Simultaneous quantification of protein-DNA contacts and transcriptomes in single cells

CRWN nuclear lamina components maintain the H3K27me3 landscape and promote successful reproduction in Arabidopsis

Arabidopsis lamin analogs CROWDED NUCLEIs (CRWNs) are necessary to maintain nuclear structure, genome function, and proper plant growth. However, whether and how CRWNs impact reproduction and genome-wide epigenetic modifications is unknown. Here, we investigate the role of CRWNs during the development of gametophytes, seeds, and endosperm, using genomic and epigenomic profiling methods. We observed defects in crwn mutant seeds including seed abortion and reduced germination rate. Quadruple crwn null genotypes were rarely transmitted through gametophytes. Because defects in seeds often stem from abnormal endosperm development, we focused on crwn1 crwn2 (crwn1/2) endosperm. These mutant seeds exhibited enlarged chalazal endosperm cysts and increased expression of stress-related genes and the MADS-box transcription factor PHERES1 and its targets. Previously, it was shown that PHERES1 expression is regulated by H3K27me3 and that CRWN1 interacts with the PRC2 interactor PWO1. Thus, we tested whether crwn1/2 alters H3K27me3 patterns. We observed a mild loss of H3K27me3 at several hundred loci, which differed between endosperm and leaves. These data indicate that CRWNs are necessary to maintain the H3K27me3 landscape, with tissue-specific chromatin and transcriptional consequences.

The probability of chromatin to be at the nuclear lamina has no systematic effect on its transcription level in fruit flies

BACKGROUND

Multiple studies have demonstrated a negative correlation between gene expression and positioning of genes at the nuclear envelope (NE) lined by nuclear lamina, but the exact relationship remains unclear, especially in light of the highly stochastic, transient nature of the gene association with the NE.

RESULTS

In this paper, we ask whether there is a causal, systematic, genome-wide relationship between the expression levels of the groups of genes in topologically associating domains (TADs) of Drosophila nuclei and the probabilities of TADs to be found at the NE. To investigate the nature of this possible relationship, we combine a coarse-grained dynamic model of the entire Drosophila nucleus with genome-wide gene expression data; we analyze the TAD averaged transcription levels of genes against the probabilities of individual TADs to be in contact with the NE in the control and lamins-depleted nuclei. Our findings demonstrate that, within the statistical error margin, the stochastic positioning of Drosophila melanogaster TADs at the NE does not, by itself, systematically affect the mean level of gene expression in these TADs, while the expected negative correlation is confirmed. The correlation is weak and disappears completely for TADs not containing lamina-associated domains (LADs) or TADs containing LADs, considered separately. Verifiable hypotheses regarding the underlying mechanism for the presence of the correlation without causality are discussed. These include the possibility that the epigenetic marks and affinity to the NE of a TAD are determined by various non-mutually exclusive mechanisms and remain relatively stable during interphase.

CONCLUSIONS

At the level of TADs, the probability of chromatin being in contact with the nuclear envelope has no systematic, causal effect on the transcription level in Drosophila. The conclusion is reached by combining model-derived time-evolution of TAD locations within the nucleus with their experimental gene expression levels.

Applications of single‑cell omics and spatial transcriptomics technologies in gastric cancer (Review)

Gastric cancer (GC) is a prominent contributor to global cancer-related mortalities, and a deeper understanding of its molecular characteristics and tumor heterogeneity is required. Single-cell omics and spatial transcriptomics (ST) technologies have revolutionized cancer research by enabling the exploration of cellular heterogeneity and molecular landscapes at the single-cell level. In the present review, an overview of the advancements in single-cell omics and ST technologies and their applications in GC research is provided. Firstly, multiple single-cell omics and ST methods are discussed, highlighting their ability to offer unique insights into gene expression, genetic alterations, epigenomic modifications, protein expression patterns and cellular location in tissues. Furthermore, a summary is provided of key findings from previous research on single-cell omics and ST methods used in GC, which have provided valuable insights into genetic alterations, tumor diagnosis and prognosis, tumor microenvironment analysis, and treatment response. In summary, the application of single-cell omics and ST technologies has revealed the levels of cellular heterogeneity and the molecular characteristics of GC, and holds promise for improving diagnostics, personalized treatments and patient outcomes in GC.

Advances in single-cell omics and multiomics for high-resolution molecular profiling

Single-cell omics technologies have revolutionized molecular profiling by providing high-resolution insights into cellular heterogeneity and complexity. Traditional bulk omics approaches average signals from heterogeneous cell populations, thereby obscuring important cellular nuances. Single-cell omics studies enable the analysis of individual cells and reveal diverse cell types, dynamic cellular states, and rare cell populations. These techniques offer unprecedented resolution and sensitivity, enabling researchers to unravel the molecular landscape of individual cells. Furthermore, the integration of multimodal omics data within a single cell provides a comprehensive and holistic view of cellular processes. By combining multiple omics dimensions, multimodal omics approaches can facilitate the elucidation of complex cellular interactions, regulatory networks, and molecular mechanisms. This integrative approach enhances our understanding of cellular systems, from development to disease. This review provides an overview of the recent advances in single-cell and multimodal omics for high-resolution molecular profiling. We discuss the principles and methodologies for representatives of each omics method, highlighting the strengths and limitations of the different techniques. In addition, we present case studies demonstrating the applications of single-cell and multimodal omics in various fields, including developmental biology, neurobiology, cancer research, immunology, and precision medicine.

Combinatorial single-cell profiling of major chromatin types with MAbID

Gene expression programs result from the collective activity of numerous regulatory factors. Studying their cooperative mode of action is imperative to understand gene regulation, but simultaneously measuring these factors within one sample has been challenging. Here we introduce Multiplexing Antibodies by barcode Identification (MAbID), a method for combinatorial genomic profiling of histone modifications and chromatin-binding proteins. MAbID employs antibody-DNA conjugates to integrate barcodes at the genomic location of the epitope, enabling combined incubation of multiple antibodies to reveal the distributions of many epigenetic markers simultaneously. We used MAbID to profile major chromatin types and multiplexed measurements without loss of individual data quality. Moreover, we obtained joint measurements of six epitopes in single cells of mouse bone marrow and during mouse in vitro differentiation, capturing associated changes in multifactorial chromatin states. Thus, MAbID holds the potential to gain unique insights into the interplay between gene regulatory mechanisms, especially for low-input samples and in single cells.

