A Single-Cell Atlas of In Vivo Mammalian Chromatin Accessibility

scBasset: sequence-based modeling of single-cell ATAC-seq using convolutional neural networks

Single-cell assay for transposase-accessible chromatin using sequencing (scATAC) shows great promise for studying cellular heterogeneity in epigenetic landscapes, but there remain important challenges in the analysis of scATAC data due to the inherent high dimensionality and sparsity. Here we introduce scBasset, a sequence-based convolutional neural network method to model scATAC data. We show that by leveraging the DNA sequence information underlying accessibility peaks and the expressiveness of a neural network model, scBasset achieves state-of-the-art performance across a variety of tasks on scATAC and single-cell multiome datasets, including cell clustering, scATAC profile denoising, data integration across assays and transcription factor activity inference.

Blocking CHOP-dependent TXNIP shuttling to mitochondria attenuates albuminuria and mitigates kidney injury in nephrotic syndrome

Albuminuria is a hallmark of glomerular disease of various etiologies. It is not only a symptom of glomerular disease but also a cause leading to glomerulosclerosis, interstitial fibrosis, and eventually, a decline in kidney function. The molecular mechanism underlying albuminuria-induced kidney injury remains poorly defined. In our genetic model of nephrotic syndrome (NS), we have identified CHOP (C/EBP homologous protein)-TXNIP (thioredoxin-interacting protein) as critical molecular linkers between albuminuria-induced ER dysfunction and mitochondria dyshomeostasis. TXNIP is a ubiquitously expressed redox protein that binds to and inhibits antioxidant enzyme, cytosolic thioredoxin 1 (Trx1), and mitochondrial Trx2. However, very little is known about the regulation and function of TXNIP in NS. By utilizing Chop-/- and Txnip-/- mice as well as 68Ga-Galuminox, our molecular imaging probe for detection of mitochondrial reactive oxygen species (ROS) in vivo, we demonstrate that CHOP up-regulation induced by albuminuria drives TXNIP shuttling from nucleus to mitochondria, where it is required for the induction of mitochondrial ROS. The increased ROS accumulation in mitochondria oxidizes Trx2, thus liberating TXNIP to associate with mitochondrial nod-like receptor protein 3 (NLRP3) to activate inflammasome, as well as releasing mitochondrial apoptosis signal-regulating kinase 1 (ASK1) to induce mitochondria-dependent apoptosis. Importantly, inhibition of TXNIP translocation and mitochondrial ROS overproduction by CHOP deletion suppresses NLRP3 inflammasome activation and p-ASK1-dependent mitochondria apoptosis in NS. Thus, targeting TXNIP represents a promising therapeutic strategy for the treatment of NS.

Epigenetic perspectives of COVID-19: Virus infection to disease progression and therapeutic control

COVID-19 has caused numerous deaths as well as imposed social isolation and upheaval world-wide. Although, the genome and the composition of the virus, the entry process and replication mechanisms are well investigated from by several laboratories across the world, there are many unknown remaining questions. For example, what are the functions of membrane lipids during entry, packaging and exit of virus particles? Also, the metabolic aspects of the infected tissue cells are poorly understood. In the course of virus replication and formation of virus particles within the host cell, the enhanced metabolic activities of the host is directly proportional to viral loads. The epigenetic landscape of the host cells is also altered, particularly the expression/repression of genes associated with cellular metabolism as well as cellular processes that are antagonistic to the virus. Metabolic pathways are enzyme driven processes and the expression profile and mechanism of regulations of the respective genes encoding those enzymes during the course of pathogen invasion might be highly informative on the course of the disease. Recently, the metabolic profile of the patients' sera have been analysed from few patients. In view of this, and to gain further insights into the roles that epigenetic mechanisms might play in this scenario in regulation of metabolic pathways during the progression of COVID-19 are discussed and summarised in this contribution for ensuring best therapy.

Toxicoepigenetics and Environmental Health: Challenges and Opportunities

The rapidly growing field of toxicoepigenetics seeks to understand how toxicant exposures interact with the epigenome to influence disease risk. Toxicoepigenetics is a promising field of environmental health research, as integrating epigenetics into the field of toxicology will enable a more thorough evaluation of toxicant-induced disease mechanisms as well as the elucidation of the role of the epigenome as a biomarker of exposure and disease and possible mediator of exposure effects. Likewise, toxicoepigenetics will enhance our knowledge of how environmental exposures, lifestyle factors, and diet interact to influence health. Ultimately, an understanding of how the environment impacts the epigenome to cause disease may inform risk assessment, permit noninvasive biomonitoring, and provide potential opportunities for therapeutic intervention. However, the translation of research from this exciting field into benefits for human and animal health presents several challenges and opportunities. Here, we describe four significant areas in which we see opportunity to transform the field and improve human health by reducing the disease burden caused by environmental exposures. These include (1) research into the mechanistic role for epigenetic change in environment-induced disease, (2) understanding key factors influencing vulnerability to the adverse effects of environmental exposures, (3) identifying appropriate biomarkers of environmental exposures and their associated diseases, and (4) determining whether the adverse effects of environment on the epigenome and human health are reversible through pharmacologic, dietary, or behavioral interventions. We then highlight several initiatives currently underway to address these challenges.

Narrative engineering of the liver

Liver organoids are primary or pluripotent stem cell-derived three-dimensional structures that recapitulate regenerative or ontogenetic processes in vitro towards biomedical applications including disease modelling and diagnostics, drug safety and efficacy prediction, and therapeutic use. The cellular composition and structural organization of liver organoids may vary depending on the goal at hand, and the key challenge in general is to direct their development in a rational and controlled fashion for gaining targeted maturity, reproducibility, and scalability. Such endeavor begins with a detailed understanding of the biological processes in space and time behind hepatogenesis, followed by precise translation of these narrative processes through a bioengineering approach. Here, we discuss advancements in liver organoid technology through the lens of 'narrative engineering' in an attempt to synergize evolving understanding around molecular and cellular landscape governing hepatogenesis with engineering-inspired approaches for organoidgenesis.

