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Weinreb, A.

Publications and source records attributed to Weinreb, A..

13 recordsLinked to original sources

A gene expression atlas of a juvenile nervous system

Although the fundamental architecture of metazoan nervous systems is typically established in the embryo, substantial numbers of neurons are added during post-natal development while existing neurons expand in size, refine connectivity, and undergo additional differentiation. To reveal the underlying molecular determinants of postembryonic neurogenesis and maturation, we have produced gene expression profiles of all neuron types and their progenitors in the first larval stage (L1) of C. elegans. Comparisons of the L1 profile to the embryo and to the later L4 larval stage identified thousands of differentially expressed genes across individual neurons throughout the nervous system. Key neuropeptide signaling networks, for example, are remodeled during larval development. Gene regulatory network analysis revealed potential transcription factors driving the temporal changes in gene expression across the nervous system, including a broad role for the heterochronic transcription factor lin-14. We utilized available connectomic data of juvenile animals in combination with our neuron-specific atlas to identify potential molecular determinants of membrane contact and synaptic connectivity. These expression data are available through a user-friendly interface at CeNGEN.org for independent investigations of the maturation, connectivity and function of a developing nervous system.

neuroscience↗

Axon termination of the SAB motor neurons in C. elegans depends on pre- and postsynaptic activity

Axon termination is a critical step in neural circuit formation, but the contribution of activity from postsynaptic targets to this process remains unclear. Using Caenorhabditis elegans SAB neurons as a model system, we showed that inhibition of muscle activity during a critical period of postembryonic development led to axonal overgrowth and ectopic synapse formation. This effect is mediated by a local retrograde signal and requires neuronal voltage-gated calcium channels (VGCCs) acting cell-autonomously to constrain axon growth. Manipulating SAB neuron excitability demonstrated that increased intrinsic neuronal activity drives overgrowth, while reducing activity suppresses it, establishing a functional link between muscle-derived cues and presynaptic excitability. Transcriptomic analysis and genetic studies further implicate the neuropeptides FLP-18 and NLP-12 as essential modulators of this activity-dependent process. Our findings reveal a temporally and spatially restricted retrograde signaling mechanism in motor neurons, where target activity, neuronal calcium dynamics and neuropeptide signaling cooperate to ensure proper axon termination. These results highlight conserved principles of activity-dependent regulation at neuromuscular junctions and provide a framework for understanding how motor circuits integrate target feedback to sculpt precise connectivity.

neuroscience↗

Systematic identification of oscillatory gene expression in single cell types

Many biological cycles are driven by oscillatory gene expression coordinated across cell types. For example, larval development in Caenorhabditis elegans involves coordinated cyclic changes in cell division, behavior, and growth, the latter requiring production of a structured extracellular matrix called the cuticle. Here, we combine single-cell RNA sequencing and novel computational approaches to identify oscillatory gene expression in individual cell types. We find that many cell types exhibit looping structures in PCA and UMAP space that correspond to transcriptional oscillations at each larval stage. Oscillatory gene expression is found in all cuticle-producing cell types, including glia, but not detected in neurons or muscle. We develop rigorous statistical approaches for de novo identification of oscillatory genes and cell types, yielding >5,000 genes. While many oscillatory genes relate to cuticle production, each cell type expresses largely distinct genes, suggesting that cuticle production is a patchwork of cell-type-specific programs. Finally, we derive a potential set of regulatory transcription factors that can explain coordinated oscillatory gene expression and find that shared upstream factors likely control gene timing across cell types. Together, our results suggest that shared regulators control cell-type-specific oscillatory gene expression, including in previously overlooked cell types such as glia.

genomics↗

CellSpliceNet: Interpretable Multimodal Modeling ofAlternative Splicing Across Neurons in C. elegans