Perturbations in 3D genome organization can promote acquired drug resistance

Acquired drug resistance is a major problem in the treatment of cancer. hTERT-immortalized, untransformed RPE-1 cells can acquire resistance to Taxol by derepressing the ABCB1 gene, encoding for the multidrug transporter P-gP. Here, we investigate how the ABCB1 gene is derepressed. ABCB1 activation is associated with reduced H3K9 trimethylation, increased H3K27 acetylation, and ABCB1 displacement from the nuclear lamina. While altering DNA methylation and H3K27 methylation had no major impact on ABCB1 expression, nor did it promote resistance, disrupting the nuclear lamina component Lamin B Receptor did promote the acquisition of a Taxol-resistant phenotype in a subset of cells. CRISPRa-mediated gene activation supported the notion that lamina dissociation influences ABCB1 derepression. We propose a model in which nuclear lamina dissociation of a repressed gene allows for its activation, implying that deregulation of the 3D genome topology could play an important role in tumor evolution and the acquisition of drug resistance.

Interactions of Chromatin with the Nuclear Lamina and Nuclear Pore Complexes

Heterochromatin and euchromatin form different spatial compartments in the interphase nucleus, with heterochromatin being localized mainly at the nuclear periphery. The mechanisms responsible for peripheral localization of heterochromatin are still not fully understood. The nuclear lamina and nuclear pore complexes were obvious candidates for the role of heterochromatin binders. This review is focused on recent studies showing that heterochromatin interactions with the nuclear lamina and nuclear pore complexes maintain its peripheral localization. Differences in chromatin interactions with the nuclear envelope in cell populations and in individual cells are also discussed.

Single-cell sequencing technology applied to epigenetics for the study of tumor heterogeneity

BACKGROUND

Previous studies have traditionally attributed the initiation of cancer cells to genetic mutations, considering them as the fundamental drivers of carcinogenesis. However, recent research has shed light on the crucial role of epigenomic alterations in various cell types present within the tumor microenvironment, suggesting their potential contribution to tumor formation and progression. Despite these significant findings, the progress in understanding the epigenetic mechanisms regulating tumor heterogeneity has been impeded over the past few years due to the lack of appropriate technical tools and methodologies.

RESULTS

The emergence of single-cell sequencing has enhanced our understanding of the epigenetic mechanisms governing tumor heterogeneity by revealing the distinct epigenetic layers of individual cells (chromatin accessibility, DNA/RNA methylation, histone modifications, nucleosome localization) and the diverse omics (transcriptomics, genomics, multi-omics) at the single-cell level. These technologies provide us with new insights into the molecular basis of intratumoral heterogeneity and help uncover key molecular events and driving mechanisms in tumor development.

CONCLUSION

This paper provides a comprehensive review of the emerging analytical and experimental approaches of single-cell sequencing in various omics, focusing specifically on epigenomics. These approaches have the potential to capture and integrate multiple dimensions of individual cancer cells, thereby revealing tumor heterogeneity and epigenetic features. Additionally, this paper outlines the future trends of these technologies and their current technical limitations.

CRWN nuclear lamina components maintain the H3K27me3 landscape and promote successful reproduction in Arabidopsis

The nuclear lamina, a sub-nuclear protein matrix, maintains nuclear structure and genome function. Here, we investigate the role of Arabidopsis lamin analogs CROWDED NUCLEIs during gametophyte and seed development. We observed defects in crwn mutant seeds, including seed abortion and reduced germination rate. Quadruple crwn null genotypes were rarely transmitted through gametophytes. We focused on the crwn1 crwn2 (crwn1/2) endosperm, which exhibited enlarged chalazal cysts and increased expression of stress-related genes and the MADS-box transcription factor PHERES1 and its targets. Previously, it was shown that PHERES1 is regulated by H3K27me3 and that CRWN1 interacts with the PRC2 interactor PWO1. Thus, we tested whether crwn1/2 alters H3K27me3 patterns. We observed a mild loss of H3K27me3 at several hundred loci, which differed between endosperm and leaves. These data indicate that CRWNs are necessary to maintain the H3K27me3 landscape, with tissue-specific chromatin and transcriptional consequences.

Decoding Human Biology and Disease Using Single-cell Omics Technologies

Over the past decade, advances in single-cell omics (SCO) technologies have enabled the investigation of cellular heterogeneity at an unprecedented resolution and scale, opening a new avenue for understanding human biology and disease. In this review, we summarize the developments of sequencing-based SCO technologies and computational methods, and focus on considerable insights acquired from SCO sequencing studies to understand normal and diseased properties, with a particular emphasis on cancer research. We also discuss the technological improvements of SCO and its possible contribution to fundamental research of the human, as well as its great potential in clinical diagnoses and personalized therapies of human disease.

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.

Understanding virus-host interactions in tissues

Although virus-host interactions are usually studied in a single cell type using in vitro assays in immortalized cell lines or isolated cell populations, it is important to remember that what is happening inside one infected cell does not translate to understanding how an infected cell behaves in a tissue, organ or whole organism. Infections occur in complex tissue environments, which contain a host of factors that can alter the course of the infection, including immune cells, non-immune cells and extracellular-matrix components. These factors affect how the host responds to the virus and form the basis of the protective response. To understand virus infection, tools are needed that can profile the tissue environment. This Review highlights methods to study virus-host interactions in the infection microenvironment.