Temporally divergent regulatory mechanisms govern neuronal diversification and maturation in the mouse and marmoset neocortex

Mammalian neocortical neurons span one of the most diverse cell type spectra of any tissue. Cortical neurons are born during embryonic development, and their maturation extends into postnatal life. The regulatory strategies underlying progressive neuronal development and maturation remain unclear. Here we present an integrated single-cell epigenomic and transcriptional analysis of individual mouse and marmoset cortical neuron classes, spanning both early postmitotic stages of identity acquisition and later stages of neuronal plasticity and circuit integration. We found that, in both species, the regulatory strategies controlling early and late stages of pan-neuronal development diverge. Early postmitotic neurons use more widely shared and evolutionarily conserved molecular regulatory programs. In contrast, programs active during later neuronal maturation are more brain- and neuron-specific and more evolutionarily divergent. Our work uncovers a temporal shift in regulatory choices during neuronal diversification and maturation in both mice and marmosets, which likely reflects unique evolutionary constraints on distinct events of neuronal development in the neocortex.

Analyzing the gene regulatory network in hepatitis B patients by single-cell ATAC sequencing

OBJECTIVE

This study aims to provide a new perspective of determining the pathophysiology of chronic hepatitis B (CHB) development by analyzing the gene regulatory network in CHB patients using single-cell ATAC sequencing.

BACKGROUND

Hepatitis B virus (HBV)-related liver disease induces liver damage by hepatic immune and inflammatory responses. The exact mechanism is unknown. As such, there is an urgent need to address this problem and study the relationship between aberrant peripheral blood mononuclear cell (PBMC) immune response and progression of liver disease.

METHOD

The sequencing of the chromatin accessibility of 8016 cells from the whole venous blood of normal control (NC) individuals and CHB patients was performed through assay for transposase-accessible chromatin in single-cell sequencing (ScATAC-seq). Unsupervised clustering and annotation analyses were performed by Signac (version 1.7.0) and Seurat clustering to identify different cell types. Then, TF motif enrichment analysis and differentially expressed peak analysis were performed to identify cell-type-specific candidate open chromatins related to CHB.

RESULT

We identified 12 leukocytic clusters corresponding to five cell types. The specific cell types associated with CHB were found to be located in B-0 and T-3. We have drawn the regulatory network of the hepatitis B signal pathway composed of genes linked to the differentially expressed peaks of these two CHB disease-specific cell types. Further, we profoundly explored the potential mechanisms of B-0-associated TF motif IRF2 and T-3-associated TF motif FOXC2 in the occurrence of CHB.

CONCLUSION

We have drawn a systematic and distinguishing gene regulatory network of CHB-related PBMCs. Key Points • Peripheral blood mononuclear cells were robustly clustered based on their types without using antibodies. • We draw a systematic and distinctive gene regulatory network of CHB-related PBMC through ScATAC-seq.

What is a cell type and how to define it?

Cell types are the basic functional units of an organism. Cell types exhibit diverse phenotypic properties at multiple levels, making them challenging to define, categorize, and understand. This review provides an overview of the basic principles of cell types rooted in evolution and development and discusses approaches to characterize and classify cell types and investigate how they contribute to the organism's function, using the mammalian brain as a primary example. I propose a roadmap toward a conceptual framework and knowledge base of cell types that will enable a deeper understanding of the dynamic changes of cellular function under healthy and diseased conditions.

Single-cell multiomics analysis reveals regulatory programs in clear cell renal cell carcinoma

The clear cell renal cell carcinoma (ccRCC) microenvironment consists of many different cell types and structural components that play critical roles in cancer progression and drug resistance, but the cellular architecture and underlying gene regulatory features of ccRCC have not been fully characterized. Here, we applied single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) to generate transcriptional and epigenomic landscapes of ccRCC. We identified tumor cell-specific regulatory programs mediated by four key transcription factors (TFs) (HOXC5, VENTX, ISL1, and OTP), and these TFs have prognostic significance in The Cancer Genome Atlas (TCGA) database. Targeting these TFs via short hairpin RNAs (shRNAs) or small molecule inhibitors decreased tumor cell proliferation. We next performed an integrative analysis of chromatin accessibility and gene expression for CD8⁺ T cells and macrophages to reveal the different regulatory elements in their subgroups. Furthermore, we delineated the intercellular communications mediated by ligand–receptor interactions within the tumor microenvironment. Taken together, our multiomics approach further clarifies the cellular heterogeneity of ccRCC and identifies potential therapeutic targets.

Age and diet shape the genetic architecture of body weight in diversity outbred mice

Understanding how genetic variation shapes a complex trait relies on accurately quantifying both the additive genetic and genotype–environment interaction effects in an age-dependent manner. We used a linear mixed model to quantify diet-dependent genetic contributions to body weight measured through adulthood in diversity outbred female mice under five diets. We observed that heritability of body weight declined with age under all diets, except the 40% calorie restriction diet. We identified 14 loci with age-dependent associations and 19 loci with age- and diet-dependent associations, with many diet-dependent loci previously linked to neurological function and behavior in mice or humans. We found their allelic effects to be dynamic with respect to genomic background, age, and diet, identifying several loci where distinct alleles affect body weight at different ages. These results enable us to more fully understand and predict the effectiveness of dietary intervention on overall health throughout age in distinct genetic backgrounds.

Body weight is one trait influenced by genes, age and environmental factors. Both internal and external environmental pressures are known to affect genetic variation over time. However, it is largely unknown how all factors – including age – interact to shape metabolism and bodyweight.

Wright et al. set out to quantify the interactions between genes and diet in ageing mice and found that the effect of genetics on mouse body weight changes with age. In the experiments, Wright et al. weighed 960 female mice with diverse genetic backgrounds, starting at two months of age into adulthood. The animals were randomized to different diets at six months of age. Some mice had unlimited food access, others received 20% or 40% less calories than a typical mouse diet, and some fasted one or two days per week.

Variations in their genetic background explained about 80% of differences in mice’s weight, but the influence of genetics relative to non-genetic factors decreased as they aged. Mice on the 40% calorie restriction diet were an exception to this rule and genetics accounted for 80% of their weight throughout adulthood, likely due to reduced influence from diet and reduced interactions between diet and genes. Several genes involved in metabolism, neurological function, or behavior, were associated with mouse weight.

