Neuron
NeuroView The CeNGEN Project: The Complete Gene Expression Map of an Entire Nervous System Marc Hammarlund,1,* Oliver Hobert,2,3 David M. Miller 3rd,4 and Nenad Sestan1 1Departments
of Genetics and Neuroscience, Yale University School of Medicine, New Haven, CT, USA of Biological Sciences, Columbia University, New York, New York, USA 3Howard Hughes Medical Institute 4Department of Cell and Developmental Biology and Program in Neuroscience, Vanderbilt University, Nashville, TN, USA *Correspondence:
[email protected] https://doi.org/10.1016/j.neuron.2018.07.042 2Department
Differential gene expression defines individual neuron types and determines how each contributes to circuit physiology and responds to injury and disease. The C. elegans Neuronal Gene Expression Map & Network (CeNGEN) will establish a comprehensive gene expression atlas of an entire nervous system at single-neuron resolution. Detailed knowledge of differential gene expression within every cell of a nervous system would elucidate fundamental mechanisms that generate neuronal diversity, including regulation of gene expression, alternative splicing, and miRNA function. Here we describe a project to discover and analyze the C. elegans Neuronal Gene Expression Map & Network (CeNGEN). By describing gene expression in the nervous system of a single species in detail, CeNGEN will help address broad questions in neuroscience, such as: how many kinds of neurons are there? What is the nature of neuronal diversity in terms of gene expression—that is, how are different neurons different? What mechanisms regulate genetic diversity in neurons? How and to what extent do genetic differences between neurons control other types of differences, such as differences in function, morphology, or resistance to stress and disease? The nematode Caenorhabditis elegans is particularly amenable to the goal of relating differential gene expression to neuronal structure, function, and development at an integrative, nervous system-wide level. The nervous system of the C. elegans hermaphrodite contains 302 neurons (Figure 1A), divided into 118 anatomic classes, each comprised of 1–13 cells (White et al., 1986). The nervous system of the male contains 391 neurons, falling into 143 classes. A total of 294 neurons (116 classes) are shared by both sexes, while the remainder are sexspecific. The anatomy and developmental history of both the male and hermaphro-
dite nervous system are exceptionally well defined; analysis of serial electron micrographs reconstructed the position, anatomy, and synaptic connectivity of every neuron in both the male and hermaphrodite (Jarrell et al., 2012; White et al., 1986). Similarly, live imaging of developing embryos and larvae established the cell lineage of every neuron (and of all cells) (Sulston and Horvitz, 1977; Sulston et al., 1983). Emerging whole-nervous-system imaging of neuronal activity with cellular resolution is also revealing insights into neuronal function and information processing (Prevedel et al., 2014). Thus, the C. elegans model is described in detail at the level of individual neurons, multiplied across an entire nervous system. Despite these landmark achievements, the over-arching goal of linking neuron anatomy and function to the underlying genetic blueprint has been stymied by the incomplete annotation of gene expression in the C. elegans nervous system. As the first steps toward such a comprehensive understanding, a substantial number of molecular markers for individual neurons have been defined by the C. elegans community over the past few decades. On average, 32 molecular markers are known for each neuron in the hermaphrodite (range 5–141) (Hobert et al., 2016), a number sufficient to support the original anatomical classification scheme of neuron types but clearly only scratching the surface of the molecular repertoire of each individual neuron.
