Similar Datasets
Project description:The brain controls nearly all bodily functions via spinal projecting neurons (SPNs) that carry command signals from the brain to the spinal cord. However, a comprehensive molecular characterization of brain-wide SPNs is still lacking. Here we transcriptionally profiled a total of 65,002 SPNs, identified 76 region-specific SPN types, and mapped these types into a companion atlas of the whole mouse brain1. This taxonomy reveals a three-component organization of SPNs: (1) molecularly homogeneous excitatory SPNs from the cortex, red nucleus and cerebellum with somatotopic spinal terminations suitable for point-to-point communication; (2) heterogeneous populations in the reticular formation with broad spinal termination patterns, suitable for relaying commands related to the activities of the entire spinal cord; and (3) modulatory neurons expressing slow-acting neurotransmitters and/or neuropeptides in the hypothalamus, midbrain and reticular formation for 'gain setting' of brain-spinal signals. In addition, this atlas revealed a LIM homeobox transcription factor code that parcellates the reticulospinal neurons into five molecularly distinct and spatially segregated populations. Finally, we found transcriptional signatures of a subset of SPNs with large soma size and correlated these with fast-firing electrophysiological properties. Together, this study establishes a comprehensive taxonomy of brain-wide SPNs and provides insight into the functional organization of SPNs in mediating brain control of bodily functions.
| S-EPMC10719099 | biostudies-literature
Project description:The brain executes control of nearly all bodily functions via spinal projecting neurons (SPNs) that carry command signals from numerous supraspinal regions to the spinal cord. Despite their physiological and clinical relevance, a comprehensive molecular characterization of SPNs is still lacking. Here, we use retrograde labeling, whole-brain imaging, and high-throughput transcriptional profiling to generate a unified brain-wide anatomic and transcriptomic atlas of adult mouse SPNs at single-cell resolution. We transcriptionally profiled a total of 65,002 SPNs, identified 76 region-specific SPN types, and mapped these types into a companion atlas of the whole mouse brain generated by the Allen Institute for Brain Science within the BRAIN Initiative Cell Census Network (BICCN). This SPN taxonomy reveals a three-component organization of SPNs: (1) molecularly homogeneous excitatory SPNs from the cortex, red nucleus, and cerebellum with somatotopic spinal terminations suitable for point-to-point communication; (2) highly heterogeneous excitatory and inhibitory populations in the reticular formation with broad spinal termination patterns, thus suitable for relaying commands related to the activities of the entire spinal cord; and (3) modulatory neurons expressing slow-acting neurotransmitters and/or neuropeptides in the hypothalamus, midbrain, and reticular formation for gain control of brain-spinal signals. Within each of these components, this atlas revealed additional insights. From components (2) and (3), we discovered a LIM homeobox transcription factor code that parcellates the most transcriptionally complex population, reticulospinal neurons, into five molecularly distinct and spatially segregated populations. For neurons in component (1), we found transcriptional signatures of a subset of SPNs with large soma size and correlated these with fast-firing electrophysiological properties; thus, at least two different cable lines (namely, Pvalb/Kcng4/Spp1 positive and negative) with different electrophysiological properties might underlie the transmission of brain signals to the spinal cord. Together, by integrating the anatomy, molecular identity, and physiological properties, this study establishes a comprehensive taxonomy of brain-wide SPNs and provides insight into the functional organization of SPNs in mediating brain control of bodily functions.
2023-12-14 | GSE247594 | GEO
Project description:The brain executes control of nearly all bodily functions via spinal projecting neurons (SPNs) that carry command signals from numerous supraspinal regions to the spinal cord. Despite their physiological and clinical relevance, a comprehensive molecular characterization of SPNs is still lacking. Here, we use retrograde labeling, whole-brain imaging, and high-throughput transcriptional profiling to generate a unified brain-wide anatomic and transcriptomic atlas of adult mouse SPNs at single-cell resolution. We transcriptionally profiled a total of 65,002 SPNs, identified 76 region-specific SPN types, and mapped these types into a companion atlas of the whole mouse brain generated by the Allen Institute for Brain Science within the BRAIN Initiative Cell Census Network (BICCN). This SPN taxonomy reveals a three-component organization of SPNs: (1) molecularly homogeneous excitatory SPNs from the cortex, red nucleus, and cerebellum with somatotopic spinal terminations suitable for point-to-point communication; (2) highly heterogeneous excitatory and inhibitory populations in the reticular formation with broad spinal termination patterns, thus suitable for relaying commands related to the activities of the entire spinal cord; and (3) modulatory neurons expressing slow-acting neurotransmitters and/or neuropeptides in the hypothalamus, midbrain, and reticular formation for gain control of brain-spinal signals. Within each of these components, this atlas revealed additional insights. From components (2) and (3), we discovered a LIM homeobox transcription factor code that parcellates the most transcriptionally complex population, reticulospinal neurons, into five molecularly distinct and spatially segregated populations. For neurons in component (1), we found transcriptional signatures of a subset of SPNs with large soma size and correlated these with fast-firing electrophysiological properties; thus, at least two different cable lines (namely, Pvalb/Kcng4/Spp1 positive and negative) with different electrophysiological properties might underlie the transmission of brain signals to the spinal cord. Together, by integrating the anatomy, molecular identity, and physiological properties, this study establishes a comprehensive taxonomy of brain-wide SPNs and provides insight into the functional organization of SPNs in mediating brain control of bodily functions.
