Comprehensive Identification and Spatial Mapping of Habenular Neuronal Types Using Single-Cell RNA-Seq

Spatial presentation of biological molecules to cells by localized diffusive transfer

Cellular decisions in human development, homeostasis, regeneration, and disease are coordinated in large part by signals that are spatially localized in tissues. These signals are often soluble, such that biomolecules produced by one cell diffuse to receiving cells. To recapitulate soluble factor patterning in vitro, several microscale strategies have been developed. However, these techniques often introduce new variables into cell culture experiments (e.g., fluid flow) or are limited in their ability to pattern diverse solutes in a user-defined manner. To address these challenges, we developed an adaptable method that facilitates spatial presentation of biomolecules across cells in traditional open cultures in vitro. This technique employs device inserts that are placed in standard culture wells, which support localized diffusive pattern transmission through microscale spaces between device features and adherent cells. Devices can be removed and cultures can be returned to standard media following patterning. We use this method to spatially control cell labeling with pattern features ranging in scale from several hundred microns to millimeters and with sequential application of multiple patterns. To better understand the method we investigate relationships between pattern fidelity, device geometry, and consumption and diffusion kinetics using finite element modeling. We then apply the method to spatially defining reporter cell heterogeneity by patterning a small molecule modulator of genetic recombination with the requisite sustained exposure. Finally, we demonstrate use of this method for patterning larger and more slowly diffusing particles by creating focal sites of gene delivery and infection with adenoviral, lentiviral, and Zika virus particles. Thus, our method leverages devices that interface with standard culture vessels to pattern diverse diffusible factors, geometries, exposure dynamics, and recipient cell types, making it well poised for adoption by researchers across various fields of biological research.

Single cell RNA-sequencing: replicability of cell types

Recent technical advances have enabled transcriptomics experiments at an unprecedented scale, and single-cell profiles from neural tissue are accumulating rapidly. There has been considerable effort to use these profiles to understand cell diversity, primarily through unsupervised clustering and differential expression analysis. However, current practices to validate these findings vary. In this review, we describe recent efforts to evaluate clusters from single-cell RNA-sequencing data, and provide a framework for considering current evidence and practices in terms of their capacity to establish principles of cell biology. Single-cell RNA-sequencing has already transformed neuroscience. By facilitating detailed comparative and genetic perturbation analyses, it may provide the tools to uncover fundamental mechanisms of neural diversity throughout the tree of life.

Advantages and Challenges of Cardiovascular and Lymphatic Studies in Zebrafish Research

Since its introduction, the zebrafish has provided an important reference system to model and study cardiovascular development as well as lymphangiogenesis in vertebrates. A scientific workshop, held at the 2018 European Zebrafish Principal Investigators Meeting in Trento (Italy) and chaired by Massimo Santoro, focused on the most recent methods and studies on cardiac, vascular and lymphatic development. Daniela Panáková and Natascia Tiso described new molecular mechanisms and signaling pathways involved in cardiac differentiation and disease. Arndt Siekmann and Wiebke Herzog discussed novel roles for Wnt and VEGF signaling in brain angiogenesis. In addition, Brant Weinstein's lab presented data concerning the discovery of endothelium-derived macrophage-like perivascular cells in the zebrafish brain, while Monica Beltrame's studies refined the role of Sox transcription factors in vascular and lymphatic development. In this article, we will summarize the details of these recent discoveries in support of the overall value of the zebrafish model system not only to study normal development, but also associated disease states.

[The roles of habenula and related neural circuits in neuropsychiatric diseases]

The habenula is a small and bilateral nucleus above dorsal thalamus, which contains several different types of neurons. The habenula has extensive connections with the forebrain, septum and monoaminergic nuclei in the midbrain and brainstem. Habenula is known as an 'anti-reward' nucleus, which can be activated by aversive stimulus and negative reward prediction errors. Accumulating researchs have implicated that the habenula is involved in several behaviors crucial to survival. Meanwhile, the roles of the habenula in neuropsychiatric diseases have received increasing attention. This review summaries the studies regarding the roles of habenula and the related circuits in neuropathic pain, depression, drug addiction and schizophrenia, and discusses the possibility to use the habenula as a treatment target.

Identification of a regeneration-organizing cell in the Xenopus tail

Unlike mammals, Xenopus laevis tadpoles have a high regenerative potential. To characterize this regenerative response, we performed single-cell RNA sequencing after tail amputation. By comparing naturally occurring regeneration-competent and -incompetent tadpoles, we identified a previously unrecognized cell type, which we term the regeneration-organizing cell (ROC). ROCs are present in the epidermis during normal tail development and specifically relocalize to the amputation plane of regeneration-competent tadpoles, forming the wound epidermis. Genetic ablation or manual removal of ROCs blocks regeneration, whereas transplantation of ROC-containing grafts induces ectopic outgrowths in early embryos. Transcriptional profiling revealed that ROCs secrete ligands associated with key regenerative pathways, signaling to progenitors to reconstitute lost tissue. These findings reveal the cellular mechanism through which ROCs form the wound epidermis and ensure successful regeneration.