The experiments highlight the importance of considering interactions between genetics, environment, and age in determining complex traits like body weight. The results and the approaches used by Wright et al. may help other scientists learn more about how the genetic predisposition to disease changes with environmental stimuli and age.

Epigenetic Memories in Hematopoietic Stem and Progenitor Cells

The recent development of next-generation sequencing (NGS) technologies has contributed to research into various biological processes. These novel NGS technologies have revealed the involvement of epigenetic memories in trained immunity, which are responses to transient stimulation and result in better responses to secondary challenges. Not only innate system cells, such as macrophages, monocytes, and natural killer cells, but also bone marrow hematopoietic stem cells (HSCs) have been found to gain memories upon transient stimulation, leading to the enhancement of responses to secondary challenges. Various stimuli, including microbial infection, can induce the epigenetic reprogramming of innate immune cells and HSCs, which can result in an augmented response to secondary stimulation. In this review, we introduce novel NGS technologies and their application to unraveling epigenetic memories that are key in trained immunity and summarize the recent findings in trained immunity. We also discuss our most recent finding regarding epigenetic memory in aged HSCs, which may be associated with the exposure of HSCs to aging-related stresses.

Pro-inflammatory cytokines mediate the epithelial-to-mesenchymal-like transition of pediatric posterior fossa ependymoma

Pediatric ependymoma is a devastating brain cancer marked by its relapsing pattern and lack of effective chemotherapies. This shortage of treatments is due to limited knowledge about ependymoma tumorigenic mechanisms. By means of single-nucleus chromatin accessibility and gene expression profiling of posterior fossa primary tumors and distal metastases, we reveal key transcription factors and enhancers associated with the differentiation of ependymoma tumor cells into tumor-derived cell lineages and their transition into a mesenchymal-like state. We identify NFκB, AP-1, and MYC as mediators of this transition, and show that the gene expression profiles of tumor cells and infiltrating microglia are consistent with abundant pro-inflammatory signaling between these populations. In line with these results, both TGF-β1 and TNF-α induce the expression of mesenchymal genes on a patient-derived cell model, and TGF-β1 leads to an invasive phenotype. Altogether, these data suggest that tumor gliosis induced by inflammatory cytokines and oxidative stress underlies the mesenchymal phenotype of posterior fossa ependymoma.

A single-cell map of dynamic chromatin landscapes of immune cells in renal cell carcinoma

A complete chart of the chromatin regulatory elements of immune cells in patients with cancer and their dynamic behavior is necessary to understand the developmental fates and guide therapeutic strategies. Here, we map the single-cell chromatin landscape of immune cells from blood, normal tumor-adjacent kidney tissue and malignant tissue from patients with early-stage clear cell renal cell carcinoma (ccRCC). We catalog the T cell states dictated by tissue-specific and developmental-stage-specific chromatin accessibility patterns, infer key chromatin regulators and observe rewiring of regulatory networks in the progression to dysfunction in CD8⁺ T cells. Unexpectedly, among the transcription factors orchestrating the path to dysfunction, NF-κB is associated with a pro-apoptotic program in late stages of dysfunction in tumor-infiltrating CD8⁺ T cells. Importantly, this epigenomic profiling stratified ccRCC patients based on a NF-κB-driven pro-apoptotic signature. This study provides a rich resource for understanding the functional states and regulatory dynamics of immune cells in ccRCC.

Systematic identification of cell-fate regulatory programs using a single-cell atlas of mouse development

Waddington's epigenetic landscape is a metaphor frequently used to illustrate cell differentiation. Recent advances in single-cell genomics are altering our understanding of the Waddington landscape, yet the molecular mechanisms of cell-fate decisions remain poorly understood. We constructed a cell landscape of mouse lineage differentiation during development at the single-cell level and described both lineage-common and lineage-specific regulatory programs during cell-type maturation. We also found lineage-common regulatory programs that are broadly active during the development of invertebrates and vertebrates. In particular, we identified Xbp1 as an evolutionarily conserved regulator of cell-fate determinations across different species. We demonstrated that Xbp1 transcriptional regulation is important for the stabilization of the gene-regulatory networks for a wide range of mouse cell types. Our results offer genetic and molecular insights into cellular gene-regulatory programs and will serve as a basis for further advancing the understanding of cell-fate decisions.

Single-Cell Chromatin and Gene-Regulatory Dynamics of Mouse Nephron Progenitors

BACKGROUND

We reasoned that unraveling the dynamic changes in accessibility of genomic regulatory elements and gene expression at single-cell resolution will inform the basic mechanisms of nephrogenesis.

METHODS

We performed single-cell ATAC-seq and RNA-seq both individually (singleomes; Six2GFP cells) and jointly in the same cells (multiomes; kidneys) to generate integrated chromatin and transcriptional maps in mouse embryonic and neonatal nephron progenitor cells.

RESULTS

We demonstrate that singleomes and multiomes are comparable in assigning most cell states, identification of new cell type markers, and defining the transcription factors driving cell identity. However, multiomes are more precise in defining the progenitor population. Multiomes identified a "pioneer" bHLH/Fox motif signature in nephron progenitor cells. Moreover, we identified a subset of Fox factors exhibiting high chromatin activity in podocytes. One of these Fox factors, Foxp1, is important for nephrogenesis. Key nephrogenic factors are distinguished by strong correlation between linked gene regulatory elements and gene expression.

CONCLUSION

Mapping the regulatory landscape at single-cell resolution informs the regulatory hierarchy of nephrogenesis. Paired single-cell epigenomes and transcriptomes of nephron progenitors should provide a foundation to understand prenatal programming, regeneration after injury, and ex vivo nephrogenesis.

