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

The behavioral relevance of a modular organization in the lateral habenula

Behavioral strategies for survival rely on the updates the brain continuously makes based on the surrounding environment. External stimuli-neutral, positive, and negative-relay core information to the brain, where a complex anatomical network rapidly organizes actions, including approach or escape, and regulates emotions. Human neuroimaging and physiology in nonhuman primates, rodents, and teleosts suggest a pivotal role of the lateral habenula in translating external information into survival behaviors. Here, we review the literature describing how discrete habenular modules-reflecting the molecular signatures, anatomical connectivity, and functional components-are recruited by environmental stimuli and cooperate to prompt specific behavioral outcomes. We argue that integration of these findings in the context of valence processing for reinforcing or discouraging behaviors is necessary, offering a compelling model to guide future work.

Transcriptomic analysis of the human habenula in schizophrenia

Pathophysiology of many neuropsychiatric disorders, including schizophrenia (SCZD), is linked to habenula (Hb) function. While pharmacotherapies and deep brain stimulation targeting the Hb are emerging as promising therapeutic treatments, little is known about the cell type-specific transcriptomic organization of the human Hb or how it is altered in SCZD. Here we define the molecular neuroanatomy of the human Hb and identify transcriptomic changes in individuals with SCZD compared to neurotypical controls. Utilizing Hb-enriched postmortem human brain tissue, we performed single nucleus RNA-sequencing (snRNA-seq; n=7 neurotypical donors) and identified 17 molecularly defined Hb cell types across 16,437 nuclei, including 3 medial and 7 lateral Hb populations, several of which were conserved between rodents and humans. Single molecule fluorescent in situ hybridization (smFISH; n=3 neurotypical donors) validated snRNA-seq Hb cell types and mapped their spatial locations. Bulk RNA-sequencing and cell type deconvolution in Hb-enriched tissue from 35 individuals with SCZD and 33 neurotypical controls yielded 45 SCZD-associated differentially expressed genes (DEGs, FDR < 0.05), with 32 (71%) unique to Hb-enriched tissue. eQTL analysis identified 717 independent SNP-gene pairs (FDR < 0.05), where either the SNP is a SCZD risk variant (16 pairs) or the gene is a SCZD DEG (7 pairs). eQTL and SCZD risk colocalization analysis identified 16 colocalized genes. These results identify topographically organized cell types with distinct molecular signatures in the human Hb and demonstrate unique genetic changes associated with SCZD, thereby providing novel molecular insights into the role of Hb in neuropsychiatric disorders.

One Sentence Summary

Transcriptomic analysis of the human habenula and identification of molecular changes associated with schizophrenia risk and illness state.

Application of Lineage Tracing in Central Nervous System Development and Regeneration

The central nervous system (CNS) is a complicated neural network. The origin and evolution of functional neurons and glia cells remain unclear, as do the cellular alterations that occur during the course of cerebral disease rehabilitation. Lineage tracing is a valuable method for tracing specific cells and achieving a better understanding of the CNS. Recently, various technological breakthroughs have been made in lineage tracing, such as the application of various combinations of fluorescent reporters and advances in barcode technology. The development of lineage tracing has given us a deeper understanding of the normal physiology of the CNS, especially the pathological processes. In this review, we summarize these advances of lineage tracing and their applications in CNS. We focus on the use of lineage tracing techniques to elucidate the process CNS development and especially the mechanism of injury repair. Deep understanding of the central nervous system will help us to use existing technologies to diagnose and treat diseases.

Deciphering the genetic code of neuronal type connectivity through bilinear modeling

Understanding how different neuronal types connect and communicate is critical to interpreting brain function and behavior. However, it has remained a formidable challenge to decipher the genetic underpinnings that dictate the specific connections formed between neuronal types. To address this, we propose a novel bilinear modeling approach that leverages the architecture similar to that of recommendation systems. Our model transforms the gene expressions of presynaptic and postsynaptic neuronal types, obtained from single-cell transcriptomics, into a covariance matrix. The objective is to construct this covariance matrix that closely mirrors a connectivity matrix, derived from connectomic data, reflecting the known anatomical connections between these neuronal types. When tested on a dataset of Caenorhabditis elegans, our model achieved a performance comparable to, if slightly better than, the previously proposed spatial connectome model (SCM) in reconstructing electrical synaptic connectivity based on gene expressions. Through a comparative analysis, our model not only captured all genetic interactions identified by the SCM but also inferred additional ones. Applied to a mouse retinal neuronal dataset, the bilinear model successfully recapitulated recognized connectivity motifs between bipolar cells and retinal ganglion cells, and provided interpretable insights into genetic interactions shaping the connectivity. Specifically, it identified unique genetic signatures associated with different connectivity motifs, including genes important to cell-cell adhesion and synapse formation, highlighting their role in orchestrating specific synaptic connections between these neurons. Our work establishes an innovative computational strategy for decoding the genetic programming of neuronal type connectivity. It not only sets a new benchmark for single-cell transcriptomic analysis of synaptic connections but also paves the way for mechanistic studies of neural circuit assembly and genetic manipulation of circuit wiring.

Barcoding Notch signaling in the developing brain

Developmental signaling inputs are fundamental for shaping cell fates and behavior. However, traditional fluorescent-based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER-seq, a CRISPR-Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single-cell transcriptomics. We applied SABER-seq to record Notch signaling in developing zebrafish brains. SABER-seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch-dependent manner with inducible control while the recorder accumulates mutations that represent Notch activity in founder cells. We combine SABER-seq with an expanded juvenile brain atlas to define cell types whose fates are determined downstream of Notch signaling. We identified examples wherein Notch signaling may have differential impact on terminal cell fates. SABER-seq is a novel platform for rapid, scalable and high-resolution mapping of signaling activity during development.

Paradoxical effects of feeding status on food consumption and learning performance in zebrafish (Danio rerio)

Associative learning is often studied using food reward as the unconditioned stimulus (US). With warm-blooded species, to get the subject more motivated the solution has been to feed less, making the subject hungrier. Here we show the opposite with zebrafish. We randomly assigned zebrafish to two groups: a once-a-day-fed and a five-times-a-day-fed group, with the same amount of food fed per occasion for fish of both groups, a feeding regimen that lasted for three months. Subsequently, we trained fish by pairing food (US) with a red cue card (the conditioned stimulus, CS), which were placed together in one arm of a plus-maze across eight training sessions. We also ran unpaired training, in which the CS and US were presented in different arms. We found the previously once-a-day-fed zebrafish to consume less food throughout habituation and training sessions compared to the previously five-times-a-day-fed ones. Furthermore, five-times-a-day-fed fish in the paired group swam significantly closer to the CS during a post-training probe trial compared to the five-times-a-day-fed unpaired fish, a paired training effect that was absent in once-a-day-fed fish. Groups did not differ in health or general activity. In sum, elevated chronic feeding improved food consumption and enhanced learning and memory performance without affecting activity levels in adult zebrafish.