Single-cell technologies in multiple myeloma: new insights into disease pathogenesis and translational implications

Multiple myeloma (MM) is a hematological malignancy characterized by clonal proliferation of plasma cells. Although therapeutic advances have been made to improve clinical outcomes and to prolong patients' survival in the past two decades, MM remains largely incurable. Single-cell sequencing (SCS) is a powerful method to dissect the cellular and molecular landscape at single-cell resolution, instead of providing averaged results. The application of single-cell technologies promises to address outstanding questions in myeloma biology and has revolutionized our understanding of the inter- and intra-tumor heterogeneity, tumor microenvironment, and mechanisms of therapeutic resistance in MM. In this review, we summarize the recently developed SCS methodologies and latest MM research progress achieved by single-cell profiling, including information regarding the cancer and immune cell landscapes, tumor heterogeneities, underlying mechanisms and biomarkers associated with therapeutic response and resistance. We also discuss future directions of applying transformative SCS approaches with contribution to clinical translation.

Methods for mapping 3D-chromosome architecture around nucleoli

The nucleolus is the largest subcompartment of the nucleus, known to be the place of ribosome biogenesis. Emerging evidence has started to implicate the nucleolus in the organization of chromosomes in the nucleus. Genomic domains contacting the nucleolus are defined as nucleolar associated domains (NADs) and are generally characterized by repressive chromatin states. However, the role of the nucleolus in genome architecture remains still not fully understood mainly because the lack of a membrane has challenged the establishment of methods for accurate identification of NADs. Here, we will discuss recent advances on methods to identify and characterize NADs, discuss their improvements relative to old methods, and highlight future perspectives.

Single-Cell Molecular Barcoding to Decode Multimodal Information Defining Cell States

Single-cell research has provided a breakthrough in biology to understand heterogeneous cell groups, such as tissues and organs, in development and disease. Molecular barcoding and subsequent sequencing technology insert a singlecell barcode into isolated single cells, allowing separation cell by cell. Given that multimodal information from a cell defines precise cellular states, recent technical advances in methods focus on simultaneously extracting multimodal data recorded in different biological materials (DNA, RNA, protein, etc.). This review summarizes recently developed singlecell multiomics approaches regarding genome, epigenome, and protein profiles with the transcriptome. In particular, we focus on how to anchor or tag molecules from a cell, improve throughputs with sample multiplexing, and record lineages, and we further discuss the future developments of the technology.

An atlas of lamina-associated chromatin across twelve human cell types reveals an intermediate chromatin subtype

BACKGROUND

Association of chromatin with lamin proteins at the nuclear periphery has emerged as a potential mechanism to coordinate cell type-specific gene expression and maintain cellular identity via gene silencing. Unlike many histone modifications and chromatin-associated proteins, lamina-associated domains (LADs) are mapped genome-wide in relatively few genetically normal human cell types, which limits our understanding of the role peripheral chromatin plays in development and disease.

RESULTS

To address this gap, we map LAMIN B1 occupancy across twelve human cell types encompassing pluripotent stem cells, intermediate progenitors, and differentiated cells from all three germ layers. Integrative analyses of this atlas with gene expression and repressive histone modification maps reveal that lamina-associated chromatin in all twelve cell types is organized into at least two subtypes defined by differences in LAMIN B1 occupancy, gene expression, chromatin accessibility, transposable elements, replication timing, and radial positioning. Imaging of fluorescently labeled DNA in single cells validates these subtypes and shows radial positioning of LADs with higher LAMIN B1 occupancy and heterochromatic histone modifications primarily embedded within the lamina. In contrast, the second subtype of lamina-associated chromatin is relatively gene dense, accessible, dynamic across development, and positioned adjacent to the lamina. Most genes gain or lose LAMIN B1 occupancy consistent with cell types along developmental trajectories; however, we also identify examples where the enhancer, but not the gene body and promoter, changes LAD state.

CONCLUSIONS

Altogether, this atlas represents the largest resource to date for peripheral chromatin organization studies and reveals an intermediate chromatin subtype.

Multimodal chromatin profiling using nanobody-based single-cell CUT&Tag

Probing histone modifications at a single-cell level in thousands of cells has been enabled by technologies such as single-cell CUT&Tag. Here we describe nano-CUT&Tag (nano-CT), which allows simultaneous mapping of up to three epigenomic modalities at single-cell resolution using nanobody-Tn5 fusion proteins. Multimodal nano-CT is compatible with starting materials as low as 25,000–200,000 cells and has significantly higher sensitivity and number of fragments per cell than single-cell CUT&Tag. We use nano-CT to simultaneously profile chromatin accessibility, H3K27ac, and H3K27me3 in juvenile mouse brain, allowing for discrimination of more cell types and states than unimodal single-cell CUT&Tag. We also infer chromatin velocity between assay for transposase-accessible chromatin (ATAC) and H3K27ac in the oligodendrocyte lineage and deconvolute H3K27me3 repressive states, finding two sequential waves of H3K27me3 repression at distinct gene modules during oligodendrocyte lineage progression. Given its high resolution, versatility, and multimodal features, nano-CT allows unique insights in epigenetic landscapes in complex biological systems at the single-cell level.

Integrating Micro and Nano Technologies for Cell Engineering and Analysis: Toward the Next Generation of Cell Therapy Workflows

The emerging field of cell therapy offers the potential to treat and even cure a diverse array of diseases for which existing interventions are inadequate. Recent advances in micro and nanotechnology have added a multitude of single cell analysis methods to our research repertoire. At the same time, techniques have been developed for the precise engineering and manipulation of cells. Together, these methods have aided the understanding of disease pathophysiology, helped formulate corrective interventions at the cellular level, and expanded the spectrum of available cell therapeutic options. This review discusses how micro and nanotechnology have catalyzed the development of cell sorting, cellular engineering, and single cell analysis technologies, which have become essential workflow components in developing cell-based therapeutics. The review focuses on the technologies adopted in research studies and explores the opportunities and challenges in combining the various elements of cell engineering and single cell analysis into the next generation of integrated and automated platforms that can accelerate preclinical studies and translational research.

