Poff, A. | bioRxiv Science

bioRxiv2025

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↗

bioRxiv2024

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↗

bioRxiv2022

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↗

bioRxiv2020

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↗

bioRxiv2019

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↗