Mapping the transcriptional diversity of genetically and anatomically defined cell populations in the mouse brain

Neurogenesis in Caenorhabditis elegans

Animals rely on their nervous systems to process sensory inputs, integrate these with internal signals, and produce behavioral outputs. This is enabled by the highly specialized morphologies and functions of neurons. Neuronal cells share multiple structural and physiological features, but they also come in a large diversity of types or classes that give the nervous system its broad range of functions and plasticity. This diversity, first recognized over a century ago, spurred classification efforts based on morphology, function, and molecular criteria. Caenorhabditis elegans, with its precisely mapped nervous system at the anatomical level, an extensive molecular description of most of its neurons, and its genetic amenability, has been a prime model for understanding how neurons develop and diversify at a mechanistic level. Here, we review the gene regulatory mechanisms driving neurogenesis and the diversification of neuron classes and subclasses in C. elegans. We discuss our current understanding of the specification of neuronal progenitors and their differentiation in terms of the transcription factors involved and ensuing changes in gene expression and chromatin landscape. The central theme that has emerged is that the identity of a neuron is defined by modules of gene batteries that are under control of parallel yet interconnected regulatory mechanisms. We focus on how, to achieve these terminal identities, cells integrate information along their developmental lineages. Moreover, we discuss how neurons are diversified postembryonically in a time-, genetic sex-, and activity-dependent manner. Finally, we discuss how the understanding of neuronal development can provide insights into the evolution of neuronal diversity.

Making Ramón y Cajal proud: Development of cell identity and diversity in the cerebral cortex

Since the beautiful images of Santiago Ramón y Cajal provided a first glimpse into the immense diversity and complexity of cell types found in the cerebral cortex, neuroscience has been challenged and inspired to understand how these diverse cells are generated and how they interact with each other to orchestrate the development of this remarkable tissue. Some fundamental questions drive the field's quest to understand cortical development: what are the mechanistic principles that govern the emergence of neuronal diversity? How do extrinsic and intrinsic signals integrate with physical forces and activity to shape cell identity? How do the diverse populations of neurons and glia influence each other during development to guarantee proper integration and function? The advent of powerful new technologies to profile and perturb cortical development at unprecedented resolution and across a variety of modalities has offered a new opportunity to integrate past knowledge with brand new data. Here, we review some of this progress using cortical excitatory projection neurons as a system to draw out general principles of cell diversification and the role of cell-cell interactions during cortical development.

Evo-devo applied to sleep research: an approach whose time has come

Sleep occurs in all animals but its amount, form, and timing vary considerably between species and between individuals. Currently, little is known about the basis for these differences, in part, because we lack a complete understanding of the brain circuitry controlling sleep-wake states and markers for the cell types which can identify similar circuits across phylogeny. Here, I explain the utility of an "Evo-devo" approach for comparative studies of sleep regulation and function as well as for sleep medicine. This approach focuses on the regulation of evolutionary ancient transcription factors which act as master controllers of cell-type specification. Studying these developmental transcription factor cascades can identify novel cell clusters which control sleep and wakefulness, reveal the mechanisms which control differences in sleep timing, amount, and expression, and identify the timepoint in evolution when different sleep-wake control neurons appeared. Spatial transcriptomic studies, which identify cell clusters based on transcription factor expression, will greatly aid this approach. Conserved developmental pathways regulate sleep in mice, Drosophila, and C. elegans. Members of the LIM Homeobox (Lhx) gene family control the specification of sleep and circadian neurons in the forebrain and hypothalamus. Increased Lhx9 activity may account for increased orexin/hypocretin neurons and reduced sleep in Mexican cavefish. Other transcription factor families specify sleep-wake circuits in the brainstem, hypothalamus, and basal forebrain. The expression of transcription factors allows the generation of specific cell types for transplantation approaches. Furthermore, mutations in developmental transcription factors are linked to variation in sleep duration in humans, risk for restless legs syndrome, and sleep-disordered breathing. This paper is part of the "Genetic and other molecular underpinnings of sleep, sleep disorders, and circadian rhythms including translational approaches" collection.

40 years of homeodomain transcription factors in the Drosophila nervous system

Drosophila nervous system development progresses through a series of well-characterized steps in which homeodomain transcription factors (HDTFs) play key roles during most, if not all, phases. Strikingly, although some HDTFs have only one role, many others are involved in multiple steps of the developmental process. Most Drosophila HDTFs engaged in nervous system development are conserved in vertebrates and often play similar roles during vertebrate development. In this Spotlight, we focus on the role of HDTFs during embryogenesis, where they were first characterized.

DeepDecon accurately estimates cancer cell fractions in bulk RNA-seq data

Understanding the cellular composition of a disease-related tissue is important in disease diagnosis, prognosis, and downstream treatment. Recent advances in single-cell RNA-sequencing (scRNA-seq) technique have allowed the measurement of gene expression profiles for individual cells. However, scRNA-seq is still too expensive to be used for large-scale population studies, and bulk RNA-seq is still widely used in such situations. An essential challenge is to deconvolve cellular composition for bulk RNA-seq data based on scRNA-seq data. Here, we present DeepDecon, a deep neural network model that leverages single-cell gene expression information to accurately predict the fraction of cancer cells in bulk tissues. It provides a refining strategy in which the cancer cell fraction is iteratively estimated by a set of trained models. When applied to simulated and real cancer data, DeepDecon exhibits superior performance compared to existing decomposition methods in terms of accuracy.

Parallel gene size and isoform expansion of ancient neuronal genes

How nervous systems evolved is a central question in biology. A diversity of synaptic proteins is thought to play a central role in the formation of specific synapses leading to nervous system complexity. The largest animal genes, often spanning hundreds of thousands of base pairs, are known to be enriched for expression in neurons at synapses and are frequently mutated or misregulated in neurological disorders and diseases. Although many of these genes have been studied independently in the context of nervous system evolution and disease, general principles underlying their parallel evolution remain unknown. To investigate this, we directly compared orthologous gene sizes across eukaryotes. By comparing relative gene sizes within organisms, we identified a distinct class of large genes with origins predating the diversification of animals and, in many cases, the emergence of neurons as dedicated cell types. We traced this class of ancient large genes through evolution and found orthologs of the large synaptic genes potentially driving the immense complexity of metazoan nervous systems, including in humans and cephalopods. Moreover, we found that while these genes are evolving under strong purifying selection, as demonstrated by low dN/dS ratios, they have simultaneously grown larger and gained the most isoforms in animals. This work provides a new lens through which to view this distinctive class of large and multi-isoform genes and demonstrates how intrinsic genomic properties, such as gene length, can provide flexibility in molecular evolution and allow groups of genes and their host organisms to evolve toward complexity.