Factorized discriminant analysis for genetic signatures of neuronal phenotypes

Navigating the complex landscape of single-cell transcriptomic data presents significant challenges. Central to this challenge is the identification of a meaningful representation of high-dimensional gene expression patterns that sheds light on the structural and functional properties of cell types. Pursuing model interpretability and computational simplicity, we often look for a linear transformation of the original data that aligns with key phenotypic features of cells. In response to this need, we introduce factorized linear discriminant analysis (FLDA), a novel method for linear dimensionality reduction. The crux of FLDA lies in identifying a linear function of gene expression levels that is highly correlated with one phenotypic feature while minimizing the influence of others. To augment this method, we integrate it with a sparsity-based regularization algorithm. This integration is crucial as it selects a subset of genes pivotal to a specific phenotypic feature or a combination thereof. To illustrate the effectiveness of FLDA, we apply it to transcriptomic datasets from neurons in the Drosophila optic lobe. We demonstrate that FLDA not only captures the inherent structural patterns aligned with phenotypic features but also uncovers key genes associated with each phenotype.

Single-Nucleus Transcriptional Profiling of GAD2-Positive Neurons From Mouse Lateral Habenula Reveals Distinct Expression of Neurotransmission- and Depression-Related Genes

Background

Glutamatergic projection neurons of the lateral habenula (LHb) drive behavioral state modulation by regulating the activity of midbrain monoaminergic neurons. Identifying circuit mechanisms that modulate LHb output is of interest for understanding control of motivated behaviors.

Methods

A small population of neurons within the medial subnucleus of the mouse LHb express the GABAergic (gamma-aminobutyric acidergic)-synthesizing enzyme GAD2, and they can inhibit nearby LHb projection neurons; however, these neurons lack markers of classic inhibitory interneurons, and they coexpress the vesicular glutamate transporter VGLUT2. To determine the molecular phenotype of these neurons, we genetically tagged the nuclei of GAD2-positive cells and used fluorescence-activated nuclear sorting to isolate and enrich these nuclei for single-nucleus RNA sequencing.

Results

Our data confirm that GAD2+/VGLUT2+ neurons intrinsic to the LHb coexpress markers of both glutamatergic and GABAergic transmission and that they are transcriptionally distinct from either GABAergic interneurons or habenular glutamatergic neurons. We identify gene expression programs within these cells that show sex-specific differences in expression and that are implicated in major depressive disorder, which has been linked to LHb hyperactivity. Finally, we identify the Ntng2 gene encoding the cell adhesion protein netrin-G2 as a marker of LHb GAD2+/VGLUT2+ neurons and a gene product that may contribute to their target projections.

Conclusions

These data show the value of using genetic enrichment of rare cell types for transcriptome studies, and they advance understanding of the molecular composition of a functionally important class of GAD2+ neurons in the LHb.

Retina-derived signals control pace of neurogenesis in visual brain areas but not circuit assembly

Brain development is orchestrated by both innate and experience-dependent mechanisms, but their relative contributions are difficult to disentangle. Here we asked if and how central visual areas are altered in a vertebrate brain depleted of any and all signals from retinal ganglion cells throughout development. We transcriptionally profiled neurons in pretectum, thalamus and other retinorecipient areas of larval zebrafish and searched for changes in lakritz mutants that lack all retinal connections. Although individual genes are dysregulated, the complete set of 77 neuronal types develops in apparently normal proportions, at normal locations, and along normal differentiation trajectories. Strikingly, the cell-cycle exits of proliferating progenitors in these areas are delayed, and a greater fraction of early postmitotic precursors remain uncommitted or are diverted to a pre-glial fate. Optogenetic stimulation targeting groups of neurons normally involved in processing visual information evokes behaviors indistinguishable from wildtype. In conclusion, we show that signals emitted by retinal axons influence the pace of neurogenesis in visual brain areas, but do not detectably affect the specification or wiring of downstream neurons.

Cross-species transcriptomics reveals bifurcation point during the arterial-to-hemogenic transition

Hemogenic endothelium (HE) with hematopoietic stem cell (HSC)-forming potential emerge from specialized arterial endothelial cells (AECs) undergoing the endothelial-to-hematopoietic transition (EHT) in the aorta-gonad-mesonephros (AGM) region. Characterization of this AECs subpopulation and whether this phenomenon is conserved across species remains unclear. Here we introduce HomologySeeker, a cross-species method that leverages refined mouse information to explore under-studied human EHT. Utilizing single-cell transcriptomic ensembles of EHT, HomologySeeker reveals a parallel developmental relationship between these two species, with minimal pre-HSC signals observed in human cells. The pre-HE stage contains a conserved bifurcation point between the two species, where cells progress towards HE or late AECs. By harnessing human spatial transcriptomics, we identify ligand modules that contribute to the bifurcation choice and validate CXCL12 in promoting hemogenic choice using a human in vitro differentiation system. Our findings advance human arterial-to-hemogenic transition understanding and offer valuable insights for manipulating HSC generation using in vitro models.

Single cell transcriptome analyses of the developing zebrafish eye- perspectives and applications

Within a relatively short period of time, single cell transcriptome analyses (SCT) have become increasingly ubiquitous with transcriptomic research, uncovering plentiful details that boost our molecular understanding of various biological processes. Stemming from SCT analyses, the ever-growing number of newly assigned genetic markers increases our understanding of general function and development, while providing opportunities for identifying genes associated with disease. SCT analyses have been carried out using tissue from numerous organisms. However, despite the great potential of zebrafish as a model organism, other models are still preferably used. In this mini review, we focus on eye research as an example of the advantages in using zebrafish, particularly its usefulness for single cell transcriptome analyses of developmental processes. As studies have already shown, the unique opportunities offered by zebrafish, including similarities to the human eye, in combination with the possibility to analyze and extract specific cells at distinct developmental time points makes the model a uniquely powerful one. Particularly the practicality of collecting large numbers of embryos and therefore isolation of sufficient numbers of developing cells is a distinct advantage compared to other model organisms. Lastly, the advent of highly efficient genetic knockouts methods offers opportunities to characterize target gene function in a more cost-efficient way. In conclusion, we argue that the use of zebrafish for SCT approaches has great potential to further deepen our molecular understanding of not only eye development, but also many other organ systems.

Nicotine reduces social dominance and neutralizes experience-dependent effects during social conflicts in zebrafish (Danio rerio)

Nicotine, a psychoactive pollutant, binds to nicotinic acetylcholine receptors and disrupts the cholinergic modulation and reward systems of the brain, leading to attention deficit, memory loss, and addiction. However, whether nicotine affects social behaviors remains unknown. We assessed the effects of nicotine on the fighting behavior of zebrafish. Adult zebrafish treated with 5 μM nicotine were used in dyadic fighting tests with size-matched control siblings. The results indicate that nicotine treatment not only significantly reduced the likelihood of winning but also impaired the winner-loser effects (winner and loser fish did not show higher winning and losing tendencies in the second fight, respectively, after treatment.) Nicotine led to a considerable increase in c-fos-positive signals in the interpeduncular nucleus (IPN) of the brain, indicating that nicotine induces neural activity in the habenula (Hb)-IPN circuit. We used transgenic fish in which the Hb-IPN circuit was silenced to verify whether nicotine impaired the winner-loser effect through the Hb-IPN pathway. Nicotine-treated fish in which the medial part of the dorsal Hb was silenced did not have a higher winning rate, and nicotine-treated fish in which the lateral part of the dorsal Hb was silenced did not have a higher loss rate. This finding suggests that nicotine impairs the winner-loser effect by modulating the Hb-IPN circuit. Therefore, in these zebrafish, nicotine exposure impaired social dominance and neutralized experience-dependent effects in social conflicts, and it may thereby disturb the social hierarchy and population stability of such fish.

