3D mapping and accelerated super-resolution imaging of the human genome using in situ sequencing

Single-cell mapping of cell-type specific chromatin architecture in the central nervous system

Determining how chromatin is structured in the nucleus is critical to studying its role in gene regulation. Recent advances in the analysis of single-cell chromatin architecture have considerably improved our understanding of cell-type-specific chromosome conformation and nuclear architecture. In this review, we discuss the methods used for analysis of 3D chromatin conformation, including sequencing-based methods, imaging-based techniques, and computational approaches. We further review the application of these methods in the study of the role of chromatin topology in neural development and disorders.

A practical guide to spatial transcriptomics

Spatial transcriptomics is revolutionizing modern biology, offering researchers an unprecedented ability to unravel intricate gene expression patterns within tissues. From pioneering techniques to newly commercialized platforms, the field of spatial transcriptomics has evolved rapidly, ushering in a new era of understanding across various disciplines, from developmental biology to disease research. This dynamic expansion is reflected in the rapidly growing number of technologies and data analysis techniques developed and introduced. However, the expanding landscape presents a considerable challenge for researchers, especially newcomers to the field, as staying informed about these advancements becomes increasingly complex. To address this challenge, we have prepared an updated review with a particular focus on technologies that have reached commercialization and are, therefore, accessible to a broad spectrum of potential new users. In this review, we present the fundamental principles of spatial transcriptomic methods, discuss the challenges in data analysis, provide insights into experimental considerations, offer information about available resources for spatial transcriptomics, and conclude with a guide for method selection and a forward-looking perspective. Our aim is to serve as a guiding resource for both experienced users and newcomers navigating the complex realm of spatial transcriptomics in this era of rapid development. We intend to equip researchers with the necessary knowledge to make informed decisions and contribute to the cutting-edge research that spatial transcriptomics offers.

Advances in the multimodal analysis of the 3D chromatin structure and gene regulation

Recent studies have demonstrated that the three-dimensional conformation of the chromatin plays a crucial role in gene regulation, with aberrations potentially leading to various diseases. Advanced methodologies have revealed a link between the chromatin conformation and biological function. This review divides these methodologies into sequencing-based and imaging-based methodologies, tracing their development over time. We particularly highlight innovative techniques that facilitate the simultaneous mapping of RNAs, histone modifications, and proteins within the context of the 3D architecture of chromatin. This multimodal integration substantially improves our ability to establish a robust connection between the spatial arrangement of molecular components in the nucleus and their functional roles. Achieving a comprehensive understanding of gene regulation requires capturing diverse data modalities within individual cells, enabling the direct inference of functional relationships between these components. In this context, imaging-based technologies have emerged as an especially promising approach for gathering spatial information across multiple components in the same cell.

Enhancer-promoter specificity in gene transcription: molecular mechanisms and disease associations

Although often located at a distance from their target gene promoters, enhancers are the primary genomic determinants of temporal and spatial transcriptional specificity in metazoans. Since the discovery of the first enhancer element in simian virus 40, there has been substantial interest in unraveling the mechanism(s) by which enhancers communicate with their partner promoters to ensure proper gene expression. These research efforts have benefited considerably from the application of increasingly sophisticated sequencing- and imaging-based approaches in conjunction with innovative (epi)genome-editing technologies; however, despite various proposed models, the principles of enhancer-promoter interaction have still not been fully elucidated. In this review, we provide an overview of recent progress in the eukaryotic gene transcription field pertaining to enhancer-promoter specificity. A better understanding of the mechanistic basis of lineage- and context-dependent enhancer-promoter engagement, along with the continued identification of functional enhancers, will provide key insights into the spatiotemporal control of gene expression that can reveal therapeutic opportunities for a range of enhancer-related diseases.

Computational methods for analysing multiscale 3D genome organization

Recent progress in whole-genome mapping and imaging technologies has enabled the characterization of the spatial organization and folding of the genome in the nucleus. In parallel, advanced computational methods have been developed to leverage these mapping data to reveal multiscale three-dimensional (3D) genome features and to provide a more complete view of genome structure and its connections to genome functions such as transcription. Here, we discuss how recently developed computational tools, including machine-learning-based methods and integrative structure-modelling frameworks, have led to a systematic, multiscale delineation of the connections among different scales of 3D genome organization, genomic and epigenomic features, functional nuclear components and genome function. However, approaches that more comprehensively integrate a wide variety of genomic and imaging datasets are still needed to uncover the functional role of 3D genome structure in defining cellular phenotypes in health and disease.

Lanthanide-Complex-Enhanced Bioorthogonal Branched DNA Amplification

Fluorescence in situ hybridization (FISH) is a widely used technique for detecting intracellular nucleic acids. However, its effectiveness in detecting low-copy nucleic acids is limited due to its low fluorescence intensity and background autofluorescence. To address these challenges, we present here an approach of lanthanide-complex-enhanced bioorthogonal-branched DNA amplification (LEBODA) with high sensitivity for in situ nuclear acid detection in single cells. The approach capitalizes on two levels of signal amplification. First, it utilizes click chemistry to directly link a substantial number of bridge probes to target-recognizing probes, providing an initial boost in signal intensity. Second, it incorporates high-density lanthanide complexes into each bridge probe, enabling secondary amplifications. Compared to the traditional "double Z" probes used in the RNAscope method, LEBODA exhibits 4 times the single enhancement for RNA detection signal with the click chemistry approach. Using SARS-CoV-2 pseudovirus-infected HeLa cells, we demonstrate the superiority in the detection of viral-infected cells in rare populations as low as 20% infectious rate. More encouragingly, the LEBODA approach can be adapted for DNA-FISH and single-molecule RNA-FISH, as well as other hybridization-based signal amplification methods. This adaptability broadens the potential applications of LEBODA in the sensitive detection of biomolecules, indicating promising prospects for future research and practical use.