Neuronal Spike Shapes (NSS): A straightforward approach to investigate heterogeneity in neuronal excitability states

The mammalian brain exhibits a remarkable diversity of neurons, contributing to its intricate architecture and functional complexity. The analysis of multimodal single-cell datasets enables the investigation of cell types and states heterogeneity. In this study, we introduce the Neuronal Spike Shapes (NSS), a straightforward approach for the exploration of excitability states of neurons based on their Action Potential (AP) waveforms. The NSS method describes the AP waveform based on a triangular representation complemented by a set of derived electrophysiological (EP) features. To support this hypothesis, we validate the proposed approach on two datasets of murine cortical neurons, focusing it on GABAergic neurons. The validation process involves a combination of NSS-based clustering analysis, features exploration, Differential Expression (DE), and Gene Ontology (GO) enrichment analysis. Results show that the NSS-based analysis captures neuronal excitability states that possess biological relevance independently of cell subtype. In particular, Neuronal Spike Shapes (NSS) captures, among others, a well-characterized fast-spiking excitability state, supported by both electrophysiological and transcriptomic validation. Gene Ontology Enrichment Analysis reveals voltage-gated potassium (K+) channels as specific markers of the identified NSS partitions. This finding strongly corroborates the biological relevance of NSS partitions as excitability states, as the expression of voltage-gated K+ channels regulates the hyperpolarization phase of the AP, being directly implicated in the regulation of neuronal excitability.

Neurosecretory Protein GM-Expressing Neurons Participate in Lipid Storage and Inflammation in Newly Developed Cre Driver Male Mice

Obesity induces inflammation in the hypothalamus and adipose tissue, resulting in metabolic disorders. A novel hypothalamic neuropeptide, neurosecretory protein GM (NPGM), was previously identified in the hypothalamus of vertebrates. While NPGM plays an important role in lipid metabolism in chicks, its metabolic regulatory effects in mammals remain unclear. In this study, a novel Cre driver line, NPGM-Cre, was generated for cell-specific manipulation. Cre-dependent overexpression of Npgm led to fat accumulation without increased food consumption in male NPGM-Cre mice. Chemogenetic activation of NPGM neurons in the hypothalamus acutely promoted feeding behavior and chronically resulted in a transient increase in body mass gain. Furthermore, the ablated NPGM neurons exhibited a tendency to be glucose intolerant, with infiltration of proinflammatory macrophages into the adipose tissue. These results suggest that NPGM neurons may regulate lipid storage and inflammatory responses, thereby maintaining glucose homeostasis.

Cell-type specific molecular architecture for mu opioid receptor function in pain and addiction circuits

Opioids are potent analgesics broadly used for pain management; however, they can produce dangerous side effects including addiction and respiratory depression. These harmful effects have led to an epidemic of opioid abuse and overdose deaths, creating an urgent need for the development of both safer pain medications and treatments for opioid use disorders. Both the analgesic and addictive properties of opioids are mediated by the mu opioid receptor (MOR), making resolution of the cell types and neural circuits responsible for each of the effects of opioids a critical research goal. Single-cell RNA sequencing (scRNA-seq) technology is enabling the identification of MOR-expressing cell types throughout the nervous system, creating new opportunities for mapping distinct opioid effects onto newly discovered cell types. Here, we describe molecularly defined MOR-expressing neuronal cell types throughout the peripheral and central nervous systems and their potential contributions to opioid analgesia and addiction.

Silc1 long noncoding RNA is an immediate-early gene promoting efficient memory formation

Long noncoding RNAs (lncRNAs) are expressed in many brain circuits and types of neurons; nevertheless, their functional significance for normal brain functions remains elusive. Here, we study the functions in the central nervous system of Silc1, an lncRNA we have shown previously to be important for neuronal regeneration in the peripheral nervous system. We found that Silc1 is rapidly and strongly induced in the hippocampus upon exposure to novelty and is required for efficient spatial learning. Silc1 production is important for induction of Sox11 (its cis-regulated target gene) throughout the CA1-CA3 regions and proper expression of key Sox11 target genes. Consistent with its role in neuronal plasticity, Silc1 levels decline during aging and in models of Alzheimer's disease. Overall, we describe a plasticity pathway in which Silc1 acts as an immediate-early gene to activate Sox11 and induce a neuronal growth-associated transcriptional program important for learning.

Spatial transcriptomics in neuroscience

The brain is one of the most complex living tissue types and is composed of an exceptional diversity of cell types displaying unique functional connectivity. Single-cell RNA sequencing (scRNA-seq) can be used to efficiently map the molecular identities of the various cell types in the brain by providing the transcriptomic profiles of individual cells isolated from the tissue. However, the lack of spatial context in scRNA-seq prevents a comprehensive understanding of how different configurations of cell types give rise to specific functions in individual brain regions and how each distinct cell is connected to form a functional unit. To understand how the various cell types contribute to specific brain functions, it is crucial to correlate the identities of individual cells obtained through scRNA-seq with their spatial information in intact tissue. Spatial transcriptomics (ST) can resolve the complex spatial organization of cell types in the brain and their connectivity. Various ST tools developed during the past decade based on imaging and sequencing technology have permitted the creation of functional atlases of the brain and have pulled the properties of neural circuits into ever-sharper focus. In this review, we present a summary of several ST tools and their applications in neuroscience and discuss the unprecedented insights these tools have made possible.