ISSAAC-seq enables sensitive and flexible multimodal profiling of chromatin accessibility and gene expression in single cells

Joint profiling of chromatin accessibility and gene expression from the same single cell provides critical information about cell types in a tissue and cell states during a dynamic process. Here, we develop in situ sequencing hetero RNA-DNA-hybrid after assay for transposase-accessible chromatin-sequencing (ISSAAC-seq), a highly sensitive and flexible single-cell multi-omics method to interrogate chromatin accessibility and gene expression from the same single nucleus. We demonstrated that ISSAAC-seq is sensitive and provides high quality data with orders of magnitude more features than existing methods. Using the joint profiles from over 10,000 nuclei from the mouse cerebral cortex, we uncovered major and rare cell types and cell-type specific regulatory elements and identified heterogeneity at the chromatin level within established cell types defined by gene expression. Finally, we revealed distinct dynamics and relationships of gene expression and chromatin accessibility during an oligodendrocyte maturation trajectory.

D2 Plot, a Matrix of DNA Density and Distance to Periphery, Reveals Functional Genome Regions

The execution of biological activities inside space-limited cell nuclei requires sophisticated organization. Current studies on the 3D genome focus on chromatin interactions and local structures, e.g., topologically associating domains (TADs). In this study, two global physical properties: DNA density and distance to nuclear periphery (DisTP), are introduced and a 2D matrix, D² plot, is constructed for mapping genetic and epigenetic markers. Distinct patterns of functional markers on the D² plot, indicating its ability to compartmentalize functional genome regions, are observed. Furthermore, enrichments of transcription-related markers are concatenated into a cross-species transcriptional activation model, where the nucleus is divided into four areas: active, intermediate, repress and histone, and repress and repeat. Based on the trajectories of the genomic regions on D² plot, the constantly active and newly activated genes are successfully identified during olfactory sensory neuron maturation. The analysis reveals that the D² plot effectively categorizes functional regions and provides a universal and transcription-related measurement for the 3D genome.

Measuring transcription factor binding and gene expression using barcoded self-reporting transposon calling cards and transcriptomes

Calling cards technology using self-reporting transposons enables the identification of DNA-protein interactions through RNA sequencing. Although immensely powerful, current implementations of calling cards in bulk experiments on populations of cells are technically cumbersome and require many replicates to identify independent insertions into the same genomic locus. Here, we have drastically reduced the cost and labor requirements of calling card experiments in bulk populations of cells by introducing a DNA barcode into the calling card itself. An additional barcode incorporated during reverse transcription enables simultaneous transcriptome measurement in a facile and affordable protocol. We demonstrate that barcoded self-reporting transposons recover in vitro binding sites for four basic helix-loop-helix transcription factors with important roles in cell fate specification: ASCL1, MYOD1, NEUROD2 and NGN1. Further, simultaneous calling cards and transcriptional profiling during transcription factor overexpression identified both binding sites and gene expression changes for two of these factors. Lastly, we demonstrated barcoded calling cards can record binding in vivo in the mouse brain. In sum, RNA-based identification of transcription factor binding sites and gene expression through barcoded self-reporting transposon calling cards and transcriptomes is an efficient and powerful method to infer gene regulatory networks in a population of cells.

Single cell cancer epigenetics

Bulk sequencing methodologies have allowed us to make great progress in cancer research. Unfortunately, these techniques lack the resolution to fully unravel the epigenetic mechanisms that govern tumor heterogeneity. Consequently, many novel single cell-sequencing methodologies have been developed over the past decade, allowing us to explore the epigenetic components that regulate different aspects of cancer heterogeneity, namely: clonal heterogeneity, tumor microenvironment (TME), spatial organization, intratumoral differentiation programs, metastasis, and resistance mechanisms. In this review, we explore the different sequencing techniques that enable researchers to study different aspects of epigenetics (DNA methylation, chromatin accessibility, histone modifications, DNA-protein interactions, and chromatin 3D architecture) at the single cell level, their potential applications in cancer, and their current technical limitations.

scPCOR-seq enables co-profiling of chromatin occupancy and RNAs in single cells

Cell-to-cell variation in gene expression is a widespread phenomenon, which may play important roles in cellular differentiation, function, and disease development^1–9. Chromatin is implicated in contributing to the cellular heterogeneity in gene expression^10–16. Fully understanding the mechanisms of cellular heterogeneity requires simultaneous measurement of RNA and occupancy of histone modifications and transcription factors on chromatin due to their critical roles in transcriptional regulation^17,18. We generally term the occupancy of histone modifications and transcription factors as Chromatin occupancy. Here, we report a technique, termed scPCOR-seq (single-cell Profiling of Chromatin Occupancy and RNAs Sequencing), for simultaneously profiling genome-wide chromatin protein binding or histone modification marks and RNA expression in the same cell. We demonstrated that scPCOR-seq can profile either H3K4me3 or RNAPII and RNAs in a mixture of human H1, GM12878 and 293 T cells at a single-cell resolution and either H3K4me3, RNAPII, or RNA profile can correctly separate the cells. Application of scPCOR-seq to the in vitro differentiation of the erythrocyte precursor CD36 cells from human CD34 stem or progenitor cells revealed that H3K4me3 and RNA exhibit distinct properties in clustering cells during differentiation. Overall, our work provides a promising approach to understand the relationships among different omics layers.

scPCOR-seq is a single-cell sequencing technique that enables simultaneous profiling of genome-wide chromatin protein binding or histone modification marks and RNA expression in the same cell.

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.

Multiomic chromatin and transcription profiling with EpiDamID

DamID maps protein-genome interactions using DNA adenine methyltransferase tethered to individual chromatin proteins. In a recent issue of Molecluar Cell, Rang et al. introduce EpiDamID, a powerful extension of DamID suitable for mapping histone marks while simultaneously measuring mRNA levels in single cells.