Single-cell roadmap of human gonadal development

Gonadal development is a complex process that involves sex determination followed by divergent maturation into either testes or ovaries1. Historically, limited tissue accessibility, a lack of reliable in vitro models and critical differences between humans and mice have hampered our knowledge of human gonadogenesis, despite its importance in gonadal conditions and infertility. Here, we generated a comprehensive map of first- and second-trimester human gonads using a combination of single-cell and spatial transcriptomics, chromatin accessibility assays and fluorescent microscopy. We extracted human-specific regulatory programmes that control the development of germline and somatic cell lineages by profiling equivalent developmental stages in mice. In both species, we define the somatic cell states present at the time of sex specification, including the bipotent early supporting population that, in males, upregulates the testis-determining factor SRY and sPAX8s, a gonadal lineage located at the gonadal-mesonephric interface. In females, we resolve the cellular and molecular events that give rise to the first and second waves of granulosa cells that compartmentalize the developing ovary to modulate germ cell differentiation. In males, we identify human SIGLEC15+ and TREM2+ fetal testicular macrophages, which signal to somatic cells outside and inside the developing testis cords, respectively. This study provides a comprehensive spatiotemporal map of human and mouse gonadal differentiation, which can guide in vitro gonadogenesis.

Kidney Development: Recent Insights from Technological Advances

The kidney is a complex organ, and how it forms is a fascinating process. New technologies, such as single-cell transcriptomics, and enhanced imaging modalities are offering new approaches to understand the complex and intertwined processes during embryonic kidney development.

Single-cell multi-omics sequencing and its applications in studying the nervous system

Single-cell sequencing has become one of the most powerful and popular techniques in dissecting molecular heterogeneity and modeling the cellular architecture of a biological system. During the past twenty years, the throughput of single-cell sequencing has increased from hundreds of cells to over tens of thousands of cells in parallel. Moreover, this technology has been developed from sequencing transcriptome to measure different omics such as DNA methylome, chromatin accessibility, and so on. Currently, multi-omics which can analyze different omics in the same cell is rapidly advancing. This work advances the study of many biosystems, including the nervous system. Here, we review current single-cell multi-omics sequencing techniques and describe how they improve our understanding of the nervous system. Finally, we discuss the open scientific questions in neural research that may be answered through further improvement of single-cell multi-omics sequencing technology.

The Art of Reprogramming for Regenerative Medicine

Traditional pharmaceuticals in the forms of small chemical compounds or macromolecules such as proteins or RNAs have provided lifesaving solutions to many acute and chronic conditions to date. However, there are still many unmet medical needs, especially those of degenerative nature. The advent of cell-based therapy holds the promise to meet these challenges. In this review, we highlight a relatively new paradigm for generating or regenerating functional cells for replacement therapy against conditions such as type I diabetes, myocardial infarction, neurodegenerative diseases and liver fibrosis. We focus on the latest progresses in cellular reprogramming for generating diverse functional cell types. We will also discuss the mechanisms involved and conclude with likely general principles underlying reprogramming.

scDART: integrating unmatched scRNA-seq and scATAC-seq data and learning cross-modality relationship simultaneously

It is a challenging task to integrate scRNA-seq and scATAC-seq data obtained from different batches. Existing methods tend to use a pre-defined gene activity matrix to convert the scATAC-seq data into scRNA-seq data. The pre-defined gene activity matrix is often of low quality and does not reflect the dataset-specific relationship between the two data modalities. We propose scDART, a deep learning framework that integrates scRNA-seq and scATAC-seq data and learns cross-modalities relationships simultaneously. Specifically, the design of scDART allows it to preserve cell trajectories in continuous cell populations and can be applied to trajectory inference on integrated data.

SCRaPL: A Bayesian hierarchical framework for detecting technical associates in single cell multiomics data

Single-cell multi-omics assays offer unprecedented opportunities to explore epigenetic regulation at cellular level. However, high levels of technical noise and data sparsity frequently lead to a lack of statistical power in correlative analyses, identifying very few, if any, significant associations between different molecular layers. Here we propose SCRaPL, a novel computational tool that increases power by carefully modelling noise in the experimental systems. We show on real and simulated multi-omics single-cell data sets that SCRaPL achieves higher sensitivity and better robustness in identifying correlations, while maintaining a similar level of false positives as standard analyses based on Pearson and Spearman correlation.

A map of bat virus receptors derived from single-cell multiomics

Bats are considered reservoirs of many lethal zoonotic viruses and have been implicated in several outbreaks of emerging infectious diseases, such as SARS-CoV, MERS-CoV, and SARS-CoV-2. It is necessary to systematically derive the expression patterns of bat virus receptors and their regulatory features for future research into bat-borne viruses and the prediction and prevention of pandemics. Here, we performed single-nucleus RNA sequencing (snRNA-seq) and single-nucleus assay for transposase-accessible chromatin using sequencing (snATAC-seq) of major organ samples collected from Chinese horseshoe bats (Rhinolophus affinis) and systematically checked the expression pattern of bat-related virus receptors and chromatin accessibility across organs and cell types, providing a valuable dataset for studying the nature of infection among bat-borne viruses.

Remodeling of gene regulatory networks underlying thermogenic stimuli-induced adipose beiging

Beige adipocytes are induced by cold temperatures or β3-adrenergic receptor (Adrb3) agonists. They create heat through glucose and fatty acid (FA) oxidation, conferring metabolic benefits. The distinct and shared mechanisms by which these treatments induce beiging are unknown. Here, we perform single-nucleus assay for transposase-accessible chromatin sequencing (snATAC-seq) on adipose tissue from mice exposed to cold or an Adrb3 agonist to identify cellular and chromatin accessibility dynamics during beiging. Both stimuli induce chromatin remodeling that influence vascularization and inflammation in adipose. Beige adipocytes from cold-exposed mice have increased accessibility at genes regulating glycolytic processes, whereas Adrb3 activation increases cAMP responses. While both thermogenic stimuli increase accessibility at genes regulating thermogenesis, lipogenesis, and beige adipocyte development, the kinetics and magnitudes of the changes are distinct for the stimuli. Accessibility changes at lipogenic genes are linked to functional changes in lipid composition of adipose. Both stimuli tend to decrease the proportion of palmitic acids, a saturated FA in adipose. However, Adrb3 activation increases the proportion of monounsaturated FAs, whereas cold increases the proportion of polyunsaturated FAs. These findings reveal common and distinct mechanisms of cold and Adrb3 induced beige adipocyte biogenesis, and identify unique functional consequences of manipulating these pathways in vivo.