Alternative splicing profoundly diversifies the transcriptome and proteome, but decoding its regulatory mechanisms remains a challenge. We introduce CellSpliceNet, an interpretable transformer-based multimodal deep learning framework designed to predict splicing outcomes across the neurons of C. elegans. By integrating four complementary data modalities, namely long-range genomic sequence, local regions of interest (ROIs) in the RNA sequence, secondary structure, and gene expression, CellSpliceNet captures the complex interplay of factors that influence splicing decisions within the cellular context. CellSpliceNet employs modality-specific transformer embeddings, incorporating structural representations guided by mutual information and scattering graph embeddings. To this end, a novel and carefully designed multimodal multi-head attention mechanism preserves the integrity of each modality while facilitating selective cross-modal interactions, notably allowing gene expression data to inform sequence and structural predictions. Attention-based pooling within each modality highlights biologically critical elements, such as canonical intron-exon splice boundaries and accessible single-stranded RNA loop structures within the exon. Quantitative comparisons with current state-of-the-art methods demonstrated CellSpliceNet s superior predictive accuracy (Spearman{rho} = 0.88) and high accuracy across diverse neuron subtypes. Furthermore, CellSpliceNet elucidates a hierarchical, neuron-specific splicing code by preferentially weighting upstream enhancer motifs (e.g., GGAAGAAC) and identifying neuron-class-specific splicing-factor signatures, including smu-1, unc-75, and hrp-1. Thus, CellSpliceNet not only advances the frontiers of alternative splicing predictive capabilities but also provides mechanistic insights into the multimodal regulation of alternative splicing.

genetics↗

Integrating bulk and single cell RNA-seq refines transcriptomic profiles of individual C. elegans neurons

Neuron-specific morphology and function are fundamentally tied to differences in gene expression across the nervous system. We previously generated a single cell RNA-seq (scRNA-Seq) dataset for every anatomical neuron class in the C. elegans hermaphrodite. Here we present a complementary set of bulk RNA-seq samples for 52 of the 118 canonical neuron classes in C. elegans. We show that the bulk RNA-seq dataset captures both lowly expressed and noncoding RNAs that are not detected in the scRNA-Seq profile, but also includes false positives due to contamination by other cell types. We present an analytical strategy that integrates the two datasets, preserving both the specificity of scRNA-Seq data and the sensitivity of bulk RNA-Seq. We show that this integrated dataset enhances the sensitivity and accuracy of transcript detection and differential gene analysis. In addition, we show that the bulk RNA-Seq data set detects differentially expressed non-coding RNAs across neuron types, including multiple families of non-polyadenylated transcripts. We propose that our approach provides a new strategy for interrogating gene expression by bridging the gap between bulk and single cell methodologies for transcriptomic studies. We suggest that these datasets advance the goal of delineating the mechanisms that define morphology and connectivity in the nervous system.

genomics↗

A trans-synaptic IgLON adhesion molecular complex directly contacts and clusters a nicotinic receptor

The localization and clustering of neurotransmitter receptors at appropriate postsynaptic sites is a key step in the control of synaptic transmission. Here, we identify a novel paradigm for the synaptic localization of an ionotropic acetylcholine receptor (AChR) based on the direct interaction of its extracellular domain with a cell adhesion molecule of the IgLON family. Our results show that RIG-5 and ZIG-8, which encode the sole IgLONs in C. elegans, are tethered in the pre- and postsynaptic membranes, respectively, and interact in vivo through their first immunoglobulin-like (Ig) domains. In addition, ZIG-8 traps ACR-16 via a direct cis-interaction between the ZIG-8 Ig2 domain and the base of the large extracellular AChR domain. Such mechanism has never been reported, but all these molecules are conserved during evolution. Similar interactions may directly couple Ig superfamily adhesion molecules and members of the large family of Cys-loop ionotropic receptors, including AChRs, in the mammalian nervous system, and may be relevant in the context of IgLON-associated brain diseases.