Enablers and challenges of spatial omics, a melting pot of technologies

Spatial omics has emerged as a rapidly growing and fruitful field with hundreds of publications presenting novel methods for obtaining spatially resolved information for any omics data type on spatial scales ranging from subcellular to organismal. From a technology development perspective, spatial omics is a highly interdisciplinary field that integrates imaging and omics, spatial and molecular analyses, sequencing and mass spectrometry, and image analysis and bioinformatics. The emergence of this field has not only opened a window into spatial biology, but also created multiple novel opportunities, questions, and challenges for method developers. Here, we provide the perspective of technology developers on what makes the spatial omics field unique. After providing a brief overview of the state of the art, we discuss technological enablers and challenges and present our vision about the future applications and impact of this melting pot.

SnapFISH: a computational pipeline to identify chromatin loops from multiplexed DNA FISH data

Multiplexed DNA fluorescence in situ hybridization (FISH) imaging technologies have been developed to map the folding of chromatin fibers at tens of nanometers and up to several kilobases in resolution in single cells. However, computational methods to reliably identify chromatin loops from such imaging datasets are still lacking. Here we present a Single-Nucleus Analysis Pipeline for multiplexed DNA FISH (SnapFISH), to process the multiplexed DNA FISH data and identify chromatin loops. SnapFISH can identify known chromatin loops from mouse embryonic stem cells with high sensitivity and accuracy. In addition, SnapFISH obtains comparable results of chromatin loops across datasets generated from diverse imaging technologies. SnapFISH is freely available at https://github.com/HuMingLab/SnapFISH .

Spatial and temporal organization of the genome: Current state and future aims of the 4D nucleome project

The four-dimensional nucleome (4DN) consortium studies the architecture of the genome and the nucleus in space and time. We summarize progress by the consortium and highlight the development of technologies for (1) mapping genome folding and identifying roles of nuclear components and bodies, proteins, and RNA, (2) characterizing nuclear organization with time or single-cell resolution, and (3) imaging of nuclear organization. With these tools, the consortium has provided over 2,000 public datasets. Integrative computational models based on these data are starting to reveal connections between genome structure and function. We then present a forward-looking perspective and outline current aims to (1) delineate dynamics of nuclear architecture at different timescales, from minutes to weeks as cells differentiate, in populations and in single cells, (2) characterize cis-determinants and trans-modulators of genome organization, (3) test functional consequences of changes in cis- and trans-regulators, and (4) develop predictive models of genome structure and function.

Evaluating the role of the nuclear microenvironment in gene function by population-based modeling

The nuclear folding of chromosomes relative to nuclear bodies is an integral part of gene function. Here, we demonstrate that population-based modeling-from ensemble Hi-C data-provides a detailed description of the nuclear microenvironment of genes and its role in gene function. We define the microenvironment by the subnuclear positions of genomic regions with respect to nuclear bodies, local chromatin compaction, and preferences in chromatin compartmentalization. These structural descriptors are determined in single-cell models, thereby revealing the structural variability between cells. We demonstrate that the microenvironment of a genomic region is linked to its functional potential in gene transcription, replication, and chromatin compartmentalization. Some chromatin regions feature a strong preference for a single microenvironment, due to association with specific nuclear bodies in most cells. Other chromatin shows high structural variability, which is a strong indicator of functional heterogeneity. Moreover, we identify specialized nuclear microenvironments, which distinguish chromatin in different functional states and reveal a key role of nuclear speckles in chromosome organization. We demonstrate that our method produces highly predictive three-dimensional genome structures, which accurately reproduce data from a variety of orthogonal experiments, thus considerably expanding the range of Hi-C data analysis.

Methods and applications for single-cell and spatial multi-omics

The joint analysis of the genome, epigenome, transcriptome, proteome and/or metabolome from single cells is transforming our understanding of cell biology in health and disease. In less than a decade, the field has seen tremendous technological revolutions that enable crucial new insights into the interplay between intracellular and intercellular molecular mechanisms that govern development, physiology and pathogenesis. In this Review, we highlight advances in the fast-developing field of single-cell and spatial multi-omics technologies (also known as multimodal omics approaches), and the computational strategies needed to integrate information across these molecular layers. We demonstrate their impact on fundamental cell biology and translational research, discuss current challenges and provide an outlook to the future.

Next-generation sequencing methodologies to detect low-frequency mutations: "Catch me if you can"

Mutations, the irreversible changes in an organism's DNA sequence, are present in tissues at a variant allele frequency (VAF) ranging from ∼10-8 per bp for a founder mutation to ∼10-3 for a histologically normal tissue sample containing several independent clones - compared to 1%- 50% for a heterozygous tumor mutation or a polymorphism. The rarity of these events poses a challenge for accurate clinical diagnosis and prognosis, toxicology, and discovering new disease etiologies. Standard Next-Generation Sequencing (NGS) technologies report VAFs as low as 0.5% per nt, but reliably observing rarer precursor events requires additional sophistication to measure ultralow-frequency mutations. We detail the challenge; define terms used to characterize the results, which vary between laboratories and sometimes conflict between biologists and bioinformaticists; and describe recent innovations to improve standard NGS methodologies including: single-strand consensus sequence methods such as Safe-SeqS and SiMSen-Seq; tandem-strand consensus sequence methods such as o2n-Seq and SMM-Seq; and ultrasensitive parent-strand consensus sequence methods such as DuplexSeq, PacBio HiFi, SinoDuplex, OPUSeq, EcoSeq, BotSeqS, Hawk-Seq, NanoSeq, SaferSeq, and CODEC. Practical applications are also noted. Several methods quantify VAF down to 10-5 at a nt and mutation frequency (MF) in a target region down to 10-7 per nt. By expanding to > 1 Mb of sites never observed twice, thus forgoing VAF, other methods quantify MF < 10-9 per nt or < 15 errors per haploid genome. Clonal expansion cannot be directly distinguished from independent mutations by sequencing, so it is essential for a paper to report whether its MF counted only different mutations - the minimum independent-mutation frequency MFminI - or all mutations observed including recurrences - the larger maximum independent-mutation frequency MFmaxI which may reflect clonal expansion. Ultrasensitive methods reveal that, without their use, even mutations with VAF 0.5-1% are usually spurious.