Neuronal Dynamics Regulating Brain and Behavioral State Transitions

Prolonged behavioral challenges can cause animals to switch from active to passive coping strategies to manage effort-expenditure during stress; such normally adaptive behavioral state transitions can become maladaptive in psychiatric disorders such as depression. The underlying neuronal dynamics and brainwide interactions important for passive coping have remained unclear. Here, we develop a paradigm to study these behavioral state transitions at cellular-resolution across the entire vertebrate brain. Using brainwide imaging in zebrafish, we observed that the transition to passive coping is manifested by progressive activation of neurons in the ventral (lateral) habenula. Activation of these ventral-habenula neurons suppressed downstream neurons in the serotonergic raphe nucleus and caused behavioral passivity, whereas inhibition of these neurons prevented passivity. Data-driven recurrent neural network modeling pointed to altered intra-habenula interactions as a contributory mechanism. These results demonstrate ongoing encoding of experience features in the habenula, which guides recruitment of downstream networks and imposes a passive coping behavioral strategy.

Phenotypic Landscape of Schizophrenia-Associated Genes Defines Candidates and Their Shared Functions

Genomic studies have identified hundreds of candidate genes near loci associated with risk for schizophrenia. To define candidates and their functions, we mutated zebrafish orthologs of 132 human schizophrenia-associated genes. We created a phenotype atlas consisting of whole-brain activity maps, brain structural differences, and profiles of behavioral abnormalities. Phenotypes were diverse but specific, including altered forebrain development and decreased prepulse inhibition. Exploration of these datasets identified promising candidates in more than 10 gene-rich regions, including the magnesium transporter cnnm2 and the translational repressor gigyf2, and revealed shared anatomical sites of activity differences, including the pallium, hypothalamus, and tectum. Single-cell RNA sequencing uncovered an essential role for the understudied transcription factor znf536 in the development of forebrain neurons implicated in social behavior and stress. This phenotypic landscape of schizophrenia-associated genes prioritizes more than 30 candidates for further study and provides hypotheses to bridge the divide between genetic association and biological mechanism.

Molecular Classification and Comparative Taxonomics of Foveal and Peripheral Cells in Primate Retina

High-acuity vision in primates, including humans, is mediated by a small central retinal region called the fovea. As more accessible organisms lack a fovea, its specialized function and its dysfunction in ocular diseases remain poorly understood. We used 165,000 single-cell RNA-seq profiles to generate comprehensive cellular taxonomies of macaque fovea and peripheral retina. More than 80% of >60 cell types match between the two regions but exhibit substantial differences in proportions and gene expression, some of which we relate to functional differences. Comparison of macaque retinal types with those of mice reveals that interneuron types are tightly conserved. In contrast, projection neuron types and programs diverge, despite exhibiting conserved transcription factor codes. Key macaque types are conserved in humans, allowing mapping of cell-type and region-specific expression of >190 genes associated with 7 human retinal diseases. Our work provides a framework for comparative single-cell analysis across tissue regions and species.

Identification of Cell Types from Single-Cell Transcriptomic Data

Unprecedented technological advances in single-cell RNA-sequencing (scRNA-seq) technology have now made it possible to profile genome-wide expression in single cells at low cost and high throughput. There is substantial ongoing effort to use scRNA-seq measurements to identify the "cell types" that form components of a complex tissue, akin to taxonomizing species in ecology. Cell type classification from scRNA-seq data involves the application of computational tools rooted in dimensionality reduction and clustering, and statistical analysis to identify molecular signatures that are unique to each type. As datasets continue to grow in size and complexity, computational challenges abound, requiring analytical methods to be scalable, flexible, and robust. Moreover, careful consideration needs to be paid to experimental biases and statistical challenges that are unique to these measurements to avoid artifacts. This chapter introduces these topics in the context of cell-type identification, and outlines an instructive step-by-step example bioinformatic pipeline for researchers entering this field.

Molecular, spatial, and functional single-cell profiling of the hypothalamic preoptic region

The hypothalamus controls essential social behaviors and homeostatic functions. However, the cellular architecture of hypothalamic nuclei-including the molecular identity, spatial organization, and function of distinct cell types-is poorly understood. Here, we developed an imaging-based in situ cell-type identification and mapping method and combined it with single-cell RNA-sequencing to create a molecularly annotated and spatially resolved cell atlas of the mouse hypothalamic preoptic region. We profiled ~1 million cells, identified ~70 neuronal populations characterized by distinct neuromodulatory signatures and spatial organizations, and defined specific neuronal populations activated during social behaviors in male and female mice, providing a high-resolution framework for mechanistic investigation of behavior circuits. The approach described opens a new avenue for the construction of cell atlases in diverse tissues and organisms.