Advances in Single-Cell Multi-Omics and Application in Cardiovascular Research

With the development of ever more powerful and versatile high-throughput sequencing techniques and innovative ways to capture single cells, mapping the multicellular tissues at the single-cell level is becoming routine practice. However, it is still challenging to depict the epigenetic landscape of a single cell, especially the genome-wide chromatin accessibility, histone modifications, and DNA methylation. We summarize the most recent methodologies to profile these epigenetic marks at the single-cell level. We also discuss the development and advancement of several multi-omics sequencing technologies from individual cells. Advantages and limitations of various methods to compare and integrate datasets obtained from different sources are also included with specific practical notes. Understanding the heart tissue at single-cell resolution and multi-modal levels will help to elucidate the cell types and states involved in physiological and pathological events during heart development and disease. The rich information produced from single-cell multi-omics studies will also promote the research of heart regeneration and precision medicine on heart diseases.

Haematopoiesis in Zebrafish (Danio Rerio)

Haematopoiesis in fish and mammals is a complex process, and many aspects regarding its model and the differentiation of haematopoietic stem cells (HSCs) still remain enigmatic despite advanced studies. The effects of microenvironmental factors or HSCs niche and signalling pathways on haematopoiesis are also unclear. This review presents Danio rerio as a model organism for studies on haematopoiesis in vertebrates and discusses the development of this process during the embryonic period and in adult fish. It describes the role of the microenvironment of the haematopoietic process in regulating the formation and function of HSCs/HSPCs (hematopoietic stem/progenitor cells) and highlights facts and research areas important for haematopoiesis in fish and mammals.

Human and mouse trigeminal ganglia cell atlas implicates multiple cell types in migraine

Sensitization of trigeminal ganglion neurons contributes to primary headache disorders such as migraine, but the specific neuronal and non-neuronal trigeminal subtypes that are involved remain unclear. We thus developed a cell atlas in which human and mouse trigeminal ganglia are transcriptionally and epigenomically profiled at single-cell resolution. These data describe evolutionarily conserved and human-specific gene expression patterns within each trigeminal ganglion cell type, as well as the transcription factors and gene regulatory elements that contribute to cell-type-specific gene expression. We then leveraged these data to identify trigeminal ganglion cell types that are implicated both by human genetic variation associated with migraine and two mouse models of headache. This trigeminal ganglion cell atlas improves our understanding of the cell types, genes, and epigenomic features involved in headache pathophysiology and establishes a rich resource of cell-type-specific molecular features to guide the development of more selective treatments for headache and facial pain.

Decoding Expression Dynamics of Protein and Transcriptome at the Single-Cell Level in Paired Picoliter Chambers

Simultaneous analysis of mRNAs and proteins at the single-cell level provides information about the dynamics and correlations of gene and protein expressions in individual cells, enabling a comprehensive study of cellular heterogeneity and expression patterns. Here, we present a platform for about 1000 cellular indexing of mRNAs and membrane proteins, named multi-Paired-seq, with high cell utilization, accurate molecular measurement, and low cost. Based on hydrodynamic differential flow resistance, multi-Paired-seq largely improves cell utilization in the percentage of cells measured in population (>95%). Combined with the pump/valve structure, cell-free antibodies and mRNAs can be removed completely for highly accurate detection (R = 0.96) of protein copies. The picoliter reaction chambers allow high detection sensitivity for both mRNA transcripts and protein copies and low sequencing cost. Using multi-Paired-seq, three clusters of known breast cancer cell types are identified according to multimodal measurements, and the expression correlations between mRNAs and proteins under altered conditions are quantified. Multi-Paired-seq provides multimodal measurements at the single-cell level, which offers a new tool for cell biology, developmental biology, drug discovery, and precision medicine.

Robust temporal map of human in vitro myelopoiesis using single-cell genomics

Myeloid cells are central to homeostasis and immunity. Characterising in vitro myelopoiesis protocols is imperative for their use in research, immunotherapies, and understanding human myelopoiesis. Here, we generate a >470K cells molecular map of human induced pluripotent stem cells (iPSC) differentiation into macrophages. Integration with in vivo single-cell atlases shows in vitro differentiation recapitulates features of yolk sac hematopoiesis, before definitive hematopoietic stem cells (HSC) emerge. The diversity of myeloid cells generated, including mast cells and monocytes, suggests that HSC-independent hematopoiesis can produce multiple myeloid lineages. We uncover poorly described myeloid progenitors and conservation between in vivo and in vitro regulatory programs. Additionally, we develop a protocol to produce iPSC-derived dendritic cells (DC) resembling cDC2. Using CRISPR/Cas9 knock-outs, we validate the effects of key transcription factors in macrophage and DC ontogeny. This roadmap of myeloid differentiation is an important resource for investigating human fetal hematopoiesis and new therapeutic opportunities.

Breaking the Immune Complexity of the Tumor Microenvironment Using Single-Cell Technologies

Tumors are not a simple aggregate of transformed cells but rather a complicated ecosystem containing various components, including infiltrating immune cells, tumor-related stromal cells, endothelial cells, soluble factors, and extracellular matrix proteins. Profiling the immune contexture of this intricate framework is now mandatory to develop more effective cancer therapies and precise immunotherapeutic approaches by identifying exact targets or predictive biomarkers, respectively. Conventional technologies are limited in reaching this goal because they lack high resolution. Recent developments in single-cell technologies, such as single-cell RNA transcriptomics, mass cytometry, and multiparameter immunofluorescence, have revolutionized the cancer immunology field, capturing the heterogeneity of tumor-infiltrating immune cells and the dynamic complexity of tenets that regulate cell networks in the tumor microenvironment. In this review, we describe some of the current single-cell technologies and computational techniques applied for immune-profiling the cancer landscape and discuss future directions of how integrating multi-omics data can guide a new "precision oncology" advancement.

