CRISPR Activation Reverses Haploinsufficiency and Functional Deficits Caused by TTN Truncation Variants.

BACKGROUND: TTN truncation variants (TTNtvs) are the most common genetic lesion identified in individuals with dilated cardiomyopathy, a disease with high morbidity and mortality rates. TTNtvs reduce normal TTN (titin) protein levels, produce truncated proteins, and impair sarcomere content and function. Therapeutics targeting TTNtvs have been elusive because of the immense size of TTN, the rarity of specific TTNtvs, and incomplete knowledge of TTNtv pathogenicity. METHODS: We adapted CRISPR activation using dCas9-VPR to functionally interrogate TTNtv pathogenicity and develop a therapeutic in human cardiomyocytes and 3-dimensional cardiac microtissues engineered from induced pluripotent stem cell models harboring a dilated cardiomyopathy-associated TTNtv. We performed guide RNA screening with custom TTN reporter assays, agarose gel electrophoresis to quantify TTN protein levels and isoforms, and RNA sequencing to identify molecular consequences of TTN activation. Cardiomyocyte epigenetic assays were also used to nominate DNA regulatory elements to enable cardiomyocyte-specific TTN activation. RESULTS: CRISPR activation of TTN using single guide RNAs targeting either the TTN promoter or regulatory elements in spatial proximity to the TTN promoter through 3-dimensional chromatin interactions rescued TTN protein deficits disturbed by TTNtvs. Increasing TTN protein levels normalized sarcomere content and contractile function despite increasing truncated TTN protein. In addition to TTN transcripts, CRISPR activation also increased levels of myofibril assembly-related and sarcomere-related transcripts. CONCLUSIONS: TTN CRISPR activation rescued TTNtv-related functional deficits despite increasing truncated TTN levels, which provides evidence to support haploinsufficiency as a relevant genetic mechanism underlying heterozygous TTNtvs. CRISPR activation could be developed as a therapeutic to treat a large proportion of TTNtvs.

An allelic series of spontaneous Rorb mutant mice exhibit a gait phenotype, changes in retina morphology and behavior, and gene expression signatures associated with the unfolded protein response.

The Retinoid-related orphan receptor beta (RORß) gene encodes a developmental transcription factor and has 2 predominant isoforms created through alternative first exon usage; one specific to the retina and another present more broadly in the central nervous system, particularly regions involved in sensory processing. RORß belongs to the nuclear receptor family and plays important roles in cell fate specification in the retina and cortical layer formation. In mice, loss of RORß causes disorganized retina layers, postnatal degeneration, and production of immature cone photoreceptors. Hyperflexion or "high-stepping" of rear limbs caused by reduced presynaptic inhibition by Rorb-expressing inhibitory interneurons of the spinal cord is evident in RORß-deficient mice. RORß variants in patients are associated with susceptibility to various neurodevelopmental conditions, primarily generalized epilepsies, but including intellectual disability, bipolar, and autism spectrum disorders. The mechanisms by which RORß variants confer susceptibility to these neurodevelopmental disorders are unknown but may involve aberrant neural circuit formation and hyperexcitability during development. Here we report an allelic series in 5 strains of spontaneous Rorb mutant mice with a high-stepping gait phenotype. We show retinal abnormalities in a subset of these mutants and demonstrate significant differences in various behavioral phenotypes related to cognition. Gene expression analyses in all 5 mutants reveal a shared over-representation of the unfolded protein response and pathways related to endoplasmic reticulum stress, suggesting a possible mechanism of susceptibility relevant to patients.

ChIATAC is an efficient strategy for multi-omics mapping of 3D epigenomes from low-cell inputs.