Single-cell profiling of transcriptome and histone modifications with EpiDamID

Recent advances in single-cell sequencing technologies have enabled simultaneous measurement of multiple cellular modalities, but the combined detection of histone post-translational modifications and transcription at single-cell resolution has remained limited. Here, we introduce EpiDamID, an experimental approach to target a diverse set of chromatin types by leveraging the binding specificities of single-chain variable fragment antibodies, engineered chromatin reader domains, and endogenous chromatin-binding proteins. Using these, we render the DamID technology compatible with the genome-wide identification of histone post-translational modifications. Importantly, this includes the possibility to jointly measure chromatin marks and transcription at the single-cell level. We use EpiDamID to profile single-cell Polycomb occupancy in mouse embryoid bodies and provide evidence for hierarchical gene regulatory networks. In addition, we map H3K9me3 in early zebrafish embryogenesis, and detect striking heterochromatic regions specific to notochord. Overall, EpiDamID is a new addition to a vast toolbox to study chromatin states during dynamic cellular processes.

Single-Cell Multiomics Techniques: From Conception to Applications

Recent advances in methods for single-cell analyses and barcoding strategies have led to considerable progress in research. The development of multiplexed assays offers the possibility to conduct parallel analyses of multiple factors and processes for comprehensive characterization of cellular and molecular states in health and disease. These technologies have expanded extremely rapidly in the past years and constantly evolve and provide better specificity, precision and resolution. This review summarizes recent progress in single-cell multiomics approaches, and focuses, in particular, on the most innovative techniques that integrate genome, epigenome and transcriptome profiling. It describes the methodologies, discusses their advantages and limitations, and explains how they have been applied to studies on cell heterogeneity and differentiation, and epigenetic reprogramming.

The Intriguing Landscape of Single-Cell Protein Analysis

Profiling protein expression at single-cell resolution is essential for fundamental biological research (such as cell differentiation and tumor microenvironmental examination) and clinical precision medicine where only a limited number of primary cells are permitted. With the recent advances in engineering, chemistry, and biology, single-cell protein analysis methods are developed rapidly, which enable high-throughput and multiplexed protein measurements in thousands of individual cells. In combination with single cell RNA sequencing and mass spectrometry, single-cell multi-omics analysis can simultaneously measure multiple modalities including mRNAs, proteins, and metabolites in single cells, and obtain a more comprehensive exploration of cellular signaling processes, such as DNA modifications, chromatin accessibility, protein abundance, and gene perturbation. Here, the recent progress and applications of single-cell protein analysis technologies in the last decade are summarized. Current limitations, challenges, and possible future directions in this field are also discussed.

Single-cell RNA sequencing technologies and applications: A brief overview

Single-cell RNA sequencing (scRNA-seq) technology has become the state-of-the-art approach for unravelling the heterogeneity and complexity of RNA transcripts within individual cells, as well as revealing the composition of different cell types and functions within highly organized tissues/organs/organisms. Since its first discovery in 2009, studies based on scRNA-seq provide massive information across different fields making exciting new discoveries in better understanding the composition and interaction of cells within humans, model animals and plants. In this review, we provide a concise overview about the scRNA-seq technology, experimental and computational procedures for transforming the biological and molecular processes into computational and statistical data. We also provide an explanation of the key technological steps in implementing the technology. We highlight a few examples on how scRNA-seq can provide unique information for better understanding health and diseases. One important application of the scRNA-seq technology is to build a better and high-resolution catalogue of cells in all living organism, commonly known as atlas, which is key resource to better understand and provide a solution in treating diseases. While great promises have been demonstrated with the technology in all areas, we further highlight a few remaining challenges to be overcome and its great potentials in transforming current protocols in disease diagnosis and treatment.

Simultaneous Quantification of Spatial Genome Positioning and Transcriptomics in Single Cells with scDam&T-Seq

Spatial genome organization is considered to play an important role in mammalian cells, by guiding gene expression programs and supporting lineage specification. Yet it is still an outstanding question in the field what the direct impact of spatial genome organization on gene expression is. To elucidate this relationship further, we have recently developed scDam&T-seq, a method that simultaneously quantifies protein-DNA interactions and transcriptomes in single cells. This method efficiently combines two preexisting methods: DamID for measuring protein-DNA contacts and CEL-Seq2 for quantification of the transcriptome in single cells. scDam&T-seq has been successfully applied to measure DNA contacts with the nuclear lamina, while at the same time revealing the effect of these contacts on gene expression. This method is applicable to many different proteins of interest and can thereby aid in studying the relationship between protein-DNA interactions and gene expression in single cells.

Integrated single-cell sequencing of 5-hydroxymethylcytosine and genomic DNA using scH&G-seq

The asymmetric distribution of 5-hydroxymethylcytosine (5hmC) between two DNA strands of a chromosome enables endogenous reconstruction of cellular lineages at an individual-cell-division resolution. Further, when integrated with data on genomic variants to infer clonal lineages, this combinatorial information accurately reconstructs larger lineage trees. Here, we provide a detailed protocol for single-cell 5-hydroxymethylcytosine and genomic DNA sequencing (scH&G-seq) to simultaneously quantify 5hmC and genomic DNA from the same cell to reconstruct lineage trees at a single-cell-division resolution.

For complete details on the use and execution of this protocol, please refer to Wangsanuwat et al., 2021.

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scH&G-seq enables quantification of 5hmC and genomic DNA (gDNA) from the same cell

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Strand-specific 5hmC enables reconstructing trees at a single-cell-division resolution

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Genomic variants allow identification of clonal subtrees within a lineage tree

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Integrated 5hmC and gDNA detection improves prediction accuracy of larger lineage trees

High-throughput single-cell epigenomic profiling by targeted insertion of promoters (TIP-seq)

Chromatin profiling in single cells has been extremely challenging and almost exclusively limited to histone proteins. In cases where single-cell methods have shown promise, many require highly specialized equipment or cell type-specific protocols and are relatively low throughput. Here, we combine the advantages of tagmentation, linear amplification, and combinatorial indexing to produce a high-throughput single-cell DNA binding site mapping method that is simple, inexpensive, and capable of multiplexing several independent samples per experiment. Targeted insertion of promoters sequencing (TIP-seq) uses Tn5 fused to proteinA to insert a T7 RNA polymerase promoter adjacent to a chromatin protein of interest. Linear amplification of flanking DNA with T7 polymerase before sequencing library preparation provides ∼10-fold higher unique reads per single cell compared with other methods. We applied TIP-seq to map histone modifications, RNA polymerase II (RNAPII), and transcription factor CTCF binding sites in single human and mouse cells.