Diversity of cells and signals in the cardiovascular system

This white paper is the outcome of the seventh UC Davis Cardiovascular Research Symposium on Systems Approach to Understanding Cardiovascular Disease and Arrhythmia. This biannual meeting aims to bring together leading experts in subfields of cardiovascular biomedicine to focus on topics of importance to the field. The theme of the 2022 Symposium was 'Cell Diversity in the Cardiovascular System, cell-autonomous and cell-cell signalling'. Experts in the field contributed their experimental and mathematical modelling perspectives and discussed emerging questions, controversies, and challenges in examining cell and signal diversity, co-ordination and interrelationships involved in cardiovascular function. This paper originates from the topics of formal presentations and informal discussions from the Symposium, which aimed to develop a holistic view of how the multiple cell types in the cardiovascular system integrate to influence cardiovascular function, disease progression and therapeutic strategies. The first section describes the major cell types (e.g. cardiomyocytes, vascular smooth muscle and endothelial cells, fibroblasts, neurons, immune cells, etc.) and the signals involved in cardiovascular function. The second section emphasizes the complexity at the subcellular, cellular and system levels in the context of cardiovascular development, ageing and disease. Finally, the third section surveys the technological innovations that allow the interrogation of this diversity and advancing our understanding of the integrated cardiovascular function and dysfunction.

A spatial genome aligner for resolving chromatin architectures from multiplexed DNA FISH

Multiplexed fluorescence in situ hybridization (FISH) is a widely used approach for analyzing three-dimensional genome organization, but it is challenging to derive chromosomal conformations from noisy fluorescence signals, and tracing chromatin is not straightforward. Here we report a spatial genome aligner that parses true chromatin signal from noise by aligning signals to a DNA polymer model. Using genomic distances separating imaged loci, our aligner estimates spatial distances expected to separate loci on a polymer in three-dimensional space. Our aligner then evaluates the physical probability observed signals belonging to these loci are connected, thereby tracing chromatin structures. We demonstrate that this spatial genome aligner can efficiently model chromosome architectures from DNA FISH data across multiple scales and be used to predict chromosome ploidies de novo in interphase cells. Reprocessing of previous whole-genome chromosome tracing data with this method indicates the spatial aggregation of sister chromatids in S/G2 phase cells in asynchronous mouse embryonic stem cells and provides evidence for extranumerary chromosomes that remain tightly paired in postmitotic neurons of the adult mouse cortex.

True-to-scale DNA-density maps correlate with major accessibility differences between active and inactive chromatin

Chromatin compaction differences may have a strong impact on accessibility of individual macromolecules and macromolecular assemblies to their DNA target sites. Estimates based on fluorescence microscopy with conventional resolution, however, suggest only modest compaction differences (∼2-10×) between the active nuclear compartment (ANC) and inactive nuclear compartment (INC). Here, we present maps of nuclear landscapes with true-to-scale DNA densities, ranging from <5 to >300 Mbp/μm3. Maps are generated from individual human and mouse cell nuclei with single-molecule localization microscopy at ∼20 nm lateral and ∼100 nm axial optical resolution and are supplemented by electron spectroscopic imaging. Microinjection of fluorescent nanobeads with sizes corresponding to macromolecular assemblies for transcription into nuclei of living cells demonstrates their localization and movements within the ANC and exclusion from the INC.

Probabilistic establishment of speckle-associated inter-chromosomal interactions

Inter-chromosomal interactions play a crucial role in genome organization, yet the organizational principles remain elusive. Here, we introduce a novel computational method to systematically characterize inter-chromosomal interactions using in situ Hi-C results from various cell types. Our method successfully identifies two apparently hub-like inter-chromosomal contacts associated with nuclear speckles and nucleoli, respectively. Interestingly, we discover that nuclear speckle-associated inter-chromosomal interactions are highly cell-type invariant with a marked enrichment of cell-type common super-enhancers (CSEs). Validation using DNA Oligopaint fluorescence in situ hybridization (FISH) shows a strong but probabilistic interaction behavior between nuclear speckles and CSE-harboring genomic regions. Strikingly, we find that the likelihood of speckle-CSE associations can accurately predict two experimentally measured inter-chromosomal contacts from Hi-C and Oligopaint DNA FISH. Our probabilistic establishment model well describes the hub-like structure observed at the population level as a cumulative effect of summing individual stochastic chromatin-speckle interactions. Lastly, we observe that CSEs are highly co-occupied by MAZ binding and MAZ depletion leads to significant disorganization of speckle-associated inter-chromosomal contacts. Taken together, our results propose a simple organizational principle of inter-chromosomal interactions mediated by MAZ-occupied CSEs.

Integrative approaches to study enhancer-promoter communication

The spatiotemporal control of gene expression in complex multicellular organisms relies on noncoding regulatory sequences such as enhancers, which activate transcription of target genes often over large genomic distances. Despite the advances in the identification and characterization of enhancers, the principles and mechanisms by which enhancers select and control their target genes remain largely unknown. Here, we review recent interdisciplinary and quantitative approaches based on emerging techniques that aim to address open questions in the field, notably how regulatory information is encoded in the DNA sequence, how this information is transferred from enhancers to promoters, and how these processes are regulated in time.

Genome-wide tracing to decipher nuclear organization

Nuclear organization impacts gene expression activity and cell phenotype. Our current understanding is mainly derived from ensemble-level sequencing studies that reflect the 3D genome structure of millions of cells. These approaches have provided invaluable details on the 3D organizations of the genome and their relation to other nuclear landmarks. However, they mostly lack the ability to provide multimodal information simultaneously at the single-cell level. In recent years, cutting-edge imaging technologies have risen to the challenge of simultaneously describing multiple components of the nuclear space at the single-cell level, paving the way for a deeper understanding of the genome structure-function relationship. This review will focus on the development and utilization of such technologies to gain a multi-component view of the nucleus at single-cell resolution, dissecting the complexity and heterogeneity of nuclear organization.