Large-scale reconstruction of cell lineages using single-cell readout of transcriptomes and CRISPR-Cas9 barcodes by scGESTALT

Lineage relationships among the large number of heterogeneous cell types generated during development are difficult to reconstruct in a high-throughput manner. We recently established a method, scGESTALT, that combines cumulative editing of a lineage barcode array by CRISPR-Cas9 with large-scale transcriptional profiling using droplet-based single-cell RNA sequencing (scRNA-seq). The technique generates edits in the barcode array over multiple timepoints using Cas9 and pools of single-guide RNAs (sgRNAs) introduced during early and late zebrafish embryonic development, which distinguishes it from similar Cas9 lineage-tracing methods. The recorded lineages are captured, along with thousands of cellular transcriptomes, to build lineage trees with hundreds of branches representing relationships among profiled cell types. Here, we provide details for (i) generating transgenic zebrafish; (ii) performing multi-timepoint barcode editing; (iii) building scRNA-seq libraries from brain tissue; and (iv) concurrently amplifying lineage barcodes from captured single cells. Generating transgenic lines takes 6 months, and performing barcode editing and generating single-cell libraries involve 7 d of hands-on time. scGESTALT provides a scalable platform to map lineage relationships between cell types in any system that permits genome editing during development, regeneration, or disease.

Transcriptomic Characterization of the Human Habenula Highlights Drug Metabolism and the Neuroimmune System

Due to size and accessibility, most information about the habenula is derived from rodent studies. To better understand the molecular signature of the habenula we characterized the genes that have high expression in the habenula. We compared anatomical expression profiles of three normal adult human brains and four fetal brains. We used gene set enrichment analyses to determine if genes annotated to specific molecular functions, cellular components, and biological processes are enriched in the habenula. We also tested gene sets related to depression and addiction to determine if they uniquely involve the habenula. As expected, we observed high habenular expression of GPR151, nicotinic cholinergic receptors, and cilia-associated genes (medial division). Genes identified in genetic studies of smoking and associated with nicotine response were enriched in the habenula. Genes associated with major depressive disorder did not have enriched expression in the habenula but genes negatively correlated with hedonic well-being were, providing a link to anhedonia. We observed enrichment of genes associated with diseases that are comorbid with addictions (hematopoiesis, thrombosis, liver cirrhosis, pneumonia, and pulmonary fibrosis) and depression (rheumatoid arthritis, multiple sclerosis, and kidney disease). These inflammatory diseases mark a neuroimmune signature that is supported by genes associated with mast cells, acute inflammatory response, and leukocyte migration. We also found enrichment of cytochrome p450 genes suggesting the habenula is uniquely sensitive to endogenous and xenobiotic compounds. Our results suggest the habenula receives negative reward signals from immune and drug processing molecules. This is consistent with the habenular role in the "anti-reward" system and suggests it may be a key bridge between autoimmune disorders, drug use, and psychiatric diseases.

Methods for Mapping Neuronal Activity to Synaptic Connectivity: Lessons From Larval Zebrafish

For a mechanistic understanding of neuronal circuits in the brain, a detailed description of information flow is necessary. Thereby it is crucial to link neuron function to the underlying circuit structure. Multiphoton calcium imaging is the standard technique to record the activity of hundreds of neurons simultaneously. Similarly, recent advances in high-throughput electron microscopy techniques allow for the reconstruction of synaptic resolution wiring diagrams. These two methods can be combined to study both function and structure in the same specimen. Due to its small size and optical transparency, the larval zebrafish brain is one of the very few vertebrate systems where both, activity and connectivity of all neurons from entire, anatomically defined brain regions, can be analyzed. Here, we describe different methods and the tools required for combining multiphoton microscopy with dense circuit reconstruction from electron microscopy stacks of entire brain regions in the larval zebrafish.

Single-cell reconstruction of developmental trajectories during zebrafish embryogenesis

During embryogenesis, cells acquire distinct fates by transitioning through transcriptional states. To uncover these transcriptional trajectories during zebrafish embryogenesis, we sequenced 38,731 cells and developed URD, a simulated diffusion-based computational reconstruction method. URD identified the trajectories of 25 cell types through early somitogenesis, gene expression along them, and their spatial origin in the blastula. Analysis of Nodal signaling mutants revealed that their transcriptomes were canalized into a subset of wild-type transcriptional trajectories. Some wild-type developmental branch points contained cells that express genes characteristic of multiple fates. These cells appeared to trans-specify from one fate to another. These findings reconstruct the transcriptional trajectories of a vertebrate embryo, highlight the concurrent canalization and plasticity of embryonic specification, and provide a framework with which to reconstruct complex developmental trees from single-cell transcriptomes.

Simultaneous single-cell profiling of lineages and cell types in the vertebrate brain

The lineage relationships among the hundreds of cell types generated during development are difficult to reconstruct. A recent method, GESTALT, used CRISPR-Cas9 barcode editing for large-scale lineage tracing, but was restricted to early development and did not identify cell types. Here we present scGESTALT, which combines the lineage recording capabilities of GESTALT with cell-type identification by single-cell RNA sequencing. The method relies on an inducible system that enables barcodes to be edited at multiple time points, capturing lineage information from later stages of development. Sequencing of ~60,000 transcriptomes from the juvenile zebrafish brain identifies >100 cell types and marker genes. Using these data, we generate lineage trees with hundreds of branches that help uncover restrictions at the level of cell types, brain regions, and gene expression cascades during differentiation. scGESTALT can be applied to other multicellular organisms to simultaneously characterize molecular identities and lineage histories of thousands of cells during development and disease.