Evaluating microglial phenotypes using single-cell technologies

Recent single-cell technologies have enabled researchers to simultaneously assess the transcriptomes and other modalities of thousands of cells within their spatial context. Here, we have summarized available single-cell methods for dissociated tissues and tissue slides with respect to the specifics of microglial biology. We have focused on next-generation-based technologies. We review the potential of these single-cell sequencing methods and newer multiomics approaches to extend the understanding of microglia function beyond the status quo.

Single-Cell Genomics: Catalyst for Cell Fate Engineering

As we near a complete catalog of mammalian cell types, the capability to engineer specific cell types on demand would transform biomedical research and regenerative medicine. However, the current pace of discovering new cell types far outstrips our ability to engineer them. One attractive strategy for cellular engineering is direct reprogramming, where induction of specific transcription factor (TF) cocktails orchestrates cell state transitions. Here, we review the foundational studies of TF-mediated reprogramming in the context of a general framework for cell fate engineering, which consists of: discovering new reprogramming cocktails, assessing engineered cells, and revealing molecular mechanisms. Traditional bulk reprogramming methods established a strong foundation for TF-mediated reprogramming, but were limited by their small scale and difficulty resolving cellular heterogeneity. Recently, single-cell technologies have overcome these challenges to rapidly accelerate progress in cell fate engineering. In the next decade, we anticipate that these tools will enable unprecedented control of cell state.

Tissue-specific DamID protocol using nanopore sequencing

DNA adenine methylation identification (DamID) is a powerful method to determine DNA binding profiles of proteins at a genomic scale. The method leverages the fusion between a protein of interest and the Dam methyltransferase of E. coli, which methylates proximal DNA in vivo. Here, we present an optimized procedure, which was developed for tissue-specific analyses in Caenorhabditis elegans and successfully used to footprint genes actively transcribed by RNA polymerases and to map transcription factor binding in gene regulatory regions. The present protocol details C. elegans-specific steps involved in the preparation of transgenic lines and genomic DNA samples, as well as broadly applicable steps for the DamID procedure, including the isolation of methylated DNA fragments, the preparation of multiplexed libraries, Nanopore sequencing, and data analysis. Two distinctive features of the approach are (i) the use of an efficient recombination-based strategy to selectively analyze rare cell types and (ii) the use of Nanopore sequencing, which streamlines the process. The method allows researchers to go from genomic DNA samples to sequencing results in less than a week, while being sensitive enough to report reliable DNA footprints in cell types as rare as 2 cells per animal.

Understanding the pathogenesis of infectious diseases by single-cell RNA sequencing

Infections are highly orchestrated and dynamic processes, which involve both pathogen and host. Transcriptional profiling at the single-cell level enables the analysis of cell diversity, heterogeneity of the immune response, and detailed molecular mechanisms underlying infectious diseases caused by bacteria, viruses, fungi, and parasites. Herein, we highlight recent remarkable advances in single-cell RNA sequencing (scRNA-seq) technologies and their applications in the investigation of host-pathogen interactions, current challenges and potential prospects for disease treatment are discussed as well. We propose that with the aid of scRNA-seq, the mechanism of infectious diseases will be further revealed thus inspiring the development of novel interventions and therapies.

A probabilistic framework for cellular lineage reconstruction using integrated single-cell 5-hydroxymethylcytosine and genomic DNA sequencing

Lineage reconstruction is central to understanding tissue development and maintenance. To overcome the limitations of current techniques that typically reconstruct clonal trees using genetically encoded reporters, we report scPECLR, a probabilistic algorithm to endogenously infer lineage trees at a single-cell-division resolution by using 5-hydroxymethylcytosine (5hmC). When applied to 8-cell pre-implantation mouse embryos, scPECLR predicts the full lineage tree with greater than 95% accuracy. In addition, we developed scH&G-seq to sequence both 5hmC and genomic DNA from the same cell. Given that genomic DNA sequencing yields information on both copy number variations and single-nucleotide polymorphisms, when combined with scPECLR it enables more accurate lineage reconstruction of larger trees. Finally, we show that scPECLR can also be used to map chromosome strand segregation patterns during cell division, thereby providing a strategy to test the "immortal strand" hypothesis. Thus, scPECLR provides a generalized method to endogenously reconstruct lineage trees at an individual-cell-division resolution.

Understanding 3D genome organization by multidisciplinary methods

Understanding how chromatin is folded in the nucleus is fundamental to understanding its function. Although 3D genome organization has been historically difficult to study owing to a lack of relevant methodologies, major technological breakthroughs in genome-wide mapping of chromatin contacts and advances in imaging technologies in the twenty-first century considerably improved our understanding of chromosome conformation and nuclear architecture. In this Review, we discuss methods of 3D genome organization analysis, including sequencing-based techniques, such as Hi-C and its derivatives, Micro-C, DamID and others; microscopy-based techniques, such as super-resolution imaging coupled with fluorescence in situ hybridization (FISH), multiplex FISH, in situ genome sequencing and live microscopy methods; and computational and modelling approaches. We describe the most commonly used techniques and their contribution to our current knowledge of nuclear architecture and, finally, we provide a perspective on up-and-coming methods that open possibilities for future major discoveries.