neuroscience↗

Alternative splicing across the C. elegans nervous system

Alternative splicing is a key mechanism that shapes neuronal transcriptomes, helping to define neuronal identity and modulate function. Here, we present an atlas of alternative splicing across the nervous system of Caenorhabditis elegans. Our analysis identifies novel alternative splicing in key neuronal genes such as unc-40/DCC and sax-3/ROBO. Globally, we delineate patterns of differential alternative splicing in almost 2,000 genes, and estimate that a quarter of neuronal genes undergo differential splicing. We introduce a web interface for examination of splicing patterns across neuron types. We explore the relationship between neuron type and splicing patterns, and between splicing patterns and differential gene expression. We identify RNA features that correlate with differential alternative splicing, and describe the enrichment of microexons. Finally, we compute a splicing regulatory network that can be used to generate hypotheses on the regulation and targets of alternative splicing in neurons.

neuroscience↗

Polarized localization of kinesin-1 and RIC-7 drives axonal mitochondria anterograde transport

Mitochondria transport is crucial for mitochondria distribution in axons and is mediated by kinesin-1-based anterograde and dynein-based retrograde motor complexes. While Miro and Milton/TRAK were identified as key adaptors between mitochondria and kinesin-1, recent studies suggest the presence of additional mechanisms. In C. elegans, ric-7 is the only single gene described so far, other than kinesin-1, that is absolutely required for axonal mitochondria localization. Using CRISPR engineering in C. elegans, we find that Miro is important but is not essential for anterograde traffic, whereas it is required for retrograde traffic. Both the endogenous RIC-7 and kinesin-1 act at the leading end to transport mitochondria anterogradely. RIC-7 recruitment to mitochondria requires its N-terminal domain and partially relies on MIRO-1, whereas RIC-7 accumulation at the leading end depends on its disordered region, kinesin-1 and metaxin2. We conclude that polarized transport complexes containing kinesin-1 and RIC-7 form at the leading edge of mitochondria, and that these complexes are required for anterograde axonal transport. Summary statementAnterograde transport of axonal mitochondria is critical for maintenance of the mitochondria pool and neuronal health. Wu et al. show that the endogenous kinesin-1 and RIC-7 localize at the leading end of mitochondria to drive axonal anterograde transport in vivo.

cell biology↗

The neuropeptidergic connectome of C. elegans

SummaryEfforts are currently ongoing to map synaptic wiring diagrams or connectomes in order to understand the neural basis of brain function. However, chemical synapses represent only one type of functionally important neuronal connection; in particular, extrasynaptic, "wireless" signaling by neuropeptides is widespread and plays essential roles in all nervous systems. By integrating single-cell anatomical and gene expression datasets with a biochemical analysis of receptor-ligand interactions, we have generated a draft connectome of neuropeptide signaling in the C. elegans nervous system. This connectome is characterized by a high connection density, extended signaling cascades, autocrine foci, and a decentralized topology, with a large, highly interconnected core containing three constituent communities sharing similar patterns of input connectivity. Intriguingly, several of the most important nodes in this connectome are little-studied neurons that are specialized for peptidergic neuromodulation. We anticipate that the C. elegans neuropeptidergic connectome will serve as a prototype to understand basic organizational principles of neuroendocrine signaling networks.

neuroscience↗

Integrating bulk and single cell RNA-seq refines transcriptomic profiles of specific C. elegans neurons.

Neuron-specific morphology and function are fundamentally tied to differences in gene expression across the nervous system. We previously generated a single cell RNA-seq (scRNA-Seq) dataset for every anatomical neuron class in the C. elegans hermaphrodite. Here we present a complementary set of bulk RNA-seq samples for 52 of the 118 canonical neuron classes in C. elegans. We show that the bulk RNA-seq dataset captures both lowly expressed and noncoding RNAs that are not detected in the scRNA-Seq profile, but also includes false positives due to contamination by other cell types. We present an analytical strategy that integrates the two datasets, preserving both the specificity of scRNA-Seq data and the sensitivity of bulk RNA-Seq. We show that this integrated dataset enhances the sensitivity and accuracy of transcript detection and differential gene analysis. In addition, we show that the bulk RNA-Seq data set detects differentially expressed non-coding RNAs across neuron types, including multiple families of non-polyadenylated transcripts. We propose that our approach provides a new strategy for interrogating gene expression by bridging the gap between bulk and single cell methodologies for transcriptomic studies. We suggest that these datasets advance the goal of delineating the mechanisms that define morphology and connectivity in the nervous system.