Connecting genes to their cis-regulatory elements has been enabled by genome-wide mapping of chromatin interactions using proximity ligation in ChIA-PET, Hi-C, and their derivatives. However, these methods require millions of input cells for high-quality data and thus are unsuitable for many studies when only limited cells are available. Conversely, epigenomic profiling via transposase digestion in ATAC-seq requires only hundreds to thousands of cells to robustly map open chromatin associated with transcription activity, but it cannot directly connect active genes to their distal enhancers. Here, we combine proximity ligation in ChIA-PET and transposase accessibility in ATAC-seq into ChIATAC to efficiently map interactions between open chromatin loci in low numbers of input cells. We validate ChIATAC in Drosophila cells and optimize it for mapping 3D epigenomes in human cells robustly. Applying ChIATAC to primary human T cells, we reveal mechanisms that topologically regulate transcriptional programs during T cell activation.

Oncogenic extrachromosomal DNA functions as mobile enhancers to globally amplify chromosomal transcription.

Extrachromosomal, circular DNA (ecDNA) is emerging as a prevalent yet less characterized oncogenic alteration in cancer genomes. We leverage ChIA-PET and ChIA-Drop chromatin interaction assays to characterize genome-wide ecDNA-mediated chromatin contacts that impact transcriptional programs in cancers. ecDNAs in glioblastoma patient-derived neurosphere and prostate cancer cell cultures are marked by widespread intra-ecDNA and genome-wide chromosomal interactions. ecDNA-chromatin contact foci are characterized by broad and high-level H3K27ac signals converging predominantly on chromosomal genes of increased expression levels. Prostate cancer cells harboring synthetic ecDNA circles composed of characterized enhancers result in the genome-wide activation of chromosomal gene transcription. Deciphering the chromosomal targets of ecDNAs at single-molecule resolution reveals an association with actively expressed oncogenes spatially clustered within ecDNA-directed interaction networks. Our results suggest that ecDNA can function as mobile transcriptional enhancers to promote tumor progression and manifest a potential synthetic aneuploidy mechanism of transcription control in cancer.

ChIA-PIPE: A fully automated pipeline for comprehensive ChIA-PET data analysis and visualization.

ChIA-PET (chromatin interaction analysis with paired-end tags) enables genome-wide discovery of chromatin interactions involving specific protein factors, with base pair resolution. Interpretation of ChIA-PET data requires a robust analytic pipeline. Here, we introduce ChIA-PIPE, a fully automated pipeline for ChIA-PET data processing, quality assessment, visualization, and analysis. ChIA-PIPE performs linker filtering, read mapping, peak calling, and loop calling and automates quality control assessment for each dataset. To enable visualization, ChIA-PIPE generates input files for two-dimensional contact map viewing with Juicebox and HiGlass and provides a new dockerized visualization tool for high-resolution, browser-based exploration of peaks and loops. To enable structural interpretation, ChIA-PIPE calls chromatin contact domains, resolves allele-specific peaks and loops, and annotates enhancer-promoter loops. ChIA-PIPE also supports the analysis of other related chromatin-mapping data types.

Chromatin interaction analyses elucidate the roles of PRC2-bound silencers in mouse development.

Lineage-specific gene expression is modulated by a balance between transcriptional activation and repression during animal development. Knowledge about enhancer-centered transcriptional activation has advanced considerably, but silencers and their roles in normal development remain poorly understood. Here, we performed chromatin interaction analyses of Polycomb repressive complex 2 (PRC2), a key inducer of transcriptional gene silencing, to uncover silencers, their molecular identity and associated chromatin connectivity. Systematic analysis of cis-regulatory silencer elements reveals their chromatin features and gene-targeting specificity. Deletion of certain PRC2-bound silencers in mice results in transcriptional derepression of their interacting genes and pleiotropic developmental phenotypes, including embryonic lethality. While some PRC2-bound elements function as silencers in pluripotent cells, they can transition into active tissue-specific enhancers during development, highlighting their regulatory versatility. Our study characterizes the molecular profile of silencers and their associated chromatin architectures, and suggests the possibility of targeted reactivation of epigenetically silenced genes.

Mapping the Global Chromatin Connectivity Network for Sox2 Function in Neural Stem Cell Maintenance.