High-resolution spatial multi-omics reveals cell-type specific nuclear compartments

The mammalian nucleus is compartmentalized by diverse subnuclear structures. These subnuclear structures, marked by nuclear bodies and histone modifications, are often cell-type specific and affect gene regulation and 3D genome organization1-3. Understanding nuclear organization requires identifying the molecular constituents of subnuclear structures and mapping their associations with specific genomic loci in individual cells, within complex tissues. Here, we introduce two-layer DNA seqFISH+, which allows simultaneous mapping of 100,049 genomic loci, together with nascent transcriptome for 17,856 genes and a diverse set of immunofluorescently labeled subnuclear structures all in single cells in cell lines and adult mouse cerebellum. Using these multi-omics datasets, we showed that repressive chromatin compartments are more variable by cell type than active compartments. We also discovered a single exception to this rule: an RNA polymerase II (RNAPII)-enriched compartment was associated with long, cell-type specific genes (> 200kb), in a manner distinct from nuclear speckles. Further, our analysis revealed that cell-type specific facultative and constitutive heterochromatin compartments marked by H3K27me3 and H4K20me3 are enriched at specific genes and gene clusters, respectively, and shape radial chromosomal positioning and inter-chromosomal interactions in neurons and glial cells. Together, our results provide a single-cell high-resolution multi-omics view of subnuclear compartments, associated genomic loci, and their impacts on gene regulation, directly within complex tissues.

The magic of unraveling genome architecture and function

Over the last decades, technological breakthroughs in super-resolution microscopy have allowed us to reach molecular resolution and design experiments of unprecedented complexity. Investigating how chromatin is folded in 3D, from the nucleosome level up to the entire genome, is becoming possible by "magic" (imaging genomic), i.e., the combination of imaging and genomic approaches. This offers endless opportunities to delve into the relationship between genome structure and function. Here, we review recently achieved objectives and the conceptual and technical challenges the field of genome architecture is currently undertaking. We discuss what we have learned so far and where we are heading. We elucidate how the different super-resolution microscopy approaches and, more specifically, live-cell imaging have contributed to the understanding of genome folding. Moreover, we discuss how future technical developments could address remaining open questions.

Contributions of 3D chromatin structure to cell-type-specific gene regulation

Eukaryotic genomes are organized in 3D in a multiscale manner, and different mechanisms acting at each of these scales can contribute to transcriptional regulation. However, the large single-cell variability in 3D chromatin structures represents a challenge to understand how transcription may be differentially regulated between cell types in a robust and efficient manner. Here, we describe the different mechanisms by which 3D chromatin structure was shown to contribute to cell-type-specific transcriptional regulation. Excitingly, several novel methodologies able to measure 3D chromatin conformation and transcription in single cells in their native tissue context, or to detect the dynamics of cis-regulatory interactions, are starting to allow quantitative dissection of chromatin structure noise and relate it to how transcription may be regulated between different cell types and cell states.

Spatiotemporal dissection of tumor microenvironment via in situ sensing and monitoring in tumor-on-a-chip

Real-time monitoring in the tumor microenvironment provides critical insights of cancer progression and mechanistic understanding of responses to cancer treatments. However, clinical challenges and significant questions remain regarding assessment of limited clinical tissue samples, establishment of validated, controllable pre-clinical cancer models, monitoring of static versus dynamic markers, and the translation of insights gained from in vitro tumor microenvironments to systematic investigation and understanding in clinical practice. State-of-art tumor-on-a-chip strategies will be reviewed herein, and emerging real-time sensing and monitoring platforms for on-chip analysis of tumor microenvironment will also be examined. The integration of the sensors with tumor-on-a-chip platforms to provide spatiotemporal information of the tumor microenvironment and the associated challenges will be further evaluated. Though optimal integrated systems for in situ monitoring are still in evolution, great promises lie ahead that will open new paradigm for rapid, comprehensive analysis of cancer development and assist clinicians with powerful tools to guide the diagnosis, prognosis and treatment course in cancer.

Fluorescence-based super-resolution-microscopy strategies for chromatin studies

Super-resolution microscopy (SRM) is a prime tool to study chromatin organisation at near biomolecular resolution in the native cellular environment. With fluorescent labels DNA, chromatin-associated proteins and specific epigenetic states can be identified with high molecular specificity. The aim of this review is to introduce the field of diffraction-unlimited SRM to enable an informed selection of the most suitable SRM method for a specific chromatin-related research question. We will explain both diffraction-unlimited approaches (coordinate-targeted and stochastic-localisation-based) and list their characteristic spatio-temporal resolutions, live-cell compatibility, image-processing, and ability for multi-colour imaging. As the increase in resolution, compared to, e.g. confocal microscopy, leads to a central role of the sample quality, important considerations for sample preparation and concrete examples of labelling strategies applicable to chromatin research are discussed. To illustrate how SRM-based methods can significantly improve our understanding of chromatin functioning, and to serve as an inspiring starting point for future work, we conclude with examples of recent applications of SRM in chromatin research.

Spatial profiling technologies illuminate the tumor microenvironment

The tumor microenvironment (TME) is composed of many different cellular and acellular components that together drive tumor growth, invasion, metastasis, and response to therapies. Increasing realization of the significance of the TME in cancer biology has shifted cancer research from a cancer-centric model to one that considers the TME as a whole. Recent technological advancements in spatial profiling methodologies provide a systematic view and illuminate the physical localization of the components of the TME. In this review, we provide an overview of major spatial profiling technologies. We present the types of information that can be extracted from these data and describe their applications, findings and challenges in cancer research. Finally, we provide a future perspective of how spatial profiling could be integrated into cancer research to improve patient diagnosis, prognosis, stratification to treatment and development of novel therapeutics.