Bi-order multimodal integration of single-cell data

Integration of single-cell multiomics profiles generated by different single-cell technologies from the same biological sample is still challenging. Previous approaches based on shared features have only provided approximate solutions. Here, we present a novel mathematical solution named bi-order canonical correlation analysis (bi-CCA), which extends the widely used CCA approach to iteratively align the rows and the columns between data matrices. Bi-CCA is generally applicable to combinations of any two single-cell modalities. Validations using co-assayed ground truth data and application to a CAR-NK study and a fetal muscle atlas demonstrate its capability in generating accurate multimodal co-embeddings and discovering cellular identity.

Epigenetic Regulation of Endothelial Cell Lineages During Zebrafish Development-New Insights From Technical Advances

Epigenetic regulation is integral in orchestrating the spatiotemporal regulation of gene expression which underlies tissue development. The emergence of new tools to assess genome-wide epigenetic modifications has enabled significant advances in the field of vascular biology in zebrafish. Zebrafish represents a powerful model to investigate the activity of cis-regulatory elements in vivo by combining technologies such as ATAC-seq, ChIP-seq and CUT&Tag with the generation of transgenic lines and live imaging to validate the activity of these regulatory elements. Recently, this approach led to the identification and characterization of key enhancers of important vascular genes, such as gata2a, notch1b and dll4. In this review we will discuss how the latest technologies in epigenetics are being used in the zebrafish to determine chromatin states and assess the function of the cis-regulatory sequences that shape the zebrafish vascular network.

High-throughput single-сell sequencing in cancer research

With advances in sequencing and instrument technology, bioinformatics analysis is being applied to batches of massive cells at single-cell resolution. High-throughput single-cell sequencing can be utilized for multi-omics characterization of tumor cells, stromal cells or infiltrated immune cells to evaluate tumor progression, responses to environmental perturbations, heterogeneous composition of the tumor microenvironment, and complex intercellular interactions between these factors. Particularly, single-cell sequencing of T cell receptors, alone or in combination with single-cell RNA sequencing, is useful in the fields of tumor immunology and immunotherapy. Clinical insights obtained from single-cell analysis are critically important for exploring the biomarkers of disease progression or antitumor treatment, as well as for guiding precise clinical decision-making for patients with malignant tumors. In this review, we summarize the clinical applications of single-cell sequencing in the fields of tumor cell evolution, tumor immunology, and tumor immunotherapy. Additionally, we analyze the tumor cell response to antitumor treatment, heterogeneity of the tumor microenvironment, and response or resistance to immune checkpoint immunotherapy. The limitations of single-cell analysis in cancer research are also discussed.

Discovery and functional assessment of a novel adipocyte population driven by intracellular Wnt/β-catenin signaling in mammals

Wnt/β-catenin signaling has been well established as a potent inhibitor of adipogenesis. Here, we identified a population of adipocytes that exhibit persistent activity of Wnt/β-catenin signaling, as revealed by the Tcf/Lef-GFP reporter allele, in embryonic and adult mouse fat depots, named as Wnt⁺ adipocytes. We showed that this β-catenin-mediated signaling activation in these cells is Wnt ligand- and receptor-independent but relies on AKT/mTOR pathway and is essential for cell survival. Such adipocytes are distinct from classical ones in transcriptomic and genomic signatures and can be induced from various sources of mesenchymal stromal cells including human cells. Genetic lineage-tracing and targeted cell ablation studies revealed that these adipocytes convert into beige adipocytes directly and are also required for beige fat recruitment under thermal challenge, demonstrating both cell autonomous and non-cell autonomous roles in adaptive thermogenesis. Furthermore, mice bearing targeted ablation of these adipocytes exhibited glucose intolerance, while mice receiving exogenously supplied such cells manifested enhanced glucose utilization. Our studies uncover a unique adipocyte population in regulating beiging in adipose tissues and systemic glucose homeostasis.

WashU Epigenome Browser update 2022

WashU Epigenome Browser (https://epigenomegateway.wustl.edu/browser/) is a web-based genomic data exploration tool that provides visualization, integration, and analysis of epigenomic datasets. The newly renovated user interface and functions have enabled researchers to engage with the browser and genomic data more efficiently and effectively since 2018. Here, we introduce a new integrated panel design in the browser that allows users to interact with 1D (genomic features), 2D (such as Hi-C), 3D (genome structure), and 4D (time series) data in a single web page. The browser can display three-dimensional chromatin structures with the 3D viewer module. The 4D tracks, called ‘Dynamic’ tracks, animatedly display time-series data, allowing for a more striking visual impact to identify the gene or genomic region candidates as a function of time. Genomic data, such as annotation features, numerical values, and chromatin interaction data can all be viewed in the dynamic track mode. Imaging data from microscopy experiments can also be displayed in the browser. In addition to software development, we continue to service and expand the data hubs we host for large consortia including 4DN, Roadmap Epigenomics, TaRGET and ENCODE, among others. Our growing user/developer community developed additional track types as plugins, such as qBed and dynseq tracks, which extend the utility of the browser. The browser serves as a foundation for additional genomics platforms including the WashU Virus Genome Browser (for COVID-19 research) and the Comparative Genome Browser. The WashU Epigenome Browser can also be accessed freely through Amazon Web Services at https://epigenomegateway.org/.

H3K9 trimethylation in active chromatin restricts the usage of functional CTCF sites in SINE B2 repeats

Here, Gualdrini et al. found that loss of H3K9me3 caused by SETDB1 depletion was associated with increased recruitment of CTCF to >1600 DNA binding motifs contained within SINE B2 repeats, a previously unidentified target of SETDB1-mediated repression. Their findings suggest a role for H3K9me3 in restraining genomic distribution and activity of CTCF, influencing chromatin organization and gene regulation.