The SOX2 transcription factor is critical for neural stem cell (NSC) maintenance and brain development. Through chromatin immunoprecipitation (ChIP) and chromatin interaction analysis (ChIA-PET), we determined genome-wide SOX2-bound regions and Pol II-mediated long-range chromatin interactions in brain-derived NSCs. SOX2-bound DNA was highly enriched in distal chromatin regions interacting with promoters and carrying epigenetic enhancer marks. Sox2 deletion caused widespread reduction of Pol II-mediated long-range interactions and decreased gene expression. Genes showing reduced expression in Sox2-deleted cells were significantly enriched in interactions between promoters and SOX2-bound distal enhancers. Expression of one such gene, Suppressor of Cytokine Signaling 3 (Socs3), rescued the self-renewal defect of Sox2-ablated NSCs. Our work identifies SOX2 as a major regulator of gene expression through connections to the enhancer network in NSCs. Through the definition of such a connectivity network, our study shows the way to the identification of genes and enhancers involved in NSC maintenance and neurodevelopmental disorders.

Picky comprehensively detects high-resolution structural variants in nanopore long reads.

Acquired genomic structural variants (SVs) are major hallmarks of cancer genomes, but they are challenging to reconstruct from short-read sequencing data. Here we exploited the long reads of the nanopore platform using our customized pipeline, Picky ( https://github.com/TheJacksonLaboratory/Picky ), to reveal SVs of diverse architecture in a breast cancer model. We identified the full spectrum of SVs with superior specificity and sensitivity relative to short-read analyses, and uncovered repetitive DNA as the major source of variation. Examination of genome-wide breakpoints at nucleotide resolution uncovered micro-insertions as the common structural features associated with SVs. Breakpoint density across the genome is associated with the propensity for interchromosomal connectivity and was found to be enriched in promoters and transcribed regions of the genome. Furthermore, we observed an over-representation of reciprocal translocations from chromosomal double-crossovers through phased SVs. We demonstrate that Picky analysis is an effective tool for comprehensive detection of SVs in cancer genomes from long-read data.

Producing genome structure populations with the dynamic and automated PGS software.

Chromosome conformation capture technologies such as Hi-C are widely used to investigate the spatial organization of genomes. Because genome structures can vary considerably between individual cells of a population, interpreting ensemble-averaged Hi-C data can be challenging, in particular for long-range and interchromosomal interactions. We pioneered a probabilistic approach for the generation of a population of distinct diploid 3D genome structures consistent with all the chromatin-chromatin interaction probabilities from Hi-C experiments. Each structure in the population is a physical model of the genome in 3D. Analysis of these models yields new insights into the causes and the functional properties of the genome's organization in space and time. We provide a user-friendly software package, called PGS, which runs on local machines (for practice runs) and high-performance computing platforms. PGS takes a genome-wide Hi-C contact frequency matrix, along with information about genome segmentation, and produces an ensemble of 3D genome structures entirely consistent with the input. The software automatically generates an analysis report, and provides tools to extract and analyze the 3D coordinates of specific domains. Basic Linux command-line knowledge is sufficient for using this software. A typical running time of the pipeline is ∼3 d with 300 cores on a computer cluster to generate a population of 1,000 diploid genome structures at topological-associated domain (TAD)-level resolution.

Quantitative Methods to Investigate the 4D Dynamics of Heterochromatic Repair Sites in Drosophila Cells.

Heterochromatin is mostly composed of long stretches of repeated DNA sequences prone to ectopic recombination during double-strand break (DSB) repair. In Drosophila, "safe" homologous recombination (HR) repair of heterochromatic DSBs relies on a striking relocalization of repair sites to the nuclear periphery. Central to understanding heterochromatin repair is the ability to investigate the 4D dynamics (movement in space and time) of repair sites. A specific challenge of these studies is preventing phototoxicity and photobleaching effects while imaging the sample over long periods of time, and with sufficient time points and Z-stacks to track repair foci over time. Here we describe an optimized approach for high-resolution live imaging of heterochromatic DSBs in Drosophila cells, with a specific emphasis on the fluorescent markers and imaging setup used to capture the motion of repair foci over long-time periods. We detail approaches that minimize photobleaching and phototoxicity with a DeltaVision widefield deconvolution microscope, and image processing techniques for signal recovery postimaging using SoftWorX and Imaris software. We present a method to derive mean square displacement curves revealing some of the biophysical properties of the motion. Finally, we describe a method in R to identify tracts of directed motions (DMs) in mixed trajectories. These approaches enable a deeper understanding of the mechanisms of heterochromatin dynamics and genome stability in the three-dimensional context of the nucleus and have broad applicability in the field of nuclear dynamics.