Interpretable and context-free deconvolution of multi-scale whole transcriptomic data with UniCell deconvolve

We introduce UniCell: Deconvolve Base (UCDBase), a pre-trained, interpretable, deep learning model to deconvolve cell type fractions and predict cell identity across Spatial, bulk-RNA-Seq, and scRNA-Seq datasets without contextualized reference data. UCD is trained on 10 million pseudo-mixtures from a fully-integrated scRNA-Seq training database comprising over 28 million annotated single cells spanning 840 unique cell types from 898 studies. We show that our UCDBase and transfer-learning models achieve comparable or superior performance on in-silico mixture deconvolution to existing, reference-based, state-of-the-art methods. Feature attribute analysis uncovers gene signatures associated with cell-type specific inflammatory-fibrotic responses in ischemic kidney injury, discerns cancer subtypes, and accurately deconvolves tumor microenvironments. UCD identifies pathologic changes in cell fractions among bulk-RNA-Seq data for several disease states. Applied to lung cancer scRNA-Seq data, UCD annotates and distinguishes normal from cancerous cells. Overall, UCD enhances transcriptomic data analysis, aiding in assessment of cellular and spatial context.

The anti-immune dengue subgenomic flaviviral RNA is present in vesicles in mosquito saliva and is associated with increased infectivity

Mosquito transmission of dengue viruses to humans starts with infection of skin resident cells at the biting site. There is great interest in identifying transmission-enhancing factors in mosquito saliva in order to counteract them. Here we report the discovery of high levels of the anti-immune subgenomic flaviviral RNA (sfRNA) in dengue virus 2-infected mosquito saliva. We established that sfRNA is present in saliva using three different methods: northern blot, RT-qPCR and RNA sequencing. We next show that salivary sfRNA is protected in detergent-sensitive compartments, likely extracellular vesicles. In support of this hypothesis, we visualized viral RNAs in vesicles in mosquito saliva and noted a marked enrichment of signal from 3'UTR sequences, which is consistent with the presence of sfRNA. Furthermore, we show that incubation with mosquito saliva containing higher sfRNA levels results in higher virus infectivity in a human hepatoma cell line and human primary dermal fibroblasts. Transfection of 3'UTR RNA prior to DENV2 infection inhibited type I and III interferon induction and signaling, and enhanced viral replication. Therefore, we posit that sfRNA present in salivary extracellular vesicles is delivered to cells at the biting site to inhibit innate immunity and enhance dengue virus transmission.

Subcellular omics: a new frontier pushing the limits of resolution, complexity and throughput

We argue that the study of single-cell subcellular organelle omics is needed to understand and regulate cell function. This requires and is being enabled by new technology development.

Dynamics of nuclear architecture during early embryonic development and lessons from liveimaging

Nuclear organization has emerged as a potential key regulator of genome function. During development, the deployment of transcriptional programs must be tightly coordinated with cell division and is often accompanied by major changes in the repertoire of expressed genes. These transcriptional and developmental events are paralleled by changes in the chromatin landscape. Numerous studies have revealed the dynamics of nuclear organization underlying them. In addition, advances in live-imaging-based methodologies enable the study of nuclear organization with high spatial and temporal resolution. In this Review, we summarize the current knowledge of the changes in nuclear architecture in the early embryogenesis of various model systems. Furthermore, to highlight the importance of integrating fixed-cell and live approaches, we discuss how different live-imaging techniques can be applied to examine nuclear processes and their contribution to our understanding of transcription and chromatin dynamics in early development. Finally, we provide future avenues for outstanding questions in this field.

Conformational analysis of chromosome structures reveals vital role of chromosome morphology in gene function

The 3D conformations of chromosomes are highly variant and stochastic between single cells. Recent progress in multiplexed 3D FISH imaging, single cell Hi-C and genome structure modeling allows a closer analysis of the structural variations of chromosomes between cells to infer the functional implications of structural heterogeneity. Here, we introduce a two-step dimensionality reduction method to classify a population of single cell 3D chromosome structures, either from simulation or imaging experiment, into dominant conformational clusters with distinct chromosome morphologies. We found that almost half of all structures for each chromosome can be described by 5-10 dominant chromosome morphologies, which play a fundamental role in establishing conformational variation of chromosomes. These morphologies are conserved in different cell types, but vary in their relative proportion of structures. Chromosome morphologies are distinguished by the presence or absence of characteristic chromosome territory domains, which expose some chromosomal regions to varying nuclear environments in different morphologies, such as nuclear positions and associations to nuclear speckles, lamina, and nucleoli. These observations point to distinct functional variations for the same chromosomal region in different chromosome morphologies. We validated chromosome conformational clusters and their associated subnuclear locations with data from DNA-MERFISH imaging and single cell sci-HiC data. Our method provides an important approach to assess the variation of chromosome structures between cells and link differences in conformational states with distinct gene functions.

Unveiling the Machinery behind Chromosome Folding by Polymer Physics Modeling

Understanding the mechanisms underlying the complex 3D architecture of mammalian genomes poses, at a more fundamental level, the problem of how two or multiple genomic sites can establish physical contacts in the nucleus of the cells. Beyond stochastic and fleeting encounters related to the polymeric nature of chromatin, experiments have revealed specific, privileged patterns of interactions that suggest the existence of basic organizing principles of folding. In this review, we focus on two major and recently proposed physical processes of chromatin organization: loop-extrusion and polymer phase-separation, both supported by increasing experimental evidence. We discuss their implementation into polymer physics models, which we test against available single-cell super-resolution imaging data, showing that both mechanisms can cooperate to shape chromatin structure at the single-molecule level. Next, by exploiting the comprehension of the underlying molecular mechanisms, we illustrate how such polymer models can be used as powerful tools to make predictions in silico that can complement experiments in understanding genome folding. To this aim, we focus on recent key applications, such as the prediction of chromatin structure rearrangements upon disease-associated mutations and the identification of the putative chromatin organizing factors that orchestrate the specificity of DNA regulatory contacts genome-wide.