Ancient origins of complex neuronal genes

How nervous systems evolved is a central question in biology. An increasing diversity of synaptic proteins is thought to play a central role in the formation of specific synapses leading to nervous system complexity. The largest animal genes, often spanning millions of base pairs, are known to be enriched for expression in neurons at synapses and are frequently mutated or misregulated in neurological disorders and diseases. While many of these genes have been studied independently in the context of nervous system evolution and disease, general principles underlying their parallel evolution remain unknown. To investigate this, we directly compared orthologous gene sizes across eukaryotes. By comparing relative gene sizes within organisms, we identified a distinct class of large genes with origins predating the diversification of animals and in many cases the emergence of dedicated neuronal cell types. We traced this class of ancient large genes through evolution and found orthologs of the large synaptic genes driving the immense complexity of metazoan nervous systems, including in humans and cephalopods. Moreover, we found that while these genes are evolving under strong purifying selection as demonstrated by low dN/dS scores, they have simultaneously grown larger and gained the most isoforms in animals. This work provides a new lens through which to view this distinctive class of large and multi-isoform genes and demonstrates how intrinsic genomic properties, such as gene length, can provide flexibility in molecular evolution and allow groups of genes and their host organisms to evolve toward complexity.

Neuro-Vulnerability in Energy Metabolism Regulation: A Comprehensive Narrative Review

This comprehensive narrative review explores the concept of neuro-vulnerability in energy metabolism regulation and its implications for metabolic disorders. The review highlights the complex interactions among the neural, hormonal, and metabolic pathways involved in the regulation of energy metabolism. The key topics discussed include the role of organs, hormones, and neural circuits in maintaining metabolic balance. The review investigates the association between neuro-vulnerability and metabolic disorders, such as obesity, insulin resistance, and eating disorders, considering genetic, epigenetic, and environmental factors that influence neuro-vulnerability and subsequent metabolic dysregulation. Neuroendocrine interactions and the neural regulation of food intake and energy expenditure are examined, with a focus on the impact of neuro-vulnerability on appetite dysregulation and altered energy expenditure. The role of neuroinflammation in metabolic health and neuro-vulnerability is discussed, emphasizing the bidirectional relationship between metabolic dysregulation and neuroinflammatory processes. This review also evaluates the use of neuroimaging techniques in studying neuro-vulnerability and their potential applications in clinical settings. Furthermore, the association between neuro-vulnerability and eating disorders, as well as its contribution to obesity, is examined. Potential therapeutic interventions targeting neuro-vulnerability, including pharmacological treatments and lifestyle modifications, are reviewed. In conclusion, understanding the concept of neuro-vulnerability in energy metabolism regulation is crucial for addressing metabolic disorders. This review provides valuable insights into the underlying neurobiological mechanisms and their implications for metabolic health. Targeting neuro-vulnerability holds promise for developing innovative strategies in the prevention and treatment of metabolic disorders, ultimately improving metabolic health outcomes.

Profiling mouse brown and white adipocytes to identify metabolically relevant small ORFs and functional microproteins

Microproteins (MPs) are a potentially rich source of uncharacterized metabolic regulators. Here, we use ribosome profiling (Ribo-seq) to curate 3,877 unannotated MP-encoding small ORFs (smORFs) in primary brown, white, and beige mouse adipocytes. Of these, we validated 85 MPs by proteomics, including 33 circulating MPs in mouse plasma. Analyses of MP-encoding mRNAs under different physiological conditions (high-fat diet) revealed that numerous MPs are regulated in adipose tissue in vivo and are co-expressed with established metabolic genes. Furthermore, Ribo-seq provided evidence for the translation of Gm8773, which encodes a secreted MP that is homologous to human and chicken FAM237B. Gm8773 is highly expressed in the arcuate nucleus of the hypothalamus, and intracerebroventricular administration of recombinant mFAM237B showed orexigenic activity in obese mice. Together, these data highlight the value of this adipocyte MP database in identifying MPs with roles in fundamental metabolic and physiological processes such as feeding.

The implication of a diversity of non-neuronal cells in disorders affecting brain networks

In the central nervous system (CNS) neurons are classically considered the functional unit of the brain. Analysis of the physical connections and co-activation of neurons, referred to as structural and functional connectivity, respectively, is a metric used to understand their interplay at a higher level. A myriad of glial cell types throughout the brain composed of microglia, astrocytes and oligodendrocytes are key players in the maintenance and regulation of neuronal network dynamics. Microglia are the central immune cells of the CNS, able to affect neuronal populations in number and connectivity, allowing for maturation and plasticity of the CNS. Microglia and astrocytes are part of the neurovascular unit, and together they are essential to protect and supply nutrients to the CNS. Oligodendrocytes are known for their canonical role in axonal myelination, but also contribute, with microglia and astrocytes, to CNS energy metabolism. Glial cells can achieve this variety of roles because of their heterogeneous populations comprised of different states. The neuroglial relationship can be compromised in various manners in case of pathologies affecting development and plasticity of the CNS, but also consciousness and mood. This review covers structural and functional connectivity alterations in schizophrenia, major depressive disorder, and disorder of consciousness, as well as their correlation with vascular connectivity. These networks are further explored at the cellular scale by integrating the role of glial cell diversity across the CNS to explain how these networks are affected in pathology.

A conserved transcriptional fingerprint of multi-neurotransmitter neurons necessary for social behavior

Background

An essential determinant of a neuron’s functionality is its neurotransmitter phenotype. We previously identified a defined subpopulation of cholinergic neurons required for social orienting behavior in zebrafish.

Results

We transcriptionally profiled these neurons and discovered that they are capable of synthesizing both acetylcholine and GABA. We also established a constellation of transcription factors and neurotransmitter markers that can be used as a “transcriptomic fingerprint” to recognize a homologous neuronal population in another vertebrate.

Conclusion

Our results suggest that this transcriptomic fingerprint and the cholinergic-GABAergic neuronal subtype that it defines are evolutionarily conserved.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08879-w.