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Aims The National Institute of Neurological Diseases and Stroke (NINDS) has decided to fill this gap by funding the CeNGEN project. CeNGEN will detail, with high accuracy, all protein-coding and regulatory RNA (miRNA)-encoding genes expressed in each of the 118 classes of neurons of the C. elegans hermaphrodite as well as selected neurons in the male. CeNGEN results will be useful for elucidating a number of fundamental questions in neuroscience: (1) CeNGEN findings are expected to point to fundamental mechanisms of gene expression in the nervous system. By relating the cellular specificity of protein coding transcripts as well as alternatively spliced isoforms to the expression of transcription factors (TFs), RNA binding proteins, and miRNAs, regulatory frameworks that drive diversity in gene expression profiles will be implicated. (2) CeNGEN data should reveal poorly understood aspects of nervous system structure and function. For example, CeNGEN will identify potential ‘‘circuits’’ for biogenic amine (octopamine, tyramine, dopamine, and serotonin) and neuropeptide function. By identifying the neurons with the machinery for synthesizing, packaging, and releasing these molecules, and also the neurons capable of responding to them (i.e., expressing specific
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NeuroView resource of existing data on the C. elegans nervous system. Decades of work have defined neuron class-specific features (e.g., lineage, anatomy, function, and connectivity). By linking neuron-specific maps of gene expression with these data, our findings will greatly aid the goal of elucidating the molecular mechanisms that drive specificity and diversity within the individual cells of an entire nervous system. (6) Perhaps most importantly, data produced by CeNGEN will provide a platform for future genetic analysis. Gene expression-based ‘‘reverse’’ genetic analysis of individual genes will be facilitated by the recent emergence of powerful Cas9/CRISPR-based genome engineering technology, to which C. elegans is amenable.
Figure 1. Labeling Individual Neuron Classes (A) The nervous system of the C. elegans hermaphrodite. From openworm.org. (B) Strategies to isolate individual neuron classes. In the intersectional strategies, transgenic lines expressing distinct GFP (green) and RFP (red) reporter transgenes are crossed together.
receptors), CeNGEN will provide a foundation for investigating how these signals propagate across the nervous system. Overall, CeNGEN can be expected to point to key biomolecules and pathways responsible for neuronal identity, morphology, synaptic specificity, and specialized function. (3) Nervous systems are not static. To produce clear examples of this feature, CeNGEN will profile all L4-stage neuron classes as well as specific postmitotic neurons at earlier juvenile stages. Because this approach will reveal developmentally regulated changes in gene expression that are linked to the lineage and identity of specific neuron classes, these datasets
should provide especially useful jumping-off points for focused investigations of gene function in neuron fate determination. (4) CeNGEN will profile distinct neuron classes in the two different C. elegans sexes. Specifically, we will profile a subset of shared neurons that display sex-specific differences in wiring. Additional profiling at earlier developmental stages should reveal dynamic changes in neuron-specific gene expression that are governed by sex and thus link gene expression with connections that are differentially modified between males and hermaphrodites (Oren-Suissa et al., 2016). (5) CeNGEN will integrate its gene expression profiles with a rich
Conceptually, the CeNGEN resource will be similar to the Allen Brain Atlas and other transcriptional resources for mammalian central nervous systems that have greatly enhanced mammalian neuroscience (Sousa et al., 2017). Because of the small size and invariant nature of the C. elegans nervous system, CeNGEN offers the additional benefit of providing gene expression data at cellular resolution. Experimental Approach We have opted to focus on neurons from L4-stage animals in the initial molecular mapping effort for two reasons: (1) neuronal development and connectivity are largely complete, and (2) neuronal anatomy and function are especially well characterized, therefore providing a rich source of datasets with which the gene expression profiles can be correlated. Animals will be carefully synchronized and grown under tightly controlled conditions. To ensure maximal coverage of neuronspecific transcriptomes, CeNGEN will employ bulk RNA-sequencing of individual neuron classes. For this purpose, we will use established FACS protocols (Spencer et al., 2014) to isolate each neuron class (> 1,000 sorted cells) from dissociated L4-stage animals. This strategy is enabled by the availability of hundreds of neuron-specific transgenic