Evolution of neuronal cell classes and types in the vertebrate retina

The basic plan of the retina is conserved across vertebrates, yet species differ profoundly in their visual needs (Baden et al., 2020). One might expect that retinal cell types evolved to accommodate these varied needs, but this has not been systematically studied. Here, we generated and integrated single-cell transcriptomic atlases of the retina from 17 species: humans, two non-human primates, four rodents, three ungulates, opossum, ferret, tree shrew, a teleost fish, a bird, a reptile and a lamprey. Molecular conservation of the six retinal cell classes (photoreceptors, horizontal cells, bipolar cells, amacrine cells, retinal ganglion cells [RGCs] and Muller glia) is striking, with transcriptomic differences across species correlated with evolutionary distance. Major subclasses are also conserved, whereas variation among types within classes or subclasses is more pronounced. However, an integrative analysis revealed that numerous types are shared across species based on conserved gene expression programs that likely trace back to the common ancestor of jawed vertebrates. The degree of variation among types increases from the outer retina (photoreceptors) to the inner retina (RGCs), suggesting that evolution acts preferentially to shape the retinal output. Finally, we identified mammalian orthologs of midget RGCs, which comprise >80% of RGCs in the human retina, subserve high-acuity vision, and were believed to be primate-specific (Berson, 2008); in contrast, the mouse orthologs comprise <2% of mouse RGCs. Projections both primate and mouse orthologous types are overrepresented in the thalamus, which supplies the primary visual cortex. We suggest that midget RGCs are not primate innovations, but descendants of evolutionarily ancient types that decreased in size and increased in number as primates evolved, thereby facilitating high visual acuity and increased cortical processing of visual information.

A single-cell transcriptome atlas of the maturing zebrafish telencephalon

The zebrafish telencephalon is composed of highly specialized subregions that regulate complex behaviors such as learning, memory, and social interactions. The transcriptional signatures of the neuronal cell types in the telencephalon and the timeline of their emergence from larva to adult remain largely undescribed. Using an integrated analysis of single-cell transcriptomes of approximately 64,000 cells obtained from 6-day-postfertilization (dpf), 15-dpf, and adult telencephalon, we delineated nine main neuronal cell types in the pallium and eight in the subpallium and nominated novel marker genes. Comparing zebrafish and mouse neuronal cell types revealed both conserved and absent types and marker genes. Mapping of cell types onto a spatial larval reference atlas created a resource for anatomical and functional studies. Using this multiage approach, we discovered that although most neuronal subtypes are established early in the 6-dpf fish, some emerge or expand in number later in development. Analyzing the samples from each age separately revealed further complexity in the data, including several cell types that expand substantially in the adult forebrain and do not form clusters at the larval stages. Together, our work provides a comprehensive transcriptional analysis of the cell types in the zebrafish telencephalon and a resource for dissecting its development and function.

scEvoNet: a gradient boosting-based method for prediction of cell state evolution

BACKGROUND

Exploring the function or the developmental history of cells in various organisms provides insights into a given cell type's core molecular characteristics and putative evolutionary mechanisms. Numerous computational methods now exist for analyzing single-cell data and identifying cell states. These methods mostly rely on the expression of genes considered as markers for a given cell state. Yet, there is a lack of scRNA-seq computational tools to study the evolution of cell states, particularly how cell states change their molecular profiles. This can include novel gene activation or the novel deployment of programs already existing in other cell types, known as co-option.

RESULTS

Here we present scEvoNet, a Python tool for predicting cell type evolution in cross-species or cancer-related scRNA-seq datasets. ScEvoNet builds the confusion matrix of cell states and a bipartite network connecting genes and cell states. It allows a user to obtain a set of genes shared by the characteristic signature of two cell states even between distantly-related datasets. These genes can be used as indicators of either evolutionary divergence or co-option occurring during organism or tumor evolution. Our results on cancer and developmental datasets indicate that scEvoNet is a helpful tool for the initial screening of such genes as well as for measuring cell state similarities.

CONCLUSION

The scEvoNet package is implemented in Python and is freely available from https://github.com/monsoro/scEvoNet . Utilizing this framework and exploring the continuum of transcriptome states between developmental stages and species will help explain cell state dynamics.

Single-nucleus transcriptional profiling of GAD2-positive neurons from mouse lateral habenula reveals distinct expression of neurotransmission- and depression-related genes

Glutamatergic projection neurons of the lateral habenula (LHb) drive behavioral state modulation by regulating the activity of midbrain monoaminergic neurons. Identifying circuit mechanisms that modulate LHb output is of interest for understanding control of motivated behaviors. A small population of neurons within the medial subnucleus of the mouse LHb express the GABAergic synthesizing enzyme GAD2, and they can inhibit nearby LHb projection neurons; however, these neurons lack markers of classic inhibitory interneurons and they co-express the vesicular glutamate transporter VGLUT2. To determine the molecular phenotype of these neurons, we genetically tagged the nuclei of GAD2-positive cells and used fluorescence-activated nuclear sorting to isolate and enrich these nuclei for single nuclear RNA sequencing (FANS-snRNAseq). Our data confirm that GAD2+/VGLUT2+ neurons intrinsic to the LHb co-express markers of both glutamatergic and GABAergic transmission and that they are transcriptionally distinct from either GABAergic interneurons or habenular glutamatergic neurons. We identify gene expression programs within these cells that show sex-specific differences in expression and that are implicated in major depressive disorder (MDD), which has been linked to LHb hyperactivity. Finally, we identify the Ntng2 gene encoding the cell adhesion protein Netrin-G2 as a marker of LHb GAD2+/VGLUT+ neurons and a gene product that may contribute to their target projections. These data show the value of using genetic enrichment of rare cell types for transcriptome studies, and they advance understanding of the molecular composition of a functionally important class of GAD2+ neurons in the LHb.

Defining Selective Neuronal Resilience and Identifying Targets of Neuroprotection and Axon Regeneration Using Single-Cell RNA Sequencing: Computational Approaches

We describe a computational workflow to analyze single-cell RNA-sequencing (scRNA-seq) profiles of axotomized retinal ganglion cells (RGCs) in mice. Our goal is to identify differences in the dynamics of survival among 46 molecularly defined RGC types together with molecular signatures that correlate with these differences. The data consists of scRNA-seq profiles of RGCs collected at six time points following optic nerve crush (ONC) (see companion chapter by Jacobi and Tran). We use a supervised classification-based approach to map injured RGCs to type identities and quantify type-specific differences in survival at 2 weeks post crush. As injury-related changes in gene expression confound the inference of type identity in surviving cells, the approach deconvolves type-specific gene signatures from injury responses by using an iterative strategy that leverages measurements along the time course. We use these classifications to compare expression differences between resilient and susceptible subpopulations, identifying potential mediators of resilience. The conceptual framework underlying the method is sufficiently general for analysis of selective vulnerability in other neuronal systems.