2023-12-14 | GSE247597 | GEO
Project description:A transcriptomic taxonomy of mouse brain-wide spinal projecting neurons
| PRJNA1039797 | ENA
Project description:A transcriptomic taxonomy of mouse brain-wide spinal projecting neurons (SmartSeq)
| PRJNA1039794 | ENA
Project description:A transcriptomic taxonomy of mouse brain-wide spinal projecting neurons (10X)
| PRJNA1039791 | ENA
Project description:von Economo neurons (VENs) are bipolar, spindle-shaped neurons restricted to layer 5 of human frontoinsula and anterior cingulate cortex that appear to be selectively vulnerable to neuropsychiatric and neurodegenerative diseases, although little is known about other VEN cellular phenotypes. Single nucleus RNA-sequencing of frontoinsula layer 5 identifies a transcriptomically-defined cell cluster that contained VENs, but also fork cells and a subset of pyramidal neurons. Cross-species alignment of this cell cluster with a well-annotated mouse classification shows strong homology to extratelencephalic (ET) excitatory neurons that project to subcerebral targets. This cluster also shows strong homology to a putative ET cluster in human temporal cortex, but with a strikingly specific regional signature. Together these results suggest that VENs are a regionally distinctive type of ET neuron. Additionally, we describe the first patch clamp recordings of VENs from neurosurgically-resected tissue that show distinctive intrinsic membrane properties relative to neighboring pyramidal neurons.
| S-EPMC7054400 | biostudies-literature
Project description: Not available
| S-EPMC7870733 | biostudies-literature
Project description:Many different functions are regulated by circadian rhythms, including those orchestrated by discrete clock neurons within animal brains. To comprehensively characterize and assign cell identity to the 75 pairs of Drosophila circadian neurons, we optimized a single-cell RNA sequencing method and assayed clock neuron gene expression at different times of day. The data identify at least 17 clock neuron categories with striking spatial regulation of gene expression. Transcription factor regulation is prominent and likely contributes to the robust circadian oscillation of many transcripts, including those that encode cell-surface proteins previously shown to be important for cell recognition and synapse formation during development. The many other clock-regulated genes also constitute an important resource for future mechanistic and functional studies between clock neurons and/or for temporal signaling to circuits elsewhere in the fly brain.
| S-EPMC7837698 | biostudies-literature
Project description:The complete understanding of the mammalian brain requires exact knowledge of the function of each neuron subpopulation composing its parts. To achieve this goal, an exhaustive, precise, reproducible, and robust neuronal taxonomy should be defined. In this paper, a new circular taxonomy based on transcriptomic features and novel electrophysiological features is proposed. The approach is validated by analysing more than 1850 electrophysiological signals of different mouse visual cortex neurons proceeding from the Allen Cell Types database. The study is conducted on two different levels: neurons and their cell-type aggregation into Cre lines. At the neuronal level, electrophysiological features have been extracted with a promising model that has already proved its worth in neuronal dynamics. At the Cre line level, electrophysiological and transcriptomic features are joined on cell types with available genetic information. A taxonomy with a circular order is revealed by a simple transformation of the first two principal components that allow the characterization of the different Cre lines. Moreover, the proposed methodology locates other Cre lines in the taxonomy that do not have transcriptomic features available. Finally, the taxonomy is validated by Machine Learning methods which are able to discriminate the different neuron types with the proposed electrophysiological features.
| S-EPMC8350032 | biostudies-literature