Boolean implication analysis of single-cell data predicts retinal cell type markers

Background

The retina is a complex tissue containing multiple cell types that are essential for vision. Understanding the gene expression patterns of various retinal cell types has potential applications in regenerative medicine. Retinal organoids (optic vesicles) derived from pluripotent stem cells have begun to yield insights into the transcriptomics of developing retinal cell types in humans through single cell RNA-sequencing studies. Previous methods of gene reporting have relied upon techniques in vivo using microarray data, or correlational and dimension reduction methods for analyzing single cell RNA-sequencing data computationally. We aimed to develop a state-of-the-art Boolean method that filtered out noise, could be applied to a wide variety of datasets and lent insight into gene expression over differentiation.

Results

Here, we present a bioinformatic approach using Boolean implication to discover genes which are retinal cell type-specific or involved in retinal cell fate. We apply this approach to previously published retina and retinal organoid datasets and improve upon previously published correlational methods. Our method improves the prediction accuracy of marker genes of retinal cell types and discovers several new high confidence cone and rod-specific genes.

Conclusions

The results of this study demonstrate the benefits of a Boolean approach that considers asymmetric relationships. We have shown a statistically significant improvement from correlational, symmetric methods in the prediction accuracy of retinal cell-type specific genes.

Furthermore, our method contains no cell or tissue-specific tuning and hence could impact other areas of gene expression analyses in cancer and other human diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04915-4.

Meso-seq for in-depth transcriptomics in ultra-low amounts of FACS-purified neuronal nuclei

Profiling of gene expression in sparse populations of genetically defined neurons is essential for dissecting the molecular mechanisms that control the development and plasticity of neural circuits. However, current transcriptomic approaches are ill suited for detailed mechanistic studies in sparse neuronal populations, as they either are technically complex and relatively expensive (e.g., single-cell RNA sequencing [RNA-seq]) or require large amounts of input material (e.g., traditional bulk RNA-seq). Thus, we established Meso-seq, a meso-scale protocol for identifying more than 10,000 robustly expressed genes in as little as 50 FACS-sorted neuronal nuclei. We demonstrate that Meso-seq works well for multiple neuroscience applications, including transcriptomics in antibody-labeled cortical neurons in mice and non-human primates, analyses of experience-regulated gene programs, and RNA-seq from visual cortex neurons labeled ultra-sparsely with viruses. Given its simplicity, robustness, and relatively low costs, Meso-seq is well suited for molecular-mechanistic studies in ultra-sparse neuronal populations in the brain.

RNA and neuronal function: the importance of post-transcriptional regulation

The brain represents an organ with a particularly high diversity of genes that undergo post-transcriptional gene regulation through multiple mechanisms that affect RNA metabolism and, consequently, brain function. This vast regulatory process in the brain allows for a tight spatiotemporal control over protein expression, a necessary factor due to the unique morphologies of neurons. The numerous mechanisms of post-transcriptional regulation or translational control of gene expression in the brain include alternative splicing, RNA editing, mRNA stability and transport. A large number of trans-elements such as RNA-binding proteins and micro RNAs bind to specific cis-elements on transcripts to dictate the fate of mRNAs including its stability, localization, activation and degradation. Several trans-elements are exemplary regulators of translation, employing multiple cofactors and regulatory machinery so as to influence mRNA fate. Networks of regulatory trans-elements exert control over key neuronal processes such as neurogenesis, synaptic transmission and plasticity. Perturbations in these networks may directly or indirectly cause neuropsychiatric and neurodegenerative disorders. We will be reviewing multiple mechanisms of gene regulation by trans-elements occurring specifically in neurons.

Dietary emulsifier consumption alters gene expression in the amygdala and paraventricular nucleus of the hypothalamus in mice

Dietary emulsifier consumption promotes systemic low-grade inflammation, metabolic deregulation, and possibly an anxiety-like phenotype. The latter finding suggests that dietary emulsifiers impact brain areas that modulate stress responses. The goal of the current study was to test whether emulsifier consumption is associated with changes in gene expression in the amygdala and the paraventricular nucleus of the hypothalamus (PVN), two brain areas that are involved in behavioral and neuroendocrine responses to stress. Using RNA-Seq, we compared groups consuming either carboxymethylcellulose or polysorbate 80 for 12-weeks. A total of 243 genes were differentially expressed in the amygdala and PVN of emulsifier-treated mice compared to controls. There was minimal overlap of differentially expressed genes in CMC- and P80-treated animals, suggesting that each emulsifier acts via distinct molecular mechanisms to produce an anxiety-like phenotype. Furthermore, gene ontology and pathway analysis revealed that various stress, metabolic, and immune terms and pathways were altered by emulsifiers. These findings are the first to demonstrate that emulsifier consumption changes gene expression in brain regions that are critical for stress responding, providing possible molecular mechanisms that may underly the previously observed anxiety-like phenotype.

Single‐cell RNA sequencing of motoneurons identifies regulators of synaptic wiring in Drosophila embryos

The correct wiring of neuronal circuits is one of the most complex processes in development, since axons form highly specific connections out of a vast number of possibilities. Circuit structure is genetically determined in vertebrates and invertebrates, but the mechanisms guiding each axon to precisely innervate a unique pre‐specified target cell are poorly understood. We investigated Drosophila embryonic motoneurons using single‐cell genomics, imaging, and genetics. We show that a cell‐specific combination of homeodomain transcription factors and downstream immunoglobulin domain proteins is expressed in individual cells and plays an important role in determining cell‐specific connections between differentiated motoneurons and target muscles. We provide genetic evidence for a functional role of five homeodomain transcription factors and four immunoglobulins in the neuromuscular wiring. Knockdown and ectopic expression of these homeodomain transcription factors induces cell‐specific synaptic wiring defects that are partly phenocopied by genetic modulations of their immunoglobulin targets. Taken together, our data suggest that homeodomain transcription factor and immunoglobulin molecule expression could be directly linked and function as a crucial determinant of neuronal circuit structure.

p53-mediated neurodegeneration in the absence of the nuclear protein Akirin2

Proper gene regulation is critical for both neuronal development and maintenance as the brain matures. We previously demonstrated that Akirin2, an essential nuclear protein that interacts with transcription factors and chromatin remodeling complexes, is required for the embryonic formation of the cerebral cortex. Here we show that Akirin2 plays a mechanistically distinct role in maintaining healthy neurons during cortical maturation. Restricting Akirin2 loss to excitatory cortical neurons resulted in progressive neurodegeneration via necroptosis and severe cortical atrophy with age. Comparing transcriptomes from Akirin2-null postnatal neurons and cortical progenitors revealed that targets of the tumor suppressor p53, a regulator of both proliferation and cell death encoded by Trp53, were consistently upregulated. Reduction of Trp53 rescued neurodegeneration in Akirin2-null neurons. These data: (1) implicate Akirin2 as a critical neuronal maintenance protein, (2) identify p53 pathways as mediators of Akirin2 functions, and (3) suggest Akirin2 dysfunction may be relevant to neurodegenerative diseases.