Vision-Dependent and -Independent Molecular Maturation of Mouse Retinal Ganglion Cells

The development and connectivity of retinal ganglion cells (RGCs), the retina's sole output neurons, are patterned by activity-independent transcriptional programs and activity-dependent remodeling. To inventory the molecular correlates of these influences, we applied high-throughput single-cell RNA sequencing (scRNA-seq) to mouse RGCs at six embryonic and postnatal ages. We identified temporally regulated modules of genes that correlate with, and likely regulate, multiple phases of RGC development, ranging from differentiation and axon guidance to synaptic recognition and refinement. Some of these genes are expressed broadly while others, including key transcription factors and recognition molecules, are selectively expressed by one or a few of the 45 transcriptomically distinct types defined previously in adult mice. Next, we used these results as a foundation to analyze the transcriptomes of RGCs in mice lacking visual experience due to dark rearing from birth or to mutations that ablate either bipolar or photoreceptor cells. 98.5% of visually deprived (VD) RGCs could be unequivocally assigned to a single RGC type based on their transcriptional profiles, demonstrating that visual activity is dispensable for acquisition and maintenance of RGC type identity. However, visual deprivation significantly reduced the transcriptomic distinctions among RGC types, implying that activity is required for complete RGC maturation or maintenance. Consistent with this notion, transcriptomic alternations in VD RGCs significantly overlapped with gene modules found in developing RGCs. Our results provide a resource for mechanistic analyses of RGC differentiation and maturation, and for investigating the role of activity in these processes.

Diversification of habenular organization and asymmetries in teleosts: Insights from the Atlantic salmon and European eel

Habenulae asymmetries are widespread across vertebrates and analyses in zebrafish, the reference model organism for this process, have provided insight into their molecular nature, their mechanisms of formation and their important roles in the integration of environmental and internal cues with a variety of organismal adaptive responses. However, the generality of the characteristics identified in this species remains an open question, even on a relatively short evolutionary scale, in teleosts. To address this question, we have characterized the broad organization of habenulae in the Atlantic salmon and quantified the asymmetries in each of the identified subdomains. Our results show that a highly conserved partitioning into a dorsal and a ventral component is retained in the Atlantic salmon and that asymmetries are mainly observed in the former as in zebrafish. A remarkable difference is that a prominent left-restricted pax6 positive nucleus is observed in the Atlantic salmon, but undetectable in zebrafish. This nucleus is not observed outside teleosts, and harbors a complex presence/absence pattern in this group, retaining its location and cytoarchitectonic organization in an elopomorph, the European eel. These findings suggest an ancient origin and high evolvability of this trait in the taxon. Taken together, our data raise novel questions about the variability of asymmetries across teleosts and their biological significance depending on ecological contexts.

Cell-type-specific population dynamics of diverse reward computations

Computational analysis of cellular activity has developed largely independently of modern transcriptomic cell typology, but integrating these approaches may be essential for full insight into cellular-level mechanisms underlying brain function and dysfunction. Applying this approach to the habenula (a structure with diverse, intermingled molecular, anatomical, and computational features), we identified encoding of reward-predictive cues and reward outcomes in distinct genetically defined neural populations, including TH+ cells and Tac1+ cells. Data from genetically targeted recordings were used to train an optimized nonlinear dynamical systems model and revealed activity dynamics consistent with a line attractor. High-density, cell-type-specific electrophysiological recordings and optogenetic perturbation provided supporting evidence for this model. Reverse-engineering predicted how Tac1+ cells might integrate reward history, which was complemented by in vivo experimentation. This integrated approach describes a process by which data-driven computational models of population activity can generate and frame actionable hypotheses for cell-type-specific investigation in biological systems.

Microfluidics for Neuronal Cell and Circuit Engineering

The widespread adoption of microfluidic devices among the neuroscience and neurobiology communities has enabled addressing a broad range of questions at the molecular, cellular, circuit, and system levels. Here, we review biomedical engineering approaches that harness the power of microfluidics for bottom-up generation of neuronal cell types and for the assembly and analysis of neural circuits. Microfluidics-based approaches are instrumental to generate the knowledge necessary for the derivation of diverse neuronal cell types from human pluripotent stem cells, as they enable the isolation and subsequent examination of individual neurons of interest. Moreover, microfluidic devices allow to engineer neural circuits with specific orientations and directionality by providing control over neuronal cell polarity and permitting the isolation of axons in individual microchannels. Similarly, the use of microfluidic chips enables the construction not only of 2D but also of 3D brain, retinal, and peripheral nervous system model circuits. Such brain-on-a-chip and organoid-on-a-chip technologies are promising platforms for studying these organs as they closely recapitulate some aspects of in vivo biological processes. Microfluidic 3D neuronal models, together with 2D in vitro systems, are widely used in many applications ranging from drug development and toxicology studies to neurological disease modeling and personalized medicine. Altogether, microfluidics provide researchers with powerful systems that complement and partially replace animal models.

Molecular archaeology of human cognitive traits

The brains and minds of our human ancestors remain inaccessible for experimental exploration. Therefore, we reconstructed human cognitive evolution by projecting nonsynonymous/synonymous rate ratios (ω values) in mammalian phylogeny onto the anatomically modern human (AMH) brain. This atlas retraces human neurogenetic selection and allows imputation of ancestral evolution in task-related functional networks (FNs). Adaptive evolution (high ω values) is associated with excitatory neurons and synaptic function. It shifted from FNs for motor control in anthropoid ancestry (60-41 mya) to attention in ancient hominoids (26-19 mya) and hominids (19-7.4 mya). Selection in FNs for language emerged with an early hominin ancestor (7.4-1.7 mya) and was later accompanied by adaptive evolution in FNs for strategic thinking during recent (0.8 mya-present) speciation of AMHs. This pattern mirrors increasingly complex cognitive demands and suggests that co-selection for language alongside strategic thinking may have separated AMHs from their archaic Denisovan and Neanderthal relatives.

Dynamics and potential significance of spontaneous activity in the habenula

The habenula is an evolutionarily conserved structure of the vertebrate brain that is essential for behavioural flexibility and mood control. It is spontaneously active and is able to access diverse states when the animal is exposed to sensory stimuli. Here we investigate the dynamics of habenula spontaneous activity, to gain insight into how sensitivity is optimized. Two-photon calcium imaging was performed in resting zebrafish larvae at single cell resolution. An analysis of avalanches of inferred spikes suggests that the habenula is subcritical. Activity had low covariance and a small mean, arguing against dynamic criticality. A multiple regression estimator of autocorrelation time suggests that the habenula is neither fully asynchronous nor perfectly critical, but is reverberating. This pattern of dynamics may enable integration of information and high flexibility in the tuning of network properties, thus providing a potential mechanism for the optimal responses to a changing environment.Significance StatementSpontaneous activity in neurons shapes the response to stimuli. One structure with a high level of spontaneous neuronal activity is the habenula, a regulator of broadly acting neuromodulators involved in mood and learning. How does this activity influence habenula function? We show here that the habenula of a resting animal is near criticality, in a state termed reverberation. This pattern of dynamics is consistent with high sensitivity and flexibility, and may enable the habenula to respond optimally to a wide range of stimuli.