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NeuroView reporter lines that have been generated by the C. elegans community (curated at www.wormbase.org) and that can be used to mark anatomically defined neuron types. Specifically, 39 of the 118 neuron classes can be uniquely labeled with available single fluorescent markers, and 77 of the 79 (all but two) remaining neuron classes can be selectively marked using approaches involving two differentcolored reporter lines (e.g., GFP and RFP). In the ‘‘AND’’ intersectional strategy, expression of the two reporters overlaps only in the neuron class of interest, while in the ‘‘XOR’’ strategy, the desired cell expresses one reporter but not the other (Figure 1B). To produce useful data as quickly as possible, we will prioritize individual neuron types in two ways. First, we will prioritize by the availability of existing markers. For this, we will include markers that we test as well as those that are suggested by members of the community. Second, we will prioritize by defined subgroups: for example, the datasets of all neurons that perform a particular function (e.g., locomotion or pharyngeal function) or that share a common lineage would be useful to have, even in advance of completion of the project. While generating these prioritized datasets, we will work concurrently on optimizing markers for the remaining neuron types. Bulk sequencing of isolated neuron classes is best suited to provide maximum coverage of transcripts in a population of cells, but this approach could also obscure two important aspects of neuronal identity. (1) Are neurons of a single, anatomically defined class actually comprised of cells with similar but not identical patterns of gene expression? Current molecular markers already hint at differences, albeit subtle, between individual neuron classes (Hobert et al., 2016). (2) What is the stability of the neuronal transcriptome from animal to animal? To address these questions, CeNGEN will also use single-cell-sequencing technology (scRNA-seq) to provide singleneuron resolution at selected developmental stages. The bulk sequencing data will provide an exceptionally robust scaffold for interpreting single-cell data (Cao et al., 2017).
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For both bulk sequencing and scRNAseq, we expect new experimental techniques to arise over the course of the project. We will adopt the best possible approach, balanced by the goal of consistency across the datasets. The CeNGEN Advisory Board will help guide these decisions so that the data are as robust and as useful as possible. Because of biological variability and the fact that our profiling effort is limited to a subset of larval stages and will therefore fail to capture many developmentally regulated changes in gene expression, our experiments will fall short of providing a comprehensive description of dynamic gene expression in the C. elegans nervous system. However, CeNGEN results should nonetheless serve as a framework for discovery that is currently missing from the field. Data Analysis A host of different types of analyses can be performed with the comprehensive gene expression datasets that CeNGEN will produce. For example, gene coexpression analysis should suggest regulatory networks and possibly identify relevant cis-regulatory motifs responding to TFs that coordinate those networks. Two types of additional analyses are especially notable because they exploit parameter spaces that currently only exist in C. elegans: the neuronal lineage and the synaptic wiring diagram. The single-cell resolution of these features is unrivaled in biology. Thus, our RNA-seq data will provide a powerful foundation for investigating links between cell lineage and the transcriptome profile. Similarly, computational strategies that seek correlations between the wiring diagram and neuronspecific gene expression could reveal genetic drivers of synaptic connectivity. In addition to identifying gene expression modules that may be correlated with the wiring diagram, we also expect to establish the cell type-specific expression of neuropeptides and receptors that define the ‘‘wireless’’ network that likely modulates function throughout the nervous system. Community Involvement To aid construction and validation of reporter lines, we encourage the community to contact us and to provide strains in
which their favorite neuron type is uniquely labeled for isolation by FACS. Submitted strains will be prioritized for analysis. Data Management and Distribution Validated datasets will be pushed to publicly available servers (WormBase, WormAtlas) as well as deposited in GEO (https://www.ncbi.nlm.nih.gov/geo/). We will work closely with WormBase to develop a portal for ready access to these data as they are produced. We will also work with existing data sources to integrate data. For example, we will provide WormAtlas with images of each neuron class as we identify promoters. We will provide links to gene expression data for each gene in WormBase and each neuron in WormAtlas. Conclusions CeNGEN will facilitate efforts to understand the control of neuron-specific gene expression. Expected significant outcomes include identification of conserved regulatory mechanisms that generate neuronal specificity and diversity; detailed understanding of alternative splicing and miRNA function across the nervous system; and relationship of differential gene expression to neuronal lineage, anatomy, function, and connectivity. CeNGEN will also serve as a resource for future studies and will provide a framework for addressing differential gene expression in more complex nervous systems that are currently not amenable to this comprehensive approach. ACKNOWLEDGMENTS This work was R01NS100547.
supported
by
NIH
grant
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