An expansion of the non-coding genome and its regulatory potential underlies vertebrate neuronal diversity

Proper assembly and function of the nervous system requires the generation of a uniquely diverse population of neurons expressing a cell-type-specific combination of effector genes that collectively define neuronal morphology, connectivity, and function. How countless partially overlapping but cell-type-specific patterns of gene expression are controlled at the genomic level remains poorly understood. Here we show that neuronal genes are associated with highly complex gene regulatory systems composed of independent cell-type- and cell-stage-specific regulatory elements that reside in expanded non-coding genomic domains. Mapping enhancer-promoter interactions revealed that motor neuron enhancers are broadly distributed across the large chromatin domains. This distributed regulatory architecture is not a unique property of motor neurons but is employed throughout the nervous system. The number of regulatory elements increased dramatically during the transition from invertebrates to vertebrates, suggesting that acquisition of new enhancers might be a fundamental process underlying the evolutionary increase in cellular complexity.

Topoisomerase-Mediated DNA Damage in Neurological Disorders

The nervous system is vulnerable to genomic instability and mutations in DNA damage response factors lead to numerous developmental and progressive neurological disorders. Despite this, the sources and mechanisms of DNA damage that are most relevant to the development of neuronal dysfunction are poorly understood. The identification of primarily neurological abnormalities in patients with mutations in TDP1 and TDP2 suggest that topoisomerase-mediated DNA damage could be an important underlying source of neuronal dysfunction. Here we review the potential sources of topoisomerase-induced DNA damage in neurons, describe the cellular mechanisms that have evolved to repair such damage, and discuss the importance of these repair mechanisms for preventing neurological disorders.

Regulation of Axon Initial Segment Diameter by COUP-TFI Fine-tunes Action Potential Generation

The axon initial segment (AIS) is a specialized structure that controls neuronal excitability via action potential (AP) generation. Currently, AIS plasticity with regard to changes in length and location in response to neural activity has been extensively investigated, but how AIS diameter is regulated remains elusive. Here we report that COUP-TFI (chicken ovalbumin upstream promotor-transcription factor 1) is an essential regulator of AIS diameter in both developing and adult mouse neocortex. Either embryonic or adult ablation of COUP-TFI results in reduced AIS diameter and impaired AP generation. Although COUP-TFI ablations in sparse single neurons and in populations of neurons have similar impacts on AIS diameter and AP generation, they strengthen and weaken, respectively, the receiving spontaneous network in mutant neurons. In contrast, overexpression of COUP-TFI in sparse single neurons increases the AIS diameter and facilitates AP generation, but decreases the receiving spontaneous network. Our findings demonstrate that COUP-TFI is indispensable for both the expansion and maintenance of AIS diameter and that AIS diameter fine-tunes action potential generation and synaptic inputs in mammalian cortical neurons.

NuMorph: Tools for cortical cellular phenotyping in tissue-cleared whole-brain images

Tissue-clearing methods allow every cell in the mouse brain to be imaged without physical sectioning. However, the computational tools currently available for cell quantification in cleared tissue images have been limited to counting sparse cell populations in stereotypical mice. Here, we introduce NuMorph, a group of analysis tools to quantify all nuclei and nuclear markers within the mouse cortex after clearing and imaging by light-sheet microscopy. We apply NuMorph to investigate two distinct mouse models: a Topoisomerase 1 (Top1) model with severe neurodegenerative deficits and a Neurofibromin 1 (Nf1) model with a more subtle brain overgrowth phenotype. In each case, we identify differential effects of gene deletion on individual cell-type counts and distribution across cortical regions that manifest as alterations of gross brain morphology. These results underline the value of whole-brain imaging approaches, and the tools are widely applicable for studying brain structure phenotypes at cellular resolution.

Isoform cell-type specificity in the mouse primary motor cortex

Full-length SMART-seq1 single-cell RNA sequencing can be used to measure gene expression at isoform resolution, making possible the identification of specific isoform markers for different cell types. Used in conjunction with spatial RNA capture and gene-tagging methods, this enables the inference of spatially resolved isoform expression for different cell types. Here, in a comprehensive analysis of 6,160 mouse primary motor cortex cells assayed with SMART-seq, 280,327 cells assayed with MERFISH2 and 94,162 cells assayed with 10x Genomics sequencing3, we find examples of isoform specificity in cell types-including isoform shifts between cell types that are masked in gene-level analysis-as well as examples of transcriptional regulation. Additionally, we show that isoform specificity helps to refine cell types, and that a multi-platform analysis of single-cell transcriptomic data leveraging multiple measurements provides a comprehensive atlas of transcription in the mouse primary motor cortex that improves on the possibilities offered by any single technology.

Homeobox genes and the specification of neuronal identity

The enormous diversity of cell types that characterizes any animal nervous system is defined by neuron-type-specific gene batteries that endow cells with distinct anatomical and functional properties. To understand how such cellular diversity is genetically specified, one needs to understand the gene regulatory programmes that control the expression of cell-type-specific gene batteries. The small nervous system of the nematode Caenorhabditis elegans has been comprehensively mapped at the cellular and molecular levels, which has enabled extensive, nervous system-wide explorations into whether there are common underlying mechanisms that specify neuronal cell-type diversity. One principle that emerged from these studies is that transcription factors termed 'terminal selectors' coordinate the expression of individual members of neuron-type-specific gene batteries, thereby assigning unique identities to individual neuron types. Systematic mutant analyses and recent nervous system-wide expression analyses have revealed that one transcription factor family, the homeobox gene family, is broadly used throughout the entire C. elegans nervous system to specify neuronal identity as terminal selectors. I propose that the preponderance of homeobox genes in neuronal identity control is a reflection of an evolutionary trajectory in which an ancestral neuron type was specified by one or more ancestral homeobox genes, and that this functional linkage then duplicated and diversified to generate distinct cell types in an evolving nervous system.