The spatial organization of transcriptional control

In animals, the sequences for controlling gene expression do not concentrate just at the transcription start site of genes, but are frequently thousands to millions of base pairs distal to it. The interaction of these sequences with one another and their transcription start sites is regulated by factors that shape the three-dimensional (3D) organization of the genome within the nucleus. Over the past decade, indirect tools exploiting high-throughput DNA sequencing have helped to map this 3D organization, have identified multiple key regulators of its structure and, in the process, have substantially reshaped our view of how 3D genome architecture regulates transcription. Now, new tools for high-throughput super-resolution imaging of chromatin have directly visualized the 3D chromatin organization, settling some debates left unresolved by earlier indirect methods, challenging some earlier models of regulatory specificity and creating hypotheses about the role of chromatin structure in transcriptional regulation.

Application of spatial transcriptome technologies to neurological diseases

Spatial transcriptome technology acquires gene expression profiles while retaining spatial location information, it displays the gene expression properties of cells in situ. Through the investigation of cell heterogeneity, microenvironment, function, and cellular interactions, spatial transcriptome technology can deeply explore the pathogenic mechanisms of cell-type-specific responses and spatial localization in neurological diseases. The present article overviews spatial transcriptome technologies based on microdissection, in situ hybridization, in situ sequencing, in situ capture, and live cell labeling. Each technology is described along with its methods, detection throughput, spatial resolution, benefits, and drawbacks. Furthermore, their applications in neurodegenerative disease, neuropsychiatric illness, stroke and epilepsy are outlined. This information can be used to understand disease mechanisms, pick therapeutic targets, and establish biomarkers.

Multiplexed Organelles Portrait Barcodes for Subcellular MicroRNA Array Detection in Living Cells

Multiplexed profiling of microRNAs' subcellular expression and distribution is essential to understand their spatiotemporal function information, but it remains a crucial challenge. Herein, we report an encoding approach that leverages combinational fluorescent dye barcodes, organelle targeting elements, and an independent quantification signal, termed Multiplexed Organelles Portrait Barcodes (MOPB), for high-throughput profiling of miRNAs from organelles. The MOPB barcodes consist of heterochromatic fluorescent dye-loaded shell-core mesoporous silica nanoparticles modified with organelle targeting peptides and molecular beacon detection probes. Using mitochondria and endoplasmic reticulum as models, we encoded four Cy3/AMCA ER-MOPB and four Cy5/AMCA Mito-MOPB by varying the Cy3 and Cy5 intensity for distinguishing eight organelles' miRNAs. Significantly, the MOPB strategy successfully and accurately profiled eight subcellular organelle miRNAs' alterations in the drug-induced Ca²⁺ homeostasis breakdown. The approach should allow more widespread application of subcellular miRNAs and multiplexed subcellular protein biomarkers' monitoring for drug discovery, cellular metabolism, signaling transduction, and gene expression regulation readout.

RS-FISH: precise, interactive, fast, and scalable FISH spot detection

Fluorescent in-situ hybridization (FISH)-based methods extract spatially resolved genetic and epigenetic information from biological samples by detecting fluorescent spots in microscopy images, an often challenging task. We present Radial Symmetry-FISH (RS-FISH), an accurate, fast, and user-friendly software for spot detection in two- and three-dimensional images. RS-FISH offers interactive parameter tuning and readily scales to large datasets and image volumes of cleared or expanded samples using distributed processing on workstations, clusters, or the cloud. RS-FISH maintains high detection accuracy and low localization error across a wide range of signal-to-noise ratios, a key feature for single-molecule FISH, spatial transcriptomics, or spatial genomics applications.

Integrative studies of 3D genome organization and chromatin structure

The structural organization of the genome is emerging as a crucial regulator of the cell state, affecting gene transcription, DNA replication, and repair. Over the last twenty years, increasing evidence prompted the development of new experimental techniques to study genome structure. In parallel with the complexity of the novel techniques, computational approaches have become an essential tool in any structural genomics laboratory to analyze and model the data. For biologists to be able to apply the most appropriate modeling approach, it is fundamental to understand the conceptual bases of distinct methods and the insights they can provide. Here, we will discuss recent advances that were possible thanks to 3D genome modeling, discuss their limitations and highlight future perspectives.

FRET-FISH probes chromatin compaction at individual genomic loci in single cells

Chromatin compaction is a key biophysical property that influences multiple DNA transactions. Lack of chromatin accessibility is frequently used as proxy for chromatin compaction. However, we currently lack tools for directly probing chromatin compaction at individual genomic loci. To fill this gap, here we present FRET-FISH, a method combining fluorescence resonance energy transfer (FRET) with DNA fluorescence in situ hybridization (FISH) to probe chromatin compaction at select loci in single cells. We first validate FRET-FISH by comparing it with ATAC-seq, demonstrating that local compaction and accessibility are strongly correlated. FRET-FISH also detects expected differences in compaction upon treatment with drugs perturbing global chromatin condensation. We then leverage FRET-FISH to study local chromatin compaction on the active and inactive X chromosome, along the nuclear radius, in different cell cycle phases, and during increasing passage number. FRET-FISH is a robust tool for probing local chromatin compaction in single cells.

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.

Every gene everywhere all at once: High-precision measurement of 3D chromosome architecture with single-cell Hi-C

The three-dimensional (3D) structure of chromosomes influences essential biological processes such as gene expression, genome replication, and DNA damage repair and has been implicated in many developmental and degenerative diseases. In the past two centuries, two complementary genres of technology-microscopy, such as fluorescence in situ hybridization (FISH), and biochemistry, such as chromosome conformation capture (3C or Hi-C)-have revealed general principles of chromosome folding in the cell nucleus. However, the extraordinary complexity and cell-to-cell variability of the chromosome structure necessitate new tools with genome-wide coverage and single-cell precision. In the past decade, single-cell Hi-C emerges as a new approach that builds upon yet conceptually differs from bulk Hi-C assays. Instead of measuring population-averaged statistical properties of chromosome folding, single-cell Hi-C works as a proximity-based "biochemical microscope" that measures actual 3D structures of individual genomes, revealing features hidden in bulk Hi-C such as radial organization, multi-way interactions, and chromosome intermingling. Single-cell Hi-C has been used to study highly dynamic processes such as the cell cycle, cell-type-specific chromosome architecture ("structure types"), and structure-expression interplay, deepening our understanding of DNA organization and function.

