scholarly journals Classifying Drosophila Olfactory Projection Neuron Subtypes by Single-cell RNA Sequencing

2017 ◽  
Author(s):  
Hongjie Li ◽  
Felix Horns ◽  
Bing Wu ◽  
Qijing Xie ◽  
Jiefu Li ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Neuronal Cell ◽  
Projection Neuron ◽  
Projection Neurons ◽  
Open Questions ◽  
Olfactory Glomeruli ◽  
Single Cell Rna Sequencing ◽  
Genes Encoding ◽  
Circuit Assembly

AbstractHow a neuronal cell type is defined and how this relates to its transcriptome are still open questions. The Drosophila olfactory projection neurons (PNs) are among the best-characterized neuronal types: Different PN classes target dendrites to distinct olfactory glomeruli and PNs of the same class exhibit indistinguishable anatomical and physiological properties. Using single-cell RNA-sequencing, we comprehensively characterized the transcriptomes of 40 PN classes and unequivocally identified transcriptomes for 6 classes. We found a new lineage-specific transcription factor that instructs PN dendrite targeting. Transcriptomes of closely-related PN classes exhibit the largest difference during circuit assembly, but become indistinguishable in adults, suggesting that neuronal subtype diversity peaks during development. Genes encoding transcription factors and cell-surface molecules are the most differentially expressed, indicating their central roles in specifying neuronal identity. Finally, we show that PNs use highly redundant combinatorial molecular codes to distinguish subtypes, enabling robust specification of cell identity and circuit assembly.

scholarly journals Single cell RNA sequencing of the Strongylocentrotus purpuratus larva reveals the blueprint of major cell types and nervous system of a non-chordate deuterostome

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Periklis Paganos ◽  
Danila Voronov ◽  
Jacob M Musser ◽  
Detlev Arendt ◽  
Maria Ina Arnone
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Sea Urchin ◽  
Regulatory Networks ◽  
Sea Urchins ◽  
Neuronal Cell ◽  
Cell Types ◽  
Molecular Fingerprint ◽  
Larval Body ◽  
Single Cell Rna Sequencing

Identifying the molecular fingerprint of organismal cell types is key for understanding their function and evolution. Here, we use single cell RNA sequencing (scRNA-seq) to survey the cell types of the sea urchin early pluteus larva, representing an important developmental transition from non-feeding to feeding larva. We identify 21 distinct cell clusters, representing cells of the digestive, skeletal, immune, and nervous systems. Further subclustering of these reveal a highly detailed portrait of cell diversity across the larva, including the identification of neuronal cell types. We then validate important gene regulatory networks driving sea urchin development and reveal new domains of activity within the larval body. Focusing on neurons that co-express Pdx-1 and Brn1/2/4, we identify an unprecedented number of genes shared by this population of neurons in sea urchin and vertebrate endocrine pancreatic cells. Using differential expression results from Pdx-1 knockdown experiments, we show that Pdx1 is necessary for the acquisition of the neuronal identity of these cells. We hypothesize that a network similar to the one orchestrated by Pdx1 in the sea urchin neurons was active in an ancestral cell type and then inherited by neuronal and pancreatic developmental lineages in sea urchins and vertebrates.

scholarly journals Classifying Drosophila Olfactory Projection Neuron Subtypes by Single-Cell RNA Sequencing

Cell ◽  
2017 ◽  
Vol 171 (5) ◽  
pp. 1206-1220.e22 ◽  
Author(s):  
Hongjie Li ◽  
Felix Horns ◽  
Bing Wu ◽  
Qijing Xie ◽  
Jiefu Li ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Projection Neuron ◽  
Single Cell Rna Sequencing

scholarly journals Single cell RNA sequencing of theStrongylocentrotus purpuratuslarva reveals the blueprint of major cell types and nervous system of a non-chordate deuterostome

2021 ◽  
Author(s):  
Periklis Paganos ◽  
Danila Voronov ◽  
Jacob Musser ◽  
Detlev Arendt ◽  
Maria I. Arnone
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Sea Urchin ◽  
Regulatory Networks ◽  
Neuronal Cell ◽  
Cell Types ◽  
Molecular Fingerprint ◽  
Distinct Cell ◽  
Single Cell Rna Sequencing ◽  
Cell Diversity