Habenula bibliometrics: Thematic development and research fronts of a resurgent field

The habenula (Hb) is a small structure of the posterior diencephalon that is highly conserved across vertebrates but nonetheless has attracted relatively little research attention until the past two decades. The resurgent interest is motivated by neurobehavioral studies demonstrating critical functions in a broad spectrum of motivational and cognitive processes, including functions relevant to psychiatric diseases. The Hb is widely conceived as an “anti-reward” center that acts by regulating brain monoaminergic systems. However, there is still no general conceptual framework for habenula research, and no study has focused on uncovering potentially significant but overlooked topics that may advance our understanding of physiological functions or suggest potential clinical applications of Hb-targeted interventions. Using science mapping tools, we quantitatively and qualitatively analyzed the relevant publications retrieved from the Web of Science Core Collection (WoSCC) database from 2002 to 2021. Herein we present an overview of habenula-related publications, reveal primary research trends, and prioritize some key research fronts by complementary bibliometric analysis. High-priority research fronts include Ventral Pallidum, Nucleus Accumbens, Nicotine and MHb, GLT-1, Zebrafish, and GCaMP, Ketamine, Deep Brain Stimulation, and GPR139. The high intrinsic heterogeneity of the Hb, extensive connectivity with both hindbrain and forebrain structures, and emerging associations with all three dimensions of mental disorders (internalizing, externalizing, and psychosis) suggest that the Hb may be the neuronal substrate for a common psychopathology factor shared by all mental illnesses termed the p factor. A future challenge is to explore the therapeutic potential of habenular modulation at circuit, cellular, and molecular levels.

Molecular signatures and cellular diversity during mouse habenula development

The habenula plays a key role in various motivated and pathological behaviors and is composed of molecularly distinct neuron subtypes. Despite progress in identifying mature habenula neuron subtypes, how these subtypes develop and organize into functional brain circuits remains largely unknown. Here, we performed single-cell transcriptional profiling of mouse habenular neurons at critical developmental stages, instructed by detailed three-dimensional anatomical data. Our data reveal cellular and molecular trajectories during embryonic and postnatal development, leading to different habenular subtypes. Further, based on this analysis, our work establishes the distinctive functional properties and projection target of a subtype of Cartpt⁺ habenula neurons. Finally, we show how comparison of single-cell transcriptional profiles and GWAS data links specific developing habenular subtypes to psychiatric disease. Together, our study begins to dissect the mechanisms underlying habenula neuron subtype-specific development and creates a framework for further interrogation of habenular development in normal and disease states.

Cell clustering for spatial transcriptomics data with graph neural networks

Spatial transcriptomics data can provide high-throughput gene expression profiling and the spatial structure of tissues simultaneously. Most studies have relied on only the gene expression information but cannot utilize the spatial information efficiently. Taking advantage of spatial transcriptomics and graph neural networks, we introduce cell clustering for spatial transcriptomics data with graph neural networks, an unsupervised cell clustering method based on graph convolutional networks to improve ab initio cell clustering and discovery of cell subtypes based on curated cell category annotation. On the basis of its application to five in vitro and in vivo spatial datasets, we show that cell clustering for spatial transcriptomics outperforms other spatial clustering approaches on spatial transcriptomics datasets and can clearly identify all four cell cycle phases from multiplexed error-robust fluorescence in situ hybridization data of cultured cells. From enhanced sequential fluorescence in situ hybridization data of brain, cell clustering for spatial transcriptomics finds functional cell subtypes with different micro-environments, which are all validated experimentally, inspiring biological hypotheses about the underlying interactions among the cell state, cell type and micro-environment.

Diversification of multipotential postmitotic mouse retinal ganglion cell precursors into discrete types

The genesis of broad neuronal classes from multipotential neural progenitor cells has been extensively studied, but less is known about the diversification of a single neuronal class into multiple types. We used single-cell RNA-seq to study how newly born (postmitotic) mouse retinal ganglion cell (RGC) precursors diversify into ~45 discrete types. Computational analysis provides evidence that RGC transcriptomic type identity is not specified at mitotic exit, but acquired by gradual, asynchronous restriction of postmitotic multipotential precursors. Some types are not identifiable until a week after they are generated. Immature RGCs may be specified to project ipsilaterally or contralaterally to the rest of the brain before their type identity emerges. Optimal transport inference identifies groups of RGC precursors with largely nonoverlapping fates, distinguished by selectively expressed transcription factors that could act as fate determinants. Our study provides a framework for investigating the molecular diversification of discrete types within a neuronal class.

Functional Analysis of Zebrafish socs4a: Impacts on the Notochord and Sensory Function

The suppressor of cytokine signaling (SOCS) proteins play important roles in cytokine and growth factor signaling, where they act principally as negative feedback regulators, particularly of the downstream signal transducer and activator of transcription (STAT) transcription factors. This critical mode of regulation impacts on both development and homeostasis. However, understanding of the function of SOCS4 remains limited. To address this, we investigated one of the zebrafish SOCS4 paralogues, socs4a, analyzing its expression and the consequences of its ablation. The socs4a gene had a dynamic expression profile during zebrafish embryogenesis, with initial ubiquitous expression becoming restricted to sensory ganglion within the developing nervous system. The knockdown of zebrafish socs4a revealed novel roles in notochord development, as well as the formation of a functional sensory system.

Role of Habenula in Social and Reproductive Behaviors in Fish: Comparison With Mammals

Social behaviors such as mating, parenting, fighting, and avoiding are essential functions as a communication tool in social animals, and are critical for the survival of individuals and species. Social behaviors are controlled by a complex circuitry that comprises several key social brain regions, which is called the social behavior network (SBN). The SBN further integrates social information with external and internal factors to select appropriate behavioral responses to social circumstances, called social decision-making. The social decision-making network (SDMN) and SBN are structurally, neurochemically and functionally conserved in vertebrates. The social decision-making process is also closely influenced by emotional assessment. The habenula has recently been recognized as a crucial center for emotion-associated adaptation behaviors. Here we review the potential role of the habenula in social function with a special emphasis on fish studies. Further, based on evolutional, molecular, morphological, and behavioral perspectives, we discuss the crucial role of the habenula in the vertebrate SDMN.

Single-Cell RNA Sequencing Characterizes the Molecular Heterogeneity of the Larval Zebrafish Optic Tectum

The optic tectum (OT) is a multilaminated midbrain structure that acts as the primary retinorecipient in the zebrafish brain. Homologous to the mammalian superior colliculus, the OT is responsible for the reception and integration of stimuli, followed by elicitation of salient behavioral responses. While the OT has been the focus of functional experiments for decades, less is known concerning specific cell types, microcircuitry, and their individual functions within the OT. Recent efforts have contributed substantially to the knowledge of tectal cell types; however, a comprehensive cell catalog is incomplete. Here we contribute to this growing effort by applying single-cell RNA Sequencing (scRNA-seq) to characterize the transcriptomic profiles of tectal cells labeled by the transgenic enhancer trap line y304Et(cfos:Gal4;UAS:Kaede). We sequenced 13,320 cells, a 4X cellular coverage, and identified 25 putative OT cell populations. Within those cells, we identified several mature and developing neuronal populations, as well as non-neuronal cell types including oligodendrocytes and microglia. Although most mature neurons demonstrate GABAergic activity, several glutamatergic populations are present, as well as one glycinergic population. We also conducted Gene Ontology analysis to identify enriched biological processes, and computed RNA velocity to infer current and future transcriptional cell states. Finally, we conducted in situ hybridization to validate our bioinformatic analyses and spatially map select clusters. In conclusion, the larval zebrafish OT is a complex structure containing at least 25 transcriptionally distinct cell populations. To our knowledge, this is the first time scRNA-seq has been applied to explore the OT alone and in depth.