MiOS, an integrated imaging and computational strategy to model gene folding with nucleosome resolution

The linear sequence of DNA provides invaluable information about genes and their regulatory elements along chromosomes. However, to fully understand gene function and regulation, we need to dissect how genes physically fold in the three-dimensional nuclear space. Here we describe immuno-OligoSTORM, an imaging strategy that reveals the distribution of nucleosomes within specific genes in super-resolution, through the simultaneous visualization of DNA and histones. We combine immuno-OligoSTORM with restraint-based and coarse-grained modeling approaches to integrate super-resolution imaging data with Hi-C contact frequencies and deconvoluted micrococcal nuclease-sequencing information. The resulting method, called Modeling immuno-OligoSTORM, allows quantitative modeling of genes with nucleosome resolution and provides information about chromatin accessibility for regulatory factors, such as RNA polymerase II. With Modeling immuno-OligoSTORM, we explore intercellular variability, transcriptional-dependent gene conformation, and folding of housekeeping and pluripotency-related genes in human pluripotent and differentiated cells, thereby obtaining the highest degree of data integration achieved so far to our knowledge.

Understanding the function of regulatory DNA interactions in the interpretation of non-coding GWAS variants

Genome-wide association studies (GWAS) have identified a vast number of variants associated with various complex human diseases and traits. However, most of these GWAS variants reside in non-coding regions producing no proteins, making the interpretation of these variants a daunting challenge. Prior evidence indicates that a subset of non-coding variants detected within or near cis-regulatory elements (e.g., promoters, enhancers, silencers, and insulators) might play a key role in disease etiology by regulating gene expression. Advanced sequencing- and imaging-based technologies, together with powerful computational methods, enabling comprehensive characterization of regulatory DNA interactions, have substantially improved our understanding of the three-dimensional (3D) genome architecture. Recent literature witnesses plenty of examples where using chromosome conformation capture (3C)-based technologies successfully links non-coding variants to their target genes and prioritizes relevant tissues or cell types. These examples illustrate the critical capability of 3D genome organization in annotating non-coding GWAS variants. This review discusses how 3D genome organization information contributes to elucidating the potential roles of non-coding GWAS variants in disease etiology.

The emerging landscape of spatial profiling technologies

Improved scale, multiplexing and resolution are establishing spatial nucleic acid and protein profiling methods as a major pillar for cellular atlas building of complex samples, from tissues to full organisms. Emerging methods yield omics measurements at resolutions covering the nano- to microscale, enabling the charting of cellular heterogeneity, complex tissue architectures and dynamic changes during development and disease. We present an overview of the developing landscape of in situ spatial genome, transcriptome and proteome technologies, exemplify their impact on cell biology and translational research, and discuss current challenges for their community-wide adoption. Among many transformative applications, we envision that spatial methods will map entire organs and enable next-generation pathology.

Uncovering the statistical physics of 3D chromosomal organization using data-driven modeling

In recent years, much effort has been devoted to understanding the three-dimensional (3D) organization of the genome and how genomic structure mediates nuclear function. The development of experimental techniques that combine DNA proximity ligation with high-throughput sequencing, such as Hi-C, have substantially improved our knowledge about chromatin organization. Numerous experimental advancements, not only utilizing DNA proximity ligation but also high-resolution genome imaging (DNA tracing), have required theoretical modeling to determine the structural ensembles consistent with such data. These 3D polymer models of the genome provide an understanding of the physical mechanisms governing genome architecture. Here, we present an overview of the recent advances in modeling the ensemble of 3D chromosomal structures by employing the maximum entropy approach combined with polymer physics. Particularly, we discuss the minimal chromatin model (MiChroM) along with the "maximum entropy genomic annotations from biomarkers associated with structural ensembles" (MEGABASE) model, which have been remarkably successful in the accurate modeling of chromosomes consistent with both Hi-C and DNA-tracing data.

Nuclear speckles - a driving force in gene expression

Nuclear speckles are dynamic membraneless bodies located in the cell nucleus. They harbor RNAs and proteins, many of which are splicing factors, that together display complex biophysical properties dictating nuclear speckle formation and maintenance. Although these nuclear bodies were discovered decades ago, only recently has in-depth genomic analysis begun to unravel their essential functions in modulation of gene activity. Major advancements in genomic mapping techniques combined with microscopy approaches have enabled insights into the roles nuclear speckles may play in enhancing gene expression, and how gene positioning to specific nuclear landmarks can regulate gene expression and RNA processing. Some studies have drawn a link between nuclear speckles and disease. Certain maladies either involve nuclear speckles directly or dictate the localization and reorganization of many nuclear speckle factors. This is most striking during viral infection, as viruses alter the entire nuclear architecture and highjack host machinery. As discussed in this Review, nuclear speckles represent a fascinating target of study not only to reveal the links between gene positioning, genome subcompartments and gene activity, but also as a potential target for therapeutics.

The era of 3D and spatial genomics

Over a decade ago the advent of high-throughput chromosome conformation capture (Hi-C) sparked a new era of 3D genomics. Since then the number of methods for mapping the 3D genome has flourished, enabling an ever-increasing understanding of how DNA is packaged in the nucleus and how the spatiotemporal organization of the genome orchestrates its vital functions. More recently, the next generation of spatial genomics technologies has begun to reveal how genome sequence and 3D genome organization vary between cells in their tissue context. We summarize how the toolkit for charting genome topology has evolved over the past decade and discuss how new technological developments are advancing the field of 3D and spatial genomics.