The three-dimensional genome organization of Drosophila melanogaster through data integration.

BACKGROUND: Genome structures are dynamic and non-randomly organized in the nucleus of higher eukaryotes. To maximize the accuracy and coverage of three-dimensional genome structural models, it is important to integrate all available sources of experimental information about a genome's organization. It remains a major challenge to integrate such data from various complementary experimental methods. Here, we present an approach for data integration to determine a population of complete three-dimensional genome structures that are statistically consistent with data from both genome-wide chromosome conformation capture (Hi-C) and lamina-DamID experiments. RESULTS: Our structures resolve the genome at the resolution of topological domains, and reproduce simultaneously both sets of experimental data. Importantly, this data deconvolution framework allows for structural heterogeneity between cells, and hence accounts for the expected plasticity of genome structures. As a case study we choose Drosophila melanogaster embryonic cells, for which both data types are available. Our three-dimensional genome structures have strong predictive power for structural features not directly visible in the initial data sets, and reproduce experimental hallmarks of the D. melanogaster genome organization from independent and our own imaging experiments. Also they reveal a number of new insights about genome organization and its functional relevance, including the preferred locations of heterochromatic satellites of different chromosomes, and observations about homologous pairing that cannot be directly observed in the original Hi-C or lamina-DamID data. CONCLUSIONS: Our approach allows systematic integration of Hi-C and lamina-DamID data for complete three-dimensional genome structure calculation, while also explicitly considering genome structural variability.

Electrostatic effects on the folding stability of FKBP12.

The roles of electrostatic interactions in protein folding stability have been a matter of debate, largely due to the complexity in the theoretical treatment of these interactions. We have developed computational methods for calculating electrostatic effects on protein folding stability. To rigorously test and further refine these methods, here we carried out experimental studies into electrostatic effects on the folding stability of the human 12-kD FK506 binding protein (FKBP12). This protein has a close homologue, FKBP12.6, with amino acid substitutions in only 18 of their 107 residues. Of the 18 substitutions, 8 involve charged residues. Upon mutating FKBP12 residues at these 8 positions individually into the counterparts in FKBP12.6, the unfolding free energy (ΔGu) of FKBP12 changed by -0.3 to 0.7 kcal/mol. Accumulating stabilizing substitutions resulted in a mutant with a 0.9 kcal/mol increase in stability. Additional charge mutations were grafted from a thermophilic homologue, MtFKBP17, which aligns to FKBP12 with 31% sequence identity over 89 positions. Eleven such charge mutations were studied, with ΔΔGu varying from -2.9 to 0.1 kcal/mol. The predicted electrostatic effects by our computational methods with refinements herein had a root-mean-square deviation of 0.9 kcal/mol from the experimental ΔΔGu values on 16 single mutations of FKBP12. The difference in ΔΔGu between mutations grafted from FKBP12.6 and those from MtFKBP17 suggests that more distant homologues are less able to provide guidance for enhancing folding stability.

Mining 3D genome structure populations identifies major factors governing the stability of regulatory communities.

Three-dimensional (3D) genome structures vary from cell to cell even in an isogenic sample. Unlike protein structures, genome structures are highly plastic, posing a significant challenge for structure-function mapping. Here we report an approach to comprehensively identify 3D chromatin clusters that each occurs frequently across a population of genome structures, either deconvoluted from ensemble-averaged Hi-C data or from a collection of single-cell Hi-C data. Applying our method to a population of genome structures (at the macrodomain resolution) of lymphoblastoid cells, we identify an atlas of stable inter-chromosomal chromatin clusters. A large number of these clusters are enriched in binding of specific regulatory factors and are therefore defined as 'Regulatory Communities.' We reveal two major factors, centromere clustering and transcription factor binding, which significantly stabilize such communities. Finally, we show that the regulatory communities differ substantially from cell to cell, indicating that expression variability could be impacted by genome structures.