AbstractIdentifying the molecular fingerprint of organismal cell types is key for understanding their function and evolution. Here, we use single cell RNA sequencing (scRNA-seq) to survey the cell types of the sea urchin early pluteus larva, representing an important developmental transition from non-feeding to feeding larva. We identified 21 distinct cell clusters, representing cells of the digestive, skeletal, immune, and nervous systems. Further subclustering of these revealed a highly detailed portrait of cell diversity across the larva, including the identification of 12 distinct neuronal cell types. Moreover, we corroborated co-expression of key regulatory genes previously shown to drive sea urchin gene regulatory networks, and revealed additional domains in which these regulatory networks are likely to function within the larva. Lastly, we recovered a neuronal cell type co-expressingPdx-1andBrn1/2/4, which had previously been shown to share similar gene expression with vertebrate pancreas. Our results extend this finding, revealing twenty transcription factors shared by this population of neurons in sea urchin and vertebrate pancreatic cells. Using differential expression results from Pdx-1 knockdown experiments, we generate a draft of the Pdx-1 regulatory network in these cells, and hypothesize this network was present in an ancestral deuterostome neuron before being co-opted into the pancreas developmental lineage in vertebrates.

scholarly journals Diversity of developing peripheral glia revealed by single cell RNA sequencing

2020 ◽  
Author(s):  
OE Tasdemir-Yilmaz ◽  
NR Druckenbrod ◽  
OO Olukoya ◽  
AR Yung ◽  
I Bastille ◽  
...  
Keyword(s):  
Nervous System ◽  
Single Cell ◽  
Rna Sequencing ◽  
Neuronal Cell ◽  
Neuronal Diversity ◽  
Sensory Stimuli ◽  
Neuronal Cell Bodies ◽  
Single Cell Rna Sequencing ◽  
Comprehensive Survey ◽  
Peripheral Glia

AbstractThe peripheral nervous system responds to a wide variety of sensory stimuli, a process that requires great neuronal diversity. These diverse peripheral sensory neurons are closely associated with glial cells that originate from the neural crest (NC). However, the molecular nature and origins of diversity among peripheral glia is not understood. Here we used single cell RNA sequencing to profile and compare developing and mature glia from somatosensory lumbar dorsal root ganglia (DRG) and auditory spiral ganglia (SG). We found that the glial precursors (GPs) differ in their transcriptional profile and prevalence in these two systems. Despite their unique features, somatosensory and auditory GPs undergo convergent differentiation to generate myelinating and non-myelinating Schwann cells that are molecularly uniform. By contrast, although satellite glia surround the neuronal cell bodies in both ganglia, we found that those in the SG express multiple myelination-associated genes, while DRG satellite cells express components that suppress myelination. Lastly, we identified a set of glial signature genes that are also expressed by placode-derived supporting cells, providing new insights into commonalities among glia across the nervous system. This comprehensive survey of gene expression in peripheral glia constitutes a valuable resource for understanding how glia acquire specialized functions and how their roles differ across sensory modalities.

scholarly journals Characterization of Alzheimer’s Disease-Associated Excitatory Neurons via Single-Cell RNA Sequencing Analysis

2021 ◽  
Vol 13 ◽  
Author(s):  
Fanghong Shao ◽  
Meiting Wang ◽  
Qi Guo ◽  
Bowen Zhang ◽  
Xiangting Wang
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Single Cell ◽  
Rna Sequencing ◽  
Neuronal Cell ◽  
Cell Populations ◽  
Sequencing Analysis ◽  
Single Cell Rna Sequencing ◽  
Excitatory Neurons

The detailed characteristics of neuronal cell populations in Alzheimer’s disease (AD) using single-cell RNA sequencing have not been fully elucidated. To explore the characterization of neuronal cell populations in AD, this study utilized the publicly available single-nucleus RNA-sequencing datasets in the transgenic model of 5X familial Alzheimer’s disease (5XFAD) and wild-type mice to reveal an AD-associated excitatory neuron population (C3:Ex.Neuron). The relative abundance of C3:Ex.Neuron increased at 1.5 months and peaked at 4.7 months in AD mice. Functional pathways analyses showed that the pathways positively related to neurodegenerative disease progression were downregulated in the C3:Ex.Neuron at 1.5 months in AD mice. Based on the differentially expressed genes among the C3:Ex.Neuron, four subtypes (C3.1–4) were identified, which exhibited distinct abundance regulatory patterns during the development of AD. Among these subtypes, the C3.1 neurons [marked by netrin G1 (Ntng1)] exhibited a similar regulatory pattern as the C3:Ex.Neuron in abundance during the development of AD. In addition, our gene set variation analysis (GSEA) showed that the C3.1 neurons, instead of other subtypes of the C3:Ex.Neuron, possessed downregulated AD pathways at an early stage (1.5 months) of AD mice. Collectively, our results identified a previously unidentified subset of excitatory neurons and provide a potential application of these neurons to modulate the disease susceptibility.

scholarly journals Model-based Trajectory Inference for Single-Cell RNA Sequencing Using Deep Learning with a Mixture Prior