Six methyltransferases divide labor in establishing genomic profiles of histone H3 lysine 9 methylation (H3K9me), an epigenomic modification controlling constitutive heterochromatin, gene repression, and silencing of retroelements. Among them, SETDB1 is recruited to active chromatin domains to silence the expression of endogenous retroviruses. In the context of experiments aimed at determining the impact of SETDB1 on stimulus-inducible gene expression in macrophages, we found that loss of H3K9me3 caused by SETDB1 depletion was associated with increased recruitment of CTCF to >1600 DNA binding motifs contained within SINE B2 repeats, a previously unidentified target of SETDB1-mediated repression. CTCF is an essential regulator of chromatin folding that restrains DNA looping by cohesin, thus creating boundaries among adjacent topological domains. Increased CTCF binding to SINE B2 repeats enhanced insulation at hundreds of sites and increased loop formation within topological domains containing lipopolysaccharide-inducible genes, which correlated with their impaired regulation in response to stimulation. These data indicate a role of H3K9me3 in restraining genomic distribution and activity of CTCF, with an impact on chromatin organization and gene regulation.

Modelling the genetic aetiology of complex disease: human-mouse conservation of noncoding features and disease-associated loci

Understanding the genetic aetiology of loci associated with a disease is crucial for developing preventative measures and effective treatments. Mouse models are used extensively to understand human pathobiology and mechanistic functions of disease-associated loci. However, the utility of mouse models is limited in part by evolutionary divergence in transcription regulation for pathways of interest. Here, we summarize the alignment of genomic (exonic and multi-cell regulatory) annotations alongside Mendelian and complex disease-associated variant sites between humans and mice. Our results highlight the importance of understanding evolutionary divergence in transcription regulation when interpreting functional studies using mice as models for human disease variants.

Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer's disease: review, recommendation, implementation and application

Alzheimer's disease (AD) is the most common form of dementia, characterized by progressive cognitive impairment and neurodegeneration. Extensive clinical and genomic studies have revealed biomarkers, risk factors, pathways, and targets of AD in the past decade. However, the exact molecular basis of AD development and progression remains elusive. The emerging single-cell sequencing technology can potentially provide cell-level insights into the disease. Here we systematically review the state-of-the-art bioinformatics approaches to analyze single-cell sequencing data and their applications to AD in 14 major directions, including 1) quality control and normalization, 2) dimension reduction and feature extraction, 3) cell clustering analysis, 4) cell type inference and annotation, 5) differential expression, 6) trajectory inference, 7) copy number variation analysis, 8) integration of single-cell multi-omics, 9) epigenomic analysis, 10) gene network inference, 11) prioritization of cell subpopulations, 12) integrative analysis of human and mouse sc-RNA-seq data, 13) spatial transcriptomics, and 14) comparison of single cell AD mouse model studies and single cell human AD studies. We also address challenges in using human postmortem and mouse tissues and outline future developments in single cell sequencing data analysis. Importantly, we have implemented our recommended workflow for each major analytic direction and applied them to a large single nucleus RNA-sequencing (snRNA-seq) dataset in AD. Key analytic results are reported while the scripts and the data are shared with the research community through  GitHub. In summary, this comprehensive review provides insights into various approaches to analyze single cell sequencing data and offers specific guidelines for study design and a variety of analytic directions. The review and the accompanied software tools will serve as a valuable resource for studying cellular and molecular mechanisms of AD, other diseases, or biological systems at the single cell level.

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 cellular and molecular phenotyping of embryonic mutants using single-cell regulatory trajectories

Developmental progression and cellular diversity are largely driven by transcription factors (TFs); yet, characterizing their loss-of-function phenotypes remains challenging and often disconnected from their underlying molecular mechanisms. Here, we combine single-cell regulatory genomics with loss-of-function mutants to jointly assess both cellular and molecular phenotypes. Performing sci-ATAC-seq at eight overlapping time points during Drosophila mesoderm development could reconstruct the developmental trajectories of all major muscle types and reveal the TFs and enhancers involved. To systematically assess mutant phenotypes, we developed a single-nucleus genotyping strategy to process embryo pools of mixed genotypes. Applying this to four TF mutants could identify and quantify their characterized phenotypes de novo and discover new ones, while simultaneously revealing their regulatory input and mode of action. Our approach is a general framework to dissect the functional input of TFs in a systematic, unbiased manner, identifying both cellular and molecular phenotypes at a scale and resolution that has not been feasible before.

Deciphering the Retinal Epigenome during Development, Disease and Reprogramming: Advancements, Challenges and Perspectives

Retinal neurogenesis is driven by concerted actions of transcription factors, some of which are expressed in a continuum and across several cell subtypes throughout development. While seemingly redundant, many factors diversify their regulatory outcome on gene expression, by coordinating variations in chromatin landscapes to drive divergent retinal specification programs. Recent studies have furthered the understanding of the epigenetic contribution to the progression of age-related macular degeneration, a leading cause of blindness in the elderly. The knowledge of the epigenomic mechanisms that control the acquisition and stabilization of retinal cell fates and are evoked upon damage, holds the potential for the treatment of retinal degeneration. Herein, this review presents the state-of-the-art approaches to investigate the retinal epigenome during development, disease, and reprogramming. A pipeline is then reviewed to functionally interrogate the epigenetic and transcriptional networks underlying cell fate specification, relying on a truly unbiased screening of open chromatin states. The related work proposes an inferential model to identify gene regulatory networks, features the first footprinting analysis and the first tentative, systematic query of candidate pioneer factors in the retina ever conducted in any model organism, leading to the identification of previously uncharacterized master regulators of retinal cell identity, such as the nuclear factor I, NFI. This pipeline is virtually applicable to the study of genetic programs and candidate pioneer factors in any developmental context. Finally, challenges and limitations intrinsic to the current next-generation sequencing techniques are discussed, as well as recent advances in super-resolution imaging, enabling spatio-temporal resolution of the genome.

Simultaneous dimensionality reduction and integration for single-cell ATAC-seq data using deep learning

Advances in single-cell technologies enable the routine interrogation of chromatin accessibility for tens of thousands of single cells, elucidating gene regulatory processes at an unprecedented resolution. Meanwhile, size, sparsity and high dimensionality of the resulting data continue to pose challenges for its computational analysis, and specifically the integration of data from different sources. We have developed a dedicated computational approach: a variational auto-encoder using a noise model specifically designed for single-cell ATAC-seq (assay for transposase-accessible chromatin with high-throughput sequencing) data, which facilitates simultaneous dimensionality reduction and batch correction via an adversarial learning strategy. We showcase its benefits for detailed cell-type characterization on individual real and simulated datasets as well as for integrating multiple complex datasets.