Population-based 3D genome structure analysis reveals driving forces in spatial genome organization.

Conformation capture technologies (e.g., Hi-C) chart physical interactions between chromatin regions on a genome-wide scale. However, the structural variability of the genome between cells poses a great challenge to interpreting ensemble-averaged Hi-C data, particularly for long-range and interchromosomal interactions. Here, we present a probabilistic approach for deconvoluting Hi-C data into a model population of distinct diploid 3D genome structures, which facilitates the detection of chromatin interactions likely to co-occur in individual cells. Our approach incorporates the stochastic nature of chromosome conformations and allows a detailed analysis of alternative chromatin structure states. For example, we predict and experimentally confirm the presence of large centromere clusters with distinct chromosome compositions varying between individual cells. The stability of these clusters varies greatly with their chromosome identities. We show that these chromosome-specific clusters can play a key role in the overall chromosome positioning in the nucleus and stabilizing specific chromatin interactions. By explicitly considering genome structural variability, our population-based method provides an important tool for revealing novel insights into the key factors shaping the spatial genome organization.

Global reorganization of budding yeast chromosome conformation in different physiological conditions.

The organization of the genome is nonrandom and important for correct function. Specifically, the nuclear envelope plays a critical role in gene regulation. It generally constitutes a repressive environment, but several genes, including the GAL locus in budding yeast, are recruited to the nuclear periphery on activation. Here, we combine imaging and computational modeling to ask how the association of a single gene locus with the nuclear envelope influences the surrounding chromosome architecture. Systematic analysis of an entire yeast chromosome establishes that peripheral recruitment of the GAL locus is part of a large-scale rearrangement that shifts many chromosomal regions closer to the nuclear envelope. This process is likely caused by the presence of several independent anchoring points. To identify novel factors required for peripheral anchoring, we performed a genome-wide screen and demonstrated that the histone acetyltransferase SAGA and the activity of histone deacetylases are needed for this extensive gene recruitment to the nuclear periphery.

TopDom: an efficient and deterministic method for identifying topological domains in genomes.

Genome-wide proximity ligation assays allow the identification of chromatin contacts at unprecedented resolution. Several studies reveal that mammalian chromosomes are composed of topological domains (TDs) in sub-mega base resolution, which appear to be conserved across cell types and to some extent even between organisms. Identifying topological domains is now an important step toward understanding the structure and functions of spatial genome organization. However, current methods for TD identification demand extensive computational resources, require careful tuning and/or encounter inconsistencies in results. In this work, we propose an efficient and deterministic method, TopDom, to identify TDs, along with a set of statistical methods for evaluating their quality. TopDom is much more efficient than existing methods and depends on just one intuitive parameter, a window size, for which we provide easy-to-implement optimization guidelines. TopDom also identifies more and higher quality TDs than the popular directional index algorithm. The TDs identified by TopDom provide strong support for the cross-tissue TD conservation. Finally, our analysis reveals that the locations of housekeeping genes are closely associated with cross-tissue conserved TDs. The software package and source codes of TopDom are available athttp://zhoulab.usc.edu/TopDom/.

Comparative 3D genome structure analysis of the fission and the budding yeast.