2020 ◽  
Author(s):  
Jin-Hong Du ◽  
Ming Gao ◽  
Jingshu Wang
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Developmental Trajectories ◽  
Probabilistic Method ◽  
Synthetic Data ◽  
Developmental Trajectory ◽  
Projection Neurons ◽  
Single Cell Rna Sequencing ◽  
Mixture Prior ◽  
Inference Methods

AbstractTrajectory inference methods analyze thousands of cells from single-cell sequencing technologies and computationally infer their developmental trajectories. Though many tools have been developed for trajectory inference, most of them lack a coherent statistical model and reliable uncertainty quantification. In this paper, we present VITAE, a probabilistic method combining a latent hierarchical mixture model with variational autoencoders to infer trajectories from posterior approximations. VITAE is computationally scalable and can adjust for confounding covariates to integrate multiple datasets. We show that VITAE outperforms other state-of-the-art trajectory inference methods on both real and synthetic data under various trajectory topologies. We also apply VITAE to jointly analyze two single-cell RNA sequencing datasets on mouse neocortex. Our results suggest that VITAE can successfully uncover a shared developmental trajectory of the projection neurons and reliably order cells from both datasets along the inferred trajectory.

scholarly journals Single Cell RNA-Sequencing Uncovers Paracrine Functions of the Epicardial-Derived Cells in Arrhythmogenic Cardiomyopathy

Circulation ◽  
2021 ◽  
Author(s):  
Ping Yuan ◽  
Sirisha M. Cheedipudi ◽  
Leila Rouhi ◽  
Siyang Fan ◽  
Lukas Simon ◽  
...  
Keyword(s):  
Epithelial Cells ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cardiac Myocytes ◽  
Cardiac Dysfunction ◽  
Arrhythmogenic Cardiomyopathy ◽  
Paracrine Factors ◽  
Epicardial Cells ◽  
Single Cell Rna Sequencing ◽  
Genes Encoding

Background: Arrhythmogenic cardiomyopathy (ACM) manifests with sudden death, arrhythmias, heart failure, apoptosis, and myocardial fibro-adipogenesis. The phenotype typically starts at the epicardium and advances transmurally. Mutations in genes encoding desmosome proteins, including DSP (desmoplakin), are major causes of ACM. Methods: To delineate contributions of the epicardium to the pathogenesis of ACM, the Dsp allele was conditionally deleted in the epicardial cells in mice upon expression of tamoxifen-inducible Cre from the Wt1 locus. Wild type (WT) and Wt1-Cre ERT2 :Dsp W/F were crossed to Rosa26 mT/mG (R26 mT/mG ) dual reporter mice to tag the epicardial-derived cells (EDCs) with the EGFP reporter protein. Tagged EDCs from adult Wt1-Cre ERT2 :R26 mT/mG and Wt1-Cre ERT2 : R26 mT/mG : Dsp W/F mouse hearts were isolated by FACS and sequenced by single cell RNA-sequencing (scRNA-Seq). Results: WT1 expression was progressively restricted postnatally and was exclusive to the epicardium by postnatal day 21. Expression of Dsp was reduced in the epicardial cells but not in cardiac myocytes in the Wt1-Cre ERT2 :Dsp W/F mice. The Wt1-Cre ERT2 :Dsp W/F mice exhibited premature death, cardiac dysfunction, arrhythmias, myocardial fibro-adipogenesis, and apoptosis. ScRNA-Seq of ~ 18,000 EGFP-tagged EDCs identified genotype-independent clusters of endothelial cells (ECs), fibroblasts, epithelial cells, and a very small cluster of cardiac myocytes, which were confirmed upon co-immunofluorescence staining of the myocardial sections. Differentially expressed genes (DEGs) between the paired clusters in the two genotypes predicted activation of the inflammatory and mitotic pathways, including the TGFβ1 and fibroblast growth factors (FGFs), in the epicardial-derived fibroblast and epithelial clusters but their suppression in the EC cluster. The findings were corroborated by analysis of gene expression in the pooled RNA-Seq data, which identified predominant dysregulation of genes involved in epithelial-mesenchymal transition (EMT), and dysregulation of 146 genes encoding the secreted proteins (secretome), including genes in the TGFβ1 pathway. Activation of the TGFβ1 and its co-localization with fibrosis in the Wt1-Cre ERT2 :R26 mT/mG : Dsp W/F mouse heart was validated by complementary methods. Conclusions: Epicardial-derived cardiac fibroblasts and epithelial cells express paracrine factors, including TGFβ1 and FGFs, which mediate EMT, and contribute to the pathogenesis of myocardial fibrosis, apoptosis, arrhythmias, and cardiac dysfunction in a mouse model of ACM. The findings uncover contributions of the EDCs to the pathogenesis of ACM.

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