Perspectives on Bulk-Tissue RNA Sequencing and Single-Cell RNA Sequencing for Cardiac Transcriptomics

The heart has been the center of numerous transcriptomic studies in the past decade. Even though our knowledge of the key organ in our cardiovascular system has significantly increased over the last years, it is still not fully understood yet. In recent years, extensive efforts were made to understand the genetic and transcriptomic contribution to cardiac function and failure in more detail. The advent of Next Generation Sequencing (NGS) technologies has brought many discoveries but it is unable to comprehend the finely orchestrated interactions between and within the various cell types of the heart. With the emergence of single-cell sequencing more than 10 years ago, researchers gained a valuable new tool to enable the exploration of new subpopulations of cells, cell-cell interactions, and integration of multi-omic approaches at a single-cell resolution. Despite this innovation, it is essential to make an informed choice regarding the appropriate technique for transcriptomic studies, especially when working with myocardial tissue. Here, we provide a primer for researchers interested in transcriptomics using NGS technologies.

Recent advances on single-cell sequencing technologies

Single-cell omics sequencing was first achieved for transcriptome in 2009, which was followed by fast development of technologies for profiling genome, DNA methylome, 3D genome architecture, chromatin accessibility, histone modifications and so on, in an individual cell. In this review we mainly focus on the recent progresses in four topics in single cell omics field- single-cell epigenome sequencing, single-cell genome sequencing for lineage tracing, spatially resolved single-cell transcriptomics, and third-generation sequencing platform-based single cell omics sequencing. We also discuss the potential applications and future directions of these single cell omics sequencing technologies for different biomedical systems, especially for the human stem cell field.

Single Cell Transcriptomic and Chromatin Profiles Suggest Layer Vb Is the Only Layer With Shared Excitatory Cell Types in the Medial and Lateral Entorhinal Cortex

All brain functionality arises from the activity in neural circuits in different anatomical regions. These regions contain different circuits comprising unique cell types. An integral part to understanding neural circuits is a full census of the constituent parts, i.e., the neural cell types. This census can be based on different characteristics. Previously combinations of morphology and physiology, gene expression, and chromatin accessibility have been used in various cortical and subcortical regions. This has given an extensive yet incomplete overview of neural cell types. However, these techniques have not been applied to all brain regions. Here we apply single cell analysis of accessible chromatin on two similar but different cortical regions, the medial and the lateral entorhinal cortices. Even though these two regions are anatomically similar, their intrinsic and extrinsic connectivity are different. In 4,136 cells we identify 20 different clusters representing different cell types. As expected, excitatory cells show regionally specific clusters, whereas inhibitory neurons are shared between regions. We find that several deep layer excitatory neuronal cell types as defined by chromatin profile are also shared between the two different regions. Integration with a larger scRNA-seq dataset maintains this shared characteristic for cells in Layer Vb. Interestingly, this layer contains three clusters, two specific to either subregion and one shared between the two. These clusters can be putatively associated with particular functional and anatomical cell types found in this layer. This information is a step forwards into elucidating the cell types within the entorhinal circuit and by extension its functional underpinnings.

FoxP3 associates with enhancer-promoter loops to regulate Treg-specific gene expression

Gene expression programs are specified by higher-order chromatin structure and enhancer-promoter loops (EPLs). T regulatory cell (Treg) identity is dominantly specified by the transcription factor (TF) FoxP3, whose mechanism of action is unclear. We applied chromatin conformation capture with immunoprecipitation (HiChIP) in Treg and closely related conventional CD4+ T cells (Tconv). EPLs identified by H3K27Ac HiChIP showed a range of connection intensity, with some superconnected genes. TF-specific HiChIP showed that FoxP3 interacts with EPLs at a large number of genes, including some not differentially expressed in Treg versus Tconv, but enriched at the core Treg signature loci that it up-regulates. FoxP3 association correlated with heightened H3K27Ac looping, as ascertained by analysis of FoxP3-deficient Treg-like cells. There was marked asymmetry in the loci where FoxP3 associated at the enhancer- or the promoter-side of EPLs, with enrichment for different transcriptional cofactors. FoxP3 EPL intensity distinguished gene clusters identified by single-cell ATAC-seq as covarying between individual Tregs, supporting a direct transactivation model for FoxP3 in determining Treg identity.

Single-cell-resolved dynamics of chromatin architecture delineate cell and regulatory states in zebrafish embryos

DNA accessibility of cis-regulatory elements (CREs) dictates transcriptional activity and drives cell differentiation during development. While many genes regulating embryonic development have been identified, the underlying CRE dynamics controlling their expression remain largely uncharacterized. To address this, we produced a multimodal resource and genomic regulatory map for the zebrafish community, which integrates single-cell combinatorial indexing assay for transposase-accessible chromatin with high-throughput sequencing (sci-ATAC-seq) with bulk histone PTMs and Hi-C data to achieve a genome-wide classification of the regulatory architecture determining transcriptional activity in the 24-h post-fertilization (hpf) embryo. We characterized the genome-wide chromatin architecture at bulk and single-cell resolution, applying sci-ATAC-seq on whole 24-hpf stage zebrafish embryos, generating accessibility profiles for ∼23,000 single nuclei. We developed a genome segmentation method, ScregSeg (single-cell regulatory landscape segmentation), for defining regulatory programs, and candidate CREs, specific to one or more cell types. We integrated the ScregSeg output with bulk measurements for histone post-translational modifications and 3D genome organization and identified new regulatory principles between chromatin modalities prevalent during zebrafish development. Sci-ATAC-seq profiling of npas4l/cloche mutant embryos identified novel cellular roles for this hematovascular transcriptional master regulator and suggests an intricate mechanism regulating its expression. Our work defines regulatory architecture and principles in the zebrafish embryo and establishes a resource of cell-type-specific genome-wide regulatory annotations and candidate CREs, providing a valuable open resource for genomics, developmental, molecular, and computational biology.