Can 3D diploid genome reconstruction from unphased Hi-C data be salvaged?

The three-dimensional (3D) configuration of chromatin impacts numerous cellular processes. However, directly observing chromatin architecture at high resolution is challenging. Accordingly, inferring 3D structure utilizing chromatin conformation capture assays, notably Hi-C, has received considerable attention, with a multitude of reconstruction algorithms advanced. While these have enhanced appreciation of chromatin organization, most suffer from a serious shortcoming when faced with diploid genomes: inability to disambiguate contacts between corresponding loci on homologous chromosomes, making attendant reconstructions potentially meaningless. Three recent proposals offer a computational way forward at the expense of strong assumptions. Here, we show that making plausible assumptions about the components of homologous chromosome contacts provides a basis for rescuing conventional consensus-based, unphased reconstruction. This would be consequential since not only are assumptions needed for diploid reconstruction considerable, but the sophistication of select unphased algorithms affords substantive advantages with regard resolution and folding complexity. Rather than presuming that the requisite salvaging assumptions are met, we exploit a recent imaging technology, in situ genome sequencing (IGS), to comprehensively evaluate their reasonableness. We analogously use IGS to assess assumptions underpinning diploid reconstruction algorithms. Results convincingly demonstrate that, in all instances, assumptions are not met, making further algorithm development, potentially informed by IGS data, essential.

Spatial transcriptomics and the kidney

PURPOSE OF REVIEW

The application of spatial transcriptomics technologies to the interrogation of kidney tissue is a burgeoning effort. These technologies share a common purpose in mapping both the expression of individual molecules and entire transcriptomic signatures of kidney cell types and structures. Such information is often superimposed upon a histologic image. The resulting datasets are readily merged with other imaging and transcriptomic techniques to establish a spatially anchored atlas of the kidney. This review provides an overview of the various spatial transcriptomic technologies and recent studies in kidney disease. Potential applications gleaned from the interrogation of other organ systems, but relative to the kidney, are also discussed.

RECENT FINDINGS

Spatial transcriptomic technologies have enabled localization of whole transcriptome mRNA expression, correlation of mRNA to histology, measurement of in situ changes in expression across time, and even subcellular localization of transcripts within the kidney. These innovations continue to aid in the development of human cellular atlases of the kidney, the reclassification of disease, and the identification of important therapeutic targets.

SUMMARY

Spatial localization of gene expression will complement our current understanding of disease derived from single cell RNA sequencing, histopathology, protein immunofluorescence, and electron microscopy. Although spatial technologies continue to evolve rapidly, their importance in the localization of disease signatures is already apparent. Further efforts are required to integrate whole transcriptome and subcellular expression signatures into the individualized assessment of human kidney disease.

Open Structural Data in Precision Medicine

Three-dimensional protein structural data at the molecular level are pivotal for successful precision medicine. Such data are crucial not only for discovering drugs that act to block the active site of the target mutant protein but also for clarifying to the patient and the clinician how the mutations harbored by the patient work. The relative paucity of structural data reflects their cost, challenges in their interpretation, and lack of clinical guidelines for their utilization. Rapid technological advancements in experimental high-resolution structural determination increasingly generate structures. Computationally, modeling algorithms, including molecular dynamics simulations, are becoming more powerful, as are compute-intensive hardware, particularly graphics processing units, overlapping with the inception of the exascale era. Accessible, freely available, and detailed structural and dynamical data can be merged with big data to powerfully transform personalized pharmacology. Here we review protein and emerging genome high-resolution data, along with means, applications, and examples underscoring their usefulness in precision medicine. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Understanding Regulatory Mechanisms of Brain Function and Disease through 3D Genome Organization

The human genome has a complex and dynamic three-dimensional (3D) organization, which plays a critical role for gene regulation and genome function. The importance of 3D genome organization in brain development and function has been well characterized in a region- and cell-type-specific fashion. Recent technological advances in chromosome conformation capture (3C)-based techniques, imaging approaches, and ligation-free methods, along with computational methods to analyze the data generated, have revealed 3D genome features at different scales in the brain that contribute to our understanding of genetic mechanisms underlying neuropsychiatric diseases and other brain-related traits. In this review, we discuss how these advances aid in the genetic dissection of brain-related traits.

ChromoMap: an R package for interactive visualization of multi-omics data and annotation of chromosomes

Background

The recent advancements in high-throughput sequencing have resulted in the availability of annotated genomes, as well as of multi-omics data for many living organisms. This has increased the need for graphic tools that allow the concurrent visualization of genomes and feature-associated multi-omics data on single publication-ready plots.

Results

We present chromoMap, an R package, developed for the construction of interactive visualizations of chromosomes/chromosomal regions, mapping of any chromosomal feature with known coordinates (i.e., protein coding genes, transposable elements, non-coding RNAs, microsatellites, etc.), and chromosomal regional characteristics (i.e. genomic feature density, gene expression, DNA methylation, chromatin modifications, etc.) of organisms with a genome assembly. ChromoMap can also integrate multi-omics data (genomics, transcriptomics and epigenomics) in relation to their occurrence across chromosomes. ChromoMap takes tab-delimited files (BED like) or alternatively R objects to specify the genomic co-ordinates of the chromosomes and elements to annotate. Rendered chromosomes are composed of continuous windows of a given range, which, on hover, display detailed information about the elements annotated within that range. By adjusting parameters of a single function, users can generate a variety of plots that can either be saved as static image or as HTML documents.

Conclusions

ChromoMap’s flexibility allows for concurrent visualization of genomic data in each strand of a given chromosome, or of more than one homologous chromosome; allowing the comparison of multi-omic data between genotypes (e.g. species, varieties, etc.) or between homologous chromosomes of phased diploid/polyploid genomes. chromoMap is an extensive tool that can be potentially used in various bioinformatics analysis pipelines for genomic visualization of multi-omics data.