Linking minimal and detailed models of CA1 microcircuits reveals how theta rhythms emerge and their frequencies controlled

The wide variety of cell types and their biophysical complexities pose a challenge in our ability to understand oscillatory activities produced by cellular-based computational network models. This challenge stems from their high-dimensional and multiparametric natures. To overcome this, we implement a solution by linking minimal and detailed models of CA1 microcircuits that generate intrahippocampal (3-12 Hz) theta rhythms. We leverage insights from minimal models to guide explorations of more detailed models and obtain a cellular perspective of theta generation. Our findings distinguish the pyramidal cells as the theta rhythm initiators and reveal that their activity is regularized by the inhibitory cell populations, supporting a proposed hypothesis of an "inhibition-based tuning" mechanism. We find a strong correlation between input current to the pyramidal cells and the resulting local field potential theta frequency, indicating that intrinsic pyramidal cell properties underpin network frequency characteristics. This work provides a cellular-based foundation from which in vivo theta activities can be explored.

Oligodendrocyte Secreted Factors Shape Hippocampal GABAergic Neuron Transcriptome and Physiology

Oligodendrocytes form myelin for central nervous system axons and release factors which signal to neurons during myelination. Here, we ask how oligodendroglial factors influence hippocampal GABAergic neuron physiology. In mixed hippocampal cultures, GABAergic neurons fired action potentials (APs) of short duration and received high frequencies of excitatory synaptic events. In purified neuronal cultures without glial cells, GABAergic neuron excitability increased and the frequency of synaptic events decreased. These effects were largely reversed by adding oligodendrocyte conditioned medium (OCM). We compared the transcriptomic signature with the electrophysiological phenotype of single neurons in these three culture conditions. Genes expressed by single pyramidal or GABAergic neurons largely conformed to expected cell-type specific patterns. Multiple genes of GABAergic neurons were significantly downregulated by the transition from mixed cultures containing glial cells to purified neuronal cultures. Levels of these genes were restored by the addition of OCM to purified cultures. Clustering genes with similar changes in expression between different culture conditions revealed processes affected by oligodendroglial factors. Enriched genes are linked to roles in synapse assembly, AP generation, and transmembrane ion transport, including of zinc. These results provide new insight into the molecular targets by which oligodendrocytes influence neuron excitability and synaptic function.

Single-cell molecular and developmental perspectives of sexually dimorphic circuits underlying innate social behaviors

While single-cell transcriptomics in the brain has uncovered a vast diversity of neural cell types in unprecedented detail, it is becoming increasingly urgent to address what exactly their functional roles are in the context of circuits and behavior. In this review, we discuss the molecular profiling of cell types in circuits underlying social behaviors in mice as a prominent case study. We first highlight key roles of molecularly identified sensory and downstream neurons involved in sexually dimorphic behaviors. We then propose future opportunities to define cell types using multimodal criteria, especially gene expression, physiology, as well as the developmental origin, to advance our understanding of these circuits.

Distinct Evolutionary Trajectories of Neuronal and Hair Cell Nicotinic Acetylcholine Receptors

The expansion and pruning of ion channel families has played a crucial role in the evolution of nervous systems. Nicotinic acetylcholine receptors (nAChRs) are ligand-gated ion channels with distinct roles in synaptic transmission at the neuromuscular junction, the central and peripheral nervous system, and the inner ear. Remarkably, the complement of nAChR subunits has been highly conserved along vertebrate phylogeny. To ask whether the different subtypes of receptors underwent different evolutionary trajectories, we performed a comprehensive analysis of vertebrate nAChRs coding sequences, mouse single-cell expression patterns, and comparative functional properties of receptors from three representative tetrapod species. We found significant differences between hair cell and neuronal receptors that were most likely shaped by the differences in coexpression patterns and coassembly rules of component subunits. Thus, neuronal nAChRs showed high degree of coding sequence conservation, coupled to greater coexpression variance and conservation of functional properties across tetrapod clades. In contrast, hair cell α9α10 nAChRs exhibited greater sequence divergence, narrow coexpression pattern, and great variability of functional properties across species. These results point to differential substrates for random change within the family of gene paralogs that relate to the segregated roles of nAChRs in synaptic transmission.

Activity labeling in vivo using CaMPARI2 reveals intrinsic and synaptic differences between neurons with high and low firing rate set points

Neocortical pyramidal neurons regulate firing around a stable mean firing rate (FR) that can differ by orders of magnitude between neurons, but the factors that determine where individual neurons sit within this broad FR distribution are not understood. To access low- and high-FR neurons for ex vivo analysis, we used Ca2+- and UV-dependent photoconversion of CaMPARI2 in vivo to permanently label neurons according to mean FR. CaMPARI2 photoconversion was correlated with immediate early gene expression and higher FRs ex vivo and tracked the drop and rebound in ensemble mean FR induced by prolonged monocular deprivation. High-activity L4 pyramidal neurons had greater intrinsic excitability and recurrent excitatory synaptic strength, while E/I ratio, local output strength, and local connection probability were not different. Thus, in L4 pyramidal neurons (considered a single transcriptional cell type), a broad mean FR distribution is achieved through graded differences in both intrinsic and synaptic properties.

Developmental mechanisms underlying circuit wiring: Novel insights and challenges ahead

Synaptic connectivity within neural circuits is characterized by high degrees of cellular and subcellular specificity. This precision arises from the combined action of several classes of molecular cues, transmembrane receptors, secreted cues and extracellular matrix components, coordinating transitions between axon guidance, dendrite patterning, axon branching and synapse specificity. We focus this review on recent insights into some of the molecular and cellular mechanisms controlling these transitions and present the results of large-scale efforts and technological developments aimed at mapping neural connectivity at single cell resolution in the mouse cortex as a mammalian model organism. Finally, we outline some of the technical and conceptual challenges lying ahead as the field is starting to explore one of the most challenging problems in neuroscience: the molecular and cellular logic underlying the emergence of the connectome characterizing specific circuits within the central nervous system of mammals.

