scholarly journals Modular transcriptional programs separately define axon and dendrite connectivity

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Yerbol Z Kurmangaliyev ◽  
Juyoun Yoo ◽  
Samuel A LoCascio ◽  
S Lawrence Zipursky
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
Transcriptional Control ◽  
Surface Proteins ◽  
Synaptic Connectivity ◽  
Loss Of Function ◽  
Neuronal Connectivity ◽  
Cell Surface Proteins ◽  
Single Cell Rna Sequencing ◽  
Single Cell Profiling

Patterns of synaptic connectivity are remarkably precise and complex. Single-cell RNA sequencing has revealed a vast transcriptional diversity of neurons. Nevertheless, a clear logic underlying the transcriptional control of neuronal connectivity has yet to emerge. Here, we focused on Drosophila T4/T5 neurons, a class of closely related neuronal subtypes with different wiring patterns. Eight subtypes of T4/T5 neurons are defined by combinations of two patterns of dendritic inputs and four patterns of axonal outputs. Single-cell profiling during development revealed distinct transcriptional programs defining each dendrite and axon wiring pattern. These programs were defined by the expression of a few transcription factors and different combinations of cell surface proteins. Gain and loss of function studies provide evidence for independent control of different wiring features. We propose that modular transcriptional programs for distinct wiring features are assembled in different combinations to generate diverse patterns of neuronal connectivity.

scholarly journals Modular transcriptional programs separately define axon and dendrite connectivity

2019 ◽  
Author(s):  
Yerbol Z. Kurmangaliyev ◽  
Juyoun Yoo ◽  
Samuel A. LoCascio ◽  
S. Lawrence Zipursky
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
Transcriptional Control ◽  
Surface Proteins ◽  
Synaptic Connectivity ◽  
Loss Of Function ◽  
Neuronal Connectivity ◽  
Cell Surface Proteins ◽  
Single Cell Rna Sequencing ◽  
Single Cell Profiling

AbstractPatterns of synaptic connectivity are remarkably precise and complex. Single-cell RNA sequencing has revealed a vast transcriptional diversity of neurons. Nevertheless, a clear logic underlying the transcriptional control of neuronal connectivity has yet to emerge. Here, we focused on Drosophila T4/T5 neurons, a class of closely related neuronal subtypes with different wiring patterns. Eight subtypes of T4/T5 neurons are defined by combinations of two patterns of dendritic inputs and four patterns of axonal outputs. Single-cell profiling during development revealed distinct transcriptional programs defining each dendrite and axon wiring pattern. These programs were defined by the expression of a few transcription factors and different combinations of cell surface proteins. Gain and loss of function studies provide evidence for independent control of different wiring features. We propose that modular transcriptional programs for distinct wiring features are assembled in different combinations to generate diverse patterns of neuronal connectivity.

scholarly journals Molecular basis of synaptic specificity by immunoglobulin superfamily receptors in Drosophila

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Shouqiang Cheng ◽  
James Ashley ◽  
Justyna D Kurleto ◽  
Meike Lobb-Rabe ◽  
Yeonhee Jenny Park ◽  
...  
Keyword(s):  
Axon Guidance ◽  
Molecular Basis ◽  
Surface Proteins ◽  
Synaptic Connectivity ◽  
Immunoglobulin Superfamily ◽  
Neuronal Connectivity ◽  
Cell Surface Proteins ◽  
Synaptic Specificity ◽  
Immunoglobulin Superfamily Proteins ◽  
Synapse Targeting

In stereotyped neuronal networks, synaptic connectivity is dictated by cell surface proteins, which assign unique identities to neurons, and physically mediate axon guidance and synapse targeting. We recently identified two groups of immunoglobulin superfamily proteins in Drosophila, Dprs and DIPs, as strong candidates for synapse targeting functions. Here, we uncover the molecular basis of specificity in Dpr–DIP mediated cellular adhesions and neuronal connectivity. First, we present five crystal structures of Dpr–DIP and DIP–DIP complexes, highlighting the evolutionary and structural origins of diversification in Dpr and DIP proteins and their interactions. We further show that structures can be used to rationally engineer receptors with novel specificities or modified affinities, which can be used to study specific circuits that require Dpr–DIP interactions to help establish connectivity. We investigate one pair, engineered Dpr10 and DIP-α, for function in the neuromuscular circuit in flies, and reveal roles for homophilic and heterophilic binding in wiring.

scholarly journals Surface protein imputation from single cell transcriptomes by deep neural networks