Recent advance in single-cell epigenomics

The analysis of gene expression regulation, or the epigenome analysis, at the single-cell level is at the forefront of genomics research. To elucidate the mechanisms that regulate gene expression, chromatin immunoprecipitation has been conventionally used for determining the binding sites of DNA-binding proteins, such as histones and transcription factors. Now several new approaches have been emerged to reveal epigenome states at the single-cell level. Instead of using immunoprecipitation of fragmented chromatin, in situ reactions using cells or nuclei, combining with transposase tagging and other methods, have enabled single-cell analysis. Furthermore, single-cell multiomics techniques to simultaneously profiling transcriptome and open chromatin or histone modification have been developed. These single-cell analyses have the potential to identify different cell types in a cell population and reveal the dynamic changes of gene regulation, although those technologies have not yet reached a level for general application.

Chromatin Profiling Techniques: Exploring the Chromatin Environment and Its Contributions to Complex Traits

The genetic architecture of complex traits is multifactorial. Genome-wide association studies (GWASs) have identified risk loci for complex traits and diseases that are disproportionately located at the non-coding regions of the genome. On the other hand, we have just begun to understand the regulatory roles of the non-coding genome, making it challenging to precisely interpret the functions of non-coding variants associated with complex diseases. Additionally, the epigenome plays an active role in mediating cellular responses to fluctuations of sensory or environmental stimuli. However, it remains unclear how exactly non-coding elements associate with epigenetic modifications to regulate gene expression changes and mediate phenotypic outcomes. Therefore, finer interrogations of the human epigenomic landscape in associating with non-coding variants are warranted. Recently, chromatin-profiling techniques have vastly improved our understanding of the numerous functions mediated by the epigenome and DNA structure. Here, we review various chromatin-profiling techniques, such as assays of chromatin accessibility, nucleosome distribution, histone modifications, and chromatin topology, and discuss their applications in unraveling the brain epigenome and etiology of complex traits at tissue homogenate and single-cell resolution. These techniques have elucidated compositional and structural organizing principles of the chromatin environment. Taken together, we believe that high-resolution epigenomic and DNA structure profiling will be one of the best ways to elucidate how non-coding genetic variations impact complex diseases, ultimately allowing us to pinpoint cell-type targets with therapeutic potential.

Dopamine Neuron Diversity: Recent Advances and Current Challenges in Human Stem Cell Models and Single Cell Sequencing

Human midbrain dopamine (DA) neurons are a heterogeneous group of cells that share a common neurotransmitter phenotype and are in close anatomical proximity but display different functions, sensitivity to degeneration, and axonal innervation targets. The A9 DA neuron subtype controls motor function and is primarily degenerated in Parkinson’s disease (PD), whereas A10 neurons are largely unaffected by the condition, and their dysfunction is associated with neuropsychiatric disorders. Currently, DA neurons can only be reliably classified on the basis of topographical features, including anatomical location in the midbrain and projection targets in the forebrain. No systematic molecular classification at the genome-wide level has been proposed to date. Although many years of scientific efforts in embryonic and adult mouse brain have positioned us to better understand the complexity of DA neuron biology, many biological phenomena specific to humans are not amenable to being reproduced in animal models. The establishment of human cell-based systems combined with advanced computational single-cell transcriptomics holds great promise for decoding the mechanisms underlying maturation and diversification of human DA neurons, and linking their molecular heterogeneity to functions in the midbrain. Human pluripotent stem cells have emerged as a useful tool to recapitulate key molecular features of mature DA neuron subtypes. Here, we review some of the most recent advances and discuss the current challenges in using stem cells, to model human DA biology. We also describe how single cell RNA sequencing may provide key insights into the molecular programs driving DA progenitor specification into mature DA neuron subtypes. Exploiting the state-of-the-art approaches will lead to a better understanding of stem cell-derived DA neurons and their use in disease modeling and regenerative medicine.

Single-cell joint detection of chromatin occupancy and transcriptome enables higher-dimensional epigenomic reconstructions

Deciphering mechanisms in cell-fate decisions requires single-cell holistic reconstructions of multidimensional epigenomic states in transcriptional regulation. Here we develop CoTECH, a combinatorial barcoding method allowing high-throughput single-cell joint detection of chromatin occupancy and transcriptome. We used CoTECH to examine bivalent histone marks (H3K4me3 and H3K27me3) with transcription from naive to primed mouse embryonic stem cells. We also derived concurrent bivalent marks in pseudosingle cells using transcriptome as an anchor for resolving pseudotemporal bivalency trajectories and disentangling a context-specific interplay between H3K4me3/H3K27me3 and transcription level. Next, we revealed the regulatory basis of endothelial-to-hematopoietic transition in two waves of hematopoietic cells and distinctive enhancer-gene-linking schemes guiding hemogenic endothelial cell emergence, indicating a unique epigenetic control of transcriptional regulation for hematopoietic stem cell priming. CoTECH provides an efficient framework for single-cell coassay of chromatin occupancy and transcription, thus enabling higher-dimensional epigenomic reconstructions.

Endocrine Pancreas Development and Dysfunction Through the Lens of Single-Cell RNA-Sequencing

A chronic inability to maintain blood glucose homeostasis leads to diabetes, which can damage multiple organs. The pancreatic islets regulate blood glucose levels through the coordinated action of islet cell-secreted hormones, with the insulin released by β-cells playing a crucial role in this process. Diabetes is caused by insufficient insulin secretion due to β-cell loss, or a pancreatic dysfunction. The restoration of a functional β-cell mass might, therefore, offer a cure. To this end, major efforts are underway to generate human β-cells de novo, in vitro, or in vivo. The efficient generation of functional β-cells requires a comprehensive knowledge of pancreas development, including the mechanisms driving cell fate decisions or endocrine cell maturation. Rapid progress in single-cell RNA sequencing (scRNA-Seq) technologies has brought a new dimension to pancreas development research. These methods can capture the transcriptomes of thousands of individual cells, including rare cell types, subtypes, and transient states. With such massive datasets, it is possible to infer the developmental trajectories of cell transitions and gene regulatory pathways. Here, we summarize recent advances in our understanding of endocrine pancreas development and function from scRNA-Seq studies on developing and adult pancreas and human endocrine differentiation models. We also discuss recent scRNA-Seq findings for the pathological pancreas in diabetes, and their implications for better treatment.