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.

Comprehensive Estimates of Potential Synaptic Connections in Local Circuits of the Rodent Hippocampal Formation by Axonal-Dendritic Overlap

A quantitative description of the hippocampal formation synaptic architecture is essential for understanding the neural mechanisms of episodic memory. Yet the existing knowledge of connectivity statistics between different neuron types in the rodent hippocampus only captures a mere 5% of this circuitry. We present a systematic pipeline to produce first-approximation estimates for most of the missing information. Leveraging the www.Hippocampome.org knowledge base, we derive local connection parameters between distinct pairs of morphologically identified neuron types based on their axonal-dendritic overlap within every layer and subregion of the hippocampal formation. Specifically, we adapt modern image analysis technology to determine the parcel-specific neurite lengths of every neuron type from representative morphologic reconstructions obtained from either sex. We then compute the average number of synapses per neuron pair using relevant anatomic volumes from the mouse brain atlas and ultrastructurally established interaction distances. Hence, we estimate connection probabilities and number of contacts for >1900 neuron type pairs, increasing the available quantitative assessments more than 11-fold. Connectivity statistics thus remain unknown for only a minority of potential synapses in the hippocampal formation, including those involving long-range (23%) or perisomatic (6%) connections and neuron types without morphologic tracings (7%). The described approach also yields approximate measurements of synaptic distances from the soma along the dendritic and axonal paths, which may affect signal attenuation and delay. Overall, this dataset fills a substantial gap in quantitatively describing hippocampal circuits and provides useful model specifications for biologically realistic neural network simulations, until further direct experimental data become available.SIGNIFICANCE STATEMENT The hippocampal formation is a crucial functional substrate for episodic memory and spatial representation. Characterizing the complex neuron type circuit of this brain region is thus important to understand the cellular mechanisms of learning and navigation. Here we present the first numerical estimates of connection probabilities, numbers of contacts per connected pair, and synaptic distances from the soma along the axonal and dendritic paths, for more than 1900 distinct neuron type pairs throughout the dentate gyrus, CA3, CA2, CA1, subiculum, and entorhinal cortex. This comprehensive dataset, publicly released online at www.Hippocampome.org, constitutes an unprecedented quantification of the majority of the local synaptic circuit for a prominent mammalian neural system and provides an essential foundation for data-driven, anatomically realistic neural network models.

Translation-Focused Approaches to GPCR Drug Discovery for Cognitive Impairments Associated with Schizophrenia

There are no effective therapeutics for cognitive impairments associated with schizophrenia (CIAS), which includes deficits in executive functions (working memory and cognitive flexibility) and episodic memory. Compounds that have entered clinical trials are inadequate in terms of efficacy and/or tolerability, highlighting a clear translational bottleneck and a need for a cohesive preclinical drug development strategy. In this review we propose hippocampal-prefrontal-cortical (HPC-PFC) circuitry underlying CIAS-relevant cognitive processes across mammalian species as a target source to guide the translation-focused discovery and development of novel, procognitive agents. We highlight several G protein-coupled receptors (GPCRs) enriched within HPC-PFC circuitry as therapeutic targets of interest, including noncanonical approaches (biased agonism and allosteric modulation) to conventional clinical targets, such as dopamine and muscarinic acetylcholine receptors, along with prospective novel targets, including the orphan receptors GPR52 and GPR139. We also describe the translational limitations of popular preclinical cognition tests and suggest touchscreen-based assays that probe cognitive functions reliant on HPC-PFC circuitry and reflect tests used in the clinic, as tests of greater translational relevance. Combining pharmacological and behavioral testing strategies based in HPC-PFC circuit function creates a cohesive, translation-focused approach to preclinical drug development that may improve the translational bottleneck currently hindering the development of treatments for CIAS.

Cortical RORβ is required for layer 4 transcriptional identity and barrel integrity

Retinoic acid-related orphan receptor beta (RORβ) is a transcription factor (TF) and marker of layer 4 (L4) neurons, which are distinctive both in transcriptional identity and the ability to form aggregates such as barrels in rodent somatosensory cortex. However, the relationship between transcriptional identity and L4 cytoarchitecture is largely unknown. We find RORβ is required in the cortex for L4 aggregation into barrels and thalamocortical afferent (TCA) segregation. Interestingly, barrel organization also degrades with age in wildtype mice. Loss of RORβ delays excitatory input and disrupts gene expression and chromatin accessibility, with down-regulation of L4 and up-regulation of L5 genes, suggesting a disruption in cellular specification. Expression and binding site accessibility change for many other TFs, including closure of neurodevelopmental TF binding sites and increased expression and binding capacity of activity-regulated TFs. Lastly, a putative target of RORβ, Thsd7a, is down-regulated without RORβ, and Thsd7a knock-out alone disrupts TCA organization in adult barrels.

Unique homeobox codes delineate all the neuron classes of C. elegans

It is presently not known whether neuronal cell type diversity, defined by cell type-specific anatomical, biophysical, functional and molecular signatures, can be reduced to relatively simple molecular descriptors of neuronal identity ¹. Examination of the expression of all conserved homeodomain proteins encoded by the Caenorhabditis elegans genome ² reveals that the complete set of 118 C. elegans neuron classes can be described individually by unique combinations of homeodomain protein expression, thereby providing the simplest currently known descriptor of neuronal diversity. Computational as well as genetic loss of function analyses corroborate that homeodomain proteins not only provide unique descriptors of neuron type, but also play a critical role specifying neuronal identity. We speculate that the pervasive employment of homeobox genes in defining unique neuronal identities reflects the evolutionary history of neuronal cell-type specification.