We studied the 3D structural organization of the fission yeast genome, which emerges from the tethering of heterochromatic regions in otherwise randomly configured chromosomes represented as flexible polymer chains in an nuclear environment. This model is sufficient to explain in a statistical manner many experimentally determined distinctive features of the fission yeast genome, including chromatin interaction patterns from Hi-C experiments and the co-locations of functionally related and co-expressed genes, such as genes expressed by Pol-III. Our findings demonstrate that some previously described structure-function correlations can be explained as a consequence of random chromatin collisions driven by a few geometric constraints (mainly due to centromere-SPB and telomere-NE tethering) combined with the specific gene locations in the chromosome sequence. We also performed a comparative analysis between the fission and budding yeast genome structures, for which we previously detected a similar organizing principle. However, due to the different chromosome sizes and numbers, substantial differences are observed in the 3D structural genome organization between the two species, most notably in the nuclear locations of orthologous genes, and the extent of nuclear territories for genes and chromosomes. However, despite those differences, remarkably, functional similarities are maintained, which is evident when comparing spatial clustering of functionally related genes in both yeasts. Functionally related genes show a similar spatial clustering behavior in both yeasts, even though their nuclear locations are largely different between the yeast species.

Physical tethering and volume exclusion determine higher-order genome organization in budding yeast.

In this paper we show that tethering of heterochromatic regions to nuclear landmarks and random encounters of chromosomes in the confined nuclear volume are sufficient to explain the higher-order organization of the budding yeast genome. We have quantitatively characterized the contact patterns and nuclear territories that emerge when chromosomes are allowed to behave as constrained but otherwise randomly configured flexible polymer chains in the nucleus. Remarkably, this constrained random encounter model explains in a statistical manner the experimental hallmarks of the S. cerevisiae genome organization, including (1) the folding patterns of individual chromosomes; (2) the highly enriched interactions between specific chromatin regions and chromosomes; (3) the emergence, shape, and position of gene territories; (4) the mean distances between pairs of telomeres; and (5) even the co-location of functionally related gene loci, including early replication start sites and tRNA genes. Therefore, most aspects of the yeast genome organization can be explained without calling on biochemically mediated chromatin interactions. Such interactions may modulate the pre-existing propensity for co-localization but seem not to be the cause for the observed higher-order organization. The fact that geometrical constraints alone yield a highly organized genome structure, on which different functional elements are specifically distributed, has strong implications for the folding principles of the genome and the evolution of its function.

Genome architectures revealed by tethered chromosome conformation capture and population-based modeling.

We describe tethered conformation capture (TCC), a method for genome-wide mapping of chromatin interactions. By performing ligations on solid substrates rather than in solution, TCC substantially enhances the signal-to-noise ratio, thereby facilitating a detailed analysis of interactions within and between chromosomes. We identified a group of regions in each chromosome in human cells that account for the majority of interchromosomal interactions. These regions are marked by high transcriptional activity, suggesting that their interactions are mediated by transcriptional machinery. Each of these regions interacts with numerous other such regions throughout the genome in an indiscriminate fashion, partly driven by the accessibility of the partners. As a different combination of interactions is likely present in different cells, we developed a computational method to translate the TCC data into physical chromatin contacts in a population of three-dimensional genome structures. Statistical analysis of the resulting population demonstrates that the indiscriminate properties of interchromosomal interactions are consistent with the well-known architectural features of the human genome.

Exploring the spatial and temporal organization of a cell's proteome.

To increase our current understanding of cellular processes, such as cell signaling and division, knowledge is needed about the spatial and temporal organization of the proteome at different organizational levels. These levels cover a wide range of length and time scales: from the atomic structures of macromolecules for inferring their molecular function, to the quantitative description of their abundance, and spatial distribution in the cell. Emerging new experimental technologies are greatly increasing the availability of such spatial information on the molecular organization in living cells. This review addresses three fields that have significantly contributed to our understanding of the proteome's spatial and temporal organization: first, methods for the structure determination of individual macromolecular assemblies, specifically the fitting of atomic structures into density maps generated from electron microscopy techniques; second, research that visualizes the spatial distributions of these complexes within the cellular context using cryo electron tomography techniques combined with computational image processing; and third, methods for the spatial modeling of the dynamic organization of the proteome, specifically those methods for simulating reaction and diffusion of proteins and complexes in crowded intracellular fluids. The long-term goal is to integrate the varied data about a proteome's organization into a spatially explicit, predictive model of cellular processes.