of genome organization are becoming increasingly better characterized, but less is known about how these structures respond to perturbation or shape changes. Low-salt swelling of isolated chromatin fibers or nuclei has been used for decades to investigate the structural properties of chromatin. But, visible changes in chromatin appearance have not been linked to known building blocks of genome structure or features along the genome sequence. We combine low-salt swelling of isolated nuclei with genome-wide chromosome conformation capture (Hi-C) and imaging approaches to probe the effects of chromatin extension genome-wide. Photoconverted patterns on nuclei during expansion and contraction indicate that global genome structure is preserved after dramatic nuclear volume swelling, suggesting a highly elastic chromosome topology. Hi-C experiments before, during, and after nuclear swelling show changes in average contact probabilities at short length scales, reflecting the extension of the local chromatin fiber. But, surprisingly, during this large increase in nuclear volume, there is a striking maintenance of loops, TADs, active and inactive compartments, and chromosome territories. Subtle differences after expansion are observed, suggesting that the local chromatin state, protein interactions, and location in the nucleus can affect how strongly a given structure is maintained under stress. From these observations, we propose that genome topology is robust to extension of the chromatin fiber and isotropic shape change, and that this elasticity may be beneficial in physiological circumstances of changes in nuclear size and volume.

SMILE: mutual information learning for integration of single-cell omics data.

MOTIVATION: Deep learning approaches have empowered single-cell omics data analysis in many ways and generated new insights from complex cellular systems. As there is an increasing need for single-cell omics data to be integrated across sources, types and features of data, the challenges of integrating single-cell omics data are rising. Here, we present an unsupervised deep learning algorithm that learns discriminative representations for single-cell data via maximizing mutual information, SMILE (Single-cell Mutual Information Learning). RESULTS: Using a unique cell-pairing design, SMILE successfully integrates multisource single-cell transcriptome data, removing batch effects and projecting similar cell types, even from different tissues, into the shared space. SMILE can also integrate data from two or more modalities, such as joint-profiling technologies using single-cell ATAC-seq, RNA-seq, DNA methylation, Hi-C and ChIP data. When paired cells are known, SMILE can integrate data with unmatched feature, such as genes for RNA-seq and genome-wide peaks for ATAC-seq. Integrated representations learned from joint-profiling technologies can then be used as a framework for comparing independent single source data. AVAILABILITY AND IMPLEMENTATION: The source code of SMILE including analyses of key results in the study can be found at: https://github.com/rpmccordlab/SMILE, implemented in Python. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Chromosome compartmentalization alterations in prostate cancer cell lines model disease progression.

Prostate cancer aggressiveness and metastatic potential are influenced by gene expression and genomic aberrations, features that can be influenced by the 3D structure of chromosomes inside the nucleus. Using chromosome conformation capture (Hi-C), we conducted a systematic genome architecture comparison on a cohort of cell lines that model prostate cancer progression, from normal epithelium to bone metastasis. We describe spatial compartment identity (A-open versus B-closed) changes with progression in these cell lines and their relation to gene expression changes in both cell lines and patient samples. In particular, 48 gene clusters switch from the B to the A compartment, including androgen receptor, WNT5A, and CDK14. These switches are accompanied by changes in the structure, size, and boundaries of topologically associating domains (TADs). Further, compartment changes in chromosome 21 are exacerbated with progression and may explain, in part, the genesis of the TMPRSS2-ERG translocation. These results suggest that discrete 3D genome structure changes play a deleterious role in prostate cancer progression. .

Inferring chromosome radial organization from Hi-C data.

BACKGROUND: The nonrandom radial organization of eukaryotic chromosome territories (CTs) inside the nucleus plays an important role in nuclear functional compartmentalization. Increasingly, chromosome conformation capture (Hi-C) based approaches are being used to characterize the genome structure of many cell types and conditions. Computational methods to extract 3D arrangements of CTs from this type of pairwise contact data will thus increase our ability to analyze CT organization in a wider variety of biological situations. RESULTS: A number of full-scale polymer models have successfully reconstructed the 3D structure of chromosome territories from Hi-C. To supplement such methods, we explore alternative, direct, and less computationally intensive approaches to capture radial CT organization from Hi-C data. We show that we can infer relative chromosome ordering using PCA on a thresholded inter-chromosomal contact matrix. We simulate an ensemble of possible CT arrangements using a force-directed network layout algorithm and propose an approach to integrate additional chromosome properties into our predictions. Our CT radial organization predictions have a high correlation with microscopy imaging data for various cell nucleus geometries (lymphoblastoid, skin fibroblast, and breast epithelial cells), and we can capture previously documented changes in senescent and progeria cells. CONCLUSIONS: Our analysis approaches provide rapid and modular approaches to screen for alterations in CT organization across widely available Hi-C data. We demonstrate which stages of the approach can extract meaningful information, and also describe limitations of pairwise contacts alone to predict absolute 3D positions.

Using contact statistics to characterize structure transformation of biopolymer ensembles.

As a unique subset of functional polymers, many biopolymers have a set of well-defined three-dimensional (3D) structural characteristics that can be described by spatial contacts between monomers. Statistical analysis of the contacts has been extremely productive in characterizing the biopolymer structural ensemble, such as for 3D chromosome structures. Often, native contacts and compartment structures are the focus of the studies, while the generic polymer aspect, such as the overall decaying of contacts with increasing sequence distance, is analyzed separately or preemptively removed. Here, we explore insights that can be gained by performing "compartment analysis" that keeps the distance decay, which we believe is particularly useful for characterizing the structure transformation of biopolymers. We tested contact analysis on several such transformations under physical perturbation or biological processes, including (1) unfolding of proteins induced by thermal denaturation, (2) chromosome conformation transition during the cell cycle, and (3) chromosome unpacking by physicochemical perturbations. Useful score functions were developed to further quantitatively characterize the transformation judging from the contact analysis. We also find that the sinusoidal undertone of eigenvector patterns (the "unwanted," low frequency signal, in contrast to the detailed A/B compartment) that had previously been attributed to biological effects of centromere proximal and distal interactions may in fact reflect a universal feature of polymers that have relatively weaker long-range contacts.