Circuitry Underlying Experience-Dependent Plasticity in the Mouse Visual System

Since the discovery of ocular dominance plasticity, neuroscientists have understood that changes in visual experience during a discrete developmental time, the critical period, trigger robust changes in the visual cortex. State-of-the-art tools used to probe connectivity with cell-type-specific resolution have expanded the understanding of circuit changes underlying experience-dependent plasticity. Here, we review the visual circuitry of the mouse, describing projections from retina to thalamus, between thalamus and cortex, and within cortex. We discuss how visual circuit development leads to precise connectivity and identify synaptic loci, which can be altered by activity or experience. Plasticity extends to visual features beyond ocular dominance, involving subcortical and cortical regions, and connections between cortical inhibitory interneurons. Experience-dependent plasticity contributes to the alignment of networks spanning retina to thalamus to cortex. Disruption of this plasticity may underlie aberrant sensory processing in some neurodevelopmental disorders.

Intron and gene size expansion during nervous system evolution

Background

The evolutionary radiation of animals was accompanied by extensive expansion of gene and genome sizes, increased isoform diversity, and complexity of regulation.

Results

Here we show that the longest genes are enriched for expression in neuronal tissues of diverse vertebrates and of invertebrates. Additionally, we show that neuronal gene size expansion occurred predominantly through net gains in intron size, with a positional bias toward the 5′ end of each gene.

Conclusions

We find that intron and gene size expansion is a feature of many genes whose expression is enriched in nervous systems. We speculate that unique attributes of neurons may subject neuronal genes to evolutionary forces favoring net size expansion. This process could be associated with tissue-specific constraints on gene function and/or the evolution of increasingly complex gene regulation in nervous systems.

Molecular profiling of single neurons of known identity in two ganglia from the crab Cancer borealis

Single-cell transcriptional profiling has become a widespread tool in cell identification, particularly in the nervous system, based on the notion that genomic information determines cell identity. However, many cell-type classification studies are unconstrained by other cellular attributes (e.g., morphology, physiology). Here, we systematically test how accurately transcriptional profiling can assign cell identity to well-studied anatomically and functionally identified neurons in 2 small neuronal networks. While these neurons clearly possess distinct patterns of gene expression across cell types, their expression profiles are not sufficient to unambiguously confirm their identity. We suggest that true cell identity can only be determined by combining gene expression data with other cellular attributes such as innervation pattern, morphology, or physiology.

Understanding circuit organization depends on identification of cell types. Recent advances in transcriptional profiling methods have enabled classification of cell types by their gene expression. While exceptionally powerful and high throughput, the ground-truth validation of these methods is difficult: If cell type is unknown, how does one assess whether a given analysis accurately captures neuronal identity? To shed light on the capabilities and limitations of solely using transcriptional profiling for cell-type classification, we performed 2 forms of transcriptional profiling—RNA-seq and quantitative RT-PCR, in single, unambiguously identified neurons from 2 small crustacean neuronal networks: The stomatogastric and cardiac ganglia. We then combined our knowledge of cell type with unbiased clustering analyses and supervised machine learning to determine how accurately functionally defined neuron types can be classified by expression profile alone. The results demonstrate that expression profile is able to capture neuronal identity most accurately when combined with multimodal information that allows for post hoc grouping, so analysis can proceed from a supervised perspective. Solely unsupervised clustering can lead to misidentification and an inability to distinguish between 2 or more cell types. Therefore, this study supports the general utility of cell identification by transcriptional profiling, but adds a caution: It is difficult or impossible to know under what conditions transcriptional profiling alone is capable of assigning cell identity. Only by combining multiple modalities of information such as physiology, morphology, or innervation target can neuronal identity be unambiguously determined.

Single-cell transcriptomic evidence for dense intracortical neuropeptide networks

Seeking new insights into the homeostasis, modulation and plasticity of cortical synaptic networks, we have analyzed results from a single-cell RNA-seq study of 22,439 mouse neocortical neurons. Our analysis exposes transcriptomic evidence for dozens of molecularly distinct neuropeptidergic modulatory networks that directly interconnect all cortical neurons. This evidence begins with a discovery that transcripts of one or more neuropeptide precursor (NPP) and one or more neuropeptide-selective G-protein-coupled receptor (NP-GPCR) genes are highly abundant in all, or very nearly all, cortical neurons. Individual neurons express diverse subsets of NP signaling genes from palettes encoding 18 NPPs and 29 NP-GPCRs. These 47 genes comprise 37 cognate NPP/NP-GPCR pairs, implying the likelihood of local neuropeptide signaling. Here, we use neuron-type-specific patterns of NP gene expression to offer specific, testable predictions regarding 37 peptidergic neuromodulatory networks that may play prominent roles in cortical homeostasis and plasticity.

ATAC-seq on Sorted Adult Mouse Neurons

Transcription regulation is a key aspect of cellular identity established during development and maintained into adulthood. Molecular and biochemical assays that probe the genome are critical tools in exploring mechanisms of transcription regulation and cell type identity. The mammalian brain is composed of a huge diversity of cell types with distinct properties and functions. To understand these specific roles, it is necessary to selectively target cell populations for study. However, the need to selectively study restricted cell populations poses a challenge in neurobiology. It is often difficult to collect sufficient cellular input for many standard biochemical and molecular assays. Recently, important advances have been made to scale assays down, opening up new frontiers to explore molecular mechanisms in neurons. Concurrently, methodologies for preparing neurons for such assays has advanced taking into consideration specific methods to preserve the cell biology meant to be assayed. Here we describe a method for preparing live neurons from adult brain tissue for the Assay for Transposase Accessible Chromatin (ATAC).

A repeated molecular architecture across thalamic pathways

The thalamus is the central communication hub of the forebrain and provides the cerebral cortex with inputs from sensory organs, subcortical systems and the cortex itself. Multiple thalamic regions send convergent information to each cortical region, but the organizational logic of thalamic projections has remained elusive. Through comprehensive transcriptional analyses of retrogradely labeled thalamic neurons in adult mice, we identify three major profiles of thalamic pathways. These profiles exist along a continuum that is repeated across all major projection systems, such as those for vision, motor control and cognition. The largest component of gene expression variation in the mouse thalamus is topographically organized, with features conserved in humans. Transcriptional differences between these thalamic neuronal identities are tied to cellular features that are critical for function, such as axonal morphology and membrane properties. Molecular profiling therefore reveals covariation in the properties of thalamic pathways serving all major input modalities and output targets, thus establishing a molecular framework for understanding the thalamus.