Clustering spatial transcriptomics data

MOTIVATION

Recent advancements in fluorescence in situ hybridization (FISH) techniques enable them to concurrently obtain information on the location and gene expression of single cells. A key question in the initial analysis of such spatial transcriptomics data is the assignment of cell types. To date, most studies used methods that only rely on the expression levels of the genes in each cell for such assignments. To fully utilize the data and to improve the ability to identify novel sub-types, we developed a new method, FICT, which combines both expression and neighborhood information when assigning cell types.

RESULTS

FICT optimizes a probabilistic function that we formalize and for which we provide learning and inference algorithms. We used FICT to analyze both simulated and several real spatial transcriptomics data. As we show, FICT can accurately identify cell types and sub-types, improving on expression only methods and other methods proposed for clustering spatial transcriptomics data. Some of the spatial sub-types identified by FICT provide novel hypotheses about the new functions for excitatory and inhibitory neurons.

AVAILABILITY AND IMPLEMENTATION

FICT is available at: https://github.com/haotianteng/FICT.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Functions of habenula in reproduction and socio-reproductive behaviours

Habenula is an evolutionarily conserved structure in the brain of vertebrates. Recent reports have drawn attention to the habenula as a processing centre for emotional decision-making and its role in psychiatric disorders. Emotional decision-making process is also known to be closely associated with reproductive conditions. The habenula receives innervations from reproductive centres within the brain and signals from key reproductive neuroendocrine regulators such as gonadal sex steroids, gonadotropin-releasing hormone (GnRH), and kisspeptin. In this review, based on morphological, biochemical, physiological, and pharmacological evidence we discuss an emerging role of the habenula in reproduction. Further, we discuss the modulatory role of reproductive endocrine factors in the habenula and their association with socio-reproductive behaviours such as mating, anxiety and aggression.

Neural correlates of state transitions elicited by a chemosensory danger cue

BACKGROUND

Detection of predator cues changes the brain state in prey species and helps them avoid danger. Dysfunctionality in changing the central state appropriately in stressful situations is proposed to be an underlying cause of multiple psychiatric disorders in humans.

METHODS

Here, we investigate the dynamics of neural circuits mediating response to a threat, to characterize these states and to identify potential control networks. We use resonant scanning 2-photon microscopy for in vivo brain-wide imaging and custom designed behavioral assays for the study.

RESULTS

We first show that 5-7 day old zebrafish larvae react to an alarm pheromone (Schreckstoff) with reduced mobility. They subsequently display heightened vigilance, as evidenced by increased dark avoidance. Calcium imaging indicates that exposure to Schreckstoff elicits stimulus-locked activity in olfactory sensory neurons innervating a lateral glomerulus and in telencephalic regions including the putative medial amygdala and entopeduncular nucleus. Sustained activity outlasting the stimulus delivery was detected in regions regulating neuromodulator release, including the lateral habenula, posterior tuberculum, superior raphe, and locus coeruleus.

CONCLUSION

We propose that these latter regions contribute to the network that defines the "threatened" state, while neurons with transient activity serve as the trigger. Our study highlights the utility of the zebrafish larval alarm response system to examine neural circuits during stress dependent brain state transitions and to discover potential therapeutic agents when such transitions are disrupted.

Habenula orphan G-protein coupled receptors in the pathophysiology of fear and anxiety

The phasic emotion, fear, and the tonic emotion, anxiety, have been conventionally inspected in clinical frameworks to epitomize memory acquisition, storage, and retrieval. However, inappropriate expression of learned fear in a safe environment and its resistance to suppression is a cardinal feature of various fear-related disorders. A significant body of literature suggests the involvement of extra-amygdala circuitry in fear disorders. Consistent with this view, the present review underlies incentives for the association between the habenula and fear memory. G protein-coupled receptors (GPCRs) are important to understand the molecular mechanisms central to fear learning due to their neuromodulatory role. The efficacy of a pharmacological strategy aimed at exploiting habenular-GPCR desensitization machinery can serve as a therapeutic target combating the pathophysiology of fear disorders. Originating from this milieu, the conserved nature of orphan GPCRs in the brain, with some having the highest expression in the habenula can lead to recent endeavors in understanding its functionality in fear circuitry.

Single-Cell Sequencing Reveals Differential Cell Types in Skin Tissues of Liaoning Cashmere Goats and Key Genes Related Potentially to the Fineness of Cashmere Fiber

Cashmere fineness is one of the important factors determining cashmere quality; however, our understanding of the regulation of cashmere fineness at the cellular level is limited. Here, we used single-cell RNA sequencing and computational models to identify 13 skin cell types in Liaoning cashmere goats. We also analyzed the molecular changes in the development process by cell trajectory analysis and revealed the maturation process in the gene expression profile in Liaoning cashmere goats. Weighted gene co-expression network analysis explored hub genes in cell clusters related to cashmere formation. Secondary hair follicle dermal papilla cells (SDPCs) play an important role in the growth and density of cashmere. ACTA2, a marker gene of SDPCs, was selected for immunofluorescence (IF) and Western blot (WB) verification. Our results indicate that ACTA2 is mainly expressed in SDPCs, and WB results show different expression levels. COL1A1 is a highly expressed gene in SDPCs, which was verified by IF and WB. We then selected CXCL8 of SDPCs to verify and prove the differential expression in the coarse and fine types of Liaoning cashmere goats. Therefore, the CXCL8 gene may regulate cashmere fineness. These genes may be involved in regulating the fineness of cashmere in goat SDPCs; our research provides new insights into the mechanism of cashmere growth and fineness regulation by cells.

Selecting gene features for unsupervised analysis of single-cell gene expression data

Single-cell RNA sequencing (scRNA-seq) technologies facilitate the characterization of transcriptomic landscapes in diverse species, tissues, and cell types with unprecedented molecular resolution. In order to evaluate various biological hypotheses using high-dimensional single-cell gene expression data, most computational and statistical methods depend on a gene feature selection step to identify genes with high biological variability and reduce computational complexity. Even though many gene selection methods have been developed for scRNA-seq analysis, there lacks a systematic comparison of the assumptions, statistical models, and selection criteria used by these methods. In this article, we summarize and discuss 17 computational methods for selecting gene features in unsupervised analysis of single-cell gene expression data, with unified notations and statistical frameworks. Our discussion provides a useful summary to help practitioners select appropriate methods based on their assumptions and applicability, and to assist method developers in designing new computational tools for unsupervised learning of scRNA-seq data.