genetics↗

An optimized ribodepletion approach for C. elegans RNA-sequencing libraries

A recent and powerful technique is to obtain transcriptomes from rare cell populations, such as single neurons in C. elegans, by enriching dissociated cells using fluorescent sorting. However, these cell samples often have low yields of RNA that present challenges in library preparation. This can lead to PCR duplicates, noisy gene expression for lowly expressed genes, and other issues that limit endpoint analysis. Further, some common resources, such as sequence specific kits for removing ribosomal RNA, are not optimized for non-mammalian samples. To optimize library construction for such challenging samples, we compared two approaches for building RNAseq libraries from less than 10 nanograms of C. elegans RNA: SMARTSeq V4 (Takara), a widely used kit for selecting poly-adenylated transcripts; and SoLo Ovation (Tecan Genomics), a newly developed ribodepletion-based approach. For ribodepletion, we used a custom kit of 200 probes designed to match C. elegans rRNA gene sequences. We found that SoLo Ovation, in combination with our custom C. elegans probe set for rRNA depletion, detects an expanded set of noncoding RNAs, shows reduced noise in lowly expressed genes, and more accurately counts expression of long genes. The approach described here should be broadly useful for similar efforts to analyze transcriptomics when RNA is limiting.

genomics↗

Molecular topography of an entire nervous system

Nervous systems are constructed from a deep repertoire of neuron types but the underlying gene expression programs that specify individual neuron identities are poorly understood. To address this deficit, we have produced an expression profile of all 302 neurons of the C. elegans nervous system that matches the single cell resolution of its anatomy and wiring diagram. Our results suggest that individual neuron classes can be solely identified by combinatorial expression of specific gene families. For example, each neuron class expresses unique codes of [~]23 neuropeptide-encoding genes and [~]36 neuropeptide receptors thus pointing to an expansive "wireless" signaling network. To demonstrate the utility of this uniquely comprehensive gene expression catalog, we used computational approaches to (1) identify cis-regulatory elements for neuron-specific gene expression across the nervous system and (2) reveal adhesion proteins with potential roles in synaptic specificity and process placement. These data are available at cengen.org and can be interrogated at the web application CengenApp. We expect that this neuron-specific directory of gene expression will spur investigations of underlying mechanisms that define anatomy, connectivity and function throughout the C. elegans nervous system.

neuroscience↗

Expression profiling of the mature C. elegans nervous system by single-cell RNA-Sequencing

A single neuron and its synapses define the fundamental structural motif of the brain but the underlying gene expression programs that specify individual neuron types are poorly understood. To address this question in a model organism, we have produced a gene expression profile of >90% of the individual neuron classes in the C. elegans nervous system, an ensemble of neurons for which both the anatomy and connectivity are uniquely defined at single cell resolution. We generated single cell transcriptomes for 52,412 neurons that resolve as clusters corresponding to 109 of the canonical 118 neuron classes in the mature hermaphrodite nervous system. Detailed analysis revealed molecular signatures that further subdivide identified classes into specific neuronal subtypes. Notably, neuropeptide-related genes are often differentially expressed between subtypes of the given neuron class which points to distinct functional characteristics. All of these data are publicly available at our website (http://www.cengen.org) and can be interrogated at the web application SCeNGEA (https://cengen.shinyapps.io/SCeNGEA). We expect that this gene expression catalog will spur the goal of delineating the underlying mechanisms that define the developmental lineage, detailed anatomy, synaptic connectivity and function of each type of C. elegans neuron.

neuroscience↗