2019 ◽  
Author(s):  
Zilu Zhou ◽  
Chengzhong Ye ◽  
Jingshu Wang ◽  
Nancy R. Zhang
Keyword(s):  
Neural Networks ◽  
Cell Surface ◽  
Single Cell ◽  
Deep Neural Networks ◽  
Surface Protein ◽  
Surface Proteins ◽  
Cell Populations ◽  
Cell Surface Proteins ◽  
Learning Framework ◽  
Single Cell Rna Sequencing

While single cell RNA sequencing (scRNA-seq) is invaluable for studying cell populations, cell-surface proteins are often integral markers of cellular function and serve as primary targets for therapeutic intervention. Here we propose a transfer learning framework, single cell Transcriptome to Protein prediction with deep neural network (cTP-net), to impute surface protein abundances from scRNA-seq data by learning from existing single-cell multi-omic resources.

scholarly journals Comprehensive network modeling from single cell RNA sequencing of human and mouse reveals well conserved transcription regulation of hematopoiesis

BMC Genomics ◽  
2020 ◽  
Vol 21 (S11) ◽  
Author(s):  
Shouguo Gao ◽  
Zhijie Wu ◽  
Xingmin Feng ◽  
Sachiko Kajigaya ◽  
Xujing Wang ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Transcription Factors ◽  
Single Cell ◽  
Rna Sequencing ◽  
Transcription Regulation ◽  
Regulatory Networks ◽  
Stem Cell Differentiation ◽  
Hematopoietic Stem ◽  
Single Cell Rna Sequencing ◽  
Human And Mouse

Abstract Background Presently, there is no comprehensive analysis of the transcription regulation network in hematopoiesis. Comparison of networks arising from gene co-expression across species can facilitate an understanding of the conservation of functional gene modules in hematopoiesis. Results We used single-cell RNA sequencing to profile bone marrow from human and mouse, and inferred transcription regulatory networks in each species in order to characterize transcriptional programs governing hematopoietic stem cell differentiation. We designed an algorithm for network reconstruction to conduct comparative transcriptomic analysis of hematopoietic gene co-expression and transcription regulation in human and mouse bone marrow cells. Co-expression network connectivity of hematopoiesis-related genes was found to be well conserved between mouse and human. The co-expression network showed “small-world” and “scale-free” architecture. The gene regulatory network formed a hierarchical structure, and hematopoiesis transcription factors localized to the hierarchy’s middle level. Conclusions Transcriptional regulatory networks are well conserved between human and mouse. The hierarchical organization of transcription factors may provide insights into hematopoietic cell lineage commitment, and to signal processing, cell survival and disease initiation.

scholarly journals Control of Synaptic Connectivity by a Network of Drosophila IgSF Cell Surface Proteins

Cell ◽  
2015 ◽  
Vol 163 (7) ◽  
pp. 1770-1782 ◽  
Author(s):  
Robert A. Carrillo ◽  
Engin Özkan ◽  
Kaushiki P. Menon ◽  
Sonal Nagarkar-Jaiswal ◽  
Pei-Tseng Lee ◽  
...  
Keyword(s):  
Cell Surface ◽  
Surface Proteins ◽  
Synaptic Connectivity ◽  
Cell Surface Proteins

scholarly journals Molecular identification of sixty-three amacrine cell types completes a mouse retinal cell atlas

2020 ◽  
Author(s):  
Wenjun Yan ◽  
Mallory A. Laboulaye ◽  
Nicholas M. Tran ◽  
Irene E. Whitney ◽  
Inbal Benhar ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
High Throughput ◽  
Amacrine Cells ◽  
Cell Types ◽  
Retinal Cell ◽  
Mouse Retina ◽  
Single Cell Rna Sequencing ◽  
Neuronal Types ◽  
The Brain

ABSTRACTAmacrine cells (ACs) are a diverse class of interneurons that modulate input from photoreceptors to retinal ganglion cells (RGCs), rendering each RGC type selectively sensitive to particular visual features, which are then relayed to the brain. While many AC types have been identified morphologically and physiologically, they have not been comprehensively classified or molecularly characterized. We used high-throughput single-cell RNA sequencing (scRNA-seq) to profile >32,000 ACs from mouse retina, and applied computational methods to identify 63 AC types. We identified molecular markers for each type, and used them to characterize the morphology of multiple types. We show that they include nearly all previously known AC types as well as many that had not been described. Consistent with previous studies, most of the AC types express markers for the canonical inhibitory neurotransmitters GABA or glycine, but several express neither or both. In addition, many express one or more neuropeptides, and two express glutamatergic markers. We also explored transcriptomic relationships among AC types and identified transcription factors expressed by individual or multiple closely related types. Noteworthy among these were Meis2 and Tcf4, expressed by most GABAergic and most glycinergic types, respectively. Together, these results provide a foundation for developmental and functional studies of ACs, as well as means for genetically accessing them. Along with previous molecular, physiological and morphological analyses, they establish the existence of at least 130 neuronal types and nearly 140 cell types in mouse retina.SIGNIFICANCE STATEMENTThe mouse retina is a leading model for analyzing the development, structure, function and pathology of neural circuits. A complete molecular atlas of retinal cell types provides an important foundation for these studies. We used high-throughput single-cell RNA sequencing (scRNA-seq) to characterize the most heterogeneous class of retinal interneurons, amacrine cells, identifying 63 distinct types. The atlas includes types identified previously as well as many novel types. We provide evidence for use of multiple neurotransmitters and neuropeptides and identify transcription factors expressed by groups of closely related types. Combining these results with those obtained previously, we proposed that the mouse retina contains 130 neuronal types, and is therefore comparable in complexity to other regions of the brain.