Wnt1 Role in the Development of the Habenula and the Fasciculus Retroflexus

Wnt1 is one of the morphogenes that controls the specification and differentiation of neuronal populations in the developing central nervous system. The habenula is a diencephalic neuronal complex located in the most dorsal aspect of the thalamic prosomere. This diencephalic neuronal population is involved in the limbic system and its malfunction is related with several psychiatric disorders. Our aim is to elucidate the Wnt1 role in the habenula and its main efferent tract, the fasciculus retroflexus, development. In order to achieve these objectives, we analyzed these structures development in a Wnt1 lack of function mouse model. The habenula was generated in our model, but it presented an enlarged volume. This alteration was due to an increment in habenular neuroblasts proliferation rate. The fasciculus retroflexus also presented a wider and disorganized distribution and a disturbed final trajectory toward its target. The mid-hindbrain territories that the tract must cross were miss-differentiated in our model. The specification of the habenula is Wnt1 independent. Nevertheless, it controls its precursors proliferation rate. Wnt1 expressed in the isthmic organizer is vital to induce the midbrain and rostral hindbrain territories. The alteration of these areas is responsible for the fasciculus retroflexus axons misroute.

The habenula clock influences response to a stressor

The response of an animal to a sensory stimulus depends on the nature of the stimulus and on expectations, which are mediated by spontaneous activity. Here, we ask how circadian variation in the expectation of danger, and thus the response to a potential threat, is controlled. We focus on the habenula, a mediator of threat response that functions by regulating neuromodulator release, and use zebrafish as the experimental system. Single cell transcriptomics indicates that multiple clock genes are expressed throughout the habenula, while quantitative in situ hybridization confirms that the clock oscillates. Two-photon calcium imaging indicates a circadian change in spontaneous activity of habenula neurons. To assess the role of this clock, a truncated clocka gene was specifically expressed in the habenula. This partially inhibited the clock, as shown by changes in per3 expression as well as altered day-night variation in dopamine, serotonin and acetylcholine levels. Behaviourally, anxiety-like responses evoked by an alarm pheromone were reduced. Circadian effects of the pheromone were disrupted, such that responses in the day resembled those at night. Behaviours that are regulated by the pineal clock and not triggered by stressors were unaffected. We suggest that the habenula clock regulates the expectation of danger, thus providing one mechanism for circadian change in the response to a stressor.

Choice of pre-processing pipeline influences clustering quality of scRNA-seq datasets

BACKGROUND

Single-cell RNA sequencing (scRNA-seq) has quickly become one of the most dominant techniques in modern transcriptome assessment. In particular, 10X Genomics' Chromium system, with its high throughput approach, turn key and thorough user guide made this cutting-edge technique accessible to many laboratories using diverse animal models. However, standard pre-processing, including the alignment and cell filtering pipelines might not be ideal for every organism or tissue. Here we applied an alternative strategy, based on the pseudoaligner kallisto, on twenty-two publicly available single cell sequencing datasets from a wide range of tissues of eight organisms and compared the results with the standard 10X Genomics' Cell Ranger pipeline.

RESULTS

In most of the tested samples, kallisto produced higher sequencing read alignment rates and total gene detection rates in comparison to Cell Ranger. Although datasets processed with Cell Ranger had higher cell counts, outside of human and mouse datasets, these additional cells were routinely of low quality, containing low gene detection rates. Thorough downstream analysis of one kallisto processed dataset, obtained from the zebrafish pineal gland, revealed clearer clustering, allowing the identification of an additional photoreceptor cell type that previously went undetected. The finding of the new cluster suggests that the photoreceptive pineal gland is essentially a bi-chromatic tissue containing both green and red cone-like photoreceptors and implies that the alignment and pre-processing pipeline can affect the discovery of biologically-relevant cell types.

CONCLUSION

While Cell Ranger favors higher cell numbers, using kallisto results in datasets with higher median gene detection per cell. We could demonstrate that cell type identification was not hampered by the lower cell count, but in fact improved as a result of the high gene detection rate and the more stringent filtering. Depending on the acquired dataset, it can be beneficial to favor high quality cells and accept a lower cell count, leading to an improved classification of cell types.

Ongoing habenular activity is driven by forebrain networks and modulated by olfactory stimuli

Ongoing neural activity, which represents internal brain states, is constantly modulated by the sensory information that is generated by the environment. In this study, we show that the habenular circuits act as a major brain hub integrating the structured ongoing activity of the limbic forebrain circuitry and the olfactory information. We demonstrate that ancestral homologs of amygdala and hippocampus in zebrafish forebrain are the major drivers of ongoing habenular activity. We also reveal that odor stimuli can modulate the activity of specific habenular neurons that are driven by this forebrain circuitry. Our results highlight a major role for the olfactory system in regulating the ongoing activity of the habenula and the forebrain, thereby altering brain's internal states.

Single-cell deconstruction of stem-cell-driven schistosome development

Schistosomes cause one of the most devastating neglected tropical diseases, schistosomiasis. Their transmission is accomplished through a complex life cycle with two obligate hosts and requires multiple radically different body plans specialized for infecting and reproducing in each host. Recent single-cell transcriptomic studies on several schistosome body plans provide a comprehensive map of their cell types, which include stem cells and their differentiated progeny along an intricate developmental hierarchy. This progress not only extends our understanding of the basic biology of the schistosome life cycle but can also inform new therapeutic and preventive strategies against the disease, as blocking the development of specific cell types through genetic manipulations has shown promise in inhibiting parasite survival, growth, and reproduction.

DRscDB: A single-cell RNA-seq resource for data mining and data comparison across species

With the advent of single-cell RNA sequencing (scRNA-seq) technologies, there has been a spike in studies involving scRNA-seq of several tissues across diverse species including Drosophila. Although a few databases exist for users to query genes of interest within the scRNA-seq studies, search tools that enable users to find orthologous genes and their cell type-specific expression patterns across species are limited. Here, we built a new search database, DRscDB (https://www.flyrnai.org/tools/single_cell/web/), to address this need. DRscDB serves as a comprehensive repository for published scRNA-seq datasets for Drosophila and relevant datasets from human and other model organisms. DRscDB is based on manual curation of Drosophila scRNA-seq studies of various tissue types and their corresponding analogous tissues in vertebrates including zebrafish, mouse, and human. Of note, our search database provides most of the literature-derived marker genes, thus preserving the original analysis of the published scRNA-seq datasets. Finally, DRscDB serves as a web-based user interface that allows users to mine gene expression data from scRNA-seq studies and perform cell cluster enrichment analyses pertaining to various scRNA-seq studies, both within and across species.

DEEPsc: A Deep Learning-Based Map Connecting Single-Cell Transcriptomics and Spatial Imaging Data

Single-cell RNA sequencing (scRNA-seq) data provides unprecedented information on cell fate decisions; however, the spatial arrangement of cells is often lost. Several recent computational methods have been developed to impute spatial information onto a scRNA-seq dataset through analyzing known spatial expression patterns of a small subset of genes known as a reference atlas. However, there is a lack of comprehensive analysis of the accuracy, precision, and robustness of the mappings, along with the generalizability of these methods, which are often designed for specific systems. We present a system-adaptive deep learning-based method (DEEPsc) to impute spatial information onto a scRNA-seq dataset from a given spatial reference atlas. By introducing a comprehensive set of metrics that evaluate the spatial mapping methods, we compare DEEPsc with four existing methods on four biological systems. We find that while DEEPsc has comparable accuracy to other methods, an improved balance between precision and robustness is achieved. DEEPsc provides a data-adaptive tool to connect scRNA-seq datasets and spatial imaging datasets to analyze cell fate decisions. Our implementation with a uniform API can serve as a portal with access to all the methods investigated in this work for spatial exploration of cell fate decisions in scRNA-seq data. All methods evaluated in this work are implemented as an open-source software with a uniform interface.