Strand-specific single-cell methylomics reveals distinct modes of DNA demethylation dynamics during early mammalian development

DNA methylation (5mC) is central to cellular identity. The global erasure of 5mC from the parental genomes during preimplantation mammalian development is critical to reset the methylome of gametes to the cells in the blastocyst. While active and passive modes of demethylation have both been suggested to play a role in this process, the relative contribution of these two mechanisms to 5mC erasure remains unclear. Here, we report a single-cell method (scMspJI-seq) that enables strand-specific quantification of 5mC, allowing us to systematically probe the dynamics of global demethylation. When applied to mouse embryonic stem cells, we identified substantial cell-to-cell strand-specific 5mC heterogeneity, with a small group of cells displaying asymmetric levels of 5mCpG between the two DNA strands of a chromosome suggesting loss of maintenance methylation. Next, in preimplantation mouse embryos, we discovered that methylation maintenance is active till the 16-cell stage followed by passive demethylation in a fraction of cells within the early blastocyst at the 32-cell stage of development. Finally, human preimplantation embryos qualitatively show temporally delayed yet similar demethylation dynamics as mouse embryos. Collectively, these results demonstrate that scMspJI-seq is a sensitive and cost-effective method to map the strand-specific genome-wide patterns of 5mC in single cells.

Genome-in-a-Box: Building a Chromosome from the Bottom Up

Chromosome structure and dynamics are essential for life, as the way that our genomes are spatially organized within cells is crucial for gene expression, differentiation, and genome transfer to daughter cells. There is a wide variety of methods available to study chromosomes, ranging from live-cell studies to single-molecule biophysics, which we briefly review. While these technologies have yielded a wealth of data, such studies still leave a significant gap between top-down experiments on live cells and bottom-up in vitro single-molecule studies of DNA-protein interactions. Here, we introduce "genome-in-a-box" (GenBox) as an alternative in vitro approach to build and study chromosomes, which bridges this gap. The concept is to assemble a chromosome from the bottom up by taking deproteinated genome-sized DNA isolated from live cells and subsequently add purified DNA-organizing elements, followed by encapsulation in cell-sized containers using microfluidics. Grounded in the rationale of synthetic cell research, the approach would enable to experimentally study emergent effects at the global genome level that arise from the collective action of local DNA-structuring elements. We review the various DNA-structuring elements present in nature, from nucleoid-associated proteins and SMC complexes to phase separation and macromolecular crowders. Finally, we discuss how GenBox can contribute to several open questions on chromosome structure and dynamics.

Single-cell genomics to understand disease pathogenesis

Cells are minimal functional units in biological phenomena, and therefore single-cell analysis is needed to understand the molecular behavior leading to cellular function in organisms. In addition, omics analysis technology can be used to identify essential molecular mechanisms in an unbiased manner. Recently, single-cell genomics has unveiled hidden molecular systems leading to disease pathogenesis in patients. In this review, I summarize the recent advances in single-cell genomics for the understanding of disease pathogenesis and discuss future perspectives.

Attach and stretch: Emerging roles for genome-lamina contacts in shaping the 3D genome

A large proportion of the metazoan genome is spatially segregated at the nuclear periphery through genomic contacts with the nuclear lamina, a thin meshwork of lamin filaments that lines the inner-nuclear membrane. Lamina-associated domains are believed to contribute to the regulation of gene transcription and to provide structural three-dimensional support to the organization of the genome in A and B compartments and topologically associating domains. In this review, we will evaluate recent work addressing the role of lamina-associated domains in three-dimensional genome organization and propose experimental frameworks that may expand our understanding of their interdependence.

Applications of Single-Cell Omics to Dissect Tumor Microenvironment

The recent technical and computational advances in single-cell sequencing technologies have significantly broaden our toolkit to study tumor microenvironment (TME) directly from human specimens. The TME is the complex and dynamic ecosystem composed of multiple cell types, including tumor cells, immune cells, stromal cells, endothelial cells, and other non-cellular components such as the extracellular matrix and secreted signaling molecules. The great success on immune checkpoint blockade therapy has highlighted the importance of TME on anti-tumor immunity and has made it a prime target for further immunotherapy strategies. Applications of single-cell transcriptomics on studying TME has yielded unprecedented resolution of the cellular and molecular complexity of the TME, accelerating our understanding of the heterogeneity, plasticity, and complex cross-interaction between different cell types within the TME. In this review, we discuss the recent advances by single-cell sequencing on understanding the diversity of TME and its functional impact on tumor progression and immunotherapy response driven by single-cell sequencing. We primarily focus on the major immune cell types infiltrated in the human TME, including T cells, dendritic cells, and macrophages. We further discuss the limitations of the existing methodologies and the prospects on future studies utilizing single-cell multi-omics technologies. Since immune cells undergo continuous activation and differentiation within the TME in response to various environmental cues, we highlight the importance of integrating multimodal datasets to enable retrospective lineage tracing and epigenetic profiling of the tumor infiltrating immune cells. These novel technologies enable better characterization of the developmental lineages and differentiation states that are critical for the understanding of the underlying mechanisms driving the functional diversity of immune cells within the TME. We envision that with the continued accumulation of single-cell omics datasets, single-cell sequencing will become an indispensable aspect of the immune-oncology experimental toolkit. It will continue to drive the scientific innovations in precision immunotherapy and will be ultimately adopted by routine clinical practice in the foreseeable future.

Novel orthogonal methods to uncover the complexity and diversity of nuclear architecture

Recent years have seen a vast expansion of knowledge on three-dimensional (3D) genome organization. The majority of studies on chromosome topology consists of pairwise interaction data of bulk populations of cells and therefore conceals heterogenic and more complex folding patterns. Here, we discuss novel methodologies to study the variation in genome topologies between different cells and techniques that allow analysis of complex, multi-way interactions. These technologies will aid the interpretation of genome-wide chromosome conformation data and provide strategies to further dissect the interplay between genome architecture and transcription regulation.