scholarly journals Transcription Factor Control of Dendrite Targeting via Combinatorial Cell-Surface Codes

2021 ◽  
Author(s):  
Liqun Luo ◽  
Qijing Xie ◽  
Jiefu Li ◽  
Hongjie Li ◽  
Namrata Udeshi ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
Cell Surface ◽  
Surface Protein ◽  
Surface Proteins ◽  
Projection Neurons ◽  
Cell Surface Protein ◽  
Cell Surface Proteins ◽  
Cellular Environment ◽  
Combinatorial Expression

Abstract Transcription factors are central commanders specifying cell fate, morphology, and physiology while cell-surface proteins execute these commands through interaction with cellular environment. In developing neurons, it is presumed that transcription factors control wiring specificity through regulation of cell-surface protein expression. However, the number and identity of cell-surface protein(s) a transcription factor regulates remain largely unclear1,2. Also unknown is whether a transcription factor regulates the same or different cell-surface proteins in different neuron types to specify their connectivity. Here we use a lineage-defining transcription factor, Acj6 (ref. 3), to investigate how it controls precise dendrite targeting of Drosophila olfactory projection neurons (PNs). Quantitative cell-surface proteomic profiling of wild-type and acj6 mutant PNs in intact developing brains and a proteome-informed genetic screen identified PN surface proteins that execute Acj6-regulated wiring decisions. These include canonical cell adhesion proteins and proteins previously not associated with wiring, such as the mechanosensitive ion channel Piezo—whose channel activity is dispensable for its wiring function. Comprehensive genetic analyses revealed that Acj6 employs unique sets of cell-surface proteins in different PN types for dendrite targeting. Combinatorial expression of Acj6 wiring executors rescued acj6 mutant phenotypes with higher efficacy and breadth than expression of individual executors. Thus, a key transcription factor controls wiring specificity of different neuron types by specifying distinct combinatorial expression of cell-surface executors.

scholarly journals VirtualCytometry: a webserver for evaluating immune cell differentiation using single-cell RNA sequencing data

2019 ◽  
Vol 36 (2) ◽  
pp. 546-551 ◽  
Author(s):  
Kyungsoo Kim ◽  
Sunmo Yang ◽  
Sang-Jun Ha ◽  
Insuk Lee
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Cell Differentiation ◽  
T Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Immune Cell ◽  
Signaling Molecules ◽  
Single Cell Rna Sequencing ◽  
Functional States

Abstract Motivation The immune system has diverse types of cells that are differentiated or activated via various signaling pathways and transcriptional regulation upon challenging conditions. Immunophenotyping by flow and mass cytometry are the major approaches for identifying key signaling molecules and transcription factors directing the transition between the functional states of immune cells. However, few proteins can be evaluated by flow cytometry in a single experiment, preventing researchers from obtaining a comprehensive picture of the molecular programs involved in immune cell differentiation. Recent advances in single-cell RNA sequencing (scRNA-seq) have enabled unbiased genome-wide quantification of gene expression in individual cells on a large scale, providing a new and versatile analytical pipeline for studying immune cell differentiation. Results We present VirtualCytometry, a web-based computational pipeline for evaluating immune cell differentiation by exploiting cell-to-cell variation in gene expression with scRNA-seq data. Differentiating cells often show a continuous spectrum of cellular states rather than distinct populations. VirtualCytometry enables the identification of cellular subsets for different functional states of differentiation based on the expression of marker genes. Case studies have highlighted the usefulness of this subset analysis strategy for discovering signaling molecules and transcription factors for human T-cell exhaustion, a state of T-cell dysfunction, in tumor and mouse dendritic cells activated by pathogens. With more than 226 scRNA-seq datasets precompiled from public repositories covering diverse mouse and human immune cell types in normal and disease tissues, VirtualCytometry is a useful resource for the molecular dissection of immune cell differentiation. Availability and implementation www.grnpedia.org/cytometry

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