Habenula GPR139 is associated with fear learning in the zebrafish

G-protein coupled receptor 139 (GPR139) is an evolutionarily conserved orphan receptor, predominantly expressing in the habenula of vertebrate species. The habenula has recently been implicated in aversive response and its associated learning. Here, we tested the hypothesis that GPR139 signalling in the habenula may play a role in fear learning in the zebrafish. We examined the effect of intraperitoneal injections of a human GPR139-selective agonist (JNJ-63533054) on alarm substance-induced fear learning using conditioned place avoidance paradigm, where an aversive stimulus is paired with one compartment, while its absence is associated with the other compartment of the apparatus. The results indicate that fish treated with 1 µg/g body weight of GPR139 agonist displayed no difference in locomotor activity and alarm substance-induced fear response. However, avoidance to fear-conditioned compartment was diminished, which suggests that the agonist blocks the consolidation of contextual fear memory. On the other hand, fish treated with 0.1 µg/g body weight of GPR139 agonist spent a significantly longer time in the unconditioned neutral compartment as compared to the conditioned (punished and unpunished) compartments. These results suggest that activation of GPR139 signalling in the habenula may be involved in fear learning and the decision-making process in the zebrafish.

Zebrafish Tools for Deciphering Habenular Network-Linked Mental Disorders

Simple Summary

Everything that we think, feel or do depends on the function of neural networks in the brain. These are highly complex structures made of cells (neurons) and their interconnections (axons), which develop dependent on precisely coordinated interactions of genes. Any gene mutation can result in unwanted alterations in neural network formation and concomitant brain disorders. The habenula neural network is one of these important circuits, which has been linked to autism, schizophrenia, depression and bipolar disorder. Studies using the zebrafish have uncovered genes involved in the development of this network. Intriguingly, some of these genes have also been identified as risk genes of human brain disorders highlighting the power of this animal model to link risk genes and the affected network to human disease. But can we use the advantages of this model to identify new targets and compounds with ameliorating effects on brain dysfunction? In this review, we summarise the current knowledge on techniques to manipulate the habenula neural network to study the consequences on behavior. Moreover, we give an overview of existing behavioral test to mimic aspects of mental disorders and critically discuss the applicability of the zebrafish model in this field of research.

Abstract

The prevalence of patients suffering from mental disorders is substantially increasing in recent years and represents a major burden to society. The underlying causes and neuronal circuits affected are complex and difficult to unravel. Frequent disorders such as depression, schizophrenia, autism, and bipolar disorder share links to the habenular neural circuit. This conserved neurotransmitter system relays cognitive information between different brain areas steering behaviors ranging from fear and anxiety to reward, sleep, and social behaviors. Advances in the field using the zebrafish model organism have uncovered major genetic mechanisms underlying the formation of the habenular neural circuit. Some of the identified genes involved in regulating Wnt/beta-catenin signaling have previously been suggested as risk genes of human mental disorders. Hence, these studies on habenular genetics contribute to a better understanding of brain diseases. We are here summarizing how the gained knowledge on the mechanisms underlying habenular neural circuit development can be used to introduce defined manipulations into the system to study the functional behavioral consequences. We further give an overview of existing behavior assays to address phenotypes related to mental disorders and critically discuss the power but also the limits of the zebrafish model for identifying suitable targets to develop therapies.

Molecular classification of zebrafish retinal ganglion cells links genes to cell types to behavior

Retinal ganglion cells (RGCs) form an array of feature detectors, which convey visual information to central brain regions. Characterizing RGC diversity is required to understand the logic of the underlying functional segregation. Using single-cell transcriptomics, we systematically classified RGCs in adult and larval zebrafish, thereby identifying marker genes for >30 mature types and several developmental intermediates. We used this dataset to engineer transgenic driver lines, enabling specific experimental access to a subset of RGC types. Expression of one or few transcription factors often predicts dendrite morphologies and axonal projections to specific tectal layers and extratectal targets. In vivo calcium imaging revealed that molecularly defined RGCs exhibit specific functional tuning. Finally, chemogenetic ablation of eomesa+ RGCs, which comprise melanopsin-expressing types with projections to a small subset of central targets, selectively impaired phototaxis. Together, our study establishes a framework for systematically studying the functional architecture of the visual system.

Habenula as the experience-dependent controlling switchboard of behavior and attention in social conflict and learning

The habenula is among the evolutionarily most conserved parts of the brain and has been known for its role in the control of behavior to cope with aversive stimuli. Recent studies in zebrafish have revealed the novel roles of the two parallel neural pathways from the dorsal habenula to its target, the interpeduncular nucleus, in the control of behavioral choice whether to behave dominantly or submissively in the social conflict. They are modifiable depending on the internal state of the fish such as hunger and play another important role in orientation of attention whether to direct it internally to oneself or externally to others. These studies, therefore, are revealing a novel role for the habenula as the integrated switchboard for concertedly controlling behavior either as a winner with self-centered (idiothetic) attention or a loser with others-oriented (allothetic) attention.

A cell atlas of the chick retina based on single-cell transcriptomics

Retinal structure and function have been studied in many vertebrate orders, but molecular characterization has been largely confined to mammals. We used single-cell RNA sequencing (scRNA-seq) to generate a cell atlas of the chick retina. We identified 136 cell types plus 14 positional or developmental intermediates distributed among the six classes conserved across vertebrates - photoreceptor, horizontal, bipolar, amacrine, retinal ganglion, and glial cells. To assess morphology of molecularly defined types, we adapted a method for CRISPR-based integration of reporters into selectively expressed genes. For Müller glia, we found that transcriptionally distinct cells were regionally localized along the anterior-posterior, dorsal-ventral, and central-peripheral retinal axes. We also identified immature photoreceptor, horizontal cell, and oligodendrocyte types that persist into late embryonic stages. Finally, we analyzed relationships among chick, mouse, and primate retinal cell classes and types. Our results provide a foundation for anatomical, physiological, evolutionary, and developmental studies of the avian visual system.

The landscape of regulatory genes in brain-wide neuronal phenotypes of a vertebrate brain

Multidimensional landscapes of regulatory genes in neuronal phenotypes at whole-brain levels in the vertebrate remain elusive. We generated single-cell transcriptomes of ~67,000 region- and neurotransmitter/neuromodulator-identifiable cells from larval zebrafish brains. Hierarchical clustering based on effector gene profiles ('terminal features') distinguished major brain cell types. Sister clusters at hierarchical termini displayed similar terminal features. It was further verified by a population-level statistical method. Intriguingly, glutamatergic/GABAergic sister clusters mostly expressed distinct transcription factor (TF) profiles ('convergent pattern'), whereas neuromodulator-type sister clusters predominantly expressed the same TF profiles ('matched pattern'). Interestingly, glutamatergic/GABAergic clusters with similar TF profiles could also display different terminal features ('divergent pattern'). It led us to identify a library of RNA-binding proteins that differentially marked divergent pair clusters, suggesting the post-transcriptional regulation of neuron diversification. Thus, our findings reveal multidimensional landscapes of transcriptional and post-transcriptional regulators in whole-brain neuronal phenotypes in the zebrafish brain.